WorldWideScience

Sample records for bind-n-seq high-throughput analysis

  1. Multiplexed ChIP-Seq Using Direct Nucleosome Barcoding: A Tool for High-Throughput Chromatin Analysis.

    Science.gov (United States)

    Chabbert, Christophe D; Adjalley, Sophie H; Steinmetz, Lars M; Pelechano, Vicent

    2018-01-01

    Chromatin immunoprecipitation followed by sequencing (ChIP-Seq) or microarray hybridization (ChIP-on-chip) are standard methods for the study of transcription factor binding sites and histone chemical modifications. However, these approaches only allow profiling of a single factor or protein modification at a time.In this chapter, we present Bar-ChIP, a higher throughput version of ChIP-Seq that relies on the direct ligation of molecular barcodes to chromatin fragments. Bar-ChIP enables the concurrent profiling of multiple DNA-protein interactions and is therefore amenable to experimental scale-up, without the need for any robotic instrumentation.

  2. Discovering transcription factor binding sites in highly repetitive regions of genomes with multi-read analysis of ChIP-Seq data.

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    Chung, Dongjun; Kuan, Pei Fen; Li, Bo; Sanalkumar, Rajendran; Liang, Kun; Bresnick, Emery H; Dewey, Colin; Keleş, Sündüz

    2011-07-01

    Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) is rapidly replacing chromatin immunoprecipitation combined with genome-wide tiling array analysis (ChIP-chip) as the preferred approach for mapping transcription-factor binding sites and chromatin modifications. The state of the art for analyzing ChIP-seq data relies on using only reads that map uniquely to a relevant reference genome (uni-reads). This can lead to the omission of up to 30% of alignable reads. We describe a general approach for utilizing reads that map to multiple locations on the reference genome (multi-reads). Our approach is based on allocating multi-reads as fractional counts using a weighted alignment scheme. Using human STAT1 and mouse GATA1 ChIP-seq datasets, we illustrate that incorporation of multi-reads significantly increases sequencing depths, leads to detection of novel peaks that are not otherwise identifiable with uni-reads, and improves detection of peaks in mappable regions. We investigate various genome-wide characteristics of peaks detected only by utilization of multi-reads via computational experiments. Overall, peaks from multi-read analysis have similar characteristics to peaks that are identified by uni-reads except that the majority of them reside in segmental duplications. We further validate a number of GATA1 multi-read only peaks by independent quantitative real-time ChIP analysis and identify novel target genes of GATA1. These computational and experimental results establish that multi-reads can be of critical importance for studying transcription factor binding in highly repetitive regions of genomes with ChIP-seq experiments.

  3. Discovering transcription factor binding sites in highly repetitive regions of genomes with multi-read analysis of ChIP-Seq data.

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    Dongjun Chung

    2011-07-01

    Full Text Available Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq is rapidly replacing chromatin immunoprecipitation combined with genome-wide tiling array analysis (ChIP-chip as the preferred approach for mapping transcription-factor binding sites and chromatin modifications. The state of the art for analyzing ChIP-seq data relies on using only reads that map uniquely to a relevant reference genome (uni-reads. This can lead to the omission of up to 30% of alignable reads. We describe a general approach for utilizing reads that map to multiple locations on the reference genome (multi-reads. Our approach is based on allocating multi-reads as fractional counts using a weighted alignment scheme. Using human STAT1 and mouse GATA1 ChIP-seq datasets, we illustrate that incorporation of multi-reads significantly increases sequencing depths, leads to detection of novel peaks that are not otherwise identifiable with uni-reads, and improves detection of peaks in mappable regions. We investigate various genome-wide characteristics of peaks detected only by utilization of multi-reads via computational experiments. Overall, peaks from multi-read analysis have similar characteristics to peaks that are identified by uni-reads except that the majority of them reside in segmental duplications. We further validate a number of GATA1 multi-read only peaks by independent quantitative real-time ChIP analysis and identify novel target genes of GATA1. These computational and experimental results establish that multi-reads can be of critical importance for studying transcription factor binding in highly repetitive regions of genomes with ChIP-seq experiments.

  4. Methylation Sensitive Amplification Polymorphism Sequencing (MSAP-Seq)-A Method for High-Throughput Analysis of Differentially Methylated CCGG Sites in Plants with Large Genomes.

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    Chwialkowska, Karolina; Korotko, Urszula; Kosinska, Joanna; Szarejko, Iwona; Kwasniewski, Miroslaw

    2017-01-01

    Epigenetic mechanisms, including histone modifications and DNA methylation, mutually regulate chromatin structure, maintain genome integrity, and affect gene expression and transposon mobility. Variations in DNA methylation within plant populations, as well as methylation in response to internal and external factors, are of increasing interest, especially in the crop research field. Methylation Sensitive Amplification Polymorphism (MSAP) is one of the most commonly used methods for assessing DNA methylation changes in plants. This method involves gel-based visualization of PCR fragments from selectively amplified DNA that are cleaved using methylation-sensitive restriction enzymes. In this study, we developed and validated a new method based on the conventional MSAP approach called Methylation Sensitive Amplification Polymorphism Sequencing (MSAP-Seq). We improved the MSAP-based approach by replacing the conventional separation of amplicons on polyacrylamide gels with direct, high-throughput sequencing using Next Generation Sequencing (NGS) and automated data analysis. MSAP-Seq allows for global sequence-based identification of changes in DNA methylation. This technique was validated in Hordeum vulgare . However, MSAP-Seq can be straightforwardly implemented in different plant species, including crops with large, complex and highly repetitive genomes. The incorporation of high-throughput sequencing into MSAP-Seq enables parallel and direct analysis of DNA methylation in hundreds of thousands of sites across the genome. MSAP-Seq provides direct genomic localization of changes and enables quantitative evaluation. We have shown that the MSAP-Seq method specifically targets gene-containing regions and that a single analysis can cover three-quarters of all genes in large genomes. Moreover, MSAP-Seq's simplicity, cost effectiveness, and high-multiplexing capability make this method highly affordable. Therefore, MSAP-Seq can be used for DNA methylation analysis in crop

  5. Comparing the normalization methods for the differential analysis of Illumina high-throughput RNA-Seq data.

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    Li, Peipei; Piao, Yongjun; Shon, Ho Sun; Ryu, Keun Ho

    2015-10-28

    Recently, rapid improvements in technology and decrease in sequencing costs have made RNA-Seq a widely used technique to quantify gene expression levels. Various normalization approaches have been proposed, owing to the importance of normalization in the analysis of RNA-Seq data. A comparison of recently proposed normalization methods is required to generate suitable guidelines for the selection of the most appropriate approach for future experiments. In this paper, we compared eight non-abundance (RC, UQ, Med, TMM, DESeq, Q, RPKM, and ERPKM) and two abundance estimation normalization methods (RSEM and Sailfish). The experiments were based on real Illumina high-throughput RNA-Seq of 35- and 76-nucleotide sequences produced in the MAQC project and simulation reads. Reads were mapped with human genome obtained from UCSC Genome Browser Database. For precise evaluation, we investigated Spearman correlation between the normalization results from RNA-Seq and MAQC qRT-PCR values for 996 genes. Based on this work, we showed that out of the eight non-abundance estimation normalization methods, RC, UQ, Med, TMM, DESeq, and Q gave similar normalization results for all data sets. For RNA-Seq of a 35-nucleotide sequence, RPKM showed the highest correlation results, but for RNA-Seq of a 76-nucleotide sequence, least correlation was observed than the other methods. ERPKM did not improve results than RPKM. Between two abundance estimation normalization methods, for RNA-Seq of a 35-nucleotide sequence, higher correlation was obtained with Sailfish than that with RSEM, which was better than without using abundance estimation methods. However, for RNA-Seq of a 76-nucleotide sequence, the results achieved by RSEM were similar to without applying abundance estimation methods, and were much better than with Sailfish. Furthermore, we found that adding a poly-A tail increased alignment numbers, but did not improve normalization results. Spearman correlation analysis revealed that RC, UQ

  6. Methylation Sensitive Amplification Polymorphism Sequencing (MSAP-Seq)—A Method for High-Throughput Analysis of Differentially Methylated CCGG Sites in Plants with Large Genomes

    Science.gov (United States)

    Chwialkowska, Karolina; Korotko, Urszula; Kosinska, Joanna; Szarejko, Iwona; Kwasniewski, Miroslaw

    2017-01-01

    Epigenetic mechanisms, including histone modifications and DNA methylation, mutually regulate chromatin structure, maintain genome integrity, and affect gene expression and transposon mobility. Variations in DNA methylation within plant populations, as well as methylation in response to internal and external factors, are of increasing interest, especially in the crop research field. Methylation Sensitive Amplification Polymorphism (MSAP) is one of the most commonly used methods for assessing DNA methylation changes in plants. This method involves gel-based visualization of PCR fragments from selectively amplified DNA that are cleaved using methylation-sensitive restriction enzymes. In this study, we developed and validated a new method based on the conventional MSAP approach called Methylation Sensitive Amplification Polymorphism Sequencing (MSAP-Seq). We improved the MSAP-based approach by replacing the conventional separation of amplicons on polyacrylamide gels with direct, high-throughput sequencing using Next Generation Sequencing (NGS) and automated data analysis. MSAP-Seq allows for global sequence-based identification of changes in DNA methylation. This technique was validated in Hordeum vulgare. However, MSAP-Seq can be straightforwardly implemented in different plant species, including crops with large, complex and highly repetitive genomes. The incorporation of high-throughput sequencing into MSAP-Seq enables parallel and direct analysis of DNA methylation in hundreds of thousands of sites across the genome. MSAP-Seq provides direct genomic localization of changes and enables quantitative evaluation. We have shown that the MSAP-Seq method specifically targets gene-containing regions and that a single analysis can cover three-quarters of all genes in large genomes. Moreover, MSAP-Seq's simplicity, cost effectiveness, and high-multiplexing capability make this method highly affordable. Therefore, MSAP-Seq can be used for DNA methylation analysis in crop

  7. Quartz-Seq2: a high-throughput single-cell RNA-sequencing method that effectively uses limited sequence reads.

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    Sasagawa, Yohei; Danno, Hiroki; Takada, Hitomi; Ebisawa, Masashi; Tanaka, Kaori; Hayashi, Tetsutaro; Kurisaki, Akira; Nikaido, Itoshi

    2018-03-09

    High-throughput single-cell RNA-seq methods assign limited unique molecular identifier (UMI) counts as gene expression values to single cells from shallow sequence reads and detect limited gene counts. We thus developed a high-throughput single-cell RNA-seq method, Quartz-Seq2, to overcome these issues. Our improvements in the reaction steps make it possible to effectively convert initial reads to UMI counts, at a rate of 30-50%, and detect more genes. To demonstrate the power of Quartz-Seq2, we analyzed approximately 10,000 transcriptomes from in vitro embryonic stem cells and an in vivo stromal vascular fraction with a limited number of reads.

  8. A model-based approach to identify binding sites in CLIP-Seq data.

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    Tao Wang

    Full Text Available Cross-linking immunoprecipitation coupled with high-throughput sequencing (CLIP-Seq has made it possible to identify the targeting sites of RNA-binding proteins in various cell culture systems and tissue types on a genome-wide scale. Here we present a novel model-based approach (MiClip to identify high-confidence protein-RNA binding sites from CLIP-seq datasets. This approach assigns a probability score for each potential binding site to help prioritize subsequent validation experiments. The MiClip algorithm has been tested in both HITS-CLIP and PAR-CLIP datasets. In the HITS-CLIP dataset, the signal/noise ratios of miRNA seed motif enrichment produced by the MiClip approach are between 17% and 301% higher than those by the ad hoc method for the top 10 most enriched miRNAs. In the PAR-CLIP dataset, the MiClip approach can identify ∼50% more validated binding targets than the original ad hoc method and two recently published methods. To facilitate the application of the algorithm, we have released an R package, MiClip (http://cran.r-project.org/web/packages/MiClip/index.html, and a public web-based graphical user interface software (http://galaxy.qbrc.org/tool_runner?tool_id=mi_clip for customized analysis.

  9. Pyicos: a versatile toolkit for the analysis of high-throughput sequencing data.

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    Althammer, Sonja; González-Vallinas, Juan; Ballaré, Cecilia; Beato, Miguel; Eyras, Eduardo

    2011-12-15

    High-throughput sequencing (HTS) has revolutionized gene regulation studies and is now fundamental for the detection of protein-DNA and protein-RNA binding, as well as for measuring RNA expression. With increasing variety and sequencing depth of HTS datasets, the need for more flexible and memory-efficient tools to analyse them is growing. We describe Pyicos, a powerful toolkit for the analysis of mapped reads from diverse HTS experiments: ChIP-Seq, either punctuated or broad signals, CLIP-Seq and RNA-Seq. We prove the effectiveness of Pyicos to select for significant signals and show that its accuracy is comparable and sometimes superior to that of methods specifically designed for each particular type of experiment. Pyicos facilitates the analysis of a variety of HTS datatypes through its flexibility and memory efficiency, providing a useful framework for data integration into models of regulatory genomics. Open-source software, with tutorials and protocol files, is available at http://regulatorygenomics.upf.edu/pyicos or as a Galaxy server at http://regulatorygenomics.upf.edu/galaxy eduardo.eyras@upf.edu Supplementary data are available at Bioinformatics online.

  10. An effective approach for identification of in vivo protein-DNA binding sites from paired-end ChIP-Seq data

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    Wilson Zoe A

    2010-02-01

    Full Text Available Abstract Background ChIP-Seq, which combines chromatin immunoprecipitation (ChIP with high-throughput massively parallel sequencing, is increasingly being used for identification of protein-DNA interactions in vivo in the genome. However, to maximize the effectiveness of data analysis of such sequences requires the development of new algorithms that are able to accurately predict DNA-protein binding sites. Results Here, we present SIPeS (Site Identification from Paired-end Sequencing, a novel algorithm for precise identification of binding sites from short reads generated by paired-end solexa ChIP-Seq technology. In this paper we used ChIP-Seq data from the Arabidopsis basic helix-loop-helix transcription factor ABORTED MICROSPORES (AMS, which is expressed within the anther during pollen development, the results show that SIPeS has better resolution for binding site identification compared to two existing ChIP-Seq peak detection algorithms, Cisgenome and MACS. Conclusions When compared to Cisgenome and MACS, SIPeS shows better resolution for binding site discovery. Moreover, SIPeS is designed to calculate the mappable genome length accurately with the fragment length based on the paired-end reads. Dynamic baselines are also employed to effectively discriminate closely adjacent binding sites, for effective binding sites discovery, which is of particular value when working with high-density genomes.

  11. Practical guidelines for the comprehensive analysis of ChIP-seq data.

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    Timothy Bailey

    Full Text Available Mapping the chromosomal locations of transcription factors, nucleosomes, histone modifications, chromatin remodeling enzymes, chaperones, and polymerases is one of the key tasks of modern biology, as evidenced by the Encyclopedia of DNA Elements (ENCODE Project. To this end, chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq is the standard methodology. Mapping such protein-DNA interactions in vivo using ChIP-seq presents multiple challenges not only in sample preparation and sequencing but also for computational analysis. Here, we present step-by-step guidelines for the computational analysis of ChIP-seq data. We address all the major steps in the analysis of ChIP-seq data: sequencing depth selection, quality checking, mapping, data normalization, assessment of reproducibility, peak calling, differential binding analysis, controlling the false discovery rate, peak annotation, visualization, and motif analysis. At each step in our guidelines we discuss some of the software tools most frequently used. We also highlight the challenges and problems associated with each step in ChIP-seq data analysis. We present a concise workflow for the analysis of ChIP-seq data in Figure 1 that complements and expands on the recommendations of the ENCODE and modENCODE projects. Each step in the workflow is described in detail in the following sections.

  12. Identification and removal of low-complexity sites in allele-specific analysis of ChIP-seq data.

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    Waszak, Sebastian M; Kilpinen, Helena; Gschwind, Andreas R; Orioli, Andrea; Raghav, Sunil K; Witwicki, Robert M; Migliavacca, Eugenia; Yurovsky, Alisa; Lappalainen, Tuuli; Hernandez, Nouria; Reymond, Alexandre; Dermitzakis, Emmanouil T; Deplancke, Bart

    2014-01-15

    High-throughput sequencing technologies enable the genome-wide analysis of the impact of genetic variation on molecular phenotypes at unprecedented resolution. However, although powerful, these technologies can also introduce unexpected artifacts. We investigated the impact of library amplification bias on the identification of allele-specific (AS) molecular events from high-throughput sequencing data derived from chromatin immunoprecipitation assays (ChIP-seq). Putative AS DNA binding activity for RNA polymerase II was determined using ChIP-seq data derived from lymphoblastoid cell lines of two parent-daughter trios. We found that, at high-sequencing depth, many significant AS binding sites suffered from an amplification bias, as evidenced by a larger number of clonal reads representing one of the two alleles. To alleviate this bias, we devised an amplification bias detection strategy, which filters out sites with low read complexity and sites featuring a significant excess of clonal reads. This method will be useful for AS analyses involving ChIP-seq and other functional sequencing assays. The R package abs filter for library clonality simulations and detection of amplification-biased sites is available from http://updepla1srv1.epfl.ch/waszaks/absfilter

  13. iMir: an integrated pipeline for high-throughput analysis of small non-coding RNA data obtained by smallRNA-Seq.

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    Giurato, Giorgio; De Filippo, Maria Rosaria; Rinaldi, Antonio; Hashim, Adnan; Nassa, Giovanni; Ravo, Maria; Rizzo, Francesca; Tarallo, Roberta; Weisz, Alessandro

    2013-12-13

    RNAs. In addition, iMir allowed also the identification of ~70 piRNAs (piwi-interacting RNAs), some of which differentially expressed in proliferating vs growth arrested cells. The integrated data analysis pipeline described here is based on a reliable, flexible and fully automated workflow, useful to rapidly and efficiently analyze high-throughput smallRNA-Seq data, such as those produced by the most recent high-performance next generation sequencers. iMir is available at http://www.labmedmolge.unisa.it/inglese/research/imir.

  14. The simple fool's guide to population genomics via RNA-Seq: An introduction to high-throughput sequencing data analysis

    DEFF Research Database (Denmark)

    De Wit, P.; Pespeni, M.H.; Ladner, J.T.

    2012-01-01

    to Population Genomics via RNA-seq' (SFG), a document intended to serve as an easy-to-follow protocol, walking a user through one example of high-throughput sequencing data analysis of nonmodel organisms. It is by no means an exhaustive protocol, but rather serves as an introduction to the bioinformatic methods...... used in population genomics, enabling a user to gain familiarity with basic analysis steps. The SFG consists of two parts. This document summarizes the steps needed and lays out the basic themes for each and a simple approach to follow. The second document is the full SFG, publicly available at http://sfg.......stanford.edu, that includes detailed protocols for data processing and analysis, along with a repository of custom-made scripts and sample files. Steps included in the SFG range from tissue collection to de novo assembly, blast annotation, alignment, gene expression, functional enrichment, SNP detection, principal components...

  15. PASSPORT-seq: A Novel High-Throughput Bioassay to Functionally Test Polymorphisms in Micro-RNA Target Sites

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    Joseph Ipe

    2018-06-01

    Full Text Available Next-generation sequencing (NGS studies have identified large numbers of genetic variants that are predicted to alter miRNA–mRNA interactions. We developed a novel high-throughput bioassay, PASSPORT-seq, that can functionally test in parallel 100s of these variants in miRNA binding sites (mirSNPs. The results are highly reproducible across both technical and biological replicates. The utility of the bioassay was demonstrated by testing 100 mirSNPs in HEK293, HepG2, and HeLa cells. The results of several of the variants were validated in all three cell lines using traditional individual luciferase assays. Fifty-five mirSNPs were functional in at least one of three cell lines (FDR ≤ 0.05; 11, 36, and 27 of them were functional in HEK293, HepG2, and HeLa cells, respectively. Only four of the variants were functional in all three cell lines, which demonstrates the cell-type specific effects of mirSNPs and the importance of testing the mirSNPs in multiple cell lines. Using PASSPORT-seq, we functionally tested 111 variants in the 3′ UTR of 17 pharmacogenes that are predicted to alter miRNA regulation. Thirty-three of the variants tested were functional in at least one cell line.

  16. Computer and Statistical Analysis of Transcription Factor Binding and Chromatin Modifications by ChIP-seq data in Embryonic Stem Cell

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    Orlov Yuriy

    2012-06-01

    Full Text Available Advances in high throughput sequencing technology have enabled the identification of transcription factor (TF binding sites in genome scale. TF binding studies are important for medical applications and stem cell research. Somatic cells can be reprogrammed to a pluripotent state by the combined introduction of factors such as Oct4, Sox2, c-Myc, Klf4. These reprogrammed cells share many characteristics with embryonic stem cells (ESCs and are known as induced pluripotent stem cells (iPSCs. The signaling requirements for maintenance of human and murine embryonic stem cells (ESCs differ considerably. Genome wide ChIP-seq TF binding maps in mouse stem cells include Oct4, Sox2, Nanog, Tbx3, Smad2 as well as group of other factors. ChIP-seq allows study of new candidate transcription factors for reprogramming. It was shown that Nr5a2 could replace Oct4 for reprogramming. Epigenetic modifications play important role in regulation of gene expression adding additional complexity to transcription network functioning. We have studied associations between different histone modification using published data together with RNA Pol II sites. We found strong associations between activation marks and TF binding sites and present it qualitatively. To meet issues of statistical analysis of genome ChIP-sequencing maps we developed computer program to filter out noise signals and find significant association between binding site affinity and number of sequence reads. The data provide new insights into the function of chromatin organization and regulation in stem cells.

  17. HTSstation: a web application and open-access libraries for high-throughput sequencing data analysis.

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    David, Fabrice P A; Delafontaine, Julien; Carat, Solenne; Ross, Frederick J; Lefebvre, Gregory; Jarosz, Yohan; Sinclair, Lucas; Noordermeer, Daan; Rougemont, Jacques; Leleu, Marion

    2014-01-01

    The HTSstation analysis portal is a suite of simple web forms coupled to modular analysis pipelines for various applications of High-Throughput Sequencing including ChIP-seq, RNA-seq, 4C-seq and re-sequencing. HTSstation offers biologists the possibility to rapidly investigate their HTS data using an intuitive web application with heuristically pre-defined parameters. A number of open-source software components have been implemented and can be used to build, configure and run HTS analysis pipelines reactively. Besides, our programming framework empowers developers with the possibility to design their own workflows and integrate additional third-party software. The HTSstation web application is accessible at http://htsstation.epfl.ch.

  18. Discovery of Protein–lncRNA Interactions by Integrating Large-Scale CLIP-Seq and RNA-Seq Datasets

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    Li, Jun-Hao; Liu, Shun; Zheng, Ling-Ling; Wu, Jie; Sun, Wen-Ju; Wang, Ze-Lin; Zhou, Hui; Qu, Liang-Hu, E-mail: lssqlh@mail.sysu.edu.cn; Yang, Jian-Hua, E-mail: lssqlh@mail.sysu.edu.cn [RNA Information Center, Key Laboratory of Gene Engineering of the Ministry of Education, State Key Laboratory for Biocontrol, Sun Yat-sen University, Guangzhou (China)

    2015-01-14

    Long non-coding RNAs (lncRNAs) are emerging as important regulatory molecules in developmental, physiological, and pathological processes. However, the precise mechanism and functions of most of lncRNAs remain largely unknown. Recent advances in high-throughput sequencing of immunoprecipitated RNAs after cross-linking (CLIP-Seq) provide powerful ways to identify biologically relevant protein–lncRNA interactions. In this study, by analyzing millions of RNA-binding protein (RBP) binding sites from 117 CLIP-Seq datasets generated by 50 independent studies, we identified 22,735 RBP–lncRNA regulatory relationships. We found that one single lncRNA will generally be bound and regulated by one or multiple RBPs, the combination of which may coordinately regulate gene expression. We also revealed the expression correlation of these interaction networks by mining expression profiles of over 6000 normal and tumor samples from 14 cancer types. Our combined analysis of CLIP-Seq data and genome-wide association studies data discovered hundreds of disease-related single nucleotide polymorphisms resided in the RBP binding sites of lncRNAs. Finally, we developed interactive web implementations to provide visualization, analysis, and downloading of the aforementioned large-scale datasets. Our study represented an important step in identification and analysis of RBP–lncRNA interactions and showed that these interactions may play crucial roles in cancer and genetic diseases.

  19. Discovery of Protein–lncRNA Interactions by Integrating Large-Scale CLIP-Seq and RNA-Seq Datasets

    International Nuclear Information System (INIS)

    Li, Jun-Hao; Liu, Shun; Zheng, Ling-Ling; Wu, Jie; Sun, Wen-Ju; Wang, Ze-Lin; Zhou, Hui; Qu, Liang-Hu; Yang, Jian-Hua

    2015-01-01

    Long non-coding RNAs (lncRNAs) are emerging as important regulatory molecules in developmental, physiological, and pathological processes. However, the precise mechanism and functions of most of lncRNAs remain largely unknown. Recent advances in high-throughput sequencing of immunoprecipitated RNAs after cross-linking (CLIP-Seq) provide powerful ways to identify biologically relevant protein–lncRNA interactions. In this study, by analyzing millions of RNA-binding protein (RBP) binding sites from 117 CLIP-Seq datasets generated by 50 independent studies, we identified 22,735 RBP–lncRNA regulatory relationships. We found that one single lncRNA will generally be bound and regulated by one or multiple RBPs, the combination of which may coordinately regulate gene expression. We also revealed the expression correlation of these interaction networks by mining expression profiles of over 6000 normal and tumor samples from 14 cancer types. Our combined analysis of CLIP-Seq data and genome-wide association studies data discovered hundreds of disease-related single nucleotide polymorphisms resided in the RBP binding sites of lncRNAs. Finally, we developed interactive web implementations to provide visualization, analysis, and downloading of the aforementioned large-scale datasets. Our study represented an important step in identification and analysis of RBP–lncRNA interactions and showed that these interactions may play crucial roles in cancer and genetic diseases.

  20. IS-seq: a novel high throughput survey of in vivo IS6110 transposition in multiple Mycobacterium tuberculosis genomes

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    Reyes Alejandro

    2012-06-01

    Full Text Available Abstract Background The insertion element IS6110 is one of the main sources of genomic variability in Mycobacterium tuberculosis, the etiological agent of human tuberculosis. Although IS 6110 has been used extensively as an epidemiological marker, the identification of the precise chromosomal insertion sites has been limited by technical challenges. Here, we present IS-seq, a novel method that combines high-throughput sequencing using Illumina technology with efficient combinatorial sample multiplexing to simultaneously probe 519 clinical isolates, identifying almost all the flanking regions of the element in a single experiment. Results We identified a total of 6,976 IS6110 flanking regions on the different isolates. When validated using reference strains, the method had 100% specificity and 98% positive predictive value. The insertions mapped to both coding and non-coding regions, and in some cases interrupted genes thought to be essential for virulence or in vitro growth. Strains were classified into families using insertion sites, and high agreement with previous studies was observed. Conclusions This high-throughput IS-seq method, which can also be used to map insertions in other organisms, extends previous surveys of in vivo interrupted loci and provides a baseline for probing the consequences of disruptions in M. tuberculosis strains.

  1. eRNA: a graphic user interface-based tool optimized for large data analysis from high-throughput RNA sequencing.

    Science.gov (United States)

    Yuan, Tiezheng; Huang, Xiaoyi; Dittmar, Rachel L; Du, Meijun; Kohli, Manish; Boardman, Lisa; Thibodeau, Stephen N; Wang, Liang

    2014-03-05

    RNA sequencing (RNA-seq) is emerging as a critical approach in biological research. However, its high-throughput advantage is significantly limited by the capacity of bioinformatics tools. The research community urgently needs user-friendly tools to efficiently analyze the complicated data generated by high throughput sequencers. We developed a standalone tool with graphic user interface (GUI)-based analytic modules, known as eRNA. The capacity of performing parallel processing and sample management facilitates large data analyses by maximizing hardware usage and freeing users from tediously handling sequencing data. The module miRNA identification" includes GUIs for raw data reading, adapter removal, sequence alignment, and read counting. The module "mRNA identification" includes GUIs for reference sequences, genome mapping, transcript assembling, and differential expression. The module "Target screening" provides expression profiling analyses and graphic visualization. The module "Self-testing" offers the directory setups, sample management, and a check for third-party package dependency. Integration of other GUIs including Bowtie, miRDeep2, and miRspring extend the program's functionality. eRNA focuses on the common tools required for the mapping and quantification analysis of miRNA-seq and mRNA-seq data. The software package provides an additional choice for scientists who require a user-friendly computing environment and high-throughput capacity for large data analysis. eRNA is available for free download at https://sourceforge.net/projects/erna/?source=directory.

  2. oPOSSUM-3: advanced analysis of regulatory motif over-representation across genes or ChIP-Seq datasets.

    Science.gov (United States)

    Kwon, Andrew T; Arenillas, David J; Worsley Hunt, Rebecca; Wasserman, Wyeth W

    2012-09-01

    oPOSSUM-3 is a web-accessible software system for identification of over-represented transcription factor binding sites (TFBS) and TFBS families in either DNA sequences of co-expressed genes or sequences generated from high-throughput methods, such as ChIP-Seq. Validation of the system with known sets of co-regulated genes and published ChIP-Seq data demonstrates the capacity for oPOSSUM-3 to identify mediating transcription factors (TF) for co-regulated genes or co-recovered sequences. oPOSSUM-3 is available at http://opossum.cisreg.ca.

  3. Global Mapping of Transcription Factor Binding Sites by Sequencing Chromatin Surrogates: a Perspective on Experimental Design, Data Analysis, and Open Problems.

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    Wei, Yingying; Wu, George; Ji, Hongkai

    2013-05-01

    Mapping genome-wide binding sites of all transcription factors (TFs) in all biological contexts is a critical step toward understanding gene regulation. The state-of-the-art technologies for mapping transcription factor binding sites (TFBSs) couple chromatin immunoprecipitation (ChIP) with high-throughput sequencing (ChIP-seq) or tiling array hybridization (ChIP-chip). These technologies have limitations: they are low-throughput with respect to surveying many TFs. Recent advances in genome-wide chromatin profiling, including development of technologies such as DNase-seq, FAIRE-seq and ChIP-seq for histone modifications, make it possible to predict in vivo TFBSs by analyzing chromatin features at computationally determined DNA motif sites. This promising new approach may allow researchers to monitor the genome-wide binding sites of many TFs simultaneously. In this article, we discuss various experimental design and data analysis issues that arise when applying this approach. Through a systematic analysis of the data from the Encyclopedia Of DNA Elements (ENCODE) project, we compare the predictive power of individual and combinations of chromatin marks using supervised and unsupervised learning methods, and evaluate the value of integrating information from public ChIP and gene expression data. We also highlight the challenges and opportunities for developing novel analytical methods, such as resolving the one-motif-multiple-TF ambiguity and distinguishing functional and non-functional TF binding targets from the predicted binding sites. The online version of this article (doi:10.1007/s12561-012-9066-5) contains supplementary material, which is available to authorized users.

  4. MOCCS: Clarifying DNA-binding motif ambiguity using ChIP-Seq data.

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    Ozaki, Haruka; Iwasaki, Wataru

    2016-08-01

    As a key mechanism of gene regulation, transcription factors (TFs) bind to DNA by recognizing specific short sequence patterns that are called DNA-binding motifs. A single TF can accept ambiguity within its DNA-binding motifs, which comprise both canonical (typical) and non-canonical motifs. Clarification of such DNA-binding motif ambiguity is crucial for revealing gene regulatory networks and evaluating mutations in cis-regulatory elements. Although chromatin immunoprecipitation sequencing (ChIP-seq) now provides abundant data on the genomic sequences to which a given TF binds, existing motif discovery methods are unable to directly answer whether a given TF can bind to a specific DNA-binding motif. Here, we report a method for clarifying the DNA-binding motif ambiguity, MOCCS. Given ChIP-Seq data of any TF, MOCCS comprehensively analyzes and describes every k-mer to which that TF binds. Analysis of simulated datasets revealed that MOCCS is applicable to various ChIP-Seq datasets, requiring only a few minutes per dataset. Application to the ENCODE ChIP-Seq datasets proved that MOCCS directly evaluates whether a given TF binds to each DNA-binding motif, even if known position weight matrix models do not provide sufficient information on DNA-binding motif ambiguity. Furthermore, users are not required to provide numerous parameters or background genomic sequence models that are typically unavailable. MOCCS is implemented in Perl and R and is freely available via https://github.com/yuifu/moccs. By complementing existing motif-discovery software, MOCCS will contribute to the basic understanding of how the genome controls diverse cellular processes via DNA-protein interactions. Copyright © 2016 Elsevier Ltd. All rights reserved.

  5. Methylation Sensitive Amplification Polymorphism Sequencing (MSAP-Seq—A Method for High-Throughput Analysis of Differentially Methylated CCGG Sites in Plants with Large Genomes

    Directory of Open Access Journals (Sweden)

    Karolina Chwialkowska

    2017-11-01

    Full Text Available Epigenetic mechanisms, including histone modifications and DNA methylation, mutually regulate chromatin structure, maintain genome integrity, and affect gene expression and transposon mobility. Variations in DNA methylation within plant populations, as well as methylation in response to internal and external factors, are of increasing interest, especially in the crop research field. Methylation Sensitive Amplification Polymorphism (MSAP is one of the most commonly used methods for assessing DNA methylation changes in plants. This method involves gel-based visualization of PCR fragments from selectively amplified DNA that are cleaved using methylation-sensitive restriction enzymes. In this study, we developed and validated a new method based on the conventional MSAP approach called Methylation Sensitive Amplification Polymorphism Sequencing (MSAP-Seq. We improved the MSAP-based approach by replacing the conventional separation of amplicons on polyacrylamide gels with direct, high-throughput sequencing using Next Generation Sequencing (NGS and automated data analysis. MSAP-Seq allows for global sequence-based identification of changes in DNA methylation. This technique was validated in Hordeum vulgare. However, MSAP-Seq can be straightforwardly implemented in different plant species, including crops with large, complex and highly repetitive genomes. The incorporation of high-throughput sequencing into MSAP-Seq enables parallel and direct analysis of DNA methylation in hundreds of thousands of sites across the genome. MSAP-Seq provides direct genomic localization of changes and enables quantitative evaluation. We have shown that the MSAP-Seq method specifically targets gene-containing regions and that a single analysis can cover three-quarters of all genes in large genomes. Moreover, MSAP-Seq's simplicity, cost effectiveness, and high-multiplexing capability make this method highly affordable. Therefore, MSAP-Seq can be used for DNA methylation

  6. SignalSpider: Probabilistic pattern discovery on multiple normalized ChIP-Seq signal profiles

    KAUST Repository

    Wong, Kachun; Li, Yue; Peng, Chengbin; Zhang, Zhaolei

    2014-01-01

    Motivation: Chromatin immunoprecipitation (ChIP) followed by high-throughput sequencing (ChIP-Seq) measures the genome-wide occupancy of transcription factors in vivo. Different combinations of DNA-binding protein occupancies may result in a gene

  7. Parallel factor ChIP provides essential internal control for quantitative differential ChIP-seq.

    Science.gov (United States)

    Guertin, Michael J; Cullen, Amy E; Markowetz, Florian; Holding, Andrew N

    2018-04-17

    A key challenge in quantitative ChIP combined with high-throughput sequencing (ChIP-seq) is the normalization of data in the presence of genome-wide changes in occupancy. Analysis-based normalization methods were developed for transcriptomic data and these are dependent on the underlying assumption that total transcription does not change between conditions. For genome-wide changes in transcription factor (TF) binding, these assumptions do not hold true. The challenges in normalization are confounded by experimental variability during sample preparation, processing and recovery. We present a novel normalization strategy utilizing an internal standard of unchanged peaks for reference. Our method can be readily applied to monitor genome-wide changes by ChIP-seq that are otherwise lost or misrepresented through analytical normalization. We compare our approach to normalization by total read depth and two alternative methods that utilize external experimental controls to study TF binding. We successfully resolve the key challenges in quantitative ChIP-seq analysis and demonstrate its application by monitoring the loss of Estrogen Receptor-alpha (ER) binding upon fulvestrant treatment, ER binding in response to estrodiol, ER mediated change in H4K12 acetylation and profiling ER binding in patient-derived xenographs. This is supported by an adaptable pipeline to normalize and quantify differential TF binding genome-wide and generate metrics for differential binding at individual sites.

  8. Identification of fluorescent compounds with non-specific binding property via high throughput live cell microscopy.

    Directory of Open Access Journals (Sweden)

    Sangeeta Nath

    Full Text Available INTRODUCTION: Compounds exhibiting low non-specific intracellular binding or non-stickiness are concomitant with rapid clearing and in high demand for live-cell imaging assays because they allow for intracellular receptor localization with a high signal/noise ratio. The non-stickiness property is particularly important for imaging intracellular receptors due to the equilibria involved. METHOD: Three mammalian cell lines with diverse genetic backgrounds were used to screen a combinatorial fluorescence library via high throughput live cell microscopy for potential ligands with high in- and out-flux properties. The binding properties of ligands identified from the first screen were subsequently validated on plant root hair. A correlative analysis was then performed between each ligand and its corresponding physiochemical and structural properties. RESULTS: The non-stickiness property of each ligand was quantified as a function of the temporal uptake and retention on a cell-by-cell basis. Our data shows that (i mammalian systems can serve as a pre-screening tool for complex plant species that are not amenable to high-throughput imaging; (ii retention and spatial localization of chemical compounds vary within and between each cell line; and (iii the structural similarities of compounds can infer their non-specific binding properties. CONCLUSION: We have validated a protocol for identifying chemical compounds with non-specific binding properties that is testable across diverse species. Further analysis reveals an overlap between the non-stickiness property and the structural similarity of compounds. The net result is a more robust screening assay for identifying desirable ligands that can be used to monitor intracellular localization. Several new applications of the screening protocol and results are also presented.

  9. Analysis of ChIP-seq Data in R/Bioconductor.

    Science.gov (United States)

    de Santiago, Ines; Carroll, Thomas

    2018-01-01

    The development of novel high-throughput sequencing methods for ChIP (chromatin immunoprecipitation) has provided a very powerful tool to study gene regulation in multiple conditions at unprecedented resolution and scale. Proactive quality-control and appropriate data analysis techniques are of critical importance to extract the most meaningful results from the data. Over the last years, an array of R/Bioconductor tools has been developed allowing researchers to process and analyze ChIP-seq data. This chapter provides an overview of the methods available to analyze ChIP-seq data based primarily on software packages from the open-source Bioconductor project. Protocols described in this chapter cover basic steps including data alignment, peak calling, quality control and data visualization, as well as more complex methods such as the identification of differentially bound regions and functional analyses to annotate regulatory regions. The steps in the data analysis process were demonstrated on publicly available data sets and will serve as a demonstration of the computational procedures routinely used for the analysis of ChIP-seq data in R/Bioconductor, from which readers can construct their own analysis pipelines.

  10. CRISPR-Cas9-Edited Site Sequencing (CRES-Seq): An Efficient and High-Throughput Method for the Selection of CRISPR-Cas9-Edited Clones.

    Science.gov (United States)

    Veeranagouda, Yaligara; Debono-Lagneaux, Delphine; Fournet, Hamida; Thill, Gilbert; Didier, Michel

    2018-01-16

    The emergence of clustered regularly interspaced short palindromic repeats-Cas9 (CRISPR-Cas9) gene editing systems has enabled the creation of specific mutants at low cost, in a short time and with high efficiency, in eukaryotic cells. Since a CRISPR-Cas9 system typically creates an array of mutations in targeted sites, a successful gene editing project requires careful selection of edited clones. This process can be very challenging, especially when working with multiallelic genes and/or polyploid cells (such as cancer and plants cells). Here we described a next-generation sequencing method called CRISPR-Cas9 Edited Site Sequencing (CRES-Seq) for the efficient and high-throughput screening of CRISPR-Cas9-edited clones. CRES-Seq facilitates the precise genotyping up to 96 CRISPR-Cas9-edited sites (CRES) in a single MiniSeq (Illumina) run with an approximate sequencing cost of $6/clone. CRES-Seq is particularly useful when multiple genes are simultaneously targeted by CRISPR-Cas9, and also for screening of clones generated from multiallelic genes/polyploid cells. © 2018 by John Wiley & Sons, Inc. Copyright © 2018 John Wiley & Sons, Inc.

  11. Combining multiple ChIP-seq peak detection systems using combinatorial fusion.

    Science.gov (United States)

    Schweikert, Christina; Brown, Stuart; Tang, Zuojian; Smith, Phillip R; Hsu, D Frank

    2012-01-01

    Due to the recent rapid development in ChIP-seq technologies, which uses high-throughput next-generation DNA sequencing to identify the targets of Chromatin Immunoprecipitation, there is an increasing amount of sequencing data being generated that provides us with greater opportunity to analyze genome-wide protein-DNA interactions. In particular, we are interested in evaluating and enhancing computational and statistical techniques for locating protein binding sites. Many peak detection systems have been developed; in this study, we utilize the following six: CisGenome, MACS, PeakSeq, QuEST, SISSRs, and TRLocator. We define two methods to merge and rescore the regions of two peak detection systems and analyze the performance based on average precision and coverage of transcription start sites. The results indicate that ChIP-seq peak detection can be improved by fusion using score or rank combination. Our method of combination and fusion analysis would provide a means for generic assessment of available technologies and systems and assist researchers in choosing an appropriate system (or fusion method) for analyzing ChIP-seq data. This analysis offers an alternate approach for increasing true positive rates, while decreasing false positive rates and hence improving the ChIP-seq peak identification process.

  12. Identification of Rift Valley fever virus nucleocapsid protein-RNA binding inhibitors using a high-throughput screening assay.

    Science.gov (United States)

    Ellenbecker, Mary; Lanchy, Jean-Marc; Lodmell, J Stephen

    2012-09-01

    Rift Valley fever virus (RVFV) is an emerging infectious pathogen that causes severe disease in humans and livestock and has the potential for global spread. Currently, there is no proven effective treatment for RVFV infection, and there is no licensed vaccine. Inhibition of RNA binding to the essential viral nucleocapsid (N) protein represents a potential antiviral therapeutic strategy because all of the functions performed by N during infection involve RNA binding. To target this interaction, we developed a fluorescence polarization-based high-throughput drug-screening assay and tested 26 424 chemical compounds for their ability to disrupt an N-RNA complex. From libraries of Food and Drug Administration-approved drugs, druglike molecules, and natural product extracts, we identified several lead compounds that are promising candidates for medicinal chemistry.

  13. Impact of artefact removal on ChIP quality metrics in ChIP-seq and ChIP-exo data.

    Directory of Open Access Journals (Sweden)

    Thomas Samuel Carroll

    2014-04-01

    Full Text Available With the advent of ChIP-seq multiplexing technologies and the subsequent increase in ChIP-seq throughput, the development of working standards for the quality assessment of ChIP-seq studies has received significant attention. The ENCODE consortium’s large scale analysis of transcription factor binding and epigenetic marks as well as concordant work on ChIP-seq by other laboratories has established a new generation of ChIP-seq quality control measures. The use of these metrics alongside common processing steps has however not been evaluated. In this study, we investigate the effects of blacklisting and removal of duplicated reads on established metrics of ChIP-seq quality and show that the interpretation of these metrics is highly dependent on the ChIP-seq preprocessing steps applied. Further to this we perform the first investigation of the use of these metrics for ChIP-exo data and make recommendations for the adaptation of the NSC statistic to allow for the assessment of ChIP-exo efficiency.

  14. An integrated model of multiple-condition ChIP-Seq data reveals predeterminants of Cdx2 binding.

    Directory of Open Access Journals (Sweden)

    Shaun Mahony

    2014-03-01

    Full Text Available Regulatory proteins can bind to different sets of genomic targets in various cell types or conditions. To reliably characterize such condition-specific regulatory binding we introduce MultiGPS, an integrated machine learning approach for the analysis of multiple related ChIP-seq experiments. MultiGPS is based on a generalized Expectation Maximization framework that shares information across multiple experiments for binding event discovery. We demonstrate that our framework enables the simultaneous modeling of sparse condition-specific binding changes, sequence dependence, and replicate-specific noise sources. MultiGPS encourages consistency in reported binding event locations across multiple-condition ChIP-seq datasets and provides accurate estimation of ChIP enrichment levels at each event. MultiGPS's multi-experiment modeling approach thus provides a reliable platform for detecting differential binding enrichment across experimental conditions. We demonstrate the advantages of MultiGPS with an analysis of Cdx2 binding in three distinct developmental contexts. By accurately characterizing condition-specific Cdx2 binding, MultiGPS enables novel insight into the mechanistic basis of Cdx2 site selectivity. Specifically, the condition-specific Cdx2 sites characterized by MultiGPS are highly associated with pre-existing genomic context, suggesting that such sites are pre-determined by cell-specific regulatory architecture. However, MultiGPS-defined condition-independent sites are not predicted by pre-existing regulatory signals, suggesting that Cdx2 can bind to a subset of locations regardless of genomic environment. A summary of this paper appears in the proceedings of the RECOMB 2014 conference, April 2-5.

  15. Genome wide binding (ChIP-Seq of murine Bapx1 and Sox9 proteins in vivo and in vitro

    Directory of Open Access Journals (Sweden)

    Sumantra Chatterjee

    2016-12-01

    Full Text Available This work pertains to GEO submission GSE36672, in vivo and in vitro genome wide binding (ChIP-Seq of Bapx1/Nkx3.2 and Sox9 proteins. We have previously shown that data from a genome wide binding assay combined with transcriptional profiling is an insightful means to divulge the mechanisms directing cell type specification and the generation of tissues and subsequent organs [1]. Our earlier work identified the role of the DNA-binding homeodomain containing protein Bapx1/Nkx3.2 in midgestation murine embryos. Microarray analysis of EGFP-tagged cells (both wildtype and null was integrated using ChIP-Seq analysis of Bapx1/Nkx3.2 and Sox9 DNA-binding proteins in living tissue.

  16. High-throughput transcriptome analysis of barley (Hordeum vulgare) exposed to excessive boron.

    Science.gov (United States)

    Tombuloglu, Guzin; Tombuloglu, Huseyin; Sakcali, M Serdal; Unver, Turgay

    2015-02-15

    Boron (B) is an essential micronutrient for optimum plant growth. However, above certain threshold B is toxic and causes yield loss in agricultural lands. While a number of studies were conducted to understand B tolerance mechanism, a transcriptome-wide approach for B tolerant barley is performed here for the first time. A high-throughput RNA-Seq (cDNA) sequencing technology (Illumina) was used with barley (Hordeum vulgare), yielding 208 million clean reads. In total, 256,874 unigenes were generated and assigned to known peptide databases: Gene Ontology (GO) (99,043), Swiss-Prot (38,266), Clusters of Orthologous Groups (COG) (26,250), and the Kyoto Encyclopedia of Genes and Genomes (KEGG) (36,860), as determined by BLASTx search. According to the digital gene expression (DGE) analyses, 16% and 17% of the transcripts were found to be differentially regulated in root and leaf tissues, respectively. Most of them were involved in cell wall, stress response, membrane, protein kinase and transporter mechanisms. Some of the genes detected as highly expressed in root tissue are phospholipases, predicted divalent heavy-metal cation transporters, formin-like proteins and calmodulin/Ca(2+)-binding proteins. In addition, chitin-binding lectin precursor, ubiquitin carboxyl-terminal hydrolase, and serine/threonine-protein kinase AFC2 genes were indicated to be highly regulated in leaf tissue upon excess B treatment. Some pathways, such as the Ca(2+)-calmodulin system, are activated in response to B toxicity. The differential regulation of 10 transcripts was confirmed by qRT-PCR, revealing the tissue-specific responses against B toxicity and their putative function in B-tolerance mechanisms. Copyright © 2014. Published by Elsevier B.V.

  17. High throughput screening of ligand binding to macromolecules using high resolution powder diffraction

    Science.gov (United States)

    Von Dreele, Robert B.; D'Amico, Kevin

    2006-10-31

    A process is provided for the high throughput screening of binding of ligands to macromolecules using high resolution powder diffraction data including producing a first sample slurry of a selected polycrystalline macromolecule material and a solvent, producing a second sample slurry of a selected polycrystalline macromolecule material, one or more ligands and the solvent, obtaining a high resolution powder diffraction pattern on each of said first sample slurry and the second sample slurry, and, comparing the high resolution powder diffraction pattern of the first sample slurry and the high resolution powder diffraction pattern of the second sample slurry whereby a difference in the high resolution powder diffraction patterns of the first sample slurry and the second sample slurry provides a positive indication for the formation of a complex between the selected polycrystalline macromolecule material and at least one of the one or more ligands.

  18. The ChIP-Seq tools and web server: a resource for analyzing ChIP-seq and other types of genomic data.

    Science.gov (United States)

    Ambrosini, Giovanna; Dreos, René; Kumar, Sunil; Bucher, Philipp

    2016-11-18

    ChIP-seq and related high-throughput chromatin profilig assays generate ever increasing volumes of highly valuable biological data. To make sense out of it, biologists need versatile, efficient and user-friendly tools for access, visualization and itegrative analysis of such data. Here we present the ChIP-Seq command line tools and web server, implementing basic algorithms for ChIP-seq data analysis starting with a read alignment file. The tools are optimized for memory-efficiency and speed thus allowing for processing of large data volumes on inexpensive hardware. The web interface provides access to a large database of public data. The ChIP-Seq tools have a modular and interoperable design in that the output from one application can serve as input to another one. Complex and innovative tasks can thus be achieved by running several tools in a cascade. The various ChIP-Seq command line tools and web services either complement or compare favorably to related bioinformatics resources in terms of computational efficiency, ease of access to public data and interoperability with other web-based tools. The ChIP-Seq server is accessible at http://ccg.vital-it.ch/chipseq/ .

  19. An improved ChIP-seq peak detection system for simultaneously identifying post-translational modified transcription factors by combinatorial fusion, using SUMOylation as an example.

    Science.gov (United States)

    Cheng, Chia-Yang; Chu, Chia-Han; Hsu, Hung-Wei; Hsu, Fang-Rong; Tang, Chung Yi; Wang, Wen-Ching; Kung, Hsing-Jien; Chang, Pei-Ching

    2014-01-01

    Post-translational modification (PTM) of transcriptional factors and chromatin remodelling proteins is recognized as a major mechanism by which transcriptional regulation occurs. Chromatin immunoprecipitation (ChIP) in combination with high-throughput sequencing (ChIP-seq) is being applied as a gold standard when studying the genome-wide binding sites of transcription factor (TFs). This has greatly improved our understanding of protein-DNA interactions on a genomic-wide scale. However, current ChIP-seq peak calling tools are not sufficiently sensitive and are unable to simultaneously identify post-translational modified TFs based on ChIP-seq analysis; this is largely due to the wide-spread presence of multiple modified TFs. Using SUMO-1 modification as an example; we describe here an improved approach that allows the simultaneous identification of the particular genomic binding regions of all TFs with SUMO-1 modification. Traditional peak calling methods are inadequate when identifying multiple TF binding sites that involve long genomic regions and therefore we designed a ChIP-seq processing pipeline for the detection of peaks via a combinatorial fusion method. Then, we annotate the peaks with known transcription factor binding sites (TFBS) using the Transfac Matrix Database (v7.0), which predicts potential SUMOylated TFs. Next, the peak calling result was further analyzed based on the promoter proximity, TFBS annotation, a literature review, and was validated by ChIP-real-time quantitative PCR (qPCR) and ChIP-reChIP real-time qPCR. The results show clearly that SUMOylated TFs are able to be pinpointed using our pipeline. A methodology is presented that analyzes SUMO-1 ChIP-seq patterns and predicts related TFs. Our analysis uses three peak calling tools. The fusion of these different tools increases the precision of the peak calling results. TFBS annotation method is able to predict potential SUMOylated TFs. Here, we offer a new approach that enhances ChIP-seq

  20. glbase: a framework for combining, analyzing and displaying heterogeneous genomic and high-throughput sequencing data

    Directory of Open Access Journals (Sweden)

    Andrew Paul Hutchins

    2014-01-01

    Full Text Available Genomic datasets and the tools to analyze them have proliferated at an astonishing rate. However, such tools are often poorly integrated with each other: each program typically produces its own custom output in a variety of non-standard file formats. Here we present glbase, a framework that uses a flexible set of descriptors that can quickly parse non-binary data files. glbase includes many functions to intersect two lists of data, including operations on genomic interval data and support for the efficient random access to huge genomic data files. Many glbase functions can produce graphical outputs, including scatter plots, heatmaps, boxplots and other common analytical displays of high-throughput data such as RNA-seq, ChIP-seq and microarray expression data. glbase is designed to rapidly bring biological data into a Python-based analytical environment to facilitate analysis and data processing. In summary, glbase is a flexible and multifunctional toolkit that allows the combination and analysis of high-throughput data (especially next-generation sequencing and genome-wide data, and which has been instrumental in the analysis of complex data sets. glbase is freely available at http://bitbucket.org/oaxiom/glbase/.

  1. glbase: a framework for combining, analyzing and displaying heterogeneous genomic and high-throughput sequencing data.

    Science.gov (United States)

    Hutchins, Andrew Paul; Jauch, Ralf; Dyla, Mateusz; Miranda-Saavedra, Diego

    2014-01-01

    Genomic datasets and the tools to analyze them have proliferated at an astonishing rate. However, such tools are often poorly integrated with each other: each program typically produces its own custom output in a variety of non-standard file formats. Here we present glbase, a framework that uses a flexible set of descriptors that can quickly parse non-binary data files. glbase includes many functions to intersect two lists of data, including operations on genomic interval data and support for the efficient random access to huge genomic data files. Many glbase functions can produce graphical outputs, including scatter plots, heatmaps, boxplots and other common analytical displays of high-throughput data such as RNA-seq, ChIP-seq and microarray expression data. glbase is designed to rapidly bring biological data into a Python-based analytical environment to facilitate analysis and data processing. In summary, glbase is a flexible and multifunctional toolkit that allows the combination and analysis of high-throughput data (especially next-generation sequencing and genome-wide data), and which has been instrumental in the analysis of complex data sets. glbase is freely available at http://bitbucket.org/oaxiom/glbase/.

  2. High-throughput analysis using non-depletive SPME: challenges and applications to the determination of free and total concentrations in small sample volumes.

    Science.gov (United States)

    Boyacı, Ezel; Bojko, Barbara; Reyes-Garcés, Nathaly; Poole, Justen J; Gómez-Ríos, Germán Augusto; Teixeira, Alexandre; Nicol, Beate; Pawliszyn, Janusz

    2018-01-18

    In vitro high-throughput non-depletive quantitation of chemicals in biofluids is of growing interest in many areas. Some of the challenges facing researchers include the limited volume of biofluids, rapid and high-throughput sampling requirements, and the lack of reliable methods. Coupled to the above, growing interest in the monitoring of kinetics and dynamics of miniaturized biosystems has spurred the demand for development of novel and revolutionary methodologies for analysis of biofluids. The applicability of solid-phase microextraction (SPME) is investigated as a potential technology to fulfill the aforementioned requirements. As analytes with sufficient diversity in their physicochemical features, nicotine, N,N-Diethyl-meta-toluamide, and diclofenac were selected as test compounds for the study. The objective was to develop methodologies that would allow repeated non-depletive sampling from 96-well plates, using 100 µL of sample. Initially, thin film-SPME was investigated. Results revealed substantial depletion and consequent disruption in the system. Therefore, new ultra-thin coated fibers were developed. The applicability of this device to the described sampling scenario was tested by determining the protein binding of the analytes. Results showed good agreement with rapid equilibrium dialysis. The presented method allows high-throughput analysis using small volumes, enabling fast reliable free and total concentration determinations without disruption of system equilibrium.

  3. ChIP-PIT: Enhancing the Analysis of ChIP-Seq Data Using Convex-Relaxed Pair-Wise Interaction Tensor Decomposition.

    Science.gov (United States)

    Zhu, Lin; Guo, Wei-Li; Deng, Su-Ping; Huang, De-Shuang

    2016-01-01

    In recent years, thanks to the efforts of individual scientists and research consortiums, a huge amount of chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) experimental data have been accumulated. Instead of investigating them independently, several recent studies have convincingly demonstrated that a wealth of scientific insights can be gained by integrative analysis of these ChIP-seq data. However, when used for the purpose of integrative analysis, a serious drawback of current ChIP-seq technique is that it is still expensive and time-consuming to generate ChIP-seq datasets of high standard. Most researchers are therefore unable to obtain complete ChIP-seq data for several TFs in a wide variety of cell lines, which considerably limits the understanding of transcriptional regulation pattern. In this paper, we propose a novel method called ChIP-PIT to overcome the aforementioned limitation. In ChIP-PIT, ChIP-seq data corresponding to a diverse collection of cell types, TFs and genes are fused together using the three-mode pair-wise interaction tensor (PIT) model, and the prediction of unperformed ChIP-seq experimental results is formulated as a tensor completion problem. Computationally, we propose efficient first-order method based on extensions of coordinate descent method to learn the optimal solution of ChIP-PIT, which makes it particularly suitable for the analysis of massive scale ChIP-seq data. Experimental evaluation the ENCODE data illustrate the usefulness of the proposed model.

  4. High-throughput genetic analysis in a cohort of patients with Ocular Developmental Anomalies

    Directory of Open Access Journals (Sweden)

    Suganya Kandeeban

    2017-10-01

    Full Text Available Anophthalmia and microphthalmia (A/M are developmental ocular malformations in which the eye fails to form or is smaller than normal with both genetic and environmental etiology. Microphthalmia is often associated with additional ocular anomalies, most commonly coloboma or cataract [1, 2]. A/M has a combined incidence between 1-3.2 cases per 10,000 live births in Caucasians [3, 4]. The spectrum of genetic abnormalities (chromosomal and molecular associated with these ocular developmental defects are being investigated in the current study. A detailed pedigree analysis and ophthalmic examination have been documented for the enrolled patients followed by blood collection and DNA extraction. The strategies for genetic analysis included chromosomal analysis by conventional and array based (affymetrix cytoscan HD array methods, targeted re-sequencing of the candidate genes and whole exome sequencing (WES in Illumina HiSEQ 2500. WES was done in families excluded for mutations in candidate genes. Twenty four samples (Microphthalmia (M-5, Anophthalmia (A-7,Coloboma-2, M&A-1, microphthalmia and coloboma / other ocular features-9 were initially analyzed using conventional Geimsa Trypsin Geimsa banding of which 4 samples revealed gross chromosomal aberrations (deletions in 3q26.3-28, 11p13 (N=2 and 11q23 regions. Targeted re sequencing of candidate genes showed mutations in CHX10, PAX6, FOXE3, ABCB6 and SHH genes in 6 samples. High throughput array based chromosomal analysis revealed aberrations in 4 samples (17q21dup (n=2, 8p11del (n=2. Overall, genetic alterations in known candidate genes are seen in 50% of the study subjects. Whole exome sequencing was performed in samples that were excluded for mutations in candidate genes and the results are discussed.

  5. High Throughput Synthesis and Screening for Agents Inhibiting Androgen Receptor Mediated Gene Transcription

    National Research Council Canada - National Science Library

    Boger, Dale L

    2005-01-01

    .... This entails the high throughput synthesis of DNA binding agents related to distamycin, their screening for binding to androgen response elements using a new high throughput DNA binding screen...

  6. High Throughput Synthesis and Screening for Agents Inhibiting Androgen Receptor Mediated Gene Transcription

    National Research Council Canada - National Science Library

    Boger, Dale

    2004-01-01

    .... This entails the high throughput synthesis of DNA binding agents related to distamycin, their screening for binding to androgen response elements using a new high throughput DNA binding screen...

  7. Evolving Transcription Factor Binding Site Models From Protein Binding Microarray Data

    KAUST Repository

    Wong, Ka-Chun; Peng, Chengbin; Li, Yue

    2016-01-01

    Protein binding microarray (PBM) is a high-throughput platform that can measure the DNA binding preference of a protein in a comprehensive and unbiased manner. In this paper, we describe the PBM motif model building problem. We apply several evolutionary computation methods and compare their performance with the interior point method, demonstrating their performance advantages. In addition, given the PBM domain knowledge, we propose and describe a novel method called kmerGA which makes domain-specific assumptions to exploit PBM data properties to build more accurate models than the other models built. The effectiveness and robustness of kmerGA is supported by comprehensive performance benchmarking on more than 200 datasets, time complexity analysis, convergence analysis, parameter analysis, and case studies. To demonstrate its utility further, kmerGA is applied to two real world applications: 1) PBM rotation testing and 2) ChIP-Seq peak sequence prediction. The results support the biological relevance of the models learned by kmerGA, and thus its real world applicability.

  8. Evolving Transcription Factor Binding Site Models From Protein Binding Microarray Data

    KAUST Repository

    Wong, Ka-Chun

    2016-02-02

    Protein binding microarray (PBM) is a high-throughput platform that can measure the DNA binding preference of a protein in a comprehensive and unbiased manner. In this paper, we describe the PBM motif model building problem. We apply several evolutionary computation methods and compare their performance with the interior point method, demonstrating their performance advantages. In addition, given the PBM domain knowledge, we propose and describe a novel method called kmerGA which makes domain-specific assumptions to exploit PBM data properties to build more accurate models than the other models built. The effectiveness and robustness of kmerGA is supported by comprehensive performance benchmarking on more than 200 datasets, time complexity analysis, convergence analysis, parameter analysis, and case studies. To demonstrate its utility further, kmerGA is applied to two real world applications: 1) PBM rotation testing and 2) ChIP-Seq peak sequence prediction. The results support the biological relevance of the models learned by kmerGA, and thus its real world applicability.

  9. Nanoscale Synaptic Membrane Mimetic Allows Unbiased High Throughput Screen That Targets Binding Sites for Alzheimer's-Associated Aβ Oligomers.

    Directory of Open Access Journals (Sweden)

    Kyle C Wilcox

    Full Text Available Despite their value as sources of therapeutic drug targets, membrane proteomes are largely inaccessible to high-throughput screening (HTS tools designed for soluble proteins. An important example comprises the membrane proteins that bind amyloid β oligomers (AβOs. AβOs are neurotoxic ligands thought to instigate the synapse damage that leads to Alzheimer's dementia. At present, the identities of initial AβO binding sites are highly uncertain, largely because of extensive protein-protein interactions that occur following attachment of AβOs to surface membranes. Here, we show that AβO binding sites can be obtained in a state suitable for unbiased HTS by encapsulating the solubilized synaptic membrane proteome into nanoscale lipid bilayers (Nanodiscs. This method gives a soluble membrane protein library (SMPL--a collection of individualized synaptic proteins in a soluble state. Proteins within SMPL Nanodiscs showed enzymatic and ligand binding activity consistent with conformational integrity. AβOs were found to bind SMPL Nanodiscs with high affinity and specificity, with binding dependent on intact synaptic membrane proteins, and selective for the higher molecular weight oligomers known to accumulate at synapses. Combining SMPL Nanodiscs with a mix-incubate-read chemiluminescence assay provided a solution-based HTS platform to discover antagonists of AβO binding. Screening a library of 2700 drug-like compounds and natural products yielded one compound that potently reduced AβO binding to SMPL Nanodiscs, synaptosomes, and synapses in nerve cell cultures. Although not a therapeutic candidate, this small molecule inhibitor of synaptic AβO binding will provide a useful experimental antagonist for future mechanistic studies of AβOs in Alzheimer's model systems. Overall, results provide proof of concept for using SMPLs in high throughput screening for AβO binding antagonists, and illustrate in general how a SMPL Nanodisc system can

  10. Nanoscale Synaptic Membrane Mimetic Allows Unbiased High Throughput Screen That Targets Binding Sites for Alzheimer's-Associated Aβ Oligomers.

    Science.gov (United States)

    Wilcox, Kyle C; Marunde, Matthew R; Das, Aditi; Velasco, Pauline T; Kuhns, Benjamin D; Marty, Michael T; Jiang, Haoming; Luan, Chi-Hao; Sligar, Stephen G; Klein, William L

    2015-01-01

    Despite their value as sources of therapeutic drug targets, membrane proteomes are largely inaccessible to high-throughput screening (HTS) tools designed for soluble proteins. An important example comprises the membrane proteins that bind amyloid β oligomers (AβOs). AβOs are neurotoxic ligands thought to instigate the synapse damage that leads to Alzheimer's dementia. At present, the identities of initial AβO binding sites are highly uncertain, largely because of extensive protein-protein interactions that occur following attachment of AβOs to surface membranes. Here, we show that AβO binding sites can be obtained in a state suitable for unbiased HTS by encapsulating the solubilized synaptic membrane proteome into nanoscale lipid bilayers (Nanodiscs). This method gives a soluble membrane protein library (SMPL)--a collection of individualized synaptic proteins in a soluble state. Proteins within SMPL Nanodiscs showed enzymatic and ligand binding activity consistent with conformational integrity. AβOs were found to bind SMPL Nanodiscs with high affinity and specificity, with binding dependent on intact synaptic membrane proteins, and selective for the higher molecular weight oligomers known to accumulate at synapses. Combining SMPL Nanodiscs with a mix-incubate-read chemiluminescence assay provided a solution-based HTS platform to discover antagonists of AβO binding. Screening a library of 2700 drug-like compounds and natural products yielded one compound that potently reduced AβO binding to SMPL Nanodiscs, synaptosomes, and synapses in nerve cell cultures. Although not a therapeutic candidate, this small molecule inhibitor of synaptic AβO binding will provide a useful experimental antagonist for future mechanistic studies of AβOs in Alzheimer's model systems. Overall, results provide proof of concept for using SMPLs in high throughput screening for AβO binding antagonists, and illustrate in general how a SMPL Nanodisc system can facilitate drug discovery

  11. Integrative ChIP-seq/microarray analysis identifies a CTNNB1 target signature enriched in intestinal stem cells and colon cancer.

    Science.gov (United States)

    Watanabe, Kazuhide; Biesinger, Jacob; Salmans, Michael L; Roberts, Brian S; Arthur, William T; Cleary, Michele; Andersen, Bogi; Xie, Xiaohui; Dai, Xing

    2014-01-01

    Deregulation of canonical Wnt/CTNNB1 (beta-catenin) pathway is one of the earliest events in the pathogenesis of colon cancer. Mutations in APC or CTNNB1 are highly frequent in colon cancer and cause aberrant stabilization of CTNNB1, which activates the transcription of Wnt target genes by binding to chromatin via the TCF/LEF transcription factors. Here we report an integrative analysis of genome-wide chromatin occupancy of CTNNB1 by chromatin immunoprecipitation coupled with high-throughput sequencing (ChIP-seq) and gene expression profiling by microarray analysis upon RNAi-mediated knockdown of CTNNB1 in colon cancer cells. We observed 3629 CTNNB1 binding peaks across the genome and a significant correlation between CTNNB1 binding and knockdown-induced gene expression change. Our integrative analysis led to the discovery of a direct Wnt target signature composed of 162 genes. Gene ontology analysis of this signature revealed a significant enrichment of Wnt pathway genes, suggesting multiple feedback regulations of the pathway. We provide evidence that this gene signature partially overlaps with the Lgr5+ intestinal stem cell signature, and is significantly enriched in normal intestinal stem cells as well as in clinical colorectal cancer samples. Interestingly, while the expression of the CTNNB1 target gene set does not correlate with survival, elevated expression of negative feedback regulators within the signature predicts better prognosis. Our data provide a genome-wide view of chromatin occupancy and gene regulation of Wnt/CTNNB1 signaling in colon cancer cells.

  12. Peptide Binding to HLA Class I Molecules: Homogenous, High-Throughput Screening, and Affinity Assays

    DEFF Research Database (Denmark)

    Harndahl, Mikkel; Justesen, Sune Frederik Lamdahl; Lamberth, Kasper

    2009-01-01

    , better signal-to-background ratios, and a higher capacity. They also describe an efficient approach to screen peptides for binding to HLA molecules. For the occasional user, this will serve as a robust, simple peptide-HLA binding assay. For the more dedicated user, it can easily be performed in a high-throughput...... the luminescent oxygen channeling immunoassay technology (abbreviated LOCI and commercialized as AlphaScreen (TM)). Compared with an enzyme-linked immunosorbent assay-based peptide-HLA class I binding assay, the LOCI assay yields virtually identical affinity measurements, although having a broader dynamic range...... screening mode using standard liquid handling robotics and 384-well plates. We have successfully applied this assay to more than 60 different HLA molecules, leading to more than 2 million measurements. (Journal of Biomolecular Screening 2009: 173-180)...

  13. A novel ultra high-throughput 16S rRNA gene amplicon sequencing library preparation method for the Illumina HiSeq platform.

    Science.gov (United States)

    de Muinck, Eric J; Trosvik, Pål; Gilfillan, Gregor D; Hov, Johannes R; Sundaram, Arvind Y M

    2017-07-06

    Advances in sequencing technologies and bioinformatics have made the analysis of microbial communities almost routine. Nonetheless, the need remains to improve on the techniques used for gathering such data, including increasing throughput while lowering cost and benchmarking the techniques so that potential sources of bias can be better characterized. We present a triple-index amplicon sequencing strategy to sequence large numbers of samples at significantly lower c ost and in a shorter timeframe compared to existing methods. The design employs a two-stage PCR protocol, incorpo rating three barcodes to each sample, with the possibility to add a fourth-index. It also includes heterogeneity spacers to overcome low complexity issues faced when sequencing amplicons on Illumina platforms. The library preparation method was extensively benchmarked through analysis of a mock community in order to assess biases introduced by sample indexing, number of PCR cycles, and template concentration. We further evaluated the method through re-sequencing of a standardized environmental sample. Finally, we evaluated our protocol on a set of fecal samples from a small cohort of healthy adults, demonstrating good performance in a realistic experimental setting. Between-sample variation was mainly related to batch effects, such as DNA extraction, while sample indexing was also a significant source of bias. PCR cycle number strongly influenced chimera formation and affected relative abundance estimates of species with high GC content. Libraries were sequenced using the Illumina HiSeq and MiSeq platforms to demonstrate that this protocol is highly scalable to sequence thousands of samples at a very low cost. Here, we provide the most comprehensive study of performance and bias inherent to a 16S rRNA gene amplicon sequencing method to date. Triple-indexing greatly reduces the number of long custom DNA oligos required for library preparation, while the inclusion of variable length

  14. The Impact of Normalization Methods on RNA-Seq Data Analysis

    Science.gov (United States)

    Zyprych-Walczak, J.; Szabelska, A.; Handschuh, L.; Górczak, K.; Klamecka, K.; Figlerowicz, M.; Siatkowski, I.

    2015-01-01

    High-throughput sequencing technologies, such as the Illumina Hi-seq, are powerful new tools for investigating a wide range of biological and medical problems. Massive and complex data sets produced by the sequencers create a need for development of statistical and computational methods that can tackle the analysis and management of data. The data normalization is one of the most crucial steps of data processing and this process must be carefully considered as it has a profound effect on the results of the analysis. In this work, we focus on a comprehensive comparison of five normalization methods related to sequencing depth, widely used for transcriptome sequencing (RNA-seq) data, and their impact on the results of gene expression analysis. Based on this study, we suggest a universal workflow that can be applied for the selection of the optimal normalization procedure for any particular data set. The described workflow includes calculation of the bias and variance values for the control genes, sensitivity and specificity of the methods, and classification errors as well as generation of the diagnostic plots. Combining the above information facilitates the selection of the most appropriate normalization method for the studied data sets and determines which methods can be used interchangeably. PMID:26176014

  15. Nanoscale Synaptic Membrane Mimetic Allows Unbiased High Throughput Screen That Targets Binding Sites for Alzheimer?s-Associated A? Oligomers

    OpenAIRE

    Wilcox, Kyle C.; Marunde, Matthew R.; Das, Aditi; Velasco, Pauline T.; Kuhns, Benjamin D.; Marty, Michael T.; Jiang, Haoming; Luan, Chi-Hao; Sligar, Stephen G.; Klein, William L.

    2015-01-01

    Despite their value as sources of therapeutic drug targets, membrane proteomes are largely inaccessible to high-throughput screening (HTS) tools designed for soluble proteins. An important example comprises the membrane proteins that bind amyloid β oligomers (AβOs). AβOs are neurotoxic ligands thought to instigate the synapse damage that leads to Alzheimer's dementia. At present, the identities of initial AβO binding sites are highly uncertain, largely because of extensive protein-protein int...

  16. Nanoscale Synaptic Membrane Mimetic Allows Unbiased High Throughput Screen That Targets Binding Sites for Alzheimer’s-Associated Aβ Oligomers

    Science.gov (United States)

    Wilcox, Kyle C.; Marunde, Matthew R.; Das, Aditi; Velasco, Pauline T.; Kuhns, Benjamin D.; Marty, Michael T.; Jiang, Haoming; Luan, Chi-Hao; Sligar, Stephen G.; Klein, William L.

    2015-01-01

    Despite their value as sources of therapeutic drug targets, membrane proteomes are largely inaccessible to high-throughput screening (HTS) tools designed for soluble proteins. An important example comprises the membrane proteins that bind amyloid β oligomers (AβOs). AβOs are neurotoxic ligands thought to instigate the synapse damage that leads to Alzheimer’s dementia. At present, the identities of initial AβO binding sites are highly uncertain, largely because of extensive protein-protein interactions that occur following attachment of AβOs to surface membranes. Here, we show that AβO binding sites can be obtained in a state suitable for unbiased HTS by encapsulating the solubilized synaptic membrane proteome into nanoscale lipid bilayers (Nanodiscs). This method gives a soluble membrane protein library (SMPL)—a collection of individualized synaptic proteins in a soluble state. Proteins within SMPL Nanodiscs showed enzymatic and ligand binding activity consistent with conformational integrity. AβOs were found to bind SMPL Nanodiscs with high affinity and specificity, with binding dependent on intact synaptic membrane proteins, and selective for the higher molecular weight oligomers known to accumulate at synapses. Combining SMPL Nanodiscs with a mix-incubate-read chemiluminescence assay provided a solution-based HTS platform to discover antagonists of AβO binding. Screening a library of 2700 drug-like compounds and natural products yielded one compound that potently reduced AβO binding to SMPL Nanodiscs, synaptosomes, and synapses in nerve cell cultures. Although not a therapeutic candidate, this small molecule inhibitor of synaptic AβO binding will provide a useful experimental antagonist for future mechanistic studies of AβOs in Alzheimer’s model systems. Overall, results provide proof of concept for using SMPLs in high throughput screening for AβO binding antagonists, and illustrate in general how a SMPL Nanodisc system can facilitate drug

  17. Predicting gene regulatory networks of soybean nodulation from RNA-Seq transcriptome data.

    Science.gov (United States)

    Zhu, Mingzhu; Dahmen, Jeremy L; Stacey, Gary; Cheng, Jianlin

    2013-09-22

    High-throughput RNA sequencing (RNA-Seq) is a revolutionary technique to study the transcriptome of a cell under various conditions at a systems level. Despite the wide application of RNA-Seq techniques to generate experimental data in the last few years, few computational methods are available to analyze this huge amount of transcription data. The computational methods for constructing gene regulatory networks from RNA-Seq expression data of hundreds or even thousands of genes are particularly lacking and urgently needed. We developed an automated bioinformatics method to predict gene regulatory networks from the quantitative expression values of differentially expressed genes based on RNA-Seq transcriptome data of a cell in different stages and conditions, integrating transcriptional, genomic and gene function data. We applied the method to the RNA-Seq transcriptome data generated for soybean root hair cells in three different development stages of nodulation after rhizobium infection. The method predicted a soybean nodulation-related gene regulatory network consisting of 10 regulatory modules common for all three stages, and 24, 49 and 70 modules separately for the first, second and third stage, each containing both a group of co-expressed genes and several transcription factors collaboratively controlling their expression under different conditions. 8 of 10 common regulatory modules were validated by at least two kinds of validations, such as independent DNA binding motif analysis, gene function enrichment test, and previous experimental data in the literature. We developed a computational method to reliably reconstruct gene regulatory networks from RNA-Seq transcriptome data. The method can generate valuable hypotheses for interpreting biological data and designing biological experiments such as ChIP-Seq, RNA interference, and yeast two hybrid experiments.

  18. Systematic evaluation of the impact of ChIP-seq read designs on genome coverage, peak identification, and allele-specific binding detection.

    Science.gov (United States)

    Zhang, Qi; Zeng, Xin; Younkin, Sam; Kawli, Trupti; Snyder, Michael P; Keleş, Sündüz

    2016-02-24

    Chromatin immunoprecipitation followed by sequencing (ChIP-seq) experiments revolutionized genome-wide profiling of transcription factors and histone modifications. Although maturing sequencing technologies allow these experiments to be carried out with short (36-50 bps), long (75-100 bps), single-end, or paired-end reads, the impact of these read parameters on the downstream data analysis are not well understood. In this paper, we evaluate the effects of different read parameters on genome sequence alignment, coverage of different classes of genomic features, peak identification, and allele-specific binding detection. We generated 101 bps paired-end ChIP-seq data for many transcription factors from human GM12878 and MCF7 cell lines. Systematic evaluations using in silico variations of these data as well as fully simulated data, revealed complex interplay between the sequencing parameters and analysis tools, and indicated clear advantages of paired-end designs in several aspects such as alignment accuracy, peak resolution, and most notably, allele-specific binding detection. Our work elucidates the effect of design on the downstream analysis and provides insights to investigators in deciding sequencing parameters in ChIP-seq experiments. We present the first systematic evaluation of the impact of ChIP-seq designs on allele-specific binding detection and highlights the power of pair-end designs in such studies.

  19. Cell-type specificity of ChIP-predicted transcription factor binding sites

    Directory of Open Access Journals (Sweden)

    Håndstad Tony

    2012-08-01

    Full Text Available Abstract Background Context-dependent transcription factor (TF binding is one reason for differences in gene expression patterns between different cellular states. Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq identifies genome-wide TF binding sites for one particular context—the cells used in the experiment. But can such ChIP-seq data predict TF binding in other cellular contexts and is it possible to distinguish context-dependent from ubiquitous TF binding? Results We compared ChIP-seq data on TF binding for multiple TFs in two different cell types and found that on average only a third of ChIP-seq peak regions are common to both cell types. Expectedly, common peaks occur more frequently in certain genomic contexts, such as CpG-rich promoters, whereas chromatin differences characterize cell-type specific TF binding. We also find, however, that genotype differences between the cell types can explain differences in binding. Moreover, ChIP-seq signal intensity and peak clustering are the strongest predictors of common peaks. Compared with strong peaks located in regions containing peaks for multiple transcription factors, weak and isolated peaks are less common between the cell types and are less associated with data that indicate regulatory activity. Conclusions Together, the results suggest that experimental noise is prevalent among weak peaks, whereas strong and clustered peaks represent high-confidence binding events that often occur in other cellular contexts. Nevertheless, 30-40% of the strongest and most clustered peaks show context-dependent regulation. We show that by combining signal intensity with additional data—ranging from context independent information such as binding site conservation and position weight matrix scores to context dependent chromatin structure—we can predict whether a ChIP-seq peak is likely to be present in other cellular contexts.

  20. An efficient method to transcription factor binding sites imputation via simultaneous completion of multiple matrices with positional consistency.

    Science.gov (United States)

    Guo, Wei-Li; Huang, De-Shuang

    2017-08-22

    Transcription factors (TFs) are DNA-binding proteins that have a central role in regulating gene expression. Identification of DNA-binding sites of TFs is a key task in understanding transcriptional regulation, cellular processes and disease. Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) enables genome-wide identification of in vivo TF binding sites. However, it is still difficult to map every TF in every cell line owing to cost and biological material availability, which poses an enormous obstacle for integrated analysis of gene regulation. To address this problem, we propose a novel computational approach, TFBSImpute, for predicting additional TF binding profiles by leveraging information from available ChIP-seq TF binding data. TFBSImpute fuses the dataset to a 3-mode tensor and imputes missing TF binding signals via simultaneous completion of multiple TF binding matrices with positional consistency. We show that signals predicted by our method achieve overall similarity with experimental data and that TFBSImpute significantly outperforms baseline approaches, by assessing the performance of imputation methods against observed ChIP-seq TF binding profiles. Besides, motif analysis shows that TFBSImpute preforms better in capturing binding motifs enriched in observed data compared with baselines, indicating that the higher performance of TFBSImpute is not simply due to averaging related samples. We anticipate that our approach will constitute a useful complement to experimental mapping of TF binding, which is beneficial for further study of regulation mechanisms and disease.

  1. Integrative ChIP-seq/microarray analysis identifies a CTNNB1 target signature enriched in intestinal stem cells and colon cancer.

    Directory of Open Access Journals (Sweden)

    Kazuhide Watanabe

    Full Text Available Deregulation of canonical Wnt/CTNNB1 (beta-catenin pathway is one of the earliest events in the pathogenesis of colon cancer. Mutations in APC or CTNNB1 are highly frequent in colon cancer and cause aberrant stabilization of CTNNB1, which activates the transcription of Wnt target genes by binding to chromatin via the TCF/LEF transcription factors. Here we report an integrative analysis of genome-wide chromatin occupancy of CTNNB1 by chromatin immunoprecipitation coupled with high-throughput sequencing (ChIP-seq and gene expression profiling by microarray analysis upon RNAi-mediated knockdown of CTNNB1 in colon cancer cells.We observed 3629 CTNNB1 binding peaks across the genome and a significant correlation between CTNNB1 binding and knockdown-induced gene expression change. Our integrative analysis led to the discovery of a direct Wnt target signature composed of 162 genes. Gene ontology analysis of this signature revealed a significant enrichment of Wnt pathway genes, suggesting multiple feedback regulations of the pathway. We provide evidence that this gene signature partially overlaps with the Lgr5+ intestinal stem cell signature, and is significantly enriched in normal intestinal stem cells as well as in clinical colorectal cancer samples. Interestingly, while the expression of the CTNNB1 target gene set does not correlate with survival, elevated expression of negative feedback regulators within the signature predicts better prognosis.Our data provide a genome-wide view of chromatin occupancy and gene regulation of Wnt/CTNNB1 signaling in colon cancer cells.

  2. Network-Based Isoform Quantification with RNA-Seq Data for Cancer Transcriptome Analysis.

    Directory of Open Access Journals (Sweden)

    Wei Zhang

    2015-12-01

    Full Text Available High-throughput mRNA sequencing (RNA-Seq is widely used for transcript quantification of gene isoforms. Since RNA-Seq data alone is often not sufficient to accurately identify the read origins from the isoforms for quantification, we propose to explore protein domain-domain interactions as prior knowledge for integrative analysis with RNA-Seq data. We introduce a Network-based method for RNA-Seq-based Transcript Quantification (Net-RSTQ to integrate protein domain-domain interaction network with short read alignments for transcript abundance estimation. Based on our observation that the abundances of the neighboring isoforms by domain-domain interactions in the network are positively correlated, Net-RSTQ models the expression of the neighboring transcripts as Dirichlet priors on the likelihood of the observed read alignments against the transcripts in one gene. The transcript abundances of all the genes are then jointly estimated with alternating optimization of multiple EM problems. In simulation Net-RSTQ effectively improved isoform transcript quantifications when isoform co-expressions correlate with their interactions. qRT-PCR results on 25 multi-isoform genes in a stem cell line, an ovarian cancer cell line, and a breast cancer cell line also showed that Net-RSTQ estimated more consistent isoform proportions with RNA-Seq data. In the experiments on the RNA-Seq data in The Cancer Genome Atlas (TCGA, the transcript abundances estimated by Net-RSTQ are more informative for patient sample classification of ovarian cancer, breast cancer and lung cancer. All experimental results collectively support that Net-RSTQ is a promising approach for isoform quantification. Net-RSTQ toolbox is available at http://compbio.cs.umn.edu/Net-RSTQ/.

  3. Gene expression profiling of human breast tissue samples using SAGE-Seq.

    Science.gov (United States)

    Wu, Zhenhua Jeremy; Meyer, Clifford A; Choudhury, Sibgat; Shipitsin, Michail; Maruyama, Reo; Bessarabova, Marina; Nikolskaya, Tatiana; Sukumar, Saraswati; Schwartzman, Armin; Liu, Jun S; Polyak, Kornelia; Liu, X Shirley

    2010-12-01

    We present a powerful application of ultra high-throughput sequencing, SAGE-Seq, for the accurate quantification of normal and neoplastic mammary epithelial cell transcriptomes. We develop data analysis pipelines that allow the mapping of sense and antisense strands of mitochondrial and RefSeq genes, the normalization between libraries, and the identification of differentially expressed genes. We find that the diversity of cancer transcriptomes is significantly higher than that of normal cells. Our analysis indicates that transcript discovery plateaus at 10 million reads/sample, and suggests a minimum desired sequencing depth around five million reads. Comparison of SAGE-Seq and traditional SAGE on normal and cancerous breast tissues reveals higher sensitivity of SAGE-Seq to detect less-abundant genes, including those encoding for known breast cancer-related transcription factors and G protein-coupled receptors (GPCRs). SAGE-Seq is able to identify genes and pathways abnormally activated in breast cancer that traditional SAGE failed to call. SAGE-Seq is a powerful method for the identification of biomarkers and therapeutic targets in human disease.

  4. Cyber-T web server: differential analysis of high-throughput data.

    Science.gov (United States)

    Kayala, Matthew A; Baldi, Pierre

    2012-07-01

    The Bayesian regularization method for high-throughput differential analysis, described in Baldi and Long (A Bayesian framework for the analysis of microarray expression data: regularized t-test and statistical inferences of gene changes. Bioinformatics 2001: 17: 509-519) and implemented in the Cyber-T web server, is one of the most widely validated. Cyber-T implements a t-test using a Bayesian framework to compute a regularized variance of the measurements associated with each probe under each condition. This regularized estimate is derived by flexibly combining the empirical measurements with a prior, or background, derived from pooling measurements associated with probes in the same neighborhood. This approach flexibly addresses problems associated with low replication levels and technology biases, not only for DNA microarrays, but also for other technologies, such as protein arrays, quantitative mass spectrometry and next-generation sequencing (RNA-seq). Here we present an update to the Cyber-T web server, incorporating several useful new additions and improvements. Several preprocessing data normalization options including logarithmic and (Variance Stabilizing Normalization) VSN transforms are included. To augment two-sample t-tests, a one-way analysis of variance is implemented. Several methods for multiple tests correction, including standard frequentist methods and a probabilistic mixture model treatment, are available. Diagnostic plots allow visual assessment of the results. The web server provides comprehensive documentation and example data sets. The Cyber-T web server, with R source code and data sets, is publicly available at http://cybert.ics.uci.edu/.

  5. Computational Methods for ChIP-seq Data Analysis and Applications

    KAUST Repository

    Ashoor, Haitham

    2017-04-25

    integrates several experimental data including ChIP-seq data for TF binding sites. Finally, I present an extensive computational comparison of different ab-initio motif identification methods based on TF ChIP-seq data. The comparison included 10 different methods over 159 different TF datasets. Recommendations of this comparison indicate that the usage of simple methods outperforms the usage of high order models.

  6. High-throughput molecular binding analysis on open-microfluidic platform

    OpenAIRE

    Pan, Yuchen

    2016-01-01

    Biomolecular binding interactions underpin life sciences tools that are essential to fields as diverse as molecular biology and clinical chemistry. Merging needs in life science research entail fast, robust and quantitative binding reaction characterization, such as antibody selection, gene regulation screening and drug screening. Identification, characterization, and optimization of these diverse molecular binding reactions demands the availability of powerful, quantitative analytical tools....

  7. High-Throughput Testing of Antibody-Dependent Binding Inhibition of Placental Malaria Parasites

    DEFF Research Database (Denmark)

    Nielsen, Morten A; Salanti, Ali

    2015-01-01

    The particular virulence of Plasmodium falciparum manifests in diverse severe malaria syndromes as cerebral malaria, severe anemia and placental malaria. The cause of both the severity and the diversity of infection outcome, is the ability of the infected erythrocyte (IE) to bind a range......-throughput assay used in the preclinical and clinical development of a VAR2CSA based vaccine against placental malaria....

  8. rSeqNP: a non-parametric approach for detecting differential expression and splicing from RNA-Seq data.

    Science.gov (United States)

    Shi, Yang; Chinnaiyan, Arul M; Jiang, Hui

    2015-07-01

    High-throughput sequencing of transcriptomes (RNA-Seq) has become a powerful tool to study gene expression. Here we present an R package, rSeqNP, which implements a non-parametric approach to test for differential expression and splicing from RNA-Seq data. rSeqNP uses permutation tests to access statistical significance and can be applied to a variety of experimental designs. By combining information across isoforms, rSeqNP is able to detect more differentially expressed or spliced genes from RNA-Seq data. The R package with its source code and documentation are freely available at http://www-personal.umich.edu/∼jianghui/rseqnp/. jianghui@umich.edu Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  9. High-sensitivity HLA typing by Saturated Tiling Capture Sequencing (STC-Seq).

    Science.gov (United States)

    Jiao, Yang; Li, Ran; Wu, Chao; Ding, Yibin; Liu, Yanning; Jia, Danmei; Wang, Lifeng; Xu, Xiang; Zhu, Jing; Zheng, Min; Jia, Junling

    2018-01-15

    Highly polymorphic human leukocyte antigen (HLA) genes are responsible for fine-tuning the adaptive immune system. High-resolution HLA typing is important for the treatment of autoimmune and infectious diseases. Additionally, it is routinely performed for identifying matched donors in transplantation medicine. Although many HLA typing approaches have been developed, the complexity, low-efficiency and high-cost of current HLA-typing assays limit their application in population-based high-throughput HLA typing for donors, which is required for creating large-scale databases for transplantation and precision medicine. Here, we present a cost-efficient Saturated Tiling Capture Sequencing (STC-Seq) approach to capturing 14 HLA class I and II genes. The highly efficient capture (an approximately 23,000-fold enrichment) of these genes allows for simplified allele calling. Tests on five genes (HLA-A/B/C/DRB1/DQB1) from 31 human samples and 351 datasets using STC-Seq showed results that were 98% consistent with the known two sets of digitals (field1 and field2) genotypes. Additionally, STC can capture genomic DNA fragments longer than 3 kb from HLA loci, making the library compatible with the third-generation sequencing. STC-Seq is a highly accurate and cost-efficient method for HLA typing which can be used to facilitate the establishment of population-based HLA databases for the precision and transplantation medicine.

  10. The integrated analysis of RNA-seq and microRNA-seq depicts miRNA-mRNA networks involved in Japanese flounder (Paralichthys olivaceus) albinism.

    Science.gov (United States)

    Wang, Na; Wang, Ruoqing; Wang, Renkai; Tian, Yongsheng; Shao, Changwei; Jia, Xiaodong; Chen, Songlin

    2017-01-01

    Albinism, a phenomenon characterized by pigmentation deficiency on the ocular side of Japanese flounder (Paralichthys olivaceus), has caused significant damage. Limited mRNA and microRNA (miRNA) information is available on fish pigmentation deficiency. In this study, a high-throughput sequencing strategy was employed to identify the mRNA and miRNAs involved in P. olivaceus albinism. Based on P. olivaceus genome, RNA-seq identified 21,787 know genes and 711 new genes by transcripts assembly. Of those, 235 genes exhibited significantly different expression pattern (fold change ≥2 or ≤0.5 and q-value≤0.05), including 194 down-regulated genes and 41 up-regulated genes in albino versus normally pigmented individuals. These genes were enriched to 81 GO terms and 9 KEGG pathways (p≤0.05). Among those, the pigmentation related pathways-Melanogenesis and tyrosine metabolism were contained. High-throughput miRNA sequencing identified a total of 475 miRNAs, including 64 novel miRNAs. Furthermore, 33 differentially expressed miRNAs containing 13 up-regulated and 20 down-regulated miRNAs were identified in albino versus normally pigmented individuals (fold change ≥1.5 or ≤0.67 and p≤0.05). The next target prediction discovered a variety of putative target genes, of which, 134 genes including Tyrosinase (TYR), Tyrosinase-related protein 1 (TYRP1), Microphthalmia-associated transcription factor (MITF) were overlapped with differentially expressed genes derived from RNA-seq. These target genes were significantly enriched to 254 GO terms and 103 KEGG pathways (p<0.001). Of those, tyrosine metabolism, lysosomes, phototransduction pathways, etc., attracted considerable attention due to their involvement in regulating skin pigmentation. Expression patterns of differentially expressed mRNA and miRNAs were validated in 10 mRNA and 10 miRNAs by qRT-PCR. With high-throughput mRNA and miRNA sequencing and analysis, a series of interested mRNA and miRNAs involved in fish

  11. Pipeline for the Analysis of ChIP-seq Data and New Motif Ranking Procedure

    KAUST Repository

    Ashoor, Haitham

    2011-06-01

    This thesis presents a computational methodology for ab-initio identification of transcription factor binding sites based on ChIP-seq data. This method consists of three main steps, namely ChIP-seq data processing, motif discovery and models selection. A novel method for ranking the models of motifs identified in this process is proposed. This method combines multiple factors in order to rank the provided candidate motifs. It combines the model coverage of the ChIP-seq fragments that contain motifs from which that model is built, the suitable background data made up of shuffled ChIP-seq fragments, and the p-value that resulted from evaluating the model on actual and background data. Two ChIP-seq datasets retrieved from ENCODE project are used to evaluate and demonstrate the ability of the method to predict correct TFBSs with high precision. The first dataset relates to neuron-restrictive silencer factor, NRSF, while the second one corresponds to growth-associated binding protein, GABP. The pipeline system shows high precision prediction for both datasets, as in both cases the top ranked motif closely resembles the known motifs for the respective transcription factors.

  12. ReMap 2018: an updated atlas of regulatory regions from an integrative analysis of DNA-binding ChIP-seq experiments.

    Science.gov (United States)

    Chèneby, Jeanne; Gheorghe, Marius; Artufel, Marie; Mathelier, Anthony; Ballester, Benoit

    2018-01-04

    With this latest release of ReMap (http://remap.cisreg.eu), we present a unique collection of regulatory regions in human, as a result of a large-scale integrative analysis of ChIP-seq experiments for hundreds of transcriptional regulators (TRs) such as transcription factors, transcriptional co-activators and chromatin regulators. In 2015, we introduced the ReMap database to capture the genome regulatory space by integrating public ChIP-seq datasets, covering 237 TRs across 13 million (M) peaks. In this release, we have extended this catalog to constitute a unique collection of regulatory regions. Specifically, we have collected, analyzed and retained after quality control a total of 2829 ChIP-seq datasets available from public sources, covering a total of 485 TRs with a catalog of 80M peaks. Additionally, the updated database includes new search features for TR names as well as aliases, including cell line names and the ability to navigate the data directly within genome browsers via public track hubs. Finally, full access to this catalog is available online together with a TR binding enrichment analysis tool. ReMap 2018 provides a significant update of the ReMap database, providing an in depth view of the complexity of the regulatory landscape in human. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  13. PRAPI: post-transcriptional regulation analysis pipeline for Iso-Seq.

    Science.gov (United States)

    Gao, Yubang; Wang, Huiyuan; Zhang, Hangxiao; Wang, Yongsheng; Chen, Jinfeng; Gu, Lianfeng

    2018-05-01

    The single-molecule real-time (SMRT) isoform sequencing (Iso-Seq) based on Pacific Bioscience (PacBio) platform has received increasing attention for its ability to explore full-length isoforms. Thus, comprehensive tools for Iso-Seq bioinformatics analysis are extremely useful. Here, we present a one-stop solution for Iso-Seq analysis, called PRAPI to analyze alternative transcription initiation (ATI), alternative splicing (AS), alternative cleavage and polyadenylation (APA), natural antisense transcripts (NAT), and circular RNAs (circRNAs) comprehensively. PRAPI is capable of combining Iso-Seq full-length isoforms with short read data, such as RNA-Seq or polyadenylation site sequencing (PAS-seq) for differential expression analysis of NAT, AS, APA and circRNAs. Furthermore, PRAPI can annotate new genes and correct mis-annotated genes when gene annotation is available. Finally, PRAPI generates high-quality vector graphics to visualize and highlight the Iso-Seq results. The Dockerfile of PRAPI is available at http://www.bioinfor.org/tool/PRAPI. lfgu@fafu.edu.cn.

  14. High-throughput gender identification of penguin species using melting curve analysis.

    Science.gov (United States)

    Tseng, Chao-Neng; Chang, Yung-Ting; Chiu, Hui-Tzu; Chou, Yii-Cheng; Huang, Hurng-Wern; Cheng, Chien-Chung; Liao, Ming-Hui; Chang, Hsueh-Wei

    2014-04-03

    Most species of penguins are sexual monomorphic and therefore it is difficult to visually identify their genders for monitoring population stability in terms of sex ratio analysis. In this study, we evaluated the suitability using melting curve analysis (MCA) for high-throughput gender identification of penguins. Preliminary test indicated that the Griffiths's P2/P8 primers were not suitable for MCA analysis. Based on sequence alignment of Chromo-Helicase-DNA binding protein (CHD)-W and CHD-Z genes from four species of penguins (Pygoscelis papua, Aptenodytes patagonicus, Spheniscus magellanicus, and Eudyptes chrysocome), we redesigned forward primers for the CHD-W/CHD-Z-common region (PGU-ZW2) and the CHD-W-specific region (PGU-W2) to be used in combination with the reverse Griffiths's P2 primer. When tested with P. papua samples, PCR using P2/PGU-ZW2 and P2/PGU-W2 primer sets generated two amplicons of 148- and 356-bp, respectively, which were easily resolved in 1.5% agarose gels. MCA analysis indicated the melting temperature (Tm) values for P2/PGU-ZW2 and P2/PGU-W2 amplicons of P. papua samples were 79.75°C-80.5°C and 81.0°C-81.5°C, respectively. Females displayed both ZW-common and W-specific Tm peaks, whereas male was positive only for ZW-common peak. Taken together, our redesigned primers coupled with MCA analysis allows precise high throughput gender identification for P. papua, and potentially for other penguin species such as A. patagonicus, S. magellanicus, and E. chrysocome as well.

  15. HOCOMOCO: towards a complete collection of transcription factor binding models for human and mouse via large-scale ChIP-Seq analysis

    KAUST Repository

    Kulakovskiy, Ivan V.; Vorontsov, Ilya E.; Yevshin, Ivan S.; Sharipov, Ruslan N.; Fedorova, Alla D.; Rumynskiy, Eugene I.; Medvedeva, Yulia A.; Magana-Mora, Arturo; Bajic, Vladimir B.; Papatsenko, Dmitry A.; Kolpakov, Fedor A.; Makeev, Vsevolod J.

    2017-01-01

    We present a major update of the HOCOMOCO collection that consists of patterns describing DNA binding specificities for human and mouse transcription factors. In this release, we profited from a nearly doubled volume of published in vivo experiments on transcription factor (TF) binding to expand the repertoire of binding models, replace low-quality models previously based on in vitro data only and cover more than a hundred TFs with previously unknown binding specificities. This was achieved by systematic motif discovery from more than five thousand ChIP-Seq experiments uniformly processed within the BioUML framework with several ChIP-Seq peak calling tools and aggregated in the GTRD database. HOCOMOCO v11 contains binding models for 453 mouse and 680 human transcription factors and includes 1302 mononucleotide and 576 dinucleotide position weight matrices, which describe primary binding preferences of each transcription factor and reliable alternative binding specificities. An interactive interface and bulk downloads are available on the web: http://hocomoco.autosome.ru and http://www.cbrc.kaust.edu.sa/hocomoco11. In this release, we complement HOCOMOCO by MoLoTool (Motif Location Toolbox, http://molotool.autosome.ru) that applies HOCOMOCO models for visualization of binding sites in short DNA sequences.

  16. HOCOMOCO: towards a complete collection of transcription factor binding models for human and mouse via large-scale ChIP-Seq analysis

    KAUST Repository

    Kulakovskiy, Ivan V.

    2017-10-31

    We present a major update of the HOCOMOCO collection that consists of patterns describing DNA binding specificities for human and mouse transcription factors. In this release, we profited from a nearly doubled volume of published in vivo experiments on transcription factor (TF) binding to expand the repertoire of binding models, replace low-quality models previously based on in vitro data only and cover more than a hundred TFs with previously unknown binding specificities. This was achieved by systematic motif discovery from more than five thousand ChIP-Seq experiments uniformly processed within the BioUML framework with several ChIP-Seq peak calling tools and aggregated in the GTRD database. HOCOMOCO v11 contains binding models for 453 mouse and 680 human transcription factors and includes 1302 mononucleotide and 576 dinucleotide position weight matrices, which describe primary binding preferences of each transcription factor and reliable alternative binding specificities. An interactive interface and bulk downloads are available on the web: http://hocomoco.autosome.ru and http://www.cbrc.kaust.edu.sa/hocomoco11. In this release, we complement HOCOMOCO by MoLoTool (Motif Location Toolbox, http://molotool.autosome.ru) that applies HOCOMOCO models for visualization of binding sites in short DNA sequences.

  17. A comparative study of techniques for differential expression analysis on RNA-Seq data.

    Directory of Open Access Journals (Sweden)

    Zong Hong Zhang

    Full Text Available Recent advances in next-generation sequencing technology allow high-throughput cDNA sequencing (RNA-Seq to be widely applied in transcriptomic studies, in particular for detecting differentially expressed genes between groups. Many software packages have been developed for the identification of differentially expressed genes (DEGs between treatment groups based on RNA-Seq data. However, there is a lack of consensus on how to approach an optimal study design and choice of suitable software for the analysis. In this comparative study we evaluate the performance of three of the most frequently used software tools: Cufflinks-Cuffdiff2, DESeq and edgeR. A number of important parameters of RNA-Seq technology were taken into consideration, including the number of replicates, sequencing depth, and balanced vs. unbalanced sequencing depth within and between groups. We benchmarked results relative to sets of DEGs identified through either quantitative RT-PCR or microarray. We observed that edgeR performs slightly better than DESeq and Cuffdiff2 in terms of the ability to uncover true positives. Overall, DESeq or taking the intersection of DEGs from two or more tools is recommended if the number of false positives is a major concern in the study. In other circumstances, edgeR is slightly preferable for differential expression analysis at the expense of potentially introducing more false positives.

  18. Whole transcriptome expression analysis and comparison of two different strains of Plasmodium falciparum using RNA-Seq

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    Hiasindh Ashmi Antony

    2016-06-01

    Full Text Available The emergence and distribution of drug resistance in malaria are serious public health concerns in tropical and subtropical regions of the world. However, the molecular mechanism of drug resistance remains unclear. In the present study, we performed a high-throughput RNA-Seq to identify and characterize the differentially expressed genes between the chloroquine (CQ sensitive (3D7 and resistant (Dd2 strains of Plasmodium falciparum. The parasite cells were cultured in the presence and absence of CQ by in vitro method. Total RNA was isolated from the harvested parasite cells using TRIzol, and RNA-Seq was conducted using an Illumina HiSeq 2500 sequencing platform with paired-end reads and annotated using Tophat. The transcriptome analysis of P. falciparum revealed the expression of ~5000 genes, in which ~60% of the genes have unknown function. Cuffdiff program was used to identify the differentially expressed genes between the CQ-sensitive and resistant strains. Here, we furnish a detailed description of the experimental design, procedure, and analysis of the transcriptome sequencing data, that have been deposited in the National Center for Biotechnology Information (accession nos. PRJNA308455 and GSE77499.

  19. High-specificity detection of rare alleles with Paired-End Low Error Sequencing (PELE-Seq).

    Science.gov (United States)

    Preston, Jessica L; Royall, Ariel E; Randel, Melissa A; Sikkink, Kristin L; Phillips, Patrick C; Johnson, Eric A

    2016-06-14

    Polymorphic loci exist throughout the genomes of a population and provide the raw genetic material needed for a species to adapt to changes in the environment. The minor allele frequencies of rare Single Nucleotide Polymorphisms (SNPs) within a population have been difficult to track with Next-Generation Sequencing (NGS), due to the high error rate of standard methods such as Illumina sequencing. We have developed a wet-lab protocol and variant-calling method that identifies both sequencing and PCR errors, called Paired-End Low Error Sequencing (PELE-Seq). To test the specificity and sensitivity of the PELE-Seq method, we sequenced control E. coli DNA libraries containing known rare alleles present at frequencies ranging from 0.2-0.4 % of the total reads. PELE-Seq had higher specificity and sensitivity than standard libraries. We then used PELE-Seq to characterize rare alleles in a Caenorhabditis remanei nematode worm population before and after laboratory adaptation, and found that minor and rare alleles can undergo large changes in frequency during lab-adaptation. We have developed a method of rare allele detection that mitigates both sequencing and PCR errors, called PELE-Seq. PELE-Seq was evaluated using control E. coli populations and was then used to compare a wild C. remanei population to a lab-adapted population. The PELE-Seq method is ideal for investigating the dynamics of rare alleles in a broad range of reduced-representation sequencing methods, including targeted amplicon sequencing, RAD-Seq, ddRAD, and GBS. PELE-Seq is also well-suited for whole genome sequencing of mitochondria and viruses, and for high-throughput rare mutation screens.

  20. XplorSeq: a software environment for integrated management and phylogenetic analysis of metagenomic sequence data.

    Science.gov (United States)

    Frank, Daniel N

    2008-10-07

    Advances in automated DNA sequencing technology have accelerated the generation of metagenomic DNA sequences, especially environmental ribosomal RNA gene (rDNA) sequences. As the scale of rDNA-based studies of microbial ecology has expanded, need has arisen for software that is capable of managing, annotating, and analyzing the plethora of diverse data accumulated in these projects. XplorSeq is a software package that facilitates the compilation, management and phylogenetic analysis of DNA sequences. XplorSeq was developed for, but is not limited to, high-throughput analysis of environmental rRNA gene sequences. XplorSeq integrates and extends several commonly used UNIX-based analysis tools by use of a Macintosh OS-X-based graphical user interface (GUI). Through this GUI, users may perform basic sequence import and assembly steps (base-calling, vector/primer trimming, contig assembly), perform BLAST (Basic Local Alignment and Search Tool; 123) searches of NCBI and local databases, create multiple sequence alignments, build phylogenetic trees, assemble Operational Taxonomic Units, estimate biodiversity indices, and summarize data in a variety of formats. Furthermore, sequences may be annotated with user-specified meta-data, which then can be used to sort data and organize analyses and reports. A document-based architecture permits parallel analysis of sequence data from multiple clones or amplicons, with sequences and other data stored in a single file. XplorSeq should benefit researchers who are engaged in analyses of environmental sequence data, especially those with little experience using bioinformatics software. Although XplorSeq was developed for management of rDNA sequence data, it can be applied to most any sequencing project. The application is available free of charge for non-commercial use at http://vent.colorado.edu/phyloware.

  1. A survey of motif finding Web tools for detecting binding site motifs in ChIP-Seq data.

    Science.gov (United States)

    Tran, Ngoc Tam L; Huang, Chun-Hsi

    2014-02-20

    ChIP-Seq (chromatin immunoprecipitation sequencing) has provided the advantage for finding motifs as ChIP-Seq experiments narrow down the motif finding to binding site locations. Recent motif finding tools facilitate the motif detection by providing user-friendly Web interface. In this work, we reviewed nine motif finding Web tools that are capable for detecting binding site motifs in ChIP-Seq data. We showed each motif finding Web tool has its own advantages for detecting motifs that other tools may not discover. We recommended the users to use multiple motif finding Web tools that implement different algorithms for obtaining significant motifs, overlapping resemble motifs, and non-overlapping motifs. Finally, we provided our suggestions for future development of motif finding Web tool that better assists researchers for finding motifs in ChIP-Seq data.

  2. Characterization of in vivo DNA-binding events of plant transcription factors by ChIP-seq

    NARCIS (Netherlands)

    Mourik, Van Hilda; Muiño, J.M.; Pajoro, Alice; Angenent, G.C.; Kaufmann, Kerstin

    2015-01-01

    Chromatin immunoprecipitation followed by next-generation sequencing (ChIP-seq) is a powerful technique for genome-wide identification of in vivo binding sites of DNA-binding proteins. The technique had been used to study many DNA-binding proteins in a broad variety of species. The basis of the

  3. Microfluidic PCR Amplification and MiSeq Amplicon Sequencing Techniques for High-Throughput Detection and Genotyping of Human Pathogenic RNA Viruses in Human Feces, Sewage, and Oysters

    Directory of Open Access Journals (Sweden)

    Mamoru Oshiki

    2018-04-01

    Full Text Available Detection and genotyping of pathogenic RNA viruses in human and environmental samples are useful for monitoring the circulation and prevalence of these pathogens, whereas a conventional PCR assay followed by Sanger sequencing is time-consuming and laborious. The present study aimed to develop a high-throughput detection-and-genotyping tool for 11 human RNA viruses [Aichi virus; astrovirus; enterovirus; norovirus genogroup I (GI, GII, and GIV; hepatitis A virus; hepatitis E virus; rotavirus; sapovirus; and human parechovirus] using a microfluidic device and next-generation sequencer. Microfluidic nested PCR was carried out on a 48.48 Access Array chip, and the amplicons were recovered and used for MiSeq sequencing (Illumina, Tokyo, Japan; genotyping was conducted by homology searching and phylogenetic analysis of the obtained sequence reads. The detection limit of the 11 tested viruses ranged from 100 to 103 copies/μL in cDNA sample, corresponding to 101–104 copies/mL-sewage, 105–108 copies/g-human feces, and 102–105 copies/g-digestive tissues of oyster. The developed assay was successfully applied for simultaneous detection and genotyping of RNA viruses to samples of human feces, sewage, and artificially contaminated oysters. Microfluidic nested PCR followed by MiSeq sequencing enables efficient tracking of the fate of multiple RNA viruses in various environments, which is essential for a better understanding of the circulation of human pathogenic RNA viruses in the human population.

  4. CEL-Seq: Single-Cell RNA-Seq by Multiplexed Linear Amplification

    Directory of Open Access Journals (Sweden)

    Tamar Hashimshony

    2012-09-01

    Full Text Available High-throughput sequencing has allowed for unprecedented detail in gene expression analyses, yet its efficient application to single cells is challenged by the small starting amounts of RNA. We have developed CEL-Seq, a method for overcoming this limitation by barcoding and pooling samples before linearly amplifying mRNA with the use of one round of in vitro transcription. We show that CEL-Seq gives more reproducible, linear, and sensitive results than a PCR-based amplification method. We demonstrate the power of this method by studying early C. elegans embryonic development at single-cell resolution. Differential distribution of transcripts between sister cells is seen as early as the two-cell stage embryo, and zygotic expression in the somatic cell lineages is enriched for transcription factors. The robust transcriptome quantifications enabled by CEL-Seq will be useful for transcriptomic analyses of complex tissues containing populations of diverse cell types.

  5. Illumina MiSeq Sequencing for Preliminary Analysis of Microbiome Causing Primary Endodontic Infections in Egypt

    Directory of Open Access Journals (Sweden)

    Sally Ali Tawfik

    2018-01-01

    Full Text Available The use of high throughput next generation technologies has allowed more comprehensive analysis than traditional Sanger sequencing. The specific aim of this study was to investigate the microbial diversity of primary endodontic infections using Illumina MiSeq sequencing platform in Egyptian patients. Samples were collected from 19 patients in Suez Canal University Hospital (Endodontic Department using sterile # 15K file and paper points. DNA was extracted using Mo Bio power soil DNA isolation extraction kit followed by PCR amplification and agarose gel electrophoresis. The microbiome was characterized on the basis of the V3 and V4 hypervariable region of the 16S rRNA gene by using paired-end sequencing on Illumina MiSeq device. MOTHUR software was used in sequence filtration and analysis of sequenced data. A total of 1858 operational taxonomic units at 97% similarity were assigned to 26 phyla, 245 families, and 705 genera. Four main phyla Firmicutes, Bacteroidetes, Proteobacteria, and Synergistetes were predominant in all samples. At genus level, Prevotella, Bacillus, Porphyromonas, Streptococcus, and Bacteroides were the most abundant. Illumina MiSeq platform sequencing can be used to investigate oral microbiome composition of endodontic infections. Elucidating the ecology of endodontic infections is a necessary step in developing effective intracanal antimicrobials.

  6. Male-biased genes in catfish as revealed by RNA-Seq analysis of the testis transcriptome.

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    Fanyue Sun

    Full Text Available BACKGROUND: Catfish has a male-heterogametic (XY sex determination system, but genes involved in gonadogenesis, spermatogenesis, testicular determination, and sex determination are poorly understood. As a first step of understanding the transcriptome of the testis, here, we conducted RNA-Seq analysis using high throughput Illumina sequencing. METHODOLOGY/PRINCIPAL FINDINGS: A total of 269.6 million high quality reads were assembled into 193,462 contigs with a N50 length of 806 bp. Of these contigs, 67,923 contigs had hits to a set of 25,307 unigenes, including 167 unique genes that had not been previously identified in catfish. A meta-analysis of expressed genes in the testis and in the gynogen (double haploid female allowed the identification of 5,450 genes that are preferentially expressed in the testis, providing a pool of putative male-biased genes. Gene ontology and annotation analysis suggested that many of these male-biased genes were involved in gonadogenesis, spermatogenesis, testicular determination, gametogenesis, gonad differentiation, and possibly sex determination. CONCLUSION/SIGNIFICANCE: We provide the first transcriptome-level analysis of the catfish testis. Our analysis would lay the basis for sequential follow-up studies of genes involved in sex determination and differentiation in catfish.

  7. beachmat: A Bioconductor C++ API for accessing high-throughput biological data from a variety of R matrix types.

    Directory of Open Access Journals (Sweden)

    Aaron T L Lun

    2018-05-01

    Full Text Available Biological experiments involving genomics or other high-throughput assays typically yield a data matrix that can be explored and analyzed using the R programming language with packages from the Bioconductor project. Improvements in the throughput of these assays have resulted in an explosion of data even from routine experiments, which poses a challenge to the existing computational infrastructure for statistical data analysis. For example, single-cell RNA sequencing (scRNA-seq experiments frequently generate large matrices containing expression values for each gene in each cell, requiring sparse or file-backed representations for memory-efficient manipulation in R. These alternative representations are not easily compatible with high-performance C++ code used for computationally intensive tasks in existing R/Bioconductor packages. Here, we describe a C++ interface named beachmat, which enables agnostic data access from various matrix representations. This allows package developers to write efficient C++ code that is interoperable with dense, sparse and file-backed matrices, amongst others. We evaluated the performance of beachmat for accessing data from each matrix representation using both simulated and real scRNA-seq data, and defined a clear memory/speed trade-off to motivate the choice of an appropriate representation. We also demonstrate how beachmat can be incorporated into the code of other packages to drive analyses of a very large scRNA-seq data set.

  8. beachmat: A Bioconductor C++ API for accessing high-throughput biological data from a variety of R matrix types.

    Science.gov (United States)

    Lun, Aaron T L; Pagès, Hervé; Smith, Mike L

    2018-05-01

    Biological experiments involving genomics or other high-throughput assays typically yield a data matrix that can be explored and analyzed using the R programming language with packages from the Bioconductor project. Improvements in the throughput of these assays have resulted in an explosion of data even from routine experiments, which poses a challenge to the existing computational infrastructure for statistical data analysis. For example, single-cell RNA sequencing (scRNA-seq) experiments frequently generate large matrices containing expression values for each gene in each cell, requiring sparse or file-backed representations for memory-efficient manipulation in R. These alternative representations are not easily compatible with high-performance C++ code used for computationally intensive tasks in existing R/Bioconductor packages. Here, we describe a C++ interface named beachmat, which enables agnostic data access from various matrix representations. This allows package developers to write efficient C++ code that is interoperable with dense, sparse and file-backed matrices, amongst others. We evaluated the performance of beachmat for accessing data from each matrix representation using both simulated and real scRNA-seq data, and defined a clear memory/speed trade-off to motivate the choice of an appropriate representation. We also demonstrate how beachmat can be incorporated into the code of other packages to drive analyses of a very large scRNA-seq data set.

  9. beachmat: A Bioconductor C++ API for accessing high-throughput biological data from a variety of R matrix types

    Science.gov (United States)

    Pagès, Hervé

    2018-01-01

    Biological experiments involving genomics or other high-throughput assays typically yield a data matrix that can be explored and analyzed using the R programming language with packages from the Bioconductor project. Improvements in the throughput of these assays have resulted in an explosion of data even from routine experiments, which poses a challenge to the existing computational infrastructure for statistical data analysis. For example, single-cell RNA sequencing (scRNA-seq) experiments frequently generate large matrices containing expression values for each gene in each cell, requiring sparse or file-backed representations for memory-efficient manipulation in R. These alternative representations are not easily compatible with high-performance C++ code used for computationally intensive tasks in existing R/Bioconductor packages. Here, we describe a C++ interface named beachmat, which enables agnostic data access from various matrix representations. This allows package developers to write efficient C++ code that is interoperable with dense, sparse and file-backed matrices, amongst others. We evaluated the performance of beachmat for accessing data from each matrix representation using both simulated and real scRNA-seq data, and defined a clear memory/speed trade-off to motivate the choice of an appropriate representation. We also demonstrate how beachmat can be incorporated into the code of other packages to drive analyses of a very large scRNA-seq data set. PMID:29723188

  10. Integration of ATAC-seq and RNA-seq identifies human alpha cell and beta cell signature genes.

    Science.gov (United States)

    Ackermann, Amanda M; Wang, Zhiping; Schug, Jonathan; Naji, Ali; Kaestner, Klaus H

    2016-03-01

    Although glucagon-secreting α-cells and insulin-secreting β-cells have opposing functions in regulating plasma glucose levels, the two cell types share a common developmental origin and exhibit overlapping transcriptomes and epigenomes. Notably, destruction of β-cells can stimulate repopulation via transdifferentiation of α-cells, at least in mice, suggesting plasticity between these cell fates. Furthermore, dysfunction of both α- and β-cells contributes to the pathophysiology of type 1 and type 2 diabetes, and β-cell de-differentiation has been proposed to contribute to type 2 diabetes. Our objective was to delineate the molecular properties that maintain islet cell type specification yet allow for cellular plasticity. We hypothesized that correlating cell type-specific transcriptomes with an atlas of open chromatin will identify novel genes and transcriptional regulatory elements such as enhancers involved in α- and β-cell specification and plasticity. We sorted human α- and β-cells and performed the "Assay for Transposase-Accessible Chromatin with high throughput sequencing" (ATAC-seq) and mRNA-seq, followed by integrative analysis to identify cell type-selective gene regulatory regions. We identified numerous transcripts with either α-cell- or β-cell-selective expression and discovered the cell type-selective open chromatin regions that correlate with these gene activation patterns. We confirmed cell type-selective expression on the protein level for two of the top hits from our screen. The "group specific protein" (GC; or vitamin D binding protein) was restricted to α-cells, while CHODL (chondrolectin) immunoreactivity was only present in β-cells. Furthermore, α-cell- and β-cell-selective ATAC-seq peaks were identified to overlap with known binding sites for islet transcription factors, as well as with single nucleotide polymorphisms (SNPs) previously identified as risk loci for type 2 diabetes. We have determined the genetic landscape of

  11. Development of automatic image analysis methods for high-throughput and high-content screening

    NARCIS (Netherlands)

    Di, Zi

    2013-01-01

    This thesis focuses on the development of image analysis methods for ultra-high content analysis of high-throughput screens where cellular phenotype responses to various genetic or chemical perturbations that are under investigation. Our primary goal is to deliver efficient and robust image analysis

  12. PeakAnalyzer: Genome-wide annotation of chromatin binding and modification loci

    Directory of Open Access Journals (Sweden)

    Tammoja Kairi

    2010-08-01

    Full Text Available Abstract Background Functional genomic studies involving high-throughput sequencing and tiling array applications, such as ChIP-seq and ChIP-chip, generate large numbers of experimentally-derived signal peaks across the genome under study. In analyzing these loci to determine their potential regulatory functions, areas of signal enrichment must be considered relative to proximal genes and regulatory elements annotated throughout the target genome Regions of chromatin association by transcriptional regulators should be distinguished as individual binding sites in order to enhance downstream analyses, such as the identification of known and novel consensus motifs. Results PeakAnalyzer is a set of high-performance utilities for the automated processing of experimentally-derived peak regions and annotation of genomic loci. The programs can accurately subdivide multimodal regions of signal enrichment into distinct subpeaks corresponding to binding sites or chromatin modifications, retrieve genomic sequences encompassing the computed subpeak summits, and identify positional features of interest such as intersection with exon/intron gene components, proximity to up- or downstream transcriptional start sites and cis-regulatory elements. The software can be configured to run either as a pipeline component for high-throughput analyses, or as a cross-platform desktop application with an intuitive user interface. Conclusions PeakAnalyzer comprises a number of utilities essential for ChIP-seq and ChIP-chip data analysis. High-performance implementations are provided for Unix pipeline integration along with a GUI version for interactive use. Source code in C++ and Java is provided, as are native binaries for Linux, Mac OS X and Windows systems.

  13. Mapping RNA-seq Reads with STAR.

    Science.gov (United States)

    Dobin, Alexander; Gingeras, Thomas R

    2015-09-03

    Mapping of large sets of high-throughput sequencing reads to a reference genome is one of the foundational steps in RNA-seq data analysis. The STAR software package performs this task with high levels of accuracy and speed. In addition to detecting annotated and novel splice junctions, STAR is capable of discovering more complex RNA sequence arrangements, such as chimeric and circular RNA. STAR can align spliced sequences of any length with moderate error rates, providing scalability for emerging sequencing technologies. STAR generates output files that can be used for many downstream analyses such as transcript/gene expression quantification, differential gene expression, novel isoform reconstruction, and signal visualization. In this unit, we describe computational protocols that produce various output files, use different RNA-seq datatypes, and utilize different mapping strategies. STAR is open source software that can be run on Unix, Linux, or Mac OS X systems. Copyright © 2015 John Wiley & Sons, Inc.

  14. RNA CoMPASS: a dual approach for pathogen and host transcriptome analysis of RNA-seq datasets.

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    Guorong Xu

    Full Text Available High-throughput RNA sequencing (RNA-seq has become an instrumental assay for the analysis of multiple aspects of an organism's transcriptome. Further, the analysis of a biological specimen's associated microbiome can also be performed using RNA-seq data and this application is gaining interest in the scientific community. There are many existing bioinformatics tools designed for analysis and visualization of transcriptome data. Despite the availability of an array of next generation sequencing (NGS analysis tools, the analysis of RNA-seq data sets poses a challenge for many biomedical researchers who are not familiar with command-line tools. Here we present RNA CoMPASS, a comprehensive RNA-seq analysis pipeline for the simultaneous analysis of transcriptomes and metatranscriptomes from diverse biological specimens. RNA CoMPASS leverages existing tools and parallel computing technology to facilitate the analysis of even very large datasets. RNA CoMPASS has a web-based graphical user interface with intrinsic queuing to control a distributed computational pipeline. RNA CoMPASS was evaluated by analyzing RNA-seq data sets from 45 B-cell samples. Twenty-two of these samples were derived from lymphoblastoid cell lines (LCLs generated by the infection of naïve B-cells with the Epstein Barr virus (EBV, while another 23 samples were derived from Burkitt's lymphomas (BL, some of which arose in part through infection with EBV. Appropriately, RNA CoMPASS identified EBV in all LCLs and in a fraction of the BLs. Cluster analysis of the human transcriptome component of the RNA CoMPASS output clearly separated the BLs (which have a germinal center-like phenotype from the LCLs (which have a blast-like phenotype with evidence of activated MYC signaling and lower interferon and NF-kB signaling in the BLs. Together, this analysis illustrates the utility of RNA CoMPASS in the simultaneous analysis of transcriptome and metatranscriptome data. RNA CoMPASS is freely

  15. Empirical methods for controlling false positives and estimating confidence in ChIP-Seq peaks

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    Courdy Samir J

    2008-12-01

    Full Text Available Abstract Background High throughput signature sequencing holds many promises, one of which is the ready identification of in vivo transcription factor binding sites, histone modifications, changes in chromatin structure and patterns of DNA methylation across entire genomes. In these experiments, chromatin immunoprecipitation is used to enrich for particular DNA sequences of interest and signature sequencing is used to map the regions to the genome (ChIP-Seq. Elucidation of these sites of DNA-protein binding/modification are proving instrumental in reconstructing networks of gene regulation and chromatin remodelling that direct development, response to cellular perturbation, and neoplastic transformation. Results Here we present a package of algorithms and software that makes use of control input data to reduce false positives and estimate confidence in ChIP-Seq peaks. Several different methods were compared using two simulated spike-in datasets. Use of control input data and a normalized difference score were found to more than double the recovery of ChIP-Seq peaks at a 5% false discovery rate (FDR. Moreover, both a binomial p-value/q-value and an empirical FDR were found to predict the true FDR within 2–3 fold and are more reliable estimators of confidence than a global Poisson p-value. These methods were then used to reanalyze Johnson et al.'s neuron-restrictive silencer factor (NRSF ChIP-Seq data without relying on extensive qPCR validated NRSF sites and the presence of NRSF binding motifs for setting thresholds. Conclusion The methods developed and tested here show considerable promise for reducing false positives and estimating confidence in ChIP-Seq data without any prior knowledge of the chIP target. They are part of a larger open source package freely available from http://useq.sourceforge.net/.

  16. DIVERSITY in binding, regulation, and evolution revealed from high-throughput ChIP.

    Science.gov (United States)

    Mitra, Sneha; Biswas, Anushua; Narlikar, Leelavati

    2018-04-23

    Genome-wide in vivo protein-DNA interactions are routinely mapped using high-throughput chromatin immunoprecipitation (ChIP). ChIP-reported regions are typically investigated for enriched sequence-motifs, which are likely to model the DNA-binding specificity of the profiled protein and/or of co-occurring proteins. However, simple enrichment analyses can miss insights into the binding-activity of the protein. Note that ChIP reports regions making direct contact with the protein as well as those binding through intermediaries. For example, consider a ChIP experiment targeting protein X, which binds DNA at its cognate sites, but simultaneously interacts with four other proteins. Each of these proteins also binds to its own specific cognate sites along distant parts of the genome, a scenario consistent with the current view of transcriptional hubs and chromatin loops. Since ChIP will pull down all X-associated regions, the final reported data will be a union of five distinct sets of regions, each containing binding sites of one of the five proteins, respectively. Characterizing all five different motifs and the corresponding sets is important to interpret the ChIP experiment and ultimately, the role of X in regulation. We present diversity which attempts exactly this: it partitions the data so that each partition can be characterized with its own de novo motif. Diversity uses a Bayesian approach to identify the optimal number of motifs and the associated partitions, which together explain the entire dataset. This is in contrast to standard motif finders, which report motifs individually enriched in the data, but do not necessarily explain all reported regions. We show that the different motifs and associated regions identified by diversity give insights into the various complexes that may be forming along the chromatin, something that has so far not been attempted from ChIP data. Webserver at http://diversity.ncl.res.in/; standalone (Mac OS X/Linux) from https

  17. GC-Content Normalization for RNA-Seq Data

    Science.gov (United States)

    2011-01-01

    Background Transcriptome sequencing (RNA-Seq) has become the assay of choice for high-throughput studies of gene expression. However, as is the case with microarrays, major technology-related artifacts and biases affect the resulting expression measures. Normalization is therefore essential to ensure accurate inference of expression levels and subsequent analyses thereof. Results We focus on biases related to GC-content and demonstrate the existence of strong sample-specific GC-content effects on RNA-Seq read counts, which can substantially bias differential expression analysis. We propose three simple within-lane gene-level GC-content normalization approaches and assess their performance on two different RNA-Seq datasets, involving different species and experimental designs. Our methods are compared to state-of-the-art normalization procedures in terms of bias and mean squared error for expression fold-change estimation and in terms of Type I error and p-value distributions for tests of differential expression. The exploratory data analysis and normalization methods proposed in this article are implemented in the open-source Bioconductor R package EDASeq. Conclusions Our within-lane normalization procedures, followed by between-lane normalization, reduce GC-content bias and lead to more accurate estimates of expression fold-changes and tests of differential expression. Such results are crucial for the biological interpretation of RNA-Seq experiments, where downstream analyses can be sensitive to the supplied lists of genes. PMID:22177264

  18. Cox-nnet: An artificial neural network method for prognosis prediction of high-throughput omics data.

    Science.gov (United States)

    Ching, Travers; Zhu, Xun; Garmire, Lana X

    2018-04-01

    Artificial neural networks (ANN) are computing architectures with many interconnections of simple neural-inspired computing elements, and have been applied to biomedical fields such as imaging analysis and diagnosis. We have developed a new ANN framework called Cox-nnet to predict patient prognosis from high throughput transcriptomics data. In 10 TCGA RNA-Seq data sets, Cox-nnet achieves the same or better predictive accuracy compared to other methods, including Cox-proportional hazards regression (with LASSO, ridge, and mimimax concave penalty), Random Forests Survival and CoxBoost. Cox-nnet also reveals richer biological information, at both the pathway and gene levels. The outputs from the hidden layer node provide an alternative approach for survival-sensitive dimension reduction. In summary, we have developed a new method for accurate and efficient prognosis prediction on high throughput data, with functional biological insights. The source code is freely available at https://github.com/lanagarmire/cox-nnet.

  19. SignalSpider: Probabilistic pattern discovery on multiple normalized ChIP-Seq signal profiles

    KAUST Repository

    Wong, Kachun

    2014-09-05

    Motivation: Chromatin immunoprecipitation (ChIP) followed by high-throughput sequencing (ChIP-Seq) measures the genome-wide occupancy of transcription factors in vivo. Different combinations of DNA-binding protein occupancies may result in a gene being expressed in different tissues or at different developmental stages. To fully understand the functions of genes, it is essential to develop probabilistic models on multiple ChIP-Seq profiles to decipher the combinatorial regulatory mechanisms by multiple transcription factors. Results: In this work, we describe a probabilistic model (SignalSpider) to decipher the combinatorial binding events of multiple transcription factors. Comparing with similar existing methods, we found SignalSpider performs better in clustering promoter and enhancer regions. Notably, SignalSpider can learn higher-order combinatorial patterns from multiple ChIP-Seq profiles. We have applied SignalSpider on the normalized ChIP-Seq profiles from the ENCODE consortium and learned model instances. We observed different higher-order enrichment and depletion patterns across sets of proteins. Those clustering patterns are supported by Gene Ontology (GO) enrichment, evolutionary conservation and chromatin interaction enrichment, offering biological insights for further focused studies. We also proposed a specific enrichment map visualization method to reveal the genome-wide transcription factor combinatorial patterns from the models built, which extend our existing fine-scale knowledge on gene regulation to a genome-wide level. Availability and implementation: The matrix-algebra-optimized executables and source codes are available at the authors\\' websites: http://www.cs.toronto.edu/∼wkc/SignalSpider. Contact: Supplementary information: Supplementary data are available at Bioinformatics online.

  20. Identification of microRNAs from Eugenia uniflora by high-throughput sequencing and bioinformatics analysis.

    Science.gov (United States)

    Guzman, Frank; Almerão, Mauricio P; Körbes, Ana P; Loss-Morais, Guilherme; Margis, Rogerio

    2012-01-01

    microRNAs or miRNAs are small non-coding regulatory RNAs that play important functions in the regulation of gene expression at the post-transcriptional level by targeting mRNAs for degradation or inhibiting protein translation. Eugenia uniflora is a plant native to tropical America with pharmacological and ecological importance, and there have been no previous studies concerning its gene expression and regulation. To date, no miRNAs have been reported in Myrtaceae species. Small RNA and RNA-seq libraries were constructed to identify miRNAs and pre-miRNAs in Eugenia uniflora. Solexa technology was used to perform high throughput sequencing of the library, and the data obtained were analyzed using bioinformatics tools. From 14,489,131 small RNA clean reads, we obtained 1,852,722 mature miRNA sequences representing 45 conserved families that have been identified in other plant species. Further analysis using contigs assembled from RNA-seq allowed the prediction of secondary structures of 25 known and 17 novel pre-miRNAs. The expression of twenty-seven identified miRNAs was also validated using RT-PCR assays. Potential targets were predicted for the most abundant mature miRNAs in the identified pre-miRNAs based on sequence homology. This study is the first large scale identification of miRNAs and their potential targets from a species of the Myrtaceae family without genomic sequence resources. Our study provides more information about the evolutionary conservation of the regulatory network of miRNAs in plants and highlights species-specific miRNAs.

  1. Identification of high-confidence RNA regulatory elements by combinatorial classification of RNA-protein binding sites.

    Science.gov (United States)

    Li, Yang Eric; Xiao, Mu; Shi, Binbin; Yang, Yu-Cheng T; Wang, Dong; Wang, Fei; Marcia, Marco; Lu, Zhi John

    2017-09-08

    Crosslinking immunoprecipitation sequencing (CLIP-seq) technologies have enabled researchers to characterize transcriptome-wide binding sites of RNA-binding protein (RBP) with high resolution. We apply a soft-clustering method, RBPgroup, to various CLIP-seq datasets to group together RBPs that specifically bind the same RNA sites. Such combinatorial clustering of RBPs helps interpret CLIP-seq data and suggests functional RNA regulatory elements. Furthermore, we validate two RBP-RBP interactions in cell lines. Our approach links proteins and RNA motifs known to possess similar biochemical and cellular properties and can, when used in conjunction with additional experimental data, identify high-confidence RBP groups and their associated RNA regulatory elements.

  2. High-throughput sequencing of forensic genetic samples using punches of FTA cards with buccal swabs

    DEFF Research Database (Denmark)

    Kampmann, Marie-Louise; Buchard, Anders; Børsting, Claus

    2016-01-01

    Here, we demonstrate that punches from buccal swab samples preserved on FTA cards can be used for high-throughput DNA sequencing, also known as massively parallel sequencing (MPS). We typed 44 reference samples with the HID-Ion AmpliSeq Identity Panel using washed 1.2 mm punches from FTA cards...

  3. DAG expression: high-throughput gene expression analysis of real-time PCR data using standard curves for relative quantification.

    Directory of Open Access Journals (Sweden)

    María Ballester

    Full Text Available BACKGROUND: Real-time quantitative PCR (qPCR is still the gold-standard technique for gene-expression quantification. Recent technological advances of this method allow for the high-throughput gene-expression analysis, without the limitations of sample space and reagent used. However, non-commercial and user-friendly software for the management and analysis of these data is not available. RESULTS: The recently developed commercial microarrays allow for the drawing of standard curves of multiple assays using the same n-fold diluted samples. Data Analysis Gene (DAG Expression software has been developed to perform high-throughput gene-expression data analysis using standard curves for relative quantification and one or multiple reference genes for sample normalization. We discuss the application of DAG Expression in the analysis of data from an experiment performed with Fluidigm technology, in which 48 genes and 115 samples were measured. Furthermore, the quality of our analysis was tested and compared with other available methods. CONCLUSIONS: DAG Expression is a freely available software that permits the automated analysis and visualization of high-throughput qPCR. A detailed manual and a demo-experiment are provided within the DAG Expression software at http://www.dagexpression.com/dage.zip.

  4. High throughput on-chip analysis of high-energy charged particle tracks using lensfree imaging

    Energy Technology Data Exchange (ETDEWEB)

    Luo, Wei; Shabbir, Faizan; Gong, Chao; Gulec, Cagatay; Pigeon, Jeremy; Shaw, Jessica; Greenbaum, Alon; Tochitsky, Sergei; Joshi, Chandrashekhar [Electrical Engineering Department, University of California, Los Angeles, California 90095 (United States); Ozcan, Aydogan, E-mail: ozcan@ucla.edu [Electrical Engineering Department, University of California, Los Angeles, California 90095 (United States); Bioengineering Department, University of California, Los Angeles, California 90095 (United States); California NanoSystems Institute (CNSI), University of California, Los Angeles, California 90095 (United States)

    2015-04-13

    We demonstrate a high-throughput charged particle analysis platform, which is based on lensfree on-chip microscopy for rapid ion track analysis using allyl diglycol carbonate, i.e., CR-39 plastic polymer as the sensing medium. By adopting a wide-area opto-electronic image sensor together with a source-shifting based pixel super-resolution technique, a large CR-39 sample volume (i.e., 4 cm × 4 cm × 0.1 cm) can be imaged in less than 1 min using a compact lensfree on-chip microscope, which detects partially coherent in-line holograms of the ion tracks recorded within the CR-39 detector. After the image capture, using highly parallelized reconstruction and ion track analysis algorithms running on graphics processing units, we reconstruct and analyze the entire volume of a CR-39 detector within ∼1.5 min. This significant reduction in the entire imaging and ion track analysis time not only increases our throughput but also allows us to perform time-resolved analysis of the etching process to monitor and optimize the growth of ion tracks during etching. This computational lensfree imaging platform can provide a much higher throughput and more cost-effective alternative to traditional lens-based scanning optical microscopes for ion track analysis using CR-39 and other passive high energy particle detectors.

  5. PolyaPeak: Detecting Transcription Factor Binding Sites from ChIP-seq Using Peak Shape Information

    Science.gov (United States)

    Wu, Hao; Ji, Hongkai

    2014-01-01

    ChIP-seq is a powerful technology for detecting genomic regions where a protein of interest interacts with DNA. ChIP-seq data for mapping transcription factor binding sites (TFBSs) have a characteristic pattern: around each binding site, sequence reads aligned to the forward and reverse strands of the reference genome form two separate peaks shifted away from each other, and the true binding site is located in between these two peaks. While it has been shown previously that the accuracy and resolution of binding site detection can be improved by modeling the pattern, efficient methods are unavailable to fully utilize that information in TFBS detection procedure. We present PolyaPeak, a new method to improve TFBS detection by incorporating the peak shape information. PolyaPeak describes peak shapes using a flexible Pólya model. The shapes are automatically learnt from the data using Minorization-Maximization (MM) algorithm, then integrated with the read count information via a hierarchical model to distinguish true binding sites from background noises. Extensive real data analyses show that PolyaPeak is capable of robustly improving TFBS detection compared with existing methods. An R package is freely available. PMID:24608116

  6. csaw: a Bioconductor package for differential binding analysis of ChIP-seq data using sliding windows

    Science.gov (United States)

    Lun, Aaron T.L.; Smyth, Gordon K.

    2016-01-01

    Chromatin immunoprecipitation with massively parallel sequencing (ChIP-seq) is widely used to identify binding sites for a target protein in the genome. An important scientific application is to identify changes in protein binding between different treatment conditions, i.e. to detect differential binding. This can reveal potential mechanisms through which changes in binding may contribute to the treatment effect. The csaw package provides a framework for the de novo detection of differentially bound genomic regions. It uses a window-based strategy to summarize read counts across the genome. It exploits existing statistical software to test for significant differences in each window. Finally, it clusters windows into regions for output and controls the false discovery rate properly over all detected regions. The csaw package can handle arbitrarily complex experimental designs involving biological replicates. It can be applied to both transcription factor and histone mark datasets, and, more generally, to any type of sequencing data measuring genomic coverage. csaw performs favorably against existing methods for de novo DB analyses on both simulated and real data. csaw is implemented as a R software package and is freely available from the open-source Bioconductor project. PMID:26578583

  7. SeqAPASS to evaluate conservation of high-throughput screening targets across non-mammalian species

    Science.gov (United States)

    Cell-based high-throughput screening (HTS) and computational technologies are being applied as tools for toxicity testing in the 21st century. The U.S. Environmental Protection Agency (EPA) embraced these technologies and created the ToxCast Program in 2007, which has served as a...

  8. Proposed high throughput electrorefining treatment for spent N- Reactor fuel

    International Nuclear Information System (INIS)

    Gay, E.C.; Miller, W.E.; Laidler, J.J.

    1996-01-01

    A high-throughput electrorefining process is being adapted to treat spent N-Reactor fuel for ultimate disposal in a geologic repository. Anodic dissolution tests were made with unirradiated N-Reactor fuel to determine the type of fragmentation necessary to provide fuel segments suitable for this process. Based on these tests, a conceptual design was produced of a plant-scale electrorefiner. In this design, the diameter of an electrode assembly is about 1.07 m (42 in.). Three of these assemblies in an electrorefiner would accommodate a 3-metric-ton batch of N-Reactor fuel that would be processed at a rate of 42 kg of uranium per hour

  9. ASPeak: an abundance sensitive peak detection algorithm for RIP-Seq.

    Science.gov (United States)

    Kucukural, Alper; Özadam, Hakan; Singh, Guramrit; Moore, Melissa J; Cenik, Can

    2013-10-01

    Unlike DNA, RNA abundances can vary over several orders of magnitude. Thus, identification of RNA-protein binding sites from high-throughput sequencing data presents unique challenges. Although peak identification in ChIP-Seq data has been extensively explored, there are few bioinformatics tools tailored for peak calling on analogous datasets for RNA-binding proteins. Here we describe ASPeak (abundance sensitive peak detection algorithm), an implementation of an algorithm that we previously applied to detect peaks in exon junction complex RNA immunoprecipitation in tandem experiments. Our peak detection algorithm yields stringent and robust target sets enabling sensitive motif finding and downstream functional analyses. ASPeak is implemented in Perl as a complete pipeline that takes bedGraph files as input. ASPeak implementation is freely available at https://sourceforge.net/projects/as-peak under the GNU General Public License. ASPeak can be run on a personal computer, yet is designed to be easily parallelizable. ASPeak can also run on high performance computing clusters providing efficient speedup. The documentation and user manual can be obtained from http://master.dl.sourceforge.net/project/as-peak/manual.pdf.

  10. A technical assessment of the porcine ejaculated spermatozoa for a sperm-specific RNA-seq analysis.

    Science.gov (United States)

    Gòdia, Marta; Mayer, Fabiana Quoos; Nafissi, Julieta; Castelló, Anna; Rodríguez-Gil, Joan Enric; Sánchez, Armand; Clop, Alex

    2018-04-26

    The study of the boar sperm transcriptome by RNA-seq can provide relevant information on sperm quality and fertility and might contribute to animal breeding strategies. However, the analysis of the spermatozoa RNA is challenging as these cells harbor very low amounts of highly fragmented RNA, and the ejaculates also contain other cell types with larger amounts of non-fragmented RNA. Here, we describe a strategy for a successful boar sperm purification, RNA extraction and RNA-seq library preparation. Using these approaches our objectives were: (i) to evaluate the sperm recovery rate (SRR) after boar spermatozoa purification by density centrifugation using the non-porcine-specific commercial reagent BoviPure TM ; (ii) to assess the correlation between SRR and sperm quality characteristics; (iii) to evaluate the relationship between sperm cell RNA load and sperm quality traits and (iv) to compare different library preparation kits for both total RNA-seq (SMARTer Universal Low Input RNA and TruSeq RNA Library Prep kit) and small RNA-seq (NEBNext Small RNA and TailorMix miRNA Sample Prep v2) for high-throughput sequencing. Our results show that pig SRR (~22%) is lower than in other mammalian species and that it is not significantly dependent of the sperm quality parameters analyzed in our study. Moreover, no relationship between the RNA yield per sperm cell and sperm phenotypes was found. We compared a RNA-seq library preparation kit optimized for low amounts of fragmented RNA with a standard kit designed for high amount and quality of input RNA and found that for sperm, a protocol designed to work on low-quality RNA is essential. We also compared two small RNA-seq kits and did not find substantial differences in their performance. We propose the methodological workflow described for the RNA-seq screening of the boar spermatozoa transcriptome. FPKM: fragments per kilobase of transcript per million mapped reads; KRT1: keratin 1; miRNA: micro-RNA; miscRNA: miscellaneous

  11. A FRET-based high throughput screening assay to identify inhibitors of anthrax protective antigen binding to capillary morphogenesis gene 2 protein.

    Directory of Open Access Journals (Sweden)

    Michael S Rogers

    Full Text Available Anti-angiogenic therapies are effective for the treatment of cancer, a variety of ocular diseases, and have potential benefits in cardiovascular disease, arthritis, and psoriasis. We have previously shown that anthrax protective antigen (PA, a non-pathogenic component of anthrax toxin, is an inhibitor of angiogenesis, apparently as a result of interaction with the cell surface receptors capillary morphogenesis gene 2 (CMG2 protein and tumor endothelial marker 8 (TEM8. Hence, molecules that bind the anthrax toxin receptors may be effective to slow or halt pathological vascular growth. Here we describe development and testing of an effective homogeneous steady-state fluorescence resonance energy transfer (FRET high throughput screening assay designed to identify molecules that inhibit binding of PA to CMG2. Molecules identified in the screen can serve as potential lead compounds for the development of anti-angiogenic and anti-anthrax therapies. The assay to screen for inhibitors of this protein-protein interaction is sensitive and robust, with observed Z' values as high as 0.92. Preliminary screens conducted with a library of known bioactive compounds identified tannic acid and cisplatin as inhibitors of the PA-CMG2 interaction. We have confirmed that tannic acid both binds CMG2 and has anti-endothelial properties. In contrast, cisplatin appears to inhibit PA-CMG2 interaction by binding both PA and CMG2, and observed cisplatin anti-angiogenic effects are not mediated by interaction with CMG2. This work represents the first reported high throughput screening assay targeting CMG2 to identify possible inhibitors of both angiogenesis and anthrax intoxication.

  12. Towards a high throughput droplet-based agglutination assay

    KAUST Repository

    Kodzius, Rimantas; Castro, David; Foulds, Ian G.

    2013-01-01

    This work demonstrates the detection method for a high throughput droplet based agglutination assay system. Using simple hydrodynamic forces to mix and aggregate functionalized microbeads we avoid the need to use magnetic assistance or mixing structures. The concentration of our target molecules was estimated by agglutination strength, obtained through optical image analysis. Agglutination in droplets was performed with flow rates of 150 µl/min and occurred in under a minute, with potential to perform high-throughput measurements. The lowest target concentration detected in droplet microfluidics was 0.17 nM, which is three orders of magnitude more sensitive than a conventional card based agglutination assay.

  13. Towards a high throughput droplet-based agglutination assay

    KAUST Repository

    Kodzius, Rimantas

    2013-10-22

    This work demonstrates the detection method for a high throughput droplet based agglutination assay system. Using simple hydrodynamic forces to mix and aggregate functionalized microbeads we avoid the need to use magnetic assistance or mixing structures. The concentration of our target molecules was estimated by agglutination strength, obtained through optical image analysis. Agglutination in droplets was performed with flow rates of 150 µl/min and occurred in under a minute, with potential to perform high-throughput measurements. The lowest target concentration detected in droplet microfluidics was 0.17 nM, which is three orders of magnitude more sensitive than a conventional card based agglutination assay.

  14. Characterization of Intestinal Microbiomes of Hirschsprung's Disease Patients with or without Enterocolitis Using Illumina-MiSeq High-Throughput Sequencing.

    Directory of Open Access Journals (Sweden)

    Yuqing Li

    Full Text Available Hirschsprung-associated enterocolitis (HAEC is a life-threatening complication of Hirschsprung's disease (HD. Although the pathological mechanisms are still unclear, studies have shown that HAEC has a close relationship with the disturbance of intestinal microbiota. This study aimed to investigate the characteristics of the intestinal microbiome of HD patients with or without enterocolitis. During routine or emergency surgery, we collected 35 intestinal content samples from five patients with HAEC and eight HD patients, including three HD patients with a history of enterocolitis who were in a HAEC remission (HAEC-R phase. Using Illumina-MiSeq high-throughput sequencing, we sequenced the V4 region of bacterial 16S rRNA, and operational taxonomic units (OTUs were defined by 97% sequence similarity. Principal coordinate analysis (PCoA of weighted UniFrac distances was performed to evaluate the diversity of each intestinal microbiome sample. The microbiota differed significantly between the HD patients (characterized by the prevalence of Bacteroidetes and HAEC patients (characterized by the prevalence of Proteobacteria, while the microbiota of the HAEC-R patients was more similar to that of the HAEC patients. We also observed that the specimens from different intestinal sites of each HD patient differed significantly, while the specimens from different intestinal sites of each HAEC and HAEC-R patient were more similar. In conclusion, the microbiome pattern of the HAEC-R patients was more similar to that of the HAEC patients than to that of the HD patients. The HD patients had a relatively distinct, more stable community than the HAEC and HAEC-R patients, suggesting that enterocolitis may either be caused by or result in a disruption of the patient's uniquely adapted intestinal flora. The intestinal microbiota associated with enterocolitis may persist following symptom resolution and can be implicated in the symptom recurrence.

  15. Spatio-temporal model for multiple ChIP-seq experiments

    NARCIS (Netherlands)

    Ranciati, Saverio; Viroli, Cinzia; Wit, Ernst

    2015-01-01

    The increasing availability of ChIP-seq data demands for advanced statistical tools to analyze the results of such experiments. The inherent features of high-throughput sequencing output call for a modelling framework that can account for the spatial dependency between neighboring regions of the

  16. Identification of cytokinin-responsive genes using microarray meta-analysis and RNA-Seq in Arabidopsis.

    Science.gov (United States)

    Bhargava, Apurva; Clabaugh, Ivory; To, Jenn P; Maxwell, Bridey B; Chiang, Yi-Hsuan; Schaller, G Eric; Loraine, Ann; Kieber, Joseph J

    2013-05-01

    Cytokinins are N(6)-substituted adenine derivatives that play diverse roles in plant growth and development. We sought to define a robust set of genes regulated by cytokinin as well as to query the response of genes not represented on microarrays. To this end, we performed a meta-analysis of microarray data from a variety of cytokinin-treated samples and used RNA-seq to examine cytokinin-regulated gene expression in Arabidopsis (Arabidopsis thaliana). Microarray meta-analysis using 13 microarray experiments combined with empirically defined filtering criteria identified a set of 226 genes differentially regulated by cytokinin, a subset of which has previously been validated by other methods. RNA-seq validated about 73% of the up-regulated genes identified by this meta-analysis. In silico promoter analysis indicated an overrepresentation of type-B Arabidopsis response regulator binding elements, consistent with the role of type-B Arabidopsis response regulators as primary mediators of cytokinin-responsive gene expression. RNA-seq analysis identified 73 cytokinin-regulated genes that were not represented on the ATH1 microarray. Representative genes were verified using quantitative reverse transcription-polymerase chain reaction and NanoString analysis. Analysis of the genes identified reveals a substantial effect of cytokinin on genes encoding proteins involved in secondary metabolism, particularly those acting in flavonoid and phenylpropanoid biosynthesis, as well as in the regulation of redox state of the cell, particularly a set of glutaredoxin genes. Novel splicing events were found in members of some gene families that are known to play a role in cytokinin signaling or metabolism. The genes identified in this analysis represent a robust set of cytokinin-responsive genes that are useful in the analysis of cytokinin function in plants.

  17. High throughput screening of starch structures using carbohydrate microarrays

    DEFF Research Database (Denmark)

    Tanackovic, Vanja; Rydahl, Maja Gro; Pedersen, Henriette Lodberg

    2016-01-01

    In this study we introduce the starch-recognising carbohydrate binding module family 20 (CBM20) from Aspergillus niger for screening biological variations in starch molecular structure using high throughput carbohydrate microarray technology. Defined linear, branched and phosphorylated...

  18. High-resolution detection of DNA binding sites of the global transcriptional regulator GlxR in Corynebacterium glutamicum

    DEFF Research Database (Denmark)

    Jungwirth, Britta; Sala, Claudia; Kohl, Thomas A

    2013-01-01

    of the 6C non-coding RNA gene and to non-canonical DNA binding sites within protein-coding regions. The present study underlines the dynamics within the GlxR regulon by identifying in vivo targets during growth on glucose and contributes to the expansion of knowledge of this important transcriptional......The transcriptional regulator GlxR has been characterized as a global hub within the gene-regulatory network of Corynebacterium glutamicum. Chromatin immunoprecipitation with a specific anti-GlxR antibody and subsequent high-throughput sequencing (ChIP-seq) was applied to C. glutamicum to get new...... mapping of these data on the genome sequence of C. glutamicum, 107 enriched DNA fragments were detected from cells grown with glucose as carbon source. GlxR binding sites were identified in the sequence of 79 enriched DNA fragments, of which 21 sites were not previously reported. Electrophoretic mobility...

  19. Detecting Differential Transcription Factor Activity from ATAC-Seq Data

    Directory of Open Access Journals (Sweden)

    Ignacio J. Tripodi

    2018-05-01

    Full Text Available Transcription factors are managers of the cellular factory, and key components to many diseases. Many non-coding single nucleotide polymorphisms affect transcription factors, either by directly altering the protein or its functional activity at individual binding sites. Here we first briefly summarize high-throughput approaches to studying transcription factor activity. We then demonstrate, using published chromatin accessibility data (specifically ATAC-seq, that the genome-wide profile of TF recognition motifs relative to regions of open chromatin can determine the key transcription factor altered by a perturbation. Our method of determining which TFs are altered by a perturbation is simple, is quick to implement, and can be used when biological samples are limited. In the future, we envision that this method could be applied to determine which TFs show altered activity in response to a wide variety of drugs and diseases.

  20. Recent advances in quantitative high throughput and high content data analysis.

    Science.gov (United States)

    Moutsatsos, Ioannis K; Parker, Christian N

    2016-01-01

    High throughput screening has become a basic technique with which to explore biological systems. Advances in technology, including increased screening capacity, as well as methods that generate multiparametric readouts, are driving the need for improvements in the analysis of data sets derived from such screens. This article covers the recent advances in the analysis of high throughput screening data sets from arrayed samples, as well as the recent advances in the analysis of cell-by-cell data sets derived from image or flow cytometry application. Screening multiple genomic reagents targeting any given gene creates additional challenges and so methods that prioritize individual gene targets have been developed. The article reviews many of the open source data analysis methods that are now available and which are helping to define a consensus on the best practices to use when analyzing screening data. As data sets become larger, and more complex, the need for easily accessible data analysis tools will continue to grow. The presentation of such complex data sets, to facilitate quality control monitoring and interpretation of the results will require the development of novel visualizations. In addition, advanced statistical and machine learning algorithms that can help identify patterns, correlations and the best features in massive data sets will be required. The ease of use for these tools will be important, as they will need to be used iteratively by laboratory scientists to improve the outcomes of complex analyses.

  1. Dissecting Cell-Type Composition and Activity-Dependent Transcriptional State in Mammalian Brains by Massively Parallel Single-Nucleus RNA-Seq.

    Science.gov (United States)

    Hu, Peng; Fabyanic, Emily; Kwon, Deborah Y; Tang, Sheng; Zhou, Zhaolan; Wu, Hao

    2017-12-07

    Massively parallel single-cell RNA sequencing can precisely resolve cellular diversity in a high-throughput manner at low cost, but unbiased isolation of intact single cells from complex tissues such as adult mammalian brains is challenging. Here, we integrate sucrose-gradient-assisted purification of nuclei with droplet microfluidics to develop a highly scalable single-nucleus RNA-seq approach (sNucDrop-seq), which is free of enzymatic dissociation and nucleus sorting. By profiling ∼18,000 nuclei isolated from cortical tissues of adult mice, we demonstrate that sNucDrop-seq not only accurately reveals neuronal and non-neuronal subtype composition with high sensitivity but also enables in-depth analysis of transient transcriptional states driven by neuronal activity, at single-cell resolution, in vivo. Copyright © 2017 Elsevier Inc. All rights reserved.

  2. Fluorescent foci quantitation for high-throughput analysis

    Directory of Open Access Journals (Sweden)

    Elena Ledesma-Fernández

    2015-06-01

    Full Text Available A number of cellular proteins localize to discrete foci within cells, for example DNA repair proteins, microtubule organizing centers, P bodies or kinetochores. It is often possible to measure the fluorescence emission from tagged proteins within these foci as a surrogate for the concentration of that specific protein. We wished to develop tools that would allow quantitation of fluorescence foci intensities in high-throughput studies. As proof of principle we have examined the kinetochore, a large multi-subunit complex that is critical for the accurate segregation of chromosomes during cell division. Kinetochore perturbations lead to aneuploidy, which is a hallmark of cancer cells. Hence, understanding kinetochore homeostasis and regulation are important for a global understanding of cell division and genome integrity. The 16 budding yeast kinetochores colocalize within the nucleus to form a single focus. Here we have created a set of freely-available tools to allow high-throughput quantitation of kinetochore foci fluorescence. We use this ‘FociQuant’ tool to compare methods of kinetochore quantitation and we show proof of principle that FociQuant can be used to identify changes in kinetochore protein levels in a mutant that affects kinetochore function. This analysis can be applied to any protein that forms discrete foci in cells.

  3. Coop-Seq Analysis Demonstrates that Sox2 Evokes Latent Specificities in the DNA Recognition by Pax6.

    Science.gov (United States)

    Hu, Caizhen; Malik, Vikas; Chang, Yiming Kenny; Veerapandian, Veeramohan; Srivastava, Yogesh; Huang, Yong-Heng; Hou, Linlin; Cojocaru, Vlad; Stormo, Gary D; Jauch, Ralf

    2017-11-24

    Sox2 and Pax6 co-regulate genes in neural lineages and the lens by forming a ternary complex likely facilitated allosterically through DNA. We used the quantitative and scalable cooperativity-by-sequencing (Coop-seq) approach to interrogate Sox2/Pax6 dimerization on a DNA library where five positions of the Pax6 half-site were randomized yielding 1024 cooperativity factors. Consensus positions normally required for the high-affinity DNA binding by Pax6 need to be mutated for effective dimerization with Sox2. Out of the five randomized bases, a 5' thymidine is present in most of the top ranking elements. However, this thymidine maps to a region outside of the Pax half site and is not expected to directly interact with Pax6 in known binding modes suggesting structural reconfigurations. Re-analysis of ChIP-seq data identified several genomic regions where the cooperativity promoting sequence pattern is co-bound by Sox2 and Pax6. A highly conserved Sox2/Pax6 bound site near the Sprouty2 locus was verified to promote cooperative dimerization designating Sprouty2 as a potential target reliant on Sox2/Pax6 cooperativity in several neural cell types. Collectively, the functional interplay of Sox2 and Pax6 demands the relaxation of high-affinity binding sites and is enabled by alternative DNA sequences. We conclude that this binding mode evolved to warrant that a subset of target genes is only regulated in the presence of suitable partner factors. Copyright © 2017 Elsevier Ltd. All rights reserved.

  4. Strand-Specific RNA-Seq Analyses of Fruiting Body Development in Coprinopsis cinerea.

    Directory of Open Access Journals (Sweden)

    Hajime Muraguchi

    Full Text Available The basidiomycete fungus Coprinopsis cinerea is an important model system for multicellular development. Fruiting bodies of C. cinerea are typical mushrooms, which can be produced synchronously on defined media in the laboratory. To investigate the transcriptome in detail during fruiting body development, high-throughput sequencing (RNA-seq was performed using cDNA libraries strand-specifically constructed from 13 points (stages/tissues with two biological replicates. The reads were aligned to 14,245 predicted transcripts, and counted for forward and reverse transcripts. Differentially expressed genes (DEGs between two adjacent points and between vegetative mycelium and each point were detected by Tag Count Comparison (TCC. To validate RNA-seq data, expression levels of selected genes were compared using RPKM values in RNA-seq data and qRT-PCR data, and DEGs detected in microarray data were examined in MA plots of RNA-seq data by TCC. We discuss events deduced from GO analysis of DEGs. In addition, we uncovered both transcription factor candidates and antisense transcripts that are likely to be involved in developmental regulation for fruiting.

  5. Evaluation of tools for highly variable gene discovery from single-cell RNA-seq data.

    Science.gov (United States)

    Yip, Shun H; Sham, Pak Chung; Wang, Junwen

    2018-02-21

    Traditional RNA sequencing (RNA-seq) allows the detection of gene expression variations between two or more cell populations through differentially expressed gene (DEG) analysis. However, genes that contribute to cell-to-cell differences are not discoverable with RNA-seq because RNA-seq samples are obtained from a mixture of cells. Single-cell RNA-seq (scRNA-seq) allows the detection of gene expression in each cell. With scRNA-seq, highly variable gene (HVG) discovery allows the detection of genes that contribute strongly to cell-to-cell variation within a homogeneous cell population, such as a population of embryonic stem cells. This analysis is implemented in many software packages. In this study, we compare seven HVG methods from six software packages, including BASiCS, Brennecke, scLVM, scran, scVEGs and Seurat. Our results demonstrate that reproducibility in HVG analysis requires a larger sample size than DEG analysis. Discrepancies between methods and potential issues in these tools are discussed and recommendations are made.

  6. Role of SeqA and Dam in Escherichia coli gene expression: A global/microarray analysis

    DEFF Research Database (Denmark)

    Løbner-Olesen, Anders; Marinus, M.G.; Hansen, Flemming G.

    2003-01-01

    High-density oligonucleotide arrays were used to monitor global transcription patterns in Escherichia coli with various levels of Dam and SeqA proteins. Cells lacking Dam methyltransferase showed a modest increase in transcription of the genes belonging to the SOS regulon. Bacteria devoid...... of the SeqA protein, which preferentially binds hemimethylated DNA, were found to have a transcriptional profile almost identical to WT bacteria overexpressing Dam methyltransferase. The latter two strains differed from WT in two ways. First, the origin proximal genes were transcribed with increased...... frequency due to increased gene dosage. Second, chromosomal domains of high transcriptional activity alternate with regions of low activity, and our results indicate that the activity in each domain is modulated in the same way by SeqA deficiency or Dam overproduction. We suggest that the methylation status...

  7. HTSeq--a Python framework to work with high-throughput sequencing data.

    Science.gov (United States)

    Anders, Simon; Pyl, Paul Theodor; Huber, Wolfgang

    2015-01-15

    A large choice of tools exists for many standard tasks in the analysis of high-throughput sequencing (HTS) data. However, once a project deviates from standard workflows, custom scripts are needed. We present HTSeq, a Python library to facilitate the rapid development of such scripts. HTSeq offers parsers for many common data formats in HTS projects, as well as classes to represent data, such as genomic coordinates, sequences, sequencing reads, alignments, gene model information and variant calls, and provides data structures that allow for querying via genomic coordinates. We also present htseq-count, a tool developed with HTSeq that preprocesses RNA-Seq data for differential expression analysis by counting the overlap of reads with genes. HTSeq is released as an open-source software under the GNU General Public Licence and available from http://www-huber.embl.de/HTSeq or from the Python Package Index at https://pypi.python.org/pypi/HTSeq. © The Author 2014. Published by Oxford University Press.

  8. Accurate molecular diagnosis of phenylketonuria and tetrahydrobiopterin-deficient hyperphenylalaninemias using high-throughput targeted sequencing

    Science.gov (United States)

    Trujillano, Daniel; Perez, Belén; González, Justo; Tornador, Cristian; Navarrete, Rosa; Escaramis, Georgia; Ossowski, Stephan; Armengol, Lluís; Cornejo, Verónica; Desviat, Lourdes R; Ugarte, Magdalena; Estivill, Xavier

    2014-01-01

    Genetic diagnostics of phenylketonuria (PKU) and tetrahydrobiopterin (BH4) deficient hyperphenylalaninemia (BH4DH) rely on methods that scan for known mutations or on laborious molecular tools that use Sanger sequencing. We have implemented a novel and much more efficient strategy based on high-throughput multiplex-targeted resequencing of four genes (PAH, GCH1, PTS, and QDPR) that, when affected by loss-of-function mutations, cause PKU and BH4DH. We have validated this approach in a cohort of 95 samples with the previously known PAH, GCH1, PTS, and QDPR mutations and one control sample. Pooled barcoded DNA libraries were enriched using a custom NimbleGen SeqCap EZ Choice array and sequenced using a HiSeq2000 sequencer. The combination of several robust bioinformatics tools allowed us to detect all known pathogenic mutations (point mutations, short insertions/deletions, and large genomic rearrangements) in the 95 samples, without detecting spurious calls in these genes in the control sample. We then used the same capture assay in a discovery cohort of 11 uncharacterized HPA patients using a MiSeq sequencer. In addition, we report the precise characterization of the breakpoints of four genomic rearrangements in PAH, including a novel deletion of 899 bp in intron 3. Our study is a proof-of-principle that high-throughput-targeted resequencing is ready to substitute classical molecular methods to perform differential genetic diagnosis of hyperphenylalaninemias, allowing the establishment of specifically tailored treatments a few days after birth. PMID:23942198

  9. High throughput sample processing and automated scoring

    Directory of Open Access Journals (Sweden)

    Gunnar eBrunborg

    2014-10-01

    Full Text Available The comet assay is a sensitive and versatile method for assessing DNA damage in cells. In the traditional version of the assay, there are many manual steps involved and few samples can be treated in one experiment. High throughput modifications have been developed during recent years, and they are reviewed and discussed. These modifications include accelerated scoring of comets; other important elements that have been studied and adapted to high throughput are cultivation and manipulation of cells or tissues before and after exposure, and freezing of treated samples until comet analysis and scoring. High throughput methods save time and money but they are useful also for other reasons: large-scale experiments may be performed which are otherwise not practicable (e.g., analysis of many organs from exposed animals, and human biomonitoring studies, and automation gives more uniform sample treatment and less dependence on operator performance. The high throughput modifications now available vary largely in their versatility, capacity, complexity and costs. The bottleneck for further increase of throughput appears to be the scoring.

  10. Novel high-throughput cell-based hybridoma screening methodology using the Celigo Image Cytometer.

    Science.gov (United States)

    Zhang, Haohai; Chan, Leo Li-Ying; Rice, William; Kassam, Nasim; Longhi, Maria Serena; Zhao, Haitao; Robson, Simon C; Gao, Wenda; Wu, Yan

    2017-08-01

    Hybridoma screening is a critical step for antibody discovery, which necessitates prompt identification of potential clones from hundreds to thousands of hybridoma cultures against the desired immunogen. Technical issues associated with ELISA- and flow cytometry-based screening limit accuracy and diminish high-throughput capability, increasing time and cost. Conventional ELISA screening with coated antigen is also impractical for difficult-to-express hydrophobic membrane antigens or multi-chain protein complexes. Here, we demonstrate novel high-throughput screening methodology employing the Celigo Image Cytometer, which avoids nonspecific signals by contrasting antibody binding signals directly on living cells, with and without recombinant antigen expression. The image cytometry-based high-throughput screening method was optimized by detecting the binding of hybridoma supernatants to the recombinant antigen CD39 expressed on Chinese hamster ovary (CHO) cells. Next, the sensitivity of the image cytometer was demonstrated by serial dilution of purified CD39 antibody. Celigo was used to measure antibody affinities of commercial and in-house antibodies to membrane-bound CD39. This cell-based screening procedure can be completely accomplished within one day, significantly improving throughput and efficiency of hybridoma screening. Furthermore, measuring direct antibody binding to living cells eliminated both false positive and false negative hits. The image cytometry method was highly sensitive and versatile, and could detect positive antibody in supernatants at concentrations as low as ~5ng/mL, with concurrent K d binding affinity coefficient determination. We propose that this screening method will greatly facilitate antibody discovery and screening technologies. Copyright © 2017 Elsevier B.V. All rights reserved.

  11. Comparative analysis of transcriptomes in aerial stems and roots of Ephedra sinica based on high-throughput mRNA sequencing

    Directory of Open Access Journals (Sweden)

    Taketo Okada

    2016-12-01

    Full Text Available Ephedra plants are taxonomically classified as gymnosperms, and are medicinally important as the botanical origin of crude drugs and as bioresources that contain pharmacologically active chemicals. Here we show a comparative analysis of the transcriptomes of aerial stems and roots of Ephedra sinica based on high-throughput mRNA sequencing by RNA-Seq. De novo assembly of short cDNA sequence reads generated 23,358, 13,373, and 28,579 contigs longer than 200 bases from aerial stems, roots, or both aerial stems and roots, respectively. The presumed functions encoded by these contig sequences were annotated by BLAST (blastx. Subsequently, these contigs were classified based on gene ontology slims, Enzyme Commission numbers, and the InterPro database. Furthermore, comparative gene expression analysis was performed between aerial stems and roots. These transcriptome analyses revealed differences and similarities between the transcriptomes of aerial stems and roots in E. sinica. Deep transcriptome sequencing of Ephedra should open the door to molecular biological studies based on the entire transcriptome, tissue- or organ-specific transcriptomes, or targeted genes of interest.

  12. Label-free cell-cycle analysis by high-throughput quantitative phase time-stretch imaging flow cytometry

    Science.gov (United States)

    Mok, Aaron T. Y.; Lee, Kelvin C. M.; Wong, Kenneth K. Y.; Tsia, Kevin K.

    2018-02-01

    Biophysical properties of cells could complement and correlate biochemical markers to characterize a multitude of cellular states. Changes in cell size, dry mass and subcellular morphology, for instance, are relevant to cell-cycle progression which is prevalently evaluated by DNA-targeted fluorescence measurements. Quantitative-phase microscopy (QPM) is among the effective biophysical phenotyping tools that can quantify cell sizes and sub-cellular dry mass density distribution of single cells at high spatial resolution. However, limited camera frame rate and thus imaging throughput makes QPM incompatible with high-throughput flow cytometry - a gold standard in multiparametric cell-based assay. Here we present a high-throughput approach for label-free analysis of cell cycle based on quantitative-phase time-stretch imaging flow cytometry at a throughput of > 10,000 cells/s. Our time-stretch QPM system enables sub-cellular resolution even at high speed, allowing us to extract a multitude (at least 24) of single-cell biophysical phenotypes (from both amplitude and phase images). Those phenotypes can be combined to track cell-cycle progression based on a t-distributed stochastic neighbor embedding (t-SNE) algorithm. Using multivariate analysis of variance (MANOVA) discriminant analysis, cell-cycle phases can also be predicted label-free with high accuracy at >90% in G1 and G2 phase, and >80% in S phase. We anticipate that high throughput label-free cell cycle characterization could open new approaches for large-scale single-cell analysis, bringing new mechanistic insights into complex biological processes including diseases pathogenesis.

  13. Optimizing transformations for automated, high throughput analysis of flow cytometry data.

    Science.gov (United States)

    Finak, Greg; Perez, Juan-Manuel; Weng, Andrew; Gottardo, Raphael

    2010-11-04

    In a high throughput setting, effective flow cytometry data analysis depends heavily on proper data preprocessing. While usual preprocessing steps of quality assessment, outlier removal, normalization, and gating have received considerable scrutiny from the community, the influence of data transformation on the output of high throughput analysis has been largely overlooked. Flow cytometry measurements can vary over several orders of magnitude, cell populations can have variances that depend on their mean fluorescence intensities, and may exhibit heavily-skewed distributions. Consequently, the choice of data transformation can influence the output of automated gating. An appropriate data transformation aids in data visualization and gating of cell populations across the range of data. Experience shows that the choice of transformation is data specific. Our goal here is to compare the performance of different transformations applied to flow cytometry data in the context of automated gating in a high throughput, fully automated setting. We examine the most common transformations used in flow cytometry, including the generalized hyperbolic arcsine, biexponential, linlog, and generalized Box-Cox, all within the BioConductor flowCore framework that is widely used in high throughput, automated flow cytometry data analysis. All of these transformations have adjustable parameters whose effects upon the data are non-intuitive for most users. By making some modelling assumptions about the transformed data, we develop maximum likelihood criteria to optimize parameter choice for these different transformations. We compare the performance of parameter-optimized and default-parameter (in flowCore) data transformations on real and simulated data by measuring the variation in the locations of cell populations across samples, discovered via automated gating in both the scatter and fluorescence channels. We find that parameter-optimized transformations improve visualization, reduce

  14. Optimizing transformations for automated, high throughput analysis of flow cytometry data

    Directory of Open Access Journals (Sweden)

    Weng Andrew

    2010-11-01

    Full Text Available Abstract Background In a high throughput setting, effective flow cytometry data analysis depends heavily on proper data preprocessing. While usual preprocessing steps of quality assessment, outlier removal, normalization, and gating have received considerable scrutiny from the community, the influence of data transformation on the output of high throughput analysis has been largely overlooked. Flow cytometry measurements can vary over several orders of magnitude, cell populations can have variances that depend on their mean fluorescence intensities, and may exhibit heavily-skewed distributions. Consequently, the choice of data transformation can influence the output of automated gating. An appropriate data transformation aids in data visualization and gating of cell populations across the range of data. Experience shows that the choice of transformation is data specific. Our goal here is to compare the performance of different transformations applied to flow cytometry data in the context of automated gating in a high throughput, fully automated setting. We examine the most common transformations used in flow cytometry, including the generalized hyperbolic arcsine, biexponential, linlog, and generalized Box-Cox, all within the BioConductor flowCore framework that is widely used in high throughput, automated flow cytometry data analysis. All of these transformations have adjustable parameters whose effects upon the data are non-intuitive for most users. By making some modelling assumptions about the transformed data, we develop maximum likelihood criteria to optimize parameter choice for these different transformations. Results We compare the performance of parameter-optimized and default-parameter (in flowCore data transformations on real and simulated data by measuring the variation in the locations of cell populations across samples, discovered via automated gating in both the scatter and fluorescence channels. We find that parameter

  15. High-Throughput Analysis of Enzyme Activities

    Energy Technology Data Exchange (ETDEWEB)

    Lu, Guoxin [Iowa State Univ., Ames, IA (United States)

    2007-01-01

    High-throughput screening (HTS) techniques have been applied to many research fields nowadays. Robot microarray printing technique and automation microtiter handling technique allows HTS performing in both heterogeneous and homogeneous formats, with minimal sample required for each assay element. In this dissertation, new HTS techniques for enzyme activity analysis were developed. First, patterns of immobilized enzyme on nylon screen were detected by multiplexed capillary system. The imaging resolution is limited by the outer diameter of the capillaries. In order to get finer images, capillaries with smaller outer diameters can be used to form the imaging probe. Application of capillary electrophoresis allows separation of the product from the substrate in the reaction mixture, so that the product doesn't have to have different optical properties with the substrate. UV absorption detection allows almost universal detection for organic molecules. Thus, no modifications of either the substrate or the product molecules are necessary. This technique has the potential to be used in screening of local distribution variations of specific bio-molecules in a tissue or in screening of multiple immobilized catalysts. Another high-throughput screening technique is developed by directly monitoring the light intensity of the immobilized-catalyst surface using a scientific charge-coupled device (CCD). Briefly, the surface of enzyme microarray is focused onto a scientific CCD using an objective lens. By carefully choosing the detection wavelength, generation of product on an enzyme spot can be seen by the CCD. Analyzing the light intensity change over time on an enzyme spot can give information of reaction rate. The same microarray can be used for many times. Thus, high-throughput kinetic studies of hundreds of catalytic reactions are made possible. At last, we studied the fluorescence emission spectra of ADP and obtained the detection limits for ADP under three different

  16. A priori Considerations When Conducting High-Throughput Amplicon-Based Sequence Analysis

    Directory of Open Access Journals (Sweden)

    Aditi Sengupta

    2016-03-01

    Full Text Available Amplicon-based sequencing strategies that include 16S rRNA and functional genes, alongside “meta-omics” analyses of communities of microorganisms, have allowed researchers to pose questions and find answers to “who” is present in the environment and “what” they are doing. Next-generation sequencing approaches that aid microbial ecology studies of agricultural systems are fast gaining popularity among agronomy, crop, soil, and environmental science researchers. Given the rapid development of these high-throughput sequencing techniques, researchers with no prior experience will desire information about the best practices that can be used before actually starting high-throughput amplicon-based sequence analyses. We have outlined items that need to be carefully considered in experimental design, sampling, basic bioinformatics, sequencing of mock communities and negative controls, acquisition of metadata, and in standardization of reaction conditions as per experimental requirements. Not all considerations mentioned here may pertain to a particular study. The overall goal is to inform researchers about considerations that must be taken into account when conducting high-throughput microbial DNA sequencing and sequences analysis.

  17. High Throughput Neuro-Imaging Informatics

    Directory of Open Access Journals (Sweden)

    Michael I Miller

    2013-12-01

    Full Text Available This paper describes neuroinformatics technologies at 1 mm anatomical scale based on high throughput 3D functional and structural imaging technologies of the human brain. The core is an abstract pipeline for converting functional and structural imagery into their high dimensional neuroinformatic representations index containing O(E3-E4 discriminating dimensions. The pipeline is based on advanced image analysis coupled to digital knowledge representations in the form of dense atlases of the human brain at gross anatomical scale. We demonstrate the integration of these high-dimensional representations with machine learning methods, which have become the mainstay of other fields of science including genomics as well as social networks. Such high throughput facilities have the potential to alter the way medical images are stored and utilized in radiological workflows. The neuroinformatics pipeline is used to examine cross-sectional and personalized analyses of neuropsychiatric illnesses in clinical applications as well as longitudinal studies. We demonstrate the use of high throughput machine learning methods for supporting (i cross-sectional image analysis to evaluate the health status of individual subjects with respect to the population data, (ii integration of image and non-image information for diagnosis and prognosis.

  18. Genome-wide analysis of CDX2 binding in intestinal epithelial cells (Caco-2)

    DEFF Research Database (Denmark)

    Boyd, Mette; Hansen, Morten; Jensen, Tine G K

    2010-01-01

    The CDX2 transcription factor is known to play a crucial role in inhibiting proliferation, promoting differentiation and the expression of intestinal specific genes in intestinal cells. The overall effect of CDX2 in intestinal cells has previously been investigated in conditional knock-out mice......, revealing a critical role of CDX2 in the formation of the normal intestinal identity. The identification of direct targets of transcription factors is a key problem in the study of gene regulatory networks. The ChIP-seq technique combines chromatin immunoprecipitation (ChIP) with next generation sequencing...... resulting in a high throughput experimental method of identifying direct targets of specific transcription factors. The method was applied to CDX2, leading to the identification of the direct binding of CDX2 to several known and novel target genes in the intestinal cell. Examination of the transcript levels...

  19. BioVLAB-MMIA-NGS: microRNA-mRNA integrated analysis using high-throughput sequencing data.

    Science.gov (United States)

    Chae, Heejoon; Rhee, Sungmin; Nephew, Kenneth P; Kim, Sun

    2015-01-15

    It is now well established that microRNAs (miRNAs) play a critical role in regulating gene expression in a sequence-specific manner, and genome-wide efforts are underway to predict known and novel miRNA targets. However, the integrated miRNA-mRNA analysis remains a major computational challenge, requiring powerful informatics systems and bioinformatics expertise. The objective of this study was to modify our widely recognized Web server for the integrated mRNA-miRNA analysis (MMIA) and its subsequent deployment on the Amazon cloud (BioVLAB-MMIA) to be compatible with high-throughput platforms, including next-generation sequencing (NGS) data (e.g. RNA-seq). We developed a new version called the BioVLAB-MMIA-NGS, deployed on both Amazon cloud and on a high-performance publicly available server called MAHA. By using NGS data and integrating various bioinformatics tools and databases, BioVLAB-MMIA-NGS offers several advantages. First, sequencing data is more accurate than array-based methods for determining miRNA expression levels. Second, potential novel miRNAs can be detected by using various computational methods for characterizing miRNAs. Third, because miRNA-mediated gene regulation is due to hybridization of an miRNA to its target mRNA, sequencing data can be used to identify many-to-many relationship between miRNAs and target genes with high accuracy. http://epigenomics.snu.ac.kr/biovlab_mmia_ngs/. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  20. Combinatorial chemoenzymatic synthesis and high-throughput screening of sialosides.

    Science.gov (United States)

    Chokhawala, Harshal A; Huang, Shengshu; Lau, Kam; Yu, Hai; Cheng, Jiansong; Thon, Vireak; Hurtado-Ziola, Nancy; Guerrero, Juan A; Varki, Ajit; Chen, Xi

    2008-09-19

    Although the vital roles of structures containing sialic acid in biomolecular recognition are well documented, limited information is available on how sialic acid structural modifications, sialyl linkages, and the underlying glycan structures affect the binding or the activity of sialic acid-recognizing proteins and related downstream biological processes. A novel combinatorial chemoenzymatic method has been developed for the highly efficient synthesis of biotinylated sialosides containing different sialic acid structures and different underlying glycans in 96-well plates from biotinylated sialyltransferase acceptors and sialic acid precursors. By transferring the reaction mixtures to NeutrAvidin-coated plates and assaying for the yields of enzymatic reactions using lectins recognizing sialyltransferase acceptors but not the sialylated products, the biotinylated sialoside products can be directly used, without purification, for high-throughput screening to quickly identify the ligand specificity of sialic acid-binding proteins. For a proof-of-principle experiment, 72 biotinylated alpha2,6-linked sialosides were synthesized in 96-well plates from 4 biotinylated sialyltransferase acceptors and 18 sialic acid precursors using a one-pot three-enzyme system. High-throughput screening assays performed in NeutrAvidin-coated microtiter plates show that whereas Sambucus nigra Lectin binds to alpha2,6-linked sialosides with high promiscuity, human Siglec-2 (CD22) is highly selective for a number of sialic acid structures and the underlying glycans in its sialoside ligands.

  1. High throughput, cell type-specific analysis of key proteins in human endometrial biopsies of women from fertile and infertile couples

    Science.gov (United States)

    Leach, Richard E.; Jessmon, Philip; Coutifaris, Christos; Kruger, Michael; Myers, Evan R.; Ali-Fehmi, Rouba; Carson, Sandra A.; Legro, Richard S.; Schlaff, William D.; Carr, Bruce R.; Steinkampf, Michael P.; Silva, Susan; Leppert, Phyllis C.; Giudice, Linda; Diamond, Michael P.; Armant, D. Randall

    2012-01-01

    BACKGROUND Although histological dating of endometrial biopsies provides little help for prediction or diagnosis of infertility, analysis of individual endometrial proteins, proteomic profiling and transcriptome analysis have suggested several biomarkers with altered expression arising from intrinsic abnormalities, inadequate stimulation by or in response to gonadal steroids or altered function due to systemic disorders. The objective of this study was to delineate the developmental dynamics of potentially important proteins in the secretory phase of the menstrual cycle, utilizing a collection of endometrial biopsies from women of fertile (n = 89) and infertile (n = 89) couples. METHODS AND RESULTS Progesterone receptor-B (PGR-B), leukemia inhibitory factor, glycodelin/progestagen-associated endometrial protein (PAEP), homeobox A10, heparin-binding EGF-like growth factor, calcitonin and chemokine ligand 14 (CXCL14) were measured using a high-throughput, quantitative immunohistochemical method. Significant cyclic and tissue-specific regulation was documented for each protein, as well as their dysregulation in women of infertile couples. Infertile patients demonstrated a delay early in the secretory phase in the decline of PGR-B (P localization provided important insights into the potential roles of these proteins in normal and pathological development of the endometrium that is not attainable from transcriptome analysis, establishing a basis for biomarker, diagnostic and targeted drug development for women with infertility. PMID:22215622

  2. Quantitative in vitro-to-in vivo extrapolation in a high-throughput environment

    International Nuclear Information System (INIS)

    Wetmore, Barbara A.

    2015-01-01

    High-throughput in vitro toxicity screening provides an efficient way to identify potential biological targets for environmental and industrial chemicals while conserving limited testing resources. However, reliance on the nominal chemical concentrations in these in vitro assays as an indicator of bioactivity may misrepresent potential in vivo effects of these chemicals due to differences in clearance, protein binding, bioavailability, and other pharmacokinetic factors. Development of high-throughput in vitro hepatic clearance and protein binding assays and refinement of quantitative in vitro-to-in vivo extrapolation (QIVIVE) methods have provided key tools to predict xenobiotic steady state pharmacokinetics. Using a process known as reverse dosimetry, knowledge of the chemical steady state behavior can be incorporated with HTS data to determine the external in vivo oral exposure needed to achieve internal blood concentrations equivalent to those eliciting bioactivity in the assays. These daily oral doses, known as oral equivalents, can be compared to chronic human exposure estimates to assess whether in vitro bioactivity would be expected at the dose-equivalent level of human exposure. This review will describe the use of QIVIVE methods in a high-throughput environment and the promise they hold in shaping chemical testing priorities and, potentially, high-throughput risk assessment strategies

  3. CrossCheck: an open-source web tool for high-throughput screen data analysis.

    Science.gov (United States)

    Najafov, Jamil; Najafov, Ayaz

    2017-07-19

    Modern high-throughput screening methods allow researchers to generate large datasets that potentially contain important biological information. However, oftentimes, picking relevant hits from such screens and generating testable hypotheses requires training in bioinformatics and the skills to efficiently perform database mining. There are currently no tools available to general public that allow users to cross-reference their screen datasets with published screen datasets. To this end, we developed CrossCheck, an online platform for high-throughput screen data analysis. CrossCheck is a centralized database that allows effortless comparison of the user-entered list of gene symbols with 16,231 published datasets. These datasets include published data from genome-wide RNAi and CRISPR screens, interactome proteomics and phosphoproteomics screens, cancer mutation databases, low-throughput studies of major cell signaling mediators, such as kinases, E3 ubiquitin ligases and phosphatases, and gene ontological information. Moreover, CrossCheck includes a novel database of predicted protein kinase substrates, which was developed using proteome-wide consensus motif searches. CrossCheck dramatically simplifies high-throughput screen data analysis and enables researchers to dig deep into the published literature and streamline data-driven hypothesis generation. CrossCheck is freely accessible as a web-based application at http://proteinguru.com/crosscheck.

  4. Global mapping of binding sites for Nrf2 identifies novel targets in cell survival response through ChIP-Seq profiling and network analysis

    Science.gov (United States)

    Malhotra, Deepti; Portales-Casamar, Elodie; Singh, Anju; Srivastava, Siddhartha; Arenillas, David; Happel, Christine; Shyr, Casper; Wakabayashi, Nobunao; Kensler, Thomas W.; Wasserman, Wyeth W.; Biswal, Shyam

    2010-01-01

    The Nrf2 (nuclear factor E2 p45-related factor 2) transcription factor responds to diverse oxidative and electrophilic environmental stresses by circumventing repression by Keap1, translocating to the nucleus, and activating cytoprotective genes. Nrf2 responses provide protection against chemical carcinogenesis, chronic inflammation, neurodegeneration, emphysema, asthma and sepsis in murine models. Nrf2 regulates the expression of a plethora of genes that detoxify oxidants and electrophiles and repair or remove damaged macromolecules, such as through proteasomal processing. However, many direct targets of Nrf2 remain undefined. Here, mouse embryonic fibroblasts (MEF) with either constitutive nuclear accumulation (Keap1−/−) or depletion (Nrf2−/−) of Nrf2 were utilized to perform chromatin-immunoprecipitation with parallel sequencing (ChIP-Seq) and global transcription profiling. This unique Nrf2 ChIP-Seq dataset is highly enriched for Nrf2-binding motifs. Integrating ChIP-Seq and microarray analyses, we identified 645 basal and 654 inducible direct targets of Nrf2, with 244 genes at the intersection. Modulated pathways in stress response and cell proliferation distinguish the inducible and basal programs. Results were confirmed in an in vivo stress model of cigarette smoke-exposed mice. This study reveals global circuitry of the Nrf2 stress response emphasizing Nrf2 as a central node in cell survival response. PMID:20460467

  5. High-throughput Transcriptome analysis, CAGE and beyond

    KAUST Repository

    Kodzius, Rimantas

    2008-11-25

    1. Current research - PhD work on discovery of new allergens - Postdoctoral work on Transcriptional Start Sites a) Tag based technologies allow higher throughput b) CAGE technology to define promoters c) CAGE data analysis to understand Transcription - Wo

  6. High-throughput Transcriptome analysis, CAGE and beyond

    KAUST Repository

    Kodzius, Rimantas

    2008-01-01

    1. Current research - PhD work on discovery of new allergens - Postdoctoral work on Transcriptional Start Sites a) Tag based technologies allow higher throughput b) CAGE technology to define promoters c) CAGE data analysis to understand Transcription - Wo

  7. Fully automated pipeline for detection of sex linked genes using RNA-Seq data.

    Science.gov (United States)

    Michalovova, Monika; Kubat, Zdenek; Hobza, Roman; Vyskot, Boris; Kejnovsky, Eduard

    2015-03-11

    Sex chromosomes present a genomic region which to some extent, differs between the genders of a single species. Reliable high-throughput methods for detection of sex chromosomes specific markers are needed, especially in species where genome information is limited. Next generation sequencing (NGS) opens the door for identification of unique sequences or searching for nucleotide polymorphisms between datasets. A combination of classical genetic segregation analysis along with RNA-Seq data can present an ideal tool to map and identify sex chromosome-specific expressed markers. To address this challenge, we established genetic cross of dioecious plant Rumex acetosa and generated RNA-Seq data from both parental generation and male and female offspring. We present a pipeline for detection of sex linked genes based on nucleotide polymorphism analysis. In our approach, tracking of nucleotide polymorphisms is carried out using a cross of preferably distant populations. For this reason, only 4 datasets are needed - reads from high-throughput sequencing platforms for parent generation (mother and father) and F1 generation (male and female progeny). Our pipeline uses custom scripts together with external assembly, mapping and variant calling software. Given the resource-intensive nature of the computation, servers with high capacity are a requirement. Therefore, in order to keep this pipeline easily accessible and reproducible, we implemented it in Galaxy - an open, web-based platform for data-intensive biomedical research. Our tools are present in the Galaxy Tool Shed, from which they can be installed to any local Galaxy instance. As an output of the pipeline, user gets a FASTA file with candidate transcriptionally active sex-linked genes, sorted by their relevance. At the same time, a BAM file with identified genes and alignment of reads is also provided. Thus, polymorphisms following segregation pattern can be easily visualized, which significantly enhances primer design

  8. Nebula--a web-server for advanced ChIP-seq data analysis.

    Science.gov (United States)

    Boeva, Valentina; Lermine, Alban; Barette, Camille; Guillouf, Christel; Barillot, Emmanuel

    2012-10-01

    ChIP-seq consists of chromatin immunoprecipitation and deep sequencing of the extracted DNA fragments. It is the technique of choice for accurate characterization of the binding sites of transcription factors and other DNA-associated proteins. We present a web service, Nebula, which allows inexperienced users to perform a complete bioinformatics analysis of ChIP-seq data. Nebula was designed for both bioinformaticians and biologists. It is based on the Galaxy open source framework. Galaxy already includes a large number of functionalities for mapping reads and peak calling. We added the following to Galaxy: (i) peak calling with FindPeaks and a module for immunoprecipitation quality control, (ii) de novo motif discovery with ChIPMunk, (iii) calculation of the density and the cumulative distribution of peak locations relative to gene transcription start sites, (iv) annotation of peaks with genomic features and (v) annotation of genes with peak information. Nebula generates the graphs and the enrichment statistics at each step of the process. During Steps 3-5, Nebula optionally repeats the analysis on a control dataset and compares these results with those from the main dataset. Nebula can also incorporate gene expression (or gene modulation) data during these steps. In summary, Nebula is an innovative web service that provides an advanced ChIP-seq analysis pipeline providing ready-to-publish results. Nebula is available at http://nebula.curie.fr/ Supplementary data are available at Bioinformatics online.

  9. Simultaneous characterization of cellular RNA structure and function with in-cell SHAPE-Seq.

    Science.gov (United States)

    Watters, Kyle E; Abbott, Timothy R; Lucks, Julius B

    2016-01-29

    Many non-coding RNAs form structures that interact with cellular machinery to control gene expression. A central goal of molecular and synthetic biology is to uncover design principles linking RNA structure to function to understand and engineer this relationship. Here we report a simple, high-throughput method called in-cell SHAPE-Seq that combines in-cell probing of RNA structure with a measurement of gene expression to simultaneously characterize RNA structure and function in bacterial cells. We use in-cell SHAPE-Seq to study the structure-function relationship of two RNA mechanisms that regulate translation in Escherichia coli. We find that nucleotides that participate in RNA-RNA interactions are highly accessible when their binding partner is absent and that changes in RNA structure due to RNA-RNA interactions can be quantitatively correlated to changes in gene expression. We also characterize the cellular structures of three endogenously expressed non-coding RNAs: 5S rRNA, RNase P and the btuB riboswitch. Finally, a comparison between in-cell and in vitro folded RNA structures revealed remarkable similarities for synthetic RNAs, but significant differences for RNAs that participate in complex cellular interactions. Thus, in-cell SHAPE-Seq represents an easily approachable tool for biologists and engineers to uncover relationships between sequence, structure and function of RNAs in the cell. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

  10. Targeted Capture and High-Throughput Sequencing Using Molecular Inversion Probes (MIPs).

    Science.gov (United States)

    Cantsilieris, Stuart; Stessman, Holly A; Shendure, Jay; Eichler, Evan E

    2017-01-01

    Molecular inversion probes (MIPs) in combination with massively parallel DNA sequencing represent a versatile, yet economical tool for targeted sequencing of genomic DNA. Several thousand genomic targets can be selectively captured using long oligonucleotides containing unique targeting arms and universal linkers. The ability to append sequencing adaptors and sample-specific barcodes allows large-scale pooling and subsequent high-throughput sequencing at relatively low cost per sample. Here, we describe a "wet bench" protocol detailing the capture and subsequent sequencing of >2000 genomic targets from 192 samples, representative of a single lane on the Illumina HiSeq 2000 platform.

  11. A high-density genetic map and QTL analysis of agronomic traits in foxtail millet [Setaria italica (L.) P. Beauv.] using RAD-seq.

    Science.gov (United States)

    Wang, Jun; Wang, Zhilan; Du, Xiaofen; Yang, Huiqing; Han, Fang; Han, Yuanhuai; Yuan, Feng; Zhang, Linyi; Peng, Shuzhong; Guo, Erhu

    2017-01-01

    Foxtail millet (Setaria italica), a very important grain crop in China, has become a new model plant for cereal crops and biofuel grasses. Although its reference genome sequence was released recently, quantitative trait loci (QTLs) controlling complex agronomic traits remains limited. The development of massively parallel genotyping methods and next-generation sequencing technologies provides an excellent opportunity for developing single-nucleotide polymorphisms (SNPs) for linkage map construction and QTL analysis of complex quantitative traits. In this study, a high-throughput and cost-effective RAD-seq approach was employed to generate a high-density genetic map for foxtail millet. A total of 2,668,587 SNP loci were detected according to the reference genome sequence; meanwhile, 9,968 SNP markers were used to genotype 124 F2 progenies derived from the cross between Hongmiaozhangu and Changnong35; a high-density genetic map spanning 1648.8 cM, with an average distance of 0.17 cM between adjacent markers was constructed; 11 major QTLs for eight agronomic traits were identified; five co-dominant DNA markers were developed. These findings will be of value for the identification of candidate genes and marker-assisted selection in foxtail millet.

  12. CASSys: an integrated software-system for the interactive analysis of ChIP-seq data

    Directory of Open Access Journals (Sweden)

    Alawi Malik

    2011-06-01

    Full Text Available The mapping of DNA-protein interactions is crucial for a full understanding of transcriptional regulation. Chromatin-immunoprecipitation followed bymassively parallel sequencing (ChIP-seq has become the standard technique for analyzing these interactions on a genome-wide scale. We have developed a software system called CASSys (ChIP-seq data Analysis Software System spanning all steps of ChIP-seq data analysis. It supersedes the laborious application of several single command line tools. CASSys provides functionality ranging from quality assessment and -control of short reads, over the mapping of reads against a reference genome (readmapping and the detection of enriched regions (peakdetection to various follow-up analyses. The latter are accessible via a state-of-the-art web interface and can be performed interactively by the user. The follow-up analyses allow for flexible user defined association of putative interaction sites with genes, visualization of their genomic context with an integrated genome browser, the detection of putative binding motifs, the identification of over-represented Gene Ontology-terms, pathway analysis and the visualization of interaction networks. The system is client-server based, accessible via a web browser and does not require any software installation on the client side. To demonstrate CASSys’s functionality we used the system for the complete data analysis of a publicly available Chip-seq study that investigated the role of the transcription factor estrogen receptor-α in breast cancer cells.

  13. JASPAR 2010: the greatly expanded open-access database of transcription factor binding profiles

    Science.gov (United States)

    Portales-Casamar, Elodie; Thongjuea, Supat; Kwon, Andrew T.; Arenillas, David; Zhao, Xiaobei; Valen, Eivind; Yusuf, Dimas; Lenhard, Boris; Wasserman, Wyeth W.; Sandelin, Albin

    2010-01-01

    JASPAR (http://jaspar.genereg.net) is the leading open-access database of matrix profiles describing the DNA-binding patterns of transcription factors (TFs) and other proteins interacting with DNA in a sequence-specific manner. Its fourth major release is the largest expansion of the core database to date: the database now holds 457 non-redundant, curated profiles. The new entries include the first batch of profiles derived from ChIP-seq and ChIP-chip whole-genome binding experiments, and 177 yeast TF binding profiles. The introduction of a yeast division brings the convenience of JASPAR to an active research community. As binding models are refined by newer data, the JASPAR database now uses versioning of matrices: in this release, 12% of the older models were updated to improved versions. Classification of TF families has been improved by adopting a new DNA-binding domain nomenclature. A curated catalog of mammalian TFs is provided, extending the use of the JASPAR profiles to additional TFs belonging to the same structural family. The changes in the database set the system ready for more rapid acquisition of new high-throughput data sources. Additionally, three new special collections provide matrix profile data produced by recent alternative high-throughput approaches. PMID:19906716

  14. SeqAn An efficient, generic C++ library for sequence analysis

    Directory of Open Access Journals (Sweden)

    Rausch Tobias

    2008-01-01

    Full Text Available Abstract Background The use of novel algorithmic techniques is pivotal to many important problems in life science. For example the sequencing of the human genome 1 would not have been possible without advanced assembly algorithms. However, owing to the high speed of technological progress and the urgent need for bioinformatics tools, there is a widening gap between state-of-the-art algorithmic techniques and the actual algorithmic components of tools that are in widespread use. Results To remedy this trend we propose the use of SeqAn, a library of efficient data types and algorithms for sequence analysis in computational biology. SeqAn comprises implementations of existing, practical state-of-the-art algorithmic components to provide a sound basis for algorithm testing and development. In this paper we describe the design and content of SeqAn and demonstrate its use by giving two examples. In the first example we show an application of SeqAn as an experimental platform by comparing different exact string matching algorithms. The second example is a simple version of the well-known MUMmer tool rewritten in SeqAn. Results indicate that our implementation is very efficient and versatile to use. Conclusion We anticipate that SeqAn greatly simplifies the rapid development of new bioinformatics tools by providing a collection of readily usable, well-designed algorithmic components which are fundamental for the field of sequence analysis. This leverages not only the implementation of new algorithms, but also enables a sound analysis and comparison of existing algorithms.

  15. Chromatographic Monoliths for High-Throughput Immunoaffinity Isolation of Transferrin from Human Plasma

    Directory of Open Access Journals (Sweden)

    Irena Trbojević-Akmačić

    2016-06-01

    Full Text Available Changes in protein glycosylation are related to different diseases and have a potential as diagnostic and prognostic disease biomarkers. Transferrin (Tf glycosylation changes are common marker for congenital disorders of glycosylation. However, biological interindividual variability of Tf N-glycosylation and genes involved in glycosylation regulation are not known. Therefore, high-throughput Tf isolation method and large scale glycosylation studies are needed in order to address these questions. Due to their unique chromatographic properties, the use of chromatographic monoliths enables very fast analysis cycle, thus significantly increasing sample preparation throughput. Here, we are describing characterization of novel immunoaffinity-based monolithic columns in a 96-well plate format for specific high-throughput purification of human Tf from blood plasma. We optimized the isolation and glycan preparation procedure for subsequent ultra performance liquid chromatography (UPLC analysis of Tf N-glycosylation and managed to increase the sensitivity for approximately three times compared to initial experimental conditions, with very good reproducibility. This work is licensed under a Creative Commons Attribution 4.0 International License.

  16. CMT: a constrained multi-level thresholding approach for ChIP-Seq data analysis.

    Directory of Open Access Journals (Sweden)

    Iman Rezaeian

    Full Text Available Genome-wide profiling of DNA-binding proteins using ChIP-Seq has emerged as an alternative to ChIP-chip methods. ChIP-Seq technology offers many advantages over ChIP-chip arrays, including but not limited to less noise, higher resolution, and more coverage. Several algorithms have been developed to take advantage of these abilities and find enriched regions by analyzing ChIP-Seq data. However, the complexity of analyzing various patterns of ChIP-Seq signals still needs the development of new algorithms. Most current algorithms use various heuristics to detect regions accurately. However, despite how many formulations are available, it is still difficult to accurately determine individual peaks corresponding to each binding event. We developed Constrained Multi-level Thresholding (CMT, an algorithm used to detect enriched regions on ChIP-Seq data. CMT employs a constraint-based module that can target regions within a specific range. We show that CMT has higher accuracy in detecting enriched regions (peaks by objectively assessing its performance relative to other previously proposed peak finders. This is shown by testing three algorithms on the well-known FoxA1 Data set, four transcription factors (with a total of six antibodies for Drosophila melanogaster and the H3K4ac antibody dataset.

  17. Supplementary Material for Finding the Stable Structures of N1-xWX with an Ab-initio High-Throughput Approach

    Science.gov (United States)

    2015-05-08

    Supplementary material for “Finding the stable structures of N1−xWX with an ab - initio high-throughput approach” Michael J. Mehl∗ Center for...AND SUBTITLE Supplementary Material for ’Finding the Stable Structures of N1-xWX with an ab - initio High-throughput Approach’ 5a. CONTRACT NUMBER 5b...and J. Hafner, Ab initio molecular dynamics for open-shell transition metals, Phys. Rev. B 48, 13115–13118 (1993). 2 G. Kresse and J. Hafner, Ab initio

  18. Optimization and high-throughput screening of antimicrobial peptides.

    Science.gov (United States)

    Blondelle, Sylvie E; Lohner, Karl

    2010-01-01

    While a well-established process for lead compound discovery in for-profit companies, high-throughput screening is becoming more popular in basic and applied research settings in academia. The development of combinatorial libraries combined with easy and less expensive access to new technologies have greatly contributed to the implementation of high-throughput screening in academic laboratories. While such techniques were earlier applied to simple assays involving single targets or based on binding affinity, they have now been extended to more complex systems such as whole cell-based assays. In particular, the urgent need for new antimicrobial compounds that would overcome the rapid rise of drug-resistant microorganisms, where multiple target assays or cell-based assays are often required, has forced scientists to focus onto high-throughput technologies. Based on their existence in natural host defense systems and their different mode of action relative to commercial antibiotics, antimicrobial peptides represent a new hope in discovering novel antibiotics against multi-resistant bacteria. The ease of generating peptide libraries in different formats has allowed a rapid adaptation of high-throughput assays to the search for novel antimicrobial peptides. Similarly, the availability nowadays of high-quantity and high-quality antimicrobial peptide data has permitted the development of predictive algorithms to facilitate the optimization process. This review summarizes the various library formats that lead to de novo antimicrobial peptide sequences as well as the latest structural knowledge and optimization processes aimed at improving the peptides selectivity.

  19. Integration of Genome-Wide TF Binding and Gene Expression Data to Characterize Gene Regulatory Networks in Plant Development.

    Science.gov (United States)

    Chen, Dijun; Kaufmann, Kerstin

    2017-01-01

    Key transcription factors (TFs) controlling the morphogenesis of flowers and leaves have been identified in the model plant Arabidopsis thaliana. Recent genome-wide approaches based on chromatin immunoprecipitation (ChIP) followed by high-throughput DNA sequencing (ChIP-seq) enable systematic identification of genome-wide TF binding sites (TFBSs) of these regulators. Here, we describe a computational pipeline for analyzing ChIP-seq data to identify TFBSs and to characterize gene regulatory networks (GRNs) with applications to the regulatory studies of flower development. In particular, we provide step-by-step instructions on how to download, analyze, visualize, and integrate genome-wide data in order to construct GRNs for beginners of bioinformatics. The practical guide presented here is ready to apply to other similar ChIP-seq datasets to characterize GRNs of interest.

  20. Genome-wide binding and transcriptome analysis of human farnesoid X receptor in primary human hepatocytes.

    Directory of Open Access Journals (Sweden)

    Le Zhan

    Full Text Available Farnesoid X receptor (FXR, NR1H4 is a ligand-activated transcription factor, belonging to the nuclear receptor superfamily. FXR is highly expressed in the liver and is essential in regulating bile acid homeostasis. FXR deficiency is implicated in numerous liver diseases and mice with modulation of FXR have been used as animal models to study liver physiology and pathology. We have reported genome-wide binding of FXR in mice by chromatin immunoprecipitation - deep sequencing (ChIP-seq, with results indicating that FXR may be involved in regulating diverse pathways in liver. However, limited information exists for the functions of human FXR and the suitability of using murine models to study human FXR functions.In the current study, we performed ChIP-seq in primary human hepatocytes (PHHs treated with a synthetic FXR agonist, GW4064 or DMSO control. In parallel, RNA deep sequencing (RNA-seq and RNA microarray were performed for GW4064 or control treated PHHs and wild type mouse livers, respectively.ChIP-seq showed similar profiles of genome-wide FXR binding in humans and mice in terms of motif analysis and pathway prediction. However, RNA-seq and microarray showed more different transcriptome profiles between PHHs and mouse livers upon GW4064 treatment.In summary, we have established genome-wide human FXR binding and transcriptome profiles. These results will aid in determining the human FXR functions, as well as judging to what level the mouse models could be used to study human FXR functions.

  1. Integrated analysis of RNA-binding protein complexes using in vitro selection and high-throughput sequencing and sequence specificity landscapes (SEQRS).

    Science.gov (United States)

    Lou, Tzu-Fang; Weidmann, Chase A; Killingsworth, Jordan; Tanaka Hall, Traci M; Goldstrohm, Aaron C; Campbell, Zachary T

    2017-04-15

    RNA-binding proteins (RBPs) collaborate to control virtually every aspect of RNA function. Tremendous progress has been made in the area of global assessment of RBP specificity using next-generation sequencing approaches both in vivo and in vitro. Understanding how protein-protein interactions enable precise combinatorial regulation of RNA remains a significant problem. Addressing this challenge requires tools that can quantitatively determine the specificities of both individual proteins and multimeric complexes in an unbiased and comprehensive way. One approach utilizes in vitro selection, high-throughput sequencing, and sequence-specificity landscapes (SEQRS). We outline a SEQRS experiment focused on obtaining the specificity of a multi-protein complex between Drosophila RBPs Pumilio (Pum) and Nanos (Nos). We discuss the necessary controls in this type of experiment and examine how the resulting data can be complemented with structural and cell-based reporter assays. Additionally, SEQRS data can be integrated with functional genomics data to uncover biological function. Finally, we propose extensions of the technique that will enhance our understanding of multi-protein regulatory complexes assembled onto RNA. Copyright © 2016 Elsevier Inc. All rights reserved.

  2. SNP discovery in the bovine milk transcriptome using RNA-Seq technology.

    Science.gov (United States)

    Cánovas, Angela; Rincon, Gonzalo; Islas-Trejo, Alma; Wickramasinghe, Saumya; Medrano, Juan F

    2010-12-01

    High-throughput sequencing of RNA (RNA-Seq) was developed primarily to analyze global gene expression in different tissues. However, it also is an efficient way to discover coding SNPs. The objective of this study was to perform a SNP discovery analysis in the milk transcriptome using RNA-Seq. Seven milk samples from Holstein cows were analyzed by sequencing cDNAs using the Illumina Genome Analyzer system. We detected 19,175 genes expressed in milk samples corresponding to approximately 70% of the total number of genes analyzed. The SNP detection analysis revealed 100,734 SNPs in Holstein samples, and a large number of those corresponded to differences between the Holstein breed and the Hereford bovine genome assembly Btau4.0. The number of polymorphic SNPs within Holstein cows was 33,045. The accuracy of RNA-Seq SNP discovery was tested by comparing SNPs detected in a set of 42 candidate genes expressed in milk that had been resequenced earlier using Sanger sequencing technology. Seventy of 86 SNPs were detected using both RNA-Seq and Sanger sequencing technologies. The KASPar Genotyping System was used to validate unique SNPs found by RNA-Seq but not observed by Sanger technology. Our results confirm that analyzing the transcriptome using RNA-Seq technology is an efficient and cost-effective method to identify SNPs in transcribed regions. This study creates guidelines to maximize the accuracy of SNP discovery and prevention of false-positive SNP detection, and provides more than 33,000 SNPs located in coding regions of genes expressed during lactation that can be used to develop genotyping platforms to perform marker-trait association studies in Holstein cattle.

  3. High-Throughput Method for Strontium Isotope Analysis by Multi-Collector-Inductively Coupled Plasma-Mass Spectrometer

    Energy Technology Data Exchange (ETDEWEB)

    Wall, Andrew J. [National Energy Technology Lab. (NETL), Pittsburgh, PA, (United States); Capo, Rosemary C. [Univ. of Pittsburgh, PA (United States); Stewart, Brian W. [Univ. of Pittsburgh, PA (United States); Phan, Thai T. [Univ. of Pittsburgh, PA (United States); Jain, Jinesh C. [National Energy Technology Lab. (NETL), Pittsburgh, PA, (United States); Hakala, Alexandra [National Energy Technology Lab. (NETL), Pittsburgh, PA, (United States); Guthrie, George D. [National Energy Technology Lab. (NETL), Pittsburgh, PA, (United States)

    2016-09-22

    This technical report presents the details of the Sr column configuration and the high-throughput Sr separation protocol. Data showing the performance of the method as well as the best practices for optimizing Sr isotope analysis by MC-ICP-MS is presented. Lastly, this report offers tools for data handling and data reduction of Sr isotope results from the Thermo Scientific Neptune software to assist in data quality assurance, which help avoid issues of data glut associated with high sample throughput rapid analysis.

  4. High-Throughput Method for Strontium Isotope Analysis by Multi-Collector-Inductively Coupled Plasma-Mass Spectrometer

    Energy Technology Data Exchange (ETDEWEB)

    Hakala, Jacqueline Alexandra [National Energy Technology Lab. (NETL), Morgantown, WV (United States)

    2016-11-22

    This technical report presents the details of the Sr column configuration and the high-throughput Sr separation protocol. Data showing the performance of the method as well as the best practices for optimizing Sr isotope analysis by MC-ICP-MS is presented. Lastly, this report offers tools for data handling and data reduction of Sr isotope results from the Thermo Scientific Neptune software to assist in data quality assurance, which help avoid issues of data glut associated with high sample throughput rapid analysis.

  5. PCR cycles above routine numbers do not compromise high-throughput DNA barcoding results.

    Science.gov (United States)

    Vierna, J; Doña, J; Vizcaíno, A; Serrano, D; Jovani, R

    2017-10-01

    High-throughput DNA barcoding has become essential in ecology and evolution, but some technical questions still remain. Increasing the number of PCR cycles above the routine 20-30 cycles is a common practice when working with old-type specimens, which provide little amounts of DNA, or when facing annealing issues with the primers. However, increasing the number of cycles can raise the number of artificial mutations due to polymerase errors. In this work, we sequenced 20 COI libraries in the Illumina MiSeq platform. Libraries were prepared with 40, 45, 50, 55, and 60 PCR cycles from four individuals belonging to four species of four genera of cephalopods. We found no relationship between the number of PCR cycles and the number of mutations despite using a nonproofreading polymerase. Moreover, even when using a high number of PCR cycles, the resulting number of mutations was low enough not to be an issue in the context of high-throughput DNA barcoding (but may still remain an issue in DNA metabarcoding due to chimera formation). We conclude that the common practice of increasing the number of PCR cycles should not negatively impact the outcome of a high-throughput DNA barcoding study in terms of the occurrence of point mutations.

  6. High-throughput sequence alignment using Graphics Processing Units

    Directory of Open Access Journals (Sweden)

    Trapnell Cole

    2007-12-01

    Full Text Available Abstract Background The recent availability of new, less expensive high-throughput DNA sequencing technologies has yielded a dramatic increase in the volume of sequence data that must be analyzed. These data are being generated for several purposes, including genotyping, genome resequencing, metagenomics, and de novo genome assembly projects. Sequence alignment programs such as MUMmer have proven essential for analysis of these data, but researchers will need ever faster, high-throughput alignment tools running on inexpensive hardware to keep up with new sequence technologies. Results This paper describes MUMmerGPU, an open-source high-throughput parallel pairwise local sequence alignment program that runs on commodity Graphics Processing Units (GPUs in common workstations. MUMmerGPU uses the new Compute Unified Device Architecture (CUDA from nVidia to align multiple query sequences against a single reference sequence stored as a suffix tree. By processing the queries in parallel on the highly parallel graphics card, MUMmerGPU achieves more than a 10-fold speedup over a serial CPU version of the sequence alignment kernel, and outperforms the exact alignment component of MUMmer on a high end CPU by 3.5-fold in total application time when aligning reads from recent sequencing projects using Solexa/Illumina, 454, and Sanger sequencing technologies. Conclusion MUMmerGPU is a low cost, ultra-fast sequence alignment program designed to handle the increasing volume of data produced by new, high-throughput sequencing technologies. MUMmerGPU demonstrates that even memory-intensive applications can run significantly faster on the relatively low-cost GPU than on the CPU.

  7. Elucidating the 16S rRNA 3' boundaries and defining optimal SD/aSD pairing in Escherichia coli and Bacillus subtilis using RNA-Seq data.

    Science.gov (United States)

    Wei, Yulong; Silke, Jordan R; Xia, Xuhua

    2017-12-15

    Bacterial translation initiation is influenced by base pairing between the Shine-Dalgarno (SD) sequence in the 5' UTR of mRNA and the anti-SD (aSD) sequence at the free 3' end of the 16S rRNA (3' TAIL) due to: 1) the SD/aSD sequence binding location and 2) SD/aSD binding affinity. In order to understand what makes an SD/aSD interaction optimal, we must define: 1) terminus of the 3' TAIL and 2) extent of the core aSD sequence within the 3' TAIL. Our approach to characterize these components in Escherichia coli and Bacillus subtilis involves 1) mapping the 3' boundary of the mature 16S rRNA using high-throughput RNA sequencing (RNA-Seq), and 2) identifying the segment within the 3' TAIL that is strongly preferred in SD/aSD pairing. Using RNA-Seq data, we resolve previous discrepancies in the reported 3' TAIL in B. subtilis and recovered the established 3' TAIL in E. coli. Furthermore, we extend previous studies to suggest that both highly and lowly expressed genes favor SD sequences with intermediate binding affinity, but this trend is exclusive to SD sequences that complement the core aSD sequences defined herein.

  8. Immunoglobulin G (IgG) Fab glycosylation analysis using a new mass spectrometric high-throughput profiling method reveals pregnancy-associated changes.

    Science.gov (United States)

    Bondt, Albert; Rombouts, Yoann; Selman, Maurice H J; Hensbergen, Paul J; Reiding, Karli R; Hazes, Johanna M W; Dolhain, Radboud J E M; Wuhrer, Manfred

    2014-11-01

    The N-linked glycosylation of the constant fragment (Fc) of immunoglobulin G has been shown to change during pathological and physiological events and to strongly influence antibody inflammatory properties. In contrast, little is known about Fab-linked N-glycosylation, carried by ∼ 20% of IgG. Here we present a high-throughput workflow to analyze Fab and Fc glycosylation of polyclonal IgG purified from 5 μl of serum. We were able to detect and quantify 37 different N-glycans by means of MALDI-TOF-MS analysis in reflectron positive mode using a novel linkage-specific derivatization of sialic acid. This method was applied to 174 samples of a pregnancy cohort to reveal Fab glycosylation features and their change with pregnancy. Data analysis revealed marked differences between Fab and Fc glycosylation, especially in the levels of galactosylation and sialylation, incidence of bisecting GlcNAc, and presence of high mannose structures, which were all higher in the Fab portion than the Fc, whereas Fc showed higher levels of fucosylation. Additionally, we observed several changes during pregnancy and after delivery. Fab N-glycan sialylation was increased and bisection was decreased relative to postpartum time points, and nearly complete galactosylation of Fab glycans was observed throughout. Fc glycosylation changes were similar to results described before, with increased galactosylation and sialylation and decreased bisection during pregnancy. We expect that the parallel analysis of IgG Fab and Fc, as set up in this paper, will be important for unraveling roles of these glycans in (auto)immunity, which may be mediated via recognition by human lectins or modulation of antigen binding. © 2014 by The American Society for Biochemistry and Molecular Biology, Inc.

  9. Immunoglobulin G (IgG) Fab Glycosylation Analysis Using a New Mass Spectrometric High-throughput Profiling Method Reveals Pregnancy-associated Changes*

    Science.gov (United States)

    Bondt, Albert; Rombouts, Yoann; Selman, Maurice H. J.; Hensbergen, Paul J.; Reiding, Karli R.; Hazes, Johanna M. W.; Dolhain, Radboud J. E. M.; Wuhrer, Manfred

    2014-01-01

    The N-linked glycosylation of the constant fragment (Fc) of immunoglobulin G has been shown to change during pathological and physiological events and to strongly influence antibody inflammatory properties. In contrast, little is known about Fab-linked N-glycosylation, carried by ∼20% of IgG. Here we present a high-throughput workflow to analyze Fab and Fc glycosylation of polyclonal IgG purified from 5 μl of serum. We were able to detect and quantify 37 different N-glycans by means of MALDI-TOF-MS analysis in reflectron positive mode using a novel linkage-specific derivatization of sialic acid. This method was applied to 174 samples of a pregnancy cohort to reveal Fab glycosylation features and their change with pregnancy. Data analysis revealed marked differences between Fab and Fc glycosylation, especially in the levels of galactosylation and sialylation, incidence of bisecting GlcNAc, and presence of high mannose structures, which were all higher in the Fab portion than the Fc, whereas Fc showed higher levels of fucosylation. Additionally, we observed several changes during pregnancy and after delivery. Fab N-glycan sialylation was increased and bisection was decreased relative to postpartum time points, and nearly complete galactosylation of Fab glycans was observed throughout. Fc glycosylation changes were similar to results described before, with increased galactosylation and sialylation and decreased bisection during pregnancy. We expect that the parallel analysis of IgG Fab and Fc, as set up in this paper, will be important for unraveling roles of these glycans in (auto)immunity, which may be mediated via recognition by human lectins or modulation of antigen binding. PMID:25004930

  10. ChIPBase: a database for decoding the transcriptional regulation of long non-coding RNA and microRNA genes from ChIP-Seq data.

    Science.gov (United States)

    Yang, Jian-Hua; Li, Jun-Hao; Jiang, Shan; Zhou, Hui; Qu, Liang-Hu

    2013-01-01

    Long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) represent two classes of important non-coding RNAs in eukaryotes. Although these non-coding RNAs have been implicated in organismal development and in various human diseases, surprisingly little is known about their transcriptional regulation. Recent advances in chromatin immunoprecipitation with next-generation DNA sequencing (ChIP-Seq) have provided methods of detecting transcription factor binding sites (TFBSs) with unprecedented sensitivity. In this study, we describe ChIPBase (http://deepbase.sysu.edu.cn/chipbase/), a novel database that we have developed to facilitate the comprehensive annotation and discovery of transcription factor binding maps and transcriptional regulatory relationships of lncRNAs and miRNAs from ChIP-Seq data. The current release of ChIPBase includes high-throughput sequencing data that were generated by 543 ChIP-Seq experiments in diverse tissues and cell lines from six organisms. By analysing millions of TFBSs, we identified tens of thousands of TF-lncRNA and TF-miRNA regulatory relationships. Furthermore, two web-based servers were developed to annotate and discover transcriptional regulatory relationships of lncRNAs and miRNAs from ChIP-Seq data. In addition, we developed two genome browsers, deepView and genomeView, to provide integrated views of multidimensional data. Moreover, our web implementation supports diverse query types and the exploration of TFs, lncRNAs, miRNAs, gene ontologies and pathways.

  11. MetaUniDec: High-Throughput Deconvolution of Native Mass Spectra

    Science.gov (United States)

    Reid, Deseree J.; Diesing, Jessica M.; Miller, Matthew A.; Perry, Scott M.; Wales, Jessica A.; Montfort, William R.; Marty, Michael T.

    2018-04-01

    The expansion of native mass spectrometry (MS) methods for both academic and industrial applications has created a substantial need for analysis of large native MS datasets. Existing software tools are poorly suited for high-throughput deconvolution of native electrospray mass spectra from intact proteins and protein complexes. The UniDec Bayesian deconvolution algorithm is uniquely well suited for high-throughput analysis due to its speed and robustness but was previously tailored towards individual spectra. Here, we optimized UniDec for deconvolution, analysis, and visualization of large data sets. This new module, MetaUniDec, centers around a hierarchical data format 5 (HDF5) format for storing datasets that significantly improves speed, portability, and file size. It also includes code optimizations to improve speed and a new graphical user interface for visualization, interaction, and analysis of data. To demonstrate the utility of MetaUniDec, we applied the software to analyze automated collision voltage ramps with a small bacterial heme protein and large lipoprotein nanodiscs. Upon increasing collisional activation, bacterial heme-nitric oxide/oxygen binding (H-NOX) protein shows a discrete loss of bound heme, and nanodiscs show a continuous loss of lipids and charge. By using MetaUniDec to track changes in peak area or mass as a function of collision voltage, we explore the energetic profile of collisional activation in an ultra-high mass range Orbitrap mass spectrometer. [Figure not available: see fulltext.

  12. Limitations and possibilities of low cell number ChIP-seq

    Directory of Open Access Journals (Sweden)

    Gilfillan Gregor D

    2012-11-01

    Full Text Available Abstract Background Chromatin immunoprecipitation coupled with high-throughput DNA sequencing (ChIP-seq offers high resolution, genome-wide analysis of DNA-protein interactions. However, current standard methods require abundant starting material in the range of 1–20 million cells per immunoprecipitation, and remain a bottleneck to the acquisition of biologically relevant epigenetic data. Using a ChIP-seq protocol optimised for low cell numbers (down to 100,000 cells / IP, we examined the performance of the ChIP-seq technique on a series of decreasing cell numbers. Results We present an enhanced native ChIP-seq method tailored to low cell numbers that represents a 200-fold reduction in input requirements over existing protocols. The protocol was tested over a range of starting cell numbers covering three orders of magnitude, enabling determination of the lower limit of the technique. At low input cell numbers, increased levels of unmapped and duplicate reads reduce the number of unique reads generated, and can drive up sequencing costs and affect sensitivity if ChIP is attempted from too few cells. Conclusions The optimised method presented here considerably reduces the input requirements for performing native ChIP-seq. It extends the applicability of the technique to isolated primary cells and rare cell populations (e.g. biobank samples, stem cells, and in many cases will alleviate the need for cell culture and any associated alteration of epigenetic marks. However, this study highlights a challenge inherent to ChIP-seq from low cell numbers: as cell input numbers fall, levels of unmapped sequence reads and PCR-generated duplicate reads rise. We discuss a number of solutions to overcome the effects of reducing cell number that may aid further improvements to ChIP performance.

  13. High-throughput screening with micro-x-ray fluorescence

    International Nuclear Information System (INIS)

    Havrilla, George J.; Miller, Thomasin C.

    2005-01-01

    Micro-x-ray fluorescence (MXRF) is a useful characterization tool for high-throughput screening of combinatorial libraries. Due to the increasing threat of use of chemical warfare (CW) agents both in military actions and against civilians by terrorist extremists, there is a strong push to improve existing methods and develop means for the detection of a broad spectrum of CW agents in a minimal amount of time to increase national security. This paper describes a combinatorial high-throughput screening technique for CW receptor discovery to aid in sensor development. MXRF can screen materials for elemental composition at the mesoscale level (tens to hundreds of micrometers). The key aspect of this work is the use of commercial MXRF instrumentation coupled with the inherent heteroatom elements within the target molecules of the combinatorial reaction to provide rapid and specific identification of lead species. The method is demonstrated by screening an 11-mer oligopeptide library for selective binding of the degradation products of the nerve agent VX. The identified oligopeptides can be used as selective molecular receptors for sensor development. The MXRF screening method is nondestructive, requires minimal sample preparation or special tags for analysis, and the screening time depends on the desired sensitivity

  14. Gene expression change in human dental pulp cells exposed to a low-level toxic concentration of triethylene glycol dimethacrylate: an RNA-seq analysis.

    Science.gov (United States)

    Cho, Sung-Geun; Lee, Jin-Woo; Heo, Jung Sun; Kim, Sun-Young

    2014-09-01

    Dental composite resin restoration for defective tooth may lead unpolymerized resin monomers to be leached into dental pulp tissue. The aim of this study was to investigate the early gene expression change over time of human dental pulp cells (HDPCs) treated with a low-level toxic concentration of Triethylene Glycol Dimethacrylate (TEGDMA), a common dental resin monomer, by adopting the novel high-throughput transcriptome analysis of RNA-seq. The low-level toxic concentration of TEGDMA was determined through MTT assays with serially diluted concentrations. After the HDPCs were exposed to TEGDMA for 6, 12, 24 or 48 hr, the total RNA of the samples was prepared for RNA-seq. qRT-PCR for several genes was performed for validation of RNA-seq results. In the treated group, 1280 genes were differentially expressed compared with the control group. Five patterns of time-series gene expression profiles were identified through k-means clustering analysis. Angiogenesis, cell adhesion and migration, extracellular matrix organization, response to extracellular stimulus, inflammatory response and mineralization-related process were major gene ontology terms in functional annotation clustering. HMOX1, OSGIN1, SMN2, SRXN1 AKR1C1, SPP1 and TOMM40L were highly up-regulated genes, and WRAP53 and CCL2 were highly down-regulated genes over time. qRT-PCR for several genes exhibited a high level of agreement with RNA-seq. TEGDMA induced the HDPCs to show massive and dynamic gene expression changes over time. The previously suggested toxic mechanism of TEGDMA was not only verified, but new genes whose functions have yet to be determined were also found. © 2014 Nordic Association for the Publication of BCPT (former Nordic Pharmacological Society).

  15. Joint modeling of ChIP-seq data via a Markov random field model

    NARCIS (Netherlands)

    Bao, Yanchun; Vinciotti, Veronica; Wit, Ernst; 't Hoen, Peter A C

    Chromatin ImmunoPrecipitation-sequencing (ChIP-seq) experiments have now become routine in biology for the detection of protein-binding sites. In this paper, we present a Markov random field model for the joint analysis of multiple ChIP-seq experiments. The proposed model naturally accounts for

  16. Simultaneous SNP identification and assessment of allele-specific bias from ChIP-seq data

    Directory of Open Access Journals (Sweden)

    Ni Yunyun

    2012-09-01

    Full Text Available Abstract Background Single nucleotide polymorphisms (SNPs have been associated with many aspects of human development and disease, and many non-coding SNPs associated with disease risk are presumed to affect gene regulation. We have previously shown that SNPs within transcription factor binding sites can affect transcription factor binding in an allele-specific and heritable manner. However, such analysis has relied on prior whole-genome genotypes provided by large external projects such as HapMap and the 1000 Genomes Project. This requirement limits the study of allele-specific effects of SNPs in primary patient samples from diseases of interest, where complete genotypes are not readily available. Results In this study, we show that we are able to identify SNPs de novo and accurately from ChIP-seq data generated in the ENCODE Project. Our de novo identified SNPs from ChIP-seq data are highly concordant with published genotypes. Independent experimental verification of more than 100 sites estimates our false discovery rate at less than 5%. Analysis of transcription factor binding at de novo identified SNPs revealed widespread heritable allele-specific binding, confirming previous observations. SNPs identified from ChIP-seq datasets were significantly enriched for disease-associated variants, and we identified dozens of allele-specific binding events in non-coding regions that could distinguish between disease and normal haplotypes. Conclusions Our approach combines SNP discovery, genotyping and allele-specific analysis, but is selectively focused on functional regulatory elements occupied by transcription factors or epigenetic marks, and will therefore be valuable for identifying the functional regulatory consequences of non-coding SNPs in primary disease samples.

  17. RNA-Seq-Based Transcript Structure Analysis with TrBorderExt.

    Science.gov (United States)

    Wang, Yejun; Sun, Ming-An; White, Aaron P

    2018-01-01

    RNA-Seq has become a routine strategy for genome-wide gene expression comparisons in bacteria. Despite lower resolution in transcript border parsing compared with dRNA-Seq, TSS-EMOTE, Cappable-seq, Term-seq, and others, directional RNA-Seq still illustrates its advantages: low cost, quantification and transcript border analysis with a medium resolution (±10-20 nt). To facilitate mining of directional RNA-Seq datasets especially with respect to transcript structure analysis, we developed a tool, TrBorderExt, which can parse transcript start sites and termination sites accurately in bacteria. A detailed protocol is described in this chapter for how to use the software package step by step to identify bacterial transcript borders from raw RNA-Seq data. The package was developed with Perl and R programming languages, and is accessible freely through the website: http://www.szu-bioinf.org/TrBorderExt .

  18. Applications of ambient mass spectrometry in high-throughput screening.

    Science.gov (United States)

    Li, Li-Ping; Feng, Bao-Sheng; Yang, Jian-Wang; Chang, Cui-Lan; Bai, Yu; Liu, Hu-Wei

    2013-06-07

    The development of rapid screening and identification techniques is of great importance for drug discovery, doping control, forensic identification, food safety and quality control. Ambient mass spectrometry (AMS) allows rapid and direct analysis of various samples in open air with little sample preparation. Recently, its applications in high-throughput screening have been in rapid progress. During the past decade, various ambient ionization techniques have been developed and applied in high-throughput screening. This review discusses typical applications of AMS, including DESI (desorption electrospray ionization), DART (direct analysis in real time), EESI (extractive electrospray ionization), etc., in high-throughput screening (HTS).

  19. Meta-Analysis of High-Throughput Datasets Reveals Cellular Responses Following Hemorrhagic Fever Virus Infection

    Directory of Open Access Journals (Sweden)

    Gavin C. Bowick

    2011-05-01

    Full Text Available The continuing use of high-throughput assays to investigate cellular responses to infection is providing a large repository of information. Due to the large number of differentially expressed transcripts, often running into the thousands, the majority of these data have not been thoroughly investigated. Advances in techniques for the downstream analysis of high-throughput datasets are providing additional methods for the generation of additional hypotheses for further investigation. The large number of experimental observations, combined with databases that correlate particular genes and proteins with canonical pathways, functions and diseases, allows for the bioinformatic exploration of functional networks that may be implicated in replication or pathogenesis. Herein, we provide an example of how analysis of published high-throughput datasets of cellular responses to hemorrhagic fever virus infection can generate additional functional data. We describe enrichment of genes involved in metabolism, post-translational modification and cardiac damage; potential roles for specific transcription factors and a conserved involvement of a pathway based around cyclooxygenase-2. We believe that these types of analyses can provide virologists with additional hypotheses for continued investigation.

  20. High Throughput Analysis of Photocatalytic Water Purification

    NARCIS (Netherlands)

    Sobral Romao, J.I.; Baiao Barata, David; Habibovic, Pamela; Mul, Guido; Baltrusaitis, Jonas

    2014-01-01

    We present a novel high throughput photocatalyst efficiency assessment method based on 96-well microplates and UV-Vis spectroscopy. We demonstrate the reproducibility of the method using methyl orange (MO) decomposition, and compare kinetic data obtained with those provided in the literature for

  1. High-Throughput Investigation of a Lead-Free AlN-Based Piezoelectric Material, (Mg,Hf)xAl1-xN.

    Science.gov (United States)

    Nguyen, Hung H; Oguchi, Hiroyuki; Van Minh, Le; Kuwano, Hiroki

    2017-06-12

    We conducted a high-throughput investigation of the fundamental properties of (Mg,Hf) x Al 1-x N thin films (0 piezoelectric materials. For the high-throughput investigation, we prepared composition-gradient (Mg,Hf) x Al 1-x N films grown on a Si(100) substrate at 600 °C by cosputtering AlN and MgHf targets. To measure the properties of the various compositions at different positions within a single sample, we used characterization techniques with spatial resolution. X-ray diffraction (XRD) with a beam spot diameter of 1.0 mm verified that Mg and Hf had substituted into the Al sites and caused an elongation of the c-axis of AlN from 5.00 Å for x = 0 to 5.11 Å for x = 0.24. In addition, the uniaxial crystal orientation and high crystallinity required for piezoelectric materials to be used as application devices were confirmed. The piezoelectric response microscope indicated that this c-axis elongation increased the piezoelectric coefficient almost linearly from 1.48 pm/V for x = 0 to 5.19 pm/V for x = 0.24. The dielectric constants of (Mg,Hf) x Al 1-x N were investigated using parallel plate capacitor structures with ∼0.07 mm 2 electrodes and showed a slight increase by substitution. These results verified that (Mg,Hf) x Al 1-x N is a promising material for piezoelectric-based application devices, especially for vibrational energy harvesters.

  2. A structured sparse regression method for estimating isoform expression level from multi-sample RNA-seq data.

    Science.gov (United States)

    Zhang, L; Liu, X J

    2016-06-03

    With the rapid development of next-generation high-throughput sequencing technology, RNA-seq has become a standard and important technique for transcriptome analysis. For multi-sample RNA-seq data, the existing expression estimation methods usually deal with each single-RNA-seq sample, and ignore that the read distributions are consistent across multiple samples. In the current study, we propose a structured sparse regression method, SSRSeq, to estimate isoform expression using multi-sample RNA-seq data. SSRSeq uses a non-parameter model to capture the general tendency of non-uniformity read distribution for all genes across multiple samples. Additionally, our method adds a structured sparse regularization, which not only incorporates the sparse specificity between a gene and its corresponding isoform expression levels, but also reduces the effects of noisy reads, especially for lowly expressed genes and isoforms. Four real datasets were used to evaluate our method on isoform expression estimation. Compared with other popular methods, SSRSeq reduced the variance between multiple samples, and produced more accurate isoform expression estimations, and thus more meaningful biological interpretations.

  3. High-Throughput Next-Generation Sequencing of Polioviruses

    Science.gov (United States)

    Montmayeur, Anna M.; Schmidt, Alexander; Zhao, Kun; Magaña, Laura; Iber, Jane; Castro, Christina J.; Chen, Qi; Henderson, Elizabeth; Ramos, Edward; Shaw, Jing; Tatusov, Roman L.; Dybdahl-Sissoko, Naomi; Endegue-Zanga, Marie Claire; Adeniji, Johnson A.; Oberste, M. Steven; Burns, Cara C.

    2016-01-01

    ABSTRACT The poliovirus (PV) is currently targeted for worldwide eradication and containment. Sanger-based sequencing of the viral protein 1 (VP1) capsid region is currently the standard method for PV surveillance. However, the whole-genome sequence is sometimes needed for higher resolution global surveillance. In this study, we optimized whole-genome sequencing protocols for poliovirus isolates and FTA cards using next-generation sequencing (NGS), aiming for high sequence coverage, efficiency, and throughput. We found that DNase treatment of poliovirus RNA followed by random reverse transcription (RT), amplification, and the use of the Nextera XT DNA library preparation kit produced significantly better results than other preparations. The average viral reads per total reads, a measurement of efficiency, was as high as 84.2% ± 15.6%. PV genomes covering >99 to 100% of the reference length were obtained and validated with Sanger sequencing. A total of 52 PV genomes were generated, multiplexing as many as 64 samples in a single Illumina MiSeq run. This high-throughput, sequence-independent NGS approach facilitated the detection of a diverse range of PVs, especially for those in vaccine-derived polioviruses (VDPV), circulating VDPV, or immunodeficiency-related VDPV. In contrast to results from previous studies on other viruses, our results showed that filtration and nuclease treatment did not discernibly increase the sequencing efficiency of PV isolates. However, DNase treatment after nucleic acid extraction to remove host DNA significantly improved the sequencing results. This NGS method has been successfully implemented to generate PV genomes for molecular epidemiology of the most recent PV isolates. Additionally, the ability to obtain full PV genomes from FTA cards will aid in facilitating global poliovirus surveillance. PMID:27927929

  4. Elucidation of terpenoid metabolism in Scoparia dulcis by RNA-seq analysis.

    Science.gov (United States)

    Yamamura, Yoshimi; Kurosaki, Fumiya; Lee, Jung-Bum

    2017-03-07

    Scoparia dulcis biosynthesize bioactive diterpenes, such as scopadulcic acid B (SDB), which are known for their unique molecular skeleton. Although the biosynthesis of bioactive diterpenes is catalyzed by a sequence of class II and class I diterpene synthases (diTPSs), the mechanisms underlying this process are yet to be fully identified. To elucidate these biosynthetic machinery, we performed a high-throughput RNA-seq analysis, and de novo assembly of clean reads revealed 46,332 unique transcripts and 40,503 two unigenes. We found diTPSs genes including a putative syn-copalyl diphosphate synthase (SdCPS2) and two kaurene synthase-like (SdKSLs) genes. Besides them, total 79 full-length of cytochrome P450 (CYP450) genes were also discovered. The expression analyses showed selected CYP450s associated with their expression pattern of SdCPS2 and SdKSL1, suggesting that CYP450 candidates involved diterpene modification. SdCPS2 represents the first predicted gene to produce syn-copalyl diphosphate in dicots. In addition, SdKSL1 potentially contributes to the SDB biosynthetic pathway. Therefore, these identified genes associated with diterpene biosynthesis lead to the development of genetic engineering focus on diterpene metabolism in S. dulcis.

  5. On the optimal trimming of high-throughput mRNA sequence data

    Directory of Open Access Journals (Sweden)

    Matthew D MacManes

    2014-01-01

    Full Text Available The widespread and rapid adoption of high-throughput sequencing technologies has afforded researchers the opportunity to gain a deep understanding of genome level processes that underlie evolutionary change, and perhaps more importantly, the links between genotype and phenotype. In particular, researchers interested in functional biology and adaptation have used these technologies to sequence mRNA transcriptomes of specific tissues, which in turn are often compared to other tissues, or other individuals with different phenotypes. While these techniques are extremely powerful, careful attention to data quality is required. In particular, because high-throughput sequencing is more error-prone than traditional Sanger sequencing, quality trimming of sequence reads should be an important step in all data processing pipelines. While several software packages for quality trimming exist, no general guidelines for the specifics of trimming have been developed. Here, using empirically derived sequence data, I provide general recommendations regarding the optimal strength of trimming, specifically in mRNA-Seq studies. Although very aggressive quality trimming is common, this study suggests that a more gentle trimming, specifically of those nucleotides whose Phred score < 2 or < 5, is optimal for most studies across a wide variety of metrics.

  6. Multispot single-molecule FRET: High-throughput analysis of freely diffusing molecules.

    Directory of Open Access Journals (Sweden)

    Antonino Ingargiola

    Full Text Available We describe an 8-spot confocal setup for high-throughput smFRET assays and illustrate its performance with two characteristic experiments. First, measurements on a series of freely diffusing doubly-labeled dsDNA samples allow us to demonstrate that data acquired in multiple spots in parallel can be properly corrected and result in measured sample characteristics consistent with those obtained with a standard single-spot setup. We then take advantage of the higher throughput provided by parallel acquisition to address an outstanding question about the kinetics of the initial steps of bacterial RNA transcription. Our real-time kinetic analysis of promoter escape by bacterial RNA polymerase confirms results obtained by a more indirect route, shedding additional light on the initial steps of transcription. Finally, we discuss the advantages of our multispot setup, while pointing potential limitations of the current single laser excitation design, as well as analysis challenges and their solutions.

  7. High-throughput scoring of seed germination

    NARCIS (Netherlands)

    Ligterink, Wilco; Hilhorst, Henk W.M.

    2017-01-01

    High-throughput analysis of seed germination for phenotyping large genetic populations or mutant collections is very labor intensive and would highly benefit from an automated setup. Although very often used, the total germination percentage after a nominated period of time is not very

  8. Examination of Csr regulatory circuitry using epistasis analysis with RNA-seq (Epi-seq) confirms that CsrD affects gene expression via CsrA, CsrB and CsrC.

    Science.gov (United States)

    Potts, Anastasia H; Leng, Yuanyuan; Babitzke, Paul; Romeo, Tony

    2018-03-29

    The Csr global regulatory system coordinates gene expression in response to metabolic status. This system utilizes the RNA binding protein CsrA to regulate gene expression by binding to transcripts of structural and regulatory genes, thus affecting their structure, stability, translation, and/or transcription elongation. CsrA activity is controlled by sRNAs, CsrB and CsrC, which sequester CsrA away from other transcripts. CsrB/C levels are partly determined by their rates of turnover, which requires CsrD to render them susceptible to RNase E cleavage. Previous epistasis analysis suggested that CsrD affects gene expression through the other Csr components, CsrB/C and CsrA. However, those conclusions were based on a limited analysis of reporters. Here, we reassessed the global behavior of the Csr circuitry using epistasis analysis with RNA seq (Epi-seq). Because CsrD effects on mRNA levels were entirely lost in the csrA mutant and largely eliminated in a csrB/C mutant under our experimental conditions, while the majority of CsrA effects persisted in the absence of csrD, the original model accounts for the global behavior of the Csr system. Our present results also reflect a more nuanced role of CsrA as terminal regulator of the Csr system than has been recognized.

  9. Granatum: a graphical single-cell RNA-Seq analysis pipeline for genomics scientists.

    Science.gov (United States)

    Zhu, Xun; Wolfgruber, Thomas K; Tasato, Austin; Arisdakessian, Cédric; Garmire, David G; Garmire, Lana X

    2017-12-05

    Single-cell RNA sequencing (scRNA-Seq) is an increasingly popular platform to study heterogeneity at the single-cell level. Computational methods to process scRNA-Seq data are not very accessible to bench scientists as they require a significant amount of bioinformatic skills. We have developed Granatum, a web-based scRNA-Seq analysis pipeline to make analysis more broadly accessible to researchers. Without a single line of programming code, users can click through the pipeline, setting parameters and visualizing results via the interactive graphical interface. Granatum conveniently walks users through various steps of scRNA-Seq analysis. It has a comprehensive list of modules, including plate merging and batch-effect removal, outlier-sample removal, gene-expression normalization, imputation, gene filtering, cell clustering, differential gene expression analysis, pathway/ontology enrichment analysis, protein network interaction visualization, and pseudo-time cell series construction. Granatum enables broad adoption of scRNA-Seq technology by empowering bench scientists with an easy-to-use graphical interface for scRNA-Seq data analysis. The package is freely available for research use at http://garmiregroup.org/granatum/app.

  10. Improving Hierarchical Models Using Historical Data with Applications in High-Throughput Genomics Data Analysis.

    Science.gov (United States)

    Li, Ben; Li, Yunxiao; Qin, Zhaohui S

    2017-06-01

    Modern high-throughput biotechnologies such as microarray and next generation sequencing produce a massive amount of information for each sample assayed. However, in a typical high-throughput experiment, only limited amount of data are observed for each individual feature, thus the classical 'large p , small n ' problem. Bayesian hierarchical model, capable of borrowing strength across features within the same dataset, has been recognized as an effective tool in analyzing such data. However, the shrinkage effect, the most prominent feature of hierarchical features, can lead to undesirable over-correction for some features. In this work, we discuss possible causes of the over-correction problem and propose several alternative solutions. Our strategy is rooted in the fact that in the Big Data era, large amount of historical data are available which should be taken advantage of. Our strategy presents a new framework to enhance the Bayesian hierarchical model. Through simulation and real data analysis, we demonstrated superior performance of the proposed strategy. Our new strategy also enables borrowing information across different platforms which could be extremely useful with emergence of new technologies and accumulation of data from different platforms in the Big Data era. Our method has been implemented in R package "adaptiveHM", which is freely available from https://github.com/benliemory/adaptiveHM.

  11. Improvements and impacts of GRCh38 human reference on high throughput sequencing data analysis.

    Science.gov (United States)

    Guo, Yan; Dai, Yulin; Yu, Hui; Zhao, Shilin; Samuels, David C; Shyr, Yu

    2017-03-01

    Analyses of high throughput sequencing data starts with alignment against a reference genome, which is the foundation for all re-sequencing data analyses. Each new release of the human reference genome has been augmented with improved accuracy and completeness. It is presumed that the latest release of human reference genome, GRCh38 will contribute more to high throughput sequencing data analysis by providing more accuracy. But the amount of improvement has not yet been quantified. We conducted a study to compare the genomic analysis results between the GRCh38 reference and its predecessor GRCh37. Through analyses of alignment, single nucleotide polymorphisms, small insertion/deletions, copy number and structural variants, we show that GRCh38 offers overall more accurate analysis of human sequencing data. More importantly, GRCh38 produced fewer false positive structural variants. In conclusion, GRCh38 is an improvement over GRCh37 not only from the genome assembly aspect, but also yields more reliable genomic analysis results. Copyright © 2017. Published by Elsevier Inc.

  12. Comparison of transcriptomic landscapes of bovine embryos using RNA-Seq

    Directory of Open Access Journals (Sweden)

    Khatib Hasan

    2010-12-01

    Full Text Available Abstract Background Advances in sequencing technologies have opened a new era of high throughput investigations. Although RNA-seq has been demonstrated in many organisms, no study has provided a comprehensive investigation of the bovine transcriptome using RNA-seq. Results In this study, we provide a deep survey of the bovine embryonic transcriptomes, the first application of RNA-seq in cattle. Embryos cultured in vitro were used as models to study early embryonic development in cattle. RNA amplified from limited amounts of starting total RNA were sequenced and mapped to the reference genome to obtain digital gene expression at single base resolution. In particular, gene expression estimates from more than 1.6 million unannotated bases in 1785 novel transcribed units were obtained. We compared the transcriptomes of embryos showing distinct developmental statuses and found genes that showed differential overall expression as well as alternative splicing. Conclusion Our study demonstrates the power of RNA-seq and provides further understanding of bovine preimplantation embryonic development at a fine scale.

  13. MIPHENO: Data normalization for high throughput metabolic analysis.

    Science.gov (United States)

    High throughput methodologies such as microarrays, mass spectrometry and plate-based small molecule screens are increasingly used to facilitate discoveries from gene function to drug candidate identification. These large-scale experiments are typically carried out over the course...

  14. NGScloud: RNA-seq analysis of non-model species using cloud computing.

    Science.gov (United States)

    Mora-Márquez, Fernando; Vázquez-Poletti, José Luis; López de Heredia, Unai

    2018-05-03

    RNA-seq analysis usually requires large computing infrastructures. NGScloud is a bioinformatic system developed to analyze RNA-seq data using the cloud computing services of Amazon that permit the access to ad hoc computing infrastructure scaled according to the complexity of the experiment, so its costs and times can be optimized. The application provides a user-friendly front-end to operate Amazon's hardware resources, and to control a workflow of RNA-seq analysis oriented to non-model species, incorporating the cluster concept, which allows parallel runs of common RNA-seq analysis programs in several virtual machines for faster analysis. NGScloud is freely available at https://github.com/GGFHF/NGScloud/. A manual detailing installation and how-to-use instructions is available with the distribution. unai.lopezdeheredia@upm.es.

  15. A quantitative and qualitative comparison of illumina MiSeq and 454 amplicon sequencing for genotyping the highly polymorphic major histocompatibility complex (MHC) in a non-model species.

    Science.gov (United States)

    Razali, Haslina; O'Connor, Emily; Drews, Anna; Burke, Terry; Westerdahl, Helena

    2017-07-28

    High-throughput sequencing enables high-resolution genotyping of extremely duplicated genes. 454 amplicon sequencing (454) has become the standard technique for genotyping the major histocompatibility complex (MHC) genes in non-model organisms. However, illumina MiSeq amplicon sequencing (MiSeq), which offers a much higher read depth, is now superseding 454. The aim of this study was to quantitatively and qualitatively evaluate the performance of MiSeq in relation to 454 for genotyping MHC class I alleles using a house sparrow (Passer domesticus) dataset with pedigree information. House sparrows provide a good study system for this comparison as their MHC class I genes have been studied previously and, consequently, we had prior expectations concerning the number of alleles per individual. We found that 454 and MiSeq performed equally well in genotyping amplicons with low diversity, i.e. amplicons from individuals that had fewer than 6 alleles. Although there was a higher rate of failure in the 454 dataset in resolving amplicons with higher diversity (6-9 alleles), the same genotypes were identified by both 454 and MiSeq in 98% of cases. We conclude that low diversity amplicons are equally well genotyped using either 454 or MiSeq, but the higher coverage afforded by MiSeq can lead to this approach outperforming 454 in amplicons with higher diversity.

  16. Automated analysis of high-throughput B-cell sequencing data reveals a high frequency of novel immunoglobulin V gene segment alleles.

    Science.gov (United States)

    Gadala-Maria, Daniel; Yaari, Gur; Uduman, Mohamed; Kleinstein, Steven H

    2015-02-24

    Individual variation in germline and expressed B-cell immunoglobulin (Ig) repertoires has been associated with aging, disease susceptibility, and differential response to infection and vaccination. Repertoire properties can now be studied at large-scale through next-generation sequencing of rearranged Ig genes. Accurate analysis of these repertoire-sequencing (Rep-Seq) data requires identifying the germline variable (V), diversity (D), and joining (J) gene segments used by each Ig sequence. Current V(D)J assignment methods work by aligning sequences to a database of known germline V(D)J segment alleles. However, existing databases are likely to be incomplete and novel polymorphisms are hard to differentiate from the frequent occurrence of somatic hypermutations in Ig sequences. Here we develop a Tool for Ig Genotype Elucidation via Rep-Seq (TIgGER). TIgGER analyzes mutation patterns in Rep-Seq data to identify novel V segment alleles, and also constructs a personalized germline database containing the specific set of alleles carried by a subject. This information is then used to improve the initial V segment assignments from existing tools, like IMGT/HighV-QUEST. The application of TIgGER to Rep-Seq data from seven subjects identified 11 novel V segment alleles, including at least one in every subject examined. These novel alleles constituted 13% of the total number of unique alleles in these subjects, and impacted 3% of V(D)J segment assignments. These results reinforce the highly polymorphic nature of human Ig V genes, and suggest that many novel alleles remain to be discovered. The integration of TIgGER into Rep-Seq processing pipelines will increase the accuracy of V segment assignments, thus improving B-cell repertoire analyses.

  17. High-Throughput Analysis and Automation for Glycomics Studies

    NARCIS (Netherlands)

    Shubhakar, A.; Reiding, K.R.; Gardner, R.A.; Spencer, D.I.R.; Fernandes, D.L.; Wuhrer, M.

    2015-01-01

    This review covers advances in analytical technologies for high-throughput (HTP) glycomics. Our focus is on structural studies of glycoprotein glycosylation to support biopharmaceutical realization and the discovery of glycan biomarkers for human disease. For biopharmaceuticals, there is increasing

  18. SeqBox: RNAseq/ChIPseq reproducible analysis on a consumer game computer.

    Science.gov (United States)

    Beccuti, Marco; Cordero, Francesca; Arigoni, Maddalena; Panero, Riccardo; Amparore, Elvio G; Donatelli, Susanna; Calogero, Raffaele A

    2018-03-01

    Short reads sequencing technology has been used for more than a decade now. However, the analysis of RNAseq and ChIPseq data is still computational demanding and the simple access to raw data does not guarantee results reproducibility between laboratories. To address these two aspects, we developed SeqBox, a cheap, efficient and reproducible RNAseq/ChIPseq hardware/software solution based on NUC6I7KYK mini-PC (an Intel consumer game computer with a fast processor and a high performance SSD disk), and Docker container platform. In SeqBox the analysis of RNAseq and ChIPseq data is supported by a friendly GUI. This allows access to fast and reproducible analysis also to scientists with/without scripting experience. Docker container images, docker4seq package and the GUI are available at http://www.bioinformatica.unito.it/reproducibile.bioinformatics.html. beccuti@di.unito.it. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

  19. Gene Expression Analysis of Escherichia Coli Grown in Miniaturized Bioreactor Platforms for High-Throughput Analysis of Growth and genomic Data

    DEFF Research Database (Denmark)

    Boccazzi, P.; Zanzotto, A.; Szita, Nicolas

    2005-01-01

    Combining high-throughput growth physiology and global gene expression data analysis is of significant value for integrating metabolism and genomics. We compared global gene expression using 500 ng of total RNA from Escherichia coli cultures grown in rich or defined minimal media in a miniaturize...... cultures using just 500 ng of total RNA indicate that high-throughput integration of growth physiology and genomics will be possible with novel biochemical platforms and improved detection technologies....

  20. RNA-Seq analysis and annotation of a draft blueberry genome assembly identifies candidate genes involved in fruit ripening, biosynthesis of bioactive compounds, and stage-specific alternative splicing.

    Science.gov (United States)

    Gupta, Vikas; Estrada, April D; Blakley, Ivory; Reid, Rob; Patel, Ketan; Meyer, Mason D; Andersen, Stig Uggerhøj; Brown, Allan F; Lila, Mary Ann; Loraine, Ann E

    2015-01-01

    Blueberries are a rich source of antioxidants and other beneficial compounds that can protect against disease. Identifying genes involved in synthesis of bioactive compounds could enable the breeding of berry varieties with enhanced health benefits. Toward this end, we annotated a previously sequenced draft blueberry genome assembly using RNA-Seq data from five stages of berry fruit development and ripening. Genome-guided assembly of RNA-Seq read alignments combined with output from ab initio gene finders produced around 60,000 gene models, of which more than half were similar to proteins from other species, typically the grape Vitis vinifera. Comparison of gene models to the PlantCyc database of metabolic pathway enzymes identified candidate genes involved in synthesis of bioactive compounds, including bixin, an apocarotenoid with potential disease-fighting properties, and defense-related cyanogenic glycosides, which are toxic. Cyanogenic glycoside (CG) biosynthetic enzymes were highly expressed in green fruit, and a candidate CG detoxification enzyme was up-regulated during fruit ripening. Candidate genes for ethylene, anthocyanin, and 400 other biosynthetic pathways were also identified. Homology-based annotation using Blast2GO and InterPro assigned Gene Ontology terms to around 15,000 genes. RNA-Seq expression profiling showed that blueberry growth, maturation, and ripening involve dynamic gene expression changes, including coordinated up- and down-regulation of metabolic pathway enzymes and transcriptional regulators. Analysis of RNA-seq alignments identified developmentally regulated alternative splicing, promoter use, and 3' end formation. We report genome sequence, gene models, functional annotations, and RNA-Seq expression data that provide an important new resource enabling high throughput studies in blueberry.

  1. MiSeq: A Next Generation Sequencing Platform for Genomic Analysis.

    Science.gov (United States)

    Ravi, Rupesh Kanchi; Walton, Kendra; Khosroheidari, Mahdieh

    2018-01-01

    MiSeq, Illumina's integrated next generation sequencing instrument, uses reversible-terminator sequencing-by-synthesis technology to provide end-to-end sequencing solutions. The MiSeq instrument is one of the smallest benchtop sequencers that can perform onboard cluster generation, amplification, genomic DNA sequencing, and data analysis, including base calling, alignment and variant calling, in a single run. It performs both single- and paired-end runs with adjustable read lengths from 1 × 36 base pairs to 2 × 300 base pairs. A single run can produce output data of up to 15 Gb in as little as 4 h of runtime and can output up to 25 M single reads and 50 M paired-end reads. Thus, MiSeq provides an ideal platform for rapid turnaround time. MiSeq is also a cost-effective tool for various analyses focused on targeted gene sequencing (amplicon sequencing and target enrichment), metagenomics, and gene expression studies. For these reasons, MiSeq has become one of the most widely used next generation sequencing platforms. Here, we provide a protocol to prepare libraries for sequencing using the MiSeq instrument and basic guidelines for analysis of output data from the MiSeq sequencing run.

  2. SpliceSeq: a resource for analysis and visualization of RNA-Seq data on alternative splicing and its functional impacts.

    Science.gov (United States)

    Ryan, Michael C; Cleland, James; Kim, RyangGuk; Wong, Wing Chung; Weinstein, John N

    2012-09-15

    SpliceSeq is a resource for RNA-Seq data that provides a clear view of alternative splicing and identifies potential functional changes that result from splice variation. It displays intuitive visualizations and prioritized lists of results that highlight splicing events and their biological consequences. SpliceSeq unambiguously aligns reads to gene splice graphs, facilitating accurate analysis of large, complex transcript variants that cannot be adequately represented in other formats. SpliceSeq is freely available at http://bioinformatics.mdanderson.org/main/SpliceSeq:Overview. The application is a Java program that can be launched via a browser or installed locally. Local installation requires MySQL and Bowtie. mryan@insilico.us.com Supplementary data are available at Bioinformatics online.

  3. web cellHTS2: A web-application for the analysis of high-throughput screening data

    Directory of Open Access Journals (Sweden)

    Boutros Michael

    2010-04-01

    Full Text Available Abstract Background The analysis of high-throughput screening data sets is an expanding field in bioinformatics. High-throughput screens by RNAi generate large primary data sets which need to be analyzed and annotated to identify relevant phenotypic hits. Large-scale RNAi screens are frequently used to identify novel factors that influence a broad range of cellular processes, including signaling pathway activity, cell proliferation, and host cell infection. Here, we present a web-based application utility for the end-to-end analysis of large cell-based screening experiments by cellHTS2. Results The software guides the user through the configuration steps that are required for the analysis of single or multi-channel experiments. The web-application provides options for various standardization and normalization methods, annotation of data sets and a comprehensive HTML report of the screening data analysis, including a ranked hit list. Sessions can be saved and restored for later re-analysis. The web frontend for the cellHTS2 R/Bioconductor package interacts with it through an R-server implementation that enables highly parallel analysis of screening data sets. web cellHTS2 further provides a file import and configuration module for common file formats. Conclusions The implemented web-application facilitates the analysis of high-throughput data sets and provides a user-friendly interface. web cellHTS2 is accessible online at http://web-cellHTS2.dkfz.de. A standalone version as a virtual appliance and source code for platforms supporting Java 1.5.0 can be downloaded from the web cellHTS2 page. web cellHTS2 is freely distributed under GPL.

  4. Genome-wide analysis of host-chromosome binding sites for Epstein-Barr Virus Nuclear Antigen 1 (EBNA1

    Directory of Open Access Journals (Sweden)

    Wang Pu

    2010-10-01

    Full Text Available Abstract The Epstein-Barr Virus (EBV Nuclear Antigen 1 (EBNA1 protein is required for the establishment of EBV latent infection in proliferating B-lymphocytes. EBNA1 is a multifunctional DNA-binding protein that stimulates DNA replication at the viral origin of plasmid replication (OriP, regulates transcription of viral and cellular genes, and tethers the viral episome to the cellular chromosome. EBNA1 also provides a survival function to B-lymphocytes, potentially through its ability to alter cellular gene expression. To better understand these various functions of EBNA1, we performed a genome-wide analysis of the viral and cellular DNA sites associated with EBNA1 protein in a latently infected Burkitt lymphoma B-cell line. Chromatin-immunoprecipitation (ChIP combined with massively parallel deep-sequencing (ChIP-Seq was used to identify cellular sites bound by EBNA1. Sites identified by ChIP-Seq were validated by conventional real-time PCR, and ChIP-Seq provided quantitative, high-resolution detection of the known EBNA1 binding sites on the EBV genome at OriP and Qp. We identified at least one cluster of unusually high-affinity EBNA1 binding sites on chromosome 11, between the divergent FAM55 D and FAM55B genes. A consensus for all cellular EBNA1 binding sites is distinct from those derived from the known viral binding sites, suggesting that some of these sites are indirectly bound by EBNA1. EBNA1 also bound close to the transcriptional start sites of a large number of cellular genes, including HDAC3, CDC7, and MAP3K1, which we show are positively regulated by EBNA1. EBNA1 binding sites were enriched in some repetitive elements, especially LINE 1 retrotransposons, and had weak correlations with histone modifications and ORC binding. We conclude that EBNA1 can interact with a large number of cellular genes and chromosomal loci in latently infected cells, but that these sites are likely to represent a complex ensemble of direct and indirect EBNA

  5. High-throughput screening of small-molecule adsorption in MOF-74

    Science.gov (United States)

    Thonhauser, T.; Canepa, P.

    2014-03-01

    Using high-throughput screening coupled with state-of-the-art van der Waals density functional theory, we investigate the adsorption properties of four important molecules, H2, CO2, CH4, and H2O in MOF-74-  with  = Be, Mg, Al, Ca, Sc, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Sr, Zr, Nb, Ru, Rh, Pd, La, W, Os, Ir, and Pt. We show that high-throughput techniques can aid in speeding up the development and refinement of effective materials for hydrogen storage, carbon capture, and gas separation. The exploration of the configurational adsorption space allows us to extract crucial information concerning, for example, the competition of water with CO2 for the adsorption binding sites. We find that only a few noble metals--Rh, Pd, Os, Ir, and Pt--favor the adsorption of CO2 and hence are potential candidates for effective carbon-capture materials. Our findings further reveal significant differences in the binding characteristics of H2, CO2, CH4, and H2O within the MOF structure, indicating that molecular blends can be successfully separated by these nano-porous materials. Supported by DOE DE-FG02-08ER46491.

  6. An Automated High Throughput Proteolysis and Desalting Platform for Quantitative Proteomic Analysis

    Directory of Open Access Journals (Sweden)

    Albert-Baskar Arul

    2013-06-01

    Full Text Available Proteomics for biomarker validation needs high throughput instrumentation to analyze huge set of clinical samples for quantitative and reproducible analysis at a minimum time without manual experimental errors. Sample preparation, a vital step in proteomics plays a major role in identification and quantification of proteins from biological samples. Tryptic digestion a major check point in sample preparation for mass spectrometry based proteomics needs to be more accurate with rapid processing time. The present study focuses on establishing a high throughput automated online system for proteolytic digestion and desalting of proteins from biological samples quantitatively and qualitatively in a reproducible manner. The present study compares online protein digestion and desalting of BSA with conventional off-line (in-solution method and validated for real time sample for reproducibility. Proteins were identified using SEQUEST data base search engine and the data were quantified using IDEALQ software. The present study shows that the online system capable of handling high throughput samples in 96 well formats carries out protein digestion and peptide desalting efficiently in a reproducible and quantitative manner. Label free quantification showed clear increase of peptide quantities with increase in concentration with much linearity compared to off line method. Hence we would like to suggest that inclusion of this online system in proteomic pipeline will be effective in quantification of proteins in comparative proteomics were the quantification is really very crucial.

  7. RNA-Seq Analysis of Abdominal Fat Reveals Differences between Modern Commercial Broiler Chickens with High and Low Feed Efficiencies.

    Directory of Open Access Journals (Sweden)

    Zhu Zhuo

    Full Text Available For economic and environmental reasons, chickens with superior feed efficiency (FE are preferred in the broiler chicken industry. High FE (HFE chickens typically have reduced abdominal fat, the major adipose tissue in chickens. In addition to its function of energy storage, adipose tissue is a metabolically active organ that also possesses endocrine and immune regulatory functions. It plays a central role in maintaining energy homeostasis. Comprehensive understanding of the gene expression in the adipose tissue and the biological basis of FE are of significance to optimize selection and breeding strategies. Through gene expression profiling of abdominal fat from high and low FE (LFE commercial broiler chickens, the present study aimed to characterize the differences of gene expression between HFE and LFE chickens. mRNA-seq analysis was carried out on the total RNA of abdominal fat from 10 HFE and 12 LFE commercial broiler chickens, and 1.48 billion of 75-base sequence reads were generated in total. On average, 11,565 genes were expressed (>5 reads/gene/sample in the abdominal fat tissue, of which 286 genes were differentially expressed (DE at q (False Discover Rate 1.3 between HFE and LFE chickens. Expression levels from RNA-seq were confirmed with the NanoString nCounter analysis system. Functional analysis showed that the DE genes were significantly (p < 0.01 enriched in lipid metabolism, coagulation, and immune regulation pathways. Specifically, the LFE chickens had higher expression of lipid synthesis genes and lower expression of triglyceride hydrolysis and cholesterol transport genes. In conclusion, our study reveals the overall differences of gene expression in the abdominal fat from HFE and LFE chickens, and the results suggest that the divergent expression of lipid metabolism genes represents the major differences.

  8. Getting the most out of RNA-seq data analysis

    Directory of Open Access Journals (Sweden)

    Tsung Fei Khang

    2015-10-01

    Full Text Available Background. A common research goal in transcriptome projects is to find genes that are differentially expressed in different phenotype classes. Biologists might wish to validate such gene candidates experimentally, or use them for downstream systems biology analysis. Producing a coherent differential gene expression analysis from RNA-seq count data requires an understanding of how numerous sources of variation such as the replicate size, the hypothesized biological effect size, and the specific method for making differential expression calls interact. We believe an explicit demonstration of such interactions in real RNA-seq data sets is of practical interest to biologists.Results. Using two large public RNA-seq data sets—one representing strong, and another mild, biological effect size—we simulated different replicate size scenarios, and tested the performance of several commonly-used methods for calling differentially expressed genes in each of them. We found that, when biological effect size was mild, RNA-seq experiments should focus on experimental validation of differentially expressed gene candidates. Importantly, at least triplicates must be used, and the differentially expressed genes should be called using methods with high positive predictive value (PPV, such as NOISeq or GFOLD. In contrast, when biological effect size was strong, differentially expressed genes mined from unreplicated experiments using NOISeq, ASC and GFOLD had between 30 to 50% mean PPV, an increase of more than 30-fold compared to the cases of mild biological effect size. Among methods with good PPV performance, having triplicates or more substantially improved mean PPV to over 90% for GFOLD, 60% for DESeq2, 50% for NOISeq, and 30% for edgeR. At a replicate size of six, we found DESeq2 and edgeR to be reasonable methods for calling differentially expressed genes at systems level analysis, as their PPV and sensitivity trade-off were superior to the other methods

  9. Gold-coated polydimethylsiloxane microwells for high-throughput electrochemiluminescence analysis of intracellular glucose at single cells.

    Science.gov (United States)

    Xia, Juan; Zhou, Junyu; Zhang, Ronggui; Jiang, Dechen; Jiang, Depeng

    2018-06-04

    In this communication, a gold-coated polydimethylsiloxane (PDMS) chip with cell-sized microwells was prepared through a stamping and spraying process that was applied directly for high-throughput electrochemiluminescence (ECL) analysis of intracellular glucose at single cells. As compared with the previous multiple-step fabrication of photoresist-based microwells on the electrode, the preparation process is simple and offers fresh electrode surface for higher luminescence intensity. More luminescence intensity was recorded from cell-retained microwells than that at the planar region among the microwells that was correlated with the content of intracellular glucose. The successful monitoring of intracellular glucose at single cells using this PDMS chip will provide an alternative strategy for high-throughput single-cell analysis. Graphical abstract ᅟ.

  10. WaveSeq: a novel data-driven method of detecting histone modification enrichments using wavelets.

    Directory of Open Access Journals (Sweden)

    Apratim Mitra

    Full Text Available BACKGROUND: Chromatin immunoprecipitation followed by next-generation sequencing is a genome-wide analysis technique that can be used to detect various epigenetic phenomena such as, transcription factor binding sites and histone modifications. Histone modification profiles can be either punctate or diffuse which makes it difficult to distinguish regions of enrichment from background noise. With the discovery of histone marks having a wide variety of enrichment patterns, there is an urgent need for analysis methods that are robust to various data characteristics and capable of detecting a broad range of enrichment patterns. RESULTS: To address these challenges we propose WaveSeq, a novel data-driven method of detecting regions of significant enrichment in ChIP-Seq data. Our approach utilizes the wavelet transform, is free of distributional assumptions and is robust to diverse data characteristics such as low signal-to-noise ratios and broad enrichment patterns. Using publicly available datasets we showed that WaveSeq compares favorably with other published methods, exhibiting high sensitivity and precision for both punctate and diffuse enrichment regions even in the absence of a control data set. The application of our algorithm to a complex histone modification data set helped make novel functional discoveries which further underlined its utility in such an experimental setup. CONCLUSIONS: WaveSeq is a highly sensitive method capable of accurate identification of enriched regions in a broad range of data sets. WaveSeq can detect both narrow and broad peaks with a high degree of accuracy even in low signal-to-noise ratio data sets. WaveSeq is also suited for application in complex experimental scenarios, helping make biologically relevant functional discoveries.

  11. High Throughput Facility

    Data.gov (United States)

    Federal Laboratory Consortium — Argonne?s high throughput facility provides highly automated and parallel approaches to material and materials chemistry development. The facility allows scientists...

  12. NBLDA: negative binomial linear discriminant analysis for RNA-Seq data.

    Science.gov (United States)

    Dong, Kai; Zhao, Hongyu; Tong, Tiejun; Wan, Xiang

    2016-09-13

    RNA-sequencing (RNA-Seq) has become a powerful technology to characterize gene expression profiles because it is more accurate and comprehensive than microarrays. Although statistical methods that have been developed for microarray data can be applied to RNA-Seq data, they are not ideal due to the discrete nature of RNA-Seq data. The Poisson distribution and negative binomial distribution are commonly used to model count data. Recently, Witten (Annals Appl Stat 5:2493-2518, 2011) proposed a Poisson linear discriminant analysis for RNA-Seq data. The Poisson assumption may not be as appropriate as the negative binomial distribution when biological replicates are available and in the presence of overdispersion (i.e., when the variance is larger than or equal to the mean). However, it is more complicated to model negative binomial variables because they involve a dispersion parameter that needs to be estimated. In this paper, we propose a negative binomial linear discriminant analysis for RNA-Seq data. By Bayes' rule, we construct the classifier by fitting a negative binomial model, and propose some plug-in rules to estimate the unknown parameters in the classifier. The relationship between the negative binomial classifier and the Poisson classifier is explored, with a numerical investigation of the impact of dispersion on the discriminant score. Simulation results show the superiority of our proposed method. We also analyze two real RNA-Seq data sets to demonstrate the advantages of our method in real-world applications. We have developed a new classifier using the negative binomial model for RNA-seq data classification. Our simulation results show that our proposed classifier has a better performance than existing works. The proposed classifier can serve as an effective tool for classifying RNA-seq data. Based on the comparison results, we have provided some guidelines for scientists to decide which method should be used in the discriminant analysis of RNA-Seq data

  13. Data reduction for a high-throughput neutron activation analysis system

    International Nuclear Information System (INIS)

    Bowman, W.W.

    1979-01-01

    To analyze samples collected as part of a geochemical survey for the National Uranium Resource Evaluation program, Savannah River Laboratory has installed a high-throughput neutron activation analysis system. As part of that system, computer programs have been developed to reduce raw data to elemental concentrations in two steps. Program RAGS reduces gamma-ray spectra to lists of photopeak energies, peak areas, and statistical errors. Program RICHES determines the elemental concentrations from photopeak and delayed-neutron data, detector efficiencies, analysis parameters (neutron flux and activation, decay, and counting times), and spectrometric and cross-section data from libraries. Both programs have been streamlined for on-line operation with a minicomputer, each requiring approx. 64 kbytes of core. 3 tables

  14. Image Harvest: an open-source platform for high-throughput plant image processing and analysis

    Science.gov (United States)

    Knecht, Avi C.; Campbell, Malachy T.; Caprez, Adam; Swanson, David R.; Walia, Harkamal

    2016-01-01

    High-throughput plant phenotyping is an effective approach to bridge the genotype-to-phenotype gap in crops. Phenomics experiments typically result in large-scale image datasets, which are not amenable for processing on desktop computers, thus creating a bottleneck in the image-analysis pipeline. Here, we present an open-source, flexible image-analysis framework, called Image Harvest (IH), for processing images originating from high-throughput plant phenotyping platforms. Image Harvest is developed to perform parallel processing on computing grids and provides an integrated feature for metadata extraction from large-scale file organization. Moreover, the integration of IH with the Open Science Grid provides academic researchers with the computational resources required for processing large image datasets at no cost. Image Harvest also offers functionalities to extract digital traits from images to interpret plant architecture-related characteristics. To demonstrate the applications of these digital traits, a rice (Oryza sativa) diversity panel was phenotyped and genome-wide association mapping was performed using digital traits that are used to describe different plant ideotypes. Three major quantitative trait loci were identified on rice chromosomes 4 and 6, which co-localize with quantitative trait loci known to regulate agronomically important traits in rice. Image Harvest is an open-source software for high-throughput image processing that requires a minimal learning curve for plant biologists to analyzephenomics datasets. PMID:27141917

  15. WormScan: a technique for high-throughput phenotypic analysis of Caenorhabditis elegans.

    Directory of Open Access Journals (Sweden)

    Mark D Mathew

    Full Text Available BACKGROUND: There are four main phenotypes that are assessed in whole organism studies of Caenorhabditis elegans; mortality, movement, fecundity and size. Procedures have been developed that focus on the digital analysis of some, but not all of these phenotypes and may be limited by expense and limited throughput. We have developed WormScan, an automated image acquisition system that allows quantitative analysis of each of these four phenotypes on standard NGM plates seeded with E. coli. This system is very easy to implement and has the capacity to be used in high-throughput analysis. METHODOLOGY/PRINCIPAL FINDINGS: Our system employs a readily available consumer grade flatbed scanner. The method uses light stimulus from the scanner rather than physical stimulus to induce movement. With two sequential scans it is possible to quantify the induced phototactic response. To demonstrate the utility of the method, we measured the phenotypic response of C. elegans to phosphine gas exposure. We found that stimulation of movement by the light of the scanner was equivalent to physical stimulation for the determination of mortality. WormScan also provided a quantitative assessment of health for the survivors. Habituation from light stimulation of continuous scans was similar to habituation caused by physical stimulus. CONCLUSIONS/SIGNIFICANCE: There are existing systems for the automated phenotypic data collection of C. elegans. The specific advantages of our method over existing systems are high-throughput assessment of a greater range of phenotypic endpoints including determination of mortality and quantification of the mobility of survivors. Our system is also inexpensive and very easy to implement. Even though we have focused on demonstrating the usefulness of WormScan in toxicology, it can be used in a wide range of additional C. elegans studies including lifespan determination, development, pathology and behavior. Moreover, we have even adapted the

  16. A nanofluidic bioarray chip for fast and high-throughput detection of antibodies in biological fluids

    Science.gov (United States)

    Lee, Jonathan; Gulzar, Naveed; Scott, Jamie K.; Li, Paul C. H.

    2012-10-01

    Immunoassays have become a standard in secretome analysis in clinical and research analysis. In this field there is a need for a high throughput method that uses low sample volumes. Microfluidics and nanofluidics have been developed for this purpose. Our lab has developed a nanofluidic bioarray (NBA) chip with the goal being a high throughput system that assays low sample volumes against multiple probes. A combination of horizontal and vertical channels are produced to create an array antigens on the surface of the NBA chip in one dimension that is probed by flowing in the other dimension antibodies from biological fluids. We have tested the NBA chip by immobilizing streptavidin and then biotinylated peptide to detect the presence of a mouse monoclonal antibody (MAb) that is specific for the peptide. Bound antibody is detected by an AlexaFluor 647 labeled goat (anti-mouse IgG) polyclonal antibody. Using the NBA chip, we have successfully detected peptide binding by small-volume (0.5 μl) samples containing 50 attomoles (100 pM) MAb.

  17. Statistical methods for the analysis of high-throughput metabolomics data

    Directory of Open Access Journals (Sweden)

    Fabian J. Theis

    2013-01-01

    Full Text Available Metabolomics is a relatively new high-throughput technology that aims at measuring all endogenous metabolites within a biological sample in an unbiased fashion. The resulting metabolic profiles may be regarded as functional signatures of the physiological state, and have been shown to comprise effects of genetic regulation as well as environmental factors. This potential to connect genotypic to phenotypic information promises new insights and biomarkers for different research fields, including biomedical and pharmaceutical research. In the statistical analysis of metabolomics data, many techniques from other omics fields can be reused. However recently, a number of tools specific for metabolomics data have been developed as well. The focus of this mini review will be on recent advancements in the analysis of metabolomics data especially by utilizing Gaussian graphical models and independent component analysis.

  18. High-Throughput Analysis and Automation for Glycomics Studies.

    Science.gov (United States)

    Shubhakar, Archana; Reiding, Karli R; Gardner, Richard A; Spencer, Daniel I R; Fernandes, Daryl L; Wuhrer, Manfred

    This review covers advances in analytical technologies for high-throughput (HTP) glycomics. Our focus is on structural studies of glycoprotein glycosylation to support biopharmaceutical realization and the discovery of glycan biomarkers for human disease. For biopharmaceuticals, there is increasing use of glycomics in Quality by Design studies to help optimize glycan profiles of drugs with a view to improving their clinical performance. Glycomics is also used in comparability studies to ensure consistency of glycosylation both throughout product development and between biosimilars and innovator drugs. In clinical studies there is as well an expanding interest in the use of glycomics-for example in Genome Wide Association Studies-to follow changes in glycosylation patterns of biological tissues and fluids with the progress of certain diseases. These include cancers, neurodegenerative disorders and inflammatory conditions. Despite rising activity in this field, there are significant challenges in performing large scale glycomics studies. The requirement is accurate identification and quantitation of individual glycan structures. However, glycoconjugate samples are often very complex and heterogeneous and contain many diverse branched glycan structures. In this article we cover HTP sample preparation and derivatization methods, sample purification, robotization, optimized glycan profiling by UHPLC, MS and multiplexed CE, as well as hyphenated techniques and automated data analysis tools. Throughout, we summarize the advantages and challenges with each of these technologies. The issues considered include reliability of the methods for glycan identification and quantitation, sample throughput, labor intensity, and affordability for large sample numbers.

  19. High-Throughput Tools for Characterization of Antibody Epitopes

    DEFF Research Database (Denmark)

    Christiansen, Anders

    mapping. In Chapter 1, it was examined whether combining phage display, a traditional epitope mapping approach, with HTS would improve the method. The developed approach was successfully used to map Ara h 1 epitopes in sera from patients with peanut allergy. Notably, the sera represented difficult...... proliferation advantages. Finally, in Chapter 4, a different emerging technology, next-generation peptide microarrays, was applied for epitope mapping of major peanut allergens using sera from allergic patients. New developments in the peptide microarray have enabled a greatly increased throughput....... In this study, these improvements were utilized to characterize epitopes at high resolution, i.e. determine the importance of each residue for antibody binding, for all major peanut allergens. Epitope reactivity among patients often converged on known epitope hotspots, however the binding patterns were somewhat...

  20. Statistical removal of background signals from high-throughput 1H NMR line-broadening ligand-affinity screens

    International Nuclear Information System (INIS)

    Worley, Bradley; Sisco, Nicholas J.; Powers, Robert

    2015-01-01

    NMR ligand-affinity screens are vital to drug discovery, are routinely used to screen fragment-based libraries, and used to verify chemical leads from high-throughput assays and virtual screens. NMR ligand-affinity screens are also a highly informative first step towards identifying functional epitopes of unknown proteins, as well as elucidating the biochemical functions of protein–ligand interaction at their binding interfaces. While simple one-dimensional 1 H NMR experiments are capable of indicating binding through a change in ligand line shape, they are plagued by broad, ill-defined background signals from protein 1 H resonances. We present an uncomplicated method for subtraction of protein background in high-throughput ligand-based affinity screens, and show that its performance is maximized when phase-scatter correction is applied prior to subtraction

  1. High-throughput sequencing of forensic genetic samples using punches of FTA cards with buccal swabs.

    Science.gov (United States)

    Kampmann, Marie-Louise; Buchard, Anders; Børsting, Claus; Morling, Niels

    2016-01-01

    Here, we demonstrate that punches from buccal swab samples preserved on FTA cards can be used for high-throughput DNA sequencing, also known as massively parallel sequencing (MPS). We typed 44 reference samples with the HID-Ion AmpliSeq Identity Panel using washed 1.2 mm punches from FTA cards with buccal swabs and compared the results with those obtained with DNA extracted using the EZ1 DNA Investigator Kit. Concordant profiles were obtained for all samples. Our protocol includes simple punch, wash, and PCR steps, reducing cost and hands-on time in the laboratory. Furthermore, it facilitates automation of DNA sequencing.

  2. Using Poisson mixed-effects model to quantify transcript-level gene expression in RNA-Seq.

    Science.gov (United States)

    Hu, Ming; Zhu, Yu; Taylor, Jeremy M G; Liu, Jun S; Qin, Zhaohui S

    2012-01-01

    RNA sequencing (RNA-Seq) is a powerful new technology for mapping and quantifying transcriptomes using ultra high-throughput next-generation sequencing technologies. Using deep sequencing, gene expression levels of all transcripts including novel ones can be quantified digitally. Although extremely promising, the massive amounts of data generated by RNA-Seq, substantial biases and uncertainty in short read alignment pose challenges for data analysis. In particular, large base-specific variation and between-base dependence make simple approaches, such as those that use averaging to normalize RNA-Seq data and quantify gene expressions, ineffective. In this study, we propose a Poisson mixed-effects (POME) model to characterize base-level read coverage within each transcript. The underlying expression level is included as a key parameter in this model. Since the proposed model is capable of incorporating base-specific variation as well as between-base dependence that affect read coverage profile throughout the transcript, it can lead to improved quantification of the true underlying expression level. POME can be freely downloaded at http://www.stat.purdue.edu/~yuzhu/pome.html. yuzhu@purdue.edu; zhaohui.qin@emory.edu Supplementary data are available at Bioinformatics online.

  3. Variation in RNA-Seq transcriptome profiles of peripheral whole blood from healthy individuals with and without globin depletion.

    Directory of Open Access Journals (Sweden)

    Heesun Shin

    Full Text Available BACKGROUND: The molecular profile of circulating blood can reflect physiological and pathological events occurring in other tissues and organs of the body and delivers a comprehensive view of the status of the immune system. Blood has been useful in studying the pathobiology of many diseases. It is accessible and easily collected making it ideally suited to the development of diagnostic biomarker tests. The blood transcriptome has a high complement of globin RNA that could potentially saturate next-generation sequencing platforms, masking lower abundance transcripts. Methods to deplete globin mRNA are available, but their effect has not been comprehensively studied in peripheral whole blood RNA-Seq data. In this study we aimed to assess technical variability associated with globin depletion in addition to assessing general technical variability in RNA-Seq from whole blood derived samples. RESULTS: We compared technical and biological replicates having undergone globin depletion or not and found that the experimental globin depletion protocol employed removed approximately 80% of globin transcripts, improved the correlation of technical replicates, allowed for reliable detection of thousands of additional transcripts and generally increased transcript abundance measures. Differential expression analysis revealed thousands of genes significantly up-regulated as a result of globin depletion. In addition, globin depletion resulted in the down-regulation of genes involved in both iron and zinc metal ion bonding. CONCLUSIONS: Globin depletion appears to meaningfully improve the quality of peripheral whole blood RNA-Seq data, and may improve our ability to detect true biological variation. Some concerns remain, however. Key amongst them the significant reduction in RNA yields following globin depletion. More generally, our investigation of technical and biological variation with and without globin depletion finds that high-throughput sequencing by RNA-Seq

  4. Data for automated, high-throughput microscopy analysis of intracellular bacterial colonies using spot detection.

    Science.gov (United States)

    Ernstsen, Christina L; Login, Frédéric H; Jensen, Helene H; Nørregaard, Rikke; Møller-Jensen, Jakob; Nejsum, Lene N

    2017-10-01

    Quantification of intracellular bacterial colonies is useful in strategies directed against bacterial attachment, subsequent cellular invasion and intracellular proliferation. An automated, high-throughput microscopy-method was established to quantify the number and size of intracellular bacterial colonies in infected host cells (Detection and quantification of intracellular bacterial colonies by automated, high-throughput microscopy, Ernstsen et al., 2017 [1]). The infected cells were imaged with a 10× objective and number of intracellular bacterial colonies, their size distribution and the number of cell nuclei were automatically quantified using a spot detection-tool. The spot detection-output was exported to Excel, where data analysis was performed. In this article, micrographs and spot detection data are made available to facilitate implementation of the method.

  5. 3D-SURFER: software for high-throughput protein surface comparison and analysis.

    Science.gov (United States)

    La, David; Esquivel-Rodríguez, Juan; Venkatraman, Vishwesh; Li, Bin; Sael, Lee; Ueng, Stephen; Ahrendt, Steven; Kihara, Daisuke

    2009-11-01

    We present 3D-SURFER, a web-based tool designed to facilitate high-throughput comparison and characterization of proteins based on their surface shape. As each protein is effectively represented by a vector of 3D Zernike descriptors, comparison times for a query protein against the entire PDB take, on an average, only a couple of seconds. The web interface has been designed to be as interactive as possible with displays showing animated protein rotations, CATH codes and structural alignments using the CE program. In addition, geometrically interesting local features of the protein surface, such as pockets that often correspond to ligand binding sites as well as protrusions and flat regions can also be identified and visualized. 3D-SURFER is a web application that can be freely accessed from: http://dragon.bio.purdue.edu/3d-surfer dkihara@purdue.edu Supplementary data are available at Bioinformatics online.

  6. High-throughput SHAPE analysis reveals structures in HIV-1 genomic RNA strongly conserved across distinct biological states.

    Directory of Open Access Journals (Sweden)

    Kevin A Wilkinson

    2008-04-01

    Full Text Available Replication and pathogenesis of the human immunodeficiency virus (HIV is tightly linked to the structure of its RNA genome, but genome structure in infectious virions is poorly understood. We invent high-throughput SHAPE (selective 2'-hydroxyl acylation analyzed by primer extension technology, which uses many of the same tools as DNA sequencing, to quantify RNA backbone flexibility at single-nucleotide resolution and from which robust structural information can be immediately derived. We analyze the structure of HIV-1 genomic RNA in four biologically instructive states, including the authentic viral genome inside native particles. Remarkably, given the large number of plausible local structures, the first 10% of the HIV-1 genome exists in a single, predominant conformation in all four states. We also discover that noncoding regions functioning in a regulatory role have significantly lower (p-value < 0.0001 SHAPE reactivities, and hence more structure, than do viral coding regions that function as the template for protein synthesis. By directly monitoring protein binding inside virions, we identify the RNA recognition motif for the viral nucleocapsid protein. Seven structurally homologous binding sites occur in a well-defined domain in the genome, consistent with a role in directing specific packaging of genomic RNA into nascent virions. In addition, we identify two distinct motifs that are targets for the duplex destabilizing activity of this same protein. The nucleocapsid protein destabilizes local HIV-1 RNA structure in ways likely to facilitate initial movement both of the retroviral reverse transcriptase from its tRNA primer and of the ribosome in coding regions. Each of the three nucleocapsid interaction motifs falls in a specific genome domain, indicating that local protein interactions can be organized by the long-range architecture of an RNA. High-throughput SHAPE reveals a comprehensive view of HIV-1 RNA genome structure, and further

  7. High-throughput metagenomic technologies for complex microbial community analysis: open and closed formats.

    Science.gov (United States)

    Zhou, Jizhong; He, Zhili; Yang, Yunfeng; Deng, Ye; Tringe, Susannah G; Alvarez-Cohen, Lisa

    2015-01-27

    Understanding the structure, functions, activities and dynamics of microbial communities in natural environments is one of the grand challenges of 21st century science. To address this challenge, over the past decade, numerous technologies have been developed for interrogating microbial communities, of which some are amenable to exploratory work (e.g., high-throughput sequencing and phenotypic screening) and others depend on reference genes or genomes (e.g., phylogenetic and functional gene arrays). Here, we provide a critical review and synthesis of the most commonly applied "open-format" and "closed-format" detection technologies. We discuss their characteristics, advantages, and disadvantages within the context of environmental applications and focus on analysis of complex microbial systems, such as those in soils, in which diversity is high and reference genomes are few. In addition, we discuss crucial issues and considerations associated with applying complementary high-throughput molecular technologies to address important ecological questions. Copyright © 2015 Zhou et al.

  8. Image Harvest: an open-source platform for high-throughput plant image processing and analysis.

    Science.gov (United States)

    Knecht, Avi C; Campbell, Malachy T; Caprez, Adam; Swanson, David R; Walia, Harkamal

    2016-05-01

    High-throughput plant phenotyping is an effective approach to bridge the genotype-to-phenotype gap in crops. Phenomics experiments typically result in large-scale image datasets, which are not amenable for processing on desktop computers, thus creating a bottleneck in the image-analysis pipeline. Here, we present an open-source, flexible image-analysis framework, called Image Harvest (IH), for processing images originating from high-throughput plant phenotyping platforms. Image Harvest is developed to perform parallel processing on computing grids and provides an integrated feature for metadata extraction from large-scale file organization. Moreover, the integration of IH with the Open Science Grid provides academic researchers with the computational resources required for processing large image datasets at no cost. Image Harvest also offers functionalities to extract digital traits from images to interpret plant architecture-related characteristics. To demonstrate the applications of these digital traits, a rice (Oryza sativa) diversity panel was phenotyped and genome-wide association mapping was performed using digital traits that are used to describe different plant ideotypes. Three major quantitative trait loci were identified on rice chromosomes 4 and 6, which co-localize with quantitative trait loci known to regulate agronomically important traits in rice. Image Harvest is an open-source software for high-throughput image processing that requires a minimal learning curve for plant biologists to analyzephenomics datasets. © The Author 2016. Published by Oxford University Press on behalf of the Society for Experimental Biology.

  9. Fluorescence-based high-throughput screening of dicer cleavage activity.

    Science.gov (United States)

    Podolska, Katerina; Sedlak, David; Bartunek, Petr; Svoboda, Petr

    2014-03-01

    Production of small RNAs by ribonuclease III Dicer is a key step in microRNA and RNA interference pathways, which employ Dicer-produced small RNAs as sequence-specific silencing guides. Further studies and manipulations of microRNA and RNA interference pathways would benefit from identification of small-molecule modulators. Here, we report a study of a fluorescence-based in vitro Dicer cleavage assay, which was adapted for high-throughput screening. The kinetic assay can be performed under single-turnover conditions (35 nM substrate and 70 nM Dicer) in a small volume (5 µL), which makes it suitable for high-throughput screening in a 1536-well format. As a proof of principle, a small library of bioactive compounds was analyzed, demonstrating potential of the assay.

  10. High-throughput continuous cryopump

    International Nuclear Information System (INIS)

    Foster, C.A.

    1986-01-01

    A cryopump with a unique method of regeneration which allows continuous operation at high throughput has been constructed and tested. Deuterium was pumped continuously at a throughput of 30 Torr.L/s at a speed of 2000 L/s and a compression ratio of 200. Argon was pumped at a throughput of 60 Torr.L/s at a speed of 1275 L/s. To produce continuous operation of the pump, a method of regeneration that does not thermally cycle the pump is employed. A small chamber (the ''snail'') passes over the pumping surface and removes the frost from it either by mechanical action with a scraper or by local heating. The material removed is topologically in a secondary vacuum system with low conductance into the primary vacuum; thus, the exhaust can be pumped at pressures up to an effective compression ratio determined by the ratio of the pumping speed to the leakage conductance of the snail. The pump, which is all-metal-sealed and dry and which regenerates every 60 s, would be an ideal system for pumping tritium. Potential fusion applications are for mpmp limiters, for repeating pneumatic pellet injection lines, and for the centrifuge pellet injector spin tank, all of which will require pumping tritium at high throughput. Industrial applications requiring ultraclean pumping of corrosive gases at high throughput, such as the reactive ion etch semiconductor process, may also be feasible

  11. HDAT: web-based high-throughput screening data analysis tools

    International Nuclear Information System (INIS)

    Liu, Rong; Hassan, Taimur; Rallo, Robert; Cohen, Yoram

    2013-01-01

    The increasing utilization of high-throughput screening (HTS) in toxicity studies of engineered nano-materials (ENMs) requires tools for rapid and reliable processing and analyses of large HTS datasets. In order to meet this need, a web-based platform for HTS data analyses tools (HDAT) was developed that provides statistical methods suitable for ENM toxicity data. As a publicly available computational nanoinformatics infrastructure, HDAT provides different plate normalization methods, various HTS summarization statistics, self-organizing map (SOM)-based clustering analysis, and visualization of raw and processed data using both heat map and SOM. HDAT has been successfully used in a number of HTS studies of ENM toxicity, thereby enabling analysis of toxicity mechanisms and development of structure–activity relationships for ENM toxicity. The online approach afforded by HDAT should encourage standardization of and future advances in HTS as well as facilitate convenient inter-laboratory comparisons of HTS datasets. (paper)

  12. LncRNA Expression Profile of Human Thoracic Aortic Dissection by High-Throughput Sequencing.

    Science.gov (United States)

    Sun, Jie; Chen, Guojun; Jing, Yuanwen; He, Xiang; Dong, Jianting; Zheng, Junmeng; Zou, Meisheng; Li, Hairui; Wang, Shifei; Sun, Yili; Liao, Wangjun; Liao, Yulin; Feng, Li; Bin, Jianping

    2018-01-01

    In this study, the long non-coding RNA (lncRNA) expression profile in human thoracic aortic dissection (TAD), a highly lethal cardiovascular disease, was investigated. Human TAD (n=3) and normal aortic tissues (NA) (n=3) were examined by high-throughput sequencing. Bioinformatics analyses were performed to predict the roles of aberrantly expressed lncRNAs. Quantitative real-time polymerase chain reaction (qRT-PCR) was applied to validate the results. A total of 269 lncRNAs (159 up-regulated and 110 down-regulated) and 2, 255 mRNAs (1 294 up-regulated and 961 down-regulated) were aberrantly expressed in human TAD (fold-change> 1.5, PTAD than in NA. The predicted binding motifs of three up-regulated lncRNAs (ENSG00000248508, ENSG00000226530, and EG00000259719) were correlated with up-regulated RUNX1 (R=0.982, PTAD. These findings suggest that lncRNAs are novel potential therapeutic targets for human TAD. © 2018 The Author(s). Published by S. Karger AG, Basel.

  13. Geochip: A high throughput genomic tool for linking community structure to functions

    Energy Technology Data Exchange (ETDEWEB)

    Van Nostrand, Joy D.; Liang, Yuting; He, Zhili; Li, Guanghe; Zhou, Jizhong

    2009-01-30

    GeoChip is a comprehensive functional gene array that targets key functional genes involved in the geochemical cycling of N, C, and P, sulfate reduction, metal resistance and reduction, and contaminant degradation. Studies have shown the GeoChip to be a sensitive, specific, and high-throughput tool for microbial community analysis that has the power to link geochemical processes with microbial community structure. However, several challenges remain regarding the development and applications of microarrays for microbial community analysis.

  14. High-throughput immuno-profiling of mamba (Dendroaspis) venom toxin epitopes using high-density peptide microarrays

    DEFF Research Database (Denmark)

    Engmark, Mikael; Andersen, Mikael Rørdam; Laustsen, Andreas Hougaard

    2016-01-01

    Snakebite envenoming is a serious condition requiring medical attention and administration of antivenom. Current antivenoms are antibody preparations obtained from the plasma of animals immunised with whole venom(s) and contain antibodies against snake venom toxins, but also against other antigens....... In order to better understand the molecular interactions between antivenom antibodies and epitopes on snake venom toxins, a high-throughput immuno-profiling study on all manually curated toxins from Dendroaspis species and selected African Naja species was performed based on custom-made high......-density peptide microarrays displaying linear toxin fragments. By detection of binding for three different antivenoms and performing an alanine scan, linear elements of epitopes and the positions important for binding were identified. A strong tendency of antivenom antibodies recognizing and binding to epitopes...

  15. High-throughput analysis for preparation, processing and analysis of TiO2 coatings on steel by chemical solution deposition

    International Nuclear Information System (INIS)

    Cuadrado Gil, Marcos; Van Driessche, Isabel; Van Gils, Sake; Lommens, Petra; Castelein, Pieter; De Buysser, Klaartje

    2012-01-01

    Highlights: ► High-throughput preparation of TiO 2 aqueous precursors. ► Analysis of stability and surface tension. ► Deposition of TiO 2 coatings. - Abstract: A high-throughput preparation, processing and analysis of titania coatings prepared by chemical solution deposition from water-based precursors at low temperature (≈250 °C) on two different types of steel substrates (Aluzinc® and bright annealed) is presented. The use of the high-throughput equipment allows fast preparation of multiple samples saving time, energy and material; and helps to test the scalability of the process. The process itself includes the use of IR curing for aqueous ceramic precursors and possibilities of using UV irradiation before the final sintering step. The IR curing method permits a much faster curing step compared to normal high temperature treatments in traditional convection devices (i.e., tube furnaces). The formulations, also prepared by high-throughput equipment, are found to be stable in the operational pH range of the substrates (6.5–8.5). Titanium alkoxides itself lack stability in pure water-based environments, but the presence of the different organic complexing agents prevents it from hydrolysis and precipitation reactions. The wetting interaction between the substrates and the various formulations is studied by the determination of the surface free energy of the substrates and the polar and dispersive components of the surface tension of the solutions. The mild temperature program used for preparation of the coatings however does not lead to the formation of pure crystalline material, necessary for the desired photocatalytic and super-hydrophilic behavior of these coatings. Nevertheless, some activity can be reported for these amorphous coatings by monitoring the discoloration of methylene blue in water under UV irradiation.

  16. Genome-wide conserved consensus transcription factor binding motifs are hyper-methylated

    Directory of Open Access Journals (Sweden)

    Down Thomas A

    2010-09-01

    Full Text Available Abstract Background DNA methylation can regulate gene expression by modulating the interaction between DNA and proteins or protein complexes. Conserved consensus motifs exist across the human genome ("predicted transcription factor binding sites": "predicted TFBS" but the large majority of these are proven by chromatin immunoprecipitation and high throughput sequencing (ChIP-seq not to be biological transcription factor binding sites ("empirical TFBS". We hypothesize that DNA methylation at conserved consensus motifs prevents promiscuous or disorderly transcription factor binding. Results Using genome-wide methylation maps of the human heart and sperm, we found that all conserved consensus motifs as well as the subset of those that reside outside CpG islands have an aggregate profile of hyper-methylation. In contrast, empirical TFBS with conserved consensus motifs have a profile of hypo-methylation. 40% of empirical TFBS with conserved consensus motifs resided in CpG islands whereas only 7% of all conserved consensus motifs were in CpG islands. Finally we further identified a minority subset of TF whose profiles are either hypo-methylated or neutral at their respective conserved consensus motifs implicating that these TF may be responsible for establishing or maintaining an un-methylated DNA state, or whose binding is not regulated by DNA methylation. Conclusions Our analysis supports the hypothesis that at least for a subset of TF, empirical binding to conserved consensus motifs genome-wide may be controlled by DNA methylation.

  17. High throughput protein production screening

    Science.gov (United States)

    Beernink, Peter T [Walnut Creek, CA; Coleman, Matthew A [Oakland, CA; Segelke, Brent W [San Ramon, CA

    2009-09-08

    Methods, compositions, and kits for the cell-free production and analysis of proteins are provided. The invention allows for the production of proteins from prokaryotic sequences or eukaryotic sequences, including human cDNAs using PCR and IVT methods and detecting the proteins through fluorescence or immunoblot techniques. This invention can be used to identify optimized PCR and WT conditions, codon usages and mutations. The methods are readily automated and can be used for high throughput analysis of protein expression levels, interactions, and functional states.

  18. Isolation and characterization of antigen-specific alpaca (Lama pacos) VHH antibodies by biopanning followed by high-throughput sequencing.

    Science.gov (United States)

    Miyazaki, Nobuo; Kiyose, Norihiko; Akazawa, Yoko; Takashima, Mizuki; Hagihara, Yosihisa; Inoue, Naokazu; Matsuda, Tomonari; Ogawa, Ryu; Inoue, Seiya; Ito, Yuji

    2015-09-01

    The antigen-binding domain of camelid dimeric heavy chain antibodies, known as VHH or Nanobody, has much potential in pharmaceutical and industrial applications. To establish the isolation process of antigen-specific VHH, a VHH phage library was constructed with a diversity of 8.4 × 10(7) from cDNA of peripheral blood mononuclear cells of an alpaca (Lama pacos) immunized with a fragment of IZUMO1 (IZUMO1PFF) as a model antigen. By conventional biopanning, 13 antigen-specific VHHs were isolated. The amino acid sequences of these VHHs, designated as N-group VHHs, were very similar to each other (>93% identity). To find more diverse antibodies, we performed high-throughput sequencing (HTS) of VHH genes. By comparing the frequencies of each sequence between before and after biopanning, we found the sequences whose frequencies were increased by biopanning. The top 100 sequences of them were supplied for phylogenic tree analysis. In total 75% of them belonged to N-group VHHs, but the other were phylogenically apart from N-group VHHs (Non N-group). Two of three VHHs selected from non N-group VHHs showed sufficient antigen binding ability. These results suggested that biopanning followed by HTS provided a useful method for finding minor and diverse antigen-specific clones that could not be identified by conventional biopanning. © The Authors 2015. Published by Oxford University Press on behalf of the Japanese Biochemical Society. All rights reserved.

  19. High-Throughput Scoring of Seed Germination.

    Science.gov (United States)

    Ligterink, Wilco; Hilhorst, Henk W M

    2017-01-01

    High-throughput analysis of seed germination for phenotyping large genetic populations or mutant collections is very labor intensive and would highly benefit from an automated setup. Although very often used, the total germination percentage after a nominated period of time is not very informative as it lacks information about start, rate, and uniformity of germination, which are highly indicative of such traits as dormancy, stress tolerance, and seed longevity. The calculation of cumulative germination curves requires information about germination percentage at various time points. We developed the GERMINATOR package: a simple, highly cost-efficient, and flexible procedure for high-throughput automatic scoring and evaluation of germination that can be implemented without the use of complex robotics. The GERMINATOR package contains three modules: (I) design of experimental setup with various options to replicate and randomize samples; (II) automatic scoring of germination based on the color contrast between the protruding radicle and seed coat on a single image; and (III) curve fitting of cumulative germination data and the extraction, recap, and visualization of the various germination parameters. GERMINATOR is a freely available package that allows the monitoring and analysis of several thousands of germination tests, several times a day by a single person.

  20. DockoMatic: automated peptide analog creation for high throughput virtual screening.

    Science.gov (United States)

    Jacob, Reed B; Bullock, Casey W; Andersen, Tim; McDougal, Owen M

    2011-10-01

    The purpose of this manuscript is threefold: (1) to describe an update to DockoMatic that allows the user to generate cyclic peptide analog structure files based on protein database (pdb) files, (2) to test the accuracy of the peptide analog structure generation utility, and (3) to evaluate the high throughput capacity of DockoMatic. The DockoMatic graphical user interface interfaces with the software program Treepack to create user defined peptide analogs. To validate this approach, DockoMatic produced cyclic peptide analogs were tested for three-dimensional structure consistency and binding affinity against four experimentally determined peptide structure files available in the Research Collaboratory for Structural Bioinformatics database. The peptides used to evaluate this new functionality were alpha-conotoxins ImI, PnIA, and their published analogs. Peptide analogs were generated by DockoMatic and tested for their ability to bind to X-ray crystal structure models of the acetylcholine binding protein originating from Aplysia californica. The results, consisting of more than 300 simulations, demonstrate that DockoMatic predicts the binding energy of peptide structures to within 3.5 kcal mol(-1), and the orientation of bound ligand compares to within 1.8 Å root mean square deviation for ligand structures as compared to experimental data. Evaluation of high throughput virtual screening capacity demonstrated that Dockomatic can collect, evaluate, and summarize the output of 10,000 AutoDock jobs in less than 2 hours of computational time, while 100,000 jobs requires approximately 15 hours and 1,000,000 jobs is estimated to take up to a week. Copyright © 2011 Wiley Periodicals, Inc.

  1. High-throughput characterization methods for lithium batteries

    Directory of Open Access Journals (Sweden)

    Yingchun Lyu

    2017-09-01

    Full Text Available The development of high-performance lithium ion batteries requires the discovery of new materials and the optimization of key components. By contrast with traditional one-by-one method, high-throughput method can synthesize and characterize a large number of compositionally varying samples, which is able to accelerate the pace of discovery, development and optimization process of materials. Because of rapid progress in thin film and automatic control technologies, thousands of compounds with different compositions could be synthesized rapidly right now, even in a single experiment. However, the lack of rapid or combinatorial characterization technologies to match with high-throughput synthesis methods, limit the application of high-throughput technology. Here, we review a series of representative high-throughput characterization methods used in lithium batteries, including high-throughput structural and electrochemical characterization methods and rapid measuring technologies based on synchrotron light sources.

  2. A Comparison Study for DNA Motif Modeling on Protein Binding Microarray

    KAUST Repository

    Wong, Ka-Chun; Li, Yue; Peng, Chengbin; Wong, Hau-San

    2015-01-01

    Transcription Factor Binding Sites (TFBSs) are relatively short (5-15 bp) and degenerate. Identifying them is a computationally challenging task. In particular, Protein Binding Microarray (PBM) is a high-throughput platform that can measure the DNA binding preference of a protein in a comprehensive and unbiased manner; for instance, a typical PBM experiment can measure binding signal intensities of a protein to all possible DNA k-mers (k=810). Since proteins can often bind to DNA with different binding intensities, one of the major challenges is to build motif models which can fully capture the quantitative binding affinity data. To learn DNA motif models from the non-convex objective function landscape, several optimization methods are compared and applied to the PBM motif model building problem. In particular, representative methods from different optimization paradigms have been chosen for modeling performance comparison on hundreds of PBM datasets. The results suggest that the multimodal optimization methods are very effective for capturing the binding preference information from PBM data. In particular, we observe a general performance improvement using di-nucleotide modeling over mono-nucleotide modeling. In addition, the models learned by the best-performing method are applied to two independent applications: PBM probe rotation testing and ChIP-Seq peak sequence prediction, demonstrating its biological applicability.

  3. A Comparison Study for DNA Motif Modeling on Protein Binding Microarray

    KAUST Repository

    Wong, Ka-Chun

    2015-06-11

    Transcription Factor Binding Sites (TFBSs) are relatively short (5-15 bp) and degenerate. Identifying them is a computationally challenging task. In particular, Protein Binding Microarray (PBM) is a high-throughput platform that can measure the DNA binding preference of a protein in a comprehensive and unbiased manner; for instance, a typical PBM experiment can measure binding signal intensities of a protein to all possible DNA k-mers (k=810). Since proteins can often bind to DNA with different binding intensities, one of the major challenges is to build motif models which can fully capture the quantitative binding affinity data. To learn DNA motif models from the non-convex objective function landscape, several optimization methods are compared and applied to the PBM motif model building problem. In particular, representative methods from different optimization paradigms have been chosen for modeling performance comparison on hundreds of PBM datasets. The results suggest that the multimodal optimization methods are very effective for capturing the binding preference information from PBM data. In particular, we observe a general performance improvement using di-nucleotide modeling over mono-nucleotide modeling. In addition, the models learned by the best-performing method are applied to two independent applications: PBM probe rotation testing and ChIP-Seq peak sequence prediction, demonstrating its biological applicability.

  4. Rnnotator: an automated de novo transcriptome assembly pipeline from stranded RNA-Seq reads

    Energy Technology Data Exchange (ETDEWEB)

    Martin, Jeffrey; Bruno, Vincent M.; Fang, Zhide; Meng, Xiandong; Blow, Matthew; Zhang, Tao; Sherlock, Gavin; Snyder, Michael; Wang, Zhong

    2010-11-19

    Background: Comprehensive annotation and quantification of transcriptomes are outstanding problems in functional genomics. While high throughput mRNA sequencing (RNA-Seq) has emerged as a powerful tool for addressing these problems, its success is dependent upon the availability and quality of reference genome sequences, thus limiting the organisms to which it can be applied. Results: Here, we describe Rnnotator, an automated software pipeline that generates transcript models by de novo assembly of RNA-Seq data without the need for a reference genome. We have applied the Rnnotator assembly pipeline to two yeast transcriptomes and compared the results to the reference gene catalogs of these organisms. The contigs produced by Rnnotator are highly accurate (95percent) and reconstruct full-length genes for the majority of the existing gene models (54.3percent). Furthermore, our analyses revealed many novel transcribed regions that are absent from well annotated genomes, suggesting Rnnotator serves as a complementary approach to analysis based on a reference genome for comprehensive transcriptomics. Conclusions: These results demonstrate that the Rnnotator pipeline is able to reconstruct full-length transcripts in the absence of a complete reference genome.

  5. High-throughput fragment screening by affinity LC-MS.

    Science.gov (United States)

    Duong-Thi, Minh-Dao; Bergström, Maria; Fex, Tomas; Isaksson, Roland; Ohlson, Sten

    2013-02-01

    Fragment screening, an emerging approach for hit finding in drug discovery, has recently been proven effective by its first approved drug, vemurafenib, for cancer treatment. Techniques such as nuclear magnetic resonance, surface plasmon resonance, and isothemal titration calorimetry, with their own pros and cons, have been employed for screening fragment libraries. As an alternative approach, screening based on high-performance liquid chromatography separation has been developed. In this work, we present weak affinity LC/MS as a method to screen fragments under high-throughput conditions. Affinity-based capillary columns with immobilized thrombin were used to screen a collection of 590 compounds from a fragment library. The collection was divided into 11 mixtures (each containing 35 to 65 fragments) and screened by MS detection. The primary screening was performed in 3500 fragments per day). Thirty hits were defined, which subsequently entered a secondary screening using an active site-blocked thrombin column for confirmation of specificity. One hit showed selective binding to thrombin with an estimated dissociation constant (K (D)) in the 0.1 mM range. This study shows that affinity LC/MS is characterized by high throughput, ease of operation, and low consumption of target and fragments, and therefore it promises to be a valuable method for fragment screening.

  6. Functional recombinant MHC class II molecules and high-throughput peptide-binding assays

    DEFF Research Database (Denmark)

    Justesen, Sune; Harndahl, Mikkel; Lamberth, Kasper

    2009-01-01

    BACKGROUND: Molecules of the class II major histocompability complex (MHC-II) specifically bind and present exogenously derived peptide epitopes to CD4+ T helper cells. The extreme polymorphism of the MHC-II hampers the complete analysis of peptide binding. It is also a significant hurdle......-II molecules and accompanying HTS peptide-binding assay were successfully developed for nine different MHC-II molecules including the DPA1*0103/DPB1*0401 (DP401) and DQA1*0501/DQB1*0201, where both alpha and beta chains are polymorphic, illustrating the advantages of producing the two chains separately....... CONCLUSION: We have successfully developed versatile MHC-II resources, which may assist in the generation of MHC class II -wide reagents, data, and tools....

  7. Differential Expression and Functional Analysis of High-Throughput -Omics Data Using Open Source Tools.

    Science.gov (United States)

    Kebschull, Moritz; Fittler, Melanie Julia; Demmer, Ryan T; Papapanou, Panos N

    2017-01-01

    Today, -omics analyses, including the systematic cataloging of messenger RNA and microRNA sequences or DNA methylation patterns in a cell population, organ, or tissue sample, allow for an unbiased, comprehensive genome-level analysis of complex diseases, offering a large advantage over earlier "candidate" gene or pathway analyses. A primary goal in the analysis of these high-throughput assays is the detection of those features among several thousand that differ between different groups of samples. In the context of oral biology, our group has successfully utilized -omics technology to identify key molecules and pathways in different diagnostic entities of periodontal disease.A major issue when inferring biological information from high-throughput -omics studies is the fact that the sheer volume of high-dimensional data generated by contemporary technology is not appropriately analyzed using common statistical methods employed in the biomedical sciences.In this chapter, we outline a robust and well-accepted bioinformatics workflow for the initial analysis of -omics data generated using microarrays or next-generation sequencing technology using open-source tools. Starting with quality control measures and necessary preprocessing steps for data originating from different -omics technologies, we next outline a differential expression analysis pipeline that can be used for data from both microarray and sequencing experiments, and offers the possibility to account for random or fixed effects. Finally, we present an overview of the possibilities for a functional analysis of the obtained data.

  8. Annotating Protein Functional Residues by Coupling High-Throughput Fitness Profile and Homologous-Structure Analysis

    Directory of Open Access Journals (Sweden)

    Yushen Du

    2016-11-01

    Full Text Available Identification and annotation of functional residues are fundamental questions in protein sequence analysis. Sequence and structure conservation provides valuable information to tackle these questions. It is, however, limited by the incomplete sampling of sequence space in natural evolution. Moreover, proteins often have multiple functions, with overlapping sequences that present challenges to accurate annotation of the exact functions of individual residues by conservation-based methods. Using the influenza A virus PB1 protein as an example, we developed a method to systematically identify and annotate functional residues. We used saturation mutagenesis and high-throughput sequencing to measure the replication capacity of single nucleotide mutations across the entire PB1 protein. After predicting protein stability upon mutations, we identified functional PB1 residues that are essential for viral replication. To further annotate the functional residues important to the canonical or noncanonical functions of viral RNA-dependent RNA polymerase (vRdRp, we performed a homologous-structure analysis with 16 different vRdRp structures. We achieved high sensitivity in annotating the known canonical polymerase functional residues. Moreover, we identified a cluster of noncanonical functional residues located in the loop region of the PB1 β-ribbon. We further demonstrated that these residues were important for PB1 protein nuclear import through the interaction with Ran-binding protein 5. In summary, we developed a systematic and sensitive method to identify and annotate functional residues that are not restrained by sequence conservation. Importantly, this method is generally applicable to other proteins about which homologous-structure information is available.

  9. Full-length single-cell RNA-seq applied to a viral human cancer: applications to HPV expression and splicing analysis in HeLa S3 cells.

    Science.gov (United States)

    Wu, Liang; Zhang, Xiaolong; Zhao, Zhikun; Wang, Ling; Li, Bo; Li, Guibo; Dean, Michael; Yu, Qichao; Wang, Yanhui; Lin, Xinxin; Rao, Weijian; Mei, Zhanlong; Li, Yang; Jiang, Runze; Yang, Huan; Li, Fuqiang; Xie, Guoyun; Xu, Liqin; Wu, Kui; Zhang, Jie; Chen, Jianghao; Wang, Ting; Kristiansen, Karsten; Zhang, Xiuqing; Li, Yingrui; Yang, Huanming; Wang, Jian; Hou, Yong; Xu, Xun

    2015-01-01

    Viral infection causes multiple forms of human cancer, and HPV infection is the primary factor in cervical carcinomas. Recent single-cell RNA-seq studies highlight the tumor heterogeneity present in most cancers, but virally induced tumors have not been studied. HeLa is a well characterized HPV+ cervical cancer cell line. We developed a new high throughput platform to prepare single-cell RNA on a nanoliter scale based on a customized microwell chip. Using this method, we successfully amplified full-length transcripts of 669 single HeLa S3 cells and 40 of them were randomly selected to perform single-cell RNA sequencing. Based on these data, we obtained a comprehensive understanding of the heterogeneity of HeLa S3 cells in gene expression, alternative splicing and fusions. Furthermore, we identified a high diversity of HPV-18 expression and splicing at the single-cell level. By co-expression analysis we identified 283 E6, E7 co-regulated genes, including CDC25, PCNA, PLK4, BUB1B and IRF1 known to interact with HPV viral proteins. Our results reveal the heterogeneity of a virus-infected cell line. It not only provides a transcriptome characterization of HeLa S3 cells at the single cell level, but is a demonstration of the power of single cell RNA-seq analysis of virally infected cells and cancers.

  10. Developing a novel fiber optic fluorescence device for multiplexed high-throughput cytotoxic screening.

    Science.gov (United States)

    Lee, Dennis; Barnes, Stephen

    2010-01-01

    The need for new pharmacological agents is unending. Yet the drug discovery process has changed substantially over the past decade and continues to evolve in response to new technologies. There is presently a high demand to reduce discovery time by improving specific lab disciplines and developing new technology platforms in the area of cell-based assay screening. Here we present the developmental concept and early stage testing of the Ab-Sniffer, a novel fiber optic fluorescence device for high-throughput cytotoxicity screening using an immobilized whole cell approach. The fused silica fibers are chemically functionalized with biotin to provide interaction with fluorescently labeled, streptavidin functionalized alginate-chitosan microspheres. The microspheres are also functionalized with Concanavalin A to facilitate binding to living cells. By using lymphoma cells and rituximab in an adaptation of a well-known cytotoxicity protocol we demonstrate the utility of the Ab-Sniffer for functional screening of potential drug compounds rather than indirect, non-functional screening via binding assay. The platform can be extended to any assay capable of being tied to a fluorescence response including multiple target cells in each well of a multi-well plate for high-throughput screening.

  11. High throughput testing of the SV40 Large T antigen binding to cellular p53 identifies putative drugs for the treatment of SV40-related cancers

    International Nuclear Information System (INIS)

    Carbone, Michele; Rudzinski, Jennifer; Bocchetta, Maurizio

    2003-01-01

    SV40 has been linked to some human malignancies, and the evidence that this virus plays a causative role in mesothelioma and brain tumors is mounting. The major SV40 oncoprotein is the Large tumor antigen (Tag). A key Tag transforming activity is connected to its capability to bind and inactivate cellular p53. In this study we developed an effective, high throughput, ELISA-based method to study Tag-p53 interaction in vitro. This assay allowed us to screen a chemical library and to identify a chemical inhibitor of the Tag binding to p53. We propose that our in vitro assay is a useful method to identify molecules that may be used as therapeutic agents for the treatment of SV40-related human cancers

  12. msBiodat analysis tool, big data analysis for high-throughput experiments.

    Science.gov (United States)

    Muñoz-Torres, Pau M; Rokć, Filip; Belužic, Robert; Grbeša, Ivana; Vugrek, Oliver

    2016-01-01

    Mass spectrometry (MS) are a group of a high-throughput techniques used to increase knowledge about biomolecules. They produce a large amount of data which is presented as a list of hundreds or thousands of proteins. Filtering those data efficiently is the first step for extracting biologically relevant information. The filtering may increase interest by merging previous data with the data obtained from public databases, resulting in an accurate list of proteins which meet the predetermined conditions. In this article we present msBiodat Analysis Tool, a web-based application thought to approach proteomics to the big data analysis. With this tool, researchers can easily select the most relevant information from their MS experiments using an easy-to-use web interface. An interesting feature of msBiodat analysis tool is the possibility of selecting proteins by its annotation on Gene Ontology using its Gene Id, ensembl or UniProt codes. The msBiodat analysis tool is a web-based application that allows researchers with any programming experience to deal with efficient database querying advantages. Its versatility and user-friendly interface makes easy to perform fast and accurate data screening by using complex queries. Once the analysis is finished, the result is delivered by e-mail. msBiodat analysis tool is freely available at http://msbiodata.irb.hr.

  13. Optimization Of A High-Throughput Transcriptomic (HTTr) Bioactivity Screen In MCF7 Cells Using Targeted RNA-Seq (SOT)

    Science.gov (United States)

    Recent advances in targeted RNA-Seq technology allow researchers to efficiently and cost-effectively obtain whole transcriptome profiles using picograms of mRNA from human cell lysates. Low mRNA input requirements and sample multiplexing capabilities has made time- and concentrat...

  14. HAMS: High-Affinity Mass Spectrometry Screening. A High-Throughput Screening Method for Identifying the Tightest-Binding Lead Compounds for Target Proteins with No False Positive Identifications.

    Science.gov (United States)

    Imaduwage, Kasun P; Go, Eden P; Zhu, Zhikai; Desaire, Heather

    2016-11-01

    A major challenge in drug discovery is the identification of high affinity lead compounds that bind a particular target protein; these leads are typically identified by high throughput screens. Mass spectrometry has become a detection method of choice in drug screening assays because the target and the ligand need not be modified. Label-free assays are advantageous because they can be developed more rapidly than assays requiring labels, and they eliminate the risk of the label interfering with the binding event. However, in commonly used MS-based screening methods, detection of false positives is a major challenge. Here, we describe a detection strategy designed to eliminate false positives. In this approach, the protein and the ligands are incubated together, and the non-binders are separated for detection. Hits (protein binders) are not detectable by MS after incubation with the protein, but readily identifiable by MS when the target protein is not present in the incubation media. The assay was demonstrated using three different proteins and hundreds of non-inhibitors; no false positive hits were identified in any experiment. The assay can be tuned to select for ligands of a particular binding affinity by varying the quantity of protein used and the immobilization method. As examples, the method selectively detected inhibitors that have K i values of 0.2 μM, 50 pM, and 700 pM. These findings demonstrate that the approach described here compares favorably with traditional MS-based screening methods. Graphical Abstract ᅟ.

  15. The Role of Genome Accessibility in Transcription Factor Binding in Bacteria.

    Directory of Open Access Journals (Sweden)

    Antonio L C Gomes

    2016-04-01

    Full Text Available ChIP-seq enables genome-scale identification of regulatory regions that govern gene expression. However, the biological insights generated from ChIP-seq analysis have been limited to predictions of binding sites and cooperative interactions. Furthermore, ChIP-seq data often poorly correlate with in vitro measurements or predicted motifs, highlighting that binding affinity alone is insufficient to explain transcription factor (TF-binding in vivo. One possibility is that binding sites are not equally accessible across the genome. A more comprehensive biophysical representation of TF-binding is required to improve our ability to understand, predict, and alter gene expression. Here, we show that genome accessibility is a key parameter that impacts TF-binding in bacteria. We developed a thermodynamic model that parameterizes ChIP-seq coverage in terms of genome accessibility and binding affinity. The role of genome accessibility is validated using a large-scale ChIP-seq dataset of the M. tuberculosis regulatory network. We find that accounting for genome accessibility led to a model that explains 63% of the ChIP-seq profile variance, while a model based in motif score alone explains only 35% of the variance. Moreover, our framework enables de novo ChIP-seq peak prediction and is useful for inferring TF-binding peaks in new experimental conditions by reducing the need for additional experiments. We observe that the genome is more accessible in intergenic regions, and that increased accessibility is positively correlated with gene expression and anti-correlated with distance to the origin of replication. Our biophysically motivated model provides a more comprehensive description of TF-binding in vivo from first principles towards a better representation of gene regulation in silico, with promising applications in systems biology.

  16. SeqAnt: A web service to rapidly identify and annotate DNA sequence variations

    Directory of Open Access Journals (Sweden)

    Patel Viren

    2010-09-01

    Full Text Available Abstract Background The enormous throughput and low cost of second-generation sequencing platforms now allow research and clinical geneticists to routinely perform single experiments that identify tens of thousands to millions of variant sites. Existing methods to annotate variant sites using information from publicly available databases via web browsers are too slow to be useful for the large sequencing datasets being routinely generated by geneticists. Because sequence annotation of variant sites is required before functional characterization can proceed, the lack of a high-throughput pipeline to efficiently annotate variant sites can act as a significant bottleneck in genetics research. Results SeqAnt (Sequence Annotator is an open source web service and software package that rapidly annotates DNA sequence variants and identifies recessive or compound heterozygous loci in human, mouse, fly, and worm genome sequencing experiments. Variants are characterized with respect to their functional type, frequency, and evolutionary conservation. Annotated variants can be viewed on a web browser, downloaded in a tab-delimited text file, or directly uploaded in a BED format to the UCSC genome browser. To demonstrate the speed of SeqAnt, we annotated a series of publicly available datasets that ranged in size from 37 to 3,439,107 variant sites. The total time to completely annotate these data completely ranged from 0.17 seconds to 28 minutes 49.8 seconds. Conclusion SeqAnt is an open source web service and software package that overcomes a critical bottleneck facing research and clinical geneticists using second-generation sequencing platforms. SeqAnt will prove especially useful for those investigators who lack dedicated bioinformatics personnel or infrastructure in their laboratories.

  17. Computational and statistical methods for high-throughput analysis of post-translational modifications of proteins

    DEFF Research Database (Denmark)

    Schwämmle, Veit; Braga, Thiago Verano; Roepstorff, Peter

    2015-01-01

    The investigation of post-translational modifications (PTMs) represents one of the main research focuses for the study of protein function and cell signaling. Mass spectrometry instrumentation with increasing sensitivity improved protocols for PTM enrichment and recently established pipelines...... for high-throughput experiments allow large-scale identification and quantification of several PTM types. This review addresses the concurrently emerging challenges for the computational analysis of the resulting data and presents PTM-centered approaches for spectra identification, statistical analysis...

  18. Robust Identification of Developmentally Active Endothelial Enhancers in Zebrafish Using FANS-Assisted ATAC-Seq.

    Science.gov (United States)

    Quillien, Aurelie; Abdalla, Mary; Yu, Jun; Ou, Jianhong; Zhu, Lihua Julie; Lawson, Nathan D

    2017-07-18

    Identification of tissue-specific and developmentally active enhancers provides insights into mechanisms that control gene expression during embryogenesis. However, robust detection of these regulatory elements remains challenging, especially in vertebrate genomes. Here, we apply fluorescent-activated nuclei sorting (FANS) followed by Assay for Transposase-Accessible Chromatin with high-throughput sequencing (ATAC-seq) to identify developmentally active endothelial enhancers in the zebrafish genome. ATAC-seq of nuclei from Tg(fli1a:egfp) y1 transgenic embryos revealed expected patterns of nucleosomal positioning at transcriptional start sites throughout the genome and association with active histone modifications. Comparison of ATAC-seq from GFP-positive and -negative nuclei identified more than 5,000 open elements specific to endothelial cells. These elements flanked genes functionally important for vascular development and that displayed endothelial-specific gene expression. Importantly, a majority of tested elements drove endothelial gene expression in zebrafish embryos. Thus, FANS-assisted ATAC-seq using transgenic zebrafish embryos provides a robust approach for genome-wide identification of active tissue-specific enhancer elements. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

  19. TRANSIT--A Software Tool for Himar1 TnSeq Analysis.

    Directory of Open Access Journals (Sweden)

    Michael A DeJesus

    2015-10-01

    Full Text Available TnSeq has become a popular technique for determining the essentiality of genomic regions in bacterial organisms. Several methods have been developed to analyze the wealth of data that has been obtained through TnSeq experiments. We developed a tool for analyzing Himar1 TnSeq data called TRANSIT. TRANSIT provides a graphical interface to three different statistical methods for analyzing TnSeq data. These methods cover a variety of approaches capable of identifying essential genes in individual datasets as well as comparative analysis between conditions. We demonstrate the utility of this software by analyzing TnSeq datasets of M. tuberculosis grown on glycerol and cholesterol. We show that TRANSIT can be used to discover genes which have been previously implicated for growth on these carbon sources. TRANSIT is written in Python, and thus can be run on Windows, OSX and Linux platforms. The source code is distributed under the GNU GPL v3 license and can be obtained from the following GitHub repository: https://github.com/mad-lab/transit.

  20. GlycoExtractor: a web-based interface for high throughput processing of HPLC-glycan data.

    Science.gov (United States)

    Artemenko, Natalia V; Campbell, Matthew P; Rudd, Pauline M

    2010-04-05

    Recently, an automated high-throughput HPLC platform has been developed that can be used to fully sequence and quantify low concentrations of N-linked sugars released from glycoproteins, supported by an experimental database (GlycoBase) and analytical tools (autoGU). However, commercial packages that support the operation of HPLC instruments and data storage lack platforms for the extraction of large volumes of data. The lack of resources and agreed formats in glycomics is now a major limiting factor that restricts the development of bioinformatic tools and automated workflows for high-throughput HPLC data analysis. GlycoExtractor is a web-based tool that interfaces with a commercial HPLC database/software solution to facilitate the extraction of large volumes of processed glycan profile data (peak number, peak areas, and glucose unit values). The tool allows the user to export a series of sample sets to a set of file formats (XML, JSON, and CSV) rather than a collection of disconnected files. This approach not only reduces the amount of manual refinement required to export data into a suitable format for data analysis but also opens the field to new approaches for high-throughput data interpretation and storage, including biomarker discovery and validation and monitoring of online bioprocessing conditions for next generation biotherapeutics.

  1. High-throughput purification of recombinant proteins using self-cleaving intein tags.

    Science.gov (United States)

    Coolbaugh, M J; Shakalli Tang, M J; Wood, D W

    2017-01-01

    High throughput methods for recombinant protein production using E. coli typically involve the use of affinity tags for simple purification of the protein of interest. One drawback of these techniques is the occasional need for tag removal before study, which can be hard to predict. In this work, we demonstrate two high throughput purification methods for untagged protein targets based on simple and cost-effective self-cleaving intein tags. Two model proteins, E. coli beta-galactosidase (βGal) and superfolder green fluorescent protein (sfGFP), were purified using self-cleaving versions of the conventional chitin-binding domain (CBD) affinity tag and the nonchromatographic elastin-like-polypeptide (ELP) precipitation tag in a 96-well filter plate format. Initial tests with shake flask cultures confirmed that the intein purification scheme could be scaled down, with >90% pure product generated in a single step using both methods. The scheme was then validated in a high throughput expression platform using 24-well plate cultures followed by purification in 96-well plates. For both tags and with both target proteins, the purified product was consistently obtained in a single-step, with low well-to-well and plate-to-plate variability. This simple method thus allows the reproducible production of highly pure untagged recombinant proteins in a convenient microtiter plate format. Copyright © 2016 Elsevier Inc. All rights reserved.

  2. High-throughput kinase assays with protein substrates using fluorescent polymer superquenching

    Directory of Open Access Journals (Sweden)

    Weatherford Wendy

    2005-05-01

    Full Text Available Abstract Background High-throughput screening is used by the pharmaceutical industry for identifying lead compounds that interact with targets of pharmacological interest. Because of the key role that aberrant regulation of protein phosphorylation plays in diseases such as cancer, diabetes and hypertension, kinases have become one of the main drug targets. With the exception of antibody-based assays, methods to screen for specific kinase activity are generally restricted to the use of small synthetic peptides as substrates. However, the use of natural protein substrates has the advantage that potential inhibitors can be detected that affect enzyme activity by binding to a site other than the catalytic site. We have previously reported a non-radioactive and non-antibody-based fluorescence quench assay for detection of phosphorylation or dephosphorylation using synthetic peptide substrates. The aim of this work is to develop an assay for detection of phosphorylation of chemically unmodified proteins based on this polymer superquenching platform. Results Using a modified QTL Lightspeed™ assay, phosphorylation of native protein was quantified by the interaction of the phosphorylated proteins with metal-ion coordinating groups co-located with fluorescent polymer deposited onto microspheres. The binding of phospho-protein inhibits a dye-labeled "tracer" peptide from associating to the phosphate-binding sites present on the fluorescent microspheres. The resulting inhibition of quench generates a "turn on" assay, in which the signal correlates with the phosphorylation of the substrate. The assay was tested on three different proteins: Myelin Basic Protein (MBP, Histone H1 and Phosphorylated heat- and acid-stable protein (PHAS-1. Phosphorylation of the proteins was detected by Protein Kinase Cα (PKCα and by the Interleukin -1 Receptor-associated Kinase 4 (IRAK4. Enzyme inhibition yielded IC50 values that were comparable to those obtained using

  3. High-throughput kinase assays with protein substrates using fluorescent polymer superquenching.

    Science.gov (United States)

    Rininsland, Frauke; Stankewicz, Casey; Weatherford, Wendy; McBranch, Duncan

    2005-05-31

    High-throughput screening is used by the pharmaceutical industry for identifying lead compounds that interact with targets of pharmacological interest. Because of the key role that aberrant regulation of protein phosphorylation plays in diseases such as cancer, diabetes and hypertension, kinases have become one of the main drug targets. With the exception of antibody-based assays, methods to screen for specific kinase activity are generally restricted to the use of small synthetic peptides as substrates. However, the use of natural protein substrates has the advantage that potential inhibitors can be detected that affect enzyme activity by binding to a site other than the catalytic site. We have previously reported a non-radioactive and non-antibody-based fluorescence quench assay for detection of phosphorylation or dephosphorylation using synthetic peptide substrates. The aim of this work is to develop an assay for detection of phosphorylation of chemically unmodified proteins based on this polymer superquenching platform. Using a modified QTL Lightspeed assay, phosphorylation of native protein was quantified by the interaction of the phosphorylated proteins with metal-ion coordinating groups co-located with fluorescent polymer deposited onto microspheres. The binding of phospho-protein inhibits a dye-labeled "tracer" peptide from associating to the phosphate-binding sites present on the fluorescent microspheres. The resulting inhibition of quench generates a "turn on" assay, in which the signal correlates with the phosphorylation of the substrate. The assay was tested on three different proteins: Myelin Basic Protein (MBP), Histone H1 and Phosphorylated heat- and acid-stable protein (PHAS-1). Phosphorylation of the proteins was detected by Protein Kinase Calpha (PKCalpha) and by the Interleukin -1 Receptor-associated Kinase 4 (IRAK4). Enzyme inhibition yielded IC50 values that were comparable to those obtained using peptide substrates. Statistical parameters that

  4. A strand-specific RNA-Seq analysis of the transcriptome of the typhoid bacillus Salmonella typhi.

    Directory of Open Access Journals (Sweden)

    Timothy T Perkins

    2009-07-01

    Full Text Available High-density, strand-specific cDNA sequencing (ssRNA-seq was used to analyze the transcriptome of Salmonella enterica serovar Typhi (S. Typhi. By mapping sequence data to the entire S. Typhi genome, we analyzed the transcriptome in a strand-specific manner and further defined transcribed regions encoded within prophages, pseudogenes, previously un-annotated, and 3'- or 5'-untranslated regions (UTR. An additional 40 novel candidate non-coding RNAs were identified beyond those previously annotated. Proteomic analysis was combined with transcriptome data to confirm and refine the annotation of a number of hpothetical genes. ssRNA-seq was also combined with microarray and proteome analysis to further define the S. Typhi OmpR regulon and identify novel OmpR regulated transcripts. Thus, ssRNA-seq provides a novel and powerful approach to the characterization of the bacterial transcriptome.

  5. Targeted DNA Methylation Analysis by High Throughput Sequencing in Porcine Peri-attachment Embryos

    OpenAIRE

    MORRILL, Benson H.; COX, Lindsay; WARD, Anika; HEYWOOD, Sierra; PRATHER, Randall S.; ISOM, S. Clay

    2013-01-01

    Abstract The purpose of this experiment was to implement and evaluate the effectiveness of a next-generation sequencing-based method for DNA methylation analysis in porcine embryonic samples. Fourteen discrete genomic regions were amplified by PCR using bisulfite-converted genomic DNA derived from day 14 in vivo-derived (IVV) and parthenogenetic (PA) porcine embryos as template DNA. Resulting PCR products were subjected to high-throughput sequencing using the Illumina Genome Analyzer IIx plat...

  6. The high throughput biomedicine unit at the institute for molecular medicine Finland: high throughput screening meets precision medicine.

    Science.gov (United States)

    Pietiainen, Vilja; Saarela, Jani; von Schantz, Carina; Turunen, Laura; Ostling, Paivi; Wennerberg, Krister

    2014-05-01

    The High Throughput Biomedicine (HTB) unit at the Institute for Molecular Medicine Finland FIMM was established in 2010 to serve as a national and international academic screening unit providing access to state of the art instrumentation for chemical and RNAi-based high throughput screening. The initial focus of the unit was multiwell plate based chemical screening and high content microarray-based siRNA screening. However, over the first four years of operation, the unit has moved to a more flexible service platform where both chemical and siRNA screening is performed at different scales primarily in multiwell plate-based assays with a wide range of readout possibilities with a focus on ultraminiaturization to allow for affordable screening for the academic users. In addition to high throughput screening, the equipment of the unit is also used to support miniaturized, multiplexed and high throughput applications for other types of research such as genomics, sequencing and biobanking operations. Importantly, with the translational research goals at FIMM, an increasing part of the operations at the HTB unit is being focused on high throughput systems biological platforms for functional profiling of patient cells in personalized and precision medicine projects.

  7. Annotating Protein Functional Residues by Coupling High-Throughput Fitness Profile and Homologous-Structure Analysis.

    Science.gov (United States)

    Du, Yushen; Wu, Nicholas C; Jiang, Lin; Zhang, Tianhao; Gong, Danyang; Shu, Sara; Wu, Ting-Ting; Sun, Ren

    2016-11-01

    Identification and annotation of functional residues are fundamental questions in protein sequence analysis. Sequence and structure conservation provides valuable information to tackle these questions. It is, however, limited by the incomplete sampling of sequence space in natural evolution. Moreover, proteins often have multiple functions, with overlapping sequences that present challenges to accurate annotation of the exact functions of individual residues by conservation-based methods. Using the influenza A virus PB1 protein as an example, we developed a method to systematically identify and annotate functional residues. We used saturation mutagenesis and high-throughput sequencing to measure the replication capacity of single nucleotide mutations across the entire PB1 protein. After predicting protein stability upon mutations, we identified functional PB1 residues that are essential for viral replication. To further annotate the functional residues important to the canonical or noncanonical functions of viral RNA-dependent RNA polymerase (vRdRp), we performed a homologous-structure analysis with 16 different vRdRp structures. We achieved high sensitivity in annotating the known canonical polymerase functional residues. Moreover, we identified a cluster of noncanonical functional residues located in the loop region of the PB1 β-ribbon. We further demonstrated that these residues were important for PB1 protein nuclear import through the interaction with Ran-binding protein 5. In summary, we developed a systematic and sensitive method to identify and annotate functional residues that are not restrained by sequence conservation. Importantly, this method is generally applicable to other proteins about which homologous-structure information is available. To fully comprehend the diverse functions of a protein, it is essential to understand the functionality of individual residues. Current methods are highly dependent on evolutionary sequence conservation, which is

  8. Linnorm: improved statistical analysis for single cell RNA-seq expression data.

    Science.gov (United States)

    Yip, Shun H; Wang, Panwen; Kocher, Jean-Pierre A; Sham, Pak Chung; Wang, Junwen

    2017-12-15

    Linnorm is a novel normalization and transformation method for the analysis of single cell RNA sequencing (scRNA-seq) data. Linnorm is developed to remove technical noises and simultaneously preserve biological variations in scRNA-seq data, such that existing statistical methods can be improved. Using real scRNA-seq data, we compared Linnorm with existing normalization methods, including NODES, SAMstrt, SCnorm, scran, DESeq and TMM. Linnorm shows advantages in speed, technical noise removal and preservation of cell heterogeneity, which can improve existing methods in the discovery of novel subtypes, pseudo-temporal ordering of cells, clustering analysis, etc. Linnorm also performs better than existing DEG analysis methods, including BASiCS, NODES, SAMstrt, Seurat and DESeq2, in false positive rate control and accuracy. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  9. Development of a High-Throughput Screen for Inhibitors of Epstein-Barr Virus EBNA1

    Science.gov (United States)

    Thompson, Scott; Messick, Troy; Schultz, David C.; Reichman, Melvin; Lieberman, Paul M.

    2012-01-01

    Latent infection with Epstein-Barr Virus (EBV) is a carcinogenic cofactor in several lymphoid and epithelial cell malignancies. At present, there are no small molecule inhibitors that specifically target EBV latent infection or latency-associated oncoproteins. EBNA1 is an EBV-encoded sequence-specific DNA-binding protein that is consistently expressed in EBV-associated tumors and required for stable maintenance of the viral genome in proliferating cells. EBNA1 is also thought to provide cell survival function in latently infected cells. In this work we describe the development of a biochemical high-throughput screening (HTS) method using a homogenous fluorescence polarization (FP) assay monitoring EBNA1 binding to its cognate DNA binding site. An FP-based counterscreen was developed using another EBV-encoded DNA binding protein, Zta, and its cognate DNA binding site. We demonstrate that EBNA1 binding to a fluorescent labeled DNA probe provides a robust assay with a Z-factor consistently greater than 0.6. A pilot screen of a small molecule library of ~14,000 compounds identified 3 structurally related molecules that selectively inhibit EBNA1, but not Zta. All three compounds had activity in a cell-based assay specific for the disruption of EBNA1 transcription repression function. One of the compounds was effective in reducing EBV genome copy number in Raji Burkitt lymphoma cells. These experiments provide a proof-of-concept that small molecule inhibitors of EBNA1 can be identified by biochemical high-throughput screening of compound libraries. Further screening in conjunction with medicinal chemistry optimization may provide a selective inhibitor of EBNA1 and EBV latent infection. PMID:20930215

  10. High-throughput sequencing and pathway analysis reveal alteration of the pituitary transcriptome by 17α-ethynylestradiol (EE2) in female coho salmon, Oncorhynchus kisutch

    Energy Technology Data Exchange (ETDEWEB)

    Harding, Louisa B. [School of Aquatic and Fishery Sciences, University of Washington, Seattle, WA 98195 (United States); Schultz, Irvin R. [Battelle, Marine Sciences Laboratory – Pacific Northwest National Laboratory, 1529 West Sequim Bay Road, Sequim, WA 98382 (United States); Goetz, Giles W. [School of Aquatic and Fishery Sciences, University of Washington, Seattle, WA 98195 (United States); Luckenbach, J. Adam [Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, 2725 Montlake Blvd E, Seattle, WA 98112 (United States); Center for Reproductive Biology, Washington State University, Pullman, WA 98164 (United States); Young, Graham [School of Aquatic and Fishery Sciences, University of Washington, Seattle, WA 98195 (United States); Center for Reproductive Biology, Washington State University, Pullman, WA 98164 (United States); Goetz, Frederick W. [Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Manchester Research Station, P.O. Box 130, Manchester, WA 98353 (United States); Swanson, Penny, E-mail: penny.swanson@noaa.gov [Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, 2725 Montlake Blvd E, Seattle, WA 98112 (United States); Center for Reproductive Biology, Washington State University, Pullman, WA 98164 (United States)

    2013-10-15

    Highlights: •Studied impacts of ethynylestradiol (EE2) exposure on salmon pituitary transcriptome. •High-throughput sequencing, RNAseq, and pathway analysis were performed. •EE2 altered mRNAs for genes in circadian rhythm, GnRH, and TGFβ signaling pathways. •LH and FSH beta subunit mRNAs were most highly up- and down-regulated by EE2, respectively. •Estrogens may alter processes associated with reproductive timing in salmon. -- Abstract: Considerable research has been done on the effects of endocrine disrupting chemicals (EDCs) on reproduction and gene expression in the brain, liver and gonads of teleost fish, but information on impacts to the pituitary gland are still limited despite its central role in regulating reproduction. The aim of this study was to further our understanding of the potential effects of natural and synthetic estrogens on the brain–pituitary–gonad axis in fish by determining the effects of 17α-ethynylestradiol (EE2) on the pituitary transcriptome. We exposed sub-adult coho salmon (Oncorhynchus kisutch) to 0 or 12 ng EE2/L for up to 6 weeks and effects on the pituitary transcriptome of females were assessed using high-throughput Illumina{sup ®} sequencing, RNA-Seq and pathway analysis. After 1 or 6 weeks, 218 and 670 contiguous sequences (contigs) respectively, were differentially expressed in pituitaries of EE2-exposed fish relative to control. Two of the most highly up- and down-regulated contigs were luteinizing hormone β subunit (241-fold and 395-fold at 1 and 6 weeks, respectively) and follicle-stimulating hormone β subunit (−3.4-fold at 6 weeks). Additional contigs related to gonadotropin synthesis and release were differentially expressed in EE2-exposed fish relative to controls. These included contigs involved in gonadotropin releasing hormone (GNRH) and transforming growth factor-β signaling. There was an over-representation of significantly affected contigs in 33 and 18 canonical pathways at 1 and 6 weeks

  11. High-throughput sequencing and pathway analysis reveal alteration of the pituitary transcriptome by 17α-ethynylestradiol (EE2) in female coho salmon, Oncorhynchus kisutch

    International Nuclear Information System (INIS)

    Harding, Louisa B.; Schultz, Irvin R.; Goetz, Giles W.; Luckenbach, J. Adam; Young, Graham; Goetz, Frederick W.; Swanson, Penny

    2013-01-01

    Highlights: •Studied impacts of ethynylestradiol (EE2) exposure on salmon pituitary transcriptome. •High-throughput sequencing, RNAseq, and pathway analysis were performed. •EE2 altered mRNAs for genes in circadian rhythm, GnRH, and TGFβ signaling pathways. •LH and FSH beta subunit mRNAs were most highly up- and down-regulated by EE2, respectively. •Estrogens may alter processes associated with reproductive timing in salmon. -- Abstract: Considerable research has been done on the effects of endocrine disrupting chemicals (EDCs) on reproduction and gene expression in the brain, liver and gonads of teleost fish, but information on impacts to the pituitary gland are still limited despite its central role in regulating reproduction. The aim of this study was to further our understanding of the potential effects of natural and synthetic estrogens on the brain–pituitary–gonad axis in fish by determining the effects of 17α-ethynylestradiol (EE2) on the pituitary transcriptome. We exposed sub-adult coho salmon (Oncorhynchus kisutch) to 0 or 12 ng EE2/L for up to 6 weeks and effects on the pituitary transcriptome of females were assessed using high-throughput Illumina ® sequencing, RNA-Seq and pathway analysis. After 1 or 6 weeks, 218 and 670 contiguous sequences (contigs) respectively, were differentially expressed in pituitaries of EE2-exposed fish relative to control. Two of the most highly up- and down-regulated contigs were luteinizing hormone β subunit (241-fold and 395-fold at 1 and 6 weeks, respectively) and follicle-stimulating hormone β subunit (−3.4-fold at 6 weeks). Additional contigs related to gonadotropin synthesis and release were differentially expressed in EE2-exposed fish relative to controls. These included contigs involved in gonadotropin releasing hormone (GNRH) and transforming growth factor-β signaling. There was an over-representation of significantly affected contigs in 33 and 18 canonical pathways at 1 and 6 weeks

  12. Development and evaluation of the first high-throughput SNP array for common carp (Cyprinus carpio).

    Science.gov (United States)

    Xu, Jian; Zhao, Zixia; Zhang, Xiaofeng; Zheng, Xianhu; Li, Jiongtang; Jiang, Yanliang; Kuang, Youyi; Zhang, Yan; Feng, Jianxin; Li, Chuangju; Yu, Juhua; Li, Qiang; Zhu, Yuanyuan; Liu, Yuanyuan; Xu, Peng; Sun, Xiaowen

    2014-04-24

    A large number of single nucleotide polymorphisms (SNPs) have been identified in common carp (Cyprinus carpio) but, as yet, no high-throughput genotyping platform is available for this species. C. carpio is an important aquaculture species that accounts for nearly 14% of freshwater aquaculture production worldwide. We have developed an array for C. carpio with 250,000 SNPs and evaluated its performance using samples from various strains of C. carpio. The SNPs used on the array were selected from two resources: the transcribed sequences from RNA-seq data of four strains of C. carpio, and the genome re-sequencing data of five strains of C. carpio. The 250,000 SNPs on the resulting array are distributed evenly across the reference C.carpio genome with an average spacing of 6.6 kb. To evaluate the SNP array, 1,072 C. carpio samples were collected and tested. Of the 250,000 SNPs on the array, 185,150 (74.06%) were found to be polymorphic sites. Genotyping accuracy was checked using genotyping data from a group of full-siblings and their parents, and over 99.8% of the qualified SNPs were found to be reliable. Analysis of the linkage disequilibrium on all samples and on three domestic C.carpio strains revealed that the latter had the longer haplotype blocks. We also evaluated our SNP array on 80 samples from eight species related to C. carpio, with from 53,526 to 71,984 polymorphic SNPs. An identity by state analysis divided all the samples into three clusters; most of the C. carpio strains formed the largest cluster. The Carp SNP array described here is the first high-throughput genotyping platform for C. carpio. Our evaluation of this array indicates that it will be valuable for farmed carp and for genetic and population biology studies in C. carpio and related species.

  13. High-throughput bioaffinity mass spectrometry for screening and identification of designer anabolic steroids in dietary supplements.

    Science.gov (United States)

    Aqai, Payam; Cevik, Ebru; Gerssen, Arjen; Haasnoot, Willem; Nielen, Michel W F

    2013-03-19

    A generic high-throughput bioaffinity liquid chromatography-mass spectrometry (BioMS) approach was developed and applied for the screening and identification of known and unknown recombinant human sex hormone-binding globulin (rhSHBG)-binding designer steroids in dietary supplements. For screening, a semi-automated competitive inhibition binding assay was combined with fast ultrahigh-performance-LC-electrospray ionization-triple-quadrupole-MS (UPLC-QqQ-MS). 17β-Testosterone-D3 was used as the stable isotope label of which the binding to rhSHBG-coated paramagnetic microbeads was inhibited by any other binding (designer) steroid. The assay was performed in a 96-well plate and combined with the fast LC-MS, 96 measurements could be performed within 4 h. The concentration-dependent inhibition of the label by steroids in buffer and dietary supplements was demonstrated. Following an adjusted bioaffinity isolation procedure, suspect extracts were injected into a chip-UPLC(NanoTile)-Q-time-of-flight-MS system for full-scan accurate mass identification. Next to known steroids, 1-testosterone was identified in three of the supplements studied and the designer steroid tetrahydrogestrinone was identified in a spiked supplement. The generic steroid-binding assay can be used for high-throughput screening of androgens, estrogens, and gestagens in dietary supplements to fight doping. When combined with chip-UPLC-MS, it is a powerful tool for early warning of unknown emerging rhSHBG bioactive designer steroids in dietary supplements.

  14. The Open Connectome Project Data Cluster: Scalable Analysis and Vision for High-Throughput Neuroscience

    Science.gov (United States)

    Burns, Randal; Roncal, William Gray; Kleissas, Dean; Lillaney, Kunal; Manavalan, Priya; Perlman, Eric; Berger, Daniel R.; Bock, Davi D.; Chung, Kwanghun; Grosenick, Logan; Kasthuri, Narayanan; Weiler, Nicholas C.; Deisseroth, Karl; Kazhdan, Michael; Lichtman, Jeff; Reid, R. Clay; Smith, Stephen J.; Szalay, Alexander S.; Vogelstein, Joshua T.; Vogelstein, R. Jacob

    2013-01-01

    We describe a scalable database cluster for the spatial analysis and annotation of high-throughput brain imaging data, initially for 3-d electron microscopy image stacks, but for time-series and multi-channel data as well. The system was designed primarily for workloads that build connectomes— neural connectivity maps of the brain—using the parallel execution of computer vision algorithms on high-performance compute clusters. These services and open-science data sets are publicly available at openconnecto.me. The system design inherits much from NoSQL scale-out and data-intensive computing architectures. We distribute data to cluster nodes by partitioning a spatial index. We direct I/O to different systems—reads to parallel disk arrays and writes to solid-state storage—to avoid I/O interference and maximize throughput. All programming interfaces are RESTful Web services, which are simple and stateless, improving scalability and usability. We include a performance evaluation of the production system, highlighting the effec-tiveness of spatial data organization. PMID:24401992

  15. The Open Connectome Project Data Cluster: Scalable Analysis and Vision for High-Throughput Neuroscience.

    Science.gov (United States)

    Burns, Randal; Roncal, William Gray; Kleissas, Dean; Lillaney, Kunal; Manavalan, Priya; Perlman, Eric; Berger, Daniel R; Bock, Davi D; Chung, Kwanghun; Grosenick, Logan; Kasthuri, Narayanan; Weiler, Nicholas C; Deisseroth, Karl; Kazhdan, Michael; Lichtman, Jeff; Reid, R Clay; Smith, Stephen J; Szalay, Alexander S; Vogelstein, Joshua T; Vogelstein, R Jacob

    2013-01-01

    We describe a scalable database cluster for the spatial analysis and annotation of high-throughput brain imaging data, initially for 3-d electron microscopy image stacks, but for time-series and multi-channel data as well. The system was designed primarily for workloads that build connectomes - neural connectivity maps of the brain-using the parallel execution of computer vision algorithms on high-performance compute clusters. These services and open-science data sets are publicly available at openconnecto.me. The system design inherits much from NoSQL scale-out and data-intensive computing architectures. We distribute data to cluster nodes by partitioning a spatial index. We direct I/O to different systems-reads to parallel disk arrays and writes to solid-state storage-to avoid I/O interference and maximize throughput. All programming interfaces are RESTful Web services, which are simple and stateless, improving scalability and usability. We include a performance evaluation of the production system, highlighting the effec-tiveness of spatial data organization.

  16. esATAC: An Easy-to-use Systematic pipeline for ATAC-seq data analysis.

    Science.gov (United States)

    Wei, Zheng; Zhang, Wei; Fang, Huan; Li, Yanda; Wang, Xiaowo

    2018-03-07

    ATAC-seq is rapidly emerging as one of the major experimental approaches to probe chromatin accessibility genome-wide. Here, we present "esATAC", a highly integrated easy-to-use R/Bioconductor package, for systematic ATAC-seq data analysis. It covers essential steps for full analyzing procedure, including raw data processing, quality control and downstream statistical analysis such as peak calling, enrichment analysis and transcription factor footprinting. esATAC supports one command line execution for preset pipelines, and provides flexible interfaces for building customized pipelines. esATAC package is open source under the GPL-3.0 license. It is implemented in R and C ++. Source code and binaries for Linux, MAC OS X and Windows are available through Bioconductor https://www.bioconductor.org/packages/release/bioc/html/esATAC.html). xwwang@tsinghua.edu.cn. Supplementary data are available at Bioinformatics online.

  17. A ChIP-Seq benchmark shows that sequence conservation mainly improves detection of strong transcription factor binding sites.

    Directory of Open Access Journals (Sweden)

    Tony Håndstad

    Full Text Available BACKGROUND: Transcription factors are important controllers of gene expression and mapping transcription factor binding sites (TFBS is key to inferring transcription factor regulatory networks. Several methods for predicting TFBS exist, but there are no standard genome-wide datasets on which to assess the performance of these prediction methods. Also, it is believed that information about sequence conservation across different genomes can generally improve accuracy of motif-based predictors, but it is not clear under what circumstances use of conservation is most beneficial. RESULTS: Here we use published ChIP-seq data and an improved peak detection method to create comprehensive benchmark datasets for prediction methods which use known descriptors or binding motifs to detect TFBS in genomic sequences. We use this benchmark to assess the performance of five different prediction methods and find that the methods that use information about sequence conservation generally perform better than simpler motif-scanning methods. The difference is greater on high-affinity peaks and when using short and information-poor motifs. However, if the motifs are specific and information-rich, we find that simple motif-scanning methods can perform better than conservation-based methods. CONCLUSIONS: Our benchmark provides a comprehensive test that can be used to rank the relative performance of transcription factor binding site prediction methods. Moreover, our results show that, contrary to previous reports, sequence conservation is better suited for predicting strong than weak transcription factor binding sites.

  18. High throughput integrated thermal characterization with non-contact optical calorimetry

    Science.gov (United States)

    Hou, Sichao; Huo, Ruiqing; Su, Ming

    2017-10-01

    Commonly used thermal analysis tools such as calorimeter and thermal conductivity meter are separated instruments and limited by low throughput, where only one sample is examined each time. This work reports an infrared based optical calorimetry with its theoretical foundation, which is able to provide an integrated solution to characterize thermal properties of materials with high throughput. By taking time domain temperature information of spatially distributed samples, this method allows a single device (infrared camera) to determine the thermal properties of both phase change systems (melting temperature and latent heat of fusion) and non-phase change systems (thermal conductivity and heat capacity). This method further allows these thermal properties of multiple samples to be determined rapidly, remotely, and simultaneously. In this proof-of-concept experiment, the thermal properties of a panel of 16 samples including melting temperatures, latent heats of fusion, heat capacities, and thermal conductivities have been determined in 2 min with high accuracy. Given the high thermal, spatial, and temporal resolutions of the advanced infrared camera, this method has the potential to revolutionize the thermal characterization of materials by providing an integrated solution with high throughput, high sensitivity, and short analysis time.

  19. Insight into dynamic genome imaging: Canonical framework identification and high-throughput analysis.

    Science.gov (United States)

    Ronquist, Scott; Meixner, Walter; Rajapakse, Indika; Snyder, John

    2017-07-01

    The human genome is dynamic in structure, complicating researcher's attempts at fully understanding it. Time series "Fluorescent in situ Hybridization" (FISH) imaging has increased our ability to observe genome structure, but due to cell type and experimental variability this data is often noisy and difficult to analyze. Furthermore, computational analysis techniques are needed for homolog discrimination and canonical framework detection, in the case of time-series images. In this paper we introduce novel ideas for nucleus imaging analysis, present findings extracted using dynamic genome imaging, and propose an objective algorithm for high-throughput, time-series FISH imaging. While a canonical framework could not be detected beyond statistical significance in the analyzed dataset, a mathematical framework for detection has been outlined with extension to 3D image analysis. Copyright © 2017 Elsevier Inc. All rights reserved.

  20. expVIP: a Customizable RNA-seq Data Analysis and Visualization Platform.

    Science.gov (United States)

    Borrill, Philippa; Ramirez-Gonzalez, Ricardo; Uauy, Cristobal

    2016-04-01

    The majority of transcriptome sequencing (RNA-seq) expression studies in plants remain underutilized and inaccessible due to the use of disparate transcriptome references and the lack of skills and resources to analyze and visualize these data. We have developed expVIP, an expression visualization and integration platform, which allows easy analysis of RNA-seq data combined with an intuitive and interactive interface. Users can analyze public and user-specified data sets with minimal bioinformatics knowledge using the expVIP virtual machine. This generates a custom Web browser to visualize, sort, and filter the RNA-seq data and provides outputs for differential gene expression analysis. We demonstrate expVIP's suitability for polyploid crops and evaluate its performance across a range of biologically relevant scenarios. To exemplify its use in crop research, we developed a flexible wheat (Triticum aestivum) expression browser (www.wheat-expression.com) that can be expanded with user-generated data in a local virtual machine environment. The open-access expVIP platform will facilitate the analysis of gene expression data from a wide variety of species by enabling the easy integration, visualization, and comparison of RNA-seq data across experiments. © 2016 American Society of Plant Biologists. All Rights Reserved.

  1. Data exploration, quality control and statistical analysis of ChIP-exo/nexus experiments.

    Science.gov (United States)

    Welch, Rene; Chung, Dongjun; Grass, Jeffrey; Landick, Robert; Keles, Sündüz

    2017-09-06

    ChIP-exo/nexus experiments rely on innovative modifications of the commonly used ChIP-seq protocol for high resolution mapping of transcription factor binding sites. Although many aspects of the ChIP-exo data analysis are similar to those of ChIP-seq, these high throughput experiments pose a number of unique quality control and analysis challenges. We develop a novel statistical quality control pipeline and accompanying R/Bioconductor package, ChIPexoQual, to enable exploration and analysis of ChIP-exo and related experiments. ChIPexoQual evaluates a number of key issues including strand imbalance, library complexity, and signal enrichment of data. Assessment of these features are facilitated through diagnostic plots and summary statistics computed over regions of the genome with varying levels of coverage. We evaluated our QC pipeline with both large collections of public ChIP-exo/nexus data and multiple, new ChIP-exo datasets from Escherichia coli. ChIPexoQual analysis of these datasets resulted in guidelines for using these QC metrics across a wide range of sequencing depths and provided further insights for modelling ChIP-exo data. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  2. MSP-HTPrimer: a high-throughput primer design tool to improve assay design for DNA methylation analysis in epigenetics.

    Science.gov (United States)

    Pandey, Ram Vinay; Pulverer, Walter; Kallmeyer, Rainer; Beikircher, Gabriel; Pabinger, Stephan; Kriegner, Albert; Weinhäusel, Andreas

    2016-01-01

    Bisulfite (BS) conversion-based and methylation-sensitive restriction enzyme (MSRE)-based PCR methods have been the most commonly used techniques for locus-specific DNA methylation analysis. However, both methods have advantages and limitations. Thus, an integrated approach would be extremely useful to quantify the DNA methylation status successfully with great sensitivity and specificity. Designing specific and optimized primers for target regions is the most critical and challenging step in obtaining the adequate DNA methylation results using PCR-based methods. Currently, no integrated, optimized, and high-throughput methylation-specific primer design software methods are available for both BS- and MSRE-based methods. Therefore an integrated, powerful, and easy-to-use methylation-specific primer design pipeline with great accuracy and success rate will be very useful. We have developed a new web-based pipeline, called MSP-HTPrimer, to design primers pairs for MSP, BSP, pyrosequencing, COBRA, and MSRE assays on both genomic strands. First, our pipeline converts all target sequences into bisulfite-treated templates for both forward and reverse strand and designs all possible primer pairs, followed by filtering for single nucleotide polymorphisms (SNPs) and known repeat regions. Next, each primer pairs are annotated with the upstream and downstream RefSeq genes, CpG island, and cut sites (for COBRA and MSRE). Finally, MSP-HTPrimer selects specific primers from both strands based on custom and user-defined hierarchical selection criteria. MSP-HTPrimer produces a primer pair summary output table in TXT and HTML format for display and UCSC custom tracks for resulting primer pairs in GTF format. MSP-HTPrimer is an integrated, web-based, and high-throughput pipeline and has no limitation on the number and size of target sequences and designs MSP, BSP, pyrosequencing, COBRA, and MSRE assays. It is the only pipeline, which automatically designs primers on both genomic

  3. Accurate CpG and non-CpG cytosine methylation analysis by high-throughput locus-specific pyrosequencing in plants.

    Science.gov (United States)

    How-Kit, Alexandre; Daunay, Antoine; Mazaleyrat, Nicolas; Busato, Florence; Daviaud, Christian; Teyssier, Emeline; Deleuze, Jean-François; Gallusci, Philippe; Tost, Jörg

    2015-07-01

    Pyrosequencing permits accurate quantification of DNA methylation of specific regions where the proportions of the C/T polymorphism induced by sodium bisulfite treatment of DNA reflects the DNA methylation level. The commercially available high-throughput locus-specific pyrosequencing instruments allow for the simultaneous analysis of 96 samples, but restrict the DNA methylation analysis to CpG dinucleotide sites, which can be limiting in many biological systems. In contrast to mammals where DNA methylation occurs nearly exclusively on CpG dinucleotides, plants genomes harbor DNA methylation also in other sequence contexts including CHG and CHH motives, which cannot be evaluated by these pyrosequencing instruments due to software limitations. Here, we present a complete pipeline for accurate CpG and non-CpG cytosine methylation analysis at single base-resolution using high-throughput locus-specific pyrosequencing. The devised approach includes the design and validation of PCR amplification on bisulfite-treated DNA and pyrosequencing assays as well as the quantification of the methylation level at every cytosine from the raw peak intensities of the Pyrograms by two newly developed Visual Basic Applications. Our method presents accurate and reproducible results as exemplified by the cytosine methylation analysis of the promoter regions of two Tomato genes (NOR and CNR) encoding transcription regulators of fruit ripening during different stages of fruit development. Our results confirmed a significant and temporally coordinated loss of DNA methylation on specific cytosines during the early stages of fruit development in both promoters as previously shown by WGBS. The manuscript describes thus the first high-throughput locus-specific DNA methylation analysis in plants using pyrosequencing.

  4. Fish the ChIPs: a pipeline for automated genomic annotation of ChIP-Seq data

    Directory of Open Access Journals (Sweden)

    Minucci Saverio

    2011-10-01

    Full Text Available Abstract Background High-throughput sequencing is generating massive amounts of data at a pace that largely exceeds the throughput of data analysis routines. Here we introduce Fish the ChIPs (FC, a computational pipeline aimed at a broad public of users and designed to perform complete ChIP-Seq data analysis of an unlimited number of samples, thus increasing throughput, reproducibility and saving time. Results Starting from short read sequences, FC performs the following steps: 1 quality controls, 2 alignment to a reference genome, 3 peak calling, 4 genomic annotation, 5 generation of raw signal tracks for visualization on the UCSC and IGV genome browsers. FC exploits some of the fastest and most effective tools today available. Installation on a Mac platform requires very basic computational skills while configuration and usage are supported by a user-friendly graphic user interface. Alternatively, FC can be compiled from the source code on any Unix machine and then run with the possibility of customizing each single parameter through a simple configuration text file that can be generated using a dedicated user-friendly web-form. Considering the execution time, FC can be run on a desktop machine, even though the use of a computer cluster is recommended for analyses of large batches of data. FC is perfectly suited to work with data coming from Illumina Solexa Genome Analyzers or ABI SOLiD and its usage can potentially be extended to any sequencing platform. Conclusions Compared to existing tools, FC has two main advantages that make it suitable for a broad range of users. First of all, it can be installed and run by wet biologists on a Mac machine. Besides it can handle an unlimited number of samples, being convenient for large analyses. In this context, computational biologists can increase reproducibility of their ChIP-Seq data analyses while saving time for downstream analyses. Reviewers This article was reviewed by Gavin Huttley, George

  5. Simultaneous measurements of auto-immune and infectious disease specific antibodies using a high throughput multiplexing tool.

    Directory of Open Access Journals (Sweden)

    Atul Asati

    Full Text Available Considering importance of ganglioside antibodies as biomarkers in various immune-mediated neuropathies and neurological disorders, we developed a high throughput multiplexing tool for the assessment of gangliosides-specific antibodies based on Biolpex/Luminex platform. In this report, we demonstrate that the ganglioside high throughput multiplexing tool is robust, highly specific and demonstrating ∼100-fold higher concentration sensitivity for IgG detection than ELISA. In addition to the ganglioside-coated array, the high throughput multiplexing tool contains beads coated with influenza hemagglutinins derived from H1N1 A/Brisbane/59/07 and H1N1 A/California/07/09 strains. Influenza beads provided an added advantage of simultaneous detection of ganglioside- and influenza-specific antibodies, a capacity important for the assay of both infectious antigen-specific and autoimmune antibodies following vaccination or disease. Taken together, these results support the potential adoption of the ganglioside high throughput multiplexing tool for measuring ganglioside antibodies in various neuropathic and neurological disorders.

  6. High-Throughput Fabrication of Nanocone Substrates through Polymer Injection Moulding For SERS Analysis in Microfluidic Systems

    DEFF Research Database (Denmark)

    Viehrig, Marlitt; Matteucci, Marco; Thilsted, Anil H.

    analysis. Metal-capped silicon nanopillars, fabricated through a maskless ion etch, are state-of-the-art for on-chip SERS substrates. A dense cluster of high aspect ratio polymer nanocones was achieved by using high-throughput polymer injection moulding over a large area replicating a silicon nanopillar...... structure. Gold-capped polymer nanocones display similar SERS sensitivity as silicon nanopillars, while being easily integrable into a microfluidic chips....

  7. Assessing the utility and limitations of high throughput virtual screening

    Directory of Open Access Journals (Sweden)

    Paul Daniel Phillips

    2016-05-01

    Full Text Available Due to low cost, speed, and unmatched ability to explore large numbers of compounds, high throughput virtual screening and molecular docking engines have become widely utilized by computational scientists. It is generally accepted that docking engines, such as AutoDock, produce reliable qualitative results for ligand-macromolecular receptor binding, and molecular docking results are commonly reported in literature in the absence of complementary wet lab experimental data. In this investigation, three variants of the sixteen amino acid peptide, α-conotoxin MII, were docked to a homology model of the a3β2-nicotinic acetylcholine receptor. DockoMatic version 2.0 was used to perform a virtual screen of each peptide ligand to the receptor for ten docking trials consisting of 100 AutoDock cycles per trial. The results were analyzed for both variation in the calculated binding energy obtained from AutoDock, and the orientation of bound peptide within the receptor. The results show that, while no clear correlation exists between consistent ligand binding pose and the calculated binding energy, AutoDock is able to determine a consistent positioning of bound peptide in the majority of trials when at least ten trials were evaluated.

  8. High Throughput In vivo Analysis of Plant Leaf Chemical Properties Using Hyperspectral Imaging

    Directory of Open Access Journals (Sweden)

    Piyush Pandey

    2017-08-01

    Full Text Available Image-based high-throughput plant phenotyping in greenhouse has the potential to relieve the bottleneck currently presented by phenotypic scoring which limits the throughput of gene discovery and crop improvement efforts. Numerous studies have employed automated RGB imaging to characterize biomass and growth of agronomically important crops. The objective of this study was to investigate the utility of hyperspectral imaging for quantifying chemical properties of maize and soybean plants in vivo. These properties included leaf water content, as well as concentrations of macronutrients nitrogen (N, phosphorus (P, potassium (K, magnesium (Mg, calcium (Ca, and sulfur (S, and micronutrients sodium (Na, iron (Fe, manganese (Mn, boron (B, copper (Cu, and zinc (Zn. Hyperspectral images were collected from 60 maize and 60 soybean plants, each subjected to varying levels of either water deficit or nutrient limitation stress with the goal of creating a wide range of variation in the chemical properties of plant leaves. Plants were imaged on an automated conveyor belt system using a hyperspectral imager with a spectral range from 550 to 1,700 nm. Images were processed to extract reflectance spectrum from each plant and partial least squares regression models were developed to correlate spectral data with chemical data. Among all the chemical properties investigated, water content was predicted with the highest accuracy [R2 = 0.93 and RPD (Ratio of Performance to Deviation = 3.8]. All macronutrients were also quantified satisfactorily (R2 from 0.69 to 0.92, RPD from 1.62 to 3.62, with N predicted best followed by P, K, and S. The micronutrients group showed lower prediction accuracy (R2 from 0.19 to 0.86, RPD from 1.09 to 2.69 than the macronutrient groups. Cu and Zn were best predicted, followed by Fe and Mn. Na and B were the only two properties that hyperspectral imaging was not able to quantify satisfactorily (R2 < 0.3 and RPD < 1.2. This study suggested

  9. A High-Throughput Biological Calorimetry Core: Steps to Startup, Run, and Maintain a Multiuser Facility.

    Science.gov (United States)

    Yennawar, Neela H; Fecko, Julia A; Showalter, Scott A; Bevilacqua, Philip C

    2016-01-01

    Many labs have conventional calorimeters where denaturation and binding experiments are setup and run one at a time. While these systems are highly informative to biopolymer folding and ligand interaction, they require considerable manual intervention for cleaning and setup. As such, the throughput for such setups is limited typically to a few runs a day. With a large number of experimental parameters to explore including different buffers, macromolecule concentrations, temperatures, ligands, mutants, controls, replicates, and instrument tests, the need for high-throughput automated calorimeters is on the rise. Lower sample volume requirements and reduced user intervention time compared to the manual instruments have improved turnover of calorimetry experiments in a high-throughput format where 25 or more runs can be conducted per day. The cost and efforts to maintain high-throughput equipment typically demands that these instruments be housed in a multiuser core facility. We describe here the steps taken to successfully start and run an automated biological calorimetry facility at Pennsylvania State University. Scientists from various departments at Penn State including Chemistry, Biochemistry and Molecular Biology, Bioengineering, Biology, Food Science, and Chemical Engineering are benefiting from this core facility. Samples studied include proteins, nucleic acids, sugars, lipids, synthetic polymers, small molecules, natural products, and virus capsids. This facility has led to higher throughput of data, which has been leveraged into grant support, attracting new faculty hire and has led to some exciting publications. © 2016 Elsevier Inc. All rights reserved.

  10. Comparative RNA-Seq and microarray analysis of gene expression changes in B-cell lymphomas of Canis familiaris.

    Directory of Open Access Journals (Sweden)

    Marie Mooney

    Full Text Available Comparative oncology is a developing research discipline that is being used to assist our understanding of human neoplastic diseases. Companion canines are a preferred animal oncology model due to spontaneous tumor development and similarity to human disease at the pathophysiological level. We use a paired RNA sequencing (RNA-Seq/microarray analysis of a set of four normal canine lymph nodes and ten canine lymphoma fine needle aspirates to identify technical biases and variation between the technologies and convergence on biological disease pathways. Surrogate Variable Analysis (SVA provides a formal multivariate analysis of the combined RNA-Seq/microarray data set. Applying SVA to the data allows us to decompose variation into contributions associated with transcript abundance, differences between the technology, and latent variation within each technology. A substantial and highly statistically significant component of the variation reflects transcript abundance, and RNA-Seq appeared more sensitive for detection of transcripts expressed at low levels. Latent random variation among RNA-Seq samples is also distinct in character from that impacting microarray samples. In particular, we observed variation between RNA-Seq samples that reflects transcript GC content. Platform-independent variable decomposition without a priori knowledge of the sources of variation using SVA represents a generalizable method for accomplishing cross-platform data analysis. We identified genes differentially expressed between normal lymph nodes of disease free dogs and a subset of the diseased dogs diagnosed with B-cell lymphoma using each technology. There is statistically significant overlap between the RNA-Seq and microarray sets of differentially expressed genes. Analysis of overlapping genes in the context of biological systems suggests elevated expression and activity of PI3K signaling in B-cell lymphoma biopsies compared with normal biopsies, consistent with

  11. High-Throughput Analysis of T-DNA Location and Structure Using Sequence Capture.

    Science.gov (United States)

    Inagaki, Soichi; Henry, Isabelle M; Lieberman, Meric C; Comai, Luca

    2015-01-01

    Agrobacterium-mediated transformation of plants with T-DNA is used both to introduce transgenes and for mutagenesis. Conventional approaches used to identify the genomic location and the structure of the inserted T-DNA are laborious and high-throughput methods using next-generation sequencing are being developed to address these problems. Here, we present a cost-effective approach that uses sequence capture targeted to the T-DNA borders to select genomic DNA fragments containing T-DNA-genome junctions, followed by Illumina sequencing to determine the location and junction structure of T-DNA insertions. Multiple probes can be mixed so that transgenic lines transformed with different T-DNA types can be processed simultaneously, using a simple, index-based pooling approach. We also developed a simple bioinformatic tool to find sequence read pairs that span the junction between the genome and T-DNA or any foreign DNA. We analyzed 29 transgenic lines of Arabidopsis thaliana, each containing inserts from 4 different T-DNA vectors. We determined the location of T-DNA insertions in 22 lines, 4 of which carried multiple insertion sites. Additionally, our analysis uncovered a high frequency of unconventional and complex T-DNA insertions, highlighting the needs for high-throughput methods for T-DNA localization and structural characterization. Transgene insertion events have to be fully characterized prior to use as commercial products. Our method greatly facilitates the first step of this characterization of transgenic plants by providing an efficient screen for the selection of promising lines.

  12. Capturing the Alternative Cleavage and Polyadenylation Sites of 14 NAC Genes in Populus Using a Combination of 3′-RACE and High-Throughput Sequencing

    Directory of Open Access Journals (Sweden)

    Haoran Wang

    2018-03-01

    Full Text Available Detection of complex splice sites (SSs and polyadenylation sites (PASs of eukaryotic genes is essential for the elucidation of gene regulatory mechanisms. Transcriptome-wide studies using high-throughput sequencing (HTS have revealed prevalent alternative splicing (AS and alternative polyadenylation (APA in plants. However, small-scale and high-depth HTS aimed at detecting genes or gene families are very few and limited. We explored a convenient and flexible method for profiling SSs and PASs, which combines rapid amplification of 3′-cDNA ends (3′-RACE and HTS. Fourteen NAC (NAM, ATAF1/2, CUC2 transcription factor genes of Populus trichocarpa were analyzed by 3′-RACE-seq. Based on experimental reproducibility, boundary sequence analysis and reverse transcription PCR (RT-PCR verification, only canonical SSs were considered to be authentic. Based on stringent criteria, candidate PASs without any internal priming features were chosen as authentic PASs and assumed to be PAS-rich markers. Thirty-four novel canonical SSs, six intronic/internal exons and thirty 3′-UTR PAS-rich markers were revealed by 3′-RACE-seq. Using 3′-RACE and real-time PCR, we confirmed that three APA transcripts ending in/around PAS-rich markers were differentially regulated in response to plant hormones. Our results indicate that 3′-RACE-seq is a robust and cost-effective method to discover SSs and label active regions subjected to APA for genes or gene families. The method is suitable for small-scale AS and APA research in the initial stage.

  13. Temporal dynamics of soil microbial communities under different moisture regimes: high-throughput sequencing and bioinformatics analysis

    Science.gov (United States)

    Semenov, Mikhail; Zhuravleva, Anna; Semenov, Vyacheslav; Yevdokimov, Ilya; Larionova, Alla

    2017-04-01

    Recent climate scenarios predict not only continued global warming but also an increased frequency and intensity of extreme climatic events such as strong changes in temperature and precipitation regimes. Microorganisms are well known to be more sensitive to changes in environmental conditions than to other soil chemical and physical parameters. In this study, we determined the shifts in soil microbial community structure as well as indicative taxa in soils under three moisture regimes using high-throughput Illumina sequencing and range of bioinformatics approaches for the assessment of sequence data. Incubation experiments were performed in soil-filled (Greyic Phaeozems Albic) rhizoboxes with maize and without plants. Three contrasting moisture regimes were being simulated: 1) optimal wetting (OW), a watering 2-3 times per week to maintain soil moisture of 20-25% by weight; 2) periodic wetting (PW), with alternating periods of wetting and drought; and 3) constant insufficient wetting (IW), while soil moisture of 12% by weight was permanently maintained. Sampled fresh soils were homogenized, and the total DNA of three replicates was extracted using the FastDNA® SPIN kit for Soil. DNA replicates were combined in a pooled sample and the DNA was used for PCR with specific primers for the 16S V3 and V4 regions. In order to compare variability between different samples and replicates within a single sample, some DNA replicates treated separately. The products were purified and submitted to Illumina MiSeq sequencing. Sequence data were evaluated by alpha-diversity (Chao1 and Shannon H' diversity indexes), beta-diversity (UniFrac and Bray-Curtis dissimilarity), heatmap, tagcloud, and plot-bar analyses using the MiSeq Reporter Metagenomics Workflow and R packages (phyloseq, vegan, tagcloud). Shannon index varied in a rather narrow range (4.4-4.9) with the lowest values for microbial communities under PW treatment. Chao1 index varied from 385 to 480, being a more flexible

  14. RNA-Seq as an Emerging Tool for Marine Dinoflagellate Transcriptome Analysis: Process and Challenges

    Directory of Open Access Journals (Sweden)

    Muhamad Afiq Akbar

    2018-01-01

    Full Text Available Dinoflagellates are the large group of marine phytoplankton with primary studies interest regarding their symbiosis with coral reef and the abilities to form harmful algae blooms (HABs. Toxin produced by dinoflagellates during events of HABs cause severe negative impact both in the economy and health sector. However, attempts to understand the dinoflagellates genomic features are hindered by their complex genome organization. Transcriptomics have been employed to understand dinoflagellates genome structure, profile genes and gene expression. RNA-seq is one of the latest methods for transcriptomics study. This method is capable of profiling the dinoflagellates transcriptomes and has several advantages, including highly sensitive, cost effective and deeper sequence coverage. Thus, in this review paper, the current workflow of dinoflagellates RNA-seq starts with the extraction of high quality RNA and is followed by cDNA sequencing using the next-generation sequencing platform, dinoflagellates transcriptome assembly and computational analysis will be discussed. Certain consideration needs will be highlighted such as difficulty in dinoflagellates sequence annotation, post-transcriptional activity and the effect of RNA pooling when using RNA-seq.

  15. GUItars: a GUI tool for analysis of high-throughput RNA interference screening data.

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    Asli N Goktug

    Full Text Available High-throughput RNA interference (RNAi screening has become a widely used approach to elucidating gene functions. However, analysis and annotation of large data sets generated from these screens has been a challenge for researchers without a programming background. Over the years, numerous data analysis methods were produced for plate quality control and hit selection and implemented by a few open-access software packages. Recently, strictly standardized mean difference (SSMD has become a widely used method for RNAi screening analysis mainly due to its better control of false negative and false positive rates and its ability to quantify RNAi effects with a statistical basis. We have developed GUItars to enable researchers without a programming background to use SSMD as both a plate quality and a hit selection metric to analyze large data sets.The software is accompanied by an intuitive graphical user interface for easy and rapid analysis workflow. SSMD analysis methods have been provided to the users along with traditionally-used z-score, normalized percent activity, and t-test methods for hit selection. GUItars is capable of analyzing large-scale data sets from screens with or without replicates. The software is designed to automatically generate and save numerous graphical outputs known to be among the most informative high-throughput data visualization tools capturing plate-wise and screen-wise performances. Graphical outputs are also written in HTML format for easy access, and a comprehensive summary of screening results is written into tab-delimited output files.With GUItars, we demonstrated robust SSMD-based analysis workflow on a 3840-gene small interfering RNA (siRNA library and identified 200 siRNAs that increased and 150 siRNAs that decreased the assay activities with moderate to stronger effects. GUItars enables rapid analysis and illustration of data from large- or small-scale RNAi screens using SSMD and other traditional analysis

  16. Leveraging the Power of High Performance Computing for Next Generation Sequencing Data Analysis: Tricks and Twists from a High Throughput Exome Workflow

    Science.gov (United States)

    Wonczak, Stephan; Thiele, Holger; Nieroda, Lech; Jabbari, Kamel; Borowski, Stefan; Sinha, Vishal; Gunia, Wilfried; Lang, Ulrich; Achter, Viktor; Nürnberg, Peter

    2015-01-01

    Next generation sequencing (NGS) has been a great success and is now a standard method of research in the life sciences. With this technology, dozens of whole genomes or hundreds of exomes can be sequenced in rather short time, producing huge amounts of data. Complex bioinformatics analyses are required to turn these data into scientific findings. In order to run these analyses fast, automated workflows implemented on high performance computers are state of the art. While providing sufficient compute power and storage to meet the NGS data challenge, high performance computing (HPC) systems require special care when utilized for high throughput processing. This is especially true if the HPC system is shared by different users. Here, stability, robustness and maintainability are as important for automated workflows as speed and throughput. To achieve all of these aims, dedicated solutions have to be developed. In this paper, we present the tricks and twists that we utilized in the implementation of our exome data processing workflow. It may serve as a guideline for other high throughput data analysis projects using a similar infrastructure. The code implementing our solutions is provided in the supporting information files. PMID:25942438

  17. Evaluating whole transcriptome amplification for gene profiling experiments using RNA-Seq.

    Science.gov (United States)

    Faherty, Sheena L; Campbell, C Ryan; Larsen, Peter A; Yoder, Anne D

    2015-07-30

    RNA-Seq has enabled high-throughput gene expression profiling to provide insight into the functional link between genotype and phenotype. Low quantities of starting RNA can be a severe hindrance for studies that aim to utilize RNA-Seq. To mitigate this bottleneck, whole transcriptome amplification (WTA) technologies have been developed to generate sufficient sequencing targets from minute amounts of RNA. Successful WTA requires accurate replication of transcript abundance without the loss or distortion of specific mRNAs. Here, we test the efficacy of NuGEN's Ovation RNA-Seq V2 system, which uses linear isothermal amplification with a unique chimeric primer for amplification, using white adipose tissue from standard laboratory rats (Rattus norvegicus). Our goal was to investigate potential biological artifacts introduced through WTA approaches by establishing comparisons between matched raw and amplified RNA libraries derived from biological replicates. We found that 93% of expressed genes were identical between all unamplified versus matched amplified comparisons, also finding that gene density is similar across all comparisons. Our sequencing experiment and downstream bioinformatic analyses using the Tuxedo analysis pipeline resulted in the assembly of 25,543 high-quality transcripts. Libraries constructed from raw RNA and WTA samples averaged 15,298 and 15,253 expressed genes, respectively. Although significant differentially expressed genes (P < 0.05) were identified in all matched samples, each of these represents less than 0.15% of all shared genes for each comparison. Transcriptome amplification is efficient at maintaining relative transcript frequencies with no significant bias when using this NuGEN linear isothermal amplification kit under ideal laboratory conditions as presented in this study. This methodology has broad applications, from clinical and diagnostic, to field-based studies when sample acquisition, or sample preservation, methods prove

  18. High-throughput differentiation of heparin from other glycosaminoglycans by pyrolysis mass spectrometry.

    Science.gov (United States)

    Nemes, Peter; Hoover, William J; Keire, David A

    2013-08-06

    Sensors with high chemical specificity and enhanced sample throughput are vital to screening food products and medical devices for chemical or biochemical contaminants that may pose a threat to public health. For example, the rapid detection of oversulfated chondroitin sulfate (OSCS) in heparin could prevent reoccurrence of heparin adulteration that caused hundreds of severe adverse events including deaths worldwide in 2007-2008. Here, rapid pyrolysis is integrated with direct analysis in real time (DART) mass spectrometry to rapidly screen major glycosaminoglycans, including heparin, chondroitin sulfate A, dermatan sulfate, and OSCS. The results demonstrate that, compared to traditional liquid chromatography-based analyses, pyrolysis mass spectrometry achieved at least 250-fold higher sample throughput and was compatible with samples volume-limited to about 300 nL. Pyrolysis yielded an abundance of fragment ions (e.g., 150 different m/z species), many of which were specific to the parent compound. Using multivariate and statistical data analysis models, these data enabled facile differentiation of the glycosaminoglycans with high throughput. After method development was completed, authentically contaminated samples obtained during the heparin crisis by the FDA were analyzed in a blinded manner for OSCS contamination. The lower limit of differentiation and detection were 0.1% (w/w) OSCS in heparin and 100 ng/μL (20 ng) OSCS in water, respectively. For quantitative purposes the linear dynamic range spanned approximately 3 orders of magnitude. Moreover, this chemical readout was successfully employed to find clues in the manufacturing history of the heparin samples that can be used for surveillance purposes. The presented technology and data analysis protocols are anticipated to be readily adaptable to other chemical and biochemical agents and volume-limited samples.

  19. Preliminary High-Throughput Metagenome Assembly

    Energy Technology Data Exchange (ETDEWEB)

    Dusheyko, Serge; Furman, Craig; Pangilinan, Jasmyn; Shapiro, Harris; Tu, Hank

    2007-03-26

    Metagenome data sets present a qualitatively different assembly problem than traditional single-organism whole-genome shotgun (WGS) assembly. The unique aspects of such projects include the presence of a potentially large number of distinct organisms and their representation in the data set at widely different fractions. In addition, multiple closely related strains could be present, which would be difficult to assemble separately. Failure to take these issues into account can result in poor assemblies that either jumble together different strains or which fail to yield useful results. The DOE Joint Genome Institute has sequenced a number of metagenomic projects and plans to considerably increase this number in the coming year. As a result, the JGI has a need for high-throughput tools and techniques for handling metagenome projects. We present the techniques developed to handle metagenome assemblies in a high-throughput environment. This includes a streamlined assembly wrapper, based on the JGI?s in-house WGS assembler, Jazz. It also includes the selection of sensible defaults targeted for metagenome data sets, as well as quality control automation for cleaning up the raw results. While analysis is ongoing, we will discuss preliminary assessments of the quality of the assembly results (http://fames.jgi-psf.org).

  20. In-field High Throughput Phenotyping and Cotton Plant Growth Analysis Using LiDAR.

    Science.gov (United States)

    Sun, Shangpeng; Li, Changying; Paterson, Andrew H; Jiang, Yu; Xu, Rui; Robertson, Jon S; Snider, John L; Chee, Peng W

    2018-01-01

    Plant breeding programs and a wide range of plant science applications would greatly benefit from the development of in-field high throughput phenotyping technologies. In this study, a terrestrial LiDAR-based high throughput phenotyping system was developed. A 2D LiDAR was applied to scan plants from overhead in the field, and an RTK-GPS was used to provide spatial coordinates. Precise 3D models of scanned plants were reconstructed based on the LiDAR and RTK-GPS data. The ground plane of the 3D model was separated by RANSAC algorithm and a Euclidean clustering algorithm was applied to remove noise generated by weeds. After that, clean 3D surface models of cotton plants were obtained, from which three plot-level morphologic traits including canopy height, projected canopy area, and plant volume were derived. Canopy height ranging from 85th percentile to the maximum height were computed based on the histogram of the z coordinate for all measured points; projected canopy area was derived by projecting all points on a ground plane; and a Trapezoidal rule based algorithm was proposed to estimate plant volume. Results of validation experiments showed good agreement between LiDAR measurements and manual measurements for maximum canopy height, projected canopy area, and plant volume, with R 2 -values of 0.97, 0.97, and 0.98, respectively. The developed system was used to scan the whole field repeatedly over the period from 43 to 109 days after planting. Growth trends and growth rate curves for all three derived morphologic traits were established over the monitoring period for each cultivar. Overall, four different cultivars showed similar growth trends and growth rate patterns. Each cultivar continued to grow until ~88 days after planting, and from then on varied little. However, the actual values were cultivar specific. Correlation analysis between morphologic traits and final yield was conducted over the monitoring period. When considering each cultivar individually

  1. Cell surface profiling using high-throughput flow cytometry: a platform for biomarker discovery and analysis of cellular heterogeneity.

    Directory of Open Access Journals (Sweden)

    Craig A Gedye

    Full Text Available Cell surface proteins have a wide range of biological functions, and are often used as lineage-specific markers. Antibodies that recognize cell surface antigens are widely used as research tools, diagnostic markers, and even therapeutic agents. The ability to obtain broad cell surface protein profiles would thus be of great value in a wide range of fields. There are however currently few available methods for high-throughput analysis of large numbers of cell surface proteins. We describe here a high-throughput flow cytometry (HT-FC platform for rapid analysis of 363 cell surface antigens. Here we demonstrate that HT-FC provides reproducible results, and use the platform to identify cell surface antigens that are influenced by common cell preparation methods. We show that multiple populations within complex samples such as primary tumors can be simultaneously analyzed by co-staining of cells with lineage-specific antibodies, allowing unprecedented depth of analysis of heterogeneous cell populations. Furthermore, standard informatics methods can be used to visualize, cluster and downsample HT-FC data to reveal novel signatures and biomarkers. We show that the cell surface profile provides sufficient molecular information to classify samples from different cancers and tissue types into biologically relevant clusters using unsupervised hierarchical clustering. Finally, we describe the identification of a candidate lineage marker and its subsequent validation. In summary, HT-FC combines the advantages of a high-throughput screen with a detection method that is sensitive, quantitative, highly reproducible, and allows in-depth analysis of heterogeneous samples. The use of commercially available antibodies means that high quality reagents are immediately available for follow-up studies. HT-FC has a wide range of applications, including biomarker discovery, molecular classification of cancers, or identification of novel lineage specific or stem cell

  2. Cell surface profiling using high-throughput flow cytometry: a platform for biomarker discovery and analysis of cellular heterogeneity.

    Science.gov (United States)

    Gedye, Craig A; Hussain, Ali; Paterson, Joshua; Smrke, Alannah; Saini, Harleen; Sirskyj, Danylo; Pereira, Keira; Lobo, Nazleen; Stewart, Jocelyn; Go, Christopher; Ho, Jenny; Medrano, Mauricio; Hyatt, Elzbieta; Yuan, Julie; Lauriault, Stevan; Meyer, Mona; Kondratyev, Maria; van den Beucken, Twan; Jewett, Michael; Dirks, Peter; Guidos, Cynthia J; Danska, Jayne; Wang, Jean; Wouters, Bradly; Neel, Benjamin; Rottapel, Robert; Ailles, Laurie E

    2014-01-01

    Cell surface proteins have a wide range of biological functions, and are often used as lineage-specific markers. Antibodies that recognize cell surface antigens are widely used as research tools, diagnostic markers, and even therapeutic agents. The ability to obtain broad cell surface protein profiles would thus be of great value in a wide range of fields. There are however currently few available methods for high-throughput analysis of large numbers of cell surface proteins. We describe here a high-throughput flow cytometry (HT-FC) platform for rapid analysis of 363 cell surface antigens. Here we demonstrate that HT-FC provides reproducible results, and use the platform to identify cell surface antigens that are influenced by common cell preparation methods. We show that multiple populations within complex samples such as primary tumors can be simultaneously analyzed by co-staining of cells with lineage-specific antibodies, allowing unprecedented depth of analysis of heterogeneous cell populations. Furthermore, standard informatics methods can be used to visualize, cluster and downsample HT-FC data to reveal novel signatures and biomarkers. We show that the cell surface profile provides sufficient molecular information to classify samples from different cancers and tissue types into biologically relevant clusters using unsupervised hierarchical clustering. Finally, we describe the identification of a candidate lineage marker and its subsequent validation. In summary, HT-FC combines the advantages of a high-throughput screen with a detection method that is sensitive, quantitative, highly reproducible, and allows in-depth analysis of heterogeneous samples. The use of commercially available antibodies means that high quality reagents are immediately available for follow-up studies. HT-FC has a wide range of applications, including biomarker discovery, molecular classification of cancers, or identification of novel lineage specific or stem cell markers.

  3. iTAR: a web server for identifying target genes of transcription factors using ChIP-seq or ChIP-chip data.

    Science.gov (United States)

    Yang, Chia-Chun; Andrews, Erik H; Chen, Min-Hsuan; Wang, Wan-Yu; Chen, Jeremy J W; Gerstein, Mark; Liu, Chun-Chi; Cheng, Chao

    2016-08-12

    Chromatin immunoprecipitation followed by massively parallel DNA sequencing (ChIP-seq) or microarray hybridization (ChIP-chip) has been widely used to determine the genomic occupation of transcription factors (TFs). We have previously developed a probabilistic method, called TIP (Target Identification from Profiles), to identify TF target genes using ChIP-seq/ChIP-chip data. To achieve high specificity, TIP applies a conservative method to estimate significance of target genes, with the trade-off being a relatively low sensitivity of target gene identification compared to other methods. Additionally, TIP's output does not render binding-peak locations or intensity, information highly useful for visualization and general experimental biological use, while the variability of ChIP-seq/ChIP-chip file formats has made input into TIP more difficult than desired. To improve upon these facets, here we present are fined TIP with key extensions. First, it implements a Gaussian mixture model for p-value estimation, increasing target gene identification sensitivity and more accurately capturing the shape of TF binding profile distributions. Second, it enables the incorporation of TF binding-peak data by identifying their locations in significant target gene promoter regions and quantifies their strengths. Finally, for full ease of implementation we have incorporated it into a web server ( http://syslab3.nchu.edu.tw/iTAR/ ) that enables flexibility of input file format, can be used across multiple species and genome assembly versions, and is freely available for public use. The web server additionally performs GO enrichment analysis for the identified target genes to reveal the potential function of the corresponding TF. The iTAR web server provides a user-friendly interface and supports target gene identification in seven species, ranging from yeast to human. To facilitate investigating the quality of ChIP-seq/ChIP-chip data, the web server generates the chart of the

  4. High-throughput identification of potential minor histocompatibility antigens by MHC tetramer-based screening

    DEFF Research Database (Denmark)

    Hombrink, Pleun; Hadrup, Sine R; Bakker, Arne

    2011-01-01

    the technical feasibility of high-throughput analysis of antigen-specific T-cell responses in small patient samples. However, the high-sensitivity of this approach requires the use of potential epitope sets that are not solely based on MHC binding, to prevent the frequent detection of T-cell responses that lack......T-cell recognition of minor histocompatibility antigens (MiHA) plays an important role in the graft-versus-tumor (GVT) effect of allogeneic stem cell transplantation (allo-SCT). However, the number of MiHA identified to date remains limited, making clinical application of MiHA reactive T......MHC-tetramer-based enrichment and multi-color flow cytometry. Using this approach, 71 peptide-reactive T-cell populations were generated. The isolation of a T-cell line specifically recognizing target cells expressing the MAP4K1(IMA) antigen demonstrates that identification of MiHA through this approach is in principle...

  5. Transcriptional regulation of rod photoreceptor homeostasis revealed by in vivo NRL targetome analysis.

    Directory of Open Access Journals (Sweden)

    Hong Hao

    Full Text Available A stringent control of homeostasis is critical for functional maintenance and survival of neurons. In the mammalian retina, the basic motif leucine zipper transcription factor NRL determines rod versus cone photoreceptor cell fate and activates the expression of many rod-specific genes. Here, we report an integrated analysis of NRL-centered gene regulatory network by coupling chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-Seq data from Illumina and ABI platforms with global expression profiling and in vivo knockdown studies. We identified approximately 300 direct NRL target genes. Of these, 22 NRL targets are associated with human retinal dystrophies, whereas 95 mapped to regions of as yet uncloned retinal disease loci. In silico analysis of NRL ChIP-Seq peak sequences revealed an enrichment of distinct sets of transcription factor binding sites. Specifically, we discovered that genes involved in photoreceptor function include binding sites for both NRL and homeodomain protein CRX. Evaluation of 26 ChIP-Seq regions validated their enhancer functions in reporter assays. In vivo knockdown of 16 NRL target genes resulted in death or abnormal morphology of rod photoreceptors, suggesting their importance in maintaining retinal function. We also identified histone demethylase Kdm5b as a novel secondary node in NRL transcriptional hierarchy. Exon array analysis of flow-sorted photoreceptors in which Kdm5b was knocked down by shRNA indicated its role in regulating rod-expressed genes. Our studies identify candidate genes for retinal dystrophies, define cis-regulatory module(s for photoreceptor-expressed genes and provide a framework for decoding transcriptional regulatory networks that dictate rod homeostasis.

  6. Identification of innate lymphoid cells in single-cell RNA-Seq data.

    Science.gov (United States)

    Suffiotti, Madeleine; Carmona, Santiago J; Jandus, Camilla; Gfeller, David

    2017-07-01

    Innate lymphoid cells (ILCs) consist of natural killer (NK) cells and non-cytotoxic ILCs that are broadly classified into ILC1, ILC2, and ILC3 subtypes. These cells recently emerged as important early effectors of innate immunity for their roles in tissue homeostasis and inflammation. Over the last few years, ILCs have been extensively studied in mouse and human at the functional and molecular level, including gene expression profiling. However, sorting ILCs with flow cytometry for gene expression analysis is a delicate and time-consuming process. Here we propose and validate a novel framework for studying ILCs at the transcriptomic level using single-cell RNA-Seq data. Our approach combines unsupervised clustering and a new cell type classifier trained on mouse ILC gene expression data. We show that this approach can accurately identify different ILCs, especially ILC2 cells, in human lymphocyte single-cell RNA-Seq data. Our new model relies only on genes conserved across vertebrates, thereby making it in principle applicable in any vertebrate species. Considering the rapid increase in throughput of single-cell RNA-Seq technology, our work provides a computational framework for studying ILC2 cells in single-cell transcriptomic data and may help exploring their conservation in distant vertebrate species.

  7. Integrative Analysis of High-throughput Cancer Studies with Contrasted Penalization

    Science.gov (United States)

    Shi, Xingjie; Liu, Jin; Huang, Jian; Zhou, Yong; Shia, BenChang; Ma, Shuangge

    2015-01-01

    In cancer studies with high-throughput genetic and genomic measurements, integrative analysis provides a way to effectively pool and analyze heterogeneous raw data from multiple independent studies and outperforms “classic” meta-analysis and single-dataset analysis. When marker selection is of interest, the genetic basis of multiple datasets can be described using the homogeneity model or the heterogeneity model. In this study, we consider marker selection under the heterogeneity model, which includes the homogeneity model as a special case and can be more flexible. Penalization methods have been developed in the literature for marker selection. This study advances from the published ones by introducing the contrast penalties, which can accommodate the within- and across-dataset structures of covariates/regression coefficients and, by doing so, further improve marker selection performance. Specifically, we develop a penalization method that accommodates the across-dataset structures by smoothing over regression coefficients. An effective iterative algorithm, which calls an inner coordinate descent iteration, is developed. Simulation shows that the proposed method outperforms the benchmark with more accurate marker identification. The analysis of breast cancer and lung cancer prognosis studies with gene expression measurements shows that the proposed method identifies genes different from those using the benchmark and has better prediction performance. PMID:24395534

  8. A high-throughput, multi-channel photon-counting detector with picosecond timing

    CERN Document Server

    Lapington, J S; Miller, G M; Ashton, T J R; Jarron, P; Despeisse, M; Powolny, F; Howorth, J; Milnes, J

    2009-01-01

    High-throughput photon counting with high time resolution is a niche application area where vacuum tubes can still outperform solid-state devices. Applications in the life sciences utilizing time-resolved spectroscopies, particularly in the growing field of proteomics, will benefit greatly from performance enhancements in event timing and detector throughput. The HiContent project is a collaboration between the University of Leicester Space Research Centre, the Microelectronics Group at CERN, Photek Ltd., and end-users at the Gray Cancer Institute and the University of Manchester. The goal is to develop a detector system specifically designed for optical proteomics, capable of high content (multi-parametric) analysis at high throughput. The HiContent detector system is being developed to exploit this niche market. It combines multi-channel, high time resolution photon counting in a single miniaturized detector system with integrated electronics. The combination of enabling technologies; small pore microchanne...

  9. RAP: RNA-Seq Analysis Pipeline, a new cloud-based NGS web application.

    Science.gov (United States)

    D'Antonio, Mattia; D'Onorio De Meo, Paolo; Pallocca, Matteo; Picardi, Ernesto; D'Erchia, Anna Maria; Calogero, Raffaele A; Castrignanò, Tiziana; Pesole, Graziano

    2015-01-01

    The study of RNA has been dramatically improved by the introduction of Next Generation Sequencing platforms allowing massive and cheap sequencing of selected RNA fractions, also providing information on strand orientation (RNA-Seq). The complexity of transcriptomes and of their regulative pathways make RNA-Seq one of most complex field of NGS applications, addressing several aspects of the expression process (e.g. identification and quantification of expressed genes and transcripts, alternative splicing and polyadenylation, fusion genes and trans-splicing, post-transcriptional events, etc.). In order to provide researchers with an effective and friendly resource for analyzing RNA-Seq data, we present here RAP (RNA-Seq Analysis Pipeline), a cloud computing web application implementing a complete but modular analysis workflow. This pipeline integrates both state-of-the-art bioinformatics tools for RNA-Seq analysis and in-house developed scripts to offer to the user a comprehensive strategy for data analysis. RAP is able to perform quality checks (adopting FastQC and NGS QC Toolkit), identify and quantify expressed genes and transcripts (with Tophat, Cufflinks and HTSeq), detect alternative splicing events (using SpliceTrap) and chimeric transcripts (with ChimeraScan). This pipeline is also able to identify splicing junctions and constitutive or alternative polyadenylation sites (implementing custom analysis modules) and call for statistically significant differences in genes and transcripts expression, splicing pattern and polyadenylation site usage (using Cuffdiff2 and DESeq). Through a user friendly web interface, the RAP workflow can be suitably customized by the user and it is automatically executed on our cloud computing environment. This strategy allows to access to bioinformatics tools and computational resources without specific bioinformatics and IT skills. RAP provides a set of tabular and graphical results that can be helpful to browse, filter and export

  10. High-throughput transformation of Saccharomyces cerevisiae using liquid handling robots.

    Directory of Open Access Journals (Sweden)

    Guangbo Liu

    Full Text Available Saccharomyces cerevisiae (budding yeast is a powerful eukaryotic model organism ideally suited to high-throughput genetic analyses, which time and again has yielded insights that further our understanding of cell biology processes conserved in humans. Lithium Acetate (LiAc transformation of yeast with DNA for the purposes of exogenous protein expression (e.g., plasmids or genome mutation (e.g., gene mutation, deletion, epitope tagging is a useful and long established method. However, a reliable and optimized high throughput transformation protocol that runs almost no risk of human error has not been described in the literature. Here, we describe such a method that is broadly transferable to most liquid handling high-throughput robotic platforms, which are now commonplace in academic and industry settings. Using our optimized method, we are able to comfortably transform approximately 1200 individual strains per day, allowing complete transformation of typical genomic yeast libraries within 6 days. In addition, use of our protocol for gene knockout purposes also provides a potentially quicker, easier and more cost-effective approach to generating collections of double mutants than the popular and elegant synthetic genetic array methodology. In summary, our methodology will be of significant use to anyone interested in high throughput molecular and/or genetic analysis of yeast.

  11. A non-parametric peak calling algorithm for DamID-Seq.

    Directory of Open Access Journals (Sweden)

    Renhua Li

    Full Text Available Protein-DNA interactions play a significant role in gene regulation and expression. In order to identify transcription factor binding sites (TFBS of double sex (DSX-an important transcription factor in sex determination, we applied the DNA adenine methylation identification (DamID technology to the fat body tissue of Drosophila, followed by deep sequencing (DamID-Seq. One feature of DamID-Seq data is that induced adenine methylation signals are not assured to be symmetrically distributed at TFBS, which renders the existing peak calling algorithms for ChIP-Seq, including SPP and MACS, inappropriate for DamID-Seq data. This challenged us to develop a new algorithm for peak calling. A challenge in peaking calling based on sequence data is estimating the averaged behavior of background signals. We applied a bootstrap resampling method to short sequence reads in the control (Dam only. After data quality check and mapping reads to a reference genome, the peaking calling procedure compromises the following steps: 1 reads resampling; 2 reads scaling (normalization and computing signal-to-noise fold changes; 3 filtering; 4 Calling peaks based on a statistically significant threshold. This is a non-parametric method for peak calling (NPPC. We also used irreproducible discovery rate (IDR analysis, as well as ChIP-Seq data to compare the peaks called by the NPPC. We identified approximately 6,000 peaks for DSX, which point to 1,225 genes related to the fat body tissue difference between female and male Drosophila. Statistical evidence from IDR analysis indicated that these peaks are reproducible across biological replicates. In addition, these peaks are comparable to those identified by use of ChIP-Seq on S2 cells, in terms of peak number, location, and peaks width.

  12. A non-parametric peak calling algorithm for DamID-Seq.

    Science.gov (United States)

    Li, Renhua; Hempel, Leonie U; Jiang, Tingbo

    2015-01-01

    Protein-DNA interactions play a significant role in gene regulation and expression. In order to identify transcription factor binding sites (TFBS) of double sex (DSX)-an important transcription factor in sex determination, we applied the DNA adenine methylation identification (DamID) technology to the fat body tissue of Drosophila, followed by deep sequencing (DamID-Seq). One feature of DamID-Seq data is that induced adenine methylation signals are not assured to be symmetrically distributed at TFBS, which renders the existing peak calling algorithms for ChIP-Seq, including SPP and MACS, inappropriate for DamID-Seq data. This challenged us to develop a new algorithm for peak calling. A challenge in peaking calling based on sequence data is estimating the averaged behavior of background signals. We applied a bootstrap resampling method to short sequence reads in the control (Dam only). After data quality check and mapping reads to a reference genome, the peaking calling procedure compromises the following steps: 1) reads resampling; 2) reads scaling (normalization) and computing signal-to-noise fold changes; 3) filtering; 4) Calling peaks based on a statistically significant threshold. This is a non-parametric method for peak calling (NPPC). We also used irreproducible discovery rate (IDR) analysis, as well as ChIP-Seq data to compare the peaks called by the NPPC. We identified approximately 6,000 peaks for DSX, which point to 1,225 genes related to the fat body tissue difference between female and male Drosophila. Statistical evidence from IDR analysis indicated that these peaks are reproducible across biological replicates. In addition, these peaks are comparable to those identified by use of ChIP-Seq on S2 cells, in terms of peak number, location, and peaks width.

  13. HPeak: an HMM-based algorithm for defining read-enriched regions in ChIP-Seq data

    Directory of Open Access Journals (Sweden)

    Maher Christopher A

    2010-07-01

    Full Text Available Abstract Background Protein-DNA interaction constitutes a basic mechanism for the genetic regulation of target gene expression. Deciphering this mechanism has been a daunting task due to the difficulty in characterizing protein-bound DNA on a large scale. A powerful technique has recently emerged that couples chromatin immunoprecipitation (ChIP with next-generation sequencing, (ChIP-Seq. This technique provides a direct survey of the cistrom of transcription factors and other chromatin-associated proteins. In order to realize the full potential of this technique, increasingly sophisticated statistical algorithms have been developed to analyze the massive amount of data generated by this method. Results Here we introduce HPeak, a Hidden Markov model (HMM-based Peak-finding algorithm for analyzing ChIP-Seq data to identify protein-interacting genomic regions. In contrast to the majority of available ChIP-Seq analysis software packages, HPeak is a model-based approach allowing for rigorous statistical inference. This approach enables HPeak to accurately infer genomic regions enriched with sequence reads by assuming realistic probability distributions, in conjunction with a novel weighting scheme on the sequencing read coverage. Conclusions Using biologically relevant data collections, we found that HPeak showed a higher prevalence of the expected transcription factor binding motifs in ChIP-enriched sequences relative to the control sequences when compared to other currently available ChIP-Seq analysis approaches. Additionally, in comparison to the ChIP-chip assay, ChIP-Seq provides higher resolution along with improved sensitivity and specificity of binding site detection. Additional file and the HPeak program are freely available at http://www.sph.umich.edu/csg/qin/HPeak.

  14. High-throughput sequencing of microbial community diversity in soil, grapes, leaves, grape juice and wine of grapevine from China.

    Science.gov (United States)

    Wei, Yu-Jie; Wu, Yun; Yan, Yin-Zhuo; Zou, Wan; Xue, Jie; Ma, Wen-Rui; Wang, Wei; Tian, Ge; Wang, Li-Ye

    2018-01-01

    In this study Illumina MiSeq was performed to investigate microbial diversity in soil, leaves, grape, grape juice and wine. A total of 1,043,102 fungal Internal Transcribed Spacer (ITS) reads and 2,422,188 high quality bacterial 16S rDNA sequences were used for taxonomic classification, revealed five fungal and eight bacterial phyla. At the genus level, the dominant fungi were Ascomycota, Sordariales, Tetracladium and Geomyces in soil, Aureobasidium and Pleosporaceae in grapes leaves, Aureobasidium in grape and grape juice. The dominant bacteria were Kaistobacter, Arthrobacter, Skermanella and Sphingomonas in soil, Pseudomonas, Acinetobacter and Kaistobacter in grape and grapes leaves, and Oenococcus in grape juice and wine. Principal coordinate analysis showed structural separation between the composition of fungi and bacteria in all samples. This is the first study to understand microbiome population in soil, grape, grapes leaves, grape juice and wine in Xinjiang through High-throughput Sequencing and identify microorganisms like Saccharomyces cerevisiae and Oenococcus spp. that may contribute to the quality and flavor of wine.

  15. High-throughput sequencing of microbial community diversity in soil, grapes, leaves, grape juice and wine of grapevine from China

    Science.gov (United States)

    Yan, Yin-zhuo; Zou, Wan; Ma, Wen-rui; Wang, Wei; Tian, Ge; Wang, Li-ye

    2018-01-01

    In this study Illumina MiSeq was performed to investigate microbial diversity in soil, leaves, grape, grape juice and wine. A total of 1,043,102 fungal Internal Transcribed Spacer (ITS) reads and 2,422,188 high quality bacterial 16S rDNA sequences were used for taxonomic classification, revealed five fungal and eight bacterial phyla. At the genus level, the dominant fungi were Ascomycota, Sordariales, Tetracladium and Geomyces in soil, Aureobasidium and Pleosporaceae in grapes leaves, Aureobasidium in grape and grape juice. The dominant bacteria were Kaistobacter, Arthrobacter, Skermanella and Sphingomonas in soil, Pseudomonas, Acinetobacter and Kaistobacter in grape and grapes leaves, and Oenococcus in grape juice and wine. Principal coordinate analysis showed structural separation between the composition of fungi and bacteria in all samples. This is the first study to understand microbiome population in soil, grape, grapes leaves, grape juice and wine in Xinjiang through High-throughput Sequencing and identify microorganisms like Saccharomyces cerevisiae and Oenococcus spp. that may contribute to the quality and flavor of wine. PMID:29565999

  16. Characterization of a high affinity cocaine binding site in rat brain

    International Nuclear Information System (INIS)

    Calligaro, D.; Eldefrawi, M.

    1986-01-01

    Binding of [ 3 H]cocaine to synaptic membranes from whole rat brain was reversible and saturable. Nonlinear regression analysis of binding isotherms indicated two binding affinities: one with k/sub d/ = 16 nM, B/sub max/ = 0.65 pmoles/mg protein and the other with K/sub d/ = 660 nM, B/sub max/ = 5.1 pmoles/mg protein. The high-affinity binding of [ 3 H]cocaine was sensitive to the actions of trypsin and chymotrypsin but not carboxypeptidase, and was eliminated by exposure of the membranes to 95 0 C for 5 min. Specific binding at 2 nM was higher at pH 8.8 than at pH 7.0. Binding of [ 3 H]cocaine (15 nM) was inhibited by increasing concentrations of Na + ions. Several cocaine analogues, neurotransmitter uptake inhibitors and local anesthetics displaced specific [ 3 H]cocaine binding at 2 nM with various potencies. The cocaine analogue (-)-norcocaine was the most potent (IC 50 = 10 nM), while the local anesthetic tetracaine was the least potent in inhibiting [ 3 H]cocaine binding. Several biogenic amine uptake inhibitors, including tricyclic antidepressants and phencyclidine, had IC 50 values below μM concentrations

  17. Identification of Rift Valley Fever Virus Nucleocapsid Protein-RNA Binding Inhibitors Using a High-Throughput Screening Assay

    OpenAIRE

    Ellenbecker, Mary; Lanchy, Jean-Marc; Lodmell, J. Stephen

    2012-01-01

    Rift Valley fever virus (RVFV) is an emerging infectious pathogen that causes severe disease in humans and livestock and has the potential for global spread. Currently, there is no proven effective treatment for RVFV infection and there is no licensed vaccine. Inhibition of RNA binding to the essential viral nucleocapsid (N) protein represents a potential anti-viral therapeutic strategy because all of the functions performed by N during infection involve RNA binding. To target this interactio...

  18. Effectiveness of a high-throughput genetic analysis in the identification of responders/non-responders to CYP2D6-metabolized drugs.

    Science.gov (United States)

    Savino, Maria; Seripa, Davide; Gallo, Antonietta P; Garrubba, Maria; D'Onofrio, Grazia; Bizzarro, Alessandra; Paroni, Giulia; Paris, Francesco; Mecocci, Patrizia; Masullo, Carlo; Pilotto, Alberto; Santini, Stefano A

    2011-01-01

    Recent studies investigating the single cytochrome P450 (CYP) 2D6 allele *2A reported an association with the response to drug treatments. More genetic data can be obtained, however, by high-throughput based-technologies. Aim of this study is the high-throughput analysis of the CYP2D6 polymorphisms to evaluate its effectiveness in the identification of patient responders/non-responders to CYP2D6-metabolized drugs. An attempt to compare our results with those previously obtained with the standard analysis of CYP2D6 allele *2A was also made. Sixty blood samples from patients treated with CYP2D6-metabolized drugs previously genotyped for the allele CYP2D6*2A, were analyzed for the CYP2D6 polymorphisms with the AutoGenomics INFINITI CYP4502D6-I assay on the AutoGenomics INFINITI analyzer. A higher frequency of mutated alleles in responder than in non-responder patients (75.38 % vs 43.48 %; p = 0.015) was observed. Thus, the presence of a mutated allele of CYP2D6 was associated with a response to CYP2D6-metabolized drugs (OR = 4.044 (1.348 - 12.154). No difference was observed in the distribution of allele *2A (p = 0.320). The high-throughput genetic analysis of the CYP2D6 polymorphisms better discriminate responders/non-responders with respect to the standard analysis of the CYP2D6 allele *2A. A high-throughput genetic assay of the CYP2D6 may be useful to identify patients with different clinical responses to CYP2D6-metabolized drugs.

  19. Ultra-high-throughput screening of an in vitro-synthesized horseradish peroxidase displayed on microbeads using cell sorter.

    Directory of Open Access Journals (Sweden)

    Bo Zhu

    Full Text Available The C1a isoenzyme of horseradish peroxidase (HRP is an industrially important heme-containing enzyme that utilizes hydrogen peroxide to oxidize a wide variety of inorganic and organic compounds for practical applications, including synthesis of fine chemicals, medical diagnostics, and bioremediation. To develop a ultra-high-throughput screening system for HRP, we successfully produced active HRP in an Escherichia coli cell-free protein synthesis system, by adding disulfide bond isomerase DsbC and optimizing the concentrations of hemin and calcium ions and the temperature. The biosynthesized HRP was fused with a single-chain Cro (scCro DNA-binding tag at its N-terminal and C-terminal sites. The addition of the scCro-tag at both ends increased the solubility of the protein. Next, HRP and its fusion proteins were successfully synthesized in a water droplet emulsion by using hexadecane as the oil phase and SunSoft No. 818SK as the surfactant. HRP fusion proteins were displayed on microbeads attached with double-stranded DNA (containing the scCro binding sequence via scCro-DNA interactions. The activities of the immobilized HRP fusion proteins were detected with a tyramide-based fluorogenic assay using flow cytometry. Moreover, a model microbead library containing wild type hrp (WT and inactive mutant (MUT genes was screened using fluorescence-activated cell-sorting, thus efficiently enriching the WT gene from the 1:100 (WT:MUT library. The technique described here could serve as a novel platform for the ultra-high-throughput discovery of more useful HRP mutants and other heme-containing peroxidases.

  20. High-Throughput Analysis of T-DNA Location and Structure Using Sequence Capture.

    Directory of Open Access Journals (Sweden)

    Soichi Inagaki

    Full Text Available Agrobacterium-mediated transformation of plants with T-DNA is used both to introduce transgenes and for mutagenesis. Conventional approaches used to identify the genomic location and the structure of the inserted T-DNA are laborious and high-throughput methods using next-generation sequencing are being developed to address these problems. Here, we present a cost-effective approach that uses sequence capture targeted to the T-DNA borders to select genomic DNA fragments containing T-DNA-genome junctions, followed by Illumina sequencing to determine the location and junction structure of T-DNA insertions. Multiple probes can be mixed so that transgenic lines transformed with different T-DNA types can be processed simultaneously, using a simple, index-based pooling approach. We also developed a simple bioinformatic tool to find sequence read pairs that span the junction between the genome and T-DNA or any foreign DNA. We analyzed 29 transgenic lines of Arabidopsis thaliana, each containing inserts from 4 different T-DNA vectors. We determined the location of T-DNA insertions in 22 lines, 4 of which carried multiple insertion sites. Additionally, our analysis uncovered a high frequency of unconventional and complex T-DNA insertions, highlighting the needs for high-throughput methods for T-DNA localization and structural characterization. Transgene insertion events have to be fully characterized prior to use as commercial products. Our method greatly facilitates the first step of this characterization of transgenic plants by providing an efficient screen for the selection of promising lines.

  1. Real-time, high-throughput measurements of peptide-MHC-I dissociation using a scintillation proximity assay

    DEFF Research Database (Denmark)

    Harndahl, Mikkel; Rasmussen, Michael; Røder, Gustav Andreas

    2011-01-01

    and it is well suited for high-throughput screening. To exemplify this, we screened a panel of 384 high-affinity peptides binding to the MHC class I molecule, HLA-A*02:01, and observed the rates of dissociation that ranged from 0.1h to 46h depending on the peptide used.......Efficient presentation of peptide-MHC class I complexes to immune T cells depends upon stable peptide-MHC class I interactions. Theoretically, determining the rate of dissociation of a peptide-MHC class I complexes is straightforward; in practical terms, however, generating the accurate and closely...... timed data needed to determine the rate of dissociation is not simple. Ideally, one should use a homogenous assay involving an inexhaustible and label-free assay principle. Here, we present a homogenous, high-throughput peptide-MHC class I dissociation assay, which by and large fulfill these ideal...

  2. High Throughput Transcriptomics @ USEPA (Toxicology ...

    Science.gov (United States)

    The ideal chemical testing approach will provide complete coverage of all relevant toxicological responses. It should be sensitive and specific It should identify the mechanism/mode-of-action (with dose-dependence). It should identify responses relevant to the species of interest. Responses should ideally be translated into tissue-, organ-, and organism-level effects. It must be economical and scalable. Using a High Throughput Transcriptomics platform within US EPA provides broader coverage of biological activity space and toxicological MOAs and helps fill the toxicological data gap. Slide presentation at the 2016 ToxForum on using High Throughput Transcriptomics at US EPA for broader coverage biological activity space and toxicological MOAs.

  3. High throughput screening of phenoxy carboxylic acids with dispersive solid phase extraction followed by direct analysis in real time mass spectrometry.

    Science.gov (United States)

    Wang, Jiaqin; Zhu, Jun; Si, Ling; Du, Qi; Li, Hongli; Bi, Wentao; Chen, David Da Yong

    2017-12-15

    A high throughput, low environmental impact methodology for rapid determination of phenoxy carboxylic acids (PCAs) in water samples was developed by combing dispersive solid phase extraction (DSPE) using velvet-like graphitic carbon nitride (V-g-C 3 N 4 ) and direct analysis in real time mass spectrometry (DART-MS). Due to the large surface area and good dispersity of V-g-C 3 N 4 , the DSPE of PCAs in water was completed within 20 s, and the elution of PCAs was accomplished in 20 s as well using methanol. The eluents were then analyzed and quantified using DART ionization source coupled to a high resolution mass spectrometer, where an internal standard was added in the samples. The limit of detection ranged from 0.5 ng L -1 to 2 ng L -1 on the basis of 50 mL water sample; the recovery 79.9-119.1%; and the relative standard deviation 0.23%-9.82% (≥5 replicates). With the ease of use and speed of DART-MS, the whole protocol can complete within mere minutes, including sample preparation, extraction, elution, detection and quantitation. The methodology developed here is simple, fast, sensitive, quantitative, requiring little sample preparation and consuming significantly less toxic organic solvent, which can be used for high throughput screening of PCAs and potentially other contaminants in water. Copyright © 2017 Elsevier B.V. All rights reserved.

  4. Application of ToxCast High-Throughput Screening and ...

    Science.gov (United States)

    Slide presentation at the SETAC annual meeting on High-Throughput Screening and Modeling Approaches to Identify Steroidogenesis Distruptors Slide presentation at the SETAC annual meeting on High-Throughput Screening and Modeling Approaches to Identify Steroidogenssis Distruptors

  5. A Transcriptome Map of Actinobacillus pleuropneumoniae at Single-Nucleotide Resolution Using Deep RNA-Seq.

    Directory of Open Access Journals (Sweden)

    Zhipeng Su

    Full Text Available Actinobacillus pleuropneumoniae is the pathogen of porcine contagious pleuropneumoniae, a highly contagious respiratory disease of swine. Although the genome of A. pleuropneumoniae was sequenced several years ago, limited information is available on the genome-wide transcriptional analysis to accurately annotate the gene structures and regulatory elements. High-throughput RNA sequencing (RNA-seq has been applied to study the transcriptional landscape of bacteria, which can efficiently and accurately identify gene expression regions and unknown transcriptional units, especially small non-coding RNAs (sRNAs, UTRs and regulatory regions. The aim of this study is to comprehensively analyze the transcriptome of A. pleuropneumoniae by RNA-seq in order to improve the existing genome annotation and promote our understanding of A. pleuropneumoniae gene structures and RNA-based regulation. In this study, we utilized RNA-seq to construct a single nucleotide resolution transcriptome map of A. pleuropneumoniae. More than 3.8 million high-quality reads (average length ~90 bp from a cDNA library were generated and aligned to the reference genome. We identified 32 open reading frames encoding novel proteins that were mis-annotated in the previous genome annotations. The start sites for 35 genes based on the current genome annotation were corrected. Furthermore, 51 sRNAs in the A. pleuropneumoniae genome were discovered, of which 40 sRNAs were never reported in previous studies. The transcriptome map also enabled visualization of 5'- and 3'-UTR regions, in which contained 11 sRNAs. In addition, 351 operons covering 1230 genes throughout the whole genome were identified. The RNA-Seq based transcriptome map validated annotated genes and corrected annotations of open reading frames in the genome, and led to the identification of many functional elements (e.g. regions encoding novel proteins, non-coding sRNAs and operon structures. The transcriptional units

  6. elegantRingAnalysis An Interface for High-Throughput Analysis of Storage Ring Lattices Using elegant

    CERN Document Server

    Borland, Michael

    2005-01-01

    The code {\\tt elegant} is widely used for simulation of linacs for drivers for free-electron lasers. Less well known is that elegant is also a very capable code for simulation of storage rings. In this paper, we show a newly-developed graphical user interface that allows the user to easily take advantage of these capabilities. The interface is designed for use on a Linux cluster, providing very high throughput. It can also be used on a single computer. Among the features it gives access to are basic calculations (Twiss parameters, radiation integrals), phase-space tracking, nonlinear dispersion, dynamic aperture (on- and off-momentum), frequency map analysis, and collective effects (IBS, bunch-lengthening). Using a cluster, it is easy to get highly detailed dynamic aperture and frequency map results in a surprisingly short time.

  7. High-throughput peptide mass fingerprinting and protein macroarray analysis using chemical printing strategies

    International Nuclear Information System (INIS)

    Sloane, A.J.; Duff, J.L.; Hopwood, F.G.; Wilson, N.L.; Smith, P.E.; Hill, C.J.; Packer, N.H.; Williams, K.L.; Gooley, A.A.; Cole, R.A.; Cooley, P.W.; Wallace, D.B.

    2001-01-01

    We describe a 'chemical printer' that uses piezoelectric pulsing for rapid and accurate microdispensing of picolitre volumes of fluid for proteomic analysis of 'protein macroarrays'. Unlike positive transfer and pin transfer systems, our printer dispenses fluid in a non-contact process that ensures that the fluid source cannot be contaminated by substrate during a printing event. We demonstrate automated delivery of enzyme and matrix solutions for on-membrane protein digestion and subsequent peptide mass fingerprinting (pmf) analysis directly from the membrane surface using matrix-assisted laser-desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS). This approach bypasses the more commonly used multi-step procedures, thereby permitting a more rapid procedure for protein identification. We also highlight the advantage of printing different chemistries onto an individual protein spot for multiple microscale analyses. This ability is particularly useful when detailed characterisation of rare and valuable sample is required. Using a combination of PNGase F and trypsin we have mapped sites of N-glycosylation using on-membrane digestion strategies. We also demonstrate the ability to print multiple serum samples in a micro-ELISA format and rapidly screen a protein macroarray of human blood plasma for pathogen-derived antigens. We anticipate that the 'chemical printer' will be a major component of proteomic platforms for high-throughput protein identification and characterisation with widespread applications in biomedical and diagnostic discovery

  8. High-throughput shotgun lipidomics by quadrupole time-of-flight mass spectrometry

    DEFF Research Database (Denmark)

    Ståhlman, Marcus; Ejsing, Christer S.; Tarasov, Kirill

    2009-01-01

    Technological advances in mass spectrometry and meticulous method development have produced several shotgun lipidomic approaches capable of characterizing lipid species by direct analysis of total lipid extracts. Shotgun lipidomics by hybrid quadrupole time-of-flight mass spectrometry allows...... the absolute quantification of hundreds of molecular glycerophospholipid species, glycerolipid species, sphingolipid species and sterol lipids. Future applications in clinical cohort studies demand detailed lipid molecule information and the application of high-throughput lipidomics platforms. In this review...... we describe a novel high-throughput shotgun lipidomic platform based on 96-well robot-assisted lipid extraction, automated sample infusion by mircofluidic-based nanoelectrospray ionization, and quantitative multiple precursor ion scanning analysis on a quadrupole time-of-flight mass spectrometer...

  9. Genetic high throughput screening in Retinitis Pigmentosa based on high resolution melting (HRM) analysis.

    Science.gov (United States)

    Anasagasti, Ander; Barandika, Olatz; Irigoyen, Cristina; Benitez, Bruno A; Cooper, Breanna; Cruchaga, Carlos; López de Munain, Adolfo; Ruiz-Ederra, Javier

    2013-11-01

    Retinitis Pigmentosa (RP) involves a group of genetically determined retinal diseases caused by a large number of mutations that result in rod photoreceptor cell death followed by gradual death of cone cells. Most cases of RP are monogenic, with more than 80 associated genes identified so far. The high number of genes and variants involved in RP, among other factors, is making the molecular characterization of RP a real challenge for many patients. Although HRM has been used for the analysis of isolated variants or single RP genes, as far as we are concerned, this is the first study that uses HRM analysis for a high-throughput screening of several RP genes. Our main goal was to test the suitability of HRM analysis as a genetic screening technique in RP, and to compare its performance with two of the most widely used NGS platforms, Illumina and PGM-Ion Torrent technologies. RP patients (n = 96) were clinically diagnosed at the Ophthalmology Department of Donostia University Hospital, Spain. We analyzed a total of 16 RP genes that meet the following inclusion criteria: 1) size: genes with transcripts of less than 4 kb; 2) number of exons: genes with up to 22 exons; and 3) prevalence: genes reported to account for, at least, 0.4% of total RP cases worldwide. For comparison purposes, RHO gene was also sequenced with Illumina (GAII; Illumina), Ion semiconductor technologies (PGM; Life Technologies) and Sanger sequencing (ABI 3130xl platform; Applied Biosystems). Detected variants were confirmed in all cases by Sanger sequencing and tested for co-segregation in the family of affected probands. We identified a total of 65 genetic variants, 15 of which (23%) were novel, in 49 out of 96 patients. Among them, 14 (4 novel) are probable disease-causing genetic variants in 7 RP genes, affecting 15 patients. Our HRM analysis-based study, proved to be a cost-effective and rapid method that provides an accurate identification of genetic RP variants. This approach is effective for

  10. DAVID Knowledgebase: a gene-centered database integrating heterogeneous gene annotation resources to facilitate high-throughput gene functional analysis

    Directory of Open Access Journals (Sweden)

    Baseler Michael W

    2007-11-01

    Full Text Available Abstract Background Due to the complex and distributed nature of biological research, our current biological knowledge is spread over many redundant annotation databases maintained by many independent groups. Analysts usually need to visit many of these bioinformatics databases in order to integrate comprehensive annotation information for their genes, which becomes one of the bottlenecks, particularly for the analytic task associated with a large gene list. Thus, a highly centralized and ready-to-use gene-annotation knowledgebase is in demand for high throughput gene functional analysis. Description The DAVID Knowledgebase is built around the DAVID Gene Concept, a single-linkage method to agglomerate tens of millions of gene/protein identifiers from a variety of public genomic resources into DAVID gene clusters. The grouping of such identifiers improves the cross-reference capability, particularly across NCBI and UniProt systems, enabling more than 40 publicly available functional annotation sources to be comprehensively integrated and centralized by the DAVID gene clusters. The simple, pair-wise, text format files which make up the DAVID Knowledgebase are freely downloadable for various data analysis uses. In addition, a well organized web interface allows users to query different types of heterogeneous annotations in a high-throughput manner. Conclusion The DAVID Knowledgebase is designed to facilitate high throughput gene functional analysis. For a given gene list, it not only provides the quick accessibility to a wide range of heterogeneous annotation data in a centralized location, but also enriches the level of biological information for an individual gene. Moreover, the entire DAVID Knowledgebase is freely downloadable or searchable at http://david.abcc.ncifcrf.gov/knowledgebase/.

  11. A high throughput DNA extraction method with high yield and quality

    Directory of Open Access Journals (Sweden)

    Xin Zhanguo

    2012-07-01

    Full Text Available Abstract Background Preparation of large quantity and high quality genomic DNA from a large number of plant samples is a major bottleneck for most genetic and genomic analyses, such as, genetic mapping, TILLING (Targeting Induced Local Lesion IN Genome, and next-generation sequencing directly from sheared genomic DNA. A variety of DNA preparation methods and commercial kits are available. However, they are either low throughput, low yield, or costly. Here, we describe a method for high throughput genomic DNA isolation from sorghum [Sorghum bicolor (L. Moench] leaves and dry seeds with high yield, high quality, and affordable cost. Results We developed a high throughput DNA isolation method by combining a high yield CTAB extraction method with an improved cleanup procedure based on MagAttract kit. The method yielded large quantity and high quality DNA from both lyophilized sorghum leaves and dry seeds. The DNA yield was improved by nearly 30 fold with 4 times less consumption of MagAttract beads. The method can also be used in other plant species, including cotton leaves and pine needles. Conclusion A high throughput system for DNA extraction from sorghum leaves and seeds was developed and validated. The main advantages of the method are low cost, high yield, high quality, and high throughput. One person can process two 96-well plates in a working day at a cost of $0.10 per sample of magnetic beads plus other consumables that other methods will also need.

  12. High-throughput fractionation of human plasma for fast enrichment of low- and high-abundance proteins.

    Science.gov (United States)

    Breen, Lucas; Cao, Lulu; Eom, Kirsten; Srajer Gajdosik, Martina; Camara, Lila; Giacometti, Jasminka; Dupuy, Damian E; Josic, Djuro

    2012-05-01

    Fast, cost-effective and reproducible isolation of IgM from plasma is invaluable to the study of IgM and subsequent understanding of the human immune system. Additionally, vast amounts of information regarding human physiology and disease can be derived from analysis of the low abundance proteome of the plasma. In this study, methods were optimized for both the high-throughput isolation of IgM from human plasma, and the high-throughput isolation and fractionation of low abundance plasma proteins. To optimize the chromatographic isolation of IgM from human plasma, many variables were examined including chromatography resin, mobile phases, and order of chromatographic separations. Purification of IgM was achieved most successfully through isolation of immunoglobulin from human plasma using Protein A chromatography with a specific resin followed by subsequent fractionation using QA strong anion exchange chromatography. Through these optimization experiments, an additional method was established to prepare plasma for analysis of low abundance proteins. This method involved chromatographic depletion of high-abundance plasma proteins and reduction of plasma proteome complexity through further chromatographic fractionation. Purification of IgM was achieved with high purity as confirmed by SDS-PAGE and IgM-specific immunoblot. Isolation and fractionation of low abundance protein was also performed successfully, as confirmed by SDS-PAGE and mass spectrometry analysis followed by label-free quantitative spectral analysis. The level of purity of the isolated IgM allows for further IgM-specific analysis of plasma samples. The developed fractionation scheme can be used for high throughput screening of human plasma in order to identify low and high abundance proteins as potential prognostic and diagnostic disease biomarkers.

  13. Accelerating the design of biomimetic materials by integrating RNA-seq with proteomics and materials science.

    Science.gov (United States)

    Guerette, Paul A; Hoon, Shawn; Seow, Yiqi; Raida, Manfred; Masic, Admir; Wong, Fong T; Ho, Vincent H B; Kong, Kiat Whye; Demirel, Melik C; Pena-Francesch, Abdon; Amini, Shahrouz; Tay, Gavin Z; Ding, Dawei; Miserez, Ali

    2013-10-01

    Efforts to engineer new materials inspired by biological structures are hampered by the lack of genomic data from many model organisms studied in biomimetic research. Here we show that biomimetic engineering can be accelerated by integrating high-throughput RNA-seq with proteomics and advanced materials characterization. This approach can be applied to a broad range of systems, as we illustrate by investigating diverse high-performance biological materials involved in embryo protection, adhesion and predation. In one example, we rapidly engineer recombinant squid sucker ring teeth proteins into a range of structural and functional materials, including nanopatterned surfaces and photo-cross-linked films that exceed the mechanical properties of most natural and synthetic polymers. Integrating RNA-seq with proteomics and materials science facilitates the molecular characterization of natural materials and the effective translation of their molecular designs into a wide range of bio-inspired materials.

  14. High-throughput image analysis of tumor spheroids: a user-friendly software application to measure the size of spheroids automatically and accurately.

    Science.gov (United States)

    Chen, Wenjin; Wong, Chung; Vosburgh, Evan; Levine, Arnold J; Foran, David J; Xu, Eugenia Y

    2014-07-08

    The increasing number of applications of three-dimensional (3D) tumor spheroids as an in vitro model for drug discovery requires their adaptation to large-scale screening formats in every step of a drug screen, including large-scale image analysis. Currently there is no ready-to-use and free image analysis software to meet this large-scale format. Most existing methods involve manually drawing the length and width of the imaged 3D spheroids, which is a tedious and time-consuming process. This study presents a high-throughput image analysis software application - SpheroidSizer, which measures the major and minor axial length of the imaged 3D tumor spheroids automatically and accurately; calculates the volume of each individual 3D tumor spheroid; then outputs the results in two different forms in spreadsheets for easy manipulations in the subsequent data analysis. The main advantage of this software is its powerful image analysis application that is adapted for large numbers of images. It provides high-throughput computation and quality-control workflow. The estimated time to process 1,000 images is about 15 min on a minimally configured laptop, or around 1 min on a multi-core performance workstation. The graphical user interface (GUI) is also designed for easy quality control, and users can manually override the computer results. The key method used in this software is adapted from the active contour algorithm, also known as Snakes, which is especially suitable for images with uneven illumination and noisy background that often plagues automated imaging processing in high-throughput screens. The complimentary "Manual Initialize" and "Hand Draw" tools provide the flexibility to SpheroidSizer in dealing with various types of spheroids and diverse quality images. This high-throughput image analysis software remarkably reduces labor and speeds up the analysis process. Implementing this software is beneficial for 3D tumor spheroids to become a routine in vitro model

  15. Novel strategy for protein exploration: high-throughput screening assisted with fuzzy neural network.

    Science.gov (United States)

    Kato, Ryuji; Nakano, Hideo; Konishi, Hiroyuki; Kato, Katsuya; Koga, Yuchi; Yamane, Tsuneo; Kobayashi, Takeshi; Honda, Hiroyuki

    2005-08-19

    To engineer proteins with desirable characteristics from a naturally occurring protein, high-throughput screening (HTS) combined with directed evolutional approach is the essential technology. However, most HTS techniques are simple positive screenings. The information obtained from the positive candidates is used only as results but rarely as clues for understanding the structural rules, which may explain the protein activity. In here, we have attempted to establish a novel strategy for exploring functional proteins associated with computational analysis. As a model case, we explored lipases with inverted enantioselectivity for a substrate p-nitrophenyl 3-phenylbutyrate from the wild-type lipase of Burkhorderia cepacia KWI-56, which is originally selective for (S)-configuration of the substrate. Data from our previous work on (R)-enantioselective lipase screening were applied to fuzzy neural network (FNN), bioinformatic algorithm, to extract guidelines for screening and engineering processes to be followed. FNN has an advantageous feature of extracting hidden rules that lie between sequences of variants and their enzyme activity to gain high prediction accuracy. Without any prior knowledge, FNN predicted a rule indicating that "size at position L167," among four positions (L17, F119, L167, and L266) in the substrate binding core region, is the most influential factor for obtaining lipase with inverted (R)-enantioselectivity. Based on the guidelines obtained, newly engineered novel variants, which were not found in the actual screening, were experimentally proven to gain high (R)-enantioselectivity by engineering the size at position L167. We also designed and assayed two novel variants, namely FIGV (L17F, F119I, L167G, and L266V) and FFGI (L17F, L167G, and L266I), which were compatible with the guideline obtained from FNN analysis, and confirmed that these designed lipases could acquire high inverted enantioselectivity. The results have shown that with the aid of

  16. Affinity selection-mass spectrometry and its emerging application to the high throughput screening of G protein-coupled receptors.

    Science.gov (United States)

    Whitehurst, Charles E; Annis, D Allen

    2008-07-01

    Advances in combinatorial chemistry and genomics have inspired the development of novel affinity selection-based screening techniques that rely on mass spectrometry to identify compounds that preferentially bind to a protein target. Of the many affinity selection-mass spectrometry techniques so far documented, only a few solution-based implementations that separate target-ligand complexes away from unbound ligands persist today as routine high throughput screening platforms. Because affinity selection-mass spectrometry techniques do not rely on radioactive or fluorescent reporters or enzyme activities, they can complement traditional biochemical and cell-based screening assays and enable scientists to screen targets that may not be easily amenable to other methods. In addition, by employing mass spectrometry for ligand detection, these techniques enable high throughput screening of massive library collections of pooled compound mixtures, vastly increasing the chemical space that a target can encounter during screening. Of all drug targets, G protein coupled receptors yield the highest percentage of therapeutically effective drugs. In this manuscript, we present the emerging application of affinity selection-mass spectrometry to the high throughput screening of G protein coupled receptors. We also review how affinity selection-mass spectrometry can be used as an analytical tool to guide receptor purification, and further used after screening to characterize target-ligand binding interactions, enabling the classification of orthosteric and allosteric binders.

  17. Transcriptomic analysis of Petunia hybrida in response to salt stress using high throughput RNA sequencing.

    Directory of Open Access Journals (Sweden)

    Gonzalo H Villarino

    Full Text Available Salinity and drought stress are the primary cause of crop losses worldwide. In sodic saline soils sodium chloride (NaCl disrupts normal plant growth and development. The complex interactions of plant systems with abiotic stress have made RNA sequencing a more holistic and appealing approach to study transcriptome level responses in a single cell and/or tissue. In this work, we determined the Petunia transcriptome response to NaCl stress by sequencing leaf samples and assembling 196 million Illumina reads with Trinity software. Using our reference transcriptome we identified more than 7,000 genes that were differentially expressed within 24 h of acute NaCl stress. The proposed transcriptome can also be used as an excellent tool for biological and bioinformatics in the absence of an available Petunia genome and it is available at the SOL Genomics Network (SGN http://solgenomics.net. Genes related to regulation of reactive oxygen species, transport, and signal transductions as well as novel and undescribed transcripts were among those differentially expressed in response to salt stress. The candidate genes identified in this study can be applied as markers for breeding or to genetically engineer plants to enhance salt tolerance. Gene Ontology analyses indicated that most of the NaCl damage happened at 24 h inducing genotoxicity, affecting transport and organelles due to the high concentration of Na+ ions. Finally, we report a modification to the library preparation protocol whereby cDNA samples were bar-coded with non-HPLC purified primers, without affecting the quality and quantity of the RNA-seq data. The methodological improvement presented here could substantially reduce the cost of sample preparation for future high-throughput RNA sequencing experiments.

  18. Transcriptomic analysis of Petunia hybrida in response to salt stress using high throughput RNA sequencing.

    Science.gov (United States)

    Villarino, Gonzalo H; Bombarely, Aureliano; Giovannoni, James J; Scanlon, Michael J; Mattson, Neil S

    2014-01-01

    Salinity and drought stress are the primary cause of crop losses worldwide. In sodic saline soils sodium chloride (NaCl) disrupts normal plant growth and development. The complex interactions of plant systems with abiotic stress have made RNA sequencing a more holistic and appealing approach to study transcriptome level responses in a single cell and/or tissue. In this work, we determined the Petunia transcriptome response to NaCl stress by sequencing leaf samples and assembling 196 million Illumina reads with Trinity software. Using our reference transcriptome we identified more than 7,000 genes that were differentially expressed within 24 h of acute NaCl stress. The proposed transcriptome can also be used as an excellent tool for biological and bioinformatics in the absence of an available Petunia genome and it is available at the SOL Genomics Network (SGN) http://solgenomics.net. Genes related to regulation of reactive oxygen species, transport, and signal transductions as well as novel and undescribed transcripts were among those differentially expressed in response to salt stress. The candidate genes identified in this study can be applied as markers for breeding or to genetically engineer plants to enhance salt tolerance. Gene Ontology analyses indicated that most of the NaCl damage happened at 24 h inducing genotoxicity, affecting transport and organelles due to the high concentration of Na+ ions. Finally, we report a modification to the library preparation protocol whereby cDNA samples were bar-coded with non-HPLC purified primers, without affecting the quality and quantity of the RNA-seq data. The methodological improvement presented here could substantially reduce the cost of sample preparation for future high-throughput RNA sequencing experiments.

  19. High-throughput technology for novel SO2 oxidation catalysts

    International Nuclear Information System (INIS)

    Loskyll, Jonas; Stoewe, Klaus; Maier, Wilhelm F

    2011-01-01

    We review the state of the art and explain the need for better SO 2 oxidation catalysts for the production of sulfuric acid. A high-throughput technology has been developed for the study of potential catalysts in the oxidation of SO 2 to SO 3 . High-throughput methods are reviewed and the problems encountered with their adaptation to the corrosive conditions of SO 2 oxidation are described. We show that while emissivity-corrected infrared thermography (ecIRT) can be used for primary screening, it is prone to errors because of the large variations in the emissivity of the catalyst surface. UV-visible (UV-Vis) spectrometry was selected instead as a reliable analysis method of monitoring the SO 2 conversion. Installing plain sugar absorbents at reactor outlets proved valuable for the detection and quantitative removal of SO 3 from the product gas before the UV-Vis analysis. We also overview some elements used for prescreening and those remaining after the screening of the first catalyst generations. (topical review)

  20. 3D material cytometry (3DMaC): a very high-replicate, high-throughput analytical method using microfabricated, shape-specific, cell-material niches.

    Science.gov (United States)

    Parratt, Kirsten; Jeong, Jenny; Qiu, Peng; Roy, Krishnendu

    2017-08-08

    Studying cell behavior within 3D material niches is key to understanding cell biology in health and diseases, and developing biomaterials for regenerative medicine applications. Current approaches to studying these cell-material niches have low throughput and can only analyze a few replicates per experiment resulting in reduced measurement assurance and analytical power. Here, we report 3D material cytometry (3DMaC), a novel high-throughput method based on microfabricated, shape-specific 3D cell-material niches and imaging cytometry. 3DMaC achieves rapid and highly multiplexed analyses of very high replicate numbers ("n" of 10 4 -10 6 ) of 3D biomaterial constructs. 3DMaC overcomes current limitations of low "n", low-throughput, and "noisy" assays, to provide rapid and simultaneous analyses of potentially hundreds of parameters in 3D biomaterial cultures. The method is demonstrated here for a set of 85 000 events containing twelve distinct cell-biomaterial micro-niches along with robust, customized computational methods for high-throughput analytics with potentially unprecedented statistical power.

  1. Development of Thinopyrum ponticum-specific molecular markers and FISH probes based on SLAF-seq technology.

    Science.gov (United States)

    Liu, Liqin; Luo, Qiaoling; Teng, Wan; Li, Bin; Li, Hongwei; Li, Yiwen; Li, Zhensheng; Zheng, Qi

    2018-05-01

    Based on SLAF-seq, 67 Thinopyrum ponticum-specific markers and eight Th. ponticum-specific FISH probes were developed, and these markers and probes could be used for detection of alien chromatin in a wheat background. Decaploid Thinopyrum ponticum (2n = 10x = 70) is a valuable gene reservoir for wheat improvement. Identification of Th. ponticum introgression would facilitate its transfer into diverse wheat genetic backgrounds and its practical utilization in wheat improvement. Based on specific-locus-amplified fragment sequencing (SLAF-seq) technology, 67 new Th. ponticum-specific molecular markers and eight Th. ponticum-specific fluorescence in situ hybridization (FISH) probes have been developed from a tiny wheat-Th. ponticum translocation line. These newly developed molecular markers allowed the detection of Th. ponticum DNA in a variety of materials specifically and steadily at high throughput. According to the hybridization signal pattern, the eight Th. ponticum-specific probes could be divided into two groups. The first group including five dispersed repetitive sequence probes could identify Th. ponticum chromatin more sensitively and accurately than genomic in situ hybridization (GISH). Whereas the second group having three tandem repetitive sequence probes enabled the discrimination of Th. ponticum chromosomes together with another clone pAs1 in wheat-Th. ponticum partial amphiploid Xiaoyan 68.

  2. Continuing Development of Alternative High-Throughput Screens to Determine Endocrine Disruption, Focusing on Androgen Receptor, Steroidogenesis, and Thyroid Pathways

    Science.gov (United States)

    The focus of this meeting is the SAP's review and comment on the Agency's proposed high-throughput computational model of androgen receptor pathway activity as an alternative to the current Tier 1 androgen receptor assay (OCSPP 890.1150: Androgen Receptor Binding Rat Prostate Cyt...

  3. RNA-Seq transcriptomics and pathway analyses reveal potential regulatory genes and molecular mechanisms in high- and low-residual feed intake in Nordic dairy cattle

    DEFF Research Database (Denmark)

    Salleh, M. S.; Mazzoni, G.; Höglund, J. K.

    2017-01-01

    -throughput RNA sequencing data of liver biopsies from 19 dairy cows were used to identify differentially expressed genes (DEGs) between high- and low-FE groups of cows (based on Residual Feed Intake or RFI). Subsequently, a profile of the pathways connecting the DEGs to FE was generated, and a list of candidate...... genes and biomarkers was derived for their potential inclusion in breeding programmes to improve FE. The bovine RNA-Seq gene expression data from the liver was analysed to identify DEGs and, subsequently, identify the molecular mechanisms, pathways and possible candidate biomarkers of feed efficiency....... On average, 57 million reads (short reads or short mRNA sequences ...

  4. Homologous high-throughput expression and purification of highly conserved E coli proteins

    Directory of Open Access Journals (Sweden)

    Duchmann Rainer

    2007-06-01

    Full Text Available Abstract Background Genetic factors and a dysregulated immune response towards commensal bacteria contribute to the pathogenesis of Inflammatory Bowel Disease (IBD. Animal models demonstrated that the normal intestinal flora is crucial for the development of intestinal inflammation. However, due to the complexity of the intestinal flora, it has been difficult to design experiments for detection of proinflammatory bacterial antigen(s involved in the pathogenesis of the disease. Several studies indicated a potential association of E. coli with IBD. In addition, T cell clones of IBD patients were shown to cross react towards antigens from different enteric bacterial species and thus likely responded to conserved bacterial antigens. We therefore chose highly conserved E. coli proteins as candidate antigens for abnormal T cell responses in IBD and used high-throughput techniques for cloning, expression and purification under native conditions of a set of 271 conserved E. coli proteins for downstream immunologic studies. Results As a standardized procedure, genes were PCR amplified and cloned into the expression vector pQTEV2 in order to express proteins N-terminally fused to a seven-histidine-tag. Initial small-scale expression and purification under native conditions by metal chelate affinity chromatography indicated that the vast majority of target proteins were purified in high yields. Targets that revealed low yields after purification probably due to weak solubility were shuttled into Gateway (Invitrogen destination vectors in order to enhance solubility by N-terminal fusion of maltose binding protein (MBP, N-utilizing substance A (NusA, or glutathione S-transferase (GST to the target protein. In addition, recombinant proteins were treated with polymyxin B coated magnetic beads in order to remove lipopolysaccharide (LPS. Thus, 73% of the targeted proteins could be expressed and purified in large-scale to give soluble proteins in the range of 500

  5. Management of High-Throughput DNA Sequencing Projects: Alpheus.

    Science.gov (United States)

    Miller, Neil A; Kingsmore, Stephen F; Farmer, Andrew; Langley, Raymond J; Mudge, Joann; Crow, John A; Gonzalez, Alvaro J; Schilkey, Faye D; Kim, Ryan J; van Velkinburgh, Jennifer; May, Gregory D; Black, C Forrest; Myers, M Kathy; Utsey, John P; Frost, Nicholas S; Sugarbaker, David J; Bueno, Raphael; Gullans, Stephen R; Baxter, Susan M; Day, Steve W; Retzel, Ernest F

    2008-12-26

    High-throughput DNA sequencing has enabled systems biology to begin to address areas in health, agricultural and basic biological research. Concomitant with the opportunities is an absolute necessity to manage significant volumes of high-dimensional and inter-related data and analysis. Alpheus is an analysis pipeline, database and visualization software for use with massively parallel DNA sequencing technologies that feature multi-gigabase throughput characterized by relatively short reads, such as Illumina-Solexa (sequencing-by-synthesis), Roche-454 (pyrosequencing) and Applied Biosystem's SOLiD (sequencing-by-ligation). Alpheus enables alignment to reference sequence(s), detection of variants and enumeration of sequence abundance, including expression levels in transcriptome sequence. Alpheus is able to detect several types of variants, including non-synonymous and synonymous single nucleotide polymorphisms (SNPs), insertions/deletions (indels), premature stop codons, and splice isoforms. Variant detection is aided by the ability to filter variant calls based on consistency, expected allele frequency, sequence quality, coverage, and variant type in order to minimize false positives while maximizing the identification of true positives. Alpheus also enables comparisons of genes with variants between cases and controls or bulk segregant pools. Sequence-based differential expression comparisons can be developed, with data export to SAS JMP Genomics for statistical analysis.

  6. Computational and statistical methods for high-throughput mass spectrometry-based PTM analysis

    DEFF Research Database (Denmark)

    Schwämmle, Veit; Vaudel, Marc

    2017-01-01

    Cell signaling and functions heavily rely on post-translational modifications (PTMs) of proteins. Their high-throughput characterization is thus of utmost interest for multiple biological and medical investigations. In combination with efficient enrichment methods, peptide mass spectrometry analy...

  7. Global mapping of cell type-specific open chromatin by FAIRE-seq reveals the regulatory role of the NFI family in adipocyte differentiation.

    Directory of Open Access Journals (Sweden)

    Hironori Waki

    2011-10-01

    Full Text Available Identification of regulatory elements within the genome is crucial for understanding the mechanisms that govern cell type-specific gene expression. We generated genome-wide maps of open chromatin sites in 3T3-L1 adipocytes (on day 0 and day 8 of differentiation and NIH-3T3 fibroblasts using formaldehyde-assisted isolation of regulatory elements coupled with high-throughput sequencing (FAIRE-seq. FAIRE peaks at the promoter were associated with active transcription and histone modifications of H3K4me3 and H3K27ac. Non-promoter FAIRE peaks were characterized by H3K4me1+/me3-, the signature of enhancers, and were largely located in distal regions. The non-promoter FAIRE peaks showed dynamic change during differentiation, while the promoter FAIRE peaks were relatively constant. Functionally, the adipocyte- and preadipocyte-specific non-promoter FAIRE peaks were, respectively, associated with genes up-regulated and down-regulated by differentiation. Genes highly up-regulated during differentiation were associated with multiple clustered adipocyte-specific FAIRE peaks. Among the adipocyte-specific FAIRE peaks, 45.3% and 11.7% overlapped binding sites for, respectively, PPARγ and C/EBPα, the master regulators of adipocyte differentiation. Computational motif analyses of the adipocyte-specific FAIRE peaks revealed enrichment of a binding motif for nuclear family I (NFI transcription factors. Indeed, ChIP assay showed that NFI occupy the adipocyte-specific FAIRE peaks and/or the PPARγ binding sites near PPARγ, C/EBPα, and aP2 genes. Overexpression of NFIA in 3T3-L1 cells resulted in robust induction of these genes and lipid droplet formation without differentiation stimulus. Overexpression of dominant-negative NFIA or siRNA-mediated knockdown of NFIA or NFIB significantly suppressed both induction of genes and lipid accumulation during differentiation, suggesting a physiological function of these factors in the adipogenic program. Together, our

  8. A High-Throughput Cell-Based Screen Identified a 2-[(E)-2-Phenylvinyl]-8-Quinolinol Core Structure That Activates p53.

    Science.gov (United States)

    Bechill, John; Zhong, Rong; Zhang, Chen; Solomaha, Elena; Spiotto, Michael T

    2016-01-01

    p53 function is frequently inhibited in cancer either through mutations or by increased degradation via MDM2 and/or E6AP E3-ubiquitin ligases. Most agents that restore p53 expression act by binding MDM2 or E6AP to prevent p53 degradation. However, fewer compounds directly bind to and activate p53. Here, we identified compounds that shared a core structure that bound p53, caused nuclear localization of p53 and caused cell death. To identify these compounds, we developed a novel cell-based screen to redirect p53 degradation to the Skip-Cullin-F-box (SCF) ubiquitin ligase complex in cells expressing high levels of p53. In a multiplexed assay, we coupled p53 targeted degradation with Rb1 targeted degradation in order to identify compounds that prevented p53 degradation while not inhibiting degradation through the SCF complex or other proteolytic machinery. High-throughput screening identified several leads that shared a common 2-[(E)-2-phenylvinyl]-8-quinolinol core structure that stabilized p53. Surface plasmon resonance analysis indicated that these compounds bound p53 with a KD of 200 ± 52 nM. Furthermore, these compounds increased p53 nuclear localization and transcription of the p53 target genes PUMA, BAX, p21 and FAS in cancer cells. Although p53-null cells had a 2.5±0.5-fold greater viability compared to p53 wild type cells after treatment with core compounds, loss of p53 did not completely rescue cell viability suggesting that compounds may target both p53-dependent and p53-independent pathways to inhibit cell proliferation. Thus, we present a novel, cell-based high-throughput screen to identify a 2-[(E)-2-phenylvinyl]-8-quinolinol core structure that bound to p53 and increased p53 activity in cancer cells. These compounds may serve as anti-neoplastic agents in part by targeting p53 as well as other potential pathways.

  9. SALP, a new single-stranded DNA library preparation method especially useful for the high-throughput characterization of chromatin openness states.

    Science.gov (United States)

    Wu, Jian; Dai, Wei; Wu, Lin; Wang, Jinke

    2018-02-13

    Next-generation sequencing (NGS) is fundamental to the current biological and biomedical research. Construction of sequencing library is a key step of NGS. Therefore, various library construction methods have been explored. However, the current methods are still limited by some shortcomings. This study developed a new NGS library construction method, Single strand Adaptor Library Preparation (SALP), by using a novel single strand adaptor (SSA). SSA is a double-stranded oligonucleotide with a 3' overhang of 3 random nucleotides, which can be efficiently ligated to the 3' end of single strand DNA by T4 DNA ligase. SALP can be started with any denatured DNA fragments such as those sheared by Tn5 tagmentation, enzyme digestion and sonication. When started with Tn5-tagmented chromatin, SALP can overcome a key limitation of ATAC-seq and become a high-throughput NGS library construction method, SALP-seq, which can be used to comparatively characterize the chromatin openness state of multiple cells unbiasly. In this way, this study successfully characterized the comparative chromatin openness states of four different cell lines, including GM12878, HepG2, HeLa and 293T, with SALP-seq. Similarly, this study also successfully characterized the chromatin openness states of HepG2 cells with SALP-seq by using 10 5 to 500 cells. This study developed a new NGS library construction method, SALP, by using a novel kind of single strand adaptor (SSA), which should has wide applications in the future due to its unique performance.

  10. Multiplexed homogeneous proximity ligation assays for high throughput protein biomarker research in serological material

    DEFF Research Database (Denmark)

    Lundberg, Martin; Thorsen, Stine Buch; Assarsson, Erika

    2011-01-01

    A high throughput protein biomarker discovery tool has been developed based on multiplexed proximity ligation assays (PLA) in a homogeneous format in the sense of no washing steps. The platform consists of four 24-plex panels profiling 74 putative biomarkers with sub pM sensitivity each consuming...... sequences are united by DNA ligation upon simultaneous target binding forming a PCR amplicon. Multiplex PLA thereby converts multiple target analytes into real-time PCR amplicons that are individually quantificatied using microfluidic high capacity qPCR in nano liter volumes. The assay shows excellent...

  11. Simultaneous and complete genome sequencing of influenza A and B with high coverage by Illumina MiSeq Platform.

    Science.gov (United States)

    Rutvisuttinunt, Wiriya; Chinnawirotpisan, Piyawan; Simasathien, Sriluck; Shrestha, Sanjaya K; Yoon, In-Kyu; Klungthong, Chonticha; Fernandez, Stefan

    2013-11-01

    Active global surveillance and characterization of influenza viruses are essential for better preparation against possible pandemic events. Obtaining comprehensive information about the influenza genome can improve our understanding of the evolution of influenza viruses and emergence of new strains, and improve the accuracy when designing preventive vaccines. This study investigated the use of deep sequencing by the next-generation sequencing (NGS) Illumina MiSeq Platform to obtain complete genome sequence information from influenza virus isolates. The influenza virus isolates were cultured from 6 respiratory acute clinical specimens collected in Thailand and Nepal. DNA libraries obtained from each viral isolate were mixed and all were sequenced simultaneously. Total information of 2.6 Gbases was obtained from a 455±14 K/mm2 density with 95.76% (8,571,655/8,950,724 clusters) of the clusters passing quality control (QC) filters. Approximately 93.7% of all sequences from Read1 and 83.5% from Read2 contained high quality sequences that were ≥Q30, a base calling QC score standard. Alignments analysis identified three seasonal influenza A H3N2 strains, one 2009 pandemic influenza A H1N1 strain and two influenza B strains. The nearly entire genomes of all six virus isolates yielded equal or greater than 600-fold sequence coverage depth. MiSeq Platform identified seasonal influenza A H3N2, 2009 pandemic influenza A H1N1and influenza B in the DNA library mixtures efficiently. Copyright © 2013 The Authors. Published by Elsevier B.V. All rights reserved.

  12. High-Throughput Screening and Quantitation of Target Compounds in Biofluids by Coated Blade Spray-Mass Spectrometry.

    Science.gov (United States)

    Tascon, Marcos; Gómez-Ríos, Germán Augusto; Reyes-Garcés, Nathaly; Poole, Justen; Boyacı, Ezel; Pawliszyn, Janusz

    2017-08-15

    Most contemporary methods of screening and quantitating controlled substances and therapeutic drugs in biofluids typically require laborious, time-consuming, and expensive analytical workflows. In recent years, our group has worked toward developing microextraction (μe)-mass spectrometry (MS) technologies that merge all of the tedious steps of the classical methods into a simple, efficient, and low-cost methodology. Unquestionably, the automation of these technologies allows for faster sample throughput, greater reproducibility, and radically reduced analysis times. Coated blade spray (CBS) is a μe technology engineered for extracting/enriching analytes of interest in complex matrices, and it can be directly coupled with MS instruments to achieve efficient screening and quantitative analysis. In this study, we introduced CBS as a technology that can be arranged to perform either rapid diagnostics (single vial) or the high-throughput (96-well plate) analysis of biofluids. Furthermore, we demonstrate that performing 96-CBS extractions at the same time allows the total analysis time to be reduced to less than 55 s per sample. Aiming to validate the versatility of CBS, substances comprising a broad range of molecular weights, moieties, protein binding, and polarities were selected. Thus, the high-throughput (HT)-CBS technology was used for the concomitant quantitation of 18 compounds (mixture of anabolics, β-2 agonists, diuretics, stimulants, narcotics, and β-blockers) spiked in human urine and plasma samples. Excellent precision (∼2.5%), accuracy (≥90%), and linearity (R 2 ≥ 0.99) were attained for all the studied compounds, and the limits of quantitation (LOQs) were within the range of 0.1 to 10 ng·mL -1 for plasma and 0.25 to 10 ng·mL -1 for urine. The results reported in this paper confirm CBS's great potential for achieving subsixty-second analyses of target compounds in a broad range of fields such as those related to clinical diagnosis, food, the

  13. An automated, high-throughput plant phenotyping system using machine learning-based plant segmentation and image analysis.

    Science.gov (United States)

    Lee, Unseok; Chang, Sungyul; Putra, Gian Anantrio; Kim, Hyoungseok; Kim, Dong Hwan

    2018-01-01

    A high-throughput plant phenotyping system automatically observes and grows many plant samples. Many plant sample images are acquired by the system to determine the characteristics of the plants (populations). Stable image acquisition and processing is very important to accurately determine the characteristics. However, hardware for acquiring plant images rapidly and stably, while minimizing plant stress, is lacking. Moreover, most software cannot adequately handle large-scale plant imaging. To address these problems, we developed a new, automated, high-throughput plant phenotyping system using simple and robust hardware, and an automated plant-imaging-analysis pipeline consisting of machine-learning-based plant segmentation. Our hardware acquires images reliably and quickly and minimizes plant stress. Furthermore, the images are processed automatically. In particular, large-scale plant-image datasets can be segmented precisely using a classifier developed using a superpixel-based machine-learning algorithm (Random Forest), and variations in plant parameters (such as area) over time can be assessed using the segmented images. We performed comparative evaluations to identify an appropriate learning algorithm for our proposed system, and tested three robust learning algorithms. We developed not only an automatic analysis pipeline but also a convenient means of plant-growth analysis that provides a learning data interface and visualization of plant growth trends. Thus, our system allows end-users such as plant biologists to analyze plant growth via large-scale plant image data easily.

  14. High-Throughput Screening and Hit Validation of Extracellular-Related Kinase 5 (ERK5) Inhibitors.

    Science.gov (United States)

    Myers, Stephanie M; Bawn, Ruth H; Bisset, Louise C; Blackburn, Timothy J; Cottyn, Betty; Molyneux, Lauren; Wong, Ai-Ching; Cano, Celine; Clegg, William; Harrington, Ross W; Leung, Hing; Rigoreau, Laurent; Vidot, Sandrine; Golding, Bernard T; Griffin, Roger J; Hammonds, Tim; Newell, David R; Hardcastle, Ian R

    2016-08-08

    The extracellular-related kinase 5 (ERK5) is a promising target for cancer therapy. A high-throughput screen was developed for ERK5, based on the IMAP FP progressive binding system, and used to identify hits from a library of 57 617 compounds. Four distinct chemical series were evident within the screening hits. Resynthesis and reassay of the hits demonstrated that one series did not return active compounds, whereas three series returned active hits. Structure-activity studies demonstrated that the 4-benzoylpyrrole-2-carboxamide pharmacophore had excellent potential for further development. The minimum kinase binding pharmacophore was identified, and key examples demonstrated good selectivity for ERK5 over p38α kinase.

  15. High Throughput PBTK: Open-Source Data and Tools for ...

    Science.gov (United States)

    Presentation on High Throughput PBTK at the PBK Modelling in Risk Assessment meeting in Ispra, Italy Presentation on High Throughput PBTK at the PBK Modelling in Risk Assessment meeting in Ispra, Italy

  16. Commentary: Roles for Pathologists in a High-throughput Image Analysis Team.

    Science.gov (United States)

    Aeffner, Famke; Wilson, Kristin; Bolon, Brad; Kanaly, Suzanne; Mahrt, Charles R; Rudmann, Dan; Charles, Elaine; Young, G David

    2016-08-01

    Historically, pathologists perform manual evaluation of H&E- or immunohistochemically-stained slides, which can be subjective, inconsistent, and, at best, semiquantitative. As the complexity of staining and demand for increased precision of manual evaluation increase, the pathologist's assessment will include automated analyses (i.e., "digital pathology") to increase the accuracy, efficiency, and speed of diagnosis and hypothesis testing and as an important biomedical research and diagnostic tool. This commentary introduces the many roles for pathologists in designing and conducting high-throughput digital image analysis. Pathology review is central to the entire course of a digital pathology study, including experimental design, sample quality verification, specimen annotation, analytical algorithm development, and report preparation. The pathologist performs these roles by reviewing work undertaken by technicians and scientists with training and expertise in image analysis instruments and software. These roles require regular, face-to-face interactions between team members and the lead pathologist. Traditional pathology training is suitable preparation for entry-level participation on image analysis teams. The future of pathology is very exciting, with the expanding utilization of digital image analysis set to expand pathology roles in research and drug development with increasing and new career opportunities for pathologists. © 2016 by The Author(s) 2016.

  17. High throughput 16S rRNA gene amplicon sequencing

    DEFF Research Database (Denmark)

    Nierychlo, Marta; Larsen, Poul; Jørgensen, Mads Koustrup

    S rRNA gene amplicon sequencing has been developed over the past few years and is now ready to use for more comprehensive studies related to plant operation and optimization thanks to short analysis time, low cost, high throughput, and high taxonomic resolution. In this study we show how 16S r......RNA gene amplicon sequencing can be used to reveal factors of importance for the operation of full-scale nutrient removal plants related to settling problems and floc properties. Using optimized DNA extraction protocols, indexed primers and our in-house Illumina platform, we prepared multiple samples...... be correlated to the presence of the species that are regarded as “strong” and “weak” floc formers. In conclusion, 16S rRNA gene amplicon sequencing provides a high throughput approach for a rapid and cheap community profiling of activated sludge that in combination with multivariate statistics can be used...

  18. Subnuclear foci quantification using high-throughput 3D image cytometry

    Science.gov (United States)

    Wadduwage, Dushan N.; Parrish, Marcus; Choi, Heejin; Engelward, Bevin P.; Matsudaira, Paul; So, Peter T. C.

    2015-07-01

    Ionising radiation causes various types of DNA damages including double strand breaks (DSBs). DSBs are often recognized by DNA repair protein ATM which forms gamma-H2AX foci at the site of the DSBs that can be visualized using immunohistochemistry. However most of such experiments are of low throughput in terms of imaging and image analysis techniques. Most of the studies still use manual counting or classification. Hence they are limited to counting a low number of foci per cell (5 foci per nucleus) as the quantification process is extremely labour intensive. Therefore we have developed a high throughput instrumentation and computational pipeline specialized for gamma-H2AX foci quantification. A population of cells with highly clustered foci inside nuclei were imaged, in 3D with submicron resolution, using an in-house developed high throughput image cytometer. Imaging speeds as high as 800 cells/second in 3D were achieved by using HiLo wide-field depth resolved imaging and a remote z-scanning technique. Then the number of foci per cell nucleus were quantified using a 3D extended maxima transform based algorithm. Our results suggests that while most of the other 2D imaging and manual quantification studies can count only up to about 5 foci per nucleus our method is capable of counting more than 100. Moreover we show that 3D analysis is significantly superior compared to the 2D techniques.

  19. ToxCast Workflow: High-throughput screening assay data processing, analysis and management (SOT)

    Science.gov (United States)

    US EPA’s ToxCast program is generating data in high-throughput screening (HTS) and high-content screening (HCS) assays for thousands of environmental chemicals, for use in developing predictive toxicity models. Currently the ToxCast screening program includes over 1800 unique c...

  20. High-throughput bioinformatics with the Cyrille2 pipeline system

    Directory of Open Access Journals (Sweden)

    de Groot Joost CW

    2008-02-01

    Full Text Available Abstract Background Modern omics research involves the application of high-throughput technologies that generate vast volumes of data. These data need to be pre-processed, analyzed and integrated with existing knowledge through the use of diverse sets of software tools, models and databases. The analyses are often interdependent and chained together to form complex workflows or pipelines. Given the volume of the data used and the multitude of computational resources available, specialized pipeline software is required to make high-throughput analysis of large-scale omics datasets feasible. Results We have developed a generic pipeline system called Cyrille2. The system is modular in design and consists of three functionally distinct parts: 1 a web based, graphical user interface (GUI that enables a pipeline operator to manage the system; 2 the Scheduler, which forms the functional core of the system and which tracks what data enters the system and determines what jobs must be scheduled for execution, and; 3 the Executor, which searches for scheduled jobs and executes these on a compute cluster. Conclusion The Cyrille2 system is an extensible, modular system, implementing the stated requirements. Cyrille2 enables easy creation and execution of high throughput, flexible bioinformatics pipelines.

  1. Robust, high-throughput solution structural analyses by small angle X-ray scattering (SAXS)

    Energy Technology Data Exchange (ETDEWEB)

    Hura, Greg L.; Menon, Angeli L.; Hammel, Michal; Rambo, Robert P.; Poole II, Farris L.; Tsutakawa, Susan E.; Jenney Jr, Francis E.; Classen, Scott; Frankel, Kenneth A.; Hopkins, Robert C.; Yang, Sungjae; Scott, Joseph W.; Dillard, Bret D.; Adams, Michael W. W.; Tainer, John A.

    2009-07-20

    We present an efficient pipeline enabling high-throughput analysis of protein structure in solution with small angle X-ray scattering (SAXS). Our SAXS pipeline combines automated sample handling of microliter volumes, temperature and anaerobic control, rapid data collection and data analysis, and couples structural analysis with automated archiving. We subjected 50 representative proteins, mostly from Pyrococcus furiosus, to this pipeline and found that 30 were multimeric structures in solution. SAXS analysis allowed us to distinguish aggregated and unfolded proteins, define global structural parameters and oligomeric states for most samples, identify shapes and similar structures for 25 unknown structures, and determine envelopes for 41 proteins. We believe that high-throughput SAXS is an enabling technology that may change the way that structural genomics research is done.

  2. A high content, high throughput cellular thermal stability assay for measuring drug-target engagement in living cells.

    Science.gov (United States)

    Massey, Andrew J

    2018-01-01

    Determining and understanding drug target engagement is critical for drug discovery. This can be challenging within living cells as selective readouts are often unavailable. Here we describe a novel method for measuring target engagement in living cells based on the principle of altered protein thermal stabilization / destabilization in response to ligand binding. This assay (HCIF-CETSA) utilizes high content, high throughput single cell immunofluorescent detection to determine target protein levels following heating of adherent cells in a 96 well plate format. We have used target engagement of Chk1 by potent small molecule inhibitors to validate the assay. Target engagement measured by this method was subsequently compared to target engagement measured by two alternative methods (autophosphorylation and CETSA). The HCIF-CETSA method appeared robust and a good correlation in target engagement measured by this method and CETSA for the selective Chk1 inhibitor V158411 was observed. However, these EC50 values were 23- and 12-fold greater than the autophosphorylation IC50. The described method is therefore a valuable advance in the CETSA method allowing the high throughput determination of target engagement in adherent cells.

  3. High throughput screening method for assessing heterogeneity of microorganisms

    NARCIS (Netherlands)

    Ingham, C.J.; Sprenkels, A.J.; van Hylckama Vlieg, J.E.T.; Bomer, Johan G.; de Vos, W.M.; van den Berg, Albert

    2006-01-01

    The invention relates to the field of microbiology. Provided is a method which is particularly powerful for High Throughput Screening (HTS) purposes. More specific a high throughput method for determining heterogeneity or interactions of microorganisms is provided.

  4. Secure and robust cloud computing for high-throughput forensic microsatellite sequence analysis and databasing.

    Science.gov (United States)

    Bailey, Sarah F; Scheible, Melissa K; Williams, Christopher; Silva, Deborah S B S; Hoggan, Marina; Eichman, Christopher; Faith, Seth A

    2017-11-01

    Next-generation Sequencing (NGS) is a rapidly evolving technology with demonstrated benefits for forensic genetic applications, and the strategies to analyze and manage the massive NGS datasets are currently in development. Here, the computing, data storage, connectivity, and security resources of the Cloud were evaluated as a model for forensic laboratory systems that produce NGS data. A complete front-to-end Cloud system was developed to upload, process, and interpret raw NGS data using a web browser dashboard. The system was extensible, demonstrating analysis capabilities of autosomal and Y-STRs from a variety of NGS instrumentation (Illumina MiniSeq and MiSeq, and Oxford Nanopore MinION). NGS data for STRs were concordant with standard reference materials previously characterized with capillary electrophoresis and Sanger sequencing. The computing power of the Cloud was implemented with on-demand auto-scaling to allow multiple file analysis in tandem. The system was designed to store resulting data in a relational database, amenable to downstream sample interpretations and databasing applications following the most recent guidelines in nomenclature for sequenced alleles. Lastly, a multi-layered Cloud security architecture was tested and showed that industry standards for securing data and computing resources were readily applied to the NGS system without disadvantageous effects for bioinformatic analysis, connectivity or data storage/retrieval. The results of this study demonstrate the feasibility of using Cloud-based systems for secured NGS data analysis, storage, databasing, and multi-user distributed connectivity. Copyright © 2017 Elsevier B.V. All rights reserved.

  5. Quantitative digital image analysis of chromogenic assays for high throughput screening of alpha-amylase mutant libraries.

    Science.gov (United States)

    Shankar, Manoharan; Priyadharshini, Ramachandran; Gunasekaran, Paramasamy

    2009-08-01

    An image analysis-based method for high throughput screening of an alpha-amylase mutant library using chromogenic assays was developed. Assays were performed in microplates and high resolution images of the assay plates were read using the Virtual Microplate Reader (VMR) script to quantify the concentration of the chromogen. This method is fast and sensitive in quantifying 0.025-0.3 mg starch/ml as well as 0.05-0.75 mg glucose/ml. It was also an effective screening method for improved alpha-amylase activity with a coefficient of variance of 18%.

  6. voom: Precision weights unlock linear model analysis tools for RNA-seq read counts.

    Science.gov (United States)

    Law, Charity W; Chen, Yunshun; Shi, Wei; Smyth, Gordon K

    2014-02-03

    New normal linear modeling strategies are presented for analyzing read counts from RNA-seq experiments. The voom method estimates the mean-variance relationship of the log-counts, generates a precision weight for each observation and enters these into the limma empirical Bayes analysis pipeline. This opens access for RNA-seq analysts to a large body of methodology developed for microarrays. Simulation studies show that voom performs as well or better than count-based RNA-seq methods even when the data are generated according to the assumptions of the earlier methods. Two case studies illustrate the use of linear modeling and gene set testing methods.

  7. Infra-red thermography for high throughput field phenotyping in Solanum tuberosum.

    Directory of Open Access Journals (Sweden)

    Ankush Prashar

    Full Text Available The rapid development of genomic technology has made high throughput genotyping widely accessible but the associated high throughput phenotyping is now the major limiting factor in genetic analysis of traits. This paper evaluates the use of thermal imaging for the high throughput field phenotyping of Solanum tuberosum for differences in stomatal behaviour. A large multi-replicated trial of a potato mapping population was used to investigate the consistency in genotypic rankings across different trials and across measurements made at different times of day and on different days. The results confirmed a high degree of consistency between the genotypic rankings based on relative canopy temperature on different occasions. Genotype discrimination was enhanced both through normalising data by expressing genotype temperatures as differences from image means and through the enhanced replication obtained by using overlapping images. A Monte Carlo simulation approach was used to confirm the magnitude of genotypic differences that it is possible to discriminate. The results showed a clear negative association between canopy temperature and final tuber yield for this population, when grown under ample moisture supply. We have therefore established infrared thermography as an easy, rapid and non-destructive screening method for evaluating large population trials for genetic analysis. We also envisage this approach as having great potential for evaluating plant response to stress under field conditions.

  8. Integrated Automation of High-Throughput Screening and Reverse Phase Protein Array Sample Preparation

    DEFF Research Database (Denmark)

    Pedersen, Marlene Lemvig; Block, Ines; List, Markus

    into automated robotic high-throughput screens, which allows subsequent protein quantification. In this integrated solution, samples are directly forwarded to automated cell lysate preparation and preparation of dilution series, including reformatting to a protein spotter-compatible format after the high......-throughput screening. Tracking of huge sample numbers and data analysis from a high-content screen to RPPAs is accomplished via MIRACLE, a custom made software suite developed by us. To this end, we demonstrate that the RPPAs generated in this manner deliver reliable protein readouts and that GAPDH and TFR levels can...

  9. Seq2Logo: a method for construction and visualization of amino acid binding motifs and sequence profiles including sequence weighting, pseudo counts and two-sided representation of amino acid enrichment and depletion

    DEFF Research Database (Denmark)

    Thomsen, Martin Christen Frølund; Nielsen, Morten

    2012-01-01

    Seq2Logo is a web-based sequence logo generator. Sequence logos are a graphical representation of the information content stored in a multiple sequence alignment (MSA) and provide a compact and highly intuitive representation of the position-specific amino acid composition of binding motifs, active...... related to amino acid enrichment and depletion. Besides allowing input in the format of peptides and MSA, Seq2Logo accepts input as Blast sequence profiles, providing easy access for non-expert end-users to characterize and identify functionally conserved/variable amino acids in any given protein...... sites, etc. in biological sequences. Accurate generation of sequence logos is often compromised by sequence redundancy and low number of observations. Moreover, most methods available for sequence logo generation focus on displaying the position-specific enrichment of amino acids, discarding the equally...

  10. High-throughput sample adaptive offset hardware architecture for high-efficiency video coding

    Science.gov (United States)

    Zhou, Wei; Yan, Chang; Zhang, Jingzhi; Zhou, Xin

    2018-03-01

    A high-throughput hardware architecture for a sample adaptive offset (SAO) filter in the high-efficiency video coding video coding standard is presented. First, an implementation-friendly and simplified bitrate estimation method of rate-distortion cost calculation is proposed to reduce the computational complexity in the mode decision of SAO. Then, a high-throughput VLSI architecture for SAO is presented based on the proposed bitrate estimation method. Furthermore, multiparallel VLSI architecture for in-loop filters, which integrates both deblocking filter and SAO filter, is proposed. Six parallel strategies are applied in the proposed in-loop filters architecture to improve the system throughput and filtering speed. Experimental results show that the proposed in-loop filters architecture can achieve up to 48% higher throughput in comparison with prior work. The proposed architecture can reach a high-operating clock frequency of 297 MHz with TSMC 65-nm library and meet the real-time requirement of the in-loop filters for 8 K × 4 K video format at 132 fps.

  11. High-throughput verification of transcriptional starting sites by Deep-RACE

    DEFF Research Database (Denmark)

    Olivarius, Signe; Plessy, Charles; Carninci, Piero

    2009-01-01

    We present a high-throughput method for investigating the transcriptional starting sites of genes of interest, which we named Deep-RACE (Deep–rapid amplification of cDNA ends). Taking advantage of the latest sequencing technology, it allows the parallel analysis of multiple genes and is free...

  12. Digital Biomass Accumulation Using High-Throughput Plant Phenotype Data Analysis.

    Science.gov (United States)

    Rahaman, Md Matiur; Ahsan, Md Asif; Gillani, Zeeshan; Chen, Ming

    2017-09-01

    Biomass is an important phenotypic trait in functional ecology and growth analysis. The typical methods for measuring biomass are destructive, and they require numerous individuals to be cultivated for repeated measurements. With the advent of image-based high-throughput plant phenotyping facilities, non-destructive biomass measuring methods have attempted to overcome this problem. Thus, the estimation of plant biomass of individual plants from their digital images is becoming more important. In this paper, we propose an approach to biomass estimation based on image derived phenotypic traits. Several image-based biomass studies state that the estimation of plant biomass is only a linear function of the projected plant area in images. However, we modeled the plant volume as a function of plant area, plant compactness, and plant age to generalize the linear biomass model. The obtained results confirm the proposed model and can explain most of the observed variance during image-derived biomass estimation. Moreover, a small difference was observed between actual and estimated digital biomass, which indicates that our proposed approach can be used to estimate digital biomass accurately.

  13. ASAP: a web-based platform for the analysis and interactive visualization of single-cell RNA-seq data.

    Science.gov (United States)

    Gardeux, Vincent; David, Fabrice P A; Shajkofci, Adrian; Schwalie, Petra C; Deplancke, Bart

    2017-10-01

    Single-cell RNA-sequencing (scRNA-seq) allows whole transcriptome profiling of thousands of individual cells, enabling the molecular exploration of tissues at the cellular level. Such analytical capacity is of great interest to many research groups in the world, yet these groups often lack the expertise to handle complex scRNA-seq datasets. We developed a fully integrated, web-based platform aimed at the complete analysis of scRNA-seq data post genome alignment: from the parsing, filtering and normalization of the input count data files, to the visual representation of the data, identification of cell clusters, differentially expressed genes (including cluster-specific marker genes), and functional gene set enrichment. This Automated Single-cell Analysis Pipeline (ASAP) combines a wide range of commonly used algorithms with sophisticated visualization tools. Compared with existing scRNA-seq analysis platforms, researchers (including those lacking computational expertise) are able to interact with the data in a straightforward fashion and in real time. Furthermore, given the overlap between scRNA-seq and bulk RNA-seq analysis workflows, ASAP should conceptually be broadly applicable to any RNA-seq dataset. As a validation, we demonstrate how we can use ASAP to simply reproduce the results from a single-cell study of 91 mouse cells involving five distinct cell types. The tool is freely available at asap.epfl.ch and R/Python scripts are available at github.com/DeplanckeLab/ASAP. bart.deplancke@epfl.ch. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

  14. High Throughput Determinations of Critical Dosing Parameters (IVIVE workshop)

    Science.gov (United States)

    High throughput toxicokinetics (HTTK) is an approach that allows for rapid estimations of TK for hundreds of environmental chemicals. HTTK-based reverse dosimetry (i.e, reverse toxicokinetics or RTK) is used in order to convert high throughput in vitro toxicity screening (HTS) da...

  15. Mapping RNA Structure In Vitro with SHAPE Chemistry and Next-Generation Sequencing (SHAPE-Seq).

    Science.gov (United States)

    Watters, Kyle E; Lucks, Julius B

    2016-01-01

    Mapping RNA structure with selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) chemistry has proven to be a versatile method for characterizing RNA structure in a variety of contexts. SHAPE reagents covalently modify RNAs in a structure-dependent manner to create adducts at the 2'-OH group of the ribose backbone at nucleotides that are structurally flexible. The positions of these adducts are detected using reverse transcriptase (RT) primer extension, which stops one nucleotide before the modification, to create a pool of cDNAs whose lengths reflect the location of SHAPE modification. Quantification of the cDNA pools is used to estimate the "reactivity" of each nucleotide in an RNA molecule to the SHAPE reagent. High reactivities indicate nucleotides that are structurally flexible, while low reactivities indicate nucleotides that are inflexible. These SHAPE reactivities can then be used to infer RNA structures by restraining RNA structure prediction algorithms. Here, we provide a state-of-the-art protocol describing how to perform in vitro RNA structure probing with SHAPE chemistry using next-generation sequencing to quantify cDNA pools and estimate reactivities (SHAPE-Seq). The use of next-generation sequencing allows for higher throughput, more consistent data analysis, and multiplexing capabilities. The technique described herein, SHAPE-Seq v2.0, uses a universal reverse transcription priming site that is ligated to the RNA after SHAPE modification. The introduced priming site allows for the structural analysis of an RNA independent of its sequence.

  16. High-throughput identification of off-targets for the mechanistic study of severe adverse drug reactions induced by analgesics

    Energy Technology Data Exchange (ETDEWEB)

    Pan, Jian-Bo [Department of Chemical Biology, College of Chemistry and Chemical Engineering, The Key Laboratory for Chemical Biology of Fujian Province, Xiamen University, Xiamen, Fujian 361005 (China); Ji, Nan; Pan, Wen; Hong, Ru [State Key Laboratory of Stress Cell Biology, School of Life Sciences, Xiamen University, Xiamen, Fujian 361102 (China); Wang, Hao [Department of Chemical Biology, College of Chemistry and Chemical Engineering, The Key Laboratory for Chemical Biology of Fujian Province, Xiamen University, Xiamen, Fujian 361005 (China); Ji, Zhi-Liang, E-mail: appo@xmu.edu.cn [State Key Laboratory of Stress Cell Biology, School of Life Sciences, Xiamen University, Xiamen, Fujian 361102 (China); Department of Chemical Biology, College of Chemistry and Chemical Engineering, The Key Laboratory for Chemical Biology of Fujian Province, Xiamen University, Xiamen, Fujian 361005 (China)

    2014-01-01

    Drugs may induce adverse drug reactions (ADRs) when they unexpectedly bind to proteins other than their therapeutic targets. Identification of these undesired protein binding partners, called off-targets, can facilitate toxicity assessment in the early stages of drug development. In this study, a computational framework was introduced for the exploration of idiosyncratic mechanisms underlying analgesic-induced severe adverse drug reactions (SADRs). The putative analgesic-target interactions were predicted by performing reverse docking of analgesics or their active metabolites against human/mammal protein structures in a high-throughput manner. Subsequently, bioinformatics analyses were undertaken to identify ADR-associated proteins (ADRAPs) and pathways. Using the pathways and ADRAPs that this analysis identified, the mechanisms of SADRs such as cardiac disorders were explored. For instance, 53 putative ADRAPs and 24 pathways were linked with cardiac disorders, of which 10 ADRAPs were confirmed by previous experiments. Moreover, it was inferred that pathways such as base excision repair, glycolysis/glyconeogenesis, ErbB signaling, calcium signaling, and phosphatidyl inositol signaling likely play pivotal roles in drug-induced cardiac disorders. In conclusion, our framework offers an opportunity to globally understand SADRs at the molecular level, which has been difficult to realize through experiments. It also provides some valuable clues for drug repurposing. - Highlights: • A novel computational framework was developed for mechanistic study of SADRs. • Off-targets of drugs were identified in large scale and in a high-throughput manner. • SADRs like cardiac disorders were systematically explored in molecular networks. • A number of ADR-associated proteins were identified.

  17. High-throughput identification of off-targets for the mechanistic study of severe adverse drug reactions induced by analgesics

    International Nuclear Information System (INIS)

    Pan, Jian-Bo; Ji, Nan; Pan, Wen; Hong, Ru; Wang, Hao; Ji, Zhi-Liang

    2014-01-01

    Drugs may induce adverse drug reactions (ADRs) when they unexpectedly bind to proteins other than their therapeutic targets. Identification of these undesired protein binding partners, called off-targets, can facilitate toxicity assessment in the early stages of drug development. In this study, a computational framework was introduced for the exploration of idiosyncratic mechanisms underlying analgesic-induced severe adverse drug reactions (SADRs). The putative analgesic-target interactions were predicted by performing reverse docking of analgesics or their active metabolites against human/mammal protein structures in a high-throughput manner. Subsequently, bioinformatics analyses were undertaken to identify ADR-associated proteins (ADRAPs) and pathways. Using the pathways and ADRAPs that this analysis identified, the mechanisms of SADRs such as cardiac disorders were explored. For instance, 53 putative ADRAPs and 24 pathways were linked with cardiac disorders, of which 10 ADRAPs were confirmed by previous experiments. Moreover, it was inferred that pathways such as base excision repair, glycolysis/glyconeogenesis, ErbB signaling, calcium signaling, and phosphatidyl inositol signaling likely play pivotal roles in drug-induced cardiac disorders. In conclusion, our framework offers an opportunity to globally understand SADRs at the molecular level, which has been difficult to realize through experiments. It also provides some valuable clues for drug repurposing. - Highlights: • A novel computational framework was developed for mechanistic study of SADRs. • Off-targets of drugs were identified in large scale and in a high-throughput manner. • SADRs like cardiac disorders were systematically explored in molecular networks. • A number of ADR-associated proteins were identified

  18. miRge - A Multiplexed Method of Processing Small RNA-Seq Data to Determine MicroRNA Entropy.

    Directory of Open Access Journals (Sweden)

    Alexander S Baras

    Full Text Available Small RNA RNA-seq for microRNAs (miRNAs is a rapidly developing field where opportunities still exist to create better bioinformatics tools to process these large datasets and generate new, useful analyses. We built miRge to be a fast, smart small RNA-seq solution to process samples in a highly multiplexed fashion. miRge employs a Bayesian alignment approach, whereby reads are sequentially aligned against customized mature miRNA, hairpin miRNA, noncoding RNA and mRNA sequence libraries. miRNAs are summarized at the level of raw reads in addition to reads per million (RPM. Reads for all other RNA species (tRNA, rRNA, snoRNA, mRNA are provided, which is useful for identifying potential contaminants and optimizing small RNA purification strategies. miRge was designed to optimally identify miRNA isomiRs and employs an entropy based statistical measurement to identify differential production of isomiRs. This allowed us to identify decreasing entropy in isomiRs as stem cells mature into retinal pigment epithelial cells. Conversely, we show that pancreatic tumor miRNAs have similar entropy to matched normal pancreatic tissues. In a head-to-head comparison with other miRNA analysis tools (miRExpress 2.0, sRNAbench, omiRAs, miRDeep2, Chimira, UEA small RNA Workbench, miRge was faster (4 to 32-fold and was among the top-two methods in maximally aligning miRNAs reads per sample. Moreover, miRge has no inherent limits to its multiplexing. miRge was capable of simultaneously analyzing 100 small RNA-Seq samples in 52 minutes, providing an integrated analysis of miRNA expression across all samples. As miRge was designed for analysis of single as well as multiple samples, miRge is an ideal tool for high and low-throughput users. miRge is freely available at http://atlas.pathology.jhu.edu/baras/miRge.html.

  19. Guidance for RNA-seq co-expression network construction and analysis: safety in numbers.

    Science.gov (United States)

    Ballouz, S; Verleyen, W; Gillis, J

    2015-07-01

    RNA-seq co-expression analysis is in its infancy and reasonable practices remain poorly defined. We assessed a variety of RNA-seq expression data to determine factors affecting functional connectivity and topology in co-expression networks. We examine RNA-seq co-expression data generated from 1970 RNA-seq samples using a Guilt-By-Association framework, in which genes are assessed for the tendency of co-expression to reflect shared function. Minimal experimental criteria to obtain performance on par with microarrays were >20 samples with read depth >10 M per sample. While the aggregate network constructed shows good performance (area under the receiver operator characteristic curve ∼0.71), the dependency on number of experiments used is nearly identical to that present in microarrays, suggesting thousands of samples are required to obtain 'gold-standard' co-expression. We find a major topological difference between RNA-seq and microarray co-expression in the form of low overlaps between hub-like genes from each network due to changes in the correlation of expression noise within each technology. jgillis@cshl.edu or sballouz@cshl.edu Networks are available at: http://gillislab.labsites.cshl.edu/supplements/rna-seq-networks/ and supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  20. Automated image alignment for 2D gel electrophoresis in a high-throughput proteomics pipeline.

    Science.gov (United States)

    Dowsey, Andrew W; Dunn, Michael J; Yang, Guang-Zhong

    2008-04-01

    The quest for high-throughput proteomics has revealed a number of challenges in recent years. Whilst substantial improvements in automated protein separation with liquid chromatography and mass spectrometry (LC/MS), aka 'shotgun' proteomics, have been achieved, large-scale open initiatives such as the Human Proteome Organization (HUPO) Brain Proteome Project have shown that maximal proteome coverage is only possible when LC/MS is complemented by 2D gel electrophoresis (2-DE) studies. Moreover, both separation methods require automated alignment and differential analysis to relieve the bioinformatics bottleneck and so make high-throughput protein biomarker discovery a reality. The purpose of this article is to describe a fully automatic image alignment framework for the integration of 2-DE into a high-throughput differential expression proteomics pipeline. The proposed method is based on robust automated image normalization (RAIN) to circumvent the drawbacks of traditional approaches. These use symbolic representation at the very early stages of the analysis, which introduces persistent errors due to inaccuracies in modelling and alignment. In RAIN, a third-order volume-invariant B-spline model is incorporated into a multi-resolution schema to correct for geometric and expression inhomogeneity at multiple scales. The normalized images can then be compared directly in the image domain for quantitative differential analysis. Through evaluation against an existing state-of-the-art method on real and synthetically warped 2D gels, the proposed analysis framework demonstrates substantial improvements in matching accuracy and differential sensitivity. High-throughput analysis is established through an accelerated GPGPU (general purpose computation on graphics cards) implementation. Supplementary material, software and images used in the validation are available at http://www.proteomegrid.org/rain/.

  1. A rapid enzymatic assay for high-throughput screening of adenosine-producing strains

    Science.gov (United States)

    Dong, Huina; Zu, Xin; Zheng, Ping; Zhang, Dawei

    2015-01-01

    Adenosine is a major local regulator of tissue function and industrially useful as precursor for the production of medicinal nucleoside substances. High-throughput screening of adenosine overproducers is important for industrial microorganism breeding. An enzymatic assay of adenosine was developed by combined adenosine deaminase (ADA) with indophenol method. The ADA catalyzes the cleavage of adenosine to inosine and NH3, the latter can be accurately determined by indophenol method. The assay system was optimized to deliver a good performance and could tolerate the addition of inorganic salts and many nutrition components to the assay mixtures. Adenosine could be accurately determined by this assay using 96-well microplates. Spike and recovery tests showed that this assay can accurately and reproducibly determine increases in adenosine in fermentation broth without any pretreatment to remove proteins and potentially interfering low-molecular-weight molecules. This assay was also applied to high-throughput screening for high adenosine-producing strains. The high selectivity and accuracy of the ADA assay provides rapid and high-throughput analysis of adenosine in large numbers of samples. PMID:25580842

  2. A high-throughput, multi-channel photon-counting detector with picosecond timing

    Science.gov (United States)

    Lapington, J. S.; Fraser, G. W.; Miller, G. M.; Ashton, T. J. R.; Jarron, P.; Despeisse, M.; Powolny, F.; Howorth, J.; Milnes, J.

    2009-06-01

    High-throughput photon counting with high time resolution is a niche application area where vacuum tubes can still outperform solid-state devices. Applications in the life sciences utilizing time-resolved spectroscopies, particularly in the growing field of proteomics, will benefit greatly from performance enhancements in event timing and detector throughput. The HiContent project is a collaboration between the University of Leicester Space Research Centre, the Microelectronics Group at CERN, Photek Ltd., and end-users at the Gray Cancer Institute and the University of Manchester. The goal is to develop a detector system specifically designed for optical proteomics, capable of high content (multi-parametric) analysis at high throughput. The HiContent detector system is being developed to exploit this niche market. It combines multi-channel, high time resolution photon counting in a single miniaturized detector system with integrated electronics. The combination of enabling technologies; small pore microchannel plate devices with very high time resolution, and high-speed multi-channel ASIC electronics developed for the LHC at CERN, provides the necessary building blocks for a high-throughput detector system with up to 1024 parallel counting channels and 20 ps time resolution. We describe the detector and electronic design, discuss the current status of the HiContent project and present the results from a 64-channel prototype system. In the absence of an operational detector, we present measurements of the electronics performance using a pulse generator to simulate detector events. Event timing results from the NINO high-speed front-end ASIC captured using a fast digital oscilloscope are compared with data taken with the proposed electronic configuration which uses the multi-channel HPTDC timing ASIC.

  3. A high-throughput, multi-channel photon-counting detector with picosecond timing

    International Nuclear Information System (INIS)

    Lapington, J.S.; Fraser, G.W.; Miller, G.M.; Ashton, T.J.R.; Jarron, P.; Despeisse, M.; Powolny, F.; Howorth, J.; Milnes, J.

    2009-01-01

    High-throughput photon counting with high time resolution is a niche application area where vacuum tubes can still outperform solid-state devices. Applications in the life sciences utilizing time-resolved spectroscopies, particularly in the growing field of proteomics, will benefit greatly from performance enhancements in event timing and detector throughput. The HiContent project is a collaboration between the University of Leicester Space Research Centre, the Microelectronics Group at CERN, Photek Ltd., and end-users at the Gray Cancer Institute and the University of Manchester. The goal is to develop a detector system specifically designed for optical proteomics, capable of high content (multi-parametric) analysis at high throughput. The HiContent detector system is being developed to exploit this niche market. It combines multi-channel, high time resolution photon counting in a single miniaturized detector system with integrated electronics. The combination of enabling technologies; small pore microchannel plate devices with very high time resolution, and high-speed multi-channel ASIC electronics developed for the LHC at CERN, provides the necessary building blocks for a high-throughput detector system with up to 1024 parallel counting channels and 20 ps time resolution. We describe the detector and electronic design, discuss the current status of the HiContent project and present the results from a 64-channel prototype system. In the absence of an operational detector, we present measurements of the electronics performance using a pulse generator to simulate detector events. Event timing results from the NINO high-speed front-end ASIC captured using a fast digital oscilloscope are compared with data taken with the proposed electronic configuration which uses the multi-channel HPTDC timing ASIC.

  4. Development of high-throughput analysis system using highly-functional organic polymer monoliths

    International Nuclear Information System (INIS)

    Umemura, Tomonari; Kojima, Norihisa; Ueki, Yuji

    2008-01-01

    The growing demand for high-throughput analysis in the current competitive life sciences and industries has promoted the development of high-speed HPLC techniques and tools. As one of such tools, monolithic columns have attracted increasing attention and interest in the last decade due to the low flow-resistance and excellent mass transfer, allowing for rapid separations and reactions at high flow rates with minimal loss of column efficiency. Monolithic materials are classified into two main groups: silica- and organic polymer-based monoliths, each with their own advantages and disadvantages. Organic polymer monoliths have several distinct advantages in life-science research, including wide pH stability, less irreversible adsorption, facile preparation and modification. Thus, we have so far tried to develop organic polymer monoliths for various chemical operations, such as separation, extraction, preconcentration, and reaction. In the present paper, recent progress in the development of organic polymer monoliths is discussed. Especially, the procedure for the preparation of methacrylate-based monoliths with various functional groups is described, where the influence of different compositional and processing parameters on the monolithic structure is also addressed. Furthermore, the performance of the produced monoliths is demonstrated through the results for (1) rapid separations of alklybenzenes at high flow rates, (2) flow-through enzymatic digestion of cytochrome c on a trypsin-immobilized monolithic column, and (3) separation of the tryptic digest on a reversed-phase monolithic column. The flexibility and versatility of organic polymer monoliths will be beneficial for further enhancing analytical performance, and will open the way for new applications and opportunities both in scientific and industrial research. (author)

  5. High throughput reaction screening using desorption electrospray ionization mass spectrometry.

    Science.gov (United States)

    Wleklinski, Michael; Loren, Bradley P; Ferreira, Christina R; Jaman, Zinia; Avramova, Larisa; Sobreira, Tiago J P; Thompson, David H; Cooks, R Graham

    2018-02-14

    We report the high throughput analysis of reaction mixture arrays using methods and data handling routines that were originally developed for biological tissue imaging. Desorption electrospray ionization (DESI) mass spectrometry (MS) is applied in a continuous on-line process at rates that approach 10 4 reactions per h at area densities of up to 1 spot per mm 2 (6144 spots per standard microtiter plate) with the sprayer moving at ca. 10 4 microns per s. Data are analyzed automatically by MS using in-house software to create ion images of selected reagents and products as intensity plots in standard array format. Amine alkylation reactions were used to optimize the system performance on PTFE membrane substrates using methanol as the DESI spray/analysis solvent. Reaction times can be screening of processes like N -alkylation and Suzuki coupling reactions as reported herein. Products and by-products were confirmed by on-line MS/MS upon rescanning of the array.

  6. A high-throughput screening system for barley/powdery mildew interactions based on automated analysis of light micrographs.

    Science.gov (United States)

    Ihlow, Alexander; Schweizer, Patrick; Seiffert, Udo

    2008-01-23

    To find candidate genes that potentially influence the susceptibility or resistance of crop plants to powdery mildew fungi, an assay system based on transient-induced gene silencing (TIGS) as well as transient over-expression in single epidermal cells of barley has been developed. However, this system relies on quantitative microscopic analysis of the barley/powdery mildew interaction and will only become a high-throughput tool of phenomics upon automation of the most time-consuming steps. We have developed a high-throughput screening system based on a motorized microscope which evaluates the specimens fully automatically. A large-scale double-blind verification of the system showed an excellent agreement of manual and automated analysis and proved the system to work dependably. Furthermore, in a series of bombardment experiments an RNAi construct targeting the Mlo gene was included, which is expected to phenocopy resistance mediated by recessive loss-of-function alleles such as mlo5. In most cases, the automated analysis system recorded a shift towards resistance upon RNAi of Mlo, thus providing proof of concept for its usefulness in detecting gene-target effects. Besides saving labor and enabling a screening of thousands of candidate genes, this system offers continuous operation of expensive laboratory equipment and provides a less subjective analysis as well as a complete and enduring documentation of the experimental raw data in terms of digital images. In general, it proves the concept of enabling available microscope hardware to handle challenging screening tasks fully automatically.

  7. High-throughput screening using the differential radial capillary action of ligand assay identifies ebselen as an inhibitor of diguanylate cyclases.

    Science.gov (United States)

    Lieberman, Ori J; Orr, Mona W; Wang, Yan; Lee, Vincent T

    2014-01-17

    The rise of bacterial resistance to traditional antibiotics has motivated recent efforts to identify new drug candidates that target virulence factors or their regulatory pathways. One such antivirulence target is the cyclic-di-GMP (cdiGMP) signaling pathway, which regulates biofilm formation, motility, and pathogenesis. Pseudomonas aeruginosa is an important opportunistic pathogen that utilizes cdiGMP-regulated polysaccharides, including alginate and pellicle polysaccharide (PEL), to mediate virulence and antibiotic resistance. CdiGMP activates PEL and alginate biosynthesis by binding to specific receptors including PelD and Alg44. Mutations that abrogate cdiGMP binding to these receptors prevent polysaccharide production. Identification of small molecules that can inhibit cdiGMP binding to the allosteric sites on these proteins could mimic binding defective mutants and potentially reduce biofilm formation or alginate secretion. Here, we report the development of a rapid and quantitative high-throughput screen for inhibitors of protein-cdiGMP interactions based on the differential radial capillary action of ligand assay (DRaCALA). Using this approach, we identified ebselen as an inhibitor of cdiGMP binding to receptors containing an RxxD domain including PelD and diguanylate cyclases (DGC). Ebselen reduces diguanylate cyclase activity by covalently modifying cysteine residues. Ebselen oxide, the selenone analogue of ebselen, also inhibits cdiGMP binding through the same covalent mechanism. Ebselen and ebselen oxide inhibit cdiGMP regulation of biofilm formation and flagella-mediated motility in P. aeruginosa through inhibition of diguanylate cyclases. The identification of ebselen provides a proof-of-principle that a DRaCALA high-throughput screening approach can be used to identify bioactive agents that reverse regulation of cdiGMP signaling by targeting cdiGMP-binding domains.

  8. High-throughput bioscreening system utilizing high-performance affinity magnetic carriers exhibiting minimal non-specific protein binding

    International Nuclear Information System (INIS)

    Hanyu, Naohiro; Nishio, Kosuke; Hatakeyama, Mamoru; Yasuno, Hiroshi; Tanaka, Toshiyuki; Tada, Masaru; Nakagawa, Takashi; Sandhu, Adarsh; Abe, Masanori; Handa, Hiroshi

    2009-01-01

    For affinity purification of drug target protein we have developed magnetic carriers, narrow in size distribution (184±9 nm), which exhibit minimal non-specific binding of unwanted proteins. The carriers were highly dispersed in aqueous solutions and highly resistant to organic solvents, which enabled immobilization of various hydrophobic chemicals as probes on the carrier surfaces. Utilizing the carriers we have automated the process of separation and purification of the target proteins that had been done by manual operation previously.

  9. Diverse modes of binding in structures of Leishmania majorN-myristoyltransferase with selective inhibitors

    Directory of Open Access Journals (Sweden)

    James A. Brannigan

    2014-07-01

    Full Text Available The leishmaniases are a spectrum of global diseases of poverty associated with immune dysfunction and are the cause of high morbidity. Despite the long history of these diseases, no effective vaccine is available and the currently used drugs are variously compromised by moderate efficacy, complex side effects and the emergence of resistance. It is therefore widely accepted that new therapies are needed. N-Myristoyltransferase (NMT has been validated pre-clinically as a target for the treatment of fungal and parasitic infections. In a previously reported high-throughput screening program, a number of hit compounds with activity against NMT from Leishmania donovani have been identified. Here, high-resolution crystal structures of representative compounds from four hit series in ternary complexes with myristoyl-CoA and NMT from the closely related L. major are reported. The structures reveal that the inhibitors associate with the peptide-binding groove at a site adjacent to the bound myristoyl-CoA and the catalytic α-carboxylate of Leu421. Each inhibitor makes extensive apolar contacts as well as a small number of polar contacts with the protein. Remarkably, the compounds exploit different features of the peptide-binding groove and collectively occupy a substantial volume of this pocket, suggesting that there is potential for the design of chimaeric inhibitors with significantly enhanced binding. Despite the high conservation of the active sites of the parasite and human NMTs, the inhibitors act selectively over the host enzyme. The role of conformational flexibility in the side chain of Tyr217 in conferring selectivity is discussed.

  10. High-throughput screening (HTS) and modeling of the retinoid ...

    Science.gov (United States)

    Presentation at the Retinoids Review 2nd workshop in Brussels, Belgium on the application of high throughput screening and model to the retinoid system Presentation at the Retinoids Review 2nd workshop in Brussels, Belgium on the application of high throughput screening and model to the retinoid system

  11. Spatially conserved regulatory elements identified within human and mouse Cd247 gene using high-throughput sequencing data from the ENCODE project

    DEFF Research Database (Denmark)

    Pundhir, Sachin; Hannibal, Tine Dahlbæk; Bang-Berthelsen, Claus Heiner

    2014-01-01

    . In this study, we have utilized the wealth of high-throughput sequencing data produced during the Encyclopedia of DNA Elements (ENCODE) project to identify spatially conserved regulatory elements within the Cd247 gene from human and mouse. We show the presence of two transcription factor binding sites...

  12. A recombinant fusion protein-based, fluorescent protease assay for high throughput-compatible substrate screening.

    Science.gov (United States)

    Bozóki, Beáta; Gazda, Lívia; Tóth, Ferenc; Miczi, Márió; Mótyán, János András; Tőzsér, József

    2018-01-01

    In connection with the intensive investigation of proteases, several methods have been developed for analysis of the substrate specificity. Due to the great number of proteases and the expected target molecules to be analyzed, time- and cost-efficient high-throughput screening (HTS) methods are preferred. Here we describe the development and application of a separation-based HTS-compatible fluorescent protease assay, which is based on the use of recombinant fusion proteins as substrates of proteases. The protein substrates used in this assay consists of N-terminal (hexahistidine and maltose binding protein) fusion tags, cleavage sequences of the tobacco etch virus (TEV) and HIV-1 proteases, and a C-terminal fluorescent protein (mApple or mTurquoise2). The assay is based on the fluorimetric detection of the fluorescent proteins, which are released from the magnetic bead-attached substrates by the proteolytic cleavage. The protease assay has been applied for activity measurements of TEV and HIV-1 proteases to test the suitability of the system for enzyme kinetic measurements, inhibition studies, and determination of pH optimum. We also found that denatured fluorescent proteins can be renatured after SDS-PAGE of denaturing conditions, but showed differences in their renaturation abilities. After in-gel renaturation both substrates and cleavage products can be identified by in-gel UV detection. Copyright © 2017 Elsevier Inc. All rights reserved.

  13. Using ALFA for high throughput, distributed data transmission in the ALICE O2 system

    Science.gov (United States)

    Wegrzynek, A.; ALICE Collaboration

    2017-10-01

    ALICE (A Large Ion Collider Experiment) is a heavy-ion detector designed to study the physics of strongly interacting matter (the Quark-Gluon Plasma at the CERN LHC (Large Hadron Collider). ALICE has been successfully collecting physics data in Run 2 since spring 2015. In parallel, preparations for a major upgrade of the computing system, called O2 (Online-Offline), scheduled for the Long Shutdown 2 in 2019-2020, are being made. One of the major requirements of the system is the capacity to transport data between so-called FLPs (First Level Processors), equipped with readout cards, and the EPNs (Event Processing Node), performing data aggregation, frame building and partial reconstruction. It is foreseen to have 268 FLPs dispatching data to 1500 EPNs with an average output of 20 Gb/s each. In overall, the O2 processing system will operate at terabits per second of throughput while handling millions of concurrent connections. The ALFA framework will standardize and handle software related tasks such as readout, data transport, frame building, calibration, online reconstruction and more in the upgraded computing system. ALFA supports two data transport libraries: ZeroMQ and nanomsg. This paper discusses the efficiency of ALFA in terms of high throughput data transport. The tests were performed with multiple FLPs pushing data to multiple EPNs. The transfer was done using push-pull communication patterns and two socket configurations: bind, connect. The set of benchmarks was prepared to get the most performant results on each hardware setup. The paper presents the measurement process and final results - data throughput combined with computing resources usage as a function of block size. The high number of nodes and connections in the final set up may cause race conditions that can lead to uneven load balancing and poor scalability. The performed tests allow us to validate whether the traffic is distributed evenly over all receivers. It also measures the behaviour of

  14. Multiplex enrichment quantitative PCR (ME-qPCR): a high-throughput, highly sensitive detection method for GMO identification.

    Science.gov (United States)

    Fu, Wei; Zhu, Pengyu; Wei, Shuang; Zhixin, Du; Wang, Chenguang; Wu, Xiyang; Li, Feiwu; Zhu, Shuifang

    2017-04-01

    Among all of the high-throughput detection methods, PCR-based methodologies are regarded as the most cost-efficient and feasible methodologies compared with the next-generation sequencing or ChIP-based methods. However, the PCR-based methods can only achieve multiplex detection up to 15-plex due to limitations imposed by the multiplex primer interactions. The detection throughput cannot meet the demands of high-throughput detection, such as SNP or gene expression analysis. Therefore, in our study, we have developed a new high-throughput PCR-based detection method, multiplex enrichment quantitative PCR (ME-qPCR), which is a combination of qPCR and nested PCR. The GMO content detection results in our study showed that ME-qPCR could achieve high-throughput detection up to 26-plex. Compared to the original qPCR, the Ct values of ME-qPCR were lower for the same group, which showed that ME-qPCR sensitivity is higher than the original qPCR. The absolute limit of detection for ME-qPCR could achieve levels as low as a single copy of the plant genome. Moreover, the specificity results showed that no cross-amplification occurred for irrelevant GMO events. After evaluation of all of the parameters, a practical evaluation was performed with different foods. The more stable amplification results, compared to qPCR, showed that ME-qPCR was suitable for GMO detection in foods. In conclusion, ME-qPCR achieved sensitive, high-throughput GMO detection in complex substrates, such as crops or food samples. In the future, ME-qPCR-based GMO content identification may positively impact SNP analysis or multiplex gene expression of food or agricultural samples. Graphical abstract For the first-step amplification, four primers (A, B, C, and D) have been added into the reaction volume. In this manner, four kinds of amplicons have been generated. All of these four amplicons could be regarded as the target of second-step PCR. For the second-step amplification, three parallels have been taken for

  15. High-throughput sequencing and copy number variation detection using formalin fixed embedded tissue in metastatic gastric cancer.

    Directory of Open Access Journals (Sweden)

    Seokhwi Kim

    Full Text Available In the era of targeted therapy, mutation profiling of cancer is a crucial aspect of making therapeutic decisions. To characterize cancer at a molecular level, the use of formalin-fixed paraffin-embedded tissue is important. We tested the Ion AmpliSeq Cancer Hotspot Panel v2 and nCounter Copy Number Variation Assay in 89 formalin-fixed paraffin-embedded gastric cancer samples to determine whether they are applicable in archival clinical samples for personalized targeted therapies. We validated the results with Sanger sequencing, real-time quantitative PCR, fluorescence in situ hybridization and immunohistochemistry. Frequently detected somatic mutations included TP53 (28.17%, APC (10.1%, PIK3CA (5.6%, KRAS (4.5%, SMO (3.4%, STK11 (3.4%, CDKN2A (3.4% and SMAD4 (3.4%. Amplifications of HER2, CCNE1, MYC, KRAS and EGFR genes were observed in 8 (8.9%, 4 (4.5%, 2 (2.2%, 1 (1.1% and 1 (1.1% cases, respectively. In the cases with amplification, fluorescence in situ hybridization for HER2 verified gene amplification and immunohistochemistry for HER2, EGFR and CCNE1 verified the overexpression of proteins in tumor cells. In conclusion, we successfully performed semiconductor-based sequencing and nCounter copy number variation analyses in formalin-fixed paraffin-embedded gastric cancer samples. High-throughput screening in archival clinical samples enables faster, more accurate and cost-effective detection of hotspot mutations or amplification in genes.

  16. Development of rapid high throughput biodosimetry tools for radiological triage

    International Nuclear Information System (INIS)

    Balajee, Adayabalam S.; Escalona, Maria; Smith, Tammy; Ryan, Terri; Dainiak, Nicholas

    2018-01-01

    Accidental or intentional radiological or nuclear (R/N) disasters constitute a major threat around the globe that can affect several tens, hundreds and thousands of humans. Currently available cytogenetic biodosimeters are time consuming and laborious to perform making them impractical for triage scenarios. Therefore, it is imperative to develop high throughput techniques which will enable timely assessment of personalized dose for making an appropriate 'life-saving' clinical decision

  17. Evaluation of logistic regression models and effect of covariates for case-control study in RNA-Seq analysis.

    Science.gov (United States)

    Choi, Seung Hoan; Labadorf, Adam T; Myers, Richard H; Lunetta, Kathryn L; Dupuis, Josée; DeStefano, Anita L

    2017-02-06

    Next generation sequencing provides a count of RNA molecules in the form of short reads, yielding discrete, often highly non-normally distributed gene expression measurements. Although Negative Binomial (NB) regression has been generally accepted in the analysis of RNA sequencing (RNA-Seq) data, its appropriateness has not been exhaustively evaluated. We explore logistic regression as an alternative method for RNA-Seq studies designed to compare cases and controls, where disease status is modeled as a function of RNA-Seq reads using simulated and Huntington disease data. We evaluate the effect of adjusting for covariates that have an unknown relationship with gene expression. Finally, we incorporate the data adaptive method in order to compare false positive rates. When the sample size is small or the expression levels of a gene are highly dispersed, the NB regression shows inflated Type-I error rates but the Classical logistic and Bayes logistic (BL) regressions are conservative. Firth's logistic (FL) regression performs well or is slightly conservative. Large sample size and low dispersion generally make Type-I error rates of all methods close to nominal alpha levels of 0.05 and 0.01. However, Type-I error rates are controlled after applying the data adaptive method. The NB, BL, and FL regressions gain increased power with large sample size, large log2 fold-change, and low dispersion. The FL regression has comparable power to NB regression. We conclude that implementing the data adaptive method appropriately controls Type-I error rates in RNA-Seq analysis. Firth's logistic regression provides a concise statistical inference process and reduces spurious associations from inaccurately estimated dispersion parameters in the negative binomial framework.

  18. High-Throughput Tabular Data Processor - Platform independent graphical tool for processing large data sets.

    Science.gov (United States)

    Madanecki, Piotr; Bałut, Magdalena; Buckley, Patrick G; Ochocka, J Renata; Bartoszewski, Rafał; Crossman, David K; Messiaen, Ludwine M; Piotrowski, Arkadiusz

    2018-01-01

    High-throughput technologies generate considerable amount of data which often requires bioinformatic expertise to analyze. Here we present High-Throughput Tabular Data Processor (HTDP), a platform independent Java program. HTDP works on any character-delimited column data (e.g. BED, GFF, GTF, PSL, WIG, VCF) from multiple text files and supports merging, filtering and converting of data that is produced in the course of high-throughput experiments. HTDP can also utilize itemized sets of conditions from external files for complex or repetitive filtering/merging tasks. The program is intended to aid global, real-time processing of large data sets using a graphical user interface (GUI). Therefore, no prior expertise in programming, regular expression, or command line usage is required of the user. Additionally, no a priori assumptions are imposed on the internal file composition. We demonstrate the flexibility and potential of HTDP in real-life research tasks including microarray and massively parallel sequencing, i.e. identification of disease predisposing variants in the next generation sequencing data as well as comprehensive concurrent analysis of microarray and sequencing results. We also show the utility of HTDP in technical tasks including data merge, reduction and filtering with external criteria files. HTDP was developed to address functionality that is missing or rudimentary in other GUI software for processing character-delimited column data from high-throughput technologies. Flexibility, in terms of input file handling, provides long term potential functionality in high-throughput analysis pipelines, as the program is not limited by the currently existing applications and data formats. HTDP is available as the Open Source software (https://github.com/pmadanecki/htdp).

  19. Polymerase chain reaction-hybridization method using urease gene sequences for high-throughput Ureaplasma urealyticum and Ureaplasma parvum detection and differentiation.

    Science.gov (United States)

    Xu, Chen; Zhang, Nan; Huo, Qianyu; Chen, Minghui; Wang, Rengfeng; Liu, Zhili; Li, Xue; Liu, Yunde; Bao, Huijing

    2016-04-15

    In this article, we discuss the polymerase chain reaction (PCR)-hybridization assay that we developed for high-throughput simultaneous detection and differentiation of Ureaplasma urealyticum and Ureaplasma parvum using one set of primers and two specific DNA probes based on urease gene nucleotide sequence differences. First, U. urealyticum and U. parvum DNA samples were specifically amplified using one set of biotin-labeled primers. Furthermore, amine-modified DNA probes, which can specifically react with U. urealyticum or U. parvum DNA, were covalently immobilized to a DNA-BIND plate surface. The plate was then incubated with the PCR products to facilitate sequence-specific DNA binding. Horseradish peroxidase-streptavidin conjugation and a colorimetric assay were used. Based on the results, the PCR-hybridization assay we developed can specifically differentiate U. urealyticum and U. parvum with high sensitivity (95%) compared with cultivation (72.5%). Hence, this study demonstrates a new method for high-throughput simultaneous differentiation and detection of U. urealyticum and U. parvum with high sensitivity. Based on these observations, the PCR-hybridization assay developed in this study is ideal for detecting and discriminating U. urealyticum and U. parvum in clinical applications. Copyright © 2016 Elsevier Inc. All rights reserved.

  20. Fast and Efficient Fragment-Based Lead Generation by Fully Automated Processing and Analysis of Ligand-Observed NMR Binding Data.

    Science.gov (United States)

    Peng, Chen; Frommlet, Alexandra; Perez, Manuel; Cobas, Carlos; Blechschmidt, Anke; Dominguez, Santiago; Lingel, Andreas

    2016-04-14

    NMR binding assays are routinely applied in hit finding and validation during early stages of drug discovery, particularly for fragment-based lead generation. To this end, compound libraries are screened by ligand-observed NMR experiments such as STD, T1ρ, and CPMG to identify molecules interacting with a target. The analysis of a high number of complex spectra is performed largely manually and therefore represents a limiting step in hit generation campaigns. Here we report a novel integrated computational procedure that processes and analyzes ligand-observed proton and fluorine NMR binding data in a fully automated fashion. A performance evaluation comparing automated and manual analysis results on (19)F- and (1)H-detected data sets shows that the program delivers robust, high-confidence hit lists in a fraction of the time needed for manual analysis and greatly facilitates visual inspection of the associated NMR spectra. These features enable considerably higher throughput, the assessment of larger libraries, and shorter turn-around times.

  1. Creation of a small high-throughput screening facility.

    Science.gov (United States)

    Flak, Tod

    2009-01-01

    The creation of a high-throughput screening facility within an organization is a difficult task, requiring a substantial investment of time, money, and organizational effort. Major issues to consider include the selection of equipment, the establishment of data analysis methodologies, and the formation of a group having the necessary competencies. If done properly, it is possible to build a screening system in incremental steps, adding new pieces of equipment and data analysis modules as the need grows. Based upon our experience with the creation of a small screening service, we present some guidelines to consider in planning a screening facility.

  2. High-throughput screening of metal-porphyrin-like graphenes for selective capture of carbon dioxide.

    Science.gov (United States)

    Bae, Hyeonhu; Park, Minwoo; Jang, Byungryul; Kang, Yura; Park, Jinwoo; Lee, Hosik; Chung, Haegeun; Chung, ChiHye; Hong, Suklyun; Kwon, Yongkyung; Yakobson, Boris I; Lee, Hoonkyung

    2016-02-23

    Nanostructured materials, such as zeolites and metal-organic frameworks, have been considered to capture CO2. However, their application has been limited largely because they exhibit poor selectivity for flue gases and low capture capacity under low pressures. We perform a high-throughput screening for selective CO2 capture from flue gases by using first principles thermodynamics. We find that elements with empty d orbitals selectively attract CO2 from gaseous mixtures under low CO2 pressures (~10(-3) bar) at 300 K and release it at ~450 K. CO2 binding to elements involves hybridization of the metal d orbitals with the CO2 π orbitals and CO2-transition metal complexes were observed in experiments. This result allows us to perform high-throughput screening to discover novel promising CO2 capture materials with empty d orbitals (e.g., Sc- or V-porphyrin-like graphene) and predict their capture performance under various conditions. Moreover, these findings provide physical insights into selective CO2 capture and open a new path to explore CO2 capture materials.

  3. High-throughput screening of metal-porphyrin-like graphenes for selective capture of carbon dioxide

    Science.gov (United States)

    Bae, Hyeonhu; Park, Minwoo; Jang, Byungryul; Kang, Yura; Park, Jinwoo; Lee, Hosik; Chung, Haegeun; Chung, Chihye; Hong, Suklyun; Kwon, Yongkyung; Yakobson, Boris I.; Lee, Hoonkyung

    2016-02-01

    Nanostructured materials, such as zeolites and metal-organic frameworks, have been considered to capture CO2. However, their application has been limited largely because they exhibit poor selectivity for flue gases and low capture capacity under low pressures. We perform a high-throughput screening for selective CO2 capture from flue gases by using first principles thermodynamics. We find that elements with empty d orbitals selectively attract CO2 from gaseous mixtures under low CO2 pressures (~10-3 bar) at 300 K and release it at ~450 K. CO2 binding to elements involves hybridization of the metal d orbitals with the CO2 π orbitals and CO2-transition metal complexes were observed in experiments. This result allows us to perform high-throughput screening to discover novel promising CO2 capture materials with empty d orbitals (e.g., Sc- or V-porphyrin-like graphene) and predict their capture performance under various conditions. Moreover, these findings provide physical insights into selective CO2 capture and open a new path to explore CO2 capture materials.

  4. Nascent-Seq reveals novel features of mouse circadian transcriptional regulation

    Science.gov (United States)

    Menet, Jerome S; Rodriguez, Joseph; Abruzzi, Katharine C; Rosbash, Michael

    2012-01-01

    A substantial fraction of the metazoan transcriptome undergoes circadian oscillations in many cells and tissues. Based on the transcription feedback loops important for circadian timekeeping, it is commonly assumed that this mRNA cycling reflects widespread transcriptional regulation. To address this issue, we directly measured the circadian dynamics of mouse liver transcription using Nascent-Seq (genome-wide sequencing of nascent RNA). Although many genes are rhythmically transcribed, many rhythmic mRNAs manifest poor transcriptional rhythms, indicating a prominent contribution of post-transcriptional regulation to circadian mRNA expression. This analysis of rhythmic transcription also showed that the rhythmic DNA binding profile of the transcription factors CLOCK and BMAL1 does not determine the transcriptional phase of most target genes. This likely reflects gene-specific collaborations of CLK:BMAL1 with other transcription factors. These insights from Nascent-Seq indicate that it should have broad applicability to many other gene expression regulatory issues. DOI: http://dx.doi.org/10.7554/eLife.00011.001 PMID:23150795

  5. A High Throughput, 384-Well, Semi-Automated, Hepatocyte Intrinsic Clearance Assay for Screening New Molecular Entities in Drug Discovery.

    Science.gov (United States)

    Heinle, Lance; Peterkin, Vincent; de Morais, Sonia M; Jenkins, Gary J; Badagnani, Ilaria

    2015-01-01

    A high throughput, semi-automated clearance screening assay in hepatocytes was developed allowing a scientist to generate data for 96 compounds in one week. The 384-well format assay utilizes a Thermo Multidrop Combi and an optimized LC-MS/MS method. The previously reported LCMS/ MS method reduced the analytical run time by 3-fold, down to 1.2 min injection-to-injection. The Multidrop was able to deliver hepatocytes to 384-well plates with minimal viability loss. Comparison of results from the new 384-well and historical 24-well assays yielded a correlation of 0.95. In addition, results obtained for 25 marketed drugs with various metabolism pathways had a correlation of 0.75 when compared with literature values. Precision was maintained in the new format as 8 compounds tested in ≥39 independent experiments had coefficients of variation ≤21%. The ability to predict in vivo clearances using the new stability assay format was also investigated using 22 marketed drugs and 26 AbbVie compounds. Correction of intrinsic clearance values with binding to hepatocytes (in vitro data) and plasma (in vivo data) resulted in a higher in vitro to in vivo correlation when comparing 22 marketed compounds in human (0.80 vs 0.35) and 26 AbbVie Discovery compounds in rat (0.56 vs 0.17), demonstrating the importance of correcting for binding in clearance studies. This newly developed high throughput, semi-automated clearance assay allows for rapid screening of Discovery compounds to enable Structure Activity Relationship (SAR) analysis based on high quality hepatocyte stability data in sufficient quantity and quality to drive the next round of compound synthesis.

  6. Hydrogel Based 3-Dimensional (3D) System for Toxicity and High-Throughput (HTP) Analysis for Cultured Murine Ovarian Follicles

    Science.gov (United States)

    Zhou, Hong; Malik, Malika Amattullah; Arab, Aarthi; Hill, Matthew Thomas; Shikanov, Ariella

    2015-01-01

    Various toxicants, drugs and their metabolites carry potential ovarian toxicity. Ovarian follicles, the functional unit of the ovary, are susceptible to this type of damage at all stages of their development. However, despite of the large scale of potential negative impacts, assays that study ovarian toxicity are limited. Exposure of cultured ovarian follicles to toxicants of interest served as an important tool for evaluation of toxic effects for decades. Mouse follicles cultured on the bottom of a culture dish continue to serve an important approach for mechanistic studies. In this paper, we demonstrated the usefulness of a hydrogel based 3-dimensional (3D) mouse ovarian follicle culture as a tool to study ovarian toxicity in a different setup. The 3D in vitro culture, based on fibrin alginate interpenetrating network (FA-IPN), preserves the architecture of the ovarian follicle and physiological structure-function relationship. We applied the novel 3D high-throughput (HTP) in vitro ovarian follicle culture system to study the ovotoxic effects of an anti-cancer drug, Doxorobucin (DXR). The fibrin component in the system is degraded by plasmin and appears as a clear circle around the encapsulated follicle. The degradation area of the follicle is strongly correlated with follicle survival and growth. To analyze fibrin degradation in a high throughput manner, we created a custom MATLAB® code that converts brightfield micrographs of follicles encapsulated in FA-IPN to binary images, followed by image analysis. We did not observe any significant difference between manually processed images to the automated MATLAB® method, thereby confirming that the automated program is suitable to measure fibrin degradation to evaluate follicle health. The cultured follicles were treated with DXR at concentrations ranging from 0.005 nM to 200 nM, corresponding to the therapeutic plasma levels of DXR in patients. Follicles treated with DXR demonstrated decreased survival rate in

  7. Hydrogel Based 3-Dimensional (3D System for Toxicity and High-Throughput (HTP Analysis for Cultured Murine Ovarian Follicles.

    Directory of Open Access Journals (Sweden)

    Hong Zhou

    Full Text Available Various toxicants, drugs and their metabolites carry potential ovarian toxicity. Ovarian follicles, the functional unit of the ovary, are susceptible to this type of damage at all stages of their development. However, despite of the large scale of potential negative impacts, assays that study ovarian toxicity are limited. Exposure of cultured ovarian follicles to toxicants of interest served as an important tool for evaluation of toxic effects for decades. Mouse follicles cultured on the bottom of a culture dish continue to serve an important approach for mechanistic studies. In this paper, we demonstrated the usefulness of a hydrogel based 3-dimensional (3D mouse ovarian follicle culture as a tool to study ovarian toxicity in a different setup. The 3D in vitro culture, based on fibrin alginate interpenetrating network (FA-IPN, preserves the architecture of the ovarian follicle and physiological structure-function relationship. We applied the novel 3D high-throughput (HTP in vitro ovarian follicle culture system to study the ovotoxic effects of an anti-cancer drug, Doxorobucin (DXR. The fibrin component in the system is degraded by plasmin and appears as a clear circle around the encapsulated follicle. The degradation area of the follicle is strongly correlated with follicle survival and growth. To analyze fibrin degradation in a high throughput manner, we created a custom MATLAB® code that converts brightfield micrographs of follicles encapsulated in FA-IPN to binary images, followed by image analysis. We did not observe any significant difference between manually processed images to the automated MATLAB® method, thereby confirming that the automated program is suitable to measure fibrin degradation to evaluate follicle health. The cultured follicles were treated with DXR at concentrations ranging from 0.005 nM to 200 nM, corresponding to the therapeutic plasma levels of DXR in patients. Follicles treated with DXR demonstrated decreased

  8. Characterization of relative abundance of lactic acid bacteria species in French organic sourdough by cultural, qPCR and MiSeq high-throughput sequencing methods.

    Science.gov (United States)

    Michel, Elisa; Monfort, Clarisse; Deffrasnes, Marion; Guezenec, Stéphane; Lhomme, Emilie; Barret, Matthieu; Sicard, Delphine; Dousset, Xavier; Onno, Bernard

    2016-12-19

    In order to contribute to the description of sourdough LAB composition, MiSeq sequencing and qPCR methods were performed in association with cultural methods. A panel of 16 French organic bakers and farmer-bakers were selected for this work. The lactic acid bacteria (LAB) diversity of their organic sourdoughs was investigated quantitatively and qualitatively combining (i) Lactobacillus sanfranciscensis-specific qPCR, (ii) global sequencing with MiSeq Illumina technology and (iii) molecular isolates identification. In addition, LAB and yeast enumeration, pH, Total Titratable Acidity, organic acids and bread specific volume were analyzed. Microbial and physico-chemical data were statistically treated by Principal Component Analysis (PCA) and Hierarchical Ascendant Classification (HAC). Total yeast counts were 6 log 10 to 7.6 log 10 CFU/g while LAB counts varied from 7.2 log 10 to 9.6 log 10 CFU/g. Values obtained by L. sanfranciscensis-specific qPCR were estimated between 7.2 and 10.3 log 10 CFU/g, except for one sample at 4.4 log 10 CFU/g. HAC and PCA clustered the sixteen sourdoughs into three classes described by their variables but without links to bakers' practices. L. sanfranciscensis was the dominant species in 13 of the 16 sourdoughs analyzed by Next Generation Sequencing (NGS), by the culture dependent method this species was dominant only in only 10 samples. Based on isolates identification, LAB diversity was higher for 7 sourdoughs with the recovery of L. curvatus, L. brevis, L. heilongjiangensis, L. xiangfangensis, L. koreensis, L. pontis, Weissella sp. and Pediococcus pentosaceus, as the most representative species. L. koreensis, L. heilongjiangensis and L. xiangfangensis were identified in traditional Asian food and here for the first time as dominant in organic sourdough. This study highlighted that L. sanfranciscensis was not the major species in 6/16 sourdough samples and that a relatively high LAB diversity can be observed in French organic

  9. High-throughput tandem mass spectrometry multiplex analysis for newborn urinary screening of creatine synthesis and transport disorders, Triple H syndrome and OTC deficiency.

    Science.gov (United States)

    Auray-Blais, Christiane; Maranda, Bruno; Lavoie, Pamela

    2014-09-25

    Creatine synthesis and transport disorders, Triple H syndrome and ornithine transcarbamylase deficiency are treatable inborn errors of metabolism. Early screening of patients was found to be beneficial. Mass spectrometry analysis of specific urinary biomarkers might lead to early detection and treatment in the neonatal period. We developed a high-throughput mass spectrometry methodology applicable to newborn screening using dried urine on filter paper for these aforementioned diseases. A high-throughput methodology was devised for the simultaneous analysis of creatine, guanidineacetic acid, orotic acid, uracil, creatinine and respective internal standards, using both positive and negative electrospray ionization modes, depending on the compound. The precision and accuracy varied by screening for inherited disorders by biochemical laboratories. Copyright © 2014 Elsevier B.V. All rights reserved.

  10. Sensitivity of the ViroSeq HIV-1 Genotyping System for Detection of the K103N Resistance Mutation in HIV-1 Subtypes A, C, and D

    Science.gov (United States)

    Church, Jessica D.; Jones, Dana; Flys, Tamara; Hoover, Donald; Marlowe, Natalia; Chen, Shu; Shi, Chanjuan; Eshleman, James R.; Guay, Laura A.; Jackson, J. Brooks; Kumwenda, Newton; Taha, Taha E.; Eshleman, Susan H.

    2006-01-01

    The US Food and Drug Administration-cleared ViroSeq HIV-1 Genotyping System (ViroSeq) and other population sequencing-based human immunodeficiency virus type 1 (HIV-1) genotyping methods detect antiretroviral drug resistance mutations present in the major viral population of a test sample. These assays also detect some mutations in viral variants that are present as mixtures. We compared detection of the K103N nevirapine resistance mutation using ViroSeq and a sensitive, quantitative point mutation assay, LigAmp. The LigAmp assay measured the percentage of K103N-containing variants in the viral population (percentage of K103N). We analyzed 305 samples with HIV-1 subtypes A, C, and D collected from African women after nevirapine administration. ViroSeq detected K103N in 100% of samples with >20% K103N, 77.8% of samples with 10 to 20% K103N, 71.4% of samples with 5 to 10% K103N, and 16.9% of samples with 1 to 5% K103N. The sensitivity of ViroSeq for detection of K103N was similar for subtypes A, C, and D. These data indicate that the ViroSeq system reliably detects the K103N mutation at levels above 20% and frequently detects the mutation at lower levels. Further studies are needed to compare the sensitivity of different assays for detection of HIV-1 drug resistance mutations and to determine the clinical relevance of HIV-1 minority variants. PMID:16931582

  11. A protein that binds to the P1 origin core and the oriC 13mer region in a methylation-specific fashion is the product of the host seqA gene.

    Science.gov (United States)

    Brendler, T; Abeles, A; Austin, S

    1995-08-15

    The P1 plasmid replication origin P1oriR is controlled by methylation of four GATC adenine methylation sites within heptamer repeats. A comparable (13mer) region is present in the host origin, oriC. The two origins show comparable responses to methylation; negative control by recognition of hemimethylated DNA (sequestration) and a positive requirement for methylation for efficient function. We have isolated a host protein that recognizes the P1 origin region only when it is isolated from a strain proficient for adenine methylation. The substantially purified 22 kDa protein also binds to the 13mer region of oriC in a methylation-specific fashion. It proved to be the product of the seqA gene that acts in the negative control of oriC by sequestration. We conclude that the role of the SeqA protein in sequestration is to recognize the methylation state of P1oriR and oriC by direct DNA binding. Using synthetic substrates we show that SeqA binds exclusively to the hemimethylated forms of these origins forms that are the immediate products of replication in a methylation-proficient strain. We also show that the protein can recognize sequences with multiple GATC sites, irrespective of the surrounding sequence. The basis for origin specificity is primarily the persistence of hemimethylated forms that are over-represented in the natural. DNA preparations relative to controls.

  12. High Resolution Melting (HRM for High-Throughput Genotyping—Limitations and Caveats in Practical Case Studies

    Directory of Open Access Journals (Sweden)

    Marcin Słomka

    2017-11-01

    Full Text Available High resolution melting (HRM is a convenient method for gene scanning as well as genotyping of individual and multiple single nucleotide polymorphisms (SNPs. This rapid, simple, closed-tube, homogenous, and cost-efficient approach has the capacity for high specificity and sensitivity, while allowing easy transition to high-throughput scale. In this paper, we provide examples from our laboratory practice of some problematic issues which can affect the performance and data analysis of HRM results, especially with regard to reference curve-based targeted genotyping. We present those examples in order of the typical experimental workflow, and discuss the crucial significance of the respective experimental errors and limitations for the quality and analysis of results. The experimental details which have a decisive impact on correct execution of a HRM genotyping experiment include type and quality of DNA source material, reproducibility of isolation method and template DNA preparation, primer and amplicon design, automation-derived preparation and pipetting inconsistencies, as well as physical limitations in melting curve distinction for alternative variants and careful selection of samples for validation by sequencing. We provide a case-by-case analysis and discussion of actual problems we encountered and solutions that should be taken into account by researchers newly attempting HRM genotyping, especially in a high-throughput setup.

  13. High Resolution Melting (HRM) for High-Throughput Genotyping—Limitations and Caveats in Practical Case Studies

    Science.gov (United States)

    Słomka, Marcin; Sobalska-Kwapis, Marta; Wachulec, Monika; Bartosz, Grzegorz

    2017-01-01

    High resolution melting (HRM) is a convenient method for gene scanning as well as genotyping of individual and multiple single nucleotide polymorphisms (SNPs). This rapid, simple, closed-tube, homogenous, and cost-efficient approach has the capacity for high specificity and sensitivity, while allowing easy transition to high-throughput scale. In this paper, we provide examples from our laboratory practice of some problematic issues which can affect the performance and data analysis of HRM results, especially with regard to reference curve-based targeted genotyping. We present those examples in order of the typical experimental workflow, and discuss the crucial significance of the respective experimental errors and limitations for the quality and analysis of results. The experimental details which have a decisive impact on correct execution of a HRM genotyping experiment include type and quality of DNA source material, reproducibility of isolation method and template DNA preparation, primer and amplicon design, automation-derived preparation and pipetting inconsistencies, as well as physical limitations in melting curve distinction for alternative variants and careful selection of samples for validation by sequencing. We provide a case-by-case analysis and discussion of actual problems we encountered and solutions that should be taken into account by researchers newly attempting HRM genotyping, especially in a high-throughput setup. PMID:29099791

  14. High Resolution Melting (HRM) for High-Throughput Genotyping-Limitations and Caveats in Practical Case Studies.

    Science.gov (United States)

    Słomka, Marcin; Sobalska-Kwapis, Marta; Wachulec, Monika; Bartosz, Grzegorz; Strapagiel, Dominik

    2017-11-03

    High resolution melting (HRM) is a convenient method for gene scanning as well as genotyping of individual and multiple single nucleotide polymorphisms (SNPs). This rapid, simple, closed-tube, homogenous, and cost-efficient approach has the capacity for high specificity and sensitivity, while allowing easy transition to high-throughput scale. In this paper, we provide examples from our laboratory practice of some problematic issues which can affect the performance and data analysis of HRM results, especially with regard to reference curve-based targeted genotyping. We present those examples in order of the typical experimental workflow, and discuss the crucial significance of the respective experimental errors and limitations for the quality and analysis of results. The experimental details which have a decisive impact on correct execution of a HRM genotyping experiment include type and quality of DNA source material, reproducibility of isolation method and template DNA preparation, primer and amplicon design, automation-derived preparation and pipetting inconsistencies, as well as physical limitations in melting curve distinction for alternative variants and careful selection of samples for validation by sequencing. We provide a case-by-case analysis and discussion of actual problems we encountered and solutions that should be taken into account by researchers newly attempting HRM genotyping, especially in a high-throughput setup.

  15. Application of high-throughput sequencing in understanding human oral microbiome related with health and disease

    OpenAIRE

    Chen, Hui; Jiang, Wen

    2014-01-01

    The oral microbiome is one of most diversity habitat in the human body and they are closely related with oral health and disease. As the technique developing,, high throughput sequencing has become a popular approach applied for oral microbial analysis. Oral bacterial profiles have been studied to explore the relationship between microbial diversity and oral diseases such as caries and periodontal disease. This review describes the application of high-throughput sequencing for characterizati...

  16. 20180311 - High Throughput Transcriptomics: From screening to pathways (SOT 2018)

    Science.gov (United States)

    The EPA ToxCast effort has screened thousands of chemicals across hundreds of high-throughput in vitro screening assays. The project is now leveraging high-throughput transcriptomic (HTTr) technologies to substantially expand its coverage of biological pathways. The first HTTr sc...

  17. High throughput label-free platform for statistical bio-molecular sensing

    DEFF Research Database (Denmark)

    Bosco, Filippo; Hwu, En-Te; Chen, Ching-Hsiu

    2011-01-01

    Sensors are crucial in many daily operations including security, environmental control, human diagnostics and patient monitoring. Screening and online monitoring require reliable and high-throughput sensing. We report on the demonstration of a high-throughput label-free sensor platform utilizing...

  18. High throughput synthesis and characterization of the PbnNb2O5+n (0.5 < n < 4.1) system on a single chip

    International Nuclear Information System (INIS)

    Mirsaneh, Mehdi; Hayden, Brian E.; Miao Shu; Pokorny, Jan; Perini, Steve; Furman, Eugene; Lanagan, Michael T.; Ubic, Rick; Reaney, Ian M.

    2011-01-01

    Most high throughput studies focus on assessing the effect of composition within a single known fundamental structure type, such as perovskite. Here we demonstrate how high throughput synthesis and screening can be used to establish structure-property relations in the PbO-Nb 2 O 5 system, for which eight distinct fundamental structure types are known to exist. PbNb 4 O 11 , PbNb 2 O 6 and pyrochlore could be easily distinguished by X-ray diffraction (XRD). However, XRD was insensitive to distortions of the pyrochlore structure and instead Raman spectroscopy was utilized to determine changes in symmetry from cubic to rhombohedral as the PbO concentration increased. High throughput screening of the capacitance revealed permittivity (ε r ) maxima in the PbNb 4 O 11 (ε r = 700) and cubic pyrochlore phases (ε r = 450). The ε r of PbNb 4 O 11 has not to date been reported but the value for cubic pyrochlore is higher than that reported for bulk ceramics (ε r = 270). Initial high electric field studies also revealed exceptionally high tunability (four times that reported for bismuth zinc niobate-based pyrochlores) of the capacitance in the pyrochlore phase.

  19. High-throughput analysis of amino acids in plant materials by single quadrupole mass spectrometry

    DEFF Research Database (Denmark)

    Dahl-Lassen, Rasmus; van Hecke, Jan Julien Josef; Jørgensen, Henning

    2018-01-01

    that it is very time consuming with typical chromatographic run times of 70 min or more. Results: We have here developed a high-throughput method for analysis of amino acid profiles in plant materials. The method combines classical protein hydrolysis and derivatization with fast separation by UHPLC and detection...... reducing the overall analytical costs compared to methods based on more advanced mass spectrometers....... by a single quadrupole (QDa) mass spectrometer. The chromatographic run time is reduced to 10 min and the precision, accuracy and sensitivity of the method are in line with other recent methods utilizing advanced and more expensive mass spectrometers. The sensitivity of the method is at least a factor 10...

  20. CLIP-seq analysis of multi-mapped reads discovers novel functional RNA regulatory sites in the human transcriptome.

    Science.gov (United States)

    Zhang, Zijun; Xing, Yi

    2017-09-19

    Crosslinking or RNA immunoprecipitation followed by sequencing (CLIP-seq or RIP-seq) allows transcriptome-wide discovery of RNA regulatory sites. As CLIP-seq/RIP-seq reads are short, existing computational tools focus on uniquely mapped reads, while reads mapped to multiple loci are discarded. We present CLAM (CLIP-seq Analysis of Multi-mapped reads). CLAM uses an expectation-maximization algorithm to assign multi-mapped reads and calls peaks combining uniquely and multi-mapped reads. To demonstrate the utility of CLAM, we applied it to a wide range of public CLIP-seq/RIP-seq datasets involving numerous splicing factors, microRNAs and m6A RNA methylation. CLAM recovered a large number of novel RNA regulatory sites inaccessible by uniquely mapped reads. The functional significance of these sites was demonstrated by consensus motif patterns and association with alternative splicing (splicing factors), transcript abundance (AGO2) and mRNA half-life (m6A). CLAM provides a useful tool to discover novel protein-RNA interactions and RNA modification sites from CLIP-seq and RIP-seq data, and reveals the significant contribution of repetitive elements to the RNA regulatory landscape of the human transcriptome. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  1. Genome-wide profiling of DNA-binding proteins using barcode-based multiplex Solexa sequencing.

    Science.gov (United States)

    Raghav, Sunil Kumar; Deplancke, Bart

    2012-01-01

    Chromatin immunoprecipitation (ChIP) is a commonly used technique to detect the in vivo binding of proteins to DNA. ChIP is now routinely paired to microarray analysis (ChIP-chip) or next-generation sequencing (ChIP-Seq) to profile the DNA occupancy of proteins of interest on a genome-wide level. Because ChIP-chip introduces several biases, most notably due to the use of a fixed number of probes, ChIP-Seq has quickly become the method of choice as, depending on the sequencing depth, it is more sensitive, quantitative, and provides a greater binding site location resolution. With the ever increasing number of reads that can be generated per sequencing run, it has now become possible to analyze several samples simultaneously while maintaining sufficient sequence coverage, thus significantly reducing the cost per ChIP-Seq experiment. In this chapter, we provide a step-by-step guide on how to perform multiplexed ChIP-Seq analyses. As a proof-of-concept, we focus on the genome-wide profiling of RNA Polymerase II as measuring its DNA occupancy at different stages of any biological process can provide insights into the gene regulatory mechanisms involved. However, the protocol can also be used to perform multiplexed ChIP-Seq analyses of other DNA-binding proteins such as chromatin modifiers and transcription factors.

  2. Integrated RNA-Seq and sRNA-Seq Analysis Identifies Chilling and Freezing Responsive Key Molecular Players and Pathways in Tea Plant (Camellia sinensis)

    Science.gov (United States)

    Zheng, Chao; Zhao, Lei; Wang, Yu; Shen, Jiazhi; Zhang, Yinfei; Jia, Sisi; Li, Yusheng; Ding, Zhaotang

    2015-01-01

    Tea [Camellia sinensis (L) O. Kuntze, Theaceae] is one of the most popular non-alcoholic beverages worldwide. Cold stress is one of the most severe abiotic stresses that limit tea plants’ growth, survival and geographical distribution. However, the genetic regulatory network and signaling pathways involved in cold stress responses in tea plants remain unearthed. Using RNA-Seq, DGE and sRNA-Seq technologies, we performed an integrative analysis of miRNA and mRNA expression profiling and their regulatory network of tea plants under chilling (4℃) and freezing (-5℃) stress. Differentially expressed (DE) miRNA and mRNA profiles were obtained based on fold change analysis, miRNAs and target mRNAs were found to show both coherent and incoherent relationships in the regulatory network. Furthermore, we compared several key pathways (e.g., ‘Photosynthesis’), GO terms (e.g., ‘response to karrikin’) and transcriptional factors (TFs, e.g., DREB1b/CBF1) which were identified as involved in the early chilling and/or freezing response of tea plants. Intriguingly, we found that karrikins, a new group of plant growth regulators, and β-primeverosidase (BPR), a key enzyme functionally relevant with the formation of tea aroma might play an important role in both early chilling and freezing response of tea plants. Quantitative reverse transcriptase-polymerase chain reaction (qRT-PCR) analysis further confirmed the results from RNA-Seq and sRNA-Seq analysis. This is the first study to simultaneously profile the expression patterns of both miRNAs and mRNAs on a genome-wide scale to elucidate the molecular mechanisms of early responses of tea plants to cold stress. In addition to gaining a deeper insight into the cold resistant characteristics of tea plants, we provide a good case study to analyse mRNA/miRNA expression and profiling of non-model plant species using next-generation sequencing technology. PMID:25901577

  3. COBRA-Seq: Sensitive and Quantitative Methylome Profiling

    Directory of Open Access Journals (Sweden)

    Hilal Varinli

    2015-10-01

    Full Text Available Combined Bisulfite Restriction Analysis (COBRA quantifies DNA methylation at a specific locus. It does so via digestion of PCR amplicons produced from bisulfite-treated DNA, using a restriction enzyme that contains a cytosine within its recognition sequence, such as TaqI. Here, we introduce COBRA-seq, a genome wide reduced methylome method that requires minimal DNA input (0.1–1.0 mg and can either use PCR or linear amplification to amplify the sequencing library. Variants of COBRA-seq can be used to explore CpG-depleted as well as CpG-rich regions in vertebrate DNA. The choice of enzyme influences enrichment for specific genomic features, such as CpG-rich promoters and CpG islands, or enrichment for less CpG dense regions such as enhancers. COBRA-seq coupled with linear amplification has the additional advantage of reduced PCR bias by producing full length fragments at high abundance. Unlike other reduced representative methylome methods, COBRA-seq has great flexibility in the choice of enzyme and can be multiplexed and tuned, to reduce sequencing costs and to interrogate different numbers of sites. Moreover, COBRA-seq is applicable to non-model organisms without the reference genome and compatible with the investigation of non-CpG methylation by using restriction enzymes containing CpA, CpT, and CpC in their recognition site.

  4. MIDAS: Mining differentially activated subpaths of KEGG pathways from multi-class RNA-seq data.

    Science.gov (United States)

    Lee, Sangseon; Park, Youngjune; Kim, Sun

    2017-07-15

    Pathway based analysis of high throughput transcriptome data is a widely used approach to investigate biological mechanisms. Since a pathway consists of multiple functions, the recent approach is to determine condition specific sub-pathways or subpaths. However, there are several challenges. First, few existing methods utilize explicit gene expression information from RNA-seq. More importantly, subpath activity is usually an average of statistical scores, e.g., correlations, of edges in a candidate subpath, which fails to reflect gene expression quantity information. In addition, none of existing methods can handle multiple phenotypes. To address these technical problems, we designed and implemented an algorithm, MIDAS, that determines condition specific subpaths, each of which has different activities across multiple phenotypes. MIDAS utilizes gene expression quantity information fully and the network centrality information to determine condition specific subpaths. To test performance of our tool, we used TCGA breast cancer RNA-seq gene expression profiles with five molecular subtypes. 36 differentially activate subpaths were determined. The utility of our method, MIDAS, was demonstrated in four ways. All 36 subpaths are well supported by the literature information. Subsequently, we showed that these subpaths had a good discriminant power for five cancer subtype classification and also had a prognostic power in terms of survival analysis. Finally, in a performance comparison of MIDAS to a recent subpath prediction method, PATHOME, our method identified more subpaths and much more genes that are well supported by the literature information. http://biohealth.snu.ac.kr/software/MIDAS/. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  5. Discovery and validation of information theory-based transcription factor and cofactor binding site motifs.

    Science.gov (United States)

    Lu, Ruipeng; Mucaki, Eliseos J; Rogan, Peter K

    2017-03-17

    Data from ChIP-seq experiments can derive the genome-wide binding specificities of transcription factors (TFs) and other regulatory proteins. We analyzed 765 ENCODE ChIP-seq peak datasets of 207 human TFs with a novel motif discovery pipeline based on recursive, thresholded entropy minimization. This approach, while obviating the need to compensate for skewed nucleotide composition, distinguishes true binding motifs from noise, quantifies the strengths of individual binding sites based on computed affinity and detects adjacent cofactor binding sites that coordinate with the targets of primary, immunoprecipitated TFs. We obtained contiguous and bipartite information theory-based position weight matrices (iPWMs) for 93 sequence-specific TFs, discovered 23 cofactor motifs for 127 TFs and revealed six high-confidence novel motifs. The reliability and accuracy of these iPWMs were determined via four independent validation methods, including the detection of experimentally proven binding sites, explanation of effects of characterized SNPs, comparison with previously published motifs and statistical analyses. We also predict previously unreported TF coregulatory interactions (e.g. TF complexes). These iPWMs constitute a powerful tool for predicting the effects of sequence variants in known binding sites, performing mutation analysis on regulatory SNPs and predicting previously unrecognized binding sites and target genes. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

  6. Data for automated, high-throughput microscopy analysis of intracellular bacterial colonies using spot detection

    DEFF Research Database (Denmark)

    Ernstsen, Christina Lundgaard; Login, Frédéric H.; Jensen, Helene Halkjær

    2017-01-01

    Quantification of intracellular bacterial colonies is useful in strategies directed against bacterial attachment, subsequent cellular invasion and intracellular proliferation. An automated, high-throughput microscopy-method was established to quantify the number and size of intracellular bacteria...

  7. High Throughput In vivo Analysis of Plant Leaf Chemical Properties Using Hyperspectral Imaging

    Science.gov (United States)

    Pandey, Piyush; Ge, Yufeng; Stoerger, Vincent; Schnable, James C.

    2017-01-01

    Image-based high-throughput plant phenotyping in greenhouse has the potential to relieve the bottleneck currently presented by phenotypic scoring which limits the throughput of gene discovery and crop improvement efforts. Numerous studies have employed automated RGB imaging to characterize biomass and growth of agronomically important crops. The objective of this study was to investigate the utility of hyperspectral imaging for quantifying chemical properties of maize and soybean plants in vivo. These properties included leaf water content, as well as concentrations of macronutrients nitrogen (N), phosphorus (P), potassium (K), magnesium (Mg), calcium (Ca), and sulfur (S), and micronutrients sodium (Na), iron (Fe), manganese (Mn), boron (B), copper (Cu), and zinc (Zn). Hyperspectral images were collected from 60 maize and 60 soybean plants, each subjected to varying levels of either water deficit or nutrient limitation stress with the goal of creating a wide range of variation in the chemical properties of plant leaves. Plants were imaged on an automated conveyor belt system using a hyperspectral imager with a spectral range from 550 to 1,700 nm. Images were processed to extract reflectance spectrum from each plant and partial least squares regression models were developed to correlate spectral data with chemical data. Among all the chemical properties investigated, water content was predicted with the highest accuracy [R2 = 0.93 and RPD (Ratio of Performance to Deviation) = 3.8]. All macronutrients were also quantified satisfactorily (R2 from 0.69 to 0.92, RPD from 1.62 to 3.62), with N predicted best followed by P, K, and S. The micronutrients group showed lower prediction accuracy (R2 from 0.19 to 0.86, RPD from 1.09 to 2.69) than the macronutrient groups. Cu and Zn were best predicted, followed by Fe and Mn. Na and B were the only two properties that hyperspectral imaging was not able to quantify satisfactorily (R2 designing experiments to vary plant nutrients

  8. A DNA fingerprinting procedure for ultra high-throughput genetic analysis of insects.

    Science.gov (United States)

    Schlipalius, D I; Waldron, J; Carroll, B J; Collins, P J; Ebert, P R

    2001-12-01

    Existing procedures for the generation of polymorphic DNA markers are not optimal for insect studies in which the organisms are often tiny and background molecular information is often non-existent. We have used a new high throughput DNA marker generation protocol called randomly amplified DNA fingerprints (RAF) to analyse the genetic variability in three separate strains of the stored grain pest, Rhyzopertha dominica. This protocol is quick, robust and reliable even though it requires minimal sample preparation, minute amounts of DNA and no prior molecular analysis of the organism. Arbitrarily selected oligonucleotide primers routinely produced approximately 50 scoreable polymorphic DNA markers, between individuals of three independent field isolates of R. dominica. Multivariate cluster analysis using forty-nine arbitrarily selected polymorphisms generated from a single primer reliably separated individuals into three clades corresponding to their geographical origin. The resulting clades were quite distinct, with an average genetic difference of 37.5 +/- 6.0% between clades and of 21.0 +/- 7.1% between individuals within clades. As a prelude to future gene mapping efforts, we have also assessed the performance of RAF under conditions commonly used in gene mapping. In this analysis, fingerprints from pooled DNA samples accurately and reproducibly reflected RAF profiles obtained from individual DNA samples that had been combined to create the bulked samples.

  9. Genome-wide identification of Bcl11b gene targets reveals role in brain-derived neurotrophic factor signaling.

    Directory of Open Access Journals (Sweden)

    Bin Tang

    Full Text Available B-cell leukemia/lymphoma 11B (Bcl11b is a transcription factor showing predominant expression in the striatum. To date, there are no known gene targets of Bcl11b in the nervous system. Here, we define targets for Bcl11b in striatal cells by performing chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq in combination with genome-wide expression profiling. Transcriptome-wide analysis revealed that 694 genes were significantly altered in striatal cells over-expressing Bcl11b, including genes showing striatal-enriched expression similar to Bcl11b. ChIP-seq analysis demonstrated that Bcl11b bound a mixture of coding and non-coding sequences that were within 10 kb of the transcription start site of an annotated gene. Integrating all ChIP-seq hits with the microarray expression data, 248 direct targets of Bcl11b were identified. Functional analysis on the integrated gene target list identified several zinc-finger encoding genes as Bcl11b targets, and further revealed a significant association of Bcl11b to brain-derived neurotrophic factor/neurotrophin signaling. Analysis of ChIP-seq binding regions revealed significant consensus DNA binding motifs for Bcl11b. These data implicate Bcl11b as a novel regulator of the BDNF signaling pathway, which is disrupted in many neurological disorders. Specific targeting of the Bcl11b-DNA interaction could represent a novel therapeutic approach to lowering BDNF signaling specifically in striatal cells.

  10. A Fully Automated High-Throughput Zebrafish Behavioral Ototoxicity Assay.

    Science.gov (United States)

    Todd, Douglas W; Philip, Rohit C; Niihori, Maki; Ringle, Ryan A; Coyle, Kelsey R; Zehri, Sobia F; Zabala, Leanne; Mudery, Jordan A; Francis, Ross H; Rodriguez, Jeffrey J; Jacob, Abraham

    2017-08-01

    Zebrafish animal models lend themselves to behavioral assays that can facilitate rapid screening of ototoxic, otoprotective, and otoregenerative drugs. Structurally similar to human inner ear hair cells, the mechanosensory hair cells on their lateral line allow the zebrafish to sense water flow and orient head-to-current in a behavior called rheotaxis. This rheotaxis behavior deteriorates in a dose-dependent manner with increased exposure to the ototoxin cisplatin, thereby establishing itself as an excellent biomarker for anatomic damage to lateral line hair cells. Building on work by our group and others, we have built a new, fully automated high-throughput behavioral assay system that uses automated image analysis techniques to quantify rheotaxis behavior. This novel system consists of a custom-designed swimming apparatus and imaging system consisting of network-controlled Raspberry Pi microcomputers capturing infrared video. Automated analysis techniques detect individual zebrafish, compute their orientation, and quantify the rheotaxis behavior of a zebrafish test population, producing a powerful, high-throughput behavioral assay. Using our fully automated biological assay to test a standardized ototoxic dose of cisplatin against varying doses of compounds that protect or regenerate hair cells may facilitate rapid translation of candidate drugs into preclinical mammalian models of hearing loss.

  11. High-Throughput Analysis With 96-Capillary Array Electrophoresis and Integrated Sample Preparation for DNA Sequencing Based on Laser Induced Fluorescence Detection

    Energy Technology Data Exchange (ETDEWEB)

    Xue, Gang [Iowa State Univ., Ames, IA (United States)

    2001-01-01

    The purpose of this research was to improve the fluorescence detection for the multiplexed capillary array electrophoresis, extend its use beyond the genomic analysis, and to develop an integrated micro-sample preparation system for high-throughput DNA sequencing. The authors first demonstrated multiplexed capillary zone electrophoresis (CZE) and micellar electrokinetic chromatography (MEKC) separations in a 96-capillary array system with laser-induced fluorescence detection. Migration times of four kinds of fluoresceins and six polyaromatic hydrocarbons (PAHs) are normalized to one of the capillaries using two internal standards. The relative standard deviations (RSD) after normalization are 0.6-1.4% for the fluoresceins and 0.1-1.5% for the PAHs. Quantitative calibration of the separations based on peak areas is also performed, again with substantial improvement over the raw data. This opens up the possibility of performing massively parallel separations for high-throughput chemical analysis for process monitoring, combinatorial synthesis, and clinical diagnosis. The authors further improved the fluorescence detection by step laser scanning. A computer-controlled galvanometer scanner is adapted for scanning a focused laser beam across a 96-capillary array for laser-induced fluorescence detection. The signal at a single photomultiplier tube is temporally sorted to distinguish among the capillaries. The limit of detection for fluorescein is 3 x 10-11 M (S/N = 3) for 5-mW of total laser power scanned at 4 Hz. The observed cross-talk among capillaries is 0.2%. Advantages include the efficient utilization of light due to the high duty-cycle of step scan, good detection performance due to the reduction of stray light, ruggedness due to the small mass of the galvanometer mirror, low cost due to the simplicity of components, and flexibility due to the independent paths for excitation and emission.

  12. High throughput imaging cytometer with acoustic focussing.

    Science.gov (United States)

    Zmijan, Robert; Jonnalagadda, Umesh S; Carugo, Dario; Kochi, Yu; Lemm, Elizabeth; Packham, Graham; Hill, Martyn; Glynne-Jones, Peter

    2015-10-31

    We demonstrate an imaging flow cytometer that uses acoustic levitation to assemble cells and other particles into a sheet structure. This technique enables a high resolution, low noise CMOS camera to capture images of thousands of cells with each frame. While ultrasonic focussing has previously been demonstrated for 1D cytometry systems, extending the technology to a planar, much higher throughput format and integrating imaging is non-trivial, and represents a significant jump forward in capability, leading to diagnostic possibilities not achievable with current systems. A galvo mirror is used to track the images of the moving cells permitting exposure times of 10 ms at frame rates of 50 fps with motion blur of only a few pixels. At 80 fps, we demonstrate a throughput of 208 000 beads per second. We investigate the factors affecting motion blur and throughput, and demonstrate the system with fluorescent beads, leukaemia cells and a chondrocyte cell line. Cells require more time to reach the acoustic focus than beads, resulting in lower throughputs; however a longer device would remove this constraint.

  13. High-throughput GPU-based LDPC decoding

    Science.gov (United States)

    Chang, Yang-Lang; Chang, Cheng-Chun; Huang, Min-Yu; Huang, Bormin

    2010-08-01

    Low-density parity-check (LDPC) code is a linear block code known to approach the Shannon limit via the iterative sum-product algorithm. LDPC codes have been adopted in most current communication systems such as DVB-S2, WiMAX, WI-FI and 10GBASE-T. LDPC for the needs of reliable and flexible communication links for a wide variety of communication standards and configurations have inspired the demand for high-performance and flexibility computing. Accordingly, finding a fast and reconfigurable developing platform for designing the high-throughput LDPC decoder has become important especially for rapidly changing communication standards and configurations. In this paper, a new graphic-processing-unit (GPU) LDPC decoding platform with the asynchronous data transfer is proposed to realize this practical implementation. Experimental results showed that the proposed GPU-based decoder achieved 271x speedup compared to its CPU-based counterpart. It can serve as a high-throughput LDPC decoder.

  14. ORMAN: optimal resolution of ambiguous RNA-Seq multimappings in the presence of novel isoforms.

    Science.gov (United States)

    Dao, Phuong; Numanagić, Ibrahim; Lin, Yen-Yi; Hach, Faraz; Karakoc, Emre; Donmez, Nilgun; Collins, Colin; Eichler, Evan E; Sahinalp, S Cenk

    2014-03-01

    RNA-Seq technology is promising to uncover many novel alternative splicing events, gene fusions and other variations in RNA transcripts. For an accurate detection and quantification of transcripts, it is important to resolve the mapping ambiguity for those RNA-Seq reads that can be mapped to multiple loci: >17% of the reads from mouse RNA-Seq data and 50% of the reads from some plant RNA-Seq data have multiple mapping loci. In this study, we show how to resolve the mapping ambiguity in the presence of novel transcriptomic events such as exon skipping and novel indels towards accurate downstream analysis. We introduce ORMAN ( O ptimal R esolution of M ultimapping A mbiguity of R N A-Seq Reads), which aims to compute the minimum number of potential transcript products for each gene and to assign each multimapping read to one of these transcripts based on the estimated distribution of the region covering the read. ORMAN achieves this objective through a combinatorial optimization formulation, which is solved through well-known approximation algorithms, integer linear programs and heuristics. On a simulated RNA-Seq dataset including a random subset of transcripts from the UCSC database, the performance of several state-of-the-art methods for identifying and quantifying novel transcripts, such as Cufflinks, IsoLasso and CLIIQ, is significantly improved through the use of ORMAN. Furthermore, in an experiment using real RNA-Seq reads, we show that ORMAN is able to resolve multimapping to produce coverage values that are similar to the original distribution, even in genes with highly non-uniform coverage. ORMAN is available at http://orman.sf.net

  15. Evaluating High Throughput Toxicokinetics and Toxicodynamics for IVIVE (WC10)

    Science.gov (United States)

    High-throughput screening (HTS) generates in vitro data for characterizing potential chemical hazard. TK models are needed to allow in vitro to in vivo extrapolation (IVIVE) to real world situations. The U.S. EPA has created a public tool (R package “httk” for high throughput tox...

  16. Sentence‐Chain Based Seq2seq Model for Corpus Expansion

    Directory of Open Access Journals (Sweden)

    Euisok Chung

    2017-08-01

    Full Text Available This study focuses on a method for sequential data augmentation in order to alleviate data sparseness problems. Specifically, we present corpus expansion techniques for enhancing the coverage of a language model. Recent recurrent neural network studies show that a seq2seq model can be applied for addressing language generation issues; it has the ability to generate new sentences from given input sentences. We present a method of corpus expansion using a sentence‐chain based seq2seq model. For training the seq2seq model, sentence chains are used as triples. The first two sentences in a triple are used for the encoder of the seq2seq model, while the last sentence becomes a target sequence for the decoder. Using only internal resources, evaluation results show an improvement of approximately 7.6% relative perplexity over a baseline language model of Korean text. Additionally, from a comparison with a previous study, the sentence chain approach reduces the size of the training data by 38.4% while generating 1.4‐times the number of n‐grams with superior performance for English text.

  17. A Customizable Flow Injection System for Automated, High Throughput, and Time Sensitive Ion Mobility Spectrometry and Mass Spectrometry Measurements

    Energy Technology Data Exchange (ETDEWEB)

    Orton, Daniel J. [Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, United States; Tfaily, Malak M. [Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, United States; Moore, Ronald J. [Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, United States; LaMarche, Brian L. [Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, United States; Zheng, Xueyun [Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, United States; Fillmore, Thomas L. [Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, United States; Chu, Rosalie K. [Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, United States; Weitz, Karl K. [Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, United States; Monroe, Matthew E. [Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, United States; Kelly, Ryan T. [Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, United States; Smith, Richard D. [Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, United States; Baker, Erin S. [Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, United States

    2017-12-13

    To better understand disease conditions and environmental perturbations, multi-omic studies (i.e. proteomic, lipidomic, metabolomic, etc. analyses) are vastly increasing in popularity. In a multi-omic study, a single sample is typically extracted in multiple ways and numerous analyses are performed using different instruments. Thus, one sample becomes many analyses, making high throughput and reproducible evaluations a necessity. One way to address the numerous samples and varying instrumental conditions is to utilize a flow injection analysis (FIA) system for rapid sample injection. While some FIA systems have been created to address these challenges, many have limitations such as high consumable costs, low pressure capabilities, limited pressure monitoring and fixed flow rates. To address these limitations, we created an automated, customizable FIA system capable of operating at diverse flow rates (~50 nL/min to 500 µL/min) to accommodate low- and high-flow instrument sources. This system can also operate at varying analytical throughputs from 24 to 1200 samples per day to enable different MS analysis approaches. Applications ranging from native protein analyses to molecular library construction were performed using the FIA system. The results from these studies showed a highly robust platform, providing consistent performance over many days without carryover as long as washing buffers specific to each molecular analysis were utilized.

  18. Centroid based clustering of high throughput sequencing reads based on n-mer counts.

    Science.gov (United States)

    Solovyov, Alexander; Lipkin, W Ian

    2013-09-08

    Many problems in computational biology require alignment-free sequence comparisons. One of the common tasks involving sequence comparison is sequence clustering. Here we apply methods of alignment-free comparison (in particular, comparison using sequence composition) to the challenge of sequence clustering. We study several centroid based algorithms for clustering sequences based on word counts. Study of their performance shows that using k-means algorithm with or without the data whitening is efficient from the computational point of view. A higher clustering accuracy can be achieved using the soft expectation maximization method, whereby each sequence is attributed to each cluster with a specific probability. We implement an open source tool for alignment-free clustering. It is publicly available from github: https://github.com/luscinius/afcluster. We show the utility of alignment-free sequence clustering for high throughput sequencing analysis despite its limitations. In particular, it allows one to perform assembly with reduced resources and a minimal loss of quality. The major factor affecting performance of alignment-free read clustering is the length of the read.

  19. Pathway Processor 2.0: a web resource for pathway-based analysis of high-throughput data.

    Science.gov (United States)

    Beltrame, Luca; Bianco, Luca; Fontana, Paolo; Cavalieri, Duccio

    2013-07-15

    Pathway Processor 2.0 is a web application designed to analyze high-throughput datasets, including but not limited to microarray and next-generation sequencing, using a pathway centric logic. In addition to well-established methods such as the Fisher's test and impact analysis, Pathway Processor 2.0 offers innovative methods that convert gene expression into pathway expression, leading to the identification of differentially regulated pathways in a dataset of choice. Pathway Processor 2.0 is available as a web service at http://compbiotoolbox.fmach.it/pathwayProcessor/. Sample datasets to test the functionality can be used directly from the application. duccio.cavalieri@fmach.it Supplementary data are available at Bioinformatics online.

  20. Machine learning in computational biology to accelerate high-throughput protein expression.

    Science.gov (United States)

    Sastry, Anand; Monk, Jonathan; Tegel, Hanna; Uhlen, Mathias; Palsson, Bernhard O; Rockberg, Johan; Brunk, Elizabeth

    2017-08-15

    The Human Protein Atlas (HPA) enables the simultaneous characterization of thousands of proteins across various tissues to pinpoint their spatial location in the human body. This has been achieved through transcriptomics and high-throughput immunohistochemistry-based approaches, where over 40 000 unique human protein fragments have been expressed in E. coli. These datasets enable quantitative tracking of entire cellular proteomes and present new avenues for understanding molecular-level properties influencing expression and solubility. Combining computational biology and machine learning identifies protein properties that hinder the HPA high-throughput antibody production pipeline. We predict protein expression and solubility with accuracies of 70% and 80%, respectively, based on a subset of key properties (aromaticity, hydropathy and isoelectric point). We guide the selection of protein fragments based on these characteristics to optimize high-throughput experimentation. We present the machine learning workflow as a series of IPython notebooks hosted on GitHub (https://github.com/SBRG/Protein_ML). The workflow can be used as a template for analysis of further expression and solubility datasets. ebrunk@ucsd.edu or johanr@biotech.kth.se. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

  1. High-throughput analysis of endogenous fruit glycosyl hydrolases using a novel chromogenic hydrogel substrate assay

    DEFF Research Database (Denmark)

    Schückel, Julia; Kracun, Stjepan Kresimir; Lausen, Thomas Frederik

    2017-01-01

    A broad range of enzyme activities can be found in a wide range of different fruits and fruiting bodies but there is a lack of methods where many samples can be handled in a high-throughput and efficient manner. In particular, plant polysaccharide degrading enzymes – glycosyl hydrolases (GHs) play...... led to a more profound understanding of the importance of GH activity and regulation, current methods for determining glycosyl hydrolase activity are lacking in throughput and fail to keep up with data output from transcriptome research. Here we present the use of a versatile, easy...

  2. Genome-wide RNA-seq analysis of human and mouse platelet transcriptomes

    Science.gov (United States)

    Rowley, Jesse W.; Oler, Andrew J.; Tolley, Neal D.; Hunter, Benjamin N.; Low, Elizabeth N.; Nix, David A.; Yost, Christian C.; Zimmerman, Guy A.

    2011-01-01

    Inbred mice are a useful tool for studying the in vivo functions of platelets. Nonetheless, the mRNA signature of mouse platelets is not known. Here, we use paired-end next-generation RNA sequencing (RNA-seq) to characterize the polyadenylated transcriptomes of human and mouse platelets. We report that RNA-seq provides unprecedented resolution of mRNAs that are expressed across the entire human and mouse genomes. Transcript expression and abundance are often conserved between the 2 species. Several mRNAs, however, are differentially expressed in human and mouse platelets. Moreover, previously described functional disparities between mouse and human platelets are reflected in differences at the transcript level, including protease activated receptor-1, protease activated receptor-3, platelet activating factor receptor, and factor V. This suggests that RNA-seq is a useful tool for predicting differences in platelet function between mice and humans. Our next-generation sequencing analysis provides new insights into the human and murine platelet transcriptomes. The sequencing dataset will be useful in the design of mouse models of hemostasis and a catalyst for discovery of new functions of platelets. Access to the dataset is found in the “Introduction.” PMID:21596849

  3. An RNA-Based Fluorescent Biosensor for High-Throughput Analysis of the cGAS-cGAMP-STING Pathway.

    Science.gov (United States)

    Bose, Debojit; Su, Yichi; Marcus, Assaf; Raulet, David H; Hammond, Ming C

    2016-12-22

    In mammalian cells, the second messenger (2'-5',3'-5') cyclic guanosine monophosphate-adenosine monophosphate (2',3'-cGAMP), is produced by the cytosolic DNA sensor cGAMP synthase (cGAS), and subsequently bound by the stimulator of interferon genes (STING) to trigger interferon response. Thus, the cGAS-cGAMP-STING pathway plays a critical role in pathogen detection, as well as pathophysiological conditions including cancer and autoimmune disorders. However, studying and targeting this immune signaling pathway has been challenging due to the absence of tools for high-throughput analysis. We have engineered an RNA-based fluorescent biosensor that responds to 2',3'-cGAMP. The resulting "mix-and-go" cGAS activity assay shows excellent statistical reliability as a high-throughput screening (HTS) assay and distinguishes between direct and indirect cGAS inhibitors. Furthermore, the biosensor enables quantitation of 2',3'-cGAMP in mammalian cell lysates. We envision this biosensor-based assay as a resource to study the cGAS-cGAMP-STING pathway in the context of infectious diseases, cancer immunotherapy, and autoimmune diseases. Copyright © 2016 Elsevier Ltd. All rights reserved.

  4. IspE inhibitors identified by a combination of in silico and in vitro high-throughput screening.

    Directory of Open Access Journals (Sweden)

    Naomi Tidten-Luksch

    Full Text Available CDP-ME kinase (IspE contributes to the non-mevalonate or deoxy-xylulose phosphate (DOXP pathway for isoprenoid precursor biosynthesis found in many species of bacteria and apicomplexan parasites. IspE has been shown to be essential by genetic methods and since it is absent from humans it constitutes a promising target for antimicrobial drug development. Using in silico screening directed against the substrate binding site and in vitro high-throughput screening directed against both, the substrate and co-factor binding sites, non-substrate-like IspE inhibitors have been discovered and structure-activity relationships were derived. The best inhibitors in each series have high ligand efficiencies and favourable physico-chemical properties rendering them promising starting points for drug discovery. Putative binding modes of the ligands were suggested which are consistent with established structure-activity relationships. The applied screening methods were complementary in discovering hit compounds, and a comparison of both approaches highlights their strengths and weaknesses. It is noteworthy that compounds identified by virtual screening methods provided the controls for the biochemical screens.

  5. Synthetic Biomaterials to Rival Nature's Complexity-a Path Forward with Combinatorics, High-Throughput Discovery, and High-Content Analysis.

    Science.gov (United States)

    Zhang, Douglas; Lee, Junmin; Kilian, Kristopher A

    2017-10-01

    Cells in tissue receive a host of soluble and insoluble signals in a context-dependent fashion, where integration of these cues through a complex network of signal transduction cascades will define a particular outcome. Biomaterials scientists and engineers are tasked with designing materials that can at least partially recreate this complex signaling milieu towards new materials for biomedical applications. In this progress report, recent advances in high throughput techniques and high content imaging approaches that are facilitating the discovery of efficacious biomaterials are described. From microarrays of synthetic polymers, peptides and full-length proteins, to designer cell culture systems that present multiple biophysical and biochemical cues in tandem, it is discussed how the integration of combinatorics with high content imaging and analysis is essential to extracting biologically meaningful information from large scale cellular screens to inform the design of next generation biomaterials. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  6. ChIP-seq Mapping of Distant-Acting Enhancers and Their In Vivo Activities

    Energy Technology Data Exchange (ETDEWEB)

    Visel, Axel; Pennacchio, Len A.

    2011-06-01

    The genomic location and function of most distant-acting transcriptional enhancers in the human genome remains unknown We performed ChIP-seq for various transcriptional coactivator proteins (such as p300) directly from different embryonic mouse tissues, identifying thousands of binding sitesTransgenic mouse experiments show that p300 and other co-activator peaks are highly predictive of genomic location AND tissue-specific activity patterns of distant-acting enhancersMost enhancers are active only in one or very few tissues Genomic location of tissue-specific p300 peaks correlates with tissue-specific expression of nearby genes Most binding sites are conserved, but the global degree of conservation varies between tissues

  7. From root to fruit: RNA-Seq analysis shows that arbuscular mycorrhizal symbiosis may affect tomato fruit metabolism.

    Science.gov (United States)

    Zouari, Inès; Salvioli, Alessandra; Chialva, Matteo; Novero, Mara; Miozzi, Laura; Tenore, Gian Carlo; Bagnaresi, Paolo; Bonfante, Paola

    2014-03-21

    Tomato (Solanum lycopersicum) establishes a beneficial symbiosis with arbuscular mycorrhizal (AM) fungi. The formation of the mycorrhizal association in the roots leads to plant-wide modulation of gene expression. To understand the systemic effect of the fungal symbiosis on the tomato fruit, we used RNA-Seq to perform global transcriptome profiling on Moneymaker tomato fruits at the turning ripening stage. Fruits were collected at 55 days after flowering, from plants colonized with Funneliformis mosseae and from control plants, which were fertilized to avoid responses related to nutrient deficiency. Transcriptome analysis identified 712 genes that are differentially expressed in fruits from mycorrhizal and control plants. Gene Ontology (GO) enrichment analysis of these genes showed 81 overrepresented functional GO classes. Up-regulated GO classes include photosynthesis, stress response, transport, amino acid synthesis and carbohydrate metabolism functions, suggesting a general impact of fungal symbiosis on primary metabolisms and, particularly, on mineral nutrition. Down-regulated GO classes include cell wall, metabolism and ethylene response pathways. Quantitative RT-PCR validated the RNA-Seq results for 12 genes out of 14 when tested at three fruit ripening stages, mature green, breaker and turning. Quantification of fruit nutraceutical and mineral contents produced values consistent with the expression changes observed by RNA-Seq analysis. This RNA-Seq profiling produced a novel data set that explores the intersection of mycorrhization and fruit development. We found that the fruits of mycorrhizal plants show two transcriptomic "signatures": genes characteristic of a climacteric fleshy fruit, and genes characteristic of mycorrhizal status, like phosphate and sulphate transporters. Moreover, mycorrhizal plants under low nutrient conditions produce fruits with a nutrient content similar to those from non-mycorrhizal plants under high nutrient conditions

  8. High-throughput optical system for HDES hyperspectral imager

    Science.gov (United States)

    Václavík, Jan; Melich, Radek; Pintr, Pavel; Pleštil, Jan

    2015-01-01

    Affordable, long-wave infrared hyperspectral imaging calls for use of an uncooled FPA with high-throughput optics. This paper describes the design of the optical part of a stationary hyperspectral imager in a spectral range of 7-14 um with a field of view of 20°×10°. The imager employs a push-broom method made by a scanning mirror. High throughput and a demand for simplicity and rigidity led to a fully refractive design with highly aspheric surfaces and off-axis positioning of the detector array. The design was optimized to exploit the machinability of infrared materials by the SPDT method and a simple assemblage.

  9. Crystal Symmetry Algorithms in a High-Throughput Framework for Materials

    Science.gov (United States)

    Taylor, Richard

    The high-throughput framework AFLOW that has been developed and used successfully over the last decade is improved to include fully-integrated software for crystallographic symmetry characterization. The standards used in the symmetry algorithms conform with the conventions and prescriptions given in the International Tables of Crystallography (ITC). A standard cell choice with standard origin is selected, and the space group, point group, Bravais lattice, crystal system, lattice system, and representative symmetry operations are determined. Following the conventions of the ITC, the Wyckoff sites are also determined and their labels and site symmetry are provided. The symmetry code makes no assumptions on the input cell orientation, origin, or reduction and has been integrated in the AFLOW high-throughput framework for materials discovery by adding to the existing code base and making use of existing classes and functions. The software is written in object-oriented C++ for flexibility and reuse. A performance analysis and examination of the algorithms scaling with cell size and symmetry is also reported.

  10. MultiSeq: unifying sequence and structure data for evolutionary analysis

    Directory of Open Access Journals (Sweden)

    Wright Dan

    2006-08-01

    Full Text Available Abstract Background Since the publication of the first draft of the human genome in 2000, bioinformatic data have been accumulating at an overwhelming pace. Currently, more than 3 million sequences and 35 thousand structures of proteins and nucleic acids are available in public databases. Finding correlations in and between these data to answer critical research questions is extremely challenging. This problem needs to be approached from several directions: information science to organize and search the data; information visualization to assist in recognizing correlations; mathematics to formulate statistical inferences; and biology to analyze chemical and physical properties in terms of sequence and structure changes. Results Here we present MultiSeq, a unified bioinformatics analysis environment that allows one to organize, display, align and analyze both sequence and structure data for proteins and nucleic acids. While special emphasis is placed on analyzing the data within the framework of evolutionary biology, the environment is also flexible enough to accommodate other usage patterns. The evolutionary approach is supported by the use of predefined metadata, adherence to standard ontological mappings, and the ability for the user to adjust these classifications using an electronic notebook. MultiSeq contains a new algorithm to generate complete evolutionary profiles that represent the topology of the molecular phylogenetic tree of a homologous group of distantly related proteins. The method, based on the multidimensional QR factorization of multiple sequence and structure alignments, removes redundancy from the alignments and orders the protein sequences by increasing linear dependence, resulting in the identification of a minimal basis set of sequences that spans the evolutionary space of the homologous group of proteins. Conclusion MultiSeq is a major extension of the Multiple Alignment tool that is provided as part of VMD, a structural

  11. Bulk segregant analysis by high-throughput sequencing reveals a novel xylose utilization gene from Saccharomyces cerevisiae.

    Directory of Open Access Journals (Sweden)

    Jared W Wenger

    2010-05-01

    Full Text Available Fermentation of xylose is a fundamental requirement for the efficient production of ethanol from lignocellulosic biomass sources. Although they aggressively ferment hexoses, it has long been thought that native Saccharomyces cerevisiae strains cannot grow fermentatively or non-fermentatively on xylose. Population surveys have uncovered a few naturally occurring strains that are weakly xylose-positive, and some S. cerevisiae have been genetically engineered to ferment xylose, but no strain, either natural or engineered, has yet been reported to ferment xylose as efficiently as glucose. Here, we used a medium-throughput screen to identify Saccharomyces strains that can increase in optical density when xylose is presented as the sole carbon source. We identified 38 strains that have this xylose utilization phenotype, including strains of S. cerevisiae, other sensu stricto members, and hybrids between them. All the S. cerevisiae xylose-utilizing strains we identified are wine yeasts, and for those that could produce meiotic progeny, the xylose phenotype segregates as a single gene trait. We mapped this gene by Bulk Segregant Analysis (BSA using tiling microarrays and high-throughput sequencing. The gene is a putative xylitol dehydrogenase, which we name XDH1, and is located in the subtelomeric region of the right end of chromosome XV in a region not present in the S288c reference genome. We further characterized the xylose phenotype by performing gene expression microarrays and by genetically dissecting the endogenous Saccharomyces xylose pathway. We have demonstrated that natural S. cerevisiae yeasts are capable of utilizing xylose as the sole carbon source, characterized the genetic basis for this trait as well as the endogenous xylose utilization pathway, and demonstrated the feasibility of BSA using high-throughput sequencing.

  12. Computational Investigations of Post-Transcriptional Regulation

    DEFF Research Database (Denmark)

    Rasmussen, Simon Horskjær

    and miRNA regulation was studied by cross-linking immunoprecipitation (CLIP) and RBP double knockdown experiments. A comprehensive analysis of 107 CLIP datasets of 49 RBPs demonstrated that RBPs modulate miRNA regulation. Results suggest it is mediated by RBP-binding hotspots that likely...... investigated using high-throughput data. Analysis of IMP RIP-seq, iCLIP and RNA-seq datasets identified transcripts associated with cytoplasmic IMP ribonucleoproteins. Many of these transcripts were functionally involved in actin cytoskeletal remodeling. Further analyses of this data permitted estimation...... of a bipartite motif, composed of an AU-rich and a CA-rich domain. In addition, a regulatory motif discovery method was developed and applied to identify motifs using differential expression data and CLIP-data in the above investigations. This thesis increased the understanding of the role of RBPs in mi...

  13. Bioinformatics analysis of RNA-seq data revealed critical genes in colon adenocarcinoma.

    Science.gov (United States)

    Xi, W-D; Liu, Y-J; Sun, X-B; Shan, J; Yi, L; Zhang, T-T

    2017-07-01

    RNA-seq data of colon adenocarcinoma (COAD) were analyzed with bioinformatics tools to discover critical genes in the disease. Relevant small molecule drugs, transcription factors (TFs) and microRNAs (miRNAs) were also investigated. RNA-seq data of COAD were downloaded from The Cancer Genome Atlas (TCGA). Differential analysis was performed with package edgeR. False positive discovery (FDR) 1 were set as the cut-offs to screen out differentially expressed genes (DEGs). Gene coexpression network was constructed with package Ebcoexpress. GO enrichment analysis was performed for the DEGs in the gene coexpression network with DAVID. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was also performed for the genes with KOBASS 2.0. Modules were identified with MCODE of Cytoscape. Relevant small molecules drugs were predicted by Connectivity map. Relevant miRNAs and TFs were searched by WebGestalt. A total of 457 DEGs, including 255 up-regulated and 202 down-regulated genes, were identified from 437 COAD and 39 control samples. A gene coexpression network was constructed containing 40 DEGs and 101 edges. The genes were mainly associated with collagen fibril organization, extracellular matrix organization and translation. Two modules were identified from the gene coexpression network, which were implicated in muscle contraction and extracellular matrix organization, respectively. Several critical genes were disclosed, such as MYH11, COL5A2 and ribosomal proteins. Nine relevant small molecule drugs were identified, such as scriptaid and STOCK1N-35874. Accordingly, a total of 17 TFs and 10 miRNAs related to COAD were acquired, such as ETS2, NFAT, AP4, miR-124A, MiR-9, miR-96 and let-7. Several critical genes and relevant drugs, TFs and miRNAs were revealed in COAD. These findings could advance the understanding of the disease and benefit therapy development.

  14. High Performance Computing Modernization Program Kerberos Throughput Test Report

    Science.gov (United States)

    2017-10-26

    Naval Research Laboratory Washington, DC 20375-5320 NRL/MR/5524--17-9751 High Performance Computing Modernization Program Kerberos Throughput Test ...NUMBER 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 2. REPORT TYPE1. REPORT DATE (DD-MM-YYYY) 4. TITLE AND SUBTITLE 6. AUTHOR(S) 8. PERFORMING...PAGE 18. NUMBER OF PAGES 17. LIMITATION OF ABSTRACT High Performance Computing Modernization Program Kerberos Throughput Test Report Daniel G. Gdula* and

  15. In Silico Pooling of ChIP-seq Control Experiments

    Science.gov (United States)

    Sun, Guannan; Srinivasan, Rajini; Lopez-Anido, Camila; Hung, Holly A.; Svaren, John; Keleş, Sündüz

    2014-01-01

    As next generation sequencing technologies are becoming more economical, large-scale ChIP-seq studies are enabling the investigation of the roles of transcription factor binding and epigenome on phenotypic variation. Studying such variation requires individual level ChIP-seq experiments. Standard designs for ChIP-seq experiments employ a paired control per ChIP-seq sample. Genomic coverage for control experiments is often sacrificed to increase the resources for ChIP samples. However, the quality of ChIP-enriched regions identifiable from a ChIP-seq experiment depends on the quality and the coverage of the control experiments. Insufficient coverage leads to loss of power in detecting enrichment. We investigate the effect of in silico pooling of control samples within multiple biological replicates, multiple treatment conditions, and multiple cell lines and tissues across multiple datasets with varying levels of genomic coverage. Our computational studies suggest guidelines for performing in silico pooling of control experiments. Using vast amounts of ENCODE data, we show that pairwise correlations between control samples originating from multiple biological replicates, treatments, and cell lines/tissues can be grouped into two classes representing whether or not in silico pooling leads to power gain in detecting enrichment between the ChIP and the control samples. Our findings have important implications for multiplexing samples. PMID:25380244

  16. High-throughput sequencing of microRNA transcriptome and expression assay in the sturgeon, Acipenser schrenckii.

    Directory of Open Access Journals (Sweden)

    Lihong Yuan

    Full Text Available Sturgeons are considered as living fossils and have very high evolutionary, economical and conservation values. The multiploidy of sturgeon that has been caused by chromosome duplication may lead to the emergence of new microRNAs (miRNAs involved in the ploidy and physiological processes. In the present study, we performed the first sturgeon miRNAs analysis by RNA-seq high-throughput sequencing combined with expression assay of microarray and real-time PCR, and aimed to discover the sturgeon-specific miRNAs, confirm the expressed pattern of miRNAs and illustrate the potential role of miRNAs-targets on sturgeon biological processes. A total of 103 miRNAs were identified, including 58 miRNAs with strongly detected signals (signal >500 and P≤0.01, which were detected by microarray. Real-time PCR assay supported the expression pattern obtained by microarray. Moreover, co-expression of 21 miRNAs in all five tissues and tissue-specific expression of 16 miRNAs implied the crucial and particular function of them in sturgeon physiological processes. Target gene prediction, especially the enriched functional gene groups (369 GO terms and pathways (37 KEGG regulated by 58 miRNAs (P<0.05, illustrated the interaction of miRNAs and putative mRNAs, and also the potential mechanism involved in these biological processes. Our new findings of sturgeon miRNAs expand the public database of transcriptome information for this species, contribute to our understanding of sturgeon biology, and also provide invaluable data that may be applied in sturgeon breeding.

  17. High-throughput sequencing of microRNA transcriptome and expression assay in the sturgeon, Acipenser schrenckii.

    Science.gov (United States)

    Yuan, Lihong; Zhang, Xiujuan; Li, Linmiao; Jiang, Haiying; Chen, Jinping

    2014-01-01

    Sturgeons are considered as living fossils and have very high evolutionary, economical and conservation values. The multiploidy of sturgeon that has been caused by chromosome duplication may lead to the emergence of new microRNAs (miRNAs) involved in the ploidy and physiological processes. In the present study, we performed the first sturgeon miRNAs analysis by RNA-seq high-throughput sequencing combined with expression assay of microarray and real-time PCR, and aimed to discover the sturgeon-specific miRNAs, confirm the expressed pattern of miRNAs and illustrate the potential role of miRNAs-targets on sturgeon biological processes. A total of 103 miRNAs were identified, including 58 miRNAs with strongly detected signals (signal >500 and P≤0.01), which were detected by microarray. Real-time PCR assay supported the expression pattern obtained by microarray. Moreover, co-expression of 21 miRNAs in all five tissues and tissue-specific expression of 16 miRNAs implied the crucial and particular function of them in sturgeon physiological processes. Target gene prediction, especially the enriched functional gene groups (369 GO terms) and pathways (37 KEGG) regulated by 58 miRNAs (P<0.05), illustrated the interaction of miRNAs and putative mRNAs, and also the potential mechanism involved in these biological processes. Our new findings of sturgeon miRNAs expand the public database of transcriptome information for this species, contribute to our understanding of sturgeon biology, and also provide invaluable data that may be applied in sturgeon breeding.

  18. Laser-Induced Fluorescence Detection in High-Throughput Screening of Heterogeneous Catalysts and Single Cells Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Su, Hui [Iowa State Univ., Ames, IA (United States)

    2001-01-01

    Laser-induced fluorescence detection is one of the most sensitive detection techniques and it has found enormous applications in various areas. The purpose of this research was to develop detection approaches based on laser-induced fluorescence detection in two different areas, heterogeneous catalysts screening and single cell study. First, we introduced laser-induced imaging (LIFI) as a high-throughput screening technique for heterogeneous catalysts to explore the use of this high-throughput screening technique in discovery and study of various heterogeneous catalyst systems. This scheme is based on the fact that the creation or the destruction of chemical bonds alters the fluorescence properties of suitably designed molecules. By irradiating the region immediately above the catalytic surface with a laser, the fluorescence intensity of a selected product or reactant can be imaged by a charge-coupled device (CCD) camera to follow the catalytic activity as a function of time and space. By screening the catalytic activity of vanadium pentoxide catalysts in oxidation of naphthalene, we demonstrated LIFI has good detection performance and the spatial and temporal resolution needed for high-throughput screening of heterogeneous catalysts. The sample packing density can reach up to 250 x 250 subunits/cm2 for 40-μm wells. This experimental set-up also can screen solid catalysts via near infrared thermography detection.

  19. Laser-Induced Fluorescence Detection in High-Throughput Screening of Heterogeneous Catalysts and Single Cells Analysis

    International Nuclear Information System (INIS)

    Hui Su

    2001-01-01

    Laser-induced fluorescence detection is one of the most sensitive detection techniques and it has found enormous applications in various areas. The purpose of this research was to develop detection approaches based on laser-induced fluorescence detection in two different areas, heterogeneous catalysts screening and single cell study. First, we introduced laser-induced imaging (LIFI) as a high-throughput screening technique for heterogeneous catalysts to explore the use of this high-throughput screening technique in discovery and study of various heterogeneous catalyst systems. This scheme is based on the fact that the creation or the destruction of chemical bonds alters the fluorescence properties of suitably designed molecules. By irradiating the region immediately above the catalytic surface with a laser, the fluorescence intensity of a selected product or reactant can be imaged by a charge-coupled device (CCD) camera to follow the catalytic activity as a function of time and space. By screening the catalytic activity of vanadium pentoxide catalysts in oxidation of naphthalene, we demonstrated LIFI has good detection performance and the spatial and temporal resolution needed for high-throughput screening of heterogeneous catalysts. The sample packing density can reach up to 250 x 250 subunits/cm(sub 2) for 40-(micro)m wells. This experimental set-up also can screen solid catalysts via near infrared thermography detection

  20. Probing protein phosphatase substrate binding

    DEFF Research Database (Denmark)

    Højlys-Larsen, Kim B.; Sørensen, Kasper Kildegaard; Jensen, Knud Jørgen

    2012-01-01

    Proteomics and high throughput analysis for systems biology can benefit significantly from solid-phase chemical tools for affinity pull-down of proteins from complex mixtures. Here we report the application of solid-phase synthesis of phosphopeptides for pull-down and analysis of the affinity...... profile of the integrin-linked kinase associated phosphatase (ILKAP), a member of the protein phosphatase 2C (PP2C) family. Phosphatases can potentially dephosphorylate these phosphopeptide substrates but, interestingly, performing the binding studies at 4 °C allowed efficient binding to phosphopeptides......, without the need for phosphopeptide mimics or phosphatase inhibitors. As no proven ILKAP substrates were available, we selected phosphopeptide substrates among known PP2Cδ substrates including the protein kinases: p38, ATM, Chk1, Chk2 and RSK2 and synthesized directly on PEGA solid supports through a BAL...

  1. A continuous high-throughput bioparticle sorter based on 3D traveling-wave dielectrophoresis.

    Science.gov (United States)

    Cheng, I-Fang; Froude, Victoria E; Zhu, Yingxi; Chang, Hsueh-Chia; Chang, Hsien-Chang

    2009-11-21

    We present a high throughput (maximum flow rate approximately 10 microl/min or linear velocity approximately 3 mm/s) continuous bio-particle sorter based on 3D traveling-wave dielectrophoresis (twDEP) at an optimum AC frequency of 500 kHz. The high throughput sorting is achieved with a sustained twDEP particle force normal to the continuous through-flow, which is applied over the entire chip by a single 3D electrode array. The design allows continuous fractionation of micron-sized particles into different downstream sub-channels based on differences in their twDEP mobility on both sides of the cross-over. Conventional DEP is integrated upstream to focus the particles into a single levitated queue to allow twDEP sorting by mobility difference and to minimize sedimentation and field-induced lysis. The 3D electrode array design minimizes the offsetting effect of nDEP (negative DEP with particle force towards regions with weak fields) on twDEP such that both forces increase monotonically with voltage to further increase the throughput. Effective focusing and separation of red blood cells from debris-filled heterogeneous samples are demonstrated, as well as size-based separation of poly-dispersed liposome suspensions into two distinct bands at 2.3 to 4.6 microm and 1.5 to 2.7 microm, at the highest throughput recorded in hand-held chips of 6 microl/min.

  2. Throughput Analysis of Large Wireless Networks with Regular Topologies

    Directory of Open Access Journals (Sweden)

    Hong Kezhu

    2007-01-01

    Full Text Available The throughput of large wireless networks with regular topologies is analyzed under two medium-access control schemes: synchronous array method (SAM and slotted ALOHA. The regular topologies considered are square, hexagon, and triangle. Both nonfading channels and Rayleigh fading channels are examined. Furthermore, both omnidirectional antennas and directional antennas are considered. Our analysis shows that the SAM leads to a much higher network throughput than the slotted ALOHA. The network throughput in this paper is measured in either bits-hops per second per Hertz per node or bits-meters per second per Hertz per node. The exact connection between the two measures is shown for each topology. With these two fundamental units, the network throughput shown in this paper can serve as a reliable benchmark for future works on network throughput of large networks.

  3. Throughput Analysis of Large Wireless Networks with Regular Topologies

    Directory of Open Access Journals (Sweden)

    Kezhu Hong

    2007-04-01

    Full Text Available The throughput of large wireless networks with regular topologies is analyzed under two medium-access control schemes: synchronous array method (SAM and slotted ALOHA. The regular topologies considered are square, hexagon, and triangle. Both nonfading channels and Rayleigh fading channels are examined. Furthermore, both omnidirectional antennas and directional antennas are considered. Our analysis shows that the SAM leads to a much higher network throughput than the slotted ALOHA. The network throughput in this paper is measured in either bits-hops per second per Hertz per node or bits-meters per second per Hertz per node. The exact connection between the two measures is shown for each topology. With these two fundamental units, the network throughput shown in this paper can serve as a reliable benchmark for future works on network throughput of large networks.

  4. Qgui: A high-throughput interface for automated setup and analysis of free energy calculations and empirical valence bond simulations in biological systems.

    Science.gov (United States)

    Isaksen, Geir Villy; Andberg, Tor Arne Heim; Åqvist, Johan; Brandsdal, Bjørn Olav

    2015-07-01

    Structural information and activity data has increased rapidly for many protein targets during the last decades. In this paper, we present a high-throughput interface (Qgui) for automated free energy and empirical valence bond (EVB) calculations that use molecular dynamics (MD) simulations for conformational sampling. Applications to ligand binding using both the linear interaction energy (LIE) method and the free energy perturbation (FEP) technique are given using the estrogen receptor (ERα) as a model system. Examples of free energy profiles obtained using the EVB method for the rate-limiting step of the enzymatic reaction catalyzed by trypsin are also shown. In addition, we present calculation of high-precision Arrhenius plots to obtain the thermodynamic activation enthalpy and entropy with Qgui from running a large number of EVB simulations. Copyright © 2015 Elsevier Inc. All rights reserved.

  5. Quantitative characterization of conformational-specific protein-DNA binding using a dual-spectral interferometric imaging biosensor

    Science.gov (United States)

    Zhang, Xirui; Daaboul, George G.; Spuhler, Philipp S.; Dröge, Peter; Ünlü, M. Selim

    2016-03-01

    DNA-binding proteins play crucial roles in the maintenance and functions of the genome and yet, their specific binding mechanisms are not fully understood. Recently, it was discovered that DNA-binding proteins recognize specific binding sites to carry out their functions through an indirect readout mechanism by recognizing and capturing DNA conformational flexibility and deformation. High-throughput DNA microarray-based methods that provide large-scale protein-DNA binding information have shown effective and comprehensive analysis of protein-DNA binding affinities, but do not provide information of DNA conformational changes in specific protein-DNA complexes. Building on the high-throughput capability of DNA microarrays, we demonstrate a quantitative approach that simultaneously measures the amount of protein binding to DNA and nanometer-scale DNA conformational change induced by protein binding in a microarray format. Both measurements rely on spectral interferometry on a layered substrate using a single optical instrument in two distinct modalities. In the first modality, we quantitate the amount of binding of protein to surface-immobilized DNA in each DNA spot using a label-free spectral reflectivity technique that accurately measures the surface densities of protein and DNA accumulated on the substrate. In the second modality, for each DNA spot, we simultaneously measure DNA conformational change using a fluorescence vertical sectioning technique that determines average axial height of fluorophores tagged to specific nucleotides of the surface-immobilized DNA. The approach presented in this paper, when combined with current high-throughput DNA microarray-based technologies, has the potential to serve as a rapid and simple method for quantitative and large-scale characterization of conformational specific protein-DNA interactions.DNA-binding proteins play crucial roles in the maintenance and functions of the genome and yet, their specific binding mechanisms are

  6. Entrapment of alpha1-acid glycoprotein in high-performance affinity columns for drug-protein binding studies.

    Science.gov (United States)

    Bi, Cong; Jackson, Abby; Vargas-Badilla, John; Li, Rong; Rada, Giana; Anguizola, Jeanethe; Pfaunmiller, Erika; Hage, David S

    2016-05-15

    A slurry-based method was developed for the entrapment of alpha1-acid glycoprotein (AGP) for use in high-performance affinity chromatography to study drug interactions with this serum protein. Entrapment was achieved based on the physical containment of AGP in hydrazide-activated porous silica supports and by using mildly oxidized glycogen as a capping agent. The conditions needed for this process were examined and optimized. When this type of AGP column was used in binding studies, the association equilibrium constant (Ka) measured by frontal analysis at pH 7.4 and 37°C for carbamazepine with AGP was found to be 1.0 (±0.5)×10(5)M(-1), which agreed with a previously reported value of 1.0 (±0.1)×10(5)M(-1). Binding studies based on zonal elution were conducted for several other drugs with such columns, giving equilibrium constants that were consistent with literature values. An entrapped AGP column was also used in combination with a column containing entrapped HSA in a screening assay format to compare the binding of various drugs to AGP and HSA. These results also agreed with previous data that have been reported in literature for both of these proteins. The same entrapment method could be extended to other proteins and to the investigation of additional types of drug-protein interactions. Potential applications include the rapid quantitative analysis of biological interactions and the high-throughput screening of drug candidates for their binding to a given protein. Copyright © 2015 Elsevier B.V. All rights reserved.

  7. Combinatorial approach toward high-throughput analysis of direct methanol fuel cells.

    Science.gov (United States)

    Jiang, Rongzhong; Rong, Charles; Chu, Deryn

    2005-01-01

    A 40-member array of direct methanol fuel cells (with stationary fuel and convective air supplies) was generated by electrically connecting the fuel cells in series. High-throughput analysis of these fuel cells was realized by fast screening of voltages between the two terminals of a fuel cell at constant current discharge. A large number of voltage-current curves (200) were obtained by screening the voltages through multiple small-current steps. Gaussian distribution was used to statistically analyze the large number of experimental data. The standard deviation (sigma) of voltages of these fuel cells increased linearly with discharge current. The voltage-current curves at various fuel concentrations were simulated with an empirical equation of voltage versus current and a linear equation of sigma versus current. The simulated voltage-current curves fitted the experimental data well. With increasing methanol concentration from 0.5 to 4.0 M, the Tafel slope of the voltage-current curves (at sigma=0.0), changed from 28 to 91 mV.dec-1, the cell resistance from 2.91 to 0.18 Omega, and the power output from 3 to 18 mW.cm-2.

  8. NiftyPET: a High-throughput Software Platform for High Quantitative Accuracy and Precision PET Imaging and Analysis.

    Science.gov (United States)

    Markiewicz, Pawel J; Ehrhardt, Matthias J; Erlandsson, Kjell; Noonan, Philip J; Barnes, Anna; Schott, Jonathan M; Atkinson, David; Arridge, Simon R; Hutton, Brian F; Ourselin, Sebastien

    2018-01-01

    We present a standalone, scalable and high-throughput software platform for PET image reconstruction and analysis. We focus on high fidelity modelling of the acquisition processes to provide high accuracy and precision quantitative imaging, especially for large axial field of view scanners. All the core routines are implemented using parallel computing available from within the Python package NiftyPET, enabling easy access, manipulation and visualisation of data at any processing stage. The pipeline of the platform starts from MR and raw PET input data and is divided into the following processing stages: (1) list-mode data processing; (2) accurate attenuation coefficient map generation; (3) detector normalisation; (4) exact forward and back projection between sinogram and image space; (5) estimation of reduced-variance random events; (6) high accuracy fully 3D estimation of scatter events; (7) voxel-based partial volume correction; (8) region- and voxel-level image analysis. We demonstrate the advantages of this platform using an amyloid brain scan where all the processing is executed from a single and uniform computational environment in Python. The high accuracy acquisition modelling is achieved through span-1 (no axial compression) ray tracing for true, random and scatter events. Furthermore, the platform offers uncertainty estimation of any image derived statistic to facilitate robust tracking of subtle physiological changes in longitudinal studies. The platform also supports the development of new reconstruction and analysis algorithms through restricting the axial field of view to any set of rings covering a region of interest and thus performing fully 3D reconstruction and corrections using real data significantly faster. All the software is available as open source with the accompanying wiki-page and test data.

  9. Ethoscopes: An open platform for high-throughput ethomics.

    Directory of Open Access Journals (Sweden)

    Quentin Geissmann

    2017-10-01

    Full Text Available Here, we present the use of ethoscopes, which are machines for high-throughput analysis of behavior in Drosophila and other animals. Ethoscopes provide a software and hardware solution that is reproducible and easily scalable. They perform, in real-time, tracking and profiling of behavior by using a supervised machine learning algorithm, are able to deliver behaviorally triggered stimuli to flies in a feedback-loop mode, and are highly customizable and open source. Ethoscopes can be built easily by using 3D printing technology and rely on Raspberry Pi microcomputers and Arduino boards to provide affordable and flexible hardware. All software and construction specifications are available at http://lab.gilest.ro/ethoscope.

  10. Global Analysis of Photosynthesis Transcriptional Regulatory Networks

    Science.gov (United States)

    Imam, Saheed; Noguera, Daniel R.; Donohue, Timothy J.

    2014-01-01

    Photosynthesis is a crucial biological process that depends on the interplay of many components. This work analyzed the gene targets for 4 transcription factors: FnrL, PrrA, CrpK and MppG (RSP_2888), which are known or predicted to control photosynthesis in Rhodobacter sphaeroides. Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) identified 52 operons under direct control of FnrL, illustrating its regulatory role in photosynthesis, iron homeostasis, nitrogen metabolism and regulation of sRNA synthesis. Using global gene expression analysis combined with ChIP-seq, we mapped the regulons of PrrA, CrpK and MppG. PrrA regulates ∼34 operons encoding mainly photosynthesis and electron transport functions, while CrpK, a previously uncharacterized Crp-family protein, regulates genes involved in photosynthesis and maintenance of iron homeostasis. Furthermore, CrpK and FnrL share similar DNA binding determinants, possibly explaining our observation of the ability of CrpK to partially compensate for the growth defects of a ΔFnrL mutant. We show that the Rrf2 family protein, MppG, plays an important role in photopigment biosynthesis, as part of an incoherent feed-forward loop with PrrA. Our results reveal a previously unrealized, high degree of combinatorial regulation of photosynthetic genes and significant cross-talk between their transcriptional regulators, while illustrating previously unidentified links between photosynthesis and the maintenance of iron homeostasis. PMID:25503406

  11. Global analysis of photosynthesis transcriptional regulatory networks.

    Directory of Open Access Journals (Sweden)

    Saheed Imam

    2014-12-01

    Full Text Available Photosynthesis is a crucial biological process that depends on the interplay of many components. This work analyzed the gene targets for 4 transcription factors: FnrL, PrrA, CrpK and MppG (RSP_2888, which are known or predicted to control photosynthesis in Rhodobacter sphaeroides. Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq identified 52 operons under direct control of FnrL, illustrating its regulatory role in photosynthesis, iron homeostasis, nitrogen metabolism and regulation of sRNA synthesis. Using global gene expression analysis combined with ChIP-seq, we mapped the regulons of PrrA, CrpK and MppG. PrrA regulates ∼34 operons encoding mainly photosynthesis and electron transport functions, while CrpK, a previously uncharacterized Crp-family protein, regulates genes involved in photosynthesis and maintenance of iron homeostasis. Furthermore, CrpK and FnrL share similar DNA binding determinants, possibly explaining our observation of the ability of CrpK to partially compensate for the growth defects of a ΔFnrL mutant. We show that the Rrf2 family protein, MppG, plays an important role in photopigment biosynthesis, as part of an incoherent feed-forward loop with PrrA. Our results reveal a previously unrealized, high degree of combinatorial regulation of photosynthetic genes and significant cross-talk between their transcriptional regulators, while illustrating previously unidentified links between photosynthesis and the maintenance of iron homeostasis.

  12. IMB2026791, a Xanthone, Stimulates Cholesterol Efflux by Increasing the Binding of Apolipoprotein A-I to ATP-Binding Cassette Transporter A1

    Directory of Open Access Journals (Sweden)

    Zijian Xie

    2012-03-01

    Full Text Available It is known that the ATP-binding cassette transporter A1 (ABCA1 plays a major role in cholesterol homeostasis and high density lipoprotein (HDL metabolism. Several laboratories have demonstrated that ABCA1 binding to lipid-poor apolipoprotein A-I (apoA-I will mediate the assembly of nascent HDL and cellular cholesterol efflux, which suggests a possible receptor-ligand interaction between ABCA1 and apoA-I. In this study, a cell-based-ELISA-like high-throughput screening (HTS method was developed to identify the synthetic and natural compounds that can regulate binding activity of ABCA1 to apoA-I. The cell-based-ELISA-like high-throughput screen was conducted in a 96-well format using Chinese hamster ovary (CHO cells stably transfected with ABCA1 pIRE2-EGFP (Enhanced Green Fluorecence Protein expression vector and the known ABCA1 inhibitor glibenclamide as the antagonist control. From 2,600 compounds, a xanthone compound (IMB 2026791 was selected using this HTS assay, and it was proved as an apoA-I binding agonist to ABCA1 by a flow cytometry assay and western blot analysis. The [3H] cholesterol efflux assay of IMB2026791 treated ABCA1-CHO cells and PMA induced THP-1 macrophages (human acute monocytic leukemia cell further confirmed the compound as an accelerator of cholesterol efflux in a dose-dependent manner with an EC50 of 25.23 μM.

  13. High-throughput theoretical design of lithium battery materials

    International Nuclear Information System (INIS)

    Ling Shi-Gang; Gao Jian; Xiao Rui-Juan; Chen Li-Quan

    2016-01-01

    The rapid evolution of high-throughput theoretical design schemes to discover new lithium battery materials is reviewed, including high-capacity cathodes, low-strain cathodes, anodes, solid state electrolytes, and electrolyte additives. With the development of efficient theoretical methods and inexpensive computers, high-throughput theoretical calculations have played an increasingly important role in the discovery of new materials. With the help of automatic simulation flow, many types of materials can be screened, optimized and designed from a structural database according to specific search criteria. In advanced cell technology, new materials for next generation lithium batteries are of great significance to achieve performance, and some representative criteria are: higher energy density, better safety, and faster charge/discharge speed. (topical review)

  14. rMATS: robust and flexible detection of differential alternative splicing from replicate RNA-Seq data.

    Science.gov (United States)

    Shen, Shihao; Park, Juw Won; Lu, Zhi-xiang; Lin, Lan; Henry, Michael D; Wu, Ying Nian; Zhou, Qing; Xing, Yi

    2014-12-23

    Ultra-deep RNA sequencing (RNA-Seq) has become a powerful approach for genome-wide analysis of pre-mRNA alternative splicing. We previously developed multivariate analysis of transcript splicing (MATS), a statistical method for detecting differential alternative splicing between two RNA-Seq samples. Here we describe a new statistical model and computer program, replicate MATS (rMATS), designed for detection of differential alternative splicing from replicate RNA-Seq data. rMATS uses a hierarchical model to simultaneously account for sampling uncertainty in individual replicates and variability among replicates. In addition to the analysis of unpaired replicates, rMATS also includes a model specifically designed for paired replicates between sample groups. The hypothesis-testing framework of rMATS is flexible and can assess the statistical significance over any user-defined magnitude of splicing change. The performance of rMATS is evaluated by the analysis of simulated and real RNA-Seq data. rMATS outperformed two existing methods for replicate RNA-Seq data in all simulation settings, and RT-PCR yielded a high validation rate (94%) in an RNA-Seq dataset of prostate cancer cell lines. Our data also provide guiding principles for designing RNA-Seq studies of alternative splicing. We demonstrate that it is essential to incorporate biological replicates in the study design. Of note, pooling RNAs or merging RNA-Seq data from multiple replicates is not an effective approach to account for variability, and the result is particularly sensitive to outliers. The rMATS source code is freely available at rnaseq-mats.sourceforge.net/. As the popularity of RNA-Seq continues to grow, we expect rMATS will be useful for studies of alternative splicing in diverse RNA-Seq projects.

  15. Optical tools for high-throughput screening of abrasion resistance of combinatorial libraries of organic coatings

    Science.gov (United States)

    Potyrailo, Radislav A.; Chisholm, Bret J.; Olson, Daniel R.; Brennan, Michael J.; Molaison, Chris A.

    2002-02-01

    Design, validation, and implementation of an optical spectroscopic system for high-throughput analysis of combinatorially developed protective organic coatings are reported. Our approach replaces labor-intensive coating evaluation steps with an automated system that rapidly analyzes 8x6 arrays of coating elements that are deposited on a plastic substrate. Each coating element of the library is 10 mm in diameter and 2 to 5 micrometers thick. Performance of coatings is evaluated with respect to their resistance to wear abrasion because this parameter is one of the primary considerations in end-use applications. Upon testing, the organic coatings undergo changes that are impossible to quantitatively predict using existing knowledge. Coatings are abraded using industry-accepted abrasion test methods at single-or multiple-abrasion conditions, followed by high- throughput analysis of abrasion-induced light scatter. The developed automated system is optimized for the analysis of diffusively scattered light that corresponds to 0 to 30% haze. System precision of 0.1 to 2.5% relative standard deviation provides capability for the reliable ranking of coatings performance. While the system was implemented for high-throughput screening of combinatorially developed organic protective coatings for automotive applications, it can be applied to a variety of other applications where materials ranking can be achieved using optical spectroscopic tools.

  16. COMPUTER APPROACHES TO WHEAT HIGH-THROUGHPUT PHENOTYPING

    Directory of Open Access Journals (Sweden)

    Afonnikov D.

    2012-08-01

    Full Text Available The growing need for rapid and accurate approaches for large-scale assessment of phenotypic characters in plants becomes more and more obvious in the studies looking into relationships between genotype and phenotype. This need is due to the advent of high throughput methods for analysis of genomes. Nowadays, any genetic experiment involves data on thousands and dozens of thousands of plants. Traditional ways of assessing most phenotypic characteristics (those with reliance on the eye, the touch, the ruler are little effective on samples of such sizes. Modern approaches seek to take advantage of automated phenotyping, which warrants a much more rapid data acquisition, higher accuracy of the assessment of phenotypic features, measurement of new parameters of these features and exclusion of human subjectivity from the process. Additionally, automation allows measurement data to be rapidly loaded into computer databases, which reduces data processing time.In this work, we present the WheatPGE information system designed to solve the problem of integration of genotypic and phenotypic data and parameters of the environment, as well as to analyze the relationships between the genotype and phenotype in wheat. The system is used to consolidate miscellaneous data on a plant for storing and processing various morphological traits and genotypes of wheat plants as well as data on various environmental factors. The system is available at www.wheatdb.org. Its potential in genetic experiments has been demonstrated in high-throughput phenotyping of wheat leaf pubescence.

  17. High-Throughput Block Optical DNA Sequence Identification.

    Science.gov (United States)

    Sagar, Dodderi Manjunatha; Korshoj, Lee Erik; Hanson, Katrina Bethany; Chowdhury, Partha Pratim; Otoupal, Peter Britton; Chatterjee, Anushree; Nagpal, Prashant

    2018-01-01

    Optical techniques for molecular diagnostics or DNA sequencing generally rely on small molecule fluorescent labels, which utilize light with a wavelength of several hundred nanometers for detection. Developing a label-free optical DNA sequencing technique will require nanoscale focusing of light, a high-throughput and multiplexed identification method, and a data compression technique to rapidly identify sequences and analyze genomic heterogeneity for big datasets. Such a method should identify characteristic molecular vibrations using optical spectroscopy, especially in the "fingerprinting region" from ≈400-1400 cm -1 . Here, surface-enhanced Raman spectroscopy is used to demonstrate label-free identification of DNA nucleobases with multiplexed 3D plasmonic nanofocusing. While nanometer-scale mode volumes prevent identification of single nucleobases within a DNA sequence, the block optical technique can identify A, T, G, and C content in DNA k-mers. The content of each nucleotide in a DNA block can be a unique and high-throughput method for identifying sequences, genes, and other biomarkers as an alternative to single-letter sequencing. Additionally, coupling two complementary vibrational spectroscopy techniques (infrared and Raman) can improve block characterization. These results pave the way for developing a novel, high-throughput block optical sequencing method with lossy genomic data compression using k-mer identification from multiplexed optical data acquisition. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  18. A method for quantitative analysis of standard and high-throughput qPCR expression data based on input sample quantity.

    Directory of Open Access Journals (Sweden)

    Mateusz G Adamski

    Full Text Available Over the past decade rapid advances have occurred in the understanding of RNA expression and its regulation. Quantitative polymerase chain reactions (qPCR have become the gold standard for quantifying gene expression. Microfluidic next generation, high throughput qPCR now permits the detection of transcript copy number in thousands of reactions simultaneously, dramatically increasing the sensitivity over standard qPCR. Here we present a gene expression analysis method applicable to both standard polymerase chain reactions (qPCR and high throughput qPCR. This technique is adjusted to the input sample quantity (e.g., the number of cells and is independent of control gene expression. It is efficiency-corrected and with the use of a universal reference sample (commercial complementary DNA (cDNA permits the normalization of results between different batches and between different instruments--regardless of potential differences in transcript amplification efficiency. Modifications of the input quantity method include (1 the achievement of absolute quantification and (2 a non-efficiency corrected analysis. When compared to other commonly used algorithms the input quantity method proved to be valid. This method is of particular value for clinical studies of whole blood and circulating leukocytes where cell counts are readily available.

  19. A simple, high throughput method to locate single copy sequences from Bacterial Artificial Chromosome (BAC libraries using High Resolution Melt analysis

    Directory of Open Access Journals (Sweden)

    Caligari Peter DS

    2010-05-01

    Full Text Available Abstract Background The high-throughput anchoring of genetic markers into contigs is required for many ongoing physical mapping projects. Multidimentional BAC pooling strategies for PCR-based screening of large insert libraries is a widely used alternative to high density filter hybridisation of bacterial colonies. To date, concerns over reliability have led most if not all groups engaged in high throughput physical mapping projects to favour BAC DNA isolation prior to amplification by conventional PCR. Results Here, we report the first combined use of Multiplex Tandem PCR (MT-PCR and High Resolution Melt (HRM analysis on bacterial stocks of BAC library superpools as a means of rapidly anchoring markers to BAC colonies and thereby to integrate genetic and physical maps. We exemplify the approach using a BAC library of the model plant Arabidopsis thaliana. Super pools of twenty five 384-well plates and two-dimension matrix pools of the BAC library were prepared for marker screening. The entire procedure only requires around 3 h to anchor one marker. Conclusions A pre-amplification step during MT-PCR allows high multiplexing and increases the sensitivity and reliability of subsequent HRM discrimination. This simple gel-free protocol is more reliable, faster and far less costly than conventional PCR screening. The option to screen in parallel 3 genetic markers in one MT-PCR-HRM reaction using templates from directly pooled bacterial stocks of BAC-containing bacteria further reduces time for anchoring markers in physical maps of species with large genomes.

  20. Marine Invertebrate Xenobiotic-Activated Nuclear Receptors: Their Application as Sensor Elements in High-Throughput Bioassays for Marine Bioactive Compounds

    Directory of Open Access Journals (Sweden)

    Ingrid Richter

    2014-11-01

    Full Text Available Developing high-throughput assays to screen marine extracts for bioactive compounds presents both conceptual and technical challenges. One major challenge is to develop assays that have well-grounded ecological and evolutionary rationales. In this review we propose that a specific group of ligand-activated transcription factors are particularly well-suited to act as sensors in such bioassays. More specifically, xenobiotic-activated nuclear receptors (XANRs regulate transcription of genes involved in xenobiotic detoxification. XANR ligand-binding domains (LBDs may adaptively evolve to bind those bioactive, and potentially toxic, compounds to which organisms are normally exposed to through their specific diets. A brief overview of the function and taxonomic distribution of both vertebrate and invertebrate XANRs is first provided. Proof-of-concept experiments are then described which confirm that a filter-feeding marine invertebrate XANR LBD is activated by marine bioactive compounds. We speculate that increasing access to marine invertebrate genome sequence data, in combination with the expression of functional recombinant marine invertebrate XANR LBDs, will facilitate the generation of high-throughput bioassays/biosensors of widely differing specificities, but all based on activation of XANR LBDs. Such assays may find application in screening marine extracts for bioactive compounds that could act as drug lead compounds.

  1. High Throughput In vivo Analysis of Plant Leaf Chemical Properties Using Hyperspectral Imaging.

    Science.gov (United States)

    Pandey, Piyush; Ge, Yufeng; Stoerger, Vincent; Schnable, James C

    2017-01-01

    Image-based high-throughput plant phenotyping in greenhouse has the potential to relieve the bottleneck currently presented by phenotypic scoring which limits the throughput of gene discovery and crop improvement efforts. Numerous studies have employed automated RGB imaging to characterize biomass and growth of agronomically important crops. The objective of this study was to investigate the utility of hyperspectral imaging for quantifying chemical properties of maize and soybean plants in vivo . These properties included leaf water content, as well as concentrations of macronutrients nitrogen (N), phosphorus (P), potassium (K), magnesium (Mg), calcium (Ca), and sulfur (S), and micronutrients sodium (Na), iron (Fe), manganese (Mn), boron (B), copper (Cu), and zinc (Zn). Hyperspectral images were collected from 60 maize and 60 soybean plants, each subjected to varying levels of either water deficit or nutrient limitation stress with the goal of creating a wide range of variation in the chemical properties of plant leaves. Plants were imaged on an automated conveyor belt system using a hyperspectral imager with a spectral range from 550 to 1,700 nm. Images were processed to extract reflectance spectrum from each plant and partial least squares regression models were developed to correlate spectral data with chemical data. Among all the chemical properties investigated, water content was predicted with the highest accuracy [ R 2 = 0.93 and RPD (Ratio of Performance to Deviation) = 3.8]. All macronutrients were also quantified satisfactorily ( R 2 from 0.69 to 0.92, RPD from 1.62 to 3.62), with N predicted best followed by P, K, and S. The micronutrients group showed lower prediction accuracy ( R 2 from 0.19 to 0.86, RPD from 1.09 to 2.69) than the macronutrient groups. Cu and Zn were best predicted, followed by Fe and Mn. Na and B were the only two properties that hyperspectral imaging was not able to quantify satisfactorily ( R 2 plant chemical traits. Future

  2. High throughput salt separation from uranium deposits

    Energy Technology Data Exchange (ETDEWEB)

    Kwon, S.W.; Park, K.M.; Kim, J.G.; Kim, I.T.; Park, S.B., E-mail: swkwon@kaeri.re.kr [Korea Atomic Energy Research Inst. (Korea, Republic of)

    2014-07-01

    It is very important to increase the throughput of the salt separation system owing to the high uranium content of spent nuclear fuel and high salt fraction of uranium dendrites in pyroprocessing. Multilayer porous crucible system was proposed to increase a throughput of the salt distiller in this study. An integrated sieve-crucible assembly was also investigated for the practical use of the porous crucible system. The salt evaporation behaviors were compared between the conventional nonporous crucible and the porous crucible. Two step weight reductions took place in the porous crucible, whereas the salt weight reduced only at high temperature by distillation in a nonporous crucible. The first weight reduction in the porous crucible was caused by the liquid salt penetrated out through the perforated crucible during the temperature elevation until the distillation temperature. Multilayer porous crucibles have a benefit to expand the evaporation surface area. (author)

  3. The monoclonal S9.6 antibody exhibits highly variable binding affinities towards different R-loop sequences.

    Directory of Open Access Journals (Sweden)

    Fabian König

    Full Text Available The monoclonal antibody S9.6 is a widely-used tool to purify, analyse and quantify R-loop structures in cells. A previous study using the surface plasmon resonance technology and a single-chain variable fragment (scFv of S9.6 showed high affinity (0.6 nM for DNA-RNA and also a high affinity (2.7 nM for RNA-RNA hybrids. We used the microscale thermophoresis method allowing surface independent interaction studies and electromobility shift assays to evaluate additional RNA-DNA hybrid sequences and to quantify the binding affinities of the S9.6 antibody with respect to distinct sequences and their GC-content. Our results confirm high affinity binding to previously analysed sequences, but reveals that binding affinities are highly sequence specific. Our study presents R-loop sequences that independent of GC-content and in different sequence variations exhibit either no binding, binding affinities in the micromolar range and as well high affinity binding in the nanomolar range. Our study questions the usefulness of the S9.6 antibody in the quantitative analysis of R-loop sequences in vivo.

  4. A bioimage informatics platform for high-throughput embryo phenotyping.

    Science.gov (United States)

    Brown, James M; Horner, Neil R; Lawson, Thomas N; Fiegel, Tanja; Greenaway, Simon; Morgan, Hugh; Ring, Natalie; Santos, Luis; Sneddon, Duncan; Teboul, Lydia; Vibert, Jennifer; Yaikhom, Gagarine; Westerberg, Henrik; Mallon, Ann-Marie

    2018-01-01

    High-throughput phenotyping is a cornerstone of numerous functional genomics projects. In recent years, imaging screens have become increasingly important in understanding gene-phenotype relationships in studies of cells, tissues and whole organisms. Three-dimensional (3D) imaging has risen to prominence in the field of developmental biology for its ability to capture whole embryo morphology and gene expression, as exemplified by the International Mouse Phenotyping Consortium (IMPC). Large volumes of image data are being acquired by multiple institutions around the world that encompass a range of modalities, proprietary software and metadata. To facilitate robust downstream analysis, images and metadata must be standardized to account for these differences. As an open scientific enterprise, making the data readily accessible is essential so that members of biomedical and clinical research communities can study the images for themselves without the need for highly specialized software or technical expertise. In this article, we present a platform of software tools that facilitate the upload, analysis and dissemination of 3D images for the IMPC. Over 750 reconstructions from 80 embryonic lethal and subviable lines have been captured to date, all of which are openly accessible at mousephenotype.org. Although designed for the IMPC, all software is available under an open-source licence for others to use and develop further. Ongoing developments aim to increase throughput and improve the analysis and dissemination of image data. Furthermore, we aim to ensure that images are searchable so that users can locate relevant images associated with genes, phenotypes or human diseases of interest. © The Author 2016. Published by Oxford University Press.

  5. Network analysis of ChIP-Seq data reveals key genes in prostate cancer.

    Science.gov (United States)

    Zhang, Yu; Huang, Zhen; Zhu, Zhiqiang; Liu, Jianwei; Zheng, Xin; Zhang, Yuhai

    2014-09-03

    Prostate cancer (PC) is the second most common cancer among men in the United States, and it imposes a considerable threat to human health. A deep understanding of its underlying molecular mechanisms is the premise for developing effective targeted therapies. Recently, deep transcriptional sequencing has been used as an effective genomic assay to obtain insights into diseases and may be helpful in the study of PC. In present study, ChIP-Seq data for PC and normal samples were compared, and differential peaks identified, based upon fold changes (with P-values calculated with t-tests). Annotations of these peaks were performed. Protein-protein interaction (PPI) network analysis was performed with BioGRID and constructed with Cytoscape, following which the highly connected genes were screened. We obtained a total of 5,570 differential peaks, including 3,726 differentially enriched peaks in tumor samples and 1,844 differentially enriched peaks in normal samples. There were eight significant regions of the peaks. The intergenic region possessed the highest score (51%), followed by intronic (31%) and exonic (11%) regions. The analysis revealed the top 35 highly connected genes, which comprised 33 differential genes (such as YWHAQ, tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein and θ polypeptide) from ChIP-Seq data and 2 differential genes retrieved from the PPI network: UBA52 (ubiquitin A-52 residue ribosomal protein fusion product (1) and SUMO2 (SMT3 suppressor of mif two 3 homolog (2) . Our findings regarding potential PC-related genes increase the understanding of PC and provides direction for future research.

  6. High throughput, low set-up time reconfigurable linear feedback shift registers

    NARCIS (Netherlands)

    Nas, R.J.M.; Berkel, van C.H.

    2010-01-01

    This paper presents a hardware design for a scalable, high throughput, configurable LFSR. High throughput is achieved by producing L consecutive outputs per clock cycle with a clock cycle period that, for practical cases, increases only logarithmically with the block size L and the length of the

  7. High throughput and accurate serum proteome profiling by integrated sample preparation technology and single-run data independent mass spectrometry analysis.

    Science.gov (United States)

    Lin, Lin; Zheng, Jiaxin; Yu, Quan; Chen, Wendong; Xing, Jinchun; Chen, Chenxi; Tian, Ruijun

    2018-03-01

    Mass spectrometry (MS)-based serum proteome analysis is extremely challenging due to its high complexity and dynamic range of protein abundances. Developing high throughput and accurate serum proteomic profiling approach capable of analyzing large cohorts is urgently needed for biomarker discovery. Herein, we report a streamlined workflow for fast and accurate proteomic profiling from 1μL of blood serum. The workflow combined an integrated technique for highly sensitive and reproducible sample preparation and a new data-independent acquisition (DIA)-based MS method. Comparing with standard data dependent acquisition (DDA) approach, the optimized DIA method doubled the number of detected peptides and proteins with better reproducibility. Without protein immunodepletion and prefractionation, the single-run DIA analysis enables quantitative profiling of over 300 proteins with 50min gradient time. The quantified proteins span more than five orders of magnitude of abundance range and contain over 50 FDA-approved disease markers. The workflow allowed us to analyze 20 serum samples per day, with about 358 protein groups per sample being identified. A proof-of-concept study on renal cell carcinoma (RCC) serum samples confirmed the feasibility of the workflow for large scale serum proteomic profiling and disease-related biomarker discovery. Blood serum or plasma is the predominant specimen for clinical proteomic studies while the analysis is extremely challenging for its high complexity. Many efforts had been made in the past for serum proteomics for maximizing protein identifications, whereas few have been concerned with throughput and reproducibility. Here, we establish a rapid, robust and high reproducible DIA-based workflow for streamlined serum proteomic profiling from 1μL serum. The workflow doesn't need protein depletion and pre-fractionation, while still being able to detect disease-relevant proteins accurately. The workflow is promising in clinical application

  8. High-throughput epitope identification for snakebite antivenom

    DEFF Research Database (Denmark)

    Engmark, Mikael; De Masi, Federico; Laustsen, Andreas Hougaard

    Insight into the epitopic recognition pattern for polyclonal antivenoms is a strong tool for accurate prediction of antivenom cross-reactivity and provides a basis for design of novel antivenoms. In this work, a high-throughput approach was applied to characterize linear epitopes in 966 individua...... toxins from pit vipers (Crotalidae) using the ICP Crotalidae antivenom. Due to an abundance of snake venom metalloproteinases and phospholipase A2s in the venoms used for production of the investigated antivenom, this study focuses on these toxin families.......Insight into the epitopic recognition pattern for polyclonal antivenoms is a strong tool for accurate prediction of antivenom cross-reactivity and provides a basis for design of novel antivenoms. In this work, a high-throughput approach was applied to characterize linear epitopes in 966 individual...

  9. DaMiRseq-an R/Bioconductor package for data mining of RNA-Seq data: normalization, feature selection and classification.

    Science.gov (United States)

    Chiesa, Mattia; Colombo, Gualtiero I; Piacentini, Luca

    2018-04-15

    RNA-Seq is becoming the technique of choice for high-throughput transcriptome profiling, which, besides class comparison for differential expression, promises to be an effective and powerful tool for biomarker discovery. However, a systematic analysis of high-dimensional genomic data is a demanding task for such a purpose. DaMiRseq offers an organized, flexible and convenient framework to remove noise and bias, select the most informative features and perform accurate classification. DaMiRseq is developed for the R environment (R ≥ 3.4) and is released under GPL (≥2) License. The package runs on Windows, Linux and Macintosh operating systems and is freely available to non-commercial users at the Bioconductor open-source, open-development software project repository (https://bioconductor.org/packages/DaMiRseq/). In compliance with Bioconductor standards, the authors ensure stable package maintenance through software and documentation updates. luca.piacentini@ccfm.it. Supplementary data are available at Bioinformatics online.

  10. High-throughput analysis of ammonia oxidiser community composition via a novel, amoA-based functional gene array.

    Directory of Open Access Journals (Sweden)

    Guy C J Abell

    Full Text Available Advances in microbial ecology research are more often than not limited by the capabilities of available methodologies. Aerobic autotrophic nitrification is one of the most important and well studied microbiological processes in terrestrial and aquatic ecosystems. We have developed and validated a microbial diagnostic microarray based on the ammonia-monooxygenase subunit A (amoA gene, enabling the in-depth analysis of the community structure of bacterial and archaeal ammonia oxidisers. The amoA microarray has been successfully applied to analyse nitrifier diversity in marine, estuarine, soil and wastewater treatment plant environments. The microarray has moderate costs for labour and consumables and enables the analysis of hundreds of environmental DNA or RNA samples per week per person. The array has been thoroughly validated with a range of individual and complex targets (amoA clones and environmental samples, respectively, combined with parallel analysis using traditional sequencing methods. The moderate cost and high throughput of the microarray makes it possible to adequately address broader questions of the ecology of microbial ammonia oxidation requiring high sample numbers and high resolution of the community composition.

  11. WormSizer: high-throughput analysis of nematode size and shape.

    Directory of Open Access Journals (Sweden)

    Brad T Moore

    Full Text Available The fundamental phenotypes of growth rate, size and morphology are the result of complex interactions between genotype and environment. We developed a high-throughput software application, WormSizer, which computes size and shape of nematodes from brightfield images. Existing methods for estimating volume either coarsely model the nematode as a cylinder or assume the worm shape or opacity is invariant. Our estimate is more robust to changes in morphology or optical density as it only assumes radial symmetry. This open source software is written as a plugin for the well-known image-processing framework Fiji/ImageJ. It may therefore be extended easily. We evaluated the technical performance of this framework, and we used it to analyze growth and shape of several canonical Caenorhabditis elegans mutants in a developmental time series. We confirm quantitatively that a Dumpy (Dpy mutant is short and fat and that a Long (Lon mutant is long and thin. We show that daf-2 insulin-like receptor mutants are larger than wild-type upon hatching but grow slow, and WormSizer can distinguish dauer larvae from normal larvae. We also show that a Small (Sma mutant is actually smaller than wild-type at all stages of larval development. WormSizer works with Uncoordinated (Unc and Roller (Rol mutants as well, indicating that it can be used with mutants despite behavioral phenotypes. We used our complete data set to perform a power analysis, giving users a sense of how many images are needed to detect different effect sizes. Our analysis confirms and extends on existing phenotypic characterization of well-characterized mutants, demonstrating the utility and robustness of WormSizer.

  12. High-throughput quantitative biochemical characterization of algal biomass by NIR spectroscopy; multiple linear regression and multivariate linear regression analysis.

    Science.gov (United States)

    Laurens, L M L; Wolfrum, E J

    2013-12-18

    One of the challenges associated with microalgal biomass characterization and the comparison of microalgal strains and conversion processes is the rapid determination of the composition of algae. We have developed and applied a high-throughput screening technology based on near-infrared (NIR) spectroscopy for the rapid and accurate determination of algal biomass composition. We show that NIR spectroscopy can accurately predict the full composition using multivariate linear regression analysis of varying lipid, protein, and carbohydrate content of algal biomass samples from three strains. We also demonstrate a high quality of predictions of an independent validation set. A high-throughput 96-well configuration for spectroscopy gives equally good prediction relative to a ring-cup configuration, and thus, spectra can be obtained from as little as 10-20 mg of material. We found that lipids exhibit a dominant, distinct, and unique fingerprint in the NIR spectrum that allows for the use of single and multiple linear regression of respective wavelengths for the prediction of the biomass lipid content. This is not the case for carbohydrate and protein content, and thus, the use of multivariate statistical modeling approaches remains necessary.

  13. MITIE: Simultaneous RNA-Seq-based transcript identification and quantification in multiple samples.

    Science.gov (United States)

    Behr, Jonas; Kahles, André; Zhong, Yi; Sreedharan, Vipin T; Drewe, Philipp; Rätsch, Gunnar

    2013-10-15

    High-throughput sequencing of mRNA (RNA-Seq) has led to tremendous improvements in the detection of expressed genes and reconstruction of RNA transcripts. However, the extensive dynamic range of gene expression, technical limitations and biases, as well as the observed complexity of the transcriptional landscape, pose profound computational challenges for transcriptome reconstruction. We present the novel framework MITIE (Mixed Integer Transcript IdEntification) for simultaneous transcript reconstruction and quantification. We define a likelihood function based on the negative binomial distribution, use a regularization approach to select a few transcripts collectively explaining the observed read data and show how to find the optimal solution using Mixed Integer Programming. MITIE can (i) take advantage of known transcripts, (ii) reconstruct and quantify transcripts simultaneously in multiple samples, and (iii) resolve the location of multi-mapping reads. It is designed for genome- and assembly-based transcriptome reconstruction. We present an extensive study based on realistic simulated RNA-Seq data. When compared with state-of-the-art approaches, MITIE proves to be significantly more sensitive and overall more accurate. Moreover, MITIE yields substantial performance gains when used with multiple samples. We applied our system to 38 Drosophila melanogaster modENCODE RNA-Seq libraries and estimated the sensitivity of reconstructing omitted transcript annotations and the specificity with respect to annotated transcripts. Our results corroborate that a well-motivated objective paired with appropriate optimization techniques lead to significant improvements over the state-of-the-art in transcriptome reconstruction. MITIE is implemented in C++ and is available from http://bioweb.me/mitie under the GPL license.

  14. High Throughout Synthesis and Screening for Agents Inhibiting Androgen Receptor Mediated Gene Transcription

    National Research Council Canada - National Science Library

    Boger, Dale

    2003-01-01

    .... This entails the high throughput synthesis of DNA binding agents related to distamycin, their screening for binding to androgen response elements using a new high throughput DNA binding screen...

  15. Reconstitution of high-affinity opioid agonist binding in brain membranes

    Energy Technology Data Exchange (ETDEWEB)

    Remmers, A.E.; Medzihradsky, F. (Univ. of Michigan Medical School, Ann Arbor (United States))

    1991-03-15

    In synaptosomal membranes from rat brain cortex, the {mu} selective agonist ({sup 3}H)dihydromorphine in the absence of sodium, and the nonselective antagonist ({sup 3}H)naltrexone in the presence of sodium, bound to two populations of opioid receptor sites with K{sub d} values of 0.69 and 8.7 nM for dihydromorphine, and 0.34 and 5.5 nM for naltrexone. The addition of 5 {mu}M guanosine 5{prime}-({gamma}-thio)triphosphate (GTP({gamma}S)) strongly reduced high-affinity agonist but not antagonist binding. Exposure of the membranes to high pH reduced the number of GTP({gamma}-{sup 35}S) binding sites by 90% and low K{sub m}, opioid-sensitive GTPase activity by 95%. In these membranes, high-affinity agonist binding was abolished and modulation of residual binding by GTP({gamma}S) was diminished. Alkali treatment of the glioma cell membranes prior to fusion inhibited most of the low K{sub m} GTPase activity and prevented the reconstitution of agonist binding. The results show that high-affinity opioid agonist binding reflects the ligand-occupied receptor - guanine nucleotide binding protein complex.

  16. A Sensitive in Vitro High-Throughput Screen To Identify Pan-filoviral Replication Inhibitors Targeting the VP35–NP Interface

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Gai; Nash, Peter J.; Johnson, Britney; Pietzsch, Colette; Ilagan, Ma. Xenia G.; Bukreyev, Alexander; Basler, Christopher F.; Bowlin, Terry L.; Moir, Donald T.; Leung, Daisy W.; Amarasinghe, Gaya K. (WU-MED); (GSU); (Texas-MED); (Microbiotix)

    2017-01-24

    The 2014 Ebola outbreak in West Africa, the largest outbreak on record, highlighted the need for novel approaches to therapeutics targeting Ebola virus (EBOV). Within the EBOV replication complex, the interaction between polymerase cofactor, viral protein 35 (VP35), and nucleoprotein (NP) is critical for viral RNA synthesis. We recently identified a peptide at the N-terminus of VP35 (termed NPBP) that is sufficient for interaction with NP and suppresses EBOV replication, suggesting that the NPBP binding pocket can serve as a potential drug target. Here we describe the development and validation of a sensitive high-throughput screen (HTS) using a fluorescence polarization assay. Initial hits from this HTS include the FDA-approved compound tolcapone, whose potency against EBOV infection was validated in a nonfluorescent secondary assay. High conservation of the NP–VP35 interface among filoviruses suggests that this assay has the capacity to identify pan-filoviral inhibitors for development as antivirals.

  17. Insight into biases and sequencing errors for amplicon sequencing with the Illumina MiSeq platform.

    Science.gov (United States)

    Schirmer, Melanie; Ijaz, Umer Z; D'Amore, Rosalinda; Hall, Neil; Sloan, William T; Quince, Christopher

    2015-03-31

    With read lengths of currently up to 2 × 300 bp, high throughput and low sequencing costs Illumina's MiSeq is becoming one of the most utilized sequencing platforms worldwide. The platform is manageable and affordable even for smaller labs. This enables quick turnaround on a broad range of applications such as targeted gene sequencing, metagenomics, small genome sequencing and clinical molecular diagnostics. However, Illumina error profiles are still poorly understood and programs are therefore not designed for the idiosyncrasies of Illumina data. A better knowledge of the error patterns is essential for sequence analysis and vital if we are to draw valid conclusions. Studying true genetic variation in a population sample is fundamental for understanding diseases, evolution and origin. We conducted a large study on the error patterns for the MiSeq based on 16S rRNA amplicon sequencing data. We tested state-of-the-art library preparation methods for amplicon sequencing and showed that the library preparation method and the choice of primers are the most significant sources of bias and cause distinct error patterns. Furthermore we tested the efficiency of various error correction strategies and identified quality trimming (Sickle) combined with error correction (BayesHammer) followed by read overlapping (PANDAseq) as the most successful approach, reducing substitution error rates on average by 93%. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

  18. Receptor-based high-throughput screening and identification of estrogens in dietary supplements using bioaffinity liquid-chromatography ion mobility mass spectrometry.

    Science.gov (United States)

    Aqai, Payam; Blesa, Natalia Gómez; Major, Hilary; Pedotti, Mattia; Varani, Luca; Ferrero, Valentina E V; Haasnoot, Willem; Nielen, Michel W F

    2013-11-01

    A high-throughput bioaffinity liquid chromatography-mass spectrometry (BioMS) approach was developed and applied for the screening and identification of recombinant human estrogen receptor α (ERα) ligands in dietary supplements. For screening, a semi-automated mass spectrometric ligand binding assay was developed applying (13)C2, (15) N-tamoxifen as non-radioactive label and fast ultra-high-performance-liquid chromatography-electrospray ionisation-triple-quadrupole-MS (UPLC-QqQ-MS), operated in the single reaction monitoring mode, as a readout system. Binding of the label to ERα-coated paramagnetic microbeads was inhibited by competing estrogens in the sample extract yielding decreased levels of the label in UPLC-QqQ-MS. The label showed high ionisation efficiency in positive electrospray ionisation (ESI) mode, so the developed BioMS approach is able to screen for estrogens in dietary supplements despite their poor ionisation efficiency in both positive and negative ESI modes. The assay was performed in a 96-well plate, and all these wells could be measured within 3 h. Estrogens in suspect extracts were identified by full-scan accurate mass and collision-cross section (CCS) values from a UPLC-ion mobility-Q-time-of-flight-MS (UPLC-IM-Q-ToF-MS) equipped with a novel atmospheric pressure ionisation source. Thanks to the novel ion source, this instrument provided picogram sensitivity for estrogens in the negative ion mode and an additional identification point (experimental CCS values) next to retention time, accurate mass and tandem mass spectrometry data. The developed combination of bioaffinity screening with UPLC-QqQ-MS and identification with UPLC-IM-Q-ToF-MS provides an extremely powerful analytical tool for early warning of ERα bioactive compounds in dietary supplements as demonstrated by analysis of selected dietary supplements in which different estrogens were identified.

  19. High Throughput In Situ XAFS Screening of Catalysts

    International Nuclear Information System (INIS)

    Tsapatsaris, Nikolaos; Beesley, Angela M.; Weiher, Norbert; Tatton, Helen; Schroeder, Sven L. M.; Dent, Andy J.; Mosselmans, Frederick J. W.; Tromp, Moniek; Russu, Sergio; Evans, John; Harvey, Ian; Hayama, Shu

    2007-01-01

    We outline and demonstrate the feasibility of high-throughput (HT) in situ XAFS for synchrotron radiation studies. An XAS data acquisition and control system for the analysis of dynamic materials libraries under control of temperature and gaseous environments has been developed. The system is compatible with the 96-well industry standard and coupled to multi-stream quadrupole mass spectrometry (QMS) analysis of reactor effluents. An automated analytical workflow generates data quickly compared to traditional individual spectrum acquisition and analyses them in quasi-real time using an HT data analysis tool based on IFFEFIT. The system was used for the automated characterization of a library of 91 catalyst precursors containing ternary combinations of Cu, Pt, and Au on γ-Al2O3, and for the in situ characterization of Au catalysts supported on Al2O3 and TiO2

  20. High-throughput screening of small molecule libraries using SAMDI mass spectrometry.

    Science.gov (United States)

    Gurard-Levin, Zachary A; Scholle, Michael D; Eisenberg, Adam H; Mrksich, Milan

    2011-07-11

    High-throughput screening is a common strategy used to identify compounds that modulate biochemical activities, but many approaches depend on cumbersome fluorescent reporters or antibodies and often produce false-positive hits. The development of "label-free" assays addresses many of these limitations, but current approaches still lack the throughput needed for applications in drug discovery. This paper describes a high-throughput, label-free assay that combines self-assembled monolayers with mass spectrometry, in a technique called SAMDI, as a tool for screening libraries of 100,000 compounds in one day. This method is fast, has high discrimination, and is amenable to a broad range of chemical and biological applications.