Genome-wide detection and analysis of hippocampus core promoters using DeepCAGE

DEFF Research Database (Denmark)

Valen, Eivind; Pascarella, Giovanni; Chalk, Alistair

2009-01-01

in a given tissue. Here, we present a new method for high-throughput sequencing of 5' cDNA tags-DeepCAGE: merging the Cap Analysis of Gene Expression method with ultra-high-throughput sequence technology. We apply DeepCAGE to characterize 1.4 million sequenced TSS from mouse hippocampus and reveal a wealth...

Ultra-deep sequencing of intra-host rabies virus populations during cross-species transmission.

Directory of Open Access Journals (Sweden)

Monica K Borucki

2013-11-01

Full Text Available One of the hurdles to understanding the role of viral quasispecies in RNA virus cross-species transmission (CST events is the need to analyze a densely sampled outbreak using deep sequencing in order to measure the amount of mutation occurring on a small time scale. In 2009, the California Department of Public Health reported a dramatic increase (350 in the number of gray foxes infected with a rabies virus variant for which striped skunks serve as a reservoir host in Humboldt County. To better understand the evolution of rabies, deep-sequencing was applied to 40 unpassaged rabies virus samples from the Humboldt outbreak. For each sample, approximately 11 kb of the 12 kb genome was amplified and sequenced using the Illumina platform. Average coverage was 17,448 and this allowed characterization of the rabies virus population present in each sample at unprecedented depths. Phylogenetic analysis of the consensus sequence data demonstrated that samples clustered according to date (1995 vs. 2009 and geographic location (northern vs. southern. A single amino acid change in the G protein distinguished a subset of northern foxes from a haplotype present in both foxes and skunks, suggesting this mutation may have played a role in the observed increased transmission among foxes in this region. Deep-sequencing data indicated that many genetic changes associated with the CST event occurred prior to 2009 since several nonsynonymous mutations that were present in the consensus sequences of skunk and fox rabies samples obtained from 20032010 were present at the sub-consensus level (as rare variants in the viral population in skunk and fox samples from 1995. These results suggest that analysis of rare variants within a viral population may yield clues to ancestral genomes and identify rare variants that have the potential to be selected for if environment conditions change.

Workup of Human Blood Samples for Deep Sequencing of HIV-1 Genomes

NARCIS (Netherlands)

Cornelissen, Marion; Gall, Astrid; van der Kuyl, Antoinette; Wymant, Chris; Blanquart, François; Fraser, Christophe; Berkhout, Ben

2018-01-01

We describe a detailed protocol for the manual workup of blood (plasma/serum) samples from individuals infected with the human immunodeficiency virus type 1 (HIV-1) for deep sequence analysis of the viral genome. The study optimizing the assay was performed in the context of the BEEHIVE (Bridging

Predicting effects of noncoding variants with deep learning-based sequence model.

Science.gov (United States)

Zhou, Jian; Troyanskaya, Olga G

2015-10-01

Identifying functional effects of noncoding variants is a major challenge in human genetics. To predict the noncoding-variant effects de novo from sequence, we developed a deep learning-based algorithmic framework, DeepSEA (http://deepsea.princeton.edu/), that directly learns a regulatory sequence code from large-scale chromatin-profiling data, enabling prediction of chromatin effects of sequence alterations with single-nucleotide sensitivity. We further used this capability to improve prioritization of functional variants including expression quantitative trait loci (eQTLs) and disease-associated variants.

Deep Packet/Flow Analysis using GPUs

Energy Technology Data Exchange (ETDEWEB)

Gong, Qian [Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States); Wu, Wenji [Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States); DeMar, Phil [Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States)

2017-11-12

Deep packet inspection (DPI) faces severe performance challenges in high-speed networks (40/100 GE) as it requires a large amount of raw computing power and high I/O throughputs. Recently, researchers have tentatively used GPUs to address the above issues and boost the performance of DPI. Typically, DPI applications involve highly complex operations in both per-packet and per-flow data level, often in real-time. The parallel architecture of GPUs fits exceptionally well for per-packet network traffic processing. However, for stateful network protocols such as TCP, their data stream need to be reconstructed in a per-flow level to deliver a consistent content analysis. Since the flow-centric operations are naturally antiparallel and often require large memory space for buffering out-of-sequence packets, they can be problematic for GPUs, whose memory is normally limited to several gigabytes. In this work, we present a highly efficient GPU-based deep packet/flow analysis framework. The proposed design includes a purely GPU-implemented flow tracking and TCP stream reassembly. Instead of buffering and waiting for TCP packets to become in sequence, our framework process the packets in batch and uses a deterministic finite automaton (DFA) with prefix-/suffix- tree method to detect patterns across out-of-sequence packets that happen to be located in different batches. In conclusion, evaluation shows that our code can reassemble and forward tens of millions of packets per second and conduct a stateful signature-based deep packet inspection at 55 Gbit/s using an NVIDIA K40 GPU.

Transcriptome sequences resolve deep relationships of the grape family.

Science.gov (United States)

Wen, Jun; Xiong, Zhiqiang; Nie, Ze-Long; Mao, Likai; Zhu, Yabing; Kan, Xian-Zhao; Ickert-Bond, Stefanie M; Gerrath, Jean; Zimmer, Elizabeth A; Fang, Xiao-Dong

2013-01-01

Previous phylogenetic studies of the grape family (Vitaceae) yielded poorly resolved deep relationships, thus impeding our understanding of the evolution of the family. Next-generation sequencing now offers access to protein coding sequences very easily, quickly and cost-effectively. To improve upon earlier work, we extracted 417 orthologous single-copy nuclear genes from the transcriptomes of 15 species of the Vitaceae, covering its phylogenetic diversity. The resulting transcriptome phylogeny provides robust support for the deep relationships, showing the phylogenetic utility of transcriptome data for plants over a time scale at least since the mid-Cretaceous. The pros and cons of transcriptome data for phylogenetic inference in plants are also evaluated.

miRBase: integrating microRNA annotation and deep-sequencing data.

Science.gov (United States)

Kozomara, Ana; Griffiths-Jones, Sam

2011-01-01

miRBase is the primary online repository for all microRNA sequences and annotation. The current release (miRBase 16) contains over 15,000 microRNA gene loci in over 140 species, and over 17,000 distinct mature microRNA sequences. Deep-sequencing technologies have delivered a sharp rise in the rate of novel microRNA discovery. We have mapped reads from short RNA deep-sequencing experiments to microRNAs in miRBase and developed web interfaces to view these mappings. The user can view all read data associated with a given microRNA annotation, filter reads by experiment and count, and search for microRNAs by tissue- and stage-specific expression. These data can be used as a proxy for relative expression levels of microRNA sequences, provide detailed evidence for microRNA annotations and alternative isoforms of mature microRNAs, and allow us to revisit previous annotations. miRBase is available online at: http://www.mirbase.org/.

Discovery radiomics via evolutionary deep radiomic sequencer discovery for pathologically proven lung cancer detection.

Science.gov (United States)

Shafiee, Mohammad Javad; Chung, Audrey G; Khalvati, Farzad; Haider, Masoom A; Wong, Alexander

2017-10-01

While lung cancer is the second most diagnosed form of cancer in men and women, a sufficiently early diagnosis can be pivotal in patient survival rates. Imaging-based, or radiomics-driven, detection methods have been developed to aid diagnosticians, but largely rely on hand-crafted features that may not fully encapsulate the differences between cancerous and healthy tissue. Recently, the concept of discovery radiomics was introduced, where custom abstract features are discovered from readily available imaging data. We propose an evolutionary deep radiomic sequencer discovery approach based on evolutionary deep intelligence. Motivated by patient privacy concerns and the idea of operational artificial intelligence, the evolutionary deep radiomic sequencer discovery approach organically evolves increasingly more efficient deep radiomic sequencers that produce significantly more compact yet similarly descriptive radiomic sequences over multiple generations. As a result, this framework improves operational efficiency and enables diagnosis to be run locally at the radiologist's computer while maintaining detection accuracy. We evaluated the evolved deep radiomic sequencer (EDRS) discovered via the proposed evolutionary deep radiomic sequencer discovery framework against state-of-the-art radiomics-driven and discovery radiomics methods using clinical lung CT data with pathologically proven diagnostic data from the LIDC-IDRI dataset. The EDRS shows improved sensitivity (93.42%), specificity (82.39%), and diagnostic accuracy (88.78%) relative to previous radiomics approaches.

Transcriptome sequences resolve deep relationships of the grape family.

Directory of Open Access Journals (Sweden)

Jun Wen

Full Text Available Previous phylogenetic studies of the grape family (Vitaceae yielded poorly resolved deep relationships, thus impeding our understanding of the evolution of the family. Next-generation sequencing now offers access to protein coding sequences very easily, quickly and cost-effectively. To improve upon earlier work, we extracted 417 orthologous single-copy nuclear genes from the transcriptomes of 15 species of the Vitaceae, covering its phylogenetic diversity. The resulting transcriptome phylogeny provides robust support for the deep relationships, showing the phylogenetic utility of transcriptome data for plants over a time scale at least since the mid-Cretaceous. The pros and cons of transcriptome data for phylogenetic inference in plants are also evaluated.

DeepGO: predicting protein functions from sequence and interactions using a deep ontology-aware classifier

KAUST Repository

Kulmanov, Maxat

2017-09-27

Motivation A large number of protein sequences are becoming available through the application of novel high-throughput sequencing technologies. Experimental functional characterization of these proteins is time-consuming and expensive, and is often only done rigorously for few selected model organisms. Computational function prediction approaches have been suggested to fill this gap. The functions of proteins are classified using the Gene Ontology (GO), which contains over 40 000 classes. Additionally, proteins have multiple functions, making function prediction a large-scale, multi-class, multi-label problem. Results We have developed a novel method to predict protein function from sequence. We use deep learning to learn features from protein sequences as well as a cross-species protein–protein interaction network. Our approach specifically outputs information in the structure of the GO and utilizes the dependencies between GO classes as background information to construct a deep learning model. We evaluate our method using the standards established by the Computational Assessment of Function Annotation (CAFA) and demonstrate a significant improvement over baseline methods such as BLAST, in particular for predicting cellular locations.

DeepProbe: Information Directed Sequence Understanding and Chatbot Design via Recurrent Neural Networks

OpenAIRE

Yin, Zi; Chang, Keng-hao; Zhang, Ruofei

2017-01-01

Information extraction and user intention identification are central topics in modern query understanding and recommendation systems. In this paper, we propose DeepProbe, a generic information-directed interaction framework which is built around an attention-based sequence to sequence (seq2seq) recurrent neural network. DeepProbe can rephrase, evaluate, and even actively ask questions, leveraging the generative ability and likelihood estimation made possible by seq2seq models. DeepProbe makes...

Accurate identification of RNA editing sites from primitive sequence with deep neural networks.

Science.gov (United States)

Ouyang, Zhangyi; Liu, Feng; Zhao, Chenghui; Ren, Chao; An, Gaole; Mei, Chuan; Bo, Xiaochen; Shu, Wenjie

2018-04-16

RNA editing is a post-transcriptional RNA sequence alteration. Current methods have identified editing sites and facilitated research but require sufficient genomic annotations and prior-knowledge-based filtering steps, resulting in a cumbersome, time-consuming identification process. Moreover, these methods have limited generalizability and applicability in species with insufficient genomic annotations or in conditions of limited prior knowledge. We developed DeepRed, a deep learning-based method that identifies RNA editing from primitive RNA sequences without prior-knowledge-based filtering steps or genomic annotations. DeepRed achieved 98.1% and 97.9% area under the curve (AUC) in training and test sets, respectively. We further validated DeepRed using experimentally verified U87 cell RNA-seq data, achieving 97.9% positive predictive value (PPV). We demonstrated that DeepRed offers better prediction accuracy and computational efficiency than current methods with large-scale, mass RNA-seq data. We used DeepRed to assess the impact of multiple factors on editing identification with RNA-seq data from the Association of Biomolecular Resource Facilities and Sequencing Quality Control projects. We explored developmental RNA editing pattern changes during human early embryogenesis and evolutionary patterns in Drosophila species and the primate lineage using DeepRed. Our work illustrates DeepRed's state-of-the-art performance; it may decipher the hidden principles behind RNA editing, making editing detection convenient and effective.

Transcriptome analysis of the model protozoan, Tetrahymena thermophila, using Deep RNA sequencing.

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Jie Xiong

Full Text Available BACKGROUND: The ciliated protozoan Tetrahymena thermophila is a well-studied single-celled eukaryote model organism for cellular and molecular biology. However, the lack of extensive T. thermophila cDNA libraries or a large expressed sequence tag (EST database limited the quality of the original genome annotation. METHODOLOGY/PRINCIPAL FINDINGS: This RNA-seq study describes the first deep sequencing analysis of the T. thermophila transcriptome during the three major stages of the life cycle: growth, starvation and conjugation. Uniquely mapped reads covered more than 96% of the 24,725 predicted gene models in the somatic genome. More than 1,000 new transcribed regions were identified. The great dynamic range of RNA-seq allowed detection of a nearly six order-of-magnitude range of measurable gene expression orchestrated by this cell. RNA-seq also allowed the first prediction of transcript untranslated regions (UTRs and an updated (larger size estimate of the T. thermophila transcriptome: 57 Mb, or about 55% of the somatic genome. Our study identified nearly 1,500 alternative splicing (AS events distributed over 5.2% of T. thermophila genes. This percentage represents a two order-of-magnitude increase over previous EST-based estimates in Tetrahymena. Evidence of stage-specific regulation of alternative splicing was also obtained. Finally, our study allowed us to completely confirm about 26.8% of the genes originally predicted by the gene finder, to correct coding sequence boundaries and intron-exon junctions for about a third, and to reassign microarray probes and correct earlier microarray data. CONCLUSIONS/SIGNIFICANCE: RNA-seq data significantly improve the genome annotation and provide a fully comprehensive view of the global transcriptome of T. thermophila. To our knowledge, 5.2% of T. thermophila genes with AS is the highest percentage of genes showing AS reported in a unicellular eukaryote. Tetrahymena thus becomes an excellent unicellular

Identification of microRNAs from Amur grape (Vitis amurensis Rupr.) by deep sequencing and analysis of microRNA variations with bioinformatics.

Science.gov (United States)

Wang, Chen; Han, Jian; Liu, Chonghuai; Kibet, Korir Nicholas; Kayesh, Emrul; Shangguan, Lingfei; Li, Xiaoying; Fang, Jinggui

2012-03-29

MicroRNA (miRNA) is a class of functional non-coding small RNA with 19-25 nucleotides in length while Amur grape (Vitis amurensis Rupr.) is an important wild fruit crop with the strongest cold resistance among the Vitis species, is used as an excellent breeding parent for grapevine, and has elicited growing interest in wine production. To date, there is a relatively large number of grapevine miRNAs (vv-miRNAs) from cultivated grapevine varieties such as Vitis vinifera L. and hybrids of V. vinifera and V. labrusca, but there is no report on miRNAs from Vitis amurensis Rupr, a wild grapevine species. A small RNA library from Amur grape was constructed and Solexa technology used to perform deep sequencing of the library followed by subsequent bioinformatics analysis to identify new miRNAs. In total, 126 conserved miRNAs belonging to 27 miRNA families were identified, and 34 known but non-conserved miRNAs were also found. Significantly, 72 new potential Amur grape-specific miRNAs were discovered. The sequences of these new potential va-miRNAs were further validated through miR-RACE, and accumulation of 18 new va-miRNAs in seven tissues of grapevines confirmed by real time RT-PCR (qRT-PCR) analysis. The expression levels of va-miRNAs in flowers and berries were found to be basically consistent in identity to those from deep sequenced sRNAs libraries of combined corresponding tissues. We also describe the conservation and variation of va-miRNAs using miR-SNPs and miR-LDs during plant evolution based on comparison of orthologous sequences, and further reveal that the number and sites of miR-SNP in diverse miRNA families exhibit distinct divergence. Finally, 346 target genes for the new miRNAs were predicted and they include a number of Amur grape stress tolerance genes and many genes regulating anthocyanin synthesis and sugar metabolism. Deep sequencing of short RNAs from Amur grape flowers and berries identified 72 new potential miRNAs and 34 known but non-conserved mi

Identification of microRNAs from Amur grape (vitis amurensis Rupr. by deep sequencing and analysis of microRNA variations with bioinformatics

Directory of Open Access Journals (Sweden)

Wang Chen

2012-03-01

Full Text Available Abstract Background MicroRNA (miRNA is a class of functional non-coding small RNA with 19-25 nucleotides in length while Amur grape (Vitis amurensis Rupr. is an important wild fruit crop with the strongest cold resistance among the Vitis species, is used as an excellent breeding parent for grapevine, and has elicited growing interest in wine production. To date, there is a relatively large number of grapevine miRNAs (vv-miRNAs from cultivated grapevine varieties such as Vitis vinifera L. and hybrids of V. vinifera and V. labrusca, but there is no report on miRNAs from Vitis amurensis Rupr, a wild grapevine species. Results A small RNA library from Amur grape was constructed and Solexa technology used to perform deep sequencing of the library followed by subsequent bioinformatics analysis to identify new miRNAs. In total, 126 conserved miRNAs belonging to 27 miRNA families were identified, and 34 known but non-conserved miRNAs were also found. Significantly, 72 new potential Amur grape-specific miRNAs were discovered. The sequences of these new potential va-miRNAs were further validated through miR-RACE, and accumulation of 18 new va-miRNAs in seven tissues of grapevines confirmed by real time RT-PCR (qRT-PCR analysis. The expression levels of va-miRNAs in flowers and berries were found to be basically consistent in identity to those from deep sequenced sRNAs libraries of combined corresponding tissues. We also describe the conservation and variation of va-miRNAs using miR-SNPs and miR-LDs during plant evolution based on comparison of orthologous sequences, and further reveal that the number and sites of miR-SNP in diverse miRNA families exhibit distinct divergence. Finally, 346 target genes for the new miRNAs were predicted and they include a number of Amur grape stress tolerance genes and many genes regulating anthocyanin synthesis and sugar metabolism. Conclusions Deep sequencing of short RNAs from Amur grape flowers and berries identified 72

A Bioinformatic Pipeline for Monitoring of the Mutational Stability of Viral Drug Targets with Deep-Sequencing Technology.

Science.gov (United States)

Kravatsky, Yuri; Chechetkin, Vladimir; Fedoseeva, Daria; Gorbacheva, Maria; Kravatskaya, Galina; Kretova, Olga; Tchurikov, Nickolai

2017-11-23

The efficient development of antiviral drugs, including efficient antiviral small interfering RNAs (siRNAs), requires continuous monitoring of the strict correspondence between a drug and the related highly variable viral DNA/RNA target(s). Deep sequencing is able to provide an assessment of both the general target conservation and the frequency of particular mutations in the different target sites. The aim of this study was to develop a reliable bioinformatic pipeline for the analysis of millions of short, deep sequencing reads corresponding to selected highly variable viral sequences that are drug target(s). The suggested bioinformatic pipeline combines the available programs and the ad hoc scripts based on an original algorithm of the search for the conserved targets in the deep sequencing data. We also present the statistical criteria for the threshold of reliable mutation detection and for the assessment of variations between corresponding data sets. These criteria are robust against the possible sequencing errors in the reads. As an example, the bioinformatic pipeline is applied to the study of the conservation of RNA interference (RNAi) targets in human immunodeficiency virus 1 (HIV-1) subtype A. The developed pipeline is freely available to download at the website http://virmut.eimb.ru/. Brief comments and comparisons between VirMut and other pipelines are also presented.

Deep sequencing analysis of HBV genotype shift and correlation with antiviral efficiency during adefovir dipivoxil therapy.

Directory of Open Access Journals (Sweden)

Yuwei Wang

Full Text Available Viral genotype shift in chronic hepatitis B (CHB patients during antiviral therapy has been reported, but the underlying mechanism remains elusive.38 CHB patients treated with ADV for one year were selected for studying genotype shift by both deep sequencing and Sanger sequencing method.Sanger sequencing method found that 7.9% patients showed mixed genotype before ADV therapy. In contrast, all 38 patients showed mixed genotype before ADV treatment by deep sequencing. 95.5% mixed genotype rate was also obtained from additional 200 treatment-naïve CHB patients. Of the 13 patients with genotype shift, the fraction of the minor genotype in 5 patients (38% increased gradually during the course of ADV treatment. Furthermore, responses to ADV and HBeAg seroconversion were associated with the high rate of genotype shift, suggesting drug and immune pressure may be key factors to induce genotype shift. Interestingly, patients with genotype C had a significantly higher rate of genotype shift than genotype B. In genotype shift group, ADV treatment induced a marked enhancement of genotype B ratio accompanied by a reduction of genotype C ratio, suggesting genotype C may be more sensitive to ADV than genotype B. Moreover, patients with dominant genotype C may have a better therapeutic effect. Finally, genotype shifts was correlated with clinical improvement in terms of ALT.Our findings provided a rational explanation for genotype shift among ADV-treated CHB patients. The genotype and genotype shift might be associated with antiviral efficiency.

Development of genic-SSR markers by deep transcriptome sequencing in pigeonpea [Cajanus cajan (L.) Millspaugh

Science.gov (United States)

2011-01-01

Background Pigeonpea [Cajanus cajan (L.) Millspaugh], one of the most important food legumes of semi-arid tropical and subtropical regions, has limited genomic resources, particularly expressed sequence based (genic) markers. We report a comprehensive set of validated genic simple sequence repeat (SSR) markers using deep transcriptome sequencing, and its application in genetic diversity analysis and mapping. Results In this study, 43,324 transcriptome shotgun assembly unigene contigs were assembled from 1.696 million 454 GS-FLX sequence reads of separate pooled cDNA libraries prepared from leaf, root, stem and immature seed of two pigeonpea varieties, Asha and UPAS 120. A total of 3,771 genic-SSR loci, excluding homopolymeric and compound repeats, were identified; of which 2,877 PCR primer pairs were designed for marker development. Dinucleotide was the most common repeat motif with a frequency of 60.41%, followed by tri- (34.52%), hexa- (2.62%), tetra- (1.67%) and pentanucleotide (0.76%) repeat motifs. Primers were synthesized and tested for 772 of these loci with repeat lengths of ≥18 bp. Of these, 550 markers were validated for consistent amplification in eight diverse pigeonpea varieties; 71 were found to be polymorphic on agarose gel electrophoresis. Genetic diversity analysis was done on 22 pigeonpea varieties and eight wild species using 20 highly polymorphic genic-SSR markers. The number of alleles at these loci ranged from 4-10 and the polymorphism information content values ranged from 0.46 to 0.72. Neighbor-joining dendrogram showed distinct separation of the different groups of pigeonpea cultivars and wild species. Deep transcriptome sequencing of the two parental lines helped in silico identification of polymorphic genic-SSR loci to facilitate the rapid development of an intra-species reference genetic map, a subset of which was validated for expected allelic segregation in the reference mapping population. Conclusion We developed 550 validated genic

LookSeq: A browser-based viewer for deep sequencing data

OpenAIRE

Manske, Heinrich Magnus; Kwiatkowski, Dominic P.

2009-01-01

Sequencing a genome to great depth can be highly informative about heterogeneity within an individual or a population. Here we address the problem of how to visualize the multiple layers of information contained in deep sequencing data. We propose an interactive AJAX-based web viewer for browsing large data sets of aligned sequence reads. By enabling seamless browsing and fast zooming, the LookSeq program assists the user to assimilate information at different levels of resolution, from an ov...

A Bioinformatic Pipeline for Monitoring of the Mutational Stability of Viral Drug Targets with Deep-Sequencing Technology

Directory of Open Access Journals (Sweden)

Yuri Kravatsky

2017-11-01

Full Text Available The efficient development of antiviral drugs, including efficient antiviral small interfering RNAs (siRNAs, requires continuous monitoring of the strict correspondence between a drug and the related highly variable viral DNA/RNA target(s. Deep sequencing is able to provide an assessment of both the general target conservation and the frequency of particular mutations in the different target sites. The aim of this study was to develop a reliable bioinformatic pipeline for the analysis of millions of short, deep sequencing reads corresponding to selected highly variable viral sequences that are drug target(s. The suggested bioinformatic pipeline combines the available programs and the ad hoc scripts based on an original algorithm of the search for the conserved targets in the deep sequencing data. We also present the statistical criteria for the threshold of reliable mutation detection and for the assessment of variations between corresponding data sets. These criteria are robust against the possible sequencing errors in the reads. As an example, the bioinformatic pipeline is applied to the study of the conservation of RNA interference (RNAi targets in human immunodeficiency virus 1 (HIV-1 subtype A. The developed pipeline is freely available to download at the website http://virmut.eimb.ru/. Brief comments and comparisons between VirMut and other pipelines are also presented.

Deep amplicon sequencing reveals mixed phytoplasma infection within single grapevine plants

DEFF Research Database (Denmark)

Nicolaisen, Mogens; Contaldo, Nicoletta; Makarova, Olga

2011-01-01

The diversity of phytoplasmas within single plants has not yet been fully investigated. In this project, deep amplicon sequencing was used to generate 50,926 phytoplasma sequences from 11 phytoplasma-infected grapevine samples from a PCR amplicon in the 5' end of the 16S region. After clustering ...

A simple method for the parallel deep sequencing of full influenza A genomes

DEFF Research Database (Denmark)

Kampmann, Marie-Louise; Fordyce, Sarah Louise; Avila Arcos, Maria del Carmen

2011-01-01

Given the major threat of influenza A to human and animal health, and its ability to evolve rapidly through mutation and reassortment, tools that enable its timely characterization are necessary to help monitor its evolution and spread. For this purpose, deep sequencing can be a very valuable tool....... This study reports a comprehensive method that enables deep sequencing of the complete genomes of influenza A subtypes using the Illumina Genome Analyzer IIx (GAIIx). By using this method, the complete genomes of nine viruses were sequenced in parallel, representing the 2009 pandemic H1N1 virus, H5N1 virus...

Unified Deep Learning Architecture for Modeling Biology Sequence.

Science.gov (United States)

Wu, Hongjie; Cao, Chengyuan; Xia, Xiaoyan; Lu, Qiang

2017-10-09

Prediction of the spatial structure or function of biological macromolecules based on their sequence remains an important challenge in bioinformatics. When modeling biological sequences using traditional sequencing models, characteristics, such as long-range interactions between basic units, the complicated and variable output of labeled structures, and the variable length of biological sequences, usually lead to different solutions on a case-by-case basis. This study proposed the use of bidirectional recurrent neural networks based on long short-term memory or a gated recurrent unit to capture long-range interactions by designing the optional reshape operator to adapt to the diversity of the output labels and implementing a training algorithm to support the training of sequence models capable of processing variable-length sequences. Additionally, the merge and pooling operators enhanced the ability to capture short-range interactions between basic units of biological sequences. The proposed deep-learning model and its training algorithm might be capable of solving currently known biological sequence-modeling problems through the use of a unified framework. We validated our model on one of the most difficult biological sequence-modeling problems currently known, with our results indicating the ability of the model to obtain predictions of protein residue interactions that exceeded the accuracy of current popular approaches by 10% based on multiple benchmarks.

DeepGO: predicting protein functions from sequence and interactions using a deep ontology-aware classifier.

Science.gov (United States)

Kulmanov, Maxat; Khan, Mohammed Asif; Hoehndorf, Robert; Wren, Jonathan

2018-02-15

A large number of protein sequences are becoming available through the application of novel high-throughput sequencing technologies. Experimental functional characterization of these proteins is time-consuming and expensive, and is often only done rigorously for few selected model organisms. Computational function prediction approaches have been suggested to fill this gap. The functions of proteins are classified using the Gene Ontology (GO), which contains over 40 000 classes. Additionally, proteins have multiple functions, making function prediction a large-scale, multi-class, multi-label problem. We have developed a novel method to predict protein function from sequence. We use deep learning to learn features from protein sequences as well as a cross-species protein-protein interaction network. Our approach specifically outputs information in the structure of the GO and utilizes the dependencies between GO classes as background information to construct a deep learning model. We evaluate our method using the standards established by the Computational Assessment of Function Annotation (CAFA) and demonstrate a significant improvement over baseline methods such as BLAST, in particular for predicting cellular locations. Web server: http://deepgo.bio2vec.net, Source code: https://github.com/bio-ontology-research-group/deepgo. robert.hoehndorf@kaust.edu.sa. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

A novel wavelet sequence based on deep bidirectional LSTM network model for ECG signal classification.

Science.gov (United States)

Yildirim, Özal

2018-05-01

Long-short term memory networks (LSTMs), which have recently emerged in sequential data analysis, are the most widely used type of recurrent neural networks (RNNs) architecture. Progress on the topic of deep learning includes successful adaptations of deep versions of these architectures. In this study, a new model for deep bidirectional LSTM network-based wavelet sequences called DBLSTM-WS was proposed for classifying electrocardiogram (ECG) signals. For this purpose, a new wavelet-based layer is implemented to generate ECG signal sequences. The ECG signals were decomposed into frequency sub-bands at different scales in this layer. These sub-bands are used as sequences for the input of LSTM networks. New network models that include unidirectional (ULSTM) and bidirectional (BLSTM) structures are designed for performance comparisons. Experimental studies have been performed for five different types of heartbeats obtained from the MIT-BIH arrhythmia database. These five types are Normal Sinus Rhythm (NSR), Ventricular Premature Contraction (VPC), Paced Beat (PB), Left Bundle Branch Block (LBBB), and Right Bundle Branch Block (RBBB). The results show that the DBLSTM-WS model gives a high recognition performance of 99.39%. It has been observed that the wavelet-based layer proposed in the study significantly improves the recognition performance of conventional networks. This proposed network structure is an important approach that can be applied to similar signal processing problems. Copyright © 2018 Elsevier Ltd. All rights reserved.

Deep whole-genome sequencing of 90 Han Chinese genomes.

Science.gov (United States)

Lan, Tianming; Lin, Haoxiang; Zhu, Wenjuan; Laurent, Tellier Christian Asker Melchior; Yang, Mengcheng; Liu, Xin; Wang, Jun; Wang, Jian; Yang, Huanming; Xu, Xun; Guo, Xiaosen

2017-09-01

Next-generation sequencing provides a high-resolution insight into human genetic information. However, the focus of previous studies has primarily been on low-coverage data due to the high cost of sequencing. Although the 1000 Genomes Project and the Haplotype Reference Consortium have both provided powerful reference panels for imputation, low-frequency and novel variants remain difficult to discover and call with accuracy on the basis of low-coverage data. Deep sequencing provides an optimal solution for the problem of these low-frequency and novel variants. Although whole-exome sequencing is also a viable choice for exome regions, it cannot account for noncoding regions, sometimes resulting in the absence of important, causal variants. For Han Chinese populations, the majority of variants have been discovered based upon low-coverage data from the 1000 Genomes Project. However, high-coverage, whole-genome sequencing data are limited for any population, and a large amount of low-frequency, population-specific variants remain uncharacterized. We have performed whole-genome sequencing at a high depth (∼×80) of 90 unrelated individuals of Chinese ancestry, collected from the 1000 Genomes Project samples, including 45 Northern Han Chinese and 45 Southern Han Chinese samples. Eighty-three of these 90 have been sequenced by the 1000 Genomes Project. We have identified 12 568 804 single nucleotide polymorphisms, 2 074 210 short InDels, and 26 142 structural variations from these 90 samples. Compared to the Han Chinese data from the 1000 Genomes Project, we have found 7 000 629 novel variants with low frequency (defined as minor allele frequency genome. Compared to the 1000 Genomes Project, these Han Chinese deep sequencing data enhance the characterization of a large number of low-frequency, novel variants. This will be a valuable resource for promoting Chinese genetics research and medical development. Additionally, it will provide a valuable supplement to the 1000

Deep sequencing discovery of novel and conserved microRNAs in trifoliate orange (Citrus trifoliata

Directory of Open Access Journals (Sweden)

Yu Huaping

2010-07-01

Full Text Available Abstract Background MicroRNAs (miRNAs play a critical role in post-transcriptional gene regulation and have been shown to control many genes involved in various biological and metabolic processes. There have been extensive studies to discover miRNAs and analyze their functions in model plant species, such as Arabidopsis and rice. Deep sequencing technologies have facilitated identification of species-specific or lowly expressed as well as conserved or highly expressed miRNAs in plants. Results In this research, we used Solexa sequencing to discover new microRNAs in trifoliate orange (Citrus trifoliata which is an important rootstock of citrus. A total of 13,106,753 reads representing 4,876,395 distinct sequences were obtained from a short RNA library generated from small RNA extracted from C. trifoliata flower and fruit tissues. Based on sequence similarity and hairpin structure prediction, we found that 156,639 reads representing 63 sequences from 42 highly conserved miRNA families, have perfect matches to known miRNAs. We also identified 10 novel miRNA candidates whose precursors were all potentially generated from citrus ESTs. In addition, five miRNA* sequences were also sequenced. These sequences had not been earlier described in other plant species and accumulation of the 10 novel miRNAs were confirmed by qRT-PCR analysis. Potential target genes were predicted for most conserved and novel miRNAs. Moreover, four target genes including one encoding IRX12 copper ion binding/oxidoreductase and three genes encoding NB-LRR disease resistance protein have been experimentally verified by detection of the miRNA-mediated mRNA cleavage in C. trifoliata. Conclusion Deep sequencing of short RNAs from C. trifoliata flowers and fruits identified 10 new potential miRNAs and 42 highly conserved miRNA families, indicating that specific miRNAs exist in C. trifoliata. These results show that regulatory miRNAs exist in agronomically important trifoliate orange

Sequence-based prediction of protein protein interaction using a deep-learning algorithm.

Science.gov (United States)

Sun, Tanlin; Zhou, Bo; Lai, Luhua; Pei, Jianfeng

2017-05-25

Protein-protein interactions (PPIs) are critical for many biological processes. It is therefore important to develop accurate high-throughput methods for identifying PPI to better understand protein function, disease occurrence, and therapy design. Though various computational methods for predicting PPI have been developed, their robustness for prediction with external datasets is unknown. Deep-learning algorithms have achieved successful results in diverse areas, but their effectiveness for PPI prediction has not been tested. We used a stacked autoencoder, a type of deep-learning algorithm, to study the sequence-based PPI prediction. The best model achieved an average accuracy of 97.19% with 10-fold cross-validation. The prediction accuracies for various external datasets ranged from 87.99% to 99.21%, which are superior to those achieved with previous methods. To our knowledge, this research is the first to apply a deep-learning algorithm to sequence-based PPI prediction, and the results demonstrate its potential in this field.

Deep sequencing methods for protein engineering and design.

Science.gov (United States)

Wrenbeck, Emily E; Faber, Matthew S; Whitehead, Timothy A

2017-08-01

The advent of next-generation sequencing (NGS) has revolutionized protein science, and the development of complementary methods enabling NGS-driven protein engineering have followed. In general, these experiments address the functional consequences of thousands of protein variants in a massively parallel manner using genotype-phenotype linked high-throughput functional screens followed by DNA counting via deep sequencing. We highlight the use of information rich datasets to engineer protein molecular recognition. Examples include the creation of multiple dual-affinity Fabs targeting structurally dissimilar epitopes and engineering of a broad germline-targeted anti-HIV-1 immunogen. Additionally, we highlight the generation of enzyme fitness landscapes for conducting fundamental studies of protein behavior and evolution. We conclude with discussion of technological advances. Copyright © 2016 Elsevier Ltd. All rights reserved.

Genomic region operation kit for flexible processing of deep sequencing data.

Science.gov (United States)

Ovaska, Kristian; Lyly, Lauri; Sahu, Biswajyoti; Jänne, Olli A; Hautaniemi, Sampsa

2013-01-01

Computational analysis of data produced in deep sequencing (DS) experiments is challenging due to large data volumes and requirements for flexible analysis approaches. Here, we present a mathematical formalism based on set algebra for frequently performed operations in DS data analysis to facilitate translation of biomedical research questions to language amenable for computational analysis. With the help of this formalism, we implemented the Genomic Region Operation Kit (GROK), which supports various DS-related operations such as preprocessing, filtering, file conversion, and sample comparison. GROK provides high-level interfaces for R, Python, Lua, and command line, as well as an extension C++ API. It supports major genomic file formats and allows storing custom genomic regions in efficient data structures such as red-black trees and SQL databases. To demonstrate the utility of GROK, we have characterized the roles of two major transcription factors (TFs) in prostate cancer using data from 10 DS experiments. GROK is freely available with a user guide from >http://csbi.ltdk.helsinki.fi/grok/.

Identification of miRNAs and their target genes in developing soybean seeds by deep sequencing

Directory of Open Access Journals (Sweden)

Chen Shou-Yi

2011-01-01

Full Text Available Abstract Background MicroRNAs (miRNAs regulate gene expression by mediating gene silencing at transcriptional and post-transcriptional levels in higher plants. miRNAs and related target genes have been widely studied in model plants such as Arabidopsis and rice; however, the number of identified miRNAs in soybean (Glycine max is limited, and global identification of the related miRNA targets has not been reported in previous research. Results In our study, a small RNA library and a degradome library were constructed from developing soybean seeds for deep sequencing. We identified 26 new miRNAs in soybean by bioinformatic analysis and further confirmed their expression by stem-loop RT-PCR. The miRNA star sequences of 38 known miRNAs and 8 new miRNAs were also discovered, providing additional evidence for the existence of miRNAs. Through degradome sequencing, 145 and 25 genes were identified as targets of annotated miRNAs and new miRNAs, respectively. GO analysis indicated that many of the identified miRNA targets may function in soybean seed development. Additionally, a soybean homolog of Arabidopsis SUPPRESSOR OF GENE SLIENCING 3 (AtSGS3 was detected as a target of the newly identified miRNA Soy_25, suggesting the presence of feedback control of miRNA biogenesis. Conclusions We have identified large numbers of miRNAs and their related target genes through deep sequencing of a small RNA library and a degradome library. Our study provides more information about the regulatory network of miRNAs in soybean and advances our understanding of miRNA functions during seed development.

Identification of ribonucleotide reductase mutation causing temperature-sensitivity of herpes simplex virus isolates from whitlow by deep sequencing.

Science.gov (United States)

Daikoku, Tohru; Oyama, Yukari; Yajima, Misako; Sekizuka, Tsuyoshi; Kuroda, Makoto; Shimada, Yuka; Takehara, Kazuhiko; Miwa, Naoko; Okuda, Tomoko; Sata, Tetsutaro; Shiraki, Kimiyasu

2015-06-01

Herpes simplex virus 2 caused a genital ulcer, and a secondary herpetic whitlow appeared during acyclovir therapy. The secondary and recurrent whitlow isolates were acyclovir-resistant and temperature-sensitive in contrast to a genital isolate. We identified the ribonucleotide reductase mutation responsible for temperature-sensitivity by deep-sequencing analysis.

Continuous Distributed Representation of Biological Sequences for Deep Proteomics and Genomics.

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Ehsaneddin Asgari

Full Text Available We introduce a new representation and feature extraction method for biological sequences. Named bio-vectors (BioVec to refer to biological sequences in general with protein-vectors (ProtVec for proteins (amino-acid sequences and gene-vectors (GeneVec for gene sequences, this representation can be widely used in applications of deep learning in proteomics and genomics. In the present paper, we focus on protein-vectors that can be utilized in a wide array of bioinformatics investigations such as family classification, protein visualization, structure prediction, disordered protein identification, and protein-protein interaction prediction. In this method, we adopt artificial neural network approaches and represent a protein sequence with a single dense n-dimensional vector. To evaluate this method, we apply it in classification of 324,018 protein sequences obtained from Swiss-Prot belonging to 7,027 protein families, where an average family classification accuracy of 93%±0.06% is obtained, outperforming existing family classification methods. In addition, we use ProtVec representation to predict disordered proteins from structured proteins. Two databases of disordered sequences are used: the DisProt database as well as a database featuring the disordered regions of nucleoporins rich with phenylalanine-glycine repeats (FG-Nups. Using support vector machine classifiers, FG-Nup sequences are distinguished from structured protein sequences found in Protein Data Bank (PDB with a 99.8% accuracy, and unstructured DisProt sequences are differentiated from structured DisProt sequences with 100.0% accuracy. These results indicate that by only providing sequence data for various proteins into this model, accurate information about protein structure can be determined. Importantly, this model needs to be trained only once and can then be applied to extract a comprehensive set of information regarding proteins of interest. Moreover, this representation can be

Deciphering KRAS and NRAS mutated clone dynamics in MLL-AF4 paediatric leukaemia by ultra deep sequencing analysis.

Science.gov (United States)

Trentin, Luca; Bresolin, Silvia; Giarin, Emanuela; Bardini, Michela; Serafin, Valentina; Accordi, Benedetta; Fais, Franco; Tenca, Claudya; De Lorenzo, Paola; Valsecchi, Maria Grazia; Cazzaniga, Giovanni; Kronnie, Geertruy Te; Basso, Giuseppe

2016-10-04

To induce and sustain the leukaemogenic process, MLL-AF4+ leukaemia seems to require very few genetic alterations in addition to the fusion gene itself. Studies of infant and paediatric patients with MLL-AF4+ B cell precursor acute lymphoblastic leukaemia (BCP-ALL) have reported mutations in KRAS and NRAS with incidences ranging from 25 to 50%. Whereas previous studies employed Sanger sequencing, here we used next generation amplicon deep sequencing for in depth evaluation of RAS mutations in 36 paediatric patients at diagnosis of MLL-AF4+ leukaemia. RAS mutations including those in small sub-clones were detected in 63.9% of patients. Furthermore, the mutational analysis of 17 paired samples at diagnosis and relapse revealed complex RAS clone dynamics and showed that the mutated clones present at relapse were almost all originated from clones that were already detectable at diagnosis and survived to the initial therapy. Finally, we showed that mutated patients were indeed characterized by a RAS related signature at both transcriptional and protein levels and that the targeting of the RAS pathway could be of beneficial for treatment of MLL-AF4+ BCP-ALL clones carrying somatic RAS mutations.

miRBase: annotating high confidence microRNAs using deep sequencing data.

Science.gov (United States)

Kozomara, Ana; Griffiths-Jones, Sam

2014-01-01

We describe an update of the miRBase database (http://www.mirbase.org/), the primary microRNA sequence repository. The latest miRBase release (v20, June 2013) contains 24 521 microRNA loci from 206 species, processed to produce 30 424 mature microRNA products. The rate of deposition of novel microRNAs and the number of researchers involved in their discovery continue to increase, driven largely by small RNA deep sequencing experiments. In the face of these increases, and a range of microRNA annotation methods and criteria, maintaining the quality of the microRNA sequence data set is a significant challenge. Here, we describe recent developments of the miRBase database to address this issue. In particular, we describe the collation and use of deep sequencing data sets to assign levels of confidence to miRBase entries. We now provide a high confidence subset of miRBase entries, based on the pattern of mapped reads. The high confidence microRNA data set is available alongside the complete microRNA collection at http://www.mirbase.org/. We also describe embedding microRNA-specific Wikipedia pages on the miRBase website to encourage the microRNA community to contribute and share textual and functional information.

LookSeq: a browser-based viewer for deep sequencing data.

Science.gov (United States)

Manske, Heinrich Magnus; Kwiatkowski, Dominic P

2009-11-01

Sequencing a genome to great depth can be highly informative about heterogeneity within an individual or a population. Here we address the problem of how to visualize the multiple layers of information contained in deep sequencing data. We propose an interactive AJAX-based web viewer for browsing large data sets of aligned sequence reads. By enabling seamless browsing and fast zooming, the LookSeq program assists the user to assimilate information at different levels of resolution, from an overview of a genomic region to fine details such as heterogeneity within the sample. A specific problem, particularly if the sample is heterogeneous, is how to depict information about structural variation. LookSeq provides a simple graphical representation of paired sequence reads that is more revealing about potential insertions and deletions than are conventional methods.

AUC-Maximized Deep Convolutional Neural Fields for Protein Sequence Labeling.

Science.gov (United States)

Wang, Sheng; Sun, Siqi; Xu, Jinbo

2016-09-01

Deep Convolutional Neural Networks (DCNN) has shown excellent performance in a variety of machine learning tasks. This paper presents Deep Convolutional Neural Fields (DeepCNF), an integration of DCNN with Conditional Random Field (CRF), for sequence labeling with an imbalanced label distribution. The widely-used training methods, such as maximum-likelihood and maximum labelwise accuracy, do not work well on imbalanced data. To handle this, we present a new training algorithm called maximum-AUC for DeepCNF. That is, we train DeepCNF by directly maximizing the empirical Area Under the ROC Curve (AUC), which is an unbiased measurement for imbalanced data. To fulfill this, we formulate AUC in a pairwise ranking framework, approximate it by a polynomial function and then apply a gradient-based procedure to optimize it. Our experimental results confirm that maximum-AUC greatly outperforms the other two training methods on 8-state secondary structure prediction and disorder prediction since their label distributions are highly imbalanced and also has similar performance as the other two training methods on solvent accessibility prediction, which has three equally-distributed labels. Furthermore, our experimental results show that our AUC-trained DeepCNF models greatly outperform existing popular predictors of these three tasks. The data and software related to this paper are available at https://github.com/realbigws/DeepCNF_AUC.

Deep sequencing-based transcriptome analysis of Plutella xylostella larvae parasitized by Diadegma semiclausum

Science.gov (United States)

2011-01-01

Background Parasitoid insects manipulate their hosts' physiology by injecting various factors into their host upon parasitization. Transcriptomic approaches provide a powerful approach to study insect host-parasitoid interactions at the molecular level. In order to investigate the effects of parasitization by an ichneumonid wasp (Diadegma semiclausum) on the host (Plutella xylostella), the larval transcriptome profile was analyzed using a short-read deep sequencing method (Illumina). Symbiotic polydnaviruses (PDVs) associated with ichneumonid parasitoids, known as ichnoviruses, play significant roles in host immune suppression and developmental regulation. In the current study, D. semiclausum ichnovirus (DsIV) genes expressed in P. xylostella were identified and their sequences compared with other reported PDVs. Five of these genes encode proteins of unknown identity, that have not previously been reported. Results De novo assembly of cDNA sequence data generated 172,660 contigs between 100 and 10000 bp in length; with 35% of > 200 bp in length. Parasitization had significant impacts on expression levels of 928 identified insect host transcripts. Gene ontology data illustrated that the majority of the differentially expressed genes are involved in binding, catalytic activity, and metabolic and cellular processes. In addition, the results show that transcription levels of antimicrobial peptides, such as gloverin, cecropin E and lysozyme, were up-regulated after parasitism. Expression of ichnovirus genes were detected in parasitized larvae with 19 unique sequences identified from five PDV gene families including vankyrin, viral innexin, repeat elements, a cysteine-rich motif, and polar residue rich protein. Vankyrin 1 and repeat element 1 genes showed the highest transcription levels among the DsIV genes. Conclusion This study provides detailed information on differential expression of P. xylostella larval genes following parasitization, DsIV genes expressed in the

Deep RNA Sequencing of the Skeletal Muscle Transcriptome in Swimming Fish

NARCIS (Netherlands)

Palstra, A.P.; Beltran, S.; Burgerhout, E.; Brittijn, S.A.; Magnoni, L.J.; Henkel, C.V.; Jansen, A.; Thillart, G.E.E.J.M.; Spaink, H.P.; Planas, J.V.

2013-01-01

Deep RNA sequencing (RNA-seq) was performed to provide an in-depth view of the transcriptome of red and white skeletal muscle of exercised and non-exercised rainbow trout (Oncorhynchus mykiss) with the specific objective to identify expressed genes and quantify the transcriptomic effects of

Deep Sequence Analysis of AgoshRNA Processing Reveals 3' A Addition and Trimming.

Science.gov (United States)

Harwig, Alex; Herrera-Carrillo, Elena; Jongejan, Aldo; van Kampen, Antonius Hubertus; Berkhout, Ben

2015-07-14

The RNA interference (RNAi) pathway, in which microprocessor and Dicer collaborate to process microRNAs (miRNA), was recently expanded by the description of alternative processing routes. In one of these noncanonical pathways, Dicer action is replaced by the Argonaute2 (Ago2) slicer function. It was recently shown that the stem-length of precursor-miRNA or short hairpin RNA (shRNA) molecules is a major determinant for Dicer versus Ago2 processing. Here we present the results of a deep sequence study on the processing of shRNAs with different stem length and a top G·U wobble base pair (bp). This analysis revealed some unexpected properties of these so-called AgoshRNA molecules that are processed by Ago2 instead of Dicer. First, we confirmed the gradual shift from Dicer to Ago2 processing upon shortening of the hairpin length. Second, hairpins with a stem larger than 19 base pair are inefficiently cleaved by Ago2 and we noticed a shift in the cleavage site. Third, the introduction of a top G·U bp in a regular shRNA can promote Ago2-cleavage, which coincides with a loss of Ago2-loading of the Dicer-cleaved 3' strand. Fourth, the Ago2-processed AgoshRNAs acquire a short 3' tail of 1-3 A-nucleotides (nt) and we present evidence that this product is subsequently trimmed by the poly(A)-specific ribonuclease (PARN).

Deep sequencing-based analysis of the anaerobic stimulon in Neisseria gonorrhoeae

Directory of Open Access Journals (Sweden)

Clark Virginia L

2011-01-01

Full Text Available Abstract Background Maintenance of an anaerobic denitrification system in the obligate human pathogen, Neisseria gonorrhoeae, suggests that an anaerobic lifestyle may be important during the course of infection. Furthermore, mounting evidence suggests that reduction of host-produced nitric oxide has several immunomodulary effects on the host. However, at this point there have been no studies analyzing the complete gonococcal transcriptome response to anaerobiosis. Here we performed deep sequencing to compare the gonococcal transcriptomes of aerobically and anaerobically grown cells. Using the information derived from this sequencing, we discuss the implications of the robust transcriptional response to anaerobic growth. Results We determined that 198 chromosomal genes were differentially expressed (~10% of the genome in response to anaerobic conditions. We also observed a large induction of genes encoded within the cryptic plasmid, pJD1. Validation of RNA-seq data using translational-lacZ fusions or RT-PCR demonstrated the RNA-seq results to be very reproducible. Surprisingly, many genes of prophage origin were induced anaerobically, as well as several transcriptional regulators previously unknown to be involved in anaerobic growth. We also confirmed expression and regulation of a small RNA, likely a functional equivalent of fnrS in the Enterobacteriaceae family. We also determined that many genes found to be responsive to anaerobiosis have also been shown to be responsive to iron and/or oxidative stress. Conclusions Gonococci will be subject to many forms of environmental stress, including oxygen-limitation, during the course of infection. Here we determined that the anaerobic stimulon in gonococci was larger than previous studies would suggest. Many new targets for future research have been uncovered, and the results derived from this study may have helped to elucidate factors or mechanisms of virulence that may have otherwise been overlooked.

Determining mutant spectra of three RNA viral samples using ultra-deep sequencing

Energy Technology Data Exchange (ETDEWEB)

Chen, H

2012-06-06

RNA viruses have extremely high mutation rates that enable the virus to adapt to new host environments and even jump from one species to another. As part of a viral transmission study, three viral samples collected from naturally infected animals were sequenced using Illumina paired-end technology at ultra-deep coverage. In order to determine the mutant spectra within the viral quasispecies, it is critical to understand the sequencing error rates and control for false positive calls of viral variants (point mutantations). I will estimate the sequencing error rate from two control sequences and characterize the mutant spectra in the natural samples with this error rate.

Rapid and Deep Proteomes by Faster Sequencing on a Benchtop Quadrupole Ultra-High-Field Orbitrap Mass Spectrometer

DEFF Research Database (Denmark)

Kelstrup, Christian D; Jersie-Christensen, Rosa R; Batth, Tanveer Singh

2014-01-01

per second or up to 600 new peptides sequenced per gradient minute. We identify 4400 proteins from one microgram of HeLa digest using a one hour gradient, which is an approximately 30% improvement compared to previous instrumentation. In addition, we show very deep proteome coverage can be achieved...... in less than 24 hours of analysis time by offline high pH reversed-phase peptide fractionation from which we identify more than 140,000 unique peptide sequences. This is comparable to state-of-the-art multi-day, multi-enzyme efforts. Finally the acquisition methods are evaluated for single...

miRanalyzer: a microRNA detection and analysis tool for next-generation sequencing experiments.

Science.gov (United States)

Hackenberg, Michael; Sturm, Martin; Langenberger, David; Falcón-Pérez, Juan Manuel; Aransay, Ana M

2009-07-01

Next-generation sequencing allows now the sequencing of small RNA molecules and the estimation of their expression levels. Consequently, there will be a high demand of bioinformatics tools to cope with the several gigabytes of sequence data generated in each single deep-sequencing experiment. Given this scene, we developed miRanalyzer, a web server tool for the analysis of deep-sequencing experiments for small RNAs. The web server tool requires a simple input file containing a list of unique reads and its copy numbers (expression levels). Using these data, miRanalyzer (i) detects all known microRNA sequences annotated in miRBase, (ii) finds all perfect matches against other libraries of transcribed sequences and (iii) predicts new microRNAs. The prediction of new microRNAs is an especially important point as there are many species with very few known microRNAs. Therefore, we implemented a highly accurate machine learning algorithm for the prediction of new microRNAs that reaches AUC values of 97.9% and recall values of up to 75% on unseen data. The web tool summarizes all the described steps in a single output page, which provides a comprehensive overview of the analysis, adding links to more detailed output pages for each analysis module. miRanalyzer is available at http://web.bioinformatics.cicbiogune.es/microRNA/.

Identification and Removal of Contaminant Sequences From Ribosomal Gene Databases: Lessons From the Census of Deep Life.

Science.gov (United States)

Sheik, Cody S; Reese, Brandi Kiel; Twing, Katrina I; Sylvan, Jason B; Grim, Sharon L; Schrenk, Matthew O; Sogin, Mitchell L; Colwell, Frederick S

2018-01-01

Earth's subsurface environment is one of the largest, yet least studied, biomes on Earth, and many questions remain regarding what microorganisms are indigenous to the subsurface. Through the activity of the Census of Deep Life (CoDL) and the Deep Carbon Observatory, an open access 16S ribosomal RNA gene sequence database from diverse subsurface environments has been compiled. However, due to low quantities of biomass in the deep subsurface, the potential for incorporation of contaminants from reagents used during sample collection, processing, and/or sequencing is high. Thus, to understand the ecology of subsurface microorganisms (i.e., the distribution, richness, or survival), it is necessary to minimize, identify, and remove contaminant sequences that will skew the relative abundances of all taxa in the sample. In this meta-analysis, we identify putative contaminants associated with the CoDL dataset, recommend best practices for removing contaminants from samples, and propose a series of best practices for subsurface microbiology sampling. The most abundant putative contaminant genera observed, independent of evenness across samples, were Propionibacterium , Aquabacterium , Ralstonia , and Acinetobacter . While the top five most frequently observed genera were Pseudomonas , Propionibacterium , Acinetobacter , Ralstonia , and Sphingomonas . The majority of the most frequently observed genera (high evenness) were associated with reagent or potential human contamination. Additionally, in DNA extraction blanks, we observed potential archaeal contaminants, including methanogens, which have not been discussed in previous contamination studies. Such contaminants would directly affect the interpretation of subsurface molecular studies, as methanogenesis is an important subsurface biogeochemical process. Utilizing previously identified contaminant genera, we found that ∼27% of the total dataset were identified as contaminant sequences that likely originate from DNA

De novo transcriptome assembly and positive selection analysis of an individual deep-sea fish.

Science.gov (United States)

Lan, Yi; Sun, Jin; Xu, Ting; Chen, Chong; Tian, Renmao; Qiu, Jian-Wen; Qian, Pei-Yuan

2018-05-24

High hydrostatic pressure and low temperatures make the deep sea a harsh environment for life forms. Actin organization and microtubules assembly, which are essential for intracellular transport and cell motility, can be disrupted by high hydrostatic pressure. High hydrostatic pressure can also damage DNA. Nucleic acids exposed to low temperatures can form secondary structures that hinder genetic information processing. To study how deep-sea creatures adapt to such a hostile environment, one of the most straightforward ways is to sequence and compare their genes with those of their shallow-water relatives. We captured an individual of the fish species Aldrovandia affinis, which is a typical deep-sea inhabitant, from the Okinawa Trough at a depth of 1550 m using a remotely operated vehicle (ROV). We sequenced its transcriptome and analyzed its molecular adaptation. We obtained 27,633 protein coding sequences using an Illumina platform and compared them with those of several shallow-water fish species. Analysis of 4918 single-copy orthologs identified 138 positively selected genes in A. affinis, including genes involved in microtubule regulation. Particularly, functional domains related to cold shock as well as DNA repair are exposed to positive selection pressure in both deep-sea fish and hadal amphipod. Overall, we have identified a set of positively selected genes related to cytoskeleton structures, DNA repair and genetic information processing, which shed light on molecular adaptation to the deep sea. These results suggest that amino acid substitutions of these positively selected genes may contribute crucially to the adaptation of deep-sea animals. Additionally, we provide a high-quality transcriptome of a deep-sea fish for future deep-sea studies.

Chiron: translating nanopore raw signal directly into nucleotide sequence using deep learning

KAUST Repository

Teng, Haotian; Cao, Minh Duc; Hall, Michael B; Duarte, Tania; Wang, Sheng; Coin, Lachlan J M

2018-01-01

Sequencing by translocating DNA fragments through an array of nanopores is a rapidly maturing technology that offers faster and cheaper sequencing than other approaches. However, accurately deciphering the DNA sequence from the noisy and complex electrical signal is challenging. Here, we report Chiron, the first deep learning model to achieve end-to-end basecalling and directly translate the raw signal to DNA sequence without the error-prone segmentation step. Trained with only a small set of 4,000 reads, we show that our model provides state-of-the-art basecalling accuracy, even on previously unseen species. Chiron achieves basecalling speeds of more than 2,000 bases per second using desktop computer graphics processing units.

Chiron: translating nanopore raw signal directly into nucleotide sequence using deep learning

KAUST Repository

Teng, Haotian

2018-04-10

Sequencing by translocating DNA fragments through an array of nanopores is a rapidly maturing technology that offers faster and cheaper sequencing than other approaches. However, accurately deciphering the DNA sequence from the noisy and complex electrical signal is challenging. Here, we report Chiron, the first deep learning model to achieve end-to-end basecalling and directly translate the raw signal to DNA sequence without the error-prone segmentation step. Trained with only a small set of 4,000 reads, we show that our model provides state-of-the-art basecalling accuracy, even on previously unseen species. Chiron achieves basecalling speeds of more than 2,000 bases per second using desktop computer graphics processing units.

Deep sequencing-based transcriptome profiling analysis of bacteria-challenged Lateolabrax japonicus reveals insight into the immune-relevant genes in marine fish

Directory of Open Access Journals (Sweden)

Xiang Li-xin

2010-08-01

Full Text Available Abstract Background Systematic research on fish immunogenetics is indispensable in understanding the origin and evolution of immune systems. This has long been a challenging task because of the limited number of deep sequencing technologies and genome backgrounds of non-model fish available. The newly developed Solexa/Illumina RNA-seq and Digital gene expression (DGE are high-throughput sequencing approaches and are powerful tools for genomic studies at the transcriptome level. This study reports the transcriptome profiling analysis of bacteria-challenged Lateolabrax japonicus using RNA-seq and DGE in an attempt to gain insights into the immunogenetics of marine fish. Results RNA-seq analysis generated 169,950 non-redundant consensus sequences, among which 48,987 functional transcripts with complete or various length encoding regions were identified. More than 52% of these transcripts are possibly involved in approximately 219 known metabolic or signalling pathways, while 2,673 transcripts were associated with immune-relevant genes. In addition, approximately 8% of the transcripts appeared to be fish-specific genes that have never been described before. DGE analysis revealed that the host transcriptome profile of Vibrio harveyi-challenged L. japonicus is considerably altered, as indicated by the significant up- or down-regulation of 1,224 strong infection-responsive transcripts. Results indicated an overall conservation of the components and transcriptome alterations underlying innate and adaptive immunity in fish and other vertebrate models. Analysis suggested the acquisition of numerous fish-specific immune system components during early vertebrate evolution. Conclusion This study provided a global survey of host defence gene activities against bacterial challenge in a non-model marine fish. Results can contribute to the in-depth study of candidate genes in marine fish immunity, and help improve current understanding of host

Genetic diversity of archaea in deep-sea hydrothermal vent environments.

Science.gov (United States)

Takai, K; Horikoshi, K

1999-08-01

Molecular phylogenetic analysis of naturally occurring archaeal communities in deep-sea hydrothermal vent environments was carried out by PCR-mediated small subunit rRNA gene (SSU rDNA) sequencing. As determined through partial sequencing of rDNA clones amplified with archaea-specific primers, the archaeal populations in deep-sea hydrothermal vent environments showed a great genetic diversity, and most members of these populations appeared to be uncultivated and unidentified organisms. In the phylogenetic analysis, a number of rDNA sequences obtained from deep-sea hydrothermal vents were placed in deep lineages of the crenarchaeotic phylum prior to the divergence of cultivated thermophilic members of the crenarchaeota or between thermophilic members of the euryarchaeota and members of the methanogen-halophile clade. Whole cell in situ hybridization analysis suggested that some microorganisms of novel phylotypes predicted by molecular phylogenetic analysis were likely present in deep-sea hydrothermal vent environments. These findings expand our view of the genetic diversity of archaea in deep-sea hydrothermal vent environments and of the phylogenetic organization of archaea.

Deep RNA sequencing of the skeletal muscle transcriptome in swimming fish.

Directory of Open Access Journals (Sweden)

Arjan P Palstra

Full Text Available Deep RNA sequencing (RNA-seq was performed to provide an in-depth view of the transcriptome of red and white skeletal muscle of exercised and non-exercised rainbow trout (Oncorhynchus mykiss with the specific objective to identify expressed genes and quantify the transcriptomic effects of swimming-induced exercise. Pubertal autumn-spawning seawater-raised female rainbow trout were rested (n = 10 or swum (n = 10 for 1176 km at 0.75 body-lengths per second in a 6,000-L swim-flume under reproductive conditions for 40 days. Red and white muscle RNA of exercised and non-exercised fish (4 lanes was sequenced and resulted in 15-17 million reads per lane that, after de novo assembly, yielded 149,159 red and 118,572 white muscle contigs. Most contigs were annotated using an iterative homology search strategy against salmonid ESTs, the zebrafish Danio rerio genome and general Metazoan genes. When selecting for large contigs (>500 nucleotides, a number of novel rainbow trout gene sequences were identified in this study: 1,085 and 1,228 novel gene sequences for red and white muscle, respectively, which included a number of important molecules for skeletal muscle function. Transcriptomic analysis revealed that sustained swimming increased transcriptional activity in skeletal muscle and specifically an up-regulation of genes involved in muscle growth and developmental processes in white muscle. The unique collection of transcripts will contribute to our understanding of red and white muscle physiology, specifically during the long-term reproductive migration of salmonids.

Deep Sequence Analysis of AgoshRNA Processing Reveals 3’ A Addition and Trimming

Directory of Open Access Journals (Sweden)

Alex Harwig

2015-01-01

Full Text Available The RNA interference (RNAi pathway, in which microprocessor and Dicer collaborate to process microRNAs (miRNA, was recently expanded by the description of alternative processing routes. In one of these noncanonical pathways, Dicer action is replaced by the Argonaute2 (Ago2 slicer function. It was recently shown that the stem-length of precursor-miRNA or short hairpin RNA (shRNA molecules is a major determinant for Dicer versus Ago2 processing. Here we present the results of a deep sequence study on the processing of shRNAs with different stem length and a top G·U wobble base pair (bp. This analysis revealed some unexpected properties of these so-called AgoshRNA molecules that are processed by Ago2 instead of Dicer. First, we confirmed the gradual shift from Dicer to Ago2 processing upon shortening of the hairpin length. Second, hairpins with a stem larger than 19 base pair are inefficiently cleaved by Ago2 and we noticed a shift in the cleavage site. Third, the introduction of a top G·U bp in a regular shRNA can promote Ago2-cleavage, which coincides with a loss of Ago2-loading of the Dicer-cleaved 3’ strand. Fourth, the Ago2-processed AgoshRNAs acquire a short 3’ tail of 1–3 A-nucleotides (nt and we present evidence that this product is subsequently trimmed by the poly(A-specific ribonuclease (PARN.

Deep Sequencing Reveals the Complete Genome and Evidence for Transcriptional Activity of the First Virus-Like Sequences Identified in Aristotelia chilensis (Maqui Berry

Directory of Open Access Journals (Sweden)

Javier Villacreses

2015-04-01

Full Text Available Here, we report the genome sequence and evidence for transcriptional activity of a virus-like element in the native Chilean berry tree Aristotelia chilensis. We propose to name the endogenous sequence as Aristotelia chilensis Virus 1 (AcV1. High-throughput sequencing of the genome of this tree uncovered an endogenous viral element, with a size of 7122 bp, corresponding to the complete genome of AcV1. Its sequence contains three open reading frames (ORFs: ORFs 1 and 2 shares 66%–73% amino acid similarity with members of the Caulimoviridae virus family, especially the Petunia vein clearing virus (PVCV, Petuvirus genus. ORF1 encodes a movement protein (MP; ORF2 a Reverse Transcriptase (RT and a Ribonuclease H (RNase H domain; and ORF3 showed no amino acid sequence similarity with any other known virus proteins. Analogous to other known endogenous pararetrovirus sequences (EPRVs, AcV1 is integrated in the genome of Maqui Berry and showed low viral transcriptional activity, which was detected by deep sequencing technology (DNA and RNA-seq. Phylogenetic analysis of AcV1 and other pararetroviruses revealed a closer resemblance with Petuvirus. Overall, our data suggests that AcV1 could be a new member of Caulimoviridae family, genus Petuvirus, and the first evidence of this kind of virus in a fruit plant.

Efficient forward propagation of time-sequences in convolutional neural networks using Deep Shifting

NARCIS (Netherlands)

K.L. Groenland (Koen); S.M. Bohte (Sander)

2016-01-01

textabstractWhen a Convolutional Neural Network is used for on-the-fly evaluation of continuously updating time-sequences, many redundant convolution operations are performed. We propose the method of Deep Shifting, which remembers previously calculated results of convolution operations in order

HIV-1 transmission patterns in antiretroviral therapy-naive, HIV-infected North Americans based on phylogenetic analysis by population level and ultra-deep DNA sequencing.

Directory of Open Access Journals (Sweden)

Lisa L Ross

Full Text Available Factors that contribute to the transmission of human immunodeficiency virus type 1 (HIV-1, especially drug-resistant HIV-1 variants remain a significant public health concern. In-depth phylogenetic analyses of viral sequences obtained in the screening phase from antiretroviral-naïve HIV-infected patients seeking enrollment in EPZ108859, a large open-label study in the USA, Canada and Puerto Rico (ClinicalTrials.gov NCT00440947 were examined for insights into the roles of drug resistance and epidemiological factors that could impact disease dissemination. Viral transmission clusters (VTCs were initially predicted from a phylogenetic analysis of population level HIV-1 pol sequences obtained from 690 antiretroviral-naïve subjects in 2007. Subsequently, the predicted VTCs were tested for robustness by ultra deep sequencing (UDS using pyrosequencing technology and further phylogenetic analyses. The demographic characteristics of clustered and non-clustered subjects were then compared. From 690 subjects, 69 were assigned to 1 of 30 VTCs, each containing 2 to 5 subjects. Race composition of VTCs were significantly more likely to be white (72% vs. 60%; p = 0.04. VTCs had fewer reverse transcriptase and major PI resistance mutations (9% vs. 24%; p = 0.002 than non-clustered sequences. Both men-who-have-sex-with-men (MSM (68% vs. 48%; p = 0.001 and Canadians (29% vs. 14%; p = 0.03 were significantly more frequent in VTCs than non-clustered sequences. Of the 515 subjects who initiated antiretroviral therapy, 33 experienced confirmed virologic failure through 144 weeks while only 3/33 were from VTCs. Fewer VTCs subjects (as compared to those with non-clustering virus had HIV-1 with resistance-associated mutations or experienced virologic failure during the course of the study. Our analysis shows specific geographical and drug resistance trends that correlate well with transmission clusters defined by HIV sequences of similarity

Prognostic value of deep sequencing method for minimal residual disease detection in multiple myeloma

Science.gov (United States)

Lahuerta, Juan J.; Pepin, François; González, Marcos; Barrio, Santiago; Ayala, Rosa; Puig, Noemí; Montalban, María A.; Paiva, Bruno; Weng, Li; Jiménez, Cristina; Sopena, María; Moorhead, Martin; Cedena, Teresa; Rapado, Immaculada; Mateos, María Victoria; Rosiñol, Laura; Oriol, Albert; Blanchard, María J.; Martínez, Rafael; Bladé, Joan; San Miguel, Jesús; Faham, Malek; García-Sanz, Ramón

2014-01-01

We assessed the prognostic value of minimal residual disease (MRD) detection in multiple myeloma (MM) patients using a sequencing-based platform in bone marrow samples from 133 MM patients in at least very good partial response (VGPR) after front-line therapy. Deep sequencing was carried out in patients in whom a high-frequency myeloma clone was identified and MRD was assessed using the IGH-VDJH, IGH-DJH, and IGK assays. The results were contrasted with those of multiparametric flow cytometry (MFC) and allele-specific oligonucleotide polymerase chain reaction (ASO-PCR). The applicability of deep sequencing was 91%. Concordance between sequencing and MFC and ASO-PCR was 83% and 85%, respectively. Patients who were MRD– by sequencing had a significantly longer time to tumor progression (TTP) (median 80 vs 31 months; P < .0001) and overall survival (median not reached vs 81 months; P = .02), compared with patients who were MRD+. When stratifying patients by different levels of MRD, the respective TTP medians were: MRD ≥10−3 27 months, MRD 10−3 to 10−5 48 months, and MRD <10−5 80 months (P = .003 to .0001). Ninety-two percent of VGPR patients were MRD+. In complete response patients, the TTP remained significantly longer for MRD– compared with MRD+ patients (131 vs 35 months; P = .0009). PMID:24646471

Foundations of Sequence-to-Sequence Modeling for Time Series

OpenAIRE

Kuznetsov, Vitaly; Mariet, Zelda

2018-01-01

The availability of large amounts of time series data, paired with the performance of deep-learning algorithms on a broad class of problems, has recently led to significant interest in the use of sequence-to-sequence models for time series forecasting. We provide the first theoretical analysis of this time series forecasting framework. We include a comparison of sequence-to-sequence modeling to classical time series models, and as such our theory can serve as a quantitative guide for practiti...

microRNA expression profiling in fetal single ventricle malformation identified by deep sequencing.

Science.gov (United States)

Yu, Zhang-Bin; Han, Shu-Ping; Bai, Yun-Fei; Zhu, Chun; Pan, Ya; Guo, Xi-Rong

2012-01-01

microRNAs (miRNAs) have emerged as key regulators in many biological processes, particularly cardiac growth and development, although the specific miRNA expression profile associated with this process remains to be elucidated. This study aimed to characterize the cellular microRNA profile involved in the development of congenital heart malformation, through the investigation of single ventricle (SV) defects. Comprehensive miRNA profiling in human fetal SV cardiac tissue was performed by deep sequencing. Differential expression of 48 miRNAs was revealed by sequencing by oligonucleotide ligation and detection (SOLiD) analysis. Of these, 38 were down-regulated and 10 were up-regulated in differentiated SV cardiac tissue, compared to control cardiac tissue. This was confirmed by real-time quantitative reverse transcription-polymerase chain reaction (qRT-PCR) analysis. Predicted target genes of the 48 differentially expressed miRNAs were analyzed by gene ontology and categorized according to cellular process, regulation of biological process and metabolic process. Pathway-Express analysis identified the WNT and mTOR signaling pathways as the most significant processes putatively affected by the differential expression of these miRNAs. The candidate genes involved in cardiac development were identified as potential targets for these differentially expressed microRNAs and the collaborative network of microRNAs and cardiac development related-mRNAs was constructed. These data provide the basis for future investigation of the mechanism of the occurrence and development of fetal SV malformations.

Integrative analysis of deep sequencing data identifies estrogen receptor early response genes and links ATAD3B to poor survival in breast cancer.

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Kristian Ovaska

Full Text Available Identification of responsive genes to an extra-cellular cue enables characterization of pathophysiologically crucial biological processes. Deep sequencing technologies provide a powerful means to identify responsive genes, which creates a need for computational methods able to analyze dynamic and multi-level deep sequencing data. To answer this need we introduce here a data-driven algorithm, SPINLONG, which is designed to search for genes that match the user-defined hypotheses or models. SPINLONG is applicable to various experimental setups measuring several molecular markers in parallel. To demonstrate the SPINLONG approach, we analyzed ChIP-seq data reporting PolII, estrogen receptor α (ERα, H3K4me3 and H2A.Z occupancy at five time points in the MCF-7 breast cancer cell line after estradiol stimulus. We obtained 777 ERa early responsive genes and compared the biological functions of the genes having ERα binding within 20 kb of the transcription start site (TSS to genes without such binding site. Our results show that the non-genomic action of ERα via the MAPK pathway, instead of direct ERa binding, may be responsible for early cell responses to ERα activation. Our results also indicate that the ERα responsive genes triggered by the genomic pathway are transcribed faster than those without ERα binding sites. The survival analysis of the 777 ERα responsive genes with 150 primary breast cancer tumors and in two independent validation cohorts indicated the ATAD3B gene, which does not have ERα binding site within 20 kb of its TSS, to be significantly associated with poor patient survival.

Evaluation of Nine Somatic Variant Callers for Detection of Somatic Mutations in Exome and Targeted Deep Sequencing Data

DEFF Research Database (Denmark)

Krøigård, Anne Bruun; Thomassen, Mads; Lænkholm, Anne Vibeke

2016-01-01

a comprehensive evaluation using exome sequencing and targeted deep sequencing data of paired tumor-normal samples from five breast cancer patients to evaluate the performance of nine publicly available somatic variant callers: EBCall, Mutect, Seurat, Shimmer, Indelocator, Somatic Sniper, Strelka, VarScan 2...

Deep Learning and Its Applications in Biomedicine.

Science.gov (United States)

Cao, Chensi; Liu, Feng; Tan, Hai; Song, Deshou; Shu, Wenjie; Li, Weizhong; Zhou, Yiming; Bo, Xiaochen; Xie, Zhi

2018-02-01

Advances in biological and medical technologies have been providing us explosive volumes of biological and physiological data, such as medical images, electroencephalography, genomic and protein sequences. Learning from these data facilitates the understanding of human health and disease. Developed from artificial neural networks, deep learning-based algorithms show great promise in extracting features and learning patterns from complex data. The aim of this paper is to provide an overview of deep learning techniques and some of the state-of-the-art applications in the biomedical field. We first introduce the development of artificial neural network and deep learning. We then describe two main components of deep learning, i.e., deep learning architectures and model optimization. Subsequently, some examples are demonstrated for deep learning applications, including medical image classification, genomic sequence analysis, as well as protein structure classification and prediction. Finally, we offer our perspectives for the future directions in the field of deep learning. Copyright © 2018. Production and hosting by Elsevier B.V.

Transcriptional Slippage and RNA Editing Increase the Diversity of Transcripts in Chloroplasts: Insight from Deep Sequencing of Vigna radiata Genome and Transcriptome.

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Ching-Ping Lin

Full Text Available We performed deep sequencing of the nuclear and organellar genomes of three mungbean genotypes: Vigna radiata ssp. sublobata TC1966, V. radiata var. radiata NM92 and the recombinant inbred line RIL59 derived from a cross between TC1966 and NM92. Moreover, we performed deep sequencing of the RIL59 transcriptome to investigate transcript variability. The mungbean chloroplast genome has a quadripartite structure including a pair of inverted repeats separated by two single copy regions. A total of 213 simple sequence repeats were identified in the chloroplast genomes of NM92 and RIL59; 78 single nucleotide variants and nine indels were discovered in comparing the chloroplast genomes of TC1966 and NM92. Analysis of the mungbean chloroplast transcriptome revealed mRNAs that were affected by transcriptional slippage and RNA editing. Transcriptional slippage frequency was positively correlated with the length of simple sequence repeats of the mungbean chloroplast genome (R2=0.9911. In total, 41 C-to-U editing sites were found in 23 chloroplast genes and in one intergenic spacer. No editing site that swapped U to C was found. A combination of bioinformatics and experimental methods revealed that the plastid-encoded RNA polymerase-transcribed genes psbF and ndhA are affected by transcriptional slippage in mungbean and in main lineages of land plants, including three dicots (Glycine max, Brassica rapa, and Nicotiana tabacum, two monocots (Oryza sativa and Zea mays, two gymnosperms (Pinus taeda and Ginkgo biloba and one moss (Physcomitrella patens. Transcript analysis of the rps2 gene showed that transcriptional slippage could affect transcripts at single sequence repeat regions with poly-A runs. It showed that transcriptional slippage together with incomplete RNA editing may cause sequence diversity of transcripts in chloroplasts of land plants.

Evaluation of Nine Somatic Variant Callers for Detection of Somatic Mutations in Exome and Targeted Deep Sequencing Data.

Science.gov (United States)

Krøigård, Anne Bruun; Thomassen, Mads; Lænkholm, Anne-Vibeke; Kruse, Torben A; Larsen, Martin Jakob

2016-01-01

Next generation sequencing is extensively applied to catalogue somatic mutations in cancer, in research settings and increasingly in clinical settings for molecular diagnostics, guiding therapy decisions. Somatic variant callers perform paired comparisons of sequencing data from cancer tissue and matched normal tissue in order to detect somatic mutations. The advent of many new somatic variant callers creates a need for comparison and validation of the tools, as no de facto standard for detection of somatic mutations exists and only limited comparisons have been reported. We have performed a comprehensive evaluation using exome sequencing and targeted deep sequencing data of paired tumor-normal samples from five breast cancer patients to evaluate the performance of nine publicly available somatic variant callers: EBCall, Mutect, Seurat, Shimmer, Indelocator, Somatic Sniper, Strelka, VarScan 2 and Virmid for the detection of single nucleotide mutations and small deletions and insertions. We report a large variation in the number of calls from the nine somatic variant callers on the same sequencing data and highly variable agreement. Sequencing depth had markedly diverse impact on individual callers, as for some callers, increased sequencing depth highly improved sensitivity. For SNV calling, we report EBCall, Mutect, Virmid and Strelka to be the most reliable somatic variant callers for both exome sequencing and targeted deep sequencing. For indel calling, EBCall is superior due to high sensitivity and robustness to changes in sequencing depths.

High-resolution deep sequencing reveals biodiversity, population structure, and persistence of HIV-1 quasispecies within host ecosystems

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Yin Li

2012-12-01

Full Text Available Abstract Background Deep sequencing provides the basis for analysis of biodiversity of taxonomically similar organisms in an environment. While extensively applied to microbiome studies, population genetics studies of viruses are limited. To define the scope of HIV-1 population biodiversity within infected individuals, a suite of phylogenetic and population genetic algorithms was applied to HIV-1 envelope hypervariable domain 3 (Env V3 within peripheral blood mononuclear cells from a group of perinatally HIV-1 subtype B infected, therapy-naïve children. Results Biodiversity of HIV-1 Env V3 quasispecies ranged from about 70 to 270 unique sequence clusters across individuals. Viral population structure was organized into a limited number of clusters that included the dominant variants combined with multiple clusters of low frequency variants. Next generation viral quasispecies evolved from low frequency variants at earlier time points through multiple non-synonymous changes in lineages within the evolutionary landscape. Minor V3 variants detected as long as four years after infection co-localized in phylogenetic reconstructions with early transmitting viruses or with subsequent plasma virus circulating two years later. Conclusions Deep sequencing defines HIV-1 population complexity and structure, reveals the ebb and flow of dominant and rare viral variants in the host ecosystem, and identifies an evolutionary record of low-frequency cell-associated viral V3 variants that persist for years. Bioinformatics pipeline developed for HIV-1 can be applied for biodiversity studies of virome populations in human, animal, or plant ecosystems.

Ultra-deep sequencing of mouse mitochondrial DNA: mutational patterns and their origins.

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Adam Ameur

2011-03-01

Full Text Available Somatic mutations of mtDNA are implicated in the aging process, but there is no universally accepted method for their accurate quantification. We have used ultra-deep sequencing to study genome-wide mtDNA mutation load in the liver of normally- and prematurely-aging mice. Mice that are homozygous for an allele expressing a proof-reading-deficient mtDNA polymerase (mtDNA mutator mice have 10-times-higher point mutation loads than their wildtype siblings. In addition, the mtDNA mutator mice have increased levels of a truncated linear mtDNA molecule, resulting in decreased sequence coverage in the deleted region. In contrast, circular mtDNA molecules with large deletions occur at extremely low frequencies in mtDNA mutator mice and can therefore not drive the premature aging phenotype. Sequence analysis shows that the main proportion of the mutation load in heterozygous mtDNA mutator mice and their wildtype siblings is inherited from their heterozygous mothers consistent with germline transmission. We found no increase in levels of point mutations or deletions in wildtype C57Bl/6N mice with increasing age, thus questioning the causative role of these changes in aging. In addition, there was no increased frequency of transversion mutations with time in any of the studied genotypes, arguing against oxidative damage as a major cause of mtDNA mutations. Our results from studies of mice thus indicate that most somatic mtDNA mutations occur as replication errors during development and do not result from damage accumulation in adult life.

Deep Ion Torrent sequencing identifies soil fungal community shifts after frequent prescribed fires in a southeastern US forest ecosystem.

Science.gov (United States)

Brown, Shawn P; Callaham, Mac A; Oliver, Alena K; Jumpponen, Ari

2013-12-01

Prescribed burning is a common management tool to control fuel loads, ground vegetation, and facilitate desirable game species. We evaluated soil fungal community responses to long-term prescribed fire treatments in a loblolly pine forest on the Piedmont of Georgia and utilized deep Internal Transcribed Spacer Region 1 (ITS1) amplicon sequencing afforded by the recent Ion Torrent Personal Genome Machine (PGM). These deep sequence data (19,000 + reads per sample after subsampling) indicate that frequent fires (3-year fire interval) shift soil fungus communities, whereas infrequent fires (6-year fire interval) permit system resetting to a state similar to that without prescribed fire. Furthermore, in nonmetric multidimensional scaling analyses, primarily ectomycorrhizal taxa were correlated with axes associated with long fire intervals, whereas soil saprobes tended to be correlated with the frequent fire recurrence. We conclude that (1) multiplexed Ion Torrent PGM analyses allow deep cost effective sequencing of fungal communities but may suffer from short read lengths and inconsistent sequence quality adjacent to the sequencing adaptor; (2) frequent prescribed fires elicit a shift in soil fungal communities; and (3) such shifts do not occur when fire intervals are longer. Our results emphasize the general responsiveness of these forests to management, and the importance of fire return intervals in meeting management objectives. © 2013 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved.

Evaluation of Nine Somatic Variant Callers for Detection of Somatic Mutations in Exome and Targeted Deep Sequencing Data.

Directory of Open Access Journals (Sweden)

Anne Bruun Krøigård

Full Text Available Next generation sequencing is extensively applied to catalogue somatic mutations in cancer, in research settings and increasingly in clinical settings for molecular diagnostics, guiding therapy decisions. Somatic variant callers perform paired comparisons of sequencing data from cancer tissue and matched normal tissue in order to detect somatic mutations. The advent of many new somatic variant callers creates a need for comparison and validation of the tools, as no de facto standard for detection of somatic mutations exists and only limited comparisons have been reported. We have performed a comprehensive evaluation using exome sequencing and targeted deep sequencing data of paired tumor-normal samples from five breast cancer patients to evaluate the performance of nine publicly available somatic variant callers: EBCall, Mutect, Seurat, Shimmer, Indelocator, Somatic Sniper, Strelka, VarScan 2 and Virmid for the detection of single nucleotide mutations and small deletions and insertions. We report a large variation in the number of calls from the nine somatic variant callers on the same sequencing data and highly variable agreement. Sequencing depth had markedly diverse impact on individual callers, as for some callers, increased sequencing depth highly improved sensitivity. For SNV calling, we report EBCall, Mutect, Virmid and Strelka to be the most reliable somatic variant callers for both exome sequencing and targeted deep sequencing. For indel calling, EBCall is superior due to high sensitivity and robustness to changes in sequencing depths.

Phylogenetic and genome-wide deep-sequencing analyses of canine parvovirus reveal co-infection with field variants and emergence of a recent recombinant strain.

Directory of Open Access Journals (Sweden)

Ruben Pérez

Full Text Available Canine parvovirus (CPV, a fast-evolving single-stranded DNA virus, comprises three antigenic variants (2a, 2b, and 2c with different frequencies and genetic variability among countries. The contribution of co-infection and recombination to the genetic variability of CPV is far from being fully elucidated. Here we took advantage of a natural CPV population, recently formed by the convergence of divergent CPV-2c and CPV-2a strains, to study co-infection and recombination. Complete sequences of the viral coding region of CPV-2a and CPV-2c strains from 40 samples were generated and analyzed using phylogenetic tools. Two samples showed co-infection and were further analyzed by deep sequencing. The sequence profile of one of the samples revealed the presence of CPV-2c and CPV-2a strains that differed at 29 nucleotides. The other sample included a minor CPV-2a strain (13.3% of the viral population and a major recombinant strain (86.7%. The recombinant strain arose from inter-genotypic recombination between CPV-2c and CPV-2a strains within the VP1/VP2 gene boundary. Our findings highlight the importance of deep-sequencing analysis to provide a better understanding of CPV molecular diversity.

Phylogenetic and Genome-Wide Deep-Sequencing Analyses of Canine Parvovirus Reveal Co-Infection with Field Variants and Emergence of a Recent Recombinant Strain

Science.gov (United States)

Pérez, Ruben; Calleros, Lucía; Marandino, Ana; Sarute, Nicolás; Iraola, Gregorio; Grecco, Sofia; Blanc, Hervé; Vignuzzi, Marco; Isakov, Ofer; Shomron, Noam; Carrau, Lucía; Hernández, Martín; Francia, Lourdes; Sosa, Katia; Tomás, Gonzalo; Panzera, Yanina

2014-01-01

Canine parvovirus (CPV), a fast-evolving single-stranded DNA virus, comprises three antigenic variants (2a, 2b, and 2c) with different frequencies and genetic variability among countries. The contribution of co-infection and recombination to the genetic variability of CPV is far from being fully elucidated. Here we took advantage of a natural CPV population, recently formed by the convergence of divergent CPV-2c and CPV-2a strains, to study co-infection and recombination. Complete sequences of the viral coding region of CPV-2a and CPV-2c strains from 40 samples were generated and analyzed using phylogenetic tools. Two samples showed co-infection and were further analyzed by deep sequencing. The sequence profile of one of the samples revealed the presence of CPV-2c and CPV-2a strains that differed at 29 nucleotides. The other sample included a minor CPV-2a strain (13.3% of the viral population) and a major recombinant strain (86.7%). The recombinant strain arose from inter-genotypic recombination between CPV-2c and CPV-2a strains within the VP1/VP2 gene boundary. Our findings highlight the importance of deep-sequencing analysis to provide a better understanding of CPV molecular diversity. PMID:25365348

High-Quality Draft Single-Cell Genome Sequence Belonging to the Archaeal Candidate Division SA1, Isolated from Nereus Deep in the Red Sea

KAUST Repository

Ngugi, David; Stingl, Ulrich

2018-01-01

Candidate division SA1 encompasses a phylogenetically coherent archaeal group ubiquitous in deep hypersaline anoxic brines around the globe. Recently, the genome sequences of two cultivated representatives from hypersaline soda lake sediments were published. Here, we present a single-cell genome sequence from Nereus Deep in the Red Sea that represents a putatively novel family within SA1.

High-Quality Draft Single-Cell Genome Sequence Belonging to the Archaeal Candidate Division SA1, Isolated from Nereus Deep in the Red Sea

KAUST Repository

Ngugi, David

2018-05-09

Candidate division SA1 encompasses a phylogenetically coherent archaeal group ubiquitous in deep hypersaline anoxic brines around the globe. Recently, the genome sequences of two cultivated representatives from hypersaline soda lake sediments were published. Here, we present a single-cell genome sequence from Nereus Deep in the Red Sea that represents a putatively novel family within SA1.

An introduction to deep learning on biological sequence data: examples and solutions.

Science.gov (United States)

Jurtz, Vanessa Isabell; Johansen, Alexander Rosenberg; Nielsen, Morten; Almagro Armenteros, Jose Juan; Nielsen, Henrik; Sønderby, Casper Kaae; Winther, Ole; Sønderby, Søren Kaae

2017-11-15

Deep neural network architectures such as convolutional and long short-term memory networks have become increasingly popular as machine learning tools during the recent years. The availability of greater computational resources, more data, new algorithms for training deep models and easy to use libraries for implementation and training of neural networks are the drivers of this development. The use of deep learning has been especially successful in image recognition; and the development of tools, applications and code examples are in most cases centered within this field rather than within biology. Here, we aim to further the development of deep learning methods within biology by providing application examples and ready to apply and adapt code templates. Given such examples, we illustrate how architectures consisting of convolutional and long short-term memory neural networks can relatively easily be designed and trained to state-of-the-art performance on three biological sequence problems: prediction of subcellular localization, protein secondary structure and the binding of peptides to MHC Class II molecules. All implementations and datasets are available online to the scientific community at https://github.com/vanessajurtz/lasagne4bio. skaaesonderby@gmail.com. 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

Simultaneous identification of DNA and RNA viruses present in pig faeces using process-controlled deep sequencing.

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Jana Sachsenröder

Full Text Available BACKGROUND: Animal faeces comprise a community of many different microorganisms including bacteria and viruses. Only scarce information is available about the diversity of viruses present in the faeces of pigs. Here we describe a protocol, which was optimized for the purification of the total fraction of viral particles from pig faeces. The genomes of the purified DNA and RNA viruses were simultaneously amplified by PCR and subjected to deep sequencing followed by bioinformatic analyses. The efficiency of the method was monitored using a process control consisting of three bacteriophages (T4, M13 and MS2 with different morphology and genome types. Defined amounts of the bacteriophages were added to the sample and their abundance was assessed by quantitative PCR during the preparation procedure. RESULTS: The procedure was applied to a pooled faecal sample of five pigs. From this sample, 69,613 sequence reads were generated. All of the added bacteriophages were identified by sequence analysis of the reads. In total, 7.7% of the reads showed significant sequence identities with published viral sequences. They mainly originated from bacteriophages (73.9% and mammalian viruses (23.9%; 0.8% of the sequences showed identities to plant viruses. The most abundant detected porcine viruses were kobuvirus, rotavirus C, astrovirus, enterovirus B, sapovirus and picobirnavirus. In addition, sequences with identities to the chimpanzee stool-associated circular ssDNA virus were identified. Whole genome analysis indicates that this virus, tentatively designated as pig stool-associated circular ssDNA virus (PigSCV, represents a novel pig virus. CONCLUSION: The established protocol enables the simultaneous detection of DNA and RNA viruses in pig faeces including the identification of so far unknown viruses. It may be applied in studies investigating aetiology, epidemiology and ecology of diseases. The implemented process control serves as quality control, ensures

Deep sequencing and flow cytometric characterization of expanded effector memory CD8+CD57+ T cells frequently reveals T-cell receptor Vβ oligoclonality and CDR3 homology in acquired aplastic anemia.

Science.gov (United States)

Giudice, Valentina; Feng, Xingmin; Lin, Zenghua; Hu, Wei; Zhang, Fanmao; Qiao, Wangmin; Ibanez, Maria Del Pilar Fernandez; Rios, Olga; Young, Neal S

2018-05-01

Oligoclonal expansion of CD8 + CD28 - lymphocytes has been considered indirect evidence for a pathogenic immune response in acquired aplastic anemia. A subset of CD8 + CD28 - cells with CD57 expression, termed effector memory cells, is expanded in several immune-mediated diseases and may have a role in immune surveillance. We hypothesized that effector memory CD8 + CD28 - CD57 + cells may drive aberrant oligoclonal expansion in aplastic anemia. We found CD8 + CD57 + cells frequently expanded in the blood of aplastic anemia patients, with oligoclonal characteristics by flow cytometric Vβ usage analysis: skewing in 1-5 Vβ families and frequencies of immunodominant clones ranging from 1.98% to 66.5%. Oligoclonal characteristics were also observed in total CD8 + cells from aplastic anemia patients with CD8 + CD57 + cell expansion by T-cell receptor deep sequencing, as well as the presence of 1-3 immunodominant clones. Oligoclonality was confirmed by T-cell receptor repertoire deep sequencing of enriched CD8 + CD57 + cells, which also showed decreased diversity compared to total CD4 + and CD8 + cell pools. From analysis of complementarity-determining region 3 sequences in the CD8 + cell pool, a total of 29 sequences were shared between patients and controls, but these sequences were highly expressed in aplastic anemia subjects and also present in their immunodominant clones. In summary, expansion of effector memory CD8 + T cells is frequent in aplastic anemia and mirrors Vβ oligoclonal expansion. Flow cytometric Vβ usage analysis combined with deep sequencing technologies allows high resolution characterization of the T-cell receptor repertoire, and might represent a useful tool in the diagnosis and periodic evaluation of aplastic anemia patients. (Registered at clinicaltrials.gov identifiers: 00001620, 01623167, 00001397, 00071045, 00081523, 00961064 ). Copyright © 2018 Ferrata Storti Foundation.

Micropathogen Community Analysis in Hyalomma rufipes via High-Throughput Sequencing of Small RNAs

Science.gov (United States)

Luo, Jin; Liu, Min-Xuan; Ren, Qiao-Yun; Chen, Ze; Tian, Zhan-Cheng; Hao, Jia-Wei; Wu, Feng; Liu, Xiao-Cui; Luo, Jian-Xun; Yin, Hong; Wang, Hui; Liu, Guang-Yuan

2017-01-01

Ticks are important vectors in the transmission of a broad range of micropathogens to vertebrates, including humans. Because of the role of ticks in disease transmission, identifying and characterizing the micropathogen profiles of tick populations have become increasingly important. The objective of this study was to survey the micropathogens of Hyalomma rufipes ticks. Illumina HiSeq2000 technology was utilized to perform deep sequencing of small RNAs (sRNAs) extracted from field-collected H. rufipes ticks in Gansu Province, China. The resultant sRNA library data revealed that the surveyed tick populations produced reads that were homologous to St. Croix River Virus (SCRV) sequences. We also observed many reads that were homologous to microbial and/or pathogenic isolates, including bacteria, protozoa, and fungi. As part of this analysis, a phylogenetic tree was constructed to display the relationships among the homologous sequences that were identified. The study offered a unique opportunity to gain insight into the micropathogens of H. rufipes ticks. The effective control of arthropod vectors in the future will require knowledge of the micropathogen composition of vectors harboring infectious agents. Understanding the ecological factors that regulate vector propagation in association with the prevalence and persistence of micropathogen lineages is also imperative. These interactions may affect the evolution of micropathogen lineages, especially if the micropathogens rely on the vector or host for dispersal. The sRNA deep-sequencing approach used in this analysis provides an intuitive method to survey micropathogen prevalence in ticks and other vector species. PMID:28861401

Analysis of microRNA profile of Anopheles sinensis by deep sequencing and bioinformatic approaches.

Science.gov (United States)

Feng, Xinyu; Zhou, Xiaojian; Zhou, Shuisen; Wang, Jingwen; Hu, Wei

2018-03-12

microRNAs (miRNAs) are small non-coding RNAs widely identified in many mosquitoes. They are reported to play important roles in development, differentiation and innate immunity. However, miRNAs in Anopheles sinensis, one of the Chinese malaria mosquitoes, remain largely unknown. We investigated the global miRNA expression profile of An. sinensis using Illumina Hiseq 2000 sequencing. Meanwhile, we applied a bioinformatic approach to identify potential miRNAs in An. sinensis. The identified miRNA profiles were compared and analyzed by two approaches. The selected miRNAs from the sequencing result and the bioinformatic approach were confirmed with qRT-PCR. Moreover, target prediction, GO annotation and pathway analysis were carried out to understand the role of miRNAs in An. sinensis. We identified 49 conserved miRNAs and 12 novel miRNAs by next-generation high-throughput sequencing technology. In contrast, 43 miRNAs were predicted by the bioinformatic approach, of which two were assigned as novel. Comparative analysis of miRNA profiles by two approaches showed that 21 miRNAs were shared between them. Twelve novel miRNAs did not match any known miRNAs of any organism, indicating that they are possibly species-specific. Forty miRNAs were found in many mosquito species, indicating that these miRNAs are evolutionally conserved and may have critical roles in the process of life. Both the selected known and novel miRNAs (asi-miR-281, asi-miR-184, asi-miR-14, asi-miR-nov5, asi-miR-nov4, asi-miR-9383, and asi-miR-2a) could be detected by quantitative real-time PCR (qRT-PCR) in the sequenced sample, and the expression patterns of these miRNAs measured by qRT-PCR were in concordance with the original miRNA sequencing data. The predicted targets for the known and the novel miRNAs covered many important biological roles and pathways indicating the diversity of miRNA functions. We also found 21 conserved miRNAs and eight counterparts of target immune pathway genes in An. sinensis

Poly(A)-tag deep sequencing data processing to extract poly(A) sites.

Science.gov (United States)

Wu, Xiaohui; Ji, Guoli; Li, Qingshun Quinn

2015-01-01

Polyadenylation [poly(A)] is an essential posttranscriptional processing step in the maturation of eukaryotic mRNA. The advent of next-generation sequencing (NGS) technology has offered feasible means to generate large-scale data and new opportunities for intensive study of polyadenylation, particularly deep sequencing of the transcriptome targeting the junction of 3'-UTR and the poly(A) tail of the transcript. To take advantage of this unprecedented amount of data, we present an automated workflow to identify polyadenylation sites by integrating NGS data cleaning, processing, mapping, normalizing, and clustering. In this pipeline, a series of Perl scripts are seamlessly integrated to iteratively map the single- or paired-end sequences to the reference genome. After mapping, the poly(A) tags (PATs) at the same genome coordinate are grouped into one cleavage site, and the internal priming artifacts removed. Then the ambiguous region is introduced to parse the genome annotation for cleavage site clustering. Finally, cleavage sites within a close range of 24 nucleotides and from different samples can be clustered into poly(A) clusters. This procedure could be used to identify thousands of reliable poly(A) clusters from millions of NGS sequences in different tissues or treatments.

Protein model discrimination using mutational sensitivity derived from deep sequencing.

Science.gov (United States)

Adkar, Bharat V; Tripathi, Arti; Sahoo, Anusmita; Bajaj, Kanika; Goswami, Devrishi; Chakrabarti, Purbani; Swarnkar, Mohit K; Gokhale, Rajesh S; Varadarajan, Raghavan

2012-02-08

A major bottleneck in protein structure prediction is the selection of correct models from a pool of decoys. Relative activities of ∼1,200 individual single-site mutants in a saturation library of the bacterial toxin CcdB were estimated by determining their relative populations using deep sequencing. This phenotypic information was used to define an empirical score for each residue (RankScore), which correlated with the residue depth, and identify active-site residues. Using these correlations, ∼98% of correct models of CcdB (RMSD ≤ 4Å) were identified from a large set of decoys. The model-discrimination methodology was further validated on eleven different monomeric proteins using simulated RankScore values. The methodology is also a rapid, accurate way to obtain relative activities of each mutant in a large pool and derive sequence-structure-function relationships without protein isolation or characterization. It can be applied to any system in which mutational effects can be monitored by a phenotypic readout. Copyright © 2012 Elsevier Ltd. All rights reserved.

Deep-Sea, Deep-Sequencing: Metabarcoding Extracellular DNA from Sediments of Marine Canyons.

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Magdalena Guardiola

Full Text Available Marine sediments are home to one of the richest species pools on Earth, but logistics and a dearth of taxonomic work-force hinders the knowledge of their biodiversity. We characterized α- and β-diversity of deep-sea assemblages from submarine canyons in the western Mediterranean using an environmental DNA metabarcoding. We used a new primer set targeting a short eukaryotic 18S sequence (ca. 110 bp. We applied a protocol designed to obtain extractions enriched in extracellular DNA from replicated sediment corers. With this strategy we captured information from DNA (local or deposited from the water column that persists adsorbed to inorganic particles and buffered short-term spatial and temporal heterogeneity. We analysed replicated samples from 20 localities including 2 deep-sea canyons, 1 shallower canal, and two open slopes (depth range 100-2,250 m. We identified 1,629 MOTUs, among which the dominant groups were Metazoa (with representatives of 19 phyla, Alveolata, Stramenopiles, and Rhizaria. There was a marked small-scale heterogeneity as shown by differences in replicates within corers and within localities. The spatial variability between canyons was significant, as was the depth component in one of the canyons where it was tested. Likewise, the composition of the first layer (1 cm of sediment was significantly different from deeper layers. We found that qualitative (presence-absence and quantitative (relative number of reads data showed consistent trends of differentiation between samples and geographic areas. The subset of exclusively benthic MOTUs showed similar patterns of β-diversity and community structure as the whole dataset. Separate analyses of the main metazoan phyla (in number of MOTUs showed some differences in distribution attributable to different lifestyles. Our results highlight the differentiation that can be found even between geographically close assemblages, and sets the ground for future monitoring and conservation

Hybridization-based reconstruction of small non-coding RNA transcripts from deep sequencing data.

Science.gov (United States)

Ragan, Chikako; Mowry, Bryan J; Bauer, Denis C

2012-09-01

Recent advances in RNA sequencing technology (RNA-Seq) enables comprehensive profiling of RNAs by producing millions of short sequence reads from size-fractionated RNA libraries. Although conventional tools for detecting and distinguishing non-coding RNAs (ncRNAs) from reference-genome data can be applied to sequence data, ncRNA detection can be improved by harnessing the full information content provided by this new technology. Here we present NorahDesk, the first unbiased and universally applicable method for small ncRNAs detection from RNA-Seq data. NorahDesk utilizes the coverage-distribution of small RNA sequence data as well as thermodynamic assessments of secondary structure to reliably predict and annotate ncRNA classes. Using publicly available mouse sequence data from brain, skeletal muscle, testis and ovary, we evaluated our method with an emphasis on the performance for microRNAs (miRNAs) and piwi-interacting small RNA (piRNA). We compared our method with Dario and mirDeep2 and found that NorahDesk produces longer transcripts with higher read coverage. This feature makes it the first method particularly suitable for the prediction of both known and novel piRNAs.

Draft Genome Sequence of Deep-Sea Alteromonas sp. Strain V450 Isolated from the Marine Sponge Leiodermatium sp.

Science.gov (United States)

Wang, Guojun; Barrett, Nolan H; McCarthy, Peter J

2017-02-02

The proteobacterium Alteromonas sp. strain V450 was isolated from the Atlantic deep-sea sponge Leiodermatium sp. Here, we report the draft genome sequence of this strain, with a genome size of approx. 4.39 Mb and a G+C content of 44.01%. The results will aid deep-sea microbial ecology, evolution, and sponge-microbe association studies. Copyright © 2017 Wang et al.

De Novo Deep Transcriptome Analysis of Medicinal Plants for Gene Discovery in Biosynthesis of Plant Natural Products.

Science.gov (United States)

Han, R; Rai, A; Nakamura, M; Suzuki, H; Takahashi, H; Yamazaki, M; Saito, K

2016-01-01

Study on transcriptome, the entire pool of transcripts in an organism or single cells at certain physiological or pathological stage, is indispensable in unraveling the connection and regulation between DNA and protein. Before the advent of deep sequencing, microarray was the main approach to handle transcripts. Despite obvious shortcomings, including limited dynamic range and difficulties to compare the results from distinct experiments, microarray was widely applied. During the past decade, next-generation sequencing (NGS) has revolutionized our understanding of genomics in a fast, high-throughput, cost-effective, and tractable manner. By adopting NGS, efficiency and fruitful outcomes concerning the efforts to elucidate genes responsible for producing active compounds in medicinal plants were profoundly enhanced. The whole process involves steps, from the plant material sampling, to cDNA library preparation, to deep sequencing, and then bioinformatics takes over to assemble enormous-yet fragmentary-data from which to comb and extract information. The unprecedentedly rapid development of such technologies provides so many choices to facilitate the task, which can cause confusion when choosing the suitable methodology for specific purposes. Here, we review the general approaches for deep transcriptome analysis and then focus on their application in discovering biosynthetic pathways of medicinal plants that produce important secondary metabolites. © 2016 Elsevier Inc. All rights reserved.

InFusion: Advancing Discovery of Fusion Genes and Chimeric Transcripts from Deep RNA-Sequencing Data.

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Konstantin Okonechnikov

Full Text Available Analysis of fusion transcripts has become increasingly important due to their link with cancer development. Since high-throughput sequencing approaches survey fusion events exhaustively, several computational methods for the detection of gene fusions from RNA-seq data have been developed. This kind of analysis, however, is complicated by native trans-splicing events, the splicing-induced complexity of the transcriptome and biases and artefacts introduced in experiments and data analysis. There are a number of tools available for the detection of fusions from RNA-seq data; however, certain differences in specificity and sensitivity between commonly used approaches have been found. The ability to detect gene fusions of different types, including isoform fusions and fusions involving non-coding regions, has not been thoroughly studied yet. Here, we propose a novel computational toolkit called InFusion for fusion gene detection from RNA-seq data. InFusion introduces several unique features, such as discovery of fusions involving intergenic regions, and detection of anti-sense transcription in chimeric RNAs based on strand-specificity. Our approach demonstrates superior detection accuracy on simulated data and several public RNA-seq datasets. This improved performance was also evident when evaluating data from RNA deep-sequencing of two well-established prostate cancer cell lines. InFusion identified 26 novel fusion events that were validated in vitro, including alternatively spliced gene fusion isoforms and chimeric transcripts that include intergenic regions. The toolkit is freely available to download from http:/bitbucket.org/kokonech/infusion.

Biogeography of Persephonella in deep-sea hydrothermal vents of the Western Pacific.

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Sayaka eMino

2013-04-01

Full Text Available Deep-sea hydrothermal vent fields are areas on the seafloor with high biological productivity fueled by microbial chemosynthesis. Members of the Aquificales genus Persephonella are obligately chemosynthetic bacteria, and appear to be key players in carbon, sulfur, and nitrogen cycles in high temperature habitats at deep-sea vents. Although this group of bacteria has cosmopolitan distribution in deep-sea hydrothermal ecosystem around the world, little is known about their population structure such as intraspecific genomic diversity, distribution pattern, and phenotypic diversity. We developed the multi-locus sequence analysis (MLSA scheme for their genomic characterization. Sequence variation was determined in five housekeeping genes and one functional gene of 36 P. hydrogeniphila strains originated from the Okinawa Trough and the South Mariana Trough. Although the strains share > 98.7% similarities in 16S rRNA gene sequences, MLSA revealed 35 different sequence types, indicating their extensive genomic diversity. A phylogenetic tree inferred from all concatenated gene sequences revealed the clustering of isolates according to the geographic origin. In addition, the phenotypic clustering pattern inferred from whole-cell matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF/MS analysis can be correlated to their MLSA clustering pattern. This study represents the first MLSA combined with phenotypic analysis indicative of allopatric speciation of deep-sea hydrothermal vent bacteria.

Insights into the genetic structure and diversity of 38 South Asian Indians from deep whole-genome sequencing.

Science.gov (United States)

Wong, Lai-Ping; Lai, Jason Kuan-Han; Saw, Woei-Yuh; Ong, Rick Twee-Hee; Cheng, Anthony Youzhi; Pillai, Nisha Esakimuthu; Liu, Xuanyao; Xu, Wenting; Chen, Peng; Foo, Jia-Nee; Tan, Linda Wei-Lin; Koo, Seok-Hwee; Soong, Richie; Wenk, Markus Rene; Lim, Wei-Yen; Khor, Chiea-Chuen; Little, Peter; Chia, Kee-Seng; Teo, Yik-Ying

2014-05-01

South Asia possesses a significant amount of genetic diversity due to considerable intergroup differences in culture and language. There have been numerous reports on the genetic structure of Asian Indians, although these have mostly relied on genotyping microarrays or targeted sequencing of the mitochondria and Y chromosomes. Asian Indians in Singapore are primarily descendants of immigrants from Dravidian-language-speaking states in south India, and 38 individuals from the general population underwent deep whole-genome sequencing with a target coverage of 30X as part of the Singapore Sequencing Indian Project (SSIP). The genetic structure and diversity of these samples were compared against samples from the Singapore Sequencing Malay Project and populations in Phase 1 of the 1,000 Genomes Project (1 KGP). SSIP samples exhibited greater intra-population genetic diversity and possessed higher heterozygous-to-homozygous genotype ratio than other Asian populations. When compared against a panel of well-defined Asian Indians, the genetic makeup of the SSIP samples was closely related to South Indians. However, even though the SSIP samples clustered distinctly from the Europeans in the global population structure analysis with autosomal SNPs, eight samples were assigned to mitochondrial haplogroups that were predominantly present in Europeans and possessed higher European admixture than the remaining samples. An analysis of the relative relatedness between SSIP with two archaic hominins (Denisovan, Neanderthal) identified higher ancient admixture in East Asian populations than in SSIP. The data resource for these samples is publicly available and is expected to serve as a valuable complement to the South Asian samples in Phase 3 of 1 KGP.

Deep sequence characterisation of a divergent HPIV-4a from an adult with prolonged influenza-like illness

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Katherine E. Arden

2015-12-01

Deep sequencing allowed identification and genomic characterisation of a possible pathogen from an ILI as well as being an important tool to aid future understanding of the linkages between viral genetic variation, transmission and disease prognosis.

MicroRNA discovery and analysis of pinewood nematode Bursaphelenchus xylophilus by deep sequencing.

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Qi-Xing Huang

Full Text Available BACKGROUND: MicroRNAs (miRNAs are considered to be very important in regulating the growth, development, behavior and stress response in animals and plants in post-transcriptional gene regulation. Pinewood nematode, Bursaphelenchus xylophilus, is an important invasive plant parasitic nematode in Asia. To have a comprehensive knowledge about miRNAs of the nematode is necessary for further in-depth study on roles of miRNAs in the ecological adaptation of the invasive species. METHODS AND FINDINGS: Five small RNA libraries were constructed and sequenced by Illumina/Solexa deep-sequencing technology. A total of 810 miRNA candidates (49 conserved and 761 novel were predicted by a computational pipeline, of which 57 miRNAs (20 conserved and 37 novel encoded by 53 miRNA precursors were identified by experimental methods. Ten novel miRNAs were considered to be species-specific miRNAs of B. xylophilus. Comparison of expression profiles of miRNAs in the five small RNA libraries showed that many miRNAs exhibited obviously different expression levels in the third-stage dispersal juvenile and at a cold-stressed status. Most of the miRNAs exhibited obviously down-regulated expression in the dispersal stage. But differences among the three geographic libraries were not prominent. A total of 979 genes were predicted to be targets of these authentic miRNAs. Among them, seven heat shock protein genes were targeted by 14 miRNAs, and six FMRFamide-like neuropeptides genes were targeted by 17 miRNAs. A real-time quantitative polymerase chain reaction was used to quantify the mRNA expression levels of target genes. CONCLUSIONS: Basing on the fact that a negative correlation existed between the expression profiles of miRNAs and the mRNA expression profiles of their target genes (hsp, flp by comparing those of the nematodes at a cold stressed status and a normal status, we suggested that miRNAs might participate in ecological adaptation and behavior regulation of the

Genetic diversity of archaea in deep-sea hydrothermal vent environments.

OpenAIRE

Takai, K; Horikoshi, K

1999-01-01

Molecular phylogenetic analysis of naturally occurring archaeal communities in deep-sea hydrothermal vent environments was carried out by PCR-mediated small subunit rRNA gene (SSU rDNA) sequencing. As determined through partial sequencing of rDNA clones amplified with archaea-specific primers, the archaeal populations in deep-sea hydrothermal vent environments showed a great genetic diversity, and most members of these populations appeared to be uncultivated and unidentified organisms. In the...

Enhanced arbovirus surveillance with deep sequencing: Identification of novel rhabdoviruses and bunyaviruses in Australian mosquitoes.

Science.gov (United States)

Coffey, Lark L; Page, Brady L; Greninger, Alexander L; Herring, Belinda L; Russell, Richard C; Doggett, Stephen L; Haniotis, John; Wang, Chunlin; Deng, Xutao; Delwart, Eric L

2014-01-05

Viral metagenomics characterizes known and identifies unknown viruses based on sequence similarities to any previously sequenced viral genomes. A metagenomics approach was used to identify virus sequences in Australian mosquitoes causing cytopathic effects in inoculated mammalian cell cultures. Sequence comparisons revealed strains of Liao Ning virus (Reovirus, Seadornavirus), previously detected only in China, livestock-infecting Stretch Lagoon virus (Reovirus, Orbivirus), two novel dimarhabdoviruses, named Beaumont and North Creek viruses, and two novel orthobunyaviruses, named Murrumbidgee and Salt Ash viruses. The novel virus proteomes diverged by ≥ 50% relative to their closest previously genetically characterized viral relatives. Deep sequencing also generated genomes of Warrego and Wallal viruses, orbiviruses linked to kangaroo blindness, whose genomes had not been fully characterized. This study highlights viral metagenomics in concert with traditional arbovirus surveillance to characterize known and new arboviruses in field-collected mosquitoes. Follow-up epidemiological studies are required to determine whether the novel viruses infect humans. © 2013 Elsevier Inc. All rights reserved.

3' terminal diversity of MRP RNA and other human noncoding RNAs revealed by deep sequencing.

Science.gov (United States)

Goldfarb, Katherine C; Cech, Thomas R

2013-09-21

Post-transcriptional 3' end processing is a key component of RNA regulation. The abundant and essential RNA subunit of RNase MRP has been proposed to function in three distinct cellular compartments and therefore may utilize this mode of regulation. Here we employ 3' RACE coupled with high-throughput sequencing to characterize the 3' terminal sequences of human MRP RNA and other noncoding RNAs that form RNP complexes. The 3' terminal sequence of MRP RNA from HEK293T cells has a distinctive distribution of genomically encoded termini (including an assortment of U residues) with a portion of these selectively tagged by oligo(A) tails. This profile contrasts with the relatively homogenous 3' terminus of an in vitro transcribed MRP RNA control and the differing 3' terminal profiles of U3 snoRNA, RNase P RNA, and telomerase RNA (hTR). 3' RACE coupled with deep sequencing provides a valuable framework for the functional characterization of 3' terminal sequences of noncoding RNAs.

Viral metagenomics: Analysis of begomoviruses by illumina high-throughput sequencing

KAUST Repository

Idris, Ali

2014-03-12

Traditional DNA sequencing methods are inefficient, lack the ability to discern the least abundant viral sequences, and ineffective for determining the extent of variability in viral populations. Here, populations of single-stranded DNA plant begomoviral genomes and their associated beta- and alpha-satellite molecules (virus-satellite complexes) (genus, Begomovirus; family, Geminiviridae) were enriched from total nucleic acids isolated from symptomatic, field-infected plants, using rolling circle amplification (RCA). Enriched virus-satellite complexes were subjected to Illumina-Next Generation Sequencing (NGS). CASAVA and SeqMan NGen programs were implemented, respectively, for quality control and for de novo and reference-guided contig assembly of viral-satellite sequences. The authenticity of the begomoviral sequences, and the reproducibility of the Illumina-NGS approach for begomoviral deep sequencing projects, were validated by comparing NGS results with those obtained using traditional molecular cloning and Sanger sequencing of viral components and satellite DNAs, also enriched by RCA or amplified by polymerase chain reaction. As the use of NGS approaches, together with advances in software development, make possible deep sequence coverage at a lower cost; the approach described herein will streamline the exploration of begomovirus diversity and population structure from naturally infected plants, irrespective of viral abundance. This is the first report of the implementation of Illumina-NGS to explore the diversity and identify begomoviral-satellite SNPs directly from plants naturally-infected with begomoviruses under field conditions. 2014 by the authors; licensee MDPI, Basel, Switzerland.

Viral Metagenomics: Analysis of Begomoviruses by Illumina High-Throughput Sequencing

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Ali Idris

2014-03-01

Full Text Available Traditional DNA sequencing methods are inefficient, lack the ability to discern the least abundant viral sequences, and ineffective for determining the extent of variability in viral populations. Here, populations of single-stranded DNA plant begomoviral genomes and their associated beta- and alpha-satellite molecules (virus-satellite complexes (genus, Begomovirus; family, Geminiviridae were enriched from total nucleic acids isolated from symptomatic, field-infected plants, using rolling circle amplification (RCA. Enriched virus-satellite complexes were subjected to Illumina-Next Generation Sequencing (NGS. CASAVA and SeqMan NGen programs were implemented, respectively, for quality control and for de novo and reference-guided contig assembly of viral-satellite sequences. The authenticity of the begomoviral sequences, and the reproducibility of the Illumina-NGS approach for begomoviral deep sequencing projects, were validated by comparing NGS results with those obtained using traditional molecular cloning and Sanger sequencing of viral components and satellite DNAs, also enriched by RCA or amplified by polymerase chain reaction. As the use of NGS approaches, together with advances in software development, make possible deep sequence coverage at a lower cost; the approach described herein will streamline the exploration of begomovirus diversity and population structure from naturally infected plants, irrespective of viral abundance. This is the first report of the implementation of Illumina-NGS to explore the diversity and identify begomoviral-satellite SNPs directly from plants naturally-infected with begomoviruses under field conditions.

Insights into the genetic structure and diversity of 38 South Asian Indians from deep whole-genome sequencing.

Directory of Open Access Journals (Sweden)

Lai-Ping Wong

2014-05-01

Full Text Available South Asia possesses a significant amount of genetic diversity due to considerable intergroup differences in culture and language. There have been numerous reports on the genetic structure of Asian Indians, although these have mostly relied on genotyping microarrays or targeted sequencing of the mitochondria and Y chromosomes. Asian Indians in Singapore are primarily descendants of immigrants from Dravidian-language-speaking states in south India, and 38 individuals from the general population underwent deep whole-genome sequencing with a target coverage of 30X as part of the Singapore Sequencing Indian Project (SSIP. The genetic structure and diversity of these samples were compared against samples from the Singapore Sequencing Malay Project and populations in Phase 1 of the 1,000 Genomes Project (1 KGP. SSIP samples exhibited greater intra-population genetic diversity and possessed higher heterozygous-to-homozygous genotype ratio than other Asian populations. When compared against a panel of well-defined Asian Indians, the genetic makeup of the SSIP samples was closely related to South Indians. However, even though the SSIP samples clustered distinctly from the Europeans in the global population structure analysis with autosomal SNPs, eight samples were assigned to mitochondrial haplogroups that were predominantly present in Europeans and possessed higher European admixture than the remaining samples. An analysis of the relative relatedness between SSIP with two archaic hominins (Denisovan, Neanderthal identified higher ancient admixture in East Asian populations than in SSIP. The data resource for these samples is publicly available and is expected to serve as a valuable complement to the South Asian samples in Phase 3 of 1 KGP.

The subclonal structure and genomic evolution of oral squamous cell carcinoma revealed by ultra-deep sequencing

DEFF Research Database (Denmark)

Tabatabaeifar, Siavosh; Thomassen, Mads; Larsen, Martin J

2017-01-01

Recent studies suggest that head and neck squamous cell carcinomas are very heterogeneous between patients; however the subclonal structure remains unexplored mainly due to studies using only a single biopsy per patient. To deconvolutethe clonal structure and describe the genomic cancer evolution......, we applied whole-exome sequencing combined with ultra-deep targeted sequencing on oral squamous cell carcinomas (OSCC). From each patient, a set of biopsies was sampled from distinct geographical sites in primary tumor and lymph node metastasis.We demonstrate that the included OSCCs show a high...

Improved detection of CXCR4-using HIV by V3 genotyping: application of population-based and "deep" sequencing to plasma RNA and proviral DNA.

Science.gov (United States)

Swenson, Luke C; Moores, Andrew; Low, Andrew J; Thielen, Alexander; Dong, Winnie; Woods, Conan; Jensen, Mark A; Wynhoven, Brian; Chan, Dennison; Glascock, Christopher; Harrigan, P Richard

2010-08-01

Tropism testing should rule out CXCR4-using HIV before treatment with CCR5 antagonists. Currently, the recombinant phenotypic Trofile assay (Monogram) is most widely utilized; however, genotypic tests may represent alternative methods. Independent triplicate amplifications of the HIV gp120 V3 region were made from either plasma HIV RNA or proviral DNA. These underwent standard, population-based sequencing with an ABI3730 (RNA n = 63; DNA n = 40), or "deep" sequencing with a Roche/454 Genome Sequencer-FLX (RNA n = 12; DNA n = 12). Position-specific scoring matrices (PSSMX4/R5) (-6.96 cutoff) and geno2pheno[coreceptor] (5% false-positive rate) inferred tropism from V3 sequence. These methods were then independently validated with a separate, blinded dataset (n = 278) of screening samples from the maraviroc MOTIVATE trials. Standard sequencing of HIV RNA with PSSM yielded 69% sensitivity and 91% specificity, relative to Trofile. The validation dataset gave 75% sensitivity and 83% specificity. Proviral DNA plus PSSM gave 77% sensitivity and 71% specificity. "Deep" sequencing of HIV RNA detected >2% inferred-CXCR4-using virus in 8/8 samples called non-R5 by Trofile, and <2% in 4/4 samples called R5. Triplicate analyses of V3 standard sequence data detect greater proportions of CXCR4-using samples than previously achieved. Sequencing proviral DNA and "deep" V3 sequencing may also be useful tools for assessing tropism.

Tools for integrated sequence-structure analysis with UCSF Chimera

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Huang Conrad C

2006-07-01

Full Text Available Abstract Background Comparing related structures and viewing the structures in the context of sequence alignments are important tasks in protein structure-function research. While many programs exist for individual aspects of such work, there is a need for interactive visualization tools that: (a provide a deep integration of sequence and structure, far beyond mapping where a sequence region falls in the structure and vice versa; (b facilitate changing data of one type based on the other (for example, using only sequence-conserved residues to match structures, or adjusting a sequence alignment based on spatial fit; (c can be used with a researcher's own data, including arbitrary sequence alignments and annotations, closely or distantly related sets of proteins, etc.; and (d interoperate with each other and with a full complement of molecular graphics features. We describe enhancements to UCSF Chimera to achieve these goals. Results The molecular graphics program UCSF Chimera includes a suite of tools for interactive analyses of sequences and structures. Structures automatically associate with sequences in imported alignments, allowing many kinds of crosstalk. A novel method is provided to superimpose structures in the absence of a pre-existing sequence alignment. The method uses both sequence and secondary structure, and can match even structures with very low sequence identity. Another tool constructs structure-based sequence alignments from superpositions of two or more proteins. Chimera is designed to be extensible, and mechanisms for incorporating user-specific data without Chimera code development are also provided. Conclusion The tools described here apply to many problems involving comparison and analysis of protein structures and their sequences. Chimera includes complete documentation and is intended for use by a wide range of scientists, not just those in the computational disciplines. UCSF Chimera is free for non-commercial use and is

Ultra-deep sequencing reveals high prevalence and broad structural diversity of hepatitis B surface antigen mutations in a global population.

Science.gov (United States)

Gencay, Mikael; Hübner, Kirsten; Gohl, Peter; Seffner, Anja; Weizenegger, Michael; Neofytos, Dionysios; Batrla, Richard; Woeste, Andreas; Kim, Hyon-Suk; Westergaard, Gaston; Reinsch, Christine; Brill, Eva; Thu Thuy, Pham Thi; Hoang, Bui Huu; Sonderup, Mark; Spearman, C Wendy; Pabinger, Stephan; Gautier, Jérémie; Brancaccio, Giuseppina; Fasano, Massimo; Santantonio, Teresa; Gaeta, Giovanni B; Nauck, Markus; Kaminski, Wolfgang E

2017-01-01

The diversity of the hepatitis B surface antigen (HBsAg) has a significant impact on the performance of diagnostic screening tests and the clinical outcome of hepatitis B infection. Neutralizing or diagnostic antibodies against the HBsAg are directed towards its highly conserved major hydrophilic region (MHR), in particular towards its "a" determinant subdomain. Here, we explored, on a global scale, the genetic diversity of the HBsAg MHR in a large, multi-ethnic cohort of randomly selected subjects with HBV infection from four continents. A total of 1553 HBsAg positive blood samples of subjects originating from 20 different countries across Africa, America, Asia and central Europe were characterized for amino acid variation in the MHR. Using highly sensitive ultra-deep sequencing, we found 72.8% of the successfully sequenced subjects (n = 1391) demonstrated amino acid sequence variation in the HBsAg MHR. This indicates that the global variation frequency in the HBsAg MHR is threefold higher than previously reported. The majority of the amino acid mutations were found in the HBV genotypes B (28.9%) and C (25.4%). Collectively, we identified 345 distinct amino acid mutations in the MHR. Among these, we report 62 previously unknown mutations, which extends the worldwide pool of currently known HBsAg MHR mutations by 22%. Importantly, topological analysis identified the "a" determinant upstream flanking region as the structurally most diverse subdomain of the HBsAg MHR. The highest prevalence of "a" determinant region mutations was observed in subjects from Asia, followed by the African, American and European cohorts, respectively. Finally, we found that more than half (59.3%) of all HBV subjects investigated carried multiple MHR mutations. Together, this worldwide ultra-deep sequencing based genotyping study reveals that the global prevalence and structural complexity of variation in the hepatitis B surface antigen have, to date, been significantly underappreciated.

Prevalence of Hepatitis C Virus Subgenotypes 1a and 1b in Japanese Patients: Ultra-Deep Sequencing Analysis of HCV NS5B Genotype-Specific Region

Science.gov (United States)

Wu, Shuang; Kanda, Tatsuo; Nakamoto, Shingo; Jiang, Xia; Miyamura, Tatsuo; Nakatani, Sueli M.; Ono, Suzane Kioko; Takahashi-Nakaguchi, Azusa; Gonoi, Tohru; Yokosuka, Osamu

2013-01-01

Background Hepatitis C virus (HCV) subgenotypes 1a and 1b have different impacts on the treatment response to peginterferon plus ribavirin with direct-acting antivirals (DAAs) against patients infected with HCV genotype 1, as the emergence rates of resistance mutations are different between these two subgenotypes. In Japan, almost all of HCV genotype 1 belongs to subgenotype 1b. Methods and Findings To determine HCV subgenotype 1a or 1b in Japanese patients infected with HCV genotype 1, real-time PCR-based method and Sanger method were used for the HCV NS5B region. HCV subgenotypes were determined in 90% by real-time PCR-based method. We also analyzed the specific probe regions for HCV subgenotypes 1a and 1b using ultra-deep sequencing, and uncovered mutations that could not be revealed using direct-sequencing by Sanger method. We estimated the prevalence of HCV subgenotype 1a as 1.2-2.5% of HCV genotype 1 patients in Japan. Conclusions Although real-time PCR-based HCV subgenotyping method seems fair for differentiating HCV subgenotypes 1a and 1b, it may not be sufficient for clinical practice. Ultra-deep sequencing is useful for revealing the resistant strain(s) of HCV before DAA treatment as well as mixed infection with different genotypes or subgenotypes of HCV. PMID:24069214

Deep analysis of cellular transcriptomes – LongSAGE versus classic MPSS

Directory of Open Access Journals (Sweden)

Davis Simon J

2007-09-01

Full Text Available Abstract Background Deep transcriptome analysis will underpin a large fraction of post-genomic biology. 'Closed' technologies, such as microarray analysis, only detect the set of transcripts chosen for analysis, whereas 'open' e.g. tag-based technologies are capable of identifying all possible transcripts, including those that were previously uncharacterized. Although new technologies are now emerging, at present the major resources for open-type analysis are the many publicly available SAGE (serial analysis of gene expression and MPSS (massively parallel signature sequencing libraries. These technologies have never been compared for their utility in the context of deep transcriptome mining. Results We used a single LongSAGE library of 503,431 tags and a "classic" MPSS library of 1,744,173 tags, both prepared from the same T cell-derived RNA sample, to compare the ability of each method to probe, at considerable depth, a human cellular transcriptome. We show that even though LongSAGE is more error-prone than MPSS, our LongSAGE library nevertheless generated 6.3-fold more genome-matching (and therefore likely error-free tags than the MPSS library. An analysis of a set of 8,132 known genes detectable by both methods, and for which there is no ambiguity about tag matching, shows that MPSS detects only half (54% the number of transcripts identified by SAGE (3,617 versus 1,955. Analysis of two additional MPSS libraries shows that each library samples a different subset of transcripts, and that in combination the three MPSS libraries (4,274,992 tags in total still only detect 73% of the genes identified in our test set using SAGE. The fraction of transcripts detected by MPSS is likely to be even lower for uncharacterized transcripts, which tend to be more weakly expressed. The source of the loss of complexity in MPSS libraries compared to SAGE is unclear, but its effects become more severe with each sequencing cycle (i.e. as MPSS tag length increases

Microbial Dark Matter: Unusual intervening sequences in 16S rRNA genes of candidate phyla from the deep subsurface

Energy Technology Data Exchange (ETDEWEB)

Jarett, Jessica; Stepanauskas, Ramunas; Kieft, Thomas; Onstott, Tullis; Woyke, Tanja

2014-03-17

The Microbial Dark Matter project has sequenced genomes from over 200 single cells from candidate phyla, greatly expanding our knowledge of the ecology, inferred metabolism, and evolution of these widely distributed, yet poorly understood lineages. The second phase of this project aims to sequence an additional 800 single cells from known as well as potentially novel candidate phyla derived from a variety of environments. In order to identify whole genome amplified single cells, screening based on phylogenetic placement of 16S rRNA gene sequences is being conducted. Briefly, derived 16S rRNA gene sequences are aligned to a custom version of the Greengenes reference database and added to a reference tree in ARB using parsimony. In multiple samples from deep subsurface habitats but not from other habitats, a large number of sequences proved difficult to align and therefore to place in the tree. Based on comparisons to reference sequences and structural alignments using SSU-ALIGN, many of these ?difficult? sequences appear to originate from candidate phyla, and contain intervening sequences (IVSs) within the 16S rRNA genes. These IVSs are short (39 - 79 nt) and do not appear to be self-splicing or to contain open reading frames. IVSs were found in the loop regions of stem-loop structures in several different taxonomic groups. Phylogenetic placement of sequences is strongly affected by IVSs; two out of three groups investigated were classified as different phyla after their removal. Based on data from samples screened in this project, IVSs appear to be more common in microbes occurring in deep subsurface habitats, although the reasons for this remain elusive.

Application of Tandem Two-Dimensional Mass Spectrometry for Top-Down Deep Sequencing of Calmodulin.

Science.gov (United States)

Floris, Federico; Chiron, Lionel; Lynch, Alice M; Barrow, Mark P; Delsuc, Marc-André; O'Connor, Peter B

2018-06-04

Two-dimensional mass spectrometry (2DMS) involves simultaneous acquisition of the fragmentation patterns of all the analytes in a mixture by correlating their precursor and fragment ions by modulating precursor ions systematically through a fragmentation zone. Tandem two-dimensional mass spectrometry (MS/2DMS) unites the ultra-high accuracy of Fourier transform ion cyclotron resonance (FT-ICR) MS/MS and the simultaneous data-independent fragmentation of 2DMS to achieve extensive inter-residue fragmentation of entire proteins. 2DMS was recently developed for top-down proteomics (TDP), and applied to the analysis of calmodulin (CaM), reporting a cleavage coverage of about ~23% using infrared multiphoton dissociation (IRMPD) as fragmentation technique. The goal of this work is to expand the utility of top-down protein analysis using MS/2DMS in order to extend the cleavage coverage in top-down proteomics further into the interior regions of the protein. In this case, using MS/2DMS, the cleavage coverage of CaM increased from ~23% to ~42%. Graphical Abstract Two-dimensional mass spectrometry, when applied to primary fragment ions from the source, allows deep-sequencing of the protein calmodulin.

Deep sequencing reveals persistence of cell-associated mumps vaccine virus in chronic encephalitis.

Science.gov (United States)

Morfopoulou, Sofia; Mee, Edward T; Connaughton, Sarah M; Brown, Julianne R; Gilmour, Kimberly; Chong, W K 'Kling'; Duprex, W Paul; Ferguson, Deborah; Hubank, Mike; Hutchinson, Ciaran; Kaliakatsos, Marios; McQuaid, Stephen; Paine, Simon; Plagnol, Vincent; Ruis, Christopher; Virasami, Alex; Zhan, Hong; Jacques, Thomas S; Schepelmann, Silke; Qasim, Waseem; Breuer, Judith

2017-01-01

Routine childhood vaccination against measles, mumps and rubella has virtually abolished virus-related morbidity and mortality. Notwithstanding this, we describe here devastating neurological complications associated with the detection of live-attenuated mumps virus Jeryl Lynn (MuV JL5 ) in the brain of a child who had undergone successful allogeneic transplantation for severe combined immunodeficiency (SCID). This is the first confirmed report of MuV JL5 associated with chronic encephalitis and highlights the need to exclude immunodeficient individuals from immunisation with live-attenuated vaccines. The diagnosis was only possible by deep sequencing of the brain biopsy. Sequence comparison of the vaccine batch to the MuV JL5 isolated from brain identified biased hypermutation, particularly in the matrix gene, similar to those found in measles from cases of SSPE. The findings provide unique insights into the pathogenesis of paramyxovirus brain infections.

Deep learning—Accelerating Next Generation Performance Analysis Systems?

Directory of Open Access Journals (Sweden)

Heike Brock

2018-02-01

Full Text Available Deep neural network architectures show superior performance in recognition and prediction tasks of the image, speech and natural language domains. The success of such multi-layered networks encourages their implementation in further application scenarios as the retrieval of relevant motion information for performance enhancement in sports. However, to date deep learning is only seldom applied to activity recognition problems of the human motion domain. Therefore, its use for sports data analysis might remain abstract to many practitioners. This paper provides a survey on recent works in the field of high-performance motion data and examines relevant technologies for subsequent deployment in real training systems. In particular, it discusses aspects of data acquisition, processing and network modeling. Analysis suggests the advantage of deep neural networks under difficult and noisy data conditions. However, further research is necessary to confirm the benefit of deep learning for next generation performance analysis systems.

Identification and characterization of novel serum microRNA candidates from deep sequencing in cervical cancer patients.

Science.gov (United States)

Juan, Li; Tong, Hong-li; Zhang, Pengjun; Guo, Guanghong; Wang, Zi; Wen, Xinyu; Dong, Zhennan; Tian, Ya-ping

2014-09-03

Small non-coding microRNAs (miRNAs) are involved in cancer development and progression, and serum profiles of cervical cancer patients may be useful for identifying novel miRNAs. We performed deep sequencing on serum pools of cervical cancer patients and healthy controls with 3 replicates and constructed a small RNA library. We used MIREAP to predict novel miRNAs and identified 2 putative novel miRNAs between serum pools of cervical cancer patients and healthy controls after filtering out pseudo-pre-miRNAs using Triplet-SVM analysis. The 2 putative novel miRNAs were validated by real time PCR and were significantly decreased in cervical cancer patients compared with healthy controls. One novel miRNA had an area under curve (AUC) of 0.921 (95% CI: 0.883, 0.959) with a sensitivity of 85.7% and a specificity of 88.2% when discriminating between cervical cancer patients and healthy controls. Our results suggest that characterizing serum profiles of cervical cancers by Solexa sequencing may be a good method for identifying novel miRNAs and that the validated novel miRNAs described here may be cervical cancer-associated biomarkers.

Characterization and Development of EST-SSRs by Deep Transcriptome Sequencing in Chinese Cabbage (Brassica rapa L. ssp. pekinensis

Directory of Open Access Journals (Sweden)

Qian Ding

2015-01-01

Full Text Available Simple sequence repeats (SSRs are among the most important markers for population analysis and have been widely used in plant genetic mapping and molecular breeding. Expressed sequence tag-SSR (EST-SSR markers, located in the coding regions, are potentially more efficient for QTL mapping, gene targeting, and marker-assisted breeding. In this study, we investigated 51,694 nonredundant unigenes, assembled from clean reads from deep transcriptome sequencing with a Solexa/Illumina platform, for identification and development of EST-SSRs in Chinese cabbage. In total, 10,420 EST-SSRs with over 12 bp were identified and characterized, among which 2744 EST-SSRs are new and 2317 are known ones showing polymorphism with previously reported SSRs. A total of 7877 PCR primer pairs for 1561 EST-SSR loci were designed, and primer pairs for twenty-four EST-SSRs were selected for primer evaluation. In nineteen EST-SSR loci (79.2%, amplicons were successfully generated with high quality. Seventeen (89.5% showed polymorphism in twenty-four cultivars of Chinese cabbage. The polymorphic alleles of each polymorphic locus were sequenced, and the results showed that most polymorphisms were due to variations of SSR repeat motifs. The EST-SSRs identified and characterized in this study have important implications for developing new tools for genetics and molecular breeding in Chinese cabbage.

Facies analysis and paleoenvironmental reconstruction of Upper Cretaceous sequences in the eastern Para-Tethys Basin, NW Iran

Energy Technology Data Exchange (ETDEWEB)

Omidvar, M.; Safari, A.; Vaziri-Moghaddam, H.; Ghalavand, H.

2016-07-01

Upper Cretaceous mixed carbonate-siliciclastic sequences are among the most important targets for hydrocarbon exploration in the Moghan area, located in the eastern Para-Tethys Basin. Despite of their significance, little is known about their facies characteristics and depositional environments. Detailed facies analysis and paleoenvironmental reconstruction of these sequences have been carried out in eight surface sections. Accordingly, four siliciclastic facies, eight carbonate facies and one volcanic facies have been recognized. Detailed facies descriptions and interpretations, together with the results of facies frequency analysis, standard facies models and Upper Cretaceous depositional models of Para-Tethys Basin, have been integrated and a non-rimmed carbonate platform is presented. This platform was affected by siliciclastic influx, in the form of coastal fan delta and submarine fans in the shallow- to deep-marine parts, respectively. This model is interpreted to be shallower in the central and northeastern parts of the Moghan area. Toward the southeast and southwest, this shallow platform turns into deep marine settings along steep slopes without remarkable marginal barriers. (Author)

Uniform, optimal signal processing of mapped deep-sequencing data.

Science.gov (United States)

Kumar, Vibhor; Muratani, Masafumi; Rayan, Nirmala Arul; Kraus, Petra; Lufkin, Thomas; Ng, Huck Hui; Prabhakar, Shyam

2013-07-01

Despite their apparent diversity, many problems in the analysis of high-throughput sequencing data are merely special cases of two general problems, signal detection and signal estimation. Here we adapt formally optimal solutions from signal processing theory to analyze signals of DNA sequence reads mapped to a genome. We describe DFilter, a detection algorithm that identifies regulatory features in ChIP-seq, DNase-seq and FAIRE-seq data more accurately than assay-specific algorithms. We also describe EFilter, an estimation algorithm that accurately predicts mRNA levels from as few as 1-2 histone profiles (R ∼0.9). Notably, the presence of regulatory motifs in promoters correlates more with histone modifications than with mRNA levels, suggesting that histone profiles are more predictive of cis-regulatory mechanisms. We show by applying DFilter and EFilter to embryonic forebrain ChIP-seq data that regulatory protein identification and functional annotation are feasible despite tissue heterogeneity. The mathematical formalism underlying our tools facilitates integrative analysis of data from virtually any sequencing-based functional profile.

Deep sequencing-based analysis of the Cymbidium ensifolium floral transcriptome.

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Xiaobai Li

Full Text Available Cymbidium ensifolium is a Chinese Cymbidium with an elegant shape, beautiful appearance, and a fragrant aroma. C. ensifolium has a long history of cultivation in China and it has excellent commercial value as a potted plant and cut flower. The development of C. ensifolium genomic resources has been delayed because of its large genome size. Taking advantage of technical and cost improvement of RNA-Seq, we extracted total mRNA from flower buds and mature flowers and obtained a total of 9.52 Gb of filtered nucleotides comprising 98,819,349 filtered reads. The filtered reads were assembled into 101,423 isotigs, representing 51,696 genes. Of the 101,423 isotigs, 41,873 were putative homologs of annotated sequences in the public databases, of which 158 were associated with floral development and 119 were associated with flowering. The isotigs were categorized according to their putative functions. In total, 10,212 of the isotigs were assigned into 25 eukaryotic orthologous groups (KOGs, 41,690 into 58 gene ontology (GO terms, and 9,830 into 126 Arabidopsis Kyoto Encyclopedia of Genes and Genomes (KEGG pathways, and 9,539 isotigs into 123 rice pathways. Comparison of the isotigs with those of the two related orchid species P. equestris and C. sinense showed that 17,906 isotigs are unique to C. ensifolium. In addition, a total of 7,936 SSRs and 16,676 putative SNPs were identified. To our knowledge, this transcriptome database is the first major genomic resource for C. ensifolium and the most comprehensive transcriptomic resource for genus Cymbidium. These sequences provide valuable information for understanding the molecular mechanisms of floral development and flowering. Sequences predicted to be unique to C. ensifolium would provide more insights into C. ensifolium gene diversity. The numerous SNPs and SSRs identified in the present study will contribute to marker development for C. ensifolium.

Genomic variation in macrophage-cultured European porcine reproductive and respiratory syndrome virus Olot/91 revealed using ultra-deep next generation sequencing.

Science.gov (United States)

Lu, Zen H; Brown, Alexander; Wilson, Alison D; Calvert, Jay G; Balasch, Monica; Fuentes-Utrilla, Pablo; Loecherbach, Julia; Turner, Frances; Talbot, Richard; Archibald, Alan L; Ait-Ali, Tahar

2014-03-04

Porcine Reproductive and Respiratory Syndrome (PRRS) is a disease of major economic impact worldwide. The etiologic agent of this disease is the PRRS virus (PRRSV). Increasing evidence suggest that microevolution within a coexisting quasispecies population can give rise to high sequence heterogeneity in PRRSV. We developed a pipeline based on the ultra-deep next generation sequencing approach to first construct the complete genome of a European PRRSV, strain Olot/9, cultured on macrophages and then capture the rare variants representative of the mixed quasispecies population. Olot/91 differs from the reference Lelystad strain by about 5% and a total of 88 variants, with frequencies as low as 1%, were detected in the mixed population. These variants included 16 non-synonymous variants concentrated in the genes encoding structural and nonstructural proteins; including Glycoprotein 2a and 5. Using an ultra-deep sequencing methodology, the complete genome of Olot/91 was constructed without any prior knowledge of the sequence. Rare variants that constitute minor fractions of the heterogeneous PRRSV population could successfully be detected to allow further exploration of microevolutionary events.

3′ terminal diversity of MRP RNA and other human noncoding RNAs revealed by deep sequencing

Science.gov (United States)

2013-01-01

Background Post-transcriptional 3′ end processing is a key component of RNA regulation. The abundant and essential RNA subunit of RNase MRP has been proposed to function in three distinct cellular compartments and therefore may utilize this mode of regulation. Here we employ 3′ RACE coupled with high-throughput sequencing to characterize the 3′ terminal sequences of human MRP RNA and other noncoding RNAs that form RNP complexes. Results The 3′ terminal sequence of MRP RNA from HEK293T cells has a distinctive distribution of genomically encoded termini (including an assortment of U residues) with a portion of these selectively tagged by oligo(A) tails. This profile contrasts with the relatively homogenous 3′ terminus of an in vitro transcribed MRP RNA control and the differing 3′ terminal profiles of U3 snoRNA, RNase P RNA, and telomerase RNA (hTR). Conclusions 3′ RACE coupled with deep sequencing provides a valuable framework for the functional characterization of 3′ terminal sequences of noncoding RNAs. PMID:24053768

A combination of LongSAGE with Solexa sequencing is well suited to explore the depth and the complexity of transcriptome

Directory of Open Access Journals (Sweden)

Scoté-Blachon Céline

2008-09-01

Full Text Available Abstract Background "Open" transcriptome analysis methods allow to study gene expression without a priori knowledge of the transcript sequences. As of now, SAGE (Serial Analysis of Gene Expression, LongSAGE and MPSS (Massively Parallel Signature Sequencing are the mostly used methods for "open" transcriptome analysis. Both LongSAGE and MPSS rely on the isolation of 21 pb tag sequences from each transcript. In contrast to LongSAGE, the high throughput sequencing method used in MPSS enables the rapid sequencing of very large libraries containing several millions of tags, allowing deep transcriptome analysis. However, a bias in the complexity of the transcriptome representation obtained by MPSS was recently uncovered. Results In order to make a deep analysis of mouse hypothalamus transcriptome avoiding the limitation introduced by MPSS, we combined LongSAGE with the Solexa sequencing technology and obtained a library of more than 11 millions of tags. We then compared it to a LongSAGE library of mouse hypothalamus sequenced with the Sanger method. Conclusion We found that Solexa sequencing technology combined with LongSAGE is perfectly suited for deep transcriptome analysis. In contrast to MPSS, it gives a complex representation of transcriptome as reliable as a LongSAGE library sequenced by the Sanger method.

Deep sequencing of cardiac microRNA-mRNA interactomes in clinical and experimental cardiomyopathy.

Science.gov (United States)

Matkovich, Scot J; Dorn, Gerald W

2015-01-01

MicroRNAs are a family of short (~21 nucleotide) noncoding RNAs that serve key roles in cellular growth and differentiation and the response of the heart to stress stimuli. As the sequence-specific recognition element of RNA-induced silencing complexes (RISCs), microRNAs bind mRNAs and prevent their translation via mechanisms that may include transcript degradation and/or prevention of ribosome binding. Short microRNA sequences and the ability of microRNAs to bind to mRNA sites having only partial/imperfect sequence complementarity complicate purely computational analyses of microRNA-mRNA interactomes. Furthermore, computational microRNA target prediction programs typically ignore biological context, and therefore the principal determinants of microRNA-mRNA binding: the presence and quantity of each. To address these deficiencies we describe an empirical method, developed via studies of stressed and failing hearts, to determine disease-induced changes in microRNAs, mRNAs, and the mRNAs targeted to the RISC, without cross-linking mRNAs to RISC proteins. Deep sequencing methods are used to determine RNA abundances, delivering unbiased, quantitative RNA data limited only by their annotation in the genome of interest. We describe the laboratory bench steps required to perform these experiments, experimental design strategies to achieve an appropriate number of sequencing reads per biological replicate, and computer-based processing tools and procedures to convert large raw sequencing data files into gene expression measures useful for differential expression analyses.

Biological sequence analysis

DEFF Research Database (Denmark)

Durbin, Richard; Eddy, Sean; Krogh, Anders Stærmose

This book provides an up-to-date and tutorial-level overview of sequence analysis methods, with particular emphasis on probabilistic modelling. Discussed methods include pairwise alignment, hidden Markov models, multiple alignment, profile searches, RNA secondary structure analysis, and phylogene...

DeepARG: a deep learning approach for predicting antibiotic resistance genes from metagenomic data.

Science.gov (United States)

Arango-Argoty, Gustavo; Garner, Emily; Pruden, Amy; Heath, Lenwood S; Vikesland, Peter; Zhang, Liqing

2018-02-01

Growing concerns about increasing rates of antibiotic resistance call for expanded and comprehensive global monitoring. Advancing methods for monitoring of environmental media (e.g., wastewater, agricultural waste, food, and water) is especially needed for identifying potential resources of novel antibiotic resistance genes (ARGs), hot spots for gene exchange, and as pathways for the spread of ARGs and human exposure. Next-generation sequencing now enables direct access and profiling of the total metagenomic DNA pool, where ARGs are typically identified or predicted based on the "best hits" of sequence searches against existing databases. Unfortunately, this approach produces a high rate of false negatives. To address such limitations, we propose here a deep learning approach, taking into account a dissimilarity matrix created using all known categories of ARGs. Two deep learning models, DeepARG-SS and DeepARG-LS, were constructed for short read sequences and full gene length sequences, respectively. Evaluation of the deep learning models over 30 antibiotic resistance categories demonstrates that the DeepARG models can predict ARGs with both high precision (> 0.97) and recall (> 0.90). The models displayed an advantage over the typical best hit approach, yielding consistently lower false negative rates and thus higher overall recall (> 0.9). As more data become available for under-represented ARG categories, the DeepARG models' performance can be expected to be further enhanced due to the nature of the underlying neural networks. Our newly developed ARG database, DeepARG-DB, encompasses ARGs predicted with a high degree of confidence and extensive manual inspection, greatly expanding current ARG repositories. The deep learning models developed here offer more accurate antimicrobial resistance annotation relative to current bioinformatics practice. DeepARG does not require strict cutoffs, which enables identification of a much broader diversity of ARGs. The

Population-genomic variation within RNA viruses of the Western honey bee, Apis mellifera, inferred from deep sequencing.

Science.gov (United States)

Cornman, Robert Scott; Boncristiani, Humberto; Dainat, Benjamin; Chen, Yanping; vanEngelsdorp, Dennis; Weaver, Daniel; Evans, Jay D

2013-03-07

Deep sequencing of viruses isolated from infected hosts is an efficient way to measure population-genetic variation and can reveal patterns of dispersal and natural selection. In this study, we mined existing Illumina sequence reads to investigate single-nucleotide polymorphisms (SNPs) within two RNA viruses of the Western honey bee (Apis mellifera), deformed wing virus (DWV) and Israel acute paralysis virus (IAPV). All viral RNA was extracted from North American samples of honey bees or, in one case, the ectoparasitic mite Varroa destructor. Coverage depth was generally lower for IAPV than DWV, and marked gaps in coverage occurred in several narrow regions (selection. The Kakugo strain of DWV fell outside of all other DWV sequences at 100% bootstrap support. IAPV consensus sequences supported the existence of multiple clades as had been previously reported, and Fu and Li's D was closer to neutral expectation overall, although a sliding-window analysis identified a significantly positive D within the protease region, suggesting selection maintains diversity in that region. Within-sample mean diversity was comparable between the two viruses on average, although for both viruses there was substantial variation among samples in mean diversity at third codon positions and in the number of high-diversity sites. FST values were bimodal for DWV, likely reflecting neutral divergence in two low-diversity populations, whereas IAPV had several sites that were strong outliers with very low FST. This initial survey of genetic variation within honey bee RNA viruses suggests future directions for studies examining the underlying causes of population-genetic structure in these economically important pathogens.

Deep Borehole Emplacement Mode Hazard Analysis Revision 0

Energy Technology Data Exchange (ETDEWEB)

Sevougian, S. David [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2015-08-07

This letter report outlines a methodology and provides resource information for the Deep Borehole Emplacement Mode Hazard Analysis (DBEMHA). The main purpose is identify the accident hazards and accident event sequences associated with the two emplacement mode options (wireline or drillstring), to outline a methodology for computing accident probabilities and frequencies, and to point to available databases on the nature and frequency of accidents typically associated with standard borehole drilling and nuclear handling operations. Risk mitigation and prevention measures, which have been incorporated into the two emplacement designs (see Cochran and Hardin 2015), are also discussed. A key intent of this report is to provide background information to brief subject matter experts involved in the Emplacement Mode Design Study. [Note: Revision 0 of this report is concentrated more on the wireline emplacement mode. It is expected that Revision 1 will contain further development of the preliminary fault and event trees for the drill string emplacement mode.

Molecular analysis of deep subsurface bacteria

International Nuclear Information System (INIS)

Jimenez Baez, L.E.

1989-09-01

Deep sediments samples from site C10a, in Appleton, and sites, P24, P28, and P29, at the Savannah River Site (SRS), near Aiken, South Carolina were studied to determine their microbial community composition, DNA homology and mol %G+C. Different geological formations with great variability in hydrogeological parameters were found across the depth profile. Phenotypic identification of deep subsurface bacteria underestimated the bacterial diversity at the three SRS sites, since bacteria with the same phenotype have different DNA composition and less than 70% DNA homology. Total DNA hybridization and mol %G+C analysis of deep sediment bacterial isolates suggested that each formation is comprised of different microbial communities. Depositional environment was more important than site and geological formation on the DNA relatedness between deep subsurface bacteria, since more 70% of bacteria with 20% or more of DNA homology came from the same depositional environments. Based on phenotypic and genotypic tests Pseudomonas spp. and Acinetobacter spp.-like bacteria were identified in 85 million years old sediments. This suggests that these microbial communities might have been adapted during a long period of time to the environmental conditions of the deep subsurface

DeepRT: deep learning for peptide retention time prediction in proteomics

OpenAIRE

Ma, Chunwei; Zhu, Zhiyong; Ye, Jun; Yang, Jiarui; Pei, Jianguo; Xu, Shaohang; Zhou, Ruo; Yu, Chang; Mo, Fan; Wen, Bo; Liu, Siqi

2017-01-01

Accurate predictions of peptide retention times (RT) in liquid chromatography have many applications in mass spectrometry-based proteomics. Herein, we present DeepRT, a deep learning based software for peptide retention time prediction. DeepRT automatically learns features directly from the peptide sequences using the deep convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) model, which eliminates the need to use hand-crafted features or rules. After the feature learning, pr...

Image sequence analysis

CERN Document Server

1981-01-01

The processing of image sequences has a broad spectrum of important applica­ tions including target tracking, robot navigation, bandwidth compression of TV conferencing video signals, studying the motion of biological cells using microcinematography, cloud tracking, and highway traffic monitoring. Image sequence processing involves a large amount of data. However, because of the progress in computer, LSI, and VLSI technologies, we have now reached a stage when many useful processing tasks can be done in a reasonable amount of time. As a result, research and development activities in image sequence analysis have recently been growing at a rapid pace. An IEEE Computer Society Workshop on Computer Analysis of Time-Varying Imagery was held in Philadelphia, April 5-6, 1979. A related special issue of the IEEE Transactions on Pattern Anal­ ysis and Machine Intelligence was published in November 1980. The IEEE Com­ puter magazine has also published a special issue on the subject in 1981. The purpose of this book ...

Genome-wide analysis of SRSF10-regulated alternative splicing by deep sequencing of chicken transcriptome

Directory of Open Access Journals (Sweden)

Xuexia Zhou

2014-12-01

Full Text Available Splicing factor SRSF10 is known to function as a sequence-specific splicing activator that is capable of regulating alternative splicing both in vitro and in vivo. We recently used an RNA-seq approach coupled with bioinformatics analysis to identify the extensive splicing network regulated by SRSF10 in chicken cells. We found that SRSF10 promoted both exon inclusion and exclusion. Functionally, many of the SRSF10-verified alternative exons are linked to pathways of response to external stimulus. Here we describe in detail the experimental design, bioinformatics analysis and GO/pathway enrichment analysis of SRSF10-regulated genes to correspond with our data in the Gene Expression Omnibus with accession number GSE53354. Our data thus provide a resource for studying regulation of alternative splicing in vivo that underlines biological functions of splicing regulatory proteins in cells.

Automated analysis of high-content microscopy data with deep learning.

Science.gov (United States)

Kraus, Oren Z; Grys, Ben T; Ba, Jimmy; Chong, Yolanda; Frey, Brendan J; Boone, Charles; Andrews, Brenda J

2017-04-18

Existing computational pipelines for quantitative analysis of high-content microscopy data rely on traditional machine learning approaches that fail to accurately classify more than a single dataset without substantial tuning and training, requiring extensive analysis. Here, we demonstrate that the application of deep learning to biological image data can overcome the pitfalls associated with conventional machine learning classifiers. Using a deep convolutional neural network (DeepLoc) to analyze yeast cell images, we show improved performance over traditional approaches in the automated classification of protein subcellular localization. We also demonstrate the ability of DeepLoc to classify highly divergent image sets, including images of pheromone-arrested cells with abnormal cellular morphology, as well as images generated in different genetic backgrounds and in different laboratories. We offer an open-source implementation that enables updating DeepLoc on new microscopy datasets. This study highlights deep learning as an important tool for the expedited analysis of high-content microscopy data. © 2017 The Authors. Published under the terms of the CC BY 4.0 license.

fCCAC: functional canonical correlation analysis to evaluate covariance between nucleic acid sequencing datasets.

Science.gov (United States)

Madrigal, Pedro

2017-03-01

Computational evaluation of variability across DNA or RNA sequencing datasets is a crucial step in genomic science, as it allows both to evaluate reproducibility of biological or technical replicates, and to compare different datasets to identify their potential correlations. Here we present fCCAC, an application of functional canonical correlation analysis to assess covariance of nucleic acid sequencing datasets such as chromatin immunoprecipitation followed by deep sequencing (ChIP-seq). We show how this method differs from other measures of correlation, and exemplify how it can reveal shared covariance between histone modifications and DNA binding proteins, such as the relationship between the H3K4me3 chromatin mark and its epigenetic writers and readers. An R/Bioconductor package is available at http://bioconductor.org/packages/fCCAC/ . pmb59@cam.ac.uk. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Ultra Deep Sequencing of a Baculovirus Population Reveals Widespread Genomic Variations

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Aurélien Chateigner

2015-07-01

Full Text Available Viruses rely on widespread genetic variation and large population size for adaptation. Large DNA virus populations are thought to harbor little variation though natural populations may be polymorphic. To measure the genetic variation present in a dsDNA virus population, we deep sequenced a natural strain of the baculovirus Autographa californica multiple nucleopolyhedrovirus. With 124,221X average genome coverage of our 133,926 bp long consensus, we could detect low frequency mutations (0.025%. K-means clustering was used to classify the mutations in four categories according to their frequency in the population. We found 60 high frequency non-synonymous mutations under balancing selection distributed in all functional classes. These mutants could alter viral adaptation dynamics, either through competitive or synergistic processes. Lastly, we developed a technique for the delimitation of large deletions in next generation sequencing data. We found that large deletions occur along the entire viral genome, with hotspots located in homologous repeat regions (hrs. Present in 25.4% of the genomes, these deletion mutants presumably require functional complementation to complete their infection cycle. They might thus have a large impact on the fitness of the baculovirus population. Altogether, we found a wide breadth of genomic variation in the baculovirus population, suggesting it has high adaptive potential.

Deep-sequencing to resolve complex diversity of apicomplexan parasites in platypuses and echidnas: Proof of principle for wildlife disease investigation.

Science.gov (United States)

Šlapeta, Jan; Saverimuttu, Stefan; Vogelnest, Larry; Sangster, Cheryl; Hulst, Frances; Rose, Karrie; Thompson, Paul; Whittington, Richard

2017-11-01

The short-beaked echidna (Tachyglossus aculeatus) and the platypus (Ornithorhynchus anatinus) are iconic egg-laying monotremes (Mammalia: Monotremata) from Australasia. The aim of this study was to demonstrate the utility of diversity profiles in disease investigations of monotremes. Using small subunit (18S) rDNA amplicon deep-sequencing we demonstrated the presence of apicomplexan parasites and confirmed by direct and cloned amplicon gene sequencing Theileria ornithorhynchi, Theileria tachyglossi, Eimeria echidnae and Cryptosporidium fayeri. Using a combination of samples from healthy and diseased animals, we show a close evolutionary relationship between species of coccidia (Eimeria) and piroplasms (Theileria) from the echidna and platypus. The presence of E. echidnae was demonstrated in faeces and tissues affected by disseminated coccidiosis. Moreover, the presence of E. echidnae DNA in the blood of echidnas was associated with atoxoplasma-like stages in white blood cells, suggesting Hepatozoon tachyglossi blood stages are disseminated E. echidnae stages. These next-generation DNA sequencing technologies are suited to material and organisms that have not been previously characterised and for which the material is scarce. The deep sequencing approach supports traditional diagnostic methods, including microscopy, clinical pathology and histopathology, to better define the status quo. This approach is particularly suitable for wildlife disease investigation. Copyright © 2017 Elsevier B.V. All rights reserved.

Deep-sequencing protocols influence the results obtained in small-RNA sequencing.

Directory of Open Access Journals (Sweden)

Joern Toedling

Full Text Available Second-generation sequencing is a powerful method for identifying and quantifying small-RNA components of cells. However, little attention has been paid to the effects of the choice of sequencing platform and library preparation protocol on the results obtained. We present a thorough comparison of small-RNA sequencing libraries generated from the same embryonic stem cell lines, using different sequencing platforms, which represent the three major second-generation sequencing technologies, and protocols. We have analysed and compared the expression of microRNAs, as well as populations of small RNAs derived from repetitive elements. Despite the fact that different libraries display a good correlation between sequencing platforms, qualitative and quantitative variations in the results were found, depending on the protocol used. Thus, when comparing libraries from different biological samples, it is strongly recommended to use the same sequencing platform and protocol in order to ensure the biological relevance of the comparisons.

Analysis of hepatitis C NS5A resistance associated polymorphisms using ultra deep single molecule real time (SMRT) sequencing.

Science.gov (United States)

Bergfors, Assar; Leenheer, Daniël; Bergqvist, Anders; Ameur, Adam; Lennerstrand, Johan

2016-02-01

Development of Hepatitis C virus (HCV) resistance against direct-acting antivirals (DAAs), including NS5A inhibitors, is an obstacle to successful treatment of HCV when DAAs are used in sub-optimal combinations. Furthermore, it has been shown that baseline (pre-existing) resistance against DAAs is present in treatment naïve-patients and this will potentially complicate future treatment strategies in different HCV genotypes (GTs). Thus the aim was to detect low levels of NS5A resistant associated variants (RAVs) in a limited sample set of treatment-naïve patients of HCV GT1a and 3a, since such polymorphisms can display in vitro resistance as high as 60000 fold. Ultra-deep single molecule real time (SMRT) sequencing with the Pacific Biosciences (PacBio) RSII instrument was used to detect these RAVs. The SMRT sequencing was conducted on ten samples; three of them positive with Sanger sequencing (GT1a Q30H and Y93N, and GT3a Y93H), five GT1a samples, and two GT3a non-positive samples. The same methods were applied to the HCV GT1a H77-plasmid in a dilution series, in order to determine the error rates of replication, which in turn was used to determine the limit of detection (LOD), as defined by mean + 3SD, of minority variants down to 0.24%. We found important baseline NS5A RAVs at levels between 0.24 and 0.5%, which could potentially have clinical relevance. This new method with low level detection of baseline RAVs could be useful in predicting the most cost-efficient combination of DAA treatment, and reduce the treatment duration for an HCV infected individual. Copyright © 2015 Elsevier B.V. All rights reserved.

Deep Learning in Medical Image Analysis.

Science.gov (United States)

Shen, Dinggang; Wu, Guorong; Suk, Heung-Il

2017-06-21

This review covers computer-assisted analysis of images in the field of medical imaging. Recent advances in machine learning, especially with regard to deep learning, are helping to identify, classify, and quantify patterns in medical images. At the core of these advances is the ability to exploit hierarchical feature representations learned solely from data, instead of features designed by hand according to domain-specific knowledge. Deep learning is rapidly becoming the state of the art, leading to enhanced performance in various medical applications. We introduce the fundamentals of deep learning methods and review their successes in image registration, detection of anatomical and cellular structures, tissue segmentation, computer-aided disease diagnosis and prognosis, and so on. We conclude by discussing research issues and suggesting future directions for further improvement.

Mapping vaccinia virus DNA replication origins at nucleotide level by deep sequencing.

Science.gov (United States)

Senkevich, Tatiana G; Bruno, Daniel; Martens, Craig; Porcella, Stephen F; Wolf, Yuri I; Moss, Bernard

2015-09-01

Poxviruses reproduce in the host cytoplasm and encode most or all of the enzymes and factors needed for expression and synthesis of their double-stranded DNA genomes. Nevertheless, the mode of poxvirus DNA replication and the nature and location of the replication origins remain unknown. A current but unsubstantiated model posits only leading strand synthesis starting at a nick near one covalently closed end of the genome and continuing around the other end to generate a concatemer that is subsequently resolved into unit genomes. The existence of specific origins has been questioned because any plasmid can replicate in cells infected by vaccinia virus (VACV), the prototype poxvirus. We applied directional deep sequencing of short single-stranded DNA fragments enriched for RNA-primed nascent strands isolated from the cytoplasm of VACV-infected cells to pinpoint replication origins. The origins were identified as the switching points of the fragment directions, which correspond to the transition from continuous to discontinuous DNA synthesis. Origins containing a prominent initiation point mapped to a sequence within the hairpin loop at one end of the VACV genome and to the same sequence within the concatemeric junction of replication intermediates. These findings support a model for poxvirus genome replication that involves leading and lagging strand synthesis and is consistent with the requirements for primase and ligase activities as well as earlier electron microscopic and biochemical studies implicating a replication origin at the end of the VACV genome.

Draft Genome Sequences of TwoThiomicrospiraStrains Isolated from the Brine-Seawater Interface of Kebrit Deep in the Red Sea

KAUST Repository

Zhang, Guishan

2016-03-11

Two Thiomicrospira strains, WB1 and XS5, were isolated from the Kebrit Deep brine-seawater interface in the Red Sea, Saudi Arabia. Here, we present the draft genome sequences of these gammaproteobacteria, which both produce sulfuric acid from thiosulfate in culture.

Draft Genome Sequences of TwoThiomicrospiraStrains Isolated from the Brine-Seawater Interface of Kebrit Deep in the Red Sea

KAUST Repository

Zhang, Guishan; Haroon, Mohamed; Zhang, Ruifu; Hikmawan, Tyas I.; Stingl, Ulrich

2016-01-01

Two Thiomicrospira strains, WB1 and XS5, were isolated from the Kebrit Deep brine-seawater interface in the Red Sea, Saudi Arabia. Here, we present the draft genome sequences of these gammaproteobacteria, which both produce sulfuric acid from thiosulfate in culture.

Characterization of the Complete Mitochondrial Genome Sequence of the Globose Head Whiptail Cetonurus globiceps (Gadiformes: Macrouridae and Its Phylogenetic Analysis.

Directory of Open Access Journals (Sweden)

Xiaofeng Shi

Full Text Available The particular environmental characteristics of deep water such as its immense scale and high pressure systems, presents technological problems that have prevented research to broaden our knowledge of deep-sea fish. Here, we described the mitogenome sequence of a deep-sea fish, Cetonurus globiceps. The genome is 17,137 bp in length, with a standard set of 22 transfer RNA genes (tRNAs, two ribosomal RNA genes, 13 protein-coding genes, and two typical non-coding control regions. Additionally, a 70 bp tRNA(Thr-tRNA(Pro intergenic spacer is present. The C. globiceps mitogenome exhibited strand-specific asymmetry in nucleotide composition. The AT-skew and GC-skew values in the whole genome of C. globiceps were 0 and -0.2877, respectively, revealing that the H-strand had equal amounts of A and T and that the overall nucleotide composition was C skewed. All of the tRNA genes could be folded into cloverleaf secondary structures, while the secondary structure of tRNA(Ser(AGY lacked a discernible dihydrouridine stem. By comparing this genome sequence with the recognition sites in teleost species, several conserved sequence blocks were identified in the control region. However, the GTGGG-box, the typical characteristic of conserved sequence block E (CSB-E, was absent. Notably, tandem repeats were identified in the 3' portion of the control region. No similar repetitive motifs are present in most of other gadiform species. Phylogenetic analysis based on 12 protein coding genes provided strong support that C. globiceps was the most derived in the clade. Some relationships however, are in contrast with those presented in previous studies. This study enriches our knowledge of mitogenomes of the genus Cetonurus and provides valuable information on the evolution of Macrouridae mtDNA and deep-sea fish.

A Survey on Deep Learning in Medical Image Analysis

NARCIS (Netherlands)

Litjens, G.J.; Kooi, T.; Ehteshami Bejnordi, B.; Setio, A.A.A.; Ciompi, F.; Ghafoorian, M.; Laak, J.A.W.M. van der; Ginneken, B. van; Sanchez, C.I.

2017-01-01

Deep learning algorithms, in particular convolutional networks, have rapidly become a methodology of choice for analyzing medical images. This paper reviews the major deep learning concepts pertinent to medical image analysis and summarizes over 300 contributions to the field, most of which appeared

Identification of microRNAs Involved in the Host Response to Enterovirus 71 Infection by a Deep Sequencing Approach

Directory of Open Access Journals (Sweden)

Lunbiao Cui

2010-01-01

Full Text Available Role of microRNA (miRNA has been highlighted in pathogen-host interactions recently. To identify cellular miRNAs involved in the host response to enterovirus 71 (EV71 infection, we performed a comprehensive miRNA profiling in EV71-infected Hep2 cells through deep sequencing. 64 miRNAs were found whose expression levels changed for more than 2-fold in response to EV71 infection. Gene ontology analysis revealed that many of these mRNAs play roles in neurological process, immune response, and cell death pathways, which are known to be associated with the extreme virulence of EV71. To our knowledge, this is the first study on host miRNAs expression alteration response to EV71 infection. Our findings supported the hypothesis that certain miRNAs might be essential in the host-pathogen interactions.

Large-Scale Genotyping-by-Sequencing Indicates High Levels of Gene Flow in the Deep-Sea Octocoral Swiftia simplex (Nutting 1909 on the West Coast of the United States.

Directory of Open Access Journals (Sweden)

Meredith V Everett

Full Text Available Deep-sea corals are a critical component of habitat in the deep-sea, existing as regional hotspots for biodiversity, and are associated with increased assemblages of fish, including commercially important species. Because sampling these species is so difficult, little is known about the connectivity and life history of deep-sea octocoral populations. This study evaluates the genetic connectivity among 23 individuals of the deep-sea octocoral Swiftia simplex collected from Eastern Pacific waters along the west coast of the United States. We utilized high-throughput restriction-site associated DNA (RAD-tag sequencing to develop the first molecular genetic resource for the deep-sea octocoral, Swiftia simplex. Using this technique we discovered thousands of putative genome-wide SNPs in this species, and after quality control, successfully genotyped 1,145 SNPs across individuals sampled from California to Washington. These SNPs were used to assess putative population structure across the region. A STRUCTURE analysis as well as a principal coordinates analysis both failed to detect any population differentiation across all geographic areas in these collections. Additionally, after assigning individuals to putative population groups geographically, no significant FST values could be detected (FST for the full data set 0.0056, and no significant isolation by distance could be detected (p = 0.999. Taken together, these results indicate a high degree of connectivity and potential panmixia in S. simplex along this portion of the continental shelf.

Fractals in DNA sequence analysis

Institute of Scientific and Technical Information of China (English)

Yu Zu-Guo(喻祖国); Vo Anh; Gong Zhi-Min(龚志民); Long Shun-Chao(龙顺潮)

2002-01-01

Fractal methods have been successfully used to study many problems in physics, mathematics, engineering, finance,and even in biology. There has been an increasing interest in unravelling the mysteries of DNA; for example, how can we distinguish coding and noncoding sequences, and the problems of classification and evolution relationship of organisms are key problems in bioinformatics. Although much research has been carried out by taking into consideration the long-range correlations in DNA sequences, and the global fractal dimension has been used in these works by other people, the models and methods are somewhat rough and the results are not satisfactory. In recent years, our group has introduced a time series model (statistical point of view) and a visual representation (geometrical point of view)to DNA sequence analysis. We have also used fractal dimension, correlation dimension, the Hurst exponent and the dimension spectrum (multifractal analysis) to discuss problems in this field. In this paper, we introduce these fractal models and methods and the results of DNA sequence analysis.

Recurrent chimeric RNAs enriched in human prostate cancer identified by deep sequencing

Science.gov (United States)

Kannan, Kalpana; Wang, Liguo; Wang, Jianghua; Ittmann, Michael M.; Li, Wei; Yen, Laising

2011-01-01

Transcription-induced chimeric RNAs, possessing sequences from different genes, are expected to increase the proteomic diversity through chimeric proteins or altered regulation. Despite their importance, few studies have focused on chimeric RNAs especially regarding their presence/roles in human cancers. By deep sequencing the transcriptome of 20 human prostate cancer and 10 matched benign prostate tissues, we obtained 1.3 billion sequence reads, which led to the identification of 2,369 chimeric RNA candidates. Chimeric RNAs occurred in significantly higher frequency in cancer than in matched benign samples. Experimental investigation of a selected 46 set led to the confirmation of 32 chimeric RNAs, of which 27 were highly recurrent and previously undescribed in prostate cancer. Importantly, a subset of these chimeras was present in prostate cancer cell lines, but not detectable in primary human prostate epithelium cells, implying their associations with cancer. These chimeras contain discernable 5′ and 3′ splice sites at the RNA junction, indicating that their formation is mediated by splicing. Their presence is also largely independent of the expression of parental genes, suggesting that other factors are involved in their production and regulation. One chimera, TMEM79-SMG5, is highly differentially expressed in human cancer samples and therefore a potential biomarker. The prevalence of chimeric RNAs may allow the limited number of human genes to encode a substantially larger number of RNAs and proteins, forming an additional layer of cellular complexity. Together, our results suggest that chimeric RNAs are widespread, and increased chimeric RNA events could represent a unique class of molecular alteration in cancer. PMID:21571633

Identifying genomic changes associated with insecticide resistance in the dengue mosquito Aedes aegypti by deep targeted sequencing

Science.gov (United States)

Faucon, Frederic; Dusfour, Isabelle; Gaude, Thierry; Navratil, Vincent; Boyer, Frederic; Chandre, Fabrice; Sirisopa, Patcharawan; Thanispong, Kanutcharee; Juntarajumnong, Waraporn; Poupardin, Rodolphe; Chareonviriyaphap, Theeraphap; Girod, Romain; Corbel, Vincent; Reynaud, Stephane; David, Jean-Philippe

2015-01-01

The capacity of mosquitoes to resist insecticides threatens the control of diseases such as dengue and malaria. Until alternative control tools are implemented, characterizing resistance mechanisms is crucial for managing resistance in natural populations. Insecticide biodegradation by detoxification enzymes is a common resistance mechanism; however, the genomic changes underlying this mechanism have rarely been identified, precluding individual resistance genotyping. In particular, the role of copy number variations (CNVs) and polymorphisms of detoxification enzymes have never been investigated at the genome level, although they can represent robust markers of metabolic resistance. In this context, we combined target enrichment with high-throughput sequencing for conducting the first comprehensive screening of gene amplifications and polymorphisms associated with insecticide resistance in mosquitoes. More than 760 candidate genes were captured and deep sequenced in several populations of the dengue mosquito Ae. aegypti displaying distinct genetic backgrounds and contrasted resistance levels to the insecticide deltamethrin. CNV analysis identified 41 gene amplifications associated with resistance, most affecting cytochrome P450s overtranscribed in resistant populations. Polymorphism analysis detected more than 30,000 variants and strong selection footprints in specific genomic regions. Combining Bayesian and allele frequency filtering approaches identified 55 nonsynonymous variants strongly associated with resistance. Both CNVs and polymorphisms were conserved within regions but differed across continents, confirming that genomic changes underlying metabolic resistance to insecticides are not universal. By identifying novel DNA markers of insecticide resistance, this study opens the way for tracking down metabolic changes developed by mosquitoes to resist insecticides within and among populations. PMID:26206155

Relationship between aging and T1 relaxation time in deep gray matter: A voxel-based analysis.

Science.gov (United States)

Okubo, Gosuke; Okada, Tomohisa; Yamamoto, Akira; Fushimi, Yasutaka; Okada, Tsutomu; Murata, Katsutoshi; Togashi, Kaori

2017-09-01

To investigate age-related changes in T 1 relaxation time in deep gray matter structures in healthy volunteers using magnetization-prepared 2 rapid acquisition gradient echoes (MP2RAGE). In all, 70 healthy volunteers (aged 20-76, mean age 42.6 years) were scanned at 3T magnetic resonance imaging (MRI). A MP2RAGE sequence was employed to quantify T 1 relaxation times. After the spatial normalization of T 1 maps with the diffeomorphic anatomical registration using the exponentiated Lie algebra algorithm, voxel-based regression analysis was conducted. In addition, linear and quadratic regression analyses of regions of interest (ROIs) were also performed. With aging, voxel-based analysis (VBA) revealed significant T 1 value decreases in the ventral-inferior putamen, nucleus accumbens, and amygdala, whereas T 1 values significantly increased in the thalamus and white matter as well (P time vary by location in deep gray matter. 2 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:724-731. © 2017 International Society for Magnetic Resonance in Medicine.

Genome Sequencing and Analysis Conference IV

Energy Technology Data Exchange (ETDEWEB)

1993-12-31

J. Craig Venter and C. Thomas Caskey co-chaired Genome Sequencing and Analysis Conference IV held at Hilton Head, South Carolina from September 26--30, 1992. Venter opened the conference by noting that approximately 400 researchers from 16 nations were present four times as many participants as at Genome Sequencing Conference I in 1989. Venter also introduced the Data Fair, a new component of the conference allowing exchange and on-site computer analysis of unpublished sequence data.

Geochemical features and effects on deep-seated fluids during the May-June 2012 southern Po Valley seismic sequence

Directory of Open Access Journals (Sweden)

Francesco Italiano

2012-10-01

Full Text Available A periodic sampling of the groundwaters and dissolved and free gases in selected deep wells located in the area affected by the May-June 2012 southern Po Valley seismic sequence has provided insight into seismogenic-induced changes of the local aquifer systems. The results obtained show progressive changes in the fluid geochemistry, allowing it to be established that deep-seated fluids were mobilized during the seismic sequence and reached surface layers along faults and fractures, which generated significant geochemical anomalies. The May-June 2012 seismic swarm (mainshock on May 29, 2012, M 5.8; 7 shocks M >5, about 200 events 3 > M > 5 induced several modifications in the circulating fluids. This study reports the preliminary results obtained for the geochemical features of the waters and gases collected over the epicentral area from boreholes drilled at different depths, thus intercepting water and gases with different origins and circulation. The aim of the investigations was to improve our knowledge of the fluids circulating over the seismic area (e.g. origin, provenance, interactions, mixing of different components, temporal changes. This was achieved by collecting samples from both shallow and deep-drilled boreholes, and then, after the selection of the relevant sites, we looked for temporal changes with mid-to-long-term monitoring activity following a constant sampling rate. This allowed us to gain better insight into the relationships between the fluid circulation and the faulting activity. The sampling sites are listed in Table 1, along with the analytical results of the gas phase. […

Analysis of deep learning methods for blind protein contact prediction in CASP12.

Science.gov (United States)

Wang, Sheng; Sun, Siqi; Xu, Jinbo

2018-03-01

Here we present the results of protein contact prediction achieved in CASP12 by our RaptorX-Contact server, which is an early implementation of our deep learning method for contact prediction. On a set of 38 free-modeling target domains with a median family size of around 58 effective sequences, our server obtained an average top L/5 long- and medium-range contact accuracy of 47% and 44%, respectively (L = length). A complete implementation has an average accuracy of 59% and 57%, respectively. Our deep learning method formulates contact prediction as a pixel-level image labeling problem and simultaneously predicts all residue pairs of a protein using a combination of two deep residual neural networks, taking as input the residue conservation information, predicted secondary structure and solvent accessibility, contact potential, and coevolution information. Our approach differs from existing methods mainly in (1) formulating contact prediction as a pixel-level image labeling problem instead of an image-level classification problem; (2) simultaneously predicting all contacts of an individual protein to make effective use of contact occurrence patterns; and (3) integrating both one-dimensional and two-dimensional deep convolutional neural networks to effectively learn complex sequence-structure relationship including high-order residue correlation. This paper discusses the RaptorX-Contact pipeline, both contact prediction and contact-based folding results, and finally the strength and weakness of our method. © 2017 Wiley Periodicals, Inc.

Roadside video data analysis deep learning

CERN Document Server

Verma, Brijesh; Stockwell, David

2017-01-01

This book highlights the methods and applications for roadside video data analysis, with a particular focus on the use of deep learning to solve roadside video data segmentation and classification problems. It describes system architectures and methodologies that are specifically built upon learning concepts for roadside video data processing, and offers a detailed analysis of the segmentation, feature extraction and classification processes. Lastly, it demonstrates the applications of roadside video data analysis including scene labelling, roadside vegetation classification and vegetation biomass estimation in fire risk assessment.

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.

FINITE ELEMENT ANALYSIS OF DEEP BEAM UNDER DIRECT AND INDIRECT LOAD

Directory of Open Access Journals (Sweden)

Haleem K. Hussain

2018-05-01

Full Text Available This research study the effect of exist of opening in web of deep beam loaded directly and indirectly and the behavior of reinforced concrete deep beams without with and without web reinforcement, the opening size and shear span ratio (a/d was constant. Nonlinear analysis using the finite element method with ANSYS software release 12.0 program was used to predict the ultimate load capacity and crack propagation for reinforced concrete deep beams with openings. The adopted beam models depend on experimental test program of reinforced concrete deep beam with and without openings and the finite element analysis result showed a good agreement with small amount of deference in ultimate beam capacity with (ANSYS analysis and it was completely efficient to simulate the behavior of reinforced concrete deep beams. The mid-span deflection at ultimate applied load and inclined cracked were highly compatible with experimental results. The model with opening in the shear span shows a reduction in the load-carrying capacity of beam and adding the vertical stirrup has improve the capacity of ultimate beam load.

Deep learning

CERN Document Server

Goodfellow, Ian; Courville, Aaron

2016-01-01

Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language proces...

Evolutionary process of deep-sea bathymodiolus mussels.

Science.gov (United States)

Miyazaki, Jun-Ichi; de Oliveira Martins, Leonardo; Fujita, Yuko; Matsumoto, Hiroto; Fujiwara, Yoshihiro

2010-04-27

Since the discovery of deep-sea chemosynthesis-based communities, much work has been done to clarify their organismal and environmental aspects. However, major topics remain to be resolved, including when and how organisms invade and adapt to deep-sea environments; whether strategies for invasion and adaptation are shared by different taxa or unique to each taxon; how organisms extend their distribution and diversity; and how they become isolated to speciate in continuous waters. Deep-sea mussels are one of the dominant organisms in chemosynthesis-based communities, thus investigations of their origin and evolution contribute to resolving questions about life in those communities. We investigated worldwide phylogenetic relationships of deep-sea Bathymodiolus mussels and their mytilid relatives by analyzing nucleotide sequences of the mitochondrial cytochrome c oxidase subunit I (COI) and NADH dehydrogenase subunit 4 (ND4) genes. Phylogenetic analysis of the concatenated sequence data showed that mussels of the subfamily Bathymodiolinae from vents and seeps were divided into four groups, and that mussels of the subfamily Modiolinae from sunken wood and whale carcasses assumed the outgroup position and shallow-water modioline mussels were positioned more distantly to the bathymodioline mussels. We provisionally hypothesized the evolutionary history of Bathymodilolus mussels by estimating evolutionary time under a relaxed molecular clock model. Diversification of bathymodioline mussels was initiated in the early Miocene, and subsequently diversification of the groups occurred in the early to middle Miocene. The phylogenetic relationships support the "Evolutionary stepping stone hypothesis," in which mytilid ancestors exploited sunken wood and whale carcasses in their progressive adaptation to deep-sea environments. This hypothesis is also supported by the evolutionary transition of symbiosis in that nutritional adaptation to the deep sea proceeded from extracellular

Time and space resolved deep metagenomics to investigate selection pressures on low abundant species in complex environments

DEFF Research Database (Denmark)

Albertsen, Mads; Saunders, Aaron Marc; Nielsen, Kåre Lehmann

and between EBPR plants we sequenced a total of 10 samples from 3 different plants over a 3 year period at a depth of 25 Gb each. In addition, one time point was selected for deep sequencing, generating 200 Gb of sequence divided between replicates. Quantitative FISH analysis using >30 oligonucleotide probes...

Robustness analysis of chiller sequencing control

International Nuclear Information System (INIS)

Liao, Yundan; Sun, Yongjun; Huang, Gongsheng

2015-01-01

Highlights: • Uncertainties with chiller sequencing control were systematically quantified. • Robustness of chiller sequencing control was systematically analyzed. • Different sequencing control strategies were sensitive to different uncertainties. • A numerical method was developed for easy selection of chiller sequencing control. - Abstract: Multiple-chiller plant is commonly employed in the heating, ventilating and air-conditioning system to increase operational feasibility and energy-efficiency under part load condition. In a multiple-chiller plant, chiller sequencing control plays a key role in achieving overall energy efficiency while not sacrifices the cooling sufficiency for indoor thermal comfort. Various sequencing control strategies have been developed and implemented in practice. Based on the observation that (i) uncertainty, which cannot be avoided in chiller sequencing control, has a significant impact on the control performance and may cause the control fail to achieve the expected control and/or energy performance; and (ii) in current literature few studies have systematically addressed this issue, this paper therefore presents a study on robustness analysis of chiller sequencing control in order to understand the robustness of various chiller sequencing control strategies under different types of uncertainty. Based on the robustness analysis, a simple and applicable method is developed to select the most robust control strategy for a given chiller plant in the presence of uncertainties, which will be verified using case studies

Sequence comparison and phylogenetic analysis of core gene of ...

African Journals Online (AJOL)

Phylogenetic analysis suggests that our sequences are clustered with sequences reported from Japan. This is the first phylogenetic analysis of HCV core gene from Pakistani population. Our sequences and sequences from Japan are grouped into same cluster in the phylogenetic tree. Sequence comparison and ...

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...

miRDis: a Web tool for endogenous and exogenous microRNA discovery based on deep-sequencing data analysis.

Science.gov (United States)

Zhang, Hanyuan; Vieira Resende E Silva, Bruno; Cui, Juan

2018-05-01

Small RNA sequencing is the most widely used tool for microRNA (miRNA) discovery, and shows great potential for the efficient study of miRNA cross-species transport, i.e., by detecting the presence of exogenous miRNA sequences in the host species. Because of the increased appreciation of dietary miRNAs and their far-reaching implication in human health, research interests are currently growing with regard to exogenous miRNAs bioavailability, mechanisms of cross-species transport and miRNA function in cellular biological processes. In this article, we present microRNA Discovery (miRDis), a new small RNA sequencing data analysis pipeline for both endogenous and exogenous miRNA detection. Specifically, we developed and deployed a Web service that supports the annotation and expression profiling data of known host miRNAs and the detection of novel miRNAs, other noncoding RNAs, and the exogenous miRNAs from dietary species. As a proof-of-concept, we analyzed a set of human plasma sequencing data from a milk-feeding study where 225 human miRNAs were detected in the plasma samples and 44 show elevated expression after milk intake. By examining the bovine-specific sequences, data indicate that three bovine miRNAs (bta-miR-378, -181* and -150) are present in human plasma possibly because of the dietary uptake. Further evaluation based on different sets of public data demonstrates that miRDis outperforms other state-of-the-art tools in both detection and quantification of miRNA from either animal or plant sources. The miRDis Web server is available at: http://sbbi.unl.edu/miRDis/index.php.

Congruent Deep Relationships in the Grape Family (Vitaceae) Based on Sequences of Chloroplast Genomes and Mitochondrial Genes via Genome Skimming.

Science.gov (United States)

Zhang, Ning; Wen, Jun; Zimmer, Elizabeth A

2015-01-01

Vitaceae is well-known for having one of the most economically important fruits, i.e., the grape (Vitis vinifera). The deep phylogeny of the grape family was not resolved until a recent phylogenomic analysis of 417 nuclear genes from transcriptome data. However, it has been reported extensively that topologies based on nuclear and organellar genes may be incongruent due to differences in their evolutionary histories. Therefore, it is important to reconstruct a backbone phylogeny of the grape family using plastomes and mitochondrial genes. In this study,next-generation sequencing data sets of 27 species were obtained using genome skimming with total DNAs from silica-gel preserved tissue samples on an Illumina NextSeq 500 instrument [corrected]. Plastomes were assembled using the combination of de novo and reference genome (of V. vinifera) methods. Sixteen mitochondrial genes were also obtained via genome skimming using the reference genome of V. vinifera. Extensive phylogenetic analyses were performed using maximum likelihood and Bayesian methods. The topology based on either plastome data or mitochondrial genes is congruent with the one using hundreds of nuclear genes, indicating that the grape family did not exhibit significant reticulation at the deep level. The results showcase the power of genome skimming in capturing extensive phylogenetic data: especially from chloroplast and mitochondrial DNAs.

Congruent Deep Relationships in the Grape Family (Vitaceae Based on Sequences of Chloroplast Genomes and Mitochondrial Genes via Genome Skimming.

Directory of Open Access Journals (Sweden)

Ning Zhang

Full Text Available Vitaceae is well-known for having one of the most economically important fruits, i.e., the grape (Vitis vinifera. The deep phylogeny of the grape family was not resolved until a recent phylogenomic analysis of 417 nuclear genes from transcriptome data. However, it has been reported extensively that topologies based on nuclear and organellar genes may be incongruent due to differences in their evolutionary histories. Therefore, it is important to reconstruct a backbone phylogeny of the grape family using plastomes and mitochondrial genes. In this study,next-generation sequencing data sets of 27 species were obtained using genome skimming with total DNAs from silica-gel preserved tissue samples on an Illumina NextSeq 500 instrument [corrected]. Plastomes were assembled using the combination of de novo and reference genome (of V. vinifera methods. Sixteen mitochondrial genes were also obtained via genome skimming using the reference genome of V. vinifera. Extensive phylogenetic analyses were performed using maximum likelihood and Bayesian methods. The topology based on either plastome data or mitochondrial genes is congruent with the one using hundreds of nuclear genes, indicating that the grape family did not exhibit significant reticulation at the deep level. The results showcase the power of genome skimming in capturing extensive phylogenetic data: especially from chloroplast and mitochondrial DNAs.

Draft Genome Sequence of Pseudoalteromonas sp. Strain XI10 Isolated from the Brine-Seawater Interface of Erba Deep in the Red Sea

KAUST Repository

Zhang, Guishan; Haroon, Mohamed; Zhang, Ruifu; Hikmawan, Tyas I.; Stingl, Ulrich

2016-01-01

Pseudoalteromonas sp. strain XI10 was isolated from the brine-seawater interface of Erba Deep in the Red Sea, Saudi Arabia. Here, we present the draft genome sequence of strain XI10, a gammaproteobacterium that synthesizes polysaccharides for biofilm formation when grown in liquid culture.

Draft Genome Sequence of Pseudoalteromonas sp. Strain XI10 Isolated from the Brine-Seawater Interface of Erba Deep in the Red Sea

KAUST Repository

Zhang, Guishan

2016-03-10

Pseudoalteromonas sp. strain XI10 was isolated from the brine-seawater interface of Erba Deep in the Red Sea, Saudi Arabia. Here, we present the draft genome sequence of strain XI10, a gammaproteobacterium that synthesizes polysaccharides for biofilm formation when grown in liquid culture.

Integrated analysis of gene expression, CpG island methylation, and gene copy number in breast cancer cells by deep sequencing.

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Zhifu Sun

Full Text Available We used deep sequencing technology to profile the transcriptome, gene copy number, and CpG island methylation status simultaneously in eight commonly used breast cell lines to develop a model for how these genomic features are integrated in estrogen receptor positive (ER+ and negative breast cancer. Total mRNA sequence, gene copy number, and genomic CpG island methylation were carried out using the Illumina Genome Analyzer. Sequences were mapped to the human genome to obtain digitized gene expression data, DNA copy number in reference to the non-tumor cell line (MCF10A, and methylation status of 21,570 CpG islands to identify differentially expressed genes that were correlated with methylation or copy number changes. These were evaluated in a dataset from 129 primary breast tumors. Gene expression in cell lines was dominated by ER-associated genes. ER+ and ER- cell lines formed two distinct, stable clusters, and 1,873 genes were differentially expressed in the two groups. Part of chromosome 8 was deleted in all ER- cells and part of chromosome 17 amplified in all ER+ cells. These loci encoded 30 genes that were overexpressed in ER+ cells; 9 of these genes were overexpressed in ER+ tumors. We identified 149 differentially expressed genes that exhibited differential methylation of one or more CpG islands within 5 kb of the 5' end of the gene and for which mRNA abundance was inversely correlated with CpG island methylation status. In primary tumors we identified 84 genes that appear to be robust components of the methylation signature that we identified in ER+ cell lines. Our analyses reveal a global pattern of differential CpG island methylation that contributes to the transcriptome landscape of ER+ and ER- breast cancer cells and tumors. The role of gene amplification/deletion appears to more modest, although several potentially significant genes appear to be regulated by copy number aberrations.

Deep Sequencing Analysis of miRNA Expression in Breast Muscle of Fast-Growing and Slow-Growing Broilers

Directory of Open Access Journals (Sweden)

Hongjia Ouyang

2015-07-01

Full Text Available Growth performance is an important economic trait in chicken. MicroRNAs (miRNAs have been shown to play important roles in various biological processes, but their functions in chicken growth are not yet clear. To investigate the function of miRNAs in chicken growth, breast muscle tissues of the two-tail samples (highest and lowest body weight from Recessive White Rock (WRR and Xinghua Chickens (XH were performed on high throughput small RNA deep sequencing. In this study, a total of 921 miRNAs were identified, including 733 known mature miRNAs and 188 novel miRNAs. There were 200, 279, 257 and 297 differentially expressed miRNAs in the comparisons of WRRh vs. WRRl, WRRh vs. XHh, WRRl vs. XHl, and XHh vs. XHl group, respectively. A total of 22 highly differentially expressed miRNAs (fold change > 2 or < 0.5; p-value < 0.05; q-value < 0.01, which also have abundant expression (read counts > 1000 were found in our comparisons. As far as two analyses (WRRh vs. WRRl, and XHh vs. XHl are concerned, we found 80 common differentially expressed miRNAs, while 110 miRNAs were found in WRRh vs. XHh and WRRl vs. XHl. Furthermore, 26 common miRNAs were identified among all four comparisons. Four differentially expressed miRNAs (miR-223, miR-16, miR-205a and miR-222b-5p were validated by quantitative real-time RT-PCR (qRT-PCR. Regulatory networks of interactions among miRNAs and their targets were constructed using integrative miRNA target-prediction and network-analysis. Growth hormone receptor (GHR was confirmed as a target of miR-146b-3p by dual-luciferase assay and qPCR, indicating that miR-34c, miR-223, miR-146b-3p, miR-21 and miR-205a are key growth-related target genes in the network. These miRNAs are proposed as candidate miRNAs for future studies concerning miRNA-target function on regulation of chicken growth.

Deep sequencing of Salmonella RNA associated with heterologous Hfq proteins in vivo reveals small RNAs as a major target class and identifies RNA processing phenotypes.

Science.gov (United States)

Sittka, Alexandra; Sharma, Cynthia M; Rolle, Katarzyna; Vogel, Jörg

2009-01-01

The bacterial Sm-like protein, Hfq, is a key factor for the stability and function of small non-coding RNAs (sRNAs) in Escherichia coli. Homologues of this protein have been predicted in many distantly related organisms yet their functional conservation as sRNA-binding proteins has not entirely been clear. To address this, we expressed in Salmonella the Hfq proteins of two eubacteria (Neisseria meningitides, Aquifex aeolicus) and an archaeon (Methanocaldococcus jannaschii), and analyzed the associated RNA by deep sequencing. This in vivo approach identified endogenous Salmonella sRNAs as a major target of the foreign Hfq proteins. New Salmonella sRNA species were also identified, and some of these accumulated specifically in the presence of a foreign Hfq protein. In addition, we observed specific RNA processing defects, e.g., suppression of precursor processing of SraH sRNA by Methanocaldococcus Hfq, or aberrant accumulation of extracytoplasmic target mRNAs of the Salmonella GcvB, MicA or RybB sRNAs. Taken together, our study provides evidence of a conserved inherent sRNA-binding property of Hfq, which may facilitate the lateral transmission of regulatory sRNAs among distantly related species. It also suggests that the expression of heterologous RNA-binding proteins combined with deep sequencing analysis of RNA ligands can be used as a molecular tool to dissect individual steps of RNA metabolism in vivo.

Oasis: online analysis of small RNA deep sequencing data.

Science.gov (United States)

Capece, Vincenzo; Garcia Vizcaino, Julio C; Vidal, Ramon; Rahman, Raza-Ur; Pena Centeno, Tonatiuh; Shomroni, Orr; Suberviola, Irantzu; Fischer, Andre; Bonn, Stefan

2015-07-01

Oasis is a web application that allows for the fast and flexible online analysis of small-RNA-seq (sRNA-seq) data. It was designed for the end user in the lab, providing an easy-to-use web frontend including video tutorials, demo data and best practice step-by-step guidelines on how to analyze sRNA-seq data. Oasis' exclusive selling points are a differential expression module that allows for the multivariate analysis of samples, a classification module for robust biomarker detection and an advanced programming interface that supports the batch submission of jobs. Both modules include the analysis of novel miRNAs, miRNA targets and functional analyses including GO and pathway enrichment. Oasis generates downloadable interactive web reports for easy visualization, exploration and analysis of data on a local system. Finally, Oasis' modular workflow enables for the rapid (re-) analysis of data. Oasis is implemented in Python, R, Java, PHP, C++ and JavaScript. It is freely available at http://oasis.dzne.de. stefan.bonn@dzne.de Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

Profile of microbial communities on carbonate stones of the medieval church of San Leonardo di Siponto (Italy) by Illumina-based deep sequencing.

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Chimienti, Guglielmina; Piredda, Roberta; Pepe, Gabriella; van der Werf, Inez Dorothé; Sabbatini, Luigia; Crecchio, Carmine; Ricciuti, Patrizia; D'Erchia, Anna Maria; Manzari, Caterina; Pesole, Graziano

2016-10-01

Comprehensive studies of the biodiversity of the microbial epilithic community on monuments may provide critical insights for clarifying factors involved in the colonization processes. We carried out a high-throughput investigation of the communities colonizing the medieval church of San Leonardo di Siponto (Italy) by Illumina-based deep sequencing. The metagenomic analysis of sequences revealed the presence of Archaea, Bacteria, and Eukarya. Bacteria were Actinobacteria, Proteobacteria, Bacteroidetes, Cyanobacteria, Chloroflexi, Firmicutes and Candidatus Saccharibacteria. The predominant phylum was Actinobacteria, with the orders Actynomycetales and Rubrobacteriales, represented by the genera Pseudokineococcus, Sporichthya, Blastococcus, Arthrobacter, Geodermatophilus, Friedmanniella, Modestobacter, and Rubrobacter, respectively. Cyanobacteria sequences showing strong similarity with an uncultured bacterium sequence were identified. The presence of the green algae Oocystaceae and Trebuxiaceae was revealed. The microbial diversity was explored at qualitative and quantitative levels, evaluating the richness (the number of operational taxonomic units (OTUs)) and the abundance of reads associated with each OTU. The rarefaction curves approached saturation, suggesting that the majority of OTUs were recovered. The results highlighted a structured community, showing low diversity, made up of extremophile organisms adapted to desiccation and UV radiation. Notably, the microbiome appeared to be composed not only of microorganisms possibly involved in biodeterioration but also of carbonatogenic bacteria, such as those belonging to the genus Arthrobacter, which could be useful in bioconservation. Our investigation demonstrated that molecular tools, and in particular the easy-to-run next-generation sequencing, are powerful to perform a microbiological diagnosis in order to plan restoration and protection strategies.

Sequence of structures in fine-grained turbidites: Comparison of recent deep-sea and ancient flysch sediments

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Stow, Dorrik A. V.; Shanmugam, Ganapathy

1980-01-01

A comparative study of the sequence of sedimentary structures in ancient and modern fine-grained turbidites is made in three contrasting areas. They are (1) Holocene and Pleistocene deep-sea muds of the Nova Scotian Slope and Rise, (2) Middle Ordovician Sevier Shale of the Valley and Ridge Province of the Southern Appalachians, and (3) Cambro-Ordovician Halifax Slate of the Meguma Group in Nova Scotia. A standard sequence of structures is proposed for fine-grained turbidites. The complete sequence has nine sub-divisions that are here termed T 0 to T 8. "The lower subdivision (T 0) comprises a silt lamina which has a sharp, scoured and load-cast base, internal parallel-lamination and cross-lamination, and a sharp current-lineated or wavy surface with 'fading-ripples' (= Type C etc. …)." (= Type C ripple-drift cross-lamination, Jopling and Walker, 1968). The overlying sequence shows textural and compositional grading through alternating silt and mud laminae. A convolute-laminated sub-division (T 1) is overlain by low-amplitude climbing ripples (T 2), thin regular laminae (T 3), thin indistinct laminae (T 4), and thin wipsy or convolute laminae (T 5). The topmost three divisions, graded mud (T 6), ungraded mud (T 7) and bioturbated mud (T 8), do not have silt laminae but rare patchy silt lenses and silt pseudonodules and a thin zone of micro-burrowing near the upper surface. The proposed sequence is analogous to the Bouma (1962) structural scheme for sandy turbidites and is approximately equivalent to Bouma's (C)DE divisions. The repetition of partial sequences characterizes different parts of the slope/base-of-slope/basin plain environment, and represents deposition from different stages of evolution of a large, muddy, turbidity flow. Microstructural detail and sequence are well preserved in ancient and even slightly metamorphosed sediments. Their recognition is important for determining depositional processes and for palaeoenvironmental interpretation.

Comparison of illumina and 454 deep sequencing in participants failing raltegravir-based antiretroviral therapy.

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Jonathan Z Li

Full Text Available The impact of raltegravir-resistant HIV-1 minority variants (MVs on raltegravir treatment failure is unknown. Illumina sequencing offers greater throughput than 454, but sequence analysis tools for viral sequencing are needed. We evaluated Illumina and 454 for the detection of HIV-1 raltegravir-resistant MVs.A5262 was a single-arm study of raltegravir and darunavir/ritonavir in treatment-naïve patients. Pre-treatment plasma was obtained from 5 participants with raltegravir resistance at the time of virologic failure. A control library was created by pooling integrase clones at predefined proportions. Multiplexed sequencing was performed with Illumina and 454 platforms at comparable costs. Illumina sequence analysis was performed with the novel snp-assess tool and 454 sequencing was analyzed with V-Phaser.Illumina sequencing resulted in significantly higher sequence coverage and a 0.095% limit of detection. Illumina accurately detected all MVs in the control library at ≥0.5% and 7/10 MVs expected at 0.1%. 454 sequencing failed to detect any MVs at 0.1% with 5 false positive calls. For MVs detected in the patient samples by both 454 and Illumina, the correlation in the detected variant frequencies was high (R2 = 0.92, P<0.001. Illumina sequencing detected 2.4-fold greater nucleotide MVs and 2.9-fold greater amino acid MVs compared to 454. The only raltegravir-resistant MV detected was an E138K mutation in one participant by Illumina sequencing, but not by 454.In participants of A5262 with raltegravir resistance at virologic failure, baseline raltegravir-resistant MVs were rarely detected. At comparable costs to 454 sequencing, Illumina demonstrated greater depth of coverage, increased sensitivity for detecting HIV MVs, and fewer false positive variant calls.

DeepLoc: prediction of protein subcellular localization using deep learning

DEFF Research Database (Denmark)

Almagro Armenteros, Jose Juan; Sønderby, Casper Kaae; Sønderby, Søren Kaae

2017-01-01

The prediction of eukaryotic protein subcellular localization is a well-studied topic in bioinformatics due to its relevance in proteomics research. Many machine learning methods have been successfully applied in this task, but in most of them, predictions rely on annotation of homologues from...... knowledge databases. For novel proteins where no annotated homologues exist, and for predicting the effects of sequence variants, it is desirable to have methods for predicting protein properties from sequence information only. Here, we present a prediction algorithm using deep neural networks to predict...... current state-of-the-art algorithms, including those relying on homology information. The method is available as a web server at http://www.cbs.dtu.dk/services/DeepLoc . Example code is available at https://github.com/JJAlmagro/subcellular_localization . The dataset is available at http...

Deep sequencing of foot-and-mouth disease virus reveals RNA sequences involved in genome packaging.

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Logan, Grace; Newman, Joseph; Wright, Caroline F; Lasecka-Dykes, Lidia; Haydon, Daniel T; Cottam, Eleanor M; Tuthill, Tobias J

2017-10-18

Non-enveloped viruses protect their genomes by packaging them into an outer shell or capsid of virus-encoded proteins. Packaging and capsid assembly in RNA viruses can involve interactions between capsid proteins and secondary structures in the viral genome as exemplified by the RNA bacteriophage MS2 and as proposed for other RNA viruses of plants, animals and human. In the picornavirus family of non-enveloped RNA viruses, the requirements for genome packaging remain poorly understood. Here we show a novel and simple approach to identify predicted RNA secondary structures involved in genome packaging in the picornavirus foot-and-mouth disease virus (FMDV). By interrogating deep sequencing data generated from both packaged and unpackaged populations of RNA we have determined multiple regions of the genome with constrained variation in the packaged population. Predicted secondary structures of these regions revealed stem loops with conservation of structure and a common motif at the loop. Disruption of these features resulted in attenuation of virus growth in cell culture due to a reduction in assembly of mature virions. This study provides evidence for the involvement of predicted RNA structures in picornavirus packaging and offers a readily transferable methodology for identifying packaging requirements in many other viruses. Importance In order to transmit their genetic material to a new host, non-enveloped viruses must protect their genomes by packaging them into an outer shell or capsid of virus-encoded proteins. For many non-enveloped RNA viruses the requirements for this critical part of the viral life cycle remain poorly understood. We have identified RNA sequences involved in genome packaging of the picornavirus foot-and-mouth disease virus. This virus causes an economically devastating disease of livestock affecting both the developed and developing world. The experimental methods developed to carry out this work are novel, simple and transferable to the

Direct chloroplast sequencing: comparison of sequencing platforms and analysis tools for whole chloroplast barcoding.

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Marta Brozynska

Full Text Available Direct sequencing of total plant DNA using next generation sequencing technologies generates a whole chloroplast genome sequence that has the potential to provide a barcode for use in plant and food identification. Advances in DNA sequencing platforms may make this an attractive approach for routine plant identification. The HiSeq (Illumina and Ion Torrent (Life Technology sequencing platforms were used to sequence total DNA from rice to identify polymorphisms in the whole chloroplast genome sequence of a wild rice plant relative to cultivated rice (cv. Nipponbare. Consensus chloroplast sequences were produced by mapping sequence reads to the reference rice chloroplast genome or by de novo assembly and mapping of the resulting contigs to the reference sequence. A total of 122 polymorphisms (SNPs and indels between the wild and cultivated rice chloroplasts were predicted by these different sequencing and analysis methods. Of these, a total of 102 polymorphisms including 90 SNPs were predicted by both platforms. Indels were more variable with different sequencing methods, with almost all discrepancies found in homopolymers. The Ion Torrent platform gave no apparent false SNP but was less reliable for indels. The methods should be suitable for routine barcoding using appropriate combinations of sequencing platform and data analysis.

Subsurface microbial diversity in deep-granitic-fracture water in Colorado

Science.gov (United States)

Sahl, J.W.; Schmidt, R.; Swanner, E.D.; Mandernack, K.W.; Templeton, A.S.; Kieft, Thomas L.; Smith, R.L.; Sanford, W.E.; Callaghan, R.L.; Mitton, J.B.; Spear, J.R.

2008-01-01

A microbial community analysis using 16S rRNA gene sequencing was performed on borehole water and a granite rock core from Henderson Mine, a >1,000-meter-deep molybdenum mine near Empire, CO. Chemical analysis of borehole water at two separate depths (1,044 m and 1,004 m below the mine entrance) suggests that a sharp chemical gradient exists, likely from the mixing of two distinct subsurface fluids, one metal rich and one relatively dilute; this has created unique niches for microorganisms. The microbial community analyzed from filtered, oxic borehole water indicated an abundance of sequences from iron-oxidizing bacteria (Gallionella spp.) and was compared to the community from the same borehole after 2 weeks of being plugged with an expandable packer. Statistical analyses with UniFrac revealed a significant shift in community structure following the addition of the packer. Phospholipid fatty acid (PLFA) analysis suggested that Nitrosomonadales dominated the oxic borehole, while PLFAs indicative of anaerobic bacteria were most abundant in the samples from the plugged borehole. Microbial sequences were represented primarily by Firmicutes, Proteobacteria, and a lineage of sequences which did not group with any identified bacterial division; phylogenetic analyses confirmed the presence of a novel candidate division. This "Henderson candidate division" dominated the clone libraries from the dilute anoxic fluids. Sequences obtained from the granitic rock core (1,740 m below the surface) were represented by the divisions Proteobacteria (primarily the family Ralstoniaceae) and Firmicutes. Sequences grouping within Ralstoniaceae were also found in the clone libraries from metal-rich fluids yet were absent in more dilute fluids. Lineage-specific comparisons, combined with phylogenetic statistical analyses, show that geochemical variance has an important effect on microbial community structure in deep, subsurface systems. Copyright ?? 2008, American Society for Microbiology

Sequencing and de novo analysis of a coral larval transcriptome using 454 GSFlx

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Colbourne John K

2009-05-01

Full Text Available Abstract Background New methods are needed for genomic-scale analysis of emerging model organisms that exemplify important biological questions but lack fully sequenced genomes. For example, there is an urgent need to understand the potential for corals to adapt to climate change, but few molecular resources are available for studying these processes in reef-building corals. To facilitate genomics studies in corals and other non-model systems, we describe methods for transcriptome sequencing using 454, as well as strategies for assembling a useful catalog of genes from the output. We have applied these methods to sequence the transcriptome of planulae larvae from the coral Acropora millepora. Results More than 600,000 reads produced in a single 454 sequencing run were assembled into ~40,000 contigs with five-fold average sequencing coverage. Based on sequence similarity with known proteins, these analyses identified ~11,000 different genes expressed in a range of conditions including thermal stress and settlement induction. Assembled sequences were annotated with gene names, conserved domains, and Gene Ontology terms. Targeted searches using these annotations identified the majority of genes associated with essential metabolic pathways and conserved signaling pathways, as well as novel candidate genes for stress-related processes. Comparisons with the genome of the anemone Nematostella vectensis revealed ~8,500 pairs of orthologs and ~100 candidate coral-specific genes. More than 30,000 SNPs were detected in the coral sequences, and a subset of these validated by re-sequencing. Conclusion The methods described here for deep sequencing of the transcriptome should be widely applicable to generate catalogs of genes and genetic markers in emerging model organisms. Our data provide the most comprehensive sequence resource currently available for reef-building corals, and include an extensive collection of potential genetic markers for association and

Deep-Coverage MPS Analysis of Heteroplasmic Variants within the mtGenome Allows for Frequent Differentiation of Maternal Relatives

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Mitchell M. Holland

2018-02-01

Full Text Available Distinguishing between maternal relatives through mitochondrial (mt DNA sequence analysis has been a longstanding desire of the forensic community. Using a deep-coverage, massively parallel sequencing (DCMPS approach, we studied the pattern of mtDNA heteroplasmy across the mtgenomes of 39 mother-child pairs of European decent; haplogroups H, J, K, R, T, U, and X. Both shared and differentiating heteroplasmy were observed on a frequent basis in these closely related maternal relatives, with the minor variant often presented as 2–10% of the sequencing reads. A total of 17 pairs exhibited differentiating heteroplasmy (44%, with the majority of sites (76%, 16 of 21 occurring in the coding region, further illustrating the value of conducting sequence analysis on the entire mtgenome. A number of the sites of differentiating heteroplasmy resulted in non-synonymous changes in protein sequence (5 of 21, and to changes in transfer or ribosomal RNA sequences (5 of 21, highlighting the potentially deleterious nature of these heteroplasmic states. Shared heteroplasmy was observed in 12 of the 39 mother-child pairs (31%, with no duplicate sites of either differentiating or shared heteroplasmy observed; a single nucleotide position (16093 was duplicated between the data sets. Finally, rates of heteroplasmy in blood and buccal cells were compared, as it is known that rates can vary across tissue types, with similar observations in the current study. Our data support the view that differentiating heteroplasmy across the mtgenome can be used to frequently distinguish maternal relatives, and could be of interest to both the medical genetics and forensic communities.

DeepCNF-D: Predicting Protein Order/Disorder Regions by Weighted Deep Convolutional Neural Fields

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Sheng Wang

2015-07-01

Full Text Available Intrinsically disordered proteins or protein regions are involved in key biological processes including regulation of transcription, signal transduction, and alternative splicing. Accurately predicting order/disorder regions ab initio from the protein sequence is a prerequisite step for further analysis of functions and mechanisms for these disordered regions. This work presents a learning method, weighted DeepCNF (Deep Convolutional Neural Fields, to improve the accuracy of order/disorder prediction by exploiting the long-range sequential information and the interdependency between adjacent order/disorder labels and by assigning different weights for each label during training and prediction to solve the label imbalance issue. Evaluated by the CASP9 and CASP10 targets, our method obtains 0.855 and 0.898 AUC values, which are higher than the state-of-the-art single ab initio predictors.

Oral Microbiome of Deep and Shallow Dental Pockets In Chronic Periodontitis

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Ge, Xiuchun; Rodriguez, Rafael; Trinh, My; Gunsolley, John; Xu, Ping

2013-01-01

We examined the subgingival bacterial biodiversity in untreated chronic periodontitis patients by sequencing 16S rRNA genes. The primary purpose of the study was to compare the oral microbiome in deep (diseased) and shallow (healthy) sites. A secondary purpose was to evaluate the influences of smoking, race and dental caries on this relationship. A total of 88 subjects from two clinics were recruited. Paired subgingival plaque samples were taken from each subject, one from a probing site depth >5 mm (deep site) and the other from a probing site depth ≤3mm (shallow site). A universal primer set was designed to amplify the V4–V6 region for oral microbial 16S rRNA sequences. Differences in genera and species attributable to deep and shallow sites were determined by statistical analysis using a two-part model and false discovery rate. Fifty-one of 170 genera and 200 of 746 species were found significantly different in abundances between shallow and deep sites. Besides previously identified periodontal disease-associated bacterial species, additional species were found markedly changed in diseased sites. Cluster analysis revealed that the microbiome difference between deep and shallow sites was influenced by patient-level effects such as clinic location, race and smoking. The differences between clinic locations may be influenced by racial distribution, in that all of the African Americans subjects were seen at the same clinic. Our results suggested that there were influences from the microbiome for caries and periodontal disease and these influences are independent. PMID:23762384

Deep sequencing of ESTs from nacreous and prismatic layer producing tissues and a screen for novel shell formation-related genes in the pearl oyster.

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Shigeharu Kinoshita

Full Text Available BACKGROUND: Despite its economic importance, we have a limited understanding of the molecular mechanisms underlying shell formation in pearl oysters, wherein the calcium carbonate crystals, nacre and prism, are formed in a highly controlled manner. We constructed comprehensive expressed gene profiles in the shell-forming tissues of the pearl oyster Pinctada fucata and identified novel shell formation-related genes candidates. PRINCIPAL FINDINGS: We employed the GS FLX 454 system and constructed transcriptome data sets from pallial mantle and pearl sac, which form the nacreous layer, and from the mantle edge, which forms the prismatic layer in P. fucata. We sequenced 260477 reads and obtained 29682 unique sequences. We also screened novel nacreous and prismatic gene candidates by a combined analysis of sequence and expression data sets, and identified various genes encoding lectin, protease, protease inhibitors, lysine-rich matrix protein, and secreting calcium-binding proteins. We also examined the expression of known nacreous and prismatic genes in our EST library and identified novel isoforms with tissue-specific expressions. CONCLUSIONS: We constructed EST data sets from the nacre- and prism-producing tissues in P. fucata and found 29682 unique sequences containing novel gene candidates for nacreous and prismatic layer formation. This is the first report of deep sequencing of ESTs in the shell-forming tissues of P. fucata and our data provide a powerful tool for a comprehensive understanding of the molecular mechanisms of molluscan biomineralization.

Integrated sequence analysis. Final report

International Nuclear Information System (INIS)

Andersson, K.; Pyy, P.

1998-02-01

The NKS/RAK subprojet 3 'integrated sequence analysis' (ISA) was formulated with the overall objective to develop and to test integrated methodologies in order to evaluate event sequences with significant human action contribution. The term 'methodology' denotes not only technical tools but also methods for integration of different scientific disciplines. In this report, we first discuss the background of ISA and the surveys made to map methods in different application fields, such as man machine system simulation software, human reliability analysis (HRA) and expert judgement. Specific event sequences were, after the surveys, selected for application and testing of a number of ISA methods. The event sequences discussed in the report were cold overpressure of BWR, shutdown LOCA of BWR, steam generator tube rupture of a PWR and BWR disturbed signal view in the control room after an external event. Different teams analysed these sequences by using different ISA and HRA methods. Two kinds of results were obtained from the ISA project: sequence specific and more general findings. The sequence specific results are discussed together with each sequence description. The general lessons are discussed under a separate chapter by using comparisons of different case studies. These lessons include areas ranging from plant safety management (design, procedures, instrumentation, operations, maintenance and safety practices) to methodological findings (ISA methodology, PSA,HRA, physical analyses, behavioural analyses and uncertainty assessment). Finally follows a discussion about the project and conclusions are presented. An interdisciplinary study of complex phenomena is a natural way to produce valuable and innovative results. This project came up with structured ways to perform ISA and managed to apply the in practice. The project also highlighted some areas where more work is needed. In the HRA work, development is required for the use of simulators and expert judgement as

Integrated sequence analysis. Final report

Energy Technology Data Exchange (ETDEWEB)

Andersson, K.; Pyy, P

1998-02-01

The NKS/RAK subprojet 3 `integrated sequence analysis` (ISA) was formulated with the overall objective to develop and to test integrated methodologies in order to evaluate event sequences with significant human action contribution. The term `methodology` denotes not only technical tools but also methods for integration of different scientific disciplines. In this report, we first discuss the background of ISA and the surveys made to map methods in different application fields, such as man machine system simulation software, human reliability analysis (HRA) and expert judgement. Specific event sequences were, after the surveys, selected for application and testing of a number of ISA methods. The event sequences discussed in the report were cold overpressure of BWR, shutdown LOCA of BWR, steam generator tube rupture of a PWR and BWR disturbed signal view in the control room after an external event. Different teams analysed these sequences by using different ISA and HRA methods. Two kinds of results were obtained from the ISA project: sequence specific and more general findings. The sequence specific results are discussed together with each sequence description. The general lessons are discussed under a separate chapter by using comparisons of different case studies. These lessons include areas ranging from plant safety management (design, procedures, instrumentation, operations, maintenance and safety practices) to methodological findings (ISA methodology, PSA,HRA, physical analyses, behavioural analyses and uncertainty assessment). Finally follows a discussion about the project and conclusions are presented. An interdisciplinary study of complex phenomena is a natural way to produce valuable and innovative results. This project came up with structured ways to perform ISA and managed to apply the in practice. The project also highlighted some areas where more work is needed. In the HRA work, development is required for the use of simulators and expert judgement as

Deep learning methods for protein torsion angle prediction.

Science.gov (United States)

Li, Haiou; Hou, Jie; Adhikari, Badri; Lyu, Qiang; Cheng, Jianlin

2017-09-18

Deep learning is one of the most powerful machine learning methods that has achieved the state-of-the-art performance in many domains. Since deep learning was introduced to the field of bioinformatics in 2012, it has achieved success in a number of areas such as protein residue-residue contact prediction, secondary structure prediction, and fold recognition. In this work, we developed deep learning methods to improve the prediction of torsion (dihedral) angles of proteins. We design four different deep learning architectures to predict protein torsion angles. The architectures including deep neural network (DNN) and deep restricted Boltzmann machine (DRBN), deep recurrent neural network (DRNN) and deep recurrent restricted Boltzmann machine (DReRBM) since the protein torsion angle prediction is a sequence related problem. In addition to existing protein features, two new features (predicted residue contact number and the error distribution of torsion angles extracted from sequence fragments) are used as input to each of the four deep learning architectures to predict phi and psi angles of protein backbone. The mean absolute error (MAE) of phi and psi angles predicted by DRNN, DReRBM, DRBM and DNN is about 20-21° and 29-30° on an independent dataset. The MAE of phi angle is comparable to the existing methods, but the MAE of psi angle is 29°, 2° lower than the existing methods. On the latest CASP12 targets, our methods also achieved the performance better than or comparable to a state-of-the art method. Our experiment demonstrates that deep learning is a valuable method for predicting protein torsion angles. The deep recurrent network architecture performs slightly better than deep feed-forward architecture, and the predicted residue contact number and the error distribution of torsion angles extracted from sequence fragments are useful features for improving prediction accuracy.

The complete mitochondrial genome of the deep-sea sponge Poecillastra laminaris (Astrophorida, Vulcanellidae).

Science.gov (United States)

Zeng, Cong; Thomas, Leighton J; Kelly, Michelle; Gardner, Jonathan P A

2016-05-01

The complete mitochondrial genome of a New Zealand specimen of the deep-sea sponge Poecillastra laminaris (Sollas, 1886) (Astrophorida, Vulcanellidae), from the Colville Ridge, New Zealand, was sequenced using the 454 Life Science pyrosequencing system. To identify homologous mitochondrial sequences, the 454 reads were mapped to the complete mitochondrial genome sequence of Geodia neptuni (GeneBank No. NC_006990). The P. laminaris genome is 18,413 bp in length and includes 14 protein-coding genes, 24 transfer RNA genes and 2 ribosomal RNA genes. Gene order resembled that of other demosponges. The base composition of the genome is A (29.1%), T (35.2%), C (14.0%) and G (21.7%). This is the second published mitogenome for a sponge of the order Astrophorida and will be useful in future phylogenetic analysis of deep-sea sponges.

Genome-wide analyses of long noncoding RNA expression profiles correlated with radioresistance in nasopharyngeal carcinoma via next-generation deep sequencing.

Science.gov (United States)

Li, Guo; Liu, Yong; Liu, Chao; Su, Zhongwu; Ren, Shuling; Wang, Yunyun; Deng, Tengbo; Huang, Donghai; Tian, Yongquan; Qiu, Yuanzheng

2016-09-06

Radioresistance is one of the major factors limiting the therapeutic efficacy and prognosis of patients with nasopharyngeal carcinoma (NPC). Accumulating evidence has suggested that aberrant expression of long noncoding RNAs (lncRNAs) contributes to cancer progression. Therefore, here we identified lncRNAs associated with radioresistance in NPC. The differential expression profiles of lncRNAs associated with NPC radioresistance were constructed by next-generation deep sequencing by comparing radioresistant NPC cells with their parental cells. LncRNA-related mRNAs were predicted and analyzed using bioinformatics algorithms compared with the mRNA profiles related to radioresistance obtained in our previous study. Several lncRNAs and associated mRNAs were validated in established NPC radioresistant cell models and NPC tissues. By comparison between radioresistant CNE-2-Rs and parental CNE-2 cells by next-generation deep sequencing, a total of 781 known lncRNAs and 2054 novel lncRNAs were annotated. The top five upregulated and downregulated known/novel lncRNAs were detected using quantitative real-time reverse transcription-polymerase chain reaction, and 7/10 known lncRNAs and 3/10 novel lncRNAs were demonstrated to have significant differential expression trends that were the same as those predicted by deep sequencing. From the prediction process, 13 pairs of lncRNAs and their associated genes were acquired, and the prediction trends of three pairs were validated in both radioresistant CNE-2-Rs and 6-10B-Rs cell lines, including lncRNA n373932 and SLITRK5, n409627 and PRSS12, and n386034 and RIMKLB. LncRNA n373932 and its related SLITRK5 showed dramatic expression changes in post-irradiation radioresistant cells and a negative expression correlation in NPC tissues (R = -0.595, p < 0.05). Our study provides an overview of the expression profiles of radioresistant lncRNAs and potentially related mRNAs, which will facilitate future investigations into the

Characterization of Liaoning cashmere goat transcriptome: sequencing, de novo assembly, functional annotation and comparative analysis.

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Hongliang Liu

Full Text Available Liaoning cashmere goat is a famous goat breed for cashmere wool. In order to increase the transcriptome data and accelerate genetic improvement for this breed, we performed de novo transcriptome sequencing to generate the first expressed sequence tag dataset for the Liaoning cashmere goat, using next-generation sequencing technology.Transcriptome sequencing of Liaoning cashmere goat on a Roche 454 platform yielded 804,601 high-quality reads. Clustering and assembly of these reads produced a non-redundant set of 117,854 unigenes, comprising 13,194 isotigs and 104,660 singletons. Based on similarity searches with known proteins, 17,356 unigenes were assigned to 6,700 GO categories, and the terms were summarized into three main GO categories and 59 sub-categories. 3,548 and 46,778 unigenes had significant similarity to existing sequences in the KEGG and COG databases, respectively. Comparative analysis revealed that 42,254 unigenes were aligned to 17,532 different sequences in NCBI non-redundant nucleotide databases. 97,236 (82.51% unigenes were mapped to the 30 goat chromosomes. 35,551 (30.17% unigenes were matched to 11,438 reported goat protein-coding genes. The remaining non-matched unigenes were further compared with cattle and human reference genes, 67 putative new goat genes were discovered. Additionally, 2,781 potential simple sequence repeats were initially identified from all unigenes.The transcriptome of Liaoning cashmere goat was deep sequenced, de novo assembled, and annotated, providing abundant data to better understand the Liaoning cashmere goat transcriptome. The potential simple sequence repeats provide a material basis for future genetic linkage and quantitative trait loci analyses.

Evolutionary process of deep-sea bathymodiolus mussels.

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Jun-Ichi Miyazaki

Full Text Available BACKGROUND: Since the discovery of deep-sea chemosynthesis-based communities, much work has been done to clarify their organismal and environmental aspects. However, major topics remain to be resolved, including when and how organisms invade and adapt to deep-sea environments; whether strategies for invasion and adaptation are shared by different taxa or unique to each taxon; how organisms extend their distribution and diversity; and how they become isolated to speciate in continuous waters. Deep-sea mussels are one of the dominant organisms in chemosynthesis-based communities, thus investigations of their origin and evolution contribute to resolving questions about life in those communities. METHODOLOGY/PRINCIPAL FINDING: We investigated worldwide phylogenetic relationships of deep-sea Bathymodiolus mussels and their mytilid relatives by analyzing nucleotide sequences of the mitochondrial cytochrome c oxidase subunit I (COI and NADH dehydrogenase subunit 4 (ND4 genes. Phylogenetic analysis of the concatenated sequence data showed that mussels of the subfamily Bathymodiolinae from vents and seeps were divided into four groups, and that mussels of the subfamily Modiolinae from sunken wood and whale carcasses assumed the outgroup position and shallow-water modioline mussels were positioned more distantly to the bathymodioline mussels. We provisionally hypothesized the evolutionary history of Bathymodilolus mussels by estimating evolutionary time under a relaxed molecular clock model. Diversification of bathymodioline mussels was initiated in the early Miocene, and subsequently diversification of the groups occurred in the early to middle Miocene. CONCLUSIONS/SIGNIFICANCE: The phylogenetic relationships support the "Evolutionary stepping stone hypothesis," in which mytilid ancestors exploited sunken wood and whale carcasses in their progressive adaptation to deep-sea environments. This hypothesis is also supported by the evolutionary transition of

Bioinformatics for whole-genome shotgun sequencing of microbial communities.

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Kevin Chen

2005-07-01

Full Text Available The application of whole-genome shotgun sequencing to microbial communities represents a major development in metagenomics, the study of uncultured microbes via the tools of modern genomic analysis. In the past year, whole-genome shotgun sequencing projects of prokaryotic communities from an acid mine biofilm, the Sargasso Sea, Minnesota farm soil, three deep-sea whale falls, and deep-sea sediments have been reported, adding to previously published work on viral communities from marine and fecal samples. The interpretation of this new kind of data poses a wide variety of exciting and difficult bioinformatics problems. The aim of this review is to introduce the bioinformatics community to this emerging field by surveying existing techniques and promising new approaches for several of the most interesting of these computational problems.

A survey on deep learning in medical image analysis.

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Litjens, Geert; Kooi, Thijs; Bejnordi, Babak Ehteshami; Setio, Arnaud Arindra Adiyoso; Ciompi, Francesco; Ghafoorian, Mohsen; van der Laak, Jeroen A W M; van Ginneken, Bram; Sánchez, Clara I

2017-12-01

Deep learning algorithms, in particular convolutional networks, have rapidly become a methodology of choice for analyzing medical images. This paper reviews the major deep learning concepts pertinent to medical image analysis and summarizes over 300 contributions to the field, most of which appeared in the last year. We survey the use of deep learning for image classification, object detection, segmentation, registration, and other tasks. Concise overviews are provided of studies per application area: neuro, retinal, pulmonary, digital pathology, breast, cardiac, abdominal, musculoskeletal. We end with a summary of the current state-of-the-art, a critical discussion of open challenges and directions for future research. Copyright © 2017 Elsevier B.V. All rights reserved.

Evolution of simeprevir-resistant variants over time by ultra-deep sequencing in HCV genotype 1b.

Science.gov (United States)

Akuta, Norio; Suzuki, Fumitaka; Sezaki, Hitomi; Suzuki, Yoshiyuki; Hosaka, Tetsuya; Kobayashi, Masahiro; Kobayashi, Mariko; Saitoh, Satoshi; Ikeda, Kenji; Kumada, Hiromitsu

2014-08-01

Using ultra-deep sequencing technology, the present study was designed to investigate the evolution of simeprevir-resistant variants (amino acid substitutions of aa80, aa155, aa156, and aa168 positions in HCV NS3 region) over time. In Toranomon Hospital, 18 Japanese patients infected with HCV genotype 1b, received triple therapy of simeprevir/PEG-IFN/ribavirin (DRAGON or CONCERT study). Sustained virological response rate was 67%, and that was significantly higher in patients with IL28B rs8099917 TT than in those with non-TT. Six patients, who did not achieve sustained virological response, were tested for resistant variants by ultra-deep sequencing, at the baseline, at the time of re-elevation of viral loads, and at 96 weeks after the completion of treatment. Twelve of 18 resistant variants, detected at re-elevation of viral load, were de novo resistant variants. Ten of 12 de novo resistant variants become undetectable over time, and that five of seven resistant variants, detected at baseline, persisted over time. In one patient, variants of Q80R at baseline (0.3%) increased at 96-week after the cessation of treatment (10.2%), and de novo resistant variants of D168E (0.3%) also increased at 96-week after the cessation of treatment (9.7%). In conclusion, the present study indicates that the emergence of simeprevir-resistant variants after the start of treatment could not be predicted at baseline, and the majority of de novo resistant variants become undetectable over time. Further large-scale prospective studies should be performed to investigate the clinical utility in detecting simeprevir-resistant variants. © 2014 Wiley Periodicals, Inc.

Direct, rapid RNA sequence analysis

International Nuclear Information System (INIS)

Peattie, D.A.

1987-01-01

The original methods of RNA sequence analysis were based on enzymatic production and chromatographic separation of overlapping oligonucleotide fragments from within an RNA molecule followed by identification of the mononucleotides comprising the oligomer. Over the past decade the field of nucleic acid sequencing has changed dramatically, however, and RNA molecules now can be sequenced in a variety of more streamlined fashions. Most of the more recent advances in RNA sequencing have involved one-dimensional electrophoretic separation of 32 P-end-labeled oligoribonucleotides on polyacrylamide gels. In this chapter the author discusses two of these methods for determining the nucleotide sequences of RNA molecules rapidly: the chemical method and the enzymatic method. Both methods are direct and degradative, i.e., they rely on fragmatic and chemical approaches should be utilized. The single-strand-specific ribonucleases (A, T 1 , T 2 , and S 1 ) provide an efficient means to locate double-helical regions rapidly, and the chemical reactions provide a means to determine the RNA sequence within these regions. In addition, the chemical reactions allow one to assign interactions to specific atoms and to distinguish secondary interactions from tertiary ones. If the RNA molecule is small enough to be sequenced directly by the enzymatic or chemical method, the probing reactions can be done easily at the same time as sequencing reactions

Image sequence analysis workstation for multipoint motion analysis

Science.gov (United States)

Mostafavi, Hassan

1990-08-01

This paper describes an application-specific engineering workstation designed and developed to analyze motion of objects from video sequences. The system combines the software and hardware environment of a modem graphic-oriented workstation with the digital image acquisition, processing and display techniques. In addition to automation and Increase In throughput of data reduction tasks, the objective of the system Is to provide less invasive methods of measurement by offering the ability to track objects that are more complex than reflective markers. Grey level Image processing and spatial/temporal adaptation of the processing parameters is used for location and tracking of more complex features of objects under uncontrolled lighting and background conditions. The applications of such an automated and noninvasive measurement tool include analysis of the trajectory and attitude of rigid bodies such as human limbs, robots, aircraft in flight, etc. The system's key features are: 1) Acquisition and storage of Image sequences by digitizing and storing real-time video; 2) computer-controlled movie loop playback, freeze frame display, and digital Image enhancement; 3) multiple leading edge tracking in addition to object centroids at up to 60 fields per second from both live input video or a stored Image sequence; 4) model-based estimation and tracking of the six degrees of freedom of a rigid body: 5) field-of-view and spatial calibration: 6) Image sequence and measurement data base management; and 7) offline analysis software for trajectory plotting and statistical analysis.

Evaluating the Factors that Facilitate a Deep Understanding of Data Analysis

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Oliver Burmeister

1995-11-01

Full Text Available Ideally the product of tertiary informatic study is more than a qualification, it is a rewarding experience of learning in a discipline area. It should build a desire for a deeper understanding and lead to fruitful research both personally and for the benefit of the wider community. This paper asks: 'What are the factors that lead to this type of quality (deep learning in data analysis?' In the study reported in this paper, students whose general approach to learning was achieving or surface oriented adopted a deep approach when the context encouraged it. An overseas study found a decline in deep learning at this stage of a tertiary program; the contention of this paper is that the opposite of this expected outcome was achieved due to the enhanced learning environment. Though only 15.1% of students involved in this study were deep learners, the data analysis instructional context resulted in 38.8% of students achieving deep learning outcomes. Other factors discovered that contributed to deep learning outcomes were an increase in the intrinsic motivation of students to study the domain area; their prior knowledge of informatics; assessment that sought an integrated, developed yet comprehensive understanding of analytical concepts and processes; and, their learning preferences. The preferences of deep learning students are analyzed in comparison to another such study of professionals in informatics, examining commonalties and differences between this and the wider professional study.

Deep Sequencing of Porphyromonas gingivalis and comparative transcriptome analysis of a LuxS mutant

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Takanoi eHirano

2012-06-01

Full Text Available Porphyromonas gingivalis is a major etiological agent and chronic and aggressive forms of periodontal disease. The organism is an assacharolytic anaerobe and is a constituent of mixed species biofilms in a variety of microenvironments in the oral cavity. P. gingivalis expresses a range of virulence factors over which it exerts tight control. High-throughput sequencing technologies provide the opportunity to relate functional genomics to basic biology. In this study we report qualitative and quantitative RNA-Seq analysis of the transcriptome of P. gingivalis. We have also applied RNA-Seq to the transcriptome of a ΔluxS mutant of P. gingivalis deficient in AI-2-mediated bacterial communication. The transcriptome analysis confirmed the expression of all predicted ORFs for strain ATCC 33277, including 854 hypothetical proteins, and allowed the identification of hitherto unknown transcriptional units. Twelve noncoding RNAs were identified, including 11 small RNAs and one cobalamine riboswitch. Fifty seven genes were differentially regulated in the LuxS mutant. Addition of exogenous synthetic 4,5-dihydroxy-2,3-pentanedione (DPD, AI-2 precursor to the ΔluxS mutant culture complemented expression of a subset of genes, indicating that LuxS is involved in both AI-2 signaling and non-signaling dependent systems in P. gingivalis. This work provides an important dataset for future study of P. gingivalis pathophysiology and further defines the LuxS regulon in this oral pathogen.

Deep sequencing of the Camellia sinensis transcriptome revealed candidate genes for major metabolic pathways of tea-specific compounds

Energy Technology Data Exchange (ETDEWEB)

Shi, CY; Yang, H; Wei, CL; Yu, O; Zhang, ZZ; Sun, J; Wan, XC

2011-01-01

Tea is one of the most popular non-alcoholic beverages worldwide. However, the tea plant, Camellia sinensis, is difficult to culture in vitro, to transform, and has a large genome, rendering little genomic information available. Recent advances in large-scale RNA sequencing (RNA-seq) provide a fast, cost-effective, and reliable approach to generate large expression datasets for functional genomic analysis, which is especially suitable for non-model species with un-sequenced genomes. Using high-throughput Illumina RNA-seq, the transcriptome from poly (A){sup +} RNA of C. sinensis was analyzed at an unprecedented depth (2.59 gigabase pairs). Approximate 34.5 million reads were obtained, trimmed, and assembled into 127,094 unigenes, with an average length of 355 bp and an N50 of 506 bp, which consisted of 788 contig clusters and 126,306 singletons. This number of unigenes was 10-fold higher than existing C. sinensis sequences deposited in GenBank (as of August 2010). Sequence similarity analyses against six public databases (Uniprot, NR and COGs at NCBI, Pfam, InterPro and KEGG) found 55,088 unigenes that could be annotated with gene descriptions, conserved protein domains, or gene ontology terms. Some of the unigenes were assigned to putative metabolic pathways. Targeted searches using these annotations identified the majority of genes associated with several primary metabolic pathways and natural product pathways that are important to tea quality, such as flavonoid, theanine and caffeine biosynthesis pathways. Novel candidate genes of these secondary pathways were discovered. Comparisons with four previously prepared cDNA libraries revealed that this transcriptome dataset has both a high degree of consistency with previous EST data and an approximate 20 times increase in coverage. Thirteen unigenes related to theanine and flavonoid synthesis were validated. Their expression patterns in different organs of the tea plant were analyzed by RT-PCR and quantitative real

Deep sequencing of the Camellia sinensis transcriptome revealed candidate genes for major metabolic pathways of tea-specific compounds

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Chen Qi

2011-02-01

Full Text Available Abstract Background Tea is one of the most popular non-alcoholic beverages worldwide. However, the tea plant, Camellia sinensis, is difficult to culture in vitro, to transform, and has a large genome, rendering little genomic information available. Recent advances in large-scale RNA sequencing (RNA-seq provide a fast, cost-effective, and reliable approach to generate large expression datasets for functional genomic analysis, which is especially suitable for non-model species with un-sequenced genomes. Results Using high-throughput Illumina RNA-seq, the transcriptome from poly (A+ RNA of C. sinensis was analyzed at an unprecedented depth (2.59 gigabase pairs. Approximate 34.5 million reads were obtained, trimmed, and assembled into 127,094 unigenes, with an average length of 355 bp and an N50 of 506 bp, which consisted of 788 contig clusters and 126,306 singletons. This number of unigenes was 10-fold higher than existing C. sinensis sequences deposited in GenBank (as of August 2010. Sequence similarity analyses against six public databases (Uniprot, NR and COGs at NCBI, Pfam, InterPro and KEGG found 55,088 unigenes that could be annotated with gene descriptions, conserved protein domains, or gene ontology terms. Some of the unigenes were assigned to putative metabolic pathways. Targeted searches using these annotations identified the majority of genes associated with several primary metabolic pathways and natural product pathways that are important to tea quality, such as flavonoid, theanine and caffeine biosynthesis pathways. Novel candidate genes of these secondary pathways were discovered. Comparisons with four previously prepared cDNA libraries revealed that this transcriptome dataset has both a high degree of consistency with previous EST data and an approximate 20 times increase in coverage. Thirteen unigenes related to theanine and flavonoid synthesis were validated. Their expression patterns in different organs of the tea plant were

Advancing Eucalyptus genomics: identification and sequencing of lignin biosynthesis genes from deep-coverage BAC libraries

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Kudrna David

2011-03-01

Full Text Available Abstract Background Eucalyptus species are among the most planted hardwoods in the world because of their rapid growth, adaptability and valuable wood properties. The development and integration of genomic resources into breeding practice will be increasingly important in the decades to come. Bacterial artificial chromosome (BAC libraries are key genomic tools that enable positional cloning of important traits, synteny evaluation, and the development of genome framework physical maps for genetic linkage and genome sequencing. Results We describe the construction and characterization of two deep-coverage BAC libraries EG_Ba and EG_Bb obtained from nuclear DNA fragments of E. grandis (clone BRASUZ1 digested with HindIII and BstYI, respectively. Genome coverages of 17 and 15 haploid genome equivalents were estimated for EG_Ba and EG_Bb, respectively. Both libraries contained large inserts, with average sizes ranging from 135 Kb (Eg_Bb to 157 Kb (Eg_Ba, very low extra-nuclear genome contamination providing a probability of finding a single copy gene ≥ 99.99%. Libraries were screened for the presence of several genes of interest via hybridizations to high-density BAC filters followed by PCR validation. Five selected BAC clones were sequenced and assembled using the Roche GS FLX technology providing the whole sequence of the E. grandis chloroplast genome, and complete genomic sequences of important lignin biosynthesis genes. Conclusions The two E. grandis BAC libraries described in this study represent an important milestone for the advancement of Eucalyptus genomics and forest tree research. These BAC resources have a highly redundant genome coverage (> 15×, contain large average inserts and have a very low percentage of clones with organellar DNA or empty vectors. These publicly available BAC libraries are thus suitable for a broad range of applications in genetic and genomic research in Eucalyptus and possibly in related species of Myrtaceae

Compositional Bias in Naïve and Chemically-modified Phage-Displayed Libraries uncovered by Paired-end Deep Sequencing.

Science.gov (United States)

He, Bifang; Tjhung, Katrina F; Bennett, Nicholas J; Chou, Ying; Rau, Andrea; Huang, Jian; Derda, Ratmir

2018-01-19

Understanding the composition of a genetically-encoded (GE) library is instrumental to the success of ligand discovery. In this manuscript, we investigate the bias in GE-libraries of linear, macrocyclic and chemically post-translationally modified (cPTM) tetrapeptides displayed on the M13KE platform, which are produced via trinucleotide cassette synthesis (19 codons) and NNK-randomized codon. Differential enrichment of synthetic DNA {S}, ligated vector {L} (extension and ligation of synthetic DNA into the vector), naïve libraries {N} (transformation of the ligated vector into the bacteria followed by expression of the library for 4.5 hours to yield a "naïve" library), and libraries chemically modified by aldehyde ligation and cysteine macrocyclization {M} characterized by paired-end deep sequencing, detected a significant drop in diversity in {L} → {N}, but only a minor compositional difference in {S} → {L} and {N} → {M}. Libraries expressed at the N-terminus of phage protein pIII censored positively charged amino acids Arg and Lys; libraries expressed between pIII domains N1 and N2 overcame Arg/Lys-censorship but introduced new bias towards Gly and Ser. Interrogation of biases arising from cPTM by aldehyde ligation and cysteine macrocyclization unveiled censorship of sequences with Ser/Phe. Analogous analysis can be used to explore library diversity in new display platforms and optimize cPTM of these libraries.

Markov chains and entropy tests in genetic-based lithofacies analysis of deep-water clastic depositional systems

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Borka Szabolcs

2016-01-01

Full Text Available The aim of this study was to examine the relationship between structural elements and the so-called genetic lithofacies in a clastic deep-water depositional system. Process-sedimentology has recently been gaining importance in the characterization of these systems. This way the recognized facies attributes can be associated with the depositional processes establishing the genetic lithofacies. In this paper this approach was presented through a case study of a Tertiary deep-water sequence of the Pannonian-basin.

Deep Learning Neural Networks and Bayesian Neural Networks in Data Analysis

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Chernoded Andrey

2017-01-01

Full Text Available Most of the modern analyses in high energy physics use signal-versus-background classification techniques of machine learning methods and neural networks in particular. Deep learning neural network is the most promising modern technique to separate signal and background and now days can be widely and successfully implemented as a part of physical analysis. In this article we compare Deep learning and Bayesian neural networks application as a classifiers in an instance of top quark analysis.

The 2007 Nazko, British Columbia, earthquake sequence: Injection of magma deep in the crust beneath the Anahim volcanic belt

Science.gov (United States)

Cassidy, J.F.; Balfour, N.; Hickson, C.; Kao, H.; White, Rickie; Caplan-Auerbach, J.; Mazzotti, S.; Rogers, Gary C.; Al-Khoubbi, I.; Bird, A.L.; Esteban, L.; Kelman, M.; Hutchinson, J.; McCormack, D.

2011-01-01

On 9 October 2007, an unusual sequence of earthquakes began in central British Columbia about 20 km west of the Nazko cone, the most recent (circa 7200 yr) volcanic center in the Anahim volcanic belt. Within 25 hr, eight earthquakes of magnitude 2.3-2.9 occurred in a region where no earthquakes had previously been recorded. During the next three weeks, more than 800 microearthquakes were located (and many more detected), most at a depth of 25-31 km and within a radius of about 5 km. After about two months, almost all activity ceased. The clear P- and S-wave arrivals indicated that these were high-frequency (volcanic-tectonic) earthquakes and the b value of 1.9 that we calculated is anomalous for crustal earthquakes but consistent with volcanic-related events. Analysis of receiver functions at a station immediately above the seismicity indicated a Moho near 30 km depth. Precise relocation of the seismicity using a double-difference method suggested a horizontal migration at the rate of about 0:5 km=d, with almost all events within the lowermost crust. Neither harmonic tremor nor long-period events were observed; however, some spasmodic bursts were recorded and determined to be colocated with the earthquake hypocenters. These observations are all very similar to a deep earthquake sequence recorded beneath Lake Tahoe, California, in 2003-2004. Based on these remarkable similarities, we interpret the Nazko sequence as an indication of an injection of magma into the lower crust beneath the Anahim volcanic belt. This magma injection fractures rock, producing high-frequency, volcanic-tectonic earthquakes and spasmodic bursts.

Preliminary hazard analysis using sequence tree method

International Nuclear Information System (INIS)

Huang Huiwen; Shih Chunkuan; Hung Hungchih; Chen Minghuei; Yih Swu; Lin Jiinming

2007-01-01

A system level PHA using sequence tree method was developed to perform Safety Related digital I and C system SSA. The conventional PHA is a brainstorming session among experts on various portions of the system to identify hazards through discussions. However, this conventional PHA is not a systematic technique, the analysis results strongly depend on the experts' subjective opinions. The analysis quality cannot be appropriately controlled. Thereby, this research developed a system level sequence tree based PHA, which can clarify the relationship among the major digital I and C systems. Two major phases are included in this sequence tree based technique. The first phase uses a table to analyze each event in SAR Chapter 15 for a specific safety related I and C system, such as RPS. The second phase uses sequence tree to recognize what I and C systems are involved in the event, how the safety related systems work, and how the backup systems can be activated to mitigate the consequence if the primary safety systems fail. In the sequence tree, the defense-in-depth echelons, including Control echelon, Reactor trip echelon, ESFAS echelon, and Indication and display echelon, are arranged to construct the sequence tree structure. All the related I and C systems, include digital system and the analog back-up systems are allocated in their specific echelon. By this system centric sequence tree based analysis, not only preliminary hazard can be identified systematically, the vulnerability of the nuclear power plant can also be recognized. Therefore, an effective simplified D3 evaluation can be performed as well. (author)

Bacterial diversity and biogeography in deep-sea sediments of the South Atlantic Ocean

DEFF Research Database (Denmark)

Schauer, Regina; Bienhold, Christina; Ramette, Alban

2010-01-01

in 1051 sequences. Phylotypes affiliated with Gammaproteobacteria, Deltaproteobacteria and Acidobacteria were present in all three basins. The distribution of these shared phylotypes seemed to be influenced neither by the Walvis Ridge nor by different deep water masses, suggesting a high dispersal......Microbial biogeographic patterns in the deep sea depend on the ability of microorganisms to disperse. One possible limitation to microbial dispersal may be the Walvis Ridge that separates the Antarctic Lower Circumpolar Deep Water from the North Atlantic Deep Water. We examined bacterial...... communities in three basins of the eastern South Atlantic Ocean to determine diversity and biogeography of bacterial communities in deep-sea surface sediments. The analysis of 16S ribosomal RNA (rRNA) gene clone libraries in each basin revealed a high diversity, representing 521 phylotypes with 98% identity...

DeepPVP: phenotype-based prioritization of causative variants using deep learning

KAUST Repository

Boudellioua, Imene

2018-05-02

Background: Prioritization of variants in personal genomic data is a major challenge. Recently, computational methods that rely on comparing phenotype similarity have shown to be useful to identify causative variants. In these methods, pathogenicity prediction is combined with a semantic similarity measure to prioritize not only variants that are likely to be dysfunctional but those that are likely involved in the pathogenesis of a patient\\'s phenotype. Results: We have developed DeepPVP, a variant prioritization method that combined automated inference with deep neural networks to identify the likely causative variants in whole exome or whole genome sequence data. We demonstrate that DeepPVP performs significantly better than existing methods, including phenotype-based methods that use similar features. DeepPVP is freely available at https://github.com/bio-ontology-research-group/phenomenet-vp Conclusions: DeepPVP further improves on existing variant prioritization methods both in terms of speed as well as accuracy.

Deep Illumina-based shotgun sequencing reveals dietary effects on the structure and function of the fecal microbiome of growing kittens.

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Oliver Deusch

Full Text Available Previously, we demonstrated that dietary protein:carbohydrate ratio dramatically affects the fecal microbial taxonomic structure of kittens using targeted 16S gene sequencing. The present study, using the same fecal samples, applied deep Illumina shotgun sequencing to identify the diet-associated functional potential and analyze taxonomic changes of the feline fecal microbiome.Fecal samples from kittens fed one of two diets differing in protein and carbohydrate content (high-protein, low-carbohydrate, HPLC; and moderate-protein, moderate-carbohydrate, MPMC were collected at 8, 12 and 16 weeks of age (n = 6 per group. A total of 345.3 gigabases of sequence were generated from 36 samples, with 99.75% of annotated sequences identified as bacterial. At the genus level, 26% and 39% of reads were annotated for HPLC- and MPMC-fed kittens, with HPLC-fed cats showing greater species richness and microbial diversity. Two phyla, ten families and fifteen genera were responsible for more than 80% of the sequences at each taxonomic level for both diet groups, consistent with the previous taxonomic study. Significantly different abundances between diet groups were observed for 324 genera (56% of all genera identified demonstrating widespread diet-induced changes in microbial taxonomic structure. Diversity was not affected over time. Functional analysis identified 2,013 putative enzyme function groups were different (p<0.000007 between the two dietary groups and were associated to 194 pathways, which formed five discrete clusters based on average relative abundance. Of those, ten contained more (p<0.022 enzyme functions with significant diet effects than expected by chance. Six pathways were related to amino acid biosynthesis and metabolism linking changes in dietary protein with functional differences of the gut microbiome.These data indicate that feline feces-derived microbiomes have large structural and functional differences relating to the dietary

Personalized mapping of the deep brain with a white matter attenuated inversion recovery (WAIR) sequence at 1.5-tesla: Experience based on a series of 156 patients.

Science.gov (United States)

Zerroug, A; Gabrillargues, J; Coll, G; Vassal, F; Jean, B; Chabert, E; Claise, B; Khalil, T; Sakka, L; Feschet, F; Durif, F; Boyer, L; Coste, J; Lemaire, J-J

2016-08-01

Deep brain mapping has been proposed for direct targeting in stereotactic functional surgery, aiming to personalize electrode implantation according to individual MRI anatomy without atlas or statistical template. We report our clinical experience of direct targeting in a series of 156 patients operated on using a dedicated Inversion Recovery Turbo Spin Echo sequence at 1.5-tesla, called White Matter Attenuated Inversion Recovery (WAIR). After manual contouring of all pertinent structures and 3D planning of trajectories, 312 DBS electrodes were implanted. Detailed anatomy of close neighbouring structures, whether gray nuclei or white matter regions, was identified during each planning procedure. We gathered the experience of these 312 deep brain mappings and elaborated consistent procedures of anatomical MRI mapping for pallidal, subthalamic and ventral thalamic regions. We studied the number of times the central track anatomically optimized was selected for implantation of definitive electrodes. WAIR sequence provided high-quality images of most common functional targets, successfully used for pure direct stereotactic targeting: the central track corresponding to the optimized primary anatomical trajectory was chosen for implantation of definitive electrodes in 90.38%. WAIR sequence is anatomically reliable, enabling precise deep brain mapping and direct stereotactic targeting under routine clinical conditions. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Deep sequencing analysis of HIV-1 reverse transcriptase at baseline and time of failure in patients receiving rilpivirine in the phase III studies ECHO and THRIVE.

Science.gov (United States)

Van Eygen, Veerle; Thys, Kim; Van Hove, Carl; Rimsky, Laurence T; De Meyer, Sandra; Aerssens, Jeroen; Picchio, Gaston; Vingerhoets, Johan

2016-05-01

Minority variants (1.0-25.0%) were evaluated by deep sequencing (DS) at baseline and virological failure (VF) in a selection of antiretroviral treatment-naïve, HIV-1-infected patients from the rilpivirine ECHO/THRIVE phase III studies. Linkage between frequently emerging resistance-associated mutations (RAMs) was determined. DS (llIumina®) and population sequencing (PS) results were available at baseline for 47 VFs and time of failure for 48 VFs; and at baseline for 49 responders matched for baseline characteristics. Minority mutations were accurately detected at frequencies down to 1.2% of the HIV-1 quasispecies. No baseline minority rilpivirine RAMs were detected in VFs; one responder carried 1.9% F227C. Baseline minority mutations associated with resistance to other non-nucleoside reverse transcriptase inhibitors (NNRTIs) were detected in 8/47 VFs (17.0%) and 7/49 responders (14.3%). Baseline minority nucleoside/nucleotide reverse transcriptase inhibitor (NRTI) RAMs M184V and L210W were each detected in one VF (none in responders). At failure, two patients without NNRTI RAMs by PS carried minority rilpivirine RAMs K101E and/or E138K; and five additional patients carried other minority NNRTI RAMs V90I, V106I, V179I, V189I, and Y188H. Overall at failure, minority NNRTI RAMs and NRTI RAMs were found in 29/48 (60.4%) and 16/48 VFs (33.3%), respectively. Linkage analysis showed that E138K and K101E were usually not observed on the same viral genome. In conclusion, baseline minority rilpivirine RAMs and other NNRTI/NRTI RAMs were uncommon in the rilpivirine arm of the ECHO and THRIVE studies. DS at failure showed emerging NNRTI resistant minority variants in seven rilpivirine VFs who had no detectable NNRTI RAMs by PS. © 2015 Wiley Periodicals, Inc.

Deep Recurrent Neural Networks for Human Activity Recognition

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Abdulmajid Murad

2017-11-01

Full Text Available Adopting deep learning methods for human activity recognition has been effective in extracting discriminative features from raw input sequences acquired from body-worn sensors. Although human movements are encoded in a sequence of successive samples in time, typical machine learning methods perform recognition tasks without exploiting the temporal correlations between input data samples. Convolutional neural networks (CNNs address this issue by using convolutions across a one-dimensional temporal sequence to capture dependencies among input data. However, the size of convolutional kernels restricts the captured range of dependencies between data samples. As a result, typical models are unadaptable to a wide range of activity-recognition configurations and require fixed-length input windows. In this paper, we propose the use of deep recurrent neural networks (DRNNs for building recognition models that are capable of capturing long-range dependencies in variable-length input sequences. We present unidirectional, bidirectional, and cascaded architectures based on long short-term memory (LSTM DRNNs and evaluate their effectiveness on miscellaneous benchmark datasets. Experimental results show that our proposed models outperform methods employing conventional machine learning, such as support vector machine (SVM and k-nearest neighbors (KNN. Additionally, the proposed models yield better performance than other deep learning techniques, such as deep believe networks (DBNs and CNNs.

Deep Recurrent Neural Networks for Human Activity Recognition.

Science.gov (United States)

Murad, Abdulmajid; Pyun, Jae-Young

2017-11-06

Adopting deep learning methods for human activity recognition has been effective in extracting discriminative features from raw input sequences acquired from body-worn sensors. Although human movements are encoded in a sequence of successive samples in time, typical machine learning methods perform recognition tasks without exploiting the temporal correlations between input data samples. Convolutional neural networks (CNNs) address this issue by using convolutions across a one-dimensional temporal sequence to capture dependencies among input data. However, the size of convolutional kernels restricts the captured range of dependencies between data samples. As a result, typical models are unadaptable to a wide range of activity-recognition configurations and require fixed-length input windows. In this paper, we propose the use of deep recurrent neural networks (DRNNs) for building recognition models that are capable of capturing long-range dependencies in variable-length input sequences. We present unidirectional, bidirectional, and cascaded architectures based on long short-term memory (LSTM) DRNNs and evaluate their effectiveness on miscellaneous benchmark datasets. Experimental results show that our proposed models outperform methods employing conventional machine learning, such as support vector machine (SVM) and k-nearest neighbors (KNN). Additionally, the proposed models yield better performance than other deep learning techniques, such as deep believe networks (DBNs) and CNNs.

AMID: Accurate Magnetic Indoor Localization Using Deep Learning

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Namkyoung Lee

2018-05-01

Full Text Available Geomagnetic-based indoor positioning has drawn a great attention from academia and industry due to its advantage of being operable without infrastructure support and its reliable signal characteristics. However, it must overcome the problems of ambiguity that originate with the nature of geomagnetic data. Most studies manage this problem by incorporating particle filters along with inertial sensors. However, they cannot yield reliable positioning results because the inertial sensors in smartphones cannot precisely predict the movement of users. There have been attempts to recognize the magnetic sequence pattern, but these attempts are proven only in a one-dimensional space, because magnetic intensity fluctuates severely with even a slight change of locations. This paper proposes accurate magnetic indoor localization using deep learning (AMID, an indoor positioning system that recognizes magnetic sequence patterns using a deep neural network. Features are extracted from magnetic sequences, and then the deep neural network is used for classifying the sequences by patterns that are generated by nearby magnetic landmarks. Locations are estimated by detecting the landmarks. AMID manifested the proposed features and deep learning as an outstanding classifier, revealing the potential of accurate magnetic positioning with smartphone sensors alone. The landmark detection accuracy was over 80% in a two-dimensional environment.

Sequence analysis by iterated maps, a review.

Science.gov (United States)

Almeida, Jonas S

2014-05-01

Among alignment-free methods, Iterated Maps (IMs) are on a particular extreme: they are also scale free (order free). The use of IMs for sequence analysis is also distinct from other alignment-free methodologies in being rooted in statistical mechanics instead of computational linguistics. Both of these roots go back over two decades to the use of fractal geometry in the characterization of phase-space representations. The time series analysis origin of the field is betrayed by the title of the manuscript that started this alignment-free subdomain in 1990, 'Chaos Game Representation'. The clash between the analysis of sequences as continuous series and the better established use of Markovian approaches to discrete series was almost immediate, with a defining critique published in same journal 2 years later. The rest of that decade would go by before the scale-free nature of the IM space was uncovered. The ensuing decade saw this scalability generalized for non-genomic alphabets as well as an interest in its use for graphic representation of biological sequences. Finally, in the past couple of years, in step with the emergence of BigData and MapReduce as a new computational paradigm, there is a surprising third act in the IM story. Multiple reports have described gains in computational efficiency of multiple orders of magnitude over more conventional sequence analysis methodologies. The stage appears to be now set for a recasting of IMs with a central role in processing nextgen sequencing results.

Protein Secondary Structure Prediction Using Deep Convolutional Neural Fields.

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Wang, Sheng; Peng, Jian; Ma, Jianzhu; Xu, Jinbo

2016-01-11

Protein secondary structure (SS) prediction is important for studying protein structure and function. When only the sequence (profile) information is used as input feature, currently the best predictors can obtain ~80% Q3 accuracy, which has not been improved in the past decade. Here we present DeepCNF (Deep Convolutional Neural Fields) for protein SS prediction. DeepCNF is a Deep Learning extension of Conditional Neural Fields (CNF), which is an integration of Conditional Random Fields (CRF) and shallow neural networks. DeepCNF can model not only complex sequence-structure relationship by a deep hierarchical architecture, but also interdependency between adjacent SS labels, so it is much more powerful than CNF. Experimental results show that DeepCNF can obtain ~84% Q3 accuracy, ~85% SOV score, and ~72% Q8 accuracy, respectively, on the CASP and CAMEO test proteins, greatly outperforming currently popular predictors. As a general framework, DeepCNF can be used to predict other protein structure properties such as contact number, disorder regions, and solvent accessibility.

Laser Capture and Deep Sequencing Reveals the Transcriptomic Programmes Regulating the Onset of Pancreas and Liver Differentiation in Human Embryos

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Rachel E. Jennings

2017-11-01

Full Text Available To interrogate the alternative fates of pancreas and liver in the earliest stages of human organogenesis, we developed laser capture, RNA amplification, and computational analysis of deep sequencing. Pancreas-enriched gene expression was less conserved between human and mouse than for liver. The dorsal pancreatic bud was enriched for components of Notch, Wnt, BMP, and FGF signaling, almost all genes known to cause pancreatic agenesis or hypoplasia, and over 30 unexplored transcription factors. SOX9 and RORA were imputed as key regulators in pancreas compared with EP300, HNF4A, and FOXA family members in liver. Analyses implied that current in vitro human stem cell differentiation follows a dorsal rather than a ventral pancreatic program and pointed to additional factors for hepatic differentiation. In summary, we provide the transcriptional codes regulating the start of human liver and pancreas development to facilitate stem cell research and clinical interpretation without inter-species extrapolation.

Statistical-Mechanical Analysis of Pre-training and Fine Tuning in Deep Learning

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Ohzeki, Masayuki

2015-03-01

In this paper, we present a statistical-mechanical analysis of deep learning. We elucidate some of the essential components of deep learning — pre-training by unsupervised learning and fine tuning by supervised learning. We formulate the extraction of features from the training data as a margin criterion in a high-dimensional feature-vector space. The self-organized classifier is then supplied with small amounts of labelled data, as in deep learning. Although we employ a simple single-layer perceptron model, rather than directly analyzing a multi-layer neural network, we find a nontrivial phase transition that is dependent on the number of unlabelled data in the generalization error of the resultant classifier. In this sense, we evaluate the efficacy of the unsupervised learning component of deep learning. The analysis is performed by the replica method, which is a sophisticated tool in statistical mechanics. We validate our result in the manner of deep learning, using a simple iterative algorithm to learn the weight vector on the basis of belief propagation.

Unveiling the Biodiversity of Deep-Sea Nematodes through Metabarcoding: Are We Ready to Bypass the Classical Taxonomy?

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Dell'Anno, Antonio; Carugati, Laura; Corinaldesi, Cinzia; Riccioni, Giulia; Danovaro, Roberto

2015-01-01

Nematodes inhabiting benthic deep-sea ecosystems account for >90% of the total metazoan abundances and they have been hypothesised to be hyper-diverse, but their biodiversity is still largely unknown. Metabarcoding could facilitate the census of biodiversity, especially for those tiny metazoans for which morphological identification is difficult. We compared, for the first time, different DNA extraction procedures based on the use of two commercial kits and a previously published laboratory protocol and tested their suitability for sequencing analyses of 18S rDNA of marine nematodes. We also investigated the reliability of Roche 454 sequencing analyses for assessing the biodiversity of deep-sea nematode assemblages previously morphologically identified. Finally, intra-genomic variation in 18S rRNA gene repeats was investigated by Illumina MiSeq in different deep-sea nematode morphospecies to assess the influence of polymorphisms on nematode biodiversity estimates. Our results indicate that the two commercial kits should be preferred for the molecular analysis of biodiversity of deep-sea nematodes since they consistently provide amplifiable DNA suitable for sequencing. We report that the morphological identification of deep-sea nematodes matches the results obtained by metabarcoding analysis only at the order-family level and that a large portion of Operational Clustered Taxonomic Units (OCTUs) was not assigned. We also show that independently from the cut-off criteria and bioinformatic pipelines used, the number of OCTUs largely exceeds the number of individuals and that 18S rRNA gene of different morpho-species of nematodes displayed intra-genomic polymorphisms. Our results indicate that metabarcoding is an important tool to explore the diversity of deep-sea nematodes, but still fails in identifying most of the species due to limited number of sequences deposited in the public databases, and in providing quantitative data on the species encountered. These aspects

Establishing a framework for comparative analysis of genome sequences

Energy Technology Data Exchange (ETDEWEB)

Bansal, A.K.

1995-06-01

This paper describes a framework and a high-level language toolkit for comparative analysis of genome sequence alignment The framework integrates the information derived from multiple sequence alignment and phylogenetic tree (hypothetical tree of evolution) to derive new properties about sequences. Multiple sequence alignments are treated as an abstract data type. Abstract operations have been described to manipulate a multiple sequence alignment and to derive mutation related information from a phylogenetic tree by superimposing parsimonious analysis. The framework has been applied on protein alignments to derive constrained columns (in a multiple sequence alignment) that exhibit evolutionary pressure to preserve a common property in a column despite mutation. A Prolog toolkit based on the framework has been implemented and demonstrated on alignments containing 3000 sequences and 3904 columns.

Rhodopsin in the Dark Hot Sea: Molecular Analysis of Rhodopsin in a Snailfish, Careproctus rhodomelas, Living near the Deep-Sea Hydrothermal Vent.

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Rie Sakata

Full Text Available Visual systems in deep-sea fishes have been previously studied from a photobiological aspect; however, those of deep-sea fish inhabiting the hydrothermal vents are far less understood due to sampling difficulties. In this study, we analyzed the visual pigment of a deep-sea snailfish, Careproctus rhodomelas, discovered and collected only near the hydrothermal vents of oceans around Japan. Proteins were solubilized from the C. rhodomelas eyeball and subjected to spectroscopic analysis, which revealed the presence of a pigment characterized by an absorption maximum (λmax at 480 nm. Immunoblot analysis of the ocular protein showed a rhodopsin-like immunoreactivity. We also isolated a retinal cDNA encoding the entire coding sequence of putative C. rhodomelas rhodopsin (CrRh. HEK293EBNA cells were transfected with the CrRh cDNA and the proteins extracted from the cells were subjected to spectroscopic analysis. The recombinant CrRh showed the absorption maximum at 480 nm in the presence of 11-cis retinal. Comparison of the results from the eyeball extract and the recombinant CrRh strongly suggests that CrRh has an A1-based 11-cis-retinal chromophore and works as a photoreceptor in the C. rhodomelas retina, and hence that C. rhodomelas responds to dim blue light much the same as other deep-sea fishes. Because hydrothermal vent is a huge supply of viable food, C. rhodomelas likely do not need to participate diel vertical migration and may recognize the bioluminescence produced by aquatic animals living near the hydrothermal vents.

Integrated Risk-Capability Analysis under Deep Uncertainty : An ESDMA Approach

NARCIS (Netherlands)

Pruyt, E.; Kwakkel, J.H.

2012-01-01

Integrated risk-capability analysis methodologies for dealing with increasing degrees of complexity and deep uncertainty are urgently needed in an ever more complex and uncertain world. Although scenario approaches, risk assessment methods, and capability analysis methods are used, few organizations

Designing small universal k-mer hitting sets for improved analysis of high-throughput sequencing.

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Yaron Orenstein

2017-10-01

Full Text Available With the rapidly increasing volume of deep sequencing data, more efficient algorithms and data structures are needed. Minimizers are a central recent paradigm that has improved various sequence analysis tasks, including hashing for faster read overlap detection, sparse suffix arrays for creating smaller indexes, and Bloom filters for speeding up sequence search. Here, we propose an alternative paradigm that can lead to substantial further improvement in these and other tasks. For integers k and L > k, we say that a set of k-mers is a universal hitting set (UHS if every possible L-long sequence must contain a k-mer from the set. We develop a heuristic called DOCKS to find a compact UHS, which works in two phases: The first phase is solved optimally, and for the second we propose several efficient heuristics, trading set size for speed and memory. The use of heuristics is motivated by showing the NP-hardness of a closely related problem. We show that DOCKS works well in practice and produces UHSs that are very close to a theoretical lower bound. We present results for various values of k and L and by applying them to real genomes show that UHSs indeed improve over minimizers. In particular, DOCKS uses less than 30% of the 10-mers needed to span the human genome compared to minimizers. The software and computed UHSs are freely available at github.com/Shamir-Lab/DOCKS/ and acgt.cs.tau.ac.il/docks/, respectively.

Statistical Analysis of Deep Drilling Process Conditions Using Vibrations and Force Signals

Directory of Open Access Journals (Sweden)

Syafiq Hazwan

2016-01-01

Full Text Available Cooling systems is a key point for hot forming process of Ultra High Strength Steels (UHSS. Normally, cooling systems is made using deep drilling technique. Although deep twist drill is better than other drilling techniques in term of higher productivity however its main problem is premature tool breakage, which affects the production quality. In this paper, analysis of deep twist drill process parameters such as cutting speed, feed rate and depth of cut by using statistical analysis to identify the tool condition is presented. The comparisons between different two tool geometries are also studied. Measured data from vibrations and force sensors are being analyzed through several statistical parameters such as root mean square (RMS, mean, kurtosis, standard deviation and skewness. Result found that kurtosis and skewness value are the most appropriate parameters to represent the deep twist drill tool conditions behaviors from vibrations and forces data. The condition of the deep twist drill process been classified according to good, blunt and fracture. It also found that the different tool geometry parameters affect the performance of the tool drill. It believe the results of this study are useful in determining the suitable analysis method to be used for developing online tool condition monitoring system to identify the tertiary tool life stage and helps to avoid mature of tool fracture during drilling process.

SHARAKU: an algorithm for aligning and clustering read mapping profiles of deep sequencing in non-coding RNA processing.

Science.gov (United States)

Tsuchiya, Mariko; Amano, Kojiro; Abe, Masaya; Seki, Misato; Hase, Sumitaka; Sato, Kengo; Sakakibara, Yasubumi

2016-06-15

Deep sequencing of the transcripts of regulatory non-coding RNA generates footprints of post-transcriptional processes. After obtaining sequence reads, the short reads are mapped to a reference genome, and specific mapping patterns can be detected called read mapping profiles, which are distinct from random non-functional degradation patterns. These patterns reflect the maturation processes that lead to the production of shorter RNA sequences. Recent next-generation sequencing studies have revealed not only the typical maturation process of miRNAs but also the various processing mechanisms of small RNAs derived from tRNAs and snoRNAs. We developed an algorithm termed SHARAKU to align two read mapping profiles of next-generation sequencing outputs for non-coding RNAs. In contrast with previous work, SHARAKU incorporates the primary and secondary sequence structures into an alignment of read mapping profiles to allow for the detection of common processing patterns. Using a benchmark simulated dataset, SHARAKU exhibited superior performance to previous methods for correctly clustering the read mapping profiles with respect to 5'-end processing and 3'-end processing from degradation patterns and in detecting similar processing patterns in deriving the shorter RNAs. Further, using experimental data of small RNA sequencing for the common marmoset brain, SHARAKU succeeded in identifying the significant clusters of read mapping profiles for similar processing patterns of small derived RNA families expressed in the brain. The source code of our program SHARAKU is available at http://www.dna.bio.keio.ac.jp/sharaku/, and the simulated dataset used in this work is available at the same link. Accession code: The sequence data from the whole RNA transcripts in the hippocampus of the left brain used in this work is available from the DNA DataBank of Japan (DDBJ) Sequence Read Archive (DRA) under the accession number DRA004502. yasu@bio.keio.ac.jp Supplementary data are available

mESAdb: microRNA expression and sequence analysis database.

Science.gov (United States)

Kaya, Koray D; Karakülah, Gökhan; Yakicier, Cengiz M; Acar, Aybar C; Konu, Ozlen

2011-01-01

microRNA expression and sequence analysis database (http://konulab.fen.bilkent.edu.tr/mirna/) (mESAdb) is a regularly updated database for the multivariate analysis of sequences and expression of microRNAs from multiple taxa. mESAdb is modular and has a user interface implemented in PHP and JavaScript and coupled with statistical analysis and visualization packages written for the R language. The database primarily comprises mature microRNA sequences and their target data, along with selected human, mouse and zebrafish expression data sets. mESAdb analysis modules allow (i) mining of microRNA expression data sets for subsets of microRNAs selected manually or by motif; (ii) pair-wise multivariate analysis of expression data sets within and between taxa; and (iii) association of microRNA subsets with annotation databases, HUGE Navigator, KEGG and GO. The use of existing and customized R packages facilitates future addition of data sets and analysis tools. Furthermore, the ability to upload and analyze user-specified data sets makes mESAdb an interactive and expandable analysis tool for microRNA sequence and expression data.

Discrepancy between Hepatitis C Virus Genotypes and NS4-Based Serotypes: Association with Their Subgenomic Sequences

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Nan Nwe Win

2017-01-01

Full Text Available Determination of hepatitis C virus (HCV genotypes plays an important role in the direct-acting agent era. Discrepancies between HCV genotyping and serotyping assays are occasionally observed. Eighteen samples with discrepant results between genotyping and serotyping methods were analyzed. HCV serotyping and genotyping were based on the HCV nonstructural 4 (NS4 region and 5′-untranslated region (5′-UTR, respectively. HCV core and NS4 regions were chosen to be sequenced and were compared with the genotyping and serotyping results. Deep sequencing was also performed for the corresponding HCV NS4 regions. Seventeen out of 18 discrepant samples could be sequenced by the Sanger method. Both HCV core and NS4 sequences were concordant with that of genotyping in the 5′-UTR in all 17 samples. In cloning analysis of the HCV NS4 region, there were several amino acid variations, but each sequence was much closer to the peptide with the same genotype. Deep sequencing revealed that minor clones with different subgenotypes existed in two of the 17 samples. Genotyping by genome amplification showed high consistency, while several false reactions were detected by serotyping. The deep sequencing method also provides accurate genotyping results and may be useful for analyzing discrepant cases. HCV genotyping should be correctly determined before antiviral treatment.

Key roles for freshwater Actinobacteria revealed by deep metagenomic sequencing.

Science.gov (United States)

Ghai, Rohit; Mizuno, Carolina Megumi; Picazo, Antonio; Camacho, Antonio; Rodriguez-Valera, Francisco

2014-12-01

Freshwater ecosystems are critical but fragile environments directly affecting society and its welfare. However, our understanding of genuinely freshwater microbial communities, constrained by our capacity to manipulate its prokaryotic participants in axenic cultures, remains very rudimentary. Even the most abundant components, freshwater Actinobacteria, remain largely unknown. Here, applying deep metagenomic sequencing to the microbial community of a freshwater reservoir, we were able to circumvent this traditional bottleneck and reconstruct de novo seven distinct streamlined actinobacterial genomes. These genomes represent three new groups of photoheterotrophic, planktonic Actinobacteria. We describe for the first time genomes of two novel clades, acMicro (Micrococcineae, related to Luna2,) and acAMD (Actinomycetales, related to acTH1). Besides, an aggregate of contigs belonged to a new branch of the Acidimicrobiales. All are estimated to have small genomes (approximately 1.2 Mb), and their GC content varied from 40 to 61%. One of the Micrococcineae genomes encodes a proteorhodopsin, a rhodopsin type reported for the first time in Actinobacteria. The remarkable potential capacity of some of these genomes to transform recalcitrant plant detrital material, particularly lignin-derived compounds, suggests close linkages between the terrestrial and aquatic realms. Moreover, abundances of Actinobacteria correlate inversely to those of Cyanobacteria that are responsible for prolonged and frequently irretrievable damage to freshwater ecosystems. This suggests that they might serve as sentinels of impending ecological catastrophes. © 2014 John Wiley & Sons Ltd.

Deep sequencing reveals a novel closterovirus associated with wild rose leaf rosette disease.

Science.gov (United States)

He, Yan; Yang, Zuokun; Hong, Ni; Wang, Guoping; Ning, Guogui; Xu, Wenxing

2015-06-01

A bizarre virus-like symptom of a leaf rosette formed by dense small leaves on branches of wild roses (Rosa multiflora Thunb.), designated as 'wild rose leaf rosette disease' (WRLRD), was observed in China. To investigate the presumed causal virus, a wild rose sample affected by WRLRD was subjected to deep sequencing of small interfering RNAs (siRNAs) for a complete survey of the infecting viruses and viroids. The assembly of siRNAs led to the reconstruction of the complete genomes of three known viruses, namely Apple stem grooving virus (ASGV), Blackberry chlorotic ringspot virus (BCRV) and Prunus necrotic ringspot virus (PNRSV), and of a novel virus provisionally named 'rose leaf rosette-associated virus' (RLRaV). Phylogenetic analysis clearly placed RLRaV alongside members of the genus Closterovirus, family Closteroviridae. Genome organization of RLRaV RNA (17,653 nucleotides) showed 13 open reading frames (ORFs), except ORF1 and the quintuple gene block, most of which showed no significant similarities with known viral proteins, but, instead, had detectable identities to fungal or bacterial proteins. Additional novel molecular features indicated that RLRaV seems to be the most complex virus among the known genus members. To our knowledge, this is the first report of WRLRD and its associated closterovirus, as well as two ilarviruses and one capilovirus, infecting wild roses. Our findings present novel information about the closterovirus and the aetiology of this rose disease which should facilitate its control. More importantly, the novel features of RLRaV help to clarify the molecular and evolutionary features of the closterovirus. © 2014 BSPP AND JOHN WILEY & SONS LTD.

Molecular diet analysis of two African free-tailed bats (Molossidae) using high throughput sequencing

DEFF Research Database (Denmark)

Bohmann, Kristine; Monadjem, Ara; Noer, Christina Lehmkuhl

2011-01-01

Given the diversity of prey consumed by insectivorous bats, it is difficult to discern the composition of their diet using morphological or conventional PCR-based analyses of their faeces. We demonstrate the use of a powerful alternate tool, the use of the Roche FLX sequencing platform to deep......-sequence uniquely 5′ tagged insect-generic barcode cytochrome c oxidase I (COI) fragments, that were PCR amplified from faecal pellets of two free-tailed bat species Chaerephon pumilus and Mops condylurus (family: Molossidae). Although the analyses were challenged by the paucity of southern African insect COI...

Numerical Analysis on Seepage in the deep overburden CFRD

Science.gov (United States)

Zeyu, GUO; Junrui, CHAI; Yuan, QIN

2017-12-01

There are many problems in the construction of hydraulic structures on deep overburden because of its complex foundation structure and poor geological condition. Seepage failure is one of the main problems. The Combination of the seepage control system of the face rockfill dam and the deep overburden can effectively control the seepage of construction of the concrete face rockfill dam on the deep overburden. Widely used anti-seepage measures are horizontal blanket, waterproof wall, curtain grouting and so on, but the method, technique and its effect of seepage control still have many problems thus need further study. Due to the above considerations, Three-dimensional seepage field numerical analysis based on practical engineering case is conducted to study the seepage prevention effect under different seepage prevention methods, which is of great significance to the development of dam technology and the development of hydropower resources in China.

A deep learning method for lincRNA detection using auto-encoder algorithm.

Science.gov (United States)

Yu, Ning; Yu, Zeng; Pan, Yi

2017-12-06

RNA sequencing technique (RNA-seq) enables scientists to develop novel data-driven methods for discovering more unidentified lincRNAs. Meantime, knowledge-based technologies are experiencing a potential revolution ignited by the new deep learning methods. By scanning the newly found data set from RNA-seq, scientists have found that: (1) the expression of lincRNAs appears to be regulated, that is, the relevance exists along the DNA sequences; (2) lincRNAs contain some conversed patterns/motifs tethered together by non-conserved regions. The two evidences give the reasoning for adopting knowledge-based deep learning methods in lincRNA detection. Similar to coding region transcription, non-coding regions are split at transcriptional sites. However, regulatory RNAs rather than message RNAs are generated. That is, the transcribed RNAs participate the biological process as regulatory units instead of generating proteins. Identifying these transcriptional regions from non-coding regions is the first step towards lincRNA recognition. The auto-encoder method achieves 100% and 92.4% prediction accuracy on transcription sites over the putative data sets. The experimental results also show the excellent performance of predictive deep neural network on the lincRNA data sets compared with support vector machine and traditional neural network. In addition, it is validated through the newly discovered lincRNA data set and one unreported transcription site is found by feeding the whole annotated sequences through the deep learning machine, which indicates that deep learning method has the extensive ability for lincRNA prediction. The transcriptional sequences of lincRNAs are collected from the annotated human DNA genome data. Subsequently, a two-layer deep neural network is developed for the lincRNA detection, which adopts the auto-encoder algorithm and utilizes different encoding schemes to obtain the best performance over intergenic DNA sequence data. Driven by those newly

Complete genome sequence of the aerobic, heterotroph Marinithermus hydrothermalis type strain (T1T) from a deep-sea hydrothermal vent chimney

Energy Technology Data Exchange (ETDEWEB)

Copeland, A [U.S. Department of Energy, Joint Genome Institute; Gu, Wei [U.S. Department of Energy, Joint Genome Institute; Yasawong, Montri [HZI - Helmholtz Centre for Infection Research, Braunschweig, Germany; Lapidus, Alla L. [U.S. Department of Energy, Joint Genome Institute; Lucas, Susan [U.S. Department of Energy, Joint Genome Institute; Deshpande, Shweta [U.S. Department of Energy, Joint Genome Institute; Pagani, Ioanna [U.S. Department of Energy, Joint Genome Institute; Tapia, Roxanne [Los Alamos National Laboratory (LANL); Cheng, Jan-Fang [U.S. Department of Energy, Joint Genome Institute; Goodwin, Lynne A. [Los Alamos National Laboratory (LANL); Pitluck, Sam [U.S. Department of Energy, Joint Genome Institute; Liolios, Konstantinos [U.S. Department of Energy, Joint Genome Institute; Ivanova, N [U.S. Department of Energy, Joint Genome Institute; Mavromatis, K [U.S. Department of Energy, Joint Genome Institute; Mikhailova, Natalia [U.S. Department of Energy, Joint Genome Institute; Pati, Amrita [U.S. Department of Energy, Joint Genome Institute; Chen, Amy [U.S. Department of Energy, Joint Genome Institute; Palaniappan, Krishna [U.S. Department of Energy, Joint Genome Institute; Land, Miriam L [ORNL; Pan, Chongle [ORNL; Brambilla, Evelyne-Marie [DSMZ - German Collection of Microorganisms and Cell Cultures GmbH, Braunschweig, Germany; Rohde, Manfred [HZI - Helmholtz Centre for Infection Research, Braunschweig, Germany; Tindall, Brian [DSMZ - German Collection of Microorganisms and Cell Cultures GmbH, Braunschweig, Germany; Sikorski, Johannes [DSMZ - German Collection of Microorganisms and Cell Cultures GmbH, Braunschweig, Germany; Goker, Markus [DSMZ - German Collection of Microorganisms and Cell Cultures GmbH, Braunschweig, Germany; Detter, J. Chris [U.S. Department of Energy, Joint Genome Institute; Bristow, James [U.S. Department of Energy, Joint Genome Institute; Eisen, Jonathan [U.S. Department of Energy, Joint Genome Institute; Markowitz, Victor [U.S. Department of Energy, Joint Genome Institute; Hugenholtz, Philip [U.S. Department of Energy, Joint Genome Institute; Kyrpides, Nikos C [U.S. Department of Energy, Joint Genome Institute; Klenk, Hans-Peter [DSMZ - German Collection of Microorganisms and Cell Cultures GmbH, Braunschweig, Germany; Woyke, Tanja [U.S. Department of Energy, Joint Genome Institute

2012-01-01

Marinithermus hydrothermalis Sako et al. 2003 is the type species of the monotypic genus Marinithermus. M. hydrothermalis T1 T was the first isolate within the phylum ThermusDeinococcus to exhibit optimal growth under a salinity equivalent to that of sea water and to have an absolute requirement for NaCl for growth. M. hydrothermalis T1 T is of interest because it may provide a new insight into the ecological significance of the aerobic, thermophilic decomposers in the circulation of organic compounds in deep-sea hydrothermal vent ecosystems. This is the first completed genome sequence of a member of the genus Marinithermus and the seventh sequence from the family Thermaceae. Here we describe the features of this organism, together with the complete genome sequence and annotation. The 2,269,167 bp long genome with its 2,251 protein-coding and 59 RNA genes is a part of the Genomic Encyclopedia of Bacteria and Archaea project.

Complete genome sequence of the aerobic, heterotroph Marinithermus hydrothermalis type strain (T1(T)) from a deep-sea hydrothermal vent chimney.

Science.gov (United States)

Copeland, Alex; Gu, Wei; Yasawong, Montri; Lapidus, Alla; Lucas, Susan; Deshpande, Shweta; Pagani, Ioanna; Tapia, Roxanne; Cheng, Jan-Fang; Goodwin, Lynne A; Pitluck, Sam; Liolios, Konstantinos; Ivanova, Natalia; Mavromatis, Konstantinos; Mikhailova, Natalia; Pati, Amrita; Chen, Amy; Palaniappan, Krishna; Land, Miriam; Pan, Chongle; Brambilla, Evelyne-Marie; Rohde, Manfred; Tindall, Brian J; Sikorski, Johannes; Göker, Markus; Detter, John C; Bristow, James; Eisen, Jonathan A; Markowitz, Victor; Hugenholtz, Philip; Kyrpides, Nikos C; Klenk, Hans-Peter; Woyke, Tanja

2012-03-19

Marinithermus hydrothermalis Sako et al. 2003 is the type species of the monotypic genus Marinithermus. M. hydrothermalis T1(T) was the first isolate within the phylum "Thermus-Deinococcus" to exhibit optimal growth under a salinity equivalent to that of sea water and to have an absolute requirement for NaCl for growth. M. hydrothermalis T1(T) is of interest because it may provide a new insight into the ecological significance of the aerobic, thermophilic decomposers in the circulation of organic compounds in deep-sea hydrothermal vent ecosystems. This is the first completed genome sequence of a member of the genus Marinithermus and the seventh sequence from the family Thermaceae. Here we describe the features of this organism, together with the complete genome sequence and annotation. The 2,269,167 bp long genome with its 2,251 protein-coding and 59 RNA genes is a part of the Genomic Encyclopedia of Bacteria and Archaea project.

RDNAnalyzer: A tool for DNA secondary structure prediction and sequence analysis.

Science.gov (United States)

Afzal, Muhammad; Shahid, Ahmad Ali; Shehzadi, Abida; Nadeem, Shahid; Husnain, Tayyab

2012-01-01

RDNAnalyzer is an innovative computer based tool designed for DNA secondary structure prediction and sequence analysis. It can randomly generate the DNA sequence or user can upload the sequences of their own interest in RAW format. It uses and extends the Nussinov dynamic programming algorithm and has various application for the sequence analysis. It predicts the DNA secondary structure and base pairings. It also provides the tools for routinely performed sequence analysis by the biological scientists such as DNA replication, reverse compliment generation, transcription, translation, sequence specific information as total number of nucleotide bases, ATGC base contents along with their respective percentages and sequence cleaner. RDNAnalyzer is a unique tool developed in Microsoft Visual Studio 2008 using Microsoft Visual C# and Windows Presentation Foundation and provides user friendly environment for sequence analysis. It is freely available. http://www.cemb.edu.pk/sw.html RDNAnalyzer - Random DNA Analyser, GUI - Graphical user interface, XAML - Extensible Application Markup Language.

Fusarium musae as cause of superficial and deep-seated human infections.

Science.gov (United States)

Esposto, M C; Prigitano, A; Tortorano, A M

2016-12-01

BLAST analysis in GenBank of 60 Fusarium verticillioides clinical isolates using the sequence of translation elongation factor 1-alpha allowed the identification of four F. musae confirming that this species is not a rare etiology of superficial and deep infections and that its habitat is not restricted to banana fruits. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Discovery of Bovine Digital Dermatitis-Associated Treponema spp. in the Dairy Herd Environment by a Targeted Deep-Sequencing Approach

DEFF Research Database (Denmark)

Schou, Kirstine Klitgaard; Weiss Nielsen, Martin; Ingerslev, Hans-Christian

2014-01-01

The bacteria associated with the infectious claw disease bovine digital dermatitis (DD) are spirochetes of the genus Treponema; however, their environmental reservoir remains unknown. To our knowledge, the current study is the first report of the discovery and phylogenetic characterization of r...... of this disease among cows within a herd as well as between herds. To address the issue of DD infection reservoirs, we searched for evidence of DD-associated treponemes in fresh feces, in slurry, and in hoof lesions by deep sequencing of the V3 and V4 hypervariable regions of the 16S rRNA gene coupled...... with identification at the operational-taxonomic-unit level. Using treponeme-specific primers in this high-throughput approach, we identified small amounts of DNA (on average 0.6% of the total amount of sequence reads) from DD-associated treponemes in 43 of 64 samples from slurry and cow feces collected from six...

An introduction to Deep learning on biological sequence data - Examples and solutions

DEFF Research Database (Denmark)

Jurtz, Vanessa Isabell; Johansen, Alexander Rosenberg; Nielsen, Morten

2017-01-01

Deep neural network architectures such as convolutional and long short-term memory networks have become increasingly popular as machine learning tools during the recent years. The availability of greater computational resources, more data, new algorithms for training deep models and easy to use....... Here, we aim to further the development of deep learning methods within biology by providing application examples and ready to apply and adapt code templates. Given such examples, we illustrate how architectures consisting of convolutional and long short-term memory neural networks can relatively...

DEEP: a general computational framework for predicting enhancers

KAUST Repository

Kleftogiannis, Dimitrios A.

2014-11-05

Transcription regulation in multicellular eukaryotes is orchestrated by a number of DNA functional elements located at gene regulatory regions. Some regulatory regions (e.g. enhancers) are located far away from the gene they affect. Identification of distal regulatory elements is a challenge for the bioinformatics research. Although existing methodologies increased the number of computationally predicted enhancers, performance inconsistency of computational models across different cell-lines, class imbalance within the learning sets and ad hoc rules for selecting enhancer candidates for supervised learning, are some key questions that require further examination. In this study we developed DEEP, a novel ensemble prediction framework. DEEP integrates three components with diverse characteristics that streamline the analysis of enhancer\\'s properties in a great variety of cellular conditions. In our method we train many individual classification models that we combine to classify DNA regions as enhancers or non-enhancers. DEEP uses features derived from histone modification marks or attributes coming from sequence characteristics. Experimental results indicate that DEEP performs better than four state-of-the-art methods on the ENCODE data. We report the first computational enhancer prediction results on FANTOM5 data where DEEP achieves 90.2% accuracy and 90% geometric mean (GM) of specificity and sensitivity across 36 different tissues. We further present results derived using in vivo-derived enhancer data from VISTA database. DEEP-VISTA, when tested on an independent test set, achieved GM of 80.1% and accuracy of 89.64%. DEEP framework is publicly available at http://cbrc.kaust.edu.sa/deep/.

DEEP: a general computational framework for predicting enhancers

KAUST Repository

Kleftogiannis, Dimitrios A.; Kalnis, Panos; Bajic, Vladimir B.

2014-01-01

Transcription regulation in multicellular eukaryotes is orchestrated by a number of DNA functional elements located at gene regulatory regions. Some regulatory regions (e.g. enhancers) are located far away from the gene they affect. Identification of distal regulatory elements is a challenge for the bioinformatics research. Although existing methodologies increased the number of computationally predicted enhancers, performance inconsistency of computational models across different cell-lines, class imbalance within the learning sets and ad hoc rules for selecting enhancer candidates for supervised learning, are some key questions that require further examination. In this study we developed DEEP, a novel ensemble prediction framework. DEEP integrates three components with diverse characteristics that streamline the analysis of enhancer's properties in a great variety of cellular conditions. In our method we train many individual classification models that we combine to classify DNA regions as enhancers or non-enhancers. DEEP uses features derived from histone modification marks or attributes coming from sequence characteristics. Experimental results indicate that DEEP performs better than four state-of-the-art methods on the ENCODE data. We report the first computational enhancer prediction results on FANTOM5 data where DEEP achieves 90.2% accuracy and 90% geometric mean (GM) of specificity and sensitivity across 36 different tissues. We further present results derived using in vivo-derived enhancer data from VISTA database. DEEP-VISTA, when tested on an independent test set, achieved GM of 80.1% and accuracy of 89.64%. DEEP framework is publicly available at http://cbrc.kaust.edu.sa/deep/.

Scalable Kernel Methods and Algorithms for General Sequence Analysis

Science.gov (United States)

Kuksa, Pavel

2011-01-01

Analysis of large-scale sequential data has become an important task in machine learning and pattern recognition, inspired in part by numerous scientific and technological applications such as the document and text classification or the analysis of biological sequences. However, current computational methods for sequence comparison still lack…

Accident sequence analysis of human-computer interface design

International Nuclear Information System (INIS)

Fan, C.-F.; Chen, W.-H.

2000-01-01

It is important to predict potential accident sequences of human-computer interaction in a safety-critical computing system so that vulnerable points can be disclosed and removed. We address this issue by proposing a Multi-Context human-computer interaction Model along with its analysis techniques, an Augmented Fault Tree Analysis, and a Concurrent Event Tree Analysis. The proposed augmented fault tree can identify the potential weak points in software design that may induce unintended software functions or erroneous human procedures. The concurrent event tree can enumerate possible accident sequences due to these weak points

Analysis of a deep nucleus of Tehuantepec Gulf

International Nuclear Information System (INIS)

Ordonez R, E.; Lopez M, J.; Ramirez T, J. J.; Machain C, M. L.

2009-10-01

A nucleus of sediments obtained in the deep of Tehuantepec Gulf is analyzed; this nucleus has the particularity of to be a sampling of longitude of 18.3 m that include the total of last period glacial, few times obtained in our country. The physical chemistry composition of 10 selected fractions are analyzed with the purpose of to understand the formation processes of deep ocean along the period of 120 000 years, that includes the extracted fraction. Crystallography analysis, morphology, physical chemistry characterization and activity gamma were made. Finding that the content of organic matter falls as the superficial area increases, also was found the presence of natural uranium in similar concentration and balance with its radiogenic descendants along the nucleus profile what suggests the uranium migration to interior of mineral grains. (Author)

VL1 Digs A Deep Hole On Mars

Science.gov (United States)

1977-01-01

VIKING LANDER DIGS A DEEP HOLE ON MARS -- This six-inch-deep, 12- inch-wide, 29-inch-long hole was dug Feb. 12 and 14 by Viking Lander 1 as the first sequence in an attempt to reach a foot beneath the surface of the red planet. The activity is in the same area where Lander 1 acquired its first soil samples last July. The trench was dug by repeatedly backhoeing in a left-right-center pattern. The backhoe teeth produced the small parallel ridges at the far end of the trench (upper left). The larger ridges running the length of the trench are material left behind during the backhoe operation. What appears to be small rocks along the ridges and in the soil at the near end of the trench are really small dirt clods. The clods and the steepness of the trench walls indicate the material is cohesive and behaves something like ordinary flour. After a later sequence, to be performed March 1 and 2, a soil sample will be taken from the bottom of the trench for inorganic soil analysis and later for biology analysis. Information about the soil taken from the bottom of the trench may help explain the weathering process on Mars and may help resolve the dilemma created by Viking findings that first suggest but then cast doubt on the possibility of life in the Martian soil. The trench shown here is a result of one of the most complex command sequences yet performed by the lander. Viking l has been operating at Chryse Planitia on Mars since it landed July 20, 1976.

Inverse Analysis to Formability Design in a Deep Drawing Process

Science.gov (United States)

Buranathiti, Thaweepat; Cao, Jian

Deep drawing process is an important process adding values to flat sheet metals in many industries. An important concern in the design of a deep drawing process generally is formability. This paper aims to present the connection between formability and inverse analysis (IA), which is a systematical means for determining an optimal blank configuration for a deep drawing process. In this paper, IA is presented and explored by using a commercial finite element software package. A number of numerical studies on the effect of blank configurations to the quality of a part produced by a deep drawing process were conducted and analyzed. The quality of the drawing processes is numerically analyzed by using an explicit incremental nonlinear finite element code. The minimum distance between elemental principal strains and the strain-based forming limit curve (FLC) is defined as tearing margin to be the key performance index (KPI) implying the quality of the part. The initial blank configuration has shown that it plays a highly important role in the quality of the product via the deep drawing process. In addition, it is observed that if a blank configuration is not greatly deviated from the one obtained from IA, the blank can still result a good product. The strain history around the bottom fillet of the part is also observed. The paper concludes that IA is an important part of the design methodology for deep drawing processes.

Application of Deep Learning in Automated Analysis of Molecular Images in Cancer: A Survey

Science.gov (United States)

Xue, Yong; Chen, Shihui; Liu, Yong

2017-01-01

Molecular imaging enables the visualization and quantitative analysis of the alterations of biological procedures at molecular and/or cellular level, which is of great significance for early detection of cancer. In recent years, deep leaning has been widely used in medical imaging analysis, as it overcomes the limitations of visual assessment and traditional machine learning techniques by extracting hierarchical features with powerful representation capability. Research on cancer molecular images using deep learning techniques is also increasing dynamically. Hence, in this paper, we review the applications of deep learning in molecular imaging in terms of tumor lesion segmentation, tumor classification, and survival prediction. We also outline some future directions in which researchers may develop more powerful deep learning models for better performance in the applications in cancer molecular imaging. PMID:29114182

Deep RNA sequencing reveals dynamic regulation of myocardial noncoding RNAs in failing human heart and remodeling with mechanical circulatory support.

Science.gov (United States)

Yang, Kai-Chien; Yamada, Kathryn A; Patel, Akshar Y; Topkara, Veli K; George, Isaac; Cheema, Faisal H; Ewald, Gregory A; Mann, Douglas L; Nerbonne, Jeanne M

2014-03-04

Microarrays have been used extensively to profile transcriptome remodeling in failing human heart, although the genomic coverage provided is limited and fails to provide a detailed picture of the myocardial transcriptome landscape. Here, we describe sequencing-based transcriptome profiling, providing comprehensive analysis of myocardial mRNA, microRNA (miRNA), and long noncoding RNA (lncRNA) expression in failing human heart before and after mechanical support with a left ventricular (LV) assist device (LVAD). Deep sequencing of RNA isolated from paired nonischemic (NICM; n=8) and ischemic (ICM; n=8) human failing LV samples collected before and after LVAD and from nonfailing human LV (n=8) was conducted. These analyses revealed high abundance of mRNA (37%) and lncRNA (71%) of mitochondrial origin. miRNASeq revealed 160 and 147 differentially expressed miRNAs in ICM and NICM, respectively, compared with nonfailing LV. Among these, only 2 (ICM) and 5 (NICM) miRNAs are normalized with LVAD. RNASeq detected 18 480, including 113 novel, lncRNAs in human LV. Among the 679 (ICM) and 570 (NICM) lncRNAs differentially expressed with heart failure, ≈10% are improved or normalized with LVAD. In addition, the expression signature of lncRNAs, but not miRNAs or mRNAs, distinguishes ICM from NICM. Further analysis suggests that cis-gene regulation represents a major mechanism of action of human cardiac lncRNAs. The myocardial transcriptome is dynamically regulated in advanced heart failure and after LVAD support. The expression profiles of lncRNAs, but not mRNAs or miRNAs, can discriminate failing hearts of different pathologies and are markedly altered in response to LVAD support. These results suggest an important role for lncRNAs in the pathogenesis of heart failure and in reverse remodeling observed with mechanical support.

An optimum analysis sequence for environmental gamma-ray spectrometry

International Nuclear Information System (INIS)

De la Torre, F.; Rios M, C.; Ruvalcaba A, M. G.; Mireles G, F.; Saucedo A, S.; Davila R, I.; Pinedo, J. L.

2010-10-01

This work aims to obtain an optimum analysis sequence for environmental gamma-ray spectroscopy by means of Genie 2000 (Canberra). Twenty different analysis sequences were customized using different peak area percentages and different algorithms for: 1) peak finding, and 2) peak area determination, and with or without the use of a library -based on evaluated nuclear data- of common gamma-ray emitters in environmental samples. The use of an optimum analysis sequence with certified nuclear information avoids the problems originated by the significant variations in out-of-date nuclear parameters of commercial software libraries. Interference-free gamma ray energies with absolute emission probabilities greater than 3.75% were included in the customized library. The gamma-ray spectroscopy system (based on a Ge Re-3522 Canberra detector) was calibrated both in energy and shape by means of the IAEA-2002 reference spectra for software intercomparison. To test the performance of the analysis sequences, the IAEA-2002 reference spectrum was used. The z-score and the reduced χ 2 criteria were used to determine the optimum analysis sequence. The results show an appreciable variation in the peak area determinations and their corresponding uncertainties. Particularly, the combination of second derivative peak locate with simple peak area integration algorithms provides the greater accuracy. Lower accuracy comes from the combination of library directed peak locate algorithm and Genie's Gamma-M peak area determination. (Author)

DeepGO: predicting protein functions from sequence and interactions using a deep ontology-aware classifier

KAUST Repository

Kulmanov, Maxat; Khan, Mohammed Asif; Hoehndorf, Robert

2017-01-01

A large number of protein sequences are becoming available through the application of novel high-throughput sequencing technologies. Experimental functional characterization of these proteins is time-consuming and expensive, and is often

Invited talk: Deep Learning Meets Physics

CERN Multimedia

CERN. Geneva

2018-01-01

Deep Learning has emerged as one of the most successful fields of machine learning and artificial intelligence with overwhelming success in industrial speech, text and vision benchmarks. Consequently it evolved into the central field of research for IT giants like Google, facebook, Microsoft, Baidu, and Amazon. Deep Learning is founded on novel neural network techniques, the recent availability of very fast computers, and massive data sets. In its core, Deep Learning discovers multiple levels of abstract representations of the input. The main obstacle to learning deep neural networks is the vanishing gradient problem. The vanishing gradient impedes credit assignment to the first layers of a deep network or to early elements of a sequence, therefore limits model selection. Major advances in Deep Learning can be related to avoiding the vanishing gradient like stacking, ReLUs, residual networks, highway networks, and LSTM. For Deep Learning, we suggested self-normalizing neural networks (SNNs) which automatica...

Characterization and sequence analysis of cysteine and glycine-rich ...

African Journals Online (AJOL)

Primers specific for CSRP3 were designed using known cDNA sequences of Bos taurus published in database with different accession numbers. Polymerase chain reaction (PCR) was performed and products were purified and sequenced. Sequence analysis and alignment were carried out using CLUSTAL W (1.83).

Real-time regression analysis with deep convolutional neural networks

OpenAIRE

Huerta, E. A.; George, Daniel; Zhao, Zhizhen; Allen, Gabrielle

2018-01-01

We discuss the development of novel deep learning algorithms to enable real-time regression analysis for time series data. We showcase the application of this new method with a timely case study, and then discuss the applicability of this approach to tackle similar challenges across science domains.

Maximum entropy methods for extracting the learned features of deep neural networks.

Science.gov (United States)

Finnegan, Alex; Song, Jun S

2017-10-01

New architectures of multilayer artificial neural networks and new methods for training them are rapidly revolutionizing the application of machine learning in diverse fields, including business, social science, physical sciences, and biology. Interpreting deep neural networks, however, currently remains elusive, and a critical challenge lies in understanding which meaningful features a network is actually learning. We present a general method for interpreting deep neural networks and extracting network-learned features from input data. We describe our algorithm in the context of biological sequence analysis. Our approach, based on ideas from statistical physics, samples from the maximum entropy distribution over possible sequences, anchored at an input sequence and subject to constraints implied by the empirical function learned by a network. Using our framework, we demonstrate that local transcription factor binding motifs can be identified from a network trained on ChIP-seq data and that nucleosome positioning signals are indeed learned by a network trained on chemical cleavage nucleosome maps. Imposing a further constraint on the maximum entropy distribution also allows us to probe whether a network is learning global sequence features, such as the high GC content in nucleosome-rich regions. This work thus provides valuable mathematical tools for interpreting and extracting learned features from feed-forward neural networks.

DeepInfer: open-source deep learning deployment toolkit for image-guided therapy

Science.gov (United States)

Mehrtash, Alireza; Pesteie, Mehran; Hetherington, Jorden; Behringer, Peter A.; Kapur, Tina; Wells, William M.; Rohling, Robert; Fedorov, Andriy; Abolmaesumi, Purang

2017-03-01

Deep learning models have outperformed some of the previous state-of-the-art approaches in medical image analysis. Instead of using hand-engineered features, deep models attempt to automatically extract hierarchical representations at multiple levels of abstraction from the data. Therefore, deep models are usually considered to be more flexible and robust solutions for image analysis problems compared to conventional computer vision models. They have demonstrated significant improvements in computer-aided diagnosis and automatic medical image analysis applied to such tasks as image segmentation, classification and registration. However, deploying deep learning models often has a steep learning curve and requires detailed knowledge of various software packages. Thus, many deep models have not been integrated into the clinical research work ows causing a gap between the state-of-the-art machine learning in medical applications and evaluation in clinical research procedures. In this paper, we propose "DeepInfer" - an open-source toolkit for developing and deploying deep learning models within the 3D Slicer medical image analysis platform. Utilizing a repository of task-specific models, DeepInfer allows clinical researchers and biomedical engineers to deploy a trained model selected from the public registry, and apply it to new data without the need for software development or configuration. As two practical use cases, we demonstrate the application of DeepInfer in prostate segmentation for targeted MRI-guided biopsy and identification of the target plane in 3D ultrasound for spinal injections.

The thickness of cover sequences in the Western Desert of Iraq from a power spectrum analysis of gravity and magnetic data

Science.gov (United States)

Mousa, Ahmed; Mickus, Kevin; Al-Rahim, Ali

2017-05-01

The Western Desert of Iraq is part of the stable shelf region on the Arabian Plate where the subsurface structural makeup is relatively unknown due to the lack of cropping out rocks, deep drill holes and deep seismic refraction and reflection profiles. To remedy this situation, magnetic and gravity data were analyzed to determine the thickness of the Phanerozoic cover sequences. The 2-D power spectrum method was used to estimate the depth to density and magnetic susceptibility interfaces by using 0.5° square windows. Additionally, the gravity data were analyzed using isostatic residual and decompensative methods to isolate gravity anomalies due to upper crustal density sources. The decompensative gravity anomaly and the differentially reduced to the pole magnetic map indicate a series of mainly north-south and northwest-southeast trending maxima and minima anomalies related to Proterozoic basement lithologies and the varying thickness of cover sequences. The magnetic and gravity derived thickness of cover sequences maps indicate that these thicknesses range from 4.5 to 11.5 km. Both maps in general are in agreement but more detail in the cover thicknesses was determined by the gravity analysis. The gravity-based cover thickness maps indicates regions with shallower depths than the magnetic-based cover thickness t map which may be due to density differences between limestone and shale units within the Paleozoic sediments. The final thickness maps indicate that the Western Desert is a complicated region of basins and uplifts that are more complex than have been shown on previous structural maps of the Western Desert. These basins and uplifts may be related to Paleozoic compressional tectonic events and possibly to the opening of the Tethys Ocean. In addition, petroleum exploration could be extended to three basins outlined by our analysis within the relatively unexplored western portions of the Western Desert.

Whole-Genome Sequencing Coupled to Imputation Discovers Genetic Signals for Anthropometric Traits

NARCIS (Netherlands)

I. Tachmazidou (Ioanna); Süveges, D. (Dániel); J. Min (Josine); G.R.S. Ritchie (Graham R.S.); Steinberg, J. (Julia); K. Walter (Klaudia); V. Iotchkova (Valentina); J.A. Schwartzentruber (Jeremy); J. Huang (Jian); Y. Memari (Yasin); McCarthy, S. (Shane); Crawford, A.A. (Andrew A.); C. Bombieri (Cristina); M. Cocca (Massimiliano); A.-E. Farmaki (Aliki-Eleni); T.R. Gaunt (Tom); P. Jousilahti (Pekka); M.N. Kooijman (Marjolein ); Lehne, B. (Benjamin); G. Malerba (Giovanni); S. Männistö (Satu); A. Matchan (Angela); M.C. Medina-Gomez (Carolina); S. Metrustry (Sarah); A. Nag (Abhishek); I. Ntalla (Ioanna); L. Paternoster (Lavinia); N.W. Rayner (Nigel William); C. Sala (Cinzia); W.R. Scott (William R.); H.A. Shihab (Hashem A.); L. Southam (Lorraine); B. St Pourcain (Beate); M. Traglia (Michela); K. Trajanoska (Katerina); Zaza, G. (Gialuigi); W. Zhang (Weihua); M.S. Artigas; Bansal, N. (Narinder); M. Benn (Marianne); Chen, Z. (Zhongsheng); P. Danecek (Petr); Lin, W.-Y. (Wei-Yu); A. Locke (Adam); J. Luan (Jian'An); A.K. Manning (Alisa); Mulas, A. (Antonella); C. Sidore (Carlo); A. Tybjaerg-Hansen; A. Varbo (Anette); M. Zoledziewska (Magdalena); C. Finan (Chris); Hatzikotoulas, K. (Konstantinos); A.E. Hendricks (Audrey E.); J.P. Kemp (John); A. Moayyeri (Alireza); Panoutsopoulou, K. (Kalliope); Szpak, M. (Michal); S.G. Wilson (Scott); M. Boehnke (Michael); F. Cucca (Francesco); Di Angelantonio, E. (Emanuele); C. Langenberg (Claudia); C.M. Lindgren (Cecilia M.); McCarthy, M.I. (Mark I.); A.P. Morris (Andrew); B.G. Nordestgaard (Børge); R.A. Scott (Robert); M.D. Tobin (Martin); N.J. Wareham (Nick); P.R. Burton (Paul); J.C. Chambers (John); Smith, G.D. (George Davey); G.V. Dedoussis (George); J.F. Felix (Janine); O.H. Franco (Oscar); Gambaro, G. (Giovanni); P. Gasparini (Paolo); C.J. Hammond (Christopher J.); A. Hofman (Albert); V.W.V. Jaddoe (Vincent); M.E. Kleber (Marcus); J.S. Kooner (Jaspal S.); M. Perola (Markus); C.L. Relton (Caroline); S.M. Ring (Susan); F. Rivadeneira Ramirez (Fernando); V. Salomaa (Veikko); T.D. Spector (Timothy); O. Stegle (Oliver); D. Toniolo (Daniela); A.G. Uitterlinden (André); I.E. Barroso (Inês); C.M.T. Greenwood (Celia); Perry, J.R.B. (John R.B.); Walker, B.R. (Brian R.); A.S. Butterworth (Adam); Y. Xue (Yali); R. Durbin (Richard); K.S. Small (Kerrin); N. Soranzo (Nicole); N.J. Timpson (Nicholas); E. Zeggini (Eleftheria)

2016-01-01

textabstractDeep sequence-based imputation can enhance the discovery power of genome-wide association studies by assessing previously unexplored variation across the common- and low-frequency spectra. We applied a hybrid whole-genome sequencing (WGS) and deep imputation approach to examine the

Whole-Genome Sequencing Coupled to Imputation Discovers Genetic Signals for Anthropometric Traits

DEFF Research Database (Denmark)

Tachmazidou, Ioanna; Süveges, Dániel; Min, Josine L

2017-01-01

Deep sequence-based imputation can enhance the discovery power of genome-wide association studies by assessing previously unexplored variation across the common- and low-frequency spectra. We applied a hybrid whole-genome sequencing (WGS) and deep imputation approach to examine the broader alleli...

Long-read sequencing data analysis for yeasts.

Science.gov (United States)

Yue, Jia-Xing; Liti, Gianni

2018-06-01

Long-read sequencing technologies have become increasingly popular due to their strengths in resolving complex genomic regions. As a leading model organism with small genome size and great biotechnological importance, the budding yeast Saccharomyces cerevisiae has many isolates currently being sequenced with long reads. However, analyzing long-read sequencing data to produce high-quality genome assembly and annotation remains challenging. Here, we present a modular computational framework named long-read sequencing data analysis for yeasts (LRSDAY), the first one-stop solution that streamlines this process. Starting from the raw sequencing reads, LRSDAY can produce chromosome-level genome assembly and comprehensive genome annotation in a highly automated manner with minimal manual intervention, which is not possible using any alternative tool available to date. The annotated genomic features include centromeres, protein-coding genes, tRNAs, transposable elements (TEs), and telomere-associated elements. Although tailored for S. cerevisiae, we designed LRSDAY to be highly modular and customizable, making it adaptable to virtually any eukaryotic organism. When applying LRSDAY to an S. cerevisiae strain, it takes ∼41 h to generate a complete and well-annotated genome from ∼100× Pacific Biosciences (PacBio) running the basic workflow with four threads. Basic experience working within the Linux command-line environment is recommended for carrying out the analysis using LRSDAY.

Transcriptome sequencing of the Microarray Quality Control (MAQC RNA reference samples using next generation sequencing

Directory of Open Access Journals (Sweden)

Thierry-Mieg Danielle

2009-06-01

Full Text Available Abstract Background Transcriptome sequencing using next-generation sequencing platforms will soon be competing with DNA microarray technologies for global gene expression analysis. As a preliminary evaluation of these promising technologies, we performed deep sequencing of cDNA synthesized from the Microarray Quality Control (MAQC reference RNA samples using Roche's 454 Genome Sequencer FLX. Results We generated more that 3.6 million sequence reads of average length 250 bp for the MAQC A and B samples and introduced a data analysis pipeline for translating cDNA read counts into gene expression levels. Using BLAST, 90% of the reads mapped to the human genome and 64% of the reads mapped to the RefSeq database of well annotated genes with e-values ≤ 10-20. We measured gene expression levels in the A and B samples by counting the numbers of reads that mapped to individual RefSeq genes in multiple sequencing runs to evaluate the MAQC quality metrics for reproducibility, sensitivity, specificity, and accuracy and compared the results with DNA microarrays and Quantitative RT-PCR (QRTPCR from the MAQC studies. In addition, 88% of the reads were successfully aligned directly to the human genome using the AceView alignment programs with an average 90% sequence similarity to identify 137,899 unique exon junctions, including 22,193 new exon junctions not yet contained in the RefSeq database. Conclusion Using the MAQC metrics for evaluating the performance of gene expression platforms, the ExpressSeq results for gene expression levels showed excellent reproducibility, sensitivity, and specificity that improved systematically with increasing shotgun sequencing depth, and quantitative accuracy that was comparable to DNA microarrays and QRTPCR. In addition, a careful mapping of the reads to the genome using the AceView alignment programs shed new light on the complexity of the human transcriptome including the discovery of thousands of new splice variants.

DRREP: deep ridge regressed epitope predictor.

Science.gov (United States)

Sher, Gene; Zhi, Degui; Zhang, Shaojie

2017-10-03

The ability to predict epitopes plays an enormous role in vaccine development in terms of our ability to zero in on where to do a more thorough in-vivo analysis of the protein in question. Though for the past decade there have been numerous advancements and improvements in epitope prediction, on average the best benchmark prediction accuracies are still only around 60%. New machine learning algorithms have arisen within the domain of deep learning, text mining, and convolutional networks. This paper presents a novel analytically trained and string kernel using deep neural network, which is tailored for continuous epitope prediction, called: Deep Ridge Regressed Epitope Predictor (DRREP). DRREP was tested on long protein sequences from the following datasets: SARS, Pellequer, HIV, AntiJen, and SEQ194. DRREP was compared to numerous state of the art epitope predictors, including the most recently published predictors called LBtope and DMNLBE. Using area under ROC curve (AUC), DRREP achieved a performance improvement over the best performing predictors on SARS (13.7%), HIV (8.9%), Pellequer (1.5%), and SEQ194 (3.1%), with its performance being matched only on the AntiJen dataset, by the LBtope predictor, where both DRREP and LBtope achieved an AUC of 0.702. DRREP is an analytically trained deep neural network, thus capable of learning in a single step through regression. By combining the features of deep learning, string kernels, and convolutional networks, the system is able to perform residue-by-residue prediction of continues epitopes with higher accuracy than the current state of the art predictors.

Taxonomic research on deep-sea macrofauna in the South China Sea using the Chinese deep-sea submersible Jiaolong.

Science.gov (United States)

Li, Xinzheng

2017-07-01

This paper reviews the taxonomic and biodiversity studies of deep-sea invertebrates in the South China Sea based on the samples collected by the Chinese manned deep-sea submersible Jiaolong. To date, 6 new species have been described, including the sponges Lophophysema eversa, Saccocalyx microhexactin and Semperella jiaolongae as well as the crustaceans Uroptychus jiaolongae, Uroptychus spinulosus and Globospongicola jiaolongi; some newly recorded species from the South China Sea have also been reported. The Bathymodiolus platifrons-Shinkaia crosnieri deep-sea cold seep community has been reported by Li (2015), as has the mitochondrial genome of the glass sponge L. eversa by Zhang et al. (2016). The population structures of two dominant species, the shrimp Shinkaia crosnieri and the mussel Bathymodiolus platifrons, from the cold seep Bathymodiolus platifrons-Shinkaia crosnieri community in the South China Sea and the hydrothermal vents in the Okinawa Trough, were compared using molecular analysis. The systematic position of the shrimp genus Globospongicola was discussed based on 16S rRNA gene sequences. © 2017 International Society of Zoological Sciences, Institute of Zoology/Chinese Academy of Sciences and John Wiley & Sons Australia, Ltd.

Computer-aided visualization and analysis system for sequence evaluation

Energy Technology Data Exchange (ETDEWEB)

Chee, Mark S.; Wang, Chunwei; Jevons, Luis C.; Bernhart, Derek H.; Lipshutz, Robert J.

2004-05-11

A computer system for analyzing nucleic acid sequences is provided. The computer system is used to perform multiple methods for determining unknown bases by analyzing the fluorescence intensities of hybridized nucleic acid probes. The results of individual experiments are improved by processing nucleic acid sequences together. Comparative analysis of multiple experiments is also provided by displaying reference sequences in one area and sample sequences in another area on a display device.

Analysis for Behavior of Reinforcement Lap Splices in Deep Beams

Directory of Open Access Journals (Sweden)

Ammar Yaser Ali

2018-03-01

Full Text Available The present study includes an experimental and theoretical investigation of reinforced concrete deep beams containing tensile reinforcement lap splices at constant moment zone under static load. The study included two stages: in the first one, an experimental work included testing of eight simply supported RC deep beams having a total length (L = 2000 mm, overall depth (h= 600 mm and width (b = 150 mm. The tested specimens were divided into three groups to study the effect of main variables: lap length, location of splice, internal confinement (stirrups and external confinement (strengthening by CFRP laminates. The experimental results showed that the use of CFRP as external strengthening in deep beam with lap spliced gives best behavior such as increase in stiffness, decrease in deflection, delaying the cracks appearance and reducing the crack width. The reduction in deflection about (14-21 % than the unstrengthened beam and about (5-14 % than the beam with continuous bars near ultimate load. Also, it was observed that the beams with unstrengthened tensile reinforcement lap splices had three types of cracks: flexural, flexural-shear and splitting cracks while the beams with strengthened tensile reinforcement lap splices or continuous bars don’t observe splitting cracks. In the second stage, a numerical analysis of three dimensional finite element analysis was utilized to explore the behavior of the RC deep beams with tensile reinforcement lap splices, in addition to parametric study of many variables. The comparison between the experimental and theoretical results showed reasonable agreement. The average difference of the deflection at service load was less than 5%.

An optimum analysis sequence for environmental gamma-ray spectrometry

Energy Technology Data Exchange (ETDEWEB)

De la Torre, F.; Rios M, C.; Ruvalcaba A, M. G.; Mireles G, F.; Saucedo A, S.; Davila R, I.; Pinedo, J. L., E-mail: fta777@hotmail.co [Universidad Autonoma de Zacatecas, Centro Regional de Estudis Nucleares, Calle Cipres No. 10, Fracc. La Penuela, 98068 Zacatecas (Mexico)

2010-10-15

This work aims to obtain an optimum analysis sequence for environmental gamma-ray spectroscopy by means of Genie 2000 (Canberra). Twenty different analysis sequences were customized using different peak area percentages and different algorithms for: 1) peak finding, and 2) peak area determination, and with or without the use of a library -based on evaluated nuclear data- of common gamma-ray emitters in environmental samples. The use of an optimum analysis sequence with certified nuclear information avoids the problems originated by the significant variations in out-of-date nuclear parameters of commercial software libraries. Interference-free gamma ray energies with absolute emission probabilities greater than 3.75% were included in the customized library. The gamma-ray spectroscopy system (based on a Ge Re-3522 Canberra detector) was calibrated both in energy and shape by means of the IAEA-2002 reference spectra for software intercomparison. To test the performance of the analysis sequences, the IAEA-2002 reference spectrum was used. The z-score and the reduced {chi}{sup 2} criteria were used to determine the optimum analysis sequence. The results show an appreciable variation in the peak area determinations and their corresponding uncertainties. Particularly, the combination of second derivative peak locate with simple peak area integration algorithms provides the greater accuracy. Lower accuracy comes from the combination of library directed peak locate algorithm and Genie's Gamma-M peak area determination. (Author)

Accelerated Evolution of Conserved Noncoding Sequences in theHuman Genome

Energy Technology Data Exchange (ETDEWEB)

Prambhakar, Shyam; Noonan, James P.; Paabo, Svante; Rubin, EdwardM.

2006-07-06

Genomic comparisons between human and distant, non-primatemammals are commonly used to identify cis-regulatory elements based onconstrained sequence evolution. However, these methods fail to detect"cryptic" functional elements, which are too weakly conserved amongmammals to distinguish from nonfunctional DNA. To address this problem,we explored the potential of deep intra-primate sequence comparisons. Wesequenced the orthologs of 558 kb of human genomic sequence, coveringmultiple loci involved in cholesterol homeostasis, in 6 nonhumanprimates. Our analysis identified 6 noncoding DNA elements displayingsignificant conservation among primates, but undetectable in more distantcomparisons. In vitro and in vivo tests revealed that at least three ofthese 6 elements have regulatory function. Notably, the mouse orthologsof these three functional human sequences had regulatory activity despitetheir lack of significant sequence conservation, indicating that they arecryptic ancestral cis-regulatory elements. These regulatory elementscould still be detected in a smaller set of three primate speciesincluding human, rhesus and marmoset. Since the human and rhesus genomesequences are already available, and the marmoset genome is activelybeing sequenced, the primate-specific conservation analysis describedhere can be applied in the near future on a whole-genome scale, tocomplement the annotation provided by more distant speciescomparisons.

Species-level analysis of DNA sequence data from the NIH Human Microbiome Project.

Science.gov (United States)

Conlan, Sean; Kong, Heidi H; Segre, Julia A

2012-01-01

Outbreaks of antibiotic-resistant bacterial infections emphasize the importance of surveillance of potentially pathogenic bacteria. Genomic sequencing of clinical microbiological specimens expands our capacity to study cultivable, fastidious and uncultivable members of the bacterial community. Herein, we compared the primary data collected by the NIH's Human Microbiome Project (HMP) with published epidemiological surveillance data of Staphylococcus aureus. The HMP's initial dataset contained microbial survey data from five body regions (skin, nares, oral cavity, gut and vagina) of 242 healthy volunteers. A significant component of the HMP dataset was deep sequencing of the 16S ribosomal RNA gene, which contains variable regions enabling taxonomic classification. Since species-level identification is essential in clinical microbiology, we built a reference database and used phylogenetic placement followed by most recent common ancestor classification to look at the species distribution for Staphylococcus, Klebsiella and Enterococcus. We show that selecting the accurate region of the 16S rRNA gene to sequence is analogous to carefully selecting culture conditions to distinguish closely related bacterial species. Analysis of the HMP data showed that Staphylococcus aureus was present in the nares of 36% of healthy volunteers, consistent with culture-based epidemiological data. Klebsiella pneumoniae and Enterococcus faecalis were found less frequently, but across many habitats. This work demonstrates that large 16S rRNA survey studies can be used to support epidemiological goals in the context of an increasing awareness that microbes flourish and compete within a larger bacterial community. This study demonstrates how genomic techniques and information could be critically important to trace microbial evolution and implement hospital infection control.

Deep Microbial Ecosystems in the U.S. Great Basin: A Second Home for Desulforudis audaxviator?

Science.gov (United States)

Moser, D. P.

2012-12-01

Deep subsurface microbial ecosystems have attracted scientific and public interest in recent years. Of deep habitats so far investigated, continental hard rock environments may be the least understood. Our Census of Deep Life (CoDL) project targets deep microbial ecosystems of three little explored (for microbiology), North American geological provinces: the Basin and Range, Black Hills, and Canadian Shield. Here we focus on the Basin and Range, specifically radioactive fluids from nuclear device test cavities (U12N.10 tunnel and ER-EC-11) at the Nevada National Security Site (NNSS) and non-radioactive samples from a deep dolomite aquifer associated with Death Valley, CA (BLM-1 and Nevares Deep Well 2). Six pyrotag sequencing runs were attempted at the Marine Biology Lab (MBL) (bacterial v6v4 amplification for all sites and archaeal v6v4 amplification for BLM-1 and Nevares DW2). Of these, DNA extracts from five samples (all but Nevares DW2 Arch) successfully amplified. Bacterial libraries were generally dominated by Proteobacteria, Firmicutes, and Nitrospirae (ER-EC-11: Proteobacteria (45%), Deinococcus-Thermus (35%), Firmicutes (15%); U12N.10: Proteobacteria (37%), Firmicutes (32%), Nitrospirae (15%), Bacteroidetes (11%); BLM-1 (Bact): Firmicutes (93%); and Nevares DW2: Firmicutes (51%), Proteobacteria (16%), Nitrospirae (15%)). The BLM-1 (Arch) library contained >99% Euryarchaeota, with 98% of sequences represented by a single uncharacterized species of Methanothermobacter. Alpha diversity was calculated using the MBL VAMPS (Visualization and Analysis of Microbial Population Structures) system; showing the highest richness at both the phylum and genus levels in U12N.10 (Sp = 42; Sg = 341), and the lowest (Sp = 3; Sg = 11) in the BLM-1(Arch) library. Diversity was covered well at this depth of sequencing (~20,000 reads per sample) based on rarefaction analysis. One Firmicute lineage, candidatus D. audaxviator, has been shown to dominate microbial communities from

Incident sequence analysis; event trees, methods and graphical symbols

International Nuclear Information System (INIS)

1980-11-01

When analyzing incident sequences, unwanted events resulting from a certain cause are looked for. Graphical symbols and explanations of graphical representations are presented. The method applies to the analysis of incident sequences in all types of facilities. By means of the incident sequence diagram, incident sequences, i.e. the logical and chronological course of repercussions initiated by the failure of a component or by an operating error, can be presented and analyzed simply and clearly

Accident Sequence Precursor Analysis for SGTR by Using Dynamic PSA Approach

International Nuclear Information System (INIS)

Lee, Han Sul; Heo, Gyun Young; Kim, Tae Wan

2016-01-01

In order to address this issue, this study suggests the sequence tree model to analyze accident sequence systematically. Using the sequence tree model, all possible scenarios which need a specific safety action to prevent the core damage can be identified and success conditions of safety action under complicated situation such as combined accident will be also identified. Sequence tree is branch model to divide plant condition considering the plant dynamics. Since sequence tree model can reflect the plant dynamics, arising from interaction of different accident timing and plant condition and from the interaction between the operator action, mitigation system, and the indicators for operation, sequence tree model can be used to develop the dynamic event tree model easily. Target safety action for this study is a feed-and-bleed (F and B) operation. A F and B operation directly cools down the reactor cooling system (RCS) using the primary cooling system when residual heat removal by the secondary cooling system is not available. In this study, a TLOFW accident and a TLOFW accident with LOCA were the target accidents. Based on the conventional PSA model and indicators, the sequence tree model for a TLOFW accident was developed. Based on the results of a sampling analysis and data from the conventional PSA model, the CDF caused by Sequence no. 26 can be realistically estimated. For a TLOFW accident with LOCA, second accident timings were categorized according to plant condition. Indicators were selected as branch point using the flow chart and tables, and a corresponding sequence tree model was developed. If sampling analysis is performed, practical accident sequences can be identified based on the sequence analysis. If a realistic distribution for the variables can be obtained for sampling analysis, much more realistic accident sequences can be described. Moreover, if the initiating event frequency under a combined accident can be quantified, the sequence tree model

CAFE: aCcelerated Alignment-FrEe sequence analysis.

Science.gov (United States)

Lu, Yang Young; Tang, Kujin; Ren, Jie; Fuhrman, Jed A; Waterman, Michael S; Sun, Fengzhu

2017-07-03

Alignment-free genome and metagenome comparisons are increasingly important with the development of next generation sequencing (NGS) technologies. Recently developed state-of-the-art k-mer based alignment-free dissimilarity measures including CVTree, $d_2^*$ and $d_2^S$ are more computationally expensive than measures based solely on the k-mer frequencies. Here, we report a standalone software, aCcelerated Alignment-FrEe sequence analysis (CAFE), for efficient calculation of 28 alignment-free dissimilarity measures. CAFE allows for both assembled genome sequences and unassembled NGS shotgun reads as input, and wraps the output in a standard PHYLIP format. In downstream analyses, CAFE can also be used to visualize the pairwise dissimilarity measures, including dendrograms, heatmap, principal coordinate analysis and network display. CAFE serves as a general k-mer based alignment-free analysis platform for studying the relationships among genomes and metagenomes, and is freely available at https://github.com/younglululu/CAFE. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Three-dimensional fluid-attenuated inversion recovery sequence for visualisation of subthalamic nucleus for deep brain stimulation in Parkinson's disease

Energy Technology Data Exchange (ETDEWEB)

Heo, Young Jin [University of Ulsan College of Medicine, Asan Medical Center, Department of Radiology, Research Institute of Radiology, Seoul (Korea, Republic of); Inje University, Department of Radiology, Busan Paik Hospital, Busan (Korea, Republic of); Kim, Sang Joon; Kim, Ho Sung; Choi, Choong Gon; Jung, Seung Chai [University of Ulsan College of Medicine, Asan Medical Center, Department of Radiology, Research Institute of Radiology, Seoul (Korea, Republic of); Lee, Jung Kyo [University of Ulsan College of Medicine, Asan Medical Center, Department of Neurosurgery, Seoul (Korea, Republic of); Lee, Chong Sik; Chung, Sun J. [University of Ulsan College of Medicine, Asan Medical Center, Department of Neurology, Seoul (Korea, Republic of); Cho, So Hyun [Department of Radiology, Busan (Korea, Republic of); Lee, Gyoung Ro [Philips HealthCare Korea, Seoul (Korea, Republic of)

2015-09-15

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an accepted treatment for advanced Parkinson's disease (PD). However, targeting the STN is difficult due to its relatively small size and variable location. The purpose of this study was to assess which of the following sequences obtained with the 3.0 T MR system can accurately delineate the STN: coronal 3D fluid-attenuated inversion recovery (FLAIR), 2D T2*-weighted fast-field echo (T2*-FFE) and 2D T2-weighted turbo spin-echo (TSE) sequences. We included 20 consecutive patients with PD who underwent 3.0 T MR for DBS targeting. 3D FLAIR, 2D T2*-FFE and T2-TSE images were obtained for all study patients. Image quality and demarcation of the STN were analysed using 4-point scales, and contrast ratio (CR) of the STN and normal white matter was calculated. The Friedman test was used to compare the three sequences. In qualitative analysis, the 2D T2*-FFE image showed more artefacts than 3D FLAIR or 2D T2-TSE, but the difference did not reach statistical significance. 3D FLAIR images showed significantly superior demarcation of the STN compared with 2D T2*-FFE and T2-TSE images (P < 0.001, respectively). The CR of 3D FLAIR was significantly higher than that of 2D T2*-FFE or T2-TSE images in multiple comparison correction (P < 0.001), but there was no significant difference in the CR between 2D T2*-FFE and T2-TSE images. Coronal 3D FLAIR images showed the most accurate demarcation of the STN for DBS targeting among coronal 3D FLAIR, 2D T2*-FFE and T2-TSE images. (orig.)

Three-dimensional fluid-attenuated inversion recovery sequence for visualisation of subthalamic nucleus for deep brain stimulation in Parkinson's disease

International Nuclear Information System (INIS)

Heo, Young Jin; Kim, Sang Joon; Kim, Ho Sung; Choi, Choong Gon; Jung, Seung Chai; Lee, Jung Kyo; Lee, Chong Sik; Chung, Sun J.; Cho, So Hyun; Lee, Gyoung Ro

2015-01-01

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an accepted treatment for advanced Parkinson's disease (PD). However, targeting the STN is difficult due to its relatively small size and variable location. The purpose of this study was to assess which of the following sequences obtained with the 3.0 T MR system can accurately delineate the STN: coronal 3D fluid-attenuated inversion recovery (FLAIR), 2D T2*-weighted fast-field echo (T2*-FFE) and 2D T2-weighted turbo spin-echo (TSE) sequences. We included 20 consecutive patients with PD who underwent 3.0 T MR for DBS targeting. 3D FLAIR, 2D T2*-FFE and T2-TSE images were obtained for all study patients. Image quality and demarcation of the STN were analysed using 4-point scales, and contrast ratio (CR) of the STN and normal white matter was calculated. The Friedman test was used to compare the three sequences. In qualitative analysis, the 2D T2*-FFE image showed more artefacts than 3D FLAIR or 2D T2-TSE, but the difference did not reach statistical significance. 3D FLAIR images showed significantly superior demarcation of the STN compared with 2D T2*-FFE and T2-TSE images (P < 0.001, respectively). The CR of 3D FLAIR was significantly higher than that of 2D T2*-FFE or T2-TSE images in multiple comparison correction (P < 0.001), but there was no significant difference in the CR between 2D T2*-FFE and T2-TSE images. Coronal 3D FLAIR images showed the most accurate demarcation of the STN for DBS targeting among coronal 3D FLAIR, 2D T2*-FFE and T2-TSE images. (orig.)

Deconstructing the genetic basis of spent sulphite liquor tolerance using deep sequencing of genome-shuffled yeast.

Science.gov (United States)

Pinel, Dominic; Colatriano, David; Jiang, Heng; Lee, Hung; Martin, Vincent Jj

2015-01-01

Identifying the genetic basis of complex microbial phenotypes is currently a major barrier to our understanding of multigenic traits and our ability to rationally design biocatalysts with highly specific attributes for the biotechnology industry. Here, we demonstrate that strain evolution by meiotic recombination-based genome shuffling coupled with deep sequencing can be used to deconstruct complex phenotypes and explore the nature of multigenic traits, while providing concrete targets for strain development. We determined genomic variations found within Saccharomyces cerevisiae previously evolved in our laboratory by genome shuffling for tolerance to spent sulphite liquor. The representation of these variations was backtracked through parental mutant pools and cross-referenced with RNA-seq gene expression analysis to elucidate the importance of single mutations and key biological processes that play a role in our trait of interest. Our findings pinpoint novel genes and biological determinants of lignocellulosic hydrolysate inhibitor tolerance in yeast. These include the following: protein homeostasis constituents, including Ubp7p and Art5p, related to ubiquitin-mediated proteolysis; stress response transcriptional repressor, Nrg1p; and NADPH-dependent glutamate dehydrogenase, Gdh1p. Reverse engineering a prominent mutation in ubiquitin-specific protease gene UBP7 in a laboratory S. cerevisiae strain effectively increased spent sulphite liquor tolerance. This study advances understanding of yeast tolerance mechanisms to inhibitory substrates and biocatalyst design for a biomass-to-biofuel/biochemical industry, while providing insights into the process of mutation accumulation that occurs during genome shuffling.

Deep Recurrent Convolutional Neural Network: Improving Performance For Speech Recognition

OpenAIRE

Zhang, Zewang; Sun, Zheng; Liu, Jiaqi; Chen, Jingwen; Huo, Zhao; Zhang, Xiao

2016-01-01

A deep learning approach has been widely applied in sequence modeling problems. In terms of automatic speech recognition (ASR), its performance has significantly been improved by increasing large speech corpus and deeper neural network. Especially, recurrent neural network and deep convolutional neural network have been applied in ASR successfully. Given the arising problem of training speed, we build a novel deep recurrent convolutional network for acoustic modeling and then apply deep resid...

Complete genome sequence of a Chinese isolate of pepper vein yellows virus and evolutionary analysis based on the CP, MP and RdRp coding regions.

Science.gov (United States)

Liu, Maoyan; Liu, Xiangning; Li, Xun; Zhang, Deyong; Dai, Liangyin; Tang, Qianjun

2016-03-01

The genome sequence of pepper vein yellows virus (PeVYV) (PeVYV-HN, accession number KP326573), isolated from pepper plants (Capsicum annuum L.) grown at the Hunan Vegetables Institute (Changsha, Hunan, China), was determined by deep sequencing of small RNAs. The PeVYV-HN genome consists of 6244 nucleotides, contains six open reading frames (ORFs), and is similar to that of an isolate (AB594828) from Japan. Its genomic organization is similar to that of members of the genus Polerovirus. Sequence analysis revealed that PeVYV-HN shared 92% sequence identity with the Japanese PeVYV genome at both the nucleotide and amino acid levels. Evolutionary analysis based on the coat protein (CP), movement protein (MP), and RNA-dependent RNA polymerase (RdRP) showed that PeVYV could be divided into two major lineages corresponding to their geographical origins. The Asian isolates have a higher population expansion frequency than the African isolates. Negative selection and genetic drift (founder effect) were found to be the potential drivers of the molecular evolution of PeVYV. Moreover, recombination was not the distinct cause of PeVYV evolution. This is the first report of a complete genomic sequence of PeVYV in China.

Bacterial Pathogens and Community Composition in Advanced Sewage Treatment Systems Revealed by Metagenomics Analysis Based on High-Throughput Sequencing

Science.gov (United States)

Lu, Xin; Zhang, Xu-Xiang; Wang, Zhu; Huang, Kailong; Wang, Yuan; Liang, Weigang; Tan, Yunfei; Liu, Bo; Tang, Junying

2015-01-01

This study used 454 pyrosequencing, Illumina high-throughput sequencing and metagenomic analysis to investigate bacterial pathogens and their potential virulence in a sewage treatment plant (STP) applying both conventional and advanced treatment processes. Pyrosequencing and Illumina sequencing consistently demonstrated that Arcobacter genus occupied over 43.42% of total abundance of potential pathogens in the STP. At species level, potential pathogens Arcobacter butzleri, Aeromonas hydrophila and Klebsiella pneumonia dominated in raw sewage, which was also confirmed by quantitative real time PCR. Illumina sequencing also revealed prevalence of various types of pathogenicity islands and virulence proteins in the STP. Most of the potential pathogens and virulence factors were eliminated in the STP, and the removal efficiency mainly depended on oxidation ditch. Compared with sand filtration, magnetic resin seemed to have higher removals in most of the potential pathogens and virulence factors. However, presence of the residual A. butzleri in the final effluent still deserves more concerns. The findings indicate that sewage acts as an important source of environmental pathogens, but STPs can effectively control their spread in the environment. Joint use of the high-throughput sequencing technologies is considered a reliable method for deep and comprehensive overview of environmental bacterial virulence. PMID:25938416

Arthropod phylogenetics in light of three novel millipede (myriapoda: diplopoda mitochondrial genomes with comments on the appropriateness of mitochondrial genome sequence data for inferring deep level relationships.

Directory of Open Access Journals (Sweden)

Michael S Brewer

Full Text Available BACKGROUND: Arthropods are the most diverse group of eukaryotic organisms, but their phylogenetic relationships are poorly understood. Herein, we describe three mitochondrial genomes representing orders of millipedes for which complete genomes had not been characterized. Newly sequenced genomes are combined with existing data to characterize the protein coding regions of myriapods and to attempt to reconstruct the evolutionary relationships within the Myriapoda and Arthropoda. RESULTS: The newly sequenced genomes are similar to previously characterized millipede sequences in terms of synteny and length. Unique translocations occurred within the newly sequenced taxa, including one half of the Appalachioria falcifera genome, which is inverted with respect to other millipede genomes. Across myriapods, amino acid conservation levels are highly dependent on the gene region. Additionally, individual loci varied in the level of amino acid conservation. Overall, most gene regions showed low levels of conservation at many sites. Attempts to reconstruct the evolutionary relationships suffered from questionable relationships and low support values. Analyses of phylogenetic informativeness show the lack of signal deep in the trees (i.e., genes evolve too quickly. As a result, the myriapod tree resembles previously published results but lacks convincing support, and, within the arthropod tree, well established groups were recovered as polyphyletic. CONCLUSIONS: The novel genome sequences described herein provide useful genomic information concerning millipede groups that had not been investigated. Taken together with existing sequences, the variety of compositions and evolution of myriapod mitochondrial genomes are shown to be more complex than previously thought. Unfortunately, the use of mitochondrial protein-coding regions in deep arthropod phylogenetics appears problematic, a result consistent with previously published studies. Lack of phylogenetic

Arthropod phylogenetics in light of three novel millipede (myriapoda: diplopoda) mitochondrial genomes with comments on the appropriateness of mitochondrial genome sequence data for inferring deep level relationships.

Science.gov (United States)

Brewer, Michael S; Swafford, Lynn; Spruill, Chad L; Bond, Jason E

2013-01-01

Arthropods are the most diverse group of eukaryotic organisms, but their phylogenetic relationships are poorly understood. Herein, we describe three mitochondrial genomes representing orders of millipedes for which complete genomes had not been characterized. Newly sequenced genomes are combined with existing data to characterize the protein coding regions of myriapods and to attempt to reconstruct the evolutionary relationships within the Myriapoda and Arthropoda. The newly sequenced genomes are similar to previously characterized millipede sequences in terms of synteny and length. Unique translocations occurred within the newly sequenced taxa, including one half of the Appalachioria falcifera genome, which is inverted with respect to other millipede genomes. Across myriapods, amino acid conservation levels are highly dependent on the gene region. Additionally, individual loci varied in the level of amino acid conservation. Overall, most gene regions showed low levels of conservation at many sites. Attempts to reconstruct the evolutionary relationships suffered from questionable relationships and low support values. Analyses of phylogenetic informativeness show the lack of signal deep in the trees (i.e., genes evolve too quickly). As a result, the myriapod tree resembles previously published results but lacks convincing support, and, within the arthropod tree, well established groups were recovered as polyphyletic. The novel genome sequences described herein provide useful genomic information concerning millipede groups that had not been investigated. Taken together with existing sequences, the variety of compositions and evolution of myriapod mitochondrial genomes are shown to be more complex than previously thought. Unfortunately, the use of mitochondrial protein-coding regions in deep arthropod phylogenetics appears problematic, a result consistent with previously published studies. Lack of phylogenetic signal renders the resulting tree topologies as suspect

Sequence-to-Sequence Prediction of Vehicle Trajectory via LSTM Encoder-Decoder Architecture

OpenAIRE

Park, Seong Hyeon; Kim, ByeongDo; Kang, Chang Mook; Chung, Chung Choo; Choi, Jun Won

2018-01-01

In this paper, we propose a deep learning based vehicle trajectory prediction technique which can generate the future trajectory sequence of surrounding vehicles in real time. We employ the encoder-decoder architecture which analyzes the pattern underlying in the past trajectory using the long short-term memory (LSTM) based encoder and generates the future trajectory sequence using the LSTM based decoder. This structure produces the $K$ most likely trajectory candidates over occupancy grid ma...

galaxie--CGI scripts for sequence identification through automated phylogenetic analysis.

Science.gov (United States)

Nilsson, R Henrik; Larsson, Karl-Henrik; Ursing, Björn M

2004-06-12

The prevalent use of similarity searches like BLAST to identify sequences and species implicitly assumes the reference database to be of extensive sequence sampling. This is often not the case, restraining the correctness of the outcome as a basis for sequence identification. Phylogenetic inference outperforms similarity searches in retrieving correct phylogenies and consequently sequence identities, and a project was initiated to design a freely available script package for sequence identification through automated Web-based phylogenetic analysis. Three CGI scripts were designed to facilitate qualified sequence identification from a Web interface. Query sequences are aligned to pre-made alignments or to alignments made by ClustalW with entries retrieved from a BLAST search. The subsequent phylogenetic analysis is based on the PHYLIP package for inferring neighbor-joining and parsimony trees. The scripts are highly configurable. A service installation and a version for local use are found at http://andromeda.botany.gu.se/galaxiewelcome.html and http://galaxie.cgb.ki.se

Sequence-specific bias correction for RNA-seq data using recurrent neural networks.

Science.gov (United States)

Zhang, Yao-Zhong; Yamaguchi, Rui; Imoto, Seiya; Miyano, Satoru

2017-01-25

The recent success of deep learning techniques in machine learning and artificial intelligence has stimulated a great deal of interest among bioinformaticians, who now wish to bring the power of deep learning to bare on a host of bioinformatical problems. Deep learning is ideally suited for biological problems that require automatic or hierarchical feature representation for biological data when prior knowledge is limited. In this work, we address the sequence-specific bias correction problem for RNA-seq data redusing Recurrent Neural Networks (RNNs) to model nucleotide sequences without pre-determining sequence structures. The sequence-specific bias of a read is then calculated based on the sequence probabilities estimated by RNNs, and used in the estimation of gene abundance. We explore the application of two popular RNN recurrent units for this task and demonstrate that RNN-based approaches provide a flexible way to model nucleotide sequences without knowledge of predetermined sequence structures. Our experiments show that training a RNN-based nucleotide sequence model is efficient and RNN-based bias correction methods compare well with the-state-of-the-art sequence-specific bias correction method on the commonly used MAQC-III data set. RNNs provides an alternative and flexible way to calculate sequence-specific bias without explicitly pre-determining sequence structures.

Sequence Quality Analysis Tool for HIV Type 1 Protease and Reverse Transcriptase

OpenAIRE

DeLong, Allison K.; Wu, Mingham; Bennett, Diane; Parkin, Neil; Wu, Zhijin; Hogan, Joseph W.; Kantor, Rami

2012-01-01

Access to antiretroviral therapy is increasing globally and drug resistance evolution is anticipated. Currently, protease (PR) and reverse transcriptase (RT) sequence generation is increasing, including the use of in-house sequencing assays, and quality assessment prior to sequence analysis is essential. We created a computational HIV PR/RT Sequence Quality Analysis Tool (SQUAT) that runs in the R statistical environment. Sequence quality thresholds are calculated from a large dataset (46,802...

Performance Analysis of High-Speed Deep/Shallow Recessed Hybrid Bearing

Directory of Open Access Journals (Sweden)

Lei Wang

2013-01-01

Full Text Available The present paper proposes a theoretical analysis of the performance of deep/shallow recessed hybrid bearing. It is intended that, on the basis of the numerical results drawn from this study, appropriate shallow recess depth and width can be determined for use in the bearing design process. By adopting bulk flow theory, the turbulent Reynolds equation and energy equation are modified and solved numerically including concentrated inertia effects at the recess edge with different depth and width of shallow recess. The results indicate that the load capacity, drag torque increases as the depth of shallow recess is shallower and the width ratio (half angle of deep recess versus half angle of shallow recess is smaller. In contrast, the flow rate decreases as the depth of shallow recess is shallower and the width ratio is smaller. Nevertheless, the appropriate design of the depth and width of shallow recess might well induce the performance of high-speed deep/shallow recessed hybrid bearing.

Integrative Data Analysis of Multi-Platform Cancer Data with a Multimodal Deep Learning Approach.

Science.gov (United States)

Liang, Muxuan; Li, Zhizhong; Chen, Ting; Zeng, Jianyang

2015-01-01

Identification of cancer subtypes plays an important role in revealing useful insights into disease pathogenesis and advancing personalized therapy. The recent development of high-throughput sequencing technologies has enabled the rapid collection of multi-platform genomic data (e.g., gene expression, miRNA expression, and DNA methylation) for the same set of tumor samples. Although numerous integrative clustering approaches have been developed to analyze cancer data, few of them are particularly designed to exploit both deep intrinsic statistical properties of each input modality and complex cross-modality correlations among multi-platform input data. In this paper, we propose a new machine learning model, called multimodal deep belief network (DBN), to cluster cancer patients from multi-platform observation data. In our integrative clustering framework, relationships among inherent features of each single modality are first encoded into multiple layers of hidden variables, and then a joint latent model is employed to fuse common features derived from multiple input modalities. A practical learning algorithm, called contrastive divergence (CD), is applied to infer the parameters of our multimodal DBN model in an unsupervised manner. Tests on two available cancer datasets show that our integrative data analysis approach can effectively extract a unified representation of latent features to capture both intra- and cross-modality correlations, and identify meaningful disease subtypes from multi-platform cancer data. In addition, our approach can identify key genes and miRNAs that may play distinct roles in the pathogenesis of different cancer subtypes. Among those key miRNAs, we found that the expression level of miR-29a is highly correlated with survival time in ovarian cancer patients. These results indicate that our multimodal DBN based data analysis approach may have practical applications in cancer pathogenesis studies and provide useful guidelines for

Sequence Matching Analysis for Curriculum Development

Directory of Open Access Journals (Sweden)

Liem Yenny Bendatu

2015-06-01

Full Text Available Many organizations apply information technologies to support their business processes. Using the information technologies, the actual events are recorded and utilized to conform with predefined model. Conformance checking is an approach to measure the fitness and appropriateness between process model and actual events. However, when there are multiple events with the same timestamp, the traditional approach unfit to result such measures. This study attempts to develop a sequence matching analysis. Considering conformance checking as the basis of this approach, this proposed approach utilizes the current control flow technique in process mining domain. A case study in the field of educational process has been conducted. This study also proposes a curriculum analysis framework to test the proposed approach. By considering the learning sequence of students, it results some measurements for curriculum development. Finally, the result of the proposed approach has been verified by relevant instructors for further development.

Analysis of xylem formation in pine by cDNA sequencing

Science.gov (United States)

Allona, I.; Quinn, M.; Shoop, E.; Swope, K.; St Cyr, S.; Carlis, J.; Riedl, J.; Retzel, E.; Campbell, M. M.; Sederoff, R.;

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.

Finite Element Analysis and Optimization for the Multi-stage Deep Drawing of Molybdenum Sheet

International Nuclear Information System (INIS)

Kim, Heung-Kyu; Hong, Seok Kwan; Kang, Jeong Jin; Heo, Young-moo; Lee, Jong-Kil; Jeon, Byung-Hee

2005-01-01

Molybdenum, a bcc refractory metal with a melting point of about 2600 deg. C, has a high heat and electrical conductivity. In addition, it remains strong mechanically at high temperatures as well as at low temperatures. Therefore it is a technologically very important material for the applications operating at high temperatures. However, a multi-stage process is required due to the low drawability for making a deep drawn part from the molybdenum sheet. In this study, a multi-stage deep drawing process for a molybdenum circular cup was designed by combining the drawing with the ironing, which was effective for the low drawability materials. A parametric study by FE analysis for the multi-stage deep drawing was conducted for evaluation of the design variables effect. Based on the FE analysis result, the multi-stage deep drawing process was parameterized by the design variables, and an optimum process design was obtained by the process optimization based on the FE simulation at each stage

Analysis of well test data from selected intervals in Leuggern deep borehole

International Nuclear Information System (INIS)

Karasaki, K.

1990-07-01

Applicability of the PTST technique was verified by conducting a sensitivity study to the various parameters. The study showed that for ranges of skin parameters the true formation permeability was still successfully estimated using the PTST analysis technique. The analysis technique was then applied to field data from the deep borehole in Leuggern, Northern Switzerland. The analysis indicated that the formation permeability may be as much as one order of magnitude larger than the value based on no-skin analysis. Swabbing data from the Leuggern deep borehole were also analyzed assuming that they are constant pressure tests. The analysis of the swabbing data indicates that the formation transmissivity is as much as 20 times larger than the previously obtained value. This study is part of an investigation of the feasibility of geologic isolation of nuclear wastes being carried out by the US Department of Energy and the National Cooperative for the Storage of Radioactive Waste of Switzerland

Detection of Weakly Conserved Ancestral Mammalian RegulatorySequences by Primate Comparisons

Energy Technology Data Exchange (ETDEWEB)

Wang, Qian-fei; Prabhakar, Shyam; Chanan, Sumita; Cheng,Jan-Fang; Rubin, Edward M.; Boffelli, Dario

2006-06-01

Genomic comparisons between human and distant, non-primatemammals are commonly used to identify cis-regulatory elements based onconstrained sequence evolution. However, these methods fail to detectcryptic functional elements, which are too weakly conserved among mammalsto distinguish from nonfunctional DNA. To address this problem, weexplored the potential of deep intra-primate sequence comparisons. Wesequenced the orthologs of 558 kb of human genomic sequence, coveringmultiple loci involved in cholesterol homeostasis, in 6 nonhumanprimates. Our analysis identified 6 noncoding DNA elements displayingsignificant conservation among primates, but undetectable in more distantcomparisons. In vitro and in vivo tests revealed that at least three ofthese 6 elements have regulatory function. Notably, the mouse orthologsof these three functional human sequences had regulatory activity despitetheir lack of significant sequence conservation, indicating that they arecryptic ancestral cis-regulatory elements. These regulatory elementscould still be detected in a smaller set of three primate speciesincluding human, rhesus and marmoset. Since the human and rhesus genomesequences are already available, and the marmoset genome is activelybeing sequenced, the primate-specific conservation analysis describedhere can be applied in the near future on a whole-genome scale, tocomplement the annotation provided by more distant speciescomparisons.

Coupling Deep Transcriptome Analysis with Untargeted Metabolic Profiling in Ophiorrhiza pumila to Further the Understanding of the Biosynthesis of the Anti-Cancer Alkaloid Camptothecin and Anthraquinones

Science.gov (United States)

Yamazaki, Mami; Mochida, Keiichi; Asano, Takashi; Nakabayashi, Ryo; Chiba, Motoaki; Udomson, Nirin; Yamazaki, Yasuyo; Goodenowe, Dayan B.; Sankawa, Ushio; Yoshida, Takuhiro; Toyoda, Atsushi; Totoki, Yasushi; Sakaki, Yoshiyuki; Góngora-Castillo, Elsa; Buell, C. Robin; Sakurai, Tetsuya; Saito, Kazuki

2013-01-01

The Rubiaceae species, Ophiorrhiza pumila, accumulates camptothecin, an anti-cancer alkaloid with a potent DNA topoisomerase I inhibitory activity, as well as anthraquinones that are derived from the combination of the isochorismate and hemiterpenoid pathways. The biosynthesis of these secondary products is active in O. pumila hairy roots yet very low in cell suspension culture. Deep transcriptome analysis was conducted in O. pumila hairy roots and cell suspension cultures using the Illumina platform, yielding a total of 2 Gb of sequence for each sample. We generated a hybrid transcriptome assembly of O. pumila using the Illumina-derived short read sequences and conventional Sanger-derived expressed sequence tag clones derived from a full-length cDNA library constructed using RNA from hairy roots. Among 35,608 non-redundant unigenes, 3,649 were preferentially expressed in hairy roots compared with cell suspension culture. Candidate genes involved in the biosynthetic pathway for the monoterpenoid indole alkaloid camptothecin were identified; specifically, genes involved in post-strictosamide biosynthetic events and genes involved in the biosynthesis of anthraquinones and chlorogenic acid. Untargeted metabolomic analysis by Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) indicated that most of the proposed intermediates in the camptothecin biosynthetic pathway accumulated in hairy roots in a preferential manner compared with cell suspension culture. In addition, a number of anthraquinones and chlorogenic acid preferentially accumulated in hairy roots compared with cell suspension culture. These results suggest that deep transcriptome and metabolome data sets can facilitate the identification of genes and intermediates involved in the biosynthesis of secondary products including camptothecin in O. pumila. PMID:23503598

Microbiome analysis of a disease affecting the deep-sea sponge Geodia barretti.

Science.gov (United States)

Luter, Heidi M; Bannister, Raymond J; Whalan, Steve; Kutti, Tina; Pineda, Mari-Carmen; Webster, Nicole S

2017-05-24

Reports of sponge disease are becoming increasingly frequent, although almost all instances involve shallow-water, tropical species. Here, we describe the first disease affecting the deep-water sponge, Geodia barretti. The disease is characterised by brown/black discolouration of the sponge tissue, extensive levels of tissue disintegration and increased levels of fouling. Disease prevalence was quantified using video survey transects conducted between 100 and 220 meters in Korsfjorden, Norway and the microbial communities of healthy and diseased sponges were compared using 16S rRNA gene sequencing. Highly divergent community profiles were evident between the different health states; with distinct community shifts involving higher relative abundances of Bacteroidetes, Firmicutes and Deltaproteobacteria in diseased individuals. In addition, three Operational Taxonomic Units (OTUs) were exclusively present in diseased individuals and were shared between the disease lesions and the apparently healthy tissue of diseased individuals, suggesting a non-localised infection or dysbiosis. Genomic analysis of the G. barretti microbiome combined with experimental work to assess the mechanisms of infection will further elucidate the role of microorganisms in the disease. © FEMS 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Validation of Genotyping-By-Sequencing Analysis in Populations of Tetraploid Alfalfa by 454 Sequencing

Science.gov (United States)

Rocher, Solen; Jean, Martine; Castonguay, Yves; Belzile, François

2015-01-01

Genotyping-by-sequencing (GBS) is a relatively low-cost high throughput genotyping technology based on next generation sequencing and is applicable to orphan species with no reference genome. A combination of genome complexity reduction and multiplexing with DNA barcoding provides a simple and affordable way to resolve allelic variation between plant samples or populations. GBS was performed on ApeKI libraries using DNA from 48 genotypes each of two heterogeneous populations of tetraploid alfalfa (Medicago sativa spp. sativa): the synthetic cultivar Apica (ATF0) and a derived population (ATF5) obtained after five cycles of recurrent selection for superior tolerance to freezing (TF). Nearly 400 million reads were obtained from two lanes of an Illumina HiSeq 2000 sequencer and analyzed with the Universal Network-Enabled Analysis Kit (UNEAK) pipeline designed for species with no reference genome. Following the application of whole dataset-level filters, 11,694 single nucleotide polymorphism (SNP) loci were obtained. About 60% had a significant match on the Medicago truncatula syntenic genome. The accuracy of allelic ratios and genotype calls based on GBS data was directly assessed using 454 sequencing on a subset of SNP loci scored in eight plant samples. Sequencing depth in this study was not sufficient for accurate tetraploid allelic dosage, but reliable genotype calls based on diploid allelic dosage were obtained when using additional quality filtering. Principal Component Analysis of SNP loci in plant samples revealed that a small proportion (<5%) of the genetic variability assessed by GBS is able to differentiate ATF0 and ATF5. Our results confirm that analysis of GBS data using UNEAK is a reliable approach for genome-wide discovery of SNP loci in outcrossed polyploids. PMID:26115486

Deep Sequence Analysis of Non-Small Cell Lung Cancer: Integrated Analysis of Gene Expression, Alternative Splicing, and Single Nucleotide Variations in Lung Adenocarcinomas with and without Oncogenic KRAS Mutations

International Nuclear Information System (INIS)

Kalari, Krishna R.; Rossell, David; Necela, Brian M.; Asmann, Yan W.; Nair, Asha

2012-01-01

KRAS mutations are highly prevalent in non-small cell lung cancer (NSCLC), and tumors harboring these mutations tend to be aggressive and resistant to chemotherapy. We used next-generation sequencing technology to identify pathways that are specifically altered in lung tumors harboring a KRAS mutation. Paired-end RNA-sequencing of 15 primary lung adenocarcinoma tumors (8 harboring mutant KRAS and 7 with wild-type KRAS) were performed. Sequences were mapped to the human genome, and genomic features, including differentially expressed genes, alternate splicing isoforms and single nucleotide variants, were determined for tumors with and without KRAS mutation using a variety of computational methods. Network analysis was carried out on genes showing differential expression (374 genes), alternate splicing (259 genes), and SNV-related changes (65 genes) in NSCLC tumors harboring a KRAS mutation. Genes exhibiting two or more connections from the lung adenocarcinoma network were used to carry out integrated pathway analysis. The most significant signaling pathways identified through this analysis were the NFκB, ERK1/2, and AKT pathways. A 27 gene mutant KRAS-specific sub network was extracted based on gene–gene connections from the integrated network, and interrogated for druggable targets. Our results confirm previous evidence that mutant KRAS tumors exhibit activated NFκB, ERK1/2, and AKT pathways and may be preferentially sensitive to target therapeutics toward these pathways. In addition, our analysis indicates novel, previously unappreciated links between mutant KRAS and the TNFR and PPARγ signaling pathways, suggesting that targeted PPARγ antagonists and TNFR inhibitors may be useful therapeutic strategies for treatment of mutant KRAS lung tumors. Our study is the first to integrate genomic features from RNA-Seq data from NSCLC and to define a first draft genomic landscape model that is unique to tumors with oncogenic KRAS mutations.

Species-level analysis of DNA sequence data from the NIH Human Microbiome Project.

Directory of Open Access Journals (Sweden)

Sean Conlan

Full Text Available BACKGROUND: Outbreaks of antibiotic-resistant bacterial infections emphasize the importance of surveillance of potentially pathogenic bacteria. Genomic sequencing of clinical microbiological specimens expands our capacity to study cultivable, fastidious and uncultivable members of the bacterial community. Herein, we compared the primary data collected by the NIH's Human Microbiome Project (HMP with published epidemiological surveillance data of Staphylococcus aureus. METHODS: The HMP's initial dataset contained microbial survey data from five body regions (skin, nares, oral cavity, gut and vagina of 242 healthy volunteers. A significant component of the HMP dataset was deep sequencing of the 16S ribosomal RNA gene, which contains variable regions enabling taxonomic classification. Since species-level identification is essential in clinical microbiology, we built a reference database and used phylogenetic placement followed by most recent common ancestor classification to look at the species distribution for Staphylococcus, Klebsiella and Enterococcus. MAIN RESULTS: We show that selecting the accurate region of the 16S rRNA gene to sequence is analogous to carefully selecting culture conditions to distinguish closely related bacterial species. Analysis of the HMP data showed that Staphylococcus aureus was present in the nares of 36% of healthy volunteers, consistent with culture-based epidemiological data. Klebsiella pneumoniae and Enterococcus faecalis were found less frequently, but across many habitats. CONCLUSIONS: This work demonstrates that large 16S rRNA survey studies can be used to support epidemiological goals in the context of an increasing awareness that microbes flourish and compete within a larger bacterial community. This study demonstrates how genomic techniques and information could be critically important to trace microbial evolution and implement hospital infection control.

Inspecting Targeted Deep Sequencing of Whole Genome Amplified DNA Versus Fresh DNA for Somatic Mutation Detection: A Genetic Study in Myelodysplastic Syndrome Patients.

Science.gov (United States)

Palomo, Laura; Fuster-Tormo, Francisco; Alvira, Daniel; Ademà, Vera; Armengol, María Pilar; Gómez-Marzo, Paula; de Haro, Nuri; Mallo, Mar; Xicoy, Blanca; Zamora, Lurdes; Solé, Francesc

2017-08-01

Whole genome amplification (WGA) has become an invaluable method for preserving limited samples of precious stock material and has been used during the past years as an alternative tool to increase the amount of DNA before library preparation for next-generation sequencing. Myelodysplastic syndromes (MDS) are a group of clonal hematopoietic stem cell disorders characterized by presenting somatic mutations in several myeloid-related genes. In this work, targeted deep sequencing has been performed on four paired fresh DNA and WGA DNA samples from bone marrow of MDS patients, to assess the feasibility of using WGA DNA for detecting somatic mutations. The results of this study highlighted that, in general, the sequencing and alignment statistics of fresh DNA and WGA DNA samples were similar. However, after variant calling and when considering variants detected at all frequencies, there was a high level of discordance between fresh DNA and WGA DNA (overall, a higher number of variants was detected in WGA DNA). After proper filtering, a total of three somatic mutations were detected in the cohort. All somatic mutations detected in fresh DNA were also identified in WGA DNA and validated by whole exome sequencing.

Digital image sequence processing, compression, and analysis

CERN Document Server

Reed, Todd R

2004-01-01

IntroductionTodd R. ReedCONTENT-BASED IMAGE SEQUENCE REPRESENTATIONPedro M. Q. Aguiar, Radu S. Jasinschi, José M. F. Moura, andCharnchai PluempitiwiriyawejTHE COMPUTATION OF MOTIONChristoph Stiller, Sören Kammel, Jan Horn, and Thao DangMOTION ANALYSIS AND DISPLACEMENT ESTIMATION IN THE FREQUENCY DOMAINLuca Lucchese and Guido Maria CortelazzoQUALITY OF SERVICE ASSESSMENT IN NEW GENERATION WIRELESS VIDEO COMMUNICATIONSGaetano GiuntaERROR CONCEALMENT IN DIGITAL VIDEOFrancesco G.B. De NataleIMAGE SEQUENCE RESTORATION: A WIDER PERSPECTIVEAnil KokaramVIDEO SUMMARIZATIONCuneyt M. Taskiran and Edward

Deep sequencing as a method of typing bluetongue virus isolates.

Science.gov (United States)

Rao, Pavuluri Panduranga; Reddy, Yella Narasimha; Ganesh, Kapila; Nair, Shreeja G; Niranjan, Vidya; Hegde, Nagendra R

2013-11-01

Bluetongue (BT) is an economically important endemic disease of livestock in tropics and subtropics. In addition, its recent spread to temperate regions like North America and Northern Europe is of serious concern. Rapid serotyping and characterization of BT virus (BTV) is an essential step in the identification of origin of the virus and for controlling the disease. Serotyping of BTV is typically performed by serum neutralization, and of late by nucleotide sequencing. This report describes the near complete genome sequencing and typing of two isolates of BTV using Illumina next generation sequencing platform. Two of the BTV RNAs were multiplexed with ten other unknown samples. Viral RNA was isolated and fragmented, reverse transcribed, the cDNA ends were repaired and ligated with a multiplex oligo. The genome library was amplified using primers complementary to the ligated oligo and subjected to single and paired end sequencing. The raw reads were assembled using a de novo method and reference-based assembly was performed based on the contig data. Near complete sequences of all segments of BTV were obtained with more than 20× coverage, and single read sequencing method was sufficient to identify the genotype and serotype of the virus. The two viruses used in this study were typed as BTV-1 and BTV-9E. Copyright © 2013 Elsevier B.V. All rights reserved.

Cloning and sequence analysis of benzo-a-pyreneinducible ...

African Journals Online (AJOL)

The phylogenetic tree based on the amino acid sequences clearly shows tilapia CYP1A and killifish CYP1A to be more closely related to each other than to the other CYP1A subfamilies. Sequence analysis of 3727 bp of genomic DNA showed that the clone obtained was the structural gene of CYP1A which consists of ...

Tensor-Dictionary Learning with Deep Kruskal-Factor Analysis

Energy Technology Data Exchange (ETDEWEB)

Stevens, Andrew J.; Pu, Yunchen; Sun, Yannan; Spell, Gregory; Carin, Lawrence

2017-04-20

We introduce new dictionary learning methods for tensor-variate data of any order. We represent each data item as a sum of Kruskal decomposed dictionary atoms within the framework of beta-process factor analysis (BPFA). Our model is nonparametric and can infer the tensor-rank of each dictionary atom. This Kruskal-Factor Analysis (KFA) is a natural generalization of BPFA. We also extend KFA to a deep convolutional setting and develop online learning methods. We test our approach on image processing and classification tasks achieving state of the art results for 2D & 3D inpainting and Caltech 101. The experiments also show that atom-rank impacts both overcompleteness and sparsity.

The Transcriptome of Compatible and Incompatible Interactions of Potato (Solanum tuberosum) with Phytophthora infestans Revealed by DeepSAGE Analysis

DEFF Research Database (Denmark)

Gyetvai, Gabor; Sønderkær, Mads; Göbel, Ulrike

2012-01-01

of the compatible and incompatible interaction were captured by DeepSAGE analysis of 44 biological samples comprising five genotypes, differing only by the presence or absence of the R1 transgene, three infection time points and three biological replicates. 30.859 unique 21 base pair sequence tags were obtained......Late blight, caused by the oomycete Phytophthora infestans, is the most important disease of potato (Solanum tuberosum). Understanding the molecular basis of resistance and susceptibility to late blight is therefore highly relevant for developing resistant cultivars, either by marker...... interactions over the infection time course and between compatible and incompatible genotypes. Transcriptional changes were more numerous in compatible than in incompatible interactions. In contrast to incompatible interactions, transcriptional changes in the compatible interaction were observed predominantly...

System-level hazard analysis using the sequence-tree method

International Nuclear Information System (INIS)

Huang, H.-W.; Shih Chunkuan; Yih Swu; Chen, M.-H.

2008-01-01

A system-level PHA using the sequence-tree method is presented to perform safety-related digital I and C system SSA. The conventional PHA involves brainstorming among experts on various portions of the system to identify hazards through discussions. However, since the conventional PHA is not a systematic technique, the analysis results depend strongly on the experts' subjective opinions. The quality of analysis cannot be appropriately controlled. Therefore, this study presents a system-level sequence tree based PHA, which can clarify the relationship among the major digital I and C systems. This sequence-tree-based technique has two major phases. The first phase adopts a table to analyze each event in SAR Chapter 15 for a specific safety-related I and C system, such as RPS. The second phase adopts a sequence tree to recognize the I and C systems involved in the event, the working of the safety-related systems and how the backup systems can be activated to mitigate the consequence if the primary safety systems fail. The defense-in-depth echelons, namely the Control echelon, Reactor trip echelon, ESFAS echelon and Monitoring and indicator echelon, are arranged to build the sequence-tree structure. All the related I and C systems, including the digital systems and the analog back-up systems, are allocated in their specific echelons. This system-centric sequence-tree analysis not only systematically identifies preliminary hazards, but also vulnerabilities in a nuclear power plant. Hence, an effective simplified D3 evaluation can also be conducted

WebMGA: a customizable web server for fast metagenomic sequence analysis.

Science.gov (United States)

Wu, Sitao; Zhu, Zhengwei; Fu, Liming; Niu, Beifang; Li, Weizhong

2011-09-07

The new field of metagenomics studies microorganism communities by culture-independent sequencing. With the advances in next-generation sequencing techniques, researchers are facing tremendous challenges in metagenomic data analysis due to huge quantity and high complexity of sequence data. Analyzing large datasets is extremely time-consuming; also metagenomic annotation involves a wide range of computational tools, which are difficult to be installed and maintained by common users. The tools provided by the few available web servers are also limited and have various constraints such as login requirement, long waiting time, inability to configure pipelines etc. We developed WebMGA, a customizable web server for fast metagenomic analysis. WebMGA includes over 20 commonly used tools such as ORF calling, sequence clustering, quality control of raw reads, removal of sequencing artifacts and contaminations, taxonomic analysis, functional annotation etc. WebMGA provides users with rapid metagenomic data analysis using fast and effective tools, which have been implemented to run in parallel on our local computer cluster. Users can access WebMGA through web browsers or programming scripts to perform individual analysis or to configure and run customized pipelines. WebMGA is freely available at http://weizhongli-lab.org/metagenomic-analysis. WebMGA offers to researchers many fast and unique tools and great flexibility for complex metagenomic data analysis.

WebMGA: a customizable web server for fast metagenomic sequence analysis

Directory of Open Access Journals (Sweden)

Niu Beifang

2011-09-01

Full Text Available Abstract Background The new field of metagenomics studies microorganism communities by culture-independent sequencing. With the advances in next-generation sequencing techniques, researchers are facing tremendous challenges in metagenomic data analysis due to huge quantity and high complexity of sequence data. Analyzing large datasets is extremely time-consuming; also metagenomic annotation involves a wide range of computational tools, which are difficult to be installed and maintained by common users. The tools provided by the few available web servers are also limited and have various constraints such as login requirement, long waiting time, inability to configure pipelines etc. Results We developed WebMGA, a customizable web server for fast metagenomic analysis. WebMGA includes over 20 commonly used tools such as ORF calling, sequence clustering, quality control of raw reads, removal of sequencing artifacts and contaminations, taxonomic analysis, functional annotation etc. WebMGA provides users with rapid metagenomic data analysis using fast and effective tools, which have been implemented to run in parallel on our local computer cluster. Users can access WebMGA through web browsers or programming scripts to perform individual analysis or to configure and run customized pipelines. WebMGA is freely available at http://weizhongli-lab.org/metagenomic-analysis. Conclusions WebMGA offers to researchers many fast and unique tools and great flexibility for complex metagenomic data analysis.

Noncoding sequence classification based on wavelet transform analysis: part I

Science.gov (United States)

Paredes, O.; Strojnik, M.; Romo-Vázquez, R.; Vélez Pérez, H.; Ranta, R.; Garcia-Torales, G.; Scholl, M. K.; Morales, J. A.

2017-09-01

DNA sequences in human genome can be divided into the coding and noncoding ones. Coding sequences are those that are read during the transcription. The identification of coding sequences has been widely reported in literature due to its much-studied periodicity. Noncoding sequences represent the majority of the human genome. They play an important role in gene regulation and differentiation among the cells. However, noncoding sequences do not exhibit periodicities that correlate to their functions. The ENCODE (Encyclopedia of DNA elements) and Epigenomic Roadmap Project projects have cataloged the human noncoding sequences into specific functions. We study characteristics of noncoding sequences with wavelet analysis of genomic signals.

Testing genotyping strategies for ultra-deep sequencing of a co-amplifying gene family: MHC class I in a passerine bird.

Science.gov (United States)

Biedrzycka, Aleksandra; Sebastian, Alvaro; Migalska, Magdalena; Westerdahl, Helena; Radwan, Jacek

2017-07-01

Characterization of highly duplicated genes, such as genes of the major histocompatibility complex (MHC), where multiple loci often co-amplify, has until recently been hindered by insufficient read depths per amplicon. Here, we used ultra-deep Illumina sequencing to resolve genotypes at exon 3 of MHC class I genes in the sedge warbler (Acrocephalus schoenobaenus). We sequenced 24 individuals in two replicates and used this data, as well as a simulated data set, to test the effect of amplicon coverage (range: 500-20 000 reads per amplicon) on the repeatability of genotyping using four different genotyping approaches. A third replicate employed unique barcoding to assess the extent of tag jumping, that is swapping of individual tag identifiers, which may confound genotyping. The reliability of MHC genotyping increased with coverage and approached or exceeded 90% within-method repeatability of allele calling at coverages of >5000 reads per amplicon. We found generally high agreement between genotyping methods, especially at high coverages. High reliability of the tested genotyping approaches was further supported by our analysis of the simulated data set, although the genotyping approach relying primarily on replication of variants in independent amplicons proved sensitive to repeatable errors. According to the most repeatable genotyping method, the number of co-amplifying variants per individual ranged from 19 to 42. Tag jumping was detectable, but at such low frequencies that it did not affect the reliability of genotyping. We thus demonstrate that gene families with many co-amplifying genes can be reliably genotyped using HTS, provided that there is sufficient per amplicon coverage. © 2016 John Wiley & Sons Ltd.

Illumina sequencing-based analysis of a microbial community enriched under anaerobic methane oxidation condition coupled to denitrification revealed coexistence of aerobic and anaerobic methanotrophs.

Science.gov (United States)

Siniscalchi, Luciene Alves Batista; Leite, Laura Rabelo; Oliveira, Guilherme; Chernicharo, Carlos Augusto Lemos; de Araújo, Juliana Calabria

2017-07-01

Methane is produced in anaerobic environments, such as reactors used to treat wastewaters, and can be consumed by methanotrophs. The composition and structure of a microbial community enriched from anaerobic sewage sludge under methane-oxidation condition coupled to denitrification were investigated. Denaturing gradient gel electrophoresis (DGGE) analysis retrieved sequences of Methylocaldum and Chloroflexi. Deep sequencing analysis revealed a complex community that changed over time and was affected by methane concentration. Methylocaldum (8.2%), Methylosinus (2.3%), Methylomonas (0.02%), Methylacidiphilales (0.45%), Nitrospirales (0.18%), and Methanosarcinales (0.3%) were detected. Despite denitrifying conditions provided, Nitrospirales and Methanosarcinales, known to perform anaerobic methane oxidation coupled to denitrification (DAMO) process, were in very low abundance. Results demonstrated that aerobic and anaerobic methanotrophs coexisted in the reactor together with heterotrophic microorganisms, suggesting that a diverse microbial community was important to sustain methanotrophic activity. The methanogenic sludge was a good inoculum to enrich methanotrophs, and cultivation conditions play a selective role in determining community composition.

Energy consumption analysis of the Venus Deep Space Station (DSS-13)

Science.gov (United States)

Hayes, N. V.

1983-01-01

This report continues the energy consumption analysis and verification study of the tracking stations of the Goldstone Deep Space Communications Complex, and presents an audit of the Venus Deep Space Station (DSS 13). Due to the non-continuous radioastronomy research and development operations at the station, estimations of energy usage were employed in the energy consumption simulation of both the 9-meter and 26-meter antenna buildings. A 17.9% decrease in station energy consumption was experienced over the 1979-1981 years under study. A comparison of the ECP computer simulations and the station's main watt-hour meter readings showed good agreement.

Quantiprot - a Python package for quantitative analysis of protein sequences.

Science.gov (United States)

Konopka, Bogumił M; Marciniak, Marta; Dyrka, Witold

2017-07-17

The field of protein sequence analysis is dominated by tools rooted in substitution matrices and alignments. A complementary approach is provided by methods of quantitative characterization. A major advantage of the approach is that quantitative properties defines a multidimensional solution space, where sequences can be related to each other and differences can be meaningfully interpreted. Quantiprot is a software package in Python, which provides a simple and consistent interface to multiple methods for quantitative characterization of protein sequences. The package can be used to calculate dozens of characteristics directly from sequences or using physico-chemical properties of amino acids. Besides basic measures, Quantiprot performs quantitative analysis of recurrence and determinism in the sequence, calculates distribution of n-grams and computes the Zipf's law coefficient. We propose three main fields of application of the Quantiprot package. First, quantitative characteristics can be used in alignment-free similarity searches, and in clustering of large and/or divergent sequence sets. Second, a feature space defined by quantitative properties can be used in comparative studies of protein families and organisms. Third, the feature space can be used for evaluating generative models, where large number of sequences generated by the model can be compared to actually observed sequences.

Recurrence time statistics: versatile tools for genomic DNA sequence analysis.

Science.gov (United States)

Cao, Yinhe; Tung, Wen-Wen; Gao, J B

2004-01-01

With the completion of the human and a few model organisms' genomes, and the genomes of many other organisms waiting to be sequenced, it has become increasingly important to develop faster computational tools which are capable of easily identifying the structures and extracting features from DNA sequences. One of the more important structures in a DNA sequence is repeat-related. Often they have to be masked before protein coding regions along a DNA sequence are to be identified or redundant expressed sequence tags (ESTs) are to be sequenced. Here we report a novel recurrence time based method for sequence analysis. The method can conveniently study all kinds of periodicity and exhaustively find all repeat-related features from a genomic DNA sequence. An efficient codon index is also derived from the recurrence time statistics, which has the salient features of being largely species-independent and working well on very short sequences. Efficient codon indices are key elements of successful gene finding algorithms, and are particularly useful for determining whether a suspected EST belongs to a coding or non-coding region. We illustrate the power of the method by studying the genomes of E. coli, the yeast S. cervisivae, the nematode worm C. elegans, and the human, Homo sapiens. Computationally, our method is very efficient. It allows us to carry out analysis of genomes on the whole genomic scale by a PC.

ComplexContact: a web server for inter-protein contact prediction using deep learning

KAUST Repository

Zeng, Hong; Wang, Sheng; Zhou, Tianming; Zhao, Feifeng; Li, Xiufeng; Wu, Qing; Xu, Jinbo

2018-01-01

ComplexContact (http://raptorx2.uchicago.edu/ComplexContact/) is a web server for sequence-based interfacial residue-residue contact prediction of a putative protein complex. Interfacial residue-residue contacts are critical for understanding how proteins form complex and interact at residue level. When receiving a pair of protein sequences, ComplexContact first searches for their sequence homologs and builds two paired multiple sequence alignments (MSA), then it applies co-evolution analysis and a CASP-winning deep learning (DL) method to predict interfacial contacts from paired MSAs and visualizes the prediction as an image. The DL method was originally developed for intra-protein contact prediction and performed the best in CASP12. Our large-scale experimental test further shows that ComplexContact greatly outperforms pure co-evolution methods for inter-protein contact prediction, regardless of the species.

ComplexContact: a web server for inter-protein contact prediction using deep learning

KAUST Repository

Zeng, Hong

2018-05-20

ComplexContact (http://raptorx2.uchicago.edu/ComplexContact/) is a web server for sequence-based interfacial residue-residue contact prediction of a putative protein complex. Interfacial residue-residue contacts are critical for understanding how proteins form complex and interact at residue level. When receiving a pair of protein sequences, ComplexContact first searches for their sequence homologs and builds two paired multiple sequence alignments (MSA), then it applies co-evolution analysis and a CASP-winning deep learning (DL) method to predict interfacial contacts from paired MSAs and visualizes the prediction as an image. The DL method was originally developed for intra-protein contact prediction and performed the best in CASP12. Our large-scale experimental test further shows that ComplexContact greatly outperforms pure co-evolution methods for inter-protein contact prediction, regardless of the species.

ComplexContact: a web server for inter-protein contact prediction using deep learning.

Science.gov (United States)

Zeng, Hong; Wang, Sheng; Zhou, Tianming; Zhao, Feifeng; Li, Xiufeng; Wu, Qing; Xu, Jinbo

2018-05-22

ComplexContact (http://raptorx2.uchicago.edu/ComplexContact/) is a web server for sequence-based interfacial residue-residue contact prediction of a putative protein complex. Interfacial residue-residue contacts are critical for understanding how proteins form complex and interact at residue level. When receiving a pair of protein sequences, ComplexContact first searches for their sequence homologs and builds two paired multiple sequence alignments (MSA), then it applies co-evolution analysis and a CASP-winning deep learning (DL) method to predict interfacial contacts from paired MSAs and visualizes the prediction as an image. The DL method was originally developed for intra-protein contact prediction and performed the best in CASP12. Our large-scale experimental test further shows that ComplexContact greatly outperforms pure co-evolution methods for inter-protein contact prediction, regardless of the species.

RESEARCH NOTE Genome-based exome-sequencing analysis ...

Indian Academy of Sciences (India)

Navya

2017-02-22

Feb 22, 2017 ... Genome-based exome-sequencing analysis identifies GYG1, DIS3L, DDRGK1 genes ... Cardiology Division, Department of Internal Medicine, Severance .... with p values of <0.05 byanalyzing differences in allele distribution.

Diverse deep-sea fungi from the South China Sea and their antimicrobial activity.

Science.gov (United States)

Zhang, Xiao-Yong; Zhang, Yun; Xu, Xin-Ya; Qi, Shu-Hua

2013-11-01

We investigated the diversity of fungal communities in nine different deep-sea sediment samples of the South China Sea by culture-dependent methods followed by analysis of fungal internal transcribed spacer (ITS) sequences. Although 14 out of 27 identified species were reported in a previous study, 13 species were isolated from sediments of deep-sea environments for the first report. Moreover, these ITS sequences of six isolates shared 84-92 % similarity with their closest matches in GenBank, which suggested that they might be novel phylotypes of genera Ajellomyces, Podosordaria, Torula, and Xylaria. The antimicrobial activities of these fungal isolates were explored using a double-layer technique. A relatively high proportion (56 %) of fungal isolates exhibited antimicrobial activity against at least one pathogenic bacterium or fungus among four marine pathogenic microbes (Micrococcus luteus, Pseudoaltermonas piscida, Aspergerillus versicolor, and A. sydowii). Out of these antimicrobial fungi, the genera Arthrinium, Aspergillus, and Penicillium exhibited antibacterial and antifungal activities, while genus Aureobasidium displayed only antibacterial activity, and genera Acremonium, Cladosporium, Geomyces, and Phaeosphaeriopsis displayed only antifungal activity. To our knowledge, this is the first report to investigate the diversity and antimicrobial activity of culturable deep-sea-derived fungi in the South China Sea. These results suggest that diverse deep-sea fungi from the South China Sea are a potential source for antibiotics' discovery and further increase the pool of fungi available for natural bioactive product screening.

Deep learning in TMVA Benchmarking Benchmarking TMVA DNN Integration of a Deep Autoencoder

CERN Document Server

Huwiler, Marc

2017-01-01

The TMVA library in ROOT is dedicated to multivariate analysis, and in partic- ular oers numerous machine learning algorithms in a standardized framework. It is widely used in High Energy Physics for data analysis, mainly to perform regression and classication. To keep up to date with the state of the art in deep learning, a new deep learning module was being developed this summer, oering deep neural net- work, convolutional neural network, and autoencoder. TMVA did not have yet any autoencoder method, and the present project consists in implementing the TMVA autoencoder class based on the deep learning module. It also includes some bench- marking performed on the actual deep neural network implementation, in comparison to the Keras framework with Tensorflow and Theano backend.

The complete genome sequence of a new polerovirus in strawberry plants from eastern Canada showing strawberry decline symptoms.

Science.gov (United States)

Xiang, Yu; Bernardy, Mike; Bhagwat, Basdeo; Wiersma, Paul A; DeYoung, Robyn; Bouthillier, Michel

2015-02-01

Strawberry decline disease, probably caused by synergistic reactions of mixed virus infections, threatens the North American strawberry industry. Deep sequencing of strawberry plant samples from eastern Canada resulted in the identification of a new virus genome resembling poleroviruses in sequence and genome structure. Phylogenetic analysis suggests that it is a new member of the genus Polerovirus, family Luteoviridae. The virus is tentatively named "strawberry polerovirus 1" (SPV1).

Deep Borehole Disposal Safety Analysis.

Energy Technology Data Exchange (ETDEWEB)

Freeze, Geoffrey A. [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); Stein, Emily [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); Price, Laura L. [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); MacKinnon, Robert J. [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); Tillman, Jack Bruce [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)

2016-10-01

This report presents a preliminary safety analysis for the deep borehole disposal (DBD) concept, using a safety case framework. A safety case is an integrated collection of qualitative and quantitative arguments, evidence, and analyses that substantiate the safety, and the level of confidence in the safety, of a geologic repository. This safety case framework for DBD follows the outline of the elements of a safety case, and identifies the types of information that will be required to satisfy these elements. At this very preliminary phase of development, the DBD safety case focuses on the generic feasibility of the DBD concept. It is based on potential system designs, waste forms, engineering, and geologic conditions; however, no specific site or regulatory framework exists. It will progress to a site-specific safety case as the DBD concept advances into a site-specific phase, progressing through consent-based site selection and site investigation and characterization.

Analysis and Visualization Tool for Targeted Amplicon Bisulfite Sequencing on Ion Torrent Sequencers.

Directory of Open Access Journals (Sweden)

Stephan Pabinger

Full Text Available Targeted sequencing of PCR amplicons generated from bisulfite deaminated DNA is a flexible, cost-effective way to study methylation of a sample at single CpG resolution and perform subsequent multi-target, multi-sample comparisons. Currently, no platform specific protocol, support, or analysis solution is provided to perform targeted bisulfite sequencing on a Personal Genome Machine (PGM. Here, we present a novel tool, called TABSAT, for analyzing targeted bisulfite sequencing data generated on Ion Torrent sequencers. The workflow starts with raw sequencing data, performs quality assessment, and uses a tailored version of Bismark to map the reads to a reference genome. The pipeline visualizes results as lollipop plots and is able to deduce specific methylation-patterns present in a sample. The obtained profiles are then summarized and compared between samples. In order to assess the performance of the targeted bisulfite sequencing workflow, 48 samples were used to generate 53 different Bisulfite-Sequencing PCR amplicons from each sample, resulting in 2,544 amplicon targets. We obtained a mean coverage of 282X using 1,196,822 aligned reads. Next, we compared the sequencing results of these targets to the methylation level of the corresponding sites on an Illumina 450k methylation chip. The calculated average Pearson correlation coefficient of 0.91 confirms the sequencing results with one of the industry-leading CpG methylation platforms and shows that targeted amplicon bisulfite sequencing provides an accurate and cost-efficient method for DNA methylation studies, e.g., to provide platform-independent confirmation of Illumina Infinium 450k methylation data. TABSAT offers a novel way to analyze data generated by Ion Torrent instruments and can also be used with data from the Illumina MiSeq platform. It can be easily accessed via the Platomics platform, which offers a web-based graphical user interface along with sample and parameter storage

Magnetic resonance imaging (MRI) of articular cartilage of the knee using ultrashort echo time (uTE) sequences with spiral acquisition

International Nuclear Information System (INIS)

Goto, Hajimu; Fujii, Masahiko; Iwama, Yuki; Aoyama, Nobukazu; Ohno, Yoshiharu; Sugimura, Kazuro

2012-01-01

The objective of this study was to evaluate the sensitivity of ultrashort echo time (uTE) sequence for visualisation of calcified deep layers of articular cartilage. MRI with a uTE sequence was performed on five healthy volunteers. Signals from the calcified deep layers of the articular knee cartilage were evaluated on uTE subtraction images and computed tomography images. The calcified deep layers of the articular cartilage changed from having a low to a high signal when imaged with a uTE sequence. The reported uTE sequence was effective in imaging the deep layers of the knee cartilage.

Diversity, abundance and distribution of amoA-encoding archaea in deep-sea methane seep sediments of the Okhotsk Sea.

Science.gov (United States)

Dang, Hongyue; Luan, Xi-Wu; Chen, Ruipeng; Zhang, Xiaoxia; Guo, Lizhong; Klotz, Martin G

2010-06-01

The ecological characteristics of amoA-encoding archaea (AEA) in deep-sea sediments are largely unsolved. This paper aimed to study the diversity, structure, distribution and abundance of the archaeal community and especially its AEA components in the cold seep surface sediments of the Okhotsk Sea, a marginal sea harboring one of the largest methane hydrate reservoirs in the world. Diverse archaeal 16S rRNA gene sequences were identified, with the majority being related to sequences from other cold seep and methane-rich sediment environments. However, the AEA diversity and abundance were quite low as revealed by amoA gene analyses. Correlation analysis indicates that the abundance of the archaeal amoA genes was correlated with the sediment organic matter content. Thus, it is possible that the amoA-carrying archaea here might utilize organic matter for a living. The affiliation of certain archaeal amoA sequences to the GenBank sequences originally obtained from deep-sea hydrothermal vent environments indicated that the related AEA either have a wide range of temperature adaptation or they have a thermophilic evolutionary history in the modern cold deep-sea sediments of the Okhotsk Sea. The dominance of ammonia-oxidizing bacteria over AEA may indicate that bacteria play a significant role in nitrification in the Okhotsk Sea cold seep sediments.

Transcriptome sequencing and metabolite analysis reveals the role of delphinidin metabolism in flower colour in grape hyacinth.

Science.gov (United States)

Lou, Qian; Liu, Yali; Qi, Yinyan; Jiao, Shuzhen; Tian, Feifei; Jiang, Ling; Wang, Yuejin

2014-07-01

Grape hyacinth (Muscari) is an important ornamental bulbous plant with an extraordinary blue colour. Muscari armeniacum, whose flowers can be naturally white, provides an opportunity to unravel the complex metabolic networks underlying certain biochemical traits, especially colour. A blue flower cDNA library of M. armeniacum and a white flower library of M. armeniacum f. album were used for transcriptome sequencing. A total of 89 926 uni-transcripts were isolated, 143 of which could be identified as putative homologues of colour-related genes in other species. Based on a comprehensive analysis relating colour compounds to gene expression profiles, the mechanism of colour biosynthesis was studied in M. armeniacum. Furthermore, a new hypothesis explaining the lack of colour phenotype of the grape hyacinth flower is proposed. Alteration of the substrate competition between flavonol synthase (FLS) and dihydroflavonol 4-reductase (DFR) may lead to elimination of blue pigmentation while the multishunt from the limited flux in the cyanidin (Cy) synthesis pathway seems to be the most likely reason for the colour change in the white flowers of M. armeniacum. Moreover, mass sequence data obtained by the deep sequencing of M. armeniacum and its white variant provided a platform for future function and molecular biological research on M. armeniacum. © The Author 2014. Published by Oxford University Press on behalf of the Society for Experimental Biology.

Predicting backbone Cα angles and dihedrals from protein sequences by stacked sparse auto-encoder deep neural network.

Science.gov (United States)

Lyons, James; Dehzangi, Abdollah; Heffernan, Rhys; Sharma, Alok; Paliwal, Kuldip; Sattar, Abdul; Zhou, Yaoqi; Yang, Yuedong

2014-10-30

Because a nearly constant distance between two neighbouring Cα atoms, local backbone structure of proteins can be represented accurately by the angle between C(αi-1)-C(αi)-C(αi+1) (θ) and a dihedral angle rotated about the C(αi)-C(αi+1) bond (τ). θ and τ angles, as the representative of structural properties of three to four amino-acid residues, offer a description of backbone conformations that is complementary to φ and ψ angles (single residue) and secondary structures (>3 residues). Here, we report the first machine-learning technique for sequence-based prediction of θ and τ angles. Predicted angles based on an independent test have a mean absolute error of 9° for θ and 34° for τ with a distribution on the θ-τ plane close to that of native values. The average root-mean-square distance of 10-residue fragment structures constructed from predicted θ and τ angles is only 1.9Å from their corresponding native structures. Predicted θ and τ angles are expected to be complementary to predicted ϕ and ψ angles and secondary structures for using in model validation and template-based as well as template-free structure prediction. The deep neural network learning technique is available as an on-line server called Structural Property prediction with Integrated DEep neuRal network (SPIDER) at http://sparks-lab.org. Copyright © 2014 Wiley Periodicals, Inc.

Third-Generation Sequencing and Analysis of Four Complete Pig Liver Esterase Gene Sequences in Clones Identified by Screening BAC Library.

Science.gov (United States)

Zhou, Qiongqiong; Sun, Wenjuan; Liu, Xiyan; Wang, Xiliang; Xiao, Yuncai; Bi, Dingren; Yin, Jingdong; Shi, Deshi

2016-01-01

Pig liver carboxylesterase (PLE) gene sequences in GenBank are incomplete, which has led to difficulties in studying the genetic structure and regulation mechanisms of gene expression of PLE family genes. The aim of this study was to obtain and analysis of complete gene sequences of PLE family by screening from a Rongchang pig BAC library and third-generation PacBio gene sequencing. After a number of existing incomplete PLE isoform gene sequences were analysed, primers were designed based on conserved regions in PLE exons, and the whole pig genome used as a template for Polymerase chain reaction (PCR) amplification. Specific primers were then selected based on the PCR amplification results. A three-step PCR screening method was used to identify PLE-positive clones by screening a Rongchang pig BAC library and PacBio third-generation sequencing was performed. BLAST comparisons and other bioinformatics methods were applied for sequence analysis. Five PLE-positive BAC clones, designated BAC-10, BAC-70, BAC-75, BAC-119 and BAC-206, were identified. Sequence analysis yielded the complete sequences of four PLE genes, PLE1, PLE-B9, PLE-C4, and PLE-G2. Complete PLE gene sequences were defined as those containing regulatory sequences, exons, and introns. It was found that, not only did the PLE exon sequences of the four genes show a high degree of homology, but also that the intron sequences were highly similar. Additionally, the regulatory region of the genes contained two 720bps reverse complement sequences that may have an important function in the regulation of PLE gene expression. This is the first report to confirm the complete sequences of four PLE genes. In addition, the study demonstrates that each PLE isoform is encoded by a single gene and that the various genes exhibit a high degree of sequence homology, suggesting that the PLE family evolved from a single ancestral gene. Obtaining the complete sequences of these PLE genes provides the necessary foundation for

Next-Generation Sequencing Analysis and Algorithms for PDX and CDX Models.

Science.gov (United States)

Khandelwal, Garima; Girotti, María Romina; Smowton, Christopher; Taylor, Sam; Wirth, Christopher; Dynowski, Marek; Frese, Kristopher K; Brady, Ged; Dive, Caroline; Marais, Richard; Miller, Crispin

2017-08-01

Patient-derived xenograft (PDX) and circulating tumor cell-derived explant (CDX) models are powerful methods for the study of human disease. In cancer research, these methods have been applied to multiple questions, including the study of metastatic progression, genetic evolution, and therapeutic drug responses. As PDX and CDX models can recapitulate the highly heterogeneous characteristics of a patient tumor, as well as their response to chemotherapy, there is considerable interest in combining them with next-generation sequencing to monitor the genomic, transcriptional, and epigenetic changes that accompany oncogenesis. When used for this purpose, their reliability is highly dependent on being able to accurately distinguish between sequencing reads that originate from the host, and those that arise from the xenograft itself. Here, we demonstrate that failure to correctly identify contaminating host reads when analyzing DNA- and RNA-sequencing (DNA-Seq and RNA-Seq) data from PDX and CDX models is a major confounding factor that can lead to incorrect mutation calls and a failure to identify canonical mutation signatures associated with tumorigenicity. In addition, a highly sensitive algorithm and open source software tool for identifying and removing contaminating host sequences is described. Importantly, when applied to PDX and CDX models of melanoma, these data demonstrate its utility as a sensitive and selective tool for the correction of PDX- and CDX-derived whole-exome and RNA-Seq data. Implications: This study describes a sensitive method to identify contaminating host reads in xenograft and explant DNA- and RNA-Seq data and is applicable to other forms of deep sequencing. Mol Cancer Res; 15(8); 1012-6. ©2017 AACR . ©2017 American Association for Cancer Research.

Evidence for thermal convection in the deep carbonate aquifer of the eastern sector of the Po Plain, Italy

Science.gov (United States)

Pasquale, V.; Chiozzi, P.; Verdoya, M.

2013-05-01

Temperatures recorded in wells as deep as 6 km drilled for hydrocarbon prospecting were used together with geological information to depict the thermal regime of the sedimentary sequence of the eastern sector of the Po Plain. After correction for drilling disturbance, temperature data were analyzed through an inversion technique based on a laterally constant thermal gradient model. The obtained thermal gradient is quite low within the deep carbonate unit (14 mK m- 1), while it is larger (53 mK m- 1) in the overlying impermeable formations. In the uppermost sedimentary layers, the thermal gradient is close to the regional average (21 mK m- 1). We argue that such a vertical change cannot be ascribed to thermal conductivity variation within the sedimentary sequence, but to deep groundwater flow. Since the hydrogeological characteristics (including litho-stratigraphic sequence and structural setting) hardly permit forced convection, we suggest that thermal convection might occur within the deep carbonate aquifer. The potential of this mechanism was evaluated by means of the Rayleigh number analysis. It turned out that permeability required for convection to occur must be larger than 3 10- 15 m2. The average over-heat ratio is 0.45. The lateral variation of hydrothermal regime was tested by using temperature data representing the aquifer thermal conditions. We found that thermal convection might be more developed and variable at the Ferrara High and its surroundings, where widespread fracturing may have increased permeability.

Position-specific automated processing of V3 env ultra-deep pyrosequencing data for predicting HIV-1 tropism.

Science.gov (United States)

Jeanne, Nicolas; Saliou, Adrien; Carcenac, Romain; Lefebvre, Caroline; Dubois, Martine; Cazabat, Michelle; Nicot, Florence; Loiseau, Claire; Raymond, Stéphanie; Izopet, Jacques; Delobel, Pierre

2015-11-20

HIV-1 coreceptor usage must be accurately determined before starting CCR5 antagonist-based treatment as the presence of undetected minor CXCR4-using variants can cause subsequent virological failure. Ultra-deep pyrosequencing of HIV-1 V3 env allows to detect low levels of CXCR4-using variants that current genotypic approaches miss. However, the computation of the mass of sequence data and the need to identify true minor variants while excluding artifactual sequences generated during amplification and ultra-deep pyrosequencing is rate-limiting. Arbitrary fixed cut-offs below which minor variants are discarded are currently used but the errors generated during ultra-deep pyrosequencing are sequence-dependant rather than random. We have developed an automated processing of HIV-1 V3 env ultra-deep pyrosequencing data that uses biological filters to discard artifactual or non-functional V3 sequences followed by statistical filters to determine position-specific sensitivity thresholds, rather than arbitrary fixed cut-offs. It allows to retain authentic sequences with point mutations at V3 positions of interest and discard artifactual ones with accurate sensitivity thresholds.

Multilocus Sequence Analysis and rpoB Sequencing of Mycobacterium abscessus (Sensu Lato) Strains▿

Science.gov (United States)

Macheras, Edouard; Roux, Anne-Laure; Bastian, Sylvaine; Leão, Sylvia Cardoso; Palaci, Moises; Sivadon-Tardy, Valérie; Gutierrez, Cristina; Richter, Elvira; Rüsch-Gerdes, Sabine; Pfyffer, Gaby; Bodmer, Thomas; Cambau, Emmanuelle; Gaillard, Jean-Louis; Heym, Beate

2011-01-01

Mycobacterium abscessus, Mycobacterium bolletii, and Mycobacterium massiliense (Mycobacterium abscessus sensu lato) are closely related species that currently are identified by the sequencing of the rpoB gene. However, recent studies show that rpoB sequencing alone is insufficient to discriminate between these species, and some authors have questioned their current taxonomic classification. We studied here a large collection of M. abscessus (sensu lato) strains by partial rpoB sequencing (752 bp) and multilocus sequence analysis (MLSA). The final MLSA scheme developed was based on the partial sequences of eight housekeeping genes: argH, cya, glpK, gnd, murC, pgm, pta, and purH. The strains studied included the three type strains (M. abscessus CIP 104536T, M. massiliense CIP 108297T, and M. bolletii CIP 108541T) and 120 isolates recovered between 1997 and 2007 in France, Germany, Switzerland, and Brazil. The rpoB phylogenetic tree confirmed the existence of three main clusters, each comprising the type strain of one species. However, divergence values between the M. massiliense and M. bolletii clusters all were below 3% and between the M. abscessus and M. massiliense clusters were from 2.66 to 3.59%. The tree produced using the concatenated MLSA gene sequences (4,071 bp) also showed three main clusters, each comprising the type strain of one species. The M. abscessus cluster had a bootstrap value of 100% and was mostly compact. Bootstrap values for the M. massiliense and M. bolletii branches were much lower (71 and 61%, respectively), with the M. massiliense cluster having a fuzzy aspect. Mean (range) divergence values were 2.17% (1.13 to 2.58%) between the M. abscessus and M. massiliense clusters, 2.37% (1.5 to 2.85%) between the M. abscessus and M. bolletii clusters, and 2.28% (0.86 to 2.68%) between the M. massiliense and M. bolletii clusters. Adding the rpoB sequence to the MLSA-concatenated sequence (total sequence, 4,823 bp) had little effect on the clustering

Multilocus sequence analysis and rpoB sequencing of Mycobacterium abscessus (sensu lato) strains.

Science.gov (United States)

Macheras, Edouard; Roux, Anne-Laure; Bastian, Sylvaine; Leão, Sylvia Cardoso; Palaci, Moises; Sivadon-Tardy, Valérie; Gutierrez, Cristina; Richter, Elvira; Rüsch-Gerdes, Sabine; Pfyffer, Gaby; Bodmer, Thomas; Cambau, Emmanuelle; Gaillard, Jean-Louis; Heym, Beate

2011-02-01

Mycobacterium abscessus, Mycobacterium bolletii, and Mycobacterium massiliense (Mycobacterium abscessus sensu lato) are closely related species that currently are identified by the sequencing of the rpoB gene. However, recent studies show that rpoB sequencing alone is insufficient to discriminate between these species, and some authors have questioned their current taxonomic classification. We studied here a large collection of M. abscessus (sensu lato) strains by partial rpoB sequencing (752 bp) and multilocus sequence analysis (MLSA). The final MLSA scheme developed was based on the partial sequences of eight housekeeping genes: argH, cya, glpK, gnd, murC, pgm, pta, and purH. The strains studied included the three type strains (M. abscessus CIP 104536(T), M. massiliense CIP 108297(T), and M. bolletii CIP 108541(T)) and 120 isolates recovered between 1997 and 2007 in France, Germany, Switzerland, and Brazil. The rpoB phylogenetic tree confirmed the existence of three main clusters, each comprising the type strain of one species. However, divergence values between the M. massiliense and M. bolletii clusters all were below 3% and between the M. abscessus and M. massiliense clusters were from 2.66 to 3.59%. The tree produced using the concatenated MLSA gene sequences (4,071 bp) also showed three main clusters, each comprising the type strain of one species. The M. abscessus cluster had a bootstrap value of 100% and was mostly compact. Bootstrap values for the M. massiliense and M. bolletii branches were much lower (71 and 61%, respectively), with the M. massiliense cluster having a fuzzy aspect. Mean (range) divergence values were 2.17% (1.13 to 2.58%) between the M. abscessus and M. massiliense clusters, 2.37% (1.5 to 2.85%) between the M. abscessus and M. bolletii clusters, and 2.28% (0.86 to 2.68%) between the M. massiliense and M. bolletii clusters. Adding the rpoB sequence to the MLSA-concatenated sequence (total sequence, 4,823 bp) had little effect on the

Trace maps for arbitrary substitution sequences

International Nuclear Information System (INIS)

Avishai, Y.

1993-01-01

The discovery of quasi-crystals and their 1-dimensional modeling have led to a deep mathematical study of Schroedinger operators with an arbitrary deterministic potential sequence. In this work we address this problem and find trace maps for an arbitrary substitution sequence. our trace maps have lower dimensionality than those of Kolar and Nori, which make them quite attractive for actual applications. (authors)

Theonellapeptolide IIIe, a new cyclic peptolide from the New Zealand deep water sponge, Lamellomorpha strongylata.

Science.gov (United States)

Li, S; Dumdei, E J; Blunt, J W; Munro, M H; Robinson, W T; Pannell, L K

1998-06-26

The structure, stereochemistry, and conformation of theonellapeptolide IIIe (1), a new 36-membered ring cyclic peptolide from the New Zealand deep-water sponge Lamellomorpha strongylata, is described. The sequence of the cytotoxic peptolide was determined through a combination of NMR and MS-MS techniques and confirmed by X-ray crystal structure analysis, which, with chiral HPLC, established the absolute stereochemistry.

DNAApp: a mobile application for sequencing data analysis.

Science.gov (United States)

Nguyen, Phi-Vu; Verma, Chandra Shekhar; Gan, Samuel Ken-En

2014-11-15

There have been numerous applications developed for decoding and visualization of ab1 DNA sequencing files for Windows and MAC platforms, yet none exists for the increasingly popular smartphone operating systems. The ability to decode sequencing files cannot easily be carried out using browser accessed Web tools. To overcome this hurdle, we have developed a new native app called DNAApp that can decode and display ab1 sequencing file on Android and iOS. In addition to in-built analysis tools such as reverse complementation, protein translation and searching for specific sequences, we have incorporated convenient functions that would facilitate the harnessing of online Web tools for a full range of analysis. Given the high usage of Android/iOS tablets and smartphones, such bioinformatics apps would raise productivity and facilitate the high demand for analyzing sequencing data in biomedical research. The Android version of DNAApp is available in Google Play Store as 'DNAApp', and the iOS version is available in the App Store. More details on the app can be found at www.facebook.com/APDLab; www.bii.a-star.edu.sg/research/trd/apd.php The DNAApp user guide is available at http://tinyurl.com/DNAAppuser, and a video tutorial is available on Google Play Store and App Store, as well as on the Facebook page. samuelg@bii.a-star.edu.sg. © The Author 2014. Published by Oxford University Press.

DNAApp: a mobile application for sequencing data analysis

Science.gov (United States)

Nguyen, Phi-Vu; Verma, Chandra Shekhar; Gan, Samuel Ken-En

2014-01-01

Summary: There have been numerous applications developed for decoding and visualization of ab1 DNA sequencing files for Windows and MAC platforms, yet none exists for the increasingly popular smartphone operating systems. The ability to decode sequencing files cannot easily be carried out using browser accessed Web tools. To overcome this hurdle, we have developed a new native app called DNAApp that can decode and display ab1 sequencing file on Android and iOS. In addition to in-built analysis tools such as reverse complementation, protein translation and searching for specific sequences, we have incorporated convenient functions that would facilitate the harnessing of online Web tools for a full range of analysis. Given the high usage of Android/iOS tablets and smartphones, such bioinformatics apps would raise productivity and facilitate the high demand for analyzing sequencing data in biomedical research. Availability and implementation: The Android version of DNAApp is available in Google Play Store as ‘DNAApp’, and the iOS version is available in the App Store. More details on the app can be found at www.facebook.com/APDLab; www.bii.a-star.edu.sg/research/trd/apd.php The DNAApp user guide is available at http://tinyurl.com/DNAAppuser, and a video tutorial is available on Google Play Store and App Store, as well as on the Facebook page. Contact: samuelg@bii.a-star.edu.sg PMID:25095882

Bacterial and archaeal communities in the deep-sea sediments of inactive hydrothermal vents in the Southwest India Ridge

Science.gov (United States)

Zhang, Likui; Kang, Manyu; Xu, Jiajun; Xu, Jian; Shuai, Yinjie; Zhou, Xiaojian; Yang, Zhihui; Ma, Kesen

2016-05-01

Active deep-sea hydrothermal vents harbor abundant thermophilic and hyperthermophilic microorganisms. However, microbial communities in inactive hydrothermal vents have not been well documented. Here, we investigated bacterial and archaeal communities in the two deep-sea sediments (named as TVG4 and TVG11) collected from inactive hydrothermal vents in the Southwest India Ridge using the high-throughput sequencing technology of Illumina MiSeq2500 platform. Based on the V4 region of 16S rRNA gene, sequence analysis showed that bacterial communities in the two samples were dominated by Proteobacteria, followed by Bacteroidetes, Actinobacteria and Firmicutes. Furthermore, archaeal communities in the two samples were dominated by Thaumarchaeota and Euryarchaeota. Comparative analysis showed that (i) TVG4 displayed the higher bacterial richness and lower archaeal richness than TVG11; (ii) the two samples had more divergence in archaeal communities than bacterial communities. Bacteria and archaea that are potentially associated with nitrogen, sulfur metal and methane cycling were detected in the two samples. Overall, we first provided a comparative picture of bacterial and archaeal communities and revealed their potentially ecological roles in the deep-sea environments of inactive hydrothermal vents in the Southwest Indian Ridge, augmenting microbial communities in inactive hydrothermal vents.

Deep Sequencing of 71 Candidate Genes to Characterize Variation Associated with Alcohol Dependence.

Science.gov (United States)

Clark, Shaunna L; McClay, Joseph L; Adkins, Daniel E; Kumar, Gaurav; Aberg, Karolina A; Nerella, Srilaxmi; Xie, Linying; Collins, Ann L; Crowley, James J; Quackenbush, Corey R; Hilliard, Christopher E; Shabalin, Andrey A; Vrieze, Scott I; Peterson, Roseann E; Copeland, William E; Silberg, Judy L; McGue, Matt; Maes, Hermine; Iacono, William G; Sullivan, Patrick F; Costello, Elizabeth J; van den Oord, Edwin J

2017-04-01

Previous genomewide association studies (GWASs) have identified a number of putative risk loci for alcohol dependence (AD). However, only a few loci have replicated and these replicated variants only explain a small proportion of AD risk. Using an innovative approach, the goal of this study was to generate hypotheses about potentially causal variants for AD that can be explored further through functional studies. We employed targeted capture of 71 candidate loci and flanking regions followed by next-generation deep sequencing (mean coverage 78X) in 806 European Americans. Regions included in our targeted capture library were genes identified through published GWAS of alcohol, all human alcohol and aldehyde dehydrogenases, reward system genes including dopaminergic and opioid receptors, prioritized candidate genes based on previous associations, and genes involved in the absorption, distribution, metabolism, and excretion of drugs. We performed single-locus tests to determine if any single variant was associated with AD symptom count. Sets of variants that overlapped with biologically meaningful annotations were tested for association in aggregate. No single, common variant was significantly associated with AD in our study. We did, however, find evidence for association with several variant sets. Two variant sets were significant at the q-value <0.10 level: a genic enhancer for ADHFE1 (p = 1.47 × 10 -5 ; q = 0.019), an alcohol dehydrogenase, and ADORA1 (p = 5.29 × 10 -5 ; q = 0.035), an adenosine receptor that belongs to a G-protein-coupled receptor gene family. To our knowledge, this is the first sequencing study of AD to examine variants in entire genes, including flanking and regulatory regions. We found that in addition to protein coding variant sets, regulatory variant sets may play a role in AD. From these findings, we have generated initial functional hypotheses about how these sets may influence AD. Copyright © 2017 by the Research Society on

RESEARCH NOTE Molecular genetic analysis of consanguineous ...

Indian Academy of Sciences (India)

Navya

Molecular genetic analysis of consanguineous families with primary microcephaly ... Translational Research Institute, Academic Health System, Hamad Medical ..... bridging the gap between homozygosity mapping and deep sequencing.

Expression profiles of mRNA and long noncoding RNA in the ovaries of letrozole-induced polycystic ovary syndrome rat model through deep sequencing.

Science.gov (United States)

Fu, Lu-Lu; Xu, Ying; Li, Dan-Dan; Dai, Xiao-Wei; Xu, Xin; Zhang, Jing-Shun; Ming, Hao; Zhang, Xue-Ying; Zhang, Guo-Qing; Ma, Ya-Lan; Zheng, Lian-Wen

2018-05-30

Polycystic ovary syndrome (PCOS) is one of the most common endocrine disorders in reproductive-aged women. However, the exact pathophysiology of PCOS remains largely unclear. We performed deep sequencing to investigate the mRNA and long noncoding RNA (lncRNA) expression profiles in the ovarian tissues of letrozole-induced PCOS rat model and control rats. A total of 2147 mRNAs and 158 lncRNAs were differentially expressed between the PCOS models and control. Gene ontology analysis indicated that differentially expressed mRNAs were associated with biological adhesion, reproduction, and metabolic process. Pathway analysis results indicated that these aberrantly expressed mRNAs were related to several specific signaling pathways, including insulin resistance, steroid hormone biosynthesis, PPAR signaling pathway, cell adhesion molecules, autoimmune thyroid disease, and AMPK signaling pathway. The relative expression levels of mRNAs and lncRNAs were validated through qRT-PCR. LncRNA-miRNA-mRNA network was constructed to explore ceRNAs involved in the PCOS model and were also verified by qRTPCR experiment. These findings may provide insight into the pathogenesis of PCOS and clues to find key diagnostic and therapeutic roles of lncRNA in PCOS. Copyright © 2018 Elsevier B.V. All rights reserved.

Deep RNA-Seq analysis reveals unexpected features of human prostate basal epithelial cells

Directory of Open Access Journals (Sweden)

Dingxiao Zhang

2016-03-01

Full Text Available Prostate cancer is the second leading cause of cancer-related deaths among American men [1]. The prostate gland mainly contains basal and luminal cells, which are constructed as a pseudostratified epithelium. Annotation of prostate epithelial transcriptomes provides a foundation for discoveries that can impact disease understanding and treatment. Here, for the first time, we describe a whole-genome transcriptome analysis of human benign prostatic basal and luminal populations by using deep RNA sequencing (GSE67070 [2]. Combined with comprehensive molecular and biological characterizations, we show that the differential gene expression profiles account for their distinct functional phenotypes. Strikingly, in contrast to luminal cells, basal cells preferentially express gene categories associated with stem cells, neural and neuronal development, and RNA processing. Of clinical relevance, the treatment failed castration-resistant and anaplastic prostate cancers molecularly resemble a basal-like phenotype. We also identified genes associated with patient clinical outcome. Therefore, we provide a gene expression resource for understanding human prostate epithelial lineages, and link the cell-type specific gene signatures to subtypes of prostate cancer development. Keywords: Prostate epithelial cells, Basal cells, Luminal cells, RNA-seq

Utility of RNA Sequencing for Analysis of Maize Reproductive Transcriptomes

Directory of Open Access Journals (Sweden)

Rebecca M. Davidson

2011-11-01

Full Text Available Transcriptome sequencing is a powerful method for studying global expression patterns in large, complex genomes. Evaluation of sequence-based expression profiles during reproductive development would provide functional annotation to genes underlying agronomic traits. We generated transcriptome profiles for 12 diverse maize ( L. reproductive tissues representing male, female, developing seed, and leaf tissues using high throughput transcriptome sequencing. Overall, ∼80% of annotated genes were expressed. Comparative analysis between sequence and hybridization-based methods demonstrated the utility of ribonucleic acid sequencing (RNA-seq for expression determination and differentiation of paralagous genes (∼85% of maize genes. Analysis of 4975 gene families across reproductive tissues revealed expression divergence is proportional to family size. In all pairwise comparisons between tissues, 7 (pre- vs. postemergence cobs to 48% (pollen vs. ovule of genes were differentially expressed. Genes with expression restricted to a single tissue within this study were identified with the highest numbers observed in leaves, endosperm, and pollen. Coexpression network analysis identified 17 gene modules with complex and shared expression patterns containing many previously described maize genes. The data and analyses in this study provide valuable tools through improved gene annotation, gene family characterization, and a core set of candidate genes to further characterize maize reproductive development and improve grain yield potential.

Energy consumption analysis for the Mars deep space station

Science.gov (United States)

Hayes, N. V.

1982-01-01

Results for the energy consumption analysis at the Mars deep space station are presented. It is shown that the major energy consumers are the 64-Meter antenna building and the operations support building. Verification of the antenna's energy consumption is highly dependent on an accurate knowlege of the tracking operations. The importance of a regular maintenance schedule for the watt hour meters installed at the station is indicated.

Recent advances in nanopore-based nucleic acid analysis and sequencing

International Nuclear Information System (INIS)

Shi, Jidong; Fang, Ying; Hou, Junfeng

2016-01-01

Nanopore-based sequencing platforms are transforming the field of genomic science. This review (containing 116 references) highlights some recent progress on nanopore-based nucleic acid analysis and sequencing. These studies are classified into three categories, biological, solid-state, and hybrid nanopores, according to their nanoporous materials. We begin with a brief description of the translocation-based detection mechanism of nanopores. Next, specific examples are given in nanopore-based nucleic acid analysis and sequencing, with an emphasis on identifying strategies that can improve the resolution of nanopores. This review concludes with a discussion of future research directions that will advance the practical applications of nanopore technology. (author)

Exome Sequencing and the Management of Neurometabolic Disorders.

Science.gov (United States)

Tarailo-Graovac, Maja; Shyr, Casper; Ross, Colin J; Horvath, Gabriella A; Salvarinova, Ramona; Ye, Xin C; Zhang, Lin-Hua; Bhavsar, Amit P; Lee, Jessica J Y; Drögemöller, Britt I; Abdelsayed, Mena; Alfadhel, Majid; Armstrong, Linlea; Baumgartner, Matthias R; Burda, Patricie; Connolly, Mary B; Cameron, Jessie; Demos, Michelle; Dewan, Tammie; Dionne, Janis; Evans, A Mark; Friedman, Jan M; Garber, Ian; Lewis, Suzanne; Ling, Jiqiang; Mandal, Rupasri; Mattman, Andre; McKinnon, Margaret; Michoulas, Aspasia; Metzger, Daniel; Ogunbayo, Oluseye A; Rakic, Bojana; Rozmus, Jacob; Ruben, Peter; Sayson, Bryan; Santra, Saikat; Schultz, Kirk R; Selby, Kathryn; Shekel, Paul; Sirrs, Sandra; Skrypnyk, Cristina; Superti-Furga, Andrea; Turvey, Stuart E; Van Allen, Margot I; Wishart, David; Wu, Jiang; Wu, John; Zafeiriou, Dimitrios; Kluijtmans, Leo; Wevers, Ron A; Eydoux, Patrice; Lehman, Anna M; Vallance, Hilary; Stockler-Ipsiroglu, Sylvia; Sinclair, Graham; Wasserman, Wyeth W; van Karnebeek, Clara D

2016-06-09

Whole-exome sequencing has transformed gene discovery and diagnosis in rare diseases. Translation into disease-modifying treatments is challenging, particularly for intellectual developmental disorder. However, the exception is inborn errors of metabolism, since many of these disorders are responsive to therapy that targets pathophysiological features at the molecular or cellular level. To uncover the genetic basis of potentially treatable inborn errors of metabolism, we combined deep clinical phenotyping (the comprehensive characterization of the discrete components of a patient's clinical and biochemical phenotype) with whole-exome sequencing analysis through a semiautomated bioinformatics pipeline in consecutively enrolled patients with intellectual developmental disorder and unexplained metabolic phenotypes. We performed whole-exome sequencing on samples obtained from 47 probands. Of these patients, 6 were excluded, including 1 who withdrew from the study. The remaining 41 probands had been born to predominantly nonconsanguineous parents of European descent. In 37 probands, we identified variants in 2 genes newly implicated in disease, 9 candidate genes, 22 known genes with newly identified phenotypes, and 9 genes with expected phenotypes; in most of the genes, the variants were classified as either pathogenic or probably pathogenic. Complex phenotypes of patients in five families were explained by coexisting monogenic conditions. We obtained a diagnosis in 28 of 41 probands (68%) who were evaluated. A test of a targeted intervention was performed in 18 patients (44%). Deep phenotyping and whole-exome sequencing in 41 probands with intellectual developmental disorder and unexplained metabolic abnormalities led to a diagnosis in 68%, the identification of 11 candidate genes newly implicated in neurometabolic disease, and a change in treatment beyond genetic counseling in 44%. (Funded by BC Children's Hospital Foundation and others.).

Software for rapid time dependent ChIP-sequencing analysis (TDCA).

Science.gov (United States)

Myschyshyn, Mike; Farren-Dai, Marco; Chuang, Tien-Jui; Vocadlo, David

2017-11-25

Chromatin immunoprecipitation followed by DNA sequencing (ChIP-seq) and associated methods are widely used to define the genome wide distribution of chromatin associated proteins, post-translational epigenetic marks, and modifications found on DNA bases. An area of emerging interest is to study time dependent changes in the distribution of such proteins and marks by using serial ChIP-seq experiments performed in a time resolved manner. Despite such time resolved studies becoming increasingly common, software to facilitate analysis of such data in a robust automated manner is limited. We have designed software called Time-Dependent ChIP-Sequencing Analyser (TDCA), which is the first program to automate analysis of time-dependent ChIP-seq data by fitting to sigmoidal curves. We provide users with guidance for experimental design of TDCA for modeling of time course (TC) ChIP-seq data using two simulated data sets. Furthermore, we demonstrate that this fitting strategy is widely applicable by showing that automated analysis of three previously published TC data sets accurately recapitulates key findings reported in these studies. Using each of these data sets, we highlight how biologically relevant findings can be readily obtained by exploiting TDCA to yield intuitive parameters that describe behavior at either a single locus or sets of loci. TDCA enables customizable analysis of user input aligned DNA sequencing data, coupled with graphical outputs in the form of publication-ready figures that describe behavior at either individual loci or sets of loci sharing common traits defined by the user. TDCA accepts sequencing data as standard binary alignment map (BAM) files and loci of interest in browser extensible data (BED) file format. TDCA accurately models the number of sequencing reads, or coverage, at loci from TC ChIP-seq studies or conceptually related TC sequencing experiments. TC experiments are reduced to intuitive parametric values that facilitate biologically

MRI Texture Analysis Reveals Deep Gray Nuclei Damage in Amyotrophic Lateral Sclerosis.

Science.gov (United States)

de Albuquerque, Milena; Anjos, Lara G V; Maia Tavares de Andrade, Helen; de Oliveira, Márcia S; Castellano, Gabriela; Junqueira Ribeiro de Rezende, Thiago; Nucci, Anamarli; França Junior, Marcondes Cavalcante

2016-01-01

Amyotrophic Lateral Sclerosis (ALS) is characterized by extensive corticospinal damage, but extrapyramidal involvement is suggested in pathological studies. Texture analysis (TA) is an image processing technique that evaluates the distribution of gray levels between pixels in a given region of interest (ROI). It provides quantitative data and has been employed in several neurodegenerative disorders. Here, we used TA to investigate possible deep gray nuclei (DGN) abnormalities in a cohort of ALS patients. Thirty-two ALS patients and 32 healthy controls underwent MRI in a 3T scanner. The T1 volumetric sequence was used for DGN segmentation and extraction of 11 texture parameters using the MaZda software. Statistical analyses were performed using the Mann-Whitney non-parametric test, with a significance level set at α = 0.025 (FDR-corrected) for TA. Patients had significantly higher values for the parameter correlation (CO) in both thalami and in the right caudate nucleus compared to healthy controls. Also, the parameter Inverse Difference Moment or Homogeneity (IDM) presented significantly smaller values in the ALS group in both thalami. TA of T1 weighted images revealed DGN alterations in patients with ALS, namely in the thalami and caudate nuclei. Copyright © 2015 by the American Society of Neuroimaging.

Multiscale deep drawing analysis of dual-phase steels using grain cluster-based RGC scheme

International Nuclear Information System (INIS)

Tjahjanto, D D; Eisenlohr, P; Roters, F

2015-01-01

Multiscale modelling and simulation play an important role in sheet metal forming analysis, since the overall material responses at macroscopic engineering scales, e.g. formability and anisotropy, are strongly influenced by microstructural properties, such as grain size and crystal orientations (texture). In the present report, multiscale analysis on deep drawing of dual-phase steels is performed using an efficient grain cluster-based homogenization scheme.The homogenization scheme, called relaxed grain cluster (RGC), is based on a generalization of the grain cluster concept, where a (representative) volume element consists of p  ×  q  ×  r (hexahedral) grains. In this scheme, variation of the strain or deformation of individual grains is taken into account through the, so-called, interface relaxation, which is formulated within an energy minimization framework. An interfacial penalty term is introduced into the energy minimization framework in order to account for the effects of grain boundaries.The grain cluster-based homogenization scheme has been implemented and incorporated into the advanced material simulation platform DAMASK, which purposes to bridge the macroscale boundary value problems associated with deep drawing analysis to the micromechanical constitutive law, e.g. crystal plasticity model. Standard Lankford anisotropy tests are performed to validate the model parameters prior to the deep drawing analysis. Model predictions for the deep drawing simulations are analyzed and compared to the corresponding experimental data. The result shows that the predictions of the model are in a very good agreement with the experimental measurement. (paper)

Connectivity between surface and deep waters determines prokaryotic diversity in the North Atlantic Deep Water.

Science.gov (United States)

Frank, Alexander H; Garcia, Juan A L; Herndl, Gerhard J; Reinthaler, Thomas

2016-06-01

To decipher the influence of depth stratification and surface provincialism on the dark ocean prokaryotic community composition, we sampled the major deep-water masses in the eastern North Atlantic covering three biogeographic provinces. Their diversity was evaluated using ordination and canonical analysis of 454 pyrotag sequences. Variance partitioning suggested that 16% of the variation in the bacterial community composition was based on depth stratification while 9% of the variation was due to geographic location. General linear mixed effect models showed that the community of the subsurface waters was connected to the dark ocean prokaryotic communities in different biogeographic provinces. Cluster analysis indicated that some prokaryotic taxa are specific to distinct regions in bathypelagic water masses. Taken together, our data suggest that the dark ocean prokaryotic community composition of the eastern North Atlantic is primed by the formation and the horizontal transport of water masses. © 2016 Society for Applied Microbiology and John Wiley & Sons Ltd.

Comparing methods of classifying life courses: Sequence analysis and latent class analysis

NARCIS (Netherlands)

Elzinga, C.H.; Liefbroer, Aart C.; Han, Sapphire

2017-01-01

We compare life course typology solutions generated by sequence analysis (SA) and latent class analysis (LCA). First, we construct an analytic protocol to arrive at typology solutions for both methodologies and present methods to compare the empirical quality of alternative typologies. We apply this

Comparing methods of classifying life courses: sequence analysis and latent class analysis

NARCIS (Netherlands)

Han, Y.; Liefbroer, A.C.; Elzinga, C.

2017-01-01

We compare life course typology solutions generated by sequence analysis (SA) and latent class analysis (LCA). First, we construct an analytic protocol to arrive at typology solutions for both methodologies and present methods to compare the empirical quality of alternative typologies. We apply this

Characterization of bacterial diversity associated with deep sea ferromanganese nodules from the South China Sea.

Science.gov (United States)

Zhang, De-Chao; Liu, Yan-Xia; Li, Xin-Zheng

2015-09-01

Deep sea ferromanganese (FeMn) nodules contain metallic mineral resources and have great economic potential. In this study, a combination of culture-dependent and culture-independent (16S rRNA genes clone library and pyrosequencing) methods was used to investigate the bacterial diversity in FeMn nodules from Jiaolong Seamount, the South China Sea. Eleven bacterial strains including some moderate thermophiles were isolated. The majority of strains belonged to the phylum Proteobacteria; one isolate belonged to the phylum Firmicutes. A total of 259 near full-length bacterial 16S rRNA gene sequences in a clone library and 67,079 valid reads obtained using pyrosequencing indicated that members of the Gammaproteobacteria dominated, with the most abundant bacterial genera being Pseudomonas and Alteromonas. Sequence analysis indicated the presence of many organisms whose closest relatives are known manganese oxidizers, iron reducers, hydrogen-oxidizing bacteria and methylotrophs. This is the first reported investigation of bacterial diversity associated with deep sea FeMn nodules from the South China Sea.

MUFOLD-SS: New deep inception-inside-inception networks for protein secondary structure prediction.

Science.gov (United States)

Fang, Chao; Shang, Yi; Xu, Dong

2018-05-01

Protein secondary structure prediction can provide important information for protein 3D structure prediction and protein functions. Deep learning offers a new opportunity to significantly improve prediction accuracy. In this article, a new deep neural network architecture, named the Deep inception-inside-inception (Deep3I) network, is proposed for protein secondary structure prediction and implemented as a software tool MUFOLD-SS. The input to MUFOLD-SS is a carefully designed feature matrix corresponding to the primary amino acid sequence of a protein, which consists of a rich set of information derived from individual amino acid, as well as the context of the protein sequence. Specifically, the feature matrix is a composition of physio-chemical properties of amino acids, PSI-BLAST profile, and HHBlits profile. MUFOLD-SS is composed of a sequence of nested inception modules and maps the input matrix to either eight states or three states of secondary structures. The architecture of MUFOLD-SS enables effective processing of local and global interactions between amino acids in making accurate prediction. In extensive experiments on multiple datasets, MUFOLD-SS outperformed the best existing methods and other deep neural networks significantly. MUFold-SS can be downloaded from http://dslsrv8.cs.missouri.edu/~cf797/MUFoldSS/download.html. © 2018 Wiley Periodicals, Inc.

Analysis of hyper-baric biofilms on engineering surfaces formed in the Deep Sea

Science.gov (United States)

Meier, A.; Tsaloglou, N. M.; Connelly, D.; Keevil, B.; Mowlem, M.

2012-04-01

Long-term monitoring of the environment is essential to our understanding of global processes, such as global warming, and their impact. As biofilm formation occurs after only short deployment periods in the marine environment, it is a major problem in long-term operation of environmental sensors. This makes the development of anti-fouling strategies for in situ sensors critical to their function. The effects on sensors can range from measurement drift, which can be compensated, to blockage of channels and material degradation, rendering them inoperative. In general, the longer the deployment period the more severe the effects of the biofouling become. Until now, biofilm research has focused mainly on the eutrophic and euphotic zones of the oceans. Hyper-baric biofilms are poorly understood due to difficulties in experimental setup and the assumption that biofouling in these oligotrophic regions could be regarded as insignificant. Our study shows significant biofilm formation occurs in the deep sea. We deployed a variety of materials, typically used in engineering structures, on a 4500 metre deep mooring during a cruise to the Cayman Trough, for 10 days. The materials were clear plain glass, poly-methyl methacrylate (PMMA), Delrin™, and copper, a known antifouling agent. The biofilms were studied by fluorescence microscopy and molecular analysis. For microscopy the nucleic acid stain, SYTO©9, was used and surface coverage was quantified by using a custom MATLAB™ program. Further molecular analyses, including UV Vis spectrometric quantification of DNA, nucleic acid amplification using Polymerase Chain Reaction (PCR), and Denaturing Gradient Gel Electrophoresis (DGGE), were utilised for the analysis of the microbial community composition of these biofilms. Six 16S/18S universal primer sets representative for the three kingdoms, Archea, Bacteria, and Eukarya were used for the PCR and DGGE. Preliminary results from fluorescence microscopy showed that the biofilm

CSReport: A New Computational Tool Designed for Automatic Analysis of Class Switch Recombination Junctions Sequenced by High-Throughput Sequencing.

Science.gov (United States)

Boyer, François; Boutouil, Hend; Dalloul, Iman; Dalloul, Zeinab; Cook-Moreau, Jeanne; Aldigier, Jean-Claude; Carrion, Claire; Herve, Bastien; Scaon, Erwan; Cogné, Michel; Péron, Sophie

2017-05-15

B cells ensure humoral immune responses due to the production of Ag-specific memory B cells and Ab-secreting plasma cells. In secondary lymphoid organs, Ag-driven B cell activation induces terminal maturation and Ig isotype class switch (class switch recombination [CSR]). CSR creates a virtually unique IgH locus in every B cell clone by intrachromosomal recombination between two switch (S) regions upstream of each C region gene. Amount and structural features of CSR junctions reveal valuable information about the CSR mechanism, and analysis of CSR junctions is useful in basic and clinical research studies of B cell functions. To provide an automated tool able to analyze large data sets of CSR junction sequences produced by high-throughput sequencing (HTS), we designed CSReport, a software program dedicated to support analysis of CSR recombination junctions sequenced with a HTS-based protocol (Ion Torrent technology). CSReport was assessed using simulated data sets of CSR junctions and then used for analysis of Sμ-Sα and Sμ-Sγ1 junctions from CH12F3 cells and primary murine B cells, respectively. CSReport identifies junction segment breakpoints on reference sequences and junction structure (blunt-ended junctions or junctions with insertions or microhomology). Besides the ability to analyze unprecedentedly large libraries of junction sequences, CSReport will provide a unified framework for CSR junction studies. Our results show that CSReport is an accurate tool for analysis of sequences from our HTS-based protocol for CSR junctions, thereby facilitating and accelerating their study. Copyright © 2017 by The American Association of Immunologists, Inc.

Deep sequencing reveals different compositions of mRNA transcribed from the F8 gene in a panel of FVIII-producing CHO cell lines

DEFF Research Database (Denmark)

Kaas, Christian Schrøder; Bolt, Gert; Hansen, Jens J

2015-01-01

orders of magnitude lower than for antibodies. In the present study we investigated CHO DXB11 cells transfected with a plasmid encoding human coagulation factor VIII. Single cell clones were isolated from the pool of transfectants and a panel of 14 clones representing a dynamic range of FVIII...... FVIII productivity. It was found that three MTX resistant, nonproducing clones had different truncations of the F8 transcripts. We find that by using deep sequencing, in contrast to microarray technology, for determining the transcriptome from CHO transfectants, we are able to accurately deduce...

Deep learning, audio adversaries, and music content analysis

DEFF Research Database (Denmark)

Kereliuk, Corey Mose; Sturm, Bob L.; Larsen, Jan

2015-01-01

We present the concept of adversarial audio in the context of deep neural networks (DNNs) for music content analysis. An adversary is an algorithm that makes minor perturbations to an input that cause major repercussions to the system response. In particular, we design an adversary for a DNN...... that takes as input short-time spectral magnitudes of recorded music and outputs a high-level music descriptor. We demonstrate how this adversary can make the DNN behave in any way with only extremely minor changes to the music recording signal. We show that the adversary cannot be neutralised by a simple...... filtering of the input. Finally, we discuss adversaries in the broader context of the evaluation of music content analysis systems....

The Ebola virus VP35 protein binds viral immunostimulatory and host RNAs identified through deep sequencing.

Directory of Open Access Journals (Sweden)

Kari A Dilley

Full Text Available Ebola virus and Marburg virus are members of the Filovirdae family and causative agents of hemorrhagic fever with high fatality rates in humans. Filovirus virulence is partially attributed to the VP35 protein, a well-characterized inhibitor of the RIG-I-like receptor pathway that triggers the antiviral interferon (IFN response. Prior work demonstrates the ability of VP35 to block potent RIG-I activators, such as Sendai virus (SeV, and this IFN-antagonist activity is directly correlated with its ability to bind RNA. Several structural studies demonstrate that VP35 binds short synthetic dsRNAs; yet, there are no data that identify viral immunostimulatory RNAs (isRNA or host RNAs bound to VP35 in cells. Utilizing a SeV infection model, we demonstrate that both viral isRNA and host RNAs are bound to Ebola and Marburg VP35s in cells. By deep sequencing the purified VP35-bound RNA, we identified the SeV copy-back defective interfering (DI RNA, previously identified as a robust RIG-I activator, as the isRNA bound by multiple filovirus VP35 proteins, including the VP35 protein from the West African outbreak strain (Makona EBOV. Moreover, RNAs isolated from a VP35 RNA-binding mutant were not immunostimulatory and did not include the SeV DI RNA. Strikingly, an analysis of host RNAs bound by wild-type, but not mutant, VP35 revealed that select host RNAs are preferentially bound by VP35 in cell culture. Taken together, these data support a model in which VP35 sequesters isRNA in virus-infected cells to avert RIG-I like receptor (RLR activation.

The Ebola virus VP35 protein binds viral immunostimulatory and host RNAs identified through deep sequencing.

Science.gov (United States)

Dilley, Kari A; Voorhies, Alexander A; Luthra, Priya; Puri, Vinita; Stockwell, Timothy B; Lorenzi, Hernan; Basler, Christopher F; Shabman, Reed S

2017-01-01

Ebola virus and Marburg virus are members of the Filovirdae family and causative agents of hemorrhagic fever with high fatality rates in humans. Filovirus virulence is partially attributed to the VP35 protein, a well-characterized inhibitor of the RIG-I-like receptor pathway that triggers the antiviral interferon (IFN) response. Prior work demonstrates the ability of VP35 to block potent RIG-I activators, such as Sendai virus (SeV), and this IFN-antagonist activity is directly correlated with its ability to bind RNA. Several structural studies demonstrate that VP35 binds short synthetic dsRNAs; yet, there are no data that identify viral immunostimulatory RNAs (isRNA) or host RNAs bound to VP35 in cells. Utilizing a SeV infection model, we demonstrate that both viral isRNA and host RNAs are bound to Ebola and Marburg VP35s in cells. By deep sequencing the purified VP35-bound RNA, we identified the SeV copy-back defective interfering (DI) RNA, previously identified as a robust RIG-I activator, as the isRNA bound by multiple filovirus VP35 proteins, including the VP35 protein from the West African outbreak strain (Makona EBOV). Moreover, RNAs isolated from a VP35 RNA-binding mutant were not immunostimulatory and did not include the SeV DI RNA. Strikingly, an analysis of host RNAs bound by wild-type, but not mutant, VP35 revealed that select host RNAs are preferentially bound by VP35 in cell culture. Taken together, these data support a model in which VP35 sequesters isRNA in virus-infected cells to avert RIG-I like receptor (RLR) activation.

[Predominant strains of polycyclic aromatic hydrocarbon-degrading consortia from deep sea of the Middle Atlantic Ridge].

Science.gov (United States)

Cui, Zhisong; Shao, Zongze

2009-07-01

In order to identify the predominant strains of polycyclic aromatic hydrocarbon (PAH)-degrading consortia harboring in sea water and surface sediment collected from deep sea of the Middle Atlantic Ridge. We employed enrichment method and spread-plate method to isolate cultivable bacteria and PAHs degraders from deep sea samples. Phylogenetic analysis was conducted by 16S rRNA gene sequencing of the bacteria. Then we analyzed the dominant bacteria in the PAHs-degrading consortia by denaturing gradient gel electrophoresis (DGGE) combined with DNA sequencing. Altogether 16 cultivable bacteria were obtained, including one PAHs degrader Novosphingobium sp. 4D. Phylogenetic analysis showed that strains closely related to Alcanivorax dieselolei NO1A (5/16) and Tistrella mobilis TISTR 1108T (5/16) constituted two biggest groups among the cultivable bacteria. DGGE analysis showed that strain 4L (also 4M and 4N, Alcanivorax dieselolei NO1A, 99.21%), 4D (Novosphingobium pentaromativorans US6-1(T), 97.07%) and 4B (also 4E, 4H and 4K, Tistrella mobilis TISTR 1108T, > 99%) dominated the consortium MC2D. While in consortium MC3CO, the predominant strains were strain 5C (also 5H, Alcanivorax dieselolei NO1A, > 99%), uncultivable strain represented by band 5-8 (Novosphingobium aromaticivorans DSM 12444T, 99.41%), 5J (Tistrella mobilis TISTR 1108T, 99.52%) and 5F (also 5G, Thalassospira lucentensis DSM 14000T, degrading consortia in sea water and surface sediment of Middle Atlantic Ridge deep sea, with Novosphingobium spp. as their main PAHs degraders.

Transmission Bottleneck Size Estimation from Pathogen Deep-Sequencing Data, with an Application to Human Influenza A Virus.

Science.gov (United States)

Sobel Leonard, Ashley; Weissman, Daniel B; Greenbaum, Benjamin; Ghedin, Elodie; Koelle, Katia

2017-07-15

The bottleneck governing infectious disease transmission describes the size of the pathogen population transferred from the donor to the recipient host. Accurate quantification of the bottleneck size is particularly important for rapidly evolving pathogens such as influenza virus, as narrow bottlenecks reduce the amount of transferred viral genetic diversity and, thus, may decrease the rate of viral adaptation. Previous studies have estimated bottleneck sizes governing viral transmission by using statistical analyses of variants identified in pathogen sequencing data. These analyses, however, did not account for variant calling thresholds and stochastic viral replication dynamics within recipient hosts. Because these factors can skew bottleneck size estimates, we introduce a new method for inferring bottleneck sizes that accounts for these factors. Through the use of a simulated data set, we first show that our method, based on beta-binomial sampling, accurately recovers transmission bottleneck sizes, whereas other methods fail to do so. We then apply our method to a data set of influenza A virus (IAV) infections for which viral deep-sequencing data from transmission pairs are available. We find that the IAV transmission bottleneck size estimates in this study are highly variable across transmission pairs, while the mean bottleneck size of 196 virions is consistent with a previous estimate for this data set. Furthermore, regression analysis shows a positive association between estimated bottleneck size and donor infection severity, as measured by temperature. These results support findings from experimental transmission studies showing that bottleneck sizes across transmission events can be variable and influenced in part by epidemiological factors. IMPORTANCE The transmission bottleneck size describes the size of the pathogen population transferred from the donor to the recipient host and may affect the rate of pathogen adaptation within host populations. Recent

Sequence analysis of putative swrW gene required for surfactant ...

African Journals Online (AJOL)

Serratia marcescens produces biosurfactant serrawettin, essential for its population migration behavior. Serrawettin W1 was revealed to be an antibiotic serratamolide that makes it significant for deoxyribonucleic acid (DNA) and protein sequence analysis. Four nucleotide and amino-acid sequences from local strains ...

Phylogenetic analysis of the genus Hordeum using repetitive DNA sequences

DEFF Research Database (Denmark)

Svitashev, S.; Bryngelsson, T.; Vershinin, A.

1994-01-01

A set of six cloned barley (Hordeum vulgare) repetitive DNA sequences was used for the analysis of phylogenetic relationships among 31 species (46 taxa) of the genus Hordeum, using molecular hybridization techniques. In situ hybridization experiments showed dispersed organization of the sequences...

Rapid Response of Eastern Mediterranean Deep Sea Microbial Communities to Oil

Energy Technology Data Exchange (ETDEWEB)

Liu, Jiang; Techtmann, Stephen M.; Woo, Hannah L.; Ning, Daliang; Fortney, Julian L.; Hazen, Terry C.

2017-07-18

Deep marine oil spills like the Deepwater Horizon (DWH) in the Gulf of Mexico have the potential to drastically impact marine systems. Crude oil contamination in marine systems remains a concern, especially for countries around the Mediterranean Sea with off shore oil production. The goal of this study was to investigate the response of indigenous microbial communities to crude oil in the deep Eastern Mediterranean Sea (E. Med.) water column and to minimize potential bias associated with storage and shifts in microbial community structure from sample storage. 16S rRNA amplicon sequencing was combined with GeoChip metagenomic analysis to monitor the microbial community changes to the crude oil and dispersant in on-ship microcosms set up immediately after water collection. After 3 days of incubation at 14 °C, the microbial communities from two different water depths: 824 m and 1210 m became dominated by well-known oil degrading bacteria. The archaeal population and the overall microbial community diversity drastically decreased. Similarly, GeoChip metagenomic analysis revealed a tremendous enrichment of genes related to oil biodegradation, which was consistent with the results from the DWH oil spill. These results highlight a rapid microbial adaption to oil contamination in the deep E. Med., and indicate strong oil biodegradation potentia

Comparative analysis of catfish BAC end sequences with the zebrafish genome

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Abernathy Jason

2009-12-01

Full Text Available Abstract Background Comparative mapping is a powerful tool to transfer genomic information from sequenced genomes to closely related species for which whole genome sequence data are not yet available. However, such an approach is still very limited in catfish, the most important aquaculture species in the United States. This project was initiated to generate additional BAC end sequences and demonstrate their applications in comparative mapping in catfish. Results We reported the generation of 43,000 BAC end sequences and their applications for comparative genome analysis in catfish. Using these and the additional 20,000 existing BAC end sequences as a resource along with linkage mapping and existing physical map, conserved syntenic regions were identified between the catfish and zebrafish genomes. A total of 10,943 catfish BAC end sequences (17.3% had significant BLAST hits to the zebrafish genome (cutoff value ≤ e-5, of which 3,221 were unique gene hits, providing a platform for comparative mapping based on locations of these genes in catfish and zebrafish. Genetic linkage mapping of microsatellites associated with contigs allowed identification of large conserved genomic segments and construction of super scaffolds. Conclusion BAC end sequences and their associated polymorphic markers are great resources for comparative genome analysis in catfish. Highly conserved chromosomal regions were identified to exist between catfish and zebrafish. However, it appears that the level of conservation at local genomic regions are high while a high level of chromosomal shuffling and rearrangements exist between catfish and zebrafish genomes. Orthologous regions established through comparative analysis should facilitate both structural and functional genome analysis in catfish.

Deep Sequencing of Plant and Animal DNA Contained within Traditional Chinese Medicines Reveals Legality Issues and Health Safety Concerns

Science.gov (United States)

Coghlan, Megan L.; Haile, James; Houston, Jayne; Murray, Dáithí C.; White, Nicole E.; Moolhuijzen, Paula; Bellgard, Matthew I.; Bunce, Michael

2012-01-01

Traditional Chinese medicine (TCM) has been practiced for thousands of years, but only within the last few decades has its use become more widespread outside of Asia. Concerns continue to be raised about the efficacy, legality, and safety of many popular complementary alternative medicines, including TCMs. Ingredients of some TCMs are known to include derivatives of endangered, trade-restricted species of plants and animals, and therefore contravene the Convention on International Trade in Endangered Species (CITES) legislation. Chromatographic studies have detected the presence of heavy metals and plant toxins within some TCMs, and there are numerous cases of adverse reactions. It is in the interests of both biodiversity conservation and public safety that techniques are developed to screen medicinals like TCMs. Targeting both the p-loop region of the plastid trnL gene and the mitochondrial 16S ribosomal RNA gene, over 49,000 amplicon sequence reads were generated from 15 TCM samples presented in the form of powders, tablets, capsules, bile flakes, and herbal teas. Here we show that second-generation, high-throughput sequencing (HTS) of DNA represents an effective means to genetically audit organic ingredients within complex TCMs. Comparison of DNA sequence data to reference databases revealed the presence of 68 different plant families and included genera, such as Ephedra and Asarum, that are potentially toxic. Similarly, animal families were identified that include genera that are classified as vulnerable, endangered, or critically endangered, including Asiatic black bear (Ursus thibetanus) and Saiga antelope (Saiga tatarica). Bovidae, Cervidae, and Bufonidae DNA were also detected in many of the TCM samples and were rarely declared on the product packaging. This study demonstrates that deep sequencing via HTS is an efficient and cost-effective way to audit highly processed TCM products and will assist in monitoring their legality and safety especially when

Genome re-sequencing of semi-wild soybean reveals a complex Soja population structure and deep introgression.

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Jie Qiu

Full Text Available Semi-wild soybean is a unique type of soybean that retains both wild and domesticated characteristics, which provides an important intermediate type for understanding the evolution of the subgenus Soja population in the Glycine genus. In this study, a semi-wild soybean line (Maliaodou and a wild line (Lanxi 1 collected from the lower Yangtze regions were deeply sequenced while nine other semi-wild lines were sequenced to a 3-fold genome coverage. Sequence analysis revealed that (1 no independent phylogenetic branch covering all 10 semi-wild lines was observed in the Soja phylogenetic tree; (2 besides two distinct subpopulations of wild and cultivated soybean in the Soja population structure, all semi-wild lines were mixed with some wild lines into a subpopulation rather than an independent one or an intermediate transition type of soybean domestication; (3 high heterozygous rates (0.19-0.49 were observed in several semi-wild lines; and (4 over 100 putative selective regions were identified by selective sweep analysis, including those related to the development of seed size. Our results suggested a hybridization origin for the semi-wild soybean, which makes a complex Soja population structure.

Probing the Rare Biosphere of the North-West Mediterranean Sea: An Experiment with High Sequencing Effort.

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Bibiana G Crespo

Full Text Available High-throughput sequencing (HTS techniques have suggested the existence of a wealth of species with very low relative abundance: the rare biosphere. We attempted to exhaustively map this rare biosphere in two water samples by performing an exceptionally deep pyrosequencing analysis (~500,000 final reads per sample. Species data were derived by a 97% identity criterion and various parametric distributions were fitted to the observed counts. Using the best-fitting Sichel distribution we estimate a total species richness of 1,568-1,669 (95% Credible Interval and 5,027-5,196 for surface and deep water samples respectively, implying that 84-89% of the total richness in those two samples was sequenced, and we predict that a quadrupling of the present sequencing effort would suffice to observe 90% of the total richness in both samples. Comparing the HTS results with a culturing approach we found that most of the cultured taxa were not obtained by HTS, despite the high sequencing effort. Culturing therefore remains a useful tool for uncovering marine bacterial diversity, in addition to its other uses for studying the ecology of marine bacteria.

Probing the Rare Biosphere of the North-West Mediterranean Sea: An Experiment with High Sequencing Effort.

Science.gov (United States)

Crespo, Bibiana G; Wallhead, Philip J; Logares, Ramiro; Pedrós-Alió, Carlos

2016-01-01

High-throughput sequencing (HTS) techniques have suggested the existence of a wealth of species with very low relative abundance: the rare biosphere. We attempted to exhaustively map this rare biosphere in two water samples by performing an exceptionally deep pyrosequencing analysis (~500,000 final reads per sample). Species data were derived by a 97% identity criterion and various parametric distributions were fitted to the observed counts. Using the best-fitting Sichel distribution we estimate a total species richness of 1,568-1,669 (95% Credible Interval) and 5,027-5,196 for surface and deep water samples respectively, implying that 84-89% of the total richness in those two samples was sequenced, and we predict that a quadrupling of the present sequencing effort would suffice to observe 90% of the total richness in both samples. Comparing the HTS results with a culturing approach we found that most of the cultured taxa were not obtained by HTS, despite the high sequencing effort. Culturing therefore remains a useful tool for uncovering marine bacterial diversity, in addition to its other uses for studying the ecology of marine bacteria.

[Phylogenetic diversity of microorganisms associated with the deep-water sponge Baikalospongia intermedia].

Science.gov (United States)

Kalyzhnaya, O V; Itskovich, V B

2014-07-01

The diversity of bacteria associated with deep-water sponge Baikalospongia intermedia was evaluated by sequence analysis of 16S rRNA genes from two sponge samples collected in Lake Baikal from depths of 550 and 1204 m. A total of 64 operational taxonomic units, belonging to nine bacterial phyla, Proteobacteria (classes Alphaproteobacteria,. Betaproteobacteria, Gammaproteobacteria, and Deltaproteobacteria), Actinobacteria, Planctomycetes, Cloroflexi, Verrucomicrobia, Acidobacteria, Chlorobi, and Nitrospirae, including candidate phylum WS5, were identified. Phylogenetic analysis showed that the examined communities contained phylotypes exhibiting homology to uncultured bacteria from different lake ecosystems, freshwater sediments, soil and geological formations. Moreover, a number of phylotypes were relative to psychrophilic, methane-oxidizing, sulfate-reducing bacteria, and to microorganisms resistant to the influence of heavy metals. It seems likely that the unusual habitation conditions of deep-water sponges contribute to the taxonomic diversity of associated bacteria and have an influence on the presence of functionally important microorganisms in bacterial communities.

Virus pathotype and deep sequencing of the HA gene of a low pathogenicity H7N1 avian influenza virus causing mortality in Turkeys.

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Munir Iqbal

Full Text Available Low pathogenicity avian influenza (LPAI viruses of the H7 subtype generally cause mild disease in poultry. However the evolution of a LPAI virus into highly pathogenic avian influenza (HPAI virus results in the generation of a virus that can cause severe disease and death. The classification of these two pathotypes is based, in part, on disease signs and death in chickens, as assessed in an intravenous pathogenicity test, but the effect of LPAI viruses in turkeys is less well understood. During an investigation of LPAI virus infection of turkeys, groups of three-week-old birds inoculated with A/chicken/Italy/1279/99 (H7N1 showed severe disease signs and died or were euthanised within seven days of infection. Virus was detected in many internal tissues and organs from culled birds. To examine the possible evolution of the infecting virus to a highly pathogenic form in these turkeys, sequence analysis of the haemagglutinin (HA gene cleavage site was carried out by analysing multiple cDNA amplicons made from swabs and tissue sample extracts employing Sanger and Next Generation Sequencing. In addition, a RT-PCR assay to detect HPAI virus was developed. There was no evidence of the presence of HPAI virus in either the virus used as inoculum or from swabs taken from infected birds. However, a small proportion (<0.5% of virus carried in individual tracheal or liver samples did contain a molecular signature typical of a HPAI virus at the HA cleavage site. All the signature sequences were identical and were similar to HPAI viruses collected during the Italian epizootic in 1999/2000. We assume that the detection of HPAI virus in tissue samples following infection with A/chicken/Italy/1279/99 reflected amplification of a virus present at very low levels within the mixed inoculum but, strikingly, we observed no new HPAI virus signatures in the amplified DNA analysed by deep-sequencing.

Experimental evolution, genetic analysis and genome re-sequencing reveal the mutation conferring artemisinin resistance in an isogenic lineage of malaria parasites

KAUST Repository

Hunt, Paul; Martinelli, Axel; Modrzynska, Katarzyna; Borges, Sofia; Creasey, Alison; Rodrigues, Louise; Beraldi, Dario; Loewe, Laurence; Fawcett, Richard; Kumar, Sujai; Thomson, Marian; Trivedi, Urmi; Otto, Thomas D; Pain, Arnab; Blaxter, Mark; Cravo, Pedro

2010-01-01

was mapped to a region of chromosome 2 by Linkage Group Selection in two different genetic crosses. Whole-genome deep coverage short-read re-sequencing (IlluminaSolexa) defined the point mutations, insertions, deletions and copy-number variations arising

An Imaging And Graphics Workstation For Image Sequence Analysis

Science.gov (United States)

Mostafavi, Hassan

1990-01-01

This paper describes an application-specific engineering workstation designed and developed to analyze imagery sequences from a variety of sources. The system combines the software and hardware environment of the modern graphic-oriented workstations with the digital image acquisition, processing and display techniques. The objective is to achieve automation and high throughput for many data reduction tasks involving metric studies of image sequences. The applications of such an automated data reduction tool include analysis of the trajectory and attitude of aircraft, missile, stores and other flying objects in various flight regimes including launch and separation as well as regular flight maneuvers. The workstation can also be used in an on-line or off-line mode to study three-dimensional motion of aircraft models in simulated flight conditions such as wind tunnels. The system's key features are: 1) Acquisition and storage of image sequences by digitizing real-time video or frames from a film strip; 2) computer-controlled movie loop playback, slow motion and freeze frame display combined with digital image sharpening, noise reduction, contrast enhancement and interactive image magnification; 3) multiple leading edge tracking in addition to object centroids at up to 60 fields per second from both live input video or a stored image sequence; 4) automatic and manual field-of-view and spatial calibration; 5) image sequence data base generation and management, including the measurement data products; 6) off-line analysis software for trajectory plotting and statistical analysis; 7) model-based estimation and tracking of object attitude angles; and 8) interface to a variety of video players and film transport sub-systems.

PseudoMLSA: a database for multigenic sequence analysis of Pseudomonas species

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Lalucat Jorge

2010-04-01

Full Text Available Abstract Background The genus Pseudomonas comprises more than 100 species of environmental, clinical, agricultural, and biotechnological interest. Although, the recommended method for discriminating bacterial species is DNA-DNA hybridisation, alternative techniques based on multigenic sequence analysis are becoming a common practice in bacterial species discrimination studies. Since there is not a general criterion for determining which genes are more useful for species resolution; the number of strains and genes analysed is increasing continuously. As a result, sequences of different genes are dispersed throughout several databases. This sequence information needs to be collected in a common database, in order to be useful for future identification-based projects. Description The PseudoMLSA Database is a comprehensive database of multiple gene sequences from strains of Pseudomonas species. The core of the database is composed of selected gene sequences from all Pseudomonas type strains validly assigned to the genus through 2008. The database is aimed to be useful for MultiLocus Sequence Analysis (MLSA procedures, for the identification and characterisation of any Pseudomonas bacterial isolate. The sequences are available for download via a direct connection to the National Center for Biotechnology Information (NCBI. Additionally, the database includes an online BLAST interface for flexible nucleotide queries and similarity searches with the user's datasets, and provides a user-friendly output for easily parsing, navigating, and analysing BLAST results. Conclusions The PseudoMLSA database amasses strains and sequence information of validly described Pseudomonas species, and allows free querying of the database via a user-friendly, web-based interface available at http://www.uib.es/microbiologiaBD/Welcome.html. The web-based platform enables easy retrieval at strain or gene sequence information level; including references to published peer

De novo transcriptome sequencing and sequence analysis of the malaria vector Anopheles sinensis (Diptera: Culicidae)

Science.gov (United States)

2014-01-01

Background Anopheles sinensis is the major malaria vector in China and Southeast Asia. Vector control is one of the most effective measures to prevent malaria transmission. However, there is little transcriptome information available for the malaria vector. To better understand the biological basis of malaria transmission and to develop novel and effective means of vector control, there is a need to build a transcriptome dataset for functional genomics analysis by large-scale RNA sequencing (RNA-seq). Methods To provide a more comprehensive and complete transcriptome of An. sinensis, eggs, larvae, pupae, male adults and female adults RNA were pooled together for cDNA preparation, sequenced using the Illumina paired-end sequencing technology and assembled into unigenes. These unigenes were then analyzed in their genome mapping, functional annotation, homology, codon usage bias and simple sequence repeats (SSRs). Results Approximately 51.6 million clean reads were obtained, trimmed, and assembled into 38,504 unigenes with an average length of 571 bp, an N50 of 711 bp, and an average GC content 51.26%. Among them, 98.4% of unigenes could be mapped onto the reference genome, and 69% of unigenes could be annotated with known biological functions. Homology analysis identified certain numbers of An. sinensis unigenes that showed homology or being putative 1:1 orthologues with genomes of other Dipteran species. Codon usage bias was analyzed and 1,904 SSRs were detected, which will provide effective molecular markers for the population genetics of this species. Conclusions Our data and analysis provide the most comprehensive transcriptomic resource and characteristics currently available for An. sinensis, and will facilitate genetic, genomic studies, and further vector control of An. sinensis. PMID:25000941

Deep sequencing reveals distinct patterns of DNA methylation in prostate cancer.

Science.gov (United States)

Kim, Jung H; Dhanasekaran, Saravana M; Prensner, John R; Cao, Xuhong; Robinson, Daniel; Kalyana-Sundaram, Shanker; Huang, Christina; Shankar, Sunita; Jing, Xiaojun; Iyer, Matthew; Hu, Ming; Sam, Lee; Grasso, Catherine; Maher, Christopher A; Palanisamy, Nallasivam; Mehra, Rohit; Kominsky, Hal D; Siddiqui, Javed; Yu, Jindan; Qin, Zhaohui S; Chinnaiyan, Arul M

2011-07-01

Beginning with precursor lesions, aberrant DNA methylation marks the entire spectrum of prostate cancer progression. We mapped the global DNA methylation patterns in select prostate tissues and cell lines using MethylPlex-next-generation sequencing (M-NGS). Hidden Markov model-based next-generation sequence analysis identified ∼68,000 methylated regions per sample. While global CpG island (CGI) methylation was not differential between benign adjacent and cancer samples, overall promoter CGI methylation significantly increased from ~12.6% in benign samples to 19.3% and 21.8% in localized and metastatic cancer tissues, respectively (P-value prostate tissues, 2481 differentially methylated regions (DMRs) are cancer-specific, including numerous novel DMRs. A novel cancer-specific DMR in the WFDC2 promoter showed frequent methylation in cancer (17/22 tissues, 6/6 cell lines), but not in the benign tissues (0/10) and normal PrEC cells. Integration of LNCaP DNA methylation and H3K4me3 data suggested an epigenetic mechanism for alternate transcription start site utilization, and these modifications segregated into distinct regions when present on the same promoter. Finally, we observed differences in repeat element methylation, particularly LINE-1, between ERG gene fusion-positive and -negative cancers, and we confirmed this observation using pyrosequencing on a tissue panel. This comprehensive methylome map will further our understanding of epigenetic regulation in prostate cancer progression.

Deep sequencing of the viral phoH gene reveals temporal variation, depth-specific composition, and persistent dominance of the same viral phoH genes in the Sargasso Sea

Directory of Open Access Journals (Sweden)

Dawn B. Goldsmith

2015-06-01

Full Text Available Deep sequencing of the viral phoH gene, a host-derived auxiliary metabolic gene, was used to track viral diversity throughout the water column at the Bermuda Atlantic Time-series Study (BATS site in the summer (September and winter (March of three years. Viral phoH sequences reveal differences in the viral communities throughout a depth profile and between seasons in the same year. Variation was also detected between the same seasons in subsequent years, though these differences were not as great as the summer/winter distinctions. Over 3,600 phoH operational taxonomic units (OTUs; 97% sequence identity were identified. Despite high richness, most phoH sequences belong to a few large, common OTUs whereas the majority of the OTUs are small and rare. While many OTUs make sporadic appearances at just a few times or depths, a small number of OTUs dominate the community throughout the seasons, depths, and years.

Regularized rare variant enrichment analysis for case-control exome sequencing data.

Science.gov (United States)

Larson, Nicholas B; Schaid, Daniel J

2014-02-01

Rare variants have recently garnered an immense amount of attention in genetic association analysis. However, unlike methods traditionally used for single marker analysis in GWAS, rare variant analysis often requires some method of aggregation, since single marker approaches are poorly powered for typical sequencing study sample sizes. Advancements in sequencing technologies have rendered next-generation sequencing platforms a realistic alternative to traditional genotyping arrays. Exome sequencing in particular not only provides base-level resolution of genetic coding regions, but also a natural paradigm for aggregation via genes and exons. Here, we propose the use of penalized regression in combination with variant aggregation measures to identify rare variant enrichment in exome sequencing data. In contrast to marginal gene-level testing, we simultaneously evaluate the effects of rare variants in multiple genes, focusing on gene-based least absolute shrinkage and selection operator (LASSO) and exon-based sparse group LASSO models. By using gene membership as a grouping variable, the sparse group LASSO can be used as a gene-centric analysis of rare variants while also providing a penalized approach toward identifying specific regions of interest. We apply extensive simulations to evaluate the performance of these approaches with respect to specificity and sensitivity, comparing these results to multiple competing marginal testing methods. Finally, we discuss our findings and outline future research. © 2013 WILEY PERIODICALS, INC.

Survey sequencing and comparative analysis of the elephant shark (Callorhinchus milii genome.

Directory of Open Access Journals (Sweden)

Byrappa Venkatesh

2007-04-01

Full Text Available Owing to their phylogenetic position, cartilaginous fishes (sharks, rays, skates, and chimaeras provide a critical reference for our understanding of vertebrate genome evolution. The relatively small genome of the elephant shark, Callorhinchus milii, a chimaera, makes it an attractive model cartilaginous fish genome for whole-genome sequencing and comparative analysis. Here, the authors describe survey sequencing (1.4x coverage and comparative analysis of the elephant shark genome, one of the first cartilaginous fish genomes to be sequenced to this depth. Repetitive sequences, represented mainly by a novel family of short interspersed element-like and long interspersed element-like sequences, account for about 28% of the elephant shark genome. Fragments of approximately 15,000 elephant shark genes reveal specific examples of genes that have been lost differentially during the evolution of tetrapod and teleost fish lineages. Interestingly, the degree of conserved synteny and conserved sequences between the human and elephant shark genomes are higher than that between human and teleost fish genomes. Elephant shark contains putative four Hox clusters indicating that, unlike teleost fish genomes, the elephant shark genome has not experienced an additional whole-genome duplication. These findings underscore the importance of the elephant shark as a critical reference vertebrate genome for comparative analysis of the human and other vertebrate genomes. This study also demonstrates that a survey-sequencing approach can be applied productively for comparative analysis of distantly related vertebrate genomes.

[Complete genome sequencing and sequence analysis of BCG Tice].

Science.gov (United States)

Wang, Zhiming; Pan, Yuanlong; Wu, Jun; Zhu, Baoli

2012-10-04

The objective of this study is to obtain the complete genome sequence of Bacillus Calmette-Guerin Tice (BCG Tice), in order to provide more information about the molecular biology of BCG Tice and design more reasonable vaccines to prevent tuberculosis. We assembled the data from high-throughput sequencing with SOAPdenovo software, with many contigs and scaffolds obtained. There are many sequence gaps and physical gaps remained as a result of regional low coverage and low quality. We designed primers at the end of contigs and performed PCR amplification in order to link these contigs and scaffolds. With various enzymes to perform PCR amplification, adjustment of PCR reaction conditions, and combined with clone construction to sequence, all the gaps were finished. We obtained the complete genome sequence of BCG Tice and submitted it to GenBank of National Center for Biotechnology Information (NCBI). The genome of BCG Tice is 4334064 base pairs in length, with GC content 65.65%. The problems and strategies during the finishing step of BCG Tice sequencing are illuminated here, with the hope of affording some experience to those who are involved in the finishing step of genome sequencing. The microarray data were verified by our results.

Neuronal pathology in deep grey matter structures: a multimodal imaging analysis combining PET and MRI

Energy Technology Data Exchange (ETDEWEB)

Bosque-Freeman, L.; Leroy, C.; Galanaud, D.; Sureau, F.; Assouad, R.; Tourbah, A.; Papeix, C.; Comtat, C.; Trebossen, R.; Lubetzki, C.; Delforge, J.; Bottlaender, M.; Stankoff, B. [Serv. Hosp. Frederic Joliot, Orsay (France)

2009-07-01

Objective: To assess neuronal damage in deep gray matter structures by positron emission tomography (PET) using [{sup 11}C]-flumazenil (FMZ), a specific central benzodiazepine receptor antagonist, and [{sup 18}F]-fluorodeoxyglucose (FDG), which reflects neuronal metabolism. To compare results obtained by PET and those with multimodal magnetic resonance imaging (MRI). Background: It is now accepted that neuronal injury plays a crucial role in the occurrence and progression of neurological disability in multiple sclerosis (MS). To date, available MRI techniques do not specifically assess neuronal damage, but early abnormalities, such as iron deposition or atrophy, have been described in deep gray matter structures. Whether those MRI modifications correspond to neuronal damage remains to be further investigated. Materials and methods: Nine healthy volunteers were compared to 10 progressive and 9 relapsing remitting (RR) MS patients. Each subject performed two PET examinations with [{sup 11}C]-FMZ and [{sup 18}F]-FDG, on a high resolution research tomograph dedicated to brain imaging (Siemens Medical Solution, spatial resolution of 2.5 mm). Deep gray matter regions were manually segmented on T1-weighted MR images with the mutual information algorithm (www.brainvisa.info), and co-registered with PET images. A multimodal MRI including T1 pre and post gadolinium, T2-proton density sequences, magnetization transfer, diffusion tensor, and protonic spectroscopy was also performed for each subject. Results: On PET with [{sup 11}C]-FMZ, there was a pronounced decrease in receptor density for RR patients in all deep gray matter structures investigated, whereas the density was unchanged or even increased in the same regions for progressive patients. Whether the different patterns between RR and progressive patients reflect distinct pathogenic mechanisms is currently investigated by comparing PET and multimodal MRI results. Conclusion: Combination of PET and multimodal MR imaging

Docker Containers for Deep Learning Experiments

OpenAIRE

Gerke, Paul K.

2017-01-01

Deep learning is a powerful tool to solve problems in the area of image analysis. The dominant compute platform for deep learning is Nvidia’s proprietary CUDA, which can only be used together with Nvidia graphics cards. The nivida-docker project allows exposing Nvidia graphics cards to docker containers and thus makes it possible to run deep learning experiments in docker containers.In our department, we use deep learning to solve problems in the area of medical image analysis and use docker ...

FAST: FAST Analysis of Sequences Toolbox

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Travis J. Lawrence

2015-05-01

Full Text Available FAST (FAST Analysis of Sequences Toolbox provides simple, powerful open source command-line tools to filter, transform, annotate and analyze biological sequence data. Modeled after the GNU (GNU’s Not Unix Textutils such as grep, cut, and tr, FAST tools such as fasgrep, fascut, and fastr make it easy to rapidly prototype expressive bioinformatic workflows in a compact and generic command vocabulary. Compact combinatorial encoding of data workflows with FAST commands can simplify the documentation and reproducibility of bioinformatic protocols, supporting better transparency in biological data science. Interface self-consistency and conformity with conventions of GNU, Matlab, Perl, BioPerl, R and GenBank help make FAST easy and rewarding to learn. FAST automates numerical, taxonomic, and text-based sorting, selection and transformation of sequence records and alignment sites based on content, index ranges, descriptive tags, annotated features, and in-line calculated analytics, including composition and codon usage. Automated content- and feature-based extraction of sites and support for molecular population genetic statistics makes FAST useful for molecular evolutionary analysis. FAST is portable, easy to install and secure thanks to the relative maturity of its Perl and BioPerl foundations, with stable releases posted to CPAN. Development as well as a publicly accessible Cookbook and Wiki are available on the FAST GitHub repository at https://github.com/tlawrence3/FAST. The default data exchange format in FAST is Multi-FastA (specifically, a restriction of BioPerl FastA format. Sanger and Illumina 1.8+ FastQ formatted files are also supported. FAST makes it easier for non-programmer biologists to interactively investigate and control biological data at the speed of thought.

MicroRNAs in Amoebozoa: deep sequencing of the small RNA population in the social amoeba Dictyostelium discoideum reveals developmentally regulated microRNAs.

Science.gov (United States)

Avesson, Lotta; Reimegård, Johan; Wagner, E Gerhart H; Söderbom, Fredrik

2012-10-01

The RNA interference machinery has served as a guardian of eukaryotic genomes since the divergence from prokaryotes. Although the basic components have a shared origin, silencing pathways directed by small RNAs have evolved in diverse directions in different eukaryotic lineages. Micro (mi)RNAs regulate protein-coding genes and play vital roles in plants and animals, but less is known about their functions in other organisms. Here, we report, for the first time, deep sequencing of small RNAs from the social amoeba Dictyostelium discoideum. RNA from growing single-cell amoebae as well as from two multicellular developmental stages was sequenced. Computational analyses combined with experimental data reveal the expression of miRNAs, several of them exhibiting distinct expression patterns during development. To our knowledge, this is the first report of miRNAs in the Amoebozoa supergroup. We also show that overexpressed miRNA precursors generate miRNAs and, in most cases, miRNA* sequences, whose biogenesis is dependent on the Dicer-like protein DrnB, further supporting the presence of miRNAs in D. discoideum. In addition, we find miRNAs processed from hairpin structures originating from an intron as well as from a class of repetitive elements. We believe that these repetitive elements are sources for newly evolved miRNAs.

Comparing sequencing assays and human-machine analyses in actionable genomics for glioblastoma.

Science.gov (United States)

Wrzeszczynski, Kazimierz O; Frank, Mayu O; Koyama, Takahiko; Rhrissorrakrai, Kahn; Robine, Nicolas; Utro, Filippo; Emde, Anne-Katrin; Chen, Bo-Juen; Arora, Kanika; Shah, Minita; Vacic, Vladimir; Norel, Raquel; Bilal, Erhan; Bergmann, Ewa A; Moore Vogel, Julia L; Bruce, Jeffrey N; Lassman, Andrew B; Canoll, Peter; Grommes, Christian; Harvey, Steve; Parida, Laxmi; Michelini, Vanessa V; Zody, Michael C; Jobanputra, Vaidehi; Royyuru, Ajay K; Darnell, Robert B

2017-08-01

To analyze a glioblastoma tumor specimen with 3 different platforms and compare potentially actionable calls from each. Tumor DNA was analyzed by a commercial targeted panel. In addition, tumor-normal DNA was analyzed by whole-genome sequencing (WGS) and tumor RNA was analyzed by RNA sequencing (RNA-seq). The WGS and RNA-seq data were analyzed by a team of bioinformaticians and cancer oncologists, and separately by IBM Watson Genomic Analytics (WGA), an automated system for prioritizing somatic variants and identifying drugs. More variants were identified by WGS/RNA analysis than by targeted panels. WGA completed a comparable analysis in a fraction of the time required by the human analysts. The development of an effective human-machine interface in the analysis of deep cancer genomic datasets may provide potentially clinically actionable calls for individual patients in a more timely and efficient manner than currently possible. NCT02725684.

Application of sequence stratigraphy to carbonate reservoir prediction, Early Palaeozoic eastern Warburton basin, South Australia

Energy Technology Data Exchange (ETDEWEB)

Xiaowen S.; Stuart, W.J.

1996-12-31

The Early Palaeozoic Warburton Basin underlies the gas and oil producing Cooper and Eromanga Basins. Postdepositional tectonism created high potential fracture porosities, complicating the stratigraphy and making reservoir prediction difficult. Sequence stratigraphy integrating core, cuttings, well-log, seismic and biostratigraphic data has recognized a carbonate-dominated to mixed carbonate/siliciclastic supersequence comprising several depositional sequences. Biostratigraphy based on trilobites and conodonts ensures reliable well and seismic correlations across structurally complex areas. Lithofacies interpretation indicates sedimentary environments ranging from carbonate inner shelf, peritidal, shelf edge, deep outer shelf and slope to basin. Log facies show gradually upward shallowing trends or abrupt changes indicating possible sequence boundaries. With essential depositional models and sequence analysis from well data, seismic facies suggest general reflection configurations including parallel-continuous layered patterns indicating uniform neuritic shelf, and mounded structures suggesting carbonate build-ups and pre-existing volcanic relief. Seismic stratigraphy also reveals inclined slope and onlapping margins of a possibly isolated platform geometry. The potential reservoirs are dolomitized carbonates containing oomoldic, vuggy, intercrystalline and fracture porosities in lowstand systems tracts either on carbonate mounds and shelf crests or below shelf edge. The source rock is a deep basinal argillaceous mudstone, and the seal is fine-grained siltstone/shale of the transgressive system tract.

Application of sequence stratigraphy to carbonate reservoir prediction, Early Palaeozoic eastern Warburton basin, South Australia

Energy Technology Data Exchange (ETDEWEB)

Xiaowen S.; Stuart, W.J.

1996-01-01

The Early Palaeozoic Warburton Basin underlies the gas and oil producing Cooper and Eromanga Basins. Postdepositional tectonism created high potential fracture porosities, complicating the stratigraphy and making reservoir prediction difficult. Sequence stratigraphy integrating core, cuttings, well-log, seismic and biostratigraphic data has recognized a carbonate-dominated to mixed carbonate/siliciclastic supersequence comprising several depositional sequences. Biostratigraphy based on trilobites and conodonts ensures reliable well and seismic correlations across structurally complex areas. Lithofacies interpretation indicates sedimentary environments ranging from carbonate inner shelf, peritidal, shelf edge, deep outer shelf and slope to basin. Log facies show gradually upward shallowing trends or abrupt changes indicating possible sequence boundaries. With essential depositional models and sequence analysis from well data, seismic facies suggest general reflection configurations including parallel-continuous layered patterns indicating uniform neuritic shelf, and mounded structures suggesting carbonate build-ups and pre-existing volcanic relief. Seismic stratigraphy also reveals inclined slope and onlapping margins of a possibly isolated platform geometry. The potential reservoirs are dolomitized carbonates containing oomoldic, vuggy, intercrystalline and fracture porosities in lowstand systems tracts either on carbonate mounds and shelf crests or below shelf edge. The source rock is a deep basinal argillaceous mudstone, and the seal is fine-grained siltstone/shale of the transgressive system tract.

A DNA Structure-Based Bionic Wavelet Transform and Its Application to DNA Sequence Analysis

Directory of Open Access Journals (Sweden)

Fei Chen

2003-01-01

Full Text Available DNA sequence analysis is of great significance for increasing our understanding of genomic functions. An important task facing us is the exploration of hidden structural information stored in the DNA sequence. This paper introduces a DNA structure-based adaptive wavelet transform (WT – the bionic wavelet transform (BWT – for DNA sequence analysis. The symbolic DNA sequence can be separated into four channels of indicator sequences. An adaptive symbol-to-number mapping, determined from the structural feature of the DNA sequence, was introduced into WT. It can adjust the weight value of each channel to maximise the useful energy distribution of the whole BWT output. The performance of the proposed BWT was examined by analysing synthetic and real DNA sequences. Results show that BWT performs better than traditional WT in presenting greater energy distribution. This new BWT method should be useful for the detection of the latent structural features in future DNA sequence analysis.

OTU analysis using metagenomic shotgun sequencing data.

Directory of Open Access Journals (Sweden)

Xiaolin Hao

Full Text Available Because of technological limitations, the primer and amplification biases in targeted sequencing of 16S rRNA genes have veiled the true microbial diversity underlying environmental samples. However, the protocol of metagenomic shotgun sequencing provides 16S rRNA gene fragment data with natural immunity against the biases raised during priming and thus the potential of uncovering the true structure of microbial community by giving more accurate predictions of operational taxonomic units (OTUs. Nonetheless, the lack of statistically rigorous comparison between 16S rRNA gene fragments and other data types makes it difficult to interpret previously reported results using 16S rRNA gene fragments. Therefore, in the present work, we established a standard analysis pipeline that would help confirm if the differences in the data are true or are just due to potential technical bias. This pipeline is built by using simulated data to find optimal mapping and OTU prediction methods. The comparison between simulated datasets revealed a relationship between 16S rRNA gene fragments and full-length 16S rRNA sequences that a 16S rRNA gene fragment having a length >150 bp provides the same accuracy as a full-length 16S rRNA sequence using our proposed pipeline, which could serve as a good starting point for experimental design and making the comparison between 16S rRNA gene fragment-based and targeted 16S rRNA sequencing-based surveys possible.

Deep sequencing-based identification of small regulatory RNAs in Synechocystis sp. PCC 6803.

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Wen Xu

Full Text Available Synechocystis sp. PCC 6803 is a genetically tractable model organism for photosynthesis research. The genome of Synechocystis sp. PCC 6803 consists of a circular chromosome and seven plasmids. The importance of small regulatory RNAs (sRNAs as mediators of a number of cellular processes in bacteria has begun to be recognized. However, little is known regarding sRNAs in Synechocystis sp. PCC 6803. To provide a comprehensive overview of sRNAs in this model organism, the sRNAs of Synechocystis sp. PCC 6803 were analyzed using deep sequencing, and 7,951,189 reads were obtained. High quality mapping reads (6,127,890 were mapped onto the genome and assembled into 16,192 transcribed regions (clusters based on read overlap. A total number of 5211 putative sRNAs were revealed from the genome and the 4 megaplasmids, and 27 of these molecules, including four from plasmids, were confirmed by RT-PCR. In addition, possible target genes regulated by all of the putative sRNAs identified in this study were predicted by IntaRNA and analyzed for functional categorization and biological pathways, which provided evidence that sRNAs are indeed involved in many different metabolic pathways, including basic metabolic pathways, such as glycolysis/gluconeogenesis, the citrate cycle, fatty acid metabolism and adaptations to environmentally stress-induced changes. The information from this study provides a valuable reservoir for understanding the sRNA-mediated regulation of the complex physiology and metabolic processes of cyanobacteria.

The complete genome of Zunongwangia profunda SM-A87 reveals its adaptation to the deep-sea environment and ecological role in sedimentary organic nitrogen degradation

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Zhou Bai-Cheng

2010-04-01

Full Text Available Abstract Background Zunongwangia profunda SM-A87, which was isolated from deep-sea sediment, is an aerobic, gram-negative bacterium that represents a new genus of Flavobacteriaceae. This is the first sequenced genome of a deep-sea bacterium from the phylum Bacteroidetes. Results The Z. profunda SM-A87 genome has a single 5 128 187-bp circular chromosome with no extrachromosomal elements and harbors 4 653 predicted protein-coding genes. SM-A87 produces a large amount of capsular polysaccharides and possesses two polysaccharide biosynthesis gene clusters. It has a total of 130 peptidases, 61 of which have signal peptides. In addition to extracellular peptidases, SM-A87 also has various extracellular enzymes for carbohydrate, lipid and DNA degradation. These extracellular enzymes suggest that the bacterium is able to hydrolyze organic materials in the sediment, especially carbohydrates and proteinaceous organic nitrogen. There are two clustered regularly interspaced short palindromic repeats in the genome, but their spacers do not match any sequences in the public sequence databases. SM-A87 is a moderate halophile. Our protein isoelectric point analysis indicates that extracellular proteins have lower predicted isoelectric points than intracellular proteins. SM-A87 accumulates organic osmolytes in the cell, so its extracelluar proteins are more halophilic than its intracellular proteins. Conclusion Here, we present the first complete genome of a deep-sea sedimentary bacterium from the phylum Bacteroidetes. The genome analysis shows that SM-A87 has some common features of deep-sea bacteria, as well as an important capacity to hydrolyze sedimentary organic nitrogen.

Sequence quality analysis tool for HIV type 1 protease and reverse transcriptase.

Science.gov (United States)

Delong, Allison K; Wu, Mingham; Bennett, Diane; Parkin, Neil; Wu, Zhijin; Hogan, Joseph W; Kantor, Rami

2012-08-01

Access to antiretroviral therapy is increasing globally and drug resistance evolution is anticipated. Currently, protease (PR) and reverse transcriptase (RT) sequence generation is increasing, including the use of in-house sequencing assays, and quality assessment prior to sequence analysis is essential. We created a computational HIV PR/RT Sequence Quality Analysis Tool (SQUAT) that runs in the R statistical environment. Sequence quality thresholds are calculated from a large dataset (46,802 PR and 44,432 RT sequences) from the published literature ( http://hivdb.Stanford.edu ). Nucleic acid sequences are read into SQUAT, identified, aligned, and translated. Nucleic acid sequences are flagged if with >five 1-2-base insertions; >one 3-base insertion; >one deletion; >six PR or >18 RT ambiguous bases; >three consecutive PR or >four RT nucleic acid mutations; >zero stop codons; >three PR or >six RT ambiguous amino acids; >three consecutive PR or >four RT amino acid mutations; >zero unique amino acids; or 15% genetic distance from another submitted sequence. Thresholds are user modifiable. SQUAT output includes a summary report with detailed comments for troubleshooting of flagged sequences, histograms of pairwise genetic distances, neighbor joining phylogenetic trees, and aligned nucleic and amino acid sequences. SQUAT is a stand-alone, free, web-independent tool to ensure use of high-quality HIV PR/RT sequences in interpretation and reporting of drug resistance, while increasing awareness and expertise and facilitating troubleshooting of potentially problematic sequences.

DeepPicker: A deep learning approach for fully automated particle picking in cryo-EM.

Science.gov (United States)

Wang, Feng; Gong, Huichao; Liu, Gaochao; Li, Meijing; Yan, Chuangye; Xia, Tian; Li, Xueming; Zeng, Jianyang

2016-09-01

Particle picking is a time-consuming step in single-particle analysis and often requires significant interventions from users, which has become a bottleneck for future automated electron cryo-microscopy (cryo-EM). Here we report a deep learning framework, called DeepPicker, to address this problem and fill the current gaps toward a fully automated cryo-EM pipeline. DeepPicker employs a novel cross-molecule training strategy to capture common features of particles from previously-analyzed micrographs, and thus does not require any human intervention during particle picking. Tests on the recently-published cryo-EM data of three complexes have demonstrated that our deep learning based scheme can successfully accomplish the human-level particle picking process and identify a sufficient number of particles that are comparable to those picked manually by human experts. These results indicate that DeepPicker can provide a practically useful tool to significantly reduce the time and manual effort spent in single-particle analysis and thus greatly facilitate high-resolution cryo-EM structure determination. DeepPicker is released as an open-source program, which can be downloaded from https://github.com/nejyeah/DeepPicker-python. Copyright © 2016 Elsevier Inc. All rights reserved.

REFGEN and TREENAMER: Automated Sequence Data Handling for Phylogenetic Analysis in the Genomic Era

Science.gov (United States)

Leonard, Guy; Stevens, Jamie R.; Richards, Thomas A.

2009-01-01

The phylogenetic analysis of nucleotide sequences and increasingly that of amino acid sequences is used to address a number of biological questions. Access to extensive datasets, including numerous genome projects, means that standard phylogenetic analyses can include many hundreds of sequences. Unfortunately, most phylogenetic analysis programs do not tolerate the sequence naming conventions of genome databases. Managing large numbers of sequences and standardizing sequence labels for use in phylogenetic analysis programs can be a time consuming and laborious task. Here we report the availability of an online resource for the management of gene sequences recovered from public access genome databases such as GenBank. These web utilities include the facility for renaming every sequence in a FASTA alignment file, with each sequence label derived from a user-defined combination of the species name and/or database accession number. This facility enables the user to keep track of the branching order of the sequences/taxa during multiple tree calculations and re-optimisations. Post phylogenetic analysis, these webpages can then be used to rename every label in the subsequent tree files (with a user-defined combination of species name and/or database accession number). Together these programs drastically reduce the time required for managing sequence alignments and labelling phylogenetic figures. Additional features of our platform include the automatic removal of identical accession numbers (recorded in the report file) and generation of species and accession number lists for use in supplementary materials or figure legends. PMID:19812722

Complete genome sequence of a new enamovirus from Argentina infecting alfalfa plants showing dwarfism symptoms.

Science.gov (United States)

Bejerman, Nicolás; Giolitti, Fabián; Trucco, Verónica; de Breuil, Soledad; Dietzgen, Ralf G; Lenardon, Sergio

2016-07-01

Alfalfa dwarf disease, probably caused by synergistic interactions of mixed virus infections, is a major and emergent disease that threatens alfalfa production in Argentina. Deep sequencing of diseased alfalfa plant samples from the central region of Argentina resulted in the identification of a new virus genome resembling enamoviruses in sequence and genome structure. Phylogenetic analysis suggests that it is a new member of the genus Enamovirus, family Luteoviridae. The virus is tentatively named "alfalfa enamovirus 1" (AEV-1). The availability of the AEV-1 genome sequence will make it possible to assess the genetic variability of this virus and to construct an infectious clone to investigate its role in alfalfa dwarfism disease.

Norwegian deep-water coral reefs: cultivation and molecular analysis of planktonic microbial communities.

Science.gov (United States)

Jensen, Sigmund; Lynch, Michael D J; Ray, Jessica L; Neufeld, Josh D; Hovland, Martin

2015-10-01

Deep-sea coral reefs do not receive sunlight and depend on plankton. Little is known about the plankton composition at such reefs, even though they constitute habitats for many invertebrates and fish. We investigated plankton communities from three reefs at 260-350 m depth at hydrocarbon fields off the mid-Norwegian coast using a combination of cultivation and small subunit (SSU) rRNA gene and transcript sequencing. Eight months incubations of a reef water sample with minimal medium, supplemented with carbon dioxide and gaseous alkanes at in situ-like conditions, enabled isolation of mostly Alphaproteobacteria (Sulfitobacter, Loktanella), Gammaproteobacteria (Colwellia) and Flavobacteria (Polaribacter). The relative abundance of isolates in the original sample ranged from ∼ 0.01% to 0.80%. Comparisons of bacterial SSU sequences from filtered plankton of reef and non-reef control samples indicated high abundance and metabolic activity of primarily Alphaproteobacteria (SAR11 Ia), Gammaproteobacteria (ARCTIC96BD-19), but also of Deltaproteobacteria (Nitrospina, SAR324). Eukaryote SSU sequences indicated metabolically active microalgae and animals, including codfish, at the reef sites. The plankton community composition varied between reefs and differed between DNA and RNA assessments. Over 5000 operational taxonomic units were detected, some indicators of reef sites (e.g. Flavobacteria, Cercozoa, Demospongiae) and some more active at reef sites (e.g. Gammaproteobacteria, Ciliophora, Copepoda). © 2014 Society for Applied Microbiology and John Wiley & Sons Ltd.

Biological sequence analysis: probabilistic models of proteins and nucleic acids

National Research Council Canada - National Science Library

Durbin, Richard

1998-01-01

... analysis methods are now based on principles of probabilistic modelling. Examples of such methods include the use of probabilistically derived score matrices to determine the significance of sequence alignments, the use of hidden Markov models as the basis for profile searches to identify distant members of sequence families, and the inference...

Deep sequencing of the Trypanosoma cruzi GP63 surface proteases reveals diversity and diversifying selection among chronic and congenital Chagas disease patients.

Science.gov (United States)

Llewellyn, Martin S; Messenger, Louisa A; Luquetti, Alejandro O; Garcia, Lineth; Torrico, Faustino; Tavares, Suelene B N; Cheaib, Bachar; Derome, Nicolas; Delepine, Marc; Baulard, Céline; Deleuze, Jean-Francois; Sauer, Sascha; Miles, Michael A

2015-04-01

Chagas disease results from infection with the diploid protozoan parasite Trypanosoma cruzi. T. cruzi is highly genetically diverse, and multiclonal infections in individual hosts are common, but little studied. In this study, we explore T. cruzi infection multiclonality in the context of age, sex and clinical profile among a cohort of chronic patients, as well as paired congenital cases from Cochabamba, Bolivia and Goias, Brazil using amplicon deep sequencing technology. A 450bp fragment of the trypomastigote TcGP63I surface protease gene was amplified and sequenced across 70 chronic and 22 congenital cases on the Illumina MiSeq platform. In addition, a second, mitochondrial target--ND5--was sequenced across the same cohort of cases. Several million reads were generated, and sequencing read depths were normalized within patient cohorts (Goias chronic, n = 43, Goias congenital n = 2, Bolivia chronic, n = 27; Bolivia congenital, n = 20), Among chronic cases, analyses of variance indicated no clear correlation between intra-host sequence diversity and age, sex or symptoms, while principal coordinate analyses showed no clustering by symptoms between patients. Between congenital pairs, we found evidence for the transmission of multiple sequence types from mother to infant, as well as widespread instances of novel genotypes in infants. Finally, non-synonymous to synonymous (dn:ds) nucleotide substitution ratios among sequences of TcGP63Ia and TcGP63Ib subfamilies within each cohort provided powerful evidence of strong diversifying selection at this locus. Our results shed light on the diversity of parasite DTUs within each patient, as well as the extent to which parasite strains pass between mother and foetus in congenital cases. Although we were unable to find any evidence that parasite diversity accumulates with age in our study cohorts, putative diversifying selection within members of the TcGP63I gene family suggests a link between genetic diversity within this gene

Total RNA Sequencing Analysis of DCIS Progressing to Invasive Breast Cancer

Science.gov (United States)

2017-09-01

AWARD NUMBER: W81XWH-14-1-0080 TITLE: Total RNA Sequencing Analysis of DCIS Progressing to Invasive Breast Cancer . PRINCIPAL INVESTIGATOR...TITLE AND SUBTITLE Total RNA Sequencing Analysis of DCIS Progressing to Invasive Breast Cancer . 5a. CONTRACT NUMBER 5b. GRANT NUMBER GRANT11489...institutional, NIH-funded study of genetic and epigenetic alterations of pre-invasive DCIS that did or did not progress to invasive breast cancer , with an

Cloning and sequence analysis of hyaluronoglucosaminidase (nagH gene of Clostridium chauvoei

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Saroj K. Dangi

2017-09-01

Full Text Available Aim: Blackleg disease is caused by Clostridium chauvoei in ruminants. Although virulence factors such as C. chauvoei toxin A, sialidase, and flagellin are well characterized, hyaluronidases of C. chauvoei are not characterized. The present study was aimed at cloning and sequence analysis of hyaluronoglucosaminidase (nagH gene of C. chauvoei. Materials and Methods: C. chauvoei strain ATCC 10092 was grown in ATCC 2107 media and confirmed by polymerase chain reaction (PCR using the primers specific for 16-23S rDNA spacer region. nagH gene of C. chauvoei was amplified and cloned into pRham-SUMO vector and transformed into Escherichia cloni 10G cells. The construct was then transformed into E. cloni cells. Colony PCR was carried out to screen the colonies followed by sequencing of nagH gene in the construct. Results: PCR amplification yielded nagH gene of 1143 bp product, which was cloned in prokaryotic expression system. Colony PCR, as well as sequencing of nagH gene, confirmed the presence of insert. Sequence was then subjected to BLAST analysis of NCBI, which confirmed that the sequence was indeed of nagH gene of C. chauvoei. Phylogenetic analysis of the sequence showed that it is closely related to Clostridium perfringens and Clostridium paraputrificum. Conclusion: The gene for virulence factor nagH was cloned into a prokaryotic expression vector and confirmed by sequencing.

DELIMINATE--a fast and efficient method for loss-less compression of genomic sequences: sequence analysis.

Science.gov (United States)

Mohammed, Monzoorul Haque; Dutta, Anirban; Bose, Tungadri; Chadaram, Sudha; Mande, Sharmila S

2012-10-01

An unprecedented quantity of genome sequence data is currently being generated using next-generation sequencing platforms. This has necessitated the development of novel bioinformatics approaches and algorithms that not only facilitate a meaningful analysis of these data but also aid in efficient compression, storage, retrieval and transmission of huge volumes of the generated data. We present a novel compression algorithm (DELIMINATE) that can rapidly compress genomic sequence data in a loss-less fashion. Validation results indicate relatively higher compression efficiency of DELIMINATE when compared with popular general purpose compression algorithms, namely, gzip, bzip2 and lzma. Linux, Windows and Mac implementations (both 32 and 64-bit) of DELIMINATE are freely available for download at: http://metagenomics.atc.tcs.com/compression/DELIMINATE. sharmila@atc.tcs.com Supplementary data are available at Bioinformatics online.

Deep learning improves prediction of CRISPR-Cpf1 guide RNA activity.

Science.gov (United States)

Kim, Hui Kwon; Min, Seonwoo; Song, Myungjae; Jung, Soobin; Choi, Jae Woo; Kim, Younggwang; Lee, Sangeun; Yoon, Sungroh; Kim, Hyongbum Henry

2018-03-01

We present two algorithms to predict the activity of AsCpf1 guide RNAs. Indel frequencies for 15,000 target sequences were used in a deep-learning framework based on a convolutional neural network to train Seq-deepCpf1. We then incorporated chromatin accessibility information to create the better-performing DeepCpf1 algorithm for cell lines for which such information is available and show that both algorithms outperform previous machine learning algorithms on our own and published data sets.

Deep sequencing of H7N8 avian influenza viruses from surveillance zone supports H7N8 high pathogenicity avian influenza was limited to a single outbreak farm in Indiana during 2016.

Science.gov (United States)

Lee, Dong-Hun; Torchetti, Mia Kim; Killian, Mary Lea; Swayne, David E

2017-07-01

In mid-January 2016, an outbreak of H7N8 high-pathogenicity avian influenza virus (HPAIV) in commercial turkeys occurred in Indiana. Surveillance within the 10km control zone identified H7N8 low-pathogenicity avian influenza virus (LPAIV) in nine surrounding turkey flocks but no other HPAIV-affected premises. We sequenced four of the H7N8 HPAIV isolated from the single farm and nine LPAIV identified during control zone surveillance. Evaluation included phylogenetic network analysis indicating close relatedness across the HPAIV and LPAIV, and that the progenitor H7N8 LPAIV spread among the affected turkey farms in Indiana, followed by spontaneous mutation to HPAIV on a single premise through acquisition of three basic amino acids at the hemagglutinin cleavage site. Deep sequencing of the available viruses failed to identify subpopulations in either the HPAIV or LPAIV suggesting mutation to HPAIV likely occurred on a single farm and the HPAIV did not spread to epidemiologically linked LPAIV-affected farms. Published by Elsevier Inc.

A basic analysis toolkit for biological sequences

Directory of Open Access Journals (Sweden)

Siragusa Enrico

2007-09-01

Full Text Available Abstract This paper presents a software library, nicknamed BATS, for some basic sequence analysis tasks. Namely, local alignments, via approximate string matching, and global alignments, via longest common subsequence and alignments with affine and concave gap cost functions. Moreover, it also supports filtering operations to select strings from a set and establish their statistical significance, via z-score computation. None of the algorithms is new, but although they are generally regarded as fundamental for sequence analysis, they have not been implemented in a single and consistent software package, as we do here. Therefore, our main contribution is to fill this gap between algorithmic theory and practice by providing an extensible and easy to use software library that includes algorithms for the mentioned string matching and alignment problems. The library consists of C/C++ library functions as well as Perl library functions. It can be interfaced with Bioperl and can also be used as a stand-alone system with a GUI. The software is available at http://www.math.unipa.it/~raffaele/BATS/ under the GNU GPL.

Analysis of large optical ground stations for deep-space optical communications

Science.gov (United States)

Garcia-Talavera, M. Reyes; Rivera, C.; Murga, G.; Montilla, I.; Alonso, A.

2017-11-01

Inter-satellite and ground to satellite optical communications have been successfully demonstrated over more than a decade with several experiments, the most recent being NASA's lunar mission Lunar Atmospheric Dust Environment Explorer (LADEE). The technology is in a mature stage that allows to consider optical communications as a high-capacity solution for future deep-space communications [1][2], where there is an increasing demand on downlink data rate to improve science return. To serve these deep-space missions, suitable optical ground stations (OGS) have to be developed providing large collecting areas. The design of such OGSs must face both technical and cost constraints in order to achieve an optimum implementation. To that end, different approaches have already been proposed and analyzed, namely, a large telescope based on a segmented primary mirror, telescope arrays, and even the combination of RF and optical receivers in modified versions of existing Deep-Space Network (DSN) antennas [3][4][5]. Array architectures have been proposed to relax some requirements, acting as one of the key drivers of the present study. The advantages offered by the array approach are attained at the expense of adding subsystems. Critical issues identified for each implementation include their inherent efficiency and losses, as well as its performance under high-background conditions, and the acquisition, pointing, tracking, and synchronization capabilities. It is worth noticing that, due to the photon-counting nature of detection, the system performance is not solely given by the signal-to-noise ratio parameter. To start with the analysis, first the main implications of the deep space scenarios are summarized, since they are the driving requirements to establish the technical specifications for the large OGS. Next, both the main characteristics of the OGS and the potential configuration approaches are presented, getting deeper in key subsystems with strong impact in the

REFGEN and TREENAMER: Automated Sequence Data Handling for Phylogenetic Analysis in the Genomic Era

Directory of Open Access Journals (Sweden)

Guy Leonard

2009-01-01

Full Text Available The phylogenetic analysis of nucleotide sequences and increasingly that of amino acid sequences is used to address a number of biological questions. Access to extensive datasets, including numerous genome projects, means that standard phylogenetic analyses can include many hundreds of sequences. Unfortunately, most phylogenetic analysis programs do not tolerate the sequence naming conventions of genome databases. Managing large numbers of sequences and standardizing sequence labels for use in phylogenetic analysis programs can be a time consuming and laborious task. Here we report the availability of an online resource for the management of gene sequences recovered from public access genome databases such as GenBank. These web utilities include the facility for renaming every sequence in a FASTA alignment fi le, with each sequence label derived from a user-defined combination of the species name and/or database accession number. This facility enables the user to keep track of the branching order of the sequences/taxa during multiple tree calculations and re-optimisations. Post phylogenetic analysis, these webpages can then be used to rename every label in the subsequent tree fi les (with a user-defined combination of species name and/or database accession number. Together these programs drastically reduce the time required for managing sequence alignments and labelling phylogenetic figures. Additional features of our platform include the automatic removal of identical accession numbers (recorded in the report file and generation of species and accession number lists for use in supplementary materials or figure legends.

Seismic response analysis of the deep saturated soil deposits in Shanghai

Science.gov (United States)

Huang, Yu; Ye, Weimin; Chen, Zhuchang

2009-01-01

The quaternary deposits in Shanghai are horizontal soil layers of thickness up to about 280 m in the urban area with an annual groundwater table between 0.5 and 0.7 m from the surface. The characteristics of deep saturated deposits may have important influences upon seismic response of the ground in Shanghai. Based on the Biot theory for porous media, the water-saturated soil deposits are modeled as a two-phase porous system consisting of solid and fluid phases, in this paper. A nonlinear constitutive model for predicting the seismic response of the ground is developed to describe the dynamic characters of the deep-saturated soil deposits in Shanghai. Subsequently, the seismic response of a typical site with 280 m deep soil layers, which is subjected to four base excitations (El Centro, Taft, Sunan, and Tangshan earthquakes), is analyzed in terms of an effective stress-based finite element method with the proposed constitutive model. Special emphasis is given to the computed results of accelerations, excess pore-water pressures, and settlements during the seismic excitations. It has been found that the analysis can capture fundamental aspects of the ground response and produce preliminary results for seismic assessment.

Sequence analysis of PROTEOLYSIS 6 from Solanum lycopersicum