RCK: accurate and efficient inference of sequence- and structure-based protein-RNA binding models from RNAcompete data.

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Orenstein, Yaron; Wang, Yuhao; Berger, Bonnie

2016-06-15

Protein-RNA interactions, which play vital roles in many processes, are mediated through both RNA sequence and structure. CLIP-based methods, which measure protein-RNA binding in vivo, suffer from experimental noise and systematic biases, whereas in vitro experiments capture a clearer signal of protein RNA-binding. Among them, RNAcompete provides binding affinities of a specific protein to more than 240 000 unstructured RNA probes in one experiment. The computational challenge is to infer RNA structure- and sequence-based binding models from these data. The state-of-the-art in sequence models, Deepbind, does not model structural preferences. RNAcontext models both sequence and structure preferences, but is outperformed by GraphProt. Unfortunately, GraphProt cannot detect structural preferences from RNAcompete data due to the unstructured nature of the data, as noted by its developers, nor can it be tractably run on the full RNACompete dataset. We develop RCK, an efficient, scalable algorithm that infers both sequence and structure preferences based on a new k-mer based model. Remarkably, even though RNAcompete data is designed to be unstructured, RCK can still learn structural preferences from it. RCK significantly outperforms both RNAcontext and Deepbind in in vitro binding prediction for 244 RNAcompete experiments. Moreover, RCK is also faster and uses less memory, which enables scalability. While currently on par with existing methods in in vivo binding prediction on a small scale test, we demonstrate that RCK will increasingly benefit from experimentally measured RNA structure profiles as compared to computationally predicted ones. By running RCK on the entire RNAcompete dataset, we generate and provide as a resource a set of protein-RNA structure-based models on an unprecedented scale. Software and models are freely available at http://rck.csail.mit.edu/ bab@mit.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by

ISVASE: identification of sequence variant associated with splicing event using RNA-seq data.

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Aljohi, Hasan Awad; Liu, Wanfei; Lin, Qiang; Yu, Jun; Hu, Songnian

2017-06-28

Exon recognition and splicing precisely and efficiently by spliceosome is the key to generate mature mRNAs. About one third or a half of disease-related mutations affect RNA splicing. Software PVAAS has been developed to identify variants associated with aberrant splicing by directly using RNA-seq data. However, it bases on the assumption that annotated splicing site is normal splicing, which is not true in fact. We develop the ISVASE, a tool for specifically identifying sequence variants associated with splicing events (SVASE) by using RNA-seq data. Comparing with PVAAS, our tool has several advantages, such as multi-pass stringent rule-dependent filters and statistical filters, only using split-reads, independent sequence variant identification in each part of splicing (junction), sequence variant detection for both of known and novel splicing event, additional exon-exon junction shift event detection if known splicing events provided, splicing signal evaluation, known DNA mutation and/or RNA editing data supported, higher precision and consistency, and short running time. Using a realistic RNA-seq dataset, we performed a case study to illustrate the functionality and effectiveness of our method. Moreover, the output of SVASEs can be used for downstream analysis such as splicing regulatory element study and sequence variant functional analysis. ISVASE is useful for researchers interested in sequence variants (DNA mutation and/or RNA editing) associated with splicing events. The package is freely available at https://sourceforge.net/projects/isvase/ .

Unifying cancer and normal RNA sequencing data from different sources

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Wang, Qingguo; Armenia, Joshua; Zhang, Chao; Penson, Alexander V.; Reznik, Ed; Zhang, Liguo; Minet, Thais; Ochoa, Angelica; Gross, Benjamin E.; Iacobuzio-Donahue, Christine A.; Betel, Doron; Taylor, Barry S.; Gao, Jianjiong; Schultz, Nikolaus

2018-01-01

Driven by the recent advances of next generation sequencing (NGS) technologies and an urgent need to decode complex human diseases, a multitude of large-scale studies were conducted recently that have resulted in an unprecedented volume of whole transcriptome sequencing (RNA-seq) data, such as the Genotype Tissue Expression project (GTEx) and The Cancer Genome Atlas (TCGA). While these data offer new opportunities to identify the mechanisms underlying disease, the comparison of data from different sources remains challenging, due to differences in sample and data processing. Here, we developed a pipeline that processes and unifies RNA-seq data from different studies, which includes uniform realignment, gene expression quantification, and batch effect removal. We find that uniform alignment and quantification is not sufficient when combining RNA-seq data from different sources and that the removal of other batch effects is essential to facilitate data comparison. We have processed data from GTEx and TCGA and successfully corrected for study-specific biases, enabling comparative analysis between TCGA and GTEx. The normalized datasets are available for download on figshare. PMID:29664468

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

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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

TurboFold: Iterative probabilistic estimation of secondary structures for multiple RNA sequences

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Sharma Gaurav

2011-04-01

Full Text Available Abstract Background The prediction of secondary structure, i.e. the set of canonical base pairs between nucleotides, is a first step in developing an understanding of the function of an RNA sequence. The most accurate computational methods predict conserved structures for a set of homologous RNA sequences. These methods usually suffer from high computational complexity. In this paper, TurboFold, a novel and efficient method for secondary structure prediction for multiple RNA sequences, is presented. Results TurboFold takes, as input, a set of homologous RNA sequences and outputs estimates of the base pairing probabilities for each sequence. The base pairing probabilities for a sequence are estimated by combining intrinsic information, derived from the sequence itself via the nearest neighbor thermodynamic model, with extrinsic information, derived from the other sequences in the input set. For a given sequence, the extrinsic information is computed by using pairwise-sequence-alignment-based probabilities for co-incidence with each of the other sequences, along with estimated base pairing probabilities, from the previous iteration, for the other sequences. The extrinsic information is introduced as free energy modifications for base pairing in a partition function computation based on the nearest neighbor thermodynamic model. This process yields updated estimates of base pairing probability. The updated base pairing probabilities in turn are used to recompute extrinsic information, resulting in the overall iterative estimation procedure that defines TurboFold. TurboFold is benchmarked on a number of ncRNA datasets and compared against alternative secondary structure prediction methods. The iterative procedure in TurboFold is shown to improve estimates of base pairing probability with each iteration, though only small gains are obtained beyond three iterations. Secondary structures composed of base pairs with estimated probabilities higher than a

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

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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.

RNAcontext: a new method for learning the sequence and structure binding preferences of RNA-binding proteins.

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Hilal Kazan

2010-07-01

Full Text Available Metazoan genomes encode hundreds of RNA-binding proteins (RBPs. These proteins regulate post-transcriptional gene expression and have critical roles in numerous cellular processes including mRNA splicing, export, stability and translation. Despite their ubiquity and importance, the binding preferences for most RBPs are not well characterized. In vitro and in vivo studies, using affinity selection-based approaches, have successfully identified RNA sequence associated with specific RBPs; however, it is difficult to infer RBP sequence and structural preferences without specifically designed motif finding methods. In this study, we introduce a new motif-finding method, RNAcontext, designed to elucidate RBP-specific sequence and structural preferences with greater accuracy than existing approaches. We evaluated RNAcontext on recently published in vitro and in vivo RNA affinity selected data and demonstrate that RNAcontext identifies known binding preferences for several control proteins including HuR, PTB, and Vts1p and predicts new RNA structure preferences for SF2/ASF, RBM4, FUSIP1 and SLM2. The predicted preferences for SF2/ASF are consistent with its recently reported in vivo binding sites. RNAcontext is an accurate and efficient motif finding method ideally suited for using large-scale RNA-binding affinity datasets to determine the relative binding preferences of RBPs for a wide range of RNA sequences and structures.

MicroRNA Array Normalization: An Evaluation Using a Randomized Dataset as the Benchmark

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Qin, Li-Xuan; Zhou, Qin

2014-01-01

MicroRNA arrays possess a number of unique data features that challenge the assumption key to many normalization methods. We assessed the performance of existing normalization methods using two microRNA array datasets derived from the same set of tumor samples: one dataset was generated using a blocked randomization design when assigning arrays to samples and hence was free of confounding array effects; the second dataset was generated without blocking or randomization and exhibited array effects. The randomized dataset was assessed for differential expression between two tumor groups and treated as the benchmark. The non-randomized dataset was assessed for differential expression after normalization and compared against the benchmark. Normalization improved the true positive rate significantly in the non-randomized data but still possessed a false discovery rate as high as 50%. Adding a batch adjustment step before normalization further reduced the number of false positive markers while maintaining a similar number of true positive markers, which resulted in a false discovery rate of 32% to 48%, depending on the specific normalization method. We concluded the paper with some insights on possible causes of false discoveries to shed light on how to improve normalization for microRNA arrays. PMID:24905456

Metaxa: a software tool for automated detection and discrimination among ribosomal small subunit (12S/16S/18S) sequences of archaea, bacteria, eukaryotes, mitochondria, and chloroplasts in metagenomes and environmental sequencing datasets.

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Bengtsson, Johan; Eriksson, K Martin; Hartmann, Martin; Wang, Zheng; Shenoy, Belle Damodara; Grelet, Gwen-Aëlle; Abarenkov, Kessy; Petri, Anna; Rosenblad, Magnus Alm; Nilsson, R Henrik

2011-10-01

The ribosomal small subunit (SSU) rRNA gene has emerged as an important genetic marker for taxonomic identification in environmental sequencing datasets. In addition to being present in the nucleus of eukaryotes and the core genome of prokaryotes, the gene is also found in the mitochondria of eukaryotes and in the chloroplasts of photosynthetic eukaryotes. These three sets of genes are conceptually paralogous and should in most situations not be aligned and analyzed jointly. To identify the origin of SSU sequences in complex sequence datasets has hitherto been a time-consuming and largely manual undertaking. However, the present study introduces Metaxa ( http://microbiology.se/software/metaxa/ ), an automated software tool to extract full-length and partial SSU sequences from larger sequence datasets and assign them to an archaeal, bacterial, nuclear eukaryote, mitochondrial, or chloroplast origin. Using data from reference databases and from full-length organelle and organism genomes, we show that Metaxa detects and scores SSU sequences for origin with very low proportions of false positives and negatives. We believe that this tool will be useful in microbial and evolutionary ecology as well as in metagenomics.

QNB: differential RNA methylation analysis for count-based small-sample sequencing data with a quad-negative binomial model.

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Liu, Lian; Zhang, Shao-Wu; Huang, Yufei; Meng, Jia

2017-08-31

As a newly emerged research area, RNA epigenetics has drawn increasing attention recently for the participation of RNA methylation and other modifications in a number of crucial biological processes. Thanks to high throughput sequencing techniques, such as, MeRIP-Seq, transcriptome-wide RNA methylation profile is now available in the form of count-based data, with which it is often of interests to study the dynamics at epitranscriptomic layer. However, the sample size of RNA methylation experiment is usually very small due to its costs; and additionally, there usually exist a large number of genes whose methylation level cannot be accurately estimated due to their low expression level, making differential RNA methylation analysis a difficult task. We present QNB, a statistical approach for differential RNA methylation analysis with count-based small-sample sequencing data. Compared with previous approaches such as DRME model based on a statistical test covering the IP samples only with 2 negative binomial distributions, QNB is based on 4 independent negative binomial distributions with their variances and means linked by local regressions, and in the way, the input control samples are also properly taken care of. In addition, different from DRME approach, which relies only the input control sample only for estimating the background, QNB uses a more robust estimator for gene expression by combining information from both input and IP samples, which could largely improve the testing performance for very lowly expressed genes. QNB showed improved performance on both simulated and real MeRIP-Seq datasets when compared with competing algorithms. And the QNB model is also applicable to other datasets related RNA modifications, including but not limited to RNA bisulfite sequencing, m 1 A-Seq, Par-CLIP, RIP-Seq, etc.

Harnessing NGS and Big Data Optimally: Comparison of miRNA Prediction from Assembled versus Non-assembled Sequencing Data--The Case of the Grass Aegilops tauschii Complex Genome.

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Budak, Hikmet; Kantar, Melda

2015-07-01

MicroRNAs (miRNAs) are small, endogenous, non-coding RNA molecules that regulate gene expression at the post-transcriptional level. As high-throughput next generation sequencing (NGS) and Big Data rapidly accumulate for various species, efforts for in silico identification of miRNAs intensify. Surprisingly, the effect of the input genomics sequence on the robustness of miRNA prediction was not evaluated in detail to date. In the present study, we performed a homology-based miRNA and isomiRNA prediction of the 5D chromosome of bread wheat progenitor, Aegilops tauschii, using two distinct sequence data sets as input: (1) raw sequence reads obtained from 454-GS FLX Titanium sequencing platform and (2) an assembly constructed from these reads. We also compared this method with a number of available plant sequence datasets. We report here the identification of 62 and 22 miRNAs from raw reads and the assembly, respectively, of which 16 were predicted with high confidence from both datasets. While raw reads promoted sensitivity with the high number of miRNAs predicted, 55% (12 out of 22) of the assembly-based predictions were supported by previous observations, bringing specificity forward compared to the read-based predictions, of which only 37% were supported. Importantly, raw reads could identify several repeat-related miRNAs that could not be detected with the assembly. However, raw reads could not capture 6 miRNAs, for which the stem-loops could only be covered by the relatively longer sequences from the assembly. In summary, the comparison of miRNA datasets obtained by these two strategies revealed that utilization of raw reads, as well as assemblies for in silico prediction, have distinct advantages and disadvantages. Consideration of these important nuances can benefit future miRNA identification efforts in the current age of NGS and Big Data driven life sciences innovation.

RNA-Pareto: interactive analysis of Pareto-optimal RNA sequence-structure alignments.

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Schnattinger, Thomas; Schöning, Uwe; Marchfelder, Anita; Kestler, Hans A

2013-12-01

Incorporating secondary structure information into the alignment process improves the quality of RNA sequence alignments. Instead of using fixed weighting parameters, sequence and structure components can be treated as different objectives and optimized simultaneously. The result is not a single, but a Pareto-set of equally optimal solutions, which all represent different possible weighting parameters. We now provide the interactive graphical software tool RNA-Pareto, which allows a direct inspection of all feasible results to the pairwise RNA sequence-structure alignment problem and greatly facilitates the exploration of the optimal solution set.

Identification and validation of differentially expressed transcripts by RNA-sequencing of formalin-fixed, paraffin-embedded (FFPE) lung tissue from patients with Idiopathic Pulmonary Fibrosis.

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Vukmirovic, Milica; Herazo-Maya, Jose D; Blackmon, John; Skodric-Trifunovic, Vesna; Jovanovic, Dragana; Pavlovic, Sonja; Stojsic, Jelena; Zeljkovic, Vesna; Yan, Xiting; Homer, Robert; Stefanovic, Branko; Kaminski, Naftali

2017-01-12

Idiopathic Pulmonary Fibrosis (IPF) is a lethal lung disease of unknown etiology. A major limitation in transcriptomic profiling of lung tissue in IPF has been a dependence on snap-frozen fresh tissues (FF). In this project we sought to determine whether genome scale transcript profiling using RNA Sequencing (RNA-Seq) could be applied to archived Formalin-Fixed Paraffin-Embedded (FFPE) IPF tissues. We isolated total RNA from 7 IPF and 5 control FFPE lung tissues and performed 50 base pair paired-end sequencing on Illumina 2000 HiSeq. TopHat2 was used to map sequencing reads to the human genome. On average ~62 million reads (53.4% of ~116 million reads) were mapped per sample. 4,131 genes were differentially expressed between IPF and controls (1,920 increased and 2,211 decreased (FDR < 0.05). We compared our results to differentially expressed genes calculated from a previously published dataset generated from FF tissues analyzed on Agilent microarrays (GSE47460). The overlap of differentially expressed genes was very high (760 increased and 1,413 decreased, FDR < 0.05). Only 92 differentially expressed genes changed in opposite directions. Pathway enrichment analysis performed using MetaCore confirmed numerous IPF relevant genes and pathways including extracellular remodeling, TGF-beta, and WNT. Gene network analysis of MMP7, a highly differentially expressed gene in both datasets, revealed the same canonical pathways and gene network candidates in RNA-Seq and microarray data. For validation by NanoString nCounter® we selected 35 genes that had a fold change of 2 in at least one dataset (10 discordant, 10 significantly differentially expressed in one dataset only and 15 concordant genes). High concordance of fold change and FDR was observed for each type of the samples (FF vs FFPE) with both microarrays (r = 0.92) and RNA-Seq (r = 0.90) and the number of discordant genes was reduced to four. Our results demonstrate that RNA sequencing of RNA

viRome: an R package for the visualization and analysis of viral small RNA sequence datasets.

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Watson, Mick; Schnettler, Esther; Kohl, Alain

2013-08-01

RNA interference (RNAi) is known to play an important part in defence against viruses in a range of species. Second-generation sequencing technologies allow us to assay these systems and the small RNAs that play a key role with unprecedented depth. However, scientists need access to tools that can condense, analyse and display the resulting data. Here, we present viRome, a package for R that takes aligned sequence data and produces a range of essential plots and reports. viRome is released under the BSD license as a package for R available for both Windows and Linux http://virome.sf.net. Additional information and a tutorial is available on the ARK-Genomics website: http://www.ark-genomics.org/bioinformatics/virome. mick.watson@roslin.ed.ac.uk.

Analysis of Pteridium ribosomal RNA sequences by rapid direct sequencing.

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Tan, M K

1991-08-01

A total of 864 bases from 5 regions interspersed in the 18S and 26S rRNA molecules from various clones of Pteridium covering the general geographical distribution of the genus was analysed using a rapid rRNA sequencing technique. No base difference has been detected amongst the three major lineages, two of which apparently separated before the breakup of the ancient supercontinent, Pangaea. These regions of the rRNA sequences have thus been conserved for at least 160 million years and are here compared with other eukaryotic, especially plant rRNAs.

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

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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.

Deep sequencing analysis of the developing mouse brain reveals a novel microRNA

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Piltz Sandra

2011-04-01

Full Text Available Abstract Background MicroRNAs (miRNAs are small non-coding RNAs that can exert multilevel inhibition/repression at a post-transcriptional or protein synthesis level during disease or development. Characterisation of miRNAs in adult mammalian brains by deep sequencing has been reported previously. However, to date, no small RNA profiling of the developing brain has been undertaken using this method. We have performed deep sequencing and small RNA analysis of a developing (E15.5 mouse brain. Results We identified the expression of 294 known miRNAs in the E15.5 developing mouse brain, which were mostly represented by let-7 family and other brain-specific miRNAs such as miR-9 and miR-124. We also discovered 4 putative 22-23 nt miRNAs: mm_br_e15_1181, mm_br_e15_279920, mm_br_e15_96719 and mm_br_e15_294354 each with a 70-76 nt predicted pre-miRNA. We validated the 4 putative miRNAs and further characterised one of them, mm_br_e15_1181, throughout embryogenesis. Mm_br_e15_1181 biogenesis was Dicer1-dependent and was expressed in E3.5 blastocysts and E7 whole embryos. Embryo-wide expression patterns were observed at E9.5 and E11.5 followed by a near complete loss of expression by E13.5, with expression restricted to a specialised layer of cells within the developing and early postnatal brain. Mm_br_e15_1181 was upregulated during neurodifferentiation of P19 teratocarcinoma cells. This novel miRNA has been identified as miR-3099. Conclusions We have generated and analysed the first deep sequencing dataset of small RNA sequences of the developing mouse brain. The analysis revealed a novel miRNA, miR-3099, with potential regulatory effects on early embryogenesis, and involvement in neuronal cell differentiation/function in the brain during late embryonic and early neonatal development.

Chimira: analysis of small RNA sequencing data and microRNA modifications.

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Vitsios, Dimitrios M; Enright, Anton J

2015-10-15

Chimira is a web-based system for microRNA (miRNA) analysis from small RNA-Seq data. Sequences are automatically cleaned, trimmed, size selected and mapped directly to miRNA hairpin sequences. This generates count-based miRNA expression data for subsequent statistical analysis. Moreover, it is capable of identifying epi-transcriptomic modifications in the input sequences. Supported modification types include multiple types of 3'-modifications (e.g. uridylation, adenylation), 5'-modifications and also internal modifications or variation (ADAR editing or single nucleotide polymorphisms). Besides cleaning and mapping of input sequences to miRNAs, Chimira provides a simple and intuitive set of tools for the analysis and interpretation of the results (see also Supplementary Material). These allow the visual study of the differential expression between two specific samples or sets of samples, the identification of the most highly expressed miRNAs within sample pairs (or sets of samples) and also the projection of the modification profile for specific miRNAs across all samples. Other tools have already been published in the past for various types of small RNA-Seq analysis, such as UEA workbench, seqBuster, MAGI, OASIS and CAP-miRSeq, CPSS for modifications identification. A comprehensive comparison of Chimira with each of these tools is provided in the Supplementary Material. Chimira outperforms all of these tools in total execution speed and aims to facilitate simple, fast and reliable analysis of small RNA-Seq data allowing also, for the first time, identification of global microRNA modification profiles in a simple intuitive interface. Chimira has been developed as a web application and it is accessible here: http://www.ebi.ac.uk/research/enright/software/chimira. aje@ebi.ac.uk Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

Size, Shape, and Sequence-Dependent Immunogenicity of RNA Nanoparticles

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Sijin Guo

2017-12-01

Full Text Available RNA molecules have emerged as promising therapeutics. Like all other drugs, the safety profile and immune response are important criteria for drug evaluation. However, the literature on RNA immunogenicity has been controversial. Here, we used the approach of RNA nanotechnology to demonstrate that the immune response of RNA nanoparticles is size, shape, and sequence dependent. RNA triangle, square, pentagon, and tetrahedron with same shape but different sizes, or same size but different shapes were used as models to investigate the immune response. The levels of pro-inflammatory cytokines induced by these RNA nanoarchitectures were assessed in macrophage-like cells and animals. It was found that RNA polygons without extension at the vertexes were immune inert. However, when single-stranded RNA with a specific sequence was extended from the vertexes of RNA polygons, strong immune responses were detected. These immunostimulations are sequence specific, because some other extended sequences induced little or no immune response. Additionally, larger-size RNA square induced stronger cytokine secretion. 3D RNA tetrahedron showed stronger immunostimulation than planar RNA triangle. These results suggest that the immunogenicity of RNA nanoparticles is tunable to produce either a minimal immune response that can serve as safe therapeutic vectors, or a strong immune response for cancer immunotherapy or vaccine adjuvants.

Evaluation of two main RNA-seq approaches for gene quantification in clinical RNA sequencing: polyA+ selection versus rRNA depletion.

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Zhao, Shanrong; Zhang, Ying; Gamini, Ramya; Zhang, Baohong; von Schack, David

2018-03-19

To allow efficient transcript/gene detection, highly abundant ribosomal RNAs (rRNA) are generally removed from total RNA either by positive polyA+ selection or by rRNA depletion (negative selection) before sequencing. Comparisons between the two methods have been carried out by various groups, but the assessments have relied largely on non-clinical samples. In this study, we evaluated these two RNA sequencing approaches using human blood and colon tissue samples. Our analyses showed that rRNA depletion captured more unique transcriptome features, whereas polyA+ selection outperformed rRNA depletion with higher exonic coverage and better accuracy of gene quantification. For blood- and colon-derived RNAs, we found that 220% and 50% more reads, respectively, would have to be sequenced to achieve the same level of exonic coverage in the rRNA depletion method compared with the polyA+ selection method. Therefore, in most cases we strongly recommend polyA+ selection over rRNA depletion for gene quantification in clinical RNA sequencing. Our evaluation revealed that a small number of lncRNAs and small RNAs made up a large fraction of the reads in the rRNA depletion RNA sequencing data. Thus, we recommend that these RNAs are specifically depleted to improve the sequencing depth of the remaining RNAs.

Rfam: annotating families of non-coding RNA sequences.

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Daub, Jennifer; Eberhardt, Ruth Y; Tate, John G; Burge, Sarah W

2015-01-01

The primary task of the Rfam database is to collate experimentally validated noncoding RNA (ncRNA) sequences from the published literature and facilitate the prediction and annotation of new homologues in novel nucleotide sequences. We group homologous ncRNA sequences into "families" and related families are further grouped into "clans." We collate and manually curate data cross-references for these families from other databases and external resources. Our Web site offers researchers a simple interface to Rfam and provides tools with which to annotate their own sequences using our covariance models (CMs), through our tools for searching, browsing, and downloading information on Rfam families. In this chapter, we will work through examples of annotating a query sequence, collating family information, and searching for data.

miRBase: integrating microRNA annotation and deep-sequencing data.

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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/.

Size, Shape, and Sequence-Dependent Immunogenicity of RNA Nanoparticles.

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Guo, Sijin; Li, Hui; Ma, Mengshi; Fu, Jian; Dong, Yizhou; Guo, Peixuan

2017-12-15

RNA molecules have emerged as promising therapeutics. Like all other drugs, the safety profile and immune response are important criteria for drug evaluation. However, the literature on RNA immunogenicity has been controversial. Here, we used the approach of RNA nanotechnology to demonstrate that the immune response of RNA nanoparticles is size, shape, and sequence dependent. RNA triangle, square, pentagon, and tetrahedron with same shape but different sizes, or same size but different shapes were used as models to investigate the immune response. The levels of pro-inflammatory cytokines induced by these RNA nanoarchitectures were assessed in macrophage-like cells and animals. It was found that RNA polygons without extension at the vertexes were immune inert. However, when single-stranded RNA with a specific sequence was extended from the vertexes of RNA polygons, strong immune responses were detected. These immunostimulations are sequence specific, because some other extended sequences induced little or no immune response. Additionally, larger-size RNA square induced stronger cytokine secretion. 3D RNA tetrahedron showed stronger immunostimulation than planar RNA triangle. These results suggest that the immunogenicity of RNA nanoparticles is tunable to produce either a minimal immune response that can serve as safe therapeutic vectors, or a strong immune response for cancer immunotherapy or vaccine adjuvants. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

RNA deep sequencing reveals differential microRNA expression during development of sea urchin and sea star.

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Sabah Kadri

Full Text Available microRNAs (miRNAs are small (20-23 nt, non-coding single stranded RNA molecules that act as post-transcriptional regulators of mRNA gene expression. They have been implicated in regulation of developmental processes in diverse organisms. The echinoderms, Strongylocentrotus purpuratus (sea urchin and Patiria miniata (sea star are excellent model organisms for studying development with well-characterized transcriptional networks. However, to date, nothing is known about the role of miRNAs during development in these organisms, except that the genes that are involved in the miRNA biogenesis pathway are expressed during their developmental stages. In this paper, we used Illumina Genome Analyzer (Illumina, Inc. to sequence small RNA libraries in mixed stage population of embryos from one to three days after fertilization of sea urchin and sea star (total of 22,670,000 reads. Analysis of these data revealed the miRNA populations in these two species. We found that 47 and 38 known miRNAs are expressed in sea urchin and sea star, respectively, during early development (32 in common. We also found 13 potentially novel miRNAs in the sea urchin embryonic library. miRNA expression is generally conserved between the two species during development, but 7 miRNAs are highly expressed in only one species. We expect that our two datasets will be a valuable resource for everyone working in the field of developmental biology and the regulatory networks that affect it. The computational pipeline to analyze Illumina reads is available at http://www.benoslab.pitt.edu/services.html.

RNA Deep Sequencing Reveals Differential MicroRNA Expression during Development of Sea Urchin and Sea Star

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Kadri, Sabah; Hinman, Veronica F.; Benos, Panayiotis V.

2011-01-01

microRNAs (miRNAs) are small (20–23 nt), non-coding single stranded RNA molecules that act as post-transcriptional regulators of mRNA gene expression. They have been implicated in regulation of developmental processes in diverse organisms. The echinoderms, Strongylocentrotus purpuratus (sea urchin) and Patiria miniata (sea star) are excellent model organisms for studying development with well-characterized transcriptional networks. However, to date, nothing is known about the role of miRNAs during development in these organisms, except that the genes that are involved in the miRNA biogenesis pathway are expressed during their developmental stages. In this paper, we used Illumina Genome Analyzer (Illumina, Inc.) to sequence small RNA libraries in mixed stage population of embryos from one to three days after fertilization of sea urchin and sea star (total of 22,670,000 reads). Analysis of these data revealed the miRNA populations in these two species. We found that 47 and 38 known miRNAs are expressed in sea urchin and sea star, respectively, during early development (32 in common). We also found 13 potentially novel miRNAs in the sea urchin embryonic library. miRNA expression is generally conserved between the two species during development, but 7 miRNAs are highly expressed in only one species. We expect that our two datasets will be a valuable resource for everyone working in the field of developmental biology and the regulatory networks that affect it. The computational pipeline to analyze Illumina reads is available at http://www.benoslab.pitt.edu/services.html. PMID:22216218

Integrated mRNA and microRNA transcriptome sequencing characterizes sequence variants and mRNA–microRNA regulatory network in nasopharyngeal carcinoma model systems

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Carol Ying-Ying Szeto

2014-01-01

Full Text Available Nasopharyngeal carcinoma (NPC is a prevalent malignancy in Southeast Asia among the Chinese population. Aberrant regulation of transcripts has been implicated in many types of cancers including NPC. Herein, we characterized mRNA and miRNA transcriptomes by RNA sequencing (RNASeq of NPC model systems. Matched total mRNA and small RNA of undifferentiated Epstein–Barr virus (EBV-positive NPC xenograft X666 and its derived cell line C666, well-differentiated NPC cell line HK1, and the immortalized nasopharyngeal epithelial cell line NP460 were sequenced by Solexa technology. We found 2812 genes and 149 miRNAs (human and EBV to be differentially expressed in NP460, HK1, C666 and X666 with RNASeq; 533 miRNA–mRNA target pairs were inversely regulated in the three NPC cell lines compared to NP460. Integrated mRNA/miRNA expression profiling and pathway analysis show extracellular matrix organization, Beta-1 integrin cell surface interactions, and the PI3K/AKT, EGFR, ErbB, and Wnt pathways were potentially deregulated in NPC. Real-time quantitative PCR was performed on selected mRNA/miRNAs in order to validate their expression. Transcript sequence variants such as short insertions and deletions (INDEL, single nucleotide variant (SNV, and isomiRs were characterized in the NPC model systems. A novel TP53 transcript variant was identified in NP460, HK1, and C666. Detection of three previously reported novel EBV-encoded BART miRNAs and their isomiRs were also observed. Meta-analysis of a model system to a clinical system aids the choice of different cell lines in NPC studies. This comprehensive characterization of mRNA and miRNA transcriptomes in NPC cell lines and the xenograft provides insights on miRNA regulation of mRNA and valuable resources on transcript variation and regulation in NPC, which are potentially useful for mechanistic and preclinical studies.

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

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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.

Computational prediction of miRNA genes from small RNA sequencing data

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Wenjing eKang

2015-01-01

Full Text Available Next-generation sequencing now for the first time allows researchers to gauge the depth and variation of entire transcriptomes. However, now as rare transcripts can be detected that are present in cells at single copies, more advanced computational tools are needed to accurately annotate and profile them. miRNAs are 22 nucleotide small RNAs (sRNAs that post-transcriptionally reduce the output of protein coding genes. They have established roles in numerous biological processes, including cancers and other diseases. During miRNA biogenesis, the sRNAs are sequentially cleaved from precursor molecules that have a characteristic hairpin RNA structure. The vast majority of new miRNA genes that are discovered are mined from small RNA sequencing (sRNA-seq, which can detect more than a billion RNAs in a single run. However, given that many of the detected RNAs are degradation products from all types of transcripts, the accurate identification of miRNAs remain a non-trivial computational problem. Here we review the tools available to predict animal miRNAs from sRNA sequencing data. We present tools for generalist and specialist use cases, including prediction from massively pooled data or in species without reference genome. We also present wet-lab methods used to validate predicted miRNAs, and approaches to computationally benchmark prediction accuracy. For each tool, we reference validation experiments and benchmarking efforts. Last, we discuss the future of the field.

RNA sequencing: current and prospective uses in metabolic research.

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Vikman, Petter; Fadista, Joao; Oskolkov, Nikolay

2014-10-01

Previous global RNA analysis was restricted to known transcripts in species with a defined transcriptome. Next generation sequencing has transformed transcriptomics by making it possible to analyse expressed genes with an exon level resolution from any tissue in any species without any a priori knowledge of which genes that are being expressed, splice patterns or their nucleotide sequence. In addition, RNA sequencing is a more sensitive technique compared with microarrays with a larger dynamic range, and it also allows for investigation of imprinting and allele-specific expression. This can be done for a cost that is able to compete with that of a microarray, making RNA sequencing a technique available to most researchers. Therefore RNA sequencing has recently become the state of the art with regards to large-scale RNA investigations and has to a large extent replaced microarrays. The only drawback is the large data amounts produced, which together with the complexity of the data can make a researcher spend far more time on analysis than performing the actual experiment. © 2014 Society for Endocrinology.

De novo clustering methods outperform reference-based methods for assigning 16S rRNA gene sequences to operational taxonomic units

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Sarah L. Westcott

2015-12-01

Full Text Available Background. 16S rRNA gene sequences are routinely assigned to operational taxonomic units (OTUs that are then used to analyze complex microbial communities. A number of methods have been employed to carry out the assignment of 16S rRNA gene sequences to OTUs leading to confusion over which method is optimal. A recent study suggested that a clustering method should be selected based on its ability to generate stable OTU assignments that do not change as additional sequences are added to the dataset. In contrast, we contend that the quality of the OTU assignments, the ability of the method to properly represent the distances between the sequences, is more important.Methods. Our analysis implemented six de novo clustering algorithms including the single linkage, complete linkage, average linkage, abundance-based greedy clustering, distance-based greedy clustering, and Swarm and the open and closed-reference methods. Using two previously published datasets we used the Matthew’s Correlation Coefficient (MCC to assess the stability and quality of OTU assignments.Results. The stability of OTU assignments did not reflect the quality of the assignments. Depending on the dataset being analyzed, the average linkage and the distance and abundance-based greedy clustering methods generated OTUs that were more likely to represent the actual distances between sequences than the open and closed-reference methods. We also demonstrated that for the greedy algorithms VSEARCH produced assignments that were comparable to those produced by USEARCH making VSEARCH a viable free and open source alternative to USEARCH. Further interrogation of the reference-based methods indicated that when USEARCH or VSEARCH were used to identify the closest reference, the OTU assignments were sensitive to the order of the reference sequences because the reference sequences can be identical over the region being considered. More troubling was the observation that while both USEARCH and

Nucleotide sequence of a human tRNA gene heterocluster

International Nuclear Information System (INIS)

Chang, Y.N.; Pirtle, I.L.; Pirtle, R.M.

1986-01-01

Leucine tRNA from bovine liver was used as a hybridization probe to screen a human gene library harbored in Charon-4A of bacteriophage lambda. The human DNA inserts from plaque-pure clones were characterized by restriction endonuclease mapping and Southern hybridization techniques, using both [3'- 32 P]-labeled bovine liver leucine tRNA and total tRNA as hybridization probes. An 8-kb Hind III fragment of one of these γ-clones was subcloned into the Hind III site of pBR322. Subsequent fine restriction mapping and DNA sequence analysis of this plasmid DNA indicated the presence of four tRNA genes within the 8-kb DNA fragment. A leucine tRNA gene with an anticodon of AAG and a proline tRNA gene with an anticodon of AGG are in a 1.6-kb subfragment. A threonine tRNA gene with an anticodon of UGU and an as yet unidentified tRNA gene are located in a 1.1-kb subfragment. These two different subfragments are separated by 2.8 kb. The coding regions of the three sequenced genes contain characteristic internal split promoter sequences and do not have intervening sequences. The 3'-flanking region of these three genes have typical RNA polymerase III termination sites of at least four consecutive T residues

Novel Approach to Analyzing MFE of Noncoding RNA Sequences.

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George, Tina P; Thomas, Tessamma

2016-01-01

Genomic studies have become noncoding RNA (ncRNA) centric after the study of different genomes provided enormous information on ncRNA over the past decades. The function of ncRNA is decided by its secondary structure, and across organisms, the secondary structure is more conserved than the sequence itself. In this study, the optimal secondary structure or the minimum free energy (MFE) structure of ncRNA was found based on the thermodynamic nearest neighbor model. MFE of over 2600 ncRNA sequences was analyzed in view of its signal properties. Mathematical models linking MFE to the signal properties were found for each of the four classes of ncRNA analyzed. MFE values computed with the proposed models were in concordance with those obtained with the standard web servers. A total of 95% of the sequences analyzed had deviation of MFE values within ±15% relative to those obtained from standard web servers.

Sequence analysis of RNase MRP RNA reveals its origination from eukaryotic RNase P RNA

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Zhu, Yanglong; Stribinskis, Vilius; Ramos, Kenneth S.; Li, Yong

2006-01-01

RNase MRP is a eukaryote-specific endoribonuclease that generates RNA primers for mitochondrial DNA replication and processes precursor rRNA. RNase P is a ubiquitous endoribonuclease that cleaves precursor tRNA transcripts to produce their mature 5′ termini. We found extensive sequence homology of catalytic domains and specificity domains between their RNA subunits in many organisms. In Candida glabrata, the internal loop of helix P3 is 100% conserved between MRP and P RNAs. The helix P8 of MRP RNA from microsporidia Encephalitozoon cuniculi is identical to that of P RNA. Sequence homology can be widely spread over the whole molecule of MRP RNA and P RNA, such as those from Dictyostelium discoideum. These conserved nucleotides between the MRP and P RNAs strongly support the hypothesis that the MRP RNA is derived from the P RNA molecule in early eukaryote evolution. PMID:16540690

Nicotiana small RNA sequences support a host genome origin of cucumber mosaic virus satellite RNA.

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Kiran Zahid

2015-01-01

Full Text Available Satellite RNAs (satRNAs are small noncoding subviral RNA pathogens in plants that depend on helper viruses for replication and spread. Despite many decades of research, the origin of satRNAs remains unknown. In this study we show that a β-glucuronidase (GUS transgene fused with a Cucumber mosaic virus (CMV Y satellite RNA (Y-Sat sequence (35S-GUS:Sat was transcriptionally repressed in N. tabacum in comparison to a 35S-GUS transgene that did not contain the Y-Sat sequence. This repression was not due to DNA methylation at the 35S promoter, but was associated with specific DNA methylation at the Y-Sat sequence. Both northern blot hybridization and small RNA deep sequencing detected 24-nt siRNAs in wild-type Nicotiana plants with sequence homology to Y-Sat, suggesting that the N. tabacum genome contains Y-Sat-like sequences that give rise to 24-nt sRNAs capable of guiding RNA-directed DNA methylation (RdDM to the Y-Sat sequence in the 35S-GUS:Sat transgene. Consistent with this, Southern blot hybridization detected multiple DNA bands in Nicotiana plants that had sequence homology to Y-Sat, suggesting that Y-Sat-like sequences exist in the Nicotiana genome as repetitive DNA, a DNA feature associated with 24-nt sRNAs. Our results point to a host genome origin for CMV satRNAs, and suggest novel approach of using small RNA sequences for finding the origin of other satRNAs.

SearchSmallRNA: a graphical interface tool for the assemblage of viral genomes using small RNA libraries data.

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de Andrade, Roberto R S; Vaslin, Maite F S

2014-03-07

Next-generation parallel sequencing (NGS) allows the identification of viral pathogens by sequencing the small RNAs of infected hosts. Thus, viral genomes may be assembled from host immune response products without prior virus enrichment, amplification or purification. However, mapping of the vast information obtained presents a bioinformatics challenge. In order to by pass the need of line command and basic bioinformatics knowledge, we develop a mapping software with a graphical interface to the assemblage of viral genomes from small RNA dataset obtained by NGS. SearchSmallRNA was developed in JAVA language version 7 using NetBeans IDE 7.1 software. The program also allows the analysis of the viral small interfering RNAs (vsRNAs) profile; providing an overview of the size distribution and other features of the vsRNAs produced in infected cells. The program performs comparisons between each read sequenced present in a library and a chosen reference genome. Reads showing Hamming distances smaller or equal to an allowed mismatched will be selected as positives and used to the assemblage of a long nucleotide genome sequence. In order to validate the software, distinct analysis using NGS dataset obtained from HIV and two plant viruses were used to reconstruct viral whole genomes. SearchSmallRNA program was able to reconstructed viral genomes using NGS of small RNA dataset with high degree of reliability so it will be a valuable tool for viruses sequencing and discovery. It is accessible and free to all research communities and has the advantage to have an easy-to-use graphical interface. SearchSmallRNA was written in Java and is freely available at http://www.microbiologia.ufrj.br/ssrna/.

A procedure to validate and correct the {sup 13}C chemical shift calibration of RNA datasets

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Aeschbacher, Thomas; Schubert, Mario, E-mail: schubert@mol.biol.ethz.ch; Allain, Frederic H.-T., E-mail: allain@mol.biol.ethz.ch [ETH Zuerich, Institute for Molecular Biology and Biophysics (Switzerland)

2012-02-15

Chemical shifts reflect the structural environment of a certain nucleus and can be used to extract structural and dynamic information. Proper calibration is indispensable to extract such information from chemical shifts. Whereas a variety of procedures exist to verify the chemical shift calibration for proteins, no such procedure is available for RNAs to date. We present here a procedure to analyze and correct the calibration of {sup 13}C NMR data of RNAs. Our procedure uses five {sup 13}C chemical shifts as a reference, each of them found in a narrow shift range in most datasets deposited in the Biological Magnetic Resonance Bank. In 49 datasets we could evaluate the {sup 13}C calibration and detect errors or inconsistencies in RNA {sup 13}C chemical shifts based on these chemical shift reference values. More than half of the datasets (27 out of those 49) were found to be improperly referenced or contained inconsistencies. This large inconsistency rate possibly explains that no clear structure-{sup 13}C chemical shift relationship has emerged for RNA so far. We were able to recalibrate or correct 17 datasets resulting in 39 usable {sup 13}C datasets. 6 new datasets from our lab were used to verify our method increasing the database to 45 usable datasets. We can now search for structure-chemical shift relationships with this improved list of {sup 13}C chemical shift data. This is demonstrated by a clear relationship between ribose {sup 13}C shifts and the sugar pucker, which can be used to predict a C2 Prime - or C3 Prime -endo conformation of the ribose with high accuracy. The improved quality of the chemical shift data allows statistical analysis with the potential to facilitate assignment procedures, and the extraction of restraints for structure calculations of RNA.

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.

mESAdb: microRNA expression and sequence analysis database.

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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.

RISC RNA sequencing for context-specific identification of in vivo microRNA targets.

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Matkovich, Scot J; Van Booven, Derek J; Eschenbacher, William H; Dorn, Gerald W

2011-01-07

MicroRNAs (miRs) are expanding our understanding of cardiac disease and have the potential to transform cardiovascular therapeutics. One miR can target hundreds of individual mRNAs, but existing methodologies are not sufficient to accurately and comprehensively identify these mRNA targets in vivo. To develop methods permitting identification of in vivo miR targets in an unbiased manner, using massively parallel sequencing of mouse cardiac transcriptomes in combination with sequencing of mRNA associated with mouse cardiac RNA-induced silencing complexes (RISCs). We optimized techniques for expression profiling small amounts of RNA without introducing amplification bias and applied this to anti-Argonaute 2 immunoprecipitated RISCs (RISC-Seq) from mouse hearts. By comparing RNA-sequencing results of cardiac RISC and transcriptome from the same individual hearts, we defined 1645 mRNAs consistently targeted to mouse cardiac RISCs. We used this approach in hearts overexpressing miRs from Myh6 promoter-driven precursors (programmed RISC-Seq) to identify 209 in vivo targets of miR-133a and 81 in vivo targets of miR-499. Consistent with the fact that miR-133a and miR-499 have widely differing "seed" sequences and belong to different miR families, only 6 targets were common to miR-133a- and miR-499-programmed hearts. RISC-sequencing is a highly sensitive method for general RISC profiling and individual miR target identification in biological context and is applicable to any tissue and any disease state.

International interlaboratory study comparing single organism 16S rRNA gene sequencing data: Beyond consensus sequence comparisons

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Olson, Nathan D.; Lund, Steven P.; Zook, Justin M.; Rojas-Cornejo, Fabiola; Beck, Brian; Foy, Carole; Huggett, Jim; Whale, Alexandra S.; Sui, Zhiwei; Baoutina, Anna; Dobeson, Michael; Partis, Lina; Morrow, Jayne B.

2015-01-01

This study presents the results from an interlaboratory sequencing study for which we developed a novel high-resolution method for comparing data from different sequencing platforms for a multi-copy, paralogous gene. The combination of PCR amplification and 16S ribosomal RNA gene (16S rRNA) sequencing has revolutionized bacteriology by enabling rapid identification, frequently without the need for culture. To assess variability between laboratories in sequencing 16S rRNA, six laboratories sequenced the gene encoding the 16S rRNA from Escherichia coli O157:H7 strain EDL933 and Listeria monocytogenes serovar 4b strain NCTC11994. Participants performed sequencing methods and protocols available in their laboratories: Sanger sequencing, Roche 454 pyrosequencing®, or Ion Torrent PGM®. The sequencing data were evaluated on three levels: (1) identity of biologically conserved position, (2) ratio of 16S rRNA gene copies featuring identified variants, and (3) the collection of variant combinations in a set of 16S rRNA gene copies. The same set of biologically conserved positions was identified for each sequencing method. Analytical methods using Bayesian and maximum likelihood statistics were developed to estimate variant copy ratios, which describe the ratio of nucleotides at each identified biologically variable position, as well as the likely set of variant combinations present in 16S rRNA gene copies. Our results indicate that estimated variant copy ratios at biologically variable positions were only reproducible for high throughput sequencing methods. Furthermore, the likely variant combination set was only reproducible with increased sequencing depth and longer read lengths. We also demonstrate novel methods for evaluating variable positions when comparing multi-copy gene sequence data from multiple laboratories generated using multiple sequencing technologies. PMID:27077030

International interlaboratory study comparing single organism 16S rRNA gene sequencing data: Beyond consensus sequence comparisons

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Nathan D. Olson

2015-03-01

Full Text Available This study presents the results from an interlaboratory sequencing study for which we developed a novel high-resolution method for comparing data from different sequencing platforms for a multi-copy, paralogous gene. The combination of PCR amplification and 16S ribosomal RNA gene (16S rRNA sequencing has revolutionized bacteriology by enabling rapid identification, frequently without the need for culture. To assess variability between laboratories in sequencing 16S rRNA, six laboratories sequenced the gene encoding the 16S rRNA from Escherichia coli O157:H7 strain EDL933 and Listeria monocytogenes serovar 4b strain NCTC11994. Participants performed sequencing methods and protocols available in their laboratories: Sanger sequencing, Roche 454 pyrosequencing®, or Ion Torrent PGM®. The sequencing data were evaluated on three levels: (1 identity of biologically conserved position, (2 ratio of 16S rRNA gene copies featuring identified variants, and (3 the collection of variant combinations in a set of 16S rRNA gene copies. The same set of biologically conserved positions was identified for each sequencing method. Analytical methods using Bayesian and maximum likelihood statistics were developed to estimate variant copy ratios, which describe the ratio of nucleotides at each identified biologically variable position, as well as the likely set of variant combinations present in 16S rRNA gene copies. Our results indicate that estimated variant copy ratios at biologically variable positions were only reproducible for high throughput sequencing methods. Furthermore, the likely variant combination set was only reproducible with increased sequencing depth and longer read lengths. We also demonstrate novel methods for evaluating variable positions when comparing multi-copy gene sequence data from multiple laboratories generated using multiple sequencing technologies.

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

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

2015-01-15

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

Nested PCR Biases in Interpreting Microbial Community Structure in 16S rRNA Gene Sequence Datasets.

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Yu, Guoqin; Fadrosh, Doug; Goedert, James J; Ravel, Jacques; Goldstein, Alisa M

2015-01-01

Sequencing of the PCR-amplified 16S rRNA gene has become a common approach to microbial community investigations in the fields of human health and environmental sciences. This approach, however, is difficult when the amount of DNA is too low to be amplified by standard PCR. Nested PCR can be employed as it can amplify samples with DNA concentration several-fold lower than standard PCR. However, potential biases with nested PCRs that could affect measurement of community structure have received little attention. In this study, we used 17 DNAs extracted from vaginal swabs and 12 DNAs extracted from stool samples to study the influence of nested PCR amplification of the 16S rRNA gene on the estimation of microbial community structure using Illumina MiSeq sequencing. Nested and standard PCR methods were compared on alpha- and beta-diversity metrics and relative abundances of bacterial genera. The effects of number of cycles in the first round of PCR (10 vs. 20) and microbial diversity (relatively low in vagina vs. high in stool) were also investigated. Vaginal swab samples showed no significant difference in alpha diversity or community structure between nested PCR and standard PCR (one round of 40 cycles). Stool samples showed significant differences in alpha diversity (except Shannon's index) and relative abundance of 13 genera between nested PCR with 20 cycles in the first round and standard PCR (Pnested PCR with 10 cycles in the first round and standard PCR. Operational taxonomic units (OTUs) that had low relative abundance (sum of relative abundance 27% of total OTUs in stool). Nested PCR introduced bias in estimated diversity and community structure. The bias was more significant for communities with relatively higher diversity and when more cycles were applied in the first round of PCR. We conclude that nested PCR could be used when standard PCR does not work. However, rare taxa detected by nested PCR should be validated by other technologies.

Bellerophon: a program to detect chimeric sequences in multiple sequence alignments.

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Huber, Thomas; Faulkner, Geoffrey; Hugenholtz, Philip

2004-09-22

Bellerophon is a program for detecting chimeric sequences in multiple sequence datasets by an adaption of partial treeing analysis. Bellerophon was specifically developed to detect 16S rRNA gene chimeras in PCR-clone libraries of environmental samples but can be applied to other nucleotide sequence alignments. Bellerophon is available as an interactive web server at http://foo.maths.uq.edu.au/~huber/bellerophon.pl

Reconstruction of ancestral RNA sequences under multiple structural constraints.

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Tremblay-Savard, Olivier; Reinharz, Vladimir; Waldispühl, Jérôme

2016-11-11

Secondary structures form the scaffold of multiple sequence alignment of non-coding RNA (ncRNA) families. An accurate reconstruction of ancestral ncRNAs must use this structural signal. However, the inference of ancestors of a single ncRNA family with a single consensus structure may bias the results towards sequences with high affinity to this structure, which are far from the true ancestors. In this paper, we introduce achARNement, a maximum parsimony approach that, given two alignments of homologous ncRNA families with consensus secondary structures and a phylogenetic tree, simultaneously calculates ancestral RNA sequences for these two families. We test our methodology on simulated data sets, and show that achARNement outperforms classical maximum parsimony approaches in terms of accuracy, but also reduces by several orders of magnitude the number of candidate sequences. To conclude this study, we apply our algorithms on the Glm clan and the FinP-traJ clan from the Rfam database. Our results show that our methods reconstruct small sets of high-quality candidate ancestors with better agreement to the two target structures than with classical approaches. Our program is freely available at: http://csb.cs.mcgill.ca/acharnement .

Deep Sequencing Insights in Therapeutic shRNA Processing and siRNA Target Cleavage Precision.

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Denise, Hubert; Moschos, Sterghios A; Sidders, Benjamin; Burden, Frances; Perkins, Hannah; Carter, Nikki; Stroud, Tim; Kennedy, Michael; Fancy, Sally-Ann; Lapthorn, Cris; Lavender, Helen; Kinloch, Ross; Suhy, David; Corbau, Romu

2014-02-04

TT-034 (PF-05095808) is a recombinant adeno-associated virus serotype 8 (AAV8) agent expressing three short hairpin RNA (shRNA) pro-drugs that target the hepatitis C virus (HCV) RNA genome. The cytosolic enzyme Dicer cleaves each shRNA into multiple, potentially active small interfering RNA (siRNA) drugs. Using next-generation sequencing (NGS) to identify and characterize active shRNAs maturation products, we observed that each TT-034-encoded shRNA could be processed into as many as 95 separate siRNA strands. Few of these appeared active as determined by Sanger 5' RNA Ligase-Mediated Rapid Amplification of cDNA Ends (5-RACE) and through synthetic shRNA and siRNA analogue studies. Moreover, NGS scrutiny applied on 5-RACE products (RACE-seq) suggested that synthetic siRNAs could direct cleavage in not one, but up to five separate positions on targeted RNA, in a sequence-dependent manner. These data support an on-target mechanism of action for TT-034 without cytotoxicity and question the accepted precision of substrate processing by the key RNA interference (RNAi) enzymes Dicer and siRNA-induced silencing complex (siRISC).Molecular Therapy-Nucleic Acids (2014) 3, e145; doi:10.1038/mtna.2013.73; published online 4 February 2014.

Reconstruction of ancestral RNA sequences under multiple structural constraints

OpenAIRE

Tremblay-Savard, Olivier; Reinharz, Vladimir; Waldisp?hl, J?r?me

2016-01-01

Background Secondary structures form the scaffold of multiple sequence alignment of non-coding RNA (ncRNA) families. An accurate reconstruction of ancestral ncRNAs must use this structural signal. However, the inference of ancestors of a single ncRNA family with a single consensus structure may bias the results towards sequences with high affinity to this structure, which are far from the true ancestors. Methods In this paper, we introduce achARNement, a maximum parsimony approach that, given...

TIMPs of parasitic helminths - a large-scale analysis of high-throughput sequence datasets.

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Cantacessi, Cinzia; Hofmann, Andreas; Pickering, Darren; Navarro, Severine; Mitreva, Makedonka; Loukas, Alex

2013-05-30

Tissue inhibitors of metalloproteases (TIMPs) are a multifunctional family of proteins that orchestrate extracellular matrix turnover, tissue remodelling and other cellular processes. In parasitic helminths, such as hookworms, TIMPs have been proposed to play key roles in the host-parasite interplay, including invasion of and establishment in the vertebrate animal hosts. Currently, knowledge of helminth TIMPs is limited to a small number of studies on canine hookworms, whereas no information is available on the occurrence of TIMPs in other parasitic helminths causing neglected diseases. In the present study, we conducted a large-scale investigation of TIMP proteins of a range of neglected human parasites including the hookworm Necator americanus, the roundworm Ascaris suum, the liver flukes Clonorchis sinensis and Opisthorchis viverrini, as well as the schistosome blood flukes. This entailed mining available transcriptomic and/or genomic sequence datasets for the presence of homologues of known TIMPs, predicting secondary structures of defined protein sequences, systematic phylogenetic analyses and assessment of differential expression of genes encoding putative TIMPs in the developmental stages of A. suum, N. americanus and Schistosoma haematobium which infect the mammalian hosts. A total of 15 protein sequences with high homology to known eukaryotic TIMPs were predicted from the complement of sequence data available for parasitic helminths and subjected to in-depth bioinformatic analyses. Supported by the availability of gene manipulation technologies such as RNA interference and/or transgenesis, this work provides a basis for future functional explorations of helminth TIMPs and, in particular, of their role/s in fundamental biological pathways linked to long-term establishment in the vertebrate hosts, with a view towards the development of novel approaches for the control of neglected helminthiases.

Next-generation sequencing library preparation method for identification of RNA viruses on the Ion Torrent Sequencing Platform.

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Chen, Guiqian; Qiu, Yuan; Zhuang, Qingye; Wang, Suchun; Wang, Tong; Chen, Jiming; Wang, Kaicheng

2018-05-09

Next generation sequencing (NGS) is a powerful tool for the characterization, discovery, and molecular identification of RNA viruses. There were multiple NGS library preparation methods published for strand-specific RNA-seq, but some methods are not suitable for identifying and characterizing RNA viruses. In this study, we report a NGS library preparation method to identify RNA viruses using the Ion Torrent PGM platform. The NGS sequencing adapters were directly inserted into the sequencing library through reverse transcription and polymerase chain reaction, without fragmentation and ligation of nucleic acids. The results show that this method is simple to perform, able to identify multiple species of RNA viruses in clinical samples.

SigEMD: A powerful method for differential gene expression analysis in single-cell RNA sequencing data.

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Wang, Tianyu; Nabavi, Sheida

2018-04-24

Differential gene expression analysis is one of the significant efforts in single cell RNA sequencing (scRNAseq) analysis to discover the specific changes in expression levels of individual cell types. Since scRNAseq exhibits multimodality, large amounts of zero counts, and sparsity, it is different from the traditional bulk RNA sequencing (RNAseq) data. The new challenges of scRNAseq data promote the development of new methods for identifying differentially expressed (DE) genes. In this study, we proposed a new method, SigEMD, that combines a data imputation approach, a logistic regression model and a nonparametric method based on the Earth Mover's Distance, to precisely and efficiently identify DE genes in scRNAseq data. The regression model and data imputation are used to reduce the impact of large amounts of zero counts, and the nonparametric method is used to improve the sensitivity of detecting DE genes from multimodal scRNAseq data. By additionally employing gene interaction network information to adjust the final states of DE genes, we further reduce the false positives of calling DE genes. We used simulated datasets and real datasets to evaluate the detection accuracy of the proposed method and to compare its performance with those of other differential expression analysis methods. Results indicate that the proposed method has an overall powerful performance in terms of precision in detection, sensitivity, and specificity. Copyright © 2018 Elsevier Inc. All rights reserved.

Sequence-structure relationships in RNA loops: establishing the basis for loop homology modeling.

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Schudoma, Christian; May, Patrick; Nikiforova, Viktoria; Walther, Dirk

2010-01-01

The specific function of RNA molecules frequently resides in their seemingly unstructured loop regions. We performed a systematic analysis of RNA loops extracted from experimentally determined three-dimensional structures of RNA molecules. A comprehensive loop-structure data set was created and organized into distinct clusters based on structural and sequence similarity. We detected clear evidence of the hallmark of homology present in the sequence-structure relationships in loops. Loops differing by structures. Thus, our results support the application of homology modeling for RNA loop model building. We established a threshold that may guide the sequence divergence-based selection of template structures for RNA loop homology modeling. Of all possible sequences that are, under the assumption of isosteric relationships, theoretically compatible with actual sequences observed in RNA structures, only a small fraction is contained in the Rfam database of RNA sequences and classes implying that the actual RNA loop space may consist of a limited number of unique loop structures and conserved sequences. The loop-structure data sets are made available via an online database, RLooM. RLooM also offers functionalities for the modeling of RNA loop structures in support of RNA engineering and design efforts.

Mutation of miRNA target sequences during human evolution

DEFF Research Database (Denmark)

Gardner, Paul P; Vinther, Jeppe

2008-01-01

It has long-been hypothesized that changes in non-protein-coding genes and the regulatory sequences controlling expression could undergo positive selection. Here we identify 402 putative microRNA (miRNA) target sequences that have been mutated specifically in the human lineage and show that genes...... containing such deletions are more highly expressed than their mouse orthologs. Our findings indicate that some miRNA target mutations are fixed by positive selection and might have been involved in the evolution of human-specific traits....

Assessing the 5S ribosomal RNA heterogeneity in Arabidopsis thaliana using short RNA next generation sequencing data.

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Szymanski, Maciej; Karlowski, Wojciech M

2016-01-01

In eukaryotes, ribosomal 5S rRNAs are products of multigene families organized within clusters of tandemly repeated units. Accumulation of genomic data obtained from a variety of organisms demonstrated that the potential 5S rRNA coding sequences show a large number of variants, often incompatible with folding into a correct secondary structure. Here, we present results of an analysis of a large set of short RNA sequences generated by the next generation sequencing techniques, to address the problem of heterogeneity of the 5S rRNA transcripts in Arabidopsis and identification of potentially functional rRNA-derived fragments.

sRNAnalyzer-a flexible and customizable small RNA sequencing data analysis pipeline.

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Wu, Xiaogang; Kim, Taek-Kyun; Baxter, David; Scherler, Kelsey; Gordon, Aaron; Fong, Olivia; Etheridge, Alton; Galas, David J; Wang, Kai

2017-12-01

Although many tools have been developed to analyze small RNA sequencing (sRNA-Seq) data, it remains challenging to accurately analyze the small RNA population, mainly due to multiple sequence ID assignment caused by short read length. Additional issues in small RNA analysis include low consistency of microRNA (miRNA) measurement results across different platforms, miRNA mapping associated with miRNA sequence variation (isomiR) and RNA editing, and the origin of those unmapped reads after screening against all endogenous reference sequence databases. To address these issues, we built a comprehensive and customizable sRNA-Seq data analysis pipeline-sRNAnalyzer, which enables: (i) comprehensive miRNA profiling strategies to better handle isomiRs and summarization based on each nucleotide position to detect potential SNPs in miRNAs, (ii) different sequence mapping result assignment approaches to simulate results from microarray/qRT-PCR platforms and a local probabilistic model to assign mapping results to the most-likely IDs, (iii) comprehensive ribosomal RNA filtering for accurate mapping of exogenous RNAs and summarization based on taxonomy annotation. We evaluated our pipeline on both artificial samples (including synthetic miRNA and Escherichia coli cultures) and biological samples (human tissue and plasma). sRNAnalyzer is implemented in Perl and available at: http://srnanalyzer.systemsbiology.net/. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

sRNAnalyzer—a flexible and customizable small RNA sequencing data analysis pipeline

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Kim, Taek-Kyun; Baxter, David; Scherler, Kelsey; Gordon, Aaron; Fong, Olivia; Etheridge, Alton; Galas, David J.

2017-01-01

Abstract Although many tools have been developed to analyze small RNA sequencing (sRNA-Seq) data, it remains challenging to accurately analyze the small RNA population, mainly due to multiple sequence ID assignment caused by short read length. Additional issues in small RNA analysis include low consistency of microRNA (miRNA) measurement results across different platforms, miRNA mapping associated with miRNA sequence variation (isomiR) and RNA editing, and the origin of those unmapped reads after screening against all endogenous reference sequence databases. To address these issues, we built a comprehensive and customizable sRNA-Seq data analysis pipeline—sRNAnalyzer, which enables: (i) comprehensive miRNA profiling strategies to better handle isomiRs and summarization based on each nucleotide position to detect potential SNPs in miRNAs, (ii) different sequence mapping result assignment approaches to simulate results from microarray/qRT-PCR platforms and a local probabilistic model to assign mapping results to the most-likely IDs, (iii) comprehensive ribosomal RNA filtering for accurate mapping of exogenous RNAs and summarization based on taxonomy annotation. We evaluated our pipeline on both artificial samples (including synthetic miRNA and Escherichia coli cultures) and biological samples (human tissue and plasma). sRNAnalyzer is implemented in Perl and available at: http://srnanalyzer.systemsbiology.net/. PMID:29069500

Reconstruction of ancestral RNA sequences under multiple structural constraints

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Olivier Tremblay-Savard

2016-11-01

Full Text Available Abstract Background Secondary structures form the scaffold of multiple sequence alignment of non-coding RNA (ncRNA families. An accurate reconstruction of ancestral ncRNAs must use this structural signal. However, the inference of ancestors of a single ncRNA family with a single consensus structure may bias the results towards sequences with high affinity to this structure, which are far from the true ancestors. Methods In this paper, we introduce achARNement, a maximum parsimony approach that, given two alignments of homologous ncRNA families with consensus secondary structures and a phylogenetic tree, simultaneously calculates ancestral RNA sequences for these two families. Results We test our methodology on simulated data sets, and show that achARNement outperforms classical maximum parsimony approaches in terms of accuracy, but also reduces by several orders of magnitude the number of candidate sequences. To conclude this study, we apply our algorithms on the Glm clan and the FinP-traJ clan from the Rfam database. Conclusions Our results show that our methods reconstruct small sets of high-quality candidate ancestors with better agreement to the two target structures than with classical approaches. Our program is freely available at: http://csb.cs.mcgill.ca/acharnement .

Nuclear RNA sequencing of the mouse erythroid cell transcriptome.

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Jennifer A Mitchell

Full Text Available In addition to protein coding genes a substantial proportion of mammalian genomes are transcribed. However, most transcriptome studies investigate steady-state mRNA levels, ignoring a considerable fraction of the transcribed genome. In addition, steady-state mRNA levels are influenced by both transcriptional and posttranscriptional mechanisms, and thus do not provide a clear picture of transcriptional output. Here, using deep sequencing of nuclear RNAs (nucRNA-Seq in parallel with chromatin immunoprecipitation sequencing (ChIP-Seq of active RNA polymerase II, we compared the nuclear transcriptome of mouse anemic spleen erythroid cells with polymerase occupancy on a genome-wide scale. We demonstrate that unspliced transcripts quantified by nucRNA-seq correlate with primary transcript frequencies measured by RNA FISH, but differ from steady-state mRNA levels measured by poly(A-enriched RNA-seq. Highly expressed protein coding genes showed good correlation between RNAPII occupancy and transcriptional output; however, genome-wide we observed a poor correlation between transcriptional output and RNAPII association. This poor correlation is due to intergenic regions associated with RNAPII which correspond with transcription factor bound regulatory regions and a group of stable, nuclear-retained long non-coding transcripts. In conclusion, sequencing the nuclear transcriptome provides an opportunity to investigate the transcriptional landscape in a given cell type through quantification of unspliced primary transcripts and the identification of nuclear-retained long non-coding RNAs.

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

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

2014-03-05

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

Classifying next-generation sequencing data using a zero-inflated Poisson model.

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Zhou, Yan; Wan, Xiang; Zhang, Baoxue; Tong, Tiejun

2018-04-15

With the development of high-throughput techniques, RNA-sequencing (RNA-seq) is becoming increasingly popular as an alternative for gene expression analysis, such as RNAs profiling and classification. Identifying which type of diseases a new patient belongs to with RNA-seq data has been recognized as a vital problem in medical research. As RNA-seq data are discrete, statistical methods developed for classifying microarray data cannot be readily applied for RNA-seq data classification. Witten proposed a Poisson linear discriminant analysis (PLDA) to classify the RNA-seq data in 2011. Note, however, that the count datasets are frequently characterized by excess zeros in real RNA-seq or microRNA sequence data (i.e. when the sequence depth is not enough or small RNAs with the length of 18-30 nucleotides). Therefore, it is desired to develop a new model to analyze RNA-seq data with an excess of zeros. In this paper, we propose a Zero-Inflated Poisson Logistic Discriminant Analysis (ZIPLDA) for RNA-seq data with an excess of zeros. The new method assumes that the data are from a mixture of two distributions: one is a point mass at zero, and the other follows a Poisson distribution. We then consider a logistic relation between the probability of observing zeros and the mean of the genes and the sequencing depth in the model. Simulation studies show that the proposed method performs better than, or at least as well as, the existing methods in a wide range of settings. Two real datasets including a breast cancer RNA-seq dataset and a microRNA-seq dataset are also analyzed, and they coincide with the simulation results that our proposed method outperforms the existing competitors. The software is available at http://www.math.hkbu.edu.hk/∼tongt. xwan@comp.hkbu.edu.hk or tongt@hkbu.edu.hk. Supplementary data are available at Bioinformatics online.

A tale of two sequences: microRNA-target chimeric reads.

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Broughton, James P; Pasquinelli, Amy E

2016-04-04

In animals, a functional interaction between a microRNA (miRNA) and its target RNA requires only partial base pairing. The limited number of base pair interactions required for miRNA targeting provides miRNAs with broad regulatory potential and also makes target prediction challenging. Computational approaches to target prediction have focused on identifying miRNA target sites based on known sequence features that are important for canonical targeting and may miss non-canonical targets. Current state-of-the-art experimental approaches, such as CLIP-seq (cross-linking immunoprecipitation with sequencing), PAR-CLIP (photoactivatable-ribonucleoside-enhanced CLIP), and iCLIP (individual-nucleotide resolution CLIP), require inference of which miRNA is bound at each site. Recently, the development of methods to ligate miRNAs to their target RNAs during the preparation of sequencing libraries has provided a new tool for the identification of miRNA target sites. The chimeric, or hybrid, miRNA-target reads that are produced by these methods unambiguously identify the miRNA bound at a specific target site. The information provided by these chimeric reads has revealed extensive non-canonical interactions between miRNAs and their target mRNAs, and identified many novel interactions between miRNAs and noncoding RNAs.

RStrucFam: a web server to associate structure and cognate RNA for RNA-binding proteins from sequence information.

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Ghosh, Pritha; Mathew, Oommen K; Sowdhamini, Ramanathan

2016-10-07

RNA-binding proteins (RBPs) interact with their cognate RNA(s) to form large biomolecular assemblies. They are versatile in their functionality and are involved in a myriad of processes inside the cell. RBPs with similar structural features and common biological functions are grouped together into families and superfamilies. It will be useful to obtain an early understanding and association of RNA-binding property of sequences of gene products. Here, we report a web server, RStrucFam, to predict the structure, type of cognate RNA(s) and function(s) of proteins, where possible, from mere sequence information. The web server employs Hidden Markov Model scan (hmmscan) to enable association to a back-end database of structural and sequence families. The database (HMMRBP) comprises of 437 HMMs of RBP families of known structure that have been generated using structure-based sequence alignments and 746 sequence-centric RBP family HMMs. The input protein sequence is associated with structural or sequence domain families, if structure or sequence signatures exist. In case of association of the protein with a family of known structures, output features like, multiple structure-based sequence alignment (MSSA) of the query with all others members of that family is provided. Further, cognate RNA partner(s) for that protein, Gene Ontology (GO) annotations, if any and a homology model of the protein can be obtained. The users can also browse through the database for details pertaining to each family, protein or RNA and their related information based on keyword search or RNA motif search. RStrucFam is a web server that exploits structurally conserved features of RBPs, derived from known family members and imprinted in mathematical profiles, to predict putative RBPs from sequence information. Proteins that fail to associate with such structure-centric families are further queried against the sequence-centric RBP family HMMs in the HMMRBP database. Further, all other essential

Defining reference sequences for Nocardia species by similarity and clustering analyses of 16S rRNA gene sequence data.

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Manal Helal

Full Text Available BACKGROUND: The intra- and inter-species genetic diversity of bacteria and the absence of 'reference', or the most representative, sequences of individual species present a significant challenge for sequence-based identification. The aims of this study were to determine the utility, and compare the performance of several clustering and classification algorithms to identify the species of 364 sequences of 16S rRNA gene with a defined species in GenBank, and 110 sequences of 16S rRNA gene with no defined species, all within the genus Nocardia. METHODS: A total of 364 16S rRNA gene sequences of Nocardia species were studied. In addition, 110 16S rRNA gene sequences assigned only to the Nocardia genus level at the time of submission to GenBank were used for machine learning classification experiments. Different clustering algorithms were compared with a novel algorithm or the linear mapping (LM of the distance matrix. Principal Components Analysis was used for the dimensionality reduction and visualization. RESULTS: The LM algorithm achieved the highest performance and classified the set of 364 16S rRNA sequences into 80 clusters, the majority of which (83.52% corresponded with the original species. The most representative 16S rRNA sequences for individual Nocardia species have been identified as 'centroids' in respective clusters from which the distances to all other sequences were minimized; 110 16S rRNA gene sequences with identifications recorded only at the genus level were classified using machine learning methods. Simple kNN machine learning demonstrated the highest performance and classified Nocardia species sequences with an accuracy of 92.7% and a mean frequency of 0.578. CONCLUSION: The identification of centroids of 16S rRNA gene sequence clusters using novel distance matrix clustering enables the identification of the most representative sequences for each individual species of Nocardia and allows the quantitation of inter- and intra

Full-length mRNA sequencing uncovers a widespread coupling between transcription initiation and mRNA processing.

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Anvar, Seyed Yahya; Allard, Guy; Tseng, Elizabeth; Sheynkman, Gloria M; de Klerk, Eleonora; Vermaat, Martijn; Yin, Raymund H; Johansson, Hans E; Ariyurek, Yavuz; den Dunnen, Johan T; Turner, Stephen W; 't Hoen, Peter A C

2018-03-29

The multifaceted control of gene expression requires tight coordination of regulatory mechanisms at transcriptional and post-transcriptional level. Here, we studied the interdependence of transcription initiation, splicing and polyadenylation events on single mRNA molecules by full-length mRNA sequencing. In MCF-7 breast cancer cells, we find 2700 genes with interdependent alternative transcription initiation, splicing and polyadenylation events, both in proximal and distant parts of mRNA molecules, including examples of coupling between transcription start sites and polyadenylation sites. The analysis of three human primary tissues (brain, heart and liver) reveals similar patterns of interdependency between transcription initiation and mRNA processing events. We predict thousands of novel open reading frames from full-length mRNA sequences and obtained evidence for their translation by shotgun proteomics. The mapping database rescues 358 previously unassigned peptides and improves the assignment of others. By recognizing sample-specific amino-acid changes and novel splicing patterns, full-length mRNA sequencing improves proteogenomics analysis of MCF-7 cells. Our findings demonstrate that our understanding of transcriptome complexity is far from complete and provides a basis to reveal largely unresolved mechanisms that coordinate transcription initiation and mRNA processing.

"Transcriptomics": molecular diagnosis of inborn errors of metabolism via RNA-sequencing.

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Kremer, Laura S; Wortmann, Saskia B; Prokisch, Holger

2018-01-25

Exome wide sequencing techniques have revolutionized molecular diagnostics in patients with suspected inborn errors of metabolism or neuromuscular disorders. However, the diagnostic yield of 25-60% still leaves a large fraction of individuals without a diagnosis. This indicates a causative role for non-exonic regulatory variants not covered by whole exome sequencing. Here we review how systematic RNA-sequencing analysis (RNA-seq, "transcriptomics") lead to a molecular diagnosis in 10-35% of patients in whom whole exome sequencing failed to do so. Importantly, RNA-sequencing based discoveries cannot only guide molecular diagnosis but might also unravel therapeutic intervention points such as antisense oligonucleotide treatment for splicing defects as recently reported for spinal muscular atrophy.

Mirnovo: genome-free prediction of microRNAs from small RNA sequencing data and single-cells using decision forests.

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Vitsios, Dimitrios M; Kentepozidou, Elissavet; Quintais, Leonor; Benito-Gutiérrez, Elia; van Dongen, Stijn; Davis, Matthew P; Enright, Anton J

2017-12-01

The discovery of microRNAs (miRNAs) remains an important problem, particularly given the growth of high-throughput sequencing, cell sorting and single cell biology. While a large number of miRNAs have already been annotated, there may well be large numbers of miRNAs that are expressed in very particular cell types and remain elusive. Sequencing allows us to quickly and accurately identify the expression of known miRNAs from small RNA-Seq data. The biogenesis of miRNAs leads to very specific characteristics observed in their sequences. In brief, miRNAs usually have a well-defined 5' end and a more flexible 3' end with the possibility of 3' tailing events, such as uridylation. Previous approaches to the prediction of novel miRNAs usually involve the analysis of structural features of miRNA precursor hairpin sequences obtained from genome sequence. We surmised that it may be possible to identify miRNAs by using these biogenesis features observed directly from sequenced reads, solely or in addition to structural analysis from genome data. To this end, we have developed mirnovo, a machine learning based algorithm, which is able to identify known and novel miRNAs in animals and plants directly from small RNA-Seq data, with or without a reference genome. This method performs comparably to existing tools, however is simpler to use with reduced run time. Its performance and accuracy has been tested on multiple datasets, including species with poorly assembled genomes, RNaseIII (Drosha and/or Dicer) deficient samples and single cells (at both embryonic and adult stage). © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

MicroRNA sequence motifs reveal asymmetry between the stem arms

DEFF Research Database (Denmark)

Gorodkin, Jan; Havgaard, Jakob Hull; Ensterö, M.

2006-01-01

The processing of micro RNAs (miRNAs) from their stemloop precursor have revealed asymmetry in the processing of the mature and its star sequence. Furthermore, the miRNA processing system between organism differ. To assess this at the sequence level we have investigated mature miRNAs in their gen......The processing of micro RNAs (miRNAs) from their stemloop precursor have revealed asymmetry in the processing of the mature and its star sequence. Furthermore, the miRNA processing system between organism differ. To assess this at the sequence level we have investigated mature mi...

A powerful and flexible approach to the analysis of RNA sequence count data.

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Zhou, Yi-Hui; Xia, Kai; Wright, Fred A

2011-10-01

A number of penalization and shrinkage approaches have been proposed for the analysis of microarray gene expression data. Similar techniques are now routinely applied to RNA sequence transcriptional count data, although the value of such shrinkage has not been conclusively established. If penalization is desired, the explicit modeling of mean-variance relationships provides a flexible testing regimen that 'borrows' information across genes, while easily incorporating design effects and additional covariates. We describe BBSeq, which incorporates two approaches: (i) a simple beta-binomial generalized linear model, which has not been extensively tested for RNA-Seq data and (ii) an extension of an expression mean-variance modeling approach to RNA-Seq data, involving modeling of the overdispersion as a function of the mean. Our approaches are flexible, allowing for general handling of discrete experimental factors and continuous covariates. We report comparisons with other alternate methods to handle RNA-Seq data. Although penalized methods have advantages for very small sample sizes, the beta-binomial generalized linear model, combined with simple outlier detection and testing approaches, appears to have favorable characteristics in power and flexibility. An R package containing examples and sample datasets is available at http://www.bios.unc.edu/research/genomic_software/BBSeq yzhou@bios.unc.edu; fwright@bios.unc.edu Supplementary data are available at Bioinformatics online.

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

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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.

Nucleotide sequence and genetic organization of barley stripe mosaic virus RNA gamma.

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Gustafson, G; Hunter, B; Hanau, R; Armour, S L; Jackson, A O

1987-06-01

The complete nucleotide sequences of RNA gamma from the Type and ND18 strains of barley stripe mosaic virus (BSMV) have been determined. The sequences are 3164 (Type) and 2791 (ND18) nucleotides in length. Both sequences contain a 5'-noncoding region (87 or 88 nucleotides) which is followed by a long open reading frame (ORF1). A 42-nucleotide intercistronic region separates ORF1 from a second, shorter open reading frame (ORF2) located near the 3'-end of the RNA. There is a high degree of homology between the Type and ND18 strains in the nucleotide sequence of ORF1. However, the Type strain contains a 366 nucleotide direct tandem repeat within ORF1 which is absent in the ND18 strain. Consequently, the predicted translation product of Type RNA gamma ORF1 (mol wt 87,312) is significantly larger than that of ND18 RNA gamma ORF1 (mol wt 74,011). The amino acid sequence of the ORF1 polypeptide contains homologies with putative RNA polymerases from other RNA viruses, suggesting that this protein may function in replication of the BSMV genome. The nucleotide sequence of RNA gamma ORF2 is nearly identical in the Type and ND18 strains. ORF2 codes for a polypeptide with a predicted molecular weight of 17,209 (Type) or 17,074 (ND18) which is known to be translated from a subgenomic (sg) RNA. The initiation point of this sgRNA has been mapped to a location 27 nucleotides upstream of the ORF2 initiation codon in the intercistronic region between ORF1 and ORF2. The sgRNA is not coterminal with the 3'-end of the genomic RNA, but instead contains heterogeneous poly(A) termini up to 150 nucleotides long (J. Stanley, R. Hanau, and A. O. Jackson, 1984, Virology 139, 375-383). In the genomic RNA gamma, ORF2 is followed by a short poly(A) tract and a 238-nucleotide tRNA-like structure.

Study design requirements for RNA sequencing-based breast cancer diagnostics.

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Mer, Arvind Singh; Klevebring, Daniel; Grönberg, Henrik; Rantalainen, Mattias

2016-02-01

Sequencing-based molecular characterization of tumors provides information required for individualized cancer treatment. There are well-defined molecular subtypes of breast cancer that provide improved prognostication compared to routine biomarkers. However, molecular subtyping is not yet implemented in routine breast cancer care. Clinical translation is dependent on subtype prediction models providing high sensitivity and specificity. In this study we evaluate sample size and RNA-sequencing read requirements for breast cancer subtyping to facilitate rational design of translational studies. We applied subsampling to ascertain the effect of training sample size and the number of RNA sequencing reads on classification accuracy of molecular subtype and routine biomarker prediction models (unsupervised and supervised). Subtype classification accuracy improved with increasing sample size up to N = 750 (accuracy = 0.93), although with a modest improvement beyond N = 350 (accuracy = 0.92). Prediction of routine biomarkers achieved accuracy of 0.94 (ER) and 0.92 (Her2) at N = 200. Subtype classification improved with RNA-sequencing library size up to 5 million reads. Development of molecular subtyping models for cancer diagnostics requires well-designed studies. Sample size and the number of RNA sequencing reads directly influence accuracy of molecular subtyping. Results in this study provide key information for rational design of translational studies aiming to bring sequencing-based diagnostics to the clinic.

Mechanisms controlling mRNA processing and translation : decoding the regulatory layers defining gene expression through RNA sequencing

NARCIS (Netherlands)

Klerk, Eleonora de

2015-01-01

The work described in this thesis focuses on the mechanisms that give rise to alternative mRNAs and their alternative translation into proteins. Each of the described studies has been based on a specific set of high-throughput RNA sequencing technologies. An overview of the available RNA sequencing

Organism-specific rRNA capture system for application in next-generation sequencing.

Directory of Open Access Journals (Sweden)

Sai-Kam Li

Full Text Available RNA-sequencing is a powerful tool in studying RNomics. However, the highly abundance of ribosomal RNAs (rRNA and transfer RNA (tRNA have predominated in the sequencing reads, thereby hindering the study of lowly expressed genes. Therefore, rRNA depletion prior to sequencing is often performed in order to preserve the subtle alteration in gene expression especially those at relatively low expression levels. One of the commercially available methods is to use DNA or RNA probes to hybridize to the target RNAs. However, there is always a concern with the non-specific binding and unintended removal of messenger RNA (mRNA when the same set of probes is applied to different organisms. The degree of such unintended mRNA removal varies among organisms due to organism-specific genomic variation. We developed a computer-based method to design probes to deplete rRNA in an organism-specific manner. Based on the computation results, biotinylated-RNA-probes were produced by in vitro transcription and were used to perform rRNA depletion with subtractive hybridization. We demonstrated that the designed probes of 16S rRNAs and 23S rRNAs can efficiently remove rRNAs from Mycobacterium smegmatis. In comparison with a commercial subtractive hybridization-based rRNA removal kit, using organism-specific probes is better in preserving the RNA integrity and abundance. We believe the computer-based design approach can be used as a generic method in preparing RNA of any organisms for next-generation sequencing, particularly for the transcriptome analysis of microbes.

RNA inverse folding using Monte Carlo tree search.

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Yang, Xiufeng; Yoshizoe, Kazuki; Taneda, Akito; Tsuda, Koji

2017-11-06

Artificially synthesized RNA molecules provide important ways for creating a variety of novel functional molecules. State-of-the-art RNA inverse folding algorithms can design simple and short RNA sequences of specific GC content, that fold into the target RNA structure. However, their performance is not satisfactory in complicated cases. We present a new inverse folding algorithm called MCTS-RNA, which uses Monte Carlo tree search (MCTS), a technique that has shown exceptional performance in Computer Go recently, to represent and discover the essential part of the sequence space. To obtain high accuracy, initial sequences generated by MCTS are further improved by a series of local updates. Our algorithm has an ability to control the GC content precisely and can deal with pseudoknot structures. Using common benchmark datasets for evaluation, MCTS-RNA showed a lot of promise as a standard method of RNA inverse folding. MCTS-RNA is available at https://github.com/tsudalab/MCTS-RNA .

High throughput 16S rRNA gene amplicon sequencing

DEFF Research Database (Denmark)

Nierychlo, Marta; Larsen, Poul; Jørgensen, Mads Koustrup

S rRNA gene amplicon sequencing has been developed over the past few years and is now ready to use for more comprehensive studies related to plant operation and optimization thanks to short analysis time, low cost, high throughput, and high taxonomic resolution. In this study we show how 16S r......RNA gene amplicon sequencing can be used to reveal factors of importance for the operation of full-scale nutrient removal plants related to settling problems and floc properties. Using optimized DNA extraction protocols, indexed primers and our in-house Illumina platform, we prepared multiple samples...... be correlated to the presence of the species that are regarded as “strong” and “weak” floc formers. In conclusion, 16S rRNA gene amplicon sequencing provides a high throughput approach for a rapid and cheap community profiling of activated sludge that in combination with multivariate statistics can be used...

Phylogenetic relationships of Salmonella based on rRNA sequences

DEFF Research Database (Denmark)

Christensen, H.; Nordentoft, Steen; Olsen, J.E.

1998-01-01

separated by 16S rRNA analysis and found to be closely related to the Escherichia coli and Shigella complex by both 16S and 23S rRNA analyses. The diphasic serotypes S. enterica subspp. I and VI were separated from the monophasic serotypes subspp. IIIa and IV, including S. bongori, by 23S rRNA sequence...

CoVennTree: A new method for the comparative analysis of large datasets

Directory of Open Access Journals (Sweden)

Steffen C. Lott

2015-02-01

Full Text Available The visualization of massive datasets, such as those resulting from comparative metatranscriptome analyses or the analysis of microbial population structures using ribosomal RNA sequences, is a challenging task. We developed a new method called CoVennTree (Comparative weighted Venn Tree that simultaneously compares up to three multifarious datasets by aggregating and propagating information from the bottom to the top level and produces a graphical output in Cytoscape. With the introduction of weighted Venn structures, the contents and relationships of various datasets can be correlated and simultaneously aggregated without losing information. We demonstrate the suitability of this approach using a dataset of 16S rDNA sequences obtained from microbial populations at three different depths of the Gulf of Aqaba in the Red Sea. CoVennTree has been integrated into the Galaxy ToolShed and can be directly downloaded and integrated into the user instance.

Sequence-specific RNA Photocleavage by Single-stranded DNA in Presence of Riboflavin

Science.gov (United States)

Zhao, Yongyun; Chen, Gangyi; Yuan, Yi; Li, Na; Dong, Juan; Huang, Xin; Cui, Xin; Tang, Zhuo

2015-10-01

Constant efforts have been made to develop new method to realize sequence-specific RNA degradation, which could cause inhibition of the expression of targeted gene. Herein, by using an unmodified short DNA oligonucleotide for sequence recognition and endogenic small molecue, vitamin B2 (riboflavin) as photosensitizer, we report a simple strategy to realize the sequence-specific photocleavage of targeted RNA. The DNA strand is complimentary to the target sequence to form DNA/RNA duplex containing a G•U wobble in the middle. The cleavage reaction goes through oxidative elimination mechanism at the nucleoside downstream of U of the G•U wobble in duplex to obtain unnatural RNA terminal, and the whole process is under tight control by using light as switch, which means the cleavage could be carried out according to specific spatial and temporal requirements. The biocompatibility of this method makes the DNA strand in combination with riboflavin a promising molecular tool for RNA manipulation.

Complete Genome Sequence of a Double-Stranded RNA Virus from Avocado

OpenAIRE

Villanueva, Francisco; Sabanadzovic, Sead; Valverde, Rodrigo A.; Navas-Castillo, Jesús

2012-01-01

A number of avocado (Persea americana) cultivars are known to contain high-molecular-weight double-stranded RNA (dsRNA) molecules for which a viral nature has been suggested, although sequence data are not available. Here we report the cloning and complete sequencing of a 13.5-kbp dsRNA virus isolated from avocado and show that it corresponds to the genome of a new species of the genus Endornavirus (family Endornaviridae), tentatively named Persea americana endornavirus (PaEV).

Predicting Consensus Structures for RNA Alignments Via Pseudo-Energy Minimization

Directory of Open Access Journals (Sweden)

Junilda Spirollari

2009-01-01

Full Text Available Thermodynamic processes with free energy parameters are often used in algorithms that solve the free energy minimization problem to predict secondary structures of single RNA sequences. While results from these algorithms are promising, an observation is that single sequence-based methods have moderate accuracy and more information is needed to improve on RNA secondary structure prediction, such as covariance scores obtained from multiple sequence alignments. We present in this paper a new approach to predicting the consensus secondary structure of a set of aligned RNA sequences via pseudo-energy minimization. Our tool, called RSpredict, takes into account sequence covariation and employs effective heuristics for accuracy improvement. RSpredict accepts, as input data, a multiple sequence alignment in FASTA or ClustalW format and outputs the consensus secondary structure of the input sequences in both the Vienna style Dot Bracket format and the Connectivity Table format. Our method was compared with some widely used tools including KNetFold, Pfold and RNAalifold. A comprehensive test on different datasets including Rfam sequence alignments and a multiple sequence alignment obtained from our study on the Drosophila X chromosome reveals that RSpredict is competitive with the existing tools on the tested datasets. RSpredict is freely available online as a web server and also as a jar file for download at http:// datalab.njit.edu/biology/RSpredict.

Optimizing a massive parallel sequencing workflow for quantitative miRNA expression analysis.

Directory of Open Access Journals (Sweden)

Francesca Cordero

Full Text Available BACKGROUND: Massive Parallel Sequencing methods (MPS can extend and improve the knowledge obtained by conventional microarray technology, both for mRNAs and short non-coding RNAs, e.g. miRNAs. The processing methods used to extract and interpret the information are an important aspect of dealing with the vast amounts of data generated from short read sequencing. Although the number of computational tools for MPS data analysis is constantly growing, their strengths and weaknesses as part of a complex analytical pipe-line have not yet been well investigated. PRIMARY FINDINGS: A benchmark MPS miRNA dataset, resembling a situation in which miRNAs are spiked in biological replication experiments was assembled by merging a publicly available MPS spike-in miRNAs data set with MPS data derived from healthy donor peripheral blood mononuclear cells. Using this data set we observed that short reads counts estimation is strongly under estimated in case of duplicates miRNAs, if whole genome is used as reference. Furthermore, the sensitivity of miRNAs detection is strongly dependent by the primary tool used in the analysis. Within the six aligners tested, specifically devoted to miRNA detection, SHRiMP and MicroRazerS show the highest sensitivity. Differential expression estimation is quite efficient. Within the five tools investigated, two of them (DESseq, baySeq show a very good specificity and sensitivity in the detection of differential expression. CONCLUSIONS: The results provided by our analysis allow the definition of a clear and simple analytical optimized workflow for miRNAs digital quantitative analysis.

Optimizing a massive parallel sequencing workflow for quantitative miRNA expression analysis.

Science.gov (United States)

Cordero, Francesca; Beccuti, Marco; Arigoni, Maddalena; Donatelli, Susanna; Calogero, Raffaele A

2012-01-01

Massive Parallel Sequencing methods (MPS) can extend and improve the knowledge obtained by conventional microarray technology, both for mRNAs and short non-coding RNAs, e.g. miRNAs. The processing methods used to extract and interpret the information are an important aspect of dealing with the vast amounts of data generated from short read sequencing. Although the number of computational tools for MPS data analysis is constantly growing, their strengths and weaknesses as part of a complex analytical pipe-line have not yet been well investigated. A benchmark MPS miRNA dataset, resembling a situation in which miRNAs are spiked in biological replication experiments was assembled by merging a publicly available MPS spike-in miRNAs data set with MPS data derived from healthy donor peripheral blood mononuclear cells. Using this data set we observed that short reads counts estimation is strongly under estimated in case of duplicates miRNAs, if whole genome is used as reference. Furthermore, the sensitivity of miRNAs detection is strongly dependent by the primary tool used in the analysis. Within the six aligners tested, specifically devoted to miRNA detection, SHRiMP and MicroRazerS show the highest sensitivity. Differential expression estimation is quite efficient. Within the five tools investigated, two of them (DESseq, baySeq) show a very good specificity and sensitivity in the detection of differential expression. The results provided by our analysis allow the definition of a clear and simple analytical optimized workflow for miRNAs digital quantitative analysis.

Nucleotide sequence and genetic organization of Hungarian grapevine chrome mosaic nepovirus RNA2.

Science.gov (United States)

Brault, V; Hibrand, L; Candresse, T; Le Gall, O; Dunez, J

1989-10-11

The complete nucleotide sequence of hungarian grapevine chrome mosaic nepovirus (GCMV) RNA2 has been determined. The RNA sequence is 4441 nucleotides in length, excluding the poly(A) tail. A polyprotein of 1324 amino acids with a calculated molecular weight of 146 kDa is encoded in a single long open reading frame extending from nucleotides 218 to 4190. This polyprotein is homologous with the protein encoded by the S strain of tomato black ring virus (TBRV) RNA2, the only other nepovirus sequenced so far. Direct sequencing of the viral coat protein and in vitro translation of transcripts derived from cDNA sequences demonstrate that, as for comoviruses, the coat protein is located at the carboxy terminus of the polyprotein. A model for the expression of GCMV RNA2 is presented.

Genome-wide RNA-seq analysis of human and mouse platelet transcriptomes

Science.gov (United States)

Rowley, Jesse W.; Oler, Andrew J.; Tolley, Neal D.; Hunter, Benjamin N.; Low, Elizabeth N.; Nix, David A.; Yost, Christian C.; Zimmerman, Guy A.

2011-01-01

Inbred mice are a useful tool for studying the in vivo functions of platelets. Nonetheless, the mRNA signature of mouse platelets is not known. Here, we use paired-end next-generation RNA sequencing (RNA-seq) to characterize the polyadenylated transcriptomes of human and mouse platelets. We report that RNA-seq provides unprecedented resolution of mRNAs that are expressed across the entire human and mouse genomes. Transcript expression and abundance are often conserved between the 2 species. Several mRNAs, however, are differentially expressed in human and mouse platelets. Moreover, previously described functional disparities between mouse and human platelets are reflected in differences at the transcript level, including protease activated receptor-1, protease activated receptor-3, platelet activating factor receptor, and factor V. This suggests that RNA-seq is a useful tool for predicting differences in platelet function between mice and humans. Our next-generation sequencing analysis provides new insights into the human and murine platelet transcriptomes. The sequencing dataset will be useful in the design of mouse models of hemostasis and a catalyst for discovery of new functions of platelets. Access to the dataset is found in the “Introduction.” PMID:21596849

Complete Genome Sequence of a Double-Stranded RNA Virus from Avocado

Science.gov (United States)

Villanueva, Francisco; Sabanadzovic, Sead; Valverde, Rodrigo A.

2012-01-01

A number of avocado (Persea americana) cultivars are known to contain high-molecular-weight double-stranded RNA (dsRNA) molecules for which a viral nature has been suggested, although sequence data are not available. Here we report the cloning and complete sequencing of a 13.5-kbp dsRNA virus isolated from avocado and show that it corresponds to the genome of a new species of the genus Endornavirus (family Endornaviridae), tentatively named Persea americana endornavirus (PaEV). PMID:22205720

RNA-ID, a Powerful Tool for Identifying and Characterizing Regulatory Sequences.

Science.gov (United States)

Brule, C E; Dean, K M; Grayhack, E J

2016-01-01

The identification and analysis of sequences that regulate gene expression is critical because regulated gene expression underlies biology. RNA-ID is an efficient and sensitive method to discover and investigate regulatory sequences in the yeast Saccharomyces cerevisiae, using fluorescence-based assays to detect green fluorescent protein (GFP) relative to a red fluorescent protein (RFP) control in individual cells. Putative regulatory sequences can be inserted either in-frame or upstream of a superfolder GFP fusion protein whose expression, like that of RFP, is driven by the bidirectional GAL1,10 promoter. In this chapter, we describe the methodology to identify and study cis-regulatory sequences in the RNA-ID system, explaining features and variations of the RNA-ID reporter, as well as some applications of this system. We describe in detail the methods to analyze a single regulatory sequence, from construction of a single GFP variant to assay of variants by flow cytometry, as well as modifications required to screen libraries of different strains simultaneously. We also describe subsequent analyses of regulatory sequences. © 2016 Elsevier Inc. All rights reserved.

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

Science.gov (United States)

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

2017-09-08

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

Quantitative miRNA expression analysis: comparing microarrays with next-generation sequencing

DEFF Research Database (Denmark)

Willenbrock, Hanni; Salomon, Jesper; Søkilde, Rolf

2009-01-01

Recently, next-generation sequencing has been introduced as a promising, new platform for assessing the copy number of transcripts, while the existing microarray technology is considered less reliable for absolute, quantitative expression measurements. Nonetheless, so far, results from the two...... technologies have only been compared based on biological data, leading to the conclusion that, although they are somewhat correlated, expression values differ significantly. Here, we use synthetic RNA samples, resembling human microRNA samples, to find that microarray expression measures actually correlate...... better with sample RNA content than expression measures obtained from sequencing data. In addition, microarrays appear highly sensitive and perform equivalently to next-generation sequencing in terms of reproducibility and relative ratio quantification....

Identification of Bacterial Small RNAs by RNA Sequencing

DEFF Research Database (Denmark)

Gómez Lozano, María; Marvig, Rasmus Lykke; Molin, Søren

2014-01-01

sequencing (RNA-seq) is described that involves the preparation and analysis of three different sequencing libraries. As a signifi cant number of unique sRNAs are identifi ed in each library, the libraries can be used either alone or in combination to increase the number of sRNAs identifi ed. The approach......Small regulatory RNAs (sRNAs) in bacteria are known to modulate gene expression and control a variety of processes including metabolic reactions, stress responses, and pathogenesis in response to environmental signals. A method to identify bacterial sRNAs on a genome-wide scale based on RNA...... may be applied to identify sRNAs in any bacterium under different growth and stress conditions....

Identification of novel RNA viruses in alfalfa (Medicago sativa): an Alphapartitivirus, a Deltapartitivirus, and a Marafivirus.

Science.gov (United States)

Kim, Hyein; Park, Dongbin; Hahn, Yoonsoo

2018-01-05

Genomic RNA molecules of plant RNA viruses are often co-isolated with the host RNAs, and their sequences can be detected in plant transcriptome datasets. Here, an alfalfa (Medicago sativa) transcriptome dataset was analyzed and three new RNA viruses were identified, which were named Medicago sativa alphapartitivirus 1 (MsAPV1), Medicago sativa deltapartitivirus 1 (MsDPV1), and Medicago sativa marafivirus 1 (MsMV1). The RNA-dependent RNA polymerases of MsAPV1, MsDPV1, and MsMV1 showed about 68%, 58%, and 46% amino acid sequence identity, respectively, with their closest virus species. Sequence similarity and phylogenetic analyses indicated that MsAPV1, MsDPV1, and MsMV1 were novel RNA virus species that belong to the genus Alphapartitivirus of the family Partitiviridae, the genus Deltapartitivirus of the family Partitiviridae, and the genus Marafivirus of the family Tymoviridae, respectively. The bioinformatics procedure applied in this study may facilitate the identification of novel RNA viruses from plant transcriptome data. Copyright © 2017 Elsevier B.V. All rights reserved.

The chemical structure of DNA sequence signals for RNA transcription

Science.gov (United States)

George, D. G.; Dayhoff, M. O.

1982-01-01

The proposed recognition sites for RNA transcription for E. coli NRA polymerase, bacteriophage T7 RNA polymerase, and eukaryotic RNA polymerase Pol II are evaluated in the light of the requirements for efficient recognition. It is shown that although there is good experimental evidence that specific nucleic acid sequence patterns are involved in transcriptional regulation in bacteria and bacterial viruses, among the sequences now available, only in the case of the promoters recognized by bacteriophage T7 polymerase does it seem likely that the pattern is sufficient. It is concluded that the eukaryotic pattern that is investigated is not restrictive enough to serve as a recognition site.

The UEA Small RNA Workbench: A Suite of Computational Tools for Small RNA Analysis.

Science.gov (United States)

Mohorianu, Irina; Stocks, Matthew Benedict; Applegate, Christopher Steven; Folkes, Leighton; Moulton, Vincent

2017-01-01

RNA silencing (RNA interference, RNAi) is a complex, highly conserved mechanism mediated by short, typically 20-24 nt in length, noncoding RNAs known as small RNAs (sRNAs). They act as guides for the sequence-specific transcriptional and posttranscriptional regulation of target mRNAs and play a key role in the fine-tuning of biological processes such as growth, response to stresses, or defense mechanism.High-throughput sequencing (HTS) technologies are employed to capture the expression levels of sRNA populations. The processing of the resulting big data sets facilitated the computational analysis of the sRNA patterns of variation within biological samples such as time point experiments, tissue series or various treatments. Rapid technological advances enable larger experiments, often with biological replicates leading to a vast amount of raw data. As a result, in this fast-evolving field, the existing methods for sequence characterization and prediction of interaction (regulatory) networks periodically require adapting or in extreme cases, a complete redesign to cope with the data deluge. In addition, the presence of numerous tools focused only on particular steps of HTS analysis hinders the systematic parsing of the results and their interpretation.The UEA small RNA Workbench (v1-4), described in this chapter, provides a user-friendly, modular, interactive analysis in the form of a suite of computational tools designed to process and mine sRNA datasets for interesting characteristics that can be linked back to the observed phenotypes. First, we show how to preprocess the raw sequencing output and prepare it for downstream analysis. Then we review some quality checks that can be used as a first indication of sources of variability between samples. Next we show how the Workbench can provide a comparison of the effects of different normalization approaches on the distributions of expression, enhanced methods for the identification of differentially expressed

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.

Accurate RNA consensus sequencing for high-fidelity detection of transcriptional mutagenesis-induced epimutations.

Science.gov (United States)

Reid-Bayliss, Kate S; Loeb, Lawrence A

2017-08-29

Transcriptional mutagenesis (TM) due to misincorporation during RNA transcription can result in mutant RNAs, or epimutations, that generate proteins with altered properties. TM has long been hypothesized to play a role in aging, cancer, and viral and bacterial evolution. However, inadequate methodologies have limited progress in elucidating a causal association. We present a high-throughput, highly accurate RNA sequencing method to measure epimutations with single-molecule sensitivity. Accurate RNA consensus sequencing (ARC-seq) uniquely combines RNA barcoding and generation of multiple cDNA copies per RNA molecule to eliminate errors introduced during cDNA synthesis, PCR, and sequencing. The stringency of ARC-seq can be scaled to accommodate the quality of input RNAs. We apply ARC-seq to directly assess transcriptome-wide epimutations resulting from RNA polymerase mutants and oxidative stress.

Sequence characterization of 5S ribosomal RNA from eight gram positive procaryotes

Science.gov (United States)

Woese, C. R.; Luehrsen, K. R.; Pribula, C. D.; Fox, G. E.

1976-01-01

Complete nucleotide sequences are presented for 5S rRNA from Bacillus subtilis, B. firmus, B. pasteurii, B. brevis, Lactobacillus brevis, and Streptococcus faecalis, and 5S rRNA oligonucleotide catalogs and partial sequence data are given for B. cereus and Sporosarcina ureae. These data demonstrate a striking consistency of 5S rRNA primary and secondary structure within a given bacterial grouping. An exception is B. brevis, in which the 5S rRNA sequence varies significantly from that of other bacilli in the tuned helix and the procaryotic loop. The localization of these variations suggests that B. brevis occupies an ecological niche that selects such changes. It is noted that this organism produces antibiotics which affect ribosome function.

TargetM6A: Identifying N6-Methyladenosine Sites From RNA Sequences via Position-Specific Nucleotide Propensities and a Support Vector Machine.

Science.gov (United States)

Li, Guang-Qing; Liu, Zi; Shen, Hong-Bin; Yu, Dong-Jun

2016-10-01

As one of the most ubiquitous post-transcriptional modifications of RNA, N 6 -methyladenosine ( [Formula: see text]) plays an essential role in many vital biological processes. The identification of [Formula: see text] sites in RNAs is significantly important for both basic biomedical research and practical drug development. In this study, we designed a computational-based method, called TargetM6A, to rapidly and accurately target [Formula: see text] sites solely from the primary RNA sequences. Two new features, i.e., position-specific nucleotide/dinucleotide propensities (PSNP/PSDP), are introduced and combined with the traditional nucleotide composition (NC) feature to formulate RNA sequences. The extracted features are further optimized to obtain a much more compact and discriminative feature subset by applying an incremental feature selection (IFS) procedure. Based on the optimized feature subset, we trained TargetM6A on the training dataset with a support vector machine (SVM) as the prediction engine. We compared the proposed TargetM6A method with existing methods for predicting [Formula: see text] sites by performing stringent jackknife tests and independent validation tests on benchmark datasets. The experimental results show that the proposed TargetM6A method outperformed the existing methods for predicting [Formula: see text] sites and remarkably improved the prediction performances, with MCC = 0.526 and AUC = 0.818. We also provided a user-friendly web server for TargetM6A, which is publicly accessible for academic use at http://csbio.njust.edu.cn/bioinf/TargetM6A.

Small molecule alteration of RNA sequence in cells and animals.

Science.gov (United States)

Guan, Lirui; Luo, Yiling; Ja, William W; Disney, Matthew D

2017-10-18

RNA regulation and maintenance are critical for proper cell function. Small molecules that specifically alter RNA sequence would be exceptionally useful as probes of RNA structure and function or as potential therapeutics. Here, we demonstrate a photochemical approach for altering the trinucleotide expanded repeat causative of myotonic muscular dystrophy type 1 (DM1), r(CUG) exp . The small molecule, 2H-4-Ru, binds to r(CUG) exp and converts guanosine residues to 8-oxo-7,8-dihydroguanosine upon photochemical irradiation. We demonstrate targeted modification upon irradiation in cell culture and in Drosophila larvae provided a diet containing 2H-4-Ru. Our results highlight a general chemical biology approach for altering RNA sequence in vivo by using small molecules and photochemistry. Furthermore, these studies show that addition of 8-oxo-G lesions into RNA 3' untranslated regions does not affect its steady state levels. Copyright © 2017 Elsevier Ltd. All rights reserved.

Common 5S rRNA variants are likely to be accepted in many sequence contexts

Science.gov (United States)

Zhang, Zhengdong; D'Souza, Lisa M.; Lee, Youn-Hyung; Fox, George E.

2003-01-01

Over evolutionary time RNA sequences which are successfully fixed in a population are selected from among those that satisfy the structural and chemical requirements imposed by the function of the RNA. These sequences together comprise the structure space of the RNA. In principle, a comprehensive understanding of RNA structure and function would make it possible to enumerate which specific RNA sequences belong to a particular structure space and which do not. We are using bacterial 5S rRNA as a model system to attempt to identify principles that can be used to predict which sequences do or do not belong to the 5S rRNA structure space. One promising idea is the very intuitive notion that frequently seen sequence changes in an aligned data set of naturally occurring 5S rRNAs would be widely accepted in many other 5S rRNA sequence contexts. To test this hypothesis, we first developed well-defined operational definitions for a Vibrio region of the 5S rRNA structure space and what is meant by a highly variable position. Fourteen sequence variants (10 point changes and 4 base-pair changes) were identified in this way, which, by the hypothesis, would be expected to incorporate successfully in any of the known sequences in the Vibrio region. All 14 of these changes were constructed and separately introduced into the Vibrio proteolyticus 5S rRNA sequence where they are not normally found. Each variant was evaluated for its ability to function as a valid 5S rRNA in an E. coli cellular context. It was found that 93% (13/14) of the variants tested are likely valid 5S rRNAs in this context. In addition, seven variants were constructed that, although present in the Vibrio region, did not meet the stringent criteria for a highly variable position. In this case, 86% (6/7) are likely valid. As a control we also examined seven variants that are seldom or never seen in the Vibrio region of 5S rRNA sequence space. In this case only two of seven were found to be potentially valid. The

Finding the most significant common sequence and structure motifs in a set of RNA sequences

DEFF Research Database (Denmark)

Gorodkin, Jan; Heyer, L.J.; Stormo, G.D.

1997-01-01

We present a computational scheme to locally align a collection of RNA sequences using sequence and structure constraints, In addition, the method searches for the resulting alignments with the most significant common motifs, among all possible collections, The first part utilizes a simplified...

Evaluating Methods for Isolating Total RNA and Predicting the Success of Sequencing Phylogenetically Diverse Plant Transcriptomes

Science.gov (United States)

Bruskiewich, Richard; Burris, Jason N.; Carrigan, Charlotte T.; Chase, Mark W.; Clarke, Neil D.; Covshoff, Sarah; dePamphilis, Claude W.; Edger, Patrick P.; Goh, Falicia; Graham, Sean; Greiner, Stephan; Hibberd, Julian M.; Jordon-Thaden, Ingrid; Kutchan, Toni M.; Leebens-Mack, James; Melkonian, Michael; Miles, Nicholas; Myburg, Henrietta; Patterson, Jordan; Pires, J. Chris; Ralph, Paula; Rolf, Megan; Sage, Rowan F.; Soltis, Douglas; Soltis, Pamela; Stevenson, Dennis; Stewart, C. Neal; Surek, Barbara; Thomsen, Christina J. M.; Villarreal, Juan Carlos; Wu, Xiaolei; Zhang, Yong; Deyholos, Michael K.; Wong, Gane Ka-Shu

2012-01-01

Next-generation sequencing plays a central role in the characterization and quantification of transcriptomes. Although numerous metrics are purported to quantify the quality of RNA, there have been no large-scale empirical evaluations of the major determinants of sequencing success. We used a combination of existing and newly developed methods to isolate total RNA from 1115 samples from 695 plant species in 324 families, which represents >900 million years of phylogenetic diversity from green algae through flowering plants, including many plants of economic importance. We then sequenced 629 of these samples on Illumina GAIIx and HiSeq platforms and performed a large comparative analysis to identify predictors of RNA quality and the diversity of putative genes (scaffolds) expressed within samples. Tissue types (e.g., leaf vs. flower) varied in RNA quality, sequencing depth and the number of scaffolds. Tissue age also influenced RNA quality but not the number of scaffolds ≥1000 bp. Overall, 36% of the variation in the number of scaffolds was explained by metrics of RNA integrity (RIN score), RNA purity (OD 260/230), sequencing platform (GAIIx vs HiSeq) and the amount of total RNA used for sequencing. However, our results show that the most commonly used measures of RNA quality (e.g., RIN) are weak predictors of the number of scaffolds because Illumina sequencing is robust to variation in RNA quality. These results provide novel insight into the methods that are most important in isolating high quality RNA for sequencing and assembling plant transcriptomes. The methods and recommendations provided here could increase the efficiency and decrease the cost of RNA sequencing for individual labs and genome centers. PMID:23185583

Genetic architecture of vitamin B12 and folate levels uncovered applying deeply sequenced large datasets

DEFF Research Database (Denmark)

Grarup, Niels; Sulem, Patrick; Sandholt, Camilla H

2013-01-01

of the underlying biology of human traits and diseases. Here, we used a large Icelandic whole genome sequence dataset combined with Danish exome sequence data to gain insight into the genetic architecture of serum levels of vitamin B12 (B12) and folate. Up to 22.9 million sequence variants were analyzed in combined...... in serum B12 or folate levels do not modify the risk of developing these conditions. Yet, the study demonstrates the value of combining whole genome and exome sequencing approaches to ascertain the genetic and molecular architectures underlying quantitative trait associations....

Nucleotide sequence of tomato ringspot virus RNA-2.

Science.gov (United States)

Rott, M E; Tremaine, J H; Rochon, D M

1991-07-01

The sequence of tomato ringspot virus (TomRSV) RNA-2 has been determined. It is 7273 nucleotides in length excluding the 3' poly(A) tail and contains a single long open reading frame (ORF) of 5646 nucleotides in the positive sense beginning at position 78 and terminating at position 5723. A second in-frame AUG at position 441 is in a more favourable context for initiation of translation and may act as a site for initiation of translation. The TomRSV RNA-2 3' noncoding region is 1550 nucleotides in length. The coat protein is located in the C-terminal region of the large polypeptide and shows significant but limited amino acid sequence similarity to the putative coat proteins of the nepoviruses tomato black ring (TBRV), Hungarian grapevine chrome mosaic (GCMV) and grapevine fanleaf (GFLV). Comparisons of the coding and non-coding regions of TomRSV RNA-2 and the RNA components of TBRV, GCMV, GFLV and the comovirus cowpea mosaic virus revealed significant similarity for over 300 amino acids between the coding region immediately to the N-terminal side of the putative coat proteins of TomRSV and GFLV; very little similarity could be detected among the non-coding regions of TomRSV and any of these viruses.

Functional Advantages of Conserved Intrinsic Disorder in RNA-Binding Proteins

OpenAIRE

Varadi, Mihaly; Zsolyomi, Fruzsina; Guharoy, Mainak; Tompa, Peter

2015-01-01

Proteins form large macromolecular assemblies with RNA that govern essential molecular processes. RNA-binding proteins have often been associated with conformational flexibility, yet the extent and functional implications of their intrinsic disorder have never been fully assessed. Here, through large-scale analysis of comprehensive protein sequence and structure datasets we demonstrate the prevalence of intrinsic structural disorder in RNA-binding proteins and domains. We addressed their func...

Unusual loop-sequence flexibility of the proximal RNA replication element in EMCV.

Directory of Open Access Journals (Sweden)

Jan Zoll

Full Text Available Picornaviruses contain stable RNA structures at the 5' and 3' ends of the RNA genome, OriL and OriR involved in viral RNA replication. The OriL RNA element found at the 5' end of the enterovirus genome folds into a cloverleaf-like configuration. In vivo SELEX experiments revealed that functioning of the poliovirus cloverleaf depends on a specific structure in this RNA element. Little is known about the OriL of cardioviruses. Here, we investigated structural aspects and requirements of the apical loop of proximal stem-loop SL-A of mengovirus, a strain of EMCV. Using NMR spectroscopy, we showed that the mengovirus SL-A apical loop consists of an octaloop. In vivo SELEX experiments demonstrated that a large number of random sequences are tolerated in the apical octaloop that support virus replication. Mutants in which the SL-A loop size and the length of the upper part of the stem were varied showed that both stem-length and stability of the octaloop are important determinants for viral RNA replication and virus reproduction. Together, these data show that stem-loop A plays an important role in virus replication. The high degree of sequence flexibility and the lack of selective pressure on the octaloop argue against a role in sequence specific RNA-protein or RNA-RNA interactions in which octaloop nucleotides are involved.

Systems genetics of complex diseases using RNA-sequencing methods

DEFF Research Database (Denmark)

Mazzoni, Gianluca; Kogelman, Lisette; Suravajhala, Prashanth

2015-01-01

Next generation sequencing technologies have enabled the generation of huge quantities of biological data, and nowadays extensive datasets at different ‘omics levels have been generated. Systems genetics is a powerful approach that allows to integrate different ‘omics level and understand the bio...

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

Complete sequence of RNA1 of grapevine Anatolian ringspot virus.

Science.gov (United States)

Digiaro, Michele; Nahdi, Sabrine; Elbeaino, Toufic

2012-10-01

The nucleotide sequence of RNA1 of grapevine Anatolian ringspot virus (GARSV), a nepovirus of subgroup B, was determined from cDNA clones. It is 7,288 nucleotides in length excluding the 3' terminal poly(A) tail and contains a large open reading frame (ORF), extending from nucleotides 272 to 7001, encoding a polypeptide of 2,243 amino acids with a predicted molecular mass of 250 kDa. The primary structure of the polyprotein, compared with that of other viral polyproteins, revealed the presence of all the characteristic domains of members of the order Picornavirales, i.e., the NTP-binding protein (1B(Hel)), the viral genome-linked protein (1C(VPg)), the proteinase (1D(Prot)), the RNA-dependent RNA polymerase (1E(Pol)), and of the protease cofactor (1A(Pro-cof)) shared by members of the subfamily Comovirinae within the family Secoviridae. The cleavage sites predicted within the polyprotein were found to be in agreement with those previously reported for nepoviruses of subgroup B, processing from 1A to 1E proteins of 67, 64, 3, 23 and 92 kDa, respectively. The RNA1-encoded polyprotein (p1) shared the highest amino acid sequence identity (66 %) with tomato black ring virus (TBRV) and beet ringspot virus (BRSV). The 5'- and 3'-noncoding regions (NCRs) of GARSV-RNA1 shared 89 % and 95 % nucleotide sequence identity respectively with the corresponding regions in RNA2. Phylogenetic analysis confirmed the close relationship of GARSV to members of subgroup B of the genus Nepovirus.

High-Throughput Mapping of Single-Neuron Projections by Sequencing of Barcoded RNA.

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Kebschull, Justus M; Garcia da Silva, Pedro; Reid, Ashlan P; Peikon, Ian D; Albeanu, Dinu F; Zador, Anthony M

2016-09-07

Neurons transmit information to distant brain regions via long-range axonal projections. In the mouse, area-to-area connections have only been systematically mapped using bulk labeling techniques, which obscure the diverse projections of intermingled single neurons. Here we describe MAPseq (Multiplexed Analysis of Projections by Sequencing), a technique that can map the projections of thousands or even millions of single neurons by labeling large sets of neurons with random RNA sequences ("barcodes"). Axons are filled with barcode mRNA, each putative projection area is dissected, and the barcode mRNA is extracted and sequenced. Applying MAPseq to the locus coeruleus (LC), we find that individual LC neurons have preferred cortical targets. By recasting neuroanatomy, which is traditionally viewed as a problem of microscopy, as a problem of sequencing, MAPseq harnesses advances in sequencing technology to permit high-throughput interrogation of brain circuits. Copyright © 2016 Elsevier Inc. All rights reserved.

DCJ-RNA - double cut and join for RNA secondary structures.

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Badr, Ghada H; Al-Aqel, Haifa A

2017-10-16

Genome rearrangements are essential processes for evolution and are responsible for existing varieties of genome architectures. Many studies have been conducted to obtain an algorithm that identifies the minimum number of inversions that are necessary to transform one genome into another; this allows for genome sequence representation in polynomial time. Studies have not been conducted on the topic of rearranging a genome when it is represented as a secondary structure. Unlike sequences, the secondary structure preserves the functionality of the genome. Sequences can be different, but they all share the same structure and, therefore, the same functionality. This paper proposes a double cut and join for RNA secondary structures (DCJ-RNA) algorithm. This algorithm allows for the description of evolutionary scenarios that are based on secondary structures rather than sequences. The main aim of this paper is to suggest an efficient algorithm that can help researchers compare two ribonucleic acid (RNA) secondary structures based on rearrangement operations. The results, which are based on real datasets, show that the algorithm is able to count the minimum number of rearrangement operations, as well as to report an optimum scenario that can increase the similarity between the two structures. The algorithm calculates the distance between structures and reports a scenario based on the minimum rearrangement operations required to make the given structure similar to the other. DCJ-RNA can also be used to measure the distance between the two structures. This can help identify the common functionalities between different species.

High-Throughput Sequencing Based Methods of RNA Structure Investigation

DEFF Research Database (Denmark)

Kielpinski, Lukasz Jan

In this thesis we describe the development of four related methods for RNA structure probing that utilize massive parallel sequencing. Using them, we were able to gather structural data for multiple, long molecules simultaneously. First, we have established an easy to follow experimental...... and computational protocol for detecting the reverse transcription termination sites (RTTS-Seq). This protocol was subsequently applied to hydroxyl radical footprinting of three dimensional RNA structures to give a probing signal that correlates well with the RNA backbone solvent accessibility. Moreover, we applied...

OTU analysis using metagenomic shotgun sequencing data.

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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.

Sequencing of 16S rRNA gene for id ntification of Sta h lococcus ...

African Journals Online (AJOL)

Asdmin

2014-01-15

Jan 15, 2014 ... as the type strains of a species of genus Trichoderma based on phylogenetic tree analysis together with the 18S rRNA gene sequence search in Ribosomal Database Project, small subunit rRNA and large subunit rRNA databases. The sequence was deposited in GenBank with the accession numbers.

RNA2 of grapevine fanleaf virus: sequence analysis and coat protein cistron location.

Science.gov (United States)

Serghini, M A; Fuchs, M; Pinck, M; Reinbolt, J; Walter, B; Pinck, L

1990-07-01

The nucleotide sequence of the genomic RNA2 (3774 nucleotides) of grapevine fanleaf virus strain F13 was determined from overlapping cDNA clones and its genetic organization was deduced. Two rapid and efficient methods were used for cDNA cloning of the 5' region of RNA2. The complete sequence contained only one long open reading frame of 3555 nucleotides (1184 codons, 131K product). The analysis of the N-terminal sequence of purified coat protein (CP) and identification of its C-terminal residue have allowed the CP cistron to be precisely positioned within the polyprotein. The CP produced by proteolytic cleavage at the Arg/Gly site between residues 680 and 681 contains 504 amino acids (Mr 56019) and has hydrophobic properties. The Arg/Gly cleavage site deduced by N-terminal amino acid sequence analysis is the first for a nepovirus coat protein and for plant viruses expressing their genomic RNAs by polyprotein synthesis. Comparison of GFLV RNA2 with M RNA of cowpea mosaic comovirus and with RNA2 of two closely related nepoviruses, tomato black ring virus and Hungarian grapevine chrome mosaic virus, showed strong similarities among the 3' non-coding regions but less similarity among the 5' end non-coding sequences than reported among other nepovirus RNAs.

Inaugural Genomics Automation Congress and the coming deluge of sequencing data.

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Creighton, Chad J

2010-10-01

Presentations at Select Biosciences's first 'Genomics Automation Congress' (Boston, MA, USA) in 2010 focused on next-generation sequencing and the platforms and methodology around them. The meeting provided an overview of sequencing technologies, both new and emerging. Speakers shared their recent work on applying sequencing to profile cells for various levels of biomolecular complexity, including DNA sequences, DNA copy, DNA methylation, mRNA and microRNA. With sequencing time and costs continuing to drop dramatically, a virtual explosion of very large sequencing datasets is at hand, which will probably present challenges and opportunities for high-level data analysis and interpretation, as well as for information technology infrastructure.

Analysis of 16S rRNA amplicon sequencing options on the Roche/454 next-generation titanium sequencing platform.

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Hideyuki Tamaki

Full Text Available BACKGROUND: 16S rRNA gene pyrosequencing approach has revolutionized studies in microbial ecology. While primer selection and short read length can affect the resulting microbial community profile, little is known about the influence of pyrosequencing methods on the sequencing throughput and the outcome of microbial community analyses. The aim of this study is to compare differences in output, ease, and cost among three different amplicon pyrosequencing methods for the Roche/454 Titanium platform METHODOLOGY/PRINCIPAL FINDINGS: The following three pyrosequencing methods for 16S rRNA genes were selected in this study: Method-1 (standard method is the recommended method for bi-directional sequencing using the LIB-A kit; Method-2 is a new option designed in this study for unidirectional sequencing with the LIB-A kit; and Method-3 uses the LIB-L kit for unidirectional sequencing. In our comparison among these three methods using 10 different environmental samples, Method-2 and Method-3 produced 1.5-1.6 times more useable reads than the standard method (Method-1, after quality-based trimming, and did not compromise the outcome of microbial community analyses. Specifically, Method-3 is the most cost-effective unidirectional amplicon sequencing method as it provided the most reads and required the least effort in consumables management. CONCLUSIONS: Our findings clearly demonstrated that alternative pyrosequencing methods for 16S rRNA genes could drastically affect sequencing output (e.g. number of reads before and after trimming but have little effect on the outcomes of microbial community analysis. This finding is important for both researchers and sequencing facilities utilizing 16S rRNA gene pyrosequencing for microbial ecological studies.

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

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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

The RNA world, automatic sequences and oncogenetics

Energy Technology Data Exchange (ETDEWEB)

Tahir Shah, K

1993-04-01

We construct a model of the RNA world in terms of naturally evolving nucleotide sequences assuming only Crick-Watson base pairing and self-cleaving/splicing capability. These sequences have the following properties. (1) They are recognizable by an automation (or automata). That is, to each k-sequence, there exist a k-automation which accepts, recognizes or generates the k-sequence. These are known as automatic sequences. Fibonacci and Morse-Thue sequences are the most natural outcome of pre-biotic chemical conditions. (2) Infinite (resp. large) sequences are self-similar (resp. nearly self-similar) under certain rewrite rules and consequently give rise to fractal (resp.fractal-like) structures. Computationally, such sequences can also be generated by their corresponding deterministic parallel re-write system, known as a DOL system. The self-similar sequences are fixed points of their respective rewrite rules. Some of these automatic sequences have the capability that they can read or ``accept`` other sequences while others can detect errors and trigger error-correcting mechanisms. They can be enlarged and have block and/or palindrome structure. Linear recurring sequences such as Fibonacci sequence are simply Feed-back Shift Registers, a well know model of information processing machines. We show that a mutation of any rewrite rule can cause a combinatorial explosion of error and relates this to oncogenetical behavior. On the other hand, a mutation of sequences that are not rewrite rules, leads to normal evolutionary change. Known experimental results support our hypothesis. (author). Refs.

The RNA world, automatic sequences and oncogenetics

International Nuclear Information System (INIS)

Tahir Shah, K.

1993-04-01

We construct a model of the RNA world in terms of naturally evolving nucleotide sequences assuming only Crick-Watson base pairing and self-cleaving/splicing capability. These sequences have the following properties. 1) They are recognizable by an automation (or automata). That is, to each k-sequence, there exist a k-automation which accepts, recognizes or generates the k-sequence. These are known as automatic sequences. Fibonacci and Morse-Thue sequences are the most natural outcome of pre-biotic chemical conditions. 2) Infinite (resp. large) sequences are self-similar (resp. nearly self-similar) under certain rewrite rules and consequently give rise to fractal (resp.fractal-like) structures. Computationally, such sequences can also be generated by their corresponding deterministic parallel re-write system, known as a DOL system. The self-similar sequences are fixed points of their respective rewrite rules. Some of these automatic sequences have the capability that they can read or 'accept' other sequences while others can detect errors and trigger error-correcting mechanisms. They can be enlarged and have block and/or palindrome structure. Linear recurring sequences such as Fibonacci sequence are simply Feed-back Shift Registers, a well know model of information processing machines. We show that a mutation of any rewrite rule can cause a combinatorial explosion of error and relates this to oncogenetical behavior. On the other hand, a mutation of sequences that are not rewrite rules, leads to normal evolutionary change. Known experimental results support our hypothesis. (author). Refs

Small RNA Deep Sequencing and the Effects of microRNA408 on Root Gravitropic Bending in Arabidopsis

Science.gov (United States)

Li, Huasheng; Lu, Jinying; Sun, Qiao; Chen, Yu; He, Dacheng; Liu, Min

2015-11-01

MicroRNA (miRNA) is a non-coding small RNA composed of 20 to 24 nucleotides that influences plant root development. This study analyzed the miRNA expression in Arabidopsis root tip cells using Illumina sequencing and real-time PCR before (sample 0) and 15 min after (sample 15) a 3-D clinostat rotational treatment was administered. After stimulation was performed, the expression levels of seven miRNA genes, including Arabidopsis miR160, miR161, miR394, miR402, miR403, miR408, and miR823, were significantly upregulated. Illumina sequencing results also revealed two novel miRNAsthat have not been previously reported, The target genes of these miRNAs included pentatricopeptide repeat-containing protein and diadenosine tetraphosphate hydrolase. An overexpression vector of Arabidopsis miR408 was constructed and transferred to Arabidopsis plant. The roots of plants over expressing miR408 exhibited a slower reorientation upon gravistimulation in comparison with those of wild-type. This result indicate that miR408 could play a role in root gravitropic response.

Sequence analysis of L RNA of Lassa virus

International Nuclear Information System (INIS)

Vieth, Simon; Torda, Andrew E.; Asper, Marcel; Schmitz, Herbert; Guenther, Stephan

2004-01-01

The L RNA of three Lassa virus strains originating from Nigeria, Ghana/Ivory Coast, and Sierra Leone was sequenced and the data subjected to structure predictions and phylogenetic analyses. The L gene products had 2218-2221 residues, diverged by 18% at the amino acid level, and contained several conserved regions. Only one region of 504 residues (positions 1043-1546) could be assigned a function, namely that of an RNA polymerase. Secondary structure predictions suggest that this domain is very similar to RNA-dependent RNA polymerases of known structure encoded by plus-strand RNA viruses, permitting a model to be built. Outside the polymerase region, there is little structural data, except for regions of strong alpha-helical content and probably a coiled-coil domain at the N terminus. No evidence for reassortment or recombination during Lassa virus evolution was found. The secondary structure-assisted alignment of the RNA polymerase region permitted a reliable reconstruction of the phylogeny of all negative-strand RNA viruses, indicating that Arenaviridae are most closely related to Nairoviruses. In conclusion, the data provide a basis for structural and functional characterization of the Lassa virus L protein and reveal new insights into the phylogeny of negative-strand RNA viruses

Combined DECS Analysis and Next-Generation Sequencing Enable Efficient Detection of Novel Plant RNA Viruses

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Hironobu Yanagisawa

2016-03-01

Full Text Available The presence of high molecular weight double-stranded RNA (dsRNA within plant cells is an indicator of infection with RNA viruses as these possess genomic or replicative dsRNA. DECS (dsRNA isolation, exhaustive amplification, cloning, and sequencing analysis has been shown to be capable of detecting unknown viruses. We postulated that a combination of DECS analysis and next-generation sequencing (NGS would improve detection efficiency and usability of the technique. Here, we describe a model case in which we efficiently detected the presumed genome sequence of Blueberry shoestring virus (BSSV, a member of the genus Sobemovirus, which has not so far been reported. dsRNAs were isolated from BSSV-infected blueberry plants using the dsRNA-binding protein, reverse-transcribed, amplified, and sequenced using NGS. A contig of 4,020 nucleotides (nt that shared similarities with sequences from other Sobemovirus species was obtained as a candidate of the BSSV genomic sequence. Reverse transcription (RT-PCR primer sets based on sequences from this contig enabled the detection of BSSV in all BSSV-infected plants tested but not in healthy controls. A recombinant protein encoded by the putative coat protein gene was bound by the BSSV-antibody, indicating that the candidate sequence was that of BSSV itself. Our results suggest that a combination of DECS analysis and NGS, designated here as “DECS-C,” is a powerful method for detecting novel plant viruses.

Preparation of highly multiplexed small RNA sequencing libraries.

Science.gov (United States)

Persson, Helena; Søkilde, Rolf; Pirona, Anna Chiara; Rovira, Carlos

2017-08-01

MicroRNAs (miRNAs) are ~22-nucleotide-long small non-coding RNAs that regulate the expression of protein-coding genes by base pairing to partially complementary target sites, preferentially located in the 3´ untranslated region (UTR) of target mRNAs. The expression and function of miRNAs have been extensively studied in human disease, as well as the possibility of using these molecules as biomarkers for prognostication and treatment guidance. To identify and validate miRNAs as biomarkers, their expression must be screened in large collections of patient samples. Here, we develop a scalable protocol for the rapid and economical preparation of a large number of small RNA sequencing libraries using dual indexing for multiplexing. Combined with the use of off-the-shelf reagents, more samples can be sequenced simultaneously on large-scale sequencing platforms at a considerably lower cost per sample. Sample preparation is simplified by pooling libraries prior to gel purification, which allows for the selection of a narrow size range while minimizing sample variation. A comparison with publicly available data from benchmarking of miRNA analysis platforms showed that this method captures absolute and differential expression as effectively as commercially available alternatives.

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

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.

CREST--classification resources for environmental sequence tags.

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Anders Lanzén

Full Text Available Sequencing of taxonomic or phylogenetic markers is becoming a fast and efficient method for studying environmental microbial communities. This has resulted in a steadily growing collection of marker sequences, most notably of the small-subunit (SSU ribosomal RNA gene, and an increased understanding of microbial phylogeny, diversity and community composition patterns. However, to utilize these large datasets together with new sequencing technologies, a reliable and flexible system for taxonomic classification is critical. We developed CREST (Classification Resources for Environmental Sequence Tags, a set of resources and tools for generating and utilizing custom taxonomies and reference datasets for classification of environmental sequences. CREST uses an alignment-based classification method with the lowest common ancestor algorithm. It also uses explicit rank similarity criteria to reduce false positives and identify novel taxa. We implemented this method in a web server, a command line tool and the graphical user interfaced program MEGAN. Further, we provide the SSU rRNA reference database and taxonomy SilvaMod, derived from the publicly available SILVA SSURef, for classification of sequences from bacteria, archaea and eukaryotes. Using cross-validation and environmental datasets, we compared the performance of CREST and SilvaMod to the RDP Classifier. We also utilized Greengenes as a reference database, both with CREST and the RDP Classifier. These analyses indicate that CREST performs better than alignment-free methods with higher recall rate (sensitivity as well as precision, and with the ability to accurately identify most sequences from novel taxa. Classification using SilvaMod performed better than with Greengenes, particularly when applied to environmental sequences. CREST is freely available under a GNU General Public License (v3 from http://apps.cbu.uib.no/crest and http://lcaclassifier.googlecode.com.

Transcriptome Analysis of Ceriops tagal in Saline Environments Using RNA-Sequencing.

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Xiaorong Xiao

Full Text Available Identification of genes involved in mangrove species' adaptation to salt stress can provide valuable information for developing salt-tolerant crops and understanding the molecular evolution of salt tolerance in halophiles. Ceriops tagal is a salt-tolerant mangrove tree growing in mudflats and marshes in tropical and subtropical areas, without any prior genome information. In this study, we assessed the biochemical and transcriptional responses of C. tagal to high salt treatment (500 mmol/L NaCl by hydroponic experiments and RNA-seq. In C. tagal root tissues under salt stress, proline accumulated strongly from 3 to 12 h of treatment; meanwhile, malondialdehyde content progressively increased from 0 to 9 h, then dropped to lower than control levels by 24 h. These implied that C. tagal plants could survive salt stress through biochemical modification. Using the Illumina sequencing platform, approximately 27.39 million RNA-seq reads were obtained from three salt-treated and control (untreated root samples. These reads were assembled into 47,111 transcripts with an average length of 514 bp and an N50 of 632 bp. Approximately 78% of the transcripts were annotated, and a total of 437 genes were putative transcription factors. Digital gene expression analysis was conducted by comparing transcripts from the untreated control to the three salt treated samples, and 7,330 differentially expressed transcripts were identified. Using k-means clustering, these transcripts were divided into six clusters that differed in their expression patterns across four treatment time points. The genes identified as being up- or downregulated are involved in salt stress responses, signal transduction, and DNA repair. Our study shows the main adaptive pathway of C. tagal in saline environments, under short-term and long-term treatments of salt stress. This provides vital clues as to which genes may be candidates for breeding salt-tolerant crops and clarifying molecular

Single-Cell RNA Sequencing of Glioblastoma Cells.

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Sen, Rajeev; Dolgalev, Igor; Bayin, N Sumru; Heguy, Adriana; Tsirigos, Aris; Placantonakis, Dimitris G

2018-01-01

Single-cell RNA sequencing (sc-RNASeq) is a recently developed technique used to evaluate the transcriptome of individual cells. As opposed to conventional RNASeq in which entire populations are sequenced in bulk, sc-RNASeq can be beneficial when trying to better understand gene expression patterns in markedly heterogeneous populations of cells or when trying to identify transcriptional signatures of rare cells that may be underrepresented when using conventional bulk RNASeq. In this method, we describe the generation and analysis of cDNA libraries from single patient-derived glioblastoma cells using the C1 Fluidigm system. The protocol details the use of the C1 integrated fluidics circuit (IFC) for capturing, imaging and lysing cells; performing reverse transcription; and generating cDNA libraries that are ready for sequencing and analysis.

Reanalysis of RNA-sequencing data reveals several additional fusion genes with multiple isoforms.

Science.gov (United States)

Kangaspeska, Sara; Hultsch, Susanne; Edgren, Henrik; Nicorici, Daniel; Murumägi, Astrid; Kallioniemi, Olli

2012-01-01

RNA-sequencing and tailored bioinformatic methodologies have paved the way for identification of expressed fusion genes from the chaotic genomes of solid tumors. We have recently successfully exploited RNA-sequencing for the discovery of 24 novel fusion genes in breast cancer. Here, we demonstrate the importance of continuous optimization of the bioinformatic methodology for this purpose, and report the discovery and experimental validation of 13 additional fusion genes from the same samples. Integration of copy number profiling with the RNA-sequencing results revealed that the majority of the gene fusions were promoter-donating events that occurred at copy number transition points or involved high-level DNA-amplifications. Sequencing of genomic fusion break points confirmed that DNA-level rearrangements underlie selected fusion transcripts. Furthermore, a significant portion (>60%) of the fusion genes were alternatively spliced. This illustrates the importance of reanalyzing sequencing data as gene definitions change and bioinformatic methods improve, and highlights the previously unforeseen isoform diversity among fusion transcripts.

Reanalysis of RNA-sequencing data reveals several additional fusion genes with multiple isoforms.

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Sara Kangaspeska

Full Text Available RNA-sequencing and tailored bioinformatic methodologies have paved the way for identification of expressed fusion genes from the chaotic genomes of solid tumors. We have recently successfully exploited RNA-sequencing for the discovery of 24 novel fusion genes in breast cancer. Here, we demonstrate the importance of continuous optimization of the bioinformatic methodology for this purpose, and report the discovery and experimental validation of 13 additional fusion genes from the same samples. Integration of copy number profiling with the RNA-sequencing results revealed that the majority of the gene fusions were promoter-donating events that occurred at copy number transition points or involved high-level DNA-amplifications. Sequencing of genomic fusion break points confirmed that DNA-level rearrangements underlie selected fusion transcripts. Furthermore, a significant portion (>60% of the fusion genes were alternatively spliced. This illustrates the importance of reanalyzing sequencing data as gene definitions change and bioinformatic methods improve, and highlights the previously unforeseen isoform diversity among fusion transcripts.

Highly divergent 16S rRNA sequences in ribosomal operons of Scytonema hyalinum (Cyanobacteria.

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Jeffrey R Johansen

Full Text Available A highly divergent 16S rRNA gene was found in one of the five ribosomal operons present in a species complex currently circumscribed as Scytonema hyalinum (Nostocales, Cyanobacteria using clone libraries. If 16S rRNA sequence macroheterogeneity among ribosomal operons due to insertions, deletions or truncation is excluded, the sequence heterogeneity observed in S. hyalinum was the highest observed in any prokaryotic species thus far (7.3-9.0%. The secondary structure of the 16S rRNA molecules encoded by the two divergent operons was nearly identical, indicating possible functionality. The 23S rRNA gene was examined for a few strains in this complex, and it was also found to be highly divergent from the gene in Type 2 operons (8.7%, and likewise had nearly identical secondary structure between the Type 1 and Type 2 operons. Furthermore, the 16S-23S ITS showed marked differences consistent between operons among numerous strains. Both operons have promoter sequences that satisfy consensus requirements for functional prokaryotic transcription initiation. Horizontal gene transfer from another unknown heterocytous cyanobacterium is considered the most likely explanation for the origin of this molecule, but does not explain the ultimate origin of this sequence, which is very divergent from all 16S rRNA sequences found thus far in cyanobacteria. The divergent sequence is highly conserved among numerous strains of S. hyalinum, suggesting adaptive advantage and selective constraint of the divergent sequence.

Appendix: a solution hybridization assay to detect radioactive globin messenger RNA nucleotide sequences

Energy Technology Data Exchange (ETDEWEB)

Ross, J

1976-09-15

In view of the sensitivity and specificity of the solution hybridization assay for unlabeled globin mRNA a similar technique has been devised to detect radioactive globin mRNA sequences with unlabeled globin cDNA. Several properties of the hybridization reaction are presented since RNA kinetic experiments reported recently depend on the validity of this assay. Data on hybridization analysis of (/sup 3/H)RNA from mouse fetal liver or erythroleukemia cell cytoplasm are presented. These data indicate that the excess cDNA solution assay for radioactive globin mRNA detection is specific for globin mRNA sequences. It can be performed rapidly and is highly reproducible from experiment. It is at least 500-fold less sensitive than the assay for unlabeled globin mRNA, due to the RNAase backgrounds of 0.05 to 0.15 %. However, this limitation has not affected kinetic experiments with non-dividing fetal liver erythroid cells, which synthesize relatively large quantities of globin mRNA.

Cloning and sequencing of full-length cDNAs of RNA1 and RNA2 of a Tomato black ring virus isolate from Poland.

Science.gov (United States)

Jończyk, M; Le Gall, O; Pałucha, A; Borodynko, N; Pospieszny, H

2004-04-01

Full-length cDNA clones corresponding to the RNA1 and RNA2 of the Polish isolate MJ of Tomato black ring virus (TBRV, genus Nepovirus) were obtained using a direct recombination strategy in yeast, and their complete nucleotide sequences were established. RNA1 is 7358 nucleotides and RNA2 is 4633 nucleotides in length, excluding the poly(A) tails. Both RNAs contain a single open reading frame encoding polyproteins of 254 kDa and 149 kDa for RNA1 and RNA2 respectively. Putative cleavage sites were identified, and the relationships between TBRV and related nepoviruses were studied by sequence comparison.

A comprehensive comparison of comparative RNA structure prediction approaches

DEFF Research Database (Denmark)

Gardner, P. P.; Giegerich, R.

2004-01-01

-finding and multiple-sequence-alignment algorithms. Results Here we evaluate a number of RNA folding algorithms using reliable RNA data-sets and compare their relative performance. Conclusions We conclude that comparative data can enhance structure prediction but structure-prediction-algorithms vary widely in terms......Background An increasing number of researchers have released novel RNA structure analysis and prediction algorithms for comparative approaches to structure prediction. Yet, independent benchmarking of these algorithms is rarely performed as is now common practice for protein-folding, gene...

TSSer: an automated method to identify transcription start sites in prokaryotic genomes from differential RNA sequencing data.

Science.gov (United States)

Jorjani, Hadi; Zavolan, Mihaela

2014-04-01

Accurate identification of transcription start sites (TSSs) is an essential step in the analysis of transcription regulatory networks. In higher eukaryotes, the capped analysis of gene expression technology enabled comprehensive annotation of TSSs in genomes such as those of mice and humans. In bacteria, an equivalent approach, termed differential RNA sequencing (dRNA-seq), has recently been proposed, but the application of this approach to a large number of genomes is hindered by the paucity of computational analysis methods. With few exceptions, when the method has been used, annotation of TSSs has been largely done manually. In this work, we present a computational method called 'TSSer' that enables the automatic inference of TSSs from dRNA-seq data. The method rests on a probabilistic framework for identifying both genomic positions that are preferentially enriched in the dRNA-seq data as well as preferentially captured relative to neighboring genomic regions. Evaluating our approach for TSS calling on several publicly available datasets, we find that TSSer achieves high consistency with the curated lists of annotated TSSs, but identifies many additional TSSs. Therefore, TSSer can accelerate genome-wide identification of TSSs in bacterial genomes and can aid in further characterization of bacterial transcription regulatory networks. TSSer is freely available under GPL license at http://www.clipz.unibas.ch/TSSer/index.php

incaRNAfbinv: a web server for the fragment-based design of RNA sequences

Science.gov (United States)

Drory Retwitzer, Matan; Reinharz, Vladimir; Ponty, Yann; Waldispühl, Jérôme; Barash, Danny

2016-01-01

Abstract In recent years, new methods for computational RNA design have been developed and applied to various problems in synthetic biology and nanotechnology. Lately, there is considerable interest in incorporating essential biological information when solving the inverse RNA folding problem. Correspondingly, RNAfbinv aims at including biologically meaningful constraints and is the only program to-date that performs a fragment-based design of RNA sequences. In doing so it allows the design of sequences that do not necessarily exactly fold into the target, as long as the overall coarse-grained tree graph shape is preserved. Augmented by the weighted sampling algorithm of incaRNAtion, our web server called incaRNAfbinv implements the method devised in RNAfbinv and offers an interactive environment for the inverse folding of RNA using a fragment-based design approach. It takes as input: a target RNA secondary structure; optional sequence and motif constraints; optional target minimum free energy, neutrality and GC content. In addition to the design of synthetic regulatory sequences, it can be used as a pre-processing step for the detection of novel natural occurring RNAs. The two complementary methodologies RNAfbinv and incaRNAtion are merged together and fully implemented in our web server incaRNAfbinv, available at http://www.cs.bgu.ac.il/incaRNAfbinv. PMID:27185893

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

Thousands of primer-free, high-quality, full-length SSU rRNA sequences from all domains of life

DEFF Research Database (Denmark)

Karst, Soeren M; Dueholm, Morten S; McIlroy, Simon J

2016-01-01

Ribosomal RNA (rRNA) genes are the consensus marker for determination of microbial diversity on the planet, invaluable in studies of evolution and, for the past decade, high-throughput sequencing of variable regions of ribosomal RNA genes has become the backbone of most microbial ecology studies...... (SSU) rRNA genes and synthetic long read sequencing by molecular tagging, to generate primer-free, full-length SSU rRNA gene sequences from all domains of life, with a median raw error rate of 0.17%. We generated thousands of full-length SSU rRNA sequences from five well-studied ecosystems (soil, human...... gut, fresh water, anaerobic digestion, and activated sludge) and obtained sequences covering all domains of life and the majority of all described phyla. Interestingly, 30% of all bacterial operational taxonomic units were novel, compared to the SILVA database (less than 97% similarity...

RNA-DNA sequence differences spell genetic code ambiguities

DEFF Research Database (Denmark)

Bentin, Thomas; Nielsen, Michael L

2013-01-01

A recent paper in Science by Li et al. 2011(1) reports widespread sequence differences in the human transcriptome between RNAs and their encoding genes termed RNA-DNA differences (RDDs). The findings could add a new layer of complexity to gene expression but the study has been criticized. ...

The clinical value of lncRNA NEAT1 in digestive system malignancies: A comprehensive investigation based on 57 microarray and RNA-seq datasets.

Science.gov (United States)

Xiong, Dan-Dan; Feng, Zhen-Bo; Cen, Wei-Luan; Zeng, Jing-Jing; Liang, Lu; Tang, Rui-Xue; Gan, Xiao-Ning; Liang, Hai-Wei; Li, Zu-Yun; Chen, Gang; Luo, Dian-Zhong

2017-03-14

This comprehensive investigation was performed to evaluate the expression level and potential clinical value of NEAT1 in digestive system malignancies. A total of 57 lncRNA datasets of microarray or RNA-seq and 5 publications were included. The pooled standard mean deviation (SMD) indicated that NEAT1 was down-regulated in esophageal carcinoma (ESCA, SMD = -0.35, 95% CI: -0.5~-0.20, P digestive system malignancies (HR: 1.50, 95% CI: 1.28-1.76, P digestive system cancers and could be a potential diagnostic and prognostic biomarker in patients with digestive system carcinomas. Further and stricter studies with a larger number of cases are necessary to strengthen our conclusions.

Adenylylation of small RNA sequencing adapters using the TS2126 RNA ligase I.

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Lama, Lodoe; Ryan, Kevin

2016-01-01

Many high-throughput small RNA next-generation sequencing protocols use 5' preadenylylated DNA oligonucleotide adapters during cDNA library preparation. Preadenylylation of the DNA adapter's 5' end frees from ATP-dependence the ligation of the adapter to RNA collections, thereby avoiding ATP-dependent side reactions. However, preadenylylation of the DNA adapters can be costly and difficult. The currently available method for chemical adenylylation of DNA adapters is inefficient and uses techniques not typically practiced in laboratories profiling cellular RNA expression. An alternative enzymatic method using a commercial RNA ligase was recently introduced, but this enzyme works best as a stoichiometric adenylylating reagent rather than a catalyst and can therefore prove costly when several variant adapters are needed or during scale-up or high-throughput adenylylation procedures. Here, we describe a simple, scalable, and highly efficient method for the 5' adenylylation of DNA oligonucleotides using the thermostable RNA ligase 1 from bacteriophage TS2126. Adapters with 3' blocking groups are adenylylated at >95% yield at catalytic enzyme-to-adapter ratios and need not be gel purified before ligation to RNA acceptors. Experimental conditions are also reported that enable DNA adapters with free 3' ends to be 5' adenylylated at >90% efficiency. © 2015 Lama and Ryan; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

Interference by clustered regularly interspaced short palindromic repeat (CRISPR) RNA is governed by a seed sequence

NARCIS (Netherlands)

Semenova, E.V.; Jore, M.M.; Westra, E.R.; Oost, van der J.; Brouns, S.J.J.

2011-01-01

Prokaryotic clustered regularly interspaced short palindromic repeat (CRISPR)/Cas (CRISPR-associated sequences) systems provide adaptive immunity against viruses when a spacer sequence of small CRISPR RNA (crRNA) matches a protospacer sequence in the viral genome. Viruses that escape CRISPR/Cas

High-throughput sequencing of human plasma RNA by using thermostable group II intron reverse transcriptases

Science.gov (United States)

Qin, Yidan; Yao, Jun; Wu, Douglas C.; Nottingham, Ryan M.; Mohr, Sabine; Hunicke-Smith, Scott; Lambowitz, Alan M.

2016-01-01

Next-generation RNA-sequencing (RNA-seq) has revolutionized transcriptome profiling, gene expression analysis, and RNA-based diagnostics. Here, we developed a new RNA-seq method that exploits thermostable group II intron reverse transcriptases (TGIRTs) and used it to profile human plasma RNAs. TGIRTs have higher thermostability, processivity, and fidelity than conventional reverse transcriptases, plus a novel template-switching activity that can efficiently attach RNA-seq adapters to target RNA sequences without RNA ligation. The new TGIRT-seq method enabled construction of RNA-seq libraries from RNA in RNA in 1-mL plasma samples from a healthy individual revealed RNA fragments mapping to a diverse population of protein-coding gene and long ncRNAs, which are enriched in intron and antisense sequences, as well as nearly all known classes of small ncRNAs, some of which have never before been seen in plasma. Surprisingly, many of the small ncRNA species were present as full-length transcripts, suggesting that they are protected from plasma RNases in ribonucleoprotein (RNP) complexes and/or exosomes. This TGIRT-seq method is readily adaptable for profiling of whole-cell, exosomal, and miRNAs, and for related procedures, such as HITS-CLIP and ribosome profiling. PMID:26554030

Evaluating Quality of Aged Archival Formalin-Fixed Paraffin-Embedded Samples for RNA-Sequencing

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Archival formalin-fixed paraffin-embedded (FFPE) samples offer a vast, untapped source of genomic data for biomarker discovery. However, the quality of FFPE samples is often highly variable, and conventional methods to assess RNA quality for RNA-sequencing (RNA-seq) are not infor...

Quantum Point Contact Single-Nucleotide Conductance for DNA and RNA Sequence Identification.

Science.gov (United States)

Afsari, Sepideh; Korshoj, Lee E; Abel, Gary R; Khan, Sajida; Chatterjee, Anushree; Nagpal, Prashant

2017-11-28

Several nanoscale electronic methods have been proposed for high-throughput single-molecule nucleic acid sequence identification. While many studies display a large ensemble of measurements as "electronic fingerprints" with some promise for distinguishing the DNA and RNA nucleobases (adenine, guanine, cytosine, thymine, and uracil), important metrics such as accuracy and confidence of base calling fall well below the current genomic methods. Issues such as unreliable metal-molecule junction formation, variation of nucleotide conformations, insufficient differences between the molecular orbitals responsible for single-nucleotide conduction, and lack of rigorous base calling algorithms lead to overlapping nanoelectronic measurements and poor nucleotide discrimination, especially at low coverage on single molecules. Here, we demonstrate a technique for reproducible conductance measurements on conformation-constrained single nucleotides and an advanced algorithmic approach for distinguishing the nucleobases. Our quantum point contact single-nucleotide conductance sequencing (QPICS) method uses combed and electrostatically bound single DNA and RNA nucleotides on a self-assembled monolayer of cysteamine molecules. We demonstrate that by varying the applied bias and pH conditions, molecular conductance can be switched ON and OFF, leading to reversible nucleotide perturbation for electronic recognition (NPER). We utilize NPER as a method to achieve >99.7% accuracy for DNA and RNA base calling at low molecular coverage (∼12×) using unbiased single measurements on DNA/RNA nucleotides, which represents a significant advance compared to existing sequencing methods. These results demonstrate the potential for utilizing simple surface modifications and existing biochemical moieties in individual nucleobases for a reliable, direct, single-molecule, nanoelectronic DNA and RNA nucleotide identification method for sequencing.

An efficient annotation and gene-expression derivation tool for Illumina Solexa datasets.

Science.gov (United States)

Hosseini, Parsa; Tremblay, Arianne; Matthews, Benjamin F; Alkharouf, Nadim W

2010-07-02

The data produced by an Illumina flow cell with all eight lanes occupied, produces well over a terabyte worth of images with gigabytes of reads following sequence alignment. The ability to translate such reads into meaningful annotation is therefore of great concern and importance. Very easily, one can get flooded with such a great volume of textual, unannotated data irrespective of read quality or size. CASAVA, a optional analysis tool for Illumina sequencing experiments, enables the ability to understand INDEL detection, SNP information, and allele calling. To not only extract from such analysis, a measure of gene expression in the form of tag-counts, but furthermore to annotate such reads is therefore of significant value. We developed TASE (Tag counting and Analysis of Solexa Experiments), a rapid tag-counting and annotation software tool specifically designed for Illumina CASAVA sequencing datasets. Developed in Java and deployed using jTDS JDBC driver and a SQL Server backend, TASE provides an extremely fast means of calculating gene expression through tag-counts while annotating sequenced reads with the gene's presumed function, from any given CASAVA-build. Such a build is generated for both DNA and RNA sequencing. Analysis is broken into two distinct components: DNA sequence or read concatenation, followed by tag-counting and annotation. The end result produces output containing the homology-based functional annotation and respective gene expression measure signifying how many times sequenced reads were found within the genomic ranges of functional annotations. TASE is a powerful tool to facilitate the process of annotating a given Illumina Solexa sequencing dataset. Our results indicate that both homology-based annotation and tag-count analysis are achieved in very efficient times, providing researchers to delve deep in a given CASAVA-build and maximize information extraction from a sequencing dataset. TASE is specially designed to translate sequence data

RNA-Seq of Bacillus licheniformis: active regulatory RNA features expressed within a productive fermentation

Science.gov (United States)

2013-01-01

Background The production of enzymes by an industrial strain requires a complex adaption of the bacterial metabolism to the conditions within the fermenter. Regulatory events within the process result in a dynamic change of the transcriptional activity of the genome. This complex network of genes is orchestrated by proteins as well as regulatory RNA elements. Here we present an RNA-Seq based study considering selected phases of an industry-oriented fermentation of Bacillus licheniformis. Results A detailed analysis of 20 strand-specific RNA-Seq datasets revealed a multitude of transcriptionally active genomic regions. 3314 RNA features encoded by such active loci have been identified and sorted into ten functional classes. The identified sequences include the expected RNA features like housekeeping sRNAs, metabolic riboswitches and RNA switches well known from studies on Bacillus subtilis as well as a multitude of completely new candidates for regulatory RNAs. An unexpectedly high number of 855 RNA features are encoded antisense to annotated protein and RNA genes, in addition to 461 independently transcribed small RNAs. These antisense transcripts contain molecules with a remarkable size range variation from 38 to 6348 base pairs in length. The genome of the type strain B. licheniformis DSM13 was completely reannotated using data obtained from RNA-Seq analyses and from public databases. Conclusion The hereby generated data-sets represent a solid amount of knowledge on the dynamic transcriptional activities during the investigated fermentation stages. The identified regulatory elements enable research on the understanding and the optimization of crucial metabolic activities during a productive fermentation of Bacillus licheniformis strains. PMID:24079885

RNA-Seq of Bacillus licheniformis: active regulatory RNA features expressed within a productive fermentation.

Science.gov (United States)

Wiegand, Sandra; Dietrich, Sascha; Hertel, Robert; Bongaerts, Johannes; Evers, Stefan; Volland, Sonja; Daniel, Rolf; Liesegang, Heiko

2013-10-01

The production of enzymes by an industrial strain requires a complex adaption of the bacterial metabolism to the conditions within the fermenter. Regulatory events within the process result in a dynamic change of the transcriptional activity of the genome. This complex network of genes is orchestrated by proteins as well as regulatory RNA elements. Here we present an RNA-Seq based study considering selected phases of an industry-oriented fermentation of Bacillus licheniformis. A detailed analysis of 20 strand-specific RNA-Seq datasets revealed a multitude of transcriptionally active genomic regions. 3314 RNA features encoded by such active loci have been identified and sorted into ten functional classes. The identified sequences include the expected RNA features like housekeeping sRNAs, metabolic riboswitches and RNA switches well known from studies on Bacillus subtilis as well as a multitude of completely new candidates for regulatory RNAs. An unexpectedly high number of 855 RNA features are encoded antisense to annotated protein and RNA genes, in addition to 461 independently transcribed small RNAs. These antisense transcripts contain molecules with a remarkable size range variation from 38 to 6348 base pairs in length. The genome of the type strain B. licheniformis DSM13 was completely reannotated using data obtained from RNA-Seq analyses and from public databases. The hereby generated data-sets represent a solid amount of knowledge on the dynamic transcriptional activities during the investigated fermentation stages. The identified regulatory elements enable research on the understanding and the optimization of crucial metabolic activities during a productive fermentation of Bacillus licheniformis strains.

16S ribosomal RNA sequence analysis for determination of phylogenetic relationship among methylotrophs.

Science.gov (United States)

Tsuji, K; Tsien, H C; Hanson, R S; DePalma, S R; Scholtz, R; LaRoche, S

1990-01-01

16S ribosomal RNAs (rRNA) of 12 methylotrophic bacteria have been almost completely sequenced to establish their phylogenetic relationships. Methylotrophs that are physiologically related are phylogenetically diverse and are scattered among the purple eubacteria (class Proteobacteria). Group I methylotrophs can be classified in the beta- and the gamma-subdivisions and group II methylotrophs in the alpha-subdivision of the purple eubacteria, respectively. Pink-pigmented facultative and non-pigmented obligate group II methylotrophs form two distinctly separate branches within the alpha-subdivision. The secondary structures of the 16S rRNA sequences of 'Methylocystis parvus' strain OBBP, 'Methylosinus trichosporium' strain OB3b, 'Methylosporovibrio methanica' strain 81Z and Hyphomicrobium sp. strain DM2 are similar, and these non-pigmented obligate group II methylotrophs form one tight cluster in the alpha-subdivision. The pink-pigmented facultative methylotrophs, Methylobacterium extorquens strain AM1, Methylobacterium sp. strain DM4 and Methylobacterium organophilum strain XX form another cluster within the alpha-subdivision. Although similar in phenotypic characteristics, Methylobacterium organophilum strain XX and Methylobacterium extorquens strain AM1 are clearly distinguishable by their 16S rRNA sequences. The group I methylotrophs, Methylophilus methylotrophus strain AS1 and methylotrophic species DM11, which do not utilize methane, are similar in 16S rRNA sequence to bacteria in the beta-subdivision. The methane-utilizing, obligate group I methanotrophs, Methylococcus capsulatus strain BATH and Methylomonas methanica, are placed in the gamma-subdivision. The results demonstrate that it is possible to distinguish and classify the methylotrophic bacteria using 16S rRNA sequence analysis.

Small RNA sequencing reveals metastasis-related microRNAs in lung adenocarcinoma

DEFF Research Database (Denmark)

Daugaard, Iben; Venø, Morten T.; Yan, Yan

2017-01-01

The majority of lung cancer deaths are caused by metastatic disease. MicroRNAs (miRNAs) are posttranscriptional regulators of gene expression and miRNA dysregulation can contribute to metastatic progression. Here, small RNA sequencing was used to profile the miRNA and piwi-interacting RNA (piRNA......) transcriptomes in relation to lung cancer metastasis. RNA-seq was performed using RNA extracted from formalin-fixed paraffin embedded (FFPE) lung adenocarcinomas (LAC) and brain metastases from 8 patients, and LACs from 8 patients without detectable metastatic disease. Impact on miRNA and piRNA transcriptomes...... was subtle with 9 miRNAs and 8 piRNAs demonstrating differential expression between metastasizing and non-metastasizing LACs. For piRNAs, decreased expression of piR-57125 was the most significantly associated with distant metastasis. Validation by RT-qPCR in a LAC cohort comprising 52 patients confirmed...

Efficient construction of an inverted minimal H1 promoter driven siRNA expression cassette: facilitation of promoter and siRNA sequence exchange.

Directory of Open Access Journals (Sweden)

Hoorig Nassanian

2007-08-01

Full Text Available RNA interference (RNAi, mediated by small interfering RNA (siRNA, is an effective method used to silence gene expression at the post-transcriptional level. Upon introduction into target cells, siRNAs incorporate into the RNA-induced silencing complex (RISC. The antisense strand of the siRNA duplex then "guides" the RISC to the homologous mRNA, leading to target degradation and gene silencing. In recent years, various vector-based siRNA expression systems have been developed which utilize opposing polymerase III promoters to independently drive expression of the sense and antisense strands of the siRNA duplex from the same template.We show here the use of a ligase chain reaction (LCR to develop a new vector system called pInv-H1 in which a DNA sequence encoding a specific siRNA is placed between two inverted minimal human H1 promoters (approximately 100 bp each. Expression of functional siRNAs from this construct has led to efficient silencing of both reporter and endogenous genes. Furthermore, the inverted H1 promoter-siRNA expression cassette was used to generate a retrovirus vector capable of transducing and silencing expression of the targeted protein by>80% in target cells.The unique design of this construct allows for the efficient exchange of siRNA sequences by the directional cloning of short oligonucleotides via asymmetric restriction sites. This provides a convenient way to test the functionality of different siRNA sequences. Delivery of the siRNA cassette by retroviral transduction suggests that a single copy of the siRNA expression cassette efficiently knocks down gene expression at the protein level. We note that this vector system can potentially be used to generate a random siRNA library. The flexibility of the ligase chain reaction suggests that additional control elements can easily be introduced into this siRNA expression cassette.

Using small RNA (sRNA) deep sequencing to understand global virus distribution in plants

Science.gov (United States)

Small RNAs (sRNAs), a class of regulatory RNAs, have been used to serve as the specificity determinants of suppressing gene expression in plants and animals. Next generation sequencing (NGS) uncovered the sRNA landscape in most organisms including their associated microbes. In the current study, w...

Intracellular diversity of the V4 and V9 regions of the 18S rRNA in marine protists (radiolarians) assessed by high-throughput sequencing.

Science.gov (United States)

Decelle, Johan; Romac, Sarah; Sasaki, Eriko; Not, Fabrice; Mahé, Frédéric

2014-01-01

Metabarcoding is a powerful tool for exploring microbial diversity in the environment, but its accurate interpretation is impeded by diverse technical (e.g. PCR and sequencing errors) and biological biases (e.g. intra-individual polymorphism) that remain poorly understood. To help interpret environmental metabarcoding datasets, we investigated the intracellular diversity of the V4 and V9 regions of the 18S rRNA gene from Acantharia and Nassellaria (radiolarians) using 454 pyrosequencing. Individual cells of radiolarians were isolated, and PCRs were performed with generalist primers to amplify the V4 and V9 regions. Different denoising procedures were employed to filter the pyrosequenced raw amplicons (Acacia, AmpliconNoise, Linkage method). For each of the six isolated cells, an average of 541 V4 and 562 V9 amplicons assigned to radiolarians were obtained, from which one numerically dominant sequence and several minor variants were found. At the 97% identity, a diversity metrics commonly used in environmental surveys, up to 5 distinct OTUs were detected in a single cell. However, most amplicons grouped within a single OTU whereas other OTUs contained very few amplicons. Different analytical methods provided evidence that most minor variants forming different OTUs correspond to PCR and sequencing artifacts. Duplicate PCR and sequencing from the same DNA extract of a single cell had only 9 to 16% of unique amplicons in common, and alignment visualization of V4 and V9 amplicons showed that most minor variants contained substitutions in highly-conserved regions. We conclude that intracellular variability of the 18S rRNA in radiolarians is very limited despite its multi-copy nature and the existence of multiple nuclei in these protists. Our study recommends some technical guidelines to conservatively discard artificial amplicons from metabarcoding datasets, and thus properly assess the diversity and richness of protists in the environment.

On the optimal trimming of high-throughput mRNA sequence data

Directory of Open Access Journals (Sweden)

Matthew D MacManes

2014-01-01

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

A DNA sequence obtained by replacement of the dopamine RNA aptamer bases is not an aptamer.

Science.gov (United States)

Álvarez-Martos, Isabel; Ferapontova, Elena E

2017-08-05

A unique specificity of the aptamer-ligand biorecognition and binding facilitates bioanalysis and biosensor development, contributing to discrimination of structurally related molecules, such as dopamine and other catecholamine neurotransmitters. The aptamer sequence capable of specific binding of dopamine is a 57 nucleotides long RNA sequence reported in 1997 (Biochemistry, 1997, 36, 9726). Later, it was suggested that the DNA homologue of the RNA aptamer retains the specificity of dopamine binding (Biochem. Biophys. Res. Commun., 2009, 388, 732). Here, we show that the DNA sequence obtained by the replacement of the RNA aptamer bases for their DNA analogues is not able of specific biorecognition of dopamine, in contrast to the original RNA aptamer sequence. This DNA sequence binds dopamine and structurally related catecholamine neurotransmitters non-specifically, as any DNA sequence, and, thus, is not an aptamer and cannot be used neither for in vivo nor in situ analysis of dopamine in the presence of structurally related neurotransmitters. Copyright © 2017 Elsevier Inc. All rights reserved.

Improved annotation of 3' untranslated regions and complex loci by combination of strand-specific direct RNA sequencing, RNA-Seq and ESTs.

Directory of Open Access Journals (Sweden)

Nicholas J Schurch

Full Text Available The reference annotations made for a genome sequence provide the framework for all subsequent analyses of the genome. Correct and complete annotation in addition to the underlying genomic sequence is particularly important when interpreting the results of RNA-seq experiments where short sequence reads are mapped against the genome and assigned to genes according to the annotation. Inconsistencies in annotations between the reference and the experimental system can lead to incorrect interpretation of the effect on RNA expression of an experimental treatment or mutation in the system under study. Until recently, the genome-wide annotation of 3' untranslated regions received less attention than coding regions and the delineation of intron/exon boundaries. In this paper, data produced for samples in Human, Chicken and A. thaliana by the novel single-molecule, strand-specific, Direct RNA Sequencing technology from Helicos Biosciences which locates 3' polyadenylation sites to within +/- 2 nt, were combined with archival EST and RNA-Seq data. Nine examples are illustrated where this combination of data allowed: (1 gene and 3' UTR re-annotation (including extension of one 3' UTR by 5.9 kb; (2 disentangling of gene expression in complex regions; (3 clearer interpretation of small RNA expression and (4 identification of novel genes. While the specific examples displayed here may become obsolete as genome sequences and their annotations are refined, the principles laid out in this paper will be of general use both to those annotating genomes and those seeking to interpret existing publically available annotations in the context of their own experimental data.

Genetic selection and DNA sequences of 4.5S RNA homologs

DEFF Research Database (Denmark)

Brown, S; Thon, G; Tolentino, E

1989-01-01

A general strategy for cloning the functional homologs of an Escherichia coli gene was used to clone homologs of 4.5S RNA from other bacteria. The genes encoding these homologs were selected by their ability to complement a deletion of the gene for 4.5S RNA. DNA sequences of the regions encoding...

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

Science.gov (United States)

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

2017-04-15

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

Beta-Poisson model for single-cell RNA-seq data analyses.

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Vu, Trung Nghia; Wills, Quin F; Kalari, Krishna R; Niu, Nifang; Wang, Liewei; Rantalainen, Mattias; Pawitan, Yudi

2016-07-15

Single-cell RNA-sequencing technology allows detection of gene expression at the single-cell level. One typical feature of the data is a bimodality in the cellular distribution even for highly expressed genes, primarily caused by a proportion of non-expressing cells. The standard and the over-dispersed gamma-Poisson models that are commonly used in bulk-cell RNA-sequencing are not able to capture this property. We introduce a beta-Poisson mixture model that can capture the bimodality of the single-cell gene expression distribution. We further integrate the model into the generalized linear model framework in order to perform differential expression analyses. The whole analytical procedure is called BPSC. The results from several real single-cell RNA-seq datasets indicate that ∼90% of the transcripts are well characterized by the beta-Poisson model; the model-fit from BPSC is better than the fit of the standard gamma-Poisson model in > 80% of the transcripts. Moreover, in differential expression analyses of simulated and real datasets, BPSC performs well against edgeR, a conventional method widely used in bulk-cell RNA-sequencing data, and against scde and MAST, two recent methods specifically designed for single-cell RNA-seq data. An R package BPSC for model fitting and differential expression analyses of single-cell RNA-seq data is available under GPL-3 license at https://github.com/nghiavtr/BPSC CONTACT: yudi.pawitan@ki.se or mattias.rantalainen@ki.se Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

The role of upstream sequences in selecting the reading frame on tmRNA

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Dewey Jonathan D

2008-06-01

Full Text Available Abstract Background tmRNA acts first as a tRNA and then as an mRNA to rescue stalled ribosomes in eubacteria. Two unanswered questions about tmRNA function remain: how does tmRNA, lacking an anticodon, bypass the decoding machinery and enter the ribosome? Secondly, how does the ribosome choose the proper codon to resume translation on tmRNA? According to the -1 triplet hypothesis, the answer to both questions lies in the unique properties of the three nucleotides upstream of the first tmRNA codon. These nucleotides assume an A-form conformation that mimics the codon-anticodon interaction, leading to recognition by the decoding center and choice of the reading frame. The -1 triplet hypothesis is important because it is the most credible model in which direct binding and recognition by the ribosome sets the reading frame on tmRNA. Results Conformational analysis predicts that 18 triplets cannot form the correct structure to function as the -1 triplet of tmRNA. We tested the tmRNA activity of all possible -1 triplet mutants using a genetic assay in Escherichia coli. While many mutants displayed reduced activity, our findings do not match the predictions of this model. Additional mutagenesis identified sequences further upstream that are required for tmRNA function. An immunoblot assay for translation of the tmRNA tag revealed that certain mutations in U85, A86, and the -1 triplet sequence result in improper selection of the first codon and translation in the wrong frame (-1 or +1 in vivo. Conclusion Our findings disprove the -1 triplet hypothesis. The -1 triplet is not required for accommodation of tmRNA into the ribosome, although it plays a minor role in frame selection. Our results strongly disfavor direct ribosomal recognition of the upstream sequence, instead supporting a model in which the binding of a separate ligand to A86 is primarily responsible for frame selection.

StarScan: a web server for scanning small RNA targets from degradome sequencing data.

Science.gov (United States)

Liu, Shun; Li, Jun-Hao; Wu, Jie; Zhou, Ke-Ren; Zhou, Hui; Yang, Jian-Hua; Qu, Liang-Hu

2015-07-01

Endogenous small non-coding RNAs (sRNAs), including microRNAs, PIWI-interacting RNAs and small interfering RNAs, play important gene regulatory roles in animals and plants by pairing to the protein-coding and non-coding transcripts. However, computationally assigning these various sRNAs to their regulatory target genes remains technically challenging. Recently, a high-throughput degradome sequencing method was applied to identify biologically relevant sRNA cleavage sites. In this study, an integrated web-based tool, StarScan (sRNA target Scan), was developed for scanning sRNA targets using degradome sequencing data from 20 species. Given a sRNA sequence from plants or animals, our web server performs an ultrafast and exhaustive search for potential sRNA-target interactions in annotated and unannotated genomic regions. The interactions between small RNAs and target transcripts were further evaluated using a novel tool, alignScore. A novel tool, degradomeBinomTest, was developed to quantify the abundance of degradome fragments located at the 9-11th nucleotide from the sRNA 5' end. This is the first web server for discovering potential sRNA-mediated RNA cleavage events in plants and animals, which affords mechanistic insights into the regulatory roles of sRNAs. The StarScan web server is available at http://mirlab.sysu.edu.cn/starscan/. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

The nucleotide sequence of satellite RNA in grapevine fanleaf virus, strain F13.

Science.gov (United States)

Fuchs, M; Pinck, M; Serghini, M A; Ravelonandro, M; Walter, B; Pinck, L

1989-04-01

The nucleotide sequence of cDNA copies of grapevine fanleaf virus (strain F13) satellite RNA has been determined. The primary structure obtained was 1114 nucleotides in length, excluding the poly(A) tail, and contained only one long open reading frame encoding a 341 residue, highly hydrophilic polypeptide of Mr37275. The coding sequence was bordered by a leader of 14 nucleotides and a 3'-terminal non-coding region of 74 nucleotides. No homology has been found with small satellite RNAs associated with other nepoviruses. Two limited homologies of eight nucleotides have been detected between the satellite RNA in grapevine fanleaf virus and those in tomato black ring virus, and a consensus sequence U.G/UGAAAAU/AU/AU/A at the 5' end of nepovirus RNAs is reported. A less extended consensus exists in this region in comovirus and picornavirus RNA.

Single-cell mRNA cytometry via sequence-specific nanoparticle clustering and trapping

Science.gov (United States)

Labib, Mahmoud; Mohamadi, Reza M.; Poudineh, Mahla; Ahmed, Sharif U.; Ivanov, Ivaylo; Huang, Ching-Lung; Moosavi, Maral; Sargent, Edward H.; Kelley, Shana O.

2018-05-01

Cell-to-cell variation in gene expression creates a need for techniques that can characterize expression at the level of individual cells. This is particularly true for rare circulating tumour cells, in which subtyping and drug resistance are of intense interest. Here we describe a method for cell analysis—single-cell mRNA cytometry—that enables the isolation of rare cells from whole blood as a function of target mRNA sequences. This approach uses two classes of magnetic particles that are labelled to selectively hybridize with different regions of the target mRNA. Hybridization leads to the formation of large magnetic clusters that remain localized within the cells of interest, thereby enabling the cells to be magnetically separated. Targeting specific intracellular mRNAs enablescirculating tumour cells to be distinguished from normal haematopoietic cells. No polymerase chain reaction amplification is required to determine RNA expression levels and genotype at the single-cell level, and minimal cell manipulation is required. To demonstrate this approach we use single-cell mRNA cytometry to detect clinically important sequences in prostate cancer specimens.

Survey of the transcriptome of Aspergillus oryzae via massively parallel mRNA sequencing

OpenAIRE

Wang, Bin; Guo, Guangwu; Wang, Chao; Lin, Ying; Wang, Xiaoning; Zhao, Mouming; Guo, Yong; He, Minghui; Zhang, Yong; Pan, Li

2010-01-01

Aspergillus oryzae, an important filamentous fungus used in food fermentation and the enzyme industry, has been shown through genome sequencing and various other tools to have prominent features in its genomic composition. However, the functional complexity of the A. oryzae transcriptome has not yet been fully elucidated. Here, we applied direct high-throughput paired-end RNA-sequencing (RNA-Seq) to the transcriptome of A. oryzae under four different culture conditions. With the high resoluti...

Computational sequence analysis of predicted long dsRNA transcriptomes of major crops reveals sequence complementarity with human genes.

Science.gov (United States)

Jensen, Peter D; Zhang, Yuanji; Wiggins, B Elizabeth; Petrick, Jay S; Zhu, Jin; Kerstetter, Randall A; Heck, Gregory R; Ivashuta, Sergey I

2013-01-01

Long double-stranded RNAs (long dsRNAs) are precursors for the effector molecules of sequence-specific RNA-based gene silencing in eukaryotes. Plant cells can contain numerous endogenous long dsRNAs. This study demonstrates that such endogenous long dsRNAs in plants have sequence complementarity to human genes. Many of these complementary long dsRNAs have perfect sequence complementarity of at least 21 nucleotides to human genes; enough complementarity to potentially trigger gene silencing in targeted human cells if delivered in functional form. However, the number and diversity of long dsRNA molecules in plant tissue from crops such as lettuce, tomato, corn, soy and rice with complementarity to human genes that have a long history of safe consumption supports a conclusion that long dsRNAs do not present a significant dietary risk.

Improving model predictions for RNA interference activities that use support vector machine regression by combining and filtering features

Directory of Open Access Journals (Sweden)

Peek Andrew S

2007-06-01

Full Text Available Abstract Background RNA interference (RNAi is a naturally occurring phenomenon that results in the suppression of a target RNA sequence utilizing a variety of possible methods and pathways. To dissect the factors that result in effective siRNA sequences a regression kernel Support Vector Machine (SVM approach was used to quantitatively model RNA interference activities. Results Eight overall feature mapping methods were compared in their abilities to build SVM regression models that predict published siRNA activities. The primary factors in predictive SVM models are position specific nucleotide compositions. The secondary factors are position independent sequence motifs (N-grams and guide strand to passenger strand sequence thermodynamics. Finally, the factors that are least contributory but are still predictive of efficacy are measures of intramolecular guide strand secondary structure and target strand secondary structure. Of these, the site of the 5' most base of the guide strand is the most informative. Conclusion The capacity of specific feature mapping methods and their ability to build predictive models of RNAi activity suggests a relative biological importance of these features. Some feature mapping methods are more informative in building predictive models and overall t-test filtering provides a method to remove some noisy features or make comparisons among datasets. Together, these features can yield predictive SVM regression models with increased predictive accuracy between predicted and observed activities both within datasets by cross validation, and between independently collected RNAi activity datasets. Feature filtering to remove features should be approached carefully in that it is possible to reduce feature set size without substantially reducing predictive models, but the features retained in the candidate models become increasingly distinct. Software to perform feature prediction and SVM training and testing on nucleic acid

The nucleotide sequence of 5S ribosomal RNA from Micrococcus lysodeikticus.

Science.gov (United States)

Hori, H; Osawa, S; Murao, K; Ishikura, H

1980-01-01

The nucleotide sequence of ribosomal 5S RNA from Micrococcus lysodeikticus is pGUUACGGCGGCUAUAGCGUGGGGGAAACGCCCGGCCGUAUAUCGAACCCGGAAGCUAAGCCCCAUAGCGCCGAUGGUUACUGUAACCGGGAGGUUGUGGGAGAGUAGGUCGCCGCCGUGAOH. When compared to other 5S RNAs, the sequence homology is greatest with Thermus aquaticus, and these two 5S RNAs reveal several features intermediate between those of typical gram-positive bacteria and gram-negative bacteria. PMID:6780979

Screening for sequence-specific RNA-BPs by comprehensive UV crosslinking

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Le Meuth-Metzinger Valerie

2002-06-01

Full Text Available Abstract Background Specific cis-elements and the associated trans-acting factors have been implicated in the post-transcriptional regulation of gene expression. In the era of genome wide analyses identifying novel trans-acting factors and cis-regulatory elements is a step towards understanding coordinated gene expression. UV-crosslink analysis is a standard method used to identify RNA-binding proteins. Uridine is traditionally used to radiolabel substrate RNAs, however, proteins binding to cis-elments particularly uridine poor will be weakly or not detected. We evaluate here the possibility of using UV-crosslinking with RNA substrates radiolabeled with each of the four ribonucleotides as an approach for screening for novel sequence specific RNA-binding proteins. Results The radiolabeled RNA substrates were derived from the 3'UTRs of the cloned Eg and c-mos Xenopus laevis maternal mRNAs. Specific, but not identical, uv-crosslinking signals were obtained, some of which corresponded to already identified proteins. A signal for a novel 90 kDa protein was observed with the c-mos 3'UTR radiolabeled with both CTP and GTP but not with UTP. The binding site of the 90 kDa RNA-binding protein was localised to a 59-nucleotide portion of the c-mos 3'UTR. Conclusion That the 90 kDa signal was detected with RNAs radiolabeled with CTP or GTP but not UTP illustrates the advantage of radiolabeling all four nucleotides in a UV-crosslink based screen. This method can be used for both long and short RNAs and does not require knowledge of the cis-acting sequence. It should be amenable to high throughput screening for RNA binding proteins.

Mapping RNA Structure In Vitro with SHAPE Chemistry and Next-Generation Sequencing (SHAPE-Seq).

Science.gov (United States)

Watters, Kyle E; Lucks, Julius B

2016-01-01

Mapping RNA structure with selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) chemistry has proven to be a versatile method for characterizing RNA structure in a variety of contexts. SHAPE reagents covalently modify RNAs in a structure-dependent manner to create adducts at the 2'-OH group of the ribose backbone at nucleotides that are structurally flexible. The positions of these adducts are detected using reverse transcriptase (RT) primer extension, which stops one nucleotide before the modification, to create a pool of cDNAs whose lengths reflect the location of SHAPE modification. Quantification of the cDNA pools is used to estimate the "reactivity" of each nucleotide in an RNA molecule to the SHAPE reagent. High reactivities indicate nucleotides that are structurally flexible, while low reactivities indicate nucleotides that are inflexible. These SHAPE reactivities can then be used to infer RNA structures by restraining RNA structure prediction algorithms. Here, we provide a state-of-the-art protocol describing how to perform in vitro RNA structure probing with SHAPE chemistry using next-generation sequencing to quantify cDNA pools and estimate reactivities (SHAPE-Seq). The use of next-generation sequencing allows for higher throughput, more consistent data analysis, and multiplexing capabilities. The technique described herein, SHAPE-Seq v2.0, uses a universal reverse transcription priming site that is ligated to the RNA after SHAPE modification. The introduced priming site allows for the structural analysis of an RNA independent of its sequence.

A validated pipeline for detection of SNVs and short InDels from RNA Sequencing

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Nitin Mandloi

2017-12-01

In this study, we have developed a pipeline to detect germline variants from RNA-seq data. The pipeline steps include: pre-processing, alignment, GATK best practices for RNA-seq and variant filtering. The pre-processing step includes base and adapter trimming and removal of contamination reads from rRNA, tRNA, mitochondrial DNA and repeat regions. The read alignment of the pre-processed reads is performed using STAR/HiSAT. After this we used GATK best practices for the RNA-seq dataset to call germline variants. We benchmarked our pipeline on NA12878 RNA-seq data downloaded from SRA (SRR1258218. After variant calling, the quality passed variants were compared against the gold standard variants provided by GIAB consortium. Of the total ~3.6 million high quality variants reported as gold standard variants for this sample (considering whole genome, our pipeline identified ~58,104 variants to be expressed in RNA-seq. Our pipeline achieved more than 99% of sensitivity in detection of germline variants.

Sequence-specific inhibition of Dicer measured with a force-based microarray for RNA ligands.

Science.gov (United States)

Limmer, Katja; Aschenbrenner, Daniela; Gaub, Hermann E

2013-04-01

Malfunction of protein translation causes many severe diseases, and suitable correction strategies may become the basis of effective therapies. One major regulatory element of protein translation is the nuclease Dicer that cuts double-stranded RNA independently of the sequence into pieces of 19-22 base pairs starting the RNA interference pathway and activating miRNAs. Inhibiting Dicer is not desirable owing to its multifunctional influence on the cell's gene regulation. Blocking specific RNA sequences by small-molecule binding, however, is a promising approach to affect the cell's condition in a controlled manner. A label-free assay for the screening of site-specific interference of small molecules with Dicer activity is thus needed. We used the Molecular Force Assay (MFA), recently developed in our lab, to measure the activity of Dicer. As a model system, we used an RNA sequence that forms an aptamer-binding site for paromomycin, a 615-dalton aminoglycoside. We show that Dicer activity is modulated as a function of concentration and incubation time: the addition of paromomycin leads to a decrease of Dicer activity according to the amount of ligand. The measured dissociation constant of paromomycin to its aptamer was found to agree well with literature values. The parallel format of the MFA allows a large-scale search and analysis for ligands for any RNA sequence.

Detection and characterization of Pasteuria 16S rRNA gene sequences from nematodes and soils.

Science.gov (United States)

Duan, Y P; Castro, H F; Hewlett, T E; White, J H; Ogram, A V

2003-01-01

Various bacterial species in the genus Pasteuria have great potential as biocontrol agents against plant-parasitic nematodes, although study of this important genus is hampered by the current inability to cultivate Pasteuria species outside their host. To aid in the study of this genus, an extensive 16S rRNA gene sequence phylogeny was constructed and this information was used to develop cultivation-independent methods for detection of Pasteuria in soils and nematodes. Thirty new clones of Pasteuria 16S rRNA genes were obtained directly from nematodes and soil samples. These were sequenced and used to construct an extensive phylogeny of this genus. These sequences were divided into two deeply branching clades within the low-G + C, Gram-positive division; some sequences appear to represent novel species within the genus Pasteuria. In addition, a surprising degree of 16S rRNA gene sequence diversity was observed within what had previously been designated a single strain of Pasteuria penetrans (P-20). PCR primers specific to Pasteuria 16S rRNA for detection of Pasteuria in soils were also designed and evaluated. Detection limits for soil DNA were 100-10,000 Pasteuria endospores (g soil)(-1).

Low Maternal Microbiota Sharing across Gut, Breast Milk and Vagina, as Revealed by 16S rRNA Gene and Reduced Metagenomic Sequencing

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Ekaterina Avershina

2018-05-01

Full Text Available The maternal microbiota plays an important role in infant gut colonization. In this work we have investigated which bacterial species are shared across the breast milk, vaginal and stool microbiotas of 109 women shortly before and after giving birth using 16S rRNA gene sequencing and a novel reduced metagenomic sequencing (RMS approach in a subgroup of 16 women. All the species predicted by the 16S rRNA gene sequencing were also detected by RMS analysis and there was good correspondence between their relative abundances estimated by both approaches. Both approaches also demonstrate a low level of maternal microbiota sharing across the population and RMS analysis identified only two species common to most women and in all sample types (Bifidobacterium longum and Enterococcus faecalis. Breast milk was the only sample type that had significantly higher intra- than inter- individual similarity towards both vaginal and stool samples. We also searched our RMS dataset against an in silico generated reference database derived from bacterial isolates in the Human Microbiome Project. The use of this reference-based search enabled further separation of Bifidobacterium longum into Bifidobacterium longum ssp. longum and Bifidobacterium longum ssp. infantis. We also detected the Lactobacillus rhamnosus GG strain, which was used as a probiotic supplement by some women, demonstrating the potential of RMS approach for deeper taxonomic delineation and estimation.

Accuracy of taxonomy prediction for 16S rRNA and fungal ITS sequences

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Robert C. Edgar

2018-04-01

Full Text Available Prediction of taxonomy for marker gene sequences such as 16S ribosomal RNA (rRNA is a fundamental task in microbiology. Most experimentally observed sequences are diverged from reference sequences of authoritatively named organisms, creating a challenge for prediction methods. I assessed the accuracy of several algorithms using cross-validation by identity, a new benchmark strategy which explicitly models the variation in distances between query sequences and the closest entry in a reference database. When the accuracy of genus predictions was averaged over a representative range of identities with the reference database (100%, 99%, 97%, 95% and 90%, all tested methods had ≤50% accuracy on the currently-popular V4 region of 16S rRNA. Accuracy was found to fall rapidly with identity; for example, better methods were found to have V4 genus prediction accuracy of ∼100% at 100% identity but ∼50% at 97% identity. The relationship between identity and taxonomy was quantified as the probability that a rank is the lowest shared by a pair of sequences with a given pair-wise identity. With the V4 region, 95% identity was found to be a twilight zone where taxonomy is highly ambiguous because the probabilities that the lowest shared rank between pairs of sequences is genus, family, order or class are approximately equal.

A novel RNA sequencing data analysis method for cell line authentication.

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Erik Fasterius

Full Text Available We have developed a novel analysis method that can interrogate the authenticity of biological samples used for generation of transcriptome profiles in public data repositories. The method uses RNA sequencing information to reveal mutations in expressed transcripts and subsequently confirms the identity of analysed cells by comparison with publicly available cell-specific mutational profiles. Cell lines constitute key model systems widely used within cancer research, but their identity needs to be confirmed in order to minimise the influence of cell contaminations and genetic drift on the analysis. Using both public and novel data, we demonstrate the use of RNA-sequencing data analysis for cell line authentication by examining the validity of COLO205, DLD1, HCT15, HCT116, HKE3, HT29 and RKO colorectal cancer cell lines. We successfully authenticate the studied cell lines and validate previous reports indicating that DLD1 and HCT15 are synonymous. We also show that the analysed HKE3 cells harbour an unexpected KRAS-G13D mutation and confirm that this cell line is a genuine KRAS dosage mutant, rather than a true isogenic derivative of HCT116 expressing only the wild type KRAS. This authentication method could be used to revisit the numerous cell line based RNA sequencing experiments available in public data repositories, analyse new experiments where whole genome sequencing is not available, as well as facilitate comparisons of data from different experiments, platforms and laboratories.

Pairwise local structural alignment of RNA sequences with sequence similarity less than 40%

DEFF Research Database (Denmark)

Havgaard, Jakob Hull; Lyngsø, Rune B.; Stormo, Gary D.

2005-01-01

detect two genes with low sequence similarity, where the genes are part of a larger genomic region. Results: Here we present such an approach for pairwise local alignment which is based on FILDALIGN and the Sankoff algorithm for simultaneous structural alignment of multiple sequences. We include...... the ability to conduct mutual scans of two sequences of arbitrary length while searching for common local structural motifs of some maximum length. This drastically reduces the complexity of the algorithm. The scoring scheme includes structural parameters corresponding to those available for free energy....... The structure prediction performance for a family is typically around 0.7 using Matthews correlation coefficient. In case (2), the algorithm is successful at locating RNA families with an average sensitivity of 0.8 and a positive predictive value of 0.9 using a BLAST-like hit selection scheme. Availability...

Genomics dataset of unidentified disclosed isolates

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Bhagwan N. Rekadwad

2016-09-01

Full Text Available Analysis of DNA sequences is necessary for higher hierarchical classification of the organisms. It gives clues about the characteristics of organisms and their taxonomic position. This dataset is chosen to find complexities in the unidentified DNA in the disclosed patents. A total of 17 unidentified DNA sequences were thoroughly analyzed. The quick response codes were generated. AT/GC content of the DNA sequences analysis was carried out. The QR is helpful for quick identification of isolates. AT/GC content is helpful for studying their stability at different temperatures. Additionally, a dataset on cleavage code and enzyme code studied under the restriction digestion study, which helpful for performing studies using short DNA sequences was reported. The dataset disclosed here is the new revelatory data for exploration of unique DNA sequences for evaluation, identification, comparison and analysis. Keywords: BioLABs, Blunt ends, Genomics, NEB cutter, Restriction digestion, Short DNA sequences, Sticky ends

Spatially resolved RNA-sequencing of the embryonic heart identifies a role for Wnt/β-catenin signaling in autonomic control of heart rate

Science.gov (United States)

Burkhard, Silja Barbara

2018-01-01

Development of specialized cells and structures in the heart is regulated by spatially -restricted molecular pathways. Disruptions in these pathways can cause severe congenital cardiac malformations or functional defects. To better understand these pathways and how they regulate cardiac development we used tomo-seq, combining high-throughput RNA-sequencing with tissue-sectioning, to establish a genome-wide expression dataset with high spatial resolution for the developing zebrafish heart. Analysis of the dataset revealed over 1100 genes differentially expressed in sub-compartments. Pacemaker cells in the sinoatrial region induce heart contractions, but little is known about the mechanisms underlying their development. Using our transcriptome map, we identified spatially restricted Wnt/β-catenin signaling activity in pacemaker cells, which was controlled by Islet-1 activity. Moreover, Wnt/β-catenin signaling controls heart rate by regulating pacemaker cellular response to parasympathetic stimuli. Thus, this high-resolution transcriptome map incorporating all cell types in the embryonic heart can expose spatially restricted molecular pathways critical for specific cardiac functions. PMID:29400650

Combined sequencing of mRNA and DNA from human embryonic stem cells

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Florian Mertes

2016-06-01

Full Text Available Combined transcriptome and whole genome sequencing of the same ultra-low input sample down to single cells is a rapidly evolving approach for the analysis of rare cells. Besides stem cells, rare cells originating from tissues like tumor or biopsies, circulating tumor cells and cells from early embryonic development are under investigation. Herein we describe a universal method applicable for the analysis of minute amounts of sample material (150 to 200 cells derived from sub-colony structures from human embryonic stem cells. The protocol comprises the combined isolation and separate amplification of poly(A mRNA and whole genome DNA followed by next generation sequencing. Here we present a detailed description of the method developed and an overview of the results obtained for RNA and whole genome sequencing of human embryonic stem cells, sequencing data is available in the Gene Expression Omnibus (GEO database under accession number GSE69471.

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/.

How to Tackle the Challenge of siRNA Delivery with Sequence-Defined Oligoamino Amides.

Science.gov (United States)

Reinhard, Sören; Wagner, Ernst

2017-01-01

RNA interference (RNAi) as a mechanism of gene regulation provides exciting opportunities for medical applications. Synthetic small interfering RNA (siRNA) triggers the knockdown of complementary mRNA sequences in a catalytic fashion and has to be delivered into the cytosol of the targeted cells. The design of adequate carrier systems to overcome multiple extracellular and intracellular roadblocks within the delivery process has utmost importance. Cationic polymers form polyplexes through electrostatic interaction with negatively charged nucleic acids and present a promising class of carriers. Issues of polycations regarding toxicity, heterogeneity, and polydispersity can be overcome by solid-phase-assisted synthesis of sequence-defined cationic oligomers. These medium-sized highly versatile nucleic acid carriers display low cytotoxicity and can be modified and tailored in multiple ways to meet specific requirements of nucleic acid binding, polyplex size, shielding, targeting, and intracellular release of the cargo. In this way, sequence-defined cationic oligomers can mimic the dynamic and bioresponsive behavior of viruses. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Stormbow: A Cloud-Based Tool for Reads Mapping and Expression Quantification in Large-Scale RNA-Seq Studies.

Science.gov (United States)

Zhao, Shanrong; Prenger, Kurt; Smith, Lance

2013-01-01

RNA-Seq is becoming a promising replacement to microarrays in transcriptome profiling and differential gene expression study. Technical improvements have decreased sequencing costs and, as a result, the size and number of RNA-Seq datasets have increased rapidly. However, the increasing volume of data from large-scale RNA-Seq studies poses a practical challenge for data analysis in a local environment. To meet this challenge, we developed Stormbow, a cloud-based software package, to process large volumes of RNA-Seq data in parallel. The performance of Stormbow has been tested by practically applying it to analyse 178 RNA-Seq samples in the cloud. In our test, it took 6 to 8 hours to process an RNA-Seq sample with 100 million reads, and the average cost was $3.50 per sample. Utilizing Amazon Web Services as the infrastructure for Stormbow allows us to easily scale up to handle large datasets with on-demand computational resources. Stormbow is a scalable, cost effective, and open-source based tool for large-scale RNA-Seq data analysis. Stormbow can be freely downloaded and can be used out of box to process Illumina RNA-Seq datasets.

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

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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.

Dataset of transcriptional landscape of B cell early activation

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Alexander S. Garruss

2015-09-01

Full Text Available Signaling via B cell receptors (BCR and Toll-like receptors (TLRs result in activation of B cells with distinct physiological outcomes, but transcriptional regulatory mechanisms that drive activation and distinguish these pathways remain unknown. At early time points after BCR and TLR ligand exposure, 0.5 and 2 h, RNA-seq was performed allowing observations on rapid transcriptional changes. At 2 h, ChIP-seq was performed to allow observations on important regulatory mechanisms potentially driving transcriptional change. The dataset includes RNA-seq, ChIP-seq of control (Input, RNA Pol II, H3K4me3, H3K27me3, and a separate RNA-seq for miRNA expression, which can be found at Gene Expression Omnibus Dataset GSE61608. Here, we provide details on the experimental and analysis methods used to obtain and analyze this dataset and to examine the transcriptional landscape of B cell early activation.

Partial nucleotide sequence analysis of 18S ribosomal RNA gene of the four genotypes of Trypanosoma congolense

International Nuclear Information System (INIS)

Osanya, A.; Majiwa, P.A.O.; Kinyanjui, P.W.

2006-01-01

Specific oligonucleotide primers based on conserved nucleotide sequences of 18s ribisomal RNA (18s rRNA) gene of Trypanosoma brucei, Leishmania donovani, Triponema aequale and Lagenidium gigantum have been designed and used in the ploymerase chain reaction (PCR) to amplify genomic DNA from four different clones each representing a different genotypic group of T. congolence. PCR products of approximately 1Kb were generated using as template DNA from each of the trypanosomes. The PCR products cross-hybridized with genomic DNA from T.brucei, T. simiae and the four genotypes of T.congolense implying significant sequence homology of 18S rRNA gene among trypanosomes. The nucleotide sequence of a segment of the PCR products were determined by direct sequencing to provide partial nucleotide sequence of the 18s rRNA gene in each T.congolense genotypic group. The sequences obtained together with those that have been published for T.brucei reveals that although most regions show inter and intra species nucleotide identity, there are several sites where deletions, insertions and base changes have occured in nucleotide sequence of of T.brucei and the four genotypes of T.congolense.(author)

Fast selection of miRNA candidates based on large-scale pre-computed MFE sets of randomized sequences.

Science.gov (United States)

Warris, Sven; Boymans, Sander; Muiser, Iwe; Noback, Michiel; Krijnen, Wim; Nap, Jan-Peter

2014-01-13

Small RNAs are important regulators of genome function, yet their prediction in genomes is still a major computational challenge. Statistical analyses of pre-miRNA sequences indicated that their 2D structure tends to have a minimal free energy (MFE) significantly lower than MFE values of equivalently randomized sequences with the same nucleotide composition, in contrast to other classes of non-coding RNA. The computation of many MFEs is, however, too intensive to allow for genome-wide screenings. Using a local grid infrastructure, MFE distributions of random sequences were pre-calculated on a large scale. These distributions follow a normal distribution and can be used to determine the MFE distribution for any given sequence composition by interpolation. It allows on-the-fly calculation of the normal distribution for any candidate sequence composition. The speedup achieved makes genome-wide screening with this characteristic of a pre-miRNA sequence practical. Although this particular property alone will not be able to distinguish miRNAs from other sequences sufficiently discriminative, the MFE-based P-value should be added to the parameters of choice to be included in the selection of potential miRNA candidates for experimental verification.

TranslatomeDB: a comprehensive database and cloud-based analysis platform for translatome sequencing data.

Science.gov (United States)

Liu, Wanting; Xiang, Lunping; Zheng, Tingkai; Jin, Jingjie; Zhang, Gong

2018-01-04

Translation is a key regulatory step, linking transcriptome and proteome. Two major methods of translatome investigations are RNC-seq (sequencing of translating mRNA) and Ribo-seq (ribosome profiling). To facilitate the investigation of translation, we built a comprehensive database TranslatomeDB (http://www.translatomedb.net/) which provides collection and integrated analysis of published and user-generated translatome sequencing data. The current version includes 2453 Ribo-seq, 10 RNC-seq and their 1394 corresponding mRNA-seq datasets in 13 species. The database emphasizes the analysis functions in addition to the dataset collections. Differential gene expression (DGE) analysis can be performed between any two datasets of same species and type, both on transcriptome and translatome levels. The translation indices translation ratios, elongation velocity index and translational efficiency can be calculated to quantitatively evaluate translational initiation efficiency and elongation velocity, respectively. All datasets were analyzed using a unified, robust, accurate and experimentally-verifiable pipeline based on the FANSe3 mapping algorithm and edgeR for DGE analyzes. TranslatomeDB also allows users to upload their own datasets and utilize the identical unified pipeline to analyze their data. We believe that our TranslatomeDB is a comprehensive platform and knowledgebase on translatome and proteome research, releasing the biologists from complex searching, analyzing and comparing huge sequencing data without needing local computational power. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Exploratory Bioinformatics Study of lncRNAs in Alzheimer’s Disease mRNA Sequences with Application to Drug Development

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T. Holden

2013-01-01

Full Text Available Long noncoding RNA (lncRNA within mRNA sequences of Alzheimer’s disease genes, namely, APP, APOE, PSEN1, and PSEN2, has been analyzed using fractal dimension (FD computation and correlation analysis. We examined lncRNA by comparing mRNA FD to corresponding coding DNA sequences (CDSs FD. APP, APOE, and PSEN1 CDSs select slightly higher FDs compared to the mRNA, while PSEN2 CDSs FDs are lower. The correlation coefficient for these sequences is 0.969. A comparative study of differentially expressed MAPK signaling pathway lncRNAs in pancreatic cancer cells shows a correlation of 0.771. Selection of higher FD CDSs could indicate interaction of Alzheimer’s gene products APP, APOE, and PSEN1. Including hypocretin sequences (where all CDSs have higher fractal dimensions than mRNA in the APP, APOE, and PSEN1 sequence analyses improves correlation, but the inclusion of erythropoietin (where all CDSs have higher FD than mRNA would suppress correlation, suggesting that HCRT, a hypothalamus neurotransmitter related to the wake/sleep cycle, might be better when compared to EPO, a glycoprotein hormone, for targeting Alzheimer’s disease drug development. Fractal dimension and entropy correlation have provided supporting evidence, consistent with evolutionary studies, for using a zebrafish model together with a mouse model, in HCRT drug development.

RNAPattMatch: a web server for RNA sequence/structure motif detection based on pattern matching with flexible gaps

Science.gov (United States)

Drory Retwitzer, Matan; Polishchuk, Maya; Churkin, Elena; Kifer, Ilona; Yakhini, Zohar; Barash, Danny

2015-01-01

Searching for RNA sequence-structure patterns is becoming an essential tool for RNA practitioners. Novel discoveries of regulatory non-coding RNAs in targeted organisms and the motivation to find them across a wide range of organisms have prompted the use of computational RNA pattern matching as an enhancement to sequence similarity. State-of-the-art programs differ by the flexibility of patterns allowed as queries and by their simplicity of use. In particular—no existing method is available as a user-friendly web server. A general program that searches for RNA sequence-structure patterns is RNA Structator. However, it is not available as a web server and does not provide the option to allow flexible gap pattern representation with an upper bound of the gap length being specified at any position in the sequence. Here, we introduce RNAPattMatch, a web-based application that is user friendly and makes sequence/structure RNA queries accessible to practitioners of various background and proficiency. It also extends RNA Structator and allows a more flexible variable gaps representation, in addition to analysis of results using energy minimization methods. RNAPattMatch service is available at http://www.cs.bgu.ac.il/rnapattmatch. A standalone version of the search tool is also available to download at the site. PMID:25940619

Novel sequence variations in LAMA2 and SGCG genes modulating cis-acting regulatory elements and RNA secondary structure

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Olfa Siala

2010-01-01

Full Text Available In this study, we detected new sequence variations in LAMA2 and SGCG genes in 5 ethnic populations, and analysed their effect on enhancer composition and mRNA structure. PCR amplification and DNA sequencing were performed and followed by bioinformatics analyses using ESEfinder as well as MFOLD software. We found 3 novel sequence variations in the LAMA2 (c.3174+22_23insAT and c.6085 +12delA and SGCG (c.*102A/C genes. These variations were present in 210 tested healthy controls from Tunisian, Moroccan, Algerian, Lebanese and French populations suggesting that they represent novel polymorphisms within LAMA2 and SGCG genes sequences. ESEfinder showed that the c.*102A/C substitution created a new exon splicing enhancer in the 3'UTR of SGCG genes, whereas the c.6085 +12delA deletion was situated in the base pairing region between LAMA2 mRNA and the U1snRNA spliceosomal components. The RNA structure analyses showed that both variations modulated RNA secondary structure. Our results are suggestive of correlations between mRNA folding and the recruitment of spliceosomal components mediating splicing, including SR proteins. The contribution of common sequence variations to mRNA structural and functional diversity will contribute to a better study of gene expression.

The distribution, diversity, and importance of 16S rRNA gene introns in the order Thermoproteales.

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Jay, Zackary J; Inskeep, William P

2015-07-09

Intron sequences are common in 16S rRNA genes of specific thermophilic lineages of Archaea, specifically the Thermoproteales (phylum Crenarchaeota). Environmental sequencing (16S rRNA gene and metagenome) from geothermal habitats in Yellowstone National Park (YNP) has expanded the available datasets for investigating 16S rRNA gene introns. The objectives of this study were to characterize and curate archaeal 16S rRNA gene introns from high-temperature habitats, evaluate the conservation and distribution of archaeal 16S rRNA introns in geothermal systems, and determine which "universal" archaeal 16S rRNA gene primers are impacted by the presence of intron sequences. Several new introns were identified and their insertion loci were constrained to thirteen locations across the 16S rRNA gene. Many of these introns encode homing endonucleases, although some introns were short or partial sequences. Pyrobaculum, Thermoproteus, and Caldivirga 16S rRNA genes contained the most abundant and diverse intron sequences. Phylogenetic analysis of introns revealed that sequences within the same locus are distributed biogeographically. The most diverse set of introns were observed in a high-temperature, circumneutral (pH 6) sulfur sediment environment, which also contained the greatest diversity of different Thermoproteales phylotypes. The widespread presence of introns in the Thermoproteales indicates a high probability of misalignments using different "universal" 16S rRNA primers employed in environmental microbial community analysis.

Next Generation Sequencing Analysis of Human Platelet PolyA+ mRNAs and rRNA-Depleted Total RNA

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Kissopoulou, Antheia; Jonasson, Jon; Lindahl, Tomas L.; Osman, Abdimajid

2013-01-01

Background Platelets are small anucleate cells circulating in the blood vessels where they play a key role in hemostasis and thrombosis. Here, we compared platelet RNA-Seq results obtained from polyA+ mRNA and rRNA-depleted total RNA. Materials and Methods We used purified, CD45 depleted, human blood platelets collected by apheresis from three male and one female healthy blood donors. The Illumina HiSeq 2000 platform was employed to sequence cDNA converted either from oligo(dT) isolated polyA+ RNA or from rRNA-depleted total RNA. The reads were aligned to the GRCh37 reference assembly with the TopHat/Cufflinks alignment package using Ensembl annotations. A de novo assembly of the platelet transcriptome using the Trinity software package and RSEM was also performed. The bioinformatic tools HTSeq and DESeq from Bioconductor were employed for further statistical analyses of read counts. Results Consistent with previous findings our data suggests that mitochondrially expressed genes comprise a substantial fraction of the platelet transcriptome. We also identified high transcript levels for protein coding genes related to the cytoskeleton function, chemokine signaling, cell adhesion, aggregation, as well as receptor interaction between cells. Certain transcripts were particularly abundant in platelets compared with other cell and tissue types represented by RNA-Seq data from the Illumina Human Body Map 2.0 project. Irrespective of the different library preparation and sequencing protocols, there was good agreement between samples from the 4 individuals. Eighteen differentially expressed genes were identified in the two sexes at 10% false discovery rate using DESeq. Conclusion The present data suggests that platelets may have a unique transcriptome profile characterized by a relative over-expression of mitochondrially encoded genes and also of genomic transcripts related to the cytoskeleton function, chemokine signaling and surface components compared with other cell and

Next generation sequencing analysis of human platelet PolyA+ mRNAs and rRNA-depleted total RNA.

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Antheia Kissopoulou

Full Text Available BACKGROUND: Platelets are small anucleate cells circulating in the blood vessels where they play a key role in hemostasis and thrombosis. Here, we compared platelet RNA-Seq results obtained from polyA+ mRNA and rRNA-depleted total RNA. MATERIALS AND METHODS: We used purified, CD45 depleted, human blood platelets collected by apheresis from three male and one female healthy blood donors. The Illumina HiSeq 2000 platform was employed to sequence cDNA converted either from oligo(dT isolated polyA+ RNA or from rRNA-depleted total RNA. The reads were aligned to the GRCh37 reference assembly with the TopHat/Cufflinks alignment package using Ensembl annotations. A de novo assembly of the platelet transcriptome using the Trinity software package and RSEM was also performed. The bioinformatic tools HTSeq and DESeq from Bioconductor were employed for further statistical analyses of read counts. RESULTS: Consistent with previous findings our data suggests that mitochondrially expressed genes comprise a substantial fraction of the platelet transcriptome. We also identified high transcript levels for protein coding genes related to the cytoskeleton function, chemokine signaling, cell adhesion, aggregation, as well as receptor interaction between cells. Certain transcripts were particularly abundant in platelets compared with other cell and tissue types represented by RNA-Seq data from the Illumina Human Body Map 2.0 project. Irrespective of the different library preparation and sequencing protocols, there was good agreement between samples from the 4 individuals. Eighteen differentially expressed genes were identified in the two sexes at 10% false discovery rate using DESeq. CONCLUSION: The present data suggests that platelets may have a unique transcriptome profile characterized by a relative over-expression of mitochondrially encoded genes and also of genomic transcripts related to the cytoskeleton function, chemokine signaling and surface components

Linking maternal and somatic 5S rRNA types with different sequence-specific non-LTR retrotransposons.

Science.gov (United States)

Locati, Mauro D; Pagano, Johanna F B; Ensink, Wim A; van Olst, Marina; van Leeuwen, Selina; Nehrdich, Ulrike; Zhu, Kongju; Spaink, Herman P; Girard, Geneviève; Rauwerda, Han; Jonker, Martijs J; Dekker, Rob J; Breit, Timo M

2017-04-01

5S rRNA is a ribosomal core component, transcribed from many gene copies organized in genomic repeats. Some eukaryotic species have two 5S rRNA types defined by their predominant expression in oogenesis or adult tissue. Our next-generation sequencing study on zebrafish egg, embryo, and adult tissue identified maternal-type 5S rRNA that is exclusively accumulated during oogenesis, replaced throughout the embryogenesis by a somatic-type, and thus virtually absent in adult somatic tissue. The maternal-type 5S rDNA contains several thousands of gene copies on chromosome 4 in tandem repeats with small intergenic regions, whereas the somatic-type is present in only 12 gene copies on chromosome 18 with large intergenic regions. The nine-nucleotide variation between the two 5S rRNA types likely affects TFIII binding and riboprotein L5 binding, probably leading to storage of maternal-type rRNA. Remarkably, these sequence differences are located exactly at the sequence-specific target site for genome integration by the 5S rRNA-specific Mutsu retrotransposon family. Thus, we could define maternal- and somatic-type MutsuDr subfamilies. Furthermore, we identified four additional maternal-type and two new somatic-type MutsuDr subfamilies, each with their own target sequence. This target-site specificity, frequently intact maternal-type retrotransposon elements, plus specific presence of Mutsu retrotransposon RNA and piRNA in egg and adult tissue, suggest an involvement of retrotransposons in achieving the differential copy number of the two types of 5S rDNA loci. © 2017 Locati et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

Protein-RNA interface residue prediction using machine learning: an assessment of the state of the art.

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Walia, Rasna R; Caragea, Cornelia; Lewis, Benjamin A; Towfic, Fadi; Terribilini, Michael; El-Manzalawy, Yasser; Dobbs, Drena; Honavar, Vasant

2012-05-10

RNA molecules play diverse functional and structural roles in cells. They function as messengers for transferring genetic information from DNA to proteins, as the primary genetic material in many viruses, as catalysts (ribozymes) important for protein synthesis and RNA processing, and as essential and ubiquitous regulators of gene expression in living organisms. Many of these functions depend on precisely orchestrated interactions between RNA molecules and specific proteins in cells. Understanding the molecular mechanisms by which proteins recognize and bind RNA is essential for comprehending the functional implications of these interactions, but the recognition 'code' that mediates interactions between proteins and RNA is not yet understood. Success in deciphering this code would dramatically impact the development of new therapeutic strategies for intervening in devastating diseases such as AIDS and cancer. Because of the high cost of experimental determination of protein-RNA interfaces, there is an increasing reliance on statistical machine learning methods for training predictors of RNA-binding residues in proteins. However, because of differences in the choice of datasets, performance measures, and data representations used, it has been difficult to obtain an accurate assessment of the current state of the art in protein-RNA interface prediction. We provide a review of published approaches for predicting RNA-binding residues in proteins and a systematic comparison and critical assessment of protein-RNA interface residue predictors trained using these approaches on three carefully curated non-redundant datasets. We directly compare two widely used machine learning algorithms (Naïve Bayes (NB) and Support Vector Machine (SVM)) using three different data representations in which features are encoded using either sequence- or structure-based windows. Our results show that (i) Sequence-based classifiers that use a position-specific scoring matrix (PSSM

Bayesian Correlation Analysis for Sequence Count Data.

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Daniel Sánchez-Taltavull

Full Text Available Evaluating the similarity of different measured variables is a fundamental task of statistics, and a key part of many bioinformatics algorithms. Here we propose a Bayesian scheme for estimating the correlation between different entities' measurements based on high-throughput sequencing data. These entities could be different genes or miRNAs whose expression is measured by RNA-seq, different transcription factors or histone marks whose expression is measured by ChIP-seq, or even combinations of different types of entities. Our Bayesian formulation accounts for both measured signal levels and uncertainty in those levels, due to varying sequencing depth in different experiments and to varying absolute levels of individual entities, both of which affect the precision of the measurements. In comparison with a traditional Pearson correlation analysis, we show that our Bayesian correlation analysis retains high correlations when measurement confidence is high, but suppresses correlations when measurement confidence is low-especially for entities with low signal levels. In addition, we consider the influence of priors on the Bayesian correlation estimate. Perhaps surprisingly, we show that naive, uniform priors on entities' signal levels can lead to highly biased correlation estimates, particularly when different experiments have widely varying sequencing depths. However, we propose two alternative priors that provably mitigate this problem. We also prove that, like traditional Pearson correlation, our Bayesian correlation calculation constitutes a kernel in the machine learning sense, and thus can be used as a similarity measure in any kernel-based machine learning algorithm. We demonstrate our approach on two RNA-seq datasets and one miRNA-seq dataset.

Physiological recordings and RNA sequencing of the gustatory appendages of the yellow-fever mosquito Aedes aegypti.

Science.gov (United States)

Sparks, Jackson T; Dickens, Joseph C

2014-12-30

Electrophysiological recording of action potentials from sensory neurons of mosquitoes provides investigators a glimpse into the chemical perception of these disease vectors. We have recently identified a bitter sensing neuron in the labellum of female Aedes aegypti that responds to DEET and other repellents, as well as bitter quinine, through direct electrophysiological investigation. These gustatory receptor neuron responses prompted our sequencing of total mRNA from both male and female labella and tarsi samples to elucidate the putative chemoreception genes expressed in these contact chemoreception tissues. Samples of tarsi were divided into pro-, meso- and metathoracic subtypes for both sexes. We then validated our dataset by conducting qRT-PCR on the same tissue samples and used statistical methods to compare results between the two methods. Studies addressing molecular function may now target specific genes to determine those involved in repellent perception by mosquitoes. These receptor pathways may be used to screen novel repellents towards disruption of host-seeking behavior to curb the spread of harmful viruses.

Statistical modeling of isoform splicing dynamics from RNA-seq time series data.

Science.gov (United States)

Huang, Yuanhua; Sanguinetti, Guido

2016-10-01

Isoform quantification is an important goal of RNA-seq experiments, yet it remains problematic for genes with low expression or several isoforms. These difficulties may in principle be ameliorated by exploiting correlated experimental designs, such as time series or dosage response experiments. Time series RNA-seq experiments, in particular, are becoming increasingly popular, yet there are no methods that explicitly leverage the experimental design to improve isoform quantification. Here, we present DICEseq, the first isoform quantification method tailored to correlated RNA-seq experiments. DICEseq explicitly models the correlations between different RNA-seq experiments to aid the quantification of isoforms across experiments. Numerical experiments on simulated datasets show that DICEseq yields more accurate results than state-of-the-art methods, an advantage that can become considerable at low coverage levels. On real datasets, our results show that DICEseq provides substantially more reproducible and robust quantifications, increasing the correlation of estimates from replicate datasets by up to 10% on genes with low or moderate expression levels (bottom third of all genes). Furthermore, DICEseq permits to quantify the trade-off between temporal sampling of RNA and depth of sequencing, frequently an important choice when planning experiments. Our results have strong implications for the design of RNA-seq experiments, and offer a novel tool for improved analysis of such datasets. Python code is freely available at http://diceseq.sf.net G.Sanguinetti@ed.ac.uk Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Comprehensive processing of high-throughput small RNA sequencing data including quality checking, normalization, and differential expression analysis using the UEA sRNA Workbench.

Science.gov (United States)

Beckers, Matthew; Mohorianu, Irina; Stocks, Matthew; Applegate, Christopher; Dalmay, Tamas; Moulton, Vincent

2017-06-01

Recently, high-throughput sequencing (HTS) has revealed compelling details about the small RNA (sRNA) population in eukaryotes. These 20 to 25 nt noncoding RNAs can influence gene expression by acting as guides for the sequence-specific regulatory mechanism known as RNA silencing. The increase in sequencing depth and number of samples per project enables a better understanding of the role sRNAs play by facilitating the study of expression patterns. However, the intricacy of the biological hypotheses coupled with a lack of appropriate tools often leads to inadequate mining of the available data and thus, an incomplete description of the biological mechanisms involved. To enable a comprehensive study of differential expression in sRNA data sets, we present a new interactive pipeline that guides researchers through the various stages of data preprocessing and analysis. This includes various tools, some of which we specifically developed for sRNA analysis, for quality checking and normalization of sRNA samples as well as tools for the detection of differentially expressed sRNAs and identification of the resulting expression patterns. The pipeline is available within the UEA sRNA Workbench, a user-friendly software package for the processing of sRNA data sets. We demonstrate the use of the pipeline on a H. sapiens data set; additional examples on a B. terrestris data set and on an A. thaliana data set are described in the Supplemental Information A comparison with existing approaches is also included, which exemplifies some of the issues that need to be addressed for sRNA analysis and how the new pipeline may be used to do this. © 2017 Beckers et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

[Characterization of Black and Dichothrix Cyanobacteria Based on the 16S Ribosomal RNA Gene Sequence

Science.gov (United States)

Ortega, Maya

2010-01-01

My project focuses on characterizing different cyanobacteria in thrombolitic mats found on the island of Highborn Cay, Bahamas. Thrombolites are interesting ecosystems because of the ability of bacteria in these mats to remove carbon dioxide from the atmosphere and mineralize it as calcium carbonate. In the future they may be used as models to develop carbon sequestration technologies, which could be used as part of regenerative life systems in space. These thrombolitic communities are also significant because of their similarities to early communities of life on Earth. I targeted two cyanobacteria in my research, Dichothrix spp. and whatever black is, since they are believed to be important to carbon sequestration in these thrombolitic mats. The goal of my summer research project was to molecularly identify these two cyanobacteria. DNA was isolated from each organism through mat dissections and DNA extractions. I ran Polymerase Chain Reactions (PCR) to amplify the 16S ribosomal RNA (rRNA) gene in each cyanobacteria. This specific gene is found in almost all bacteria and is highly conserved, meaning any changes in the sequence are most likely due to evolution. As a result, the 16S rRNA gene can be used for bacterial identification of different species based on the sequence of their 16S rRNA gene. Since the exact sequence of the Dichothrix gene was unknown, I designed different primers that flanked the gene based on the known sequences from other taxonomically similar cyanobacteria. Once the 16S rRNA gene was amplified, I cloned the gene into specialized Escherichia coli cells and sent the gene products for sequencing. Once the sequence is obtained, it will be added to a genetic database for future reference to and classification of other Dichothrix sp.

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.

JNSViewer-A JavaScript-based Nucleotide Sequence Viewer for DNA/RNA secondary structures.

Science.gov (United States)

Shi, Jieming; Li, Xi; Dong, Min; Graham, Mitchell; Yadav, Nehul; Liang, Chun

2017-01-01

Many tools are available for visualizing RNA or DNA secondary structures, but there is scarce implementation in JavaScript that provides seamless integration with the increasingly popular web computational platforms. We have developed JNSViewer, a highly interactive web service, which is bundled with several popular tools for DNA/RNA secondary structure prediction and can provide precise and interactive correspondence among nucleotides, dot-bracket data, secondary structure graphs, and genic annotations. In JNSViewer, users can perform RNA secondary structure predictions with different programs and settings, add customized genic annotations in GFF format to structure graphs, search for specific linear motifs, and extract relevant structure graphs of sub-sequences. JNSViewer also allows users to choose a transcript or specific segment of Arabidopsis thaliana genome sequences and predict the corresponding secondary structure. Popular genome browsers (i.e., JBrowse and BrowserGenome) were integrated into JNSViewer to provide powerful visualizations of chromosomal locations, genic annotations, and secondary structures. In addition, we used StructureFold with default settings to predict some RNA structures for Arabidopsis by incorporating in vivo high-throughput RNA structure profiling data and stored the results in our web server, which might be a useful resource for RNA secondary structure studies in plants. JNSViewer is available at http://bioinfolab.miamioh.edu/jnsviewer/index.html.

JNSViewer—A JavaScript-based Nucleotide Sequence Viewer for DNA/RNA secondary structures

Science.gov (United States)

Dong, Min; Graham, Mitchell; Yadav, Nehul

2017-01-01

Many tools are available for visualizing RNA or DNA secondary structures, but there is scarce implementation in JavaScript that provides seamless integration with the increasingly popular web computational platforms. We have developed JNSViewer, a highly interactive web service, which is bundled with several popular tools for DNA/RNA secondary structure prediction and can provide precise and interactive correspondence among nucleotides, dot-bracket data, secondary structure graphs, and genic annotations. In JNSViewer, users can perform RNA secondary structure predictions with different programs and settings, add customized genic annotations in GFF format to structure graphs, search for specific linear motifs, and extract relevant structure graphs of sub-sequences. JNSViewer also allows users to choose a transcript or specific segment of Arabidopsis thaliana genome sequences and predict the corresponding secondary structure. Popular genome browsers (i.e., JBrowse and BrowserGenome) were integrated into JNSViewer to provide powerful visualizations of chromosomal locations, genic annotations, and secondary structures. In addition, we used StructureFold with default settings to predict some RNA structures for Arabidopsis by incorporating in vivo high-throughput RNA structure profiling data and stored the results in our web server, which might be a useful resource for RNA secondary structure studies in plants. JNSViewer is available at http://bioinfolab.miamioh.edu/jnsviewer/index.html. PMID:28582416

JNSViewer-A JavaScript-based Nucleotide Sequence Viewer for DNA/RNA secondary structures.

Directory of Open Access Journals (Sweden)

Jieming Shi

Full Text Available Many tools are available for visualizing RNA or DNA secondary structures, but there is scarce implementation in JavaScript that provides seamless integration with the increasingly popular web computational platforms. We have developed JNSViewer, a highly interactive web service, which is bundled with several popular tools for DNA/RNA secondary structure prediction and can provide precise and interactive correspondence among nucleotides, dot-bracket data, secondary structure graphs, and genic annotations. In JNSViewer, users can perform RNA secondary structure predictions with different programs and settings, add customized genic annotations in GFF format to structure graphs, search for specific linear motifs, and extract relevant structure graphs of sub-sequences. JNSViewer also allows users to choose a transcript or specific segment of Arabidopsis thaliana genome sequences and predict the corresponding secondary structure. Popular genome browsers (i.e., JBrowse and BrowserGenome were integrated into JNSViewer to provide powerful visualizations of chromosomal locations, genic annotations, and secondary structures. In addition, we used StructureFold with default settings to predict some RNA structures for Arabidopsis by incorporating in vivo high-throughput RNA structure profiling data and stored the results in our web server, which might be a useful resource for RNA secondary structure studies in plants. JNSViewer is available at http://bioinfolab.miamioh.edu/jnsviewer/index.html.

Extensive 16S rRNA gene sequence diversity in Campylobacter hyointestinalis strains: taxonomic and applied implications

DEFF Research Database (Denmark)

Harrington, C.S.; On, Stephen L.W.

1999-01-01

Phylogenetic relationships of Campylobacter hyointestinalis subspecies were examined by means of 16S rRNA gene sequencing. Sequence similarities among C. hyointestinalis subsp. lawsonii strains exceeded 99.0 %, but values among C. hyointestinalis subsp. hyointestinalis strains ranged from 96...... of the genus Campylobacter, emphasizing the need for multiple strain analysis when using 16S rRNA gene sequence comparisons for taxonomic investigations........4 to 100 %. Sequence similarites between strains representing the two different subspecies ranged from 95.7 to 99.0 %. An intervening sequence was identified in certain of the C. hyointestinalis subsp. lawsonii strains. C. hyointestinalis strains occupied two distinct branches in a phylogenetic analysis...

CoLIde: A bioinformatics tool for CO-expression based small RNA Loci Identification using high-throughput sequencing data

OpenAIRE

Mohorianu, Irina; Stocks, Matthew Benedict; Wood, John; Dalmay, Tamas; Moulton, Vincent

2013-01-01

Small RNAs (sRNAs) are 20–25 nt non-coding RNAs that act as guides for the highly sequence-specific regulatory mechanism known as RNA silencing. Due to the recent increase in sequencing depth, a highly complex and diverse population of sRNAs in both plants and animals has been revealed. However, the exponential increase in sequencing data has also made the identification of individual sRNA transcripts corresponding to biological units (sRNA loci) more challenging when based exclusively on the...

Impact of target mRNA structure on siRNA silencing efficiency: A large-scale study.

Science.gov (United States)

Gredell, Joseph A; Berger, Angela K; Walton, S Patrick

2008-07-01

The selection of active siRNAs is generally based on identifying siRNAs with certain sequence and structural properties. However, the efficiency of RNA interference has also been shown to depend on the structure of the target mRNA, primarily through studies using exogenous transcripts with well-defined secondary structures in the vicinity of the target sequence. While these studies provide a means for examining the impact of target sequence and structure independently, the predicted secondary structures for these transcripts are often not reflective of structures that form in full-length, native mRNAs where interactions can occur between relatively remote segments of the mRNAs. Here, using a combination of experimental results and analysis of a large dataset, we demonstrate that the accessibility of certain local target structures on the mRNA is an important determinant in the gene silencing ability of siRNAs. siRNAs targeting the enhanced green fluorescent protein were chosen using a minimal siRNA selection algorithm followed by classification based on the predicted minimum free energy structures of the target transcripts. Transfection into HeLa and HepG2 cells revealed that siRNAs targeting regions of the mRNA predicted to have unpaired 5'- and 3'-ends resulted in greater gene silencing than regions predicted to have other types of secondary structure. These results were confirmed by analysis of gene silencing data from previously published siRNAs, which showed that mRNA target regions unpaired at either the 5'-end or 3'-end were silenced, on average, approximately 10% more strongly than target regions unpaired in the center or primarily paired throughout. We found this effect to be independent of the structure of the siRNA guide strand. Taken together, these results suggest minimal requirements for nucleation of hybridization between the siRNA guide strand and mRNA and that both mRNA and guide strand structure should be considered when choosing candidate si

NSAMD: A new approach to discover structured contiguous substrings in sequence datasets using Next-Symbol-Array.

Science.gov (United States)

Pari, Abdolvahed; Baraani, Ahmad; Parseh, Saeed

2016-10-01

In many sequence data mining applications, the goal is to find frequent substrings. Some of these applications like extracting motifs in protein and DNA sequences are looking for frequently occurring approximate contiguous substrings called simple motifs. By approximate we mean that some mismatches are allowed during similarity test between substrings, and it helps to discover unknown patterns. Structured motifs in DNA sequences are frequent structured contiguous substrings which contains two or more simple motifs. There are some works that have been done to find simple motifs but these works have problems such as low scalability, high execution time, no guarantee to find all patterns, and low flexibility in adaptation to other application. The Flame is the only algorithm that can find all unknown structured patterns in a dataset and has solved most of these problems but its scalability for very large sequences is still weak. In this research a new approach named Next-Symbol-Array based Motif Discovery (NSAMD) is represented to improve scalability in extracting all unknown simple and structured patterns. To reach this goal a new data structure has been presented called Next-Symbol-Array. This data structure makes change in how to find patterns by NSAMD in comparison with Flame and helps to find structured motif faster. Proposed algorithm is as accurate as Flame and extracts all existing patterns in dataset. Performance comparisons show that NSAMD outperforms Flame in extracting structured motifs in both execution time (51% faster) and memory usage (more than 99%). Proposed algorithm is slower in extracting simple motifs but considerable improvement in memory usage (more than 99%) makes NSAMD more scalable than Flame. This advantage of NSAMD is very important in biological applications in which very large sequences are applied. Copyright © 2016 Elsevier Ltd. All rights reserved.

MicroRNA identity and abundance in porcine skeletal muscles determined by deep sequencing

DEFF Research Database (Denmark)

Nielsen, M; Hansen, J H; Hedegaard, J

2010-01-01

levels of 212 annotated miRNA genes, thereby providing a thorough account of the miRNA transcriptome in porcine muscle tissue. The expression levels displayed a very large range, as reflected by the number of sequence reads, which varied from single counts for rare miRNAs to several million reads...

Sex chromosomes and germline transcriptomics explored by single-cell sequencing and RNA-tomography

NARCIS (Netherlands)

Vértesy, Ábel

2018-01-01

In our study of germ cell differentiation, we applied two recently developed technologies on the germline of various model organisms: single-cell mRNA sequencing and RNA-tomography. For the first time we could look at gene expression with such a high resolution, and this led us to discover the

Characterization of novel precursor miRNAs using next generation sequencing and prediction of miRNA targets in Atlantic halibut.

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Teshome Tilahun Bizuayehu

Full Text Available BACKGROUND: microRNAs (miRNAs are implicated in regulation of many cellular processes. miRNAs are processed to their mature functional form in a step-wise manner by multiple proteins and cofactors in the nucleus and cytoplasm. Many miRNAs are conserved across vertebrates. Mature miRNAs have recently been characterized in Atlantic halibut (Hippoglossus hippoglossus L.. The aim of this study was to identify and characterize precursor miRNA (pre-miRNAs and miRNA targets in this non-model flatfish. Discovery of miRNA precursor forms and targets in non-model organisms is difficult because of limited source information available. Therefore, we have developed a methodology to overcome this limitation. METHODS: Genomic DNA and small transcriptome of Atlantic halibut were sequenced using Roche 454 pyrosequencing and SOLiD next generation sequencing (NGS, respectively. Identified pre- miRNAs were further validated with reverse-transcription PCR. miRNA targets were identified using miRanda and RNAhybrid target prediction tools using sequences from public databases. Some of miRNA targets were also identified using RACE-PCR. miRNA binding sites were validated with luciferase assay using the RTS34st cell line. RESULTS: We obtained more than 1.3 M and 92 M sequence reads from 454 genomic DNA sequencing and SOLiD small RNA sequencing, respectively. We identified 34 known and 9 novel pre-miRNAs. We predicted a number of miRNA target genes involved in various biological pathways. miR-24 binding to kisspeptin 1 receptor-2 (kiss1-r2 was confirmed using luciferase assay. CONCLUSION: This study demonstrates that identification of conserved and novel pre-miRNAs in a non-model vertebrate lacking substantial genomic resources can be performed by combining different next generation sequencing technologies. Our results indicate a wide conservation of miRNA precursors and involvement of miRNA in multiple regulatory pathways, and provide resources for further research on miRNA

Mapping a nucleolar targeting sequence of an RNA binding nucleolar protein, Nop25

International Nuclear Information System (INIS)

Fujiwara, Takashi; Suzuki, Shunji; Kanno, Motoko; Sugiyama, Hironobu; Takahashi, Hisaaki; Tanaka, Junya

2006-01-01

Nop25 is a putative RNA binding nucleolar protein associated with rRNA transcription. The present study was undertaken to determine the mechanism of Nop25 localization in the nucleolus. Deletion experiments of Nop25 amino acid sequence showed Nop25 to contain a nuclear targeting sequence in the N-terminal and a nucleolar targeting sequence in the C-terminal. By expressing derivative peptides from the C-terminal as GFP-fusion proteins in the cells, a lysine and arginine residue-enriched peptide (KRKHPRRAQDSTKKPPSATRTSKTQRRRR) allowed a GFP-fusion protein to be transported and fully retained in the nucleolus. When the peptide was fused with cMyc epitope and expressed in the cells, a cMyc epitope was then detected in the nucleolus. Nop25 did not localize in the nucleolus by deletion of the peptide from Nop25. Furthermore, deletion of a subdomain (KRKHPRRAQ) in the peptide or amino acid substitution of lysine and arginine residues in the subdomain resulted in the loss of Nop25 nucleolar localization. These results suggest that the lysine and arginine residue-enriched peptide is the most prominent nucleolar targeting sequence of Nop25 and that the long stretch of basic residues might play an important role in the nucleolar localization of Nop25. Although Nop25 contained putative SUMOylation, phosphorylation and glycosylation sites, the amino acid substitution in these sites had no effect on the nucleolar localization, thus suggesting that these post-translational modifications did not contribute to the localization of Nop25 in the nucleolus. The treatment of the cells, which expressed a GFP-fusion protein with a nucleolar targeting sequence of Nop25, with RNase A resulted in a complete dislocation of the protein from the nucleolus. These data suggested that the nucleolar targeting sequence might therefore play an important role in the binding of Nop25 to RNA molecules and that the RNA binding of Nop25 might be essential for the nucleolar localization of Nop25

Identification and analysis of pig chimeric mRNAs using RNA sequencing data

Science.gov (United States)

2012-01-01

Background Gene fusion is ubiquitous over the course of evolution. It is expected to increase the diversity and complexity of transcriptomes and proteomes through chimeric sequence segments or altered regulation. However, chimeric mRNAs in pigs remain unclear. Here we identified some chimeric mRNAs in pigs and analyzed the expression of them across individuals and breeds using RNA-sequencing data. Results The present study identified 669 putative chimeric mRNAs in pigs, of which 251 chimeric candidates were detected in a set of RNA-sequencing data. The 618 candidates had clear trans-splicing sites, 537 of which obeyed the canonical GU-AG splice rule. Only two putative pig chimera variants whose fusion junction was overlapped with that of a known human chimeric mRNA were found. A set of unique chimeric events were considered middle variances in the expression across individuals and breeds, and revealed non-significant variance between sexes. Furthermore, the genomic region of the 5′ partner gene shares a similar DNA sequence with that of the 3′ partner gene for 458 putative chimeric mRNAs. The 81 of those shared DNA sequences significantly matched the known DNA-binding motifs in the JASPAR CORE database. Four DNA motifs shared in parental genomic regions had significant similarity with known human CTCF binding sites. Conclusions The present study provided detailed information on some pig chimeric mRNAs. We proposed a model that trans-acting factors, such as CTCF, induced the spatial organisation of parental genes to the same transcriptional factory so that parental genes were coordinatively transcribed to give birth to chimeric mRNAs. PMID:22925561

Identification and analysis of pig chimeric mRNAs using RNA sequencing data

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Ma Lei

2012-08-01

Full Text Available Abstract Background Gene fusion is ubiquitous over the course of evolution. It is expected to increase the diversity and complexity of transcriptomes and proteomes through chimeric sequence segments or altered regulation. However, chimeric mRNAs in pigs remain unclear. Here we identified some chimeric mRNAs in pigs and analyzed the expression of them across individuals and breeds using RNA-sequencing data. Results The present study identified 669 putative chimeric mRNAs in pigs, of which 251 chimeric candidates were detected in a set of RNA-sequencing data. The 618 candidates had clear trans-splicing sites, 537 of which obeyed the canonical GU-AG splice rule. Only two putative pig chimera variants whose fusion junction was overlapped with that of a known human chimeric mRNA were found. A set of unique chimeric events were considered middle variances in the expression across individuals and breeds, and revealed non-significant variance between sexes. Furthermore, the genomic region of the 5′ partner gene shares a similar DNA sequence with that of the 3′ partner gene for 458 putative chimeric mRNAs. The 81 of those shared DNA sequences significantly matched the known DNA-binding motifs in the JASPAR CORE database. Four DNA motifs shared in parental genomic regions had significant similarity with known human CTCF binding sites. Conclusions The present study provided detailed information on some pig chimeric mRNAs. We proposed a model that trans-acting factors, such as CTCF, induced the spatial organisation of parental genes to the same transcriptional factory so that parental genes were coordinatively transcribed to give birth to chimeric mRNAs.

Sequences within the 5' untranslated region regulate the levels of a kinetoplast DNA topoisomerase mRNA during the cell cycle.

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Pasion, S G; Hines, J C; Ou, X; Mahmood, R; Ray, D S

1996-12-01

Gene expression in trypanosomatids appears to be regulated largely at the posttranscriptional level and involves maturation of mRNA precursors by trans splicing of a 39-nucleotide miniexon sequence to the 5' end of the mRNA and cleavage and polyadenylation at the 3' end of the mRNA. To initiate the identification of sequences involved in the periodic expression of DNA replication genes in trypanosomatids, we have mapped splice acceptor sites in the 5' flanking region of the TOP2 gene, which encodes the kinetoplast DNA topoisomerase, and have carried out deletion analysis of this region on a plasmid-encoded TOP2 gene. Block deletions within the 5' untranslated region (UTR) identified two regions (-608 to -388 and -387 to -186) responsible for periodic accumulation of the mRNA. Deletion of one or the other of these sequences had no effect on periodic expression of the mRNA, while deletion of both regions resulted in constitutive expression of the mRNA throughout the cell cycle. Subcloning of these sequences into the 5' UTR of a construct lacking both regions of the TOP2 5' UTR has shown that an octamer consensus sequence present in the 5' UTR of the TOP2, RPA1, and DHFR-TS mRNAs is required for normal cycling of the TOP2 mRNA. Mutation of the consensus octamer sequence in the TOP2 5' UTR in a plasmid construct containing only a single consensus octamer and that shows normal cycling of the plasmid-encoded TOP2 mRNA resulted in substantial reduction of the cycling of the mRNA level. These results imply a negative regulation of TOP2 mRNA during the cell cycle by a mechanism involving redundant elements containing one or more copies of a conserved octamer sequence within the 5' UTR of TOP2 mRNA.

RNA shotgun metagenomic sequencing of northern California (USA mosquitoes uncovers viruses, bacteria, and fungi

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James Angus eChandler

2015-03-01

Full Text Available Mosquitoes, most often recognized for the microbial agents of disease they may carry, harbor diverse microbial communities that include viruses, bacteria, and fungi, collectively called the microbiota. The composition of the microbiota can directly and indirectly affect disease transmission through microbial interactions that could be revealed by its characterization in natural populations of mosquitoes. Furthermore, the use of shotgun metagenomic sequencing (SMS approaches could allow the discovery of unknown members of the microbiota. In this study, we use RNA SMS to characterize the microbiota of seven individual mosquitoes (species include Culex pipiens, Culiseta incidens, and Ochlerotatus sierrensis collected from a variety of habitats in California, USA. Sequencing was performed on the Illumina HiSeq platform and the resulting sequences were quality-checked and assembled into contigs using the A5 pipeline. Sequences related to single stranded RNA viruses of the Bunyaviridae and Rhabdoviridae were uncovered, along with an unclassified genus of double-stranded RNA viruses. Phylogenetic analysis finds that in all three cases, the closest relatives of the identified viral sequences are other mosquito-associated viruses, suggesting widespread host-group specificity among disparate viral taxa. Interestingly, we identified a Narnavirus of fungi, also reported elsewhere in mosquitoes, that potentially demonstrates a nested host-parasite association between virus, fungi, and mosquito. Sequences related to 8 bacterial families and 13 fungal families were found across the seven samples. Bacillus and Escherichia/Shigella were identified in all samples and Wolbachia was identified in all Cx. pipiens samples, while no single fungal genus was found in more than two samples. This study exemplifies the utility of RNA SMS in the characterization of the natural microbiota of mosquitoes and, in particular, the value of identifying all microbes associated with

AllelicImbalance: An R/ bioconductor package for detecting, managing, and visualizing allele expression imbalance data from RNA sequencing

DEFF Research Database (Denmark)

Gådin, Jesper R.; van't Hooft, Ferdinand M.; Eriksson, Per

2015-01-01

the possible biases. Results: We present AllelicImblance, a software program that is designed to detect, manage, and visualize allelic imbalances comprehensively. The purpose of this software is to allow users to pose genetic questions in any RNA sequencing experiment quickly, enhancing the general utility...... of RNA sequencing. The visualization features can reveal notable, non-trivial allelic imbalance behavior over specific regions, such as exons. Conclusions: The software provides a complete framework to perform allelic imbalance analyses of aligned RNA sequencing data, from detection to visualization...

An Efficient Method for Identifying Gene Fusions by Targeted RNA Sequencing from Fresh Frozen and FFPE Samples.

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Jonathan A Scolnick

Full Text Available Fusion genes are known to be key drivers of tumor growth in several types of cancer. Traditionally, detecting fusion genes has been a difficult task based on fluorescent in situ hybridization to detect chromosomal abnormalities. More recently, RNA sequencing has enabled an increased pace of fusion gene identification. However, RNA-Seq is inefficient for the identification of fusion genes due to the high number of sequencing reads needed to detect the small number of fusion transcripts present in cells of interest. Here we describe a method, Single Primer Enrichment Technology (SPET, for targeted RNA sequencing that is customizable to any target genes, is simple to use, and efficiently detects gene fusions. Using SPET to target 5701 exons of 401 known cancer fusion genes for sequencing, we were able to identify known and previously unreported gene fusions from both fresh-frozen and formalin-fixed paraffin-embedded (FFPE tissue RNA in both normal tissue and cancer cells.

Correlation between sequence conservation and structural thermodynamics of microRNA precursors from human, mouse, and chicken genomes

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Wang Shengqi

2010-10-01

Full Text Available Abstract Background Previous studies have shown that microRNA precursors (pre-miRNAs have considerably more stable secondary structures than other native RNAs (tRNA, rRNA, and mRNA and artificial RNA sequences. However, pre-miRNAs with ultra stable secondary structures have not been investigated. It is not known if there is a tendency in pre-miRNA sequences towards or against ultra stable structures? Furthermore, the relationship between the structural thermodynamic stability of pre-miRNA and their evolution remains unclear. Results We investigated the correlation between pre-miRNA sequence conservation and structural stability as measured by adjusted minimum folding free energies in pre-miRNAs isolated from human, mouse, and chicken. The analysis revealed that conserved and non-conserved pre-miRNA sequences had structures with similar average stabilities. However, the relatively ultra stable and unstable pre-miRNAs were more likely to be non-conserved than pre-miRNAs with moderate stability. Non-conserved pre-miRNAs had more G+C than A+U nucleotides, while conserved pre-miRNAs contained more A+U nucleotides. Notably, the U content of conserved pre-miRNAs was especially higher than that of non-conserved pre-miRNAs. Further investigations showed that conserved and non-conserved pre-miRNAs exhibited different structural element features, even though they had comparable levels of stability. Conclusions We proposed that there is a correlation between structural thermodynamic stability and sequence conservation for pre-miRNAs from human, mouse, and chicken genomes. Our analyses suggested that pre-miRNAs with relatively ultra stable or unstable structures were less favoured by natural selection than those with moderately stable structures. Comparison of nucleotide compositions between non-conserved and conserved pre-miRNAs indicated the importance of U nucleotides in the pre-miRNA evolutionary process. Several characteristic structural elements were

High-throughput sequencing of RNA silencing-associated small RNAs in olive (Olea europaea L..

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Livia Donaire

Full Text Available Small RNAs (sRNAs of 20 to 25 nucleotides (nt in length maintain genome integrity and control gene expression in a multitude of developmental and physiological processes. Despite RNA silencing has been primarily studied in model plants, the advent of high-throughput sequencing technologies has enabled profiling of the sRNA component of more than 40 plant species. Here, we used deep sequencing and molecular methods to report the first inventory of sRNAs in olive (Olea europaea L.. sRNA libraries prepared from juvenile and adult shoots revealed that the 24-nt class dominates the sRNA transcriptome and atypically accumulates to levels never seen in other plant species, suggesting an active role of heterochromatin silencing in the maintenance and integrity of its large genome. A total of 18 known miRNA families were identified in the libraries. Also, 5 other sRNAs derived from potential hairpin-like precursors remain as plausible miRNA candidates. RNA blots confirmed miRNA expression and suggested tissue- and/or developmental-specific expression patterns. Target mRNAs of conserved miRNAs were computationally predicted among the olive cDNA collection and experimentally validated through endonucleolytic cleavage assays. Finally, we use expression data to uncover genetic components of the miR156, miR172 and miR390/TAS3-derived trans-acting small interfering RNA (tasiRNA regulatory nodes, suggesting that these interactive networks controlling developmental transitions are fully operational in olive.

AtRTD2: A Reference Transcript Dataset for accurate quantification of alternative splicing and expression changes in Arabidopsis thaliana RNA-seq data

KAUST Repository

Zhang, Runxuan

2016-05-06

Background Alternative splicing is the major post-transcriptional mechanism by which gene expression is regulated and affects a wide range of processes and responses in most eukaryotic organisms. RNA-sequencing (RNA-seq) can generate genome-wide quantification of individual transcript isoforms to identify changes in expression and alternative splicing. RNA-seq is an essential modern tool but its ability to accurately quantify transcript isoforms depends on the diversity, completeness and quality of the transcript information. Results We have developed a new Reference Transcript Dataset for Arabidopsis (AtRTD2) for RNA-seq analysis containing over 82k non-redundant transcripts, whereby 74,194 transcripts originate from 27,667 protein-coding genes. A total of 13,524 protein-coding genes have at least one alternatively spliced transcript in AtRTD2 such that about 60% of the 22,453 protein-coding, intron-containing genes in Arabidopsis undergo alternative splicing. More than 600 putative U12 introns were identified in more than 2,000 transcripts. AtRTD2 was generated from transcript assemblies of ca. 8.5 billion pairs of reads from 285 RNA-seq data sets obtained from 129 RNA-seq libraries and merged along with the previous version, AtRTD, and Araport11 transcript assemblies. AtRTD2 increases the diversity of transcripts and through application of stringent filters represents the most extensive and accurate transcript collection for Arabidopsis to date. We have demonstrated a generally good correlation of alternative splicing ratios from RNA-seq data analysed by Salmon and experimental data from high resolution RT-PCR. However, we have observed inaccurate quantification of transcript isoforms for genes with multiple transcripts which have variation in the lengths of their UTRs. This variation is not effectively corrected in RNA-seq analysis programmes and will therefore impact RNA-seq analyses generally. To address this, we have tested different genome

ESPRIT-Forest: Parallel clustering of massive amplicon sequence data in subquadratic time.

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Cai, Yunpeng; Zheng, Wei; Yao, Jin; Yang, Yujie; Mai, Volker; Mao, Qi; Sun, Yijun

2017-04-01

The rapid development of sequencing technology has led to an explosive accumulation of genomic sequence data. Clustering is often the first step to perform in sequence analysis, and hierarchical clustering is one of the most commonly used approaches for this purpose. However, it is currently computationally expensive to perform hierarchical clustering of extremely large sequence datasets due to its quadratic time and space complexities. In this paper we developed a new algorithm called ESPRIT-Forest for parallel hierarchical clustering of sequences. The algorithm achieves subquadratic time and space complexity and maintains a high clustering accuracy comparable to the standard method. The basic idea is to organize sequences into a pseudo-metric based partitioning tree for sub-linear time searching of nearest neighbors, and then use a new multiple-pair merging criterion to construct clusters in parallel using multiple threads. The new algorithm was tested on the human microbiome project (HMP) dataset, currently one of the largest published microbial 16S rRNA sequence dataset. Our experiment demonstrated that with the power of parallel computing it is now compu- tationally feasible to perform hierarchical clustering analysis of tens of millions of sequences. The software is available at http://www.acsu.buffalo.edu/∼yijunsun/lab/ESPRIT-Forest.html.

The nucleotide sequence of RNA1 of Lettuce big-vein virus, genus Varicosavirus, reveals its relation to nonsegmented negative-strand RNA viruses.

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Sasaya, Takahide; Ishikawa, Koichi; Koganezawa, Hiroki

2002-06-05

The complete nucleotide sequence of RNA1 from Lettuce big-vein virus (LBVV), the type member of the genus Varicosavirus, was determined. LBVV RNA1 consists of 6797 nucleotides and contains one large ORF that encodes a large (L) protein of 2040 amino acids with a predicted M(r) of 232,092. Northern blot hybridization analysis indicated that the LBVV RNA1 is a negative-sense RNA. Database searches showed that the amino acid sequence of L protein is homologous to those of L polymerases of nonsegmented negative-strand RNA viruses. A cluster dendrogram derived from alignments of the LBVV L protein and the L polymerases indicated that the L protein is most closely related to the L polymerases of plant rhabdoviruses. Transcription termination/polyadenylation signal-like poly(U) tracts that resemble those in rhabdovirus and paramyxovirus RNAs were present upstream and downstream of the coding region. Although LBVV is related to rhabdoviruses, a key distinguishing feature is that the genome of LBVV is segmented. The results reemphasize the need to reconsider the taxonomic position of varicosaviruses.

An RNA-Seq strategy to detect the complete coding and non-coding transcriptome including full-length imprinted macro ncRNAs.

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Ru Huang

Full Text Available Imprinted macro non-protein-coding (nc RNAs are cis-repressor transcripts that silence multiple genes in at least three imprinted gene clusters in the mouse genome. Similar macro or long ncRNAs are abundant in the mammalian genome. Here we present the full coding and non-coding transcriptome of two mouse tissues: differentiated ES cells and fetal head using an optimized RNA-Seq strategy. The data produced is highly reproducible in different sequencing locations and is able to detect the full length of imprinted macro ncRNAs such as Airn and Kcnq1ot1, whose length ranges between 80-118 kb. Transcripts show a more uniform read coverage when RNA is fragmented with RNA hydrolysis compared with cDNA fragmentation by shearing. Irrespective of the fragmentation method, all coding and non-coding transcripts longer than 8 kb show a gradual loss of sequencing tags towards the 3' end. Comparisons to published RNA-Seq datasets show that the strategy presented here is more efficient in detecting known functional imprinted macro ncRNAs and also indicate that standardization of RNA preparation protocols would increase the comparability of the transcriptome between different RNA-Seq datasets.

Next-generation small RNA sequencing for microRNAs profiling in the honey bee Apis mellifera.

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Chen, X; Yu, X; Cai, Y; Zheng, H; Yu, D; Liu, G; Zhou, Q; Hu, S; Hu, F

2010-12-01

MicroRNAs (miRNAs) are key regulators in various physiological and pathological processes via post-transcriptional regulation of gene expression. The honey bee (Apis mellifera) is a key model for highly social species, and its complex social behaviour can be interpreted theoretically as changes in gene regulation, in which miRNAs are thought to be involved. We used the SOLiD sequencing system to identify the repertoire of miRNAs in the honey bee by sequencing a mixed small RNA library from different developmental stages. We obtained a total of 36,796,459 raw sequences; of which 5,491,100 short sequences were fragments of mRNA and other noncoding RNAs (ncRNA), and 1,759,346 reads mapped to the known miRNAs. We predicted 267 novel honey bee miRNAs representing 380,182 short reads, including eight miRNAs of other insects in 14,107,583 genome-mapped sequences. We verified 50 of them using stem-loop reverse-transcription PCR (RT-PCR), in which 35 yielded PCR products. Cross-species analyses showed 81 novel miRNAs with homologues in other insects, suggesting that they were authentic miRNAs and have similar functions. The results of this study provide a basis for studies of the miRNA-modulating networks in development and some intriguing phenomena such as caste differentiation in A. mellifera. © 2010 The Authors. Insect Molecular Biology © 2010 The Royal Entomological Society.

Comparing sequencing assays and human-machine analyses in actionable genomics for glioblastoma.

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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.

A short autocomplementary sequence plays an essential role in avian sarcoma-leukosis virus RNA dimerization.

Science.gov (United States)

Fossé, P; Motté, N; Roumier, A; Gabus, C; Muriaux, D; Darlix, J L; Paoletti, J

1996-12-24

Retroviral genomes consist of two identical RNA molecules joined noncovalently near their 5'-ends. Recently, two models have been proposed for RNA dimer formation on the basis of results obtained in vitro with human immunodeficiency virus type 1 RNA and Moloney murine leukemia virus RNA. It was first proposed that viral RNA dimerizes by forming an interstrand quadruple helix with purine tetrads. The second model postulates that RNA dimerization is initiated by a loop-loop interaction between the two RNA molecules. In order to better characterize the dimerization process of retroviral genomic RNA, we analyzed the in vitro dimerization of avian sarcoma-leukosis virus (ASLV) RNA using different transcripts. We determined the requirements for heterodimer formation, the thermal dissociation of RNA dimers, and the influence of antisense DNA oligonucleotides on dimer formation. Our results strongly suggest that purine tetrads are not involved in dimer formation. Data show that an autocomplementary sequence located upstream from the splice donor site and within a major packaging signal plays a crucial role in ASLV RNA dimer formation in vitro. This sequence is able to form a stem-loop structure, and phylogenetic analysis reveals that it is conserved in 28 different avian sarcoma and leukosis viruses. These results suggest that dimerization of ASLV RNA is initiated by a loop-loop interaction between two RNA molecules and provide an additional argument for the ubiquity of the dimerization process via loop-loop interaction.

Elucidating MicroRNA Regulatory Networks Using Transcriptional, Post-transcriptional, and Histone Modification Measurements

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Sara J.C. Gosline

2016-01-01

Full Text Available MicroRNAs (miRNAs regulate diverse biological processes by repressing mRNAs, but their modest effects on direct targets, together with their participation in larger regulatory networks, make it challenging to delineate miRNA-mediated effects. Here, we describe an approach to characterizing miRNA-regulatory networks by systematically profiling transcriptional, post-transcriptional and epigenetic activity in a pair of isogenic murine fibroblast cell lines with and without Dicer expression. By RNA sequencing (RNA-seq and CLIP (crosslinking followed by immunoprecipitation sequencing (CLIP-seq, we found that most of the changes induced by global miRNA loss occur at the level of transcription. We then introduced a network modeling approach that integrated these data with epigenetic data to identify specific miRNA-regulated transcription factors that explain the impact of miRNA perturbation on gene expression. In total, we demonstrate that combining multiple genome-wide datasets spanning diverse regulatory modes enables accurate delineation of the downstream miRNA-regulated transcriptional network and establishes a model for studying similar networks in other systems.

Complete genome sequencing of the luminescent bacterium, Vibrio qinghaiensis sp. Q67 using PacBio technology

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Gong, Liang; Wu, Yu; Jian, Qijie; Yin, Chunxiao; Li, Taotao; Gupta, Vijai Kumar; Duan, Xuewu; Jiang, Yueming

2018-01-01

Vibrio qinghaiensis sp.-Q67 (Vqin-Q67) is a freshwater luminescent bacterium that continuously emits blue-green light (485 nm). The bacterium has been widely used for detecting toxic contaminants. Here, we report the complete genome sequence of Vqin-Q67, obtained using third-generation PacBio sequencing technology. Continuous long reads were attained from three PacBio sequencing runs and reads >500 bp with a quality value of >0.75 were merged together into a single dataset. This resultant highly-contiguous de novo assembly has no genome gaps, and comprises two chromosomes with substantial genetic information, including protein-coding genes, non-coding RNA, transposon and gene islands. Our dataset can be useful as a comparative genome for evolution and speciation studies, as well as for the analysis of protein-coding gene families, the pathogenicity of different Vibrio species in fish, the evolution of non-coding RNA and transposon, and the regulation of gene expression in relation to the bioluminescence of Vqin-Q67.

Annotating the protein-RNA interaction sites in proteins using evolutionary information and protein backbone structure.

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Li, Tao; Li, Qian-Zhong

2012-11-07

RNA-protein interactions play important roles in various biological processes. The precise detection of RNA-protein interaction sites is very important for understanding essential biological processes and annotating the function of the proteins. In this study, based on various features from amino acid sequence and structure, including evolutionary information, solvent accessible surface area and torsion angles (φ, ψ) in the backbone structure of the polypeptide chain, a computational method for predicting RNA-binding sites in proteins is proposed. When the method is applied to predict RNA-binding sites in three datasets: RBP86 containing 86 protein chains, RBP107 containing 107 proteins chains and RBP109 containing 109 proteins chains, better sensitivities and specificities are obtained compared to previously published methods in five-fold cross-validation tests. In order to make further examination for the efficiency of our method, the RBP107 dataset is used as training set, RBP86 and RBP109 datasets are used as the independent test sets. In addition, as examples of our prediction, RNA-binding sites in a few proteins are presented. The annotated results are consistent with the PDB annotation. These results show that our method is useful for annotating RNA binding sites of novel proteins.

Identification of microRNA-Like RNAs in the filamentous fungus Trichoderma reesei by solexa sequencing.

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Kang Kang

Full Text Available microRNAs (miRNAs are non-coding small RNAs (sRNAs capable of negatively regulating gene expression. Recently, microRNA-like small RNAs (milRNAs were discovered in several filamentous fungi but not yet in Trichoderma reesei, an industrial filamentous fungus that can secrete abundant hydrolases. To explore the presence of milRNA in T. reesei and evaluate their expression under induction of cellulose, two T. reesei sRNA libraries of cellulose induction (IN and non-induction (CON were generated and sequenced using Solexa sequencing technology. A total of 726 and 631 sRNAs were obtained from the IN and CON samples, respectively. Global expression analysis showed an extensively differential expression of sRNAs in T. reesei under the two conditions. Thirteen predicted milRNAs were identified in T. reesei based on the short hairpin structure analysis. The milRNA profiles obtained in deep sequencing were further validated by RT-qPCR assay. Computational analysis predicted a number of potential targets relating to many processes including regulation of enzyme expression. The presence and differential expression of T. reesei milRNAs imply that milRNA might play a role in T. reesei growth and cellulase induction. This work lays foundation for further functional study of fungal milRNAs and their industrial application.

Predicting protein-binding RNA nucleotides with consideration of binding partners.

Science.gov (United States)

Tuvshinjargal, Narankhuu; Lee, Wook; Park, Byungkyu; Han, Kyungsook

2015-06-01

In recent years several computational methods have been developed to predict RNA-binding sites in protein. Most of these methods do not consider interacting partners of a protein, so they predict the same RNA-binding sites for a given protein sequence even if the protein binds to different RNAs. Unlike the problem of predicting RNA-binding sites in protein, the problem of predicting protein-binding sites in RNA has received little attention mainly because it is much more difficult and shows a lower accuracy on average. In our previous study, we developed a method that predicts protein-binding nucleotides from an RNA sequence. In an effort to improve the prediction accuracy and usefulness of the previous method, we developed a new method that uses both RNA and protein sequence data. In this study, we identified effective features of RNA and protein molecules and developed a new support vector machine (SVM) model to predict protein-binding nucleotides from RNA and protein sequence data. The new model that used both protein and RNA sequence data achieved a sensitivity of 86.5%, a specificity of 86.2%, a positive predictive value (PPV) of 72.6%, a negative predictive value (NPV) of 93.8% and Matthews correlation coefficient (MCC) of 0.69 in a 10-fold cross validation; it achieved a sensitivity of 58.8%, a specificity of 87.4%, a PPV of 65.1%, a NPV of 84.2% and MCC of 0.48 in independent testing. For comparative purpose, we built another prediction model that used RNA sequence data alone and ran it on the same dataset. In a 10 fold-cross validation it achieved a sensitivity of 85.7%, a specificity of 80.5%, a PPV of 67.7%, a NPV of 92.2% and MCC of 0.63; in independent testing it achieved a sensitivity of 67.7%, a specificity of 78.8%, a PPV of 57.6%, a NPV of 85.2% and MCC of 0.45. In both cross-validations and independent testing, the new model that used both RNA and protein sequences showed a better performance than the model that used RNA sequence data alone in

Discovery and validation of Barrett's esophagus microRNA transcriptome by next generation sequencing.

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Ajay Bansal

Full Text Available Barrett's esophagus (BE is transition from squamous to columnar mucosa as a result of gastroesophageal reflux disease (GERD. The role of microRNA during this transition has not been systematically studied.For initial screening, total RNA from 5 GERD and 6 BE patients was size fractionated. RNA <70 nucleotides was subjected to SOLiD 3 library preparation and next generation sequencing (NGS. Bioinformatics analysis was performed using R package "DEseq". A p value<0.05 adjusted for a false discovery rate of 5% was considered significant. NGS-identified miRNA were validated using qRT-PCR in an independent group of 40 GERD and 27 BE patients. MicroRNA expression of human BE tissues was also compared with three BE cell lines.NGS detected 19.6 million raw reads per sample. 53.1% of filtered reads mapped to miRBase version 18. NGS analysis followed by qRT-PCR validation found 10 differentially expressed miRNA; several are novel (-708-5p, -944, -224-5p and -3065-5p. Up- or down- regulation predicted by NGS was matched by qRT-PCR in every case. Human BE tissues and BE cell lines showed a high degree of concordance (70-80% in miRNA expression. Prediction analysis identified targets that mapped to developmental signaling pathways such as TGFβ and Notch and inflammatory pathways such as toll-like receptor signaling and TGFβ. Cluster analysis found similarly regulated (up or down miRNA to share common targets suggesting coordination between miRNA.Using highly sensitive next-generation sequencing, we have performed a comprehensive genome wide analysis of microRNA in BE and GERD patients. Differentially expressed miRNA between BE and GERD have been further validated. Expression of miRNA between BE human tissues and BE cell lines are highly correlated. These miRNA should be studied in biological models to further understand BE development.

Import of desired nucleic acid sequences using addressing motif of mitochondrial ribosomal 5S-rRNA for fluorescent in vivo hybridization of mitochondrial DNA and RNA.

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Zelenka, Jaroslav; Alán, Lukáš; Jabůrek, Martin; Ježek, Petr

2014-04-01

Based on the matrix-addressing sequence of mitochondrial ribosomal 5S-rRNA (termed MAM), which is naturally imported into mitochondria, we have constructed an import system for in vivo targeting of mitochondrial DNA (mtDNA) or mt-mRNA, in order to provide fluorescence hybridization of the desired sequences. Thus DNA oligonucleotides were constructed, containing the 5'-flanked T7 RNA polymerase promoter. After in vitro transcription and fluorescent labeling with Alexa Fluor(®) 488 or 647 dye, we obtained the fluorescent "L-ND5 probe" containing MAM and exemplar cargo, i.e., annealing sequence to a short portion of ND5 mRNA and to the light-strand mtDNA complementary to the heavy strand nd5 mt gene (5'-end 21 base pair sequence). For mitochondrial in vivo fluorescent hybridization, HepG2 cells were treated with dequalinium micelles, containing the fluorescent probes, bringing the probes proximally to the mitochondrial outer membrane and to the natural import system. A verification of import into the mitochondrial matrix of cultured HepG2 cells was provided by confocal microscopy colocalizations. Transfections using lipofectamine or probes without 5S-rRNA addressing MAM sequence or with MAM only were ineffective. Alternatively, the same DNA oligonucleotides with 5'-CACC overhang (substituting T7 promoter) were transcribed from the tetracycline-inducible pENTRH1/TO vector in human embryonic kidney T-REx®-293 cells, while mitochondrial matrix localization after import of the resulting unlabeled RNA was detected by PCR. The MAM-containing probe was then enriched by three-order of magnitude over the natural ND5 mRNA in the mitochondrial matrix. In conclusion, we present a proof-of-principle for mitochondrial in vivo hybridization and mitochondrial nucleic acid import.

Determining RNA quality for NextGen sequencing: some exceptions to the gold standard rule of 23S to 16S rRNA ratio

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Using next-generation-sequencing technology to assess entire transcriptomes requires high quality starting RNA. Currently, RNA quality is routinely judged using automated microfluidic gel electrophoresis platforms and associated algorithms. Here we report that such automated methods generate false-n...

Sequence-engineered mRNA Without Chemical Nucleoside Modifications Enables an Effective Protein Therapy in Large Animals

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Thess, Andreas; Grund, Stefanie; Mui, Barbara L; Hope, Michael J; Baumhof, Patrick; Fotin-Mleczek, Mariola; Schlake, Thomas

2015-01-01

Being a transient carrier of genetic information, mRNA could be a versatile, flexible, and safe means for protein therapies. While recent findings highlight the enormous therapeutic potential of mRNA, evidence that mRNA-based protein therapies are feasible beyond small animals such as mice is still lacking. Previous studies imply that mRNA therapeutics require chemical nucleoside modifications to obtain sufficient protein expression and avoid activation of the innate immune system. Here we show that chemically unmodified mRNA can achieve those goals as well by applying sequence-engineered molecules. Using erythropoietin (EPO) driven production of red blood cells as the biological model, engineered Epo mRNA elicited meaningful physiological responses from mice to nonhuman primates. Even in pigs of about 20 kg in weight, a single adequate dose of engineered mRNA encapsulated in lipid nanoparticles (LNPs) induced high systemic Epo levels and strong physiological effects. Our results demonstrate that sequence-engineered mRNA has the potential to revolutionize human protein therapies. PMID:26050989

Ebola virus RNA editing depends on the primary editing site sequence and an upstream secondary structure.

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Masfique Mehedi

Full Text Available Ebolavirus (EBOV, the causative agent of a severe hemorrhagic fever and a biosafety level 4 pathogen, increases its genome coding capacity by producing multiple transcripts encoding for structural and nonstructural glycoproteins from a single gene. This is achieved through RNA editing, during which non-template adenosine residues are incorporated into the EBOV mRNAs at an editing site encoding for 7 adenosine residues. However, the mechanism of EBOV RNA editing is currently not understood. In this study, we report for the first time that minigenomes containing the glycoprotein gene editing site can undergo RNA editing, thereby eliminating the requirement for a biosafety level 4 laboratory to study EBOV RNA editing. Using a newly developed dual-reporter minigenome, we have characterized the mechanism of EBOV RNA editing, and have identified cis-acting sequences that are required for editing, located between 9 nt upstream and 9 nt downstream of the editing site. Moreover, we show that a secondary structure in the upstream cis-acting sequence plays an important role in RNA editing. EBOV RNA editing is glycoprotein gene-specific, as a stretch encoding for 7 adenosine residues located in the viral polymerase gene did not serve as an editing site, most likely due to an absence of the necessary cis-acting sequences. Finally, the EBOV protein VP30 was identified as a trans-acting factor for RNA editing, constituting a novel function for this protein. Overall, our results provide novel insights into the RNA editing mechanism of EBOV, further understanding of which might result in novel intervention strategies against this viral pathogen.

Ebola virus RNA editing depends on the primary editing site sequence and an upstream secondary structure.

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Mehedi, Masfique; Hoenen, Thomas; Robertson, Shelly; Ricklefs, Stacy; Dolan, Michael A; Taylor, Travis; Falzarano, Darryl; Ebihara, Hideki; Porcella, Stephen F; Feldmann, Heinz

2013-01-01

Ebolavirus (EBOV), the causative agent of a severe hemorrhagic fever and a biosafety level 4 pathogen, increases its genome coding capacity by producing multiple transcripts encoding for structural and nonstructural glycoproteins from a single gene. This is achieved through RNA editing, during which non-template adenosine residues are incorporated into the EBOV mRNAs at an editing site encoding for 7 adenosine residues. However, the mechanism of EBOV RNA editing is currently not understood. In this study, we report for the first time that minigenomes containing the glycoprotein gene editing site can undergo RNA editing, thereby eliminating the requirement for a biosafety level 4 laboratory to study EBOV RNA editing. Using a newly developed dual-reporter minigenome, we have characterized the mechanism of EBOV RNA editing, and have identified cis-acting sequences that are required for editing, located between 9 nt upstream and 9 nt downstream of the editing site. Moreover, we show that a secondary structure in the upstream cis-acting sequence plays an important role in RNA editing. EBOV RNA editing is glycoprotein gene-specific, as a stretch encoding for 7 adenosine residues located in the viral polymerase gene did not serve as an editing site, most likely due to an absence of the necessary cis-acting sequences. Finally, the EBOV protein VP30 was identified as a trans-acting factor for RNA editing, constituting a novel function for this protein. Overall, our results provide novel insights into the RNA editing mechanism of EBOV, further understanding of which might result in novel intervention strategies against this viral pathogen.

Genome-Wide Analysis of Gene and microRNA Expression in Diploid and Autotetraploid Paulownia fortunei (Seem Hemsl. under Drought Stress by Transcriptome, microRNA, and Degradome Sequencing

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Zhenli Zhao

2018-02-01

Full Text Available Drought is a common and recurring climatic condition in many parts of the world, and it can have disastrous impacts on plant growth and development. Many genes involved in the drought response of plants have been identified. Transcriptome, microRNA (miRNA, and degradome analyses are rapid ways of identifying drought-responsive genes. The reference genome sequence of Paulownia fortunei (Seem Hemsl. is now available, which makes it easier to explore gene expression, transcriptional regulation, and post-transcriptional in this species. In this study, four transcriptome, small RNA, and degradome libraries were sequenced by Illumina sequencing, respectively. A total of 258 genes and 11 miRNAs were identified for drought-responsive genes and miRNAs in P. fortunei. Degradome sequencing detected 28 miRNA target genes that were cleaved by members of nine conserved miRNA families and 12 novel miRNAs. The results here will contribute toward enriching our understanding of the response of Paulownia fortunei trees to drought stress and may provide new direction for further experimental studies related the development of molecular markers, the genetic map construction, and other genomic research projects in Paulownia.

Evolution of the RNase P RNA structural domain in Leptospira spp.

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Ravishankar, Vigneshwaran; Ahmed, Ahmed; Sivagnanam, Ulaganathan; Muthuraman, Krishnaraja; Karthikaichamy, Anbarasu; Wilson, Herald A; Devendran, Ajay; Hartskeerl, Rudy A; Raj, Stephen M L

2014-12-01

We have employed the RNase P RNA (RPR) gene, which is present as single copy in chromosome I of Leptospira spp. to investigate the phylogeny of structural domains present in the RNA subunit of the tRNA processing enzyme, RNase P. RPR gene sequences of 150 strains derived from NCBI database along with sequences determined from 8 reference strains were examined to fathom strain specific structural differences present in leptospiral RPR. Sequence variations in the RPR gene impacted on the configuration of loops, stems and bulges found in the RPR highlighting species and strain specific structural motifs. In vitro transcribed leptospiral RPR ribozymes are demonstrated to process pre-tRNA into mature tRNA in consonance with the positioning of Leptospira in the taxonomic domain of bacteria. RPR sequence datasets used to construct a phylogenetic tree exemplified the segregation of strains into their respective lineages with a (re)speciation of strain SH 9 to Leptospira borgpetersenii, strains Fiocruz LV 3954 and Fiocruz LV 4135 to Leptospira santarosai, strain CBC 613 to Leptospira kirschneri and strain HAI 1536 to Leptospira noguchii. Furthermore, it allowed characterization of an isolate P2653, presumptively characterized as either serovar Hebdomadis, Kremastos or Longnan to Leptospira weilii, serovar Longnan. Copyright © 2014 Institut Pasteur. Published by Elsevier Masson SAS. All rights reserved.

CoverageAnalyzer (CAn: A Tool for Inspection of Modification Signatures in RNA Sequencing Profiles

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Ralf Hauenschild

2016-11-01

Full Text Available Combination of reverse transcription (RT and deep sequencing has emerged as a powerful instrument for the detection of RNA modifications, a field that has seen a recent surge in activity because of its importance in gene regulation. Recent studies yielded high-resolution RT signatures of modified ribonucleotides relying on both sequence-dependent mismatch patterns and reverse transcription arrests. Common alignment viewers lack specialized functionality, such as filtering, tailored visualization, image export and differential analysis. Consequently, the community will profit from a platform seamlessly connecting detailed visual inspection of RT signatures and automated screening for modification candidates. CoverageAnalyzer (CAn was developed in response to the demand for a powerful inspection tool. It is freely available for all three main operating systems. With SAM file format as standard input, CAn is an intuitive and user-friendly tool that is generally applicable to the large community of biomedical users, starting from simple visualization of RNA sequencing (RNA-Seq data, up to sophisticated modification analysis with significance-based modification candidate calling.

Selective amplification and sequencing of cyclic phosphate-containing RNAs by the cP-RNA-seq method.

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Honda, Shozo; Morichika, Keisuke; Kirino, Yohei

2016-03-01

RNA digestions catalyzed by many ribonucleases generate RNA fragments that contain a 2',3'-cyclic phosphate (cP) at their 3' termini. However, standard RNA-seq methods are unable to accurately capture cP-containing RNAs because the cP inhibits the adapter ligation reaction. We recently developed a method named cP-RNA-seq that is able to selectively amplify and sequence cP-containing RNAs. Here we describe the cP-RNA-seq protocol in which the 3' termini of all RNAs, except those containing a cP, are cleaved through a periodate treatment after phosphatase treatment; hence, subsequent adapter ligation and cDNA amplification steps are exclusively applied to cP-containing RNAs. cP-RNA-seq takes ∼6 d, excluding the time required for sequencing and bioinformatics analyses, which are not covered in detail in this protocol. Biochemical validation of the existence of cP in the identified RNAs takes ∼3 d. Even though the cP-RNA-seq method was developed to identify angiogenin-generating 5'-tRNA halves as a proof of principle, the method should be applicable to global identification of cP-containing RNA repertoires in various transcriptomes.

Deep sequencing of subseafloor eukaryotic rRNA reveals active Fungi across marine subsurface provinces.

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William Orsi

Full Text Available The deep marine subsurface is a vast habitat for microbial life where cells may live on geologic timescales. Because DNA in sediments may be preserved on long timescales, ribosomal RNA (rRNA is suggested to be a proxy for the active fraction of a microbial community in the subsurface. During an investigation of eukaryotic 18S rRNA by amplicon pyrosequencing, unique profiles of Fungi were found across a range of marine subsurface provinces including ridge flanks, continental margins, and abyssal plains. Subseafloor fungal populations exhibit statistically significant correlations with total organic carbon (TOC, nitrate, sulfide, and dissolved inorganic carbon (DIC. These correlations are supported by terminal restriction length polymorphism (TRFLP analyses of fungal rRNA. Geochemical correlations with fungal pyrosequencing and TRFLP data from this geographically broad sample set suggests environmental selection of active Fungi in the marine subsurface. Within the same dataset, ancient rRNA signatures were recovered from plants and diatoms in marine sediments ranging from 0.03 to 2.7 million years old, suggesting that rRNA from some eukaryotic taxa may be much more stable than previously considered in the marine subsurface.

Profiling microRNA expression in bovine alveolar macrophages using RNA-seq.

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Vegh, Peter; Foroushani, Amir B K; Magee, David A; McCabe, Matthew S; Browne, John A; Nalpas, Nicolas C; Conlon, Kevin M; Gordon, Stephen V; Bradley, Daniel G; MacHugh, David E; Lynn, David J

2013-10-01

MicroRNAs (miRNAs) are important regulators of gene expression and are known to play a key role in regulating both adaptive and innate immunity. Bovine alveolar macrophages (BAMs) help maintain lung homeostasis and constitute the front line of host defense against several infectious respiratory diseases, such as bovine tuberculosis. Little is known, however, about the role miRNAs play in these cells. In this study, we used a high-throughput sequencing approach, RNA-seq, to determine the expression levels of known and novel miRNAs in unchallenged BAMs isolated from lung lavages of eight different healthy Holstein-Friesian male calves. Approximately 80 million sequence reads were generated from eight BAM miRNA Illumina sequencing libraries, and 80 miRNAs were identified as being expressed in BAMs at a threshold of at least 100 reads per million (RPM). The expression levels of miRNAs varied over a large dynamic range, with a few miRNAs expressed at very high levels (up to 800,000RPM), and the majority lowly expressed. Notably, many of the most highly expressed miRNAs in BAMs have known roles in regulating immunity in other species (e.g. bta-let-7i, bta-miR-21, bta-miR-27, bta-miR-99b, bta-miR-146, bta-miR-147, bta-miR-155 and bta-miR-223). The most highly expressed miRNA in BAMs was miR-21, which has been shown to regulate the expression of antimicrobial peptides in Mycobacterium leprae-infected human monocytes. Furthermore, the predicted target genes of BAM-expressed miRNAs were found to be statistically enriched for roles in innate immunity. In addition to profiling the expression of known miRNAs, the RNA-seq data was also analysed to identify potentially novel bovine miRNAs. One putatively novel bovine miRNA was identified. To the best of our knowledge, this is the first RNA-seq study to profile miRNA expression in BAMs and provides an important reference dataset for investigating the regulatory roles miRNAs play in this important immune cell type. Copyright �

Full Genome Sequence and sfRNA Interferon Antagonist Activity of Zika Virus from Recife, Brazil.

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Claire L Donald

2016-10-01

Full Text Available The outbreak of Zika virus (ZIKV in the Americas has transformed a previously obscure mosquito-transmitted arbovirus of the Flaviviridae family into a major public health concern. Little is currently known about the evolution and biology of ZIKV and the factors that contribute to the associated pathogenesis. Determining genomic sequences of clinical viral isolates and characterization of elements within these are an important prerequisite to advance our understanding of viral replicative processes and virus-host interactions.We obtained a ZIKV isolate from a patient who presented with classical ZIKV-associated symptoms, and used high throughput sequencing and other molecular biology approaches to determine its full genome sequence, including non-coding regions. Genome regions were characterized and compared to the sequences of other isolates where available. Furthermore, we identified a subgenomic flavivirus RNA (sfRNA in ZIKV-infected cells that has antagonist activity against RIG-I induced type I interferon induction, with a lesser effect on MDA-5 mediated action.The full-length genome sequence including non-coding regions of a South American ZIKV isolate from a patient with classical symptoms will support efforts to develop genetic tools for this virus. Detection of sfRNA that counteracts interferon responses is likely to be important for further understanding of pathogenesis and virus-host interactions.

Escherichia coli promoter sequences predict in vitro RNA polymerase selectivity.

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Mulligan, M E; Hawley, D K; Entriken, R; McClure, W R

1984-01-11

We describe a simple algorithm for computing a homology score for Escherichia coli promoters based on DNA sequence alone. The homology score was related to 31 values, measured in vitro, of RNA polymerase selectivity, which we define as the product KBk2, the apparent second order rate constant for open complex formation. We found that promoter strength could be predicted to within a factor of +/-4.1 in KBk2 over a range of 10(4) in the same parameter. The quantitative evaluation was linked to an automated (Apple II) procedure for searching and evaluating possible promoters in DNA sequence files.

Molecular-Sized DNA or RNA Sequencing Machine | NCI Technology Transfer Center | TTC

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The National Cancer Institute's Gene Regulation and Chromosome Biology Laboratory is seeking statements of capability or interest from parties interested in collaborative research to co-develop a molecular-sized DNA or RNA sequencing machine.

Avian reovirus L2 genome segment sequences and predicted structure/function of the encoded RNA-dependent RNA polymerase protein

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Xu Wanhong

2008-12-01

Full Text Available Abstract Background The orthoreoviruses are infectious agents that possess a genome comprised of 10 double-stranded RNA segments encased in two concentric protein capsids. Like virtually all RNA viruses, an RNA-dependent RNA polymerase (RdRp enzyme is required for viral propagation. RdRp sequences have been determined for the prototype mammalian orthoreoviruses and for several other closely-related reoviruses, including aquareoviruses, but have not yet been reported for any avian orthoreoviruses. Results We determined the L2 genome segment nucleotide sequences, which encode the RdRp proteins, of two different avian reoviruses, strains ARV138 and ARV176 in order to define conserved and variable regions within reovirus RdRp proteins and to better delineate structure/function of this important enzyme. The ARV138 L2 genome segment was 3829 base pairs long, whereas the ARV176 L2 segment was 3830 nucleotides long. Both segments were predicted to encode λB RdRp proteins 1259 amino acids in length. Alignments of these newly-determined ARV genome segments, and their corresponding proteins, were performed with all currently available homologous mammalian reovirus (MRV and aquareovirus (AqRV genome segment and protein sequences. There was ~55% amino acid identity between ARV λB and MRV λ3 proteins, making the RdRp protein the most highly conserved of currently known orthoreovirus proteins, and there was ~28% identity between ARV λB and homologous MRV and AqRV RdRp proteins. Predictive structure/function mapping of identical and conserved residues within the known MRV λ3 atomic structure indicated most identical amino acids and conservative substitutions were located near and within predicted catalytic domains and lining RdRp channels, whereas non-identical amino acids were generally located on the molecule's surfaces. Conclusion The ARV λB and MRV λ3 proteins showed the highest ARV:MRV identity values (~55% amongst all currently known ARV and MRV

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

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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.

Sequence-based heuristics for faster annotation of non-coding RNA families.

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Weinberg, Zasha; Ruzzo, Walter L

2006-01-01

Non-coding RNAs (ncRNAs) are functional RNA molecules that do not code for proteins. Covariance Models (CMs) are a useful statistical tool to find new members of an ncRNA gene family in a large genome database, using both sequence and, importantly, RNA secondary structure information. Unfortunately, CM searches are extremely slow. Previously, we created rigorous filters, which provably sacrifice none of a CM's accuracy, while making searches significantly faster for virtually all ncRNA families. However, these rigorous filters make searches slower than heuristics could be. In this paper we introduce profile HMM-based heuristic filters. We show that their accuracy is usually superior to heuristics based on BLAST. Moreover, we compared our heuristics with those used in tRNAscan-SE, whose heuristics incorporate a significant amount of work specific to tRNAs, where our heuristics are generic to any ncRNA. Performance was roughly comparable, so we expect that our heuristics provide a high-quality solution that--unlike family-specific solutions--can scale to hundreds of ncRNA families. The source code is available under GNU Public License at the supplementary web site.

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

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

2013-12-13

Qualitative and quantitative analysis of small non-coding RNAs by next generation sequencing (smallRNA-Seq) represents a novel technology increasingly used to investigate with high sensitivity and specificity RNA population comprising microRNAs and other regulatory small transcripts. Analysis of smallRNA-Seq data to gather biologically relevant information, i.e. detection and differential expression analysis of known and novel non-coding RNAs, target prediction, etc., requires implementation of multiple statistical and bioinformatics tools from different sources, each focusing on a specific step of the analysis pipeline. As a consequence, the analytical workflow is slowed down by the need for continuous interventions by the operator, a critical factor when large numbers of datasets need to be analyzed at once. We designed a novel modular pipeline (iMir) for comprehensive analysis of smallRNA-Seq data, comprising specific tools for adapter trimming, quality filtering, differential expression analysis, biological target prediction and other useful options by integrating multiple open source modules and resources in an automated workflow. As statistics is crucial in deep-sequencing data analysis, we devised and integrated in iMir tools based on different statistical approaches to allow the operator to analyze data rigorously. The pipeline created here proved to be efficient and time-saving than currently available methods and, in addition, flexible enough to allow the user to select the preferred combination of analytical steps. We present here the results obtained by applying this pipeline to analyze simultaneously 6 smallRNA-Seq datasets from either exponentially growing or growth-arrested human breast cancer MCF-7 cells, that led to the rapid and accurate identification, quantitation and differential expression analysis of ~450 miRNAs, including several novel miRNAs and isomiRs, as well as identification of the putative mRNA targets of differentially expressed mi

Identification of human microRNA-like sequences embedded within the protein-encoding genes of the human immunodeficiency virus.

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Bryan Holland

Full Text Available BACKGROUND: MicroRNAs (miRNAs are highly conserved, short (18-22 nts, non-coding RNA molecules that regulate gene expression by binding to the 3' untranslated regions (3'UTRs of mRNAs. While numerous cellular microRNAs have been associated with the progression of various diseases including cancer, miRNAs associated with retroviruses have not been well characterized. Herein we report identification of microRNA-like sequences in coding regions of several HIV-1 genomes. RESULTS: Based on our earlier proteomics and bioinformatics studies, we have identified 8 cellular miRNAs that are predicted to bind to the mRNAs of multiple proteins that are dysregulated during HIV-infection of CD4+ T-cells in vitro. In silico analysis of the full length and mature sequences of these 8 miRNAs and comparisons with all the genomic and subgenomic sequences of HIV-1 strains in global databases revealed that the first 18/18 sequences of the mature hsa-miR-195 sequence (including the short seed sequence, matched perfectly (100%, or with one nucleotide mismatch, within the envelope (env genes of five HIV-1 genomes from Africa. In addition, we have identified 4 other miRNA-like sequences (hsa-miR-30d, hsa-miR-30e, hsa-miR-374a and hsa-miR-424 within the env and the gag-pol encoding regions of several HIV-1 strains, albeit with reduced homology. Mapping of the miRNA-homologues of env within HIV-1 genomes localized these sequence to the functionally significant variable regions of the env glycoprotein gp120 designated V1, V2, V4 and V5. CONCLUSIONS: We conclude that microRNA-like sequences are embedded within the protein-encoding regions of several HIV-1 genomes. Given that the V1 to V5 regions of HIV-1 envelopes contain specific, well-characterized domains that are critical for immune responses, virus neutralization and disease progression, we propose that the newly discovered miRNA-like sequences within the HIV-1 genomes may have evolved to self-regulate survival of the

TRDistiller: a rapid filter for enrichment of sequence datasets with proteins containing tandem repeats.

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Richard, François D; Kajava, Andrey V

2014-06-01

The dramatic growth of sequencing data evokes an urgent need to improve bioinformatics tools for large-scale proteome analysis. Over the last two decades, the foremost efforts of computer scientists were devoted to proteins with aperiodic sequences having globular 3D structures. However, a large portion of proteins contain periodic sequences representing arrays of repeats that are directly adjacent to each other (so called tandem repeats or TRs). These proteins frequently fold into elongated fibrous structures carrying different fundamental functions. Algorithms specific to the analysis of these regions are urgently required since the conventional approaches developed for globular domains have had limited success when applied to the TR regions. The protein TRs are frequently not perfect, containing a number of mutations, and some of them cannot be easily identified. To detect such "hidden" repeats several algorithms have been developed. However, the most sensitive among them are time-consuming and, therefore, inappropriate for large scale proteome analysis. To speed up the TR detection we developed a rapid filter that is based on the comparison of composition and order of short strings in the adjacent sequence motifs. Tests show that our filter discards up to 22.5% of proteins which are known to be without TRs while keeping almost all (99.2%) TR-containing sequences. Thus, we are able to decrease the size of the initial sequence dataset enriching it with TR-containing proteins which allows a faster subsequent TR detection by other methods. The program is available upon request. Copyright © 2014 Elsevier Inc. All rights reserved.

Quantifying alternative splicing from paired-end RNA-sequencing data

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Rossell, David; Stephan-Otto Attolini, Camille; Kroiss, Manuel; Stöcker, Almond

2014-01-01

RNA-sequencing has revolutionized biomedical research and, in particular, our ability to study gene alternative splicing. The problem has important implications for human health, as alternative splicing may be involved in malfunctions at the cellular level and multiple diseases. However, the high-dimensional nature of the data and the existence of experimental biases pose serious data analysis challenges. We find that the standard data summaries used to study alternative splicing are severely...

De novo transcriptome sequence assembly from coconut leaves and seeds with a focus on factors involved in RNA-directed DNA methylation.

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Huang, Ya-Yi; Lee, Chueh-Pai; Fu, Jason L; Chang, Bill Chia-Han; Matzke, Antonius J M; Matzke, Marjori

2014-09-04

Coconut palm (Cocos nucifera) is a symbol of the tropics and a source of numerous edible and nonedible products of economic value. Despite its nutritional and industrial significance, coconut remains under-represented in public repositories for genomic and transcriptomic data. We report de novo transcript assembly from RNA-seq data and analysis of gene expression in seed tissues (embryo and endosperm) and leaves of a dwarf coconut variety. Assembly of 10 GB sequencing data for each tissue resulted in 58,211 total unigenes in embryo, 61,152 in endosperm, and 33,446 in leaf. Within each unigene pool, 24,857 could be annotated in embryo, 29,731 could be annotated in endosperm, and 26,064 could be annotated in leaf. A KEGG analysis identified 138, 138, and 139 pathways, respectively, in transcriptomes of embryo, endosperm, and leaf tissues. Given the extraordinarily large size of coconut seeds and the importance of small RNA-mediated epigenetic regulation during seed development in model plants, we used homology searches to identify putative homologs of factors required for RNA-directed DNA methylation in coconut. The findings suggest that RNA-directed DNA methylation is important during coconut seed development, particularly in maturing endosperm. This dataset will expand the genomics resources available for coconut and provide a foundation for more detailed analyses that may assist molecular breeding strategies aimed at improving this major tropical crop. Copyright © 2014 Huang et al.

Co-LncRNA: investigating the lncRNA combinatorial effects in GO annotations and KEGG pathways based on human RNA-Seq data.

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Zhao, Zheng; Bai, Jing; Wu, Aiwei; Wang, Yuan; Zhang, Jinwen; Wang, Zishan; Li, Yongsheng; Xu, Juan; Li, Xia

2015-01-01

Long non-coding RNAs (lncRNAs) are emerging as key regulators of diverse biological processes and diseases. However, the combinatorial effects of these molecules in a specific biological function are poorly understood. Identifying co-expressed protein-coding genes of lncRNAs would provide ample insight into lncRNA functions. To facilitate such an effort, we have developed Co-LncRNA, which is a web-based computational tool that allows users to identify GO annotations and KEGG pathways that may be affected by co-expressed protein-coding genes of a single or multiple lncRNAs. LncRNA co-expressed protein-coding genes were first identified in publicly available human RNA-Seq datasets, including 241 datasets across 6560 total individuals representing 28 tissue types/cell lines. Then, the lncRNA combinatorial effects in a given GO annotations or KEGG pathways are taken into account by the simultaneous analysis of multiple lncRNAs in user-selected individual or multiple datasets, which is realized by enrichment analysis. In addition, this software provides a graphical overview of pathways that are modulated by lncRNAs, as well as a specific tool to display the relevant networks between lncRNAs and their co-expressed protein-coding genes. Co-LncRNA also supports users in uploading their own lncRNA and protein-coding gene expression profiles to investigate the lncRNA combinatorial effects. It will be continuously updated with more human RNA-Seq datasets on an annual basis. Taken together, Co-LncRNA provides a web-based application for investigating lncRNA combinatorial effects, which could shed light on their biological roles and could be a valuable resource for this community. Database URL: http://www.bio-bigdata.com/Co-LncRNA/. © The Author(s) 2015. Published by Oxford University Press.

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

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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

Directory of Open Access Journals (Sweden)

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

SOAPsplice: genome-wide ab initio detection of splice junctions from RNA-Seq data

Directory of Open Access Journals (Sweden)

Songbo eHuang

2011-07-01

Full Text Available RNA-Seq, a method using next generation sequencing technologies to sequence the transcriptome, facilitates genome-wide analysis of splice junction sites. In this paper, we introduce SOAPsplice, a robust tool to detect splice junctions using RNA-Seq data without using any information of known splice junctions. SOAPsplice uses a novel two-step approach consisting of first identifying as many reasonable splice junction candidates as possible, and then, filtering the false positives with two effective filtering strategies. In both simulated and real datasets, SOAPsplice is able to detect many reliable splice junctions with low false positive rate. The improvement gained by SOAPsplice, when compared to other existing tools, becomes more obvious when the depth of sequencing is low. SOAPsplice is freely available at http://soap.genomics.org.cn/soapsplice.html.

Small RNA sequencing reveals a comprehensive miRNA signature of BRCA1-associated high-grade serous ovarian cancer

NARCIS (Netherlands)

Brouwer, Jan; Kluiver, Joost; de Almeida, Rodrigo C.; Modderman, Rutger; Terpstra, Martijn; Kok, Klaas; Withoff, Sebo; Hollema, Harry; Reitsma, Welmoed; de Bock, Geertruida H.; Mourits, Marian J. E.; van den Berg, Anke

2016-01-01

AimsBRCA1 mutation carriers are at increased risk of developing high-grade serous ovarian cancer (HGSOC), a malignancy that originates from fallopian tube epithelium. We aimed to identify differentially expressed known and novel miRNAs in BRCA1-associated HGSOC. Methods Small RNA sequencing was

Calling genotypes from public RNA-sequencing data enables identification of genetic variants that affect gene-expression levels

NARCIS (Netherlands)

Deelen, Patrick; Zhernakova, Daria V.; de Haan, Mark; van der Sijde, Marijke; Bonder, Marc Jan; Karjalainen, Juha; van der Velde, K. Joeri; Abbott, Kristin M.; Fu, Jingyuan; Wijmenga, Cisca; Sinke, Richard J.; Swertz, Morris A.; Franke, Lude

2015-01-01

Background: RNA-sequencing (RNA-seq) is a powerful technique for the identification of genetic variants that affect gene-expression levels, either through expression quantitative trait locus (eQTL) mapping or through allele-specific expression (ASE) analysis. Given increasing numbers of RNA-seq

Phylogenetic analysis of Fusobacterium prausnitzii based upon the 16S rRNA gene sequence and PCR confirmation.

Science.gov (United States)

Wang, R F; Cao, W W; Cerniglia, C E

1996-01-01

In order to develop a PCR method to detect Fusobacterium prausnitzii in human feces and to clarify the phylogenetic position of this species, its 16S rRNA gene sequence was determined. The sequence described in this paper is different from the 16S rRNA gene sequence is specific for F. prausnitzii, and the results of this assay confirmed that F. prausnitzii is the most common species in human feces. However, a PCR assay based on the original GenBank sequence was negative when it was performed with two strains of F. prausnitzii obtained from the American Type Culture Collection. A phylogenetic tree based on the new 16S rRNA gene sequence was constructed. On this tree F. prausnitzii was not a member of the Fusobacterium group but was closer to some Eubacterium spp. and located between Clostridium "clusters III and IV" (M.D. Collins, P.A. Lawson, A. Willems, J.J. Cordoba, J. Fernandez-Garayzabal, P. Garcia, J. Cai, H. Hippe, and J.A.E. Farrow, Int. J. Syst. Bacteriol. 44:812-826, 1994).

Molecular characterizations of somatic hybrids developed between Pleurotus florida and Lentinus squarrosulus through inter-simple sequence repeat markers and sequencing of ribosomal RNA-ITS gene.

Science.gov (United States)

Mallick, Pijush; Chattaraj, Shruti; Sikdar, Samir Ranjan

2017-10-01

The 12 pfls somatic hybrids and 2 parents of Pleurotus florida and Lentinus s quarrosulus were characterized by ISSR and sequencing of rRNA-ITS genes. Five ISSR primers were used and amplified a total of 54 reproducible fragments with 98.14% polymorphism among all the pfls hybrid populations and parental strains. UPGMA-based cluster exhibited a dendrogram with three major groups between the parents and pfls hybrids. Parent P . florida and L . squarrosulus showed different degrees of genetic distance with all the hybrid lines and they showed closeness to hybrid pfls 1m and pfls 1h , respectively. ITS1(F) and ITS4(R) amplified the rRNA-ITS gene with 611-867 bp sequence length. The nucleotide polymorphisms were found in the ITS1, ITS2 and 5.8S rRNA region with different number of bases. Based on rRNA-ITS sequence, UPGMA cluster exhibited three distinct groups between L. squarrosulus and pfls 1p , pfls 1m and pfls 1s , and pfls 1e and P. florida .

RNA-Sequencing of Primary Retinoblastoma Tumors Provides New Insights and Challenges Into Tumor Development

Directory of Open Access Journals (Sweden)

Sailaja V. Elchuri

2018-05-01

Full Text Available Retinoblastoma is rare tumor of the retina caused by the homozygous loss of the Retinoblastoma 1 tumor suppressor gene (RB1. Loss of the RB1 protein, pRB, results in de-regulated activity of the E2F transcription factors, chromatin changes and developmental defects leading to tumor development. Extensive microarray profiles of these tumors have enabled the identification of genes sensitive to pRB disruption, however, this technology has a number of limitations in the RNA profiles that they generate. The advent of RNA-sequencing has enabled the global profiling of all of the RNA within the cell including both coding and non-coding features and the detection of aberrant RNA processing events. In this perspective, we focus on discussing how RNA-sequencing of rare Retinoblastoma tumors will build on existing data and open up new area’s to improve our understanding of the biology of these tumors. In particular, we discuss how the RB-research field may be to use this data to determine how RB1 loss results in the expression of; non-coding RNAs, causes aberrant RNA processing events and how a deeper analysis of metabolic RNA changes can be utilized to model tumor specific shifts in metabolism. Each section discusses new opportunities and challenges associated with these types of analyses and aims to provide an honest assessment of how understanding these different processes may contribute to the treatment of Retinoblastoma.

The binding of TIA-1 to RNA C-rich sequences is driven by its C-terminal RRM domain.

Science.gov (United States)

Cruz-Gallardo, Isabel; Aroca, Ángeles; Gunzburg, Menachem J; Sivakumaran, Andrew; Yoon, Je-Hyun; Angulo, Jesús; Persson, Cecilia; Gorospe, Myriam; Karlsson, B Göran; Wilce, Jacqueline A; Díaz-Moreno, Irene

2014-01-01

T-cell intracellular antigen-1 (TIA-1) is a key DNA/RNA binding protein that regulates translation by sequestering target mRNAs in stress granules (SG) in response to stress conditions. TIA-1 possesses three RNA recognition motifs (RRM) along with a glutamine-rich domain, with the central domains (RRM2 and RRM3) acting as RNA binding platforms. While the RRM2 domain, which displays high affinity for U-rich RNA sequences, is primarily responsible for interaction with RNA, the contribution of RRM3 to bind RNA as well as the target RNA sequences that it binds preferentially are still unknown. Here we combined nuclear magnetic resonance (NMR) and surface plasmon resonance (SPR) techniques to elucidate the sequence specificity of TIA-1 RRM3. With a novel approach using saturation transfer difference NMR (STD-NMR) to quantify protein-nucleic acids interactions, we demonstrate that isolated RRM3 binds to both C- and U-rich stretches with micromolar affinity. In combination with RRM2 and in the context of full-length TIA-1, RRM3 significantly enhanced the binding to RNA, particularly to cytosine-rich RNA oligos, as assessed by biotinylated RNA pull-down analysis. Our findings provide new insight into the role of RRM3 in regulating TIA-1 binding to C-rich stretches, that are abundant at the 5' TOPs (5' terminal oligopyrimidine tracts) of mRNAs whose translation is repressed under stress situations.

16S rRNA gene sequence and phylogenetic tree of lactobacillus ...

African Journals Online (AJOL)

... processed by denaturing gradient gel electrophoresis (DGGE). Phylogenetic tree was constructed with the sequences of the V2-V3 region of 16S rRNA gene. Results show two distinct divisions among the Lactobacillus species. The study presents a new understanding of the nature of the Lactobacillus vaginal microbiota ...

Customized workflow development and data modularization concepts for RNA-Sequencing and metatranscriptome experiments.

Science.gov (United States)

Lott, Steffen C; Wolfien, Markus; Riege, Konstantin; Bagnacani, Andrea; Wolkenhauer, Olaf; Hoffmann, Steve; Hess, Wolfgang R

2017-11-10

RNA-Sequencing (RNA-Seq) has become a widely used approach to study quantitative and qualitative aspects of transcriptome data. The variety of RNA-Seq protocols, experimental study designs and the characteristic properties of the organisms under investigation greatly affect downstream and comparative analyses. In this review, we aim to explain the impact of structured pre-selection, classification and integration of best-performing tools within modularized data analysis workflows and ready-to-use computing infrastructures towards experimental data analyses. We highlight examples for workflows and use cases that are presented for pro-, eukaryotic and mixed dual RNA-Seq (meta-transcriptomics) experiments. In addition, we are summarizing the expertise of the laboratories participating in the project consortium "Structured Analysis and Integration of RNA-Seq experiments" (de.STAIR) and its integration with the Galaxy-workbench of the RNA Bioinformatics Center (RBC). Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

DNA sequencing reveals limited heterogeneity in the 16S rRNA gene from the rrnB operon among five Mycoplasma hominis isolates

DEFF Research Database (Denmark)

Mygind, T; Birkelund, Svend; Christiansen, Gunna

1998-01-01

To investigate the intraspecies heterogeneity within the 16S rRNA gene of Mycoplasma hominis, five isolates with diverse antigenic profiles, variable/identical P120 hypervariable domains, and different 16S rRNA gene RFLP patterns were analysed. The 16S rRNA gene from the rrnB operon was amplified...... by PCR and the PCR products were sequenced. Three isolates had identical 16S rRNA sequences and two isolates had sequences that differed from the others by only one nucleotide....

Survey of the transcriptome of Aspergillus oryzae via massively parallel mRNA sequencing.

Science.gov (United States)

Wang, Bin; Guo, Guangwu; Wang, Chao; Lin, Ying; Wang, Xiaoning; Zhao, Mouming; Guo, Yong; He, Minghui; Zhang, Yong; Pan, Li

2010-08-01

Aspergillus oryzae, an important filamentous fungus used in food fermentation and the enzyme industry, has been shown through genome sequencing and various other tools to have prominent features in its genomic composition. However, the functional complexity of the A. oryzae transcriptome has not yet been fully elucidated. Here, we applied direct high-throughput paired-end RNA-sequencing (RNA-Seq) to the transcriptome of A. oryzae under four different culture conditions. With the high resolution and sensitivity afforded by RNA-Seq, we were able to identify a substantial number of novel transcripts, new exons, untranslated regions, alternative upstream initiation codons and upstream open reading frames, which provide remarkable insight into the A. oryzae transcriptome. We were also able to assess the alternative mRNA isoforms in A. oryzae and found a large number of genes undergoing alternative splicing. Many genes and pathways that might be involved in higher levels of protein production in solid-state culture than in liquid culture were identified by comparing gene expression levels between different cultures. Our analysis indicated that the transcriptome of A. oryzae is much more complex than previously anticipated, and these results may provide a blueprint for further study of the A. oryzae transcriptome.

RNA Sequencing and Bioinformatics Analysis Implicate the Regulatory Role of a Long Noncoding RNA-mRNA Network in Hepatic Stellate Cell Activation.

Science.gov (United States)

Guo, Can-Jie; Xiao, Xiao; Sheng, Li; Chen, Lili; Zhong, Wei; Li, Hai; Hua, Jing; Ma, Xiong

2017-01-01

To analyze the long noncoding (lncRNA)-mRNA expression network and potential roles in rat hepatic stellate cells (HSCs) during activation. LncRNA expression was analyzed in quiescent and culture-activated HSCs by RNA sequencing, and differentially expressed lncRNAs verified by quantitative reverse transcription polymerase chain reaction (qRT-PCR) were subjected to bioinformatics analysis. In vivo analyses of differential lncRNA-mRNA expression were performed on a rat model of liver fibrosis. We identified upregulation of 12 lncRNAs and 155 mRNAs and downregulation of 12 lncRNAs and 374 mRNAs in activated HSCs. Additionally, we identified the differential expression of upregulated lncRNAs (NONRATT012636.2, NONRATT016788.2, and NONRATT021402.2) and downregulated lncRNAs (NONRATT007863.2, NONRATT019720.2, and NONRATT024061.2) in activated HSCs relative to levels observed in quiescent HSCs, and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses showed that changes in lncRNAs associated with HSC activation revealed 11 significantly enriched pathways according to their predicted targets. Moreover, based on the predicted co-expression network, the relative dynamic levels of NONRATT013819.2 and lysyl oxidase (Lox) were compared during HSC activation both in vitro and in vivo. Our results confirmed the upregulation of lncRNA NONRATT013819.2 and Lox mRNA associated with the extracellular matrix (ECM)-related signaling pathway in HSCs and fibrotic livers. Our results detailing a dysregulated lncRNA-mRNA network might provide new treatment strategies for hepatic fibrosis based on findings indicating potentially critical roles for NONRATT013819.2 and Lox in ECM remodeling during HSC activation. © 2017 The Author(s). Published by S. Karger AG, Basel.

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

Science.gov (United States)

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

2018-03-09

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

Simultaneous sequencing of coding and noncoding RNA reveals a human transcriptome dominated by a small number of highly expressed noncoding genes.

Science.gov (United States)

Boivin, Vincent; Deschamps-Francoeur, Gabrielle; Couture, Sonia; Nottingham, Ryan M; Bouchard-Bourelle, Philia; Lambowitz, Alan M; Scott, Michelle S; Abou-Elela, Sherif

2018-07-01

Comparing the abundance of one RNA molecule to another is crucial for understanding cellular functions but most sequencing techniques can target only specific subsets of RNA. In this study, we used a new fragmented ribodepleted TGIRT sequencing method that uses a thermostable group II intron reverse transcriptase (TGIRT) to generate a portrait of the human transcriptome depicting the quantitative relationship of all classes of nonribosomal RNA longer than 60 nt. Comparison between different sequencing methods indicated that FRT is more accurate in ranking both mRNA and noncoding RNA than viral reverse transcriptase-based sequencing methods, even those that specifically target these species. Measurements of RNA abundance in different cell lines using this method correlate with biochemical estimates, confirming tRNA as the most abundant nonribosomal RNA biotype. However, the single most abundant transcript is 7SL RNA, a component of the signal recognition particle. S tructured n on c oding RNAs (sncRNAs) associated with the same biological process are expressed at similar levels, with the exception of RNAs with multiple functions like U1 snRNA. In general, sncRNAs forming RNPs are hundreds to thousands of times more abundant than their mRNA counterparts. Surprisingly, only 50 sncRNA genes produce half of the non-rRNA transcripts detected in two different cell lines. Together the results indicate that the human transcriptome is dominated by a small number of highly expressed sncRNAs specializing in functions related to translation and splicing. © 2018 Boivin et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

Rtools: a web server for various secondary structural analyses on single RNA sequences.

Science.gov (United States)

Hamada, Michiaki; Ono, Yukiteru; Kiryu, Hisanori; Sato, Kengo; Kato, Yuki; Fukunaga, Tsukasa; Mori, Ryota; Asai, Kiyoshi

2016-07-08

The secondary structures, as well as the nucleotide sequences, are the important features of RNA molecules to characterize their functions. According to the thermodynamic model, however, the probability of any secondary structure is very small. As a consequence, any tool to predict the secondary structures of RNAs has limited accuracy. On the other hand, there are a few tools to compensate the imperfect predictions by calculating and visualizing the secondary structural information from RNA sequences. It is desirable to obtain the rich information from those tools through a friendly interface. We implemented a web server of the tools to predict secondary structures and to calculate various structural features based on the energy models of secondary structures. By just giving an RNA sequence to the web server, the user can get the different types of solutions of the secondary structures, the marginal probabilities such as base-paring probabilities, loop probabilities and accessibilities of the local bases, the energy changes by arbitrary base mutations as well as the measures for validations of the predicted secondary structures. The web server is available at http://rtools.cbrc.jp, which integrates software tools, CentroidFold, CentroidHomfold, IPKnot, CapR, Raccess, Rchange and RintD. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

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.

The hormone response element mimic sequence of GAS5 lncRNA is sufficient to induce apoptosis in breast cancer cells

Science.gov (United States)

Pickard, Mark R.; Williams, Gwyn T.

2016-01-01

Growth arrest-specific 5 (GAS5) lncRNA promotes apoptosis, and its expression is down-regulated in breast cancer. GAS5 lncRNA is a decoy of glucocorticoid/related receptors; a stem-loop sequence constitutes the GAS5 hormone response element mimic (HREM), which is essential for the regulation of breast cancer cell apoptosis. This preclinical study aimed to determine if the GAS5 HREM sequence alone promotes the apoptosis of breast cancer cells. Nucleofection of hormone-sensitive and –insensitive breast cancer cell lines with a GAS5 HREM DNA oligonucleotide increased both basal and ultraviolet-C-induced apoptosis, and decreased culture viability and clonogenic growth, similar to GAS5 lncRNA. The HREM oligonucleotide demonstrated similar sequence specificity to the native HREM for its functional activity and had no effect on endogenous GAS5 lncRNA levels. Certain chemically modified HREM oligonucleotides, notably DNA and RNA phosphorothioates, retained pro-apoptotic. activity. Crucially the HREM oligonucleotide could overcome apoptosis resistance secondary to deficient endogenous GAS5 lncRNA levels. Thus, the GAS5 lncRNA HREM sequence alone is sufficient to induce apoptosis in breast cancer cells, including triple-negative breast cancer cells. These findings further suggest that emerging knowledge of structure/function relationships in the field of lncRNA biology can be exploited for the development of entirely novel, oligonucleotide mimic-based, cancer therapies. PMID:26862727

Efficient RNA extraction protocol for the wood mangrove species Laguncularia racemosa suited for next-generation RNA sequencing

International Nuclear Information System (INIS)

Wilwerth, M. W.; Rossetto, P.

2016-01-01

Mangrove flora and habitat have immeasurable importance in marine and coastal ecology as well as in the economy. Despite their importance, they are constantly threatened by oil spill accidents and environmental contamination; therefore, it is crucial to understand the changes in gene expression to better predict toxicity in these plants. Among the species of Atlantic coast mangrove (Americas and Africa), Laguncularia racemosa, or white mangrove, is a conspicuous species. The wide distribution of L. racemosa in areas where marine oil exploration is rapidly increasing make it a candidate mangrove species model to uncover the impact of oil spills at the molecular level with the use of massive transcriptome sequencing. However, for this purpose, the RNA extraction protocol should ensure low levels of contaminants and structure integrity. In this study, eight RNA extraction methods were tested and analysed using downstream applications. The InviTrap Spin Plant RNA Mini Kit performed best with regard to purity and integrity. Moreover, the obtained RNA was submitted to cDNA synthesis and RT-PCR, successfully generating amplification products of the expected size. These Results show the applicability of the RNA obtained here for downstream methodologies, such as the construction of cDNA libraries for the Illumina Hi-seq platform. (author)

The nucleotide sequence of the RNA-2 of an isolate of the English serotype of tomato black ring virus: RNA recombination in the history of nepoviruses.

Science.gov (United States)

Le Gall, O L; Lanneau, M; Candresse, T; Dunez, J

1995-05-01

The RNA-2 of a carrot isolate from the English serotype of tomato black ring nepovirus (TBRV-ED) has been sequenced. It is 4618 nucleotides long and contains one open reading frame encoding a polypeptide of 1344 amino acids. The 5' non-coding region contains three repetitions of a stem-loop structure also conserved in TBRV-Scottish and grapevine chrome mosaic nepovirus (GCMV). The coat protein domain was mapped to the carboxy-terminal one-third of the polyprotein. Sequence comparisons indicate that TBRV-ED RNA-2 probably arose by an RNA recombination event that resulted in the exchange of the putative movement protein gene between TBRV and GCMV.

Non-codingRNA sequence variations in human chronic lymphocytic leukemia and colorectal cancer.

Science.gov (United States)

Wojcik, Sylwia E; Rossi, Simona; Shimizu, Masayoshi; Nicoloso, Milena S; Cimmino, Amelia; Alder, Hansjuerg; Herlea, Vlad; Rassenti, Laura Z; Rai, Kanti R; Kipps, Thomas J; Keating, Michael J; Croce, Carlo M; Calin, George A

2010-02-01

Cancer is a genetic disease in which the interplay between alterations in protein-coding genes and non-coding RNAs (ncRNAs) plays a fundamental role. In recent years, the full coding component of the human genome was sequenced in various cancers, whereas such attempts related to ncRNAs are still fragmentary. We screened genomic DNAs for sequence variations in 148 microRNAs (miRNAs) and ultraconserved regions (UCRs) loci in patients with chronic lymphocytic leukemia (CLL) or colorectal cancer (CRC) by Sanger technique and further tried to elucidate the functional consequences of some of these variations. We found sequence variations in miRNAs in both sporadic and familial CLL cases, mutations of UCRs in CLLs and CRCs and, in certain instances, detected functional effects of these variations. Furthermore, by integrating our data with previously published data on miRNA sequence variations, we have created a catalog of DNA sequence variations in miRNAs/ultraconserved genes in human cancers. These findings argue that ncRNAs are targeted by both germ line and somatic mutations as well as by single-nucleotide polymorphisms with functional significance for human tumorigenesis. Sequence variations in ncRNA loci are frequent and some have functional and biological significance. Such information can be exploited to further investigate on a genome-wide scale the frequency of genetic variations in ncRNAs and their functional meaning, as well as for the development of new diagnostic and prognostic markers for leukemias and carcinomas.

A comprehensive evaluation of the sl1p pipeline for 16S rRNA gene sequencing analysis.

Science.gov (United States)

Whelan, Fiona J; Surette, Michael G

2017-08-14

Advances in next-generation sequencing technologies have allowed for detailed, molecular-based studies of microbial communities such as the human gut, soil, and ocean waters. Sequencing of the 16S rRNA gene, specific to prokaryotes, using universal PCR primers has become a common approach to studying the composition of these microbiota. However, the bioinformatic processing of the resulting millions of DNA sequences can be challenging, and a standardized protocol would aid in reproducible analyses. The short-read library 16S rRNA gene sequencing pipeline (sl1p, pronounced "slip") was designed with the purpose of mitigating this lack of reproducibility by combining pre-existing tools into a computational pipeline. This pipeline automates the processing of raw 16S rRNA gene sequencing data to create human-readable tables, graphs, and figures to make the collected data more readily accessible. Data generated from mock communities were compared using eight OTU clustering algorithms, two taxon assignment approaches, and three 16S rRNA gene reference databases. While all of these algorithms and options are available to sl1p users, through testing with human-associated mock communities, AbundantOTU+, the RDP Classifier, and the Greengenes 2011 reference database were chosen as sl1p's defaults based on their ability to best represent the known input communities. sl1p promotes reproducible research by providing a comprehensive log file, and reduces the computational knowledge needed by the user to process next-generation sequencing data. sl1p is freely available at https://bitbucket.org/fwhelan/sl1p .

RNA-Mediated Gene Duplication and Retroposons: Retrogenes, LINEs, SINEs, and Sequence Specificity

Science.gov (United States)

2013-01-01

A substantial number of “retrogenes” that are derived from the mRNA of various intron-containing genes have been reported. A class of mammalian retroposons, long interspersed element-1 (LINE1, L1), has been shown to be involved in the reverse transcription of retrogenes (or processed pseudogenes) and non-autonomous short interspersed elements (SINEs). The 3′-end sequences of various SINEs originated from a corresponding LINE. As the 3′-untranslated regions of several LINEs are essential for retroposition, these LINEs presumably require “stringent” recognition of the 3′-end sequence of the RNA template. However, the 3′-ends of mammalian L1s do not exhibit any similarity to SINEs, except for the presence of 3′-poly(A) repeats. Since the 3′-poly(A) repeats of L1 and Alu SINE are critical for their retroposition, L1 probably recognizes the poly(A) repeats, thereby mobilizing not only Alu SINE but also cytosolic mRNA. Many flowering plants only harbor L1-clade LINEs and a significant number of SINEs with poly(A) repeats, but no homology to the LINEs. Moreover, processed pseudogenes have also been found in flowering plants. I propose that the ancestral L1-clade LINE in the common ancestor of green plants may have recognized a specific RNA template, with stringent recognition then becoming relaxed during the course of plant evolution. PMID:23984183

Body fluid identification of blood, saliva and semen using second generation sequencing of micro-RNA

DEFF Research Database (Denmark)

Petersen, Christel H.; Hjort, Benjamin Benn; Tvedebrink, Torben

2013-01-01

We report a new second generation sequencing method for identification micro-RNA (miRNA) that can be used to identify body fluids and tissues. Principal component analysis of 10 miRNAs with high expression in 16 samples of blood, saliva and semen showed clear differences in the expression of mi...

A probabilistic model for the evolution of RNA structure

Directory of Open Access Journals (Sweden)

Holmes Ian

2004-10-01

Full Text Available Abstract Background For the purposes of finding and aligning noncoding RNA gene- and cis-regulatory elements in multiple-genome datasets, it is useful to be able to derive multi-sequence stochastic grammars (and hence multiple alignment algorithms systematically, starting from hypotheses about the various kinds of random mutation event and their rates. Results Here, we consider a highly simplified evolutionary model for RNA, called "The TKF91 Structure Tree" (following Thorne, Kishino and Felsenstein's 1991 model of sequence evolution with indels, which we have implemented for pairwise alignment as proof of principle for such an approach. The model, its strengths and its weaknesses are discussed with reference to four examples of functional ncRNA sequences: a riboswitch (guanine, a zipcode (nanos, a splicing factor (U4 and a ribozyme (RNase P. As shown by our visualisations of posterior probability matrices, the selected examples illustrate three different signatures of natural selection that are highly characteristic of ncRNA: (i co-ordinated basepair substitutions, (ii co-ordinated basepair indels and (iii whole-stem indels. Conclusions Although all three types of mutation "event" are built into our model, events of type (i and (ii are found to be better modeled than events of type (iii. Nevertheless, we hypothesise from the model's performance on pairwise alignments that it would form an adequate basis for a prototype multiple alignment and genefinding tool.

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

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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

The nucleotide sequence and organization of nuclear 5S rRNA genes in yellow lupine

International Nuclear Information System (INIS)

Nuc, K.; Nuc, P.; Pawelkiewicz, J.

1993-01-01

We have isolated a genomic clone containing 'Lupinus luteus' 5S ribosomal RNA genes by screening with 5S rDNA probe clones that were hybridized previously with the initiator methionine tRNA preparation (contaminated) with traces of rRNA or its degradation products). The clone isolated contains ten repeat units of 342 bp with 119 bp fragment showing 100% homology to the 5S rRNA from yellow lupine. Sequence analysis indicates only point heterogeneities among the flanking regions of the genes. (author). 6 refs, 3 figs

The PETfold and PETcofold web servers for intra- and intermolecular structures of multiple RNA sequences

DEFF Research Database (Denmark)

Seemann, Ernst Stefan; Menzel, Karl Peter; Backofen, Rolf

2011-01-01

gene. We present web servers to analyze multiple RNA sequences for common RNA structure and for RNA interaction sites. The web servers are based on the recent PET (Probabilistic Evolutionary and Thermodynamic) models PETfold and PETcofold, but add user friendly features ranging from a graphical layer...... to interactive usage of the predictors. Additionally, the web servers provide direct access to annotated RNA alignments, such as the Rfam 10.0 database and multiple alignments of 16 vertebrate genomes with human. The web servers are freely available at: http://rth.dk/resources/petfold/...

Massively parallel sequencing, aCGH, and RNA-Seq technologies provide a comprehensive molecular diagnosis of Fanconi anemia.

Science.gov (United States)

Chandrasekharappa, Settara C; Lach, Francis P; Kimble, Danielle C; Kamat, Aparna; Teer, Jamie K; Donovan, Frank X; Flynn, Elizabeth; Sen, Shurjo K; Thongthip, Supawat; Sanborn, Erica; Smogorzewska, Agata; Auerbach, Arleen D; Ostrander, Elaine A

2013-05-30

Current methods for detecting mutations in Fanconi anemia (FA)-suspected patients are inefficient and often miss mutations. We have applied recent advances in DNA sequencing and genomic capture to the diagnosis of FA. Specifically, we used custom molecular inversion probes or TruSeq-enrichment oligos to capture and sequence FA and related genes, including introns, from 27 samples from the International Fanconi Anemia Registry at The Rockefeller University. DNA sequencing was complemented with custom array comparative genomic hybridization (aCGH) and RNA sequencing (RNA-seq) analysis. aCGH identified deletions/duplications in 4 different FA genes. RNA-seq analysis revealed lack of allele specific expression associated with a deletion and splicing defects caused by missense, synonymous, and deep-in-intron variants. The combination of TruSeq-targeted capture, aCGH, and RNA-seq enabled us to identify the complementation group and biallelic germline mutations in all 27 families: FANCA (7), FANCB (3), FANCC (3), FANCD1 (1), FANCD2 (3), FANCF (2), FANCG (2), FANCI (1), FANCJ (2), and FANCL (3). FANCC mutations are often the cause of FA in patients of Ashkenazi Jewish (AJ) ancestry, and we identified 2 novel FANCC mutations in 2 patients of AJ ancestry. We describe here a strategy for efficient molecular diagnosis of FA.

RAG-3D: a search tool for RNA 3D substructures

Science.gov (United States)

Zahran, Mai; Sevim Bayrak, Cigdem; Elmetwaly, Shereef; Schlick, Tamar

2015-01-01

To address many challenges in RNA structure/function prediction, the characterization of RNA's modular architectural units is required. Using the RNA-As-Graphs (RAG) database, we have previously explored the existence of secondary structure (2D) submotifs within larger RNA structures. Here we present RAG-3D—a dataset of RNA tertiary (3D) structures and substructures plus a web-based search tool—designed to exploit graph representations of RNAs for the goal of searching for similar 3D structural fragments. The objects in RAG-3D consist of 3D structures translated into 3D graphs, cataloged based on the connectivity between their secondary structure elements. Each graph is additionally described in terms of its subgraph building blocks. The RAG-3D search tool then compares a query RNA 3D structure to those in the database to obtain structurally similar structures and substructures. This comparison reveals conserved 3D RNA features and thus may suggest functional connections. Though RNA search programs based on similarity in sequence, 2D, and/or 3D structural elements are available, our graph-based search tool may be advantageous for illuminating similarities that are not obvious; using motifs rather than sequence space also reduces search times considerably. Ultimately, such substructuring could be useful for RNA 3D structure prediction, structure/function inference and inverse folding. PMID:26304547

3' end labelling of RNA with /sup 32/P suitable for rapid gel sequencing

Energy Technology Data Exchange (ETDEWEB)

Winter, G; Brownlee, G G [Medical Research Council, Cambridge (UK)

1978-09-01

A new general method of labelling the 2', 3'-diol end of RNA with /sup 32/P has been devised suitable for gel sequencing. Poly(A) polymerase (E.coli) is incubated with the RNA and limiting amounts of ..cap alpha..-/sup 32/P-ATP. The mono-addition product is then cleaved with periodate and ..beta..-eliminated with aniline, leaving the RNA terminally labelled with 3'/sup 32/P-phosphate. When applied to a model compound, tRNAsup(Phe) from E. coli, over 28 residues could be read from the 3' end.

A Mechanistic Beta-Binomial Probability Model for mRNA Sequencing Data.

Science.gov (United States)

Smith, Gregory R; Birtwistle, Marc R

2016-01-01

A main application for mRNA sequencing (mRNAseq) is determining lists of differentially-expressed genes (DEGs) between two or more conditions. Several software packages exist to produce DEGs from mRNAseq data, but they typically yield different DEGs, sometimes markedly so. The underlying probability model used to describe mRNAseq data is central to deriving DEGs, and not surprisingly most softwares use different models and assumptions to analyze mRNAseq data. Here, we propose a mechanistic justification to model mRNAseq as a binomial process, with data from technical replicates given by a binomial distribution, and data from biological replicates well-described by a beta-binomial distribution. We demonstrate good agreement of this model with two large datasets. We show that an emergent feature of the beta-binomial distribution, given parameter regimes typical for mRNAseq experiments, is the well-known quadratic polynomial scaling of variance with the mean. The so-called dispersion parameter controls this scaling, and our analysis suggests that the dispersion parameter is a continually decreasing function of the mean, as opposed to current approaches that impose an asymptotic value to the dispersion parameter at moderate mean read counts. We show how this leads to current approaches overestimating variance for moderately to highly expressed genes, which inflates false negative rates. Describing mRNAseq data with a beta-binomial distribution thus may be preferred since its parameters are relatable to the mechanistic underpinnings of the technique and may improve the consistency of DEG analysis across softwares, particularly for moderately to highly expressed genes.

visnormsc: A Graphical User Interface to Normalize Single-cell RNA Sequencing Data.

Science.gov (United States)

Tang, Lijun; Zhou, Nan

2017-12-26

Single-cell RNA sequencing (RNA-seq) allows the analysis of gene expression with high resolution. The intrinsic defects of this promising technology imports technical noise into the single-cell RNA-seq data, increasing the difficulty of accurate downstream inference. Normalization is a crucial step in single-cell RNA-seq data pre-processing. SCnorm is an accurate and efficient method that can be used for this purpose. An R implementation of this method is currently available. On one hand, the R package possesses many excellent features from R. On the other hand, R programming ability is required, which prevents the biologists who lack the skills from learning to use it quickly. To make this method more user-friendly, we developed a graphical user interface, visnormsc, for normalization of single-cell RNA-seq data. It is implemented in Python and is freely available at https://github.com/solo7773/visnormsc . Although visnormsc is based on the existing method, it contributes to this field by offering a user-friendly alternative. The out-of-the-box and cross-platform features make visnormsc easy to learn and to use. It is expected to serve biologists by simplifying single-cell RNA-seq normalization.

Novel approaches for bioinformatic analysis of salivary RNA sequencing data for development.

Science.gov (United States)

Kaczor-Urbanowicz, Karolina Elzbieta; Kim, Yong; Li, Feng; Galeev, Timur; Kitchen, Rob R; Gerstein, Mark; Koyano, Kikuye; Jeong, Sung-Hee; Wang, Xiaoyan; Elashoff, David; Kang, So Young; Kim, Su Mi; Kim, Kyoung; Kim, Sung; Chia, David; Xiao, Xinshu; Rozowsky, Joel; Wong, David T W

2018-01-01

Analysis of RNA sequencing (RNA-Seq) data in human saliva is challenging. Lack of standardization and unification of the bioinformatic procedures undermines saliva's diagnostic potential. Thus, it motivated us to perform this study. We applied principal pipelines for bioinformatic analysis of small RNA-Seq data of saliva of 98 healthy Korean volunteers including either direct or indirect mapping of the reads to the human genome using Bowtie1. Analysis of alignments to exogenous genomes by another pipeline revealed that almost all of the reads map to bacterial genomes. Thus, salivary exRNA has fundamental properties that warrant the design of unique additional steps while performing the bioinformatic analysis. Our pipelines can serve as potential guidelines for processing of RNA-Seq data of human saliva. Processing and analysis results of the experimental data generated by the exceRpt (v4.6.3) small RNA-seq pipeline (github.gersteinlab.org/exceRpt) are available from exRNA atlas (exrna-atlas.org). Alignment to exogenous genomes and their quantification results were used in this paper for the analyses of small RNAs of exogenous origin. dtww@ucla.edu. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

High throughput sequencing of small RNA component of leaves and inflorescence revealed conserved and novel miRNAs as well as phasiRNA loci in chickpea.

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Srivastava, Sangeeta; Zheng, Yun; Kudapa, Himabindu; Jagadeeswaran, Guru; Hivrale, Vandana; Varshney, Rajeev K; Sunkar, Ramanjulu

2015-06-01

Among legumes, chickpea (Cicer arietinum L.) is the second most important crop after soybean. MicroRNAs (miRNAs) play important roles by regulating target gene expression important for plant development and tolerance to stress conditions. Additionally, recently discovered phased siRNAs (phasiRNAs), a new class of small RNAs, are abundantly produced in legumes. Nevertheless, little is known about these regulatory molecules in chickpea. The small RNA population was sequenced from leaves and flowers of chickpea to identify conserved and novel miRNAs as well as phasiRNAs/phasiRNA loci. Bioinformatics analysis revealed 157 miRNA loci for the 96 highly conserved and known miRNA homologs belonging to 38 miRNA families in chickpea. Furthermore, 20 novel miRNAs belonging to 17 miRNA families were identified. Sequence analysis revealed approximately 60 phasiRNA loci. Potential target genes likely to be regulated by these miRNAs were predicted and some were confirmed by modified 5' RACE assay. Predicted targets are mostly transcription factors that might be important for developmental processes, and others include superoxide dismutases, plantacyanin, laccases and F-box proteins that could participate in stress responses and protein degradation. Overall, this study provides an inventory of miRNA-target gene interactions for chickpea, useful for the comparative analysis of small RNAs among legumes. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

The analysis of novel microRNA mimic sequences in cancer cells reveals lack of specificity in stem-loop RT-qPCR-based microRNA detection.

Science.gov (United States)

Winata, Patrick; Williams, Marissa; McGowan, Eileen; Nassif, Najah; van Zandwijk, Nico; Reid, Glen

2017-11-17

MicroRNAs are frequently downregulated in cancer, and restoring expression has tumour suppressive activity in tumour cells. Our recent phase I clinical trial investigated microRNA-based therapy in patients with malignant pleural mesothelioma. Treatment with TargomiRs, microRNA mimics with novel sequence packaged in EGFR antibody-targeted bacterial minicells, revealed clear signs of clinical activity. In order to detect delivery of microRNA mimics to tumour cells in future clinical trials, we tested hydrolysis probe-based assays specific for the sequence of the novel mimics in transfected mesothelioma cell lines using RT-qPCR. The custom assays efficiently and specifically amplified the consensus mimics. However, we found that these assays gave a signal when total RNA from untransfected and control mimic-transfected cells were used as templates. Further investigation revealed that the reverse transcription step using stem-loop primers appeared to introduce substantial non-specific amplification with either total RNA or synthetic RNA templates. This suggests that reverse transcription using stem-loop primers suffers from an intrinsic lack of specificity for the detection of highly similar microRNAs in the same family, especially when analysing total RNA. These results suggest that RT-qPCR is unlikely to be an effective means to detect delivery of microRNA mimic-based drugs to tumour cells in patients.

MicroRNA Profiling in Aqueous Humor of Individual Human Eyes by Next-Generation Sequencing.

Science.gov (United States)

Wecker, Thomas; Hoffmeier, Klaus; Plötner, Anne; Grüning, Björn Andreas; Horres, Ralf; Backofen, Rolf; Reinhard, Thomas; Schlunck, Günther

2016-04-01

Extracellular microRNAs (miRNAs) in aqueous humor were suggested to have a role in transcellular signaling and may serve as disease biomarkers. The authors adopted next-generation sequencing (NGS) techniques to further characterize the miRNA profile in single samples of 60 to 80 μL human aqueous humor. Samples were obtained at the outset of cataract surgery in nine independent, otherwise healthy eyes. Four samples were used to extract RNA and generate sequencing libraries, followed by an adapter-driven amplification step, electrophoretic size selection, sequencing, and data analysis. Five samples were used for quantitative PCR (qPCR) validation of NGS results. Published NGS data on circulating miRNAs in blood were analyzed in comparison. One hundred fifty-eight miRNAs were consistently detected by NGS in all four samples; an additional 59 miRNAs were present in at least three samples. The aqueous humor miRNA profile shows some overlap with published NGS-derived inventories of circulating miRNAs in blood plasma with high prevalence of human miR-451a, -21, and -16. In contrast to blood, miR-184, -4448, -30a, -29a, -29c, -19a, -30d, -205, -24, -22, and -3074 were detected among the 20 most prevalent miRNAs in aqueous humor. Relative expression patterns of miR-451a, -202, and -144 suggested by NGS were confirmed by qPCR. Our data illustrate the feasibility of miRNA analysis by NGS in small individual aqueous humor samples. Intraocular cells as well as blood plasma contribute to the extracellular aqueous humor miRNome. The data suggest possible roles of miRNA in intraocular cell adhesion and signaling by TGF-β and Wnt, which are important in intraocular pressure regulation and glaucoma.

CoLIde: a bioinformatics tool for CO-expression-based small RNA Loci Identification using high-throughput sequencing data.

Science.gov (United States)

Mohorianu, Irina; Stocks, Matthew Benedict; Wood, John; Dalmay, Tamas; Moulton, Vincent

2013-07-01

Small RNAs (sRNAs) are 20-25 nt non-coding RNAs that act as guides for the highly sequence-specific regulatory mechanism known as RNA silencing. Due to the recent increase in sequencing depth, a highly complex and diverse population of sRNAs in both plants and animals has been revealed. However, the exponential increase in sequencing data has also made the identification of individual sRNA transcripts corresponding to biological units (sRNA loci) more challenging when based exclusively on the genomic location of the constituent sRNAs, hindering existing approaches to identify sRNA loci. To infer the location of significant biological units, we propose an approach for sRNA loci detection called CoLIde (Co-expression based sRNA Loci Identification) that combines genomic location with the analysis of other information such as variation in expression levels (expression pattern) and size class distribution. For CoLIde, we define a locus as a union of regions sharing the same pattern and located in close proximity on the genome. Biological relevance, detected through the analysis of size class distribution, is also calculated for each locus. CoLIde can be applied on ordered (e.g., time-dependent) or un-ordered (e.g., organ, mutant) series of samples both with or without biological/technical replicates. The method reliably identifies known types of loci and shows improved performance on sequencing data from both plants (e.g., A. thaliana, S. lycopersicum) and animals (e.g., D. melanogaster) when compared with existing locus detection techniques. CoLIde is available for use within the UEA Small RNA Workbench which can be downloaded from: http://srna-workbench.cmp.uea.ac.uk.

Double-stranded RNA interferes in a sequence-specific manner with the infection of representative members of the two viroid families

International Nuclear Information System (INIS)

Carbonell, Alberto; Martinez de Alba, Angel-Emilio; Flores, Ricardo; Gago, Selma

2008-01-01

Infection by viroids, non-protein-coding circular RNAs, occurs with the accumulation of 21-24 nt viroid-derived small RNAs (vd-sRNAs) with characteristic properties of small interfering RNAs (siRNAs) associated to RNA silencing. The vd-sRNAs most likely derive from dicer-like (DCL) enzymes acting on viroid-specific dsRNA, the key elicitor of RNA silencing, or on the highly structured genomic RNA. Previously, viral dsRNAs delivered mechanically or agroinoculated have been shown to interfere with virus infection in a sequence-specific manner. Here, we report similar results with members of the two families of nuclear- and chloroplast-replicating viroids. Moreover, homologous vd-sRNAs co-delivered mechanically also interfered with one of the viroids examined. The interference was sequence-specific, temperature-dependent and, in some cases, also dependent on the dose of the co-inoculated dsRNA or vd-sRNAs. The sequence-specific nature of these effects suggests the involvement of the RNA induced silencing complex (RISC), which provides sequence specificity to RNA silencing machinery. Therefore, viroid titer in natural infections might be regulated by the concerted action of DCL and RISC. Viroids could have evolved their secondary structure as a compromise between resistance to DCL and RISC, which act preferentially against RNAs with compact and relaxed secondary structures, respectively. In addition, compartmentation, association with proteins or active replication might also help viroids to elude their host RNA silencing machinery

StralSV: assessment of sequence variability within similar 3D structures and application to polio RNA-dependent RNA polymerase

Energy Technology Data Exchange (ETDEWEB)

Zemla, A; Lang, D; Kostova, T; Andino, R; Zhou, C

2010-11-29

Most of the currently used methods for protein function prediction rely on sequence-based comparisons between a query protein and those for which a functional annotation is provided. A serious limitation of sequence similarity-based approaches for identifying residue conservation among proteins is the low confidence in assigning residue-residue correspondences among proteins when the level of sequence identity between the compared proteins is poor. Multiple sequence alignment methods are more satisfactory - still, they cannot provide reliable results at low levels of sequence identity. Our goal in the current work was to develop an algorithm that could overcome these difficulties and facilitate the identification of structurally (and possibly functionally) relevant residue-residue correspondences between compared protein structures. Here we present StralSV, a new algorithm for detecting closely related structure fragments and quantifying residue frequency from tight local structure alignments. We apply StralSV in a study of the RNA-dependent RNA polymerase of poliovirus and demonstrate that the algorithm can be used to determine regions of the protein that are relatively unique or that shared structural similarity with structures that are distantly related. By quantifying residue frequencies among many residue-residue pairs extracted from local alignments, one can infer potential structural or functional importance of specific residues that are determined to be highly conserved or that deviate from a consensus. We further demonstrate that considerable detailed structural and phylogenetic information can be derived from StralSV analyses. StralSV is a new structure-based algorithm for identifying and aligning structure fragments that have similarity to a reference protein. StralSV analysis can be used to quantify residue-residue correspondences and identify residues that may be of particular structural or functional importance, as well as unusual or unexpected

Complete nucleotide sequence of the RNA-2 of grapevine deformation and Grapevine Anatolian ringspot viruses.

Science.gov (United States)

Ghanem-Sabanadzovic, Nina Abou; Sabanadzovic, Sead; Digiaro, Michele; Martelli, Giovanni P

2005-05-01

The nucleotide sequence of RNA-2 of Grapevine Anatolian ringspot virus (GARSV) and Grapevine deformation virus (GDefV), two recently described nepoviruses, has been determined. These RNAs are 3753 nt (GDefV) and 4607 nt (GARSV) in size and contain a single open reading frame encoding a polyprotein of 122 kDa (GDefV) and 150 kDa (GARSV). Full-length nucleotide sequence comparison disclosed 71-73% homology between GDefV RNA-2 and that of Grapevine fanleaf virus (GFLV) and Arabis mosaic virus (ArMV), and 62-64% homology between GARSV RNA-2 and that of Grapevine chrome mosaic virus (GCMV) and Tomato black ring virus (TBRV). As previously observed in other nepoviruses, the 5' non-coding regions of both RNAs are capable of forming stem-loop structures. Phylogenetic analysis of the three proteins encoded by RNA-2 (i.e. protein 2A, movement protein and coat protein) confirmed that GDefV and GARSV are distinct viruses which can be assigned as definitive species in subgroup A and subgroup B of the genus Nepovirus, respectively.

Genetic divergence of Asiatic Bdellocephala (Turbellaria, Tricladida, Paludicola) as revealed by partial 18S rRNA gene sequence comparisons.

Science.gov (United States)

Kuznedelov, K D; Timoshkin, O A; Goldman, E

1997-01-01

Polymerase chain reaction (PCR) and direct sequencing of small ribosomal RNA genes were used for analysis of genetic differences among Asiatic species of freshwater triclad genus Bdellocephala. Representatives of four species and four subspecies of this genus were used to establish homology between nucleotides in the 5'-end portion of small ribosomal RNA gene sequences. Within 552 nucleotide sites of aligned sequences compared, six variable base positions were discovered, dividing Bdellocephala into five different genotypes. Sequence data allow to distinguish two groups of these genotypes. One of them unites species from Kamchatka and Japan, another one unites Baikalian taxa. Agreement between available morphological, cytological and sequence data is discussed.

Functional Advantages of Conserved Intrinsic Disorder in RNA-Binding Proteins.

Science.gov (United States)

Varadi, Mihaly; Zsolyomi, Fruzsina; Guharoy, Mainak; Tompa, Peter

2015-01-01

Proteins form large macromolecular assemblies with RNA that govern essential molecular processes. RNA-binding proteins have often been associated with conformational flexibility, yet the extent and functional implications of their intrinsic disorder have never been fully assessed. Here, through large-scale analysis of comprehensive protein sequence and structure datasets we demonstrate the prevalence of intrinsic structural disorder in RNA-binding proteins and domains. We addressed their functionality through a quantitative description of the evolutionary conservation of disordered segments involved in binding, and investigated the structural implications of flexibility in terms of conformational stability and interface formation. We conclude that the functional role of intrinsically disordered protein segments in RNA-binding is two-fold: first, these regions establish extended, conserved electrostatic interfaces with RNAs via induced fit. Second, conformational flexibility enables them to target different RNA partners, providing multi-functionality, while also ensuring specificity. These findings emphasize the functional importance of intrinsically disordered regions in RNA-binding proteins.

Functional Advantages of Conserved Intrinsic Disorder in RNA-Binding Proteins.

Directory of Open Access Journals (Sweden)

Mihaly Varadi

Full Text Available Proteins form large macromolecular assemblies with RNA that govern essential molecular processes. RNA-binding proteins have often been associated with conformational flexibility, yet the extent and functional implications of their intrinsic disorder have never been fully assessed. Here, through large-scale analysis of comprehensive protein sequence and structure datasets we demonstrate the prevalence of intrinsic structural disorder in RNA-binding proteins and domains. We addressed their functionality through a quantitative description of the evolutionary conservation of disordered segments involved in binding, and investigated the structural implications of flexibility in terms of conformational stability and interface formation. We conclude that the functional role of intrinsically disordered protein segments in RNA-binding is two-fold: first, these regions establish extended, conserved electrostatic interfaces with RNAs via induced fit. Second, conformational flexibility enables them to target different RNA partners, providing multi-functionality, while also ensuring specificity. These findings emphasize the functional importance of intrinsically disordered regions in RNA-binding proteins.

A framework for establishing predictive relationships between specific bacterial 16S rRNA sequence abundances and biotransformation rates.

Science.gov (United States)

Helbling, Damian E; Johnson, David R; Lee, Tae Kwon; Scheidegger, Andreas; Fenner, Kathrin

2015-03-01

The rates at which wastewater treatment plant (WWTP) microbial communities biotransform specific substrates can differ by orders of magnitude among WWTP communities. Differences in taxonomic compositions among WWTP communities may predict differences in the rates of some types of biotransformations. In this work, we present a novel framework for establishing predictive relationships between specific bacterial 16S rRNA sequence abundances and biotransformation rates. We selected ten WWTPs with substantial variation in their environmental and operational metrics and measured the in situ ammonia biotransformation rate constants in nine of them. We isolated total RNA from samples from each WWTP and analyzed 16S rRNA sequence reads. We then developed multivariate models between the measured abundances of specific bacterial 16S rRNA sequence reads and the ammonia biotransformation rate constants. We constructed model scenarios that systematically explored the effects of model regularization, model linearity and non-linearity, and aggregation of 16S rRNA sequences into operational taxonomic units (OTUs) as a function of sequence dissimilarity threshold (SDT). A large percentage (greater than 80%) of model scenarios resulted in well-performing and significant models at intermediate SDTs of 0.13-0.14 and 0.26. The 16S rRNA sequences consistently selected into the well-performing and significant models at those SDTs were classified as Nitrosomonas and Nitrospira groups. We then extend the framework by applying it to the biotransformation rate constants of ten micropollutants measured in batch reactors seeded with the ten WWTP communities. We identified phylogenetic groups that were robustly selected into all well-performing and significant models constructed with biotransformation rates of isoproturon, propachlor, ranitidine, and venlafaxine. These phylogenetic groups can be used as predictive biomarkers of WWTP microbial community activity towards these specific

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

Directory of Open Access Journals (Sweden)

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

Analysis and Visualization of ChIP-Seq and RNA-Seq Sequence Alignments Using ngs.plot.

Science.gov (United States)

Loh, Yong-Hwee Eddie; Shen, Li

2016-01-01

The continual maturation and increasing applications of next-generation sequencing technology in scientific research have yielded ever-increasing amounts of data that need to be effectively and efficiently analyzed and innovatively mined for new biological insights. We have developed ngs.plot-a quick and easy-to-use bioinformatics tool that performs visualizations of the spatial relationships between sequencing alignment enrichment and specific genomic features or regions. More importantly, ngs.plot is customizable beyond the use of standard genomic feature databases to allow the analysis and visualization of user-specified regions of interest generated by the user's own hypotheses. In this protocol, we demonstrate and explain the use of ngs.plot using command line executions, as well as a web-based workflow on the Galaxy framework. We replicate the underlying commands used in the analysis of a true biological dataset that we had reported and published earlier and demonstrate how ngs.plot can easily generate publication-ready figures. With ngs.plot, users would be able to efficiently and innovatively mine their own datasets without having to be involved in the technical aspects of sequence coverage calculations and genomic databases.

Molecular characterization and phylogenetic relationships among microsporidian isolates infecting silkworm, Bombyx mori using small subunit rRNA (SSU-rRNA) gene sequence analysis.

Science.gov (United States)

Nath, B Surendra; Gupta, S K; Bajpai, A K

2012-12-01

The life cycle, spore morphology, pathogenicity, tissue specificity, mode of transmission and small subunit rRNA (SSU-rRNA) gene sequence analysis of the five new microsporidian isolates viz., NIWB-11bp, NIWB-12n, NIWB-13md, NIWB-14b and NIWB-15mb identified from the silkworm, Bombyx mori have been studied along with type species, NIK-1s_mys. The life cycle of the microsporidians identified exhibited the sequential developmental cycles that are similar to the general developmental cycle of the genus, Nosema. The spores showed considerable variations in their shape, length and width. The pathogenicity observed was dose-dependent and differed from each of the microsporidian isolates; the NIWB-15mb was found to be more virulent than other isolates. All of the microsporidians were found to infect most of the tissues examined and showed gonadal infection and transovarial transmission in the infected silkworms. SSU-rRNA sequence based phylogenetic tree placed NIWB-14b, NIWB-12n and NIWB-11bp in a separate branch along with other Nosema species and Nosema bombycis; while NIWB-15mb and NIWB-13md together formed another cluster along with other Nosema species. NIK-1s_mys revealed a signature sequence similar to standard type species, N. bombycis, indicating that NIK-1s_mys is similar to N. bombycis. Based on phylogenetic relationships, branch length information based on genetic distance and nucleotide differences, we conclude that the microsporidian isolates identified are distinctly different from the other known species and belonging to the genus, Nosema. This SSU-rRNA gene sequence analysis method is found to be more useful approach in detecting different and closely related microsporidians of this economically important domestic insect.

FASTQSim: platform-independent data characterization and in silico read generation for NGS datasets.

Science.gov (United States)

Shcherbina, Anna

2014-08-15

High-throughput next generation sequencing technologies have enabled rapid characterization of clinical and environmental samples. Consequently, the largest bottleneck to actionable data has become sample processing and bioinformatics analysis, creating a need for accurate and rapid algorithms to process genetic data. Perfectly characterized in silico datasets are a useful tool for evaluating the performance of such algorithms. Background contaminating organisms are observed in sequenced mixtures of organisms. In silico samples provide exact truth. To create the best value for evaluating algorithms, in silico data should mimic actual sequencer data as closely as possible. FASTQSim is a tool that provides the dual functionality of NGS dataset characterization and metagenomic data generation. FASTQSim is sequencing platform-independent, and computes distributions of read length, quality scores, indel rates, single point mutation rates, indel size, and similar statistics for any sequencing platform. To create training or testing datasets, FASTQSim has the ability to convert target sequences into in silico reads with specific error profiles obtained in the characterization step. FASTQSim enables users to assess the quality of NGS datasets. The tool provides information about read length, read quality, repetitive and non-repetitive indel profiles, and single base pair substitutions. FASTQSim allows the user to simulate individual read datasets that can be used as standardized test scenarios for planning sequencing projects or for benchmarking metagenomic software. In this regard, in silico datasets generated with the FASTQsim tool hold several advantages over natural datasets: they are sequencing platform independent, extremely well characterized, and less expensive to generate. Such datasets are valuable in a number of applications, including the training of assemblers for multiple platforms, benchmarking bioinformatics algorithm performance, and creating challenge

Reconstruction of ribosomal RNA genes from metagenomic data.

Directory of Open Access Journals (Sweden)

Lu Fan

Full Text Available Direct sequencing of environmental DNA (metagenomics has a great potential for describing the 16S rRNA gene diversity of microbial communities. However current approaches using this 16S rRNA gene information to describe community diversity suffer from low taxonomic resolution or chimera problems. Here we describe a new strategy that involves stringent assembly and data filtering to reconstruct full-length 16S rRNA genes from metagenomicpyrosequencing data. Simulations showed that reconstructed 16S rRNA genes provided a true picture of the community diversity, had minimal rates of chimera formation and gave taxonomic resolution down to genus level. The strategy was furthermore compared to PCR-based methods to determine the microbial diversity in two marine sponges. This showed that about 30% of the abundant phylotypes reconstructed from metagenomic data failed to be amplified by PCR. Our approach is readily applicable to existing metagenomic datasets and is expected to lead to the discovery of new microbial phylotypes.

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.

Utility of RNA Sequencing for Analysis of Maize Reproductive Transcriptomes

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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.

16S rRNA gene sequencing in routine identification of anaerobic bacteria isolated from blood cultures

DEFF Research Database (Denmark)

Justesen, Ulrik Stenz; Skov, Marianne Nielsine; Knudsen, Elisa

2010-01-01

A comparison between conventional identification and 16S rRNA gene sequencing of anaerobic bacteria isolated from blood cultures in a routine setting was performed (n = 127). With sequencing, 89% were identified to the species level, versus 52% with conventional identification. The times...

Comparison of two approaches for the classification of 16S rRNA gene sequences.

Science.gov (United States)

Chatellier, Sonia; Mugnier, Nathalie; Allard, Françoise; Bonnaud, Bertrand; Collin, Valérie; van Belkum, Alex; Veyrieras, Jean-Baptiste; Emler, Stefan

2014-10-01

The use of 16S rRNA gene sequences for microbial identification in clinical microbiology is accepted widely, and requires databases and algorithms. We compared a new research database containing curated 16S rRNA gene sequences in combination with the lca (lowest common ancestor) algorithm (RDB-LCA) to a commercially available 16S rDNA Centroid approach. We used 1025 bacterial isolates characterized by biochemistry, matrix-assisted laser desorption/ionization time-of-flight MS and 16S rDNA sequencing. Nearly 80 % of isolates were identified unambiguously at the species level by both classification platforms used. The remaining isolates were mostly identified correctly at the genus level due to the limited resolution of 16S rDNA sequencing. Discrepancies between both 16S rDNA platforms were due to differences in database content and the algorithm used, and could amount to up to 10.5 %. Up to 1.4 % of the analyses were found to be inconclusive. It is important to realize that despite the overall good performance of the pipelines for analysis, some inconclusive results remain that require additional in-depth analysis performed using supplementary methods. © 2014 The Authors.

Co-transcriptomic Analysis by RNA Sequencing to Simultaneously Measure Regulated Gene Expression in Host and Bacterial Pathogen

KAUST Repository

Ravasi, Timothy; Mavromatis, Charalampos Harris; Bokil, Nilesh J.; Schembri, Mark A.; Sweet, Matthew J.

2016-01-01

Intramacrophage pathogens subvert antimicrobial defence pathways using various mechanisms, including the targeting of host TLR-mediated transcriptional responses. Conversely, TLR-inducible host defence mechanisms subject intramacrophage pathogens to stress, thus altering pathogen gene expression programs. Important biological insights can thus be gained through the analysis of gene expression changes in both the host and the pathogen during an infection. Traditionally, research methods have involved the use of qPCR, microarrays and/or RNA sequencing to identify transcriptional changes in either the host or the pathogen. Here we describe the application of RNA sequencing using samples obtained from in vitro infection assays to simultaneously quantify both host and bacterial pathogen gene expression changes, as well as general approaches that can be undertaken to interpret the RNA sequencing data that is generated. These methods can be used to provide insights into host TLR-regulated transcriptional responses to microbial challenge, as well as pathogen subversion mechanisms against such responses.

Co-transcriptomic Analysis by RNA Sequencing to Simultaneously Measure Regulated Gene Expression in Host and Bacterial Pathogen

KAUST Repository

Ravasi, Timothy

2016-01-24

Intramacrophage pathogens subvert antimicrobial defence pathways using various mechanisms, including the targeting of host TLR-mediated transcriptional responses. Conversely, TLR-inducible host defence mechanisms subject intramacrophage pathogens to stress, thus altering pathogen gene expression programs. Important biological insights can thus be gained through the analysis of gene expression changes in both the host and the pathogen during an infection. Traditionally, research methods have involved the use of qPCR, microarrays and/or RNA sequencing to identify transcriptional changes in either the host or the pathogen. Here we describe the application of RNA sequencing using samples obtained from in vitro infection assays to simultaneously quantify both host and bacterial pathogen gene expression changes, as well as general approaches that can be undertaken to interpret the RNA sequencing data that is generated. These methods can be used to provide insights into host TLR-regulated transcriptional responses to microbial challenge, as well as pathogen subversion mechanisms against such responses.

Polyadenylation of RNA transcribed from mammalian SINEs by RNA polymerase III: Complex requirements for nucleotide sequences.

Science.gov (United States)

Borodulina, Olga R; Golubchikova, Julia S; Ustyantsev, Ilia G; Kramerov, Dmitri A

2016-02-01

It is generally accepted that only transcripts synthesized by RNA polymerase II (e.g., mRNA) were subject to AAUAAA-dependent polyadenylation. However, we previously showed that RNA transcribed by RNA polymerase III (pol III) from mouse B2 SINE could be polyadenylated in an AAUAAA-dependent manner. Many species of mammalian SINEs end with the pol III transcriptional terminator (TTTTT) and contain hexamers AATAAA in their A-rich tail. Such SINEs were united into Class T(+), whereas SINEs lacking the terminator and AATAAA sequences were classified as T(-). Here we studied the structural features of SINE pol III transcripts that are necessary for their polyadenylation. Eight and six SINE families from classes T(+) and T(-), respectively, were analyzed. The replacement of AATAAA with AACAAA in T(+) SINEs abolished the RNA polyadenylation. Interestingly, insertion of the polyadenylation signal (AATAAA) and pol III transcription terminator in T(-) SINEs did not result in polyadenylation. The detailed analysis of three T(+) SINEs (B2, DIP, and VES) revealed areas important for the polyadenylation of their pol III transcripts: the polyadenylation signal and terminator in A-rich tail, β region positioned immediately downstream of the box B of pol III promoter, and τ region located upstream of the tail. In DIP and VES (but not in B2), the τ region is a polypyrimidine motif which is also characteristic of many other T(+) SINEs. Most likely, SINEs of different mammals acquired these structural features independently as a result of parallel evolution. Copyright © 2015 Elsevier B.V. All rights reserved.

Comparative and joint analysis of two metagenomic datasets from a biogas fermenter obtained by 454-pyrosequencing.

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Sebastian Jaenicke

Full Text Available Biogas production from renewable resources is attracting increased attention as an alternative energy source due to the limited availability of traditional fossil fuels. Many countries are promoting the use of alternative energy sources for sustainable energy production. In this study, a metagenome from a production-scale biogas fermenter was analysed employing Roche's GS FLX Titanium technology and compared to a previous dataset obtained from the same community DNA sample that was sequenced on the GS FLX platform. Taxonomic profiling based on 16S rRNA-specific sequences and an Environmental Gene Tag (EGT analysis employing CARMA demonstrated that both approaches benefit from the longer read lengths obtained on the Titanium platform. Results confirmed Clostridia as the most prevalent taxonomic class, whereas species of the order Methanomicrobiales are dominant among methanogenic Archaea. However, the analyses also identified additional taxa that were missed by the previous study, including members of the genera Streptococcus, Acetivibrio, Garciella, Tissierella, and Gelria, which might also play a role in the fermentation process leading to the formation of methane. Taking advantage of the CARMA feature to correlate taxonomic information of sequences with their assigned functions, it appeared that Firmicutes, followed by Bacteroidetes and Proteobacteria, dominate within the functional context of polysaccharide degradation whereas Methanomicrobiales represent the most abundant taxonomic group responsible for methane production. Clostridia is the most important class involved in the reductive CoA pathway (Wood-Ljungdahl pathway that is characteristic for acetogenesis. Based on binning of 16S rRNA-specific sequences allocated to the dominant genus Methanoculleus, it could be shown that this genus is represented by several different species. Phylogenetic analysis of these sequences placed them in close proximity to the hydrogenotrophic methanogen

Comparative and Joint Analysis of Two Metagenomic Datasets from a Biogas Fermenter Obtained by 454-Pyrosequencing

Science.gov (United States)

Jaenicke, Sebastian; Ander, Christina; Bekel, Thomas; Bisdorf, Regina; Dröge, Marcus; Gartemann, Karl-Heinz; Jünemann, Sebastian; Kaiser, Olaf; Krause, Lutz; Tille, Felix; Zakrzewski, Martha; Pühler, Alfred

2011-01-01

Biogas production from renewable resources is attracting increased attention as an alternative energy source due to the limited availability of traditional fossil fuels. Many countries are promoting the use of alternative energy sources for sustainable energy production. In this study, a metagenome from a production-scale biogas fermenter was analysed employing Roche's GS FLX Titanium technology and compared to a previous dataset obtained from the same community DNA sample that was sequenced on the GS FLX platform. Taxonomic profiling based on 16S rRNA-specific sequences and an Environmental Gene Tag (EGT) analysis employing CARMA demonstrated that both approaches benefit from the longer read lengths obtained on the Titanium platform. Results confirmed Clostridia as the most prevalent taxonomic class, whereas species of the order Methanomicrobiales are dominant among methanogenic Archaea. However, the analyses also identified additional taxa that were missed by the previous study, including members of the genera Streptococcus, Acetivibrio, Garciella, Tissierella, and Gelria, which might also play a role in the fermentation process leading to the formation of methane. Taking advantage of the CARMA feature to correlate taxonomic information of sequences with their assigned functions, it appeared that Firmicutes, followed by Bacteroidetes and Proteobacteria, dominate within the functional context of polysaccharide degradation whereas Methanomicrobiales represent the most abundant taxonomic group responsible for methane production. Clostridia is the most important class involved in the reductive CoA pathway (Wood-Ljungdahl pathway) that is characteristic for acetogenesis. Based on binning of 16S rRNA-specific sequences allocated to the dominant genus Methanoculleus, it could be shown that this genus is represented by several different species. Phylogenetic analysis of these sequences placed them in close proximity to the hydrogenotrophic methanogen Methanoculleus

Improved taxonomic assignment of human intestinal 16S rRNA sequences by a dedicated reference database

NARCIS (Netherlands)

Ritari, Jarmo; Salojärvi, Jarkko; Lahti, Leo; Vos, de Willem M.

2015-01-01

Background: Current sequencing technology enables taxonomic profiling of microbial ecosystems at high resolution and depth by using the 16S rRNA gene as a phylogenetic marker. Taxonomic assignation of newly acquired data is based on sequence comparisons with comprehensive reference databases to

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

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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.

Linking Maternal and Somatic 5S rRNA types with Different Sequence-Specific Non-LTR Retrotransposons

NARCIS (Netherlands)

Locati, M.D.; Pagano, J.F.B.; Ensink, W.A.; van Olst, M.; van Leeuwen, S.; Nehrdich, U.; Zhu, K.; Spaink, H.P.; Girard, G.; Rauwerda, H.; Jonker, M.J.; Dekker, R.J.; Breit, T.M.

5S rRNA is a ribosomal core component, transcribed from many gene copies organized in genomic repeats. Some eukaryotic species have two 5S rRNA types defined by their predominant expression in oogenesis or adult tissue. Our next-generation sequencing study on zebrafish egg, embryo and adult tissue,

BrAD-seq: Breath Adapter Directional sequencing: a streamlined, ultra-simple and fast library preparation protocol for strand specific mRNA library construction.

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Brad Thomas Townsley

2015-05-01

Full Text Available Next Generation Sequencing (NGS is driving rapid advancement in biological understanding and RNA-sequencing (RNA-seq has become an indispensable tool for biology and medicine. There is a growing need for access to these technologies although preparation of NGS libraries remains a bottleneck to wider adoption. Here we report a novel method for the production of strand specific RNA-seq libraries utilizing inherent properties of double-stranded cDNA to capture and incorporate a sequencing adapter. Breath Adapter Directional sequencing (BrAD-seq reduces sample handling and requires far fewer enzymatic steps than most available methods to produce high quality strand-specific RNA-seq libraries. The method we present is optimized for 3-prime Digital Gene Expression (DGE libraries and can easily extend to full transcript coverage shotgun (SHO type strand-specific libraries and is modularized to accommodate a diversity of RNA and DNA input materials. BrAD-seq offers a highly streamlined and inexpensive option for RNA-seq libraries.

From benchmarking HITS-CLIP peak detection programs to a new method for identification of miRNA-binding sites from Ago2-CLIP data.

Science.gov (United States)

Bottini, Silvia; Hamouda-Tekaya, Nedra; Tanasa, Bogdan; Zaragosi, Laure-Emmanuelle; Grandjean, Valerie; Repetto, Emanuela; Trabucchi, Michele

2017-05-19

Experimental evidence indicates that about 60% of miRNA-binding activity does not follow the canonical rule about the seed matching between miRNA and target mRNAs, but rather a non-canonical miRNA targeting activity outside the seed or with a seed-like motifs. Here, we propose a new unbiased method to identify canonical and non-canonical miRNA-binding sites from peaks identified by Ago2 Cross-Linked ImmunoPrecipitation associated to high-throughput sequencing (CLIP-seq). Since the quality of peaks is of pivotal importance for the final output of the proposed method, we provide a comprehensive benchmarking of four peak detection programs, namely CIMS, PIPE-CLIP, Piranha and Pyicoclip, on four publicly available Ago2-HITS-CLIP datasets and one unpublished in-house Ago2-dataset in stem cells. We measured the sensitivity, the specificity and the position accuracy toward miRNA binding sites identification, and the agreement with TargetScan. Secondly, we developed a new pipeline, called miRBShunter, to identify canonical and non-canonical miRNA-binding sites based on de novo motif identification from Ago2 peaks and prediction of miRNA::RNA heteroduplexes. miRBShunter was tested and experimentally validated on the in-house Ago2-dataset and on an Ago2-PAR-CLIP dataset in human stem cells. Overall, we provide guidelines to choose a suitable peak detection program and a new method for miRNA-target identification. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Alternative splicing of human elastin mRNA indicated by sequence analysis of cloned genomic and complementary DNA

International Nuclear Information System (INIS)

Indik, Z.; Yeh, H.; Ornstein-goldstein, N.; Sheppard, P.; Anderson, N.; Rosenbloom, J.C.; Peltonen, L.; Rosenbloom, J.

1987-01-01

Poly(A) + RNA, isolated from a single 7-mo fetal human aorta, was used to synthesize cDNA by the RNase H method, and the cDNA was inserted into λgt10. Recombinant phage containing elastin sequences were identified by hybridization with cloned, exon-containing fragments of the human elastin gene. Three clones containing inserts of 3.3, 2.7, and 2.3 kilobases were selected for further analysis. Three overlapping clones containing 17.8 kilobases of the human elastin gene were also isolated from genomic libraries. Complete sequence analysis of the six clones demonstrated that: (i) the cDNA encompassed the entire translated portion of the mRNA encoding 786 amino acids, including several unusual hydrophilic amino acid sequences not previously identified in porcine tropoelastin, (ii) exons encoding either hydrophobic or crosslinking domains in the protein alternated in the gene, and (iii) a great abundance of Alu repetitive sequences occurred throughout the introns. The data also indicated substantial alternative splicing of the mRNA. These results suggest the potential for significant variation in the precise molecular structure of the elastic fiber in the human population

Direct detection of RNA in vitro and in situ by target-primed RCA: The impact of E. coli RNase III on the detection efficiency of RNA sequences distanced far from the 3'-end.

Science.gov (United States)

Merkiene, Egle; Gaidamaviciute, Edita; Riauba, Laurynas; Janulaitis, Arvydas; Lagunavicius, Arunas

2010-08-01

We improved the target RNA-primed RCA technique for direct detection and analysis of RNA in vitro and in situ. Previously we showed that the 3' --> 5' single-stranded RNA exonucleolytic activity of Phi29 DNA polymerase converts the target RNA into a primer and uses it for RCA initiation. However, in some cases, the single-stranded RNA exoribonucleolytic activity of the polymerase is hindered by strong double-stranded structures at the 3'-end of target RNAs. We demonstrate that in such hampered cases, the double-stranded RNA-specific Escherichia coli RNase III efficiently assists Phi29 DNA polymerase in converting the target RNA into a primer. These observations extend the target RNA-primed RCA possibilities to test RNA sequences distanced far from the 3'-end and customize this technique for the inner RNA sequence analysis.

MicroRNA prediction using a fixed-order Markov model based on the secondary structure pattern.

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Wei Shen

Full Text Available Predicting miRNAs is an arduous task, due to the diversity of the precursors and complexity of enzyme processes. Although several prediction approaches have reached impressive performances, few of them could achieve a full-function recognition of mature miRNA directly from the candidate hairpins across species. Therefore, researchers continue to seek a more powerful model close to biological recognition to miRNA structure. In this report, we describe a novel miRNA prediction algorithm, known as FOMmiR, using a fixed-order Markov model based on the secondary structural pattern. For a training dataset containing 809 human pre-miRNAs and 6441 human pseudo-miRNA hairpins, the model's parameters were defined and evaluated. The results showed that FOMmiR reached 91% accuracy on the human dataset through 5-fold cross-validation. Moreover, for the independent test datasets, the FOMmiR presented an outstanding prediction in human and other species including vertebrates, Drosophila, worms and viruses, even plants, in contrast to the well-known algorithms and models. Especially, the FOMmiR was not only able to distinguish the miRNA precursors from the hairpins, but also locate the position and strand of the mature miRNA. Therefore, this study provides a new generation of miRNA prediction algorithm, which successfully realizes a full-function recognition of the mature miRNAs directly from the hairpin sequences. And it presents a new understanding of the biological recognition based on the strongest signal's location detected by FOMmiR, which might be closely associated with the enzyme cleavage mechanism during the miRNA maturation.

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

PACCMIT/PACCMIT-CDS: identifying microRNA targets in 3' UTRs and coding sequences.

Science.gov (United States)

Šulc, Miroslav; Marín, Ray M; Robins, Harlan S; Vaníček, Jiří

2015-07-01

The purpose of the proposed web server, publicly available at http://paccmit.epfl.ch, is to provide a user-friendly interface to two algorithms for predicting messenger RNA (mRNA) molecules regulated by microRNAs: (i) PACCMIT (Prediction of ACcessible and/or Conserved MIcroRNA Targets), which identifies primarily mRNA transcripts targeted in their 3' untranslated regions (3' UTRs), and (ii) PACCMIT-CDS, designed to find mRNAs targeted within their coding sequences (CDSs). While PACCMIT belongs among the accurate algorithms for predicting conserved microRNA targets in the 3' UTRs, the main contribution of the web server is 2-fold: PACCMIT provides an accurate tool for predicting targets also of weakly conserved or non-conserved microRNAs, whereas PACCMIT-CDS addresses the lack of similar portals adapted specifically for targets in CDS. The web server asks the user for microRNAs and mRNAs to be analyzed, accesses the precomputed P-values for all microRNA-mRNA pairs from a database for all mRNAs and microRNAs in a given species, ranks the predicted microRNA-mRNA pairs, evaluates their significance according to the false discovery rate and finally displays the predictions in a tabular form. The results are also available for download in several standard formats. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Complete plastid genome sequence of Primula sinensis (Primulaceae: structure comparison, sequence variation and evidence for accD transfer to nucleus

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Tong-Jian Liu

2016-06-01

Full Text Available Species-rich genus Primula L. is a typical plant group with which to understand genetic variance between species in different levels of relationships. Chloroplast genome sequences are used to be the information resource for quantifying this difference and reconstructing evolutionary history. In this study, we reported the complete chloroplast genome sequence of Primula sinensis and compared it with other related species. This genome of chloroplast showed a typical circular quadripartite structure with 150,859 bp in sequence length consisting of 37.2% GC base. Two inverted repeated regions (25,535 bp were separated by a large single-copy region (82,064 bp and a small single-copy region (17,725 bp. The genome consists of 112 genes, including 78 protein-coding genes, 30 tRNA genes and four rRNA genes. Among them, seven coding genes, seven tRNA genes and four rRNA genes have two copies due to their locations in the IR regions. The accD and infA genes lacking intact open reading frames (ORF were identified as pseudogenes. SSR and sequence variation analyses were also performed on the plastome of Primula sinensis, comparing with another available plastome of P. poissonii. The four most variable regions, rpl36–rps8, rps16–trnQ, trnH–psbA and ndhC–trnV, were identified. Phylogenetic relationship estimates using three sub-datasets extracted from a matrix of 57 protein-coding gene sequences showed the identical result that was consistent with previous studies. A transcript found from P. sinensis transcriptome showed a high similarity to plastid accD functional region and was identified as a putative plastid transit peptide at the N-terminal region. The result strongly suggested that plastid accD has been functionally transferred to the nucleus in P. sinensis.

An AU-rich element in the 3{prime} untranslated region of the spinach chloroplast petD gene participates in sequence-specific RNA-protein complex formation

Energy Technology Data Exchange (ETDEWEB)

Chen, Qiuyun; Adams, C.C.; Usack, L. [Cornell Univ., Ithaca, NY (United States)] [and others

1995-04-01

In chloroplasts, the 3{prime} untranslated regions of most mRNAs contain a stem-loop-forming inverted repeat (IR) sequence that is required for mRNA stability and correct 3{prime}-end formation. The IR regions of several mRNAs are also known to bind chloroplast proteins, as judged from in vitro gel mobility shift and UV cross-linking assays, and these RNA-protein interactions may be involved in the regulation of chloroplast mRNA processing and/or stability. Here we describe in detail the RNA and protein components that are involved in 3{prime} IR-containing RNA (3{prime} IR-RNA)-protein complex formation for the spinach chloroplast petD gene, which encodes subunit IV of the cytochrome b{sub 6}/f complex. We show that the complex contains 55-, 41-, and 29-kDa RNA-binding proteins (ribonucleoproteins [RNPs]). These proteins together protect a 90-nucleotide segment of RNA from RNase T{sub 1} digestion; this RNA contains the IR and downstream flanking sequences. Competition experiments using 3{prime} IR-RNAs from the psbA or rbcL gene demonstrate that the RNPs have a strong specificity for the petD sequence. Site-directed mutagenesis was carried out to define the RNA sequence elements required for complex formation. These studies identified an 8-nucleotide AU-rich sequence downstream of the IR; mutations within this sequence had moderate to severe effects on RNA-protein complex formation. Although other similar sequences are present in the petD 3{prime} untranslated region, only a single copy, which we have termed box II, appears to be essential for in vivo protein binding. In addition, the IR itself is necessary for optimal complex formation. These two sequence elements together with an RNP complex may direct correct 3{prime}-end processing and/or influence the stability of petD mRNA in chloroplasts. 48 refs., 9 figs., 2 tabs.

RNA-SSPT: RNA Secondary Structure Prediction Tools.

Science.gov (United States)

Ahmad, Freed; Mahboob, Shahid; Gulzar, Tahsin; Din, Salah U; Hanif, Tanzeela; Ahmad, Hifza; Afzal, Muhammad

2013-01-01

The prediction of RNA structure is useful for understanding evolution for both in silico and in vitro studies. Physical methods like NMR studies to predict RNA secondary structure are expensive and difficult. Computational RNA secondary structure prediction is easier. Comparative sequence analysis provides the best solution. But secondary structure prediction of a single RNA sequence is challenging. RNA-SSPT is a tool that computationally predicts secondary structure of a single RNA sequence. Most of the RNA secondary structure prediction tools do not allow pseudoknots in the structure or are unable to locate them. Nussinov dynamic programming algorithm has been implemented in RNA-SSPT. The current studies shows only energetically most favorable secondary structure is required and the algorithm modification is also available that produces base pairs to lower the total free energy of the secondary structure. For visualization of RNA secondary structure, NAVIEW in C language is used and modified in C# for tool requirement. RNA-SSPT is built in C# using Dot Net 2.0 in Microsoft Visual Studio 2005 Professional edition. The accuracy of RNA-SSPT is tested in terms of Sensitivity and Positive Predicted Value. It is a tool which serves both secondary structure prediction and secondary structure visualization purposes.

Divergent homologs of the predicted small RNA BpCand697 in Burkholderia spp.

Science.gov (United States)

Damiri, Nadzirah; Mohd-Padil, Hirzahida; Firdaus-Raih, Mohd

2015-09-01

The small RNA (sRNA) gene candidate, BpCand697 was previously reported to be unique to Burkholderia spp. and is encoded at 3' non-coding region of a putative AraC family transcription regulator gene. This study demonstrates the conservation of BpCand697 sequence across 32 Burkholderia spp. including B. pseudomallei, B. mallei, B. thailandensis and Burkholderia sp. by integrating both sequence homology and secondary structural analyses of BpCand697 within the dataset. The divergent sequence of BpCand697 was also used as a discriminatory power in clustering the dataset according to the potential virulence of Burkholderia spp., showing that B. thailandensis was clearly secluded from the virulent cluster of B. pseudomallei and B. mallei. Finally, the differential co-transcript expression of BpCand697 and its flanking gene, bpsl2391 was detected in Burkholderia pseudomallei D286 after grown under two different culture conditions using nutrient-rich and minimal media. It is hypothesized that the differential expression of BpCand697-bpsl2391 co-transcript between the two standard prepared media might correlate with nutrient availability in the culture media, suggesting that the physical co-localization of BpCand697 in B. pseudomallei D286 might be directly or indirectly involved with the transcript regulation of bpsl2391 under the selected in vitro culture conditions.

The complete nucleotide sequence of RNA 3 of a peach isolate of Prunus necrotic ringspot virus.

Science.gov (United States)

Hammond, R W; Crosslin, J M

1995-04-01

The complete nucleotide sequence of RNA 3 of the PE-5 peach isolate of Prunus necrotic ringspot ilarvirus (PNRSV) was obtained from cloned cDNA. The RNA sequence is 1941 nucleotides and contains two open reading frames (ORFs). ORF 1 consisted of 284 amino acids with a calculated molecular weight of 31,729 Da and ORF 2 contained 224 amino acids with a calculated molecular weight of 25,018 Da. ORF 2 corresponds to the coat protein gene. Expression of ORF 2 engineered into a pTrcHis vector in Escherichia coli results in a fusion polypeptide of approximately 28 kDa which cross-reacts with PNRSV polyclonal antiserum. Analysis of the coat protein amino acid sequence reveals a putative "zinc-finger" domain at the amino-terminal portion of the protein. Two tetranucleotide AUGC motifs occur in the 3'-UTR of the RNA and may function in coat protein binding and genome activation. ORF 1 homologies to other ilarviruses and alfalfa mosaic virus are confined to limited regions of conserved amino acids. The translated amino acid sequence of the coat protein gene shows 92% similarity to one isolate of apple mosaic virus, a closely related member of the ilarvirus group of plant viruses, but only 66% similarity to the amino acid sequence of the coat protein gene of a second isolate. These relationships are also reflected at the nucleotide sequence level. These results in one instance confirm the close similarities observed at the biophysical and serological levels between these two viruses, but on the other hand call into question the nomenclature used to describe these viruses.

GLASSgo – Automated and Reliable Detection of sRNA Homologs From a Single Input Sequence

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Steffen C. Lott

2018-04-01

Full Text Available Bacterial small RNAs (sRNAs are important post-transcriptional regulators of gene expression. The functional and evolutionary characterization of sRNAs requires the identification of homologs, which is frequently challenging due to their heterogeneity, short length and partly, little sequence conservation. We developed the GLobal Automatic Small RNA Search go (GLASSgo algorithm to identify sRNA homologs in complex genomic databases starting from a single sequence. GLASSgo combines an iterative BLAST strategy with pairwise identity filtering and a graph-based clustering method that utilizes RNA secondary structure information. We tested the specificity, sensitivity and runtime of GLASSgo, BLAST and the combination RNAlien/cmsearch in a typical use case scenario on 40 bacterial sRNA families. The sensitivity of the tested methods was similar, while the specificity of GLASSgo and RNAlien/cmsearch was significantly higher than that of BLAST. GLASSgo was on average ∼87 times faster than RNAlien/cmsearch, and only ∼7.5 times slower than BLAST, which shows that GLASSgo optimizes the trade-off between speed and accuracy in the task of finding sRNA homologs. GLASSgo is fully automated, whereas BLAST often recovers only parts of homologs and RNAlien/cmsearch requires extensive additional bioinformatic work to get a comprehensive set of homologs. GLASSgo is available as an easy-to-use web server to find homologous sRNAs in large databases.

Evolution of blue-flowered species of genus Linum based on high-throughput sequencing of ribosomal RNA genes.

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Bolsheva, Nadezhda L; Melnikova, Nataliya V; Kirov, Ilya V; Speranskaya, Anna S; Krinitsina, Anastasia A; Dmitriev, Alexey A; Belenikin, Maxim S; Krasnov, George S; Lakunina, Valentina A; Snezhkina, Anastasiya V; Rozhmina, Tatiana A; Samatadze, Tatiana E; Yurkevich, Olga Yu; Zoshchuk, Svyatoslav A; Amosova, Аlexandra V; Kudryavtseva, Anna V; Muravenko, Olga V

2017-12-28

The species relationships within the genus Linum have already been studied several times by means of different molecular and phylogenetic approaches. Nevertheless, a number of ambiguities in phylogeny of Linum still remain unresolved. In particular, the species relationships within the sections Stellerolinum and Dasylinum need further clarification. Also, the question of independence of the species of the section Adenolinum still remains unanswered. Moreover, the relationships of L. narbonense and other species of the section Linum require further clarification. Additionally, the origin of tetraploid species of the section Linum (2n = 30) including the cultivated species L. usitatissimum has not been explored. The present study examines the phylogeny of blue-flowered species of Linum by comparisons of 5S rRNA gene sequences as well as ITS1 and ITS2 sequences of 35S rRNA genes. High-throughput sequencing has been used for analysis of multicopy rRNA gene families. In addition to the molecular phylogenetic analysis, the number and chromosomal localization of 5S and 35S rDNA sites has been determined by FISH. Our findings confirm that L. stelleroides forms a basal branch from the clade of blue-flowered flaxes which is independent of the branch formed by species of the sect. Dasylinum. The current molecular phylogenetic approaches, the cytogenetic analysis as well as different genomic DNA fingerprinting methods applied previously did not discriminate certain species within the sect. Adenolinum. The allotetraploid cultivated species L. usitatissimum and its wild ancestor L. angustifolium (2n = 30) could originate either as the result of hybridization of two diploid species (2n = 16) related to the modern L. gandiflorum and L. decumbens, or hybridization of a diploid species (2n = 16) and a diploid ancestor of modern L. narbonense (2n = 14). High-throughput sequencing of multicopy rRNA gene families allowed us to make several adjustments to the

Application of small RNA sequencing to identify microRNAs in acute kidney injury and fibrosis

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Pellegrini, Kathryn L. [Department of Medicine, Renal Division, Brigham and Women' s Hospital, Harvard Medical School, Boston, MA (United States); Gerlach, Cory V. [Department of Medicine, Renal Division, Brigham and Women' s Hospital, Harvard Medical School, Boston, MA (United States); Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA (United States); Laboratory of Systems Pharmacology, Harvard Program in Therapeutic Sciences, Harvard Medical School, Boston, MA (United States); Craciun, Florin L.; Ramachandran, Krithika [Department of Medicine, Renal Division, Brigham and Women' s Hospital, Harvard Medical School, Boston, MA (United States); Bijol, Vanesa [Department of Pathology, Brigham and Women' s Hospital, Harvard Medical School, Boston, MA (United States); Kissick, Haydn T. [Department of Surgery, Urology Division, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA (United States); Vaidya, Vishal S., E-mail: vvaidya@bwh.harvard.edu [Department of Medicine, Renal Division, Brigham and Women' s Hospital, Harvard Medical School, Boston, MA (United States); Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA (United States); Laboratory of Systems Pharmacology, Harvard Program in Therapeutic Sciences, Harvard Medical School, Boston, MA (United States)

2016-12-01

Establishing a microRNA (miRNA) expression profile in affected tissues provides an important foundation for the discovery of miRNAs involved in the development or progression of pathologic conditions. We conducted small RNA sequencing to generate a temporal profile of miRNA expression in the kidneys using a mouse model of folic acid-induced (250 mg/kg i.p.) kidney injury and fibrosis. From the 103 miRNAs that were differentially expressed over the time course (> 2-fold, p < 0.05), we chose to further investigate miR-18a-5p, which is expressed during the acute stage of the injury; miR-132-3p, which is upregulated during transition between acute and fibrotic injury; and miR-146b-5p, which is highly expressed at the peak of fibrosis. Using qRT-PCR, we confirmed the increased expression of these candidate miRNAs in the folic acid model as well as in other established mouse models of acute injury (ischemia/reperfusion injury) and fibrosis (unilateral ureteral obstruction). In situ hybridization confirmed high expression of miR-18a-5p, miR-132-3p and miR-146b-5p throughout the kidney cortex in mice and humans with severe kidney injury or fibrosis. When primary human proximal tubular epithelial cells were treated with model nephrotoxicants such as cadmium chloride (CdCl{sub 2}), arsenic trioxide, aristolochic acid (AA), potassium dichromate (K{sub 2}Cr{sub 2}O{sub 7}) and cisplatin, miRNA-132-3p was upregulated 4.3-fold after AA treatment and 1.5-fold after K{sub 2}Cr{sub 2}O{sub 7} and CdCl{sub 2} treatment. These results demonstrate the application of temporal small RNA sequencing to identify miR-18a, miR-132 and miR-146b as differentially expressed miRNAs during distinct phases of kidney injury and fibrosis progression. - Highlights: • We used small RNA sequencing to identify differentially expressed miRNAs in kidney. • Distinct patterns were found for acute injury and fibrotic stages in the kidney. • Upregulation of miR-18a, -132 and -146b was confirmed in mice

MicroRNA and piRNA profiles in normal human testis detected by next generation sequencing.

Directory of Open Access Journals (Sweden)

Qingling Yang

Full Text Available BACKGROUND: MicroRNAs (miRNAs are the class of small endogenous RNAs that play an important regulatory role in cells by negatively affecting gene expression at transcriptional and post-transcriptional levels. There have been extensive studies aiming to discover miRNAs and to analyze their functions in the cells from a variety of species. However, there are no published studies of miRNA profiles in human testis using next generation sequencing (NGS technology. RESULTS: We employed Solexa sequencing technology to profile miRNAs in normal human testis. Total 770 known and 5 novel human miRNAs, and 20121 piRNAs were detected, indicating that the human testis has a complex population of small RNAs. The expression of 15 known and 5 novel detected miRNAs was validated by qRT-PCR. We have also predicted the potential target genes of the abundant known and novel miRNAs, and subjected them to GO and pathway analysis, revealing the involvement of miRNAs in many important biological phenomenon including meiosis and p53-related pathways that are implicated in the regulation of spermatogenesis. CONCLUSIONS: This study reports the first genome-wide miRNA profiles in human testis using a NGS approach. The presence of large number of miRNAs and the nature of their target genes suggested that miRNAs play important roles in spermatogenesis. Here we provide a useful resource for further elucidation of the regulatory role of miRNAs and piRNAs in the spermatogenesis. It may also facilitate the development of prophylactic strategies for male infertility.

Inhibition of hepatitis B virus replication with linear DNA sequences expressing antiviral micro-RNA shuttles

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Chattopadhyay, Saket; Ely, Abdullah; Bloom, Kristie; Weinberg, Marc S. [Antiviral Gene Therapy Research Unit, University of the Witwatersrand (South Africa); Arbuthnot, Patrick, E-mail: Patrick.Arbuthnot@wits.ac.za [Antiviral Gene Therapy Research Unit, University of the Witwatersrand (South Africa)

2009-11-20

RNA interference (RNAi) may be harnessed to inhibit viral gene expression and this approach is being developed to counter chronic infection with hepatitis B virus (HBV). Compared to synthetic RNAi activators, DNA expression cassettes that generate silencing sequences have advantages of sustained efficacy and ease of propagation in plasmid DNA (pDNA). However, the large size of pDNAs and inclusion of sequences conferring antibiotic resistance and immunostimulation limit delivery efficiency and safety. To develop use of alternative DNA templates that may be applied for therapeutic gene silencing, we assessed the usefulness of PCR-generated linear expression cassettes that produce anti-HBV micro-RNA (miR) shuttles. We found that silencing of HBV markers of replication was efficient (>75%) in cell culture and in vivo. miR shuttles were processed to form anti-HBV guide strands and there was no evidence of induction of the interferon response. Modification of terminal sequences to include flanking human adenoviral type-5 inverted terminal repeats was easily achieved and did not compromise silencing efficacy. These linear DNA sequences should have utility in the development of gene silencing applications where modifications of terminal elements with elimination of potentially harmful and non-essential sequences are required.

Inhibition of hepatitis B virus replication with linear DNA sequences expressing antiviral micro-RNA shuttles

International Nuclear Information System (INIS)

Chattopadhyay, Saket; Ely, Abdullah; Bloom, Kristie; Weinberg, Marc S.; Arbuthnot, Patrick

2009-01-01

RNA interference (RNAi) may be harnessed to inhibit viral gene expression and this approach is being developed to counter chronic infection with hepatitis B virus (HBV). Compared to synthetic RNAi activators, DNA expression cassettes that generate silencing sequences have advantages of sustained efficacy and ease of propagation in plasmid DNA (pDNA). However, the large size of pDNAs and inclusion of sequences conferring antibiotic resistance and immunostimulation limit delivery efficiency and safety. To develop use of alternative DNA templates that may be applied for therapeutic gene silencing, we assessed the usefulness of PCR-generated linear expression cassettes that produce anti-HBV micro-RNA (miR) shuttles. We found that silencing of HBV markers of replication was efficient (>75%) in cell culture and in vivo. miR shuttles were processed to form anti-HBV guide strands and there was no evidence of induction of the interferon response. Modification of terminal sequences to include flanking human adenoviral type-5 inverted terminal repeats was easily achieved and did not compromise silencing efficacy. These linear DNA sequences should have utility in the development of gene silencing applications where modifications of terminal elements with elimination of potentially harmful and non-essential sequences are required.

DeAnnIso: a tool for online detection and annotation of isomiRs from small RNA sequencing data.

Science.gov (United States)

Zhang, Yuanwei; Zang, Qiguang; Zhang, Huan; Ban, Rongjun; Yang, Yifan; Iqbal, Furhan; Li, Ao; Shi, Qinghua

2016-07-08

Small RNA (sRNA) Sequencing technology has revealed that microRNAs (miRNAs) are capable of exhibiting frequent variations from their canonical sequences, generating multiple variants: the isoforms of miRNAs (isomiRs). However, integrated tool to precisely detect and systematically annotate isomiRs from sRNA sequencing data is still in great demand. Here, we present an online tool, DeAnnIso (Detection and Annotation of IsomiRs from sRNA sequencing data). DeAnnIso can detect all the isomiRs in an uploaded sample, and can extract the differentially expressing isomiRs from paired or multiple samples. Once the isomiRs detection is accomplished, detailed annotation information, including isomiRs expression, isomiRs classification, SNPs in miRNAs and tissue specific isomiR expression are provided to users. Furthermore, DeAnnIso provides a comprehensive module of target analysis and enrichment analysis for the selected isomiRs. Taken together, DeAnnIso is convenient for users to screen for isomiRs of their interest and useful for further functional studies. The server is implemented in PHP + Perl + R and available to all users for free at: http://mcg.ustc.edu.cn/bsc/deanniso/ and http://mcg2.ustc.edu.cn/bsc/deanniso/. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Genetic relatedness of orbiviruses by RNA-RNA blot hybridization

International Nuclear Information System (INIS)

Bodkin, D.K.

1985-01-01

RNA-RNA blot hybridization was developed in order to identify type-specific genes among double-stranded (ds) RNA viruses, to assess the genetic relatedness of dsRNA viruses and to classify new strains. Viral dsRNA segments were electrophoresed through 10% polyacrylamide gels, transferred to membranes, and hybridized to [5' 32 P]-pCp labeled genomic RNA from a related strain. Hybridization was performed at 52 0 C, 50% formamide, 5X SSC. Under these conditions heterologous RNA species must share ≥ 74% sequence homology in order to form stable dsRNA hybrids. Cognate genes of nine members of the Palyam serogroup of orbiviruses were identified and their sequence relatedness to the prototype. Palyam virus, was determined. Reciprocal blot hybridizations were performed using radiolabeled genomic RNA of all members of the Palyam serogroup. Unique and variant genes were identified by lack of cross-homology or by weak homology between segments. Since genes 2 and 6 exhibited the highest degree of sequence variability, response to the vertebrate immune system may be a major cause of sequence divergence among members of a single serogroup. Changuinola serogroup isolates were compared by dot-blot hybridization, while Colorado tick fever (CTF) serogroup isolates were compared by the RNA-RNA blot hybridization procedure described for reovirus and Palyam serogroup isolates. Preliminary blot hybridization data were also obtained on the relatedness of members of different Orbivirus serogroups

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

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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.

Sequence, 'subtle' alternative splicing and expression of the CYYR1 (cysteine/tyrosine-rich 1) mRNA in human neuroendocrine tumors