QuickRNASeq lifts large-scale RNA-seq data analyses to the next level of automation and interactive visualization.

PubMed

Zhao, Shanrong; Xi, Li; Quan, Jie; Xi, Hualin; Zhang, Ying; von Schack, David; Vincent, Michael; Zhang, Baohong

2016-01-08

RNA sequencing (RNA-seq), a next-generation sequencing technique for transcriptome profiling, is being increasingly used, in part driven by the decreasing cost of sequencing. Nevertheless, the analysis of the massive amounts of data generated by large-scale RNA-seq remains a challenge. Multiple algorithms pertinent to basic analyses have been developed, and there is an increasing need to automate the use of these tools so as to obtain results in an efficient and user friendly manner. Increased automation and improved visualization of the results will help make the results and findings of the analyses readily available to experimental scientists. By combing the best open source tools developed for RNA-seq data analyses and the most advanced web 2.0 technologies, we have implemented QuickRNASeq, a pipeline for large-scale RNA-seq data analyses and visualization. The QuickRNASeq workflow consists of three main steps. In Step #1, each individual sample is processed, including mapping RNA-seq reads to a reference genome, counting the numbers of mapped reads, quality control of the aligned reads, and SNP (single nucleotide polymorphism) calling. Step #1 is computationally intensive, and can be processed in parallel. In Step #2, the results from individual samples are merged, and an integrated and interactive project report is generated. All analyses results in the report are accessible via a single HTML entry webpage. Step #3 is the data interpretation and presentation step. The rich visualization features implemented here allow end users to interactively explore the results of RNA-seq data analyses, and to gain more insights into RNA-seq datasets. In addition, we used a real world dataset to demonstrate the simplicity and efficiency of QuickRNASeq in RNA-seq data analyses and interactive visualizations. The seamless integration of automated capabilites with interactive visualizations in QuickRNASeq is not available in other published RNA-seq pipelines. The high degree

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

PubMed

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

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

PubMed Central

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

2009-01-01

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, ~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 siRNAs. PMID

Preparation of highly multiplexed small RNA sequencing libraries.

PubMed

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.

Accurate multiple sequence-structure alignment of RNA sequences using combinatorial optimization.

PubMed

Bauer, Markus; Klau, Gunnar W; Reinert, Knut

2007-07-27

The discovery of functional non-coding RNA sequences has led to an increasing interest in algorithms related to RNA analysis. Traditional sequence alignment algorithms, however, fail at computing reliable alignments of low-homology RNA sequences. The spatial conformation of RNA sequences largely determines their function, and therefore RNA alignment algorithms have to take structural information into account. We present a graph-based representation for sequence-structure alignments, which we model as an integer linear program (ILP). We sketch how we compute an optimal or near-optimal solution to the ILP using methods from combinatorial optimization, and present results on a recently published benchmark set for RNA alignments. The implementation of our algorithm yields better alignments in terms of two published scores than the other programs that we tested: This is especially the case with an increasing number of input sequences. Our program LARA is freely available for academic purposes from http://www.planet-lisa.net.

Terminator oligo blocking efficiently eliminates rRNA from Drosophila small RNA sequencing libraries.

PubMed

Wickersheim, Michelle L; Blumenstiel, Justin P

2013-11-01

A large number of methods are available to deplete ribosomal RNA reads from high-throughput RNA sequencing experiments. Such methods are critical for sequencing Drosophila small RNAs between 20 and 30 nucleotides because size selection is not typically sufficient to exclude the highly abundant class of 30 nucleotide 2S rRNA. Here we demonstrate that pre-annealing terminator oligos complimentary to Drosophila 2S rRNA prior to 5' adapter ligation and reverse transcription efficiently depletes 2S rRNA sequences from the sequencing reaction in a simple and inexpensive way. This depletion is highly specific and is achieved with minimal perturbation of miRNA and piRNA profiles.

ssHMM: extracting intuitive sequence-structure motifs from high-throughput RNA-binding protein data

PubMed Central

Krestel, Ralf; Ohler, Uwe; Vingron, Martin; Marsico, Annalisa

2017-01-01

Abstract RNA-binding proteins (RBPs) play an important role in RNA post-transcriptional regulation and recognize target RNAs via sequence-structure motifs. The extent to which RNA structure influences protein binding in the presence or absence of a sequence motif is still poorly understood. Existing RNA motif finders either take the structure of the RNA only partially into account, or employ models which are not directly interpretable as sequence-structure motifs. We developed ssHMM, an RNA motif finder based on a hidden Markov model (HMM) and Gibbs sampling which fully captures the relationship between RNA sequence and secondary structure preference of a given RBP. Compared to previous methods which output separate logos for sequence and structure, it directly produces a combined sequence-structure motif when trained on a large set of sequences. ssHMM’s model is visualized intuitively as a graph and facilitates biological interpretation. ssHMM can be used to find novel bona fide sequence-structure motifs of uncharacterized RBPs, such as the one presented here for the YY1 protein. ssHMM reaches a high motif recovery rate on synthetic data, it recovers known RBP motifs from CLIP-Seq data, and scales linearly on the input size, being considerably faster than MEMERIS and RNAcontext on large datasets while being on par with GraphProt. It is freely available on Github and as a Docker image. PMID:28977546

Evaluation of 16S rRNA amplicon sequencing using two next-generation sequencing technologies for phylogenetic analysis of the rumen bacterial community in steers

USDA-ARS?s Scientific Manuscript database

Next generation sequencing technologies have vastly changed the approach of sequencing of the 16S rRNA gene for studies in microbial ecology. Three distinct technologies are available for large-scale 16S sequencing. All three are subject to biases introduced by sequencing error rates, amplificatio...

Using relational databases for improved sequence similarity searching and large-scale genomic analyses.

PubMed

Mackey, Aaron J; Pearson, William R

2004-10-01

Relational databases are designed to integrate diverse types of information and manage large sets of search results, greatly simplifying genome-scale analyses. Relational databases are essential for management and analysis of large-scale sequence analyses, and can also be used to improve the statistical significance of similarity searches by focusing on subsets of sequence libraries most likely to contain homologs. This unit describes using relational databases to improve the efficiency of sequence similarity searching and to demonstrate various large-scale genomic analyses of homology-related data. This unit describes the installation and use of a simple protein sequence database, seqdb_demo, which is used as a basis for the other protocols. These include basic use of the database to generate a novel sequence library subset, how to extend and use seqdb_demo for the storage of sequence similarity search results and making use of various kinds of stored search results to address aspects of comparative genomic analysis.

Proteogenomic database construction driven from large scale RNA-seq data.

PubMed

Woo, Sunghee; Cha, Seong Won; Merrihew, Gennifer; He, Yupeng; Castellana, Natalie; Guest, Clark; MacCoss, Michael; Bafna, Vineet

2014-01-03

The advent of inexpensive RNA-seq technologies and other deep sequencing technologies for RNA has the promise to radically improve genomic annotation, providing information on transcribed regions and splicing events in a variety of cellular conditions. Using MS-based proteogenomics, many of these events can be confirmed directly at the protein level. However, the integration of large amounts of redundant RNA-seq data and mass spectrometry data poses a challenging problem. Our paper addresses this by construction of a compact database that contains all useful information expressed in RNA-seq reads. Applying our method to cumulative C. elegans data reduced 496.2 GB of aligned RNA-seq SAM files to 410 MB of splice graph database written in FASTA format. This corresponds to 1000× compression of data size, without loss of sensitivity. We performed a proteogenomics study using the custom data set, using a completely automated pipeline, and identified a total of 4044 novel events, including 215 novel genes, 808 novel exons, 12 alternative splicings, 618 gene-boundary corrections, 245 exon-boundary changes, 938 frame shifts, 1166 reverse strands, and 42 translated UTRs. Our results highlight the usefulness of transcript + proteomic integration for improved genome annotations.

DSAP: deep-sequencing small RNA analysis pipeline.

PubMed

Huang, Po-Jung; Liu, Yi-Chung; Lee, Chi-Ching; Lin, Wei-Chen; Gan, Richie Ruei-Chi; Lyu, Ping-Chiang; Tang, Petrus

2010-07-01

DSAP is an automated multiple-task web service designed to provide a total solution to analyzing deep-sequencing small RNA datasets generated by next-generation sequencing technology. DSAP uses a tab-delimited file as an input format, which holds the unique sequence reads (tags) and their corresponding number of copies generated by the Solexa sequencing platform. The input data will go through four analysis steps in DSAP: (i) cleanup: removal of adaptors and poly-A/T/C/G/N nucleotides; (ii) clustering: grouping of cleaned sequence tags into unique sequence clusters; (iii) non-coding RNA (ncRNA) matching: sequence homology mapping against a transcribed sequence library from the ncRNA database Rfam (http://rfam.sanger.ac.uk/); and (iv) known miRNA matching: detection of known miRNAs in miRBase (http://www.mirbase.org/) based on sequence homology. The expression levels corresponding to matched ncRNAs and miRNAs are summarized in multi-color clickable bar charts linked to external databases. DSAP is also capable of displaying miRNA expression levels from different jobs using a log(2)-scaled color matrix. Furthermore, a cross-species comparative function is also provided to show the distribution of identified miRNAs in different species as deposited in miRBase. DSAP is available at http://dsap.cgu.edu.tw.

PRADA: pipeline for RNA sequencing data analysis.

PubMed

Torres-García, Wandaliz; Zheng, Siyuan; Sivachenko, Andrey; Vegesna, Rahulsimham; Wang, Qianghu; Yao, Rong; Berger, Michael F; Weinstein, John N; Getz, Gad; Verhaak, Roel G W

2014-08-01

Technological advances in high-throughput sequencing necessitate improved computational tools for processing and analyzing large-scale datasets in a systematic automated manner. For that purpose, we have developed PRADA (Pipeline for RNA-Sequencing Data Analysis), a flexible, modular and highly scalable software platform that provides many different types of information available by multifaceted analysis starting from raw paired-end RNA-seq data: gene expression levels, quality metrics, detection of unsupervised and supervised fusion transcripts, detection of intragenic fusion variants, homology scores and fusion frame classification. PRADA uses a dual-mapping strategy that increases sensitivity and refines the analytical endpoints. PRADA has been used extensively and successfully in the glioblastoma and renal clear cell projects of The Cancer Genome Atlas program.  http://sourceforge.net/projects/prada/  gadgetz@broadinstitute.org or rverhaak@mdanderson.org  Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Precision medicine in the age of big data: The present and future role of large-scale unbiased sequencing in drug discovery and development.

PubMed

Vicini, P; Fields, O; Lai, E; Litwack, E D; Martin, A-M; Morgan, T M; Pacanowski, M A; Papaluca, M; Perez, O D; Ringel, M S; Robson, M; Sakul, H; Vockley, J; Zaks, T; Dolsten, M; Søgaard, M

2016-02-01

High throughput molecular and functional profiling of patients is a key driver of precision medicine. DNA and RNA characterization has been enabled at unprecedented cost and scale through rapid, disruptive progress in sequencing technology, but challenges persist in data management and interpretation. We analyze the state-of-the-art of large-scale unbiased sequencing in drug discovery and development, including technology, application, ethical, regulatory, policy and commercial considerations, and discuss issues of LUS implementation in clinical and regulatory practice. © 2015 American Society for Clinical Pharmacology and Therapeutics.

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

PubMed

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.

Structurally complex and highly active RNA ligases derived from random RNA sequences

NASA Technical Reports Server (NTRS)

Ekland, E. H.; Szostak, J. W.; Bartel, D. P.

1995-01-01

Seven families of RNA ligases, previously isolated from random RNA sequences, fall into three classes on the basis of secondary structure and regiospecificity of ligation. Two of the three classes of ribozymes have been engineered to act as true enzymes, catalyzing the multiple-turnover transformation of substrates into products. The most complex of these ribozymes has a minimal catalytic domain of 93 nucleotides. An optimized version of this ribozyme has a kcat exceeding one per second, a value far greater than that of most natural RNA catalysts and approaching that of comparable protein enzymes. The fact that such a large and complex ligase emerged from a very limited sampling of sequence space implies the existence of a large number of distinct RNA structures of equivalent complexity and activity.

Modeling bias and variation in the stochastic processes of small RNA sequencing

PubMed Central

Etheridge, Alton; Sakhanenko, Nikita; Galas, David

2017-01-01

Abstract The use of RNA-seq as the preferred method for the discovery and validation of small RNA biomarkers has been hindered by high quantitative variability and biased sequence counts. In this paper we develop a statistical model for sequence counts that accounts for ligase bias and stochastic variation in sequence counts. This model implies a linear quadratic relation between the mean and variance of sequence counts. Using a large number of sequencing datasets, we demonstrate how one can use the generalized additive models for location, scale and shape (GAMLSS) distributional regression framework to calculate and apply empirical correction factors for ligase bias. Bias correction could remove more than 40% of the bias for miRNAs. Empirical bias correction factors appear to be nearly constant over at least one and up to four orders of magnitude of total RNA input and independent of sample composition. Using synthetic mixes of known composition, we show that the GAMLSS approach can analyze differential expression with greater accuracy, higher sensitivity and specificity than six existing algorithms (DESeq2, edgeR, EBSeq, limma, DSS, voom) for the analysis of small RNA-seq data. PMID:28369495

Cloud-based bioinformatics workflow platform for large-scale next-generation sequencing analyses

PubMed Central

Liu, Bo; Madduri, Ravi K; Sotomayor, Borja; Chard, Kyle; Lacinski, Lukasz; Dave, Utpal J; Li, Jianqiang; Liu, Chunchen; Foster, Ian T

2014-01-01

Due to the upcoming data deluge of genome data, the need for storing and processing large-scale genome data, easy access to biomedical analyses tools, efficient data sharing and retrieval has presented significant challenges. The variability in data volume results in variable computing and storage requirements, therefore biomedical researchers are pursuing more reliable, dynamic and convenient methods for conducting sequencing analyses. This paper proposes a Cloud-based bioinformatics workflow platform for large-scale next-generation sequencing analyses, which enables reliable and highly scalable execution of sequencing analyses workflows in a fully automated manner. Our platform extends the existing Galaxy workflow system by adding data management capabilities for transferring large quantities of data efficiently and reliably (via Globus Transfer), domain-specific analyses tools preconfigured for immediate use by researchers (via user-specific tools integration), automatic deployment on Cloud for on-demand resource allocation and pay-as-you-go pricing (via Globus Provision), a Cloud provisioning tool for auto-scaling (via HTCondor scheduler), and the support for validating the correctness of workflows (via semantic verification tools). Two bioinformatics workflow use cases as well as performance evaluation are presented to validate the feasibility of the proposed approach. PMID:24462600

antaRNA: ant colony-based RNA sequence design.

PubMed

Kleinkauf, Robert; Mann, Martin; Backofen, Rolf

2015-10-01

RNA sequence design is studied at least as long as the classical folding problem. Although for the latter the functional fold of an RNA molecule is to be found ,: inverse folding tries to identify RNA sequences that fold into a function-specific target structure. In combination with RNA-based biotechnology and synthetic biology ,: reliable RNA sequence design becomes a crucial step to generate novel biochemical components. In this article ,: the computational tool antaRNA is presented. It is capable of compiling RNA sequences for a given structure that comply in addition with an adjustable full range objective GC-content distribution ,: specific sequence constraints and additional fuzzy structure constraints. antaRNA applies ant colony optimization meta-heuristics and its superior performance is shown on a biological datasets. http://www.bioinf.uni-freiburg.de/Software/antaRNA CONTACT: backofen@informatik.uni-freiburg.de Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

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

PubMed

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.

Rainbow: a tool for large-scale whole-genome sequencing data analysis using cloud computing.

PubMed

Zhao, Shanrong; Prenger, Kurt; Smith, Lance; Messina, Thomas; Fan, Hongtao; Jaeger, Edward; Stephens, Susan

2013-06-27

Technical improvements have decreased sequencing costs and, as a result, the size and number of genomic datasets have increased rapidly. Because of the lower cost, large amounts of sequence data are now being produced by small to midsize research groups. Crossbow is a software tool that can detect single nucleotide polymorphisms (SNPs) in whole-genome sequencing (WGS) data from a single subject; however, Crossbow has a number of limitations when applied to multiple subjects from large-scale WGS projects. The data storage and CPU resources that are required for large-scale whole genome sequencing data analyses are too large for many core facilities and individual laboratories to provide. To help meet these challenges, we have developed Rainbow, a cloud-based software package that can assist in the automation of large-scale WGS data analyses. Here, we evaluated the performance of Rainbow by analyzing 44 different whole-genome-sequenced subjects. Rainbow has the capacity to process genomic data from more than 500 subjects in two weeks using cloud computing provided by the Amazon Web Service. The time includes the import and export of the data using Amazon Import/Export service. The average cost of processing a single sample in the cloud was less than 120 US dollars. Compared with Crossbow, the main improvements incorporated into Rainbow include the ability: (1) to handle BAM as well as FASTQ input files; (2) to split large sequence files for better load balance downstream; (3) to log the running metrics in data processing and monitoring multiple Amazon Elastic Compute Cloud (EC2) instances; and (4) to merge SOAPsnp outputs for multiple individuals into a single file to facilitate downstream genome-wide association studies. Rainbow is a scalable, cost-effective, and open-source tool for large-scale WGS data analysis. For human WGS data sequenced by either the Illumina HiSeq 2000 or HiSeq 2500 platforms, Rainbow can be used straight out of the box. Rainbow is available

Cloud-based bioinformatics workflow platform for large-scale next-generation sequencing analyses.

PubMed

Liu, Bo; Madduri, Ravi K; Sotomayor, Borja; Chard, Kyle; Lacinski, Lukasz; Dave, Utpal J; Li, Jianqiang; Liu, Chunchen; Foster, Ian T

2014-06-01

Due to the upcoming data deluge of genome data, the need for storing and processing large-scale genome data, easy access to biomedical analyses tools, efficient data sharing and retrieval has presented significant challenges. The variability in data volume results in variable computing and storage requirements, therefore biomedical researchers are pursuing more reliable, dynamic and convenient methods for conducting sequencing analyses. This paper proposes a Cloud-based bioinformatics workflow platform for large-scale next-generation sequencing analyses, which enables reliable and highly scalable execution of sequencing analyses workflows in a fully automated manner. Our platform extends the existing Galaxy workflow system by adding data management capabilities for transferring large quantities of data efficiently and reliably (via Globus Transfer), domain-specific analyses tools preconfigured for immediate use by researchers (via user-specific tools integration), automatic deployment on Cloud for on-demand resource allocation and pay-as-you-go pricing (via Globus Provision), a Cloud provisioning tool for auto-scaling (via HTCondor scheduler), and the support for validating the correctness of workflows (via semantic verification tools). Two bioinformatics workflow use cases as well as performance evaluation are presented to validate the feasibility of the proposed approach. Copyright © 2014 Elsevier Inc. All rights reserved.

Digital RNA sequencing minimizes sequence-dependent bias and amplification noise with optimized single-molecule barcodes

PubMed Central

Shiroguchi, Katsuyuki; Jia, Tony Z.; Sims, Peter A.; Xie, X. Sunney

2012-01-01

RNA sequencing (RNA-Seq) is a powerful tool for transcriptome profiling, but is hampered by sequence-dependent bias and inaccuracy at low copy numbers intrinsic to exponential PCR amplification. We developed a simple strategy for mitigating these complications, allowing truly digital RNA-Seq. Following reverse transcription, a large set of barcode sequences is added in excess, and nearly every cDNA molecule is uniquely labeled by random attachment of barcode sequences to both ends. After PCR, we applied paired-end deep sequencing to read the two barcodes and cDNA sequences. Rather than counting the number of reads, RNA abundance is measured based on the number of unique barcode sequences observed for a given cDNA sequence. We optimized the barcodes to be unambiguously identifiable, even in the presence of multiple sequencing errors. This method allows counting with single-copy resolution despite sequence-dependent bias and PCR-amplification noise, and is analogous to digital PCR but amendable to quantifying a whole transcriptome. We demonstrated transcriptome profiling of Escherichia coli with more accurate and reproducible quantification than conventional RNA-Seq. PMID:22232676

Computational Analysis of Mouse piRNA Sequence and Biogenesis

PubMed Central

Betel, Doron; Sheridan, Robert; Marks, Debora S; Sander, Chris

2007-01-01

The recent discovery of a new class of 30-nucleotide long RNAs in mammalian testes, called PIWI-interacting RNA (piRNA), with similarities to microRNAs and repeat-associated small interfering RNAs (rasiRNAs), has raised puzzling questions regarding their biogenesis and function. We report a comparative analysis of currently available piRNA sequence data from the pachytene stage of mouse spermatogenesis that sheds light on their sequence diversity and mechanism of biogenesis. We conclude that (i) there are at least four times as many piRNAs in mouse testes than currently known; (ii) piRNAs, which originate from long precursor transcripts, are generated by quasi-random enzymatic processing that is guided by a weak sequence signature at the piRNA 5′ends resulting in a large number of distinct sequences; and (iii) many of the piRNA clusters contain inverted repeats segments capable of forming double-strand RNA fold-back segments that may initiate piRNA processing analogous to transposon silencing. PMID:17997596

Rainbow: a tool for large-scale whole-genome sequencing data analysis using cloud computing

PubMed Central

2013-01-01

Background Technical improvements have decreased sequencing costs and, as a result, the size and number of genomic datasets have increased rapidly. Because of the lower cost, large amounts of sequence data are now being produced by small to midsize research groups. Crossbow is a software tool that can detect single nucleotide polymorphisms (SNPs) in whole-genome sequencing (WGS) data from a single subject; however, Crossbow has a number of limitations when applied to multiple subjects from large-scale WGS projects. The data storage and CPU resources that are required for large-scale whole genome sequencing data analyses are too large for many core facilities and individual laboratories to provide. To help meet these challenges, we have developed Rainbow, a cloud-based software package that can assist in the automation of large-scale WGS data analyses. Results Here, we evaluated the performance of Rainbow by analyzing 44 different whole-genome-sequenced subjects. Rainbow has the capacity to process genomic data from more than 500 subjects in two weeks using cloud computing provided by the Amazon Web Service. The time includes the import and export of the data using Amazon Import/Export service. The average cost of processing a single sample in the cloud was less than 120 US dollars. Compared with Crossbow, the main improvements incorporated into Rainbow include the ability: (1) to handle BAM as well as FASTQ input files; (2) to split large sequence files for better load balance downstream; (3) to log the running metrics in data processing and monitoring multiple Amazon Elastic Compute Cloud (EC2) instances; and (4) to merge SOAPsnp outputs for multiple individuals into a single file to facilitate downstream genome-wide association studies. Conclusions Rainbow is a scalable, cost-effective, and open-source tool for large-scale WGS data analysis. For human WGS data sequenced by either the Illumina HiSeq 2000 or HiSeq 2500 platforms, Rainbow can be used straight out of

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

PubMed Central

Matkovich, Scot J.; Dorn, Gerald W.

2018-01-01

Summary 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 complicates 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. PMID:25836573

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

PubMed

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.

Large-Scale Biomonitoring of Remote and Threatened Ecosystems via High-Throughput Sequencing

PubMed Central

Gibson, Joel F.; Shokralla, Shadi; Curry, Colin; Baird, Donald J.; Monk, Wendy A.; King, Ian; Hajibabaei, Mehrdad

2015-01-01

Biodiversity metrics are critical for assessment and monitoring of ecosystems threatened by anthropogenic stressors. Existing sorting and identification methods are too expensive and labour-intensive to be scaled up to meet management needs. Alternately, a high-throughput DNA sequencing approach could be used to determine biodiversity metrics from bulk environmental samples collected as part of a large-scale biomonitoring program. Here we show that both morphological and DNA sequence-based analyses are suitable for recovery of individual taxonomic richness, estimation of proportional abundance, and calculation of biodiversity metrics using a set of 24 benthic samples collected in the Peace-Athabasca Delta region of Canada. The high-throughput sequencing approach was able to recover all metrics with a higher degree of taxonomic resolution than morphological analysis. The reduced cost and increased capacity of DNA sequence-based approaches will finally allow environmental monitoring programs to operate at the geographical and temporal scale required by industrial and regulatory end-users. PMID:26488407

Batch effects in single-cell RNA-sequencing data are corrected by matching mutual nearest neighbors.

PubMed

Haghverdi, Laleh; Lun, Aaron T L; Morgan, Michael D; Marioni, John C

2018-06-01

Large-scale single-cell RNA sequencing (scRNA-seq) data sets that are produced in different laboratories and at different times contain batch effects that may compromise the integration and interpretation of the data. Existing scRNA-seq analysis methods incorrectly assume that the composition of cell populations is either known or identical across batches. We present a strategy for batch correction based on the detection of mutual nearest neighbors (MNNs) in the high-dimensional expression space. Our approach does not rely on predefined or equal population compositions across batches; instead, it requires only that a subset of the population be shared between batches. We demonstrate the superiority of our approach compared with existing methods by using both simulated and real scRNA-seq data sets. Using multiple droplet-based scRNA-seq data sets, we demonstrate that our MNN batch-effect-correction method can be scaled to large numbers of cells.

Unifying cancer and normal RNA sequencing data from different sources

PubMed Central

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

Simulations Using Random-Generated DNA and RNA Sequences

ERIC Educational Resources Information Center

Bryce, C. F. A.

1977-01-01

Using a very simple computer program written in BASIC, a very large number of random-generated DNA or RNA sequences are obtained. Students use these sequences to predict complementary sequences and translational products, evaluate base compositions, determine frequencies of particular triplet codons, and suggest possible secondary structures.…

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

PubMed

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.

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

PubMed

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.

Sequence to Structure (S2S): display, manipulate and interconnect RNA data from sequence to structure.

PubMed

Jossinet, Fabrice; Westhof, Eric

2005-08-01

Efficient RNA sequence manipulations (such as multiple alignments) need to be constrained by rules of RNA structure folding. The structural knowledge has increased dramatically in the last years with the accumulation of several large RNA structures similar to those of the bacterial ribosome subunits. However, no tool in the RNA community provides an easy way to link and integrate progress made at the sequence level using the available three-dimensional information. Sequence to Structure (S2S) proposes a framework in which an user can easily display, manipulate and interconnect heterogeneous RNA data, such as multiple sequence alignments, secondary and tertiary structures. S2S has been implemented using the Java language and has been developed and tested under UNIX systems, such as Linux and MacOSX. S2S is available at http://bioinformatics.org/S2S/.

Exploring Connectivity in Sequence Space of Functional RNA

NASA Technical Reports Server (NTRS)

Wei, Chenyu; Pohorille, Andrzej; Popovic, Milena; Ditzler, Mark

2017-01-01

Emergence of replicable genetic molecules was one of the marking points in the origin of life, evolution of which can be conceptualized as a walk through the space of all possible sequences. A theoretical concept of fitness landscape helps to understand evolutionary processes through assigning a value of fitness to each genotype. Then, evolution of a phenotype is viewed as a series of consecutive, single-point mutations. Natural selection biases evolution toward peaks of high fitness and away from valleys of low fitness. whereas neutral drift occurs in the sequence space without direction as mutations are introduced at random. Large networks of neutral or near-neutral mutations on a fitness landscape, especially for sufficiently long genomes, are possible or even inevitable. Their detection in experiments, however, has been elusive. Although a few near-neutral evolutionary pathways have been found, recent experimental evidence indicates landscapes consist of largely isolated islands. The generality of these results, however, is not clear, as the genome length or the fraction of functional molecules in the genotypic space might have been insufficient for the emergence of large, neutral networks. Thorough investigation on the structure of the fitness landscape is essential to understand the mechanisms of evolution of early genomes. RNA molecules are commonly assumed to play the pivotal role in the origin of genetic systems. They are widely believed to be early, if not the earliest, genetic and catalytic molecules, with abundant biochemical activities as aptamers and ribozymes, i.e. RNA molecules capable, respectively, to bind small molecules or catalyze chemical reactions. Here, we present results of our recent studies on the structure of the sequence space of RNA ligase ribozymes selected through in vitro evolution. Several hundred thousands of sequences active to a different degree were obtained by way of deep sequencing. Analysis of these sequences revealed

Metagenomic and near full-length 16S rRNA sequence data in support of the phylogenetic analysis of the rumen bacterial community in steers

USDA-ARS?s Scientific Manuscript database

Next generation sequencing technologies have vastly changed the approach of sequencing of the 16S rRNA gene for studies in microbial ecology. Three distinct technologies are available for large-scale 16S sequencing. All three are subject to biases introduced by sequencing error rates, amplificatio...

An evolutionary conserved pattern of 18S rRNA sequence complementarity to mRNA 5′ UTRs and its implications for eukaryotic gene translation regulation

PubMed Central

Pánek, Josef; Kolář, Michal; Vohradský, Jiří; Shivaya Valášek, Leoš

2013-01-01

There are several key mechanisms regulating eukaryotic gene expression at the level of protein synthesis. Interestingly, the least explored mechanisms of translational control are those that involve the translating ribosome per se, mediated for example via predicted interactions between the ribosomal RNAs (rRNAs) and mRNAs. Here, we took advantage of robustly growing large-scale data sets of mRNA sequences for numerous organisms, solved ribosomal structures and computational power to computationally explore the mRNA–rRNA complementarity that is statistically significant across the species. Our predictions reveal highly specific sequence complementarity of 18S rRNA sequences with mRNA 5′ untranslated regions (UTRs) forming a well-defined 3D pattern on the rRNA sequence of the 40S subunit. Broader evolutionary conservation of this pattern may imply that 5′ UTRs of eukaryotic mRNAs, which have already emerged from the mRNA-binding channel, may contact several complementary spots on 18S rRNA situated near the exit of the mRNA binding channel and on the middle-to-lower body of the solvent-exposed 40S ribosome including its left foot. We discuss physiological significance of this structurally conserved pattern and, in the context of previously published experimental results, propose that it modulates scanning of the 40S subunit through 5′ UTRs of mRNAs. PMID:23804757

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

PubMed

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.

Integrating RNA sequencing into neuro-oncology practice.

PubMed

Rogawski, David S; Vitanza, Nicholas A; Gauthier, Angela C; Ramaswamy, Vijay; Koschmann, Carl

2017-11-01

Malignant tumors of the central nervous system (CNS) cause substantial morbidity and mortality, yet efforts to optimize chemo- and radiotherapy have largely failed to improve dismal prognoses. Over the past decade, RNA sequencing (RNA-seq) has emerged as a powerful tool to comprehensively characterize the transcriptome of CNS tumor cells in one high-throughput step, leading to improved understanding of CNS tumor biology and suggesting new routes for targeted therapies. RNA-seq has been instrumental in improving the diagnostic classification of brain tumors, characterizing oncogenic fusion genes, and shedding light on intratumor heterogeneity. Currently, RNA-seq is beginning to be incorporated into regular neuro-oncology practice in the form of precision neuro-oncology programs, which use information from tumor sequencing to guide implementation of personalized targeted therapies. These programs show great promise in improving patient outcomes for tumors where single agent trials have been ineffective. As RNA-seq is a relatively new technique, many further applications yielding new advances in CNS tumor research and management are expected in the coming years. Copyright © 2017 Elsevier Inc. All rights reserved.

Spliced synthetic genes as internal controls in RNA sequencing experiments.

PubMed

Hardwick, Simon A; Chen, Wendy Y; Wong, Ted; Deveson, Ira W; Blackburn, James; Andersen, Stacey B; Nielsen, Lars K; Mattick, John S; Mercer, Tim R

2016-09-01

RNA sequencing (RNA-seq) can be used to assemble spliced isoforms, quantify expressed genes and provide a global profile of the transcriptome. However, the size and diversity of the transcriptome, the wide dynamic range in gene expression and inherent technical biases confound RNA-seq analysis. We have developed a set of spike-in RNA standards, termed 'sequins' (sequencing spike-ins), that represent full-length spliced mRNA isoforms. Sequins have an entirely artificial sequence with no homology to natural reference genomes, but they align to gene loci encoded on an artificial in silico chromosome. The combination of multiple sequins across a range of concentrations emulates alternative splicing and differential gene expression, and it provides scaling factors for normalization between samples. We demonstrate the use of sequins in RNA-seq experiments to measure sample-specific biases and determine the limits of reliable transcript assembly and quantification in accompanying human RNA samples. In addition, we have designed a complementary set of sequins that represent fusion genes arising from rearrangements of the in silico chromosome to aid in cancer diagnosis. RNA sequins provide a qualitative and quantitative reference with which to navigate the complexity of the human transcriptome.

Comparative Analysis of Single-Cell RNA Sequencing Methods.

PubMed

Ziegenhain, Christoph; Vieth, Beate; Parekh, Swati; Reinius, Björn; Guillaumet-Adkins, Amy; Smets, Martha; Leonhardt, Heinrich; Heyn, Holger; Hellmann, Ines; Enard, Wolfgang

2017-02-16

Single-cell RNA sequencing (scRNA-seq) offers new possibilities to address biological and medical questions. However, systematic comparisons of the performance of diverse scRNA-seq protocols are lacking. We generated data from 583 mouse embryonic stem cells to evaluate six prominent scRNA-seq methods: CEL-seq2, Drop-seq, MARS-seq, SCRB-seq, Smart-seq, and Smart-seq2. While Smart-seq2 detected the most genes per cell and across cells, CEL-seq2, Drop-seq, MARS-seq, and SCRB-seq quantified mRNA levels with less amplification noise due to the use of unique molecular identifiers (UMIs). Power simulations at different sequencing depths showed that Drop-seq is more cost-efficient for transcriptome quantification of large numbers of cells, while MARS-seq, SCRB-seq, and Smart-seq2 are more efficient when analyzing fewer cells. Our quantitative comparison offers the basis for an informed choice among six prominent scRNA-seq methods, and it provides a framework for benchmarking further improvements of scRNA-seq protocols. Copyright © 2017 Elsevier Inc. All rights reserved.

Using complementary DNA from MyoD-transduced fibroblasts to sequence large muscle genes.

PubMed

Waddell, Leigh B; Monnier, Nicole; Cooper, Sandra T; North, Kathryn N; Clarke, Nigel F

2011-08-01

Large muscle genes are often sequenced using complementary DNA (cDNA) made from muscle messenger RNA (mRNA) to reduce the cost and workload associated with sequencing from genomic DNA. Two potential barriers are the availability of a frozen muscle biopsy, and difficulties in detecting nonsense mutations due to nonsense-mediated mRNA decay (NMD). We present patient examples showing that use of MyoD-transduced fibroblasts as a source of muscle-specific mRNA overcomes these potential difficulties in sequencing large muscle-related genes. Copyright © 2011 Wiley Periodicals, Inc.

Transcriptome and Small RNA Deep Sequencing Reveals Deregulation of miRNA Biogenesis in Human Glioma

PubMed Central

Moore, Lynette M.; Kivinen, Virpi; Liu, Yuexin; Annala, Matti; Cogdell, David; Liu, Xiuping; Liu, Chang-Gong; Sawaya, Raymond; Yli-Harja, Olli; Shmulevich, Ilya; Fuller, Gregory N.; Zhang, Wei; Nykter, Matti

2013-01-01

Altered expression of oncogenic and tumor-suppressing microRNAs (miRNAs) is widely associated with tumorigenesis. However, the regulatory mechanisms underlying these alterations are poorly understood. We sought to shed light on the deregulation of miRNA biogenesis promoting the aberrant miRNA expression profiles identified in these tumors. Using sequencing technology to perform both whole-transcriptome and small RNA sequencing of glioma patient samples, we examined precursor and mature miRNAs to directly evaluate the miRNA maturation process, and interrogated expression profiles for genes involved in the major steps of miRNA biogenesis. We found that ratios of mature to precursor forms of a large number of miRNAs increased with the progression from normal brain to low-grade and then to high-grade gliomas. The expression levels of genes involved in each of the three major steps of miRNA biogenesis (nuclear processing, nucleo-cytoplasmic transport, and cytoplasmic processing) were systematically altered in glioma tissues. Survival analysis of an independent data set demonstrated that the alteration of genes involved in miRNA maturation correlates with survival in glioma patients. Direct quantification of miRNA maturation with deep sequencing demonstrated that deregulation of the miRNA biogenesis pathway is a hallmark for glioma genesis and progression. PMID:23007860

Sequence data for two large-subunit rRNA genes from an Asian strain of Alexandrium catenella.

PubMed Central

Yeung, P K; Kong, K F; Wong, F T; Wong, J T

1996-01-01

PCR generated two distinct products from a toxic isolate of Alexandrium catenella, which had been taken from Dai Ya Bay (southern China), by using primers for large-subunit rRNA. This pattern is distinct from published data for North American Alexandrium species. Sequences of the two products suggest that the smaller was generated by a deletion event. Single-cell PCR generated the same pattern, confirming that the two products were not the results from different individuals. PMID:8900010

Sequencing and Characterisation of an Extensive Atlantic Salmon (Salmo salar L.) MicroRNA Repertoire

PubMed Central

Bekaert, Michaël; Lowe, Natalie R.; Bishop, Stephen C.; Bron, James E.; Taggart, John B.; Houston, Ross D.

2013-01-01

Atlantic salmon (Salmo salar L.), a member of the family Salmonidae, is a totemic species of ecological and cultural significance that is also economically important in terms of both sports fisheries and aquaculture. These factors have promoted the continuous development of genomic resources for this species, furthering both fundamental and applied research. MicroRNAs (miRNA) are small endogenous non-coding RNA molecules that control spatial and temporal expression of targeted genes through post-transcriptional regulation. While miRNA have been characterised in detail for many other species, this is not yet the case for Atlantic salmon. To identify miRNAs from Atlantic salmon, we constructed whole fish miRNA libraries for 18 individual juveniles (fry, four months post hatch) and characterised them by Illumina high-throughput sequencing (total of 354,505,167 paired-ended reads). We report an extensive and partly novel repertoire of miRNA sequences, comprising 888 miRNA genes (547 unique mature miRNA sequences), quantify their expression levels in basal conditions, examine their homology to miRNAs from other species and identify their predicted target genes. We also identify the location and putative copy number of the miRNA genes in the draft Atlantic salmon reference genome sequence. The Atlantic salmon miRNAs experimentally identified in this study provide a robust large-scale resource for functional genome research in salmonids. There is an opportunity to explore the evolution of salmonid miRNAs following the relatively recent whole genome duplication event in salmonid species and to investigate the role of miRNAs in the regulation of gene expression in particular their contribution to variation in economically and ecologically important traits. PMID:23922936

Enabling large-scale next-generation sequence assembly with Blacklight

PubMed Central

Couger, M. Brian; Pipes, Lenore; Squina, Fabio; Prade, Rolf; Siepel, Adam; Palermo, Robert; Katze, Michael G.; Mason, Christopher E.; Blood, Philip D.

2014-01-01

Summary A variety of extremely challenging biological sequence analyses were conducted on the XSEDE large shared memory resource Blacklight, using current bioinformatics tools and encompassing a wide range of scientific applications. These include genomic sequence assembly, very large metagenomic sequence assembly, transcriptome assembly, and sequencing error correction. The data sets used in these analyses included uncategorized fungal species, reference microbial data, very large soil and human gut microbiome sequence data, and primate transcriptomes, composed of both short-read and long-read sequence data. A new parallel command execution program was developed on the Blacklight resource to handle some of these analyses. These results, initially reported previously at XSEDE13 and expanded here, represent significant advances for their respective scientific communities. The breadth and depth of the results achieved demonstrate the ease of use, versatility, and unique capabilities of the Blacklight XSEDE resource for scientific analysis of genomic and transcriptomic sequence data, and the power of these resources, together with XSEDE support, in meeting the most challenging scientific problems. PMID:25294974

Chromosome evolution in the Thermotogales: large-scale inversions and strain diversification of CRISPR sequences.

PubMed

DeBoy, Robert T; Mongodin, Emmanuel F; Emerson, Joanne B; Nelson, Karen E

2006-04-01

In the present study, the chromosomes of two members of the Thermotogales were compared. A whole-genome alignment of Thermotoga maritima MSB8 and Thermotoga neapolitana NS-E has revealed numerous large-scale DNA rearrangements, most of which are associated with CRISPR DNA repeats and/or tRNA genes. These DNA rearrangements do not include the putative origin of DNA replication but move within the same replichore, i.e., the same replicating half of the chromosome (delimited by the replication origin and terminus). Based on cumulative GC skew analysis, both the T. maritima and T. neapolitana lineages contain one or two major inverted DNA segments. Also, based on PCR amplification and sequence analysis of the DNA joints that are associated with the major rearrangements, the overall chromosome architecture was found to be conserved at most DNA joints for other strains of T. neapolitana. Taken together, the results from this analysis suggest that the observed chromosomal rearrangements in the Thermotogales likely occurred by successive inversions after their divergence from a common ancestor and before strain diversification. Finally, sequence analysis shows that size polymorphisms in the DNA joints associated with CRISPRs can be explained by expansion and possibly contraction of the DNA repeat and spacer unit, providing a tool for discerning the relatedness of strains from different geographic locations.

AMPLIFICATION OF RIBOSOMAL RNA SEQUENCES

EPA Science Inventory

This book chapter offers an overview of the use of ribosomal RNA sequences. A history of the technology traces the evolution of techniques to measure bacterial phylogenetic relationships and recent advances in obtaining rRNA sequence information. The manual also describes procedu...

ReSeqTools: an integrated toolkit for large-scale next-generation sequencing based resequencing analysis.

PubMed

He, W; Zhao, S; Liu, X; Dong, S; Lv, J; Liu, D; Wang, J; Meng, Z

2013-12-04

Large-scale next-generation sequencing (NGS)-based resequencing detects sequence variations, constructs evolutionary histories, and identifies phenotype-related genotypes. However, NGS-based resequencing studies generate extraordinarily large amounts of data, making computations difficult. Effective use and analysis of these data for NGS-based resequencing studies remains a difficult task for individual researchers. Here, we introduce ReSeqTools, a full-featured toolkit for NGS (Illumina sequencing)-based resequencing analysis, which processes raw data, interprets mapping results, and identifies and annotates sequence variations. ReSeqTools provides abundant scalable functions for routine resequencing analysis in different modules to facilitate customization of the analysis pipeline. ReSeqTools is designed to use compressed data files as input or output to save storage space and facilitates faster and more computationally efficient large-scale resequencing studies in a user-friendly manner. It offers abundant practical functions and generates useful statistics during the analysis pipeline, which significantly simplifies resequencing analysis. Its integrated algorithms and abundant sub-functions provide a solid foundation for special demands in resequencing projects. Users can combine these functions to construct their own pipelines for other purposes.

Single-Cell RNA-Sequencing: Assessment of Differential Expression Analysis Methods.

PubMed

Dal Molin, Alessandra; Baruzzo, Giacomo; Di Camillo, Barbara

2017-01-01

The sequencing of the transcriptomes of single-cells, or single-cell RNA-sequencing, has now become the dominant technology for the identification of novel cell types and for the study of stochastic gene expression. In recent years, various tools for analyzing single-cell RNA-sequencing data have been proposed, many of them with the purpose of performing differentially expression analysis. In this work, we compare four different tools for single-cell RNA-sequencing differential expression, together with two popular methods originally developed for the analysis of bulk RNA-sequencing data, but largely applied to single-cell data. We discuss results obtained on two real and one synthetic dataset, along with considerations about the perspectives of single-cell differential expression analysis. In particular, we explore the methods performance in four different scenarios, mimicking different unimodal or bimodal distributions of the data, as characteristic of single-cell transcriptomics. We observed marked differences between the selected methods in terms of precision and recall, the number of detected differentially expressed genes and the overall performance. Globally, the results obtained in our study suggest that is difficult to identify a best performing tool and that efforts are needed to improve the methodologies for single-cell RNA-sequencing data analysis and gain better accuracy of results.

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

PubMed

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.

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

PubMed

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.

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

PubMed Central

2013-01-01

Background 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. Methods 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. Results 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. Conclusions 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. PMID:23721526

Large-Scale Sequencing: The Future of Genomic Sciences Colloquium

DOE Office of Scientific and Technical Information (OSTI.GOV)

Margaret Riley; Merry Buckley

2009-01-01

Genetic sequencing and the various molecular techniques it has enabled have revolutionized the field of microbiology. Examining and comparing the genetic sequences borne by microbes - including bacteria, archaea, viruses, and microbial eukaryotes - provides researchers insights into the processes microbes carry out, their pathogenic traits, and new ways to use microorganisms in medicine and manufacturing. Until recently, sequencing entire microbial genomes has been laborious and expensive, and the decision to sequence the genome of an organism was made on a case-by-case basis by individual researchers and funding agencies. Now, thanks to new technologies, the cost and effort of sequencingmore » is within reach for even the smallest facilities, and the ability to sequence the genomes of a significant fraction of microbial life may be possible. The availability of numerous microbial genomes will enable unprecedented insights into microbial evolution, function, and physiology. However, the current ad hoc approach to gathering sequence data has resulted in an unbalanced and highly biased sampling of microbial diversity. A well-coordinated, large-scale effort to target the breadth and depth of microbial diversity would result in the greatest impact. The American Academy of Microbiology convened a colloquium to discuss the scientific benefits of engaging in a large-scale, taxonomically-based sequencing project. A group of individuals with expertise in microbiology, genomics, informatics, ecology, and evolution deliberated on the issues inherent in such an effort and generated a set of specific recommendations for how best to proceed. The vast majority of microbes are presently uncultured and, thus, pose significant challenges to such a taxonomically-based approach to sampling genome diversity. However, we have yet to even scratch the surface of the genomic diversity among cultured microbes. A coordinated sequencing effort of cultured organisms is an appropriate place

High-Throughput Single-Cell RNA Sequencing and Data Analysis.

PubMed

Sagar; Herman, Josip Stefan; Pospisilik, John Andrew; Grün, Dominic

2018-01-01

Understanding biological systems at a single cell resolution may reveal several novel insights which remain masked by the conventional population-based techniques providing an average readout of the behavior of cells. Single-cell transcriptome sequencing holds the potential to identify novel cell types and characterize the cellular composition of any organ or tissue in health and disease. Here, we describe a customized high-throughput protocol for single-cell RNA-sequencing (scRNA-seq) combining flow cytometry and a nanoliter-scale robotic system. Since scRNA-seq requires amplification of a low amount of endogenous cellular RNA, leading to substantial technical noise in the dataset, downstream data filtering and analysis require special care. Therefore, we also briefly describe in-house state-of-the-art data analysis algorithms developed to identify cellular subpopulations including rare cell types as well as to derive lineage trees by ordering the identified subpopulations of cells along the inferred differentiation trajectories.

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

PubMed Central

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

RISE: a database of RNA interactome from sequencing experiments

PubMed Central

Gong, Jing; Shao, Di; Xu, Kui

2018-01-01

Abstract We present RISE (http://rise.zhanglab.net), a database of RNA Interactome from Sequencing Experiments. RNA-RNA interactions (RRIs) are essential for RNA regulation and function. RISE provides a comprehensive collection of RRIs that mainly come from recent transcriptome-wide sequencing-based experiments like PARIS, SPLASH, LIGR-seq, and MARIO, as well as targeted studies like RIA-seq, RAP-RNA and CLASH. It also includes interactions aggregated from other primary databases and publications. The RISE database currently contains 328,811 RNA-RNA interactions mainly in human, mouse and yeast. While most existing RNA databases mainly contain interactions of miRNA targeting, notably, more than half of the RRIs in RISE are among mRNA and long non-coding RNAs. We compared different RRI datasets in RISE and found limited overlaps in interactions resolved by different techniques and in different cell lines. It may suggest technology preference and also dynamic natures of RRIs. We also analyzed the basic features of the human and mouse RRI networks and found that they tend to be scale-free, small-world, hierarchical and modular. The analysis may nominate important RNAs or RRIs for further investigation. Finally, RISE provides a Circos plot and several table views for integrative visualization, with extensive molecular and functional annotations to facilitate exploration of biological functions for any RRI of interest. PMID:29040625

INFO-RNA--a server for fast inverse RNA folding satisfying sequence constraints.

PubMed

Busch, Anke; Backofen, Rolf

2007-07-01

INFO-RNA is a new web server for designing RNA sequences that fold into a user given secondary structure. Furthermore, constraints on the sequence can be specified, e.g. one can restrict sequence positions to a fixed nucleotide or to a set of nucleotides. Moreover, the user can allow violations of the constraints at some positions, which can be advantageous in complicated cases. The INFO-RNA web server allows biologists to design RNA sequences in an automatic manner. It is clearly and intuitively arranged and easy to use. The procedure is fast, as most applications are completed within seconds and it proceeds better and faster than other existing tools. The INFO-RNA web server is freely available at http://www.bioinf.uni-freiburg.de/Software/INFO-RNA/

Sequence variation between 462 human individuals fine-tunes functional sites of RNA processing

NASA Astrophysics Data System (ADS)

Ferreira, Pedro G.; Oti, Martin; Barann, Matthias; Wieland, Thomas; Ezquina, Suzana; Friedländer, Marc R.; Rivas, Manuel A.; Esteve-Codina, Anna; Estivill, Xavier; Guigó, Roderic; Dermitzakis, Emmanouil; Antonarakis, Stylianos; Meitinger, Thomas; Strom, Tim M.; Palotie, Aarno; François Deleuze, Jean; Sudbrak, Ralf; Lerach, Hans; Gut, Ivo; Syvänen, Ann-Christine; Gyllensten, Ulf; Schreiber, Stefan; Rosenstiel, Philip; Brunner, Han; Veltman, Joris; Hoen, Peter A. C. T.; Jan van Ommen, Gert; Carracedo, Angel; Brazma, Alvis; Flicek, Paul; Cambon-Thomsen, Anne; Mangion, Jonathan; Bentley, David; Hamosh, Ada; Rosenstiel, Philip; Strom, Tim M.; Lappalainen, Tuuli; Guigó, Roderic; Sammeth, Michael

2016-09-01

Recent advances in the cost-efficiency of sequencing technologies enabled the combined DNA- and RNA-sequencing of human individuals at the population-scale, making genome-wide investigations of the inter-individual genetic impact on gene expression viable. Employing mRNA-sequencing data from the Geuvadis Project and genome sequencing data from the 1000 Genomes Project we show that the computational analysis of DNA sequences around splice sites and poly-A signals is able to explain several observations in the phenotype data. In contrast to widespread assessments of statistically significant associations between DNA polymorphisms and quantitative traits, we developed a computational tool to pinpoint the molecular mechanisms by which genetic markers drive variation in RNA-processing, cataloguing and classifying alleles that change the affinity of core RNA elements to their recognizing factors. The in silico models we employ further suggest RNA editing can moonlight as a splicing-modulator, albeit less frequently than genomic sequence diversity. Beyond existing annotations, we demonstrate that the ultra-high resolution of RNA-Seq combined from 462 individuals also provides evidence for thousands of bona fide novel elements of RNA processing—alternative splice sites, introns, and cleavage sites—which are often rare and lowly expressed but in other characteristics similar to their annotated counterparts.

APRICOT: an integrated computational pipeline for the sequence-based identification and characterization of RNA-binding proteins.

PubMed

Sharan, Malvika; Förstner, Konrad U; Eulalio, Ana; Vogel, Jörg

2017-06-20

RNA-binding proteins (RBPs) have been established as core components of several post-transcriptional gene regulation mechanisms. Experimental techniques such as cross-linking and co-immunoprecipitation have enabled the identification of RBPs, RNA-binding domains (RBDs) and their regulatory roles in the eukaryotic species such as human and yeast in large-scale. In contrast, our knowledge of the number and potential diversity of RBPs in bacteria is poorer due to the technical challenges associated with the existing global screening approaches. We introduce APRICOT, a computational pipeline for the sequence-based identification and characterization of proteins using RBDs known from experimental studies. The pipeline identifies functional motifs in protein sequences using position-specific scoring matrices and Hidden Markov Models of the functional domains and statistically scores them based on a series of sequence-based features. Subsequently, APRICOT identifies putative RBPs and characterizes them by several biological properties. Here we demonstrate the application and adaptability of the pipeline on large-scale protein sets, including the bacterial proteome of Escherichia coli. APRICOT showed better performance on various datasets compared to other existing tools for the sequence-based prediction of RBPs by achieving an average sensitivity and specificity of 0.90 and 0.91 respectively. The command-line tool and its documentation are available at https://pypi.python.org/pypi/bio-apricot. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Introduction to Single-Cell RNA Sequencing.

PubMed

Olsen, Thale Kristin; Baryawno, Ninib

2018-04-01

During the last decade, high-throughput sequencing methods have revolutionized the entire field of biology. The opportunity to study entire transcriptomes in great detail using RNA sequencing (RNA-seq) has fueled many important discoveries and is now a routine method in biomedical research. However, RNA-seq is typically performed in "bulk," and the data represent an average of gene expression patterns across thousands to millions of cells; this might obscure biologically relevant differences between cells. Single-cell RNA-seq (scRNA-seq) represents an approach to overcome this problem. By isolating single cells, capturing their transcripts, and generating sequencing libraries in which the transcripts are mapped to individual cells, scRNA-seq allows assessment of fundamental biological properties of cell populations and biological systems at unprecedented resolution. Here, we present the most common scRNA-seq protocols in use today and the basics of data analysis and discuss factors that are important to consider before planning and designing an scRNA-seq project. © 2018 by John Wiley & Sons, Inc. Copyright © 2018 John Wiley & Sons, Inc.

Low-coverage single-cell mRNA sequencing reveals cellular heterogeneity and activated signaling pathways in developing cerebral cortex.

PubMed

Pollen, Alex A; Nowakowski, Tomasz J; Shuga, Joe; Wang, Xiaohui; Leyrat, Anne A; Lui, Jan H; Li, Nianzhen; Szpankowski, Lukasz; Fowler, Brian; Chen, Peilin; Ramalingam, Naveen; Sun, Gang; Thu, Myo; Norris, Michael; Lebofsky, Ronald; Toppani, Dominique; Kemp, Darnell W; Wong, Michael; Clerkson, Barry; Jones, Brittnee N; Wu, Shiquan; Knutsson, Lawrence; Alvarado, Beatriz; Wang, Jing; Weaver, Lesley S; May, Andrew P; Jones, Robert C; Unger, Marc A; Kriegstein, Arnold R; West, Jay A A

2014-10-01

Large-scale surveys of single-cell gene expression have the potential to reveal rare cell populations and lineage relationships but require efficient methods for cell capture and mRNA sequencing. Although cellular barcoding strategies allow parallel sequencing of single cells at ultra-low depths, the limitations of shallow sequencing have not been investigated directly. By capturing 301 single cells from 11 populations using microfluidics and analyzing single-cell transcriptomes across downsampled sequencing depths, we demonstrate that shallow single-cell mRNA sequencing (~50,000 reads per cell) is sufficient for unbiased cell-type classification and biomarker identification. In the developing cortex, we identify diverse cell types, including multiple progenitor and neuronal subtypes, and we identify EGR1 and FOS as previously unreported candidate targets of Notch signaling in human but not mouse radial glia. Our strategy establishes an efficient method for unbiased analysis and comparison of cell populations from heterogeneous tissue by microfluidic single-cell capture and low-coverage sequencing of many cells.

Primer-independent RNA sequencing with bacteriophage phi6 RNA polymerase and chain terminators.

PubMed

Makeyev, E V; Bamford, D H

2001-05-01

Here we propose a new general method for directly determining RNA sequence based on the use of the RNA-dependent RNA polymerase from bacteriophage phi6 and the chain terminators (RdRP sequencing). The following properties of the polymerase render it appropriate for this application: (1) the phi6 polymerase can replicate a number of single-stranded RNA templates in vitro. (2) In contrast to the primer-dependent DNA polymerases utilized in the sequencing procedure by Sanger et al. (Proc Natl Acad Sci USA, 1977, 74:5463-5467), it initiates nascent strand synthesis without a primer, starting the polymerization on the very 3'-terminus of the template. (3) The polymerase can incorporate chain-terminating nucleotide analogs into the nascent RNA chain to produce a set of base-specific termination products. Consequently, 3' proximal or even complete sequence of many target RNA molecules can be rapidly deduced without prior sequence information. The new technique proved useful for sequencing several synthetic ssRNA templates. Furthermore, using genomic segments of the bluetongue virus we show that RdRP sequencing can also be applied to naturally occurring dsRNA templates. This suggests possible uses of the method in the RNA virus research and diagnostics.

RNA processing in Neurospora crassa mitochondria: use of transfer RNA sequences as signals.

PubMed Central

Breitenberger, C A; Browning, K S; Alzner-DeWeerd, B; RajBhandary, U L

1985-01-01

We have used RNA gel transfer hybridization, S1 nuclease mapping and primer extension to analyze transcripts derived from several genes in Neurospora crassa mitochondria. The transcripts studied include those for cytochrome oxidase subunit III, 17S rRNA and an unidentified open reading frame. In all three cases, initial transcripts are long, include tRNA sequences, and are subsequently processed to generate the mature RNAs. We find that endpoints of the most abundant transcripts generally coincide with those of tRNA sequences. We therefore conclude that tRNA sequences in long transcripts act as primary signals for RNA processing in N. crassa mitochondria. The situation is somewhat analogous to that observed in mammalian mitochondrial systems. The difference, however, is that in mammalian mitochondria, noncoding spacers between tRNA, rRNA and protein genes are very short and in many cases non-existent, allowing no room for intergenic RNA processing signals whereas, in N. crassa mtDNA, intergenic non-coding sequences are usually several hundred nucleotides long and contain highly conserved GC-rich palindromic sequences. Since these GC-rich palindromic sequences are retained in the processed mature RNAs, we conclude that they do not serve as signals for RNA processing. Images Fig. 2. Fig. 3. Fig. 4. Fig. 5. Fig. 6. Fig. 7. PMID:2990893

RNase H-assisted RNA-primed rolling circle amplification for targeted RNA sequence detection.

PubMed

Takahashi, Hirokazu; Ohkawachi, Masahiko; Horio, Kyohei; Kobori, Toshiro; Aki, Tsunehiro; Matsumura, Yukihiko; Nakashimada, Yutaka; Okamura, Yoshiko

2018-05-17

RNA-primed rolling circle amplification (RPRCA) is a useful laboratory method for RNA detection; however, the detection of RNA is limited by the lack of information on 3'-terminal sequences. We uncovered that conventional RPRCA using pre-circularized probes could potentially detect the internal sequence of target RNA molecules in combination with RNase H. However, the specificity for mRNA detection was low, presumably due to non-specific hybridization of non-target RNA with the circular probe. To overcome this technical problem, we developed a method for detecting a sequence of interest in target RNA molecules via RNase H-assisted RPRCA using padlocked probes. When padlock probes are hybridized to the target RNA molecule, they are converted to the circular form by SplintR ligase. Subsequently, RNase H creates nick sites only in the hybridized RNA sequence, and single-stranded DNA is finally synthesized from the nick site by phi29 DNA polymerase. This method could specifically detect at least 10 fmol of the target RNA molecule without reverse transcription. Moreover, this method detected GFP mRNA present in 10 ng of total RNA isolated from Escherichia coli without background DNA amplification. Therefore, this method can potentially detect almost all types of RNA molecules without reverse transcription and reveal full-length sequence information.

Exploration of RNA Sequence Space in the Absence of a Replicase.

PubMed

Tirumalai, Madhan R; Tran, Quyen; Paci, Maxim; Chavan, Dimple; Marathe, Anuradha; Fox, George E

2018-05-11

It is generally considered that if an RNA World ever existed that it would be driven by an RNA capable of RNA replication. Whether such a catalytic RNA could emerge in an RNA World or not, there would need to be prior routes to increasing complexity in order to produce it. It is hypothesized here that increasing sequence variety, if not complexity, can in fact readily emerge in response to a dynamic equilibrium between synthesis and degradation. A model system in which T4 RNA ligase catalyzes synthesis and Benzonase catalyzes degradation was constructed. An initial 20-mer served as a seed and was subjected to 180 min of simultaneous ligation and degradation. The seed RNA rapidly disappeared and was replaced by an increasing number and variety of both larger and smaller variants. Variants of 40-80 residues were consistently seen, typically representing 2-4% of the unique sequences. In a second experiment with four individual 9-mers, numerous variants were again produced. These included variants of the individual 9-mers as well as sequences that contained sequence segments from two or more 9-mers. In both cases, the RNA products lack large numbers of point mutations but instead incorporate additions and subtractions of fragments of the original RNAs. The system demonstrates that if such equilibrium were established in a prebiotic world it would result in significant exploration of RNA sequence space and likely increased complexity. It remains to be seen if the variety of products produced is affected by the presence of small peptide oligomers.

Analyses of transcriptome sequences reveal multiple ancient large-scale duplication events in the ancestor of Sphagnopsida (Bryophyta).

PubMed

Devos, Nicolas; Szövényi, Péter; Weston, David J; Rothfels, Carl J; Johnson, Matthew G; Shaw, A Jonathan

2016-07-01

The goal of this research was to investigate whether there has been a whole-genome duplication (WGD) in the ancestry of Sphagnum (peatmoss) or the class Sphagnopsida, and to determine if the timing of any such duplication(s) and patterns of paralog retention could help explain the rapid radiation and current ecological dominance of peatmosses. RNA sequencing (RNA-seq) data were generated for nine taxa in Sphagnopsida (Bryophyta). Analyses of frequency plots for synonymous substitutions per synonymous site (Ks ) between paralogous gene pairs and reconciliation of 578 gene trees were conducted to assess evidence of large-scale or genome-wide duplication events in each transcriptome. Both Ks frequency plots and gene tree-based analyses indicate multiple duplication events in the history of the Sphagnopsida. The most recent WGD event predates divergence of Sphagnum from the two other genera of Sphagnopsida. Duplicate retention is highly variable across species, which might be best explained by local adaptation. Our analyses indicate that the last WGD could have been an important factor underlying the diversification of peatmosses and facilitated their rise to ecological dominance in peatlands. The timing of the duplication events and their significance in the evolutionary history of peat mosses are discussed. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

Targeted RNA-Sequencing with Competitive Multiplex-PCR Amplicon Libraries

PubMed Central

Blomquist, Thomas M.; Crawford, Erin L.; Lovett, Jennie L.; Yeo, Jiyoun; Stanoszek, Lauren M.; Levin, Albert; Li, Jia; Lu, Mei; Shi, Leming; Muldrew, Kenneth; Willey, James C.

2013-01-01

Whole transcriptome RNA-sequencing is a powerful tool, but is costly and yields complex data sets that limit its utility in molecular diagnostic testing. A targeted quantitative RNA-sequencing method that is reproducible and reduces the number of sequencing reads required to measure transcripts over the full range of expression would be better suited to diagnostic testing. Toward this goal, we developed a competitive multiplex PCR-based amplicon sequencing library preparation method that a) targets only the sequences of interest and b) controls for inter-target variation in PCR amplification during library preparation by measuring each transcript native template relative to a known number of synthetic competitive template internal standard copies. To determine the utility of this method, we intentionally selected PCR conditions that would cause transcript amplification products (amplicons) to converge toward equimolar concentrations (normalization) during library preparation. We then tested whether this approach would enable accurate and reproducible quantification of each transcript across multiple library preparations, and at the same time reduce (through normalization) total sequencing reads required for quantification of transcript targets across a large range of expression. We demonstrate excellent reproducibility (R2 = 0.997) with 97% accuracy to detect 2-fold change using External RNA Controls Consortium (ERCC) reference materials; high inter-day, inter-site and inter-library concordance (R2 = 0.97–0.99) using FDA Sequencing Quality Control (SEQC) reference materials; and cross-platform concordance with both TaqMan qPCR (R2 = 0.96) and whole transcriptome RNA-sequencing following “traditional” library preparation using Illumina NGS kits (R2 = 0.94). Using this method, sequencing reads required to accurately quantify more than 100 targeted transcripts expressed over a 107-fold range was reduced more than 10,000-fold, from 2.3×109 to 1

The nucleotide sequence of the entire ribosomal DNA operon and the structure of the large subunit rRNA of Giardia muris.

PubMed

van Keulen, H; Gutell, R R; Campbell, S R; Erlandsen, S L; Jarroll, E L

1992-10-01

The total nucleotide sequence of the rDNA of Giardia muris, an intestinal protozoan parasite of rodents, has been determined. The repeat unit is 7668 basepairs (bp) in size and consists of a spacer of 3314 bp, a small-subunit rRNA (SSU-rRNA) gene of 1429, and a large-subunit rRNA (LSU-rRNA) gene of 2698 bp. The spacer contains long direct repeats and is heterogeneous in size. The LSU-rRNA of G. muris was compared to that of the human intestinal parasite Giardia duodenalis, to the bird parasite Giardia ardeae, and to that of Escherichia coli. The LSU-rRNA has a size comparable to the 23S rRNA of E. coli but shows structural features typical for eukaryotes. Some variable regions are typically small and account for the overall smaller size of this rRNA. The structure of the G. muris LSU-rRNA is similar to that of the other Giardia rRNA, but each rRNA has characteristic features residing in a number of variable regions.

Structator: fast index-based search for RNA sequence-structure patterns

PubMed Central

2011-01-01

Background The secondary structure of RNA molecules is intimately related to their function and often more conserved than the sequence. Hence, the important task of searching databases for RNAs requires to match sequence-structure patterns. Unfortunately, current tools for this task have, in the best case, a running time that is only linear in the size of sequence databases. Furthermore, established index data structures for fast sequence matching, like suffix trees or arrays, cannot benefit from the complementarity constraints introduced by the secondary structure of RNAs. Results We present a novel method and readily applicable software for time efficient matching of RNA sequence-structure patterns in sequence databases. Our approach is based on affix arrays, a recently introduced index data structure, preprocessed from the target database. Affix arrays support bidirectional pattern search, which is required for efficiently handling the structural constraints of the pattern. Structural patterns like stem-loops can be matched inside out, such that the loop region is matched first and then the pairing bases on the boundaries are matched consecutively. This allows to exploit base pairing information for search space reduction and leads to an expected running time that is sublinear in the size of the sequence database. The incorporation of a new chaining approach in the search of RNA sequence-structure patterns enables the description of molecules folding into complex secondary structures with multiple ordered patterns. The chaining approach removes spurious matches from the set of intermediate results, in particular of patterns with little specificity. In benchmark experiments on the Rfam database, our method runs up to two orders of magnitude faster than previous methods. Conclusions The presented method's sublinear expected running time makes it well suited for RNA sequence-structure pattern matching in large sequence databases. RNA molecules containing several

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

PubMed

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

Delimitation of the Thoracosphaeraceae (Dinophyceae), including the calcareous dinoflagellates, based on large amounts of ribosomal RNA sequence data.

PubMed

Gottschling, Marc; Soehner, Sylvia; Zinssmeister, Carmen; John, Uwe; Plötner, Jörg; Schweikert, Michael; Aligizaki, Katerina; Elbrächter, Malte

2012-01-01

The phylogenetic relationships of the Dinophyceae (Alveolata) are not sufficiently resolved at present. The Thoracosphaeraceae (Peridiniales) are the only group of the Alveolata that include members with calcareous coccoid stages; this trait is considered apomorphic. Although the coccoid stage apparently is not calcareous, Bysmatrum has been assigned to the Thoracosphaeraceae based on thecal morphology. We tested the monophyly of the Thoracosphaeraceae using large sets of ribosomal RNA sequence data of the Alveolata including the Dinophyceae. Phylogenetic analyses were performed using Maximum Likelihood and Bayesian approaches. The Thoracosphaeraceae were monophyletic, but included also a number of non-calcareous dinophytes (such as Pentapharsodinium and Pfiesteria) and even parasites (such as Duboscquodinium and Tintinnophagus). Bysmatrum had an isolated and uncertain phylogenetic position outside the Thoracosphaeraceae. The phylogenetic relationships among calcareous dinophytes appear complex, and the assumption of the single origin of the potential to produce calcareous structures is challenged. The application of concatenated ribosomal RNA sequence data may prove promising for phylogenetic reconstructions of the Dinophyceae in future. Copyright © 2011 Elsevier GmbH. All rights reserved.

Short intronic repeat sequences facilitate circular RNA production.

PubMed

Liang, Dongming; Wilusz, Jeremy E

2014-10-15

Recent deep sequencing studies have revealed thousands of circular noncoding RNAs generated from protein-coding genes. These RNAs are produced when the precursor messenger RNA (pre-mRNA) splicing machinery "backsplices" and covalently joins, for example, the two ends of a single exon. However, the mechanism by which the spliceosome selects only certain exons to circularize is largely unknown. Using extensive mutagenesis of expression plasmids, we show that miniature introns containing the splice sites along with short (∼ 30- to 40-nucleotide) inverted repeats, such as Alu elements, are sufficient to allow the intervening exons to circularize in cells. The intronic repeats must base-pair to one another, thereby bringing the splice sites into close proximity to each other. More than simple thermodynamics is clearly at play, however, as not all repeats support circularization, and increasing the stability of the hairpin between the repeats can sometimes inhibit circular RNA biogenesis. The intronic repeats and exonic sequences must collaborate with one another, and a functional 3' end processing signal is required, suggesting that circularization may occur post-transcriptionally. These results suggest detailed and generalizable models that explain how the splicing machinery determines whether to produce a circular noncoding RNA or a linear mRNA. © 2014 Liang and Wilusz; Published by Cold Spring Harbor Laboratory Press.

Short intronic repeat sequences facilitate circular RNA production

PubMed Central

Liang, Dongming

2014-01-01

Recent deep sequencing studies have revealed thousands of circular noncoding RNAs generated from protein-coding genes. These RNAs are produced when the precursor messenger RNA (pre-mRNA) splicing machinery “backsplices” and covalently joins, for example, the two ends of a single exon. However, the mechanism by which the spliceosome selects only certain exons to circularize is largely unknown. Using extensive mutagenesis of expression plasmids, we show that miniature introns containing the splice sites along with short (∼30- to 40-nucleotide) inverted repeats, such as Alu elements, are sufficient to allow the intervening exons to circularize in cells. The intronic repeats must base-pair to one another, thereby bringing the splice sites into close proximity to each other. More than simple thermodynamics is clearly at play, however, as not all repeats support circularization, and increasing the stability of the hairpin between the repeats can sometimes inhibit circular RNA biogenesis. The intronic repeats and exonic sequences must collaborate with one another, and a functional 3′ end processing signal is required, suggesting that circularization may occur post-transcriptionally. These results suggest detailed and generalizable models that explain how the splicing machinery determines whether to produce a circular noncoding RNA or a linear mRNA. PMID:25281217

Single-Cell RNA-Sequencing in Glioma.

PubMed

Johnson, Eli; Dickerson, Katherine L; Connolly, Ian D; Hayden Gephart, Melanie

2018-04-10

In this review, we seek to summarize the literature concerning the use of single-cell RNA-sequencing for CNS gliomas. Single-cell analysis has revealed complex tumor heterogeneity, subpopulations of proliferating stem-like cells and expanded our view of tumor microenvironment influence in the disease process. Although bulk RNA-sequencing has guided our initial understanding of glioma genetics, this method does not accurately define the heterogeneous subpopulations found within these tumors. Single-cell techniques have appealing applications in cancer research, as diverse cell types and the tumor microenvironment have important implications in therapy. High cost and difficult protocols prevent widespread use of single-cell RNA-sequencing; however, continued innovation will improve accessibility and expand our of knowledge gliomas.

Large-scale chromosome folding versus genomic DNA sequences: A discrete double Fourier transform technique.

PubMed

Chechetkin, V R; Lobzin, V V

2017-08-07

Using state-of-the-art techniques combining imaging methods and high-throughput genomic mapping tools leaded to the significant progress in detailing chromosome architecture of various organisms. However, a gap still remains between the rapidly growing structural data on the chromosome folding and the large-scale genome organization. Could a part of information on the chromosome folding be obtained directly from underlying genomic DNA sequences abundantly stored in the databanks? To answer this question, we developed an original discrete double Fourier transform (DDFT). DDFT serves for the detection of large-scale genome regularities associated with domains/units at the different levels of hierarchical chromosome folding. The method is versatile and can be applied to both genomic DNA sequences and corresponding physico-chemical parameters such as base-pairing free energy. The latter characteristic is closely related to the replication and transcription and can also be used for the assessment of temperature or supercoiling effects on the chromosome folding. We tested the method on the genome of E. coli K-12 and found good correspondence with the annotated domains/units established experimentally. As a brief illustration of further abilities of DDFT, the study of large-scale genome organization for bacteriophage PHIX174 and bacterium Caulobacter crescentus was also added. The combined experimental, modeling, and bioinformatic DDFT analysis should yield more complete knowledge on the chromosome architecture and genome organization. Copyright © 2017 Elsevier Ltd. All rights reserved.

Nucleotide sequence of an exceptionally long 5.8S ribosomal RNA from Crithidia fasciculata.

PubMed Central

Schnare, M N; Gray, M W

1982-01-01

In Crithidia fasciculata, a trypanosomatid protozoan, the large ribosomal subunit contains five small RNA species (e, f, g, i, j) in addition to 5S rRNA [Gray, M.W. (1981) Mol. Cell. Biol. 1, 347-357]. The complete primary sequence of species i is shown here to be pAACGUGUmCGCGAUGGAUGACUUGGCUUCCUAUCUCGUUGA ... AGAmACGCAGUAAAGUGCGAUAAGUGGUApsiCAAUUGmCAGAAUCAUUCAAUUACCGAAUCUUUGAACGAAACGG ... CGCAUGGGAGAAGCUCUUUUGAGUCAUCCCCGUGCAUGCCAUAUUCUCCAmGUGUCGAA(C)OH. This sequence establishes that species i is a 5.8S rRNA, despite its exceptional length (171-172 nucleotides). The extra nucleotides in C. fasciculata 5.8S rRNA are located in a region whose primary sequence and length are highly variable among 5.8S rRNAs, but which is capable of forming a stable hairpin loop structure (the "G+C-rich hairpin"). The sequence of C. fasciculata 5.8S rRNA is no more closely related to that of another protozoan, Acanthamoeba castellanii, than it is to representative 5.8S rRNA sequences from the other eukaryotic kingdoms, emphasizing the deep phylogenetic divisions that seem to exist within the Kingdom Protista. Images PMID:7079176

YM500: a small RNA sequencing (smRNA-seq) database for microRNA research

PubMed Central

Cheng, Wei-Chung; Chung, I-Fang; Huang, Tse-Shun; Chang, Shih-Ting; Sun, Hsing-Jen; Tsai, Cheng-Fong; Liang, Muh-Lii; Wong, Tai-Tong; Wang, Hsei-Wei

2013-01-01

MicroRNAs (miRNAs) are small RNAs ∼22 nt in length that are involved in the regulation of a variety of physiological and pathological processes. Advances in high-throughput small RNA sequencing (smRNA-seq), one of the next-generation sequencing applications, have reshaped the miRNA research landscape. In this study, we established an integrative database, the YM500 (http://ngs.ym.edu.tw/ym500/), containing analysis pipelines and analysis results for 609 human and mice smRNA-seq results, including public data from the Gene Expression Omnibus (GEO) and some private sources. YM500 collects analysis results for miRNA quantification, for isomiR identification (incl. RNA editing), for arm switching discovery, and, more importantly, for novel miRNA predictions. Wetlab validation on >100 miRNAs confirmed high correlation between miRNA profiling and RT-qPCR results (R = 0.84). This database allows researchers to search these four different types of analysis results via our interactive web interface. YM500 allows researchers to define the criteria of isomiRs, and also integrates the information of dbSNP to help researchers distinguish isomiRs from SNPs. A user-friendly interface is provided to integrate miRNA-related information and existing evidence from hundreds of sequencing datasets. The identified novel miRNAs and isomiRs hold the potential for both basic research and biotech applications. PMID:23203880

repRNA: a web server for generating various feature vectors of RNA sequences.

PubMed

Liu, Bin; Liu, Fule; Fang, Longyun; Wang, Xiaolong; Chou, Kuo-Chen

2016-02-01

With the rapid growth of RNA sequences generated in the postgenomic age, it is highly desired to develop a flexible method that can generate various kinds of vectors to represent these sequences by focusing on their different features. This is because nearly all the existing machine-learning methods, such as SVM (support vector machine) and KNN (k-nearest neighbor), can only handle vectors but not sequences. To meet the increasing demands and speed up the genome analyses, we have developed a new web server, called "representations of RNA sequences" (repRNA). Compared with the existing methods, repRNA is much more comprehensive, flexible and powerful, as reflected by the following facts: (1) it can generate 11 different modes of feature vectors for users to choose according to their investigation purposes; (2) it allows users to select the features from 22 built-in physicochemical properties and even those defined by users' own; (3) the resultant feature vectors and the secondary structures of the corresponding RNA sequences can be visualized. The repRNA web server is freely accessible to the public at http://bioinformatics.hitsz.edu.cn/repRNA/ .

Analysis of Pteridium ribosomal RNA sequences by rapid direct sequencing.

PubMed

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.

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

PubMed

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.

Evidence for plant-derived xenomiRs based on a large-scale analysis of public small RNA sequencing data from human samples.

PubMed

Zhao, Qi; Liu, Yuanning; Zhang, Ning; Hu, Menghan; Zhang, Hao; Joshi, Trupti; Xu, Dong

2018-01-01

In recent years, an increasing number of studies have reported the presence of plant miRNAs in human samples, which resulted in a hypothesis asserting the existence of plant-derived exogenous microRNA (xenomiR). However, this hypothesis is not widely accepted in the scientific community due to possible sample contamination and the small sample size with lack of rigorous statistical analysis. This study provides a systematic statistical test that can validate (or invalidate) the plant-derived xenomiR hypothesis by analyzing 388 small RNA sequencing data from human samples in 11 types of body fluids/tissues. A total of 166 types of plant miRNAs were found in at least one human sample, of which 14 plant miRNAs represented more than 80% of the total plant miRNAs abundance in human samples. Plant miRNA profiles were characterized to be tissue-specific in different human samples. Meanwhile, the plant miRNAs identified from microbiome have an insignificant abundance compared to those from humans, while plant miRNA profiles in human samples were significantly different from those in plants, suggesting that sample contamination is an unlikely reason for all the plant miRNAs detected in human samples. This study also provides a set of testable synthetic miRNAs with isotopes that can be detected in situ after being fed to animals.

Characterizing the replicability of cell types defined by single cell RNA-sequencing data using MetaNeighbor.

PubMed

Crow, Megan; Paul, Anirban; Ballouz, Sara; Huang, Z Josh; Gillis, Jesse

2018-02-28

Single-cell RNA-sequencing (scRNA-seq) technology provides a new avenue to discover and characterize cell types; however, the experiment-specific technical biases and analytic variability inherent to current pipelines may undermine its replicability. Meta-analysis is further hampered by the use of ad hoc naming conventions. Here we demonstrate our replication framework, MetaNeighbor, that quantifies the degree to which cell types replicate across datasets, and enables rapid identification of clusters with high similarity. We first measure the replicability of neuronal identity, comparing results across eight technically and biologically diverse datasets to define best practices for more complex assessments. We then apply this to novel interneuron subtypes, finding that 24/45 subtypes have evidence of replication, which enables the identification of robust candidate marker genes. Across tasks we find that large sets of variably expressed genes can identify replicable cell types with high accuracy, suggesting a general route forward for large-scale evaluation of scRNA-seq data.

Captured metagenomics: large-scale targeting of genes based on ‘sequence capture’ reveals functional diversity in soils

PubMed Central

Manoharan, Lokeshwaran; Kushwaha, Sandeep K.; Hedlund, Katarina; Ahrén, Dag

2015-01-01

Microbial enzyme diversity is a key to understand many ecosystem processes. Whole metagenome sequencing (WMG) obtains information on functional genes, but it is costly and inefficient due to large amount of sequencing that is required. In this study, we have applied a captured metagenomics technique for functional genes in soil microorganisms, as an alternative to WMG. Large-scale targeting of functional genes, coding for enzymes related to organic matter degradation, was applied to two agricultural soil communities through captured metagenomics. Captured metagenomics uses custom-designed, hybridization-based oligonucleotide probes that enrich functional genes of interest in metagenomic libraries where only probe-bound DNA fragments are sequenced. The captured metagenomes were highly enriched with targeted genes while maintaining their target diversity and their taxonomic distribution correlated well with the traditional ribosomal sequencing. The captured metagenomes were highly enriched with genes related to organic matter degradation; at least five times more than similar, publicly available soil WMG projects. This target enrichment technique also preserves the functional representation of the soils, thereby facilitating comparative metagenomics projects. Here, we present the first study that applies the captured metagenomics approach in large scale, and this novel method allows deep investigations of central ecosystem processes by studying functional gene abundances. PMID:26490729

Methods for processing high-throughput RNA sequencing data.

PubMed

Ares, Manuel

2014-11-03

High-throughput sequencing (HTS) methods for analyzing RNA populations (RNA-Seq) are gaining rapid application to many experimental situations. The steps in an RNA-Seq experiment require thought and planning, especially because the expense in time and materials is currently higher and the protocols are far less routine than those used for other high-throughput methods, such as microarrays. As always, good experimental design will make analysis and interpretation easier. Having a clear biological question, an idea about the best way to do the experiment, and an understanding of the number of replicates needed will make the entire process more satisfying. Whether the goal is capturing transcriptome complexity from a tissue or identifying small fragments of RNA cross-linked to a protein of interest, conversion of the RNA to cDNA followed by direct sequencing using the latest methods is a developing practice, with new technical modifications and applications appearing every day. Even more rapid are the development and improvement of methods for analysis of the very large amounts of data that arrive at the end of an RNA-Seq experiment, making considerations regarding reproducibility, validation, visualization, and interpretation increasingly important. This introduction is designed to review and emphasize a pathway of analysis from experimental design through data presentation that is likely to be successful, with the recognition that better methods are right around the corner. © 2014 Cold Spring Harbor Laboratory Press.

Integrative analyses of RNA editing, alternative splicing, and expression of young genes in human brain transcriptome by deep RNA sequencing.

PubMed

Wu, Dong-Dong; Ye, Ling-Qun; Li, Yan; Sun, Yan-Bo; Shao, Yi; Chen, Chunyan; Zhu, Zhu; Zhong, Li; Wang, Lu; Irwin, David M; Zhang, Yong E; Zhang, Ya-Ping

2015-08-01

Next-generation RNA sequencing has been successfully used for identification of transcript assembly, evaluation of gene expression levels, and detection of post-transcriptional modifications. Despite these large-scale studies, additional comprehensive RNA-seq data from different subregions of the human brain are required to fully evaluate the evolutionary patterns experienced by the human brain transcriptome. Here, we provide a total of 6.5 billion RNA-seq reads from different subregions of the human brain. A significant correlation was observed between the levels of alternative splicing and RNA editing, which might be explained by a competition between the molecular machineries responsible for the splicing and editing of RNA. Young human protein-coding genes demonstrate biased expression to the neocortical and non-neocortical regions during evolution on the lineage leading to humans. We also found that a significantly greater number of young human protein-coding genes are expressed in the putamen, a tissue that was also observed to have the highest level of RNA-editing activity. The putamen, which previously received little attention, plays an important role in cognitive ability, and our data suggest a potential contribution of the putamen to human evolution. © The Author (2015). Published by Oxford University Press on behalf of Journal of Molecular Cell Biology, IBCB, SIBS, CAS. All rights reserved.

Experimental investigation of an RNA sequence space

NASA Technical Reports Server (NTRS)

Lee, Youn-Hyung; Dsouza, Lisa; Fox, George E.

1993-01-01

Modern rRNAs are the historic consequence of an ongoing evolutionary exploration of a sequence space. These extant sequences belong to a special subset of the sequence space that is comprised only of those primary sequences that can validly perform the biological function(s) required of the particular RNA. If it were possible to readily identify all such valid sequences, stochastic predictions could be made about the relative likelihood of various evolutionary pathways available to an RNA. Herein an experimental system which can assess whether a particular sequence is likely to have validity as a eubacterial 5S rRNA is described. A total of ten naturally occurring, and hence known to be valid, sequences and two point mutants of unknown validity were used to test the usefulness of the approach. Nine of the ten valid sequences tested positive whereas both mutants tested as clearly defective. The tenth valid sequence gave results that would be interpreted as reflecting a borderline status were the answer not known. These results demonstrate that it is possible to experimentally determine which sequences in local regions of the sequence space are potentially valid 5S rRNAs.

Ribosomal RNA sequence suggest microsporidia are extremely ancient eukaryotes

NASA Technical Reports Server (NTRS)

Vossbrinck, C. R.; Maddox, J. V.; Friedman, S.; Debrunner-Vossbrinck, B. A.; Woese, C. R.

1987-01-01

A comparative sequence analysis of the 18S small subunit ribosomal RNA (rRNA) of the microsporidium Vairimorpha necatrix is presented. The results show that this rRNA sequence is more unlike those of other eukaryotes than any known eukaryote rRNA sequence. It is concluded that the lineage leading to microsporidia branched very early from that leading to other eukaryotes.

RNAcentral: A comprehensive database of non-coding RNA sequences

DOE Office of Scientific and Technical Information (OSTI.GOV)

Williams, Kelly Porter; Lau, Britney Yan

RNAcentral is a database of non-coding RNA (ncRNA) sequences that aggregates data from specialised ncRNA resources and provides a single entry point for accessing ncRNA sequences of all ncRNA types from all organisms. Since its launch in 2014, RNAcentral has integrated twelve new resources, taking the total number of collaborating database to 22, and began importing new types of data, such as modified nucleotides from MODOMICS and PDB. We created new species-specific identifiers that refer to unique RNA sequences within a context of single species. Furthermore, the website has been subject to continuous improvements focusing on text and sequence similaritymore » searches as well as genome browsing functionality.« less

RNAcentral: A comprehensive database of non-coding RNA sequences

DOE PAGES

Williams, Kelly Porter; Lau, Britney Yan

2016-10-28

RNAcentral is a database of non-coding RNA (ncRNA) sequences that aggregates data from specialised ncRNA resources and provides a single entry point for accessing ncRNA sequences of all ncRNA types from all organisms. Since its launch in 2014, RNAcentral has integrated twelve new resources, taking the total number of collaborating database to 22, and began importing new types of data, such as modified nucleotides from MODOMICS and PDB. We created new species-specific identifiers that refer to unique RNA sequences within a context of single species. Furthermore, the website has been subject to continuous improvements focusing on text and sequence similaritymore » searches as well as genome browsing functionality.« less

A surprisingly large RNase P RNA in Candida glabrata

PubMed Central

KACHOURI, RYM; STRIBINSKIS, VILIUS; ZHU, YANGLONG; RAMOS, KENNETH S.; WESTHOF, ERIC; LI, YONG

2005-01-01

We have found an extremely large ribonuclease P (RNase P) RNA (RPR1) in the human pathogen Candida glabrata and verified that this molecule is expressed and present in the active enzyme complex of this hemiascomycete yeast. A structural alignment of the C. glabrata sequence with 36 other hemiascomycete RNase P RNAs (abbreviated as P RNAs) allows us to characterize the types of insertions. In addition, 15 P RNA sequences were newly characterized by searching in the recently sequenced genomes Candida albicans, C. glabrata, Debaryomyces hansenii, Eremothecium gossypii, Kluyveromyces lactis, Kluyveromyces waltii, Naumovia castellii, Saccharomyces kudriavzevii, Saccharomyces mikatae, and Yarrowia lipolytica; and by PCR amplification for other Candida species (Candida guilliermondii, Candida krusei, Candida parapsilosis, Candida stellatoidea, and Candida tropicalis). The phylogenetic comparative analysis identifies a hemiascomycete secondary structure consensus that presents a conserved core in all species with variable insertions or deletions. The most significant variability is found in C. glabrata P RNA in which three insertions exceeding in total 700 nt are present in the Specificity domain. This P RNA is more than twice the length of any other homologous P RNAs known in the three domains of life and is eight times the size of the smallest. RNase P RNA, therefore, represents one of the most diversified noncoding RNAs in terms of size variation and structural diversity. PMID:15987816

Solid-Phase Nucleic Acid Sequence-Based Amplification and Length-Scale Effects during RNA Amplification.

PubMed

Ma, Youlong; Teng, Feiyue; Libera, Matthew

2018-06-05

Solid-phase oligonucleotide amplification is of interest because of possible applications to next-generation sequencing, multiplexed microarray-based detection, and cell-free synthetic biology. Its efficiency is, however, less than that of traditional liquid-phase amplification involving unconstrained primers and enzymes, and understanding how to optimize the solid-phase amplification process remains challenging. Here, we demonstrate the concept of solid-phase nucleic acid sequence-based amplification (SP-NASBA) and use it to study the effect of tethering density on amplification efficiency. SP-NASBA involves two enzymes, avian myeloblastosis virus reverse transcriptase (AMV-RT) and RNase H, to convert tethered forward and reverse primers into tethered double-stranded DNA (ds-DNA) bridges from which RNA - amplicons can be generated by a third enzyme, T7 RNA polymerase. We create microgels on silicon surfaces using electron-beam patterning of thin-film blends of hydroxyl-terminated and biotin-terminated poly(ethylene glycol) (PEG-OH, PEG-B). The tethering density is linearly related to the PEG-B concentration, and biotinylated primers and molecular beacon detection probes are tethered to streptavidin-activated microgels. While SP-NASBA is very efficient at low tethering densities, the efficiency decreases dramatically with increasing tethering density due to three effects: (a) a reduced hybridization efficiency of tethered molecular beacon detection probes; (b) a decrease in T7 RNA polymerase efficiency; (c) inhibition of T7 RNA polymerase activity by AMV-RT.

A Bayesian taxonomic classification method for 16S rRNA gene sequences with improved species-level accuracy.

PubMed

Gao, Xiang; Lin, Huaiying; Revanna, Kashi; Dong, Qunfeng

2017-05-10

its higher computational costs, our method is still suitable for analyzing large-scale microbiome datasets for practical purposes. Furthermore, our method can be applied for taxonomic classification of any phylogenetic marker gene sequences. Our software, called BLCA, is freely available at https://github.com/qunfengdong/BLCA .

SSMART: Sequence-structure motif identification for RNA-binding proteins.

PubMed

Munteanu, Alina; Mukherjee, Neelanjan; Ohler, Uwe

2018-06-11

RNA-binding proteins (RBPs) regulate every aspect of RNA metabolism and function. There are hundreds of RBPs encoded in the eukaryotic genomes, and each recognize its RNA targets through a specific mixture of RNA sequence and structure properties. For most RBPs, however, only a primary sequence motif has been determined, while the structure of the binding sites is uncharacterized. We developed SSMART, an RNA motif finder that simultaneously models the primary sequence and the structural properties of the RNA targets sites. The sequence-structure motifs are represented as consensus strings over a degenerate alphabet, extending the IUPAC codes for nucleotides to account for secondary structure preferences. Evaluation on synthetic data showed that SSMART is able to recover both sequence and structure motifs implanted into 3'UTR-like sequences, for various degrees of structured/unstructured binding sites. In addition, we successfully used SSMART on high-throughput in vivo and in vitro data, showing that we not only recover the known sequence motif, but also gain insight into the structural preferences of the RBP. Availability: SSMART is freely available at https://ohlerlab.mdc-berlin.de/software/SSMART_137/. Supplementary data are available at Bioinformatics online.

RNAcentral: A vision for an international database of RNA sequences

PubMed Central

Bateman, Alex; Agrawal, Shipra; Birney, Ewan; Bruford, Elspeth A.; Bujnicki, Janusz M.; Cochrane, Guy; Cole, James R.; Dinger, Marcel E.; Enright, Anton J.; Gardner, Paul P.; Gautheret, Daniel; Griffiths-Jones, Sam; Harrow, Jen; Herrero, Javier; Holmes, Ian H.; Huang, Hsien-Da; Kelly, Krystyna A.; Kersey, Paul; Kozomara, Ana; Lowe, Todd M.; Marz, Manja; Moxon, Simon; Pruitt, Kim D.; Samuelsson, Tore; Stadler, Peter F.; Vilella, Albert J.; Vogel, Jan-Hinnerk; Williams, Kelly P.; Wright, Mathew W.; Zwieb, Christian

2011-01-01

During the last decade there has been a great increase in the number of noncoding RNA genes identified, including new classes such as microRNAs and piRNAs. There is also a large growth in the amount of experimental characterization of these RNA components. Despite this growth in information, it is still difficult for researchers to access RNA data, because key data resources for noncoding RNAs have not yet been created. The most pressing omission is the lack of a comprehensive RNA sequence database, much like UniProt, which provides a comprehensive set of protein knowledge. In this article we propose the creation of a new open public resource that we term RNAcentral, which will contain a comprehensive collection of RNA sequences and fill an important gap in the provision of biomedical databases. We envision RNA researchers from all over the world joining a federated RNAcentral network, contributing specialized knowledge and databases. RNAcentral would centralize key data that are currently held across a variety of databases, allowing researchers instant access to a single, unified resource. This resource would facilitate the next generation of RNA research and help drive further discoveries, including those that improve food production and human and animal health. We encourage additional RNA database resources and research groups to join this effort. We aim to obtain international network funding to further this endeavor. PMID:21940779

Large-Scale Concatenation cDNA Sequencing

PubMed Central

Yu, Wei; Andersson, Björn; Worley, Kim C.; Muzny, Donna M.; Ding, Yan; Liu, Wen; Ricafrente, Jennifer Y.; Wentland, Meredith A.; Lennon, Greg; Gibbs, Richard A.

1997-01-01

A total of 100 kb of DNA derived from 69 individual human brain cDNA clones of 0.7–2.0 kb were sequenced by concatenated cDNA sequencing (CCS), whereby multiple individual DNA fragments are sequenced simultaneously in a single shotgun library. The method yielded accurate sequences and a similar efficiency compared with other shotgun libraries constructed from single DNA fragments (>20 kb). Computer analyses were carried out on 65 cDNA clone sequences and their corresponding end sequences to examine both nucleic acid and amino acid sequence similarities in the databases. Thirty-seven clones revealed no DNA database matches, 12 clones generated exact matches (≥98% identity), and 16 clones generated nonexact matches (57%–97% identity) to either known human or other species genes. Of those 28 matched clones, 8 had corresponding end sequences that failed to identify similarities. In a protein similarity search, 27 clone sequences displayed significant matches, whereas only 20 of the end sequences had matches to known protein sequences. Our data indicate that full-length cDNA insert sequences provide significantly more nucleic acid and protein sequence similarity matches than expressed sequence tags (ESTs) for database searching. [All 65 cDNA clone sequences described in this paper have been submitted to the GenBank data library under accession nos. U79240–U79304.] PMID:9110174

Combined Targeted DNA Sequencing in Non-Small Cell Lung Cancer (NSCLC) Using UNCseq and NGScopy, and RNA Sequencing Using UNCqeR for the Detection of Genetic Aberrations in NSCLC

PubMed Central

Walter, Vonn; Patel, Nirali M.; Eberhard, David A.; Hayward, Michele C.; Salazar, Ashley H.; Jo, Heejoon; Soloway, Matthew G.; Wilkerson, Matthew D.; Parker, Joel S.; Yin, Xiaoying; Zhang, Guosheng; Siegel, Marni B.; Rosson, Gary B.; Earp, H. Shelton; Sharpless, Norman E.; Gulley, Margaret L.; Weck, Karen E.

2015-01-01

The recent FDA approval of the MiSeqDx platform provides a unique opportunity to develop targeted next generation sequencing (NGS) panels for human disease, including cancer. We have developed a scalable, targeted panel-based assay termed UNCseq, which involves a NGS panel of over 200 cancer-associated genes and a standardized downstream bioinformatics pipeline for detection of single nucleotide variations (SNV) as well as small insertions and deletions (indel). In addition, we developed a novel algorithm, NGScopy, designed for samples with sparse sequencing coverage to detect large-scale copy number variations (CNV), similar to human SNP Array 6.0 as well as small-scale intragenic CNV. Overall, we applied this assay to 100 snap-frozen lung cancer specimens lacking same-patient germline DNA (07–0120 tissue cohort) and validated our results against Sanger sequencing, SNP Array, and our recently published integrated DNA-seq/RNA-seq assay, UNCqeR, where RNA-seq of same-patient tumor specimens confirmed SNV detected by DNA-seq, if RNA-seq coverage depth was adequate. In addition, we applied the UNCseq assay on an independent lung cancer tumor tissue collection with available same-patient germline DNA (11–1115 tissue cohort) and confirmed mutations using assays performed in a CLIA-certified laboratory. We conclude that UNCseq can identify SNV, indel, and CNV in tumor specimens lacking germline DNA in a cost-efficient fashion. PMID:26076459

The sequence of sequencers: The history of sequencing DNA

PubMed Central

Heather, James M.; Chain, Benjamin

2016-01-01

Determining the order of nucleic acid residues in biological samples is an integral component of a wide variety of research applications. Over the last fifty years large numbers of researchers have applied themselves to the production of techniques and technologies to facilitate this feat, sequencing DNA and RNA molecules. This time-scale has witnessed tremendous changes, moving from sequencing short oligonucleotides to millions of bases, from struggling towards the deduction of the coding sequence of a single gene to rapid and widely available whole genome sequencing. This article traverses those years, iterating through the different generations of sequencing technology, highlighting some of the key discoveries, researchers, and sequences along the way. PMID:26554401

PASTA: splice junction identification from RNA-Sequencing data

PubMed Central

2013-01-01

Background Next generation transcriptome sequencing (RNA-Seq) is emerging as a powerful experimental tool for the study of alternative splicing and its regulation, but requires ad-hoc analysis methods and tools. PASTA (Patterned Alignments for Splicing and Transcriptome Analysis) is a splice junction detection algorithm specifically designed for RNA-Seq data, relying on a highly accurate alignment strategy and on a combination of heuristic and statistical methods to identify exon-intron junctions with high accuracy. Results Comparisons against TopHat and other splice junction prediction software on real and simulated datasets show that PASTA exhibits high specificity and sensitivity, especially at lower coverage levels. Moreover, PASTA is highly configurable and flexible, and can therefore be applied in a wide range of analysis scenarios: it is able to handle both single-end and paired-end reads, it does not rely on the presence of canonical splicing signals, and it uses organism-specific regression models to accurately identify junctions. Conclusions PASTA is a highly efficient and sensitive tool to identify splicing junctions from RNA-Seq data. Compared to similar programs, it has the ability to identify a higher number of real splicing junctions, and provides highly annotated output files containing detailed information about their location and characteristics. Accurate junction data in turn facilitates the reconstruction of the splicing isoforms and the analysis of their expression levels, which will be performed by the remaining modules of the PASTA pipeline, still under development. Use of PASTA can therefore enable the large-scale investigation of transcription and alternative splicing. PMID:23557086

miRBase: integrating microRNA annotation and deep-sequencing data.

PubMed

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/.

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

PubMed

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.

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

PubMed

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.

HYBRIDIZATION PROPERTIES OF DNA SEQUENCES DIRECTING THE SYNTHESIS OF MESSENGER RNA AND HETEROGENEOUS NUCLEAR RNA

PubMed Central

Greenberg, Jay R.; Perry, Robert P.

1971-01-01

The relationship of the DNA sequences from which polyribosomal messenger RNA (mRNA) and heterogeneous nuclear RNA (NRNA) of mouse L cells are transcribed was investigated by means of hybridization kinetics and thermal denaturation of the hybrids. Hybridization was performed in formamide solutions at DNA excess. Under these conditions most of the hybridizing mRNA and NRNA react at values of Dot (DNA concentration multiplied by time) expected for RNA transcribed from the nonrepeated or rarely repeated fraction of the genome. However, a fraction of both mRNA and NRNA hybridize at values of Dot about 10,000 times lower, and therefore must be transcribed from highly redundant DNA sequences. The fraction of NRNA hybridizing to highly repeated sequences is about 1.7 times greater than the corresponding fraction of mRNA. The hybrids formed by the rapidly reacting fractions of both NRNA and mRNA melt over a narrow temperature range with a midpoint about 11°C below that of native L cell DNA. This indicates that these hybrids consist of partially complementary sequences with approximately 11% mismatching of bases. Hybrids formed by the slowly reacting fraction of NRNA melt within 4°–6°C of native DNA, indicating very little, if any, mismatching of bases. Hybrids of the slowly reacting components of mRNA, formed under conditions of sufficiently low RNA input, have a high thermal stability, similar to that observed for hybrids of the slowly reacting NRNA component. However, when higher inputs of mRNA are used, hybrids are formed which have a strikingly lower thermal stability. This observation can be explained by assuming that there is sufficient similarity among the relatively rare DNA sequences coding for mRNA so that under hybridization conditions, in which these DNA sequences are not truly in excess, reversible hybrids exhibiting a considerable amount of mispairing are formed. The fact that a comparable phenomenon has not been observed for NRNA may mean that there is

RNAcentral: an international database of ncRNA sequences

DOE PAGES

Williams, Kelly Porter

2014-10-28

The field of non-coding RNA biology has been hampered by the lack of availability of a comprehensive, up-to-date collection of accessioned RNA sequences. Here we present the first release of RNAcentral, a database that collates and integrates information from an international consortium of established RNA sequence databases. The initial release contains over 8.1 million sequences, including representatives of all major functional classes. A web portal (http://rnacentral.org) provides free access to data, search functionality, cross-references, source code and an integrated genome browser for selected species.

RNA circularization reveals terminal sequence heterogeneity in a double-stranded RNA virus.

PubMed

Widmer, G

1993-03-01

Double-stranded RNA viruses (dsRNA), termed LRV1, have been found in several strains of the protozoan parasite Leishmania. With the aim of constructing a full-length cDNA copy of the viral genome, including its terminal sequences, a protocol based on PCR amplification across the 3'-5' junction of circularized RNA was developed. This method proved to be applicable to dsRNA. It provided a relatively simple alternative to one-sided PCR, without loss of specificity inherent in the use of generic primers. LRV1 terminal nucleotide sequences obtained by this method showed a considerable variation in length, particularly at the 5' end of the positive strand, as well as the potential for forming 3' overhangs. The opposite genomic end terminates in 0, 1, or 2 TCA trinucleotide repeats. These results are compared with terminal sequences derived from one-sided PCR experiments.

DNA and RNA sequencing by nanoscale reading through programmable electrophoresis and nanoelectrode-gated tunneling and dielectric detection

DOEpatents

Lee, James W.; Thundat, Thomas G.

2005-06-14

An apparatus and method for performing nucleic acid (DNA and/or RNA) sequencing on a single molecule. The genetic sequence information is obtained by probing through a DNA or RNA molecule base by base at nanometer scale as though looking through a strip of movie film. This DNA sequencing nanotechnology has the theoretical capability of performing DNA sequencing at a maximal rate of about 1,000,000 bases per second. This enhanced performance is made possible by a series of innovations including: novel applications of a fine-tuned nanometer gap for passage of a single DNA or RNA molecule; thin layer microfluidics for sample loading and delivery; and programmable electric fields for precise control of DNA or RNA movement. Detection methods include nanoelectrode-gated tunneling current measurements, dielectric molecular characterization, and atomic force microscopy/electrostatic force microscopy (AFM/EFM) probing for nanoscale reading of the nucleic acid sequences.

Computational Prediction of the Immunomodulatory Potential of RNA Sequences.

PubMed

Nagpal, Gandharva; Chaudhary, Kumardeep; Dhanda, Sandeep Kumar; Raghava, Gajendra Pal Singh

2017-01-01

Advances in the knowledge of various roles played by non-coding RNAs have stimulated the application of RNA molecules as therapeutics. Among these molecules, miRNA, siRNA, and CRISPR-Cas9 associated gRNA have been identified as the most potent RNA molecule classes with diverse therapeutic applications. One of the major limitations of RNA-based therapeutics is immunotoxicity of RNA molecules as it may induce the innate immune system. In contrast, RNA molecules that are potent immunostimulators are strong candidates for use in vaccine adjuvants. Thus, it is important to understand the immunotoxic or immunostimulatory potential of these RNA molecules. The experimental techniques for determining immunostimulatory potential of siRNAs are time- and resource-consuming. To overcome this limitation, recently our group has developed a web-based server "imRNA" for predicting the immunomodulatory potential of RNA sequences. This server integrates a number of modules that allow users to perform various tasks including (1) generation of RNA analogs with reduced immunotoxicity, (2) identification of highly immunostimulatory regions in RNA sequence, and (3) virtual screening. This server may also assist users in the identification of minimum mutations required in a given RNA sequence to minimize its immunomodulatory potential that is required for designing RNA-based therapeutics. Besides, the server can be used for designing RNA-based vaccine adjuvants as it may assist users in the identification of mutations required for increasing immunomodulatory potential of a given RNA sequence. In summary, this chapter describes major applications of the "imRNA" server in designing RNA-based therapeutics and vaccine adjuvants (http://www.imtech.res.in/raghava/imrna/).

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

PubMed

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.

Fast online and index-based algorithms for approximate search of RNA sequence-structure patterns

PubMed Central

2013-01-01

Background It is well known that the search for homologous RNAs is more effective if both sequence and structure information is incorporated into the search. However, current tools for searching with RNA sequence-structure patterns cannot fully handle mutations occurring on both these levels or are simply not fast enough for searching large sequence databases because of the high computational costs of the underlying sequence-structure alignment problem. Results We present new fast index-based and online algorithms for approximate matching of RNA sequence-structure patterns supporting a full set of edit operations on single bases and base pairs. Our methods efficiently compute semi-global alignments of structural RNA patterns and substrings of the target sequence whose costs satisfy a user-defined sequence-structure edit distance threshold. For this purpose, we introduce a new computing scheme to optimally reuse the entries of the required dynamic programming matrices for all substrings and combine it with a technique for avoiding the alignment computation of non-matching substrings. Our new index-based methods exploit suffix arrays preprocessed from the target database and achieve running times that are sublinear in the size of the searched sequences. To support the description of RNA molecules that fold into complex secondary structures with multiple ordered sequence-structure patterns, we use fast algorithms for the local or global chaining of approximate sequence-structure pattern matches. The chaining step removes spurious matches from the set of intermediate results, in particular of patterns with little specificity. In benchmark experiments on the Rfam database, our improved online algorithm is faster than the best previous method by up to factor 45. Our best new index-based algorithm achieves a speedup of factor 560. Conclusions The presented methods achieve considerable speedups compared to the best previous method. This, together with the expected

Identification of characteristic oligonucleotides in the bacterial 16S ribosomal RNA sequence dataset

NASA Technical Reports Server (NTRS)

Zhang, Zhengdong; Willson, Richard C.; Fox, George E.

2002-01-01

MOTIVATION: The phylogenetic structure of the bacterial world has been intensively studied by comparing sequences of 16S ribosomal RNA (16S rRNA). This database of sequences is now widely used to design probes for the detection of specific bacteria or groups of bacteria one at a time. The success of such methods reflects the fact that there are local sequence segments that are highly characteristic of particular organisms or groups of organisms. It is not clear, however, the extent to which such signature sequences exist in the 16S rRNA dataset. A better understanding of the numbers and distribution of highly informative oligonucleotide sequences may facilitate the design of hybridization arrays that can characterize the phylogenetic position of an unknown organism or serve as the basis for the development of novel approaches for use in bacterial identification. RESULTS: A computer-based algorithm that characterizes the extent to which any individual oligonucleotide sequence in 16S rRNA is characteristic of any particular bacterial grouping was developed. A measure of signature quality, Q(s), was formulated and subsequently calculated for every individual oligonucleotide sequence in the size range of 5-11 nucleotides and for 15mers with reference to each cluster and subcluster in a 929 organism representative phylogenetic tree. Subsequently, the perfect signature sequences were compared to the full set of 7322 sequences to see how common false positives were. The work completed here establishes beyond any doubt that highly characteristic oligonucleotides exist in the bacterial 16S rRNA sequence dataset in large numbers. Over 16,000 15mers were identified that might be useful as signatures. Signature oligonucleotides are available for over 80% of the nodes in the representative tree.

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

PubMed

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

BioPig: a Hadoop-based analytic toolkit for large-scale sequence data.

PubMed

Nordberg, Henrik; Bhatia, Karan; Wang, Kai; Wang, Zhong

2013-12-01

The recent revolution in sequencing technologies has led to an exponential growth of sequence data. As a result, most of the current bioinformatics tools become obsolete as they fail to scale with data. To tackle this 'data deluge', here we introduce the BioPig sequence analysis toolkit as one of the solutions that scale to data and computation. We built BioPig on the Apache's Hadoop MapReduce system and the Pig data flow language. Compared with traditional serial and MPI-based algorithms, BioPig has three major advantages: first, BioPig's programmability greatly reduces development time for parallel bioinformatics applications; second, testing BioPig with up to 500 Gb sequences demonstrates that it scales automatically with size of data; and finally, BioPig can be ported without modification on many Hadoop infrastructures, as tested with Magellan system at National Energy Research Scientific Computing Center and the Amazon Elastic Compute Cloud. In summary, BioPig represents a novel program framework with the potential to greatly accelerate data-intensive bioinformatics analysis.

Highly multiplexed subcellular RNA sequencing in situ

PubMed Central

Lee, Je Hyuk; Daugharthy, Evan R.; Scheiman, Jonathan; Kalhor, Reza; Ferrante, Thomas C.; Yang, Joyce L.; Terry, Richard; Jeanty, Sauveur S. F.; Li, Chao; Amamoto, Ryoji; Peters, Derek T.; Turczyk, Brian M.; Marblestone, Adam H.; Inverso, Samuel A.; Bernard, Amy; Mali, Prashant; Rios, Xavier; Aach, John; Church, George M.

2014-01-01

Understanding the spatial organization of gene expression with single nucleotide resolution requires localizing the sequences of expressed RNA transcripts within a cell in situ. Here we describe fluorescent in situ RNA sequencing (FISSEQ), in which stably cross-linked cDNA amplicons are sequenced within a biological sample. Using 30-base reads from 8,742 genes in situ, we examined RNA expression and localization in human primary fibroblasts using a simulated wound healing assay. FISSEQ is compatible with tissue sections and whole mount embryos, and reduces the limitations of optical resolution and noisy signals on single molecule detection. Our platform enables massively parallel detection of genetic elements, including gene transcripts and molecular barcodes, and can be used to investigate cellular phenotype, gene regulation, and environment in situ. PMID:24578530

Computational Prediction of miRNA Genes from Small RNA Sequencing Data

PubMed Central

Kang, Wenjing; Friedländer, Marc R.

2015-01-01

Next-generation sequencing now for the first time allows researchers to gage 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. microRNAs (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. PMID:25674563

The sequence of sequencers: The history of sequencing DNA.

PubMed

Heather, James M; Chain, Benjamin

2016-01-01

Determining the order of nucleic acid residues in biological samples is an integral component of a wide variety of research applications. Over the last fifty years large numbers of researchers have applied themselves to the production of techniques and technologies to facilitate this feat, sequencing DNA and RNA molecules. This time-scale has witnessed tremendous changes, moving from sequencing short oligonucleotides to millions of bases, from struggling towards the deduction of the coding sequence of a single gene to rapid and widely available whole genome sequencing. This article traverses those years, iterating through the different generations of sequencing technology, highlighting some of the key discoveries, researchers, and sequences along the way. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

How Messenger RNA and Nascent Chain Sequences Regulate Translation Elongation.

PubMed

Choi, Junhong; Grosely, Rosslyn; Prabhakar, Arjun; Lapointe, Christopher P; Wang, Jinfan; Puglisi, Joseph D

2018-06-20

Translation elongation is a highly coordinated, multistep, multifactor process that ensures accurate and efficient addition of amino acids to a growing nascent-peptide chain encoded in the sequence of translated messenger RNA (mRNA). Although translation elongation is heavily regulated by external factors, there is clear evidence that mRNA and nascent-peptide sequences control elongation dynamics, determining both the sequence and structure of synthesized proteins. Advances in methods have driven experiments that revealed the basic mechanisms of elongation as well as the mechanisms of regulation by mRNA and nascent-peptide sequences. In this review, we highlight how mRNA and nascent-peptide elements manipulate the translation machinery to alter the dynamics and pathway of elongation.

A weighted sampling algorithm for the design of RNA sequences with targeted secondary structure and nucleotide distribution.

PubMed

Reinharz, Vladimir; Ponty, Yann; Waldispühl, Jérôme

2013-07-01

The design of RNA sequences folding into predefined secondary structures is a milestone for many synthetic biology and gene therapy studies. Most of the current software uses similar local search strategies (i.e. a random seed is progressively adapted to acquire the desired folding properties) and more importantly do not allow the user to control explicitly the nucleotide distribution such as the GC-content in their sequences. However, the latter is an important criterion for large-scale applications as it could presumably be used to design sequences with better transcription rates and/or structural plasticity. In this article, we introduce IncaRNAtion, a novel algorithm to design RNA sequences folding into target secondary structures with a predefined nucleotide distribution. IncaRNAtion uses a global sampling approach and weighted sampling techniques. We show that our approach is fast (i.e. running time comparable or better than local search methods), seedless (we remove the bias of the seed in local search heuristics) and successfully generates high-quality sequences (i.e. thermodynamically stable) for any GC-content. To complete this study, we develop a hybrid method combining our global sampling approach with local search strategies. Remarkably, our glocal methodology overcomes both local and global approaches for sampling sequences with a specific GC-content and target structure. IncaRNAtion is available at csb.cs.mcgill.ca/incarnation/. Supplementary data are available at Bioinformatics online.

Ecological Consistency of SSU rRNA-Based Operational Taxonomic Units at a Global Scale

PubMed Central

Schmidt, Thomas S. B.; Matias Rodrigues, João F.; von Mering, Christian

2014-01-01

Operational Taxonomic Units (OTUs), usually defined as clusters of similar 16S/18S rRNA sequences, are the most widely used basic diversity units in large-scale characterizations of microbial communities. However, it remains unclear how well the various proposed OTU clustering algorithms approximate ‘true’ microbial taxa. Here, we explore the ecological consistency of OTUs – based on the assumption that, like true microbial taxa, they should show measurable habitat preferences (niche conservatism). In a global and comprehensive survey of available microbial sequence data, we systematically parse sequence annotations to obtain broad ecological descriptions of sampling sites. Based on these, we observe that sequence-based microbial OTUs generally show high levels of ecological consistency. However, different OTU clustering methods result in marked differences in the strength of this signal. Assuming that ecological consistency can serve as an objective external benchmark for cluster quality, we conclude that hierarchical complete linkage clustering, which provided the most ecologically consistent partitions, should be the default choice for OTU clustering. To our knowledge, this is the first approach to assess cluster quality using an external, biologically meaningful parameter as a benchmark, on a global scale. PMID:24763141

Next-Generation Sequencing of the Chrysanthemum nankingense (Asteraceae) Transcriptome Permits Large-Scale Unigene Assembly and SSR Marker Discovery

PubMed Central

Wang, Haibin; Jiang, Jiafu; Chen, Sumei; Qi, Xiangyu; Peng, Hui; Li, Pirui; Song, Aiping; Guan, Zhiyong; Fang, Weimin; Liao, Yuan; Chen, Fadi

2013-01-01

Background Simple sequence repeats (SSRs) are ubiquitous in eukaryotic genomes. Chrysanthemum is one of the largest genera in the Asteraceae family. Only few Chrysanthemum expressed sequence tag (EST) sequences have been acquired to date, so the number of available EST-SSR markers is very low. Methodology/Principal Findings Illumina paired-end sequencing technology produced over 53 million sequencing reads from C. nankingense mRNA. The subsequent de novo assembly yielded 70,895 unigenes, of which 45,789 (64.59%) unigenes showed similarity to the sequences in NCBI database. Out of 45,789 sequences, 107 have hits to the Chrysanthemum Nr protein database; 679 and 277 sequences have hits to the database of Helianthus and Lactuca species, respectively. MISA software identified a large number of putative EST-SSRs, allowing 1,788 primer pairs to be designed from the de novo transcriptome sequence and a further 363 from archival EST sequence. Among 100 primer pairs randomly chosen, 81 markers have amplicons and 20 are polymorphic for genotypes analysis in Chrysanthemum. The results showed that most (but not all) of the assays were transferable across species and that they exposed a significant amount of allelic diversity. Conclusions/Significance SSR markers acquired by transcriptome sequencing are potentially useful for marker-assisted breeding and genetic analysis in the genus Chrysanthemum and its related genera. PMID:23626799

XLID-Causing Mutations and Associated Genes Challenged in Light of Data From Large-Scale Human Exome Sequencing

PubMed Central

Piton, Amélie; Redin, Claire; Mandel, Jean-Louis

2013-01-01

Because of the unbalanced sex ratio (1.3–1.4 to 1) observed in intellectual disability (ID) and the identification of large ID-affected families showing X-linked segregation, much attention has been focused on the genetics of X-linked ID (XLID). Mutations causing monogenic XLID have now been reported in over 100 genes, most of which are commonly included in XLID diagnostic gene panels. Nonetheless, the boundary between true mutations and rare non-disease-causing variants often remains elusive. The sequencing of a large number of control X chromosomes, required for avoiding false-positive results, was not systematically possible in the past. Such information is now available thanks to large-scale sequencing projects such as the National Heart, Lung, and Blood (NHLBI) Exome Sequencing Project, which provides variation information on 10,563 X chromosomes from the general population. We used this NHLBI cohort to systematically reassess the implication of 106 genes proposed to be involved in monogenic forms of XLID. We particularly question the implication in XLID of ten of them (AGTR2, MAGT1, ZNF674, SRPX2, ATP6AP2, ARHGEF6, NXF5, ZCCHC12, ZNF41, and ZNF81), in which truncating variants or previously published mutations are observed at a relatively high frequency within this cohort. We also highlight 15 other genes (CCDC22, CLIC2, CNKSR2, FRMPD4, HCFC1, IGBP1, KIAA2022, KLF8, MAOA, NAA10, NLGN3, RPL10, SHROOM4, ZDHHC15, and ZNF261) for which replication studies are warranted. We propose that similar reassessment of reported mutations (and genes) with the use of data from large-scale human exome sequencing would be relevant for a wide range of other genetic diseases. PMID:23871722

XLID-causing mutations and associated genes challenged in light of data from large-scale human exome sequencing.

PubMed

Piton, Amélie; Redin, Claire; Mandel, Jean-Louis

2013-08-08

Because of the unbalanced sex ratio (1.3-1.4 to 1) observed in intellectual disability (ID) and the identification of large ID-affected families showing X-linked segregation, much attention has been focused on the genetics of X-linked ID (XLID). Mutations causing monogenic XLID have now been reported in over 100 genes, most of which are commonly included in XLID diagnostic gene panels. Nonetheless, the boundary between true mutations and rare non-disease-causing variants often remains elusive. The sequencing of a large number of control X chromosomes, required for avoiding false-positive results, was not systematically possible in the past. Such information is now available thanks to large-scale sequencing projects such as the National Heart, Lung, and Blood (NHLBI) Exome Sequencing Project, which provides variation information on 10,563 X chromosomes from the general population. We used this NHLBI cohort to systematically reassess the implication of 106 genes proposed to be involved in monogenic forms of XLID. We particularly question the implication in XLID of ten of them (AGTR2, MAGT1, ZNF674, SRPX2, ATP6AP2, ARHGEF6, NXF5, ZCCHC12, ZNF41, and ZNF81), in which truncating variants or previously published mutations are observed at a relatively high frequency within this cohort. We also highlight 15 other genes (CCDC22, CLIC2, CNKSR2, FRMPD4, HCFC1, IGBP1, KIAA2022, KLF8, MAOA, NAA10, NLGN3, RPL10, SHROOM4, ZDHHC15, and ZNF261) for which replication studies are warranted. We propose that similar reassessment of reported mutations (and genes) with the use of data from large-scale human exome sequencing would be relevant for a wide range of other genetic diseases. Copyright © 2013 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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.

Novel Approach to Analyzing MFE of Noncoding RNA Sequences

PubMed Central

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. PMID:27695341

Novel Approach to Analyzing MFE of Noncoding RNA Sequences.

PubMed

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.

Diversity analysis in Cannabis sativa based on large-scale development of expressed sequence tag-derived simple sequence repeat markers.

PubMed

Gao, Chunsheng; Xin, Pengfei; Cheng, Chaohua; Tang, Qing; Chen, Ping; Wang, Changbiao; Zang, Gonggu; Zhao, Lining

2014-01-01

Cannabis sativa L. is an important economic plant for the production of food, fiber, oils, and intoxicants. However, lack of sufficient simple sequence repeat (SSR) markers has limited the development of cannabis genetic research. Here, large-scale development of expressed sequence tag simple sequence repeat (EST-SSR) markers was performed to obtain more informative genetic markers, and to assess genetic diversity in cannabis (Cannabis sativa L.). Based on the cannabis transcriptome, 4,577 SSRs were identified from 3,624 ESTs. From there, a total of 3,442 complementary primer pairs were designed as SSR markers. Among these markers, trinucleotide repeat motifs (50.99%) were the most abundant, followed by hexanucleotide (25.13%), dinucleotide (16.34%), tetranucloetide (3.8%), and pentanucleotide (3.74%) repeat motifs, respectively. The AAG/CTT trinucleotide repeat (17.96%) was the most abundant motif detected in the SSRs. One hundred and seventeen EST-SSR markers were randomly selected to evaluate primer quality in 24 cannabis varieties. Among these 117 markers, 108 (92.31%) were successfully amplified and 87 (74.36%) were polymorphic. Forty-five polymorphic primer pairs were selected to evaluate genetic diversity and relatedness among the 115 cannabis genotypes. The results showed that 115 varieties could be divided into 4 groups primarily based on geography: Northern China, Europe, Central China, and Southern China. Moreover, the coefficient of similarity when comparing cannabis from Northern China with the European group cannabis was higher than that when comparing with cannabis from the other two groups, owing to a similar climate. This study outlines the first large-scale development of SSR markers for cannabis. These data may serve as a foundation for the development of genetic linkage, quantitative trait loci mapping, and marker-assisted breeding of cannabis.

Diversity Analysis in Cannabis sativa Based on Large-Scale Development of Expressed Sequence Tag-Derived Simple Sequence Repeat Markers

PubMed Central

Cheng, Chaohua; Tang, Qing; Chen, Ping; Wang, Changbiao; Zang, Gonggu; Zhao, Lining

2014-01-01

Cannabis sativa L. is an important economic plant for the production of food, fiber, oils, and intoxicants. However, lack of sufficient simple sequence repeat (SSR) markers has limited the development of cannabis genetic research. Here, large-scale development of expressed sequence tag simple sequence repeat (EST-SSR) markers was performed to obtain more informative genetic markers, and to assess genetic diversity in cannabis (Cannabis sativa L.). Based on the cannabis transcriptome, 4,577 SSRs were identified from 3,624 ESTs. From there, a total of 3,442 complementary primer pairs were designed as SSR markers. Among these markers, trinucleotide repeat motifs (50.99%) were the most abundant, followed by hexanucleotide (25.13%), dinucleotide (16.34%), tetranucloetide (3.8%), and pentanucleotide (3.74%) repeat motifs, respectively. The AAG/CTT trinucleotide repeat (17.96%) was the most abundant motif detected in the SSRs. One hundred and seventeen EST-SSR markers were randomly selected to evaluate primer quality in 24 cannabis varieties. Among these 117 markers, 108 (92.31%) were successfully amplified and 87 (74.36%) were polymorphic. Forty-five polymorphic primer pairs were selected to evaluate genetic diversity and relatedness among the 115 cannabis genotypes. The results showed that 115 varieties could be divided into 4 groups primarily based on geography: Northern China, Europe, Central China, and Southern China. Moreover, the coefficient of similarity when comparing cannabis from Northern China with the European group cannabis was higher than that when comparing with cannabis from the other two groups, owing to a similar climate. This study outlines the first large-scale development of SSR markers for cannabis. These data may serve as a foundation for the development of genetic linkage, quantitative trait loci mapping, and marker-assisted breeding of cannabis. PMID:25329551

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

PubMed Central

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

Analysis of sequencing data for probing RNA secondary structures and protein-RNA binding in studying posttranscriptional regulations.

PubMed

Hu, Xihao; Wu, Yang; Lu, Zhi John; Yip, Kevin Y

2016-11-01

High-throughput sequencing has been used to study posttranscriptional regulations, where the identification of protein-RNA binding is a major and fast-developing sub-area, which is in turn benefited by the sequencing methods for whole-transcriptome probing of RNA secondary structures. In the study of RNA secondary structures using high-throughput sequencing, bases are modified or cleaved according to their structural features, which alter the resulting composition of sequencing reads. In the study of protein-RNA binding, methods have been proposed to immuno-precipitate (IP) protein-bound RNA transcripts in vitro or in vivo By sequencing these transcripts, the protein-RNA interactions and the binding locations can be identified. For both types of data, read counts are affected by a combination of confounding factors, including expression levels of transcripts, sequence biases, mapping errors and the probing or IP efficiency of the experimental protocols. Careful processing of the sequencing data and proper extraction of important features are fundamentally important to a successful analysis. Here we review and compare different experimental methods for probing RNA secondary structures and binding sites of RNA-binding proteins (RBPs), and the computational methods proposed for analyzing the corresponding sequencing data. We suggest how these two types of data should be integrated to study the structural properties of RBP binding sites as a systematic way to better understand posttranscriptional regulations. © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Evaluation of 16S Rrna amplicon sequencing using two next-generation sequencing technologies for phylogenetic analysis of the rumen bacterial community in steers

USDA-ARS?s Scientific Manuscript database

Next generation sequencing technologies have vastly changed the approach of sequencing of the 16S rRNA gene for studies in microbial ecology. Three distinct technologies are available for large-scale 16S sequencing. All three are subject to biases introduced by sequencing error rates, amplificatio...

RNA-TVcurve: a Web server for RNA secondary structure comparison based on a multi-scale similarity of its triple vector curve representation.

PubMed

Li, Ying; Shi, Xiaohu; Liang, Yanchun; Xie, Juan; Zhang, Yu; Ma, Qin

2017-01-21

RNAs have been found to carry diverse functionalities in nature. Inferring the similarity between two given RNAs is a fundamental step to understand and interpret their functional relationship. The majority of functional RNAs show conserved secondary structures, rather than sequence conservation. Those algorithms relying on sequence-based features usually have limitations in their prediction performance. Hence, integrating RNA structure features is very critical for RNA analysis. Existing algorithms mainly fall into two categories: alignment-based and alignment-free. The alignment-free algorithms of RNA comparison usually have lower time complexity than alignment-based algorithms. An alignment-free RNA comparison algorithm was proposed, in which novel numerical representations RNA-TVcurve (triple vector curve representation) of RNA sequence and corresponding secondary structure features are provided. Then a multi-scale similarity score of two given RNAs was designed based on wavelet decomposition of their numerical representation. In support of RNA mutation and phylogenetic analysis, a web server (RNA-TVcurve) was designed based on this alignment-free RNA comparison algorithm. It provides three functional modules: 1) visualization of numerical representation of RNA secondary structure; 2) detection of single-point mutation based on secondary structure; and 3) comparison of pairwise and multiple RNA secondary structures. The inputs of the web server require RNA primary sequences, while corresponding secondary structures are optional. For the primary sequences alone, the web server can compute the secondary structures using free energy minimization algorithm in terms of RNAfold tool from Vienna RNA package. RNA-TVcurve is the first integrated web server, based on an alignment-free method, to deliver a suite of RNA analysis functions, including visualization, mutation analysis and multiple RNAs structure comparison. The comparison results with two popular RNA

Identifying novel sequence variants of RNA 3D motifs

PubMed Central

Zirbel, Craig L.; Roll, James; Sweeney, Blake A.; Petrov, Anton I.; Pirrung, Meg; Leontis, Neocles B.

2015-01-01

Predicting RNA 3D structure from sequence is a major challenge in biophysics. An important sub-goal is accurately identifying recurrent 3D motifs from RNA internal and hairpin loop sequences extracted from secondary structure (2D) diagrams. We have developed and validated new probabilistic models for 3D motif sequences based on hybrid Stochastic Context-Free Grammars and Markov Random Fields (SCFG/MRF). The SCFG/MRF models are constructed using atomic-resolution RNA 3D structures. To parameterize each model, we use all instances of each motif found in the RNA 3D Motif Atlas and annotations of pairwise nucleotide interactions generated by the FR3D software. Isostericity relations between non-Watson–Crick basepairs are used in scoring sequence variants. SCFG techniques model nested pairs and insertions, while MRF ideas handle crossing interactions and base triples. We use test sets of randomly-generated sequences to set acceptance and rejection thresholds for each motif group and thus control the false positive rate. Validation was carried out by comparing results for four motif groups to RMDetect. The software developed for sequence scoring (JAR3D) is structured to automatically incorporate new motifs as they accumulate in the RNA 3D Motif Atlas when new structures are solved and is available free for download. PMID:26130723

Indel detection from DNA and RNA sequencing data with transIndel.

PubMed

Yang, Rendong; Van Etten, Jamie L; Dehm, Scott M

2018-04-19

Insertions and deletions (indels) are a major class of genomic variation associated with human disease. Indels are primarily detected from DNA sequencing (DNA-seq) data but their transcriptional consequences remain unexplored due to challenges in discriminating medium-sized and large indels from splicing events in RNA-seq data. Here, we developed transIndel, a splice-aware algorithm that parses the chimeric alignments predicted by a short read aligner and reconstructs the mid-sized insertions and large deletions based on the linear alignments of split reads from DNA-seq or RNA-seq data. TransIndel exhibits competitive or superior performance over eight state-of-the-art indel detection tools on benchmarks using both synthetic and real DNA-seq data. Additionally, we applied transIndel to DNA-seq and RNA-seq datasets from 333 primary prostate cancer patients from The Cancer Genome Atlas (TCGA) and 59 metastatic prostate cancer patients from AACR-PCF Stand-Up- To-Cancer (SU2C) studies. TransIndel enhanced the taxonomy of DNA- and RNA-level alterations in prostate cancer by identifying recurrent FOXA1 indels as well as exitron splicing in genes implicated in disease progression. Our study demonstrates that transIndel is a robust tool for elucidation of medium- and large-sized indels from DNA-seq and RNA-seq data. Including RNA-seq in indel discovery efforts leads to significant improvements in sensitivity for identification of med-sized and large indels missed by DNA-seq, and reveals non-canonical RNA-splicing events in genes associated with disease pathology.

Short RNA indicator sequences are not completely degraded by autoclaving

PubMed Central

Unnithan, Veena V.; Unc, Adrian; Joe, Valerisa; Smith, Geoffrey B.

2014-01-01

Short indicator RNA sequences (<100 bp) persist after autoclaving and are recovered intact by molecular amplification. Primers targeting longer sequences are most likely to produce false positives due to amplification errors easily verified by melting curves analyses. If short indicator RNA sequences are used for virus identification and quantification then post autoclave RNA degradation methodology should be employed, which may include further autoclaving. PMID:24518856

RNA-Puzzles Round II: assessment of RNA structure prediction programs applied to three large RNA structures

PubMed Central

Miao, Zhichao; Adamiak, Ryszard W.; Blanchet, Marc-Frédérick; Boniecki, Michal; Bujnicki, Janusz M.; Chen, Shi-Jie; Cheng, Clarence; Chojnowski, Grzegorz; Chou, Fang-Chieh; Cordero, Pablo; Cruz, José Almeida; Ferré-D'Amaré, Adrian R.; Das, Rhiju; Ding, Feng; Dokholyan, Nikolay V.; Dunin-Horkawicz, Stanislaw; Kladwang, Wipapat; Krokhotin, Andrey; Lach, Grzegorz; Magnus, Marcin; Major, François; Mann, Thomas H.; Masquida, Benoît; Matelska, Dorota; Meyer, Mélanie; Peselis, Alla; Popenda, Mariusz; Purzycka, Katarzyna J.; Serganov, Alexander; Stasiewicz, Juliusz; Szachniuk, Marta; Tandon, Arpit; Tian, Siqi; Wang, Jian; Xiao, Yi; Xu, Xiaojun; Zhang, Jinwei; Zhao, Peinan; Zok, Tomasz; Westhof, Eric

2015-01-01

This paper is a report of a second round of RNA-Puzzles, a collective and blind experiment in three-dimensional (3D) RNA structure prediction. Three puzzles, Puzzles 5, 6, and 10, represented sequences of three large RNA structures with limited or no homology with previously solved RNA molecules. A lariat-capping ribozyme, as well as riboswitches complexed to adenosylcobalamin and tRNA, were predicted by seven groups using RNAComposer, ModeRNA/SimRNA, Vfold, Rosetta, DMD, MC-Fold, 3dRNA, and AMBER refinement. Some groups derived models using data from state-of-the-art chemical-mapping methods (SHAPE, DMS, CMCT, and mutate-and-map). The comparisons between the predictions and the three subsequently released crystallographic structures, solved at diffraction resolutions of 2.5–3.2 Å, were carried out automatically using various sets of quality indicators. The comparisons clearly demonstrate the state of present-day de novo prediction abilities as well as the limitations of these state-of-the-art methods. All of the best prediction models have similar topologies to the native structures, which suggests that computational methods for RNA structure prediction can already provide useful structural information for biological problems. However, the prediction accuracy for non-Watson–Crick interactions, key to proper folding of RNAs, is low and some predicted models had high Clash Scores. These two difficulties point to some of the continuing bottlenecks in RNA structure prediction. All submitted models are available for download at http://ahsoka.u-strasbg.fr/rnapuzzles/. PMID:25883046

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

PubMed

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.

mESAdb: microRNA Expression and Sequence Analysis Database

PubMed Central

Kaya, Koray D.; Karakülah, Gökhan; Yakıcıer, Cengiz M.; Acar, Aybar C.; Konu, Özlen

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. PMID:21177657

mESAdb: microRNA expression and sequence analysis database.

PubMed

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.

Evaluating hypotheses of basal animal phylogeny using complete sequences of large and small subunit rRNA.

PubMed

Medina, M; Collins, A G; Silberman, J D; Sogin, M L

2001-08-14

We studied the evolutionary relationships among basal metazoan lineages by using complete large subunit (LSU) and small subunit (SSU) ribosomal RNA sequences for 23 taxa. After identifying competing hypotheses, we performed maximum likelihood searches for trees conforming to each hypothesis. Kishino-Hasegawa tests were used to determine whether the data (LSU, SSU, and combined) reject any of the competing hypotheses. We also conducted unconstrained tree searches, compared the resulting topologies, and calculated bootstrap indices. Shimodaira-Hasegawa tests were applied to determine whether the data reject any of the topologies resulting from the constrained and unconstrained tree searches. LSU, SSU, and the combined data strongly contradict two assertions pertaining to sponge phylogeny. Hexactinellid sponges are not likely to be the basal lineage of a monophyletic Porifera or the sister group to all other animals. Instead, Hexactinellida and Demospongia form a well-supported clade of siliceous sponges, Silicea. It remains unclear, on the basis of these data alone, whether the calcarean sponges are more closely related to Silicea or to nonsponge animals. The SSU and combined data reject the hypothesis that Bilateria is more closely related to Ctenophora than it is to Cnidaria, whereas LSU data alone do not refute either hypothesis. LSU and SSU data agree in supporting the monophyly of Bilateria, Cnidaria, Ctenophora, and Metazoa. LSU sequence data reveal phylogenetic structure in a data set with limited taxon sampling. Continued accumulation of LSU sequences should increase our understanding of animal phylogeny.

Evaluating hypotheses of basal animal phylogeny using complete sequences of large and small subunit rRNA

DOE Office of Scientific and Technical Information (OSTI.GOV)

Medina, Monica; Collins, Allen G.; Silberman, Jeffrey

2001-06-21

We studied the evolutionary relationships among basal metazoan lineages by using complete large subunit (LSU) and small subunit (SSU) ribosomal RNA sequences for 23 taxa. After identifying competing hypotheses, we performed maximum likelihood searches for trees conforming to each hypothesis. Kishino-Hasegawa tests were used to determine whether the data (LSU, SSU, and combined) reject any of the competing hypotheses. We also conducted unconstrained tree searches, compared the resulting topologies, and calculated bootstrap indices. Shimodaira-Hasegawa tests were applied to determine whether the data reject any of the topologies resulting from the constrained and unconstrained tree searches. LSU, SSU, and the combinedmore » data strongly contradict two assertions pertaining to sponge phylogeny. Hexactinellid sponges are not likely to be the basal lineage of amonophyletic Porifera or the sister group to all other animals. Instead, Hexactinellida and Demospongia form a well-supported clade of siliceous sponges, Silicea. It remains unclear, on the basis of these data alone, whether the calcarean sponges are more closely related to Silicea or to nonsponge animals. The SSU and combined data reject the hypothesis that Bilateria is more closely related to Ctenophora than it is to Cnidaria, whereas LSU data alone do not refute either hypothesis. LSU and SSU data agree in supporting the monophyly of Bilateria, Cnidaria, Ctenophora, and Metazoa. LSU sequence data reveal phylogenetic structure in a data set with limited taxon sampling. Continued accumulation of LSU sequences should increase our understanding of animal phylogeny.« less

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

PubMed

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

PubMed Central

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

An Optimized Transient Dual Luciferase Assay for Quantifying MicroRNA Directed Repression of Targeted Sequences

PubMed Central

Moyle, Richard L.; Carvalhais, Lilia C.; Pretorius, Lara-Simone; Nowak, Ekaterina; Subramaniam, Gayathery; Dalton-Morgan, Jessica; Schenk, Peer M.

2017-01-01

Studies investigating the action of small RNAs on computationally predicted target genes require some form of experimental validation. Classical molecular methods of validating microRNA action on target genes are laborious, while approaches that tag predicted target sequences to qualitative reporter genes encounter technical limitations. The aim of this study was to address the challenge of experimentally validating large numbers of computationally predicted microRNA-target transcript interactions using an optimized, quantitative, cost-effective, and scalable approach. The presented method combines transient expression via agroinfiltration of Nicotiana benthamiana leaves with a quantitative dual luciferase reporter system, where firefly luciferase is used to report the microRNA-target sequence interaction and Renilla luciferase is used as an internal standard to normalize expression between replicates. We report the appropriate concentration of N. benthamiana leaf extracts and dilution factor to apply in order to avoid inhibition of firefly LUC activity. Furthermore, the optimal ratio of microRNA precursor expression construct to reporter construct and duration of the incubation period post-agroinfiltration were determined. The optimized dual luciferase assay provides an efficient, repeatable and scalable method to validate and quantify microRNA action on predicted target sequences. The optimized assay was used to validate five predicted targets of rice microRNA miR529b, with as few as six technical replicates. The assay can be extended to assess other small RNA-target sequence interactions, including assessing the functionality of an artificial miRNA or an RNAi construct on a targeted sequence. PMID:28979287

Chromatin-associated RNA sequencing (ChAR-seq) maps genome-wide RNA-to-DNA contacts

PubMed Central

Jukam, David; Teran, Nicole A; Risca, Viviana I; Smith, Owen K; Johnson, Whitney L; Skotheim, Jan M; Greenleaf, William James

2018-01-01

RNA is a critical component of chromatin in eukaryotes, both as a product of transcription, and as an essential constituent of ribonucleoprotein complexes that regulate both local and global chromatin states. Here, we present a proximity ligation and sequencing method called Chromatin-Associated RNA sequencing (ChAR-seq) that maps all RNA-to-DNA contacts across the genome. Using Drosophila cells, we show that ChAR-seq provides unbiased, de novo identification of targets of chromatin-bound RNAs including nascent transcripts, chromosome-specific dosage compensation ncRNAs, and genome-wide trans-associated RNAs involved in co-transcriptional RNA processing. PMID:29648534

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

PubMed

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.

Genotypic variation of Pneumocystis jirovecii isolates in India based on sequence diversity at mitochondrial large subunit rRNA.

PubMed

Gupta, Rashmi; Mirdha, Bijay Ranjan; Guleria, Randeep; Agarwal, Sanjay Kumar; Samantaray, Jyotish Chandra; Kumar, Lalit; Kabra, Sushil Kumar; Luthra, Kalpana; Sreenivas, Vishnubhatla; Iyer, Venkateswaran K

2011-03-01

Pneumocystis pneumonia (PCP), a common and serious opportunistic infection in immunocompromised patients, is caused by Pneumocystis jirovecii (formerly known as Pneumocystis carinii f. sp. hominis). The aim of the present study was to describe the prevalence and distribution of genotypes of P. jirovecii based on sequence polymorphisms at mitochondrial large subunit ribosomal RNA (mt LSU rRNA) region in both HIV and non-HIV immunocompromised individuals with a positive PCR result for PCP in a tertiary health care centre in northern India. From January 2005 to October 2008, 50 patients [22 HIV-seropositive individuals, 10 post-renal transplant (PRT) recipients, 3 cancer patients, and 15 patients with various other kinds of immunosuppression] were found to be positive for P. jirovecii using PCR at the mt LSU rRNA gene. Genotyping of the positive samples was performed at the mt LSU rRNA locus. Genotype 2 was the most common accounting for 42% of total types. This was followed by the genotypes 3 (24%), 1 (20%), and 4 (8%). Mixed infection was observed in 3 cases (6%). The rates of genotype distribution were similar in HIV-seropositive individuals, cancer patients, and in patients with other kinds of immunosuppression. In the PRT recipients, genotype 1 was the most prevalent type (80%). This is the first study describing the prevalence of genotypes in HIV-infected and HIV-uninfected, immunocompromised patients based on the mt LSU rRNA gene from the Indian subcontinent. The most prevalent genotype observed was type 2 in contrast to many studies from other parts of the world where genotype 1 was the most prevalent type, suggesting geographical variation. Copyright © 2010 Elsevier GmbH. All rights reserved.

Quantifying the relationship between sequence and three-dimensional structure conservation in RNA

PubMed Central

2010-01-01

Background In recent years, the number of available RNA structures has rapidly grown reflecting the increased interest on RNA biology. Similarly to the studies carried out two decades ago for proteins, which gave the fundamental grounds for developing comparative protein structure prediction methods, we are now able to quantify the relationship between sequence and structure conservation in RNA. Results Here we introduce an all-against-all sequence- and three-dimensional (3D) structure-based comparison of a representative set of RNA structures, which have allowed us to quantitatively confirm that: (i) there is a measurable relationship between sequence and structure conservation that weakens for alignments resulting in below 60% sequence identity, (ii) evolution tends to conserve more RNA structure than sequence, and (iii) there is a twilight zone for RNA homology detection. Discussion The computational analysis here presented quantitatively describes the relationship between sequence and structure for RNA molecules and defines a twilight zone region for detecting RNA homology. Our work could represent the theoretical basis and limitations for future developments in comparative RNA 3D structure prediction. PMID:20550657

Computational solutions to large-scale data management and analysis

PubMed Central

Schadt, Eric E.; Linderman, Michael D.; Sorenson, Jon; Lee, Lawrence; Nolan, Garry P.

2011-01-01

Today we can generate hundreds of gigabases of DNA and RNA sequencing data in a week for less than US$5,000. The astonishing rate of data generation by these low-cost, high-throughput technologies in genomics is being matched by that of other technologies, such as real-time imaging and mass spectrometry-based flow cytometry. Success in the life sciences will depend on our ability to properly interpret the large-scale, high-dimensional data sets that are generated by these technologies, which in turn requires us to adopt advances in informatics. Here we discuss how we can master the different types of computational environments that exist — such as cloud and heterogeneous computing — to successfully tackle our big data problems. PMID:20717155

Synthetic Spike-in Standards Improve Run-Specific Systematic Error Analysis for DNA and RNA Sequencing

PubMed Central

Zook, Justin M.; Samarov, Daniel; McDaniel, Jennifer; Sen, Shurjo K.; Salit, Marc

2012-01-01

While the importance of random sequencing errors decreases at higher DNA or RNA sequencing depths, systematic sequencing errors (SSEs) dominate at high sequencing depths and can be difficult to distinguish from biological variants. These SSEs can cause base quality scores to underestimate the probability of error at certain genomic positions, resulting in false positive variant calls, particularly in mixtures such as samples with RNA editing, tumors, circulating tumor cells, bacteria, mitochondrial heteroplasmy, or pooled DNA. Most algorithms proposed for correction of SSEs require a data set used to calculate association of SSEs with various features in the reads and sequence context. This data set is typically either from a part of the data set being “recalibrated” (Genome Analysis ToolKit, or GATK) or from a separate data set with special characteristics (SysCall). Here, we combine the advantages of these approaches by adding synthetic RNA spike-in standards to human RNA, and use GATK to recalibrate base quality scores with reads mapped to the spike-in standards. Compared to conventional GATK recalibration that uses reads mapped to the genome, spike-ins improve the accuracy of Illumina base quality scores by a mean of 5 Phred-scaled quality score units, and by as much as 13 units at CpG sites. In addition, since the spike-in data used for recalibration are independent of the genome being sequenced, our method allows run-specific recalibration even for the many species without a comprehensive and accurate SNP database. We also use GATK with the spike-in standards to demonstrate that the Illumina RNA sequencing runs overestimate quality scores for AC, CC, GC, GG, and TC dinucleotides, while SOLiD has less dinucleotide SSEs but more SSEs for certain cycles. We conclude that using these DNA and RNA spike-in standards with GATK improves base quality score recalibration. PMID:22859977

Evaluation of Targeted Sequencing for Transcriptional Analysis of Archival Formalin-Fixed Paraffin-Embedded (FFPE) Samples

EPA Science Inventory

Next-generation sequencing provides unprecedented access to genomic information in archival FFPE tissue samples. However, costs and technical challenges related to RNA isolation and enrichment limit use of whole-genome RNA-sequencing for large-scale studies of FFPE specimens. Rec...

Impact of sequencing depth and read length on single cell RNA sequencing data of T cells.

PubMed

Rizzetto, Simone; Eltahla, Auda A; Lin, Peijie; Bull, Rowena; Lloyd, Andrew R; Ho, Joshua W K; Venturi, Vanessa; Luciani, Fabio

2017-10-06

Single cell RNA sequencing (scRNA-seq) provides great potential in measuring the gene expression profiles of heterogeneous cell populations. In immunology, scRNA-seq allowed the characterisation of transcript sequence diversity of functionally relevant T cell subsets, and the identification of the full length T cell receptor (TCRαβ), which defines the specificity against cognate antigens. Several factors, e.g. RNA library capture, cell quality, and sequencing output affect the quality of scRNA-seq data. We studied the effects of read length and sequencing depth on the quality of gene expression profiles, cell type identification, and TCRαβ reconstruction, utilising 1,305 single cells from 8 publically available scRNA-seq datasets, and simulation-based analyses. Gene expression was characterised by an increased number of unique genes identified with short read lengths (<50 bp), but these featured higher technical variability compared to profiles from longer reads. Successful TCRαβ reconstruction was achieved for 6 datasets (81% - 100%) with at least 0.25 millions (PE) reads of length >50 bp, while it failed for datasets with <30 bp reads. Sufficient read length and sequencing depth can control technical noise to enable accurate identification of TCRαβ and gene expression profiles from scRNA-seq data of T cells.

Exploring the feasibility of using copy number variants as genetic markers through large-scale whole genome sequencing experiments

USDA-ARS?s Scientific Manuscript database

Copy number variants (CNV) are large scale duplications or deletions of genomic sequence that are caused by a diverse set of molecular phenomena that are distinct from single nucleotide polymorphism (SNP) formation. Due to their different mechanisms of formation, CNVs are often difficult to track us...

Sequence determinants of improved CRISPR sgRNA design.

PubMed

Xu, Han; Xiao, Tengfei; Chen, Chen-Hao; Li, Wei; Meyer, Clifford A; Wu, Qiu; Wu, Di; Cong, Le; Zhang, Feng; Liu, Jun S; Brown, Myles; Liu, X Shirley

2015-08-01

The CRISPR/Cas9 system has revolutionized mammalian somatic cell genetics. Genome-wide functional screens using CRISPR/Cas9-mediated knockout or dCas9 fusion-mediated inhibition/activation (CRISPRi/a) are powerful techniques for discovering phenotype-associated gene function. We systematically assessed the DNA sequence features that contribute to single guide RNA (sgRNA) efficiency in CRISPR-based screens. Leveraging the information from multiple designs, we derived a new sequence model for predicting sgRNA efficiency in CRISPR/Cas9 knockout experiments. Our model confirmed known features and suggested new features including a preference for cytosine at the cleavage site. The model was experimentally validated for sgRNA-mediated mutation rate and protein knockout efficiency. Tested on independent data sets, the model achieved significant results in both positive and negative selection conditions and outperformed existing models. We also found that the sequence preference for CRISPRi/a is substantially different from that for CRISPR/Cas9 knockout and propose a new model for predicting sgRNA efficiency in CRISPRi/a experiments. These results facilitate the genome-wide design of improved sgRNA for both knockout and CRISPRi/a studies. © 2015 Xu et al.; Published by Cold Spring Harbor Laboratory Press.

Large-scale sequencing trials begin

DOE Office of Scientific and Technical Information (OSTI.GOV)

Roberts, L.

1990-12-07

As genome sequencing gets under way, investigators are grappling not just with new techniques but also with questions about what is acceptable accuracy and when data should be released. Four groups are embarking on projects that could make or break the human genome project. They are setting out to sequence the longest stretches of DNA ever tackled-several million bases each-and to do it faster and cheaper than anyone has before. If these groups can't pull it off, then prospects for knocking off the entire human genome, all 3 billion bases, in 15 years and for $3 billion will look increasinglymore » unlikely. Harvard's Walter Gilbert, is first tackling the genome of Mycoplasma capricolum. At Stanford, David Botstein and Ron Davis are sequencing Saccharomyces cerevisiae. In a collaborative effort, Robert Waterson at Washington University and John Sulston at the Medical Research Council lab in Cambridge, England, have already started on the nematode Caenorhabditis elegans. And in the only longstanding project of the bunch, University of Wisconsin geneticist Fred Blattner is already several hundred kilobases into the Escherichia coli genome.« less

Equally parsimonious pathways through an RNA sequence space are not equally likely

NASA Technical Reports Server (NTRS)

Lee, Y. H.; DSouza, L. M.; Fox, G. E.

1997-01-01

An experimental system for determining the potential ability of sequences resembling 5S ribosomal RNA (rRNA) to perform as functional 5S rRNAs in vivo in the Escherichia coli cellular environment was devised previously. Presumably, the only 5S rRNA sequences that would have been fixed by ancestral populations are ones that were functionally valid, and hence the actual historical paths taken through RNA sequence space during 5S rRNA evolution would have most likely utilized valid sequences. Herein, we examine the potential validity of all sequence intermediates along alternative equally parsimonious trajectories through RNA sequence space which connect two pairs of sequences that had previously been shown to behave as valid 5S rRNAs in E. coli. The first trajectory requires a total of four changes. The 14 sequence intermediates provide 24 apparently equally parsimonious paths by which the transition could occur. The second trajectory involves three changes, six intermediate sequences, and six potentially equally parsimonious paths. In total, only eight of the 20 sequence intermediates were found to be clearly invalid. As a consequence of the position of these invalid intermediates in the sequence space, seven of the 30 possible paths consisted of exclusively valid sequences. In several cases, the apparent validity/invalidity of the intermediate sequences could not be anticipated on the basis of current knowledge of the 5S rRNA structure. This suggests that the interdependencies in RNA sequence space may be more complex than currently appreciated. If ancestral sequences predicted by parsimony are to be regarded as actual historical sequences, then the present results would suggest that they should also satisfy a validity requirement and that, in at least limited cases, this conjecture can be tested experimentally.

GOLabeler: Improving Sequence-based Large-scale Protein Function Prediction by Learning to Rank.

PubMed

You, Ronghui; Zhang, Zihan; Xiong, Yi; Sun, Fengzhu; Mamitsuka, Hiroshi; Zhu, Shanfeng

2018-03-07

Gene Ontology (GO) has been widely used to annotate functions of proteins and understand their biological roles. Currently only <1% of more than 70 million proteins in UniProtKB have experimental GO annotations, implying the strong necessity of automated function prediction (AFP) of proteins, where AFP is a hard multilabel classification problem due to one protein with a diverse number of GO terms. Most of these proteins have only sequences as input information, indicating the importance of sequence-based AFP (SAFP: sequences are the only input). Furthermore homology-based SAFP tools are competitive in AFP competitions, while they do not necessarily work well for so-called difficult proteins, which have <60% sequence identity to proteins with annotations already. Thus the vital and challenging problem now is how to develop a method for SAFP, particularly for difficult proteins. The key of this method is to extract not only homology information but also diverse, deep- rooted information/evidence from sequence inputs and integrate them into a predictor in a both effective and efficient manner. We propose GOLabeler, which integrates five component classifiers, trained from different features, including GO term frequency, sequence alignment, amino acid trigram, domains and motifs, and biophysical properties, etc., in the framework of learning to rank (LTR), a paradigm of machine learning, especially powerful for multilabel classification. The empirical results obtained by examining GOLabeler extensively and thoroughly by using large-scale datasets revealed numerous favorable aspects of GOLabeler, including significant performance advantage over state-of-the-art AFP methods. http://datamining-iip.fudan.edu.cn/golabeler. zhusf@fudan.edu.cn. Supplementary data are available at Bioinformatics online.

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

PubMed

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.

The zinc fingers of YY1 bind single-stranded RNA with low sequence specificity.

PubMed

Wai, Dorothy C C; Shihab, Manar; Low, Jason K K; Mackay, Joel P

2016-11-02

Classical zinc fingers (ZFs) are traditionally considered to act as sequence-specific DNA-binding domains. More recently, classical ZFs have been recognised as potential RNA-binding modules, raising the intriguing possibility that classical-ZF transcription factors are involved in post-transcriptional gene regulation via direct RNA binding. To date, however, only one classical ZF-RNA complex, that involving TFIIIA, has been structurally characterised. Yin Yang-1 (YY1) is a multi-functional transcription factor involved in many regulatory processes, and binds DNA via four classical ZFs. Recent evidence suggests that YY1 also interacts with RNA, but the molecular nature of the interaction remains unknown. In the present work, we directly assess the ability of YY1 to bind RNA using in vitro assays. Systematic Evolution of Ligands by EXponential enrichment (SELEX) was used to identify preferred RNA sequences bound by the YY1 ZFs from a randomised library over multiple rounds of selection. However, a strong motif was not consistently recovered, suggesting that the RNA sequence selectivity of these domains is modest. YY1 ZF residues involved in binding to single-stranded RNA were identified by NMR spectroscopy and found to be largely distinct from the set of residues involved in DNA binding, suggesting that interactions between YY1 and ssRNA constitute a separate mode of nucleic acid binding. Our data are consistent with recent reports that YY1 can bind to RNA in a low-specificity, yet physiologically relevant manner. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Detecting cooperative sequences in the binding of RNA Polymerase-II

NASA Astrophysics Data System (ADS)

Glass, Kimberly; Rozenberg, Julian; Girvan, Michelle; Losert, Wolfgang; Ott, Ed; Vinson, Charles

2008-03-01

Regulation of the expression level of genes is a key biological process controlled largely by the 1000 base pair (bp) sequence preceding each gene (the promoter region). Within that region transcription factor binding sites (TFBS), 5-10 bp long sequences, act individually or cooperate together in the recruitment of, and therefore subsequent gene transcription by, RNA Polymerase-II (RNAP). We have measured the binding of RNAP to promoters on a genome-wide basis using Chromatin Immunoprecipitation (ChIP-on-Chip) microarray assays. Using all 8-base pair long sequences as a test set, we have identified the DNA sequences that are enriched in promoters with high RNAP binding values. We are able to demonstrate that virtually all sequences enriched in such promoters contain a CpG dinucleotide, indicating that TFBS that contain the CpG dinucleotide are involved in RNAP binding to promoters. Further analysis shows that the presence of pairs of CpG containing sequences cooperate to enhance the binding of RNAP to the promoter.

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

PubMed

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.

A highly efficient method for extracting next-generation sequencing quality RNA from adipose tissue of recalcitrant animal species.

PubMed

Sharma, Davinder; Golla, Naresh; Singh, Dheer; Onteru, Suneel K

2018-03-01

The next-generation sequencing (NGS) based RNA sequencing (RNA-Seq) and transcriptome profiling offers an opportunity to unveil complex biological processes. Successful RNA-Seq and transcriptome profiling requires a large amount of high-quality RNA. However, NGS-quality RNA isolation is extremely difficult from recalcitrant adipose tissue (AT) with high lipid content and low cell numbers. Further, the amount and biochemical composition of AT lipid varies depending upon the animal species which can pose different degree of resistance to RNA extraction. Currently available approaches may work effectively in one species but can be almost unproductive in another species. Herein, we report a two step protocol for the extraction of NGS quality RNA from AT across a broad range of animal species. © 2017 Wiley Periodicals, Inc.

Influence of 5'-flanking sequence on 4.5SI RNA gene transcription by RNA polymerase III.

PubMed

Gogolevskaya, Irina K; Stasenko, Danil V; Tatosyan, Karina A; Kramerov, Dmitri A

2018-05-01

Short nuclear 4.5SI RNA can be found in three related rodent families. Its function remains unknown. The genes of 4.5SI RNA contain an internal promoter of RNA polymerase III composed of the boxes A and B. Here, the effect of the sequence immediately upstream of the mouse 4.5SI RNA gene on its transcription was studied. The gene with deletions and substitutions in the 5'-flanking sequence was used to transfect HeLa cells and its transcriptional activity was evaluated from the cellular level of 4.5SI RNA. Single-nucleotide substitutions in the region adjacent to the transcription start site (positions -2 to -8) decreased the expression activity of the gene down to 40%-60% of the control. The substitution of the conserved pentanucleotide AGAAT (positions -14 to -18) could either decrease (43%-56%) or increase (134%) the gene expression. A TATA-like box (TACATGA) was found at positions -24 to -30 of the 4.5SI RNA gene. Its replacement with a polylinker fragment of the vector did not decrease the transcription level, while its replacement with a GC-rich sequence almost completely (down to 2%-5%) suppressed the transcription of the 4.5SI RNA gene. The effect of plasmid sequences bordering the gene on its transcription by RNA polymerase III is discussed.

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

PubMed

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 <25% in sequence identity fold into very similar 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.

Discriminative Prediction of A-To-I RNA Editing Events from DNA Sequence

PubMed Central

Sun, Jiangming; Singh, Pratibha; Bagge, Annika; Valtat, Bérengère; Vikman, Petter; Spégel, Peter; Mulder, Hindrik

2016-01-01

RNA editing is a post-transcriptional alteration of RNA sequences that, via insertions, deletions or base substitutions, can affect protein structure as well as RNA and protein expression. Recently, it has been suggested that RNA editing may be more frequent than previously thought. A great impediment, however, to a deeper understanding of this process is the paramount sequencing effort that needs to be undertaken to identify RNA editing events. Here, we describe an in silico approach, based on machine learning, that ameliorates this problem. Using 41 nucleotide long DNA sequences, we show that novel A-to-I RNA editing events can be predicted from known A-to-I RNA editing events intra- and interspecies. The validity of the proposed method was verified in an independent experimental dataset. Using our approach, 203 202 putative A-to-I RNA editing events were predicted in the whole human genome. Out of these, 9% were previously reported. The remaining sites require further validation, e.g., by targeted deep sequencing. In conclusion, the approach described here is a useful tool to identify potential A-to-I RNA editing events without the requirement of extensive RNA sequencing. PMID:27764195

Chimeric 16S rRNA sequence formation and detection in Sanger and 454-pyrosequenced PCR amplicons

PubMed Central

Haas, Brian J.; Gevers, Dirk; Earl, Ashlee M.; Feldgarden, Mike; Ward, Doyle V.; Giannoukos, Georgia; Ciulla, Dawn; Tabbaa, Diana; Highlander, Sarah K.; Sodergren, Erica; Methé, Barbara; DeSantis, Todd Z.; Petrosino, Joseph F.; Knight, Rob; Birren, Bruce W.

2011-01-01

Bacterial diversity among environmental samples is commonly assessed with PCR-amplified 16S rRNA gene (16S) sequences. Perceived diversity, however, can be influenced by sample preparation, primer selection, and formation of chimeric 16S amplification products. Chimeras are hybrid products between multiple parent sequences that can be falsely interpreted as novel organisms, thus inflating apparent diversity. We developed a new chimera detection tool called Chimera Slayer (CS). CS detects chimeras with greater sensitivity than previous methods, performs well on short sequences such as those produced by the 454 Life Sciences (Roche) Genome Sequencer, and can scale to large data sets. By benchmarking CS performance against sequences derived from a controlled DNA mixture of known organisms and a simulated chimera set, we provide insights into the factors that affect chimera formation such as sequence abundance, the extent of similarity between 16S genes, and PCR conditions. Chimeras were found to reproducibly form among independent amplifications and contributed to false perceptions of sample diversity and the false identification of novel taxa, with less-abundant species exhibiting chimera rates exceeding 70%. Shotgun metagenomic sequences of our mock community appear to be devoid of 16S chimeras, supporting a role for shotgun metagenomics in validating novel organisms discovered in targeted sequence surveys. PMID:21212162

High-throughput illumina strand-specific RNA sequencing library preparation

USDA-ARS?s Scientific Manuscript database

Conventional Illumina RNA-Seq does not have the resolution to decode the complex eukaryote transcriptome due to the lack of RNA polarity information. Strand-specific RNA sequencing (ssRNA-Seq) can overcome these limitations and as such is better suited for genome annotation, de novo transcriptome as...

Comprehensive evaluation of AmpliSeq transcriptome, a novel targeted whole transcriptome RNA sequencing methodology for global gene expression analysis.

PubMed

Li, Wenli; Turner, Amy; Aggarwal, Praful; Matter, Andrea; Storvick, Erin; Arnett, Donna K; Broeckel, Ulrich

2015-12-16

Whole transcriptome sequencing (RNA-seq) represents a powerful approach for whole transcriptome gene expression analysis. However, RNA-seq carries a few limitations, e.g., the requirement of a significant amount of input RNA and complications led by non-specific mapping of short reads. The Ion AmpliSeq Transcriptome Human Gene Expression Kit (AmpliSeq) was recently introduced by Life Technologies as a whole-transcriptome, targeted gene quantification kit to overcome these limitations of RNA-seq. To assess the performance of this new methodology, we performed a comprehensive comparison of AmpliSeq with RNA-seq using two well-established next-generation sequencing platforms (Illumina HiSeq and Ion Torrent Proton). We analyzed standard reference RNA samples and RNA samples obtained from human induced pluripotent stem cell derived cardiomyocytes (hiPSC-CMs). Using published data from two standard RNA reference samples, we observed a strong concordance of log2 fold change for all genes when comparing AmpliSeq to Illumina HiSeq (Pearson's r = 0.92) and Ion Torrent Proton (Pearson's r = 0.92). We used ROC, Matthew's correlation coefficient and RMSD to determine the overall performance characteristics. All three statistical methods demonstrate AmpliSeq as a highly accurate method for differential gene expression analysis. Additionally, for genes with high abundance, AmpliSeq outperforms the two RNA-seq methods. When analyzing four closely related hiPSC-CM lines, we show that both AmpliSeq and RNA-seq capture similar global gene expression patterns consistent with known sources of variations. Our study indicates that AmpliSeq excels in the limiting areas of RNA-seq for gene expression quantification analysis. Thus, AmpliSeq stands as a very sensitive and cost-effective approach for very large scale gene expression analysis and mRNA marker screening with high accuracy.

Characterization of Human Salivary Extracellular RNA by Next-generation Sequencing.

PubMed

Li, Feng; Kaczor-Urbanowicz, Karolina Elżbieta; Sun, Jie; Majem, Blanca; Lo, Hsien-Chun; Kim, Yong; Koyano, Kikuye; Liu Rao, Shannon; Young Kang, So; Mi Kim, Su; Kim, Kyoung-Mee; Kim, Sung; Chia, David; Elashoff, David; Grogan, Tristan R; Xiao, Xinshu; Wong, David T W

2018-04-23

It was recently discovered that abundant and stable extracellular RNA (exRNA) species exist in bodily fluids. Saliva is an emerging biofluid for biomarker development for noninvasive detection and screening of local and systemic diseases. Use of RNA-Sequencing (RNA-Seq) to profile exRNA is rapidly growing; however, no single preparation and analysis protocol can be used for all biofluids. Specifically, RNA-Seq of saliva is particularly challenging owing to high abundance of bacterial contents and low abundance of salivary exRNA. Given the laborious procedures needed for RNA-Seq library construction, sequencing, data storage, and data analysis, saliva-specific and optimized protocols are essential. We compared different RNA isolation methods and library construction kits for long and small RNA sequencing. The role of ribosomal RNA (rRNA) depletion also was evaluated. The miRNeasy Micro Kit (Qiagen) showed the highest total RNA yield (70.8 ng/mL cell-free saliva) and best small RNA recovery, and the NEBNext library preparation kits resulted in the highest number of detected human genes [5649-6813 at 1 reads per kilobase RNA per million mapped (RPKM)] and small RNAs [482-696 microRNAs (miRNAs) and 190-214 other small RNAs]. The proportion of human RNA-Seq reads was much higher in rRNA-depleted saliva samples (41%) than in samples without rRNA depletion (14%). In addition, the transfer RNA (tRNA)-derived RNA fragments (tRFs), a novel class of small RNAs, were highly abundant in human saliva, specifically tRF-4 (4%) and tRF-5 (15.25%). Our results may help in selection of the best adapted methods of RNA isolation and small and long RNA library constructions for salivary exRNA studies. © 2018 American Association for Clinical Chemistry.

Comparison of ribosomal RNA removal methods for transcriptome sequencing workflows in teleost fish

USDA-ARS?s Scientific Manuscript database

RNA sequencing (RNA-Seq) is becoming the standard for transcriptome analysis. Removal of contaminating ribosomal RNA (rRNA) is a priority in the preparation of libraries suitable for sequencing. rRNAs are commonly removed from total RNA via either mRNA selection or rRNA depletion. These methods have...

Ultra Deep Sequencing of Listeria monocytogenes sRNA Transcriptome Revealed New Antisense RNAs

PubMed Central

Behrens, Sebastian; Widder, Stefanie; Mannala, Gopala Krishna; Qing, Xiaoxing; Madhugiri, Ramakanth; Kefer, Nathalie; Mraheil, Mobarak Abu; Rattei, Thomas; Hain, Torsten

2014-01-01

Listeria monocytogenes, a gram-positive pathogen, and causative agent of listeriosis, has become a widely used model organism for intracellular infections. Recent studies have identified small non-coding RNAs (sRNAs) as important factors for regulating gene expression and pathogenicity of L. monocytogenes. Increased speed and reduced costs of high throughput sequencing (HTS) techniques have made RNA sequencing (RNA-Seq) the state-of-the-art method to study bacterial transcriptomes. We created a large transcriptome dataset of L. monocytogenes containing a total of 21 million reads, using the SOLiD sequencing technology. The dataset contained cDNA sequences generated from L. monocytogenes RNA collected under intracellular and extracellular condition and additionally was size fractioned into three different size ranges from <40 nt, 40–150 nt and >150 nt. We report here, the identification of nine new sRNAs candidates of L. monocytogenes and a reevaluation of known sRNAs of L. monocytogenes EGD-e. Automatic comparison to known sRNAs revealed a high recovery rate of 55%, which was increased to 90% by manual revision of the data. Moreover, thorough classification of known sRNAs shed further light on their possible biological functions. Interestingly among the newly identified sRNA candidates are antisense RNAs (asRNAs) associated to the housekeeping genes purA, fumC and pgi and potentially their regulation, emphasizing the significance of sRNAs for metabolic adaptation in L. monocytogenes. PMID:24498259

SHAPE Selection (SHAPES) enrich for RNA structure signal in SHAPE sequencing-based probing data

PubMed Central

Poulsen, Line Dahl; Kielpinski, Lukasz Jan; Salama, Sofie R.; Krogh, Anders; Vinther, Jeppe

2015-01-01

Selective 2′ Hydroxyl Acylation analyzed by Primer Extension (SHAPE) is an accurate method for probing of RNA secondary structure. In existing SHAPE methods, the SHAPE probing signal is normalized to a no-reagent control to correct for the background caused by premature termination of the reverse transcriptase. Here, we introduce a SHAPE Selection (SHAPES) reagent, N-propanone isatoic anhydride (NPIA), which retains the ability of SHAPE reagents to accurately probe RNA structure, but also allows covalent coupling between the SHAPES reagent and a biotin molecule. We demonstrate that SHAPES-based selection of cDNA–RNA hybrids on streptavidin beads effectively removes the large majority of background signal present in SHAPE probing data and that sequencing-based SHAPES data contain the same amount of RNA structure data as regular sequencing-based SHAPE data obtained through normalization to a no-reagent control. Moreover, the selection efficiently enriches for probed RNAs, suggesting that the SHAPES strategy will be useful for applications with high-background and low-probing signal such as in vivo RNA structure probing. PMID:25805860

DrImpute: imputing dropout events in single cell RNA sequencing data.

PubMed

Gong, Wuming; Kwak, Il-Youp; Pota, Pruthvi; Koyano-Nakagawa, Naoko; Garry, Daniel J

2018-06-08

The single cell RNA sequencing (scRNA-seq) technique begin a new era by allowing the observation of gene expression at the single cell level. However, there is also a large amount of technical and biological noise. Because of the low number of RNA transcriptomes and the stochastic nature of the gene expression pattern, there is a high chance of missing nonzero entries as zero, which are called dropout events. We develop DrImpute to impute dropout events in scRNA-seq data. We show that DrImpute has significantly better performance on the separation of the dropout zeros from true zeros than existing imputation algorithms. We also demonstrate that DrImpute can significantly improve the performance of existing tools for clustering, visualization and lineage reconstruction of nine published scRNA-seq datasets. DrImpute can serve as a very useful addition to the currently existing statistical tools for single cell RNA-seq analysis. DrImpute is implemented in R and is available at https://github.com/gongx030/DrImpute .

INFO-RNA—a server for fast inverse RNA folding satisfying sequence constraints

PubMed Central

Busch, Anke; Backofen, Rolf

2007-01-01

INFO-RNA is a new web server for designing RNA sequences that fold into a user given secondary structure. Furthermore, constraints on the sequence can be specified, e.g. one can restrict sequence positions to a fixed nucleotide or to a set of nucleotides. Moreover, the user can allow violations of the constraints at some positions, which can be advantageous in complicated cases. The INFO-RNA web server allows biologists to design RNA sequences in an automatic manner. It is clearly and intuitively arranged and easy to use. The procedure is fast, as most applications are completed within seconds and it proceeds better and faster than other existing tools. The INFO-RNA web server is freely available at http://www.bioinf.uni-freiburg.de/Software/INFO-RNA/ PMID:17452349

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

PubMed

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.

Method for rapid base sequencing in DNA and RNA

DOEpatents

Jett, J.H.; Keller, R.A.; Martin, J.C.; Moyzis, R.K.; Ratliff, R.L.; Shera, E.B.; Stewart, C.C.

1987-10-07

A method is provided for the rapid base sequencing of DNA or RNA fragments wherein a single fragment of DNA or RNA is provided with identifiable bases and suspended in a moving flow stream. An exonuclease sequentially cleaves individual bases from the end of the suspended fragment. The moving flow stream maintains the cleaved bases in an orderly train for subsequent detection and identification. In a particular embodiment, individual bases forming the DNA or RNA fragments are individually tagged with a characteristic fluorescent dye. The train of bases is then excited to fluorescence with an output spectrum characteristic of the individual bases. Accordingly, the base sequence of the original DNA or RNA fragment can be reconstructed. 2 figs.

Method for rapid base sequencing in DNA and RNA

DOEpatents

Jett, J.H.; Keller, R.A.; Martin, J.C.; Moyzis, R.K.; Ratliff, R.L.; Shera, E.B.; Stewart, C.C.

1990-10-09

A method is provided for the rapid base sequencing of DNA or RNA fragments wherein a single fragment of DNA or RNA is provided with identifiable bases and suspended in a moving flow stream. An exonuclease sequentially cleaves individual bases from the end of the suspended fragment. The moving flow stream maintains the cleaved bases in an orderly train for subsequent detection and identification. In a particular embodiment, individual bases forming the DNA or RNA fragments are individually tagged with a characteristic fluorescent dye. The train of bases is then excited to fluorescence with an output spectrum characteristic of the individual bases. Accordingly, the base sequence of the original DNA or RNA fragment can be reconstructed. 2 figs.

Method for rapid base sequencing in DNA and RNA

DOEpatents

Jett, James H.; Keller, Richard A.; Martin, John C.; Moyzis, Robert K.; Ratliff, Robert L.; Shera, E. Brooks; Stewart, Carleton C.

1990-01-01

A method is provided for the rapid base sequencing of DNA or RNA fragments wherein a single fragment of DNA or RNA is provided with identifiable bases and suspended in a moving flow stream. An exonuclease sequentially cleaves individual bases from the end of the suspended fragment. The moving flow stream maintains the cleaved bases in an orderly train for subsequent detection and identification. In a particular embodiment, individual bases forming the DNA or RNA fragments are individually tagged with a characteristic fluorescent dye. The train of bases is then excited to fluorescence with an output spectrum characteristic of the individual bases. Accordingly, the base sequence of the original DNA or RNA fragment can be reconstructed.

Quantitative assessment of RNA-protein interactions with high-throughput sequencing-RNA affinity profiling.

PubMed

Ozer, Abdullah; Tome, Jacob M; Friedman, Robin C; Gheba, Dan; Schroth, Gary P; Lis, John T

2015-08-01

Because RNA-protein interactions have a central role in a wide array of biological processes, methods that enable a quantitative assessment of these interactions in a high-throughput manner are in great demand. Recently, we developed the high-throughput sequencing-RNA affinity profiling (HiTS-RAP) assay that couples sequencing on an Illumina GAIIx genome analyzer with the quantitative assessment of protein-RNA interactions. This assay is able to analyze interactions between one or possibly several proteins with millions of different RNAs in a single experiment. We have successfully used HiTS-RAP to analyze interactions of the EGFP and negative elongation factor subunit E (NELF-E) proteins with their corresponding canonical and mutant RNA aptamers. Here we provide a detailed protocol for HiTS-RAP that can be completed in about a month (8 d hands-on time). This includes the preparation and testing of recombinant proteins and DNA templates, clustering DNA templates on a flowcell, HiTS and protein binding with a GAIIx instrument, and finally data analysis. We also highlight aspects of HiTS-RAP that can be further improved and points of comparison between HiTS-RAP and two other recently developed methods, quantitative analysis of RNA on a massively parallel array (RNA-MaP) and RNA Bind-n-Seq (RBNS), for quantitative analysis of RNA-protein interactions.

A resource of large-scale molecular markers for monitoring Agropyron cristatum chromatin introgression in wheat background based on transcriptome sequences.

PubMed

Zhang, Jinpeng; Liu, Weihua; Lu, Yuqing; Liu, Qunxing; Yang, Xinming; Li, Xiuquan; Li, Lihui

2017-09-20

Agropyron cristatum is a wild grass of the tribe Triticeae and serves as a gene donor for wheat improvement. However, very few markers can be used to monitor A. cristatum chromatin introgressions in wheat. Here, we reported a resource of large-scale molecular markers for tracking alien introgressions in wheat based on transcriptome sequences. By aligning A. cristatum unigenes with the Chinese Spring reference genome sequences, we designed 9602 A. cristatum expressed sequence tag-sequence-tagged site (EST-STS) markers for PCR amplification and experimental screening. As a result, 6063 polymorphic EST-STS markers were specific for the A. cristatum P genome in the single-receipt wheat background. A total of 4956 randomly selected polymorphic EST-STS markers were further tested in eight wheat variety backgrounds, and 3070 markers displaying stable and polymorphic amplification were validated. These markers covered more than 98% of the A. cristatum genome, and the marker distribution density was approximately 1.28 cM. An application case of all EST-STS markers was validated on the A. cristatum 6 P chromosome. These markers were successfully applied in the tracking of alien A. cristatum chromatin. Altogether, this study provided a universal method of large-scale molecular marker development to monitor wild relative chromatin in wheat.

Mapping specificity landscapes of RNA-protein interactions by high throughput sequencing.

PubMed

Jankowsky, Eckhard; Harris, Michael E

2017-04-15

To function in a biological setting, RNA binding proteins (RBPs) have to discriminate between alternative binding sites in RNAs. This discrimination can occur in the ground state of an RNA-protein binding reaction, in its transition state, or in both. The extent by which RBPs discriminate at these reaction states defines RBP specificity landscapes. Here, we describe the HiTS-Kin and HiTS-EQ techniques, which combine kinetic and equilibrium binding experiments with high throughput sequencing to quantitatively assess substrate discrimination for large numbers of substrate variants at ground and transition states of RNA-protein binding reactions. We discuss experimental design, practical considerations and data analysis and outline how a combination of HiTS-Kin and HiTS-EQ allows the mapping of RBP specificity landscapes. Copyright © 2017 Elsevier Inc. All rights reserved.

Nucleotide sequence determination of guinea-pig casein B mRNA reveals homology with bovine and rat alpha s1 caseins and conservation of the non-coding regions of the mRNA.

PubMed Central

Hall, L; Laird, J E; Craig, R K

1984-01-01

Nucleotide sequence analysis of cloned guinea-pig casein B cDNA sequences has identified two casein B variants related to the bovine and rat alpha s1 caseins. Amino acid homology was largely confined to the known bovine or predicted rat phosphorylation sites and within the 'signal' precursor sequence. Comparison of the deduced nucleotide sequence of the guinea-pig and rat alpha s1 casein mRNA species showed greater sequence conservation in the non-coding than in the coding regions, suggesting a functional and possibly regulatory role for the non-coding regions of casein mRNA. The results provide insight into the evolution of the casein genes, and raise questions as to the role of conserved nucleotide sequences within the non-coding regions of mRNA species. Images Fig. 1. PMID:6548375

High-throughput sequencing reveals circular substrates for an archaeal RNA ligase

PubMed Central

Becker, Hubert F.; Héliou, Alice; Djaout, Kamel; Lestini, Roxane; Regnier, Mireille; Myllykallio, Hannu

2017-01-01

ABSTRACT It is only recently that the abundant presence of circular RNAs (circRNAs) in all kingdoms of Life, including the hyperthermophilic archaeon Pyrococcus abyssi, has emerged. This led us to investigate the physiologic significance of a previously observed weak intramolecular ligation activity of Pab1020 RNA ligase. Here we demonstrate that this enzyme, despite sharing significant sequence similarity with DNA ligases, is indeed an RNA-specific polynucleotide ligase efficiently acting on physiologically significant substrates. Using a combination of RNA immunoprecipitation assays and RNA-seq, our genome-wide studies revealed 133 individual circRNA loci in P. abyssi. The large majority of these loci interacted with Pab1020 in cells and circularization of selected C/D Box and 5S rRNA transcripts was confirmed biochemically. Altogether these studies revealed that Pab1020 is required for RNA circularization. Our results further suggest the functional speciation of an ancestral NTase domain and/or DNA ligase toward RNA ligase activity and prompt for further characterization of the widespread functions of circular RNAs in prokaryotes. Detailed insight into the cellular substrates of Pab1020 may facilitate the development of new biotechnological applications e.g. in ligation of preadenylated adaptors to RNA molecules. PMID:28277897

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

PubMed Central

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.

2017-01-01

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. PMID:28003516

Random access in large-scale DNA data storage.

PubMed

Organick, Lee; Ang, Siena Dumas; Chen, Yuan-Jyue; Lopez, Randolph; Yekhanin, Sergey; Makarychev, Konstantin; Racz, Miklos Z; Kamath, Govinda; Gopalan, Parikshit; Nguyen, Bichlien; Takahashi, Christopher N; Newman, Sharon; Parker, Hsing-Yeh; Rashtchian, Cyrus; Stewart, Kendall; Gupta, Gagan; Carlson, Robert; Mulligan, John; Carmean, Douglas; Seelig, Georg; Ceze, Luis; Strauss, Karin

2018-03-01

Synthetic DNA is durable and can encode digital data with high density, making it an attractive medium for data storage. However, recovering stored data on a large-scale currently requires all the DNA in a pool to be sequenced, even if only a subset of the information needs to be extracted. Here, we encode and store 35 distinct files (over 200 MB of data), in more than 13 million DNA oligonucleotides, and show that we can recover each file individually and with no errors, using a random access approach. We design and validate a large library of primers that enable individual recovery of all files stored within the DNA. We also develop an algorithm that greatly reduces the sequencing read coverage required for error-free decoding by maximizing information from all sequence reads. These advances demonstrate a viable, large-scale system for DNA data storage and retrieval.

A large-scale RNA interference screen identifies genes that regulate autophagy at different stages.

PubMed

Guo, Sujuan; Pridham, Kevin J; Virbasius, Ching-Man; He, Bin; Zhang, Liqing; Varmark, Hanne; Green, Michael R; Sheng, Zhi

2018-02-12

Dysregulated autophagy is central to the pathogenesis and therapeutic development of cancer. However, how autophagy is regulated in cancer is not well understood and genes that modulate cancer autophagy are not fully defined. To gain more insights into autophagy regulation in cancer, we performed a large-scale RNA interference screen in K562 human chronic myeloid leukemia cells using monodansylcadaverine staining, an autophagy-detecting approach equivalent to immunoblotting of the autophagy marker LC3B or fluorescence microscopy of GFP-LC3B. By coupling monodansylcadaverine staining with fluorescence-activated cell sorting, we successfully isolated autophagic K562 cells where we identified 336 short hairpin RNAs. After candidate validation using Cyto-ID fluorescence spectrophotometry, LC3B immunoblotting, and quantitative RT-PCR, 82 genes were identified as autophagy-regulating genes. 20 genes have been reported previously and the remaining 62 candidates are novel autophagy mediators. Bioinformatic analyses revealed that most candidate genes were involved in molecular pathways regulating autophagy, rather than directly participating in the autophagy process. Further autophagy flux assays revealed that 57 autophagy-regulating genes suppressed autophagy initiation, whereas 21 candidates promoted autophagy maturation. Our RNA interference screen identifies identified genes that regulate autophagy at different stages, which helps decode autophagy regulation in cancer and offers novel avenues to develop autophagy-related therapies for cancer.

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

PubMed

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.

SEXCMD: Development and validation of sex marker sequences for whole-exome/genome and RNA sequencing.

PubMed

Jeong, Seongmun; Kim, Jiwoong; Park, Won; Jeon, Hongmin; Kim, Namshin

2017-01-01

Over the last decade, a large number of nucleotide sequences have been generated by next-generation sequencing technologies and deposited to public databases. However, most of these datasets do not specify the sex of individuals sampled because researchers typically ignore or hide this information. Male and female genomes in many species have distinctive sex chromosomes, XX/XY and ZW/ZZ, and expression levels of many sex-related genes differ between the sexes. Herein, we describe how to develop sex marker sequences from syntenic regions of sex chromosomes and use them to quickly identify the sex of individuals being analyzed. Array-based technologies routinely use either known sex markers or the B-allele frequency of X or Z chromosomes to deduce the sex of an individual. The same strategy has been used with whole-exome/genome sequence data; however, all reads must be aligned onto a reference genome to determine the B-allele frequency of the X or Z chromosomes. SEXCMD is a pipeline that can extract sex marker sequences from reference sex chromosomes and rapidly identify the sex of individuals from whole-exome/genome and RNA sequencing after training with a known dataset through a simple machine learning approach. The pipeline counts total numbers of hits from sex-specific marker sequences and identifies the sex of the individuals sampled based on the fact that XX/ZZ samples do not have Y or W chromosome hits. We have successfully validated our pipeline with mammalian (Homo sapiens; XY) and avian (Gallus gallus; ZW) genomes. Typical calculation time when applying SEXCMD to human whole-exome or RNA sequencing datasets is a few minutes, and analyzing human whole-genome datasets takes about 10 minutes. Another important application of SEXCMD is as a quality control measure to avoid mixing samples before bioinformatics analysis. SEXCMD comprises simple Python and R scripts and is freely available at https://github.com/lovemun/SEXCMD.

A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the Sequencing Quality Control consortium

PubMed Central

2014-01-01

We present primary results from the Sequencing Quality Control (SEQC) project, coordinated by the United States Food and Drug Administration. Examining Illumina HiSeq, Life Technologies SOLiD and Roche 454 platforms at multiple laboratory sites using reference RNA samples with built-in controls, we assess RNA sequencing (RNA-seq) performance for junction discovery and differential expression profiling and compare it to microarray and quantitative PCR (qPCR) data using complementary metrics. At all sequencing depths, we discover unannotated exon-exon junctions, with >80% validated by qPCR. We find that measurements of relative expression are accurate and reproducible across sites and platforms if specific filters are used. In contrast, RNA-seq and microarrays do not provide accurate absolute measurements, and gene-specific biases are observed, for these and qPCR. Measurement performance depends on the platform and data analysis pipeline, and variation is large for transcript-level profiling. The complete SEQC data sets, comprising >100 billion reads (10Tb), provide unique resources for evaluating RNA-seq analyses for clinical and regulatory settings. PMID:25150838

Genome-scale characterization of RNA tertiary structures and their functional impact by RNA solvent accessibility prediction.

PubMed

Yang, Yuedong; Li, Xiaomei; Zhao, Huiying; Zhan, Jian; Wang, Jihua; Zhou, Yaoqi

2017-01-01

As most RNA structures are elusive to structure determination, obtaining solvent accessible surface areas (ASAs) of nucleotides in an RNA structure is an important first step to characterize potential functional sites and core structural regions. Here, we developed RNAsnap, the first machine-learning method trained on protein-bound RNA structures for solvent accessibility prediction. Built on sequence profiles from multiple sequence alignment (RNAsnap-prof), the method provided robust prediction in fivefold cross-validation and an independent test (Pearson correlation coefficients, r, between predicted and actual ASA values are 0.66 and 0.63, respectively). Application of the method to 6178 mRNAs revealed its positive correlation to mRNA accessibility by dimethyl sulphate (DMS) experimentally measured in vivo (r = 0.37) but not in vitro (r = 0.07), despite the lack of training on mRNAs and the fact that DMS accessibility is only an approximation to solvent accessibility. We further found strong association across coding and noncoding regions between predicted solvent accessibility of the mutation site of a single nucleotide variant (SNV) and the frequency of that variant in the population for 2.2 million SNVs obtained in the 1000 Genomes Project. Moreover, mapping solvent accessibility of RNAs to the human genome indicated that introns, 5' cap of 5' and 3' cap of 3' untranslated regions, are more solvent accessible, consistent with their respective functional roles. These results support conformational selections as the mechanism for the formation of RNA-protein complexes and highlight the utility of genome-scale characterization of RNA tertiary structures by RNAsnap. The server and its stand-alone downloadable version are available at http://sparks-lab.org. © 2016 Yang et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

Large-scale sequence and structural comparisons of human naive and antigen-experienced antibody repertoires.

PubMed

DeKosky, Brandon J; Lungu, Oana I; Park, Daechan; Johnson, Erik L; Charab, Wissam; Chrysostomou, Constantine; Kuroda, Daisuke; Ellington, Andrew D; Ippolito, Gregory C; Gray, Jeffrey J; Georgiou, George

2016-05-10

Elucidating how antigen exposure and selection shape the human antibody repertoire is fundamental to our understanding of B-cell immunity. We sequenced the paired heavy- and light-chain variable regions (VH and VL, respectively) from large populations of single B cells combined with computational modeling of antibody structures to evaluate sequence and structural features of human antibody repertoires at unprecedented depth. Analysis of a dataset comprising 55,000 antibody clusters from CD19(+)CD20(+)CD27(-) IgM-naive B cells, >120,000 antibody clusters from CD19(+)CD20(+)CD27(+) antigen-experienced B cells, and >2,000 RosettaAntibody-predicted structural models across three healthy donors led to a number of key findings: (i) VH and VL gene sequences pair in a combinatorial fashion without detectable pairing restrictions at the population level; (ii) certain VH:VL gene pairs were significantly enriched or depleted in the antigen-experienced repertoire relative to the naive repertoire; (iii) antigen selection increased antibody paratope net charge and solvent-accessible surface area; and (iv) public heavy-chain third complementarity-determining region (CDR-H3) antibodies in the antigen-experienced repertoire showed signs of convergent paired light-chain genetic signatures, including shared light-chain third complementarity-determining region (CDR-L3) amino acid sequences and/or Vκ,λ-Jκ,λ genes. The data reported here address several longstanding questions regarding antibody repertoire selection and development and provide a benchmark for future repertoire-scale analyses of antibody responses to vaccination and disease.

High-Throughput Sequencing of RNA Silencing-Associated Small RNAs in Olive (Olea europaea L.)

PubMed Central

Donaire, Livia; Pedrola, Laia; de la Rosa, Raúl; Llave, César

2011-01-01

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. PMID:22140484

Effects of RNA integrity on transcript quantification by total RNA sequencing of clinically collected human placental samples.

PubMed

Reiman, Mario; Laan, Maris; Rull, Kristiina; Sõber, Siim

2017-08-01

RNA degradation is a ubiquitous process that occurs in living and dead cells, as well as during handling and storage of extracted RNA. Reduced RNA quality caused by degradation is an established source of uncertainty for all RNA-based gene expression quantification techniques. RNA sequencing is an increasingly preferred method for transcriptome analyses, and dependence of its results on input RNA integrity is of significant practical importance. This study aimed to characterize the effects of varying input RNA integrity [estimated as RNA integrity number (RIN)] on transcript level estimates and delineate the characteristic differences between transcripts that differ in degradation rate. The study used ribodepleted total RNA sequencing data from a real-life clinically collected set ( n = 32) of human solid tissue (placenta) samples. RIN-dependent alterations in gene expression profiles were quantified by using DESeq2 software. Our results indicate that small differences in RNA integrity affect gene expression quantification by introducing a moderate and pervasive bias in expression level estimates that significantly affected 8.1% of studied genes. The rapidly degrading transcript pool was enriched in pseudogenes, short noncoding RNAs, and transcripts with extended 3' untranslated regions. Typical slowly degrading transcripts (median length, 2389 nt) represented protein coding genes with 4-10 exons and high guanine-cytosine content.-Reiman, M., Laan, M., Rull, K., Sõber, S. Effects of RNA integrity on transcript quantification by total RNA sequencing of clinically collected human placental samples. © FASEB.

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

PubMed

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.

PubMed

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.

Unravelling the complexity of microRNA-mediated gene regulation in black pepper (Piper nigrum L.) using high-throughput small RNA profiling.

PubMed

Asha, Srinivasan; Sreekumar, Sweda; Soniya, E V

2016-01-01

Analysis of high-throughput small RNA deep sequencing data, in combination with black pepper transcriptome sequences revealed microRNA-mediated gene regulation in black pepper ( Piper nigrum L.). Black pepper is an important spice crop and its berries are used worldwide as a natural food additive that contributes unique flavour to foods. In the present study to characterize microRNAs from black pepper, we generated a small RNA library from black pepper leaf and sequenced it by Illumina high-throughput sequencing technology. MicroRNAs belonging to a total of 303 conserved miRNA families were identified from the sRNAome data. Subsequent analysis from recently sequenced black pepper transcriptome confirmed precursor sequences of 50 conserved miRNAs and four potential novel miRNA candidates. Stem-loop qRT-PCR experiments demonstrated differential expression of eight conserved miRNAs in black pepper. Computational analysis of targets of the miRNAs showed 223 potential black pepper unigene targets that encode diverse transcription factors and enzymes involved in plant development, disease resistance, metabolic and signalling pathways. RLM-RACE experiments further mapped miRNA-mediated cleavage at five of the mRNA targets. In addition, miRNA isoforms corresponding to 18 miRNA families were also identified from black pepper. This study presents the first large-scale identification of microRNAs from black pepper and provides the foundation for the future studies of miRNA-mediated gene regulation of stress responses and diverse metabolic processes in black pepper.

StructRNAfinder: an automated pipeline and web server for RNA families prediction.

PubMed

Arias-Carrasco, Raúl; Vásquez-Morán, Yessenia; Nakaya, Helder I; Maracaja-Coutinho, Vinicius

2018-02-17

The function of many noncoding RNAs (ncRNAs) depend upon their secondary structures. Over the last decades, several methodologies have been developed to predict such structures or to use them to functionally annotate RNAs into RNA families. However, to fully perform this analysis, researchers should utilize multiple tools, which require the constant parsing and processing of several intermediate files. This makes the large-scale prediction and annotation of RNAs a daunting task even to researchers with good computational or bioinformatics skills. We present an automated pipeline named StructRNAfinder that predicts and annotates RNA families in transcript or genome sequences. This single tool not only displays the sequence/structural consensus alignments for each RNA family, according to Rfam database but also provides a taxonomic overview for each assigned functional RNA. Moreover, we implemented a user-friendly web service that allows researchers to upload their own nucleotide sequences in order to perform the whole analysis. Finally, we provided a stand-alone version of StructRNAfinder to be used in large-scale projects. The tool was developed under GNU General Public License (GPLv3) and is freely available at http://structrnafinder.integrativebioinformatics.me . The main advantage of StructRNAfinder relies on the large-scale processing and integrating the data obtained by each tool and database employed along the workflow, of which several files are generated and displayed in user-friendly reports, useful for downstream analyses and data exploration.

Properties of a U1 RNA enhancer-like sequence.

PubMed Central

Ciliberto, G; Palla, F; Tebb, G; Mattaj, I W; Philipson, L

1987-01-01

The properties of a X.laevis U1B snRNA gene enhancer have been studied by microinjection in Xenopus oocytes. The enhancer-like sequence, defined as a short DNA stretch that is able to activate transcription in an orientation independent manner, is interchangeable between different U snRNA genes. The enhancer sequence alone does not, however, efficiently activate transcription from an SV40 pol II promoter but regains its activity when combined with the U-gene specific proximal sequence element. DNase I protection experiments show that the X.laevis U1B enhancer can interact specifically with a nuclear factor present in mammalian cells. Images PMID:3031597

Sequence, Structure, and Context Preferences of Human RNA Binding Proteins.

PubMed

Dominguez, Daniel; Freese, Peter; Alexis, Maria S; Su, Amanda; Hochman, Myles; Palden, Tsultrim; Bazile, Cassandra; Lambert, Nicole J; Van Nostrand, Eric L; Pratt, Gabriel A; Yeo, Gene W; Graveley, Brenton R; Burge, Christopher B

2018-06-07

RNA binding proteins (RBPs) orchestrate the production, processing, and function of mRNAs. Here, we present the affinity landscapes of 78 human RBPs using an unbiased assay that determines the sequence, structure, and context preferences of these proteins in vitro by deep sequencing of bound RNAs. These data enable construction of "RNA maps" of RBP activity without requiring crosslinking-based assays. We found an unexpectedly low diversity of RNA motifs, implying frequent convergence of binding specificity toward a relatively small set of RNA motifs, many with low compositional complexity. Offsetting this trend, however, we observed extensive preferences for contextual features distinct from short linear RNA motifs, including spaced "bipartite" motifs, biased flanking nucleotide composition, and bias away from or toward RNA structure. Our results emphasize the importance of contextual features in RNA recognition, which likely enable targeting of distinct subsets of transcripts by different RBPs that recognize the same linear motif. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

A large scale analysis of genetic variants within putative miRNA binding sites in prostate cancer

PubMed Central

Stegeman, Shane; Amankwah, Ernest; Klein, Kerenaftali; O’Mara, Tracy A.; Kim, Donghwa; Lin, Hui-Yi; Permuth-Wey, Jennifer; Sellers, Thomas A.; Srinivasan, Srilakshmi; Eeles, Rosalind; Easton, Doug; Kote-Jarai, Zsofia; Olama, Ali Amin Al; Benlloch, Sara; Muir, Kenneth; Giles, Graham G.; Wiklund, Fredrik; Gronberg, Henrik; Haiman, Christopher A.; Schleutker, Johanna; Nordestgaard, Børge G.; Travis, Ruth C.; Neal, David; Pharoah, Paul; Khaw, Kay-Tee; Stanford, Janet L.; Blot, William J.; Thibodeau, Stephen; Maier, Christiane; Kibel, Adam S.; Cybulski, Cezary; Cannon-Albright, Lisa; Brenner, Hermann; Kaneva, Radka; Teixeira, Manuel R.; Consortium, PRACTICAL; Spurdle, Amanda B.; Clements, Judith A.; Park, Jong Y.; Batra, Jyotsna

2015-01-01

Prostate cancer is the second most common malignancy among men worldwide. Genome-wide association studies (GWAS) have identified 100 risk variants for prostate cancer, which can explain ~33% of the familial risk of the disease. We hypothesized that a comprehensive analysis of genetic variations found within the 3′ UTR of genes predicted to affect miRNA binding (miRSNPs) can identify additional prostate cancer risk variants. We investigated the association between 2,169 miRSNPs and prostate cancer risk in a large-scale analysis of 22,301 cases and 22,320 controls of European ancestry from 23 participating studies. Twenty-two miRSNPs were associated (p<2.3×10−5) with risk of prostate cancer, 10 of which were within the 7 genes previously not mapped by GWASs. Further, using miRNA mimics and reporter gene assays, we showed that miR-3162-5p has specific affinity for the KLK3 rs1058205 miRSNP T-allele whilst miR-370 has greater affinity for the VAMP8 rs1010 miRSNP A-allele, validating their functional role. Significance Findings from this large association study suggest that a focus on miRSNPs, including functional evaluation, can identify candidate risk loci below currently accepted statistical levels of genome-wide significance. Studies of miRNAs and their interactions with SNPs could provide further insights into the mechanisms of prostate cancer risk. PMID:25691096

Accurate, Rapid Taxonomic Classification of Fungal Large-Subunit rRNA Genes

PubMed Central

Liu, Kuan-Liang; Porras-Alfaro, Andrea; Eichorst, Stephanie A.

2012-01-01

Taxonomic and phylogenetic fingerprinting based on sequence analysis of gene fragments from the large-subunit rRNA (LSU) gene or the internal transcribed spacer (ITS) region is becoming an integral part of fungal classification. The lack of an accurate and robust classification tool trained by a validated sequence database for taxonomic placement of fungal LSU genes is a severe limitation in taxonomic analysis of fungal isolates or large data sets obtained from environmental surveys. Using a hand-curated set of 8,506 fungal LSU gene fragments, we determined the performance characteristics of a naïve Bayesian classifier across multiple taxonomic levels and compared the classifier performance to that of a sequence similarity-based (BLASTN) approach. The naïve Bayesian classifier was computationally more rapid (>460-fold with our system) than the BLASTN approach, and it provided equal or superior classification accuracy. Classifier accuracies were compared using sequence fragments of 100 bp and 400 bp and two different PCR primer anchor points to mimic sequence read lengths commonly obtained using current high-throughput sequencing technologies. Accuracy was higher with 400-bp sequence reads than with 100-bp reads. It was also significantly affected by sequence location across the 1,400-bp test region. The highest accuracy was obtained across either the D1 or D2 variable region. The naïve Bayesian classifier provides an effective and rapid means to classify fungal LSU sequences from large environmental surveys. The training set and tool are publicly available through the Ribosomal Database Project (http://rdp.cme.msu.edu/classifier/classifier.jsp). PMID:22194300

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

PubMed Central

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

1996-01-01

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. PMID:8943327

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

PubMed

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.

Use of 16S Ribosomal RNA Sequences to Infer Relationships among Archaebacteria.

DTIC Science & Technology

1987-04-16

the rRNAs of one or both other kingdoms , and among the archaebacteria there are also substantial variations) (1), echinoderms (5, 11), major...Security Classification) Ln Use of 16S Ribosomal RNA Sequences to infer Relationships among Archaebacteria : Annual Report (U) q 12 PERSONAL AUTHOR(S...FIELD GROUP SUB-GROUP Archaebacteria ; Eubacteria; Eukaryotes; 16S Ribosomal RNA; 08 I Phylogeny; rRNA; RNA Sequencing; Molecular Clock; Urkingdoms; r

The Physcomitrella patens gene atlas project: large-scale RNA-seq based expression data.

PubMed

Perroud, Pierre-François; Haas, Fabian B; Hiss, Manuel; Ullrich, Kristian K; Alboresi, Alessandro; Amirebrahimi, Mojgan; Barry, Kerrie; Bassi, Roberto; Bonhomme, Sandrine; Chen, Haodong; Coates, Juliet C; Fujita, Tomomichi; Guyon-Debast, Anouchka; Lang, Daniel; Lin, Junyan; Lipzen, Anna; Nogué, Fabien; Oliver, Melvin J; Ponce de León, Inés; Quatrano, Ralph S; Rameau, Catherine; Reiss, Bernd; Reski, Ralf; Ricca, Mariana; Saidi, Younousse; Sun, Ning; Szövényi, Péter; Sreedasyam, Avinash; Grimwood, Jane; Stacey, Gary; Schmutz, Jeremy; Rensing, Stefan A

2018-07-01

High-throughput RNA sequencing (RNA-seq) has recently become the method of choice to define and analyze transcriptomes. For the model moss Physcomitrella patens, although this method has been used to help analyze specific perturbations, no overall reference dataset has yet been established. In the framework of the Gene Atlas project, the Joint Genome Institute selected P. patens as a flagship genome, opening the way to generate the first comprehensive transcriptome dataset for this moss. The first round of sequencing described here is composed of 99 independent libraries spanning 34 different developmental stages and conditions. Upon dataset quality control and processing through read mapping, 28 509 of the 34 361 v3.3 gene models (83%) were detected to be expressed across the samples. Differentially expressed genes (DEGs) were calculated across the dataset to permit perturbation comparisons between conditions. The analysis of the three most distinct and abundant P. patens growth stages - protonema, gametophore and sporophyte - allowed us to define both general transcriptional patterns and stage-specific transcripts. As an example of variation of physico-chemical growth conditions, we detail here the impact of ammonium supplementation under standard growth conditions on the protonemal transcriptome. Finally, the cooperative nature of this project allowed us to analyze inter-laboratory variation, as 13 different laboratories around the world provided samples. We compare differences in the replication of experiments in a single laboratory and between different laboratories. © 2018 The Authors The Plant Journal © 2018 John Wiley & Sons Ltd.

Enzymatic Synthesis of Self-assembled Dicer Substrate RNA Nanostructures for Programmable Gene Silencing.

PubMed

Jang, Bora; Kim, Boyoung; Kim, Hyunsook; Kwon, Hyokyoung; Kim, Minjeong; Seo, Yunmi; Colas, Marion; Jeong, Hansaem; Jeong, Eun Hye; Lee, Kyuri; Lee, Hyukjin

2018-06-08

Enzymatic synthesis of RNA nanostructures is achieved by isothermal rolling circle transcription (RCT). Each arm of RNA nanostructures provides a functional role of Dicer substrate RNA inducing sequence specific RNA interference (RNAi). Three different RNAi sequences (GFP, RFP, and BFP) are incorporated within the three-arm junction RNA nanostructures (Y-RNA). The template and helper DNA strands are designed for the large-scale in vitro synthesis of RNA strands to prepare self-assembled Y-RNA. Interestingly, Dicer processing of Y-RNA is highly influenced by its physical structure and different gene silencing activity is achieved depending on its arm length and overhang. In addition, enzymatic synthesis allows the preparation of various Y-RNA structures using a single DNA template offering on demand regulation of multiple target genes.

Optimized approach for Ion Proton RNA sequencing reveals details of RNA splicing and editing features of the transcriptome.

PubMed

Brown, Roger B; Madrid, Nathaniel J; Suzuki, Hideaki; Ness, Scott A

2017-01-01

RNA-sequencing (RNA-seq) has become the standard method for unbiased analysis of gene expression but also provides access to more complex transcriptome features, including alternative RNA splicing, RNA editing, and even detection of fusion transcripts formed through chromosomal translocations. However, differences in library methods can adversely affect the ability to recover these different types of transcriptome data. For example, some methods have bias for one end of transcripts or rely on low-efficiency steps that limit the complexity of the resulting library, making detection of rare transcripts less likely. We tested several commonly used methods of RNA-seq library preparation and found vast differences in the detection of advanced transcriptome features, such as alternatively spliced isoforms and RNA editing sites. By comparing several different protocols available for the Ion Proton sequencer and by utilizing detailed bioinformatics analysis tools, we were able to develop an optimized random primer based RNA-seq technique that is reliable at uncovering rare transcript isoforms and RNA editing features, as well as fusion reads from oncogenic chromosome rearrangements. The combination of optimized libraries and rapid Ion Proton sequencing provides a powerful platform for the transcriptome analysis of research and clinical samples.

Single Cell Total RNA Sequencing through Isothermal Amplification in Picoliter-Droplet Emulsion.

PubMed

Fu, Yusi; Chen, He; Liu, Lu; Huang, Yanyi

2016-11-15

Prevalent single cell RNA amplification and sequencing chemistries mainly focus on polyadenylated RNAs in eukaryotic cells by using oligo(dT) primers for reverse transcription. We develop a new RNA amplification method, "easier-seq", to reverse transcribe and amplify the total RNAs, both with and without polyadenylate tails, from a single cell for transcriptome sequencing with high efficiency, reproducibility, and accuracy. By distributing the reverse transcribed cDNA molecules into 1.5 × 10 5 aqueous droplets in oil, the cDNAs are isothermally amplified using random primers in each of these 65-pL reactors separately. This new method greatly improves the ease of single-cell RNA sequencing by reducing the experimental steps. Meanwhile, with less chance to induce errors, this method can easily maintain the quality of single-cell sequencing. In addition, this polyadenylate-tail-independent method can be seamlessly applied to prokaryotic cell RNA sequencing.

Characterization of the mammalian miRNA turnover landscape

PubMed Central

Guo, Yanwen; Liu, Jun; Elfenbein, Sarah J.; Ma, Yinghong; Zhong, Mei; Qiu, Caihong; Ding, Ye; Lu, Jun

2015-01-01

Steady state cellular microRNA (miRNA) levels represent the balance between miRNA biogenesis and turnover. The kinetics and sequence determinants of mammalian miRNA turnover during and after miRNA maturation are not fully understood. Through a large-scale study on mammalian miRNA turnover, we report the co-existence of multiple cellular miRNA pools with distinct turnover kinetics and biogenesis properties and reveal previously unrecognized sequence features for fast turnover miRNAs. We measured miRNA turnover rates in eight mammalian cell types with a combination of expression profiling and deep sequencing. While most miRNAs are stable, a subset of miRNAs, mostly miRNA*s, turnovers quickly, many of which display a two-step turnover kinetics. Moreover, different sequence isoforms of the same miRNA can possess vastly different turnover rates. Fast turnover miRNA isoforms are enriched for 5′ nucleotide bias against Argonaute-(AGO)-loading, but also additional 3′ and central sequence features. Modeling based on two fast turnover miRNA*s miR-222-5p and miR-125b-1-3p, we unexpectedly found that while both miRNA*s are associated with AGO, they strongly differ in HSP90 association and sensitivity to HSP90 inhibition. Our data characterize the landscape of genome-wide miRNA turnover in cultured mammalian cells and reveal differential HSP90 requirements for different miRNA*s. Our findings also implicate rules for designing stable small RNAs, such as siRNAs. PMID:25653157

Large-scale sequence and structural comparisons of human naive and antigen-experienced antibody repertoires

PubMed Central

DeKosky, Brandon J.; Lungu, Oana I.; Park, Daechan; Johnson, Erik L.; Charab, Wissam; Chrysostomou, Constantine; Kuroda, Daisuke; Ellington, Andrew D.; Ippolito, Gregory C.; Gray, Jeffrey J.; Georgiou, George

2016-01-01

Elucidating how antigen exposure and selection shape the human antibody repertoire is fundamental to our understanding of B-cell immunity. We sequenced the paired heavy- and light-chain variable regions (VH and VL, respectively) from large populations of single B cells combined with computational modeling of antibody structures to evaluate sequence and structural features of human antibody repertoires at unprecedented depth. Analysis of a dataset comprising 55,000 antibody clusters from CD19+CD20+CD27− IgM-naive B cells, >120,000 antibody clusters from CD19+CD20+CD27+ antigen–experienced B cells, and >2,000 RosettaAntibody-predicted structural models across three healthy donors led to a number of key findings: (i) VH and VL gene sequences pair in a combinatorial fashion without detectable pairing restrictions at the population level; (ii) certain VH:VL gene pairs were significantly enriched or depleted in the antigen-experienced repertoire relative to the naive repertoire; (iii) antigen selection increased antibody paratope net charge and solvent-accessible surface area; and (iv) public heavy-chain third complementarity-determining region (CDR-H3) antibodies in the antigen-experienced repertoire showed signs of convergent paired light-chain genetic signatures, including shared light-chain third complementarity-determining region (CDR-L3) amino acid sequences and/or Vκ,λ–Jκ,λ genes. The data reported here address several longstanding questions regarding antibody repertoire selection and development and provide a benchmark for future repertoire-scale analyses of antibody responses to vaccination and disease. PMID:27114511

Mapping the miRNA interactome by crosslinking ligation and sequencing of hybrids (CLASH)

PubMed Central

Helwak, Aleksandra; Tollervey, David

2014-01-01

RNA-RNA interactions play critical roles in many cellular processes but studying them is difficult and laborious. Here, we describe an experimental procedure, termed crosslinking ligation and sequencing of hybrids (CLASH), which allows high-throughput identification of sites of RNA-RNA interaction. During CLASH, a tagged bait protein is UV crosslinked in vivo to stabilise RNA interactions and purified under denaturing conditions. RNAs associated with the bait protein are partially truncated, and the ends of RNA-duplexes are ligated together. Following linker addition, cDNA library preparation and high-throughput sequencing, the ligated duplexes give rise to chimeric cDNAs, which unambiguously identify RNA-RNA interaction sites independent of bioinformatic predictions. This protocol is optimized for studying miRNA targets bound by Argonaute proteins, but should be easily adapted for other RNA-binding proteins and classes of RNA. The protocol requires around 5 days to complete, excluding the time required for high-throughput sequencing and bioinformatic analyses. PMID:24577361

[Influence of antisense RNA and sequences of viral transactivators traps on RNA synthesis of HTLV-1 virus].

PubMed

Borisenko, A S; Kotus, E V; Kaloshin, A A

2008-01-01

Significant number of scientific publications devoted to inhibition of viral replication by antisense RNA (asRNA) genes shows that this approach is useful for gene therapy of viral infections. To investigate the possibility of suppression of HTLV-1 virus reproduction by asRNA we constructed recombinant plasmids containing asRNA genes against U3 long terminal repeats region and X gene under the control of promoter of myeloproliferative sarcoma virus (MPSV) or without such promoter. Using stable calcium-phosphate transfection method with subsequent selection in the presence of G-418, RaHOS line-based cell clones carrying both asRNA genes and sequences able to bind HTLV-1 transactivator proteins (i.e. "traps" of viral transactivators, TVT) were obtained. Data from dot-hybridization analysis of viral RNA extracted from RaHOS cell clones showed that TVT sequences are able to suppress the viral RNA synthesis on 90% and asRNA against X gene synthesis--on 50%.

Advances in single-cell RNA sequencing and its applications in cancer research.

PubMed

Zhu, Sibo; Qing, Tao; Zheng, Yuanting; Jin, Li; Shi, Leming

2017-08-08

Unlike population-level approaches, single-cell RNA sequencing enables transcriptomic analysis of an individual cell. Through the combination of high-throughput sequencing and bioinformatic tools, single-cell RNA-seq can detect more than 10,000 transcripts in one cell to distinguish cell subsets and dynamic cellular changes. After several years' development, single-cell RNA-seq can now achieve massively parallel, full-length mRNA sequencing as well as in situ sequencing and even has potential for multi-omic detection. One appealing area of single-cell RNA-seq is cancer research, and it is regarded as a promising way to enhance prognosis and provide more precise target therapy by identifying druggable subclones. Indeed, progresses have been made regarding solid tumor analysis to reveal intratumoral heterogeneity, correlations between signaling pathways, stemness, drug resistance, and tumor architecture shaping the microenvironment. Furthermore, through investigation into circulating tumor cells, many genes have been shown to promote a propensity toward stemness and the epithelial-mesenchymal transition, to enhance anchoring and adhesion, and to be involved in mechanisms of anoikis resistance and drug resistance. This review focuses on advances and progresses of single-cell RNA-seq with regard to the following aspects: 1. Methodologies of single-cell RNA-seq 2. Single-cell isolation techniques 3. Single-cell RNA-seq in solid tumor research 4. Single-cell RNA-seq in circulating tumor cell research 5.

Advances in single-cell RNA sequencing and its applications in cancer research

PubMed Central

Zhu, Sibo; Qing, Tao; Zheng, Yuanting; Jin, Li; Shi, Leming

2017-01-01

Unlike population-level approaches, single-cell RNA sequencing enables transcriptomic analysis of an individual cell. Through the combination of high-throughput sequencing and bioinformatic tools, single-cell RNA-seq can detect more than 10,000 transcripts in one cell to distinguish cell subsets and dynamic cellular changes. After several years’ development, single-cell RNA-seq can now achieve massively parallel, full-length mRNA sequencing as well as in situ sequencing and even has potential for multi-omic detection. One appealing area of single-cell RNA-seq is cancer research, and it is regarded as a promising way to enhance prognosis and provide more precise target therapy by identifying druggable subclones. Indeed, progresses have been made regarding solid tumor analysis to reveal intratumoral heterogeneity, correlations between signaling pathways, stemness, drug resistance, and tumor architecture shaping the microenvironment. Furthermore, through investigation into circulating tumor cells, many genes have been shown to promote a propensity toward stemness and the epithelial-mesenchymal transition, to enhance anchoring and adhesion, and to be involved in mechanisms of anoikis resistance and drug resistance. This review focuses on advances and progresses of single-cell RNA-seq with regard to the following aspects: 1. Methodologies of single-cell RNA-seq 2. Single-cell isolation techniques 3. Single-cell RNA-seq in solid tumor research 4. Single-cell RNA-seq in circulating tumor cell research 5. Perspectives PMID:28881849

Transcription profile of boar spermatozoa as revealed by RNA-sequencing

USDA-ARS?s Scientific Manuscript database

High-throughput RNA sequencing (RNA-Seq) overcomes the limitations of the current hybridization-based techniques to detect the actual pool of RNA transcripts in spermatozoa. The application of this technology in livestock can speed the discovery of potential predictors of male fertility. As a first ...

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

PubMed

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.

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

PubMed Central

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.

2010-01-01

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. PMID:19926640

Deep sequencing and genome-wide analysis reveals the expansion of MicroRNA genes in the gall midge Mayetiola destructor

PubMed Central

2013-01-01

Background MicroRNAs (miRNAs) are small non-coding RNAs that play critical roles in regulating post transcriptional gene expression. Gall midges encompass a large group of insects that are of economic importance and also possess fascinating biological traits. The gall midge Mayetiola destructor, commonly known as the Hessian fly, is a destructive pest of wheat and model organism for studying gall midge biology and insect – host plant interactions. Results In this study, we systematically analyzed miRNAs from the Hessian fly. Deep-sequencing a Hessian fly larval transcriptome led to the identification of 89 miRNA species that are either identical or very similar to known miRNAs from other insects, and 184 novel miRNAs that have not been reported from other species. A genome-wide search through a draft Hessian fly genome sequence identified a total of 611 putative miRNA-encoding genes based on sequence similarity and the existence of a stem-loop structure for miRNA precursors. Analysis of the 611 putative genes revealed a striking feature: the dramatic expansion of several miRNA gene families. The largest family contained 91 genes that encoded 20 different miRNAs. Microarray analyses revealed the expression of miRNA genes was strictly regulated during Hessian fly larval development and abundance of many miRNA genes were affected by host genotypes. Conclusion The identification of a large number of miRNAs for the first time from a gall midge provides a foundation for further studies of miRNA functions in gall midge biology and behavior. The dramatic expansion of identical or similar miRNAs provides a unique system to study functional relations among miRNA iso-genes as well as changes in sequence specificity due to small changes in miRNAs and in their mRNA targets. These results may also facilitate the identification of miRNA genes for potential pest control through transgenic approaches. PMID:23496979

Quantitative Assessment of RNA-Protein Interactions with High Throughput Sequencing - RNA Affinity Profiling (HiTS-RAP)

PubMed Central

Ozer, Abdullah; Tome, Jacob M.; Friedman, Robin C.; Gheba, Dan; Schroth, Gary P.; Lis, John T.

2016-01-01

Because RNA-protein interactions play a central role in a wide-array of biological processes, methods that enable a quantitative assessment of these interactions in a high-throughput manner are in great demand. Recently, we developed the High Throughput Sequencing-RNA Affinity Profiling (HiTS-RAP) assay, which couples sequencing on an Illumina GAIIx with the quantitative assessment of one or several proteins’ interactions with millions of different RNAs in a single experiment. We have successfully used HiTS-RAP to analyze interactions of EGFP and NELF-E proteins with their corresponding canonical and mutant RNA aptamers. Here, we provide a detailed protocol for HiTS-RAP, which can be completed in about a month (8 days hands-on time) including the preparation and testing of recombinant proteins and DNA templates, clustering DNA templates on a flowcell, high-throughput sequencing and protein binding with GAIIx, and finally data analysis. We also highlight aspects of HiTS-RAP that can be further improved and points of comparison between HiTS-RAP and two other recently developed methods, RNA-MaP and RBNS. A successful HiTS-RAP experiment provides the sequence and binding curves for approximately 200 million RNAs in a single experiment. PMID:26182240

Deep sequencing and in silico analysis of small RNA library reveals novel miRNA from leaf Persicaria minor transcriptome.

PubMed

Samad, Abdul Fatah A; Nazaruddin, Nazaruddin; Murad, Abdul Munir Abdul; Jani, Jaeyres; Zainal, Zamri; Ismail, Ismanizan

2018-03-01

In current era, majority of microRNA (miRNA) are being discovered through computational approaches which are more confined towards model plants. Here, for the first time, we have described the identification and characterization of novel miRNA in a non-model plant, Persicaria minor ( P . minor ) using computational approach. Unannotated sequences from deep sequencing were analyzed based on previous well-established parameters. Around 24 putative novel miRNAs were identified from 6,417,780 reads of the unannotated sequence which represented 11 unique putative miRNA sequences. PsRobot target prediction tool was deployed to identify the target transcripts of putative novel miRNAs. Most of the predicted target transcripts (mRNAs) were known to be involved in plant development and stress responses. Gene ontology showed that majority of the putative novel miRNA targets involved in cellular component (69.07%), followed by molecular function (30.08%) and biological process (0.85%). Out of 11 unique putative miRNAs, 7 miRNAs were validated through semi-quantitative PCR. These novel miRNAs discoveries in P . minor may develop and update the current public miRNA database.

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

PubMed Central

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 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. PMID:20392818

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

PubMed

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.

The Use of Weighted Graphs for Large-Scale Genome Analysis

PubMed Central

Zhou, Fang; Toivonen, Hannu; King, Ross D.

2014-01-01

There is an acute need for better tools to extract knowledge from the growing flood of sequence data. For example, thousands of complete genomes have been sequenced, and their metabolic networks inferred. Such data should enable a better understanding of evolution. However, most existing network analysis methods are based on pair-wise comparisons, and these do not scale to thousands of genomes. Here we propose the use of weighted graphs as a data structure to enable large-scale phylogenetic analysis of networks. We have developed three types of weighted graph for enzymes: taxonomic (these summarize phylogenetic importance), isoenzymatic (these summarize enzymatic variety/redundancy), and sequence-similarity (these summarize sequence conservation); and we applied these types of weighted graph to survey prokaryotic metabolism. To demonstrate the utility of this approach we have compared and contrasted the large-scale evolution of metabolism in Archaea and Eubacteria. Our results provide evidence for limits to the contingency of evolution. PMID:24619061

Identification of extracellular miRNA in archived serum samples by next-generation sequencing from RNA extracted using multiple methods.

PubMed

Gautam, Aarti; Kumar, Raina; Dimitrov, George; Hoke, Allison; Hammamieh, Rasha; Jett, Marti

2016-10-01

miRNAs act as important regulators of gene expression by promoting mRNA degradation or by attenuating protein translation. Since miRNAs are stably expressed in bodily fluids, there is growing interest in profiling these miRNAs, as it is minimally invasive and cost-effective as a diagnostic matrix. A technical hurdle in studying miRNA dynamics is the ability to reliably extract miRNA as small sample volumes and low RNA abundance create challenges for extraction and downstream applications. The purpose of this study was to develop a pipeline for the recovery of miRNA using small volumes of archived serum samples. The RNA was extracted employing several widely utilized RNA isolation kits/methods with and without addition of a carrier. The small RNA library preparation was carried out using Illumina TruSeq small RNA kit and sequencing was carried out using Illumina platform. A fraction of five microliters of total RNA was used for library preparation as quantification is below the detection limit. We were able to profile miRNA levels in serum from all the methods tested. We found out that addition of nucleic acid based carrier molecules had higher numbers of processed reads but it did not enhance the mapping of any miRBase annotated sequences. However, some of the extraction procedures offer certain advantages: RNA extracted by TRIzol seemed to align to the miRBase best; extractions using TRIzol with carrier yielded higher miRNA-to-small RNA ratios. Nuclease free glycogen can be carrier of choice for miRNA sequencing. Our findings illustrate that miRNA extraction and quantification is influenced by the choice of methodologies. Addition of nucleic acid- based carrier molecules during extraction procedure is not a good choice when assaying miRNA using sequencing. The careful selection of an extraction method permits the archived serum samples to become valuable resources for high-throughput applications.

Large-scale benchmarking reveals false discoveries and count transformation sensitivity in 16S rRNA gene amplicon data analysis methods used in microbiome studies.

PubMed

Thorsen, Jonathan; Brejnrod, Asker; Mortensen, Martin; Rasmussen, Morten A; Stokholm, Jakob; Al-Soud, Waleed Abu; Sørensen, Søren; Bisgaard, Hans; Waage, Johannes

2016-11-25

There is an immense scientific interest in the human microbiome and its effects on human physiology, health, and disease. A common approach for examining bacterial communities is high-throughput sequencing of 16S rRNA gene hypervariable regions, aggregating sequence-similar amplicons into operational taxonomic units (OTUs). Strategies for detecting differential relative abundance of OTUs between sample conditions include classical statistical approaches as well as a plethora of newer methods, many borrowing from the related field of RNA-seq analysis. This effort is complicated by unique data characteristics, including sparsity, sequencing depth variation, and nonconformity of read counts to theoretical distributions, which is often exacerbated by exploratory and/or unbalanced study designs. Here, we assess the robustness of available methods for (1) inference in differential relative abundance analysis and (2) beta-diversity-based sample separation, using a rigorous benchmarking framework based on large clinical 16S microbiome datasets from different sources. Running more than 380,000 full differential relative abundance tests on real datasets with permuted case/control assignments and in silico-spiked OTUs, we identify large differences in method performance on a range of parameters, including false positive rates, sensitivity to sparsity and case/control balances, and spike-in retrieval rate. In large datasets, methods with the highest false positive rates also tend to have the best detection power. For beta-diversity-based sample separation, we show that library size normalization has very little effect and that the distance metric is the most important factor in terms of separation power. Our results, generalizable to datasets from different sequencing platforms, demonstrate how the choice of method considerably affects analysis outcome. Here, we give recommendations for tools that exhibit low false positive rates, have good retrieval power across effect sizes

Direct Sequence Detection of Structured H5 Influenza Viral RNA

PubMed Central

Kerby, Matthew B.; Freeman, Sarah; Prachanronarong, Kristina; Artenstein, Andrew W.; Opal, Steven M.; Tripathi, Anubhav

2008-01-01

We describe the development of sequence-specific molecular beacons (dual-labeled DNA probes) for identification of the H5 influenza subtype, cleavage motif, and receptor specificity when hybridized directly with in vitro transcribed viral RNA (vRNA). The cloned hemagglutinin segment from a highly pathogenic H5N1 strain, A/Hanoi/30408/2005(H5N1), isolated from humans was used as template for in vitro transcription of sense-strand vRNA. The hybridization behavior of vRNA and a conserved subtype probe was characterized experimentally by varying conditions of time, temperature, and Mg2+ to optimize detection. Comparison of the hybridization rates of probe to DNA and RNA targets indicates that conformational switching of influenza RNA structure is a rate-limiting step and that the secondary structure of vRNA dominates the binding kinetics. The sensitivity and specificity of probe recognition of other H5 strains was calculated from sequence matches to the National Center for Biotechnology Information influenza database. The hybridization specificity of the subtype probes was experimentally verified with point mutations within the probe loop at five locations corresponding to the other human H5 strains. The abundance frequencies of the hemagglutinin cleavage motif and sialic acid recognition sequences were experimentally tested for H5 in all host viral species. Although the detection assay must be coupled with isothermal amplification on the chip, the new probes form the basis of a portable point-of-care diagnostic device for influenza subtyping. PMID:18403607

Utility of next-generation RNA-sequencing in identifying chimeric transcription involving human endogenous retroviruses.

PubMed

Sokol, Martin; Jessen, Karen Margrethe; Pedersen, Finn Skou

2016-01-01

Several studies have shown that human endogenous retroviruses and endogenous retrovirus-like repeats (here collectively HERVs) impose direct regulation on human genes through enhancer and promoter motifs present in their long terminal repeats (LTRs). Although chimeric transcription in which novel gene isoforms containing retroviral and human sequence are transcribed from viral promoters are commonly associated with disease, regulation by HERVs is beneficial in other settings; for example, in human testis chimeric isoforms of TP63 induced by an ERV9 LTR protect the male germ line upon DNA damage by inducing apoptosis, whereas in the human globin locus the γ- and β-globin switch during normal hematopoiesis is mediated by complex interactions of an ERV9 LTR and surrounding human sequence. The advent of deep sequencing or next-generation sequencing (NGS) has revolutionized the way researchers solve important scientific questions and develop novel hypotheses in relation to human genome regulation. We recently applied next-generation paired-end RNA-sequencing (RNA-seq) together with chromatin immunoprecipitation with sequencing (ChIP-seq) to examine ERV9 chimeric transcription in human reference cell lines from Encyclopedia of DNA Elements (ENCODE). This led to the discovery of advanced regulation mechanisms by ERV9s and other HERVs across numerous human loci including transcription of large gene-unannotated genomic regions, as well as cooperative regulation by multiple HERVs and non-LTR repeats such as Alu elements. In this article, well-established examples of human gene regulation by HERVs are reviewed followed by a description of paired-end RNA-seq, and its application in identifying chimeric transcription genome-widely. Based on integrative analyses of RNA-seq and ChIP-seq, data we then present novel examples of regulation by ERV9s of tumor suppressor genes CADM2 and SEMA3A, as well as transcription of an unannotated region. Taken together, this article highlights

Understanding the Sequence Preference of Recurrent RNA Building Blocks using Quantum Chemistry: The Intrastrand RNA Dinucleotide Platform.

PubMed

Mládek, Arnošt; Sponer, Judit E; Kulhánek, Petr; Lu, Xiang-Jun; Olson, Wilma K; Sponer, Jiřĺ

2012-01-10

Folded RNA molecules are shaped by an astonishing variety of highly conserved noncanonical molecular interactions and backbone topologies. The dinucleotide platform is a widespread recurrent RNA modular building submotif formed by the side-by-side pairing of bases from two consecutive nucleotides within a single strand, with highly specific sequence preferences. This unique arrangement of bases is cemented by an intricate network of noncanonical hydrogen bonds and facilitated by a distinctive backbone topology. The present study investigates the gas-phase intrinsic stabilities of the three most common RNA dinucleotide platforms - 5'-GpU-3', ApA, and UpC - via state-of-the-art quantum-chemical (QM) techniques. The mean stability of base-base interactions decreases with sequence in the order GpU > ApA > UpC. Bader's atoms-in-molecules analysis reveals that the N2(G)…O4(U) hydrogen bond of the GpU platform is stronger than the corresponding hydrogen bonds in the other two platforms. The mixed-pucker sugar-phosphate backbone conformation found in most GpU platforms, in which the 5'-ribose sugar (G) is in the C2'-endo form and the 3'-sugar (U) in the C3'-endo form, is intrinsically more stable than the standard A-RNA backbone arrangement, partially as a result of a favorable O2'…O2P intra-platform interaction. Our results thus validate the hypothesis of Lu et al. (Lu Xiang-Jun, et al. Nucleic Acids Res. 2010, 38, 4868-4876), that the superior stability of GpU platforms is partially mediated by the strong O2'…O2P hydrogen bond. In contrast, ApA and especially UpC platform-compatible backbone conformations are rather diverse and do not display any characteristic structural features. The average stabilities of ApA and UpC derived backbone conformers are also lower than those of GpU platforms. Thus, the observed structural and evolutionary patterns of the dinucleotide platforms can be accounted for, to a large extent, by their intrinsic properties as described by

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

PubMed Central

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

The Landscape of Circular RNA Expression Profiles in Papillary Thyroid Carcinoma Based on RNA Sequencing.

PubMed

Lan, Xiabin; Xu, Jiajie; Chen, Chao; Zheng, Chuanming; Wang, Jiafeng; Cao, Jun; Zhu, Xuhang; Ge, Minghua

2018-05-25

Papillary thyroid carcinoma (PTC) is the most common type of thyroid cancer. However, the molecular mechanisms responsible for its tumorigenesis and progression remain largely unknown. Circular RNA (circRNA) is a novel type of noncoding RNA that can serve as an ideal biomarker due to its stability. Recent evidence suggests that circRNAs play important roles in tumorigenesis. This study aims to investigate circRNA expression profiles and their potential biological functions in PTC. High-throughput RNA sequencing was used to assess circRNA expression profiles in PTC, and quantitative real-time polymerase chain reaction (qRT-PCR) was used to validate dysregulated circRNAs. Receiver operating characteristic (ROC) curves were generated to evaluate the diagnostic value of circRNAs for PTC. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were employed to determine the biological functions of differentially expressed circRNAs. Bioinformatic analyses were applied to predict interactions between circRNAs and microRNAs (miRNAs), and a circRNA-miRNA-mRNA network was constructed using Cytoscape software. We identified a number of differentially expressed circRNAs in PTC tissues compared with paired normal thyroid tissues, with chr5: 160757890-160763776-, chr12: 40696591-40697936+, chr7: 22330794-22357656-, and chr21: 16386665-16415895- being upregulated, and chr7: 91924203-91957214+, chr2: 179514891-179516047-, chr9: 16435553-16437522-, and chr22: 36006931-36007153- being downregulated. These findings were confirmed by qRT-PCR, and ROC curves indicated that they can serve as potential biomarkers for PTC. GO and KEGG pathway analyses showed that some of these circRNAs are related to cancers. Additionally, bioinformatic analyses revealed a potential competing-endogenous-RNA-regulating network among circRNAs, miRNAs, and mRNAs. Our study results depict the landscape of circRNA expression profiles in PTC and also provide potential

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

PubMed

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.

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

PubMed

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.

Prediction of miRNA targets.

PubMed

Oulas, Anastasis; Karathanasis, Nestoras; Louloupi, Annita; Pavlopoulos, Georgios A; Poirazi, Panayiota; Kalantidis, Kriton; Iliopoulos, Ioannis

2015-01-01

Computational methods for miRNA target prediction are currently undergoing extensive review and evaluation. There is still a great need for improvement of these tools and bioinformatics approaches are looking towards high-throughput experiments in order to validate predictions. The combination of large-scale techniques with computational tools will not only provide greater credence to computational predictions but also lead to the better understanding of specific biological questions. Current miRNA target prediction tools utilize probabilistic learning algorithms, machine learning methods and even empirical biologically defined rules in order to build models based on experimentally verified miRNA targets. Large-scale protein downregulation assays and next-generation sequencing (NGS) are now being used to validate methodologies and compare the performance of existing tools. Tools that exhibit greater correlation between computational predictions and protein downregulation or RNA downregulation are considered the state of the art. Moreover, efficiency in prediction of miRNA targets that are concurrently verified experimentally provides additional validity to computational predictions and further highlights the competitive advantage of specific tools and their efficacy in extracting biologically significant results. In this review paper, we discuss the computational methods for miRNA target prediction and provide a detailed comparison of methodologies and features utilized by each specific tool. Moreover, we provide an overview of current state-of-the-art high-throughput methods used in miRNA target prediction.

Profiling of drought-responsive microRNA and mRNA in tomato using high-throughput sequencing.

PubMed

Liu, Minmin; Yu, Huiyang; Zhao, Gangjun; Huang, Qiufeng; Lu, Yongen; Ouyang, Bo

2017-06-26

Abiotic stresses cause severe loss of crop production. Among them, drought is one of the most frequent environmental stresses, which limits crop growth, development and productivity. Plant drought tolerance is fine-tuned by a complex gene regulatory network. Understanding the molecular regulation of this polygenic trait is crucial for the eventual success to improve plant yield and quality. Recent studies have demonstrated that microRNAs play critical roles in plant drought tolerance. However, little is known about the microRNA in drought response of the model plant tomato. Here, we described the profiling of drought-responsive microRNA and mRNA in tomato using high-throughput next-generation sequencing. Drought stress was applied on the seedlings of M82, a drought-sensitive cultivated tomato genotype, and IL9-1, a drought-tolerant introgression line derived from the stress-resistant wild species Solanum pennellii LA0716 and M82. Under drought, IL9-1 performed superior than M82 regarding survival rate, H 2 O 2 elimination and leaf turgor maintenance. A total of four small RNA and eight mRNA libraries were constructed and sequenced using Illumina sequencing technology. 105 conserved and 179 novel microRNAs were identified, among them, 54 and 98 were differentially expressed upon drought stress, respectively. The majority of the differentially-expressed conserved microRNAs was up-regulated in IL9-1 whereas down-regulated in M82. Under drought stress, 2714 and 1161 genes were found to be differentially expressed in M82 and IL9-1, respectively, and many of their homologues are involved in plant stress, such as genes encoding transcription factor and protein kinase. Various pathways involved in abiotic stress were revealed by Gene Ontology and pathway analysis. The mRNA sequencing results indicated that most of the target genes were regulated by their corresponding microRNAs, which suggested that microRNAs may play essential roles in the drought tolerance of tomato. In

Single-Cell RNA Sequencing of the Bronchial Epithelium in Smokers With Lung Cancer

DTIC Science & Technology

2015-07-01

AWARD NUMBER: W81XWH-14-1-0234 TITLE: Single-Cell RNA Sequencing of the Bronchial Epithelium in Smokers With Lung Cancer PRINCIPAL INVESTIGATOR...TITLE AND SUBTITLE Single-Cell RNA Sequencing of the Bronchial Epithelium in Smokers With Lung Cancer 5a. CONTRACT NUMBER 5b. GRANT NUMBER W81XWH...single cell RNA sequencing on airway epithelial cells obtained from smokers with and without lung cancer to identify cell-type dependent gene expression

SINA: accurate high-throughput multiple sequence alignment of ribosomal RNA genes.

PubMed

Pruesse, Elmar; Peplies, Jörg; Glöckner, Frank Oliver

2012-07-15

In the analysis of homologous sequences, computation of multiple sequence alignments (MSAs) has become a bottleneck. This is especially troublesome for marker genes like the ribosomal RNA (rRNA) where already millions of sequences are publicly available and individual studies can easily produce hundreds of thousands of new sequences. Methods have been developed to cope with such numbers, but further improvements are needed to meet accuracy requirements. In this study, we present the SILVA Incremental Aligner (SINA) used to align the rRNA gene databases provided by the SILVA ribosomal RNA project. SINA uses a combination of k-mer searching and partial order alignment (POA) to maintain very high alignment accuracy while satisfying high throughput performance demands. SINA was evaluated in comparison with the commonly used high throughput MSA programs PyNAST and mothur. The three BRAliBase III benchmark MSAs could be reproduced with 99.3, 97.6 and 96.1 accuracy. A larger benchmark MSA comprising 38 772 sequences could be reproduced with 98.9 and 99.3% accuracy using reference MSAs comprising 1000 and 5000 sequences. SINA was able to achieve higher accuracy than PyNAST and mothur in all performed benchmarks. Alignment of up to 500 sequences using the latest SILVA SSU/LSU Ref datasets as reference MSA is offered at http://www.arb-silva.de/aligner. This page also links to Linux binaries, user manual and tutorial. SINA is made available under a personal use license.

Enzymatic synthesis of random sequences of RNA and RNA analogues by DNA polymerase theta mutants for the generation of aptamer libraries.

PubMed

Randrianjatovo-Gbalou, Irina; Rosario, Sandrine; Sismeiro, Odile; Varet, Hugo; Legendre, Rachel; Coppée, Jean-Yves; Huteau, Valérie; Pochet, Sylvie; Delarue, Marc

2018-05-21

Nucleic acid aptamers, especially RNA, exhibit valuable advantages compared to protein therapeutics in terms of size, affinity and specificity. However, the synthesis of libraries of large random RNAs is still difficult and expensive. The engineering of polymerases able to directly generate these libraries has the potential to replace the chemical synthesis approach. Here, we start with a DNA polymerase that already displays a significant template-free nucleotidyltransferase activity, human DNA polymerase theta, and we mutate it based on the knowledge of its three-dimensional structure as well as previous mutational studies on members of the same polA family. One mutant exhibited a high tolerance towards ribonucleotides (NTPs) and displayed an efficient ribonucleotidyltransferase activity that resulted in the assembly of long RNA polymers. HPLC analysis and RNA sequencing of the products were used to quantify the incorporation of the four NTPs as a function of initial NTP concentrations and established the randomness of each generated nucleic acid sequence. The same mutant revealed a propensity to accept other modified nucleotides and to extend them in long fragments. Hence, this mutant can deliver random natural and modified RNA polymers libraries ready to use for SELEX, with custom lengths and balanced or unbalanced ratios.

Embedding siRNA sequences targeting Apolipoprotein B100 in shRNA and miRNA scaffolds results in differential processing and in vivo efficacy

PubMed Central

Maczuga, Piotr; Lubelski, Jacek; van Logtenstein, Richard; Borel, Florie; Blits, Bas; Fakkert, Erwin; Costessi, Adalberto; Butler, Derek; van Deventer, Sander; Petry, Harald; Koornneef, Annemart; Konstantinova, Pavlina

2013-01-01

Overexpression of short hairpin RNA (shRNA) often causes cytotoxicity and using microRNA (miRNA) scaffolds can circumvent this problem. In this study, identically predicted small interfering RNA (siRNA) sequences targeting apolipoprotein B100 (siApoB) were embedded in shRNA (shApoB) or miRNA (miApoB) scaffolds and a direct comparison of the processing and long-term in vivo efficacy was performed. Next generation sequencing of small RNAs originating from shApoB- or miApoB-transfected cells revealed substantial differences in processing, resulting in different siApoB length, 5′ and 3′ cleavage sites and abundance of the guide or passenger strands. Murine liver transduction with adeno-associated virus (AAV) vectors expressing shApoB or miApoB resulted in high levels of siApoB expression associated with strong decrease of plasma ApoB protein and cholesterol. Expression of miApoB from the liver-specific LP1 promoter was restricted to the liver, while the H1 promoter-expressed shApoB was ectopically present. Delivery of 1 × 1011 genome copies AAV-shApoB or AAV-miApoB led to a gradual loss of ApoB and plasma cholesterol inhibition, which was circumvented by delivering a 20-fold lower vector dose. In conclusion, incorporating identical siRNA sequences in shRNA or miRNA scaffolds results in differential processing patterns and in vivo efficacy that may have serious consequences for future RNAi-based therapeutics. PMID:23089734

The autism sequencing consortium: large-scale, high-throughput sequencing in autism spectrum disorders.

PubMed

Buxbaum, Joseph D; Daly, Mark J; Devlin, Bernie; Lehner, Thomas; Roeder, Kathryn; State, Matthew W

2012-12-20

Research during the past decade has seen significant progress in the understanding of the genetic architecture of autism spectrum disorders (ASDs), with gene discovery accelerating as the characterization of genomic variation has become increasingly comprehensive. At the same time, this research has highlighted ongoing challenges. Here we address the enormous impact of high-throughput sequencing (HTS) on ASD gene discovery, outline a consensus view for leveraging this technology, and describe a large multisite collaboration developed to accomplish these goals. Similar approaches could prove effective for severe neurodevelopmental disorders more broadly. Copyright © 2012 Elsevier Inc. All rights reserved.

The chemical structure of DNA sequence signals for RNA transcription

NASA Technical Reports Server (NTRS)

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.

Optimization of a novel biophysical model using large scale in vivo antisense hybridization data displays improved prediction capabilities of structurally accessible RNA regions.

PubMed

Vazquez-Anderson, Jorge; Mihailovic, Mia K; Baldridge, Kevin C; Reyes, Kristofer G; Haning, Katie; Cho, Seung Hee; Amador, Paul; Powell, Warren B; Contreras, Lydia M

2017-05-19

Current approaches to design efficient antisense RNAs (asRNAs) rely primarily on a thermodynamic understanding of RNA-RNA interactions. However, these approaches depend on structure predictions and have limited accuracy, arguably due to overlooking important cellular environment factors. In this work, we develop a biophysical model to describe asRNA-RNA hybridization that incorporates in vivo factors using large-scale experimental hybridization data for three model RNAs: a group I intron, CsrB and a tRNA. A unique element of our model is the estimation of the availability of the target region to interact with a given asRNA using a differential entropic consideration of suboptimal structures. We showcase the utility of this model by evaluating its prediction capabilities in four additional RNAs: a group II intron, Spinach II, 2-MS2 binding domain and glgC 5΄ UTR. Additionally, we demonstrate the applicability of this approach to other bacterial species by predicting sRNA-mRNA binding regions in two newly discovered, though uncharacterized, regulatory RNAs. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Nucleotide Sequence Analysis of RNA Synthesized from Rabbit Globin Complementary DNA

PubMed Central

Poon, Raymond; Paddock, Gary V.; Heindell, Howard; Whitcome, Philip; Salser, Winston; Kacian, Dan; Bank, Arthur; Gambino, Roberto; Ramirez, Francesco

1974-01-01

Rabbit globin complementary DNA made with RNA-dependent DNA polymerase (reverse transcriptase) was used as template for in vitro synthesis of 32P-labeled RNA. The sequences of the nucleotides in most of the fragments resulting from combined ribonuclease T1 and alkaline phosphatase digestion have been determined. Several fragments were long enough to fit uniquely with the α or β globin amino-acid sequences. These data demonstrate that the cDNA was copied from globin mRNA and contained no detectable contaminants. Images PMID:4139714

Developmental and Subcellular Organization of Single-Cell C₄ Photosynthesis in Bienertia sinuspersici Determined by Large-Scale Proteomics and cDNA Assembly from 454 DNA Sequencing.

PubMed

Offermann, Sascha; Friso, Giulia; Doroshenk, Kelly A; Sun, Qi; Sharpe, Richard M; Okita, Thomas W; Wimmer, Diana; Edwards, Gerald E; van Wijk, Klaas J

2015-05-01

Kranz C4 species strictly depend on separation of primary and secondary carbon fixation reactions in different cell types. In contrast, the single-cell C4 (SCC4) species Bienertia sinuspersici utilizes intracellular compartmentation including two physiologically and biochemically different chloroplast types; however, information on identity, localization, and induction of proteins required for this SCC4 system is currently very limited. In this study, we determined the distribution of photosynthesis-related proteins and the induction of the C4 system during development by label-free proteomics of subcellular fractions and leaves of different developmental stages. This was enabled by inferring a protein sequence database from 454 sequencing of Bienertia cDNAs. Large-scale proteome rearrangements were observed as C4 photosynthesis developed during leaf maturation. The proteomes of the two chloroplasts are different with differential accumulation of linear and cyclic electron transport components, primary and secondary carbon fixation reactions, and a triose-phosphate shuttle that is shared between the two chloroplast types. This differential protein distribution pattern suggests the presence of a mRNA or protein-sorting mechanism for nuclear-encoded, chloroplast-targeted proteins in SCC4 species. The combined information was used to provide a comprehensive model for NAD-ME type carbon fixation in SCC4 species.

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

PubMed

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.

On the Evolution of the Standard Genetic Code: Vestiges of Critical Scale Invariance from the RNA World in Current Prokaryote Genomes

PubMed Central

José, Marco V.; Govezensky, Tzipe; García, José A.; Bobadilla, Juan R.

2009-01-01

Herein two genetic codes from which the primeval RNA code could have originated the standard genetic code (SGC) are derived. One of them, called extended RNA code type I, consists of all codons of the type RNY (purine-any base-pyrimidine) plus codons obtained by considering the RNA code but in the second (NYR type) and third (YRN type) reading frames. The extended RNA code type II, comprises all codons of the type RNY plus codons that arise from transversions of the RNA code in the first (YNY type) and third (RNR) nucleotide bases. In order to test if putative nucleotide sequences in the RNA World and in both extended RNA codes, share the same scaling and statistical properties to those encountered in current prokaryotes, we used the genomes of four Eubacteria and three Archaeas. For each prokaryote, we obtained their respective genomes obeying the RNA code or the extended RNA codes types I and II. In each case, we estimated the scaling properties of triplet sequences via a renormalization group approach, and we calculated the frequency distributions of distances for each codon. Remarkably, the scaling properties of the distance series of some codons from the RNA code and most codons from both extended RNA codes turned out to be identical or very close to the scaling properties of codons of the SGC. To test for the robustness of these results, we show, via computer simulation experiments, that random mutations of current genomes, at the rates of 10−10 per site per year during three billions of years, were not enough for destroying the observed patterns. Therefore, we conclude that most current prokaryotes may still contain relics of the primeval RNA World and that both extended RNA codes may well represent two plausible evolutionary paths between the RNA code and the current SGC. PMID:19183813

RNA-seq analysis of Rubus idaeus cv. Nova: transcriptome sequencing and de novo assembly for subsequent functional genomics approaches.

PubMed

Hyun, Tae Kyung; Lee, Sarah; Kumar, Dhinesh; Rim, Yeonggil; Kumar, Ritesh; Lee, Sang Yeol; Lee, Choong Hwan; Kim, Jae-Yean

2014-10-01

Using Illumina sequencing technology, we have generated the large-scale transcriptome sequencing data containing abundant information on genes involved in the metabolic pathways in R. idaeus cv. Nova fruits. Rubus idaeus (Red raspberry) is one of the important economical crops that possess numerous nutrients, micronutrients and phytochemicals with essential health benefits to human. The molecular mechanism underlying the ripening process and phytochemical biosynthesis in red raspberry is attributed to the changes in gene expression, but very limited transcriptomic and genomic information in public databases is available. To address this issue, we generated more than 51 million sequencing reads from R. idaeus cv. Nova fruit using Illumina RNA-Seq technology. After de novo assembly, we obtained 42,604 unigenes with an average length of 812 bp. At the protein level, Nova fruit transcriptome showed 77 and 68 % sequence similarities with Rubus coreanus and Fragaria versa, respectively, indicating the evolutionary relationship between them. In addition, 69 % of assembled unigenes were annotated using public databases including NCBI non-redundant, Cluster of Orthologous Groups and Gene ontology database, suggesting that our transcriptome dataset provides a valuable resource for investigating metabolic processes in red raspberry. To analyze the relationship between several novel transcripts and the amounts of metabolites such as γ-aminobutyric acid and anthocyanins, real-time PCR and target metabolite analysis were performed on two different ripening stages of Nova. This is the first attempt using Illumina sequencing platform for RNA sequencing and de novo assembly of Nova fruit without reference genome. Our data provide the most comprehensive transcriptome resource available for Rubus fruits, and will be useful for understanding the ripening process and for breeding R. idaeus cultivars with improved fruit quality.

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

NASA Technical Reports Server (NTRS)

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.

Sequence-Based Prediction of RNA-Binding Residues in Proteins.

PubMed

Walia, Rasna R; El-Manzalawy, Yasser; Honavar, Vasant G; Dobbs, Drena

2017-01-01

Identifying individual residues in the interfaces of protein-RNA complexes is important for understanding the molecular determinants of protein-RNA recognition and has many potential applications. Recent technical advances have led to several high-throughput experimental methods for identifying partners in protein-RNA complexes, but determining RNA-binding residues in proteins is still expensive and time-consuming. This chapter focuses on available computational methods for identifying which amino acids in an RNA-binding protein participate directly in contacting RNA. Step-by-step protocols for using three different web-based servers to predict RNA-binding residues are described. In addition, currently available web servers and software tools for predicting RNA-binding sites, as well as databases that contain valuable information about known protein-RNA complexes, RNA-binding motifs in proteins, and protein-binding recognition sites in RNA are provided. We emphasize sequence-based methods that can reliably identify interfacial residues without the requirement for structural information regarding either the RNA-binding protein or its RNA partner.

Sequence-Based Prediction of RNA-Binding Residues in Proteins

PubMed Central

Walia, Rasna R.; EL-Manzalawy, Yasser; Honavar, Vasant G.; Dobbs, Drena

2017-01-01

Identifying individual residues in the interfaces of protein–RNA complexes is important for understanding the molecular determinants of protein–RNA recognition and has many potential applications. Recent technical advances have led to several high-throughput experimental methods for identifying partners in protein–RNA complexes, but determining RNA-binding residues in proteins is still expensive and time-consuming. This chapter focuses on available computational methods for identifying which amino acids in an RNA-binding protein participate directly in contacting RNA. Step-by-step protocols for using three different web-based servers to predict RNA-binding residues are described. In addition, currently available web servers and software tools for predicting RNA-binding sites, as well as databases that contain valuable information about known protein–RNA complexes, RNA-binding motifs in proteins, and protein-binding recognition sites in RNA are provided. We emphasize sequence-based methods that can reliably identify interfacial residues without the requirement for structural information regarding either the RNA-binding protein or its RNA partner. PMID:27787829

Small molecule alteration of RNA sequence in cells and animals.

PubMed

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.

Covariant Evolutionary Event Analysis for Base Interaction Prediction Using a Relational Database Management System for RNA.

PubMed

Xu, Weijia; Ozer, Stuart; Gutell, Robin R

2009-01-01

With an increasingly large amount of sequences properly aligned, comparative sequence analysis can accurately identify not only common structures formed by standard base pairing but also new types of structural elements and constraints. However, traditional methods are too computationally expensive to perform well on large scale alignment and less effective with the sequences from diversified phylogenetic classifications. We propose a new approach that utilizes coevolutional rates among pairs of nucleotide positions using phylogenetic and evolutionary relationships of the organisms of aligned sequences. With a novel data schema to manage relevant information within a relational database, our method, implemented with a Microsoft SQL Server 2005, showed 90% sensitivity in identifying base pair interactions among 16S ribosomal RNA sequences from Bacteria, at a scale 40 times bigger and 50% better sensitivity than a previous study. The results also indicated covariation signals for a few sets of cross-strand base stacking pairs in secondary structure helices, and other subtle constraints in the RNA structure.

Covariant Evolutionary Event Analysis for Base Interaction Prediction Using a Relational Database Management System for RNA

PubMed Central

Xu, Weijia; Ozer, Stuart; Gutell, Robin R.

2010-01-01

With an increasingly large amount of sequences properly aligned, comparative sequence analysis can accurately identify not only common structures formed by standard base pairing but also new types of structural elements and constraints. However, traditional methods are too computationally expensive to perform well on large scale alignment and less effective with the sequences from diversified phylogenetic classifications. We propose a new approach that utilizes coevolutional rates among pairs of nucleotide positions using phylogenetic and evolutionary relationships of the organisms of aligned sequences. With a novel data schema to manage relevant information within a relational database, our method, implemented with a Microsoft SQL Server 2005, showed 90% sensitivity in identifying base pair interactions among 16S ribosomal RNA sequences from Bacteria, at a scale 40 times bigger and 50% better sensitivity than a previous study. The results also indicated covariation signals for a few sets of cross-strand base stacking pairs in secondary structure helices, and other subtle constraints in the RNA structure. PMID:20502534

mRNA deep sequencing reveals 75 new genes and a complex transcriptional landscape in Mimivirus.

PubMed

Legendre, Matthieu; Audic, Stéphane; Poirot, Olivier; Hingamp, Pascal; Seltzer, Virginie; Byrne, Deborah; Lartigue, Audrey; Lescot, Magali; Bernadac, Alain; Poulain, Julie; Abergel, Chantal; Claverie, Jean-Michel

2010-05-01

Mimivirus, a virus infecting Acanthamoeba, is the prototype of the Mimiviridae, the latest addition to the nucleocytoplasmic large DNA viruses. The Mimivirus genome encodes close to 1000 proteins, many of them never before encountered in a virus, such as four amino-acyl tRNA synthetases. To explore the physiology of this exceptional virus and identify the genes involved in the building of its characteristic intracytoplasmic "virion factory," we coupled electron microscopy observations with the massively parallel pyrosequencing of the polyadenylated RNA fractions of Acanthamoeba castellanii cells at various time post-infection. We generated 633,346 reads, of which 322,904 correspond to Mimivirus transcripts. This first application of deep mRNA sequencing (454 Life Sciences [Roche] FLX) to a large DNA virus allowed the precise delineation of the 5' and 3' extremities of Mimivirus mRNAs and revealed 75 new transcripts including several noncoding RNAs. Mimivirus genes are expressed across a wide dynamic range, in a finely regulated manner broadly described by three main temporal classes: early, intermediate, and late. This RNA-seq study confirmed the AAAATTGA sequence as an early promoter element, as well as the presence of palindromes at most of the polyadenylation sites. It also revealed a new promoter element correlating with late gene expression, which is also prominent in Sputnik, the recently described Mimivirus "virophage." These results-validated genome-wide by the hybridization of total RNA extracted from infected Acanthamoeba cells on a tiling array (Agilent)--will constitute the foundation on which to build subsequent functional studies of the Mimivirus/Acanthamoeba system.

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

NASA Technical Reports Server (NTRS)

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

Integrating mRNA and protein sequencing enables the detection and quantitative profiling of natural protein sequence variants of Populus trichocarpa

DOE Office of Scientific and Technical Information (OSTI.GOV)

Abraham, Paul E.; Wang, Xiaojing; Ranjan, Priya

The availability of next-generation sequencing technologies has rapidly transformed our ability to link genotypes to phenotypes, and as such, promises to facilitate the dissection of genetic contribution to complex traits. Although discoveries of genetic associations will further our understanding of biology, once candidate variants have been identified, investigators are faced with the challenge of characterizing the functional effects on proteins encoded by such genes. Here we show how next-generation RNA sequencing data can be exploited to construct genotype-specific protein sequence databases, which provide a clearer picture of the molecular toolbox underlying cellular and organismal processes and their variation in amore » natural population. For this study, we used two individual genotypes (DENA-17-3 and VNDL-27-4) from a recent genome wide association (GWA) study of Populus trichocarpa, an obligate outcrosser that exhibits tremendous phenotypic variation across the natural population. This strategy allowed us to comprehensively catalogue proteins containing single amino acid polymorphisms (SAAPs) and insertions and deletions (INDELS). Based on large-scale identification of SAAPs, we profiled the frequency of 128 types of naturally occurring amino acid substitutions, with a subset of SAAPs occurring in regions of the genome having strong polymorphism patterns consistent with recent positive and/or divergent selection. In addition, we were able to explore the diploid landscape of Populus at the proteome-level, allowing the characterization of heterozygous variants.« less

Integrating mRNA and protein sequencing enables the detection and quantitative profiling of natural protein sequence variants of Populus trichocarpa

DOE PAGES

Abraham, Paul E.; Wang, Xiaojing; Ranjan, Priya; ...

2015-10-20

The availability of next-generation sequencing technologies has rapidly transformed our ability to link genotypes to phenotypes, and as such, promises to facilitate the dissection of genetic contribution to complex traits. Although discoveries of genetic associations will further our understanding of biology, once candidate variants have been identified, investigators are faced with the challenge of characterizing the functional effects on proteins encoded by such genes. Here we show how next-generation RNA sequencing data can be exploited to construct genotype-specific protein sequence databases, which provide a clearer picture of the molecular toolbox underlying cellular and organismal processes and their variation in amore » natural population. For this study, we used two individual genotypes (DENA-17-3 and VNDL-27-4) from a recent genome wide association (GWA) study of Populus trichocarpa, an obligate outcrosser that exhibits tremendous phenotypic variation across the natural population. This strategy allowed us to comprehensively catalogue proteins containing single amino acid polymorphisms (SAAPs) and insertions and deletions (INDELS). Based on large-scale identification of SAAPs, we profiled the frequency of 128 types of naturally occurring amino acid substitutions, with a subset of SAAPs occurring in regions of the genome having strong polymorphism patterns consistent with recent positive and/or divergent selection. In addition, we were able to explore the diploid landscape of Populus at the proteome-level, allowing the characterization of heterozygous variants.« less

Fragmentation of the large subunit ribosomal RNA gene in oyster mitochondrial genomes.

PubMed

Milbury, Coren A; Lee, Jung C; Cannone, Jamie J; Gaffney, Patrick M; Gutell, Robin R

2010-09-02

Discontinuous genes have been observed in bacteria, archaea, and eukaryotic nuclei, mitochondria and chloroplasts. Gene discontinuity occurs in multiple forms: the two most frequent forms result from introns that are spliced out of the RNA and the resulting exons are spliced together to form a single transcript, and fragmented gene transcripts that are not covalently attached post-transcriptionally. Within the past few years, fragmented ribosomal RNA (rRNA) genes have been discovered in bilateral metazoan mitochondria, all within a group of related oysters. In this study, we have characterized this fragmentation with comparative analysis and experimentation. We present secondary structures, modeled using comparative sequence analysis of the discontinuous mitochondrial large subunit rRNA genes of the cupped oysters C. virginica, C. gigas, and C. hongkongensis. Comparative structure models for the large subunit rRNA in each of the three oyster species are generally similar to those for other bilateral metazoans. We also used RT-PCR and analyzed ESTs to determine if the two fragmented LSU rRNAs are spliced together. The two segments are transcribed separately, and not spliced together although they still form functional rRNAs and ribosomes. Although many examples of discontinuous ribosomal genes have been documented in bacteria and archaea, as well as the nuclei, chloroplasts, and mitochondria of eukaryotes, oysters are some of the first characterized examples of fragmented bilateral animal mitochondrial rRNA genes. The secondary structures of the oyster LSU rRNA fragments have been predicted on the basis of previous comparative metazoan mitochondrial LSU rRNA structure models.

Toward Rare Blood Cell Preservation for RNA Sequencing.

PubMed

Vickovic, Sanja; Ahmadian, Afshin; Lewensohn, Rolf; Lundeberg, Joakim

2015-07-01

Cancer is driven by various events leading to cell differentiation and disease progression. Molecular tools are powerful approaches for describing how and why these events occur. With the growing field of next-generation DNA sequencing, there is an increasing need for high-quality nucleic acids derived from human cells and tissues-a prerequisite for successful cell profiling. Although advances in RNA preservation have been made, some of the largest biobanks still do not employ RNA blood preservation as standard because of limitations in low blood-input volume and RNA stability over the whole gene body. Therefore, we have developed a robust protocol for blood preservation and long-term storage while maintaining RNA integrity. Furthermore, we explored the possibility of using the protocol for preserving rare cell samples, such as circulating tumor cells. The results of our study confirmed that gene expression was not impacted by the preservation procedure (r(2) > 0.88) or by long-term storage (r(2) = 0.95), with RNA integrity number values averaging over 8. Similarly, cell surface antigens were still available for antibody selection (r(2) = 0.95). Lastly, data mining for fusion events showed that it was possible to detect rare tumor cells among a background of other cells present in blood irrespective of fixation. Thus, the developed protocol would be suitable for rare blood cell preservation followed by RNA sequencing analysis. Copyright © 2015 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.

Sequence specificity of the human mRNA N6-adenosine methylase in vitro.

PubMed Central

Harper, J E; Miceli, S M; Roberts, R J; Manley, J L

1990-01-01

N6-adenosine methylation is a frequent modification of mRNAs and their precursors, but little is known about the mechanism of the reaction or the function of the modification. To explore these questions, we developed conditions to examine N6-adenosine methylase activity in HeLa cell nuclear extracts. Transfer of the methyl group from S-[3H methyl]-adenosylmethionine to unlabeled random copolymer RNA substrates of varying ribonucleotide composition revealed a substrate specificity consistent with a previously deduced consensus sequence, Pu[G greater than A]AC[A/C/U]. 32-P labeled RNA substrates of defined sequence were used to examine the minimum sequence requirements for methylation. Each RNA was 20 nucleotides long, and contained either the core consensus sequence GGACU, or some variation of this sequence. RNAs containing GGACU, either in single or multiple copies, were good substrates for methylation, whereas RNAs containing single base substitutions within the GGACU sequence gave dramatically reduced methylation. These results demonstrate that the N6-adenosine methylase has a strict sequence specificity, and that there is no requirement for extended sequences or secondary structures for methylation. Recognition of this sequence does not require an RNA component, as micrococcal nuclease pretreatment of nuclear extracts actually increased methylation efficiency. Images PMID:2216767

Large-scale parallel 454 sequencing reveals host ecological group specificity of arbuscular mycorrhizal fungi in a boreonemoral forest.

PubMed

Opik, M; Metsis, M; Daniell, T J; Zobel, M; Moora, M

2009-10-01

* Knowledge of the diversity of arbuscular mycorrhizal fungi (AMF) in natural ecosystems is a major bottleneck in mycorrhizal ecology. Here, we aimed to apply 454 sequencing--providing a new level of descriptive power--to assess the AMF diversity in a boreonemoral forest. * 454 sequencing reads of the small subunit ribosomal RNA (SSU rRNA) gene of Glomeromycota were assigned to sequence groups by blast searches against a custom-made annotated sequence database. * We detected 47 AMF taxa in the roots of 10 plant species in a 10 x 10 m plot, which is almost the same as the number of plant species in the whole studied forest. There was a significant difference between AMF communities in the roots of forest specialist plant species and in the roots of habitat generalist plant species. Forest plant species hosted 22 specialist AMF taxa, and the generalist plants shared all but one AMF taxon with forest plants, including globally distributed generalist fungi. These AMF taxa that have been globally recorded only in forest ecosystems were significantly over-represented in the roots of forest plant species. * Our findings suggest that partner specificity in AM symbiosis may occur at the level of ecological groups, rather than at the species level, of both plant and fungal partners.

Large-scale analysis of intrinsic disorder flavors and associated functions in the protein sequence universe.

PubMed

Necci, Marco; Piovesan, Damiano; Tosatto, Silvio C E

2016-12-01

Intrinsic disorder (ID) in proteins has been extensively described for the last decade; a large-scale classification of ID in proteins is mostly missing. Here, we provide an extensive analysis of ID in the protein universe on the UniProt database derived from sequence-based predictions in MobiDB. Almost half the sequences contain an ID region of at least five residues. About 9% of proteins have a long ID region of over 20 residues which are more abundant in Eukaryotic organisms and most frequently cover less than 20% of the sequence. A small subset of about 67,000 (out of over 80 million) proteins is fully disordered and mostly found in Viruses. Most proteins have only one ID, with short ID evenly distributed along the sequence and long ID overrepresented in the center. The charged residue composition of Das and Pappu was used to classify ID proteins by structural propensities and corresponding functional enrichment. Swollen Coils seem to be used mainly as structural components and in biosynthesis in both Prokaryotes and Eukaryotes. In Bacteria, they are confined in the nucleoid and in Viruses provide DNA binding function. Coils & Hairpins seem to be specialized in ribosome binding and methylation activities. Globules & Tadpoles bind antigens in Eukaryotes but are involved in killing other organisms and cytolysis in Bacteria. The Undefined class is used by Bacteria to bind toxic substances and mediate transport and movement between and within organisms in Viruses. Fully disordered proteins behave similarly, but are enriched for glycine residues and extracellular structures. © 2016 The Protein Society.

The 28S–18S rDNA intergenic spacer from Crithidia fasciculata: repeated sequences, length heterogeneity, putative processing sites and potential interactions between U3 small nucleolar RNA and the ribosomal RNA precursor

PubMed Central

Schnare, Murray N.; Collings, James C.; Spencer, David F.; Gray, Michael W.

2000-01-01

In Crithidia fasciculata, the ribosomal RNA (rRNA) gene repeats range in size from ∼11 to 12 kb. This length heterogeneity is localized to a region of the intergenic spacer (IGS) that contains tandemly repeated copies of a 19mer sequence. The IGS also contains four copies of an ∼55 nt repeat that has an internal inverted repeat and is also present in the IGS of Leishmania species. We have mapped the C.fasciculata transcription initiation site as well as two other reverse transcriptase stop sites that may be analogous to the A0 and A′ pre-rRNA processing sites within the 5′ external transcribed spacer (ETS) of other eukaryotes. Features that could influence processing at these sites include two stretches of conserved primary sequence and three secondary structure elements present in the 5′ ETS. We also characterized the C.fasciculata U3 snoRNA, which has the potential for base-pairing with pre-rRNA sequences. Finally, we demonstrate that biosynthesis of large subunit rRNA in both C.fasciculata and Trypanosoma brucei involves 3′-terminal addition of three A residues that are not present in the corresponding DNA sequences. PMID:10982863

Large-scale transcriptome sequencing and gene analyses in the crab-eating macaque (Macaca fascicularis) for biomedical research

PubMed Central

2012-01-01

Background As a human replacement, the crab-eating macaque (Macaca fascicularis) is an invaluable non-human primate model for biomedical research, but the lack of genetic information on this primate has represented a significant obstacle for its broader use. Results Here, we sequenced the transcriptome of 16 tissues originated from two individuals of crab-eating macaque (male and female), and identified genes to resolve the main obstacles for understanding the biological response of the crab-eating macaque. From 4 million reads with 1.4 billion base sequences, 31,786 isotigs containing genes similar to those of humans, 12,672 novel isotigs, and 348,160 singletons were identified using the GS FLX sequencing method. Approximately 86% of human genes were represented among the genes sequenced in this study. Additionally, 175 tissue-specific transcripts were identified, 81 of which were experimentally validated. In total, 4,314 alternative splicing (AS) events were identified and analyzed. Intriguingly, 10.4% of AS events were associated with transposable element (TE) insertions. Finally, investigation of TE exonization events and evolutionary analysis were conducted, revealing interesting phenomena of human-specific amplified trends in TE exonization events. Conclusions This report represents the first large-scale transcriptome sequencing and genetic analyses of M. fascicularis and could contribute to its utility for biomedical research and basic biology. PMID:22554259

bigSCale: an analytical framework for big-scale single-cell data.

PubMed

Iacono, Giovanni; Mereu, Elisabetta; Guillaumet-Adkins, Amy; Corominas, Roser; Cuscó, Ivon; Rodríguez-Esteban, Gustavo; Gut, Marta; Pérez-Jurado, Luis Alberto; Gut, Ivo; Heyn, Holger

2018-06-01

Single-cell RNA sequencing (scRNA-seq) has significantly deepened our insights into complex tissues, with the latest techniques capable of processing tens of thousands of cells simultaneously. Analyzing increasing numbers of cells, however, generates extremely large data sets, extending processing time and challenging computing resources. Current scRNA-seq analysis tools are not designed to interrogate large data sets and often lack sensitivity to identify marker genes. With bigSCale, we provide a scalable analytical framework to analyze millions of cells, which addresses the challenges associated with large data sets. To handle the noise and sparsity of scRNA-seq data, bigSCale uses large sample sizes to estimate an accurate numerical model of noise. The framework further includes modules for differential expression analysis, cell clustering, and marker identification. A directed convolution strategy allows processing of extremely large data sets, while preserving transcript information from individual cells. We evaluated the performance of bigSCale using both a biological model of aberrant gene expression in patient-derived neuronal progenitor cells and simulated data sets, which underlines the speed and accuracy in differential expression analysis. To test its applicability for large data sets, we applied bigSCale to assess 1.3 million cells from the mouse developing forebrain. Its directed down-sampling strategy accumulates information from single cells into index cell transcriptomes, thereby defining cellular clusters with improved resolution. Accordingly, index cell clusters identified rare populations, such as reelin ( Reln )-positive Cajal-Retzius neurons, for which we report previously unrecognized heterogeneity associated with distinct differentiation stages, spatial organization, and cellular function. Together, bigSCale presents a solution to address future challenges of large single-cell data sets. © 2018 Iacono et al.; Published by Cold Spring Harbor

Gene expression distribution deconvolution in single-cell RNA sequencing.

PubMed

Wang, Jingshu; Huang, Mo; Torre, Eduardo; Dueck, Hannah; Shaffer, Sydney; Murray, John; Raj, Arjun; Li, Mingyao; Zhang, Nancy R

2018-06-26

Single-cell RNA sequencing (scRNA-seq) enables the quantification of each gene's expression distribution across cells, thus allowing the assessment of the dispersion, nonzero fraction, and other aspects of its distribution beyond the mean. These statistical characterizations of the gene expression distribution are critical for understanding expression variation and for selecting marker genes for population heterogeneity. However, scRNA-seq data are noisy, with each cell typically sequenced at low coverage, thus making it difficult to infer properties of the gene expression distribution from raw counts. Based on a reexamination of nine public datasets, we propose a simple technical noise model for scRNA-seq data with unique molecular identifiers (UMI). We develop deconvolution of single-cell expression distribution (DESCEND), a method that deconvolves the true cross-cell gene expression distribution from observed scRNA-seq counts, leading to improved estimates of properties of the distribution such as dispersion and nonzero fraction. DESCEND can adjust for cell-level covariates such as cell size, cell cycle, and batch effects. DESCEND's noise model and estimation accuracy are further evaluated through comparisons to RNA FISH data, through data splitting and simulations and through its effectiveness in removing known batch effects. We demonstrate how DESCEND can clarify and improve downstream analyses such as finding differentially expressed genes, identifying cell types, and selecting differentiation markers. Copyright © 2018 the Author(s). Published by PNAS.

The conserved CAAGAAAGA spacer sequence is an essential element for the formation of 3' termini of the sea urchin H3 histone mRNA by RNA processing.

PubMed Central

Georgiev, O; Birnstiel, M L

1985-01-01

Analysis of cDNA sequences obtained from the small nuclear RNA U7 has previously suggested specific contacts, by base pairing, between the conserved stem-loop structure and CAAGAAAGA sequence of the histone pre-mRNA and the 5'-terminal sequence of the U7 RNA during RNA processing. In order to test some aspects of the model we have created a series of linker scan, deletion and insertion mutants of the 3' terminus of a sea urchin H3 histone gene and have injected mutant DNAs or in vitro synthesized precursors into frog oocyte nuclei for interpretation. We find that, in addition to the stem-loop structure of the mRNA, the CAAGAAAGA spacer transcript within the histone pre-mRNA is required absolutely for RNA processing, as predicted from our model. Spacer sequences immediately downstream of the CAAGAAAGA motif are not complementary to U7 RNA. Nevertheless, they are necessary for obtaining a maximal rate of RNA processing, as is the ACCA sequence coding for the 3' terminus of the mature mRNA. An increase of distance between the mRNA palindrome and the CAAGAAAGA by as little as six nucleotides abolishes all processing. It may, therefore, be useful to regard both these sequence motifs as part of one and the same RNA processing signal with narrowly defined topologies. Interestingly, U7 RNA-dependent 3' processing of histone pre-mRNA can occur in RNA injection experiments only when the in vitro synthesized pre-mRNA contains sequence extensions well beyond the region of sequence complementarities to the U7 RNA. In addition to directing 3' processing the terminal mRNA sequences may have a role in histone mRNA stabilization in the cytoplasmic compartment. Images Fig. 3. Fig. 4. Fig. 5. Fig. 6. Fig. 7. PMID:2410259

CMSA: a heterogeneous CPU/GPU computing system for multiple similar RNA/DNA sequence alignment.

PubMed

Chen, Xi; Wang, Chen; Tang, Shanjiang; Yu, Ce; Zou, Quan

2017-06-24

The multiple sequence alignment (MSA) is a classic and powerful technique for sequence analysis in bioinformatics. With the rapid growth of biological datasets, MSA parallelization becomes necessary to keep its running time in an acceptable level. Although there are a lot of work on MSA problems, their approaches are either insufficient or contain some implicit assumptions that limit the generality of usage. First, the information of users' sequences, including the sizes of datasets and the lengths of sequences, can be of arbitrary values and are generally unknown before submitted, which are unfortunately ignored by previous work. Second, the center star strategy is suited for aligning similar sequences. But its first stage, center sequence selection, is highly time-consuming and requires further optimization. Moreover, given the heterogeneous CPU/GPU platform, prior studies consider the MSA parallelization on GPU devices only, making the CPUs idle during the computation. Co-run computation, however, can maximize the utilization of the computing resources by enabling the workload computation on both CPU and GPU simultaneously. This paper presents CMSA, a robust and efficient MSA system for large-scale datasets on the heterogeneous CPU/GPU platform. It performs and optimizes multiple sequence alignment automatically for users' submitted sequences without any assumptions. CMSA adopts the co-run computation model so that both CPU and GPU devices are fully utilized. Moreover, CMSA proposes an improved center star strategy that reduces the time complexity of its center sequence selection process from O(mn 2 ) to O(mn). The experimental results show that CMSA achieves an up to 11× speedup and outperforms the state-of-the-art software. CMSA focuses on the multiple similar RNA/DNA sequence alignment and proposes a novel bitmap based algorithm to improve the center star strategy. We can conclude that harvesting the high performance of modern GPU is a promising approach to

Total RNA Sequencing Analysis of DCIS Progressing to Invasive Breast Cancer

DTIC Science & Technology

2016-09-01

AWARD NUMBER: W81XWH-14-1-0080 TITLE: Total RNA Sequencing Analysis of DCIS Progressing to Invasive Breast Cancer. PRINCIPAL INVESTIGATOR...PREPARED FOR: U.S. Army Medical Research and Materiel Command Fort Detrick, Maryland 21702-5012 DISTRIBUTION STATEMENT: Approved for Public Release...SUBTITLE Total RNA Sequencing Analysis of DCIS Progressing to Invasive Breast Cancer. 5a. CONTRACT NUMBER 5b. GRANT NUMBER W81XWH-14-1-0080 GRANT11489

Integrated structural biology to unravel molecular mechanisms of protein-RNA recognition.

PubMed

Schlundt, Andreas; Tants, Jan-Niklas; Sattler, Michael

2017-04-15

Recent advances in RNA sequencing technologies have greatly expanded our knowledge of the RNA landscape in cells, often with spatiotemporal resolution. These techniques identified many new (often non-coding) RNA molecules. Large-scale studies have also discovered novel RNA binding proteins (RBPs), which exhibit single or multiple RNA binding domains (RBDs) for recognition of specific sequence or structured motifs in RNA. Starting from these large-scale approaches it is crucial to unravel the molecular principles of protein-RNA recognition in ribonucleoprotein complexes (RNPs) to understand the underlying mechanisms of gene regulation. Structural biology and biophysical studies at highest possible resolution are key to elucidate molecular mechanisms of RNA recognition by RBPs and how conformational dynamics, weak interactions and cooperative binding contribute to the formation of specific, context-dependent RNPs. While large compact RNPs can be well studied by X-ray crystallography and cryo-EM, analysis of dynamics and weak interaction necessitates the use of solution methods to capture these properties. Here, we illustrate methods to study the structure and conformational dynamics of protein-RNA complexes in solution starting from the identification of interaction partners in a given RNP. Biophysical and biochemical techniques support the characterization of a protein-RNA complex and identify regions relevant in structural analysis. Nuclear magnetic resonance (NMR) is a powerful tool to gain information on folding, stability and dynamics of RNAs and characterize RNPs in solution. It provides crucial information that is complementary to the static pictures derived from other techniques. NMR can be readily combined with other solution techniques, such as small angle X-ray and/or neutron scattering (SAXS/SANS), electron paramagnetic resonance (EPR), and Förster resonance energy transfer (FRET), which provide information about overall shapes, internal domain

Development and Verification of an RNA Sequencing (RNA-Seq) Assay for the Detection of Gene Fusions in Tumors.

PubMed

Winters, Jennifer L; Davila, Jaime I; McDonald, Amber M; Nair, Asha A; Fadra, Numrah; Wehrs, Rebecca N; Thomas, Brittany C; Balcom, Jessica R; Jin, Long; Wu, Xianglin; Voss, Jesse S; Klee, Eric W; Oliver, Gavin R; Graham, Rondell P; Neff, Jadee L; Rumilla, Kandelaria M; Aypar, Umut; Kipp, Benjamin R; Jenkins, Robert B; Jen, Jin; Halling, Kevin C

2018-06-13

We assessed the performance characteristics of an RNA sequencing (RNA-Seq) assay designed to detect gene fusions in 571 genes to help manage patients with cancer. Polyadenylated RNA was converted to cDNA, which was then used to prepare next-generation sequencing libraries that were sequenced on an Illumina HiSeq 2500 instrument and analyzed with an in-house developed bioinformatic pipeline. The assay identified 38 of 41 gene fusions detected by another method, such as fluorescence in situ hybridization or RT-PCR, for a sensitivity of 93%. No false-positive gene fusions were identified in 15 normal tissue specimens and 10 tumor specimens that were negative for fusions by RNA sequencing or Mate Pair NGS (100% specificity). The assay also identified 22 fusions in 17 tumor specimens that had not been detected by other methods. Eighteen of the 22 fusions had not previously been described. Good intra-assay and interassay reproducibility was observed with complete concordance for the presence or absence of gene fusions in replicates. The analytical sensitivity of the assay was tested by diluting RNA isolated from gene fusion-positive cases with fusion-negative RNA. Gene fusions were generally detectable down to 12.5% dilutions for most fusions and as little as 3% for some fusions. This assay can help identify fusions in patients with cancer; these patients may in turn benefit from both US Food and Drug Administration-approved and investigational targeted therapies. Copyright © 2018 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.

Genomic Sequence of the WHO International Standard for Hepatitis A Virus RNA.

PubMed

Jenkins, Adrian; Minhas, Rehan; Morris, Clare; Berry, Neil

2018-05-10

The World Health Organization (WHO) international standard for hepatitis A virus (HAV) RNA nucleic acid assays was characterized by complete genome sequencing. The entire coding sequence and noncoding regions were assigned HAV genotype IB. This information will aid the design, development, and evaluation of HAV RNA amplification assays. Copyright © 2018 Jenkins et al.

mRNA deep sequencing reveals 75 new genes and a complex transcriptional landscape in Mimivirus

PubMed Central

Legendre, Matthieu; Audic, Stéphane; Poirot, Olivier; Hingamp, Pascal; Seltzer, Virginie; Byrne, Deborah; Lartigue, Audrey; Lescot, Magali; Bernadac, Alain; Poulain, Julie; Abergel, Chantal; Claverie, Jean-Michel

2010-01-01

Mimivirus, a virus infecting Acanthamoeba, is the prototype of the Mimiviridae, the latest addition to the nucleocytoplasmic large DNA viruses. The Mimivirus genome encodes close to 1000 proteins, many of them never before encountered in a virus, such as four amino-acyl tRNA synthetases. To explore the physiology of this exceptional virus and identify the genes involved in the building of its characteristic intracytoplasmic “virion factory,” we coupled electron microscopy observations with the massively parallel pyrosequencing of the polyadenylated RNA fractions of Acanthamoeba castellanii cells at various time post-infection. We generated 633,346 reads, of which 322,904 correspond to Mimivirus transcripts. This first application of deep mRNA sequencing (454 Life Sciences [Roche] FLX) to a large DNA virus allowed the precise delineation of the 5′ and 3′ extremities of Mimivirus mRNAs and revealed 75 new transcripts including several noncoding RNAs. Mimivirus genes are expressed across a wide dynamic range, in a finely regulated manner broadly described by three main temporal classes: early, intermediate, and late. This RNA-seq study confirmed the AAAATTGA sequence as an early promoter element, as well as the presence of palindromes at most of the polyadenylation sites. It also revealed a new promoter element correlating with late gene expression, which is also prominent in Sputnik, the recently described Mimivirus “virophage.” These results—validated genome-wide by the hybridization of total RNA extracted from infected Acanthamoeba cells on a tiling array (Agilent)—will constitute the foundation on which to build subsequent functional studies of the Mimivirus/Acanthamoeba system. PMID:20360389

Avian acute leukemia viruses MC29 and MH2 share specific RNA sequences: Evidence for a second class of transforming genes

PubMed Central

Duesberg, Peter H.; Vogt, Peter K.

1979-01-01

The genome of the defective avian tumor virus MH2 was identified as a RNA of 5.7 kilobases by its presence in different MH2-helper virus complexes and its absence from pure helper virus, by its unique fingerprint pattern of RNase T1-resistant (T1) oligonucleotides that differed from those of two helper virus RNAs, and by its structural analogy to the RNA of MC29, another avian acute leukemia virus. Two sets of sequences were distinguished in MH2 RNA: 66% hybridized with DNA complementary to helper-independent avian tumor viruses, termed group-specific, and 34% were specific. The percentage of specific sequences is considered a minimal estimate because the MH2 RNA used was about 30% contaminated by helper virus RNA. No sequences related to the transforming src gene of avian sarcoma viruses were found in MH2. MH2 shared three large T1 oligonucleotides with MC29, two of which could also be isolated from a RNase A- and T1-resistant hybrid formed between MH2 RNA and MC29 specific cDNA. These oligonucleotides belong to a group of six that define the specific segment of MC29 RNA described previously. The group-specific sequences of MH2 and MC29 RNA shared only the two smallest out of about 20 T1 oligonucleotides associated with MH2 RNA. It is concluded that the specific sequences of MH2 and MC29 are related, and it is proposed that they are necessary for, or identical with, the onc genes of these viruses. These sequences would define a related class of transforming genes in avian tumor viruses that differs from the src genes of avian sarcoma viruses. Images PMID:221900

Streaming fragment assignment for real-time analysis of sequencing experiments

PubMed Central

Roberts, Adam; Pachter, Lior

2013-01-01

We present eXpress, a software package for highly efficient probabilistic assignment of ambiguously mapping sequenced fragments. eXpress uses a streaming algorithm with linear run time and constant memory use. It can determine abundances of sequenced molecules in real time, and can be applied to ChIP-seq, metagenomics and other large-scale sequencing data. We demonstrate its use on RNA-seq data, showing greater efficiency than other quantification methods. PMID:23160280

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

PubMed Central

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

2010-01-01

Rationale 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. Objective 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). Methods and Results 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 1,645 mRNAs consistently targeted to mouse cardiac RISCs. We employed 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. Conclusions 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. Summary MicroRNAs (miRs) are key regulators of mRNA translation in health and disease. While bioinformatic predictions suggest that a single miR may target hundreds of mRNAs, the number of experimentally verified targets of miRs is low. To enable comprehensive, unbiased examination of miR targets, we have performed deep RNA sequencing of cardiac transcriptomes in parallel with cardiac RNA-induced silencing complex

Sequence heterogeneity in the two 16S rRNA genes of Phormium yellow leaf phytoplasma.

PubMed Central

Liefting, L W; Andersen, M T; Beever, R E; Gardner, R C; Forster, R L

1996-01-01

Phormium yellow leaf (PYL) phytoplasma causes a lethal disease of the monocotyledon, New Zealand flax (Phormium tenax). The 16S rRNA genes of PYL phytoplasma were amplified from infected flax by PCR and cloned, and the nucleotide sequences were determined. DNA sequencing and Southern hybridization analysis of genomic DNA indicated the presence of two copies of the 16S rRNA gene. The two 16S rRNA genes exhibited sequence heterogeneity in 4 nucleotide positions and could be distinguished by the restriction enzymes BpmI and BsrI. This is the first record in which sequence heterogeneity in the 16S rRNA genes of a phytoplasma has been determined by sequence analysis. A phylogenetic tree based on 16S rRNA gene sequences showed that PYL phytoplasma is most closely related to the stolbur and German grapevine yellows phytoplasmas, which form the stolbur subgroup of the aster yellows group. This phylogenetic position of PYL phytoplasma was supported by 16S/23S spacer region sequence data. PMID:8795200

SMARTIV: combined sequence and structure de-novo motif discovery for in-vivo RNA binding data.

PubMed

Polishchuk, Maya; Paz, Inbal; Yakhini, Zohar; Mandel-Gutfreund, Yael

2018-05-25

Gene expression regulation is highly dependent on binding of RNA-binding proteins (RBPs) to their RNA targets. Growing evidence supports the notion that both RNA primary sequence and its local secondary structure play a role in specific Protein-RNA recognition and binding. Despite the great advance in high-throughput experimental methods for identifying sequence targets of RBPs, predicting the specific sequence and structure binding preferences of RBPs remains a major challenge. We present a novel webserver, SMARTIV, designed for discovering and visualizing combined RNA sequence and structure motifs from high-throughput RNA-binding data, generated from in-vivo experiments. The uniqueness of SMARTIV is that it predicts motifs from enriched k-mers that combine information from ranked RNA sequences and their predicted secondary structure, obtained using various folding methods. Consequently, SMARTIV generates Position Weight Matrices (PWMs) in a combined sequence and structure alphabet with assigned P-values. SMARTIV concisely represents the sequence and structure motif content as a single graphical logo, which is informative and easy for visual perception. SMARTIV was examined extensively on a variety of high-throughput binding experiments for RBPs from different families, generated from different technologies, showing consistent and accurate results. Finally, SMARTIV is a user-friendly webserver, highly efficient in run-time and freely accessible via http://smartiv.technion.ac.il/.

A new fungal large subunit ribosomal RNA primer for high throughput sequencing surveys

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mueller, Rebecca C.; Gallegos-Graves, La Verne; Kuske, Cheryl R.

The inclusion of phylogenetic metrics in community ecology has provided insights into important ecological processes, particularly when combined with high-throughput sequencing methods; however, these approaches have not been widely used in studies of fungal communities relative to other microbial groups. Two obstacles have been considered: (1) the internal transcribed spacer (ITS) region has limited utility for constructing phylogenies and (2) most PCR primers that target the large subunit (LSU) ribosomal unit generate amplicons that exceed current limits of high-throughput sequencing platforms. We designed and tested a PCR primer (LR22R) to target approximately 300–400 bp region of the D2 hypervariable regionmore » of the fungal LSU for use with the Illumina MiSeq platform. Both in silico and empirical analyses showed that the LR22R–LR3 pair captured a broad range of fungal taxonomic groups with a small fraction of non-fungal groups. Phylogenetic placement of publically available LSU D2 sequences showed broad agreement with taxonomic classification. Comparisons of the LSU D2 and the ITS2 ribosomal regions from environmental samples and known communities showed similar discriminatory abilities of the two primer sets. Altogether, these findings show that the LR22R–LR3 primer pair has utility for phylogenetic analyses of fungal communities using high-throughput sequencing methods.« less

A new fungal large subunit ribosomal RNA primer for high throughput sequencing surveys

DOE PAGES

Mueller, Rebecca C.; Gallegos-Graves, La Verne; Kuske, Cheryl R.

2015-12-09

The inclusion of phylogenetic metrics in community ecology has provided insights into important ecological processes, particularly when combined with high-throughput sequencing methods; however, these approaches have not been widely used in studies of fungal communities relative to other microbial groups. Two obstacles have been considered: (1) the internal transcribed spacer (ITS) region has limited utility for constructing phylogenies and (2) most PCR primers that target the large subunit (LSU) ribosomal unit generate amplicons that exceed current limits of high-throughput sequencing platforms. We designed and tested a PCR primer (LR22R) to target approximately 300–400 bp region of the D2 hypervariable regionmore » of the fungal LSU for use with the Illumina MiSeq platform. Both in silico and empirical analyses showed that the LR22R–LR3 pair captured a broad range of fungal taxonomic groups with a small fraction of non-fungal groups. Phylogenetic placement of publically available LSU D2 sequences showed broad agreement with taxonomic classification. Comparisons of the LSU D2 and the ITS2 ribosomal regions from environmental samples and known communities showed similar discriminatory abilities of the two primer sets. Altogether, these findings show that the LR22R–LR3 primer pair has utility for phylogenetic analyses of fungal communities using high-throughput sequencing methods.« less

The technology and biology of single-cell RNA sequencing.

PubMed

Kolodziejczyk, Aleksandra A; Kim, Jong Kyoung; Svensson, Valentine; Marioni, John C; Teichmann, Sarah A

2015-05-21

The differences between individual cells can have profound functional consequences, in both unicellular and multicellular organisms. Recently developed single-cell mRNA-sequencing methods enable unbiased, high-throughput, and high-resolution transcriptomic analysis of individual cells. This provides an additional dimension to transcriptomic information relative to traditional methods that profile bulk populations of cells. Already, single-cell RNA-sequencing methods have revealed new biology in terms of the composition of tissues, the dynamics of transcription, and the regulatory relationships between genes. Rapid technological developments at the level of cell capture, phenotyping, molecular biology, and bioinformatics promise an exciting future with numerous biological and medical applications. Copyright © 2015 Elsevier Inc. All rights reserved.

Statistical processing of large image sequences.

PubMed

Khellah, F; Fieguth, P; Murray, M J; Allen, M

2005-01-01

The dynamic estimation of large-scale stochastic image sequences, as frequently encountered in remote sensing, is important in a variety of scientific applications. However, the size of such images makes conventional dynamic estimation methods, for example, the Kalman and related filters, impractical. In this paper, we present an approach that emulates the Kalman filter, but with considerably reduced computational and storage requirements. Our approach is illustrated in the context of a 512 x 512 image sequence of ocean surface temperature. The static estimation step, the primary contribution here, uses a mixture of stationary models to accurately mimic the effect of a nonstationary prior, simplifying both computational complexity and modeling. Our approach provides an efficient, stable, positive-definite model which is consistent with the given correlation structure. Thus, the methods of this paper may find application in modeling and single-frame estimation.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chattopadhyay, Saket; Ely, Abdullah; Bloom, Kristie

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)more » 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.« less

A Universal Next-Generation Sequencing Protocol To Generate Noninfectious Barcoded cDNA Libraries from High-Containment RNA Viruses

PubMed Central

Moser, Lindsey A.; Ramirez-Carvajal, Lisbeth; Puri, Vinita; Pauszek, Steven J.; Matthews, Krystal; Dilley, Kari A.; Mullan, Clancy; McGraw, Jennifer; Khayat, Michael; Beeri, Karen; Yee, Anthony; Dugan, Vivien; Heise, Mark T.; Frieman, Matthew B.; Rodriguez, Luis L.; Bernard, Kristen A.; Wentworth, David E.

2016-01-01

ABSTRACT Several biosafety level 3 and/or 4 (BSL-3/4) pathogens are high-consequence, single-stranded RNA viruses, and their genomes, when introduced into permissive cells, are infectious. Moreover, many of these viruses are select agents (SAs), and their genomes are also considered SAs. For this reason, cDNAs and/or their derivatives must be tested to ensure the absence of infectious virus and/or viral RNA before transfer out of the BSL-3/4 and/or SA laboratory. This tremendously limits the capacity to conduct viral genomic research, particularly the application of next-generation sequencing (NGS). Here, we present a sequence-independent method to rapidly amplify viral genomic RNA while simultaneously abolishing both viral and genomic RNA infectivity across multiple single-stranded positive-sense RNA (ssRNA+) virus families. The process generates barcoded DNA amplicons that range in length from 300 to 1,000 bp, which cannot be used to rescue a virus and are stable to transport at room temperature. Our barcoding approach allows for up to 288 barcoded samples to be pooled into a single library and run across various NGS platforms without potential reconstitution of the viral genome. Our data demonstrate that this approach provides full-length genomic sequence information not only from high-titer virion preparations but it can also recover specific viral sequence from samples with limited starting material in the background of cellular RNA, and it can be used to identify pathogens from unknown samples. In summary, we describe a rapid, universal standard operating procedure that generates high-quality NGS libraries free of infectious virus and infectious viral RNA. IMPORTANCE This report establishes and validates a standard operating procedure (SOP) for select agents (SAs) and other biosafety level 3 and/or 4 (BSL-3/4) RNA viruses to rapidly generate noninfectious, barcoded cDNA amenable for next-generation sequencing (NGS). This eliminates the burden of testing all

Single-cell full-length total RNA sequencing uncovers dynamics of recursive splicing and enhancer RNAs.

PubMed

Hayashi, Tetsutaro; Ozaki, Haruka; Sasagawa, Yohei; Umeda, Mana; Danno, Hiroki; Nikaido, Itoshi

2018-02-12

Total RNA sequencing has been used to reveal poly(A) and non-poly(A) RNA expression, RNA processing and enhancer activity. To date, no method for full-length total RNA sequencing of single cells has been developed despite the potential of this technology for single-cell biology. Here we describe random displacement amplification sequencing (RamDA-seq), the first full-length total RNA-sequencing method for single cells. Compared with other methods, RamDA-seq shows high sensitivity to non-poly(A) RNA and near-complete full-length transcript coverage. Using RamDA-seq with differentiation time course samples of mouse embryonic stem cells, we reveal hundreds of dynamically regulated non-poly(A) transcripts, including histone transcripts and long noncoding RNA Neat1. Moreover, RamDA-seq profiles recursive splicing in >300-kb introns. RamDA-seq also detects enhancer RNAs and their cell type-specific activity in single cells. Taken together, we demonstrate that RamDA-seq could help investigate the dynamics of gene expression, RNA-processing events and transcriptional regulation in single cells.

Next-generation sequencing identifies the natural killer cell microRNA transcriptome

PubMed Central

Fehniger, Todd A.; Wylie, Todd; Germino, Elizabeth; Leong, Jeffrey W.; Magrini, Vincent J.; Koul, Sunita; Keppel, Catherine R.; Schneider, Stephanie E.; Koboldt, Daniel C.; Sullivan, Ryan P.; Heinz, Michael E.; Crosby, Seth D.; Nagarajan, Rakesh; Ramsingh, Giridharan; Link, Daniel C.; Ley, Timothy J.; Mardis, Elaine R.

2010-01-01

Natural killer (NK) cells are innate lymphocytes important for early host defense against infectious pathogens and surveillance against malignant transformation. Resting murine NK cells regulate the translation of effector molecule mRNAs (e.g., granzyme B, GzmB) through unclear molecular mechanisms. MicroRNAs (miRNAs) are small noncoding RNAs that post-transcriptionally regulate the translation of their mRNA targets, and are therefore candidates for mediating this control process. While the expression and importance of miRNAs in T and B lymphocytes have been established, little is known about miRNAs in NK cells. Here, we used two next-generation sequencing (NGS) platforms to define the miRNA transcriptomes of resting and cytokine-activated primary murine NK cells, with confirmation by quantitative real-time PCR (qRT-PCR) and microarrays. We delineate a bioinformatics analysis pipeline that identified 302 known and 21 novel mature miRNAs from sequences obtained from NK cell small RNA libraries. These miRNAs are expressed over a broad range and exhibit isomiR complexity, and a subset is differentially expressed following cytokine activation. Using these miRNA NGS data, miR-223 was identified as a mature miRNA present in resting NK cells with decreased expression following cytokine activation. Furthermore, we demonstrate that miR-223 specifically targets the 3′ untranslated region of murine GzmB in vitro, indicating that this miRNA may contribute to control of GzmB translation in resting NK cells. Thus, the sequenced NK cell miRNA transcriptome provides a valuable framework for further elucidation of miRNA expression and function in NK cell biology. PMID:20935160

The maize stripe virus major noncapsid protein messenger RNA transcripts contain heterogeneous leader sequences at their 5' termini.

PubMed

Huiet, L; Feldstein, P A; Tsai, J H; Falk, B W

1993-12-01

Primer extension analyses and a PCR-based cloning strategy were used to identify and characterize 5' nucleotide sequences on the maize stripe virus (MStV) RNA4 mRNA transcripts encoding the major noncapsid protein (NCP). Direct RNA sequence analysis by primer extension showed that the NCP mRNA transcripts had 10-15 nucleotides beyond the 5' terminus of the MStV RNA4 nucleotide sequence. MStV genomic RNAs isolated from ribonucleoprotein particles (RNPs) lacked the additional 5' nucleotides. cDNA clones representing the 5' region of the mRNA transcripts were constructed, and the nucleotide sequences of the 5' regions were determined for 16 clones. Each was found to have a distinct 10-15 nucleotide sequence immediately 5' of the MStV RNA4 sequence. Eleven of 16 clones had the correct MStV RNA4 5' nucleotide sequence, while five showed minor variations at or near the 5' most MStV RNA4 nucleotide. These characteristics show strong similarities to other viral mRNA transcripts which are synthesized by cap snatching.

CORALINA: a universal method for the generation of gRNA libraries for CRISPR-based screening.

PubMed

Köferle, Anna; Worf, Karolina; Breunig, Christopher; Baumann, Valentin; Herrero, Javier; Wiesbeck, Maximilian; Hutter, Lukas H; Götz, Magdalena; Fuchs, Christiane; Beck, Stephan; Stricker, Stefan H

2016-11-14

The bacterial CRISPR system is fast becoming the most popular genetic and epigenetic engineering tool due to its universal applicability and adaptability. The desire to deploy CRISPR-based methods in a large variety of species and contexts has created an urgent need for the development of easy, time- and cost-effective methods enabling large-scale screening approaches. Here we describe CORALINA (comprehensive gRNA library generation through controlled nuclease activity), a method for the generation of comprehensive gRNA libraries for CRISPR-based screens. CORALINA gRNA libraries can be derived from any source of DNA without the need of complex oligonucleotide synthesis. We show the utility of CORALINA for human and mouse genomic DNA, its reproducibility in covering the most relevant genomic features including regulatory, coding and non-coding sequences and confirm the functionality of CORALINA generated gRNAs. The simplicity and cost-effectiveness make CORALINA suitable for any experimental system. The unprecedented sequence complexities obtainable with CORALINA libraries are a necessary pre-requisite for less biased large scale genomic and epigenomic screens.

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

PubMed Central

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

Massively parallel rRNA gene sequencing exacerbates the potential for biased community diversity comparisons due to variable library sizes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gihring, Thomas; Green, Stefan; Schadt, Christopher Warren

2011-01-01

Technologies for massively parallel sequencing are revolutionizing microbial ecology and are vastly increasing the scale of ribosomal RNA (rRNA) gene studies. Although pyrosequencing has increased the breadth and depth of possible rRNA gene sampling, one drawback is that the number of reads obtained per sample is difficult to control. Pyrosequencing libraries typically vary widely in the number of sequences per sample, even within individual studies, and there is a need to revisit the behaviour of richness estimators and diversity indices with variable gene sequence library sizes. Multiple reports and review papers have demonstrated the bias in non-parametric richness estimators (e.g.more » Chao1 and ACE) and diversity indices when using clone libraries. However, we found that biased community comparisons are accumulating in the literature. Here we demonstrate the effects of sample size on Chao1, ACE, CatchAll, Shannon, Chao-Shen and Simpson's estimations specifically using pyrosequencing libraries. The need to equalize the number of reads being compared across libraries is reiterated, and investigators are directed towards available tools for making unbiased diversity comparisons.« less

How to design a single-cell RNA-sequencing experiment: pitfalls, challenges and perspectives.

PubMed

Dal Molin, Alessandra; Di Camillo, Barbara

2018-01-31

The sequencing of the transcriptome of single cells, or single-cell RNA-sequencing, has now become the dominant technology for the identification of novel cell types in heterogeneous cell populations or for the study of stochastic gene expression. In recent years, various experimental methods and computational tools for analysing single-cell RNA-sequencing data have been proposed. However, most of them are tailored to different experimental designs or biological questions, and in many cases, their performance has not been benchmarked yet, thus increasing the difficulty for a researcher to choose the optimal single-cell transcriptome sequencing (scRNA-seq) experiment and analysis workflow. In this review, we aim to provide an overview of the current available experimental and computational methods developed to handle single-cell RNA-sequencing data and, based on their peculiarities, we suggest possible analysis frameworks depending on specific experimental designs. Together, we propose an evaluation of challenges and open questions and future perspectives in the field. In particular, we go through the different steps of scRNA-seq experimental protocols such as cell isolation, messenger RNA capture, reverse transcription, amplification and use of quantitative standards such as spike-ins and Unique Molecular Identifiers (UMIs). We then analyse the current methodological challenges related to preprocessing, alignment, quantification, normalization, batch effect correction and methods to control for confounding effects. © The Author(s) 2018. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Optimization of a novel biophysical model using large scale in vivo antisense hybridization data displays improved prediction capabilities of structurally accessible RNA regions

PubMed Central

Vazquez-Anderson, Jorge; Mihailovic, Mia K.; Baldridge, Kevin C.; Reyes, Kristofer G.; Haning, Katie; Cho, Seung Hee; Amador, Paul; Powell, Warren B.

2017-01-01

Abstract Current approaches to design efficient antisense RNAs (asRNAs) rely primarily on a thermodynamic understanding of RNA–RNA interactions. However, these approaches depend on structure predictions and have limited accuracy, arguably due to overlooking important cellular environment factors. In this work, we develop a biophysical model to describe asRNA–RNA hybridization that incorporates in vivo factors using large-scale experimental hybridization data for three model RNAs: a group I intron, CsrB and a tRNA. A unique element of our model is the estimation of the availability of the target region to interact with a given asRNA using a differential entropic consideration of suboptimal structures. We showcase the utility of this model by evaluating its prediction capabilities in four additional RNAs: a group II intron, Spinach II, 2-MS2 binding domain and glgC 5΄ UTR. Additionally, we demonstrate the applicability of this approach to other bacterial species by predicting sRNA–mRNA binding regions in two newly discovered, though uncharacterized, regulatory RNAs. PMID:28334800

WImpiBLAST: web interface for mpiBLAST to help biologists perform large-scale annotation using high performance computing.

PubMed

Sharma, Parichit; Mantri, Shrikant S

2014-01-01

The function of a newly sequenced gene can be discovered by determining its sequence homology with known proteins. BLAST is the most extensively used sequence analysis program for sequence similarity search in large databases of sequences. With the advent of next generation sequencing technologies it has now become possible to study genes and their expression at a genome-wide scale through RNA-seq and metagenome sequencing experiments. Functional annotation of all the genes is done by sequence similarity search against multiple protein databases. This annotation task is computationally very intensive and can take days to obtain complete results. The program mpiBLAST, an open-source parallelization of BLAST that achieves superlinear speedup, can be used to accelerate large-scale annotation by using supercomputers and high performance computing (HPC) clusters. Although many parallel bioinformatics applications using the Message Passing Interface (MPI) are available in the public domain, researchers are reluctant to use them due to lack of expertise in the Linux command line and relevant programming experience. With these limitations, it becomes difficult for biologists to use mpiBLAST for accelerating annotation. No web interface is available in the open-source domain for mpiBLAST. We have developed WImpiBLAST, a user-friendly open-source web interface for parallel BLAST searches. It is implemented in Struts 1.3 using a Java backbone and runs atop the open-source Apache Tomcat Server. WImpiBLAST supports script creation and job submission features and also provides a robust job management interface for system administrators. It combines script creation and modification features with job monitoring and management through the Torque resource manager on a Linux-based HPC cluster. Use case information highlights the acceleration of annotation analysis achieved by using WImpiBLAST. Here, we describe the WImpiBLAST web interface features and architecture, explain design

WImpiBLAST: Web Interface for mpiBLAST to Help Biologists Perform Large-Scale Annotation Using High Performance Computing

PubMed Central

Sharma, Parichit; Mantri, Shrikant S.

2014-01-01

The function of a newly sequenced gene can be discovered by determining its sequence homology with known proteins. BLAST is the most extensively used sequence analysis program for sequence similarity search in large databases of sequences. With the advent of next generation sequencing technologies it has now become possible to study genes and their expression at a genome-wide scale through RNA-seq and metagenome sequencing experiments. Functional annotation of all the genes is done by sequence similarity search against multiple protein databases. This annotation task is computationally very intensive and can take days to obtain complete results. The program mpiBLAST, an open-source parallelization of BLAST that achieves superlinear speedup, can be used to accelerate large-scale annotation by using supercomputers and high performance computing (HPC) clusters. Although many parallel bioinformatics applications using the Message Passing Interface (MPI) are available in the public domain, researchers are reluctant to use them due to lack of expertise in the Linux command line and relevant programming experience. With these limitations, it becomes difficult for biologists to use mpiBLAST for accelerating annotation. No web interface is available in the open-source domain for mpiBLAST. We have developed WImpiBLAST, a user-friendly open-source web interface for parallel BLAST searches. It is implemented in Struts 1.3 using a Java backbone and runs atop the open-source Apache Tomcat Server. WImpiBLAST supports script creation and job submission features and also provides a robust job management interface for system administrators. It combines script creation and modification features with job monitoring and management through the Torque resource manager on a Linux-based HPC cluster. Use case information highlights the acceleration of annotation analysis achieved by using WImpiBLAST. Here, we describe the WImpiBLAST web interface features and architecture, explain design

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

NASA Astrophysics Data System (ADS)

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.

Evaluation of nearest-neighbor methods for detection of chimeric small-subunit rRNA sequences

NASA Technical Reports Server (NTRS)

Robison-Cox, J. F.; Bateson, M. M.; Ward, D. M.

1995-01-01

Detection of chimeric artifacts formed when PCR is used to retrieve naturally occurring small-subunit (SSU) rRNA sequences may rely on demonstrating that different sequence domains have different phylogenetic affiliations. We evaluated the CHECK_CHIMERA method of the Ribosomal Database Project and another method which we developed, both based on determining nearest neighbors of different sequence domains, for their ability to discern artificially generated SSU rRNA chimeras from authentic Ribosomal Database Project sequences. The reliability of both methods decreases when the parental sequences which contribute to chimera formation are more than 82 to 84% similar. Detection is also complicated by the occurrence of authentic SSU rRNA sequences that behave like chimeras. We developed a naive statistical test based on CHECK_CHIMERA output and used it to evaluate previously reported SSU rRNA chimeras. Application of this test also suggests that chimeras might be formed by retrieving SSU rRNAs as cDNA. The amount of uncertainty associated with nearest-neighbor analyses indicates that such tests alone are insufficient and that better methods are needed.

ModeRNA: a tool for comparative modeling of RNA 3D structure

PubMed Central

Rother, Magdalena; Rother, Kristian; Puton, Tomasz; Bujnicki, Janusz M.

2011-01-01

RNA is a large group of functionally important biomacromolecules. In striking analogy to proteins, the function of RNA depends on its structure and dynamics, which in turn is encoded in the linear sequence. However, while there are numerous methods for computational prediction of protein three-dimensional (3D) structure from sequence, with comparative modeling being the most reliable approach, there are very few such methods for RNA. Here, we present ModeRNA, a software tool for comparative modeling of RNA 3D structures. As an input, ModeRNA requires a 3D structure of a template RNA molecule, and a sequence alignment between the target to be modeled and the template. It must be emphasized that a good alignment is required for successful modeling, and for large and complex RNA molecules the development of a good alignment usually requires manual adjustments of the input data based on previous expertise of the respective RNA family. ModeRNA can model post-transcriptional modifications, a functionally important feature analogous to post-translational modifications in proteins. ModeRNA can also model DNA structures or use them as templates. It is equipped with many functions for merging fragments of different nucleic acid structures into a single model and analyzing their geometry. Windows and UNIX implementations of ModeRNA with comprehensive documentation and a tutorial are freely available. PMID:21300639

Transcriptomic Modification in the Cerebral Cortex following Noninvasive Brain Stimulation: RNA-Sequencing Approach

DTIC Science & Technology

2017-04-20

was attached to the skull in order to anchor the acrylic and maintain the integrity of the head cap. 2.3. Whole Transcriptome RNA-Sequencing...no. 12, article 550, 2014. [24] D. W. Huang, B. T. Sherman, and R. A. Lempicki, “Systematic and integrative analysis of large gene lists using DAVID...BMC Bioinformatics, vol. 9, article 559, 2008. [29] Z. Hu, E. S. Snitkin, and C. DeLisi, “VisANT: an integrative framework for networks in systems

Nested Machine Learning Facilitates Increased Sequence Content for Large-Scale Automated High Resolution Melt Genotyping

PubMed Central

Fraley, Stephanie I.; Athamanolap, Pornpat; Masek, Billie J.; Hardick, Justin; Carroll, Karen C.; Hsieh, Yu-Hsiang; Rothman, Richard E.; Gaydos, Charlotte A.; Wang, Tza-Huei; Yang, Samuel

2016-01-01

High Resolution Melt (HRM) is a versatile and rapid post-PCR DNA analysis technique primarily used to differentiate sequence variants among only a few short amplicons. We recently developed a one-vs-one support vector machine algorithm (OVO SVM) that enables the use of HRM for identifying numerous short amplicon sequences automatically and reliably. Herein, we set out to maximize the discriminating power of HRM + SVM for a single genetic locus by testing longer amplicons harboring significantly more sequence information. Using universal primers that amplify the hypervariable bacterial 16 S rRNA gene as a model system, we found that long amplicons yield more complex HRM curve shapes. We developed a novel nested OVO SVM approach to take advantage of this feature and achieved 100% accuracy in the identification of 37 clinically relevant bacteria in Leave-One-Out-Cross-Validation. A subset of organisms were independently tested. Those from pure culture were identified with high accuracy, while those tested directly from clinical blood bottles displayed more technical variability and reduced accuracy. Our findings demonstrate that long sequences can be accurately and automatically profiled by HRM with a novel nested SVM approach and suggest that clinical sample testing is feasible with further optimization. PMID:26778280

Ribosomal RNA maturation in Schizosaccharomyces pombe is dependent on a large ribonucleoprotein complex of the internal transcribed spacer 1.

PubMed

Lalev, A I; Abeyrathne, P D; Nazar, R N

2000-09-08

The interdependency of steps in the processing of pre-rRNA in Schizosaccharomyces pombe suggests that RNA processing, at least in part, acts as a quality control mechanism which helps assure that only functional RNA is incorporated into mature ribosomes. To determine further the role of the transcribed spacer regions in rRNA processing and to detect interactions which underlie the interdependencies, the ITS1 sequence was examined for its ability to form ribonucleoprotein complexes with cellular proteins. When incubated with protein extract, the spacer formed a specific large RNP. This complex was stable to fractionation by agarose or polyacrylamide gel electrophoresis. Modification exclusion analyses indicated that the proteins interact with a helical domain which is conserved in the internal transcribed spacers. Mutagenic analyses confirmed an interaction with this sequence and indicated that this domain is critical to the efficient maturation of the precursor RNA. The protein constituents, purified by affinity chromatography using the ITS1 sequence, retained an ability to form stable RNP. Protein analyses of gel purified complex, prepared with affinity-purified proteins, indicated at least 20 protein components ranging in size from 20-200 kDa. Peptide mapping by Maldi-Toff mass spectroscopy identified eight hypothetical RNA binding proteins which included four different RNA-binding motifs. Another protein was putatively identified as a pseudouridylate synthase. Additional RNA constituents were not detected. The significance of this complex with respect to rRNA maturation and interdependence in rRNA processing is discussed. Copyright 2000 Academic Press.

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

PubMed

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

The RNase P RNA from cyanobacteria: short tandemly repeated repetitive (STRR) sequences are present within the RNase P RNA gene in heterocyst-forming cyanobacteria.

PubMed Central

Vioque, A

1997-01-01

The RNase P RNA gene (rnpB) from 10 cyanobacteria has been characterized. These new RNAs, together with the previously available ones, provide a comprehensive data set of RNase P RNA from diverse cyanobacterial lineages. All heterocystous cyanobacteria, but none of the non-heterocystous strains analyzed, contain short tandemly repeated repetitive (STRR) sequences that increase the length of helix P12. Site-directed mutagenesis experiments indicate that the STRR sequences are not required for catalytic activity in vitro. STRR sequences seem to have recently and independently invaded the RNase P RNA genes in heterocyst-forming cyanobacteria because closely related strains contain unrelated STRR sequences. Most cyanobacteria RNase P RNAs lack the sequence GGU in the loop connecting helices P15 and P16 that has been established to interact with the 3'-end CCA in precursor tRNA substrates in other bacteria. This character is shared with plastid RNase P RNA. Helix P6 is longer than usual in most cyanobacteria as well as in plastid RNase P RNA. PMID:9254706

Structural Requirement in Clostridium perfringens Collagenase mRNA 5′ Leader Sequence for Translational Induction through Small RNA-mRNA Base Pairing

PubMed Central

Nomura, Nobuhiko; Nakamura, Kouji

2013-01-01

The Gram-positive anaerobic bacterium Clostridium perfringens is pathogenic to humans and animals, and the production of its toxins is strictly regulated during the exponential phase. We recently found that the 5′ leader sequence of the colA transcript encoding collagenase, which is a major toxin of this organism, is processed and stabilized in the presence of the small RNA VR-RNA. The primary colA 5′-untranslated region (5′UTR) forms a long stem-loop structure containing an internal bulge and masks its own ribosomal binding site. Here we found that VR-RNA directly regulates colA expression through base pairing with colA mRNA in vivo. However, when the internal bulge structure was closed by point mutations in colA mRNA, translation ceased despite the presence of VR-RNA. In addition, a mutation disrupting the colA stem-loop structure induced mRNA processing and ColA-FLAG translational activation in the absence of VR-RNA, indicating that the stem-loop and internal bulge structure of the colA 5′ leader sequence is important for regulation by VR-RNA. On the other hand, processing was required for maximal ColA expression but was not essential for VR-RNA-dependent colA regulation. Finally, colA processing and translational activation were induced at a high temperature without VR-RNA. These results suggest that inhibition of the colA 5′ leader structure through base pairing is the primary role of VR-RNA in colA regulation and that the colA 5′ leader structure is a possible thermosensor. PMID:23585542

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

PubMed

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

RNA-Catalyzed RNA Ligation on an External RNA Template

NASA Technical Reports Server (NTRS)

McGinness, Kathleen E.; Joyce, Gerald F.

2002-01-01

Variants of the hc ligase ribozyme, which catalyzes ligation of the 3' end of an RNA substrate to the 5' end of the ribozyme, were utilized to evolve a ribozyme that catalyzes ligation reactions on an external RNA template. The evolved ribozyme catalyzes the joining of an oligonucleotide 3'-hydroxyl to the 5'-triphosphate of an RNA hairpin molecule. The ribozyme can also utilize various substrate sequences, demonstrating a largely sequence-independent mechanism for substrate recognition. The ribozyme also carries out the ligation of two oligonucleotides that are bound at adjacent positions on a complementary template. Finally, it catalyzes addition of mononucleoside '5-triphosphates onto the '3 end of an oligonucleotide primer in a template-dependent manner. The development of ribozymes that catalyze polymerase-type reactions contributes to the notion that an RNA world could have existed during the early history of life on Earth.

Efficient computation of optimal oligo-RNA binding.

PubMed

Hodas, Nathan O; Aalberts, Daniel P

2004-01-01

We present an algorithm that calculates the optimal binding conformation and free energy of two RNA molecules, one or both oligomeric. This algorithm has applications to modeling DNA microarrays, RNA splice-site recognitions and other antisense problems. Although other recent algorithms perform the same calculation in time proportional to the sum of the lengths cubed, O((N1 + N2)3), our oligomer binding algorithm, called bindigo, scales as the product of the sequence lengths, O(N1*N2). The algorithm performs well in practice with the aid of a heuristic for large asymmetric loops. To demonstrate its speed and utility, we use bindigo to investigate the binding proclivities of U1 snRNA to mRNA donor splice sites.

DNA interrogation by the CRISPR RNA-guided endonuclease Cas9.

PubMed

Sternberg, Samuel H; Redding, Sy; Jinek, Martin; Greene, Eric C; Doudna, Jennifer A

2014-03-06

The clustered regularly interspaced short palindromic repeats (CRISPR)-associated enzyme Cas9 is an RNA-guided endonuclease that uses RNA-DNA base-pairing to target foreign DNA in bacteria. Cas9-guide RNA complexes are also effective genome engineering agents in animals and plants. Here we use single-molecule and bulk biochemical experiments to determine how Cas9-RNA interrogates DNA to find specific cleavage sites. We show that both binding and cleavage of DNA by Cas9-RNA require recognition of a short trinucleotide protospacer adjacent motif (PAM). Non-target DNA binding affinity scales with PAM density, and sequences fully complementary to the guide RNA but lacking a nearby PAM are ignored by Cas9-RNA. Competition assays provide evidence that DNA strand separation and RNA-DNA heteroduplex formation initiate at the PAM and proceed directionally towards the distal end of the target sequence. Furthermore, PAM interactions trigger Cas9 catalytic activity. These results reveal how Cas9 uses PAM recognition to quickly identify potential target sites while scanning large DNA molecules, and to regulate scission of double-stranded DNA.

DNA interrogation by the CRISPR RNA-guided endonuclease Cas9

NASA Astrophysics Data System (ADS)

Sternberg, Samuel H.; Redding, Sy; Jinek, Martin; Greene, Eric C.; Doudna, Jennifer A.

2014-03-01

The clustered regularly interspaced short palindromic repeats (CRISPR)-associated enzyme Cas9 is an RNA-guided endonuclease that uses RNA-DNA base-pairing to target foreign DNA in bacteria. Cas9-guide RNA complexes are also effective genome engineering agents in animals and plants. Here we use single-molecule and bulk biochemical experiments to determine how Cas9-RNA interrogates DNA to find specific cleavage sites. We show that both binding and cleavage of DNA by Cas9-RNA require recognition of a short trinucleotide protospacer adjacent motif (PAM). Non-target DNA binding affinity scales with PAM density, and sequences fully complementary to the guide RNA but lacking a nearby PAM are ignored by Cas9-RNA. Competition assays provide evidence that DNA strand separation and RNA-DNA heteroduplex formation initiate at the PAM and proceed directionally towards the distal end of the target sequence. Furthermore, PAM interactions trigger Cas9 catalytic activity. These results reveal how Cas9 uses PAM recognition to quickly identify potential target sites while scanning large DNA molecules, and to regulate scission of double-stranded DNA.

HAlign-II: efficient ultra-large multiple sequence alignment and phylogenetic tree reconstruction with distributed and parallel computing.

PubMed

Wan, Shixiang; Zou, Quan

2017-01-01

Multiple sequence alignment (MSA) plays a key role in biological sequence analyses, especially in phylogenetic tree construction. Extreme increase in next-generation sequencing results in shortage of efficient ultra-large biological sequence alignment approaches for coping with different sequence types. Distributed and parallel computing represents a crucial technique for accelerating ultra-large (e.g. files more than 1 GB) sequence analyses. Based on HAlign and Spark distributed computing system, we implement a highly cost-efficient and time-efficient HAlign-II tool to address ultra-large multiple biological sequence alignment and phylogenetic tree construction. The experiments in the DNA and protein large scale data sets, which are more than 1GB files, showed that HAlign II could save time and space. It outperformed the current software tools. HAlign-II can efficiently carry out MSA and construct phylogenetic trees with ultra-large numbers of biological sequences. HAlign-II shows extremely high memory efficiency and scales well with increases in computing resource. THAlign-II provides a user-friendly web server based on our distributed computing infrastructure. HAlign-II with open-source codes and datasets was established at http://lab.malab.cn/soft/halign.

JingleBells: A Repository of Immune-Related Single-Cell RNA-Sequencing Datasets.

PubMed

Ner-Gaon, Hadas; Melchior, Ariel; Golan, Nili; Ben-Haim, Yael; Shay, Tal

2017-05-01

Recent advances in single-cell RNA-sequencing (scRNA-seq) technology increase the understanding of immune differentiation and activation processes, as well as the heterogeneity of immune cell types. Although the number of available immune-related scRNA-seq datasets increases rapidly, their large size and various formats render them hard for the wider immunology community to use, and read-level data are practically inaccessible to the non-computational immunologist. To facilitate datasets reuse, we created the JingleBells repository for immune-related scRNA-seq datasets ready for analysis and visualization of reads at the single-cell level (http://jinglebells.bgu.ac.il/). To this end, we collected the raw data of publicly available immune-related scRNA-seq datasets, aligned the reads to the relevant genome, and saved aligned reads in a uniform format, annotated for cell of origin. We also added scripts and a step-by-step tutorial for visualizing each dataset at the single-cell level, through the commonly used Integrated Genome Viewer (www.broadinstitute.org/igv/). The uniform scRNA-seq format used in JingleBells can facilitate reuse of scRNA-seq data by computational biologists. It also enables immunologists who are interested in a specific gene to visualize the reads aligned to this gene to estimate cell-specific preferences for splicing, mutation load, or alleles. Thus JingleBells is a resource that will extend the usefulness of scRNA-seq datasets outside the programming aficionado realm. Copyright © 2017 by The American Association of Immunologists, Inc.

Single-Cell RNA Sequencing of Glioblastoma Cells.

PubMed

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.

tRNADB-CE: tRNA gene database well-timed in the era of big sequence data.

PubMed

Abe, Takashi; Inokuchi, Hachiro; Yamada, Yuko; Muto, Akira; Iwasaki, Yuki; Ikemura, Toshimichi

2014-01-01

The tRNA gene data base curated by experts "tRNADB-CE" (http://trna.ie.niigata-u.ac.jp) was constructed by analyzing 1,966 complete and 5,272 draft genomes of prokaryotes, 171 viruses', 121 chloroplasts', and 12 eukaryotes' genomes plus fragment sequences obtained by metagenome studies of environmental samples. 595,115 tRNA genes in total, and thus two times of genes compiled previously, have been registered, for which sequence, clover-leaf structure, and results of sequence-similarity and oligonucleotide-pattern searches can be browsed. To provide collective knowledge with help from experts in tRNA researches, we added a column for enregistering comments to each tRNA. By grouping bacterial tRNAs with an identical sequence, we have found high phylogenetic preservation of tRNA sequences, especially at the phylum level. Since many species-unknown tRNAs from metagenomic sequences have sequences identical to those found in species-known prokaryotes, the identical sequence group (ISG) can provide phylogenetic markers to investigate the microbial community in an environmental ecosystem. This strategy can be applied to a huge amount of short sequences obtained from next-generation sequencers, as showing that tRNADB-CE is a well-timed database in the era of big sequence data. It is also discussed that batch-learning self-organizing-map with oligonucleotide composition is useful for efficient knowledge discovery from big sequence data.

Reanalysis of RNA-Sequencing Data Reveals Several Additional Fusion Genes with Multiple Isoforms

PubMed Central

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. PMID:23119097

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

PubMed

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.

Complete nucleotide sequences and genome characterization of a novel double-stranded RNA virus infecting Rosa multiflora.

PubMed

Salem, Nidá M; Golino, Deborah A; Falk, Bryce W; Rowhani, Adib

2008-01-01

The three double-stranded (ds) RNAs were detected in Rosa multiflora plants showing rose spring dwarf (RSD) symptoms. Northern blot analysis revealed three dsRNAs in preparations of both dsRNA and total RNA from R. multiflora plants. The complete sequences of the dsRNAs (referred to as dsRNA 1, dsRNA 2 and dsRNA 3) were determined based on a combination of shotgun cloning of dsRNA cDNAs and reverse transcription-polymerase chain reaction (RT-PCR). The largest dsRNA (dsRNA 1) was 1,762 bp long with a single open reading frame (ORF) that encoded a putative polypeptide containing 479 amino acid residues with a molecular mass of 55.9 kDa. This polypeptide contains amino acid sequence motifs conserved in the RNA-dependent RNA polymerases (RdRp) of members of the family Partitiviridae. Both dsRNA 2 (1,475 bp) and dsRNA 3 (1,384 bp) contained single ORFs, encoding putative proteins of unknown function. The 5' untranslated regions (UTR) of all three segments shared regions of high sequence homology. Phylogenetic analysis using the RdRp sequences of the various partitiviruses revealed that the new sequences would constitute the genome of a virus in family Partitiviridae. This virus would cluster with Fragaria chiloensis cryptic virus and Raphanus sativus cryptic virus 2. We suggest that the three dsRNA segments constitute the genome of a novel cryptic virus infecting roses; we propose the name Rosa multiflora cryptic virus (RMCV). Detection primers were developed and used for RT-PCR detection of RMCV in rose plants.

Genome-wide evidence for local DNA methylation spreading from small RNA-targeted sequences in Arabidopsis.

PubMed

Ahmed, Ikhlak; Sarazin, Alexis; Bowler, Chris; Colot, Vincent; Quesneville, Hadi

2011-09-01

Transposable elements (TEs) and their relics play major roles in genome evolution. However, mobilization of TEs is usually deleterious and strongly repressed. In plants and mammals, this repression is typically associated with DNA methylation, but the relationship between this epigenetic mark and TE sequences has not been investigated systematically. Here, we present an improved annotation of TE sequences and use it to analyze genome-wide DNA methylation maps obtained at single-nucleotide resolution in Arabidopsis. We show that although the majority of TE sequences are methylated, ∼26% are not. Moreover, a significant fraction of TE sequences densely methylated at CG, CHG and CHH sites (where H = A, T or C) have no or few matching small interfering RNA (siRNAs) and are therefore unlikely to be targeted by the RNA-directed DNA methylation (RdDM) machinery. We provide evidence that these TE sequences acquire DNA methylation through spreading from adjacent siRNA-targeted regions. Further, we show that although both methylated and unmethylated TE sequences located in euchromatin tend to be more abundant closer to genes, this trend is least pronounced for methylated, siRNA-targeted TE sequences located 5' to genes. Based on these and other findings, we propose that spreading of DNA methylation through promoter regions explains at least in part the negative impact of siRNA-targeted TE sequences on neighboring gene expression.

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

PubMed

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

RNA sequencing confirms similarities between PPI-responsive oesophageal eosinophilia and eosinophilic oesophagitis.

PubMed

Peterson, K A; Yoshigi, M; Hazel, M W; Delker, D A; Lin, E; Krishnamurthy, C; Consiglio, N; Robson, J; Yandell, M; Clayton, F

2018-06-04

Although current American guidelines distinguish proton pump inhibitor-responsive oesophageal eosinophilia (PPI-REE) from eosinophilic oesophagitis (EoE), these entities are broadly similar. While two microarray studies showed that they have similar transcriptomes, more extensive RNA sequencing studies have not been done previously. To determine whether RNA sequencing identifies genetic markers distinguishing PPI-REE from EoE. We retrospectively examined 13 PPI-REE and 14 EoE biopsies, matched for tissue eosinophil content, and 14 normal controls. Patients and controls were not PPI-treated at the time of biopsy. We did RNA sequencing on formalin-fixed, paraffin-embedded tissue, with differential expression confirmation by quantitative polymerase chain reaction (PCR). We validated the use of formalin-fixed, paraffin-embedded vs RNAlater-preserved tissue, and compared our formalin-fixed, paraffin-embedded EoE results to a prior EoE study. By RNA sequencing, no genes were differentially expressed between the EoE and PPI-REE groups at the false discovery rate (FDR) ≤0.01 level. Compared to normal controls, 1996 genes were differentially expressed in the PPI-REE group and 1306 genes in the EoE group. By less stringent criteria, only MAPK8IP2 was differentially expressed between PPI-REE and EoE (FDR = 0.029, 2.2-fold less in EoE than in PPI-REE), with similar results by PCR. KCNJ2, which was differentially expressed in a prior study, was similar in the EoE and PPI-REE groups by both RNA sequencing and real-time PCR. Eosinophilic oesophagitis and PPI-REE have comparable transcriptomes, confirming that they are part of the same disease continuum. © 2018 John Wiley & Sons Ltd.

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

PubMed Central

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

A large microRNA cluster on chromosome 19 is a transcriptional hallmark of WHO type A and AB thymomas.

PubMed

Radovich, Milan; Solzak, Jeffrey P; Hancock, Bradley A; Conces, Madison L; Atale, Rutuja; Porter, Ryan F; Zhu, Jin; Glasscock, Jarret; Kesler, Kenneth A; Badve, Sunil S; Schneider, Bryan P; Loehrer, Patrick J

2016-02-16

Thymomas are one of the most rarely diagnosed malignancies. To better understand its biology and to identify therapeutic targets, we performed next-generation RNA sequencing. The RNA was sequenced from 13 thymic malignancies and 3 normal thymus glands. Validation of microRNA expression was performed on a separate set of 35 thymic malignancies. For cell-based studies, a thymoma cell line was used. Hierarchical clustering revealed 100% concordance between gene expression clusters and WHO subtype. A substantial differentiator was a large microRNA cluster on chr19q13.42 that was significantly overexpressed in all A and AB tumours and whose expression was virtually absent in the other thymomas and normal tissues. Overexpression of this microRNA cluster activates the PI3K/AKT/mTOR pathway. Treatment of a thymoma AB cell line with a panel of PI3K/AKT/mTOR inhibitors resulted in marked reduction of cell viability. A large microRNA cluster on chr19q13.42 is a transcriptional hallmark of type A and AB thymomas. Furthermore, this cluster activates the PI3K pathway, suggesting the possible exploration of PI3K inhibitors in patients with these subtypes of tumour. This work has led to the initiation of a phase II clinical trial of PI3K inhibition in relapsed or refractory thymomas (http://clinicaltrials.gov/ct2/show/NCT02220855).

CLAST: CUDA implemented large-scale alignment search tool.

PubMed

Yano, Masahiro; Mori, Hiroshi; Akiyama, Yutaka; Yamada, Takuji; Kurokawa, Ken

2014-12-11

Metagenomics is a powerful methodology to study microbial communities, but it is highly dependent on nucleotide sequence similarity searching against sequence databases. Metagenomic analyses with next-generation sequencing technologies produce enormous numbers of reads from microbial communities, and many reads are derived from microbes whose genomes have not yet been sequenced, limiting the usefulness of existing sequence similarity search tools. Therefore, there is a clear need for a sequence similarity search tool that can rapidly detect weak similarity in large datasets. We developed a tool, which we named CLAST (CUDA implemented large-scale alignment search tool), that enables analyses of millions of reads and thousands of reference genome sequences, and runs on NVIDIA Fermi architecture graphics processing units. CLAST has four main advantages over existing alignment tools. First, CLAST was capable of identifying sequence similarities ~80.8 times faster than BLAST and 9.6 times faster than BLAT. Second, CLAST executes global alignment as the default (local alignment is also an option), enabling CLAST to assign reads to taxonomic and functional groups based on evolutionarily distant nucleotide sequences with high accuracy. Third, CLAST does not need a preprocessed sequence database like Burrows-Wheeler Transform-based tools, and this enables CLAST to incorporate large, frequently updated sequence databases. Fourth, CLAST requires <2 GB of main memory, making it possible to run CLAST on a standard desktop computer or server node. CLAST achieved very high speed (similar to the Burrows-Wheeler Transform-based Bowtie 2 for long reads) and sensitivity (equal to BLAST, BLAT, and FR-HIT) without the need for extensive database preprocessing or a specialized computing platform. Our results demonstrate that CLAST has the potential to be one of the most powerful and realistic approaches to analyze the massive amount of sequence data from next-generation sequencing

Self-Assembly of Measles Virus Nucleocapsid-like Particles: Kinetics and RNA Sequence Dependence.

PubMed

Milles, Sigrid; Jensen, Malene Ringkjøbing; Communie, Guillaume; Maurin, Damien; Schoehn, Guy; Ruigrok, Rob W H; Blackledge, Martin

2016-08-01

Measles virus RNA genomes are packaged into helical nucleocapsids (NCs), comprising thousands of nucleo-proteins (N) that bind the entire genome. N-RNA provides the template for replication and transcription by the viral polymerase and is a promising target for viral inhibition. Elucidation of mechanisms regulating this process has been severely hampered by the inability to controllably assemble NCs. Here, we demonstrate self-organization of N into NC-like particles in vitro upon addition of RNA, providing a simple and versatile tool for investigating assembly. Real-time NMR and fluorescence spectroscopy reveals biphasic assembly kinetics. Remarkably, assembly depends strongly on the RNA-sequence, with the genomic 5' end and poly-Adenine sequences assembling efficiently, while sequences such as poly-Uracil are incompetent for NC formation. This observation has important consequences for understanding the assembly process. © 2016 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA.

Small tandemly repeated DNA sequences of higher plants likely originate from a tRNA gene ancestor.

PubMed Central

Benslimane, A A; Dron, M; Hartmann, C; Rode, A

1986-01-01

Several monomers (177 bp) of a tandemly arranged repetitive nuclear DNA sequence of Brassica oleracea have been cloned and sequenced. They share up to 95% homology between one another and up to 80% with other satellite DNA sequences of Cruciferae, suggesting a common ancestor. Both strands of these monomers show more than 50% homology with many tRNA genes; the best homologies have been obtained with Lys and His yeast mitochondrial tRNA genes (respectively 64% and 60%). These results suggest that small tandemly repeated DNA sequences of plants may have evolved from a tRNA gene ancestor. These tandem repeats have probably arisen via a process involving reverse transcription of polymerase III RNA intermediates, as is the case for interspersed DNA sequences of mammalians. A model is proposed to explain the formation of such small tandemly repeated DNA sequences. Images PMID:3774553

Suitability of partial 16S ribosomal RNA gene sequence analysis for the identification of dangerous bacterial pathogens.

PubMed

Ruppitsch, W; Stöger, A; Indra, A; Grif, K; Schabereiter-Gurtner, C; Hirschl, A; Allerberger, F

2007-03-01

In a bioterrorism event a rapid tool is needed to identify relevant dangerous bacteria. The aim of the study was to assess the usefulness of partial 16S rRNA gene sequence analysis and the suitability of diverse databases for identifying dangerous bacterial pathogens. For rapid identification purposes a 500-bp fragment of the 16S rRNA gene of 28 isolates comprising Bacillus anthracis, Brucella melitensis, Burkholderia mallei, Burkholderia pseudomallei, Francisella tularensis, Yersinia pestis, and eight genus-related and unrelated control strains was amplified and sequenced. The obtained sequence data were submitted to three public and two commercial sequence databases for species identification. The most frequent reason for incorrect identification was the lack of the respective 16S rRNA gene sequences in the database. Sequence analysis of a 500-bp 16S rDNA fragment allows the rapid identification of dangerous bacterial species. However, for discrimination of closely related species sequencing of the entire 16S rRNA gene, additional sequencing of the 23S rRNA gene or sequencing of the 16S-23S rRNA intergenic spacer is essential. This work provides comprehensive information on the suitability of partial 16S rDNA analysis and diverse databases for rapid and accurate identification of dangerous bacterial pathogens.

Phylogenetically Structured Differences in rRNA Gene Sequence Variation among Species of Arbuscular Mycorrhizal Fungi and Their Implications for Sequence Clustering

PubMed Central

Ekanayake, Saliya; Ruan, Yang; Schütte, Ursel M. E.; Kaonongbua, Wittaya; Fox, Geoffrey; Ye, Yuzhen; Bever, James D.

2016-01-01

ABSTRACT Arbuscular mycorrhizal (AM) fungi form mutualisms with plant roots that increase plant growth and shape plant communities. Each AM fungal cell contains a large amount of genetic diversity, but it is unclear if this diversity varies across evolutionary lineages. We found that sequence variation in the nuclear large-subunit (LSU) rRNA gene from 29 isolates representing 21 AM fungal species generally assorted into genus- and species-level clades, with the exception of species of the genera Claroideoglomus and Entrophospora. However, there were significant differences in the levels of sequence variation across the phylogeny and between genera, indicating that it is an evolutionarily constrained trait in AM fungi. These consistent patterns of sequence variation across both phylogenetic and taxonomic groups pose challenges to interpreting operational taxonomic units (OTUs) as approximations of species-level groups of AM fungi. We demonstrate that the OTUs produced by five sequence clustering methods using 97% or equivalent sequence similarity thresholds failed to match the expected species of AM fungi, although OTUs from AbundantOTU, CD-HIT-OTU, and CROP corresponded better to species than did OTUs from mothur or UPARSE. This lack of OTU-to-species correspondence resulted both from sequences of one species being split into multiple OTUs and from sequences of multiple species being lumped into the same OTU. The OTU richness therefore will not reliably correspond to the AM fungal species richness in environmental samples. Conservatively, this error can overestimate species richness by 4-fold or underestimate richness by one-half, and the direction of this error will depend on the genera represented in the sample. IMPORTANCE Arbuscular mycorrhizal (AM) fungi form important mutualisms with the roots of most plant species. Individual AM fungi are genetically diverse, but it is unclear whether the level of this diversity differs among evolutionary lineages. We found

Discovery of DNA viruses in wild-caught mosquitoes using small RNA high throughput sequencing.

PubMed

Ma, Maijuan; Huang, Yong; Gong, Zhengda; Zhuang, Lu; Li, Cun; Yang, Hong; Tong, Yigang; Liu, Wei; Cao, Wuchun

2011-01-01

Mosquito-borne infectious diseases pose a severe threat to public health in many areas of the world. Current methods for pathogen detection and surveillance are usually dependent on prior knowledge of the etiologic agents involved. Hence, efficient approaches are required for screening wild mosquito populations to detect known and unknown pathogens. In this study, we explored the use of Next Generation Sequencing to identify viral agents in wild-caught mosquitoes. We extracted total RNA from different mosquito species from South China. Small 18-30 bp length RNA molecules were purified, reverse-transcribed into cDNA and sequenced using Illumina GAIIx instrumentation. Bioinformatic analyses to identify putative viral agents were conducted and the results confirmed by PCR. We identified a non-enveloped single-stranded DNA densovirus in the wild-caught Culex pipiens molestus mosquitoes. The majority of the viral transcripts (.>80% of the region) were covered by the small viral RNAs, with a few peaks of very high coverage obtained. The +/- strand sequence ratio of the small RNAs was approximately 7∶1, indicating that the molecules were mainly derived from the viral RNA transcripts. The small viral RNAs overlapped, enabling contig assembly of the viral genome sequence. We identified some small RNAs in the reverse repeat regions of the viral 5'- and 3' -untranslated regions where no transcripts were expected. Our results demonstrate for the first time that high throughput sequencing of small RNA is feasible for identifying viral agents in wild-caught mosquitoes. Our results show that it is possible to detect DNA viruses by sequencing the small RNAs obtained from insects, although the underlying mechanism of small viral RNA biogenesis is unclear. Our data and those of other researchers show that high throughput small RNA sequencing can be used for pathogen surveillance in wild mosquito vectors.