rna sequence analysis

Summary

Summary: A multistage process that includes cloning, physical mapping, subcloning, sequencing, and information analysis of an RNA SEQUENCE.

Top Publications

  1. Wei B, Cai T, Zhang R, Li A, Huo N, Li S, et al. Novel microRNAs uncovered by deep sequencing of small RNA transcriptomes in bread wheat (Triticum aestivum L.) and Brachypodium distachyon (L.) Beauv. Funct Integr Genomics. 2009;9:499-511 pubmed publisher
    ..Our work significantly increases the novel miRNA numbers in wheat and provides the first set of small RNAs in B. distachyon. ..
  2. Fu X, Fu N, Guo S, Yan Z, Xu Y, Hu H, et al. Estimating accuracy of RNA-Seq and microarrays with proteomics. BMC Genomics. 2009;10:161 pubmed publisher
    ..Our result shows that in terms of overall technical performance, RNA-Seq is the technique of choice for studies that require accurate estimation of absolute transcript levels. ..
  3. van der Burgt A, Fiers M, Nap J, van Ham R. In silico miRNA prediction in metazoan genomes: balancing between sensitivity and specificity. BMC Genomics. 2009;10:204 pubmed publisher
  4. Harmanci A, Sharma G, Mathews D. Stochastic sampling of the RNA structural alignment space. Nucleic Acids Res. 2009;37:4063-75 pubmed publisher
    ..Additionally, cluster analysis identifies, on average, a few clusters, whose centroids can be presented as alternative candidates. The source code for the proposed method can be downloaded at http://rna.urmc.rochester.edu. ..
  5. Carra A, Mica E, Gambino G, Pindo M, Moser C, Pè M, et al. Cloning and characterization of small non-coding RNAs from grape. Plant J. 2009;59:750-63 pubmed publisher
  6. Fahlgren N, Sullivan C, Kasschau K, Chapman E, Cumbie J, Montgomery T, et al. Computational and analytical framework for small RNA profiling by high-throughput sequencing. RNA. 2009;15:992-1002 pubmed publisher
    ..Computational methods were also developed to rapidly and accurately parse, quantify, and map small RNA data. ..
  7. Chushak Y, Stone M. In silico selection of RNA aptamers. Nucleic Acids Res. 2009;37:e87 pubmed publisher
    ..The proposed approach reduces the RNA sequences search space by four to five orders of magnitude--significantly accelerating the experimental screening and selection of high-affinity aptamers. ..
  8. Mereau A, Anquetil V, Cibois M, Noiret M, Primot A, Vallee A, et al. Analysis of splicing patterns by pyrosequencing. Nucleic Acids Res. 2009;37:e126 pubmed publisher
    ..The PASP method is therefore reliable for analysing splicing patterns. All steps are done in 96-wells microplates, without gel electrophoresis, opening the way to high-throughput comparisons of RNA from several sources. ..
  9. Guttman M, Garber M, Levin J, Donaghey J, Robinson J, Adiconis X, et al. Ab initio reconstruction of cell type-specific transcriptomes in mouse reveals the conserved multi-exonic structure of lincRNAs. Nat Biotechnol. 2010;28:503-10 pubmed publisher
    ..Our results open the way to direct experimental manipulation of thousands of noncoding RNAs and demonstrate the power of ab initio reconstruction to render a comprehensive picture of mammalian transcriptomes. ..

More Information

Publications62

  1. Perkins T, Kingsley R, Fookes M, Gardner P, James K, Yu L, et al. A strand-specific RNA-Seq analysis of the transcriptome of the typhoid bacillus Salmonella typhi. PLoS Genet. 2009;5:e1000569 pubmed publisher
    ..Typhi OmpR regulon and identify novel OmpR regulated transcripts. Thus, ssRNA-seq provides a novel and powerful approach to the characterization of the bacterial transcriptome. ..
  2. Langenberger D, Bermudez Santana C, Hertel J, Hoffmann S, Khaitovich P, Stadler P. Evidence for human microRNA-offset RNAs in small RNA sequencing data. Bioinformatics. 2009;25:2298-301 pubmed publisher
  3. Kaye M, Chibo D, Birch C. Comparison of Bayesian and maximum-likelihood phylogenetic approaches in two legal cases involving accusations of transmission of HIV. AIDS Res Hum Retroviruses. 2009;25:741-8 pubmed publisher
  4. Richard H, Schulz M, Sultan M, Nürnberger A, Schrinner S, Balzereit D, et al. Prediction of alternative isoforms from exon expression levels in RNA-Seq experiments. Nucleic Acids Res. 2010;38:e112 pubmed publisher
    ..The software is available as an open-source R-package called Solas at http://cmb.molgen.mpg.de/2ndGenerationSequencing/Solas/. ..
  5. Hackenberg M, Sturm M, Langenberger D, Falcón Pérez J, Aransay A. miRanalyzer: a microRNA detection and analysis tool for next-generation sequencing experiments. Nucleic Acids Res. 2009;37:W68-76 pubmed publisher
    ..miRanalyzer is available at http://web.bioinformatics.cicbiogune.es/microRNA/. ..
  6. Bullard J, Purdom E, Hansen K, Dudoit S. Evaluation of statistical methods for normalization and differential expression in mRNA-Seq experiments. BMC Bioinformatics. 2010;11:94 pubmed publisher
    ..They also reveal the need for further research in the development of statistical and computational methods for mRNA-Seq. ..
  7. Maragkakis M, Reczko M, Simossis V, Alexiou P, Papadopoulos G, Dalamagas T, et al. DIANA-microT web server: elucidating microRNA functions through target prediction. Nucleic Acids Res. 2009;37:W273-6 pubmed publisher
    ..DIANA-microT 3.0 achieved there with 66% the highest ratio of correctly predicted targets over all predicted targets. The DIANA-microT web server is freely available at www.microrna.gr/microT. ..
  8. Severin A, Woody J, Bolon Y, Joseph B, Diers B, Farmer A, et al. RNA-Seq Atlas of Glycine max: a guide to the soybean transcriptome. BMC Plant Biol. 2010;10:160 pubmed publisher
    ..Data contained within this RNA-Seq atlas of Glycine max can be explored at http://www.soybase.org/soyseq. ..
  9. Xu X, Ji Y, Stormo G. Discovering cis-regulatory RNAs in Shewanella genomes by Support Vector Machines. PLoS Comput Biol. 2009;5:e1000338 pubmed publisher
    ..The RSSVM software, predictions, and analysis results on Shewanella genomes are available at http://ural.wustl.edu/resources.html#RSSVM. ..
  10. Marguerat S, Bahler J. RNA-seq: from technology to biology. Cell Mol Life Sci. 2010;67:569-79 pubmed publisher
  11. Li J, Jiang H, Wong W. Modeling non-uniformity in short-read rates in RNA-Seq data. Genome Biol. 2010;11:R50 pubmed publisher
    ..These models explain more than 50% of the variations and can lead to improved estimates of gene and isoform expressions for both Illumina and Applied Biosystems data. ..
  12. Chen H, Wu S. Mining small RNA sequencing data: a new approach to identify small nucleolar RNAs in Arabidopsis. Nucleic Acids Res. 2009;37:e69 pubmed publisher
    ..In this study, we demonstrated that the use of small RNA sequencing data can increase the complexity and the accuracy of snoRNA annotation. ..
  13. Gilad Y, Pritchard J, Thornton K. Characterizing natural variation using next-generation sequencing technologies. Trends Genet. 2009;25:463-71 pubmed publisher
    ..A better understanding of the sources of error and bias in sequencing data is essential, especially in the context of studies of variation at dynamic quantitative traits. ..
  14. Andronescu M, Pop C, Condon A. Improved free energy parameters for RNA pseudoknotted secondary structure prediction. RNA. 2010;16:26-42 pubmed publisher
    ..Specifically, the prediction accuracy when using our new parameters improves from 68% to 79% for the DP model, and from 70% to 77% for the CC model. ..
  15. de Hoon M, Taft R, Hashimoto T, Kanamori Katayama M, Kawaji H, Kawano M, et al. Cross-mapping and the identification of editing sites in mature microRNAs in high-throughput sequencing libraries. Genome Res. 2010;20:257-64 pubmed publisher
    ..Here, we develop a strategy to correct for cross-mapping, and apply it to the analysis of RNA editing in mature miRNAs. In contrast to previous reports, our analysis suggests that RNA editing in mature miRNAs is rare in animals. ..
  16. Nawrocki E, Kolbe D, Eddy S. Infernal 1.0: inference of RNA alignments. Bioinformatics. 2009;25:1335-7 pubmed publisher
    ..Source code, documentation and benchmark downloadable from http://infernal.janelia.org. INFERNAL is freely licensed under the GNU GPLv3 and should be portable to any POSIX-compliant operating system, including Linux and Mac OS/X. ..
  17. Filichkin S, Priest H, Givan S, Shen R, Bryant D, Fox S, et al. Genome-wide mapping of alternative splicing in Arabidopsis thaliana. Genome Res. 2010;20:45-58 pubmed publisher
    ..Taken together, our results suggest that like in animals, NMD and RUST may be widespread in plants and may play important roles in regulating gene expression. ..
  18. Li B, Ruotti V, Stewart R, Thomson J, Dewey C. RNA-Seq gene expression estimation with read mapping uncertainty. Bioinformatics. 2010;26:493-500 pubmed publisher
    ..Simulations with our method indicate that a read length of 20-25 bases is optimal for gene-level expression estimation from mouse and maize RNA-Seq data when sequencing throughput is fixed. ..
  19. Zhang Y, Liu J, Jia C, Li T, Wu R, Wang J, et al. Systematic identification and evolutionary features of rhesus monkey small nucleolar RNAs. BMC Genomics. 2010;11:61 pubmed publisher
    ..These findings provide important information for future functional characterization of snoRNAs during primate evolution. ..
  20. Creighton C, Reid J, Gunaratne P. Expression profiling of microRNAs by deep sequencing. Brief Bioinform. 2009;10:490-7 pubmed publisher
    ..Here we discuss tools and methodologies for the analysis of microRNA expression data from deep sequencing. ..
  21. Guffanti A, Iacono M, Pelucchi P, Kim N, Soldà G, Croft L, et al. A transcriptional sketch of a primary human breast cancer by 454 deep sequencing. BMC Genomics. 2009;10:163 pubmed publisher
  22. Zheng S, Chen L. A hierarchical Bayesian model for comparing transcriptomes at the individual transcript isoform level. Nucleic Acids Res. 2009;37:e75 pubmed publisher
    ..We applied BASIS to a human tiling-array data set and a mouse RNA-seq data set. Some of the predictions were validated by quantitative real-time RT-PCR experiments. ..
  23. Blencowe B, Ahmad S, Lee L. Current-generation high-throughput sequencing: deepening insights into mammalian transcriptomes. Genes Dev. 2009;23:1379-86 pubmed publisher
    ..We also consider how future advances in HTS technology are likely to transform our understanding of integrated cellular networks operating at the RNA level. ..
  24. Papadopoulos G, Alexiou P, Maragkakis M, Reczko M, Hatzigeorgiou A. DIANA-mirPath: Integrating human and mouse microRNAs in pathways. Bioinformatics. 2009;25:1991-3 pubmed publisher
    ..The software is available at http://microrna.gr/mirpath and is free for all users with no login or download requirement. ..
  25. Pantano L, Estivill X, Marti E. SeqBuster, a bioinformatic tool for the processing and analysis of small RNAs datasets, reveals ubiquitous miRNA modifications in human embryonic cells. Nucleic Acids Res. 2010;38:e34 pubmed publisher
    ..The exhaustive description of the isomiRs provided by SeqBuster could help to identify miRNA-variants that are relevant in physiological and pathological processes. SeqBuster is available at http://estivill_lab.crg.es/seqbuster. ..
  26. Yang J, Shao P, Zhou H, Chen Y, Qu L. deepBase: a database for deeply annotating and mining deep sequencing data. Nucleic Acids Res. 2010;38:D123-30 pubmed publisher
    ..A convenient search option, related publications and other useful information are also provided for further investigation. deepBase is available at: http://deepbase.sysu.edu.cn/. ..
  27. Wang W, Lin F, Chang W, Lin K, Huang H, Lin N. miRExpress: analyzing high-throughput sequencing data for profiling microRNA expression. BMC Bioinformatics. 2009;10:328 pubmed publisher
    ..The analysis of two Illumina data sets constructed from human and plant demonstrate the effectiveness of miRExpress to obtain miRNA expression profiles and show the usability in finding novel miRNAs. ..
  28. Copeland C, Marz M, Rose D, Hertel J, Brindley P, Santana C, et al. Homology-based annotation of non-coding RNAs in the genomes of Schistosoma mansoni and Schistosoma japonicum. BMC Genomics. 2009;10:464 pubmed publisher
    ..This data set provides an important reference for further analysis of the genomes of schistosomes and indeed eukaryotic genomes at large. ..
  29. Mica E, Piccolo V, Delledonne M, Ferrarini A, Pezzotti M, Casati C, et al. High throughput approaches reveal splicing of primary microRNA transcripts and tissue specific expression of mature microRNAs in Vitis vinifera. BMC Genomics. 2009;10:558 pubmed publisher
  30. Wang L, Feng Z, Wang X, Wang X, Zhang X. DEGseq: an R package for identifying differentially expressed genes from RNA-seq data. Bioinformatics. 2010;26:136-8 pubmed publisher
    ..The R package and a quick-start vignette is available at http://bioinfo.au.tsinghua.edu.cn/software/degseq ..
  31. Wang X, Wang X, Varma R, Beauchamp L, Magdaleno S, Sendera T. Selection of hyperfunctional siRNAs with improved potency and specificity. Nucleic Acids Res. 2009;37:e152 pubmed publisher
    ..The siRNA design web server is available at http://www5.appliedbiosystems.com/tools/siDesign/. ..
  32. Tang F, Barbacioru C, Nordman E, Li B, Xu N, Bashkirov V, et al. RNA-Seq analysis to capture the transcriptome landscape of a single cell. Nat Protoc. 2010;5:516-35 pubmed publisher
    ..Compared with cDNA microarray techniques, our assay can capture up to 75% more genes expressed in early embryos. This protocol can generate deep-sequencing libraries for 16 single-cell samples within 6 d...
  33. Han X, Wu X, Chung W, Li T, Nekrutenko A, Altman N, et al. Transcriptome of embryonic and neonatal mouse cortex by high-throughput RNA sequencing. Proc Natl Acad Sci U S A. 2009;106:12741-6 pubmed publisher
    ..Our transcriptome analysis may serve as a blueprint for gene expression pattern and provide functional clues of previously unknown genes and disease-related genes during early brain development. ..
  34. Stadler P, Chen J, Hackermüller J, Hoffmann S, Horn F, Khaitovich P, et al. Evolution of vault RNAs. Mol Biol Evol. 2009;26:1975-91 pubmed publisher
    ..In teleosts, expression of several paralogous vtRNA genes, most but not all located at the syntenically conserved protocadherin locus, was verified by reverse transcriptase-polymerase chain reaction. ..
  35. Trapnell C, Williams B, Pertea G, Mortazavi A, Kwan G, van Baren M, et al. Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat Biotechnol. 2010;28:511-5 pubmed publisher
    ..These results suggest that Cufflinks can illuminate the substantial regulatory flexibility and complexity in even this well-studied model of muscle development and that it can improve transcriptome-based genome annotation. ..
  36. Qiu D, Pan X, Wilson I, Li F, Liu M, Teng W, et al. High throughput sequencing technology reveals that the taxoid elicitor methyl jasmonate regulates microRNA expression in Chinese yew (Taxus chinensis). Gene. 2009;436:37-44 pubmed publisher
  37. Richter A, Schleberger C, Backofen R, Steglich C. Seed-based INTARNA prediction combined with GFP-reporter system identifies mRNA targets of the small RNA Yfr1. Bioinformatics. 2010;26:1-5 pubmed publisher
    ..We used mutation analysis to confirm that Yfr1 directly regulates its targets by an antisense interaction sequestering the ribosome binding site, and to assess the importance of interaction site accessibility. ..
  38. De Grazia S, Martella V, Colomba C, Cascio A, Arista S, Giammanco G. Genetic characterization of G3 rotaviruses detected in Italian children in the years 1993-2005. J Med Virol. 2009;81:2089-95 pubmed publisher
    ..By converse, after 2002 the Italian G3P[8] strains were found to possess unique mutations in significant regions of the NSP4 protein. ..
  39. Iida K, Jin H, Zhu J. Bioinformatics analysis suggests base modifications of tRNAs and miRNAs in Arabidopsis thaliana. BMC Genomics. 2009;10:155 pubmed publisher
    ..We suggest that miRNAs contain modified bases and such modifications might be important for miRNA maturation and/or function. ..
  40. Wilhelm B, Landry J. RNA-Seq-quantitative measurement of expression through massively parallel RNA-sequencing. Methods. 2009;48:249-57 pubmed publisher
    ..This article discusses the experimental approach for both sample preparation and data analysis for the technique of RNA-seq. ..
  41. Meyer M, Ames T, Smith D, Weinberg Z, Schwalbach M, Giovannoni S, et al. Identification of candidate structured RNAs in the marine organism 'Candidatus Pelagibacter ubique'. BMC Genomics. 2009;10:268 pubmed publisher
    ..This work begins the process of identifying functional RNA motifs present in the metagenomic data and illustrates how existing completed genomes may be used to aid in this task. ..
  42. Ozsolak F, Platt A, Jones D, Reifenberger J, Sass L, McInerney P, et al. Direct RNA sequencing. Nature. 2009;461:814-8 pubmed publisher
    ..This study provides a path to high-throughput and low-cost direct RNA sequencing and achieving the ultimate goal of a comprehensive and bias-free understanding of transcriptomes. ..
  43. Cloonan N, Xu Q, Faulkner G, Taylor D, Tang D, Kolle G, et al. RNA-MATE: a recursive mapping strategy for high-throughput RNA-sequencing data. Bioinformatics. 2009;25:2615-6 pubmed publisher
    ..Executables, source code, and exon-junction libraries are available from http://grimmond.imb.uq.edu.au/RNA-MATE/ ..
  44. Oliver H, Orsi R, Ponnala L, Keich U, Wang W, Sun Q, et al. Deep RNA sequencing of L. monocytogenes reveals overlapping and extensive stationary phase and sigma B-dependent transcriptomes, including multiple highly transcribed noncoding RNAs. BMC Genomics. 2009;10:641 pubmed publisher
  45. Gennarino V, Sardiello M, Avellino R, Meola N, Maselli V, Anand S, et al. MicroRNA target prediction by expression analysis of host genes. Genome Res. 2009;19:481-90 pubmed publisher
    ..Finally, our data further confirm that miRNAs have a significant impact on the mRNA levels of most of their targets. ..
  46. Denoeud F, Aury J, Da Silva C, Noel B, Rogier O, Delledonne M, et al. Annotating genomes with massive-scale RNA sequencing. Genome Biol. 2008;9:R175 pubmed publisher
    ..We present G-Mo.R-Se (Gene Modelling using RNA-Seq), an approach aimed at building gene models directly from RNA-Seq and demonstrate its utility on the grapevine genome. ..
  47. Heyne S, Will S, Beckstette M, Backofen R. Lightweight comparison of RNAs based on exact sequence-structure matches. Bioinformatics. 2009;25:2095-102 pubmed publisher
    ..The presented algorithm is implemented in the program ExpaRNA, which is available from our website (http://www.bioinf.uni-freiburg.de/Software). ..
  48. Xue X, Sun J, Zhang Q, Wang Z, Huang Y, Pan W. Identification and characterization of novel microRNAs from Schistosoma japonicum. PLoS ONE. 2008;3:e4034 pubmed publisher
    ..Although a large number of miRNAs have been identified from plants to mammals, it remains no experimental proof whether schistosome exist miRNAs...
  49. Jiang H, Wong W. Statistical inferences for isoform expression in RNA-Seq. Bioinformatics. 2009;25:1026-32 pubmed publisher
    ..Our results show that isoform expression inference in RNA-Seq is possible by employing appropriate statistical methods. ..
  50. Lee A, Hansen K, Bullard J, Dudoit S, Sherlock G. Novel low abundance and transient RNAs in yeast revealed by tiling microarrays and ultra high-throughput sequencing are not conserved across closely related yeast species. PLoS Genet. 2008;4:e1000299 pubmed publisher
    ..cerevisiae. Such regions of the genome have typically been less well-studied, and by definition transcripts from these regions will distinguish S. cerevisiae from these closely related species. ..
  51. Yoder Himes D, Chain P, Zhu Y, Wurtzel O, Rubin E, Tiedje J, et al. Mapping the Burkholderia cenocepacia niche response via high-throughput sequencing. Proc Natl Acad Sci U S A. 2009;106:3976-81 pubmed publisher
    ..Compared with the CF strain, the soil strain shows a stronger global gene expression response to its environment, which is consistent with the need for a more dynamic reaction to the heterogeneous conditions of soil. ..
  52. Liu J, Livny J, Lawrence M, Kimball M, Waldor M, Camilli A. Experimental discovery of sRNAs in Vibrio cholerae by direct cloning, 5S/tRNA depletion and parallel sequencing. Nucleic Acids Res. 2009;37:e46 pubmed publisher
  53. Reddy A, Zheng Y, Jagadeeswaran G, Macmil S, Graham W, Roe B, et al. Cloning, characterization and expression analysis of porcine microRNAs. BMC Genomics. 2009;10:65 pubmed publisher