Abstract
Next-generation sequencing has enabled genome-wide studies of alternative pre-mRNA splicing, allowing for empirical determination, characterization, and quantification of the expressed RNAs in a sample in toto. As a result, RNA sequencing (RNA-seq) has shown tremendous power to drive biological discoveries. At the same time, RNA-seq has created novel challenges that necessitate the development of increasingly sophisticated computational approaches and bioinformatic tools. In addition to the analysis of massive datasets, these tools also need to facilitate questions and analytical approaches driven by such rich data. HTS and RNA-seq are still in a stage of very rapid evolution and are, therefore, only introduced in general terms. This chapter mainly focuses on the methods for discovery, detection, and quantification of alternatively spliced transcript variants.
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References
Jacquier A (2009) The complex eukaryotic transcriptome: unexpected pervasive transcription and novel small RNAs. Nat Rev Genet 10:833–844
Fox S, Filichkin S, Mockler TC (2009) Applications of ultra-high-throughput sequencing. Methods Mol Biol 553:79–108
Mortazavi A et al (2008) Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nat Methods 5:621–628
Nagalakshmi U et al (2008) The transcriptional landscape of the yeast genome defined by RNA sequencing. Science 320: 1344–1349
Filichkin SA et al (2010) Genome-wide mapping of alternative splicing in Arabidopsis thaliana. Genome Res 20:45–58
Li H et al (2008) Determination of tag density required for digital transcriptome analysis: application to an androgen-sensitive prostate cancer model. Proc Natl Acad Sci USA 105:20179–20184
Parkhomchuk D et al (2009) Transcriptome analysis by strand-specific sequencing of complementary DNA. Nucleic Acids Res 37:e123
Ingolia NT et al (2009) Genome-wide analysis in vivo of translation with nucleotide resolution using ribosome profiling. Science 324:218–223
He Y et al (2008) The antisense transcriptomes of human cells. Science 322:1855–1857
Cloonan N et al (2008) Stem cell transcriptome profiling via massive-scale mRNA sequencing. Nat Methods 5:613–619
Lister R et al (2008) Highly integrated single-base resolution maps of the epigenome in Arabidopsis. Cell 133:523–536
Core LJ, Waterfall JJ, Lis JT (2008) Nascent RNA sequencing reveals widespread pausing and divergent initiation at human promoters. Science 322:1845–1848
Li R et al (2009) SOAP2: an improved ultrafast tool for short read alignment. Bioinformatics 25:1966–1967
Bryant DW et al (2010) Supersplat-spliced RNA-seq alignment. Bioinformatics 26:1500–1505
Bryant DW, et al (2011) Gumby—a purely empirical RNA-seq-based approach to genome annotation. Manuscript in Preparation.
Trapnell C, Pachter L, Salzberg SL (2009) TopHat: discovering splice junctions with RNA-Seq. Bioinformatics 25:1105–1111
Jiang H, Wong WH (2008) SeqMap: mapping massive amount of oligonucleotides to the genome. Bioinformatics 24:2395–2396
Li H, Ruan J, Durbin R (2008) Mapping short DNA sequencing reads and calling variants using mapping quality scores. Genome Res 18:1851–1858
Li R et al (2008) SOAP: short oligonucleotide alignment program. Bioinformatics 24: 713–714
Smith AD, Xuan Z, Zhang MQ (2008) Using quality scores and longer reads improves accuracy of Solexa read mapping. BMC Bioinformatics 9:128
Homer N, Merriman B, Nelson SF (2009) BFAST: an alignment tool for large scale genome resequencing. PLoS One 4:e7767
Rumble SM et al (2009) SHRiMP: accurate mapping of short color-space reads. PLoS Comput Biol 5:e1000386
Lunter G, Goodson M (2011) Stampy: a statistical algorithm for sensitive and fast mapping of Illumina sequence reads. Genome Res 21:936–939
Rizk G, Lavenier D (2010) GASSST: global alignment short sequence search tool. Bioinformatics 26:2534–2540
Li H et al (2009) The sequence alignment/map format and SAMtools. Bioinformatics 25:2078–2079
Li H, Durbin R (2009) Fast and accurate short read alignment with Burrows-Wheeler Transform. Bioinformatics 25:1754–1760
Wang K et al (2010) MapSplice: accurate mapping of RNA-seq reads for splice junction discovery. Nucleic Acids Res 38:e178
Au KF et al (2010) Detection of splice junctions from paired-end RNA-seq data by SpliceMap. Nucleic Acids Res 38:4570–4578
Denoeud F et al (2008) Annotating genomes with massive-scale RNA sequencing. Genome Biol 9:R175
Garber M et al (2011) Computational methods for transcriptome annotation and quantification using RNA-seq. Nat Methods 8:469–477
Costa V et al (2010) Uncovering the complexity of transcriptomes with RNA-Seq. J Biomed Biotechnol 2010:853916
Yassour M et al (2009) Ab initio construction of a eukaryotic transcriptome by massively parallel mRNA sequencing. Proc Natl Acad Sci USA 106:3264–3269
Kelley DR, Schatz MC, Salzberg SL (2010) Quake: quality-aware detection and correction of sequencing errors. Genome Biol 11:R116
Shi H et al (2010) A parallel algorithm for error correction in high-throughput short-read data on CUDA-enabled graphics hardware. J Comput Biol 17:603–615
Yang X, Dorman KS, Aluru S (2010) Reptile: representative tiling for short read error correction. Bioinformatics 26:2526–2533
Kao WC, Chan AH, Song YS (2011) ECHO: a reference-free short-read error correction algorithm. Genome Res 21:1181–1192
Zerbino DR, Birney E (2008) Velvet: algorithms for de novo short read assembly using de Bruijn graphs. Genome Res 18:821–829
Birol I, Jackman SD, Nielsen CB (2009) De novo transcriptome assembly with ABySS. Bioinformatics 25:2872–2877
Robertson G et al (2010) De novo assembly and analysis of RNA-seq data. Nat Methods 7:909–912
Grabherr MG et al (2011) Full-length transcriptome assembly from RNA-Seq data Âwithout a reference genome. Nat Biotechnol 29:644–652
De Bruijn NG (1946) A combinatorial problem. Koninklijke Nederlandse Akademie v Wetenschappen 46:6
Griffith M et al (2010) Alternative expression analysis by RNA sequencing. Nat Methods 7:843–847
Trapnell C et al (2010) Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat Biotechnol 28:511–515
Katz Y et al (2010) Analysis and design of RNA sequencing experiments for identifying isoform regulation. Nat Methods 7:1009–1015
Marioni JC et al (2008) RNA-Seq: an assessment of technical reproducibility and comparison with gene expression arrays. Genome Res 18:1509–1517
Jiang H, Wong WH (2009) Statistical inferences for isoform expression in RNA-Seq. Bioinformatics 25:1026–1032
Li B et al (2009) RNA-Seq gene expression estimation with read mapping uncertainty. Bioinformatics 26:493–500
Richard H et al (2010) Prediction of alternative isoforms from exon expression levels in RNA-Seq experiments. Nucleic Acids Res 38:e112
Robinson MD, McCarthy DJ, Smyth GK (2010) edgeR: a bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26:139–140
Anders S, Huber W (2010) Differential expression analysis for sequence count data. Genome Biol 11:R106
Langmead B, Hansen KD, Leek JT (2010) Cloud-scale RNA-sequencing differential expression analysis with Myrna. Genome Biol 11:R83
Cumbie JS, et al (2011) GENE-counter: a computational pipeline for the analysis of RNA-Seq data for gene expression differences. PLoS One (6):e25279
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Bryant, D.W., Priest, H.D., Mockler, T.C. (2012). Detection and Quantification of Alternative Splicing Variants Using RNA-seq. In: Jin, H., Gassmann, W. (eds) RNA Abundance Analysis. Methods in Molecular Biology, vol 883. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-61779-839-9_7
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DOI: https://doi.org/10.1007/978-1-61779-839-9_7
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