Mortazavi A, Williams B, McCue K, Schaeffer L, Wold B: Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nat Methods. 2008, 5: 621-628. 10.1038/nmeth.1226.
Article PubMed CAS Google Scholar
Wang Z, Gerstein M, Snyder M: RNA-Seq: a revolutionary tool for transcriptomics. Nat Rev Genet. 2009, 10: 57-63. 10.1038/nrg2484.
Article PubMed CAS PubMed Central Google Scholar
Filichkin S, Priest H, Givan S, Shen R, Bryant D, Fox S, Wong W, Mockler T: Genome-wide mapping of alternative splicing in Arabidopsis thaliana. Genome Res. 2010, 20: 45-10.1101/gr.093302.109.
Article PubMed CAS PubMed Central Google Scholar
Harr B, Turner L: Genome-wide analysis of alternative splicing evolution among Mus subspecies. Mol Ecol. 2010, 19: 228-239.
Article PubMed CAS Google Scholar
Ramani A, Calarco J, Pan Q, Mavandadi S, Wang Y, Nelson A, Lee L, Morris Q, Blencowe B, Zhen M, Fraser A: Genome-wide analysis of alternative splicing in Caenorhabditis elegans. Genome Res. 2011, 21: 342-10.1101/gr.114645.110.
Article PubMed CAS PubMed Central Google Scholar
Stamm S, Ben-Ari S, Rafalska I, Tang Y, Zhang Z, Toiber D, Thanaraj T, Soreq H: Function of alternative splicing. Gene. 2005, 344: 1-20.
Article PubMed CAS Google Scholar
Hallegger M, Llorian M, Smith CWJ: Alternative splicing: global insights. FEBS J. 2010, 277: 856-866. 10.1111/j.1742-4658.2009.07521.x.
Article PubMed CAS Google Scholar
Shendure J, Ji H: Next-generation DNA sequencing. Nat Biotechnol. 2008, 26: 1135-1145. 10.1038/nbt1486.
Article PubMed CAS Google Scholar
Li H, Ruan J, Durbin R: Mapping short DNA sequencing reads and calling variants using mapping quality scores. Genome Res. 2008, 18: 1851-10.1101/gr.078212.108.
Article PubMed CAS PubMed Central Google Scholar
Campagna D, Albiero A, Bilardi A, Caniato E, Forcato C, Manavski S, Vitulo N, Valle G: PASS: a program to align short sequences. Bioinformatics. 2009, 25: 967-10.1093/bioinformatics/btp087.
Article PubMed CAS Google Scholar
Langmead B, Trapnell C, Pop M, Salzberg S: Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol. 2009, 10: R25-10.1186/gb-2009-10-3-r25.
Article PubMed PubMed Central Google Scholar
De Bona F, Ossowski S, Schneeberger K, Rätsch G: Optimal spliced alignments of short sequence reads. BMC Bioinformatics. 2008, 9: O7-10.1186/1471-2105-9-S10-O7.
Article Google Scholar
Yassour M, Kaplan T, Fraser H, Levin J, Pfiffner J, Adiconis X, Schroth G, Luo S, Khrebtukova I, Gnirke A, Nusbaum C, Thompson D, Friedman N, Regev A: Ab initio construction of a eukaryotic transcriptome by massively parallel mRNA sequencing. Proc Natl Acad Sci USA. 2009, 106: 3264-10.1073/pnas.0812841106.
Pan Q, Shai O, Lee L, Frey B, Blencowe B: Deep surveying of alternative splicing complexity in the human transcriptome by high-throughput sequencing. Nat Genet. 2008, 40: 1413-1415. 10.1038/ng.259.
Article PubMed CAS Google Scholar
Sultan M, Schulz M, Richard H, Magen A, Klingenhoff A, Scherf M, Seifert M, Borodina T, Soldatov A, Parkhomchuk D, Schmidt D, O'Keeffe S, Haas S, Vingron M, Lehrach H, Yaspo M: A global view of gene activity and alternative splicing by deep sequencing of the human transcriptome. Science. 2008, 321: 956-959. 10.1126/science.1160342.
Article PubMed CAS Google Scholar
Wang E, Sandberg R, Luo S, Khrebtukova I, Zhang L, Mayr C, Kingsmore S, Schroth G, Burge C: Alternative isoform regulation in human tissue transcriptomes. Nature. 2008, 456: 470-476. 10.1038/nature07509.
Article PubMed CAS PubMed Central Google Scholar
Tang F, Barbacioru C, Wang Y, Nordman E, Lee C, Xu N, Wang X, Bodeau J, Tuch B, Siddiqui A, Lao K, Surani M: mRNA-Seq whole-transcriptome analysis of a single cell. Nat Methods. 2009, 6: 377-382. 10.1038/nmeth.1315.
Article PubMed CAS Google Scholar
Trapnell C, Williams B, Pertea G, Mortazavi A, Kwan G, van Baren M, Salzberg S, Wold B, Pachter L: Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat Biotechnol. 2010, 28: 511-515. 10.1038/nbt.1621.
Article PubMed CAS PubMed Central Google Scholar
Guttman M, Garber M, Levin J, Donaghey J, Robinson J, Adiconis X, Fan L, Koziol M, Gnirke A, Nusbaum C, Rinn J, Lander E, Regev A: Ab initio reconstruction of cell type-specific transcriptomes in mouse reveals the conserved multi-exonic structure of lincRNAs. Nat Biotechnol. 2010, 28: 503-510. 10.1038/nbt.1633.
Article PubMed CAS PubMed Central Google Scholar
Grabherr M, Haas B, Yassour M, Levin J, Thompson D, Amit I, Adiconis X, Fan L, Raychowdhury R, Zeng Q, Chen Z, Mauceli E, Hacohen N, Gnirke A, Rhind N, di Palma F, Birren B, Nusbaum C, Lindblad-Toh K, Friedman N, Regev A: Full-length transcriptome assembly from RNA-Seq data without a reference genome. Nat Biotechnol. 2011, 29: 644-652. 10.1038/nbt.1883.
Article PubMed CAS PubMed Central Google Scholar
Simpson J, Wong K, Jackman S, Schein J, Jones S, Birol I: ABySS: a parallel assembler for short read sequence data. Genome Res. 2009, 19: 1117-10.1101/gr.089532.108.
Article PubMed CAS PubMed Central Google Scholar
Heber S, Alekseyev M, Sze S, Tang H, Pevzner P: Splicing graphs and EST assembly problem. Bioinformatics. 2002, 18: 181-188.
Article Google Scholar
Xing Y, Resch A, Lee C: The multiassembly problem: reconstructing multiple transcript isoforms from EST fragment mixtures. Genome Res. 2004, 14: 426-10.1101/gr.1304504.
Article PubMed CAS PubMed Central Google Scholar
Sammeth M, Valiente G, Guigo R: Bubbles: alternative splicing events of arbitrary dimension in splicing graphs. Lecture Notes Comput Sci. 2008, 4955: 372-10.1007/978-3-540-78839-3_32.
Article Google Scholar
Harrington E, Bork P: Sircah: a tool for the detection and visualization of alternative transcripts. Bioinformatics. 2008, 24: 1959-10.1093/bioinformatics/btn361.
Article PubMed CAS Google Scholar
Bonizzoni P, Mauri G, Pesole G, Picardi E, Pirola Y, Rizzi R: Detecting alternative gene structures from spliced ESTs: a computational approach. J Comput Biol. 2009, 16: 43-66. 10.1089/cmb.2008.0028.
Article PubMed CAS Google Scholar
Labadorf A, Link A, Rogers M, Thomas J, Reddy A, Ben-Hur A: Genome-wide analysis of alternative splicing in Chlamydomonas reinhardtii. BMC Genomics. 2010, 11: 114-10.1186/1471-2164-11-114.
Article PubMed PubMed Central Google Scholar
Richardson D, Rogers M, Labadorf A, Ben-Hur A, Guo H, Paterson A, Reddy A: Comparative analysis of serine/arginine-rich proteins across 27 eukaryotes: insights into subfamily classification and extent of alternative splicing. PLoS ONE. 2011, 6: e24542-10.1371/journal.pone.0024542.
Article PubMed CAS PubMed Central Google Scholar
Zenoni S, Ferrarini A, Giacomelli E, Xumerle L, Fasoli M, Malerba G, Bellin D, Pezzotti M, Delledonne M: Characterization of transcriptional complexity during berry development in Vitis vinifera using RNA-Seq. Plant Physiol. 2010, 152: 1787-10.1104/pp.109.149716.
Article PubMed CAS PubMed Central Google Scholar
Reddy A: Alternative splicing of pre-messenger RNAs in plants in the genomic era. Annu Rev Plant Biol. 2007, 58: 267-294. 10.1146/annurev.arplant.58.032806.103754.
Article PubMed CAS Google Scholar
Wang B, Brendel V: Genomewide comparative analysis of alternative splicing in plants. Proc Natl Acad Sci USA. 2006, 103: 7175-10.1073/pnas.0602039103.
Article PubMed CAS PubMed Central Google Scholar
Kim E, Magen A, Ast G: Different levels of alternative splicing among eukaryotes. Nucleic Acids Res. 2007, 35: 125-10.1093/nar/gkm529.
Article PubMed CAS PubMed Central Google Scholar
Boguski M, Lowe T, Tolstoshev C: dbEST-database for "expressed sequence tags". Nat Genet. 1993, 4: 332-333. 10.1038/ng0893-332.
Article PubMed CAS Google Scholar
PlantGDB http://plantgdb.org/
Wu T, Watanabe C: GMAP: a genomic mapping and alignment program for mRNA and EST sequences. Bioinformatics. 2005, 21: 1859-10.1093/bioinformatics/bti310.
Article PubMed CAS Google Scholar
Montgomery S, Sammeth M, Gutierrez-Arcelus M, Lach R, Ingle C, Nisbett J, Guigo R, Dermitzakis E: Transcriptome genetics using second generation sequencing in a Caucasian population. Nature. 2010, 464: 773-777. 10.1038/nature08903.
Article PubMed CAS Google Scholar
Blencowe B, Ahmad S, Lee L: Current-generation high-throughput sequencing: deepening insights into mammalian transcriptomes. Genes Dev. 2009, 23: 1379-10.1101/gad.1788009.
Article PubMed CAS Google Scholar
Huang W, Khatib H: Comparison of transcriptomic landscapes of bovine embryos using RNA-Seq. BMC Genomics. 2010, 11: 711-10.1186/1471-2164-11-711.
Article PubMed CAS PubMed Central Google Scholar
Wang L, Xi Y, Yu J, Dong L, Yen L, Li W: A statistical method for the detection of alternative splicing using RNA-Seq. PLoS ONE. 2010, 5: e8529-10.1371/journal.pone.0008529.
Article PubMed PubMed Central Google Scholar
Richard H, Schulz M, Sultan M, Nürnberger A, Schrinner S, Balzereit D, Dagand E, Rasche A, Lehrach H, Vingron M, Haas S, Yaspo M: Prediction of alternative isoforms from exon expression levels in RNA-Seq experiments. Nucleic Acids Res. 2010, 38: e112-10.1093/nar/gkq041.
Swarbreck D, Wilks C, Lamesch P, Berardini T, Garcia-Hernandez M, Foerster H, Li D, Meyer T, Muller R, Ploetz L, Radenbaugh A, Singh S, Swing V, Tissier C, Zhang P, Huala E: The Arabidopsis Information Resource (TAIR): gene structure and function annotation. Nucleic Acids Res. 2008, 36: D1009-
Article PubMed CAS PubMed Central Google Scholar
Palusa S, Ali G, Reddy A: Alternative splicing of pre-mRNAs of Arabidopsis serine/arginine-rich proteins: regulation by hormones and stresses. Plant J. 2007, 49: 1091-10.1111/j.1365-313X.2006.03020.x.
Article PubMed CAS Google Scholar
Barrett T, Troup DB, Wilhite SE, Ledoux P, Evangelista C, Kim IF, Tomashevsky M, Marshall KA, Phillippy KH, Sherman PM, Muertter RN, Holko M, Ayanbule O, Yefanov A, Andrey , Soboleva : NCBI GEO: archive for functional genomics data sets-10 years on. Nucleic Acids Res. 2011, 39: D1005-D1010. 10.1093/nar/gkq1184.
Eilbeck K, Mungall C, Lewis S, Ashburner M: The Sequence Ontology Project 2009. [http://www.sequenceontology.org/gff3.shtml]
Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R: The sequence alignment/map format and SAMtools. Bioinformatics. 2009, 25: 2078-10.1093/bioinformatics/btp352.
Article PubMed PubMed Central Google Scholar
Rätsch G, Sonnenburg S: Accurate splice site detection for Caenorhabditis elegans. Kernel Methods in Computational Biology. Edited by: Schölkopf B, Tsuda K, Vert JP. 2004, MIT Press, 277-
Google Scholar
Rätsch G, Sonnenburg S, SchÄolkopf B: RASE: recognition of alternatively spliced exons in C. elegans. Bioinformatics. 2005, 21: i369-i377. 10.1093/bioinformatics/bti1053.
Article PubMed Google Scholar
Ben-Hur A, Ong C, Sonnenburg S, Schölkopf B, Rätsch G: Support vector machines and kernels for computational biology. PLoS Comput Biol. 2008, 4: e1000173-10.1371/journal.pcbi.1000173.
Article PubMed PubMed Central Google Scholar
PyML-machine learning in Python. [http://pyml.sourceforge.net/]
Page 2
AS
AS events
genes
IR
ES
Alt. 5'
Alt. 3'
Total
A. thalianamodels
4,029
1,987 (33%)
550 (9%)
1,256 (21%)
2,145 (36%)
5,938
SpliceGrapher
No ESTs
4,901
2,248 (30%)
714 (10%)
1,560 (21%)
2,866 (39%)
7,388
Novel
885
308 (21%)
164 (11%)
304 (20%)
721 (48%)
1,497
With ESTs
6,162
3,658 (33%)
994 (9%)
2,335 (21%)
4,128 (37%)
9,916
Novel
2,154
1,779 (34%)
444 (8%)
1,079 (20%)
1,983 (38%)
5,285
Cufflinks
No gene models
1,263
449 (32%)
383 (28%)
237 (17%)
319 (23%)
1,388
Novel
699
429 (32%)
380 (28%)
232 (17%)
304 (23%)
1,345
With gene models
6,056
4,029 (39%)
2,857 (27%)
1,427 (14%)
2,106 (20%)
10,419
Novel
2,319
2,232 (38%)
2,550 (43%)
552 (9%)
594 (10%)
5,928
TAU
No gene models
2,777
893 (17%)
475 (9%)
1,481 (27%)
2,555 (47%)
5,404
Novel
1,591
811 (16%)
460 (9%)
1,431 (28%)
2,351 (47%)
5,053
With gene models
10,458
94,571 (85%)
598 (1%)
5,972 (5%)
9,820 (9%)
110,961
Novel
8,364
94,124 (86%)
476 (0%)
5,697 (5%)
9,219 (8%)
109,516
V. viniferamodels
0
0 (0%)
0 (0%)
0 (0%)
0 (0%)
0
SpliceGrapher
2,039
347 (13%)
830 (31%)
640 (24%)
838 (32%)
2,655
TAU
No gene models
3,099
531 (10%)
684 (13%)
1,321 (25%)
2,743 (52%)
5,279
With gene models
15,874
135,585 (72%)
4,938 (3%)
23,615 (13%)
24,406 (13%)
188,544
Cufflinks
No gene models
1,057
324 (24%)
519 (39%)
140 (11%)
349 (26%)
1,332
With gene models
4,263
4,120 (34%)
3,148 (26%)
2,165 (18%)
2,818 (23%)
12,251
The number of AS events detected by SpliceGrapher, Cufflinks, and TAU compared with events inferred from the TAIR9 annotations. We track the following AS event types: intron retention (IR), exon skipping (ES), alternative 5' sites (Alt. 5') and alternative 3' sites (Alt. 3'). SpliceGrapher uses the TAIR9 gene models as a baseline, so it includes all of the same AS events along with additional events inferred from RNA-Seq data. Without gene models, nearly all TAU and Cufflinks predictions are novel AS events. With gene models, more than half of Cufflinks predictions reproduce AS events from the gene models. TAU uses known splice sites to predict all possible exons in a gene, generating vast numbers of novel exons and novel IR events.
