A review on the processing and analysis of next-generation RNA-seq data

Progress in Biochemistry and Biophysics

Volumn 37, Issue 8, 2010, Pages 834-846

  Wang, Xi ^a   Wang, Xiao Wo ^a   Wang, Li Kun ^a,b   Feng, Zhi Xing ^a   Zhang, Xue Gong ^a  

^a TSINGHUA UNIVERSITY   (China)

^b JILIN UNIVERSITY   (China)

Author keywords

Bioinformatics; Data processing and analysis; Gene expression; High throughput rna sequencing; Transcriptome

Indexed keywords

EID: 78649235146     PISSN: 10003282     EISSN: None     Source Type: Journal    
DOI: 10.3724/SP.J.1206.2009.00151     Document Type: Review

References (88)

1. Marioni J C, Mason C E, Mane S M, et al. RNA-seq: an assessment of technical reproducibility and comparison with gene expression arrays. Genome Res, 2008, 18(9): 1509-1517
2. Mortazavi A, Williams B A, McCue K, et al. Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nat Methods, 2008, 5(7): 621-628 (Pubitemid 351911867)
3. Nagalakshmi U, Wang Z, Waern K, et al. The transcriptional landscape of the yeast genome defined by RNA sequencing. Science, 2008, 320(5881): 1344-1349 (Pubitemid 351929471)
4. Sultan M, Schulz M H, Richard H, et al. A global view of gene activity and alternative splicing by deep sequencing of the human transcriptome. Science, 2008, 321(5891): 956-960
5. Wang E T, Sandberg R, Luo S, et al. Alternative isoform regulation in human tissue transcriptomes. Nature, 2008, 456(7221): 470-476 (Pubitemid 352759009)
6. Birzele F, Schaub J, Rust W, et al. Into the unknown: expression profiling without genome sequence information in CHO by next generation sequencing. Nucleic Acids Res, 2010, doi:10.1093/nar/gkq116
7. Sanger F, Nicklen S, Coulson A R. DNA sequencing with chainterminating inhibitors. Proc Natl Acad Sci USA, 1977, 74(12): 5463-5467
8. Margulies M, Egholm M, Altaian W E, et al. Genome sequencing in microfabricated high-density picolitre reactors. Nature, 2005, 437(7057): 376-380
9. Shendure J, Ji H. Next-generation DNA sequencing. Nat Biotechnol, 2008, 26(10): 1135-1145
10. Ruparel H, Bi L, Li Z, et al. Design and synthesis of a 3'-O-allyl photocleavable fluorescent nucleotide as a reversible terminator for DNA sequencing by synthesis. Proc Natl Acad Sei USA, 2005, 102(17): 5932-5937 (Pubitemid 40594232)
11. Seo T S, Bai X, Kim D H, et al. Four-color DNA sequencing by synthesis on a chip using photocleavable fluorescent nucleotides. Proc Natl Acad Sci USA, 2005, 102(17): 5926-5931 (Pubitemid 40594231)
12. Ju J, Kim D H, Bi L, et al. Four-color DNA sequencing by synthesis using cleavable fluorescent nucleotide reversible terminators. Proc Natl Acad Sci USA, 2006, 103(52): 19635-19640 (Pubitemid 46037483)
13. Fedurco M, Romieu A, Williams S, et al. BTA, a novel reagent for DNA attachment on glass and efficient generation of solid-phase amplified DNA colonies. Nucleic Acids Res, 2006, 34(3): e22 (Pubitemid 43380696)
14. Shendure J A, Porreca G J, Church G M. Overview of DNA sequencing strategies//Ausubel F M, Brent R, Kingston R E, et al. Current Protocols in Molecular Biology. USA: John Wiley and Sons, Inc., 2008: Unit 7.1
15. Mardis E R. Next-generation DNA sequencing methods. Annu Rev Genomics Hum Genet, 2008, 9: 387-402
16. Fuller C W, Middendorf L R, Benner S A, et al. The challenges of sequencing by synthesis. Nat Biotechnol, 2009, 27(11): 1013-1023
17. Croucher N J, Fookes M C, Perkins T T, et al. A simple method for directional transcriptome sequencing using Illumina technology. Nucleic Acids Res, 2009,37(22): e148
18. Parkhomchuk D, Borodina T, Amstislavskiy V, et al. Transcriptome analysis by strand-specific sequencing of complementary DNA. Nucleic Acids Res, 2009, 37(18): e123
19. Perkins T T, Kingsley R A, Fookes M C, et al. A strand-specific RNA-Seq analysis of the transcriptome of the typhoid bacillus Salmonella typhi. PLoS Genet, 2009, 5(7): e1000569
20. Mamanova L, Andrews R M, James K D, et al. FRT-seq: amplification-free, strand-specific transcriptome sequencing. Nat Methods, 2010, 7(2): 130-132
21. Cock P J, Fields C J, Goto N, et al. The Sanger FASTQ file format for sequences with quality scores, and the Solexa/Illumina FASTQ variants. Nucleic Acids Res, 2010, 38(6): 1767-1771
22. Shumway M, Cochrane G, Sugawara H. Archiving next generation sequencing data. Nucleic Acids Res, 2009, 38 (Database issue): D870-871
23. Kaminuma E, Mashima J, Kodama Y, et al. DDBJ launches a new archive database with analytical tools for next-generation sequence data. Nucleic Acids Res, 2009, 38(Database issue): D33-38
24. Trapnell C, Salzberg S L. How to map billions of short reads onto genomes. Nat Biotechnol, 2009, 27(5): 455-457
25. Burrows M, Wheeler D J. A Block Sorting Lossless Data Compression Algorithm [M/OL]. Technical Report 124. Digital Systems Research Center, 1994. http://Citeseerx.ist.psu.edu/viewdoc/summary?(doi=10.1.1.37.6774)
26. Li H, Ruan J, Durbin R. Mapping short DNA sequencing reads and calling variants using mapping quality scores. Genome Res, 2008, 18(11): 1851-1858
27. Langmead B, Trapnell C, Pop M, et al. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol, 2009, 10(3): R25
28. Flicek P, Bimey E. Sense from sequence reads: methods for alignment and assembly. Nat Methods, 2009, 6(11 Suppl): S6-S12
29. Smith T F, Waterman M S. Identification of common molecular subsequences. J Mol Biol, 1981, 147(1): 195-197
30. Homer N, Merriman B, Nelson S F. BFAST: an alignment tool for large scale genome resequencing. PLoS One, 2009, 4(11): e7767
31. Rumble S M, Lacroute P, Dalca A V, et al. SHRiMP: accurate mapping of short color-space reads. PLoS Comput Biol, 2009, 5(5): e1000386
32. Li H, Durbin R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics, 2009, 25(14): 1754-1760
33. Lin H, Zhang Z, Zhang M Q, et al. ZOOM! Zillions of oligos mapped. Bioinformatics, 2008, 24(21): 2431-2437
34. Li R, Yu C, Li Y, et al. SOAP2: an improved ultrafast tool for short read alignment. Bioinformatics, 2009, 25(15): 1966-1967
35. Weese D, Emde A K, Rausch T, et al. RazerS-fast read mapping with sensitivity control. Genome Res, 2009, 19(9): 1646-1654
36. Trapnell C, Pachter L, Salzberg S L. TopHat: discovering splice junctions with RNA-Seq. Bioinformatics, 2009, 25(9): 1105-1111
37. Denoeud F, Aury J M, Da Silva C, et al. Annotating genomes with massive-scale RNA sequencing. Genome Biol, 2008, 9(12): R175
38. Li B, Ruotti V, Stewart R M, et al. RNA-Seq gene expression estimation with read mapping uncertainty. Bioinformatics, 2010, 26(4): 493-500
39. Li H, Handsaker B, Wysoker A, et al. The sequence alignment/ map format and SAMtools. Bioinformatics, 2009, 25(16): 2078-2079
40. Wang Z, Gerstein M, Snyder M. RNA-Seq: a revolutionary tool for transcriptomics. Nat Rev Genet, 2009, 10(1): 57-63
41. Shendure J. The beginning of the end for microarrays?. Nat Methods, 2008, 5(7): 585-587
42. ' t Hoen P A, Ariyurek Y, Thygesen H H, et al. Deep sequencing-based expression analysis shows major advances in robustness, resolution and inter-lab portability over five microarray platforms. Nucleic Acids Res, 2008, 36(21): e141
43. Jiang H, Wong W H. Statistical inferences for isoform expression in RNA-Seq. Bioinformatics, 2009, 25(8): 1026-1032
44. Wang L, Feng Z, Wang X, et al. DEGseq: an R package for identifying differentially expressed genes from RNA-seq data. Bioinformatics, 2010, 26(1): 136-138
45. Trapnell C, Williams B A, Pertea G, et al. Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat Biotechnol, 2010, 28(5): 511-515
46. Dohm J C, Lottaz C, Borodina T, et al. Substantial biases in ultra-short read data sets from high-throughput DNA sequencing. Nucleic Acids Res, 2008, 36(16): e105
47. Li J, Jiang H, Wong W H. Modeling non-uniformity in short-read rates in RNA-Seq data. Genome Biol, 2010, 11(5): R50
48. Hansen K D, Brenner S E, Dudoit S. Biases in Illumina transcriptome sequencing caused by random hexamer priming. Nucleic Acids Res, 2010, doi:10.1093/nar/gkq 224
49. Pan Q, Shai O, Lee L J, et al. Deep surveying of alternative splicing complexity in the human transcriptome by high-throughput sequencing. Nat Genet, 2008, 40(12): 1413-1415
50. Wang L, Xi Y, Yu J, et al. A statistical method for the detection of alternative splicing using RNA-seq. PLoS One, 2010, 5(1): e8529
51. Blekhman R, Marioni J C, Zumbo P, et al. Sex-specific and lineage-specific alternative splicing in primates. Genome Res, 2010, 20(2): 180-189
52. Feng J, Li W, Jiang T. Inference of isoforms from short sequence reads//Proc. 14th Annual International Conference on Research in Computational Molecular Biology (RECOMB), Lisbon, Portugal, 2010: 138-157
53. Hiller D, Jiang H, Xu W, et al. Identifiability of isoform deconvolution from junction arrays and RNA-Seq. Bioinformatics, 2009, 25(23): 3056-3059
54. Nix D A, Courdy S J, Boucher K M. Empirical methods for controlling false positives and estimating confidence in ChIP-Seq peaks. BMC Bioinformatics, 2008, 9: 523
55. Kent W J, Sugnet C W, Furey T S, et al. The human genome browser at UCSC. Genome Res, 2002, 12(6): 996-1006
56. Ji H, Jiang H, Ma W, et al. An integrated software system for analyzing ChIP-chip and ChIP-seq data. Nat Biotechnol, 2008, 26(11): 1293-1300
57. Durinck S, Bullard J, Spellman P T, et al. GenomeGraphs: integrated genomic data visualization with R. BMC Bioinformatics, 2009, 10: 2
58. Quinlan A R, Hall I M. BEDTools: A flexible suite of utilities for comparing genomic features. Bioinformatics, 2010, 26(6): 841-842
59. Blankenberg D, Taylor J, Schenck I, et al. A framework for collaborative analysis of ENCODE data: making large-scale analyses biologist-friendly. Genome Res, 2007, 17(6): 960-964 (Pubitemid 46919731)
60. Taylor J, Schenck I, Blankenberg D, et al. Using galaxy to perform large-scale interactive data analyses//Baxevanis A D, Stein L D, Stormo G D, et al. Current Protocols in Bioinformatics. USA: John Wiley and Sens, Inc., 2007, Unit 10.5
61. Zerbino D R, Birney E. Velvet: algorithms for de novo short read assembly using de Bruijn graphs. Genome Res, 2008, 18(5): 821-829 (Pubitemid 351645072)
62. Birol I, Jackman S D, Nielsen C B, et al. De novo transcriptome assembly with ABySS. Bioinformatics, 2009, 25(21): 2872-2877
63. Katayama S, Tomaru Y, Kasukawa T, et al. Antisense transcription in the mammalian transcriptome. Science, 2005, 309(5740): 1564-1566
64. Cloonan N, Xu Q, Faulkner G J, et al. RNA-MATE: a recursive mapping strategy for high-throughput RNA-sequencing data. Bioinformatics, 2009, 25(19): 2615-2616
65. Levin J Z, Berger M F, Adiconis X, et al. Targeted next-generation sequencing of a cancer transcriptome enhances detection of sequence variants and novel fusion transcripts. Genome Biol, 2009, 10(10): R115
66. Pickrell J K, Marioni J C, Pai A A, et al. Understanding mechanisms underlying human gene expression variation with RNA sequencing. Nature, 2010, 464(7289): 768-772
67. Montgomery S B, Sammeth M, Gutierrez-Arcelus M, et al. Transcriptome genetics using second generation sequencing in a Caucasian population. Nature, 2010, 464(7289): 773-777
68. Li J B, Levanon E Y, Yoon J K, et al. Genome-wide identification of human RNA editing sites by parallel DNA capturing and sequencing. Science, 2009,324(5931): 1210-1213
69. Friedlander M R, Chen W, Adamidi C, et al. Discovering microRNAs from deep sequencing data using miRDeep. Nat Biotechnol, 2008, 26(4): 407-415 (Pubitemid 351501815)
70. Oshlack A, Wakefield M J. Transcript length bias in RNA-seq data confounds systems biology. Biol Direct, 2009, 4: 14
71. Young M D, Wakefield M J, Smyth G K, et al. Gene ontology analysis for RNA-seq: accounting for selection bias. Genome Biol, 2010, 11(2): R14
72. Bloom J S, Khan Z, Kruglyak L, et al. Measuring differential gene expression by short read sequencing: quantitative comparison to 2-channel gene expression microarrays. BMC Genomics, 2009, 10: 221
73. Robinson M D, McCarthy D J, Smyth G K. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics, 2010, 26(1): 139-140
74. Zheng S, Chen L, A hierarchical Bayesian model for comparing transcriptomes at the individual transcript isoform level. Nucleic Acids Res, 2009, 37(10): e75
75. Richard H, Schulz M H, Sultan M, et al. Prediction of alternative isoforms from exon expression levels in RNA-Seq experiments. Nucleic Acids Res, 2010, doi:10.1093/nar/gkq 041
76. Zhang X, Lu X, Shi Q, et al. Recursive SVM feature selection and sample classification for mass-spectrometry and microarray data. BMC Bioinformatics, 2006, 7: 197
77. Guyon I, Weston J, Barnhill S, et al. Gene selection for cancer classification using support vector machines. Machine Learning, 2002, 46(1): 389-422 (Pubitemid 34129977)
78. Ashburner M, Ball C A, Blake J A, et al. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet, 2000, 25(1): 25-29
79. Zeeberg B R, Feng W, Wang G, et al. GoMiner: a resource for biological interpretation of genomic and proteomic data. Genome Biol, 2003, 4(4): R28
80. Dennis G, Jr., Sherman B T, Hosack D A, et al. DAVID: Database for annotation, visualization, and integrated discovery. Genome Biol, 2003, 4(5): P3
81. Hu Z, Hung J H, Wang Y, et al. VisANT 3.5: multi-scale network visualization, analysis and inference based on the gene ontology. Nucleic Acids Res, 2009, 37(Web Server issue): W115-121
82. Wold B, Myers R M. Sequence census methods for functional genomics. Nat Methods, 2008, 5(1): 19-21
83. Li R, Fan W, Tian G, et al. The sequence and de novo assembly of the giant panda genome. Nature, 2010, 463(7279): 311-317
84. Wang J, Wang W, Li R, et al. The diploid genome sequence of an Asian individual. Nature, 2008, 456(7218): 60-65
85. Mardis E R. ChIP-seq: welcome to the new frontier. Nat Methods, 2007, 4(8): 613-614
86. Park P J. ChIP-seq: advantages and challenges of a maturing technology. Nat Rev Genet, 2009, 10(10): 669-680
87. Brunner A L, Johnson D S, Kim S W, et al. Distinct DNA methylation patterns characterize differentiated human embryonic stem cells and developing human fetal liver. Genome Res, 2009, 19(6): 1044-1056
88. Deng J, Shoemaker R, Xie B, et al. Targeted bisulfite sequencing reveals changes in DNA methylation associated with nuclear reprogramming. Nat Biotechnol, 2009, 27(4): 353-360