RNA-Seq 101

RNA-Seq, one of the applications of Next-gen sequencing technologies, has completely changed the landscape of how we study gene expression. Here is our effort to compile all basic and review papers focus on RNA-Seq technology and applications of RNA-Seq technology.

Early Papers on RNA-Seq

  1. The Transcriptional Landscape of the Yeast Genome Defined by RNA Sequencing, Ugrappa Nagalakshmi, Zhong Wang, Karl Waern, Chong Shou, Debasish Raha, Mark Gerstein, and Michael Snyder,  Science.  June 6; 320(5881): 1344–1349, 2008. [Cited:335]
  2. Mapping and quantifying mammalian transcriptomes by RNA-Seq, Mortazavi A, Williams BA, McCue K, Schaeffer L, Wold B., Nat Methods. Jul;5(7):621-8, 2008. [Cited: 695]
  3. RNA-seq: an assessment of technical reproducibility and comparison with gene expression arrays, Marioni JC, Mason CE, Mane SM, Stephens M, Gilad Y., Genome Res.  Sep;18(9):1509-17,2008. [Cited: 299]
  4. Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation, Trapnell C, Williams BA, Pertea G, Mortazavi A, Kwan G, van Baren MJ, Salzberg SL, Wold BJ, Pachter L. Nat Biotechnol. 2010 May; 28(5): 511–515, 2010. [Cited: 235]

RNA-Seq Review Papers

  1. RNA-Seq: a revolutionary tool for transcriptomics. Zhong Wang, Mark Gerstein & Michael Snyder, Nature Reviews Genetics 10, 57-63 , 2009 [Cited:467]
  2. RNA-Seq—quantitative measurement of expression through massively parallel RNA-sequencing Brian T. Wilhelma and Josette-Renée Landryb, Methods Volume 48, Issue 3,  249–257, 2009
  3. Genome-wide allele-specific analysis: insights into regulatory variation, Pastinen T., Nat Rev Genet. 2010 Aug;11(8):533-8
  4. Next-Generation transcriptome assembly. Jeffrey A. Martin & Zhong Wang Nature Reviews Genetics 12, 671-682, 2011
  5. RNA sequencing: advances, challenges and opportunities Fatih Ozsolak & Patrice M. Milos, Nature Reviews Genetics 12, 87-98, 2011
  6. Computation for ChIP-seq and RNA-seq studies, Pepke S, Wold B, Mortazavi A., Nat Methods.  Nov;6; 11 Suppl; 2009

RNA-Seq Method Papers

  1. TopHat: discovering splice junctions with RNA-Seq, Cole Trapnell, Lior Pachter and Steven L. Salzberg, Bioinformatics 25 (9): 1105-1111. 2009 [Cited: 296]
  2. How to map billions of short reads onto genomes, Trapnell C, Salzberg SL, Nat Biotechnol.  May;27(5):455-7, 2009.
  3. RNA-Seq gene expression estimation with read mapping uncertainty, Li B, Ruotti V, Stewart RM, Thomson JA, Dewey CN., Bioinformatics.  Feb 15;26(4):493-500, 2010 [Cited:46]
  4. Differential expression analysis for sequence count data, Anders S and Huber W., Genome Biol. 2010;11(10):R106 [Cited:151]
  5. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data, Robinson MD, McCarthy DJ, and Smyth GK, Bioinformatics. 2010 Jan 1;26(1):139-40. [Cited: 137]
  6. Evaluation of statistical methods for normalization and differential expression in mRNA-Seq experiments. Bullard JH, Purdom E, Hansen KD, Dudoit S. BMC Bioinformatics. 2010 Feb 18;11:94.
  7. Statistical design and analysis of RNA sequencing data. Auer PL and Doerge RW, Genetics. 2010 Jun;185(2):405-16.
  8. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genomeBo Li and Colin N Dewey, BMC Bioinformatics12:323, 2011
  9. Estimation of alternative splicing isoform frequencies from RNA-Seq data, Nicolae M, Mangul S, Măndoiu II, Zelikovsky A., Algorithms Mol Biol. 2011 Apr 19;6(1):9.
  10. Identification of novel transcripts in annotated genomes using RNA-Seq, Roberts A, Pimentel H, Trapnell C, Pachter L. Bioinformatics. Sep 1;27(17):2325-9, 2011 [Cited:14]
  11. Comparative analysis of RNA-Seq alignment algorithms and the RNA-Seq unified mapper (RUM), Grant GR, Farkas MH, Pizarro AD, Lahens NF, Schug J, Brunk BP, Stoeckert CJ, Hogenesch JB, Pierce EA., Bioinformatics. 2011 Sep 15;27(18):2518-28
  12. Improving RNA-Seq expression estimates by correcting for fragment bias, Adam Roberts, Cole Trapnell, Julie Donaghey, John L Rinn and Lior Pachter, Genome Biology 12:R22,  2011. [Cited:30]
  13. Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks., Trapnell C, Roberts A, Goff L, Pertea G, Kim D, Kelley DR, Pimentel H, Salzberg SL, Rinn JL, Pachter L., Nat Protoc. , Mar 1;7(3):562-78, 2012.
  14. Models for transcript quantification from RNA-Seq, Lior Pachter, preprint arXiv 2012,
  15. Detecting differential usage of exons from RNA-seq data, Anders S, Reyes A, Huber W., Genome Res. 2012 Oct;22(10):2008-17
  16. STAR: ultrafast universal RNA-seq aligner, Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, Batut P, Chaisson M, Gingeras TR. Bioinformatics. 2012 Oct 25. [Epub ahead of print]
  17. Differential analysis of gene regulation at transcript resolution with RNA-seq, Trapnell C, Hendrickson DG, Sauvageau M, Goff L, Rinn JL, Pachter L., Nat Biotechnol. Dec 9, 2012
  18. Ab initio construction of a eukaryotic transcriptome by massively parallel mRNA sequencing, Yassour M, Kaplan T, Fraser HB, Levin JZ, Pfiffner J, Adiconis X, Schroth G, Luo S, Khrebtukova I, Gnirke A, Nusbaum C, Thompson DA, Friedman N, Regev A. Proc Natl Acad Sci U S A. Mar 3;106(9):3264-9, 2009. [Cited: 42]

Expression QTL Papers Using RNA-Seq Data

  1. Understanding mechanisms underlying human gene expression variation with RNA sequencing, Pickrell JK, Marioni JC, Pai AA, Degner JF, Engelhardt BE, Nkadori E,  Veyrieras J-B, Stephens M, Gilad Y, Pritchard JK. .Nature. Apr 1;464(7289):768-72, 2010 [Cited: 111]
  2. Transcriptome genetics using second generation sequencing in a Caucasian population, Montgomery SB, Sammeth M, Gutierrez-Arcelus M, Lach RP, Ingle C, Nisbett J, Guigo R, Dermitzakis ET., Nature.  Apr 1;464(7289):773-7, 2010 [Cited: 94]

RNA Editing Papers using RNA-Seq Data

  1. Widespread RNA and DNA sequence differences in the human transcriptomeLi MWang IXLi YBruzel ARichards ALToung JMCheung VGScience. Jul 1;333(6038):53-8, 2011
  2. Comment on “Widespread RNA and DNA sequence differences in the human transcriptome”. [Science. 2012]
  3. Comment on “Widespread RNA and DNA sequence differences in the human transcriptome”. [Science. 2012]
  4. Comment on “Widespread RNA and DNA sequence differences in the human transcriptome”. [Science. 2012]
  5. RNA editing in the human ENCODE RNA-seq data. Park E, Williams B, Wold BJ, Mortazavi A. Genome Res. 2012 Sep;22(9):1626-33. doi: 10.1101/gr.134957.111.
  6. Accurate identification of human Alu and non-AluRNA editing sites, Ramaswami G, Lin W, Piskol R, Tan MH, Davis C, and Li JB, Nat Methods. 2012 Jun;9(6):579-81

RNA-Seq Papers on Genomic Imprinting

  1. High Resolution Analysis of Parent-of-Origin Allelic Expression in the Mouse Brain, Gregg, C., Zhang, J., Weissbourd, B., Luo, S., Schroth, G.P., Haig, D. and Dulac, C.  Science329: 643- 648, 2010 [Cited: 59]
  2. Sex-Specific Parent-of-Origin Allelic expression in the Mouse Brain. Gregg, C., Zhang, J., Butler, J.E., Haig, D. and Dulac, C.  Science329: 682- 685, 2010 [Cited:39]
  3. A survey for novel imprinted genes in the mouse placenta by mRNA-seq,  Wang X, Soloway PD, and Clark AG, Genetics. 2011 Sep;189(1):109-22
  4. Critical evaluation of imprinted gene expression by RNA-Seq: a new perspective, DeVeale B, van der Kooy D, and Babak T. PLoS Genet. 2012;8(3):e1002600