Abstract
The transcriptome encompasses a range of species including messenger RNA, and other noncoding RNA such as rRNA, tRNA, and short and long noncoding RNAs. Due to the huge role played by mRNA in development and disease, several methods have been developed to sequence and characterize mRNA, with RNA sequencing (RNA-Seq) emerging as the current method of choice particularly for large high-throughput studies. Short-read RNA-Seq which involves sequencing of short cDNA fragments and computationally assembling them to reconstruct the transcriptome, or aligning them to a reference is the most widely used approach. However, due to inherent limitations of this approach in de novo transcriptome assembly and isoform quantification, long-read RNA-Seq approaches, which also happen to be single molecule sequencing approaches, are increasingly becoming the standard for de novo transcriptome assembly and isoform quantification. In this chapter, we review the technical aspects of the current methods of RNA-Seq, both short and long-read approaches, and data analysis methods available. We discuss recent advances in single-cell RNA-Seq and direct RNA-Seq approaches, which perhaps will dominate the future of RNA-Seq.
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References
Brenner S, Jacob F, Meselson M (1961) An unstable intermediate carrying information from genes to ribosomes for protein synthesis. Nature 190:576–581
Alwine JC, Kemp DJ, Stark GR (1977) Method for detection of specific RNAs in agarose gels by transfer to diazobenzyloxymethyl-paper and hybridization with DNA probes. Proc Natl Acad Sci U S A 74(12):5350–5354
Woods D, Crampton J, Clarke B, Williamson R (1980) The construction of a recombinant cDNA library representative of the poly(A)+ mRNA population from normal human lymphocytes. Nucleic Acids Res 8(22):5157–5168
Adams MD, Kelley JM, Gocayne JD, Dubnick M, Polymeropoulos MH, Xiao H, Merril CR, Wu A, Olde B, Moreno RF et al (1991) Complementary DNA sequencing: expressed sequence tags and human genome project. Science 252(5013):1651–1656
Adams MD, Dubnick M, Kerlavage AR, Moreno R, Kelley JM, Utterback TR, Nagle JW, Fields C, Venter JC (1992) Sequence identification of 2,375 human brain genes. Nature 355(6361):632–634. https://doi.org/10.1038/355632a0
Velculescu VE, Zhang L, Vogelstein B, Kinzler KW (1995) Serial analysis of gene expression. Science 270(5235):484–487
Schena M, Shalon D, Davis RW, Brown PO (1995) Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Science 270(5235):467–470
Mortazavi A, Williams BA, McCue K, Schaeffer L, Wold B (2008) Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nat Methods 5(7):621–628. https://doi.org/10.1038/nmeth.1226
Margulies M, Egholm M, Altman WE, Attiya S, Bader JS, Bemben LA, Berka J, Braverman MS, Chen YJ, Chen Z, Dewell SB, Du L, Fierro JM, Gomes XV, Godwin BC, He W, Helgesen S, Ho CH, Irzyk GP, Jando SC, Alenquer ML, Jarvie TP, Jirage KB, Kim JB, Knight JR, Lanza JR, Leamon JH, Lefkowitz SM, Lei M, Li J, Lohman KL, Lu H, Makhijani VB, McDade KE, McKenna MP, Myers EW, Nickerson E, Nobile JR, Plant R, Puc BP, Ronan MT, Roth GT, Sarkis GJ, Simons JF, Simpson JW, Srinivasan M, Tartaro KR, Tomasz A, Vogt KA, Volkmer GA, Wang SH, Wang Y, Weiner MP, Yu P, Begley RF, Rothberg JM (2005) Genome sequencing in microfabricated high-density picolitre reactors. Nature 437(7057):376–380. https://doi.org/10.1038/nature03959
Bentley DR, Balasubramanian S, Swerdlow HP, Smith GP, Milton J, Brown CG, Hall KP, Evers DJ, Barnes CL, Bignell HR, Boutell JM, Bryant J, Carter RJ, Keira Cheetham R, Cox AJ, Ellis DJ, Flatbush MR, Gormley NA, Humphray SJ, Irving LJ, Karbelashvili MS, Kirk SM, Li H, Liu X, Maisinger KS, Murray LJ, Obradovic B, Ost T, Parkinson ML, Pratt MR, Rasolonjatovo IM, Reed MT, Rigatti R, Rodighiero C, Ross MT, Sabot A, Sankar SV, Scally A, Schroth GP, Smith ME, Smith VP, Spiridou A, Torrance PE, Tzonev SS, Vermaas EH, Walter K, Wu X, Zhang L, Alam MD, Anastasi C, Aniebo IC, Bailey DM, Bancarz IR, Banerjee S, Barbour SG, Baybayan PA, Benoit VA, Benson KF, Bevis C, Black PJ, Boodhun A, Brennan JS, Bridgham JA, Brown RC, Brown AA, Buermann DH, Bundu AA, Burrows JC, Carter NP, Castillo N, Chiara ECM, Chang S, Neil Cooley R, Crake NR, Dada OO, Diakoumakos KD, Dominguez-Fernandez B, Earnshaw DJ, Egbujor UC, Elmore DW, Etchin SS, Ewan MR, Fedurco M, Fraser LJ, Fuentes Fajardo KV, Scott Furey W, George D, Gietzen KJ, Goddard CP, Golda GS, Granieri PA, Green DE, Gustafson DL, Hansen NF, Harnish K, Haudenschild CD, Heyer NI, Hims MM, Ho JT, Horgan AM, Hoschler K, Hurwitz S, Ivanov DV, Johnson MQ, James T, Huw Jones TA, Kang GD, Kerelska TH, Kersey AD, Khrebtukova I, Kindwall AP, Kingsbury Z, Kokko-Gonzales PI, Kumar A, Laurent MA, Lawley CT, Lee SE, Lee X, Liao AK, Loch JA, Lok M, Luo S, Mammen RM, Martin JW, McCauley PG, McNitt P, Mehta P, Moon KW, Mullens JW, Newington T, Ning Z, Ling Ng B, Novo SM, O’Neill MJ, Osborne MA, Osnowski A, Ostadan O, Paraschos LL, Pickering L, Pike AC, Pike AC, Chris Pinkard D, Pliskin DP, Podhasky J, Quijano VJ, Raczy C, Rae VH, Rawlings SR, Chiva Rodriguez A, Roe PM, Rogers J, Rogert Bacigalupo MC, Romanov N, Romieu A, Roth RK, Rourke NJ, Ruediger ST, Rusman E, Sanches-Kuiper RM, Schenker MR, Seoane JM, Shaw RJ, Shiver MK, Short SW, Sizto NL, Sluis JP, Smith MA, Ernest Sohna Sohna J, Spence EJ, Stevens K, Sutton N, Szajkowski L, Tregidgo CL, Turcatti G, Vandevondele S, Verhovsky Y, Virk SM, Wakelin S, Walcott GC, Wang J, Worsley GJ, Yan J, Yau L, Zuerlein M, Rogers J, Mullikin JC, Hurles ME, McCooke NJ, West JS, Oaks FL, Lundberg PL, Klenerman D, Durbin R, Smith AJ (2008) Accurate whole human genome sequencing using reversible terminator chemistry. Nature 456(7218):53–59. https://doi.org/10.1038/nature07517
Goodwin S, McPherson JD, McCombie WR (2016) Coming of age: ten years of next-generation sequencing technologies. Nat Rev Genet 17(6):333–351. https://doi.org/10.1038/nrg.2016.49
Liedtke W, Battistini L, Brosnan CF, Raine CS (1994) A comparison of methods for RNA extraction from lymphocytes for RT-PCR. PCR Methods Appl 4(3):185–187
Feng H, Zhang X, Zhang C (2015) mRIN for direct assessment of genome-wide and gene-specific mRNA integrity from large-scale RNA-sequencing data. Nat Commun 6:7816. https://doi.org/10.1038/ncomms8816
Schroeder A, Mueller O, Stocker S, Salowsky R, Leiber M, Gassmann M, Lightfoot S, Menzel W, Granzow M, Ragg T (2006) The RIN: an RNA integrity number for assigning integrity values to RNA measurements. BMC Mol Biol 7:3. https://doi.org/10.1186/1471-2199-7-3
Hedegaard J, Thorsen K, Lund MK, Hein AM, Hamilton-Dutoit SJ, Vang S, Nordentoft I, Birkenkamp-Demtroder K, Kruhoffer M, Hager H, Knudsen B, Andersen CL, Sorensen KD, Pedersen JS, Orntoft TF, Dyrskjot L (2014) Next-generation sequencing of RNA and DNA isolated from paired fresh-frozen and formalin-fixed paraffin-embedded samples of human cancer and normal tissue. PLoS One 9(5):e98187. https://doi.org/10.1371/journal.pone.0098187
Griffin M, Abu-El-Haija M, Abu-El-Haija M, Rokhlina T, Uc A (2012) Simplified and versatile method for isolation of high-quality RNA from pancreas. Biotechniques 52(5):332–334. https://doi.org/10.2144/0000113862
Pang X, Zhou D, Song Y, Pei D, Wang J, Guo Z, Yang R (2004) Bacterial mRNA purification by magnetic capture-hybridization method. Microbiol Immunol 48(2):91–96
Su C, Sordillo LM (1998) A simple method to enrich mRNA from total prokaryotic RNA. Mol Biotechnol 10(1):83–85. https://doi.org/10.1007/BF02745865
Yi H, Cho YJ, Won S, Lee JE, Jin Yu H, Kim S, Schroth GP, Luo S, Chun J (2011) Duplex-specific nuclease efficiently removes rRNA for prokaryotic RNA-seq. Nucleic Acids Res 39(20):e140. https://doi.org/10.1093/nar/gkr617
Dunman PM, Murphy E, Haney S, Palacios D, Tucker-Kellogg G, Wu S, Brown EL, Zagursky RJ, Shlaes D, Projan SJ (2001) Transcription profiling-based identification of Staphylococcus aureus genes regulated by the agr and/or sarA loci. J Bacteriol 183(24):7341–7353. https://doi.org/10.1128/JB.183.24.7341-7353.2001
McGrath KC, Thomas-Hall SR, Cheng CT, Leo L, Alexa A, Schmidt S, Schenk PM (2008) Isolation and analysis of mRNA from environmental microbial communities. J Microbiol Methods 75(2):172–176. https://doi.org/10.1016/j.mimet.2008.05.019
Davila Lopez M, Samuelsson T (2008) Early evolution of histone mRNA 3′ end processing. RNA (New York, NY) 14(1):1–10. https://doi.org/10.1261/rna.782308
Chang H, Lim J, Ha M, Kim VN (2014) TAIL-seq: genome-wide determination of poly(A) tail length and 3′ end modifications. Mol Cell 53(6):1044–1052. https://doi.org/10.1016/j.molcel.2014.02.007
Ares M Jr (2013) Fragmentation of whole-transcriptome RNA using E. coli RNase III. Cold Spring Harb Protoc 2013(5):479–481. https://doi.org/10.1101/pdb.prot074369
Wery M, Descrimes M, Thermes C, Gautheret D, Morillon A (2013) Zinc-mediated RNA fragmentation allows robust transcript reassembly upon whole transcriptome RNA-Seq. Methods 63(1):25–31. https://doi.org/10.1016/j.ymeth.2013.03.009
Zhu YY, Machleder EM, Chenchik A, Li R, Siebert PD (2001) Reverse transcriptase template switching: a SMART approach for full-length cDNA library construction. Biotechniques 30(4):892–897
Ramskold D, Luo S, Wang YC, Li R, Deng Q, Faridani OR, Daniels GA, Khrebtukova I, Loring JF, Laurent LC, Schroth GP, Sandberg R (2012) Full-length mRNA-Seq from single-cell levels of RNA and individual circulating tumor cells. Nat Biotechnol 30(8):777–782. https://doi.org/10.1038/nbt.2282
Hrdlickova R, Toloue M, Tian B (2017) RNA-Seq methods for transcriptome analysis. Wiley interdisciplinary reviews RNA 8(1). https://doi.org/10.1002/wrna.1364
Adiconis X, Borges-Rivera D, Satija R, DeLuca DS, Busby MA, Berlin AM, Sivachenko A, Thompson DA, Wysoker A, Fennell T, Gnirke A, Pochet N, Regev A, Levin JZ (2013) Comparative analysis of RNA sequencing methods for degraded or low-input samples. Nat Methods 10(7):623–629. https://doi.org/10.1038/nmeth.2483
Arezi B, Hogrefe HH (2007) Escherichia coli DNA polymerase III epsilon subunit increases Moloney murine leukemia virus reverse transcriptase fidelity and accuracy of RT-PCR procedures. Anal Biochem 360(1):84–91. https://doi.org/10.1016/j.ab.2006.10.009
McInerney P, Adams P, Hadi MZ (2014) Error rate comparison during polymerase chain reaction by DNA polymerase. Mol Biol Int 2014:287430. https://doi.org/10.1155/2014/287430
Pelechano V, Steinmetz LM (2013) Gene regulation by antisense transcription. Nat Rev Genet 14(12):880–893. https://doi.org/10.1038/nrg3594
Levin JZ, Yassour M, Adiconis X, Nusbaum C, Thompson DA, Friedman N, Gnirke A, Regev A (2010) Comprehensive comparative analysis of strand-specific RNA sequencing methods. Nat Methods 7(9):709–715. http://www.nature.com/nmeth/journal/v7/n9/abs/nmeth.1491.html#supplementary-information
Ball JK, Desselberger U (1992) The use of uracil-N-glycosylase in the preparation of PCR products for direct sequencing. Nucleic Acids Res 20(12):3255
Parkinson NJ, Maslau S, Ferneyhough B, Zhang G, Gregory L, Buck D, Ragoussis J, Ponting CP, Fischer MD (2012) Preparation of high-quality next-generation sequencing libraries from picogram quantities of target DNA. Genome Res 22(1):125–133. https://doi.org/10.1101/gr.124016.111
Caruccio N (2011) Preparation of next-generation sequencing libraries using Nextera technology: simultaneous DNA fragmentation and adaptor tagging by in vitro transposition. Methods Mol Biol 733:241–255. https://doi.org/10.1007/978-1-61779-089-8_17
Knierim E, Lucke B, Schwarz JM, Schuelke M, Seelow D (2011) Systematic comparison of three methods for fragmentation of long-range PCR products for next generation sequencing. PLoS One 6(11):e28240. https://doi.org/10.1371/journal.pone.0028240
Poptsova MS, Il’icheva IA, Nechipurenko DY, Panchenko LA, Khodikov MV, Oparina NY, Polozov RV, Nechipurenko YD, Grokhovsky SL (2014) Non-random DNA fragmentation in next-generation sequencing. Sci Rep 4:4532. https://doi.org/10.1038/srep04532
Kumar R, Ichihashi Y, Kimura S, Chitwood DH, Headland LR, Peng J, Maloof JN, Sinha NR (2012) A high-throughput method for illumina RNA-Seq library preparation. Front Plant Sci 3:202. https://doi.org/10.3389/fpls.2012.00202
Aird D, Ross MG, Chen WS, Danielsson M, Fennell T, Russ C, Jaffe DB, Nusbaum C, Gnirke A (2011) Analyzing and minimizing PCR amplification bias in Illumina sequencing libraries. Genome Biol 12(2):R18. https://doi.org/10.1186/gb-2011-12-2-r18
Adey A, Morrison HG, Asan, Xun X, Kitzman JO, Turner EH, Stackhouse B, MacKenzie AP, Caruccio NC, Zhang X, Shendure J (2010) Rapid, low-input, low-bias construction of shotgun fragment libraries by high-density in vitro transposition. Genome Biol 11(12):R119. https://doi.org/10.1186/gb-2010-11-12-r119
Perkins TT, Kingsley RA, Fookes MC, Gardner PP, James KD, Yu L, Assefa SA, He M, Croucher NJ, Pickard DJ, Maskell DJ, Parkhill J, Choudhary J, Thomson NR, Dougan G (2009) A strand-specific RNA-Seq analysis of the transcriptome of the typhoid bacillus Salmonella typhi. PLoS Genet 5(7):e1000569. https://doi.org/10.1371/journal.pgen.1000569
Acinas SG, Sarma-Rupavtarm R, Klepac-Ceraj V, Polz MF (2005) PCR-induced sequence artifacts and bias: insights from comparison of two 16S rRNA clone libraries constructed from the same sample. Appl Environ Microbiol 71(12):8966–8969. https://doi.org/10.1128/AEM.71.12.8966-8969.2005
Panichnantakul P, Bourgey M, Montpetit A, Bourque G, Riazalhosseini Y (2016) RNA-Seq as a tool to study the tumor microenvironment. Methods Mol Biol 1458:311–337. https://doi.org/10.1007/978-1-4939-3801-8_22
Cock PJ, Fields CJ, Goto N, Heuer ML, Rice PM (2010) The Sanger FASTQ file format for sequences with quality scores, and the Solexa/Illumina FASTQ variants. Nucleic Acids Res 38(6):1767–1771. https://doi.org/10.1093/nar/gkp1137
Brown J, Pirrung M, McCue LA (2017) FQC Dashboard: integrates FastQC results into a web-based, interactive, and extensible FASTQ quality control tool. Bioinformatics. https://doi.org/10.1093/bioinformatics/btx373
Patel RK, Jain M (2012) NGS QC Toolkit: a toolkit for quality control of next generation sequencing data. PLoS One 7(2):e30619. https://doi.org/10.1371/journal.pone.0030619
Yang X, Liu D, Liu F, Wu J, Zou J, Xiao X, Zhao F, Zhu B (2013) HTQC: a fast quality control toolkit for Illumina sequencing data. BMC Bioinformatics 14:33. https://doi.org/10.1186/1471-2105-14-33
Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30(15):2114–2120. https://doi.org/10.1093/bioinformatics/btu170
Hannon:lab (2009) FASTX-Toolkit. http://hannonlabcshl.edu/fastx_toolkit/index.html
Trapnell C, Pachter L, Salzberg SL (2009) TopHat: discovering splice junctions with RNA-Seq. Bioinformatics 25(9):1105–1111. https://doi.org/10.1093/bioinformatics/btp120
Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, Batut P, Chaisson M, Gingeras TR (2013) STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29(1):15–21. https://doi.org/10.1093/bioinformatics/bts635
Wang K, Singh D, Zeng Z, Coleman SJ, Huang Y, Savich GL, He X, Mieczkowski P, Grimm SA, Perou CM, MacLeod JN, Chiang DY, Prins JF, Liu J (2010) MapSplice: accurate mapping of RNA-seq reads for splice junction discovery. Nucleic Acids Res 38(18):e178. https://doi.org/10.1093/nar/gkq622
Wu TD, Reeder J, Lawrence M, Becker G, Brauer MJ (2016) GMAP and GSNAP for genomic sequence alignment: enhancements to speed, accuracy, and functionality. Methods Mol Biol 1418:283–334. https://doi.org/10.1007/978-1-4939-3578-9_15
Chen Y, Souaiaia T, Chen T (2009) PerM: efficient mapping of short sequencing reads with periodic full sensitive spaced seeds. Bioinformatics 25(19):2514–2521. https://doi.org/10.1093/bioinformatics/btp486
Grant GR, Farkas MH, Pizarro AD, Lahens NF, Schug J, Brunk BP, Stoeckert CJ, Hogenesch JB, Pierce EA (2011) Comparative analysis of RNA-Seq alignment algorithms and the RNA-Seq unified mapper (RUM). Bioinformatics 27(18):2518–2528. https://doi.org/10.1093/bioinformatics/btr427
Engstrom PG, Steijger T, Sipos B, Grant GR, Kahles A, Ratsch G, Goldman N, Hubbard TJ, Harrow J, Guigo R, Bertone P, Consortium R (2013) Systematic evaluation of spliced alignment programs for RNA-seq data. Nat Methods 10(12):1185–1191. https://doi.org/10.1038/nmeth.2722
Baruzzo G, Hayer KE, Kim EJ, Di Camillo B, FitzGerald GA, Grant GR (2017) Simulation-based comprehensive benchmarking of RNA-seq aligners. Nat Methods 14(2):135–139. https://doi.org/10.1038/nmeth.4106
Novocraft (2010) Novoalign. http://www.novocraft.com/products/novoalign/
Kim D, Pertea G, Trapnell C, Pimentel H, Kelley R, Salzberg SL (2013) TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions. Genome Biol 14(4):R36. https://doi.org/10.1186/gb-2013-14-4-r36
DeLuca DS, Levin JZ, Sivachenko A, Fennell T, Nazaire MD, Williams C, Reich M, Winckler W, Getz G (2012) RNA-SeQC: RNA-seq metrics for quality control and process optimization. Bioinformatics 28(11):1530–1532. https://doi.org/10.1093/bioinformatics/bts196
Wang L, Wang S, Li W (2012) RSeQC: quality control of RNA-seq experiments. Bioinformatics 28(16):2184–2185. https://doi.org/10.1093/bioinformatics/bts356
Liao Y, Smyth GK, Shi W (2014) featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 30(7):923–930. https://doi.org/10.1093/bioinformatics/btt656
Li B, Dewey CN (2011) RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinformatics 12:323. https://doi.org/10.1186/1471-2105-12-323
Roberts A, Pachter L (2013) Streaming fragment assignment for real-time analysis of sequencing experiments. Nat Methods 10(1):71–73. https://doi.org/10.1038/nmeth.2251
Patro R, Mount SM, Kingsford C (2014) Sailfish enables alignment-free isoform quantification from RNA-seq reads using lightweight algorithms. Nat Biotechnol 32(5):462–464. https://doi.org/10.1038/nbt.2862
Bray NL, Pimentel H, Melsted P, Pachter L (2016) Near-optimal probabilistic RNA-seq quantification. Nat Biotechnol 34(5):525–527. https://doi.org/10.1038/nbt.3519
Trapnell C, Williams BA, Pertea G, Mortazavi A, Kwan G, van Baren MJ, Salzberg SL, Wold BJ, Pachter L (2010) Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat Biotechnol 28(5):511–515. https://doi.org/10.1038/nbt.1621
Picelli S, Bjorklund AK, Faridani OR, Sagasser S, Winberg G, Sandberg R (2013) Smart-seq2 for sensitive full-length transcriptome profiling in single cells. Nat Methods 10(11):1096–1098. https://doi.org/10.1038/nmeth.2639
Zheng W, Chung LM, Zhao H (2011) Bias detection and correction in RNA-Sequencing data. BMC Bioinformatics 12:290. https://doi.org/10.1186/1471-2105-12-290
Wellenreuther R, Schupp I, Poustka A, Wiemann S, German c DNAC (2004) SMART amplification combined with cDNA size fractionation in order to obtain large full-length clones. BMC Genomics 5(1):36. https://doi.org/10.1186/1471-2164-5-36
Hansen KD, Brenner SE, Dudoit S (2010) Biases in Illumina transcriptome sequencing caused by random hexamer priming. Nucleic Acids Res 38(12):e131. https://doi.org/10.1093/nar/gkq224
Love MI, Hogenesch JB, Irizarry RA (2016) Modeling of RNA-seq fragment sequence bias reduces systematic errors in transcript abundance estimation. Nat Biotechnol 34(12):1287–1291. https://doi.org/10.1038/nbt.3682
Evans C, Hardin J, Stoebel DM (2017) Selecting between-sample RNA-Seq normalization methods from the perspective of their assumptions. Brief Bioinform. https://doi.org/10.1093/bib/bbx008
Oshlack A, Robinson MD, Young MD (2010) From RNA-seq reads to differential expression results. Genome Biol 11(12):220. https://doi.org/10.1186/gb-2010-11-12-220
Patro R, Duggal G, Love MI, Irizarry RA, Kingsford C (2017) Salmon provides fast and bias-aware quantification of transcript expression. Nat Methods 14(4):417–419. https://doi.org/10.1038/nmeth.4197
Dillies MA, Rau A, Aubert J, Hennequet-Antier C, Jeanmougin M, Servant N, Keime C, Marot G, Castel D, Estelle J, Guernec G, Jagla B, Jouneau L, Laloe D, Le Gall C, Schaeffer B, Le Crom S, Guedj M, Jaffrezic F, French StatOmique C (2013) A comprehensive evaluation of normalization methods for Illumina high-throughput RNA sequencing data analysis. Brief Bioinform 14(6):671–683. https://doi.org/10.1093/bib/bbs046
Bolstad BM, Irizarry RA, Astrand M, Speed TP (2003) A comparison of normalization methods for high density oligonucleotide array data based on variance and bias. Bioinformatics 19(2):185–193
Anders S, Huber W (2010) Differential expression analysis for sequence count data. Genome Biol 11(10):R106. https://doi.org/10.1186/gb-2010-11-10-r106
Robinson MD, Oshlack A (2010) A scaling normalization method for differential expression analysis of RNA-seq data. Genome Biol 11(3):R25. https://doi.org/10.1186/gb-2010-11-3-r25
Robinson MD, McCarthy DJ, Smyth GK (2010) edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26(1):139–140. https://doi.org/10.1093/bioinformatics/btp616
Li J, Witten DM, Johnstone IM, Tibshirani R (2012) Normalization, testing, and false discovery rate estimation for RNA-sequencing data. Biostatistics 13(3):523–538. https://doi.org/10.1093/biostatistics/kxr031
Kadota K, Nishiyama T, Shimizu K (2012) A normalization strategy for comparing tag count data. Algorithms Mol Biol 7(1):5. https://doi.org/10.1186/1748-7188-7-5
Bullard JH, Purdom E, Hansen KD, Dudoit S (2010) Evaluation of statistical methods for normalization and differential expression in mRNA-Seq experiments. BMC Bioinformatics 11:94. https://doi.org/10.1186/1471-2105-11-94
Loven J, Orlando DA, Sigova AA, Lin CY, Rahl PB, Burge CB, Levens DL, Lee TI, Young RA (2012) Revisiting global gene expression analysis. Cell 151(3):476–482. https://doi.org/10.1016/j.cell.2012.10.012
Risso D, Ngai J, Speed TP, Dudoit S (2014) Normalization of RNA-seq data using factor analysis of control genes or samples. Nat Biotechnol 32(9):896–902. https://doi.org/10.1038/nbt.2931
Rapaport F, Khanin R, Liang Y, Pirun M, Krek A, Zumbo P, Mason CE, Socci ND, Betel D (2013) Comprehensive evaluation of differential gene expression analysis methods for RNA-seq data. Genome Biol 14(9):R95. https://doi.org/10.1186/gb-2013-14-9-r95
Hardcastle TJ, Kelly KA (2010) baySeq: empirical Bayesian methods for identifying differential expression in sequence count data. BMC Bioinformatics 11:422. https://doi.org/10.1186/1471-2105-11-422
Ritchie ME, Phipson B, Wu D, Hu Y, Law CW, Shi W, Smyth GK (2015) limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res 43(7):e47. https://doi.org/10.1093/nar/gkv007
Tyner C, Barber GP, Casper J, Clawson H, Diekhans M, Eisenhart C, Fischer CM, Gibson D, Gonzalez JN, Guruvadoo L, Haeussler M, Heitner S, Hinrichs AS, Karolchik D, Lee BT, Lee CM, Nejad P, Raney BJ, Rosenbloom KR, Speir ML, Villarreal C, Vivian J, Zweig AS, Haussler D, Kuhn RM, Kent WJ (2017) The UCSC Genome Browser database: 2017 update. Nucleic Acids Res 45(D1):D626–D634. https://doi.org/10.1093/nar/gkw1134
Aken BL, Ayling S, Barrell D, Clarke L, Curwen V, Fairley S, Fernandez Banet J, Billis K, Garcia Giron C, Hourlier T, Howe K, Kahari A, Kokocinski F, Martin FJ, Murphy DN, Nag R, Ruffier M, Schuster M, Tang YA, Vogel JH, White S, Zadissa A, Flicek P, Searle SM (2016) The Ensembl gene annotation system. Database (Oxford). https://doi.org/10.1093/database/baw093
Thorvaldsdottir H, Robinson JT, Mesirov JP (2013) Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration. Brief Bioinform 14(2):178–192. https://doi.org/10.1093/bib/bbs017
Fiume M, Williams V, Brook A, Brudno M (2010) Savant: genome browser for high-throughput sequencing data. Bioinformatics 26(16):1938–1944. https://doi.org/10.1093/bioinformatics/btq332
Roge X, Zhang X (2014) RNAseqViewer: visualization tool for RNA-Seq data. Bioinformatics 30(6):891–892. https://doi.org/10.1093/bioinformatics/btt649
Li Y, Rao X, Mattox WW, Amos CI, Liu B (2015) RNA-Seq analysis of differential splice junction usage and intron retentions by DEXSeq. PLoS One 10(9):e0136653. https://doi.org/10.1371/journal.pone.0136653
Katz Y, Wang ET, Silterra J, Schwartz S, Wong B, Thorvaldsdottir H, Robinson JT, Mesirov JP, Airoldi EM, Burge CB (2015) Quantitative visualization of alternative exon expression from RNA-seq data. Bioinformatics 31(14):2400–2402. https://doi.org/10.1093/bioinformatics/btv034
Liu Q, Chen C, Shen E, Zhao F, Sun Z, Wu J (2012) Detection, annotation and visualization of alternative splicing from RNA-Seq data with SplicingViewer. Genomics 99(3):178–182. https://doi.org/10.1016/j.ygeno.2011.12.003
Barann M, Zimmer R, Birzele F (2017) Manananggal – a novel viewer for alternative splicing events. BMC Bioinformatics 18(1):120. https://doi.org/10.1186/s12859-017-1548-5
Kanitz A, Gypas F, Gruber AJ, Gruber AR, Martin G, Zavolan M (2015) Comparative assessment of methods for the computational inference of transcript isoform abundance from RNA-seq data. Genome Biol 16:150. https://doi.org/10.1186/s13059-015-0702-5
Nariai N, Kojima K, Mimori T, Sato Y, Kawai Y, Yamaguchi-Kabata Y, Nagasaki M (2014) TIGAR2: sensitive and accurate estimation of transcript isoform expression with longer RNA-Seq reads. BMC Genomics 15(Suppl 10):S5. https://doi.org/10.1186/1471-2164-15-S10-S5
Glaus P, Honkela A, Rattray M (2012) Identifying differentially expressed transcripts from RNA-seq data with biological variation. Bioinformatics 28(13):1721–1728. https://doi.org/10.1093/bioinformatics/bts260
Hensman J, Papastamoulis P, Glaus P, Honkela A, Rattray M (2015) Fast and accurate approximate inference of transcript expression from RNA-seq data. Bioinformatics 31(24):3881–3889. https://doi.org/10.1093/bioinformatics/btv483
Angelini C, De Canditiis D, De Feis I (2014) Computational approaches for isoform detection and estimation: good and bad news. BMC Bioinformatics 15:135. https://doi.org/10.1186/1471-2105-15-135
Steijger T, Abril JF, Engstrom PG, Kokocinski F, Hubbard TJ, Guigo R, Harrow J, Bertone P (2013) Assessment of transcript reconstruction methods for RNA-seq. Nat Methods 10(12):1177–1184. https://doi.org/10.1038/nmeth.2714
Au KF, Sebastiano V, Afshar PT, Durruthy JD, Lee L, Williams BA, van Bakel H, Schadt EE, Reijo-Pera RA, Underwood JG, Wong WH (2013) Characterization of the human ESC transcriptome by hybrid sequencing. Proc Natl Acad Sci U S A 110(50):E4821–E4830. https://doi.org/10.1073/pnas.1320101110
Sharon D, Tilgner H, Grubert F, Snyder M (2013) A single-molecule long-read survey of the human transcriptome. Nat Biotechnol 31(11):1009–1014. https://doi.org/10.1038/nbt.2705
Harrow J, Frankish A, Gonzalez JM, Tapanari E, Diekhans M, Kokocinski F, Aken BL, Barrell D, Zadissa A, Searle S, Barnes I, Bignell A, Boychenko V, Hunt T, Kay M, Mukherjee G, Rajan J, Despacio-Reyes G, Saunders G, Steward C, Harte R, Lin M, Howald C, Tanzer A, Derrien T, Chrast J, Walters N, Balasubramanian S, Pei B, Tress M, Rodriguez JM, Ezkurdia I, van Baren J, Brent M, Haussler D, Kellis M, Valencia A, Reymond A, Gerstein M, Guigo R, Hubbard TJ (2012) GENCODE: the reference human genome annotation for The ENCODE Project. Genome Res 22(9):1760–1774. https://doi.org/10.1101/gr.135350.111
Bang ML, Centner T, Fornoff F, Geach AJ, Gotthardt M, McNabb M, Witt CC, Labeit D, Gregorio CC, Granzier H, Labeit S (2001) The complete gene sequence of titin, expression of an unusual approximately 700-kDa titin isoform, and its interaction with obscurin identify a novel Z-line to I-band linking system. Circ Res 89(11):1065–1072
Braslavsky I, Hebert B, Kartalov E, Quake SR (2003) Sequence information can be obtained from single DNA molecules. Proc Natl Acad Sci U S A 100(7):3960–3964. https://doi.org/10.1073/pnas.0230489100
Rhoads A, Au KF (2015) PacBio sequencing and its applications. Genom Proteom Bioinform 13(5):278–289. https://doi.org/10.1016/j.gpb.2015.08.002
Eid J, Fehr A, Gray J, Luong K, Lyle J, Otto G, Peluso P, Rank D, Baybayan P, Bettman B, Bibillo A, Bjornson K, Chaudhuri B, Christians F, Cicero R, Clark S, Dalal R, Dewinter A, Dixon J, Foquet M, Gaertner A, Hardenbol P, Heiner C, Hester K, Holden D, Kearns G, Kong X, Kuse R, Lacroix Y, Lin S, Lundquist P, Ma C, Marks P, Maxham M, Murphy D, Park I, Pham T, Phillips M, Roy J, Sebra R, Shen G, Sorenson J, Tomaney A, Travers K, Trulson M, Vieceli J, Wegener J, Wu D, Yang A, Zaccarin D, Zhao P, Zhong F, Korlach J, Turner S (2009) Real-time DNA sequencing from single polymerase molecules. Science 323(5910):133–138. https://doi.org/10.1126/science.1162986
Gonzalez-Garay ML (2016) Introduction to isoform sequencing using pacific biosciences technology (Iso-Seq). In: Wu J (ed) Transcriptomics and gene regulation. Springer Netherlands, Dordrecht, pp 141–160. https://doi.org/10.1007/978-94-017-7450-5_6
PacBio (2017) SMRT Link pipeline. https://githubcom/PacificBiosciences/SMRT-Link/
Wu TD, Watanabe CK (2005) GMAP: a genomic mapping and alignment program for mRNA and EST sequences. Bioinformatics 21(9):1859–1875. https://doi.org/10.1093/bioinformatics/bti310
Chaisson MJ, Tesler G (2012) Mapping single molecule sequencing reads using basic local alignment with successive refinement (BLASR): application and theory. BMC Bioinformatics 13:238. https://doi.org/10.1186/1471-2105-13-238
PacBio (2015) Optimizing STAR aligner for Iso Seq data. https://github.com/PacificBiosciences/cDNA_primer/wiki/Bioinfx-study:-Optimizing-STAR-aligner-for-Iso-Seq-data
Skelley T (2015) MatchAnnot. GitHub repository. https://github.com/TomSkelly/MatchAnnot
Fu J (2015) IsoView. https://github.com/JMF47/IsoView
Hu J, Uapinyoying P, Goecks J (2017) Interactive analysis of Long-read RNA isoforms with Iso-Seq Browser. bioRxiv. https://doi.org/10.1101/102905
Tardaguila M, de la Fuente L, Marti C, Pereira C, del Risco H, Ferrell M, Mellado M, Macchietto M, Verheggen K, Edelmann M, Ezkurdia I, Vazquez J, Tress M, Mortazavi A, Martens L, Rodriguez-Navarro S, Moreno V, Conesa A (2017) SQANTI: extensive characterization of long read transcript sequences for quality control in full-length transcriptome identification and quantification. bioRxiv. https://doi.org/10.1101/118083
Wang L, Park HJ, Dasari S, Wang S, Kocher JP, Li W (2013) CPAT: Coding-Potential Assessment Tool using an alignment-free logistic regression model. Nucleic Acids Res 41(6):e74. https://doi.org/10.1093/nar/gkt006
Li A, Zhang J, Zhou Z (2014) PLEK: a tool for predicting long non-coding RNAs and messenger RNAs based on an improved k-mer scheme. BMC Bioinformatics 15:311. https://doi.org/10.1186/1471-2105-15-311
PacBio (2016) ANGEL. GitHub repository. https://github.com/PacificBiosciences/ANGEL
Au:Lab (2014) SpliceMap-LSC-IDP. https://www.healthcareuiowa.edu/labs/au/IDP/
Weirather JL, Afshar PT, Clark TA, Tseng E, Powers LS, Underwood JG, Zabner J, Korlach J, Wong WH, Au KF (2015) Characterization of fusion genes and the significantly expressed fusion isoforms in breast cancer by hybrid sequencing. Nucleic Acids Res 43(18):e116. https://doi.org/10.1093/nar/gkv562
PacBio (2017) Pacific Biosciences repository. https://github.com/PacificBiosciences/
Larsen PA, Smith TP (2012) Application of circular consensus sequencing and network analysis to characterize the bovine IgG repertoire. BMC Immunol 13:52. https://doi.org/10.1186/1471-2172-13-52
Mascher M, Gundlach H, Himmelbach A, Beier S, Twardziok SO, Wicker T, Radchuk V, Dockter C, Hedley PE, Russell J, Bayer M, Ramsay L, Liu H, Haberer G, Zhang X-Q, Zhang Q, Barrero RA, Li L, Taudien S, Groth M, Felder M, Hastie A, Šimková H, Staňková H, Vrána J, Chan S, Muñoz-Amatriaín M, Ounit R, Wanamaker S, Bolser D, Colmsee C, Schmutzer T, Aliyeva-Schnorr L, Grasso S, Tanskanen J, Chailyan A, Sampath D, Heavens D, Clissold L, Cao S, Chapman B, Dai F, Han Y, Li H, Li X, Lin C, McCooke JK, Tan C, Wang P, Wang S, Yin S, Zhou G, Poland JA, Bellgard MI, Borisjuk L, Houben A, Doležel J, Ayling S, Lonardi S, Kersey P, Langridge P, Muehlbauer GJ, Clark MD, Caccamo M, Schulman AH, Mayer KFX, Platzer M, Close TJ, Scholz U, Hansson M, Zhang G, Braumann I, Spannagl M, Li C, Waugh R, Stein N (2017) A chromosome conformation capture ordered sequence of the barley genome. Nature 544(7651):427–433. https://doi.org/10.1038/nature22043. http://www.nature.com/nature/journal/v544/n7651/abs/nature22043.html#supplementary-information
Hoang NV, Furtado A, Mason PJ, Marquardt A, Kasirajan L, Thirugnanasambandam PP, Botha FC, Henry RJ (2017) A survey of the complex transcriptome from the highly polyploid sugarcane genome using full-length isoform sequencing and de novo assembly from short read sequencing. BMC Genomics 18(1):395. https://doi.org/10.1186/s12864-017-3757-8
Clavijo BJ, Venturini L, Schudoma C, Accinelli GG, Kaithakottil G, Wright J, Borrill P, Kettleborough G, Heavens D, Chapman H, Lipscombe J, Barker T, Lu FH, McKenzie N, Raats D, Ramirez-Gonzalez RH, Coince A, Peel N, Percival-Alwyn L, Duncan O, Trosch J, Yu G, Bolser DM, Namaati G, Kerhornou A, Spannagl M, Gundlach H, Haberer G, Davey RP, Fosker C, Palma FD, Phillips AL, Millar AH, Kersey PJ, Uauy C, Krasileva KV, Swarbreck D, Bevan MW, Clark MD (2017) An improved assembly and annotation of the allohexaploid wheat genome identifies complete families of agronomic genes and provides genomic evidence for chromosomal translocations. Genome Res 27(5):885–896. https://doi.org/10.1101/gr.217117.116
Kuo RI, Tseng E, Eory L, Paton IR, Archibald AL, Burt DW (2017) Normalized long read RNA sequencing in chicken reveals transcriptome complexity similar to human. BMC Genomics 18(1):323. https://doi.org/10.1186/s12864-017-3691-9
Prall TM, Graham ME, Karl JA, Wiseman RW, Ericsen AJ, Raveendran M, Alan Harris R, Muzny DM, Gibbs RA, Rogers J, O’Connor DH (2017) Improved full-length killer cell immunoglobulin-like receptor transcript discovery in Mauritian cynomolgus macaques. Immunogenetics 69(5):325–339. https://doi.org/10.1007/s00251-017-0977-7
Criscione SW, Theodosakis N, Micevic G, Cornish TC, Burns KH, Neretti N, Rodić N (2016) Genome-wide characterization of human L1 antisense promoter-driven transcripts. BMC Genomics 17(1):463. https://doi.org/10.1186/s12864-016-2800-5
Liu X, Mei W, Soltis PS, Soltis DE, Barbazuk WB (2017) Detecting alternatively spliced transcript isoforms from single-molecule long-read sequences without a reference genome. Mol Ecol Resour. https://doi.org/10.1111/1755-0998.12670
Kasianowicz JJ, Brandin E, Branton D, Deamer DW (1996) Characterization of individual polynucleotide molecules using a membrane channel. Proc Natl Acad Sci U S A 93(24):13770–13773
Loman NJ, Watson M (2015) Successful test launch for nanopore sequencing. Nat Methods 12(4):303–304. https://doi.org/10.1038/nmeth.3327
Oikonomopoulos S, Wang YC, Djambazian H, Badescu D, Ragoussis J (2016) Benchmarking of the Oxford Nanopore MinION sequencing for quantitative and qualitative assessment of cDNA populations. Sci Rep 6:31602. https://doi.org/10.1038/srep31602
Bolisetty MT, Rajadinakaran G, Graveley BR (2015) Determining exon connectivity in complex mRNAs by nanopore sequencing. Genome Biol 16:204. https://doi.org/10.1186/s13059-015-0777-z
Weirather J, de Cesare M, Wang Y, Piazza P, Sebastiano V, Wang X, Buck D, Au K (2017) Comprehensive comparison of Pacific Biosciences and Oxford Nanopore Technologies and their applications to transcriptome analysis [version 1; referees: 2 approved with reservations]. F1000Res 6:100
ONT (2016) Nanonet. https://github.com/nanoporetech/nanonet
David M, Dursi LJ, Yao D, Boutros PC, Simpson JT (2017) Nanocall: an open source basecaller for Oxford Nanopore sequencing data. Bioinformatics 33(1):49–55. https://doi.org/10.1093/bioinformatics/btw569
Boza V, Brejova B, Vinar T (2017) DeepNano: deep recurrent neural networks for base calling in MinION nanopore reads. PLoS One 12(6):e0178751. https://doi.org/10.1371/journal.pone.0178751
Loman NJ, Quinlan AR (2014) Poretools: a toolkit for analyzing nanopore sequence data. Bioinformatics 30(23):3399–3401. https://doi.org/10.1093/bioinformatics/btu555
Watson M, Thomson M, Risse J, Talbot R, Santoyo-Lopez J, Gharbi K, Blaxter M (2015) poRe: an R package for the visualization and analysis of nanopore sequencing data. Bioinformatics 31(1):114–115. https://doi.org/10.1093/bioinformatics/btu590
Leggett RM, Heavens D, Caccamo M, Clark MD, Davey RP (2016) NanoOK: multi-reference alignment analysis of nanopore sequencing data, quality and error profiles. Bioinformatics 32(1):142–144. https://doi.org/10.1093/bioinformatics/btv540
Byrne A, Beaudin AE, Olsen HE, Jain M, Cole C, Palmer T, DuBois RM, Forsberg EC, Akeson M, Vollmers C (2017) Nanopore long-read RNAseq reveals widespread transcriptional variation among the surface receptors of individual. B cells Nat Commun 8:16027. https://doi.org/10.1038/ncomms16027
Lee C, Grasso C, Sharlow MF (2002) Multiple sequence alignment using partial order graphs. Bioinformatics 18(3):452–464
Li H, Durbin R (2009) Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25(14):1754–1760. https://doi.org/10.1093/bioinformatics/btp324
Kielbasa SM, Wan R, Sato K, Horton P, Frith MC (2011) Adaptive seeds tame genomic sequence comparison. Genome Res 21(3):487–493. https://doi.org/10.1101/gr.113985.110
Jain M, Fiddes IT, Miga KH, Olsen HE, Paten B, Akeson M (2015) Improved data analysis for the MinION nanopore sequencer. Nat Methods 12(4):351–356. https://doi.org/10.1038/nmeth.3290
Sovic I, Sikic M, Wilm A, Fenlon SN, Chen S, Nagarajan N (2016) Fast and sensitive mapping of nanopore sequencing reads with GraphMap. Nat Commun 7:11307. https://doi.org/10.1038/ncomms11307
Krizanovic K, Echchiki A, Roux J, Sikic M (2017) Evaluation of tools for long read RNA-seq splice-aware alignment. Bioinformatics. https://doi.org/10.1093/bioinformatics/btx668
Brian B (2014) BBMap. https://sourceforge.net/projects/bbmap/
Kim D, Langmead B, Salzberg SL (2015) HISAT: a fast spliced aligner with low memory requirements. Nat Methods 12(4):357–360. https://doi.org/10.1038/nmeth.3317
Weirather J, de Cesare M, Wang Y, Piazza P, Sebastiano V, Wang X, Buck D, Au K (2017) Comprehensive comparison of Pacific Biosciences and Oxford Nanopore Technologies and their applications to transcriptome analysis [version 2; referees: 1 approved, 1 approved with reservations]. F1000Res 6:100
Koren S, Schatz MC, Walenz BP, Martin J, Howard JT, Ganapathy G, Wang Z, Rasko DA, McCombie WR, Jarvis ED, Adam MP (2012) Hybrid error correction and de novo assembly of single-molecule sequencing reads. Nat Biotechnol 30(7):693–700. https://doi.org/10.1038/nbt.2280
Au KF, Underwood JG, Lee L, Wong WH (2012) Improving PacBio long read accuracy by short read alignment. PLoS One 7(10):e46679. https://doi.org/10.1371/journal.pone.0046679
Hackl T, Hedrich R, Schultz J, Forster F (2014) proovread: large-scale high-accuracy PacBio correction through iterative short read consensus. Bioinformatics 30(21):3004–3011. https://doi.org/10.1093/bioinformatics/btu392
Abdel-Ghany SE, Hamilton M, Jacobi JL, Ngam P, Devitt N, Schilkey F, Ben-Hur A, Reddy AS (2016) A survey of the sorghum transcriptome using single-molecule long reads. Nat Commun 7:11706. https://doi.org/10.1038/ncomms11706
Koren S, Schatz MC, Walenz BP, Martin J, Howard JT, Ganapathy G, Wang Z, Rasko DA, McCombie WR, Jarvis ED, Phillippy AM (2012) Hybrid error correction and de novo assembly of single-molecule sequencing reads. Nat Biotechnol 30(7):693–700. http://www.nature.com/nbt/journal/v30/n7/abs/nbt.2280.html#supplementary-information
Vilfan ID, Tsai Y-C, Clark TA, Wegener J, Dai Q, Yi C, Pan T, Turner SW, Korlach J (2013) Analysis of RNA base modification and structural rearrangement by single-molecule real-time detection of reverse transcription. J Nanobiotechnol 11(1):8. https://doi.org/10.1186/1477-3155-11-8
Tilgner H, Jahanbani F, Blauwkamp T, Moshrefi A, Jaeger E, Chen F, Harel I, Bustamante CD, Rasmussen M, Snyder MP (2015) Comprehensive transcriptome analysis using synthetic long-read sequencing reveals molecular co-association of distant splicing events. Nat Biotechnol 33(7):736–742. https://doi.org/10.1038/nbt.3242
Ozsolak F, Platt AR, Jones DR, Reifenberger JG, Sass LE, McInerney P, Thompson JF, Bowers J, Jarosz M, Milos PM (2009) Direct RNA sequencing. Nature 461(7265):814–818. https://doi.org/10.1038/nature08390
Raz T, Causey M, Jones DR, Kieu A, Letovsky S, Lipson D, Thayer E, Thompson JF, Milos PM (2011) RNA sequencing and quantitation using the Helicos Genetic Analysis System. Methods Mol Biol 733:37–49. https://doi.org/10.1007/978-1-61779-089-8_3
Garalde DR, Snell EA, Jachimowicz D, Heron AJ, Bruce M, Lloyd J, Warland A, Pantic N, Admassu T, Ciccone J, Serra S, Keenan J, Martin S, McNeill L, Wallace J, Jayasinghe L, Wright C, Blasco J, Sipos B, Young S, Juul S, Clarke J, Turner DJ (2016) Highly parallel direct RNA sequencing on an array of nanopores. bioRxiv
Ross MG, Russ C, Costello M, Hollinger A, Lennon NJ, Hegarty R, Nusbaum C, Jaffe DB (2013) Characterizing and measuring bias in sequence data. Genome Biol 14(5):R51. https://doi.org/10.1186/gb-2013-14-5-r51
Xiao Z, Guifang J (2016) RNA epigenetic modification: N6-methyladenosine. Yi Chuan 38(4):275–288. https://doi.org/10.16288/j.yczz.16-049
Quick J, Quinlan AR, Loman NJ (2014) A reference bacterial genome dataset generated on the MinION portable single-molecule nanopore sequencer. Gigascience 3:22. https://doi.org/10.1186/2047-217x-3-22
Loman NJ, Quick J, Simpson JT (2015) A complete bacterial genome assembled de novo using only nanopore sequencing data. Nat Methods 12(8):733–735. https://doi.org/10.1038/nmeth.3444
Cretu Stancu M, van Roosmalen MJ, Renkens I, Nieboer M, Middelkamp S, de Ligt J, Pregno G, Giachino D, Mandrile G, Espejo Valle-Inclan J, Korzelius J, de Bruijn E, Cuppen E, Talkowski ME, Marschall T, de Ridder J, Kloosterman WP (2017) Mapping and phasing of structural variation in patient genomes using nanopore sequencing. Nat Commun 8(1):1326. https://doi.org/10.1038/s41467-017-01343-4
Perkel JM (2017) Single-cell sequencing made simple. Nature 547(7661):125–126. https://doi.org/10.1038/547125a
Grun D, Lyubimova A, Kester L, Wiebrands K, Basak O, Sasaki N, Clevers H, van Oudenaarden A (2015) Single-cell messenger RNA sequencing reveals rare intestinal cell types. Nature 525(7568):251–255. https://doi.org/10.1038/nature14966
Tirosh I, Izar B, Prakadan SM, Wadsworth MH, Treacy D, Trombetta JJ, Rotem A, Rodman C, Lian C, Murphy G, Fallahi-Sichani M, Dutton-Regester K, Lin J-R, Cohen O, Shah P, Lu D, Genshaft AS, Hughes TK, Ziegler CGK, Kazer SW, Gaillard A, Kolb KE, Villani A-C, Johannessen CM, Andreev AY, Van Allen EM, Bertagnolli M, Sorger PK, Sullivan RJ, Flaherty KT, Frederick DT, Jané-Valbuena J, Yoon CH, Rozenblatt-Rosen O, Shalek AK, Regev A, Garraway LA (2016) Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq. Science 352(6282):189
Picelli S, Faridani OR, Bjorklund AK, Winberg G, Sagasser S, Sandberg R (2014) Full-length RNA-seq from single cells using Smart-seq2. Nat Protoc 9(1):171–181. https://doi.org/10.1038/nprot.2014.006
Macosko EZ, Basu A, Satija R, Nemesh J, Shekhar K, Goldman M, Tirosh I, Bialas AR, Kamitaki N, Martersteck EM, Trombetta JJ, Weitz DA, Sanes JR, Shalek AK, Regev A, McCarroll SA (2015) Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets. Cell 161(5):1202–1214. https://doi.org/10.1016/j.cell.2015.05.002
Zheng GXY, Terry JM, Belgrader P, Ryvkin P, Bent ZW, Wilson R, Ziraldo SB, Wheeler TD, McDermott GP, Zhu J, Gregory MT, Shuga J, Montesclaros L, Masquelier DA, Nishimura SY, Schnall-Levin M, Wyatt PW, Hindson CM, Bharadwaj R, Wong A, Ness KD, Beppu LW, Deeg J, McFarland C, Loeb KR, Valente WJ, Ericson NG, Stevens EA, Radich JP, Mikkelsen TS, Hindson BJ, Bielas JH (2017) Massively parallel digital transcriptional profiling of single cells. Nat Commun 8:14049
Tang F, Barbacioru C, Nordman E, Li B, Xu N, Bashkirov VI, Lao K, Surani MA (2010) RNA-Seq analysis to capture the transcriptome landscape of a single cell. Nat Protoc 5(3):516–535. https://doi.org/10.1038/nprot.2009.236
Karlsson K, Linnarsson S (2017) Single-cell mRNA isoform diversity in the mouse brain. BMC Genomics 18(1):126. https://doi.org/10.1186/s12864-017-3528-6
Canales RD, Luo Y, Willey JC, Austermiller B, Barbacioru CC, Boysen C, Hunkapiller K, Jensen RV, Knight CR, Lee KY, Ma Y, Maqsodi B, Papallo A, Peters EH, Poulter K, Ruppel PL, Samaha RR, Shi L, Yang W, Zhang L, Goodsaid FM (2006) Evaluation of DNA microarray results with quantitative gene expression platforms. Nat Biotechnol 24(9):1115–1122. https://doi.org/10.1038/nbt1236
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Bayega, A., Fahiminiya, S., Oikonomopoulos, S., Ragoussis, J. (2018). Current and Future Methods for mRNA Analysis: A Drive Toward Single Molecule Sequencing. In: Raghavachari, N., Garcia-Reyero, N. (eds) Gene Expression Analysis. Methods in Molecular Biology, vol 1783. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7834-2_11
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