Single-cell RNA-sequencing: The future of genome biology is now

RNA Biology

Volumn 14, Issue 5, 2017, Pages 637-650

  Picelli, Simone ^a  

^a SCIENCE FOR LIFE LABORATORY   (Sweden)

Author keywords

CEL seq; CytoSeq; Drop seq; MARS seq; Nanopore; RNA sequencing; single cell; SMART seq2; STRT C1; Tn5 transposase

Indexed keywords

TN5 TRANSPOSASE; TRANSPOSASE; UNCLASSIFIED DRUG; RNA; TRANSCRIPTOME;

ARTICLE; CELL ISOLATION; EMULSION; GENOME; HUMAN; NANOPORE; NONHUMAN; REVERSE TRANSCRIPTION; RNA SEQUENCE; SINGLE CELL ANALYSIS; TRANSCRIPTOMICS; GENETICS; GENOME-WIDE ASSOCIATION STUDY; HUMAN GENOME; METABOLISM; PROCEDURES; SEQUENCE ANALYSIS;

GENOME, HUMAN; GENOME-WIDE ASSOCIATION STUDY; HUMANS; NANOPORES; RNA; SEQUENCE ANALYSIS, RNA; SINGLE-CELL ANALYSIS; TRANSCRIPTOME; TRANSPOSASES;

EID: 84978951918     PISSN: 15476286     EISSN: 15558584     Source Type: Journal    
DOI: 10.1080/15476286.2016.1201618     Document Type: Article

References (62)

1. Saliba AE, Westermann AJ, Gorski SA, Vogel J. Single-cell RNA-seq:advances and future challenges. Nucleic Acids Res 2014; 42:8845-60; PMID:25053837; http://dx.doi.org/10.1093/nar/gku555
2. Hangauer MJ, Vaughn IW, McManus MT. Pervasive transcription of the human genome produces thousands of previously unidentified long intergenic noncoding RNAs. PLoS genetics 2013; 9:e1003569; PMID:23818866; http://dx.doi.org/10.1371/journal.pgen.1003569
3. Shalek AK, Satija R, Adiconis X, Gertner RS, Gaublomme JT, Raychowdhury R, Schwartz S, Yosef N, Malboeuf C, Lu D, et al. Single-cell transcriptomics reveals bimodality in expression and splicing in immune cells. Nature 2013; 498:236-40; PMID:23685454; http://dx.doi.org/10.1038/nature12172
4. Deng Q, Ramskold D, Reinius B, Sandberg R. Single-cell RNA-seq reveals dynamic, random monoallelic gene expression in mammalian cells. Science 2014; 343:193-6; PMID:24408435; http://dx.doi.org/10.1126/science.1245316
5. Bengtsson M, Stahlberg A, Rorsman P, Kubista M. Gene expression profiling in single cells from the pancreatic islets of Langerhans reveals lognormal distribution of mRNA levels. Genome Res 2005; 15:1388-92; PMID:16204192; http://dx.doi.org/10.1101/gr.3820805
6. Chang HH, Hemberg M, Barahona M, Ingber DE, Huang S. Transcriptome-wide noise controls lineage choice in mammalian progenitor cells. Nature 2008; 453:544-7; PMID:18497826; http://dx.doi.org/10.1038/nature06965
7. Grun D, van Oudenaarden A. Design and Analysis of Single-Cell Sequencing Experiments. Cell 2015; 163:799-810; PMID:26544934; http://dx.doi.org/10.1016/j.cell.2015.10.039
8. Stegle O, Teichmann SA, Marioni JC. Computational and analytical challenges in single-cell transcriptomics. Nat Rev Genet 2015; 16:133-45; PMID:25628217; http://dx.doi.org/10.1038/nrg3833
9. Shapiro E, Biezuner T, Linnarsson S. Single-cell sequencing-based technologies will revolutionize whole-organism science. Nat Rev Genet 2013; 14:618-30; PMID:23897237; http://dx.doi.org/10.1038/nrg3542
10. He S, Wurtzel O, Singh K, Froula JL, Yilmaz S, Tringe SG, Wang Z, Chen F, Lindquist EA, Sorek R, et al. Validation of two ribosomal RNA removal methods for microbial metatranscriptomics. Nat Methods 2010; 7:807-12; PMID:20852648; http://dx.doi.org/10.1038/nmeth.1507
11. Ramskold D, Luo S, Wang YC, Li R, Deng Q, Faridani OR, Daniels GA, Khrebtukova I, Loring JF, Laurent LC, et al. Full-length mRNA-Seq from single-cell levels of RNA and individual circulating tumor cells. Nat Biotechnol 2012; 30:777-82; PMID:22820318; http://dx.doi.org/10.1038/nbt.2282
12. Picelli S, Bjorklund AK, Faridani OR, Sagasser S, Winberg G, Sandberg R. Smart-seq2 for sensitive full-length transcriptome profiling in single cells. Nat Methods 2013; 10:1096-8; PMID:24056875; http://dx.doi.org/10.1038/nmeth.2639
13. Sandberg R. Entering the era of single-cell transcriptomics in biology and medicine. Nat Methods 2014; 11:22-4; PMID:24524133; http://dx.doi.org/10.1038/nmeth.2764
14. Pelechano V, Steinmetz LM. Gene regulation by antisense transcription. Nat Rev Genet 2013; 14:880-93; PMID:24217315; http://dx.doi.org/10.1038/nrg3594
15. Zeisel A, Munoz-Manchado AB, Codeluppi S, Lonnerberg P, La Manno G, Jureus A, Marques S, Munguba H, He L, Betsholtz C, et al. Brain structure. Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq. Science 2015; 347:1138-42; PMID:25700174; http://dx.doi.org/10.1126/science.aaa1934
16. Tang F, Barbacioru C, Wang Y, Nordman E, Lee C, Xu N, Wang X, Bodeau J, Tuch BB, Siddiqui A, et al. mRNA-Seq whole-transcriptome analysis of a single cell. Nat Methods 2009; 6:377-82; PMID:19349980; http://dx.doi.org/10.1038/nmeth.1315
17. Tang F, Barbacioru C, Nordman E, Li B, Xu N, Bashkirov VI, Lao K, Surani MA. RNA-Seq analysis to capture the transcriptome landscape of a single cell. Nat Protoc 2010; 5:516-35; PMID:20203668; http://dx.doi.org/10.1038/nprot.2009.236
18. Kurimoto K, Yabuta Y, Ohinata Y, Ono Y, Uno KD, Yamada RG, Ueda HR, Saitou M. An improved single-cell cDNA amplification method for efficient high-density oligonucleotide microarray analysis. Nucleic Acids Res2006; 34:e42; PMID:16547197; http://dx.di.org/10.1093/nar/gkl050
19. Chenchik A, Diachenko L, Moqadam F, Tarabykin V, Lukyanov S, Siebert PD. Full-length cDNA cloning and determination of mRNA 5′ and 3′ ends by amplification of adaptor-ligated cDNA. BioTechniques 1996; 21:526-34; PMID:8879595
20. Zhu YY, Machleder EM, Chenchik A, Li R, Siebert PD. Reverse transcriptase template switching:a SMART approach for full-length cDNA library construction. BioTechniques 2001; 30:892-7; PMID:11314272
21. Picelli S, Faridani OR, Bjorklund AK, Winberg G, Sagasser S, Sandberg R. Full-length RNA-seq from single cells using Smart-seq2. Nat Protoc 2014; 9:171-81; PMID:24385147; http://dx.doi.org/10.1038/nprot.2014.006
22. Carninci P, Nishiyama Y, Westover A, Itoh M, Nagaoka S, Sasaki N, Okazaki Y, Muramatsu M, Hayashizaki Y. Thermostabilization and thermoactivation of thermolabile enzymes by trehalose and its application for the synthesis of full length cDNA. Proc Natl Acad Sci U S A 1998; 95:520-4; PMID:9435224; http://dx.doi.org/10.1073/pnas.95.2.520
23. Petersen M, Wengel J. LNA:a versatile tool for therapeutics and genomics. Trends Biotechnol 2003; 21:74-81; PMID:12573856; http://dx.doi.org/10.1016/S0167-7799(02)00038-0
24. Tang DT, Plessy C, Salimullah M, Suzuki AM, Calligaris R, Gustincich S, Carninci P. Suppression of artifacts and barcode bias in high-throughput transcriptome analyses utilizing template switching. Nucleic Acids Res 2013; 41:e44; PMID:23180801; http://dx.doi.org/10.1093/nar/gks1128
25. Quail MA, Otto TD, Gu Y, Harris SR, Skelly TF, McQuillan JA, Swerdlow HP, Oyola SO. Optimal enzymes for amplifying sequencing libraries. Nat Methods 2012; 9:10-1; http://dx.doi.org/10.1038/nmeth.1814
26. Kapteyn J, He R, McDowell ET, Gang DR. Incorporation of non-natural nucleotides into template-switching oligonucleotides reduces background and improves cDNA synthesis from very small RNA samples. BMC Genomics 2010; 11:413; PMID:20598146; http://dx.doi.org/10.1186/1471-2164-11-413
27. Islam S, Kjallquist U, Moliner A, Zajac P, Fan JB, Lonnerberg P, Linnarsson S. Highly multiplexed and strand-specific single-cell RNA 5′ end sequencing. Nat Protoc 2012; 7:813-28; PMID:22481528; http://dx.doi.org/10.1038/nprot.2012.022
28. Bjorklund AK, Forkel M, Picelli S, Konya V, Theorell J, Friberg D, Sandberg R, Mjosberg J. The heterogeneity of human CD127(+) innate lymphoid cells revealed by single-cell RNA sequencing. Nat Immunol 2016; 17:451-60; PMID:26878113; http://dx.doi.org/10.1038/ni.3368
29. Pinto FL, Lindblad P. A guide for in-house design of template-switch-based 5′ rapid amplification of cDNA ends systems. Anal Biochem 2010; 397:227-32; PMID:19837043; http://dx.doi.org/10.1016/j.ab.2009.10.022
30. Picelli S, Bjorklund AK, Reinius B, Sagasser S, Winberg G, Sandberg R. Tn5 transposase and tagmentation procedures for massively scaled sequencing projects. Genome Res 2014; 24:2033-40; PMID:25079858; http://dx.doi.org/10.1101/gr.177881.114
31. Sasagawa Y, Nikaido I, Hayashi T, Danno H, Uno KD, Imai T, Ueda HR. Quartz-Seq:a highly reproducible and sensitive single-cell RNA sequencing method, reveals non-genetic gene-expression heterogeneity. Genome Biol 2013; 14:R31; PMID:23594475; http://dx.doi.org/10.1186/gb-2013-14-4-r31
32. Hashimshony T, Wagner F, Sher N, Yanai I. CEL-Seq:single-cell RNA-Seq by multiplexed linear amplification. Cell reports 2012; 2:666-73; PMID:22939981; http://dx.doi.org/10.1016/j.celrep.2012.08.003
33. Eberwine J, Yeh H, Miyashiro K, Cao Y, Nair S, Finnell R, Zettel M, Coleman P. Analysis of gene expression in single live neurons. Proc Natl Acad Sci U S A 1992; 89:3010-4; PMID:1557406; http://dx.doi.org/10.1073/pnas.89.7.3010
34. Jaitin DA, Kenigsberg E, Keren-Shaul H, Elefant N, Paul F, Zaretsky I, Mildner A, Cohen N, Jung S, Tanay A, et al. Massively parallel single-cell RNA-seq for marker-free decomposition of tissues into cell types. Science 2014; 343:776-9; PMID:24531970; http://dx.doi.org/10.1126/science.1247651
35. Kivioja T, Vaharautio A, Karlsson K, Bonke M, Enge M, Linnarsson S, Taipale J. Counting absolute numbers of molecules using unique molecular identifiers. Nat Methods 2012; 9:72-4; http://dx.doi.org/10.1038/nmeth.1778
36. Jaitin DA, Keren-Shaul H, Elefant N, Amit I. Each cell counts:Hematopoiesis and immunity research in the era of single cell genomics. Semin Immunol 2015; 27:67-71; PMID:25727184; http://dx.doi.org/10.1016/j.smim.2015.01.002
37. Hashimshony T, Senderovich N, Avital G, Klochendler A, de Leeuw Y, Anavy L, Gennert D, Li S, Livak KJ, Rozenblatt-Rosen O, et al. CEL-Seq2:sensitive highly-multiplexed single-cell RNA-Seq. Genome Biol 2016; 17:77; PMID:27121950; http://dx.doi.org/10.1186/s13059-016-0938-8
38. Islam S, Kjallquist U, Moliner A, Zajac P, Fan JB, Lonnerberg P, Linnarsson S. Characterization of the single-cell transcriptional landscape by highly multiplex RNA-seq. Genome Res 2011; 21:1160-7; PMID:21543516; http://dx.doi.org/10.1101/gr.110882.110
39. Islam S, Zeisel A, Joost S, La Manno G, Zajac P, Kasper M, Lonnerberg P, Linnarsson S. Quantitative single-cell RNA-seq with unique molecular identifiers. Nat Methods 2014; 11:163-6; PMID:24363023; http://dx.doi.org/10.1038/nmeth.2772
40. Fan HC, Fu GK, Fodor SP. Expression profiling. Combinatorial labeling of single cells for gene expression cytometry. Science 2015; 347:1258367; PMID:25657253; http://dx.doi.org/10.1126/science.1258367
41. Pollen AA, Nowakowski TJ, Shuga J, Wang X, Leyrat AA, Lui JH, Li N, Szpankowski L, Fowler B, Chen P, et al. Low-coverage single-cell mRNA sequencing reveals cellular heterogeneity and activated signaling pathways in developing cerebral cortex. Nat Biotechnol 2014; 32:1053-8; PMID:25086649; http://dx.doi.org/10.1038/nbt.2967
42. Macosko EZ, Basu A, Satija R, Nemesh J, Shekhar K, Goldman M, Tirosh I, Bialas AR, Kamitaki N, Martersteck EM, et al. Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets. Cell 2015; 161:1202-14; PMID:26000488; http://dx.doi.org/10.1016/j.cell.2015.05.002
43. Klein AM, Mazutis L, Akartuna I, Tallapragada N, Veres A, Li V, Peshkin L, Weitz DA, Kirschner MW. Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells. Cell 2015; 161:1187-201; PMID:26000487; http://dx.doi.org/10.1016/j.cell.2015.04.044
44. Adey A, Morrison HG, Asan, Xun X, Kitzman JO, Turner EH, Stackhouse B, MacKenzie AP, Caruccio NC, Zhang X, et al. Rapid, low-input, low-bias construction of shotgun fragment libraries by high-density in vitro transposition. Genome Biol 2010; 11:R119; PMID:21143862; http://dx.doi.org/10.1186/gb-2010-11-12-r119
45. Reznikoff WS. Transposon Tn5. Ann Rev Genet 2008; 42:269-86; PMID:18680433; http://dx.doi.org/10.1146/annurev.genet.42.110807.091656
46. Reznikoff WS. Tn5 as a model for understanding DNA transposition. Mol Microbiol 2003; 47:1199-206; PMID:12603728; http://dx.doi.org/10.1046/j.1365-2958.2003.03382.x
47. Goryshin IY, Reznikoff WS. Tn5 in vitro transposition. J Biol Chem 1998; 273:7367-74; PMID:9516433; http://dx.doi.org/10.1074/jbc.273.13.7367
48. Lamble S, Batty E, Attar M, Buck D, Bowden R, Lunter G, Crook D, El-Fahmawi B, Piazza P. Improved workflows for high throughput library preparation using the transposome-based Nextera system. BMC Biotechnol 2013; 13:104; PMID:24256843; http://dx.doi.org/10.1186/1472-6750-13-104
49. Shapland EB, Holmes V, Reeves CD, Sorokin E, Durot M, Platt D, Allen C, Dean J, Serber Z, Newman J, et al. Low-Cost, High-Throughput Sequencing of DNA Assemblies Using a Highly Multiplexed Nextera Process. ACS Synthetic Biol 2015; 4:860-6; PMID:25913499; http://dx.doi.org/10.1021/sb500362n
50. Combs PA, Eisen MB. Low-cost, low-input RNA-seq protocols perform nearly as well as high-input protocols. PeerJ 2015; 3:e869; PMID:25834775; http://dx.doi.org/10.7717/peerj.869
51. Ke R, Mignardi M, Pacureanu A, Svedlund J, Botling J, Wahlby C, Nilsson M. In situ sequencing for RNA analysis in preserved tissue and cells. Nat Methods 2013; 10:857-60; PMID:23852452; http://dx.doi.org/10.1038/nmeth.2563
52. Crosetto N, Bienko M, van Oudenaarden A. Spatially resolved transcriptomics and beyond. Nat Rev Genet 2015; 16:57-66; PMID:25446315; http://dx.doi.org/10.1038/nrg3832
53. Kasianowicz JJ, Brandin E, Branton D, Deamer DW. Characterization of individual polynucleotide molecules using a membrane channel. Proc Natl Acad Sci U S A 1996; 93:13770-3; PMID:8943010; http://dx.doi.org/10.1073/pnas.93.24.13770
54. Bayley H. Nanopore sequencing:from imagination to reality. Clin Chem 2015; 61:25-31; PMID:25477535; http://dx.doi.org/10.1373/clinchem.2014.223016
55. Ayub M, Hardwick SW, Luisi BF, Bayley H. Nanopore-based identification of individual nucleotides for direct RNA sequencing. Nano letters 2013; 13:6144-50; PMID:24171554; http://dx.doi.org/10.1021/nl403469r
56. Cracknell JA, Japrung D, Bayley H. Translocating kilobase RNA through the Staphylococcal alpha-hemolysin nanopore. Nano letters 2013; 13:2500-5; PMID:23678965; http://dx.doi.org/10.1021/nl400560r
57. Macaulay IC, Haerty W, Kumar P, Li YI, Hu TX, Teng MJ, Goolam M, Saurat N, Coupland P, Shirley LM, et al. G&T-seq:parallel sequencing of single-cell genomes and transcriptomes. Nat Methods 2015; 12:519-22; PMID:25915121; http://dx.doi.org/10.1038/nmeth.3370
58. Dey SS, Kester L, Spanjaard B, Bienko M, van Oudenaarden A. Integrated genome and transcriptome sequencing of the same cell. Nat Biotechnol 2015; 33:285-9; PMID:25599178; http://dx.doi.org/10.1038/nbt.3129
59. Smallwood SA, Lee HJ, Angermueller C, Krueger F, Saadeh H, Peat J, Andrews SR, Stegle O, Reik W, Kelsey G. Single-cell genome-wide bisulfite sequencing for assessing epigenetic heterogeneity. Nat Methods 2014; 11:817-20; PMID:25042786; http://dx.doi.org/10.1038/nmeth.3035
60. Guo H, Zhu P, Wu X, Li X, Wen L, Tang F. Single-cell methylome landscapes of mouse embryonic stem cells and early embryos analyzed using reduced representation bisulfite sequencing. Genome Res 2013; 23:2126-35; PMID:24179143; http://dx.doi.org/10.1101/gr.161679.113
61. Hou Y, Guo H, Cao C, Li X, Hu B, Zhu P, Wu X, Wen L, Tang F, Huang Y, et al. Single-cell triple omics sequencing reveals genetic, epigenetic, and transcriptomic heterogeneity in hepatocellular carcinomas. Cell Res 2016; 26:304-19; PMID:26902283; http://dx.doi.org/10.1038/cr.2016.23
62. Sharon D, Tilgner H, Grubert F, Snyder M. A single-molecule long-read survey of the human transcriptome. Nat Biotechnol 2013; 31:1009-14; PMID:24108091; http://dx.doi.org/10.1038/nbt.2705