DOI: 10.3724/SP.J.1005.2011.00017

Hereditas (Beijing) (遗传) 2011/33:1 PP.17-24

Technological advances in single-cell genomic analyses

The technological progress of the genomics has transformed life science research. The main objectives of genomics are sequencing of new genomes and genome-wide identification of the function and the interaction of genes and their products. The recently developed second generation or next generation sequencing platforms and DNA microarray technology are immensely important and powerful tools for functional genomic analyses. However, their application is limited by the requirement of sufficient amounts of high quality nucleic acid samples. Therefore, when only a single cell or a very small number of cells are available or are preferred, the whole genomic sequencing or functional genomic objectives cannot be achieved conventionally and require a robust amplification method. This review highlights DNA amplification technologies and summarizes the strategies currently utilized for whole genome sequencing of a single cell, with specific focus on studies investigating microorganisms; An outline for targeted re-sequencing enabling the analysis of larger genomes is also provided. Furthermore, the review presents the emerging functional genomic applications using next-generation sequencing or microarray analysis to examine genome-wide transcriptional profile, chromatin modification and other types of protein-DNA binding profile, and CpG methylation mapping in a single cell or a very low quantity of cells. The nature of these technologies and their prospects are also addressed.

Key words:single-cell sequencing,next generation sequencing,functional genomics,transcriptome profiling,chromatin immunoprecipitation,CpG methylation mapping

ReleaseDate:2014-07-21 15:42:18

[1] Liu ET. Functional genomics of cancer. Curr Opin Genet Dev, 2008, 18(3): 251-256.

[2] Geschwind DH, Konopka G. Neuroscience in the era of functional genomics and systems biology. Nature, 2009, 461(7266): 908-915.

[3] Pieroni E, de la Fuente van Bentem S, Mancosu G, Capobianco E, Hirt H, de la Fuente A. Protein networking: insights into global functional organization of proteomes. Proteomics, 2008, 8(4): 799-816.

[4] Abu-Farha M, Elisma F, Zhou H, Tian R, Zhou H, Asmer MS, Figeys D. Proteomics: from technology developments to biological applications. Anal Chem, 2009, 81(12): 4585-4599.

[5] Wilusz JE, Sunwoo H, Spector DL. Long noncoding RNAs: functional surprises from the RNAworld. Genes Dev, 2009, 23(13): 1494-1504.

[6] Chen PY, Meister G. MicroRNA-guided posttranscriptional gene regulation. Biol Chem, 2005, 386(12): 1205-1218.

[7] Butcher LM, Beck S. Future impact of integrated high-throughput methylome analyses on human health and disease. J Genet Genomics, 2008, 35(7): 391-401.

[8] Beck S, Rakyan VK. The methylome: approaches for global DNA methylation profiling. Trends Genet, 2008, 24(5): 231-237.

[9] Morozova O, Marra MA. Applications of next-generation sequencing technologies in functional genomics. Genomics, 2008, 92(5): 255-264.

[10] Wold B, Myers RM. Sequence census methods for functional genomics. Nat Methods, 2008, 5(1): 19-21.

[11] 谭建新, 孙玉洁. 表观基因组学研究方法进展与评价. 遗传, 2009, 31(1): 3-12.

[12] Suzuki MM, Bird A. DNA methylation landscapes: provocative insights from epigenomics. Nat Rev Genet, 2008, 9(6): 465-476.

[13] Jirtle RL, Skinner MK. Environmental epigenomics and disease susceptibility. Nat Rev Genet, 2007, 8(4): 253-262.

[14] Esteller M. Cancer epigenomics: DNA methylomes and histone-modification maps. Nat Rev Genet, 2007, 8(4): 286-298.

[15] Gondo Y. Trends in large-scale mouse mutagenesis: from genetics to functional genomics. Nat Rev Genet, 2008, 9(10): 803-810.

[16] Gondo Y, Fukumura R, Murata T, Makino S. Next-generation gene targeting in the mouse for functional genomics. BMB Rep, 2009, 42(6): 315-323.

[17] Shendure J, Ji H. Next-generation DNA sequencing. Nat Biotechnol, 2008, 26(10): 1135-1145.

[18] Mardis ER. The impact of next-generation sequencing technology on genetics. Trends Genet, 2008, 24(3): 133-141.

[19] Wang Z, Gerstein M, Snyder M. RNA-seq: a revolutionary tool for transcriptomics. Nat Rev Genet, 2009, 10(1): 57-63.

[20] Metzker ML. Sequencing technologies-the next generation. Nat Rev Genet, 2010, 11(1): 31-46.

[21] Pushkarev D, Neff NF, Quake SR. Single-molecule sequencing of an individual human genome. Nat Biotechnol, 2009, 27(9): 847-850.

[22] Ozsolak F, Platt AR, Jones DR, Reifenberger JG, Sass LE, McInerney P, Thompson JF, Bowers J, Jarosz M, Milos PM. Direct RNA sequencing. Nature, 2009, 461(7265): 814-818.

[23] Ozsolak F, Ting DT, Wittner BS, Brannigan BW, Paul S, Bardeesy N, Ramaswamy S, Milos PM, Haber DA. Amplification-free digital gene expression profiling from minute cell quantities. Nat Methods, 2010, 7(8): 619-621.

[24] Walker A, Parkhill J. Single-cell genomics. Nat Rev Microbiol, 2008, 6(3): 176-177.

[25] Ochman H. Single-cell genomics. Environ Microbiol, 2007, 9(1): 7.

[26] Hamady M, Knight R. Microbial community profiling for human microbiome projects: tools, techniques, and challenges. Genome Res, 2009, 19(7): 1141-1152.

[27] Weckx S, De Vuyst L. Metagenome and metatranscriptome analysis: does the flag always cover the cargo? Int J Food Microbiol, 2009, 133(3): 292-293.

[28] Baveye PC. To sequence or not to sequence the whole-soil metagenome? Nat Rev Microbiol, 2009, 7(10): 756; author reply 756-757.

[29] Rajendhran J, Gunasekaran P. Strategies for accessing soil metagenome for desired applications. Biotechnol Adv, 2008, 26(6): 576-590.

[30] Hutchison CA, 3rd, Venter JC. Single-cell genomics. Nat Biotechnol, 2006, 24(6): 657-658.

[31] Polyak K. Going small is the new big. Nat Methods, 2010, 7(8): 597, 599-600.

[32] Ma C, Donnelly DF, LaMotte RH. In vivo visualization and functional characterization of primary somatic neurons. J Neurosci Methods, 2010, 191(1): 60-65.

[33] Zhao R. From single cell gene-based diagnostics to diagnostic genomics: Current applications and future perspectives. Clin Lab Sci, 2005, 18(4): 254-262.

[34] Klein CA, Hölzel D. Systemic cancer progression and tumor dormancy: mathematical models meet single cell genomics. Cell Cycle, 2006, 5(16): 1788-1798.

[35] Lange BM. Single-cell genomics. Curr Opin Plant Biol, 2005, 8(3): 236-241.

[36] Lasken RS. Single-cell genomic sequencing using Multiple Displacement Amplification. Curr Opin Microbiol, 2007, 10(5): 510-516.

[37] Mussmann M, Hu FZ, Richter M, de Beer D, Preisler A, Jorgensen BB, Huntemann M, Glockner FO, Amann R, Koopman WJ, Lasken RS, Janto B, Hogg J, Stoodley P, Boissy R, Ehrlich GD. Insights into the genome of large sulfur bacteria revealed by analysis of single filaments. PLoS Biol, 2007, 5(9): e230.

[38] Ishoey T, Woyke T, Stepanauskas R, Novotny M, Lasken RS. Genomic sequencing of single microbial cells from environmental samples. Curr Opin Microbiol, 2008, 11(3): 198-204.

[39] Dean FB, Hosono S, Fang LH, Wu XH, Faruqi AF, Bray-Ward P, Sun ZY, Zong QL, Du YF, Du J, Driscoll M, Song WM, Kingsmore SF, Egholm M, Lasken RS. Comprehensive human genome amplification using multiple displacement amplification. Proc Natl Acad Sci USA, 2002, 99(8): 5261-526.

[40] Lasken RS. Genomic DNA amplification by the multiple displacement amplification (MDA) method. Biochem Soc Trans, 2009, 37(Pt 2): 450-453.

[41] Pan XH, Urban AE, Palejev D, Schulz V, Grubert F, Hu YP, Snyder M, Weissman SM. A procedure for highly specific, sensitive, and unbiased whole-genome amplification. Proc Natl Acad Sci USA, 2008, 105(40): 15499-15504.

[42] Woyke T, Xie G, Copeland A, Gonzalez JM, Han C, Kiss H, Saw JH, Senin P, Yang C, Chatterji S, Cheng JF, Eisen JA, Sieracki ME, Stepanauskas R. Assembling the marine metagenome, one cell at a time. PLoS One, 2009, 4(4): e5299.

[43] Janda JM, Abbott SL. 16s rRNA gene sequencing for bacterial identification in the diagnostic laboratory: pluses, perils, and pitfalls. J Clin Microbiol, 2007, 45(9): 2761-2764.

[44] Mamanova L, Coffey AJ, Scott CE, Kozarewa I, Turner EH, Kumar A, Howard E, Shendure J, Turner DJ. Target-enrichment strategies for next-generation sequencing. Nat Methods, 2010, 7(2): 111-118.

[45] Vanneste E, Voet T, Le Caignec C, Ampe M, Konings P, Melotte C, Debrock S, Amyere M, Vikkula M, Schuit F, Fryns JP, Verbeke G, D'Hooghe T, Moreau Y, Vermeesch JR. Chromosome instability is common in human cleavage-stage embryos. Nat Med, 2009, 15(5): 577-583.

[46] Ling JW, Zhuang GL, Tazon-Vega B, Zhang CH, Cao BQ, Rosenwaks Z, Xu KP. Evaluation of genome coverage and fidelity of multiple displacement amplification from single cells by SNP array. Mol Hum Reprod, 2009, 15(11): 739-747.

[47] Werner T. Next generation sequencing in functional genomics. Brief Bioinform, 2010, 11 (5): 499-511.

[48] Marguerat S, Bähler J. RNA-seq: from technology to biology. Cell Mol Life Sci, 2010, 67(4): 569-579.

[49] Wang E. RNA amplification for successful gene profiling analysis. J Transl Med, 2005, 3(1): 28.

[50] 李轶女, 胡英考, 张志芳, 沈桂芳. RNA扩增的研究进展. 遗传, 2007, 29(8): 907-914.

[51] Ginsberg SD. RNA amplification strategies for small sample populations. Methods, 2005, 37(3): 229-237.

[52] Tang FC, Barbacioru C, Wang YZ, Nordman E, Lee C, Xu NL, Wang XH, Bodeau J, Tuch BB, Siddiqui A, Lao KQ, Surani MA. mRNA-seq whole-transcriptome analysis of a single cell. Nat Methods, 2009, 6(5): 377-382.

[53] Tang FC, Hajkova P, Barton SC, O'Carroll D, Lee C, Lao KQ, Surani MA. 220-plex microRNA expression profile of a single cell. Nat Protoc, 2006, 1(3): 1154-1159.

[54] Acevedo LG, Iniguez AL, Holster HL, Zhang XM, Green R, Farnham PJ. Genome-scale chip-chip analysis using 10,000 human cells. Biotechniques, 2007, 43(6): 791-797.

[55] Dahl JA, Reiner AH, Collas P. Fast genomic µCHIP-chip from 1,000 cells. Genome Biol, 2009, 10(2): R13.

[56] Adli M, Zhu J, Bernstein BE. Genome-wide chromatin maps derived from limited numbers of hematopoietic progenitors. Nat Methods, 2010, 7(8): 615-618.

[57] Fouse SD, Nagarajan RP, Costello JF. Genome-scale DNA methylation analysis. Epigenomics, 2010, 2(1): 105-117.

[58] Zilberman D, Henikoff S. Genome-wide analysis of DNA methylation patterns. Development, 2007, 134(22): 3959-3965.

[59] Shames DS, Minna JD, Gazdar AF. Methods for detecting DNA methylation in tumors: from bench to bedside. Cancer Lett, 2007, 251(2): 187-198.

[60] Wang DJ, Bodovitz S. Single cell analysis: The new frontier in 'omics'. Trends Biotechnol, 2010, 28(6): 281-290.