单细胞测序研究进展及其在口腔医学中的应用

摘要/Abstract

摘要： 单细胞测序是指在单细胞层面对细胞内的物质，特别是遗传物质进行检测、识别和分析，其分辨率可以达到单分子水平。单细胞测序通过获取和分析基因组、表观组（包括DNA甲基化、染色体可及性和染色质拓扑学等）、转录组以及空间组等信息来定义细胞类型，深入研究细胞功能、细胞谱系、细胞迁移和转变以及其中的分子对细胞命运决定的影响等。近年来，为提高单细胞测序因噪声而受限的效用和研究组学之间的相互关系，单细胞测序从单一组学迈向多组学，被广泛应用于生命科学研究的多个领域，为其发展提供了强大的技术支持。

关键词: 单细胞测序, 多组学单细胞测序, 生命科学研究

Abstract: Single-cell sequencing refers to the detection, identification and analysis of cell components especially genetic materials at the single-cell level, which can reach single-molecule resolution. Single-cell sequencing captures and analyzes the information about genome, epigenome (including DNA methylation, chromosome accessibility and chromatin topology, etc.), transcriptome as well as cell topological space to define the cell types and further study cellular function, cell lineage, cell migration and transformation as well as cell the molecular effects on cell fate determination and so on. In recent years, to improve the noise-limited effectiveness of single-cell sequencing and research the interrelationship between different omics, single-cell sequencing has developed from single-omics to multi-omics and has been widely used in many fields of life science such as molecular biology, developmental biology, neuroscience, tumor research and immunology, providing powerful technical support for life science research.

Key words: single cell sequencing, multi-omics single cell sequencing, life science research

中图分类号:

R446.7

郑明霞谭俊龙刘湘宁张永彪王晓刚. 单细胞测序研究进展及其在口腔医学中的应用[J]. 口腔医学, 2020, 40(4): 353-361.

参考文献 85

[1]	Tang F, Barbacioru C, Wang Y, et al. mRNA-Seq whole-transcriptome analysis of a single cell[J]. Nature methods, 2009, 6(5): 377-377.
[2]	Baslan T, Kendall J, Rodgers L, et al. Genome-wide copy number analysis of single cells[J]. Nature protocols, 2012, 7(6): 1024-1024.
[3]	Grindberg R V, Yee-Greenbaum J L, Mcconnell M J, et al. RNA-sequencing from single nuclei[J]. Proceedings of the National Academy of Sciences, 2013, 110(49): 19802-19807.
[4]	Navin N E. Cancer genomics: one cell at a time[J]. Genome biology, 2014, 15(8): 452-452.
[5]	Prakadan S M, Shalek A K, Weitz D A. Scaling by shrinking: empowering single-cell'omics' with microfluidic devices[J]. Nature Reviews Genetics, 2017, 18(6): 345-345.
[6]	Heitzer E, Auer M, Gasch C, et al. Complex tumor genomes inferred from single circulating tumor cells by array-CGH and next-generation sequencing[J]. Cancer research, 2013, 73(10): 2965-2975.
[7]	Ozsolak F. Third-generation sequencing techniques and applications to drug discovery[J]. Expert opinion on drug discovery, 2012, 7(3): 231-243.
[8]	Zong C, Lu S, Chapman A R, et al. Genome-wide detection of single-nucleotide and copy-number variations of a single human cell[J]. Science, 2012, 338(6114): 1622-1626.
[9]	Lasken R S. Single-cell genomic sequencing using multiple displacement amplification[J]. Current opinion in microbiology, 2007, 10(5): 510-516.
[10]	Fu Y, Li C, Lu S, et al. Uniform and accurate single-cell sequencing based on emulsion whole-genome amplification[J]. Proceedings of the National Academy of Sciences, 2015, 112(38): 11923-11928.
[11]	Leung M L, Wang Y, Waters J, et al. SNES: single nucleus exome sequencing[J]. Genome biology, 2015, 16(1): 55-55.
[12]	Han H, Zhang Y, Liu W, et al. Degenerate Oligonucleotide Primed–Polymerase Chain Reaction-Based Chromosome Painting of P Genome Chromosomes in Agropyron cristatum and Wheat–A. cristatum Addition Lines[J]. Crop Science, 2015, 55(6): 2798-2805.
[13]	Gao R, Davis A, Mcdonald T O, et al. Punctuated copy number evolution and clonal stasis in triple-negative breast cancer[J]. Nature genetics, 2016, 48(10): 1119-1119.
[14]	Blagodatskikh K A, Kramarov V M, Barsova E V, et al. Improved DOP-PCR (iDOP-PCR): A robust and simple WGA method for efficient amplification of low copy number genomic DNA[J]. PloS one, 2017, 12(9): e0184507-0184507.
[15]	Hou Y, Wu K, Shi X, et al. Comparison of variations detection between whole-genome amplification methods used in single-cell resequencing[J]. Gigascience, 2015, 4(1): 37-37.
[16]	De Bourcy C F, De Vlaminck I, Kanbar J N, et al. A quantitative comparison of single-cell whole genome amplification methods[J]. PloS one, 2014, 9(8): e105585-105585.
[17]	Islam S, Kj?llquist U, Moliner A, et al. Characterization of the single-cell transcriptional landscape by highly multiplex RNA-seq[J]. Genome research, 2011, 21(7): 1160-1167.
[18]	Hashimshony T, Wagner F, Sher N, et al. CEL-Seq: single-cell RNA-Seq by multiplexed linear amplification[J]. Cell reports, 2012, 2(3): 666-673.
[19]	Macaulay I C, Voet T. Single cell genomics: advances and future perspectives[J]. PLoS genetics, 2014, 10(1): e1004126-1004126.
[20]	Schadt E E, Turner S, Kasarskis A. A window into third-generation sequencing[J]. Human molecular genetics, 2010, 19(R2): R227-R240.
[21]	Zheng G X Y, Terry J M, Belgrader P, et al. Massively parallel digital transcriptional profiling of single cells[J]. Nature communications, 2017, 8(8): 14049-14049.
[22]	Wolf F A, Angerer P, Theis F J. SCANPY: large-scale single-cell gene expression data analysis[J]. Genome biology, 2018, 19(1): 15-15.
[23]	Satija R, Farrell J A, Gennert D, et al. Spatial reconstruction of single-cell gene expression data[J]. Nature biotechnology, 2015, 33(5): 495-495.
[24]	Trapnell C, Cacchiarelli D, Grimsby J, et al. The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells[J]. Nature biotechnology, 2014, 32(4): 381-381.
[25]	Treutlein B, Brownfield D G, Wu A R, et al. Reconstructing lineage hierarchies of the distal lung epithelium using single-cell RNA-seq[J]. Nature, 2014, 509(7500): 371-371.
[26]	Saadatpour A, Guo G, Orkin S H, et al. Characterizing heterogeneity in leukemic cells using single-cell gene expression analysis[J]. Genome biology, 2014, 15(12): 525-525.
[27]	Shapiro E, Biezuner T, Linnarsson S. Single-cell sequencing-based technologies will revolutionize whole-organism science[J]. Nature Reviews Genetics, 2013, 14(9): 618-618.
[28]	Ning L, Liu G, Li G, et al. Current challenges in the bioinformatics of single cell genomics[J]. Frontiers in oncology, 2014, 4(4): 7-7.
[29]	Baslan T, Kendall J, Ward B, et al. Optimizing sparse sequencing of single cells for highly multiplex copy number profiling[J]. Genome research, 2015, 25(5): 714-724.
[30]	Wang J, Fan H C, Behr B, et al. Genome-wide single-cell analysis of recombination activity and de novo mutation rates in human sperm[J]. Cell, 2012, 150(2): 402-412.
[31]	Navin N, Kendall J, Troge J, et al. Tumour evolution inferred by single-cell sequencing[J]. Nature, 2011, 472(7341): 90-90.
[32]	Ng S B, Turner E H, Robertson P D, et al. Targeted capture and massively parallel sequencing of 12 human exomes[J]. Nature, 2009, 461(7261): 272-272.
[33]	Zhang X, Marjani S L, Hu Z, et al. Single-cell sequencing for precise cancer research: progress and prospects[J]. Cancer Research, 2016, 76(6): 1305-1312.
[34]	Hou Y, Song L, Zhu P, et al. Single-cell exome sequencing and monoclonal evolution of a JAK2-negative myeloproliferative neoplasm[J]. Cell, 2012, 148(5): 873-885.
[35]	Xu X, Hou Y, Yin X, et al. Single-cell exome sequencing reveals single-nucleotide mutation characteristics of a kidney tumor[J]. Cell, 2012, 148(5): 886-895.
[36]	Goldberg A D, Allis C D, Bernstein E. Epigenetics: a landscape takes shape[J]. Cell, 2007, 128(4): 635-638.
[37]	Guo H, Zhu P, Guo F, et al. Profiling DNA methylome landscapes of mammalian cells with single-cell reduced-representation bisulfite sequencing[J]. Nature protocols, 2015, 10(5): 645-645.
[38]	Lorthongpanich C, Cheow L F, Balu S, et al. Single-cell DNA-methylation analysis reveals epigenetic chimerism in preimplantation embryos[J]. Science, 2013, 341(6150): 1110-1112.
[39]	Smallwood S A, Lee H J, Angermueller C, et al. Single-cell genome-wide bisulfite sequencing for assessing epigenetic heterogeneity[J]. Nature methods, 2014, 11(8): 817-817.
[40]	Clark S J, Smallwood S A, Lee H J, et al. Genome-wide base-resolution mapping of DNA methylation in single cells using single-cell bisulfite sequencing (scBS-seq) [J]. Nature protocols, 2017, 12(3): 534-534.
[41]	Mulqueen R M, Pokholok D, Norberg S J, et al. Highly scalable generation of DNA methylation profiles in single cells[J]. Nature biotechnology, 2018, 36(5): 428-428.
[42]	Luo C, Keown C L, Kurihara L, et al. Single-cell methylomes identify neuronal subtypes and regulatory elements in mammalian cortex[J]. Science, 2017, 357(6351): 600-604.
[43]	Denny S K, Yang D, Chuang C-H, et al. Nfib promotes metastasis through a widespread increase in chromatin accessibility[J]. Cell, 2016, 166(2): 328-342.
[44]	Buenrostro J D, Wu B, Litzenburger U M, et al. Single-cell chromatin accessibility reveals principles of regulatory variation[J]. Nature, 2015, 523(7561): 486-486.
[45]	Jin W, Tang Q, Wan M, et al. Genome-wide detection of DNase I hypersensitive sites in single cells and FFPE tissue samples[J]. Nature, 2015, 528(7580): 142-142.
[46]	Lu F, Liu Y, Inoue A, et al. Establishing chromatin regulatory landscape during mouse preimplantation development[J]. Cell, 2016, 165(6): 1375-1388.
[47]	Cavalli G, Misteli T. Functional implications of genome topology[J]. Nature structural & molecular biology, 2013, 20(3): 290-290.
[48]	Fudenberg G, Getz G, Meyerson M, et al. High order chromatin architecture shapes the landscape of chromosomal alterations in cancer[J]. Nature biotechnology, 2011, 29(12): 1109-1109.
[49]	Lupiá?ez D G, Spielmann M, Mundlos S. Breaking TADs: how alterations of chromatin domains result in disease[J]. Trends in Genetics, 2016, 32(4): 225-237.
[50]	Lupiá?ez D G, Kraft K, Heinrich V, et al. Disruptions of topological chromatin domains cause pathogenic rewiring of gene-enhancer interactions[J]. Cell, 2015, 161(5): 1012-1025.
[51]	Nagano T, Lubling Y, Stevens T J, et al. Single-cell Hi-C reveals cell-to-cell variability in chromosome structure[J]. Nature, 2013, 502(7469): 59-59.
[52]	Ramani V, Deng X, Qiu R, et al. Massively multiplex single-cell Hi-C[J]. Nature methods, 2017, 14(3): 263-263.
[53]	Flyamer I M, Gassler J, Imakaev M, et al. Single-nucleus Hi-C reveals unique chromatin reorganization at oocyte-to-zygote transition[J]. Nature, 2017, 544(7648): 110-110.
[54]	Kolodziejczyk A A, Kim J K, Svensson V, et al. The technology and biology of single-cell RNA sequencing[J]. Molecular cell, 2015, 58(4): 610-620.
[55]	Xue Z, Huang K, Cai C, et al. Genetic programs in human and mouse early embryos revealed by single-cell RNA sequencing[J]. Nature, 2013, 500(7464): 593-593.
[56]	Mahata B, Zhang X, Kolodziejczyk A A, et al. Single-cell RNA sequencing reveals T helper cells synthesizing steroids de novo to contribute to immune homeostasis[J]. Cell reports, 2014, 7(4): 1130-1142.
[57]	Shalek A K, Satija R, Adiconis X, et al. Single-cell transcriptomics reveals bimodality in expression and splicing in immune cells[J]. Nature, 2013, 498(7453): 236-236.
[58]	Tirosh I, Venteicher A S, Hebert C, et al. Single-cell RNA-seq supports a developmental hierarchy in human oligodendroglioma[J]. Nature, 2016, 539(7628): 309-309.
[59]	Klein A M, Mazutis L, Akartuna I, et al. Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells[J]. Cell, 2015, 161(5): 1187-1201.
[60]	Cao J, Packer J S, Ramani V, et al. Comprehensive single-cell transcriptional profiling of a multicellular organism[J]. Science, 2017, 357(6352): 661-667.
[61]	Rosenberg A B, Roco C M, Muscat R A, et al. Single-cell profiling of the developing mouse brain and spinal cord with split-pool barcoding[J]. Science, 2018, 360(6385): 176-182.
[62]	Peng G, Tam P P, Jing N. Lineage specification of early embryos and embryonic stem cells at the dawn of enabling technologies[J]. National Science Review, 2017, 4(4): 533-542.
[63]	Kruse F, Junker J P, van Oudenaarden A, et al. Tomo-seq: A method to obtain genome-wide expression data with spatial resolution[M]//Methods in cell biology. Academic Press, 2016, 135: 299-307.
[64]	Chen J, Suo S, Tam P P, et al. Spatial transcriptomic analysis of cryosectioned tissue samples with Geo-seq[J]. nature protocols, 2017, 12(3): 566-566.
[65]	Lee J H, Daugharthy E R, Scheiman J, et al. Highly multiplexed subcellular RNA sequencing in situ[J]. Science, 2014, 343(6177): 1360-1363.
[66]	Casasent A K, Schalck A, Gao R, et al. Multiclonal invasion in breast tumors identified by topographic single cell sequencing[J]. Cell, 2018, 172(1-2): 205-217. e212.
[67]	You J S, Kelly T K, De Carvalho D D, et al. OCT4 establishes and maintains nucleosome-depleted regions that provide additional layers of epigenetic regulation of its target genes[J]. Proceedings of the National Academy of Sciences, 2011, 108(35): 14497-14502.
[68]	Guo F, Yan L, Guo H, et al. The transcriptome and DNA methylome landscapes of human primordial germ cells[J]. Cell, 2015, 161(6): 1437-1452.
[69]	Linker S M, Urban L, Clark S J, et al. Combined single-cell profiling of expression and DNA methylation reveals splicing regulation and heterogeneity[J]. Genome biology, 2019, 20(1): 30-30.
[70]	Gu C, Liu S, Wu Q, et al. Integrative single-cell analysis of transcriptome, DNA methylome and chromatin accessibility in mouse oocytes[J]. Cell research, 2019, 29(2): 110-110.
[71]	Guo F, Li L, Li J, et al. Single-cell multi-omics sequencing of mouse early embryos and embryonic stem cells[J]. Cell research, 2017, 27(8): 967-967.
[72]	Lake B B, Chen S, Sos B C, et al. Integrative single-cell analysis of transcriptional and epigenetic states in the human adult brain[J]. Nature biotechnology, 2018, 36(1): 70-70.
[73]	Wang Y, Waters J, Leung M L, et al. Clonal evolution in breast cancer revealed by single nucleus genome sequencing[J]. Nature, 2014, 512(7513): 155-155.
[74]	Reuter J A, Spacek D V, Pai R K, et al. Simul-seq: combined DNA and RNA sequencing for whole-genome and transcriptome profiling[J]. Nature methods, 2016, 13(11): 953-953.
[75]	Cao J, Cusanovich D A, Ramani V, et al. Joint profiling of chromatin accessibility and gene expression in thousands of single cells[J]. Science, 2018, 361(6409): 1380-1385.
[76]	Darmanis S, Gallant C J, Marinescu V D, et al. Simultaneous multiplexed measurement of RNA and proteins in single cells[J]. Cell reports, 2016, 14(2): 380-389.
[77]	Genshaft A S, Li S, Gallant C J, et al. Multiplexed, targeted profiling of single-cell proteomes and transcriptomes in a single reaction[J]. Genome biology, 2016, 17(1): 188-188.
[78]	Youngálee J, Hunálee S. Dual transcript and protein quantification in a massive single cell array[J]. Lab on a Chip, 2016, 16(19): 3682-3688.
[79]	Xue M, Wei W, Su Y, et al. Chemical methods for the simultaneous quantitation of metabolites and proteins from single cells[J]. Journal of the American Chemical Society, 2015, 137(12): 4066-4069.
[80]	Hou Y, Guo H, Cao C, et al. Single-cell triple omics sequencing reveals genetic, epigenetic, and transcriptomic heterogeneity in hepatocellular carcinomas[J]. Cell research, 2016, 26(3): 304-304.
[81]	George J, Wang J. Assay of genome-wide transcriptome and secreted proteins on the same single immune cells by microfluidics and RNA sequencing[J]. Analytical chemistry, 2016, 88(20): 10309-10315.
[82]	Stoeckius M, Hafemeister C, Stephenson W, et al. Simultaneous epitope and transcriptome measurement in single cells[J]. Nature methods, 2017, 14(9): 865-865.
[83]	Peterson V M, Zhang K X, Kumar N, et al. Multiplexed quantification of proteins and transcripts in single cells[J]. Nature biotechnology, 2017, 35(10): 936-936.
[84]	Geiger R, Rieckmann J C, Wolf T, et al. L-arginine modulates T cell metabolism and enhances survival and anti-tumor activity[J]. Cell, 2016, 167(3): 829-842. e813.
[85]	Regev A, Teichmann S A, Lander E S, et al. Science forum: the human cell atlas[J]. Elife, 2017, 6(6): e27041-27041.