单细胞转录组测序在生殖发育领域应用进展
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摘要
细胞是生物体结构和功能的基本单位,细胞命运的决策是单细胞层面的过程。基因组和表观遗传的重编程,以及在细胞分裂和分化过程中出现的误差造成来自同一细胞系或个体的细胞呈现出不同的基因组、转录组和表观基因组,即细胞异质性。单细胞测序允许对单个细胞进行高通量分子检测,不仅在解决生物异质性方面有着强大的功能,同时在低数量的生物材料问题上有许多优势。单细胞转录组测序(scRNAseq)在观察哺乳动物配子发育以及早期胚胎发育方面均有重要作用,对生殖领域的发展意义重大。现对scRNA-seq在方法学和技术应用的研究进展进行阐述。
Cell is the fundamental unit of the structure and function of lives. The cell fate is a process that decided at the single-cell level. Due to genomic and epigenetic reprogramming, as well as errors in cell division and differentiation, cells from the same lineage or individual varies in genomes, transcriptomes and epigenomes,which is the so-called heterogeneity. Single cell sequencing allows the high-throughput molecular detection of individual cell, which not only has a powerful function in solving biological heterogeneity, but also has many advantages in rare cells problems. The single-cell transcriptome sequencing(scRNA-seq) plays an important role in the observation of mammalian gamete development and early embryo development, and is of great significance for the reproductive development. In this review, we discuss recent progress in methodology and applications of the scRNA-seq.
Cell is the fundamental unit of the structure and function of lives. The cell fate is a process that decided at the single-cell level. Due to genomic and epigenetic reprogramming, as well as errors in cell division and differentiation, cells from the same lineage or individual varies in genomes, transcriptomes and epigenomes,which is the so-called heterogeneity. Single cell sequencing allows the high-throughput molecular detection of individual cell, which not only has a powerful function in solving biological heterogeneity, but also has many advantages in rare cells problems. The single-cell transcriptome sequencing(scRNA-seq) plays an important role in the observation of mammalian gamete development and early embryo development, and is of great significance for the reproductive development. In this review, we discuss recent progress in methodology and applications of the scRNA-seq.
引文
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[33]Bendall SC,Davis KL,Amir el-AD,et al.Single-cell trajectory detection uncovers progression and regulatory coordination in human B cell development[J].Cell,2014,157(3):714-725.
[34]Li L,Dong J,Yan L,et al.Single-Cell RNA-Seq Analysis Maps Development of Human Germline Cells and Gonadal Niche Interactions[J].Cell Stem Cell,2017,20(6):891-892.
[35]Wang M,Liu X,Chang G,et al.Single-Cell RNA Sequencing Analysis Reveals Sequential Cell Fate Transition during Human Spermatogenesis[J].Cell Stem Cell,2018,23(4):599-614.e4.
[36]Guo F,Yan L,Guo H,et al.The Transcriptome and DNAMethylome Landscapes of Human Primordial Germ Cells[J].Cell,2015,161(6):1437-1452.
[37]Zhang Y,Yan Z,Qin Q,et al.Transcriptome Landscape of Human Folliculogenesis Reveals Oocyte and Granulosa Cell Interactions[J].Mol Cell,2018,72(6):1021-1034.e4.
[38]Briggs JA,Weinreb C,Wagner DE,et al.The dynamics of gene expression in vertebrate embryogenesis at single-cell resolution[J].Science,2018,360(6392):5780.
[39]Wagner DE,Weinreb C,Collins ZM,et al.Single-cell mapping of gene expression landscapes and lineage in the zebrafish embryo[J].Science,2018,360(6392):981-987.
[2]Buenrostro JD,Wu B,Chang HY,et al.ATAC-seq:A Method for Assaying Chromatin Accessibility Genome-Wide[J].Curr Protoc Mol Biol,2015,109:21.29.1-21.29.9.
[3]Heath JR,Ribas A,Mischel PS.Single-cell analysis tools for drug discovery and development[J].Nat Rev Drug Discov,2016,15(3):204-216.
[4]Cusanovich DA,Hill AJ,Aghamirzaie D,et al.A Single-Cell Atlas of In Vivo Mammalian Chromatin Accessibility[J].Cell,2018,174(5):1309-1324.e18.
[5]de Souza N.Single-cell genetics[J].Nat Methods,2013,10(9):820.
[6]Tang F,Lao K,Surani MA.Development and applications of single-cell transcriptome analysis[J].Nat Methods,2011,8(Suppl4):S6-S11.
[7]Berteli TS,Da Broi MG,Martins W,et al.Magnetic-activated cell sorting before density gradient centrifugation improves recovery of high-quality spermatozoa[J].Andrology,2017,5(4):776-782.
[8]Lovatt D,Ruble BK,Lee J,et al.Transcriptome in vivo analysis(TIVA)of spatially defined single cells in live tissue[J].Nat Methods,2014,11(2):190-196.
[9]Smith C.Cancer shows strength through diversity[J].Nature,2013,499(7459):505-508.
[10]Jaitin DA,Kenigsberg E,Keren-Shaul H,et al.Massively parallel single-cell RNA-seq for marker-free decomposition of tissues into cell types[J].Science,2014,343(6172):776-779.
[11]Picelli S,Faridani OR,Bjorklund AK,et al.Full-length RNA-seq from single cells using Smart-seq2[J].Nat Protoc,2014,9(1):171-181.
[12]Klein AM,Mazutis L,Akartuna I,et al.Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells[J].Cell,2015,161(5):1187-1201.
[13]Macosko EZ,Basu A,Satija R,et al.Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets[J].Cell,2015,161(5):1202-1214.
[14]Zheng GX,Terry JM,Belgrader P,et al.Massively parallel digital transcriptional profiling of single cells[J].Nat Commun,2017,8:14049.
[15]Shah S,Takei Y,Zhou W,et al.Dynamics and Spatial Genomics of the Nascent Transcriptome by Intron seqFISH[J].Cell,2018,174(2):363-376.e16.
[16]Sasagawa Y,Nikaido I,Hayashi T,et al.Quartz-Seq:a highly reproducible and sensitive single-cell RNA sequencing method,reveals non-genetic gene-expression heterogeneity[J].Genome Biol,2013,14(4):R31.
[17]Ramskold D,Luo S,Wang YC,et al.Full-length mRNA-Seq from single-cell levels of RNA and individual circulating tumor cells[J].Nat Biotechnol,2012,30(8):777-782.
[18]Macaulay IC,Haerty W,Kumar P,et al.G&T-seq:parallel sequencing of single-cell genomes and transcriptomes[J].Nat Methods,2015,12(6):519-522.
[19]Angermueller C,Clark SJ,Lee HJ,et al.Parallel single-cell sequencing links transcriptional and epigenetic heterogeneity[J].Nat Methods,2016,13(3):229-232.
[20]Clark SJ,Argelaguet R,Kapourani CA,et al.scNMT-seq enables joint profiling of chromatin accessibility DNA methylation and transcription in single cells[J].Nat Commun,2018,9(1):781.
[21]Regev A,Teichmann SA,Lander ES,et al.The Human Cell Atlas[J].Elife,2017,6:e27041.
[22]Brennecke P,Anders S,Kim JK,et al.Accounting for technical noise in single-cell RNA-seq experiments[J].Nat Methods,2013,10(11):1093-1095.
[23]Guo M,Wang H,Potter SS,et al.SINCERA:A Pipeline for SingleCell RNA-Seq Profiling Analysis[J].PLoS Comput Biol,2015,11(11):e1004575.
[24]Zeisel A,Munoz-Manchado AB,Codeluppi S,et al.Brain structure.Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq[J].Science,2015,347(6226):1138-1142.
[25]Zhou F,Li X,Wang W,et al.Tracing haematopoietic stem cell formation at single-cell resolution[J].Nature,2016,533(7604):487-492.
[26]Kanter I,Kalisky T.Single cell transcriptomics:methods and applications[J].Front Oncol,2015,5:53.
[27]Trapnell C.Defining cell types and states with single-cell genomics[J].Genome Res,2015,25(10):1491-1498.
[28]Rack B,Schindlbeck C,Jückstock J,et al.Circulating tumor cells predict survival in early average-to-high risk breast cancer patients[J].J Natl Cancer Inst,2014,106(5):dju066.
[29]Haghverdi L,Büttner M,Wolf FA,et al.Diffusion pseudotime robustly reconstructs lineage branching[J].Nat Methods,2016,13(10):845-848.
[30]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].Nat Biotechnol,2014,32(4):381-386.
[31]Chu LF,Leng N,Zhang J,et al.Single-cell RNA-seq reveals novel regulators of human embryonic stem cell differentiation to definitive endoderm[J].Genome Biol,2016,17(1):173.
[32]Pliner HA,PackerJ,McFaline-Figueroa JL,et al.Chromatin accessibility dynamics of myogenesis at single cell resolution[EB/OL].bioRxiv,[2017-06-26].http://dx.doi.org/10.1101/155473.
[33]Bendall SC,Davis KL,Amir el-AD,et al.Single-cell trajectory detection uncovers progression and regulatory coordination in human B cell development[J].Cell,2014,157(3):714-725.
[34]Li L,Dong J,Yan L,et al.Single-Cell RNA-Seq Analysis Maps Development of Human Germline Cells and Gonadal Niche Interactions[J].Cell Stem Cell,2017,20(6):891-892.
[35]Wang M,Liu X,Chang G,et al.Single-Cell RNA Sequencing Analysis Reveals Sequential Cell Fate Transition during Human Spermatogenesis[J].Cell Stem Cell,2018,23(4):599-614.e4.
[36]Guo F,Yan L,Guo H,et al.The Transcriptome and DNAMethylome Landscapes of Human Primordial Germ Cells[J].Cell,2015,161(6):1437-1452.
[37]Zhang Y,Yan Z,Qin Q,et al.Transcriptome Landscape of Human Folliculogenesis Reveals Oocyte and Granulosa Cell Interactions[J].Mol Cell,2018,72(6):1021-1034.e4.
[38]Briggs JA,Weinreb C,Wagner DE,et al.The dynamics of gene expression in vertebrate embryogenesis at single-cell resolution[J].Science,2018,360(6392):5780.
[39]Wagner DE,Weinreb C,Collins ZM,et al.Single-cell mapping of gene expression landscapes and lineage in the zebrafish embryo[J].Science,2018,360(6392):981-987.