{"title":"单细胞RNA测序简介","authors":"Thale Kristin Olsen, Ninib Baryawno","doi":"10.1002/cpmb.57","DOIUrl":null,"url":null,"abstract":"<p>During the last decade, high-throughput sequencing methods have revolutionized the entire field of biology. The opportunity to study entire transcriptomes in great detail using RNA sequencing (RNA-seq) has fueled many important discoveries and is now a routine method in biomedical research. However, RNA-seq is typically performed in “bulk,” and the data represent an average of gene expression patterns across thousands to millions of cells; this might obscure biologically relevant differences between cells. Single-cell RNA-seq (scRNA-seq) represents an approach to overcome this problem. By isolating single cells, capturing their transcripts, and generating sequencing libraries in which the transcripts are mapped to individual cells, scRNA-seq allows assessment of fundamental biological properties of cell populations and biological systems at unprecedented resolution. Here, we present the most common scRNA-seq protocols in use today and the basics of data analysis and discuss factors that are important to consider before planning and designing an scRNA-seq project. © 2018 by John Wiley & Sons, Inc.</p>","PeriodicalId":10734,"journal":{"name":"Current Protocols in Molecular Biology","volume":"122 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2018-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/cpmb.57","citationCount":"95","resultStr":"{\"title\":\"Introduction to Single-Cell RNA Sequencing\",\"authors\":\"Thale Kristin Olsen, Ninib Baryawno\",\"doi\":\"10.1002/cpmb.57\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>During the last decade, high-throughput sequencing methods have revolutionized the entire field of biology. The opportunity to study entire transcriptomes in great detail using RNA sequencing (RNA-seq) has fueled many important discoveries and is now a routine method in biomedical research. However, RNA-seq is typically performed in “bulk,” and the data represent an average of gene expression patterns across thousands to millions of cells; this might obscure biologically relevant differences between cells. Single-cell RNA-seq (scRNA-seq) represents an approach to overcome this problem. By isolating single cells, capturing their transcripts, and generating sequencing libraries in which the transcripts are mapped to individual cells, scRNA-seq allows assessment of fundamental biological properties of cell populations and biological systems at unprecedented resolution. Here, we present the most common scRNA-seq protocols in use today and the basics of data analysis and discuss factors that are important to consider before planning and designing an scRNA-seq project. © 2018 by John Wiley & Sons, Inc.</p>\",\"PeriodicalId\":10734,\"journal\":{\"name\":\"Current Protocols in Molecular Biology\",\"volume\":\"122 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-04-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1002/cpmb.57\",\"citationCount\":\"95\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Current Protocols in Molecular Biology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/cpmb.57\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Biochemistry, Genetics and Molecular Biology\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current Protocols in Molecular Biology","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/cpmb.57","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Biochemistry, Genetics and Molecular Biology","Score":null,"Total":0}
引用次数: 95