文章基本信息

标题：Single-cell quantification of a broad RNA spectrum reveals unique noncoding patterns associated with cell types and states
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作者：Alina Isakova ; Norma Neff ; Stephen R. Quake 等
期刊名称：Proceedings of the National Academy of Sciences
印刷版ISSN：0027-8424
电子版ISSN：1091-6490
出版年度：2021
卷号：118
期号：51
DOI：10.1073/pnas.2113568118
语种：English
出版社：The National Academy of Sciences of the United States of America
摘要：Significance Each individual cell transcribes nearly 85% of the genome. However, when it comes to the analysis of cellular RNA, most studies are still only looking at the 3% that correspond to protein-coding transcripts. The role and abundance of the remaining RNAs across individual cells remain largely unknown. In the present study we describe Smart-seq-total, an RNA-sequencing method that delivers a broad picture of the total cellular RNA content. Using Smart-seq-total, we analyzed the content of hundreds of human and mouse cells and showed that the noncoding RNA content of cells significantly differs across cell types and dynamically changes throughout the vital processes of a cell, such as cell cycle and cell differentiation. The ability to interrogate total RNA content of single cells would enable better mapping of the transcriptional logic behind emerging cell types and states. However, current single-cell RNA-sequencing (RNA-seq) methods are unable to simultaneously monitor all forms of RNA transcripts at the single-cell level, and thus deliver only a partial snapshot of the cellular RNAome. Here we describe Smart-seq-total, a method capable of assaying a broad spectrum of coding and noncoding RNA from a single cell. Smart-seq-total does not require splitting the RNA content of a cell and allows the incorporation of unique molecular identifiers into short and long RNA molecules for absolute quantification. It outperforms current poly(A)-independent total RNA-seq protocols by capturing transcripts of a broad size range, thus enabling simultaneous analysis of protein-coding, long-noncoding, microRNA, and other noncoding RNA transcripts from single cells. We used Smart-seq-total to analyze the total RNAome of human primary fibroblasts, HEK293T, and MCF7 cells, as well as that of induced murine embryonic stem cells differentiated into embryoid bodies. By analyzing the coexpression patterns of both noncoding RNA and mRNA from the same cell, we were able to discover new roles of noncoding RNA throughout essential processes, such as cell cycle and lineage commitment during embryonic development. Moreover, we show that independent classes of short-noncoding RNA can be used to determine cell-type identity.
关键词：single-cell RNA-seq; noncoding RNA; cell cycle; differentiation