Time-resolved single-cell RNA-seq using metabolic RNA labelling

被引:38
作者
Erhard, Florian [1 ]
Saliba, Antoine-Emmanuel [2 ]
Lusser, Alexandra [3 ]
Toussaint, Christophe [2 ]
Hennig, Thomas [1 ]
Prusty, Bhupesh K. [1 ]
Kirschenbaum, Daniel [4 ]
Abadie, Kathleen [4 ]
Miska, Eric A. [5 ,6 ,7 ]
Friedel, Caroline C. [8 ]
Amit, Ido [4 ]
Micura, Ronald [9 ,10 ]
Doelken, Lars [1 ,2 ]
机构
[1] Julius Maximilians Univ Wurzburg, Inst Virol & Immunobiol, Wurzburg, Germany
[2] Helmholtz Ctr Infect Res HZI, Helmholtz Inst RNA Based Infect Res HIRI, Wurzburg, Germany
[3] Med Univ Innsbruck, Bioctr, Inst Mol Biol, Innsbruck, Austria
[4] Weizmann Inst Sci, Dept Syst Immunol, Rehovot, Israel
[5] Univ Cambridge, Wellcome Trust Canc Res UK Gurdon Inst, Cambridge, England
[6] Univ Cambridge, Dept Biochem, Cambridge, England
[7] Univ Cambridge, Dept Genet, Cambridge, England
[8] Ludwig Maximilians Univ Munchen, Inst Informat, Munich, Germany
[9] Univ Innsbruck, Inst Organ Chem, Innsbruck, Austria
[10] Univ Innsbruck, Ctr Mol Biosci CMBI, Innsbruck, Austria
来源
NATURE REVIEWS METHODS PRIMERS | 2022年 / 2卷 / 01期
基金
英国惠康基金; 奥地利科学基金会; 欧洲研究理事会;
关键词
MESSENGER-RNA; NASCENT RNA; TRANSCRIPTS; GENOME; DYNAMICS; TRANSFORMATION; 4-THIOURIDINE; NUCLEOSIDES; TOMOGRAPHY; STABILITY;
D O I
10.1038/s43586-022-00157-z
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Single-cell RNA genomics technologies are revolutionizing biomedical science by profiling single cells with unprecedented resolution, providing fundamental insights into the role of different cellular states and intercellular heterogeneity in health and disease. The combination of single-cell RNA sequencing (scRNA-seq) with metabolic RNA labelling approaches now enables time-resolved monitoring of transcriptional responses for thousands of genes in thousands of individual cells in parallel. This facilitates and accelerates direct characterization of the temporal dimension of biological processes, which has been largely missing in current data. In this Primer, we provide an overview of the various metabolic RNA labelling approaches and their combination with currently available scRNA-seq and multi-omics platforms. We summarize the main challenges in the design of such experiments and discuss the various applications of time-resolved scRNA-seq in vitro and in vivo. We outline the computational tools and challenges to the analyses of the temporal dynamics of transcriptional responses at the single-cell level. We discuss the prospect of integrating data obtained by the respective time-resolved scRNA-seq approaches with complementary methods to elucidate gene regulatory networks that underlie molecular mechanisms. Finally, we discuss open questions and challenges in the field and give our thoughts for future development and applications.
引用
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页数:18
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