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RNA timestamps identify the age of single molecules in RNA sequencing
Current approaches to single-cell RNA sequencing (RNA-seq) provide only limited information about the dynamics of gene expression. Here we present RNA timestamps, a method for inferring the age of individual RNAs in RNA-seq data by exploiting RNA editing. To introduce timestamps, we tag RNA with a r...
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Published in: | Nature biotechnology 2021-03, Vol.39 (3), p.320-325 |
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description | Current approaches to single-cell RNA sequencing (RNA-seq) provide only limited information about the dynamics of gene expression. Here we present RNA timestamps, a method for inferring the age of individual RNAs in RNA-seq data by exploiting RNA editing. To introduce timestamps, we tag RNA with a reporter motif consisting of multiple MS2 binding sites that recruit the adenosine deaminase ADAR2 fused to an MS2 capsid protein. ADAR2 binding to tagged RNA causes A-to-I edits to accumulate over time, allowing the age of the RNA to be inferred with hour-scale accuracy. By combining observations of multiple timestamped RNAs driven by the same promoter, we can determine when the promoter was active. We demonstrate that the system can infer the presence and timing of multiple past transcriptional events. Finally, we apply the method to cluster single cells according to the timing of past transcriptional activity. RNA timestamps will allow the incorporation of temporal information into RNA-seq workflows.
The age of individual RNA molecules at 1-h resolution is inferred by measuring A-to-I editing. |
doi_str_mv | 10.1038/s41587-020-0704-z |
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The age of individual RNA molecules at 1-h resolution is inferred by measuring A-to-I editing.</description><identifier>ISSN: 1087-0156</identifier><identifier>ISSN: 1546-1696</identifier><identifier>EISSN: 1546-1696</identifier><identifier>DOI: 10.1038/s41587-020-0704-z</identifier><identifier>PMID: 33077959</identifier><language>eng</language><publisher>New York: Nature Publishing Group US</publisher><subject>3T3 Cells ; 631/1647/2017 ; 631/553/552 ; 631/61/212 ; Adenosine ; Adenosine deaminase ; Adenosine Deaminase - metabolism ; Age ; Agriculture ; Algorithms ; Analysis ; Animals ; Binding sites ; Bioinformatics ; Biomedical and Life Sciences ; Biomedical Engineering/Biotechnology ; Biomedicine ; Biotechnology ; Capsid protein ; Catalytic Domain ; Editing ; Gene expression ; Gene sequencing ; Genes ; Genetic transcription ; HEK293 Cells ; Humans ; Letter ; Life Sciences ; Methods ; Mice ; Protein binding ; Ribonucleic acid ; RNA ; RNA - genetics ; RNA Editing ; RNA sequencing ; RNA-Binding Proteins - metabolism ; Scientific equipment and supplies industry ; Sequence Analysis, RNA - methods ; Single Molecule Imaging - methods ; Tetracycline ; Tetracyclines ; Time Factors ; Timestamps ; Transcription ; Viral proteins</subject><ispartof>Nature biotechnology, 2021-03, Vol.39 (3), p.320-325</ispartof><rights>The Author(s), under exclusive licence to Springer Nature America, Inc. 2020</rights><rights>COPYRIGHT 2021 Nature Publishing Group</rights><rights>The Author(s), under exclusive licence to Springer Nature America, Inc. 2020.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c673t-5dc74bb6dfee21b527ea59d9f4d9e5dda0dad8966b8ca31632d85eb3854ef3b13</citedby><cites>FETCH-LOGICAL-c673t-5dc74bb6dfee21b527ea59d9f4d9e5dda0dad8966b8ca31632d85eb3854ef3b13</cites><orcidid>0000-0001-6345-1907 ; 0000-0002-0419-3351 ; 0000-0002-2509-0861 ; 0000-0003-2308-3649 ; 0000-0003-0424-3483</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,780,784,885,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33077959$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Rodriques, Samuel G.</creatorcontrib><creatorcontrib>Chen, Linlin M.</creatorcontrib><creatorcontrib>Liu, Sophia</creatorcontrib><creatorcontrib>Zhong, Ellen D.</creatorcontrib><creatorcontrib>Scherrer, Joseph R.</creatorcontrib><creatorcontrib>Boyden, Edward S.</creatorcontrib><creatorcontrib>Chen, Fei</creatorcontrib><title>RNA timestamps identify the age of single molecules in RNA sequencing</title><title>Nature biotechnology</title><addtitle>Nat Biotechnol</addtitle><addtitle>Nat Biotechnol</addtitle><description>Current approaches to single-cell RNA sequencing (RNA-seq) provide only limited information about the dynamics of gene expression. Here we present RNA timestamps, a method for inferring the age of individual RNAs in RNA-seq data by exploiting RNA editing. To introduce timestamps, we tag RNA with a reporter motif consisting of multiple MS2 binding sites that recruit the adenosine deaminase ADAR2 fused to an MS2 capsid protein. ADAR2 binding to tagged RNA causes A-to-I edits to accumulate over time, allowing the age of the RNA to be inferred with hour-scale accuracy. By combining observations of multiple timestamped RNAs driven by the same promoter, we can determine when the promoter was active. We demonstrate that the system can infer the presence and timing of multiple past transcriptional events. Finally, we apply the method to cluster single cells according to the timing of past transcriptional activity. RNA timestamps will allow the incorporation of temporal information into RNA-seq workflows.
The age of individual RNA molecules at 1-h resolution is inferred by measuring A-to-I editing.</description><subject>3T3 Cells</subject><subject>631/1647/2017</subject><subject>631/553/552</subject><subject>631/61/212</subject><subject>Adenosine</subject><subject>Adenosine deaminase</subject><subject>Adenosine Deaminase - metabolism</subject><subject>Age</subject><subject>Agriculture</subject><subject>Algorithms</subject><subject>Analysis</subject><subject>Animals</subject><subject>Binding sites</subject><subject>Bioinformatics</subject><subject>Biomedical and Life Sciences</subject><subject>Biomedical Engineering/Biotechnology</subject><subject>Biomedicine</subject><subject>Biotechnology</subject><subject>Capsid protein</subject><subject>Catalytic Domain</subject><subject>Editing</subject><subject>Gene expression</subject><subject>Gene sequencing</subject><subject>Genes</subject><subject>Genetic transcription</subject><subject>HEK293 Cells</subject><subject>Humans</subject><subject>Letter</subject><subject>Life Sciences</subject><subject>Methods</subject><subject>Mice</subject><subject>Protein binding</subject><subject>Ribonucleic acid</subject><subject>RNA</subject><subject>RNA - 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Here we present RNA timestamps, a method for inferring the age of individual RNAs in RNA-seq data by exploiting RNA editing. To introduce timestamps, we tag RNA with a reporter motif consisting of multiple MS2 binding sites that recruit the adenosine deaminase ADAR2 fused to an MS2 capsid protein. ADAR2 binding to tagged RNA causes A-to-I edits to accumulate over time, allowing the age of the RNA to be inferred with hour-scale accuracy. By combining observations of multiple timestamped RNAs driven by the same promoter, we can determine when the promoter was active. We demonstrate that the system can infer the presence and timing of multiple past transcriptional events. Finally, we apply the method to cluster single cells according to the timing of past transcriptional activity. RNA timestamps will allow the incorporation of temporal information into RNA-seq workflows.
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subjects | 3T3 Cells 631/1647/2017 631/553/552 631/61/212 Adenosine Adenosine deaminase Adenosine Deaminase - metabolism Age Agriculture Algorithms Analysis Animals Binding sites Bioinformatics Biomedical and Life Sciences Biomedical Engineering/Biotechnology Biomedicine Biotechnology Capsid protein Catalytic Domain Editing Gene expression Gene sequencing Genes Genetic transcription HEK293 Cells Humans Letter Life Sciences Methods Mice Protein binding Ribonucleic acid RNA RNA - genetics RNA Editing RNA sequencing RNA-Binding Proteins - metabolism Scientific equipment and supplies industry Sequence Analysis, RNA - methods Single Molecule Imaging - methods Tetracycline Tetracyclines Time Factors Timestamps Transcription Viral proteins |
title | RNA timestamps identify the age of single molecules in RNA sequencing |
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