Sensitive high-throughput single-cell RNA-seq reveals within-clonal transcript correlations in yeast populations

Single-cell RNA sequencing has revealed extensive cellular heterogeneity within many organisms, but few methods have been developed for microbial clonal populations. The yeast genome displays unusually dense transcript spacing, with interleaved and overlapping transcription from both strands, result...

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Detalhes bibliográficos
Autores: Nadal Ribelles, Mariona, Islam, Saiful, Wei, Wu, Latorre Domenech, Pablo, Nguyen, Michelle, Nadal Clanchet, Eulàlia de, Posas, Francesc, Steinmetz, Lars M.
Formato: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2019
País:España
Recursos:Universidad de Barcelona
Repositorio:Dipòsit Digital de la UB
OAI Identifier:oai:diposit.ub.edu:2445/220606
Acesso em linha:https://hdl.handle.net/2445/220606
Access Level:acceso abierto
Palavra-chave:Levaduras
Transcripció genètica
Yeast
Genetic transcription
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spelling Sensitive high-throughput single-cell RNA-seq reveals within-clonal transcript correlations in yeast populationsNadal Ribelles, MarionaIslam, SaifulWei, WuLatorre Domenech, PabloNguyen, MichelleNadal Clanchet, Eulàlia dePosas, FrancescSteinmetz, Lars M.LevadurasTranscripció genèticaYeastGenetic transcriptionSingle-cell RNA sequencing has revealed extensive cellular heterogeneity within many organisms, but few methods have been developed for microbial clonal populations. The yeast genome displays unusually dense transcript spacing, with interleaved and overlapping transcription from both strands, resulting in a minuscule but complex pool of RNA that is protected by a resilient cell wall. Here, we have developed a sensitive, scalable and inexpensive yeast single-cell RNA-seq (yscRNA-seq) method that digitally counts transcript start sites in a strand- and isoform-specific manner. YscRNA-seq detects the expression of low-abundance, noncoding RNAs and at least half of the protein-coding genome in each cell. In clonal cells, we observed a negative correlation for the expression of sense–antisense pairs, whereas paralogs and divergent transcripts co-expressed. By combining yscRNA-seq with index sorting, we uncovered a linear relationship between cell size and RNA content. Although we detected an average of ~3.5 molecules per gene, the number of expressed isoforms is restricted at the single-cell level. Remarkably, the expression of metabolic genes is highly variable, whereas their stochastic expression primes cells for increased fitness towards the corresponding environmental challenge. These findings suggest that functional transcript diversity acts as a mechanism that provides a selective advantage to individual cells within otherwise transcriptionally heterogeneous populations.Springer Nature2019info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersionapplication/pdfhttps://hdl.handle.net/2445/220606Articles publicats en revistes (Institut de Recerca Biomèdica (IRB Barcelona))reponame:Dipòsit Digital de la UBinstname:Universidad de BarcelonaInglésVersió postprint del document publicat a: https://doi.org/10.1038/s41564-018-0346-9Nature Microbiology, 2019, vol. 4, p. 683-692https://doi.org/10.1038/s41564-018-0346-9(c) Nadal Ribelles, Mariona et al., 2019info:eu-repo/semantics/openAccessoai:diposit.ub.edu:2445/2206062026-05-27T06:46:51Z
dc.title.none.fl_str_mv Sensitive high-throughput single-cell RNA-seq reveals within-clonal transcript correlations in yeast populations
title Sensitive high-throughput single-cell RNA-seq reveals within-clonal transcript correlations in yeast populations
spellingShingle Sensitive high-throughput single-cell RNA-seq reveals within-clonal transcript correlations in yeast populations
Nadal Ribelles, Mariona
Levaduras
Transcripció genètica
Yeast
Genetic transcription
title_short Sensitive high-throughput single-cell RNA-seq reveals within-clonal transcript correlations in yeast populations
title_full Sensitive high-throughput single-cell RNA-seq reveals within-clonal transcript correlations in yeast populations
title_fullStr Sensitive high-throughput single-cell RNA-seq reveals within-clonal transcript correlations in yeast populations
title_full_unstemmed Sensitive high-throughput single-cell RNA-seq reveals within-clonal transcript correlations in yeast populations
title_sort Sensitive high-throughput single-cell RNA-seq reveals within-clonal transcript correlations in yeast populations
dc.creator.none.fl_str_mv Nadal Ribelles, Mariona
Islam, Saiful
Wei, Wu
Latorre Domenech, Pablo
Nguyen, Michelle
Nadal Clanchet, Eulàlia de
Posas, Francesc
Steinmetz, Lars M.
author Nadal Ribelles, Mariona
author_facet Nadal Ribelles, Mariona
Islam, Saiful
Wei, Wu
Latorre Domenech, Pablo
Nguyen, Michelle
Nadal Clanchet, Eulàlia de
Posas, Francesc
Steinmetz, Lars M.
author_role author
author2 Islam, Saiful
Wei, Wu
Latorre Domenech, Pablo
Nguyen, Michelle
Nadal Clanchet, Eulàlia de
Posas, Francesc
Steinmetz, Lars M.
author2_role author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Levaduras
Transcripció genètica
Yeast
Genetic transcription
topic Levaduras
Transcripció genètica
Yeast
Genetic transcription
description Single-cell RNA sequencing has revealed extensive cellular heterogeneity within many organisms, but few methods have been developed for microbial clonal populations. The yeast genome displays unusually dense transcript spacing, with interleaved and overlapping transcription from both strands, resulting in a minuscule but complex pool of RNA that is protected by a resilient cell wall. Here, we have developed a sensitive, scalable and inexpensive yeast single-cell RNA-seq (yscRNA-seq) method that digitally counts transcript start sites in a strand- and isoform-specific manner. YscRNA-seq detects the expression of low-abundance, noncoding RNAs and at least half of the protein-coding genome in each cell. In clonal cells, we observed a negative correlation for the expression of sense–antisense pairs, whereas paralogs and divergent transcripts co-expressed. By combining yscRNA-seq with index sorting, we uncovered a linear relationship between cell size and RNA content. Although we detected an average of ~3.5 molecules per gene, the number of expressed isoforms is restricted at the single-cell level. Remarkably, the expression of metabolic genes is highly variable, whereas their stochastic expression primes cells for increased fitness towards the corresponding environmental challenge. These findings suggest that functional transcript diversity acts as a mechanism that provides a selective advantage to individual cells within otherwise transcriptionally heterogeneous populations.
publishDate 2019
dc.date.none.fl_str_mv 2019
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/acceptedVersion
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/2445/220606
url https://hdl.handle.net/2445/220606
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Versió postprint del document publicat a: https://doi.org/10.1038/s41564-018-0346-9
Nature Microbiology, 2019, vol. 4, p. 683-692
https://doi.org/10.1038/s41564-018-0346-9
dc.rights.none.fl_str_mv (c) Nadal Ribelles, Mariona et al., 2019
info:eu-repo/semantics/openAccess
rights_invalid_str_mv (c) Nadal Ribelles, Mariona et al., 2019
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Springer Nature
publisher.none.fl_str_mv Springer Nature
dc.source.none.fl_str_mv Articles publicats en revistes (Institut de Recerca Biomèdica (IRB Barcelona))
reponame:Dipòsit Digital de la UB
instname:Universidad de Barcelona
instname_str Universidad de Barcelona
reponame_str Dipòsit Digital de la UB
collection Dipòsit Digital de la UB
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.812455

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