Data-driven identification of inherent features of eukaryotic stress-responsive genes

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  • dc.contributor.author Latorre Doménech, Pablo, 1993-
  • dc.contributor.author Böttcher, René
  • dc.contributor.author Nadal Ribelles, Mariona, 1984-
  • dc.contributor.author Li, Constance H.
  • dc.contributor.author Solé, Carme
  • dc.contributor.author Martínez Cebrián, Gerard, 1992-
  • dc.contributor.author Boutros, Paul C.
  • dc.contributor.author Posas Garriga, Francesc
  • dc.contributor.author Nadal Clanchet, Eulàlia de
  • dc.date.accessioned 2022-04-25T06:36:45Z
  • dc.date.available 2022-04-25T06:36:45Z
  • dc.date.issued 2022
  • dc.description.abstract Living organisms are continuously challenged by changes in their environment that can propagate to stresses at the cellular level, such as rapid changes in osmolarity or oxygen tension. To survive these sudden changes, cells have developed stress-responsive mechanisms that tune cellular processes. The response of Saccharomyces cerevisiae to osmostress includes a massive reprogramming of gene expression. Identifying the inherent features of stress-responsive genes is of significant interest for understanding the basic principles underlying the rewiring of gene expression upon stress. Here, we generated a comprehensive catalog of osmostress-responsive genes from 5 independent RNA-seq experiments. We explored 30 features of yeast genes and found that 25 (83%) were distinct in osmostress-responsive genes. We then identified 13 non-redundant minimal osmostress gene traits and used statistical modeling to rank the most stress-predictive features. Intriguingly, the most relevant features of osmostress-responsive genes are the number of transcription factors targeting them and gene conservation. Using data on HeLa samples, we showed that the same features that define yeast osmostress-responsive genes can predict osmostress-responsive genes in humans, but with changes in the rank-ordering of feature-importance. Our study provides a holistic understanding of the basic principles of the regulation of stress-responsive gene expression across eukaryotes.
  • dc.description.sponsorship FI predoctoral fellowship and travel grant from Boehringer Ingelheim Fonds (to P.L.); Maria de Maeztu Postdoctoral Fellowship; La Caixa Junior Leader Fellow [LCF/BQ/PR20/11770001 to M.N.-R.]; Juan de la Cierva post-doctoral fellowship (to R.B.); FPI predoctoral fellowship (to G.M.-C.); National Institutes of Health [P30CA016042 to P.C.B.]; National Cancer Institute [1U01CA214194-01, 1U24CA248265-01 to P.C.B.]; Spanish Ministry of Economy and Competitiveness [BFU2017-85152-P to E.d.N., PGC2018-094136-B-I00 and FEDER to F.P.]; Catalan Government [2017 SGR 799 to E.N. and F.P.]; Unidad de Excelencia Maria de Maeztu [MDM-2014-0370 to the UPF]; F.P. and E.d.N. are recipients of an ICREA Acadèmia (Catalan Government); Spanish Ministry of Economy, Industry and Competitiveness (MINECO) through the Centres of Excellence Severo Ochoa award; CERCA Programme of the Catalan Government.
  • dc.format.mimetype application/pdf
  • dc.identifier.citation Latorre P, Böttcher R, Nadal-Ribelles M, Li CH, Solé C, Martínez-Cebrián G, Boutros PC, Posas F, de Nadal E. Data-driven identification of inherent features of eukaryotic stress-responsive genes. NAR Genom Bioinform. 2022 Mar 7;4(1):lqac018. DOI: 10.1093/nargab/lqac018
  • dc.identifier.doi http://dx.doi.org/10.1093/nargab/lqac018
  • dc.identifier.issn 2631-9268
  • dc.identifier.uri http://hdl.handle.net/10230/52876
  • dc.language.iso eng
  • dc.publisher Oxford University Press
  • dc.relation.ispartof NAR Genom Bioinform. 2022 Mar 7;4(1):lqac018
  • dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/BFU2017-85152-P
  • dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/PGC2018-094136-B-I00
  • dc.rights © The Author(s) 2022. Published by Oxford University Press on behalf of NAR Genomics and Bioinformatics. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
  • dc.rights.accessRights info:eu-repo/semantics/openAccess
  • dc.rights.uri https://creativecommons.org/licenses/by-nc/4.0/
  • dc.title Data-driven identification of inherent features of eukaryotic stress-responsive genes
  • dc.type info:eu-repo/semantics/article
  • dc.type.version info:eu-repo/semantics/publishedVersion

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