Systematic mapping of organism-scale gene-regulatory networks in aging using population asynchrony

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• dc.contributor.author Eder, Matthias
• dc.contributor.author Martin, Olivier M. F.
• dc.contributor.author Oswal, Natasha
• dc.contributor.author Sedlackova, Lucia
• dc.contributor.author Moutinho, Catia
• dc.contributor.author Carmen Fabregat, Andrea del
• dc.contributor.author Menéndez Bravo, Simón
• dc.contributor.author Sebé-Pedrós, Arnau
• dc.contributor.author Heyn, Holger
• dc.contributor.author Stroustrup, Nicholas
• dc.date.accessioned 2024-09-04T12:34:26Z
• dc.date.embargoEnd info:eu-repo/date/embargoEnd/2025-06-21
• dc.date.issued 2024
• dc.description.abstract In aging, physiologic networks decline in function at rates that differ between individuals, producing a wide distribution of lifespan. Though 70% of human lifespan variance remains unexplained by heritable factors, little is known about the intrinsic sources of physiologic heterogeneity in aging. To understand how complex physiologic networks generate lifespan variation, new methods are needed. Here, we present Asynch-seq, an approach that uses gene-expression heterogeneity within isogenic populations to study the processes generating lifespan variation. By collecting thousands of single-individual transcriptomes, we capture the Caenorhabditis elegans "pan-transcriptome"-a highly resolved atlas of non-genetic variation. We use our atlas to guide a large-scale perturbation screen that identifies the decoupling of total mRNA content between germline and soma as the largest source of physiologic heterogeneity in aging, driven by pleiotropic genes whose knockdown dramatically reduces lifespan variance. Our work demonstrates how systematic mapping of physiologic heterogeneity can be applied to reduce inter-individual disparities in aging.
• dc.description.sponsorship We thank Javier Apfeld, Ben Lehner, Elvan Böke, Jonathan Frazer, Chris Sander, and James Sharpe for critical reading of our manuscript and all members of the Dynamics of Living Systems group for discussions and encouragement throughout the project. We thank Joy Alcedo (Wayne State University) for nematode strains. Some strains were provided by the CGC, which is funded by NIH Office of Research Infrastructure Programs (P40 OD010440). We acknowledge support of the Spanish Ministry of Science and Innovation through the Centro de Excelencia Severo Ochoa (CEX2020-001049-S, MCIN/AEI /10.13039/501100011033), the Generalitat de Catalunya through the CERCA programme, and to the EMBL partnership. We are grateful to the CRG Core Technologies Programme for their support and assistance in this work, including the CRG Advanced Light Microscopy Unit. This work was technically supported by the EMBL Genomics Core facility. We acknowledge support from the MEIC Excelencia awards BFU2017-88615-P, PID2020-115189GB-I00, and PID2020-115439GB-I00, support from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 852201), and support as part of a project (BCLLATLAS) that has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 Research and Innovation Programme (grant agreement no. 810287 and 874710), and support from an award from the Glenn Foundation for Medical Research. Research for this publication has been partially carried out in the Barcelona Collaboratorium for Modelling and Predictive Biology. Research in A.S.-P. group was supported by the European Research Council (ERC-StG 851647), the Spanish Ministry of Science and Innovation (PID2021-124757NB-I00), and AGAUR (2021-SGR2021-01219).
• dc.embargo.liftdate 2025-06-21
• dc.format.mimetype application/pdf
• dc.identifier.citation Eder M, Martin OMF, Oswal N, Sedlackova L, Moutinho C, Carmen-Fabregat A, et al. Systematic mapping of organism-scale gene-regulatory networks in aging using population asynchrony. Cell. 2024 Jul 25;187(15):3919-35.e19. DOI: 10.1016/j.cell.2024.05.050
• dc.identifier.doi http://dx.doi.org/10.1016/j.cell.2024.05.050
• dc.identifier.issn 0092-8674
• dc.identifier.uri http://hdl.handle.net/10230/61015
• dc.language.iso eng
• dc.publisher Elsevier
• dc.relation.ispartof Cell. 2024 Jul 25;187(15):3919-35.e19
• dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/852201
• dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/BFU2017-88615-P
• dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/PID2020-115189GB-I00
• dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/PID2020-115439GB-I00
• dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/810287
• dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/874710
• dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/851647
• dc.relation.projectID info:eu-repo/grantAgreement/ES/3PE/PID2021-124757NB-I00
• dc.rights © Elsevier http://dx.doi.org/10.1016/j.cell.2024.05.050
• dc.rights.accessRights info:eu-repo/semantics/embargoedAccess
• dc.subject.keyword Caenorhabditis elegans
• dc.subject.keyword Aging
• dc.subject.keyword Complex systems
• dc.subject.keyword Computational biology
• dc.subject.keyword Gene regulation
• dc.subject.keyword Individual variation
• dc.subject.keyword Non-genetic individuality
• dc.subject.keyword Quantitative biology
• dc.subject.keyword Statistical modeling
• dc.title Systematic mapping of organism-scale gene-regulatory networks in aging using population asynchrony
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/acceptedVersion