Naturally segregating genetic variants contribute to thermal tolerance in a Drosophila melanogaster model system.

Complex Traits DSPR Gene Expression QTL RNA-seq RNAi Thermal Tolerance

Journal

Genetics
ISSN: 1943-2631
Titre abrégé: Genetics
Pays: United States
ID NLM: 0374636

Informations de publication

Date de publication:
20 Mar 2024
Historique:
received: 11 07 2023
revised: 11 07 2023
accepted: 26 02 2024
medline: 20 3 2024
pubmed: 20 3 2024
entrez: 20 3 2024
Statut: aheadofprint

Résumé

Thermal tolerance is a fundamental physiological complex trait for survival in many species. For example, everyday tasks such as foraging, finding a mate, and avoiding predation, are highly dependent on how well an organism can tolerate extreme temperatures. Understanding the general architecture of the natural variants within the genes that control this trait is of high importance if we want to better comprehend thermal physiology. Here, we take a multipronged approach to further dissect the genetic architecture that controls thermal tolerance in natural populations using the Drosophila Synthetic Population Resource (DSPR) as a model system. First, we used quantitative genetics and Quantitative Trait Loci (QTL) mapping to identify major effect regions within the genome that influences thermal tolerance, then integrated RNA-sequencing to identify differences in gene expression, and lastly, we used the RNAi system to 1) alter tissue-specific gene expression and 2) functionally validate our findings. This powerful integration of approaches not only allows for the identification of the genetic basis of thermal tolerance but also the physiology of thermal tolerance in a natural population, which ultimately elucidates thermal tolerance through a fitness-associated lens.

Identifiants

pubmed: 38506092
pii: 7632166
doi: 10.1093/genetics/iyae040
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© The Author(s) 2024. Published by Oxford University Press on behalf of The Genetics Society of America. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.

Auteurs

Patricka A Williams-Simon (PA)

Postdoctoral Research Associate, University of Pennsylvania, 433 S University Ave., 226 Leidy Laboratories, Philadelphia, PA 19104, USA.

Camille Oster (C)

Habitat Restoration Specialist, Ash Creek Forest Management, 2796 SE 73rd Ave., Hillsboro, OR 97123, USA.

Jordyn A Moaton (JA)

Research Assistant, University of Missouri, 2035 W Wellington Ave., Chicago, IL 60618, USA.

Ronel Ghidey (R)

Biostatistician, ECHO Data Analysis Center, Johns Hopkins Bloomberg School of Public Health, 504 Cathedral St., Baltimore, MD 2120, USA.

Enoch Ng'oma (E)

Assistant Professor of Biological Sciences, University of Missouri, Division of Biology, 226 Tucker Hall, Columbia, MO 65211, USA.

Kevin M Middleton (KM)

Associate Professor of Biological Sciences, University of Missouri, 222 Tucker Hall, Columbia, MO 65211, USA.

Elizabeth G King (EG)

Associate Professor of Biological Sciences, University of Missouri, 401 Tucker Hall, Columbia, MO 65211, USA.

Classifications MeSH