Fiche du document
12 juin 2023
- ISIDORE Id: 10670/1.b98683...
- hal: hal-04243951
- doi: 10.1093/molbev/msad140
- IRD: fdi:010088270
- PUBMED: 37307566
- WOS: 001021595400003
Ce document est lié à :
info:eu-repo/semantics/altIdentifier/doi/10.1093/molbev/msad140
Ce document est lié à :
info:eu-repo/semantics/altIdentifier/pmid/37307566
http://creativecommons.org/licenses/by/ , info:eu-repo/semantics/OpenAccess
Mots-clés
predictive ecological genomics genomic offset climate change local adaptation pearl millet -bio]/Quantitative Methods [q-bio.QM] -bio]/Ecology, environment/Bioclimatology -bio]/Genetics/Plants geneticsSujets proches
Statistical data Cases, clinical reports, statistics Statistical data Statistical analysis Statistical methods Statistical scienceCiter ce document
Clément Gain et al., « A Quantitative Theory for Genomic Offset Statistics », HAL SHS (Sciences de l’Homme et de la Société), ID : 10.1093/molbev/msad140
Métriques
Partage / Export
Résumé
Genomic offset statistics predict the maladaptation of populations to rapid habitat alteration based on association of genotypes with environmental variation. Despite substantial evidence for empirical validity, genomic offset statistics have well-identified limitations, and lack a theory that would facilitate interpretations of predicted values. Here, we clarified the theoretical relationships between genomic offset statistics and unobserved fitness traits controlled by environmentally selected loci and proposed a geometric measure to predict fitness after rapid change in local environment. The predictions of our theory were verified in computer simulations and in empirical data on African pearl millet (Cenchrus americanus) obtained from a common garden experiment. Our results proposed a unified perspective on genomic offset statistics and provided a theoretical foundation necessary when considering their potential application in conservation management in the face of environmental change.
