Uncovering the genetic basis of adaptive change: on the intersection of landscape genomics and theoretical population genetics

Détails

ID Serval
serval:BIB_E248D4216287
Type
Article: article d'un périodique ou d'un magazine.
Sous-type
Editorial
Collection
Publications
Titre
Uncovering the genetic basis of adaptive change: on the intersection of landscape genomics and theoretical population genetics
Périodique
Molecular Ecology
Auteur(s)
Joost S., Vuilleumier S., Jensen J.D., Schoville S., Leempoel K., Stucki S., Widmer I., Melodelima C., Rolland J., Manel S.
ISSN
0962-1083
Statut éditorial
Publié
Date de publication
2013
Volume
22
Numéro
14
Pages
3659-3665
Langue
anglais
Résumé
A workshop recently held at the Ecole Polytechnique Federale de Lausanne (EPFL, Switzerland) was dedicated to understanding the genetic basis of adaptive change, taking stock of the different approaches developed in theoretical population genetics and landscape genomics and bringing together knowledge accumulated in both research fields. Indeed, an important challenge in theoretical population genetics is to incorporate effects of demographic history and population structure. But important design problems (e.g. focus on populations as units, focus on hard selective sweeps, no hypothesis-based framework in the design of the statistical tests) reduce their capability of detecting adaptive genetic variation. In parallel, landscape genomics offers a solution to several of these problems and provides a number of advantages (e.g. fast computation, landscape heterogeneity integration). But the approach makes several implicit assumptions that should be carefully considered (e.g. selection has had enough time to create a functional relationship between the allele distribution and the environmental variable, or this functional relationship is assumed to be constant). To address the respective strengths and weaknesses mentioned above, the workshop brought together a panel of experts from both disciplines to present their work and discuss the relevance of combining these approaches, possibly resulting in a joint software solution in the future.
Mots-clé
Adaptation, Genome scans, Landscape genomics, Selection, Theoretical population genetics
Web of science
Open Access
Oui
Création de la notice
16/04/2013 9:08
Dernière modification de la notice
09/05/2019 2:29
Données d'usage