Horizon / Plein textes La base de ressources documentaires de l'IRD

IRD

 

Publications des scientifiques de l'IRD

De Mita S., Thuillet Anne-Céline, Gay L., Ahmadi N., Manel S., Ronfort J., Vigouroux Yves. (2013). Detecting selection along environmental gradients : analysis of eight methods and their effectiveness for outbreeding and selfing populations. Molecular Ecology, 22 (5), 1383-1399. ISSN 0962-1083

Accès réservé (Intranet IRD) Demander le PDF

Lien direct chez l'éditeur doi:10.1111/mec.12182

Titre
Detecting selection along environmental gradients : analysis of eight methods and their effectiveness for outbreeding and selfing populations
Année de publication2013
Type de documentArticle référencé dans le Web of Science WOS:000315414700015
AuteursDe Mita S., Thuillet Anne-Céline, Gay L., Ahmadi N., Manel S., Ronfort J., Vigouroux Yves.
SourceMolecular Ecology, 2013, 22 (5), p. 1383-1399. ISSN 0962-1083
RésuméThanks to genome-scale diversity data, present-day studies can provide a detailed view of how natural and cultivated species adapt to their environment and particularly to environmental gradients. However, due to their sensitivity, up-to-date studies might be more sensitive to undocumented demographic effects such as the pattern of migration and the reproduction regime. In this study, we provide guidelines for the use of popular or recently developed statistical methods to detect footprints of selection. We simulated 100 populations along a selective gradient and explored different migration models, sampling schemes and rates of self-fertilization. We investigated the power and robustness of eight methods to detect loci potentially under selection: three designed to detect genotypeenvironment correlations and five designed to detect adaptive differentiation (based on FST or similar measures). We show that genotypeenvironment correlation methods have substantially more power to detect selection than differentiation-based methods but that they generally suffer from high rates of false positives. This effect is exacerbated whenever allele frequencies are correlated, either between populations or within populations. Our results suggest that, when the underlying genetic structure of the data is unknown, a number of robust methods are preferable. Moreover, in the simulated scenario we used, sampling many populations led to better results than sampling many individuals per population. Finally, care should be taken when using methods to identify genotypeenvironment correlations without correcting for allele frequency autocorrelation because of the risk of spurious signals due to allele frequency correlations between populations.
Plan de classementSciences fondamentales / Techniques d'analyse et de recherche [020] ; Sciences du monde végétal [076] ; Sciences du milieu [021]
LocalisationFonds IRD [F B010060714]
Identifiant IRDfdi:010060714
Lien permanenthttp://www.documentation.ird.fr/hor/fdi:010060714

Export des données

Disponibilité des documents

Télechargment fichier PDF téléchargeable

Lien sur le Web lien chez l'éditeur

Accès réservé en accès réservé

HAL en libre accès sur HAL


Accès aux documents originaux :

Le FDI est labellisé CollEx

Accès direct

Bureau du chercheur

Site de la documentation

Espace intranet IST (accès réservé)

Suivi des publications IRD (accès réservé)

Mentions légales

Services Horizon

Poser une question

Consulter l'aide en ligne

Déposer une publication (accès réservé)

S'abonner au flux RSS

Voir les tableaux chronologiques et thématiques

Centres de documentation

Bondy

Montpellier (centre IRD)

Montpellier (MSE)

Cayenne

Nouméa

Papeete

Abidjan

Dakar

Niamey

Ouagadougou

Tunis

La Paz

Quito