Sampling schemes and drift can bias admixture proportions inferred by structure - INRAE - Institut national de recherche pour l’agriculture, l’alimentation et l’environnement Accéder directement au contenu
Article Dans Une Revue Molecular Ecology Resources Année : 2020

Sampling schemes and drift can bias admixture proportions inferred by structure

Résumé

The interbreeding of individuals coming from genetically differentiated but incompletely isolated populations can lead to the formation of admixed populations, having important implications in ecology and evolution. In this simulation study, we evaluate how individual admixture proportions estimated by the software structure are quantitatively affected by different factors. Using various scenarios of admixture between two diverging populations, we found that unbalanced sampling from parental populations may seriously bias the inferred admixture proportions; moreover, proportionally large samples from the admixed population can also decrease the accuracy and precision of the inferences. As expected, weak differentiation between parental populations and drift after the admixture event strongly increase the biases caused by uneven sampling. We also show that admixture proportions are generally more biased when parental populations unequally contributed to the admixed population. Finally, with few exceptions, using a large number of markers reduces those biases, but using alternative priors for individual ancestry or the uncorrelated allele model only marginally affect the inference of admixture in most situations. We conclude that unbalanced sampling may cause important biases in the admixture proportions estimated by structure, especially when a small number of markers are used, and those biases can be worsened by the effect of drift and unequal genetic contribution of parental populations. Empirical studies should thus be careful with their sampling design and consider historical characteristics when using this software to estimate the ancestry of individuals from admixed populations.
Fichier principal
Vignette du fichier
2020_toyama_molecular_ecology_resources.pdf (3.86 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-02924101 , version 1 (31-08-2020)

Licence

Paternité - Pas d'utilisation commerciale

Identifiants

Citer

Ken S. Toyama, Pierre-André Crochet, Raphaël Leblois. Sampling schemes and drift can bias admixture proportions inferred by structure. Molecular Ecology Resources, In press, ⟨10.1111/1755-0998.13234⟩. ⟨hal-02924101⟩
43 Consultations
165 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More