Quantitative genetic methods depending on the nature of the phenotypic trait

Pierre de Villemereuil (1)

1 University of Auckland [Auckland]

A consequence of the assumptions of the infinitesimal model, one of the most important theoretical foundations of quantitative genetics, is that phenotypic traits are predicted to be most often normally distributed (so-called Gaussian traits). But phenotypic traits, especially those interesting for evolutionary biology, might be shaped according to very diverse distributions. In this review, I show how quantitative genetics tools have been extended to account for a wider diversity of phenotypic traits using first the threshold model, then more recently using generalised linear mixed models. I explore the assumptions behind these models and how they can be used to study the genetics of non Gaussian complex traits. I also comment on three recent methodological advances in quantitative genetics that widen our ability to study new kinds of traits: the use of "modular" hierarchical modelling to e.g. study survival in the context of capture-recapture approaches for wild populations; the use of aster models to study a set of traits with conditional relationships (e.g. life-history traits); and finally, the study of high-dimensional traits such as gene expression.

Mots clés: quantitative genetics; non Gaussian traits; heritability; threshold model; generalised linear mixed models Quantitative genetics for non classical traits

Domaines: Evolution [q-bio.PE]

Pierre de Villemereuil. Quantitative genetic methods depending on the nature of the phenotypic trait. Annals of the New York Academy of Sciences, 2018, 1422 (1), pp.29-47. ⟨10.1111/nyas.13571⟩. ⟨hal-03043413⟩