Evol Ecol Res 14: 881-895 (2012)     Full PDF if your library subscribes.

Implementation of mixture analysis on quantitative traits in studies of neutral versus selective divergence

Cino Pertoldi1,2,3, Hanne Birgitte Hede Jørgensen4, Ettore Randi2,5, Lasse Fast Jensen6, Anders Kjærsgaard1, Volker Loeschcke1 and Søren Faurby1,7

1Department of Bioscience, Aarhus University, Aarhus, Denmark, 2Department 18/Section of Environmental Engineering, Aalborg University, Aalborg, Denmark, 3Aalborg Zoo, Aalborg, Denmark,  4Department of Molecular Biology and Genetics, Aarhus University, Tjele, Denmark,  5Laboratorio di Genetica, Istituto Superiore per la Protezione e la Ricerca Ambientale, Ozzano Emilia (BO), Italy,  6Fisheries and Maritime Museum, Esbjerg, Denmark and  7Department of Ecology and Evolutionary Biology, University of California, Los Angeles, USA

Correspondence: C. Pertoldi, Department of Bioscience, Aarhus University, Ny Munkegade 114, 8200 Aarhus, Denmark. E-mail: biocp@nf.au.dk


Background: The spatial genetic structuring of natural populations is mostly studied using neutral markers. Recently, morphometric methods have also been used to to study genetic divergence through adaptive processes. These methods provide better insights into the conservation needs of focal populations. However, all morphometric methods assume that samples obtained in different localities represent distinct populations when, in fact, they may constitute a mixture of several populations due to cryptic population structure and/or environmental variability. This may lead to biased estimates of the adaptive divergence between populations. Mixture analysis makes no a priori assumption of the affiliation of samples. It can therefore be used to assign samples and detect population structure, allowing estimation of morphometric divergence.

Methods: We perform mixture analyses on simulated data to estimate potential bias in adaptive population divergence measures due to a priori assumptions about the population structure. We present three examples illustrating the possible uses of mixture analyses for identification of distinct compartments (groups of individuals that are morphologically similar) between and within populations.

Key assumptions: We assume that the presence of distinct compartments between populations can be attributed to different environmental conditions, the presence of barriers reducing gene flow, and phylogenetic signals and plasticity of the traits analysed.

Conclusions: Certain cases of (cryptic) population structure may lead to substantial bias in the estimation of population morphometric divergence. This can have major implications for conservation guidelines and for the detection of evolutionarily distinct populations.

Keywords: evolutionarily significant unit, FST-QST and FST-PST comparisons, genetic structure, local adaptation, morphometrics, natural selection.

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