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Population divergence of genetic (co)variance matrices in a subdivided plant species, Brassica cretica
Author(s) -
Widén B.,
Andersson S.,
Rao GY.,
Widén M.
Publication year - 2002
Publication title -
journal of evolutionary biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.289
H-Index - 128
eISSN - 1420-9101
pISSN - 1010-061X
DOI - 10.1046/j.1420-9101.2002.00465.x
Subject(s) - biology , principal component analysis , divergence (linguistics) , population , genetic variation , evolutionary biology , genetic divergence , statistics , genetic drift , analysis of molecular variance , genetics , genetic diversity , genetic structure , mathematics , demography , gene , philosophy , linguistics , sociology
The present study of Brassica cretica had two objectives. First, we compared estimates of population structure ( Q st ) for seven phenotypic characters with the corresponding measures for allozyme markers ( F st ) to evaluate the supposition that genetic drift is a major determinant of the evolutionary history of this species. Secondly, we compared the genetic (co)variance ( G ) matrices of five populations to examine whether a long history of population isolation is associated with large, consistent differences in the genetic (co)variance structure. Differences between estimates of F st and Q st were too small to be declared significant, indicating that stochastic processes have played a major role in the structuring of quantitative variation in this species. Comparison of populations using the common principal component (CPC) method rejected the hypothesis that the G matrices differed by a simple constant of proportionality: most of the variation involved principal component structure rather than the eigenvalues. However, there was strong evidence for proportionality in comparisons using the method of percentage reduction in mean‐square error (MSE), at least when characters with unusually high (co)variance estimates were included in the analyses. Although the CPC and MSE methods provide different, but complementary, views of G matrix variation, we urge caution in the use of proportionality as an indicator of whether genetic drift is responsible for divergence in the G matrix.