Genetic Variance–covariance Matrices: A Critique of the Evolutionary Quantitative Genetics Research Program

Abstract

This paper outlines a critique of the use of the genetic variance-covariance matrix (G), one of the central concepts in the modern study of natural selection and evolution. Specifically, I argue that for both conceptual and empirical reasons, studies of G cannot be used to elucidate so-called constraints on natural selection, nor can they be employed to detect or to measure past selection in natural populations -contrary to what assumed by most practicing biologists. I suggest that the search for a general solution to the difficult problem of identifying causal structures given observed correlation's has led evolutionary quantitative geneticists to substitute statistical modeling for the more difficult, but much more valuable, job of teasing apart the many possible causes underlying the action of natural selection. Hence, the entire evolutionary quantitative genetics research program may be in need of a fundamental reconsideration of its goals and how they correspond to the array of mathematical and experimental techniques normally employed by its practitioners.

Effects of Selection and Drift on G Matrix Evolution in a Heterogeneous Environment: A MultivariateQst–Fst Test With the Freshwater SnailGalba truncatula

“…This could be expected, if fitness traits are the first to respond to habitat heterogeneity. In any case, this illustrates that the nature of the traits chosen to form G matrices is important, so that comparisons between trait types may be useful as pointed out by Pigliucci (2006).…”

Adaptive dynamics for physiologically structured population models

“…There is little or no understanding of which choices of M (or, equivalently, of the mutational distribution M) are the reasonable ones for each type of biological model, as the covariances are footprints of deeper devel-43 opmental, physiological and biophysical processes (cf. Pigliucci 2006). The safest conclusion to draw is that any complicated dynamical features found from the canonical equation should be dismissed as biologically irrelevant, unless they are robust against changes in M. When there is no further information about it, most people in practice choose M = id, the identity matrix.…”

MultivariateQst–Fst Comparisons: A Neutrality Test for the Evolution of the G Matrix in Structured Populations

“…More generally the problem that observable patterns in G can be due to both selective and neutral processes has led to criticisms of the whole research program that seeks to use G matrix estimates to get insights into the constraints imposed by evolutionary forces on phenotypic evolution (Pigliucci 2006). Given the already large designs required for evolutionary quantitative genetic studies, it seems that they are more likely to be improved through more appropriate statistical approaches than by increased empirical efforts.…”