The Developmental Basis of Variational Modularity: Insights from Quantitative Genetics, Morphometrics, and Developmental Biology

Abstract

Groups of correlated characters (variational modules) often are considered to be the result of dissociated local developmental factors, i.e., of a modular genotype-phenotype map. But certain sets of pleiotropic factors can equally well induce modular phenotypic variation-no local developmental factors are necessary for a modular covariance structure. It is thus not possible to infer genetic or developmental modularity from standing variation alone. Yet, only for approximately linear genotype-phenotype maps is the induced covariance structure stable over changes of the phenotypic mean. For larger genetic and phenotypic variation, such as on a macroevolutionary level, developmental effects often are nonlinear and variational modularity remains stable only when it is realized by local dissociated developmental factors with no overlap of pleiotropic ranges. The evo-devo concept of modularity concurs only at this macroevolutionary level with the quantitative notion of variational modularity. Empirical evidence on the genetic and developmental architecture underlying phenotypic variation is inconclusive and partly subject to methodological problems. Many studies seem to indicate modularized phenotypic variation and local clusters of QTL effects, whereas other studies find support for several alternative models of modularity and report continuous distributions of QTL effects. This inconsistency partly results from the neglect of spatial relationships among the measured traits. Given the complex development of higher organisms, a combination of pleiotropic factors and more local developmental effects with a hierarchical, overlapping, and more or less continuous distribution appears most likely.

How to Explore Morphological Integration in Human Evolution and Development?

“…1a, b). More often, covariances of opposite sign may not cancel out exactly but lead to a reduced total covariance, even though many developmental or genetic factors may link the traits (Clausen and Hiesey 1960;Houle 1991;Cheverud 1984;Gromko 1995;Pigliucci 2006;Mitteroecker and Bookstein 2007;Mitteroecker 2009;Pavlicev and Hansen 2011).…”

Genotype-Phenotype Maps Maximizing Evolvability: Modularity Revisited

“…Second, if the traits affected by a gene are developmentally or functionally related, a mutation may preserve functionality of this integrated module during evolutionary change (integration). Based on the premise that selection can mould the genotype-phenotype map to increase evolvability, this idea prompted studies to assess the modularity of genetic effects and patterns of variation (reviewed in Wagner et al 2007;Mitteroecker 2009). It is still controversial, however, whether genotype-phenotype maps can be regarded as adaptations for evolvability (see, e.g., Hansen 2006;Jones et al 2007;Lynch 2007a, b, c;Draghi and Wagner 2008;Pavlicev et al 2008Pavlicev et al , 2011aHansen 2011, for a variety of opinions).…”

“…Thus, while nonzero genetic correlation is usually a sign of pleiotropy, the lack of genetic correlation does not require a lack of pleiotropy. Multiple ways to generate similar correlation structures have been discussed before (e.g., Cheverud 1984;Wagner 1989;Charlesworth 1990;Houle 1991;Gromko 1995;Hallgrimsson et al 2009;Mitteroecker 2009;Roseman et al 2009). In this paper, we use Wagner's (1989) B-matrix model in a two-trait system to systematically describe which patterns of pleiotropy maximize conditional evolvability in the sense of Hansen and Houle (2008).…”

Invariance and Meaningfulness in Phenotype spaces

“…Consider also two measured distances sharing the same starting point, or the angles and distances of a triangle. Similarly, two spatially closely adjacent measurements of an organisms cannot be considered as independent (Mitteroecker and Bookstein 2007;Mitteroecker 2009). In some cases, like for landmark coordinates, variables may also lack a meaningful origin.…”