• DOI:10.1002/9780470319390.CH12
• Corpus ID: 16990514

Evolution of covariance in the mammalian skull.

@article{Hallgrmsson2007EvolutionOC,
  title={Evolution of covariance in the mammalian skull.},
  author={Benedikt Hallgr{\'i}msson and Daniel E. Lieberman and Nathan M Young and Trish E. Parsons and Stephen Wat},
  journal={Novartis Foundation symposium},
  year={2007},
  volume={284},
  pages={
          164-85; discussion 185-90
        }
}

• B. Hallgrímsson, D. Lieberman, +2 authors Stephen Wat
• Published 11 June 2007
• Biology
• Novartis Foundation symposium

The skull is a developmentally complex and highly integrated structure. Integration, which is manifested as covariance among structures, enables the skull and associated soft tissues to maintain function both across ontogeny within individuals and across the ranges of size and shape variation among individuals. Integration also contributes to evolvability by structuring the phenotypic expression of genetic variation. We argue that the pattern of covariation seen in complex phenotypes such as the skull results from the overlaying of variation introduced by developmental and environmental factors at different stages of development. Much like a palimpsest, the covariation structure of an adult skull represents the summed imprint of a succession of effects, each of which leaves a distinctive covariation signal determined by the specific set of developmental interactions involved. Covariance evolves either by altering the variance of one of these sequential effects or through the introduction of a novel covariance producing effect. Either way is consistent with the notion that evolutionary change occurs through tinkering. We illustrate these principles through analyses of how genetic perturbations acting at different developmental stages (embryonic, fetal, and postnatal) influence the covariance structure of adult mouse skulls. As predicted by the model, the results illustrate the intimate relationship between the modulation of variance and the expression of covariance. The results also demonstrate that covariance patterns have a complex relationship to the underlying developmental architecture, thus highlighting problems with making inferences about developmental relationships (e.g. modularity) based on covariation.