期刊
PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES
卷 369, 期 1649, 页码 -出版社
ROYAL SOC
DOI: 10.1098/rstb.2013.0252
关键词
quantitative genetics; G matrix; natural selection; evolutionary rates; constraint; evolvability
类别
资金
- NERC
- BBSRC
- University Royal Society Fellowship
- NERC studentship
- NIH [1R01GM094424]
- Biotechnology and Biological Sciences Research Council [BB/C516936/1, BB/L002604/1] Funding Source: researchfish
- Natural Environment Research Council [NE/H020608/1, NE/D012430/1, NE/C510659/1, NE/G016399/1, NE/H02249X/1] Funding Source: researchfish
- BBSRC [BB/L002604/1] Funding Source: UKRI
- NERC [NE/D012430/1, NE/G016399/1, NE/H02249X/1, NE/H020608/1] Funding Source: UKRI
A fundamental question in evolutionary biology is the relative importance of selection and genetic architecture in determining evolutionary rates. Adaptive evolution can be described by the multivariate breeders' equation (Delta(z) over bar = G beta), which predicts evolutionary change for a suite of phenotypic traits (Delta(z) over bar) as a product of directional selection acting on them (beta) and the genetic variance-covariance matrix for those traits (G). Despite being empirically challenging to estimate, there are enough published estimates of G and beta to allow for synthesis of general patterns across species. We use published estimates to test the hypotheses that there are systematic differences in the rate of evolution among trait types, and that these differences are, in part, due to genetic architecture. We find some evidence that sexually selected traits exhibit faster rates of evolution compared with life-history or morphological traits. This difference does not appear to be related to stronger selection on sexually selected traits. Using numerous proposed approaches to quantifying the shape, size and structure of G, we examine how these parameters relate to one another, and how they vary among taxonomic and trait groupings. Despite considerable variation, they do not explain the observed differences in evolutionary rates.
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