TY - JOUR
T1 - Directional selection rather than functional constraints can shape the G matrix in rapidly adapting asexuals
AU - Gomez, Kevin
AU - Bertram, Jason
AU - Masel, Joanna
N1 - Funding Information:
We thank Patrick Phillips and Bruce Walsh for helpful discussions, and Benjamin Good for the mathematics of Appendix B. Funding was provided by the National Science Foundation (DEB-1348262) and the National Institutes of Health (T32 GM084905).
Publisher Copyright:
© 2019 by the Genetics Society of America.
PY - 2019/2/1
Y1 - 2019/2/1
N2 - Genetic covariances represent a combination of pleiotropy and linkage disequilibrium, shaped by the population’s history. Observed genetic covariance is most often interpreted in pleiotropic terms. In particular, functional constraints restricting which phenotypes are physically possible can lead to a stable G matrix with high genetic variance in fitness-associated traits, and high pleiotropic negative covariance along the phenotypic curve of constraint. In contrast, population genetic models of relative fitness assume endless adaptation without constraint, through a series of selective sweeps that are well described by recent traveling wave models. We describe the implications of such population genetic models for the G matrix when pleiotropy is excluded by design, such that all covariance comes from linkage disequilibrium. The G matrix is far less stable than has previously been found, fluctuating over the timescale of selective sweeps. However, its orientation is relatively stable, corresponding to high genetic variance in fitnessassociated traits and strong negative covariance—the same pattern often interpreted in terms of pleiotropic constraints but caused instead by linkage disequilibrium. We find that different mechanisms drive the instabilities along vs. perpendicular to the fitness gradient. The origin of linkage disequilibrium is not drift, but small amounts of linkage disequilibrium are instead introduced by mutation and then amplified during competing selective sweeps. This illustrates the need to integrate a broader range of population genetic phenomena into quantitative genetics.
AB - Genetic covariances represent a combination of pleiotropy and linkage disequilibrium, shaped by the population’s history. Observed genetic covariance is most often interpreted in pleiotropic terms. In particular, functional constraints restricting which phenotypes are physically possible can lead to a stable G matrix with high genetic variance in fitness-associated traits, and high pleiotropic negative covariance along the phenotypic curve of constraint. In contrast, population genetic models of relative fitness assume endless adaptation without constraint, through a series of selective sweeps that are well described by recent traveling wave models. We describe the implications of such population genetic models for the G matrix when pleiotropy is excluded by design, such that all covariance comes from linkage disequilibrium. The G matrix is far less stable than has previously been found, fluctuating over the timescale of selective sweeps. However, its orientation is relatively stable, corresponding to high genetic variance in fitnessassociated traits and strong negative covariance—the same pattern often interpreted in terms of pleiotropic constraints but caused instead by linkage disequilibrium. We find that different mechanisms drive the instabilities along vs. perpendicular to the fitness gradient. The origin of linkage disequilibrium is not drift, but small amounts of linkage disequilibrium are instead introduced by mutation and then amplified during competing selective sweeps. This illustrates the need to integrate a broader range of population genetic phenomena into quantitative genetics.
KW - Clonal interference
KW - Life history traits
KW - Polygenic adaptation
KW - Stochastic processes
KW - Trait correlations
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U2 - 10.1534/genetics.118.301685
DO - 10.1534/genetics.118.301685
M3 - Article
C2 - 30559325
AN - SCOPUS:85061236764
SN - 0016-6731
VL - 211
SP - 715
EP - 729
JO - Genetics
JF - Genetics
IS - 2
ER -