A population genetics model for multiple quantitative traits exhibiting pleiotropy and epistasis

We study a population genetics model of an organism with a genome of L-tot loci that determine the Values of T quantitative traits. Each trait is cont rolled by a subset of L loci assigned randomly from the genome. There is an optimum value for each trait, and stabilizing selection acts on the phenot ype as a whole to maintain actual trait values close to their optima. The m odel contains pleiotropic effects (loci can affect more than one trait) and epistasis in fitness. We use adaptive walk simulations to find high-fitnes s genotypes and to study the way these genotypes are distributed in sequenc e space. We then simulate the evolution of haploid and diploid populations on these fitness landscapes and show that the genotypes of populations are able to drift through sequence space despite stabilizing selection on the p henotype. We study the way the rate of drift and the extent of the accessib le region of sequence space is affected by mutation rate, selection strengt h, population size, recombination rate, and the parameters L and T that con trol the landscape shape. There are three regimes of the model. If LT much less than L-tot, there are many high fitness genotypes and the population m ay evolve neutrally on high-fitness plateaux. If LT similar to L-tot, there are a few high-fitness genotypes which tend to be close together. The popu lation is confined to a small region of sequence space if selection is stro ng, but can explore more widely if selection is weaker. If LT much greater than L-tot, there are many small peaks that can be spread over a wide regio n of sequence space. Compensatory neutral mutations are important in the po pulation dynamics in this case. (C) 2000 Academic Press.