The adaptation of complex organisms to changing environments has been a central question in evolutionary quantitative genetics since its inception. The structure of the genotype-phenotype maps is critical because pleiotropic effects can generate widespread correlated responses to selection and potentially restrict the extent of evolutionary change. In this study, we use experimental evolution to dissect the genetic architecture of natural variation for acute heat stress and oxidative stress response in the nematode Caenorhabiditis remanei. Previous work in the classic model nematode Caenorhabiditis elegans has found that abiotic stress response is controlled by a handful of genes of major effect and that mutations in any one of these genes can have widespread pleiotropic effects on multiple stress response traits. Here, we find that acute heat stress response and acute oxidative response in C. remanei are polygenic, complex traits, with hundreds of genomic regions responding to selection. In contrast to expectation from mutation studies, we find that evolved acute heat stress and acute oxidative stress response for the most part display independent genetic bases. This lack of correlation is reflected at the levels of phenotype, gene expression, and in the genomic response to selection. Thus, while these findings support the general view that rapid adaptation can be generated by changes at hundreds to thousands of sites in the genome, the architecture of segregating variation is likely to be determined by the pleiotropic structure of the underlying genetic networks.
Bibliographical noteFunding Information:
This work was supported grants from the National Science Foundation (DEB-1210922 to W.A.C. and K.L.S.; DEB-1607194 to P.C.P. and C.H.O.), grants from the National Institutes of Health (GM096008, GM102511, and GM131838 to P.C.P.; RR032670 to W.A.C.), and pre-doctoral fellowships to C.H.O. from the National Science Foundation and National Institutes of Health (T32 GM007413).
© The Author(s) 2021.
- Complex traits
- Evolutionary quantitative genetics
- Experimental evolution