View Program - 2022 Population, Evolutionary, and Quantitative Genetics Conference

Pleiotropy, the phenomenon where a single locus affects multiple traits, is an important feature of the genetic architecture of traits. Current descriptions of pleiotropy have been limited by the poor spatial resolution of causal loci and the difficulty in measuring a large number of traits. In this study, we overcame these limitations by using DNA barcode sequencing based fitness assays to measure the fitness of 100,000 F1 segregant genotypes from a yeast cross in 111 different environments. These 111 environments consisted of a set of perturbation gradients (e.g. a temperature gradient) imposed on four very different base environments and thus contained both similar (“local” pleiotropy) and dissimilar environments (“global” pleiotropy). The two major aims of this study are to determine if the effect of a perturbation is the same in the different base environments and if the fitness variation in many environments can be explained by variation along a small number of dimensions or “core phenotypes”. In a pilot study using a smaller number of F1 segregant genotypes, we found that perturbation gradients showed two major patterns of correlation: clustering by base environment and clustering by gradient concentration at high concentrations. We identified causal loci responsible for fitness variation by quantitative trait locus (QTL) mapping; these causal loci were jointly mapped across environments to improve spatial resolution. Preliminary joint QTL mapping identified several genes with known fitness effects and causal loci whose effect sizes were correlated with the gradient concentration. This work provides a detailed description of pleiotropy across a variety of laboratory environments and infers a lower-dimensional space of “core phenotypes” that has good predictive power and provides biological insight into the genetic architecture of fitness.

Understanding the local and global structure of pleiotropy using a yeast cross