Local adaptation drives changes in population phenotypes that confer survival or reproductive success in specific environments. Local adaptation may be hindered or facilitated by pleiotropy, which is the control of multiple traits by a single genetic locus. In this study, we characterized the role of pleiotropy in local adaptation in the Texas endemic silverleaf sunflower, Helianthus argophyllus. Populations of H. argophyllus exhibit a bimodal life history strategy, consisting of tall, late-flowering forms and short, early-flowering forms that occur in close geographic proximity. The expression of life-history traits in H. argophyllus populations is linked to local adaptation and controlled by a highly pleiotropic locus. Still, we do not know how local adaptation and pleiotropy interact at the transcriptomic level. Here, we identify putatively locally adapted genes using whole RNA sequencing data and two selection outlier approaches. We assess transcriptomic pleiotropy by evaluating whether allelic variants within genes regulate the expression of other genes (an eQTL approach) and by assessing gene co-expression network connectivity. Candidate locally adapted genes show a modest enrichment for eQTL which control the expression of more eGenes than non-candidate eQTL. Candidate locally adapted genes also exhibit significantly higher connectivity in gene co-expression networks, greater genetic differentiation and genetic diversity, and stronger selective sweep signals than the rest of the transcriptome. Gene co-expression networks enriched for candidate locally adapted genes show higher genetic differentiation and stronger signatures of soft selective sweeps than unenriched networks. Our results support a model of ecotypic divergence under gene flow and align with recent revisions of Fisher's geometric theory, wherein large-effect pleiotropic loci can facilitate local adaptation while polygenic soft-sweeps across functional gene networks fine-tune adaptive responses.
Okinedo et al. (Mon,) studied this question.