Seasonal plasticity and adaptive fluctuations of gene expressions of D. melanogaster
Authors: Yang Yu; Alan Bergland
Affiliation: University of Virginia
Keywords: d. evolution of gene expression; a. genome evolution
Two major mechanisms for populations of short-lived organisms to respond to temporal environmental heterogeneity, such as seasonality, are adaptive tracking and plasticity. Theory predicts that transition from one mechanism to another will have detrimental effects on the populations, thus the genetic architecture between adaptive tracking and plasticity should have limited overlap. Seasonal adaptive tracking can be observed from allele frequency change at individual loci and at genome-wide levels. Although thousands of SNPs have been shown to shift in frequency repeatedly across seasons in Drosophila melanogaster populations, we still have limited understanding of the relative strength of evolutionary mechanisms that underlie seasonal adaptation. In this study, we test the hypothesis that there is distinct genetic architecture between adaptive tracking and plasticity by using genome-wide plastic gene expression profiles across the season. We first identify the genes that plastically change in expression levels across the season to gain insight into the functional response to seasonal environmental changes. Second, we will combine publicly available eQTL profiles, genome-wide allele frequency data from multiple seasonal populations, with our seasonal gene expression data to test whether the eQTLs associated with plastic genes are de-enriched for seasonal SNPs. We created and reared a genetically controlled F1 fly population from 24h embryos to adulthood in an experimental orchard across 10 seasonal time points (May to Oct in 2019) to examine the differentially expressed (DE) genes across the season. We extracted whole-tissue RNA from 3-5-day-old adult female flies and prepared pooled libraries using bulk RNA barcoding method (BRBSeq). Our next step is to identify the plastic genes and test our hypothesis that the eQTLs associated with these genes are de-enriched for seasonal SNPs. We hope to provide insight into the general understanding of seasonal adaptation from an expression perspective, and how seasonal environmental heterogeneity maintains functional genetic variation at eQTLs across time.