Genome-wide architecture of adaptation in experimentally evolved Drosophila dataset

The molecular basis of adaptation remains elusive even with the current ease of sequencing the genome and transcriptome. Previous attempts to address this question have knocked out or knocked down genes, but these approaches are not applicable to populations with moderate to high genetic variation. By contrast, experimental evolution offers replicated outbred populations with well-defined selection regimes and known evolutionary histories. We used experimentally evolved populations of Drosophila in conjunction with statistical learning tools to explore interactions between the genome, the transcriptome, and phenotypes. Our results indicate that transcriptomic measures from adult samples can predict phenotypic characters at many adult ages, which is consistent with the presumed quiescence of the Drosophila transcriptome during adulthood. Importantly, when comparing the genome and transcriptome in predicting phenotypic characters, we find that the two types of data are comparably useful. When using genome sites as predictors for the expression of the transcriptome, we find that gene expression is influenced by genomic regions across all large chromosome arms. Conversely, we found many genomic regions influencing the expression of numerous genes, which is consistent with widespread pleiotropy. Our results also highlight the power of the combination of experimental evolution, next-generation sequencing, and statistical learning tools in exploring the molecular basis of adaptation