Genetics of alcohol consumption in Drosophila melanogaster.

TLDR: The results show that the genetic architecture that underlies variation in voluntary ethanol consumption is sexually dimorphic and partially overlaps with genetic factors that control variation in feeding behavior and alcohol sensitivity.

Abstract: Individual variation in alcohol consumption in human populations is determined by genetic, environmental, social and cultural factors. In contrast to humans, genetic contributions to complex behavioral phenotypes can be readily dissected in Drosophila, where both the genetic background and environment can be controlled and behaviors quantified through simple high-throughput assays. Here, we measured voluntary consumption of ethanol in ~3,000 individuals of each sex from an advanced intercross population derived from 37 lines of the Drosophila melanogaster Genetic Reference Panel. Extreme QTL mapping identified 385 differentially segregating allelic variants located in or near 291 genes at P < 10−8. The effects of single nucleotide polymorphisms associated with voluntary ethanol consumption are sex-specific, as found for other alcohol-related phenotypes. To assess causality we used RNAi knockdown or P[MiET1] mutants and their corresponding controls and functionally validated 86% of candidate genes in at least one sex. We constructed a genetic network comprised of 23 genes along with a separate trio and a pair of connected genes. Gene ontology analyses showed enrichment of developmental genes, including development of the nervous system. Furthermore, a network of human orthologs revealed enrichment for signal transduction processes, protein metabolism and developmental processes, including nervous system development. Our results show that the genetic architecture that underlies variation in voluntary ethanol consumption is sexually dimorphic and partially overlaps with genetic factors that control variation in feeding behavior and alcohol sensitivity. This integrative genetic architecture is rooted in evolutionarily conserved features that can be extrapolated to human genetic interaction networks.