A Cyclin E Centered Genetic Network Contributes to Alcohol-Induced Variation in Drosophila Development

Abstract

Prenatal exposure to ethanol causes a wide range of adverse physiological, behavioral and cognitive consequences. However, identifying allelic variants and genetic networks associated with variation in susceptibility to prenatal alcohol exposure is challenging in human populations, since time and frequency of exposure and effective dose cannot be determined quantitatively and phenotypic manifestations are diverse. Here, we harnessed the power of natural variation in the Drosophila melanogaster Genetic Reference Panel (DGRP) to identify genes and genetic networks associated with variation in sensitivity to developmental alcohol exposure. We measured development time from egg to adult and viability of 201 DGRP lines reared on regular or ethanol- supplemented medium and identified polymorphisms associated with variation in susceptibility to developmental ethanol exposure. We also documented genotype-dependent variation in sensorimotor behavior after developmental exposure to ethanol using the startle response assay in a subset of 39 DGRP lines. Genes associated with development, including development of the nervous system, featured prominently among genes that harbored variants associated with differential sensitivity to developmental ethanol exposure. Many of them have human orthologs and mutational analyses and RNAi targeting functionally validated a high percentage of candidate genes. Analysis of genetic interaction networks identified Cyclin E (CycE) as a central, highly interconnected hub gene. Cyclin E encodes a protein kinase associated with cell cycle regulation and is prominently expressed in ovaries. Thus, exposure to ethanol during development of Drosophila melanogaster might serve as a genetic model for translational studies on fetal alcohol spectrum disorder.

Keywords: Drosophila Genetic Reference Panel; ethanol sensitivity; genetic networks; genome-wide association; mutational analysis.

Figure 1

Phenotypic variation and genome-wide associations for viability, development time and sensitivity to ethanol exposure among 201 DGRP lines. (A) Distribution histogram for variation in viability. (B) Distribution histogram for variation in development time. Blue symbols in panels A and B indicate growth on standard medium and red symbols indicate growth on medium supplemented with 10% ethanol. The differences between the two growth conditions, illustrated by the black connecting lines, represent the sensitivity to ethanol exposure. (C) GWA analysis for viability for flies reared on regular food (top panel), ethanol-supplemented medium (middle panel) and the difference, reflecting sensitivity (lower panel). (D) GWA analysis for development time for flies reared on regular food (top panel), ethanol-supplemented medium (middle panel) and the difference, reflecting sensitivity (lower panel). Sensitivity to ethanol was determined as the difference in viability or development time between flies grown on ethanol-supplemented and regular food. The X-axes in (C) and (D) indicate chromosomal locations. The dashed lines correspond to the P < 10⁻⁵ statistical threshold. Darker dots above the line indicate SNPs that pass the statistical threshold.

Figure 2

Reaction norms that illustrate variation in startle-induced locomotor activity among 39 DGRP lines grown on regular and ethanol supplemented media for females (A) and males (B). Colors represent the different DGRP lines.

Figure 3

Functional validation of candidate genes associated with variation in sensitivity to ethanol exposure for viability (A) and development time (B). Data are shown as differences between viability or development time on ethanol-supplemented food vs. regular food and presented as deviation from the appropriate control ± SE * P < 0.05; ** P < 0.001; *** P < 0.0001.

Figure 4

A genetic interaction network for ethanol-dependent variation in viability and development time. (A) The network consists of candidate genes identified by the GWA analysis at P < 5 × 10⁻⁵. We identified 184 interconnected genes (P < 0.001) with 78 candidate genes and 106 computationally recruited genes, i.e., genes that were not identified in our study, but are known to interact with our candidate genes based on published data curated in FlyBase. The network shows only genes with three or more known genetic interactions. The octagon shape in the center indicates the most highly connected CycE gene with red lines highlighting its 54 nodal connections. Hexagons indicate the additional highly connected genes mam, sgg and fz. Blue rectangular boxes indicate candidate genes identified by GWA analyses and gray boxes represent computationally recruited genes. (B) Functional validation of highly connected candidate genes from the network analysis for viability. (C). Functional validation of highly connected candidate genes from the network analysis for development time. * P < 0.05 and ** P < 0.001 indicates a significant difference between sensitivity in RNAi knockdown lines grown on ethanol-supplemented food vs. regular food. Data are shown as deviation from the appropriate control ± SE.

Figure 5

Pleiotropic effects of the hub candidate genes. (A) Locomotor reactivity. (B) Locomotion. (C) Alcohol sensitivity. Black bars indicate females, white bars indicate males. Data are shown as deviation from the appropriate control ± SE * P < 0.05; ** P < 0.001; *** P < 0.0001.

Figure 6

A genetic interaction network of human orthologs corresponding to Drosophila candidate genes. Human orthologs were identified as counterparts to Drosophila genes depicted in Figure 4A. Blue rectangles indicate genes previously implicated in alcohol-related phenotypes in model systems and humans. The probability to obtain this network by chance is P < 0.005.