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Data from: The genetic basis of variation in sexual aggression: evolution versus social plasticity

Cite this dataset

Scott, Andrew et al. (2022). Data from: The genetic basis of variation in sexual aggression: evolution versus social plasticity [Dataset]. Dryad. https://doi.org/10.5061/dryad.zs7h44jbr

Abstract

Male sexual aggression towards females is a form of sexual conflict that can result in increased fitness for males through forced copulations or coercive matings at the cost of female lifetime fitness. We used male fruit flies (Drosophila melanogaster) as a model system to uncover the genomic contributions to variation in forced copulation, both due to standing variation in a wild population, and due to plastic changes associated with variation in social experience. We used RNAseq to analyze whole-transcriptome differential expression in male head tissue associated with evolved changes in forced copulation from lineages previously selected for high and low forced copulation rate (Dukas et al., 2020), and in male flies with varying forced copulation rates due to social experience. We identified hundreds of genes associated with evolved and plastic variation in forced copulation, however only a small proportion (27 genes) showed consistent differential expression due to both modes of variation. We confirmed this trend of low concordance in gene expression effects across broader sets of genes significant in either the evolved or plastic analyses using multivariate approaches. The gene ontology terms neuropeptide hormone activity and serotonin receptor activity were significantly enriched in the set of significant genes. Of 7 genes chosen for RNAi knockdown validation tests, knockdowns of 4 genes showed the expected effect on forced copulation behaviours. Taken together, our results provide important information about the apparently independent genetic architectures that underlie natural variation in sexual aggression due to evolution and plasticity.

Usage notes

Please see attached README file for information about the data sets and experiment-specific notes on missing values.