bioRxivEvolutionary BiologyPreprint
Two forms of sexual dimorphism in gene expression in Drosophila melanogaster: their coincidence and evolutionary genetics
Abstract
Phenotypic sexual dimorphism can be mediated by sex differences in gene expression. We examine two forms of sexual dimorphism in gene expression in Drosophila melanogaster: (i) sex-biased gene expression (SBGE) in which the sexes differ in the amount a gene is expressed and (ii) sexual dimorphism in isoform usage, i.e., sex-specific splicing (SSS). In whole body (but not head) expression, we find a negative association between SBGE and SSS, possibly suggesting these are alternate routes to resolving sexual antagonistic selection. Next, we evaluate whether expression dimorphism contributes to the heterogeneity among genes in rmf, the intersexual genetic correlation in body expression that constrains the extent to which a genes expression can evolve independently between the sexes. We find lower rmf values for genes with than without SSS. We find higher rmf values for male- than female-biased genes (except genes with extreme male-bias), even though male-biased genes are known to have greater evolutionary divergence in expression. Finally, we examine population genetic patterns in relation to SBGE and SSS because genes with expression dimorphism have likely experienced a history of sex differences in selection. SSS is associated with reduced values of Tajimas D and elevated Direction of Selection (DoS) values, suggestive of higher rates of adaptive evolution. Though DoS is highly elevated for genes with extreme male bias, DoS otherwise tends to decline from female-biased to unbiased to male-biased genes. Collectively, the results indicate that SBGE and SSS are differentially distributed across the genome and are associated with different forms of selection.
- organism: Drosophila
- assay: bulk RNA-seq
- research focus: chromatin & epigenetic regulation
- research focus: gene regulatory network inference
- research focus: development & morphogenesis
- research focus: host-pathogen & immune response
- approach: statistical model
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