1 Abstract
As detailed data on gene expression become accessible from more species, we have an opportunity to test the extent to which our understanding of developmental genetics from model organisms helps predict expression patterns across species. Central to this is the question: how much variation in gene expression do we expect to observe between species? Here we provide an answer by comparing RNAseq data between twelve species of Hawaiian Drosophilidae flies, focusing on gene expression differences between the ovary and other tissues. We show that there exists a cohort of ovary-specific genes that is stable across species, and that largely corresponds to described expression patterns from laboratory model Drosophila species. However, our results also show that, as phylogenetic distance increases, variation between species overwhelms variation between tissues. Using ancestral state reconstruction of expression, we describe the distribution of evolutionary changes in tissue-biased expression profiles, and use this to identify gains and losses of ovarian expression across these twelve species. We then use this distribution to calculate the correlation in expression evolution between genes, and demonstrate that genes with known interactions in D. melanogaster are significantly more correlated in their evolution than genes with no or unknown interactions. Finally, we use this correlation matrix to infer new networks of genes that have similar evolutionary trajectories, and we provide these as a dataset of novel testable hypotheses about genetic roles and interactions.
Competing Interest Statement
The authors have declared no competing interest.
