ArticlePLoS genetics2023
The evolution of ovary-biased gene expression in Hawaiian Drosophila.
Article in PLoS genetics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- The Ring-Legged Earwig, Euborellia annulipes (Dermaptera, Insecta): A Promising Model to Study Development and Reproductive Strategies of Hemimetabolous Insects.Results and problems in cell differentiation · 2026Review
- Conserved Gene Expression Plasticity in Development Is More Pervasive Than Expression Divergence Between Species of Caenorhabditis Nematodes.Evolution & development · 2025Article
- Comparative Analysis of Maternal Gene Expression Patterns Unravels Evolutionary Signatures Across Reproductive Modes.Molecular biology and evolution · 2024Article
- Integrating phylogenies into single-cell RNA sequencing analysis allows comparisons across species, genes, and cells.PLoS biology · 2024Article
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Authors and funding
4 authors.
Funding
Abstract
With detailed data on gene expression accessible from an increasingly broad array of species, we can test the extent to which our developmental genetic knowledge from model organisms predicts expression patterns and variation across species. But to know when differences in gene expression across species are significant, we first need to know how much evolutionary variation in gene expression we expect to observe. Here we provide an answer by analyzing RNAseq data across twelve species of Hawaiian Drosophilidae flies, focusing on gene expression differences between the ovary and other tissues. We show that over evolutionary time, there exists a cohort of ovary specific genes that is stable and that largely corresponds to described expression patterns from laboratory model Drosophila species. Our results also provide a demonstration of the prediction that, as phylogenetic distance increases, variation between species overwhelms variation between tissue types. Using ancestral state reconstruction of expression, we describe the distribution of evolutionary changes in tissue-biased expression, and use this to identify gains and losses of ovary-biased expression across these twelve species. We then use this distribution to calculate the evolutionary correlation in expression changes 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 share evolutionary trajectories, and we present these results as a dataset of new testable hypotheses about genetic roles and interactions in the function and evolution of the Drosophila ovary.
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