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The evolution of ovary-biased gene expression in Hawaiian Drosophila
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 spe...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9894553/ https://www.ncbi.nlm.nih.gov/pubmed/36689550 http://dx.doi.org/10.1371/journal.pgen.1010607 |
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author | Church, Samuel H. Munro, Catriona Dunn, Casey W. Extavour, Cassandra G. |
author_facet | Church, Samuel H. Munro, Catriona Dunn, Casey W. Extavour, Cassandra G. |
author_sort | Church, Samuel H. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9894553 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-98945532023-02-03 The evolution of ovary-biased gene expression in Hawaiian Drosophila Church, Samuel H. Munro, Catriona Dunn, Casey W. Extavour, Cassandra G. PLoS Genet Research Article 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. Public Library of Science 2023-01-23 /pmc/articles/PMC9894553/ /pubmed/36689550 http://dx.doi.org/10.1371/journal.pgen.1010607 Text en © 2023 Church et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Church, Samuel H. Munro, Catriona Dunn, Casey W. Extavour, Cassandra G. The evolution of ovary-biased gene expression in Hawaiian Drosophila |
title | The evolution of ovary-biased gene expression in Hawaiian Drosophila |
title_full | The evolution of ovary-biased gene expression in Hawaiian Drosophila |
title_fullStr | The evolution of ovary-biased gene expression in Hawaiian Drosophila |
title_full_unstemmed | The evolution of ovary-biased gene expression in Hawaiian Drosophila |
title_short | The evolution of ovary-biased gene expression in Hawaiian Drosophila |
title_sort | evolution of ovary-biased gene expression in hawaiian drosophila |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9894553/ https://www.ncbi.nlm.nih.gov/pubmed/36689550 http://dx.doi.org/10.1371/journal.pgen.1010607 |
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