A graduate student in biological sciences at the University of Wisconsin-Madison and his colleagues measured the coevolution of pairs of genes shared across budding yeasts to identify the genes that participate in the same cellular ormolecular functions.
The results of this work could change the way we identify genes.
In this project, we looked at nearly 3 million pairs of genes and identified instances where pairs of genes had strong evidence of coevolution.
The project shows that genes have similar insights to those of genetic studies on model organisms. Evolutionary analyses are often less challenging and require less resources than genetic studies.
The work was made possible by a new software and data from hundreds of genomes. The evolutionary histories of genes can be used to inform our understanding of how the cell works. The target group of organisms were budding yeasts, a group of microscopic fungi that have a lot of evolutionary and genetic data available.
The first major project that heavily leaned on the software I developed was the manuscript.
The area is something of a novel terrain and his software products have been downloaded more than a hundred thousand times. He rose to this challenge by developing numerous pieces of software and integrated software development into his approach for asking how the evolution of genes can inform us about their function.
Gene function, rather than location within a chromosomes, drives the coevolution of genes. According to the authors, genomes may be viewed as extensively linked groups of genes.
The article "An orthologous gene coevolution network provides insight into cellular and eukaryotic genomic structure and function" was published in the journal Science Advances on May 4.More information: Jacob L. Steenwyk et al, An orthologous gene coevolution network provides insight into eukaryotic cellular and genomic structure and function, Science Advances (2022). DOI: 10.1126/sciadv.abn0105 Journal information: Science Advances Citation: Researchers develop new evolutionary approach for identifying proteins that functionally interact (2022, May 4) retrieved 4 May 2022 from https://phys.org/news/2022-05-evolutionary-approach-proteins-functionally-interact.html This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no part may be reproduced without the written permission. The content is provided for information purposes only.