Comparative modeling reveals the molecular determinants of aneuploidy fitness cost in a wild yeast model.

Autor:	Rojas J; Center for Genomic Science Innovation, University of Wisconsin-Madison, Madison, WI 53706, USA., Hose J; Center for Genomic Science Innovation, University of Wisconsin-Madison, Madison, WI 53706, USA., Dutcher HA; Center for Genomic Science Innovation, University of Wisconsin-Madison, Madison, WI 53706, USA., Place M; Center for Genomic Science Innovation, University of Wisconsin-Madison, Madison, WI 53706, USA; Great Lakes Bioenergy Research Center, University of Wisconsin-Madison, Madison, WI 53706, USA., Wolters JF; Laboratory of Genetics, University of Wisconsin-Madison, Madison, WI 53706, USA., Hittinger CT; Center for Genomic Science Innovation, University of Wisconsin-Madison, Madison, WI 53706, USA; Great Lakes Bioenergy Research Center, University of Wisconsin-Madison, Madison, WI 53706, USA; Laboratory of Genetics, University of Wisconsin-Madison, Madison, WI 53706, USA; J.F. Crow Institute for the Study of Evolution, University of Wisconsin-Madison, Madison, WI 53706, USA., Gasch AP; Center for Genomic Science Innovation, University of Wisconsin-Madison, Madison, WI 53706, USA; Great Lakes Bioenergy Research Center, University of Wisconsin-Madison, Madison, WI 53706, USA; Laboratory of Genetics, University of Wisconsin-Madison, Madison, WI 53706, USA; J.F. Crow Institute for the Study of Evolution, University of Wisconsin-Madison, Madison, WI 53706, USA. Electronic address: agasch@wisc.edu.
Jazyk:	angličtina
Zdroj:	Cell genomics [Cell Genom] 2024 Oct 09; Vol. 4 (10), pp. 100656. Date of Electronic Publication: 2024 Sep 23.
DOI:	10.1016/j.xgen.2024.100656
Abstrakt:	Although implicated as deleterious in many organisms, aneuploidy can underlie rapid phenotypic evolution. However, aneuploidy will be maintained only if the benefit outweighs the cost, which remains incompletely understood. To quantify this cost and the molecular determinants behind it, we generated a panel of chromosome duplications in Saccharomyces cerevisiae and applied comparative modeling and molecular validation to understand aneuploidy toxicity. We show that 74%-94% of the variance in aneuploid strains' growth rates is explained by the cumulative cost of genes on each chromosome, measured for single-gene duplications using a genomic library, along with the deleterious contribution of small nucleolar RNAs (snoRNAs) and beneficial effects of tRNAs. Machine learning to identify properties of detrimental gene duplicates provided no support for the balance hypothesis of aneuploidy toxicity and instead identified gene length as the best predictor of toxicity. Our results present a generalized framework for the cost of aneuploidy with implications for disease biology and evolution. Competing Interests: Declaration of interests The authors have no competing interests to declare. (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)
Databáze:	MEDLINE
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