Convergent expansions of keystone gene families drive metabolic innovation in Saccharomycotina yeasts

K Kyle T. David (Department of Biological Sciences, Vanderbilt University) J Joshua G. Schraiber (Department of Quantitative and Computational Biology, University of Southern California) J Johnathan G. Crandall (Laboratory of Genetics, James Franklin Crow Institute for the Study of Evolution, Center for Genomic Science Innovation, Department of Energy Great Lakes Bioenergy Research Center, Wisconsin Energy Institute, University of Wisconsin-Madison) A Abigail L. Labella (Department of Biological Sciences, Vanderbilt University) D Dana A. Opulente (Laboratory of Genetics, James Franklin Crow Institute for the Study of Evolution, Center for Genomic Science Innovation, Department of Energy Great Lakes Bioenergy Research Center, Wisconsin Energy Institute, University of Wisconsin-Madison) M Marie-Claire Harrison (Department of Biological Sciences, Vanderbilt University) J John F. Wolters (Laboratory of Genetics, James Franklin Crow Institute for the Study of Evolution, Center for Genomic Science Innovation, Department of Energy Great Lakes Bioenergy Research Center, Wisconsin Energy Institute, University of Wisconsin-Madison) X Xiaofan Zhou X Xing-Xing Shen (Key Laboratory of Biology of Crop Pathogens and Insects of Zhejiang Province, Institute of Insect Sciences, Zhejiang University) M Marizeth Groenewald (Westerdijk Fungal Biodiversity Institute) C Chris Todd Hittinger M Matt Pennell A Antonis Rokas

Abstract

Many remarkable phenotypes have repeatedly occurred across vast evolutionary distances. When convergent traits emerge on the tree of life, they are sometimes driven by the same underlying gene families, while other times, many different gene families are involved. Conversely, a gene family may be repeatedly recruited for a single trait or many different traits. To understand the general rules governing convergence at both genomic and phenotypic levels, we systematically tested associations between 56 binary metabolic traits and gene count in 14,785 gene families from 993 Saccharomycotina yeasts. Using a recently developed phylogenetic approach that reduces spurious correlations, we found that gene family expansion and contraction were significantly linked to trait gain and loss in 45/56 (80%) traits. While 595/739 (81%) significant gene families were associated with only one trait, we also identified several “keystone” gene families that were significantly associated with up to 13/56 (23%) of all traits. Strikingly, most of these families are known to encode metabolic enzymes and transporters, including all members of the industrially relevant MAL tose fermentation loci in the baker’s yeast Saccharomyces cerevisiae . These results indicate that convergent evolution on the gene family level may be more widespread across deeper timescales than previously believed.

Article Details

Volume / Issue Vol. 122, Issue 23
Published June 10, 2025
ISSN 0027-8424
Publisher National Academy of Sciences

Authors (13)

K

Kyle T. David

Department of Biological Sciences, Vanderbilt University

J

Joshua G. Schraiber

Department of Quantitative and Computational Biology, University of Southern California

J

Johnathan G. Crandall

Laboratory of Genetics, James Franklin Crow Institute for the Study of Evolution, Center for Genomic Science Innovation, Department of Energy Great Lakes Bioenergy Research Center, Wisconsin Energy Institute, University of Wisconsin-Madison

A

Abigail L. Labella

Department of Biological Sciences, Vanderbilt University

D

Dana A. Opulente

Laboratory of Genetics, James Franklin Crow Institute for the Study of Evolution, Center for Genomic Science Innovation, Department of Energy Great Lakes Bioenergy Research Center, Wisconsin Energy Institute, University of Wisconsin-Madison

M

Marie-Claire Harrison

Department of Biological Sciences, Vanderbilt University

J

John F. Wolters

Laboratory of Genetics, James Franklin Crow Institute for the Study of Evolution, Center for Genomic Science Innovation, Department of Energy Great Lakes Bioenergy Research Center, Wisconsin Energy Institute, University of Wisconsin-Madison

X

Xiaofan Zhou

X

Xing-Xing Shen

Key Laboratory of Biology of Crop Pathogens and Insects of Zhejiang Province, Institute of Insect Sciences, Zhejiang University

M

Marizeth Groenewald

Westerdijk Fungal Biodiversity Institute

C

Chris Todd Hittinger

M

Matt Pennell

A

Antonis Rokas