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

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 <i>MAL</i> tose fermentation loci in the baker's yeast <i>Saccharomyces cerevisiae</i>. These results indicate that convergent evolution on the gene family level may be more widespread across deeper timescales than previously believed.

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Publication Details

Journal
Proceedings of the National Academy of Sciences
Published
2025-06-03
DOI
https://doi.org/10.1073/pnas.2500165122
Citations
12
Primary Topic
Microbial Metabolic Engineering and Bioproduction
Type
article
Field-Weighted Citation Impact
9.67

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article

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

Marizeth Groenewald, Kyle T. David, Dana A. Opulente, John F. Wolters et al.
12 citations
Proceedings of the National Academy of Sciences
Microbial Metabolic Engineering and Bioproduction
9.67
article

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

Marizeth Groenewald, Kyle T. David, Dana A. Opulente, John F. Wolters, Joshua G. Schraiber, Xiaofan Zhou, Marie‐Claire Harrison, Antonis Rokas, Johnathan G. Crandall, Chris Todd Hittinger, Matthew W. Pennell, Abigail L. LaBella, Xing‐Xing Shen
article en
12 citations

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 <i>MAL</i> tose fermentation loci in the baker's yeast <i>Saccharomyces cerevisiae</i>. These results indicate that convergent evolution on the gene family level may be more widespread across deeper timescales than previously believed.

Proceedings of the National Academy of SciencesVol. 122(23)
South China Agricultural University (CN), University of North Carolina at Charlotte (US), University of Southern California (US), University of Wisconsin–Madison (US), Vanderbilt University (US), Cornell University (US), Great Lakes Bioenergy Research Center (US), Westerdijk Fungal Biodiversity Institute (NL), Zhejiang University (CN), Villanova University (US)
National Science Foundation
Openalex Percentile: Top 2%
Microbial Metabolic Engineering and Bioproduction
9.67
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