Repeated losses of self-fertility shaped heterozygosity and polyploidy in yeast evolution
Abstract
Evolutionary transitions in mating strategy have profound consequences for genetic variation and adaptation. In Saccharomyces cerevisiae , mating-type switching is a central feature of the life cycle that enables haploid cells to be self-fertile and mate with their own mitotic descendants (homothallism). Yet heterothallic isolates that have lost this ability are found across diverse niches, indicating that this trait is polymorphic. Here, we experimentally characterized loss of mating-type switching in a representative panel of strains. Analysis of 117 telomere-to-telomere genome assemblies revealed multiple independent loss-of-function mutations in the Ho endonuclease gene and structural variants in the silent HML and HMR cassettes, the three loci essential for switching. We estimated that at least 13 independent transitions from homothallism to heterothallism have occurred in the species history. Analysis of the HO genotype of 2,910 strains shows that at least 27% are heterothallic. We found that heterothallism is strongly associated with polyploidy and elevated genome-wide heterozygosity, although the strength of these associations varies between populations. Heterothallic isolates are most prevalent in domesticated and clinical clades, consistent with an origin linked to human-associated environments. However, they are also found, though less frequently, in natural niches. Signatures of recombination in HO sequences suggest that outcrossing contributed to the ecological and geographical distribution of the trait. Our findings reveal that mating-type switching has undergone repeated losses in S. cerevisiae evolution, with major consequences for genome architecture and ecological diversification.
Article Details
Journal Info
Proceedings of the National Academy of Sciences
National Academy of Sciences
Authors (12)
Nina Vittorelli
Sorbonne Université, CNRS, Computational, Quantitative and Synthetic Biology, CQSB
Cintia Gómez-Muñoz
Sorbonne Université, CNRS, Computational, Quantitative and Synthetic Biology, CQSB
Irina Andriushchenko
Sorbonne Université, CNRS, Computational, Quantitative and Synthetic Biology, CQSB
Louis Ollivier
Sorbonne Université, CNRS, Computational, Quantitative and Synthetic Biology, CQSB
Nicolas Agier
Sorbonne Université, CNRS, Computational, Quantitative and Synthetic Biology, CQSB
Stéphane Delmas
Sorbonne Université, CNRS, Computational, Quantitative and Synthetic Biology, CQSB
Yann Corbeau
Sorbonne Université, CNRS, Computational, Quantitative and Synthetic Biology, CQSB
Guillaume Achaz
Centre Interdisciplinaire de Recherche en Biologie, Collège de France, Université PSL, CNRS, INSERM
Marco Cosentino Lagomarsino
IFOM- Istituto Fondazione di Oncologia Molecolare
Gianni Liti
Bertrand Llorente
CRCM, Aix Marseille Université, CNRS, INSERM, Institut Paoli Calmettes
Gilles Fischer
Sorbonne Université, CNRS, Computational, Quantitative and Synthetic Biology, CQSB