Roles of Mutation, Ploidy, and Recombination in Adaptive Evolution in Two Divergent Model Yeasts

TL;DR

This paper explores how mutation, ploidy, and recombination influence adaptation in two yeasts under different environmental conditions.

Contribution

The paper integrates population genomics with ecological frameworks to study how genetic processes interact in natural yeast populations.

Findings

Mutation rates, recombination, and ploidy states vary across yeast strains and environments.

Fluctuating environments may intensify interactions among genetic processes, affecting evolution unpredictably.

Integrating genomics with ecology is crucial for understanding fungal adaptation and disease emergence.

Abstract

Genetic variation underlies the capacity of populations to adapt, yet what drives how this variation is generated and maintained in natural populations remains poorly understood. Fundamental processes such as mutation, ploidy, and recombination are known to shape genetic variation and adaptive potential but are typically studied in isolation and under controlled laboratory conditions. How these processes act together under varying environmental conditions to structure genetic variation across complex natural populations remains unresolved. In yeasts, these processes are dependent on reproductive mode, ploidy shifts, and environmental stressors, which jointly shape genomic stability and adaptive potential. Here, we review our current knowledge on the roles of mutation, ploidy, and recombination in adaptation in the model yeasts Saccharomyces cerevisiae and the human pathogenic Cryptococcus. We highlight heterogeneity in mutation rates, recombination, and ploidy states across strains, environments, and populations, challenging the assumption that these parameters are uniform. We argue that fluctuating environments, increasingly driven by climate change, are likely to intensify interactions among these processes to impact evolution in ways that remain difficult to predict. Integrating population genomics with ecologically realistic frameworks will be essential for understanding natural evolutionary dynamics and anticipating fungal adaptation and disease emergence.

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