Search for: All records

Abstract As the tree of life becomes increasingly accessible to molecular investigations, describing mechanisms underlying evolutionary convergence and constraint will be crucial to understanding diversification. The lineage including the model yeastSaccharomyces cerevisiaeevolved aerobic fermentation in part through an ancient whole genome duplication and retention of glycolytic genes. To evaluate glycolytic rates across diverse yeasts, we developed and deployed an extracellular acidification rates (ECAR) assay on 299 species that span more than 400 million years of evolution and identified a clade in the genusSaturnisporathat convergently evolved aerobic fermentation. Through comparative genomics and transcriptomics, we found that several glycolytic genes had higher expression and novel cis-regulatory elements in aerobically fermentingSaturnisporaspecies. When the transcription factor required for their activation was deleted inSaturnispora dispora, the mutants had reduced glycolytic rates and increased respiration. Intriguingly, many of the upregulated genes are orthologous to duplicated glycolytic genes inS. cerevisiae. These divergent genetic mechanisms affecting the same set of genes suggest that there are strong evolutionary constraints on how aerobic fermentation can arise. 

Abstract Saccharomycotina is a subphylum of ascomycete fungi with diverse asexual growth morphologies. Filamentous growth can comprise linear and branched budding cells that do not undergo cell separation, termed pseudohyphae, or tubular filaments with septa that perforate allowing movement of organelles, termed true hyphae. We integrated phenotypic, genomic, metabolic, and environmental data on isolation sources from 1051 species to examine the variation and evolutionary history of filamentation across Saccharomycotina and determine whether these data could predict filamentation types. We found that 63.37% of strains can form filaments; 6.56% true hyphae, 42.40% pseudohyphae, and 14.39% both true hyphae and pseudohyphae. The distributions of species that can produce true hyphae or filament were more strongly correlated with the yeast phylogeny than the distribution of species with pseudohyphae. Ancestral state reconstruction suggested that true hyphal and pseudohyphal morphologies evolved several times, that most yeast ancestors likely produced pseudohyphae or lacked filaments, and that the Saccharomycotina last common ancestor likely produced pseudohyphae but not true hyphae. Machine learning models trained on genomic and metabolic features predicted filament morphologies with ∼70% accuracy. Connecting the evolution of morphologies to their genomic, physiological, and ecological characteristics will enrich our understanding of how the diversity of lifestyles evolved in Saccharomycotina. 

Antifungal drug resistance is a major challenge in fungal infection management. Numerous genomic changes are known to contribute to acquired drug resistance in clinical isolates of specific pathogens, but whether they broadly explain natural resistance across entire lineages is unknown. We leveraged genomic, ecological, and phenotypic trait data from naturally sampled strains from nearly all known species in subphylumSaccharomycotinato examine the evolution of resistance to eight antifungal drugs. The phylogenetic distribution of drug resistance varied by drug; fluconazole resistance was widespread, while 5-fluorocytosine resistance was rare, except inLipomycetales. A random forest algorithm trained on genomic data predicted drug-resistant yeasts with 54–75% accuracy. Fluconazole resistance was consistently predicted with the highest accuracy (75.2%). Furthermore, fluconazole resistance prediction accuracy was similar between models trained on genome-wide variation in the presence and number of InterPro protein annotations acrossSaccharomycotina(75.2%) and those trained on amino acid sequence alignment data of Erg11, a protein known to be involved in fluconazole resistance (74.3-74.9%). Interestingly, the top Erg11 residues for predicting fluconazole resistance acrossSaccharomycotinado not overlap with, are not spatially close to, and are less conserved than those previously linked to resistance in clinical isolates ofCandida albicans.In silicodeep mutational scanning of theC. albicansErg11 protein reveals that amino acid variants implicated in clinical cases of resistance are almost universally destabilizing while variants in our most informative residues are energetically more neutral, explaining why the latter are much more common than the former in natural populations. Importantly, previous experimental analyses ofC. albicansErg11 have shown that amino acid variation in our most informative residues, despite having never been directly implicated in clinical cases, can directly contribute to resistance. Our results suggest that studies of natural resistance in yeast species never encountered in the clinic will yield a fuller understanding of antifungal drug resistance. 

Abstract Centromeres ensure accurate chromosome segregation, yet their DNA evolves rapidly across eukaryotes leaving the origins of new centromere architectures unclear^1–4. The brewer’s yeastSaccharomyces cerevisiaeexemplifies this long-standing puzzle. Its centromeres shifted ancestrally from large, repeat-rich, epigenetically specified forms to the compact, genetically defined ‘point’ centromeres^1,5. How this transition occurred has remained unresolved⁶. Here we identify evolutionarily related ‘proto-point’ centromeres that provide a resolution to the evolutionary origins of point centromeres. Proto-point centromeres contain a single centromeric nucleosome positioned over an AT-rich core, accompanied by relaxed organization and sequence variability of flankingcis-elements. In two species, these proto-point centromeres lie within retrotransposon-derived repeat clusters, linking ancestral repeat-rich centromeres to genetically encoded ones. Comparative and phylogenetic analyses indicate that proto-point and point centromeres evolved in an ancestor with retrotransposon-rich centromeres. These results identify long-terminal-repeat retrotransposons, specifically Ty5 sequences, as the genetic substrate for point-centromere evolution and provide a mechanistic route by which an epigenetic centromere can become genetically specified. More broadly, they show how selfish elements can be co-opted to perform essential chromosomal functions. 

Abstract A major goal of research in evolution and genetics is linking genotype to phenotype. This work could be direct, such as determining the genetic basis of a phenotype by leveraging genetic variation or divergence in a developmental, physiological, or behavioral trait. The work could also involve studying the evolutionary phenomena (e.g., reproductive isolation, adaptation, sexual dimorphism, behavior) that reveal an indirect link between genotype and a trait of interest. When the phenotype diverges across evolutionarily distinct lineages, this genotype-to-phenotype problem can be addressed using phylogenetic genotype-to-phenotype (PhyloG2P) mapping, which uses genetic signatures and convergent phenotypes on a phylogeny to infer the genetic bases of traits. The PhyloG2P approach has proven powerful in revealing key genetic changes associated with diverse traits, including the mammalian transition to marine environments and transitions between major mechanisms of photosynthesis. However, there are several intermediate traits layered in between genotype and the phenotype of interest, including but not limited to transcriptional profiles, chromatin states, protein abundances, structures, modifications, metabolites, and physiological parameters. Each intermediate trait is interesting and informative in its own right, but synthesis across data types has great promise for providing a deep, integrated, and predictive understanding of how genotypes drive phenotypic differences and convergence. We argue that an expanded PhyloG2P framework (the PhyloG2P matrix) that explicitly considers intermediate traits, and imputes those that are prohibitive to obtain, will allow a better mechanistic understanding of any trait of interest. This approach provides a proxy for functional validation and mechanistic understanding in organisms where laboratory manipulation is impractical.