Reticulate evolution: Detection and utility in the phylogenomics era.

Phylogenomics has enriched our understanding that the Tree of Life can have network-like or reticulate structures among some taxa and genes. Two non-vertical modes of evolution - hybridization/introgression and horizontal gene transfer - deviate from a strictly bifurcating tree model, causing non-treelike patterns. However, these reticulate processes can produce similar patterns to incomplete lineage sorting or recombination, potentially leading to ambiguity. Here, we present a brief overview of a phylogenomic workflow for inferring organismal histories and compare methods for distinguishing modes of reticulate evolution. We discuss how the timing of coalescent events can help disentangle introgression from incomplete lineage sorting and how horizontal gene transfer events can help determine the relative timing of speciation events. In doing so, we identify pitfalls of certain methods and discuss how to extend their utility across the Tree of Life. Workflows, methods, and future directions discussed herein underscore the need to embrace reticulate evolutionary patterns for understanding the timing and rates of evolutionary events, providing a clearer view of life's history.

A taxon-rich and genome-scale phylogeny of Opisthokonta.

Ancient divergences within Opisthokonta-a major lineage that includes organisms in the kingdoms Animalia, Fungi, and their unicellular relatives-remain contentious. To assess progress toward a genome-scale Opisthokonta phylogeny, we conducted the most taxon rich phylogenomic analysis using sets of genes inferred with different orthology inference methods and established the geological timeline of Opisthokonta diversification. We also conducted sensitivity analysis by subsampling genes or taxa from the full data matrix based on filtering criteria previously shown to improve phylogenomic inference. We found that approximately 85% of internal branches were congruent across data matrices and the approaches used. Notably, the use of different orthology inference methods was a substantial contributor to the observed incongruence: analyses using the same set of orthologs showed high congruence of 97% to 98%, whereas different sets of orthologs resulted in somewhat lower congruence (87% to 91%). Examination of unicellular Holozoa relationships suggests that the instability observed across varying gene sets may stem from weak phylogenetic signals. Our results provide a comprehensive Opisthokonta phylogenomic framework that will be useful for illuminating ancient evolutionary episodes concerning the origin and diversification of the 2 major eukaryotic kingdoms and emphasize the importance of investigating effects of orthology inference on phylogenetic analyses to resolve ancient divergences.

Diverse signatures of convergent evolution in cactus-associated yeasts.

Many distantly related organisms have convergently evolved traits and lifestyles that enable them to live in similar ecological environments. However, the extent of phenotypic convergence evolving through the same or distinct genetic trajectories remains an open question. Here, we leverage a comprehensive dataset of genomic and phenotypic data from 1,049 yeast species in the subphylum Saccharomycotina (Kingdom Fungi, Phylum Ascomycota) to explore signatures of convergent evolution in cactophilic yeasts, ecological specialists associated with cacti. We inferred that the ecological association of yeasts with cacti arose independently approximately 17 times. Using a machine learning-based approach, we further found that cactophily can be predicted with 76% accuracy from both functional genomic and phenotypic data. The most informative feature for predicting cactophily was thermotolerance, which we found to be likely associated with altered evolutionary rates of genes impacting the cell envelope in several cactophilic lineages. We also identified horizontal gene transfer and duplication events of plant cell wall-degrading enzymes in distantly related cactophilic clades, suggesting that putatively adaptive traits evolved independently through disparate molecular mechanisms. Notably, we found that multiple cactophilic species and their close relatives have been reported as emerging human opportunistic pathogens, suggesting that the cactophilic lifestyle-and perhaps more generally lifestyles favoring thermotolerance-might preadapt yeasts to cause human disease. This work underscores the potential of a multifaceted approach involving high-throughput genomic and phenotypic data to shed light onto ecological adaptation and highlights how convergent evolution to wild environments could facilitate the transition to human pathogenicity.

Evolutionary origin and population diversity of a cryptic hybrid pathogen.

Cryptic fungal pathogens pose disease management challenges due to their morphological resemblance to known pathogens. Here, we investigated the genomes and phenotypes of 53 globally distributed isolates of Aspergillus section Nidulantes fungi and found 30 clinical isolates-including four isolated from COVID-19 patients-were A. latus, a cryptic pathogen that originated via allodiploid hybridization. Notably, all A. latus isolates were misidentified. A. latus hybrids likely originated via a single hybridization event during the Miocene and harbor substantial genetic diversity. Transcriptome profiling of a clinical isolate revealed that both parental subgenomes are actively expressed and respond to environmental stimuli. Characterizing infection-relevant traits-such as drug resistance and growth under oxidative stress-revealed distinct phenotypic profiles among A. latus hybrids compared to parental and closely related species. Moreover, we identified four features that could aid A. latus taxonomic identification. Together, these findings deepen our understanding of the origin of cryptic pathogens.

Aspergillus fumigatus conidial surface-associated proteome reveals factors for fungal evasion and host immunity modulation.

Aspergillus fumigatus causes aspergillosis and relies on asexual spores (conidia) for initiating host infection. There is scarce information about A. fumigatus proteins involved in fungal evasion and host immunity modulation. Here we analysed the conidial surface proteome of A. fumigatus, two closely related non-pathogenic species, Aspergillus fischeri and Aspergillus oerlinghausenensis, as well as pathogenic Aspergillus lentulus, to identify such proteins. After identifying 62 proteins exclusively detected on the A. fumigatus conidial surface, we assessed null mutants for 42 genes encoding these proteins. Deletion of 33 of these genes altered susceptibility to macrophage, epithelial cells and cytokine production. Notably, a gene that encodes a putative glycosylasparaginase, modulating levels of the host proinflammatory cytokine IL-1ß, is important for infection in an immunocompetent murine model of fungal disease. These results suggest that A. fumigatus conidial surface proteins are important for evasion and modulation of the immune response at the onset of fungal infection.

Unique trajectory of gene family evolution from genomic analysis of nearly all known species in an ancient yeast lineage.

Gene gains and losses are a major driver of genome evolution; their precise characterization can provide insights into the origin and diversification of major lineages. Here, we examined gene family evolution of 1,154 genomes from nearly all known species in the medically and technologically important yeast subphylum Saccharomycotina. We found that yeast gene family and genome evolution are distinct from plants, animals, and filamentous ascomycetes and are characterized by small genome sizes and smaller gene numbers but larger gene family sizes. Faster-evolving lineages (FELs) in yeasts experienced significantly higher rates of gene losses-commensurate with a narrowing of metabolic niche breadth-but higher speciation rates than their slower-evolving sister lineages (SELs). Gene families most often lost are those involved in mRNA splicing, carbohydrate metabolism, and cell division and are likely associated with intron loss, metabolic breadth, and non-canonical cell cycle processes. Our results highlight the significant role of gene family contractions in the evolution of yeast metabolism, genome function, and speciation, and suggest that gene family evolutionary trajectories have differed markedly across major eukaryotic lineages.

The promise and pitfalls of synteny in phylogenomics.

Reconstructing the tree of life remains a central goal in biology. Early methods, which relied on small numbers of morphological or genetic characters, often yielded conflicting evolutionary histories, undermining confidence in the results. Investigations based on phylogenomics, which use hundreds to thousands of loci for phylogenetic inquiry, have provided a clearer picture of life's history, but certain branches remain problematic. To resolve difficult nodes on the tree of life, 2 recent studies tested the utility of synteny, the conserved collinearity of orthologous genetic loci in 2 or more organisms, for phylogenetics. Synteny exhibits compelling phylogenomic potential while also raising new challenges. This Essay identifies and discusses specific opportunities and challenges that bear on the value of synteny data and other rare genomic changes for phylogenomic studies. Synteny-based analyses of highly contiguous genome assemblies mark a new chapter in the phylogenomic era and the quest to reconstruct the tree of life.

Genome-wide patterns of noncoding and protein-coding sequence variation in the major fungal pathogen Aspergillus fumigatus.

Aspergillus fumigatus is a deadly fungal pathogen, responsible for >400,000 infections/year and high mortality rates. A. fumigatus strains exhibit variation in infection-relevant traits, including in their virulence. However, most A. fumigatus protein-coding genes, including those that modulate its virulence, are shared between A. fumigatus strains and closely related nonpathogenic relatives. We hypothesized that A. fumigatus genes exhibit substantial genetic variation in the noncoding regions immediately upstream to the start codons of genes, which could reflect differences in gene regulation between strains. To begin testing this hypothesis, we identified 5,812 single-copy orthologs across the genomes of 263 A. fumigatus strains. In general, A. fumigatus noncoding regions showed higher levels of sequence variation compared with their corresponding protein-coding regions. Focusing on 2,482 genes whose protein-coding sequence identity scores ranged between 75 and 99%, we identified 478 total genes with signatures of positive selection only in their noncoding regions and 65 total genes with signatures only in their protein-coding regions. Twenty-eight of the 478 noncoding regions and 5 of the 65 protein-coding regions under selection are associated with genes known to modulate A. fumigatus virulence. Noncoding region variation between A. fumigatus strains included single-nucleotide polymorphisms and insertions or deletions of at least a few nucleotides. These results show that noncoding regions of A. fumigatus genes harbor greater sequence variation than protein-coding regions, raising the hypothesis that this variation may contribute to A. fumigatus phenotypic heterogeneity.

Genomic factors shape carbon and nitrogen metabolic niche breadth across Saccharomycotina yeasts.

Organisms exhibit extensive variation in ecological niche breadth, from very narrow (specialists) to very broad (generalists). Two general paradigms have been proposed to explain this variation: (i) trade-offs between performance efficiency and breadth and (ii) the joint influence of extrinsic (environmental) and intrinsic (genomic) factors. We assembled genomic, metabolic, and ecological data from nearly all known species of the ancient fungal subphylum Saccharomycotina (1154 yeast strains from 1051 species), grown in 24 different environmental conditions, to examine niche breadth evolution. We found that large differences in the breadth of carbon utilization traits between yeasts stem from intrinsic differences in genes encoding specific metabolic pathways, but we found limited evidence for trade-offs. These comprehensive data argue that intrinsic factors shape niche breadth variation in microbes.

Phylogenomics reveals extensive misidentification of fungal strains from the genus Aspergillus.

Modern taxonomic classification is often based on phylogenetic analyses of a few molecular markers, although single-gene studies are still common. Here, we leverage genome-scale molecular phylogenetics (phylogenomics) of species and populations to reconstruct evolutionary relationships in a dense data set of 710 fungal genomes from the biomedically and technologically important genus Aspergillus. To do so, we generated a novel set of 1,362 high-quality molecular markers specific for Aspergillus and provided profile Hidden Markov Models for each, facilitating their use by others. Examining the resulting phylogeny helped resolve ongoing taxonomic controversies, identified new ones, and revealed extensive strain misidentification (7.59% of strains were previously misidentified), underscoring the importance of population-level sampling in species classification. These findings were corroborated using the current standard, taxonomically informative loci. These findings suggest that phylogenomics of species and populations can facilitate accurate taxonomic classifications and reconstructions of the Tree of Life.IMPORTANCEIdentification of fungal species relies on the use of molecular markers. Advances in genomic technologies have made it possible to sequence the genome of any fungal strain, making it possible to use genomic data for the accurate assignment of strains to fungal species (and for the discovery of new ones). We examined the usefulness and current limitations of genomic data using a large data set of 710 publicly available genomes from multiple strains and species of the biomedically, agriculturally, and industrially important genus Aspergillus. Our evolutionary genomic analyses revealed that nearly 8% of publicly available Aspergillus genomes are misidentified. Our work highlights the usefulness of genomic data for fungal systematic biology and suggests that systematic genome sequencing of multiple strains, including reference strains (e.g., type strains), of fungal species will be required to reduce misidentification errors in public databases.

The evolution of the gliotoxin biosynthetic gene cluster in Penicillium fungi.

Fungi biosynthesize diverse secondary metabolites, small organic bioactive molecules with key roles in fungal ecology. Fungal secondary metabolites are often encoded by physically clustered genes known as biosynthetic gene clusters (BGCs). Fungi in the genus Penicillium produce a cadre of secondary metabolites, some of which are useful (e.g. the antibiotic penicillin and the cholesterol-lowering drug mevastatin) and others harmful (e.g. the mycotoxin patulin and the immunosuppressant gliotoxin) to human affairs. Fungal genomes often also encode resistance genes that confer protection against toxic secondary metabolites. Some Penicillium species, such as Penicillium decumbens, are known to produce gliotoxin, a secondary metabolite with known immunosuppressant activity. To investigate the evolutionary conservation of homologs of the gliotoxin BGC and of genes involved in gliotoxin resistance in Penicillium, we analyzed 35 Penicillium genomes from 23 species. Homologous, lesser fragmented gliotoxin BGCs were found in 12 genomes, mostly fragmented remnants of the gliotoxin BGC were found in 21 genomes, whereas the remaining 2 Penicillium genomes lacked the gliotoxin BGC altogether. In contrast, broad conservation of homologs of resistance genes that reside outside the BGC across Penicillium genomes was observed. Evolutionary rate analysis revealed that BGCs with higher numbers of genes evolve slower than BGCs with few genes, suggestive of constraint and potential functional significance or more recent decay. Gene tree-species tree reconciliation analyses suggested that the history of homologs in the gliotoxin BGC across the genus Penicillium likely involved multiple duplications, losses, and horizontal gene transfers. Our analyses suggest that genes encoded in BGCs can have complex evolutionary histories and be retained in genomes long after the loss of secondary metabolite biosynthesis.

CryptoCEN: A Co-Expression Network for Cryptococcus neoformans reveals novel proteins involved in DNA damage repair.

Elucidating gene function is a major goal in biology, especially among non-model organisms. However, doing so is complicated by the fact that molecular conservation does not always mirror functional conservation, and that complex relationships among genes are responsible for encoding pathways and higher-order biological processes. Co-expression, a promising approach for predicting gene function, relies on the general principal that genes with similar expression patterns across multiple conditions will likely be involved in the same biological process. For Cryptococcus neoformans, a prevalent human fungal pathogen greatly diverged from model yeasts, approximately 60% of the predicted genes in the genome lack functional annotations. Here, we leveraged a large amount of publicly available transcriptomic data to generate a C. neoformans Co-Expression Network (CryptoCEN), successfully recapitulating known protein networks, predicting gene function, and enabling insights into the principles influencing co-expression. With 100% predictive accuracy, we used CryptoCEN to identify 13 new DNA damage response genes, underscoring the utility of guilt-by-association for determining gene function. Overall, co-expression is a powerful tool for uncovering gene function, and decreases the experimental tests needed to identify functions for currently under-annotated genes.

Natural trait variation across Saccharomycotina species.

Among molecular biologists, the group of fungi called Saccharomycotina is famous for its yeasts. These yeasts in turn are famous for what they have in common-genetic, biochemical, and cell-biological characteristics that serve as models for plants and animals. But behind the apparent homogeneity of Saccharomycotina species lie a wealth of differences. In this review, we discuss traits that vary across the Saccharomycotina subphylum. We describe cases of bright pigmentation; a zoo of cell shapes; metabolic specialties; and species with unique rules of gene regulation. We discuss the genetics of this diversity and why it matters, including insights into basic evolutionary principles with relevance across Eukarya.

Gene loss and cis-regulatory novelty shaped core histone gene evolution in the apiculate yeast Hanseniaspora uvarum.

Core histone genes display a remarkable diversity of cis-regulatory mechanisms despite their protein sequence conservation. However, the dynamics and significance of this regulatory turnover are not well understood. Here, we describe the evolutionary history of core histone gene regulation across 400 million years in budding yeasts. We find that canonical mode of core histone regulation-mediated by the trans-regulator Spt10-is ancient, likely emerging between 320 and 380 million years ago and is fixed in the majority of extant species. Unexpectedly, we uncovered the emergence of a novel core histone regulatory mode in the Hanseniaspora genus, from its fast-evolving lineage, which coincided with the loss of 1 copy of its paralogous core histone genes. We show that the ancestral Spt10 histone regulatory mode was replaced, via cis-regulatory changes in the histone control regions, by a derived Mcm1 histone regulatory mode and that this rewiring event occurred with no changes to the trans-regulator, Mcm1, itself. Finally, we studied the growth dynamics of the cell cycle and histone synthesis in genetically modified Hanseniaspora uvarum. We find that H. uvarum divides rapidly, with most cells completing a cell cycle within 60 minutes. Interestingly, we observed that the regulatory coupling between histone and DNA synthesis was lost in H. uvarum. Our results demonstrate that core histone gene regulation was fixed anciently in budding yeasts, however it has greatly diverged in the Hanseniaspora fast-evolving lineage.

Genomic, transcriptomic, and ecological diversity of Penicillium species in cheese rind microbiomes.

Although Penicillium molds can have significant impacts on agricultural, industrial, and biomedical systems, the ecological roles of Penicillium species in many microbiomes are not well characterized. Here we utilized a collection of 35 Penicillium strains isolated from cheese rinds to broadly investigate the genomic potential for secondary metabolism in cheese-associated Penicillium species, the impact of Penicillium on bacterial community assembly, and mechanisms of Penicillium-bacteria interactions. Using antiSMASH, we identified 1558 biosynthetic gene clusters, 406 of which were mapped to known pathways, including several mycotoxins and antimicrobial compounds. By measuring bacterial abundance and fungal mRNA expression when culturing representative Penicillium strains with a cheese rind bacterial community, we observed divergent impacts of different Penicillium strains, from strong inhibitors of bacterial growth to those with no impact on bacterial growth or community composition. Through differential mRNA expression analyses, Penicillium strains demonstrated limited differential gene expression in response to the bacterial community. We identified a few shared responses between the eight tested Penicillium strains, primarily upregulation of nutrient metabolic pathways, but we did not identify a conserved fungal response to growth in a multispecies community. These results in tandem suggest high variation among cheese-associated Penicillium species in their ability to shape bacterial community development and highlight important ecological diversity within this iconic genus.

Genome-wide patterns of non-coding sequence variation in the major fungal pathogen Aspergillus fumigatus.

A.fumigatus is a deadly fungal pathogen, responsible for >400,000 infections/year and high mortality rates. A. fumigatus strains exhibit variation in infection-relevant traits, including in their virulence. However, most A. fumigatus protein-coding genes, including those that modulate its virulence, are shared between A. fumigatus strains and closely related non-pathogenic relatives. We hypothesized that A. fumigatus genes exhibit substantial genetic variation in the non-coding regions immediately upstream to the start codons of genes, which could reflect differences in gene regulation between strains. To begin testing this hypothesis, we identified 5,812 single-copy orthologs across the genomes of 263 A. fumigatus strains. A. fumigatus non-coding regions showed higher levels of sequence variation compared to their corresponding protein-coding regions. Specifically, we found that 1,274 non-coding regions exhibited <75% nucleotide sequence similarity (compared to 928 protein-coding regions) and 3,721 non-coding regions exhibited between 75% and 99% similarity (compared to 2,482 protein-coding regions) across strains. Only 817 non-coding regions exhibited ≥99% sequence similarity compared to 2,402 protein-coding regions. By examining 2,482 genes whose protein-coding sequence identity scores ranged between 75% and 99%, we identified 478 total genes with signatures of positive selection only in their non-coding regions and 65 total genes with signatures only in their protein-coding regions. 28 of the 478 non-coding regions and 5 of the 65 protein-coding regions under selection are associated with genes known to modulate A. fumigatus virulence. Non-coding region variation between A. fumigatus strains included single nucleotide polymorphisms and insertions or deletions of at least a few nucleotides. These results show that non-coding regions of A. fumigatus genes harbor greater sequence variation than protein-coding regions, raising the hypothesis that this variation may contribute to A. fumigatus phenotypic heterogeneity.

A phylogenetic approach to explore the Aspergillus fumigatus conidial surface-associated proteome and its role in pathogenesis.

Aspergillus fumigatus , an important pulmonary fungal pathogen causing several diseases collectively called aspergillosis, relies on asexual spores or conidia for initiating host infection. Here, we used a phylogenomic approach to compare proteins in the conidial surface of A. fumigatus , two closely related non-pathogenic species, Aspergillus fischeri and Aspergillus oerlinghausenensis , and the cryptic pathogen Aspergillus lentulus . After identifying 62 proteins uniquely expressed on the A. fumigatus conidial surface, we deleted 42 genes encoding conidial proteins. We found deletion of 33 of these genes altered susceptibility to macrophage killing, penetration and damage to epithelial cells, and cytokine production. Notably, a gene that encodes glycosylasparaginase, which modulates levels of the host pro-inflammatory cytokine IL-1ß, is important for infection in an immunocompetent murine model of fungal disease. These results suggest that A. fumigatus conidial surface proteins and effectors are important for evasion and modulation of the immune response at the onset of fungal infection.

Diverse signatures of convergent evolution in cacti-associated yeasts.

Many distantly related organisms have convergently evolved traits and lifestyles that enable them to live in similar ecological environments. However, the extent of phenotypic convergence evolving through the same or distinct genetic trajectories remains an open question. Here, we leverage a comprehensive dataset of genomic and phenotypic data from 1,049 yeast species in the subphylum Saccharomycotina (Kingdom Fungi, Phylum Ascomycota) to explore signatures of convergent evolution in cactophilic yeasts, ecological specialists associated with cacti. We inferred that the ecological association of yeasts with cacti arose independently ~17 times. Using machine-learning, we further found that cactophily can be predicted with 76% accuracy from functional genomic and phenotypic data. The most informative feature for predicting cactophily was thermotolerance, which is likely associated with duplication and altered evolutionary rates of genes impacting the cell envelope in several cactophilic lineages. We also identified horizontal gene transfer and duplication events of plant cell wall-degrading enzymes in distantly related cactophilic clades, suggesting that putatively adaptive traits evolved through disparate molecular mechanisms. Remarkably, multiple cactophilic lineages and their close relatives are emerging human opportunistic pathogens, suggesting that the cactophilic lifestyle-and perhaps more generally lifestyles favoring thermotolerance-may preadapt yeasts to cause human disease. This work underscores the potential of a multifaceted approach involving high throughput genomic and phenotypic data to shed light onto ecological adaptation and highlights how convergent evolution to wild environments could facilitate the transition to human pathogenicity.

CryptoCEN: A Co-Expression Network for Cryptococcus neoformans reveals novel proteins involved in DNA damage repair.

Elucidating gene function is a major goal in biology, especially among non-model organisms. However, doing so is complicated by the fact that molecular conservation does not always mirror functional conservation, and that complex relationships among genes are responsible for encoding pathways and higher-order biological processes. Co-expression, a promising approach for predicting gene function, relies on the general principal that genes with similar expression patterns across multiple conditions will likely be involved in the same biological process. For Cryptococcus neoformans, a prevalent human fungal pathogen greatly diverged from model yeasts, approximately 60% of the predicted genes in the genome lack functional annotations. Here, we leveraged a large amount of publicly available transcriptomic data to generate a C. neoformans Co-Expression Network (CryptoCEN), successfully recapitulating known protein networks, predicting gene function, and enabling insights into the principles influencing co-expression. With 100% predictive accuracy, we used CryptoCEN to identify 13 new DNA damage response genes, underscoring the utility of guilt-by-association for determining gene function. Overall, co-expression is a powerful tool for uncovering gene function, and decreases the experimental tests needed to identify functions for currently under-annotated genes.