Genomic factors shaping codon usage across the Saccharomycotina subphylum.

Codon usage bias, or the unequal use of synonymous codons, is observed across genes, genomes, and between species. The biased use of synonymous codons has been implicated in many cellular functions, such as translation dynamics and transcript stability, but can also be shaped by neutral forces. The Saccharomycotina, the fungal subphylum containing the yeasts Saccharomyces cerevisiae and Candida albicans , has been a model system for studying codon usage. We characterized codon usage across 1,154 strains from 1,051 species to gain insight into the biases, molecular mechanisms, evolution, and genomic features contributing to codon usage patterns across the subphylum. We found evidence of a general preference for A/T-ending codons and correlations between codon usage bias, GC content, and tRNA-ome size. Codon usage bias is also distinct between the 12 orders within the subphylum to such a degree that yeasts can be classified into orders with an accuracy greater than 90% using a machine learning algorithm trained on codon usage. We also characterized the degree to which codon usage bias is impacted by translational selection. Interestingly, the degree of translational selection was influenced by a combination of genome features and assembly metrics that included the number of coding sequences, BUSCO count, and genome length. Our analysis also revealed an extreme bias in codon usage in the Saccharomycodales associated with a lack of predicted arginine tRNAs. The order contains 24 species, and 23 are computationally predicted to lack tRNAs that decode CGN codons, leaving only the AGN codons to encode arginine. Analysis of Saccharomycodales gene expression, tRNA sequences, and codon evolution suggests that extreme avoidance of the CGN codons is associated with a decline in arginine tRNA function. Codon usage bias within the Saccharomycotina is generally consistent with previous investigations in fungi, which show a role for both genomic features and GC bias in shaping codon usage. However, we find cases of extreme codon usage preference and avoidance along yeast lineages, suggesting additional forces may be shaping the evolution of specific codons.

Identification of a longevity gene through evolutionary rate covariation of insect mito-nuclear genomes.

Oxidative phosphorylation, essential for energy metabolism and linked to the regulation of longevity, involves mitochondrial and nuclear genes. The functions of these genes and their evolutionary rate covariation (ERC) have been extensively studied, but little is known about whether other nuclear genes not targeted to mitochondria evolutionarily and functionally interact with mitochondrial genes. Here we systematically examined the ERC of mitochondrial and nuclear benchmarking universal single-copy ortholog (BUSCO) genes from 472 insects, identifying 75 non-mitochondria-targeted nuclear genes. We found that the uncharacterized gene CG11837-a putative ortholog of human DIMT1-regulates insect lifespan, as its knockdown reduces median lifespan in five diverse insect species and Caenorhabditis elegans, whereas its overexpression extends median lifespans in fruit flies and C. elegans and enhances oxidative phosphorylation gene activity. Additionally, DIMT1 overexpression protects human cells from cellular senescence. Together, these data provide insights into the ERC of mito-nuclear genes and suggest that CG11837 may regulate longevity across animals.

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.

Machine learning enables identification of an alternative yeast galactose utilization pathway.

How genomic differences contribute to phenotypic differences is a major question in biology. The recently characterized genomes, isolation environments, and qualitative patterns of growth on 122 sources and conditions of 1,154 strains from 1,049 fungal species (nearly all known) in the yeast subphylum Saccharomycotina provide a powerful, yet complex, dataset for addressing this question. We used a random forest algorithm trained on these genomic, metabolic, and environmental data to predict growth on several carbon sources with high accuracy. Known structural genes involved in assimilation of these sources and presence/absence patterns of growth in other sources were important features contributing to prediction accuracy. By further examining growth on galactose, we found that it can be predicted with high accuracy from either genomic (92.2%) or growth data (82.6%) but not from isolation environment data (65.6%). Prediction accuracy was even higher (93.3%) when we combined genomic and growth data. After the GALactose utilization genes, the most important feature for predicting growth on galactose was growth on galactitol, raising the hypothesis that several species in two orders, Serinales and Pichiales (containing the emerging pathogen Candida auris and the genus Ogataea, respectively), have an alternative galactose utilization pathway because they lack the GAL genes. Growth and biochemical assays confirmed that several of these species utilize galactose through an alternative oxidoreductive D-galactose pathway, rather than the canonical GAL pathway. Machine learning approaches are powerful for investigating the evolution of the yeast genotype-phenotype map, and their application will uncover novel biology, even in well-studied traits.

Functional and Evolutionary Integration of a Fungal Gene With a Bacterial Operon.

Siderophores are crucial for iron-scavenging in microorganisms. While many yeasts can uptake siderophores produced by other organisms, they are typically unable to synthesize siderophores themselves. In contrast, Wickerhamiella/Starmerella (W/S) clade yeasts gained the capacity to make the siderophore enterobactin following the remarkable horizontal acquisition of a bacterial operon enabling enterobactin synthesis. Yet, how these yeasts absorb the iron bound by enterobactin remains unresolved. Here, we demonstrate that Enb1 is the key enterobactin importer in the W/S-clade species Starmerella bombicola. Through phylogenomic analyses, we show that ENB1 is present in all W/S clade yeast species that retained the enterobactin biosynthetic genes. Conversely, it is absent in species that lost the ent genes, except for Starmerella stellata, making this species the only cheater in the W/S clade that can utilize enterobactin without producing it. Through phylogenetic analyses, we infer that ENB1 is a fungal gene that likely existed in the W/S clade prior to the acquisition of the ent genes and subsequently experienced multiple gene losses and duplications. Through phylogenetic topology tests, we show that ENB1 likely underwent horizontal gene transfer from an ancient W/S clade yeast to the order Saccharomycetales, which includes the model yeast Saccharomyces cerevisiae, followed by extensive secondary losses. Taken together, these results suggest that the fungal ENB1 and bacterial ent genes were cooperatively integrated into a functional unit within the W/S clade that enabled adaptation to iron-limited environments. This integrated fungal-bacterial circuit and its dynamic evolution determine the extant distribution of yeast enterobactin producers and cheaters.

Saccharomycotina yeasts defy long-standing macroecological patterns.

The Saccharomycotina yeasts ("yeasts" hereafter) are a fungal clade of scientific, economic, and medical significance. Yeasts are highly ecologically diverse, found across a broad range of environments in every biome and continent on earth; however, little is known about what rules govern the macroecology of yeast species and their range limits in the wild. Here, we trained machine learning models on 12,816 terrestrial occurrence records and 96 environmental variables to infer global distribution maps at ~1 km2 resolution for 186 yeast species (~15% of described species from 75% of orders) and to test environmental drivers of yeast biogeography and macroecology. We found that predicted yeast diversity hotspots occur in mixed montane forests in temperate climates. Diversity in vegetation type and topography were some of the greatest predictors of yeast species richness, suggesting that microhabitats and environmental clines are key to yeast diversity. We further found that range limits in yeasts are significantly influenced by carbon niche breadth and range overlap with other yeast species, with carbon specialists and species in high-diversity environments exhibiting reduced geographic ranges. Finally, yeasts contravene many long-standing macroecological principles, including the latitudinal diversity gradient, temperature-dependent species richness, and a positive relationship between latitude and range size (Rapoport's rule). These results unveil how the environment governs the global diversity and distribution of species in the yeast subphylum. These high-resolution models of yeast species distributions will facilitate the prediction of economically relevant and emerging pathogenic species under current and future climate scenarios.

Create, Analyze, and Visualize Phylogenomic Datasets Using PhyloFisher.

PhyloFisher is a software package written primarily in Python3 that can be used for the creation, analysis, and visualization of phylogenomic datasets that consist of protein sequences from eukaryotic organisms. Unlike many existing phylogenomic pipelines, PhyloFisher comes with a manually curated database of 240 protein-coding genes, a subset of a previous phylogenetic dataset sampled from 304 eukaryotic taxa. The software package can also utilize a user-created database of eukaryotic proteins, which may be more appropriate for shallow evolutionary questions. PhyloFisher is also equipped with a set of utilities to aid in running routine analyses, such as the prediction of alternative genetic codes, removal of genes and/or taxa based on occupancy/completeness of the dataset, testing for amino acid compositional heterogeneity among sequences, removal of heterotachious and/or fast-evolving sites, removal of fast-evolving taxa, supermatrix creation from randomly resampled genes, and supermatrix creation from nucleotide sequences. © 2024 Wiley Periodicals LLC. Basic Protocol 1: Constructing a phylogenomic dataset Basic Protocol 2: Performing phylogenomic analyses Support Protocol 1: Installing PhyloFisher Support Protocol 2: Creating a custom phylogenomic database.

Identification of miRNA858 long-loop precursors in seed plants.

MicroRNAs (miRNAs) are a class of nonprotein-coding short transcripts that provide a layer of post-transcriptional regulation essential to many plant biological processes. MiR858, which targets the transcripts of MYB transcription factors, can affect a range of secondary metabolic processes. Although miR858 and its 187-nt precursor have been well studied in Arabidopsis (Arabidopsis thaliana), a systematic investigation of miR858 precursors and their functions across plant species is lacking due to a problem in identifying the transcripts that generate this subclass. By re-evaluating the transcript of miR858 and relaxing the length cut-off for identifying hairpins, we found in kiwifruit (Actinidia chinensis) that miR858 has long-loop hairpins (1,100 to 2,100 nt), whose intervening sequences between miRNA generating complementary sites were longer than all previously reported miRNA hairpins. Importantly, these precursors of miR858 containing long-loop hairpins (termed MIR858L) are widespread in seed plants including Arabidopsis, varying between 350 and 5,500 nt. Moreover, we showed that MIR858L has a greater impact on proanthocyanidin and flavonol levels in both Arabidopsis and kiwifruit. We suggest that an active MIR858L-MYB regulatory module appeared in the transition of early land plants to large upright flowering plants, making a key contribution to plant secondary metabolism.

Functional and evolutionary integration of a fungal gene with a bacterial operon.

Siderophores are crucial for iron-scavenging in microorganisms. While many yeasts can uptake siderophores produced by other organisms, they are typically unable to synthesize siderophores themselves. In contrast, Wickerhamiella/Starmerella (W/S) clade yeasts gained the capacity to make the siderophore enterobactin following the remarkable horizontal acquisition of a bacterial operon enabling enterobactin synthesis. Yet, how these yeasts absorb the iron bound by enterobactin remains unresolved. Here, we demonstrate that Enb1 is the key enterobactin importer in the W/S-clade species Starmerella bombicola. Through phylogenomic analyses, we show that ENB1 is present in all W/S clade yeast species that retained the enterobactin biosynthetic genes. Conversely, it is absent in species that lost the ent genes, except for Starmerella stellata, making this species the only cheater in the W/S clade that can utilize enterobactin without producing it. Through phylogenetic analyses, we infer that ENB1 is a fungal gene that likely existed in the W/S clade prior to the acquisition of the ent genes and subsequently experienced multiple gene losses and duplications. Through phylogenetic topology tests, we show that ENB1 likely underwent horizontal gene transfer from an ancient W/S clade yeast to the order Saccharomycetales, which includes the model yeast Saccharomyces cerevisiae, followed by extensive secondary losses. Taken together, these results suggest that the fungal ENB1 and bacterial ent genes were cooperatively integrated into a functional unit within the W/S clade that enabled adaptation to iron-limited environments. This integrated fungal-bacterial circuit and its dynamic evolution determines the extant distribution of yeast enterobactin producers and cheaters.

Kinematic analysis of countermovement jump performance in response to immediate neuromuscular electrical stimulation.

The purpose of this study was to examine the effect of neuromuscular electrical stimulation (NMES) immediate intervention training on the countermovement jump (CMJ) height and to explore kinematic differences in the CMJ at each instant. A total of 15 male students who had never received electrical stimulation were randomly selected as the research participants. In the first test, the CMJ performance was completed with an all-out effort. The second experiment was best performed immediately to complete the CMJ operation after NMES for 30 min. Both experiments used a high-speed camera optical capture system to collect kinematic data. The results of this experiment revealed that after im-mediate NMES training, neuromuscular activation causes post-activation potentiation, which increases the height of the center of gravity of the CMJ and affects the angular velocity of the hip joint, the velocity and acceleration of the thigh and the shank and the velocity of the soles of the feet. The use of NMES interventional training based on the improvement of technical movements and physical exercises is recommended in the future.

Saccharomycotina yeasts defy longstanding macroecological patterns.

The Saccharomycotina yeasts ("yeasts" hereafter) are a fungal clade of scientific, economic, and medical significance. Yeasts are highly ecologically diverse, found across a broad range of environments in every biome and continent on earth1; however, little is known about what rules govern the macroecology of yeast species and their range limits in the wild2. Here, we trained machine learning models on 12,221 occurrence records and 96 environmental variables to infer global distribution maps for 186 yeast species (~15% of described species from 75% of orders) and to test environmental drivers of yeast biogeography and macroecology. We found that predicted yeast diversity hotspots occur in mixed montane forests in temperate climates. Diversity in vegetation type and topography were some of the greatest predictors of yeast species richness, suggesting that microhabitats and environmental clines are key to yeast diversification. We further found that range limits in yeasts are significantly influenced by carbon niche breadth and range overlap with other yeast species, with carbon specialists and species in high diversity environments exhibiting reduced geographic ranges. Finally, yeasts contravene many longstanding macroecological principles, including the latitudinal diversity gradient, temperature-dependent species richness, and latitude-dependent range size (Rapoport's rule). These results unveil how the environment governs the global diversity and distribution of species in the yeast subphylum. These high-resolution models of yeast species distributions will facilitate the prediction of economically relevant and emerging pathogenic species under current and future climate scenarios.

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.

Genomic and ecological factors shaping specialism and generalism across an entire subphylum.

Organisms exhibit extensive variation in ecological niche breadth, from very narrow (specialists) to very broad (generalists). Paradigms proposed to explain this variation either invoke trade-offs between performance efficiency and breadth or underlying intrinsic or extrinsic factors. We assembled genomic (1,154 yeast strains from 1,049 species), metabolic (quantitative measures of growth of 843 species in 24 conditions), and ecological (environmental ontology of 1,088 species) data from nearly all known species of the ancient fungal subphylum Saccharomycotina to examine niche breadth evolution. We found large interspecific differences in carbon breadth stem from intrinsic differences in genes encoding specific metabolic pathways but no evidence of trade-offs and a limited role of extrinsic ecological factors. These comprehensive data argue that intrinsic factors driving microbial niche breadth variation.

FoxO and rotund form a binding complex governing wing polyphenism in planthoppers.

Wing polyphenism is found in a variety of insects and offers an attractive model system for studying the evolutionary significance of dispersal. The Forkhead box O (FoxO) transcription factor (TF) acts as a wing-morph switch that directs wing buds developing into long-winged (LW) or short-winged morphs in wing-dimorphic planthoppers, yet the regulatory mechanism of the FoxO module remains elusive. Here, we identified the zinc finger TF rotund as a potential wing-morph regulator via transcriptomic analysis and phenotypic screening in the brown plathopper, Nilaparvata lugens. RNA interference-mediated knockdown of rotund antagonized the LW development derived from in the context of FoxO depletion or the activation of the insulin/insulin-like growth factor signaling cascade, reversing long wings into intermediate wings. In vitro binding assays indicated that rotund physically binds to FoxO to form the FoxO combinatorial code. These findings broaden our understanding of the complexity of transcriptional regulation governing wing polyphenism in insects.

Incongruence in the phylogenomics era.

Genome-scale data and the development of novel statistical phylogenetic approaches have greatly aided the reconstruction of a broad sketch of the tree of life and resolved many of its branches. However, incongruence - the inference of conflicting evolutionary histories - remains pervasive in phylogenomic data, hampering our ability to reconstruct and interpret the tree of life. Biological factors, such as incomplete lineage sorting, horizontal gene transfer, hybridization, introgression, recombination and convergent molecular evolution, can lead to gene phylogenies that differ from the species tree. In addition, analytical factors, including stochastic, systematic and treatment errors, can drive incongruence. Here, we review these factors, discuss methodological advances to identify and handle incongruence, and highlight avenues for future research.

How has horizontal gene transfer shaped the evolution of insect genomes?

As the most diverse group of animals on Earth, insects are key organisms in ecosystems. Horizontal gene transfer (HGT) refers to the transfer of genetic material between species by non-reproductive means. HGT is a major evolutionary force in prokaryotic genome evolution, but its importance in different eukaryotic groups, such as insects, has only recently begun to be understood. Genomic data from hundreds of insect species have enabled the detection of large numbers of HGT events and the elucidation of the functions of some of these foreign genes. Although quantification of the extent of HGT in insects broadens our understanding of its role in insect evolution, the scope of its influence and underlying mechanism(s) of its occurrence remain open questions for the field.

Contrasting modes of macro and microsynteny evolution in a eukaryotic subphylum.

Examination of the changes in order and arrangement of homologous genes is key for understanding the mechanisms of genome evolution in eukaryotes. Previous comparisons between eukaryotic genomes have revealed considerable conservation across species that diverged hundreds of millions of years ago (e.g., vertebrates,1,2,3 bilaterian animals,4,5 and filamentous fungi6). However, understanding how genome organization evolves within and between eukaryotic major lineages remains underexplored. We analyzed high-quality genomes of 120 representative budding yeast species (subphylum Saccharomycotina) spanning ∼400 million years of eukaryotic evolution to examine how their genome organization evolved and to compare it with the evolution of animal and plant genome organization.7 We found that the decay of both macrosynteny (the conservation of homologous chromosomes) and microsynteny (the conservation of local gene content and order) was strongly associated with evolutionary divergence across budding yeast major clades. However, although macrosynteny decayed very fast, within ∼100 million years, the microsynteny of many genes-especially genes in metabolic clusters (e.g., in the GAL gene cluster8)-was much more deeply conserved both within major clades and across the subphylum. We further found that when genomes with similar evolutionary divergence times were compared, budding yeasts had lower macrosynteny conservation than animals and filamentous fungi but higher conservation than angiosperms. In contrast, budding yeasts had levels of microsynteny conservation on par with mammals, whereas angiosperms exhibited very low conservation. Our results provide new insight into the tempo and mode of the evolution of gene and genome organization across an entire eukaryotic subphylum.

OrthoSNAP: A tree splitting and pruning algorithm for retrieving single-copy orthologs from gene family trees.

Molecular evolution studies, such as phylogenomic studies and genome-wide surveys of selection, often rely on gene families of single-copy orthologs (SC-OGs). Large gene families with multiple homologs in 1 or more species-a phenomenon observed among several important families of genes such as transporters and transcription factors-are often ignored because identifying and retrieving SC-OGs nested within them is challenging. To address this issue and increase the number of markers used in molecular evolution studies, we developed OrthoSNAP, a software that uses a phylogenetic framework to simultaneously split gene families into SC-OGs and prune species-specific inparalogs. We term SC-OGs identified by OrthoSNAP as SNAP-OGs because they are identified using a splitting and pruning procedure analogous to snapping branches on a tree. From 415,129 orthologous groups of genes inferred across 7 eukaryotic phylogenomic datasets, we identified 9,821 SC-OGs; using OrthoSNAP on the remaining 405,308 orthologous groups of genes, we identified an additional 10,704 SNAP-OGs. Comparison of SNAP-OGs and SC-OGs revealed that their phylogenetic information content was similar, even in complex datasets that contain a whole-genome duplication, complex patterns of duplication and loss, transcriptome data where each gene typically has multiple transcripts, and contentious branches in the tree of life. OrthoSNAP is useful for increasing the number of markers used in molecular evolution data matrices, a critical step for robustly inferring and exploring the tree of life.

HGT is widespread in insects and contributes to male courtship in lepidopterans.

Horizontal gene transfer (HGT) is an important evolutionary force shaping prokaryotic and eukaryotic genomes. HGT-acquired genes have been sporadically reported in insects, a lineage containing >50% of animals. We systematically examined HGT in 218 high-quality genomes of diverse insects and found that they acquired 1,410 genes exhibiting diverse functions, including many not previously reported, via 741 distinct transfers from non-metazoan donors. Lepidopterans had the highest average number of HGT-acquired genes. HGT-acquired genes containing introns exhibited substantially higher expression levels than genes lacking introns, suggesting that intron gains were likely involved in HGT adaptation. Lastly, we used the CRISPR-Cas9 system to edit the prevalent unreported gene LOC105383139, which was transferred into the last common ancestor of moths and butterflies. In diamondback moths, males lacking LOC105383139 courted females significantly less. We conclude that HGT has been a major contributor to insect adaptation.

Fusarium fruiting body microbiome member Pantoea agglomerans inhibits fungal pathogenesis by targeting lipid rafts.

Plant-pathogenic fungi form intimate interactions with their associated bacterial microbiota during their entire life cycle. However, little is known about the structure, functions and interaction mechanisms of bacterial communities associated with fungal fruiting bodies (perithecia). Here we examined the bacterial microbiome of perithecia formed by Fusarium graminearum, the major pathogenic fungus causing Fusarium head blight in cereals. A total of 111 shared bacterial taxa were identified in the microbiome of 65 perithecium samples collected from 13 geographic locations. Within a representative culture collection, 113 isolates exhibited antagonistic activity against F. graminearum, with Pantoea agglomerans ZJU23 being the most efficient in reducing fungal growth and infectivity. Herbicolin A was identified as the key antifungal compound secreted by ZJU23. Genetic and chemical approaches led to the discovery of its biosynthetic gene cluster. Herbicolin A showed potent in vitro and in planta efficacy towards various fungal pathogens and fungicide-resistant isolates, and exerted a fungus-specific mode of action by directly binding and disrupting ergosterol-containing lipid rafts. Furthermore, herbicolin A exhibited substantially higher activity (between 5- and 141-fold higher) against the human opportunistic fungal pathogens Aspergillus fumigatus and Candida albicans in comparison with the clinically used fungicides amphotericin B and fluconazole. Its mode of action, which is distinct from that of other antifungal drugs, and its efficacy make herbicolin A a promising antifungal drug to combat devastating fungal pathogens, both in agricultural and clinical settings.