Title: The Sordariomycetes: an expanding resource with Big Data for mining in evolutionary genomics and transcriptomics
Advances in genomics and transcriptomics accompanying the rapid accumulation of omics data have provided new tools that have transformed and expanded the traditional concepts of model fungi. Evolutionary genomics and transcriptomics have flourished with the use of classical and newer fungal models that facilitate the study of diverse topics encompassing fungal biology and development. Technological advances have also created the opportunity to obtain and mine large datasets. One such continuously growing dataset is that of the Sordariomycetes, which exhibit a richness of species, ecological diversity, economic importance, and a profound research history on amenable models. Currently, 3,574 species of this class have been sequenced, comprising nearly one-third of the available ascomycete genomes. Among these genomes, multiple representatives of the model genera Fusarium , Neurospora , and Trichoderma are present. In this review, we examine recently published studies and data on the Sordariomycetes that have contributed novel insights to the field of fungal evolution via integrative analyses of the genetic, pathogenic, and other biological characteristics of the fungi. Some of these studies applied ancestral state analysis of gene expression among divergent lineages to infer regulatory network models, identify key genetic elements in fungal sexual development, and investigate the regulation of conidial germination and secondary metabolism. Such multispecies investigations address challenges in the study of fungal evolutionary genomics derived from studies that are often based on limited model genomes and that primarily focus on the aspects of biology driven by knowledge drawn from a few model species. Rapidly accumulating information and expanding capabilities for systems biological analysis of Big Data are setting the stage for the expansion of the concept of model systems from unitary taxonomic species/genera to inclusive clusters of well-studied models that can facilitate both the in-depth study of specific lineages and also investigation of trait diversity across lineages. The Sordariomycetes class, in particular, offers abundant omics data and a large and active global research community. As such, the Sordariomycetes can form a core omics clade, providing a blueprint for the expansion of our knowledge of evolution at the genomic scale in the exciting era of Big Data and artificial intelligence, and serving as a reference for the future analysis of different taxonomic levels within the fungal kingdom. more »« less
Steenwyk, Jacob L; Balamurugan, Charu; Raja, Huzefa A; Gonçalves, Carla; Li, Ningxiao; Martin, Frank; Berman, Judith; Oberlies, Nicholas H; Gibbons, John G; Goldman, Gustavo H; et al(
, Microbiology Spectrum)
Alanio, Alexandre
(Ed.)
ABSTRACT
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 genusAspergillus. To do so, we generated a novel set of 1,362 high-quality molecular markers specific forAspergillusand 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.
IMPORTANCE
Identification 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 genusAspergillus. Our evolutionary genomic analyses revealed that nearly 8% of publicly availableAspergillusgenomes 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 kingdom Fungi comprises species that inhabit nearly all ecosystems. Fungi exist as both free-living and symbiotic unicellular and multicellular organisms with diverse morphologies. The genomes of fungi encode genes that enable them to thrive in diverse environments, invade plant and animal cells, and participate in nutrient cycling in terrestrial and aquatic ecosystems. The continuously expanding databases of fungal genome sequences have been generated by individual and large-scale efforts such as Génolevures, Broad Institute's Fungal Genome Initiative, and the 1000 Fungal Genomes Project (http://1000.fungalgenomes.org). These efforts have produced a catalog of fungal genes and genomic organization. The genomic datasets can be utilized to better understand how fungi have adapted to their lifestyles and ecological niches. Large datasets of fungal genomic and transcriptomic data have enabled the use of novel methodologies and improved the study of fungal evolution from a molecular sequence perspective. Combined with microscopes, petri dishes, and woodland forays, genome sequencing supports bioinformatics and comparative genomics approaches as important tools in the study of the biology and evolution of fungi.
During surveys in central Florida of the zombie-ant fungus Ophiocordyceps camponoti-floridani , which manipulates the behavior of the carpenter ant Camponotus floridanus , two distinct fungal morphotypes were discovered associated with and purportedly parasitic on O. camponoti-floridani . Based on a combination of unique morphology, ecology and phylogenetic placement, we discovered that these morphotypes comprise two novel lineages of fungi. Here, we propose two new genera, Niveomyces and Torrubiellomyces , each including a single species within the families Cordycipitaceae and Ophiocordycipitaceae , respectively. We generated de novo draft genomes for both new species and performed morphological and multi-loci phylogenetic analyses. The macro-morphology and incidence of both new species, Niveomyces coronatus and Torrubiellomyces zombiae , suggest that these fungi are mycoparasites since their growth is observed exclusively on O. camponoti-floridani mycelium, stalks and ascomata, causing evident degradation of their fungal hosts. This work provides a starting point for more studies into fungal interactions between mycopathogens and entomopathogens, which have the potential to contribute towards efforts to battle the global rise of plant and animal mycoses.
Fungal taxonomy and ecology have been revolutionized by the application of molecular methods and both have increasing connections to genomics and functional biology. However, data streams from traditional specimen- and culture-based systematics are not yet fully integrated with those from metagenomic and metatranscriptomic studies, which limits understanding of the taxonomic diversity and metabolic properties of fungal communities. This article reviews current resources, needs, and opportunities for sequence-based classification and identification (SBCI) in fungi as well as related efforts in prokaryotes. To realize the full potential of fungal SBCI it will be necessary to make advances in multiple areas. Improvements in sequencing methods, including long-read and single-cell technologies, will empower fungal molecular ecologists to look beyond ITS and current shotgun metagenomics approaches. Data quality and accessibility will be enhanced by attention to data and metadata standards and rigorous enforcement of policies for deposition of data and workflows. Taxonomic communities will need to develop best practices for molecular characterization in their focal clades, while also contributing to globally useful datasets including ITS. Changes to nomenclatural rules are needed to enable validPUBLICation of sequence-based taxon descriptions. Finally, cultural shifts are necessary to promote adoption of SBCI and to accord professional credit to individuals who contribute to community resources.
Wang, Yan; Chang, Ying; Ortañez, Jericho; Peña, Jesús F; Carter-House, Derreck; Reynolds, Nicole K; Smith, Matthew E; Benny, Gerald; Mondo, Stephen J; Salamov, Asaf; et al(
, Genome Biology and Evolution)
Ma, Li-Jun
(Ed.)
Abstract Fungi have evolved over millions of years and their species diversity is predicted to be the second largest on the earth. Fungi have cross-kingdom interactions with many organisms that have mutually shaped their evolutionary trajectories. Zygomycete fungi hold a pivotal position in the fungal tree of life and provide important perspectives on the early evolution of fungi from aquatic to terrestrial environments. Phylogenomic analyses have found that zygomycete fungi diversified into two separate clades, the Mucoromycota which are frequently associated with plants and Zoopagomycota that are commonly animal-associated fungi. Genetic elements that contributed to the fitness and divergence of these lineages may have been shaped by the varied interactions these fungi have had with plants, animals, bacteria, and other microbes. To investigate this, we performed comparative genomic analyses of the two clades of zygomycetes in the context of Kingdom Fungi, benefiting from our generation of a new collection of zygomycete genomes, including nine produced for this study. We identified lineage-specific genomic content that may contribute to the disparate biology observed in these zygomycetes. Our findings include the discovery of undescribed diversity in CotH, a Mucormycosis pathogenicity factor, which was found in a broad set of zygomycetes. Reconciliation analysis identified multiple duplication events and an expansion of CotH copies throughout the Mucoromycotina, Mortierellomycotina, Neocallimastigomycota, and Basidiobolus lineages. A kingdom-level phylogenomic analysis also identified new evolutionary relationships within the subphyla of Mucoromycota and Zoopagomycota, including supporting the sister-clade relationship between Glomeromycotina and Mortierellomycotina and the placement of Basidiobolus as sister to other Zoopagomycota lineages.
Wang, Zheng, Kim, Wonyong, Wang, Yen-Wen, Yakubovich, Elizabeta, Dong, Caihong, Trail, Frances, Townsend, Jeffrey P., and Yarden, Oded. The Sordariomycetes: an expanding resource with Big Data for mining in evolutionary genomics and transcriptomics. Retrieved from https://par.nsf.gov/biblio/10441240. Frontiers in Fungal Biology 4. Web. doi:10.3389/ffunb.2023.1214537.
Wang, Zheng, Kim, Wonyong, Wang, Yen-Wen, Yakubovich, Elizabeta, Dong, Caihong, Trail, Frances, Townsend, Jeffrey P., & Yarden, Oded. The Sordariomycetes: an expanding resource with Big Data for mining in evolutionary genomics and transcriptomics. Frontiers in Fungal Biology, 4 (). Retrieved from https://par.nsf.gov/biblio/10441240. https://doi.org/10.3389/ffunb.2023.1214537
Wang, Zheng, Kim, Wonyong, Wang, Yen-Wen, Yakubovich, Elizabeta, Dong, Caihong, Trail, Frances, Townsend, Jeffrey P., and Yarden, Oded.
"The Sordariomycetes: an expanding resource with Big Data for mining in evolutionary genomics and transcriptomics". Frontiers in Fungal Biology 4 (). Country unknown/Code not available. https://doi.org/10.3389/ffunb.2023.1214537.https://par.nsf.gov/biblio/10441240.
@article{osti_10441240,
place = {Country unknown/Code not available},
title = {The Sordariomycetes: an expanding resource with Big Data for mining in evolutionary genomics and transcriptomics},
url = {https://par.nsf.gov/biblio/10441240},
DOI = {10.3389/ffunb.2023.1214537},
abstractNote = {Advances in genomics and transcriptomics accompanying the rapid accumulation of omics data have provided new tools that have transformed and expanded the traditional concepts of model fungi. Evolutionary genomics and transcriptomics have flourished with the use of classical and newer fungal models that facilitate the study of diverse topics encompassing fungal biology and development. Technological advances have also created the opportunity to obtain and mine large datasets. One such continuously growing dataset is that of the Sordariomycetes, which exhibit a richness of species, ecological diversity, economic importance, and a profound research history on amenable models. Currently, 3,574 species of this class have been sequenced, comprising nearly one-third of the available ascomycete genomes. Among these genomes, multiple representatives of the model genera Fusarium , Neurospora , and Trichoderma are present. In this review, we examine recently published studies and data on the Sordariomycetes that have contributed novel insights to the field of fungal evolution via integrative analyses of the genetic, pathogenic, and other biological characteristics of the fungi. Some of these studies applied ancestral state analysis of gene expression among divergent lineages to infer regulatory network models, identify key genetic elements in fungal sexual development, and investigate the regulation of conidial germination and secondary metabolism. Such multispecies investigations address challenges in the study of fungal evolutionary genomics derived from studies that are often based on limited model genomes and that primarily focus on the aspects of biology driven by knowledge drawn from a few model species. Rapidly accumulating information and expanding capabilities for systems biological analysis of Big Data are setting the stage for the expansion of the concept of model systems from unitary taxonomic species/genera to inclusive clusters of well-studied models that can facilitate both the in-depth study of specific lineages and also investigation of trait diversity across lineages. The Sordariomycetes class, in particular, offers abundant omics data and a large and active global research community. As such, the Sordariomycetes can form a core omics clade, providing a blueprint for the expansion of our knowledge of evolution at the genomic scale in the exciting era of Big Data and artificial intelligence, and serving as a reference for the future analysis of different taxonomic levels within the fungal kingdom.},
journal = {Frontiers in Fungal Biology},
volume = {4},
author = {Wang, Zheng and Kim, Wonyong and Wang, Yen-Wen and Yakubovich, Elizabeta and Dong, Caihong and Trail, Frances and Townsend, Jeffrey P. and Yarden, Oded},
}
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