The Sordariomycetes: an expanding resource with Big Data for mining in evolutionary genomics and transcriptomics

Front Fungal Biol. 2023 Jun 30:4:1214537. doi: 10.3389/ffunb.2023.1214537. eCollection 2023.

Abstract

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.

Keywords: Big Data; Fusarium; Neurospora; Sordariomycetes; Trichoderma; evolution; genomics; transcriptomics.

Publication types

  • Review

Grants and funding

The work of ZW, Y-WW, and JT was supported by funding awarded to JT by the National Institutes of Health R01, grant AI146584, and by the National Science Foundation, grant IOS 1457044; the work of EY and OY was supported by funding award BSF-2018712 to OY. The work of CD was supported by the National Natural Science Foundation of China (32272786 and 31872163). FT was supported by the National Institutes of Health, R01 grant AI146584, and the Michigan State University AgBioResearch. The work of WK and FT was supported by the National Science Foundation, IOS 1456482, awarded to FT. WK was partly supported by the Basic Science Research Program through the National Research Foundation of Korea, funded by the Ministry of Education (2019R1I1A1A01057502).