AUTHOR=Wang Zheng , Kim Wonyong , Wang Yen-Wen , Yakubovich Elizabeta , Dong Caihong , Trail Frances , Townsend Jeffrey P. , Yarden Oded 

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

JOURNAL=Frontiers in Fungal Biology

VOLUME=Volume 4 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/fungal-biology/articles/10.3389/ffunb.2023.1214537

DOI=10.3389/ffunb.2023.1214537

ISSN=2673-6128

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 using classical and newer fungal models that empower study of diverse topics encompassing fungal biology and development. Technological advances have introduced the opportunity to obtain and mine large data sets. One such continuously growing data set encompasses the Sordariomycetes, which exhibit a richness of species, ecological diversity, economic importance, and profound research history of amenable models. Currently, 3574 species of this class have been sequenced, comprising nearly a third of the available ascomycete genomes. Among these genomes, multiple representatives of the model genera Fusarium, Neurospora, and Trichoderma are present. We examined recently published studies and data within the Sordariomycetes that contributed novel insights in fungal evolution via integrative analyses of the genetic, pathogenic and other biological characteristics. Some of these studies applied ancestral state analysis on gene expression among divergent lineages to infer regulatory network models, to identify key genetic elements in fungal sexual development, and to investigate the regulation of conidial germination and secondary metabolism. Such multi-species 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 biology driven by knowledge from a few model species. Rapidly accumulating information and expanding capabilities to perform systems biological analysis of Big Data are setting the stage for expanding the concepts of model systems from unitary taxonomic species/genera to become inclusive clusters of well-studied models that empower both the in-depth study of specific lineages and also investigations of trait diversity across lineages. The class Sordariomycetes, in particular, features abundant omics data and a large and active global research community. As such, the Sordariomycetes can form a core omics clade, and providing a blueprint for how we can expand our knowledge of evolution at the genomic scale in the exciting era of Big Data and artificial intelligence, serving as a reference for the future analysis of various taxonomic levels within the fungal kingdom.