Identification and Diagnosis of Wheat Blast

Kashyap, Prem Lal; Kumar, Sudheer; Gopal, K. Raja; Mahapatra, Sunita; Hembram, Satyajit; Singh, Gyanendra Pratap

doi:10.1201/9780429470554-3

Cited by 1 publication

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“…grisea , the causal agent of rice, was sequenced in 2005 ( Dean et al., 2005 ). Rice blast causes significant economic loss: worldwide, enough rice to feed tens of millions of people is destroyed by rice blast every year ( Kumar et al., 2020 ). Closely related to M. grisea , M. oryzae attacks wheat, causing wheat blast, an emergent fungal disease that probably evolved through a series of “host jumps” and that possesses core chromosomes and mini-chromosomes with distinct evolutionary histories ( Hossain, 2022 ).…”

Section: The Need For the Evolutionary Integration Of Multiple Modelsmentioning

confidence: 99%

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

Wang

Kim

Wang

et al. 2023

Front. Fungal Biol.

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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.

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Section: The Need For the Evolutionary Integration Of Multiple Modelsmentioning

confidence: 99%