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Early Transcriptome Response of Trichoderma virens to Colonization of Maize Roots.
Taylor, James T; Wang, Ken-Der; Horwitz, Benjamin; Kolomiets, Michael; Kenerley, Charles M.
Afiliação
  • Taylor JT; Department of Plant Pathology and Microbiology, Texas A&M University, College Station, TX, United States.
  • Wang KD; Department of Plant Pathology and Microbiology, Texas A&M University, College Station, TX, United States.
  • Horwitz B; Department of Biology, Technion Israel Institute of Technology, Haifa, Israel.
  • Kolomiets M; Department of Plant Pathology and Microbiology, Texas A&M University, College Station, TX, United States.
  • Kenerley CM; Department of Plant Pathology and Microbiology, Texas A&M University, College Station, TX, United States.
Front Fungal Biol ; 2: 718557, 2021.
Article em En | MEDLINE | ID: mdl-37744095
Trichoderma virens is a well-known mycoparasitic fungal symbiont that is valued for its biocontrol capabilities. T. virens initiates a symbiotic relationship with a plant host through the colonization of its roots. To achieve colonization, the fungus must communicate with the host and evade its innate defenses. In this study, we explored the genes involved with the host communication and colonization process through transcriptomic profiling of the wild-type fungus and selected deletion mutants as they colonized maize roots. Transcriptome profiles of the T. virens colonization of maize roots over time revealed that 24 h post inoculation appeared to be a key time for plant-microbe communication, with many key gene categories, including signal transduction mechanisms and carbohydrate transport and metabolism, peaking in expression at this early colonization time point. The transcriptomic profiles of Sm1 and Sir1 deletion mutants in the presence of plants demonstrated that Sir1, rather than Sm1, appears to be the key regulator of the fungal response to maize, with 64% more unique differentially expressed genes compared to Sm1. Additionally, we developed a novel algorithm utilizing gene clustering and coexpression network analyses to select potential colonization-related gene targets for characterization. About 40% of the genes identified by the algorithm would have been missed using previous methods for selecting gene targets.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2021 Tipo de documento: Article