Molecular Basis of Mycoparasitic Performance: Genomic and Transcriptomic Comparison of Contrasting Trichoderma atroviride Strains

Authors

Bremand, E., Bastide, F., Colou, J., Denance, N., Boisard, S., Ruiz, N., Bertrand, S., Marchi, M., Verdier, J., Guillemette, T.

Abstract

Trichoderma species are widely used as biological control agents due to their ability to parasitize plant pathogens. However, substantial variability in mycoparasitic performance exists among strains, even within the same species, and the underlying molecular mechanisms remain poorly understood. Here, we performed comparative genomic and transcriptomic analyses of six Trichoderma atroviride strains exhibiting contrasting mycoparasitic performance (weakly or highly parasitic; WP or HP) against Alternaria brassicicola, Rhizoctonia solani, and Globisporangium ultimum. Comparative genomics revealed limited strain-specific differences, mainly restricted to NLR (NOD-like receptor) repertoires, with certain NLR-coding genes absent from WP strain genomes compared to HP strains, while overall genomic variation remained low. In contrast, transcriptomic analyses revealed strong differences in gene expression dynamics between HP and WP strains. Co-expression network analysis identified two modules associated with mycoparasitic performance. The first was specifically induced in response to pathogen contact and was enriched in genes encoding cell wall-degrading enzymes, with stronger expression in HP strains. The second module was more broadly overexpressed in HP strains across all conditions and included genes involved in detoxification and defense-related pathways. In addition, this module encompassed genes involved in specialized metabolite biosynthesis and effector-like protein secretion, with WP and HP strains differentially expressing distinct gene subsets within these categories. Together, these results provide a comprehensive framework for identifying the molecular drivers of mycoparasitic performance in T. atroviride. This study deepens our understanding of the functional diversity within the species and establishes a robust foundation for the future development of molecular markers to predict strain efficiency.

Preprint server: bioRxiv
The authors list and abstract were imported from bioRxiv on 27 Jun 2026.

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