Abstract
BACKGROUND: Fungicide resistance poses a significant challenge to plant disease management and influences the evolutionary dynamics of fungal pathogens. Besides being important phytopathogens, Monilinia species have become a model for discovering many fundamental questions related to fungal pathosystems. In this study, DMI-propiconazole sensitivity was investigated in view of transposable element (TE) dynamics in M. fructicola and M. laxa. RESULTS: Propiconazole-sensitivity of 109 M. fructicola and 20 M. laxa isolates from different regions of Türkiye was assessed. Comprehensive TE identification within the species revealed that Class I elements were predominant, and TEs constituted approximately 9% of the genome for both M. fructicola and M. laxa, with a total of 15,327 and 10,710 TEs, respectively. An experimental evolution plan was developed for Monilinia that allows observing phenotypic and genotypic changes over successive generations under controlled selection pressures. Dynamic changes in TE content were discovered throughout the experimental evolution of M. fructicola under propiconazole pressure. With a net change of 187 TEs, the evolved strain showed an expansion of TE sequences, whereas different TE classes displayed diverse patterns of increase/decrease. Additionally, the presence of a nested TE upstream of the CYP51 gene was observed in less-sensitive M. fructicola isolates but absent in highly-sensitive ones. Gene expressions of CYP51 differed significantly between TE-containing and TE-lacking isolates, strongly supporting the contribution of this TE to fungicide resistance. CONCLUSION: This study establishes a critical link between TEs and DMI fungicide resistance by associating a nested TE with reduced sensitivity to propiconazole. We introduce an innovative experimental evolution framework for studying genomic changes under selective pressure and provide a comprehensive characterization of Monilinia TEs. These findings significantly advance our understanding of molecular resistance mechanisms in fungal pathogens, offering insights for more effective disease management.