Integrating Host-Pathogen Genomics to Enhance Wheat Resistance Against Septoria Tritici Blotch

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Zymoseptoria tritici, the causal agent of Septoria tritici Blotch (STB), is one of the most devastating diseases of wheat, causing notable yield losses in temperate climate countries. Traditional management strategies, such as synthetic fungicide application and breeding for qualitative traits, are becoming less effective every year. Breeding for quantitative resistance via Quantitative Trait Loci (QTL) is crucial to achieve this goal. In this study, we evaluated 119 isolates of Z. tritici and their interaction with 200 durum wheat accessions. Genome-Wide Association Study (GWAS) on Whole Genome Sequencing (WGS) data from the pathogen identified 4 markers on chromosome 1, 2, 8 and 9 significantly associated with pycnidia production. The markers were found in exonic regions of 7 candidate genes. We also tested the accuracyof Genomic Prediction models including both wheat and pathogen marker information. Predictions were strongly influenced by the inoculated isolates but no significant improvement was observed compared to existing models using only wheat or pathogen genotypic information.

​Zymoseptoria tritici, the causal agent of Septoria tritici Blotch (STB), is one of the most devastating diseases of wheat, causing notable yield losses in temperate climate countries. Traditional management strategies, such as synthetic fungicide application and breeding for qualitative traits, are becoming less effective every year. Breeding for quantitative resistance via Quantitative Trait Loci (QTL) is crucial to achieve this goal. In this study, we evaluated 119 isolates of Z. tritici and their interaction with 200 durum wheat accessions. Genome-Wide Association Study (GWAS) on Whole Genome Sequencing (WGS) data from the pathogen identified 4 markers on chromosome 1, 2, 8 and 9 significantly associated with pycnidia production. The markers were found in exonic regions of 7 candidate genes. We also tested the accuracyof Genomic Prediction models including both wheat and pathogen marker information. Predictions were strongly influenced by the inoculated isolates but no significant improvement was observed compared to existing models using only wheat or pathogen genotypic information. Read More