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Updated: Jan 26, 2026

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions
Published on: March 5, 2022
Limitations of transcriptome-based prediction of pathogenicity genes in the plant pathogen Leptosphaeria maculans
Andrew S Urquhart1, Alexander Idnurm1
1School of BioSciences, 1929 Botany Building, the University of Melbourne, Parkville, VIC 3010, Australia.
Abstract:
Identification of pathogenicity determinants in Leptosphaeria maculans, a major cause of disease of oilseed crops, has been a focus of research for many years. A wealth of gene expression information from RNA sequencing promises to illuminate the mechanisms by which the fungus is able to cause blackleg disease. However, to date, no studies have tested the hypothesis that high gene transcript levels during infection correlate with importance to disease progression. In this study, we use CRISPR-Cas9 to disrupt 11 genes that are highly expressed during the early stages of disease and show that none of these genes are crucial for fungal pathogenicity on Brassica napus. This finding suggests that in order to understand the pathogenicity of this fungus more sophisticated techniques than simple expression analysis will need to be employed.
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