Comparison of non-subjective relative fungal biomass measurements to quantify the Leptosphaeria maculans-Brassica napus interaction.

Abstract

Background Blackleg disease, caused by the fungal pathogen Leptosphaeria maculans, is a serious threat to canola (Brassica napus) production worldwide. Quantitative resistance to this disease is a highly desirable trait but is difficult to precisely phenotype. Visual scores can be subjective and are prone to assessor bias. Methods to assess variation in quantitative resistance more accurately were developed based on quantifying in planta fungal biomass, including the Wheat Germ Agglutinin Chitin Assay (WAC), qPCR and ddPCR assays. Results Disease assays were conducted by inoculating a range of canola cultivars with L. maculans isolates in glasshouse experiments and assessing fungal biomass in cotyledons, petioles and stem tissue harvested at different timepoints post-inoculation. PCR and WAC assay results were well correlated, repeatable across experiments and host tissues, and able to differentiate fungal biomass in different host-isolate treatments. In addition, the ddPCR assay was shown to differentiate between L. maculans isolates. Conclusions The ddPCR assay is more sensitive in detecting pathogens and more adaptable to high-throughput methods by using robotic systems than the WAC assay. Overall, these methods proved accurate and non-subjective, providing alternatives to visual assessments to quantify the L. maculans-B. napus interaction in all plant tissues throughout the progression of the disease in seedlings and mature plants and have potential for fine-scale blackleg resistance phenotyping in canola.

Plant phenotyping relevance

カノーラ黒脚病に対する量的抵抗性の表現型評価を目的に、WAC、qPCR、ddPCRによる菌体量測定法を比較・検証しており、病害状態の非主観的な表現型取得が中心である。

Code and data availability

The paper's phenotype measurements (WAC, qPCR, ddPCR fungal biomass data) are not deposited publicly; the authors state the datasets are available from the corresponding author on request. No author analysis code, images, or trained models are publicly linked. The only URLs in the text (Primer3Plus, AutoDimer) are for,

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