Improved bivariate analysis of canola survivability against blackleg disease

The bivariate analysis of canola survivability against blackleg disease with marker-based genomic information, a flexible residual variance model, and a novel selection measure can improve genetic gain for blackleg resistance. Canola (Brassica napus) is an important oilseed crop grown extensively worldwide. It is deleteriously affected by the pathogen Leptosphaeria maculans, commonly known as blackleg, causing up to 15% yield loss in Australia annually. The most effective way to manage this disease is by growing resistant varieties. Screening genotypes for blackleg resistance has typically involved deriving percentage survivability against blackleg (from plant counts at emergence and maturity) and conducting a univariate analysis. More comprehensive approaches have involved a bivariate analysis that accounts for the correlation between plant counts. In this research, we have collated a new dataset from disease nurseries within a commercial breeding programme, comprised of related genotypes evaluated over 3 years at four locations across Australia, and outlined an innovative bivariate analysis approach. The research objectives were to (1) incorporate genomic marker information; (2) apply a more flexible residual model; and (3) develop a novel selection measure, responsiveness to blackleg disease, from the bivariate regression. Moderate to strong genetic correlations were found between traits, ranging between 0.49 and 0.91. The incorporation of genomic markers benefitted the maturity count more than emergence count. Furthermore, the more flexible residual model significantly improved model fit in five experiments. Using responsiveness as a selection measure produced comparable rankings with the univariate analysis of per cent survivability, with some re-ranking of genotypes which reflects the improved analysis through the bivariate approach. Ultimately, these results demonstrate an improvement over historic analyses, thus encouraging their adoption in canola breeding programmes to accelerate genetic gain for blackleg resistance.

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Publication Details

Journal
Theoretical and Applied Genetics
Published
2025-08-22
DOI
https://doi.org/10.1007/s00122-025-04993-x
Primary Topic
Genetics and Plant Breeding
Type
article
Field-Weighted Citation Impact
0.00

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article

Improved bivariate analysis of canola survivability against blackleg disease

James Walter, Julian Taylor, Timothy Thavarajah
Theoretical and Applied Genetics
Genetics and Plant Breeding
article

Improved bivariate analysis of canola survivability against blackleg disease

James Walter, Julian Taylor, Timothy Thavarajah
article en

Abstract

The bivariate analysis of canola survivability against blackleg disease with marker-based genomic information, a flexible residual variance model, and a novel selection measure can improve genetic gain for blackleg resistance. Canola (Brassica napus) is an important oilseed crop grown extensively worldwide. It is deleteriously affected by the pathogen Leptosphaeria maculans, commonly known as blackleg, causing up to 15% yield loss in Australia annually. The most effective way to manage this disease is by growing resistant varieties. Screening genotypes for blackleg resistance has typically involved deriving percentage survivability against blackleg (from plant counts at emergence and maturity) and conducting a univariate analysis. More comprehensive approaches have involved a bivariate analysis that accounts for the correlation between plant counts. In this research, we have collated a new dataset from disease nurseries within a commercial breeding programme, comprised of related genotypes evaluated over 3 years at four locations across Australia, and outlined an innovative bivariate analysis approach. The research objectives were to (1) incorporate genomic marker information; (2) apply a more flexible residual model; and (3) develop a novel selection measure, responsiveness to blackleg disease, from the bivariate regression. Moderate to strong genetic correlations were found between traits, ranging between 0.49 and 0.91. The incorporation of genomic markers benefitted the maturity count more than emergence count. Furthermore, the more flexible residual model significantly improved model fit in five experiments. Using responsiveness as a selection measure produced comparable rankings with the univariate analysis of per cent survivability, with some re-ranking of genotypes which reflects the improved analysis through the bivariate approach. Ultimately, these results demonstrate an improvement over historic analyses, thus encouraging their adoption in canola breeding programmes to accelerate genetic gain for blackleg resistance.

Theoretical and Applied GeneticsVol. 138(9)
EY Technologies (United States) (US), The University of Adelaide (AU), Australian Wine Research Institute (AU)
University of Adelaide
Openalex Percentile: Top 84%
Genetics and Plant Breeding
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