Thavarajah Timothy, Walter James, Taylor Julian
School of Agriculture, Food and Wine, The University of Adelaide, Waite Campus, Glen Osmond, SA, 5064, Australia.
Australian Grain Technologies Pty Ltd, 20 Leitch Road, Roseworthy, SA, 5371, Australia.
Theor Appl Genet. 2025 Aug 22;138(9):225. doi: 10.1007/s00122-025-04993-x.
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.
利用基于标记的基因组信息、灵活的残差方差模型和一种新颖的选择指标,对油菜对黑胫病的存活能力进行双变量分析,可提高黑胫病抗性的遗传增益。油菜(甘蓝型油菜)是一种在全球广泛种植的重要油料作物。它受到病原菌大茎点菌(俗称黑胫病)的有害影响,在澳大利亚每年造成高达15%的产量损失。控制这种病害最有效的方法是种植抗病品种。筛选黑胫病抗性基因型通常包括计算油菜对黑胫病的存活百分比(根据出苗期和成熟期的植株数量)并进行单变量分析。更全面的方法涉及考虑植株数量之间相关性的双变量分析。在本研究中,我们整理了一个来自商业育种项目中病害苗圃的新数据集,该数据集由在澳大利亚四个地点经过3年评估的相关基因型组成,并概述了一种创新的双变量分析方法。研究目标是:(1)纳入基因组标记信息;(2)应用更灵活的残差模型;(3)从双变量回归中开发一种新颖的选择指标——对黑胫病的反应性。在各性状之间发现了中度到高度的遗传相关性,范围在0.49至0.91之间。纳入基因组标记对成熟期的植株数量比对出苗期的植株数量更有益。此外,更灵活的残差模型在五个实验中显著改善了模型拟合度。使用反应性作为选择指标产生的排名与存活百分比的单变量分析相当,一些基因型的排名有所重新调整,这反映了通过双变量方法进行的改进分析。最终,这些结果表明相较于历史分析有了改进,从而鼓励在油菜育种项目中采用这些方法,以加速黑胫病抗性的遗传增益。