Improved bivariate analysis of canola survivability against blackleg disease.

IF 4.2 1区 农林科学 Q1 AGRONOMY
Timothy Thavarajah, James Walter, Julian Taylor
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引用次数: 0

Abstract

Key message: 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.

油菜籽抗黑腿病存活率的改进双变量分析。
利用基于标记的基因组信息、灵活的残差模型和一种新的选择方法对油菜籽抗黑腿病的生存能力进行双变量分析,可以提高油菜抗黑腿病的遗传增益。油菜(Brassica napus)是世界范围内广泛种植的重要油料作物。它受到病原体maculans钩端绦虫(俗称黑腿)的有害影响,每年在澳大利亚造成高达15%的产量损失。控制这种疾病最有效的方法是培育抗病品种。筛选黑腿病抗性的基因型通常涉及获得黑腿病的存活率(来自植物出苗期和成熟期的数量)并进行单变量分析。更全面的方法包括双变量分析,以解释植物数量之间的相关性。在这项研究中,我们整理了一个来自商业育种计划中的疾病苗圃的新数据集,其中包括在澳大利亚四个地点进行了3年多的相关基因型评估,并概述了一种创新的双变量分析方法。研究目标是:(1)整合基因组标记信息;(2)采用更灵活的残差模型;(3)根据双变量回归,提出一种新的选择方法,即对黑腿病的反应性。性状间的遗传相关性在0.49 ~ 0.91之间。基因组标记的加入对成熟计数的影响大于羽化计数。此外,更灵活的残差模型在5个实验中显著改善了模型拟合。使用响应性作为选择措施,产生了与存活率的单变量分析相当的排名,并对基因型进行了一些重新排名,这反映了通过双变量方法改进的分析。最终,这些结果证明了历史分析的改进,从而鼓励在油菜育种计划中采用它们来加速黑腿抗性的遗传增益。
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来源期刊
CiteScore
9.60
自引率
7.40%
发文量
241
审稿时长
2.3 months
期刊介绍: Theoretical and Applied Genetics publishes original research and review articles in all key areas of modern plant genetics, plant genomics and plant biotechnology. All work needs to have a clear genetic component and significant impact on plant breeding. Theoretical considerations are only accepted in combination with new experimental data and/or if they indicate a relevant application in plant genetics or breeding. Emphasizing the practical, the journal focuses on research into leading crop plants and articles presenting innovative approaches.
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