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应用贝叶斯有序动物模型估计桃[(L.)Batsch]后代对(G. Winter)蜂蜜抗性的育种值。

Application of a Bayesian ordinal animal model for the estimation of breeding values for the resistance to (G.Winter) Honey in progenies of peach [ (L.) Batsch].

作者信息

Fresnedo-Ramírez Jonathan, Famula Thomas R, Gradziel Thomas M

机构信息

Department of Plant Sciences, University of California, 1 Shields Avenue, Davis, CA 95616, USA.

Department of Animal Science, University of California, 1 Shields Avenue, Davis, CA 95616, USA.

出版信息

Breed Sci. 2017 Mar;67(2):110-122. doi: 10.1270/jsbbs.16027. Epub 2017 Feb 2.

Abstract

Fruit brown rot caused by spp. is the most important fungal disease of stone fruits worldwide. Several phenotyping protocols to accurately characterize and evaluate brown rot infection have been proposed; however, the outcomes from those studies have not led to consistent advances in resistance breeding programs. Breeding for disease resistance is one of the most challenging objectives for crop improvement because disease expression is tetrahedral: it is simultaneously influenced by agent, host, environment, and human management. The present study presents a strategy based on Bayesian inference to analyze a peach breeding progeny for resistance to brown rot, evaluated using a polytomous ordinal scale. A pedigree containing two sources of resistance, one from peach and the other from almond, several commercial cultivars, and two segregating populations were analyzed to estimate the narrow-sense heritability ( ) and breeding values (EBVs) for brown rot resistance in progenies. Results show promise for genetic improvement of disease resistance and other traits characterized by strong environmental interactions.

摘要

由**[病原菌名称未给出]引起的核果褐腐病是全球核果类最重要的真菌病害。已经提出了几种用于准确表征和评估褐腐病感染情况的表型分析方案;然而,这些研究的结果并未在抗病育种计划中带来一致的进展。抗病育种是作物改良中最具挑战性的目标之一,因为病害表现具有多面性:它同时受到病原菌、寄主、环境和人为管理的影响。本研究提出了一种基于贝叶斯推理的策略,用于分析桃育种后代对褐腐病的抗性,并使用多分类有序量表进行评估。分析了一个包含两个抗性来源(一个来自桃,另一个来自杏仁)、几个商业品种和两个分离群体的系谱,以估计后代中褐腐病抗性的狭义遗传力([遗传力符号未给出]**)和育种值(EBV)。结果显示了抗病性以及其他受强烈环境相互作用影响的性状遗传改良的前景。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c69a/5445959/5b313bfbe26e/67_16027_1.jpg

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