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首页> 外文期刊>Genetics and Molecular Research >Bayesian inference to study genetic control of resistance to gray leaf spot in maize
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Bayesian inference to study genetic control of resistance to gray leaf spot in maize

机译:贝叶斯推断研究玉米抗灰斑病的遗传调控

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Gray leaf spot (GLS) is a major maize disease in Brazil that significantly affects grain production. We used Bayesian inference to investigate the nature and magnitude of gene effects related to GLS resistance by evaluation of contrasting lines and segregating populations. The experiment was arranged in a randomized block design with three replications and the mean values were analyzed using a Bayesian shrinkage approach. Additive-dominant and epistatic effects and their variances were adjusted in an over-parametrized model. Bayesian shrinkage analysis showed to be an excellent approach to handle complex models in the study of genetic control in GLS, since this approach allows to handle overparametrized models (main and epistatic effects) without using model-selection methods. Genetic control of GLS resistance was predominantly additive, with insignificant influence of dominance and epistasis effects.
机译:灰叶斑病(GLS)是巴西的一种主要玉米病,对谷物产量产生重大影响。我们使用贝叶斯推论通过评估对比系和隔离种群来研究与GLS抗性相关的基因效应的性质和大小。该实验以随机区组设计的形式进行,重复3次,并使用贝叶斯收缩法分析平均值。在超参数化模型中调整了加性和上位性效应及其方差。在GLS遗传控制研究中,贝叶斯收缩分析是处理复杂模型的极好方法,因为这种方法无需使用模型选择方法即可处理过度参数化的模型(主效应和上位效应)。 GLS耐药性的遗传控制主要是加性的,对显性和上位性影响不显着。

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