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Dominance effects estimation of TLR4 and CACNA2D1 genes for health and production traits using logistic regression

机译:使用Logistic回归估算TLR4和CACNA2D1基因的估算逻辑回归

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摘要

Knowledge of nonadditive variance and genetic effects can be helpful in explaining the total genetic variation for most of the traits. The objective of this study was to estimate dominance effects of several single-nucleotide polymorphism (SNP) genotypes for the production traits and clinical mastitis residual (CMR), in Holstein dairy cattle in a case-control study. Records of 305 days lactation were obtained for production traits and CMR. Animals were selected based on extreme values for CMR from mixed model analyses. Samples were genotyped for four SNP-single genotypes and their associations with production traits (breeding values for protein and fat yield, and protein and fat percentage) were estimated by applying logistic regression analyses. Calculation of contrast between both homozygous and heterozygous genotypes permitted to estimate dominance effects, which ranged from to 0.35 standard deviation units for the production traits and clinical mastitis (CM), respectively. Results showed that the dominance effects may be important in contribution of total genetic effects for production traits and CM. Therefore, evaluation of animals based on additive variance alone and disregarding nonadditive effects may lead to failure in selection programmes and exactly estimating the genetic variation. The method that we used would help breeders in accurately estimation of genotypic values in a new genomic selection scenario including dominance effects.
机译:知识非二余方差和遗传效应可以有助于解释大多数性状的总遗传变异。本研究的目的是估算核心奶牛在案例对照研究中的几种单核苷酸多态性(SNP)基因型(SNP)基因型(CMR)的优势效应。获得305天哺乳期的记录,用于生产性状和CMR。根据混合模型分析,基于CMR的极值选择动物。通过施加物流回归分析估计,样品对四种SNP-单个基因型进行四种SNP-单种式基因型及其与生产性状的育种和蛋白质和脂肪产量的育种值以及蛋白质和脂肪百分比)进行综合。允许估计优势效应的纯合和杂合基因型与初级效应的对比度分别从0.35个标准偏差单位进行估计和临床乳腺炎(CM)。结果表明,优势效应对于生产性状和CM的总遗传效果的贡献可能是重要的。因此,基于单独的添加剂方差和忽略非吸附效应的动物的评估可能导致选择程序的失败并准确估计遗传变异。我们使用的方法将在新的基因组选择场景中准确地估计包括优势效应的基因型值。

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