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Genomic BLUP including additive and dominant variation in purebreds and F1 crossbreds, with an application in pigs

机译:基因组BLUP,包括纯种和F1杂种的加性和显性变异,在猪中的应用

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Most developments in quantitative genetics theory focus on the study of intra-breed/line concepts. With the availability of massive genomic information, it becomes necessary to revisit the theory for crossbred populations. We propose methods to construct genomic covariances with additive and non-additive (dominance) inheritance in the case of pure lines and crossbred populations. We describe substitution effects and dominant deviations across two pure parental populations and the crossbred population. Gene effects are assumed to be independent of the origin of alleles and allelic frequencies can differ between parental populations. Based on these assumptions, the theoretical variance components (additive and dominant) are obtained as a function of marker effects and allelic frequencies. The additive genetic variance in the crossbred population includes the biological additive and dominant effects of a gene and a covariance term. Dominance variance in the crossbred population is proportional to the product of the heterozygosity coefficients of both parental populations. A genomic BLUP (best linear unbiased prediction) equivalent model is presented. We illustrate this approach by using pig data (two pure lines and their cross, including 8265 phenotyped and genotyped sows). For the total number of piglets born, the dominance variance in the crossbred population represented about 13 % of the total genetic variance. Dominance variation is only marginally important for litter size in the crossbred population. We present a coherent marker-based model that includes purebred and crossbred data and additive and dominant actions. Using this model, it is possible to estimate breeding values, dominant deviations and variance components in a dataset that comprises data on purebred and crossbred individuals. These methods can be exploited to plan assortative mating in pig, maize or other species, in order to generate superior crossbred individuals in terms of performance.
机译:定量遗传学理论的大多数发展都集中在品种/品系概念的研究上。随着大量基因组信息的获得,有必要重新研究杂交种群的理论。在纯系和杂交种群的情况下,我们提出了构建具有加性和非加性(优势)遗传的基因组协方差的方法。我们描述了两个纯亲代种群和杂交种群之间的替代效应和显性偏差。假定基因效应与等位基因的起源无关,并且等位基因的频率在父母群体之间可能有所不同。基于这些假设,可获得理论差异分量(加性和显性)作为标记效应和等位基因频率的函数。杂种群体中的加性遗传方差包括基因和协方差项的生物加性和显性效应。杂种种群的优势变异与两个亲本种群的杂合性系数的乘积成正比。提出了基因组BLUP(最佳线性无偏预测)等效模型。我们通过使用猪的数据(两条纯系及其杂交,包括8265种表型和基因型母猪)来说明这种方法。对于出生的仔猪总数而言,杂种群体的优势变异约占总遗传变异的13%。优势变异对于杂种种群中的产仔数仅至关重要。我们提出了一个基于标记的连贯模型,其中包括纯种和杂种数据以及加性和显性作用。使用此模型,可以估计包含纯种和杂种个体数据的数据集中的育种值,显性偏差和方差成分。可以利用这些方法来计划在猪,玉米或其他物种中进行交配,从而在性能方面产生出更好的杂交个体。

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