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Estimation of Additive Dominance and Imprinting Genetic Variance Using Genomic Data

机译:使用基因组数据估算加性显性和印迹遗传变异

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摘要

Traditionally, exploration of genetic variance in humans, plants, and livestock species has been limited mostly to the use of additive effects estimated using pedigree data. However, with the development of dense panels of single-nucleotide polymorphisms (SNPs), the exploration of genetic variation of complex traits is moving from quantifying the resemblance between family members to the dissection of genetic variation at individual loci. With SNPs, we were able to quantify the contribution of additive, dominance, and imprinting variance to the total genetic variance by using a SNP regression method. The method was validated in simulated data and applied to three traits (number of teats, backfat, and lifetime daily gain) in three purebred pig populations. In simulated data, the estimates of additive, dominance, and imprinting variance were very close to the simulated values. In real data, dominance effects account for a substantial proportion of the total genetic variance (up to 44%) for these traits in these populations. The contribution of imprinting to the total phenotypic variance of the evaluated traits was relatively small (1–3%). Our results indicate a strong relationship between additive variance explained per chromosome and chromosome length, which has been described previously for other traits in other species. We also show that a similar linear relationship exists for dominance and imprinting variance. These novel results improve our understanding of the genetic architecture of the evaluated traits and shows promise to apply the SNP regression method to other traits and species, including human diseases.
机译:传统上,对人类,植物和牲畜物种的遗传变异的探索主要限于使用通过谱系数据估算的累加效应。然而,随着密集的单核苷酸多态性(SNPs)面板的发展,对复杂性状遗传变异的探索正从量化家庭成员之间的相似性转向对单个基因座的遗传变异进行解剖。使用SNP,我们能够使用SNP回归方法量化加性,优势和印迹变异对总遗传变异的贡献。该方法在模拟数据中得到验证,并应用于三个纯种猪群体的三个性状(乳头数量,后脂肪和终生日增重)。在模拟数据中,加性,支配性和压印方差的估计值与模拟值非常接近。在真实数据中,优​​势效应在这些人群中占这些性状总遗传变异的很大一部分(高达44%)。印迹对所评估性状的总表型方差的贡献相对较小(1-3%)。我们的结果表明,每个染色体解释的加性方差与染色体长度之间存在很强的关系,这在前面已经针对其他物种的其他性状进行了描述。我们还表明,对于优势度和压印方差存在相似的线性关系。这些新颖的结果提高了我们对评估性状遗传结构的理解,并显示出有望将SNP回归方法应用于其他性状和物种,包括人类疾病。

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