Genome partitioning of genetic variation for milk production and composition traits in holstein cattle.
Genome partitioning of genetic variation for milk production and composition traits in holstein cattle.
复制标题
霍尔斯坦牛的牛奶产量和成分性状的遗传变异的基因组分配。
DOI：
10.3389/fgene.2011.00019
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发表时间：
2011
影响因子：
3.7
通讯作者：
Simianer H
中科院分区：
文献类型：
--
作者：
Pimentel Eda C;Erbe M;König S;Simianer H
本研究的目的是估计荷斯坦牛中每种常染色体对产奶量、脂肪和蛋白质百分比以及体细胞评分遗传变异的贡献。使用了 2294 头荷斯坦公牛的 39,557 个常染色体标记基因型数据。应用三种方法来估计归因于每条染色体的遗传方差的比例。在其中两个中，使用在整个基因组或相对于每个染色体的子集上观察到的标记基因型来计算标记衍生的亲缘系数。然后使用方法 1 中的残差最大似然或方法 2 中的基于回归的方法来估计方差分量。在方法 3 中，以线性多元回归方法估计与每个标记相关的遗传方差，然后按染色体进行求和。一般来说，所有染色体都会导致遗传变异。对于大多数染色体，染色体的变异量被发现与其物理长度成正比。然而，对于受具有非常大影响的基因影响的性状，预计较大比例的遗传变异与这些基因所在的染色体有关。 BTA14 上的 DGAT1 基因就说明了这一点，已知该基因对牛奶中的脂肪百分比有很大影响。与 14 号染色体相关的脂肪百分比的遗传方差比例比仅根据染色体大小预测的要大两到七倍（取决于方法）。基于方法 3，建议采用一种方法来估计所研究性状遗传的有效基因数量，产生的数字在 N ≈ 400（脂肪百分比）到 N ≈ 900（产奶量）之间。有人认为，这些数字是保守的下限估计值，但与最近的发现一致，表明奶牛生产性状具有高度多基因背景。
The objective of this study was to estimate the contribution of each autosome to genetic variation of milk yield, fat, and protein percentage and somatic cell score in Holstein cattle. Data on 2294 Holstein bulls genotyped for 39,557 autosomal markers were used. Three approaches were applied to estimate the proportion of genetic variance attributed to each chromosome. In two of them, marker-derived kinship coefficients were computed, using either marker genotypes observed on the whole genome or on subsets relative to each chromosome. Variance components were then estimated using residual maximum likelihood in method 1 or a regression-based approach in method 2. In method 3, genetic variances associated to each marker were estimated in a linear multiple regression approach, and then were summed up chromosome-wise. Generally, all chromosomes contributed to genetic variation. For most of the chromosomes, the amount of variance attributed to a chromosome was found to be proportional to its physical length. Nevertheless, for traits influenced by genes with very large effects a larger proportion of the genetic variance is expected to be associated with the chromosomes where these genes are. This is illustrated with the DGAT1 gene on BTA14 which is known to have a large effect on fat percentage in milk. The proportion of genetic variance for fat percentage associated with chromosome 14 was two to sevenfold (depending on the method) larger than would be predicted from chromosome size alone. Based on method 3 an approach is suggested to estimate the effective number of genes underlying the inheritance of the studied traits, yielding numbers between N ≈ 400 (for fat percentage) to N ≈ 900 (for milk yield). It is argued that these numbers are conservative lower bound estimates, but are in line with recent findings suggesting a highly polygenic background of production traits in dairy cattle.