Kucerová J, Lund M S, Sørensen P, Sahana G, Guldbrandtsen B, Nielsen V H, Thomsen B, Bendixen C
Department of Animal Breeding, University of South Bohemia, Ceské Budejovice, 370 05, Czech Republic.
J Dairy Sci. 2006 Jun;89(6):2245-56. doi: 10.3168/jds.S0022-0302(06)72296-2.
The aims of this study were (1) to confirm previously identified quantitative trait loci (QTL) on bovine chromosomes 6, 11, 14, and 23 in the Danish Holstein cattle population, (2) to assess the pleiotropic nature of each QTL on milk production traits by building multitrait and multi-QTL models, and (3) to include pedigree information on nongenotyped individuals to improve the estimation of genetic parameters underlying the random QTL model. Nineteen grandsire families were analyzed by single-trait (ST) and multitrait (MT) QTL mapping methods. The variance component-based QTL mapping model was implemented via restricted maximum likelihood (REML) to estimate QTL position and parameters. Segregation of the previously identified QTL was confirmed on bovine chromosomes 6, 11, and 14, but not on 23. A highly significant (1% chromosome-wise level) QTL was found on chromosome 6, between 37 and 73 cM. This QTL had a strong effect on protein percentage (PP) and fat percentage (FP) according to ST analyses, and effects on PP, FP, milk yield (MY), fat yield (FY), and protein yield (PY) in MT analyses. A QTL affecting PP was detected on chromosome 11 (at 70 cM) using ST analysis. The MT analysis revealed a second QTL (at 67 cM) approaching significance with an effect on MY. The ST analysis identified a QTL for MY and FP on chromosome 14, between 10 and 24 cM. The extended pedigree (nongenotyped animals) was included to estimate genetic parameters underlying the random QTL model; that is, additive polygenic and QTL variances. In general, the estimates of the QTL variance components were smaller but more precise when the extended pedigree was considered in the analysis.
（1）在丹麦荷斯坦牛群体中确认先前在牛6号、11号、14号和23号染色体上鉴定出的数量性状基因座（QTL）；（2）通过构建多性状和多QTL模型，评估每个QTL对产奶性状的多效性；（3）纳入非基因型个体的系谱信息，以改进随机QTL模型潜在遗传参数的估计。采用单性状（ST）和多性状（MT）QTL定位方法对19个祖父系家系进行了分析。基于方差成分的QTL定位模型通过限制最大似然法（REML）实现，以估计QTL位置和参数。在牛6号、11号和14号染色体上证实了先前鉴定的QTL的分离，但在23号染色体上未得到证实。在6号染色体上37至73厘摩之间发现了一个高度显著（染色体水平1%）的QTL。根据ST分析，该QTL对蛋白质百分比（PP）和脂肪百分比（FP）有强烈影响，在MT分析中对PP、FP、产奶量（MY）、脂肪产量（FY）和蛋白质产量（PY）有影响。使用ST分析在11号染色体上（70厘摩处）检测到一个影响PP的QTL。MT分析揭示了第二个接近显著水平的QTL（67厘摩处），对MY有影响。ST分析在14号染色体上10至24厘摩之间鉴定出一个影响MY和FP的QTL。纳入扩展系谱（非基因型动物）以估计随机QTL模型潜在的遗传参数，即加性多基因和QTL方差。总体而言，在分析中考虑扩展系谱时，QTL方差成分的估计值较小但更精确。
