Safari E, Fogarty N M, Gilmour A R, Atkins K D, Mortimer S I, Swan A A, Brien F D, Greeff J C, van der Werf J H J
The Australian Sheep Industry Cooperative Research Centre, NSW Department of Primary Industries, Orange Agricultural Institute, Orange, NSW, Australia.
J Anim Breed Genet. 2007 Apr;124(2):65-72. doi: 10.1111/j.1439-0388.2007.00641.x.
Data from seven research resource flocks across Australia were combined to provide accurate estimates of genetic correlations among production traits in Merino sheep. The flocks represented contemporary Australian Merino fine, medium and broad wool strains over the past 30 years. Over 110,000 records were available for analysis for each of the major wool traits, and 50,000 records for reproduction and growth traits with over 2700 sires and 25,000 dams. Individual models developed from the single trait analyses were extended to the various combinations of two-trait models to obtain genetic correlations among six wool traits [clean fleece weight (CFW), greasy fleece weight, fibre diameter (FD), yield, coefficient of variation of fibre diameter and standard deviation of fibre diameter], four growth traits [birth weight, weaning weight, yearling weight (YWT), and hogget weight] and four reproduction traits [fertility, litter size, lambs born per ewe joined, lambs weaned per ewe joined (LW/EJ)]. This study has provided for the first time a comprehensive matrix of genetic correlations among these 14 wool, growth and reproduction traits. The large size of the data set has also provided estimates with very low standard errors. A moderate positive genetic correlation was observed between CFW and FD (0.29 +/- 0.02). YWT was positively correlated with CFW (0.23 +/- 0.04), FD (0.17 +/- 0.04) and LWEJ (0.58 +/- 0.06), while LW/EJ was negatively correlated with CFW (-0.26 +/- 0.05) and positively correlated with FD (0.06 +/- 0.04) and LS (0.68 +/- 0.04). These genetic correlations, together with the estimates of heritability and other parameters provide the basis for more accurate prediction of outcomes in complex sheep-breeding programmes designed to improve several traits.
来自澳大利亚七个研究资源羊群的数据被整合起来，以准确估计美利奴羊生产性状之间的遗传相关性。这些羊群代表了过去30年澳大利亚当代美利奴细毛、中毛和粗毛品系。每种主要羊毛性状都有超过110,000条记录可供分析，繁殖和生长性状有50,000条记录，涉及2700多头公羊和25,000头母羊。从单性状分析得出的个体模型被扩展到双性状模型的各种组合，以获得六个羊毛性状[净毛量（CFW）、污毛量、纤维直径（FD）、产毛率、纤维直径变异系数和纤维直径标准差]、四个生长性状[出生体重、断奶体重、周岁体重（YWT）和育成羊体重]以及四个繁殖性状[繁殖力、产羔数、每只配种母羊产羔数、每只配种母羊断奶羔羊数（LW/EJ）]之间的遗传相关性。本研究首次提供了这14个羊毛、生长和繁殖性状之间遗传相关性的综合矩阵。数据集的规模也使得估计值的标准误差非常低。观察到CFW和FD之间存在中等程度的正遗传相关性（0.29±0.02）。YWT与CFW（0.23±0.04）、FD（0.17±0.04）和LW/EJ（0.58±0.06）呈正相关，而LW/EJ与CFW呈负相关（-0.26±0.05），与FD（0.06±0.04）和LS（0.68±0.04）呈正相关。这些遗传相关性，连同遗传力和其他参数的估计值，为在旨在改善多个性状的复杂绵羊育种计划中更准确地预测结果提供了基础。
