Genotype by environment interaction for litter size in pigs as quantified by reaction norms analysis
Genotype by environment interaction for litter size in pigs as quantified by reaction norms analysis
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DOI：
10.1017/s1751731108003145
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发表时间：
2008-12-01
期刊：
影响因子：
3.6
通讯作者：
Su, G.
中科院分区：
文献类型：
--
作者：
Knap, P. W.;Su, G.
采用贝叶斯方法估计了北美、拉丁美洲、欧洲、亚洲和澳大利亚144个农场记录的121 104头母猪、2040头母猪的297518个产仔数记录的线性反应规范（即单个G X E样地）。该方法允许同时估计所有涉及的参数。对三个子集进行了分析，包括(i) 6号线33 641头母猪的1次胎次记录，（ii） B号线52 120头母猪的所有胎次记录，（iii） A和A X B号线121 104头母猪的所有胎次记录。反应规范截距的遗传率从0.09到0.10（最小到最大子集），斜率的遗传率为0.15,0.08和0.02（同上）。估计截距和斜率的遗传相关分别为-0.09、+0.26和+0.69（同上）。因此，这三个亚群对环境敏感性的遗传成分逐渐降低，基因型在环境（群年-季节）范围内的重新排序也逐渐减少。在统计模型中不包括反应规范的遗传评估中，部分gxe效应与加性遗传效应混淆，这可能导致加性遗传效应的估计错误；反应规范模型消除了这种混淆。最大数据子集的截距估计值显示，对于有1 - 7次产仔记录的母猪，与常规遗传评估（不包括反应规范）的产仔数估计育种值（EBV）的相关性为0.78 - 0.85，对于母猪为0.75。因此，在遗传评价中加入反应规范将使没有自身表现或后代数据的年轻选择候选者的EBV可靠性大大提高100倍(1/0.75-1)= 33%以上。反应范数斜率估计是非常苛刻的统计；因此，环境敏感性必须被归类为“难以测量”的特征。
A Bayesian procedure was used to estimate linear reaction norms (i.e. individual G X E plots) on 297518 litter size records of 121 104 sows, daughters of 2040 sires, recorded on 144 farms in North and Latin America, Europe, Asia and Australia. The method allowed for simultaneous estimation of all parameters involved. The analysis was carried out on three subsets, comprising (i) parity 1 records of 33 641 sows of line 6, (ii) all parity records of 52 120 sows of line B and (iii) all parity records of 121 104 sows of lines A, and A X B. Estimated heritabilities ranged from 0.09 to 0.10 (smallest to largest subset) for the intercept of the reaction norms, and were 0.15, 0.08 and 0.02 (ditto) for the slope. Estimated genetic correlations between intercept and slope were -0.09, +0.26 and +0.69 (ditto). The three subsets therefore showed a progressively lower genetic component to environmental sensitivity 4 and progressively less re-ranking of genotypes across the environmental (herd-year-season) range. In a genetic evaluation that does not include reaction norms in the statistical model, part of the G X E effect remains confounded with the additive genetic effect, which may lead to errors in the estimates of the additive genetic effect; the reaction norms model removes this confounding. The intercept estimates from the largest data subset show correlations with litter size estimated breeding values (EBV) from routine genetic evaluation (without reaction norms included) of 0.78 to 0.85 for sows with one to seven litter records, and 0.75 for sires. Hence, including reaction norms in genetic evaluation would increase the reliability of the EBV of young selection candidates without own performance or progeny data by considerably more than 100 X (1/0.75-1) = 33%. Reaction norm slope estimates turn out to be very demanding statistics; environmental sensitivity must therefore be classified as a 'hard-to-measure' trait.