Pinto Luis F B, Lewis Ronald M, Rocha Artur O, Freking Brad A, Wilson Carrie S, Murphy Tom W, Nilson Sara M, Burke Joan M, Brito Luiz F
Department of Animal Science, Federal University of Bahia, Salvador, BA, Brazil.
Department of Animal Sciences, Purdue University, West Lafayette, IN 47907, USA.
J Anim Sci. 2025 Jan 4;103. doi: 10.1093/jas/skaf125.
Direct genetic selection for increased ewe longevity can improve flock profitability and animal welfare. However, longevity indicator traits are not presently evaluated by the National Sheep Improvement Program (NSIP). The primary objective of this study was, therefore, to estimate genetic parameters for 8 longevity indicator traits using data collected in NSIP Katahdin flocks. Ewes (n = 12,734) were born between 1989 and 2020 in 58 flocks across the U.S. and were daughters of 1,245 sires and 6,325 dams. Traits evaluated were age at the last lambing (ALL), length of productive life (PL; number of days between the first and last lambing), total number of litters (TNL), total number of lambs born (TNB) and weaned (TNW) over ewe lifetime, total lamb birth weight (TLB) and total lamb weight at weaning (TLW) over ewe lifetime, and TLW divided by the ewe's 120 d adjusted body weight (TLWadj). Variance components were estimated using the AIREML method based on fitting an animal model using either a pedigree (A) or blended pedigree and genomic (H) relationship matrix. Genomic information of 10,032 animals genotyped with a 50K SNP chip was included in the analyses based on H matrix. Age at first lambing and birth-rearing type of the ewe were fitted as fixed effects, while the contemporary group (CG: flock-year-season of ewe's birth) was fitted as either a fixed (contemporary group fitted as a fixed effect) or random (contemporary group fitted as a random effect) effect. Breeding values and their accuracies were obtained for 127,535 animals in the pedigree using either best linear unbiased prediction (BLUP) or single-step genomic BLUP. Genetic trends were evaluated based on all combinations of CG type and method for predicting breeding values. The averages of ALL, PL, TNL, TNB, TNW, TLB, TLW, and TLWadj were 1100 d, 890 d, 2.7 litters, 4.6 lambs, 4.3 lambs, 18 kg, 70 kg, and 2.8 kg/kg of ewe weight, respectively. The H matrix performed better than the A matrix, based on akaike information criterion and estimates of breeding value accuracy. Higher average accuracy values were observed when fitting CG as a random effect. The heritability estimates ranged from 0.06 ± 0.02 (TLWadj) to 0.15 ± 0.02 (TLB). All genetic and phenotypic correlations between longevity traits were greater than 0.80. Genetic trends were significant and positive for all traits, but no substantial genetic gains were observed. Considering the observed average values and the estimated genetic parameters, we recommend that longevity becomes part of the selection objectives for U.S. Katahdin sheep.
直接对提高母羊寿命进行遗传选择可以提高羊群的盈利能力和动物福利。然而，目前国家绵羊改良计划（NSIP）并未对寿命指标性状进行评估。因此，本研究的主要目的是利用NSIP卡他丁羊群收集的数据，估计8个寿命指标性状的遗传参数。母羊（n = 12734只）于1989年至2020年出生在美国各地的58个羊群中，是1245只公羊和6325只母羊的后代。评估的性状包括最后一次产羔时的年龄（ALL）、生产寿命长度（PL；第一次和最后一次产羔之间的天数）、母羊一生中的总产羔数（TNL）、出生的羔羊总数（TNB）和断奶的羔羊总数（TNW）、母羊一生中的羔羊出生总重（TLB）和断奶时的羔羊总重（TLW），以及TLW除以母羊120天调整体重（TLWadj）。基于使用系谱（A）或混合系谱和基因组（H）关系矩阵拟合动物模型，采用AIREML方法估计方差成分。基于H矩阵的分析纳入了10032只使用50K SNP芯片进行基因分型的动物的基因组信息。首次产羔年龄和母羊的出生-饲养类型作为固定效应，而当代组（CG：母羊出生的羊群-年份-季节）作为固定（当代组作为固定效应）或随机（当代组作为随机效应）效应。使用最佳线性无偏预测（BLUP）或单步基因组BLUP，获得了系谱中127535只动物的育种值及其准确性。基于CG类型和预测育种值方法的所有组合评估遗传趋势。ALL、PL、TNL、TNB、TNW、TLB、TLW和TLWadj的平均值分别为1100天、890天、2.7窝、4.6只羔羊、4.3只羔羊、18千克、70千克和每千克母羊体重2.8千克。基于赤池信息准则和育种值准确性估计，H矩阵比A矩阵表现更好。当将CG作为随机效应拟合时，观察到更高的平均准确性值。遗传力估计值范围从0.06±0.02（TLWadj）到0.15±0.02（TLB）。寿命性状之间的所有遗传和表型相关性均大于0.80。所有性状的遗传趋势均显著且为正，但未观察到显著的遗传进展。考虑到观察到的平均值和估计的遗传参数，我们建议将寿命纳入美国卡他丁绵羊的选择目标。
