Diaz I D P S, Crews D H, Enns R M
Department of Animal Sciences, State University of Sao Paulo, Sao Paulo, Brazil; Department of Animal Sciences, Colorado State University, Fort Collins, CO, USA.
J Anim Breed Genet. 2014 Jun;131(3):217-26. doi: 10.1111/jbg.12063. Epub 2013 Nov 23.
A data set based on 50 studies including feed intake and utilization traits was used to perform a meta-analysis to obtain pooled estimates using the variance between studies of genetic parameters for average daily gain (ADG); residual feed intake (RFI); metabolic body weight (MBW); feed conversion ratio (FCR); and daily dry matter intake (DMI) in beef cattle. The total data set included 128 heritability and 122 genetic correlation estimates published in the literature from 1961 to 2012. The meta-analysis was performed using a random effects model where the restricted maximum likelihood estimator was used to evaluate variances among clusters. Also, a meta-analysis using the method of cluster analysis was used to group the heritability estimates. Two clusters were obtained for each trait by different variables. It was observed, for all traits, that the heterogeneity of variance was significant between clusters and studies for genetic correlation estimates. The pooled estimates, adding the variance between clusters, for direct heritability estimates for ADG, DMI, RFI, MBW and FCR were 0.32 ± 0.04, 0.39 ± 0.03, 0.31 ± 0.02, 0.31 ± 0.03 and 0.26 ± 0.03, respectively. Pooled genetic correlation estimates ranged from -0.15 to 0.67 among ADG, DMI, RFI, MBW and FCR. These pooled estimates of genetic parameters could be used to solve genetic prediction equations in populations where data is insufficient for variance component estimation. Cluster analysis is recommended as a statistical procedure to combine results from different studies to account for heterogeneity.
一个基于50项研究的数据集，包括采食量和利用性状，用于进行荟萃分析，以通过肉牛平均日增重（ADG）、剩余采食量（RFI）、代谢体重（MBW）、饲料转化率（FCR）和日干物质采食量（DMI）遗传参数研究间的方差获得合并估计值。该总数据集包括1961年至2012年发表在文献中的128个遗传力估计值和122个遗传相关性估计值。荟萃分析使用随机效应模型进行，其中受限最大似然估计器用于评估聚类间的方差。此外，使用聚类分析方法进行的荟萃分析用于对遗传力估计值进行分组。通过不同变量为每个性状获得了两个聚类。对于所有性状，观察到聚类间和研究间遗传相关性估计值的方差异质性显著。ADG、DMI、RFI、MBW和FCR直接遗传力估计值的合并估计值（加上聚类间的方差）分别为0.32±0.04、0.39±0.03、0.31±0.02、0.31±0.03和0.26±0.03。ADG、DMI、RFI、MBW和FCR之间的合并遗传相关性估计值范围为-0.15至0.67。这些遗传参数的合并估计值可用于在数据不足以进行方差成分估计的群体中求解遗传预测方程。建议使用聚类分析作为一种统计程序来合并不同研究的结果以考虑异质性。
