Scientia Agricultura Sinica ›› 2021, Vol. 54 ›› Issue (23): 5125-5131.doi: 10.3864/j.issn.0578-1752.2021.23.016

• ANIMAL SCIENCE·VETERINARY SCIENCE·RESOURCE INSECT • Previous Articles     Next Articles

Comparison of Genomic Prediction Accuracy for Meat Type Chicken Carcass Traits Based on GBLUP and BayesB Method

ZHU Mo1,2(),ZHENG MaiQing2,CUI HuanXian2,ZHAO GuiPing2(),LIU Yang1()   

  1. 1Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, Nanjing Agricultural University, Nanjing 210095
    2State Key Laboratory of Animal Nutrition/Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193
  • Received:2020-11-10 Accepted:2021-04-07 Online:2021-12-01 Published:2021-12-06
  • Contact: GuiPing ZHAO,Yang LIU E-mail:2018105017@njau.edu.cn;zhaoguiping@caas.cn;yangliu@njau.edu.cn

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Abstract:

【Objective】 Predicting the breeding value is the core content of livestock breeding and the accurate predicting of breeding value is an important approach to improve the selection accuracy of breeding. Carcass traits are economic important traits for broilers. However, carcass traits can only be measured postmortem. Genomic selection may be a powerful tool because of its accurate prediction of breeding values of animals without own phenotypic information. At present, there are few reports on genomic selection on carcass traits for broilers. The purpose of this study was to compare the accuracy of genomic prediction of broiler carcass traits by using GBLUP and BayesB method. 【Method】 This study investigated the efficiency of genomic prediction in a white-feathered broiler population, which was collected from 3 362 white-feathered broilers. Five carcass traits, including breast muscle rate (BrR), breast muscle weight (BrW), carcass weight (CW), thigh muscle rate (ThR) and thigh muscle weight (ThW) were taken into account. All the individuals were genotyped with “IASCHICK” chicken 55 K SNP array. PLINK software was used for the quality control of genotype data. GBLUP and BayesB method were implemented with ASReml and hibayes package in R software, respectively. Generation validation were utilized to evaluate the accuracy of genomic prediction for twenty replicates for each trait.【Result】The results showed that the accuracy of genomic selection was almost positively correlated with the heritability of each trait. The validation results indicated that the prediction accuracy of BrR was the highest with GBLUP method, and the accuracies of BrR, BrW, CW, ThR and ThW were 0.3262, 0.2871, 0.2780, 0.2153, and 0.2126, respectively. Meanwhile, the accuracy of BrR was the highest with BayesB method, and the accuracies of BrR, BrW, CW, ThR and ThW were 0.3765, 0.2257, 0.1376, 0.2525, and 0.2844, respectively. The results showed that the prediction accuracy of BayesB method was slightly higher than that of GBLUP method. It took about 1 h and 7 h for GBLUP and BayesB method, respectively, to carry out the calculating procedure for one trait. 【Conclusion】 In conclusion, the prediction accuracy of BrR, ThR and ThW with BayesB method was higher than that with GBLUP method, while the prediction accuracy of BrW and CW with GBLUP method was higher than that with BayesB method. However, the calculating time for BayesB method was longer than that for GBLUP method. In breeding practice, the balance of prediction accuracy and computational efficiency should be comprehensively considered to predict the genomic estimated breeding value.

Key words: chicken, genomic selection, generation validation, accuracy

Table 1

Descriptive statistics for each carcass trait"

性状
Trait		 个体数
Count		 最小值
Minimum		 最大值
Maximum		 平均值
Mean		 标准差
Standard deviation		 变异系数
Coefficient of variation (%)
胸肌率BrR (%) 2409 15.34 26.79 20.97 1.90 9.05
胸肌重BrW (g) 2409 220.20 686.40 434.84 86.34 19.86
屠体重CW (g) 2421 1165.20 2650.00 1879.51 268.18 14.27
腿肌率ThR (%) 2405 18.50 26.72 22.51 1.29 5.71
腿肌重ThW (g) 2405 242.80 691.60 464.53 74.73 16.09

Table 2

Results of heritability for each carcass trait"

性状
Trait		 遗传力(标准误) Heritability (SE)
系谱亲缘关系
Pedigree relationship		 全基因组亲缘关系
Genomic relationship
BrR 0.40 (0.05) 0.37 (0.03)
BrW 0.34 (0.05) 0.26 (0.03)
CW 0.35 (0.05) 0.20 (0.03)
ThR 0.25 (0.05) 0.18 (0.03)
ThW 0.31 (0.05) 0.18 (0.03)

Table 3

Results of generation validation based on GBLUP and BayesB method for each carcass trait"

性状
Trait		 准确性Accuracy
GBLUP BayesB
BrR 0.3262 0.3765
BrW 0.2871 0.2257
CW 0.2780 0.1376
ThR 0.2153 0.2525
ThW 0.2126 0.2844

Fig. 1

The comparison of computing performance of GBLUP and BayesB method for each carcass trait"

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