基于GBLUP和BayesB方法对肉鸡屠宰性状基因组预测准确性的比较

doi:10.3864/j.issn.0578-1752.2021.23.016

摘要/Abstract

摘要：

【目的】育种值估计是畜禽育种的核心内容,准确的育种值估计是提高选种准确性的重要手段。屠宰性状是肉鸡重要的经济性状,且无法活体测量,利用基因组信息进行育种值估计的基因组选择是十分有力的工具。文章通过比较GBLUP和BayesB方法对肉鸡屠宰性状的基因组预测的准确性,为肉鸡育种值估计的策略提供依据。【方法】用本课题组前期收集的3 362只白羽肉鸡的表型记录,性状包括胸肌率（BrR）、胸肌重（BrW）、屠体重（CW）、腿肌率（ThR）和腿肌重（ThW）。利用中国农业科学院自主研发的“京芯一号”鸡 55 K SNP芯片对所有个体进行了基因分型,采用PLINK软件对芯片的基因型数据进行质量控制,基因组选择的GBLUP和BayesB方法分别由基于R语言的ASReml包和hibayes包实施,并采用世代验证法评估两种方法的基因组育种值的预测准确性。【结果】研究发现基因组选择的准确性与性状的遗传力大致呈正相关。结果显示,在使用GBLUP方法时,预测准确性最高的性状为胸肌率。胸肌率、胸肌重、屠体重、腿肌率和腿肌重的基因组预测的准确性分别为0.3262、0.2871、0.2780、0.2153、0.2126;在使用BayesB方法时,预测准确性最高的性状为胸肌率。5个性状的基因组预测的准确性分别为0.3765、0.2257、0.1376、0.2525、0.2844。结果表明,对于白羽肉鸡屠宰性状的基因组选择研究,BayesB方法的预测准确性略高于GBLUP方法。对于3000的样本量和55 K的标记密度,GBLUP方法的计算时间大约为1h,BayesB方法的计算时间大约为7h。【结论】对于胸肌率、腿肌率和腿肌重,BayesB方法的预测准确性高于GBLUP方法;对于屠体重和胸肌重,GBLUP方法的预测准确性高于BayesB。畜禽的育种工作注重实效性。在实际的育种工作中,需要综合考虑育种值估计的准确性和育种的时效性来决定用何种方式估计基因组育种值。

关键词: 鸡, 基因组选择, 世代验证, 准确性

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

朱墨,郑麦青,崔焕先,赵桂苹,刘杨. 基于GBLUP和BayesB方法对肉鸡屠宰性状基因组预测准确性的比较[J]. 中国农业科学, 2021, 54(23): 5125-5131.

ZHU Mo,ZHENG MaiQing,CUI HuanXian,ZHAO GuiPing,LIU Yang. Comparison of Genomic Prediction Accuracy for Meat Type Chicken Carcass Traits Based on GBLUP and BayesB Method[J]. Scientia Agricultura Sinica, 2021, 54(23): 5125-5131.

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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

性状 Trait	遗传力(标准误) Heritability (SE)
性状 Trait	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)