北京地区大白猪基因组联合育种研究

doi:10.3864/j.issn.0578-1752.2019.12.013

中国农业科学 ›› 2019, Vol. 52 ›› Issue (12): 2161-2170.doi: 10.3864/j.issn.0578-1752.2019.12.013

• 畜牧·兽医·资源昆虫 • 上一篇下一篇

北京地区大白猪基因组联合育种研究

张金鑫¹,唐韶青²,宋海亮¹,高虹¹,蒋尧¹,江一凡¹,弥世荣³,孟庆利⁴,于凡⁵,肖炜²,云鹏²,张勤¹,丁向东¹()

¹ 中国农业大学动物科技学院/畜禽育种国家工程实验室/农业部动物遗传育种与繁殖重点实验室,北京 100193
² 北京市畜牧总站,北京 100107
³ 北京六马养猪科技有限公司,北京 101308
⁴ 北京养猪育种中心,北京 100194
⁵ 北京顺鑫农业发展集团有限公司,北京 101300

收稿日期:2018-09-03 接受日期:2019-04-02 出版日期:2019-06-16 发布日期:2019-06-22
通讯作者: 丁向东
作者简介:张金鑫,E-mail： 1599436449@qq.com。
基金资助:
国家生猪产业技术体系(CARS-35、北京市科技计划项目BAIC02-2016)

Joint Genomic Selection of Yorkshire in Beijing

ZHANG JinXin¹,TANG ShaoQing²,SONG HaiLiang¹,GAO Hong¹,JIANG Yao¹,JIANG YiFan¹,MI ShiRong³,MENG QingLi⁴,YU Fan⁵,XIAO Wei²,YUN Peng²,ZHANG Qing¹,DING XiangDong¹()

¹ Key Laboratory of Animal Genetics/Breeding and Reproduction of Ministry of Agriculture/National Engineering Laboratory for Animal Breeding/College of Animal Science and Technology, China Agricultural University, Beijing 100193
² The Beijing Municipal Animal Husbandry Station, Beijing 100107
³ Beijing Liuma Pig Breeding Co., Ltd., Beijing 101308
⁴ Beijing Pig Breeding Center, Beijing 100194
⁵ Beijing Shunxin Agricultural Co., Ltd., Beijing 101300

Received:2018-09-03 Accepted:2019-04-02 Online:2019-06-16 Published:2019-06-22
Contact: XiangDong DING

摘要/Abstract

摘要：

【目的】利用基因组选择技术,进行北京地区大白猪基因组联合遗传评估,并实施基因组选择分子育种,预测刚出生的小公猪基因组估计育种值,提高选种准确性。【方法】利用北京地区3家核心育种场英、美系大白猪2007-2017年场内性能测定记录,筛选4020头个体构建基因组选择混合参考群,性状包括达100kg体重日龄、100kg活体背膘厚和总产仔数,参考群个体和候选公猪个体基因型信息主要采用Illumina 80K SNP芯片进行测定。基因组育种值采用同时利用系谱信息和基因组信息的一步法（SSGBLUP）方法,对3家核心场猪只进行基因组联合遗传评估,分别在公猪去势前和性能测定结束时预测大白公猪生长性状和繁殖性状基因组估计育种值（GEBV）,并进行相应选种。3个场之间的场间遗传联系用关联率衡量。【结果】场间关联率计算结果表明,由于遗传背景差异,北京地区3家核心场场间遗传联系偏低,无法开展传统联合遗传评估,但基于基因组信息的G矩阵亲缘关系结果显示,不同群体间个体存在亲缘关系,说明通过基因组选择可以实现3个育种场间的基因组联合遗传评估。基因组选择实施后,累计基因组预测大白公猪1789头。与传统育种方式相比,基因组选择准确性大幅提高。实施第一次基因组选择或早期选择时（公猪去势前）,达100 kg体重日龄、100 kg活体背膘厚和总产仔数系谱指数的准确性分别为0.55,0.56和0.41,而3个性状GEBV的准确性分别为0.65,0.70和0.60,提高了10、14和19个百分点。终选（性能测定结束）时,3个性状的传统育种值（EBV）准确性为0.70、0.72和0.41,GEBV准确性进一步提高至0.78、0.84和0.60,提高了8、12和19个百分点。低遗传力的总产仔数准确性提高幅度最大。公猪去势前初选时基因组选择准确性与常规性能测定结束时的常规育种值选择准确性几乎一致,表明基因组选择早期选种效果与常规育种相当,节省了育种时间和成本。338头完成性能测定的候选公猪两次基因组选择准确性表明,第二次基因组选择由于加入了候选公猪的测定信息,达100kg体重日龄和100kg活体背膘厚的GEBV准确性由第一次的0.55和0.62分别提高到0.72和0.84,提高了17和22个百分点。无偏性系数在0.82-1.00之间,两性状GEBV的无偏性由第一次基因组选择的0.82、0.96 分别提高到0.91、1.00,说明第二次估计的偏差更小,结果可信度更高,能更准确选出优秀的种公猪。【结论】基因组选择可以建立场间遗传联系,实现常规育种不能进行的联合遗传评估,能够进行更大范围的联合育种。基因组选择的准确性高于传统的系谱指数和育种值选种,且低遗传力性状提高幅度最大。基因组选择能够实现早期选择,提高育种效益。

关键词: 基因组选择, 大白猪, 联合育种, 早期选择

Abstract:

【Objective】In this study, the molecular breeding via genomic selection was carried out in the joint genomic evaluation on Yorkshire population in Beijing, predicting the breeding value of the new born boars and making selection, so as to improve the selection accuracy of breeding. 【Method】 An admixed population consisting of 4020 individuals from three Yorkshire breeding farms with different genetic background in Beijing was established as the reference group, and the reference animals were selected according to the performance testing records between 2007-2017 in those three pig farms. Three economic traits age at 100 kg (AGE), backfat thickness at 100 kg (BF) and total number born (TNB) were taken into account. The reference and candidate animals were genotyped with Illumina Porcine80K SNP chip. GEBV was estimated by single-step GBLUP (SSGBLUP) method which could make use of both pedigree information and genomic information. GEBVs of candidate boars on the growth traits and reproductive traits were predicted before castration and after performance testing, respectively. Afterwards, the elite candidates were selected according to their GEBVs. Meanwhile, the genetic connectedness among three pig farms was measured by connectedness rating.【Result】Our results showed that the genetic connectedness based on pedigree information among three Yorkshire breeding farms was too low to carry out traditional joint genetic evaluation. However,the genomic relationship coefficients of individuals between farms in G-matrix indicated that genetic links existed among different farms. The genomic selection could realize the joint genomic evaluation through establishing the genetic connectedness via genome-wide markers. A total of 1789 boars were genomic predicted.The accuracy of genomic prediction was largely improved, compared to traditional breeding methods. At the first time of implementing genomic selection or early selection (before the castration of boars), the accuracies of Pedigree Index (PI) for three traits, age at 100 kg (AGE), backfat thickness at 100 kg (BF) and total number born (TNB) were 0.55, 0.56 and 0.41, respectively. However, the accuracies of GEBV from genomic selection were increased to 0.65, 0.70 and 0.60 with improvement of 10, 14 and 19 percentage compared to PI selection, respectively. At the second time of implementing genomic selection (after performance testing), the accuracies of GEBV for AGE, BF and TNB were further increased to 0.78, 0.84 and 0.60, respectively, yielding 8, 12 and 19 percentage higher accuracy than EBV, respectively, in which the accuracies were 0.70, 0.72 and 0.41, respectively. The largest gain of genomic selection was on trait of TNB with low heritability. The early selection based on genomic selection had the same accuracy as traditional selection based on estimated breeding values calculated from performance testing, implying genomic selection could save breeding time and cost with keeping the same accuracy. The comparison of two implementations of genomic selection on 338 boars at different stage showed that the second genomic prediction after performance testing yielded higher accuracy, because the phenotypic records of these boars were also utilized. The accuracies of GEBV for AGE and BF were improved from 0.55, 0.62 to 0.72, 0.84 by increasing 17 and 22 percentage point, respectively. The unbiasedness coefficient was between 0.82 and 1.00, and the unbiasedness of GEBV on traits of AGE and BF were increased from 0.82 and 0.96 to 0.91 and 1.00, respectively. The lower unbiasedness of second genomic selection indicated that the reliability of selecting elite boars was higher.【Conclusion】 Genomic selection could establish genetic connectedness between different farms, enabling joint genetic evaluation which was not feasible in traditional breeding plausible and more breeding farms involved. Compared to traditional PI or EBV selection, genomic selection generated much higher accuracy, and the greatest improvement was obtained on the traits with low heritability. Genomic selection was useful to achieve early selection and to improve the breeding efficiency.

Key words: genomic selection, Yorkshire, admixed population, joint breeding, early selection

张金鑫, 唐韶青, 宋海亮, 高虹, 蒋尧, 江一凡, 弥世荣, 孟庆利, 于凡, 肖炜, 云鹏, 张勤, 丁向东. 北京地区大白猪基因组联合育种研究[J]. 中国农业科学, 2019, 52(12): 2161-2170.

ZHANG JinXin, TANG ShaoQing, SONG HaiLiang, GAO Hong, JIANG Yao, JIANG YiFan, MI ShiRong, MENG QingLi, YU Fan, XIAO Wei, YUN Peng, ZHANG Qing, DING XiangDong. Joint Genomic Selection of Yorkshire in Beijing[J]. Scientia Agricultura Sinica, 2019, 52(12): 2161-2170.

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群体类型 Population type	性状名称 Trait name	北京六马 LM	顺鑫农业 XD	养猪中心 ZX	总计 Total number
参考群体 Reference population	达100 kg体重日龄Age at 100 kg live weight	2260	874	886	4020
	达100 kg活体背膘厚Backfat adjusted to 100 kg	2260	874	886	4020
	总产仔数Total number born	1687	874	854	3415
候选公猪 Candidate population	--	979	259	641	1879

猪场编号Farm Code	BJXD1	BJXD2	BJLM1	BJLM6	BJLM4	BJLM5	BBSCB
BJXD1	1	--	--	--	--	--	--
BJXD2	0.602	1	--	--	--	--	--
BJLM1	0	0	1	--	--	--	--
BJLM6	0	0	0.649	1	--	--	--
BJLM4	0	0	0.874	0.727	1	--	--
BJLM5	0	0	0.681	0.692	0.76	1	--
BBSCB	0	0	0	0	0	0	1

性状 Trait	选择阶段Selection stage	准确性Accuracy	无偏性Unbiasedness
达100 kg体重日龄 Age at 100 kg live weight	第一次基因组选择（公猪去势前） First genomic selection (before castrated)	0.55	0.82
达100 kg体重日龄 Age at 100 kg live weight	第二次基因组选择（性能测定结束） Second genomic selection (end of performance measurement)	0.72	0.96
100 kg活体背膘厚 Backfat adjusted to 100 kg	第一次基因组选择（公猪去势前） First genomic selection (before castrated)	0.62	0.91
100 kg活体背膘厚 Backfat adjusted to 100 kg	第二次基因组选择（性能测定结束） Second genomic selection (end of performance measurement)	0.84	1.00

选择阶段 Selection stage	选择标准 Selection criteria	达100 kg体重日龄 Age at 100 kg live weight	100 kg活体背膘厚 Backfat adjusted to 100 kg	总产仔数 Total number born
公猪去势前 Castration stage	基因组育种值Genomic estimated breeding value	0.65±0.04	0.70±0.03	0.60±0.04
公猪去势前 Castration stage	系谱指数 Pedigree index	0.55±0.03	0.56±0.04	0.41±0.05
测定结束 Performance testing	基因组育种值Genomic estimated breeding value	0.78±0.02	0.84±0.02	0.60±0.05
测定结束 Performance testing	育种值Estimated breeding value	0.70±0.04	0.72±0.04	0.41±0.05

北京地区大白猪基因组联合育种研究

Joint Genomic Selection of Yorkshire in Beijing

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