基于多性状模型内蒙古绒山羊早期生长性状基因组预测准确性研究

doi:10.16288/j.yczz.24-036

遗传 ›› 2024, Vol. 46 ›› Issue (5): 421-430.doi: 10.16288/j.yczz.24-036

基于多性状模型内蒙古绒山羊早期生长性状基因组预测准确性研究

高林豫¹(), 许琦¹, 何钰霄¹, 习海娇¹, 刘一帆¹, 张涛¹, 李金泉¹^,², 张燕军¹, 王瑞军¹, 吕琦¹, 梅步俊⁴, 苏蕊¹, 王志英¹^,³()

1.内蒙古农业大学动物科学学院，呼和浩特 010018
2.农业农村部肉羊遗传育种重点实验室，呼和浩特 010018
3.内蒙古自治区羊遗传育种与繁殖重点实验室，呼和浩特 010018
4.河套学院农学系，巴彦淖尔 015000

收稿日期:2024-01-31 修回日期:2024-04-25 出版日期:2024-05-06 发布日期:2024-05-06
通讯作者: 王志英 E-mail:gaolinyu0629@163.com;wzhy0321@126.com
作者简介:高林豫，硕士研究生，专业方向：畜牧学。E-mail: gaolinyu0629@163.com
基金资助:
国家重点研发计划项目(2022YFE0113300);国家重点研发计划项目(2022YFD1300201);国家重点研发计划项目(2022YFD1300204);内蒙古自治区科技攻关项目(2021GG0086);内蒙古自治区高等学校“青年科技英才支持计划”(NJYT22038);财政部和农业农村部：国家绒毛用羊产业技术体系项目(CARS-39);内蒙古农业大学高水平成果培育专项(QT202201);内蒙古自治区高等学校创新团队发展计划项目(NMGIRT2322);内蒙古自治区直属高校基本科研业务费项目(BR220112)

Comparison of genomic prediction methods for early growth traits of Inner Mongolia cashmere goats based on multi trait models

Linyu Gao¹(), Qi Xu¹, Yuxiao He¹, Haijiao Xi¹, Yifan Liu¹, Tao Zhang¹, Jinquan Li¹^,², Yanjun Zhang¹, Ruijun Wang¹, Qi Lü¹, Bujun Mei⁴, Rui Su¹, Zhiying Wang¹^,³()

1. College of Animal Science, Inner Mongolia Agricultural University, Hohhot 010018, China
2. Key Laboratory of Meat Sheep Genetic Breeding of the Ministry of Agriculture and Rural Affairs, Hohhot 010018, China
3. Key Laboratory of Sheep Genetic Breeding and Reproduction in Inner Mongolia Autonomous Region, Hohhot 010018, China
4. Department of Agriculture, Hetao University, Bayannur 015000, China

Received:2024-01-31 Revised:2024-04-25 Published:2024-05-06 Online:2024-05-06
Contact: Zhiying Wang E-mail:gaolinyu0629@163.com;wzhy0321@126.com
Supported by:
National Key Research and Development Program(2022YFE0113300);National Key Research and Development Program(2022YFD1300201);National Key Research and Development Program(2022YFD1300204);Inner Mongolia Autonomous Region Science and Technology Research Project(2021GG0086);Inner Mongolia Autonomous Region Higher Education Youth Science and Technology Talent Support Program(NJYT22038);Ministry of Finance and the Ministry of Agriculture and Rural Affairs, the National Technical System for Woolen Sheep Industry(CARS-39);High Level Achievement Cultivation Project of Inner Mongolia Agricultural University(QT202201);Inner Mongolia Autonomous Region Higher Education Innovation Team Development Program(NMGIRT2322);Basic Research Expenses of Universities Directly of Inner Mongolia Autonomous Region(BR220112)

摘要/Abstract

摘要：

内蒙古绒山羊是经过长期自然选择和人工选育后形成的优良家畜品种，是目前世界一流的绒肉兼用山羊。多性状动物模型被认为可以显著提高畜禽遗传评估的准确性，实现性状间的间接选择。本文基于内蒙古绒山羊个体的系谱、基因型、环境以及早期生长性状的表型记录，建立多性状动物模型，利用ABLUP、GBLUP、ssGBLUP三种方法进行早期生长性状(初生重、断乳重、断乳前平均日增重、周岁重)遗传参数及基因组育种值的估计，进一步利用五倍交叉验证方法评价基因组育种值估计准确性和可靠性。结果显示，3种方法估计的初生重遗传力为0.13~0.15，断乳重遗传力为0.13~0.20，日增重遗传力为0.11~0.14，周岁重遗传力为0.09~0.14，均属于中等偏低遗传力；断乳重和日增重、日增重和周岁重之间存在强的正遗传相关，相关系数分别为0.77~0.79和0.56~0.67，表型相关发现同样的规律；ABLUP、GBLUP和ssGBLUP法估计的初生重育种值准确性分别为0.5047、0.6694、0.7156，断乳重分别为0.6207、0.6456、0.7254；日增重分别为0.6110、0.6855、0.7357，周岁重分别为0.6209、0.7155、0.7756。综上所述，内蒙古绒山羊早期生长性状属于中等偏低遗传力，对其进行遗传选育改良速度相对较慢；通过对断乳重的选择可以实现其他生长性状的遗传改良；ssGBLUP方法估计内蒙古绒山羊早期生长性状基因组育种值的准确性和可靠性均最高，且显著高于ABLUP法，说明该方法是内蒙古绒山羊早期性状基因组选育的最佳方法。

关键词: 内蒙古绒山羊, 早期生长性状, 多性状动物模型, 基因组育种值估计准确性

Abstract:

Inner Mongolia cashmere goat is an excellent livestock breed formed through long-term natural selection and artificial breeding, and is currently a world-class dual-purpose breed producing cashmere and meat. Multi trait animal model is considered to significantly improve the accuracy of genetic evaluation in livestock and poultry, enabling indirect selection between traits. In this study, the pedigree, genotype, environment, and phenotypic records of early growth traits of Inner Mongolia cashmere goats were used to build multi trait animal model., Then three methods including ABLUP, GBLUP, and ssGBLUP wereused to estimate the genetic parameters and genomic breeding values of early growth traits (birth weight, weaning weight, average daily weight gain before weaning, and yearling weight). The accuracy and reliability of genomic estimated breeding value are further evaluated using the five fold cross validation method. The results showed that the heritability of birth weight estimated by three methods was 0.13-0.15, the heritability of weaning weight was 0.13-0.20, heritability of daily weight gain before weaning was 0.11-0.14, and the heritability of yearling weight was 0.09-0.14, all of which belonged to moderate to low heritability. There is a strong positive genetic correlation between weaning weight and daily weight gain before weaning, daily weight gain before weaning and yearling weight, with correlation coefficients of 0.77-0.79 and 0.56-0.67, respectively. The same pattern was found in phenotype correlation among traits. The accuracy of the estimated breeding values by ABLUP, GBLUP, and ssGBLUP methods for birth weight is 0.5047, 0.6694, and 0.7156, respectively; the weaning weight is 0.6207, 0.6456, and 0.7254, respectively; the daily weight gain before weaning was 0.6110, 0.6855, and 0.7357 respectively; and the yearling weight was 0.6209, 0.7155, and 0.7756, respectively. In summary, the early growth traits of Inner Mongolia cashmere goats belong to moderate to low heritability, and the speed of genetic improvement is relatively slow. The genetic improvement of other growth traits can be achieved through the selection of weaning weight. The ssGBLUP method has the highest accuracy and reliability in estimating genomic breeding value of early growth traits in Inner Mongolia cashmere goats, and is significantly higher than that from ABLUP method, indicating that it is the best method for genomic breeding of early growth weight in Inner Mongolia cashmere goats.

Key words: Inner Mongolia cashmere goat, early growth traits, multi trait animal model, accuracy of genomic estimated breeding value

高林豫, 许琦, 何钰霄, 习海娇, 刘一帆, 张涛, 李金泉, 张燕军, 王瑞军, 吕琦, 梅步俊, 苏蕊, 王志英. 基于多性状模型内蒙古绒山羊早期生长性状基因组预测准确性研究[J]. 遗传, 2024, 46(5): 421-430.

Linyu Gao, Qi Xu, Yuxiao He, Haijiao Xi, Yifan Liu, Tao Zhang, Jinquan Li, Yanjun Zhang, Ruijun Wang, Qi Lü, Bujun Mei, Rui Su, Zhiying Wang. Comparison of genomic prediction methods for early growth traits of Inner Mongolia cashmere goats based on multi trait models[J]. Hereditas(Beijing), 2024, 46(5): 421-430.

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参考文献 29

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性状	个体数	父本数	母本数	最大值	最小值	平均值	标准差(sd)	变异系数(C.V)
初生重	1811	87	829	4.53	1.00	2.76	0.47	16.96%
断乳重	1809	115	1351	34.77	13.60	21.97	3.34	15.42%
日增重	967	85	789	0.27	0.09	0.17	0.03	17.79%
周岁重	1953	116	1419	80.50	20.50	37.20	7.68	21.04%

方法	方差组分
方法	$\sigma _{a}^{2}$	$\sigma _{m}^{2}$	${{\sigma }_{a,m}}$	$\sigma _{c}^{2}$	$\sigma _{e}^{2}$	$\sigma _{p}^{2}$	h_a²±SE	h_m²	C²	h_T²	r_a,m
ABLUP	0.03	0.01	-3.87×10^-3	0.02	0.14	0.20	0.15±0.07	0.05	0.10	0.15	-0.22
GBLUP	0.02	0.02	-4.31×10^-3	0.02	0.12	0.18	0.11±0.05	0.11	0.11	0.13	-0.22
ssGBLUP	0.02	0.02	-4.63×10^-3	0.02	0.12	0.18	0.11±0.06	0.11	0.11	0.13	-0.23

方法	方差组分
方法	$\sigma _{a}^{2}$	$\sigma _{m}^{2}$	${{\sigma }_{a,m}}$	$\sigma _{c}^{2}$	$\sigma _{e}^{2}$	$\sigma _{p}^{2}$	h_a²±SE	h_m²	C²	h_T²	r_a,m
ABLUP	1.93	0.67	-0.91	0.13	3.12	4.94	0.39±0.13	0.14	0.03	0.18	-0.80
GBLUP	1.62	0.90	-0.83	6.46×10^-5	3.85	5.54	0.29±0.10	0.16	1.17×10^-5	0.20	-0.69
ssGBLUP	1.82	0.94	-1.07	6.94×10^-3	3.68	5.38	0.34±0.05	0.17	1.29×10^-3	0.13	-0.82

方法	方差组分
方法	$\sigma _{a}^{2}$	$\sigma _{m}^{2}$	${{\sigma }_{a,m}}$	$\sigma _{c}^{2}$	$\sigma _{e}^{2}$	$\sigma _{p}^{2}$	h_a²±SE	h_m²	C²	h_T²	r_a,m
ABLUP	3.31×10^-5	2.77×10^-5	-1.95×10^-6	2.93×10^-6	2.51×10^-4	3.13×10^-4	0.11±0.05	0.09	9.36×10^-3	0.14	-0.06
GBLUP	5.50×10^-5	2.96×10^-5	-1.49×10^-5	1.26×10^-5	3.16×10^-4	3.98×10^-4	0.14±0.04	0.07	0.03	0.12	-0.37
ssGBLUP	5.43×10^-5	3.14×10^-5	-1.42×10^-5	3.68×10^-6	3.85×10^-4	4.73×10^-4	0.11±0.05	0.07	7.78×10^-3	0.11	-0.34

方法	方差组分
方法	$\sigma _{a}^{2}$	$\sigma _{m}^{2}$	${{\sigma }_{a,m}}$	$\sigma _{c}^{2}$	$\sigma _{e}^{2}$	$\sigma _{p}^{2}$	h_a²±SE	h_m²	C²	h_T²	r_a,m
ABLUP	6.51	4.98	-4.46	3.35×10^-4	17.32	24.35	0.27±0.09	0.20	1.38×10^-5	0.09	-0.78
GBLUP	4.87	2.38	-2.33	3.80×10^-4	15.52	20.44	0.24±0.07	0.12	1.86×10^-5	0.13	-0.68
ssGBLUP	5.75	2.87	-2.64	3.67×10^-4	17.04	23.02	0.25±0.03	0.12	1.59×10^-5	0.14	-0.65

基于多性状模型内蒙古绒山羊早期生长性状基因组预测准确性研究

Comparison of genomic prediction methods for early growth traits of Inner Mongolia cashmere goats based on multi trait models

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性状	初生重	断乳重	日增重	周岁重
初生重	0.15	0.37	0.11	0.31
断乳重	0.23	0.18	0.79	0.47
日增重	0.09	0.53	0.14	0.61
周岁重	0.18	0.37	0.46	0.09

性状	初生重	断乳重	日增重	周岁重
初生重	0.13	0.39	0.17	0.35
断乳重	0.30	0.20	0.77	0.63
日增重	0.12	0.71	0.12	0.56
周岁重	0.21	0.33	0.39	0.13

性状	初生重	断乳重	日增重	周岁重
初生重	0.13	0.44	0.11	0.37
断乳重	0.31	0.13	0.79	0.59
日增重	0.09	0.70	0.11	0.67
周岁重	0.22	0.39	0.48	0.14

性状	方法	准确性	准确性误差	可靠性
初生重	ABLUP	0.5047 (0.5209)	0.1063 (0.1276)	0.2547 (0.2713)
	GBLUP	0.6694 (0.5556)	0.0097 (0.0079)	0.4481 (0.3087)
	ssGBLUP	0.7156 (0.6057)	0.0068 (0.0058)	0.5121 (0.3669)
断乳重	ABLUP	0.6207 (0.6831)	0.1021 (0.1651)	0.3853 (0.4666)
	GBLUP	0.6456 (0.7274)	0.0719 (0.0110)	0.4168 (0.5291)
	ssGBLUP	0.7254 (0.7577)	0.0658 (0.0081)	0.5262 (0.5741)
日增重	ABLUP	0.6110 (0.5857)	0.1146 (0.1604)	0.3733 (0.3430)
	GBLUP	0.6855 (0.6630)	0.0529 (0.0202)	0.4699 (0.4396)
	ssGBLUP	0.7357 (0.7021)	0.0268 (0.0080)	0.5413 (0.4929)
周岁重	ABLUP	0.6209 (0.5965)	0.1231 (0.1494)	0.3855 (0.3558)
	GBLUP	0.7155 (0.6381)	0.0082 (0.0209)	0.5119 (0.4072)
	ssGBLUP	0.7756 (0.6683)	0.0048 (0.0046)	0.6016 (0.4466)