中国荷斯坦牛繁殖性状的基因型与环境互作

doi:10.11843/j.issn.0366-6964.2024.09.021

摘要/Abstract

摘要：

旨在估计奶牛繁殖性状在不同地区的遗传参数, 检测同一繁殖性状在不同地区之间的基因型与环境互作(G×E)效应。本研究利用全国6个地区2 064个牧场2005至2022年的荷斯坦牛群繁殖记录, 计算了2个重要繁殖性状: 初产日龄(AFC)和产犊间隔(CI), 共包含1 787 590和2 476 422条表型数据。同时对该原始表型数据进行详细的质控和分组。随后, 通过BLUPF90软件的airemlf90模块利用单性状动物模型和重复力模型对6个地区的2个繁殖性状进行了遗传分析, 使用双性状动物和重复力模型估计同一性状不同地区之间的遗传相关, 作为基因型与环境之间效应(G×E)的检测指标。结果表明, 研究所设定的质控条件能够剔除分布异常的表型值; AFC的遗传力较高且在地区间差异较大(0.06~0.40), 而CI的遗传力较低且各地区间差异较小(0.02~0.04);在大多数地区组合下, 2个繁殖性状皆检测到了显著的G×E效应(P<0.05)。综上, 同一繁殖性状在不同地区的遗传表现存在差异, 且部分区域之间存在显著的G×E效应。因此, 对我国奶牛繁殖性状进行遗传改良时需考虑区域性差异及G×E效应对遗传进展的影响。

关键词: 奶牛, 繁殖性状, 遗传参数, 基因型与环境互作

Abstract:

This study aimed to estimate the genetic parameters of fertility traits in different regions, and to test the effect of genotype by environment interactions (G×E) across regions. The raw fertility data were collected from 2 064 Holstein dairy farms in 6 regions of China, including records from 2005 to 2022. A total of 1 787 590 and 2 476 422 phenotypic records were derived from the raw data for age at first calving (AFC), and calving interval (CI). Meanwhile, these phenotypes data were quality controlled and separated into different datasets for subsequent analysis. The statistical models used in this study were all incorporated in the airemlf90 module of BLUPF90. Univariate animal (and repeatability) models were used for estimating genetic parameters for these 2 traits in 6 regions, while bivariate animal (and repeatability) models were used to estimate genetic correlations between the regions, which are the indicators of G×E. The results indicated that the proposed quality control steps could filter abnormal phenotypes records. The heritabilities of AFC were relatively high and varied across regions (0.06-0.40), whereas the heritabilities of CI were low but remained similar across regions (0.02-0.04). Significant G×E effect (P<0.05) was observed across most of the regions for both traits. In conclusion, the genetic parameters of the same fertility trait varied across the regions in China, and significant G×E effect was detected for the trait in partial regions. Therefore, it is highly recommended to consider the impacts of regional difference and G×E effect on genetic advance when breeding for fertility traits of dairy cattle in China.

Key words: dairy cows, fertility traits, genetic parameters, genotype by environment interaction

中图分类号:

师睿, 李珊珊, 张海亮, 路海博, 闫青霞, 张毅, 陈绍祜, 王雅春. 中国荷斯坦牛繁殖性状的基因型与环境互作[J]. 畜牧兽医学报, 2024, 55(9): 3968-3977.

Rui SHI, Shanshan LI, Hailiang ZHANG, Haibo LU, Qingxia YAN, Yi ZHANG, Shaohu CHEN, Yachun WANG. Genotype by Environment Interaction of Fertility Traits for the Holstein Cattle in China[J]. Acta Veterinaria et Zootechnica Sinica, 2024, 55(9): 3968-3977.

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地区 Region	记录数 Records	原始数据 Raw data		质控后数据 Quality controlled data		质控后保留率/% Percentages of controlled data on raw data
地区 Region	记录数 Records	AFC	CI	AFC	CI	AFC	CI
北京	表型	165 553	240 501	136 708	209 581	82.6	87.1
BJ	牧场	127	123	63	68	49.6	55.3
天津	表型	130 568	183 190	103 187	167 552	79.0	91.5
TJ	牧场	79	74	48	52	60.8	70.3
上海	表型	152 323	222 228	134 443	186 699	88.3	84.0
SH	牧场	179	161	92	91	51.4	56.5
河北	表型	636 594	822 939	528 678	606 294	83.0	73.7
HB	牧场	600	564	343	264	57.2	46.8
河南	表型	329 679	494 981	141 607	438 628	43.0	88.6
HN	牧场	413	401	217	283	52.5	70.6
山东	表型	372 873	512 583	252 990	455 075	67.8	88.8
SD	牧场	462	436	45	222	9.7	50.9
总和	表型	1 787 590	2 476 422	1 297 613	2 063 829	72.6	83.3
Sum	牧场	1 860	1 759	808	980	43.4	55.7

地区 Region	性状 Trait	表型均值 Mean	标准差 Standard deviation	加性遗传方差 σ_a²	永久环境方差 σ_pe²	残差方差 σ_e²	遗传力 (标准误) h² (standard error)	重复力 (标准误) r² (standard error)
北京	AFC	767.77	86.67	1 077.40		3 891.40	0.22 (0.007)
BJ	CI	398.81	66.69	94.14	197.07	3 800.60	0.02 (0.002)	0.07 (0.003)
天津	AFC	747.56	84.92	981.06		2 996.10	0.25 (0.009)
TJ	CI	398.00	66.99	79.55	231.09	3 781.90	0.02 (0.003)	0.08 (0.003)
上海	AFC	767.87	73.44	242.41		3 820.40	0.06 (0.006)
SH	CI	404.80	66.77	72.05	204.42	3 501.60	0.02 (0.002)	0.07 (0.003)
河北	AFC	768.32	103.80	2 366.40		3 619.70	0.40 (0.005)
HB	CI	387.60	63.14	141.34	110.41	3 131.00	0.04 (0.003)	0.07 (0.002)
河南	AFC	779.36	102.94	1 144.00		4 215.80	0.21 (0.006)
HN	CI	390.68	60.27	74.02	85.35	2 304.90	0.03 (0.003)	0.06 (0.002)
山东	AFC	733.02	73.88	836.32		1 790.00	0.32 (0.009)
SD	CI	389.94	64.56	93.49	101.72	3 253.60	0.03 (0.002)	0.06 (0.002)
所有数据	AFC	765.06	95.70	1 425.40		3 661.00	0.28 (0.003)
Sum	CI	392.31	64.12	73.53	155.92	3 137.90	0.02 (0.001)	0.07 (0.001)

地区 Region	北京 BJ	天津 TJ	上海 SH	河北 HB	河南 HN	山东 SD
北京 BJ		0.862 (0.109)^∧	0.954 (0.054)^∧	0.580 (0.080)	0.420 (0.107)	0.600 (0.089)
天津 TJ	0.091 (0.080)^#		0.789 (0.109)	0.561 (0.110)	0.262 (0.135)^#	0.794 (0.080)
上海 SH	0.271 (0.099)	0.073 (0.098)^#		0.693 (0.098)	0.298 (0.130)	0.543 (0.103)
河北 HB	0.199 (0.043)	-0.149 (0.055)	0.099 (0.070)^#		0.189 (0.090)	0.551 (0.069)
河南 HN	0.071 (0.062)^#	-0.043 (0.065)^#	-0.040 (0.087)^#	0.079 (0.040)		0.250 (0.091)
山东 SD	0.042 (0.072)^#	0.342 (0.054)	0.122 (0.100)^#	-0.016 (0.048)^#	-0.092 (0.061)^#

地区 Region	北京 BJ	天津 TJ	上海 SH	河北 HB	河南 HN	山东 SD
北京 BJ		38.22	36.29	31.75	24.44	26.50
天津 TJ	35.71		30.82	49.79	39.22	47.22
上海 SH	32.73	28.35		44.55	37.89	43.83
河北 HB	36.15	52.75	46.46		41.50	36.94
河南 HN	23.08	38.51	37.55	43.26		36.40
山东 SD	28.53	30.99	25.25	52.32	36.36

地区 Region	北京 BJ	天津 TJ	上海 SH	河北 HB	河南 HN	山东 SD
北京 BJ		0.998 (0.057)^∧	0.865 (0.130)^∧	0.573 (0.096)	0.402 (0.120)	0.784 (0.085)
天津 TJ	0.196 (0.138)		0.930 (0.084)^∧	0.436 (0.171)	0.288 (0.154)^#	0.919 (0.082)^∧
上海 SH	0.573 (0.163)	0.157 (0.128)^#		0.782 (0.119)	0.336 (0.143)	0.528 (0.129)
河北 HB	0.025 (0.071)^#	0.002 (0.105)^#	0.161 (0.064)		0.307 (0.110)	0.607 (0.088)
河南 HN	0.055 (0.094)^#	0.122 (0.106)^#	-0.014 (0.078)^#	0.072 (0.046)^#		0.323 (0.102)
山东 SD	0.104 (0.126)^#	0.043 (0.141)^#	0.311 (0.072)	0.093 (0.055)^#	0.034 (0.077)^#