全基因组关联分析（GWAS）在母猪繁殖性状研究中的应用进展

doi:10.13560/j.cnki.biotech.bull.1985.2025-0382

摘要/Abstract

摘要：

母猪的繁殖性状在现代养猪业中占据着至关重要的地位，繁殖性状主要包括产仔数、产活仔数、断奶仔猪数、初生窝重、断奶窝重以及母猪使用年限等一系列关键指标。不仅直接决定了生产效率，还深刻影响着整个养猪产业链的效益与竞争力。然而母猪的繁殖表现为典型的复杂性状，其遗传力通常较低，遗传机制涉及大量基因及其相互作用，包括加性效应、上位效应以及潜在的表观遗传调控等，同时深受环境、管理水平及饲养条件（如营养、温度、湿度、饲养密度、应激状况和健康管理）等非遗传因素的影响，因此对其遗传改良一直是动物育种研究中的一大挑战。随着全基因组关联分析（genome-wide association study, GWAS）方法的不断发展，研究者能够借助高通量基因分型平台，在全基因组范围内筛选与目标表型相关的遗传位点，从而实现对复杂性状的精准解析。本文旨在系统综述GWAS技术的发展概况，包括其统计原理、方法学的演进以及检测效能的提升。进而重点阐述该技术在母猪关键繁殖性状遗传解析中的应用进展，总结已发现的重要遗传信号及其生物学功能。最后探讨GWAS在母猪繁殖性状研究中面临的挑战及对未来研究方向进行展望，例如整合多组学数据以深入阐释因果突变和调控网络，利用大数据和人工智能优化育种值估计，为实现高繁母猪的培育提供参考。

关键词: 全基因组关联分析（GWAS）, 繁殖性状, 候选基因, 遗传改良, 母猪育种

Abstract:

The reproductive traits of sows play a critically important role in modern swine production. These traits encompass a series of key performance indicators, including litter size, number of live births, number of weaned piglets, litter weight at birth, litter weight at weaning, and sow longevity. They not only directly determine production efficiency but also profoundly influence the profitability and competitiveness of the entire swine industry chain.However, sow reproductive performance is a typical complex trait characterized by generally low heritability. Its genetic mechanisms are involved in numerous genes and their interactions, including additive effects, epistasis, and potential epigenetic regulation. Concurrenlty, these traits are significantly influenced by non-genetic factors such as environmental conditions, management practices, and feeding regimens (such as including nutrition, temperature, humidity, stocking density, stress levels, and health management). Consequently, the genetic improvement of these traits has remained a major challenge in animal breeding research. With the continuous development of Genome-Wide Association Study (GWAS) methodology, researchers can now utilize high-throughput genotyping platforms to screen for genetic loci associated with target phenotypes across the entire genome, thereby enabling precise dissection of complex traits. This review aims to systematically summarize the developmental overview of GWAS technology, including its statistical principles, methodological evolution, and improvements in detection power. It further emphasizes the application progress of this technology in genetic analysis of key reproductive traits in sows, synthesizing important genetic signals that have been identified and their biological functions. Finally, the review discusses challenges faced by GWAS in studying sow reproductive trait and provides perspectives on future research directions, such as integrating multi-omics data to gain deeper insights into causal mutations and regulatory networks, and leveraging big data and artificial intelligence to optimize breeding value estimation, thereby providing references for the breeding of highly prolific sows.

Key words: genome-wide association study (GWAS), reproductive traits, candidate genes, genetic improvement, sow breeding

区琦, 冯瑶, 韦柳婷, 庄站伟, 赵云翔, 陈富美. 全基因组关联分析（GWAS）在母猪繁殖性状研究中的应用进展[J]. 生物技术通报, 2026, 42(4): 65-71.

OU Qi, FENG Yao, WEI Liu-ting, ZHUANG Zhan-wei, ZHAO Yun-xiang, CHEN Fu-mei. Application Status of Genome-wide Association Study (GWAS) in the Study of Reproductive Traits in Sow[J]. Biotechnology Bulletin, 2026, 42(4): 65-71.

图/表 2

参考文献 51

[1]	Jianfe L. The 9p21 chromosome polymorphism and coronary artery disease: a research progress [J]. China Mod Dr. 2014
[2]	Fathoni A, Boonkum W, Chankitisakul V, et al. Integrating genomic selection and a genome-wide association study to improve days open in Thai dairy Holstein cattle: a comprehensive genetic analysis [J]. Animals, 2025, 15(1): 43.
[3]	Bhat JA, Adeboye KA, Ahmad Ganie S, et al. Genome-wide association study, haplotype analysis, and genomic prediction reveal the genetic basis of yield-related traits in soybean (Glycine max L.) [J]. Front Genet, 2022, 13: 953833.
[4]	宋志芳. 利用GWAS对深县猪繁殖性状的研究 [D]. 保定: 河北农业大学, 2018.
	Song ZF. Study on the reproductive traits of Shenxian pig by using GWAS [D]. Baoding: Hebei Agricultural University, 2018.
[5]	邓政. 上杭槐猪繁殖性状全基因组关联分析 [J]. 中国畜牧杂志, 2024, 60(8): 205-210.
	Deng Z. Genome-wide association study, reproductive trait of Shanghang Huai pig [J]. Chin J Anim Sci, 2024, 60(8): 205-210.
[6]	Wen YJ, Zhang HW, Ni YL, et al. Methodological implementation of mixed linear models in multi-locus genome-wide association studies [J]. Brief Bioinform, 2018, 19(4): 700-712.
[7]	Giambartolomei C, Vukcevic D, Schadt EE, et al. Bayesian test for colocalisation between pairs of genetic association studies using summary statistics [J]. PLoS Genet, 2014, 10(5): e1004383.
[8]	Du ZQ, Eisley CJ, Onteru SK, et al. Identification of species-specific novel transcripts in pig reproductive tissues using RNA-seq [J]. Anim Genet, 2014, 45(2): 198-204.
[9]	Kang JH, Lee EA, Hong KC, et al. Regulatory gene network from a genome-wide association study for sow lifetime productivity traits [J]. Anim Genet, 2018, 49(3): 254-258.
[10]	Zheng XR, Zhao PJ, Yang KJ, et al. CNV analysis of Meishan pig by next-generation sequencing and effects of AHR gene CNV on pig reproductive traits [J]. J Anim Sci Biotechnol, 2020, 11(1): 42.
[11]	Hosseinzadeh S, Rafat SA, Fang LZ. Integrated TWAS GWAS and RNAseq results identify candidate genes associated with reproductive traits in cows [J]. Sci Rep, 2025, 15: 1932.
[12]	Wang JB, Zhang J, Hao WJ, et al. An interpretable integrated machine learning framework for genomic selection [J]. Smart Agric Technol, 2025, 12: 101138.
[13]	Lee MS, Choe YC. Forecasting sow’s productivity using the machine learning models [J]. J Agric Ext, 2009, 16: 939-965.
[14]	Sun JC, Xiao JH, Jiang YF, et al. Genome-wide association study on reproductive traits using imputation-based whole-genome sequence data in Yorkshire pigs [J]. Genes, 2023, 14(4): 861.
[15]	Onteru SK, Ross JW, Rothschild MF. The role of gene discovery, QTL analyses and gene expression in reproductive traits in the pig [J]. Proc, 2009, 66: 87-102.
[16]	Tam V, Patel N, Turcotte M, et al. Benefits and limitations of genome-wide association studies [J]. Nat Rev Genet, 2019, 20(8): 467-484.
[17]	Zhang SW, Chen B. Genetic variation of progesterone receptor gene and its association with reproductive traits in pig: Genetic variation of progesterone receptor gene and its association with reproductive traits in pig [J]. J Hunan Agric Univ, 2013, 39(1): 58-62.
[18]	Kumchoo T, Mekchay S. Association of NR4A1 and GNB2L1 genes with reproductive traits in commercial pig breeds [J]. Genet Mol Res, 2015, 14(4): 16276-16284.
[19]	Wang Y, Ding X, Tan Z, et al. Genome-wide association study for reproductive traits in a Large White pig population [J]. Anim Genet, 2018, 49(2): 127-131.
[20]	Uzzaman MR, Park JE, Lee KT, et al. A genome-wide association study of reproductive traits in a Yorkshire pig population [J]. Livest Sci, 2018, 209: 67-72.
[21]	Zhang LG, Zhang SY, Yuan M, et al. Genome-wide association studies and runs of homozygosity to identify reproduction-related genes in Yorkshire pig population [J]. Genes, 2023, 14(12): 2133.
[22]	Duan DD, Zhou SP, Wang ZY, et al. Genome-wide association study pinpoints novel candidate genes associated with the gestation length of the first parity in French large white sows [J]. Animals, 2025, 15(3): 447.
[23]	Zhang Z, Chen ZT, Ye SP, et al. Genome-wide association study for reproductive traits in a duroc pig population [J]. Animals, 2019, 9(10): 732.
[24]	Yin H, Du X, Li QQ, et al. Variants in BMP7 and BMP15 3'-UTRs associated with reproductive traits in a large white pig population [J]. Animals, 2019, 9(11): 905.
[25]	Sato S, Kikuchi T, Uemoto Y, et al. Effect of candidate gene polymorphisms on reproductive traits in a Large White pig population [J]. Anim Sci J, 2016, 87(12): 1455-1463.
[26]	Li TT, Wan PC, Lin Q, et al. Genome-wide association study meta-analysis elucidates genetic structure and identifies candidate genes of teat number traits in pigs [J]. Int J Mol Sci, 2024, 25(1): 451.
[27]	Jiang Y, Tang SQ, Xiao W, et al. A genome-wide association study of reproduction traits in four pig populations with different genetic backgrounds [J]. Asian-Australas J Anim Sci, 2020, 33(9): 1400-1410.
[28]	Sun J, Wei J, Pan Y, et al. Improving genomic prediction accuracy of pig reproductive traits based on genotype imputation using preselected markers with different imputation platforms [J]. animal, 2025, 19(1): 101387.
[29]	Zhao YX, Gao GX, Zhou Y, et al. Genome-wide association studies uncover genes associated with litter traits in the pig [J]. animal, 2022, 16(12): 100672.
[30]	Verardo LL, Silva FF, Varona L, et al. Bayesian GWAS and network analysis revealed new candidate genes for number of teats in pigs [J]. J Appl Genet, 2015, 56(1): 123-132.
[31]	Laplana M, Ros-Freixedes R, Estany J, et al. Whole-genome analysis of resilience based on the stability of reproduction performance during a porcine reproductive and respiratory syndrome virus outbreak in sows [J]. animal, 2024, 18(9): 101290.
[32]	Tiezzi F, Brito LF, Howard J, et al. Genomics of heat tolerance in reproductive performance investigated in four independent maternal lines of pigs [J]. Front Genet, 2020, 11: 629.
[33]	Chen JM, Wu ZY, Chen RX, et al. Identification of genomic regions and candidate genes for litter traits in French large white pigs using genome-wide association studies [J]. Animals, 2022, 12(12): 1584.
[34]	Zhang Y, Lai JH, Wang XY, et al. Genome-wide single nucleotide polymorphism (SNP) data reveal potential candidate genes for litter traits in a Yorkshire pig population [J]. Arch Anim Breed, 2023, 66(4): 357-368.
[35]	Sell-Kubiak E, Knol EF, Lopes M. Evaluation of the phenotypic and genomic background of variability based on litter size of Large White pigs [J]. Genet Sel Evol, 2022, 54(1): 1.
[36]	Norseeda W, Liu GS, et al. Effect of leukemia inhibitory factor polymorphism on litter size traits in Thai commercial pig breeds [J]. Vet Integr Sci, 2020, 19(2): 185-196.
[37]	Norseeda W, Liu GS, et al. Association of a non-synonymous SNP of IL17RA gene with litter size traits in Large White and Landrace pigs [J]. Vet Integr Sci, 2021, 19(3): 391-405.
[38]	Sell-Kubiak E, Dobrzanski J, Derks MFL, et al. Meta-analysis of SNPs determining litter traits in pigs [J]. Genes, 2022, 13(10): 1730.
[39]	孙敬春. 基于基因组变异信息鉴定大白猪繁殖性状关键候选基因的研究 [D]. 杨凌: 西北农林科技大学, 2023.
	Sun JC. Identification of key candidate genes for reproductive traits in large white pigs based on genomic variation information [D]. Yangling: Northwest A & F University, 2023.
[40]	Sun J, Wang CY, Wu Y, et al. Association analysis of METTL23 gene polymorphisms with reproductive traits in kele pigs [J]. Genes, 2024, 15(8): 1061.
[41]	Liu ZZ, Yang J, Li H, et al. Identifying candidate genes for short gestation length trait in Chinese Qingping pigs by whole-genome resequencing and RNA sequencing [J]. Front Genet, 2022, 13: 857705.
[42]	Zhang ZP, Xing SY, Qiu A, et al. The development of a porcine 50K SNP panel using genotyping by target sequencing and its application [J]. J Integr Agric, 2025, 24(5): 1930-1943.
[43]	Konte AF, Belous AA, Volkova VV, et al. Estimation of breeding value of large white pigs based on the application of a mixed model [J]. Pig-Breeding, 2024(3): 9-13.
[44]	Lopes MS, Bovenhuis H, Son MV, et al. Using markers with large effect in genetic and genomic predictions [J]. J Anim Sci, 2017, 95(1): 59-71.
[45]	Mészárosová M. Linkage disequilibrium, genomic inbreeding and effective populations size to unravel population history [J]. Acta Fytotechn Zootechn, 2021, 24(2): 161-166.
[46]	Liu X, Wang LG, Liang J, et al. Genome-wide association study for certain carcass traits and organ weights in a large white × Minzhu intercross porcine population [J]. J Integr Agric, 2014, 13(12): 2721-2730.
[47]	Tong XK, Chen D, Hu JC, et al. Accurate haplotype construction and detection of selection signatures enabled by high quality pig genome sequences [J]. Nat Commun, 2023, 14: 5126.
[48]	Utsunomiya YT, do Carmo AS, Carvalheiro R, et al. Genome-wide association study for birth weight in Nellore cattle points to previously described orthologous genes affecting human and bovine height [J]. BMC Genet, 2013, 14: 52.
[49]	Onteru SK, Fan B, Nikkilä MT, et al. Whole-genome association analyses for lifetime reproductive traits in the pig [J]. J Anim Sci, 2011, 89(4): 988-995.
[50]	Tang ZS, Xu JY, Yin LL, et al. Genome-wide association study reveals candidate genes for growth relevant traits in pigs [J]. Front Genet, 2019, 10: 302.
[51]	Luo WZ, Cheng DX, Chen SK, et al. Genome-wide association analysis of meat quality traits in a porcine large white × Minzhu intercross population [J]. Int J Biol Sci, 2012, 8(4): 580-595.

繁殖性状 Reproductive traits	候选基因名称 Candidate genes	参考文献 Reference
总产仔数 Total number of born piglets	JARID2， PDIA6， FLRT2， DICER1	［33］
	SMAD4， RPS6KA2， CAMK2A， NDST1， ADCY5	［14］
	CLCN3， CBR4， HPF1， FAM174A， SCP2， CLIC1， NKAIN2， ZFYVE9	［34］
	SCC7	［35］
产活仔数 Number of alive born piglets	LIF	［36］
	IL17RA	［37］
	SPATA33， KIF5C， EPC2	［34］
	SOSTDC1	［38］
断奶仔数 Number of weaned piglets	DGCR8	［39］
	METTL23	［40］
妊娠期长度 Gestation period length	EGFR	［41］
妊娠期长度 Gestation period length	GSK3B， DLX4， DLX3， RGS18	［14］
产活窝重 Litter weight born alive	GABRA2， GABRA4， SPATA33	［34］
死胎数 Piglets born dead	PRKD1	［38］

繁殖性状 Reproductive traits	候选基因名称 Candidate genes	参考文献 Reference
总产仔数 Total number of born piglets	JARID2， PDIA6， FLRT2， DICER1	［33］
	SMAD4， RPS6KA2， CAMK2A， NDST1， ADCY5	［14］
	CLCN3， CBR4， HPF1， FAM174A， SCP2， CLIC1， NKAIN2， ZFYVE9	［34］
	SCC7	［35］
产活仔数 Number of alive born piglets	LIF	［36］
	IL17RA	［37］
	SPATA33， KIF5C， EPC2	［34］
	SOSTDC1	［38］
断奶仔数 Number of weaned piglets	DGCR8	［39］
	METTL23	［40］
妊娠期长度 Gestation period length	EGFR	［41］
妊娠期长度 Gestation period length	GSK3B， DLX4， DLX3， RGS18	［14］
产活窝重 Litter weight born alive	GABRA2， GABRA4， SPATA33	［34］
死胎数 Piglets born dead	PRKD1	［38］