Genetic Pleiotropy and Its Research Progress in the Genetic Dissection of Key Economic Traits in Livestock and Poultry

doi:10.13560/j.cnki.biotech.bull.1985.2025-1208

Abstract

Abstract:

Genetic pleiotropy refers to the biological phenomenon in which a single gene or genetic variation simultaneously influences multiple phenotypic traits or diseases. With the rapid development of omics technology, pleiotropy research has achieved significant advances in revealing the genetic basis and molecular mechanisms of human complex traits and diseases, and a large number of pleiotropic genes and functional genetic variant sites have been identified. Important economical traits in livestock and poultry are predominantly complex in nature and commonly exhibit both phenotypic and genetic correlations, and genetic pleiotropy is one of the important mechanisms underlying this phenomenon. However, current studies on pleiotropy related to important economic traits in livestock and poultry remain relatively limited, primarily due to constraints in research strategies and technical approaches. By adapting successful methodologies from studies of human complex traits and diseases and applying them to livestock and poultry, it is conducive to deeply understanding the shared genetic architecture among correlated traits, clarifying the nature of these correlations (synergistic or antagonistic), thereby ultimately providing a robust theoretical basis for designing scientifically sound, rational, and efficient breeding programs. This review systematically summarizes the historical development, molecular mechanisms, commonly used study methods of genetic pleiotropy, and advances in the analysis of pleiotropy in important economic traits of livestock and poultry. It aims to provide references for further elucidation of the genetic basis of these traits, facilitating the discovery of pleiotropic genes and related molecular markers, and promoting genetic improvement in livestock and poultry.

Key words: livestock and poultry, important economic traits, genetic basis, pleiotropy

HAN Ya-qian, LI Hui, WANG Shou-zhi. Genetic Pleiotropy and Its Research Progress in the Genetic Dissection of Key Economic Traits in Livestock and Poultry[J]. Biotechnology Bulletin, 2026, 42(8): 47-59.

Figures/Tables 4

References 58

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分类 Category	软件 Software	许可方式 License type	编程语言 Programming language	发表年份 Publication year	优缺点 Advantages and disadvantages	网址 Website
基于个体水平数据	GEMMA	开源	C/C++	2012	运行速度快；对于非线性或非正态的表型数据估计效果不佳	https：//github.com/gemma-3/
	mvBIMBAM	开源	C/C++	2015	对样本量中等的性状估计效果较好；但输入文件复杂	https：//github.com/heejungshim/mvBIMBAM
	ASReml	付费	R	2015	功能强大；不开源，付费	http：//vsni.co.uk/software/asreml
	MTG2	开源	Fortran	2016	提供多种模型选择；对代码能力要求较高	http：//sitcs.google.com/vicw/s-hong-lcc-homecpagc/mtg2
基于GWAS汇总统计数据	CPMA	开源	R	2011	可用于三性状及以上的联合检测；结果通常只能提示多效性区域，难以对性状的效应方向以及大小进行精细解读	https：//github.com/bvoightlab/cpma
	cfdr.pleio	开源	R	2013	可实施condFDR和conjFDR两种算法，两性状可互为条件，提高统计效力；局限性在于对LD高度依赖，需要预先构建高质量LD矩阵	https：//github.com/alexploner/cfdr.pleio
	CPASSOC	开源	R	2017	SHom与SHet统计量可分别处理性状间的同质效应与异质效应；当性状间存在负相关时检测功率可减低	https：//github.com/zhangzhaoyang/CPASSOC
	CPBayes	开源	R	2018	可直接获得遗传变异多效性的后验概率；计算复杂度高	https：//cran.r-project.org/web/packages/CPBayes
	MTAG	开源	Python	2018	计算效率高，适用于大规模汇总数据；依赖于性状间的相关性	https：//github.com/JonJala/mtag
	PLACO	开源	R	2020	对微弱信号敏感；无法识别效应的方向	https：//github.com/RayDebashree/PLACO

分类 Category	软件 Software	许可方式 License type	编程语言 Programming language	发表年份 Publication year	优缺点 Advantages and disadvantages	网址 Website
基于个体水平数据	GEMMA	开源	C/C++	2012	运行速度快；对于非线性或非正态的表型数据估计效果不佳	https：//github.com/gemma-3/
	mvBIMBAM	开源	C/C++	2015	对样本量中等的性状估计效果较好；但输入文件复杂	https：//github.com/heejungshim/mvBIMBAM
	ASReml	付费	R	2015	功能强大；不开源，付费	http：//vsni.co.uk/software/asreml
	MTG2	开源	Fortran	2016	提供多种模型选择；对代码能力要求较高	http：//sitcs.google.com/vicw/s-hong-lcc-homecpagc/mtg2
基于GWAS汇总统计数据	CPMA	开源	R	2011	可用于三性状及以上的联合检测；结果通常只能提示多效性区域，难以对性状的效应方向以及大小进行精细解读	https：//github.com/bvoightlab/cpma
	cfdr.pleio	开源	R	2013	可实施condFDR和conjFDR两种算法，两性状可互为条件，提高统计效力；局限性在于对LD高度依赖，需要预先构建高质量LD矩阵	https：//github.com/alexploner/cfdr.pleio
	CPASSOC	开源	R	2017	SHom与SHet统计量可分别处理性状间的同质效应与异质效应；当性状间存在负相关时检测功率可减低	https：//github.com/zhangzhaoyang/CPASSOC
	CPBayes	开源	R	2018	可直接获得遗传变异多效性的后验概率；计算复杂度高	https：//cran.r-project.org/web/packages/CPBayes
	MTAG	开源	Python	2018	计算效率高，适用于大规模汇总数据；依赖于性状间的相关性	https：//github.com/JonJala/mtag
	PLACO	开源	R	2020	对微弱信号敏感；无法识别效应的方向	https：//github.com/RayDebashree/PLACO

物种 Species	标记、基因或基因组区域 Marker， genes or genomic regions	相关的性状 Associated traits	参考文献 Reference
鸡 Gallus gallus	IPMK	体重、采食量	［54］
	MTERF2	体重、饲料效率	［54］
	CPEB3、ACVR1、MAST2、CACNA1H	体重和产蛋数	［55］
牛 Bos taurus	RASSF6、IGFALS	体型、产犊难易、寿命、挤奶速度	［56］
	rs109234250、rs109326954	产奶量、乳脂含量、乳蛋白含量	［57］
	GC、DGAT1	产奶量和乳腺炎抗性	［57］
	SLC9A9	趾间皮炎、乳腺炎、蹄底溃疡及乳热症	［59］
	DMRT2、KANK1、DOCK8等	蹄底溃疡、白线病、趾间皮炎和子宫内膜炎	［59］
	STAT2、STAT6、DDIT3、LRP1、ARHGEF25等	皮下脂肪和内脏脂肪	［61］
	PLAG1、HMGA2等	体型、繁殖及脂肪相关性状	［62］
	MACF1、TEX2、NCAPG	胴体性状	［63］
猪 Sus scrofa	ESR1	血小板、红细胞压积等免疫性状、产仔数	［64］
	FGF6、CTC1、ROMO1	红细胞计数、血红蛋白浓度等免疫性状	［66］
	ENPP5、ENPP4、RCAN2、U6、CLIC5	阴道温度、动物体温和体温调节性状	［67］
	APK1、ANO6、UNC5C	心脏重、肝脏重、脾脏重、肺重、肾脏重、胃重	［68］
	RAMP1	掌骨骨围和骨密度	［69］
	ALGA0040260	腰肌面积和腰肌深度	［70］
	PHLPP1	平均日增重和瘦肉率	［71］
	ITGA11、TLE3、GALC	胸围、腹围和腰围	［72］
绵羊 Ovis aries	FOXI3等	羊毛性状和皮肤褶皱	［74］
	ITGA6、ANTXR1、FOXI3等	羊毛产量和羊毛质量	［75］
	TBL1X、SHROOM2、GPR143	断奶体重和1周龄体重	［77］
	PLCD4等	肉的嫩度、肉色、肌红蛋白、糖原、不饱和脂肪酸、饱和脂肪酸	［78］
	FAM3C、WNT16等	产肉量和胴体性状	［79］

物种 Species	标记、基因或基因组区域 Marker， genes or genomic regions	相关的性状 Associated traits	参考文献 Reference
鸡 Gallus gallus	IPMK	体重、采食量	［54］
	MTERF2	体重、饲料效率	［54］
	CPEB3、ACVR1、MAST2、CACNA1H	体重和产蛋数	［55］
牛 Bos taurus	RASSF6、IGFALS	体型、产犊难易、寿命、挤奶速度	［56］
	rs109234250、rs109326954	产奶量、乳脂含量、乳蛋白含量	［57］
	GC、DGAT1	产奶量和乳腺炎抗性	［57］
	SLC9A9	趾间皮炎、乳腺炎、蹄底溃疡及乳热症	［59］
	DMRT2、KANK1、DOCK8等	蹄底溃疡、白线病、趾间皮炎和子宫内膜炎	［59］
	STAT2、STAT6、DDIT3、LRP1、ARHGEF25等	皮下脂肪和内脏脂肪	［61］
	PLAG1、HMGA2等	体型、繁殖及脂肪相关性状	［62］
	MACF1、TEX2、NCAPG	胴体性状	［63］
猪 Sus scrofa	ESR1	血小板、红细胞压积等免疫性状、产仔数	［64］
	FGF6、CTC1、ROMO1	红细胞计数、血红蛋白浓度等免疫性状	［66］
	ENPP5、ENPP4、RCAN2、U6、CLIC5	阴道温度、动物体温和体温调节性状	［67］
	APK1、ANO6、UNC5C	心脏重、肝脏重、脾脏重、肺重、肾脏重、胃重	［68］
	RAMP1	掌骨骨围和骨密度	［69］
	ALGA0040260	腰肌面积和腰肌深度	［70］
	PHLPP1	平均日增重和瘦肉率	［71］
	ITGA11、TLE3、GALC	胸围、腹围和腰围	［72］
绵羊 Ovis aries	FOXI3等	羊毛性状和皮肤褶皱	［74］
	ITGA6、ANTXR1、FOXI3等	羊毛产量和羊毛质量	［75］
	TBL1X、SHROOM2、GPR143	断奶体重和1周龄体重	［77］
	PLCD4等	肉的嫩度、肉色、肌红蛋白、糖原、不饱和脂肪酸、饱和脂肪酸	［78］
	FAM3C、WNT16等	产肉量和胴体性状	［79］