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Integrated GWAS and eQTL Colocalization Identified Candidate Genes for Growth Traits in Pigs
Xiangzi Wu1,2, Junjing Wu1, Yiren Gu2
1Key Laboratory of Animal Embryo Engineering and Molecular Breeding of Hubei Province, Institute of Animal Sciences and Veterinary Medicine, Hubei Academy of Agricultural Sciences, Wuhan 430064, China.
Biology
|July 28, 2026
Summary
This study identifies novel genes influencing pig growth traits like age to 120 kg, backfat thickness, and loin muscle depth. These findings enhance understanding of pig genetics for improved breeding applications.
Area of Science:
- Animal Genetics
- Quantitative Genetics
- Genomic Selection
Background:
- Growth traits are crucial economic indicators in pig breeding, impacting production costs and carcass quality.
- Genetic improvement of growth traits is a primary focus in swine agriculture.
- Understanding the genetic basis of these traits is essential for efficient breeding programs.
Purpose of the Study:
- To identify candidate genes associated with key pig growth traits: Age to 120 kg live weight (AGE120), Backfat thickness at 120 kg (BF120), and Loin muscle depth at 120 kg (LMD120).
- To leverage genome-wide association studies (GWAS) and expression Quantitative Trait Locus (eQTL) colocalization for robust gene discovery.
- To provide a foundation for future functional validation and molecular breeding in pigs.
Main Methods:
- Collected ear tissue samples from 3364 pigs across three breeds (Large White, Landrace, Duroc).
- Performed genotyping using an 80K functional site array, followed by SNP imputation to obtain over 15 million loci.
- Conducted GWAS using a mixed linear model and integrated results with eQTL data from the PigGTEx database for colocalization analysis.
Main Results:
- Identified five previously reported genes (TAF11, ZC3HAV1L, ANKS1A, USP20, TBC1D1) associated with pig growth.
- Discovered a set of novel candidate genes, including ZNF215, UBE2Z, HOXB7, SARDH, ADAMTSL2, ATP6V0A4, RPL10A, PGM2, and RELL1.
- These genes are implicated in the genetic architecture of pig growth traits at heavy body weights.
Conclusions:
- Integrated GWAS and eQTL analyses successfully identified novel candidate genes for pig growth traits.
- The identified genes contribute to understanding the genetic basis of economically important traits in pigs.
- These findings support future functional studies and applications in molecular breeding for enhanced pig production.
