Wen Jintian, Zheng Ming, Wang Zhaochuan, Hu Xiaoxiang, Li Zhenhui
State Key Laboratory of Swine and Poultry Breeding Industry, South China Agricultural University, Guangzhou 510642, China.
Guangdong Laboratory for Lingnan Modern Agriculture, College of Animal Science, South China Agricultural University, Guangzhou 510642, China.
Genes (Basel). 2025 Aug 11;16(8):945. doi: 10.3390/genes16080945.
Genome-wide association studies (GWAS) have been extensively employed to elucidate the genetic architecture of body weight (BW) traits in chickens, which represent key economic indicators in broiler production. With the growing availability of genomic data from diverse commercial and resource chicken populations, a critical challenge lies in how to effectively integrate these datasets to enhance sample size and thereby improve the statistical power for detecting genetic variants associated with complex traits.
In this study, we performed a multi-population GWAS meta-analysis on BW traits across three genetically distinct chicken populations, focusing on BW at 56, 70, and 84 days of age: P1 (N301 Yellow Plumage Dwarf Chicken Line; = 426), P2 (F2 reciprocal cross: High Quality Line A × Huiyang Bearded chicken; = 494), and P3 (F2 cross: Black-bone chicken × White Plymouth Rock; = 223).
Compared to single-population GWAS, our meta-analysis identified 77 novel independent variants significantly associated with BW traits, while gene-based association analysis implicated 59 relevant candidate genes. Functional annotation of BW56- and BW84-associated SNPs (single-nucleotide polymorphisms) 1_170526144G>T and 1_170642110A>G, integrated with tissue-specific regulatory annotations, revealed significant enrichment of enhancer and promoter elements for and in muscle, adipose, and intestinal tissues. Through this meta-analysis and integrative genomics approach, we identified novel candidate genes associated with body weight traits in chickens.
These findings provide valuable mechanistic insights into the genetic mechanisms underlying body weight regulation in poultry and offer important references for selective breeding strategies aimed at improving production efficiency in the poultry industry.
全基因组关联研究（GWAS）已被广泛用于阐明鸡体重（BW）性状的遗传结构，鸡体重是肉鸡生产中的关键经济指标。随着来自不同商业和资源鸡群的基因组数据越来越多，一个关键挑战在于如何有效整合这些数据集以增加样本量，从而提高检测与复杂性状相关的遗传变异的统计功效。
在本研究中，我们对三个遗传上不同的鸡群的BW性状进行了多群体GWAS荟萃分析，重点关注56、70和84日龄的BW：P1（N301黄羽矮小鸡系；n = 426）、P2（F2正反交：优质系A×惠阳胡须鸡；n = 494）和P3（F2杂交：乌鸡×白洛克鸡；n = 223）。
与单群体GWAS相比，我们的荟萃分析确定了77个与BW性状显著相关的新的独立变异，而基于基因的关联分析涉及59个相关候选基因。与BW56和BW84相关的单核苷酸多态性（SNP）1_170526144G>T和1_170642110A>G的功能注释，结合组织特异性调控注释，揭示了在肌肉、脂肪和肠道组织中， 和 的增强子和启动子元件显著富集。通过这种荟萃分析和综合基因组学方法，我们鉴定了与鸡体重性状相关的新候选基因。
这些发现为家禽体重调节的遗传机制提供了有价值的机制性见解，并为旨在提高家禽业生产效率的选择性育种策略提供了重要参考。
