Body weight (BW) is an economically important trait in the broiler (meat-type chickens) industry. Under the assumption of polygenicity, a “large” number of genes with “small” effects is expected to control BW. To detect such effects, a large sample size is required in genome-wide association studies (GWAS). Our objective was to conduct a GWAS for BW measured at 35 days of age with a large sample size. The GWAS included 137,343 broilers spanning 15 pedigree generations and 392,295 imputed single nucleotide polymorphisms (SNPs). A false discovery rate of 1% was adopted to account for multiple testing when declaring significant SNPs. A Bayesian ridge regression model was implemented, using AlphaBayes, to estimate the contribution to the total genetic variance of each region harbouring significant SNPs (1 Mb up/downstream) and the combined regions harbouring non-significant SNPs. GWAS revealed 25 genomic regions harbouring 96 significant SNPs on 13 Gallus gallus autosomes (GGA1 to 4, 8, 10 to 15, 19 and 27), with the strongest associations on GGA4 at 65.67–66.31 Mb (Galgal4 assembly). The association of these regions points to several strong candidate genes including: (i) growth factors (GGA1, 4, 8, 13 and 14); (ii) leptin receptor overlapping transcript (LEPROT)/leptin receptor (LEPR) locus (GGA8), and the STAT3/STAT5B locus (GGA27), in connection with the JAK/STAT signalling pathway; (iii) T-box gene (TBX3/TBX5) on GGA15 and CHST11 (GGA1), which are both related to heart/skeleton development); and (iv) PLAG1 (GGA2). Combined together, these 25 genomic regions explained ~ 30% of the total genetic variance. The region harbouring significant SNPs that explained the largest portion of the total genetic variance (4.37%) was on GGA4 (~ 65.67–66.31 Mb). To the best of our knowledge, this is the largest GWAS that has been conducted for BW in chicken to date. In spite of the identified regions, which showed a strong association with BW, the high proportion of genetic variance attributed to regions harbouring non-significant SNPs supports the hypothesis that the genetic architecture of BW35 is polygenic and complex. Our results also suggest that a large sample size will be required for future GWAS of BW35.

中文翻译：

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对 137,343 只肉鸡测量的 35 天体重进行全基因组关联分析


体重 (BW) 是肉鸡（肉用鸡）行业的一个重要经济性状。在多基因性的假设下，预计“大量”具有“小”效应的基因可以控制体重。为了检测这种效应，全基因组关联研究（GWAS）需要大样本量。我们的目标是对 35 日龄时测量的体重进行 GWAS，样本量较大。 GWAS 包括跨越 15 个谱系代的 137,343 只肉鸡和 392,295 个估算的单核苷酸多态性 (SNP)。在宣布重要的 SNP 时，采用 1% 的错误发现率来解释多次测试。使用 AlphaBayes 实施贝叶斯岭回归模型，以估计包含显着 SNP（1 Mb 上游/下游）的每个区域和包含不显着 SNP 的组合区域对总遗传方差的贡献。 GWAS 揭示了 13 个原鸡常染色体（GGA1 至 4、8、10 至 15、19 和 27）上的 25 个基因组区域含有 96 个显着 SNP，其中与 GGA4 的关联性最强，位于 65.67-66.31 Mb（Galgal4 组装）。这些区域的关联指向几个强大的候选基因，包括： (i) 生长因子（GGA1、4、8、13 和 14）； (ii) 瘦素受体重叠转录物 (LEPROT)/瘦素受体 (LEPR) 基因座 (GGA8) 和 STAT3/STAT5B 基因座 (GGA27)，与 JAK/STAT 信号传导途径有关； (iii) GGA15和CHST11(GGA1)上的T-box基因(TBX3/TBX5)，这两者都与心脏/骨骼发育有关)； (iv) PLAG1 (GGA2)。这 25 个基因组区域加在一起解释了约 30% 的总遗传变异。具有显着 SNP 的区域可以解释总遗传变异的最大部分 (4.37%)，该区域位于 GGA4 (~ 65.67–66.31 Mb)。 据我们所知，这是迄今为止针对鸡肉 BW 进行的最大规模的 GWAS。尽管已识别的区域显示出与 BW 密切相关，但归因于包含不显着 SNP 的区域的高比例遗传变异支持了 BW35 的遗传结构是多基因且复杂的假设。我们的结果还表明，BW35 的未来 GWAS 将需要大样本量。