Abstract
Background: 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” efects is expected to control BW. To
detect such efects, 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.
Methods: 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 signifcant SNPs. A Bayesian ridge regression model was implemented, using AlphaBayes, to estimate the
contribution to the total genetic variance of each region harbouring signifcant SNPs (1 Mb up/downstream) and the
combined regions harbouring non-signifcant SNPs.
Results: GWAS revealed 25 genomic regions harbouring 96 signifcant 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 signifcant SNPs that explained
the largest portion of the total genetic variance (4.37%) was on GGA4 (~65.67–66.31 Mb).
Conclusions: 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 identifed regions, which showed a strong association with BW, the high proportion of genetic
variance attributed to regions harbouring non-signifcant 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.