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Abstract Background Feed accounts for about 70% of the total cost of poultry meat production. Residual feed intake (RFI) has become the preferred measure of feed efficiency because it is phenotypically independent of growth rate and body weight. In this study, our aim was to estimate genetic parameters and identify quantitative trait loci (QTL) for feed efficiency in 3314 purebred broilers using a genome-wide association study. Broilers were genotyped using a custom 55 K single nucleotide polymorphism (SNP) array. Results Estimates of genomic heritability for seven growth and feed efficiency traits, including body weight at 28 days of age (BW28), BW42, average daily feed intake (ADFI), RFI, and RFI adjusted for weight of abdominal fat (RFIa), ranged from 0.12 to 0.26. Eleven genome-wide significant SNPs and 15 suggestively significant SNPs were detected, of which 19 clustered around two genomic regions. A region on chromosome 16 (2.34–2.66 Mb) was associated with both BW28 and BW42, and the most significant SNP in this region, AX_101003762, accounted for 7.6% of the genetic variance of BW28. The other region, on chromosome 1 (91.27–92.43 Mb) was associated with RFI and ADFI, and contains the NSUN3 and EPHA6 as candidate genes. The most significant SNP in this region, AX_172588157, accounted for 4.4% of the genetic variance of RFI. In addition, a genomic region containing the gene AGK on chromosome 1 was found to be associated with RFIa. The NSUN3 and AGK genes were found to be differentially expressed in breast muscle, thigh muscle, and abdominal fat between male broilers with high and low RFI. Conclusions We identified QTL regions for BW28 and BW42 (spanning 0.32 Mb) and RFI (spanning 1.16 Mb). The NSUN3, EPHA6, and AGK were identified as the most likely candidate genes for these QTL. These genes are involved in mitochondrial function and behavioral regulation. These results contribute to the identification of candidate genes and variants for growth and feed efficiency in poultry.

Abstract Background Salmonella infection is a serious concern in poultry farming because of its impact on both economic loss and human health. Chicks aged 20 days or less are extremely vulnerable to Salmonella pullorum (SP), which causes high mortality. Furthermore, an outbreak of SP infection can result in a considerable number of carriers that become potential transmitters, thus, threatening fellow chickens and offspring. In this study, we conducted a genome-wide association study (GWAS) to detect potential genomic loci and candidate genes associated with two disease-related traits: death and carrier state. Methods In total, 818 birds were phenotyped for death and carrier state traits through a SP challenge experiment, and genotyped by using a 600 K high-density single nucleotide polymorphism (SNP) array. A GWAS using a single-marker linear mixed model was performed with the GEMMA software. RNA-sequencing on spleen samples was carried out for further identification of candidate genes. Results We detected a region that was located between 33.48 and 34.03 Mb on chicken chromosome 4 and was significantly associated with death, with the most significant SNP (rs314483802) accounting for 11.73% of the phenotypic variation. Two candidate genes, FBXW7 and LRBA, were identified as the most promising genes involved in resistance to SP. The expression levels of FBXW7 and LRBA were significantly downregulated after SP infection, which suggests that they may have a role in controlling SP infections. Two other significant loci and related genes (TRAF3 and gga-mir-489) were associated with carrier state, which indicates a different polygenic determinism compared with that of death. In addition, genomic inbreeding coefficients showed no correlation with resistance to SP within each breed in our study. Conclusions The results of this GWAS with a carefully organized Salmonella challenge experiment represent an important milestone in understanding the genetics of infectious disease resistance, offer a theoretical basis for breeding SP-resistant chicken lines using marker-assisted selection, and provide new information for salmonellosis research in humans and other animals.