Background: Improving feed efficiency is the most important goal for modern animal production. The regulatory mechanisms of controlling feed efficiency traits are extremely complex and include the functions related to host genetics and gut microbiota. Short-chain fatty acids (SCFAs), as significant metabolites of microbiota, could be used to refine the combined effect of host genetics and gut microbiota. However, the association of SCFAs with the gut microbiota and host genetics for regulating feed efficiency is far from understood. Results: In this study, 464 broilers were housed for RFI measuring and examining the host genome sequence. And 300 broilers were examined for cecal microbial data and SCFA concentration. Genome-wide association studies (GWAS) showed that four out of seven SCFAs had significant associations with genome variants. One locus (chr4: 29414391–29417189), located near or inside the genes MAML3, SETD7, and MGST2, was significantly associated with propionate and had a modest effect on feed efficiency traits and the microbiota. The genetic effect of the top SNP explained 8.43% variance of propionate. Individuals with genotype AA had significantly different propionate concentrations (0.074 vs. 0.131 μg/mg), feed efficiency (FCR: 1.658 vs. 1.685), and relative abundance of 14 taxa compared to those with the GG genotype. Christensenellaceae and Christensenellaceae_R-7_group were associated with feed efficiency, propionate concentration, the top SNP genotypes, and lipid metabolism. Individuals with a higher cecal abundance of these taxa showed better feed efficiency and lower concentrations of caecal SCFAs. Conclusion: Our study provides strong evidence of the pathway that host genome variants affect the cecal SCFA by influencing caecal microbiota and then regulating feed efficiency. The cecal taxa Christensenellaceae and Christensenellaceae_R-7_group were identified as representative taxa contributing to the combined effect of host genetics and SCFAs on chicken feed efficiency. These findings provided strong evidence of the combined effect of host genetics and gut microbial SCFAs in regulating feed efficiency traits.

China has the richest local chicken breeding resources in the world and is the world’s second largest producer of meat-type chickens. Development of a moderate-density SNP array for genetic analysis of chickens and breeding of meat-type chickens taking utility of those resources is urgently needed for conventional farms, breeding industry, and research areas. Eight representative local breeds or commercial broiler lines with 3 pools of 48 individuals within each breed/line were sequenced and supplied the major SNPs resource. There were 7.09 million - 9.41 million SNPs detected in each breed/line. After filtering using multiple criteria such as preferred incorporation of trait-related SNPs and uniformity of distribution across the genome, 52.18 K SNPs were selected in the final array. It consists of: (i) 19.22 K SNPs from the genomes of yellow-feathered, cyan-shank partridge and white-feathered chickens; (ii) 5.98 K SNPs related to economic traits from the Illumina 60 K SNP Bead Chip, which were found as significant associated SNPs with 15 traits in a Beijing-You crossed Cobb F2 resource population by genome-wide association study analysis; (iii) 7.63 K SNPs from 861 candidate genes of economic traits; (iv) the 0.94 K SNPs related to residual feed intake; and (v) 18.41 K from chicken SNPdb. The polymorphisms of 9 extra local breeds and 3 commercial lines were examined with this array, and 40 K - 47 K SNPs were polymorphic (with minor allele frequency > 0.05) in those breeds. The MDS result showed that those breeds can be clearly distinguished by this newly developed genotyping array. We successfully developed a 55K genotyping array by using SNPs segregated from typical local breeds and commercial lines. Compared to the existing Affy 600 K and Illumina 60 K arrays, there were 21,41 K new SNPs included on our Affy 55K array. The results of the 55K genotyping data can therefore be imputed to high-density SNPs genotyping data. The array offers a wide range of potential applications such as genomic selection breeding, GWAS of interested traits, and investigation of diversity of different chicken breeds.

Skeletal muscle satellite cells (MSC) are crucial for postnatal growth and regeneration of skeletal muscle. An interaction exists between MSC and intramuscular preadipocytes (IMPA). This study is the first to investigate the effects of IMPA on MSC in chickens and unveil the molecular mechanisms by transcriptome analysis. Primary MSC and IMPA were isolated from the pectoralis major muscle of 7-day-old chickens. After both cell types reached confluence, MSC were cultured alone or co-cultured with IMPA for 2 or 4 d. MSC treated for 2 d were subjected to RNA-seq. A total of 1653 known differentially expressed genes (DEG) were identified between co-cultured and mono-cultured MSC (|log2 FC| ≥ 1, FDR < 0.01). Based on Gene Ontology analysis, 48 DEG related to muscle development were screened, including the key genes MYOD1, MYOG, PAX7, and TMEM8C. The 44 DEG related to lipid deposition included the key genes CD36, FABP4, ACSBG2, CYP7A1 and PLIN2. Most of the DEG related to muscle development were downregulated in co-cultured MSC, and DEG related to lipid deposition were upregulated. Immunofluorescence of MHC supported IMPA impeding differentiation of MSC, and Oil Red O staining showed concurrent promotion of lipid deposition. Pathway analysis found that several key genes were enriched in JNK/MAPK and PPAR signaling, which may be the key pathways regulating differentiation and lipid deposition in MSC. Additionally, pathways related to cell junctions may also contribute to the effect of IMPA on MSC. The present study showed that IMPA impeded differentiation of MSC while promoting their lipid deposition. Pathway analysis indicated that IMPA might inhibit differentiation via the JNK/MAPK pathway, and promote lipid deposition via the PPAR pathway. This study supplies insights into the effect of IMPA on MSC, providing new clues on exposing the molecular mechanisms underlying the interplay between skeletal muscle and intramuscular fat in chickens.

Exploring the genetic loci underlying economic traits is foundational for innovation in modern animal breeding technology. Genome‐wide association studies (GWAS) have been valid and commonly used tools to dissect the genomic variants associated with phenotypes for the past ∼20 years and have contributed to our understanding of genetic and molecular bases of various traits. Here, we comprehensively review the recent research progress on GWAS methods. We highlight the methodological advancements enabled by the combination of new proteome, transcriptome, epigenome, and metagenome information and multi‐omics analysis algorithms. The advances in GWAS investigations of chickens, pigs, cattle, and other animals during the last 5 years are also described. Finally, we discuss the current applications of GWAS in cutting‐edge breeding technologies and overall future perspectives of the post‐GWAS era.

Fatty liver is a widespread disease in chickens that causes a decrease in egg production and even death. The characteristics of the inherited phenotype of acquired fatty liver and the molecular mechanisms underlying it, however, are largely unknown. In the current study, fatty liver was induced in 3 breeds by a high-fat (HF) diet and a methionine choline-deficient (MCD) diet. The results showed that the dwarf Jingxing-Huang (JXH) chicken was more susceptible to fatty liver compared with the layer White Leghorns (WL) and local Beijing-You (BJY) breeds. In addition, it was found that the paternal fatty livers induced by HF diet in JXH chickens were inherited. Compared to birds without fatty liver in the control group, both offsprings and their sires with fatty livers in the paternal group exhibited altered hepatic gene expression profiles, including upregulation of several key genes involved in fatty acid metabolism, lipid metabolism and glucose metabolism (ACACA, FASN, SCD, ACSL5, FADS2, FABP1, APOA4 and ME1). This study uniquely revealed that acquired fatty liver in cocks can be inherited. The hepatic gene expression profiles were altered in chickens with the inherited phenotype of acquired paternal fatty liver and several genes could be candidate biomarkers.

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.