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Abstract Background Improving feed efficiency (FE) is one of the main objectives in broiler breeding. It is difficult to directly measure FE traits, and breeders hence have been trying to identify biomarkers for the indirect selection and improvement of FE traits. Metabolome is the "bridge" between genome and phenome. The metabolites may potentially account for more of the phenotypic variation and can suitably serve as biomarkers for selecting FE traits. This study aimed to identify plasma metabolite markers for selecting high-FE broilers. A total of 441 birds from Northeast Agricultural University broiler lines divergently selected for abdominal fat content were used to analyze plasma metabolome and estimate the genetic parameters of differentially expressed metabolites. Results The results identified 124 differentially expressed plasma metabolites (P

Abstract KLF3 is a member of the Kruppel‐like factor (KLF) family of transcription factors, and plays an important role in several biological processes, including adipogenesis, erythropoiesis and B‐cell development. The purposes of this study are to search for polymorphisms of KLF3 coding region and to provide functional evidence for abdominal fat in chickens. A total of 168 SNPs in KLF3 coding region were detected in a unique chicken population, the Northeast Agricultural University broiler lines divergently selected for abdominal fat content (NEAUHLF). Of which three single nucleotide polymorphisms (g.3452T > C, g.8663A > G and g.10751G > A) were significantly correlated with abdominal fat weight (AFW) and abdominal fat percentage (AFP) of 329 birds from the 19th generation of NEAUHLF (FDR A (p A is a functional variant that potential would be applied to marker‐assisted selection (MAS) for selective breeding programme.

Feed consumption represents a major cost in poultry production and improving feed efficiency is one of the important goals in breeding strategies. The present study aimed to analyze the relationship between feed efficiency and relevant traits and find the proper selection method for improving feed efficiency by using the Northeast Agricultural University High and Low Fat broiler lines that were divergently selected for abdominal fat content. A total of 899 birds were used to measure the feed intake (FI), abdominal fat weight (AFW), and body weight traits. The abdominal fat percentage (AFP), feed conversion ratio (FCR), and the residual feed intake (RFI) were calculated for each individual broiler. The differences in the AFW, AFP, and in traits relevant to feed efficiency, such as FCR and RFI, between the fat line and the lean line were analyzed, and the genetic parameters were estimated for AFW, AFP, and feed efficiency relevant traits. The results showed that AFW, AFP, body weight gain (BWG), FI, FCR, and RFI were significantly higher in the fat line compared with the lean line. The heritability of FI, BWG, FCR, RFI, AFW, and AFP were 0.45, 0.28, 0.36, 0.38, 0.33, and 0.30, respectively. Both FCR and RFI showed high positive genetic correlations with FI, AFW, and AFP and relatively low, negative genetic correlations with BWG. The RFI showed much higher positive genetic correlation with the abdominal fat traits than FCR. In addition, the FCR showed negative genetic correlation with body weight of 4 wk (BW4) and 7 wk (BW7), whereas RFI showed positive genetic correlation with BW4 and BW7. The results showed that both RFI and FCR could be used for improving feed efficiency. When selecting against RFI, the AFP could be significantly reduced, and by selecting against FCR, the body weight could be improved simultaneously.

Rapid growth is one of the most important economic traits in broiler breeding programs. Identifying markers and genes for growth traits may not only benefit marker-assisted selection (MAS)/genomic selection (GS) but also provide important information for understanding the genetic architecture of growth traits in broilers. In the present study, an F2 resource population derived from a cross between the broiler and Baier yellow chicken (a Chinese local breed) was used and body weights from 1 to 12 weeks of age [body weight (BW) 1–BW12)] were measured. A total of 519 F2 birds were genome re-sequenced, and a combination of genome-wide association study (GWAS) and selective sweep analysis was carried out to characterize the genetic architecture affecting chicken body weight comprehensively. As a result, 1,539 SNPs with significant effects on body weights at different weeks of age were identified using a genome-wide efficient mixed-model association (GEMMA) package. These SNPs were distributed on chromosomes 1 and 4. Besides, windows under selection identified for BW1–BW12 varied from 1,581 to 2,265. A total of 42 genes were also identified with significant effects on BW1–BW12 based on both GWAS and selective sweep analysis. Among these genes, diacylglycerol kinase eta (DGKH), deleted in lymphocytic leukemia (DLEU7), forkhead box O17 (FOXO1), karyopherin subunit alpha 3 (KPNA3), calcium binding protein 39 like (CAB39L), potassium voltage-gated channel interacting protein 4 (KCNIP4), and slit guidance ligand 2 (SLIT2) were considered as important genes for broiler growth based on their basic functions. The results of this study may supply important information for understanding the genetic architecture of growth traits in broilers.