Background: As one of the most important poultry species worldwide, chickens provide substantial amounts of meat, eggs, and other products for human consumption. With continuous improvements in living standards, consumer demand for high-quality animal products is increasing, making it essential to understand the genetic basis of key traits such as egg production, meat quality, and disease resistance for targeted genetic improvement. Methods: In this study, a number of the candidate genes associated with important traits in chickens were screened by various comparative genomics analysis methods. To further clarify the relationship between these candidate genes and important traits in chickens, they were functionally annotated through the KOG, GO, and KEGG databases. Results: These candidate genes are mainly concentrated in the functional categories of transcription and signal transduction mechanisms and are involved in biological processes such as cyclic nucleotide biosynthesis and intracellular signaling, which involve signaling pathways such as ECM–receptor interactions and calcium signaling. Conclusions: Based on the annotation results from various databases, a functional search of the candidate genes and related literature reports, the following results were obtained: genes such as TBX22, LCORL, and GH were associated with chicken growth traits; genes such as A-FABP, H-FABP, and PRKAB2 were associated with chicken meat quality; genes such as IGF-1, SLC25A29, and WDR25 were associated with chicken reproductive traits; and genes such as C1QBP, VAV2 and IL12B were associated with chicken disease resistance traits. Overall, the findings of this study provide novel insights and candidate genes for genetic improvements in chickens, laying a foundation for future research and breeding strategies targeting key economic traits.

Excessive abdominal fat deposition accompanying rapid growth in broiler chickens seriously affects production efficiency. Using divergently selected broiler lines from Northeast Agricultural University, we integrated transcriptome sequencing, whole-genome resequencing, and three-dimensional genomic data to identify key SNPs affecting abdominal fat deposition. From 3,850,758 initial SNPs, 22,721 high-quality SNPs were selected (|ΔAF| ≥ 0.9) and validated to obtain 7341 reliable SNPs. GWAS identified 16 SNPs significantly associated with abdominal fat weight, while LD analysis revealed 22 highly linked SNPs, finally determining 2302 candidate SNPs. Transcriptome analysis identified 825 differentially expressed genes (p ≤ 0.05, |FC| ≥ 1.5). Functional annotation revealed 201 SNPs located in differentially expressed gene regions, including 8 coding SNPs and 193 non-coding SNPs, with an additional 15 SNPs potentially regulating through long-range chromatin interactions. Mechanistic analysis showed that coding SNPs regulate gene expression by altering codon translation rates or mRNA stability, while non-coding SNPs regulate transcription by affecting transcription factor binding. Phenotypic association analysis demonstrated that all 213 SNPs can cause ≥2-fold differences in abdominal fat weight, with 182 SNPs causing ≥3-fold differences. This study successfully identified 213 functional SNPs affecting abdominal fat deposition in broilers and revealed their molecular basis for regulating fat metabolism through multiple mechanisms, providing important genetic markers for low-fat breeding in broilers.

The objective of this study was to characterize the genetic basis of metatarsal length (MeL) and circumference (MeC), identify candidate loci and genes associated with these traits, and evaluate the predictive utility of integrated candidate-marker sets for broiler leg traits. A total of 330 male broilers phenotyped at 49 days of age and subjected to whole-genome resequencing were used for the analyses. Genomic heritability estimates were 0.266 for MeL and 0.516 for MeC. Single-trait GWAS identified 102 and 165 suggestive SNPs for MeL and MeC, respectively, while bivariate analysis identified 263 SNPs, including 159 not detected by either single-trait analysis. Integration with genetic differentiation and nucleotide diversity prioritized 55 candidate SNPs for MeL and 62 for MeC, with three loci shared between the two traits. Linkage disequilibrium refinement and functional annotation identified 120 candidate variants and 64 candidate genes, including APP, LDB3, ADH6, MTTP, and a missense variant in ANKRD50. Across six models, mean heritability-adjusted prediction estimates ranged from 0.197 to 0.230 for MeL and 0.273 to 0.322 for MeC. Exploratory within-population analyses indicated that the candidate-marker sets were enriched for trait-relevant predictive information. These results provide insights into the genetic architecture of broiler leg traits and provide candidate markers for further validation and evaluation in genomic prediction.

Broilers are one of the most important sources of animal protein worldwide due to their rapid growth rate and high feed efficiency. However, excessive abdominal fat deposition in broilers reduces feed efficiency and carcass quality, resulting in substantial economic losses to the poultry industry. In previous studies, we have demonstrated that connective tissue growth factor (CTGF) is a key gene affecting chicken fat deposition, but its specific molecular mechanism is still unclear. This study aimed to identify functional single-nucleotide polymorphisms (SNPs) within the CTGF gene associated with abdominal fat deposition and to elucidate their potential regulatory mechanisms in broilers. Whole-genome resequencing data from the 19th generation of broiler lines divergently selected for abdominal fat content were used to identify SNPs within CTGF and its flanking regions (±3 kb). Association analyses between SNPs and abdominal fat traits, including abdominal fat weight (AFW) and abdominal fat percentage (AFP), were subsequently performed. Seven SNPs were significantly associated with AFW and AFP, among which four were further validated as functional SNPs by Reverse Transcription Quantitative Polymerase Chain Reaction (RT-qPCR) and luciferase reporter assay, including g + 516T > C, g + 954T > C, g − 982A > G, and g *2702A > T. The results of RT-qPCR indicated that the exonic SNPs g + 516T > C and g + 954T > C may regulate CTGF expression by altering mRNA secondary structure stability. The SNP g − 982A > G, located in the 5′ flanking region, may affect CTGF transcriptional activity through allele-dependent responses to transcription factors CCAAT/enhancer-binding protein alpha (C/EBPα), upstream stimulatory factor 1 (USF1), and MYC-associated factor X (MAX). In addition, the SNP g *2702A > T, located in the 3′ flanking region, may influence CTGF regulation by affecting a potential gga-miR-1812-5p-responsive element. These findings improve our understanding of the genetic mechanisms underlying abdominal fat deposition and provide potential molecular markers for marker-assisted selection for abdominal fat content in broiler breeding programs.