The Jingyuan chicken, a local chicken breed in Ningxia, boasts advantages such as delicious meat quality and unique flavor. However, it faces challenges including slow growth rates and uneven intramuscular fat deposition. Previous studies have shown that adding 0.6% fresh corn extract (FCE) to the diet could significantly improve the meat quality of Jingyuan chickens, but the key candidate genes through which FCE affected meat quality remained unclear.

This research aimed to delve deeper into the key candidate genes influenced by FCE affecting meat quality in Jingyuan chickens, thereby providing a scientific basis for improving meat quality and optimizing meat chicken feeding strategies.

In earlier studies, 120 Jingyuan chickens at 135 days old (1.5±0.2 kg), raised under the same conditions, were divided into four groups. The control group was fed a basic diet, while the experimental groups received diets supplemented with 0.3%, 0.6%, and 0.9% FCE, respectively. After 45 days of feeding, the chickens reached 180 days old, at which point breast muscle was collected to assess meat quality, determining that the optimal addition amount was 0.6% FCE. Based on the outcomes of previous research, serum and breast muscle lipid factors were measured for the control and 0.6% FCE groups. Weighted Gene Co-expression Network Analysis (WGCNA) was utilized to conduct an in-depth analysis of the transcriptome sequencing data of breast muscle, uncovering key candidate genes significantly associated with meat quality.

The serum levels of triglycerides (TG) and very-low-density lipoproteins (VLDL) in the 0.6% FCE group were significantly higher than those in the control group (P<0.05). The TG, total cholesterol (TC), and high-density lipoproteins (HDL) in the breast muscle tissue of the 0.6% FCE group were also found to be significantly elevated (P<0.05). Through WGCNA analysis, a total of 19 co-expression modules were identified, with six target modules significantly associated with meat quality being selected: purple, midnight blue, light green, cyan, grey60, and salmon (|R²| ≥ 0.5, P<0.5). KEGG pathway enrichment analysis and Gene Ontology (GO) functional enrichment analysis of the hub genes within these modules revealed significant enrichment of the hub genes in the purple module in pathways, such as insulin signaling and mitochondrial autophagy; the midnight blue module hub genes were enriched in pyrimidine and purine metabolism; the light green module hub genes were associated with protein processing in the endoplasmic reticulum and MAPK signaling pathway; the cyan module hub genes mainly enriched pathways related to cell adhesion molecules and phagosome processes; the grey60 module hub genes were linked to vascular smooth muscle contraction and actin cytoskeleton regulation; and the salmon module hub genes enriched in MAPK signaling and p53 signaling pathways. Through comparative analyses of hub genes and differently expressed genes (DEGs), ten overlapping genes were identified. Protein interaction and functional enrichment analyses identified CLDN18, NKX2-1, and TRIB1 as key candidate genes influencing meat quality.

This study ultimately identified key candidate genes affecting meat quality, namely CLDN18, NKX2-1, and TRIB1. The findings provided a reference for understanding the molecular mechanisms by which FCE regulates meat quality and offered a new perspective for the improvement of meat quality in local chicken breeds.

Feather color is an important morphological and economic trait in poultry breeds, and understanding its genetic mechanisms is of great significance for the conservation and genetic improvement of local chicken genetic resources. The Jingyuan chicken, a distinctive local breed in China, exhibits rich diversity in feather color, providing an ideal model for studying the genetic basis of plumage coloration. Systematically exploring this genetic foundation is crucial for enhancing breeding competitiveness.

This study aimed to utilize whole-genome resequencing to identify genetic markers and candidate genes associated with black, hemp, and white feather traits in Jingyuan chickens, thereby providing a theoretical basis for elucidating the molecular mechanisms underlying feather color formation and for molecular breeding.

A total of 150 healthy 126-day-old Jingyuan hens with different feather colors(black, hemp, and white) were selected from the Jingyuan Chicken National Conservation Farm. Blood samples were collected via wing vein puncture for high-quality genomic DNA extraction, followed by whole-genome resequencing. A multi-strategy cross-validation approach was employed: four independent methods, including genetic differentiation coefficient(Fst) calculation based on sliding windows, nucleotide diversity ratio(θπ ratio) analysis, cross-population composite likelihood ratio(XP-CLR) test, and genome-wide association study(GWAS), were used to systematically screen candidate genes associated with black, hemp, and white feather colors, respectively. Venn diagrams were used to identify key significant candidate genes specific to each feather color by taking the intersection of genes identified by these methods. Furthermore, cross-population comparative analysis was conducted using Fst analysis between different feather color populations to identify significant selection signal regions associated with feather color. Gene annotation and Venn diagram intersections were used to identify core candidate genes shared across feather colors. Finally, GO functional annotation and KEGG pathway enrichment analysis were performed to systematically analyze the biological functions and regulatory networks of the identified candidate genes.

The study systematically identified several key genes associated with feather color formation in Jingyuan chickens. Black feather traits were significantly associated with the LMO3, RERGL, and RTTN, and hemp feather traits were linked to the CDH19 and SLC25A1, while white feather traits were primarily governed by the IKZF1. Cross-feather color comparative analysis further identified 15 core candidate genes: NLRC5, POT1, IPP, DCUN1D4, XRCC4, PALM2 AKAP2, UGCG, GNG10, PRIM2, SSBP2, ZBTB34, DHFR, SLC46A2, SLF1, and SHOC1. This indicated that feather color variation in Jingyuan chickens was regulated by multiple genes. Functional enrichment analysis revealed that these genes were significantly involved in important biological processes, such as the G protein-coupled receptor signaling pathway and transmembrane receptor signal transduction, forming a complex regulatory network for feather color.

Through integrated multi-omics analysis, this study identified important candidate genes associated with feather color formation in Jingyuan chickens and preliminarily revealed their potential regulatory pathways. The findings not only provided novel molecular clues and technical support for the genetic dissection of feather color traits in Jingyuan chickens, filling some gaps in the research on feather color regulation mechanisms in local chicken breeds, but also offer scientific basis and practical guidance for the precise conservation, targeted breeding, and innovative utilization of genetic resources from local high-quality chicken breeds. Furthermore, this study accumulated key data for research in frontier areas, such as the molecular pathways and genetic regulatory networks of feather pigmentation in poultry, thereby enriching the theoretical system of genetic research on functional traits in livestock and poultry.