Dataset Information

Characterization of Chicken Skin Yellowness and Exploration of Genes Involved in Skin Yellowness Deposition in Chicken.

ABSTRACT: Skin color is an important economic trait in meat-type chickens. A uniform bright skin color can increase the sales value of chicken. Chickens with bright yellow skin are more popular in China, especially in the broiler market of South China. However, the skin color of chickens can vary because of differences in breeds, diet, health, and individual genetics. To obtain greater insight into the genetic factors associated with the process of skin pigmentation in chickens, we used a colorimeter and high-resolution skin photographs to measure and analyze the skin color of chickens. By analyzing 534 chickens of the same breed, age, and feed condition, we found that the yellowness values of the chickens varied within this population. A significant positive correlation was found between the cloacal skin yellowness values before and after slaughter, and the cloacal skin yellowness value of live chickens was positively correlated with the overall body skin yellowness value. Additionally, chicken skin yellowness exhibited low heritability, ranging from 0.07 to 0.27. Through RNA sequencing, 882 genes were found to be differentially expressed between the skin with the highest and lowest yellowness values. Some of these differentially expressed genes may play an important role in yellow pigment deposition in chicken skin, which included TLR2B, IYD, SMOC1, ALDH1A3, CYP11A1, FHL2, TECRL, ACACB, TYR, PMEL, and GPR143. In addition, we found that the expression and variations of the BCO2 gene, which is referred to as the yellow skin gene, cannot be used to estimate the skin yellowness value of chickens in this population. These data will help to further our understanding of chicken skin yellowness and might contribute to the selection of specific chicken strains with consistent skin coloration.

SUBMITTER: Wu J

PROVIDER: S-EPMC8044320 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Eggs with the same total weight may have considerable differences in yolk weight. Eggs with a high percentage of yolk have a higher nutritional value, more flavor, and are more desirable to consumers. However, a large yolk proportion means more dry matter in the eggs, which reduces the feed efficiency. The elucidation of the genetic factors of yolk quantity in eggs is of scientific and practical significance. Through RNA sequencing, we explored the transcriptome of ovarian tissue from 12 Wenchang chickens, including 6 chickens that laid eggs with a high yolk percentage (32%) and 6 that laid low yolk percentage eggs (25%). We identified a total of 362 differentially expressed genes (P-value < 0.01, log2 fold change < -1, log2 fold change > 1), of which 220 were upregulated and 142 were downregulated in high yolk percentage hens. According to the Gene Ontology terms annotation and Kyoto Encyclopedia of Genes and Genomes enrichment analysis, the differentially expressed genes were associated with the regulation of various cell functions, cell differentiation and development, neuroactive ligand-receptor interactions, and calcium and ubiquitin-mediated proteolysis signaling pathways. To further filter for genes that were directly involved in yolk accumulation, the chicken quantitative trait loci database, genes within 100 kb upstream and downstream of the yolk weight trait SNP, and intersection genes in protein-protein interaction network diagrams were used to detect genes that overlapped with the differentially expressed genes. We found 7 candidate genes in total, MNR2, AOX1, ANTXRL, GRAMD1C, EEF2, COMP, and JUND, which affect female reproductive performance and the growth and development of follicles, supporting cell transport, cell proliferation, and differentiation. All candidate genes and several randomly selected genes were verified by quantitative real time PCR, and the results were consistent with the RNA sequencing. In conclusion, investigating the molecular mechanisms of high yolk percentage traits will allow breeding strategies to be optimized to alter the percentage of yolk in chicken eggs.

Project description:BACKGROUND:Fat deposits in chickens contribute significantly to meat quality attributes such as juiciness, flavor, taste and other organoleptic properties. The quantity of fat deposited increases faster and earlier in the fast-growing chickens than in slow-growing chickens. In this study, Affymetrix Genechip® Chicken Genome Arrays 32773 transcripts were used to compare gene expression profiles in liver and hypothalamus tissues of fast-growing and slow-growing chicken at 8 wk of age. Real-time RT-PCR was used to validate the differential expression of genes selected from the microarray analysis. The mRNA expression of the genes was further examined in fat tissues. The association of single nucleotide polymorphisms of four lipid-related genes with fat traits was examined in a F2 resource population. RESULTS:Four hundred genes in the liver tissues and 220 genes hypothalamus tissues, respectively, were identified to be differentially expressed in fast-growing chickens and slow-growing chickens. Expression levels of genes for lipid metabolism (SULT1B1, ACSBG2, PNPLA3, LPL, AOAH) carbohydrate metabolism (MGAT4B, XYLB, GBE1, PGM1, HKDC1)cholesttrol biosynthesis (FDPS, LSS, HMGCR, NSDHL, DHCR24, IDI1, ME1) HSD17B7 and other reaction or processes (CYP1A4, CYP1A1, AKR1B1, CYP4V2, DDO) were higher in the fast-growing White Recessive Rock chickens than in the slow-growing Xinghua chickens. On the other hand, expression levels of genes associated with multicellular organism development, immune response, DNA integration, melanin biosynthetic process, muscle organ development and oxidation-reduction (FRZB, DMD, FUT8, CYP2C45, DHRSX, and CYP2C18) and with glycol-metabolism (GCNT2, ELOVL 6, and FASN), were higher in the XH chickens than in the fast-growing chickens. RT-PCR validated high expression levels of nine out of 12 genes in fat tissues. The G1257069A and T1247123C of the ACSBG2 gene were significantly associated with abdominal fat weight. The G4928024A of the FASN gene were significantly associated with fat bandwidth, and abdominal fat percentage. The C4930169T of the FASN gene was associated with abdominal fat weight while the A59539099G of the ELOVL 6 was significantly associated with subcutaneous fat. The A8378815G of the DDT was associated with fat band width. CONCLUSION:The differences in fat deposition were reflected with differential gene expressions in fast and slow growing chickens.

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Characterization of Chicken Skin Yellowness and Exploration of Genes Involved in Skin Yellowness Deposition in Chicken.

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