Identification of SNPs Associated with Goose Meat Quality Traits Using a Genome-Wide Association Study Approach.

(1) Background: Goose meat is highly valued for its economic significance and vast market potential due to its desirable qualities, including a rich nutritional profile, tender texture, relatively low-fat content, and high levels of beneficial unsaturated fatty acids. However, there is an urgent need to improve goose breeding by identifying molecular markers associated with meat quality. (2) Methods: We evaluated meat quality traits, such as meat color, shear force (SF), cooking loss rate (CLR), and crude fat content (CFC), in a population of 215 male Sichuan white geese at 70 days of age. A GWAS was performed to identify potential molecular markers associated with goose meat quality. Furthermore, the selected SNPs linked to meat quality traits were genotyped using the MALDI-TOP MS method. (3) Results: A dataset of 2601.19 Gb of WGS data was obtained from 215 individuals, with an average sequencing depth of 10.89×. The GWAS revealed the identification of 43 potentially significant SNP markers associated with meat quality traits in the Sichuan white goose population. Additionally, 28 genes were identified as important candidate genes for meat quality. The gene enrichment analysis indicated a substantial enrichment of genes within a 1Mb vicinity of SNPs in both the protein digestion and absorption pathway and the Glycerolipid metabolism pathway. (4) Conclusion: This study provides valuable insights into the genetic and molecular mechanisms underlying goose meat quality traits, offering crucial references for molecular breeding in this field.

Genome-Wide Association Study-Based Identification of SNPs and Haplotypes Associated With Goose Reproductive Performance and Egg Quality.

Geese are one of the most economically important waterfowl. However, the low reproductive performance and egg quality of geese hinder the development of the goose industry. The identification and application of genetic markers may improve the accuracy of beneficial trait selection. To identify the genetic markers associated with goose reproductive performance and egg quality traits, we performed a genome-wide association study (GWAS) for body weight at birth (BBW), the number of eggs at 48 weeks of age (EN48), the number of eggs at 60 weeks of age (EN60) and egg yolk color (EYC). The GWAS acquired 2.896 Tb of raw sequencing data with an average depth of 12.44× and identified 9,279,339 SNPs. The results of GWAS showed that 26 SNPs were significantly associated with BBW, EN48, EN60, and EYC. Moreover, five of these SNPs significantly associated with EN48 and EN60 were in a haplotype block on chromosome 35 from 4,512,855 to 4,541,709 bp, oriented to TMEM161A and another five SNPs significantly correlated to EYC were constructed in haplotype block on chromosome 5 from 21,069,009 to 21,363,580, which annotated by TMEM161A, CALCR, TFPI2, and GLP1R. Those genes were enriched in epidermal growth factor-activated receptor activity, regulation of epidermal growth factor receptor signaling pathway. The SNPs, haplotype markers, and candidate genes identified in this study can be used to improve the accuracy of marker-assisted selection for the reproductive performance and egg quality traits of geese. In addition, the candidate genes significantly associated with these traits may provide a foundation for better understanding the mechanisms underlying reproduction and egg quality in geese.

Genome-Wide Gene Expression Profiles Reveal Distinct Molecular Characteristics of the Goose Granulosa Cells.

Granulosa cells (GCs) are decisive players in follicular development. In this study, the follicle tissues and GCs were isolated from the goose during the peak-laying period to perform hematoxylin-eosin staining and RNA-seq, respectively. Moreover, the dynamic mRNA and lncRNA expression profiles and mRNA-lncRNA network analysis were integrated to identify the important genes and lncRNAs. The morphological analysis showed that the size of the GCs did not significantly change, but the thickness of the granulosa layer cells differed significantly across the developmental stages. Subsequently, 14,286 mRNAs, 3,956 lncRNAs, and 1,329 TUCPs (transcripts with unknown coding potential) were detected in the GCs. We identified 37 common DEGs in the pre-hierarchical and hierarchical follicle stages, respectively, which might be critical for follicle development. Moreover, 3,089 significant time-course DEGs (Differentially expressed genes) and 13 core genes in 4 clusters were screened during goose GCs development. Finally, the network lncRNA G8399 with CADH5 and KLF2, and lncRNA G8399 with LARP6 and EOMES were found to be important for follicular development in GCs. Thus, the results would provide a rich resource for elucidating the reproductive biology of geese and accelerate the improvement of the egg-laying performance of geese.