Whole-transcriptome sequencing revealed the ceRNA regulatory network during the proliferation and differentiation of goose myoblast.

The Shitou goose, the largest meat-type goose breed, is an ideal model for offering insights into enhancing meat production efficiency through understanding its genetic regulation of muscle development. Here, through whole-transcriptomic analysis of embryonic leg muscles, we identified 847 differentially expressed genes (DEG), 244 differentially expressed lncRNAs (DEL), 37 differentially expressed circRNAs (DEC), and 84 differentially expressed miRNAs (DEM). Gene ontology (GO) analysis highlighted the significant enrichment of differentially expressed RNAs in muscle structure development, actin filament-based processes, and the actin cytoskeleton pathway. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis identified pathways associated with the FoxO signaling pathway, AMPK signaling pathway, Wnt signaling pathway and calcium signaling pathway. Furthermore, we utilized Miranda, TargetScan, and miRDB to identify regulatory networks that involve interactions between lncRNA-mRNA, circRNA-mRNA, miRNA-mRNA, lncRNA-miRNA-mRNA, and circRNA-miRNA-mRNA, which regulated the growth and development of skeletal muscle. Notably, differentially expressed genes within the ceRNA network were most significantly enriched in the regulation of actin cytoskeletal organization. Additionally, a lncRNA/circRNA-miRNA-mRNA ceRNA network related to muscle growth and development was constructed based on protein-protein interaction (PPI) analysis and hub genes selection using Cytoscape. This further elucidated the regulatory roles of noncoding RNAs (ncRNA) in the formation of muscle fibers in Shitou goose. In summary, this study provides a valuable transcriptional regulatory network for goose muscle development laying the groundwork for further exploration of the molecular regulatory mechanisms underlying the excellent meat production performance of Shitou goose.

Genetic characteristics and selection signatures between Southern Chinese local and commercial chickens.

The introduction of exotic breeds and the cultivation of new lines by breeding companies have posed challenges to native chickens in South China, including loss of breed characteristics, decreased genetic diversity, and declining purity. Understanding the population genetic structure and genetic diversity of native chickens in South China is crucial for further advancements in breeding efforts. In this study, we analyzed the population genetic structure and genetic diversity of 321 individuals from 10 different breeds in South China. By comparing commercial chickens with native ones, we identified selection signatures occurring between local chickens and commercial breeds. The analysis of population genetic structure revealed that the native chicken populations in South China exhibited a considerable level of genetic diversity. Moreover, the commercial lines of Xiaobai chicken and Huangma chicken displayed even higher levels of genetic diversity, which distinguished them from other native varieties at the clustering level. However, certain individuals within these commercial varieties showed a discernible genetic relationship with the native populations. Notably, both commercial varieties also retained a significant degree of genetic similarity to their respective native counterparts. In order to investigate the genomic changes occurring during the commercialization of native chickens, we employed 4 methods (Fst, ROD, XPCLR, and XPEHH) to identify potential candidate regions displaying selective signatures in Southern Chinese native chicken population. A total of 168 (identified by Fst and ROD) and 86 (identified by XPCLR and XPEHH) overlapping genes were discovered. Functional annotation analysis revealed that these genes may be associated with reproduction and growth (SAMSN1, HYLS1, ROBO3, FGF14, PRSS23), musculoskeletal development (DNER, MYBPC1, DGKB, ORC1, KLF10), disease resistance and environmental adaptability (PUS3, CRB2, CALD1, USP15, SGCD, LTBP1), as well as egg production (ADGRB3, ACSF3). Overall, native chickens in South China harbor numerous selective sweep regions compared to commercial chickens, enriching valuable genomic resources for future genetic research and breeding conservation.

A large-scale comparison of the meat quality characteristics of different chicken breeds in South China.

Meat quality traits are essential for producing high-quality broilers, but the genetic improvement has been limited by the complexity of measurement methods and the numerous traits involved. To systematically understand the meat quality characteristics of different broiler breeds, this study collected data on slaughter performance, skin color, fat deposition, and meat quality traits of 434 broilers from 12 different breeds in South China. The results showed that there was no significant difference in the live weight and slaughter weight of various broiler breeds at their respective market ages. Commercial broiler breeds such as Xiaobai and Huangma chickens had higher breast muscle and leg muscle rates. The skin and abdominal fat of Huangma chickens cultivated in the consumer market in South China exhibited significantly higher levels of yellowness compared to other varieties. Concerning fat traits, we observed that Wenchang chickens exhibited a strong ability to fat deposition, while the younger breeds showed lower fat deposition. Additionally, there were significant positive correlations found among different traits, including traits related to weight, traits related to fat, and skin color of different parts. Hierarchical clustering analysis revealed that fast-growing and large broiler Xiaobai chickens formed a distinct cluster based on carcass characteristics, skin color, and meat quality traits. Principal component analysis (PCA) was used to extract multiple principal components as substitutes for complex meat quality indicators, establishing a chicken meat quality evaluation model to differentiate between different breeds of chickens. At the same time, we identified 46, 22, and 20 SNP loci and their adjacent genes that were significantly associated with muscle mass traits, fat deposition, and skin color through genome-wide association studies (GWAS). The above results are helpful for systematically understanding the differences and characteristics of meat quality traits among different breeds.