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The genetic structure and diversity of 15 Chinese indigenous chicken breeds was investigated using 29 microsatellite markers. The total number of birds examined was 542, on average 36 birds per breed. A total of 277 alleles (mean number 9.55 alleles per locus, ranging from 2 to 25) was observed. All populations showed high levels of heterozygosity with the lowest estimate of 0.440 for the Gushi chickens, and the highest one of 0.644 observed for Wannan Three-yellow chickens. The global heterozygote deficit across all populations (F IT ) amounted to 0.180 (p<0.001). About 16% of the total genetic variability originated from differences between breeds, with all loci contributing significantly to this differentiation. An unrooted consensus tree was constructed using the Neighbour-Joining method and pair-wise distances based on marker estimated kinships. Two main groups were found. The heavy-body type populations grouped together in one cluster while the light-body type populations formed the second cluster. The STRUCTURE software was used to assess genetic clustering of these chicken breeds. Similar to the phylogenetic analysis, the heavy-body type and light-body type populations separated first. Clustering analysis provided an accurate representation of the current genetic relations among the breeds. Remarkably similar breed rankings were obtained with all methods.

Background Chicken intramuscular fat (IMF) content is closely related to meat quality and performance, such as tenderness and flavor. Abdominal fat (AF) in chickens is one of the main waste products at slaughter. Excessive AF reduces feed efficiency and carcass quality. Results To analyze the differential deposition of IMF and AF in chickens, gene expression profiles in the breast muscle (BM) and AF tissues of 18 animals were analyzed by differential expression analysis and weighted co-expression network analysis. The results showed that IMF deposition in BM was associated with pyruvate and citric acid metabolism through GAPDH, LDHA, GPX1, GBE1, and other genes. In contrast, AF deposition was related to acetyl CoA and glycerol metabolism through FABP1, ELOVL6, SCD, ADIPOQ, and other genes. Carbohydrate metabolism plays an essential role in IMF deposition, and fatty acid and glycerol metabolism regulate AF deposition. Conclusion This study elucidated the molecular mechanism governing IMF and AF deposition through crucial genes and signaling pathways and provided a theoretical basis for producing high-quality broilers.

Skeletal muscle fibers are primarily categorized into oxidative and glycolytic fibers, and the ratios of different myofiber types are important factors in determining livestock meat quality. However, the molecular mechanism for determining muscle fiber types in chickens was hardly understood. In this study, we used RNA sequencing to systematically compare mRNA and microRNA transcriptomes of the oxidative muscle sartorius (SART) and glycolytic muscle pectoralis major (PMM) of Chinese Qingyuan partridge chickens. Among the 44,705 identified mRNAs in the two types of muscles, 3,457 exhibited significantly different expression patterns, including 2,364 up-regulated and 1,093 downregulated mRNAs in the SART. A total of 698 chicken miRNAs were identified, including 189 novel miRNAs, among which 67 differentially expressed miRNAs containing 42 up-regulated and 25 downregulated miRNAs in the SART were identified. Furthermore, function enrichment showed that the differentially expressed mRNAs and miRNAs were involved in energy metabolism, muscle contraction, and calcium, peroxisome proliferator-activated receptor (PPAR), insulin and adipocytokine signaling. Using miRNA-mRNA integrated analysis, we identified several candidate miRNA-gene pairs that might affect muscle fiber performance, viz, gga-miR-499-5p/SOX6 and gga-miR-196-5p/CALM1, which were supported by target validation using the dual-luciferase reporter system. This study revealed a mass of candidate genes and miRNAs involved in muscle fiber type determination, which might help understand the molecular mechanism underlying meat quality traits in chickens. Improving meat quality has long been a goal of broiler breeding programs, especially for Chinese native breeds 1,2. However, meat quality is difficult to define because it is a complex trait influenced by numerous factors 3. As the main tissue determining meat quality, skeletal muscle is a heterogeneous tissue composed of different types of muscle fibers, varying in their biochemical and structural characteristics. Previous studies have found that different types of muscle fibers can influence meat quality traits, including meat color, tenderness, water-holding capacity, juiciness, and flavor 4,5. In chickens, myofiber can be divided into red and white fibers, which are referred to as oxidative (type I and IIA) and glycolytic fibers (type IIB), respectively. Oxidative fibers exhibit slow contractility and oxidative metabolism based on mitochondrial oxidative phosphorylation, whereas glycolytic fibers have fast contractility and glycolytic metabolism 6,7. Although the differences between various muscle fiber types in physiology and functionality have been well studied, the molecular regulation of their specification and maintenance in chickens remains largely unknown 8,9. miRNAs are highly conserved non-coding small RNAs that regulate gene expression at the post-transcriptional level in most biological processes. Emerging evidence has demonstrated that miRNAs are involved in