Genetically selected chickens with better growth and early maturation show an incidental increase in abdominal fat deposition (AFD). Accumulating evidence reveals a strong association between gut microbiota and adiposity. However, studies focusing on the role of gut microbiota in chicken obesity in conventional breeds are limited. Therefore, 400 random broilers with different levels of AFD were used to investigate the gut microbial taxa related to AFD by 16S rRNA gene sequencing of 76 representative samples, and to identify the specific microbial taxa contributing to fat-related metabolism using shotgun metagenomic analyses of eight high and low AFD chickens. The results demonstrated that the richness and diversity of the gut microbiota decrease as the accumulation of chicken abdominal fat increases. The decrease of Bacteroidetes and the increase of Firmicutes were correlated with the accumulation of chicken AFD. The Bacteroidetes phylum, including the genera Bacteroides, Parabacteroides, and the species, B. salanitronis, B. fragilis, and P. distasonis, were correlated to alleviate obesity by producing secondary metabolites. Several genera of Firmicutes phylum with circulating lipoprotein lipase activity were linked to the accumulation of chicken body fat. Moreover, the genera, Olsenella and Slackia, might positively contribute to fat and energy metabolism, whereas the genus, Methanobrevibacter, was possible to enhance energy capture, and associated to accumulate chicken AFD. These findings provide insights into the roles of the gut microbiota in complex traits and contribute to the development of effective therapies for the reduction of chicken fat accumulation.

Qingyuan partridge chicken is an important indigenous chicken in China. In its breeding schemes, chickens are usually selected at the age of 105‐day‐old for five traits, including body weight (BW), shank length (SL), shank girth (SG), comb height (CH) and feather maturity (FM). At present, genetic parameters of the aforementioned traits have still not been studied in Qingyuan partridge chickens. The objectives of this study were the following: (1) to investigate whether the optimal statistical models of these traits need to consider maternal genetic and permanent environmental effects in late‐feathering Qingyuan partridge hens, and (2) to estimate genetic parameters for these traits based on the optimal models. The numbers of records for BW, SL, SG, CH and FM were 13,721, 13,671, 13,670, 13,669 and 13,672, respectively. Variance components were estimated using average information‐restricted maximum likelihood method, and the optimal model was determined based on Bayesian information criterion. More specifically, the optimal model for BW considered maternal genetic and permanent environmental effects in addition to direct additive genetic effect; SL, SG and FM considered direct and maternal genetic effects; and CH considered direct and maternal genetic effects, and the covariance between them. The direct heritabilities of these traits estimated using the optimal models were 0.21 ± 0.04, 0.30 ± 0.05, 0.40 ± 0.05, 0.59 ± 0.09 and 0.09 ± 0.04, respectively; the maternal heritabilities were 0.01 ± 0.04, 0.05 ± 0.05, 0.04 ± 0.05, 0.09 ± 0.09 and 0.03 ± 0.04, respectively. Maternal genetic effect evidently played an important part in FM and maternal heritability accounted for 30 per cent of total heritability. Furthermore, the direct and maternal genetic effects for CH were estimated to be negatively and moderately correlated (−0.51 ± 0.11). For all traits, neglecting existent maternal effects biased the estimation of direct heritability. Therefore, to implement optimum breeding strategies for improvement of these traits in Qingyuan partridge hens, maternal effects should be taken into consideration.

Qingyuan partridge chicken is one of the most well-known Chinese indigenous yellow broilers. In breeding programmes, five traits are usually selected when the chickens are 105 days old, namely body weight (BW), comb height (CH), shank length (SL), shank girth (SG) and feather maturity (FM). The objective of this study was to estimate the genetic parameters of these five traits, especially direct additive genetic correlations, to lay the foundation for balanced selection of Qingyuan partridge chickens. Approximately 9600 records were used for estimation. Variance components for these five traits were estimated using three multitrait models incorporating different effects via Gibbs sampling. Based on model 1 in which the random effects included direct additive genetic effects and residuals, the estimated direct heritabilities for BW, CH, SL, SG and FM were 0.29 ± 0.04, 0.53 ± 0.04, 0.47 ± 0.04, 0.43 ± 0.05 and 0.18 ± 0.03, respectively. The direct genetic correlations ranged from −0.08 to 0.46. When additionally considering maternal additive genetic effects (model 2), the estimates of direct heritabilities and absolute values of direct additive genetic correlations were smaller. The heritabilities were 0.14 ± 0.04, 0.40 ± 0.02, 0.34 ± 0.05, 0.27 ± 0.05 and 0.12 ± 0.03 for BW, CH, SL, SG and FM, respectively. The direct additive genetic correlations ranged from −0.33 to 0.36. More specifically, the direct additive genetic correlations between BW and CH, SL, SG and FM were 0.19 ± 0.13, 0.15 ± 0.15, 0.36 ± 0.15 and − 0.33 ± 0.21, respectively. The genetic correlations of FM with SL, SG and CH were − 0.15 ± 0.15, −0.08 ± 0.17 and 0.18 ± 0.15, respectively. The direct genetic correlations between CH and SG and SL were − 0.02 ± 0.11 and − 0.20 ± 0.11, respectively, and that between SL and SG was 0.19 ± 0.11. The total heritabilities and maternal additive genetic correlations ranged from 0.16 to 0.44 and from −0.13 to 0.61, respectively.The third model also included the maternal permanent environmental effect for BW. The estimates of direct heritability, direct additive genetic correlation, total heritability and maternal additive genetic correlation were only slightly different

Dominance hierarchy, is described as the priority to feed, resting and territory in term of aggressive interactions. Increased studies have revealed the underpinned mechanism mediating social hierarchy in mammal, vertebrate and fishes, however, there is rare studies conducting on how brain amydala on social hierarchy in poultry. We performed cross-species analysis with mammalian amygdala, and find that cell types of human and rhesus monkeys were more closely related and that of chickens were more distant. We identified 26 clusters and divided it into 10 main clusters. Of which, GABAnic and glutamatergic neurons are associated with social behaviors, and their sub-neurons GABA_LEG and Glu3, and hub genes RHOB and CDK14, are considered mediating the social hierarchy of chickens. Additionally, high-rank chickens may have better immune functions and stress tolerance than low-rank chickens. Our results provide to serve the developmental studies of amygdala neuron system, and new insights into the underpinned mechanism of social hierarchy in poultry.