ALDH1A1 (aldehyde dehydrogenase 1A1) is a crucial protein in retinoids’ metabolism, and the lack of ALDH1A1 inhibits the fat deposition in mice. However, whether ALDH1A1 has a similar effect on chickens’ fat-depot is still unknown. In this study, we investigate the role of ALDH1A1 in chickens’ adipogenesis. The immortalized chicken preadipocyte 1 (ICP1) cell line and chicken primary preadipocytes isolated from abdominal fat were used to perform a series of experiments in vitro to elucidate the effects of ALDH1A1. In addition, lentivirus was used to verify the results of cell experiments in vivo. The data showed that overexpression of ALDH1A1 significantly weakened the proliferation of preadipocytes and suppressed the differentiation of preadipocytes through the PPARγ pathway, and the knockdown experiments had the opposite results. Moreover, chickens injected with overexpression lentivirus had higher abdominal fat percentage, a bigger size of lipid droplets, and higher triglyceride content in abdominal fat, and chickens injected with interfering lentivirus had the opposite situation. We proved that ALDH1A1 not only inhibited the proliferation and differentiation of chickens’ preadipocytes in vitro, but also inhibited the fat-depot of chickens in vivo, which was completely opposite the function of ALDH1A1 in mice, indicating that ALDH1A1 may have a different mechanism that is still unknown.

The size of the reference population is critical in order to improve the accuracy of genomic prediction. Indeed, improving genomic prediction accuracy by combining multinational reference populations has proven to be effective. In this study, we investigated the improvement of genomic prediction accuracy in seven complex traits (i.e., milk yield; fat yield; protein yield; somatic cell count; body conformation; feet and legs; and mammary system conformation) by combining the Chinese and Nordic Holstein reference populations. The estimated genetic correlations between the Chinese and Nordic Holstein populations are high with respect to protein yield, fat yield, and milk yield—whereby these correlations range from 0.621 to 0.720—and are moderate with respect to somatic cell count (0.449), but low for the three conformation traits (which range from 0.144 to 0.236). When utilizing the joint reference data and a two-trait GBLUP model, the genomic prediction accuracy in the Chinese Holsteins improves considerably with respect to the traits with moderate-to-high genetic correlations, whereas the improvement in Nordic Holsteins is small. When compared with the single population analysis, using the joint reference population for genomic prediction in younger animals, results in a 2.3 to 8.1 percent improvement in accuracy. Meanwhile, 10 replications of five-fold cross-validation were also implemented in order to evaluate the performance of joint genomic prediction, thereby resulting in a 1.6 to 5.2 percent increase in accuracy. With respect to joint genomic prediction, the bias was found to be quite low. However, for traits with low genetic correlations, the joint reference data do not improve the prediction accuracy substantially for either population.

Carcass and meat quality traits are critical in pig breeding and production. Estimating genetic parameters for these traits is a vital aspect of breeding engineering, as accurate genetic parameters are essential for estimating breeding values, predicting genetic progress, and optimizing breeding programs. This study was conducted on a population of 461 Yorkshire pigs from the same breeding farm, which were slaughtered to assess nine carcass traits and seven meat quality traits, followed by descriptive statistical analysis. Additionally, we estimated the genetic parameters of these traits using genomic information based on 50K chip data. The results indicated that sex significantly affected most carcass and meat quality traits. Carcass traits including carcass length indicators (h² = mean 0.35), backfat thickness indicators (h² = mean 0.36), eye muscle area (h² = 0.28), and the number of rib pairs (h² = 0.28) exhibited medium to high heritability. Carcass length indicators showed high genetic correlations with backfat thickness indicators (r = mean −0.49) and the number of rib pairs (r = mean 0.63), while high negative genetic correlation (r = −0.72) was noted between eye muscle area and the number of rib pairs. Meat quality traits also displayed medium to high heritability, expect for pH value measured within one hour post-slaughter (h² = 0.12). Drip loss indicators had higher genetic correlations with pH (r = mean −0.73) than with meat color indicators (r = mean 0.22). These findings may provide a theoretical reference for genetic evaluation and breeding in the Yorkshire pig population.