Intramuscular fat (IMF) content is an important trait closely related to meat quality, which is highly variable among pig breeds from diverse genetic backgrounds. High-throughput sequencing has become a powerful technique for analyzing the whole transcription profiles of organisms. In order to elucidate the molecular mechanism underlying porcine meat quality, we adopted RNA sequencing to detect transcriptome in the longissimus dorsi muscle of Wei pigs (a Chinese indigenous breed) and Yorkshire pigs (a Western lean-type breed) with different IMF content. For the Wei and Yorkshire pig libraries, over 57 and 64 million clean reads were generated by transcriptome sequencing, respectively. A total of 717 differentially expressed genes (DEGs) were identified in our study (false discovery rate < 0.05 and fold change > 2), with 323 up-regulated and 394 down-regulated genes in Wei pigs compared with Yorkshire pigs. Gene Ontology analysis showed that DEGs significantly related to skeletal muscle cell differentiation, phospholipid catabolic process, and extracellular matrix structural constituent. Pathway analysis revealed that DEGs were involved in fatty acid metabolism, steroid biosynthesis, glycerophospholipid metabolism, and protein digestion and absorption. Quantitative real time PCR confirmed the differential expression of 11 selected DEGs in both pig breeds. The results provide useful information to investigate the transcriptional profiling in skeletal muscle of different pig breeds with divergent phenotypes, and several DEGs can be taken as functional candidate genes related to lipid metabolism (ACSL1, FABP3, UCP3 and PDK4) and skeletal muscle development (ASB2, MSTN, ANKRD1 and ANKRD2).
The aim of this study was to investigate the effect of providing supplementary Cr-enriched Bacillus subtilis (CEBS) to mice with regard to their growth performance, caecal microbiology, tissue Cr concentration, insulin receptor (IR) expression and plasma biochemical profile. A total of ninety-six Kunming strain mice were allocated to four different groups: control, CEBS, inorganic Cr and B. subtilis. After 15 d of treatment, mice that received CEBS or normal B. subtilis had higher body weights than control mice, and after 30 d mice given either CEBS or B. subtilis had greater body weights than control mice or those given inorganic Cr. The concentration of Cr in tissues (heart, liver, spleen, kidney and skeletal muscle) increased after CEBS supplementation. B. subtilis and CEBS supplementation caused a significant increase in the numbers of Lactobacillus and Bifidobacterium in the caecum, whereas the numbers of Escherichia coli and Staphylococcus decreased significantly compared with the control. The levels of IR RNA and protein in skeletal muscles increased significantly. Plasma glucose, total cholesterol, TAG and LDL-cholesterol levels declined significantly in the CEBS group compared with the control group, whereas plasma insulin and HDL-cholesterol levels increased significantly. In conclusion, CEBS supplementation enhanced the regulation of body growth, increased tissue organic Cr concentrations, altered caecal microbiota and enhanced IR expression to produce significant changes in plasma biochemistry.
BackgroundWith the development of SNP chips, SNP information provides an efficient approach to further disentangle different patterns of genomic variances and covariances across the genome for traits of interest. Due to the interaction between genotype and environment as well as possible differences in genetic background, it is reasonable to treat the performances of a biological trait in different populations as different but genetic correlated traits. In the present study, we performed an investigation on the patterns of region-specific genomic variances, covariances and correlations between Chinese and Nordic Holstein populations for three milk production traits.ResultsVariances and covariances between Chinese and Nordic Holstein populations were estimated for genomic regions at three different levels of genome region (all SNP as one region, each chromosome as one region and every 100 SNP as one region) using a novel multi-trait random regression model which uses latent variables to model heterogeneous variance and covariance. In the scenario of the whole genome as one region, the genomic variances, covariances and correlations obtained from the new multi-trait Bayesian method were comparable to those obtained from a multi-trait GBLUP for all the three milk production traits. In the scenario of each chromosome as one region, BTA 14 and BTA 5 accounted for very large genomic variance, covariance and correlation for milk yield and fat yield, whereas no specific chromosome showed very large genomic variance, covariance and correlation for protein yield. In the scenario of every 100 SNP as one region, most regions explained <0.50% of genomic variance and covariance for milk yield and fat yield, and explained <0.30% for protein yield, while some regions could present large variance and covariance. Although overall correlations between two populations for the three traits were positive and high, a few regions still showed weakly positive or highly negative genomic correlations for milk yield and fat yield.ConclusionsThe new multi-trait Bayesian method using latent variables to model heterogeneous variance and covariance could work well for estimating the genomic variances and covariances for all genome regions simultaneously. Those estimated genomic parameters could be useful to improve the genomic prediction accuracy for Chinese and Nordic Holstein populations using a joint reference data in the future.Electronic supplementary materialThe online version of this article (doi:10.1186/s12863-017-0491-9) contains supplementary material, which is available to authorized users.
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