Multi-omics revealed the effects of dietary energy levels on the rumen microbiota and metabolites in yaks under feeding conditions
The sequencing data of 18 samples were processed by splicing, filtering and chimera discarding, which resulted in a total of 949,241 optimized sequences with an average sequence length of 416 bp.The RDP classifier Bayesian algorithm was used to classify and analyze the representative sequences of the OTUs at 97% similarity level, which resulted in 2,926 OTUs.The Alpha diversity analysis found that the three treatment groups differed in microbial diversity and richness, with the microbial diversity (Shannon index) of the medium-energy group being significantly higher than that of the high-energy group, and the microbial richness (Chao1 index) of the low-energy group being higher than that of the other two groups, but the difference was not significant. The microbial composition of the samples from the three treatment groups was analyzed using PLS-DA (Partial Least Squares Discriminant Analysis), and analyzed and graphed with plsda in the mixOmics package in the R language (version 3.3.1), and the results showed that the three groups could be clearly differentiated and clustered into clusters among them, which The results showed that the rumen flora composition of yaks fed diets with different energy levels differed significantly, and the difference between the middle energy group and the other two groups was larger.