The gut microbiota is closely associated with the health and production performance of livestock. Partial studies on ruminant microbiota are already in progress in the Qinghai-Tibetan Plateau Area (QTPA) in China, but large-scale and representative profiles for the QTPA are still lacking. Here, 16S rRNA sequencing was used to analyze 340 samples from yak, cattle, yak-cattle hybrids, and Tibetan sheep, which lived in a shared environment from 4 eco-regions of the QTPA during the same season, and aimed to investigate the fecal microbiota community composition, diversity, and potential function. All samples were clustered into 2 enterotypes, which were derived from the genera Ruminococcaceae UCG-005 and Acinetobacter, respectively. Environment, human activity, species, and parasitization all affected the fecal microbiota. By assessing the relationship between the fecal microbiota and the above variables, we identified a scattered pattern of fecal microbiota dissimilarity based more significantly on diet over other factors. Additionally, gastrointestinal nematode infection could reduce the capacity of the bacterial community for biosynthesis of other secondary metabolites, carbohydrate metabolism, and nucleotide metabolism. Ultimately, this study provided a fecal microbiota profile for ruminants living in 4 eco-regions of the QTPA and its potential future applications in developing animal husbandry regimes. IMPORTANCE Cattle, yak, and sheep reside as the main ruminants distributed throughout most regions of Qinghai-Tibetan Plateau Area (QTPA) in China. However, there is a lack of large-scale research in the QTPA on their fecal microbiota, which can regulate and reflect host health as an internalized "microbial organ." Our study depicted the fecal microbiota community composition and diversity of yak, cattle, yak-cattle hybrids, and Tibetan sheep from 4 eco-regions of the QTPA. Additionally, our results demonstrated here that the ruminant samples could be clustered into 2 enterotypes and that diet outweighed other factors in shaping fecal microbiota in the QTPA. This study provided a basis for understanding the microbiota characteristic of ruminants and its possible applications for livestock production in the QTPA.
Keywords: 16S rRNA sequencing; eco-region; enterotype; fecal microbiota; gastrointestinal nematode; machine learning; ruminant.