The rumen is divided into multiple rumen sacs based on anatomical structure, and each has its unique physiological environment. Tarim wapiti preserved roughage tolerance after domestication, and adaptation to the desertified environment led to the development of a unique rumen shape and intraruminal environment. In this work, six Tarim wapiti were chosen and tested for fermentation parameters, microbes, and histomorphology in four rumen areas (Dorsal sac, DS; Ventral sac, VS; Caudodorsal blind sac, CDBS; Caudoventral blind sac, CVBS). Tarim wapiti’s rumen blind sac had better developed rumen histomorphology, the ventral sac was richer in VFAs, and the dominant bacteria varied most notably in the phylum Firmicutes, which was enriched in the caudoventral blind sac. The ventral sac biomarkers focused on carbohydrate fermentation-associated bacteria, the dorsal sac focused on N recycling, and the caudoventral blind sac identified the only phylum-level bacterium, Firmicutes; we were surprised to find a probiotic bacterium, Bacillus clausii, identified as a biomarker in the ventral sac. This research provides a better understanding of rumen fermentation parameters, microorganisms, and histomorphology in the Tarim wapiti rumen within a unique ecological habitat, laying the groundwork for future regulation targeting the rumen microbiota and subsequent animal production improvement.

Background/Objectives: The Yanqi horse is a distinguished local breed in China, known for its robust physique and strong adaptability. However, due to insufficient breeding populations and a loosely structured breeding system, the number of Yanqi horses has been declining annually. To protect its genetic resources and develop scientific breeding strategies, this study aimed to analyze the genetic diversity, parentage relationships, and genetic structure of the Yanqi horse conservation population using microsatellite markers. Materials and Methods: A total of 117 Yanqi horses were selected for genotyping analysis using 16 microsatellite markers. Genetic diversity parameters (e.g., allele number, heterozygosity, F-statistics) were calculated using GeneAIEX (v.6.503) and Fstat software (v.2.9.4). Parentage analysis was conducted using Cervus software. Bayesian clustering analysis was performed using STRUCTURE software (v.2.3.4), and a phylogenetic tree was constructed based on Nei’s genetic distance to reveal the population genetic structure. Results: A total of 191 alleles were detected, with an average allele number of 11.969, observed heterozygosity of 0.481, and expected heterozygosity of 0.787. Parentage testing showed a cumulative exclusion probability (CEP) of 0.9652999 when one parent’s genotype was known and 0.9996999 when both parents’ genotypes were known, achieving an accuracy of 99%. Genetic differentiation analysis revealed moderate genetic divergence among populations (FST = 0.128) and moderate inbreeding levels (FIS = 0.396). Bayesian clustering analysis (K = 4) indicated that the Yanqi horse population could be divided into four genetic clusters, reflecting the impact of geographical isolation on genetic structure. Conclusions: The Yanqi horse conservation population exhibits moderate genetic diversity, high accuracy in parentage identification, and moderate genetic differentiation and inbreeding. The findings provide a scientific basis for the conservation and sustainable utilization of Yanqi horse genetic resources. Future efforts should focus on strengthening conservation measures, optimizing breeding strategies, and further investigating the genetic background using genomic technologies to ensure the sustainable development of the Yanqi horse population.