Abstract: The investigation of microbial diversity and its correlation with free amino acids (FAAs) and fatty acids (FAs) in mare's milk from Northern Xinjiang plays an important role in food industry. In this work, the advanced methods including metagenomic sequencing, ultra-performance liquid chromatography-mass spectrometry (UPLC-MS), and gas chromatography (GC) were employed to profile microbial communities, FAAs, and FAs across regions, respectively. Subsequently, the regional differences, as well as interactions between dominant microbiota and nutrients were further evaluated using orthogonal partial least squares-discriminant analysis (OPLS-DA) combined with Pearson correlation. Results revealed that distinct microbiota structures could be found at the genus level among the three regions, with dominant genus of Lactobacillus and predominant species of Lactobacillus helveticus, Kazachstania unispora, and Kluyveromyces marxianus were identified. In particular, a total of 35 FAAs and 27 FAs were quantified in mare's milk within three regions, with significant regional differences (P<0.05). Among above FAAs, glycine, alanine, arginine, proline, valine, taurine, palmitic acid, oleic acid, linoleic acid, arachidonic acid, and myristic acid were proposed as region-specific markers. Additionally, the significant positive correlations (P<0.05) between three microorganisms (Acetobacter pasteurianus, Lactobacillus helveticus, and Lacticaseibacillus kefiri) and 22 FAAs (leucine, lysine, γ-aminobutyric acid, etc). The similar positive correlations (P<0.05) also could be observed between Brettanomyces bruxellensis and 10 FAAs (alanine, arginine, etc). The above positive correlations among Lactobacillus, yeast genera and FAAs indicated the great contributions of Lactobacillus and yeast genera in formation of polyunsaturated fatty acid. Notably, Lactiplantibacillus plantarum and Brettanomyces bruxellensis demonstrated the strongest positive associations with fungi and bacteria species, respectively. These findings provide a theoretical basis for optimizing mare's milk quality through microbiota regulation.