Abstract
Ticks serve as major vectors of zoonotic pathogens, posing significant threats to public health and livestock. However, morphological similarity among closely related species complicates accurate identification. This study employed an integrative taxonomic approach combining morphological and molecular methods to delineate five medically important tick species in Xinjiang, China. From April to July 2024, a total of 1,128 ticks were collected from livestock across four ecological regions (Ürümqi, Turpan, Jimsar, and Aksu). Morphological features-including basis capituli, scutum, and genital aperture-were analyzed via stereomicroscopy, while molecular characterization targeted mitochondrial (16S rDNA, COI) and nuclear (ITS2) markers. Phylogenetic trees were reconstructed using the maximum likelihood method. Morphological identification confirmed five species: Hyalomma anatolicum, Hyalomma asiaticum, Hyalomma dromedarii, Rhipicephalus turanicus, and Dermacentor marginatus, supported by high-resolution imaging. Molecular data revealed notable interregional genetic affinities: H. anatolicum from Turpan shared COI similarity with strains from Kazakhstan; H. asiaticum from Turpan clustered with Iranian populations; H. dromedarii from Jimsar showed 16S rDNA similarity to Saudi Arabian lineages; R. turanicus from Aksu grouped with Egyptian COI sequences; and D. marginatus from Jimsar aligned with populations from Alashankou, China. Notably, single-gene phylogenies posed taxonomic limitations-for example, ITS2 misclassified R. turanicus as Rhipicephalus sanguineus sensu stricto. These issues were mitigated through morphological diagnostics such as scutal enamel spots in D. marginatus and the distinctive genital plates in H. dromedarii. The integrative approach improved taxonomic resolution, with 16S rDNA providing genus-level insight, COI enabling species-level discrimination, and ITS2 offering strain-level resolution. Additionally, high-resolution morphological imaging addressed gaps in existing reference databases. Overall, multi-locus strategies combined with morphological validation are essential for accurate tick identification, improving our capacity to monitor vector-borne pathogen transmission and contributing to One Health surveillance frameworks.