Advances in molecular taxonomy of Hyalomma ticks: from classical markers to next-generation omics

Ticks of the genus Hyalomma are important vectors of pathogens affecting humans and animals, including viruses, bacteria, and protozoans, and their expanding geographic range, driven by climate change and migratory birds, raises concerns about emerging disease outbreaks, specifically tick-borne diseases (TBDs) in previously unaffected regions. Despite this epidemiological significance, Hyalomma taxonomy remains challenging due to morphological variability and cryptic species complexes, particularly in immature stages. This review traces how molecular taxonomy has evolved from classical to next-generation approaches, emphasizing how successive methodological innovations have transformed species identification, phylogenetic reconstruction, and vector surveillance. Molecular systematics has greatly advanced species identification and phylogeographic understanding. For instance, mitochondrial markers enable reliable barcoding and reveal broad geographic patterns, while nuclear markers complement these insights and support functional genomics studies. Yet, earlier molecular tools have often fallen short in resolving closely related species or detecting fine-scale genetic differentiation essential for understanding vector competence and adaptation. More recently, high-throughput approaches such as population genomics, sialotranscriptomics, and MALDI-TOF MS have enhanced species discrimination and allowed rapid field-based identification. These next-generation omics platforms represent the new frontier of Hyalomma systematics, enabling comprehensive genetic, proteomic, and transcriptomic characterization that bridges taxonomy with function. However, despite these advances, significant challenges persist, including the scarcity of reference genomes for several Hyalomma species, limited integration of multi-omics datasets, and the lack of standardized bioinformatics pipelines that hinder data comparability across studies. Moreover, uneven geographic sampling and inconsistent marker selection continue to restrict our capacity to delineate cryptic lineages and link genetic diversity to epidemiological outcomes. By bridging taxonomy with function, these omics innovations establish an integrated framework linking genetic diversity to epidemiological risk and provide a roadmap for predictive, standardized, and applied Hyalomma taxonomy to improve vector surveillance and disease preparedness. This review provides the first comprehensive synthesis integrating classical, mitochondrial, nuclear, and multi-omics approaches for Hyalomma systematics.