Molecular Characterisation using 16S rRNA and COI Gene Sequences in Hard Ticks of Gwalior, India

Abstract

Tick infestation in humans and animals represents a global threat for different tick-borne diseases. In the present study, the ticks from the Gwalior region of India have been mapped to create a database of tick diversity. We explored 773 ticks collected from domestic animals and vegetation in Gwalior. Animals were screened visually, and ticks were collected manually, whereas the flag-drag method was used to collect ticks from the vegetation. The 16S rRNA and cytochrome oxidase I (COI) genes of tick samples were amplified and purified for sequencing and respective phylogenetic trees were constructed. The ticks were morphologically identified using taxonomical keys, revealing the presence of five genera in the region: Hyalomma, Haemaphysalis, Rhipicephalus, Boophilus, and Nosomma. Hyalomma spp. (Hy. annatolicum and Hy. marginatum) were the most abundant accounting for 69.598% of the total sample, followed by Rhipicephalus sanguineus (17.335%), Rhipicephalus microplus (7.115%), Haemaphysalis sp. (5.692%), and Nosomma monstrotum (0.258%). The tick sequences were submitted to the GenBank database. Phylogenetic analysis confirmed the morphological identification at the species level. The combination of molecular and morphological analyses of the ticks supported the result obtained with each method, thus providing more reliable estimates for continued surveillance studies.

Dna Barcoding of Ixodid Ticks Infesting Cattle and Sheep in Nsukka, Nigeria

“…Molecular methods accurately capture the differences among species (Bezeng et al, 2017) and complement morphological data in species identification. Molecular sequence data involving mtDNA COI gene has stronger patterns of genetic variability than those of nuclear regions (Li et al, 2014a), and the COI barcode region has been a verified effective and informative tool employed in animal identification (Hebert et al, 2010;Pawlas-Opiela et al, 2010;Li et al, 2014b) including ticks (Lv et al, 2014;Zhang and Zhang, 2014;Csordas et al, 2016;Ghosh et al, 2020;Davari et al, 2021). Integrative morphological and molecular identification of ticks gives a clear and more reliable result compared to single identification method (Ghosh et al, 2020).…”