Abstract:
Ticks and tick-borne pathogens represent the greatest vector-borne disease threat in the United States. Blacklegged ticks are responsible for most human cases, yet the disease burden is unevenly distributed across the northern and southern United States. Understanding the genetic characteristics influencing phenotypic differences in tick vectors is critical to elucidating disparities in tick-borne pathogen transmission dynamics. Applying evolutionary analyses to molecular variation in natural tick populations across ecological gradients will help identify signatures of local adaptation, which will improve control and mitigation strategies. In this study, we performed whole genome nanopore sequencing of individual (n = 1) blacklegged ticks across their geographical range (Minnesota, Pennsylvania, and Texas) to evaluate genetic divergence among populations. Our integrated analyses identified genetic variants associated with numerous biological processes and molecular functions that segregated across populations. Notably, northern populations displayed genetic variants in genes linked to xenobiotic detoxification, transmembrane transport, and sulfation that may underpin key phenotypes influencing tick dispersal, host associations, and vectorial capacity. Nanopore sequencing further allowed the recovery of complete mitochondrial and commensal endosymbiont genomes. Our study provides further evidence of genetic divergence in epidemiologically relevant gene families among blacklegged tick clades. This report emphasizes the need to elucidate the genetic basis driving divergence among conspecific blacklegged tick clades in the United States.
Description:
DATA AVAILABILITY STATEMENT : Raw read fastq files, filtered VCF files, mitogenome FASTA files, endosymbiont FASTA files, bioinformatic pipelines, and Supporting Information have been submitted to Data Dryad (DOI: 10.5061/dryad.sbcc2frh8). Mitogenome assemblies have been submitted to GenBank (accession numbers: PQ557589-PQ557592). Metadata are also stored in Data Dryad (DOI: 10.5061/dryad.sbcc2frh8). Bioinformatic pipelines and Supporting Information can also be found in the Supporting Information accompanying this manuscript.