Tick vectors and tick-borne disease are increasingly impacting human populations globally. An important challenge is to understand tick movement patterns, as this information can be used to improve management and predictive modeling of tick population dynamics. Evolutionary analysis of genetic divergence, gene flow, and local adaptation provides insight on movement patterns at large spatiotemporal scales. We develop low coverage, whole genome resequencing data for 92 samples representing range-wide variation in blacklegged ticks, Ixodes scapularis, across the U.S. Through analysis of population genomic data, we find that tick populations are structured geographically, with gradual isolation by distance separating three population clusters in the northern U.S., southeastern U.S., and a unique cluster represented by a sample from Tennessee. Populations in the northern U.S. underwent population contractions during the last glacial period and diverged from southern populations at least 50 thousand years ago. Genome scans of selection provide strong evidence of local adaptation at genes responding to host defenses, blood-feeding, and environmental variation. In addition, we explore the potential of low coverage genome sequencing of whole-tick samples for documenting the diversity of microbial pathogens. Metagenomic analyses recover important tick-borne pathogens and their geographical variation, including the higher prevalence of Borrelia burgdorferi in northern populations, geographic strain variation in Rickettsia species, and the rare occurrence of B. miyamotoi and Anaplasma phagocytophilum. The combination of restricted pathogen distribution, isolation by distance, and local adaptation in blacklegged ticks demonstrates that gene flow, including recent expansion, is limited to geographical scales of a few hundred kilometers.

The blacklegged tick, Ixodes scapularis, is a vector of Borrelia burgdorferi sensu stricto (s.s.), the causative agent of Lyme disease, part of a slow-moving epidemic of Lyme borreliosis spreading across the northern hemisphere. There are well-known geographic differences in the vectorial capacity of these ticks associated with genetic variation. Despite the need for detailed genetic information in this disease system, previous phylogeographic studies of these ticks have been restricted to relatively few populations or genetic loci. Here we present the most comprehensive phylogeographic study of I. scapularis conducted by using 3RAD and surveying 353 ticks from 33 counties throughout the range of I. scapularis. We found limited genetic variation among populations from the Northeast and Upper Midwest, where Lyme disease is most common, and higher genetic variation among populations from the South. We identify four genetic clusters of I. scapularis that are consistent with four major geographic regions, plus a distinct Central Florida group. In regions where Lyme disease is increasing in frequency, the I. scapularis populations genetically group with ticks from historically highly Lyme-endemic regions. Finally, we identify ten variable DNA sites that contribute the most to population differentiation. These variable sites cluster on one of the chromosome-scale scaffolds for I. scapularis and are within identified genes. Our findings illuminate the need for additional research to identify loci causing variation in the vectorial capacity of I. scapularis and where additional tick sampling would be most valuable to further understand disease trends caused by pathogens transmitted by I. scapularis.