2.b.v. Lyme Endemic to Non-Lyme Endemic Comparisons
Rather than using geopolitical boundaries, it is also possible to view the data relative to the 95% human Lyme disease kernel, a proxy forB. burgdorferi s.s. prevalence. Overall, populations close to or within the Lyme disease kernel were more closely related than populations more distant from the kernel. For example, the populations in North Carolina and Tennessee are within the Southeastern region, with Stokes County, NC falling within the Lyme endemic region and Watauga County, NC and Claiborne County, TN just outside the Lyme disease kernel. All three, however, are within or extremely close to the genetic cluster containing all populations within the Lyme Disease kernel, irrespective of their distance to them (Figs. 2, 3). Alternatively, the Missouri population is in the Northern geographic area, but is well outside the Lyme disease kernel, with the genetic cluster for Missouri also well away from all other Northern populations (which are inside the Lyme disease kernel; Figs. 2, 3). This leads to the hypothesis that the genetic differentiation occurring throughout the landscape likely is not solely geographically driven, but instead is correlated with B. burgdorferi s.s. prevalence. Thus, the information presented herein may be used to redraw boundaries between genetically distinct groups ofI. scapularis , relationships that seem to be correlated with human Lyme disease. Further work in this area is obviously warranted.