Prediction and Prevention of Parasitic Diseases Using a Landscape Genomics Framework

Abstract

Summary Substantial heterogeneity exists in the dispersal, distribution and transmission of parasitic species. Understanding and predicting how such features are governed by the ecological variation of landscape they inhabit is the central goal of spatial epidemiology. Genetic data can further inform functional connectivity among parasite, host and vector populations in a landscape. Gene flow correlates with the spread of epidemiologically relevant phenotypes among parasite and vector populations (e.g., virulence, drug and pesticide resistance), as well as invasion and re-invasion risk where parasite transmission is absent due to current or past intervention measures. However, the formal integration of spatial and genetic data (‘landscape genetics’) is scarcely ever applied to parasites. Here, we discuss the specific challenges and practical prospects for the use of landscape genetics and genomics to understand the biology and control of parasitic disease and present a practical framework for doing so.

Utility of theOnchocerca volvulusmitochondrial genome for delineation of parasite transmission zones

“…These zones can be delineated using parasite population structure as a proxy for 111 transmission zone boundaries: parasites from the same transmission zone are able to interbreed and thus 112 are more closely related genetically than they are to parasites from different transmission zones, with 113 which they are less likely to interbreed and thus are genetically less related. Consequently, the likelihood 114 that parasites originate from the same transmission zone and the likelihood of parasite transmission 115 between two locations (invasion) can be inferred from the degree of genetic relatedness between them, 116 and defined quantitatively by estimating parameters of population structure (Archie et al, 2009;Real and 117 Biek, 2007;Schwabl et al, 2017). 118…”

Comparative landscape genetics reveals differential effects of environment on host and pathogen genetic structure in Tasmanian devils (Sarcophilus harrisii) and their transmissible tumour

“…Even fewer multispecies studies have employed landscape genetics methods to study the dynamics of infectious diseases in wildlife systems (Biek & Real, 2010;Hemming-Schroeder et al, 2018;Kozakiewicz et al, 2018). Such comparative landscape genetics frameworks can provide valuable insights into how host-pathogen interactions shape patterns of disease transmission and spread across heterogeneous landscapes (Leo, Gonzalez, Millien, & Cristescu, 2016;Schwabl et al, 2017;Talbot et al, 2017).…”

The Expectations and Challenges of Wildlife Disease Research in the Era of Genomics: Forecasting with a Horizon Scan-like Exercise

“…More recently, the field has naturally shifted toward landscape genomics, transformed by advances in NGS, cutting-edge remote sensing, and GIS technologies (Kool et al 2013). Taken together, the incorporation of landscape genomics into wildlife disease biology promises improved prediction of disease risk, transmission, and prevention (Schwabl et al 2017). Three general prospects for the future of integrating landscape ecology with wildlife disease materialized from the horizon scan discussion: 1) inferring host and pathogen gene flow, 2) coordinating technology, data, and expertise, and 3) understanding the effects of rapid environmental change.…”