Important Dispersal Capacity of One Main Species Vector of Bluetongue and Schmallenberg Viruses Culicoides Obsoletus (Diptera: Ceratopogonidae) Revealed by Landscape Genetic Analyses 

Abstract

Background: In the last two decades, recurrent epizootics of bluetongue virus and Schmallenberg virus have been reported in the western Palearctic region. These viruses affect domestic cattle, sheep, goats and wild ruminants and are transmitted by native hematophagous midges of the genus Culicoides (Diptera: Ceratopogonidae). Culicoides dispersal is known to be stratified, i.e. due to a combination of dispersal processes occurring actively at short distances and passively or semi-actively at long distances, allowing individuals to jump hundreds of kilometers. Methods: Here, we aim to identify the environmental factors that promote or limit gene flows of Culicoides obsoletus, an abundant and widespread vector species in Europe using an innovative framework integrating spatial, population genetics and statistical approaches. A total of 348 individuals were sampled in 46 sites in France and have been genotyped using 11 newly-designed microsatellite markers. Results: We found a low genetic differentiation and population structure for C. obsoletus across the country. Using three complementary inter-individual genetic distances, we did not detect any significant isolation-by-distance, but a significant anisotropic isolation-by-distance on a North-South axis. We have employed a multiple regression approach on distance matrices to investigate the correlation between genetic and environmental distances. Among all the environmental factors that have been tested, only cattle density seems to have an impact on C. obsoletus gene flow. Conclusions: Such a high dispersal capacity of C. obsoletus over land territories calls for a re-evaluation of the impact of Culicoides on virus dispersal and highlights the urgent need to better integrate molecular, spatial and statistical information to guide vector-borne diseases control.

Using empirical datasets to quantify uncertainty in inferences of landscape genetic resistance due to variation of individual-based genetic distance metrics

“…It is perhaps not surprising that FCA/PCA-based measures perform well, as both methods emphasise differences better than metrics that weight all loci equally (such as all Other Metrics). Unsurprisingly, other studies have also foud FCA/PCA-based measures to provide better model support or fit than other genetic distance metrics, based on Mantel’s test correlation (Shirk, Wallin, Cushman, Rice, & Warheit, 2010), AICc values (Shirk et al 2017a) or r 2 (Mignotte et al, 2020). In the majority of cases, higher maximum Δdist-AICc values were obtained for each landscape factor with FCA- rather than PCA-based metrics.…”