Genetic Structuring Of Coues White Tailed Deer In The Southwestern United States

Author : William Leroy Miller
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (18 download)

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Download or read book The Genetic Structure of White-Tailed Deer to Evaluate the Potential Epizootiology of Chronic Wasting Disease in an Area of Recent Emergence written by William Leroy Miller and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Wildlife diseases are important stressors of natural populations and commonly impact species of management and conservation interest. Because of this, mitigating the negative effects of these diseases is a common goal of many management strategies. One of the key goals in areas of recent disease emergence is to minimize the geographic diffusion of diseases across landscapes so that nave populations remain minimally impacted. Prospective tools for predicting disease flow are particularly helpful in the initial stages of the epizootic cycle. Evaluating patterns of population structure, susceptibility, and connectivity can provide important insights into the potential spread of diseases across landscapes. Landscape genetic analyses, in particular, have proven particularly useful in elucidating these population characteristics. Chronic wasting disease, a fatal neurodegenerative disease of members of the family Cervidae, is a disease of particular concern due to the ecological and economic importance of infected species. Chronic wasting disease is caused by an infectious prion protein that can be passed by contact among individuals and/or through the use of shared environments. Contact among nave and infected individuals is thought to play an important role in the geographic diffusion of this disease, and management plans commonly focus on minimizing contact among these groups. Population structure and patterns of gene flow impact the distribution and occurrence of chronic wasting disease on landscape where it occurs. Thus, assessing these factors may help to identify effective management units and to predict transmission patterns within and among populations. Additionally, individual and population susceptibility to this disease is modulated by genetic variability in the prion protein (PRNP) gene, so evaluating transmission dynamics in tandem with spatial PRNP variability provides a means of assessing the innate vulnerability of populations to disease occurrence and establishment.In this study, I evaluated the genetic structure of white-tailed deer (Odocoileus virginianus) in the Mid-Atlantic region of the United States of America in order to evaluate factors that may influence the epizootiology of chronic wasting disease. I used a panel of 11 microsatellite markers to assess spatial genetic structure and gene flow. These markers were chosen from a large suite of available loci (106 candidate markers) identified from 58 previous or ongoing studies of white-tailed deer genetics. These markers were chosen because they were characterized by low genotyping error rates and were inferred to be broadly applicable across the range of white-tailed deer in North America given the geographic distribution of previous studies. I genotyped a total of 2222 individuals to assess spatial genetic structure of white-tailed deer in the Mid-Atlantic region. White-tailed deer conformed to a pattern of isolation-by-distance at both fine and broad spatial scales. Despite this, 11 distinct subpopulation clusters were identified throughout the region. The edges of these subpopulations were associated with high-volume traffic roads and areas of greater elevational relief. Despite significant structure, subpopulations maintained high rates of connectivity. There was evidence of hierarchical genetic structure with the bounds of larger population units generally corresponding to physiographic provinces. Subpopulation units defined this way are more likely to be an effective disease management unit relative to those commonly defined by anthropocentric boundaries. Population structure is only one factor influencing the geographic distribution of diseases. Cervids are farmed in this region, and several captive cervid facilities have experienced recent outbreaks of chronic wasting disease. Egression from infected facilities represents another potential pathway for transmission. I used a Bayesian assignment algorithm to test for captive egression and dispersal events among free-ranging populations, both of which may contribute to epizootic patterns. I found a low (2.0%) but significant proportion of free-ranging deer that assigned to captive origin. Two deer that were infected with chronic wasting disease had a high probability of sourcing from captive populations. The proportion of individuals that assigned to a migratory origin was as high as 13.8% among the four subsampling units, and the proportion of individuals with admixed ancestry was as high as 46.7%. This suggests dispersal is common and ongoing and is commensurate with the high migration rates reported previously. One deer infected with chronic wasting disease assigned to a migratory origin. These results may indicate that both captive egression and natural dispersal have the potential to contribute to the spread of this disease into previously uninfected regions.Individual susceptibility to chronic wasting disease is thought to be linked to variation at two single nucleotide polymorphisms in the PRNP gene. Thus, population-scale variability at these loci may influence the risk of infection and establishment. The Mid-Atlantic populations of white-tailed deer generally had a higher proportion of susceptible individuals relative to populations with a longer history of chronic wasting disease. Variability at these loci varied spatially within the region and generally conformed to patterns of population structure. This suggests that some populations may be more innately susceptible than others to chronic wasting disease establishment. Understanding patterns of population structure and susceptibility provides insights into the potential occurrence of chronic wasting disease but does not necessarily explain transmission dynamics among populations. Transmission is expected to be facilitated by dispersal, but how deer move among populations is likely a consequence of the underlying landscape matrix. I evaluated the correlation between landscape features and patterns of gene flow using a resistance surface modeling approach to identify potential transmission corridors. Patterns of genetic differentiation were best explained by a resistance surface including percent forest cover, elevational relief, and traffic volume. While large streams were also included in the resistance surface, landscape resistance related to streams was negligible. Elevational relief and traffic volume were less resistant features than areas of low forest cover, highlighting the permeability of these features to deer movement. Gene flow was facilitated through forested corridors in heterogeneous landscapes and was more diffuse in homogeneous landscapes. A large number of chronic wasting disease cases occurred in areas of high connectivity, indicating that these areas may influence disease transmission among distinct groups of deer. In conclusion, patterns of white-tailed deer genetic structure are cryptic and associated with features that are permeable to movement. Nevertheless, these features may influence the distribution of chronic wasting disease and the possibility for transmission among populations. Furthermore, spatial variability at loci associated with disease susceptibility suggests that some populations may be more innately at risk for disease establishment than others. Incorporating the inferred patterns of population structure, connectivity, and susceptibility into disease forecasting models represents a logical extension and may further elucidate the trends observed here. Other sources of infection, such as captive egression, may pose a risk independent of patterns predicted by natural population structure. Thus, joint consideration of anthropogenic and natural sources of infection may further aid in predicting future epizootic patterns.