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Spatio-temporal analyses reveal infectious disease-driven selection in a free-ranging ungulate
Author(s) -
Melanie E. F. LaCava,
Jennifer L. Malmberg,
William H. Edwards,
Laura Johnson,
Samantha E. Allen,
Holly B. Ernest
Publication year - 2021
Publication title -
royal society open science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.84
H-Index - 51
ISSN - 2054-5703
DOI - 10.1098/rsos.210802
Subject(s) - chronic wasting disease , odocoileus , ungulate , wildlife disease , biology , wildlife , disease , natural selection , allele , allele frequency , population , infectious disease (medical specialty) , selection (genetic algorithm) , evolutionary biology , genetics , zoology , gene , ecology , medicine , environmental health , habitat , scrapie , prion protein , pathology , artificial intelligence , computer science
Infectious diseases play an important role in wildlife population dynamics by altering individual fitness, but detecting disease-driven natural selection in free-ranging populations is difficult due to complex disease–host relationships. Chronic wasting disease (CWD) is a fatal infectious prion disease in cervids for which mutations in a single gene have been mechanistically linked to disease outcomes, providing a rare opportunity to study disease-driven selection in wildlife. In Wyoming, USA, CWD has gradually spread across mule deer ( Odocoileus hemionus ) populations, producing natural variation in disease history to evaluate selection pressure. We used spatial variation and a novel temporal comparison to investigate the relationship between CWD and a mutation at codon 225 of the mule deer prion protein gene that slows disease progression. We found that individuals with the ‘slow’ 225F allele were less likely to test positive for CWD, and the 225F allele was more common in herds exposed to CWD longer. We also found that in the past 2 decades, the 225F allele frequency increased more in herds with higher CWD prevalence. This study expanded on previous research by analysing spatio-temporal patterns of individual and herd-based disease data to present multiple lines of evidence for disease-driven selection in free-ranging wildlife.

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