Genotype by environment interactions for chronic wasting disease in farmed U.S. white-tailed deer
Data files
Jun 22, 2022 version files 1.27 GB
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1170_WTD_GWAAs_IncludingGxE.tsv
285.31 MB
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286_Northeast_WTD_GWAA_ForMETAL.tsv
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322_Midwest_WTD_GWAA_ForMETAL.tsv
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562_South_WTD_GWAA_ForMETAL.tsv
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AF1_RevisedChecked_EMMAX_GWAA_NoCovariates_Pseudo-Lambda.xlsx
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AF10_RevisedChecked_EMMAX_GxE_GenRegion_BinaryCC_CWD_SexAgeCovs_Pseudo-Lambda.xlsx
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AF11_RevisedChecked_PP_Plot_EMMAX_GxE_GenRegion_SexAgeCovs.png
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AF12_FigureS2_ManhattanPlots_GenomicInflationFactors.docx
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AF13_286NorthEAST_EMMAX_GWAA_NoCovariatesResults_Pseudo-Lambda.xlsx
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AF14_322Midwest_EMMAX_GWAA_NoCovariatesResults_Pseudo-Lambda.xlsx
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AF15_562South_EMMAX_GWAA_NoCovariatesResults_Pseudo-Lambda.xlsx
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AF16_286NorthEAST_EMMAX_GWAA_SexAgeCovariatesResults_Pseudo-Lambda.xlsx
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AF17_286NorthEAST_EMMAX_GWAA_SexAgeFarmCovariatesResults_Pseudo-Lambda.xlsx
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AF17-2_286NorthEAST_EMMAX_GWAA_SexAgeFarmCovariatesResults_Pseudo-Lamda.xlsx
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AF18_322Midwest_EMMAX_GWAA_SexAgeCovariatesResults_Pseudo-Lambda.xlsx
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AF19_322Midwest_EMMAX_GWAA_SexAgeFarmCovariatesResults_Pseudo-Lambda.xlsx
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AF2_PP_Plot_EMMAX_GWAA_NoCovariates.png
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AF20_562South_EMMAX_GWAA_SexAgeCovariatesResults_Pseudo-Lambda.xlsx
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AF21_562South_EMMAX_GWAA_SexAgeFarmCovariatesResults_Pseudo-Lambda.xlsx
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AF22_METAL_Meta-Analysis_WithSharedMainEffectsAndCochransQ_NoCovariates_Pseudo-Lamda.xlsx
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AF23_PP_Plot_METAL_Meta-Analysis_CochransQ_NoCovariates.png
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AF24_PP_Plot_METAL_Meta-Analysis_MainEffects_NoCovariates.png
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AF25_METAL_Meta-Analysis_WithSharedMainEffectsAndCochransQ_SexAgeCovariates_Pseudo-Lambda.xlsx
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AF26_PP_Plot_METAL_Meta-Analysis_CochransQ_SexAgeCovariates.png
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AF27_PP_Plot_METAL_Meta-Analysis_MainEffects_SexAgeCovariates.png
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AF28_METAL_Meta-Analysis_WithSharedMainEffectsAndCochransQ__SexAgeFarmCovariates_Pseudo-Lambda.xlsx
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AF29_PP_Plot_METAL_Meta-Analysis_CochransQ_SexAgeFarmCovariates.png
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AF3_RevisedChecked_EMMAX_BInaryCC_SexAgeUSGenRegionCovariates_Pseudo-Lambda.xlsx
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AF30_PP_Plot_METAL_Meta-Analysis_MainEffects_SexAgeFarmCovariates.png
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AF4_RevisedChecked_PP_Plot_EMMAX_BinaryCC_SexAgeUSGenRegionCovariates.png
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AF5_RevisedChecked_EMMAX_BinaryCC_SexAgeFarmContemp10_Pseudo-Lambda.xlsx
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AF6_RevisedChecked_PP_Plot_EMMAX_BinaryCC_SexAgeFarmContemp10.png
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AF7_FigureS1_ManhattanPlots_GenomicInflationFactors.docx
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AF8_EMMAX_GxE_GWAA_NoCovariatesResults_Pseudo-Lambda.xlsx
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AF9_PP_Plot_EMMAX_GxE_GWAA_NoCovariates.png
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MarkerMap.tsv
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README_Seabury2022.txt
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TableS1_FarmPrevalenceSeabury.xlsx
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TableS2_Revised_2022v2Final.xlsx
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WTD_MetaData_Phenos.xls
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Abstract
Despite the implementation of enhanced management practices, chronic wasting disease (CWD) in U.S. white-tailed deer (Odocoileus virginianus; hereafter WTD) continues to expand geographically. Herein, we perform the largest genome-wide association analysis (GWAA) to date for CWD (n = 412 CWD-positive; n = 758 CWD-non-detect) using a custom Affymetrix Axiom® single nucleotide polymorphism (SNP) array (n = 121,010 SNPs), and confirm that differential susceptibility to CWD is a highly heritable (h2 = 0.611 ± 0.056) polygenic trait in farmed U.S. WTD, but with greater trait complexity than previously appreciated. We also confirm PRNP codon 96 (G96S) as having the largest effects on risk (P ≤ 3.19E-08; Phenotypic Variance Explained ≥ 0.025) across three U.S. regions (Northeast, Midwest, South). However, 20 CWD-positive WTD possessing codon 96SS genotypes were also observed, including one that was lymph node and obex positive. Beyond PRNP, we also detected 23 significant SNPs (P-value ≤ 5E-05) implicating ≥ 24 positional candidate genes; many of which have been directly implicated in Parkinson’s, Alzheimer’s, and prion diseases. Genotype-by-environment (GxE) interaction GWAA revealed a SNP in the lysosomal enzyme gene ARSB as having the most significant regional heterogeneity of effects on CWD (P ≤ 3.20E-06); with increasing copy number of the minor allele increasing susceptibility to CWD in the Northeast and Midwest; but with opposite effects in the South. In addition to ARSB, 38 significant GxE SNPs (P-value ≤ 5E-05) were also detected, thereby implicating ≥ 36 positional candidate genes; the majority of which have also been associated with aspects of Parkinson’s, Alzheimer’s, and prion diseases.
Additional File (AF) 1-29 are detailed summary results and outputs from EMMAX GWAA, EMMAX GxE GWAA, and METAL meta-analysis. Table S1 and Table S2 are supplementary Tables. See ReadMe File.