The WZA: A window-based method for characterizing genotype-environment association

Abstract

Genotype environment association (GEA) studies have the potential to elucidate the genetic basis of local adaptation in natural populations. Specifically, GEA approaches look for a correlation between allele frequencies and putatively selective features of the environment. Genetic markers with extreme evidence of correlation with the environment are presumed to be tagging the location of alleles that contribute to local adaptation. In this study, we propose a new method for GEA studies called the weighted-Z analysis (WZA) that combines information from closely linked sites into analysis windows in a way that was inspired by methods for calculating FST. We analyze simulations modelling local adaptation to heterogeneous environments either using a GEA method that controls for population structure or an uncorrected approach. In the majority of cases we tested, the WZA either outperformed single-SNP based approaches or performed similarly. The WZA outperformed individual SNP approaches when the measured environment is not perfectly correlated with the true selection pressure or when a small number of individuals or demes was sampled. We apply the WZA to previously published data from lodgepole pine and identified candidate loci that were not found in the original study.

Large haploblocks underlie rapid adaptation in an invasive weed

“…To identify genome-wide spatial signatures of local adaptation in North American and European ranges, we performed genome scans for population allele frequencies among A. artemisiifolia modern samples that were both highly divergent between populations (BayPass XtX) 39 , and correlated with environmental variables (latitude, longitude and 19 WorldClim temperature and precipitation variables; table S6) 40 . Statistics were analyzed in 10kb windows using the Weighted-Z Analysis (WZA) 41 . In North America (143 samples; 43 populations), 1,480 (84.0%) of the 1,762 outlier windows for genomic divergence (XtX) were also outlier windows for at least one environmental variable (XtX-EAA), while in Europe (141 samples; 31 populations), only 908 (51.7%) of the 1,755 XtX outlier windows overlapped environmental variable outlier windows.…”

“…Associations with latitude and longitude of sampling location, along with the 19 bioclimatic variables, were assessed for correlations with population allele frequencies using Kendall’s τ statistic in R 74 . Genome-wide XtX and τ results were analyzed in non-overlapping 10kb windows using the weighted-Z analysis (WZA) 41 , with the top 5% of windows designated outliers.…”

“…Population allele frequencies were assessed for correlation with 19 bioclimatic variables using Kendall’s τ statistic in R 74 . Genome-wide XtX and τ results were analyzed in non-overlapping 10kbp windows using the weighted-Z analysis (WZA) 39 , with the top 5% of windows designated outliers.…”

Local adaptation and spatiotemporal patterns of genetic diversity revealed by repeated sampling of Caenorhabditis elegans across the Hawaiian Islands

“…Local adaptation can occur in response to varying selection pressures imposed by spatially heterogeneous environments and can cause alleles to vary in frequency across the range of a species (Kawecki & Ebert, 2004). For this reason, alleles correlated with features of the environment are often interpreted as a signature of local adaptation (Booker, Yeaman, & Whitlock, 2021;Coop, Witonsky, Di Rienzo, & Pritchard, 2010). However, disentangling the signatures of local adaptation from patterns caused by neutral forces and/or demographic histories can be difficult (Rellstab, Gugerli, Eckert, Hancock, & Holderegger, 2015).…”

Local adaptation and spatiotemporal patterns of genetic diversity revealed by repeated sampling of Caenorhabditis elegans across the Hawaiian Islands

“…Local adaptation can occur in response to varying selection pressures imposed by spatially heterogeneous environments and can cause alleles to vary in frequency across the range of a species (Kawecki & Ebert, 2004 ). For this reason, alleles correlated with features of the environment are often interpreted as a signature of local adaptation (Booker et al, 2021 ; Coop et al, 2010 ). However, disentangling the signatures of local adaptation from patterns caused by neutral forces and/or demographic histories can be difficult (Rellstab et al, 2015 ).…”