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Data from: Association of putatively adaptive genetic variation with climatic variables differs between a parasite and its host

Citation

Walters, Sheree et al. (2021), Data from: Association of putatively adaptive genetic variation with climatic variables differs between a parasite and its host, Dryad, Dataset, https://doi.org/10.5061/dryad.k3j9kd56n

Abstract

Parasitism is a pervasive phenomenon in nature with the relationship between species driving evolution in both the parasite and host. Due to their host-dependent lifestyle, parasites may adapt to the abiotic environment in ways that differ from their hosts or from free living relatives; yet rarely has this been assessed. Here, we test two competing hypotheses related to whether putatively adaptive genetic variation in a specialist mistletoe associates with the same, or different, climatic variables as its host species. We sampled 11 populations of the specialist mistletoe Amyema gibberula var. tatei (n=154) and 10 populations of its associated host Hakea recurva subsp. recurva (n=160). Reduced-representation sequencing was used to obtain genome-wide markers and putatively adaptive variation detected using genome scan methods. Climate associations were identified using generalised dissimilarity modelling and these were mapped geographically to visualise the spatial patterns of genetic composition. Our results supported the hypothesis of parasites and host species responding differently to climatic variables. Temperature was relatively more important in predicting allelic turnover in the specialist mistletoe while precipitation was more important for the host. This suggests that parasitic plants and host species may respond differently to selective pressures, potentially as a result of differing nutrient acquisition strategies. Specifically, mistletoes acquire water from hosts (rather than the abiotic environment), which may provide a buffer to precipitation as a selective pressure. This work deepens and complements the physiological and other ecological studies of adaptation, and provides a window into the evolutionary processes that underlie previously observed phenomena. Applying these methods to a comparative study in a host-parasite system has also highlighted factors that affect the study of selection pressure on non-model organisms, such as differing adaptation rates and lack of reference genomes.

Methods

Genomic data was generated from individual genotyping of 154 Amyema gibberula var. tatei individuals sampled at 11 populations and 160 Hakea recurva subsp. recurva individuals sampled at 10 populations across the species range. Climatic data was downloaded with 1 km cell resolution from the Worldclim 2.0 database (Fick & Hijmans, 2017; Hijmans et al. 2005).

Usage Notes

SNP Data file for Amyema gibberula var. tatei

This data has 2,055 SNPs row wise and 154 individuals column wise. 0 = zero copies of the reference allele, 1 = one copy of the reference allele (heterozygote), 2 = two copies of the reference allele, 9 = missing data.

SNPData_Amyema_gibberula_var_tatei.txt

 

SNP Data file for Hakea recurva subsp. recurva

This data has 15,422 SNPs row wise and 160 individuals column wise. 0 = zero copies of the reference allele, 1 = one copy of the reference allele (heterozygote), 2 = two copies of the reference allele, 9 = missing data.

SNPData_Hakea_recurva_subsp_recurva.txt

 

LFMM file for Amyema gibberula var. tatei

This data has 154 individuals row wise and 2,055 SNPs column wise. 0 = zero copies of the reference allele, 1 = one copy of the reference allele (heterozygote), 2 = two copies of the reference allele.

LFMM_Amyema_gibberula_var_tatei.lfmm

 

LFMM file for Hakea recurva subsp. recurva

This data has 160 individuals row wise and 15,422 SNPs column wise. 0 = zero copies of the reference allele, 1 = one copy of the reference allele (heterozygote), 2 = two copies of the reference allele.

LFMM_Hakea_recurva_subsp_recurva.lfmm

 

BayPass file for Amyema gibberula var. tatei

This data has allele frequency data for 2,055 SNPs row wise and 11 populations’ column wise. For each population there are two columns, one for the frequency of the reference allele and the other for the frequency of the snp allele.

BayPass_Amyema_gibberula_var_tatei.baypass

 

BayPass file for Hakea recurva subsp. recurva

This data has allele frequency data for 15,422 SNPs row wise and 10 populations’ column wise. For each population there are two columns, one for the frequency of the reference allele and the other for the frequency of the snp allele.

BayPass_Hakea_recurva_subsp_recurva.baypass

 

File with climate data for LFMM analysis of Amyema gibberula var. tatei

Climate data for each individual for use in LFMM analysis. Pop = population, ind = individual ID, bio3 = isothermality, bio4 = temperature seasonality, bio8 = mean temperature of the wettest quarter, bio9 = mean temperature of the driest quarter, bio12 = annual precipitation, bio15 = precipitation seasonality, bio18 = precipitation of the warmest quarter.

ClimateDataLFMM_Amyema_gibberula_var_tatei.txt

 

File with climate data for LFMM analysis of Hakea recurva subsp. recurva

Climate data for each individual for use in LFMM analysis. Pop = population, ind = individual ID, bio3 = isothermality, bio4 = temperature seasonality, bio8 = mean temperature of the wettest quarter, bio9 = mean temperature of the driest quarter, bio12 = annual precipitation, bio15 = precipitation seasonality, bio18 = precipitation of the warmest quarter.

ClimateDataLFMM_Hakea_recurva_subsp_recurva.txt

 

Climate and geographical information for BayPass and GDM analysis of Amyema gibberula var. tatei

Climate and geographical information for BayPass (climate data only) and GDM analysis of Amyema gibberula var. tatei. Bio3 = isothermality, bio4 = temperature seasonality, bio8 = mean temperature of the wettest quarter, bio9 = mean temperature of the driest quarter, bio12 = annual precipitation, bio15 = precipitation seasonality, bio18 = precipitation of the warmest quarter.

ClimateDataBayPassGDM_Amyema_gibberula_var_tatei.txt

 

Climate and geographical information for BayPass and GDM analysis of Hakea recurva subsp. recurva

Climate and geographical information for BayPass (climate data only) and GDM analysis of Hakea recurva subsp. recurva. Bio3 = isothermality, bio4 = temperature seasonality, bio8 = mean temperature of the wettest quarter, bio9 = mean temperature of the driest quarter, bio12 = annual precipitation, bio15 = precipitation seasonality, bio18 = precipitation of the warmest quarter.

ClimateDataBayPassGDM_Hakea_recurva_subsp_recurva.txt

 

FST Matrix for Amyema gibberula var. tatei reference SNPs

Pairwise FST matrix for 11 populations of reference SNPs for GDM analysis.

ReferenceFST_Amyema_gibberula_var_tatei.txt

 

FST Matrix for Amyema gibberula var. tatei candidate SNPs

Pairwise FST matrix for 11 populations of candidate SNPs for GDM analysis.

CandidateFST_Amyema_gibberula_var_tatei.txt

 

FST Matrix for Hakea recurva subsp. recurva reference SNPs

Pairwise FST matrix for 10 populations of reference SNPs for GDM analysis.

ReferenceFST_Hakea_recurva_subsp_recurva.txt

 

FST Matrix for Hakea recurva subsp. recurva candidate SNPs

Pairwise FST matrix for 10 populations of candidate SNPs for GDM analysis.

CandidateFST_Hakea_recurva_subsp_recurva.txt

Funding

Australian Research Council, Award: ICI150100041