DOI: 10.5061/dryad.f4qrfj76b
title: Data from: Landscape and climate-associated selection in the native and widespread bumblebee, <em>Bombus terrestris</em>

description: Anthropogenic land-use and climate change pose novel selection pressures
 on bees, yet their evolutionary responses in terms of morphological or
 physiological adaptations remain unclear. While adaptive responses are
 expected, these may be constrained by gene flow when changes in selection
 pressures are spatially heterogeneous. The buff-tailed bumblebee (Bombus
 terrestris) is a widespread species that copes well with anthropogenic
 land-use and climate change, suggesting high adaptive capacity or
 phenotypic plasticity. Here, we genotyped populations of native B.
 terrestris in south and central Sweden using RADseq to investigate genetic
 structure and local adaptation across a paired design of agricultural
 landscapes with high and low land-use complexity along a geographic
 climate gradient. We expected to find genetic structure reflective of
 regional barriers to gene flow, and molecular evidence for local
 adaptation to differing landscape and climate conditions. We found genetic
 structure separating southern Sweden from more northern regions, with a
 negative Tajima’s D indicating a potential population expansion, likely
 northwards and inland into forested areas, consistent with observational
 data indicating a range shift. We found weak but significant evidence for
 local adaptation to climate and land use, specifically to agricultural
 land cover, including genes under putative selection linked to insecticide
 resistance. Signatures of selection were also identified in relation to
 latitude, temperature, and urban land cover, with other candidate SNPs
 associated with olfaction and immune response. Our results suggest that B.
 terrestris successfully responded to anthropogenic land-use and climate
 changes, likely due to its generalist traits, enabling phenotypic
 adaptation to changing environments.
description: The study design was based on 19 study sites, organized into nine
 matched pairs based on landscape complexity (n=9), in addition to one
 unmatched study site. Within each pair, landscapes were characterized by
 either low or high availability of open semi-natural habitat (simple
 versus complex landscapes, respectively), and study site pairs were
 arranged along a temperature gradient spanning southern and central
 Sweden. Study site pairs were matched to represent
 similar temperatures across the temperature differences of the
 geographical gradient (from the southernmost to northernmost pairs). The
 design crossed three geographical regions in Sweden: Skåne (region 1),
 Västra Götaland (region 2) and Mälardalen (region 3).
 We collected <em>B. terrestris</em> workers during
 two time points at each study site in the summer of 2019 (once in June and
 once in July). <em>Bombus terrestris</em> workers were sexed
 both in the field and subsequently confirmed in the lab by counting the
 number of segments on the flagellum of the antennae under a dissecting
 microscope (males 11 segments, females 10 segments after the pedicel).
 Only female worker bees were retained in the study.
description: # Data from: Landscape and climate-associated selection in the native and
 widespread bumblebee, *Bombus terrestris* Dataset DOI:
 [10.5061/dryad.f4qrfj76b](10.5061/dryad.f4qrfj76b) ## Description of the
 data and file structure Wild *B. terrestris* workers were sampled from 19
 study sites, organized into nine matched pairs based on landscape
 complexity (n=9), in addition to one unmatched study site. Within each
 pair, landscapes were characterized by either low or high availability of
 open semi-natural habitat (simple versus complex landscapes,
 respectively), and study site pairs were arranged along a temperature
 gradient spanning southern and central Sweden. Collected *B. terrestris*
 were extracted for DNA using a custom HotSHOT protocol, followed
 by identification the COI mitochondrial gene and the PCR product  was
 submitted to Macrogen Europe for Sanger sequencing. Samples identified as
 *B. terrestris* were re-extracted for DNA and prepared into genomic
 libraries for RAD sequencing at the Diversity Arrays Technology sequencing
 (DArTseq) facility (Canberra, Australia). Samples were individually
 sequenced on an Illumina Hiseq2500 by DArTseq. ### Files and variables
 #### File: SNP_dataset_1.vcf.gz Description: Dataset 1 consist of 6702
 SNPs and was generated for selection detection analyses. It was filtered
 with the *dartR* package and with the following parameters: monomorphic
 SNPs were removed, and the dataset was filtered for a depth of coverage
 between 10-200, followed by filtering of call rate by loci of &gt;85% and
 removal of SNPs with &lt;100% reproducibility. A minor allele frequency
 (MAF) filter of &gt;0.01 was applied to reduce potential sequencing
 errors. This dataset was used for fineRADstructure, Latent Factor Mixed
 Modelling analysis (LFMM) and multivariate Redundancy Analysis (RDA). ####
 File: SNP_dataset_2.vcf Description: Dataset 2 consists of 4546 SNPs and
 was generated for neutral genetic structure analyses. It was filtered
 identical to Dataset 1 with the additional filters: SNPs were further
 filtered for being out of Hardy Weinberg (HWE), p-value threshold of 1e-6
 using *Plink v.1.9*  and removed from the dataset. Lastly, SNPs were
 filtered for linkage disequilibrium using the *--indep-pairwise 50 (window
 size),* 5 *(step size), and* 0.5 (r^2 threshold) option in *Plink v.1.9.* 
 The dataset was used for calculating the expected (HE), observed (HO)
 heterozygosity, allelic richness (AR), the inbreeding coefficient (FIS),
 pair-wise FST and Tajima’s D for each site. In addition, it was used for
 the Isolation-by-distance (IBD) analysis, PCA, DAPC, ADMIXTURE and EEMS
 analyses. For both datasets, full-siblings has been removed from the
 dataset (*--relatedness2* filter in VCFtools) and samples with high
 percentage of missing data (25 %). These files below were generated from
 Dataset 1 for selection detection analyses and used for fineRADstructure
 analysis, Latent Factor Mixed Modelling analysis (LFMM) and multivariate
 Redundancy Analysis (RDA). #### Input files for fineRADstructure: ####
 File: Dataset_1_chunks.out Description: RADpainter output file with the
 calculate co-ancestry matrix. #### File: Dataset_1_chunks.mcmc.xml
 Description: fineRADstructure output mcmc file which has the individuals
 assigned to populations. #### File: Dataset_1_chunks.mcmcTree.xml
 Description: final fineRADstructure output tree building file. #### Input
 files for LFMM and RDA analysis: Before running LFMM, missing genotypes
 were first imputed, using ancestry coefficients (*snmf* program), using
 the *impute* function within the *LEA* package. #### File: Dataset_1.lfmm
 Description: input file for imputing missing genotypes. #### File:
 Dataset_1_imputed.lfmm Description: output file from running the *snmf*
 program and the input file for the LFMM and RDA analyses.