The impact of geography and climate on the population structure and local adaptation in a wild bee

Deciphering processes that contribute to genetic differentiation and divergent selection of natural populations is useful for evaluating the adaptive potential and resilience of organisms faced with various anthropogenic stressors. Insect pollinator species, including wild bees, provide critical ecosystem services but are highly susceptible to biodiversity declines. Here, we use population genomics to infer the genetic structure and test for evidence of local adaptation in an economically important native pollinator, the small carpenter bee (Ceratina calcarata). Using genome-wide SNP data (n = 8302), collected from specimens across the species' entire distribution, we evaluated population differentiation and genetic diversity and identified putative signatures of selection in the context of geographic and environmental variation. Results of the analyses of principal component and Bayesian clustering were concordant with the presence of two to three genetic clusters, associated with landscape features and inferred phylogeography of the species. All populations examined in our study demonstrated a heterozygote deficit, along with significant levels of inbreeding. We identified 250 robust outlier SNPs, corresponding to 85 annotated genes with known functional relevance to thermoregulation, photoperiod, and responses to various abiotic and biotic stressors. Taken together, these data provide evidence for local adaptation in a wild bee and highlight genetic responses of native pollinators to landscape and climate features.

Comparative metagenomics reveals expanded insights into intra- and interspecific variation among wild bee microbiomes

The holobiont approach proposes that species are most fully understood within the context of their associated microbiomes, and that both host and microbial community are locked in a mutual circuit of co-evolutionary selection. Bees are an ideal group for this approach, as they comprise a critical group of pollinators that contribute to both ecological and agricultural health worldwide. Metagenomic analyses offer comprehensive insights into an organism’s microbiome, diet, and viral load, but remain largely unapplied to wild bees. Here, we present metagenomic data from three species of carpenter bees sampled from around the globe, representative of the first ever carpenter bee core microbiome. Machine learning, co-occurrence, and network analyses reveal that wild bee metagenomes are unique to host species. Further, we find that microbiomes are likely strongly affected by features of their local environment, and feature evidence of plant pathogens previously known only in honey bees. Performing the most comprehensive comparative analysis of bee microbiomes to date we discover that microbiome diversity is inversely proportional to host species social complexity. Our study helps to establish some of the first wild bee hologenomic data while offering powerful empirical insights into the biology and health of vital pollinators.

Global wild bee metagenomes provide insights into microbiome, sociality and pollinator health.