BackgroundApoid wasps and bees (Apoidea) are an ecologically and morphologically diverse group of Hymenoptera, with some species of bees having evolved eusocial societies. Major problems for our understanding of the evolutionary history of Apoidea have been the difficulty to trace the phylogenetic origin and to reliably estimate the geological age of bees. To address these issues, we compiled a comprehensive phylogenomic dataset by simultaneously analyzing target DNA enrichment and transcriptomic sequence data, comprising 195 single-copy protein-coding genes and covering all major lineages of apoid wasps and bee families.ResultsOur compiled data matrix comprised 284,607 nucleotide sites that we phylogenetically analyzed by applying a combination of domain- and codon-based partitioning schemes. The inferred results confirm the polyphyletic status of the former family “Crabronidae”, which comprises nine major monophyletic lineages. We found the former subfamily Pemphredoninae to be polyphyletic, comprising three distantly related clades. One of them, Ammoplanina, constituted the sister group of bees in all our analyses. We estimate the origin of bees to be in the Early Cretaceous (ca. 128 million years ago), a time period during which angiosperms rapidly radiated. Finally, our phylogenetic analyses revealed that within the Apoidea, (eu)social societies evolved exclusively in a single clade that comprises pemphredonine and philanthine wasps as well as bees.ConclusionBy combining transcriptomic sequences with those obtained via target DNA enrichment, we were able to include an unprecedented large number of apoid wasps in a phylogenetic study for tracing the phylogenetic origin of bees. Our results confirm the polyphyletic nature of the former wasp family Crabonidae, which we here suggest splitting into eight families. Of these, the family Ammoplanidae possibly represents the extant sister lineage of bees. Species of Ammoplanidae are known to hunt thrips, of which some aggregate on flowers and feed on pollen. The specific biology of Ammoplanidae as predators indicates how the transition from a predatory to pollen-collecting life style could have taken place in the evolution of bees. This insight plus the finding that (eu)social societies evolved exclusively in a single subordinated lineage of apoid wasps provides new perspectives for future comparative studies.Electronic supplementary materialThe online version of this article (10.1186/s12862-018-1155-8) contains supplementary material, which is available to authorized users.

Target DNA enrichment combined with high-throughput sequencing technologies is a powerful approach to probing a large number of loci in genomes of interest. However, software algorithms that explicitly consider nucleotide sequence information of target loci in multiple reference species for optimizing design of target enrichment baits to be applicable across a wide range of species have not been developed. Here we present an algorithm that infers target DNA enrichment baits from multiple nucleotide sequence alignments. By applying clustering methods and the combinatorial 1-center sequence optimization to bait design, we are able to minimize the total number of baits required to efficiently probe target loci in multiple species. Consequently, more loci can be probed across species with a given number of baits. Using transcript sequences of 24 apoid wasps (Hymenoptera: Crabronidae, Sphecidae) from the 1KITE project and the gene models of Nasonia vitripennis, we inferred 57,650, 120-bp-long baits for capturing 378 coding sequence sections of 282 genes in apoid wasps. Illumina reduced-representation library sequencing confirmed successful enrichment of the target DNA when applying these baits to DNA of various apoid wasps. The designed baits furthermore enriched a major fraction of the target DNA in distantly related Hymenoptera, such as Formicidae and Chalcidoidea, highlighting the baits' broad taxonomic applicability. The availability of baits with broad taxonomic applicability is of major interest in numerous disciplines, ranging from phylogenetics to biodiversity monitoring. We implemented our new approach in a software package, called BaitFisher, which is open source and freely available at https://github.com/cmayer/BaitFisher-package.git.

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