Transcriptome sequence-based phylogeny of chalcidoid wasps (Hymenoptera: Chalcidoidea) reveals a history of rapid radiations, convergence, and evolutionary success

Molecular Phylogenetics and Evolution 120 (2018) 286–296

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Molecular Phylogenetics and Evolution journal homepage: www.elsevier.com/locate/ympev

Transcriptome sequence-based phylogeny of chalcidoid wasps (Hymenoptera: Chalcidoidea) reveals a history of rapid radiations, convergence, and evolutionary success

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Ralph S. Petersa, ,1, Oliver Niehuisb,c, Simon Gunkeld, Marcel Bläsere, Christoph Mayerf, Lars Podsiadlowskig, Alexey Kozlovh, Alexander Donathf, Simon van Noorti, Shanlin Liuj,k,l, ⁎ Xin Zhoum,n, Bernhard Misoff, John Heratyo, Lars Krogmannp, ,1 a

Center of Taxonomy and Evolutionary Research, Arthropoda Department, Zoologisches Forschungsmuseum Alexander Koenig, 53113 Bonn, Germany Department of Evolutionary Biology and Ecology, Institute for Biology I (Zoology), University of Freiburg, 79104 Freiburg (Brsg.), Germany School of Life Sciences, Arizona State University, Tempe, AZ 85287, USA d Steinmann Institut für Geologie, Mineralogie und Paläontologie, 53115 Bonn, Germany e Zoological Institute, University of Cologne, Zülpicher Straße 47b, 50674 Cologne, Germany f Center for Molecular Biodiversity Research, Zoologisches Forschungsmuseum Alexander Koenig, 53113 Bonn, Germany g Institute of Evolutionary Biology and Ecology, University of Bonn, 53121 Bonn, Germany h Scientific Computing Group, Heidelberg Institute for Theoretical Studies, 69118 Heidelberg, Germany i Department of Natural History, Iziko South African Museum, PO BOX 61, Cape Town 8000, South Africa j China National GeneBank-Shenzhen, BGI-Shenzhen, Shenzhen, Guangdong Province 518083, People’s Republic of China k BGI-Shenzhen, Shenzhen, Guangdong Province 518083, People’s Republic of China l Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, Øster Voldgade 5–7, 1350 Copenhagen, Denmark m Beijing Advanced Innovation Center for Food Nutrition and Human Health, China Agricultural University, Beijing 100193, People’s Republic of China n Department of Entomology, China Agricultural University, Beijing 100193, People’s Republic of China o Department of Entomology, University of California, Riverside, CA 92521, USA p Entomologie, Staatliches Museum für Naturkunde Stuttgart, 70191 Stuttgart, Germany b c

A R T I C L E I N F O

A B S T R A C T

Keywords: Phylogenomics parasitoid wasps evolution biological shifts egg parasitoids fig wasps

Chalcidoidea are a megadiverse group of mostly parasitoid wasps of major ecological and economical importance that are omnipresent in almost all extant terrestrial habitats. The timing and pattern of chalcidoid diversification is so far poorly understood and has left many important questions on the evolutionary history of Chalcidoidea unanswered. In this study, we infer the early divergence events within Chalcidoidea and address the question of whether or not ancestral chalcidoids were small egg parasitoids. We also trace the evolution of some key traits: jumping ability, development of enlarged hind femora, and associations with figs. Our phylogenetic inference is based on the analysis of 3,239 single-copy genes across 48 chalcidoid wasps and outgroups representatives. We applied an innovative a posteriori evaluation approach to molecular clock-dating based on nine carefully validated fossils, resulting in the first molecular clock-based estimation of deep Chalcidoidea divergence times. Our results suggest a late Jurassic origin of Chalcidoidea, with a first divergence of morphologically and biologically distinct groups in the early to mid Cretaceous, between 129 and 81 million years ago (mya). Diversification of most extant lineages happened rapidly after the Cretaceous in the early Paleogene, between 75 and 53 mya. The inferred Chalcidoidea tree suggests a transition from ancestral minute egg parasitoids to larger-bodied parasitoids of other host stages during the early history of chalcidoid evolution. The ability to jump evolved independently at least three times, namely in Eupelmidae, Encyrtidae, and Tanaostigmatidae. Furthermore, the large-bodied strongly sclerotized species with enlarged hind femora in Chalcididae and Leucospidae are not closely related. Finally, the close association of some chalcidoid wasps with figs, either as pollinators, or as inquilines/gallers or as parasitoids, likely evolved at least twice independently: in the Eocene, giving rise to fig pollinators, and in the Oligocene or Miocene, resulting in non-pollinating fig-wasps, including gallers and parasitoids. The origins of very speciose lineages (e.g., Mymaridae, Eulophidae, Pteromalinae) are evenly spread across the period of chalcidoid evolution from early Cretaceous to the late

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Corresponding authors. E-mail addresses: [email protected] (R.S. Peters), [email protected] (L. Krogmann). These authors contributed equally to this work.

https://doi.org/10.1016/j.ympev.2017.12.005 Received 26 April 2017; Received in revised form 12 October 2017; Accepted 4 December 2017 Available online 13 December 2017 1055-7903/ © 2017 Elsevier Inc. All rights reserved.

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Eocene. Several shifts in biology and morphology (e.g., in host exploitation, body shape and size, life history), each followed by rapid radiations, have likely enabled the evolutionary success of Chalcidoidea.

1. Introduction

Chalcidoidea might offer even stronger support for the idea of a small size and egg parasitoidism as being ancestral in Chalcidoidea. This leads to our first working hypothesis: small size and egg parasitoidism in Trichogrammatidae are ancestral traits of Chalcidoidea shared with Mymaridae. We also focus on striking morphological and biological adaptions in Chalcidoidea, i.e., ability to jump, enlargement of hind femora in largebodied strongly sclerotized species, and fig association. One of the most obvious questions regarding chalcidoid evolution is whether the morphological similarities observed in groups with similar life history are the result of convergent evolution or common ancestry. This includes the ability to jump, which is enabled by a number of morphological adaptions, including an enlarged acropleuron, controlled flexion of the mesonotum by specialized first and second axillary sclerites, and a modified mesocoxal articulation (Gibson 1986). This jumping ability is present in Encyrtidae, Eupelmidae, Tanaostigmatidae, and in the genus Coccobius (Aphelinidae). Accordingly, Encyrtidae, Eupelmidae, and Tanaostigmatidae have been hypothesized to form a monophyletic group (LaSalle, 1987; Gibson, 1989; Heraty et al., 2013). Our second working hypothesis is: the ability for extreme jumping originated only once in Chalcidoidea. We further test whether large-bodied and strongly sclerotized groups with enlarged, ventrally toothed hind femora (Chalcididae and Leucospidae) form a natural group, as currently assumed (Gibson, 1993), or whether the apparent similarities between Chalcididae and Leucospidae are the result of convergence. Intriguingly, the function of the strikingly enlarged hind femora is still obscure even though functions for oviposition, male aggression, and courtship behavior have been suggested (Cowan, 1979). An enlarged hind femur is known also from chalcidoid lineages outside of this proposed leucospid-chalcidid clade (i.e., Agamerion and Chalcedectus in Pteromalidae and Podagrion in Torymidae), but based on many other features is suspected in these cases to be convergent (Heraty et al., 2013). Our third hypothesis is therefore: large-bodied strongly sclerotized species with enlarged, ventrally toothed hind femora in Chalcididae and Leucospidae share a common phylogenetic origin. Finally, we address the evolution of fig association. Several chalcidoid taxa are associated with figs (Ficus, Moraceae), either as obligate pollinators, inquilines/gallers, or parasitoids of other gall associates (Compton and van Noort, 1992; Gibson et al., 1999; Cook and Rasplus, 2003; Herre et al., 2008; Segar et al., 2013). It has been difficult to tell if there was a single or several independent origins of fig association, and the taxonomic placement of the fig associates has proven to be notoriously difficult (Rasplus et al., 1998; Gibson et al., 1999; Heraty et al., 2013). We included several fig-associated taxa, currently placed in five subfamilies, in our dataset in order to test our fourth hypothesis: fig association evolved more than once within Chalcidoidea. The timing of the evolutionary history of Chalcidoidea is still largely unknown. The origin of Chalcidoidea was proposed as late Jurassic to early Cretaceous (Yoshimoto, 1975; Schlee and Glöckner, 1978; Ross et al., 2010). The first fossils unambiguously referable to Chalcidoidea are stem group representatives from Aptian Lebanese amber (recently dated 130 million years ago [mya]; Maksoud et al., 2016), which cannot be assigned to extant family groups (Krogmann, unpubl.). Questionable mymarid and pteromalid fossils have been recorded from slightly younger Lower Cretaceous deposits (Kaddumi, 2005; Barling et al., 2013), but the respective family placements are highly unlikely (Heraty et al., 2013; Farache et al., 2016). The oldest unquestioned fossil of Mymaridae is from Burmese amber dated at 99 mya (Poinar and Huber, 2011). Despite a significant Cretaceous fossil record, the

Chalcidoidea (chalcidoid wasps) are a highly diverse group of insects. More than 22,500 extant species have been described and more than 500,000 might actually exist (Noyes, 2016; Heraty, 2017). Chalcidoid wasps are primarily minute parasitoid wasps with an astonishing diversity of morphology and biology (Gibson et al., 1999). Due to their parasitoid life style and broad host range, they not only have a tremendous impact on natural ecosystems, but they also include some of the most successfully and widely used species for biological control of insect pests (Heraty, 2017). Their economic value as natural control agents is inestimable. Chalcidoidea are a well-defined natural group, and, following current classification, comprise 22 families (Heraty et al., 2013). The group is nested within Proctotrupomorpha, a monophyletic group of primarily parasitoid wasps that also includes Cynipoidea, Platygastroidea, Proctotrupoidea, Diaprioidea, and Mymarommatoidea, with the latter usually considered as the sister group of Chalcidoidea (Gibson et al., 1999; Heraty et al., 2011; Sharkey et al., 2012; Heraty et al., 2013). Previous attempts to reconstruct the internal phylogeny of Chalcidoidea suffered from numerous (“a jungle of” [Krogmann and Vilhelmsen, 2006]) morphological homoplasies often associated with small body size and reductions (Krogmann and Vilhelmsen, 2006; Heraty et al., 2013), or from insufficient resolution when applying only a limited number of molecular sequence markers (Desjardins et al., 2007; Munro et al., 2011). When combining the comprehensive morphological data and the limited molecular data in phylogenetic analyses, results can be influenced by a strong bias towards the potentially homoplastic morphological character states (Heraty et al., 2013). Accordingly, a reliable hypothesis of the phylogenetic origins of the many striking evolutionary innovations in Chalcidoidea has not been formulated. In this study, we reconstruct a phylogenetic tree of Chalcidoidea based on large-scale transcriptomic data to solve the problems in understanding the evolution of key features of Chalcidoidea and to contribute towards a more stable classification of the group. We follow, with some modifications, the workflow recently established for insect phylogenomics in the international research initiative 1KITE (Misof et al., 2014). In our analyses, we included 36 species of Chalcidoidea, representing 16 families. Taxon sampling was designed to answer the most pressing questions regarding the evolutionary history of Chalcidoidea with a focus on inferring the early divergence events. First, we address the evolution of small-bodied primarily egg parasitoid lineages and their phylogenetic relationships to lineages whose species typically have a larger body size and who utilize other host stages. Small egg-parasitizing Mymaridae are currently considered as being the sister group of all remaining Chalcidoidea (Munro et al., 2011; Heraty et al., 2013; noting one exception to egg parasitoidism in Mymaridae in the genus Stethynium [Huber et al., 2006]), which has important implications on the putative ancestral biology and morphology of the superfamily. However, the position of other lineages, most notably Trichogrammatidae, which share minute body size and egg parasitoidism with Mymaridae, is still unclear and thus hampers our understanding of the early branching patterns within Chalcidoidea. Based on a combined analysis of molecular and morphological data, a shift from non-egg parasitoidism to egg parasitoidism is thought to have occurred at least nine times within Chalcidoidea, but egg parasitoidism is still considered a possible ancestral trait of the superfamily (Heraty et al., 2013). Placement of Trichogrammatidae closer to the root of

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2.3. Identification and alignment of single-copy genes in the sequenced transcriptomes

largest chalcidoid diversity does not appear until the Eocene, and a rapid post-Cretaceous radiation has been suggested for Chalcidoidea (Heraty et al., 2013; Burks et al., 2015). Here, we present the first molecular dating approach to the deep phylogeny of Chalcidoidea to gain insights into the timing and pattern of divergence events into extant groups and the environmental settings, under which divergences happened. For this purpose, we carefully selected a set of described and undescribed Chalcidoidea fossils and applied an innovative molecular clock approach that allows objective evaluation of calibration schemes and strategies based on their fit to the actual fossil record (Gunkel et al., 2017). The dated tree and our tested hypotheses will help us to understand how Chalcidoidea became what we can observe today: one of the most diverse and abundant insect lineages.

We identified contigs of putative single-copy orthologous genes in the sequenced transcriptomes with the aid of the software Orthograph version 0.5.6 (Petersen et al. 2017). The applied ortholog set comprised 3,260 genes listed by the OrthoDB version 7 database (Waterhouse et al., 2013) to be single-copy at the hierarchical level “Holometabola” and considering the official gene sets of six reference species with wellsequenced and annotated genomes (i.e., Acromyrmex echinatior, Official Gene Set (OGS) version 3.8, Nygaard et al., 2011; Camponotus floridanus and Harpegnathos saltator, each OGS version 3.3, Bonasio et al., 2010; Apis mellifera, OGS version 3.2, Honeybee Genome Sequencing Consortium, 2006; Nasonia vitripennis, OGS version 2.0, Werren et al., 2010; Tribolium castaneum, OGS version 3.0, Tribolium Genome Sequencing Consortium, 2008). For details on the ortholog set and the applied Orthograph settings, please consult Peters et al. (2017). While the amino acid and nucleotide sequences of genes of T. castaneum, A. mellifera, A. echinatior, C. floridanus, and H. saltator were considered when identifying orthologous transcripts, we did not include these sequences in the phylogenetic analyses. The resulting ortholog groups were additionally checked for contamination with sequences of Plutella moth, a potential source of contamination that was detected after the initial cross-contamination checks. The few contaminating sequences discovered were removed. For 21 genes of our ortholog set, identification of orthologous transcripts resulted in no hits. We thus proceeded with 3,239 ortholog groups (OGs). We aligned the sequences of each of the 3,239 OGs on the translational (amino acid) level with MAFFT v7.017 (Katoh and Standley, 2013) using the L-INS-i algorithm. The resulting alignments were checked for outlier amino acid sequences as outlined by Misof et al. (2014). In the next step, the procedure differed from Misof et al. (2014) and Peters et al. (2017). By visual inspection of some multiple amino acid sequence alignments (MSAs) that included sequences classified as outliers, we found that most of these were actually perfectly aligned. In some genes, the sequence variation in our dataset comprising Chalcidoidea and outgroup species surpasses the variation among the reference taxa (note: the distance between reference taxa in relation to the distance between the transcript sequence to its closest reference taxon is used for outlier identification in the procedure applied in Misof et al. (2014) and Peters et al. (2017)). This resulted in some instances in the identification of well-aligned sequences as outliers. Accordingly, we deemed the automated outlier identification check, refinement step, and eventual outlier removal, as done in Misof et al. (2014) not suitable for application on the Chalcidoidea dataset. We therefore manually checked all MSAs with amino acid sequences classified as outliers and manually removed only those that were truly misaligned or had less than 30 overlapping sites to the corresponding sequence of the reference taxon in both the amino acid and the corresponding nucleotide MSAs. All other sequences were kept in the respective MSA. Automatic search for outlier sequences in the 3,239 multiple sequence alignments at the amino acid level led to the identification of 1,504 sequences in a total of 571 genes. In contrast, after manual inspection only 53 sequences in 40 genes were considered true outliers and were removed. This procedure also excluded one gene from the dataset that did not contain any transcript sequences of Chalcidoidea or the outgroups after outlier removal. Next, we excluded sequences from T. castaneum, A. mellifera, A. echinatior, C. floridanus and removed all gap-only sites from the MSAs of amino acids that were present after the removal of outlier and reference taxa sequences. Finally, we generated corresponding nucleotide sequence alignments with a modified version of Pal2Nal version 14.1 (Suyama et al., 2006; see Misof et al., 2014 for details on the modification) using the amino acid sequence alignments as blueprints.

2. Methods 2.1. Taxon sampling and sample preservation We sampled 31 species of Chalcidoidea, which were identified to species level in most cases, representing 16 families and 24 subfamilies, for de novo transcriptome sequencing (Supplementary Table 1). In addition, we included available transcriptomes of five additional species of Chalcidoidea as well as of various outgroups (other superfamilies of Proctotrupomorpha), published by Peters et al. (2017). Outgroups included the following families: Cynipidae (3 spp.), Figitidae (1 sp.), Ibaliidae (1 sp.) (all Cynipoidea), Diapriidae (1 sp.) (Diaprioidea), Platygastridae (3 spp.) (Platygastroidea), Pelecinidae (1 sp.), and Proctotrupidae (1 sp.) (both Proctotrupoidea). All previously published transcriptomes are indicated as such in Supplementary Table 1. Finally, we included genomic sequences of Nasonia vitripennis (Pteromalidae: Pteromalinae) (Werren et al., 2010). Of each species, one or more specimens were immersed alive in RNAlater, immediately ground with a sterile plastic pestle, and then stored at 4°C until further processing. We exclusively used complete adult specimens (whole body transcriptomes). If possible, the sexes of preserved specimens were recorded. Whenever possible, additional specimens of the same species (same collection locality, same morphotype) were preserved as vouchers (paragenophore or syngenophore) (Pleijel et al., 2008), which were either card-mounted or kept in > 95 % ethanol. All vouchers are deposited at the Zoologisches Forschungsmuseum Alexander Koenig, Bonn (ZFMK) or at the Iziko South African Museum, Cape Town (SAMC). All information on specimen collection, preservation, number of specimens, sexes, and the sex ratio, if applicable, is listed in Supplementary Table 1.

2.2. Transcriptome sequencing, assembly, and contamination check RNA extraction, NGS library preparation, and sequencing of the prepared libraries on Illumina HiSeq sequencers followed the protocols given by Peters et al. (2017). cDNA libraries were paired-end sequenced on Illumina HiSeq2000 sequencing platforms (Illumina Inc., San Diego, CA, USA) with read length of 150 base pairs (bp). Libraries, which were prepared with the TruSeq mRNA Library Prep Kit (Illumina) (read length 90 bp), are marked accordingly in Supplementary Table 1. Per species, we collected about 2.5 Gbp of raw sequence data. All raw reads were quality-controlled, assembled, and screened for possible contaminant sequences (which were then removed) as described by Peters et al. (2017) (see Supplementary Table 2 for the amount of removed contaminants from each species dataset). Both the raw reads and the assembled transcriptomes are archived at the National Center for Biotechnology Information, NIH, under the Umbrella BioProject ID PRJNA183205 (“The 1KITE project: evolution of insects”). For a full list of accession numbers see Supplementary Table 3.

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way as described by Peters et al. (2017). We pruned all taxa identified as rogues with any of the settings from the bootstrap trees and made a reduced consensus tree, using the respective commands in RogueNaRok and RAxML version 8.0.26. In addition, we generated a decisive dataset, in which only data blocks are kept that contain sequence information of at least one representative of selected taxonomic groups (see Dell’Ampio et al., 2013 and Misof et al., 2014). The taxonomic groups are listed in Supplementary Table 4. For this dataset, we conducted the same search for a partitioning scheme and best-fitting models as described above and conducted ten tree searches using completely random starting trees (with the same software and methods as outlined above). Statistics of all analyzed supermatrices (number of partitions, number of amino acid or nucleotide sites) are listed in Supplementary Table 5. All phylogenetic trees were rooted with the non-chalcidoid non-diaprioid taxa, drawn with FigTree version 1.4.2, and edited with Inkscape 0.48.

2.4. Phylogenetic analyses All amino acid alignments were searched for sequence sections with random similarity or alignment ambiguity with Aliscore version 1.2 (Misof and Misof, 2009; Kück et al., 2010) using the '-e' option of a modified version of the software that is able to cope with transcript sequence alignments containing many gaps (Meusemann et al., 2010). Aliscore was run with default sliding window size and the –r 1027 option in order to compare all sequence pairs in each sliding window. We applied a protein domain-based partitioning scheme to improve the fit of substitution models to the amino acid and nucleotide sequence data, as suggested by Misof et al. (2014). We identified protein domains, families, and clans in each predicted transcript at the amino acid level by exploiting the databases Pfam A and Pfam B (release 27; Finn et al., 2014) and using the software PfamScan version 1.5 (released 2013-10-15, Finn et al., 2014) and HMMER version 3.1b2 (Eddy, 2011) as outlined by Misof et al. (2014) and Peters et al. (2017). We then merged the coordinates received from the protein domain identification with the information from Aliscore, deleting sequence sections as proposed by Aliscore, and concatenating the data blocks (consisting of domains belonging to the same clans, domains belonging to the same domain families, single domains and voids [i.e., regions without protein domain annotation] belonging to the same gene) into a supermatrix on the amino acid level and a supermatrix on the nucleotide level. When concatenating data blocks, terminal gap symbols in data blocks ('-') were masked with 'X' and 'N' in the amino acid and the nucleotide alignments, respectively. The concatenated amino acid supermatrix was used to evaluate the information content of each data block with the software MARE version 0.1.2-rc (Misof et al., 2013). All data blocks with zero information content were removed. We then searched for both an optimal partitioning scheme and bestfitting substitution models to the inferred partitions with PartitionFinder version 2.0 prerelease 2 (http://www.robertlanfear. com/partitionfinder/; Lanfear et al., 2014, 2017) with the command line options '–raxml –weights 1,1,0,1 –rcluster-max 10000 –rclusterpercent 100’. In the configuration file, we specified the following substitution models to be tested by the PartitionFinder software: WAG+G, WAG+G+F, BLOSUM62+G, BLOSUM62+G+F, DCMUT+G, DCMUT+G+F, JTT+G, JTT+G+F, LG+G, LG+G+F, LG4X. We used the corrected Akaike information criterion (AICc; Hurvich and Tsai, 1989) as optimality criterion when searching for the best partitioning scheme. When analyzing the supermatrix at the nucleotide level, we mapped the partitioning scheme from the amino acid to the nucleotide coordinates and applied the GTR+G model on all partitions. The supermatrix on the nucleotide level was analyzed with only first and second codon positions and with all three codon positions included. In both cases, we split the nucleotide partitions into separate partitions based on codon positions. Phylogenetic relationships were inferred by applying the Maximum Likelihood (ML) optimality criterion and using the software ExaML version 3.0.15 (Kozlov et al., 2015). We conducted 50 tree searches, using completely random starting trees. All starting trees were generated with RAxML version 8.0.26 (Stamatakis, 2014). We assessed support for individual phylogenetic relationships by partitioned non-parametric bootstrapping from a total of 100 (amino acids), 800 (nucleotides, 1st and 2nd position), and 50 (nucleotides, all positions) bootstrap replicates with ExaML version 3.0.15 (Kozlov et al., 2015). We assessed whether or not the number of bootstrap replicates was sufficient for assessing support for different hypothesis by applying the bootstopping criterion (Pattengale et al., 2010) as implemented in RAxML version 8.2.7 (Weighted Robinson-Foulds distance building an extended majority-rule (MRE) consensus tree (autoMRE, threshold [0.03], with 1,000 permutations; Stamatakis, 2014)). We also searched for rogue taxa in the trees inferred from analyzing the amino acid and the nucleotide sequence data (1st and 2nd codon position only), using the software RogueNaRok version 1.0 (Aberer et al., 2013) in the same

2.5. Divergence time estimation To estimate node ages, we used mcmctree, which is part of the PAML package version 4.9b (Yang, 2007). We applied the approximate likelihood method (Dos Reis and Yang, 2011) by generating a single Hessian matrix from our amino acid supermatrix with codeml using standard parameters and the JTT model. In an earlier study using the same software and a comparable transcriptome sequence dataset (Peters et al., 2017), we tested whether or not our data allowed for the generation and subsequent combination of partition-specific Hessian matrices. This approach would allow different models to be applied to different partitions. However, as in this earlier study, we found that most partitions lacked the amino acid sequence information of at least one taxon, rendering this approach unfeasible. All analyses described below used standard settings, with a conservative root age set to 300 mya, burn-in to 50,000 iterations and number of samples set to 1,000,000 iterations with a sample frequency of two. Values for burn-in and samples were based on test runs with increasing values until the results repeatedly converged, as described in more detail by Peters et al. (2017). We used a total of nine fossil calibration points (Table 1), selected in accordance with the criteria for fossil calibrations given by Parham et al. (2012). In a first series of analyses, we generated node age estimates (=dated trees) for all possible combinations of the nine calibrations points. All calibrations were implemented as soft minima with default settings (i.e., as truncated Cauchy distributions with an offset of 0.1, a scale parameter of 1, and a left tail probability of 0.025). In total, we obtained 511 dated trees with identical topologies but with different node age estimates. The 511 dated trees were scored using the λ-score method (Gunkel et al., 2017), which allows a comparison of different node age estimates for the same phylogeny. In short, the method uses a large sample of fossil taxa to estimate fossilization rates through time (here for fossil Hexapoda) and then evaluates node age estimates by their consistency with these fossilization rates, expressed by the λscore. The tree/node age estimate with the highest λ-score is considered to be the best, i.e., most likely for the dataset, given the actual fossil record. The highest λ-score (Supplementary Fig. 1) was obtained for a calibration including only three fossils (fossils C1, C3, and C6, Table 1). For different dating results and their λ-score see Supplementary Figs. 1 and 2. Note that all trees in which one or more of the nodes were younger than determined by a respective fossil/calibration point are not evaluated and not shown in Supplementary Figs. 1 and 2. In a second series of analyses, we used only these three calibration points. For each calibration point/node, we used eight different settings: (1) soft minimum only (same as in the first analysis run), (2) soft minimum and soft maximum at 300 mya, (3) soft minimum and soft maximum at the minimum plus 5 mya, (4) soft minimum and soft maximum at the minimum plus 10 mya, (5) soft minimum and soft maximum at the minimum plus 20 mya, 6) wide normal distribution, 289

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with µ set to the minimum age and σ to half the difference between the oldest and youngest age estimates for the fossil, (7) narrow normal distribution, with µ set to the minimum age as in 6, but with σ set to half its original value, (8) skewed wide normal distribution, with µ set to the minimum age and σ to half the difference between the oldest and youngest age estimates for the fossil as in 6, but with a skew value of 10. Again, all possible combinations were tested and the resulting 512 node age estimates were scored (Supplementary Fig. 2). None of the additional calibration variants had a λ-score exceeding the one obtained for the calibration using soft minima only. Accordingly, from all 1,023 calibration schemes tested, we used for Fig. 1 the node age estimates from the analysis with fossils C1, C3, and C6 included, and all calibration points defined as soft minima (for exact means and 95% confidence intervals [CIs] see Fig. 2 and Supplementary Table 6).

frenum and marginal rim of the scutellum visible in dorsal view, prepectus forms a large equilateral triangle elongated shape of metasoma

3. Results and discussion

Chalcidoidea: Ormyridae

Chalcidoidea: Leucospidae Chalcidoidea: Agaonidae

Chalcidoidea: Perilampidae: Perilampus Proctotrupoidea: Pelecinidae

C4

C5

C6 C7

C8

Archaeopelecinus tebbei Shih et al, 2009

Sandstone

171–161

The inferred phylogenetic tree of major Chalcidoidea lineages is the first one based on a phylogenomic dataset (see Supplementary Table 7 for assembly statistics and number of identified target genes in the analyzed transcriptomes) and including a time line for branching patterns across the whole superfamily. The deepest splits in this backbone tree are maximally supported in all of our analyses (Figs. 1 and 2, Supplementary Figs. 3–8). Mymaridae are identified as sister group to all remaining Chalcidoidea. This phylogenetic relationship has been suggested before based on molecular data and on combined molecular and morphology data sets (Munro et al., 2011; Sharkey et al., 2012; Heraty et al., 2013), albeit with low or moderate support. It has not been substantiated by analyzing morphological data only, likely because of convergent morphological character reductions (Krogmann and Vilhelmsen, 2006; Heraty et al., 2013). Our results provide the strongest support for a sister group relationship between Mymaridae and the remaining Chalcidoidea (node 1 in Fig. 1). This first split within Chalcidoidea is dated at 129 mya (95% confidence interval [CI]: 208–89 mya), which is in accordance with the fossil record, whereby stem group Chalcidoidea are from Aptian Lebanese amber (130 mya), while the first crown group representatives, the oldest verified Mymaridae, are significantly younger (99 mya) (Poinar and Huber, 2011). Regarding the age of Chalcidoidea, we can state that they originated roughly between 174 mya (CI: 273–114 mya, age refers to split between Chalcidoidea and the outgroups) and 129 mya (CI: 208–89 mya, age refers to split between Mymaridae and remaining Chalcidoidea), thus probably in the late Jurassic or in the very early Cretaceous. These results correspond well with what has been suggested in earlier studies (Yoshimoto, 1975; Schlee and Glöckner, 1978; Ross et al., 2010). The next split is between Trichogrammatidae and the remaining groups of Chalcidoidea (node 2). Monophyly of Trichogrammatidae has never been questioned, and as we focus on higher level relationships, we here use a single representative to place the entire family (this also applies to other monophyletic families or subfamilies, which will be discussed in the following, unless stated otherwise). As are Mymaridae, Trichogrammatidae are small egg parasitoids that lack metallic coloration. The remaining Chalcidoidea are an extraordinarily diverse group in terms of host use, body shapes, color, and biology (Fig. 1). The branching patterns between Mymaridae, Trichogrammatidae and the remaining Chalcidoidea allow parsimony-based reconstruction of the ancestral state of body size and host biology. It is equally parsimonious to assume the ancestral Chalcidoidea being small egg parasitoids or being larger-bodied parasitoids of other host stages, with two switches to being small egg parasitoids in Mymaridae and Trichogrammatidae. However, the probable sister group of Chalcidoidea, the Mymarommatoidea (Gibson et al., 1999; a rarely collected group not included in our dataset), have an unknown biology, but are also very small in size, suggesting that they might be egg parasitoids. When we further consider that the earliest Chalcidoidea fossils (fossil C1, Table 1, unpublished) are also small in size, suggesting development within host

C9

Chalcidoidea: Chalcididae: Chalcidinae Chalcidoidea: Encyrtidae C3

Perilampus pisticus Darling, 2009

Baltic amber

54–38

longitudinally folded fore wings pollen pockets

Engel (2002) Compton et al. (2010) Heraty and Darling (2009) Shih et al. (2009) Dominican amber Limestone

20–15 34

metasomal terga with rows of pits SMNS 54–38 Baltic amber

54–38

Chalcidoidea: Mymaridae C2

Undescribed species, specimen deposited in the Muséum national d’Histoire naturelle, Paris. Undescribed species, specimen deposited in the State Museum of Natural History Stuttgart. Undescribed species, specimen deposited in the State Museum of Natural History Stuttgart. Leucospis glaesaria Engel, 2002 Undescribed (called ‘Ponera’ minuta)

French Oise amber Baltic amber

55–52

SMNS

fore wing narrow, postmarginal vein absent; hind wing narrow, wing membrane presumably not extending to base metatibia with elongate spine produced well beyond tarsal insertion, postmarginal vein elongate acropleuron enlarged, cercal plates advanced Burmese amber

125–120 Chalcidoidea C1

Undescribed species, specimen deposited in the Natural History Museum of the Lebanese University, Faculty of Sciences II, Fanar, Lebanon, female, Coll. No. 874A Myanmymar aresconoides Huber, 2011

Lebanese amber

99

Poinar and Huber (2011) MNHN

presence of multiporous plate sensillae on antenna

Apomorphy Reference Age [Ma] Fossil deposit Species Placement Number

Table 1 Information on fossils used to calibrate the inferred phylogenetic tree of Chalcidoidea and to estimate divergence times. Note that the age of fossil C1 from Lebanese amber differs from the age given for Lebanese amber in the main text. The amber was redated after completion of the analyses (Maksoud et al., 2016; now 130 mya).

R.S. Peters et al.

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Fig. 1. Phylogenetic relationships and divergence time estimates of Chalcidoidea. The tree was inferred under the maximum likelihood optimality criterion, analyzing 1,469,006 amino acid sites and applying a combination of protein domain- and gene-specific substitution models. Divergence times were estimated with an independent-rates molecular clock approach and considering nine validated fossils. Divergence times shown are those from the analysis having the highest score out of 1,023 dating analyses, which comprise all possible combinations of fossils included and eight different settings for a subset of these fossils. The dating analyses were scored with an a posteriori evaluation considering the consistency of the results with the fossilization rates (see methods for more details). P = Pteromalidae, T = Torymidae. Scale bars represent 1 mm. Images by O. Niehuis, with assistance from R.S. Peters. Nodes with circled numbers are referred to in the main text.

support for this hypothesis can be derived from shared features among all Chalcidoidea that may carry the heritage of small ancestors, most notably the highly reduced wing venation. The first branching group (at 86 mya, CI: 146–62 mya) within the main group of Chalcidoidea are Eulophidae (node 3). Eulophidae are a diverse group that utilizes a variety of host groups and host stages. They may be among the first lineages in the history of Chalcidoidea using hosts other than eggs and having metallic coloration. The most notable feature of Eulophidae is the reduction of the number of tarsomeres from five to four. However, reduction of tarsomeres can be found in numerous other chalcidoid lineages (Heraty et al., 2013), reducing the historic importance (Walker, 1833) of using the number of tarsomeres for the higher classification of the superfamily. The next branching group in our phylogenetic tree includes Encyrtidae and Aphelinidae (81 mya, CI: 137–58 mya) (node 4). Note that Aphelinidae are a very diverse group, which was shown not to be monophyletic (Campbell et al., 2000; Munro et al., 2011; Heraty et al., 2013). In our dataset, Aphelinidae are represented by only two subfamilies, Aphelininae and Coccophaginae, which are likely monophyletic, although not maximally supported in the nucleotide-level analyses (Supplementary Figs. 4 and 5). Many species in this Encyrtidae-Aphelinidae clade parasitize hemipterans, although formal reconstruction of the ancestral host is impossible because of the

eggs, our results imply that the ancestral Chalcidoidea may have been small egg parasitoids and therefore support our first hypothesis, namely that small size and egg parasitoidism in Trichogrammatidae is an ancestral trait shared with Mymaridae. In this regard, the chalcidoid family Rotoitidae has to be mentioned, which is not part of our taxon sampling. Again, due to its small body size and extreme rareness, preservation of rotoitid samples for transcriptome analyses is likely impossible. Rotoitidae are restricted to New Zealand and Chile and may represent an early lineage of Chalcidoidea, probably branching off after Mymaridae (Munro et al., 2011; Heraty et al., 2013). The biology of rotoitids is unknown, but their small body size implies that they might also be egg parasitoids. Accordingly, the inclusion of Rotoitidae in our taxon sampling would not have altered the above conclusion. However, the inclusion of signiphorids, eriaporids and other lineages, which have been found putatively closely related to trichogrammatids (Heraty et al., 2013), as well as of more outgroup taxa to pinpoint the sister group of Chalcidoidea, may challenge or confirm our hypothesis in the future. Miniaturization in the groundplan of Chalcidoidea and the subsequent evolution of comparatively large-bodied forms (the body size of the largest chalcidoids exceeds 4 cm) would appear to follow Cope’s rule, which posits that it is common for stem groups of speciesrich clades to be small in body size and to experience a body size increase during diversification (Hanken and Wake, 1993). Morphological 291

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Fig. 2. Inferred ultrametric and time-calibrated tree with node numbers. The phylogenetic tree is identical to the one shown in Fig. 1, but additionally shows the 95% confidence intervals of estimated divergence times (blue bars). The consecutively numbered nodes (black numbers behind nodes) refer to Supplementary Table 6, in which all estimated divergence times and 95% confidence intervals are listed.

Pteromalinae. The Pteromalinae are generally a very morphologically uniform group of wasps, and the inclusion of the morphologically extremely diverse fig associates within this clade is a surprising, but consistent result from all of these molecular analyses. It suggests that the colonization of the fig ecological niche provided novel selection pressures, for morphological and biological adaptation, on these figassociated pteromaline lineages. This is exemplified by the extreme morphological adaptation (e.g., flattened head, enlarged mandibles) that evolved convergently in the Sycoecinae and the pollinators (Agaonidae), driven by the fact that both lineages enter the fig through the ostiole for oviposition, and hence have been exposed to the same selection pressures to facilitate successful penetration of the fig cavity (van Noort and Compton, 1996). Evolution of a long ovipositor in the parasitoid group Sycoryctinae is tied to external oviposition through the fig wall at a later stage of fig development (Tzeng et al., 2008; McLeish et al., 2010; Segar et al., 2012). The Sycoecinae and Otitesellinae are gall makers (Compton and van Noort, 1992), and given that the Pteromalinae are parasitoids, these two fig-associated lineages are likely to have developed phytophagy as a derived trait. Whether this is a result of common ancestry in an early colonizing ancestor of the two groups (Sycoecinae and Otitesellinae) or an independently evolved attribute associated with independent colonization events by the two lineages, is a question that needs to be addressed in further studies. Another independent and well-supported group of fig associates includes the true fig wasps (Agaonidae) and Epichrysomallinae (Pteromalidae) (node 6), which grouped with the other pteromalinerelated fig associates (see above) in the study by Heraty et al. (2013). We are missing in our study one subfamily of fig associates, Sycophaginae, which was placed with Agaonidae by Heraty et al. (2013). While Agaonidae are pollinators in figs, both Epichrysomallinae and Sycophaginae are gall-makers within figs (Rasplus et al., 1998).

unresolved internal phylogeny of both groups. These early branching events are dated between 129 mya (CI: 208–89 mya) and 81 mya (CI: 137–58 mya) in the Cretaceous. This indicates that the diversification of Chalcidoidea into biologically and morphologically very different groups occurred earlier than previously thought (e.g., Heraty et al. 2013). We here provide evidence that the suggested post-Cretaceous radiation of Chalcidoidea (Heraty et al., 2013) was already preceded by a major diversification in the Cretaceous. This would correlate chalcidoid diversification with the diversification of potential insect host groups (Gullan and Cook, 2007) and associated angiosperms (Soltis and Soltis, 2004). The sister group to the Aphelinidae-Encyrtidae clade is a well-supported highly diverse monophyletic group of the remaining Chalcidoidea (node 4). Within these, support for phylogenetic relationships is low, and results are partly incongruent between amino acid data and nucleotide data analyses (Fig. 1, Supplementary Figs. 3 and 4). Many relationships can be best illustrated by a polytomy as in Fig. 3 (a cladogram summarizing the highly supported clades resulting from analyzing amino acid data and nucleotide data). However, even in this part of the tree, some relationships are well-supported and congruent between the analyses of different datasets. Implications from these relationships on our formulated hypotheses are given after presentation and discussion of the well-supported groups. The first well-supported group includes Pteromalinae and three subfamilies of fig associates (i.e., Sycoecinae, Otitesellinae, and Sycoryctinae) (node 5). The latter subfamilies have been placed in Pteromalidae (Rasplus et al., 1998) or Agaonidae (Bouček, 1988). In the analyses by Munro et al. (2011) and by Heraty et al. (2013), these three subfamilies also grouped with Pteromalinae (and other pteromalid subfamilies not included in our dataset), albeit with low support. We can, for the first time, reliably place these taxa together with

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Fig. 3. Cladogram showing only those relationships as resolved that were supported by more than 70% of the bootstrap replicates in the three phylogenetic trees, inferred from analyzing the amino acid data and nucleotide data (all codon positions and 1st and 2nd codon positions only). P = Pteromalidae, T = Torymidae.

resulting from limitations in the taxon sampling. Oodera is a very unique genus that is currently placed in Cleonyminae (Pteromalidae) and has been historically placed in either Pteromalidae or Eupelmidae (Graham, 1969). Its phylogenetic origin has so far been totally unclear. Based on our results, we can safely state that Oodera is neither related to Eupelmidae (represented only by Eupelminae) nor to any of the included pteromalid subfamilies. The remaining well-supported clades include only representatives of families or subfamilies whose monophyly has never been questioned (i.e., Eurytominae, Eupelminae, Toryminae). These groups, however, along with the remaining included taxa (i.e., Spalangiinae, Cerocephalinae, Megastigminae, Chalcidinae) cannot be robustly placed, and relationships among these remain obscure. The analyses at the amino acid level favor (with maximum support, Fig. 1) a sister group relation of Chalcididae (Chalcidinae) and Eurytomidae (Eurytominae). There also is considerable support for the hypothesis of monophyletic Eupelminae plus Pteromalinae (including fig associates, see above). None of the analyses suggests Torymidae (Toryminae plus Megastigminae) being monophyletic, in agreement with results put forth by Munro et al. (2011). Resolving the phylogenetic relationships among the chalcidoid lineages mentioned above is a

Sycophaginae and the other subfamilies of Agaonidae need to be included to get a full picture of the evolution of these associations in Chalcidoidea. The third well-supported group within the virtually unresolved large Chalcidoidea clade are Perilampidae plus Eucharitidae (node 7). This relationship has been recovered before with good support from both morphology and molecular sequence data (Munro et al., 2011; Heraty et al., 2013). Perilampidae and Eucharitidae share a number of synapomorphies, the most distinct being the development of highly specialized active first-instar larvae (planidia) (Heraty and Darling, 1984). The fourth well-supported group includes Tanaostigmatidae and Ormyridae (node 8), a relationship that has not been previously suggested. Tanaostigmatidae and Ormyridae are morphologically highly distinct lineages that do not share any obvious synapomorphies. However, they share a common biological trait, which is a close and highly specific plant association. Tanaostigmatids are primarily gall formers (LaSalle, 1987), while ormyrids are primarily parasitoids of gall forming insects (Hanson, 1992). The fifth well-supported group is Oodera plus Leucospidae (node 9). This clade has not been proposed before and may be an artifact 293

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not only extremely species-rich but also very distinct in morphology, biology, life history, and development. Interestingly, our results suggest that the tremendous extant diversity in Chalcidoidea is not the result of a single evolutionary novelty but represents a continuous series of separate and very distinct successful groups (in terms of biological and species diversity), each representative of a shift in biology and host exploitation. Considering the relatively young age of the group, Chalcidoidea show an unprecedented diversity of life histories, body shapes and sizes, and separate evolutionary success stories. With this study, our understanding of Chalcidoidea evolution has improved, but we have yet to face the many stories in the evolution of the possibly 500,000 species of Chalcidoidea that are still to be unraveled, with the ultimate goal of understanding all major events and eventually grouping the extant taxa in a natural classification. Such a classification would facilitate future comparative studies on Chalcidoidea, including their biology, morphology and genomes.

challenge that needs to be targeted in a more comprehensive study based on a much larger taxon sample. However, it is possible that the difficulties of resolving this part of the Chalcidoidea tree will persist, even when more taxa and/or more genes are included in an analysis. All the splits in question seem to have occurred in a comparatively short period of time between 75 and 53 mya, towards the end of or shortly after the Cretaceous. Our data suggest a rapid post-Cretaceous radiation of Chalcidoidea that was previously only indirectly concluded from the fossil record (e.g., by Heraty et al., 2013). This historic rapid radiation, resulting in short branch lengths in the phylogenetic tree, may likely hamper obtaining full resolution of these Chalcidoidea relationships. The branching patterns presented here that are well supported have important implications for our understanding of major biological transitions during Chalcidoidea evolution. We can identify three major events of convergent evolution in morphology and biology: first, the ability to jump, along with seemingly similar modifications of the body, evolved convergently in Encyrtidae, Eupelmidae, and Tanaostigmatidae, refuting our hypothesis 2. Based on morphologyonly or combined data, the three families have been thought to constitute a monophyletic group (LaSalle, 1987; Gibson, 1989; Heraty et al., 2013), while information from molecular data alone did not support this idea (Munro et al., 2011). The insight that the three families are not closely related will foster future research on the jumping ability within these groups, under the premise that evolution has taken two or more ways to get to a very similar result. It remains puzzling why these groups independently evolved jumping behavior despite their fundamentally different biologies. Second, the habitus of comparatively large-bodied highly sclerotized forms with enlarged and toothed hind femora evolved convergently in Chalcididae and Leucospidae, refuting our hypothesis 3. Chalcididae and Leucospidae have traditionally been thought to constitute a natural group or to be at least closely related (Gibson, 1993). Tree topologies suggest their similar habitus to be the result of convergence, and, as in the groups that show the ability to jump, future studies should aim to detect the differences that are hidden behind the seeming similarity. Despite its unclear biological function, an enlarged and toothed hind femur seems prone to convergence as it also appears in other chalcidoid taxa (e.g., Pteromalidae: Cleonyminae: Chalcedectini and Torymidae: Toryminae: Podagrionini) that are considered distantly related to Chalcididae and Leucospidae (Heraty et al., 2013). These distinct morphological features seem to have special importance for the respective chalcidoid groups, with selective pressures having worked several times independently to form the same general habitus. Third, we demonstrate convergent evolution of fig association in at least two cases, confirming our hypothesis 4. An association with figs is a very striking feature in Chalcidoidea, since it includes a symbiotic relationship, in which each fig species is obligatorily pollinated by its own gall-making fig wasp (Agaonidae) (Wiebes, 1986). The fig associations in the non-pollinating chalcidoid groups are either as phytophagous gall-makers, inquilines inside figs, or as parasitoids of other fig-inhabiting chalcidoids. These two fig associations evolved at very different times (Fig. 1). Expectedly, the pollinating fig wasps are much older than their parasitoids and inquilines (49 mya, CI: 89–27 mya vs. 26 mya, CI: 39–15 mya). The age we found for the origin of fig association is younger than found by other authors but, considering the confidence intervals, in accordance with the age of 100–65 mya estimated by Rønsted et al. (2005) or 95–56 mya inferred by Cruaud et al. (2012) for crown Agaonidae. Cruaud et al. (2012) estimated the crown age of figs at 102–60 mya. As a general pattern of Chalcidoidea evolution, we found that the most diverse lineages consecutively split over a range of almost 100 million years. These diverse lineages include in the order of appearance Mymaridae (egg parasitoids), Trichogrammatidae (egg parasitoids), Eulophidae (parasitoids of various hosts), Encyrtidae plus Aphelinidae (parasitoids of “Homoptera” and various other hosts), Agaonidae (fig wasps), and Pteromalinae (parasitoids of various hosts and tentatively including the three subfamilies of fig associates). All of these groups are

Acknowledgments The presented data are the result of the collaborative efforts of the 1KITE consortium. The sequencing and assembly of the 1KITE transcriptomes were funded by BGI through support to the China National GeneBank. We thank H. Baur and G. Gibson for help with identification of samples and R. Allemand, C. Barandica, J. Chille, M. Fierke, P. Flinn, M. Kivan, T. Kothe, K. Kraaijeveld, M. Kubiak, D.W. Morgan, M. Niehuis, P. Schüle, and J. Steidle for providing valuable samples. We are grateful to S. Brown, D. Gilbert, J. Liebig, R. Waterhouse for providing information required for the transcript orthology prediction. We thank V. Achter, D. Bartel, A. Böhm, K. Meusemann, S. Simon, A. Stamatakis, V. Winkelmann, the Cologne High Efficient Operating Platform for Science (CHEOPS) at the Regionales Rechenzentrum Köln (RRZ) for computing time and/or bioinformatic support. We furthermore acknowledge the Gauss Centre for Supercomputing e.V. for funding computing time on the GCS Supercomputer SuperMUC at the Leibniz Supercomputing Centre (LRZ). We acknowledge the Amt für Umwelt, Verbraucherschutz und Lokale Agenda of Bonn, Hessen Forst, the Israeli Nature and National Parks Protection Authority, the Struktur- und Genehmigungsbehörde Süd and the Struktur- und Genehmigungsdirektion Nord (both Rhineland Palatinate) for granting permission to collect samples. A.D., B.M., C.M., J.R., L.P., M.P., O.N., R.S.P., S.G. were supported by the Leibniz Graduate School for Genomic Biodiversity Research. O.N. acknowledges the German Research Foundation (DFG) for sponsoring field work during which some of the analyzed samples were collected (NI 1387/1-1). X.Z. is also supported by the Chinese Universities Scientific Fund, 2017QC114. Author contributions B.M., L.K., O.N., and R.S.P. conceived the study. J.H., L.K., O.N., R.S.P., and S.v.N. collected or provided samples. A.D., L.P., O.N., R.S.P., S.L., and X.Z. sequenced, assembled, and processed the transcriptomes. A.K., C.M., M.B., M.P., and R.S.P. phylogenetically analyzed the transcriptomes. L.K., M.B., R.S.P., and S.G. are responsible for the dating of the inferred phylogeny. All authors contributed to the writing of the manuscript, with J.H., L.K., and R.S.P. taking the lead. Appendix A. Supplementary material Supplementary data associated with this article can be found, in the online version, at https://doi.org/10.1016/j.ympev.2017.12.005. All inferred matrices and statistics are available at the Mendeley data repository (https://doi.org/10.17632/gntfkfkryd.1). References Aberer, A.J., Krompass, D., Stamatakis, A., 2013. Pruning rogue taxa improves

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