Mitochondrial phylogenomics of the Hymenoptera

Molecular Phylogenetics and Evolution 131 (2019) 8–18

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

Mitochondrial phylogenomics of the Hymenoptera a,b,c

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a

d

e

a,b,⁎

Pu Tang , Jia-chen Zhu , Bo-yin Zheng , Shu-jun Wei , Michael Sharkey , Xue-xin Chen Alfried P. Voglerc,f

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Institute of Insect Sciences, Zhejiang University, Hangzhou 310058, China State Key Laboratory of Rice Biology and Ministry of Agriculture Key Laboratory of Molecular Biology of Crop Pathogens and Insect Pests, Zhejiang University, Hangzhou 310058, China c Department of Life Sciences, Natural History Museum, London SW7 5BD, UK d Institute of Plant and Environmental Protection, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China e Department of Entomology, University of Kentucky, Lexington, KY 40546-0091, USA f Department of Life Sciences, Silwood Park Campus, Imperial College London, Ascot SL5 7PY, UK b

A R T I C LE I N FO

A B S T R A C T

Keywords: Mitogenomics Hymenoptera Evaniomorpha basal relationships Dated tree

The insect order Hymenoptera presents marvelous morphological and ecological diversity. Higher-level hymenopteran relationships remain controversial, even after recent phylogenomic analyses, as their taxon sampling was limited. To shed light on the origin and diversification of Hymenoptera, in particular the poorly studied Parasitica, we undertook phylogenetic analyses of 40 newly and 43 previously sequenced mitochondrial genomes representing all major clades of Hymenoptera. Various Bayesian inferences using different data partitions and phylogenetic methods recovered similar phylogenetic trees with strong statistical support for almost all nodes. Novel findings of the mitogenomic phylogeny mainly affected the three infraorders Ichneumonomorpha, Proctotrupomorpha and Evaniomorpha, the latter of which was split into three clades. Basal relationships of Parasitica recovered Stephanoidea + (Gasteruptiidae + Aulacidae) as the sister group to Ichneumonomorpha + (Trigonalyoidea + Megalyroidea). This entire clade is sister to Proctotrupomorpha, and Ceraphronoidea + Evaniidae is sister to Aculeata (stinging wasps). Our divergence time analysis indicates that major hymenopteran lineages originated in the Mesozoic. The radiation of early apocritans may have been triggered by the Triassic–Jurassic mass extinction; all extant families were present by the Cretaceous.

1. Introduction Hymenoptera are one of the four hyperdiverse orders of holometabolan insects, which are traditionally subdivided into two suborders, Symphyta and Apocrita. The Symphyta has been considered a paraphyletic lineage for a long time. Members of the Symphyta are mostly phytophagous, with the exception of the Orussidae, which is the only parasitoid symphytan family and in most analyses is grouped as the sister to Apocrita (wasps, bees, and ants) (Sharkey, 2007; Song et al., 2016b). More than 90% of the Hymenoptera are Apocrita, which is monophyletic and comprises parasitic and aculeate (stinging) wasps (Huber, 2009; Sharkey, 2007). Apocritan species exhibit a wide range of lifestyles, including parasitoidism, predation, eusociality, pollen feeding and gall-making (Huber, 2009). They play vital roles in biological control, ecosystem function, and agriculture. Higher-level relationships among parasitic wasps are still controversial. Genomic data sets based on Ultra-Conserved Elements

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(UCEs) (Branstetter et al., 2017) and transcriptomes (Peters et al., 2017) did not fully resolve this problem due to uneven and unrepresentative sampling of taxa. In particular, these studies were limited in the diversity of taxa traditionally assigned to the suborders Evaniomorpha and Proctotrupomorpha (Tang and Vogler, 2017). The Parasitica, a paraphyletic concept, is one of two suborders of the Apocrita, and is highly species-rich. The other suborder, Aculeata (stinging wasps) is well studied (Branstetter et al., 2017; Peters et al., 2017). Based on morphological and fossil evidence, Rasnitsyn (1988) suggested the Parasitica can be divided into three lineages, Ichneumonomorpha, Proctotrupomorpha and Evaniomorpha, the latter two of which are considered sister groups. This system is currently used as the framework for grouping major lineages outside of the well-studied, robustly monophyletic Aculeata (Castro and Dowton, 2006; Dowton, 2001; Dowton and Austin, 1994; Dowton et al., 1997; Heraty et al., 2011; Klopfstein et al., 2013; Mao et al., 2015; Ronquist et al., 1999; Sharkey et al., 2011; Vilhelmsen et al., 2010; Wei et al., 2014).

Corresponding author at: Institute of Insect Sciences, Zhejiang University, Hangzhou 310058, China. E-mail address: [email protected] (X.-x. Chen).

https://doi.org/10.1016/j.ympev.2018.10.040 Received 14 June 2018; Received in revised form 2 September 2018; Accepted 30 October 2018 Available online 03 November 2018 1055-7903/ © 2018 Elsevier Inc. All rights reserved.

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Celera Assembler v7.0 (Myers et al., 2000), IDBA_tran (Peng et al., 2012) and Ray (Boisvert et al., 2012) for assembling each DNA library and subsequently combined contigs from the three assemblies in Geneious (Biomatters Ltd) to obtain a non-redundant set. The position of tRNA genes was conducted on the tRNAscan-SE search server (Lowe and Eddy, 1997), with a Cove cutoff score of 5, and on the Mitos WebServer (Bernt et al., 2013). When not detected by either approach, we confirmed the tRNA positions by sequence alignment with their homologs in related species. Protein-coding and rRNA genes were initially annotated with Mitos and edited in Geneious through comparison to other hymenopteran mitochondrial genomes. Mitogenomes from the sequencing mixtures were assigned to individual species using the cox1 region against sequences in the BOLD system, which could connect barcode sequences to the specimen identifications provided by taxonomists responsible for the database entries (Ratnasingham and Hebert, 2007), which unequivocally placed each mitogenome at least to family level. All other partial or complete mtDNAs downloaded from GenBank were re-annotated following the approach described above for uniform annotations.

Ichneumonomorpha has been considered as the sister of Aculeata in some morphological and early molecular studies (Dowton and Austin, 1994; Dowton et al., 1997; Rasnitsyn and Zhang, 2010; Vilhelmsen et al., 2010). Other studies recovered the Aculeata nested within the paraphyletic Evaniomorpha, whereas a sister group relationship between the Ichneumonomorpha and the Proctotrupomorpha was suggested by most subsequent molecular analyses (Dowton, 2001; Heraty et al., 2011; Klopfstein et al., 2013; Mao et al., 2015; Sharkey et al., 2011). Another scenario places Ichneumonomorpha together with the evaniomorph superfamilies Trigonalyoidea + Megalyroidea (Mao et al., 2015). Similarly, Proctotrupomorpha was not recovered as monophyletic in early studies (Dowton et al., 1997; Ronquist et al., 1999). Subsequently, more comprehensive analyses supported Proctotrupomorpha, while the internal relationships remained equivocal (Heraty et al., 2011; Klopfstein et al., 2013; Mao et al., 2015; Peters et al., 2017; Sharkey et al., 2011). The most volatile clade is Evaniomorpha, whose monophyly has not been consistently supported in either morphological or molecular analyses (Branstetter et al., 2017; Heraty et al., 2011; Klopfstein et al., 2013; Mao et al., 2014, 2015; Peters et al., 2017; Rasnitsyn and Zhang, 2010; Sharkey et al., 2011). Mitochondrial genomes of the Hymenoptera exhibit many unique characteristics, such as an exceptionally high A + T content (Wei et al., 2014), frequent gene rearrangement (Dowton et al., 2009a), high substitution rates (Oliveira et al., 2008) and a strong base composition bias (Dowton and Austin, 1997). Gene rearrangements are usually confined to specific lineages, which may be useful for phylogenetic reconstruction at lower taxonomic levels, e.g., at the subfamily level in Braconidae. However, compositional heterogeneity across lineages and convergent evolution of gene rearrangements (Dowton et al., 2009b; Wei et al., 2014) confound phylogenetic inferences in higher-level phylogenetic studies of Hymenoptera. Several studies were compromised due to sparse taxon sampling (Mao et al., 2015; Wei et al., 2014). The number of available mitochondrial genomes remains lower than for other large orders (Coleoptera and Lepidoptera) and biased towards certain groups (bees and ants). Mitochondrial genome sequencing of Apocrita has been difficult with conventional Sanger technology due to high A + T content and frequent gene rearrangements. In this study, we used a genome skimming approach for low-cost sequencing of mitogenomes from mixed total genomic DNA for dense sampling of major hymenopteran lineages to infer basal relationships, especially in the unstable clades, and to date the origin of the main hymenopteran lineages. The resulting phylogenetic hypothesis will enable insights into the origin and diversity of lifestyles in Hymenoptera.

2.2. Mitochondrial genome feature analysis Gene rearrangements were inferred using CREx which establishes the steps on a phylogenetic tree to transform one gene order into another (Bernt et al., 2007). The assessment was based on the analysis of breakpoints and changes in orientation determined in pairwise comparisons of protein coding, tRNA and rRNA genes and AT regions in the hymenopteran mitochondrial genomes, relative to the ancestral insect gene order. We calculated the proportion of GC-rich amino acid codons (GARP) and GC content in MEGA version 7.0 (Kumar et al., 2016), and the mean Ka (non-synonymous substitution rate) and Ks (synonymous substitution rate) values between each taxon and all other taxa in DNASP version 5.0 (Librado and Rozas, 2009). We obtained tip-to-root distances with Dendroscope 3 (Huson and Scornavacca, 2012). 2.3. Phylogenetic analyses The data matrices used in the phylogenetic analyses were generated in eight combinations, based on first and second codon positions only (P12), the P12 and two rRNA genes (P12RNA), all codon positions (P123), and the P123 and RNA genes (P123RNA); these four schemes were analyzed with and without the inclusion of outgroup taxa. Protein-coding genes and two rRNA genes were aligned using the GINS-i and Q-INS-i algorithms implemented in MAFFT version 7.205, respectively (Golubchik et al., 2007; Katoh and Standley, 2013). The alignment of nucleotide sequences was guided by the amino acid sequence alignment using the Perl script TranslatorX version 1.1 (Abascal et al., 2010). We concatenated the aligned sequences using the Perl script FASconCAT-G version 1.0 (Kück and Longo, 2014), then used PartitionFinder version 1.1.1 (Lanfear et al., 2012) to simultaneously choose the best partition schemes and substitution models for each matrix. The maximum possible partition schemes inputted into the PartitionFinder software was defined by codon position for nucleotide sequences of protein-coding genes and RNA genes. The search of models was set to be “Mrbayes” and “BIC”, using the greedy algorithm, with branch lengths estimated, to search for the best-fit partitioning model. The branch lengths were set as linked. Bayesian inference (BI) was conducted with MrBayes (Ronquist et al., 2012b) using the chosen partitions and model parameters (Table S2). Four simultaneous Markov chains were run for 10 million generations, with tree sampling occurring every 1000 generations and a burn-in of 25% of trees. Maximum Likelihood analyses were performed with RAxML (Stamatakis, 2014) under the GTRGAMMA model. For the analysis of each dataset, 200 runs were conducted to find the highestlikelihood tree, followed by analysis of 1000 bootstrap replicates.

2. Materials and methods 2.1. Mitochondrial genome sequencing and NGS data processing DNA extractions were performed on 40 species which were firstly identified at least to family level by taxonomic specialists (Table S1), concentrating on clades of Hymenoptera in which sampling has been scarce or whose placement was controversial (Evaniomorpha and Proctotrupomorpha). We extracted genomic DNA from individual adult specimens using a DNeasy tissue kit (Qiagen, Hilden, Germany) and determined the DNA concentration for each sample using the Qubit dsDNA high-sensitivity kit (Invitrogen). DNAs were combined in roughly equimolar concentrations and split into two pools for construction of Illumina TruSeq Nano libraries, separating close relatives (same family). The libraries were sequenced on an Illumina HiSeq sequencer (2*250 bp). Mitogenome assembly mostly followed a bioinformatics pipeline of Crampton-Platt et al. (2015), starting with the FastqExtract script to filter out mitochondrial sequences against a reference dataset including 144 hymenopteran mitochondrial genomes from 106 different species (downloaded from the Genbank database on 25 April 2016). We used 9

Note: –, not recovered; M, Monophyly; P, paraphyly; PCG, 1st, 2nd and 3rd codon positions of 13 protein-coding genes; PCG12, 1st and 2nd codon positions of 13 protein-coding genes; BI, Bayesian analysis; ML, maximum likelihood analysis; Ichn, Ichneumonomorpha; Evan-a, Stephanoidea + (Gasteruptiidae + Aulacidae); Evan-b, Trigonalyoidea + Megalyroidea; Evan-c, Ceraphronoidea + Evaniidae; Procto, Proctotrupomorpha; Acul, Aculeata; Symp, Symphyta.

M M M – – M – M – P – M M M M – – – – – P M M M M – – M – M – P M M M M M – – – – – P M M M M – – M – – – P M M M M M – – – – – P M M M M – – M – – – P M M M M M M M M M M P M M M M M M M M M M P M M M M M M M M M M P M M M M M M M M M M P M

PCG PCG12RNA PCG12RNA

PCG12

PCGRNA

10

PCGRNA

Gene arrangements were assessed for the 40 newly and 106 previously sequenced unique mitochondrial genomes relative to the putative ancestral insect gene order. We scored mitochondrial gene orders for each of 15 higher taxonomic groups of Hymenoptera (Table S3). Gene arrangements occur in all of these lineages, showing at least one translocated tRNA. Prior to this study, identical gene rearrangement only had been observed within the same family or genus. However, two distantly related species, the sawfly Xyela sp. (Xyelidae) and the ant Camponotus atrox (Formicidae), exhibited the same rearrangement due to the convergent shuffling of two tRNAs (trnQ and trnM). Gene rearrangements in the Symphyta, Stephanoidea, Aulacidae, Megalyroidea, Platygastroidea, Proctotrupoidea, Diaproidea and Evaniidae only affected the position of tRNA genes. In addition, Gasteruptiidae, Trigonaloidea, Cynipoidea, Chalcidoidea and Ceraphronoidea exhibited rearrangements of protein coding genes, while Ichneumonoidea and Aculeata included two (Cotesia vestalis and Venturia canescens) and one species (Cephalonomia gallicola), respectively, with such gene order changes. Interestingly, rearrangements of the rRNA genes only occurred in one species, Megalyra sp. (Megalyroidea). Consistency of mitochondrial rearrangements with the phylogenetic tree was tested with the CREx software. Some major types

PCG12

3.1. Mitochondrial genome organization

Clade

Table 1 Summary of the major clades recovered by different dataset and analytical approach.

Out of 42 morphologically identified species included in the two shotgun sequencing libraries, we obtained 40 full or partial mitochondrial genome assemblies. Two specimens belonging to Mymaridae and Mymarommatoidea failed to produce mitogenomes, presumably due to their small body size and insufficient yield of DNA reads. All newly sequenced mitogenomes contained the full set of 13 protein-coding genes, but the tRNA genes were missing in a few cases. Identification using barcodes and morphology were identical at least to the family level.

M M M M – – – – – P M

PCG PCG

3. Results

M M M M M M M M M P M

Without outgroup With outgroup Without outgroup

PCG12

ML BI

PCGRNA

We analyzed the concatenated DNA sequence alignment using BEAST 1.8.3 (Drummond et al., 2012). Partitioning of data and model selection was chosen as previously identified by PartitionFinder. We used the best topology from the MrBayes analyses as fixed input topology and used BEAST to estimate branch lengths under uncorrelated relaxed clocks and a Yule speciation process. We performed two independent MCMC runs for 50 million generations, sampled every 5000 generations. Burn-in sample sizes and convergence stationarity were examined using Tracer 1.6. The consensus tree was generated using Tree Annotator 1.8.3. Trees were calibrated using 19 fossils (Table 2). For each calibration point we chose a separate prior selecting 'uniform' with a given minimum and maximum age.

M M M M M – M – – P M

2.5. Divergence time estimation

M M M M M M M M M P M

PCG12 PCG PCG12RNA

With outgroup

PCGRNA

Critical nodes defining basal relationships in Hymenoptera were analyzed by four-cluster likelihood mapping in TREE-PUZZLE version 5.2 (Schmidt et al., 2002; Schmidt and von Haeseler, 2007). The method produces a graph of the tree-likeness for the three possible quartet topologies, shown as a triangle whose three corners represent the three alternative topologies. The data points represent the support for each topology based on quartets of terminals drawn from the tree at random (but representing one terminal from each of the focal taxa), and the graph can be represented as three or seven areas that record the distribution of topologies. The matrix of protein coding genes was used for this test. The GTR model was applied to the two nucleotide alignments (4 Gamma rates and invariable sites). Rate heterogeneity was set as mixed for all models.

Ichn Evan-b Ichn + Evan-b Procto Evan-c Evan-a Evan-c + Acul (Ichn + Evan-b) + Evan-a ((Ichn + Evan-b) + Evan-a) + Procto Symp Acul

PCG12RNA

2.4. Phylogenetic hypothesis tests

M M M M – – – – – P M

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Table 2 Fossils used in this study for estimation of divergence time of major clades. Species

Age (Ma)/minimum age constraint for group

Calibration group

Soft maximum bound (97.5% probability)

Reference

Pseudoxyelocerus bascharagensis Kronostephanus zigrasi Baissa magna Manlaya anglica Radiophron ibericus Cretevania concordia Cleistogaster buriatica Turgonalus cooperi Cretobraconus maculatus Amplicella beipiaoensis Khutelchalcis gobiensis Coramia minuta Dahurocynips dahurica Archaeopelecinus tebbei Proteroscelio gravatus Priorvespa longiceps Haidomyrmodes mammuthus Pompilopterus wimbledoni Melittosphex burmensis

178 97 119 142 106 131 160 127 148 131 127 142 118 160 127 123 103 142 96

Tenthredinoidea Stephanoidea Aulacidae Gasteruptiidae Ceraphronoidea Evaniidae Megalyroidea Trigonaloidea Braconidae Ichneumonidae Chalcidoidea Diaprioidea Cynipoidea Proctotrupoidea Platygastroidea Vespidae Formicidae Apoidea Anthophila

174.1–182.7 93.9–100.5 113–125 139.8–145 100.5–113 129.4–132.9 163.5–157.3 125–129.4 145–152.1 129.4–132.9 125–129.4 139.8–145 113–125 157.3–163.5 125–129.4 122.5–125 99.6–105.3 139.8–145 93.9–100.5

Nel et al. (2004) Engel and Grimaldi (2013) Rasnitsyn (1991) Rasnitsyn and Jarzembowski (1998) Ortega-Blanco et al. (2010) Rasnitsyn and Jarzembowski (1998) Rasnitsyn (1975) Rasnitsyn and Jarzembowski (1998) Rasnitsyn and Sharkey (1988) Zhang and Rasnitsyn (2003) Rasnitsyn et al. (2004) Rasnitsyn and Jarzembowski (1998) Rasnitsyn and Kovalev (1988) Shih et al. (2009) Johnson et al. (2008) Carpenter and Rasnitsyn (1990) Perrichot et al. (2007) Rasnitsyn and Jarzembowski (1998) Poinar and Danforth (2006)

specifically interested in possible nucleotide compositional biases and rate heterogeneity that might group the three Evaniomorpha clades falsely with other clades, preventing their recovery as a monophyletic group. GC content (ranging from 18% to 32%) and the corresponding preponderance of GARP amino acids differed substantially among taxa (Fig. 3). If considered in the context of the phylogenetic tree, these parameters varied greatly even between close relatives, but there were also lineage-wide patterns. Specifically, the clade composed of Evaniomorpha-c and Aculeata showed a generally increased level of GC and Ks against most of the other clades, including Evaniomorpha-a and Evaniomorpha-b that resembled more strongly the values for Ichneumonomorpha to which they were allied in the tree. Finally, we used Aligroove to test for data heterogeneity within and among the major lineages (Fig. 4). Several taxa were highlighted by this test, more so when 3rd codon positions were included and in particular when adding the rRNA genes into the analysis, but generally these outliers affected individual terminals only, indicating the lack of confounding signal at the level of major lineages based on this test.

of rearrangements involving protein coding genes were limited to particular clades, such as the inversion of the cox1–nad2–cox2 segment in Gasteruptiidae and of cox3–atp6–atp8–cox2–cox1 in Chalcidoidea, and a translocation of cox1 to a position between cox3 and nad5 (nad3–cox1–nad5) in Trigonaloidea. However, most major clades were not diagnosable by rearranged regions.

3.2. Phylogenetic analysis We conducted BI and ML analyses on the eight concatenated nucleotide sequences (PCG123, PCG123RNA, PCG12 and PCG12RNA with or without outgroup) (Table 1). All analyses robustly supported the paraphyly of Symphytaand the monophyly of Ichneumonomorpha, as expected. All BI analyses and most of the ML analyses supported Proctotrupomorpha and Aculeata as monophyletic groups, whereas Evaniomorpha were polyphyletic and separated into three major clades. One of these evaniomorph lineages, Trigonalyoidea + Megalyroidea (denoted Evaniomorpha-b), was recovered consistently as sister group to Ichneumonomorpha, corroborating the results of Mao et al. (2015). The second evaniomorph lineage grouped Gasteruptiidae with Aulacidae, as sister to Stephanoidea (= Evaniomorpha-a). This was found in almost all BI analyses except the PCG12RNA dataset without outgroups, as well as in all the ML analyses in the PCG123 matrix. The third clade of Evaniomorpha was Ceraphronoidea + Evaniidae (= Evaniomorphac), which was recovered in most BI analyses, except for the PCG12 dataset without outgroups, but none of the ML analyses supported this result (Fig. 1; Figs. S1–S15). The relationships of the three Evaniomorpha clades and their relationships with the Proctotrupomorpha and Ichneumonomorpha were assessed by four-cluster likelihood mapping (on the protein-coding genes). First, we tested relationships among at the deepest level, collapsing the Evaniomorpha-a and Evaniomorpha-b together with Ichneumonomorpha into a single clade, which weakly supported the sister relationships with the Proctotrupomorpha over the two other possible groupings with either Evaniomorpha-c or Aculeata (Fig. 2), in accordance the findings from BI analyses (Fig. 1). Secondly, we conducted four-cluster analysis within the Evaniomorpha-Ichneumonomorpha clade, which supported the Megalyroidea + Trigonaloidea (Evaniomorpha-b) as sister to Ichneumonomorpha. This arrangement was preferred over the sister relationship with Evaniidae + Ceraphronoidea (Evaniomorpha-c) or with Ichneumonomorpha (Fig. 2). The evidence against the monophyly of Evaniomorpha was further examined for possible artifacts from long-branch attraction. We were

3.3. Divergence time estimation A chronogram for Hymenoptera divergence dates and topologies based on whole mitochondrial protein coding genes is shown in Fig. 5. The base of the Hymenoptera tree was dated to 276 Million years ago (Mya) (266–286 Mya 95% CI). The clade comprising Orussidae + Apocrita diverged from the other Symphyta 239 Mya (232–247 Mya 95% CI) and Apocrita diverged from Orussoidea 232 Mya (225–239 Mya 95% CI). Apocrita diverged into two clades 224 Mya (217–230 Mya) and then all the major lineages within Apocrita diverged around 200 Mya. The ‘eusocial clade’ comprising ants, vespids and bees diverged from its sister (other aculeates) between 184 Mya (stem age; 177–192 Mya) and 170 Mya (crown age; 178–159 Mya). The most recent common ancestor of bees was estimated to have arisen 100 Mya (98–100 Mya). 4. Discussion 4.1. Phylogeny of Hymenoptera Mitochondrial genomes were at times thought to be an ineffective tool for phylogenetics due to compositional heterogeneity or high rates of change, but denser sampling could solve these problems as shown previously for beetles (Timmermans et al., 2015), termites 11

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Fig. 1. Phylogenetic tree of Hymenoptera. The tree is based on protein coding genes and Bayesian inference with an optimal partitioning scheme selected with PartitionFinder. Branch labels are the Bayesian posterior probabilities.

which is identical to the ML analysis of Heraty et al. (2011). Although Mao et al. (2015) proposed Cynipoidea as the sister group to the Diaprioidea + Chalcidoidea, most of the recent studies place Cynipoidea closer to Platygastroidea (Castro et al., 2006; Dowton, 2001; Klopfstein et al., 2013). The infraorder Evaniomorpha is polyphyletic, agreeing with most previous studies (Castro and Dowton, 2006; Gibson, 1999; Heraty et al., 2011; Klopfstein et al., 2013; Mao et al., 2014, 2015; Rasnitsyn and Zhang, 2010; Ronquist et al., 1999; Sharkey et al., 2011; Wei et al., 2014). Recently, Rasnitsyn and Zhang (2010) proposed that Evaniomorpha (sensu lato) be divided into three distinct groups, Stephanomorpha (Stephanoidea), Ceraphronomorpha (Ceraphronoidea, Megalyroidea and Trigonaloidea), and a reduced Evaniomorpha (sensu stricto, Evanioidea). Our results also show that Evaniomorpha (sensu lato) is split into three parts, supported by the four-clusters likelihood mapping test, i.e., (1) Trigonalyoidea + Megalyroidea (= Evaniomorpha-b), as the sister group to Ichneumonomorpha, as already proposed in Mao et al. (2015); (2) Ceraphronoidea + Evaniidae (= Evaniomorpha-c), which combined are the sister group of Aculeata. This grouping differs from Mao et al. (2014, 2015) who proposed Ceraphronoidea + Evanioidea; (3) Stephanoidea + (Gasteruptiidae + Aulacidae) (= Evaniomorpha-a), which is well supported, unlike in some previous studies that recognized Stephanoidea as an early branch of the apocritan lineage (Heraty et al., 2011; Mao et al., 2014, 2015; Peters et al., 2011; Sharkey et al., 2011; Vilhelmsen et al.,

(Bourguignon et al., 2015) and true bugs (Li et al., 2017). Our study now shows that mitochondrial genomes are a useful tool for constructing robust trees of Hymenoptera, despite their extremely high rate of change compared to virtually all other insect groups (Song et al., 2016a). The new data add to recent genomic studies of this order by increasing the sampling density in key parts of the tree to address questions in particular about the monophyly and relative positions of the three apocritan infraorders Ichneumonomorpha, Proctotrupomorpha and Evaniomorpha. We concentrated our sequencing on the poorly sampled Parasitica, and added only a few sequences to the existing entries for Symphyta and Aculeata. The phylogenetic tree recovers the expected paraphyly of the Symphyta, while Orussoidea forms a sister lineage with the suborder Apocrita, as shown in most previous studies (Dowton et al., 2009a; Mao et al., 2015; Sharkey et al., 2011; Song et al., 2016b; Wei et al., 2014). The suborder Apocrita is a well-established monophyletic group, but its internal relationships have been controversial (Ashmead, 1896; Dowton and Austin, 1994; Dowton et al., 2009a; Heraty et al., 2011; Klopfstein et al., 2013; Mao et al., 2015; Ronquist et al., 1999; Sharkey et al., 2011; Wei et al., 2014). Three infraorders Ichneumonomorpha, Proctotrupomorpha and Vespomorpha (Aculeata) are wellsupported by our results, as recovered in most previous studies. Within the Proctotrupomorpha, our results strongly support Platygastroidea + (Cynipoidea + (Proctotrupoidea + (Diaprioidea + Chalcidoidea))),

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Fig 2. Results from four-clusters likelihood mapping showing the support for the hypotheses of two conflict nodes (A and B). This analysis is based on matrix that 13 PCG sequences. A. Possible relationships of Evaniomorpha-a, Ichneumonomorpha, Evaniomorpha-b, Proctotrupomorpha, Evaniomorpha-c and Aculeata are displayed on the edges of the triangle. B. Possible relationships of Evaniomorpha-a, Ichneumonomorpha, Evaniomorpha-b and Proctotrupomorpha displayed on the edges of the triangle. The deeper colors on the region represent the higher support values of the relationship on this triangle.

for a wide sampling of insects. Our initial attempts using representatives of multiple orders (Coleoptera, Diptera, Lepidoptera and Neuroptera) produced confusing topologies, presumably due to difficulties with alignment and the highly divergent nature of these taxa. In line with a previous study (Peters et al., 2017), we chose only the

2010; Wei et al., 2014). Tree topologies were generally well supported by all Bayesian and ML analyses (Table 1), whether analyzed with or without the inclusion of outgroup taxa. Outgroup selection is problematic because the rooting of Hymenoptera, as sister to all other holometabolan orders, would call

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Fig. 3. Heterogeneity in nucleotide composition and substitution rates of selected Hymenoptera. For each taxon the bar charts display: droot, the root-to-tip distance obtained from the tree topology in Fig. 1; garp, the proportion of GC-rich amino acid codons; gccont, the GC content (%); ka, the mean Ka (non-synonymous substitution rate) value; ks, the mean Ks (synonymous substitution rate) in pairwise comparisons in all selected taxa. All values except root-to-tip distances were obtained from the protein coding genes.

correlated with biases in nucleotide variation. Instead, there seems a general tendency that the inclusion of 3rd codon positions and rRNA genes in the analysis increases the chance of recovering these nodes, indicating that greater amounts of data are responsible, which may provide an argument for retaining all nucleotide positions. Tests of data heterogeneity with the Aligroove method only indicate anomalous patterns affecting the tip level (individual terminals), i.e. it does not provide evidence of biases affecting the position of major clades. However, we note the general trend towards higher GC content and lower Ks in the Aculeata, compared to the other apocritan branches, while the same is true also for the Evaniomorpha-c, i.e. the sister taxon of Aculeata in our analysis. While these similarities in nucleotide composition and evolutionary rates cement these sister relationships, there is no reason to think that this is not due to common ancestry. Branstetter et al. (2017) and Peters et al. (2017) also found some lineage of Evaniomorpha (Trigonaloidea) as sister to Aculeata, supporting the current findings. However, taxon sampling was limited in both studies and was missing the Megalyroidea whose presence had great impact on this relationship even with more completely sampled data sets. Alternatively, the non-monophyly of the Evaniomorpha might result from convergent biases for lower GC content and faster rates in the other two clades (Evaniomorpha-a and Evaniomorpha-c) producing convergent biases with their respective sister group (mainly Ichneumonomorpha), but this seems equally unlikely given the findings of Branstetter et al. (2017) and Peters et al. (2017) who find some

members of Neuropteridia, which had a less drastic effect on the ingroup relationships. The inclusion or exclusion of these outgroups affect predominantly various nodes within the Apocrita but not the most basal nodes. The analysis corroborated that the Symphyta at the base of Hymenoptera is a paraphyletic grade, with Orussidae as the sister group to Apocrita. When outgroups were excluded, these basal arrangements remained unchanged but the positioning of the various subclades of Evaniomorpha and their relationships to other infraorders differed (Table 1), as the trees without outgroups often did not recover the expected relationships. Thus we confirmed previous analyses that performed better when recovering hymenopteran phylogenetic relationships using mitochondrial genomes with outgroups (Castro and Dowton, 2007). Our study used a variety of tests to examine potential biases in the data that might be responsible for spurious associations of taxa. The mean GC content and the corresponding preponderance of GARP amino acids differed substantially among taxa. Thus, problems of nucleotide heterogeneity (which we did not examine explicitly) might be directly linked to phenomena of long-branch attraction, but they should be less prevalent using amino acid sequences or nucleotide data after removal of 3rd codon positions, although other biases could affect the non-synonymous character changes. The different analyses with inclusion and exclusion of 3rd positions had no consistent effects; while Evaniomorpha-b was detected in all cases, Evaniomorpha-a and Evaniomorpha-c were not universally recovered, but this was not 14

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Fig. 4. AliGROOVE analysis for various datasets. The mean similarity score between pairs of sequences is represented by a colored square, based on AliGROOVE scores from −1, indicating great difference in sequence composition from the remainder of the data set (red coloring), to +1, indicating high similarity to all other comparisons (blue coloring). PCG, protein coding genes; PCG12, 1st and 2nd codon positions; PCGRNA with rRNA genes included.

Peters et al., 2017), although slightly older (by ∼20 Ma) than the two other calibrations (Branstetter et al., 2017; Misof et al., 2014). Apocrita diverged from Orussoidea at 232 (225–239) Mya, which implies the maximum age for the origin of parasitoidism as well. Contrary to findings of previous studies, major clades of Parasitica diverged earlier than clades of Aculeata (O'Reilly and Donoghue, 2016; Ronquist et al., 2012a). All major clades within Apocrita, including the Aculeata constituting one of these lineages, diverged almost at the same time around 200 Mya, and the Aculeata started to diverge shortly thereafter. This period coincides with the Triassic-Jurassic extinction event, which places the radiation and early divergence of Apocrita in its palaeoenvironmental context. The origin of this lineage marks the beginning of the spectacular evolutionary radiation in post-Triassic and

Evaniomorpha grouped near Ichneumonomorpha (albeit again in studies with much lower sampling). Even our greatly expanded taxon sampling of these groups remains a limited set chosen from the huge diversity of parasitic wasps. The relative ease of mitogenome sequencing should lead to the rapid addition of further taxa and thus improve the support for basal relationships and the delimitation of major clades within the “Evaniomorpha”.

4.2. Dating of major clades and diversification among Hymenoptera The phylogenetic chronogram dates the most recent hymenopteran common ancestor to the Permian, to 276 (266–286) Mya, which is consistent with several previous studies (O'Reilly and Donoghue, 2016; 15

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Fig. 5. Chronogram showing hymenopteran phylogeny and divergence time estimates. The tree presents divergence dates produced by the Beast analysis of the PCG dataset using 19 fossil calibration points. Blue bars indicate 95% mean confidence intervals of each node. A geological timescale is shown at the bottom.

Funds for the Central Universities, China [2018QNA6025]; the National Key R&D Program of China, China [2017YFD0201000]; National Natural Science Foundation of China, China [31101661] and the Biodiversity Initiative of the Natural History Museum, London, UK.

early-Jurassic ecosystems, when Apocrita acquired an astonishing range of life styles. Most modern families of Aculeata were proposed to have originated during the Late Cretaceous when angiosperms radiated and diversified (Wilson et al., 2013), which is confirmed here. This supports the idea that flourishing angiosperm diversity and herbivorous insects feeding on them increased the diet diversity and habitat complexity, as potential key factors driving diversification in predatory wasps (Johnson et al., 2013; Wilson et al., 2013). Our study suggests that this might also apply to the contemporaneously diversifying Parasitica, together with their rapidly diversifying hosts. The evolutionary shifts in life histories strategies of Hymenoptera are only slowly being resolved, given their huge diversity, but the combination of genome and mitogenome data, the latter permitting dense sampling, will provide an increasingly accurate and comprehensive tree to more fully resolve the evolutionary history of Hymenoptera.

Appendix A. Supplementary material Supplementary data to this article can be found online at https:// doi.org/10.1016/j.ympev.2018.10.040. References Abascal, F., Zardoya, R., Telford, M.J., 2010. TranslatorX: multiple alignment of nucleotide sequences guided by amino acid translations. Nucleic. Acids Res. 38, W7–W13. Ashmead, W.H., 1896. The phylogeny of the Hymenoptera. Proc. Entomol. Soc. Wash. 323–336. Bernt, M., Donath, A., Juhling, F., Externbrink, F., Florentz, C., Fritzsch, G., Putz, J., Middendorf, M., Stadler, P.F., 2013. MITOS: improved de novo metazoan mitochondrial genome annotation. Mol. Phylogenet. Evol. 69, 313–319. Bernt, M., Merkle, D., Ramsch, K., Fritzsch, G., Perseke, M., Bernhard, D., Schlegel, M., Stadler, P.F., Middendorf, M., 2007. CREx: inferring genomic rearrangements based on common intervals. Bioinformatics 23, 2957–2958. Boisvert, S., Raymond, F., Godzaridis, E., Laviolette, F., Corbeil, J., 2012. Ray Meta: scalable de novo metagenome assembly and profiling. Genome Biol. 13, R122. Bourguignon, T., Lo, N., Cameron, S.L., Sobotnik, J., Hayashi, Y., Shigenobu, S., Watanabe, D., Roisin, Y., Miura, T., Evans, T.A., 2015. The evolutionary history of termites as inferred from 66 mitochondrial genomes. Mol. Biol. Evol. 32, 406–421. Branstetter, M.G., Danforth, B.N., Pitts, J.P., Faircloth, B.C., Ward, P.S., Buffington, M.L., Gates, M.W., Kula, R.R., Brady, S.G., 2017. Phylogenomic insights into the evolution of stinging wasps and the origins of ants and bees. Curr. Biol. 27, 1019–1025.

Acknowledgments We would like to thank van C. Achterberg (Naturalis Biodiversity Center, Netherlands), J.S. Noyes (Natural History Museum, UK), Junhua He (Zhejiang University, Hangzhou, China), Meicai Wei (Central South University of Forestry and Technology, Changsha, China) and Jingxian Liu (South China Agricultural University, Guangzhou, China) for donating and identifying specimens. This work was supported by the State Key Program of National Natural Science Foundation of China, China [31230068]; National Natural Science Foundation of China, China [31401996]; the Fundamental Research 16

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