Evolutionary History of Coleoptera Revealed by Extensive Sampling of Genes and Species

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DOI: 10.1038/s41467-017-02644-4 OPEN Evolutionary history of Coleoptera revealed by extensive sampling of genes and species

Shao-Qian Zhang1, Li-Heng Che1, Yun Li1, Dan Liang1, Hong Pang1, Adam Ślipiński2 & Peng Zhang1

Beetles (Coleoptera) are the most diverse and species-rich group of insects, and a robust, time-calibrated phylogeny is fundamental to understanding macroevolutionary processes that underlie their diversity. Here we infer the phylogeny and divergence times of all major

1234567890():,; lineages of Coleoptera by analyzing 95 protein-coding genes in 373 beetle species, including ~67% of the currently recognized families. The subordinal relationships are strongly supported as Polyphaga (Adephaga (Archostemata, Myxophaga)). The series and superfamilies of Polyphaga are mostly monophyletic. The species-poor Nosodendridae is robustly recovered in a novel position sister to Staphyliniformia, Bostrichiformia, and Cucujiformia. Our divergence time analyses suggest that the crown group of extant beetles occurred ~297 million years ago (Mya) and that ~64% of families originated in the Cretaceous. Most of the herbivorous families experienced a signiﬁcant increase in diversiﬁcation rate during the Cretaceous, thus suggesting that the rise of angiosperms in the Cretaceous may have been an ‘evolutionary impetus’ driving the hyperdiversity of herbivorous beetles.

1 State Key Laboratory of Biocontrol, College of Ecology and Evolution, School of Life Sciences, Sun Yat-Sen University, Guangzhou, 510006, China. 2 Australian National Insect Collection, CSIRO, GPO Box 1700, Canberra, ACT 2601, Australia. Correspondence and requests for materials should be addressed to A.Ś. (email: [email protected]) or to P.Z. (email: [email protected])

NATURE COMMUNICATIONS | (2018) 9:205 | DOI: 10.1038/s41467-017-02644-4 | www.nature.com/naturecommunications 1 ARTICLE NATURE COMMUNICATIONS | DOI: 10.1038/s41467-017-02644-4

oleoptera, also known as beetles, are the most diverse and from ~253 to 333 Mya (million years ago) and that the diver- species-rich insect group on Earth. With more than gences of most modern lineages occurred during the Late Triassic C 1 fi 380,000 described extant species , beetles constitute ~25% to Cretaceous; however, the con dence intervals of these age of all described animal species on this planet, and many species estimates are large12,13,16,27. remain to be described2. Beetles exhibit extraordinary morpho- It is well known that both taxon sampling and gene sampling logical and ecological diversity and play important roles in nearly can affect the accuracy of phylogenetic reconstruction. In pre- all terrestrial and freshwater ecosystems3. To understand the vious beetle phylogenetic studies, when the amount of sequence processes that have resulted in the extraordinary diversity of was large (e.g., using ribosomal protein genes extracted from EST beetles, a comprehensive time-calibrated phylogeny of extant data28, whole-mitochondrial genomes15,17, or transcriptome beetles is required. However, resolving the phylogeny of beetles data23,29), the taxon sampling was small, or when the taxon has proven to be a difficult challenge because of their exceptional sampling was large, the amount of sequence was small (e.g., three species richness, complicated morphological characteristics and genes: ~3000 nt12, four genes: 6600 nt14, and eight genes: 8377 sparse molecular data. Therefore, deciphering the evolutionary nt16). Until recently, beetle molecular phylogenetics has mainly history of beetles is one of the most important and complicated relied on nuclear ribosomal DNA and mitochondrial gene problems in insect biology. sequences. These data are either too conservative (lacking infor- Since the first natural classification of beetles proposed by mation) or too heterogeneous in composition and evolutionary Crowson4, many efforts have been made to refine the framework rate (prone to systematic bias), and hence are insufficient for – based on morphological characters1,5 11. In recent years, many resolving the higher level phylogeny of beetles. Compared with researchers have attempted to resolve the beetle phylogeny on the nuclear ribosomal DNA and mitochondrial genes, nuclear – basis of molecular data12 17. These studies have made great protein-coding (NPC) genes are more informative and less biased progress; however, the resolution of the resulting phylogenies is in base composition, and they have been used to resolve many often poor, and many branches of the beetle tree-of-life remain problematic relationships in beetles16,30. However, because of the unresolved. For example, nine hypotheses regarding the rela- deep evolutionary divergences in beetles and widely varying tionships among four suborders of beetles (Fig. 1) have been evolutionary rates among taxa, NPC genes that can be amplified proposed in recent decades, but most of them did not receive across all beetles are still scarce (fewer than 10), thus resulting in – strong support11,16,18 23. In addition, the relationships among the their relatively infrequent use in higher level beetle series and superfamilies of Polyphaga have lacked consistently phylogenetics16. strong nodal support, including the phylogenetic position of the In this study, we dramatically increase the gene sampling by elusive Nosodendridae. These uncertainties have prevented the including 95 recently developed31 nuclear protein-coding genes, development of a comprehensive time-calibrated phylogeny of representing the largest source of data for beetle phylogenetics to beetles, which is necessary to understand the macroevolutionary date. In addition, our broad taxon sampling includes 373 beetles processes that promoted the beetle’s extraordinary diversity. representing all recognized suborders, series, superfamilies and Although early beetle fossils are rare, beetles are commonly 124 of 186 families. Our results establish the phylogenetic rela- thought to have first appeared in the Early Permian5,24. A recent tionships among major lineages and greatly improve robustness study has reported a fossil beetle from the Pennsylvanian (Car- throughout the entire phylogeny, especially in deep nodes. This boniferous)25, thus suggesting an earlier origin of beetles, study provides a basis for a more accurate natural classification of although other researchers have suggested that the assessment of Coleoptera. Furthermore, we also estimate the divergence times this fossil should be re-evaluated26. On the other hand, molecular for the entire beetle phylogeny and study the tempo and pattern studies have suggested that the age for crown Coleoptera ranged of diversification of beetles. We find that Coleoptera originated in

T1T2 T3 Polyphaga Polyphaga Polyphaga

Myxophaga Myxophaga Adephaga

Adephaga Adephaga Myxophaga

Archostemata Archostemata Archostemata

Outgroups Outgroups Outgroups

T4 T5 T6 Polyphaga Myxophaga Myxophaga Adephaga Adephaga Adephaga

Myxophaga Polyphaga Polyphaga Archostemata Archostemata Archostemata

Outgroups Outgroups Outgroups T7 T8 T9 Myxophaga Archostemata Myxophaga

Adephaga Adephaga Archostemata

Archostemata Myxophaga Adephaga

Polyphaga Polyphaga Polyphaga

Outgroups Outgroups Outgroups

Fig. 1 Nine proposed topologies among four suborders of Coleoptera. Topologies are derived from: T1, refs. 5,19; T2, ref. 11; T3, refs. 14,20; T4, ref. 12; T5, ref. 21; T6, ref. 22; T7, ref. 18; T8, refs. 17,23; T9 refs. 16,32

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Bothrideridae Deretaphrus CSR072 Bothrideridae Ascetoderes CSR074 Cerylonidae Philothermus CSR011 Murmidiidae Murmidius CSR078 Formicidae Atta Discolomatidae Aphanocephalus CSR018 Apidae Apis Hymenoptera Cerylonidae Ostomopsis CSR079 Drosophilidae Drosophila Euxestidae Hypodacnella CSR010 Culicidae Anopheles Diptera Teredidae Teredolaemus CSR073 Bombycidae Bombyx Outgroups Teredidae Xylariophilus CSR071 Nymphalidae Danaus Lepidoptera Teredidae Xylariophilus CSR007 Corydalidae Neochauliodes IN61 Megaloptera Alexiidae Sphaerosoma CSR002 Chrysopidae Dichochrysa IN54 Latridiidae Enicmus CSR028 Ascalaphidae Ascalohybris IN56 Neuroptera Latridiidae Corticaria CSR029 Myrmeleontidae Myrmeleon IN53 Latridiidae Melanophthalma CSR111 Cupedidae Tenomerga INB118 Archostemata Anamorphidae Papuella CSR095 Torridincolidae Satonius INB116 Myxophaga Corylophidae Periptyctus CSR086 Haliplidae Peltodytes INB121 Corylophidae Priamima CSR085 Coccinelloidea Gyrinidae Orectochilus INB037 Corylophidae Sericoderus CSR014 Noteridae Canthydrus INB115 Corylophidae Orthoperus INB209 Noteridae sp. CSR039 Endomychidae Holoparamecus CSR096 Dytiscidae Laccophilus INB111 ‘Hydradephaga’ Endomychidae Stenotarsus CSR098 Adephaga Dytiscidae Hyphydrus INB114 Endomychidae Cyclotoma CSR020 Dytiscidae Eretes INB112 Endomychidae Encymon CSR097 Dytiscidae Agabus INB109 Endomychidae Sinocymbachus INB005 Dytiscidae Rhantus INB113 Coccinellidae Microfreudea C33 Carabidae Cicindela INB101 Coccinellidae Stethorus C54 Carabidae Paussinae sp. TH2 Coccinellidae Exochomus C25 Carabidae Omoglymmius INB120 Coccinellidae Harmonia C10 Carabidae Elaphrus INB212 Coccinellidae Rhizobius C28 Carabidae Carabus INB100 Geadephaga Coccinellidae Ortalia C31 Carabidae Clivina INB167 Coccinellidae Sasajiscymnus C44 Carabidae Pheropsophus INB168 Coccinellidae Chnootriba C04 Carabidae Dischissus INB013 Nemonychidae Aragomacer CSR120 Carabidae Lebia INB170 Anthribidae Acorynus INB007 Carabidae Pentagonica INB171 Anthribidae Ozotomerus INB043 Scirtidae Pseudomicrocara CSR143 Anthribidae Peribathys INB102 Coleoptera Scirtidae Elodes INB133 ‘Scirtoidea’ Anthribidae Xylinada INB054 Scirtidae Scirtinae sp. INB041 Belidae Rhinotia CSR067 Derodontidae Derodontus CSR091 ‘Derodontoidea’ Attelabidae Involvulus INB074 Clambidae Clambus CSR082 Attelabidae Byctiscus INB076 Eucinetidae Noteucinetus CSR021 ‘Scirtoidea’ Attelabidae Phymatapoderus INB051 Curculionoidea Eucinetidae Noteucinetus CSR103 Attelabidae Paratrachelophorus INB188 Rhipiceridae Oligorhipis CSR049 Brentidae Baryrhynchus INB044 Dascillidae Dascillus INB028 Dascilloidea Brentidae Cylas INB199 Dascillidae Metallidascillus INB200 Brentidae Apion CSR075 Buprestidae Dicerca INB083 Brentidae Apion INB075 Buprestidae Coroebus INB018 Buprestoidea Curculionidae Platypodinae sp. INB045 Buprestidae Trachys INB084 Curculionidae Episomus INB010 Byrrhidae Microchaetes CSR076 Curculionidae Peribleptus INB185 Byrrhidae Cytilus INB053 Curculionidae Curculio INB184 Byrrhidae Notolioon CSR008 Curculionidae Xylosandrus INB048 Dryopidae Pachyparnus INB166 Curculionidae Dendroctonus Megalopodidae Temnaspis INB031 Dryopidae Helichus CSR019 Cucujiformia Dryopidae Helichus INB194 Cerambycidae Oberea INB067 Polyphaga Eulichadidae Eulichas INB025 Cerambycidae Dorysthenes INB150 Ptilodactylidae Ptilodactyla INB015 Cerambycidae Xylotrechus INB069 Ptilodactylidae Epilichas INB079 Cerambycidae Spondylis INB068 Callirhipidae Ennometes CSR009 Cerambycidae Strangalia INB066 Callirhipidae Simianus INB119 Chrysomelidae Bruchidius INB144 Chelonariidae Chelonarium CSR012 Chrysomelidae Sagra INB134 Psephenidae Sclerocyphon CSR043 Chrysomelidae Sominella INB138 Psephenidae Mataeopsephus INB081 Byrrhoidea Chrysomelidae Lilioceris INB135 Chrysomeloidea Psephenidae Schinostethus INB080 Chrysomelidae Chrysomela INB019 Psephenidae Schinostethus INB052 Chrysomelidae Galerucinae sp. INB140 Elmidae Stetholus CSR094 Chrysomelidae Altica INB141 Elmidae Graphelmis CSR093 Chrysomelidae Dactylispa INB136 Elmidae Stenelmis INB038 Chrysomelidae Anisodera INB137 Limnichidae Cephalobyrrhus INB082 Chrysomelidae Cassida INB006 Heteroceridae Heterocerus INB092 Chrysomelidae Trichochrysea INB139 Limnichidae Limnichus TH1 Chrysomelidae Oomorphoides INB142 Limnichidae Byrrhinus CSR112 Chrysomelidae Cryptocephalus INB143 Limnichidae Pelochares INB042 Chrysomelidae Chlamisus INB077 Artematopodidae Eurypogon INB202 Boganiidae Paracucujus CSR006 Artematopodidae Artematopus CSR004 Erotylidae Anadastus CSR100 Omethidae Drilonius INB129 Erotylidae Tetraphala INB029 Omethidae Drilonius INB127 Erotylidae Cryptophilus CSR102 Throscidae Trixagus CSR056 Erotylidae Thallis CSR099 Throscidae Trixagus INB125 Erotylidae Episcaphula CSR101 Eucnemidae Anischia CSR022 Erotylidae Episcapha INB023 Eucnemidae Hemiopsida CSR104 Helotidae Neohelota INB004 Eucnemidae Otho INB035 Protocucujidae Ericmodes CSR129 Cantharidae Malthinus INB154 Sphindidae Aspidiphorus CSR053 Cantharidae Heteromastix CSR077 Monotomidae Rhizophagus CSR119 Cantharidae Ichthyurus INB065 Monotomidae Thione INB207 Cantharidae Laemoglyptus INB153 Monotomidae Mimemodes CSR034 Cantharidae Lycocerus INB155 Monotomidae Monotomopsis CSR118 Cantharidae Prothemus INB064 Kateretidae Notobrachypterus CSR027 Cantharidae Fissocantharis INB156 Cybocephalidae Cybocephalus CSR088 Cantharidae Themus INB001 Nitidulidae Glischrochilus INB197 Cantharidae Themus INB063 Nitidulidae Brachypeplus CSR121 Elateridae Osslimus CSR092 Nitidulidae Pallodes CSR122 Lycidae Benibotarus YL0447 Nitidulidae Urophorus INB056 Cucujoidea Lycidae Platerodrilus YL0458 Nitidulidae Carpophilus INB196 Lycidae Lycostomus YL0616 Hobartiidae Hydnobioides CSR106 Lycidae Macrolycus YL0509 Cryptophagidae Micrambina CSR015 Lycidae Dilophotes YL0454 Cryptophagidae Curelius INB192 Lycidae Libnetis YL0478 Elateroidea Silvanidae Psammoecus INB095 Lycidae Porrostoma CSR113 Silvanidae Silvanoprus CSR145 Elateridae Agrypnus INB160 Silvanidae Uleiota CSR052 Elateridae Cardiotarsus INB210 Silvanidae Psammoecus INB124 Elateridae Denticollis INB165 Silvanidae Cryptamorpha CSR144 Elateridae Denticollis INB162 Cucujidae Pediacus CSR087 Elateridae Pectocera INB159 Cucujidae Platisus CSR016 Elateridae sp. INB164 Phloeostichidae Hymaea CSR127 Elateridae Penia INB163 Phloeostichidae Ropalobrachium CSR128 Elateridae Cebrio TH4 Myraboliidae Myrabolia CSR037 Elateridae Ampedus INB161 Passandridae Passandra CSR125 Elateridae Melanotus INB211 Propalticidae Propalticus CSR042 Elateridae Hemicrepidius INB016 Laemophloeidae Laemophloeus CSR110 Phengodidae Stenophrixothrix CSR041 Laemophloeidae Cryptolestes INB193 Rhagophthalmidae sp. INB128 Phalacridae Phalacrinus CSR126 Rhagophthalmidae Rhagophthalmus CSR048 Phalacridae sp. CSR040 Rhagophthalmidae Rhagophthalmus CSR132 Phalacridae Olibrus INB122 Lampyridae Gorhamia TH3 Trogossitidae Rentonellum CSR059 Lampyridae Drilaster INB157 Byturidae Haematoides INB039 Lampyridae Luciola INB061 Biphyllidae Biphyllus CSR068 Lampyridae Pristolycus INB060 Biphyllidae Althaesia CSR005 Lampyridae Cyphonocerus INB062 Trogossitidae Leperina CSR160 Lampyridae Vesta INB059 Acanthocnemidae Acanthocnemus CSR062 Lampyridae Pyrocoelia INB017 Trogossitidae Larinotus CSR058 Lampyridae Diaphanes INB158 Trogossitidae Thymalus INB024 Nosodendridae Nosodendron CSR038 ‘Derodontoidea’ Thanerocleridae Isoclerus CSR055 Histeridae Platysoma CSR023 Cleridae Tenerus CSR083 Histeridae Saprinus CSR024 Cleridae Necrobia CSR084 Hydrophilidae Georissus INB106 Cleridae Allochotes INB191 Cleroidea Hydrophilidae Anacaena INB105 Cleridae Cladiscus INB189 Hydrophilidae Sphaeridium INB107 Cleridae Xenorthrius INB012 Hydrophilidae Helochares CSR108 Hydrophiloidea Cleridae Stenocallimerus INB190 Hydrophilidae Berosus INB152 Trogossitidae Parapeltis CSR159 Hydrophilidae Oocyclus INB014 Trogossitidae Ancyrona CSR158 Hydrophilidae Sternolophus CSR107 Prionoceridae Idgia INB040 Hydrophilidae Hydrophilus INB103 Melyridae Dasytes CSR115 Ptiliidae sp. CSR044 Melyridae Carphurus CSR117 Hydraenidae Hydraena INB108 ‘Staphylinoidea’ Melyridae Carphurus INB131 Jacobsoniidae Derolathrus CSR026 Melyridae Dicranolaius CSR116 Jacobsoniidae Derolathrus CSR109 ‘Derodontoidea’ Melyridae Malachiinae sp. INB003 Agyrtidae Pteroloma INB201 Lymexylidae Atractocerus INB094 Leiodidae Agathidium CSR032 Lymexylidae Melittomma CSR033 Lymexyloidea Leiodidae Agyrtodes CSR030 Rhipiphoridae Trigonodera CSR050 Leiodidae Cholevinae sp. CSR031 Rhipiphoridae Rhipidioides CSR133 Staphylinidae Centrophthalmus INB091 Mordellidae Hoshihananomia INB034 Staphylinidae Omaliinae sp. INB176 Mycteridae Trichosalpingus CSR036 Staphylinidae Scydmaeninae sp. CSR146 Oedemeridae Ditylus INB033 Staphylinidae Dianous INB175 Oedemeridae Pseudolycus CSR124 Staphylinidae Megalopaederus INB030 Oedemeridae Thelyphassa CSR123 Staphylinidae Staphylinus INB008 Ischaliidae Ischalia INB049 Staphylinidae Staphylininae sp. INB174 ‘Staphylinoidea’ Aderidae sp. INB206 Staphylinidae Tachinus INB088 Aderidae sp. CSR001 Staphylinidae Tachinus INB090 Boridae Synercticus CSR069 Silphidae Nicrophorus INB022 Trictenotomidae Trictenotoma INB208 Silphidae Necrodes INB078 Scraptiidae Scraptia INB205 Staphylinidae Apatetica INB085 Pythidae Anaplopus CSR131 Staphylinidae Scaphidium INB089 Salpingidae Ocholissa CSR136 Staphylinidae Scaphidium CSR054 Salpingidae Euryplatus CSR134 Staphylinidae Priochirus INB086 Salpingidae Orphanotrophium CSR051 Staphylinidae Osorius INB087 Salpingidae Orphanotrophium CSR135 Trogidae Omorgus CSR057 Pyrochroidae Morpholycus CSR047 Trogidae Trox INB036 Pyrochroidae Morpholycus CSR130 Lucanidae Phalacrognathus INB098 Pyrochroidae Eupyrochroa INB027 Lucanidae Cyclommatus INB099 Pyrochroidae Pseudopyrochroa INB020 Lucanidae Aegus INB148 Anthicidae Macratria CSR065 Passalidae Ceracupes INB057 Anthicidae Macratria INB050 Passalidae Aceraius INB096 Anthicidae Trichananca CSR064 Geotrupidae Australobolbus CSR137 Anthicidae Lemodes CSR003 Geotrupidae Geotrupes INB097 Anthicidae Anthicus CSR063 Glaphyridae Amphicoma INB011 Meloidae Zonitis CSR114 Hybosoridae Liparochrus CSR025 Meloidae Epicauta INB093 Tenebrinoidea Hybosoridae Cyphopisthes CSR138 Incertae sedis Rhizonium CSR105 Scarabaeidae Rhyparus INB002 Scarabaeoidea Melandryidae Dircaeomorpha INB055 Scarabaeidae Onthophagus CSR142 Zopheridae Monomma CSR060 Scarabaeidae Copris INB146 Zopheridae Bitoma CSR061 Scarabaeidae Cheirotonus INB151 Mycetophagidae Nototriphyllus CSR035 Scarabaeidae Heteronyx CSR140 Mycetophagidae Mycetophagus INB047 Scarabaeidae Ectinohoplia INB147 Archeocrypticidae Wattianus CSR066 Scarabaeidae Dasyvalgus INB149 Ulodidae Ulodes CSR161 Scarabaeidae Protaetia INB104 Ulodidae Meryx CSR162 Scarabaeidae Allomyrina INB169 Melandryidae Melandryinae sp. INB203 Scarabaeidae Carneodon CSR139 Zopheridae Zopherosis CSR163 Scarabaeidae Mimela INB145 Ciidae Cis CSR013 Scarabaeidae Anomala CSR141 Ciidae Cis CSR080 Dermestidae Evorinea CSR090 Ciidae Australocis CSR081 Dermestidae Orphinus INB130 Tenebrionidae Adelium CSR149 Dermestidae Dermestes CSR089 Tenebrionidae Ecnolagria CSR157 Bostrichidae Lyctus CSR070 Tenebrionidae Chlorophila INB046 Bostrichidae Polycaon INB032 Bostrichoidea Tenebrionidae Cryphaeus INB181 Ptinidae Hedobia INB204 Tenebrionidae Tribolium Ptinidae Dorcatoma CSR046 Tenebrionidae Cyphaleus CSR148 Ptinidae Ptinus CSR045 Tenebrionidae Cillibus CSR150 Ptinidae Ptinus INB132 Tenebrionidae Cossyphus CSR153 Tenebrionidae Platydema CSR155 ≥ Tenebrionidae Amarygmus CSR147 PP = 1.0 and BS 90 Tenebrionidae Tanychilus CSR154 PP = 1.0 and 90 > BS ≥ 70 Tenebrionidae Cteniopinus INB073 Cucujiformia Tenebrionidae Palorus CSR151 PP = 1.0 and BS < 70 Tenebrionidae Strongylium INB180 1.0 > PP ≥ .095 and BS < 70 Tenebrionidae Tyrtaeus CSR156 Tenebrionidae Derispia CSR152 Tenebrionidae Derispia INB072

Fig. 2 Cladogram of Coleoptera. The topology was inferred from the concatenated amino acid data set by ML (RAxML) and Bayesian inference (Exabayes). Nodes with bootstrap values (BS) <70 and posterior probabilities (PP) <0.95 are not indicated by colored circles. Traditional taxonomic units that are not monophyletic are indicated with quotation marks

NATURE COMMUNICATIONS | (2018) 9:205 | DOI: 10.1038/s41467-017-02644-4 | www.nature.com/naturecommunications 3 ARTICLE NATURE COMMUNICATIONS | DOI: 10.1038/s41467-017-02644-4

Table 1 Topology test for the nine proposed hypotheses among the four suborders of beetles

No. Topology Amino acid data Nucleotide data Δln L AU test p-values Δln L AU test p-values T9 (Polyphaga, (Adephaga, (Archostemata, Myxophaga))) 0 0.920 0 0.946 T8 (Polyphaga, (Myxophaga, (Adephaga, Archostemata))) 23.65 0.123 16.64 0.151 T7 (Polyphaga, (Archostemata, (Adephaga, Myxophaga))) 19.95 0.227 21.04 0.088 T1 (Archostemata, (Adephaga, (Myxophaga, Polyphaga))) 117.83 2e − 05* 90.38 0.002* T3 (Archostemata, (Myxophaga, (Adephaga, Polyphaga))) 109.62 0.001* 70.81 0.018* T6 (Archostemata, (Polyphaga, (Myxophaga, Adephaga))) 59.96 0.036* 54.42 0.030* T2 ((Archostemata, Adephaga), (Polyphaga, Myxophaga)) 118.50 4e − 05* 93.51 1e − 22* T4 ((Archostemata, Myxophaga), (Adephaga, Polyphaga)) 92.38 5e − 04* 64.45 0.007* T5 ((Archostemata, Polyphaga), (Adephaga, Myxophaga)) 92.30 2e − 05* 80.11 0.003*

* p-value <0.05 indicates statistical rejection the earliest Permian and that most extant lineages, especially from one another (Table 1). It should be noted that our study phytophagous beetles, diverged during the Cretaceous, thus included only a single species of Archostemata and only one of suggesting that the rise of angiosperms in the Cretaceous may Myxophaga, which makes these taxa prone to long-branch have played an important role in the hyperdiversification of attraction (LBA). Therefore, the relationships among Adephaga, beetles. Our study provides a temporal perspective for under- Myxophaga, and Archostemata reported here should still be standing the evolutionary history of the Coleoptera and should considered as tentative and needed validation by future studies. provide a cornerstone for the further study of systematics of this The Adephaga has been divided into two monophyletic groups extraordinarily diverse order. (the terrestrial Geadephaga and aquatic Hydradephaga) by many molecular studies12,16,33; however, Hydradephaga is sometimes Results recovered as paraphyletic14,17,34. In agreement with the latter, our Higher level phylogenetic relationships of beetles. Our mole- analyses recovered Hydradephaga as paraphyletic with the cular data included 95 nuclear protein-coding genes from 373 aquatic Haliplidae and Gyrinidae forming a clade sister to all beetle species and 10 holometabolan outgroups (Supplementary other aquatic and terrestrial adephagans (Fig. 2). However, this Data 1). The gene coverage for species ranged from 49.1 to 96.3%, result had strong support only in the Bayesian analyses (BPP = with an average of 78.6% (Supplementary Data 2). The con- 0.96; Supplementary Figs. 5 and 6) and received negligible catenated supermatrix consisted of 23,802 amino acids (or 71,406 support in the ML analyses (BS <50%; Supplementary Figs. 1 and nucleotides). We estimated concatenated trees with both 2). Therefore, the phylogeny of Adephaga still remained nucleotide and deduced protein sequences by using two max- ambiguous. Given that our sampling of Hydradephaga was imum likelihood (ML) methods (RAxML and IQ-TREE) and a insufficient, recovering internal relationships of Adephaga may Bayesian approach (ExaBayes). The protein RAxML analysis require sampling more aquatic adephagan families Amphizoidae, produced a well-resolved phylogeny (Supplementary Fig. 1). Aspidytidae, Hygrobiidae, and Meruidae. Other ML and Bayesian analyses based on nucleotide or protein At the base of the strongly supported suborder Polyphaga, four sequences resulted in nearly identical phylogenies and similar families occupied the basal nodes, forming two successive branch support, as shown in Fig. 2 (Supplementary Figs. 2–6). branching clades sister to the remaining polyphagans (Fig. 2), Gene tree-based coalescent analysis (ASTRAL) of our data which is congruent with all recent studies12,14,16,28. In addition, recovered a tree with lower nodal support that was also congruent we corroborated the placement of Derodontidae as the sister with the ML tree after collapsing of clades with <50% bootstrap taxon to Clambidae + Eucinetidae with strong support (BS = 98%, support (Supplementary Fig. 7). These congruent results indi- BPP = 1.0; Fig. 2), which had been only weakly supported cated that the resulting phylogeny was highly robust regardless of before16. the data set and tree-building method. Series Elateriformia, which consists of the monophyletic Our phylogenetic analyses achieved well-supported resolution superfamilies Dascilloidea, Buprestoidea, Elateroidea, and of relationships among all major lineages of beetles. In the ML Byrrhoidea, was strongly recovered as the third branching lineage analyses, >85% of nodes were supported with standard bootstrap of Polyphaga, and a similar result has only recently been values (RAxML) ≥70% or ultrafast bootstrap values (IQ-TREE) proposed from an analysis of beetle mitogenomes17. ≥95% (Supplementary Figs. 1–4). More than 95% of nodes have Dascilloidea was strongly corroborated as the sister taxon to posterior probabilities between 0.95 and 1 in the Bayesian the other superfamilies of Elateriformia (BS = 100%; Fig. 2), in analyses (Supplementary Figs. 5 and 6). For this discussion, we agreement with recent studies14,16,35 but not with others12,17. use the protein RAxML tree as our preferred result (Fig. 2). Buprestoidea was recovered as a sister to a clade of Byrrhoidea At the base of the Coleoptera tree, our phylogeny strongly and Elateroidea. However, the sisterhood between Byrrhoidea and supported the relationships among suborders as Polyphaga Elateroidea was only strongly supported in Bayesian analyses (Adephaga (Myxophaga, Archostemata)), a hypothesis recently (Supplementary Figs. 3 and 4), similarly to the monophyly of reported by McKenna et al.16 and Sharkey et al.32, albeit with Byrrhoidea, in which moss-feeding Byrrhidae was only weakly negligible to moderate support. The topology recovered in this related to other byrrhoids (BS = 40%; Supplementary Fig. 1). study with high support provided an opportunity to assess Nosodendridae has previously been placed in various positions: relationships between suborders, which have been disputed for within Bostrichoidea7, within Derodontoidea11, associated with decades. The approximately unbiased (AU) test analysis showed Scirtoidea11,36, sister to Scarabaeiformia14, or grouped with that the three hypotheses with Polyphaga sister to the other three Elateriformia12,16. This family was robustly recovered in a novel suborders were significantly better than the other hypotheses, position in this study: as a sister clade to Staphyliniformia, although these three hypotheses were not significantly different Bostrichiformia, and Cucujiformia (BS = 100%; BPP = 1.0; Fig. 2).

4 NATURE COMMUNICATIONS | (2018) 9:205 | DOI: 10.1038/s41467-017-02644-4 | www.nature.com/naturecommunications NATURE COMMUNICATIONS | DOI: 10.1038/s41467-017-02644-4 ARTICLE

a 350 325 300275 250225 200175 150125 10075 5025 0 (Mya) Carboniferous Permian Triassic Jurassic Cretaceous Cenozoic Cupedidae Archostemata Torridincolidae Myxophaga Gyrinidae Haliplidae Noteridae Adephaga Dytiscidae Carabidae Scirtidae Derodontidae Scirtoidea Clambidae Eucinetidae +Derodontidae Rhipiceridae Dascillidae Dascilloidea Elateriformia Buprestidae Buprestoidea Polyphaga Byrrhidae Dryopidae Eulichadidae Ptilodactylidae Callirhipidae Chelonariidae Byrroidea Psephenidae Elmidae Limnichidae Cephalobyrrhus Limnichidae clade1 Heteroceridae Omethidae Artematopodidae Throscidae Eucnemidae Cantharidae Elateridae Osslimus Lycidae Elateroidea “Core Polyphaga” Elateridae clade1 Elateridae clade2 Phengodidae Rhagophthalmidae Lampyridae Nosodendridae Nosodendridae Histeridae Hydrophilidae Hydrophiloidea Jacobsoniidae Jacobsoniidae Ptiliidae Hydraenidae Agyrtidae Leiodidae Staphylinidae Centrophthalmus Staphylinoidea Staphylinidae Omaliinae Staphylinidae clade1 Staphylinidae clade2 Staphylinidae clade3 Silphidae Trogidae Lucanidae Geotrupidae Passalidae Scarabaeoidea Glaphyridae Hybosoridae Scarabaeidae Dermestidae Bostrichidae Bostrichoidea Ptinidae Bothrideridae Cerylonidae Philothermus Discolomatidae Murmidiidae Euxestidae Cerylonidae Ostomopsis Teredidae Coccinelloidea Alexiidae Latridiidae Anamorphidae Corylophidae Endomychidae Coccinellidae Phytophaga Megalopodidae Cerambycidae Chrysomeloidea Chrysomelidae Nemonychidae Anthribidae Belidae Curculionoidea Attelabidae Brentidae Cucujiformia Curculionidae Boganiidae Erotylidae Helotidae Sphindidae Protocucujidae Monotomidae b Cybocephalidae This study Kateretidae 360 27 Coleoptera Toussaint et al. Nitidulidae McKenna et al.16 Hobartiidae Cucujoidea 340 Polyphaga Hunt et al.12 Cryptophagidae Silvanidae 320 Cucujidae Phloeostichidae 300 Cucujiformia Myraboliidae Bostrichiformia Passandridae Elateriformia Phalacridae 280 Adephaga Propalticidae Laemophloeidae 260 Trogossitidae Rentonellum Byturidae 240 Biphyllidae Trogossitidae Leperina 220 Trogossitidae clade1 Acanthocnemidae Cleroidea Thanerocleridae 200 Cleridae Trogossitidae clade2 180 Prionoceridae Melyridae Mean divergence time and 95% CI (Mya) 160 Lymexylidae Lymexyloidea Ripiphoridae Trigonodera Coccinelloidea Cleroidea Ripiphoridae Rhipidioides 270 Elateroidea Mordellidae Ischaliidae Scarabaeoidea Curculionoidea Aderidae 240 Mycteridae Oedemeridae Dascilloidea Trictenotomidae 210 Boridae Scraptiidae Pythidae Salpingidae 180 Pyrochroidae Anthicidae Macratria Tenebrionoidea Anthicidae clade1 150 Anthicidae Anthicus Meloidae Melandryidae Dircaeomorpha 120 Incertae sedis Rhizonium Zopheridae clade1 Mycetophagidae 90 Archeocrypticidae Ulodidae Zopheridae Zopherosis

Mean divergence time and 95% CI (Mya) Melandryidae Melandryinae 60 Ciidae Tenebrionidae

350 325 300275 250225 200175 150125 10075 5025 0 (Mya)

Fig. 3 New timescale for beetle evolution and comparison of divergence times. a Time-calibrated tree of beetles. The time tree was collapsed to family level with outgroups removed (for detailed results, see Supplementary Fig. 8). Divergence times were estimated with MCMCTREE with 20 calibration points, on the basis of the amino acid data set. Fossil constraints within Coleoptera are shown with black triangles. Horizontal bars represent 95% credibility intervals. b Comparison of divergence time estimates for twelve major nodes sharing across four beetle time trees. The circle represents the mean age, and the whiskers mark the 95% credibility internals (Photo credits: Hong Pang, Yun Li, and Zhenhua Liu)

NATURE COMMUNICATIONS | (2018) 9:205 | DOI: 10.1038/s41467-017-02644-4 | www.nature.com/naturecommunications 5 ARTICLE NATURE COMMUNICATIONS | DOI: 10.1038/s41467-017-02644-4

– In agreement with many previous studies16 18,37,38, Hydro- doing so: (1) poor fossil preservation of beetles often prevents philoidea, Staphylinoidea (including Jacobsoniidae), and Scara- observation of the relevant characters, so it is possible to baeoidea formed a well-supported clade (BS = 94%; Fig. 2), thus erroneously place fossil taxa in extant families based on supporting a traditional monophyletic Haplogastra. Within this incomplete morphological characters; (2) our taxon sampling clade, Staphylinoidea (including Jacobsoniidae) was closer to does not cover all beetle families and some families are Scarabaeoidea than to Hydrophiloidea with moderate support (BS represented by only one species, the monophyly of some families = 78% and BPP = 1.0; Supplementary Figs. 1 and 5), inconsistent is not certain yet; (3) the monophyly of most superfamilies are with previous findings that Staphyliniformia (Staphylinoidea + robust but the family-level relationships within each superfamily Hydrophiloidea) was monophyletic or Hydrophiloidea was the is not robust. Therefore, it is more proper to use these fossils at sister group of Scarabaeoidea8,16,37,39. Derolathrus (Jacobsoniidae), superfamily level but not family-level under the current situation which has previously been assigned to the superfamily Derodon- of both taxon sampling and phylogenetic robustness. We also ran toidea, was strongly recovered as sister to Hydraenidae + Ptiliidae a time analysis using those fossils at family level to calibrate the within Staphylinoidea (BS >90%; Fig. 2). The same or similar stem ages of relevant families. The resulting times were on placements were recovered on the basis of both morphological and average 12% older than the times estimated by imposing fossils at molecular data11,16, thus strongly suggesting that Derolathrus superfamily level. This result indicated that the divergence times (Jacobsoniidae) should be transferred to Staphylinoidea. of beetle evolution are sensitive to the fossil calibration points, as Bostrichiformia was strongly supported as the sister group of recently suggested by Toussaint et al.27. Because the use of fossils the hyperdiverse series Cucujiformia in all of our analyses (BS = in beetle divergence time analyses is still under debate16,27,we 100%; Fig. 2). Among the seven recognized superfamilies within tentatively used the divergence times estimated by imposing Cucujiformia, Coccinelloidea was sister to the remaining super- fossils at superfamily level as our preferred time results. The full- families with moderate nodal support (BS = 69%; Fig. 2). The time tree for the 383 taxa sampled in this study is given in superfamily Cucujoidea (excluding Biphyllidae and Byturidae) Supplementary Fig. 8, and the family level time tree is was a strongly supported clade (BS = 93%; Fig. 2) and a sister summarized in Fig. 3a. The 383-taxa time tree using fossils at taxon to Phytophaga, which consists of the two highly supported family level can be found in Supplementary Fig. 9. superfamilies Curculionoidea and Chrysomeloidea (Fig. 2). The Overall, our divergence times were notably more precise (i.e., close relationships among Cucujoidea, Curculionoidea, and smaller confidence intervals) than those in the three previous Chrysomeloidea had maximal support in all analyses (BS = studies. The 95% confidence intervals (CIs) for the 12 selected 100%; BPP = 1.0; Fig. 2). Cleroidea was strongly recovered as nodes in the beetle tree (Fig. 3b) were ~50% narrower than monophyletic (BS = 100%; Fig. 2), when including Biphyllidae previous estimates. For example, the crown nodes of Coleoptera, and Byturidae, which were formerly placed in Cucujoidea but Adephaga, and Polyphaga in our study had 95% CIs ranging from recently transferred to Cleroidea12,40. The monophyly of 5.9 to 14.0 Mya, whereas McKenna et al.16 has reported CIs Lymexyloidea was moderately supported (BS = 64%; Fig. 2), and ranging from 28.9 to 43.1 Mya (Supplementary Table 2). We it was closely related to Tenebrionoidea with maximal support. redid the time analyses using our 95 genes but the exact same age These two superfamilies jointly are sister to Cleroidea, with constraints as used by McKenna et al.16 or Toussaint et al.27 and moderate support (BS = 72%; Fig. 2). still observed the increased precision of the dating results In summary, our beetle phylogeny corroborates many of the (Supplementary Fig. 10). This result indicated that the greater deeper coleopteran nodes inferred by other studies but with precision should be mainly attributed to the size of our data set greater support. Relationships among the deepest branches in the (71 kb), which exceeds those of previous studies (~8.4 kb at most) Polyphaga, for which previous studies have reported conflicting by at least eightfold. A similar increase in precision of divergence results, are now strongly supported. Our novel findings include time estimations was also found for plethodontid salamanders by the isolated position of Nosodendridae and a close relationship using 95 nuclear genes41. between Scarabaeoidea and Staphylinoidea. We estimated that the last common ancestor of extant beetles occurred during the earliest Permian at 297 Mya (95% CI 291–304), which is earlier than the Early Late Permian origin New timescale for beetle evolution. Before this study, only three (253–285 Mya) estimated by Hunt et al.12 and McKenna et al.16 comprehensive family-level studies have been performed to esti- but later than that of Toussaint et al.27 (~333 Mya) (Fig. 3b). The mate divergence times for Coleoptera with newly generated initial diversification of Polyphaga occurred at 280 (273–287) molecular data12,13,16. These three studies have suggested that the Mya, in the Early Permian, but the ‘core Polyphaga’ (excluding last common ancestor of Coleoptera first occurred in the Permian basal Scirtoidea and Derodontidae) occurred at 246 (240–253) period (253–285 Mya). However, certain time estimates have Mya, which was shortly after the Permian-Triassic (PT) boundary been criticized by Toussaint et al.27 because they conflict with (Fig. 3a). Notably, the basal Polyphaga lineages are species-poor current knowledge of the beetle fossil record. Using the data of (only ~1055 species), whereas the ‘core Polyphaga’ includes ~88% McKenna et al.16 but a different set of fossil calibration points, of the described extant species of beetles (~340,000 species), and Toussaint et al.27 have proposed a much older timescale for the branch leading to ‘core Polyphaga’ was long (24 million years Coleoptera for both deeper and shallower nodes. Their results in duration) and spanned the PT boundary (Fig. 3a). These have indicated that the crown age of Coleoptera was ~333 Mya, results indicated that Polyphaga originated in the Permian and which is in the mid Carboniferous. survived through the End-Permian mass extinction. The extensive sampling of nuclear genes in our study provides In shallower nodes, such as the origin of many beetle substantial new molecular data to estimate the divergence times superfamilies, our time estimates are considerably younger than for extant beetles. Our divergence time analyses used a Bayesian those of Toussaint et al.27 and more consistent with the results of relaxed clock method (MCMCTREE) and 20 fossil calibration the two earlier studies12,16 (Fig. 3b) and the results of other points carefully selected from currently known Coleoptera fossils researches focused on individual clades of beetles42,43. For (Supplementary Table 1). It should be pointed out that we used example, the crown age of Curculionoidea (weevils) estimated some fossils to calibrate the crown groups of the superfamilies in in this study is 157 (156–161) Mya, which is in the late Jurassic which they belong, even when the cited reference clearly places period, in agreement with the Jurassic origin proposed by the fossil in extant families. We have several considerations for Hunt et al.12 and McKenna et al.16,42. Toussaint et al.27 estimated

6 NATURE COMMUNICATIONS | (2018) 9:205 | DOI: 10.1038/s41467-017-02644-4 | www.nature.com/naturecommunications NATURE COMMUNICATIONS | DOI: 10.1038/s41467-017-02644-4 ARTICLE

300275 250225 200175 150125 10075 5025 0 (mya) Permian Triassic Jurassic Cretaceous Cenozoic

15 Cupedidae(31) Torridincolidae(60) Gyrinidae(882) Haliplidae(218) Noteridae(250) Dytiscidae(4015) Carabidae(40350) 12 Scirtidae(800) Derodontidae(30) 13 Clambidae(170) Eucinetidae(53) Rhipiceridae(70) Dascillidae(80) Buprestidae(14700) Byrrhidae(430) Dryopidae(300) Eulichadidae(30) Ptilodactylidae(500) Callirhipidae(150) Chelonariidae(250) Psephenidae(290) 10 Elmidae(1500) LimnichidaeHeteroceridae(690) Omethidae(33) Artematopodidae(45) Throscidae(150) Eucnemidae(1500) Cantharidae(5100) 5 Lissominae(150) Lycidae(4600) Elateridae1(4925) Elateridae2(4925) Phengodidae(250) Rhagophthalmidae(30) Lampyridae(2200) 14 Nosodendridae(50) Histeridae(4300) Hydrophilidae(3400) Jacobsoniidae(20) Ptiliidae(650) Hydraenidae(1600) Agyrtidae(70) Leiodidae(3700) StaphylinidaeSilphidae(56200) Trogidae(300) Lucanidae(1489) Geotrupidae(920) Passalidae(800) Glaphyridae(204) Diversification rate Hybosoridae(573) 3 Scarabaeidae(27000) 0.088 Dermestidae(1200) Bostrichidae(570) Ptinidae(2200) BothrideridSeries(1250) Alexiidae(50) Latridiidae(1000) Anamorphidae(174) 0.064 Corylophidae(200) Endomychidae(1606) Coccinellidae(6000) Megalopodidae(350) Cerambycidae(30079) Chrysomelidae(32500) 0.04 9 Nemonychidae(70) Anthribidae(3900) Belidae(375) Attelabidae(2500) Brentidae(4000) 1 Curculionidae(51000) 0.015 Boganiidae(11) Erotylidae(3500) Helotidae(107) Sphindidae(59) Protocucujidae(7) Monotomidae(250) Cybocephalidae(150) 11 Kateretidae(95) 8 Nitidulidae(4350) Hobartiidae(6) Cryptophagidae(600) Silvanidae(500) Cucujidae(44) Phloeostichidae(14) Myraboliidae(13) Passandridae(109) Phalacridae(640) 4 Propalticidae(30) Δ Laemophloeidae(430) Clade Rate AICc Rentoniinae(15) Byturidae(24) 1 0.0876 8.57 Biphyllidae(200) 2 0.0810 28.83 Trogossitidae2Acanthocnemidae(301) Thanerocleridae(30) 3 0.0804 27.78 Cleridae(3400) 7 4 0.0785 11.84 Trogossitidae1(300) Prionoceridae(160) 5 0.0710 30.98 Melyridae(6000) Lymexylidae(70) 6 0.0696 8.79 RipiphoridaeMordellidae(1900) 7 0.0678 17.96 Ischaliidae(34) Aderidae(900) 8 0.0657 6.28 Mycteridae(160) 9 0.0645 54.24 Oedemeridae(500) Trictenotomidae(13) 10 0.0642 5.44 Boridae(4) Scraptiidae(500) 11 0.0389 8.36 Pythidae(23) 12 0.0239 7.02 Salpingidae(300) Pyrochroidae(167) 13 0.0203 23.05 6 AnthicidaeMeloidae(6000) Melandryidae1(210) 14 0.0165 8.3 Incertae sedis Rhizonium(1) 15 0.0154 21.09 Zopheridae1(850) Mycetophagidae(130) Global rate 0.0484 Archeocrypticidae(60) Ulodidae(30) Zopheridae2(850) Melandryidae2(210) Ciidae(650) 2 Tenebrionidae(20000)

10,000 20,000 30,000 40,000 50,000 60,000 Number of species 300275 250225 200175 150125 10075 5025 0 (Mya)

Fig. 4 Diversification patterns of major beetle lineages inferred from MEDUSA analysis. Each terminal represents a monophyletic family-level taxon. The number in parenthesis next to the taxon name indicates the number of validly described species within the taxon. The species richness of each taxon is also indicated with histograms on the right. Branches are color coded to show the diversification rates. Clades with significant diversification rate shifts compared with the background rate are marked with circled numbers on the tree (red: rate increase; blue: rate decrease). Estimated net diversification rates and differences in AICc scores are included in the lower left table

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ab 0.1 60,000 Herbivorous & Rate accelerating event xylophagous Staphylinidae 0.09 55,000 Rate slowdown event 50,000 Fungivorous & Curculionidae 0.08 saprophagous 45,000 0.07 Predacious 40,000 Carabidae 0.06 35,000 Chrysomelidae 0.05 30,000 Cerambycidae Scarabaeidae 0.04 25,000 20,000 Tenebrionidae 0.03 Net diversification rate

Described extant species 15,000 Buprestidae* 0.02 10,000 Elateridae 0.01 5000 0 0 Permian Triassic Jurassic Cretaceous Cenozoic Permian Triassic Jurassic Cretaceous Cenozoic 300 280 260 240 220 200 180 160 140 120 100 80 60 40 20 0 (Mya) 300 280 260 240 220 200 180 160 140 120 100 80 60 40 20 0 (Mya) cd 60 40

50 30 40

30 20

20 Divergence events 10 10 Family-level divergence events

0 0 Permian Triassic Jurassic Cretaceous Cenozoic Permian Triassic Jurassic Cretaceous Cenozoic 300 280 260 240 220 200 180 160 140 120 100 80 60 40 20 0 (Mya) 300 280 260 240 220 200 180 160 140 120 100 80 60 40 20 0 (Mya)

Fig. 5 Diversification of beetles across the geological timescale. a Timing of the 15 significant changes in net diversification rate identified by MEDUSA. The dashed line denotes the background net diversification rate of Coleoptera. b Origin times and the species richness of beetle families. We used stem age as the origin time for a family when only one species is sampled for the family or when the taxon sampling did not cover the crown of the family. For non- monophyletic families, the stem age of the oldest lineage of the family was used. The nine largest families with species numbers >10,000 are highlighted with family names and feeding habits. For the Buprestidae (marked with an asterisk), we performed an additional time estimation, adding the Schizopodidae sequences from McKenna et al.16 to calculate the stem age of this family. c Number of divergence events within every 20 million year interval calculated from the 383-taxon time tree. Note that the diversification rate of beetles experienced an upsurge beginning from the late Jurassic (marked with a red line). d Number of divergence events within every 20 million year interval calculated from the family-level time tree. A similar diversification upsurge pattern was also detected in the late Jurassic this node to be 226.9 Mya (Late Triassic). In terms of the fossil have argued that there is no apparent association between the record, weevils first appear unequivocally in the Late Jurassic diversity of beetles and the diversification of angiosperms and (Karatau, Oxfordian—Kimmeridgian, 163.5–152.1 Mya), which is that the extreme diversity of beetles may be explained by their close to our time estimate. long evolutionary history, high-lineage survival, and diversifica- In summary, our new timescale for beetle evolution suggests tion in a wide range of niches. that the crown Coleoptera originated in the earliest Permian. The On the basis of the new timescale of beetles, we calculated the divergence among beetle series mainly occurred during the diversification pattern of beetles with both MEDUSA47 and Triassic, with most superfamilies appearing during the Jurassic, BAMM48. Both methods produced similar results of beetle and almost 64% of families appearing in the Cretaceous (stem diversification. We estimated the global diversification rate for ages are used here because some families have only one species Coleoptera to be 0.0484 lineages per million years (Myr) sampled in this study). Even when we use the alternative (MEDUSA) or 0.0510 lineages per million years (BAMM) (Fig. 4, calibration scheme (using fossils at family level), there are still Supplementary Fig. 11). The global diversification rate for 46% of families that originated during the Cretaceous (Supple- Coleoptera drops to ~0.045 lineages/Myr based on our alternative mentary Fig. 9). These age estimates corroborate many of the time estimate (using fossils at family level). These rates are dating results estimated by earlier studies, but with higher apparently low compared with those of other organism groups precision (having smaller CIs). that experienced rapid radiation, such as neoavian birds (0.089 lineages/Myr)47 and angiosperms (0.077 lineages/Myr)49. Because beetles originated in the lowermost Permian and have an Diversification tempo of beetles and its relationship with the apparently low-diversification rate, we agree with Hunt et al.12 rise of angiosperms. What factors cause the extraordinary species that the high-species richness of beetles as a whole should be richness of beetles are still widely discussed. From a perspective of attributed to their long history and low-lineage extinction. morphology, the sclerotized forewings (elytra), which protect the However, the MEDUSA analysis identified ten clades within membranous flying hindwings, may be responsible for the Coleoptera with significantly higher diversification rates apparent success of beetles3. Moreover, other studies have also (0.0642–0.0876 lineages/Myr) than the background diversification emphasized the importance of complete metamorphosis, devel- rate, and they all belong to the suborder Polyphaga (Fig. 4). The opment cycle and division of ecological niches to larvae and BAMM analysis also identified four rate-increase shifts that are adults as innovations of the extraordinary diversity of Holome- included within the MEDUSA results (Supplementary Fig. 11). tabola, including Coleoptera44,45. Another popular hypothesis These clades include most species-rich groups of beetles, such as suggests that the striking diversity of beetles is largely driven by Phytophaga, Scarabaeidae, Elateridae, and Tenebrionidae, which co-radiations with flowering plants42,46. However, Hunt et al.12 constitute ~56.3% of extant species of beetles, thus indicating that

8 NATURE COMMUNICATIONS | (2018) 9:205 | DOI: 10.1038/s41467-017-02644-4 | www.nature.com/naturecommunications NATURE COMMUNICATIONS | DOI: 10.1038/s41467-017-02644-4 ARTICLE more than half of beetle diversity can be attributed to fast from the Ensembl database (http://www.ensembl.org), including two beetles (Tri- diversification rates in certain clades. In addition, both BAMM and bolium castaneum and Dendronctonus ponderosae) and 6 other holometabolan fi MEDUSA analyses detected two or five clades with significantly insects. Therefore, our nal taxon sampling included 383 species (373 beetles and fi 10 outgroups). We did not include Strepsiptera as an outgroup to beetles, because lower diversi cation rates than the background rate (Fig. 4; among the 95 genes used in this study, only 44 (missing data >50%) could find Supplementary Fig. 11), and they mainly belong to the species- orthologous sequences in the published Strepsiptera genome57. All specimens poor beetle groups. Moreover, 9 of 10 rate-accelerating events derived from the Biological Museum of Sun Yet-Sen University, China and Aus- detected by MEDUSA occurred in the Cretaceous, although all five tralian National Insect Collection, CSIRO, in Canberra, Australia were marked with unique numbers. The detailed information of taxonomy, locality, collector/iden- rate slowdown events occurred much earlier (Fig. 5a). A similar tifier of specimens was provided in Supplementary Data 1. pattern was observed when we used the alternative timescale of beetles: seven identical rate-increasing events were detected and five DNA sequencing. Specimens were preserved in 95% ethanol and stored at −20 °C. of them occurred in the Cretaceous, while all rates slowdown shifts DNA was extracted from the thorax muscles, legs or the entire specimen using a predated the Cretaceous (Supplementary Fig. 12). These results TIANamp Genomic DNA kit (TIANGEN Inc., Beijing, China). Voucher specimens suggested that the Cretaceous was an important period in shaping have been deposited in the Biological Museum of Sun Yat-Sen University. Ninety-five nuclear protein-coding genes were amplified from DNA extracts by PCR using the the extreme diversity of beetles. 31 fi Flowering plants (angiosperms) diversified quickly during the protocol and primers described in Che et al. . The ampli cation products were 50,51 sequenced using a next-generation sequencing (NGS) strategy, as described by Feng Cretaceous period and became the dominant group of plants . et al.58.Briefly, all amplification products from a single specimen were pooled toge- Interestingly, among the nine largest beetle families, which have ther and purified. The specimen amplification product pools were then randomly >10,000 described species, seven were estimated to originate in sheared to small fragments (200–500 bp), the ends were repaired, and a species- fi fi the Cretaceous, and their diets are associated with plants (Fig. 5b). speci c barcode linker was added. All indexed ampli cation product pools were then mixed together, and a sequencing library was constructed with the pooled DNA using Curculionidae, Chrysomelidae, Cerambycidae, and Buprestidae the TruSeq DNA Sample Preparation kit and sequenced on an Illumina HiSeq are phytophagous, and more than three-quarters of species in 2500 sequencer. Approximately 24 GB of 90-bp Illumina HiSeq paired-end reads were Scarabaeidae are phytophagous, whereas certain species in obtained. These reads were bioinformatically sorted by barcode sequences and 59 Tenebrionidae and Elateridae are phytophagous, and many assembled into consensus sequences using Trinity . All assembled sequences were checked for possible intron insertion by using a Python script provided by Che others feed on decomposing plant materials and woody tissues. et al.31.Thefinal intron-removed sequences were further examined for frame shifts In contrast, the other two species-rich families (Staphylinidae and and stop codons to ensure that they could be properly translated. GenBank accession Carabidae) that are predominantly predacious were estimated to numbers for the new sequences are given in Supplementary Data 3. originate in the Early Jurassic, long before the Cretaceous (Fig. 5b). The coordination of diversification between angios- Sequence alignment and data partition. All 95 genes were aligned using the perms and phytophagous beetles, but not with predacious beetles, ClustalW algorithm implemented in MEGA v660 on the basis of the translated amino acid sequences. Ambiguously aligned regions were trimmed using Gblock clearly shows that the extraordinary diversity of phytophagous 61 = beetles can be attributed to co-evolution with angiosperms. v.0.91b , with all gaps allowed (-b5 a) and all other parameters at default set- fi tings. Nucleotide alignments were performed according to the corresponding To show the diversi cation tempo of beetles through time, we protein alignments using a custom Python script. All 95 protein and nucleotide counted the number of divergence events of Coleoptera within alignments were concatenated. Binning genes into ‘supergenes’ is a statistical technique that can account for sampling error by increasing signal-to-noise ratio, every interval of 20 million years from the Permian to the present, 62–64 on the basis of our 383-species time tree. We noticed that the and it has been applied in phylogenetics recently . Because many genes in our fi data set are short, we thus used data binning strategy to partition our data. The diversi cation rate of beetles experienced an upsurge in the late protein data set was divided into 10 partitions according to the evolutionary rate of Jurassic (~160 Mya) and reached the greatest speed in the each gene (measured as their overall mean P distances). ProtTest 365 was used to Cretaceous (Fig. 5c). This rate-elevating pattern remained stable identify the best-fit models for the 10 partitions with the Bayesian information when we counted divergence events on the family-level time tree criterion (BIC). We also did additional phylogenetic analyses using different partitioning schemes. The phylogenies inferred from unpartitioned and 95-gene- (Fig. 5d). Although the oldest angiosperm fossils date from the partitioned data set are almost identical to that inferred from 10-bin-partitioned 52,53 Valanginian to the Hauterivian in the Cretaceous , the crown data set, except several nodes with negligible supports (Supplementary Fig. 13). age of the angiosperms has been estimated to be at least 160 This result showed that different partitioning schemes have little influence to the Mya54,55. Therefore, the diversification rate pattern of beetles is final phylogenetic results. For the nucleotide data set, we used a Perl script (Degen_v1_4.pl; http://www.phylotools.com) to degenerate nucleotides to IUPAC still consistent with the beetle-angiosperm co-evolution hypoth- fi 46 ambiguity codes for the rst and third codon positions, an extension of RY coding, esis . However, the accelerating diversification of beetles in the which can reduce the effect of nucleotide compositional heterogeneity66. The late Jurassic also indicates that the rapid radiation of beetles degenerated nucleotide data set makes synonymous changes largely invisible but began before flowering plants flourished. non-synonymous changes largely intact, which can be supported in RAxML and IQ-TREE analyses. The resulting nucleotide data matrix was partitioned by codons Overall, no single explanation can explain the success of the (three partitions defined), and the best-fit models for every codon partition was order Coleoptera. Perhaps, the Permian origin of the crown group selected with PartitionFinder67. and a long period of evolution steadily increased the diversity of beetles. Because lineage survival was high, beetle diversification ‘ ’ Phylogenetic analyses. The protein and nucleotide data sets were analyzed with entered an exponential phase in the late Jurassic. The subsequent both ML and Bayesian inference (BI) methods. The ML analyses were conducted boom of flowering plants in the Cretaceous provided new using RAxML v.8.068 and IQ-TREE69. Branch support in the RAxML analyses were ecological opportunities for phytophagous beetles, thus further evaluated through a rapid bootstrap algorithm (-f a option) with 500 replicates. In promoting the biodiversity of beetles. All these factors together the IQ-TREE ML analyses, nodal support values were estimated using the embedded ultrafast bootstrap approach (UFBoot), which is computational efficient create the great diversity of extant beetles. and relatively unbiased70. Bayesian analyses were conducted using ExaBayes v1.4.171. Two Markov Chain Monte Carlo (MCMC) runs were performed with one cold chain and three heated Methods chains (temperature set to 0.1) for 50 million generations, and sampling was Taxon sampling. In this study, we used a Coleoptera classification that incorpo- performed every 1000 generations. The average standard deviation of split rated results from Ślipiński et al.1 and Bouchard et al.10 with the exception of frequencies (ASDSFs) and potential scale reduction factor (PSRF) were <1% and Rhysodidae, which is considered to be a subfamily of Carabidae11, and added the close to 1 across the two runs, respectively. The effective sample sizes (ESSs) were recently proposed superfamilies Coccinelloidea and eight recently elevated (or re- >200 for all parameters after the first 20% of generations were discarded. elevated) families40,56. We sampled 371 coleopteran taxa representing the 4 extant The species tree analysis without gene concatenation was performed for the suborders, 7 series, 17 superfamilies and 124 of 186 families. Four neuropterid taxa, protein data set using ASTRAL 4.7.672 under the coalescent model. For each gene, including 3 families of Neuroptera and 1 family of Megaloptera, were used as the best ML tree and 200 bootstrapping trees were inferred by RAxML under the outgroups. Most of the missing families were species-poor lineages with limited best fitting model selected by ProtTest. The species tree analysis was then distribution. Additionally, we added 8 taxa with public genome data downloaded conducted using ASTRAL taking these 95 unrooted best ML trees and

NATURE COMMUNICATIONS | (2018) 9:205 | DOI: 10.1038/s41467-017-02644-4 | www.nature.com/naturecommunications 9 ARTICLE NATURE COMMUNICATIONS | DOI: 10.1038/s41467-017-02644-4 corresponding bootstrapping trees as input, under the multilocus bootstrapping 3. Crowson, R. A. The Biology of the Coleoptera (Acadamic Press, 1981). = option with 200 replicates (-r 200). 4. Crowson, R. A. The Natural Classification of the Families of Coleoptera 73 The approximately unbiased (AU) test was used to evaluate the alternative (Nathaniel Lloyd, 1955). beetle phylogeny hypotheses, and site-wise log likelihoods of all alternative 5. Crowson, R. A. The phylogeny of Coleoptera. Annu. Rev. Entomol. 5, 111–134 topologies were calculated with RAxML using the -f g option. Then, the site log- fi (1960). likelihood le was used as input to estimate the P-values for each alternative 6. Lawrence, J. F. & Newton, A. F. Evolution and classification of beetles. Annu. hypothesis using the AU test implemented in the program CONSEL74. Rev. Ecol. Syst. 13, 261–290 (1982). 7. Lawrence, J. F. & Newton, A. F. in Biology, Phylogeny, and Classification of Divergence time estimation. Divergence times were estimated by using Coleoptera: Papers Celebrating the 80th Birthday of Roy A. Crowson MCMCTREE in the PAML package75 with the uncorrelated rate model (clock = 2). (eds. Pakaluk, J. & Ślipiński, S. A.) 779–1006 (Museum i Instytut Zoologii PAN, The protein RAxML tree was used as the reference topology. Twenty fossils Warszawa, 1995). (Supplementary Table 1), of which 13 were within the Coleoptera, were used to 8. Beutel, R. G. & Leschen, R. A. B. in Handbook of Zoology Coleoptera, Beetles: calibrate the clock. Imposing maximum bounds is necessary when estimating deep Morphology and Systematics (Archostemata, Adephaga, Myxophaga, Polyphaga 76 divergence times . Because holometabolous insects are not known from before the partim) 1 (Walter de Gruyter, 2005). Pennsylvanian of the Carboniferous, we constrained the maximum age of the 9. Leschen, R. A. B., Beutel, R. G. & Lawrence, J. F. Handbook of Zoology Coleoptera-Neuropterida split to 323.2 Mya, the Mississippian-Pennsylvanian Coleoptera, Beetles: Morphology and Systematics (Elateroidea, Bostrichiformia, boundary, which is a fairly conservative maximum bound for this node. To further fi Cucujiformia partim) 2 (Walter de Gruyter, 2010). limit the effect of imposing an erroneous maximum constraint, we speci ed the tail 10. Bouchard, P. et al. Family-group names in Coleoptera (Insecta). Zookeys 88, probability of this maximum bound as 2.5%; thus, the time estimation had a 2.5% 1–972 (2011). probability of being greater than the bound. 11. Lawrence, J. F. et al. Phylogeny of the Coleoptera based on morphological The ML estimates of the branch lengths for each of the 10 protein partitions 61 – were calculated using CODEML (in PAML) under the WAG + F + Γ model. To characters of adults and larvae. Ann. Zool. ,1 217 (2011). 12. Hunt, T. et al. A comprehensive phylogeny of beetles reveals the evolutionary specify the prior on the overall substitution rate, the root age (crown – Holometabola) was set to 345 Mya, according to a recent phylogenomic estimate23. origins of a superradiation. Science 318, 1913 1916 (2007). On the basis of the mean tree depth from the 10 protein partitions, the gamma- 13. McKenna, D. D. & Farrell, B. D. The Timetree of Life (eds Hedges, S. B. – Dirichlet prior for the overall substitution rate (rgene gamma) was set at G (1, & Kumar, S.) 278 289 (Oxford University Press, 2009). > 8.36), and the gamma-Dirichlet prior for the rate-drift parameter (sigma2 gamma) 14. Bocak, L. et al. Building the Coleoptera tree-of-life for 8000 species: was set at G (1, 4.5). The posterior time estimates were conducted by using a composition of public DNA data and fit with Linnaean classification. Syst. MCMC algorithm. After the first 100,000 iterations were discarded as burn-in, the Entomol. 39,97–110 (2014). MCMC run was sampled every 100 iterations until it achieved 10,000 samples. Two 15. Crampton-Platt, A. et al. Soup to tree: the phylogeny of beetles inferred by MCMC runs using different random seeds were compared to determine their mitochondrial metagenomics of a Bornean rainforest sample. Mol. Biol. Evol. convergence with similar results, and effective sample sizes of every node age and 32, 2302–2316 (2015). every parameter were >200, as determined in Tracer V1.477 software. 16. McKenna, D. D. et al. The beetle tree of life reveals that Coleoptera survived end-Permian mass extinction to diversify during the Cretaceous terrestrial – Diversification rate analyses. We used MEDUSA(Modeling Evolutionary revolution. Syst. Entomol. 40, 835 880 (2015). Diversification Using Stepwise AIC)47 and BAMM (Bayesian Analysis of Macro- 17. Timmermans, M. J. T. N. et al. Family-level sampling of mitochondrial evolutionary Mixture)48 to investigate the tempo of diversification of the Coleop- genomes in Coleoptera: compositional heterogeneity and phylogenetics. – tera. MEDUSA was conducted on the ultrametric phylogenetic tree with the species Genome Biol. Evol. 8, 161 175 (2016). richness data. The time-calibrated Coleoptera tree generated by MCMCTREE was 18. Kukalová-Peck, J. & Lawrence, J. F. Evolution of the hind wing in Coleoptera. pruned to a family-level chronogram so that each terminal reflected a mono- Can. Entomol. 125, 181–258 (1993). phyletic family (or possible equal). In some cases, families that were not mono- 19. Beutel, R. G. & Haas, F. Phylogenetic relationships of the suborders of phyletic were grouped together or split apart. The approximate numbers of Coleoptera (Insecta). Cladistics 141, 103–141 (2000). described species for terminals were obtained from Ślipiński et al.1. MEDUSA 20. Caterino, M. S. et al. Basal relationships of Coleoptera inferred from 18S rDNA sequentially adds rate shifts to the family-level chronogram until further additions sequences. Zool. Scr. 31,41–49 (2002). fail to have a distinct increase in model fit (i.e., the improvement in AIC score is 21. Pons, J., Ribera, I., Bertranpetit, J. & Balke, M. Nucleotide substitution rates for lower than the threshold). The MEDUSA analysis was conducted in R using the the full set of mitochondrial protein-coding genes in Coleoptera. Mol. packages Geiger78 with the default settings, including the corrected AIC (AICc) Phylogenet. Evol. 56, 796–807 (2010). criterion and mixed model. 22. Song, H., Sheffield, N. C., Cameron, S. L., Miller, K. B. & Whiting, M. F. When We also detected diversification rate shifts using BAMM v. 2.5. The 383-taxa phylogenetic assumptions are violated: Base compositional heterogeneity and time-calibrated tree was used as input tree. To account for incomplete taxa among-site rate variation in beetle mitochondrial phylogenomics. Syst. sampling, we used a non-random incomplete taxon sampling correction and Entomol. 35, 429–448 (2010). fi fi speci ed this sampling fractions by families. The family-speci c sampling 23. Misof, B. et al. Phylogenomics resolves the timing and pattern of insect probabilities were specified according to described species diversity obtained from – Ś ń 1 evolution. Science 346, 763 767 (2014). lipi ski et al. . The BAMM analysis was run for 60 million generations at a 24. Grimaldi, D. & Engel, M. S. Evolution of the Insects (Cambridge University, temperature increment parameter of 0.01 and sampled event data every 1000 fi 2005). generations. We discarded the rst 10% generations as burn-in and examined the fi – > 25. Béthoux, O. The earliest beetle identi ed. 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All new gene sequences have been deposited in 29. Peters, R. S. et al. The evolutionary history of holometabolous insects inferred GenBank (for accession numbers, Supplementary Data 3). The raw Illumina from transcriptome-based phylogeny and comprehensive morphological data. sequencing data generated in this paper can be downloaded from the NCBI BMC Evol. Biol. 14, 52 (2014). Sequence Read Archive under the BioProject Accession Number PRJNA419242. 30. Wild, A. L. & Maddison, D. R. Evaluating nuclear protein-coding genes for phylogenetic utility in beetles. Mol. Phylogenet. Evol. 48, 877–891 (2008). Received: 5 May 2017 Accepted: 15 December 2017 31. Che, L. H. et al. Genome-wide survey of nuclear protein-coding markers for beetle phylogenetics and their application in resolving both deep and shallow- level divergences. Mol. Ecol. Resour. 17, 1342–1358 (2017). 32. Sharkey, C. R. et al. 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