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Genome-wide macroevolutionary signatures of key innovations in butterflies colonizing new host plants

  • 1.

    Becerra, J. X. On the factors that promote the diversity of herbivorous insects and plants in tropical forests. Proc. Natl Acad. Sci. USA 112, 6098–6103 (2015).

    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

  • 2.

    Stork, N. E. How many species of insects and other terrestrial arthropods are there on earth? Annu. Rev. Entomol. 63, 31–45 (2018).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  • 3.

    Grimaldi, D. A. & Engel, M. S. Evolution of the Insects (Cambridge University Press, 2005).

  • 4.

    Strong, D. R., Lawton, J. H. & Southwood, R. Insects on Plants: Community Patterns and Mechanisms (Harvard University Press, 1984).

  • 5.

    Ehrlich, P. R. & Raven, P. H. Butterflies and plants: a study in coevolution. Evolution 18, 586–608 (1964).

    Article  Google Scholar 

  • 6.

    Thompson, J. N. Concepts of coevolution. Trends Ecol. Evol. 4, 179–183 (1989).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  • 7.

    Mitter, C., Farrell, B. & Wiegmann, B. The phylogenetic study of adaptive zones: has phytophagy promoted insect diversification? Am. Nat. 132, 107–128 (1988).

    Article  Google Scholar 

  • 8.

    Farrell, B. D. ‘Inordinate fondness’ explained: why are there so many beetles? Science 281, 555–559 (1998).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  • 9.

    Berenbaum, M. & Specialization, P. F. Chemical Mediation of Host-plant Specialization: The Papilionid Paradigm. Specialization, Speciation, and Radiation: The Evolutionary Biology of Herbivorous Insects (University of California Press, 2008).

  • 10.

    Winter, S., Friedman, A. L. L., Astrin, J. J., Gottsberger, B. & Letsch, H. Timing and host plant associations in the evolution of the weevil tribe Apionini (Apioninae, Brentidae, Curculionoidea, Coleoptera) indicate an ancient co-diversification pattern of beetles and flowering plants. Mol. Phylogenet. Evol. 107, 179–190 (2017).

    PubMed  Article  PubMed Central  Google Scholar 

  • 11.

    Kergoat, G. J. et al. Opposite macroevolutionary responses to environmental changes in grasses and insects during the Neogene grassland expansion. Nat. Commun. 9, 5089 (2018).

    ADS  PubMed  PubMed Central  Article  CAS  Google Scholar 

  • 12.

    Wheat, C. W. et al. The genetic basis of a plant–insect coevolutionary key innovation. Proc. Natl Acad. Sci. USA 104, 20427–20431 (2007).

    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

  • 13.

    Edger, P. P. et al. The butterfly plant arms-race escalated by gene and genome duplications. Proc. Natl Acad. Sci. USA 112, 8362–8366 (2015).

    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

  • 14.

    Calla, B. et al. Cytochrome P450 diversification and hostplant utilization patterns in specialist and generalist moths: Birth, death and adaptation. Mol. Ecol. 26, 6021–6035 (2017).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  • 15.

    Nallu, S. et al. The molecular genetic basis of herbivory between butterflies and their host plants. Nat. Ecol. Evol. 2, 1418–1427 (2018).

    PubMed  PubMed Central  Article  Google Scholar 

  • 16.

    Karageorgi, M. et al. Genome editing retraces the evolution of toxin resistance in the monarch butterfly. Nature 574, 409–412 (2019).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  • 17.

    Sahoo, R. K., Warren, A. D., Collins, S. C. & Kodandaramaiah, U. Hostplant change and paleoclimatic events explain diversification shifts in skipper butterflies (Family: Hesperiidae). BMC Evol. Biol. 17, 174 (2017).

    PubMed  PubMed Central  Article  Google Scholar 

  • 18.

    Condamine, F. L., Rolland, J., Höhna, S., Sperling, F. A. H. & Sanmartín, I. Testing the role of the red queen and court jester as drivers of the macroevolution of apollo butterflies. Syst. Biol. 67, 940–964 (2018).

    PubMed  Article  PubMed Central  Google Scholar 

  • 19.

    Letsch, H. et al. Climate and host-plant associations shaped the evolution of ceutorhynch weevils throughout the Cenozoic. Evolution 72, 1815–1828 (2018).

    PubMed  PubMed Central  Article  Google Scholar 

  • 20.

    Forister, M. L. et al. The global distribution of diet breadth in insect herbivores. Proc. Natl Acad. Sci. USA 112, 442–447 (2015).

    ADS  CAS  PubMed  Article  Google Scholar 

  • 21.

    Winkler, I. S., Mitter, C. & Scheffer, S. J. Repeated climate-linked host shifts have promoted diversification in a temperate clade of leaf-mining flies. Proc. Natl Acad. Sci. USA 106, 18103–18108 (2009).

    ADS  CAS  PubMed  Article  Google Scholar 

  • 22.

    Chomicki, G., Weber, M., Antonelli, A., Bascompte, J. & Kiers, E. T. The impact of mutualisms on species richness. Trends Ecol. Evol. 34, 698–711 (2019).

    PubMed  Article  Google Scholar 

  • 23.

    Janz, N. Ehrlich and Raven revisited: mechanisms underlying codiversification of plants and enemies. Annu. Rev. Ecol. Evol. Syst. 42, 71–89 (2011).

    Article  Google Scholar 

  • 24.

    Suchan, T. & Alvarez, N. Fifty years after Ehrlich and Raven, is there support for plant–insect coevolution as a major driver of species diversification? Entomol. Exp. Appl. 157, 98–112 (2015).

    Article  Google Scholar 

  • 25.

    Endara, M.-J. et al. Coevolutionary arms race versus host defense chase in a tropical herbivore-plant system. Proc. Natl Acad. Sci. USA 114, E7499–E7505 (2017).

    CAS  PubMed  Article  Google Scholar 

  • 26.

    Simon, J.-C. et al. Genomics of adaptation to host-plants in herbivorous insects. Brief. Funct. Genomics 14, 413–423 (2015).

    CAS  PubMed  Article  Google Scholar 

  • 27.

    Hammer, T. J., Janzen, D. H., Hallwachs, W., Jaffe, S. P. & Fierer, N. Caterpillars lack a resident gut microbiome. Proc. Natl Acad. Sci. USA 114, 9641–9646 (2017).

    CAS  PubMed  Article  Google Scholar 

  • 28.

    Hua, X. & Bromham, L. Darwinism for the genomic age: connecting mutation to diversification. Front. Genet. 8, 12 (2017).

    PubMed  PubMed Central  Article  Google Scholar 

  • 29.

    Hembry, D. H. & Weber, M. G. Ecological interactions and macroevolution: a new field with old roots. Annu. Rev. Ecol. Evol. Syst. 51, (2020).

  • 30.

    Scriber, J. M., Tsubaki, Y. & Lederhouse, R. C. Swallowtail Butterflies: Their Ecology and Evolutionary Biology (Scientific Publishers, 1995).

  • 31.

    Nishida, R. Sequestration of defensive substances from plants by Lepidoptera. Annu. Rev. Entomol. 47, 57–92 (2002).

    CAS  PubMed  Article  Google Scholar 

  • 32.

    Schmeiser, H. H., Stiborovà, M. & Arlt, V. M. Chemical and molecular basis of the carcinogenicity of Aristolochia plants. Curr. Opin. Drug Discov. Dev. 12, 141–148 (2009).

    CAS  Google Scholar 

  • 33.

    Poon, S. L. et al. Genome-wide mutational signatures of aristolochic acid and its application as a screening tool. Sci. Transl. Med. 5, 197ra101 (2013).

    PubMed  Article  CAS  Google Scholar 

  • 34.

    Condamine, F. L., Sperling, F. A. H., Wahlberg, N., Rasplus, J.-Y. & Kergoat, G. J. What causes latitudinal gradients in species diversity? Evolutionary processes and ecological constraints on swallowtail biodiversity. Ecol. Lett. 15, 267–277 (2012).

    PubMed  Article  Google Scholar 

  • 35.

    Simonsen, T. J. et al. Phylogenetics and divergence times of Papilioninae (Lepidoptera) with special reference to the enigmatic genera Teinopalpus and Meandrusa. Cladistics 27, 113–137 (2011).

    Article  Google Scholar 

  • 36.

    Berenbaum, M. R., Favret, C. & Schuler, M. A. On defining ‘Key Innovations’ in an adaptive radiation: cytochrome P450s and Papilionidae. Am. Nat. 148, S139–S155 (1996).

    Article  Google Scholar 

  • 37.

    Cohen, M. B., Schuler, M. A. & Berenbaum, M. R. A host-inducible cytochrome P-450 from a host-specific caterpillar: molecular cloning and evolution. Proc. Natl Acad. Sci. USA 89, 10920–10924 (1992).

    ADS  CAS  PubMed  Article  Google Scholar 

  • 38.

    Li, W., Schuler, M. A. & Berenbaum, M. R. Diversification of furanocoumarin-metabolizing cytochrome P450 monooxygenases in two papilionids: specificity and substrate encounter rate. Proc. Natl Acad. Sci. USA 100(Suppl.), 14593–14598 (2003).

    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

  • 39.

    Thompson, J. N. Variation in preference and specificity in monophagous and oligophagous swallowtail butterflies. Evolution 42, 118–128 (1988).

    PubMed  Article  PubMed Central  Google Scholar 

  • 40.

    Thompson, J. N., Wehling, W. & Podolsky, R. Evolutionary genetics of host use in swallowtail butterflies. Nature 344, 148–150 (1990).

    ADS  Article  Google Scholar 

  • 41.

    Berenbaum, M. R. & Feeny, P. P. in Specialization, Speciation, and Radiation: The Evolutionary Biology of Herbivorous Insects (ed. Tilmon, K.) 2–19 (University of California Press, 2008).

  • 42.

    Zakharov, E. V., Caterino, M. S. & Sperling, F. A. H. Molecular phylogeny, historical biogeography, and divergence time estimates for swallowtail butterflies of the genus Papilio (Lepidoptera: Papilionidae). Syst. Biol. 53, 193–215 (2004).

    PubMed  Article  Google Scholar 

  • 43.

    Braby, M., Trueman, J. & Eastwood, R. When and where did troidine butterflies (Lepidoptera: Papilionidae) evolve? Phylogenetic and biogeographic evidence suggests an origin in remnant Gondwana in the Late Cretaceous. Invertebr. Syst. 19, 113–143 (2005).

    Article  Google Scholar 

  • 44.

    Condamine, F. L., Silva-Brandão, K. L., Kergoat, G. J. & Sperling, F. A. Biogeographic and diversification patterns of Neotropical Troidini butterflies (Papilionidae) support a museum model of diversity dynamics for Amazonia. BMC Evol. Biol. 12, 82 (2012).

    PubMed  PubMed Central  Article  Google Scholar 

  • 45.

    Condamine, F. L. et al. Deciphering the evolution of birdwing butterflies 150 years after Alfred Russel Wallace. Sci. Rep. 5, 11860 (2015).

    ADS  PubMed  PubMed Central  Article  Google Scholar 

  • 46.

    Allio, R. et al. Whole genome shotgun phylogenomics resolves the pattern and timing of swallowtail butterfly evolution. Syst. Biol. 69, 38–60 (2020).

    CAS  PubMed  Article  Google Scholar 

  • 47.

    McKenna, D. D., Sequeira, A. S., Marvaldi, A. E. & Farrell, B. D. Temporal lags and overlap in the diversification of weevils and flowering plants. Proc. Natl Acad. Sci. USA.106, 7083–7088 (2009).

    ADS  CAS  PubMed  Article  Google Scholar 

  • 48.

    Takahashi, D. & Setoguchi, H. Molecular phylogeny and taxonomic implications of Asarum (Aristolochiaceae) based on ITS and matK sequences. Plant Species Biol. 33, 28–41 (2018).

    Article  Google Scholar 

  • 49.

    Wanke, S. et al. Evolution of Piperales—matK gene and trnK intron sequence data reveal lineage specific resolution contrast. Mol. Phylogenet. Evol. 42, 477–497 (2007).

    CAS  PubMed  Article  Google Scholar 

  • 50.

    Neinhuis, C., Wanke, S., Hilu, K. W., Müller, K. & Borsch, T. Phylogeny of Aristolochiaceae based on parsimony, likelihood, and Bayesian analyses of trnL-trnF sequences. Plant Syst. Evol. 250, 7–26 (2005).

    Article  Google Scholar 

  • 51.

    Wanke, S., González, F. & Neinhuis, C. Systematics of pipevines: combining morphological and fast‐evolving molecular characters to investigate the relationships within subfamily Aristolochioideae. Int. J. Plant Sci. 167, 1215–1227 (2006).

    CAS  Article  Google Scholar 

  • 52.

    González, F. et al. Present trans-Pacific disjunct distribution of Aristolochia subgenus Isotrema (Aristolochiaceae) was shaped by dispersal, vicariance and extinction. J. Biogeogr. 41, 380–391 (2014).

    Article  Google Scholar 

  • 53.

    Durden, C. J. & Rose, H. Butterflies from the Middle Eocene: The Earliest Occurrence of Fossil Papilionoidea (Lepidoptera) (Prarce-Sellards Ser. Tax. Mem. Mus., 1978).

  • 54.

    Sohn, J., Labandeira, C., Davis, D. & Mitter, C. An annotated catalog of fossil and subfossil Lepidoptera (Insecta: Holometabola) of the world. Zootaxa 3286, 1–132 (2012).

    Article  Google Scholar 

  • 55.

    de Jong, R. Estimating time and space in the evolution of the Lepidoptera. Tijdschr. voor Entomol. 150, 319–346 (2007).

    Article  Google Scholar 

  • 56.

    Hofmann, C.-C. & Zetter, R. Upper Cretaceous sulcate pollen from the Timerdyakh formation, Vilui Basin (Siberia). Grana 49, 170–193 (2010).

    Article  Google Scholar 

  • 57.

    Meller, B. The first fossil Aristolochia (Aristolochiaceae, Piperales) leaves from Austria. Palaeontol. Electron 17, 1–17 (2014).

    Google Scholar 

  • 58.

    Nee, S., May, R. M. & Harvey, P. H. The reconstructed evolutionary process. Philos. Trans. R. Soc. Lond. Ser. B 344, 305–311 (1994).

    ADS  CAS  Article  Google Scholar 

  • 59.

    Nee, S. Birth-death models in macroevolution. Annu. Rev. Ecol. Evol. Syst. 37, 1–17 (2006).

    Article  Google Scholar 

  • 60.

    Rabosky, D. L. & Lovette, I. J. Explosive evolutionary radiations: Decreasing speciation or increasing extinction through time? Evolution 62, 1866–1875 (2008).

    PubMed  Article  PubMed Central  Google Scholar 

  • 61.

    Crisp, M. D. & Cook, L. G. Explosive radiation or cryptic mass extinction? Interpreting signatures in molecular phylogenies. Evolution 63, 2257–2265 (2009).

    PubMed  Article  PubMed Central  Google Scholar 

  • 62.

    Quental, T. B. & Marshall, C. R. Diversity dynamics: molecular phylogenies need the fossil record. Trends Ecol. Evol. 25, 434–441 (2010).

    PubMed  Article  PubMed Central  Google Scholar 

  • 63.

    Morlon, H. Phylogenetic approaches for studying diversification. Ecol. Lett. 17, 508–525 (2014).

    PubMed  Article  PubMed Central  Google Scholar 

  • 64.

    Xue, B. et al. Accelerated diversification correlated with functional traits shapes extant diversity of the early divergent angiosperm family Annonaceae. Mol. Phylogenet. Evol. 142, 106659 (2020).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  • 65.

    Folk, R. A. et al. Rates of niche and phenotype evolution lag behind diversification in a temperate radiation. Proc. Natl Acad. Sci. USA 116, 10874–10882 (2019).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  • 66.

    Sun, M. et al. Recent accelerated diversification in rosids occurred outside the tropics. Nat. Commun. 11, 3333 (2020).

    ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

  • 67.

    Losos, J. B. Adaptive radiation, ecological opportunity, and evolutionary determinism. Am. Nat. 175, 623–639 (2010).

    PubMed  Article  PubMed Central  Google Scholar 

  • 68.

    Cheng, T. et al. Genomic adaptation to polyphagy and insecticides in a major East Asian noctuid pest. Nat. Ecol. Evol. 1, 1747–1756 (2017).

    PubMed  Article  PubMed Central  Google Scholar 

  • 69.

    Rane, R. V. et al. Detoxifying enzyme complements and host use phenotypes in 160 insect species. Curr. Opin. Insect Sci. 31, 131–138 (2019).

    MathSciNet  PubMed  Article  PubMed Central  Google Scholar 

  • 70.

    Cong, Q., Borek, D., Otwinowski, Z. & Grishin, N. V. Tiger swallowtail genome reveals mechanisms for speciation and caterpillar chemical defense. Cell Rep. 10, 910–919 (2015).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  • 71.

    Li, X. et al. Outbred genome sequencing and CRISPR/Cas9 gene editing in butterflies. Nat. Commun. 6, 8212 (2015).

    ADS  PubMed  PubMed Central  Article  Google Scholar 

  • 72.

    Nishikawa, H. et al. A genetic mechanism for female-limited Batesian mimicry in Papilio butterfly. Nat. Genet. 47, 405–409 (2015).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  • 73.

    Thomas, G. W. C. & Hahn, M. W. Determining the null model for detecting adaptive convergence from genomic data: a case study using echolocating mammals. Mol. Biol. Evol. 32, 1232–1236 (2015).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  • 74.

    Zou, Z. & Zhang, J. No genome-wide protein sequence convergence for echolocation. Mol. Biol. Evol. 32, 1237–1241 (2015).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  • 75.

    Kimura, M. The Neutral Theory of Molecular Evolution (Cambridge University Press, 1983).

  • 76.

    Yang, Z. Computational Molecular Evolution (Oxford University Press, 2006).

  • 77.

    Venkat, A., Hahn, M. W. & Thornton, J. W. Multinucleotide mutations cause false inferences of lineage-specific positive selection. Nat. Ecol. Evol. 2, 1280–1288 (2018).

    PubMed  PubMed Central  Article  Google Scholar 

  • 78.

    Mendes, F. K. & Hahn, M. W. Gene tree discordance causes apparent substitution rate variation. Syst. Biol. 65, 711–721 (2016).

    PubMed  Article  PubMed Central  Google Scholar 

  • 79.

    Dasmahapatra, K. K. et al. Butterfly genome reveals promiscuous exchange of mimicry adaptations among species. Nature 487, 94–98 (2012).

    ADS  CAS  PubMed Central  Article  Google Scholar 

  • 80.

    Walden, N. et al. Nested whole-genome duplications coincide with diversification and high morphological disparity in Brassicaceae. Nat. Commun. 11, 3795 (2020).

    ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

  • 81.

    McGee, M. D. et al. The ecological and genomic basis of explosive adaptive radiation. Nature 586, 75–79 (2020).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  • 82.

    Thomas, G. W. C. et al. Gene content evolution in the arthropods. Genome Biol. 21, 15 (2020).

    PubMed  PubMed Central  Article  Google Scholar 

  • 83.

    de Medeiros, B. A. S. & Farrell, B. D. Evaluating species interactions as a driver of phytophagous insect divergence. bioRxiv https://doi.org/10.1101/842153 (2019).

  • 84.

    Katoh, K. & Standley, D. M. MAFFT multiple sequence alignment software version 7: Improvements in performance and usability. Mol. Biol. Evol. 30, 772–780 (2013).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  • 85.

    Lanfear, R., Frandsen, P. B., Wright, A. M., Senfeld, T. & Calcott, B. PartitionFinder 2: new methods for selecting partitioned models of evolution for molecular and morphological phylogenetic analyses. Mol. Biol. Evol. 34, 772–773 (2016).

    Google Scholar 

  • 86.

    Nguyen, L.-T., Schmidt, H. A., von Haeseler, A. & Minh, B. Q. IQ-TREE: a fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Mol. Biol. Evol. 32, 268–274 (2015).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  • 87.

    Kalyaanamoorthy, S., Minh, B. Q., Wong, T. K. F., von Haeseler, A. & Jermiin, L. S. ModelFinder: fast model selection for accurate phylogenetic estimates. Nat. Methods 14, 587–589 (2017).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  • 88.

    Chernomor, O., von Haeseler, A. & Minh, B. Q. Terrace aware data structure for phylogenomic inference from supermatrices. Syst. Biol. 65, 997–1008 (2016).

    PubMed  PubMed Central  Article  Google Scholar 

  • 89.

    Minh, B. Q., Nguyen, M. A. T. & von Haeseler, A. Ultrafast approximation for phylogenetic bootstrap. Mol. Biol. Evol. 30, 1188–1195 (2013).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  • 90.

    Ronquist, F. et al. MrBayes 3.2: efficient bayesian phylogenetic inference and model choice across a large model space. Syst. Biol. 61, 539–542 (2012).

    PubMed  PubMed Central  Article  Google Scholar 

  • 91.

    Huelsenbeck, J. P., Larget, B. & Alfaro, M. E. Bayesian phylogenetic model selection using reversible jump Markov Chain Monte Carlo. Mol. Biol. Evol. 21, 1123–1133 (2004).

    CAS  PubMed  Article  Google Scholar 

  • 92.

    Rambaut, A., Drummond, A. J., Xie, D., Baele, G. & Suchard, M. A. Posterior summarization in bayesian phylogenetics using Tracer 1.7. Syst. Biol. 67, 901–904 (2018).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  • 93.

    Douady, C. J., Delsuc, F., Boucher, Y., Doolittle, W. F. & Douzery, E. J. P. Comparison of bayesian and maximum likelihood bootstrap measures of phylogenetic reliability. Mol. Biol. Evol. 20, 248–254 (2003).

    CAS  PubMed  Article  Google Scholar 

  • 94.

    Miller, M. A. et al. A RESTful API for access to phylogenetic tools via the CIPRES Science Gateway. Evol. Bioinforma. 11, EBO.S21501 (2015).

    Article  Google Scholar 

  • 95.

    Ayres, D. L. et al. BEAGLE: an application programming interface and high-performance computing library for statistical phylogenetics. Syst. Biol. 61, 170–173 (2012).

    PubMed  Article  Google Scholar 

  • 96.

    Drummond, A. J., Ho, S. Y. W., Phillips, M. J. & Rambaut, A. Relaxed phylogenetics and dating with confidence. PLoS Biol. 4, e88 (2006).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  • 97.

    Drummond, A. J., Suchard, M. A., Xie, D. & Rambaut, A. Bayesian phylogenetics with BEAUti and the BEAST 1.7. Mol. Biol. Evol. 29, 1969–1973 (2012).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  • 98.

    Smith, M. E., Singer, B. & Carroll, A. 40Ar/39Ar geochronology of the Eocene Green River Formation, Wyoming. Geol. Soc. Am. Bull. 115, 549–565 (2003).

    ADS  CAS  Article  Google Scholar 

  • 99.

    de Jong, R. Fossil butterflies, calibration points and the molecular clock (Lepidoptera: Papilionoidea). Zootaxa 4270, 1–63 (2017).

    PubMed  Article  PubMed Central  Google Scholar 

  • 100.

    Scudder, S. H. Fossil butterflies. Mem. Am. Assoc. Adv. Sci. 1, 1–99 (1875).

    Google Scholar 

  • 101.

    Rasnitsyn, A. P. & Zherikhin, V. V. in History of Insects 437–446 (Kluwer Academic Publishers, 2002).

  • 102.

    Rebel, H. Doritites bosniaskii. Sitzungsberichte der akademie der wissenschaften. Mathematischen-Naturwissenschaftliche classe. Abt. 1 Mineral. Biol. Erdkd. 1, 734–741 (1898).

    Google Scholar 

  • 103.

    Carpenter, F. Treatise on Invertebrate Paleontology: Arthropoda 4. Superclass Hexapoda (Geological Society of America, 1992).

  • 104.

    Magallón, S., Gómez-Acevedo, S., Sánchez-Reyes, L. L. & Hernández-Hernández, T. A metacalibrated time‐tree documents the early rise of flowering plant phylogenetic diversity. N. Phytol. 207, 437–453 (2015).

    Article  Google Scholar 

  • 105.

    Sohn, J.-C., Labandeira, C. C. & Davis, D. R. The fossil record and taphonomy of butterflies and moths (Insecta, Lepidoptera): implications for evolutionary diversity and divergence-time estimates. BMC Evol. Biol. 15, 12 (2015).

    PubMed  PubMed Central  Article  Google Scholar 

  • 106.

    Toussaint, E. F. A. & Condamine, F. L. To what extent do new fossil discoveries change our understanding of clade evolution? A cautionary tale from burying beetles (Coleoptera: Nicrophorus). Biol. J. Linn. Soc. 117, 686–704 (2016).

    Article  Google Scholar 

  • 107.

    Gernhard, T. The conditioned reconstructed process. J. Theor. Biol. 253, 769–778 (2008).

    MathSciNet  PubMed  MATH  Article  Google Scholar 

  • 108.

    Lewis, P. O. A likelihood approach to estimating phylogeny from discrete morphological character data. Syst. Biol. 50, 913–925 (2001).

    CAS  PubMed  Article  Google Scholar 

  • 109.

    Ree, R. H. & Smith, S. A. Maximum likelihood inference of geographic range evolution by dispersal, local extinction, and cladogenesis. Syst. Biol. 57, 4–14 (2008).

    PubMed  Article  Google Scholar 

  • 110.

    Pagel, M. & Meade, A. Bayesian analysis of correlated evolution of discrete characters by reversible-jump Markov chain Monte Carlo. Am. Nat. 167, 808–825 (2006).

    PubMed  Article  PubMed Central  Google Scholar 

  • 111.

    Igarashi, S. The classification of the Papilionidae mainly based on the morphology of their immature stages. Lepid. Sci. 34, 41–96 (1984).

    Google Scholar 

  • 112.

    Collins, N. M. & Morris, M. Threatened Swallowtail Butterflies of the World: the IUCN Red Data Book (IUCN, 1985).

  • 113.

    Tyler, H. A., Brown, K. S. & Wilson, K. H. Swallowtail Butterflies of the Americas: A Study in Biological Dynamics, Ecological Diversity, Biosystematics, and Conservation (Scientific Publishers, 1994).

  • 114.

    Ree, R. H., Moore, B. R., Webb, C. O. & Donoghue, M. J. A likelihood framework for inferring the evolution of geographic range on phylogenetic trees. Evolution 59, 2299–2311 (2005).

    PubMed  Article  PubMed Central  Google Scholar 

  • 115.

    Massoni, J., Couvreur, T. L. & Sauquet, H. Five major shifts of diversification through the long evolutionary history of Magnoliidae (Angiosperms). BMC Evol. Biol. 15, 49 (2015).

    PubMed  PubMed Central  Article  Google Scholar 

  • 116.

    Kyalangalilwa, B., Boatwright, J. S., Daru, B. H., Maurin, O. & van der Bank, M. Phylogenetic position and revised classification of Acacia s.l. (Fabaceae: Mimosoideae) in Africa, including new combinations in Vachellia and Senegalia. Bot. J. Linn. Soc. 172, 500–523 (2013).

    Article  Google Scholar 

  • 117.

    Miller, J. T., Murphy, D. J., Ho, S. Y. W., Cantrill, D. J. & Seigler, D. Comparative dating of Acacia: combining fossils and multiple phylogenies to infer ages of clades with poor fossil records. Aust. J. Bot. 61, 436–445 (2013).

    Article  Google Scholar 

  • 118.

    Michalak, I., Zhang, L.-B. & Renner, S. S. Trans-Atlantic, trans-Pacific and trans-Indian Ocean dispersal in the small Gondwanan Laurales family Hernandiaceae. J. Biogeogr. 37, 1214–1226 (2010).

    Article  Google Scholar 

  • 119.

    Wu, S.-D. et al. Evolution of asian interior arid-zone biota: Evidence from the diversification of asian Zygophyllum (Zygophyllaceae). PLoS ONE 10, e0138697 (2015).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  • 120.

    Chase, M. W. et al. An update of the Angiosperm Phylogeny Group classification for the orders and families of flowering plants: APG IV. Bot. J. Linn. Soc. 181, 1–20 (2016).

    Article  Google Scholar 

  • 121.

    Christenhusz, M. J. M., Vorontsova, M. S., Fay, M. F. & Chase, M. W. Results from an online survey of family delimitation in angiosperms and ferns: recommendations to the Angiosperm Phylogeny Group for thorny problems in plant classification. Bot. J. Linn. Soc. 178, 501–528 (2015).

    Article  Google Scholar 

  • 122.

    Gonzáles, F., Rudall, P. J. & Furness, C. A. Microsporogenesis and systematics of Aristolochiaceae. Bot. J. Linn. Soc. 137, 221–242 (2001).

    Article  Google Scholar 

  • 123.

    González, F. & Rudall, P. The questionable affinities of Lactoris: evidence from branching pattern, inflorescence morphology, and stipule development. Am. J. Bot. 88, 2143–2150 (2001).

    PubMed  Article  PubMed Central  Google Scholar 

  • 124.

    Isnard, S. et al. Growth form evolution in Piperales and its relevance for understanding angiosperm diversification: An integrative approach combining plant architecture, anatomy, and biomechanics. Int. J. Plant Sci. 173, 610–639 (2012).

    Article  Google Scholar 

  • 125.

    Wagner, S. T. et al. Major trends in stem anatomy and growth forms in the perianth-bearing Piperales, with special focus on Aristolochia. Ann. Bot. 113, 1139–1154 (2014).

    PubMed  PubMed Central  Article  Google Scholar 

  • 126.

    Nickrent, D. L. et al. Molecular data place Hydnoraceae with Aristolochiaceae. Am. J. Bot. 89, 1809–1817 (2002).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  • 127.

    Kelly, L. M. & González, F. Phylogenetic relationships in Aristolochiaceae. Syst. Bot. 28, 236–249 (2003).

    Google Scholar 

  • 128.

    Naumann, J. et al. Single-copy nuclear genes place haustorial Hydnoraceae within piperales and reveal a cretaceous origin of multiple parasitic angiosperm lineages. PLoS ONE 8, e79204 (2013).

    ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

  • 129.

    Salomo, K. et al. The emergence of earliest angiosperms may be earlier than fossil evidence indicates. Syst. Bot. 42, 607–619 (2017).

    PubMed  PubMed Central  Article  Google Scholar 

  • 130.

    Christenhusz, M. J. M. & Byng, J. W. The number of known plants species in the world and its annual increase. Phytotaxa 261, 201–217 (2016).

    Article  Google Scholar 

  • 131.

    Naumann, J. et al. Detecting and characterizing the highly divergent plastid genome of the nonphotosynthetic parasitic plant Hydnora visseri (Hydnoraceae). Genome Biol. Evol. 8, 345–363 (2016).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  • 132.

    Jost, M., Naumann, J., Rocamundi, N., Cocucci, A. A. & Wanke, S. The first plastid genome of the Holoparasitic genus Prosopanche (Hydnoraceae). Plants 9, 306 (2020).

    CAS  PubMed Central  Article  PubMed  Google Scholar 

  • 133.

    Zavada, M. S. & Benson, J. M. First fossil evidence for the primitive angiosperm family Lactoricidae. Am. J. Bot. 74, 1590–1594 (1987).

    Article  Google Scholar 

  • 134.

    Gamerro, J. C. & Barreda, V. New fossil record of Lactoridaceae in southern South America: a palaeobiogeographical approach. Bot. J. Linn. Soc. 158, 41–50 (2008).

    Article  Google Scholar 

  • 135.

    Smith, S. Y. & Stockey, R. A. Establishing a fossil record for the perianthless Piperales: Saururus tuckerae sp. nov. (Saururaceae) from the Middle Eocene Princeton Chert. Am. J. Bot. 94, 1642–1657 (2007).

    PubMed  Article  Google Scholar 

  • 136.

    Massoni, J., Doyle, J. & Sauquet, H. Fossil calibration of Magnoliidae, an ancient lineage of angiosperms. Palaeontol. Electron. 18, 1–25 (2015).

    Google Scholar 

  • 137.

    Smith, S. A. Taking into account phylogenetic and divergence-time uncertainty in a parametric biogeographical analysis of the Northern Hemisphere plant clade Caprifolieae. J. Biogeogr. 36, 2324–2337 (2009).

    Article  Google Scholar 

  • 138.

    Beeravolu, C. R. & Condamine, F. L. An extended maximum likelihood inference of geographic range evolution by dispersal, local extinction and cladogenesis. bioRxiv https://doi.org/10.1101/038695 (2016).

  • 139.

    Scotese, C. R. A continental drift flipbook. J. Geol. 112, 729–741 (2004).

    ADS  Article  Google Scholar 

  • 140.

    Blakey, R. C. Gondwana paleogeography from assembly to breakup—a 500 m.y. odyssey. Geol. Soc. Am. Spec. Pap. 441, 1–28 (2008).

    Google Scholar 

  • 141.

    Seton, M. et al. Global continental and ocean basin reconstructions since 200 Ma. Earth Sci. Rev. 113, 212–270 (2012).

    ADS  Article  Google Scholar 

  • 142.

    Chacón, J. & Renner, S. S. Assessing model sensitivity in ancestral area reconstruction using Lagrange: a case study using the Colchicaceae family. J. Biogeogr. 41, 1414–1427 (2014).

    Article  Google Scholar 

  • 143.

    Maddison, W. P., Midford, P. E. & Otto, S. P. Estimating a binary character’s effect on speciation and extinction. Syst. Biol. 56, 701–710 (2007).

    PubMed  Article  PubMed Central  Google Scholar 

  • 144.

    FitzJohn, R. G., Maddison, W. P. & Otto, S. P. Estimating trait-dependent speciation and extinction rates from incompletely resolved phylogenies. Syst. Biol. 58, 595–611 (2009).

    PubMed  Article  PubMed Central  Google Scholar 

  • 145.

    Morlon, H., Parsons, T. L. & Plotkin, J. B. Reconciling molecular phylogenies with the fossil record. Proc. Natl Acad. Sci. USA 108, 16327–16332 (2011).

    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

  • 146.

    Rabosky, D. L. et al. Rates of speciation and morphological evolution are correlated across the largest vertebrate radiation. Nat. Commun. 4, 1958 (2013).

    ADS  PubMed  Article  CAS  PubMed Central  Google Scholar 

  • 147.

    Höhna, S. et al. A Bayesian approach for estimating branch-specific speciation and extinction rates. bioRxiv https://doi.org/10.1101/555805 (2019).

  • 148.

    May, M. R., Höhna, S. & Moore, B. R. A Bayesian approach for detecting the impact of mass-extinction events on molecular phylogenies when rates of lineage diversification may vary. Methods Ecol. Evol. 7, 947–959 (2016).

    Article  Google Scholar 

  • 149.

    Magallon, S. & Sanderson, M. J. Absolute diversification rates in angiosperm clades. Evolution 55, 1762–1780 (2001).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  • 150.

    Rabosky, D. L. Likelihood methods for detecting temporal shifts in diversification rates. Evolution 60, 1152–1164 (2006).

    PubMed  Article  PubMed Central  Google Scholar 

  • 151.

    FitzJohn, R. G. Diversitree: comparative phylogenetic analyses of diversification in R. Methods Ecol. Evol. 3, 1084–1092 (2012).

    Article  Google Scholar 

  • 152.

    Scriber, J. M. in Chemical Ecology of Insects (eds Bell, W. J. & Cardé, R. T.) 159–202 (Springer US, 1984).

  • 153.

    Davis, M. P., Midford, P. E. & Maddison, W. Exploring power and parameter estimation of the BiSSE method for analyzing species diversification. BMC Evol. Biol. 13, 38 (2013).

    PubMed  PubMed Central  Article  Google Scholar 

  • 154.

    Maddison, W. P. & FitzJohn, R. G. The unsolved challenge to phylogenetic correlation tests for categorical characters. Syst. Biol. 64, 127–136 (2015).

    PubMed  Article  PubMed Central  Google Scholar 

  • 155.

    Rabosky, D. L. & Goldberg, E. E. Model inadequacy and mistaken inferences of trait-dependent speciation. Syst. Biol. 64, 340–355 (2015).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  • 156.

    Morlon, H. et al. RPANDA: an R package for macroevolutionary analyses on phylogenetic trees. Methods Ecol. Evol. 7, 589–597 (2016).

    Article  Google Scholar 

  • 157.

    Rabosky, D. L. Automatic detection of key innovations, rate shifts, and diversity-dependence on phylogenetic trees. PLoS ONE 9, e89543 (2014).

    ADS  PubMed  PubMed Central  Article  CAS  Google Scholar 

  • 158.

    Moore, B. R., Höhna, S., May, M. R., Rannala, B. & Huelsenbeck, J. P. Critically evaluating the theory and performance of Bayesian analysis of macroevolutionary mixtures. Proc. Natl Acad. Sci. USA 113, 9569–9574 (2016).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  • 159.

    Rabosky, D. L. et al. BAMMtools: an R package for the analysis of evolutionary dynamics on phylogenetic trees. Methods Ecol. Evol. 5, 701–707 (2014).

    Article  Google Scholar 

  • 160.

    Rabosky, D. L., Mitchell, J. S. & Chang, J. Is BAMM flawed? Theoretical and practical concerns in the analysis of multi-rate diversification models. Syst. Biol. 66, 477–498 (2017).

    PubMed  PubMed Central  Article  Google Scholar 

  • 161.

    Höhna, S. et al. RevBayes: Bayesian phylogenetic inference using graphical models and an interactive model-specification language. Syst. Biol. 65, 726–736 (2016).

    PubMed  PubMed Central  Article  Google Scholar 

  • 162.

    Höhna, S., May, M. R. & Moore, B. R. TESS: an R package for efficiently simulating phylogenetic trees and performing Bayesian inference of lineage diversification rates. Bioinformatics 32, 789–791 (2016).

    PubMed  Article  CAS  PubMed Central  Google Scholar 

  • 163.

    Stadler, T. Mammalian phylogeny reveals recent diversification rate shifts. Proc. Natl Acad. Sci. USA 108, 6187–6192 (2011).

    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

  • 164.

    Partha, R. et al. Subterranean mammals show convergent regression in ocular genes and enhancers, along with adaptation to tunneling. eLife 6, e25884 (2017).

    PubMed  PubMed Central  Article  Google Scholar 

  • 165.

    Wu, J., Yonezawa, T. & Kishino, H. Rates of molecular evolution suggest natural history of life history traits and a Post-K-Pg nocturnal bottleneck of placentals. Curr. Biol. 27, 3025–3033 (2017).

    CAS  PubMed  Article  Google Scholar 

  • 166.

    Zhang, G. et al. Comparative genomics reveals insights into avian genome evolution and adaptation. Science 346, 1311–1320 (2014).

    ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

  • 167.

    Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  • 168.

    Luo, R. et al. SOAPdenovo2: an empirically improved memory-efficient short-read de novo assembler. Gigascience 1, 18 (2012).

    PubMed  PubMed Central  Article  Google Scholar 

  • 169.

    Abascal, F., Zardoya, R. & Telford, M. J. TranslatorX: multiple alignment of nucleotide sequences guided by amino acid translations. Nucleic Acids Res. 38, W7–W13 (2010).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  • 170.

    Simion, P. et al. A software tool ‘CroCo’ detects pervasive cross-species contamination in next generation sequencing data. BMC Biol. 16, 28 (2018).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  • 171.

    Emms, D. M. & Kelly, S. OrthoFinder: phylogenetic orthology inference for comparative genomics. Genome Biol. 20, 238 (2019).

    PubMed  PubMed Central  Article  Google Scholar 

  • 172.

    Di Franco, A., Poujol, R., Baurain, D. & Philippe, H. Evaluating the usefulness of alignment filtering methods to reduce the impact of errors on evolutionary inferences. BMC Evol. Biol. 19, 21 (2019).

    PubMed  PubMed Central  Article  Google Scholar 

  • 173.

    Capella-Gutierrez, S., Silla-Martinez, J. M. & Gabaldon, T. trimAl: a tool for automated alignment trimming in large-scale phylogenetic analyses. Bioinformatics 25, 1972–1973 (2009).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  • 174.

    Yang, Z. & Nielsen, R. Estimating synonymous and nonsynonymous substitution rates under realistic evolutionary models. Mol. Biol. Evol. 17, 32–43 (2000).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  • 175.

    Zhang, J., Nielsen, R. & Yang, Z. Evaluation of an improved branch-site likelihood method for detecting positive selection at the molecular level. Mol. Biol. Evol. 22, 2472–2479 (2005).

    CAS  PubMed  Article  Google Scholar 

  • 176.

    Yang, Z. Likelihood ratio tests for detecting positive selection and application to primate lysozyme evolution. Mol. Biol. Evol. 15, 568–573 (1998).

    CAS  PubMed  Article  Google Scholar 

  • 177.

    Yang, Z. PAML 4: phylogenetic analysis by maximum likelihood. Mol. Biol. Evol. 24, 1586–1591 (2007).

    CAS  Article  PubMed  Google Scholar 

  • 178.

    Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. 57, 289–300 (1995).

    MathSciNet  MATH  Google Scholar 

  • 179.

    Bauer, D. F. Constructing confidence sets using rank statistics. J. Am. Stat. Assoc. 67, 687–690 (1972).

    MATH  Article  Google Scholar 

  • 180.

    Diekmann, Y. & Pereira-Leal, J. B. Gene tree affects inference of sites under selection by the branch-site test of positive selection. Evol. Bioinforma. 11, 11–17 (2015).

    Article  Google Scholar 

  • 181.

    Mallick, S., Gnerre, S., Muller, P. & Reich, D. The difficulty of avoiding false positives in genome scans for natural selection. Genome Res. 19, 922–933 (2009).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  • 182.

    Fletcher, W. & Yang, Z. The effect of insertions, deletions, and alignment errors on the branch-site test of positive selection. Mol. Biol. Evol. 27, 2257–2267 (2010).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  • 183.

    Jordan, G. & Goldman, N. The effects of alignment error and alignment filtering on the sitewise detection of positive selection. Mol. Biol. Evol. 29, 1125–1139 (2012).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  • 184.

    Duret, L. & Galtier, N. Biased gene conversion and the evolution of mammalian genomic landscapes. Annu. Rev. Genomics Hum. Genet. 10, 285–311 (2009).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  • 185.

    Galtier, N. & Duret, L. Adaptation or biased gene conversion? Extending the null hypothesis of molecular evolution. Trends Genet. 23, 273–277 (2007).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  • 186.

    Ratnakumar, A. et al. Detecting positive selection within genomes: the problem of biased gene conversion. Philos. Trans. R. Soc. Ser. B 365, 2571–2580 (2010).

    CAS  Article  Google Scholar 

  • 187.

    Guéguen, L. et al. Bio++: efficient extensible libraries and tools for computational molecular evolution. Mol. Biol. Evol. 30, 1745–1750 (2013).

    PubMed  Article  CAS  Google Scholar 

  • 188.

    Wickham, H. & Grolemund, G. R for Data Science: Import, Tidy, Transform, Visualize, and Model Data (O’Reilly Media, Inc., Canada, 2016).

  • 189.

    Wilke, C. O. cowplot: streamlined plot theme and plot annotations for ‘ggplot2.’ CRAN Repos. 2, R2 (2016).

  • 190.

    Gouy, M., Guindon, S. & Gascuel, O. SeaView version 4: a multiplatform graphical user interface for sequence alignment and phylogenetic tree building. Mol. Biol. Evol. 27, 221–224 (2010).

    CAS  PubMed  Article  Google Scholar 

  • 191.

    Redelings, B. Erasing errors due to alignment ambiguity when estimating positive selection. Mol. Biol. Evol. 31, 1979–1993 (2014).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  • 192.

    Mi, H., Muruganujan, A., Ebert, D., Huang, X. & Thomas, P. D. PANTHER version 14: More genomes, a new PANTHER GO-slim and improvements in enrichment analysis tools. Nucleic Acids Res. 47, D419–D426 (2019).

    CAS  Article  PubMed  Google Scholar 

  • 193.

    Huerta-Cepas, J. et al. Fast genome-wide functional annotation through orthology assignment by eggNOG-mapper. Mol. Biol. Evol. 34, 2115–2122 (2017).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  • 194.

    Huerta-Cepas, J. et al. eggNOG 5.0: a hierarchical, functionally and phylogenetically annotated orthology resource based on 5090 organisms and 2502 viruses. Nucleic Acids Res. 47, D309–D314 (2019).

    CAS  PubMed  Article  Google Scholar 


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