Movatterモバイル変換


[0]ホーム

URL:


Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Advertisement

Nature Ecology & Evolution
  • Article
  • Published:

Complex modular architecture around a simple toolkit of wing pattern genes

Nature Ecology & Evolutionvolume 1, Article number: 0052 (2017)Cite this article

Subjects

Abstract

Identifying the genomic changes that control morphological variation and understanding how they generate diversity is a major goal of evolutionary biology. InHeliconius butterflies, a small number of genes control the development of diverse wing colour patterns. Here, we used full-genome sequencing of individuals across theHeliconius erato radiation and closely related species to characterize genomic variation associated with wing pattern diversity. We show that variation around colour pattern genes is highly modular, with narrow genomic intervals associated with specific differences in colour and pattern. This modular architecture explains the diversity of colour patterns and provides a flexible mechanism for rapid morphological diversification.

This is a preview of subscription content,access via your institution

Access options

Access through your institution

Access Nature and 54 other Nature Portfolio journals

Get Nature+, our best-value online-access subscription

9,800 Yen / 30 days

cancel any time

Subscribe to this journal

Receive 12 digital issues and online access to articles

¥14,900 per year

only ¥1,242 per issue

Buy this article

  • Purchase on SpringerLink
  • Instant access to full article PDF

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Geographical distribution, phylogeny and colour pattern diversity of theHeliconius erato adaptive radiation.
Figure 2: Genomic divergence across theHeliconius erato phenotypic transition zones.
Figure 3: Association mapping in hybrid zones and phylogenetic comparisons identify the modular genetic architecture of black forewing variation.
Figure 4: Modular architecture of red pattern variation.
Figure 5: Independent modules generate convergent yellow hindwing bar phenotypes.
Figure 6: Modular regulatory architecture characterizes colour pattern diversity within theHeliconius erato radiation.

Similar content being viewed by others

References

  1. Dasmahapatra, K. K. et al. Butterfly genome reveals promiscuous exchange of mimicry adaptations among species.Nature487, 94–98 (2012).

    Article CAS PubMed Central  Google Scholar 

  2. Lamichhaney, S. et al. Evolution of Darwin’s finches and their beaks revealed by genome sequencing.Nature518, 371–375 (2015).

    Article CAS PubMed  Google Scholar 

  3. Brawand, D. et al. The genomic substrate for adaptive radiation in African cichlid fish.Nature513, 375–381 (2014).

    Article CAS PubMed PubMed Central  Google Scholar 

  4. Lamas, G. inHesperioidea – Papilionoidea. Gainesville, Florida: Association for Tropical Lepidoptera (ed. Lamas, G. ) 261–274 (Scientific Publisher, 2004).

    Google Scholar 

  5. Nijhout, H. F.The Development and Evolution of Butterfly Wing Patterns. (Smithsonian Institution, 1991).

    Google Scholar 

  6. Chouteau, M., Arias, M. & Joron, M. Warning signals are under positive frequency-dependent selection in nature.Proc. Natl Acad. Sci USA113, 2164–2169 (2016).

    Article CAS PubMed PubMed Central  Google Scholar 

  7. Naisbit, R. E., Jiggins, C. D. & Mallet, J. Disruptive sexual selection against hybrids contributes to speciation betweenHeliconius cydno andHeliconius melpomene .Proc. Biol. Sci.268, 1849–1854 (2001).

    Article CAS PubMed PubMed Central  Google Scholar 

  8. Turner, J. R. G. A tale of two butterflies.Nat. Hist.84, 28–37 (1975).

    Google Scholar 

  9. Sheppard, P. M., Turner, J. R. G., Brown, K. S., Benson, W. W. & Singer, M. C. Genetics and the evolution of Muellerian mimicry inHeliconius Butterflies.Phil. Trans. R. Soc. B Biol. Sci.308, 433–610 (1985).

    Article  Google Scholar 

  10. Joron, M. et al. A conserved supergene locus controls colour pattern diversity inHeliconius butterflies.PLoS Biol.4, e303 (2006).

    Article PubMed PubMed Central  Google Scholar 

  11. Papa, R. et al. Multi-allelic major effect genes interact with minor effect QTLs to control adaptive color pattern variation inHeliconius erato .PLoS ONE8, e57033 (2013).

    Article CAS PubMed PubMed Central  Google Scholar 

  12. Kronforst, M. R., Kapan, D. D. & Gilbert, L. E. Parallel genetic architecture of parallel adaptive radiations in mimeticHeliconius butterflies.Genetics174, 535–539 (2006).

    Article PubMed PubMed Central  Google Scholar 

  13. Kapan, D. D. et al. Localization of mìllerian mimicry genes on a dense linkage map ofHeliconius erato .Genetics173, 735–757 (2006).

    Article CAS PubMed PubMed Central  Google Scholar 

  14. Reed, R. D. et al.optix drives the repeated convergent evolution of butterfly wing pattern mimicry.Science333, 1137–1141 (2011).

    Article CAS PubMed  Google Scholar 

  15. Martin, A. et al. Diversification of complex butterfly wing patterns by repeated regulatory evolution of a Wnt ligand.Proc. Natl Acad. Sci. USA109, 12632–12637 (2012).

    Article CAS PubMed PubMed Central  Google Scholar 

  16. Nadeau, N. et al. The genecortex controls mimicry and crypsis in butterflies and moths.Nature534, 106–110 (2016).

    Article CAS PubMed PubMed Central  Google Scholar 

  17. Martin, A. et al. Multiple recent co-options ofOptix associated with novel traits in adaptive butterfly wing radiations.EvoDevo5, 7 (2014).

    Article PubMed PubMed Central  Google Scholar 

  18. Carroll, S. B. Evo-Devo and an expanding evolutionary synthesis: a genetic theory of morphological evolution.Cell134, 25–36 (2008).

    Article CAS PubMed  Google Scholar 

  19. Gallant, J. R. et al. Ancient homology underlies adaptive mimetic diversity across butterflies.Nat. Commun.5, 1–10 (2014).

    Article  Google Scholar 

  20. Van’t Hof, A. E. The industrial melanism mutation in British peppered moths is a transposable element.Nature534, 102–105 (2016).

    Article PubMed  Google Scholar 

  21. Rosser, N., Dasmahapatra, K. K. & Mallet, J. StableHeliconius butterfly hybrid zones are correlated with a local rainfall peak at the edge of the Amazon basin.Evolution68, 3470–3484 (2014).

    Article PubMed  Google Scholar 

  22. Supple, M., Papa, R., Hines, H. M., McMillan, W. O. & Counterman, B. A. Divergence with gene flow across a speciation continuum ofHeliconius butterflies.BMC Evol. Biol.15, 204 (2015).

    Article PubMed PubMed Central  Google Scholar 

  23. Hines, H. M. et al. Wing patterning gene redefines the mimetic history ofHeliconius butterflies.Proc. Natl Acad. Sci. USA108, 19666–19671 (2011).

    Article CAS PubMed PubMed Central  Google Scholar 

  24. Mallet, J. & Barton, N. H. Strong natural selection in a warning-color hybrid zone.Evolution43, 421–431 (1989).

    Article PubMed  Google Scholar 

  25. Kapan, D. D. Three-butterfly system provides a field test of mìllerian mimicry.Nature409, 18–20 (2001).

    Article  Google Scholar 

  26. Supple, M. A et al. Genomic architecture of adaptive color pattern divergence and convergence inHeliconius butterflies.Genome Res.23, 1248–1257 (2013).

    Article CAS PubMed PubMed Central  Google Scholar 

  27. Martin, A. et al. Diversification of complex butter flywing patterns by repeated regulatory evolution of a Wnt ligand.Proc. Natl Acad. Sci. USA109, 12632–12637 (2012).

    Article CAS PubMed PubMed Central  Google Scholar 

  28. Martin, S. H. & Van Belleghem, S. M. Exploring evolutionary relationships across the genome using topology weighting. Preprint atbioRxivhttp://dx.doi.org/10.1101/069112 (2016).

  29. Nadeau, N. J. et al. Population genomics of parallel hybrid zones in the mimetic butterflies,H. melpomene andH. erato .Genome Res.24, 1316–1333 (2014).

    Article CAS PubMed PubMed Central  Google Scholar 

  30. Danielsen, E. T. et al. Transcriptional control of steroid biosynthesis genes in theDrosophila prothoracic gland byVentral veins lacking andKnirps .PLoS Genet.10, e1004343 (2014).

    Article PubMed PubMed Central  Google Scholar 

  31. De Celis, J. F., Llimargas, M. & Casanova, J.Ventral veinless, the gene encoding the Cf1a transcription factor, links positional information and cell differentiation during embryonic and imaginal development inDrosophila melanogaster .Development121, 3405–3416 (1995).

    CAS PubMed  Google Scholar 

  32. Meier, S., Sprecher, S. G., Reichert, H. & Hirth, F.Ventral veins lacking is required for specification of the tritocerebrum in embryonic brain development ofDrosophila .Mech. Dev.123, 76–83 (2006).

    Article CAS PubMed  Google Scholar 

  33. Jivan, A ., Earnest, S., Juang, Y.-C. & Cobb, M. H. Radial spoke protein 3 is a mammalian protein kinase A-anchoring protein that binds ERK1/2.J. Biol. Chem.284, 29437–29445 (2009).

    Article CAS PubMed PubMed Central  Google Scholar 

  34. Jiggins, C. D. & Mcmillan, W. O. The genetic basis of an adaptive radiation: warning colour in twoHeliconius species.Proc. R. Soc. B264, 1167–1175 (1997).

    Article PubMed Central  Google Scholar 

  35. Baxter, S. W., Johnston, S. E. & Jiggins, C. D. Butterfly speciation and the distribution of gene effect sizes fixed during adaptation. Heredity102, 57–65 (2009).

    Article CAS PubMed  Google Scholar 

  36. Huber, B. et al. Conservatism and novelty in the genetic architecture of adaptation inHeliconius butterflies.Heredity114, 515–524 (2015).

    Article CAS PubMed PubMed Central  Google Scholar 

  37. Wallbank, R. W. R. et al. Evolutionary novelty in a butterfly wing pattern through enhancer shuffling.PLoS Biol.14, e1002353 (2016).

    Article PubMed PubMed Central  Google Scholar 

  38. Maroja, L. S., Alschuler, R., Mcmillan, W. O. & Jiggins, C. D. Partial complementarity of the mimetic yellow bar phenotype inHeliconius butterflies.PLoS ONE7, e48627 (2012).

    Article CAS PubMed PubMed Central  Google Scholar 

  39. Sheppard, P. M., Turner, J. R. G., Brown, K. S., Benson, W. W. & Singer, M. C. Genetics and the evolution of Muellerian mimicry inHeliconius butterflies.Phil. Trans. R. Soc. B Biol. Sci.308, 433–610 (1985).

    Article  Google Scholar 

  40. Mallet, J. The genetics of warning colour in Peruvian hybrid zones ofHeliconius erato andH. melpomene .Proc. R. Soc. B236, 163–185 (1989).

    Article  Google Scholar 

  41. Joron, M. et al. Chromosomal rearrangements maintain a polymorphic supergene controlling butterfly mimicry.Nature477, 203–206 (2011).

    Article CAS PubMed PubMed Central  Google Scholar 

  42. Kronforst, M. R. & Papa, R. The functional basis of wing patterning inHeliconius butterflies: The molecules behind mimicry.Genetics200, 1–19 (2015).

    Article CAS PubMed PubMed Central  Google Scholar 

  43. Lewis, J. J. et al. ChIP-Seq-annotatedHeliconius erato genome highlights patterns of cis-regulatory evolution in Lepidoptera.Cell Rep.16, 2855–2863 (2016).

    Article CAS PubMed  Google Scholar 

  44. Martin, A. & Reed, R. D. Wnt signaling underlies evolution and development of the butterfly wing pattern symmetry systems.Dev. Biol.395, 367–378 (2014).

    Article CAS PubMed  Google Scholar 

  45. Gnerre, S. et al. High-quality draft assemblies of mammalian genomes from massively parallel sequence data.Proc. Natl Acad. Sci. USA108, 1513–1518 (2011).

    Article CAS PubMed  Google Scholar 

  46. Greenfield, P., Duesing, K., Papanicolaou, A. & Bauer, D. C. Sequence analysis Blue: correcting sequencing errors using consensus and context.Bioinformatics30, 2723–2732 (2014).

    Article CAS PubMed  Google Scholar 

  47. Salmela, L. & Rivals, E. Sequence analysis LoRDEC: accurate and efficient long read error correction.Bioinformatics30, 3506–3514 (2014).

    Article CAS PubMed PubMed Central  Google Scholar 

  48. Kurtz, S. et al. Versatile and open software for comparing large genomes.Genome Biol.5, R12 (2004).

    Article PubMed PubMed Central  Google Scholar 

  49. English, A. C. et al. Mind the gap: upgrading genomes with Pacific Biosciences RS long-read sequencing technology.PLoS ONE7, e47768 (2012).

    Article CAS PubMed PubMed Central  Google Scholar 

  50. Li, H. et al. The Sequence Alignment/Map format and SAMtools.Bioinformatics25, 2078–2079 (2009).

    Article PubMed PubMed Central  Google Scholar 

  51. Rastas, P., Paulin, L., Hanski, I. & Lehtonen, R. Lep-MAP: fast and accurate linkage map construction for large SNP datasets.Bioinformatics29, 3128–3134 (2013).

    Article CAS PubMed PubMed Central  Google Scholar 

  52. Rastas, P., Calboli, F. C. F., Guo, B., Shikano, T. & Merilä, J. Construction of ultradense linkage maps with Lep-MAP2: Stickleback F2 recombinant crosses as an example.Genome Biol. Evol.8, 78–93 (2015).

    Article PubMed PubMed Central  Google Scholar 

  53. Weisenfeld, N. I. et al. Comprehensive variation discovery in single human genomes.Nat. Genet.46, 1350–1355 (2014).

    Article CAS PubMed PubMed Central  Google Scholar 

  54. Love, R. R., Weisenfeld, N. I., Jaffe, D. B., Besansky, N. J. & Neafsey, D. E. Evaluation of DISCOVARde novo using a mosquito sample for cost-effective short-read genome assembly.BMC Genomics17, 187 (2016).

    Article PubMed PubMed Central  Google Scholar 

  55. Li, H. Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. Preprint athttps://arxiv.org/abs/1303.3997 (2013).

  56. Smith, T. F. & Waterman, M. S. Identification of common molecular subsequences.J. Mol. Biol.147, 195–197 (1981).

    Article CAS PubMed  Google Scholar 

  57. Simão, F. A., Waterhouse, R. M., Ioannidis, P. & Kriventseva, E. V. BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs.Bioinformatics31, 3210–3212 (2015).

    Article PubMed  Google Scholar 

  58. Haas, B. J. et al.De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis.Nat. Protoc.8, 1494–1512 (2013).

    Article CAS PubMed  Google Scholar 

  59. Chevreux, B. et al. Using the miraEST assembler for reliable and automated mRNA transcript assembly and SNP detection in sequenced ESTs.Genome Res.14, 1147–1159 (2004).

    Article CAS PubMed PubMed Central  Google Scholar 

  60. Haas, B. J. et al. Improving theArabidopsis genome annotation using maximal transcript alignment assemblies.Nucleic Acids Res.31, 5654–5666 (2003).

    Article CAS PubMed PubMed Central  Google Scholar 

  61. Wu, T. D. & Nacu, S. Fast and SNP-tolerant detection of complex variants and splicing in short reads.Bioinformatics26, 873–881 (2010).

    Article CAS PubMed PubMed Central  Google Scholar 

  62. Benson, G. Tandem repeats finder: a program to analyze DNA sequences.Nucleic Acids Res.27, 573–580 (1999).

    Article CAS PubMed PubMed Central  Google Scholar 

  63. Smit, A. F. A., Hubley, R. & Green, P. RepeatMasker (2014);http://www.repeatmasker.org/

  64. Price, A. L., Jones, N. C. & Pevzner, P. A.De novo identification of repeat families in large genomes.Bioinformatics21, i351–358 (2005).

    Article CAS PubMed  Google Scholar 

  65. Jurka, J. et al. Repbase Update, a database of eukaryotic repetitive elements.Cytogenet. Genome Res.110, 462–467 (2005).

    Article CAS PubMed  Google Scholar 

  66. Lowe, T. M. & Eddy, S. R. tRNAscan-SE: a program for improved detection of transfer RNA genes in genomic sequence.Nucleic Acids Res.25, 955–964 (1997).

    Article CAS PubMed PubMed Central  Google Scholar 

  67. Laslett, D. & Canback, B. ARAGORN, a program to detect tRNA genes and tmRNA genes in nucleotide sequences.Nucleic Acids Res.32, 11–16 (2004).

    Article CAS PubMed PubMed Central  Google Scholar 

  68. Lomsadze, A., Burns, P. D. & Borodovsky, M. Integration of mapped RNA-Seq reads into automatic training of eukaryotic gene finding algorithm.Nucleic Acids Res.42, e119 (2014).

    Article PubMed PubMed Central  Google Scholar 

  69. Stanke, M., Schöffmann, O., Morgenstern, B. & Waack, S. Gene prediction in eukaryotes with a generalized hidden Markov model that uses hints from external sources.BMC Bioinformatics11, 1–11 (2006).

    Google Scholar 

  70. Remmert, M., Biegert, A., Hauser, A. & Johannes, S. HHblits: Lightning-fast iterative protein sequence searching by HMM-HMM alignment.Nat. Methods9, 173–175 (2012).

    Article CAS  Google Scholar 

  71. Davey, J. W. et al. Major improvements to theHeliconius melpomene genome assembly used to confirm 10 chromosome fusion events in 6 million years of butterfly evolution.G36, 695–708 (2016).

    Article CAS PubMed PubMed Central  Google Scholar 

  72. Haas, B. J. et al. Automated eukaryotic gene structure annotation using EVidenceModeler and the Program to Assemble Spliced Alignments.Genome Biol.9, R7 (2008).

    Article PubMed PubMed Central  Google Scholar 

  73. Li, H. & Durbin, R. Fast and accurate long-read alignment with Burrows-Wheeler transform.Bioinformatics26, 589–595 (2010).

    Article PubMed PubMed Central  Google Scholar 

  74. Li, H. et al. The Sequence Alignment/Map format and SAMtools.Bioinformatics25, 2078–2079 (2009).

    Article PubMed PubMed Central  Google Scholar 

  75. Van der Auwera, G. a. et al. From FastQ data to high-confidence variant calls: the Genome Analysis Toolkit best practices pipeline.Curr. Protoc. Bioinform.11.10, 1–33 (2013).

    Google Scholar 

  76. Hudson, R. R., Slatkin, M. & Maddison, W. P. Estimation of levels of gene flow from DNA sequence data.Genetics132, 583–589 (1992).

    CAS PubMed PubMed Central  Google Scholar 

  77. Nei, M. & Jin, L. Variances of the average numbers of nucleotide substitutions within and between populations.Mol. Biol. Evol.6, 290–300 (1989).

    CAS PubMed  Google Scholar 

  78. De Mita, S. & Siol, M. EggLib: processing, analysis and simulation tools for population genetics and genomics.BMC Genet.13, 27 (2012).

    Article PubMed PubMed Central  Google Scholar 

  79. Nadeau, N. J. et al. Genomic islands of divergence in hybridizingHeliconius butterflies identified by large-scale targeted sequencing.Phil. Trans. R. Soc. Lond. B. Biol. Sci.367, 343–353 (2012).

    Article CAS  Google Scholar 

  80. Price, M. N., Dehal, P. S. & Arkin, A. P. FastTree 2 – Approximately maximum-likelihood trees for large alignments.PLoS ONE5, e9490 (2010).

    Article PubMed PubMed Central  Google Scholar 

  81. Stamatakis, A. RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies.Bioinformatics30, 1312–1313 (2014).

    Article CAS PubMed PubMed Central  Google Scholar 

  82. Boftelli, D. et al. Phylogenetic shadowing of primate sequences to find functional regions of the human genome.Science299, 1391–1394 (2003).

    Article  Google Scholar 

Download references

Acknowledgements

We thank A. Tapia for maintaining theH. erato genome line and for generating our mapping family, and M. Vargas and C. Rosales for Illumina library preparation. We acknowledge the University of Puerto Rico, the Puerto Rico INBRE grant P20 GM103475 from the National Institute for General Medical Sciences (NIGMS), a component of the National Institutes of Health (NIH); CNRS Nouraugues and CEBA awards (B.A.C.); National Science Foundation awards DEB-1257839 (B.A.C.), DEB-1257689 (W.O.M.), DEB-1027019 (W.O.M.); awards 1010094 and 1002410 from the Experimental Program to Stimulate Competitive Research (EPSCoR) program of the National Science Foundation (NSF) for computational resources; and the Smithsonian Institution. This research was supported in part by Lilly Endowment, Inc., through its support for the Indiana University Pervasive Technology Institute, and in part by the Indiana METACyt Initiative. The Indiana METACyt Initiative at IU is also supported in part by Lilly Endowment, Inc.

Author information

Author notes
  1. Steven M. Van Belleghem and Pasi Rastas: These authors contributed equally to this work.

  2. Brian A. Counterman, W. Owen McMillan and Riccardo Papa: These authors jointly supervised this work.

Authors and Affiliations

  1. Department of Biology, Center for Applied Tropical Ecology and Conservation, University of Puerto Rico, Rio Piedras, Puerto Rico

    Steven M. Van Belleghem, Pasi Rastas, Mayte Ruiz, Brian A. Counterman, W. Owen McMillan & Riccardo Papa

  2. Smithsonian Tropical Research Institute, Apartado, 0843-03092, Panamá, Panama

    Steven M. Van Belleghem, Carlos F. Arias, Megan A. Supple & W. Owen McMillan

  3. Department of Zoology, University of Cambridge, Cambridge, CB2 3EJ, UK

    Pasi Rastas, Simon H. Martin, Joseph J. Hanly & Chris D. Jiggins

  4. Hawkesbury Institute for the Environment, Western Sydney University, Richmond, New South Wales 2753, Australia

    Alexie Papanicolaou

  5. Biology Program, Faculty of Natural Sciences and Mathematics, Universidad del Rosario, Carrera. 24 No. 63C-69, Bogota, 111221, DC, Colombia

    Carlos F. Arias, Camilo Salazar & Mauricio Linares

  6. Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, Massachusetts, USA

    James Mallet

  7. Department of Ecology and Evolutionary Biology, Cornell University, 215 Tower Road, Ithaca, 14853-7202, New York, USA

    James J. Lewis

  8. Department of Biology, Pennsylvania State University, University Park, Pennsylvania, 16802, USA

    Heather M. Hines & Gilson R. P. Moreira

  9. Departamento de Zoologia, PPG Biologia Animal, Universidade Federal do Rio Grande do Sul, Av. Bento Gonçalves, 9500, Bloco IV, Prédio 43435, Porto Alegre, RS 91501-970, Brazil

    Brian A. Counterman

  10. Department of Biological Sciences, Mississippi State University, 295 Lee Boulevard, 39762, Mississippi, USA

    Riccardo Papa

Authors
  1. Steven M. Van Belleghem

    You can also search for this author inPubMed Google Scholar

  2. Pasi Rastas

    You can also search for this author inPubMed Google Scholar

  3. Alexie Papanicolaou

    You can also search for this author inPubMed Google Scholar

  4. Simon H. Martin

    You can also search for this author inPubMed Google Scholar

  5. Carlos F. Arias

    You can also search for this author inPubMed Google Scholar

  6. Megan A. Supple

    You can also search for this author inPubMed Google Scholar

  7. Joseph J. Hanly

    You can also search for this author inPubMed Google Scholar

  8. James Mallet

    You can also search for this author inPubMed Google Scholar

  9. James J. Lewis

    You can also search for this author inPubMed Google Scholar

  10. Heather M. Hines

    You can also search for this author inPubMed Google Scholar

  11. Mayte Ruiz

    You can also search for this author inPubMed Google Scholar

  12. Camilo Salazar

    You can also search for this author inPubMed Google Scholar

  13. Mauricio Linares

    You can also search for this author inPubMed Google Scholar

  14. Gilson R. P. Moreira

    You can also search for this author inPubMed Google Scholar

  15. Chris D. Jiggins

    You can also search for this author inPubMed Google Scholar

  16. Brian A. Counterman

    You can also search for this author inPubMed Google Scholar

  17. W. Owen McMillan

    You can also search for this author inPubMed Google Scholar

  18. Riccardo Papa

    You can also search for this author inPubMed Google Scholar

Contributions

S.M.V.B., B.A.C., W.O.M. and R.P. designed the study and wrote the paper. P.R., A.P. and J.J.M. conducted genome assembly. P.R. conducted linkage map and genome quality assessment. A.P. conducted genome annotation. S.M.V.B. conducted population genomic, phylogenetic and comparative genomic analyses. M.R, M.A.S, H.H. and J.J.H. conducted comparative genomic analyses. S.H.M. contributed scripts for Twisst analyses. B.A.C., W.O.M., R.P., H.H., C.D.J., J.M., M.L., C.S., C.F.A. and G.M. collected samples for sequencing.

Corresponding author

Correspondence toSteven M. Van Belleghem.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary information

Supplementary Figures 1–35; Supplementary Tables 1–13 (PDF 5140 kb)

Rights and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Van Belleghem, S., Rastas, P., Papanicolaou, A.et al. Complex modular architecture around a simple toolkit of wing pattern genes.Nat Ecol Evol1, 0052 (2017). https://doi.org/10.1038/s41559-016-0052

Download citation

Access through your institution
Buy or subscribe

Associated content

Collection

On Growth and Form Centenary

Advertisement

Search

Advanced search

Quick links

Nature Briefing

Sign up for theNature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox.Sign up for Nature Briefing

[8]ページ先頭

©2009-2025 Movatter.jp