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Complex modular architecture around a simple toolkit of wing pattern genes

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

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Abstract

Identifying the genomic changes that control morphological variation and understanding how they generate diversity is a major goal of evolutionary biology. In Heliconius butterflies, a small number of genes control the development of diverse wing colour patterns. Here, we used full-genome sequencing of individuals across the Heliconius 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.

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Figure 1: Geographical distribution, phylogeny and colour pattern diversity of the Heliconius erato adaptive radiation.
Figure 2: Genomic divergence across the Heliconius 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 the Heliconius erato radiation.

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Acknowledgements

We thank A. Tapia for maintaining the H. 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.

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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

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  1. Steven M. Van Belleghem
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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.

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Correspondence to Steven M. Van Belleghem.

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Van Belleghem, S., Rastas, P., Papanicolaou, A. et al. Complex modular architecture around a simple toolkit of wing pattern genes. Nat Ecol Evol 1, 0052 (2017). https://doi.org/10.1038/s41559-016-0052

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