Genomic architecture and introgression shape a butterfly radiation

Genomic architecture and introgression shape a butterfly radiation

2019-11-01 04:05:44

The role of hybridization in evolution and species radiations has long been debated. In Heliconius butterflies, introgression was a major factor in their radiation, and the genetic variation it imparted into species is variable across the genome. Edelman et al. developed a new sequencing strategy and produced 20 Heliconius genomes (see the Perspective by Rieseberg). They also developed a means by which to identify genetic variation that originates from incomplete lineage sorting versus hybridization. Applying this model to their newly developed genomes, they investigated the evolutionary history of the genus and, in particular, the impact of introgression. Science , this issue p. [594][1]; see also p. [570][2] We used 20 de novo genome assemblies to probe the speciation history and architecture of gene flow in rapidly radiating Heliconius butterflies. Our tests to distinguish incomplete lineage sorting from introgression indicate that gene flow has obscured several ancient phylogenetic relationships in this group over large swathes of the genome. Introgressed loci are underrepresented in low-recombination and gene-rich regions, consistent with the purging of foreign alleles more tightly linked to incompatibility loci. Here, we identify a hitherto unknown inversion that traps a color pattern switch locus. We infer that this inversion was transferred between lineages by introgression and is convergent with a similar rearrangement in another part of the genus. These multiple de novo genome sequences enable improved understanding of the importance of introgression and selective processes in adaptive radiation. [1]: /lookup/doi/10.1126/science.aaw2090 [2]: /lookup/doi/10.1126/science.aaz1576

Research Article

  1. Nathaniel B. Edelman1,*,
  2. Paul B. Frandsen2,3,
  3. Michael Miyagi1,
  4. Bernardo Clavijo4,
  5. John Davey5,20,
  6. Rebecca B. Dikow3,
  7. Gonzalo García-Accinelli4,
  8. Steven M. Van Belleghem6,
  9. Nick Patterson7,8,
  10. Daniel E. Neafsey8,9,
  11. Richard Challis10,
  12. Sujai Kumar11,
  13. Gilson R. P. Moreira12,
  14. Camilo Salazar13,
  15. Mathieu Chouteau14,
  16. Brian A. Counterman15,
  17. Riccardo Papa6,16,
  18. Mark Blaxter10,
  19. Robert D. Reed17,
  20. Kanchon K. Dasmahapatra5,
  21. Marcus Kronforst18,
  22. Mathieu Joron19,
  23. Chris D. Jiggins20,
  24. W. Owen McMillan21,
  25. Federica Di Palma4,
  26. Andrew J. Blumberg22,
  27. John Wakeley1,
  28. David Jaffe8,23,
  29. James Mallet1,*
  1. 1Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA.
  2. 2Department of Plant and Wildlife Sciences, Brigham Young University, Provo, UT 84602, USA.
  3. 3Data Science Lab, Office of the Chief Information Officer, Smithsonian Institution, Washington, DC 20560, USA.
  4. 4Earlham Institute, Norwich Research Park, Norwich NR4 7UZ, UK.
  5. 5Bioscience Technology Facility, Department of Biology, University of York, York YO10 5DD, UK.
  6. 6Department of Biology, University of Puerto Rico, Río Piedras Campus, San Juan, PR 00931-3360, Puerto Rico.
  7. 7Department of Human Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA.
  8. 8Broad Institute of MIT and Harvard, Cambridge, MA, 02142 USA.
  9. 9Harvard TH Chan School of Public Health, Boston, MA 02115, USA.
  10. 10Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge CB10 1SA, UK.
  11. 11Institute of Evolutionary Biology, University of Edinburgh, Edinburgh EH9 3JT, UK.
  12. 12Departamento de Zoologia, Universidade Federal do Rio Grande do Sul, Porto Alegre, 91501-970 Brasil.
  13. 13Biology Program, Faculty of Natural Sciences and Mathematics, Universidad del Rosario, Carrera 24, No. 63C-69, Bogotá D.C. 111221, Colombia.
  14. 14Laboratoire Ecologie, Evolution, Interactions des Systèmes Amazoniens (LEEISA), USR 3456, Université De Guyane, CNRS Guyane, 275 Route de Montabo, 97334 Cayenne, French Guiana.
  15. 15Department of Biological Sciences, Mississippi State University, Starkville, MS 39762, USA.
  16. 16Molecular Sciences and Research Center, University of Puerto Rico, San Juan, PR 00931-3360, Puerto Rico.
  17. 17Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, NY 14853, USA.
  18. 18Department of Ecology and Evolution, University of Chicago, Chicago, IL 60637, USA.
  19. 19CEFE, CNRS, Université de Montpellier, Université Paul Valéry Montpellier 3, EPHE, IRD, 34090 Montpellier, France.
  20. 20Department of Zoology, University of Cambridge, Cambridge CB2 3EJ, UK.
  21. 21Smithsonian Tropical Research Institute, Apartado 0843-03092 Panamá, Panama.
  22. 22Department of Mathematics, University of Texas, Austin, TX 78712, USA.
  23. 2310x Genomics, Pleasanton, CA 94566, USA.
  1. ↵*Corresponding author. Email: nedelman{at}g.harvard.edu (N.B.E.); jmallet{at}oeb.harvard.edu (J.M.)

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Science  01 Nov 2019:
Vol. 366, Issue 6465, pp. 594-599
DOI: 10.1126/science.aaw2090

Following gene flow in butterfly genomes

The role of hybridization in evolution and species radiations has long been debated. In Heliconius butterflies, introgression was a major factor in their radiation, and the genetic variation it imparted into species is variable across the genome. Edelman et al. developed a new sequencing strategy and produced 20 Heliconius genomes (see the Perspective by Rieseberg). They also developed a means by which to identify genetic variation that originates from incomplete lineage sorting versus hybridization. Applying this model to their newly developed genomes, they investigated the evolutionary history of the genus and, in particular, the impact of introgression.

Science, this issue p. 594; see also p. 570

Abstract

We used 20 de novo genome assemblies to probe the speciation history and architecture of gene flow in rapidly radiating Heliconius butterflies. Our tests to distinguish incomplete lineage sorting from introgression indicate that gene flow has obscured several ancient phylogenetic relationships in this group over large swathes of the genome. Introgressed loci are underrepresented in low-recombination and gene-rich regions, consistent with the purging of foreign alleles more tightly linked to incompatibility loci. Here, we identify a hitherto unknown inversion that traps a color pattern switch locus. We infer that this inversion was transferred between lineages by introgression and is convergent with a similar rearrangement in another part of the genus. These multiple de novo genome sequences enable improved understanding of the importance of introgression and selective processes in adaptive radiation.

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Science: 366 (6465)