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Evolutionary dynamics of genome size and content during the adaptive radiation of Heliconiini butterflies.

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Cicconardi, Francesco  ORCID logo
Milanetti, Edoardo 
Pinheiro de Castro, Erika C  ORCID logo
Van Belleghem, Steven M  ORCID logo


Heliconius butterflies, a speciose genus of Müllerian mimics, represent a classic example of an adaptive radiation that includes a range of derived dietary, life history, physiological and neural traits. However, key lineages within the genus, and across the broader Heliconiini tribe, lack genomic resources, limiting our understanding of how adaptive and neutral processes shaped genome evolution during their radiation. Here, we generate highly contiguous genome assemblies for nine Heliconiini, 29 additional reference-assembled genomes, and improve 10 existing assemblies. Altogether, we provide a dataset of annotated genomes for a total of 63 species, including 58 species within the Heliconiini tribe. We use this extensive dataset to generate a robust and dated heliconiine phylogeny, describe major patterns of introgression, explore the evolution of genome architecture, and the genomic basis of key innovations in this enigmatic group, including an assessment of the evolution of putative regulatory regions at the Heliconius stem. Our work illustrates how the increased resolution provided by such dense genomic sampling improves our power to generate and test gene-phenotype hypotheses, and precisely characterize how genomes evolve.


Acknowledgements: This article would not be possible without the great support of the great Heliconius community. We are also grateful to the environmental ministries in Peru and Panama for permission to collect and export samples and the STRI community for assistance in the field. F.C. would like to thank Ronald Mori Pezo for his great help in collecting H. aoede and Podotricha telesiphe; Angel Corpuz for various informatics support including a great patience; Ian Fiddes, Mark Diekhans, Glenn Hichey and Marina Haukness for their great support for Cactus and CAT; Gregg Thomas and Tim Sackton for they help with PhyloACC-ST, preparation and analysis; Federica Cattonaro, Davide Scaglione and Simone Scalabrin from IGA (Udine, Italy) for their fruitful discussion on the best sequencing strategy to perfom. F.C. and S.H.M. are grateful to the High-Performance Computing team at the Advanced Computing Research Center, University of Bristol for support. We also thank the University of Puerto Rico Sequencing and Genomics Facility INBRE Grant P20 GM103475 from NIGMS, a component of the NIH, and the Bioinformatics Research Core of the INBRE. Its contents are solely the responsibility of the authors and do not necessarily represent the official view of NIGMS or NIH. This work was primarily supported by NERC IRF (NE/N014936/1) and ERC Starter Grant (758508) to S.H.M., which supported the work of F.C. Additional funding came from NSF EPSCoR RII Track-2 FEC (OIA 1736026) (R.P.), NSF IOS 1656389 (R.P.), and a Puerto Rico Science, Technology & Research Trust catalyzer award (2020-00142) (R.P.).

Funder: Royal Society URF\R1\180682


Animals, Genome Size, Butterflies, Genomics, Phenotype, Phylogeny

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Nat Commun

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Springer Science and Business Media LLC
NERC Environmental Bioinformatics Centre (NEBC) (NE/N014936/1)