Complex modular architecture around a simple toolkit of wing pattern genes
Steven M. Van Belleghem, Pasi Rastas, Alexie Papanicolaou, Simon H. Martin, Carlos F. Arias, Megan A. Supple, Joseph J. Hanly, James Mallet, James J. Lewis, Heather M. Hines, Mayte Ruiz, Camilo Salazar, Mauricio Linares, Gilson R. P. Moreira, Chris D. Jiggins, Brian A. Counterman, W. Owen McMillan & Riccardo Papa
Nature Ecology & Evolution 1, Article number: 0052 (2017)
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Comparative genomics Evolutionary genetics Mimicry
Received: 22 June 2016 Accepted: 13 December 2016
Published online: 30 January 2017
Figure 1: Geographical distribution, phylogeny and colour pattern diversity
of the Heliconius erato adaptive radiation.
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.Recent adaptive radiations, such as the Heliconius butterflies 1 , Galápagos finches 2 and African cichlids 3 , offer insight into evolutionary and ecological forces that underlie diversification. Typically, ecological opportunities allow natural and sexual selection to drive adaptive change and speciation. At a genetic level, recruitment from ancient polymorphism, introgression of adaptive variants between populations and de novo mutation are important sources of variation. However, the genetic architecture of the traits under natural and sexual selection that facilitates rapid diversification remains largely unexplored.In this study, we sequenced the genome of the Neotropical butterfly Heliconius erato and used re-sequence data from 116 additional individuals to dissect the architecture of genomic variation associated with their vividly coloured wing patterns. With over 400 different wing colour forms among 46 described species 4 , Heliconius represents one of the most visually diverse radiations in the animal kingdom and an excellent system for establishing a broad and integrative view of morphological diversification. The evolution of scale cells and the spatial coordinate system that controls wing pigmentation is a key innovation of the Lepidoptera. Wing patterns are often under strong natural and sexual selection, and these forces probably shape much of the pattern diversity we see among the more than 160,000 butterfly and moth species 5 .In Heliconius, conspicuous wing patterns are important for signalling toxicity to potential predators 6 and play a role in mate selection 7 . Natural selection favors Mìllerian mimicry among toxic butterflies, resulting in convergence between co-occurring species, as well as geographic divergence between populations of the same species 8 . Among Heliconius butterflies, the genetic basis of this wing diversity has been studied for nearly 60 years and more than 30 Mendelian loci have been described 9 . Over the past decade, however, genetic research has shown that most of the complexity of colour variation across Heliconius is actually controlled by relatively few genes acting broadly across the fore- and hindwing 10,11,12,13,14,15,16 . These genes include the transcription factor optix 14,17 , the signalling ligand wntA 15 and the cell cycle regulator cortex 16 . Hence, these studies have revealed that a limited set of ‘toolkit’ 18 genes has been repeatedly used for both highly divergent and convergent phenotypes in Heliconius, as well as other butterfly and moth species 16,19,20 . However, the key to wing pattern variation in Heliconius is not within the genes themselves, which are strongly conserved at the amino acid level, but at nearby non-coding regions that control expression during wing development 14,15,16 .Here, we sequenced the genomes of 15 distinctly coloured H. erato races and 8 closely related species to fully describe the regulatory architecture driving adaptive evolution of the major genes acting in Heliconius wing patterning (Fig. 1). Our genomic survey included samples obtained near seven transition zones of hybridizing H. erato races with divergent wing patterns (Fig. 2a). In these hybrid zones, the high rate of genetic admixture allows for detailed genotype by phenotype (G × P) association mapping to identify discrete genomic intervals associated with colour and pattern variation on Heliconius wings 21,22 . We then further investigated these intervals with a novel phylogenetic method for identifying conserved non-coding regions in closely related non-hybridizing races and species. This combined strategy of association mapping and phylogenetic inference resulted in a distinct set of narrow genomic intervals that corresponded to loci described in early crossing experiments 9 (Supplementary Table 1). All the intervals fell within non-coding regions adjacent to colour pattern genes that affect forewing band shape (wntA; Fig. 3), red pigmentation (optix; Fig. 4) and a yellow hindwing bar (cortex; Fig. 5). Our results underscore a highly modular regulatory architecture that provides a flexible mechanism for rapid morphological change (Fig. 6).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.
