1. Developmental Biology
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Cortex cis-regulatory switches establish scale colour identity and pattern diversity in Heliconius

  1. Luca Livraghi  Is a corresponding author
  2. Joseph J Hanly
  3. Steven M Van Bellghem
  4. Gabriela Montejo-Kovacevich
  5. Eva SM van der Heijden
  6. Ling Sheng Loh
  7. Anna Ren
  8. Ian A Warren
  9. James J Lewis
  10. Carolina Concha
  11. Laura Hebberecht
  12. Charlotte J Wright
  13. Jonah M Walker
  14. Jessica Foley
  15. Zachary H Goldberg
  16. Henry Arenas-Castro
  17. Camilo Salazar
  18. Michael W Perry
  19. Riccardo Papa
  20. Arnaud Martin
  21. W Owen McMillan
  22. Chris D Jiggins
  1. Department of Zoology, University of Cambridge, Downing St., United Kingdom
  2. Smithsonian Tropical Research Institute, Panama
  3. The George Washington University Department of Biological Sciences, Science and Engineering Hall, United States
  4. Department of Biology, Centre for Applied Tropical Ecology and Conservation, University of Puerto Rico, Puerto Rico
  5. Baker Institute for Animal Health, College of Veterinary Medicine, Cornell University, United States
  6. Cell & Developmental Biology, Division of Biological Sciences, UC San Diego, United States
  7. Biology Program, Faculty of Natural Sciences, Universidad del Rosario, Colombia
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Cite this article as: eLife 2021;10:e68549 doi: 10.7554/eLife.68549

Abstract

In Heliconius butterflies, wing colour pattern diversity and scale types are controlled by a few genes of large effect that regulate colour pattern switches between morphs and species across a large mimetic radiation. One of these genes, cortex, has been repeatedly associated with colour pattern evolution in butterflies. Here we carried out CRISPR knockouts in multiple Heliconius species and show that cortex is a major determinant of scale cell identity. Chromatin accessibility profiling and introgression scans identified cis-regulatory regions associated with discrete phenotypic switches. CRISPR perturbation of these regions in black hindwing genotypes recreated a yellow bar, revealing their spatially limited activity. In the H. melpomene/timareta lineage, the candidate CRE from yellow-barred phenotype morphs is interrupted by a transposable element, suggesting that cis-regulatory structural variation underlies these mimetic adaptations. Our work shows that cortex functionally controls scale colour fate and that its cis-regulatory regions control a phenotypic switch in a modular and pattern-specific fashion.

eLife digest

Heliconius butterflies have bright patterns on their wings that tell potential predators that they are toxic. As a result, predators learn to avoid eating them. Over time, unrelated species of butterflies have evolved similar patterns to avoid predation through a process known as Müllerian mimicry. Worldwide, there are over 180,000 species of butterflies and moths, most of which have different wing patterns. How do genes create this pattern diversity? And do butterflies use similar genes to create similar wing patterns?

One of the genes involved in creating wing patterns is called cortex. This gene has a large region of DNA around it that does not code for proteins, but instead, controls whether cortex is on or off in different parts of the wing. Changes in this non-coding region can act like switches, turning regions of the wing into different colours and creating complex patterns, but it is unclear how these switches have evolved.

Butterfly wings get their colour from tiny structures called scales, which each have their own unique set of pigments. In Heliconius butterflies, there are three types of scales: yellow/white scales, black scales, and red/orange/brown scales. Livraghi et al. used a DNA editing technique called CRISPR to find out whether the cortex gene affects scale type.

First, Livraghi et al. confirmed that deleting cortex turned black and red scales yellow. Next, they used the same technique to manipulate the non-coding DNA around the cortex gene to see the effect on the wing pattern. This manipulation turned a black-winged butterfly into a butterfly with a yellow wing band, a pattern that occurs naturally in Heliconius butterflies. The next step was to find the mutation responsible for the appearance of yellow wing bands in nature. It turns out that a bit of extra genetic code, derived from so-called ‘jumping genes’, had inserted itself into the non-coding DNA around the cortex gene, ‘flipping’ the switch and leading to the appearance of the yellow scales.

Genetic information contains the instructions to generate shape and form in most organisms. These instructions evolve over millions of years, creating everything from bacteria to blue whales. Butterfly wings are visual evidence of evolution, but the way their genes create new patterns isn't specific to butterflies. Understanding wing patterns can help researchers to learn how genetic switches control diversity across other species too.

Introduction

Butterfly wing pattern diversity provides a window into the ways genetic changes underlie phenotypic variation that is spatially limited to specific parts or regions of the organism (McMillan et al., 2020; Orteu and Jiggins, 2020; Rebeiz et al., 2015). Many of the underlying genetic loci controlling differences in colour patterns have been mapped to homologus ‘hotspots’ across disparate taxa. In some cases, this repeated adaptation has occurred through the alteration of downstream effector genes, such as pigment biosynthetic enzymes with functions clearly related to the trait under selection, for example, the genes tan and ebony that control insect melanin pigmentation (reviewed in Massey and Wittkopp, 2016). In other cases, upstream regulatory genes are important, and these are typically either transcription factors (e.g. optix, MITF, Sox10) or components of signalling pathways such as ligands or receptors (e.g. WntA, MC1R, Agouti). These ‘developmental toolkit genes’ influence pigment cell fate decisions by modulating gene regulatory networks (GRNs) (Kronforst and Papa, 2015; Martin and Courtier-Orgogozo, 2017; Prud'homme et al., 2007), and are commonly characterised by highly conserved functions, with rapid evolutionary change occurring through regulatory fine-tuning of expression patterns. One gene that has been repeatedly implicated in morphological evolution but does not conform to this paradigm is cortex, a gene implicated by mapping approaches in the regulation of adaptive changes in the wing patterning of butterflies and moths.

Cortex is one of four major effect genes that act as switch loci controlling both scale structure and colour patterns in Heliconius butterflies, and has been repeatedly targeted by natural selection to drive differences in pigmentation (Nadeau, 2016; Van Belleghem et al., 2017). Three of the four major effect genes correspond to the prevailing paradigm of highly conserved patterning genes; the signalling ligand WntA (Martin et al., 2012; Mazo-Vargas et al., 2017) and two transcription factors optix (Lewis et al., 2019; Reed et al., 2011; Zhang et al., 2017) and aristaless1 (Westerman et al., 2018). Cortex, on the other hand, is an insect-specific gene showing closest homology to the cdc20/fizzy family of cell cycle regulators (Chu et al., 2001; Nadeau et al., 2016; Pesin and Orr-Weaver, 2007). The lepidopteran orthologue of cortex displays rapid sequence evolution and has acquired novel expression domains that correlate with melanic wing patterns in Heliconius (Nadeau et al., 2016; Saenko et al., 2019). It therefore seems likely that the role of cortex in regulating wing patterns has involved a major shift in function, which sits in contrast to the classic model of regulatory co-option of deeply conserved patterning genes.

The genetic locus containing cortex was originally identified in the genus Heliconius as controlling differences in yellow and white wing patterns in H. melpomene and H. erato (Figure 1a) and the polymorphism in yellow, white, black, and orange elements in H. numata. This was inferred using a combination of association mapping and gene expression data (Joron et al., 2006; Nadeau et al., 2016). The same locus has also been repeatedly implicated in controlling colour pattern variation among divergent Lepidoptera, including the peppered moth Biston betularia and other geometrids, the silkmoth Bombyx mori, and other butterflies such as Junonia coenia, Bicyclus anynana, and Papilio clytia (Beldade et al., 2009; van der Burg et al., 2020; Ito et al., 2016; VanKuren et al., 2019; Van't Hof et al., 2019; Van't Hof et al., 2016). This locus therefore contains one or more genes that have repeatedly been targeted throughout the evolutionary history of the Lepidoptera to generate phenotypic diversity.

Figure 1 with 4 supplements see all
Phenotypic switches of yellow and white colour pattern elements are controlled by homologous loci in Heliconius species.

(a) Homologous loci in both H. erato and H. melpomene are associated with variation in yellow and white patterns between morphs. In H. melpomene, three tightly linked genetic elements located at chromosome 15 have been identified that control variation for the hindwing yellow bar, white margin elements, and forewing band (Yb, Sb, and N, respectively), while in H. erato, variation has been mapped to one element (Cr). The gene cortex is highlighted in red, dome/wash in blue, and dome-trunc in green. Alignments between the two co-mimetic species at the locus is shown (grey lines, 75% alignment identity). Gene models from assemblies of H. melpomene (left) and H. erato (right) are shown for the loci spanning the associated intervals controlling the phenotypic switches highlighted. Horizontal bars indicate exons, vertical bars introns. (b) Focal co-mimetic morphs of H. erato and H. melpomene used in this study, differing in the presence of a hindwing yellow bar, and their ranges across Central America are shown. Yellow: yellow banded morphs, blue: black hindwing morphs, grey: range overlap. Each dot represents a sampled location (data from Rosser et al., 2012). Country borders are indicated by dotted lines.

In Heliconius butterflies, population genomic data suggest that cis-regulatory modules surrounding cortex underlie adaptive variation of yellow and white colour pattern elements (Enciso-Romero et al., 2017; Van Belleghem et al., 2017). These studies predict the existence of modular elements that compartmentalise expression of colour pattern genes across developing wings. However, developmental genes have complex regulatory domains and recent work has suggested that pleiotropy among different enhancers may be more common than is currently appreciated (Lewis et al., 2019; Murugesan et al., 2021; Nagy et al., 2018). Further dissection of the regulatory elements controlling wing pattern variation is thus necessary to assess the relative contribution of pleiotropy versus modularity at colour pattern loci (Lewis and Van Belleghem, 2020).

While fantastically diverse, most of the pattern variation in Heliconius is created by differences in the distribution of just three major scale cell types: Type I (yellow/white), Type II (black), and Type III (red/orange/brown) (Aymone et al., 2013; Gilbert et al., 1987). Each type has a characteristic nanostructure and a fixed complement of pigments. Type I yellow scales contain the ommochrome precursor 3-hydroxykynurenine (3-OHK) (Finkbeiner et al., 2017; Koch, 1993; Reed et al., 2008), whereas Type I white scales lack pigment, and the white colour is the result of the scale cell ultrastructure (i.e. structural white) (Gilbert et al., 1987) (see Figure 9f). Structurally, Type I scales are characterised by the presence of a lamina covering the scale windows and by microribs joining the larger longitudinal ridges. In contrast, Type II scale cells are pigmented with melanin, have larger crossribs and lack a lamina covering the scale windows. Quantitative variation in scale structures between populations (but not within individuals) can cause Type II scales to range from matte black to iridescent blue (Brien et al., 2019; Parnell et al., 2018). Finally, Type III scale cells contain the red ommochrome pigments xanthommatin and dihydroxanthommatin and are characterised by larger spacing between crossribs and ridges.

Here we focus on the role of cortex in specifying these scale types in Heliconius butterflies, an adaptive radiation with over 400 different wing forms in 48 described species (Jiggins, 2017; Lamas, 2004) and where diversity in wing patterns can be directly linked to the selective forces of predation and sexual selection (Brown, 1981; Turner, 1981). Specifically, we combine expression profiling using RNA-seq, ATAC-seq, in situ hybridisation and antibody staining experiments, as well as CRISPR/Cas9 gene knockouts to determine the role that this locus plays in pattern variation of two co-mimetic morphs of H. melpomene and H. erato (Figure 1b). We focus on two mimetic morphs differing specifically in the presence/absence of a yellow hindwing bar, whose phenotypic switch has been mapped to non-coding regions surrounding the gene cortex. We also test its function in diverse patterning morphs, including ones differing in the presence of white margin elements spanning the hindwing, as well as species displaying divergent and complex phenotypes such as the tiger striped silvaniform Heiconius hecale. Despite cortex not following the prevailing paradigm of patterning loci, we demonstrate that the gene plays a fundamental role in pattern variation by modulating a switch from Type I scale cells to Type II and Type III scale cells. Moreover, we show that while the phenotypic effects of cortex extend across the entire fore- and hindwing surface, modular enhancers have evolved in two distantly related Heliconius species that control spatially restricted, pattern-specific expression of cortex. Our findings, coupled with recent functional experiments on other Heliconius patterning loci, are beginning to illuminate how major patterning genes interact during development to determine scale cell fate and drive phenotypic variation across a remarkable adaptive radiation.

Results

The genes cortex and domeless/washout are differentially expressed between colour pattern morphs and between wing sections differing in the presence of the hindwing yellow bar

To identify genes associated with the yellow bar phenotype, we performed differential gene expression (DGE) analysis using developing hindwings sampled from colour pattern morphs in H. erato and H. melpomene differing only in the presence or absence of the hindwing yellow bar (Figures 1b and 2a). In total, we sequenced 18 samples representing three developmental stages (larval, 36 h ± 1.5 h [Day 1 pupae] and 60 h ± 1.5 h [Day 2 pupae]) from two morphs in each of the two species, with hindwings divided into two parts for the pupal stages (Figure 2a). We focused our attention on genes centred on a 47-gene interval on chromosome 15 previously identified as the minimal associated region with yellow band phenotypes by recombination and population genetic association mapping (Nadeau et al., 2016, Supp Table 1; Joron et al., 2006; Moest et al., 2020; Van Belleghem et al., 2017). Both our initial expression analysis and recent analysis of selective sweeps at this locus (Moest et al., 2020) indicate that three genes show differential expression and are likely targets of selection: cortex, domeless (dome), and washout (wash) (Figure 2c). In Heliconius, dome appears to have duplicated in the ancestor of H. erato and H. melpomene, resulting in a full-length copy (referred to here as domeless) and a further copy exhibiting truncations at the C-terminus (domeless-truncated [dome-trunc]) (Figure 1—figure supplements 12). Transcriptomic and previous evidence (Lewis et al., 2020) also indicates that dome and wash are transcribed as a single bi-cistronic gene (Figure 1—figure supplements 34). Differential expression analysis was thus performed with dome/wash as a single annotation.

Figure 2 with 6 supplements see all
Differential expression of genes at Chromosome 15 implicate cortex as most likely candidate driving yellow bar differences.

(a) Hindwing tissue from co-mimetic morphs of H. melpomene and H. erato were collected at three developmental stages fifth-instar caterpillar, Day 1 Pupae (36hAPF) and Day 2 Pupae (60hAPF). For pupal tissue, hindwing tissue was dissected using the wing vein landmarks shown, corresponding to the future adult position of the hindwing yellow bar (dissection scheme based on Hanly et al., 2019). (b) Relative abundance of transcripts corresponding to the genes cortex, domeless-truncated, domeless/washout throughout developmental stages. (c) Log2FoldChange for the genes cortex, domeless-truncated (dome-t), domeless/washout (dome-wash) across developmental stages. Comparisons are for whole wing discs (Larvae, L) and across wing sections differing in the presence of a yellow bar in pupal wings (D1 and D2; see Figure 2—figure supplement 2: for depiction of contrasts analysed). *Adjusted p<0.05; n/s = not significant. N = 3 for each bar plot.

Figure 2—source data 1

RNA-seq samples were genotyped relative to protein-coding WGS SNPs from individuals from the source populations in Panama.

Both SNPs were contained in the protein-coding sequence of the gene Cortex. Individuals from the RNA-seq experiment match the genotype of the source populations.

https://cdn.elifesciences.org/articles/68549/elife-68549-fig2-data1-v1.docx
Figure 2—source data 2

This was repeated for the H. erato samples; here, only one informative protein-coding SNP was found, in the gene parn.

Once again, all individuals match the expected genotype.

https://cdn.elifesciences.org/articles/68549/elife-68549-fig2-data2-v1.docx
Figure 2—source data 3

Primers used for qPCR experiments for housekeeping genes and cortex are shown below.

https://cdn.elifesciences.org/articles/68549/elife-68549-fig2-data3-v1.docx
Figure 2—source data 4

Gene IDs in the H. melpomene Yb locus and their corresponding IDs in the H. erato genome.

https://cdn.elifesciences.org/articles/68549/elife-68549-fig2-data4-v1.docx

The two species were analysed separately, with both showing only cortex and dome/wash as significantly differentially expressed between morphs among the 47 genes in the candidate region, with cortex differential expression occurring earlier in development. In fifth-instar larvae, cortex is differentially expressed in both species between the two colour pattern morphs, with cortex showing the highest adjusted p-value (Benjamini and Hochberg correction) for any gene in the genome at this stage in H. erato (Figure 2c). Interestingly, cortex transcripts were differentially expressed in opposite directions in the two species, with higher expression in the melanic hindwing morph in H. melpomene and in the yellow banded morph in H. erato. We confirmed this pattern of expression through a SNP association analysis (Figure 2—source data 13) and RT-qPCR (Figure 2—figure supplement 1). This pattern is reversed for dome/wash in Day 1 pupae, where a statistically higher proportion of transcripts are detected in H. melpomene rosina (yellow) and in H. erato hydara (melanic) (Figure 2—figure supplements 24). No differential expression of these genes was found at Day 2 pupae.

When comparing across hindwing sections differing for the yellow bar phenotype, 22 genes of the associated 47-gene interval were differentially expressed at Day 1 between relevant wing sections in H. melpomene, including cortex and dome/wash (Figure 2—figure supplements 24). In contrast, in H. erato Day 1 pupae, only dome/wash was differentially expressed. At Day 2 pupae, there were no differentially expressed genes in either species between relevant wing sections at this locus.

Given the strong support for the involvement of cortex in driving wing patterning differences, we re-analysed its phylogenetic relationship to other cdc20 family genes with more extensive sampling than previous analyses (Nadeau et al., 2016). Our analysis finds strong monophyletic support for cortex as an insect-specific member of the cdc20 family, with no clear cortex homologs found outside of the Neoptera (Figure 2—figure supplement 5). Branch lengths indicate cortex is evolving rapidly within the lineage, despite displaying conserved anaphase promoting complex (APC/C binding motifs, including the C-Box and IR tail Figure 2—figure supplement 6Chu et al., 2001; Pesin and Orr-Weaver, 2007).

In summary, cortex is the most consistently differentially expressed gene and showed differential expression earlier in development as compared to the other candidate dome/wash. We therefore focused subsequent experiments on cortex, although at this stage we cannot rule out an additional role for dome/wash in yellow pattern specification.

Cortex transcripts localise distally in fifth-instar larval wing discs

Two studies have reported that cortex mRNA expression correlates with melanic patches in two species of Heliconius (Nadeau et al., 2016; Saenko et al., 2019). To further assess this relationship between cortex expression and adult wing patterns, we performed in situ hybridisation on developing wing discs of fifth-instar larvae, where we observed largest cortex transcript abundance, in both the yellow-barred and plain hindwing morphs of H. erato and H. melpomene. Cortex transcripts at this stage localised distally in forewings and hindwings of both species (Figure 3—figure supplement 1). In H. erato demophoon hindwings, expression was strongest at the intervein midline, but extends across vein compartments covering the distal portion of both forewing and hindwing (Figure 3a). By contrast, in H. erato hydara hindwings, cortex transcripts are more strongly localised to the intervein midline forming a sharper intervein expression domain (Figure 3c).

Figure 3 with 1 supplement see all
Expression of cortex transcripts in Heliconius melpomene, Heliconius erato, and Heliconius hecale fifth-instar wing discs.

Cortex expression in fifth-instar wing discs is restricted to the distal end of both forewings and hindwings in all species and morphs analysed. In H. erato, expression is strongest at the intervein midline but extends across vein compartments in H. erato demophoon (a), whereas it is more strongly localised to the intervein midline in H. erato hydara (c). In H. melpomene rosina (b), cortex localises in a similar manner to H. erato demophoon, with stronger expression again observed at the intervein midline, whereas expression in H. melpomene melpomene (d) extends more proximally. Expression in H. hecale melicerta (e) is strongest at the distal wing vein margins. Coloured dots represent homologous vein landmarks across the wings.

Expression in H. melpomene rosina is similar to H. erato demophoon at comparable developmental stages, again with stronger expression localised to the intervein midline but extending further proximally than in H. erato demophoon (Figure 3b). In H. melpomene melpomene, hindwing cortex expression extends across most of the hindwing, and does not appear to be restricted to the intervein midline (Figure 3c).

Given that cortex has been implicated in modulating wing patterns in many divergent lepidoptera, we also examined localisation in a Heliconius species displaying distinct patterns: H. hecale melicerta (Figure 3e). Interestingly, in this species, transcripts appear strongest in regions straddling the wing disc veins, with weak intervein expression observed only in the hindwings. Previous data has shown that variation in yellow spots (Hspot) is also controlled by a locus located a chromosome 15 (Huber et al., 2015). Expression in H. hecale melicerta forewings corresponds to melanic regions located in between yellow spots at the wing margins, indicating cortex may be modulating Hspot variation in H. hecale.

Overall, our results suggest a less clear correlation to melanic elements than reported expression patterns (Nadeau et al., 2016; Saenko et al., 2019) where cortex expression in fifth-instar caterpillars is mostly restricted to the distal regions of developing wings, but appears likely to be dynamic across fifth-instar development (Figure 3—figure supplement 1).

Cortex establishes type II and III scale identity in Heliconius butterflies

To assay the function of cortex during wing development, we generated G0 somatic mosaic mutants using CRISPR/Cas9 knock outs. We targeted multiple exons using a combination of different guides and genotyped the resulting mutants through PCR amplification, cloning, and Sanger sequencing (Figure 4—figure supplement 1). Overall KO efficiency was low when compared to similar studies in Heliconius (Concha et al., 2019; Mazo-Vargas et al., 2017), with observed wing phenotype to hatched eggs ratios ranging from 0.3% to 4.8%. Lethality was also high, with hatched to adult ratios ranging from 8.1% to 29.8% (Figure 4—source data 12).

Targeting of the cortex gene in H. erato morphs produced patches of ectopic yellow and white scales spanning regions across both forewings and hindwings (Figure 4—figure supplements 24). All colour pattern morphs were affected in a similar manner in H. erato. Mutant clones were not restricted to any specific wing region, affecting scales in both proximal and distal portions of wings. The same effect on scale pigmentation was also observed in H. melpomene morphs, with mutant clones affecting both distal and proximal regions in forewings and hindwings (Figure 5a–c). In H. erato hydara, we recovered mutant individuals where clones also spanned the red forewing band (Figure 4b, Figure 4—figure supplement 5). Clones affecting this region caused what appears to be an asymmetric deposition of pigment across the scales, as well as transformation to white, unpigmented scales (Figure 4—figure supplement 5).

Figure 4 with 5 supplements see all
Cortex loss-of-function transforms scale identity across the entire wing surface of Heliconius erato.

Phenotypes of cortex mKO across H. erato morphs reveal a loss of melanic (Type II) and red (Type III) scales and transformation to Type I (yellow or white) scales. Affected regions are not spatially restricted and span both distal and proximal portions of forewings and hindwings. The scale transformation extends to all scale types, including the wing border scales (red arrow head in (a)), and across the red band elements, where mutant scales transform to white, as well as some showing an intermediate phenotype (blue arrow heads in (b)). A positional effect is observed in some morphs, where ectopic Type I scales are either white or yellow depending on their position along the wing (H. erato cyrbia, (c)). Ectopic Type I scales can be induced from both melanic and red scales, switching to either white or yellow depending on wing position and morph. Boundaries between Wild-type (WT) to mutant scales are highlighted (dotted white line).

Figure 4—source data 1

CRISPR experiments and guides used per species/morph.

https://cdn.elifesciences.org/articles/68549/elife-68549-fig4-data1-v1.xlsx
Figure 4—source data 2

Sequences for guides yielding successful phenotypes and associated genotyping primers.

https://cdn.elifesciences.org/articles/68549/elife-68549-fig4-data2-v1.xlsx
Figure 5 with 5 supplements see all
Cortex function is conserved across Heliconius and Nymphalids Phenotypes of cortex mKO across H. melpomene colour pattern morphs.

(a–c) reveal cortex has a conserved function in switching scale cell fates, as in H. erato. This function is also conserved in outgroups to H. melpomene and H. erato (H. hecale melicerta and H. charithonia respectively (d–e)) as well as in distantly diverged nymphalids (D. plexippus (f)). Left; wild-type, middle and right; cortex mKO.

As this locus has been associated with differences in white hindwing margin phenotypes (Jiggins and McMillan, 1997Figure 1b), we also targeted cortex in mimetic morphs that display the same phenotype in the two species, H. erato cyrbia and H. melpomene cythera. Mutant scales in these colour pattern morphs were also localised across both wing surfaces, with both white and yellow ectopic scales (Figures 4c and 5c). Both the white and blue colouration in these co-mimics is structurally derived, indicating that cortex loss-of-function phenotype also affects the scale ultrastructure. Furthermore, we observed a positional effect, where ectopic scales in the forewing and anterior compartment of the hindwing shifted to yellow, and posterior hindwing scales became white (Figure 4c, Figure 4—figure supplement 5d). This positional effect likely reflects differential uptake of the yellow pigment 3-OHK across the wing surface, which may be related to cryptic differential expression of the yellow-white switch aristaless-1 (Reed et al., 2008; Westerman et al., 2018).

To further test the conservation of cortex function across the Heliconius radiation, as well as nymphalids as a whole, we knocked out cortex in H. charithonia and H. hecale melicerta, outgroups to H. erato and H. melpomene, respectively, and Danaus plexippus as an outgroup to all Heliconiini. Again, ectopic yellow and white scales appeared throughout the wing surface in all species, suggesting a conserved function with respect to scale development among butterflies (Figure 5d–f, Figure 5—figure supplements 15).

In summary, cortex mKOs appear to not be restricted to any specific wing pattern elements and instead affect regions across the surface of both forewings and hindwings. Mutant scales are always Type I scales, with differing pigmentation (3-OHK, yellow) or structural colouration (white) depending on morph and wing position. The high rate of mosaicism combined with high mortality rates suggests cortex is likely developmentally lethal. Mutant clones also appear aggregated, suggesting the cortex mKO may affect early phases of cell division or communication during development and produce a growth disadvantage or differential adhesion relative to WT cells that result in grouping effects.

Nuclear localisation of Cortex protein extends across the wing surface in pupal wings

The cortex mRNA expression patterns in larval imaginal disks suggest a dynamic progression in the distal regions, and in a few cases (Figure 3; Nadeau et al., 2016; Saenko et al., 2019), a correlation with melanic patterns whose polymorphisms associate with genetic variation at the cortex locus itself. We thus initially hypothesised that like for the WntA mimicry gene (Martin et al., 2012; Mazo-Vargas et al., 2017, Concha et al., 2019), the larval expression domains of cortex would delimit the wing territories where it is playing an active role in colour patterning. However, our CRISPR based loss-of-function experiments challenge that hypothesis because in all the morphs that we assayed, we found mutant scales across the wing surface.

This led us to re-examine our model and consider that post-larval stages of cortex expression could reconcile the observation of scale phenotypes across the entire wing, rather than in limited areas of the wing patterns. To test this hypothesis, we developed a Cortex polyclonal antibody and found nuclear expression across the epithelium of H. erato demophoon pupal hindwings without restriction to specific pattern elements (Figure 6). In fifth-instar larvae, Cortex protein was detected in a similar pattern to mRNA, with expression visible at the intervein midline of developing wings (Figure 6a). Cortex was then detected across the entire wing surface from 24 hr after pupal formation (a.p.f), until 80 hr a.p.f in our time series (Figure 6b–d, Figure 6—figure supplement 1). Localisation remained nuclear throughout development and appears equal in intensity across hindwing colour pattern elements (Figure 6e).

Figure 6 with 1 supplement see all
Cortex protein localises across the wings in H. erato demophoon.

Antibody stainings reveal Cortex protein is localised at the distal intervein midline in fifth-instar wing discs (yellow arrowheads) (a). At 24 hr APF, the protein is detected across the wing and localised strongly to the cell nuclei (b). This localisation continues at 72 hr APF(c) and 80 APF (d). In each panel, leftmost insert shows nuclei stained with DAPI (magenta), middle insert with Cortex antibody detected with a secondary alexa-fluor 555 conjugated antibody (red), and right insert shows both channels merged into a composite image. No appreciable difference in localisation is detected across presumptive pattern elements at 72 hr APF (e). The magnified portion of the imaged wing is indicated in the wing cartoon in the top left corner of ( e).

Modular cis-regulatory elements drive the evolution of the mimetic yellow bar

Given the broad effect observed for cortex across both wing surfaces, we next tested whether specific expression might be under the control of pattern-specific cis-regulatory elements (CREs). In order to look for potential CREs, we performed an Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) in fifth-instar hindwings of both co-mimetic morphs differing in the presence of the yellow bar in H. erato and H. melpomene (Figure 7—source data 1). We observed many accessible chromatin ‘peaks’ surrounding cortex (Figure 7—figure supplement 1), each of which could represent a potentially active CRE. To narrow down candidate peaks that could be regulating cortex in a pattern-specific manner, we overlayed association intervals with the ATAC-seq signals, which indicate evolved regions between populations of H. melpomene differing in the hindwing yellow bar phenotype. Specifically, we applied the phylogenetic weighting strategy Twisst (topology weighting by iterative sampling of subtrees; Martin and Van Belleghem, 2017) to identify shared or conserved genomic intervals between sets of H. melpomene populations (obtained from Moest et al., 2020) with similar phenotypes around cortex. This method identified a strong signal of association ~8 kb downstream of the annotated cortex stop codon, that overlapped with a clear ATAC-seq peak (Figure 7a,b, Figure 7—figure supplement 1).

Figure 7 with 5 supplements see all
Modular CREs control the presence of the yellow band in Heliconius melpomene and Heliconius erato.

(a) Chromatin accessibility as measured by mean sequence depth for ATAC-seq traces in H. erato (top) and H. melpomene (bottom) in fifth-instar caterpillar hindwings in yellow banded and black morphs. The gene model for cortex is shown above the traces (black rectangles are coding exons, white rectangle non-coding exon, lines are introns, direction of transcription is indicated by an arrow). The transcription start site is around 120 kb from the first coding exon of cortex. Positions of sgRNAs used for peak excision are shown (yellow scissors). Regions with >75% sequence identity between H. melpomene and H. erato are indicated by grey lines. (b) Twisst analysis results showing high genetic association for the presence of a yellow bar in H. melpomene populations with a ventral (ventral topology) or dorsal (dorsal topology) yellow bar. Abbreviations for twisst morphs: wey-gus = H. cydno weymeri-gustavi, chi = H. cydno chioneus, zel = H. cydno zelinde, pac = H. pachinus, ros = H. melpomene rosina, melG = H. melpomene melpomene French Guiana, vul = H. melpomene vulcanus, cyt = H. melpomene cythera. (c) Cortex loss-of-function at the yellow bar CREs affect scales only in the presumptive yellow bar region. CRE KO affects both dorsal (left) and ventral (right) hindwings.

Figure 7—source data 1

List of ATAC-seq samples used in this study, and corresponding accession numbers.

https://cdn.elifesciences.org/articles/68549/elife-68549-fig7-data1-v1.docx

We next sought to knock out this CRE, by designing a pair of sgRNA guides flanking the ATAC-seq signal. We reasoned that since cortex controlled the switch to melanic scales across the entire wing, knocking-out an enhancer in the melanic morph (H. melpomene melpomene), or in F1 hybrids between H. melpomene rosina and H. melpomene melpomene, should result in the appearance of yellow scales in a yellow bar-like pattern. Indeed, upon KO of this CRE we recovered mKOs consistent with a modular enhancer driving cortex expression in a yellow bar-specific pattern, with no clones exhibiting yellow scales extending out of the region that forms the yellow bar (Figure 7c, Figure 7—figure supplement 2).

To test whether the same element was driving the evolution of the yellow bar phenotype in the co-mimetic morph of H. erato, we first targeted the homologous peak, which shares both 95% sequence identity with H. melpomene, as well as the presence of an accessible chromatin mark (Figure 7a). While none of our CRISPR trials resulted in a visible phenotype at this locus (number of injected adults eclosed = 36), we did observe the presence of a further accessible region ~10 kb 3’ of the H. melpomene conserved CRE. We reasoned that a different but positionally close peak could be driving the yellow bar phenotype in H. erato. Remarkably, targeting of this CRE resulted in a yellow bar phenotype in the melanic H. erato hydara, with no clones containing yellow scales extending beyond the region that forms the yellow bar (Figure 7c, Figure 7—figure supplement 3). Deletions at each of the loci were confirmed by PCR amplification, cloning, and Sanger sequencing (Figure 7—figure supplement 4).

Finally, to confirm that the CREs were interacting with the cortex promoter, we took advantage of a previously published set of Hi-C samples in H. erato populations (Lewis et al., 2019), to check for enhancer/promoter interactions through the implementation of virtual 4C plots. For both CREs, we found a statistically significant interaction between CRE and promoter, indicating the observed effect is likely due to the CRE interacting with the cortex promoter, and not a different gene at the locus (Figure 7—figure supplement 5).

Transposable element insertions are associated with the yellow bar phenotype in geographically distinct H. melpomene populations

Given that we were able to induce a yellow bar phenotype by the deletion of a modular CRE, we next asked whether natural populations with this phenotype might also show a similar deletion. To test for the presence of deletions at the candidate CRE, we used extensive publicly available whole-genome re-sequence data for geographically isolated populations differing in the presence of the hindwing yellow bar (Darragh et al., 2019; Enciso-Romero et al., 2017; Kozak et al., 2018; Martin et al., 2019; Van Belleghem et al., 2017). In total, we assayed 16 geographically isolated subspecies across central and south America and looked for signature coverage drops at the targeted ATAC-seq peak, which could be indicative of deletions (Chan et al., 2010; Kemppainen et al., 2021Figure 8—source data 1). We observed a characteristic drop in coverage at the targeted CRE in all H. melpomene and H. timareta morphs exhibiting a yellow bar phenotype, while no drop was detected in morphs with a melanic hindwing (Figure 8a). Given this characteristic signature associated with the presence of a yellow bar in the sequencing data, we next genotyped across the putative deletion using Sanger sequencing in H. melpomene rosina and H. melpomene melpomene individuals. Surprisingly, we found two transposable element (TE) insertions in H. melpomene rosina with a Helitron-like TE found spanning the CRE peak, suggesting that the coverage drop is instead due to an insertion of repetitive sequence, rather than a deletion. Enhancer disruption is therefore likely caused by TE sequence in yellow bar morphs (Liu et al., 2019). We next assayed three other yellow-barred morphs (H. melpomene bellula, H. melpomene amaryllis, and H. timareta tristero) and found the same TE signatures in all three populations (Figure 8—figure supplement 2), suggesting the TE insertions are likely shared through introgression. No similar signature of reduced coverage was observed in co-mimetic morphs of H. erato, suggesting that sequence divergence is responsible for the evolution of the yellow bar CRE in this species (Figure 8—figure supplement 2).

Figure 8 with 2 supplements see all
Coverage drop indicative of deletions in yellow-barred populations of H. melpomene.

(a) Mean sequence depth for ATAC-seq traces for the excised CRE are shown above normalised depth in sequencing coverage for populations of H.melpomene (circles) and H. timareta (triangles) differing for the presence of a yellow bar. Yellow-barred populations display a drop in coverage for both ATAC signal and sequencing depth at a position corresponding to a portion of the targeted CRE (highlighted by the grey lines). Morphs analysed for melanic hindwing H. melpomene and H. timareta: H. m. maletti, H. m. melpomene, H. t. florencia. Morphs analysed for yellow-barred H. melpomene and H. timareta: H. m. bellula, H. m. amaryllis, H. m. rosina, H. m. burchelli, H t. thelxione, H. t. tristero. (b) Sanger sequencing of target regions in H. m. melpomene and H. m. rosina reveals an insertion of two TE elements surrounding the yellow bar CRE. A larger BovB-like element of 690 bp (blue) and a smaller 163 bp Helitron-like element (yellow) are present in the H. m. rosina sequences, but not the H. m. melpomene sequences. Base pair positions of the consensus Sanger sequencing traces are shown below.

Figure 8—source data 1

List of individuals used in coverage depth analysis, and corresponding accession numbers.

https://cdn.elifesciences.org/articles/68549/elife-68549-fig8-data1-v1.docx
Figure 8—source data 2

Consensus sequences recovered from Sanger sequencing across the H. melpomene/timareta CRE.

The BovB-like TE element is indicated in blue; The Helitron-like fragment in orange. Both are absent from the H. melpomene melpomene sequence.

https://cdn.elifesciences.org/articles/68549/elife-68549-fig8-data2-v1.docx

Cortex coding KO causes partial homeotic shifts in scale structure

Previous studies have shown an association between scale ultrastructure and pigmentation in Heliconius butterflies (Concha et al., 2019; Gilbert et al., 1987; Janssen et al., 2001; Zhang et al., 2017). In particular, it has been reported that perturbation by wounding transforms both the pigment content and structure of scales in a tightly coupled way (Janssen et al., 2001). We thus asked whether ectopic yellow/white scales generated through cortex knockout were accompanied by structural transformations using scanning electron microscopy (SEM) in the same way as ectopic colour scales generated through wounding or WntA knockouts (Janssen et al., 2001; Concha et al., 2019). To account for known positional effects on scale structure, we compared wild-type and mutant scales from homologous locations across the wing surface.

We observed ultrastructural shifts that are consistent with partial homeosis in cortex mutant scales in both H. melpomene and H. erato (Figure 9, Figure 9—figure supplement 1). In all cases where a yellow or white (Type I) clone was present in a region that would otherwise be black or blue (Type II) in the wild type, the ultrastructure of the scale was notably different. Wild-type blue and black scales have crossribs at a spacing of ~0.6 µm, lack lamina between ridges and crossribs, and have no prominent microribs, while both wild-type and mutant Type I scales have no prominent crossribs, lamina that fills the spaces between the microribs and ridges, and prominent microribs at a spacing of ~0.2 µm (Figure 9a–d, Figure 9—source data 12). A consistent difference between all Type I scales (mutant and wild type) is the presence of a lamina covering the inter-ridge space (Figure 9f). These ultrastructural shifts suggest that the perturbation of cortex affects scale fate decision, not only shifting pigmentation type, but also scale morphology.

Figure 9 with 2 supplements see all
SEM reveals structural changes induced by cortex KO.

Ultrastructural morphology of H. erato demophoon (a) and H. melpomene rosina (b) hindwing scales for wild-type (WT) black, mutant yellow and wild-type yellow scales. Light micrographs of each scale are shown below the representative SEM images. Scale morphologies are also presented for morphs displaying shifts to white scales in H. erato cyrbia (c) and H. melpomene cythera (d). Structural changes in the red scales of H. erato hydara (e) are accompanied by scale deformations, resulting in a curled appearance. Cartoon depiction of scale ultrastructure illustrating differences between scale types (f). Type I scales are characterised by the presence of a lamina covering the scale windows and by microribs joining the longitudinal ridges. Type II scale cells display larger crossribs and lack a lamina covering the scale windows. Type III scale cells and are characterised by larger spacing between crossribs and ridges. Scale bar in (a) = 3 µm.

Figure 9—source data 1

Pairwise Wilcox test adjusted p-values for quantitative measures of scale structures and features in H.melpomene.

https://cdn.elifesciences.org/articles/68549/elife-68549-fig9-data1-v1.docx
Figure 9—source data 2

Pairwise Wilcox test adjusted p-values for quantitative measures of scale structures and features in H.erato.

https://cdn.elifesciences.org/articles/68549/elife-68549-fig9-data2-v1.docx

Red scales (Type III) that are within a coding KO clone take on an aberrant structure and pigmentation. Scales were frequently found to be curled up laterally, and while ommochrome pigment is sometimes visibly deposited in the scale, it is granular in appearance rather than diffuse throughout the scale (Figure 9e, Figure 9—figure supplement 2). These ‘granular’ pigment accumulations could not be observed as a distinct structure by SEM, suggesting that they are under the surface of the scale. As with wild-type and mutant Type I scales, prominent microribs can also be observed on these rolled scales, but due to the topological deformity of these scales, it was not possible to take accurate measurements.

Discussion

Cortex is a key scale cell specification gene

The genetic locus containing the gene cortex represents a remarkable case of convergent evolution, where repeated and independent mutations surrounding the gene are associated with shifts in scale pigmentation state in at least nine divergent species of Lepidoptera (Beldade et al., 2009; van der Burg et al., 2020; Nadeau et al., 2016; Van Belleghem et al., 2017; VanKuren et al., 2019; Van't Hof et al., 2019; Van't Hof et al., 2016). While these studies have linked putative regulatory variation around cortex to the evolution of wing patterns, its precise effect on scale cell identity and pigmentation has remained speculative until now. Here, we demonstrate that cortex is a causative gene that specifies melanic and red (Type II and Type III) scale cell identity in Heliconius and acts by influencing both downstream pigmentation pathways and scale cell ultrastructure. We also show that cortex is under the control of modular enhancers that appear to control the switch between mimetic yellow bar phenotypes in both H. melpomene and H. erato. Our combination of expression studies and functional knockouts demonstrate that this gene acts as a key scale cell specification switch across the wing surface of Heliconius butterflies, and thus has the potential to generate much broader pattern variation than previously described patterning genes.

While we have shown that cortex is a key scale cell specification gene, it remains unclear how a gene with homology to the fizzy/cdc20 family of cell cycle regulators acts to modulate scale identity. In Drosophila, Fizzy proteins are known to regulate APC/C activity through the degradation of cyclins, leading to the arrest of mitosis (Raff et al., 2002). In particular, fizzy-related (fzr) induces a switch from the mitotic cycle to the endocycle, allowing the development of polyploid follicle cells in Drosophila ovaries (Schaeffer et al., 2004; Shcherbata et al., 2004). Similarly, cortex has been shown to downregulate cyclins during Drosophila female meiosis, through its interaction with the APC/C (Pesin and Orr-Weaver, 2007; Swan and Schüpbach, 2007). Immunostainings show that Cortex protein localises to the nucleus in Heliconius pupal wings, suggesting a possible interaction with the APC/C in butterfly scale building cells. Ploidy levels in Lepidoptera scale cells have been shown to correlate with pigmentation state, where increased ploidy and scale size lead to darker scales (Cho and Nijhout, 2013; Iwata and Otaki, 2016). cortex may thus be modulating ploidy levels by inducing endoreplication cycles in developing scale cells. However, we currently have no direct evidence for a causal relationship between ploidy state and pigmentation output, and a mechanistic understanding of this relationship and any role cortex may be playing in modulating ploidy levels will require future investigation.

A curious result reported from our RNA-seq dataset is that differential expression appears to occur in opposite directions between the two co-mimetic morphs. While this could represent some difference in the precise role of cortex between H. melpomene and H. erato, the pattern may also be explained by the limited sampling during fifth-instar development in both species. The dynamic expression observed during fifth-instar wing development suggests that levels of cortex expression may be changing in a precise and variable manner of short periods of development. A more precise time series across fifth-instar and early pupal development may thus be needed to reveal the precise difference in cellular function of cortex between these species.

The mimetic yellow bar phenotype switch is controlled by the evolution of modular enhancers

In H.melpomene, we were able to narrow down a clear peak of association with the presence of accessible chromatin marks and showed that KO of this region results in the appearance of a yellow bar phenotype in black hindwing morphs (Figure 7). Interestingly, when targeting the homologous peak in H. erato, we failed to recover any type of phenotype, but were able to induce the appearance of a yellow bar through the targeting of an adjacent peak, not present in the H. melpomene datasets, indicating that an independently evolved CRE is driving this phenotype in H. erato.

These results, coupled with the coding KOs, suggests that the CREs are enhancers that are able to drive cortex expression in a yellow bar specific manner. It is therefore puzzling that both the in situ hybridisation and antibody experiments failed to recover an association between Cortex localisation and the yellow bar phenotype. One possibility is that, because cortex is expressed throughout the wing, the differences in cortex expression that drive the pattern difference are either highly discrete in time and therefore hard to observe, or are the consequence of subtle changes in concentration that we could not detect with immunofluorescence. Moreover, cortex is known to have complex patterns of alternative splicing (Nadeau et al., 2016), suggesting that perhaps both our polyclonal antibody and in situ probes lack the specificity to detect localisation of specific alternatively spliced variants. This lack of a conspicuous link between expression and function is a puzzling result that will require further investigation in future. The ideal experiments would utilise the identified enhancers as enhancer traps, to show they are able to drive expression in a pattern-specific manner, as well as perform knock-in experiments in the reciprocal co-mimetic morph, to show that these regions are sufficient to drive the phenotypic switches.

In H. melpomene, we found a clear association between the absence of an accessible chromatin peak in yellow-barred populations with a characteristic drop in coverage over the same region, that overlaps with both the targeted CRISPR and association intervals. The mapped profiles show that this drop in coverage is explained by phenotype, rather than geography, in contrast to other adjacent regions. Upon further investigation, we found a large 690 bp TE insertion 5’ of the peak of interest as well as a Helitron-like sequence overlapping the peak in H. melpomene rosina. This raises the interesting possibility that this portion of the enhancer might contain the binding sites necessary to drive cortex in a yellow bar specific manner, and that recurrent TE insertions across this region are driving the evolution of this phenotype in H. melpomene populations. We also note that this insertion is observed in mimetic morphs of a different species, H. timareta, with which H. melpomene has previously been described to share regulatory regions at other patterning loci via adaptive introgression (Morris et al., 2019; Wallbank et al., 2016). Thus, adaptive introgression of this region and its structural variants is likely facilitating mimicry in this system (Heliconius Genome Consortium et al., 2012).

Heliconius wing patterning is controlled by interactions among major patterning genes

Functional knockouts now exist for all the four major loci known to drive pigmentation differences in Heliconius (Mazo-Vargas et al., 2017; Westerman et al., 2018; Zhang et al., 2017). These loci represent the major switching points in the GRNs that are ultimately responsible for determining scale cell identity. This work underscores the importance of two patterning loci, cortex and WntA, as master regulators of scale cell identity. Both are upregulated early in wing development and have broad effects on pattern variation (Concha et al., 2019; Nadeau et al., 2016). The signalling molecule WntA modulates forewing band shape in Heliconius by delineating boundaries around patterns elements, and is expressed in close association with future pattern elements (Concha et al., 2019; Martin et al., 2012). Unlike cortex mutants, WntA KOs shift scale cell identity to all three cell types (I, II, and III), depending on genetic background. Thus, WntA acts as a spatial patterning signal inducing or inhibiting colour in specific wing elements, in contrast to cortex, which acts as an ‘on-off’ switch across all scales on the butterfly wing.

Interestingly, cortex knockouts lead to shifts in scale fate irrespective of WntA expression. This suggests either that cortex is required as an inductive signal to allow WntA to signal further melanisation, or that two, independent ways to melanise a scale are available to the developing wing. The latter hypothesis is supported by certain H. erato colour pattern WntA mutants, where even in putatively cortex-positive regions, scales are able to shift to Type I in the absence of WntA alone (Concha et al., 2019). This indicates that while under certain conditions cortex is sufficient to induce the development of black scales, WntA is also required as a further signal for melanisation in some genetic backgrounds. Under this scenario, colour pattern morphs may be responding epistatically to different WntA/cortex alleles present in their respective genetic backgrounds. This is also consistent with genetic evidence for epistasis between these two loci seen in crossing experiments, whereby the yellow bar in H. erato favorinus results from an interaction between the Cortex and WntA loci (Mallet, 1989).

Under a simple model (Figure 10), cortex is one of the earliest regulators and sets scale differentiation to a specific pathway switches between Type I (yellow/white) and Type II/III (black/red) scales. Thus, we can envision a differentiating presumptive scale cell (PSC) receiving a Cortex input as becoming Type II/III competent, with complete Type III differentiation occurring in the presence of optix expression (Zhang et al., 2017). This is consistent with our data, which shows cortex is also required as a signal for Type III (red) scales to properly develop. Several cortex mutant individuals had clones across red pattern elements and failed to properly develop red pigment. The development of red scales in Heliconius butterflies is also dependent on expression of the transcription factor optix during mid-pupal development (Lewis et al., 2019; Reed et al., 2011; Zhang et al., 2017). Therefore, cortex expression is required for either downstream signalling to optix or to induce a permissive scale morphology for the synthesis and deposition of red pigment in future scales. Cortex is thus necessary for the induction of Type III scale cells but insufficient for their proper development.

Expression of key genes affect scale fate decisions and influence downstream pigmentation state.

During early-instar development, wing disc cells differentiate into presumptive scale cells (PSCs). Throughout fifth-instar growth, PSCs express key scale cell specification genes such as cortex, which induce differentiation into Type II (optix−) scales or Type III (optix+) scales. In the absence of cortex, scale cells differentiate into Type I scales, which differ in pigmentation state based on 3-OHK synthesis controlled by aristaless1 expression. Model based on the epigenetic landscape (Waddington) and by observations made by Gilbert et al., 1987.

Conversely, a PSC lacking a Cortex input differentiates into a Type I scale, whose pigmentation state depends on the presence of the transcription factor aristaless1 (al1), where al1 is responsible for inducing a switch from yellow to white scales in Heliconius by affecting the deposition of the yellow pigment 3-OHK (Westerman et al., 2018). The uptake of 3-OHK from the haemolymph occurs very late in wing development, right before the adult ecloses (Reed et al., 2008). Our cortex mKOs revealed a shift to both yellow and white scales, with their appearance being positionally dependent; more distally located scales generally switch to white, while more proximal scales become yellow. This pigmentation state is likely controlled by differences in al1 expression varying between wing sections in different ways across morphs.

However, the switch induced by Cortex under this model is likely not a simple binary toggle, and is perhaps dependent on a given protein threshold or heterochrony in expression rather than presence/absence, as we find that Cortex protein also localises to the presumptive yellow bar in developing pupal wings. Moreover, the RNA-seq data presented suggests other linked genes may also be playing a role in controlling pattern switches between Heliconius morphs. In particular, we report the presence of a bi-cistronic transcript containing the ORFs of the genes dome/wash, which are differentially expressed during early pupal wing development. While a precise role for dome/wash in wing patterning remains to be demonstrated, it raises the possibility that multiple linked genes co-operate during Heliconius wing development to drive pattern diversity. It is noteworthy that in the locally polymorphic H. numata, all wing pattern variation is controlled by inversions surrounding cortex and dome/wash, both of which are also differentially expressed in H. numata (Saenko et al., 2019). This raises the interesting possibility that evolution has favoured the interaction of multiple genes at the locus that have since become locked into a supergene in H. numata.

Conclusions

The utilisation of ‘hotspots’ in evolution has become a recurring theme of evolutionary biology, with several examples in which independent mutations surrounding the same gene have driven adaptive evolution (e.g Pitx1, Scute) (Stern and Orgogozo, 2009). One proposed facilitator of such hotspots is through the action of genes acting as ‘input-output’ modules, whereby complex spatio-temporal information is translated into a co-ordinated cell differentiation program, in a simple switch-like manner. One prediction of the nature of such genes would be a switch-like behaviour such as that observed for cortex in this study, as well as the presence of a complex modular cis-regulatory architecture surrounding the gene that is able to integrate the complex upstream positional information into the switch-like output. A conserved feature of the cortex locus in Lepidoptera is the presence of large intergenic regions surrounding the gene, with evidence these may be acting as modular cis-regulatory switches in Heliconius (Enciso-Romero et al., 2017; Van Belleghem et al., 2017), fitting the predicted structure of input-output genes. Unlike canonical input-output loci however, cortex expression appears not to be restricted to any particular colour pattern element in any given species/morph, and yet is capable of producing a switch-like output (Type I vs Type II/III scales). Furthermore, our work shows that two independent CREs in H. melpomene and H. erato evolved to control the presence/absence of a yellow hindwing bar. However, it is still unclear how cortex mechanistically affects pigmentation differences, and given its widespread usage throughout Lepidoptera, it is of general interest to understand its role in driving scale pigmentation.

Materials and methods

Butterfly husbandry

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Heliconius butterflies were collected in the tropical forests of Panama and Ecuador. Adults were provided with an artificial diet of pollen/glucose solution supplemented with flowers of Psiguria, Lantana, and/or Psychotria alata according to availability. Females were provided with Passiflora plants for egg laying (P. menispermifolia for H. melpomene, P. biflora for H. erato and H. charithonia, and P. vitifolia for H. hecale). Eggs were collected daily, and caterpillars reared on fresh shoots of P. williamsi (melpomene), P. biflora (erato and charithonia), and P. vitifolia for H. hecale. Late fifth (final) instar caterpillars were separated into individual pots in a temperature-monitored room for RNA-seq experiments, where they were closely observed for the purpose of accurate developmental staging.

Phylogenetic analysis of domeless and cortex

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To identify orthologues of dome across the Lepidoptera, we performed tBLASTn searches using the previously annotated H. melpomene Hmel2 (Hm) and H.erato demophoon V1 (Hed) dome sequences against the genomes of Operophtera brumata V1 (Ob), Trichoplusia ni Hi5.VO2 (Tn), Bombyx mori ASM15162v1 (Bm), Manduca sexta 1.0 (Ms), Plodia interpunctella V1 (Pi), Amyeolis transitella V1 (At), Phoebis sennae V1.1 (Ps), Bicyclus anynana V1.2 (Ba), Danaus plexippus V3 (Dp), Dryas iulia helico3 (Di), Agraulis vanillae helico3 (Av), Heliconius erato lativitta V1 (Hel) genomes found on Lepbase (Challi et al., 2016). As a trichopteran outgroup, we used a recently published Pacbio assembly of Stenopsyche tienmushanensis (St) (Luo et al., 2018). Recovered amino acid translations were aligned using clustal omega (Madeira et al., 2019). The resulting alignments were used to produce a phylogenetic tree using PhyML (Guindon et al., 2010), based on a best fit model using AIC criterion (selected model was JTT + G + I+F). The tree was visualised and re-rooted to the Trichopteran outgroup using FigTree.

To confirm cortex as a cdc20 gene, we retrieved full-length protein homologs from TBLASTN searches and used them to generate a curated alignment with MAFFT/Guidance2 with a column threshold of 0.5. Guidance2 is an alignment reliability method that parses aligned residues while also maximising tree robustness (Sela et al., 2015), thus ruling out biases introduced from paralog-specific domains. We then constructed a maximum-likelihood tree using W-IQ-TREE with the ‘Auto’ function to find a best-fit model of substitution.

Tissue sampling and RNA-seq

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H. melpomene rosina and H. erato demophoon butterflies were collected around Gamboa, Panama; H. melpomene melpomene and H. erato hydara butterflies were collected around Puerto Lara, Darien, Panama. Methodology for sample preparation and sequencing was performed as previously descri Hanly et al., 2019. The datasets generated and/or analysed during the current study are available in the SRA repository (PRJNA552081). Reads from each species were aligned to the respective genome assemblies Hmel2 (Davey et al., 2016) and Herato_demophoon_v1 (Van Belleghem et al., 2017), using Hisat2 with default parameters (Kim et al., 2019). The genomes and annotations used are publicly available at http://www.lepbase.org. Reads were counted with HTSeq-count in union mode (Anders et al., 2015) and statistical analysis performed with the R package DESeq2 (Love et al., 2014). Comparisons for larvae were for whole hindwings, grouping samples by pattern form. Samples for pupal stages included wings that were dissected into anterior and posterior compartment as in Hanly et al., 2019, and were analysed in DESeq2 using the GLM:

individual+compartmentmorph

(Compartments: anterior hindwing [HA], posterior hindwing [HPo]). H. melpomene and H. erato were analysed separately; homology between genes was determined by reciprocal BLAST. The fold-changes and adjusted p-values given in Figure 2 reflect the primary contrast, showing the effect of pattern form given the effect of compartment. Read counts were determined for whole hindwings at all stages.

RT-qPCR

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The expression level of cortex in larval hindwings was further analysed by qPCR in H. e. demophoon and H. e. hydara. Three individuals were used for each morph. Each individual was an independent replicate (i.e. no pooling of samples). RNA was extracted from the hindwing tissue of larva using Trizol followed by DNase-treatment. An mRNA enrichment was performed using the Dynabeads mRNA purification kit (Thermo Fisher). The mRNA was then converted to cDNA by reverse transcription using the iScript cDNA synthesis kit (Bio-Rad). All reactions had a final cDNA concentration of 2 ng µl−1 and a primer concentration of 400 nM. The RT-qPCR was carried out using Brilliant III Ultra-fast SYBR green qPCR master mix (Agilent Technologies), on a AriaMx Real-time PCR system (Agilent Technologies) according to manufacturer’s instructions. The PCR programme consisted of 95°C for 2 min followed by 40 cycles of 95°C for 5 s, 58°C for 30 s, and 70°C for 30 s. qPCR experiments were performed using three biological replicates, three technical replicates, and a no template control. Expression levels were normalised using the geometric mean of three housekeeping genes, eF1α, rpL3 and polyABP that have previously been validated for Heliconius numata (Piron Prunier et al., 2016). The relative expression levels were analysed using the R = 2−ΔΔCt method (Livak and Schmittgen, 2001). Primer specificity was confirmed using melting curve analysis and the PCR products were checked on a 2% (w/v) agarose gel. The primer efficiency of each gene was calculated using the standard curve given by a 10-fold serial dilution of cDNA (1, 10−1, 10−2, 10−3, 10−4) and regression coefficient (R2) values.

In situ hybridisations

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Fifth-instar larval wing disks and whole mount in situ hybridisations were performed following a published procedure (Martin and Reed, 2014) and imaged using a Leica S4E microscope (Leica Microsystems). Riboprobe synthesis was performed using the following primers from a fifth-instar wing disc cDNA library extracted from H. melpomene:

Forward primer 5’-CCCGAGATTCTTTCAGCGAAAC-3’ and Reverse primer 5’- ACCGCTCCAACACCAAGAAG-3’. Templates for riboprobes were designed by attaching a T7 promoter through PCR and performing a DIG labelled transcription reaction (Roche). The same H. melpomene probe was used in all in situ hybridisation experiments. The resulting probe spanned from Exon two to Exon 7 and was 841 bp long.

Immunohistochemistry and image analysis

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Pupal wings were dissected around 60–70 hr post-pupation in PBS and fixed at room temperature with fix buffer (400 µl 4% paraformaldehyde, 600 µl PBS 2 mM EGTA) for 30 min. Subsequent washes were done in wash buffer (0.1% Triton-X 100 in PBS) before blocking the wings at 4°C in block buffer (0.05 g bovine serum slbumin, 10 ml PBS 0.1% Triton-X 100). Wings were then incubated in primary antibodies against Cortex (1:200, monoclonal rabbit anti-Cortex) at 4°C overnight, washed, and added in secondary antibody (1:500, donkey anti-rabbit lgG, AlexaFlour 555, ThermoFisher Scientific A-31572). Before mounting, wings were incubated in DAPI with 50% glycerol overnight and finally transferred to mounting medium (60% glycerol/40% PBS 2 mM EGTA) for imaging. Z-stacked two-channelled confocal images were acquired using a Zeiss Cell Observer Spinning Disk Confocal microscope.

CRISPR/Cas9 genome editing

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Guide RNAs were designed corresponding to GGN20NGG sites located within the cortex coding region and across putative CREs using the program Geneious (Kearse et al., 2012). To increase target specificity, guides were checked against an alignment of both H. melpomene and H. erato re-sequence data at the scaffolds containing the cortex gene (Moest et al., 2020; Van Belleghem et al., 2017), and selected based on sequence conservation across populations. Based on these criteria, each individual guide was checked against the corresponding genome for off-target effects, using the default Geneious algorithm. Guide RNAs with high conservation and low off-target scores were then synthesised following the protocol by Bassett and Liu, 2014. Injections were performed following procedures described in Mazo-Vargas et al., 2017, within 1–4 hr of egg laying. Several combinations of guide RNAs for separate exons at different concentrations were used for different injection experiments. For H. charithonia, we used the H. erato-specific guides, and for H. hecale, we used the H. melpomene guides.

Genotyping

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DNA was extracted from mutant leg tissue and amplified using oligonucleotides flanking the sgRNAs target region. PCR amplicons were column purified, subcloned into the pGEM-T Easy Vector System (Promega), and sequenced on an ABI 3730 sequencer.

ATAC-seq

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H. melpomene rosina and H. erato demophoon butterflies were collected around Gamboa, Panama; H. melpomene melpomene and H. erato hydara butterflies were collected around Puerto Lara, Darien, Panama. Caterpillars of each species were reared on their respective host plants and allowed to grow until the wandering stage at fifth instar. Live larvae were placed on ice for 1–2 min and then pinned and dissected in 1× ice cold PBS. The colour of the imaginal discs, as well as the length of the lacunae, gradually change throughout the larva’s final day of development, so that they can be used to confirm the staging inferred from pre-dissection cues (Reed et al., 2008). All larvae used for this project were stage 3.5 or older. ATAC-seq protocol was based on previously described methodology (Lewis and Reed, 2019) and edited as follows. The imaginal discs were removed and suspended whole in 350 µl of sucrose solution (250 mM d-sucrose, 10 mM Tris–HCl, 1 mM. MgCl2, 1× protease inhibitors [Roche]) inside labelled 2 ml dounce homogenisers (Sigma-Aldrich) for nuclear extraction. Imaginal discs corresponding to the left and right hindwings were pooled. After homogenising the tissue on ice, the resulting cloudy solution was centrifuged at 1000 rcf for 7 min at 4 °C. The pellet was then resuspended in 150 µl of cold lysis buffer (10 mM Tris–HCl, 10 mM NaCl, 3 mM MgCl2, 0.1% IGEPAL CA-630 [Sigma-Aldrich], 1× protease inhibitors) to burst the cell membranes and release nuclei into the solution. Samples were then checked under a microscope with a counting chamber following each nuclear extraction, to confirm nuclei dissociation and state and to assess the concentration of nuclei in the sample. Finally, based on these observations, a calculation to assess number of nuclei, and therefore DNA, to be exposed to the transposase was performed. This number was fixed on 400,000 nuclei, which is the number of nuclei with ~0.4 Gb genomes (H. erato genome size) required to obtain the amount of DNA for which ATAC-seq is optimised (Buenrostro et al., 2013). For H. melpomene, this number was 500,333, since the genome size of H. melpomene is 0.275 Gb. (Buenrostro et al., 2013). For quality control, a 15 µl aliquot of nuclear suspension was stained with trypan blue, placed on a hemocytometer and imaged at 64×. After confirmation of adequate nuclear quality and assessment of nuclear concentration, a subsample of the volume corresponding to 400,000 nuclei (H. erato) and 500,333 (H. melpomene) was aliquoted, pelleted 1000 rcf for 7 min at 4°C and immediately resuspended in a transposition mix, containing Tn5 in a transposition buffer. The transposition reaction was incubated at 37°C for exactly 30 min. A PCR Minelute Purification Kit (Qiagen) was used to interrupt the tagmentation and purify the resulting tagged fragments, which were amplified using custom-made Nextera primers and a NEBNext High-fidelity 2× PCR Master Mix (New England Labs). Library amplification was completed between the STRI laboratory facilities in Naos (Panama) and Cambridge (UK). The amplified libraries were sequenced as 37 bp paired-end fragments with NextSeq 500 Illumina technology at the Sequencing and Genomics Facility of the University of Puerto Rico.

Topology weighting by iterative sampling of subtrees (Twisst) analysis

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We applied the phylogenetic weighting strategy Twisst (topology weighting by iterative sampling of subtrees; Martin and Van Belleghem, 2017) to identify shared or conserved genomic intervals between sets of Heliconius melpomene and Heliconius cydno populations with similar phenotypes around the cortex gene locus on chromosome 15. Given a tree and a set of pre-defined groups Twisst determines a weighting for each possible topology describing the relationship of groups or phylogenetic hypothesis. Similar to Enciso-Romero et al., 2017 we evaluated the support for two alternative phylogenetic hypotheses using genomic data obtained from Moest et al., 2020. Hypothesis one tested for monophyly of samples that have a dorsal yellow hindwing bar. This comparison included the geographic colour patterns morphs with a dorsal hindwing bar H. m. rosina, H. c. weymeri weymeri, H. c. weymeri gustavi and H. pachinus versus the all-black dorsal hindwing morphs H. m. vulcanus, H. m. melpomene (French Guiana), H. m. cythera, H. c. chioneus and H. c. zelinde. Hypothesis two tested for monophyly of samples that have a ventral yellow hindwing bar versus an all-black ventral hindwing. This comparison included the geographic colour patterns morphs with a ventral hindwing bar H. m. rosina, H. m. vulcanus, H. m. cythera, H. c. weymeri weymeri, H. c. weymeri gustavi and H. pachinus versus the all-black ventral hindwing morphs H. m. melpomene (French Guiana), H. c. chioneus and H. c. zelinde. Maximum-likelihood trees were built from sliding windows of 50 SNPs with a step size of 20 SNPs using PhyML v3.0 (Guindon et al., 2010) and tools available at https://github.com/simonhmartin/twisst (Martin, 2020).Only windows were considered that had at least 10 sites for which each population had at least 50% of its samples genotyped. Twisst was run with a fixed number of 1000 subsampling iterations.

Hi-C and virtual 4C plots

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Analysis of chromatin contacts between distal cis-regulatory loci and the cortex promoter region was performed as previously described (Lewis et al., 2019 PNAS, Lewis and Van Belleghem, 2020). In brief, Hi-C data produced from day three pupal H. e. lativitta wings was used to generate an empirical expected distribution and read counts for Hi-C contacts between 5 kb windows centred on the distal CRE and cortex promoter were used to determine the observed contacts between loci. Fisher’s exact test was then performed to determine significance of the observed contacts relative to those expected from the background model. Virtual Hi-C signal plots were generated using a custom python script (Ray et al., 2019).

Coverage depth analysis and TE genotyping

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High-depth whole-genome sequences of 16 H. melpomene, H. timareta, and H. erato subspecies were obtained from the European Nucleotide Archive, accession numbers can be found in Figure 8—source data 1. To assess structural variation putatively affecting the yellow phenotype, reads were mapped to the reference genomes of subspecies that lacked the yellow bar stored in the genome browser Lepbase, ‘hmel2.5’ for H. melpomene and H. timareta, and ‘Heliconius_erato_lativitta_v1’ for H. erato (Challi et al., 2016) with BWA mem (Li and Durbin, 2009). Median sequencing depths across the scaffold containing cortex were computed for all individuals (n = 79) in 50 bp sliding windows and a mapping quality threshold of 30 with the package Mosdepth (Pedersen and Quinlan, 2018). Window median depths were normalised by dividing them by the mean depth for the full scaffold per individual. We then averaged the normalised median depths of all individuals per subspecies, to visualise deviations from the mean sequencing depth across the region in geographically widespread subspecies with and without the yellow bar. We then genotyped across the putative H. melpomene deletion using the primers employed for CRISPR genotyping (See Figure 4—source data 2). The products were then cloned into the pGEM-T Easy Vector System (Promega) and sequenced them on an ABI 3730 sequencer from both directions using T7 forward and M13 reverse primers. Sequencing was performed from three separate colonies, and a consensus sequence was created based on an alignment of the three replicates from populations of H. m. melpomene and H. m. rosina.

SEM imaging

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Individual scales from wild-type and mutant regions of interest were collected by brushing the surface of the wing with an eyelash tool, then dusted onto an SEM stub with double-sided carbon tape. Stubs were then colour imaged under the Keyence VHX-5000 microscope for registration of scale type. Samples were sputter-coated with one 12.5 nm layer of gold for improving sample conductivity. SEM images were acquired on a FEI Teneo LV SEM, using secondary electrons and an Everhart-Thornley detector using a beam energy of 2.00 kV, beam current of 25 pA, and a 10 μs dwell time. Individual images were stitched using the Maps 3.10 software (ThermoFisher Scientific).

Morphometrics analysis

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Morphometric measurements of scale widths and ridge distances were carried out on between 10 and 20 scales of each type, using a custom semi-automated R pipeline that derives ultrastructural parameters from large SEM images (Day et al., 2019). Briefly, ridge spacing was assessed by Fourier transforming intensity traces of the ridges acquired from the FIJI software (Schindelin et al., 2012). Scale width was directly measured in FIJI by manually tracing a line, orthogonal to the ridges, at the section of maximal width.

Data availability

ATAC-Seq sequencing data have been deposited under ENA BioProject (accession number PRJEB43672). Raw data on morphometrics and high magnification images of mutants are available on Dryad (doi:https://doi.org/10.5061/dryad.8gtht76m0).

The following data sets were generated
    1. Livraghi L
    2. Hanly JJ
    3. Martin A
    (2021) Dryad Digital Repository
    Cortex cis-regulatory switches establish scale colour identity and pattern diversity in Heliconius.
    https://doi.org/10.5061/dryad.8gtht76m0
The following previously published data sets were used
    1. Hanly
    2. JJ
    3. Wallbank RWR
    4. Jiggins CDM
    5. cMillan WO
    (2019) NCBI BioProject
    ID SRAPRJNA552081. Wing RNAseq from Heliconius melpomene, Heliconius erato, Agraulis vanillae Raw sequence reads.

References

  1. Book
    1. Gilbert LE
    2. Forrest HS
    3. Schultz TD
    4. Harvey DJ
    (1987)
    Correlations of Ultrastructure and Pigmentation Suggest How Genes Control Development of Wing Scales of Heliconius Butterflies
    The Journal of research on the Lepidoptera.
  2. Book
    1. Lamas G
    (2004)
    Atlas of Neotropical Lepidoptera: Checklist Pt. 4a Hesperioidea-Papilionoidea
    Scientific Pub.
  3. Book
    1. Martin A
    2. Courtier-Orgogozo V
    (2017)
    Morphological Evolution Repeatedly Caused by Mutations in Signaling Ligand Genes
    In: Sekimura T, Nijhout H. F, editors. Diversity and Evolution of Butterfly Wing Patterns: An Integrative Approach. Springer. pp. 59–87.

Decision letter

  1. Patricia J Wittkopp
    Senior and Reviewing Editor; University of Michigan, United States
  2. Antonia Montiero
    Reviewer; National University of Singapore and Yale-NUS-College, Singapore

In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.

Acceptance summary:

This work shows how changes in butterfly wing pigmentation develop and evolve. More specifically, genetic analysis, analysis of gene expression, and characterization of scale structure was used to identify the likely causal genetic variation in the cortex locus that is responsible for the presence/absence of the yellow band on the wings of some Heliconius butterflies.

Decision letter after peer review:

[Editors’‌ ‌note:‌ ‌the‌ ‌authors‌ ‌submitted‌ ‌for‌ ‌reconsideration‌ ‌following‌ ‌the‌ ‌decision‌ ‌after‌ ‌peer‌ ‌review.‌ ‌What‌ ‌follows‌ ‌is‌ ‌the‌ ‌decision‌ ‌letter‌ ‌after‌ ‌the‌ ‌first‌ ‌round‌ ‌of‌ ‌review.]‌ ‌

Thank you for submitting your work entitled "The gene cortex controls scale colour identity in Heliconius" for consideration by eLife. Your article has been reviewed by 3 peer reviewers, one of whom is a member of our Board of Reviewing Editors, and the evaluation has been overseen by a Senior Editor. Reviewers 1 and 2 have opted to remain anonymous. Review 3 is from a collaborative peer-review group, and some members chose to share their identity publicly, as indicated below.

Our decision has been reached after consultation between two of the reviewers. Based on these discussions and the individual reviews below, we regret to inform you that your work will not be considered further for publication in eLife.

While the reviewers and editors feel that the topic of your work is timely and intriguing, the reviewers raise several issues with the study that would be difficult to address within the eLife revision window. For example, the reviewers propose that the major conclusions of the manuscript are not supported by the data presented, and that a full set of SEM data across all scale type color transformations should be presented. The reviewers also feel that, given the results presented, the relationship between cortex expression and the actual pigmentation remains unclear, and the sole phenotypic analysis is insufficient to make conclusions about the role of a gene in producing pigmentation pattern variation.

Reviewer #1:

This is an interesting but complex study that examines the role of a few genes in a previously mapped interval in being the "switch" gene that regulate the presence or absence of a yellow band in the wings of Heliconius butterflies. The study first examines whether there is a correlation between expression level of several (47) genes in the mapped interval in developing wings (or parts of wings) in two separate species of Heliconius each having a race with the yellow band and a race without the yellow band. This part of the study highlights three genes (among others) that show some pattern of differential regulation but shows that there is no simple correlation between the expression level of these three genes in either larval or pupal wings and the presence of the yellow band. The authors then examine the function of one of the genes in the interval, cortex, in scale color development by using CRISPR. They find that cortex crispant individuals display color changes across the whole wing, not just in the region of the yellow band. In particular the black scales (Type II) become white or yellow (Type I), and the red scales (Type III) also become white or yellow (although this last transformation is not documented at the SEM level). The authors examine, once again, the expression domain of the cortex gene, this time during pupal development with an antibody, and they find that the gene is expressed across the whole wing, supporting its functional effects also across the whole wing. They observe that cortex is expressed in multiple punctate domains in the nuclei of scale building cells, which are polyploid cells, and in a single punctate domain in the nucleus of non-scale building epidermal cells, which are not polyploid. They then test whether perhaps there are more of these punctate nuclei in the region of the yellow band, but they find no such correlation.

In the end the authors try to argue that either (1) cortex is the yellow-band switch gene they are after but that the switch is not in the form of a typical spatially expressed gene (in the shape of the yellow band) but perhaps in the form of some threshold or heterochronic mechanism (not clearly explained), or that (2) another gene in the mapped interval, not examined for function in this study, is instead the switch genes they are after, and which may (or may not) interact with cortex in the differentiation of the yellow band.

I believe the authors are trying hard to implicate cortex in some way, as the yellow band switch locus, but the data just does not support this. Instead the authors implicate cortex in scale color identity (the title of the manuscript). However, given that cortex (alone) cannot control a specific color either, because the effect of cortex on color is different in different parts of the wing, their model for how cortex acts is too simple and does not fit their data. A combinatorial genetic code for both scale color and morphology (see below), where cortex is simply one of the players (rather than a major switch/homeotic gene) is required to explain the data in this manuscript.

Furthermore there are several data missing from the manuscript that need to be added to support some of the conclusions drawn, and several other data that would be important to add for purposes of data replication across labs.

1) The authors claim that cortex converts Type II (black) scales into Type I (white/yellow) scales but their SEM data and scale morphological measurements presented in the supplement don't fully support this conclusion. These transformations vary from species to species (e.g. H. melpomene and H. erato show different degrees of transformation) and only some features of the scale are actually transformed (e.g., cross rib periodicity in both species, and scale width and length and ridge periodicity in H. melpomene). The remainder of the measurements show that cortex is not sufficient to convert scale Type II into scale Type I.

2) I suggest that the definition of the scale types presented should be made more explicit. What are scale types I, II and III really? In line 87 it is mentioned that these scale types are based on scale color and on scale morphology but what follows is just a description of the pigments found in each scale and not their morphology. Furthermore, the data presented in the manuscript suggests that color and morphology can be uncoupled with genetic perturbations of cortex, so, it is even useful to stick to this scale type nomenclature going forward? Something to consider.

3) There is a need for a new figure showing how the scale morphological measurements were actually conducted. There is no scale bar in the SEM images of yellow and black scales and this should be added. The SEM images used to represent a typical yellow WT scale and a transformed yellow scale of H. melpomene (in Figure 7) show very different densities of cross-ribs (but I am not even sure what exactly is being considered a cross-rib), yet the graph indicates that there is no difference between these scale types. This is confusing and needs clarification. Make sure you look up scale morphology nomenclature in Ghiradella 1991 (Applied Optics) to make sure you designate ribs (crossribs) and microribs appropriately. There seem to be quite a lot of differences in microrib density across Wt scales and transformed yellow scales in H. melpomene.

4) The authors claim that cortex converts Type III (red) scales into Type I (white) but they only describe conversions of Type II (black) into Type I (yellow) scales at the SEM level and don't provide any SEM images or quantitative data for the red to yellow, red to white, and black to white scale transformation. Adding these data is important to support the conclusions of the study.

5) I suggest the authors remove the dome-t and dome/washout gene data from the manuscript as 1) nothing about these genes is mentioned in the abstract; 2) the expression of these genes doesn't correlate with presence of the yellow band; 3) the genes are not investigated at the functional level; 4) the whole gene duplication issues surrounding these genes make the whole manuscript more difficult to read and does not, in the end, contribute to the main story that yielded results – which is the function of cortex in scale development. The function of these genes might still be worthy of investigating using CRISPR at a later date, and perhaps it would be useful to include the expression pattern data in that subsequent paper. This is merely a suggestion that I believe will make this manuscript less heavy and easier to read by focusing the reader's attention on the main points of this story.

6) Pigmentation and scale morphology is most likely controlled at the pupal stages of wing development and by measuring RNA levels of candidate switch genes at just two time points during pupal development (36hrs and 60-70 hrs after pupation) you may not have sampled the correct time window for yellow band differentiation. Several genes are expressed only during the first 16-30 hrs of pupal development, in species that need 7 days for pupal development (see Monteiro et al. 2006 for genes such as Wg, pMad and Sal) so sampling wings (for RNA-seq and antibody stains) at 36hrs and 60-70 hours may not be an ideal sampling strategy going forward.

7) The authors mention that because cortex causes changes in both scale color and morphology this suggests "that cortex acts during early stages of scale cell fate specification rather than during the deployment of effector genes". This conclusion needs more discussion. Matsuoka and Monteiro (2018) showed that knockout of the gene yellow, an effector gene at the end of a gene regulatory network for melanin pigment production, also led to both changes in scale color and morphology. These authors proposed instead that absence of certain pigments on the wing, such as dopa melanin, caused chitin to polymerize differently and form an extra lamina that prevent the windows from forming in the scales (just as seen in cortex mutants). The authors should consider and evaluate this alternative explanation in their discussion.

8) Did the authors examine whether there were protein coding changes between the 47 genes in the mapped interval between the yellow and black races? Please mention whether this was done. Please also upload the sequences of the genes that were studied and provide accession numbers for these sequences.

Reviewer #2:

This manuscript explores the role of the gene cortex in the specification of wing scales in the butterfly genus Heliconius. Species of Heliconius butterflies are notorious for their reciprocal mimicry of wing color patterns. Several genes are known to control variation of specific color pattern elements within and between species, cortex is one of them. The authors combine RNAseq analysis across wing development, in situ hybridizations, antibody stainings and analysis of crispr somatic mutations to dissect the role of cortex in the specification of scales. Their main claim is that cortex imparts scale identity (color, morphology), namely type II and type III identity.

Although this paper includes a substantial amount of work and a number of interesting observations, I am not sure what can really be concluded in the end, and several results would need follow-up experiments to reach a stable conclusion.

The strongest part, in my opinion, is the analysis of somatic mutant clones of cortex in the wings of different species. The authors show that the lack of cortex consistently results in the conversion of type II and type III scales into type I scales, and thereby demonstrate the necessity of this gene for type II and III identity. This is solid, interesting, but not a novel concept from a genetic or developmental biology point of view. There are countless examples in the 1990s literature of genes whose mutations results in such shifts in cell identity (e.g., poxn and cut in the peripheral nervous system of flies).

From this result, two questions emerge: how and when does cortex assign this identity during development? And how does cortex explain the variation in color pattern among Heliconius morphs and species? Although the paper discusses these two questions, I find the answers unclear and the results confusing.

The authors first examine the expression dynamics of cortex. They re-annotated the 47-gene genomic interval where cortex maps and analyzed the differential expression of all genes in the interval, across developmental stages, across species and morphs and also compared wing compartments.

1. Their main conclusion is that cortex is the most likely candidate in this interval to explain color pattern variation. I am not sure why the authors did this. I thought this was already clearly established from a previous paper (Nadeau et al. 2016, Nature).

2. Moreover, the explanations of the differential gene expression (DGE) analysis are often too shallow to really understand what the authors really did, including the method description. The figures are poorly annotated and it's difficult to understand if there are replicates in the RNA-seq analysis.

3. One striking result from this part, is that the DGE suggests that cortex is differentially expressed in the 5th instar larvae between 2 morphs of Heliconius erato and 2 morphs of Heliconius melpomene, but the differential expression goes into opposite directions between these 2 species. How could the same phenotypic variation between morphs of 2 species be caused by opposite DGE? They authors note that it is interesting but do not comment or analyze further.

4. They pursue their investigation with in situ hybridization on 5th larval instar wings and mitigate the notion of a spatial correlation between cortex transcripts spatial distribution and color patten elements proposed by Nadeau et al., 2016. Here again, the figure would benefit from better annotation. The authors indicate subtle differences in the local distribution of cortex transcripts between morphs but do not really conclude anything from their observation. They also give no indication of sample size or replicates, which I find unsettling given the noise associated with this experiment. I am not sure what this figure really adds to the published work, or to the present manuscript.

5. Finally, the authors examine the distribution of Cortex protein in late (2-day pupa) developing wings with a polyclonal antibody. They find, surprisingly, that the protein is distributed more or less uniformly in the wing epithelium and localizes to the cell nuclei. While this is very different from the patterned transcript distribution, it is consistent with the somatic mutant clone analysis that showed that any mutated cell at any position of the wing displayed a phenotype. But this opens many questions: what is the origin of the apparent difference in expression between protein and transcripts? Is cortex secreted and it diffuses across the wing? Or is the transcript expression spatially dynamic and the protein distribution revealed by the authors reflects the temporal integration of this expression? And if Cortex is present and functional across the wing, how does it produce discrete pattern elements?

The authors conclude their paper with a figure suggesting that cortex specifies typeII/III scale identity early during wing disc development and that the distinction between type II and type III is subsequently governed by the gene optix at a later stage. But what substantiates the idea that cortex imparts cell type identity early on? What does Cortex larval (5th instar) distribution look like? Is it as uniform as that of later stages? The data presented here do not offer the temporal or functional resolution to support this conclusion.

In conclusion, this paper shows that the mutation of the gene cortex results in scale type transformation, but fails to explain or suggest how this may happen during development. It also does not suggest how cortex may control the "fantastically diverse" pattern variation in Heliconius. I find this study insufficient to justify publication in eLife.

Reviewer #3:PREreview of "The gene cortex controls scale colour identity in Heliconius"

Authored by Luca Livraghi et al. and posted on bioRxiv DOI: 10.1101/2020.05.26.116533

Review authors in alphabetical order of last name:

Monica Granados, Vinodh Ilangovan ORCiD (http://orcid.org/0000-0002-3445-5383), Katrina Murphy, Aaron Pomerantz

This review is the result of a virtual, live-streamed preprint journal club organized and hosted by PREreview and eLife. The discussion was joined by 17 people in total, including researchers from several regions of the world.

Overview and take-home message: In this preprint, Livraghi et al. present noteworthy advances in evolutionary biology by characterizing the role of cortex gene in multiple Heliconius butterfly species, which is responsible for the wing patterns: yellow bar or the Type I scale cell fates (white/yellow). The authors identified cortex gene's major role in sympatric speciation, the modulation of convergent wing patterns, and the regulation of scale identity in multiple Heliconius species, which naturally have different niches to help explain different co-mimetic morphology. Livragi's team provides strong evidence for the cortex gene as one of the earliest regulators and its ability to set the differentiation of scale cells in a molecular switch fashion from yellow to red/black at a particular development stage through distal localization. This important discovery on the role of cortex gene fills a gap in our existing knowledge about the gene's ability to control scale cell identity and wing color patterns. Since this work is of significant interest in evolutionary biology, we outlined some concerns below that could be addressed in the next version.

Positive feedback:

* We strongly recommend this preprint to others/for peer review. In addition, we recommend this article to trainees as educational material to learn evolutionary developmental biology through interactive tutorials.

* The authors have provided a good amount of novel results and have utilized current tools to address their questions.

* This research fills a gap in our understanding of wing patterning in Heliconius while doing so in a very comprehensive way across multiple species and using techniques that systematically detail the association between gene expression and phenotype.

* It was interesting to learn that the cortex gene doesn't follow the typical pattern gene paradigm. We do not have many examples of integrator genes like cortex, which give binary outputs from a network of genes and integrate elements to produce a singular output.

* This is a textbook example and is important for evolutionary development and mimicry studies. It is hard to find and/or work with a developmentally important gene that is amenable for genetic modification and still be able to work with viable offspring and have it be relevant for evolution.

The current cortex protein data as seen in Figure 6 adds novel data to the manuscript.

Thanks to the authors for setting a great example of showing modeling information. The graphics are visually appealing and convey complex information well.

* This preprint sets up a good next step of how cortex evolved in a more broad context. We know the cortex gene is potentially implicated in wing pattern evolution in other distantly related butterflies and moths (e.g. peppered moth Biston betularia) and in possible roles of evolution/speciation by pattern changes due to genomic inversions at cortex locus.

* The authors did a good job of creating a well-composed manuscript. Yellow bar with one species had a contradiction but did reconcile with further research questions.

* Definitely, [the results are likely to lead to future research] especially with understanding how a cell cycle regulator affects developmental cell fates in terms of these scale colors and structures.

* Antibodies can open up future research. This research team figured out three elements and there are possibly more to explore. Future research might investigate how cortex possibly regulates endocycling and what this means for color identity determination.

Major concerns:

1. The use of the term "race" to define butterflies with specific phenotypes needs to be revised to clines or strains or variants. "Race" is a social construct and not a biological reality and we strongly suggest revising this term.

2. The authors state that cortex and dome/wash genes are controlled by inversion (see Line 375, page 19). Does the strain they engineered have/carry the inversion?

– We are aware that inversion for species is complex – strains, genetic background – starting material for inversion.

– Inversion events occurred millions of years ago in the loci contributing to the wing pattern. Authors describe the first generation of CRIPSR knock-outs in Heliconius sp. and hence we suggest to include further information.

3. We strongly suggest the authors elaborate on their qRT-PCR analysis pipeline. Did the authors follow MIQE guidelines (https://academic.oup.com/clinchem/article/55/4/611/5631762) in their quantitative real time PCR assays?

4. More explanation could be provided for cortex protein experiments. Figure 6 could explicitly say what developmental stage/time after pupation (they report this in the Methods section) and the rationale behind presenting data for this stage in development.

– Maybe perform a systematic developmental time series of cortex immunostaining experiments?

5. We recommend the authors mention institutional or local animal care ethical approval and safety regulations in the field working on Heliconius sp. for setting best practice reporting standards.

6. We suggest to clarify the lack of a clear correlation between in situ stains and the mutational effects of cortex CRISPR knock-outs.

7. Could a sized-down Figure S10 be added to Figure 6 in the manuscript to provide more information about the nuclear ploidy and cortex antibody signal? Even no association is informative and helps the reader think about the connection between color/endopolyploidy.

Acknowledgments:

We thank all participants for attending this preprint journal club. We especially thank those that engaged in the discussion. Their participation contributed to both a constructive and lively discussion.

Below are the names of participants who wanted to be recognized publicly for their contribution to the discussion:

Monica Granados | PREreview | Leadership Team | Ottawa, ON

Vinodh Ilangovan | Labdemic - Founder |Postdoc | @I_Vinodh

Katrina Murphy | PREreview | Project Manager | Portland, OR

Aaron Pomerantz | UC Berkeley/Marine Biological Laboratory | Ph.D. Candidate | Berkeley, CA/Woods Hole, MA

[Editors’‌ ‌note:‌ ‌further‌ ‌revisions‌ ‌were‌ ‌suggested‌ ‌prior‌ ‌to‌ ‌acceptance,‌ ‌as‌ ‌described‌ ‌below.]‌

Thank you for submitting your article "Cortex cis-regulatory switches establish scale colour identity and pattern diversity in Heliconius" for consideration by eLife. Your article has been reviewed by 3 peer reviewers, and the evaluation has been overseen by Patricia Wittkopp as the Senior and Reviewing Editor. The following individual involved in review of your submission has agreed to reveal their identity: Antonia Montiero (Reviewer #1).

The reviewers have discussed their reviews with one another, and the Reviewing Editor has drafted this to help you prepare a revised submission.

Essential revisions:

1) In line 350 the authors mention that the presence of an upper lamina is an important morphological feature of yellow/white scales and then they cite Matsuoka and Monteiro (2018). This paper shows, instead, that the white lamina forms in scales that are brown in color, not yellow nor white. In addition, several papers have shown the presence of this type of upper lamina in silver colored scales. While the presence of this lamina may indeed be a feature of Type I scales in Heliconius butterflies, I would refrain from attaching too much importance to this lamina regarding the formation of a particular color. The color changes observed in Heliconius butterflies are most likely caused by changes in pigmentation than by changes in the presence/absence of this lamina.

2) Line 160: Spell out what APC/C motifs are.

3) In Figure 9e I cannot really see/understand the effect of cortex disruptions on red scale phenotypes – both the SEM image provided and the low-resolution image of the red-colored scale are low quality. Please provide higher quality images for these data. In particular, the SEM data does not show a scale type III converting into a scale type I.

4) Line 375: Why "key early scale cell specification switch"? What does "early" refer to and what data indicates time of gene activity in the manuscript?

5) Line 376: How does the sentence above lead to the next sentence "and thus has the potential to generate much broader pattern variation than previously described patterning genes"? I don't follow what the authors are trying to convey here.

6) Lines 447-449 need revision.

7) Crossribs are sometimes written as cross-ribs. Be consistent.

8) Ln 85 Capitalize van Belleghem.

9) Lns 92-99. The authors made a marked improvement in detailing the morphological differences in the text. The authors also provide a nice visual summary of the pigment of morphological differences in Figure 9f. However, the readers suffer by not being able to connect the text in the introduction to the illustrations in Figure 9f. I understand the challenge is that figures must be referenced in order, and it definitely makes sense for Figure 9f to be placed with the CRISPR images. If possible, I would urge the journal to allow the authors to add "(see Figure 9f)" in lines 92-99, as I think it would help the reader and retain the author's figure order. The alternative would be including a version of the cartoon in 9F in Figure 1, which could be considered since the scale structure and fate are such a major component of the study.

10) Lns 130-137. I agree with Reviewer 1 that the dome/wash results detract from the main points and flow of the paper. However, I don't agree that they should be removed. Rather, I recommend that the detailed description of the dome duplication be moved to supplementary materials, as it seems the primary purpose of including the duplication description is to justify analyses were performed and interpreted accurately.

11) Ln 237. The authors state "the sharp boundaries observed between wild-type and mutant scales suggest cortex functions in a cell-autonomous manner, with little or no communication between neighbouring cells", however, I'm not convinced of this. It seems the mutant scales of single individuals are more often localized in wing regions, often with neighboring clusters of mutant scales. I understand that the sharp boundaries may suggest little cell communication, later in wing pattern development. However, the localization of clusters suggests cortex may impact communication between cells in early wing cell replication. This doesn't have much of an impact on their findings, but the authors may want to consider tempering the interpretation.

12) Ln 352-353. The authors state "…cortex is necessary for the development of lamellar structures in Heliconius scales.". This statement is too broad and encompassing. Figure 9 shows that cortex appears to be required to develop Type II and III scales with open upper lamina. In this regard, cortex is not required for the development of lamellar structures but rather required to regulate the development of architectural variation in lamellar structures. This may seem minor, but as worded it reads that "cortex is necessary for the development of lamellar structures", which I don't agree is supported by the data.

13) Ln 393-398. I find the authors attempt to explain the difference in the direction of cortex DGE between species to be quite brief and hand-waving. I'm not clear what is meant by "some relatively subtle developmental heterochrony between the two species would capture the state of differentially expressed genes in a different dynamic step." It seems the timing and levels of cortex expression could be quite precise and variable over short periods of time. In such cases, the limited sampling in each species could simply be detecting different points. In other words, it may be more informative for the reader to have the authors state that the current resolution may simply be insufficient to resolve and compare the precise cellular functions of cortex in the two species. And, that the difference between species suggests more detailed examination, perhaps even real-time expression data of cortex, may be needed.

14) Figure 10. I would consider including WntA in Figure 10. The timing of expression of WntA effecting melanic pattern is well resolved (5th instar), the authors discuss how WntA and cortex may interact, so it would seem reasonable to include WntA in Figure 10, so that the figure offered the best present model for the timing and placement of each major color patterning gene during wing development.

15) Ln 510. Italicize H. melpomene and H. erato.

16) Ln 684. Ray et al. 2019 not included in References.

17) Ln 885-886. McMillan et al. 2020 reference is incomplete.

18) Figure S15. Please remove "Lorem ipsum" from the "H. erato ridge periodicity" plot.

19) The introduction lacks a short description of the concrete wing colour patterns of the studied Heliconius species. It would be helpful for some readers to have this information between lines 100-106: Colour stripes, location on the wing, colour polymorphism,…

20) I agree with a previous reviewer that the data on cortex and dome/wash differential gene expression could be removed from this manuscript (although it should be published elsewhere). However, in the current form the manuscript starts with results that are difficult to interpret and this is confusing. The rational to investigate cortex function is already given by Nadeau et al. 2016.

21) The manuscript could therefore gain clarity if the authors re-arrange their very interesting findings. 1) CRISPR mosaics to characterize cortex function and SEM analysis on scale type 2) Identification and characterization of the CRE's and the role in stripe determination 3) cortex expression analysis that does not seem to associate with a hindwing stripe.

22) Mosaic loss of function of cortex apparently reveals a loss of melanic (Type II) and red (Type III) scales. The authors note sharp boundaries between wild-type and mKO scales and suggest cortex functions to be cell-autonomous with little or no communication between neighbouring cells. However, in Figure 4b and S10 they also report intermediate white/red scale phenotypes in scales of the "red band element". These scales sometimes have a patchy/granular red colouration. The authors further note an asymmetric deposition of pigment across the scale but should better point out what this means. Is the result conform with / contradicting their interpretation of a cortex mediated scale identity switch? Could the red pigment presence have non-autonomous sources from the surrounding tissue?

23) The Figures are very nice, but many legends lack a certain degree of precision in the description of each panel. The authors need to revise this with care, this has already been pointed out by a previous reviewer. Please indicate what the illustrations literally present. For example, Figure 1a, horizontal black bars are coding sequences? gene predictions? mapped transcripts? other elements? What reference genome assembly? Do they indicate the 47 candidate genes or just a small portion of it? Wing patterns are present on the dorsal or ventral side of the wing? Figure 1B: Are yellow and blue dots reported sampling locations?

24) Conclusion: The first part (lines 492 – 505) appears to be redundant with lines 511 -514 in the second paragraph. Maybe integrate the first paragraph into the discussion.

Reviewer #1:

In this paper the authors associate genetic variation in regulatory sequences of the gene cortex with the presence/absence of a yellow band of color in the wings of two species of Heliconius butterflies. They show that cortex is spatially regulated in larval wings, but the expression of this gene does not correlate with the presence or absence of the yellow band. Then they show that the gene is expressed in the nuclei of all cells of the pupal wing. By disrupting cortex they show that black cells (Type II) become white or yellow (Type I), and red scales (Type III) become paler across the whole wing.

By examining open regions of chromatin around cortex, they discover that at least in one of the species, the insertion of two transposable elements in an open region of chromatin associates with the presence of the yellow band. They show that disrupting this regulatory region in a race of butterflies that does not contain the yellow band, nor the TE insertions, leads to the loss of the black color in a band-like shape, and the appearance of yellow scales in that region of the wing. They identify a different region of open-chromatin in the other Heliconius species that when disrupted also leads to the transformation of black scales into yellow scales in a band-like pattern.

The authors achieved their aims and the results support their conclusions.

The strength of this manuscript lies in the use of multiple approaches to identify the likely causal genetic variation in the cortex locus that is responsible for the presence/absence of the yellow band. The only weakness (if I can call it that) is that it is still not clear how cortex, which is also expressed in the nuclei of the yellow scales in races that supposedly have the TE insertion and closed chromatin in that enhancer region, fail to develop black scales in that region of the wing.

This is one of the first few papers that examines the function of specific open regions of chromatin in the DNA of butterfly species using CRISPR-Cas9. The main novelty of this paper is in identifying how a gene with a homogeneous expression pattern across the wing (during the pupal stage) can still have "hidden" modular regulatory regions that drive unique functions (albeit not expression) is specific regions of the wing.

This work reminds me of the regulation of the vestigial gene in the wings of Drosophila. vestigial also has homogeneous expression across the wing pouch but it achieves this homogeneous expression via two separate enhancers that have complementary expression patterns.

Reviewer #3:

The gene cortex was reported to control mimicry and crypsis in butterflies (Nadeau et al. 2016). This study finds cortex function to be essential for Heliconius wing scale type determination at the transition from scale type I to type II / III. This is shown by genetic loss of function assays and characterization of scale structure by scanning electron microscopy. In particular, the authors show that cortex function is essential for scale type determination throughout the wings that mainly contain type II/III scales in Heliconius butterflies. This is revealed by a series of CRISPR/Cas9 derived somatic mosaic mutants in diverse genetic backgrounds and species. Expression of a specific yellow (type I scale) hind-wing stripe in some Heliconius melpomene and H. erato morphs was found to depend on molecular tinkering and malfunction of a discrete cortex cis-regulatory element (CRE). The authors identify distinct CRE's in both species by ATAC-seq open chromating mapping and narrow down candidate regions by genetic association to the yellow stripe. Hi-C assays were used to verify that the elements indeed interact with the cortex promoter. However, a possible regulation of other genes cannot be excluded. Tinkering of these elements appears to be a natural mechanism in wing colour pattern evolution, since a yellow stripe morph is associated with an insertion of a transposable element in the corresponding region in the morph H. melpomene timareta. Expression of cortex was investigated at different developmental stages by in-situ hybridization and immuno-staining techniques. Cortex transcripts reveal complex expression pattern that do not seem to be associated with the yellow hindwing stripe in corresponding morphs. Cortex protein is localized in the cell nucleus throughout wing cells and future studies must resolve how cortex regulatory elements determine such specific stripe-pattern. This article contrasts the widespread expression of cortex with a complex transcriptional regulation of this gene and scale type transition in discrete wing domains. The authors argue that cortex is a prime target for wing pattern evolution, acting as "input-output" module, whereby complex spatio-temporal information is translated to determine scale type and colour.

Author response:

[Editors’ note: the authors resubmitted a revised version of the paper for consideration. What follows is the authors’ response to the first round of review.]

Reviewer #1:

[…] In the end the authors try to argue that either (1) cortex is the yellow-band switch gene they are after but that the switch is not in the form of a typical spatially expressed gene (in the shape of the yellow band) but perhaps in the form of some threshold or heterochronic mechanism (not clearly explained), or that (2) another gene in the mapped interval, not examined for function in this study, is instead the switch genes they are after, and which may (or may not) interact with cortex in the differentiation of the yellow band.

I believe the authors are trying hard to implicate cortex in some way, as the yellow band switch locus, but the data just does not support this. Instead the authors implicate cortex in scale color identity (the title of the manuscript). However, given that cortex (alone) cannot control a specific color either, because the effect of cortex on color is different in different parts of the wing, their model for how cortex acts is too simple and does not fit their data. A combinatorial genetic code for both scale color and morphology (see below), where cortex is simply one of the players (rather than a major switch/homeotic gene) is required to explain the data in this manuscript.

Furthermore there are several data missing from the manuscript that need to be added to support some of the conclusions drawn, and several other data that would be important to add for purposes of data replication across labs.

1) The authors claim that cortex converts Type II (black) scales into Type I (white/yellow) scales but their SEM data and scale morphological measurements presented in the supplement don't fully support this conclusion. These transformations vary from species to species (e.g. H. melpomene and H. erato show different degrees of transformation) and only some features of the scale are actually transformed (e.g., cross rib periodicity in both species, and scale width and length and ridge periodicity in H. melpomene). The remainder of the measurements show that cortex is not sufficient to convert scale Type II into scale Type I.

Thank you for bringing this to our attention. We agree that the data does not clearly show complete homeosis. We therefore have softened our language, arguing for incomplete homeosis, but show that major structural rearrangements do accompany cortex functional perturbations. However, our cortex KO scales do show the presence of a lamina covering the scale windows as well as the presence of microribs joining the longitudinal ridges, features unique to otherwise wild-type Type I scaleswhich always occur in wild type and mutant Type I scales and never occur in type II or type III scales. We believe that nanomophometric measurements might not reflect full homeosis not because of a lack of transformation, but because of small positional differences known to affect scale structure across the wing (see Day et al., 2019). We believe the qualitative nature of the SEM images clearly reflect these structural changes, which are at least sufficient to show cortex perturbations affect both pigmentation state and ultrastructural features in a consistent way. We have also uploaded all SEM images, which include a large number of scales that consistently show homeosis in microribs and lamina, to the Dryad data repository.

2) I suggest that the definition of the scale types presented should be made more explicit. What are scale types I, II and III really? In line 87 it is mentioned that these scale types are based on scale color and on scale morphology but what follows is just a description of the pigments found in each scale and not their morphology. Furthermore, the data presented in the manuscript suggests that color and morphology can be uncoupled with genetic perturbations of cortex, so, it is even useful to stick to this scale type nomenclature going forward? Something to consider.

We agree. We have expanded upon these definitions in the introduction (See lines 89-99). We also added the citation of Janssen, Monteiro and Brakefield 2001, which argues for a strong coupling between pigmentation and ultrastructure based on wounding experiments.

3) There is a need for a new figure showing how the scale morphological measurements were actually conducted. There is no scale bar in the SEM images of yellow and black scales and this should be added. The SEM images used to represent a typical yellow WT scale and a transformed yellow scale of H. melpomene (in Figure 7) show very different densities of cross-ribs (but I am not even sure what exactly is being considered a cross-rib), yet the graph indicates that there is no difference between these scale types. This is confusing and needs clarification. Make sure you look up scale morphology nomenclature in Ghiradella 1991 (Applied Optics) to make sure you designate ribs (crossribs) and microribs appropriately. There seem to be quite a lot of differences in microrib density across Wt scales and transformed yellow scales in H. melpomene.

We apologise for the confusion in nomenclature. We have since clarified the structures as well as updated the SEM figure to reflect this (See Figure 9, f). The precise methodology relating to the scale measurements can be found in Day et al., 2019. We believe this should be enough to locate details on measurement reproducibility, but are happy to include a reproduction of the figure from Day et al. 2019 if the reviewers request this.

4) The authors claim that cortex converts Type III (red) scales into Type I (white) but they only describe conversions of Type II (black) into Type I (yellow) scales at the SEM level and don't provide any SEM images or quantitative data for the red to yellow, red to white, and black to white scale transformation. Adding these data is important to support the conclusions of the study.

We agree and have added the requested images and measurements to the new manuscript (see Figure 9 and Supplementary File 15).

5) I suggest the authors remove the dome-t and dome/washout gene data from the manuscript as 1) nothing about these genes is mentioned in the abstract; 2) the expression of these genes doesn't correlate with presence of the yellow band; 3) the genes are not investigated at the functional level; 4) the whole gene duplication issues surrounding these genes make the whole manuscript more difficult to read and does not, in the end, contribute to the main story that yielded results – which is the function of cortex in scale development. The function of these genes might still be worthy of investigating using CRISPR at a later date, and perhaps it would be useful to include the expression pattern data in that subsequent paper. This is merely a suggestion that I believe will make this manuscript less heavy and easier to read by focusing the reader's attention on the main points of this story.

We thank the reviewer for the suggestion. However, we believe it is useful to point out there are multiple genes at the locus that show patterns of differential expression, especially as these genes have been implicated in pattern evolution in other studies and might be useful for future studies to follow up on.

6) Pigmentation and scale morphology is most likely controlled at the pupal stages of wing development and by measuring RNA levels of candidate switch genes at just two time points during pupal development (36hrs and 60-70 hrs after pupation) you may not have sampled the correct time window for yellow band differentiation. Several genes are expressed only during the first 16-30 hrs of pupal development, in species that need 7 days for pupal development (see Monteiro et al. 2006 for genes such as Wg, pMad and Sal) so sampling wings (for RNA-seq and antibody stains) at 36hrs and 60-70 hours may not be an ideal sampling strategy going forward.

This is an important point. While we agree that we have likely not captured the terminal differentiation factors, we believe our new data clearly shows that cortex is a key factor that establishes the identity of Type II and III scales early in development. Furthermore, population genetic scans show that regions around the cortex gene are the only ones that are differentiated between populations differing in the presence of the yellow band, suggesting this region must be the causative locus, and not terminal pigmentation genes or other transcription factors.

7) The authors mention that because cortex causes changes in both scale color and morphology this suggests "that cortex acts during early stages of scale cell fate specification rather than during the deployment of effector genes". This conclusion needs more discussion. Matsuoka and Monteiro (2018) showed that knockout of the gene yellow, an effector gene at the end of a gene regulatory network for melanin pigment production, also led to both changes in scale color and morphology. These authors proposed instead that absence of certain pigments on the wing, such as dopa melanin, caused chitin to polymerize differently and form an extra lamina that prevent the windows from forming in the scales (just as seen in cortex mutants). The authors should consider and evaluate this alternative explanation in their discussion.

We thank the reviewer for this important comment. The idea that cortex is likely acting at an early stage came mainly from the fact that this is when we see differential expression. However, given that we see cortex protein present until at least 80hr post pupation formation, we agree that it is possible for cortex to be acting later on in development too. We have thus removed this sentence.

8) Did the authors examine whether there were protein coding changes between the 47 genes in the mapped interval between the yellow and black races? Please mention whether this was done. Please also upload the sequences of the genes that were studied and provide accession numbers for these sequences.

We did not check across all the genes in the interval, however, Nadeau et al. (2016) did show there was no evidence of fixed protein coding changes at cortex itself, and that other genes in the Yb locus as defined in that paper were not associated with SNPs (see extended table 1 of that paper). Note that the genes cortex and wash were the only genes in the locus with any associated SNPs. We can add repeat this analysis if the reviewer deems this necessary. The genes are available as annotations from the H. erato demophoon and H. melpomene melpomene genomes (found on lepbase.org). Supplementary File 4 contains all the genes within the interval as well as their corresponding Gene ID for both H. erato and H. melpomene genomes. Hopefully this is sufficient, we are happy to further upload individual sequences to ENA if this is necessary.

Reviewer #2:

[…] Although this paper includes a substantial amount of work and a number of interesting observations, I am not sure what can really be concluded in the end, and several results would need follow-up experiments to reach a stable conclusion.

The strongest part, in my opinion, is the analysis of somatic mutant clones of cortex in the wings of different species. The authors show that the lack of cortex consistently results in the conversion of type II and type III scales into type I scales, and thereby demonstrate the necessity of this gene for type II and III identity. This is solid, interesting, but not a novel concept from a genetic or developmental biology point of view. There are countless examples in the 1990s literature of genes whose mutations results in such shifts in cell identity (e.g., poxn and cut in the peripheral nervous system of flies).

From this result, two questions emerge: how and when does cortex assign this identity during development? And how does cortex explain the variation in color pattern among Heliconius morphs and species? Although the paper discusses these two questions, I find the answers unclear and the results confusing.

The authors first examine the expression dynamics of cortex. They re-annotated the 47-gene genomic interval where cortex maps and analyzed the differential expression of all genes in the interval, across developmental stages, across species and morphs and also compared wing compartments.

1. Their main conclusion is that cortex is the most likely candidate in this interval to explain color pattern variation. I am not sure why the authors did this. I thought this was already clearly established from a previous paper (Nadeau et al. 2016, Nature).

Thank you for the comment. We agree that Nadeau et al. show compelling evidence for the involvement of cortex in establishing pattern differences, however, their conclusions were drawn from microarray tiling experiments examining differences between H. melpomene morphs that did not differ specifically in the presence of a yellow bar (H.m.plesseni and H.m.malletti). We believed it necessary to expand on these analyses by showing cortex was also differentially expressed in association with the yellow bar phenotype, which is the phenotype of focus in our manuscript.

2. Moreover, the explanations of the differential gene expression (DGE) analysis are often too shallow to really understand what the authors really did, including the method description. The figures are poorly annotated and it's difficult to understand if there are replicates in the RNA-seq analysis.

We apologise for the lack of clarity regarding the differential expression experiment. We have updated the methods and expanded upon the analysis, including further analysis in Supplementary File 4. We hope this is now clearer to follow.

3. One striking result from this part, is that the DGE suggests that cortex is differentially expressed in the 5th instar larvae between 2 morphs of Heliconius erato and 2 morphs of Heliconius melpomene, but the differential expression goes into opposite directions between these 2 species. How could the same phenotypic variation between morphs of 2 species be caused by opposite DGE? They authors note that it is interesting but do not comment or analyze further.

We agree this counter-intuitive results needs more explanation. We have expanded on this in the discussion (See lines 393 to 398). We hope this provides some clarity to the discussion.

4. They pursue their investigation with in situ hybridization on 5th larval instar wings and mitigate the notion of a spatial correlation between cortex transcripts spatial distribution and color patten elements proposed by Nadeau et al., 2016. Here again, the figure would benefit from better annotation. The authors indicate subtle differences in the local distribution of cortex transcripts between morphs but do not really conclude anything from their observation. They also give no indication of sample size or replicates, which I find unsettling given the noise associated with this experiment. I am not sure what this figure really adds to the published work, or to the present manuscript.

Apologies for the lack of clarity regarding the figure. We have employed the use of landmarks using the wing veins to illustrate the differences in expression between different wings/morphs. We have added a supplementary file (Supplementary File 6), showing more replicates across the different morphs. While it is difficult to interpret the results, we believe this is useful information for future researchers wishing to address a possible function for cortex. It seems likely that whatever the mechanism by which cortex is creating these phenotypic differences, early differences in expression are likely crucial. We therefore think this would be a good reference point for future studies to expand upon.

5. Finally, the authors examine the distribution of Cortex protein in late (2-day pupa) developing wings with a polyclonal antibody. They find, surprisingly, that the protein is distributed more or less uniformly in the wing epithelium and localizes to the cell nuclei. While this is very different from the patterned transcript distribution, it is consistent with the somatic mutant clone analysis that showed that any mutated cell at any position of the wing displayed a phenotype. But this opens many questions: what is the origin of the apparent difference in expression between protein and transcripts? Is cortex secreted and it diffuses across the wing? Or is the transcript expression spatially dynamic and the protein distribution revealed by the authors reflects the temporal integration of this expression? And if Cortex is present and functional across the wing, how does it produce discrete pattern elements?

We have expanded upon this analysis to include further time points as well as show that protein localisation matches the in situ expression in 5th instar larvae. We believe the pupal expression are an important result, as these can explain the wing wide effects seen for the CRISPR KOs. We agree with the reviewer, who poses many important, yet unresolved questions. We have tried to address these in the discussion (see lines 378-398 and 407-420), but we believe a more mechanistic deep-dive into the functional role of cortex falls beyond the scope of this manuscript and will be more appropriate for a future study, as our focus deals more with the evolution of the phenotypic switches.

Reviewer #3:

[…] Major concerns:

1. The use of the term "race" to define butterflies with specific phenotypes needs to be revised to clines or strains or variants. "Race" is a social construct and not a biological reality and we strongly suggest revising this term.

Thank you for the comment. We agree and have changed to the use of morph throughout the manuscript.

2. The authors state that cortex and dome/wash genes are controlled by inversion (see Line 375, page 19). Does the strain they engineered have/carry the inversion?

– We are aware that inversion for species is complex – strains, genetic background – starting material for inversion.

– Inversion events occurred millions of years ago in the loci contributing to the wing pattern. Authors describe the first generation of CRIPSR knock-outs in Heliconius sp. and hence we suggest to include further information.

Apologies for the lack of clarity on this. The inversion is present only in the polymorphic H. numata, which appears to have locked these genes into a supergene structure. There is no evidence of a supergene in H. melpomene or H. erato.

3. We strongly suggest the authors elaborate on their qRT-PCR analysis pipeline. Did the authors follow MIQE guidelines (https://academic.oup.com/clinchem/article/55/4/611/5631762) in their quantitative real time PCR assays?

Apologies for the confusion but we are not sure which qRT-PCR experiments the reviewers are referring to, as there was no qPCR experiment in the previous version of the manuscript. We have since added qPCR validation of the RNA-Seq data, and we hope the methodology is adequate in the revised version.

4. More explanation could be provided for cortex protein experiments. Figure 6 could explicitly say what developmental stage/time after pupation (they report this in the Methods section) and the rationale behind presenting data for this stage in development.

– Maybe perform a systematic developmental time series of cortex immunostaining experiments?

Thank you for the comment. We have expanded upon this analysis and have made the staging more explicit, including control experiments in the supplementary files.

5. We recommend the authors mention institutional or local animal care ethical approval and safety regulations in the field working on Heliconius sp. for setting best practice reporting standards.

This is an important point, which other reviewers have also raised. We have added further discussion of these discrepancies (See reviewer 2 comment #4).

6. We suggest to clarify the lack of a clear correlation between in situ stains and the mutational effects of cortex CRISPR knock-outs.

Apologies for the lack of clarity. This was also raised by a previous reviewer and we have expanded upon the methodology used to generate the differential expression statistics. We hope this will be easier to follow.

7. Could a sized-down Figure S10 be added to Figure 6 in the manuscript to provide more information about the nuclear ploidy and cortex antibody signal? Even no association is informative and helps the reader think about the connection between color/endopolyploidy.

We have much expanded upon this analysis and included further stages, as well as control experiments in the supplementary. We hope this will improve clarity.

[Editors’ note: what follows is the authors’ response to the second round of review.]

Essential revisions:

1) In line 350 the authors mention that the presence of an upper lamina is an important morphological feature of yellow/white scales and then they cite Matsuoka and Monteiro (2018). This paper shows, instead, that the white lamina forms in scales that are brown in color, not yellow nor white. In addition, several papers have shown the presence of this type of upper lamina in silver colored scales. While the presence of this lamina may indeed be a feature of Type I scales in Heliconius butterflies, I would refrain from attaching too much importance to this lamina regarding the formation of a particular color. The color changes observed in Heliconius butterflies are most likely caused by changes in pigmentation than by changes in the presence/absence of this lamina.

We thank the reviewer for bringing this to our attention. We have removed the citation and limited our comments to pointing out that cortex KOs are accompanied by both ultrastructural differences and pigmentation shifts. See lines 355-359 of the revised manuscript.

2) Line 160: Spell out what APC/C motifs are.

Added to line 168.

3) In Figure 9e I cannot really see/understand the effect of cortex disruptions on red scale phenotypes – both the SEM image provided and the low-resolution image of the red-colored scale are low quality. Please provide higher quality images for these data. In particular, the SEM data does not show a scale type III converting into a scale type I.

We apologise for the lack of clarity regarding the Type III to I transformation. We have added a supplementary figure that accompanies the Figure 9e that illustrates these changes (Figure 9—figure supplement 2). We note that the transformations to Type I scales are not always complete; some scales appear to be in an “intermediate” state between Type III and I. In the discussion we thus make the argument that cortex appears to be necessary for induction of Type III scales, but not sufficient for their proper development (see lines 480-481). Following this logic, it appears that optix therefore requires an input from cortex to lead to the proper development of red scales. This epistatic interaction has also been shown to occur between certain H. melpomene crosses, where the red forewing band shape is dependent on specific cortex alleles segregating in the crosses. With regards to the SEMs not showing a full transformation, we note that it was difficult to image and measure the transformed Type III scales, as these immediately curled upon removal for imaging (suggesting that their structural integrity is compromised by cortex KOs). However, even in this curled up state, the presence of microribs and a lamina covering the spaces between the microribs and ridges can be seen (we hope this is more evident in the extra images provided in the Figure 9—figure supplement 2). It should also be noted the granular red pigment is internal to the scale and not visible in the SEMs. We believe these data fit our interpretation given in the discussion, where “…cortex expression is required for either downstream signalling to optix, or to induce a permissive scale morphology for the synthesis and deposition of red pigment in future scales.” A possible mechanism for this observation could perhaps result from differential rates of scale development induced by cortex (heterochrony hypothesis). If cortex is slowing down scale development, it may allow the scales to enter the timing of optix expression and red pigment deposition at an earlier developmental time. In the absence of cortex, scales develop quicker (as Type I scales do, see Aymone et al., 2013), and therefore the deposition of red pigment occurs at a time when scales may already be hardening, resulting in this intermediate effect in some scales.

4) Line 375: Why "key early scale cell specification switch"? What does "early" refer to and what data indicates time of gene activity in the manuscript?

Thank you for bringing this point to our attention. By “early” we were referring to the fact that differential expression of cortex occurs during fifth instar wing development, and so suggests that this is a pre-patterning effect that occurs early during wing development. However, we agree that this term is relative to developmental time chosen to be referred to as early or not, and so we have removed the word. See line 380.

5) Line 376: How does the sentence above lead to the next sentence "and thus has the potential to generate much broader pattern variation than previously described patterning genes"? I don't follow what the authors are trying to convey here.

Apologies for the lack of clarity regarding this statement. We were attempting to convey the idea that, in contrast to the other major patterning genes, cortex appears to be expressed and affect scale development throughout the entire wing surface, and therefore tinkering with its expression can lead to broad effects throughout the wing. Therefore, rather than it being a canonical “patterning” gene, perhaps it is best conceived as a conserved scale development gene, where it can affect individual scale development trajectories across the wing.

6) Lines 447-449 need revision.

Apologies for the confusing phrasing, we have edited this in a way we hope is clearer to the reader. See lines 456-460.

7) Crossribs are sometimes written as cross-ribs. Be consistent.

Thank you for alerting us to this. We have corrected it to crossribs throughout.

8) Ln 85 Capitalize van Belleghem.

Thank you for spotting this. This has been changed.

9) Lns 92-99. The authors made a marked improvement in detailing the morphological differences in the text. The authors also provide a nice visual summary of the pigment of morphological differences in Figure 9f. However, the readers suffer by not being able to connect the text in the introduction to the illustrations in Figure 9f. I understand the challenge is that figures must be referenced in order, and it definitely makes sense for Figure 9f to be placed with the CRISPR images. If possible, I would urge the journal to allow the authors to add "(see Figure 9f)" in lines 92-99, as I think it would help the reader and retain the author's figure order. The alternative would be including a version of the cartoon in 9F in Figure 1, which could be considered since the scale structure and fate are such a major component of the study.

On suggestion by the reviewer, we have added "(see Figure 9f)" to line 92. We hope the journal is OK with this suggestion, otherwise we are happy to reproduce the figure in Figure 1.

10) Lns 130-137. I agree with Reviewer 1 that the dome/wash results detract from the main points and flow of the paper. However, I don't agree that they should be removed. Rather, I recommend that the detailed description of the dome duplication be moved to supplementary materials, as it seems the primary purpose of including the duplication description is to justify analyses were performed and interpreted accurately.

Thank you for the suggestion. We have moved the analysis of the duplication to the supplementary. We have retained lines 134-136 however, as these are necessary to interpret the annotations of the gene names in Figure 3.

11) Ln 237. The authors state "the sharp boundaries observed between wild-type and mutant scales suggest cortex functions in a cell-autonomous manner, with little or no communication between neighbouring cells", however, I'm not convinced of this. It seems the mutant scales of single individuals are more often localized in wing regions, often with neighboring clusters of mutant scales. I understand that the sharp boundaries may suggest little cell communication, later in wing pattern development. However, the localization of clusters suggests cortex may impact communication between cells in early wing cell replication. This doesn't have much of an impact on their findings, but the authors may want to consider tempering the interpretation.

We thank the reviewer for bringing this to our attention. We have changed our interpretation to incorporate the idea that communication between neighbouring cells may be contributing to the observed clustering of mutant cells (see lines 244-246).

12) Ln 352-353. The authors state "…cortex is necessary for the development of lamellar structures in Heliconius scales.". This statement is too broad and encompassing. Figure 9 shows that cortex appears to be required to develop Type II and III scales with open upper lamina. In this regard, cortex is not required for the development of lamellar structures but rather required to regulate the development of architectural variation in lamellar structures. This may seem minor, but as worded it reads that "cortex is necessary for the development of lamellar structures", which I don't agree is supported by the data.

We agree with the reviewer that our wording was incorrect. We have edited these lines to reflect the fact that cortex perturbations are accompanied by morphological changes. See lines 357-359.

13) Ln 393-398. I find the authors attempt to explain the difference in the direction of cortex DGE between species to be quite brief and hand-waving. I'm not clear what is meant by "some relatively subtle developmental heterochrony between the two species would capture the state of differentially expressed genes in a different dynamic step." It seems the timing and levels of cortex expression could be quite precise and variable over short periods of time. In such cases, the limited sampling in each species could simply be detecting different points. In other words, it may be more informative for the reader to have the authors state that the current resolution may simply be insufficient to resolve and compare the precise cellular functions of cortex in the two species. And, that the difference between species suggests more detailed examination, perhaps even real-time expression data of cortex, may be needed.

We agree and have changes the lines accordingly (see lines 400-405).

14) Figure 10. I would consider including WntA in Figure 10. The timing of expression of WntA effecting melanic pattern is well resolved (5th instar), the authors discuss how WntA and cortex may interact, so it would seem reasonable to include WntA in Figure 10, so that the figure offered the best present model for the timing and placement of each major color patterning gene during wing development.

We thank the reviewer for the suggestions. Upon design of the figure, we had previously considered including WntA. However, including WntA is tricky as WntA signaling does not determine strict colour fates, but rather shapes the spatial organization of the landscape. We thought about describing the landscape itself as a metaphor for the action of WntA, whereby it can shape the hills and throughs, delimiting the spatial arrangement of specific colour pattern elements. Or having the “scaffolding” underneath the landscape be represented as WntA, however, we believe this might be stretching the metaphor a bit and become confusing to the reader.

15) Ln 510. Italicize H. melpomene and H. erato.

This has been changed.

16) Ln 684. Ray et al. 2019 not included in References.

Apologies. This has now been added.

17) Ln 885-886. McMillan et al. 2020 reference is incomplete.

This has now been updated.

18) Figure S15. Please remove "Lorem ipsum" from the "H. erato ridge periodicity" plot.

Yikes. This has now been removed.

19) The introduction lacks a short description of the concrete wing colour patterns of the studied Heliconius species. It would be helpful for some readers to have this information between lines 100-106: Colour stripes, location on the wing, colour polymorphism,…

Thank you for the comment. We have added two sentences describing the phenotypes in more detail (See lines 106-111).

20) I agree with a previous reviewer that the data on cortex and dome/wash differential gene expression could be removed from this manuscript (although it should be published elsewhere). However, in the current form the manuscript starts with results that are difficult to interpret and this is confusing. The rational to investigate cortex function is already given by Nadeau et al. 2016.

We thank the reviewer for the comment. We have tried to shorten the section dealing with dome/wash by including most of the information in the supplementary. However, we agree with the reviewer who suggested in Comment #10 that it is necessary to include part of the information in order to justify running the analysis in the way that we did. We hope this is sufficient to improve the clarity of the manuscript.

21) The manuscript could therefore gain clarity if the authors re-arrange their very interesting findings. 1) CRISPR mosaics to characterize cortex function and SEM analysis on scale type 2) Identification and characterization of the CRE's and the role in stripe determination 3) cortex expression analysis that does not seem to associate with a hindwing stripe.

We thank the reviewer for the suggestion. In terms of the set up and rationale, we would like to keep the structure as is, if the editors and reviewers agree. We agree that Nadeau et al. (2016) show compelling evidence for the involvement of cortex in establishing pattern differences, however, their conclusions were drawn from microarray tiling experiments examining differences between H. melpomene morphs that did not differ specifically in the presence of a yellow bar (H.m. plesseni and H.m. malletti). We believed it necessary to expand on these analyses by showing cortex was also differentially expressed in association with the yellow bar phenotype, which is the phenotype of focus in our manuscript. With therefore think that starting with the DGE as the first experiment is important. We also think that, while it might improve clarity to leave out dome/wash, it would be difficult not to report that there is another locus among the 47 gene interval that shows promising patterns of differential gene expression.

22) Mosaic loss of function of cortex apparently reveals a loss of melanic (Type II) and red (Type III) scales. The authors note sharp boundaries between wild-type and mKO scales and suggest cortex functions to be cell-autonomous with little or no communication between neighbouring cells. However, in Figure 4b and S10 they also report intermediate white/red scale phenotypes in scales of the "red band element". These scales sometimes have a patchy/granular red colouration. The authors further note an asymmetric deposition of pigment across the scale but should better point out what this means. Is the result conform with / contradicting their interpretation of a cortex mediated scale identity switch? Could the red pigment presence have non-autonomous sources from the surrounding tissue?

We thank the reviewer for raising this important point. We have changed our interpretation also in line with Comment #11. Regarding the more continuous nature of the red scales, we have tried to elaborate this by including more information in the supplementary (See Comment #3). In terms of the interpretation for a direct Type III to Type I switch, we agree that this is not a simple as the case observed for Type II to Type I. However, we believe that the data still supports the idea that a cortex signal is required for “proper” development of Type III scales, as these display Type-I-like structure when in a cortex negative state.

23) The Figures are very nice, but many legends lack a certain degree of precision in the description of each panel. The authors need to revise this with care, this has already been pointed out by a previous reviewer. Please indicate what the illustrations literally present. For example, Figure 1a, horizontal black bars are coding sequences? gene predictions? mapped transcripts? other elements? What reference genome assembly? Do they indicate the 47 candidate genes or just a small portion of it? Wing patterns are present on the dorsal or ventral side of the wing? Figure 1B: Are yellow and blue dots reported sampling locations?

We apologise for the lack of clarity regarding the figure legends. The legends have been edited to include more detail, we hope this has improved clarity.

24) Conclusion: The first part (lines 492 – 505) appears to be redundant with lines 511 -514 in the second paragraph. Maybe integrate the first paragraph into the discussion.

We agree with the reviewer and have shortened the conclusion to remove redundant lines.

https://doi.org/10.7554/eLife.68549.sa1

Article and author information

Author details

  1. Luca Livraghi

    1. Department of Zoology, University of Cambridge, Downing St., Cambridge, United Kingdom
    2. Smithsonian Tropical Research Institute, Gamboa, Panama
    Contribution
    Conceptualization, Resources, Data curation, Formal analysis, Supervision, Validation, Investigation, Visualization, Methodology, Writing - original draft, Project administration, Writing - review and editing
    For correspondence
    miles.livraghi@gmail.com
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2597-7550
  2. Joseph J Hanly

    1. Department of Zoology, University of Cambridge, Downing St., Cambridge, United Kingdom
    2. Smithsonian Tropical Research Institute, Gamboa, Panama
    3. The George Washington University Department of Biological Sciences, Science and Engineering Hall, Washington, United States
    Contribution
    Resources, Data curation, Software, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing - review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9459-9776
  3. Steven M Van Bellghem

    Department of Biology, Centre for Applied Tropical Ecology and Conservation, University of Puerto Rico, Rio Piedras, Puerto Rico
    Contribution
    Data curation, Software, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing - review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-9399-1007
  4. Gabriela Montejo-Kovacevich

    Department of Zoology, University of Cambridge, Downing St., Cambridge, United Kingdom
    Contribution
    Data curation, Formal analysis, Validation, Visualization, Methodology, Writing - review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3716-9929
  5. Eva SM van der Heijden

    1. Department of Zoology, University of Cambridge, Downing St., Cambridge, United Kingdom
    2. Smithsonian Tropical Research Institute, Gamboa, Panama
    Contribution
    Formal analysis, Investigation, Writing - review and editing
    Competing interests
    No competing interests declared
  6. Ling Sheng Loh

    The George Washington University Department of Biological Sciences, Science and Engineering Hall, Washington, United States
    Contribution
    Formal analysis, Investigation, Methodology
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0981-7984
  7. Anna Ren

    The George Washington University Department of Biological Sciences, Science and Engineering Hall, Washington, United States
    Contribution
    Formal analysis, Investigation, Visualization, Methodology
    Competing interests
    No competing interests declared
  8. Ian A Warren

    Department of Zoology, University of Cambridge, Downing St., Cambridge, United Kingdom
    Contribution
    Investigation, Methodology, Project administration
    Competing interests
    No competing interests declared
  9. James J Lewis

    Baker Institute for Animal Health, College of Veterinary Medicine, Cornell University, Ithaca, United States
    Contribution
    Formal analysis, Validation, Visualization, Methodology
    Competing interests
    No competing interests declared
  10. Carolina Concha

    Smithsonian Tropical Research Institute, Gamboa, Panama
    Contribution
    Formal analysis, Investigation
    Competing interests
    No competing interests declared
  11. Laura Hebberecht

    1. Department of Zoology, University of Cambridge, Downing St., Cambridge, United Kingdom
    2. Smithsonian Tropical Research Institute, Gamboa, Panama
    Contribution
    Data curation, Formal analysis, Investigation, Methodology
    Competing interests
    No competing interests declared
  12. Charlotte J Wright

    Department of Zoology, University of Cambridge, Downing St., Cambridge, United Kingdom
    Contribution
    Data curation, Investigation, Methodology
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3971-4372
  13. Jonah M Walker

    Department of Zoology, University of Cambridge, Downing St., Cambridge, United Kingdom
    Contribution
    Formal analysis, Investigation
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7355-3130
  14. Jessica Foley

    Smithsonian Tropical Research Institute, Gamboa, Panama
    Contribution
    Formal analysis, Investigation
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-4566-3989
  15. Zachary H Goldberg

    Cell & Developmental Biology, Division of Biological Sciences, UC San Diego, La Jolla, United States
    Contribution
    Formal analysis, Investigation, Methodology
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-2972-9682
  16. Henry Arenas-Castro

    Smithsonian Tropical Research Institute, Gamboa, Panama
    Contribution
    Investigation
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4845-9999
  17. Camilo Salazar

    Biology Program, Faculty of Natural Sciences, Universidad del Rosario, Bogotá, Colombia
    Contribution
    Resources, Data curation
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-9217-6588
  18. Michael W Perry

    Cell & Developmental Biology, Division of Biological Sciences, UC San Diego, La Jolla, United States
    Contribution
    Formal analysis, Investigation
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5977-8031
  19. Riccardo Papa

    Department of Biology, Centre for Applied Tropical Ecology and Conservation, University of Puerto Rico, Rio Piedras, Puerto Rico
    Contribution
    Supervision, Funding acquisition, Writing - review and editing
    Competing interests
    No competing interests declared
  20. Arnaud Martin

    The George Washington University Department of Biological Sciences, Science and Engineering Hall, Washington, United States
    Contribution
    Conceptualization, Resources, Formal analysis, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing - review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5980-2249
  21. W Owen McMillan

    Smithsonian Tropical Research Institute, Gamboa, Panama
    Contribution
    Conceptualization, Resources, Supervision, Funding acquisition, Validation, Project administration, Writing - review and editing
    Competing interests
    No competing interests declared
  22. Chris D Jiggins

    1. Department of Zoology, University of Cambridge, Downing St., Cambridge, United Kingdom
    2. Smithsonian Tropical Research Institute, Gamboa, Panama
    Contribution
    Conceptualization, Resources, Supervision, Funding acquisition, Validation, Project administration, Writing - review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7809-062X

Funding

Biotechnology and Biological Sciences Research Council (BB/R007500/1)

  • Luca Livraghi
  • Eva SM van der Heijden
  • Ian A Warren
  • Charlotte Wright
  • Chris D Jiggins

National Science Foundation (IOS-1656553 and IOS-1755329)

  • Joseph J Hanly
  • Ling Sheng Loh
  • Anna Ren
  • Arnaud Martin

Puerto Rico Science, Technology and Research Trust (#2020-00142)

  • Steven M Van Bellghem
  • Riccardo Papa

Smithsonian Institution (NSF IOS-1656389)

  • Carolina Concha
  • W Owen McMillan

National Science Foundation (NSF IOS 1656389)

  • Riccardo Papa

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Acknowledgements

We thank Oscar Paneso, Elizabeth Evans, Rachel Crisp, and Cruz Batista, for technical support with rearing of butterflies and CRISPR larvae, and to Markus Möest, and Tim Thurman for assistance with butterfly collection. We are also grateful to Krzysztof ‘Chris’ Kozak and Chi Yun for thoughtful discussions and feedback on the manuscript. We thank the GW Nanofabrication and Imaging Center for enabling SEM, and in particular Christine Brantner, Chris Day, and Anastas Popratiloff for their technical assistance.

Senior and Reviewing Editor

  1. Patricia J Wittkopp, University of Michigan, United States

Reviewer

  1. Antonia Montiero, National University of Singapore and Yale-NUS-College, Singapore

Publication history

  1. Received: March 18, 2021
  2. Accepted: June 14, 2021
  3. Version of Record published: July 19, 2021 (version 1)

Copyright

© 2021, Livraghi et al.

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

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