Selective sweeps on novel and introgressed variation shape mimicry loci in a butterfly adaptive radiation

Moest, Markus; Belleghem, Steven M. Van; James, Jennifer E.; Salazar, Camilo; Martin, Simon H.; Barker, Sarah L.; Moreira, Gilson R. P.; Mérot, Claire; Joron, Mathieu; Nadeau, Nicola J.; Steiner, Florian M.; Jiggins, Chris D.

doi:10.1371/journal.pbio.3000597

Cited by 72 publications

(82 citation statements)

References 132 publications

(297 reference statements)

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“…This inference potentially fits a signal of recent adaptive evolution (i.e. selective sweep signal) across the regulatory regions in the first intronic region of WntA of H. e. hydara populations from French Guiana, but not H. e. hydara populations from Panama, or H. m. melpomene populations from French Guiana [ 25 ]. What drives the divergence in MFB pattern between the H. erato Postman populations may include local changes in the composition of the mimicry and/or predator community [ 18 , 24 , 26 ].…”

Section: Discussionmentioning

confidence: 84%

“…This phenotypic convergence has evolved through strong selection pressures that benefit a common warning pattern that birds have learned to associate with unpalatability [ 23 , 24 ]. The discriminatory visual properties of birds appear to be quite precise, resulting in strong selection pressures for fine scale adjustments of the shape and size of colour patterns among local mimetic butterfly communities (for an overview of selection coefficients see [ 25 ]) [ 26 , 27 ].…”

Section: Introductionmentioning

confidence: 99%

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Perfect mimicry between Heliconius butterflies is constrained by genetics and development

et al. 2020

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Müllerian mimicry strongly exemplifies the power of natural selection. However, the exact measure of such adaptive phenotypic convergence and the possible causes of its imperfection often remain unidentified. Here, we first quantify wing colour pattern differences in the forewing region of 14 co-mimetic colour pattern morphs of the butterfly species Heliconius erato and Heliconius melpomene and measure the extent to which mimicking colour pattern morphs are not perfectly identical. Next, using gene-editing CRISPR/Cas9 KO experiments of the gene WntA , which has been mapped to colour pattern diversity in these butterflies, we explore the exact areas of the wings in which WntA affects colour pattern formation differently in H. erato and H. melpomene. We find that, while the relative size of the forewing pattern is generally nearly identical between co-mimics, the CRISPR/Cas9 KO results highlight divergent boundaries in the wing that prevent the co-mimics from achieving perfect mimicry. We suggest that this mismatch may be explained by divergence in the gene regulatory network that defines wing colour patterning in both species, thus constraining morphological evolution even between closely related species.

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Section: Discussionmentioning

confidence: 84%

Section: Introductionmentioning

confidence: 99%

Perfect mimicry between Heliconius butterflies is constrained by genetics and development

et al. 2020

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“…H. e. hydara versus H. m. melpomene from French Guiana). As H. erato is often suggested to be the more abundant co-mimic and, thus, the model which H. melpomene mimics [21,22], the evolution of better mimetic signals in this case may reflect a melpomene populations from French Guiana [20]. The potentially recent evolutionary change of the H. e. hydara mid-forewing band phenotype from French Guiana also crosses the developmental boundary identified in the H. e. demophoon CRISPR/Cas9 KO's, which suggests the gene regulatory network that underlies this similar wing phenotype may be diverging even within the H. erato lineage (Figure 3).…”

Section: (B) Evidence Of Gene Regulatory Network Divergence Within Spmentioning

confidence: 93%

“…These genes have been shown to be repeatedly involved in both the evolution of divergent and convergent phenotypes in Heliconius, as well as other butterfly and moth species [7,14,17]. What has been suggested to define the variability in wing color patterns in Heliconius, despite the few genes involved, is a complex array of cis-regulatory regions that control expression during their wing development [16,[18][19][20].…”

Section: Introductionmentioning

confidence: 99%

Perfect mimicry betweenHeliconiusbutterflies is constrained by genetics and development

Belleghem

Roman

Gutierrez

et al. 2020

Preprint

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Müllerian mimicry strongly exemplifies the power of natural selection. However, the exact measure of such adaptive phenotypic convergence and the possible causes of its imperfection often remain unidentified. The butterfly species Heliconius erato and Heliconius melpomene have a large diversity of co-mimicking geographic races with remarkable resemblance in melanic patterning across the midforewing that has been linked to expression patterns of the gene WntA. Recent CRISPR/Cas9 experiments have informed us on the exact areas of the wings in which WntA affects color pattern formation in both H. erato and H. melpomene, thus providing a unique comparative dataset to explore the functioning of a gene and its potential effect on phenotypic evolution. We therefore quantified wing color pattern differences in the mid-forewing region of 14 co-mimetic races of H. erato and H. melpomene and measured the extent to which mimicking races are not perfectly identical. While the relative size of the mid-forewing pattern is generally nearly identical, our results highlight the areas of the wing that prevent these species from achieving perfect mimicry and demonstrate that this mismatch can be largely explained by constraints imposed by divergence in the gene regulatory network that define wing color patterning. Divergence in the developmental architecture of a trait can thus constrain morphological evolution even between relatively closely related species.

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“…a model system for nonbifurcating patterns of phylogenetic descent and the interplay of introgression and phenotypic evolution(Dasmahapatra et al 2012;Nadeau et al 2013;Edelman et al 2019;Moest et al 2020).…”

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confidence: 99%

Chromosome-scale inference of hybrid speciation and admixture with convolutional neural networks

Blischak

Barker

Gutenkunst

2020

Preprint

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AbstractInferring the frequency and mode of hybridization among closely related organisms is an important step for understanding the process of speciation and can help to uncover reticulated patterns of phylogeny more generally. Phylogenomic methods to test for the presence of hybridization come in many varieties and typically operate by leveraging expected patterns of genealogical discordance in the absence of hybridization. An important assumption made by these tests is that the data (genes or SNPs) are independent given the species tree. However, when the data are closely linked, it is especially important to consider their non-independence. Recently, deep learning techniques such as convolutional neural networks (CNNs) have been used to perform population genetic inferences with linked SNPs coded as binary images. Here we use CNNs for selecting among candidate hybridization scenarios using the tree topology (((P1, P2), P3), Out) and a matrix of pairwise nucleotide divergence (dXY) calculated in windows across the genome. Using coalescent simulations to train and independently test a neural network showed that our method, HyDe-CNN, was able to accurately perform model selection for hybridization scenarios across a wide-breath of parameter space. We then used HyDe-CNN to test models of admixture in Heliconius butterflies, as well as comparing it to a random forest classifier trained on introgression-based statistics. Given the flexibility of our approach, the dropping cost of long-read sequencing, and the continued improvement of CNN architectures, we anticipate that inferences of hybridization using deep learning methods like ours will help researchers to better understand patterns of admixture in their study organisms.

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Selective sweeps on novel and introgressed variation shape mimicry loci in a butterfly adaptive radiation

Cited by 72 publications

References 132 publications

Perfect mimicry between Heliconius butterflies is constrained by genetics and development

Perfect mimicry between Heliconius butterflies is constrained by genetics and development

Perfect mimicry betweenHeliconiusbutterflies is constrained by genetics and development

Chromosome-scale inference of hybrid speciation and admixture with convolutional neural networks

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