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

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

Environment-dependent attack rates of cryptic and aposematic butterflies.

Many organisms have evolved adaptive coloration that reduces their risk of predation. Cryptic coloration reduces the likelihood of detection/recognition by potential predators, while warning or aposematic coloration advertises unprofitability and thereby reduces the likelihood of attack. Although some studies show that aposematic coloration functions better at decreasing attack rate than crypsis, recent work has suggested and demonstrated that crypsis and aposematism are both successful strategies for avoiding predation. Furthermore, the visual environment (e.g., ambient lighting, background) affects the ability for predators to detect prey. We investigated these 2 related hypotheses using 2 well-known visually aposematic species of Heliconius butterflies, which occupy different habitats (open-canopy vs. closed-canopy), and one palatable, cryptic, generalist species Junonia coenia. We tested if the differently colored butterflies differ in attack rates by placing plasticine models of each of the 3 species in 2 different tropical habitats where the butterflies naturally occur: disturbed, open-canopy habitat and forested, closed-canopy habitat. The cryptic model had fewer attacks than one of the aposematic models. Predation rates differed between the 2 habitats, with the open habitat having much higher predation. However, we did not find an interaction between species and habitat type, which is perplexing due to the different aposematic phenotypes naturally occurring in different habitats. Our findings suggest that during the Panamanian dry season avian predation on perched butterflies is not a leading cause in habitat segregation between the 2 aposematic species and demonstrate that cryptically colored animals at rest may be better than aposematic prey at avoiding avian attacks in certain environments.

ButterflyBase: a platform for lepidopteran genomics.

With over 100 000 species and a large community of evolutionary biologists, population ecologists, pest biologists and genome researchers, the Lepidoptera are an important insect group. Genomic resources [expressed sequence tags (ESTs), genome sequence, genetic and physical maps, proteomic and microarray datasets] are growing, but there has up to now been no single access and analysis portal for this group. Here we present ButterflyBase (http://www.butterflybase.org), a unified resource for lepidopteran genomics. A total of 273 077 ESTs from more than 30 different species have been clustered to generate stable unigene sets, and robust protein translations derived from each unigene cluster. Clusters and their protein translations are annotated with BLAST-based similarity, gene ontology (GO), enzyme classification (EC) and Kyoto encyclopaedia of genes and genomes (KEGG) terms, and are also searchable using similarity tools such as BLAST and MS-BLAST. The database supports many needs of the lepidopteran research community, including molecular marker development, orthologue prediction for deep phylogenetics, and detection of rapidly evolving proteins likely involved in host-pathogen or other evolutionary processes. ButterflyBase is expanding to include additional genomic sequence, ecological and mapping data for key species.