Opsin proteins are fundamental components of animal vision whose structure largely determines the sensitivity of visual pigments to different wavelengths of light. Surprisingly little is known about opsin evolution in beetles, even though they are the most species rich animal group on Earth and exhibit considerable variation in visual system sensitivities. We reveal the patterns of opsin evolution across 62 beetle species and relatives. Our results show that the major insect opsin class (SW) that typically confers sensitivity to “blue” wavelengths was lost ~300 million years ago, before the origin of modern beetles. We propose that UV and LW opsin gene duplications have restored the potential for trichromacy (three separate channels for colour vision) in beetles up to 12 times and more specifically, duplications within the UV opsin class have likely led to the restoration of “blue” sensitivity up to 10 times. This finding reveals unexpected plasticity within the insect visual system and highlights its remarkable ability to evolve and adapt to the available light and visual cues present in the environment.

Fireflies and their luminous courtships have inspired centuries of scientific study. Today firefly luciferase is widely used in biotechnology, but the evolutionary origin of bioluminescence within beetles remains unclear. To shed light on this long-standing question, we sequenced the genomes of two firefly species that diverged over 100 million-years-ago: the North AmericanPhotinus pyralisand JapaneseAquatica lateralis.To compare bioluminescent origins, we also sequenced the genome of a related click beetle, the CaribbeanIgnelater luminosus, with bioluminescent biochemistry near-identical to fireflies, but anatomically unique light organs, suggesting the intriguing hypothesis of parallel gains of bioluminescence. Our analyses support independent gains of bioluminescence in fireflies and click beetles, and provide new insights into the genes, chemical defenses, and symbionts that evolved alongside their luminous lifestyle.

Reconstructing the phylogenetic relationships between species is one of the most formidable tasks in evolutionary biology. Multiple methods exist to reconstruct phylogenetic trees, each with their own strengths and weaknesses. Both simulation and empirical studies have identified several “zones” of parameter space where accuracy of some methods can plummet, even for four-taxon trees. Further, some methods can have undesirable statistical properties such as statistical inconsistency and/or the tendency to be positively misleading (i.e. assert strong support for the incorrect tree topology). Recently, deep learning techniques have made inroads on a number of both new and longstanding problems in biological research. In this study, we designed a deep convolutional neural network (CNN) to infer quartet topologies from multiple sequence alignments. This CNN can readily be trained to make inferences using both gapped and ungapped data. We show that our approach is highly accurate on simulated data, often outperforming traditional methods, and is remarkably robust to bias-inducing regions of parameter space such as the Felsenstein zone and the Farris zone. We also demonstrate that the confidence scores produced by our CNN can more accurately assess support for the chosen topology than bootstrap and posterior probability scores from traditional methods. Although numerous practical challenges remain, these findings suggest that the deep learning approaches such as ours have the potential to produce more accurate phylogenetic inferences.

Odonata (dragonflies and damselflies) present an unparalleled insect model to integrate evolutionary genomics with ecology for the study of insect evolution. Key features of Odonata include their ancient phylogenetic position, extensive phenotypic and ecological diversity, several unique evolutionary innovations, ease of study in the wild and usefulness as bioindicators for freshwater ecosystems worldwide. In this review, we synthesize studies on the evolution, ecology and physiology of odonates, highlighting those areas where the integration of ecology with genomics would yield significant insights into the evolutionary processes that would not be gained easily by working on other animal groups. We argue that the unique features of this group combined with their complex life cycle, flight behaviour, diversity in ecological niches and their sensitivity to anthropogenic change make odonates a promising and fruitful taxon for genomics focused research. Future areas of research that deserve increased attention are also briefly outlined.

Introgression is an important biological process affecting at least 10% of the extant species in the animal kingdom. Introgression significantly impacts inference of phylogenetic species relationships where a strictly binary tree model cannot adequately explain reticulate net-like species relationships. Here, we use phylogenomic approaches to understand patterns of introgression along the evolutionary history of a unique, nonmodel insect system: dragonflies and damselflies (Odonata). We demonstrate that introgression is a pervasive evolutionary force across various taxonomic levels within Odonata. In particular, we show that the morphologically “intermediate” species of Anisozygoptera (one of the three primary suborders within Odonata besides Zygoptera and Anisoptera), which retain phenotypic characteristics of the other two suborders, experienced high levels of introgression likely coming from zygopteran genomes. Additionally, we find evidence for multiple cases of deep inter-superfamilial ancestral introgression. [Gene flow; Odonata; phylogenomics; reticulate evolution.]