Scorpions constitute a charismatic lineage of arthropods and comprise more than 2500 described species. Found throughout various tropical and temperate habitats, these predatory arachnids have a long evolutionary history, with a fossil record that began in the Silurian. While all scorpions are venomous, the asymmetrically diverse family Buthidae harbors nearly half the diversity of extant scorpions, and all but one of the 58 species that are medically significant to humans. However, the lack of a densely sampled scorpion phylogeny has hindered broader inferences of the diversification dynamics of scorpion toxins. To redress this gap, we assembled a phylogenomic data set of 100 scorpion venom gland transcriptomes and genomes, emphasizing the sampling of highly toxic buthid genera. To infer divergence times of venom gene families, we applied a phylogenomic node dating approach for the species tree in tandem with phylostratigraphic bracketing to estimate the minimum ages of mammal-specific toxins. Our analyses establish a robustly supported phylogeny of scorpions, particularly with regard to relationships between medically significant taxa. Analysis of venom gene families shows that mammal-active sodium channel toxins (NaTx) have independently evolved in five lineages within Buthidae. Temporal windows of mammal-targeting toxin origins are correlated with the basal diversification ofmore »
Next-generation sequencing has become exceedingly common and has transformed our ability to explore nonmodel systems. In particular, transcriptomics has facilitated the study of venom and evolution of toxins in venomous lineages; however, many challenges remain. Primarily, annotation of toxins in the transcriptome is a laborious and time-consuming task. Current annotation software often fails to predict the correct coding sequence and overestimates the number of toxins present in the transcriptome. Here, we present ToxCodAn, a python script designed to perform precise annotation of snake venom gland transcriptomes. We test ToxCodAn with a set of previously curated transcriptomes and compare the results to other annotators. In addition, we provide a guide for venom gland transcriptomics to facilitate future research and use Bothrops alternatus as a case study for ToxCodAn and our guide.
Our analysis reveals that ToxCodAn provides precise annotation of toxins present in the transcriptome of venom glands of snakes. Comparison with other annotators demonstrates that ToxCodAn has better performance with regard to run time ($>20x$ faster), coding sequence prediction ($>3x$ more accurate) and the number of toxins predicted (generating $>4x$ less false positives). In this sense, ToxCodAn is a valuable resource for toxin annotation. The ToxCodAn framework can be more »
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- Briefings in Bioinformatics
- Oxford University Press
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- National Science Foundation
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