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Data from: What makes a fang? phylogenetic and ecological controls on tooth evolution in rear-fanged snakes

Cite this dataset

Westeen, Erin et al. (2020). Data from: What makes a fang? phylogenetic and ecological controls on tooth evolution in rear-fanged snakes [Dataset]. Dryad.


Background: Fangs are a putative key innovation that revolutionized prey capture and feeding in snakes, and – along with their associated venom phenotypes – have made snakes perhaps the most medically-significant vertebrate animals. Several snake clades are known for their forward-positioned fangs, and these clades (Elapidae; Viperidae) contain the majority of snakes that are traditionally considered venomous. However, many other snakes are "rear-fanged": they possess potentially venom-delivering teeth situated at the rear end of the upper jaw. Quantification of fang phenotypes – and especially those of rear-fanged species – has proved challenging or impossible owing to the small size and relative rarity of many such snakes. Consequently, it has been difficult to understand the evolutionary history of both venom and prey-capture strategies across extant snakes. We quantified variation in the dentition of 145 colubriform (“advanced”) snake species using microCT scanning and compared dental characters with ecological data on species’ diet and prey capture method(s) to understand broader patterns in snake fang evolution.

Results: Dental traits such as maxilla length, tooth number, and fang size show strong phylogenetic signal across Colubriformes. We find extreme heterogeneity and evolutionary lability in the rear-fanged phenotype in colubrid (colubrine, dipsadine, and natricine lineages) and lamprophiid snakes, in contrast to relative uniformity in the front fanged phenotypes of other groups (vipers and, to a lesser extent, elapids). Fang size and position are correlated with venom-use in vipers, elapids, and colubrid snakes, with the latter group shifting fangs anteriorly by shortening the entire maxillary bone. We find that maxilla length and tooth number may also be correlated with the evolution of dietary specialization. Finally, an ancestral state reconstruction suggests that fang loss is a widespread phenomenon in colubrid snakes, likely accompanied by shifts in diet and prey capture mode.

Conclusions: Our study provides a framework for quantifying the complex morphologies associated with venom use in snakes. Our results suggest that fang phenotypes, and particularly the rear-fanged phenotype, in snakes are both diverse and labile, facilitating a wide range of ecological strategies and contributing to spectacular radiations of these organisms in tropical and subtropical biomes worldwide.


Morphology data: We collected morphological data from preserved museum specimens maintained at the University of Michigan Museum of Zoology (UMMZ;; three specimen models were taken from other museums (University of Florida, California Academy of Sciences) via MorphoSource. As skull and tooth morphology are known to vary ontogenetically in snakes, we selected adult specimens for scanning. All specimens were scanned using high-resolution industrial CT scanners (uCT Scanco Medical; nanotom-s nanoCT with Phoenix Datos|x 2 Acquisition; Nikon XT H225ST, Dual tube system 180kV and 225kV. 2000 x 2000 detector). Voxel size varied with specimen size, and ranges between 12 and 40 microns. All image stacks, resulting models, and associated metadata are available online at MorphoSource . We processed images in Avizo 9.2.0 3D software (FEI Company). Using the segmentation editor, we segmented skull elements from images and generated corresponding surface renditions for each specimen.

From surface models, we recorded: number of teeth on each tooth bearing bone, the length of the maxillary bone, and skull dimensions including cranium length, width, and depth. Both the number of teeth present in the specimen as well as total number of teeth, inferred from examination of the bone and corresponding tooth sockets for missing teeth, were recorded. Because snakes often have one or more replacement teeth behind each functional tooth, but these teeth may not be fully developed or are non-functional, we measured only teeth ankylosed to the maxillary bone. We then segmented the maxillary bones from each skull model. We measured the length of each maxillary tooth, from the base of the tooth where it is ankylosed to the maxillary bone, to the apical-most tip, using the 3D length tool. We recorded the putative position of all missing teeth using empty tooth sockets as guides. For specimens with grooved posterior maxillary teeth, we used the semi-landmarking tool to place 5 equidistant points from the base of the tooth to the apical-most point. At each of these points, we took measurements of tooth width, groove width, tooth depth, and groove depth. Groove length was also recorded. Measurements were repeated for each grooved tooth per specimen. From these, we derived the average relative groove dimensions (length, width, depth). 

Prey Subjugation: We searched relevant literature for descriptions of prey subjugation behavior for each species. We categorized prey subjugation mode as one of five categories: venom (medically-significant), venom (not medically-significant), constriction, venom and constriction, or neither venom nor constriction.

Diet Data: We surveyed the published literature for quantitative data on the diet contents of these species, resulting in data for 124 colubriform species. Quantitative data included any diet observation for which it was possible to determine the number of individual predators or prey involved. Thus, our database comprises a heterogeneous mixture of studies that includes observations from dissections of museum specimens as well as observations from chance encounters with free-ranging snakes caught in the act of consuming prey. We categorized diet observations in 11 prey categories as follows: reptiles, reptile eggs, birds, bird eggs, mammals, fishes, amphibians, annelids, arthropods, mollusks, and other. This categorization scheme allowed us to pool data from multiple sources.




Startup funds, University of Michigan - Ann Arbor to ARDR

oVert TCN project, ARDR and DLR, Award: NSF DBI-1701714

David and Lucile Packard Foundation award to DLR