Proteomic taxonomic identification can identify cryptic diversity of Squamata in modern and paleontological specimens

Taxonomic identification of fauna is the foundation for multiple lines of ecological and paleoecological inquiry. However, genomic analyses are increasingly finding morphological similarities can mask species diversity. This cryptic diversity is especially relevant to Squamata (snakes, lizards, and amphisbaenians), members of which tend to be morphologically conserved. ZooMS (zooarchaeology by mass spectrometry) is a proteomic method for taxonomic identification primarily applied to mammals and fish but is largely unexplored in squamates. We expanded the ZooMS reference database to include 23 species of Squamata (Phrynosomatidae and Iguanidae) and reveal proteomic species-level identification is possible for most of our tested species, including within the morphologically indistinguishable Sceloporus undulatus complex. These results open new opportunities for using the fossil record of Squamata for paleoecological investigations, including the reexamination of the long-standing North American herpetofaunal stability hypothesis. We applied this method to the fossil record of Squamata by analyzing 58 fossil lizards from ten paleontological sites in the North American southwest. We found that 37% of the fossils were morphologically misidentified, 58% of misidentifications were to the genus level, and 52% of species-level morphological identifications were incorrect. We additionally found 5% of our modern specimens from natural history collections were misidentified.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2026-04-28
DOI
https://doi.org/10.1038/s41598-025-14392-3
Primary Topic
Amphibian and Reptile Biology
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Proteomic taxonomic identification can identify cryptic diversity of Squamata in modern and paleontological specimens

Timothy M. Shanahan, C BELL, Erin M. Keenan Early, Victoria L. Todd et al.
Scientific Reports
Amphibian and Reptile Biology
article

Proteomic taxonomic identification can identify cryptic diversity of Squamata in modern and paleontological specimens

Timothy M. Shanahan, C BELL, Erin M. Keenan Early, Victoria L. Todd, Matthew J. Collins
article en

Abstract

Taxonomic identification of fauna is the foundation for multiple lines of ecological and paleoecological inquiry. However, genomic analyses are increasingly finding morphological similarities can mask species diversity. This cryptic diversity is especially relevant to Squamata (snakes, lizards, and amphisbaenians), members of which tend to be morphologically conserved. ZooMS (zooarchaeology by mass spectrometry) is a proteomic method for taxonomic identification primarily applied to mammals and fish but is largely unexplored in squamates. We expanded the ZooMS reference database to include 23 species of Squamata (Phrynosomatidae and Iguanidae) and reveal proteomic species-level identification is possible for most of our tested species, including within the morphologically indistinguishable Sceloporus undulatus complex. These results open new opportunities for using the fossil record of Squamata for paleoecological investigations, including the reexamination of the long-standing North American herpetofaunal stability hypothesis. We applied this method to the fossil record of Squamata by analyzing 58 fossil lizards from ten paleontological sites in the North American southwest. We found that 37% of the fossils were morphologically misidentified, 58% of misidentifications were to the genus level, and 52% of species-level morphological identifications were incorrect. We additionally found 5% of our modern specimens from natural history collections were misidentified.

Scientific Reports
University of Copenhagen (DK), University of Cambridge (GB), Care Resource (US), The University of Texas at Austin (US)
University of Texas System, University of Texas at Austin, Paleontological Society, University of Texas at El Paso, Texas Academy of Science
Openalex Percentile: Top 8%
Amphibian and Reptile Biology
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.