The origin of snakes: Revealing the ecology, behavior, and evolutionary history of early snakes using genomics, phenomics, and the fossil record

Abstract

Background
The highly derived morphology and astounding diversity of snakes has long inspired debate regarding the ecological and evolutionary origin of both the snake total-group (Pan-Serpentes) and crown snakes (Serpentes). Although speculation abounds on the ecology, behavior, and provenance of the earliest snakes, a rigorous, clade-wide analysis of snake origins has yet to be attempted, in part due to a dearth of adequate paleontological data on early stem snakes. Here, we present the first comprehensive analytical reconstruction of the ancestor of crown snakes and the ancestor of the snake total-group, as inferred using multiple methods of ancestral state reconstruction. We use a combined-data approach that includes new information from the fossil record on extinct crown snakes, new data on the anatomy of the stem snakes Najash rionegrina, Dinilysia patagonica, and Coniophis precedens, and a deeper understanding of the distribution of phenotypic apomorphies among the major clades of fossil and Recent snakes. Additionally, we infer time-calibrated phylogenies using both new ‘tip-dating’ and traditional node-based approaches, providing new insights on temporal patterns in the early evolutionary history of snakes.

Results
Comprehensive ancestral state reconstructions reveal that both the ancestor of crown snakes and the ancestor of total-group snakes were nocturnal, widely foraging, non-constricting stealth hunters. They likely consumed soft-bodied vertebrate and invertebrate prey that was subequal to head size, and occupied terrestrial settings in warm, well-watered, and well-vegetated environments. The snake total-group – approximated by the Coniophis node – is inferred to have originated on land during the middle Early Cretaceous (~128.5 Ma), with the crown-group following about 20 million years later, during the Albian stage. Our inferred divergence dates provide strong evidence for a major radiation of henophidian snake diversity in the wake of the Cretaceous-Paleogene (K-Pg) mass extinction, clarifying the pattern and timing of the extant snake radiation. Although the snake crown-group most likely arose on the supercontinent of Gondwana, our results suggest the possibility that the snake total-group originated on Laurasia.

Conclusions
Our study provides new insights into when, where, and how snakes originated, and presents the most complete picture of the early evolution of snakes to date. More broadly, we demonstrate the striking influence of including fossils and phenotypic data in combined analyses aimed at both phylogenetic topology inference and ancestral state reconstruction.

Electronic supplementary material
The online version of this article (doi:10.1186/s12862-015-0358-5) contains supplementary material, which is available to authorized users.

Full text

R E S E A R C H A R T I C L E Open Access
The origin of snakes: revealing the ecology,
behavior, and evolutionary history of early snakes
using genomics, phenomics, and the fossil record
Allison Y Hsiang
1*
, Daniel J Field
1,2
, Timothy H Webster
3
, Adam DB Behlke
1
, Matthew B Davis
1
,
Rachel A Racicot
1
and Jacques A Gauthier
1,4
Abstract
Background: The highly derived morphology and astounding diversity of snakes has long inspired debate regarding
the ecological and evolutionary origin of both the snake total-group (Pan-Serpentes) and crown snakes (Serpentes).
Although speculation abounds on the ecology, behavior, and provenance of the earliest snakes, a rigorous, clade-wide
analysis of snake origins has yet to be attempted, in part due to a dearth of adequate paleontological data on early
stem snakes. Here, we present the first comprehensive analytical reconstruction of the ancestor of crown snakes and
the ancestor of the snake total-group, as inferred using multiple methods of ancestral state reconstruction. We use a
combined-data approach that includes new information from the fossil record on extinct crown snakes, new data
on the anatomy of the stem snakes Najash rionegrina, Dinilysia patagonica,andConiophis precedens, and a deeper
understanding of the distribution of phenotypic apomorphies among the major clades of fossil and Recent snakes.
Additionally, we infer time-calibrated phylogenies using both new ‘tip-dating’and traditional node-based approaches,
providing new insights on temporal patterns in the early evolutionary history of snakes.
Results: Comprehensive ancestral state reconstructions reveal that both the ancestor of crown snakes and the
ancestor of total-group snakes were nocturnal, widely foraging, non-constricting stealth hunters. They likely consumed
soft-bodied vertebrate and invertebrate prey that was subequal to head size, and occupied terrestrial settings in warm,
well-watered, and well-vegetated environments. The snake total-group –approximated by the Coniophis node –is
inferred to have originated on land during the middle Early Cretaceous (~128.5 Ma), with the crown-group following
about 20 million years later, during the Albian stage. Our inferred divergence dates provide strong evidence for a
major radiation of henophidian snake diversity in the wake of the Cretaceous-Paleogene (K-Pg) mass extinction,
clarifying the pattern and timing of the extant snake radiation. Although the snake crown-group most likely arose on
the supercontinent of Gondwana, our results suggest the possibility that the snake total-group originated on Laurasia.
Conclusions: Our study provides new insights into when, where, and how snakes originated, and presents the most
complete picture of the early evolution of snakes to date. More broadly, we demonstrate the striking influence of
including fossils and phenotypic data in combined analyses aimed at both phylogenetic topology inference and
ancestral state reconstruction.
Keywords: Serpentes, Phylogeny, Ancestral state reconstruction, Divergence time estimation, Combined analysis,
Fossil tip-dating
* Correspondence: allison.hsiang@yale.edu
1
Department of Geology and Geophysics, Yale University, New Haven,
Connecticut 06520, USA
Full list of author information is available at the end of the article
© 2015 Hsiang et al.; licensee BioMed Central. This is an Open Access article distributed under the terms of the Creative
Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and
reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain
Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article,
unless otherwise stated.
Hsiang et al. BMC Evolutionary Biology (2015) 15:87
DOI 10.1186/s12862-015-0358-5

Background
Living snakes (Serpentes) comprise more than 3,400
species. They are virtually cosmopolitan in distribution,
occupying fossorial, arboreal, terrestrial, and aquatic
environs, and living in climates ranging from arid deserts
to the open ocean. Crown snakes are split into two major
clades: Scolecophidia, which includes blind snakes and
thread snakes, and Alethinophidia, which comprises all
other snakes [1]. Within Alethinophidia, the most diverse
and disparate clade is Henophidia, which includes booids
(pythons and boas) and caenophidians (viperids, elapids,
and colubrids).
The ecological and evolutionary origins of snakes have
long been debated in light of the clade’s incredible extant
diversity, and the distinctive snake body plan. Among the
major questions surrounding snake origins are whether
snakes first arose on the Mesozoic supercontinent of
Gondwana or Laurasia, whether snakes originated on land
or in the sea, and whether the earliest snakes were fossorial,
terrestrial, or arboreal in their habits. Inferring the
phenotype, ecology, and biogeography of the ancestral
snake has heretofore been hindered by the relative lack of
informative fossils of early stem snakes. Furthermore,
deciphering the evolutionary origins of snakes is compli-
cated by the fact that scolecophidian snakes, which are
sister to all other crown snakes, are highly modified and
overprinted with unique morphological and behavioral
apomorphies [2,3]. These include ecological and be-
havioral features such as exclusively fossorial habits,
specialized feeding on social insects and their larvae, as
well as derived phenotypic characteristics such as highly
reduced eyes, uniquely modified jaws, and smooth, deeply
imbricate, cycloid body scales.
However, recent discoveries of more complete,
better-preserved specimens of fossil stem snakes such
as Dinilysia patagonica (Santonian-Campanian) [4],
Najash rionegrina (Cenomanian) [5,6], and Coniophis
precedens (Maastrichtian) [7] suggest that the unique
characteristics of scolecophidians likely do not repre-
sent the ancestral condition for snakes. Phylogenetic
analyses indicate that Dinilysia,Najash,andConiophis
represent successively more remote hierarchical sisters to
crown snakes, with Dinilysia representing the imme-
diate sister to the crown [4,7,8]. These specimens
thus provide abundant new data on the origin of early
snakes. Importantly, these fossil species are also un-
ambiguously terrestrial [4,7,8]: this, in combination
with the recently revised phylogenetic position of the
limbed Tethyan marine snakes (Simoliophiidae; e.g.,
Haasiophis terrasanctus [9], Eupodophis descouensis
[10],and Pachyrachis problematicus [11]) as nested
within Alethinophidia (rather than representing stem
snakes) [4,8], offers compelling evidence against the
marine origin hypothesis for snakes.
These recent fossil findings, in conjunction with fossils
of previously unknown, extinct members of crown
Serpentes such as Sanajeh indicus [12] and Kataria
anisodonta [13], provide abundant new data on the
morphology and evolution of the earliest known
snakes, and emphasize the crucial role fossils play in
accurately inferring evolutionary history [14]. In light
of this newfound wealth of fossil data, we infer the
ecology, behavior, and biogeography of early snakes
by synthesizing information from the fossil record
with phenotypic and genetic data for Recent species.
Specifically, we reconstruct the ancestor of the snake
total-group and of crown snakes, using both established
and recently developed analytical methodologies.
Additionally, we infer divergence time trees using a
combination of traditional node-based dating and
novel fossil tip-dating methods [15,16] to explore the
pattern and timing of major events in early snake
evolution.
Results and discussion
Phylogenetic analyses
The complete dataset comprises 766 phenotypic characters,
18,320 base pairs (bp) from 21 nuclear loci and one mito-
chondriallocus,and11novelcharacters for ancestral state
reconstruction (see Methods for more details). Bayesian
phylogenetic trees were inferred using the following four
datasets: 1) phenotypic data alone (hereafter referred to as
the ‘phenotypic’topology; Figure 1); 2) genetic data alone
(hereafter referred to as the ‘genetic’topology; Figure 2);
3) the combined phenotypic and genetic dataset,
without any topological constraints (hereafter referred
to as the ‘unconstrained’topology; Figure 3); and 4)
the combined phenotypic and genetic dataset, with
topological constraints enforced such that the relationships
of the major clades correspond to those inferred using the
morphological data (hereafter referred to as the ‘constrained’
topology; Figure 4). The constrained analysis was imple-
mented in order to test hypotheses of character evolution
onthephenotypictreetopologywithbranchlengths
inferred using the complete dataset. In addition, maximum
parsimony trees were inferred using the phenotype-only
dataset (Figure 5) and the combined dataset (Figure 6).
In general, most nodes are consistent across all trees
with high support. Clades that appear in both the tree
inferred from the phenotypic dataset using parsimony
and the tree inferred using Bayesian methods are always
well supported under both optimality criteria. In the few
instances where parsimony and Bayesian topologies for
the phenotypic dataset differ, support for an alternative
topology is invariably poor (e.g., support for monophyly
of Boinae [Epicrates striatus + Boa constrictor]isstrongin
parsimony [Figure 5], while support for paraphyly of
Boinae is weak in the Bayesian analysis [Figure 1]). The
Hsiang et al. BMC Evolutionary Biology (2015) 15:87 Page 2 of 22

Anguidae
Xenosauridae
Varanoidea
‘Total-Group’ Node
‘Serpentes’ Node
Anilioidea
Scolecophidia
Simoliophiidae
Xenopeltidae
Bolyeriidae
Booidea
Pythonidae
Boinae
Tropidophiidae
Viperidae
Colubridae
Lamprophiidae
Elapidae
Alethinophidia
Macrostomata
Henophidia
Caenophidia
Colubroidea
0.4
Celestus enneagrammus
Daboia russelii
Calabaria reinhardtii
Proplatynotia longirostrata†
Varanus salvator
Tropidophis haetianus
Atractaspis irregularis
Loxocemus bicolor
Shinisaurus crocodilurus
Liotyphlops albirostris
Bothrops asper
Elgaria multicarinata
Afronatrix anoscopus
Acrochordus granulatus
Coluber constrictor
Eryx colubrinus
Sanajeh indicus†
Epicrates striatus
Lachesis muta
Causus rhombeatus
Casarea dussumieri
Xenosaurus grandis
Heloderma horridum
Cylindrophis ruffus
Natrix natrix
Lampropeltis getula
Lichanura trivirgata
Trachyboa boulengeri
Dinilysia patagonica†
Xenosaurus platyceps
Lanthanotus borneensis
Pachyrhachis problematicus†
Notechis scutatus
Azemiops feae
Xenopeltis unicolor
Typhlops jamaicensis
Helodermoides tuberculatus†
Yurlunggur camfieldensis†
Xenodermus javanicus
Lycophidion capense
Anomochilus leonardi
Xenochrophis piscator
Exiliboa placata
Ungaliophis continentalis
Micrurus fulvius
Kataria anisodonta†
Boa constrictor
Wonambi naracoortensis†
Eupodophis descouensis†
Thamnophis marcianus
Heloderma suspectum
Coniophis precedens†
Amphiesma stolata
Pareas hamptoni
Peltosaurus granulosus†
Uropeltis melanogaster
Anilius scytale
Xenophidion acanthognathus
Gobiderma pulchrum†
Agkistrodon contortrix
Aparallactus werneri
Pseudopus apodus
Najash rionegrina†
Aspidites melanocephalus
Haasiophis terrasanctus†
Laticauda colubrina
Rena dulcis
Saniwa†
Varanus acanthurus
Typhlophis squamosus
Python molurus
Naja naja
Varanus exanthematicus
0.99
0.99
0.99
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Madtsoiidae
Figure 1 Bayesian phylogenetic tree inferred from phenotypic dataset. Fifty-percent majority rule consensus tree from Bayesian analysis of the
state-partitioned phenotypic dataset (766 characters) under the Mkv model [74] in MrBayes. Node values are Bayesian posterior probability support
values; only values above 90% are shown. Scale bar represents substitutions/site. Colored boxes indicate major clades. Fossil taxa are marked with
a dagger (†).
Hsiang et al. BMC Evolutionary Biology (2015) 15:87 Page 3 of 22

parsimony and Bayesian analyses of the (unconstrained)
combined dataset also match in general, with the one
notable exception of parsimony inferring a large polytomy
at the base of Alethinophidia, comprised of Anilius,
Kataria, Tropidophiidae, the clade of Cylindrophis +
Anomochilus +Uropeltis, the Simoliophiidae, the clade of
Xenopeltis +Loxocemus + Pythonidae, and a polyphyletic
‘Booidea’(Figure 6).
The most striking differences are between trees inferred
from the phenotype vs. the genotype. Scolecophidia, for
example, is inferred to be paraphyletic (and Anomalepididae
polyphyletic) in the genetic tree (Figure 2). This result con-
curs with other recent phylogenetic analyses using genetic
data to target snake interrelationships [17-19]. However, in
the phenotypic tree (Figure 1), as well as in the combined
trees (both unconstrained [Figure 3] and constrained
Xenosauridae
‘Varanoidea’
Anguidae
‘Scolecophidia’
Bolyeriidae
Boinae
Pythonidae
‘Booidea’
Tropidophiidae
Lamprophiidae
Elapidae
Colubridae
Viperidae
‘Xenopeltidae’
‘Anilioidea’
0.06
Liotyphlops albirostris
Micrurus fulvius
Pseudopus apodus
Lichanura trivirgata
Naja naja
Tropidophis haetianus
Cylindrophis ruffus
Uropeltis melanogaster
Lycophidion capense
Amphiesma stolata
Elgaria multicarinata
Calabaria reinhardtii
Varanus acanthurus
Aparallactus werneri
Daboia russelii
Aspidites melanocephalus
Ungaliophis continentalis
Heloderma suspectum
Epicrates striatus
Agkistrodon contortrix
Heloderma horridum
Boa constrictor
Shinisaurus crocodilurus
Casarea dussumieri
Lanthanotus borneensis
Afronatrix anoscopus
Azemiops feae
Celestus enneagrammus
Rena dulcis
Python molurus
Typhlophis squamosus
Coluber constrictor
Laticauda colubrina
Lachesis muta
Loxocemus bicolor
Varanus salvator
Pareas hamptoni
Varanus exanthematicus
Xenochrophis piscator
Acrochordus granulatus
Natrix natrix
Causus rhombeatus
Thamnophis marcianus
Notechis scutatus
Trachyboa boulengeri
Xenosaurus grandis
Anilius scytale
Eryx colubrinus
Bothrops asper
Xenodermus javanicus
Typhlops jamaicensis
Lampropeltis getula
Xenopeltis unicolor
Xenosaurus platyceps
Exiliboa placata
Atractaspis irregularis
1
1
1
1
1
1
1
1
1
1
1
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1
1
0.99
0.95
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0.99
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‘Serpentes’ Node
Alethinophidia
Macrostomata
Henophidia
Caenophidia
Colubroidea
Figure 2 Bayesian phylogenetic tree inferred from genetic dataset. Fifty-percent majority rule consensus tree from Bayesian analysis of the
gene-partitioned genetic dataset (21 nuclear loci and one mitochondrial locus) in MrBayes. Node values are Bayesian posterior probability support
values; only values above 90% are shown. Scale bar represents substitutions/site. Colored boxes indicate major clades. Colored lines indicate major
clades from traditional taxonomies that do not resolve as monophyletic groups in this topology.
Hsiang et al. BMC Evolutionary Biology (2015) 15:87 Page 4 of 22

[Figure 4]), Scolecophidia is inferred to be the monophyletic
sister to Alethinophidia (however, in the phenotypic and
constrained topologies, a sister relationship between the
scolecophidian clades Leptotyphlopidae and Typhlopidae is
strongly supported, whereas in the unconstrained topology,
the anomalepidids Typhlophis squamosus and Liotyphlops
albirostris are successive sisters to Typhlopidae, rendering
Anomalepididae paraphyletic). It is particularly notable that
the unconstrained tree in our study recovers a monophyletic
Scolecophidia, as it suggests that the addition of pheno-
typic data to a dataset dominated by genetic data (as would
typically be the case in phylogenetic analyses that combine
Xenosauridae
Anguidae
‘Varanoidea’
Scolecophidia
Madtsoiidae
Simoliophiidae
Tropidophiidae ‘Anilioidea’
‘Xenopeltidae’
Pythonidae
Boinae ‘Booidea’
Bolyeriidae
Viperidae
Colubridae
Lamprophiidae
Elapidae
0.2
Heloderma horridum
Rena dulcis
Uropeltis melanogaster
Xenophidion acanthognathus
Boa constrictor
Atractaspis irregularis
Peltosaurus granulosus†
Anomochilus leonardi
Python molurus
Yurlunggur camfieldensis†
Lachesis muta
Thamnophis marcianus
Typhlophis squamosus
Calabaria reinhardtii
Xenodermus javanicus
Aspidites melanocephalus
Shinisaurus crocodilurus
Typhlops jamaicensis
Pachyrhachis problematicus†
Aparallactus werneri
Varanus acanthurus
Trachyboa boulengeri
Xenosaurus grandis
Saniwa†
Causus rhombeatus
Azemiops feae
Ungaliophis continentalis
Pseudopus apodus
Lichanura trivirgata
Proplatynotia longirostrata†
Naja naja
Daboia russelii
Lampropeltis getula
Kataria anisodonta†
Sanajeh indicus†
Afronatrix anoscopus
Epicrates striatus
Amphiesma stolata
Haasiophis terrasanctus†
Tropidophis haetianus
Elgaria multicarinata
Anilius scytale
Coluber constrictor
Gobiderma pulchrum†
Coniophis precedens†
Cylindrophis ruffus
Xenosaurus platyceps
Casarea dussumieri
Lanthanotus borneensis
Xenochrophis piscator
Pareas hamptoni
Wonambi naracoortensis†
Heloderma suspectum
Loxocemus bicolor
Lycophidion capense
Natrix natrix
Helodermoides tuberculatus†
Notechis scutatus
Najash rionegrina†
Agkistrodon contortrix
Exiliboa placata
Eryx colubrinus
Varanus salvator
Dinilysia patagonica†
Celestus enneagrammus
Micrurus fulvius
Liotyphlops albirostris
Bothrops asper
Acrochordus granulatus
Laticauda colubrina
Eupodophis descouensis†
Varanus exanthematicus
Xenopeltis unicolor
1
1
1
1
1
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0.98
0.99
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0.97
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0.92
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‘Total-Group’ Node
‘Serpentes’ Node
Alethinophidia
Macrostomata
Henophidia
Caenophidia
Colubroidea
Figure 3 Bayesian phylogenetic tree inferred from combined genetic and phenotypic dataset, unconstrained. Fifty-percent majority rule
consensus tree from Bayesian analysis of the unconstrained combined genetic and phenotypic datasets (with corresponding partition schemes)
in MrBayes. Node values are Bayesian posterior probability support values; only values above 90% are shown. Scale bar represents substitutions/
site. Colored boxes indicate major clades. Colored lines indicate major clades from traditional taxonomies that do not resolve as monophyletic
groups in this topology. Fossil taxa are marked with a dagger (†). Grayed taxon names indicate extant species that are included on the basis of
phenotypic data only.
Hsiang et al. BMC Evolutionary Biology (2015) 15:87 Page 5 of 22

Anguidae
Xenosauridae
Varanoidea
‘Total-Group’ Node
‘Serpentes’ Node
Anilioidea
Madtsoiidae
Scolecophidia
Simoliophiidae
Xenopeltidae
Bolyeriidae
Booidea
Pythonidae
Boinae
Tropidophiidae
Viperidae
Colubridae
Lamprophiidae
Elapidae
Alethinophidia
Macrostomata
Henophidia
Caenophidia
Colubroidea
0.07
Yurlunggur camfieldensis†
Laticauda colubrina
Aparallactus werneri
Casarea dussumieri
Haasiophis terrasanctus†
Coluber constrictor
Exiliboa placata
Rena dulcis
Anilius scytale
Amphiesma stolata
Notechis scutatus
Xenosaurus platyceps
Epicrates striatus
Daboia russelii
Afronatrix anoscopus
Pseudopus apodus
Eryx colubrinus
Python molurus
Eupodophis descouensis†
Trachyboa boulengeri
Uropeltis melanogaster
Xenodermus javanicus
Lachesis muta
Ungaliophis continentalis
Agkistrodon contortrix
Najash rionegrina†
Bothrops asper
Xenochrophis piscator
Dinilysia patagonica†
Cylindrophis ruffus
Typhlophis squamosus
Gobiderma pulchrum†
Lichanura trivirgata
Typhlops jamaicensis
Saniwa†
Xenophidion acanthognathus
Liotyphlops albirostris
Boa constrictor
Heloderma suspectum
Xenosaurus grandis
Lycophidion capense
Pachyrhachis problematicus†
Azemiops feae
Lanthanotus borneensis
Natrix natrix
Thamnophis marcianus
Anomochilus leonardi
Xenopeltis unicolor
Atractaspis irregularis
Varanus acanthurus
Aspidites melanocephalus
Kataria anisodonta†
Varanus salvator
Micrurus fulvius
Acrochordus granulatus
Tropidophis haetianus
Causus rhombeatus
Coniophis precedens†
Lampropeltis getula
Elgaria multicarinata
Calabaria reinhardtii
Helodermoides tuberculatus†
Celestus enneagrammus
Shinisaurus crocodilurus
Peltosaurus granulosus†
Proplatynotia longirostrata†
Sanajeh indicus†
Varanus exanthematicus
Wonambinaracoortensis†
Loxocemus bicolor
Heloderma horridum
Pareas hamptoni
Naja naja
1
0.99
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Figure 4 (See legend on next page.)
Hsiang et al. BMC Evolutionary Biology (2015) 15:87 Page 6 of 22

the two sources of data) can have significant effects on tree
topology –in this case, resulting in the more traditional
inference of scolecophidian monophyly.
Several other major differences exist between the
phenotypic/constrained trees and the genetic/unconstrained
trees. The viperid snake Daboia russelii is inferred to be
sister to Crotalinae (i.e., pit vipers; in this case, Bothrops +
Agkistrodon +Lachesis) in the phenotypic (Figure 1), uncon-
strained (Figure 3), and constrained trees (Figure 4),
whereas it is sister to Causus rhombeatus in the genetic tree
(See figure on previous page.)
Figure 4 Bayesian phylogenetic tree inferred from combined genetic and phenotypic dataset, constrained. Fifty-percent majority rule consensus
tree from Bayesian analysis of the combined genetic and phenotypic datasets, with topology constraints implemented as described in the text, as
estimated in MrBayes. Node values are Bayesian posterior probability support values; only values above 90% are shown. Scale bar represents sub-
stitutions/site. Colored boxes indicate major clades. Fossil taxa are marked with a dagger (†). Grayed taxon names indicate extant species that are
included on the basis of phenotypic data only.
Varanus salvator
Najash rionegrina†
Xenochrophis piscator
Thamnophis marcianus
Ungaliophis continentalis
Rena dulcis
Naja naja
Coluber constrictor
Shinisaurus crocodilurus
Amphiesma stolata
Saniwa†
Proplatynotia longirostrata†
Typhlophis squamosus
Wonambi naracoortensis†
Anilius scytale
Laticauda colubrina
Kataria anisodonta†
Calabaria reinhardtii
Xenosaurus grandis
Loxocemus bicolor
Agkistrodon contortrix
Xenophidion acanthognathus
Lycophidion capense
Tropidophis haetianus
Uropeltis melanogaster
Python molurus
Lichanura trivirgata
Varanus acanthurus
Eupodophis descouensis†
Heloderma horridum
Trachyboa boulengeri
Lachesis muta
Heloderma suspectum
Elgaria multicarinata
Celestus enneagrammus
Casarea dussumieri
Aspidites melanocephalus
Xenosaurus platyceps
Notechis scutatus
Epicrates striatus
Atractaspis irregularis
Lanthanotus borneensis
Aparallactus werneri
Lampropeltis getula
Pseudopus apodus
Dinilysia patagonica†
Pachyrhachis problematicus†
Bothrops asper
Peltosaurus granulosus†
Xenodermus javanicus
Liotyphlops albirostris
Boa constrictor
Natrix natrix
Gobiderma pulchrum†
Anomochilus leonardi
Coniophis precedens†
Typhlops jamaicensis
Eryx colubrinus
Micrurus fulvius
Pareas hamptoni
Haasiophis terrasanctus†
Yurlunggur camfieldensis†
Cylindrophis ruffus
Helodermoides tuberculatus†
Afronatrix anoscopus
Sanajeh indicus†
Varanus exanthematicus
Xenopeltis unicolor
Azemiops feae
Causus rhombeatus
Acrochordus granulatus
Daboia russelii
Exiliboa placata
78.3
99.2
99.4
99.6
90.3
88.5
76.4
100
99.9
96.8
99.1
78.1
94.1
100
75.6
93.3
80.4
87.1
100
93.9
100
99.9
96.5
86.6
96.2
80.9
76.9
99.1
93.1
94.3
95.3
80.6
83.1
93.0
81.6
88.2
83.2
96.7
91.7
99.6
‘Anguidae’
Xenosauridae
Varanoidea
‘Total-Group’ Node
‘Serpentes’ Node
Anilioidea
Madtsoiidae
Scolecophidia
Simoliophiidae
Xenopeltidae
Bolyeriidae
Booidea
Pythonidae
Boinae
Tropidophiidae
Viperidae
Colubridae
Lamprophiidae
Elapidae
Alethinophidia
Macrostomata
Henophidia
Caenophidia
Colubroidea
Figure 5 Phylogenetic tree inferred using parsimony using phenotypic data. Fifty-percent majority rule bootstrap consensus tree from heuristic
searches under the parsimony framework using the complete phenotypic dataset. Node values are bootstrap probabilities; only those above 75%
are shown. Colored boxes indicate major clades. Colored lines indicate major clades from traditional taxonomies that do not resolve as monophyletic
groups in this topology. Fossil taxa are marked with a dagger (†).
Hsiang et al. BMC Evolutionary Biology (2015) 15:87 Page 7 of 22

(Figure 2), making it part of a clade that is sister to all other
Viperidae. In addition, the phenotypic and constrained trees
strongly support a monophyletic Xenopeltidae (= Xenopeltis
unicolor + Loxocemus bicolor) as sister to all other members
of Macrostomata, whereas the genetic and unconstrained
trees firmly place them as successive sisters to Pythonidae
(which is also recovered to be outside Booidea). This result
concurs with other recent studies of snake phylogeny based
on concatenated gene sequences [18].
The position of Tropidophiidae within Alethinophidia
is radically different among trees derived from these
datasets. In the genetic and unconstrained trees, Anilioidea
is polyphyletic (Figures 2 and 3): Cylindrophis,Uropeltis,
and Anomochilus form a clade sister to Macrostomata,
with Anilius + Tropidophiidae (= Trachyboa boulengeri +
Tropidophis haetianus) as the next successive sister
group. The Anilius + Tropidophiidae clade, also termed
Amerophidia [20] after their exclusive extant presence in
the New World (though, notably, the earliest total-group
tropidophiids are known from Europe and North Africa in
thelateEocene[21-25]),isstronglysupportedbymolecular
data in this study, in agreement with previous phyloge-
nomic analyses of snake phylogeny [1,19,26,27]. In contrast,
the phenotypic and constrained trees recover Tropidophii-
dae in its traditional position nested within henophidian
macrostomatans, as sister to Caenophidia (Figures 1 and 4).
Notably, in the unconstrained tree, the support values
for the Anilius + Tropidophiidae clade, and for the
sister relationship between the clade of Cylindrophis +
Uropeltis + Anomochilus and Macrostomata, are not
significant. This collapse in support values relative to
the genetic tree (for which the posterior probabilities for
both hypotheses are 100%) is likely due to the inclusion of
strongly discordant phenotypic data in the unconstrained
analysis. Indeed, to date only a single morphological
apomorphy –specifically, an oviduct connecting with
diverticuli of the cloaca, instead of directly with the cloaca
as in all other squamates –has been found to be shared
by Anilius and Tropidophiidae [28]. In addition, the
splitting of Cylindrophis,Uropeltis,andAnomochilus from
Figure 6 Phylogenetic tree inferred using parsimony using the combined dataset. Fifty-percent majority rule bootstrap consensus tree from
heuristic searches under the parsimony framework using the combined (phenotypic + genetic) dataset. Node values are bootstrap probabilities;
only those above 75% are shown. Colored boxes indicate major clades. Colored lines indicate major clades from traditional taxonomies that do
not resolve as monophyletic groups in this topology. Fossil taxa are marked with a dagger (†).
Hsiang et al. BMC Evolutionary Biology (2015) 15:87 Page 8 of 22

Anilius in the genetic tree, and the placement of the
former three taxa within basal macrostomatans, would
require the “redevelopment of a complex multipinnate jaw
adductor musculature comparable to that of lizards”[29].
Furthermore, although it can be argued that Anilius and
uropeltines may be artificially drawn together due to
convergence in their skulls related to shared fossorial
habits, such an argument does not account for the
fact that other fossorial snakes, such as Loxocemus,
are never recovered as being closely allied to Anilius
or Uropeltis. The question of whether Amerophidia
(Anilius + Tropidophiidae) represents a true clade clearly
requires further study; regardless, including phenotypic
characters in our combined dataset collapses strong sup-
port for Amerophidia, again demonstrating the potential
influence of including phenotypic data even in large-scale
phylogenomic studies, despite marked discrepancies in
the number of characters from each source (in this case,
18,320 nucleotide bp vs. 766 phenotypic characters). We
emphasize here that we do not mean to suggest that the
morphological signal is necessarily the ‘correct’one, but
rather that including morphological data can be beneficial
and effective at identifying portions of phylogenetic trees
that may not be as uncontroversial as genomic data alone
may suggest –whether by directly affecting the topology
itself (as in Scolecophidia becoming monophyletic in
our unconstrained combined analysis) or by collapsing
the support values of controversial groups (as in the
case of Amerophidia). Our study presents empirical
evidence against the commonly held view that genomic
data, by virtue of their abundance, will inevitably ‘swamp
out’conflicting signals from morphological data, rendering
their contribution negligible and thus ignorable (viz., that
phenotypic characters are merely baubles to be suspended
on genomic trees).
The placement of several fossil taxa differs between the
unconstrained tree and the phenotypic and constrained
trees. For instance, marine simoliophiids are inferred to
form a clade that is sister to Alethinophidia in the uncon-
strained tree (Figure 3), in contrast to the phenotypic
(Figure 1) and constrained trees (Figure 4), where
they are nested within Alethinophidia as sister to crown
Macrostomata. The Simoliophiidae + Alethinophidia sister
relationship in the unconstrained tree is, however, poorly
supported. In all cases, simoliophiids are inferred to be
nested within crown snakes with high support, and do not
represent stem snakes (as has been suggested by some
[11]), despite retaining tiny hindlimbs.
The unconstrained, constrained, and phenotypic trees
all strongly support Madtsoiidae (= Sanajeh indicus,
Wonambi naracoortensis, and Yurlunggur camfieldensis)
as stem alethinophidians (Figures 1, 3, and 4), and thus
as belonging to the snake crown-group (see also Apesteguía
and Zaher [30] and Longrich et al. [7]). This suggests that
madtsoiids, and by extension the ancestor of crown snakes,
likely also retained tiny hindlimbs with ankles and toes, as
in stem snakes and simoliophiids –unlike any extant
snakes. At this point, however, we can only be sure that
madtsoiids retained at least part of the hindlimb, as
Wonambi naracoortensis has a scolecophidian-like
triradiate pelvis with a well-developed acetabulum for
reception of the femoral head [31].
The unconstrained tree and constrained/phenotypic
trees further differ in the placement of the Paleocene
fossil snake Kataria anisodonta, from South America
[13]. In the unconstrained topology, Kataria is recon-
structed as sister to Tropidophiidae, with Anilius scytale
as sister to both of these taxa (Figure 3). In contrast, the
phenotypic and constrained analyses (Figures 1 and 4)
infer that Kataria is nested within Macrostomata and
Henophidia as sister to Tropidophiidae + Caenophidia,
in agreement with Scanferla et al. [13]. The placement of
Kataria exhibited in the unconstrained tree is not strongly
supported, and likely reflects a passive consequence of its
allegiance with Tropidophiidae and Caenophidia, clades
that are strongly supported in all analyses of all datasets.
Both the genetic and unconstrained trees resolve
Xenodermus javanicus as the immediate sister taxon of
Colubroidea, followed by Acrochordus granulatus as sister
to the Xenodermus + Colubroidea clade (Figures 2 and 3).
This is contrary to the strongly supported phenotypic/
constrained topology, in which the positions of Xenodermus
and Acrochordus are reversed (Figures 1 and 4). Although
other studies of concatenated gene sequences have inferred
thesametopologyasourgenetictreewithequallyhigh
support [18,26], the recent Pyron et al. [19] supertree
recovered an alternate, highly supported topology in which
Xenodermatidae and Acrochordus form a clade that is
sister to Colubroidea. The disagreement between genetic
tree topologies for these taxa illustrates the existence of
extensive homoplasy in multi-gene, phylogenomic datasets
[32,33] (‘homoplasy’here intended in the broad sense as
referring to any potentially confounding phylogenetic
signal that does not arise from common ancestry –
circumscribing not merely functional convergence but
also phenomena such as long-branch attraction and
incomplete lineage sorting). Definitively unraveling the
relationships among Xenodermatidae, Acrochordus,and
Colubroidea will require further study.
In all analyses, Dinilysia patagonica, Najash rionegrina,
and Coniophis precedens form successive sisters to crown
Serpentes, supporting their status as early members of
Pan-Serpentes, with Coniophis as the earliest-diverging
stem snake currently known. Although Najash and
Coniophis are clearly stem snakes more distantly related
to the crown than is Dinilysia,theinferencethatConiophis,
rather than Najash, is sister to all other known snakes
depends on the correct attribution to that species of
Hsiang et al. BMC Evolutionary Biology (2015) 15:87 Page 9 of 22

isolated, tooth-bearing bones with numerous disarticulated
vertebrae, all from the Maastrichtian of the American
Interior West [7]. The validity of this standpoint remains
controversial, and its resolution will require additional
discoveries of associated/articulated Coniophis specimens
[34] and more complete knowledge of Najash.
Ancestral state reconstruction
Ancestral state reconstructions (ASR) were conducted
for 11 characters (see Additional file 1) for the genetic
(see Additional file 2), unconstrained (see Additional file 3),
and constrained (see Additional file 4) topologies, using
three methods: parsimony, Yang et al.’s maximum likeli-
hood (ML) re-rooting method [35], and Bayesian stochastic
character mapping [36,37], representing a total of 99 indi-
vidual ASR analyses. We chose to implement all three
methods in order to compare their results and establish
robustness (or the lack thereof ) of our results. In particular,
we were concerned with how variable reconstructions were
across methods, and how different ways of defining a
character –i.e., the binary ‘Plate I’character vs. the much
more highly atomized ‘Plate II’character –mightaffectour
results. The Bayesian stochastic character mapping method
was chosen in particular for its ability to include poly-
morphic and missing characters –which are extensive in
our dataset –during the inference process. ASR results are
reported for the ‘Serpentes’(i.e., crown-snake) node and the
‘Total-Group’node, with Bayesian results reported as pos-
terior probabilities (PP), ML results reported as proportions
of total likelihood (PTL), and the most parsimonious
state(s) reported for parsimony.
ASR results are largely invariant across different
reconstruction methods and tree topologies. However,
several reconstructions fail (i.e., produce ambiguous/
uninformative results where all possible states are
equally likely) for the genetic topology. Specifically,
this occurs for the ‘Diel’,‘Plate II’,‘Biome’,‘Habitat
Stratum’,and‘Aquatic Habits’characters. In contrast,
for the constrained and unconstrained tree topologies,
ASR fails only for the ‘Biome’character using the ML
method. This suggests that this genetic topology is
particularly poorly suited to ancestral state analyses,
perhaps because, due to its lack of intermediate,
branch-shortening fossils, it fails to approximate the
full distribution of character states that existed across
the evolutionary history of snakes. This underscores
the importance of including fossils as terminal taxa in
ancestral state reconstruction analyses; for scenarios
in which the genetic-only dataset fails in its ancestral state
reconstruction, analyses of the combined datasets fail in
only one of these (the highly variable ‘Biome’character,
using ML). Previous studies, both theoretical [38-40] and
empirical [14,41-43], have demonstrated that the inclusion
of fossil data in ancestral state reconstructions improves
the precision, accuracy, and overall performance of these
analyses. Our results corroborate these ideas, further
demonstrating that in certain cases, the lack of fossil
taxa in these analyses may actually render the recon-
struction of ancestral states impossible. Fossil data are
indispensable for reliably interpreting evolutionary
history, as they serve to constrain possible hypotheses
of character evolution and capture a more complete
picture of character state distributions across evolutionary
time and phylogenetic diversity.
Both the ancestor of crown snakes and the earliest
known ancestor of the snake total-group are reconstructed
unambiguously by all methods and on all topologies to
have been land-dwelling, supporting the hypothesis that
snakes originated in a terrestrial, rather than a marine,
setting [4,7,8]. This is consistent with independent
inferences of terrestrial habits for the oldest member of
Pan-Serpentes (late Upper Albian) [44], Najash rionegrina,
Dinilysia patagonica [45], and Lapparentophis defren-
nei [46]. These results further corroborate the sugges-
tion that the limbed Tethyan Simoliophiidae represent an
independent invasion of the marine realm. Although a ter-
restrial origin of snakes might imply that the snake body
plan (e.g., reduced limbs and long bodies) is an adaptation
for a burrowing lifestyle (fossoriality) [47], our inference
for the primary habitat stratum for both the ‘Serpentes’
and the ‘Total-Group’node is somewhat ambiguous: al-
though the Bayesian and ML methods reconstruct the
most likely stratum for both ancestors as surface-dwelling,
the PP and PTL values are relatively low in the con-
strained topology (around 0.70 to 0.80, rather than > 0.90
as in most of the other reconstructions). Furthermore, re-
constructions of terrestrial habits and fossoriality are
equally parsimonious for both ancestors and topologies.
Such ambiguity is not entirely unexpected, as many extant
snakes exhibit a combination of habits, and some species
may even vary in stratum preference based on age and size
[48]. Regardless, our results suggest that the conclusion
that the snake body plan evolved as an adaptation for a
fossorial lifestyle is by no means foregone, and that bur-
rowing taxa such as scolecophidians, and perhaps even
anilioids, may have evolved from ancestors less committed
to life underground [49].
Several additional conclusions can be drawn regarding
the ecology and behavior of both the ancestor of crown
snakes, and the ancestor of total-group snakes based
on our analyses. Both ancestors likely inhabited well-
vegetated environs in warm, moist, and equable climates
(characterized as tropical to subtropical broad-leafed
forest biomes today; note, however, that broad-leafed
evergreen forests did not exist in the middle Cretaceous,
and that these ‘biome’characters refer to analogous
physical climate conditions, regardless of the specific
plants that happen to live in them today). This ecological
Hsiang et al. BMC Evolutionary Biology (2015) 15:87 Page 10 of 22

preference spans much of the early history of snakes, from
the branch stretching from Serpentes to Caenophidia.
This may explain why, despite an extraordinary diversity
of squamate fossils from these sediments, snakes have
never been recovered from the more arid environs of the
Upper Cretaceous of Mongolia [50].
Ancestral snakes are strongly inferred to have been
nocturnal, with the acquisition of diurnal habits
apparently occurring inside Colubroidea, specifically in
the clade stemming from the last common ancestor of
Elapidae and Colubridae (Figure 7). This return to diur-
nal habits –which are likely ancestral for reptiles [51] –
may explain certain aspects of the evolutionary history
of Colubroidea. Specifically, although colubroids experi-
enced extensive diversification during Late Oligocene
climatic warming, this wide taxonomic breadth was not
Figure 7 Ancestral state reconstruction of diel activity pattern. Bayesian SIMMAP ancestral state reconstruction using the constrained tree for the
history of the ‘Diel Activity Pattern’character. Nocturnality is inferred to be ancestral for snakes. The grey box marks the clade Colubroidea, within
which diurnal habits re-evolved. Note that SIMMAP estimates the most likely states for tip taxa that are coded as missing or polymorphic –as such,
some of the tip states exhibited in this figure are inferred tip states, not coded tip states (e.g., the fossil taxa were coded as missing data; the states they
exhibit here are states inferred by the SIMMAP method). Fossil taxa are marked with a dagger (†).
Hsiang et al. BMC Evolutionary Biology (2015) 15:87 Page 11 of 22

matched with high relative abundance (compared to
other snakes such as booids) until the latter half of the
Miocene, when colubroids became dominant in the
cooler and drier habitats that emerged at higher latitudes
[52,53]. The success of the Colubroidea in these
higher-latitude environments may have been facilitated by
the reemergence of diurnality within that lineage, as
colder nighttime temperatures may have limited nocturnal
activity for ectothermic snakes.
The feeding behavior of the earliest snakes was inferred
to have been similar to that of most extant snakes: they
were likely widely foraging stealth predators, hunting soft-
bodied prey subequal to head size (likely small vertebrates,
either while active, e.g., nocturnal mammals, or asleep,
e.g., diurnal squamates). Constriction is relatively restricted
in its phylogenetic distribution, and likely did not arise
outside of crown Alethinophidia.
The Bayesian and likelihood reconstructions reported
above are all supported by parsimony ASR for all
three topologies of interest, with the exception of
prey preference, where parsimony reconstructs both
soft-bodied prey and termites/ants (including their
larvae and eggs) as being equally parsimonious on the
genetic topology. This is likely due to a combination
ofthelackoffossiltaxainthegenetictopologyand
the position of the termite-/ant-eating scolecophidians as
sister to all other extant snakes. Virtually all reconstruc-
tions are highly supported (i.e., > 0.90 PP and PTL) by
Bayesian and ML methods across the combined tree
topologies, with the exception of the ‘Biome’character for
both topologies (for which the ML ASR fails), the
‘Constriction’character for both topologies (for which the
absence of constriction at the ‘Serpentes’and ‘Total-Group’
nodes still exhibits the highest PP and PTL, but with values
less than 0.90, but greater than 0.80), and the ‘Habitat
Stratum’character for the constrained topology (for which
the surface-dwelling ‘terrestrial’reconstruction exhibits
PP and PTL values less than 0.90, but greater than 0.70).
All successful ASR analyses for the genetic topology
exhibit PP and PTL values greater than 0.80, with the
exception of the ‘Diel’character, for which the PP
value of nocturnal habits, the most highly supported
reconstruction, is 0.6610 (see Additional file 2).
Lagrange [54] biogeographic analysis of the ‘Plate II’
tectonic plate character yielded ambiguous results
(see Additional file 5) for all tree topologies when the
complete dataset (hereafter, the ‘full-genus’distribution –
whereby tip taxa were coded to represent the entire
biogeographic range of the genus to which they belong in
traditional taxonomies –see Methods) was used. When
the taxa in the analysis were instead coded to reflect only
the biogeographic ranges of individual species (‘no-genus’
distribution), Lagrange infers that both the ancestor of
crown snakes and the ancestor of the snake total-group
likely originated on Laurasia for the constrained tree
(74.70% North America, 13.12% Asia, and 12.18% for
North America + South America for the total-group node;
63.65% North America, 18.13% North American + Asia,
10.92% South America + Asia, 9.94% Asia, and 7.37% South
America for the crown-snake node). For the unconstrained
tree, the results are equivocally split between Laurasian and
Gondwanan origins (32.72% North America, 32.65% North
America + South America, 16.98 Asia, 9.92% South
America + Asia, and 7.72% for North America + Asia
for the total-group node; 37.64% South America,
34.16% South America + Asia, 13.83% North America,
9.25% for North America + Asia, and 5.11% for North
America + South America for the crown-snake node).
In contrast, the ancestor of crown snakes is unequivocally
reconstructed as having originated on Laurasia for the
genetic tree using the no-genus distribution (86.45%
North America and 13.55% North America + Asia).
However, the Laurasian reconstruction for the ancestor of
crown snakes using the no-genus distribution is poten-
tially influenced by sampling bias, as our dataset con-
tains mostly representatives of Scolecophidia from
North America and the Caribbean, despite the worldwide
distribution of scolecophidians. This phenomenon,
resulting in more complete genetic data for Nearctic
scolecophidians than for other biogeographic zones, is
likely due to the relative ease of access to these sampling
localities for researchers hailing from the Northern
Hemisphere.
The inability of the Lagrange method to produce an
unambiguous result suggests that such biogeographic
methods, which require introducing sources of uncertainty
(e.g., constructing a relative dispersal probability matrix,
for which there is no clear standard), may not be ideal for
reconstructing dispersal history across long stretches of
geological time. This is likely due in no small part to the
breakdown of the conceptual foundations of these methods
when geographical areas –which must necessarily be
predefined to create dispersal probability matrices –
change significantly through time (e.g., although the
modern-day continent of Africa belonged to the Mesozoic
supercontinent of Gondwana, it is unclear how reliably we
can reconstruct dispersal history to and from ‘Africa’when
its modern-day identity was largely irrelevant during the
Mesozoic –particularly when ambiguity abounds both in
terms of subjective ‘dispersal probabilities’and the
estimated position through time of the landmass we call
‘Africa’due to continental drift). This issue is likely aggra-
vated when the organisms under consideration are highly
dispersive, and thus likely to make biogeographic leaps that
might seem extremely unlikely a priori.
Several lines of evidence suggest that snakes, particularly
relative to other squamate reptiles, are particularly adept
dispersers: 1) snakes have been empirically demonstrated
Hsiang et al. BMC Evolutionary Biology (2015) 15:87 Page 12 of 22

to exhibit larger ranges than non-snake lizards [55,56] –
when only terrestrial species are taken into consideration,
snakes exhibit median range sizes that are ~4.5 times
larger than that of non-snake lizards [57]; 2) hydrophiine
snakes are unique among extant squamates in being
adapted exclusively for marine lifestyles (in contrast
to the iguanian Amblyrhynchus cristatus, which forages in
the ocean while living primarily on land), demonstrating
the remarkable capacity of Serpentes to adapt to and
inhabit environments that traditionally hinder the dispersal
of terrestrial organisms. This idea is corroborated by
snakes having invaded aquatic (e.g., natricines, homo-
lopsines, calamariines, Acrochordus) and marine habitats
(e.g., hydrophiines, simoliophiids, palaeophiids) multiple
times in their evolutionary history, perhaps facilitated by
natural floatation conferred by enlarged right lungs that
extend down the body, as well as a style of terrestrial
locomotion that approximates anguilliform-style swim-
ming; and 3) the biogeographic ranges of certain snake
clades suggest dispersal capabilities across large stretches
of water. For instance, Candoia is broadly distributed
across the Indo-Pacific islands, but is sister to New World
boas [58]; such a biogeographic distribution is difficult to
explain without considering the likelihood of oceanic
dispersal. Another example is the presence of Bolyeria and
Casarea on Round Island, Mauritius, while their sister
Xenophidion is found in Southeast Asia [8]. These
issues in tandem –the breakdown of the conceptual
underpinnings of biogeographic methods and the high
dispersal capabilities of snakes –suggest that the failure of
Lagrange to reconstruct the snake biogeographic history
indicates the fundamental inability of such methods
to effectively broach the deep evolutionary histories of
dispersive organisms.
In contrast to the Lagrange results,‘naïve’ASR methods
(i.e., parsimony, ML, and Bayesian stochastic character
mapping) reconstruct the ‘Serpentes’ancestor as most
likely originating on the Gondwanan Supercontinent
(note, however, that reconstructions using the genetic
topology disagree with those using the combined topologies,
strongly reconstructing the ‘Serpentes’ancestor as having
originated on Laurasia –this is likely due in no small part
to the lack of fossil information in the genetic analyses).
This conclusion agrees with previous work suggesting a
Gondwanan history for crown snakes, and in particular
Scolecophidia [59], which is sister to all other crown snakes.
Reconstructions for the ‘Total-Group’node are more
equivocal: the most parsimonious state for both the con-
strained and unconstrained topologies is a Laurasian origin,
while ML and Bayesian methods reconstruct a Gondwanan
origin as being only slightly more likely. Although the
unambiguously Laurasian geographic distribution of a suc-
cession of anguimorphan outgroups supports a Laurasian
origin for stem snakes [8], the ambiguity surrounding the
‘Total-Group’node is likely also due to the Laurasian
occurrence (specifically, North American) of the prob-
lematic early snake Coniophis precedens,whichhas
been argued to represent the sister group to all other
snakes [7]. Although this topological hypothesis is
corroborated by our phylogenetic analyses, the validity
of this argument hinges largely on whether all of the
disarticulated elements referred to Coniophis are truly
associated with a single species, a claim that requires
further investigation. Future fossil discoveries and
analyses may also potentially change our understanding of
Coniophis and the deepest portions of the snake stem
(e.g., the recent discovery of a jugal-bearing specimen of
Najash rionegrina [6], one of the plesiomorphies pre-
viously thought to indicate the stemward position of
Coniophis precedens [7]).
These results thus support a Gondwanan provenance
for crown snakes, while also suggesting the possibility of
a Laurasian origin for the snake total-group. Acceptance
or rejection of this hypothesis necessarily relies on the
future reevaluation of specimens referred to C. precedens
and the discovery of additional early representatives of
Pan-Serpentes.
Divergence time estimation
Divergence time trees were estimated for the genetic
(see Additional file 6), unconstrained (see Additional file 7),
and constrained trees (Figure 8). The constrained topology
is presented because, unlike the other topologies, it pre-
serves scolecophidian, anilioid, xenopeltid, booid, and
tropidophiid + caenophidian monophyly. The following
discussion, however, applies equally to all of the time-
calibrated trees, with the exception of specific numbers
regarding dates and their 95% highest posterior density
intervals (HPDI), and when otherwise noted.
Pan-Serpentes is inferred to have originated ~128.5 Ma
(mean age; HPDI [142.0, 117.2]), while crown snakes are
inferred to have diverged ~110.3 Ma (HPDI [117.1,
104.0]). Given the error margins in this analysis, these
events appear to have occurred in relatively quick
succession during the late Early Cretaceous (specifically,
during the Albian stage). The successive divergences of
madtsoiids, pan-anilioids, simoliophiids, and pan-
macrostomatans occurred in a remarkably rapid series
of events between 105–95 Ma, with basal splits in
crown macrostomatans following shortly thereafter
(91.4 Ma; HPDI [99.2, 82.3]). The timing of these
rapid basal divergences falls within the range of dates
associated with the Cretaceous Terrestrial Revolution
(125–80 Ma) [60], an interval when many familiar floral
and faunal groups –such as mammals [61,62], birds
[61,63], and angiosperms [64] –appear to have experienced
accelerated and widespread diversification in terres-
trial ecosystems. Our analyses suggest that snakes also
Hsiang et al. BMC Evolutionary Biology (2015) 15:87 Page 13 of 22

Figure 8 (See legend on next page.)
Hsiang et al. BMC Evolutionary Biology (2015) 15:87 Page 14 of 22

experienced a burst of radiation in the mid-Cretaceous,
and may have been participants in this significant
macroevolutionary event.
The initial splits within Macrostomata appear to have
occurred in the early Late Cretaceous, with the crown
divergence between Pan-Booidea and the tropidophiid +
caenophidian total-group following later (mean: 81.6 Ma;
HPDI [89.8, 73.7]). The modern radiation of crown
caenophidian snakes, however, seems to spring forth
later in the Cenozoic, starting around 65–50 Ma,
soon after the K-Pg Mass Extinction. Although it
should be noted that the HPDI of the deepest divergence
in Booidea crosses the K-Pg boundary, the widespread dis-
tribution and astonishing diversification of henophidian
snakes –which was driven primarily by the radiation of
the Colubroidea [65] –clearly occurred after the end-
Cretaceous mass extinction in the combined divergence
time trees. This result is in contrast to previous studies
(e.g., Burbrink and Pyron [66]), which inferred a Paleogene
origin for Colubroidea, but with confidence intervals
crossing the K-Pg boundary. However, it should be noted
that the clade definitions of Burbink and Pyron [66] differ
slightly from ours; their crown ‘Colubroidea’is equivalent
to our crown ‘Caenophidia’. The age of our crown
‘Colubroidea’(that is, Pareas , viperids, colubrids, lam-
prophiids, and elapids) appears approximately as old
as the corresponding clade in Burbrink and Pyron
[66]. Our genetic divergence time tree infers a similar
result to previous studies using only genomic data,
with a post K-Pg origination date for Colubroidea,
but with error margins crossing the boundary (mean:
64.1 Ma; HDPI [70.4, 57.8]). The inclusion of fossils as tip
taxa thus clearly affects inferred divergence dates, and
suggests that the early divergence dates for the most
species-rich modern clade of snakes are younger than
previously assumed. This radiation was likely driven
by the sudden availability of niches left vacant by the
catastrophic K-Pg extinction, mirroring the astounding
radiation of placental mammals [67], crown birds [68],
and several other surviving groups of squamates [69] in
the early Cenozoic.
Conclusions
Based on our analyses, the ancestors of crown and total-
group snakes were nocturnal stealth hunters that foraged
widely for soft-bodied prey in warm, mild, well-watered,
and well-vegetated ecosystems (Figure 9). Prey size was
relatively small compared to prey regularly consumed by
snakes exhibiting the macrostomatan condition, but
large relative to the size of prey targeted ancestrally by
non-snake lizards. It was unlikely that they employed
constriction to subdue prey. The earliest snakes were
likely active primarily on the ground surface (even if
beneath cover), although they may have also exhibited
semi-fossorial habits. Ancestral snakes are unequivocally
inferred to have originated on land, rather than in
aquatic settings. The biogeographic origin of snakes is
less clear than their early ecology and behavior; however,
our results suggest that the ancestor of crown snakes
most likely originated on the Mesozoic supercontinent
of Gondwana, and indicate the possibility that the ancestor
of total-group snakes arose instead on Laurasia. A conclu-
sive resolution of the biogeographic origin of total-group
snakes will require both reevaluation of the controversial
fossil snake Coniophis precedens, and the discovery of new
fossils of stem-group snakes.
The snake total-group, or at least the Coniophis-node,
is inferred to have arisen in the middle Early Cretaceous,
with the crown originating about 20 million years later,
during the Albian stage. A series of rapid divergences in
their early evolutionary history suggests that snakes
may have been participants in the hypothesized Early
Cretaceous Terrestrial Revolution. Our results further
suggest that henophidian diversity, which includes the
bulk of extant snake species, radiated entirely after the
K-Pg mass extinction.
These results paint the clearest picture yet of the early
evolution of snakes, shedding light on their ecological,
behavioral, biogeographic, and macroevolutionary origins.
Both the ancestors of total-group and crown-group snakes
were apparently similar in ecology and behavior to many
basal macrostomatans surviving today. This conclusion,
dependent on the inclusion of fossil stem snakes in our
analysis, would be unexpected if only extant snakes were
considered, given the sister-position of highly derived
scolecophidians to all other extant crown snakes. Thus,
the importance of fossil intermediates for illuminating
macroevolutionary processes cannot be understated.
Furthermore, our results demonstrate that the inclusion
of phenotypic and fossil data can affect the inference of
phylogenetic topologies, even when such data are vastly
outnumbered by genetic sequence data. Fossils afford
unprecedented glimpses into the grand tapestry of
evolutionary history, and can inform inferences well
(See figure on previous page.)
Figure 8 Divergence time tree inferred using the constrained topology. Divergence times inferred using the constrained tree in BEAST. Major
crown clades are named, along with two extinct clades (Simoliophiidae and Madtsoiidae). The red line separating the Mesozoic and Cenozoic
eras marks the Cretaceous-Paleogene (K-Pg) boundary at 66 Ma. Timescale is in millions of years. Circled numbers and green stars correspond to
calibration dates outlined in Additional file 12. Colored boxes indicate major clades. Fossil taxa are marked with a dagger (†). Grayed taxa names
indicate extant species that are included on the basis of phenotypic data only.
Hsiang et al. BMC Evolutionary Biology (2015) 15:87 Page 15 of 22

beyond those that can be drawn from the fortuitous
survivors comprising Earth’s modern biota. Transitional
fossils are therefore invaluable for both phylogenetic
analyses and for the accurate reconstruction of ances-
tral states.
Methods
Materials and data
Ancestral state reconstruction characters
Eleven novel characters describing ecology and habitat,
feeding behavior, diel activity pattern, and tectonic plate
occupation (see Additional file 1) were coded for 73
species –of which 15 are extinct –spanning the
snake and other anguimorphan (outgroup) tree topology.
Although our sample represents only a small percentage
of the total extant diversity of snakes, the need to include
fossils and phenotypic data precluded the inclusion of
thousands of snake species in this study from a practical
perspective. Future analyses would, of course, ideally
sample a greater proportion of living snakes; however,
even if we had examined every species of living snake,
that sample might represent no more than a small
fraction of the total diversity of a clade of such
antiquity. Nevertheless, our dataset represents the most
comprehensive sample combining genetic and phenotypic
data to date.
Character codings were based on literature searches
(see Additional file 8 for sources). All character codings
are available in Nexus format on the Dryad Digital
Depository. Although including both the ‘Tectonic Plate
I’and ‘Tectonic Plate II’characters may be interpreted
as pseudoreplication, the inclusion of both characters
is intended to facilitate testing of the potential effects
of using a simple binary character (‘Tectonic Plate I’)vs.a
highly atomized, multi-state character (‘Tectonic Plate II’)
during ancestral state reconstruction. The ‘Foraging
Mode’character refers to hunting strategy –that is,
whether the species in question actively travels and for-
ages for prey, largely remains sedentary and waits to am-
bush prey, or exhibits some combination of the two
strategies. The ‘Prey Pursuit Method’character then cap-
tures whether, upon detection of a prey item, the species
in question employs an overt, charging attack, or a covert,
stealthy approach and rapid strike (analogous to the con-
trast between the mode of hunting employed by cheetahs
vs. leopards). The ‘Prey Preference’character, in addition
to being based on published natural history observations,
is tied to tooth form; that is, teeth that are suited for
crushing/piercing are assumed to belong to taxa that feed
on prey items with relatively hard exoskeletons/exteriors,
such as beetles, whereas teeth that are suited to prehen-
sion were assumed to belong to taxa that feed on relatively
soft-bodied prey items, such as rodents and birds. This
Figure 9 Reconstruction of the ancestral crown-group snake, based on this study. Artwork by Julius Csotonyi.
Hsiang et al. BMC Evolutionary Biology (2015) 15:87 Page 16 of 22

approach allowed us to code this character for fossil taxa
in which tooth morphology, but not direct dietary infor-
mation, is preserved. The ‘Prey Size’character serves as a
proxy for understanding the evolution of the unique
macrostomatan condition –that is, a kinetic system enab-
ling them to ingest intact prey items that are much larger
than the head –within snakes (a capacity that evolved
twice if tropidophiids are basal alethinophidians as gen-
omic data suggest). As such, this character refers strictly
to whether the species in question possesses the ability to
swallow whole prey items that are larger than its head,
and not to whether it also happens to consume prey that
are smaller or subequal to head width (e.g., although Boa
constrictor has been observed to opportunistically con-
sume small prey such as mice, it would be scored as
being able to swallow prey larger than its head). The
remaining characters –‘Diel Activity Pattern,’‘Biome’,
‘Prey Subdued by Constriction’,‘Habitat Stratum’,and
‘Aquatic Habits’–are self-explanatory. ‘Biome’can admit-
tedly be ambiguous, however, as it combines biotic (often
botanical) associations with parameters of the physical
environment, such as rainfall and temperature patterns.
Reconstructions of ancestral ecologies would likely be
more accurately served by scoring organisms for ‘Cli-
mate Zones’rather than ‘Biomes’,soastoavoidcon-
fusing the former with the kinds of plants that
currently happen to inhabit them [70] (e.g., while
there were almost certainly semiarid climates in the
Early Cretaceous, it is doubtful that they supported
grasslands as they do today). As such, we would urge
biologists who wish to consider these issues in the future
to avoid this potential pitfall by considering past cli-
mate zones in lieu contemporary biome descriptions,
especially for deep time reconstructions of ecological
ancestral states.
Behavioral characters can be highly variable, and as
such we applied a modal, and we believe repeatable,
character-coding criterion. For example, diel activity
patterns are widely understood to vary seasonally in
snakes dwelling at higher latitudes; many normally
nocturnal snakes in the arid American Southwest can be
active during daylight hours, as weather permits, when
emerging from hibernation in order to bask, mate, and
feed. Nevertheless, those taxa are still regarded here as
being ‘nocturnal’so long as they exhibit that preference
during most of their active seasons. The same subjective
rationale was applied for modal state assignments to
other behaviors, such as foraging and prey pursuit, and
prey constriction. The identity of Lichanura trivirgata
as a constrictor, for example, is undisputed by herpetolo-
gists despite considerable behavioral plasticity (e.g.,
individuals of the species have been observed to consume
already dead mice without first constricting them), and is
coded in our matrix as such. Commitment to aquatic
habits and a particular stratum are arguably even more
problematic due to their continuous variation, sometimes
changing during the course of a snake’s lifetime. For
instance, although individuals of Lampropeltis getula
can occasionally be found climbing in low bushes, the
species is generally described in the herpetological
literature as “terrestrial.”In cases where our selected
taxa were regularly described in the literature as exhibiting
multimodal habits, they were accordingly scored as
polymorphic. For instance, with regard to ‘Diel Activity
Pattern,’the viper Causus rhombeatus can apparently be
found active at any time of day, and was accordingly
scored as diurnal, crepuscular, and nocturnal to reduce
potential bias in our ancestral state reconstructions.
Additionally, due to sampling limitations, certain
clades in our dataset are represented by species that do
not necessarily reflect the full diversity and disparity
of their respective clades. The most notable example
of this is our sampling of Scolecophidia: although
scolecophidian snakes are found all over the world
[71], our dataset includes only species found in North
AmericaandtheWestIndies,asaconsiderable
amount of data has been gathered from these species
due to their relative ease of access to researchers in
the United States. This sampling bias may have an effect
on the biogeographic reconstructions at our nodes of
interest. Accordingly, all taxa were scored to represent the
entire range of the genera to which they have been
assigned in traditional taxonomies. For example, Rena
(formerly Leptoyphlops)dulcis is found primarily in
the southwestern United States and northern Mexico,
but because Leptotyphlops as a clade can also be
found throughout Central and South America, R.
dulcis is coded in our matrix as both 0 and 1 (Laurasia
and Gondwana).
Phenotypic and genetic data
The complete phylogenetic dataset included 766 phenotypic
characters from the latest revision of the squamate dataset
from the Assembling the Tree of Life (AToL) project [7,8]
and 18,320 bp from 21 nuclear loci and one mitochondrial
locus downloaded from the NBCI GenBank database
(see Additional file 9). Nexus files for all datasets
(phenotypic + ancestral state characters; genetic; combined)
and a complete list of characters and character states
are available on the Dryad Digital Repository.
Total genetic data coverage was 81.3% (excluding fossil
taxa). In cases where genetic data were not available for
the species sampled in the phenotypic dataset, genetic
data were substituted from another species attributed to
the same genus in traditional taxonomies (i.e., Naja naja
and Naja kaouthia;Rena dulcis and Rena humilis;Causus
rhombeatus and Causus defilippi). Genetic sequence data
for our set of genes were unavailable for the two
Hsiang et al. BMC Evolutionary Biology (2015) 15:87 Page 17 of 22

extant species Anomochilus leonardi and Xenophidion
acanthognathus. Genetic data were aligned in Clustal
Omega (v.1.1.0) [72] using default settings, and then
inspected by eye in BioEdit (v.7.1.3.0) [73]. Model
testing for each locus was conducted in PAUP*
(v.4.0b10) [74] using the package MrModelTest (v.2.3) [75].
Under the Akaike Information Criterion, the best substitu-
tion model was determined to be GTR + I + G for all loci
except ZEB2, for which the best model was HKY + I + G.
Phylogenetic analyses
Phylogenetic trees were inferred using the following
datasets: 1) the phenotypic data alone; 2) the genetic
data alone; 3) the combined phenotypic and genetic data,
unconstrained; and 4) the combined phenotypic and gen-
etic data, constrained such that the interrelationships of
certain major clades corresponded to those exhibited in
the phenotypic-data-only tree topology (for a discussion
and list of constraints implemented, see Additional file 10).
The phenotype-only dataset was analyzed using both
maximum parsimony and Bayesian methods, while
the other three analyses were conducted using only
Bayesian methods. In all cases, Xenosauridae (= Shinisaurus
crocodilurus,Xenosaurus grandis,andXenosaurus platyceps)
was set as the monophyletic outgroup [8].
The dataset containing only phenotypic data was analyzed
in PAUP* (v.4.0b10) [74] using a heuristic search algorithm
with starting trees built using random stepwise addition
with tree bisection and reconnection (TBR) branch
swapping and twenty random addition sequence replicates.
A strict consensus tree of the six most parsimonious trees
(2,170 steps) was built (see Additional file 11). A nonpara-
metric bootstrap search was conducted under the same
heuristic search parameters for 1000 replicates, summa-
rized as a 50% majority rule consensus tree (Figure 5). The
same run parameters were used to build a tree using parsi-
mony for the combined dataset: the most parsimonious
tree consisted of 31,405 steps (see Additional file 12), and a
50% majority rule consensus tree was built from 1000
bootstrap replicates (Figure 6).
Bayesian phylogenetic analyses were run using
MrBayes (v.3.2.2) [76] on the CIPRES Science Gateway
[77]. The Mkv model [78] was used for the phenotypic
data with gamma-distributed rate variation and variable
coding. Sequence data were partitioned by gene, whereas
phenotypic data were partitioned by number of character
states (i.e., binary characters formed a partition, characters
with three states formed a partition, etc.) to reflect implicit
differences among rates of evolution for characters with
more states vs. those with fewer. All analyses were run
with a sampling frequency of 1000, two concurrent
runs, and four Metropolis-coupled chains (T=0.1).
The phenotypic-data-only analysis was run for 20 million
generations; all other datasets were run for 50 million
generations. Model parameters (character state frequencies,
substitution rates, gamma shape parameter, and proportion
of invariable sites) were unlinked across all partitions, and
rates were allowed to vary independently for all partitions.
All analyses were checked for convergence using standard
MrBayes diagnostics (e.g., PRSF < 0.01, mixing between
chains > 20%) and Tracer (v.1.5) [79] (e.g., ESS > 200). A
25% relative burn-in was implemented for all summary
statistics.
Divergence time estimation
Divergence time trees were inferred using the genetic
tree, the unconstrained tree, and the constrained tree. A
maximum of seven nodal calibration points were used
(six for the genetic tree; see Additional file 13 for list of
calibration points and age-indicative fossils), along with
tip calibration dates (see Additional file 14) for the
unconstrained and constrained analyses. All calibrations
follow the best practices protocols outlined by Parham
et al. [80]. Beginning and ending dates for each geological
period are defined by the standards of the International
Commission on Stratigraphy (ICS). The three trees were
first scaled such that the calibrated nodes matched their
respective hard minimum ages using the BLADJ module
in the Phylocom software package (v.4.2) [81]. The root
age, which is required for BLADJ,wassetat150Ma;
this is the age of the earliest known crown squamates,
including Paramacellodus, a stem-member of the scinco-
morph sister clade to all anguimorphs (including snakes)
considered in this analysis [8].
The time-calibrated analyses were run in BEAST (v.1.8.0)
[82] for 100 million generations on CIPRES. Calibration
priors for both the nodal and tip calibration dates were set
such that the youngest age of each geological period was
set as the hard minimum age constraint offset for ex-
ponential distribution age priors; the scale parameter was
then chosen such that 95% of the distribution volume was
contained within the oldest age of the geological period.
Tree operators (subtreeSlide, narrowExchange, wideEx-
change, and wilsonBalding) were switched off so that the
analyses would optimize only node ages and not tree top-
ology. For the genetic tree, the data were partitioned
according to the 22 genes with unlinked substitution
models, a single linked molecular clock model, and a
linked tree model. For the unconstrained and constrained
trees, the combined phenotypic and genetic data were
divided into 27 partitions (22 gene partitions+ 5
phenotypic partitions) with unlinked substitution models,
a single molecular clock model, a single phenotypic clock
model, and a linked tree model. The substitution models
were set for the gene loci as specified in the original
phylogenetic analyses, and the Lewis Mk model was
used for the morphological partitions. Uncorrelated
lognormal relaxed clock models were used with
Hsiang et al. BMC Evolutionary Biology (2015) 15:87 Page 18 of 22

estimated rates. The birth-death serially sampled [83] spe-
ciation tree prior was used in all cases. Clock mean priors
were set as diffuse gamma distributions (shape = 0.001,
scale = 1000). All other priors were left with their default
settings. Time-calibrated trees were summarized using
TreeAnnotator (v.1.8.0), included with the BEAST soft-
ware package, with a 25% burn-in.
Ancestral state reconstruction
Ancestral states were inferred in all cases for the most
recent common ancestor (MRCA) approximating the
snake total-group (‘Total-Group’node) and for the
MRCA of crown snakes (‘Serpentes’node). A nodal
approximation for the snake total-group –which is
certainly older than the divergence of Coniophis precedens
from other pan-snakes –is necessary, as nodes and stem
branches are not equivalent [84], but ancestral states
can only be reconstructed at nodes. Ancestral state
reconstruction (ASR) analyses were conducted under
parsimony, maximum likelihood (ML), and Bayesian
frameworks. Mesquite (v.2.75) [85] was used for parsimony
ASR. The R(v. 2.15.1) [86] package phytools (v.0.3-93) [87],
specifically the function rerootingMethod,wasusedforML
ASR. This function implements the Yang et al. [35] re-
rooting method to estimate marginal ancestral states under
a likelihood framework. For Bayesian stochastic character
mapping [36,37], the phytools function make.simmap was
used. These methods were chosen for their ability to
incorporate uncertainty (i.e., missing data) and to take
polymorphic states, which are extensive in our dataset,
into account. It should be noted that these methods
take missing data and polymorphic states into account by
imposing a prior on the distribution of states for a given tip
taxon. As a result, these states are not immutable during
ancestral state estimation (as monomorphic states are)
and may be overwritten –e.g., if taxon A is polymorphic
for states 0 and 1, but happens to be nested with a clade
in which all other clade members are monomorphic for
state 0, the ASR process may reconstruct taxon A as
exhibiting only state 0. Although this is obviously not ideal
behavior, we believe the ability to include polymorphic
data is preferable to excising such data from the analysis,
as would be required in ‘traditional’ASR methods such as
ace [88]. Similarly, if a taxon in the analysis is coded as
missing data (the ‘?’state), the SIMMAP method will
infer the most likely tip state for that taxon based on the
available data (e.g., although all taxa exhibit a concrete tip
state in Figure 6, some of those tip states –including all
fossil taxa –are inferred states, not coded states).
All ancestral state reconstructions were performed on
the time-calibrated genetic, unconstrained, and constrained
topologies. For Bayesian stochastic character mapping,
characters with missing data were initialized with a flat
prior (all character states equally likely), whereas
polymorphic characters were defined to have each poly-
morphic state be equally probable, with all other states
exhibiting zero probability (e.g., a taxon coded 0&1 for a
three-state character would have its prior set as [0.5, 0.5,
0]). The chi-squared log likelihood ratio test, using a sig-
nificance level of 0.05, was used to determine which of the
three available hierarchical models (ER, SYM, and ARD)
was most appropriate for each character for each topology.
For the genetic tree, the ER model was chosen for every
character except ‘Foraging Mode’,‘Diel Activity Pattern’,
‘Prey Preference’,‘Habitat Stratum’,and‘Aquatic Habits’,for
which SYM was chosen for ‘Foraging Mode’and ARD was
chosen for all other characters. For the unconstrained tree,
the ER model was chosen for every character. Finally, for
the constrained tree, the ER model was chosen for every
character except ‘Diel Activity Pattern’and ‘Tectonic Plate
I’, for which the SYM model was chosen. Bayesian sto-
chastic mapping analyses were run for 5000 simula-
tion replicates, with all other options set as default.
Biogeographic reconstruction
In addition to using the naïve ancestral state reconstruction
methods described in the previous section, the biogeo-
graphic method Lagrange [89] was used to reconstruct the
history of the ‘Plate II’tectonic plate character. The pro-
gram RASP (v.3.0) [90] was used to implement Lagrange
under the Dispersal-Extinction-Cladogenesis (DEC)
model. The genetic, unconstrained, and constrained trees
were each used as starting trees. All possible combina-
tions of geographic ranges were allowed, and possible
ranges were added automatically. Dispersal constraint
matrices were built for six time intervals, based on tec-
tonic plate movement: 0–3MYA,3–14 MYA, 14–50
MYA, 50–66 MYA, 66–94 MYA, and 94–133.27 (root age)
MYA. Relative dispersal probabilities were based on tec-
tonic plate reconstructions from the PALEOMAP project
[91] using the following rules: 1) Connected landmasses
are assigned a dispersal probability of 0.9; 2) Landmasses
separated by an ocean of comparable size to the Atlantic/
Indian/Tethys oceans are assigned a dispersal probability
of 0.1; 3) Landmasses separated by an ocean of compar-
able size to the Pacific Ocean are assigned a dispersal
probability of 0.01; and 4) Landmasses and close
islands (e.g., the Caribbean islands and North Amer-
ica) are assigned a dispersal probability of 0.5. In
cases where multiple rules are applicable, dispersal
probabilities are multiplied; for instance, dispersal
from North America to Australia in the Quaternary
requires transversal across the Atlantic Ocean to the
Eurasian landmass (0.1), then a jump from the Eurasian
landmass to the Indo-Pacific islands (0.5), then a jump
from the Indo-Pacific oceans to Australia (0.5), resulting
in a relative dispersal probability of 0.025. Although
dispersal between North America and Australia could also
Hsiang et al. BMC Evolutionary Biology (2015) 15:87 Page 19 of 22

theoretically proceed across the Pacific Ocean, according
to the aforementioned rules this would have a relative
probability of 0.01 –in all such cases, the higher relative
dispersal probability was used.
Availability of supporting data
The data sets supporting the results of this article are
available in the Dryad repository: https://datadryad.org/
resource/doi:10.5061/dryad.7ct1n [92].
Additional files
Additional file 1: List of characters and state descriptions for
ancestral state reconstruction.
Additional file 2: Genetic tree ASR results (MPS = Most
Parsimonious State(s); ML = Maximum Likelihood).
Additional file 3: Unconstrained tree ASR results (MPS = Most
Parsimonious State(s); ML = Maximum Likelihood).
Additional file 4: Constrained tree ASR results (MPS = Most
Parsimonious State(s); ML = Maximum Likelihood).
Additional file 5: Lagrange results for genetic, unconstrained, and
constrained topologies.
Additional file 6: Fossil-calibrated divergence time tree generated
from the genetic dataset using the genetic tree. The K-Pg boundary
(66 MYA) is marked with a red line. Blue node bars denote 95% highest
posterior density (HPD) intervals. Colored boxes indicate major clades.
Colored lines indicate major clades from traditional taxonomies that do
not resolve as monophyletic groups in this topology.
Additional file 7: Fossil-calibrated divergence time generated from the
combined phenotypic and genetic datasets using the unconstrained
tree. The K-Pg boundary (66 MYA) is marked with a red line. Blue node bars
denote 95% highest posterior density (HPD) intervals. Colored boxes indicate
major clades. Colored lines indicate major clades from traditional taxonomies
that do not resolve as monophyletic groups in this topology.
Additional file 8: List of natural history references used for coding
ancestral state reconstruction characters.
Additional file 9: GenBank accession numbers for genetic sequences
used in this study.
Additional file 10: Topology Constraints for Constrained Tree.
Additional file 11: Strict consensus cladogram of the six most
parsimonious trees from a heuristic search under a parsimony
framework using the complete phenotypic dataset. Colored boxes
indicate major clades. Colored lines indicate major clades from traditional
taxonomies that do not resolve as monophyletic groups in this topology.
Additional file 12: The most parsimonious tree inferred from a
heuristic search under a parsimony framework using the combined
phenotypic + genetic dataset. Colored boxes indicate major clades.
Colored lines indicate major clades from traditional taxonomies that do
not resolve as monophyletic groups in this topology.
Additional file 13: Nodal calibration dates for divergence time
analyses in BEAST.Node marked with a * was not used for the genetic
topology.
Additional file 14: Fossil tip calibration dates for divergence time
dating in BEAST.
Competing interests
The authors declare that they have no competing interests.
Authors’contributions
AYH participated in designing the project, conducted the phylogenetic,
time-calibration, ancestral state reconstruction, and biogeographic analyses,
and drafted the manuscript. DJF contributed to the project design/conception
and to manuscript drafting. THW participated in the project design and
provided support on the biogeographic analyses. ADBB, MBD, and RAR
participated in design of the study and conducted data matrix processing.
JAG conceived the project, participated in the study design, compiled the
fossil calibration data, and contributed to manuscript drafting. All authors
contributed to ancestral state character data collection and have read and
approved the final manuscript.
Acknowledgments
We thank G. Watkins-Colwell, D. Rosauer, J. Belmaker, D. Balaji, A. Dornburg,
V. J. Lynch, and N. R. Longrich for assistance in data collection and
discussions.
Author details
1
Department of Geology and Geophysics, Yale University, New Haven,
Connecticut 06520, USA.
2
Department of Vertebrate Zoology, National
Museum of Natural History, Smithsonian Institution, Washington, DC 20560,
USA.
3
Department of Anthropology, Yale University, New Haven, Connecticut
06520, USA.
4
Yale Peabody Museum of Natural History, Yale University, New
Haven, Connecticut 06520, USA.
Received: 23 January 2015 Accepted: 22 April 2015
References
1. Scanlon JD, Lee MSY. The major clades of living snakes. In: Aldridge RB,
Sever DM, editors. Reproductive Biology and Phylogeny of Snakes, vol. 9.
Enfield, New Hampshire: Science Publishers, Inc.; 2011. p. 55–95.
2. Webb JK, Shine R, Branch WR, Harlow PS. Life-history strategy in basal
snakes: reproduction and dietary habits of the African thread snake
Leptotyphlops scutifrons (Serpentes: Leptotyphlopidae). J Zool Lond.
2000;250:321–7.
3. Rieppel O, Kley NJ, Maisano JA. Morphology of the skull of the white-nosed
blindsnake, Liotyphlops albirostris (Scolecophidia: Anomalepidae). J Morphol.
2009;270:536–57.
4. Zaher H, Scanferla CA. The skull of the Upper Cretaceous snake Dinilysia
patagonica Smith-Woodward, 1901, and its phylogenetic position revisited.
Zool J Linn Soc. 2012;164:194–238.
5. Zaher H, Apesteguía S, Scanferla CA. The anatomy of the upper cretaceous
snake Najash rionegrina Apesteguía & Zaher, 2006, and the evolution of
limblessness in snakes. Zool J Linn Soc. 2009;156:801–26.
6. Apesteguía S, Garberoglio F. The return of Najash: new, better preserved
specimens change the face of the basalmost snake. J Vert Paleontol,
Programs and Abstracts. 2013;79.
7. Longrich NR, Bhullar B-AS, Gauthier JA. A transitional snake from the late
Cretaceous period of North America. Nature. 2012;488:205–8.
8. Gauthier JA, Kearney M, Maisano JA, Rieppel O, Behlke ADB. Assembling the
squamate tree of life: perspectives from the phenotype and the fossil
record. Bull Peabody Mus Nat Hist. 2012;53:3–308.
9. Tschernov E, Rieppel O, Zaher H, Polcyn MJ, Jacobs LL. A fossil snake with
limbs. Science. 2000;287:2010–2.
10. Rage J-C, Escuillié F. Eupodophis, new name for the genus Podophis Rage
and Escuillié, 2000, an extinct bipedal snake, preoccupied by Podophis
Wiegmann, 1834 (Lacertilia, Scincidae). Amphibia-Reptilia. 2001;23:232–3.
11. Caldwell MW, Lee MSY. A snake with legs from the marine Cretaceous of
the Middle East. Nature. 1997;386:705–9.
12. Wilson JA, Mohabey DM, Peters SE, Head JJ. Predation upon hatchling
dinosaurs by a new snake from the Late Cretaceous of India. PLoS Biol.
2010;8:e1000322. doi:10.1371/journal.pbio.1000322.
13. Scanferla A, Zaher H, Novas FE, de Muizon C, Céspedes R. A new snake skull
from the Paleocene of Bolivia sheds light on the evolution of macrostomatans.
PLoS One. 2013;8:e57583. doi:10.1371/journal.pone.0057583.
14. Finarelli JA, Flynn JJ. Ancestral state reconstruction of body size in the
Carnivora (Carnivora, Mammalia): the effects of incorporating data from the
fossil record. Syst Biol. 2006;55:301–13.
15. Pyron RA. Divergence time estimation using fossils as terminal taxa and the
origins of Lissamphibia. Syst Biol. 2011;60:466–81.
16. Ronquist F, Klopfstein S, Vilhelmsen L, Schulmeister S, Murray DL, Rasnitsyn AP.
A Total-Evidence Approach to Dating with Fossils, Applied to the Early
Radiation of the Hymenoptera. Syst Biol. 2012;61(6):973–99.
Hsiang et al. BMC Evolutionary Biology (2015) 15:87 Page 20 of 22

17. Wiens JJ, Kuczynski CA, Townsend T, Reeder TW, Mulcahy DG, Sites JW.
Combining phylogenomics and fossils in higher-level squamate reptile phylogeny:
molecular data change the placement of fossil taxa. Syst Biol. 2010;59:674–88.
18. Wiens JJ, Hutter CR, Mulcahy DG, Noonan BP, Townsend TM, Sites JW, et al.
Resolving the phylogeny of lizards and snakes (Squamata) with extensive
sampling of genes and species. Biol Lett. 2012;8:1043–6.
19. Pyron RA, Burbink FT, Wiens JJ. A phylogeny and revised classification of
Squamata, including 4161 species of lizards and snakes. BMC Evol Biol.
2013;13:93–146.
20. VidalN,DelmasA-S,HedgesSB.Thehigher-level relationships of alethinophidian
snakes inferred from seven nuclear and mitochondrial genes. In: Henderson RW,
Powell R, editors. Biology of the Boas and Pythons. Eagle Mountain, UT:
Eagle Mountain Publishing; 2007. p. 27–33.
21. Szyndlar Z, Böhme W. Redescription of Tropidonotus atavus von Meyer, 1855
from the Upper Oligocene of Rott (Germany) and its allocation to Rottophis
gen. nov. (Serpentes, Boidae). Palaeontographic Abteliung A. 1996;240:145–61.
22. Rage J-C, Augé M. Squamate reptiles from the middle Eocene of Lissieu
(France). A landmark in the middle Eocene of Europe. Geobios.
2010;43(2):253–68.
23. McCartney JA, Simons E. A new fossil snake assemblage from the Late
Eocene of the Fayum Depression, Egypt. J Vert Paleontol. 2010;30:132A.
24. McCartney JA, Stevens NJ, O’Connor PM. The earliest colubroid-dominated
snake fauna from the late Oligocene Nsungwe Formation of Southwestern
Tanzania. PLOS One. 2014;9(3), e90415.
25. McCartney JA, Seiffert ER. A late Eocene snake from the Fayum Depression,
Egypt. J Vert Paleontol. In press.
26. Wiens JJ, Kuczynski CA, Smith SA, Mulcahy D, Sites Jr JW, Townsend TM, et al.
Branch length, support, and congruence: testing the phylogenomic approach
with 20 nuclear loci in snakes. Syst Biol. 2008;57:420–31.
27. Vidal N, Rage J-C, Couloux A, Hedges SB. Snakes(Serpentes). In: Hedges SB,
Kumar S, editors. The Timetree of Life. New York: Oxford University Press;
2009. p. 390–7.
28. Siegel DS, Miralles A, Aldridge RD. Controversial snake relationships
supported by reproductive anatomy. J Anat. 2011;218(3):342–8.
29. Rieppel O. “Regressed”macrostoman snakes. Fieldiana Life Earth Sci.
2012;5:99–103.
30. Apesteguía S, Zaher H. Cretaceous terrestrial snake with robust hindlimbs
and a sacrum. Nature. 2006;440:1037–40.
31. Palci A, Caldwell MW, Scanlon JD. First report of a pelvic girdle in the fossil
snake Wonambi naracoortensis Smith, 1976, and a revised diagnosis for the
genus. J Vert Paleo. 2014;34(4):965–9.
32. Brinkmann JO, Delsuc F, Philippe H. Phylogenomics: the beginning of
incongruence? Trends Genet. 2006;22:225–31.
33. Salichos L, Rokas A. Inferring ancient divergences requires genes with
strong phylogenetic signals. Nature. 2013;497:327–31.
34. Nydam R, Caldwell M, Palci A. Reassessment of cranial elements assigned to
the fossil snake Coniophis precedens, Late Cretaceous, North America. J Vert
Paleont, Programs and Abstracts. 2014;196.
35. Yang Z, Kumar S, Nei M. A new method of inference of ancestral nucleotide
and amino acid sequences. Genetics. 1995;141:1641–50.
36. Huelsenbeck JP, Nielsen R, Bollback JP. Stochastic mapping of
morphological characters. Syst Biol. 2003;52(2):131–58. doi:10.1080/
10635150390192780.
37. Bollback JP. SIMMAP: Stochastic character mapping of discrete traits on
phylogenies. BMC Bioinformatics. 2006;7:88. doi:10.1186/1471-2105-7-88.
38. Garland T, Diaz-Uriarte R. Polytomies and phylogenetically independent
contrasts: examination of the bounded degrees of freedom approach.
Syst Biol. 1999;48:547–58.
39. Polly PD. Paleontology and the comparative method: ancestral node
reconstructions versus observed node values. Am Nat. 2001;157:596–609.
40. Slater GJ, Harmon LJ, Alfaro ME. Integrating fossils with molecular
phylogenies improves inference of trait evolution. Evolution.
2012;66(12):3931–44.
41. Oakley TH, Cunningham CW. Independent contrasts succeed where
ancestor reconstruction fails in a known bacteriophage phylogeny.
Evolution. 2000;54:397–405.
42. Springer MS, Teeling EC, Madsen O, Stanhope MJ, de Jong WW. Integrated
fossil and molecular data reconstruct bat echolocation. Proc Natl Acad Sci
U S A. 2001;98(11):6241–6.
43. Albert JS, Johnson DM, Knouft JH. Fossils provide better estimates of
ancestral body size than do extant taxa in fishes. Acta Zool. 2009;90:357–84.
44. Cuny G, Jaeger J-J, Mahboubi M, Rage J-C. Les plus anciens serpents
(Reptilia, Squamata) connus. Mise au point sur l’âge géologique des serpents
de la partie Moenne du Crétacé. C R Acad Sci II. 1990;311:1267–72.
45. Woodward AS. On some extinct reptiles from Patagonia, of the genera
Miolania, Dinilysia, and Genyodectes. J Zool. 1901;70:169–84.
46. Rage J-C. Fossil history. In: Seigel RA, Collins JT, Novak SS, editors. Snakes:
Ecology and Evolutionary Biology. New York: Macmillan; 1987. p. 51–76.
47. Bellairs A-d’A, Underwood G. The origin of snakes. Biol Rev. 1951;26:193–237.
48. Eskew EA, Wilson JD, Winne CT. Ambush site selection and ontogenetic
shifts in foraging strategy in a semi-aquatic pit viper, the Eastern cottonmouth.
J Zool. 2009;277:179–86.
49. Lee MSY, Caldwell MW. Adriosaurus and the affinities of mosasaurs,
dolichosaurs, and snakes. J Paleontol. 2000;74:915–37.
50. Gau K, Hou L. Systematics and taxonomic diversity of squamates from the
Upper Cretaceous Djadochta Formation, Bayan Mandahu, Gobi Desert,
People’s Republic of China. Can J Earth Sci. 1996;33:578–98.
51. Gauthier JA. The diversification of the amniotes. In: Prothero DR, Schoch RM,
editors. Major Features of Vertebrate Evolution, Short Courses in Paleontology,
vol. 7. Boulder, Colorado: The Paleontological Society; 1994. p. 129–59.
52. Alamillo H. Testing macroevolutionary hypotheses: diversification and
phylogenetic implications (Doctoral dissertation). Washington State
University Research Exchange. 2010. http://hdl.handle.net/2376/2783.
Accessed 27 Feb 2015.
53. Williams M. Fossil snakes and climate change: correlating the Neogene
colubrid snake radiation to global climatic changes (abstract). In: Society of
Vertebrate Paleontology 71
st
Annual Meeting, Programs & Abstracts. 2011.
Abstract 214.
54. Ree RH, Moore BR, Webb CO, Donoghue MJ. A likelihood framework for
inferring the evolution of geographic range on phylogenetic trees.
Evolution. 2005;59(11):2299–311.
55. Anderson S. Aerography of North American fishes, amphibians, and reptiles.
Am Mus Novit. 1984;2802:1–6.
56. Anderson S, Marcus LF. Aerography of Australian tetrapods. Aust J Zool.
1992;40:627–51.
57. Böhm M, Collen B, Baillie JEM, Bowles P, Chanson J, Cox N, et al. The
conservation status of the world’s reptiles. Biol Conserv. 2013;157:272–385.
58. Reynolds RG, Niemiller ML, Revell LJ. Toward a Tree-of-Life for the boas and
pythons: Multilocus species-level phylogeny with unprecedented taxon
sampling. Mol Phy Evol. 2014;71:201–13.
59. Vidal N, Marin J, Morini M, Donnellan S, Branch WR, Thomas R, et al.
Blindsnake evolutionary tree reveals long history on Gondwana. Biol Lett.
2010;6:558–61.
60. Lloyd GT, Davis KE, Pisani D, Tarver JE, Ruta M, Sakamoto M, et al.
Dinosaurs and the Cretaceous terrestrial revolution. Proc R Soc B.
2008;275:2483–90.
61. Hedges SB, Parker PH, Sibley CG, Kumar S. Continental breakup and the
ordinal diversification of birds and mammals. Nature. 1996;38:226–9.
doi:10.1038/381226a0.
62. Bininda-Emonds ORP, Cardillo M, Jones KE, MacPhee RDE, Beck RMD,
Grenyer R, et al. The delayed rise of present-day mammals. Nature.
2007;446:507–12. doi:10.1038/nature05634.
63. Foutaine TMR, Benton MJ, Dyke GJ, Nudds RL. The quality of the fossil
record of Mesozoic birds. Proc R Soc B. 2005;272:289–94. doi:10.1098/
rspb.2004.2923.
64. Dilcher D. Towards a new synthesis: major evolutionary trends in the
angiosperm fossil record. Proc Natl Acad Sci U S A. 2000;97:7030–6.
doi:10.1073/pnas.97.13.7030.
65. Pyron RA, Burbrink FT. Extinction, ecological opportunity, and the origins of
global snake diversity. Evolution. 2012;66:163–78.
66. Burbrink FT, Pyron RA. The taming of the skew: Estimating proper
confidence intervals for divergence dates. Syst Biol. 2008;57:317–28.
67. O’Leary MA, Bloch JI, Flynn JJ, Gaudin TJ, Giallombardo A, Giannini NP, et al.
The placental mammal ancestor and the post-K-Pg radiation of placentals.
Science. 2013;339:662–7.
68. Longrich N, Tokaryk T, Field DJ. Mass extinction of birds at the
Cretaceous-Paleogene (K-Pg) boundary. Proc Natl Acad Sci. 2011;108:15253–7.
69. Longrich NR, Bhullar B-AS, Gauthier JA. Mass extinction of lizards and snakes
at the Cretaceous-Paleogene boundary. Proc Natl Acad Sci U S A.
2012;110:21396–401.
70. Donoghue MJ, Edwards EJ. Biome shifts and niche evolution in plants. Annu
Rev Ecol Evol Syst. 2014;45:547–72.
Hsiang et al. BMC Evolutionary Biology (2015) 15:87 Page 21 of 22

71. McDiarmid RW, Campbell JA, Touré T. Snake Species of the World: A
Taxonomic and Geographic Reference, Lawrence, vol. 1. Kansas:
Herpetologists’League; 1999.
72. Sievers F, Wilm A, Dineen D, Gibson TJ, Karplus K, Li W, et al. Fast, scalable
generation of high-quality protein multiple sequence alignments using
Clustal Omega. Mol Syst Biol. 2011;7:539.
73. Hall TA. BioEdit: a user-friendly biological sequence alignment editor and
analysis program for Windows 95/98/NT. Nucl Acids Symp Ser. 1999;41:95–8.
74. Swofford DL. PAUP*. Phylogenetic Analysis Using Parsimony
(*and Other Methods), vol. Version 4. Sunderland, Massachusetts:
Sinauer Associates; 2003.
75. Nylander JAA. MrModeltest v2. 2004. http://www.abc.se/~nylander/.
Accessed 8 Jan 2015.
76. Ronquist F, Huelsenbeck JP. MRBAYES 3: Bayesian phylogenetic inference
under mixed models. Bioinformatics. 2003;19:1572–4.
77. Miller MA, Pfeiffer W, Schwartz T. Creating the CIPRES Science Gateway for
inference of large phylogenetic trees. In: Proceedings of the Gateway
Computing Environments Workshop. New York: IEEE; 2010. p. 1–8.
78. Lewis PO. A Likelihood Approach to Estimating Phylogeny from Discrete
Morphological Character Data. Syst Biol. 2001;50:913–25.
79. Rambaut A, Drummond AJ. Tracer v1.4. 2007. http://beast.bio.ed.ac.uk/
Tracer. Accessed 8 Jan 2015.
80. Parham JF, Donoghue PCJ, Bell CJ, Calway TD, Head JJ, Holroyd PA, et al.
Best practices for justifying fossil calibrations. Syst Biol. 2012;61(2):346–59.
81. Webb CO, Ackerly DD, Kembel SW. Phylocom: software for the analysis of
phylogenetic community structure and character evolution. Bioinformatics.
2008;24:2098–100.
82. Drummond AJ, Suchard MA, Xie D, Rambaut A. Bayesian phylogenetics with
BEAUti and the BEAST 1.7. Mol Biol Evol. 2012;29:1969–73.
83. Stadler T. Birth-death with serial samples. J Theor Biol. 2010;267:396–404.
84. Gauthier JA, de Queiroz K. Feathered dinosaurs, flying dinosaurs, crown
dinosaurs, and the name ‘Aves’.In:GauthierJ,GallLF,editors.NewPerspectives
on the Origin and Early Evolution of Birds: Procceding of the International
Symposium in Honor of John H. Ostrom. New Haven, Connecticut: Spec. Pub.
PeabodyMus.Nat.Hist;2001.p.7–41.
85. Maddison WP, Maddison DR. Mesquite: a modular system for evolutionary
analysis. Version 2.75. 2011. http://mesquiteproject.org. Accessed 8 Jan 2015.
86. R Core Team. R: a language and environment for statistical computing.
Vienna, Austria: R Foundation for Statistical Computing; 2011.
87. Revell LJ. Phytools: An R package for phylogenetic comparative biology
(and other things). Methods Ecol Evol. 2012;3:217–23.
88. Paradis E, Claude J, Strimmer K. APE: analyses of phylogenetics and
evolution in R language. Bioinformatics. 2004;20:289–90.
89. Ree RH, Smith RA. Maximum likelihood inference of geographic range
evolution by dispersal, local extinction, and cladogenesis. Syst Biol.
2008;57(1):4–14.
90. Yu Y, Harris AJ, He XJ. S-DIVA (statistical dispersal-vicariance analysis): a tool
for inferring biogeographic histories. Mol Phyl Evol. 2010;56(2):848–50.
91. Scotese CR. PALEOMAP. 2002. http://www.scotese.com. Accessed 8 Jan 2015.
92. Hsiang AY, Field DJ, Webster TH, Behlke ADB, Davis MB, Racicot RA,
Gauthier JA. Data from: The origin of snakes: revealing the ecology,
behavior, and evolutionary history of early snakes using genomics,
phenomics, and the fossil record. Dryad Digitial Repository. 2015.
doi:10.5061/dryad.7ct1n
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