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Molecular Phylogenetics and Evolution 50 (2009) 391–396
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Molecular Phylogenetics and Evolution
journal homepage: www.elsevier.com/locate/ympev
Short Communication
Phylogenetic relationships among iguanian lizards using alternative
partitioning methods and TSHZ1: A new phylogenetic marker for reptiles
James A. Schulte II *, Eva M. Cartwright
177 Clarkson Science Center, Department of Biology, MRC 5805, Clarkson University, Potsdam, NY 13699-5805, USA
a r t i c l e
i n f o
Article history:
Received 22 May 2008
Revised 11 October 2008
Accepted 28 October 2008
Available online 5 November 2008
a b s t r a c t
We present phylogenetic hypotheses for the major iguanian lizard lineages and several squamate outgroups using a combined analysis of 4950 aligned base positions representing two intronless nuclear
genes, TSHZ1 and RAG1. Bayesian analyses using reversible jump (RJ) mixture model selection are conducted and compared with a priori partitioned, mixed model maximum likelihood analyses. Bayesian
credibility values and ML bootstraps are comparable with strong support at deep nodes and within acrodonts, but weak support for the twelve iguanid lineages. Accounting for pattern and rate heterogeneity is
becoming commonplace and is essential for accurate phylogeny reconstruction.
Ó 2008 Elsevier Inc. All rights reserved.
1. Introduction
The development and analysis of lepidosaur (lizard, snake, and
Tuatara) genomic data has great potential to enhance our understanding of vertebrate genome evolution (Janes et al, 2008; Townsend et al., 2008). The first draft assembly of the Anolis carolinensis
genome (The Broad Institute) was completed in February 2007, filling a major gap in our knowledge of amniote genomics. These
comparative genomic data for a nonavian reptile are an invaluable
resource to researchers who previously relied on alignment of the
chicken (Gallus gallus) genome with various mammalian sequences
to design suitable phylogenetic markers of nuclear origin. In a recent study, 26 markers were identified with ML-corrected genetic
divergence between Gallus and Anolis at 20–90% (Townsend
et al., 2008). However, the current estimate of shared homologous
genes among amniotes is at least 12,988 genes (NCBI, Homologene
database, 28 July 2008). Thus, there is enormous potential for
developing additional markers that are suitable for phylogenetic
analyses of higher-level vertebrate relationships.
The recent accumulation of whole genome data from a wide array of organisms has resulted in a rapid increase in nuclear markers useful at moderate to deep taxonomic levels. These markers
facilitate resolution of several longstanding phylogenetic issues
across taxa such as land plants (Soltis et al., 2008), fish (Li et al.,
2007), mammals (Wildman et al., 2007), and metazoans (Ruiz-Trillo et al., 2008). Recovering strong support for most higher-level
iguanian-lizard relationships has been a particularly difficult problem among reptiles when using primarily mitochondrial DNA and
* Corresponding author. Fax: +1 315 268 7118.
E-mail address: [email protected] (J.A. Schulte).
1055-7903/$ - see front matter Ó 2008 Elsevier Inc. All rights reserved.
doi:10.1016/j.ympev.2008.10.018
morphological data (Conrad et al., 2007; Frost et al., 2001; Macey
et al., 2000; Schulte et al., 2003; Townsend et al., 2004).
Numerous molecular and morphological characters support
acrodont monophyly. Chamaeleonidae is a well-supported clade
within acrodonts, whereas Agamidae is retained as a metataxon
where monophyly is statistically neither supported nor rejected
(Schulte et al., 1998). Monophyly of the primarily New World clade
Iguanidae is strongly supported, as are its 12 subclades. Relationships among these 12 subclades, however, are poorly supported.
Multiple tests have indicated that Iguanidae may have undergone
a relatively rapid radiation in the Mesozoic (Schulte et al., 2003).
To date, very few studies have used nuclear genomic data to
address the phylogenetic relationships among iguanian lizards.
Harris et al. (2001) analyzed 375 basepairs of c-mos for squamate
reptiles, including 13 iguanian lizards, finding little support for
relationships among major subclades sampled. Recently, Townsend et al. (2004) published a phylogeny of squamates, including
25 iguanian species, based on almost three kilobases of RAG1
(2.8 kb). They recovered support for some relationships within
Agamidae, but no support for relationships among iguanid subclades. Here, we describe an additional large (2.2 kb) nuclear marker, teashirt zinc finger homeobox 1 gene (TSHZ1), in an attempt to
increase statistical support for relationships among agamid and
iguanid subclades.
In this study, 24 species of squamate reptiles and G. gallus are
sampled to examine the relationships among the major clades of
iguanian lizards. Representative species of the 12 iguanid clades,
six agamid clades, and one chameleon are sampled within Iguania.
Five outgroup species are included to represent increasing
divergence among squamate reptiles based on previous studies
(Townsend et al., 2004; Vidal and Hedges, 2005). The protein
product of TSHZ1 interacts with Hox genes and is an important
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J.A. Schulte, E.M. Cartwright / Molecular Phylogenetics and Evolution 50 (2009) 391–396
transcription-regulation element during development of the vertebrate brain, spinal cord, middle ear, and somites (Caubit et al.,
2005; Coré et al., 2007; Wang et al., 2007). These data are combined with RAG1 sequences, representing G. gallus, eight previously
published sequences from the same squamate lineages, and 16
new sequences.
We also examine the ability of new reversible-jump Bayesian
mixture-model methods to account for rate heterogeneity in our
data (Schulte and de Queiroz, 2008; Venditti et al., 2008). Mixture
models account for site heterogeneity across the data by applying
several models to each site, where the likelihood of a given site is
the sum of the likelihoods under the different models, each
weighted by its probability as estimated from the data (Pagel
and Meade, 2004, 2005; Schulte and de Queiroz, 2008). Reversible-jump (RJ) mixture-model methods estimate a posterior distribution of appropriate number of models that best explains the data
without introducing unnecessary parameters (Pagel and Meade,
2004, 2005, 2006; Venditti et al., 2008). The advantages of RJ mixture methods are fourfold (Venditti et al., 2008): (1) These methods
do not require a priori, potentially arbitrary, partitioning of the
data set; (2) pattern heterogeneity will identify sites evolving
within partitions as well as between them; (3) the substitution
model selection process, which includes site variation and model
parameter estimation is incorporated into the analysis; (4) reduction of node-density effects. Results of these analyses are compared to mixed model maximum likelihood analyses, where
partitions are determined a priori.
2. Materials and methods
See Appendix A for museum numbers, localities of voucher
specimens from which DNA was extracted, and GenBank accession
numbers for DNA sequences. Genomic DNA was extracted using
Qiagen QIAamp tissue kits. Amplification of the TSHZ1 gene from
genomic DNA was performed with PhusionTM High Fidelity DNA
Polymerase (Finnzymes Oy.) in a DNA EngineÒ (PTC-200TM) Peltier
Thermal Cycler or MyCycler (MJ Research) using an initial denaturation at 98 °C for 120 s, 35 cycles of denaturation at 98 °C for 10 s,
annealing at 64 °C for 20 s, and extension at 72 °C for 75 s.
Amplification of the RAG1 gene was performed under identical
conditions except that the annealing temperature was between
60–64 °C and the extension time was 120 s. See Appendix B for
amplification and sequencing primers for TSHZ1 and RAG1 genes.
Negative controls were run on all amplifications to check for contamination. Amplified products were visualized on 1.25% agarose
gels using LB buffer (Faster, Better Media, Inc.). Successful PCR
products were sent to Agencourt Bioscience Corporation (Beverly,
MA) for purification and DNA sequencing.
DNA sequences were aligned manually then translated to amino
acids using MacClade 4.08 (Maddison and Maddison, 2003) for
confirmation of alignment and to check for premature stop codons.
Alignment of protein-coding regions was straightforward, except
one glutamine and proline-rich variable region in TSHZ1 that was
excluded from phylogenetic analyses due to ambiguous alignment
of nucleotide positions (see Section 3). Gaps were treated as missing data. Aligned DNA sequences are available in TreeBASE (Study
Accession No. S2182; Matrix Accession No. M4137).
Phylogenetic trees were estimated using probabilistic methods
under both maximum likelihood (ML) and Bayesian criteria. Both
unpartitioned and a priori partitioned mixed model ML trees were
estimated with RAxML (Stamatakis, 2006; Stamatakis et al, 2008)
in the CIPRES web portal with separate and combined analyses of
the two genes. Analyses were performed using a general timereversible model of sequence evolution with rate variation among
sites estimated using a gamma distribution (GTR + C; Tavaré,
1986). This model was chosen based on preliminary analyses using
Modeltest v3.7 (Posada and Crandall, 1998) that chose the
TVM + C + I as the optimal model with the Akaike Information Criterion. However, current implementation of RAxML does not allow
for specification of the TVM substitution model. Proportion of
invariant sites was not estimated so that ML results were comparable to the model assumed in Bayesian analyses. All model parameter values were estimated from the data. For each of the separate
genes, default parameters were used with 25 rate categories and
an initial rearrangement limit of 10. We first conducted unpartitioned data analyses for each gene separately and the combined
data set. Next, we assumed two (codon positions 1 + 2, 3) and three
(codon positions 1, 2, 3) partitions for each gene separately. Partitions in the combined data set were three (codon positions 1, 2,
and 3 for both genes), four (codon positions 1 + 2, 3 for each gene
separately), and six (codon positions 1, 2, 3 for each gene separately). Bootstrap resampling (Felsenstein, 1985) was applied to assess support for individual nodes in each above mentioned analysis
using 250 bootstrap pseudoreplicates in RAxML with the same settings as above. We considered a bootstrap value of P95% as
strongly supported (Felsenstein and Kishino, 1993), <95 to P70%
as moderately supported, and <70% as weakly supported.
Reversible jump mixture model Bayesian analyses were performed using BayesPhylogenies, a version of Pagel and Meade
(2004, 2005; see also Venditti et al., 2008) pattern-heterogeneity
mixture model that employs a reversible-jump algorithm to estimate the number of rate matrices that best explains the data. This
method chooses the appropriate number of independent rate
matrices using Bayes factors during the MCMC procedure. By default, BayesPhylogenies assigns uniform priors on a 0–100 interval
for the gamma and substitution-rate parameters, an exponential
prior for branch lengths with a mean of 10, state frequencies drawn
from the Dirichlet distribution, and all trees are considered equally
likely a priori. These default settings were used in all mixturemodel analyses. Analyses were conducted on the combined data
set and each of the two genes separately. We performed a total
of five independent runs for each data set using the GTR model
and among-site rate variation under a gamma distribution with
four rate categories. A parameter for the proportion of invariant
sites is not implemented in BayesPhylogenies. Each MCMC run
consisted of 25 106 generations and one Markov chain. We
sampled trees at intervals of 10,000 generations. Stationarity was
assessed by plotting the –ln L per generation in Tracer 1.4
(Rambaut and Drummond, 2005) and checking for no average
improvement in the likelihood scores. We discarded the first 500
trees (5 106 generations) as ‘‘burn-in;” thus, estimates of trees
and parameter values are based on 2000 trees sampled from each
run. The resultant 10,000 trees (2000 from each of five runs) were
used to calculate Bayesian credibility values (BC) for each branch in
a 50% majority-rule consensus tree (except the combined data
set – see Section 3). Clades with BC P95% were considered strongly
supported with the caveat that BC may overestimate support for
reasons discussed by Alfaro et al. (2003), Douady et al. (2003),
and Lewis et al. (2005).
3. Results and discussion
Twenty-four new DNA sequences of TSHZ1 range in size from
2161 to 2221 bases and were aligned with publicly available Gallus
sequence resulting in 2227 aligned positions. Seventeen new RAG1
sequences were aligned with eight previously reported sequences
(Townsend et al., 2004; Appendix A) with a range in size from
2753 to 2789 bases resulting in 3038 aligned positions. Mean
nucleotide composition indicated a higher frequency of A
over the other three nucleotides (TSHZ1: A = 32.2%, C = 23.5%,
J.A. Schulte, E.M. Cartwright / Molecular Phylogenetics and Evolution 50 (2009) 391–396
G = 20.9%, T = 23.4%; RAG1: A = 31.6%, C = 20.6%, G = 22.8%,
T = 24.9%), although this difference was not statistically significant. The glutamine- and proline-rich variable region in the gene
encoding TSHZ1 could not be aligned unambiguously and was excluded. No regions in RAG1 were excluded. Excluded regions constitute less than 1.5% of aligned sequence positions (72 of 5265
positions).
Translated amino acid variation in TSHZ1 showed an interesting
pattern between acrodont and iguanid clades. Functional regions of
the TSHZ1 protein were examined using the Pfam 23.0 database
(Finn et al., 2008). Among all sequences, at least one and, for some
sequences, two C2H2 zinc finger domains were identified near the
carboxyl-terminus end. The region between approximately 550
and 620 amino acids in all sequences was identified as a homeobox
region. Finally, in the excluded region, among acrodont lizards the
average amino acid content was 31.5% glutamine and 53.0% proline, whereas among iguanid species sampled average amino acid
content was 86.3% glutamine and 9.9% proline. This difference appears to have an important functional consequence as glutamine
has a polar, hydrophilic R-group and proline contains a nonpolar,
hydrophobic R-group. This region was identified as a singlestranded DNA binding domain (Bayarsaihan et al., 1998) in all
iguanids but not inferred to a known protein domain in any examined acrodont.
Of the 4950 inferred unambiguous aligned sites, there are 1839
(1248 ingroup only) unique site patterns, 2257 (1842 ingroup only)
variable characters, and 1498 (1029 ingroup only) parsimony
informative characters. For the gene encoding TSHZ1, there are
2155 inferred unambiguous aligned sites, 634 (448 ingroup only)
unique site patterns, 751 (611 ingroup only) variable characters,
and 465 (321 ingroup only) parsimony informative characters.
For the gene encoding RAG1, there are 2795 sites inferred unambiguous aligned sites, 1315 (940 ingroup only) unique site patterns, 1506 (1231 ingroup only) variable characters, and 1033
(940 ingroup only) parsimony informative characters. The average
unpartitioned ML-corrected distance (GTR + I + C - Model parameters are as follows: a = 1.167; proportion of invariant sites = 0.503;
substitution rates R (a) = 0.876, R (b) = 5.294, R (c) = 0.962, R (d) =
0.606, and R (e) = 5.025; and estimated base frequencies
A = 0.316, C = 0.228, G = 0.209, and T = 0.247) among and within
sampled lineages for TSHZ1 is comparable to previously reported
values among nuclear regions in squamates (Townsend et al.,
2008; see for data on RAG1): Gallus–Squamata – 23.6%; Squamate
outgroups–Iguania – 12.9%; Acrodonta–Iguanidae – 13.8%; within
Acrodonta – 7.0%; within Iguanidae – 5.4%.
The ML tree with the highest likelihood ( ln L = 34460.4) using
the combined data set and six partitions is shown in Fig. 1. Monophyly of Iguania, Iguanidae, and Acrodonta is strongly supported
by ML bootstrap analysis (100%). Within Agamidae, Leiolepis is
moderately supported (94%) as the sister group to a well supported
clade (100%) containing species representing the clades Agaminae,
Amphibolurinae, Draconinae, and Hydrosaurinae. Iguanid relationships among the 12 major lineages are poorly supported by ML
bootstraps using all partitioning schemes. Among outgroup lineages, ML bootstrap analysis indicates strong support (100%) for
the sister-taxon relationship between snakes + anguimorphs and
iguanians (Toxicofera of Vidal and Hedges, 2005) as well as the
relationship (96%) between xantusiids and skinks (Scincoformata
of Vidal and Hedges, 2005). For each of the other partitions in
the separate and combined analyses, there were no strongly supported (bootstrap value >95%) relationships in conflict with those
reported in Fig. 1.
The consensus topology of the 2000 trees in the posterior distribution from mixture-model analyses of the combined data recovered no strongly supported incongruence with the ML topology
(Fig. 1). Only one of five runs was used in calculation of the cons-
393
Fig. 1. Phylogenetic relationships among iguanian lizards and six outgroup species
based on maximum likelihood and Bayesian analyses of combined and separate
partitions of the genes encoding TSHZ1 and RAG1. The topology shown corresponds
to highest ML tree from eight independent runs in RAxML (-log likelihood =
34460.4). The numbers adjacent to each node correspond to ML bootstrap
proportions as follows: ML combined data with six partitions/TSHZ1 with three
partitions/RAG1 with three partitions. Numbers below nodes correspond to
Bayesian credibility (BC) values generated by BayesPhylogenies runs including
gamma as follows: Combined data with three site patterns/TSHZ1 with two site
patterns/RAG1 with two site patterns. Two dashes indicates that either the
bootstrap proportion/BC value was below 50% or that branch was not recovered
by a particular analysis.
enus topology as these data converged on three different optima.
Of these three optima, three rate matrices best explained the data
using Bayes Factors calculated in Tracer 1.4 with an arithmetic
mean likelihood score of ln = 35,680. The two consensus topologies of 15,000 trees in the posterior distribution from analyses of
the separate genes were similar to those of the combined analysis
with comparable BC node values. The only exception was a high BC
value (100%) using TSHZ1 for a clade containing Phrynosmoa, Anolis,
and Plica; a relationship with low or no support in all other analyses (Fig. 1). Both genes estimated two rate matrices to explain each
data set with arithmetic mean likelihood scores of 23,550 and
12,020 for RAG1 and TSHZ1, respectively. BC node values for all
strongly supported nodes from ML analyses were 100%. One moderately supported node by ML bootstraps had BC values = 100%
(the clade containing Leiolepis and all other agamid lineages except
Uromastyx). For the combined and RAG1 only data sets, three nodes
had BC values between 86 and 100% but were weakly supported by
ML bootstraps. These were the sister-taxon relationship of geckos
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J.A. Schulte, E.M. Cartwright / Molecular Phylogenetics and Evolution 50 (2009) 391–396
and remaining squamate species sampled, the monophyly of
Chalarodon and Pristidactylus, and the sister-taxon relationship of
Leiocephalus and remaining iguanid lineages.
Accounting for data heterogeneity is essential for accurate
estimation of phylogenetic hypotheses (Schulte and de Queiroz,
2008). The two primary methods currently utilized are to assume a priori partitions of the data (mixed models) and to estimate the appropriate number of rate matrices that best explains
the site patterns in a data set (mixture models). Reversible-jump
model selection offers the additional advantage of incorporating
model selection into the analytical process by using the data to
estimate the appropriate model or number of rate matrices that
best explains the data (Huelsenbeck et al., 2004; Pagel and
Meade, 2004, 2005). For our data, ln L scores from ML analyses
with a priori partitioning were a better fit to the combined data
than RJ Bayesian analyses with three rate matrices estimated.
Although the RJ Bayesian mixture-model approach has several
advantages mentioned above, ML bootstrap support and BC values were comparable for most nodes. However, the advantages
of within and between partitions pattern estimation and not
having to compare multiple potentially arbitrary partitions for
multigene datasets are two practical strengths of RJ Bayesian
methods. Additional work is necessary to evaluate whether a
priori partitioning under ML reduces the node density artifact
(Venditti et al., 2008).
Our analyses did not recover strong support for all relationships among iguanid and acrodont lineages, a result not unexpected given previous studies based on nuclear and mtDNA
sequence data (Harris et al., 2001; Schulte et al., 2003; Townsend et al., 2004). However, several higher-level relationships
within Iguania and among squamate outgroups were supported.
Several relationships recovered by Townsend et al. (2004) using
RAG1 only were recovered in our TSHZ1 only analysis with
strong support including monophyly of Acrodonta and Iguanidae,
a clade containing representative species of Agaminae, Amphibolurinae, Draconinae, and Hydrosaurus, as well as the sister group
relationship of snakes and anguimorphs to Iguania. For the combined analysis, support for several branches increased relative to
using RAG1 alone, including a clade containing all acrodonts except Uromastyx and Brookesia, monophyly of Iguania and Toxicofera, a sister group relationship between Plestiodon and Xantusia,
and geckos as the sister group to all other sampled squamates.
Therefore, we found that TSHZ1 is an informative marker for
higher-level relationships and expect it to be useful for other
vertebrate clades as well.
Molecular systematists typically use two strategies to sample
multiple loci to reconstruct phylogeny. One is to use multiple
(>10) small gene fragments, typically less than 800 base pairs that
are easily amplified using conservative, ‘‘universal” primers and
concatenating these into a larger data set for analysis (Rokas
et al., 2003). Townsend et al. (2008) demonstrate a method to identify nuclear protein coding loci that can be used in squamate systematics, but most of these fragments are less than 800 basepairs
and only three are greater than 1000 nucleotide positions. An alternative strategy is to amplify fewer (<10) whole genes or larger
(>1500 bp) gene fragments (Cummings and Meyer, 2005; Driskell
et al., 2004). These alternative strategies, or combinations of the
two, have not been adequately tested to identify the most optimal
strategy systematists should employ. The addition of TSHZ1 to the
list of relatively large genes that can be used in the second strategy
will help to address this dilemma.
Acknowledgments
We thank Clarkson University and the National Science Foundation (DEB-0314092) for financial support; A. Meade and M. Pagel
for analytical advice, support, and use of their computing facilities.
C. Cicero (MVZ), F.B. Cruz (Universidad Nacional del Comahue), D.
Dittman (LSUMZ), R.Etheridge (SDSU), J. R. Macey, J. McGuire
(MVZ), T.J. Papenfuss (MVZ), S. Poe (UNM), F. Sheldon (LSUMZ),
B. Stuart (FMNH), T. Townsend (SDSU), and J. Vindum (CAS), L.P.
Vitt (OU), and D.B. Wake (MVZ) for tissue specimens and information. S. Biswas commented on an earlier version of this manuscript.
The Oklahoma Department of Conservation for permits to J.A.S. for
voucher specimen collection.
Appendix A
Museum numbers and localities for voucher specimens from
which DNA was obtained and GenBank accession numbers are presented (to be included upon acceptance of manuscript): CAS for California Academy of Sciences, San Francisco, California; FMNH, Field
Museum of Natural History, Chicago, Illinois; GNHM Re. ex., Göteborg Natural History Museum Reptilia Exotica, Göteborg, Sweden;
MLP for Museo La Plata, La Plata, Argentina; MVZ for Museum of
Vertebrate Zoology, University of California, Berkeley, California;
OU for Sam Noble Oklahoma Museum of Natural History, Norman,
Oklahoma; TNHC, Texas Memorial Museum, Austin, Texas; JAS for
uncatalogued specimen of James A. Schulte II to be deposited in
USNM; POE for uncatalogued specimen of Steven Poe to be deposited in Museum of Southwestern Biology, Albuquerque, New Mexico; PT for uncatalogued specimens of Félix B. Cruz being deposited
in the Fundación Miguel Lillo, Tucumán, Argentina. TP for uncatalogued specimen of Theodore J. Papenfuss to be deposited in MVZ.
Except where noted, specimens used for both TSHZ1 and RAG1 gene
fragments are the same. GenBank numbers are given for TSHZ1 first
followed by RAG1. Outgroups: Gallus gallus [(NC_006089 REGION:
complement (93684444..93689073); M58530]; Gekko gecko, vic
Mwe Hauk Village, Ayeyarwady Div., Myanmar (CAS204952;
FJ356750; MVZ215314–AY662625); Plestiodon fasciatus, trail near
River Oak Campground, North of Panhandle Road, State Route
613, Warren Co., Virginia, USA (JAS87; FJ356752; Eumeces inexpectatus – MVZ137529–AY662632); Xantusia vigilis, unavailable
(TP29490; FJ356751; MVZ228254–AY662642); Coluber constrictor,
open field North of Cimarron River, between levies, near intersection of N2870 and N0730 Roads, Kingfisher Co., Oklahoma,
USA (JAS189; FJ356753; Dinodon rufozonatum – CAS178042–
AY662611); Elgaria multicarinata, Hwy 162, 6.86 mi E (by rd) of
Hwy 101, Mendocino Co., California, USA (CAS201252; FJ356754;
Elgaria panamintina – MVZ227761–AY662603); Ingroups: [Acrodonta] Brookesia theili, Ambohitantely Special Preserve, Madagascar
(FMNH260003; FJ356755; AY662577); Uromastyx benti, Dhofar,
18 km N (by Salalah Rd) of Mirabat, Oman (CAS227579;
FJ356756; FJ356733); Leiolepis belliana, Pwint Phu Township, Shwesettaw Wildlife Sanctuary, Lap Pam San Camp, Magway Div., Myanmar (CAS213814; FJ356757; FJ356734); Hydrosaurus pustulatus,
Barangay San Carlos, Municipality of Valderrama, Antique Province,
Panay Island, Philippines (TNHC56762; FJ356760; Hydrosaurus sp.,
TNHC54902; AY662583); Physignathus cocincinus, Tam Dao, Vinh
Yen District, Vinh Phu Prov., Vietnam (MVZ224108, FJ356761;
FJ356737); Mantheyus phuwuanensis, near That Xay waterfall, Phou
Khao Khouay National Biodiversity Conservation Area, Thaphabat
District, Bolikhamxay Province, Lao PDR (FMNH255495;
FJ356758; FJ356735); Trapelus ruderatus, Kermanshahan Province,
Iran (GNHM Re. ex. 5212, FJ356759; FJ356736); [Iguanidae] Leiocephalus raviceps, 37 km E of Guantanamo, Yateritas, Guantanamo
Prov, Cuba (POE913; FJ356768; FJ356744); Liolaemus lineomaculatus, Laguna LaPlata, Chubut Prov., Argentina (MLP1670, FJ356764;
FJ356740); Phrynosoma cornutum, on E1490 road, 1000 meters
East of Elk Creek, Kiowa Co., Oklahoma (JAS193; FJ356762;
FJ356738); Plica plica, approximately 5 km N Porto Walker, Acre
Prov., Brazil (OU37036, FJ356766; FJ356742); Anolis carolinensis,
J.A. Schulte, E.M. Cartwright / Molecular Phylogenetics and Evolution 50 (2009) 391–396
no locality data (JAS250; FJ356763; FJ356739); Chalarodon madagascariensis, Madagascar (uncatalogued, FJ356769; FJ356745); Polychrus marmoratus, approximately 101 km S and 18 km E Santarem,
Agropecuaria Treviso LTDA, Pará , Brazil (OU36693, FJ356772;
FJ356748); Dipsosaurus dorsalis, Coachella Valley, Indio Hills, Varner
Rd, 3 mi NW of Thousand Palms, Riverside Co., California, USA
(CAS208708, FJ356771; FJ356747); Pristidactylus scapulatus, 2 km
S Esperanza, Río Negro Prov., Argentina (PT4810, FJ356770;
FJ356746); Morunasaurus peruvianus, [previously referred to as M.
annularis in Schulte et al. (2003)] Rio Cenepa, ridge on N side at
Headwaters of the Rio Kagka, Departamento Amazonas, Peru
(MVZ163062, FJ356765; FJ356741); Basiliscus galeritus, 100 m, Rio
Cauque, E Pedernales via road from Pedernales to El Carmen, Manabi Prov., Ecuador (MVZ226111, FJ356767; FJ356743); Crotaphytus
collaris, intersection of E9490 and N2160 Roads, Kiowa Co., Oklahoma, USA (JAS195; FJ356773; FJ356749).
Appendix B
‘‘f” and ‘‘r” in the primer name correspond to read direction (forward or reverse) of the primer with all primers reported to read in
the same direction. Prior to use, ‘‘r” primers should be reverse complemented. All primers are newly reported except R13F (Townsend
et al., 2004).
One primer pair was used to amplify the TSHZ1 gene from genomic DNA: TSHZ1f.1 – TTACCAGAAAGTGCCTCTGAAGGAGCC and
TSHZ1r.3 – ACATAGATCAGATGGTCCTCNGG. Both strands were
sequenced using the following primers: TSHZ1r.2 – ATCAGRTGG
TCCTCNGGAGACTTGCC; TSHZ1f.4 – GTGGTAGAAGAAAAGATACA
GTC; TSHZ1r.5 – AGATCYTCTTCTCTGAGGTACTG; TSHZ1f.6 – GATG
CAGATGGAAGTAGTTTTGAGGARGC; TSHZ1r.7 – GTCTCCCTCAAGC
TNGAAGCAAACTG; TSHZ1r.8 – GCTGTTGTCACTGTATTTTCCAGRG;
TSHZ1f.9 – CYCTGGAAAATACAGTGACAACAGC; TSHZ1r.10 – AAA
GCACTCAGAGGGTTATGAAWGATGG; TSHZ1r.11 – CTAGATCCTC
CTCTCTTAG; TSHZ1f.12 – GGCTGTAATAACTTGGGTATCATCAC.
Two primer pairs were used to amplify the RAG1 gene from
genomic DNA: R13F – TCTGAATGGAAATTCAAGCTGTT with either
JRAG1r.6 - CTATGAAATGGAAGATGTCTTAAAGC (iguanids) or
JRAG1r.8 - CTTGGGCAAGTGAGGGAAATGAGTC (acrodonts). Both
strands were sequenced using the following primers: JRAG1f.1 - C
AAAGTGAGACSACTTGGAAAGCC; JRAG1f.2 –CAAAGTRAGATCACT
TGAGAAGC; JRAG1r.3 - CGYCTAAGAGAACTCAAGCTRCAAGT;
JRAG1f.9 - CAAAGTTTTGTCACCANTGTTGG; JRAG1r.10 - TTCAAAA
GAAATTAAGCAATTC; JRAG1f.11 - TCAATCTCTTGCCAGATCTGTGA
GC; JRAG1f.12 - GAGTGGAAACCACCCTTGAAAAATG; JRAG1r.13 - G
AGTGGAAACCACCCTTGAAAAATG; JRAG1f.14 - CTTGATATGGCTGG
AATCCCAAG; JRAG1f.15 - ATGAATGGGAATTTTGCCAGAARGCT;
JRAG1r.16 - CTCATGGACCTTTACCTKAAGATGAAACC; JRAG1f.17 - A
TCTCCTTGCCAAAGTGTTC; JRAG1f.20 - AAGATATTCCAGTTTGAAA
TTGG; JRAG1r.23 - CTGTGGTGATTAAAGAGTCTTGTG; JRAG1r.24 - C
CRTGGAGTGAAGAGAAAGA; JRAG1f.25 - CARGAGGAGGTCTGTTTG
GG; JRAG1r.26 - CTTCATTCCATCACAAGGAGTC; JRAG1f.27 - ACTG
TGACATTGGCAATGCAGC; JRAG1f.28 - CAGGCCTTCATCCAGCTGT
TTGYTTGGC; JRAG1r.29 - TTGCHGGAATGTGRTTCAAAG; JRAG1f.30
- CACCTYAGTACCAAGATYCTTGC; JRAG1f.31 - GATGAAAAACTTGT
CCGTG; JRAG1r.32 - CACCTCAGTACCAAGATCCTTGC; JRAG1r.34 – C
CATCCTGAGYCCTCTTGTAGC.
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