DNA barcoding of non-avian reptiles based on the cytochrome oxidase subunit I (COI) gene is still in a very early stage, mainly due to technical problems. Using a newly developed set of reptile-specific primers for COI we present the first comprehensive study targeting the entire reptile fauna of the fourth-largest island in the world, the biodiversity hotspot of Madagascar.
Representatives of the majority of Madagascan non-avian reptile species (including Squamata and Testudines) were sampled and successfully DNA barcoded. The new primer pair achieved a constantly high success rate (72.7–100%) for most squamates. More than 250 species of reptiles (out of the 393 described ones; representing around 64% of the known diversity of species) were barcoded. The average interspecific genetic distance within families ranged from a low of 13.4% in the Boidae to a high of 29.8% in the Gekkonidae. Using the average genetic divergence between sister species as a threshold, 41–48 new candidate (undescribed) species were identified. Simulations were used to evaluate the performance of DNA barcoding as a function of completeness of taxon sampling and fragment length. Compared with available multi-gene phylogenies, DNA barcoding correctly assigned most samples to species, genus and family with high confidence and the analysis of fewer taxa resulted in an increased number of well supported lineages. Shorter marker-lengths generally decreased the number of well supported nodes, but even mini-barcodes of 100 bp correctly assigned many samples to genus and family.
The new protocols might help to promote DNA barcoding of reptiles and the established library of reference DNA barcodes will facilitate the molecular identification of Madagascan reptiles. Our results might be useful to easily recognize undescribed diversity (i.e. novel taxa), to resolve taxonomic problems, and to monitor the international pet trade without specialized expert knowledge.
Citation: Nagy ZT, Sonet G, Glaw F, Vences M (2012) First Large-Scale DNA Barcoding Assessment of Reptiles in the Biodiversity Hotspot of Madagascar, Based on Newly Designed COI Primers. PLoS ONE 7(3): e34506. doi:10.1371/journal.pone.0034506
Editor: Jerome Chave, Centre National de la Recherche Scientifique, France
Received: October 11, 2011; Accepted: March 2, 2012; Published: March 30, 2012
Copyright: © 2012 Nagy et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: The study was funded by the Belgian Science Policy Office (Belspo). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
The elementary question how many species of eukaryotic organisms live on Earth has in the past decades led to remarkable controversies –. Current estimates of global species numbers differ enormously, ranging from 2 to 100 million, while ca. 1.7–1.9 million species have thus far been formally described. However, there is a broad agreement that the highest proportion of Earth's biodiversity—expressed in species numbers—is yet to be discovered and described. Even in several of the most prominent animal groups such as vertebrates and butterflies, a remarkable proportion of undescribed diversity is being discovered (e.g. Lepidoptera: ; fish: ; amphibians: –). Given that just 16,000–20,000 species are being described per year ,  and traditional taxonomy involves high costs (estimated between $39,000–$122,000/species including salaries etc. ), strategies are required to speed up both the process of species discovery and species delimitation and description. A solution for the second of these challenges, the Linnean shortfall , is not in sight. Besides more posts for professional taxonomists , fundamentally new ideas and approaches will be required, especially in hyperdiverse groups such as small insects or nematodes. On the contrary, the initial identification of new species has been much facilitated and accelerated by DNA-based methods, and the term DNA barcoding has been proposed –. Similar to a long standing practice in microbiology , a short DNA sequence of a standard marker is used for species identification—in animals typically the mitochondrial gene for cytochrome oxidase subunit I (COI). This molecular survey method has been applied in a number of vertebrate taxa (e.g. birds: , ; fish: ) and invertebrates (e.g. spiders: , Lepidoptera: –, marine invertebrates: , and Heteroptera: ). DNA barcoding has the potential to increase the rate of discovery enormously  and to discover unexpected genetic diversity such as in butterflies – or in amphipods , . From practical point of view, DNA barcoding requires a comprehensive reference database . Such reference data sets are being assembled by the barcoding campaigns initiated by the Consortium for the Barcode of Life (CBOL). For vertebrates, campaigns focusing on fish, birds and mammals have been started: the ‘Fish Barcode of Life Initiative’ (FISH-BOL, www.fishbol.org; ), the ‘Shark Barcode of Life’ project (www.sharkbol.org), the ‘All Birds Barcoding Initiative’ (ABBI, www.barcodingbirds.org) and the ‘Mammal Barcode of Life’ (www.mammaliabol.org) project. A new barcoding campaign called ColdCode dedicated to amphibians and non-avian reptiles has been announced in September 2011, and new COI primers for amphibians have been published . Although molecular data are regularly used to discover and delimit new species of reptiles, no large-scale DNA barcoding effort has so far targeted an entire species-rich reptile fauna of a large region.
To facilitate reading, we will in the following use the traditional term ‘reptiles’ for species included in the vertebrate orders Squamata, Testudines, Crocodylia, and Rhynchocephalia, i.e. Sauropsida excluding birds. We continue using the term ‘reptiles’ for practical reasons only and without any phylogenetic relevance.
Due to technical problems in the amplification and evaluation of COI sequences in amphibians and reptiles linked to a high variability of sequences including priming sites, authors of previous attempts  have preferred the use of a fragment of the mitochondrial 16 S rRNA gene for DNA barcoding (sensu lato) despite its non-coding characteristics and resulting alignment problems. Although recent publications claim that the difficulties of COI amplification in amphibians can be overcome , various teams have experienced problems. Therefore, COI as marker for molecular identification and for phylogenetic and phylogeographic studies has been rarely used by herpetologists. Consequently, there is a serious lack of DNA barcodes for amphibians and reptiles, and according to the Barcode of Life Data Systems  DNA barcodes of most taxa of reptiles (even on higher taxonomic levels) inhabiting Madagascar are virtually absent. This highlights the need for development and testing of primers and amplification strategies for these organisms .
Here we start filling this gap and provide a DNA barcoding assessment of the reptile fauna of Madagascar, the fourth-largest island in the world that has been flagged as one of the most important hotspots for biodiversity conservation  and as a model region to study species diversification . Madagascar's biota is most fascinating due to the unique level of endemism associated with high alpha diversity . Approximately 92% of the non-marine species of Madagascan reptiles (i.e. excluding sea turtles and sea snakes) are endemic to the island, and many of them are furthermore microendemic to very small ranges . By 2007, around 370 nominal species of reptiles were known from Madagascar . Thanks to intensive and integrative taxonomic work in the last approximately 20 years, this number is continuously growing. Since 2007 alone, 22 new species have been described, bringing the total number of nominal species of reptiles from Madagascar up to 393 at present. Genetic, phylogenetic and phylogeographic information on several taxonomic groups is accumulating as well , . At the same time, increased and insufficiently controlled human activities affecting the habitats seriously threaten the long-term sustainment of this fauna and make a comprehensive assessment of the diversity a high priority.
In this study we aim to characterize the majority of Madagascan reptiles by DNA barcoding based on a newly developed set of reptile-specific primers for COI. We compare the performance of this method to assess the species diversity of a large biodiversity hotspot, exemplified by the Madagascan “microcontinent” with its clades of reptiles of different temporal diversification background, and test the performance of the method depending on barcode length and completeness of taxon sampling.
Materials and Methods
No experiments were conducted using living animals. Furthermore, none of the samples were specifically collected for this project. We exclusively used museum samples which were already available and were deposited in a tissue bank.
All field researches and collecting of specimens were approved by the Madagascan Ministère de l'Environnement, des Eaux et des Forêts (Direction des Eaux et Forêts, DEF) under the following permits: 156-MEF/SG/DGEF/DADF/SCB dated 12 December 2002; 238-MINENVEF/SG/DGEF/DPB/SCBLF dated 14 November 2003; 238-MINENV.EF/SG/DGEF/DPB/SCBLF/RECH dated 22 December 2004; 272-MINENV.EF/SG/DGEF/DPB/SCBLF/RECH dated 8 November 2005; 298-MINENV.EF/SG/DGEF/DPB/SCBLF/RECH dated 22 December 2006; 036/08 MEEFT/SG/DGEF/DSAP/SSE dated 30 January 2008; 26/09/MEEFT/SG/DGEF/DSAP/SLRSE dated 3 February 2009; 48/09/MEEFT/SG/DGEF/DSAP/SSE dated 9 March 2009; 188/09/MEEFT/SG/DGEF/DSAP/SSE dated 16 September 2009; 195/09/MEEFT/SG/DGEF/DSAP/SSE dated 28 September 2009. Export of specimens was approved by the DEF under permits: 063C-EA02/MG03, dated 26 February 2003; 094C-EA03/MG04, dated 1 March 2004; 103C-EA03/MG05, dated 15 March 2005; E 1400/06, dated 1 June 2006; 055N-EA03/MG10, dated 25 March 2010. Import of species protected by CITES into Germany was approved by the German authorities (Bundesamt für Naturschutz). Voucher specimens were euthanized using proved methods (e.g. anaesthesia with ketamine, followed by ketamine overdosis) that do not require approval by an ethics committee.
We sampled 468 specimens of Madagascan reptiles mostly deposited in publically accessible natural history collections (for list of samples, see Table S1). About 420 of these samples were determined to belonged to 251 nominal species. Another ca. 50 samples could not be reliably assigned to any nominal species based on morphology and had high sequence divergences to the other samples included (candidate species as defined below). Samples belong to nine squamate families, Chamaeleonidae, Iguanidae (Opluridae), Gerrhosauridae, Scincidae, Gekkonidae, Boidae, Lamprophiidae, Psammophiidae (the latter two snake families were formerly included in Colubridae sensu lato), Typhlopidae (sensu lato, i.e. also including the recently described Xenotyphlopidae), and to the tortoise and turtle families Testudinidae and Pelomedusidae. Due to practical problems such as restricted distribution and rareness of species, identification problems, or inclusion of species in CITES, only a limited amount of samples were available for the majority of species (on average, 1.7 samples per species, ranging from 1 to 5). Therefore, our sampling strategy was to include only single samples for most species but to select these as carefully as possible, making sure their identification is correct and they are backed by a traceable voucher specimen. For this purpose we chose, whenever possible, samples from type material (holo- or paratypes) or collected at or near the type locality. All collecting localities are listed in Table S1. Altogether about 85 species were represented by at least one specimen from the type locality or its surroundings, and altogether 23 species were represented by sequences from type specimens (marked in Table S1).
Specimens and samples were collected from numerous localities in Madagascar in the years 2000–2009. Tissue samples removed from freshly collected specimens were stored in 95–99% ethanol. Total genomic DNA was extracted with commercial kits, we used the NucleoSpin Tissue Kit (Macherey-Nagel, Germany) and the Qiagen DNeasy 96 Blood & Tissue Kit (Qiagen, Germany).
We newly designed a degenerative primer pair based on squamate mitochondrial genome sequences available in GenBank. This primer pair amplifies the standard barcoding region (maximal length: 664 bp) of the cytochrome oxidase I gene : RepCOI-F: 5′-TNT TMT CAA CNA ACC ACA AAG A-3′ and RepCOI-R: 5′-ACT TCT GGR TGK CCA AAR AAT CA-3′. The PCR protocol followed the profile of 94°C for 3 min; 40 cycles of 94°C for 40 s, 48.5°C for 30 s and 72°C for 60 s; 72°C for 7 min, and subsequent storage at 4°C. PCR products were visualized on ca. 1.2% agarose gel, and purified using the NucleoFast 96 PCR Plate (Macherey-Nagel, Germany). PCR products were sequenced bidirectionally using the same primers. The sequencing was mainly carried out on an ABI 3130xl automated capillary sequencer using BigDye v1.1 chemistry and following the manufacturer's instructions (Life Technologies, USA). Some samples were resolved on automated sequencers by a commercial service provider for DNA sequencing.
Sequences were assembled, aligned and checked for their quality using the SeqScape v2.5 software (Life Technologies, USA). Sequences of doubtful mitochondrial origin (e.g. sequences showing suspiciously high divergence to any other COI sequence or where internal stop codons were detected), were removed from the final data set. We only used sequences with a length encompassing at least 90% of the standard animal barcoding region (i.e. at least 600 bp) as a high-quality read and based our calculation on success rates on this yardstick. The alignment was submitted to a test of substitution saturation ,  as implemented in DAMBE v5.2.34 . In addition, transitions and transversions were plotted against Kimura 2-parameter (K2p) divergences to visualize possible saturation at higher divergence level. Neighbor-joining (NJ) trees based on K2p distances were calculated using MEGA5 . We also used Bayesian inference and calculated a Bayesian consensus tree and posterior probabilities supporting nodes using MrBayes v3.1.2 . For the latter analysis, the best-fit nucleotide substitution model was selected by jModeltest  using AIC(c) and BIC. In the Bayesian analysis, two parallel runs with four chains each were run for 10 million generations. The first 60% of the trees were discarded, the convergence of the chains was monitored by Tracer v1.5 . A maximum likelihood (ML) tree was calculated and a ML bootstrap test with 100 replicates was performed using the DIVEIN web server  that is based on PhyML v3.0 .
To assess the number of deep genealogical lineages in our dataset that represent potentially undescribed species, we first determined a threshold value of genetic divergences that typically are found among closely related species. For this we used a reference subset of our data with sequences of unambiguously identified specimens. This reference set included 251 well-delimited nominal species represented by single specimens and belonging to eight squamate families. Psammophiid snakes, turtles and tortoises were excluded from these analyses due to the low number of specimens and species included. Average interspecific genetic divergence (both K2p and p distance) was calculated in each squamate family involved. In addition, average values of genetic distance were calculated among all well-supported sister species (supported by >70% bootstrap and selected based on the initial NJ analysis) in each of those eight families. These average divergences were then used as family-specific thresholds for candidate species (as defined according to Vieites et al. ) in the complete data set. We counted as candidate species those unidentified lineages differentiated by a genetic divergence above the family-specific threshold from their closest relative.
We assessed by simulations the effect of a less comprehensive taxon sampling (only a certain proportion of species included) and of a reduced genetic sampling (shorter DNA fragment used) on the results. In the first test series (taxon subsampling), four times 100 random subsets of our data set were created, including 75, 50, 25, and 10% of the species included in the original data set. In the second test series, we aimed to evaluate the performance of the “mini-barcode” approach . Fragments stretching over the first 100, 200, 300, and 450 bp of the barcoding region were selected, respectively. For each subsets produced in both test series (i.e. 400 subsets in the subsampling with variable number of taxa, 4 in the subsampling with different fragment size), NJ trees based on K2p distances were calculated, and bootstrap analyses with 1000 replicates were carried out. The topology and bootstrap values of these trees were then compared with the most complete NJ tree obtained with the original data set. We checked in all trees whether genera and families were clustered as groups and recorded the support values of those groups. Groups with single specimens were obviously excluded from the analysis.
One goal of DNA barcoding is to match an unidentified sample to a certain species by comparison with existing sequences of well-identified species. When a species-level identification is ambiguous because of an incomplete set of references, it often is desirable to obtain at least a reliable attribution of the non-identified sample to a higher taxon, for example a genus. In incomplete databases, identification tends to decrease with increasing taxon coverage  but obviously with a complete set of reference sequences of all species, identification success will be very high. We tested the success of COI sequences to correctly cluster with a sequence to a higher clade by selecting a number of genera reliably known to be monophyletic from previous phylogenetic studies. (Liopholidophis, Lygodactylus, Phelsuma, Trachylepis, Uroplatus and Zonosaurus). We scored whether these genera became non-monophyletic in COI trees at lower taxon sampling or with shorter sequences, and whether this topology received high support values. Non-monophyly in this case implies a wrong genus-level assignment of at least some of the sequences and in a tree-based approach is thus an indicator to the reliability by which sequences of unknown identity without a clear match in a reference database can be attributed to genus-level. Tests were performed on the complete data set, on the ‘mini-barcode’ data set (all sequences, 100 bp) and on 100 subsets including 10% of the species (full sequence length). The automation of the subsampling and the analysis of NJ trees was implemented in an R script (Sonet & Nagy unpublished).
DNA barcodes for Madagascan reptiles
Using the new primer pair, we produced COI sequences for the majority (ca. 64%) of the Madagascan species of reptiles. Beyond well recognizable and “established” species, we also included several confirmed or unconfirmed candidate species  and indicate these as ‘sp.’ or ‘aff.’.
The success rate of the PCR amplification and DNA sequencing was constantly high even when only degraded DNA or minimal amounts of tissue samples were available. Nevertheless, in 21 cases when sequencing failed in a first attempt, we re-extracted DNA from another tissue sample of the same specimen and repeated the downstream process with unchanged conditions (as an approximation to automated, high-throughput procedures). In several cases, repeated attempts of amplification or sequencing failed again. In total, 489 tissue samples were taken, representing 468 specimens. After quality checks, 396 sequences with a maximal length of 664 bp (range of sequence length: 604–664 bp) were used to build a data set for the analyses. This corresponded to an ultimate success rate of 84.6%. Success rate varied over the taxonomy, for example turtles and geckos failed more often than chameleons and snakes (Table 1). BoL standard primers were not extensively tested after initial failure.
The substitution saturation analysis showed little overall saturation, i.e., the index of substitution saturation, Iss, was always significantly lower than the critical value of the index of substitution saturation, Iss.c; , . The graph showing transitions and transversions plotted against divergence (Figure S1), however, indicated saturation at higher divergence level.
The DNA barcoding approach generally worked well for most Madagascan reptiles as the Folmer fragment of the COI gene  distinguished well on specific as well as on higher taxonomic levels (Figure 1). All applied tree-reconstruction methods (i.e. neighbor-joining based on genetic distance, maximum likelihood and Bayesian inference) recovered many well supported groups corresponding to ranks of species, genera and even families. These tree-reconstruction analyses were largely concordant in topology (see Figures S2, S3 and S4 for NJ, Bayesian and ML trees, respectively) and, we relied on the NJ tree for further analyses.
Inset photos and genus names refer to representative species-rich genera (for a tree with complete taxon names, see Supplementary Materials). Filled circles mark groups corresponding to these genera; when a genus was reconstructed paraphyletic, open circles denote the placement of its members (not shown in all cases due to graphical reasons).
High sequence diversity on the generic and specific level
The depth of diversity calculated on average pairwise genetic distances between well-defined (‘good’) species varied remarkably among the investigated families. The lowest divergence was found among the Madagascan boas (Boidae). In general, snakes, gerrhosaurids and iguanas showed lower average divergence, while skinks, chameleons and especially geckos showed higher overall pairwise divergence (Table 2).
The average divergences between species in sister species pairs were even more obviously different among clades, although usually a low number of sister pairs were found with high bootstrap support; snakes, skinks and chameleons showed comparatively low divergences between sister pairs on average, while iguanas, geckos and gerrhosaurids showed high divergences. Based on these latter values used as threshold, we counted the number of candidate species (as summarized in Table 2). In total, our analysis revealed 41–48 candidate species in our limited data set that represent 16–19% of the included more than 250 nominal species, and 10–12% of the known diversity of reptiles in Madagascar. We emphasize that these are minimum values directly inferred by counting above-threshold lineages in our data set. Estimating the total proportion and number of candidate species across Madagascan reptiles is at present not possible because too few species in our data set are represented by multiple sequences and too few geographic locations per species have been sampled.
A few examples involving several candidate species and particularly high divergences were as follows: the chameleons in the Calumma nasutum complex (11.3–18.9% K2p divergence), the geckos in the Phelsuma lineata complex (4.2–18.6%), the skink Trachylepis gravenhorstii (6.2–14.0%), and the snake Pseudoxyrhopus tritaeniatus (7.8–9.9%). In some cases, specimens thought to belong to the same species clustered paraphyletically in clearly independent, well supported groups (see Figures S2, S3, S4 for details). The most striking example was that of the terrestrial snake species Liophidium torquatum where two deeply divergent lineages were found. One of them was closely related to the single Comoran species Liophidium mayottensis that we included in the otherwise exclusively Madagascan data set. A few notable exceptions of no or very low genetic divergences between species were the Phelsuma modesta complex, the species pair Phelsuma dubia and P. ravenala, and the species Brookesia antakarana and B. ambreensis.
The effect of taxon sampling
The complete data set included 57 genera of which 38 were represented by more than a single sequence. Twenty-two of these 38 genera clustered in monophyletic units, and 12 of them were supported by high bootstrap values (>90%) in the NJ tree. On the family level, nine of eleven families formed monophyletic groups, and eight of them were well supported in the NJ tree (Figure S2, Table S2).
Results of simulations with randomly selected subsets of 75, 50, 25, and 10% of the species were summarized in Table S2. Bootstrap values supporting genera (Figure 2) and families (Figure 3) ranged widely in the NJ trees obtained. However, on average, the number of strongly supported genera and families remained virtually unchanged in all analyses. Genera that were well supported in the original data set remained generally well supported at a lower taxon sampling. In contrast, genera and families that were weakly or not supported in the complete data set (i.e., showing bootstrap values <90%) sometimes became highly supported at lower taxon sampling depending on the set of species included in the simulation. This resulted in fluctuating bootstrap values between 0 and 100% (Figure 2, Table S2). Similar tendencies were observed on the family level (Figure 3). Seven families (Boidae, Iguanidae, Chamaeleonidae, Testudinidae, Pelomedusidae, Typhlopidae and Psammophiidae) were well supported irrespective of the depth of taxon sampling, while the other families investigated (i.e. Lamprophiidae, Scincidae, Gekkonidae and Gerrhosauridae) received increasing support with decreasing taxon sampling.
Values were obtained by neighbor-joining analyses including 100% (original data set), 75, 50, 25 and 10% (100 random subsets each) of the studied species, respectively. Support values for taxa recovered as non-monophyletic groups are not shown.
Values were obtained by neighbor-joining analyses including 100% (original data set), 75, 50, 25 and 10% (100 random subsets each) of the studied species, respectively. Support values for taxa recovered as non-monophyletic groups are not shown.
For the six species-rich genera known to be monophyletic, in 80% of the randomizations the monophyly was confirmed with high support values.
The effect of marker length – barcodes versus mini-barcodes
Neighbor-joining analyses based on shorter sequences (450, 300, 200, and 100 bp, respectively) showed that the number of well supported groups (with bootstrap values over 90%) decreased with shorter marker length (Figure 4), both on family- and genus-level. A few genera were found—mostly including a single or a couple of species only—which were highly supported in all subsets testing the effect of marker length. Also, none of the six species-rich monophyletic genera was supported significantly in the data set of mini-barcodes (100 bp). On the family level, even mini-barcodes of 100 bp length were sufficient to obtain highest support values in Chamaeleonidae, Pelomedusidae, and Psammophiidae, but low or no support was recovered for the other eight families. Results of distance-based comparisons showed that short marker sequences of 100 bp remained unique on species level, and, therefore, could be used for unambiguous identification of the samples.
Promoting DNA barcoding of reptiles
In this study we propose a newly designed degenerated primer pair. It works well with several lineages of squamates at a constantly high success rate in concert with easy-to-use protocols (standard PCR procedure with a single annealing temperature). The main goal of our study is to establish a DNA barcode database for Madagascan reptiles and to test the utility of these COI sequences for identifying species and assigning them to major units (corresponding to genera and families). We do not specifically aim to screen Madagascar's reptile fauna for cryptic species, yet our data suggest or confirm a substantial proportion of undescribed diversity in this group, with over 40 candidate species newly identified. Our barcoding approach works universally, without conspicuous differences in PCR amplification or identification success recognizable among the main evolutionary lineages of squamates. A total of ca. 15% of the samples are not reliably amplified with this new primer pair, suggesting that multiplexing with several primers or designing clade-specific primers will be necessary in applications that rely on absolute success rates in such old and diverse groups as reptiles.
The effect of sampling
The restricted amount of specimens per species included in our study permits only a limited assessment of intraspecific genetic variation. Hence, reliable comparisons of intraspecific versus interspecific diversity are difficult. In contrast, the high species coverage in our study is a suitable fundament to test the effect of missing taxa on the performance of DNA barcoding to correctly assign species to genera and other higher taxa, i.e., to provide a higher level taxonomic identification for sequences of unknown identity with no match in the database.
There is a long-standing debate on the effects of taxon (and character) sampling initiated in the 1990s, although focused to phylogenetic studies , .The overall agreement is that increased taxon sampling will typically result in higher phylogenetic accuracy (e.g. , – and many others). In particular, increased taxon sampling effects on reducing phylogenetic error (e.g. , , but other studies are contradictory ). The analysis of few taxa can be subject of strong biases, “which in turn produce high measures of repeatability (such as bootstrap proportions) in support of incorrect or misleading phylogenetic results” . Moreover, more complex evolutionary models are mainly beneficial for larger taxon sampling. To test sampling effects and estimate expected errors, simulations (i.e. randomly selected trees) are necessary .
In our simulations, we opted for the neighbor-joining method based on distances due to its simplicity and high computational speed. Furthermore, NJ based on K2p distances is a commonly used clustering method in many DNA barcoding studies , , and also recommended as a ‘minimum’ standard method . NJ yields results sufficiently similar to the results of likelihood- or parsimony-based phylogenetic analyses to be used as an approximation , especially with short DNA sequences where ML-based analyses may suffer from overparametrization.
Our simulations suggest two main trends: First, several taxonomic groups exist that always receive strong support irrespective of the depth of taxon sampling. These are mainly highly divergent evolutionary lineages. Second, we observe that the proportion of groups receiving high bootstrap support increases with decreasing taxon sampling. Apparently, the size of the unit does not determine the variation of support values in the different subsets. Anyway, some groups are not monophyletic in the most comprehensive (original) tree but become monophyletic in some simulations due to coincidental taxon sampling. This observation should be kept in mind for the evaluation of these gene-trees: high support values at low taxon sampling could potentially be misleading because they may not accurately reflect support for the entire group and are simply a consequence of missing data.
The effect of using mini-barcodes on the resolution of relationships is known . Our observations show that the number of supported taxa (in this case genera and families) are lower when using shorter sequences but on the other hand even 100 bp sequences are able to assign many samples correctly to genus and family.
COI-based clustering versus multigene phylogeny of Madagascan reptiles
DNA barcodes are usually not analyzed in a phylogenetic context. Especially at deeper divergences corresponding to higher taxonomic ranks, substitution saturation may become very substantial. Therefore, DNA barcodes may not be useful in phylogenetic reconstruction of higher taxa even with ‘maximal’ taxon sampling (e.g. Lepidoptera, ). Nevertheless, massively increased taxon sampling also increases phylogenetic signal in the data set , which can be exploited using other means. Besides this phylogenetic perspective, understanding whether sequences are correctly assigned to higher clades or not is also informative for barcoding because it indicates whether sequences of species not contained in the database will be correctly assigned to higher clades and taxa .
Although the primary goal of DNA barcoding is species identification and species discovery and not phylogenetic analysis, in many cases our results can be compared with multigene-based phylogenetic studies. Given that our barcoding data include numerous taxa that so far have remained phylogenetically unassessed, a number of tentative hypotheses can be drawn to be tested in future phylogenetic studies.
The COI tree supports the monophyly of many snake genera with maximum boostrap values in agreement with previous multigene phylogenies. The branching pattern of species within a given genus is remarkably to moderately congruent with that in the multilocus phylogenies of Compsophis , Liophidium , Liopholidophis , Thamnosophis , Madagascarophis , Sanzinia and Acrantophis , although a less complete sampling in several of the multigene trees does not allow exact comparisons. The polyphyly of the former snake genus Stenophis, only recently resolved by recognizing three monophyletic genera (Lycodryas, Parastenophis and Phisalixella; ) is also recovered, as is the polyphyly of the snake genus Liopholidophis sensu lato, splitted in the two monophyletic genera Liopholidophis and Thamnosophis . The genus Pseudoxyrhopus appears to be polyphyletic as well. The main group includes Heteroliodon fohy (suggesting that this species is perhaps just a miniaturized member of Pseudoxyrhopus, ), while at least two other species (P. heterurus and P. cf. imerinae) form two independent lineages. Unfortunately, no comprehensive multilocus phylogeny is available for this complex.
Regarding chameleons, the polyphyly of the genus Calumma is in agreement with a previous study . The genus Furcifer is recovered as monophyletic except for F. balteatus which is one of the most basal Furcifer species . The dwarf chameleons of the genus Brookesia appear as monophyletic without B. nasus which together with B. lolontany forms the most basal Brookesia clade . Among gerrhosaurids, Tracheloptychus is found to be nested within Zonosaurus, in agreement with a paraphyletic genus Zonosaurus .
The most taxonomically convoluted assemblage is that of the fossorial scincid lizards , . Our COI-based tree shows the genera Voeltzkowia, Pygomeles and Androngo nested within Amphiglossus, a result consistent with the published phylogeny , implying that taxonomic changes are required. In the gecko genus Paroedura, several sister group relationships  are correctly recovered by COI sequences. Intrageneric relationships are also largely correctly inferred among the day-geckos of the genus Phelsuma . For the leaf-tailed geckos (genus Uroplatus), we have a lower species coverage, and therefore a comparison with a phylogenetic study  is less informative. Our results on Madagascan iguanas – genera Oplurus and Chalarodon – confirm earlier findings .
Summarizing we conclude that our single-gene tree is remarkably informative in recovering shallow-level phylogenetic relationships (i.e. correct attribution to existing families, genera, and species groups in most cases). It also has the potential to point to possibly non-monophyletic species (e. g. Phelsuma madagascariensis sensu lato, P. lineata sensu lato) and genera (Amphiglossus, Brookesia, Calumma, Zonosaurus), which are so far not resolved by morphological data sets. However, in cases when results seem to be in conflict with current taxonomy, we suggest a taxonomic re-assessment to confirm or redefine species boundaries. This should be made by in-depth investigations using additional molecular markers and morphological traits.
Utility of DNA barcodes of Madagascan reptiles
Similar to Madagascan frogs , taxonomy of squamates is limping far behind the collection of specimens of candidate species by intensive field surveys. This study now allows for a further acceleration of the identification of candidate species, by comparing newly obtained sequences with our database of reliably vouchered and often topotypical sequences. DNA barcoding may thereby play an eminent role and provide an effective and cost-efficient tool to help understanding the diversity of reptiles of Madagascar, although the Linnean shortfall remains. In fact, a preliminary and often molecular-only definition of a candidate species still requires a time-consuming species delimitation analysis and subsequently a formal scientific description. For future surveys of biotic diversity in Madagascar and elsewhere, we strongly recommend the collection of tissue samples for molecular analysis of all collected specimens. Furthermore, we suggest to use DNA barcoding for a large-scale screening of genetic diversity especially in groups such as the Madagascan reptiles and amphibians where large reference sequence databases now exist (,  this study).
Two major reasons might have positively influenced our barcoding analyses. First, our comprehensive sampling includes more than 250 nominal species. Second, the long duration of faunal survey work in Madagascar is likely responsible for removing many taxonomic artefacts. Such artefacts can lead to strong and hardly reconcilable inconsistencies between barcoding data and non-molecular data and thereby strongly reduce the utility and resolution of DNA barcoding.
The use of DNA barcodes has significant applications for conservation. Numerous species of reptiles from Madagascar are highly priced in the pet trade and exported from Madagascar in large numbers , . Many of these species are listed in the appendices of the Convention on the International Trade of Endangered Species (CITES) and, thus, their commerce needs to be internationally monitored. At present, in Madagascar this applies to all chameleons, all tortoises and most turtles, all geckos of the genera Uroplatus and Phelsuma, Madagascan boas, and the Nile crocodile, a total of 140 species. Other species are subjected to export quotas from Madagascar or to recommendations to all CITES parties to suspend imports or to import bans in some countries (such as most species of chameleons in the European Union). Between 1985 and 2001, a total of 193,768 chameleons were legally exported from Madagascar and many instances of illegal trade have been recorded . A reliable identification of all life stages of Madagascan reptiles is therefore a high priority in order to set up a sustainable trade system. Identification is not trivial given the difficulties in diagnosing juvenile and female chameleons. For example, the high level of morphological similarity among juveniles often confounds the identification of species, and even genera of chameleons. Also, many species of Phelsuma and Uroplatus are very difficult to tell morphologically apart even as adults. Recent advances in obtaining reliable DNA sequences from oral or cloacal swabbing – allows almost non-invasive sampling of reptiles thereby accounting for animal welfare. The COI database provides barcodes for about 110 of the 140 Madagascan reptiles included in CITES, and thereby provides a solid basis for future controls of the trade via molecular identification methods.
Graph showing transitions and transversions plotted against K2p divergence.
Neighbor-joining tree based on COI sequences of Madagascan reptiles including specimen data.
Bayesian tree based on COI sequences of Madagascan reptiles.
Maximum likelihood tree based on COI sequences of Madagascan reptiles.
Data of specimens and samples used in the study.
Comparison of support values (bootstrap values, NJ analyses) for taxonomically relevant groups in the original data set and in simulations with subsampling.
We are indebted to a large number of friends, colleagues and students who have contributed to the sampling and accompanied us during field work over the years and of which we can only name some: Franco Andreone, Parfait Bora, Euan Edwards, Michael Franzen, Sebastian Gehring, Jörn Köhler, Maciej Pabijan, Jim and Carol Patton, Marta Puente, Louis du Preez, Liliane Raharivololoniaina, Emile Rajeriarison, Theo Rajoafiarison, Roger-Daniel Randrianiaina, Jasmin Randrianirina, Ignacio de la Riva, Axel Strauß, Meike Teschke, David R. Vieites, and Katharina C. Wollenberg. We are grateful to the staff of Madagascar National Parks, in particular to the local administration of Ranomafana and Analamazaotra-Mantadia National Parks, for continued support. MICET/ICTE provided important logistical support. We are grateful to the Malagasy authorities for research and export permits. This study was carried out under collaboration accords between the Technische Universität Braunschweig and the Département de Biologie Animale of the Université d'Antananarivo. This project ‘BarMar’ (Barcoding of Madagascan reptiles) was carried out by the Joint Experimental Molecular Unit.
Conceived and designed the experiments: ZTN MV. Performed the experiments: ZTN GS. Analyzed the data: ZTN GS FG MV. Contributed reagents/materials/analysis tools: ZTN GS FG MV. Wrote the paper: ZTN GS FG MV.
- 1. Stork NE (1988) Insect diversity: facts, fiction and speculation. Biol J Linn Soc 35: 321–337.
- 2. May RM (1990) How many species? Phil Trans R Soc B 330: 293–304.
- 3. Briggs JC (1994) Species diversity: Land and sea compared. Syst Biol 43: 130–135.
- 4. Mora C, Tittensor DP, Adl S, Simpson AGB, Worm B (2011) How many species are there on earth and in the ocean? PLoS Biol 9: e1001127.
- 5. Costello MJ, Wilson S, Houlding B (in press) Predicting total global species richness using rates of species description and estimates of taxonomic effort. Syst Biol.
- 6. Strutzenberger P, Brehm G, Fiedler K (2011) DNA barcoding-based species delimitation increases species count of Eois (Geometridae) moths in a well-studied tropical mountain forest by up to 50%. Insect Science 18: 349–362.
- 7. Lara A, Ponce de Leon JL, Rodriguez R, Casane D, Cote G, et al. (2010) DNA barcoding of Cuban freshwater fishes: evidence for cryptic species and taxonomic conflicts. Mol Ecol Res 10: 421–430.
- 8. Vieites DR, Wollenberg KC, Andreone F, Köhler J, Glaw F, et al. (2009) Vast underestimation of Madagascar's biodiversity evidenced by an integrative amphibian inventory. Proc Natl Acad Sci U S A 106: 8267–8272.
- 9. Crawford AJ, Lips KR, Bermingham E (2010) Epidemic disease decimates amphibian abundance, species diversity, and evolutionary history in the highlands of central Panama. Proc Natl Acad Sci U S A 107: 13777–13782.
- 10. Giam X, Scheffers BR, Sodhi NS, Wilcove DS, Ceballos G, et al. (2012) Reservoirs of richness: least disturbed tropical forests are centres of undescribed species diversity. Proc R Soc B 279: 67–76.
- 11. Chapman AD (2009) Numbers of living species in Australia and the world. Report for the Australian Biological Resources Study, Australian Biological Resources Study, Canberra.
- 12. ION (2011) Index of Organism Names. Available: http://www.organismnames.com/metrics.htm?page=graphs. Accessed 2011 Aug 25.
- 13. Carbayo F, Marques AC (2011) The costs of describing the entire animal kingdom. Trends Ecol Evol 26: 154–155.
- 14. Brown JH, Lomolino MV (1998) Biogeography. Sunderland, Massachusetts: Sinauer Associates. 691 p.
- 15. Hoagland KE (1996) The taxonomic impediment and the Convention of Biodiversity. Assoc Syst Collect Newsl 24: 61–62, 66–67.
- 16. Hebert PDN, Cywinska A, Ball SL, deWaard JR (2003) Biological identifications through DNA barcodes. Proc R Soc B 270: 313–321.
- 17. Hajibabaei M, Singer GAC, Hebert PDN, Hickey DA (2007) DNA barcoding: how it complements taxonomy, molecular phylogenetics and population genetics. Trends Genet 23: 167–172.
- 18. Ratnasingham S, Hebert PDN (2007) BOLD: The Barcode of Life Data System (www.barcodinglife.org). Mol Ecol Notes 7: 355–364.
- 19. Goldstein PZ, DeSalle R (2010) Integrating DNA barcode data and taxonomic practice: Determination, discovery, and description. Bioessays 33: 135–147.
- 20. Stackebrandt E, Goebel BM (1994) Taxonomic note: a place for DNA-DNA reassociation and 16 S rRNA sequence analysis in the present species definition in bacteriology. Int J Syst Bacteriol 44: 846–849.
- 21. Hebert PDN, Stoeckle MY, Zemlak TS, Francis CM (2004) Identification of birds through DNA barcodes. PLoS Biol 2: 1657–1663.
- 22. Kerr KCR, Stoeckle MY, Dove CJ, Weigt LA, Francis CM, et al. (2007) Comprehensive DNA barcode coverage of North American birds. Mol Ecol Notes 7: 535–543.
- 23. Ward RD, Zemlak TS, Innes BH, Last PR, Hebert PDN (2005) DNA barcoding Australia's fish species. Phil Trans R Soc B 360: 1847–1857.
- 24. Barrett RDH, Hebert PDN (2005) Identifying spiders through DNA barcodes. Can J Zool 83: 481–491.
- 25. Hajibabaei M, Janzen DH, Burns JM, Hallwachs W, Hebert PDN (2006) DNA barcodes distinguish species of tropical Lepidoptera. Proc Natl Acad Sci U S A 103: 968–971.
- 26. Elias M, Hill RI, Willmott KR, Dasmahapatra KK, Brower AVZ, et al. (2007) Limited performance of DNA barcoding in a diverse community of tropical butterflies. Proc R Soc B 274: 2881–2889.
- 27. Hausmann A, Haszprunar G, Hebert PDN (2011) DNA Barcoding the geometrid fauna of Bavaria (Lepidoptera): Successes, surprises, and questions. PLoS ONE 6: e17134.
- 28. Grant RA, Linse K (2009) Barcoding antarctic biodiversity; current status and the CAML initiative, a case study of marine invertebrates. Polar Biol 32: 1629–1637.
- 29. Park DS, Foottit R, Maw E, Hebert PDN (2011) Barcoding bugs: DNA-based identification of the true bugs (Insecta: Hemiptera: Heteroptera). PLoS ONE 6: e18749.
- 30. Smith MA, Fisher BL, Hebert PDN (2005) DNA barcoding for effective biodiversity assessment of a hyperdiverse arthropod group: the ants of Madagascar. Phil Trans R Soc B 360: 1825–1834.
- 31. Hebert PDN, Penton EH, Burns JM, Janzen DH, Hallwachs W (2004) Ten species in one: DNA barcoding reveals cryptic species in the neotropical skipper butterfly Astraptes fulgerator. Proc Natl Acad Sci U S A 101: 14812–14817.
- 32. Brower AVZ (2006) Problems with DNA barcodes for species delimitation: ‘ten species’ of Astraptes fulgerator reassessed (Lepidoptera: Hesperiidae). Syst Biodiv 4: 127–132.
- 33. Witt JDS, Threloff DL, Hebert PDN (2006) DNA barcoding reveals extraordinary cryptic diversity in an amphipod genus: implications for desert spring conservation. Mol Ecol 15: 3073–3082.
- 34. Havermans C, Nagy ZT, Sonet G, De Broyer C, Martin P (2011) DNA barcoding reveals new insights into the diversity of Antarctic species of Orchomene sensu lato (Crustacea: Amphipoda: Lysianassoidea). Deep Sea Res II 58: 230–241.
- 35. Ekrem T, Willassen E, Stur E (2007) A comprehensive DNA sequence library is essential for identification with DNA barcodes. Mol Phylogenet Evol 43: 530–542.
- 36. Ward RD, Hanner R, Hebert PDN (2009) The campaign to DNA barcode all fishes, FISH-BOL. J Fish Biol 74: 329–356.
- 37. Che J, Chen HM, Yang JX, Jin JQ, Jiang K, et al. (2012) Universal COI primers for DNA barcoding amphibians. Mol Ecol Resour. in press.
- 38. Vences M, Thomas M, van der Meijden A, Chiari Y, Vieites DR (2005) Comparative performance of the 16 S rRNA gene in DNA barcoding of amphibians. Frontiers Zool 2: 5.
- 39. Smith MA, Poyarkov NA Jr, Hebert PDN (2008) CO1 DNA barcoding amphibians: take the chance, meet the challenge. Mol Ecol Res 8: 235–246.
- 40. Vences M, Nagy ZT, Sonet G, Verheyen E (in press) DNA barcoding of amphibians and reptiles. In: Kress WJ, Erickson DL, editors. DNA barcodes: Methods and protocols. Berlin: Humana Press, Springer Science+Publishing Media.
- 41. Myers N, Mittermeier RA, Mittermeier CG, da Fonseca GAB, Kent J (2000) Biodiversity hotspots for conservation priorities. Nature 403: 853–858.
- 42. Vences M, Wollenberg KC, Vieites DR, Lees DC (2009) Madagascar as a model region of species diversification. Trends Ecol Evol 24: 456–465.
- 43. Yoder AD, Nowak MD (2006) Has vicariance or dispersal been the predominant biogeographic force in Madagascar? Only time will tell. Ann Rev Ecol Evol Syst 37: 405–431.
- 44. Glaw F, Vences M (2007) A field guide to the amphibians and reptiles of Madagascar. 3rd edition. Cologne: Vences and Glaw Publishers. 495 p.
- 45. Vences M (2004) Origin of Madagascar's extant fauna: a perspective from amphibians, reptiles and other non-flying vertebrates. Ital J Zool Suppl 2: 217–228.
- 46. Folmer O, Black M, Hoeh W, Lutz R, Vrijenhoek R (1994) DNA primers for amplification of mitochondrial cytochrome c oxidase subunit I from diverse metazoan invertebrates. Mol Mar Biol Biotech 3: 294–299.
- 47. Xia X, Xie Z, Salemi M, Chen L, Wang Y (2003) An index of substitution saturation and its application. Mol Phylogenet Evol 26: 1–7.
- 48. Xia X, Lemey P (2009) Assessing substitution saturation with DAMBE. In: Lemey P, Salemi M, Vandamme AM, editors. The Phylogenetic handbook: A practical approach to DNA and protein phylogeny, 2nd edition. Cambridge University Press. pp. 615–630.
- 49. Xia X, Xie Z (2001) DAMBE: Data analysis in molecular biology and evolution. J Hered 92: 371–373.
- 50. Tamura K, Peterson D, Peterson N, Stecher G, Nei M, et al. (2011) MEGA5: Molecular Evolutionary Genetics Analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods. Mol Biol Evol 28: 2731–2739.
- 51. Ronquist F, Huelsenbeck JP (2003) MrBayes 3: Bayesian phylogenetic inference under mixed models. Bioinformatics 19: 1572–1574.
- 52. Posada D (2008) jModelTest: Phylogenetic model averaging. Mol Biol Evol 25: 1253–1256.
- 53. Rambaut A, Drummond AJ (2009) Tracer v1.5. Available: http://beast.bio.ed.ac.uk/Tracer. Accessed 2012 Jan 26.
- 54. Deng W, Maust BS, Nickle DC, Learn GH, Liu Y, et al. (2010) DIVEIN: a web server to analyze phylogenies, sequence divergence, diversity, and informative sites. BioTechniques 48: 405–408.
- 55. Guindon S, Dufayard JF, Lefort V, Anisimova M, Hordijk W, et al. (2010) New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0. Syst Biol 59: 307–321.
- 56. Meusnier I, Singer GAC, Landry JF, Hickey DA, Hebert PDN, et al. (2008) A universal DNA mini-barcode for biodiversity analysis. BMC Genomics 9: 214.
- 57. Virgilio M, Backeljau T, Nevado B, De Meyer M (2010) Comparative performances of DNA barcoding across insect orders. BMC Bioinformatics 11: e206.
- 58. Hillis DM (1996) Inferring complex phylogenies. Nature 383: 130–131.
- 59. Kim J (1996) General inconsistency conditions for maximum parsimony: Effects of branch lengths and increasing numbers of taxa. Syst Biol 45: 363–374.
- 60. Graybeal A (1998) Is it better to add taxa or characters to a difficult phylogenetic problem? Syst Biol 47: 9–17.
- 61. Hillis DM (1998) Taxonomic sampling, phylogenetic accuracy, and investigator bias. Syst Biol 47: 3–8.
- 62. Rannala B, Huelsenbeck JP, Yang Z, Nielsen R (1998) Taxon sampling and the accuracy of large phylogenies. Syst Biol 47: 702–710.
- 63. Pollock DD, Zwickl DJ, McGuire JA, Hillis DM (2002) Increased taxon sampling is advantageous for phylogenetic inference. Syst Biol 51: 664–671.
- 64. Zwickl DJ, Hillis DM (2002) Increased taxon sampling greatly reduces phylogenetic error. Syst Biol 51: 588–598.
- 65. Hillis DM, Pollock DD, McGuire JA, Zwickl DJ (2003) Is sparse taxon sampling a problem for phylogenetic inference? Syst Biol 52: 124–126.
- 66. Rosenberg MS, Kumar S (2001) Incomplete taxon sampling is not a problem for phylogenetic inference. Proc Natl Acad Sci U S A 98: 10751–10756.
- 67. Heath TA, 1 Zwickl DJ, Kim J, Hillis DM (2008) Taxon sampling affects inferences of macroevolutionary processes from phylogenetic trees. Syst Biol 57: 160–166.
- 68. St John K, Warnow T, Moret B, Vawter L (2003) Performance study of phylogenetic methods: (unweighted) quartet methods and neighbor-joining. J Algorithms 48: 173–193.
- 69. Roch S (2010) Toward extracting all phylogenetic information from matrices of evolutionary distances. Science 327: 1376–1379.
- 70. Wilson JJ (2011) Assessing the value of DNA barcodes for molecular phylogenetics: Effect of increased taxon sampling in Lepidoptera. PLoS ONE 6: e24769.
- 71. Glaw F, Nagy ZT, Vences M (2007) Phylogenetic relationships and classification of the Malagasy pseudoxyrhophiine snake genera Geodipsas and Compsophis based on morphological and molecular data. Zootaxa 1517: 53–62.
- 72. Vieites DR, Ratsoavina FM, Randrianiaina RD, Nagy ZT, Glaw F, et al. (2010) A rhapsody of colours from Madagascar: discovery of a remarkable new snake of the genus Liophidium and its phylogenetic relationships. Salamandra 46: 1–10.
- 73. Glaw F, Nagy ZT, Franzen M, Vences M (2007) Molecular phylogeny and systematics of the pseudoxyrhophiine snake genus Liopholidophis (Reptilia, Colubridae): evolution of its exceptional sexual dimorphism and descriptions of new taxa. Zool Scripta 36: 291–300.
- 74. Glaw F, Nagy ZT, Köhler J, Franzen M, Vences M (2009) Phylogenetic relationships of a new species of pseudoxyrhophiine snake (Reptilia: Lamprophiidae: Thamnosophis) suggest a biogeographical link between western and northern Madagascar. Org Divers Evol 9: 13–22.
- 75. Nagy ZT, Glaw F, Andreone F, Wink M, Vences M (2007) Species boundaries in Malagasy snakes of the genus Madagascarophis (Serpentes: Colubridae sensu lato) assessed by nuclear and mitochondrial markers. Org Divers Evol 7: 241–251.
- 76. Orozco-terWengel P, Nagy ZT, Vieites DR, Vences M, Louis E Jr (2008) Phylogeography and phylogenetic relationships of Malagasy tree and ground boas. Biol J Linn Soc 95: 640–652.
- 77. Nagy ZT, Glaw F, Vences M (2010) Systematics of the snake genera Stenophis and Lycodryas from Madagascar and the Comoros. Zool Scripta 39: 426–435.
- 78. Nagy ZT, Joger U, Wink M, Glaw F, Vences M (2003) Multiple colonization of Madagascar and Socotra by colubrid snakes: evidence from nuclear and mitochondrial gene phylogenies. Proc R Soc B 270: 2613–2621.
- 79. Townsend TM, Tolley KA, Glaw F, Böhme W, Vences M (2011) Eastward from Africa: palaeocurrent-mediated chameleon dispersal to the Seychelles islands. Biol Letters 7: 225–228.
- 80. Townsend TM, Vieites DR, Glaw F, Vences M (2009) Testing species-level diversification hypotheses in Madagascar: the case of microendemic Brookesia leaf chameleons. Syst Biol 58: 641–656.
- 81. Raselimanana AP, Noonan B, Karanth KP, Gauthier J, Yoder AD (2009) Phylogeny and evolution of Malagasy plated lizards. Mol Phylogenet Evol 50: 336–344.
- 82. Crottini A, Dordel J, Köhler J, Glaw F, Schmitz A, et al. (2009) A multilocus phylogeny of Malagasy scincid lizards elucidates the relationships of the fossorial genera Androngo and Cryptoscincus. Mol Phylogenet Evol 53: 345–350.
- 83. Köhler J, Vences M, Erbacher M, Glaw F (2010) Systematics of limbless scincid lizards from northern Madagascar: morphology, phylogenetic relationships and implications for classification (Squamata: Scincidae). Org Divers Evol 10: 147–159.
- 84. Jackman TR, Bauer AM, Greenbaum E, Glaw F, Vences M (2008) Molecular phylogenetic relationships among species of the Malagasy-Comoran gecko genus Paroedura (Squamata: Gekkonidae). Mol Phylogenet Evol 46: 74–81.
- 85. Rocha S, Vences M, Glaw F, Posada D, Harris DJ (2009) Multigene phylogeny of Malagasy day geckos of the genus Phelsuma. Mol Phylogenet Evol 52: 530–537.
- 86. Greenbaum E, Bauer AM, Jackman TR, Vences M, Glaw F (2007) A phylogeny of the enigmatic Madagascan geckos of the genus Uroplatus (Squamata: Gekkonidae). Zootaxa 1493: 41–51.
- 87. Münchenberg T, Wollenberg KC, Glaw F, Vences M (2008) Molecular phylogeny and geographic variation of Malagasy iguanas (Oplurus and Chalarodon). Amphibia-Reptilia 29: 319–327.
- 88. Wollenberg KC, Vieites DR, Glaw F, Vences M (2011) Speciation in little: the role of range and body size in the diversification of Malagasy mantellid frogs. BMC Evol Biol 11: 217.
- 89. Carpenter AI, Robson O, Rowcliffe JM, Watkinson AR (2005) The impacts of international and national governance changes on a traded resource: a case study of Madagascar and its chameleon trade. Biol Cons 123: 279–287.
- 90. Todd M (2011) Trade in Malagasy reptiles and amphibians in Thailand. 30 p. TRAFFIC Southeast Asia, Petaling Jaya, Selangor, Malaysia.
- 91. Miller HC (2006) Cloacal and buccal swabs are a reliable source of DNA for microsatellite genotyping of reptiles. Cons Genet 7: 1001–1003.
- 92. Beebee TJC (2008) Buccal swabbing as a source of DNA from squamate reptiles. Cons Genet 9: 1087–1088.
- 93. Schulte U, Gebhard F, Heinz L, Veith M, Hochkirch A (2011) Buccal swabs as a reliable non-invasive tissue sampling method for DNA analysis in the lacertid lizard Podarcis muralis. North-West J Zool 7: 325–328.