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DASMAHAPATRA ET AL. Mechanitis barcoding 1 Title: Mitochondrial DNA barcoding detects “species” that are not real Kanchon K. Dasmahapatra 1 [email protected] Marianne Elias 2 [email protected] Ryan I Hill 3 [email protected] Joseph I Hoffman 4 [email protected] James Mallet 1,5 [email protected] 1 Department of Genetics, Evolution and Environment, University College London, 4 Stephenson Way, London NW1 2HE, U.K. 2 Institute of Evolutionary Biology, University of Edinburgh, West Mains Road, Edinburgh EH9 3JT, U.K. 3 Department of Integrative Biology, University of California, Berkeley, CA 94720, U.S.A. 4 Department of Zoology, University of Cambridge, Downing Street, Cambridge CB2 3EJ, U.K. 5 Wissenschaftskolleg zu Berlin, Wallotstraße 19, 14193 Berlin, Germany Author for correspondence: Kanchon K. Dasmahapatra Tel: +44 (0)207 6795100 Fax: +44 (0)207 6795052

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DASMAHAPATRA ET AL. Mechanitis barcoding

1

Title: Mitochondrial DNA barcoding detects “species” that are not real

Kanchon K. Dasmahapatra 1

[email protected]

Marianne Elias 2

[email protected]

Ryan I Hill 3

[email protected]

Joseph I Hoffman 4

[email protected]

James Mallet 1,5

[email protected]

1

Department of Genetics, Evolution and Environment, University College London, 4

Stephenson Way, London NW1 2HE, U.K.

2

Institute of Evolutionary Biology, University of Edinburgh, West Mains Road, Edinburgh

EH9 3JT, U.K.

3

Department of Integrative Biology, University of California, Berkeley, CA 94720, U.S.A.

4

Department of Zoology, University of Cambridge, Downing Street, Cambridge CB2 3EJ,

U.K.

5

Wissenschaftskolleg zu Berlin, Wallotstraße 19, 14193 Berlin, Germany

Author for correspondence: Kanchon K. Dasmahapatra

Tel: +44 (0)207 6795100

Fax: +44 (0)207 6795052

DASMAHAPATRA ET AL. Mechanitis barcoding

2

SUMMARY

Mimicry and extensive geographic subspecies polymorphism combine to make species in the

ithomiine butterfly genus Mechanitis (Lepidoptera; Nymphalidae) difficult to determine. We

use mitochondrial (mtDNA) barcoding, nuclear sequences and amplified fragment length

polymorphism (AFLP) genotyping to investigate species limits in this genus. Although earlier

biosystematics studies based on morphology described only four species, mitochondrial

barcoding revealed eight well-differentiated haplogroups, indicating the presence of four new

putative “cryptic species”. However, using AFLP markers we find support for only one of the

four putative new “cryptic species” as biologically meaningful. We demonstrate that in this

genus deep genetic divisions expected on the basis of mtDNA are not always reflected in the

nuclear genome, and advocate the use of AFLP markers as a check when mtDNA barcoding

gives unexpected results.

Keywords: DNA barcoding, AFLP, Mechanitis, cryptic species, ithomiine

DASMAHAPATRA ET AL. Mechanitis barcoding

3

1. INTRODUCTION

DNA barcoding has recently been suggested as a quick method useful for rapid species

discovery and biodiversity assessment (Borisenko et al. 2008; Hajibabaei et al. 2006; Stoeckle

& Hebert 2008). For animal taxa the majority of these studies have used a short section of

mitochondrial DNA (mtDNA), namely the first ~650 bp of the 5’ end of the cytochrome

oxidase I gene (CoI) (Elias-Gutierrez et al. 2008; Hebert et al. 2003; Rock et al. 2008). DNA

barcoding has been argued to revolutionise taxonomy allowing rapid species identification

without need for detailed taxonomic expertise with increasing economy (Hajibabaei et al.

2007; Stoeckle & Hebert 2008). But the practice of mtDNA barcoding has received much

criticism on methodological (Will & Rubinoff 2004), theoretical (Hickerson et al. 2006) and

empirical grounds (Elias et al. 2007; Hurst & Jiggins 2005; Meyer & Paulay 2005; Wiemers

& Fiedler 2007). Despite the problems, undoubted successes for mtDNA barcoding have been

the discovery of cryptic species overlooked by more traditional taxonomic methods (Burns et

al. 2008; Smith et al. 2006).

Several studies have sought to overcome some of the problems inherent in mtDNA taxonomy

by supplementing mtDNA sequences with nuclear sequences (Elias et al. 2007; Monaghan et

al. 2005). However, the use of nuclear sequences for DNA taxonomy has been limited, largely

due to the difficulty in finding and sequencing fast-evolving nuclear loci (Dasmahapatra &

Mallet 2006). A possible alternative to nuclear sequence data is analysis based on amplified

fragment length polymorphisms (AFLPs), which are typically fast-evolving anonymous

nuclear markers, readily amplifiable in any organism (Mueller & Wolfenbarger 1999; Vos et

al. 1995). In this paper we first use mtDNA sequences to test species affiliations in the

difficult ithomiine butterfly genus Mechanitis (Lepidoptera; Nymphalidae), and then further

investigate these results utilising both nuclear gene sequences and AFLP markers.

DASMAHAPATRA ET AL. Mechanitis barcoding

4

Four Mechanitis species have been described and all are both abundant locally and widely

distributed in the neotropics (Brown 1977). Like most other ithomiines, all of the Mechanitis

species show multiple geographic subspecies variation and typically have orange, brown,

yellow and black wing colouration (Brown 1979; Lamas 2004). The many geographic forms

of Mechanitis, involved in Müllerian mimicry with various members of the ~360 species of

Ithomiinae as well as Heliconius species, had led to an extremely problematic species-level

taxonomy. However, careful biosystematic studies in the 1970s gave rise to a reasonably

stable classification, based on morphology, distribution, hybrid zones, and ecology (Brown

1977), that is still generally accepted (Lamas 2004). Here, we investigate the four putative

species comprising this genus.

2. MATERIAL AND METHODS

All four species of Mechanitis were used in this study: M. mazaeus (M. m. deceptus, M. m. cf.

phasianita, M. m. messenoides, M. m. pannifera, M. m. mazaeus), M. polymnia (M. p.

proceriformis, M. p. casabranca, M. p. bolivarensis, M. p. eurydice), M. lysimnia (M. l.

roqueensis, M. l. nesaea, M. l. solaria) and M. menapis (M. m. mantineus). Our samples

reflect the wide distribution of the first three species: specimens were collected from north

and central Peru (eastern San Martin and southern Loreto), Ecuador, northern Venezuela and

the Atlantic coast of Brazil (Table 1). M. menapis has a narrower distribution, replacing M.

mazaeus west of the Andes (Brown 1979) and in Central America; our M. menapis specimens

were obtained from western Ecuador. We sampled 121 specimens, mainly from Ecuador and

Peru, together with five from each of Venezuela and eastern Brazil for comparison (Table 1).

Details of sampling locations are provided in the Supplementary Materials (Table S1).

DASMAHAPATRA ET AL. Mechanitis barcoding

5

DNA was extracted from legs and thoraces using QIAamp DNA Micro and DNeasy Blood

and Tissue Kits (QIAGEN). Approximately 640 bp of mtDNA comprising the 5’-end of CoI,

the “barcoding region”, was amplified and sequenced in all specimens. To examine the effect

of using more mtDNA sequence, a further ~1500 bp, comprising the remaining 3’ portion of

CoI, the tR�A-leu gene, and the 5’ end of CoII, was also sequenced from 71 specimens

representing all four species. To examine whether the patterns revealed by mtDNA were

reflected in the nuclear genome, sequences were also obtained from three nuclear loci: Tektin

(58 sequences), Rpl5 (68 sequences) and Tpi (73 sequences) (Mallarino et al. 2005; Whinnett

et al. 2005a). For Rpl5 and Tpi these sequences included representatives of all four species,

but for Tektin no sequences were obtained for M. menapis. PCR primers and reaction

conditions have been reported previously (Dasmahapatra et al. 2007; Elias et al. 2007;

Whinnett et al. 2005a); a detailed description is also provided in Table S2. Cycle sequencing

was carried out using the Big Dye Terminator 3.1 Cycle Sequencing Kit (Applied

Biosystems). All sequences obtained for this study have been deposited in Genbank (awaiting

Accession numbers XXXXXX-XXXXXX, EU068843-EU068856, EU068966, EU068993-

EU068900, EU069070-EU069075).

Genetic divisions revealed by mitochondrial CoI may sometimes not be captured at autosomal

nuclear loci. This could be due to lack of coalescence within species given the ~4× effective

population size (�E) of autosomal loci compared to cytoplasmic mtDNA, and also because

exons typically sequenced readily across genera tend to evolve at slower rates than CoI. The

Rpl5 and Tpi loci we have used both contain fast-evolving intronic regions. In addition, Tpi is

a sex-linked locus having only ~3× �E compared to mitochondrial loci. To obtain even higher

resolution nuclear data, we genotyped 84 specimens representing all four species and all eight

DASMAHAPATRA ET AL. Mechanitis barcoding

6

mtDNA haplogroups (Figure 1a) using AFLP markers. The samples were genotyped using

four AFLP primer combinations: TaqI-CGA + EcoRI-ACA; TaqI-CAG + EcoRI-AGC; TaqI-

CAG + EcoRI-ATG; TaqI-CCA + EcoRI-ACA. AFLP primers and protocols used are

described in Madden et al. (2004). AFLP profiles were visualised by autoradiography.

Samples with aberrant AFLP profiles were discarded (Bonin et al. 2004), and to ensure

reliability, the remaining AFLP genotypes were scored by eye; 108 putative loci were

polymorphic and could be scored reliably.

Neighbour-joining (NJ) trees for each of the four sequenced loci were constructed using

MEGA 4 (Tamura et al. 2007). The optimal number of genotypic clusters indicated by the

AFLP genotypes was established with the Bayesian programme STRUCTURE 2.2 (Pritchard

et al. 2000), using standardized inference criteria (Evanno et al. 2005). Following a 100,000

step burn-in period, data were collected over 100,000 MCMC repetitions. STRUCTURE

analysis was carried out on the dataset increasing K from 1 to 10. At each value of K the

analysis was carried out three times to check between-run consistency.

3. RESULTS

Topologies of the mtDNA NJ trees based on the 636bp CoI “barcoding” region and the full

2000bp are similar and show the same major mtDNA haplogroups. In Figure 1a we show the

former, since sequences come from a larger number of specimens. The tree shows eight major

clusters or mtDNA haplogroups: three each within M. mazaeus (mt-haplogroups A, F and H)

and M. polymnia (mt-haplogroups B, C and D), and one each corresponding to M. menapis

(mt-haplogroup G) and M. lysimnia (mt-haplogroup E). Not included in these groups are the

two specimens of M. lysimnia solaria from Venezuela that appear sister to the M. mazaeus

DASMAHAPATRA ET AL. Mechanitis barcoding

7

mt-haplogroup H, rather than lying within main M. lysimnia clade; this exception is described

further in the Discussion. The raw average pairwise distance between mt-haplogroups is

2.7%, the largest being among M. mazaeus mt-haplogroups (≥ 3.5%) and the smallest

between M. polymnia mt-haplogroups C and D (1.6%), with all other distances ≥ 2.0%. The

average intra-haplogroup variation is, in contrast, only 0.3%. Pairwise mtDNA distances

between the eight main haplogroups are shown in Table S3.

Hardly any genetic variation was present among Tektin sequences. The only clear pattern

observable is the single shared Tektin haplotype in M. lysimnia and M. polymnia, suggesting a

sister relationship (Figure 1b). In contrast, high levels of polymorphism are present at both

Tpi and Rpl5 (Figures 1c, 1d). Neither gene shows distinctions among M. polymnia mt-

haplogroups B, C and D. In the Rpl5 genealogy, there is some support for separate evolution

of M. mazaeus mt-haplogroups H from A and F, although mt-haplogroup H appears

paraphyletic. Similarly, a monophyletic M. mazaeus clade consisting of mt-haplogroups A

and F, which is distinct from M. mazaeus mt-haplogroup H, is also supported in the Tpi

genealogy, as is a separate clade corresponding to M. menapis. Overall, the nuclear gene

genealogies suggest widespread paraphyly of recognized species and mt-haplogroups.

Between-run consistency was high in the STRUCTURE analysis of AFLP genotypes:

replicate runs at each K value yielded virtually identical likelihoods. Figure 2a shows the

average likelihood from these replicates. The optimal number of groups was four (Figures 2a,

2b): two within M. mazaeus, and one each matching M. lysimnia and M. polymnia. Of the two

M. mazaeus AFLP clusters, one corresponds exactly to mt-haplogroup H (M. mazaeus

mazaeus); while the other mazaeus cluster is a mixture of mt-haplogroups A and F (M.

mazaeus deceptus, M. mazaeus cf. phasianita, and M. mazaeus messenoides), with no

DASMAHAPATRA ET AL. Mechanitis barcoding

8

evidence of subdivision between them. The M. lysimnia and M. polymnia AFLP clusters

correspond perfectly with morphology-based species designations except that one M. lysimnia

specimen shows genotypic evidence of being a hybrid between the two; and there is no

evidence for subdivision of M. polymnia along mt-haplogroup lines. There is no single AFLP

genotypic cluster associated with M. menapis; instead it appears to share genotypes largely

with M. mazaeus mt-haplogroups A + F, and to a lesser extent with M. mazaeus mt-

haplogroup H and M. lysimnia. Increasing the number of clusters to eight, the total number of

mt-haplogroups, did not alter the pattern and Figure 2b (K = 4) is virtually identical to Figure

2c (K = 8) with the four additional clusters making negligible contributions. This is further

evidence for the lack of nuclear divisions corresponding to mt-haplogroups within M.

polymnia and M. mazaeus (mt-haplogroups A and F).

4. DISCUSSION

Mitochondrial DNA barcoding of the four species in the genus Mechanitis revealed deep

genetic divisions corresponding to eight mt-haplogroups (Figure 1a). One mt-haplogroup each

corresponded to M. lysimnia and M. menapis. However three mt-haplogroups were present

within each of M. mazaeus and M. polymnia suggesting the existence of four new putative

cryptic species in addition to the four species already recognized in morphological and

biosystematic work. In contrast, while our nuclear sequence data give little resolution, our

AFLP data strongly indicate the existence of only four genetic clusters: two within M.

mazaeus and one each corresponding to M. lysimnia and M. polymnia (Figure 2b). Thus, we

obtain disparate results using mitochondrial and nuclear markers.

DASMAHAPATRA ET AL. Mechanitis barcoding

9

Mitochondrial DNA barcoding relies on intraspecific genetic variation being much less than

interspecific genetic variation. When this condition is met, a “barcoding gap” may exist

(Meyer & Paulay 2005), and clusters corresponding to genetically more homogenous entities

can be discerned. Based on such cases, some proponents of mtDNA barcoding have

advocated the use of a threshold of sequence divergence above which genetic clusters may be

considered species (Hebert et al. 2004b). Subsequent careful studies have demonstrated the

lack of a barcoding gap in a number of taxa when sampling of species, populations, and

individuals within the study group is thorough (Elias et al. 2007; Meyer & Paulay 2005;

Wiemers & Fiedler 2007). In the case of Mechanitis, we have sampled all four described

species in the genus. While we have not included all of the many geographic subspecies of

these species, we have used specimens collected across a wide geographic area representing

opposite ends of the species’ geographic distribution in S. America. With our current

sampling, mitochondrial data show eight major genetic clusters or haplogroups, clearly

separated from one another by a large average genetic distance of 2.7 %. We found no overlap

between intra- and inter-cluster genetic variation.

Only four of the eight mtDNA divisions are reflected in the nuclear genome. Evidence from

nuclear sequence information is weak, very likely a result of incomplete lineage sorting due to

recency of origin coupled with large effective population sizes within these very widespread

and common species. However, even multilocus AFLP genotyping fails to detect groups

corresponding to three of the four novel mt-haplogroups. The M. menapis samples do not

form their own AFLP genotypic cluster, instead appearing to share most alleles with the two

allopatric M. mazaeus clusters, and as such these samples are associated with a particular

genetic pattern (Figure 2b). However, no such patterns are associated with any of the three M.

polymnia mt-haplogroups or the M. mazaeus mt-haplogroups A and F.

DASMAHAPATRA ET AL. Mechanitis barcoding

10

Two possibilities might explain the mismatch between mt-haplogroups and AFLP genotypic

clusters. First, that some of the mt-haplogroups are not “real species,” which we take to mean

taxa that can maintain multilocus genetic, ecological, behavioural, and/or morphological

differences in sympatry. Second, the AFLP markers may not be sensitive enough to detect

small differences between real but closely related species detected by mtDNA barcoding.

Several lines of evidence strongly indicate that the former is more likely. Detailed

examination of the wing patterns of the specimens in the three M. polymnia mt-haplogroups

as well as M. mazaeus mt-haplogroups A and F failed to reveal any correlation between wing

patterning and mt-haplogroup. In contrast, every AFLP genetic cluster detected by

STRUCTURE is correlated with wing phenotype (discussed below). This suggests that while

the AFLP clusters are biologically relevant, some of the mitochondrial divisions are not.

AFLP markers provide a nuclear, multilocus, genome-wide picture of genetic divergence and

as they sample non-coding variation, they have relatively rapid rates of evolution. This

sensitivity is routinely exploited to reveal population genetic patterns within single species

(Baus et al. 2005; Chaput-Bardy et al. 2008; Takami et al. 2004). The sensitivity of AFLP

markers for detecting small genetic differences relative to mtDNA is also demonstrated by

results from a parallel study on butterfly species within the ithomiine genus Melinaea. In this

genus there are at least six clearly distinguishable morphological species (Melinaea satevis,

M. menophilus, M. marsaeus, M. idae, M. mneme, M. isocomma) which cannot be detected

using mtDNA barcoding (Elias et al. 2007; Whinnett et al. 2005b), Dasmahapatra et al. in

prep.). Yet where mtDNA barcoding failed to detect distinct groups, the same AFLP primer

combinations used in this paper were able to confirm morphology-based species divisions

(Dasmahapatra et al. in prep.). In contrast to the genome-wide picture obtained from AFLP

markers, mtDNA reflects evolution only of the maternally inherited mitochondrial genome,

DASMAHAPATRA ET AL. Mechanitis barcoding

11

which can be affected by factors such as interspecific hybridisation, and selection, such as via

maternally transmitted endosymbionts like Wolbachia (Hurst & Jiggins 2005). As such,

genome-wide genetic clustering revealed by AFLP markers is likely to be more generally

useful for discovery of “real species” than mtDNA barcoding.

Previous detailed morphological and biosystematic work (Brown 1977; Lamas 2004)

recognised four species within Mechanitis (M. lysimnia, M. polymnia, M. mazaeus and M.

menapis) each with multiple geographic subspecies. The nuclear data reported here strongly

support monophyletic M. lysimnia and M. polymnia clades. However, paraphyly of M.

lysimnia is suggested by two mtDNA sequences of Venezuelan M. lysimnia solaria (Figure

1a). Unfortunately, it was not possible to genotype these specimens using AFLPs as the DNA

came from old dried specimens and was degraded. This split within M. lysimnia may be

correlated with chromosome numbers (Brown et al. 2004), and a group of M. lysimnia

subspecies including M. l. solaria might represent a separate species from M. lysimnia sensu

stricto. Future investigation of phylogenetic relationships within Mechanitis should focus on

this apparent division within M. lysimnia.

M. mazaeus is also paraphyletic, and two genotypic clusters are supported by nuclear data,

one comprising mt-haplogroup H and the other combining mt-haplogroups A and F. M.

mazaeus mt-haplogroups A and F corresponds to melanic forms currently considered to

represent subspecies Mechanitis mazaeus messenoides (Colombia south to Ecuador) and

deceptus (Ecuador southwards), both of which are generally found at mid elevations on the

eastern slopes of the Andes. They are mimetic of melanic sympatric subspecies and races of

Melinaea marsaeus, Melinaea isocomma, Heliconius numata, and other species (Brown 1977;

Brown 1979). Although there is some evidence for intermediate colour patterns (Brown 1977

DASMAHAPATRA ET AL. Mechanitis barcoding

12

and Table 1), most specimens in M. mazaeus mt-haplogroup H correspond to paler lowland

M. mazaeus (sensu stricto) involved in mimicking the generalized lowland ithomiine and

heliconiine tiger patterns. We conclude that these “mazaeus” forms are best considered full

species, as their distributions overlap extensively in the Eastern foothills of the Andes (Brown

1977) with little evidence of hybridization from AFLP loci. Therefore, M. mazaeus mt-

haplogroups A and F should probably now regain species level designation as M. messenoides

(including M. messenoides messenoides C. & R. Felder 1865, M. messenoides cf. phasianita

and M. messenoides deceptus Butler 1873). The nuclear evidence points to the fourth species,

M. menapis, being a trans-Andean form close to M. mazaeus and M. messenoides, since it

shares genotypes with both cis-Andean M. mazaeus forms described above. M. menapis is not

sympatric with M. mazaeus, and instead replaces it west of the Andes and in Central America.

Morphologically based biosystematic work (Brown 1977) has shown itself to be more useful

in this genus than mtDNA barcoding. Brown (1977) and Lamas (2004) accepted four species

on the basis of morphology, a result largely upheld by our multilocus nuclear analysis. The

only major discrepancy is that intermediate colour patterns in Ecuador (Table 1) apparently

indicating hybridization between upland M. mazaeus deceptus/messenoides, and lowland

mazaeus (sensu stricto) led Brown (1977) to lump the highland melanic forms incorrectly as

subspecies of mazaeus. In comparison, mtDNA barcoding reveals eight clear monophyletic

mt-haplogroups within Mechanitis, three of which are not detected in our nuclear analysis,

suggesting that they do not correspond to “real species.” Mitochondrial DNA barcoding

provides a very sensitive technique to find new taxa, but a downside is that such taxa may

have no basis in biological reality.

DASMAHAPATRA ET AL. Mechanitis barcoding

13

Focussing on the butterfly genus Mechanitis we have used nuclear sequences and sensitive

AFLP genotyping to demonstrate how deep genetic divisions in mtDNA are not always

reflected by corresponding divisions in the nuclear genome. Such “cryptic species” clusters

may instead represent locally divergent populations that have undergone a bottleneck, rather

than having speciated in the sense of producing divergent populations that can coexist.

Putative cryptic species detected by mtDNA barcoding merit closer investigation via analysis

of nuclear genetic data, or more in-depth examination of ecology and taxonomy e.g. (Hebert

et al. 2004a; Smith et al. 2006). Owing to their ease of amplification across taxa, sensitivity to

small genetic differences and genome-wide coverage, we advocate the use of AFLP markers

in cases where mtDNA barcoding reveals unexpected results, such as a failure to recover

known taxonomic divisions or the presence of additional “cryptic” taxa. Traditional mtDNA

sequencing was always a useful way of investigating possible cryptic biological groupings

long before “DNA barcoding” was first promoted (Hebert et al. 2003). The simple argument

that mtDNA barcoding may be used in accurate species discovery, or even in identification of

known species, ignores the crucial differences between mtDNA and supermarket barcodes. In

a supermarket, each product type has a unique barcode, shared by all other examples of that

type. In organisms, there is no such unique barcode, and a one-to-one correspondence

between mtDNA sequence and species does not exist.

Acknowledgements

We are grateful to Gerardo Lamas of the Museo de Historia Natural, UNMSM, Lima, Peru,

and Keith Willmott from the Florida Museum of Natural History, Gainesville, USA, for

tireless lepidopteran expertise. Fraser Simpson assisted with many aspects of this project.

Collecting permits and support were provided by INRENA (Peru) and the Ministerio del

Ambiente and the Museo Ecuatoriano de Ciencias Naturales (Ecuador). Logistic support in

DASMAHAPATRA ET AL. Mechanitis barcoding

14

Ecuador was given by the Napo Wildlife Centre and La Selva Jungle Lodge. We thank

NERC, DEFRA–Darwin, the Leverhulme Trust and the Margaret C. Walker fund for teaching

and research in systematic entomology for funding different aspects of this project.

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REFERENCES

Baus, E., Darrock, D. J., & Bruford, M. W. 2005 Gene-flow patterns in Atlantic and

Mediterranean populations of the Lusitanian sea star Asterina gibbosa. Mol. Ecol. 14,

3373-3382.

Bonin, A., Bellemain, E., Eidesen, P. B., Pomparon, F., Brochmann, C., & Taberlet, P. 2004

How to track and assess genotyping errors in population genetics studies. Mol. Ecol.

13, 3261-3273.

Borisenko, A. V., Lim, B. K., Ivanova, N. V., Hanner, R. H., & Hebert, P. D. N. 2008 DNA

barcoding in surveys of small mammal communities: a field study in Suriname.

Molecular Ecology Resources 8, 471-479.

Brown, K. S. 1977 Geographical patterns of evolution in Neotropical Lepidoptera:

differentiation of the species of Melinaea and Mechanitis (Nymphalidae, Ithomiinae).

Syst. Entomol. 2, 161-197.

Brown, K. S. 1979 Ecologia Geográfica e Evolução nas Florestas �eotropicais. Campinas,

Brazil: Universidade Estadual de Campinas.

Brown, K. S., von Schoultz, B., & Suomalainen, E. 2004 Chromosome evolution in

neotropical Danainae and Ithomiinae (Lepidoptera). Hereditas 141, 216-236.

Chaput-Bardy, A., Lemaire, C., Picard, D., & Secondi, J. 2008 In-stream and overland

dispersal across a river network influences gene flow in a freshwater insect,

Calopteryx splendens. Mol. Ecol. 17, 3496-3505.

Dasmahapatra, K. K. & Mallet, J. 2006 DNA barcodes: recent successes and future prospects.

Heredity 97, 254-255.

DASMAHAPATRA ET AL. Mechanitis barcoding

17

Dasmahapatra, K. K., Silva, A., Chung, J.-W., & Mallet, J. 2007 Genetic analysis of a wild-

caught hybrid between non-sister Heliconius butterfly species. Biol. Lett. 3, 360-363.

Elias, M., Hill, R. I., Willmott, K. R., Dasmahapatra, K. K., Brower, A. V. Z., Mallet, J., &

Jiggins, C. D. 2007 Limited performance of DNA barcoding in a diverse community

of tropical butterflies. Proc. Roy. Soc. Lond. B 274, 2881-2889.

Elias-Gutierrez, M., Jeronimo, F. M., Ivanova, N. V., Valdez-Moreno, M., & Hebert, P. D. N.

2008 DNA barcodes for Cladocera and Copepoda from Mexico and Guatemala,

highlights and new discoveries. Zootaxa, 1-42.

Evanno, G., Regnaut, S., & Goudet, J. 2005 Detecting the number of clusters of individuals

using the software STRUCTURE: a simulation study. Mol. Ecol. 14, 2611-2620.

Hajibabaei, M., Janzen, D. H., Burns, J. M., Hallwachs, W., & Hebert, P. D. N. 2006 DNA

barcodes distinguish species of tropical Lepidoptera. Proc. �atl. Acad. Sci. U. S. A.

103, 968-971.

Hajibabaei, M., Singer, G. A. C., Hebert, P. D. N., & Hickey, D. A. 2007 DNA barcoding:

how it complements taxonomy, molecular phylogenetics and population genetics.

Trends Genet. 23, 167-172.

Hebert, P. D. N., Cywinska, A., Ball, S. L., & deWaard, J. R. 2003 Biological identifications

through DNA barcodes. Proc. Roy. Soc. Lond. B 270, 313-321.

Hebert, P. D. N., Penton, E. H., Burns, J. M., Janzen, D. H., & Hallwachs, W. 2004a Ten

species in one: DNA barcoding reveals cryptic species in the neotropical skipper

butterfly Astraptes fulgerator. Proc. �atl. Acad. Sci. U. S. A. 101, 14812-14817.

DASMAHAPATRA ET AL. Mechanitis barcoding

18

Hebert, P. D. N., Stoeckle, M. Y., Zemlak, T. S., & Francis, C. M. 2004b Identification of

birds through DNA barcodes. PLOS Biology 2, 10.

Hickerson, M., Meyer, C. P., & Moritz, C. 2006 DNA barcoding will often fail to discover

new animal species over broad parameter space. Syst. Biol. 55, 729-739.

Hurst, G. D. D. & Jiggins, F. M. 2005 Problems with mitochondrial DNA as a marker in

population, phylogeographic, and phylogenetic studies: the effects of inherited

symbionts. Proc. Roy. Soc. Lond. B 272, 1525-1534.

Lamas, G. 2004 Ithomiinae. In Atlas of �eotropical Butterflies. Checklist: 4A. Hesperioidea -

Papilionoidea (ed. G. Lamas), pp. 172-191. Gainesville: Scientific Publishers.

Madden, J. R., Lowe, T. J., Fuller, H. V., Coe, R. L., Dasmahapatra, K. K., Amos, W., &

Jury, F. 2004 Neighbouring male spotted bowerbirds are not related, but do maraud

each other. Anim. Behav. 68, 751-758.

Mallarino, R., Bermingham, E., Willmott, K. R., Whinnett, A., & Jiggins, C. D. 2005

Molecular systematics of the butterfly genus Ithomia (Lepidoptera: Ithomiinae): a

composite phylogenetic hypothesis based on seven genes. Mol. Phylogenet. Evol. 34,

625-644.

Meyer, C. P. & Paulay, G. 2005 DNA barcoding: error rates based on comprehensive

sampling. PLOS Biology 3.

Monaghan, M. T., Balke, M., Ryan Gregory, T., & Vogler, A. P. 2005 DNA-based species

delineation in tropical beetles using mitochondrial and nuclear markers. Phil. Trans.

Roy. Soc. Lond. B 360, 1925-1933.

DASMAHAPATRA ET AL. Mechanitis barcoding

19

Mueller, U. G. & Wolfenbarger, L. L. 1999 AFLP genotyping and fingerprinting. Trends

Ecol. Evol. 14, 389-394.

Pritchard, J. K., Stephens, M., & Donnelly, P. 2000 Inference of population structure using

multilocus genotype data. Genetics 155, 945-959.

Rock, J., Costa, F. O., Walker, D. D., North, A. W., Hutchinson, W. F., & Carvalho, G. R.

2008 DNA barcodes of fish of the Scotia Sea, Antarctica indicate priority groups for

taxonomic and systematics focus. Antarctic Science 20, 253-22.

Smith, M. A., Woodley, N. E., Janzen, D. H., Hallwachs, W., & Hebert, P. D. N. 2006 DNA

barcodes reveal cryptic host-specificity within the presumed polyphagous members of

a genus of parasitoid flies (Diptera: Tachinidae). Proc. �atl. Acad. Sci. U. S. A. 103,

3657-3662.

Stoeckle, M. Y. & Hebert, P. D. N. 2008 Bar code of life: DNA tags help classify life. Sci.

Amer.

Takami, Y., Koshio, C., Ishii, M., Fujii, H., Hidaka, T., & Shimizu, I. 2004 Genetic diversity

and structure of urban populations of Pieris butterflies assessed using amplified

fragment length polymorphism. Mol. Ecol. 13, 245-258.

Tamura, K., Dudley, J., Nei, M., & Kumar, S. 2007 MEGA4: Molecular Evolutionary

Genetics Analysis (MEGA) software version 4.0. Mol. Biol. Evol. 24, 1596-1599.

Vos, P., Hogers, R., Bleeker, M., Reijans, M., van de Lee, T., Hornes, M., Frijters, A., Pot, J.,

Peleman, J., Kuiper, M., & Zabeau, M. 1995 AFLP: a new technique for DNA

fingerprinting. �ucl. Acids Res. 23, 4407-4414.

DASMAHAPATRA ET AL. Mechanitis barcoding

20

Whinnett, A., Brower, A. V. Z., Lee, M. M., Willmott, K. R., & Mallet, J. 2005a Phylogenetic

utility of Tektin, a novel region for inferring systematic relationships amongst

Lepidoptera. Ann. Entomol. Soc. Amer. 98, 873-886.

Whinnett, A., Zimmermann, M., Willmott, K. R., Herrera, N., Mallarino, R., Simpson, F.,

Joron, M., Lamas, G., & Mallet, J. 2005b Strikingly variable divergence times inferred

across an Amazonian butterfly 'suture zone'. Proc. Roy. Soc. B 272, 2525-2533.

Wiemers, M. & Fiedler, K. 2007 Does the DNA barcoding gap exist? - a case study in blue

butterflies (Lepidoptera: Lycaenidae). Frontiers in Zoology 4.

Will, K. W. & Rubinoff, D. 2004 Myth of the molecule: DNA barcodes for species cannot

replace morphology for identification and classification. Cladistics 20, 47-55.

DASMAHAPATRA ET AL. Mechanitis barcoding

21

FIGURE CAPTIONS

Figure 1

Neighbour-joining trees constructed from (a) mitochondrial sequences and (b, c and d)

nuclear sequences, showing relationships between the eight Mechanitis mitochondrial

haplogroups. Nodes marked with filled and open symbols have > 90 % and > 50 % (and < 90

%) bootstrap support respectively. Scale bars represent raw percentage sequence divergence.

(dec. = deceptus; maz. = mazaeus; mess. = messenoides)

Figure 2

STRUCTURE analysis of AFLP genotypes. a) Log likelihood of data as a function of K, the

number of clusters. Likelihoods from each of the three replicate runs at each K are

indistinguishable and the average likelihood is shown. Highest likelihood is achieved with

four clusters, even though eight mt-haplogroups are present. STRUCTURE results for b) the

optimal number of genotypic clusters, K = 4, and c) the number of mt-haplogroups, K = 8.

Each of the 85 individuals is represented by a vertical bar broken into K coloured segments.

The length of each colour in the bar indicates the posterior mean proportion of ancestry from

each genetic clusters. b) and c) are virtually identical, indicating the absence of any significant

additional genetic structure for more than four clusters.

SHORT TITLE: Mechanitis barcoding

0.1

%

b)

Tek

tin

0.2

%

d)

Rp

l5

M.

ma

zaeu

sm

t-h

aplo

gro

up

H

M.

ma

zaeu

sm

t-h

aplo

gro

up

H

0.6

%

c) T

pi

M.

ma

zaeu

s

mt-

hap

log

rou

ps

A +

F

E258 M

. m

azaeus

deceptu

s: E

cuador

20846 M

. m

azaeus

deceptu

s: E

cuador

E257 M

. m

azaeus

deceptu

s: E

cuador

E370 M

. m

azaeus

deceptu

s: E

cuador

E255 M

. m

azaeus

deceptu

s: E

cuador

20648 M

. m

azaeus

mess

enoid

es:

Ecuador

E256 M

. m

azaeus

deceptu

s: E

cuador

20289 M

. m

azaeus

mess

enoid

es:

Ecuador

20820 M

. m

azaeus

mess

enoid

es:

Ecuador

4-2

74 M

. m

azaeus

cf

phasi

anit

a:

Peru

4-2

72 M

. m

azaeus

cf

phasi

anit

a:

Peru

4-2

73 M

. m

azaeus

cf

phasi

anit

a:

Peru

20208 M

. m

azaeus

mess

. x m

az.:

Ecuador

LS

03-8

1 M

. m

azaeus

mess

enoid

es:

Ecuador

5-8

21 M

. m

azaeus

deceptu

s: P

eru

4-3

06 M

. m

azaeus

cf

phasi

anit

a:

Peru

LS

03-1

50 M

. m

azaeus

mess

enoid

es:

Ecuador

5-8

22 M

. m

azaeus

deceptu

s: P

eru

LS

02-2

20 M

. m

azaeus

deceptu

s: E

cuador

LS

05-0

2 M

. m

azaeus

mess

enoid

es:

Ecuador

4-2

76 M

. m

azaeus

cf

phasi

anit

a:

Peru

2-3

48 M

. m

azaeus

deceptu

s: P

eru

20705 M

. m

azaeus

mess

enoid

es:

Ecuador

LS

02-2

19 M

. m

azaeus

mess

enoid

es:

Ecuador

20345 M

. m

azaeus

deceptu

s: E

cuador

20281 M

. m

azaeus

mess

enoid

es:

Ecuador

20853 M

. m

azaeus

deceptu

s: E

cuador

20809 M

. m

azaeus

deceptu

s: E

cuador

20315 M

. m

azaeus

mess

enoid

es:

Ecuador

LS

02-4

9 M

. m

azaeus

deceptu

s: E

cuador

20265 M

. m

azaeus

deceptu

s: E

cuador

4-5

55 M

. poly

mnia

pro

ceri

form

is:

Peru

4-8

9 M

. poly

mnia

pro

ceri

form

is:

Peru

2-2

46 M

. poly

mnia

pro

ceri

form

is:

Peru

4-4

36 M

. poly

mnia

pro

ceri

form

is:

Peru

4-4

35 M

. poly

mnia

pro

ceri

form

is:

Peru

4-2

M. poly

mnia

pro

ceri

form

is:

Peru

3-5

1 M

. poly

mnia

casa

bra

nca:

East

ern

Bra

zil

3-5

2 M

. poly

mnia

casa

bra

nca:

East

ern

Bra

zil

3-5

3 M

. poly

mnia

casa

bra

nca:

East

ern

Bra

zil

4-4

38 M

. poly

mnia

pro

ceri

form

is:

Peru

JM

84-1

2 M

. poly

mnia

boli

vare

nsi

s: V

enezuela

4-1

42 M

. poly

mnia

pro

ceri

form

is:

Peru

2-3

131 M

. poly

mnia

eury

dic

e:

Peru

4-1

41 M

. poly

mnia

pro

ceri

form

is:

Peru

4-1

40 M

. poly

mnia

pro

ceri

form

is:

Peru

2-2

45 M

. poly

mnia

pro

ceri

form

is:

Peru

20297 M

. poly

mnia

cf

pro

ceri

form

is:

Ecuador

LS

02-1

76 M

. poly

mnia

cf

pro

ceri

form

is:

Ecuador

20298 M

. poly

mnia

cf

pro

ceri

form

is:

Ecuador

20340 M

. poly

mnia

cf

pro

ceri

form

is:

Ecuador

RH

00-6

2 M

. poly

mnia

cf

pro

ceri

form

is:

Ecuador

20728 M

. poly

mnia

cf

pro

ceri

form

is:

Ecuador

3-1

39 M

. ly

sim

nia

nesa

ea:

East

ern

Bra

zil

4-2

79 M

. ly

sim

nia

roqueensi

s: P

eru

4-1

M. ly

sim

nia

roqueensi

s: P

eru

2-4

85 M

. ly

sim

nia

roqueensi

s: P

eru

3-5

0 M

. ly

sim

nia

nesa

ea:

East

ern

Bra

zil

4-1

52 M

. ly

sim

nia

roqueensi

s: P

eru

4-5

52 M

. ly

sim

nia

roqueensi

s: P

eru

4-2

78 M

. ly

sim

nia

roqueensi

s: P

eru

2-1

222 M

. ly

sim

nia

roqueensi

s: E

cuador

LS

04-1

3 M

. ly

sim

nia

roqueensi

s: E

cuador

20338 M

. ly

sim

nia

roqueensi

s: E

cuador

20646 M

. ly

sim

nia

roqueensi

s: E

cuador

E358 M

. ly

sim

nia

roqueensi

s: E

cuador

20273 M

. ly

sim

nia

roqueensi

s: E

cuador

20586 M

. ly

sim

nia

roqueensi

s: E

cuador

LS

01-6

7 M

. ly

sim

nia

roqueensi

s: E

cuador

E497 M

. m

azaeus

mess

enoid

es:

Ecuador

20765 M

. m

azaeus

deceptu

s: E

cuador

20810 M

. m

azaeus

mess

enoid

es:

Ecuador

20223 M

. m

azaeus

mess

. x m

az.:

Ecuador

20514 M

. m

azaeus

mess

enoid

es:

Ecuador

20783 M

. m

azaeus

mess

enoid

es:

Ecuador

20782 M

. m

azaeus

mess

. x m

az.:

Ecuador

20512 M

. m

azaeus

mess

enoid

es:

Ecuador

20819 M

. m

azaeus

mess

enoid

es:

Ecuador

20316 M

. m

azaeus

mess

. x m

az.:

Ecuador

2-1

743 M

. m

azaeus

deceptu

s: P

eru

4-4

06 M

. m

azaeus

cf

phasi

anit

a:

Peru

4-8

5 M

. m

azaeus

deceptu

s: P

eru

ME

Per

u25 M

. m

azaeus

deceptu

s: P

eru

ME

Per

u65 M

. m

azaeus

deceptu

s: P

eru

5-3

81 M

. m

azaeus

cf

phasi

anit

a:

Peru

2-1

895 M

. m

azaeus

deceptu

s: P

eru

E544 M

. m

enapis

manti

neus:

West

Ecuador

E589 M

. m

enapis

manti

neus:

West

Ecuador

E60 M

. m

enapis

manti

neus:

West

Ecuador

JM

84-7

M. ly

sim

nia

sola

ria:

Venezuela

JM

84-8

M. ly

sim

nia

sola

ria:

Venezuela

LS

02-1

77 M

. m

azaeus

mazaeus:

Ecuador

20282 M

. m

azaeus

mazaeus:

Ecuador

20505 M

. m

azaeus

mazaeus:

Ecuador

20701 M

. m

azaeus

mazaeus:

Ecuador

LS

02-9

6 M

. m

azaeus

mazaeus:

Ecuador

LS

01-1

27 M

. m

azaeus

mazaeus:

Ecuador

JM

84-6

M. m

azaeus

pannif

era

: V

enezuela

5-7

51 M

. m

azaeus

mazaeus:

Peru

5-5

6 M

. m

azaeus

mazaeus:

Peru

4-2

69 M

. m

azaeus

mazaeus:

Peru

4-2

70 M

. m

azaeus

mazaeus:

Peru

4-1

36 M

. m

azaeus

mazaeus:

Peru

5-3

82 M

. m

azaeus

mazaeus:

Peru

20256 M

. m

azaeus

mazaeus:

Ecuador

4-2

67 M

. m

azaeus

mazaeus:

Peru

LS

02-1

64 M

. m

az. x d

ec.:

Ecuador

20506 M

. m

azaeus

mazaeus:

Ecuador

20784 M

. m

azaeus

mazaeus:

Ecuador

20322 M

. m

azaeus

mazaeus:

Ecuador

20781 M

. m

azaeus

mazaeus:

Ecuador

4-2

71 M

. m

azaeus

mazaeus:

Peru

2-2

41 M

. m

azaeus

mazaeus:

Peru

E359 M

. m

azaeus

mazaeus:

Ecuador

4-2

75 M

. m

azaeus

mazaeus:

Peru

JM

84-4

M. m

azaeus

pannif

era

: V

enezuela

1 %

M. m

aza

eus

mt-

hap

logro

up A

M. poly

mnia

mt-

hap

logro

up B

M. poly

mnia

mt-

hap

logro

up C

M. m

aza

eus

mt-

hap

logro

up H

M. m

enapis

M. m

aza

eus

mt-

hap

logro

up F

M. ly

sim

nia

mt-

hap

logro

up E

mt-

hap

logro

up G

a) m

tDN

A

20339 M

. poly

mnia

cf

pro

ceri

form

is:

Ecuador

20494 M

. poly

mnia

cf

pro

ceri

form

is:

Ecuador

M. poly

mnia

mt-

hap

logro

up D

Fig

ure

1

Figure 2

M. lysimnia

M. menapis

M. polymnia M. mazaeus

B AFHD

0.0

1.0

0.2

0.4

0.6

0.8

CE G

mitochondrial haplogroups

b) K = 4

0.0

1.0

0.2

0.4

0.6

0.8

mitochondrial haplogroups

c) K = 8

-3100

-2700

-2300

-1900

0 2 4 6 8 10

K clustersL

n L

(K)

a)

B AFHDCE G

M. lysimnia

M. menapis

M. polymnia M. mazaeus

DA

SM

AH

AP

AT

RA

ET

AL

.

M

echanit

is b

arco

din

g

1

SU

PP

LE

ME

NT

AR

Y M

AT

ER

IAL

Sp

ecie

s S

ub

spec

ies

(by w

ing p

atte

rn)

mt-

hap

logro

up

A

FL

P g

eno

typ

ic c

lust

er

Sp

ecim

en

ID

Co

llec

tio

n l

oca

lity

L

atit

ud

e L

on

git

ud

e

M. m

aza

eus

mes

senoid

es ×

maza

eus

A

‘mes

senoid

es/d

ecep

tus’

2

02

08

N

apo

Wil

dli

fe C

entr

e, E

cuad

or

31

' 45

S

76

° 2

5' 0

1 W

M. m

aza

eus

dec

eptu

s A

‘m

esse

noid

es/d

ecep

tus’

2

02

65

N

apo

Wil

dli

fe C

entr

e, E

cuad

or

30

' 33

S

76

° 2

6’

12

W

M. m

aza

eus

mes

senoid

es

A

‘mes

senoid

es/d

ecep

tus’

2

02

81

A

nang

u B

oca

del

Rio

, E

cuad

or

31

’ 4

3 S

7

23

’ 4

1 W

M. m

aza

eus

mes

senoid

es

A

‘mes

senoid

es/d

ecep

tus’

2

02

89

A

nang

u B

oca

del

Rio

, E

cuad

or

31

’ 4

3 S

7

23

’ 4

1 W

M. m

aza

eus

mes

senoid

es

A

‘mes

senoid

es/d

ecep

tus’

2

03

15

A

nang

u B

oca

del

Rio

, E

cuad

or

31

’ 4

3 S

7

23

’ 4

1 W

M. m

aza

eus

dec

eptu

s A

‘m

esse

noid

es/d

ecep

tus’

2

03

45

A

nang

u B

oca

del

Rio

, E

cuad

or

31

’ 4

3 S

7

23

’ 4

1 W

M. m

aza

eus

mes

senoid

es

A

‘mes

senoid

es/d

ecep

tus’

2

06

48

N

apo

Wil

dli

fe C

entr

e, E

cuad

or

30

’ 3

3 S

7

26

’ 1

2 W

M. m

aza

eus

mes

senoid

es

A

‘mes

senoid

es/d

ecep

tus’

2

07

05

A

nang

u B

oca

del

Rio

, E

cuad

or

31

’ 4

3 S

7

23

’ 4

1 W

M. m

aza

eus

dec

eptu

s A

‘m

esse

noid

es/d

ecep

tus’

2

08

09

N

apo

Wil

dli

fe C

entr

e, E

cuad

or

29

’ 3

7 S

7

26

’ 4

8 W

M. m

aza

eus

mes

senoid

es

A

‘mes

senoid

es/d

ecep

tus’

2

08

20

N

apo

Wil

dli

fe C

entr

e, E

cuad

or

30

’ 3

3 S

7

26

’ 1

2 W

M. m

aza

eus

dec

eptu

s A

‘m

esse

noid

es/d

ecep

tus’

2

08

46

A

nang

u B

oca

del

Rio

, E

cuad

or

31

’ 4

3 S

7

23

’ 4

1 W

M. m

aza

eus

dec

eptu

s A

‘m

esse

noid

es/d

ecep

tus’

2

08

53

A

nang

u B

oca

del

Rio

, E

cuad

or

31

’ 4

3 S

7

23

’ 4

1 W

M. m

aza

eus

dec

eptu

s A

‘m

esse

noid

es/d

ecep

tus’

2

-34

8

Po

ngo

de

Caynar

achi,

Per

u

20

' 7 S

7

15

' 15

W

M. m

aza

eus

cf. phasianita

A

‘mes

senoid

es/d

ecep

tus’

4

-27

2

Bo

sque

vo

n H

um

bo

ldt,

IN

IA,

Per

u

49

' 48

S

75

° 0

3' 2

8 W

M. m

aza

eus

cf. phasianita

A

‘mes

senoid

es/d

ecep

tus’

4

-27

3

Bo

sque

vo

n H

um

bo

ldt,

IN

IA,

Per

u

49

' 48

S

75

° 0

3' 2

8 W

M. m

aza

eus

cf. phasianita

A

‘mes

senoid

es/d

ecep

tus’

4

-27

4

Bo

sque

vo

n H

um

bo

ldt,

IN

IA,

Per

u

49

' 48

S

75

° 0

3' 2

8 W

M. m

aza

eus

cf. phasianita

A

‘mes

senoid

es/d

ecep

tus’

4

-27

6

Bo

sque

vo

n H

um

bo

ldt,

IN

IA,

Per

u

49

' 48

S

75

° 0

3' 2

8 W

M. m

aza

eus

cf. phasianita

A

‘mes

senoid

es/d

ecep

tus’

4

-30

6

Km

7.2

, P

ongo

– B

arra

nq

uit

a, P

eru

17

' 20

S

76

° 1

3' 4

1 W

M. m

aza

eus

dec

eptu

s A

-

5-8

21

Q

ueb

rad

a Y

anayac

u,

Per

u

44

' 26

S

75

° 5

8' 5

4 W

M. m

aza

eus

dec

eptu

s A

-

5-8

22

Q

ueb

rad

a Y

anayac

u,

Per

u

44

' 26

S

75

° 5

8' 5

4 W

M. m

aza

eus

dec

eptu

s A

‘m

esse

noid

es/d

ecep

tus’

E

25

5

Po

do

carp

us

Nat

ional

Rese

rve,

Ecu

ado

r 4

° 0

6' 8

0 S

7

57

' 90

W

M. m

aza

eus

dec

eptu

s A

-

E2

56

P

odo

carp

us

Nat

ional

Rese

rve,

Ecu

ado

r 4

° 0

6' 8

0 S

7

57

' 90

W

M. m

aza

eus

dec

eptu

s A

‘m

esse

noid

es/d

ecep

tus’

E

25

7

Po

do

carp

us

Nat

ional

Rese

rve,

Ecu

ado

r 4

° 0

6' 8

0 S

7

57

' 90

W

M. m

aza

eus

dec

eptu

s A

‘m

esse

noid

es/d

ecep

tus’

E

25

8

Po

do

carp

us

Nat

ional

Rese

rve,

Ecu

ado

r 4

° 0

6' 8

0 S

7

57

' 90

W

M. m

aza

eus

dec

eptu

s A

-

E3

70

S

ucua,

Ecu

ado

r 2

° 2

7' 3

5 S

7

10

' 11

W

M. m

aza

eus

dec

eptu

s A

-

LS

02

-49

G

arza

Co

cha,

Sucu

mb

ios,

Ecu

ado

r 0

° 2

9’

47

S

76

° 2

2’

25

W

M. m

aza

eus

mes

senoid

es

A

- L

S0

2-2

19

G

arza

Co

cha,

Sucu

mb

ios,

Ecu

ado

r 0

° 2

9’

47

S

76

° 2

2’

25

W

M. m

aza

eus

dec

eptu

s A

-

LS

02

-22

0

Gar

za C

och

a, S

ucu

mb

ios,

Ecu

ado

r 0

° 2

9’

47

S

76

° 2

2’

25

W

M. m

aza

eus

mes

senoid

es

A

- L

S0

3-8

1

Gar

za C

och

a, S

ucu

mb

ios,

Ecu

ado

r 0

° 2

9’

47

S

76

° 2

2’

25

W

M. m

aza

eus

mes

senoid

es

A

- L

S0

3-1

50

G

arza

Co

cha,

Sucu

mb

ios,

Ecu

ado

r 0

° 2

9’

47

S

76

° 2

2’

25

W

M. m

aza

eus

mes

senoid

es

A

- L

S0

5-0

2

San

i Is

la,

Ecuad

or

30

’ 4

1 S

7

21

’ 0

4 W

M. m

aza

eus

mes

senoid

es

× m

aza

eus

F

‘mes

senoid

es/d

ecep

tus’

2

02

23

N

apo

Wil

dli

fe C

entr

e, E

cuad

or

30

’ 3

3 S

7

26

’ 1

2 W

DA

SM

AH

AP

AT

RA

ET

AL

.

M

echanitis

bar

codin

g

2

M. m

aza

eus

mes

senoid

es. ×

maza

eus

F

‘mes

senoid

es/d

ecep

tus’

2

03

16

A

nang

u B

oca

del

Rio

, E

cuad

or

31

’ 4

3 S

7

23

’ 4

1 W

M. m

aza

eus

mes

senoid

es

F

- 2

05

12

A

nang

u B

oca

del

Rio

, E

cuad

or

31

’ 4

3 S

7

23

’ 4

1 W

M. m

aza

eus

mes

senoid

es

F

- 2

05

14

A

nang

u B

oca

del

Rio

, E

cuad

or

31

’ 4

3 S

7

23

’ 4

1 W

M. m

aza

eus

dec

eptu

s F

-

20

765

A

nang

u B

oca

del

Rio

, E

cuad

or

31

’ 4

3 S

7

23

’ 4

1 W

M. m

aza

eus

mes

senoid

es ×

maza

eus

F

‘mes

senoid

es/d

ecep

tus’

2

07

82

N

apo

Wil

dli

fe C

entr

e, E

cuad

or

29

’ 3

7 S

7

26

’ 4

8 W

M. m

aza

eus

mes

senoid

es

F

‘mes

senoid

es/d

ecep

tus’

2

07

83

N

apo

Wil

dli

fe C

entr

e, E

cuad

or

29

’ 3

7 S

7

26

’ 4

8 W

M. m

aza

eus

mes

senoid

es

F

‘mes

senoid

es/d

ecep

tus’

2

08

10

N

apo

Wil

dli

fe C

entr

e, E

cuad

or

29

’ 3

7 S

7

26

’ 4

8 W

M. m

aza

eus

mes

senoid

es

F

‘mes

senoid

es/d

ecep

tus’

2

08

19

N

apo

Wil

dli

fe C

entr

e, E

cuad

or

30

’ 3

3 S

7

26

’ 1

2 W

M. m

aza

eus

dec

eptu

s

F

‘mes

senoid

es/d

ecep

tus’

2

-17

43

P

uen

te A

guas

Ver

des

, P

eru

39

' 50

S

77

° 3

8' 5

8 W

M. m

aza

eus

dec

eptu

s

F

‘mes

senoid

es/d

ecep

tus’

2

-18

95

K

m 3

0,

Tar

apo

to –

Yuri

mag

uas

, P

eru

24

' 81

S

76

° 1

8' 5

0 W

M. m

aza

eus

dec

eptu

s

F

‘mes

senoid

es/d

ecep

tus’

4

-85

R

ío P

revis

to s

usp

ensi

on b

rid

ge,

Per

u

06

' 13

S

75

° 4

4' 2

8 W

M. m

aza

eus

cf. phasianita

F

‘mes

senoid

es/d

ecep

tus’

4

-40

6

Km

16

, T

arap

oto

– Y

uri

mag

uas

, P

eru

27

' 18

S

76

° 1

7' 5

4 W

M. m

aza

eus

cf. phasianita

F

‘mes

senoid

es/d

ecep

tus’

5

-38

1

Cer

ro d

e M

ira

Culo

, P

eru

27

' 12

S

75

° 5

0' 1

6 W

M. m

aza

eus

mes

senoid

es

F

‘mes

senoid

es/d

ecep

tus’

E

49

7

Mo

nta

lvo

, E

cuad

or

15

' 60

S

80

° 3

8' 6

0 W

M. m

aza

eus

dec

eptu

s F

‘m

esse

noid

es/d

ecep

tus’

M

EP

eru2

5

Tar

apo

to, S

an M

arti

n,

Per

u

- -

M. m

aza

eus

dec

eptu

s F

‘m

esse

noid

es/d

ecep

tus’

M

EP

eru6

5

Tar

apo

to, S

an M

arti

n,

Per

u

- -

M. m

aza

eus

maza

eus

H

‘maza

eus’

2

02

56

N

apo

Wil

dli

fe C

entr

e, E

cuad

or

30

’ 3

3 S

7

26

’ 1

2 W

M. m

aza

eus

maza

eus

H

‘maza

eus’

2

02

82

A

nang

u B

oca

del

Rio

, E

cuad

or

31

’ 4

3 S

7

23

’ 4

1 W

M. m

aza

eus

maza

eus

H

‘maza

eus’

2

03

22

A

nang

u B

oca

del

Rio

, E

cuad

or

31

’ 4

3 S

7

23

’ 4

1 W

M. m

aza

eus

maza

eus

H

- 2

05

05

A

nang

u B

oca

del

Rio

, E

cuad

or

31

’ 4

3 S

7

23

’ 4

1 W

M. m

aza

eus

maza

eus

H

‘maza

eus’

2

05

06

A

nang

u B

oca

del

Rio

, E

cuad

or

31

’ 4

3 S

7

23

’ 4

1 W

M. m

aza

eus

maza

eus

H

‘maza

eus’

2

07

01

A

nang

u B

oca

del

Rio

, E

cuad

or

31

’ 4

3 S

7

23

’ 4

1 W

M. m

aza

eus

maza

eus

H

‘maza

eus’

2

07

81

N

apo

Wil

dli

fe C

entr

e, E

cuad

or

29

’ 3

7 S

7

26

’ 4

8 W

M. m

aza

eus

maza

eus

H

‘maza

eus’

2

07

84

N

apo

Wil

dli

fe C

entr

e, E

cuad

or

29

’ 3

7 S

7

26

’ 4

8 W

M. m

aza

eus

maza

eus

H

‘maza

eus’

2

-24

1

Km

7.2

, P

ongo

– B

arra

nq

uit

a, P

eru

17

' 20

S

76

° 1

3' 4

1 W

M. m

aza

eus

maza

eus

H

‘maza

eus’

4

-13

6

El

Pan

dis

ho

, L

ago

Yar

inac

och

a, P

eru

19

' 02

S

74

° 3

5' 2

8 W

M. m

aza

eus

maza

eus

H*

‘maza

eus’

4

-18

4

Cañ

o T

ush

mo

, L

ago

Yar

inac

och

a, P

eru

20

' 25

S

74

° 3

5' 3

0 W

M. m

aza

eus

maza

eus

H

‘maza

eus’

4

-26

7

Bo

sque

vo

n H

um

bo

ldt,

IN

IA,

Per

u

49

' 48

S

75

° 0

3' 2

8 W

M. m

aza

eus

maza

eus

H

‘maza

eus’

4

-26

9

Bo

sque

vo

n H

um

bo

ldt,

IN

IA,

Per

u

49

' 48

S

75

° 0

3' 2

8 W

M. m

aza

eus

maza

eus

H

‘maza

eus’

4

-27

0

Bo

sque

vo

n H

um

bo

ldt,

IN

IA,

Per

u

49

' 48

S

75

° 0

3' 2

8 W

M. m

aza

eus

maza

eus

H

‘maza

eus’

4

-27

1

Bo

sque

vo

n H

um

bo

ldt,

IN

IA,

Per

u

49

' 48

S

75

° 0

3' 2

8 W

M. m

aza

eus

maza

eus

H

‘maza

eus’

4

-27

5

Bo

sque

vo

n H

um

bo

ldt,

IN

IA,

Per

u

49

' 48

S

75

° 0

3' 2

8 W

M. m

aza

eus

maza

eus

H

‘maza

eus’

5

-56

R

ío P

auya/

Río

Cush

abat

ay c

onfl

uence

, P

eru

09

' 18

S

75

° 4

3' 2

4 W

M. m

aza

eus

maza

eus

H

‘maza

eus’

5

-38

2

Cer

ro d

e M

ira

Culo

, P

eru

27

' 12

S

75

° 5

0' 1

6 W

M. m

aza

eus

maza

eus

H

- 5

-75

1

Queb

rad

a Y

anayac

u,

Per

u

44

' 26

S

75

° 5

8' 5

4 W

M. m

aza

eus

maza

eus

H

‘maza

eus’

E

35

9

Co

mm

unid

ad S

huar

Mir

ado

r, E

cuad

or

- -

M. m

aza

eus

pannifer

a

H

- JM

84

-4

El

Mia

no

, 4

km

E,

Ven

ezuel

a

10

° 1

5' 4

6 N

6

17

' 50

W

DA

SM

AH

AP

AT

RA

ET

AL

.

M

echanitis

bar

codin

g

3

M. m

aza

eus

pannifer

a

H

- JM

84

-6

El

Mia

no

, 4

km

E,

Ven

ezuel

a

10

° 1

5' 4

6 N

6

17

' 50

W

M. m

aza

eus

maza

eus

H

- L

S0

1-1

27

G

arza

Co

cha,

Sucu

mb

ios,

Ecu

ado

r 0

° 2

9’

47

S

76

° 2

2’

25

W

M. m

aza

eus

maza

eus

H

- L

S0

2-9

6

San

i Is

la,

Ecuad

or

30

’ 4

1 S

7

21

’ 0

4 W

M. m

aza

eus

maza

eus ×

dec

eptu

s

H

- L

S0

2-1

64

G

arza

Co

cha,

Sucu

mb

ios,

Ecu

ado

r 0

° 2

9’

47

S

76

° 2

2’

25

W

M. m

aza

eus

maza

eus

H

- L

S0

2-1

77

G

arza

Co

cha,

Sucu

mb

ios,

Ecu

ado

r 0

° 2

9’

47

S

76

° 2

2’

25

W

M. ly

sim

nia

so

laria

(H)

- JM

84

-7

Cu

manac

oa

- C

oco

kar

, K

m 1

7,

Ven

ezuel

a 1

14

' 20

N

63

° 5

5' 1

5 W

M. ly

sim

nia

so

laria

(H)

- JM

84

-8

Cu

manac

oa

- C

oco

kar

, K

m 1

7,

Ven

ezuel

a 1

14

' 20

N

63

° 5

5' 1

5 W

M. poly

mnia

pro

cerifo

rmis

B

‘poly

mnia

’ 2

-24

6

Km

7.2

, P

ongo

– B

arra

nq

uit

a, P

eru

17

' 20

S

76

° 1

3' 4

1 W

M. poly

mnia

pro

cerifo

rmis

B

‘poly

mnia

’ 4

-2

Cas

till

o G

rand

e, T

ingo

Mar

ia,

Per

u

16

' 11

S

76

° 0

0' 2

9 W

M. poly

mnia

pro

cerifo

rmis

B

‘poly

mnia

’ 4

-89

R

ío P

revis

to s

usp

ensi

on b

rid

ge,

Per

u

06

' 13

S

75

° 4

4' 2

8 W

M. poly

mnia

pro

cerifo

rmis

B*

‘poly

mnia

’ 4

-21

2

Km

59

, P

uca

llp

a -

Tin

go

Mar

ia,

Per

u

38

' 28

S

74

° 5

7' 1

3 W

M. poly

mnia

pro

cerifo

rmis

B

‘poly

mnia

’ 4

-43

5

Km

22

, N

uev

o L

ima

- S

elva

And

ina,

Per

u

11

' 36

S

76

° 2

0' 0

6 W

M. poly

mnia

pro

cerifo

rmis

B

‘poly

mnia

’ 4

-43

6

Km

22

, N

uev

o L

ima

- S

elva

And

ina,

Per

u

11

' 36

S

76

° 2

0' 0

6 W

M. poly

mnia

pro

cerifo

rmis

B

‘poly

mnia

’ 4

-55

5

Km

22

.5,

Nuev

o L

ima

- L

a P

erla

del

Po

nac

illo

, P

eru

10

' 56

S

76

° 1

0' 5

2 W

M. poly

mnia

ca

sabra

nca

C

‘p

oly

mnia

’ 3

-51

C

am

pin

as,

Bra

zil

22

° 4

9' 3

4 S

4

4' 4

W

M. poly

mnia

ca

sabra

nca

C

‘p

oly

mnia

’ 3

-52

C

am

pin

as,

Bra

zil

22

° 4

9' 3

4 S

4

4' 4

W

M. poly

mnia

ca

sabra

nca

C

‘p

oly

mnia

’ 3

-53

C

am

pin

as,

Bra

zil

22

° 4

9' 3

4 S

4

4' 4

W

M. poly

mnia

pro

cerifo

rmis

C

‘poly

mnia

’ 4

-43

8

Km

22

, N

uev

o L

ima

- S

elva

And

ina,

Per

u

11

' 36

S

76

° 2

0' 0

6 W

M. poly

mnia

boliva

rensis

C

- JM

84

-12

E

l M

iano

, 4

km

E,

Ven

ezuel

a

10

° 1

5' 4

6 N

6

17

' 50

W

M. poly

mnia

cf

. pro

cerifo

rmis

D

‘poly

mnia

’ 2

03

40

A

nang

u B

oca

del

Rio

, E

cuad

or

31

’ 4

3 S

7

23

’ 4

1 W

M. poly

mnia

cf

. pro

cerifo

rmis

D

‘poly

mnia

’ 2

07

28

A

nang

u B

oca

del

Rio

, E

cuad

or

31

’ 4

3 S

7

23

’ 4

1 W

M. poly

mnia

cf

. pro

cerifo

rmis

D

- 2

02

97

A

nang

u B

oca

del

Rio

, E

cuad

or

31

’ 4

3 S

7

23

’ 4

1 W

M. poly

mnia

cf

. pro

cerifo

rmis

D

- 2

02

98

A

nang

u B

oca

del

Rio

, E

cuad

or

31

’ 4

3 S

7

23

’ 4

1 W

M. poly

mnia

cf

. pro

cerifo

rmis

D

- 2

03

39

A

nang

u B

oca

del

Rio

, E

cuad

or

31

’ 4

3 S

7

23

’ 4

1 W

M. poly

mnia

cf

. pro

cerifo

rmis

D

- 2

04

94

A

nang

u B

oca

del

Rio

, E

cuad

or

31

’ 4

3 S

7

23

’ 4

1 W

M. poly

mnia

pro

cerifo

rmis

D

- 2

-24

5

Km

7.2

, P

ongo

– B

arra

nq

uit

a, P

eru

17

' 20

S

76

° 1

3' 4

1 W

M. poly

mnia

eu

rydic

e D

‘p

oly

mnia

’ 2

-31

31

P

alm

a R

eal,

Per

u

12

° 3

7' 1

8 S

7

41

' 25

W

M. poly

mnia

pro

cerifo

rmis

D

‘poly

mnia

’ 4

-14

0

El

Pan

dis

ho

, L

ago

Yar

inac

och

a, P

eru

19

' 02

S

74

° 3

5' 2

8 W

M. poly

mnia

pro

cerifo

rmis

D

‘poly

mnia

’ 4

-14

1

El

Pan

dis

ho

, L

ago

Yar

inac

och

a, P

eru

19

' 02

S

74

° 3

5' 2

8 W

M. poly

mnia

pro

cerifo

rmis

D

‘poly

mnia

’ 4

-14

2

El

Pan

dis

ho

, L

ago

Yar

inac

och

a, P

eru

19

' 02

S

74

° 3

5' 2

8 W

M. poly

mnia

cf

. pro

cerifo

rmis

D

- L

S0

2-1

76

G

arza

Co

cha,

Sucu

mb

ios,

Ecu

ado

r 0

° 2

9’

47

S

76

° 2

2’

25

W

M. poly

mnia

cf

. pro

cerifo

rmis

D

- R

H0

0-6

2

Gar

za C

och

a, S

ucu

mb

ios,

Ecu

ado

r 0

° 2

9’

47

S

76

° 2

2’

25

W

M. ly

sim

nia

ro

quee

nsis

E

- 2

02

73

A

nang

u B

oca

del

Rio

, E

cuad

or

31

’ 4

3 S

7

23

’ 4

1 W

M. ly

sim

nia

ro

quee

nsis

E

‘lys

imnia

’ 2

05

86

A

nang

u B

oca

del

Rio

, E

cuad

or

31

’ 4

3 S

7

23

’ 4

1 W

M. ly

sim

nia

ro

quee

nsis

E

- 2

06

46

N

apo

Wil

dli

fe C

entr

e, E

cuad

or

30

’ 3

3 S

7

26

’ 1

2 W

M. ly

sim

nia

ro

quee

nsis

E

‘lys

imnia

’ 2

03

38

A

nang

u B

oca

del

Rio

, E

cuad

or

31

’ 4

3 S

7

23

’ 4

1 W

M. ly

sim

nia

ro

quee

nsis

E

- 2

-48

5

Km

7.2

, P

ongo

– B

arra

nq

uit

a, P

eru

17

' 20

S

76

° 1

3' 4

1 W

DA

SM

AH

AP

AT

RA

ET

AL

.

M

echanitis

bar

codin

g

4

M. ly

sim

nia

ro

quee

nsis

E

- 2

-12

22

K

m 8

, T

arap

oto

– Y

uri

maguas,

Per

u

27

' 48

S

76

° 1

9' 2

0 W

M. ly

sim

nia

nes

aea

E

‘lys

imnia

’ 3

-50

C

am

pin

as,

Bra

zil

22

° 4

9' 3

4 S

4

04

' 04

W

M. ly

sim

nia

nes

aea

E

‘lys

imnia

’ 3

-13

9

Ser

ra B

onit

a, B

razi

l 1

25

' 18

S

39

° 3

0' 1

2 W

M. ly

sim

nia

ro

quee

nsis

E

‘lys

imnia

’ 4

-1

Cas

till

o G

rand

e, T

ingo

Mar

ia,

Per

u

16

' 11

S

76

° 0

0' 2

9 W

M. ly

sim

nia

ro

quee

nsis

E*

‘lys

imnia

’ 4

-12

8

Río

Pre

vis

to s

usp

ensi

on b

rid

ge,

Per

u

06

' 13

S

75

° 4

4' 2

8 W

M. ly

sim

nia

ro

quee

nsis

E

- 4

-15

2

Cañ

o T

ush

mo

, L

ago

Yar

inac

och

a, P

eru

20

' 25

S

74

° 3

5' 3

0 W

M. ly

sim

nia

ro

quee

nsis

E

‘lys

imnia

’ 4

-27

8

Bo

sque

vo

n H

um

bo

ldt,

IN

IA,

Per

u

49

' 48

S

75

° 0

3' 2

8 W

M. ly

sim

nia

ro

quee

nsis

E

‘lys

imnia

’ 4

-27

9

Bo

sque

vo

n H

um

bo

ldt,

IN

IA,

Per

u

49

' 48

S

75

° 0

3' 2

8 W

M. ly

sim

nia

ro

quee

nsis

E

‘lys

imnia

’ 4

-55

2

Km

22

.5,

Nuev

o L

ima

- L

a P

erla

del

Po

nac

illo

, P

eru

10

' 56

S

76

° 1

0' 5

2 W

M. ly

sim

nia

ro

quee

nsis

E

‘lys

imnia

’ E

35

8

Co

mm

unid

ad S

huar

Mir

ado

r, E

cuad

or

M. ly

sim

nia

ro

quee

nsis

E

- L

S0

1-6

7

Gar

za C

och

a, S

ucu

mb

ios,

Ecu

ado

r 0

° 2

9’

47

S

76

° 2

2’

25

W

M. ly

sim

nia

ro

quee

nsis

E

- L

S0

4-1

3

Gar

za C

och

a, S

ucu

mb

ios,

Ecu

ado

r 0

° 2

9’

47

S

76

° 2

2’

25

W

M. m

enapis

m

antineu

s G

m

ixed

E

60

M

ind

o,

Ecu

ado

r 0

° 1

' 60

S

78

° 4

7' 6

0 W

M. m

enapis

m

antineu

s G

m

ixed

E

54

4

Lo

s C

edro

s, E

cuad

or

19

' 48

N

78

° 4

8' 3

6 W

M. m

enapis

mantineu

s G

m

ixed

E

58

9

Lo

s C

edro

s, E

cuad

or

19

' 48

N

78

° 4

8' 3

6 W

Tab

le S

1

Det

ails

of

sam

ple

s an

d s

ampli

ng l

oca

liti

es

* O

nly

a s

hort

er l

ength

of

mtD

NA

seq

uen

ce (

~560

bp)

could

be

obta

ined

fo

r th

ese

indiv

idual

s. T

his

was

suff

icie

nt

for

mt-

hap

logro

up

clas

sifi

cati

on, but

thes

e sp

ecim

ens

are

not

rep

rese

nte

d i

n t

he

mtD

NA

NJ

tree

(F

igu

re 1

a).

DA

SM

AH

AP

AT

RA

ET

AL

.

M

echanitis

bar

codin

g

5

Am

pli

con

Pri

mer

s P

rim

er s

equen

ces

(5’-

3’)

T

a

/ ºC

MgC

l 2

(mM

)

dN

TP

s

(mM

)

mtD

NA

bar

code

Lep

3.1

f a

Lep

3.1

r a

TC

TA

CA

AA

TC

AT

AA

AG

AT

AT

TG

GA

AC

AT

T

AA

AT

TT

TA

AT

TC

CT

GT

TG

GT

AC

AG

C

55

2.3

0.2

mtD

NA

CoI

Jerr

y b

Pat

lep a

CA

AC

AT

TT

AT

TT

TG

AT

TT

TT

TG

G

TC

CA

TT

AC

AT

AT

AA

TC

TG

CC

AT

AT

TA

57

2.3

0.2

mtD

NA

CoII

Geo

rgei

th *

Evai

th *

TA

GG

WT

TA

GC

WG

GA

AT

AC

C

GA

GA

CC

AA

TA

CT

TG

CT

TT

CA

GA

CA

TC

T

58

2.3

0.2

Tpi

Jess

*

Nab

*

AG

CA

AN

CA

GA

TW

AA

TG

AA

AT

CR

TY

A

TA

GC

CA

YT

TA

CG

NA

GA

GA

NG

C

63

– 5

6

3.0

0.8

Tek

tin c

tek3

teka

CG

CA

GT

TT

YT

GA

TR

CT

YT

AC

CA

GT

GG

RG

AY

AT

YC

TW

GG

57

2.7

5

0.6

8

Rpl5

d

Rpl5

-F44

Rpl5

-R441

TC

CG

AC

TT

TC

AA

AC

AA

GG

AT

G

CA

TA

TC

CT

GG

GA

AT

CT

CT

TG

AT

G

55

2.3

0.2

Tab

le S

2.

PC

R c

ondit

ions

for

the

ampli

cons

use

d i

n t

his

stu

dy.

All

rea

ctio

ns

wer

e ca

rrie

d o

ut

in 1

l volu

mes

usi

ng 1

bu

ffer

(S

igm

a), 0.5

µM

eac

h o

f fo

rwar

d a

nd r

ever

se p

rim

ers

and 0

.25U

Taq p

oly

mer

ase

(Sig

ma)

. F

or Tpi

0.1

6 µ

g/m

l B

SA

was

als

o a

dded

. P

CR

cycl

ing c

ondit

ions

wer

e: i

nit

ial

den

aturi

ng a

t 94ºC

for

2 m

inute

s; f

oll

ow

ed b

y 3

5 c

ycl

es

of

94ºC

for

45s,

annea

ling t

emper

ature

(T

a) f

or

45

s, 7

2ºC

for

60s;

fin

al e

xte

nsi

on a

t 72ºC

for

5 m

inute

s. F

or Tpi,

PC

R c

ycl

ing c

ondit

ions

wer

e

the

sam

e ex

cept

that

a t

ouch

dow

n p

roce

dure

was

use

d w

ith T

a dro

ppin

g f

rom

63ºC

to 5

6ºC

over

14 c

ycl

es, fo

llow

ed b

y a

furt

her

23 c

ycl

es a

t

56ºC

. * T

hes

e pri

mer

s w

ere

dev

eloped

for

this

stu

dy. Tpi

pri

mer

s Je

ss a

nd N

ab, w

ere

dev

eloped

by A

lain

e W

hin

net

t.

a (D

asm

ahap

atra

et

al. 20

07);

b (

Sim

on e

t al

. 1994);

c (W

hin

net

t et

al.

2005a)

; d (

Mal

lari

no e

t al

. 2005)

DA

SM

AH

AP

AT

RA

ET

AL

.

M

echanitis

bar

codin

g

6

Sp

ecie

s

M. ly

sim

nia

M

. m

enapis

M. poly

mnia

M

. m

aza

eus

mt-

hap

logro

up

E

G

B

C

D

A

F

H

M. ly

sim

nia

E

0.6

2

.3

2.4

2

.3

2.0

2

.8

2.8

3

.1

M. m

enapis

G

0.1

2

.5

2.5

2

.1

2.9

2

.1

2.6

M. poly

mnia

B

0.2

2

.3

2.2

2

.8

3.0

3

.3

C

0.2

1

.6

2.7

3

.3

3.3

D

0.2

2

.7

2.9

3

.2

M. m

aza

eus

A

0.6

3

.6

4.1

F

0.4

3

.5

H

0.5

Tab

le S

3. R

aw p

erce

nta

ge

pai

rwis

e dis

tance

s bet

wee

n m

tDN

A h

aplo

gro

ups.

Intr

a-hap

logro

up d

ista

nce

s ar

e it

alic

ised

.