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. 2014 Nov 21;7:519. doi: 10.1186/s13071-014-0519-1

DNA barcoding does not separate South American Triatoma (Hemiptera: Reduviidae), Chagas Disease vectors

Silvia Andrade Justi 1,2, Carolina Dale 2, Cleber Galvão 2,
PMCID: PMC4243934  PMID: 25413618

Abstract

Background

DNA barcoding assumes that a biological entity is completely separated from its closest relatives by a barcoding gap, which means that intraspecific genetic distance (from COI sequences) should never be greater than interspecific distances. We investigated the applicability of this strategy in identifying species of the genus Triatoma from South America.

Findings

We calculated intra and interspecific Kimura-2-parameter distances between species from the infestans, matogrossensis, sordida and rubrovaria subcomplexes. In every subcomplex examined we observed at least one intraspecific distance greater than interspecific distances.

Conclusions

Although DNA barcoding is a straightforward approach, it was not applicable for identifying Southern American Triatoma species, which may have diverged recently. Thus, caution should be taken in identifying vector species using this approach, especially in groups where accurate identification of taxa is fundamentally linked to public health issues.

Keywords: Triatominae, Chagas disease, DNA barcoding, Molecular identification

Findings

DNA barcoding, as proposed by Hebert et al. [1] assumes that a biological entity is completely separated from its closest relatives by a barcoding gap [2], which means that intraspecific genetic distances (from COI sequences) are never greater than interspecific distances.

Triatoma Laporte (Hemiptera: Reduviidae) is the most diverse genus of Chagas Disease vectors, and accurate identification of species is imperative for the efficiency of vector control programs. The Triatoma genus is divided into species complexes and subcomplexes according to geographic distribution and morphological similarity [3].

Recently, Justi et al. [4] reported that the relationships between species assigned to South American Triatomasubcomplexes could not be untangled with the data in hand. We were then prompted to investigate whether DNA barcoding would be a useful tool for identifying the species within the infestans, matogrossensis, sordida and rubrovaria subcomplexes [3].

Kimura-2-parameter genetic distances [5] were calculated pairwise within each of the above mentionedsubcomplexes (Table 1) using the software MEGA v. 5 [6], and intra and interspecific distances were compared.

Table 1.

K2p-distances between species of the Triatoma subcomplexes studied

Subcomplex GenBank Number Geographic Origin
infestans 1 2 3 4 5
KC249330 1 Chaco Tita, Cochabamba, Bolivia T. delpontei 53
KC249346 2 Chaco Tita, Cochabamba, Bolivia T. infestans 44 0.021
KC249349 3 Cotapachi, Cochabamba, Bolivia T. infestans 58 0.025 0.018
KC249352 4 Mataral, Cochabamba, Bolivia T. infestans 60 0.025 0.018 0.005
KC249354 5 Ilicuni, Cochabamba, Bolivia T. infestans 63 0.021 0.016 0.000 0.006
KC249355 6 Montevideo, Uruguai T. infestans 69 0.072 0.061 0.064 0.069 0.103
matogrossensis 7 8 9 10 11 12
KC249327,KC249328 7 Posse, GO, Brazil T. costalimai 35
KC249329 8 Chiquitania, Cochabamba, Bolivia T. costalimai 42 0.154
KC249360 9 São Gabriel D'oeste, MS, Brazil T. matogrossensis 192 0.134 0.138
KC249361 10 Bahia, Brazil T. matogrossensis 31 0.151 0.152 0.047
KC249391 11 Pantanal, MT, Brazil T. vandae 28 0.156 0.151 0.047 0.040
KC249392 12 Rio Verde do MatoGrosso, MT, Brazil T. vandae 73 0.138 0.146 0.005 0.046 0.045
KC249393,KC249394 13 Rondonópolis, MT, Brazil T. vandae 74 0.158 0.150 0.048 0.059 0.007 0.052
rubrovaria 14 15 16 17 18 19 20 21 22 23 24
KC249322 14 São Gerônimo, RS, Brazil T. carcavalloi 78
KC249323 15 Caçapava do Sul, RS, Brazil T. circummaculata 120 0.039
KC249324 16 Sítio Faxina, Piratini, RS, Brazil T. circummaculata 121 0.029 0.025
KC249325 17 Sítio Faxina, Piratini, RS, Brazil T. circummaculata 122 0.017 0.039 0.033
KC249356 18 Nova Petrópolis, RS, Brazil T. klugi 75 0.018 0.037 0.031 0.017
KC249369 19 Sítio Faxina, Piratini, RS, Brazil T.rubrovaria 123 0.055 0.023 0.029 0.055 0.057
KC249370 20 Sítio venda da Lagoa, Canguçu, RS, Brazil T.rubrovaria 134 0.065 0.052 0.065 0.065 0.061 0.070
KC249372 21 SítioFaxina, Pinheiro Machado, RS, Brazil T.rubrovaria 136 0.042 0.019 0.027 0.036 0.036 0.031 0.035
KC249373 22 Sítiovenda da Lagoa, Canguçu, RS, Brazil T.rubrovaria 140 0.038 0.020 0.019 0.043 0.040 0.029 0.032 0.012
KC249374 23 Canguçu, RS, Brazil T.rubrovaria 156 0.039 0.020 0.019 0.045 0.042 0.029 0.032 0.012 0.000
KC249375 24 Caçapava do Sul, RS, Brazil T.rubrovaria 76 0.021 0.029 0.021 0.016 0.016 0.033 0.074 0.034 0.038 0.038
KC249376 25 Quevedos, RS, Brazil T.rubrovaria 77 0.029 0.030 0.043 0.022 0.029 0.046 0.065 0.031 0.046 0.048 0.026
sordida 26 27 28 29 30 31 32 33 34
KC249338 26 Rivadaria, Argentina T. garciabesi 89
KC249342 27 Santa Cruz, Bolívia T. guasayana 55 0.077
KC249343 28 Santa Cruz, Bolívia T. guasayana 82 0.065 0.056
KC249379,KC249380 29 Romerillo, Cochabamba, Bolivia T. sordida 46 0.029 0.060 0.060
KC249381,KC249382 30 Romerillo, Cochabamba, Bolivia T. sordida 47 0.030 0.061 0.061 0.000
KC249383 31 La Paz, Bolívia T. sordida 83 0.081 0.013 0.063 0.066 0.066
KC249384 32 Pantanal, MS, Brazil T. sordida 85 0.069 0.012 0.062 0.065 0.065 0.025
KC249385 33 Santa Cruz, Bolívia T. sordida 86 0.043 0.082 0.074 0.035 0.035 0.073 0.082
KC249387 34 San Miguel Corrientes, Argentina T. sordida 88 0.061 0.058 0.063 0.070 0.071 0.058 0.055 0.052
KC249388 35 Poconé, MT, Brazil T. sordida 90 0.069 0.017 0.058 0.075 0.075 0.031 0.011 0.078 0.051

Highlighted distances deviate from the DNA barcoding premis that intraspecific distances are smaller than interspecific distances.

In all subcomplexes we observed at least one intraspecific distance greater than interspecific distances (Table 1). To be considered appropriate to identify species within a group, intraspecific distances must always be greater than interspecific ones [2], and therefore DNA barcoding is not accurate for the species-level identification of South American Triatoma. Moreover, the method fails to account for hybridization events, which are naturally observed in Triatoma [7,8], and introgression, which is frequent in nuclear DNA [9]. These considerations argue that Hebert et al.’s [1] proposal of cataloguing biodiversity based only on DNA barcoding may severely underestimate it.

Besides that, as highlighted by Dujardin et al. [10], the morphological changes observed in closely related “species”, or “lineages” as we prefer to call them, may have led taxonomists to rush into describing subspecies or species, even genera. Molecular phylogenetic studies are in their infancy in unravelling the evolution of Triatominae, and a comprehensive molecular phylogeny, including more than one specimen for most lineages, was published only in 2014 [4], although several analyses were conducted focusing on small species groups. Taken together, these statements make it clear that further investigations of Triatominae evolution are long overdue, preferably integrating morphological, molecular and ecological data.

Lineage evolution has not occurred, but it is happening now. Concerning lineages designated in the infestans complex (including the subcomplexes studied here), separation is much clearer in terms of morphology than in molecular systematics. In cases where lineages have not reached reciprocal monophyly, defining taxonomic entities is not a straightforward issue [11]. Therefore caution is necessary, especially in a group where accurate identification of taxa is fundamentally linked to public health issues.

Conclusions

Although DNA barcoding is a straightforward approach, it was not applicable for identifying Southern American Triatoma species, which may have diverged recently. Thus, caution should be taken in identifying vector species using this approach, especially in groups where accurate identification of taxa is fundamentally linked to public health issues.

Acknowledgements

We thank Carlos G. Schrago for reviewing our manuscript and for the useful comments.

Footnotes

Competing interests

The authors declare that they have no competing interests.

Authors’ contributions

SAJ designed the study, acquired data, performed all the analyses, interpreted the results, drafted and reviewed the manuscript. CD designed the study, acquired data, performed all the analyses, interpreted the results, drafted and reviewed the manuscript. CG designed the study and reviewed the manuscript. All authors read and approved the final version of the manuscript.

Authors’ information

CD is PhD student funded by Instituto Oswaldo Cruz and SAJ is a Post Doctoral Fellow funded by CNPq.

Contributor Information

Silvia Andrade Justi, Email: silviajusti@ioc.fiocruz.br.

Carolina Dale, Email: dale@ioc.fiocruz.br.

Cleber Galvão, Email: galvao@ioc.fiocruz.br.

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