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.
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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