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Review
. 2005 Oct 29;360(1462):1905-16.
doi: 10.1098/rstb.2005.1722.

The unholy trinity: taxonomy, species delimitation and DNA barcoding

Rob DeSalle  1 , Mary G Egan, Mark Siddall
Affiliations
Review

The unholy trinity: taxonomy, species delimitation and DNA barcoding

Rob DeSalle et al. Philos Trans R Soc Lond B Biol Sci. .

Abstract

Recent excitement over the development of an initiative to generate DNA sequences for all named species on the planet has in our opinion generated two major areas of contention as to how this 'DNA barcoding' initiative should proceed. It is critical that these two issues are clarified and resolved, before the use of DNA as a tool for taxonomy and species delimitation can be universalized. The first issue concerns how DNA data are to be used in the context of this initiative; this is the DNA barcode reader problem (or barcoder problem). Currently, many of the published studies under this initiative have used tree building methods and more precisely distance approaches to the construction of the trees that are used to place certain DNA sequences into a taxonomic context. The second problem involves the reaction of the taxonomic community to the directives of the 'DNA barcoding' initiative. This issue is extremely important in that the classical taxonomic approach and the DNA approach will need to be reconciled in order for the 'DNA barcoding' initiative to proceed with any kind of community acceptance. In fact, we feel that DNA barcoding is a misnomer. Our preference is for the title of the London meetings--Barcoding Life. In this paper we discuss these two concerns generated around the DNA barcoding initiative and attempt to present a phylogenetic systematic framework for an improved barcoder as well as a taxonomic framework for interweaving classical taxonomy with the goals of 'DNA barcoding'.

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Figures

Figure 1
Figure 1
Hypothetical example of character based diagnosis (Davis & Nixon 1992) in action. The twelve sequences represent two populations of six individuals each. The solid line through the middle of the matrix represents a geographical barrier between the two populations. A. DNA sequence attributes in these columns are purely diagnostic characters (sensu Davis & Nixon 1992). B. DNA sequence attributes in this column are not purely diagnostic, but rather the G in the three individuals in the top population are ‘private’ to that population. C. The DNA sequence attributes in the two columns by themselves constitute two private DNA positions. However, in combination these two columns provide a ‘pure’ diagnostic combination (AA versus AG or GA; ‘compound pure’ character in the terminology of Sarkar et al. 2002). D. The four columns marked by the shading for D are neither diagnostic nor private. Yet in combination the four columns provide a diagnostic system for the top population versus the bottom. The top population is diagnosed by GA, AG/GA, AG for the four columns.
Figure 2
Figure 2
The taxonomic circle. The dotted lines that traverse the inner part of the circle indicate experimental routes that can be taken in taxonomic endeavour to accomplish corroboration of taxonomic hypotheses. The only way to delineate a new taxon is to break out of the circle (the solid arrows emanating from the circle). In our scheme, it only takes one traversal of the interior of the taxonomic circle where corroboration occurs in order for the taxonomist to ‘break out’ of the circle and designate a taxon. Examples of use of the taxonomic circle using hypothetical examples. A. Classical morphological taxonomy; a taxonomic hypothesis is established on the basis of organisms appearing to be similar at a particular geographic locality. The taxonomic hypothesis is tested with morphological information and corroborated with the morphological attributes. The morphological attributes then become diagnostic characters if they corroborate the geographical hypothesis. B. Cryptic species in taxonomy; a geographical hypothesis is posed and tested with morphology. The morphological attributes collected do not corroborate the geographical hypothesis and hence the taxonomist cannot ‘break out’ of the circle. Retaining the geographical hypothesis the taxonomist then examines the aggregates established using the geographical hypothesis with DNA sequence data and corroboration ensues with DNA sequence characters being diagnostic. C. Sympatric species in taxonomy; morphological differences are recognized among a group of organisms. A hypothesis of aggregation is posited based on the morphological information. When geographical distributions are used to test the aggregation patterns, there is no geographic pattern to the distribution of the different morphological types. The taxonomist then uses DNA sequence attributes to test the morphological hypothesis of aggregation and corroborates the morphological hypothesis and the taxonomist ‘breaks out’ of the circle. D. Failure to detect a new taxon; in this example, a geographic hypothesis is made and tested with morphological information. The morphological information fails and the geographical and any morphological hypotheses of aggregation are then tested with DNA sequence information. DNA sequence information fails to reject the hypothesis of no new taxa and, hence, the taxonomist cannot ‘break out’ of the circle and the inference is that there are no differentiable aggregates and hence only a single taxon.
Figure 3
Figure 3
A DNA barcoding example for barking deer (genus Muntiacus). The table at the top of the figure shows variable nucleotide positions including several diagnostic sites in the 16s mt rDNA of multiple individuals of muntjac species. DNA from the type specimen of Muntiacus rooseveltorum was compared to recently collected putative M. rooseveltorum specimens to clarify their nomenclature (Amato et al. 1999). The word Type after the binomial indicates the sequence obtained from the type specimen of M. rooseveltorum. Shaded area indicates nucleotide position diagnostic for M. rooseveltorum. Dots (.) indicate sequence identity to the reference sequence on the first line. Colons (:) indicate missing data. Position 1 in the region sequenced corresponds to position 2305 in the Bos taurus mitochondrial DNA, complete genome (GenBank Accession Number: AB074962). Photograph of the skull of the Type specimen of M. rooseveltorum courtesy of the Field Museum of Natural History (Field Museum negative number Z82184: Muntiacus rooseveltorum Zoology specimen 31783), is used with permission. The graphic in the centre shows the multiple gene region barcode for M. rooseveltorum separated by right brackets; reading from left to right, it shows the diagnostic nucleotides and position numbers found in the mitochondrial gene regions: 16s, cytochrome b, 12s and D loop.
Figure 4
Figure 4
A DNA barcoding example from the leech species Helobdella europaea (Glossiphoniidae). The table shows diagnostic sites for Helobdella europaea (figured at top). Diagnostic characters, reading left to right, are position numbers 273, 471 and 501 in cox1, and 1160 in ND1. DNA barcoding of a broad geographic sampling along with morphological dissections and comparison to described species allowed Siddall & Budinoff (2005) to clarify the nomenclature of this species and shed light on possible explanations for an unexpected geographic distribution.
Figure 5
Figure 5
Diagnostic sites in cox1 for Hirudo verbana (position numbers: 267, 360, 507, 513, 543, and 579). A leech obtained from Ward's Biological for this study and shipped under the name of ‘Hirudo medicinalis’ unequivocally groups with Hirudo verbana. Also, both Black et al. (1997) and Siddall & Burreson (1998) obtained their representatives of Hirudo medicinalis from Carolina Biological supply, and both of those sequences group with the Asian Hirudinaria manillensis notwithstanding the fact that the specimen used by Siddall & Burreson (1998) is morphologically indistinguishable from H. verbana.
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