Defining operational taxonomic units using DNA barcode data

Abstract

The scale of diversity of life on this planet is a significant challenge for any scientific programme hoping to produce a complete catalogue, whatever means is used. For DNA barcoding studies, this difficulty is compounded by the realization that any chosen barcode sequence is not the gene 'for' speciation and that taxa have evolutionary histories. How are we to disentangle the confounding effects of reticulate population genetic processes? Using the DNA barcode data from meiofaunal surveys, here we discuss the benefits of treating the taxa defined by barcodes without reference to their correspondence to 'species', and suggest that using this non-idealist approach facilitates access to taxon groups that are not accessible to other methods of enumeration and classification. Major issues remain, in particular the methodologies for taxon discrimination in DNA barcode data.

Figure 1

The MOTU_define.pl system. (a) A schematic of the process by which MOTU_define.pl allocates sequences to MOTU. The process can be run any number of times with different sequence addition order to assess MOTU stability. (b) The effect of addition order on MOTU definition. Three sequences, A, B and C, are clustered into MOTU. A differs from B, and B from C by less than the MOTU discriminant cutoff, but C differs from A by more than the cutoff. Depending on the order of analysis of the sequences, either one or two MOTU will be defined.

Figure 2

Meiofaunal MOTU defined using nuclear SSU sequences. The bulk nSSU dataset (Bulk) and a corresponding single specimen dataset (Sin) from the same moss sample were clustered into MOTU separately using a 2 bp cutoff, and consensus sequences predicted for those MOTU with more than one member. The consensus sequences and the singleton MOTU sequences were aligned and analysed using parsimony. For each MOTU represented the number of constituent sequences is given in brackets, and the taxonomic assignment based on BLAST search similarity to database sequences is given in bold. Where a taxon is identified below the major group, the MOTU sequence nested within a clade of sequences with the more specific designation (data not shown). Inferred numbers of changes are shown above each branch. Note that the tree is unrooted.

Figure 3

Tardigrade MOTU defined using cox1 sequences. (a) A consensus sequence was derived for each MOTU, and these were aligned. The branch lengths are proportional to the number of discrete changes mapped to each. The number of sequences assigned to each MOTU is given in brackets after the MOTU name. (b) Histogram of MOTU abundance in the 121-sequence cox1 dataset.

Figure 4

Comparison of MOTU definition using nSSU and cox1 markers. This Venn diagram shows cox1 MOTU sets (solid circles) and nSSU MOTU sets (dotted squares). The numbers within each partition indicate the number of individual specimens (out of 82) placed there.

Figure 5

Variability in the number of MOTU defined by replicate analyses. The histogram shows the frequency distribution of total numbers of clusters inferred from 295 tardigrade nSSU sequences from the Glen Ettrick study site using MOTU_define.pl at three different cut off values: 2 bp (black), 3 bp (hatched) and 4 bp (open). The mean and standard deviation of each set of analyses is given.