Dataset Information

TaxI: a software tool for DNA barcoding using distance methods.

ABSTRACT: DNA barcoding is a promising approach to the diagnosis of biological diversity in which DNA sequences serve as the primary key for information retrieval. Most existing software for evolutionary analysis of DNA sequences was designed for phylogenetic analyses and, hence, those algorithms do not offer appropriate solutions for the rapid, but precise analyses needed for DNA barcoding, and are also unable to process the often large comparative datasets. We developed a flexible software tool for DNA taxonomy, named TaxI. This program calculates sequence divergences between a query sequence (taxon to be barcoded) and each sequence of a dataset of reference sequences defined by the user. Because the analysis is based on separate pairwise alignments this software is also able to work with sequences characterized by multiple insertions and deletions that are difficult to align in large sequence sets (i.e. thousands of sequences) by multiple alignment algorithms because of computational restrictions. Here, we demonstrate the utility of this approach with two datasets of fish larvae and juveniles from Lake Constance and juvenile land snails under different models of sequence evolution. Sets of ribosomal 16S rRNA sequences, characterized by multiple indels, performed as good as or better than cox1 sequence sets in assigning sequences to species, demonstrating the suitability of rRNA genes for DNA barcoding.

SUBMITTER: Steinke D

PROVIDER: S-EPMC1609227 | biostudies-literature | 2005 Oct

REPOSITORIES: biostudies-literature

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TaxI: a software tool for DNA barcoding using distance methods.

Steinke Dirk D Vences Miguel M Salzburger Walter W Meyer Axel A

Philosophical transactions of the Royal Society of London. Series B, Biological sciences 20051001 1462

DNA barcoding is a promising approach to the diagnosis of biological diversity in which DNA sequences serve as the primary key for information retrieval. Most existing software for evolutionary analysis of DNA sequences was designed for phylogenetic analyses and, hence, those algorithms do not offer appropriate solutions for the rapid, but precise analyses needed for DNA barcoding, and are also unable to process the often large comparative datasets. We developed a flexible software tool for DNA ...[more]

PMID: 16214755

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Project description:In Australia, Poaceae tribe Poeae are represented by 19 genera and 99 species, including economically and environmentally important native and introduced pasture grasses [e.g. Poa (Tussock-grasses) and Lolium (Ryegrasses)]. We used this tribe, which are well characterised in regards to morphological diversity and evolutionary relationships, to test the efficacy of DNA barcoding methods. A reference library was generated that included 93.9% of species in Australia (408 individuals, [Formula: see text] = 3.7 individuals per species). Molecular data were generated for official plant barcoding markers (rbcL, matK) and the nuclear ribosomal internal transcribed spacer (ITS) region. We investigated accuracy of specimen identifications using distance- (nearest neighbour, best-close match, and threshold identification) and tree-based (maximum likelihood, Bayesian inference) methods and applied species discovery methods (automatic barcode gap discovery, Poisson tree processes) based on molecular data to assess congruence with recognised species. Across all methods, success rate for specimen identification of genera was high (87.5-99.5%) and of species was low (25.6-44.6%). Distance- and tree-based methods were equally ineffective in providing accurate identifications for specimens to species rank (26.1-44.6% and 25.6-31.3%, respectively). The ITS marker achieved the highest success rate for specimen identification at both generic and species ranks across the majority of methods. For distance-based analyses the best-close match method provided the greatest accuracy for identification of individuals with a high percentage of "correct" (97.6%) and a low percentage of "incorrect" (0.3%) generic identifications, based on the ITS marker. For tribe Poeae, and likely for other grass lineages, sequence data in the standard DNA barcode markers are not variable enough for accurate identification of specimens to species rank. For recently diverged grass species similar challenges are encountered in the application of genetic and morphological data to species delimitations, with taxonomic signal limited by extensive infra-specific variation and shared polymorphisms among species in both data types.

Project description:BACKGROUND:DNA barcoding has recently been proposed as a promising tool for the rapid species identification in a wide range of animal taxa. Two broad methods (distance and monophyly-based methods) have been used. One method is based on degree of DNA sequence variation within and between species while another method requires the recovery of species as discrete clades (monophyly) on a phylogenetic tree. Nevertheless, some issues complicate the use of both methods. A recently applied new technique, the character-based DNA barcode method, however, characterizes species through a unique combination of diagnostic characters. METHODOLOGY/PRINCIPAL FINDINGS:Here we analyzed 108 COI and 102 16S rDNA sequences of 40 species of Neogastropoda from a wide phylogenetic range to assess the performance of distance, monophyly and character-based methods of DNA barcoding. The distance-based method for both COI and 16S rDNA genes performed poorly in terms of species identification. Obvious overlap between intraspecific and interspecific divergences for both genes was found. The "10× rule" threshold resulted in lumping about half of distinct species for both genes. The neighbour-joining phylogenetic tree of COI could distinguish all species studied. However, the 16S rDNA tree could not distinguish some closely related species. In contrast, the character-based barcode method for both genes successfully identified 100% of the neogastropod species included, and performed well in discriminating neogastropod genera. CONCLUSIONS/SIGNIFICANCE:This present study demonstrates the effectiveness of the character-based barcoding method for species identification in different taxonomic levels, especially for discriminating the closely related species. While distance and monophyly-based methods commonly use COI as the ideal gene for barcoding, the character-based approach can perform well for species identification using relatively conserved gene markers (e.g., 16S rDNA in this study). Nevertheless, distance and monophyly-based methods, especially the monophyly-based method, can still be used to flag species.

Dataset Information

TaxI: a software tool for DNA barcoding using distance methods.

Publications

TaxI: a software tool for DNA barcoding using distance methods.

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