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Does a barcoding gap exist in prokaryotes? Evidences from species delimitation in cyanobacteria.

Eckert EM, Fontaneto D, Coci M, Callieri C - Life (Basel) (2014)

Bottom Line: Nevertheless, the application of predetermined threshold in genetic distances to identify units of diversity (Operative Taxonomic Units, OTUs) may provide biased results.The application of a tool developed for animal DNA taxonomy, the Automatic Barcode Gap Detector (ABGD), revealed that a barcoding gap could actually be found in almost half of the datasets that we tested.The identification of units of diversity through this method provided results that were not compatible with those obtained with the identification of OTUs with threshold of similarity in genetic distances of 97% or 99%.

View Article: PubMed Central - PubMed

Affiliation: Microbial Ecology Group, Institute of Ecosystem Study, National Research Council, Largo Tonolli 50, 28922 Verbania, Italy. e.eckert@ise.cnr.it.

ABSTRACT
The amount of information that is available on 16S rRNA sequences for prokaryotes thanks to high-throughput sequencing could allow a better understanding of diversity. Nevertheless, the application of predetermined threshold in genetic distances to identify units of diversity (Operative Taxonomic Units, OTUs) may provide biased results. Here we tests for the existence of a barcoding gap in several groups of Cyanobacteria, defining units of diversity according to clear differences between within-species and among-species genetic distances in 16S rRNA. The application of a tool developed for animal DNA taxonomy, the Automatic Barcode Gap Detector (ABGD), revealed that a barcoding gap could actually be found in almost half of the datasets that we tested. The identification of units of diversity through this method provided results that were not compatible with those obtained with the identification of OTUs with threshold of similarity in genetic distances of 97% or 99%. The main message of our results is a call for caution in the estimate of diversity from 16S sequences only, given that different subjective choices in the method to delimit units could provide different results.

No MeSH data available.


Related in: MedlinePlus

Plot of the distribution of pairwise genetic distances in six of the 16 datasets. The three datasets on the left (A–C) provided evidence of a barcoding gap through Automatic Barcode Gap Detector (ABGD), whereas no barcoding gap could be found the three datasets on the right (D–F). Note the different scale bars of the figures.
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life-05-00050-f002: Plot of the distribution of pairwise genetic distances in six of the 16 datasets. The three datasets on the left (A–C) provided evidence of a barcoding gap through Automatic Barcode Gap Detector (ABGD), whereas no barcoding gap could be found the three datasets on the right (D–F). Note the different scale bars of the figures.

Mentions: All 16 datasets were tested to see whether the presence of a barcoding gap could be identified. For seven of the 16 tested datasets a barcoding gap could be identified (Table 1, Figure 2, Figure S2) and the sequences could thus be grouped into species. The barcoding gap existed for example in Planktothrix, Fischerella and Arthrospira (Figure 2), whereas it was not found for Anabaena-Aphanizomenon, Microcystis and Tychonema-Microcoleus.


Does a barcoding gap exist in prokaryotes? Evidences from species delimitation in cyanobacteria.

Eckert EM, Fontaneto D, Coci M, Callieri C - Life (Basel) (2014)

Plot of the distribution of pairwise genetic distances in six of the 16 datasets. The three datasets on the left (A–C) provided evidence of a barcoding gap through Automatic Barcode Gap Detector (ABGD), whereas no barcoding gap could be found the three datasets on the right (D–F). Note the different scale bars of the figures.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4390840&req=5

life-05-00050-f002: Plot of the distribution of pairwise genetic distances in six of the 16 datasets. The three datasets on the left (A–C) provided evidence of a barcoding gap through Automatic Barcode Gap Detector (ABGD), whereas no barcoding gap could be found the three datasets on the right (D–F). Note the different scale bars of the figures.
Mentions: All 16 datasets were tested to see whether the presence of a barcoding gap could be identified. For seven of the 16 tested datasets a barcoding gap could be identified (Table 1, Figure 2, Figure S2) and the sequences could thus be grouped into species. The barcoding gap existed for example in Planktothrix, Fischerella and Arthrospira (Figure 2), whereas it was not found for Anabaena-Aphanizomenon, Microcystis and Tychonema-Microcoleus.

Bottom Line: Nevertheless, the application of predetermined threshold in genetic distances to identify units of diversity (Operative Taxonomic Units, OTUs) may provide biased results.The application of a tool developed for animal DNA taxonomy, the Automatic Barcode Gap Detector (ABGD), revealed that a barcoding gap could actually be found in almost half of the datasets that we tested.The identification of units of diversity through this method provided results that were not compatible with those obtained with the identification of OTUs with threshold of similarity in genetic distances of 97% or 99%.

View Article: PubMed Central - PubMed

Affiliation: Microbial Ecology Group, Institute of Ecosystem Study, National Research Council, Largo Tonolli 50, 28922 Verbania, Italy. e.eckert@ise.cnr.it.

ABSTRACT
The amount of information that is available on 16S rRNA sequences for prokaryotes thanks to high-throughput sequencing could allow a better understanding of diversity. Nevertheless, the application of predetermined threshold in genetic distances to identify units of diversity (Operative Taxonomic Units, OTUs) may provide biased results. Here we tests for the existence of a barcoding gap in several groups of Cyanobacteria, defining units of diversity according to clear differences between within-species and among-species genetic distances in 16S rRNA. The application of a tool developed for animal DNA taxonomy, the Automatic Barcode Gap Detector (ABGD), revealed that a barcoding gap could actually be found in almost half of the datasets that we tested. The identification of units of diversity through this method provided results that were not compatible with those obtained with the identification of OTUs with threshold of similarity in genetic distances of 97% or 99%. The main message of our results is a call for caution in the estimate of diversity from 16S sequences only, given that different subjective choices in the method to delimit units could provide different results.

No MeSH data available.


Related in: MedlinePlus