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. 2016 Mar:122:38-42.
doi: 10.1016/j.mimet.2016.01.011. Epub 2016 Jan 23.

Studying long 16S rDNA sequences with ultrafast-metagenomic sequence classification using exact alignments (Kraken)

Fabiola Valenzuela-González  1 , Marcel Martínez-Porchas  2 , Enrique Villalpando-Canchola  2 , Francisco Vargas-Albores  3
Affiliations

Studying long 16S rDNA sequences with ultrafast-metagenomic sequence classification using exact alignments (Kraken)

Fabiola Valenzuela-González et al. J Microbiol Methods. 2016 Mar.

Abstract

Ultrafast-metagenomic sequence classification using exact alignments (Kraken) is a novel approach to classify 16S rDNA sequences. The classifier is based on mapping short sequences to the lowest ancestor and performing alignments to form subtrees with specific weights in each taxon node. This study aimed to evaluate the classification performance of Kraken with long 16S rDNA random environmental sequences produced by cloning and then Sanger sequenced. A total of 480 clones were isolated and expanded, and 264 of these clones formed contigs (1352 ± 153 bp). The same sequences were analyzed using the Ribosomal Database Project (RDP) classifier. Deeper classification performance was achieved by Kraken than by the RDP: 73% of the contigs were classified up to the species or variety levels, whereas 67% of these contigs were classified no further than the genus level by the RDP. The results also demonstrated that unassembled sequences analyzed by Kraken provide similar or inclusively deeper information. Moreover, sequences that did not form contigs, which are usually discarded by other programs, provided meaningful information when analyzed by Kraken. Finally, it appears that the assembly step for Sanger sequences can be eliminated when using Kraken. Kraken cumulates the information of both sequence senses, providing additional elements for the classification. In conclusion, the results demonstrate that Kraken is an excellent choice for use in the taxonomic assignment of sequences obtained by Sanger sequencing or based on third generation sequencing, of which the main goal is to generate larger sequences.

Keywords: 16S metagenomics; Classification methods; Kraken applications; Long 16S rDNA sequences; Metagenomic sequence classification; Taxonomic classification.

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