Metaxa: Automated detection and discrimination among ribosomal small subunit (12S/16S/18S) sequences of archaea, bacteria, eukaryotes, mitochondria, and chloroplasts
Conference poster, 2011

The ribosomal small subunit (SSU) rRNA gene has emerged as an important genetic marker for taxonomic identification in environmental sequencing datasets. However, the gene is not only present in the nuclear genome of eukaryotes and the core genome of prokaryotes, but also in the mitochondria and chloroplasts of eukaryotes. The SSU genes in the core genome, mitochondria and chloroplast are conceptually paralogous and should in most situations not be aligned and analyzed jointly, e.g. when estimating species diversity. Identifying the origin of SSU sequences in complex sequence datasets is a time-consuming and largely manual undertaking. To ease this situation, we have created Metaxa, an automated software tool to extract full-length and partial SSU sequences from larger sequence datasets and assign them to an archaeal, bacte- rial, nuclear eukaryote, mitochondrial, or chloroplast origin. Metaxa very efficiently detects SSU sequences from fragments as short as 200 base pairs, and correctly classifies 97% of the identified genes at read lengths typically obtained from pyrosequencing. In addition, Metaxa shows a false positive rate of 0.00012% when run on random DNA fragments, showing the robustness of the method. We believe that this tool will be useful in microbial and evolutionary ecology as well as in metagenomics.

SSU extraction

taxonomic assignment

16S extraction

rRNA extraction

Author

Johan Bengtsson

University of Gothenburg

Martin Eriksson

University of Gothenburg

Martin Hartmann

Belle D Shenoy

G Grelet

Kessy Abarenkov

Anna Petri

University of Gothenburg

Magnus Alm Rosenblad

University of Gothenburg

R. Henrik Nilsson

University of Gothenburg

SocBiN Bioinformatics Conference, Helsinki, Finland, 2011

Subject Categories

Microbiology

Bioinformatics and Systems Biology

More information

Created

10/10/2017