Metaxa: a software tool for automated detection and discrimination among ribosomal small subunit (12S/16S/18S) sequences of archaea, bacteria, eukaryotes, mitochondria, and chloroplasts in metagenomes and environmental sequencing datasets
Artikel i vetenskaplig tidskrift, 2011

The ribosomal small subunit (SSU) rRNA gene has emerged as an important genetic marker for taxonomic identification in environmental sequencing datasets. In addition to being present in the nucleus of eukaryotes and the core genome of prokaryotes, the gene is also found in the mitochondria of eukaryotes and in the chloroplasts of photosynthetic eukaryotes. These three sets of genes are conceptually paralogous and should in most situations not be aligned and analyzed jointly. To identify the origin of SSU sequences in complex sequence datasets has hitherto been a time-consuming and largely manual undertaking. However, the present study introduces Metaxa (http://microbiology.se/software/metaxa/), an automated software tool to extract full-length and partial SSU sequences from larger sequence datasets and assign them to an archaeal, bacterial, nuclear eukaryote, mitochondrial, or chloroplast origin. Using data from reference databases and from full-length organelle and organism genomes, we show that Metaxa detects and scores SSU sequences for origin with very low proportions of false positives and negatives. We believe that this tool will be useful in microbial and evolutionary ecology as well as in metagenomics.

Mikrobiella samhällen

Metagenomik

Phylogenetic assignment

Microbial communities

rRNA libraries

rRNA-bibliotek

Metagenomics

Författare

Johan Bengtsson

Göteborgs universitet

Martin Eriksson

Göteborgs universitet

Martin Hartmann

Wang Zheng

Belle Damodara Shenoy

Gwen-Aëlle Grelet

Kessy Abarenkov

Anna Petri

Göteborgs universitet

Magnus Alm Rosenblad

Göteborgs universitet

R. Henrik Nilsson

Göteborgs universitet

Antonie van Leeuwenhoek, International Journal of General and Molecular Microbiology

0003-6072 (ISSN) 1572-9699 (eISSN)

Vol. 100 3 471-475

Ämneskategorier

Ekologi

Mikrobiologi

Mikrobiologi inom det medicinska området

Bioinformatik och systembiologi

DOI

10.1007/s10482-011-9598-6

PubMed

21674231