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
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
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DOI：
10.1007/s10482-011-9598-6
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发表时间：
2011-10-01
影响因子：
2.6
通讯作者：
Nilsson, R. Henrik
中科院分区：
文献类型：
--
作者：
Bengtsson, Johan;Eriksson, K. Martin;Nilsson, R. Henrik
核糖体小亚单位（SSU） rRNA基因已成为环境测序数据集中分类鉴定的重要遗传标记。除了存在于真核生物的细胞核和原核生物的核心基因组中，该基因还存在于真核生物的线粒体和光合真核生物的叶绿体中。这三组基因在概念上是平行的，在大多数情况下不应该对齐和分析。迄今为止，在复杂的序列数据集中识别SSU序列的起源是一项耗时且主要是手工的工作。然而，本研究介绍了mettaxa （http://microbiology）。se/software/metaxa/)是一个自动化的软件工具，用于从较大的序列数据集中提取全长和部分SSU序列，并将其分配给古细菌，细菌，核真核生物，线粒体或叶绿体起源。利用参考数据库和全长细胞器和生物体基因组的数据，我们发现Metaxa检测和评分SSU序列的起源，假阳性和阴性的比例非常低。我们相信该工具将在微生物和进化生态学以及宏基因组学中发挥作用。
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.