Dataset Information

Using the RDP classifier to predict taxonomic novelty and reduce the search space for finding novel organisms.

ABSTRACT: BACKGROUND: Currently, the naïve Bayesian classifier provided by the Ribosomal Database Project (RDP) is one of the most widely used tools to classify 16S rRNA sequences, mainly collected from environmental samples. We show that RDP has 97+% assignment accuracy and is fast for 250 bp and longer reads when the read originates from a taxon known to the database. Because most environmental samples will contain organisms from taxa whose 16S rRNA genes have not been previously sequenced, we aim to benchmark how well the RDP classifier and other competing methods can discriminate these novel taxa from known taxa. PRINCIPAL FINDINGS: Because each fragment is assigned a score (containing likelihood or confidence information such as the boostrap score in the RDP classifier), we "train" a threshold to discriminate between novel and known organisms and observe its performance on a test set. The threshold that we determine tends to be conservative (low sensitivity but high specificity) for naïve Bayesian methods. Nonetheless, our method performs better with the RDP classifier than the other methods tested, measured by the f-measure and the area-under-the-curve on the receiver operating characteristic of the test set. By constraining the database to well-represented genera, sensitivity improves 3-15%. Finally, we show that the detector is a good predictor to determine novel abundant taxa (especially for finer levels of taxonomy where novelty is more likely to be present). CONCLUSIONS: We conclude that selecting a read-length appropriate RDP bootstrap score can significantly reduce the search space for identifying novel genera and higher levels in taxonomy. In addition, having a well-represented database significantly improves performance while having genera that are "highly" similar does not make a significant improvement. On a real dataset from an Amazon Terra Preta soil sample, we show that the detector can predict (or correlates to) whether novel sequences will be assigned to new taxa when the RDP database "doubles" in the future.

SUBMITTER: Lan Y

PROVIDER: S-EPMC3293824 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Using the RDP classifier to predict taxonomic novelty and reduce the search space for finding novel organisms.

Lan Yemin Y Wang Qiong Q Cole James R JR Rosen Gail L GL

PloS one 20120305 3

<h4>Background</h4>Currently, the naïve Bayesian classifier provided by the Ribosomal Database Project (RDP) is one of the most widely used tools to classify 16S rRNA sequences, mainly collected from environmental samples. We show that RDP has 97+% assignment accuracy and is fast for 250 bp and longer reads when the read originates from a taxon known to the database. Because most environmental samples will contain organisms from taxa whose 16S rRNA genes have not been previously sequenced, we ai ...[more]

PMID: 22403664

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Project description:Several cyanobacterial species are dominant primary producers in hot spring microbial mats. To date, hot spring cyanobacterial taxonomy, as well as the evolution of their genomic adaptations to high temperatures, are poorly understood, with genomic information currently available for only a few dominant genera, including Fischerella and Synechococcus. To address this knowledge gap, the present study expands the genomic landscape of hot spring cyanobacteria and traces the phylum-wide genomic consequences of evolution in high temperature environments. From 21 globally distributed hot spring metagenomes, with temperatures between 32 and 75°C, 57 medium- and high-quality cyanobacterial metagenome-assembled genomes were recovered, representing taxonomic novelty for 1 order, 3 families, 15 genera and 36 species. Comparative genomics of 93 hot spring genomes (including the 57 metagenome-assembled genomes) and 66 non-thermal genomes, showed that the former have smaller genomes and a higher GC content, as well as shorter proteins that are more hydrophilic and basic, when compared to the non-thermal genomes. Additionally, the core accessory orthogroups from the hot spring genomes of some genera had a greater abundance of functional categories, such as inorganic ion metabolism, translation and post-translational modifications. Moreover, hot spring genomes showed increased abundances of inorganic ion transport and amino acid metabolism, as well as less replication and transcription functions in the protein coding sequences. Furthermore, they showed a higher dependence on the CRISPR-Cas defense system against exogenous nucleic acids, and a reduction in secondary metabolism biosynthetic gene clusters. This suggests differences in the cyanobacterial response to environment-specific microbial communities. This phylum-wide study provides new insights into cyanobacterial genomic adaptations to a specific niche where they are dominant, which could be essential to trace bacterial evolution pathways in a warmer world, such as the current global warming scenario.

Dataset Information

Using the RDP classifier to predict taxonomic novelty and reduce the search space for finding novel organisms.

Publications

Using the RDP classifier to predict taxonomic novelty and reduce the search space for finding novel organisms.

Similar Datasets

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