SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB

Abstract

Sequencing ribosomal RNA (rRNA) genes is currently the method of choice for phylogenetic reconstruction, nucleic acid based detection and quantification of microbial diversity. The ARB software suite with its corresponding rRNA datasets has been accepted by researchers worldwide as a standard tool for large scale rRNA analysis. However, the rapid increase of publicly available rRNA sequence data has recently hampered the maintenance of comprehensive and curated rRNA knowledge databases. A new system, SILVA (from Latin silva, forest), was implemented to provide a central comprehensive web resource for up to date, quality controlled databases of aligned rRNA sequences from the Bacteria, Archaea and Eukarya domains. All sequences are checked for anomalies, carry a rich set of sequence associated contextual information, have multiple taxonomic classifications, and the latest validly described nomenclature. Furthermore, two precompiled sequence datasets compatible with ARB are offered for download on the SILVA website: (i) the reference (Ref) datasets, comprising only high quality, nearly full length sequences suitable for in-depth phylogenetic analysis and probe design and (ii) the comprehensive Parc datasets with all publicly available rRNA sequences longer than 300 nucleotides suitable for biodiversity analyses. The latest publicly available database release 91 (August 2007) hosts 547 521 sequences split into 461 823 small subunit and 85 689 large subunit rRNAs.

Dominance of Endozoicomonas bacteria throughout coral bleaching and mortality suggests structural inflexibility of the Pocillopora verrucosa microbiome

“…This resulted in 12,041,000 sequences distributed over 36 coral fragments [3 coral replicates × 4 conditions (control vs. DOC; control vs. DON) × 3 time points] and 36 water samples [3 seawater replicates × 4 conditions (control vs. DOC; control vs. DON) × 3 time points]. Remaining sequences were aligned against the SILVA database (release 119; Pruesse et al., 2007)) and preclustered (2 bp difference; Huse, Welch, Morrison, & Sogin, 2010). Chimeric sequences were removed using the UCHIME command (Edgar et al., 2011).…”

Inter-comparison of the potentially active prokaryotic communities in the halocline sediments of Mediterranean deep-sea hypersaline basins

“…sequences that appeared only once in the whole dataset, were excluded from further analysis. The remaining sequences were aligned using the SILVA SSU database (release 108, Pruesse et al, 2007). All sequences were binned into Operational Taxonomic Units (OTUs) and were clustered (average neighbor algorithm) at 97% sequence similarity (Stackebrandt andGoebel, 1994, Kunin et al, 2010).…”

Molecular characterization of microbial communities in the rhizosphere soils and roots of diseased and healthy Panax notoginseng

“…After the same data preprocessing, 276,360 bacterial sequences (ranging from 952 to 22,785 sequences per sample) and 121,357 fungal sequences (ranging from 708 to 9771 sequences per sample) from root samples were used for further analysis. For bacteria, after removal of primers, all sequences were aligned with the Silva-ARB database (version 119, Pruesse et al 2007). After chimeras were removed, all sequences were clustered into operational taxonomic units (OTUs) at 97 % identity threshold by using the unsupervised Bayesian clustering algorithm CROP (Hao et al 2011), and all OTUs were included in downstream analyses.…”