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Ribosomal RNA

About: Ribosomal RNA is a research topic. Over the lifetime, 21459 publications have been published within this topic receiving 984877 citations. The topic is also known as: rRNA & ribosomal RNA.


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Journal ArticleDOI
TL;DR: A set of oligonucleotide primers capable of initiating enzymatic amplification (polymerase chain reaction) on a phylogenetically and taxonomically wide range of bacteria is described in this paper.
Abstract: A set of oligonucleotide primers capable of initiating enzymatic amplification (polymerase chain reaction) on a phylogenetically and taxonomically wide range of bacteria is described along with methods for their use and examples. One pair of primers is capable of amplifying nearly full-length 16S ribosomal DNA (rDNA) from many bacterial genera; the additional primers are useful for various exceptional sequences. Methods for purification of amplified material, direct sequencing, cloning, sequencing, and transcription are outlined. An obligate intracellular parasite of bovine erythrocytes, Anaplasma marginale, is used as an example; its 16S rDNA was amplified, cloned, sequenced, and phylogenetically placed. Anaplasmas are related to the genera Rickettsia and Ehrlichia. In addition, 16S rDNAs from several species were readily amplified from material found in lyophilized ampoules from the American Type Culture Collection. By use of this method, the phylogenetic study of extremely fastidious or highly pathogenic bacterial species can be carried out without the need to culture them. In theory, any gene segment for which polymerase chain reaction primer design is possible can be derived from a readily obtainable lyophilized bacterial culture.

10,245 citations

Journal ArticleDOI
TL;DR: 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.
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.

5,733 citations

Journal ArticleDOI
TL;DR: The results of this study may be used as a guideline for selecting primer pairs with the best overall coverage and phylum spectrum for specific applications, therefore reducing the bias in PCR-based microbial diversity studies.
Abstract: 16S ribosomal RNA gene (rDNA) amplicon analysis remains the standard approach for the cultivation-independent investigation of microbial diversity. The accuracy of these analyses depends strongly on the choice of primers. The overall coverage and phylum spectrum of 175 primers and 512 primer pairs were evaluated in silico with respect to the SILVA 16S/18S rDNA non-redundant reference dataset (SSURef 108 NR). Based on this evaluation a selection of 'best available' primer pairs for Bacteria and Archaea for three amplicon size classes (100-400, 400-1000, ≥ 1000 bp) is provided. The most promising bacterial primer pair (S-D-Bact-0341-b-S-17/S-D-Bact-0785-a-A-21), with an amplicon size of 464 bp, was experimentally evaluated by comparing the taxonomic distribution of the 16S rDNA amplicons with 16S rDNA fragments from directly sequenced metagenomes. The results of this study may be used as a guideline for selecting primer pairs with the best overall coverage and phylum spectrum for specific applications, therefore reducing the bias in PCR-based microbial diversity studies.

5,346 citations

Journal ArticleDOI
TL;DR: Results from running RNAmmer on a large set of genomes indicate that the location of rRNAs can be predicted with a very high level of accuracy.
Abstract: The publication of a complete genome sequence is usually accompanied by annotations of its genes. In contrast to protein coding genes, genes for ribosomal RNA (rRNA) are often poorly or inconsistently annotated. This makes comparative studies based on rRNA genes difficult. We have therefore created computational predictors for the major rRNA species from all kingdoms of life and compiled them into a program called RNAmmer. The program uses hidden Markov models trained on data from the 5S ribosomal RNA database and the European ribosomal RNA database project. A pre-screening step makes the method fast with little loss of sensitivity, enabling the analysis of a complete bacterial genome in less than a minute. Results from running RNAmmer on a large set of genomes indicate that the location of rRNAs can be predicted with a very high level of accuracy. Novel, unannotated rRNAs are also predicted in many genomes. The software as well as the genome analysis results are available at the CBS web server.

4,949 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023400
2022849
2021487
2020547
2019487
2018435