16S ribosomal RNA

RNA component the mitochondrially encoded 16S LSU RNA MT-RNR2 Bacterial small subunit ribosomal RNA File:16S.svg SSU Ribosomal RNA, bacteria and archaea. From Woese 1987. Woese CR Bacterial evolution Microbiological Reviews 51 2 221–271 June 1987 2439888 373105 10.1128/MR.51.2.221-271.1987 Gene; rRNA SSU_rRNA_bacteria RF00177 Bacteria Archaeal small subunit ribosomal RNA Gene; rRNA SSU_rRNA_archaea RF01959 Bacteria thumb|Molecular structure of the 30S subunit from Thermus thermophilus. Proteins are shown in blue and the single RNA strand in a pale orange-brown colour. Schluenzen F, Tocilj A, Zarivach R, Harms J, Gluehmann M, Janell D, Bashan A, Bartels H, Agmon I, Franceschi F, Yonath A 6 Structure of functionally activated small ribosomal subunit at 3.3 angstroms resolution Cell 102 5 615–623 September 2000 11007480 10.1016/S0092-8674(00)00084-2 1024446 free 16S ribosomal RNA (or 16S rRNA) is the RNA component of the 30S subunit of a prokaryotic ribosome (SSU rRNA). It binds to the Shine-Dalgarno sequence and provides most of the SSU structure. The genes coding for it are referred to as 16S rRNA genes and are used in reconstructing phylogenies, due to the slow rates of evolution of this region of the gene. Woese CR, Fox GE Phylogenetic structure of the prokaryotic domain: the primary kingdoms Proceedings of the National Academy of Sciences of the United States of America 74 11 5088–5090 November 1977 270744 432104 10.1073/pnas.74.11.5088 George E. Fox free 1977PNAS...74.5088W Carl Woese Carl Woese and George E. Fox were two of the people who pioneered the use of 16S rRNA in phylogenetics in 1977. Woese CR, Kandler O, Wheelis ML Towards a natural system of organisms: proposal for the domains Archaea, Bacteria, and Eucarya Proceedings of the National Academy of Sciences of the United States of America 87 12 4576–4579 June 1990 2112744 54159 10.1073/pnas.87.12.4576 free 1990PNAS...87.4576W Carl Woese Multiple sequences of the 16S rRNA gene can exist within a single bacterium. Case RJ, Boucher Y, Dahllöf I, Holmström C, Doolittle WF, Kjelleberg S Use of 16S rRNA and rpoB genes as molecular markers for microbial ecology studies Applied and Environmental Microbiology 73 1 278–288 January 2007 17071787 1797146 10.1128/AEM.01177-06 2007ApEnM..73..278C Terminology The descriptor 16S refers to the size of these ribosomal subunits as reflected indirectly by the speed at which they sediment when samples are centrifuged. Thus 16S means 16 Svedberg units. Functions Like the large (23S) ribosomal RNA, it has a structural role, acting as a scaffold defining the positions of the ribosomal proteins. The 3-end contains the anti-Shine-Dalgarno sequence, which binds upstream to the AUG start codon on the mRNA. The 3-end of 16S RNA binds to the proteins S1 and S21 which are known to be involved in initiation of protein synthesis Czernilofsky AP, Kurland CG, Stöffler G Charles Kurland 30S ribosomal proteins associated with the 3'-terminus of 16S RNA FEBS Letters 58 1 281–284 October 1975 1225593 10.1016/0014-5793(75)80279-1 22941368 free 1975FEBSL..58..281C Interacts with 23S, aiding in the binding of the two ribosomal subunits (50S and 30S) Stabilizes correct codon-anticodon pairing in the A-site by forming a hydrogen bond between the N1 atom of adenine residues 1492 and 1493 and the 2OH group of the mRNA backbone. Universal primers The 16S rRNA gene is used for phylogenetic studies Weisburg WG, Barns SM, Pelletier DA, Lane DJ 16S ribosomal DNA amplification for phylogenetic study Journal of Bacteriology 173 2 697–703 January 1991 1987160 207061 10.1128/jb.173.2.697-703.1991 as it is highly conserved between different species of bacteria and archaea. Coenye T, Vandamme P Intragenomic heterogeneity between multiple 16S ribosomal RNA operons in sequenced bacterial genomes FEMS Microbiology Letters 228 1 45–49 November 2003 14612235 10.1016/S0378-1097(03)00717-1 free Carl Woese pioneered this use of 16S rRNA in 1977. It is suggested that 16S rRNA gene can be used as a reliable molecular clock because 16S rRNA sequences from distantly related bacterial lineages are shown to have similar functionalities. Tsukuda M, Kitahara K, Miyazaki K Comparative RNA function analysis reveals high functional similarity between distantly related bacterial 16 S rRNAs En Scientific Reports 7 1 9993 August 2017 28855596 5577257 10.1038/s41598-017-10214-3 free 2017NatSR...7.9993T Some thermophilic archaea (e.g. order Thermoproteales) contain 16S rRNA gene introns that are located in highly conserved regions and can impact the annealing of "universal" primers. Jay ZJ, Inskeep WP The distribution, diversity, and importance of 16S rRNA gene introns in the order Thermoproteales Biology Direct 10 35 35 July 2015 26156036 4496867 10.1186/s13062-015-0065-6 free Mitochondrial and chloroplastic rRNA are also amplified.Walker Sidney P. Barrett Maurice Hogan Glenn Flores Bueso Yensi Claesson Marcus J. Tangney Mark 2020-10-01 Non-specific amplification of human DNA is a major challenge for 16S rRNA gene sequence analysis Scientific Reports 10 1 16356 10.1038/s41598-020-73403-7 free 2045-2322 7529756 33004967 The most common primer pair was devised by Weisburg et al. (1991) and is currently referred to as 27F and 1492R; however, for some applications shorter amplicons may be necessary, for example for 454 sequencing with titanium chemistry the primer pair 27F-534R covering V1 to V3.http://www.hmpdacc.org/tools_protocols.php#sequencing Human Microbiome Project DACC - Home www.hmpdacc.org https://web.archive.org/web/20101030101644/http://hmpdacc.org/tools_protocols.php 2010-10-30 Often 8F is used rather than 27F. The two primers are almost identical, but 27F has an M instead of a C. AGAGTTTGATCMTGGCTCAG compared with 8F.http://www.lutzonilab.net/primers/page604.shtml Primers, 16S ribosomal DNA - François Lutzoni's Lab lutzonilab.net live https://web.archive.org/web/20121227103440/http://www.lutzonilab.net/primers/page604.shtml 2012-12-27 Primer name Sequence (5–3) Ref. Reference 8F AGA GTT TGA TCC TGG CTC AG Eden PA, Schmidt TM, Blakemore RP, Pace NR Phylogenetic analysis of Aquaspirillum magnetotacticum using polymerase chain reaction-amplified 16S rRNA-specific DNA International Journal of Systematic Bacteriology 41 2 324–325 April 1991 1854644 10.1099/00207713-41-2-324 free PCR for Clinical Microbiology Greg James 15 May 2018 Springer, Dordrecht 209–214 10.1007/978-90-481-9039-3_28 Universal Bacterial Identification by PCR and DNA Sequencing of 16S rRNA Gene 978-90-481-9038-627FAGA GTT TGA TCM TGG CTC AG 336R ACT GCT GCS YCC CGT AGG AGT CT 337F GAC TCC TAC GGG AGG CWG CAG Park Changwoo Kim Seung Bum Choi Sang Ho Kim Seil 2021 Comparison of 16S rRNA Gene Based Microbial Profiling Using Five Next-Generation Sequencers and Various Primers Frontiers in Microbiology 12 715500 10.3389/fmicb.2021.715500 free 34721319 1664-302X 8552068 518R GTA TTA CCG CGG CTG CTG G 533F GTG CCA GCM GCC GCG GTA A 785F GGA TTA GAT ACC CTG GTA 806R GGA CTA CVS GGG TAT CTA AT Eloe-Fadrosh EA, Ivanova NN, Woyke T, Kyrpides NC Metagenomics uncovers gaps in amplicon-based detection of microbial diversity Nature Microbiology 1 4 15032 February 2016 27572438 10.1038/nmicrobiol.2015.32 1379258 27232975 Bergmann GT, Bates ST, Eilers KG, Lauber CL, Caporaso JG, Walters WA, Knight R, Fierer N 6 The under-recognized dominance of Verrucomicrobia in soil bacterial communities Soil Biology & Biochemistry 43 7 1450–1455 July 2011 22267877 3260529 10.1016/j.soilbio.2011.03.012 2011SBiBi..43.1450B 907R CCG TCA ATT CCT TTR AGT TT 928F TAA AAC TYA AAK GAA TTG ACG GG Weidner S, Arnold W, Puhler A Diversity of uncultured microorganisms associated with the seagrass Halophila stipulacea estimated by restriction fragment length polymorphism analysis of PCR-amplified 16S rRNA genes Applied and Environmental Microbiology 62 3 766–771 http://aem.asm.org/cgi/reprint/62/3/766.pdf March 1996 8975607 167844 10.1128/AEM.62.3.766-771.1996 live 1996ApEnM..62..766W http://archive.wikiwix.com/cache/20110715015952/http://aem.asm.org/cgi/reprint/62/3/766.pdf 2011-07-15 1100F YAA CGA GCG CAA CCC 1100R GGG TTG CGC TCG TTG U1492R GGT TAC CTT GTT ACG ACT T 1492R CGG TTA CCT TGT TAC GAC TT Jiang H, Dong H, Zhang G, Yu B, Chapman LR, Fields MW Microbial diversity in water and sediment of Lake Chaka, an athalassohaline lake in northwestern China Applied and Environmental Microbiology 72 6 3832–3845 June 2006 16751487 1489620 10.1128/AEM.02869-05 2006ApEnM..72.3832J PCR and NGS applications In addition to highly conserved primer binding sites, 16S rRNA gene sequences contain hypervariable regions that can provide species-specific signature sequences useful for identification of bacteria. Pereira F, Carneiro J, Matthiesen R, van Asch B, Pinto N, Gusmão L, Amorim A Identification of species by multiplex analysis of variable-length sequences Nucleic Acids Research 38 22 e203 December 2010 20923781 3001097 10.1093/nar/gkq865 Kolbert CP, Persing DH Ribosomal DNA sequencing as a tool for identification of bacterial pathogens Current Opinion in Microbiology 2 3 299–305 June 1999 10383862 10.1016/S1369-5274(99)80052-6 As a result, 16S rRNA gene sequencing has become prevalent in medical microbiology as a rapid and cheap alternative to phenotypic methods of bacterial identification. Clarridge JE Impact of 16S rRNA gene sequence analysis for identification of bacteria on clinical microbiology and infectious diseases Clinical Microbiology Reviews 17 4 840–62, table of contents October 2004 15489351 523561 10.1128/CMR.17.4.840-862.2004 Although it was originally used to identify bacteria, 16S sequencing was subsequently found to be capable of reclassifying bacteria into completely new species, Lu T, Stroot PG, Oerther DB Reverse transcription of 16S rRNA to monitor ribosome-synthesizing bacterial populations in the environment Applied and Environmental Microbiology 75 13 4589–4598 July 2009 19395563 2704851 10.1128/AEM.02970-08 2009ApEnM..75.4589L or even genera. Brett PJ, DeShazer D, Woods DE Burkholderia thailandensis sp. nov., a Burkholderia pseudomallei-like species International Journal of Systematic Bacteriology 48 Pt 1 1 317–320 January 1998 9542103 10.1099/00207713-48-1-317 free It has also been used to describe new species that have never been successfully cultured. Schmidt TM, Relman DA Phylogenetic identification of uncultured pathogens using ribosomal RNA sequences Bacterial Pathogenesis Part A: Identification and Regulation of Virulence Factors 235 205–222 1994 7520119 10.1016/0076-6879(94)35142-2 978-0-12-182136-4 Methods in Enzymology registration https://archive.org/details/bacterialpathoge0000unse_f8b6/page/205 Gray JP, Herwig RP Phylogenetic analysis of the bacterial communities in marine sediments Applied and Environmental Microbiology 62 11 4049–4059 November 1996 8899989 168226 10.1128/AEM.62.11.4049-4059.1996 1996ApEnM..62.4049G With third-generation sequencing coming to many labs, simultaneous identification of thousands of 16S rRNA sequences is possible within hours, allowing metagenomic studies, for example of gut flora. Sanschagrin S, Yergeau E Next-generation sequencing of 16S ribosomal RNA gene amplicons Journal of Visualized Experiments 90 August 2014 25226019 4828026 10.3791/51709 In samples collected from patients with confirmed infections, 16S rRNA next-generation sequencing (NGS) demonstrated enhanced detection in 40% of cases compared to traditional culture methods; moreover, pre-sampling antibiotic consumption did not significantly affect the sensitivity of 16S NGS.Botan Alexandru Campisciano Giuseppina Zerbato Verena Di Bella Stefano Simonetti Omar Busetti Marina Toc Dan Alexandru Luzzati Roberto Comar Manola 2024-06-21 Performance of 16S rRNA Gene Next-Generation Sequencing and the Culture Method in the Detection of Bacteria in Clinical Specimens Diagnostics en 14 13 1318 10.3390/diagnostics14131318 free 39001210 2075-4418 11240331 Hypervariable regions The bacterial 16S gene contains nine hypervariable regions (V1–V9), ranging from about 30 to 100 base pairs long, that are involved in the secondary structure of the small ribosomal subunit. Gray MW, Sankoff D, Cedergren RJ On the evolutionary descent of organisms and organelles: a global phylogeny based on a highly conserved structural core in small subunit ribosomal RNA Nucleic Acids Research 12 14 5837–5852 July 1984 6462918 320035 10.1093/nar/12.14.5837 The degree of conservation varies widely between hypervariable regions, with more conserved regions correlating to higher-level taxonomy and less conserved regions to lower levels, such as genus and species. Yang B, Wang Y, Qian PY Sensitivity and correlation of hypervariable regions in 16S rRNA genes in phylogenetic analysis BMC Bioinformatics 17 1 135 March 2016 27000765 4802574 10.1186/s12859-016-0992-y free While the entire 16S sequence allows for comparison of all hypervariable regions, at approximately 1,500 base pairs long it can be prohibitively expensive for studies seeking to identify or characterize diverse bacterial communities. These studies commonly utilize the Illumina platform, which produces reads at rates 50-fold and 12,000-fold less expensive than 454 pyrosequencing and Sanger sequencing, respectively. Bartram AK, Lynch MD, Stearns JC, Moreno-Hagelsieb G, Neufeld JD Generation of multimillion-sequence 16S rRNA gene libraries from complex microbial communities by assembling paired-end illumina reads Applied and Environmental Microbiology 77 11 3846–3852 June 2011 21460107 3127616 10.1128/AEM.02772-10 2011ApEnM..77.3846B While cheaper and allowing for deeper community coverage, Illumina sequencing only produces reads 75–250 base pairs long (up to 300 base pairs with Illumina MiSeq), and has no established protocol for reliably assembling the full gene in community samples. Burke CM, Darling AE A method for high precision sequencing of near full-length 16S rRNA genes on an Illumina MiSeq PeerJ 4 e2492 2016-09-20 27688981 5036073 10.7717/peerj.2492 free Full hypervariable regions can be assembled from a single Illumina run, however, making them ideal targets for the platform. While 16S hypervariable regions can vary dramatically between bacteria, the 16S gene as a whole maintains greater length homogeneity than its eukaryotic counterpart (18S ribosomal RNA), which can make alignments easier. Van de Peer Y, Chapelle S, De Wachter R A quantitative map of nucleotide substitution rates in bacterial rRNA Nucleic Acids Research 24 17 3381–3391 September 1996 8811093 146102 10.1093/nar/24.17.3381 Additionally, the 16S gene contains highly conserved sequences between hypervariable regions, enabling the design of universal primers that can reliably produce the same sections of the 16S sequence across different taxa. Větrovský T, Baldrian P The variability of the 16S rRNA gene in bacterial genomes and its consequences for bacterial community analyses PLOS ONE 8 2 e57923 2013-02-27 23460914 3583900 10.1371/journal.pone.0057923 free 2013PLoSO...857923V Although no hypervariable region can accurately classify all bacteria from domain to species, some can reliably predict specific taxonomic levels. Many community studies select semi-conserved hypervariable regions like the V4 for this reason, as it can provide resolution at the phylum level as accurately as the full 16S gene. While lesser-conserved regions struggle to classify new species when higher order taxonomy is unknown, they are often used to detect the presence of specific pathogens. In one study by Chakravorty et al. in 2007, the authors characterized the V1–V8 regions of a variety of pathogens in order to determine which hypervariable regions would be most useful to include for disease-specific and broad assays. Chakravorty S, Helb D, Burday M, Connell N, Alland D A detailed analysis of 16S ribosomal RNA gene segments for the diagnosis of pathogenic bacteria Journal of Microbiological Methods 69 2 330–339 May 2007 17391789 2562909 10.1016/j.mimet.2007.02.005 Amongst other findings, they noted that the V3 region was best at identifying the genus for all pathogens tested, and that V6 was the most accurate at differentiating species between all CDC-watched pathogens tested, including anthrax. While 16S hypervariable region analysis is a powerful tool for bacterial taxonomic studies, it struggles to differentiate between closely related species. In the families Enterobacteriaceae, Clostridiaceae, and Peptostreptococcaceae, species can share up to 99% sequence similarity across the full 16S gene. Jovel J, Patterson J, Wang W, Hotte N, O'Keefe S, Mitchel T, Perry T, Kao D, Mason AL, Madsen KL, Wong GK 6 Characterization of the Gut Microbiome Using 16S or Shotgun Metagenomics Frontiers in Microbiology 7 459 2016-01-01 27148170 4837688 10.3389/fmicb.2016.00459 free As a result, the V4 sequences can differ by only a few nucleotides, leaving reference databases unable to reliably classify these bacteria at lower taxonomic levels. By limiting 16S analysis to select hypervariable regions, these studies can fail to observe differences in closely related taxa and group them into single taxonomic units, therefore underestimating the total diversity of the sample. Furthermore, bacterial genomes can house multiple 16S genes, with the V1, V2, and V6 regions containing the greatest intraspecies diversity. While not the most precise method of classifying bacterial species, analysis of the hypervariable regions remains one of the most useful tools available to bacterial community studies. Promiscuity of 16S rRNA genes Under the assumption that evolution is driven by vertical transmission, 16S rRNA genes have long been believed to be species-specific, and infallible as genetic markers inferring phylogenetic relationships among prokaryotes. However, a growing number of observations suggest the occurrence of horizontal transfer of these genes. In addition to observations of natural occurrence, transferability of these genes is supported experimentally using a specialized Escherichia coli genetic system. Using a null mutant of E. coli as host, growth of the mutant strain was shown to be complemented by foreign 16S rRNA genes that were phylogenetically distinct from E. coli at the phylum level. Kitahara K, Yasutake Y, Miyazaki K Mutational robustness of 16S ribosomal RNA, shown by experimental horizontal gene transfer in Escherichia coli Proceedings of the National Academy of Sciences of the United States of America 109 47 19220–19225 November 2012 23112186 3511107 10.1073/pnas.1213609109 free 2012PNAS..10919220K Tsukuda M, Kitahara K, Miyazaki K Comparative RNA function analysis reveals high functional similarity between distantly related bacterial 16 S rRNAs Scientific Reports 7 1 9993 August 2017 28855596 5577257 10.1038/s41598-017-10214-3 free 2017NatSR...7.9993T Such functional compatibility was also seen in Thermus thermophilus. Miyazaki K, Tomariguchi N Occurrence of randomly recombined functional 16S rRNA genes in Thermus thermophilus suggests genetic interoperability and promiscuity of bacterial 16S rRNAs Scientific Reports 9 1 11233 August 2019 31375780 6677816 10.1038/s41598-019-47807-z free 2019NatSR...911233M Furthermore, in T. thermophilus, both complete and partial gene transfer was observed. Partial transfer resulted in spontaneous generation of apparently random chimera between host and foreign bacterial genes. Thus, 16S rRNA genes may have evolved through multiple mechanisms, including vertical inheritance and horizontal gene transfer; the frequency of the latter may be much higher than previously thought.Miyazaki Kentaro Tomariguchi Natsuki 2019-08-02 Occurrence of randomly recombined functional 16S rRNA genes in Thermus thermophilus suggests genetic interoperability and promiscuity of bacterial 16S rRNAs Scientific Reports 9 1 11233 10.1038/s41598-019-47807-z free 2045-2322 6677816 31375780 2019NatSR...911233M 16S ribosomal databases The 16S rRNA gene is used as the standard for classification and identification of microbes, because it is present in most microbes and shows proper changes. Yarza P, Yilmaz P, Pruesse E, Glöckner FO, Ludwig W, Schleifer KH, Whitman WB, Euzéby J, Amann R, Rosselló-Móra R 6 Uniting the classification of cultured and uncultured bacteria and archaea using 16S rRNA gene sequences Nature Reviews. Microbiology 12 9 635–645 September 2014 25118885 10.1038/nrmicro3330 21895693 Type strains of 16S rRNA gene sequences for most bacteria and archaea are available on public databases, such as NCBI. However, the quality of the sequences found on these databases is often not validated. Therefore, secondary databases that collect only 16S rRNA sequences are widely used. SILVA SILVA provides comprehensive, quality checked and regularly updated datasets of aligned small (16S/18S, SSU) and large subunit (23S/28S, LSU) ribosomal RNA (rRNA) sequences for all three domains of life as well as a suite of search, primer-design and alignment tools (Bacteria, Archaea and Eukarya).Elmar Pruesse, Christian Quast, Katrin Knittel, Bernhard M. Fuchs, Wolfgang Ludwig, Jörg Peplies, Frank Oliver Glöckner (2007) Nucleic Acids Res. SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB. December; 35(21): 7188–7196. GreenGenes GreenGenes is a quality controlled, comprehensive 16S rRNA gene reference database and taxonomy based on a de novo phylogeny that provides standard operational taxonomic unit sets. DeSantis TZ, Hugenholtz P, Larsen N, Rojas M, Brodie EL, Keller K, Huber T, Dalevi D, Hu P, Andersen GL 6 Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB Applied and Environmental Microbiology 72 7 5069–5072 July 2006 16820507 1489311 10.1128/aem.03006-05 2006ApEnM..72.5069D McDonald D, Price MN, Goodrich J, Nawrocki EP, DeSantis TZ, Probst A, Andersen GL, Knight R, Hugenholtz P 6 An improved Greengenes taxonomy with explicit ranks for ecological and evolutionary analyses of bacteria and archaea The ISME Journal 6 3 610–618 March 2012 22134646 3280142 10.1038/ismej.2011.139 2012ISMEJ...6..610M In 2023, GreenGenes2 was released. McDonald D, Jiang Y, Balaban M, Cantrell K, Zhu Q, Gonzalez A, Morton JT, Nicolaou G, Parks DH, Karst SM, Albertsen M, Hugenholtz P, DeSantis T, Song SJ, Bartko A, Havulinna AS, Jousilahti P, Cheng S, Inouye M, Niiranen T, Jain M, Salomaa V, Lahti L, Mirarab S, Knight R 6 Greengenes2 unifies microbial data in a single reference tree Nature Biotechnology 42 5 715–718 July 2023 37500913 10818020 10.1038/s41587-023-01845-1 EzBioCloud EzBioCloud database, formerly known as EzTaxon, consists of a complete hierarchical taxonomic system containing 62,988 bacteria and archaea species/phylotypes which includes 15,290 valid published names as of September 2018. Based on the phylogenetic relationship such as maximum-likelihood and OrthoANI, all species/subspecies are represented by at least one 16S rRNA gene sequence. The EzBioCloud database is systematically curated and updated regularly which also includes novel candidate species. Moreover, the website provides bioinformatics tools such as ANI calculator, ContEst16S and 16S rRNA DB for QIIME and Mothur pipeline.Yoon, S. H., Ha, S. M., Kwon, S., Lim, J., Kim, Y., Seo, H. and Chun, J. (2017). Introducing EzBioCloud: A taxonomically united database of 16S rRNA and whole genome assemblies. Int J Syst Evol Microbiol. 67:1613–1617 MIMt MIMt is a compact non-redundant 16S database for a rapid metagenomic samples identification. It is composed of 48,749 full 16S sequences belonging to 24,626 well classified bacteria and archaea species. All sequences were obtained from complete genomes deposited in NCBI and for each of the sequences full taxonomic hierarchy is provided. It contains no redundancy, so only one representative for each species was considered avoiding same sequences from different strains, isolates or pathovars resulting in a very fast tool for microorganisms identification, compatible with any classification software (QIIME, Mothur, DADA, etc).https://mimt.bu.biopolis.pt/ MIMt - (Mass Identification of Metagenomics tests) mimt.bu.biopolis.pt 11 February 2024 Ribosomal Database Project The Ribosomal Database Project (RDP) was a curated database that offers ribosome data along with related programs and services. The offerings included phylogenetically ordered alignments of ribosomal RNA (rRNA) sequences, derived phylogenetic trees, rRNA secondary structure diagrams and various software packages for handling, analyzing and displaying alignments and trees. Larsen N, Olsen GJ, Maidak BL, McCaughey MJ, Overbeek R, Macke TJ, Marsh TL, Woese CR July 1993 The ribosomal database project Nucleic Acids Res. 21 13 3021–3 8332524 309730 10.1093/nar/21.13.3021 Due to its large size the RDP database is often used as the basis for bioinformatic tool development and creating manually curated databases. Allard G, Ryan FJ, Jeffery IB, Claesson MJ SPINGO: A rapid species-classifier for microbial amplicon sequences BMC Bioinformatics 16 1 324 October 2015 26450747 4599320 10.1186/s12859-015-0747-1 free The RDP server was taken offline in 2023, but the software is still available for download.The RDP Classifier is available as a stand-alone tool at https://sourceforge.net/projects/rdp-classifier/. It is written in Java and so will run on any computer that has Java installed. The RDPTools are available on GitHub and as a Docker image. See installation instructions at https://john-quensen.com/tutorials/tutorial-1/ and https://jfq3.gitbook.io/rdptools-docker/rdptools-docker/readme. Instructions for downloading a SeqMatch database and running it from the command line are available at https://john-quensen.com/tutorials/seqmatch/. References External links University of Washington Laboratory Medicine: Molecular Diagnosis | Bacterial Sequencing MIMt 16S database The Ribosomal Database Project https://web.archive.org/web/20200819061707/http://rdp.cme.msu.edu/ 2020-08-19 Ribosomes and Ribosomal RNA: (rRNA) SILVA rRNA database Greengenes: 16S rDNA data and tools EzBioCloud Category:Ribosomal RNA Category:Metagenomics