Rfam 11.0: 10 years of RNA families

By Sarah W. Burge, Jennifer Daub, R. Y. Eberhardt, John G. Tate, Lars Barquist, Eric P. Nawrocki, Sean R. Eddy, Paul P. Gardner, Alex Bateman. Nucleic Acids Res., 2012

804 citations recorded by the source corpus.

The Rfam database (available via the website at http://rfam.sanger.ac.uk and through our mirror at http://rfam.janelia.org) is a collection of non-coding RNA families, primarily RNAs with a conserved RNA secondary structure, including both RNA genes and mRNA cis-regulatory elements. Each family is represented by a multiple sequence alignment, predicted secondary structure and covariance model. Here we discuss updates to the database in the latest release, Rfam 11.0, including the introduction of genome-based alignments for large families, the introduction of the Rfam Biomart as well as other user interface improvements. Rfam is available under the Creative Commons Zero license.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/38882b2ab18886383de4f22812976450e19cfcb5

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Citations in the corpus

The UCSC Genome Browser database: 2015 update (2014, background): “The UCSC Genes set includes both protein-coding and non-coding RNA genes from RefSeq, GenBank, the tRNA Genes track (31) and RFAM (32).”
The EMBL-EBI bioinformatics web and programmatic tools framework (2015, background): “New sequence databases include ENA Coding and Non-coding sequence databases, Worm-Base ParaSite (21), Pfam (15), Rfam (22) along with many new genomes and proteomes as existing databases are updated.”
The UCSC Genome Browser database: 2014 update (2013, background): “The UCSC Genes track, which includes protein-coding genes and non-coding RNA genes from RefSeq, GenBank, CCDS (12), Rfam (13) and the tRNA Genes track (14), was updated on both the GRCh37/hg19 human and GRCm38/mm10 mouse assemblies.”
The BioMart community portal: an innovative alternative to large, centralized data repositories (2015, neutral): “Wellcome Trust Sanger Institute (WTSI), UK (28)”
Ensembl 2015 (2014, background): “Secondary structures of non-coding RNAs, based on information from RFAM if available (28) or RNAFold (29), can now be displayed.”
CopraRNA and IntaRNA: predicting small RNA targets, networks and interaction domains (2014, methodology): “Homologous sRNA sequences may be retrieved from databases such as NCBI via BLAST (26) or from Rfam (27).”
IMG 4 version of the integrated microbial genomes comparative analysis system (2013, methodology): “Transporter genes are linked to the Transport Classiﬁcation Database (21) based on their assignment to COG, Pfam or TIGRfam domains or IMG terms that correspond to transporter families.”
Characterization of active and total fungal communities in the atmosphere over the Amazon rainforest (2015, methodology): “…were identified using SortMeRNA (Kopylova et al., 2012) with the non-redundant version of the following databases: rfam 5.8S (version 11.0) (Burge et al., 2013); Unite25 (November 2011 version) (Kõljalg et al., 2013), and Silva 18S and Silva 28S (Release BGD 12, 7177–7207,…”
Ensembl comparative genomics resources (2016, background): “For ncRNA trees, the Rfam ID of each family acts as a stable identifier.”
RNA-Puzzles Round II: assessment of RNA structure prediction programs applied to three large RNA structures (2015, methodology): “The combination of SHAPE data and/or homologous sequence information from Rfam and the Vfold algorithm led of RNA secondary structure prediction.”
3D RNA and Functional Interactions from Evolutionary Couplings. (2015, neutral): “Obtaining protein alignments RNA alignments for all RNA-protein complexes were taken from RFAM (Burge et al., 2013).”
Ensembl comparative genomics resources (2016, background): “For ncRNA trees, the Rfam ID of each family acts as a stable identifier.”
The Spot 42 RNA: A regulatory small RNA with roles in the central metabolism (2015, methodology): “uk/family/RF00021).(22) Blastn searches in all domains of Bacteria were performed using spf sequences from 43 selected taxa as query sequences.”
RNA-Puzzles Round III: 3D RNA structure prediction of five riboswitches and one ribozyme (2017, methodology): “In order to further increase the accuracy of RNA 2D structure prediction, they also applied Rfam (Burge et al. 2013) to identify the possible conserved base pairs and used the most conserved base pair information as a constraint to the Vfold2D algorithm to predict 2D structures.”