Rfam 13.0: shifting to a genome-centric resource for non-coding RNA families

By Ioanna Kalvari, Joanna Argasinska, Natalia Quinones-Olvera, Eric P. Nawrocki, Elena Rivas, Sean R. Eddy, Alex Bateman, Robert D. Finn, Anton I. Petrov. Nucleic Acids Res., 2017

880 citations recorded by the source corpus.

Abstract The Rfam database is a collection of RNA families in which each family is represented by a multiple sequence alignment, a consensus secondary structure, and a covariance model. In this paper we introduce Rfam release 13.0, which switches to a new genome-centric approach that annotates a non-redundant set of reference genomes with RNA families. We describe new web interface features including faceted text search and R-scape secondary structure visualizations. We discuss a new literature curation workflow and a pipeline for building families based on RNAcentral. There are 236 new families in release 13.0, bringing the total number of families to 2687. The Rfam website is http://rfam.org.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/fc0e2f8c4ea4822b7ea27fbd6bb71dd9e8325758

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Citations in the corpus

RNA-Puzzles toolkit: a computational resource of RNA 3D structure benchmark datasets, structure manipulation, and evaluation tools (2019, methodology): “The tools help to perform searches us-ing both Blast (50) on the PDB database and Infernal (51) on the Rfam database (52).”
RNAcentral 2021: secondary structure integration, improved sequence search and new member databases (2020, methodology): “The search has been integrated into Rfam (6), miRBase (17) and snoDB (18).”
MGnify: the microbiome analysis resource in 2020 (2019, methodology): “0) (29), with analysis performed on the matching sequences using MAPseq (v1.”
Using Rosetta for RNA homology modeling (2019, methodology): “Alignment software can account for covariation in RNA secondary structure, providing more accurate alignments than those based exclusively on sequence (Kalvari et al., 2018; Nawrocki & Eddy, 2013).”
RNA-Puzzles Round IV: 3D structure predictions of four ribozymes and two aptamers (2020, methodology): “Considering some new prediction approaches may abstract RNA structure (such as the network model Kim et al. 2013), we use the Mean of Circular Quantities (Zok et al. 2014) to assess the accuracy in the torsion angle space.”
RNAcentral: a hub of information for non-coding RNA sequences (2018, neutral): “melanogaster snoRNAs described in a recent paper (9) and submitted to the INSDC (10) do not overlap with existing annotated ncRNAs (Figure 2), making these features candidates for review by databases such as FlyBase (11), snoPY (12) and Rfam (13).”
Rfam 14: expanded coverage of metagenomic, viral and microRNA families (2020, methodology): “Rfam is the database of non-coding RNA (ncRNA) families (1), each represented by a multiple sequence alignment (known as the seed), a consensus secondary structure, and a covariance model to annotate non-coding RNAs in nucleotide datasets using the Infernal software (2).”
Symmetry and simplicity spontaneously emerge from the algorithmic nature of evolution (2021, methodology): “S11 we make probability-complexity plots for RNA with L ≈ 100 data from the Rfam database [32, 33].”
GENCODE reference annotation for the human and mouse genomes (2018, methodology): “For other classes of sncRNA, including small nucleolar RNAs (snoRNAs), small nuclear RNAs (snRNAs) and small Cajal bodyspecific RNAs (scaRNAs), we use a homology-based, computational pipeline (24), which first compares sequences of known RNA families in Rfam (25) to the genome using BLAST (26).”
tRNAscan-SE 2.0: improved detection and functional classification of transfer RNA genes (2019, methodology): “We also manually identified group I introns in tRNAIle2 of multiple Acidovorax and Burkholderia species by sequence alignments and RNA family similarity search (14,20).”