Rfam 14.1 is out

January 28, 2019

We are happy to announce that a new Rfam release is now available! Rfam 14.1 includes 226 new families bringing the total number of Rfam families to 3,016. In addition, the R-scape visualisations have been updated to display pseudoknots, both manually annotated in seed alignments and predicted by R-scape (see below for details).

New families

The majority of the new families were contributed by Dr Zasha Weinberg (University of Leipzig) and were discovered by a systematic computational analysis of intergenic regions in Bacteria and metagenomic samples (see the NAR paper for more details). Many of the families come from environmental samples, so importing them into Rfam required a new procedure (described below).

This release features many families with statistically significant covariation (highlighted in green in the images below), for example Skipping-rope, Drum, and LOOT:

as well as a new unusually large, highly-structured RNA called ROOL that is found in Firmicutes, Fusobacteria and Tenericutes phylae as well as in phages and cow rumen metagenomic samples:

Browse new families in Rfam

Analysing pseudoknots using R-scape

Developed by Dr Elena Rivas (Harvard University), R-scape is a program that detects covariation support for structural pairs in RNA alignments (see the 2017 paper by Rivas et al in  Nature Methods for more details). Starting with version 1.2.0, R-scape systematically identifies pseudoknots supported by covariation (Rivas & Eddy, in preparation). For example, here is a pseudoknot from the SAM riboswitch that is not yet annotated in the Rfam seed alignment (left) but is correctly predicted by R-scape (right):

The nucleotides forming the pseudoknot are labelled pk_1, pk_2, pk_3 and so on in the structural annotation. Each pseudoknot is shown as a separate stem in an inset, and the basepairs with significant covariation are colored green similar to the other R-scape diagrams.

We are working on adding more pseudoknot annotations to the existing families based on the evidence from R-scape, 3D structures, and scientific literature. Please let us know if your favourite RNA is missing a pseudoknot.

Using RNAcentral identifiers in Rfam seed alignments

In previous releases, every sequence in every Rfam seed alignment was required to have an INSDC identifier assigned by a sequence archive like ENA or GenBank. However, when Rfam users submit their alignments to Rfam, they often include sequences that are not yet found in ENA or GenBank, especially if the sequences come from environmental samples. For example, sequence LV_Brine_h2_0102_1073789 from the MDR-NUDIX RNA does not exist in ENA so it does not have a stable identifier and is not associated with metadata such as NCBI taxid, description, or scientific literature.

In the past Rfam replaced such sequences with closely related ones or removed them altogether which required modifying the user-submitted alignments and could result in smaller, less informative seeds missing some covariation compared to the originals. In this release we implemented a new procedure that accepts RNAcentral identifiers in Rfam seed alignments in order to preserve the manually curated alignments as much as possible.

We began by importing the sequences and metadata from a recently established ZWD database (Zasha Weinberg Database) into RNAcentral where each distinct sequence is assigned a stable identifier (URS id) and linked to a NCBI taxid, its parent ZWD alignment, and scientific literature. For example, sequence LV_Brine_h2_0102_1073789 is assigned RNAcentral id URS0000D661D6_12908 so that it can be easily tracked using RNAcentral search, API, public database, or bulk download files.

Next we replaced the ZWD identifiers with RNAcentral accessions and used the ZWD-RNAcentral alignments as seeds for new Rfam families:

Following the standard Rfam protocol, we manually selected bit-score thresholds for each family that allow reliable identification of sequences from the seed alignments and other homologs from the Rfam sequence database.

A small number of sequences still had to be removed from ZWD alignments in the following cases:

  1. If a covariance model built using the alignment could not find some of its own sequences, these unmatched sequences were removed from the alignment
  2. If a sequence scored worse than a set of random sequences that serve as control when setting bit-score thresholds, such low-scoring sequences were also removed from the alignments.


In future releases we plan to expand the usage of RNAcentral identifiers in Rfam seed alignments.

Please note that any software that parses Rfam seed alignments and uses ENA or GenBank for metadata lookup will now need to include RNAcentral identifiers using the RNAcentral API. For more information or if you have any questions, please contact the RNAcentral team or Rfam help.

11 more families with 3D structure

There are 11 additional Rfam families that match 3D structures bringing the total number of families with experimentally determined structures to 98 (compared with 87 in Rfam 14.0).

Rfam familyPDB structures
RF00009 (RNaseP_nuc)6agb and 6ah3 (yeast), 6ahr and 6ahu (human) [chains A]
RF00025 (Telomerase-cil)6d6v (chain B)
RF00027 (let-7)5zal (chain C), 5zam (chain C)
RF00080 (yybP-ykoY)6cc1 (chains A and B), 6cc3 (chains A and B)
RF00233 (Tymo_tRNA-like)6mj0 (chains A and B)
RF00250 (mir-TAR)6gml (chain P)
RF00390 (UPSK)6mj0 (chains A and B)
RF01727 (SAM-SAH)6hag (chain A)
RF01826 (SAM_V)6fz0 (chain A)
RF02348 (tracrRNA)6mcb (chain B), 6mcc (chain B)
RF02553 (YrlA)6cu1 (chain A)

Other updates

Two existing families were updated with new seed alignments from ZWD, including RF02440 (ldcC RNA) and RF02840 (Lacto-3 RNA). There is also a new clan DUF805 (CL00115) that includes DUF805 and DUF805b families.

Acknowledgements

The Rfam team would like to thank Dr Elena Rivas and Dr Zasha Weinberg for the new data, software, and feedback, as well as the organisers and participants of the 2018 Benasque RNA meeting. We would also like to thank BBSRC for funding Rfam between 2015 and 2018.

Get in touch

Follow Rfam on Twitter to find out about new Rfam families and don’t hesitate to raise a GitHub issue or email us if you have any questions.

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