RNAmmer: consistent and rapid annotation of ribosomal RNA genes

By K. Lagesen, Peter F. Hallin, E. Rødland, H. Stærfeldt, Torbjørn Rognes, David Wayne Ussery. Nucleic Acids Research, 2007

5,857 citations recorded by the source corpus.

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.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/51902625d9265e9aa897e1d2b0b6ef3f65dde23f

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Citations in the corpus

Characterization and genomic analysis of kraft lignin biodegradation by the beta-proteobacterium Cupriavidus basilensis B-8 (2013, neutral): “0, rRNAmmer, tRNAscan, and Rfam software [42-45].”
The SILVA ribosomal RNA gene database project: improved data processing and web-based tools (2012, methodology): “All sequences in EMBL-Bank are scanned for rRNA gene sequences using the models and parameters from the RNAmmer software package (9), HMMER2 (http://hmmer.”
Incorporating 16S Gene Copy Number Information Improves Estimates of Microbial Diversity and Abundance (2012, methodology): “For genomes for which the 16S rRNA genes were not annotated, the RNAmmer program was used to identify the 16S rRNA genes [32].”
PathogenFinder - Distinguishing Friend from Foe Using Bacterial Whole Genome Sequence Data (2013, methodology): “One of the 10 built models can be selected for the prediction, and if the user does not know which class or phylum the organism belongs to, the webserver will identify it automatically by predicting 16S genes, using RNAmmer [34], and accordingly select the appropriate model to be used for the predic”
IMG 4 version of the integrated microbial genomes comparative analysis system (2013, methodology): “Ribosomal RNA genes (5S, 16S and 23S) are predicted using hmmsearch against the custom models generated for each type of rRNA in bacteria and archaea (7,8).”
25 years of serving the community with ribosomal RNA gene reference databases and tools. (2017, methodology): “The models and parameters from the RNAmmer software package (Lagesen et al., 2007) are used to scan all sequences in EMBL-EBI/ENA for the presence of rRNA gene sequences.”
RASTtk: A modular and extensible implementation of the RAST algorithm for building custom annotation pipelines and annotating batches of genomes (2015, background): “Many tools exist for finding and curating collections of rRNAs 13,20 , but we needed a program that is simple, lightweight and fast.”