Awesome

Barrnap

BAsic Rapid Ribosomal RNA Predictor

Description

Barrnap predicts the location of ribosomal RNA genes in genomes. It supports bacteria (5S,23S,16S), archaea (5S,5.8S,23S,16S), metazoan mitochondria (12S,16S) and eukaryotes (5S,5.8S,28S,18S).

It takes FASTA DNA sequence as input, and write GFF3 as output. It uses the new nhmmer tool that comes with HMMER 3.1 for HMM searching in RNA:DNA style. Multithreading is supported and one can expect roughly linear speed-ups with more CPUs.

Installation

Requirements

Perl 5.xx (core modules only)
nhmmer (part of HMMER 3.x)
bedtools >= 2.27.0

Conda

Install Conda or Miniconda:

conda install -c bioconda -c conda-forge barrnap

Homebrew

Install Homebrew (macOS) or Linuxbrew (Linux).

brew install brewsci/bio/barrnap

Source

This will install the latest version direct from Github. You'll need to add the bin directory to your PATH.

cd $HOME
git clone https://github.com/tseemann/barrnap.git
cd barrnap/bin
./barrnap --help

Usage

% barrnap --quiet examples/small.fna
##gff-version 3
P.marinus	barrnap:0.8	rRNA	353314	354793	0	+	.	Name=16S_rRNA;product=16S ribosomal RNA
P.marinus	barrnap:0.8	rRNA	355464	358334	0	+	.	Name=23S_rRNA;product=23S ribosomal RNA
P.marinus	barrnap:0.8	rRNA	358433	358536	7.5e-07	+	.	Name=5S_rRNA;product=5S ribosomal RNA

% barrnap -q -k mito examples/mitochondria.fna 
##gff-version 3
AF346967.1	barrnap:0.8	rRNA	643	1610	.	+	.	Name=12S_rRNA;product=12S ribosomal RNA
AF346967.1	barrnap:0.8	rRNA	1672	3228	.	+	.	Name=16S_rRNA;product=16S ribosomal RNA
  
% barrnap -o rrna.fa < contigs.fa > rrna.gff
% head -n 3 rrna.fa
>16S_rRNA::gi|329138943|tpg|BK006945.2|:455935-456864(-)
ACGGTCGGGGGCATCAGTATTCAATTGTCAGAGGTGAAATTCTTGGATT
TATTGAAGACTAACTACTGCGAAAGCATTTGCCAAGGACGTTTTCATTA

Options

General

--help show help and exit
--version print version in form barrnap X.Y and exit
--citation print a citation and exit

Search

--kingdom is the database to use: Bacteria:bac, Archaea:arc, Eukaryota:euk, Metazoan Mitochondria:mito
--threads is how many CPUs to assign to nhmmer search
--evalue is the cut-off for nhmmer reporting, before further scrutiny
--lencutoff is the proportion of the full length that qualifies as partial match
--reject will not include hits below this proportion of the expected length

Output

--quiet will not print any messages to stderr
--incseq will include the full input sequences in the output GFF
--outseq creates a FASTA file with the hit sequences

Caveats

Barrnap does not do anything fancy. It has HMM models for each different rRNA gene. They are built from full length seed alignments.

Comparison with RNAmmer

Barrnap is designed to be a substitute for RNAmmer. It was motivated by my desire to remove Prokka's dependency on RNAmmer which is encumbered by a free-for-academic sign-up license, and by RNAmmer's dependence on legacy HMMER 2.x which conflicts with HMMER 3.x that most people are using now.

RNAmmer is more sophisticated than Barrnap, and more accurate because it uses HMMER 2.x in glocal alignment mode whereas NHMMER 3.x currently only supports local alignment (Sean Eddy expected glocal to be supported in 2014, but it still isn't available in 2018).

In practice, Barrnap will find all the typical rRNA genes in a few seconds (in bacteria), but may get the end points out by a few bases and will probably miss wierd rRNAs. The HMM models it uses are derived from Rfam, Silva and RefSeq.

Data sources for HMM models

Bacteria (70S)  
        LSU 50S
                5S      RF00001
                23S     SILVA-LSU-Bac
        SSU 30S
                16S     RF00177

Archaea (70S)   
        LSU 50S
                5S      RF00001
                5.8S    RF00002
                23S     SILVA-LSU-Arc
        SSU 30S
                16S     RF01959

Eukarya (80S)   
        LSU 60S
                5S      RF00001
                5.8S    RF00002
                28S     SILVA-LSU-Euk
        SSU 40S
                18S     RF01960

Metazoan Mito
                12S     RefSeq (MT-RNR1, s-rRNA, rns)
                16S     RefSeq (MT-RNR2, l-rRNA, rnl)

Models I would like to add

Fungi	[Sajeet Haridas]
        LSU 35S ?
                5S
                5.8S
                25S
        SSU ?
                18S
        Mito [http://www.ncbi.nlm.nih.gov/nuccore/NC_001224.1]
                15S 
                21S (multiple exons)
                
Apicoplast [http://www.ncbi.nlm.nih.gov/nuccore/U87145.2]
                LSU ~2500bp 28S ?
                SSU ~1500bp 16S ?

Plant [Shaun Jackman]
	Mito [https://www.ncbi.nlm.nih.gov/nucleotide?cmd=Retrieve&dopt=GenBank&list_uids=26556996]	
		5S	~118 bp  ?	rrn5 	(use RF00001 ?)
		18S	~1935 bp ?	rrn18	(use RF01960 ?)
		26S	~2568 bp ?	rrn26

Where does the name come from?

The name Barrnap was originally derived from Bacterial/Archaeal Ribosomal RNA Predictor. However it has since been extended to support mitochondrial and eukaryotic rRNAs, and has been given the new backronym BAsic Rapid Ribosomal RNA Predictor. The project was originally spawned at CodeFest 2013 in Berlin, Germany by Torsten Seemann and Tim Booth.

License

Barrnap: GPLv3
Rfam: CC0
SILVA: Free for academic use

Author

Torsten Seemann