Whole genome annotation is the process of identifying features of interest in a set of genomic DNA sequences, and labelling them with useful information. Prokka is a software tool to annotate bacterial, archaeal and viral genomes quickly and produce standards-compliant output files.

If you use Conda you can use the Bioconda channel:

conda install -c conda-forge -c bioconda -c defaults prokka

If you are using the MacOS Brew or LinuxBrew packaging system:

brew install brewsci/bio/prokka

Maintained by https://hub.docker.com/u/staphb

docker pull staphb/prokka:latest
docker run staphb/prokka:latest prokka -h

singularity build prokka.sif docker:https://staphb/prokka:latest
singularity exec prokka.sif prokka -h

sudo apt-get install libdatetime-perl libxml-simple-perl libdigest-md5-perl git default-jre bioperl
sudo cpan Bio::Perl
git clone https://github.com/tseemann/prokka.git $HOME/prokka
$HOME/prokka/bin/prokka --setupdb

sudo yum install git perl-Time-Piece perl-XML-Simple perl-Digest-MD5 perl-App-cpanminus git java perl-CPAN perl-Module-Build
sudo cpanm Bio::Perl
git clone https://github.com/tseemann/prokka.git $HOME/prokka
$HOME/prokka/bin/prokka --setupdb

sudo cpan Time::Piece XML::Simple Digest::MD5 Bio::Perl
git clone https://github.com/tseemann/prokka.git $HOME/prokka
$HOME/prokka/bin/prokka --setupdb

• Type prokka and it should output its help screen.
• Type prokka --version and you should see an output like prokka 1.x
• Type prokka --listdb and it will show you what databases it has installed to use.

# Vanilla (but with free toppings)
% prokka contigs.fa

# Look for a folder called PROKKA_yyyymmdd (today's date) and look at stats
% cat PROKKA_yyyymmdd/*.txt

# Choose the names of the output files
% prokka --outdir mydir --prefix mygenome contigs.fa

# Visualize it in Artemis
% art mydir/mygenome.gff

# Have curated genomes I want to use to annotate from
% prokka --proteins MG1655.gbk --outdir mutant --prefix K12_mut contigs.fa

# Look at tabular features
% less -S mutant/K12_mut.tsv

# It's not just for bacteria, people
% prokka --kingdom Archaea --outdir mydir --genus Pyrococcus --locustag PYCC

# Search for your favourite gene
% exonerate --bestn 1 zetatoxin.fasta mydir/PYCC_06072012.faa | less

# Watch and learn
% prokka --outdir mydir --locustag EHEC --proteins NewToxins.faa --evalue 0.001 --gram neg --addgenes contigs.fa

# Check to see if anything went really wrong
% less mydir/EHEC_06072012.err

# Add final details using Sequin
% sequin mydir/EHEC_0607201.sqn

# Register your BioProject (e.g. PRJNA123456) and your locus_tag prefix (e.g. EHEC) first!
% prokka --compliant --centre UoN --outdir PRJNA123456 --locustag EHEC --prefix EHEC-Chr1 contigs.fa

# Check to see if anything went really wrong
% less PRJNA123456/EHEC-Chr1.err

# Add final details using Sequin
% sequin PRJNA123456/EHEC-Chr1.sqn

# Register your BioProject (e.g. PRJEB12345) and your locus_tag (e.g. EHEC) prefix first!
% prokka --compliant --centre UoN --outdir PRJEB12345 --locustag EHEC --prefix EHEC-Chr1 contigs.fa

# Check to see if anything went really wrong
% less PRJNA123456/EHEC-Chr1.err

# Install and run Sanger Pathogen group's Prokka GFF3 to EMBL converter
# available from https://github.com/sanger-pathogens/gff3toembl
# Find the closest NCBI taxonomy id (e.g. 562 for Escherichia coli)
% gff3_to_embl -i "Submitter, A." \
    -m "Escherichia coli EHEC annotated using Prokka." \
    -g linear -c PROK -n 11 -f PRJEB12345/EHEC-Chr1.embl \
    "Escherichia coli" 562 PRJEB12345 "Escherichia coli strain EHEC" PRJEB12345/EHEC-Chr1.gff

# Download and run the latest EMBL validator prior to submitting the EMBL flat file
# from https://central.maven.org/maven2/uk/ac/ebi/ena/sequence/embl-api-validator/
# which at the time of writing is v1.1.129
% curl -L -O https://central.maven.org/maven2/uk/ac/ebi/ena/sequence/embl-api-validator/1.1.129/embl-api-validator-1.1.129.jar
% java -jar embl-api-validator-1.1.129.jar -r PRJEB12345/EHEC-Chr1.embl

# Compress the file ready to upload to ENA, and calculate MD5 checksum
% gzip PRJEB12345/EHEC-Chr1.embl
% md5sum PRJEB12345/EHEC-Chr1.embl.gz

# No stinking Perl script is going to control me
% prokka \
        --outdir $HOME/genomes/Ec_POO247 --force \
        --prefix Ec_POO247 --addgenes --locustag ECPOOp \
        --increment 10 --gffver 2 --centre CDC  --compliant \
        --genus Escherichia --species coli --strain POO247 --plasmid pECPOO247 \
        --kingdom Bacteria --gcode 11 --usegenus \
        --proteins /opt/prokka/db/trusted/Ecocyc-17.6 \
        --evalue 1e-9 --rfam \
        plasmid-closed.fna

General:
  --help            This help
  --version         Print version and exit
  --citation        Print citation for referencing Prokka
  --quiet           No screen output (default OFF)
  --debug           Debug mode: keep all temporary files (default OFF)
Setup:
  --listdb          List all configured databases
  --setupdb         Index all installed databases
  --cleandb         Remove all database indices
  --depends         List all software dependencies
Outputs:
  --outdir [X]      Output folder [auto] (default '')
  --force           Force overwriting existing output folder (default OFF)
  --prefix [X]      Filename output prefix [auto] (default '')
  --addgenes        Add 'gene' features for each 'CDS' feature (default OFF)
  --locustag [X]    Locus tag prefix (default 'PROKKA')
  --increment [N]   Locus tag counter increment (default '1')
  --gffver [N]      GFF version (default '3')
  --compliant       Force Genbank/ENA/DDJB compliance: --genes --mincontiglen 200 --centre XXX (default OFF)
  --centre [X]      Sequencing centre ID. (default '')
Organism details:
  --genus [X]       Genus name (default 'Genus')
  --species [X]     Species name (default 'species')
  --strain [X]      Strain name (default 'strain')
  --plasmid [X]     Plasmid name or identifier (default '')
Annotations:
  --kingdom [X]     Annotation mode: Archaea|Bacteria|Mitochondria|Viruses (default 'Bacteria')
  --gcode [N]       Genetic code / Translation table (set if --kingdom is set) (default '0')
  --prodigaltf [X]  Prodigal training file (default '')
  --gram [X]        Gram: -/neg +/pos (default '')
  --usegenus        Use genus-specific BLAST databases (needs --genus) (default OFF)
  --proteins [X]    Fasta file of trusted proteins to first annotate from (default '')
  --hmms [X]        Trusted HMM to first annotate from (default '')
  --metagenome      Improve gene predictions for highly fragmented genomes (default OFF)
  --rawproduct      Do not clean up /product annotation (default OFF)
Computation:
  --fast            Fast mode - skip CDS /product searching (default OFF)
  --cpus [N]        Number of CPUs to use [0=all] (default '8')
  --mincontiglen [N] Minimum contig size [NCBI needs 200] (default '1')
  --evalue [n.n]    Similarity e-value cut-off (default '1e-06')
  --rfam            Enable searching for ncRNAs with Infernal+Rfam (SLOW!) (default '0')
  --norrna          Don't run rRNA search (default OFF)
  --notrna          Don't run tRNA search (default OFF)
  --rnammer         Prefer RNAmmer over Barrnap for rRNA prediction (default OFF)

The --proteins option is recommended when you have good quality reference genomes and want to ensure gene naming is consistent. Some species use specific terminology which will be often lost if you rely on the default Swiss-Prot database included with Prokka.

If you have Genbank or Protein FASTA file(s) that you want to annotate genes from as the first priority, use the --proteins myfile.gbk. Please make sure it has a recognisable file extension like .gb or .gbk or auto-detect will fail. The use of Genbank is recommended over FASTA, because it will provide /gene and /EC_number annotations that a typical .faa file will not provide, unless you have specially formatted it for Prokka.

Instead of letting prodigal train its gene model on the contigs you provide, you can pre-train it on some good closed reference genomes first using the prodigal -t option. Once you've done that, provide prokka the training file using the --prodgialtf option.

Prokka annotates proteins by using sequence similarity to other proteins in its database, or the databases the user provides via --proteins. By default, Prokka tries to "cleans" the /product names to ensure they are compliant with Genbank/ENA conventions. Some of the main things it does is:

• set vague names to hypothetical protein
• consistifies terms like possible, probable, predicted, ... to putative
• removes EC, COG and locus_tag identifiers

Full details can be found in the cleanup_product() function in the prokka script. If you feel your annotations are being ruined, try using the --rawproduct option, and please file an issue if you find an example of where it is "behaving badly" and I will fix it.

Prokka uses a variety of databases when trying to assign function to the predicted CDS features. It takes a hierarchical approach to make it fast.
A small, core set of well characterized proteins are first searched using BLAST+. This combination of small database and fast search typically completes about 70% of the workload. Then a series of slower but more sensitive HMM databases are searched using HMMER3.

The three core databases, applied in order, are:

1. ISfinder: Only the tranposase (protein) sequences; the whole transposon is not annotated.

2. NCBI Bacterial Antimicrobial Resistance Reference Gene Database: Antimicrobial resistance genes curated by NCBI.

3. UniProtKB (SwissProt): For each --kingdom we include curated proteins with evidence that (i) from Bacteria (or Archaea or Viruses); (ii) not be "Fragment" entries; and (iii) have an evidence level ("PE") of 2 or lower, which corresponds to experimental mRNA or proteomics evidence.

If you want to modify these core databases, the included script prokka-uniprot_to_fasta_db, along with the official uniprot_sprot.dat, can be used to generate a new database to put in /opt/prokka/db/kingdom/. If you add new ones, the command prokka --listdb will show you whether it has been detected properly.

⚠️ This is no longer recommended. Please use --proteins instead.

If you enable --usegenus and also provide a Genus via --genus then it will first use a BLAST database which is Genus specific. Prokka comes with a set of databases for the most common Bacterial genera; type prokka --listdb to see what they are.

If you have a set of Genbank files and want to create a new Genus database, Prokka comes with a tool called prokka-genbank_to_fasta_db to help. For example, if you had four annotated "Coccus" genomes, you could do the following:

% prokka-genbank_to_fasta_db Coccus1.gbk Coccus2.gbk Coccus3.gbk Coccus4.gbk > Coccus.faa
% cd-hit -i Coccus.faa -o Coccus -T 0 -M 0 -g 1 -s 0.8 -c 0.9
% rm -fv Coccus.faa Coccus.bak.clstr Coccus.clstr
% makeblastdb -dbtype prot -in Coccus
% mv Coccus.p* /path/to/prokka/db/genus/

Prokka comes with a bunch of HMM libraries for HMMER3. They are mostly Bacteria-specific. They are searched after the core and genus databases. You can add more simply by putting them in /opt/prokka/db/hmm. Type prokka --listdb to confirm they are recognised.

Prokka understands two annotation tag formats, a plain one and a detailed one.

The plain one is a standard FASTA-like line with the ID after the > sign, and the protein /product after the ID (the "description" part of the line):

>SeqID product

The detailed one consists of a special encoded three-part description line. The parts are the /EC_number, the /gene code, then the /product - and they are separated by a special "~~~" sequence:

>SeqID EC_number~~~gene~~~product~~~COG

Here are some examples. Note that not all parts need to be present, but the "~~~" should still be there:

>YP_492693.1 2.1.1.48~~~ermC~~~rRNA adenine N-6-methyltransferase~~~COG1234
MNEKNIKHSQNFITSKHNIDKIMTNIRLNEHDNIFEIGSGKGHFTLELVQRCNFVTAIEI
DHKLCKTTENKLVDHDNFQVLNKDILQFKFPKNQSYKIFGNIPYNISTDIIRKIVF*
>YP_492697.1 ~~~traB~~~transfer complex protein TraB~~~
MIKKFSLTTVYVAFLSIVLSNITLGAENPGPKIEQGLQQVQTFLTGLIVAVGICAGVWIV
LKKLPGIDDPMVKNEMFRGVGMVLAGVAVGAALVWLVPWVYNLFQ*
>YP_492694.1 ~~~~~~transposase~~~
MNYFRYKQFNKDVITVAVGYYLRYALSYRDISEILRGRGVNVHHSTVYRWVQEYAPILYQ
QSINTAKNTLKGIECIYALYKKNRRSLQIYGFSPCHEISIMLAS*

The same description lines apply to HMM models, except the "NAME" and "DESC" fields are used:

NAME  PRK00001
ACC   PRK00001
DESC  2.1.1.48~~~ermC~~~rRNA adenine N-6-methyltransferase~~~COG1234
LENG  284

• Where does the name "Prokka" come from?
  Prokka is a contraction of "prokaryotic annotation". It's also relatively unique within Google, and also rhymes with a native Australian marsupial called the quokka.

• Can I annotate by eukaryote genome with Prokka?
  No. Prokka is specifically designed for Bacteria, Archaea and Viruses. It can't handle multi-exon gene models; I would recommend using MAKER 2 for that purpose.

• Why does Prokka keeps on crashing when it gets to the "tbl2asn" stage?
  It seems that the tbl2asn program from NCBI "expires" after 6-12 months, and refuses to run. Unfortunately you need to install a newer version which you can download from here.

• The hmmscan step seems to hang and do nothing?
  The problem here is GNU Parallel. It seems the Debian package for hmmer has modified it to require the --gnu option to behave in the 'default' way. There is no clear reason for this. The only way to restore normal behaviour is to edit the prokka script and change parallel to parallel --gnu.

• Why does prokka fail when it gets to hmmscan?
  Unfortunately HMMER keeps changing its database format, and they aren't upward compatible. If you upgraded HMMER (from 3.0 to 3.1 say) then you need to "re-press" the files. This can be done as follows:

cd /path/to/prokka/db/hmm
mkdir new
for D in *.hmm ; do hmmconvert $D > new/$D ; done
cd new
for D in *.hmm ; do hmmpress $D ; done
mv * ..
rmdir new

• Why can't I load Prokka .GBK files into Mauve?
  Mauve uses BioJava to parse GenBank files, and it is very picky about Genbank files. It does not like long contig names, like those from Velvet or Spades. One solution is to use --centre XXX in Prokka and it will rename all your contigs to be NCBI (and Mauve) compliant. It does not like the ACCESSION and VERSION strings that Prokka produces via the "tbl2asn" tool. The following Unix command will fix them: egrep -v '^(ACCESSION|VERSION)' prokka.gbk > mauve.gbk

• How can I make my GFF not have the contig sequences in it?

sed '/^##FASTA/Q' prokka.gff > nosequence.gff

Submit problems or requests to the Issue Tracker.

• Read the release notes
• Read the ChangeLog.txt
• Look at the Github commits

Seemann T.
Prokka: rapid prokaryotic genome annotation
Bioinformatics 2014 Jul 15;30(14):2068-9. PMID:24642063

• BioPerl
  Used for input/output of various file formats
  Stajich et al, The Bioperl toolkit: Perl modules for the life sciences. Genome Res. 2002 Oct;12(10):1611-8.

• GNU Parallel
  A shell tool for executing jobs in parallel using one or more computers
  O. Tange, GNU Parallel - The Command-Line Power Tool, ;login: The USENIX Magazine, Feb 2011:42-47.

• BLAST+
  Used for similarity searching against protein sequence libraries
  Camacho C et al. BLAST+: architecture and applications. BMC Bioinformatics. 2009 Dec 15;10:421.

• Prodigal
  Finds protein-coding features (CDS)
  Hyatt D et al. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics. 2010 Mar 8;11:119.

• TBL2ASN Prepare sequence records for Genbank submission Tbl2asn home page

• Aragorn
  Finds transfer RNA features (tRNA)
  Laslett D, Canback B. ARAGORN, a program to detect tRNA genes and tmRNA genes in nucleotide sequences. Nucleic Acids Res. 2004 Jan 2;32(1):11-6.

• Barrnap
  Used to predict ribosomal RNA features (rRNA). My licence-free replacement for RNAmmmer.
  Manuscript under preparation.

• HMMER3
  Used for similarity searching against protein family profiles
  Finn RD et al. HMMER web server: interactive sequence similarity searching. Nucleic Acids Res. 2011 Jul;39(Web Server issue):W29-37.

• minced
  Finds CRISPR arrays Minced home page

• RNAmmer
  Finds ribosomal RNA features (rRNA)
  Lagesen K et al. RNAmmer: consistent and rapid annotation of ribosomal RNA genes. Nucleic Acids Res. 2007;35(9):3100-8.

• SignalP
  Finds signal peptide features in CDS (sig_peptide)
  Petersen TN et al. SignalP 4.0: discriminating signal peptides from transmembrane regions. Nat Methods. 2011 Sep 29;8(10):785-6.

• Infernal
  Used for similarity searching against ncRNA family profiles
  D. L. Kolbe, S. R. Eddy. Fast Filtering for RNA Homology Search. Bioinformatics, 27:3102-3109, 2011.

GPL v3

• Torsten Seemann
• Web: https://tseemann.github.io/
• Twitter: @torstenseemann
• Blog: The Genome Factory