/prokka-genome-annotation

name: "prokka-genome-annotation"
description: "Annotate prokaryotic genomes (bacteria, archaea, viruses) via Prokka's BLAST/HMM pipeline. Identifies CDS, rRNA, tRNA, tmRNA, signal peptides against Pfam, TIGRFAMs, RefSeq. Outputs GFF3, GenBank, FASTA, TSV. Use PGAP for NCBI GenBank submission; Bakta for faster NCBI-compatible annotation."
license: "GPL-3.0"

Prokka Genome Annotation

Overview

Prokka is a command-line pipeline for rapid annotation of prokaryotic genomes (bacteria, archaea, and viruses). It uses a tiered search strategy: protein-coding genes (CDS) are predicted with Prodigal and searched first against a genus-specific database, then RefSeq proteins, then Pfam/TIGRFAMs HMMs. Non-coding RNA genes (rRNA, tRNA, tmRNA) are identified with Barrnap, Aragorn, and Infernal. Prokka processes a single FASTA assembly in minutes and outputs a comprehensive annotation in GFF3, GenBank, FASTA, and tabular formats.

When to Use

• Annotating a newly assembled bacterial or archaeal genome from Illumina, PacBio, or Nanopore assemblies
• Getting functional protein annotations (CDS with product names, EC numbers, GO terms) from a draft or complete genome
• Preparing annotation files for downstream comparative genomics (Roary pan-genome, OrthoFinder)
• Annotating viral or phage genomes when kingdom-specific databases are important
• Performing metagenome-assembled genome (MAG) annotation with the `--metagenome` flag
• Parsing annotated outputs in Python with BioPython for downstream sequence or feature analysis
• Use **PGAP** (NCBI Prokaryotic Genome Annotation Pipeline) instead when the goal is NCBI GenBank submission with standards compliance
• Use **Bakta** instead for faster annotation with built-in NCBI-compatible outputs and a more regularly updated database

Prerequisites

• **Software**: Prokka ≥ 1.14, Perl 5, Prodigal, Barrnap, HMMER3, BLAST+, Aragorn, Infernal, tbl2asn
• **Python packages** (for output parsing): `biopython`, `pandas`, `matplotlib`
• **Input**: assembled genome in FASTA format (complete or draft with multiple contigs)
• **Environment**: conda strongly recommended to handle the Perl and C dependency stack

> **Check before installing**: The tool may already be available in the current environment (e.g., inside a `pixi` / `conda` env). Run `command -v prokka` first and skip the install commands below if it returns a path. When running inside a pixi project, invoke the tool via `pixi run prokka` rather than bare `prokka`.

# Install Prokka via conda/mamba (recommended)
conda install -c conda-forge -c bioconda prokka

# Or with mamba (faster)
mamba install -c conda-forge -c bioconda prokka

# Verify installation and database setup
prokka --version
# prokka 1.14.6

# Check that required tools are on PATH
prokka --depends
# prokka needs: awk, sed, grep, makeblastdb, blastp, hmmscan, ...

# Install Python parsing dependencies
pip install biopython pandas matplotlib

Quick Start

# Annotate a bacterial genome assembly — results in results/ directory
prokka genome.fasta \
    --outdir results/ \
    --prefix sample1 \
    --kingdom Bacteria \
    --cpus 4

# Check output summary
cat results/sample1.txt
# Organism: Genus species strain
# Contigs: 1
# Bases: 4639675
# CDS: 4140
# rRNA: 22
# tRNA: 86

echo "Annotation complete. Key output files:"
ls results/sample1.{gff,gbk,faa,ffn,tsv}

Workflow

Step 1: Install and Verify Prokka

Install Prokka and confirm all dependent tools are accessible in the current environment.

# Create a dedicated conda environment
conda create -n prokka_env -c conda-forge -c bioconda prokka python=3.10 -y
conda activate prokka_env

# Verify Prokka version and all tool dependencies
prokka --version
# prokka 1.14.6

prokka --depends
# Checking that required tools are installed...
# OK: makeblastdb is installed (2.13.0+)
# OK: blastp is installed (2.13.0+)
# OK: hmmscan is installed (3.3.2)
# OK: prodigal is installed (2.6.3)
# OK: barrnap is installed (0.9)

# Check available genus-specific databases bundled with Prokka
ls $(conda info --base)/envs/prokka_env/db/genus/
# Archaea  Bacteria  Mitochondria  Viruses

# Install Python parsing tools
pip install biopython pandas matplotlib

Step 2: Prepare the Input Genome

Clean and rename contigs to comply with Prokka's header requirements before annotation.

from Bio import SeqIO
import re

# Load and inspect assembly
input_fasta = "genome.fasta"
records = list(SeqIO.parse(input_fasta, "fasta"))
print(f"Input assembly: {len(records)} contigs")
total_bases = sum(len(r) for r in records)
print(f"Total bases: {total_bases:,}")
print(f"Largest contig: {max(len(r) for r in records):,} bp")
print(f"N50 approx: see assembly stats tool")

# Rename contigs to short IDs compatible with Prokka (max 37 chars)
# Prokka requires: no spaces, no special characters in header
cleaned = []
for i, rec in enumerate(records, 1):
    new_id = f"contig_{i:04d}"
    new_rec = rec.__class__(rec.seq, id=new_id, description=f"len={len(rec.seq)}")
    cleaned.append(new_rec)

SeqIO.write(cleaned, "genome_clean.fasta", "fasta")
print(f"\nWrote genome_clean.fasta with {len(cleaned)} renamed contigs")
# genome_clean.fasta: contig_0001 through contig_NNNN

# Alternatively, clean headers with a simple bash one-liner
awk '/^>/{print ">contig_" ++i; next}{print}' genome.fasta > genome_clean.fasta

# Filter out short contigs (< 200 bp) to reduce annotation noise
awk '/^>/{header=$0; next} length($0) >= 200 {print header; print}' \
    genome_clean.fasta > genome_filtered.fasta

echo "Filtered assembly ready: $(grep -c '>' genome_filtered.fasta) contigs"

Step 3: Run Basic Prokka Annotation

Run Prokka with standard options for a bacterial genome, specifying genus/species for database selection.

# Basic annotation with genus/species hint (uses genus-specific protein database first)
prokka genome_clean.fasta \
    --outdir annotation/ \