PADLOC is a software tool for identifying antiviral defence systems in prokaryotic genomes. PADLOC screens genomes against a database of HMMs and system classifications to find and annotate defence systems based on sequence homology and genetic architecture.
PADLOC can be installed and used via the command line or via our web server.
If you use PADLOC or PADLOC-DB please cite:
Payne, L. J., Todeschini, T. C., Wu, Y., Perry, B. J., Ronson, C. W., Fineran, P. C., Nobrega, F. L., Jackson, S. A. (2021) Identification and classification of antiviral defence systems in bacteria and archaea with PADLOC reveals new system types. Nucleic Acids Research, 49, 10868-10878. doi: https://doi.org/10/gzgh
The HMMs in PADLOC-DB were built/curated using data from various sources, we encourage you to also give credit to these groups by citing them too.
It is recommended that PADLOC be installed via conda.
# Install PADLOC into a new conda environment
conda create -n padloc -c conda-forge -c bioconda -c padlocbio padloc
# Activate the environment
conda activate padloc
# Download the latest database
padloc --db-updateThe latest development version of PADLOC can be installed by cloning this GitHub repository and installing the dependencies manually.
# Clone repo to $HOME
git clone https://github.com/padlocbio/padloc $HOME/padloc
# Add to $PATH
export PATH="$HOME/padloc/bin:$PATH"
# Download the latest database
padloc --db-update# BASIC: Search an amino acid fasta file with accompanying GFF annotations
padloc --faa genome.faa --gff features.gff# BASIC: Search a nucleic acid fasta file, identifying CDS with prodigal
padloc --fna genome.fna# BASIC: Include CRISPR array information from CRISPRDetect output
padloc --faa genome.faa --gff features.gff --crispr arrays.gff# INTERMEDIATE: Use multiple cpus and save output to a different directory
padloc --faa genome.faa --gff features.gff --outdir path_to_output --cpu 4# ADVANCED: Use your own HMMs and system models
padloc --faa genome.faa --gff features.gff --data path_to_database# Try running PADLOC on the test data provided
padloc --faa padloc/test/GCF_001688665.2.faa --gff padloc/test/GCF_001688665.2.gff
padloc --fna padloc/test/GCF_004358345.1.fnaGeneral:
--help Print this help message
--version Print version information
--citation Print citation information
--check-deps Check that dependencies are installed
--debug Run with debug messages
Database:
--db-list List all PADLOC-DB releases
--db-install [n] Install specific PADLOC-DB release [n]
--db-update Install latest PADLOC-DB release
--db-version Print database version information
Input:
--faa [f] Amino acid FASTA file (only valid with [--gff])
--gff [f] GFF file (only valid with [--faa])
--fna [f] Nucleic acid FASTA file
--crispr [f] CRISPR array input file (.gff from CRISPRDetect)
Output:
--outdir [d] Output directory
Optional:
--data [d] Data directory
--cpu [n] Use [n] CPUs (default '1')
--raw-out Include a summarised raw output file
--fix-prodigal Set this flag when providing an FAA and GFF file
generated with prodigal to force fixing of sequence IDs
| File | Description |
|---|---|
| *.domtblout | Domain table file generated by HMMER. |
| *_prodigal.faa | Amino acid FASTA file generated by prodigal. |
| *_prodigal.gff | GFF annotation file generated by prodigal. |
| *_padloc.csv | PADLOC output file for identified defence systems. |
| *_padloc.gff | GFF annotation file for identified defence systems. |
| Column | Description |
|---|---|
system.number |
Distinct system number. |
seqid |
Sequence ID of the contig. |
system |
Name of the system identified. |
target.name |
Protein ID. |
hmm.accession |
PADLOC HMM accession number. |
hmm.name |
PADLOC HMM name. |
protein.name |
Defence system protein name. |
full.seq.E.value |
Full sequence E-value. From the HMMER Documentation: "The E-value is a measure of statistical significance. The lower the E-value, the more significant the hit." |
domain.iE.value |
Domain E-value. From the HMMER Documentation: "If the full sequence E-value is significant but the single best domain E-value is not, the target sequence is probably a multidomain remote homolog". |
target.coverage |
Fraction of the target sequence aligning to the HMM. |
hmm.coverage |
Fraction of the HMM aligning to the target sequence. |
start |
Start position of the target sequence in the contig. |
end |
End position of the target sequence in the contig. |
strand |
Strand; forward (+) or reverse (-) |
target.description |
Target sequence descrition taken from the input file. |
relative.position |
Relative position of the target sequence in the contig. |
contig.end |
Relative position of the last sequence in the contig. |
all.domains |
Concatenated list of all domains identified with HMMER. |
best.hits |
Top 5 hits identified with HMMER. |
The HMMs and defence system models used by PADLOC are available from the repository PADLOC-DB. The latest version of the database can be downloaded by running padloc --db-update. Alternatively, a custom database can be specified with --data [d], refer to PADLOC-DB for more information about configuring a custom database.
-
What are the requirements for an FAA/GFF file pair as input?
The GFF file should conform to the GFF3 specification. Each sequence in the FAA file is matched to an entry in the GFF file based on its ID attribute e.g. for the following sequence:
>WP_000000001.1 molybdopterin-dependent oxidoreductase, partial [Escherichia coli] AAAAAAAGLSVPGVARAVLVSRKPSNGIKAPCRFCGTGCGVLVGTQQGRVVACQGDPDAPVNRGLNCIKG YFLPKIMYGKDRLTQPLLRMKNGKYDKEGEFTPITWDQAFDVMEEKFKTALKEKGPESIGMFGSGQWTIW EGYAASKLFKAGFRSNNIDPNARHCMASAVVGFMRTFGMDEPMGCYDDIEQADAFVLWGANMAEMHPILW SRITNRRLSNThe corresponding entry in the GFF file should contain an ID attribute of the form:
ID=WP_000000001.1orID=cds-WP_000000001.1FAA/GFF combinations that are known to work 'out-of-the-box' are from genomes annotated with:
- NCBI's prokaryotic genome annotation pipeline (i.e. genomes from RefSeq and GenBank)
- JGI's IMG annotation pipeline (i.e. genomes from IMG)
- Prokka
-
Why are there parsing failures when using a GFF file from prokka?
The following warning may be thrown when using a GFF file generated by prokka:
Warning: 46324 parsing failures. row col expected actual file 2612 -- 9 columns 1 columns 'prokka.gff' 2613 -- 9 columns 1 columns 'prokka.gff' 2614 -- 9 columns 1 columns 'prokka.gff' 2615 -- 9 columns 1 columns 'prokka.gff' 2616 -- 9 columns 1 columns 'prokka.gff' .... ... ......... ......... ............ See problems(...) for more details.This is because these GFF files are appended with the contig sequences of the annotated genome. This warning can be avoided by removing the contig sequences from the GFF file with:
sed '/^##FASTA/Q' prokka.gff > nosequence.gff
-
Why can't I use a nucleotide FASTA file with < 100 kbp?
According to Prodigal's own documentation, sequences < 100 kbp are "too short to gather enough statistics to predict genes well". To avoid issues arising from this, PADLOC won't try to run prodigal over anything < 100 kbp.
If you know what you're doing then you can use Prodigal or another gene prediction program to generate your own FAA and GFF files to then use with PADLOC.
Bugs and feature requests can be submitted to the Issues tab (see Sample bug report).
These dependencies are installed automatically when using conda.
- R >= 4.1.0
R Core Team (2018). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/.- tidyverse >= 1.3.1
Wickham et al. (2019). Welcome to the tidyverse. Journal of Open Source Software, 4(43), 1686, https://doi.org/10.21105/joss.01686. - yaml >= 2.2.1
Stephens, J., et al. (2020). yaml: Methods to Convert R Data to YAML and Back. https://CRAN.R-project.org/package=yaml. - getopt >= 1.20.3
Davis, T., et al. (2019). getopt: C-Like 'getopt' Behavior. https://CRAN.R-project.org/package=getopt.
- tidyverse >= 1.3.1
- HMMER >= 3.3.2
Finn, R.D., Clements, J., and Eddy, S.R. (2011). HMMER web server: interactive sequence similarity searching. Nucleic Acids Res 39, W29–W37.
- Prodigal >= 2.6.3
Hyatt, D., Chen, GL., Locascio, P.F., Land, M.L., Larimer, F.W., and Hauser, L.J. (2010) Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics 11, 119.
The HMMs in PADLOC-DB were built/curated using data from various sources, we encourage you to also give credit to these groups by citing them too:
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Millman, A., Melamed, S., Amitai, G. and Sorek, R. (2020) Diversity and classification of cyclic-oligonucleotide-based anti-phage signalling systems. Nature Microbiology, 5, 1608–1615. doi: 10/gg84nk
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Makarova, K. S., Wolf, Y. I., Iranzo, J., Shmakov, S. A., Alkhnbashi, O. S., Brouns, S. J. J., Charpentier, E., Cheng, D., Haft, D. H., Horvath, P., et al. (2020) Evolutionary classification of CRISPR–Cas systems: a burst of class 2 and derived variants. Nat Rev Microbiol, 18, 67–83. doi: 10/ggkfgj
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The relevant refences for individual HMMs can be found by inspecting the hmm_meta.txt file provided with PADLOC-DB.
This software and data is available as open source under the terms of the MIT License.