Synteruptor scripts

Description

This is a set of scripts that create a Synteruptor database from a set of genome files.

Installation

We recommend runnning the Docker image as it is the most straightforward way to run this program.

Docker image

See the README file in the docker/ folder for steps to build an image.

Installation requirements

If you want to install it in your own machine, here's the list of requirements.

Recommended Ubuntu packages

Assuming Ubuntu 22.04:

git parallel rename bioperl libstatistics-basic-perl ncbi-blast+ sqlite3

Details

The programs and libraries required to run the scripts are as follow:

• Perl

• Bioperl

  Hint for local installs if you don't have it in a package: use cpanminus

	curl -L http://cpanmin.us | perl - App::cpanminus
	curl -L http://cpanmin.us | perl - Bio::Perl

• Statistics::Basic (libstatistics-basic-perl)

• GNU parallel (parallel)

• Blast+ (ncbi-blast+)

• Python 3

• Python 3 libs (either from a package or with manager like pip):

  sqlite3

Environment

Add the path to the src/ folder to your PATH

Input

Synteruptor requires each genome assembly to be in a file each with both DNA sequence and annotations.

File formats supported are:

• Genbank (.gb*)
• EMBL (.dat, .embl, .txt)

Note

Make sure you have at least 2 genome files to compare.

Usage

• Move to a working directory
• Place genomic files in a subfolder NB: intermediate files will be created in that subfolder
• Run the script run_gbk.sh

run_gbk.sh -i /path/to/subfolder -n db_name

You can run this script with multiple threads by adding the parameter -j. E.g. to run on 4 cores:

run_gbk.sh -i /path/to/subfolder -n db_name -j 4

• It will then create a database named db_name.sqlite in the subfolder, as well as a Blast DB db_name.sqlite.faa
• Place the DB in the db folder of the Web Synteruptor to explore its data. Make sure the web server has permission to read the db folder and the database file.

3 genomes example

As an example, download the gbff files for 3 genomes from NCBI:

• Streptococcus anginosus C1051 (GCF_000463465.1)
• Streptococcus anginosus C238 (GCF_000463505.1)
• Streptococcus anginosus subsp. whileyi MAS624 (GCA_000478925.1) You can do this through this link.

Unzip the file and move the .gbff files in a subfolder, make sure to rename each file to something meaningful.

Then run the script on this subfolder as above (assuming 4 cores):

run_gbk.sh -i /path/to/subfolder -n db_name -j 4

Database content

Tables

The database contains the following tables at initiation:

• genes
• genomes
• genome_parts(separate DNA sequences) The data in those tables come from the input files.

When running run_migenis.sh the following tables are populated:

• orthos(orthologs and paralogs genes pairs, from BLAST BRH)
• info(metadata)
• pairs(orthologs and paralog pairs)
• blocks(synteny blocks)
• breaks(synteny breaks)
• breaks_genes(all genes in a break, per species)
• breaks_ranking
• breaks_graph (to represent similar breaks among a group of species)
• goc

Additional tables and views created to ease the queries:

• orthos_all(joined pairs with genes species1 and genes species2)
• blocks_all(joined block, orthos pairs at start of block, end of block + genes at start and end in both species)
• breaks_all(joined break, blocks left and right, orthos pairs left and right, genes at start and end un both species)

The final breaks data are stored in breaks (breaks_all for more data) and breaks_ranking (contains the various attributes used for ranking).

You can use sqlite3 .schema command to see the details of each table.