In this test drive, we will first download a bacterial genome and FASTQ files of Illumina reads. Then, we will use breseq to predict mutations that are present in the resequencing data relative to this reference genome.

1. Download data files

First, create a directory called test_drive:

$ mkdir test_drive
$ cd test_drive

Reference sequence

breseq prefers the reference sequence in Genbank or GFF3 format. In this example, the reference sequence is Escherichia coli B strain REL606. The Genbank (Refseq) accession number is: NC_012967. You can search for this sequence at https://www.ncbi.nlm.nih.gov/ or follow this direct link.

Once the sequence is displayed, you will want to select "Show sequence" from the Display options on the right then click "Update View" and let the sequence download complete. Finally, use the "Send:" menu to choose "Complete Record" and Destination: "File" and "Genbank (Full)". It should start downloading a file called sequence.gb. Rename this to NC_012967.gbk after it downloads.

[!WARNING] A common error in using breseq is to download and try to use a GenBank file that does not include the DNA sequence of the genome. Remember to "Show sequence" from the Display options on the right then click "Update View" before downloading to avoid this problem!

If you open the GenBank file that you downloaded and search or scroll way down in a text editor, you should see a section with ORIGIN followed by the DNA sequence of the genome, like this:

ORIGIN
              1 agcttttcat tctgactgca acgggcaata tgtctctgtg tggattaaaa aaagagtgtc
             61 tgatagcagc ttctgaactg gttacctgcc gtgagtaaat taaaatttta ttgacttagg
            121 tcactaaata ctttaaccaa tataggcata gcgcacagac agataaaaat tacagagtac
            181 acaacatcca tgaaacgcat tagcaccacc attaccacca ccatcaccat taccacaggt
            241 aacggtgcgg gctgacgcgt acaggaaaca cagaaaaaag cccgcacctg acagtgcggg

Read files

We're going to use Illumina genome resequencing data from a strain that evolved for 20,000 generations in the Lenski long-term evolution experiment [Barrick2009a]. This data is available in the European Nucleotide Archive (ENA). Go to https://www.ebi.ac.uk/ and search for the accession number: SRR030257. Then click on the accession number to open the record and download the two data files using the links in the 'ftp' column.

Move all three of these files into the test_drive directory that you created.

2. Run breseq

Check to be sure that you have changed into the test_drive directory and that you have all of the input files (and have uncompressed them).

$ ls
NC_012967.gbk        SRR030257_1.fastq.gz   SRR030257_2.fastq.gz

Now, run breseq:

$ breseq -r NC_012967.gbk SRR030257_1.fastq.gz SRR030257_2.fastq.gz

The first named argument (-r) is the reference sequence. If you had multiple reference sequences, you could input multiple ones (e.g., -r NC_012967.gbk -r plasmid.gbk).

The unnamed arguments at the end of the command line are the read files. You can input as many as you need and mix FASTQ files from different sequencing technologies (e.g., Illumina and 454).

For the unnamed read argument(s) but not for the reference sequence arguments you can use globs that match multiple files. For example, in this case, you could use *.fastq.gz to match both input FASTQ files.

[!WARNING] Running breseq on a full data set like this is not fast. Depending on your computer, this could take several hours. To speed things up, you should set the -j option to the number of cores on your machine to enable multithreaded execution of some steps (e.g., -j 4 for a quad-core machine). If you want to speed this example up, you might also include only one of the two input read files on the command line.

3. Open breseq output

Open the file index.html in the new output directory. This describes the predicted mutations and also evidence for mutations that breseq could not resolve into mutational events. The tables in this HTML file are more fully described in the section on output-format.