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 re-sequencing data relative to this reference genome.
1. Download data files¶
First, create a directory called test_drive:
$ mkdir test_drive $ cd test_drive
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 http://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.
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 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
We’re going to use Illumina genome re-sequencing data from a strain that evolved for 20,000 generations in a long-term evolution experiment [Barrick2009a]. This data is available in the European Nucleotide Archive (ENA). Go to http://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 SRR030257_2.fastq
Now, run breseq:
$ breseq -r NC_012967.gbk SRR030257_1.fastq SRR030257_2.fastq
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).
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 can set -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.