Andrew Severin

Andrew Severin

His PhD was in Biophysics/NMR spectroscopy. He did a Bioinformatics Postdoc in Soybean genetics and now runs the Genome Informatics Facility at Iowa State University. He is passionate about evolution and the science behind the genome. There is so much we don't know about how the elements in a genome interact to create the fine balance of gene expression, modification and 3D structure that create the dynamic range of phenotypes we observe. As sequencing technology continues to improve and the cost continues to decrease, we will be able to ask more complex questions that increase our understanding via comparative and translational genomics.

Learning Objectives

Upon completion of this section on Genome Assembly you will be able to

  • Download data from SRA
  • Evaluate the correct parameters to use when running canu for genome assembly
  • Execute Canu and obtain a the assembled genome of Bacillus thuringiensis

Let us assemble a bacterial genome Bacillus thuringiensis strain: HS18-1. This particular genome is interesting because it shows insecticidal activity against Diptera. The raw data contains 1.5G of data and the genome size is 6.4 mb. The assembly can be found on NCBI. Therefore, we will have over 200x coverage, plenty for a genome assembly with canu. Canu recommends 30-60x minimum coverage. The paper for this assembly can be read here

Download the data from ENA

The European Nucleotide Archive has the files already in fastq format and it is easy to download. The main page with this project data is PRJNA288953 We are only going to take the pacbio data which is the 3rd file link under the ‘'’Read Files’’’ tab.

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wget ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR209/006/SRR2093876/SRR2093876_subreads.fastq.gz

Running Canu

The name of the module will vary here and you should check to see what version you are using. In this tutorial we used version 1.8 with java/1.8.0_121

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#!/bin/bash
#SBATCH --nodes=1
#SBATCH --time=24:00:00
#SBATCH --mem=64G
#SBATCH --mail-user=YOUREMAILADDRESS
#SBATCH --mail-type=begin
#SBATCH --mail-type=end
#SBATCH --error=JobName.%J.err
#SBATCH --output=JobName.%J.out
module load canu

canu -p Bt2 -d Bt2_assembly genomeSize=6.2m  -pacbio-raw SRR2093876_subreads.fastq.gz

parameters explained

You can read all of this from the quick start and documentation for Canu but here are the basics.

  • -p is the assembly prefix and this is the name that will be prefixed to all output Files
  • -d is the directory that it will make and write all the files to.
  • input file types (multiple files can be listed after this parameter but should be of the same type)
    • -pacbio-raw
    • -pacbio-corrected
    • -nanopore-raw
    • -nanopore-corrected

OUTPUT

Canu took about half an hour to run this dataset. The output looked like this.

Files output from assembly
Bt2.contigs.fasta Bt2.contigs.gfa Bt2.contigs.layout
Bt2.contigs.layout.readToTig Bt2.contigs.layout.tigInfo Bt2.correctedReads.fasta.gz
Bt2.gkpStore Bt2.gkpStore.err Bt2.gkpStore.gkp
Bt2.report Bt2.trimmedReads.fasta.gz Bt2.unassembled.fasta
Bt2.unitigs.bed Bt2.unitigs.fasta Bt2.unitigs.gfa
Bt2.unitigs.layout Bt2.unitigs.layout.readToTig Bt2.unitigs.layout.tigInfo
canu.out canu-logs canu-scripts
correction trimming unitigging

You can get a sense of progress on your larger datasets by looking at the canu-scripts folder. The final script is canu.12.sh.

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Bt2_assembly/canu-scripts/
canu.01.out  canu.02.out  canu.03.out  canu.04.out  canu.05.out  canu.06.out  canu.07.out  canu.08.out  canu.09.out  canu.10.out  canu.11.out  canu.12.out
canu.01.sh   canu.02.sh   canu.03.sh   canu.04.sh   canu.05.sh   canu.06.sh   canu.07.sh   canu.08.sh   canu.09.sh   canu.10.sh   canu.11.sh   canu.12.sh

The assembled contigs are in Bt2.contigs.fasta. Recall we set the -p prefix parameter to Bt2. Other useful files include:

  • Bt2.unassembled.fasta These are reads that weren’t assembled.
  • Bt2.report This file contains information about each step.

Below I grabbed the contigs that appear to be Circular representing plasmids. This is the same number of plasmids reported by the NCBI assembly.

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grep ">" Bt2_assembly/Bt2.contigs.fasta  | grep Circular=yes
>tig00000137 len=515061 reads=2993 covStat=742.81 gappedBases=no class=contig suggestRepeat=no suggestCircular=yes
>tig00000138 len=344327 reads=1984 covStat=496.27 gappedBases=no class=contig suggestRepeat=no suggestCircular=yes
>tig00000162 len=99169 reads=378 covStat=251.39 gappedBases=no class=contig suggestRepeat=no suggestCircular=yes
>tig00000163 len=102856 reads=497 covStat=185.89 gappedBases=no class=contig suggestRepeat=no suggestCircular=yes
>tig00000167 len=52597 reads=520 covStat=-94.48 gappedBases=no class=contig suggestRepeat=no suggestCircular=yes
>tig00000168 len=14459 reads=116 covStat=-11.79 gappedBases=no class=contig suggestRepeat=no suggestCircular=yes
>tig00000169 len=24282 reads=281 covStat=-75.26 gappedBases=no class=contig suggestRepeat=no suggestCircular=yes
>tig00000175 len=8489 reads=267 covStat=-146.76 gappedBases=no class=contig suggestRepeat=no suggestCircular=yes
>tig00002887 len=15142 reads=37 covStat=32.30 gappedBases=no class=contig suggestRepeat=no suggestCircular=yes

Additional Reading

Below are links to canu documentation, GitHub repo and other relevant websites related to canu.