Overview

As has been mentioned several times, variants are anything that is different from a reference genome, but large insertions of novel DNA represent something of an unknown unknown. If a read doesn't map is it because its some kind of contamination, or is it because something new has entered into the sample. This tutorial is an attempt to use tools you are already familiar with to identify such novel DNA mutations. As this is a new tutorial any feedback is very welcome and helpful.

Learning Objectives

1. Extract reads where one or both reads do not map to reference

2. de novo assemble reads

Relationship to other tutorials

1. As presence of adapter can cause problems with assembly, make sure adapters have been trimmed

2. Reads will be mapped with bowtie2

3. non-mapped reads will be extracted, consider checking quality of these reads and possible additional trimming

4. Reads will then be assembled

None of these other tutorials are required to complete this tutorial, but additional information about individual steps may be found there.

Identification of a novel plasmid

One example of novel DNA being present is when a given sample may have a virus or plasmid associated with a sample. Here we will take a sample known to have a high copy plasmid associated with it, but map the reads against only the genome. Unaligned reads would then be expected to be able to assemble into a plasmid.

Get some data

^ above transfers 2 fastq files and a reference file.

Map read using bowtie2

This is the same process used in the read mapping tutorial, and therefore presented with little comment except to remark on differences. Refer to that tutorial for more in-depth information.

1. Convert reference to fasta

   module load bioperl bp_seqconvert.pl --from genbank --to fasta < CP009273.1_Eco_BW25113.gbk > CP009273.1_Eco_BW25113.fasta

    

    

2. Index the reference

   mkdir bowtie2 module load bowtie/2.3.4 bowtie2-build CP009273.1_Eco_BW25113.fasta bowtie2/CP009273.1_Eco_BW25113

    

    

3. The following command will take ~5 minutes to complete. Before you run the command execute 'bowtie2 -h' so while the command is running you can try to figure out what the different options are doing that we did not include in our first tutorial.

   Map reads

   bowtie2 --very-sensitive-local -t -p 48 -x bowtie2/CP009273.1_Eco_BW25113 -1 SRR4341249_1.fastq -2 SRR4341249_2.fastq -S bowtie2/SRR4341249-vsl.sam --un-conc SRR4341249-unmapped-vsl.fastq

Assemble unmapped reads

This is the same process used in the plasmid assembly portion of the genome assembly tutorial, and therefore presented with little comment except to remark on differences. Refer to that tutorial for more in-depth information.

1. Attempt to assemble with plasmidspades.py which expects to find circularized plasmid type sequences. Command expected to take ~5 minutes

   run plasmid spades

   plasmidspades.py -t 48 -o unmapped_plasmid -1 SRR4341249-unmapped-vsl.1.fastq -2 SRR4341249-unmapped-vsl.2.fastq

2. Additionally attempt to assemble with base spades.py command which uses different internal settings to potentially identify different types of novel DNA from our unmapped reads. Command expected to take ~5 minutes. 

   run plasmid spades

   spades.py -t 48 -o unmapped_full -1 SRR4341249-unmapped-vsl.1.fastq -2 SRR4341249-unmapped-vsl.2.fastq

Compare contigs generated from different assemblies

Recall from genome assembly tutorial the file we are most interested in is the contigs.fasta file in each output directory (unmapped_plasmid and unmapped_full).

Next steps

Here we have presented a proof of concept that unmapped reads can be used to find something that we actually did know was present. We also found something that was even longer that wasn't expected.

Additional questions are:

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