11  Map Reads to the Genome

Read mapping is a common bioinformatics technique that aligns sequencing reads to a reference genome. It is often used as part of RNA-seq, or transcriptomic, analyses, where the number of sequencing reads aligned to a part of the genome indicates the level to which a gene in that region is transcribed. It is also central to technologies such as ChIP-seq (chromatin immunoprecipitation and sequencing), which enables the locations of regulatory promoter binding sites to be found.

Today, you will use the same approach to compare the Wuhan 1 strain of SARS-CoV-2 that you have assembled to a reference genome from a 2003 SARS virus strain (AY278741). To do this you will use the BWA-MEM2 read mapping software (Vasimuddin et al. (2019)) to align the cleaned forward and reverse reads from Wuhan 1 to the AY278741 genome assembly and annotation.

• BWA-MEM2 documentation

ImportantGood practice

When reporting read mapping in a manuscript or dissertation, you should always state:

1. The software tool you used, with its version number and a citation of the paper describing it (if available; provide a URL to the software if there is no paper)
2. The parameters used when running the tool (if default parameters were used, state this)
3. The accession numbers of the reference genome and read data (if available)

11.1 Using BWA-MEM2

1. Navigate to the BWA-MEM2 tool
2. Select the BWA-MEM2 tool
3. Choose Use a reference from history and build index if necessary under Will you select a reference genome…
4. Choose the SARS_AY278741.fasta sequence under Use the following dataset as the reference sequence
5. Choose Paired under Single of Paired-end reads
6. Select the (R1 paired) and (R2 paired) trimmomatic output reads
7. Click Run Tool

NoteVideo: Mapping SARS-CoV-2 reads to the 2003 SARS genome using BWA-MEM2

Caution

BWA-MEM2 can take a few minutes to run to completion.

11.2 BWA-MEM2 Output

Unlike many of the other tools you will use today, BWA-MEM produces binary file output, which is not human-readable. However, Galaxy can read it and generate a human-friendly translation. The output format of BWA-MEM2 is .bam, and this can be used as an annotation track in JBrowse.

NoteVideo: Visualising the BWA-MEM2 .bam output as text

11.3 Visualising the mapping in JBrowse

We can use the .bam file in JBrowse, but we need to set up another visualisation like that in Chapter 10.

1. Navigate to the JBrowse tool in the Tools sidebar
2. Select the JBrowse tool
3. Under Reference genome to display, select the Use a genome from history option
4. Select the SARS_AY27874.fasta genome file in Select the reference genome
5. Click on + Insert Track Group to add a new track group
6. In the new track group, enter Annotation into the Track Category field
7. Click on + Insert Annotation Track to add a new track to hold the annotation
8. Make sure that the Track Type of the new annotation track is GFF/GFF3/BED Features
9. In GFF/GFF3/BED Track Data, select the SARS_AY27874.gff3 annotation file for the SARS 2003 isolate
10. Click on + Insert Track Group to add a new track group
11. In the new track group, enter Mapping into the Track Category field
12. Click on + Insert Annotation Track to add a new track to hold the mapping data
13. Make sure that the Track Type of the new annotation track is BAM Pileups
14. In BAM Track Data, select the BWA-MEM2 .bam output file
15. Select Yes under Autogenerate SNP Track
16. Click Run Tool

NoteVideo: Configuring JBrowse to visualise BWA-MEM2 mapping data

Click on the eye icon for the new JBrowse output, and select the following tracks to be shown:

1. Reference sequence
2. Annotation (SARS_AY278741.gff3)
3. Mapping (SNPs/Coverage)

to obtain a visualisation of reads that map to the spike (S) protein of SARS 2003, like that shown in Figure 11.1.

Figure 11.1: JBrowse visualisation of a BWA-MEM2 mapping of SARS-CoV-2 reads against a SARS 2003 reference genome. The annotation track shows predicted genes, including the spike (S) protein. The mapping track shows individual SNPs (teardrops), and total mapping read depth (the stacks above the teardrops).

While the spike (S) protein is being visualised, select the (mapped reads in BAM format track) to obtain a visualisation similar to the one in Figure 11.2.

Figure 11.2: JBrowse visualisation of a BWA-MEM2 mapping of SARS-CoV-2 reads against a SARS 2003 reference genome in the regions of the spike (S) protein.

You can click on the header of the SNP track in JBrowse and select Pin to top, so that you can zoom in and see individual SNPs, as in the video below.

NoteVideo: Visualising SNPs in JBrowse

TipQuestions

1. Do SARS-CoV-2 reads map uniformly to the SARS (2003) genome
2. Where do SARS-CoV-2 and SARS (2003) genomes appear to differ?
3. When SARS-CoV-2 reads do map to the SARS (2003) genome, how many SNPs are there?
4. What is the biological significance of the pattern of reads not matching the spike (S) protein?
5. What implications does this have for vaccine development?

11.4 Next Steps

We can find SNPs by visual inspection in a tool like JBrowse, but there can be very many of them - as you can see. To ensure reproducibility and accuracy, and avoid errors we need to use dedicated software and pipelines when analysing mapping data. You will have a chance to do this in Chapter 12.

Vasimuddin, Md, Sanchit Misra, Heng Li, and Srinivas Aluru. 2019. “Efficient Architecture-Aware Acceleration of BWA-MEM for Multicore Systems.” In 2019 IEEE International Parallel and Distributed Processing Symposium (IPDPS). Rio de Janeiro, Brazil: IEEE.