Our data for today is a small subset of Saimaa ringed seal RNA sequencing data (RNA_seq_reads.fasta). Let s first see how many reads are there:

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1 Practical Course in Genome Bioinformatics (CORRECTED ) Exercises - Day 5 Answer the 5 questions (Q1-Q5) according to the work report instructions and include Figures 1-2 in your work report according to the instructions below. NOTE: In command-line commands the -character means PRESS ENTER (end of command). Thus, if the - character is not visible at the end of the line, the command spans to the following line in this document. 1. Preliminaries Login to taito.csc.fi (not taito-shell.csc.fi) using PuTTY. Open also a WinSCP connection to taito.csc.fi Create a new directory for course materials and day 5 in the home directory (the default login directory) and load the biokit module: cd $WRKDIR # CORRECTED! #mkdir bioinfo cd bioinfo mkdir day5 cd day5 module load biokit Download the subject material of the day and unzip: rsync av progress /homeappl/home/jkammon/bioinfo/day5/materials_day5.zip./ ######################################################### # NOTE NOTE!! simple alternative to rsync command below # ######################################################### cp /homeappl/home/jkammon/bioinfo/day5/materials_day5.zip. unzip materials_day5.zip Our data for today is a small subset of Saimaa ringed seal RNA sequencing data (RNA_seq_reads.fasta). Let s first see how many reads are there: grep c > RNA_seq_reads.fasta The command counts the number of > -characters in the file. The FASTA-header for each read begins with this character. TIP: When using grep commands, always, ALWAYS include the -characters around the pattern to be searched. Otherwise you will overwrite (make empty) the input file. Q1: How many reads are there in RNA_seq_reads.fasta RNAseq data should be deduplicated first. This we can do with the following command: fastx_collapser v i RNA_seq_reads.fasta o RNA_seq_reads_dedup.fasta

2 Q2: Did the number of sequences get smaller? 2. RNAseq mapping with bowtie2 Today we will map our RNAseq reads to the same Saimaa ringed seal contig we have used in the previous days (ringed_seal_contig.fasta). bowtie2-build ringed_seal_contig.fasta ringed_seal_contig_index bowtie2 -x ringed_seal_contig_index -f -U RNA_seq_reads_dedup.fasta > bowtie_aln.sam Q3: Present the bowtie2 alignment info (console output for the abowe bowtie2 command). How many reads were there in RNA_seq_reads_dedup.fasta? How many reads were mapped to ringed_seal_contig.fasta unambiguously (in a single place)? Then we process the result Sequence Alignment Map (SAM) file to be used in Tablet viewer in the latter part of these exercises. Here, a software suite calledsamtools will prove useful. We will compress, sort and index the mapping file: samtools view -Sb bowtie_aln.sam > bowtie_aln.bam samtools sort bowtie_aln.bam o bowtie_aln.sorted.bam # CORRECTED samtools index bowtie_aln.sorted.bam 3. RNAseq mapping with STAR STAR is a recently developed mapping software the splice-awareness of which stems from the fact that it builds a splice junction database in order to account for possible variants of alternative splicing in eukaryotes. Due to recent developments of the software it has become the de facto standard of RNAseq read mapping. STAR mapping is performed in two passes to represent both 5 and 3 splice junctions. This is done on the command line as follows (replace USERNAME with your CSC username [lhbioxx] for student accounts ): # 1. run of STAR. # Creating genome folder 1pass # Run STAR in that folder # Inputs are: # genome sequence ringed_seal_contig.fasta # RNA sequences RNA_seq_reads_dedub.fasta mkdir STAR cd STAR # CORRECTED # CORRECTED mkdir 1pass STAR --runmode genomegenerate --genomedir 1pass --genomefastafiles../ringed_seal_contig.fasta --runthreadn 1 cd 1pass STAR --genomedir./ --readfilesin../../rna_seq_reads_dedup.fasta --runthreadn 1 # CORRECTED

3 cd.. # 2. run of STAR # Creating genome folder 2pass # Run STAR in that folder # Inputs are: # genome sequence ringed_seal_contig.fasta # RNA sequences RNA_seq_reads_dedub.fasta # Splice Junctions, 1 run 1pass/SJ.out.tab mkdir 2pass STAR --runmode genomegenerate --genomedir 2pass --genomefastafiles../ringed_seal_contig.fasta --sjdbfilechrstartend 1pass/SJ.out.tab -- sjdboverhang 75 --runthreadn 1 cd 2pass STAR --genomedir./ --readfilesin../../rna_seq_reads_dedup.fasta --runthreadn 1 # CORRECTED Result mapping is in a file called Aligned.out.sam. We will also process this into BAM format with samtools. Be sure to process here the SAM file that is in the 2pass directory: samtools view Sb Aligned.out.sam > STAR_aln.bam STAR mapping results should be further filtered as they usually are very noisy. There s another mapping file manipulation tool in biokit calledbamtools the filter function of which we are going to use next: bamtools filter -in STAR_aln.bam -isduplicate false -isprimaryalignment true -mapquality 255 -out STAR_aln_filtered.bam samtools sort STAR_aln_filtered.bam o STAR_aln_filtered.sorted.bam samtools index STAR_aln_filtered.sorted.bam #CORRECTED ABOVE Copy the following files to your local computer using WinSCP (it is recommended to copy them into same folder on the local computer, especially the.bam and.bam.bai files): ringed_seal_contig.fasta ringed_seal_genes.gff bowtie_aln.sorted.bam bowtie_aln.sorted.bam.bai STAR_aln_filtered.sorted.bam STAR_aln_filtered.sorted.bam.bai 4. Visualizing the mappings with Tablet We will next visualize the two mappings in Tablet. Tablet website can be found at: Tablet can be launched using Java Web Start (same way as DNAplotter) at the link: (Add the latter of the two links to your list of Java accepted sites in the Java Control Panel if needed.)

4 4A. Bowtie mapping visualization Select Open assembly from the top left, then set Primary assembly file to bowtie_aln.sorted.bam Set Reference/consensus file or URL to ringed_seal_contig.fasta Then click Open. Disregard any errors / warnings (Click Open / OK to all). Click the sole entry in the appearing contig list on the left side in order to open the contig for view. Click Import features from the top left, navigate to the ringed_seal_genes.gff file and click Open. Move to the Advanced tab in the main view. Set Window size on the left to 120,000 so that we can see the whole contig. Move back to Home tab and Zoom out using the small scroller in the top pane so that the whole contig can be seen. Notice the bars on the GENE track, their number and positions, etc Include a screenshot of this view as Figure 1 in your work report. Q3: Where do the predicted genes seen on the GENE track originate from and how does the evidence of the RNAseq support the the predicted genes here? 4B. STAR mapping visualization Select Open assembly from the top left, then set Primary assembly file to STAR_aln_filtered.sorted.bam Set Reference/consensus file or URL to ringed_seal_contig.fasta (it may be that already). Then click Open. Disregard any errors / warnings (click Open / OK to all). Click the sole entry in the appearing contig list on the left side in order to open the contig for view. This takes a while. Click Import features from the top left, navigate to the ringed_seal_genes.gff file and click Open. Move to the Advanced tab in the main view. Set Window size on the left to 120,000 so that we can see the whole contig. Move back to Home tab and Zoom out using the small scroller in the top pane so that the whole contig can be seen. Right click somewhere on the center bar with CIGAR-annotations and click the GENE track visible if it is not visible by default. You may also click additional tracks visible. Save a screenshot of this view as Figure 2 for your work report. Q4: What causes the red lines visible in this mapping? How does the evidence of the RNAseq with STAR mapping support the predicted genes? 5. Checking some new concepts learned Q5: Define in your own words the following concepts. One sentence should be enough but you may use more if you see fit. -RNA sequencing -Read mapping -Transcriptome

5 -Mapping coverage 6. Added tutorial on Tablet viewer I was quite lost with the tablet viewer. So here I give extra information that I gathered on Tablet. Data, used in the demonstration is here: Download the data to your computer. Unzip it to a separate directory. Start the Tablet Java viewer from the web link: Load the data from the folder that you created before. I use bowtie data in this demonstration. See section 4.a. for the required steps to load assembly and gff files. After you load your assembly you get the following interface: Figure 1: Summary of the Tablet interface. After you have imported features (gff file) and selected contig the view is following before Window size adjustment.

6 Figure 2. View before adjustment of Window Size and Zoom View above is good for looking for details at different areas but bad for overall view. This can be corrected with the Window Size adjustment and Zoom Adjustment (explained in section 4.a.). After that we see the view below: Figure 3 Tablet view with zoom all the way to left I consider a slightly detailed view better for viewing the support of RNA-seq data:

7 Figure 4. Tablet interface with slightly adjusted zoom setting By simply adjusting the zoom and by moving left and right you ll be able to browse the support from RNA sequences to different gene areas. New questions on Tablet results: Data that was generated at CSC, is also available here as a zip file: Download the data to your computer. (You could get it with winscp from CSC, as before.) Unzip it to a separate directory. Start the Tablet Java viewer from the web link: New-Q1: Load Bowtie data as in the exercises before. This was in the section 4.a. a) Can you find regions where RNA-seq data supports the predicted gene area? b) Which gene number has a strongest support? c) Is there strong peaks outside the gene regions? You can include a picture(s) of the interface to support your results. New-Q2: Load STAR results as in the exercises before. This was in the section 4.b. Now you see the gaps in the alignment as red line. a) Do the red lines stay mostly within one gene region or do they go across the different regions? b) What does this suggest about the predicted genes? Is this support against or in favor the predictions? c) Another gene prediction suggested that all four areas would be linked to same gene. Based on the results can you comment this other model? You can include a picture(s) of the interface to support your results.

8 Please return the work report of these exercises to as PDF at latest on Fri 3 March General instructions for the report can be found on the bottom of homepage: