Introduction to RNA-Seq & Transcriptome Analysis Jessica Holmes

Introduction to RNA-Seq & Transcriptome Analysis Jessica Holmes

Introduction to RNA-Seq & Transcriptome Analysis Jessica Holmes PowerPoint by Shounak Bhogale 02/04/2020 RNA-Seq Lab | Shounak Bhogale | 2019 1 Exercise 1. Use the RNA-STAR to align RNA-Seq reads 2. Use htseqCounts to count the reads. 3. Use edgeR to find differential expressed genes.

4. Use IGV for visualization (If time permits). 02/04/2020 RNA-Seq Lab | Shounak Bhogale | 2019 2 v Pipeline Overview 02/04/2020 RNA-Seq Lab | Shounak Bhogale | 2019

3 Input Data RNA-Seq: 100 bp, single end data replicate sample fastq name # reads # Replicate a_0.fastaq, TP0 100,000 1,2 b_0.fastaq

Replicate a_8.fastaq, TP8 100,000 1,2 b_8.fastaq Genome & gene information name description mouse_chr12.fn Fasta file with the sequence of chromosome 12 from the mouse genome a Mouse_chr12.gt GTF file with gene annotation, known genes f

02/04/2020 RNA-Seq Lab | Shounak Bhogale | 2019 4 Step 1A: Logging into Galaxy Go to: http://compgen.knoweng.org/galaxy Click Enter Click Login Input your login credentials. Click Login. 02/04/2020

RNA-Seq Lab | Shounak Bhogale | 2019 5 Step 1B: Galaxy Start Screen The resulting screen should look like the figure below: 02/04/2020 RNA-Seq Lab | Shounak Bhogale | 2019 6 Step 2A: Accessing Input Files

At the top of the page, click Shared Data. Then click Histories. 02/04/2020 RNA-Seq Lab | Shounak Bhogale | 2019 7 Step 2B: Accessing Input Files Click sb_transcriptomics You should see this page. Click Import History.

02/04/2020 RNA-Seq Lab | Shounak Bhogale | 2019 8 Step 2C: Accessing Input Files Click Import You should see an imported history like the following. 02/04/2020 RNA-Seq Lab | Shounak Bhogale | 2019

9 . Step 1: Alignment using RNA-STAR In this exercise, we will be aligning RNA-Seq reads to a reference genome in the absence of gene models. Splice junctions will be found de novo. Remember, we are not going to provide any genic structure information. 02/04/2020 RNA-Seq Lab | Shounak Bhogale | 2019 10

Search RNA STAR in the search box. Click on RNA STAR under NGS: RNA Analysis 02/04/2020 RNA-Seq Lab | Shounak Bhogale | 2019 11 You should see this on the screen. 02/04/2020

RNA-Seq Lab | Shounak Bhogale | 2019 12 Set fastaq file as a_0.fastq et reference genomes as input. Select mouse_chr12.fna as the fasta file. Set mouse_chr12.gtf as the input gene model. Set length as 99.

Click execute after making these changes. Keep rest of the parameters as default. 02/04/2020 RNA-Seq Lab | Shounak Bhogale | 2019 13 nce the run is complete three files generated will turn green. k on the pencil symbol next to the dataset 9 to change the name of the dataset ange the name in the name databox to a_0.bam and then click save.

02/04/2020 RNA-Seq Lab | Shounak Bhogale | 2019 14 Repeat above steps for remaining three fastaq sets b_0.fastq, a_8.fastq and b_8.fastq imilarly change the names of remaining bam files once they are generated. Now we are ready for the next step. 02/04/2020

RNA-Seq Lab | Shounak Bhogale | 2019 15 Step 2: Read aligned counts Use htseq-count to generate the aligned counts for each bam files generated in step 1. 02/04/2020 RNA-Seq Lab | Shounak Bhogale | 2019 16

Search htseq-count in the search box. Click on htseq-count to open the tool. 02/04/2020 RNA-Seq Lab | Shounak Bhogale | 2019 17 Select a_0.bam as the input. Change stranded to Reverse.

Keep rest of the parameters as default and click Execute. 02/04/2020 RNA-Seq Lab | Shounak Bhogale | 2019 18 Change the name of the following datasets. Here we generated the counts for each gene in the 4 datasets. Now we are ready for the final step. 02/04/2020

RNA-Seq Lab | Shounak Bhogale | 2019 19 Step 3: Finding differentially expressed genes Now we will use edgeR to analyze the count files generated in step 2 to find differentially expressed genes between two time points. 02/04/2020 RNA-Seq Lab | Shounak Bhogale | 2019

20 Search edgeR in the search box on the left. Click on edgeR to open the tool. This should come up on the screen. 02/04/2020 RNA-Seq Lab | Shounak Bhogale | 2019 21 Select Single Count Matrix

Select all.txt as the input dataset. Enter Mouse as factor name. Enter groups as TP8,TP8,TP0,TP0 02/04/2020 RNA-Seq Lab | Shounak Bhogale | 2019 22 Set contrast as TP8-TP0.

Click on Filter low counts. Set Yes to filter lowly expressed genes. Set Counts. Set minimum Counts as 5. Set Yes for normalized counts table and rscript. And now Execute! 02/04/2020 RNA-Seq Lab | Shounak Bhogale | 2019 23

3 files will be generated after the run is complete. Click on the eye symbol next to the rep file. Scroll down through the report. For our dataset there are no DEGs. 02/04/2020 RNA-Seq Lab | Shounak Bhogale | 2019 24 Conclusion

We did the following today. 1. Alligned RNA-seq data using RNA-STAR 2. Used htseq-count to count the aligned reads for each gene. 3. Used edgeR to find DEGs in the data 02/04/2020 RNA-Seq Lab | Shounak Bhogale | 2019 25 Useful links Online resources for RNA-Seq analysis questions http://www.biostars.org/ - Biostar (Bioinformatics explained) http://seqanswers.com/ - SEQanswers (the next generation sequencing community)

Most tools have a dedicated lists Information about the various parts of the Tuxedo suite is available here http://ccb.jhu.edu/software.shtml Genome Browsers tutorials http://www.broadinstitute.org/igv/QuickStart/ - IGV tutorials http://www.openhelix.com/ucsc/ - UCSC browser tutorials Contact us at: [email protected] [email protected] (openhelix is a great place for tutorials, UIUC has a campus-wide subscription) 02/04/2020

RNA-Seq Lab | Shounak Bhogale | 2019 26 Extra Material IGV 02/04/2020 RNA-Seq Lab | Shounak Bhogale | 2019 27 .

Visualization Using IGV The Integrative Genomics Viewer (IGV) is a tool that supports the visualization of mapped reads to a reference genome, among other functionalities. We will use it to observe where hits were called for the alignment for the two samples (TP0 and TP8), and the differentially(!) expressed genes. 02/04/2020 RNA-Seq Lab | Shounak Bhogale | 2019 28 Step 9: Start IGV In this step, we will start IGV and load the select mouse_chr12.fna file, the known genes file

(mouse_chr12.fna), the hits for both sample groups, and the merged transcriptome. Graphical Instruction: Load Genome 1. Within IGV, click the Genomes tab on the menu bar. 2. Click the the Load Genome from File option. 3. In the browser window, select mouse_chr12.fna(genome).

Graphical Instruction: Load Other Files 1. Files to Load mouse_chr12.fna Within IGV, click the FILE tab on the menu bar. a_0.bam 2. Click the Load from File option. 3.

Select the mouse_chr12.gtf file (known genesa_8.bam file). 4. Perform Steps 1-3 for the files to the right. 02/04/2020 RNA-Seq Lab | Shounak Bhogale | 2019 b_0.bam b_8.bam 29

Step 10: Visualization With IGV Click here and type the following location of a non-differentially expressed gene: NC_000078.6:17,788,398-17,793,435 02/04/2020 RNA-Seq Lab | Shounak Bhogale | 2019 30

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