Regulatory Genomics Lab Saurabh Sinha Regulatory Genomics Lab v1 | Saurabh Sinha1 Powerpoint by Casey Hanson

Regulatory Genomics Lab v1 | Saurabh Sinha 1

Regulatory Genomics Lab

Saurabh Sinha

Powerpoint by Casey Hanson


Exercise

In this exercise, we will do the following:.

1. Use Galaxy to manipulate a ChIP track for BIN in D. Mel.

2. Subject peak sets to MEME suite.

3. Compare MEME motifs with Fly Factor Survey motifs for BIN.

4. Subject peak set to a gene set enrichment test.


Step 0: Shared Desktop Directory

For viewing and manipulating files on the classroom computers, we provide a shared directory in the following folder on the desktop:

classes/mayo

In today’s lab, we will be using the following folder in the shared directory:

classes/mayo/sinha


Computational Prediction of MotifsIn this exercise, we will upload a ChIP track of the transcription factor BIN in Drosophila Melanogaster to Galaxy.

After performing various file manipulations, we will use the MEME suite to identify a motif from the top 100 ChIP regions.

Subsequently, we will compare our predicted motif with the experimentally validated motif for BIN at Fly Factor Survey.


Step 1: Upload BIN ChIP Track to GalaxyLogin to galaxy at main.g2.bx.psu.edu/

Click Get Data and then Upload File

Upload our ChIP file:

classes/mayo/sinha/BIN_Fchip_s11_1000.gff

Set the File Format to gff.

Set Genome to dm3.

Click Execute

https://main.g2.bx.psu.edu/


Step 2: Sort ChIP Track By Score

Click on Filter and Sort and Sort.

Under Sort Dataset, select our ChIP track.

Under on column, select c6 (column 6).

Under with flavor, select Numerical Sort.

Under everything in, select Descending order.

Click Execute.


Step 3: Obtain Top 100 ChIP Regions

Click on Text Manipulation and Select First.

Under Select first, enter 100 lines.

Under from, select our sorted ChIP data.

Click Execute.

.


Step 4: Extract DNA of Top 100 ChIP Regions

Click on Fetch Sequences.

Click on Extract Genomic DNA.

Under Fetch sequences for intervals in select our top 100 ChIP regions.

Set Interpret features when possible to No.

Set Source for Genomic Data to Locally cached.

Set Output data type to FASTA.

Click Execute.


Step 5: Download The Data

When finished, click on to download the file to our desktop.

This has already been done for you.

The resulting sequence is in the following file:

classes/mayo/sinha/BIN_top_100.fasta


Step 6: Submit to MEME

In this step, we will submit the sequences to MEME

Go to the following address:

http://meme.nbcr.net/meme/cgi-bin/meme.cgi

Enter your email address here.

Upload your sequences file here

Leave other parameters as default.

Click Start Search.

DO NOT RUN THIS NOW. MEME TAKES A VERY LONG TIME.





Step 7A: Analyzing MEME Results

Go to the following web address:

http://nbcr-222.ucsd.edu/opal-jobs/appMEME_4.9.01371501018575720728765/meme.html

The webpage contains a summary of MEME’s findings.

It is also available on the shared directory:

classes/mayo/sinha/MEME.htm

Let’s investigate the top hit.





Step 7B: Analyzing MEME Results

To the right is a LOGO of our predicted motif, showing the per position relative abundance of each nucleotide

At the bottom are the aligned regions in each of our sequences that helped produce this motif. As the p-value increases (becomes less significant) matches show greater divergence from our LOGO.


Step 7C: Analyzing MEME Results

Other predicted motifs do not seem as plausible.


Step 8A: Comparison with Experimentally Validated Motif for BINFlyFactorSurvey is a database of TF motifs in Drosophila Melanogaster.

Go to the following link to view the motif for BIN:

http://pgfe.umassmed.edu/ffs/TFdetails.php?FlybaseID=FBgn0045759






Step 8B: Comparison with Experimentally Validated Motif for BIN

Actual BIN Motif

There is strong agreement between the actual motif and the reverse complement of MEME’s best motif. This indicates MEME was actually able to find the motif from the top 100 ChIP regions for this TF.

Best MEME Motif

Best MEME MotifReverse Complemented


Gene Set Enrichment AnalysisIn this exercise, we will extract the nearby genes for each one of the ChIP peaks for BIN.

We will then subject the nearby genes to enrichment analysis tests on various Gene Ontology gene sets utilizing DAVID.


Step 9A: Acquire Nearby Genes

In this step, we will acquire all genes in Drosophila Melanogaster.

Select Get Data and UCSC Main.


Step 9B: Acquire Nearby GenesEnsure the following settings are configured.

Click get output and then send query to Galaxy.


Step 9C: Acquire Nearby Genes

Go back to Galaxy.

Select Operate on Genomic Intervals

Then Select Fetch Closest non-overlapping interval feature.


Step 9D: Acquire Nearby Genes

For For every interval feature in select our original ChIP track.

For Fetch closest features from select the UCSC genes track we just downloaded.

Click Execute


Step 10A: Cut Out Genes

The resulting file has the list of nearby genes in CG format in the 12th column.

We are only interested in the genes, so we need to cut them out using the CUT tool.

Under Text Manipulation click Cut


Step 10B: Cut Out Genes

For Cut Columns type c12 to denote column 12.

Under Delimited By select Tab

Under From select the track we just generated: the intersection of the ChIP-peaks and Fly Base genes.

Click Execute.


Step 11A: Convert IDs

The resulting file from the previous analysis is located in:

classes/mayo/sinha/cg_transcripts.txt

The enrichment tool we will use doesn’t accept genes in this format.

We will use the FlyBase ID converter to convert these transcript ids into FlyBase transcript ids.


Step 11B: Convert IDs

Go to http://flybase.org/static_pages/downloads/IDConv.html

Upload our cg_transcript.txt file and hit Go.

On the next page, click FlyBase Hit List and choose where to save the file.

http://flybase.org/static_pages/downloads/IDConv.html




Step 12A: Gene Set Enrichment - DAVID

The file from the previous analysis is available here:

classes/mayo/sinha/fb_transcripts.txt

With our correct ids of transcripts of genes near ChiP peaks, we now wish to perform a gene set enrichment analysis on various gene sets.

A tool that allows us to do this from a web interface is DAVID located at the following address:

http://david.abcc.ncifcrf.gov/tools.jsp

http://david.abcc.ncifcrf.gov/tools.jsp


Step 12A: Gene Set Enrichment - DAVID

We will perform a Gene Set Enrichment Analysis on our transcript list (gene list) and see what GO categories we are significantly enriched in.

Click Choose File on select our fb_transcripts.txt file.

Under Select Identifier select FLYBASE_TRANSCRIPT_ID.

Under Step 3: List Type check Gene List.

Click Submit List.


Step 12B: Gene Set Enrichment - DAVID

On the next page, select Functional Annotation Chart.

Our gene set seems to be enriched in the BP_FAT GO category!

This is consistent with the activity of the BIN transcription factor in the literature.

Documents

Regulatory Genomics Lab Saurabh Sinha Regulatory Genomics Lab v1 | Saurabh Sinha1 Powerpoint by Casey Hanson