1. Regulatory Genomics Lab
Bacterial Genome Assembly | Victor Jongeneel
Regulatory Genomics Lab
Saurabh Sinha
PowerPoint by Pei-Chen Peng
Regulatory Genomics | Saurabh Sinha | 2017

2. Bacterial Genome Assembly | Victor Jongeneel
Exercise
In this exercise, we will do the following:.
Use Galaxy to manipulate a ChIP track for BIN in D. Mel.
Subject peak sets to MEME suite.
Compare MEME motifs with Fly Factor Survey motifs for BIN.
Subject peak set to a gene set enrichment test.
Regulatory Genomics | Saurabh Sinha | 2017

3. Regulatory Genomics | Saurabh Sinha | 2017
Step 0A: Local Files
For viewing and manipulating the files needed for this laboratory exercise, insert your flash drive. Denote the path to the flash drive as the following: [course_directory] We will use the files found in: [course_directory]/07_Regulatory_Genomics/data/
Regulatory Genomics | Saurabh Sinha | 2017

4. Step 0B: Logging into Galaxy
Go to: galaxy.knowhub.org Click Enter Click Login Input your login credentials. Click Login.
Regulatory Genomics | Saurabh Sinha | 2017

5. Computational Prediction of Motifs
In 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.
Regulatory Genomics | Saurabh Sinha | 2017

6. Step 1: Upload BIN ChIP Track to Galaxy
Click Get Data and then Upload File
Click Choose local file and then upload our ChIP file:
[course_directory]/07_Regulatory_Genomics/data/BIN_Fchip_s11_1000.gf f
Set the Type to gff.
Set Genome to dm3.
Click Start
Regulatory Genomics | Saurabh Sinha | 2017

7. 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 column: 6. Under with flavor, select Numerical sort. Under everything in, select Descending order. Click Execute.
Regulatory Genomics | Saurabh Sinha | 2017

8. Step 3: Obtain Top 100 ChIP Regions
Bacterial Genome Assembly | Victor Jongeneel
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. .
Regulatory Genomics | Saurabh Sinha | 2017

9. Step 4: Extract DNA of Top 100 ChIP Regions
Bacterial Genome Assembly | Victor Jongeneel
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.
Regulatory Genomics | Saurabh Sinha | 2017

10. 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:
[course_directory]/07_Regulatory_Genomics/data/BIN_top_100.fasta
Regulatory Genomics | Saurabh Sinha | 2017

11. Regulatory Genomics | Saurabh Sinha | 2017
Step 6: Submit to MEME
DO NOT RUN THIS NOW. MEME TAKES A VERY LONG TIME.
In this step, we will submit the sequences to MEME Go to the following address: Upload your sequences file here Enter your address here. Leave other parameters as default. Click Start Search.
Regulatory Genomics | Saurabh Sinha | 2017

12. Step 7A: Analyzing MEME Results
Go to the following web address:
The webpage contains a summary of MEME’s findings.
It is also available on the results directory:
[course_directory]/07_Regulatory_Genomics/results/MEME.htm
Let’s investigate the top hit.
Regulatory Genomics | Saurabh Sinha | 2017

13. 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.
Regulatory Genomics | Saurabh Sinha | 2017

14. Step 7C: Analyzing MEME Results
Other predicted motifs do not seem as plausible.
Regulatory Genomics | Saurabh Sinha | 2017

15. Step 8A: Comparison with Experimentally Validated Motif for BIN
FlyFactorSurvey is a database of TF motifs in Drosophila Melanogaster.
Go to the following link to view the motif for BIN:
Regulatory Genomics | Saurabh Sinha | 2017

16. Step 8B: Comparison with Experimentally Validated Motif for BIN
Best MEME Motif
Reverse
Complemented
Actual BIN Motif
Best MEME 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.
Regulatory Genomics | Saurabh Sinha | 2017

17. Gene Set Enrichment Analysis
In 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.
Regulatory Genomics | Saurabh Sinha | 2017

18. Step 9A: Acquire Nearby Genes
In this step, we will acquire all genes in Drosophila Melanogaster using UCSC Main Table Browser: .
Regulatory Genomics | Saurabh Sinha | 2017

19. Step 9B: Acquire Nearby Genes
Ensure the following settings are configured. Click get output and then get BED.
Regulatory Genomics | Saurabh Sinha | 2017

20. Step 9C: Acquire Nearby Genes
Go back to Galaxy Server
Click Get Data and then Upload File
Click Choose local file and then upload our gene file:
[course_directory]/07_Regulatory_Genomics/results/
flygenes.bed
Set the Type to gff.
Set Genome to dm3.
Click Start
Regulatory Genomics | Saurabh Sinha | 2017

21. Step 9D: Acquire Nearby Genes
Select Operate on Genomic Intervals Then Select Fetch Closest non-overlapping interval feature.
Regulatory Genomics | Saurabh Sinha | 2017

22. Step 9E: 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
Regulatory Genomics | Saurabh Sinha | 2017

23. Regulatory Genomics | Saurabh Sinha | 2017
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
Regulatory Genomics | Saurabh Sinha | 2017

24. Regulatory Genomics | Saurabh Sinha | 2017
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.
Regulatory Genomics | Saurabh Sinha | 2017

25. Step 10C: 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:
[course_directory]/07_Regulatory_Genomics/results/cg_transcripts .txt
Regulatory Genomics | Saurabh Sinha | 2017

26. Regulatory Genomics | Saurabh Sinha | 2017
Step 11A: Convert IDs
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.
Regulatory Genomics | Saurabh Sinha | 2017

27. Regulatory Genomics | Saurabh Sinha | 2017
Step 11B: Convert IDs
Go to
Upload our cg_transcript.txt file and hit Go.
On the next page, click file, uniq IDs only to download the file of converted IDs.
Regulatory Genomics | Saurabh Sinha | 2017

28. Step 12A: Gene Set Enrichment - DAVID
Move the resulting file from the previous analysis to the course directory and rename it: (This has already been done for you.) [course_directory]/07_Regulatory_Genomics/results/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:
Regulatory Genomics | Saurabh Sinha | 2017

29. 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. Analyze the gene list with Functional Annotation Tool 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.
Regulatory Genomics | Saurabh Sinha | 2017

30. 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.
Regulatory Genomics | Saurabh Sinha | 2017