Regulatory Genomics Lab Saurabh Sinha Regulatory Genomics | 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. Regulatory Genomics | Saurabh Sinha | 20152

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]/10_Regulatory_Genomics/data/ Protein Sequence, Structure, and Function | Gustavo Caetano - Anolles |

Step 0B: Logging into Galaxy Go to: biocluster.igb.illinois.edu Click Enter Click Login Input your login credentials. Click Login. Regulatory Genomics | Saurabh Sinha | 20154

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 | 20155

Step 1: Upload BIN ChIP Track to Galaxy Click Get Data and then Upload File Upload our ChIP file: [course_directory]/10_Regulatory_Genomics/da ta/BIN_Fchip_s11_1000.gff Set the File Format to gff. Set Genome to dm3. Click Execute Regulatory Genomics | Saurabh Sinha | 20156

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. Regulatory Genomics | Saurabh Sinha | 20157

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 | 20158

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 | 20159

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]/10_Regulatory_Genomics/data/BIN_top_100.fasta Regulatory Genomics | Saurabh Sinha |

Step 6: Submit to MEME 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 | DO NOT RUN THIS NOW. MEME TAKES A VERY LONG TIME.

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 |

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 |

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

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: 59 Regulatory Genomics | Saurabh Sinha |

Step 8B: Comparison with Experimentally Validated Motif for BIN Actual BIN Motif Regulatory Genomics | Saurabh Sinha | 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 Reverse Complemented

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 |

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 |

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

Step 9C: Acquire Nearby Genes Click Get Data and then Upload File Upload our gene file: flygenes.bed Set the File Format to bed. Set Genome to dm3. Click Execute Regulatory Genomics | Saurabh Sinha |

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

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 |

Step 10A: Cut Out Genes The resulting file has the list of nearby genes in CG format in the 12 th 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 |

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 |

Step 11A: Convert IDs Save the resulting file. Move it to the course directory and rename it: [course_directory]/10_Regulatory_Genomics/data/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. Regulatory Genomics | Saurabh Sinha |

Step 11B: Convert IDs Regulatory Genomics | Saurabh Sinha | 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.

Step 12A: Gene Set Enrichment - DAVID Move the resulting file from the previous analysis to to the course directory and rename it: [course_directory]/10_Regulatory_Genomics/data/fb_transcr ipts.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 |

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 |

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 |