User:David K. Barclay/Notebook/Controlling Pancreas Cell Fate Using Transcription Factors/2014/09/15

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Bioinformatics to Identify Functions of Methylated Genes

  • In order to use Galaxy to identify genes that would be marked in Alpha but not in Beta, the goal of this experiment is to identify genes that are marked in Alpha and Beta and subtract the Beta marks from the Alpha marks to leave only genes that are methylated in Alpha cells but not Beta cells. This list would then be cross-referenced against promoter sequences in order to further isolate genes that only have marks around their TSS.

Protocol

  1. Left Column > Operate on Genomic Intervals > Intersect
  2. Return Overlapping of Beta 151_3 (B1) that intersect Beta 151_6 (B2) for at least 1 bp.
  3. Repeat process for Beta 152_6 (B3) that intersect the list from step 2.
  4. Repeat step 2 and 3 for Alpha 151_5 (A1) intersect Alpha 152_4 (A2) and intersect Alpha 151_2 (A3) against the list for the first two ChIP data.
  5. This should grab all genes that are marked by H3K27me3 in all 3 ChIP sequences.
  6. Left Column > Operate on Genomic Intervals > Subtract
  7. Subtract All Beta from All Alpha return Intervals with no overlap where minimal overlap is 1 bp. This process takes all Alpha gene marks and subtracts all overlap with Beta gene marks. This should return all gene sequences that are marked on Alpha, but not in Beta.
  8. Check by grabbing 5 genes from the created list. Intersect these 5 genes versus all 6 ChIP data (Alpha and Beta). This should show that there are methylation values for all Alpha but not consistent values for all Beta.
  9. Intersect the human promoters data against the Subtraction data created. This will create a list that gives gene names for genes that have Alpha methylation around their promoters but not methylation in their Beta state.
  10. Download the data set created in the previous step. Copy all genes names and run GOrilla against a Human background genome. Protocol here: GOEnrichment Protocol. For Step 2: Homo Sapiens. Step 4: Copy paste genes from data set created in previous step. Step 5: Copy paste from Human gene set. Run Process.


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