Dinh/Dinh 2012/NOTES/2012-7-18

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PGC WGBS project : Meeting July 19th 2012[edit]

The story about Tet1:

  • 1) Tet1 when downregulated leads to increased mC in Tet1 binding sites.
  • 2) This leads to downregulation of gene expression, which can lead to greater change in methylation, and misregulation of other genes.
  • 3) Tet1 have specific phenotypical effects is specific only in PGC and not somatic cells.


Methylation data: Perform re-mapping as paired-ends to get information about repetitive regions. Combine data from previous batch and this batch. Calculate the conversion rate.

Global picture: - pick at least 2 of each ( pool different libraries to make 2 of each ) - make histogram (just CpGs) .. pick just 2 best - make cluster

Expression data: Phenotype is timepoint specific...use the multiple timepoint data in gene expression. Generate the gtf file for repetitive regions and then intersect bam files with this & get expression level of repetitive regions.

For manuscript: We need to establish the first level: Tet1 to increased mC to downregulation of genes We need to get methylation histogram for Tet1 binding sites.

  • Stronger causality argument:

For the genes that shows downregulation, look for motif enrichment for related pathways & shows change in DNA methylation in promoter. - motif = transcription factor

  • Look for the expression of any transcription factor that we can find
  • Or, just take all known cell cycle genes and check whether there are DMRs.

PGC project: Meeting on July 9th[edit]

We need to downsample all the reads so that the differences in coverage will not affect the sample clustering.

  • 1. First panel - Histogram and clustering (dendrogram) and genome browser shot to show that no change globally. We are seeing highly localized changes in DNA methylation and gene expression.
  Second panel - combine DNA methylation with Tet1 binding (in ESC) information
  • 2. For those that show change in RNA-seq but not in methylation, can we check that the coverage was just not good?
  • 3. Gene ontology of DMRs and down-regulated genes (connect the Omic data with phenotype data).
  Maybe some example figures for this.
  • 4. Check out BED for chromosome3 (Sycp1)