DNA methylation and transcription: Difference between revisions

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1. Functional analysis<br>- Predict TFBS (homotypic clusters, composite elements?, conserved sites?) in promoters<br>- Estimate methylation level of each TFBS (may be, only core positions)<br>- Calculate correlation between level of methylation and expression from given promoter for each TFBS<br>- Select promoters and corresponding TFs with highest and lowest cc
1. Functional analysis<br>- Predict TFBS (homotypic clusters, composite elements?, conserved sites?) in promoters<br>- Estimate methylation level of each TFBS (may be, only core positions)<br>- Calculate correlation between level of methylation and expression from given promoter for each TFBS<br>- Select promoters and corresponding TFs with highest and lowest cc


<br>2. Evolutionary analysis<br>- Predict TFBS (homotypic clusters, composite elements, conserved sites?) in promoters<br>- For whole set of given TF's binding sites estimate probability of C&gt;T SNP (in CG or in CNG) and of C&gt;T interlineage substitution
<br>2. Evolutionary analysis<br>- Predict TFBS (homotypic clusters, composite elements?) in promoters<br>- For whole set of given TF's binding sites estimate probability of C&gt;T SNP (in CG or in CNG) and of C&gt;T interlineage substitution


'''We have data for functional analysis''':
'''We have data for functional analysis''':


Primary cells:
Primary cells: <br>peripheral blood mononuclear cells PBMC (genome-wide BS-seq + CAGE)<br>
<br>peripheral blood mononuclear cells PBMC (genome-wide BS-seq + CAGE)<br>

Andreas Lennartsson<br>
I can provide single bp resolution CpG methylation data from Illuminas Infinum 27k and 45k bead array, for the hematopoietic cell populations (common myeloid progenitor, granulocyte-monocyte progenitor, myelocyte-promyelocyte and band cells/neutrophils)+CAGE. In addition, I have CpG methylation data from almost 150 acute myeloid leukemia (AML) patient samples from the same platforms + Illumina expression array data for 15 of the AML patients. <br>
Tissues:<br>frontal cortex (genome-wide MeDIP-seq) - frontal lobe (CAGE)<br>
Tissues:<br>frontal cortex (genome-wide MeDIP-seq) - frontal lobe (CAGE)<br>


'''We are looking for data''':
'''We are looking for data''':
DNA methylation with single bp resolution (genome-wide or covering not less then 1% of genome) in primary cells, tissues or cell lines represented in FANTOM5
DNA methylation with single bp resolution (genome-wide or covering not less then 1% of genome) in primary cells, tissues or cell lines represented in FANTOM5




<br>
<br>
'''Collaboration''':
'''Collaboration''':
Piotr (you are invited to add your plans of study on influence of TF on methylation)
Piotr (you are invited to add your plans of study on influence of TF on methylation)

<br>
Sung-Joon Park (linear regression model for gene expression and methylation)<br>
- Absolute gene expression is explained by summing up the "effects" of TFBS activities and DNA methylation levels.<br>
- The first step to do is to identify functional "effects".<br>
- This will be done by a feature selection procedure based on model reduction or some statistical tests.<br>
- The feature selection will suggest which TFBS and/or methylation are indispensable to explain the gene expression.



'''== TF binding affects DNA methylation == ''' <br>
'''== TF binding affects DNA methylation == ''' <br>


Collaborators are very welcome. If you have any ideas how to improve the research, please contact me directly or add your suggestion here. <br>
Collaborators are very welcome. If you have any ideas how to improve the research, please contact me directly or add your suggestion here. <br>

<br>
Martin Frith<br>
By coincidence, I am working (outside Fantom) on methods to align bisulfite-converted DNA accurately and efficiently. This is very much a technical detail, but if you're interested, I'd be glad to share what I have.

Latest revision as of 19:21, 12 October 2011

== DNA methylation affects TF binding and transcription ==

Introduction: It's commonly accepted that DNA methylation of a promoter repress transcription of this gene in normal tissues. Recently, a class of actively expressed genes having relatively methylated promoters has been discovered.

Purpose:

  • To explore the idea that DNA methylation affects TFBS, preventing some TF from binding to DNA, and therefore represses transcription.
  • To select TFs most likely sensitive to DNA methylation (first, in human, possibly in other species)

We plan to do:

1. Functional analysis
- Predict TFBS (homotypic clusters, composite elements?, conserved sites?) in promoters
- Estimate methylation level of each TFBS (may be, only core positions)
- Calculate correlation between level of methylation and expression from given promoter for each TFBS
- Select promoters and corresponding TFs with highest and lowest cc


2. Evolutionary analysis
- Predict TFBS (homotypic clusters, composite elements?) in promoters
- For whole set of given TF's binding sites estimate probability of C>T SNP (in CG or in CNG) and of C>T interlineage substitution

We have data for functional analysis:

Primary cells:
peripheral blood mononuclear cells PBMC (genome-wide BS-seq + CAGE)

Andreas Lennartsson
I can provide single bp resolution CpG methylation data from Illuminas Infinum 27k and 45k bead array, for the hematopoietic cell populations (common myeloid progenitor, granulocyte-monocyte progenitor, myelocyte-promyelocyte and band cells/neutrophils)+CAGE. In addition, I have CpG methylation data from almost 150 acute myeloid leukemia (AML) patient samples from the same platforms + Illumina expression array data for 15 of the AML patients.

Tissues:
frontal cortex (genome-wide MeDIP-seq) - frontal lobe (CAGE)

We are looking for data: DNA methylation with single bp resolution (genome-wide or covering not less then 1% of genome) in primary cells, tissues or cell lines represented in FANTOM5



Collaboration: Piotr (you are invited to add your plans of study on influence of TF on methylation)


Sung-Joon Park (linear regression model for gene expression and methylation)
- Absolute gene expression is explained by summing up the "effects" of TFBS activities and DNA methylation levels.
- The first step to do is to identify functional "effects".
- This will be done by a feature selection procedure based on model reduction or some statistical tests.
- The feature selection will suggest which TFBS and/or methylation are indispensable to explain the gene expression.


== TF binding affects DNA methylation ==

Collaborators are very welcome. If you have any ideas how to improve the research, please contact me directly or add your suggestion here.


Martin Frith
By coincidence, I am working (outside Fantom) on methods to align bisulfite-converted DNA accurately and efficiently. This is very much a technical detail, but if you're interested, I'd be glad to share what I have.