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


Inroduction: 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. <br>
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. <br>


'''Purpose''':
Our purposes:


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


'''We plan to do''':
We plan to do:<br>1. Functional analysis<br>- Predict TFBS (TFBS clusters?) in promoters<br>- Estimate methylation level of each TFBS (may be, only core positions of TFBS)<br>- Calculate correlation between level of methylation and expression from given promoter for each TFBS<br>- Select lists of TFs with highest and lowest cc<br>2. Evolutionary analysis<br>- Predict TFBS (TFBS clusters?) 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


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?) 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:<br>Primary cells: <br>peripheral blood mononuclear cells (genome-wide BS-seq + CAGE)<br>Tissues:<br>frontal cortex (genome-wide MeDIP-seq) - frontal lobe (CAGE)<br>


Primary cells:
We seek for data:<br>DNA methyaltion with single bp resolution (genome-wide or with coverage of not less when 1% of genome) in primary cells, tissues or cell lines represented in FANTOM5
<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>


'''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)



'''TF binding affects DNA methylation''' <br>
<br>
'''Collaboration''':
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>


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.