DNA methylation and transcription: Difference between revisions
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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> |
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> |
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''' |
'''Purpose''': |
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* To explore the idea that DNA methylation affects TFBS, preventing some TF from binding to DNA, and therefore represses transcription.<br> |
* To explore the idea that DNA methylation affects TFBS, preventing some TF from binding to DNA, and therefore represses transcription.<br> |
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* To select TFs most likely sensitive to DNA methylation (first, in human, |
* To select TFs most likely sensitive to DNA methylation (first, in human, possibly in other species)<br> |
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'''We plan to do''': |
'''We plan to do''': |
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1. Functional analysis<br>- Predict TFBS ( |
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 |
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<br>2. Evolutionary analysis<br>- Predict TFBS ( |
<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>T SNP (in CG or in CNG) and of C>T interlineage substitution |
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'''We have data for functional analysis''': |
'''We have data for functional analysis''': |
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Primary cells: |
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<br>peripheral blood mononuclear cells PBMC (genome-wide BS-seq + CAGE)<br> |
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Andreas Lennartsson<br> |
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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> |
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Tissues:<br>frontal cortex (genome-wide MeDIP-seq) - frontal lobe (CAGE)<br> |
Tissues:<br>frontal cortex (genome-wide MeDIP-seq) - frontal lobe (CAGE)<br> |
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'''We |
'''We are looking for data''': |
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DNA methylation with single bp resolution (genome-wide or |
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 |
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<br> |
<br> |
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'''Collaboration''': |
'''Collaboration''': |
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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) |
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<br> |
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Sung-Joon Park (linear regression model for gene expression and methylation)<br> |
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- Absolute gene expression is explained by summing up the "effects" of TFBS activities and DNA methylation levels.<br> |
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- The first step to do is to identify functional "effects".<br> |
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- This will be done by a feature selection procedure based on model reduction or some statistical tests.<br> |
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- The feature selection will suggest which TFBS and/or methylation are indispensable to explain the gene expression. |
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'''== TF binding affects DNA methylation == ''' <br> |
'''== TF binding affects DNA methylation == ''' <br> |
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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> |
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<br> |
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Martin Frith<br> |
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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. |
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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.