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DNA Methylation Assays High Throughput Data Analysis BIOS 691-803, VCU Winter 2010 Mark Reimers, PhD.

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Presentation on theme: "DNA Methylation Assays High Throughput Data Analysis BIOS 691-803, VCU Winter 2010 Mark Reimers, PhD."— Presentation transcript:

1 DNA Methylation Assays High Throughput Data Analysis BIOS 691-803, VCU Winter 2010 Mark Reimers, PhD

2 DNA Methylation Cytosine bases sometimes methylated Shuts down transposons In vertebrates: –Condenses chromatin –Renders genes inaccessible –Heritable in cell lineages –Developmental fate decisions

3 DNA Methylation Adding a Methyl to Cytosine Cytosine methylation is passed on to daughter cells

4 How Does Methylation Happen?

5 Distribution of Methylation

6 Distribution of CpG sites

7 DNA Methylation and Transcription Methyl groups block access to some transcription factors Me-C attracts MBD proteins that further suppress transcription Heavy methylation predisposes chromatin to condense

8 Methylation in Development

9 Methylation in Cancer

10 Assaying Methylation MeDIP (Methylated DNA immuno-precipitation) –Antibody to Me-C => ChIP – chip –Doesn’t distinguish among nearby sites Multiple restriction enzyme assays Isoschizomer (HpaII/MspI) assays: –MIAMI (Microarray-based Integrated Analysis of Methylation by Isoschizomers) –HELP Bisulphite conversion of meC -> T, then hybridize to SNP style array

11 MeDIP Genomic DNA is randomly sheared by sonication Immunoprecipitate with an antibody that specifically recognizes 5- methylcytidine (5mC) Hybridize against control (no antibody) on array

12 MeDIP Data EIF2C4

13 Copyright restrictions may apply. Ordway, J.M. et al. Carcinogenesis 2006 27:2409-2423; doi:10.1093/carcin/bgl161 McrBC A schematic of three array probes (X, Y and Z) arranged along a chromosome is shown Short fragments with methylated CpG’s have been removed

14 The HELP Assay MSPI cuts at 5’-CCGG-3’ –methylated or not HPAII cuts at 5’-CCGG-3’ only if unmethylated (useful restriction enzyme) Sample MSPI HPAII LabelPCR amplify Label PCR amplify Co-hybridize

15 HELP Data

16 HELP log ratios

17 Methylation Data Analysis Regional QA Normalizing Bias in ratios –Probe sequence –CpG density –Intensity –Fragment length (for HELP & similar) Estimation –Are methylations similar at neighbors?

18 Normalizing MeDIP – CpG Bias Direct approach Compare to a standard: –fully methylated –Tanay: M.SssI treatment Indirect estimate –Regress M (ratio) on CpG density (assuming all neighbors are equal) –Down et al: BATMAN

19 Normalizing Intensity Bias Strong intensity dependent bias in each chip Different intensity dependence in each chip Correlated with CpG density Ignored by BATMAN!

20 Normalizing Sequence Bias Significant dependence of intensity on CG Dependence differs among chips!

21 HELP ratios and fragment length

22 Normalizing Fragment Length - HELP Distribution of intensity varies by L Fit density curve and line up

23 More HELP technical biases

24 CHARM

25 Critique of CHARM Improves reliability of mcrBC by assuming smoothness Doesn’t incorporate probe effects No pre-processing of Illumina data used as reference Detailed data shows ‘block’ structure –With single CpG sites deviating from most –Difficult to detect using CHARM

26 Block Structure of Methylation

27 General Principles of Complex Assay Normalization Many reactions: each influenced by differences in processing conditions Differences in technique induce similar biases in probes with similar technical characteristics Aggregating probes by technical character (IF independent of biology) is an effective way to estimate bias on each chip individually


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