1 / 74

Héctor Corrada Bravo CMSC858P Spring 2012 (many slides courtesy of Rafael Irizarry)

Introduction to epigenetics: chromatin modifications, DNA methylation and the CpG Island landscape (part 2). Héctor Corrada Bravo CMSC858P Spring 2012 (many slides courtesy of Rafael Irizarry). How do we measure DNA methylation?. Microarray Data. One question…. Where do we measure?

feryal
Télécharger la présentation

Héctor Corrada Bravo CMSC858P Spring 2012 (many slides courtesy of Rafael Irizarry)

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Introduction to epigenetics: chromatin modifications, DNA methylation and the CpG Island landscape (part 2) Héctor Corrada Bravo CMSC858P Spring 2012 (many slides courtesy of Rafael Irizarry)

  2. How do we measure DNA methylation?

  3. Microarray Data

  4. One question… • Where do we measure? • At least 7 arrays are needed to measure entire genome • CpG are depleated • Remaining CpGs cluster

  5. CpG Islands

  6. But variation seen outside

  7. McRBC Input Cuts at AmCG or GmCG No Methylation

  8. McRBC Methylation

  9. McRBC after GEL Methylation

  10. McRBC after GEL Methylation

  11. Now unmethylated No Methylation

  12. McRBC after Gel No Methylation

  13. Gene Expression Normalization does not work well here

  14. We use control probes

  15. There are also waves

  16. Smoothing

  17. McRBCon tiling two channel array We smooth

  18. Proportion of neighboring CpG also methylated/not methylated

  19. True signal (simulated)

  20. Observed data

  21. Observed data and true signal

  22. What is methylated (above 50%)?

  23. Naïve approach

  24. Many false positives (FP)

  25. Smooth

  26. No FP, but one false negative

  27. Smooth less? No FN, lots of FP

  28. We prefer this!

  29. CHARMDMR for three tissues (five replicates) Irizarry et al, Nature Genetics 2009

  30. Some findings [Irizarry et al., 2009, Nat. Genetics]

  31. Tissue easily distinguished

  32. Cancer DMR

  33. Many Regions like thisNote: hypo and hyper methylation

  34. Both hyper and hypo methylated

  35. Cancer and Tissue DMRs coincide

  36. DMR enriched in Shores

  37. Still affects expression T-DMRs

  38. Still affects expression C-DMRs

  39. Using sequencing (BS-seq)

  40. Liver Brain A A G C T A A T G C T T T C G A T T A C G A A A G C T A A T G C T T T C G A T T A C G A CH3 CH3 CH3 CH3

  41. CH3 CH3 T T C G A T T A C G A T T C G A T T A C G A T T C G A T T A C G A T T C G A T T A C G A T T C G A T T A C G A T T C G A T T A C G A A A G C T A A T G C T A A G C T A A T G C T A A G C T A A T G C T A A G C T A A T G C T A A G C T A A T G C T A A G C T A A T G C T A A G C T A A T G C T chr3:44,031,616-44,031,626 T T C G A T T A C G A CH3 CH3 CH3 CH3 CH3 CH3 CH3 CH3 CH3 CH3 CH3 CH3 85% Methylation

  42. Bisulfite Treatment

  43. Bisulfite Treatment GGGGAGCAGCATGGAGGAGCCTTCGGCTGACT GGGGAGCAGTATGGAGGAGTTTTCGGTTGATT

  44. BS-seq GTCGTAGTATTTGTCT GTCGTAGTATTTGTNN TGTCGTAGTATCTGTC TATGTCGTAGTATTTG TATATCGTAGTATTTT TATATCGTAGTATTTG NATATCGTAGTATNTG TTTTATATCGCAGTAT ATATTTTATGTCGTA ATATTTTATCTCGTA ATATTTTATGTCGTA GA-TATTTTATGTCGT Coverage: 13 Methylation Evidence: 13 Methylation Percentage: 100% GATCACAGGTCTATCACCCTATTAACCACTCACGGGAGCTCTCCATGCATTTGGTATTTTCGTCTGGGGGGTATGCACGCGATAGCATTGCGAGACGCTGGAGCCGGAGCACCCTATGTCGCAGTATCTGTCTTTGATTCCTGCCTCATCCTATTATTTATCGCACCTACGTTCAATATT

  45. BS-seq GTCGTAGTATTTGTCT GTCGTAGTATTTGTNN TGTCGTAGTATCTGTC TATGTCGTAGTATTTG TATATTGTAGTATTTT TATATCGTAGTATTTG NATATTGTAGTATNTG TTTTATATTGCAGTAT ATATTTTATGTCGTA ATATTTTATCTTGTA ATATTTTATGTCGTA GA-TATTTTATGTCGT Coverage: 13 Methylation Evidence: 9 Methylation Percentage: 69% GATCACAGGTCTATCACCCTATTAACCACTCACGGGAGCTCTCCATGCATTTGGTATTTTCGTCTGGGGGGTATGCACGCGATAGCATTGCGAGACGCTGGAGCCGGAGCACCCTATGTCGCAGTATCTGTCTTTGATTCCTGCCTCATCCTATTATTTATCGCACCTACGTTCAATATT

  46. BS-seq GTCGTAGTATTTGTCT GTCGTAGTATTTGTNN TGTTGTAGTATCTGTC TATGTTGTAGTATTTG TATATTGTAGTATTTT TATATTGTAGTATTTG NATATTGTAGTATNTG TTTTATATTGCAGTAT ATATTTTATGTCGTA ATATTTTATCTTGTA ATATTTTATGTTGTA GA-TATTTTATGTCGT Coverage: 13 Methylation Evidence: 4 Methylation Percentage: 31% GATCACAGGTCTATCACCCTATTAACCACTCACGGGAGCTCTCCATGCATTTGGTATTTTCGTCTGGGGGGTATGCACGCGATAGCATTGCGAGACGCTGGAGCCGGAGCACCCTATGTCGCAGTATCTGTCTTTGATTCCTGCCTCATCCTATTATTTATCGCACCTACGTTCAATATT

  47. BS-seq • Alignment is much trickier: • Naïve strategy: do nothing, hope not many CpG in a single read • Smarter strategy: “bisulfite convert” reference: turn all Cs to Ts • Also needs to be done on reverse complement reference and reads • Smartest strategy: be unbiased and try all combinations of methylated/un-methylated CpGs in each read • Computationally expensive (see Hansen et al, 2011, for a strategy)

More Related