1. Introduction to epigenetics: chromatin modifications, DNA methylation and the CpG Island landscape Héctor Corrada Bravo CMSC702 Spring 2013 (many slides courtesy of Rafael Irizarry)

2. Genetics: the alphabet of life Letters of DNA sequence carry the information How is this information read and parsed. We need grammar!

3. Differentiation Different genes are expressed during different stages and in different tissues

4. (3.4x10 -10 meters/bp) x (6x10 9 bp/genome) = ~2 meters/genome Radius of the nucleus is ~ 10 µM !!! Klug and Cummings, 1997

5. [(6 x 10 9 bp/genome) / (195 bp/nucleosome)] = ~ 30.8 x 10 6 nucleosomes/genome ~ 5 % of nuclear volume

6. http://www.albany.edu/~achm110/solenoidchriomatin.html Conformation is dynamic! (we’ll discuss methods to assay this conformation later on…)

7. We’ll study methods to assay a number of mechanisms of epigenetic regulation DNA methylation Nucleosome positioning and histone modifications In eukaryotes, DNA methylation usually occur at CpG dinucleotides

8. Transcriptional regulation by nucleosome and histone modification Nucleosome positioning is mainly repressive Histone modification can be either active or repressive TF TF target site TF Ace TF H3K27me3 H3K9ac TF

9. Histone code hypothesis “… multiple histone modifications, acting in a combinatorial or sequential fashion on one or multiple histone tails, specify unique downstream functions …” ― Strahl and Allis, Nature, (2000)

10. DNA Methylation is sometimes repressive Robertson and Wolffe, Nat Rev Genet, 2000 Unmethylated CpG dinucleotides Methylated CpG dinucleotides Transcription repressors bound to methyl-group

11. DNA methylation in cancer

12. DNA methylation, histone modifications and nucleosome positioning are coordinated! New technologies are allowing us to now assay this coordination [Brinkman, et al., Genome Research 2012]

13. Epigenetics: the grammar of life Epigenetics literally means above the genome

14. One more thing…. How does a cell retain epigenetic state?

15. Methylation TTCGATTACGATTCGATTACGA AAGCTAATGCTAAGCTAATGCT CH 3

16. TTCGATTACGATTCGATTACGA AAGCTAATGCTAAGCTAATGCT What happens during cell replication?

17. TTCGATTACGATTCGATTACGA AAGCTAATGCTAAGCTAATGCT TTCGATTACGATTCGATTACGA AAGCTAATGCTAAGCTAATGCT CH 3 What happens during cell replication?

18. TTCGATTACGATTCGATTACGA AAGCTAATGCTAAGCTAATGCT TTCGATTACGATTCGATTACGA AAGCTAATGCTAAGCTAATGCT CH 3 What happens during cell replication? DNA methylation is replicated!

19. TTCGATTACGATTCGATTACGA AAGCTAATGCTAAGCTAATGCT TTCGATTACGATTCGATTACGA AAGCTAATGCTAAGCTAATGCT Liver Brain

20. TTCGATTACGATTCGATTACGA AAGCTAATGCTAAGCTAATGCT CH 3 TTCGATTACGATTCGATTACGA AAGCTAATGCTAAGCTAATGCT Liver Brain

21. TTCGATTACGATTCGATTACGA AAGCTAATGCTAAGCTAATGCT CH 3 TTCGATTACGATTCGATTACGA AAGCTAATGCTAAGCTAATGCT Liver Brain TTCGATTACGATTCGATTACGA AAGCTAATGCTAAGCTAATGCT CH 3 AAGCTAATGCTAAGCTAATGCT TTCGATTACGATTCGATTACGA

22. CpG Islands We said DNA methylation occurs at CpG dinucleotides. Where are they in the genome?

23. CpGs are depleted

24. Remaining ones cluster

25. Proportion of CpG’s stratified by CG content. Two modes: high CpG rate low CpG rate

26. The clusters refered to as CpG Islands CpGs are depleted Remaining CpGs cluster into islands enriched near promoters New CGI definition: Irizarry et al. (2009) Mammalian Genome

27. CpG Island definition Gardiner-Garden and Frommer N > 200 GC-content > 50% obs/exp > 0.6 Lists contain 20,000 CGI Irizarry et al. (2009) Mammalian Genome Wu et al (2010) Biostatistics Lists contain 100,000 CGI Observed versus expected Observed dinucleotides Expected (%G x %C) Takai and Jones PNAS 2002 use a stricter definition HMM based definition GpC CpG

28. How do we measure DNA methylation?

29. TTCGATTACGATTCGATTACGA AAGCTAATGCTAAGCTAATGCT CH 3 TTCGATTACGATTCGATTACGA AAGCTAATGCTAAGCTAATGCT LiverBrain

30. TTCGATTACGATTCGATTACGA AAGCTAATGCTAAGCTAATGCT CH 3 TTCGATTACGATTCGATTACGA AAGCTAATGCTAAGCTAATGCT TTCGATTACGATTCGATTACGA AAGCTAATGCTAAGCTAATGCT TTCGATTACGATTCGATTACGA AAGCTAATGCTAAGCTAATGCT TTCGATTACGATTCGATTACGA AAGCTAATGCTAAGCTAATGCT TTCGATTACGATTCGATTACGA AAGCTAATGCTAAGCTAATGCT TTCGATTACGATTCGATTACGA AAGCTAATGCTAAGCTAATGCT 85% Methylation chr3:44,031,616-44,031,626

31. Bisulfite Treatment

32. GGGGAGCAGCATGGAGGAGCCTTCGGCTGACT GGGGAGCAGTATGGAGGAGTTTTCGGTTGATT

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

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

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

36. 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 – Smartest strategy: be unbiased and try all combinations of methylated/un-methylated CpGs in each read

37. BS-seq There are similarities to SNP calling EXCEPT: we want to measure percentages – Use a binomial model to estimate p, percentage of methylation – Allow for sequencing errors, coverage differences, etc.

38. Measuring DNA Methylation Estimating percentages Use “local-likelihood” method – Based on loess (Plot courtesy of Kasper Hansen)

39. Crosslink Y Lyse & Sonicate IP Reverse crosslinks Total Reverse crosslinks Amplify Sequence MeDIP (like ChIPchip) Other controls for IP (e.g., no antibody, non- specific antibody)

41. Next few lectures Measuring DNA methylation – How to find genomic regions that are differentially methylated in two groups (say, cancer and normal) Measuring nucleosome occupancy and histone modifications – First stabs at decoding the histone code Determining genomic 3d structure