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Slides availablewww.bioinformatics.be                        12 Maart 2013
Lab for Bioinformatics and         computational genomics     10 “genome hackers”   mostly engineers (statistics)         ...
Can bioinformatics bridge the gap ?
The genome is just the start …
250 different cell types                 Epigenetic (meta)information = stem cells
Cellular programming               Epigenetic (meta)information = stem cells
Defining Epigenetics               Genome                              DNA       Reversible changes in gene              ...
DNA Methylation Differentiates Totipotent EmbryonicStem Cells from Unipotent Adult Stem Cells                             ...
Reprogramming the DNA methylome                                  Paula Vertino, Henry Stewart Talks
Transgenerational inheritence
The epigenomeis actionable
The epigenomeis actionable
Epigenetic Changes areImportant in Causing Cancer             GENETIC                     EPIGENETIC      Example:        ...
Example of Methylationvs Mutation: Colon & Breast Cancer                                                      Dx          ...
MGMT BiologyO6 Methyl-GuanineMethyl TransferaseEssential DNA Repair EnzymeRemoves alkyl groups from damaged guaninebasesHe...
MGMT PromoterMethylation PredictsBenefit form DNA-Alkylating Chemotherapy  Post-hoc subgroup analysis of Temozolomide Clin...
Profiling the Epigenome  # markers              Discovery                          Verification                           ...
Genome-wide methylationby methylation sensitive restriction enzymes
Genome-wide methylationby probes
Profiling the EpigenomeBy next gen sequencing  # markers              Discovery                          Verification     ...
MBD_SeqCondensed Chromatin      DNA Sheared                                       Immobilized                             ...
MBD_Seq                  Immobilized                  Methyl binding domain          MgCl2                  Next Gen Seque...
Kit Comparison       0.25                                    ●                                ●                     0.20  ...
MBD_SeqMGMT = dual core
Profiling the epigenome…. by next generation sequencing  # markers 1-2 million                       MBD_Seq methylation  ...
Bock et al, Nature, 2012Bock et al. Nature 201228
29
Data integrationCorrelation tracksexpression                            expression             Corr =-1                   ...
Correlation trackin GBM @ MGMT                    +1                    -1                         31
Next_nextmiRNA, (l)ncRNA, CIS/TRANS splicing, SV, fusion loci ,bidirectional promoters ?RNA_seq: sequence RNA molecules Ne...
Direction RNAseqbidirectional promoters                          33
Profiling the Epigenome…. by next generation sequencing  # markers                      MBD_Seq              Discovery    ...
Where is the mC ?GCATCGTGACTAGCGACTGATCGATGGATGCTAGCAT
GCATCGTGACTAGCGACTGATCGATGGATGCTAGCAT
GCATCGTGACTAGCGACTGATCGATGGATGCTAGCAT    25%     50%     25%GCATCGTGACTAGCGACTGATCGATGGATGCTAGCAT
GCATCGTGACTAGCGACTGATCGATGGATGCTAGCAT    25%               50%            25%GCATCGTGACTAGCGACTGATCGATGGATGCTAGCATGCATCGTG...
Deep Sequencing                  unmethylated alleles                  methylated alleles     less methylation            ...
Deep MGMTHeterogenic complexity
ConclusionCombination of different sequencingtechniques is emerging as best practiceBioinformatics is challengingMethods ...
Slides availablewww.bioinformatics.be              4th December 2012              Johns Hopkins              Bloomberg    ...
biobix    wvcriekibiobix.bebioinformatics.be                43
2013 03 12_epigenetic_profiling
2013 03 12_epigenetic_profiling
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2013 03 12_epigenetic_profiling

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Epigenetic Profiling

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  • Here, we define epigenetics and depict the relationship between the genome and the epigenome The genome is hereditary information encoded in the DNA and the epigenome is the way cells express the encoded information 1 The epigenome is a ‘bridge’ between genotype and phenotype (epigenetics governs genotype and phenotype) Epigenetic information is included in the genome of a cell but is not encoded by the DNA 1,2 Epigenetic information may be inherited from precursor cells 1 Epigenetic changes affect chromosome structure to alter gene expression 1,2 References Goldberg AD et al. Cell 2007;128:635–8. Bernstein BE et al. Cell 2007;128:669–81.
  • There is growing evidence that epigenetic modifications are also crucial to the onset and progression of cancer 1 On the right of the slide, we see that changes in gene expression due to chromatin modifications (e.g. histone acetylation, DNA methylation) lead to altered levels of mRNA and proteins Altered levels of proteins involved in cell growth and death can lead to deregulated cell proliferation and survival, resulting in cancer 2 Examples: Silencing of p15 tumor suppressor gene expression 3 Aberrant expression of IGF2 4 Silencing of ER- α gene expression 3 References Bolden JE et al. Nat Rev Drug Discov 2006;5:769–84. Miranda E et al. Br J Cancer 2006;95:1101–7. Esteller M. N Engl J Med 2008;358:1148 – 59. Feinberg AP. Nature 2007;447:433–40.
  • Transcript of "2013 03 12_epigenetic_profiling"

    1. 1. Slides availablewww.bioinformatics.be 12 Maart 2013
    2. 2. Lab for Bioinformatics and computational genomics 10 “genome hackers” mostly engineers (statistics) 42 scientists technicians, geneticists, clinicians >100 people hardware engineers,mathematicians, molecular biologists
    3. 3. Can bioinformatics bridge the gap ?
    4. 4. The genome is just the start …
    5. 5. 250 different cell types Epigenetic (meta)information = stem cells
    6. 6. Cellular programming Epigenetic (meta)information = stem cells
    7. 7. Defining Epigenetics Genome DNA  Reversible changes in gene expression/function  Without changes in DNA Chromatin sequence Epigenome  Can be inherited from precursor cells Gene Expression  Allows to integrate intrinsic with environmental signals Phenotype (including diet)
    8. 8. DNA Methylation Differentiates Totipotent EmbryonicStem Cells from Unipotent Adult Stem Cells Alex Meissner, Henry Stewart Talks
    9. 9. Reprogramming the DNA methylome Paula Vertino, Henry Stewart Talks
    10. 10. Transgenerational inheritence
    11. 11. The epigenomeis actionable
    12. 12. The epigenomeis actionable
    13. 13. Epigenetic Changes areImportant in Causing Cancer GENETIC EPIGENETIC Example: Example: Replication errors Chromatin modification errors X X Altered Altered DNA sequence chromatin structure Oncogenesis Altered Altered levels of DNA/mRNA/proteins mRNA/proteins Tumor
    14. 14. Example of Methylationvs Mutation: Colon & Breast Cancer Dx CDx Methylated Mutated Source: Schuebel et al 2007 76-100 51-75 21-50 1-20
    15. 15. MGMT BiologyO6 Methyl-GuanineMethyl TransferaseEssential DNA Repair EnzymeRemoves alkyl groups from damaged guaninebasesHealthy individual: - MGMT is an essential DNA repair enzyme Loss of MGMT activity makes individuals susceptible to DNA damage and prone to tumor developmentGlioblastoma patient on alkylator chemotherapy: - Patients with MGMT promoter methylation show have longer PFS and OS with the use of alkylating agents as chemotherapy
    16. 16. MGMT PromoterMethylation PredictsBenefit form DNA-Alkylating Chemotherapy Post-hoc subgroup analysis of Temozolomide Clinical trial with primary glioblastoma patients show benefit for patients with MGMT promoter methylation Median Overall Survival 21.7 months plus temozolomide 12.7 months radiotherapy radiotherapy Adapted from Hegi et al. NEJM 2005 352(10):1036-8. Non-Methylated Methylated Study with 207 patients MGMT Gene MGMT Gene
    17. 17. Profiling the Epigenome # markers Discovery Verification Validation # samples
    18. 18. Genome-wide methylationby methylation sensitive restriction enzymes
    19. 19. Genome-wide methylationby probes
    20. 20. Profiling the EpigenomeBy next gen sequencing # markers Discovery Verification Validation # samples
    21. 21. MBD_SeqCondensed Chromatin DNA Sheared Immobilized Methyl Binding Domain DNA Sheared
    22. 22. MBD_Seq Immobilized Methyl binding domain MgCl2 Next Gen Sequencing GA Illumina: 100 million reads
    23. 23. Kit Comparison 0.25 ● ● 0.20 ● Fraction of reads 0.15 ● 0.10 ● 0.05 ● ● ● ● ● ● 0.00 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0 10 20 30 40 50 Number of CGs 25
    24. 24. MBD_SeqMGMT = dual core
    25. 25. Profiling the epigenome…. by next generation sequencing # markers 1-2 million MBD_Seq methylation cores Discovery # samples
    26. 26. Bock et al, Nature, 2012Bock et al. Nature 201228
    27. 27. 29
    28. 28. Data integrationCorrelation tracksexpression expression Corr =-1 Corr = 1 methylation methylation 30
    29. 29. Correlation trackin GBM @ MGMT +1 -1 31
    30. 30. Next_nextmiRNA, (l)ncRNA, CIS/TRANS splicing, SV, fusion loci ,bidirectional promoters ?RNA_seq: sequence RNA molecules Next Gen PlatformTotal RNA_seq: all RNA molecules (normalisation procedure)Directional Total RNA_seq: before amplification use different5’ and 3’ adaptorsIntegrated Directional Total RNA_seq: Combine with otherdatasets eg. enrichment sequencing data, visualise and queryin genome browser 32
    31. 31. Direction RNAseqbidirectional promoters 33
    32. 32. Profiling the Epigenome…. by next generation sequencing # markers MBD_Seq Discovery 454_BT_Seq Verification Validation # samples
    33. 33. Where is the mC ?GCATCGTGACTAGCGACTGATCGATGGATGCTAGCAT
    34. 34. GCATCGTGACTAGCGACTGATCGATGGATGCTAGCAT
    35. 35. GCATCGTGACTAGCGACTGATCGATGGATGCTAGCAT 25% 50% 25%GCATCGTGACTAGCGACTGATCGATGGATGCTAGCAT
    36. 36. GCATCGTGACTAGCGACTGATCGATGGATGCTAGCAT 25% 50% 25%GCATCGTGACTAGCGACTGATCGATGGATGCTAGCATGCATCGTGACTAGCGACTGATCGATGGATGCTAGCAT Dense methylated needed for transcriptional silencing Are there alleles with all three positions methylated ?
    37. 37. Deep Sequencing unmethylated alleles methylated alleles less methylation more methylationGCATCGTGACTTACGACTGATCGATGGATGCTAGCAT
    38. 38. Deep MGMTHeterogenic complexity
    39. 39. ConclusionCombination of different sequencingtechniques is emerging as best practiceBioinformatics is challengingMethods for normalisation underconstructionReference databases are generatedData visualization and integration is key 41
    40. 40. Slides availablewww.bioinformatics.be 4th December 2012 Johns Hopkins Bloomberg School of Public Health
    41. 41. biobix wvcriekibiobix.bebioinformatics.be 43
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