4 th December 2012 Johns Hopkins Bloomberg School of Public Health Slides available www.bioinformatics.be
May 11, 2015
4th December 2012 Johns Hopkins Bloomberg School of Public Health
Slides available www.bioinformatics.be
Lab for Bioinformatics and computational genomics
10 “genome hackers” mostly engineers (statistics)
42 scientists technicians, geneticists, clinicians
>100 people hardware engineers,
mathematicians, molecular biologists
Can bioinformatics bridge the gap ?
The genome is just the start …
Epigenetic (meta)information = stem cells
250 different cell types
Epigenetic (meta)information = stem cells
Cellular programming
Defining Epigene*cs
§ Reversible changes in gene expression/func5on
§ Without changes in DNA sequence
§ Can be inherited from precursor cells
§ Allows to integrate intrinsic with environmental signals (including diet)
Genome
DNA
Gene Expression
Epigenome
Chroma*n
Phenotype
DNA Methylation Differentiates Totipotent Embryonic Stem Cells from Unipotent Adult Stem Cells!
Alex Meissner, Henry Stewart Talks
Paula Vertino, Henry Stewart Talks
Reprogramming the DNA methylome
Transgenerational inheritence
The epigenome is ac5onable
The epigenome is ac5onable
Epigene*c Changes are Important in Causing Cancer
Example: Replica*on errors
GENETIC EPIGENETIC
Example: Chroma*n modifica*on errors
Altered DNA/mRNA/proteins
Altered DNA sequence
Altered levels of mRNA/proteins
Altered chroma*n structure
X X
Oncogenesis
Tumor
Source: Schuebel et al 2007
0
20
40
60
80
100
120
Methylated Mutated
76-‐100 51-‐75 21-‐50 1-‐20
Dx
CDx
Example of Methyla*on vs Muta*on: Colon & Breast Cancer
MGMT Biology O6 Methyl-‐Guanine Methyl Transferase
Essen5al DNA Repair Enzyme Removes alkyl groups from damaged guanine bases Healthy individual:
-‐ MGMT is an essen5al DNA repair enzyme Loss of MGMT ac5vity makes individuals suscep5ble to DNA damage and prone to tumor development
Glioblastoma pa*ent on alkylator chemotherapy: -‐ Pa5ents with MGMT promoter methyla5on show have longer PFS and OS with the use of alkyla5ng agents as chemotherapy
MGMT Promoter Methyla*on Predicts Benefit form DNA-‐Alkyla*ng Chemotherapy
Post-‐hoc subgroup analysis of Temozolomide Clinical trial with primary glioblastoma pa5ents show benefit for pa5ents with MGMT promoter methyla5on
0
5
10
15
20
25 Median Overall Survival
21.7 months
12.7 months
radiotherapy
plus temozolomide
Methylated MGMT Gene
Non-‐Methylated MGMT Gene
radiotherapy
Adapted from Hegi et al. NEJM 2005 352(10):1036-‐8. Study with 207 pa5ents
# samples
# markers
Profiling the Epigenome
Discovery
Verifica5on
Valida5on
Genome-‐wide methyla*on by methyla*on sensi*ve restric*on enzymes
Genome-‐wide methyla*on by probes
# samples
# markers
Profiling the Epigenome By next gen sequencing
Discovery
Verifica5on
Valida5on
MBD_Seq
DNA Sheared
Immobilized Methyl Binding Domain
Condensed Chroma5n
DNA Sheared
Immobilized Methyl binding domain
MgCl2
Next Gen Sequencing GA Illumina: 100 million reads
MBD_Seq
25
0 10 20 30 40 50
0.00
0.05
0.10
0.15
0.20
0.25
Number of CG's
Frac
tion
of re
ads
0 10 20 30 40 50
0.00
0.05
0.10
0.15
0.20
0.25
Number of CG's
Frac
tion
of re
ads
0 10 20 30 40 50
0.00
0.05
0.10
0.15
0.20
0.25
Number of CG's
Frac
tion
of re
ads
0 10 20 30 40 50
0.00
0.05
0.10
0.15
0.20
0.25
Number of CG's
Frac
tion
of re
ads
●
●
●
●
●
●
●
●
●
●●
● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●
Kit Comparison
MBD_Seq MGMT = dual core
# samples
# markers
MBD_Seq
Profiling the epigenome …. by next genera*on sequencing
Discovery
1-‐2 million methyla5on
cores
28
Bock et al. Nature 2012 Bock et al, Nature, 2012
29
Data integra*on Correla*on tracks
30
methylation methylation
expression expression
Corr =-1 Corr = 1
Correla*on track in GBM @ MGMT
31
+1
-1
miRNA, (l)ncRNA, CIS/TRANS splicing, SV, fusion loci , bidirec*onal promoters ? RNA_seq: sequence RNA molecules Next Gen Pla`orm Total RNA_seq: all RNA molecules (normalisa*on procedure) Direc*onal Total RNA_seq: before amplifica*on use different 5’ and 3’ adaptors Integrated Direc*onal Total RNA_seq: Combine with other datasets eg. enrichment sequencing data, visualise and query in genome browser
32
Next_next
Direc*on RNAseq bidirec*onal promoters
33
# samples
# markers
MBD_Seq
454_BT_Seq
Profiling the Epigenome …. by next genera*on sequencing
Discovery
Verifica5on
Valida5on
GCATCGTGACTAGCGACTGATCGATGGATGCTAGCAT
Where is the mC ?
GCATCGTGACTAGCGACTGATCGATGGATGCTAGCAT
GCATCGTGACTAGCGACTGATCGATGGATGCTAGCAT
25% 50% 25%
GCATCGTGACTAGCGACTGATCGATGGATGCTAGCAT
GCATCGTGACTAGCGACTGATCGATGGATGCTAGCAT
25% 50% 25%
GCATCGTGACTAGCGACTGATCGATGGATGCTAGCAT
GCATCGTGACTAGCGACTGATCGATGGATGCTAGCAT
Dense methylated needed for transcrip5onal silencing Are there alleles with all three posi.ons methylated ?
GCATCGTGACTTACGACTGATCGATGGATGCTAGCAT!
unmethylated alleles
less methyla5on methylated alleles
more methyla5on
Deep Sequencing
Deep MGMT Heterogenic complexity
Combina5on of different sequencing techniques is emerging as best prac5ce Bioinforma5cs is challenging § Methods for normalisa5on under construc5on
§ Reference databases are generated Data visualiza5on and integra5on is key
41
Conclusion
4th December 2012 Johns Hopkins Bloomberg School of Public Health
Slides available www.bioinformatics.be
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