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

43  

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