Can	  we	  exploit	  the	  power	  of	  NGS	                to	  move	  towards	  personalized	                           ...
BACKGROUND• Biology background• Part of the core human genome analysis team  within the Ensembl group -> pure  bioinformat...
DRIVING QUESTION: GENOME FUNCTION!     • Bioinformatics Pipelines can only reflect the current       (biased) understandin...
A VIEW OF THE GENOME...giovedì 14 giugno 12
A VIEW OF THE GENOME...                       Coding gene…giovedì 14 giugno 12
A VIEW OF THE GENOME...                           RNASeq: Transcripts, splicing, expression profiling                      ...
A VIEW OF THE GENOME...                                   RNASeq: Transcripts, splicing, expression profiling              ...
A VIEW OF THE GENOME...                                                 RNASeq: Transcripts, splicing, expression profiling...
A VIEW OF THE GENOME...                                                 RNASeq: Transcripts, splicing, expression profiling...
A VIEW OF THE GENOME...                                                 RNASeq: Transcripts, splicing, expression profiling...
A VIEW OF THE GENOME...                                                 RNASeq: Transcripts, splicing, expression profiling...
A VIEW OF THE GENOME...                                                 RNASeq: Transcripts, splicing, expression profiling...
GENETICS...    • We           are at a crossroads between:         • Existing  and ongoing GWAS data, based on genotyping ...
EXOME SEQUENCING IN RARE DISEASES:                        FUNCTION!     Collaboration with Phil                           ...
EXOME SEQUENCING IN RARE DISEASES:                        FUNCTION!     Collaboration with Phil                           ...
EXOME SEQUENCING IN RARE DISEASES:                        FUNCTION!     Collaboration with Phil                           ...
EXOME SEQUENCING IN RARE DISEASES:                        FUNCTION!     Collaboration with Phil                           ...
INDELS AND REPAT                       NUMBERS... IMPORTANT!giovedì 14 giugno 12
RNA: STILL A LOT OF                         UNKNOWNS    • ncRNAs? We         need a real catalogue, so far incomplete!giov...
Why it matters: an example in a Parkinson            locus                                    Collaboration with          ...
A NEW CLASS OF NCRNAS!                         Nature, 3rd revisiongiovedì 14 giugno 12
A NEW CLASS OF NCRNAS!                         Nature, 3rd revisiongiovedì 14 giugno 12
A NEW CLASS OF NCRNAS!                         Nature, 3rd revisiongiovedì 14 giugno 12
A NEW CLASS OF NCRNAS!                         Nature, 3rd revisiongiovedì 14 giugno 12
DNA METHYLATION             • Pooled 10 individuals through neurofibroma               progression:                    Col...
REPEAT ELEMENTS...                                       Collaboration                                            with    ...
EPIGENETICS IN FETAL         PROGRAMMING OF DISEASE                        Collaboration with:                        Prof...
CARDIOVASCULAR GENETICS         AND EPIGENETICSgiovedì 14 giugno 12
giovedì 14 giugno 12
HOW TO MOVE ALL THIS TO                THE CLINIC    • Moved    to San Raffaele Hospital in Milan, a highly integrated    ...
MULTIPLE SCLEROSIS FAMILY                                Collaboration                                     with           ...
HETEROGENEITY OF PATIENTS:                   OK IF KNOWN?     Whole    genomeSNP arrays  GeneExpressionRNA-SeqMedip-Seq Ch...
WEIGHTED GENETIC                          RISK SCORE                                  1.5                                 ...
GENE EXPRESSIONgiovedì 14 giugno 12
INTEGRATION NOT AS SCARY AS IT SEEMS        a, Whole-genome view of the gene ranks based on integrating ChIP-on-chip,     ...
THE TEAMgiovedì 14 giugno 12
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Can we exploit the power of NGS to move towards personalized medicine?, Center for Translational Genomics and Bioinformatics, San Raffaele Scientific Institute, Elia Stupka Copenhagenomics 2012

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At CPHx Elia Stupka discussed successes, failures and challenges ahead if we want to turn NGS into the holy grail of “personalized medicine”.

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Can we exploit the power of NGS to move towards personalized medicine?, Center for Translational Genomics and Bioinformatics, San Raffaele Scientific Institute, Elia Stupka Copenhagenomics 2012

  1. 1. Can  we  exploit  the  power  of  NGS   to  move  towards  personalized   medicine? Elia Stupka - stupka.elia@hsr.itgiovedì 14 giugno 12
  2. 2. BACKGROUND• Biology background• Part of the core human genome analysis team within the Ensembl group -> pure bioinformatics• In Singapore, headed the Fugu informatics team, again bioinformatics, involved in Fantom3 project• Since then, tried to get closer to the biology (added a wet lab 8 years ago)... and then to the clinic (added medical staff to the group last year)giovedì 14 giugno 12
  3. 3. DRIVING QUESTION: GENOME FUNCTION! • Bioinformatics Pipelines can only reflect the current (biased) understanding of what the data should be telling… • Classic examples: –“Surely a gene can’t produce so many transcripts, put a higher cut-off on your predictions” –“Delete all genes which do not encode for a protein” –“Delete all genes which are less than 200nt long” • Thus I grew an interest in… rubbish (US:garbage), or to be more precise, in elements of the genome and its grammar which did not fit accepted rules…giovedì 14 giugno 12
  4. 4. A VIEW OF THE GENOME...giovedì 14 giugno 12
  5. 5. A VIEW OF THE GENOME... Coding gene…giovedì 14 giugno 12
  6. 6. A VIEW OF THE GENOME... RNASeq: Transcripts, splicing, expression profiling Non-coding RNA RNASeq Coding gene…giovedì 14 giugno 12
  7. 7. A VIEW OF THE GENOME... RNASeq: Transcripts, splicing, expression profiling Promoter CAGE Seq Non-coding RNA RNASeq Coding gene…giovedì 14 giugno 12
  8. 8. A VIEW OF THE GENOME... RNASeq: Transcripts, splicing, expression profiling Methylation Promoter CAGE Seq Non-coding RNA RNASeq Coding gene…giovedì 14 giugno 12
  9. 9. A VIEW OF THE GENOME... RNASeq: Transcripts, splicing, expression profiling Methylation Promoter CAGE Seq Non-coding RNA Enhancer RNASeq P300 ChiPSeq Coding gene…giovedì 14 giugno 12
  10. 10. A VIEW OF THE GENOME... RNASeq: Transcripts, splicing, expression profiling Methylation Promoter Insulator CTCF CAGE Seq ChIP Seq Non-coding RNA Enhancer RNASeq P300 ChiPSeq Coding gene…giovedì 14 giugno 12
  11. 11. A VIEW OF THE GENOME... RNASeq: Transcripts, splicing, expression profiling Methylation Histone Promoter Insulator CTCF Modifications CAGE Seq ChIP Seq Non-coding RNA Enhancer RNASeq P300 ChiPSeq Coding gene…giovedì 14 giugno 12
  12. 12. A VIEW OF THE GENOME... RNASeq: Transcripts, splicing, expression profiling Methylation SNP Histone Promoter Insulator CTCF Modifications CAGE Seq ChIP Seq Non-coding RNA Enhancer RNASeq P300 ChiPSeq Coding gene…giovedì 14 giugno 12
  13. 13. GENETICS... • We are at a crossroads between: • Existing and ongoing GWAS data, based on genotyping microarrays, still cheapest and most mature for studies of 10,000s of cases • Heavy emphasis on exome sequencing, with many projects in completion examining hundreds or low1,000s of samples • BUT, no major breakthroughs in complex disease.... • Whole genome sequencing also ongoing, numbers increasing rapidly, but still quite costly for high coveragegiovedì 14 giugno 12
  14. 14. EXOME SEQUENCING IN RARE DISEASES: FUNCTION! Collaboration with Phil A Waters, F Lescai et al, submitted Beales, UCLgiovedì 14 giugno 12
  15. 15. EXOME SEQUENCING IN RARE DISEASES: FUNCTION! Collaboration with Phil A Waters, F Lescai et al, submitted Beales, UCLgiovedì 14 giugno 12
  16. 16. EXOME SEQUENCING IN RARE DISEASES: FUNCTION! Collaboration with Phil A Waters, F Lescai et al, submitted Beales, UCLgiovedì 14 giugno 12
  17. 17. EXOME SEQUENCING IN RARE DISEASES: FUNCTION! Collaboration with Phil A Waters, F Lescai et al, submitted Beales, UCLgiovedì 14 giugno 12
  18. 18. INDELS AND REPAT NUMBERS... IMPORTANT!giovedì 14 giugno 12
  19. 19. RNA: STILL A LOT OF UNKNOWNS • ncRNAs? We need a real catalogue, so far incomplete!giovedì 14 giugno 12
  20. 20. Why it matters: an example in a Parkinson locus Collaboration with Stefano Gustincich Lab, SISSAgiovedì 14 giugno 12
  21. 21. A NEW CLASS OF NCRNAS! Nature, 3rd revisiongiovedì 14 giugno 12
  22. 22. A NEW CLASS OF NCRNAS! Nature, 3rd revisiongiovedì 14 giugno 12
  23. 23. A NEW CLASS OF NCRNAS! Nature, 3rd revisiongiovedì 14 giugno 12
  24. 24. A NEW CLASS OF NCRNAS! Nature, 3rd revisiongiovedì 14 giugno 12
  25. 25. DNA METHYLATION • Pooled 10 individuals through neurofibroma progression: Collaboration with •Schwann Cells (healthy) Stephan Beck Lab •Benign tumour A Feber et al, •Malignant tumour Genome Research, 2011 • Checked DNA Methylation by Medip-Seqgiovedì 14 giugno 12
  26. 26. REPEAT ELEMENTS... Collaboration with Stephan Beck Lab A Feber et al, Genome Research, 2011giovedì 14 giugno 12
  27. 27. EPIGENETICS IN FETAL PROGRAMMING OF DISEASE Collaboration with: Prof. Adrian Clark, Barts and The London School of Medicine Prof. Simon Langley Evans, University of Nottinghamgiovedì 14 giugno 12
  28. 28. CARDIOVASCULAR GENETICS AND EPIGENETICSgiovedì 14 giugno 12
  29. 29. giovedì 14 giugno 12
  30. 30. HOW TO MOVE ALL THIS TO THE CLINIC • Moved to San Raffaele Hospital in Milan, a highly integrated campus with1,600 scientists, 5,000 hospital staff and a University with a Medical Faculty • Primary challenges: • PEOPLE: Cultural barriers, burocratic barriers, etc. • IT: Sharing data, knowledge, databases, etc. • ETHICS and BIOBANKING and CLINICAL CULTURE • EXPERIMENTAL DESIGN: plan early, impossible to fix later!giovedì 14 giugno 12
  31. 31. MULTIPLE SCLEROSIS FAMILY Collaboration with INSPE Dr Martinelli- Boneschi Prof. Giancarlo Comigiovedì 14 giugno 12
  32. 32. HETEROGENEITY OF PATIENTS: OK IF KNOWN? Whole genomeSNP arrays GeneExpressionRNA-SeqMedip-Seq Chip-Seqgiovedì 14 giugno 12
  33. 33. WEIGHTED GENETIC RISK SCORE 1.5 Family cases Family controls HSR cases HSR controls 1.0 Density 0.5 0.0 7 8 9 10 11 12 13 GRSgiovedì 14 giugno 12
  34. 34. GENE EXPRESSIONgiovedì 14 giugno 12
  35. 35. INTEGRATION NOT AS SCARY AS IT SEEMS a, Whole-genome view of the gene ranks based on integrating ChIP-on-chip, methylation and gene expression results. The y axis shows −log(P), where P is the P value of the Qstatistic corrected for multiple testing. Significantly (false discovery rate, ≤10%) downregulated (green) or upregulated (red) genes are shown. SNPs, CNVs, DNA Methylation, Histone Methylation, Gene Expression, etc. J Zhang et al, Nature, 2012 ...and... Wilks, S. Order Statistics. Bull Amer Math 54, 6-50 (1948) !!!! :)giovedì 14 giugno 12
  36. 36. THE TEAMgiovedì 14 giugno 12

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