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Personal Genome Projectile

Personal Genome Projectile. 9-9:30 AM 20-Oct NRB Room 350. Thanks to:. Agenda.

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Personal Genome Projectile

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  1. Personal Genome Projectile 9-9:30 AM 20-Oct NRB Room 350 Thanks to:

  2. Agenda 9:00 am Introduction: George Church 9:30 am PGP-10 comment period10:00 am Genomic Consultation : Joseph Thakuria MD, MGH10:30am PGP Cells: Jay Lee MD, In Hyun Park 11:00 am Response of Patients to ApoE info: Robert Green MD, Boston Univ.11:30am PGP-10 & Staff -saliva specimen collection for microbiomics12:00 pm Lunch12:45 pm Tour featuring Polonator instruments 1:00 pm Sharing: John Wilbanks, Science Commons 1:30 pm Association Studies: David Altshuler MD, Broad Institute 2:00 pm PGP-10 & Staff Flex Time 3:00 pm International PGP: Jeantine Lunshof, Amsterdam, Margret Hoehe,MD Berlin 3:30 pm PGP-10 comment period and public data release 4:00 pm Closing Remarks: George Church 4:30 pm Press conference NRB Rotunda 6:00 pm Public event sponsored by Nova scienceNow

  3. Suggestions are welcome #1: #2:

  4. Major points #1: Thank you #2: Today is a start, not a final product #3: PGP is research, not a genetics service #4: We are providing some interpretations, but mainly to initiate study & discussion. Decisions about releasing data should be largely based on other considerations. #5: Today: PGP-10: 50K exons, SNPs, CNVs, #6: 2009: PGP>100: 200K exons, RNA, microbiome, VDJome; full genomes for 10.

  5. PGP Education, ELSI, International Meetings: PG-0 28-Jun-06 Toronto, AnnArbor, PG-1 18-Jul-07 Boston, Brookline PG-2 20-Oct-08 Boston PG-3 ?? Education: pgEd.org, NecessaryFilms.com Oppenheimerfoundation.org PGP inquiries: UCSD, JCVI, UNM, Yale, ISB Berlin, Toronto, Seoul, Shenzhen, Singapore

  6. PersonalGenomes.org : gene/environment/trait data 1660 0431 1846 1070 1730 1677 1687 1731 1833 1781 1) Open access (very low barrier to participation) 2) Avoid over-promising on de-identification 3) 100% onExam to assure informed consent 4) Low cost coding sequence + regulatory data 5) Multi-traits: imaging, iPS stem cell RNA, microbes 6) Cells available for personal functional genomics 7) IRB approval for 100,000 diverse volunteers 2003 to 2008 International consortium Lunshof JE, Chadwick R, Vorhaus DB, Church GM. From genetic privacy to open consent. Nat Rev Genet. 2008 Lunshof JE, Chadwick R, Church GM (2008) Hippocrates revisited? Old ideals and new realities. Genomic Med. 2(1-2):1-3.

  7. Inherited Genomics Once in a life-time genome sequence to Predictive Medicine TRAITS (Phenome) PERSONAL GENOME 1 to 98%

  8. Inherited + Environmental Genomics Once in a life-time genome + yearly ( to daily) tests Public Health Bio-weather map : Allergens, Microbes, Viruses VDJ-ome Multi-tissue Epigenome (RNA,mC) TRAITS (Phenome) PERSONAL GENOME 1 to 98% Microbiome

  9. Omic combinatorics (Alleles^n * environments^m) vs. (lumping via pathways) 9K chem/drugs VDJ-ome 1M receptors >>250 tissues epigenome (RNA,mC) 4000 disorders + non-medical (quant)traits PERSONAL GENOME 3M alleles Microbiome 1M species

  10. Multiple hypothesis testing Pool some alleles by pathway & mutation type (not LD or chromosome position) Allele &environment combinations = Genotypic relative risk based on Risch & Merikangas (1996) Science 273: 1516

  11. Sequencing tracked Moore’s law (2X / 2 yr) until 2004-8 (10X / yr) 40X 98% genome $5K in 2008 ($50 for 1%?)

  12. A G C T Multiplex Cyclic Sequencing by Synthesis Polonator: multiple chemistries: polonies on slides or beads Polymerase-or- Ligase Shendure, Porreca, et al. 2005 Science Mitra, et al. 2003 Analyt. Biochem. 1999 NAR AB-SOLiD*, CGI* Illumina, IBS*

  13. Open-architecture hardware, software, wetware e.g. 1981 IBM PC $150K - 2 billion beads/run Polonator Rich Terry

  14. 6 Next Generation Sequencing Platforms SAB & PGP10 in 2009

  15. Association Studies & Direct to Consumer

  16. DTC: 23andme #genes 3 8 5 1 2 9 1 6 3 8

  17. The number of human genes Broad Inst.: 20,500 genes with conservation pattern indicative of function Genecard annotated: 29,479; name/location: 38,891 Genetests: 1347; #included in today’s exome: 953 1% of the genome is protein coding = 2x30Mbp

  18. In vitro Paired-end-tags (PET) Science 2005 Gap Fill Nat Methods 2007 Hybridiz. selection Red=Synthetic; Yellow=genome/cDNA 3 ways to capture alleles from genomic or c-DNA Selective genome sequencing 1. 3. 3. 2. For rearrangements Shendure, et al. Science 309:1728 Porreca et al 2007 Nat Methods 4:931 Nilsson et al. (2006) Trends Biotechnol 24:83. How do we optimize >100K 100mers ? Zhang, Chou, Shendure, Li, Leproust, Dahl, Davis,Nilsson, Church

  19. 99% Concordance : GapFill Sequencing & HapMap

  20. Concordance : GapFill Exon PGP Sequencing & Affymetrix SNP chip data (4+ reads)

  21. 3mm skin sample RNA/epigenome challenge: Multiple cell types from adults

  22. Induced Pluripotent Stem Cell Generation & Transdifferentiation (Oct4/Sox2/Myc/Klf4) Adenoviral Infection Retroviral Infection Tissue Culture on a Mouse Feeder Layer ES Cell Colony Identification Clonal Isolation and Propagation Embryoid Body Induction & Guided Differentiation Mixture of differentiated cell types & Guided Differentiation 1 week 2 months Multiple integration sites Jay Lee In Hyun Park Yamanaka, Daley, Thomson Hochedlinger, Jaenisch labs

  23. Reprogramming reproducibility

  24. Inherited + Environmental Genomics One in a life-time genome + yearly ( to daily) tests Public Health Bio-weather map : Allergens, Microbes, Viruses VDJ-ome Multi-tissue Epigenome (RNA,mC) TRAITS (Phenome) PERSONAL GENOME 1 to 98% Microbiome

  25. PGP Microbiome-Resistome: 18 Antibiotics Dantas, Sommer, Church unpublished

  26. Bacteria Subsisting on 18 Antibiotics Dantas Sommer Church Science 2008

  27. Antibody VDJ regions Lefranc, The Immunoglobulin FactsBook; Janeway, Immunobiology 2001

  28. Human B &T lymphocyte cDNA : VDJ Polonies 2-4 E6 / ml * 5L = 1E10 cells (blood) 46*23*6*67*5 = 2M combinations (24 bits vs 750 bp) Uri Laserson, Francois Vigneault http://www.infobiogen.fr/services/chromcancer/Genes/TCRBID24.html

  29. VDJ(H) 16 antigens &3 PG-B cellscombinations24x86 ImMunoGeneTics database http://imgt.cines.fr/

  30. Suggestions are welcome #1: #2:

  31. Major points #1: Thank you #2: Today is a start, not a final product #3: PGP is research, not a genetics service #4: We are providing some interpretations, but mainly to initiate study & discussion. Decisions about releasing data should be largely based on other considerations. #5: Today: PGP-10: 50K exons, SNPs, CNVs, #6: 2009: PGP>100: 200K exons, RNA, microbiome, VDJome; full genomes for 10.

  32. .

  33. Is promising anonymity realistic? Are we in denial? Trends in laws to make data public (not just at elite institutions):e.g.H.R. 2764, SEC. 218. 26Dec07 open-access for all NIH-funded research. SEC, GINA, etc (12) Identify individual case/control status from pooled SNP data Homer et al PLoS Genetics 2008 (11) Re-identification after “de-identification” using public data. Group Insurance list of birth date, gender, zip code sufficient to re-identify medical records of Governor Weld & family via voter-registration records (1998) Self identification trend (genome-altruists) (10) Unapproved self-identification. e.g. Celera IRB. (Kennedy Science. 2002) (9) Obtaining data about oneself via FOIA or sympathetic researchers. (8) DNA data CODIS data in the public domain. even if acquitted index

  34. Is promising anonymity realistic? Are we in denial? Accessing “Secure data” (7) Laptop loss. 26 million Veterans' medical records, SSN & disabilities stolen Jun 2006. (6) Hacking. A hacker gained access to confidential medical info at the U. Washington Medical Center -- 4000 files (names, conditions, etc, 2000) (5) Combination of surnames from genotype with geographical info An anonymous sperm donor traced on the internet 2005 by his 15 year old son who used his own Y chromosome data. (4) Identification by phenotype. If CT or MR imaging data is part of a study, one could reconstruct a person’s appearance . Even blood chemistry can be identifying in some cases. (3) Inferring phenotype from genotypeMarkers for eye, skin, and hair color, height, weight, geographical features, dysmorphologies, etc. are known & the list is growing. (2) “Abandoned DNA bearing samples (e.g. hair, dandruff, hand-prints, etc.) (1) Government subpoena. False positive IDs and/or family coercion index

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