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9-9:30 AM 20-Oct NRB Room 350

Thanks to:

Personal Genome Projectile

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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

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Suggestions are welcome#1: #2:

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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.

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PGP Education, ELSI, InternationalMeetings:PG-0 28-Jun-06 Toronto, AnnArbor, PG-1 18-Jul-07 Boston, BrooklinePG-2 20-Oct-08 BostonPG-3 ??

Education: pgEd.org, NecessaryFilms.comOppenheimerfoundation.org

PGP inquiries: UCSD, JCVI, UNM, Yale, ISBBerlin, Toronto, Seoul, Shenzhen, Singapore

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PersonalGenomes.org : gene/environment/trait data

1) Open access (very low barrier to participation) 2) Avoid over-promising on de-identification 3) 100% on Exam to assure informed consent4) Low cost coding sequence + regulatory data 5) Multi-traits: imaging, iPS stem cell RNA, microbes 6) Cells available for personal functional genomics7) IRB approval for 100,000 diverse volunteers 2003 to 2008 International consortium

0431

1070

1660

1677

1687

1833

1846

1731

1730 

1781

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.

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Inherited Genomics

TRAITS(Phenome)

PERSONAL GENOME1 to 98%

Once in a life-time genome sequence

to Predictive Medicine

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Inherited + Environmental Genomics

VDJ-ome

TRAITS(Phenome)

Microbiome

Multi-tissue

Epigenome

(RNA,mC)

PERSONAL GENOME1 to 98%

Once in a life-time genome + yearly ( to daily) tests

Public Health Bio-weather map : Allergens, Microbes, Viruses

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9K chem/drugs

Omic combinatorics

VDJ-ome1M receptors

4000 disorders + non-medical (quant)traits

Microbiome1M species

>>250 tissues

epigenome (RNA,mC)

PERSONAL GENOME3M alleles

(Alleles^n * environments^m) vs. (lumping via pathways)

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Multiple hypothesis testingY= Number of Sib Pairs (Assocation)

X= Number of Alleles (Hypotheses) Tested

GRR=1.5, p= 0.5 (population frequency)

0

200

400

600

800

1,000

1,200

1,400

1,600

1E+4 1E+7 1E+10 1E+13 1E+16 1E+19 1E+22

|

= Genotypic relative risk

based on Risch & Merikangas (1996) Science 273: 1516

Pool some alleles by pathway & mutation type(not LD or chromosome position)

Allele & environmentcombinations

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Sequencing tracked Moore’s law (2X / 2 yr) until 2004-8 (10X / yr)

40X 98% genome $5K in 2008 ($50 for 1%?)

0.0000001

0.000001

0.00001

0.0001

0.001

0.01

0.1

1

10

1990 1995 2000 2005 2010

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G

A

C

T

Multiplex Cyclic Sequencing by Synthesis Polonator: multiple chemistries: polonies on slides or beads

Polymerase -or- LigaseShendure,

Porreca, et al. 2005 Science

Illumina, IBS*

AB-SOLiD*, CGI*

Mitra, et al. 2003 Analyt.

Biochem.1999NAR

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Open-architecture hardware, software, wetware

Polonator

$150K - 2 billion beads/run

e.g.1981IBM PC

Rich Terry

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6 Next Generation Sequencing Platforms

Roche Illumina AB-SOLiD Helicos Polonator

$500K $680K $690K $1350K $155K

.001G/0.03h 0.2 G /2.6h 0.3 G /4h 2.8 G/2h 2G/2h

VDJ-grant Exomes Co-develop SAB Co-develop

SAB & PGP10 in 2009

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Association Studies & Direct to Consumer$350K 98% genome

$2500 0.02% 23 clinical

$999 0.02% 31 diseases

$400 0.02% 10 clinical

68 researchsubsidized 0.02% de-identified

subsidized 0.02% researcher subset

subsidized Varies -- no trait data

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DTC: 23andme

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5129

#genes

1638

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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

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Selective genome sequencing

Shendure, et al. Science 309:1728 Porreca et al 2007 Nat Methods 4:931 Nilsson et al. (2006) Trends Biotechnol

24:83.

Red=Synthetic; Yellow=genome/cDNA

How do we optimize >100K 100mers ?

3 ways to capture alleles from genomic or c-DNA

In vitro Paired-end-tags (PET)

Science Science 20052005

Hybridiz.selection

Zhang, Chou, Shendure, Li, Leproust, Dahl, Davis, Nilsson, Church

For rearrangements

2. 3.1.

GapFill

Nat Methods 2007

3.

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99% Concordance : GapFill Sequencing & HapMap

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Concordance : GapFill Exon PGP Sequencing & Affymetrix SNP chip data (4+

reads)

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RNA/epigenome challenge: Multiple cell types from adults

3mm skin sample

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Induced Pluripotent Stem Cell Generation & Transdifferentiation (Oct4/Sox2/Myc/Klf4)

Retroviral Infection

Tissue Culture on a Mouse Feeder Layer

ES Cell Colony Identification

Clonal Isolation and Propagation

Embryoid Body Induction&

Guided Differentiation

Adenoviral Infection

Mixture of differentiated cell types

&Guided Differentiation

2 monthsMultiple integration sites

1 week

Yamanaka, Daley, ThomsonHochedlinger, Jaenisch labs

Jay Lee

In HyunPark

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Reprogramming reproducibility

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Inherited + Environmental Genomics

VDJ-ome

TRAITS(Phenome)

Multi-tissue

Epigenome

(RNA,mC)

PERSONAL GENOME1 to 98%

One in a life-time genome + yearly ( to daily) tests

Public Health Bio-weather map : Allergens, Microbes, Viruses

Microbiome

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PGP MicrobiomeResistome: 18 Antibiotics

Dantas, Sommer, Churchunpublished

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Bacteria Subsisting on 18 Antibiotics

DantasSommerChurchScience

2008

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Antibody VDJ regions

Lefranc, The Immunoglobulin FactsBook; Janeway, Immunobiology 2001

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Human B &T lymphocyte cDNA : VDJ Polonies

http://www.infobiogen.fr/services/chromcancer/Genes/TCRBID24.html

2-4 E6 / ml * 5L = 1E10 cells (blood) 46*23*6*67*5 = 2M combinations (24 bits vs 750 bp)

  V D J C

IGH38-46

23 6 9

IGK31-35

- 5 1

IGL 29-32 - 4-5 4-5

TRA

45-47

- 50 1

TRB 39-46 2 13 2

TRD/A 5 3 4 1

TRG 4-6 - 5 2

Uri Laserson,

Francois Vigneault

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VDJ(H) 16 antigens &3 PG-B cells

combinations24x86

ImMunoGeneTics database http://imgt.cines.fr/

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Suggestions are welcome#1: #2:

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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.

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.

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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

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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 genotype Markers 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