Jieming Chen Yale University

CBB752a12

Mining yourPersonal Genome

What is Personal Genomics?

• Personal genomics is the branch of genomics concerned with the sequencing and analysis of the genome of an individual -- Wikipedia

• Is it not possible before?- Genetics VS genomics- Post-Human-Genome-Project (HGP) genomics

2000 2003 2006 2008 2010

Nature (2010)

Personal Genomics

1. From basic research, to clinic, then to the masses

2. Tools to mine your own genome

3. Ethics and Privacy

GENOMICS IN BASIC RESEARCHIncreasingly “personalized” genomics…

Before mass sequencing- mass genotyping -

• Genotyping- Determination of the

genotypes of parts (usually genetic variations) of an individual’s genome using biological assays

• SNP arrays Hybrid arrays- SNP (single nucleotide

polymorphisms)genotyping

- Main players: Affymetrix VS Illumina

Affymetrix: http://www.affymetrix.com/Illumina : http://www.illumina.com/

Before mass sequencing- mass genotyping -

• Array CGH (comparative genomic hybridization)

- CNV (copy number variation) genotyping- Main players: Agilent VS Nimblegen- Main application:

detection of genomic abnormalities in cancer detection of large structural aberrations (especially at the chromosomal level)

SNP arrays• Affymetrix• Illumina

• Probes on microarray technology

1K10KXba

50KHindXba

100K250KNspSty

500K SNP 5.0 SNP 6.0 Axiom

100K 240K 300K 550K 610K 650K 1M Omni

Affymetrix Axiom Solutionshttp://www.affymetrix.com/

SNP selection in array design1) SNP quantity

- limited by microarray technology2) SNP content

- random probes or probes for ‘tag’ SNPs- random probes are produced by specific enzymes in some array technology- ‘tag’ SNPs is one that represents a group of SNPs in a genomic region due to a phenomenon called, linkage disequilibrium (LD).- LD refers to the non-random association of alleles at 2 or more loci.- Haplotypes refers to a certain configuration of alleles that are transmitted together (or assumed to be).- One can, in theory, predict the larger group of SNPs with a smaller set of SNPs

Linkage Disequilibrium

A Ba b

AB

ab

High LD -> No Recombination(r2 = 1) SNP1 “tags” SNP2

A B

A B

A B

a b

a b

a b

Low LD -> RecombinationMany possibilities

A b

A ba Ba b

A BA B

a B

A b

etc…

A b

A B

X

OR

Parent 1 Parent 2

ASHG 2008 Hapmap Tutorial: http://hapmap.ncbi.nlm.nih.gov/tutorials.html.en

The International HapMap Project• Largely exploited the idea of haplotypes and

LD - reduce cost (sequencing is expensive)- capitalize on microarray technology

• Involved Illumina, Affymetrix,>20 institutions worldwide

• HapMap1 (2003) and Hapmap2 (2005)- 4 populations (270 indiv): CEU (NW European from Utah), CHB (Han Chinese from Beijing), JPT (Japanese from Tokyo), YRI (Yoruban from Nigeria)

• Hapmap3 (2010) - 11 populations (4+7, 1301 indiv)

The International HapMap Project• Provided the foundation

for future human genomic projects:- maturation of the microarray technology - tool development from industry and academia- the use of common variations in disease studies and genome-wide association studies (GWAS)- population-specific genetic differences- samples - consent and ethical issues

• Major limitations: 1) coverage (the entire genome is not covered)2) rare variants are unlikely to be uncovered3) population-based genome-wide studies

www.hapmap.org

Even with limited information, genomics is getting “personalized”…

Basic• Human reference genome refinement• Human evolution and natural selection• Comparative genomics

Ancestry of individuals• Population structure• Human migration route• Haplotyping • Linguistics

Clinical applications• Pharmacogenetics/genomics• Disease associations

ETC. ETC. ETC……HUGO PASNP Consortium (2009), Science

A C T G

Heralding the personal genomes

• HapMapP3 draft 1 came out in 2009 and paper published in 2010

• Venter genome (2007) and Watson genome (2008)

• Faster, cheaper and more accurate sequencing technologies Transitioning into personal genomes

• 2009-2011, 1000 Genomes Project sequenced 1092 genomes from 14 different populations

2007

2008

2008

2008

2009

2009

2009

200920092009

2010

Further into the personal genome

• Beyond simply sequencing the personal genome• If a family trio is sequenced (mum, dad, child), one can

potentially phase the variations of the child into its maternal and paternal alleles.*

• Phasing refers to the determination of the haplotype of an individual’s sequence.

• It can be done experimentally (not feasible for large-scale phasing) or computationally.

• Typical computational phasing algorithms include the use of HMM (e.g. BEAGLE, Browning & Browning 2007, AJHG) and EM (e.g. fastPHASE, Scheet & Stephens 2006, AJHG).*Note that phasing can also be done with unrelated individuals but you won’t know the maternal or paternal chromosomes

Phasing

Parent 1 Parent 2 Child Informative to phase child’s genome?

Homozygous Homozygous Any Yes

Homozygous Heterozygous Any Yes

Heterozygous Homozygous Any Yes

Heterozygous Heterozygous Homozygous Yes

Heterozygous Heterozygous Heterozygous No

ABcD

aBcd

Father Mother

ABCd

aBcd

Child

Bc

B

d dC

Simple example of phased sequence of the child (as opposed to ‘unphased’, highlighted black)

A a

Adapted from: http://www.chromosomechronicles.com/2009/09/30/use-family-snp-data-to-phase-your-own-genome/

Allele-specific binding (ASB) and expression (ASE)

Possible causes for ASB/ASE1) Epigenetic effects, e.g. imprinting, where methylation silences a maternal/paternal

gene2) Genetic variations (such as SNPs) disrupting a binding motif or modifying a gene on

a single parental haplotype3) Random mono-allelic expression/binding

Clinical examples1) Angelman Syndrome – maternal gene(s) on chromosome 15 inactivated or

deleted, paternal gene imprinted2) Prader-Willi Syndrome – paternal gene(s) on chromosome 15 inactivated or

deleted, maternal gene imprinted

Using a phased genome to study ASB and ASE• Integrate phased sequence with ChIP-seq (binding) and RNA-seq (expression) data

to obtain allele-specific information in binding and expression (Rozowsky J et. al. 2011)

PERSONAL GENOMICS IN CLINICAL RESEARCH

“Personalization in progress… Watch this space”

Personal genomics in ClinicSome areas that clinicians are interested in that genomics can potentially improve:• Disease prediction• Pharmocogenetics/genomics• Response to therapy• Patient care (personalized

environmental and epigenetic information, patient data privacy etc. etc.)

• Personalized medicine and healthcare

Examples of some genomic technologies in clinical research1) Genome-Wide Association Studies2) Exome sequencing3) Pharmacogenetics/genomics4) Gene expression profiles via RNA-seq

McCarthy et. al. 2008

Genome-Wide Association Studies (GWAS)

• First successful GWAS was done at Yale, in 2005 for age-related macular degeneration (AMD) (Klein R. et. al. 2005, Science) - 96 cases, 50 controls, 116K SNPs

Klein R. et. al. 2005

GWAS• Perpetuated by HapMap and microarray technology• Hypothesis-free• Main aims:

1) to find the molecular pathways/mechanisms of complex diseases/traits2) to find genetic markers that these phenotypes are associated with

• Common-disease-common-variant hypothesis- phenotypes are results of cumulative effects of a number of common variants, with at best modest effect sizes

McCarthy et. al. 2008, Nature Reviews

GWAS• Usually SNP-based• Conduct association tests for each SNP

between case VS control to see if there is a significant difference between 2 cohorts.

Allele # Cases # ControlsA nA,case nA,ctrl

B nB,case nB,ctrl

where and n is the minor allele frequency.

McCarthy et. al. 2008, Nature Reviews

GWASLimitations• Note that even though termed “whole genome”, GWAS

till now work mostly with microarray tech use ‘tag SNPs’ which are in LD with many other SNPs GWAS may not (and typically do not) find the causative variant.

• High number of false positives with array-based GWAS currently, the GWAS variants explained only a small genetic fraction of common disease risk

• Heading towards sequencing-based GWAS, especially in looking at uncommon or rare variants

GWASLimitations (cont’d)• Results can be population-specific, e.g. Type 2 diabetes risk allele frequencies decrease from

Sub-Saharan Africa through Europe to East Asia

However, they did provide new insights into novel disease-associated pathways and mechanisms – for instance in AMD.

Catalog of GWAShttp://www.genome.gov/26525384

Chen R et. al. (2012), PLoS Genetics

Pharmacogenetics/genomics

• Pharmacogenetics- refers to the study of genetic variations of individual patient responses to drugs, conventionally in single or a small set of genes

• Pharmacogenomics- refers to large-scale/genome-wide study of genetic variations of individual patient responses to drugs

Interethnic variations in drug responses

• Warfarin is a classic example. a very widely-used anti-coagulant and one of the most well-studied drug extremely difficult to dose because of a narrow therapeutic window genes with haplotypes that affect dosage: VKORC1 and CYP2C9 Warfarin sensitivity (on average): Asians>Caucasians>African Americans

Rettie A & Tai G (2006), Molecular Interventions Review

Quantifying interethnic variation in the genome: an application

• A popular measure in population genetics is the fixation index, FST, which essentially measures population differentiation.

Chen J et. al. (2010), Pharmacogenomics

A peek into a potential future

1. Charcot-Marie-Tooth neuropathy (Lupski et. al., 2010, NEJM) Whole genome sequencing of the lead author himself, who has the disease, and his family found 2 causative mutations associated with the disease, on a region on chromosome 5 affecting SH3TC2 (SH3 and tetratricopeptide repeats 2 gene)

2. The Snyder Experiment (Chen R et. al., 2012, Cell) integration of genomic, transcriptomic, proteomic, metabolomic, and autoantibody profiles of a single healthy individual over a 14-month period revealed a predisposition to Type 2 diabetes despite having no family history

EMPOWERING THE MASSES“knowledge is mightier, IF you wield it right”

Personal genomics for the Masses

What can you mine from your own genome? How can you mine your own genome?What can you tell from your own genome?

• Disease susceptibility• Ancestry• Pharmocogenetics• Traits

ETC. ETC.

The Bottom-up Pyramid Information Flow

Public

Clinical research

Basic Research

Personal genomics for the Masses

• Unprecedented accessibility to the public• Brought about by direct-to-consumer genomic

companies Big 3: DeCode, Navigenics, 23andMe

34

23andMe

• Genotype ~ 1million SNPs per genome• Illumina OmniExpress customized microarray• Ancestry

TraitsDrug responseDisease risks

• Provides your raw data which you can download

35

Beyond 23andMe – Ancestry

Middle East

Inset: http://www.clker.com/clipart-9213.html

Population panels:HAPMAP (Intl HapMap Consortium 2003, Nature)HGDP (Li JZ et. al. 2008, Science)PASNP (HUGO PASNP Consortium 2009, Science)SGVP (Teo YY et. al. 2009, Gen. Res.)

36

Beyond 23andMe – Ancestry

Chen J et. al. (2009), AJHG

PCA in genomic data

SNPs in LD can skew PCA

Modified PCA (Price et. al. (2006), Nat Genet)• 0,1,2 represent the genotypes of SNPs (0=AA, 1=AB, 2=BB,

assuming biallelic SNPs)• then instead of

normalizing by column, normalize by row

• variables = individuals• observations = SNPs• correlation matrix of individuals • plot PC1 vs PC2 by loadings (variables) instead of by PC scores

(observations)

sample YOU CEU1 CEU2 CEU3

SNP1 1 1 1 0

SNP2 2 1 2 0

SNP3 1 2 2 0

Samples

SNPs

PCA interpretation• Genetic differentiation by geography• Studies that showed cultural, linguistic and

historical association with such pattern

Novembre J et. al. 2008, Nature

International Stem Cell Consortium (2011), Nat Biotech

Disease status

• Considerations: populationpanel in which your results are based on how well-studied is the disease

Mendelian diseases• High penetrance• Highly likely to be detected,

hence the results are more likely to be true• Some populations might have a higher rate

2009 Rosner et. al. Annu. Rev. Genomics. Hum. Genet.

Drug Response

43

Ancestry Neanderthal

Tools to mine your own genomeProjects/software from the public• Dienekes Pontikos - EURO-DNA-CALC

Dienekes Anthropology Bloghttp://dienekes.blogspot.com/2008/06/euro-dna-calc-11-released.html

• Dodecad Projecthttp://dodecad.blogspot.com

• Eurogeneshttp://eurogenes.blogspot.com/

Other resources• Galaxy (http://galaxy.psu.edu/)• Interpretome (http://esquilax.stanford.edu/)• SNPTips Firefox browser extension (http://snptips.5amsolutions.com/)• SNPedia/Promethease (http://www.snpedia.com/index.php/Promethease)• A comprehensive list of tools to probe 23andMe data.

http://www.23andyou.com/3rdparty

GALAXY

• http://galaxy.psu.edu/• Web-based platform• Designed for anybody to use• Workflow concept• GALAXY demo

Everybody else

Industry

Academia

+ Clinic

Genomic elements discovery and annotation

Academia:• Human Genome Project• Hapmap• 1000 Genomes ProjectClinic:• Disease association• Pharmacogenetics• BiomarkersIndustry Expedite the democratization

process• Navigenics• 23andMe• deCodeMe• Illumina• Affymetrix

Some Privacy and ethical issues

• Privacy can your identity really be kept anonymous in a research project? Li et. al. 2004, Science“Our calculations show that measuring as few as 75 statistically independent SNPs would define a small group that contained the real owner of the DNA.”

• Ethics how much, if at all, of your genomic information do you own? where do biological relatives stand in all these? genetic discrimination especially with insurance companies