The Ashkenazi Genome Project

Shai CarmiPe’er lab, Columbia University

andThe Ashkenazi Genome Consortium (TAGC)

BostonSeptember 2013

Outline

• Ashkenazi Jewish (AJ) Genetics and TAGC

• Basic Variant Statistics

• Utility in AJ Medical Genetics

• Demographic History of AJ and Europeans

• Summary

Ashkenazi Jewish (AJ) Genetics & TAGC

Recent History of Ashkenazi Jews (AJ)

• Mediterranean origin (?)• Ca. 1000:

Small communities in Northern France, Rhineland

• Migration east• Expansion• Migration to US and Israel• ≈10M today• Relative isolation

Ashkenazi Jewish Genetics

Behar et al., Nature, 2010Bray et al., PNAS, 2010Guha et al., Genome Biol., 2012

300 Jewish individuals; SNP arrays

• Recently, AJ shown to be genetically distinct• Close to Middle-Easterners & South-Europeans

Price et al., PLoS Genet., 2008Olshen et al., BMC Genet., 2008Need et al., Genome Biol., 2009Kopelman et al., BMC Genet., 2009

AJ

Atzmon et al., AJHG, 2010

Jewish non-AJ

Middle-Eastern

Europeans

Recent Demography & IBD

A B

AB

A shared segment

• Recent, strong genetic drift leads to long identical-by-descent haplotypes.

• IBD sharing common in AJ(Gusev et al., MBE, 2011 and others)

• Inferred bottleneck of just ≈300 individuals ≈800 ya(Palamara et al., AJHG, 2012)

Ashkenazi-Jewish (AJ) Genetic Risk Factors

• Multitude of Mendelian disorders

– Carrier screening: A success story

• Breast and ovarian cancer: BRCA1, BRCA2

• Parkinson’s disease: LRRK2, GBA

Gravel et al., 2001Tay-Sachs births

AJ Genetics: Summary & Prospects

Large population (≈10M) Narrow bottleneck (≈300) Mostly isolated Recruitable Well studied Insight on both European

and Middle-Eastern past

× No genealogies× Mobile× Some recent

admixture× Significant ancient

admixture

The Ashkenazi Genome Consortium

Phase I:• 128 AJ personal genomes• Healthy controls• Unrelated, PCA-validated AJ• Technology: Complete Genomics

Goal:• 11+5 labs, mostly from the NY area• Sequence to high coverage hundreds of healthy AJ

o Use as a reference panel for imputation and clinical interpretationo Improve understanding of population history and

functional genetic variation in AJ

Basic Variant Statistics

Variant Statistics &Comparison to Europeans

• Comparison panels:o 1000 Genomes Europeanso 26 Flemish from Belgium, sequenced by Complete Genomics

Projection method: Gravel et al., PNAS, 2011

Allele Frequency Spectrum

Utility in AJ Medical Genetics

Screening AJ GenomesAn ancestry-matched reference panel is expected to filter more benign variants in clinical genomes.

A Catalog of Mutations in Known AJ Disease Genes

• Tens of genes harbor known mutations for AJ-prevalent Mendelian disorders or risk factors for multifactorial diseases.o Tay-Sachs disease, Gaucher disease, Familial dysautonomia, Niemann-Pick disease,

Torsion dystonia, Canavan disease, Bloom syndrome, etc.o Breast cancer (BRCA1/2), Colon cancer (APC), Parkinson’s (LRRK2), etc.

• We mapped 73 mutations in 48 genes.

• Detected carriers of 35 known disease mutations.

• Detected 184 missense and 18 loss-of-function novel (dbSNP135) variants.o Catalog will be made available.

Imputing AJ Arrays

• AJ outperforms CEU even for a larger CEU panel• Accuracy improved across all frequencies and by all measures

— Discordance rate, r2, false negatives/positives, Impute2 metrics

Imputation by IBD• Impute by copying long IBD segments from a fully sequenced genome into

a sparsely genotyped one.– Only 1-2 recent mutations per segment are expected

• IBD detected using Germline with additional filtering.

Fit to:>3cM

A Short Detour:

A Model for the Expected Coverage

Coverage by IBD: Theory• Problem statement:

– Reference panel (say, fully sequenced) of size nr

– Study panel (say, sparsely genotyped) of size ns

– Detect all IBD segments of length >m (Morgan) between study and reference panels– What is the average fraction of a study genome covered by IBD segments to the reference panel?

• Assumptions:– Haploid (phased), infinite genomes– All segments can be detected– Coalescent with recombination– Recombination breaks a shared segment (B>>1)

𝑁→∞

𝑁→∞

B

Time(generations)

Present

g

g+1

𝑁→∞

Prob. 1-α

Coverage by IBD: Theory• Exact solution:

– Define and – Denote the average coverage as

• Limits:– For (small reference panel, wide bottleneck), – For , – For (short length cutoff, recent bottleneck), – For ,

• Approximation:

– , – Fits very well numerically

• Diploids:

Demographic History of AJ &

Europeans

Recent AJ History Using IBD

• Assume a population of historical size diploids– Time scaled by 2N0

• Fraction of the genome in segments of length :Palamara et al., AJHG 2012

• Detect IBD in sample Infer history

Ancient History, One Population at a Time

• Fit the allele frequency spectrum, computed using diffusion• (∂a∂I, Gutenkunst et al., PLoS Genetics, 2009)

A Consequence

• Number of segregating sites Sn(t) – Zivkovic and Stephan, Theor. Pop. Biol. 2011

• n: #diploid samples; θ=4N0μ; μ: mutation rate per generation

Principal Component Analysis

Ancient History

What we know/learned so far:• AJ are a Middle-Eastern:European mix• Slightly higher heterozygosity (+2.4%)

– Larger ancient population size– Admixture– Recent explosive growth

• Many more AJ-specific variants – +14% for 25x25 genomes

• Out-of-Africa (Henn et al., PNAS, 2012)

– ≈50-60 kya– Serial founder model: Africa → Middle-East → Europe– Hunter-gatherers in Europe at ≈40-45 kya (Higham et al., Nature, 2011)

– Bottleneck and expansion at each step

The Joint AFS

• Allele frequencies correlated but substructure exists.

• Experimenting with inference using the joint AFS— For our sample size, can infer at

most ≈10 parameters— Hard to infer very recent history— Hard to infer migration rates

A Proposed ModelTime

Present

N0

Nb,OOA

Nf,AJ

Tb,OOA

Nb,EU

Nf,EU

Tb,EU

Tafa

Flemish AJ

The Inferred Model

Time(years ago)

Present

6500

230052,000

1800

58,000

10,800

170055%

Flemish AJ

7500

Out-of-Africa?

Early Neolithic migrants?

Jewish diaspora?

Middle-East/Levant?

European OriginsFarming began in Europe ≈5-8kya (“the Neolithic revolution”)

Spread of ideas (“cultural diffusion”)

Human migration(“demic diffusion”)

• For cultural diffusion, split from Middle-Easterners at ≈40-45 kya.

• We estimate ≈11 kya• Earlier than ≈5-8 kya perhaps due to

• Early substructure before actual migration• Incomplete replacement of hunter-gatherers• Traces of recovery from the Last Glacial Maximum

Confidence Intervals

Parameter Maximum likelihood

Bias-corrected mean±SD

95% confidence interval

6543 6523 25± [6475 , 6572]2256 2314 47± [2223 , 2406]

53,050 52,007 1561± [48,947 , 55,067]7632 7494 193± [7116 , 7872]1556 1802 28± [1748 , 1857]

10,600 10,835 188± [10,467 , 11202]56,519 57,977 2912± [52,270 , 63,685]1940 1686 98± [1495 , 1878]55% 55% 1%± [53% , 57%]

• Parametric bootstrap: o Simulate whole genomes with the maximum likelihood parameters

o MaCS, Chen et al., Genome Res., 2009o Infer using the simulated datasets

Hmmm…

Mutation rate

Model specification

Mutation Rate

• We used per bp per generation: the “phylogenetic rate”.• The “de-novo rate” is , and would double all population sizes and times.• We preferred the phylogenetic rate for a few (weak) reasons

– False negatives may exist in some de-novo studies– The de-novo rate does not account for selection– With the de-novo rate, the Out-of-Africa time would be >100 kya

• A decrease of 50% in the mutation rate will bring the split time to ≈16 kya– Support the LGM recovery hypothesis– Identify the Middle-East as the source of the recovery

• (Haber et al, PLoS Genetics, 2013; Pala et al., AJHG 2012)

– Still suggests genetic discontinuity from first hunter-gatherers who colonized Europe

• Debate is still open

Model SpecificationWe tried several alternative models• All models support >50% European ancestry in AJ and European-Middle-Eastern

split 10-15 kya.• For example, a two-wave model for the population of Europe supports LGM

recovery + Neolithic replacement:

Summary & Outlook• We sequenced 128 healthy AJ genomes to high coverage.

• Our reference panel will improve:– Screening of AJ clinical genomes or known disease genes– Imputation of AJ SNP arrays

• IBD sharing indicates a very recent bottleneck and expansion.

• The AJ-European joint allele frequency spectrum suggests:– Over 50% European ancestry in AJ– Europeans diverged from Middle-Easterners only ≈10-15 kya– Made possible by sequencing population with partly Middle-Eastern ancestry

• In the future:– Sequence ≈200 more genomes to cover entire bottleneck– Use genomes from more populations to fine-tune demographic models

Thank you!TAGC consortium members:Columbia University Computer Science:Itsik Pe’erFillan Grady, Ethan Kochav, James XueShlomo HershkopLong-Island Jewish Medical Center:Todd Lencz, Semanti Mukherjee, Saurav GuhaColumbia University Medical Center:Lorraine Clark, Xinmin LiuAlbert Einstein College of Medicine:Gil Atzmon, Harry Ostrer, Nir Barzilai, Kinnari Upadhyay, Danny Ben-AvrahamMount Sinai School of Medicine:Inga Peter, Laurie OzeliusMemorial Sloan Kettering Cancer Center:Ken Offit, Joseph Vijai Yale School of Medicine:Judy Cho, Ken Hui, Monica BowenThe Hebrew University of Jerusalem:Ariel Darvasi

Funding:Human Frontiers Science program

VIB, Gent, BelgiumHerwig Van Marck, Stephane PlaisanceComplete GenomicsOmicia

AJ Genetics

2,300

N

t

Effective size

45,000270

4,300,000

Years ago

800

PresentPalamara et al., AJHG 2012

0%

20%

40%

60%

80%

100%

0 50 100 150 200 250 300 350 400 450 500

# of Sequenced Individuals

% A

dditi

onal

Info

rmati

on P

oten

tial

WTCCC AJ_SCZ AJUK

Pow

er o

f im

puta

tion

by IB

D

Complete Genomics WGS

Quality Control

Property Genome (exome)Coverage ≈56x

Fraction called 96.7±0.3% (98.1%)Fraction with coverage > 20x 92.7±1.6% (94.9%)Concordance with SNP array 99.67±0.25%

Ti/Tv ratio 2.14±0.004 (3.05)

Ti/T

v

• 128 samples from two labs were sequenced in 3 batches• Minimal batch effects

• Some results are for the first batch of 57 genomes

Quality Control• False positive rate assessment

— Counting (the few) hets inside long runs of homozygosity— A duplicate sample

• Genome wide extrapolation: – SNVs: ≈10-40k FP per genome (FDR: 0.3-1.3%)– Indels: ≈10-30k FP per genome (FDR: 2-6%)

• QC: – Remove indels and poly-allelic variants– Remove HWE violations, low call rate

• FP after QC: ≈5k per genome.

hets

roh

Concordance with Arrays

0.05%Asymptotic discordance

Processing and Cleaning Pipeline

58 Complete Genomics masterVar (hg19)

AJ

VCF file

CGA tools mkvcf

Remove low-quality, half-called, or non-SNVs Remove variants not fully called in at least one individual

Remove inbred individual

Custom script; Plink/Seq

Remove poly-alleleic variantsRemove variants with high no-call rate or that are

not in Hardy-Weinberg equilibrium

Cohort-based cleaning

Plink file

Local cleaning

26 Complete Genomics masterVar (hg18)

Flemish

testvariants file

CGA tools

Liftover hg18 => hg19Remove low-quality, half-called, or non-SNVs

Remove variants not fully called in at least one individual

Cohort-based cleaning

Plink file

Local cleaning

VCF file

Custom script

Remove coordinates with reference mapping problemRemove variants with AJ-Flemish incompatible alleles

Initial filtering

Variant in both cleaned files?

Keep

Variant in one cleaned file and in

the VCF of the other?

Discard

Variant in one cleaned file and not

at all in other?

Keep and set other as hom-ref

Merge AJ-Flemish genotypes

Remove variants incompatible with 1000 Genomes

Phase and impute sporadically missing genotypes

SHAPEIT; using 1000 Genomes panel

Phase using molecular phasing

information

seqphase

128 Complete Genomics masterVar (hg19)

AJ complete project

testvariants file

CGA tools

Remove low-quality, half-called, or non-SNVs Remove variants not fully called in at least one individual

Remove poly-alleleic variantsRemove variants with high no-call rate or that are

not in Hardy-Weinberg equilibrium

Cohort-based cleaning

Plink file

Local cleaning Custom script

Phase and impute sporadically missing values

Validate AJ ancestryValidate no cryptic relatedness

Summary stats, array concordance, and

duplicates analyses

Ti/Tv statistics

Monomorphicnon-ref and

runs-of-homozygosity

analyses

SHAPEIT

Mobile Element Insertions (MEIs) & Copy Number Variants (CNVs)

Initial validation efforts suggested high false discovery rate, at least for novel events.

Novel MEIs: • 3/11 validated• Strong batch effect1000 Genomes MEIs

Variant StatisticsStatistic Per genome (exome)

Total SNPs 3.4M (22k)

Novel SNPs 3.8% (4.1%)

Het/hom ratio 1.65 (1.67)

Insertions count 220k (242)

Deletions count 235k (223)

Substitutions count 83k (374)

Synonymous SNPs 10,536

Non-synonymous SNPs 9706

Nonsense SNPs 72

Other disrupting 255

CNV count 302

SV count 1480

MEI count 4090

Imputing AJ ArraysCompare imputation accuracy of AJ SNP arrays when using either AJ or European reference panels.

AJ Arrays (1000) Phased AJ Sequences (57)

7

1000 Genomes CEU (87)

AJ arrays (1007) Reference

Panel 1 (50)Reference

Panel 2 (87)Reference

Panel 3 (137)

Study Panel (1007)

Phase (ShapeIT)

Imputed Study Panel 1

Imputed Study Panel 2

Imputed Study Panel 3

87 87Reduce to unphased arrays1000 50 50

Impute (Impute2)

Mutation Burden in AJ• Theoretically, a narrow bottleneck should increase the load of

deleterious variants (e.g., Lohmuller, Nature, 2008)o Or not? (Simons et al., arXiv, 2013)o Expect higher load in AJ.

• Define deleterious:o Derived? Minor? Non-reference? Rare?o How to weight each variant?o Account for demography, sequencing errors? o Define significance?

• Compare 26 AJ and 26 Flemish.

• AJ have between 1-10% more deleterious variants than expected (using Flemish as baseline). P-values between 0.2 and 10-60.

Mutation Burden in Disease Categories• Many diseases have been

suggested to be more prevalent in AJ (Goodman 1979)o Several Mendelian disorderso Some cancerso Inflammatory bowel diseaseso Diabetes, obesityo Some psychiatric diseases, myopia

• Annotate genes according to disease category (Omicia Inc).

• Compare non-synonymous variant load between AJ and Flemish.

Disease category #genes AJ/FL ratio

Aging 106 1.07Infectious 70 1.03Neonatal 956 1.02

Gastrointestinal 254 1.02Dental 86 1.01

Immunological 474 1.01Hemic 202 1.01

Cardiovascular 502 1.01Endocrinological 750 1.01

Oncological 471 1.01Women’s 39 1.00

Drug 82 1.00Neurological 980 1.00

Nutrition 29 0.99Respiratory 187 0.99

Kidney 285 0.96Psychiatric 21 0.93

• No category comes out significant in Gene Set Enrichment Analysis.

AJ EU

IBD observed

Het/Hom Ratiot

Years ago

Present