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Overview of SNP Genotyping
Debbie Nickerson
Department of Genome Sciences
University of Washington
[email protected]
SNP Genotyping - Overview
• Project Rationale
• Genotyping Strategies/Technical Leaps
• Data Management/Quality Control
SNP Project Rationale
• Heritability
• Power - Number of Individuals
• Number of SNPs -
Candidate Gene, Pathway or other, Genome-wide
5-10 SNPs, 96 to 1,500, 500K to 1 million
• DNA requirements
• Cost
SNP Genotyping
Matched
Probe and Target
C Allele
Mis-Matched
T Allele
C
Allele-Specific Hybridization
C
G
C
Target
Hyb ridiz e
C
Target
Taqman
C
G
Deg rade
+ddCTP
Polymerase Extension
Target
Oligonucleotide
C
Target
Ligation
A
Fail t o hybridize
Eclipse
Dash
Molecular Beacon
Affymetrix
C
A
Fail t o deg rade
C
G
A
C inco rporat ed
C Fails t o incorporat e
C
G
A
Ligat e
Fail t o ligat e
Sequenom
Ilumina - Infinium
SNPlex
Parallele
Illumina
Golden-Gate
Bead Express
SNP Typing Formats
Scale
Microtiter
Plates - Fluorescence
Single SNP
eg. Taqman - Good for a few markers - lots of
samples - PCR prior to genotyping
Size Analysis by Electrophoresis or
Mass Analysis
24-96 SNPs
eg. SNPlex - Multiplexing reduces costs - Genotype
directly on genomic DNA - new paradigm
for high throughput
Arrays - Custom or Universal
eg. Illumina, Affymetrics - Highly multiplexed
- hundreds, thousands, millions
96 - 1 M
Defining the scale of the genotyping project is key to selecting
an approach:
1000 individuals
5 to 10 SNPs in a candidate gene - Many approaches
(expensive ~ 0.60 per SNP/genotype)
96 SNPs in a handful of candidate genes
(~ 0.10 per SNP/genotype)
384 - 1,536 SNPs - cost reductions based on scale
(~0.08 - 0.15 per SNP/genotype)
500,000 to 1,000,000 SNPs defined format
(~0.002 per SNP/ genotype)
7,600-60,000 SNPs - defined and custom formats -> 1,152 samples
(~0.002 to 0.02 per SNP/genotype)
$6,000
$~10-30,000
$57,600-122,880
$350,000 -650,000
$>190,000
Many Approaches to Genotype a Handful of SNPs
PCR region prior to SNP genotyping - Adds to cost
- Many use modified primers - the more modified,
the higher the cost
• Taqman *
• Single base extension - Sequenom - Mass Spec
Illumina - Infinium
• Eclipse
• Dash
• Molecular Beacons
Taqman
Genotyping with fluorescence-based homogenous assays
(single-tube assay) = 1 SNP/ tube
SNP 1252 - T
Genotype Calling - Cluster Analysis
SNP 1252 - C
Genotyping by Mass Spectrometry - 24 SNPs
Technological Leap - No advance PCR
Universal PCR after preparing multiple regions for analysis Several based on primer specific on genomic DNA followed by
PCR of the ligated products - different strategies
and different readouts.
SNPlex (ABI), Illumina (Bead Express, Golden-Gate),
Affymetrix
Also, Genome-wide: Reduced representation - Affymetrix
Whole Genome Amplification - Illumina
SNPlex Assay - 48 SNPs
Allele Specific Sequence
ZipCode1
Universal PCR Priming site
A
G
Genomic
DNATarget
P
Locus Specific Sequence
ZipCode2
C
1. Ligation
P
A
G
C
Ligation Product Formed
(Homozygote shown in this case)
2. Clean-up
PCR & ZipChute Hybridization
3. Multiplexed Universal PCR
Univ. PCR Primer
Biotin
Univ. PCR Primer
4. Capture double stranded DNA- microtiter plate
(Streptavidin)
5. Denature double stranded DNA
6. Wash away one strand
7. Zip Chute Hybridization
•
Detection
9. Characterize on Capillary Sequencer
SNP 1
SNP 2
SNPlex Readout
ZipChuten
N(n)
T
Position n
n ~ 48/lane
~2000 lanes/day
Zipchute3
NNN
T
Position 3
Zipchute2
NN
A
Position 2
Zipchute1
N
C
Position 1
~96,000 genotypes/day
Multiplexed Genotyping
C
- Universal Tag Readouts
G
A
T
Locus 2 Specif ic Sequence
Locus 1 Specific Sequence
Tag1 sequence
Tag2 sequence
cTag1 sequence
cTag2 sequence
Subst rat e
Bead or Chip
Subst rat e
Bead or Chip
Bead Array
Chip Array
Tag 1
Tag 2
Tag 3
Tag 4
Illumina
Multiplex ~96 - 60,000 SNPs
Not dependent on primary PCR
Affymetrix
Arrays - High Density Genotyping
Thousands of SNPs and Beyond
• “Bead” Arrays - Illumina
– Manufactured by self-assembly
– Beads identified by decoding
Sentrix™ Platform
Sentrix™ 96 Multi-array Matrix matches standard
microtiter plates (96 - 1536 SNPs/well)
Up to ~140,000 assays per matrix
Fluorescent Image of BeadArray
~ 3 micron diameter
beads
~ 5 micron center-tocenter
~50,000 features on
~1.5 mm diameter
bundle
Currently: up to 1,536
SNPs genotyped per
bundle - at least 30
beads per code - many
internal replicates
Illumina Assay - 3 Primers per SNP
Universal forward
Sequences (1, 2)
5’
3’
G
(1-20 nt gap)
A
Allele specific
Sequence
5’
Locus specific
Sequence
C
T
SNP
Genomic DNA template
Universal reverse
sequence
3’
Illumicode ™
Sequence tag
Allele-Specific Extension and Ligation
Polymerase
Genomic DNA
Allele Specific
Extension &
Ligation
[T/C]
Universal
PCR Sequence 1
Universal
PCR Sequence 2
A
G
Ligase
[T/A]
illumiCode’ Address
Universal
PCR Sequence 3’
GoldenGate™ Assay
Amplification
A
Amplification
Template
PCR with
Common
Primers
Cy3 Universal
Primer 1
Cy5 Universal
Primer 2
illumiCode #561
Universal
Primer P3
Hybridization to Universal IllumiCodeTM
A/A
illumiCode
#1024
/\/\/\/
/\/\/\/
illumiCode
#217
T/T
/\/\/\/
illumiCode
#561
C/T
BeadArray Reader
•
•
•
Confocal laser scanning system
Resolution, 0.8 micron
Two lasers 532, 635 nm
– Supports Cy3 & Cy5 imaging
•
Sentrix Arrays (96 bundle) and
Slides for 100k fixed formats
Process Controls
Mismatch
High AT/GC
Gender
Gap
First Hyb
Second Hyb
Contamination
Illumina Readout for Sentrix Array
> 1,000 SNPs Assayed on 96 Samples
Genotyping for Whole Genome Association Studies
• Rapid Advances in Whole Genome Platforms
• Significant Content Improvements
now 1 million SNP chips are the standard
• Increasing coverage of multiple populations
• Decreasing costs
• Some drop in content when populations beyond the
HapMap are genotyped
DeBakker et al Nat. Genet. 38: 1298, 2006
Conrad et al Nat. Genet. 38: 1251, 2006
Genotyping Systems
Illumina
Affymetrix
100,000 or 500,000 Quasi-Random SNPs
100,000, 317,000, 550,000, 650,000Y SNPs
1 Million Products are here!
A significant proportion of common SNPs can be captured
Affymetrix’s GeneChip
Cut Genome
with restriction
enzymes
Isolate subset
of the DNA
by PCR
Generate chip
with probes
for SNPs in
this subset
Affymetrix GeneChip - 500k Assay
250 ng genomic DNA
Nsp
Nsp
Nsp
Restriction
Enzyme
Digestion
PCR: One Primer
Amplification
Adaptor
Ligation
Complexity
Reduction
Fragmentation
and Labeling
Hyb & Wash
AA BB AB
Matsuzaki et al, Genome Research, 2004
Matsuzaki et al, Nature Methods, 2004
Illumina Process
GENOMIC DNA 750ng
TT
TC
WGA
CC
UNLABELED
DNA
HYBRIDIZATION
ddNTP
FRAGMENT DNA
ALLELE DETECTION
THROUGH
SINGLE BASE EXTENSION
Illumina Infinium II Technology
(whole genome amplified DNA)
T
SNP1
A-DNP
A-DNP
SNP1
SNP2
C-Bio
SNP2
-----
SNP3
C-Bio
C-Bio
SNP3
SNP
A-DNP
- - - - - SNP
Illumina Bead Chip
Infinium II - Two-color assay
LD-based coverage of Sequence Variation
MAF > 0.05
Whole Genome Association Studies of Complex Traits
Many Advantages
–Detects common variation with small genetic contributions such as those
in complex disease traits - where multiple genes are involved
–Association defines a relatively small region (with hopefully one or few genes)
–Does not require a priori knowledge of what genes or regions are involved
Caveats
–Requires thousands of samples to find a significant association
–Extremely large datasets are generated (e.g., 2000 samples X
500,000 loci or more than 1 billion genotypes)
– This is just the Start - Analysis and Replication Strategies Are Key
The Hope
The identified targets will lead to new biological and medical Insights
and translate into new and improved treatments for common human diseases
Applying Genome Variation - Will it work? YES!!
Hits:
Macular Degeneration, Obesity, Cardiac Repolarization,
Inflammatory Bowel Disease, Diabetes T1 and T2, Coronary Artery
Disease, Rheumatoid Arthritis, Breast Cancer, Colon Cancer, Asthma
……
- There are misses as well; unclear why - phenotype, coverage,
environmental contexts?
Example of a miss - Hypertension
-There are lots more hits in these data sets - sample size, low
proxy coverage with other SNPs …..
- Analysis of associations between phenotype(s,) and even individual
sites is daunting, and this will just be the first stage, and this does even
consider multi-site interactions.
Genome-wide Tour de force Nature 447: 661-678
Read all the
supplemental
materials too!
Overview of Sample Processing and Analysis - WTCCC
Data Quality Control
•
•
•
•
Estimating Error Rates
Hardy Weinberg Equilibrium
Frequency Analysis
Missing Data
Measuring Error Rates
• Genotype replicate
samples - sentinel
sample
• Error rates generally <
<1%
• Error rates are usually
SNP specific
Rep 1
Rep 2
CC
CT
TT
CC
CT
TT
24
0
0
1
50
0
0
0
25
Measuring Error Rates
• Genotype replicate
samples
• Absolute number of
replicates is more important
than percentage
– E.g. 1 or 2
samples/plate
– HapMap OK - sentinel
samples
Rep 1
Rep 2
CC
CT
TT
CC
CT
TT
24
0
0
1
50
0
0
0
25
Replicate samples
• Replicates can also
detect sample handling
errors
– Wrong plate
– Plate rotation
Sample Handling Errors
• Sexing samples
• Other known
genotypes
– Blood type
– HLA
– Etc.
Hardy Weinberg Equilibrium
• Given
– p = Allele 1 frequency
– q = 1-p
• Expectations
– p2 = frequency 11
– 2pq = frequency 12
– q2 = frequency 22
Hardy Weinberg Disequilibrium
• Heterozygote excess
– Biologic
• Differential survival
– Technical
• Nonspecific assays
Duplicated regions
• Homozygote excess
– Biologic
• Population stratification
• Null allele
– Technical
• Allele dropout
Frequency and LD Analysis
tagSNP Allele Frequency
100%
IGAP
80%
60%
40%
White
European
Black
African
20%
0%
0%
20%
40%
60%
80%
100%
PGA
• Check Allele frequencies and LD against HapMap
HWE Departures - Eliminate SNPs Lots of reasons - Poor genotyping, or Copy
Number Variants
Analysis of Genotypes - Good, Bad and Ugly
Population Stratification - Observed in UK
Q-Q Plots (Observed vs Expected) Exploring Outilers
WTCCC - The Hits and Misses
Comparing Hits to Documented Associations to Specific Diseases
New Associations Uncovered
Replication A Must
Replication
Replication
Replication
Hirschhorn & Daly Nat. Genet. Rev. 6: 95, 2005
NCI-NHGRI Working Group on Replication Nature 447: 655, 2007
Replication on Custom Arrays
Affymetrix MIP Technology
20,000
Molecular Inversion Probes (MIP)
Affymetrix’s Chip
Custom Illumina Platform - iSelect
• 12 samples/slide
• Each section can be used to
genotype one individual from 7,600 60,000 SNPs
Individual
sample
GWAS - CAD First report
WTCCC Second
New Variation to Consider - Structural Variation
Types of Structural Variants
Insertions/Deletions
Inversions
Duplications
Translocations
Size:
Large-scale (>100 kb)
intermediate-scale (500 bp–100 kb)
Fine-scale (1–500 bp)
More than 10% of
the genome
sequence
Nature 447: 161-165, 2007
Detection of Outliers of the Distribution
X-linked SNP
Unknown SNP
Carlson et al, Hum. Mol. Genet. 15: 1931-1937, 2006
Structural Variation - Large Insertion-Deletion Events
Structural Variants Identified in the HapMap
• Conrad, et al. (Nature Genetics 38:75-81, 2006)
• Hinds, et al. (Nature Genetics 38:82-85, 2006)
• McCarroll, et al. (Nature Genetics 38:86-92, 2006)
Nearly 4,000 now known
Genetic Strategy - New Insights
STRONG
LINKAGE
effect
size
ASSOCIATION
Common Disease
Many Rare Variants
??
WEAK
LOW
allele frequency
HIGH
Ardlie, Kruglyak & Seielstad (2002) Nat. Genet. Rev. 3: 299-309
Zondervan & Cardon (2004) Nat. Genet. Rev. 5: 89-100
Individuals
Sequencing Known Candidate Genes for Functional Variation
From Individuals at the Tails of the Trait Distribution
Low HDL
High HDL
High Density Lipoprotein (HDL)
ABCA1 and HDL-C
–Cohen et al, Science
305, 869-872, 2004
Many examples emerging
Common Disease
Rare Variants
• Observed excess of rare, nonsynonymous variants in low HDL-C
samples at ABCA1
• Demonstrated functional relevance in cell culture
Personalized Human Genome Sequencing
Solexa - an example
Genotyping Summary
• HapMap - the spectrum of common variation
• New Genotyping Platforms - Not perfect but successful
• Uncovering Many Associations - Many regions underlying common
disease associations uncovered - WTCC as a paradigm
• Stratification is being uncovered on many levels - within and between
populations and these generate artificial associations
• Replication is a must to explore genome-wide associations
• New technologies for replication on large-scale
• New variants and sequencing technologies emerging