genome-wide associations
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Genome-wide Associations
Lakshmi K Matukumalli
Illumina SNP Genotyping
Chemistry
Genotype Data
Fine Mapping with SNP Markers
Advantages of SNPs as genetic markersas compared to microsatellites.
•High abundance
•Distribution throughout the genome
•Ease of genotyping
•Improved accuracy
•Availability of high throughput
multiplex genotyping platforms
Objectives for GWA
Create Cures for Diseases (Humans) Localize diseases to narrow chromosomal regions Identify causative mutations for disease Genetic predisposition to drugs / diseases Personalized medicine
Selection Decisions (Live stock & Plants) Increased productivity, disease resistance, composition
(Fat, protein, tenderness) Identification of QTL regions Application of Marker assisted selection Genome Selection
QTL
LINKAGE MAPPINGWhere genes are mapped by typing genetic markers in families to identify regions that are associated with disease or trait values within pedigrees more often than are expected by chance. Such linked regions are more likely to contain a causal genetic variant.
ADMIXTURE MAPPINGPredicting the recent ancestry of chromosomal segments across the genome to identify regions for which recent ancestry in a particular population correlates with disease or trait values. Such regions are more likely to contain causal variants that are more common in the ancestral population.
PENETRANCEThe proportion of individuals with a specific genotype who manifest the genotype at the phenotypic level. For example, if all individuals with a specific disease genotype show the disease phenotype, then the genotype is said to be 'completely penetrant'.
HERITABILITYThe proportion of the variation in a given characteristic or state that can be attributed to (additive) genetic factors.
Traditional Methods
Common
Ancestor
Emergence of Variations Over Time
time present
Linkage Mapping
Non-Parametric Linkage
Transmission Disequilibrium Test (TDT)
Principles
• Fisher’s theory of additive effects of common alleles
* Human heterozygosity is attributed to common ancestral variants (CDCV Common disease common variant hypothesis)
* Variants influencing common late onset diseases of modernity may not have been subject to purifying selection
Genome Wide Association
Whole Genome Prediction
Fit haplotype block into a statistical model:
Effect A B C D E F G H I J K L M
Levels1
3
4
3
1
3
4
1
3
4
1
3
1
3
4
1 1
3 3
1
3
1
2
3
1 1 1
2 2 2 2 22 2 2 22 2 2
1 1
2
Genome Enhanced PBVBlock
GEPBVHaplotype A B C D
1 +0.01 +1.03 -1.23 +6.35
2 +0.06 -0.74 +0.98 +2.19
3 +0.05
4 -8.59
Animal 1
1 1 1 2 2 2 1 3
0.01
+0.01
1.03
-0.74
0.98
+0.98
6.35
+0.05 8.67
Animal 2
2 2 1 1 2 2 2 4
0.06
+0.06
1.03
+1.03
0.98
+0.98
2.19
-8.59 -2.26
a. Gene centric approachb. Non-ascertained (Uniformly spaced / Tag SNPs)
Genome Wide Association - Methods
Age-Related Macular Degeneration
Complement Factor H Polymorphism
Samples
1,464 Patients T2D
1,464 Case Controls
Traits
Glucose metabolism
Lipids
Obesity
Blood pressure
Follow-up
107 SNPs on extreme p-values genotyped on 10, 850 additional populations
Type 2 diabetes and triglyceride levels
T2D
•non-coding region near CDKN2A and CDKN2B
•Intron of IGF2BP2
•Intron of CDKAL1
Triglycerides
Intron of glucokinase regulatory protein
Coronary Heart Disease
375,00 SNPs
WTCCC
1926 Case
2938 Controls
German GI Family
875 Case
1644 Control
Genotyping by candidate gene approach
Significant Associations
9p21.3 regionP=1.80 x 10(-14) WTCCCP=3.40 x 10(-6), German MI Family.
The WTCCC study revealed nine loci that were strongly associated with coronary artery disease (P<1.2 x 10(-5)) and less than a 50% chance of being falsely positive). Two additional loci at 6q25.1 and 2q36.3 were also successfully replicated in the German study:
The combined analysis of the two studies identified four additional loci significantly associated with coronary artery disease (P<1.3 x 10(-6))) and a high probability (>80%) of a true association: chromosomes 1p13.3, 1q41, 10q11.21, and 15q22.33.
GWA of seven Common Diseases
14,000 Cases (2,000 each)
3,000 shared controls
Determining Marker Order
Chromosome segments
Clones
Genotyping
A BC D E F G
Neutral Evolution Versus
Positive Natural Selectionhttp://ai.stanford.edu/~serafim/CS374_2006/
presentations/lecture5.ppt
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