1. The International Consortium. The International HapMap Project.
Nature. 426, (2003)

2. The International HapMap Project
Launched October 29, 2002
Major initiative to map human genetic variation based on haplotype patterns.
Characterize sequence variants, their frequencies, and correlations between them.
Serve as a key resource for finding genes that affect health, disease, and drug response.

3. Direct Approach: Laborious and Expensive
Whole genome sequencing of numerous patient samples to identify candidate variations
Test each variant for correlation with a disease.
Genotyping 3 million SNPs in 1000 people =
3 billion separate genotyping assays

4. Indirect Approach: Efficient and Comprehensive
Relatively small set of variants will capture most common variation patterns.
Linkage Disequilibrium (LD) in SNPs = few haplotypes in many chromosome regions
A set of sequence variants serve as genetic markers to detect association between a particular genomic region and disease.

5. HapMap
A few common haplotypes among many chromosome regions account for most of the variation in the human genome.
Human genome can be divided into 200,000 haplotype blocks.
Identify 200,000 to 1 million tag SNPs
Efficient and comprehensive

6. SNPs, Haplotypes, and Tag SNPs
Genotyping 3 tag SNPs out of 20 SNPs is sufficient to distinquish
one haplotype from another.

7. Haplotype Map: Search for genes on Chromosome 5
Related to Crohn’s Disease
Haplotype blocks contain 2-4 flavors of SNP combinations ( orange, purple, etc. )
Dashed lines indicate relationships between blocks
Percentages indicate occurrence of each SNP set in patients.

8. DNA Samples and Populations
Population Sampling: samples chosen from particular populations based on ethnicity and geography.
Ancestry Location Number of Samples
N & W European United States 90
African Ibadan, Nigeria 90 ( 30 trios )
Japanese Tokyo, Japan 45 ( unrelated )
Chinese Beijing, China 45 ( unrelated )
Include a substantial amount of genetic variation
Trios and unrelated individuals: local LD patterns.
Unrelated DNA samples: identify 99% of haplotypes, frequency of 5% or greater in a population

9. SNP Selection Priorities
High density of SNPs to adequately describe genetic variation
LD and haplotype density varies 100 fold across the genome.
Hierarchical strategy will allow regions of the genome with the least LD to be characterized with higher SNP density.
Priorities
Verified SNPs with available allele frequency and genotyping data
Double-hit SNPs seen twice in two different DNA samples
SNPs that cause amino acid changes

10. GENOTYPING
10 genotyping centers: Japan, UK, Canada, China, US, and Nigeria
5 high-throughput genotyping technologies
Performance criteria:
1. Data produced must be 99.2% complete & 99.5% accurate.
2. All experiments must include samples for internal quality checks.
3. Samples of SNP genotypes from each center re-genotyped by other centers.
Various platforms allow for comparisons for accuracy, success
rate, throughput, and cost.
Complete and reliable data production

11. DATA ANALYSIS Analyze LD between markers.
Measure proportion of common ancestral chromosomes that have not recombined
Sliding window LD profiles
LD unit maps
Haplotype blocks
Meiotic recombination rates
Statistical methods, replication studies, and functional analyses of variants – confirm the findings and identify functionally significant SNPs.