# Presentation: 335279

## Population genetics / genomics subgroup:

- SNP discovery and haplotype analysis

***BPC3***

- David Altshuler MD, PhD
*Director, Program in Medical and Population Genetics*
- Broad Institute of Harvard and MIT
- Massachusetts General Hospital  and Harvard Medical School

## Overall approach

- Systematically test variants for a role in breast and prostate cancer

**Discover**
**potential **
**causal variants**

**Measure **
**frequencies **
**in patients **
**and controls**

**Statistical **
**analysis**

- Sequence exons and haplotype analysis

- Asking which are characteristic of patients with cancer

- Integrating genetic information with environmental and clinical data

## BPC3: population genetics goals

*A two pronged approach to capturing genetic variation*
- Directly discover putative causal variants
- “rare, heterogeneous coding variant” hypothesis
- Systematically test common variation without assumption causal variants are coding, using LD
- “common variant hypothesis” (coding or regulatory)

## Goals: sequencing & discovery

- In each gene, sequence all coding exons in DNA from 192 advanced cancer cases
- For each site, 19 from each of 5 ethnic groups
- Genotype common SNPs at high density across each locus, capturing variation at non-coding sites
- 384 samples from CEPH european sample
- 384 samples from CEPH diversity sample
- 270 HapMap samples

## Shared ancestry across regions

## Linkage disequilibrium patterns

- Recombination hotspots: McVean et al, Science 2004

- Pairwise LD: red is strong D’ and LOD > 3.0

*Daly et al, Nature Genetics 2001*
*Gabriel et al, Science, 2002*

## A dense SNP map provides excellent 

*Gabriel et al, Science 2002; HapMap ENCODE Project www.hapmap.org*

- A dense SNP map provides excellent
- power and completeness for common variants

- Block-based

- Block-agnostic

## BPC3 Division of labor

- Broad Institute: 30 genes*, 220 coding exons
- CEPH: 24 genes, 175 coding exons
- NCI: 6 genes*, 49 exons, 309 kb span
- * In addition to original proposal, six genes were added by Broad Institute / USC group, and six genes by NCI / Chanock

## Progress to date

- In total, 560 targets sequenced to date in each of 190 advanced cancer case DNAs
- In total, 3,248 SNPs have been genotyped in the reference samples
- Able to increase marker density using new technology (Illumina at Broad Institute)

## Using this data to select the best markers to type in cancer samples

- Enable selection of the best markers to type in the cancer cohorts
- Partnership of population genetics group and the biostatistics group of BPC3
- Make it possible to evaluate methods and develop best practices more generally

## Data release

- All genotype data on public website, including SNPs found by resequencing
- Where public databases exist (dbSNP, CEPH, HapMap, SNP500, etc), deposit all genotypes for integration with other data

## Future directions

## International Haplotype Map Project

*Goal:  a genome-wide, public database of genotype data to guide selection of efficient and powerful “tag” SNPs for association studies*
*Currently: **	**genotypes for 1.2M markers available in 270 individuals*
*By 2005: **	**genotypes for 6M markers available in 270 individuals*

- http://www.hapmap.org

## Using BPC3 data to evaluate the utility of HapMap for cancer cohort research

- best possible: ~90% @ *r*2>.8, mean *r*2=0.93

- Based on data from BPC3, we have shown that HapMap information can be used to select markers for use in the cancer samples used by BPC3 with little loss of power

*Paul de Bakker, Mark Daly, Brian Henderson, Joel Hirschhorn, David Altshuler*

**Notes:**
When we pick tags with our multi-marker tests, we observe the predicted gain in efficiency albeit at a slight power loss.

## Decreasing cost, increasing throughput of SNP genotyping over time

- Increasing number of SNPs per reaction

## Summary

- Two-pronged approach to capture rare coding changes as well as common variants across entire gene locus
- Over 560 exons sequenced in 190 cases, and 3,000 SNPs genotyped to support cancer association studies
- Going forward, genome-wide resources make comprehensive genetic association studies practical