hapmap project

HapMap PROJECT

Basics

HapMap

• The International HapMap Project is analyzing DNA from populations with African, Asian, and European ancestry

Multiple Populations

• The DNA samples for the HapMap have come from a total of 270 people. – The Yoruba people of Ibadan, Nigeria, provided 30

sets of samples from two parents and an adult child (each such set is called a trio).

– In Japan, 45 unrelated individuals from the Tokyo area provided samples.

– In China, 45 unrelated individuals from Beijing provided samples.

– Thirty U.S. trios provided samples, which were collected in 1980 from U.S. residents with northern and western European ancestry by the Centre d'Etude du Polymorphisme Humain (CEPH).

Methods

• The blood samples are being converted into cell lines, DNA extracted.

• The samples and cell lines are not linked to any individual in the populations studied. However, the samples and cell lines are identified as coming from one of the four populations participating in the study, which raises ethical issues associated with conducting genetic research in named populations.

SNP Nomenclature

• http://snp500cancer.nci.nih.gov/terms_snp_region.cfm

Hardy Weinberg Test

• http://innateimmunity.net/IIPGA2/Bioinformatics/exacthweform

IIPGA

Exact HWE

Fishers Exact Test

Fishers Exact Test

Homework

http://www.hsph.harvard.edu/bioinfocore/Documents/Talk%20slides/Bioinfo_training_August_10_05_tutorial_Niu_T.pdf

SNPcutterhttp://bioinfo.bsd.uchicago.edu/SNP_cutter.htm

SNP and Cancer

• A SNP is defined as a genomic locus where two or more alternative bases occur with appreciable frequency (>1%).

• Occurs every several hundred bases.

• Whole genome SNP analysis is possible.

Applications

• Direct Association Analysis:– Test association between putative functional

variants and disease risk.• Evaluation of nonsynonymous SNPs or regulatory

polymorphisms = functional SNPs.• Problem: there are not that many functional SNPs.• Uncharacterized de novo mutations???

Examples

• 2 MMP9 nonsynonymous SNPs associated with risk of lung cancer with metastasis (Hu et al. 2005b)

• Coding polymorphisms within UGT1A7 predict response of colorectal patients to capecitabine (Carlini et al. 2005).

• Functional MTHFR mutations linked to several different cancers.

Direct Association

• Candidate gene or genomic region.– Linkage analysis– Expression array analysis– Knowledge of development and physiology– Comparative genomics

Tools

• PANTHER database- evolutionary analysis of coding SNPs.

• SNPEffect-estimate likelihood that a particular SNP is causing a functional effect.

• SNPSeek->90 000 coding SNPs in the exons of known genes

• SNP500Cancer – identification, validation, and characterization of polymorphisms.

PANTHERhttp://www.pantherdb.org/tools/csnpScoreForm.jsp

PANTHERhttp://www.pantherdb.org/tools/csnpScoreForm.jsp

PANTHER

ABCA1

PolyPhen

• http://genetics.bwh.harvard.edu/pph/

PolyPhen

• http://genetics.bwh.harvard.edu/pph/

SNPEffecthttp://snpeffect.vib.be/search.php

SNPSeek

Search for BRCA1

Search for BRCA1

Search for BRCA1

Search for BRCA1

SNP500 Cancer Database

SNP500 vs HDP

Test if SNP500 and HDP differ

Do subpopulations differ?

Compare Caucasion vs African

Compare Caucasian vs Hispanic

Test whether in HWE

HWE

HWE

TDT

TDT

HapMap

• Polymorphisms identified by HapMap are likely to be neural in phenotypic effect but can inform on nearby alleles that might play a role in disease.

Haplotype

• SNP alleles tend to be correlated together in a predictable way-known as haplotype.– The linear, LD ordered arrangement of alleles

on a chromosome

• The correlation between SNPs is mediated by linkage disequilibrium (LD).– LD exists when alleles at distinctive loci occur

together more frequently than expected given the known allele frequencies and recombination fraction between the loci.

Disease allele and haplotypes

• In the presence of LD, polymorphisms that are in physical proximity to a causal polymorphism will show a difference between cases and controls.

HapMap

• Three phases:I, II, III• I: completed in October 2005-genotyping

of 1M SNPs at average spacing of 5kb. An additional SNP finding in 48 samples from original populations across 10 specific 500kb ENCODE regions (represent a genome wide rage of evolutionary conservation and gene density). Later this was extended to 269 samples.

HapMap

• Phase II: 269 samples, 2.9 M SNPs were genotyped, a total of 3.9 M.

• Phase III: other populations will be added.

Results of Phase I and Phase II

• Intensity of SNP data across ENCODE regions 1SNP/279 bp.

• Intensity of phase II Hapmap 1SNP/kb

Robust measures of LD

• D’ and r2 are the two major measures of LD.

• D’, if two SNPs have not been separated by recombination during the history of the sample D’ is 1.

• R2 is the correlation between two SNPs; when two SNPs always observed together r2 is 1. Generally is a better measure.

Linkage Studies

• Family-based approaches to identify a disease gene.

• A disease gene segregates in a family, genomic markers in close proximity to the disease will segregate in the same manner due to lack of recombination.– Identify families with disease; genotype each

individual.– Compare the marker allele and disease distributions

within the family. Assign a LOD score.

Linkage studies

• Genome wide scans for linkage analysis performed using several hundred microsatellites at a 10cM density throughout genome.

• SNP-based linkage studies use a panel of 10000 SNPs.

Examples

• Multiple sclerosis

• Neonatal diabetes

• Familial glucocorticoid deficiency.