Polymorphism

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Polymorphism

• Haixu Tang
• School of Informatics

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Genome variations
underlie phenotypic differences
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Restriction fragment length polymorphism (RFLP)
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RFLP
Haplotype
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Microsattelite (short tandem repeats)
polymorphysim
7 repeats
8 repeats
the repeat region is variable between samples
while the flanking regions where PCR primers bind
are constant
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Which Suspect, A or B, cannot be excluded
from potential perpetrators of this assault?
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Single nucleotide polymorphism

• The highest possible dense polymorphism
• A SNP is defined as a single base change in a DNA
  sequence that occurs in a significant proportion
  (more than 1 percent) of a large population.

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Some Facts

• In human beings, 99.9 percent bases are same.
• Remaining 0.1 percent makes a person unique.
• Different attributes / characteristics / traits
• how a person looks,
• diseases he or she develops.
• These variations can be
• Harmless (change in phenotype)
• Harmful (diabetes, cancer, heart disease,
  Huntington's disease, and hemophilia )
• Latent (variations found in coding and regulatory
  regions, are not harmful on their own, and the
  change in each gene only becomes apparent under
  certain conditions e.g. susceptibility to lung
  cancer)

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SNP facts

• SNPs are found in
• coding and (mostly) noncoding regions.
• Occur with a very high frequency
• about 1 in 1000 bases to 1 in 100 to 300 bases.
• The abundance of SNPs and the ease with which
  they can be measured make these genetic
  variations significant.
• SNPs close to particular gene can acts as a
  marker for that gene.

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SNP maps

• Sequence genomes of a large number of people
• Compare the base sequences to discover SNPs.
• Generate a single map of the human genome
  containing all possible SNPs gt SNP maps

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How do we find sequence variations?
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Automated polymorphism discovery
Marth et al. Nature Genetics 1999
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Large SNP mining projects
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How to use markers to find disease?
genome-wide, dense SNP marker map

• genotyping using millions of markers
  simultaneously for an association study

• depends on the patterns of allelic association
  in the human genome

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Allelic association

• allelic association is the non-random assortment
  between alleles i.e. it measures how well
  knowledge of the allele state at one site permits
  prediction at another

functional site
marker site

• significant allelic association between a marker
  and a functional site permits localization
  (mapping) even without having the functional site
  in our collection

• by necessity, the strength of allelic
  association is measured between markers

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Linkage disequilibrium

• LD measures the deviation from random assortment
  of the alleles at a pair of polymorphic sites

• other measures of LD are derived from D, by e.g.
  normalizing according to allele frequencies (r2)

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Haplotype diversity

• the most useful multi-marker measures of
  associations are related to haplotype diversity

2n possible haplotypes
n markers
random assortment of alleles at different sites
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Haplotype blocks
Daly et al. Nature Genetics 2001

• experimental evidence for reduced haplotype
  diversity (mainly in European samples)

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The promise for medical genetics

• within blocks a small number of SNPs are
  sufficient to distinguish the few common
  haplotypes ? significant marker reduction is
  possible

CACTACCGA CACGACTAT TTGGCGTAT
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The HapMap initiative

• goal to map out human allele and association
  structure of at the kilobase scale

• deliverables a set of physical and
  informational reagents

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Haplotyping

• the problem the substrate for genotyping is
  diploid, genomic DNA phasing of alleles at
  multiple loci is in general not possible with
  certainty

• experimental methods of haplotype determination
  (single-chromosome isolation followed by
  whole-genome PCR amplification, radiation
  hybrids, somatic cell hybrids) are expensive and
  laborious

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A example of hyplotyping

• Mother GG AT CA TT
• Father CC AA AC CT
• Children GC AA CC CT
• Children GC AT AA TT
• Children GC AA AC CT

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Haplotypes

• a
  b
• Mother I G A C T G T A T
• II G T C T G A A
  T
• Father I C A A C C A C T
• II C A A T C A C
  C

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A example of hyplotyping

• Mother GG AT CA TT
• Father CC AA AC CT
• Children GC AA CC CT (M-Ia F-IIb)
• Children GC AT AA TT (M-Ib F-IIa)
• Children GC AA AC CT (M-Ia F-Ia
• or
  M-IIb F-IIb) ?

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HapMap Project
A freely-available public resource to increase
the power and efficiency of genetic association
studies to medical traits

• High-density SNP genotyping across the genome
  provides information about
• SNP validation, frequency, assay conditions
• correlation structure of alleles in the genome

All data is freely available on the web for
application in study design and analyses as
researchers see fit
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HapMap Samples

• 90 Yoruba individuals (30 parent-parent-offspring
  trios) from Ibadan, Nigeria (YRI)
• 90 individuals (30 trios) of European descent
  from Utah (CEU)
• 45 Han Chinese individuals from Beijing (CHB)
• 45 Japanese individuals from Tokyo (JPT)

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HapMap progress
PHASE I completed, described in Nature
paper 1,000,000 SNPs successfully typed in all
270 HapMap samples PHASE II data generation
complete, data released gt3,500,000 SNPs
typed in total !!!
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ENCODE-HAPMAP variation project

• Ten typical 500kb regions
• 48 samples sequenced
• All discovered SNPs (and any others in dbSNP)
  typed in all 270 HapMap samples
• Current data set 1 SNP every 279 bp

A much more complete variation resource by
which the genome-wide map can evaluated
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Tagging from HapMap

• Since HapMap describes the majority of common
  variation in the genome, choosing non-redundant
  sets of SNPs from HapMap offers considerable
  efficiency without power loss in association
  studies

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Pairwise tagging
Tags SNP 1 SNP 3 SNP 6 3 in total Test for
association SNP 1 SNP 3 SNP 6
After Carlson et al. (2004) AJHG 74106