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Office hoursWednesday 3-4pm304A Stanley Hall

Fig. 11.26

Association mapping (qualitative)

Association scan, qualitative

43347G’s797141C’s

controlsosteoarthritisχ2 test

Association scan, quantitative

Association vs. linkage Association vs. linkage

Unrelatedindividuals (usually)

Relatedindividuals

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Association vs. linkage

Unrelatedindividuals (usually)

Relatedindividuals

Extreme of linkage study is one large family; lesslikely that phenotype has multiple genetic causes

(locus heterogeneity).


Strong, easy to detect

Unrelatedindividuals

Relatedindividuals


Strong, easy to detect,but rare in population


Relatedindividuals


Strong, easy to detect,but rare in population


Relatedindividuals

(e.g. BRCA1)


Strong, easy to detect,but rare in population;may not be reflective ofcommon disease.


Relatedindividuals


Strong, easy to detect,but rare in population;may not be reflective ofcommon disease.Also, hard to collect familydata.


Relatedindividuals

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Common but weakeffects


Relatedindividuals



Common but weakeffects; need 1000’sof samples to detect


Relatedindividuals



Common but weakeffects; need 1000’sof samples to detect.If no common cause,can fail.


Relatedindividuals

Another key feature ofassociation mapping:

resolution


manyrecombinationshave happenedsince commonancestor;shared regionis small; no co-inheritancebetweendistant markers

Association vs. linkagesmallnumber ofgenerations;individualsshare bigchunks ofgenome;can get co-inheritancebetweendistantmarkers


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So you need very high densityof markers to get signal in anassociation study, but you getvery high spatial resolution.



In the “old days” of sparsemarkers, linkage analysis was

the best strategy.

Causative variant very close

-log(χ

2 p-

valu

e)

rs377472

But there is a pitfall ofassociation tests: “population

structure”

Diabetes in Native Americans

(1971)

Diabetes in Native Americans

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(1971)

Family studiesindicate it is atleast partlygenetic, notenvironmental.

Diabetes in Native Americans Association mapping causal loci

Typed IgG heavy chains with protein assay.Phenotypes can serve as markers too…

Association mapping causal loci

Typed IgG heavy chains with protein assay.Phenotypes can serve as markers too…

(Multiple proteins from chr 14 region: haplotype)


32841343no Gm27023Gmcontroldiabetes




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“Gm is protective against diabetes?”


Self-identified heritage Self-identified heritageMost “full heritage”members don’t havethe haplotype

Self-identified heritageMost “full heritage”members don’t havethe haplotype

The few without N.A.heritage are muchmore likely to havethe haplotype

Gm haplotype is very rare inself-identified 100% Pima

members.

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Gm haplotype is very rare inself-identified 100% Pima

members.

Gm is a marker for Caucasian ancestry.

Association and admixture

Association and admixture Association and admixture

hugealmost negligible


these are all theCaucasians…

Association and admixtureGm doesn’t look like it hasmuch additional protective

effect if you stratify byfamilial origin first!

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Caucasian ancestry isassociated with Gm haplotype.


Caucasian ancestry isassociated with Gm haplotype.Caucasian ancestry isassociated with lower diabetesrisk.


Caucasian ancestry isassociated with Gm haplotype.Caucasian ancestry isassociated with lower diabetesrisk.But Gm is not associated withlower diabetes risk!


Cases

Controls

Controls are enriched for Caucasians


Cases

Controls

=

=

N.A. and Caucasians aredifferent at many loci

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Cases

Controls

=

=

At any one of these loci, Caucasian-like allele will beenriched in control samples.

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Cases

Controls

=

=

Don’t believe any one locus is causative!

Microarrays and genotyping

DNA microarrays

Fig. 10.21

DNA microarrays

Fig. 10.21

Post-genome era:the sequence andlocation of theoligos are known

DNA microarrays

Fig. 1.13

Genotyping by array

Fig. 11.8

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Genotyping by array

Fig. 11.10

Genotyping by array

Fig. 11.10

oligo (human genome fragment) index

Genotyping by array

Fig. 11.10


Genotyping by array

Fig. 11.10


Genotyping by array

Fig. 11.10


Genotyping by array

Fig. 11.10

middle nucleotide onchip oligo


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Genotyping by array

Fig. 11.10


Sample DNA is labeled, allowed to hybridize

Genotyping by array

Fig. 11.10

readout of sample


Genotyping by array

Fig. 11.10

readout of sample


Genotyping by array

Fabrication technology allows millions of oligos (eachpresent in millions of copies) on a single slide

Genotyping by single-baseextension

Fig. 11.11

Genotyping by single-baseextension

http://www.illumina.com/downloads/InfiniumIIWorkflow.pdf

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High density of markersnecessary for association

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