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Office hoursWednesday 3-4pm304A Stanley Hall
Review session5pm Thursday, Dec. 11
GPB100
Association vs. linkage
Strong, easy to detect,but rare in population;may not be reflective ofcommon disease.Also, hard to collect familydata.
Common but weakeffects; need 1000’sof samples to detect.If no common cause,can fail.
Unrelatedindividuals
Relatedindividuals
Association vs. linkagesmallnumber ofgenerations;individualsshare bigchunks ofgenome;can get co-inheritancebetweendistantmarkers
manyrecombinationshave happenedsince commonancestor;shared regionis small; no co-inheritancebetweendistant markers
So you need very high densityof markers to get signal in anassociation study, but you getvery high spatial resolution.
Association and admixture
Cases
Controls
=
=
At any one of these loci, Caucasian-like allele will beenriched in control samples.
Genotyping by array
Fig. 11.8
Expression microarrays
Fig. 1.13
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Labeled DNA sample vs.labeled mRNA (cDNA) sample
Labeled DNA sample vs.labeled mRNA (cDNA) sample
(reverse transcription in the test tube)
Coding sequence array
Fig. 1.13
Coding sequence array
Fig. 1.13
say, with chemotherapeutic
Coding sequence array
Fig. 1.13
Coding sequence array
Fig. 1.13
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Coding sequence array
Fig. 1.13
expression
expression
expressed
not expressed
Why measure expression ofall genes at once?
“Regulon” expression response
http://www.mcb.mcgill.ca/~hallett/GEP/Lecture2/Image17.gif
(e.g. cortisol)
“Regulon” expression response
http://www2.kenyon.edu/Depts/BioEllipse/courses/biol114/Chap06/week08a_files/regulon.gif
Finding regulatoryresponse on a large scale
Oligo expression array
transcripts
(soybean component)
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Expression profiles
Time since drug administered
Expression profiles
Time since drug administered
Time since drug administered
Expression profiles
Time since drug administered
Time since drug administered
Each color is aregulon, or“cluster,” of co-regulated genes
Expression effects of cancer
Cancer classification Cancer classification
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Histological classification isfinicky: can we do better?
Diagnosis via transcriptional profile
Diagnosis via transcriptional profile
transcripts
patient samples
Diagnosis via transcriptional profile
Diagnosis via transcriptional profile Natural variation among “normals”
Two human chromosomes differ at ~1/1000 bases.
96% of these differences are not in protein-coding sequence.Why?
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Two human chromosomes differ at ~1/1000 bases.
96% of these differences are not in protein-coding sequence.Most protein coding mutations are deleterious;appear but are culled by natural selection.
Natural variation among “normals” Natural variation among “normals”
Natural variation among “normals” Genetic variation in mRNA levels
ORFTFTF
G
kinaseTF
Genetic variation in mRNA levels
ORFTFTF
G
kinaseTF
Likely to be a complex trait.
Many mRNA differences at once
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Linkage mapping of mRNA levels
“Black 6” mouse x “DBA” mouse
Linkage mapping of mRNA levels
“Black 6” mouse x “DBA” mouse
~10% mRNA levels significantly different
Linkage mapping of mRNA levels
“Black 6” mouse x “DBA” mouse
111 F2 progeny
…
Linkage mapping of mRNA levels
“Black 6” mouse x “DBA” mouse
111 F2 progeny
Microarrayeach F2 liver
…
Linkage mapping of mRNA levels
“Black 6” mouse x “DBA” mouse
111 F2 progeny
Microarrayeach F2 liver
…
Genotypeeach F2
Linkage mapping of mRNA levels
“Black 6” mouse x “DBA” mouse
111 F2 progeny
Microarrayeach F2 liver
…
Genotypeeach F2
Looking for linkage (coinheritance) betweenmarker and mRNA level.
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Marker is linked to polymorphism inexpression regulation cascade
ORFTFTF
G
kinaseTF
Marker is linked to polymorphism inexpression regulation cascade
ORFTFTF
G
kinaseTF
G
G
Marker is linked to polymorphism inexpression regulation cascade
ORFTFTF
G
kinaseTF
G
G
Marker is linked to polymorphism inexpression regulation cascade
ORFTFTF
G
kinaseTF
G
G One allele = high mRNA,the other = low mRNA
Marker is linked to polymorphism inexpression regulation cascade
ORFTFTF
G
kinaseTF
Marker is linked to polymorphism inexpression regulation cascade
ORFTFTF
G
kinaseTF
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Marker is linked to polymorphism inexpression regulation cascade
ORFTFTF
G
kinaseTF
mRNA level shows linkage to locus of polymorphicregulator(s).
Marker is linked to polymorphism inexpression regulation cascade
ORFTFTF
G
kinaseTF
mRNA level shows linkage to locus of polymorphicregulator(s).
Locally acting polymorphisms Locally acting polymorphisms
Locally acting polymorphisms
Polymorphism responsible for mRNA difference is at the locusof the gene itself
Locally acting polymorphisms
ORFTFTF
G
kinaseTF
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Locally acting polymorphisms
ORFTFTF
G
kinaseTF
Locally acting polymorphisms
Polymorphism responsible for mRNA difference is at the locusof the gene itself
Locally acting polymorphisms
Polymorphism responsible for mRNA difference is at the locusof the gene itself
~25% of varying mRNAsare caused by locallyacting polymorphism
Nonlocal polymorphisms
Nonlocal polymorphisms
One polymorphism in a key regulator can affect aregulon: 100’s of related mRNAs.
Clinical applications
“Black 6” mouse x “DBA” mouse
111 F2 progeny
Microarrayeach F2 liver
…
Genotypeeach F2
Measure fatpad each F2
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Clinical applications Clinical applications
Colored curves= fat mass atdifferent bodylocations
Clinical applications
Finding polymorphism responsible fordifference in macroscopic phenotype is hard
Clinical applications
Finding polymorphism responsible fordifference in macroscopic phenotype is hard
If mRNAs change too, can learn mechanismfrom known function of encoded proteins
Clinical applications Clinical applications
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Clinical applications Clinical applicationsCounts allele 1/allele 2, casesCounts allele 1/allele 2, controls
= 1.5
Clinical applications Clinical applications
Marker predicts quantitative expression level = association
Can we map expression traitsfirst, disease afterward?
Linkage of human transcripts
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Linkage of human transcripts Association of human transcripts
Association of human transcriptslinkage(families)
assoc(unrelated)
Association in multiple populations
Han Chinese and Japanese
European-Americans in Utah
Association in multiple populations
