Association vs linkage Office hours Wednesday 3 4pm 304A Stanley Hall Unrelated individuals Review session 5pm Thursday Dec 11 GPB100 Common but weak effects need 1000 s of samples to detect If no common cause can fail Association vs linkage So you need very high density of markers to get signal in an association study but you get very high spatial resolution Strong easy to detect but rare in population may not be reflective of common disease Also hard to collect family data Association and admixture small number of generations individuals share big chunks of genome can get coinheritance between distant markers many recombinations have happened since common ancestor shared region is small no coinheritance between distant markers Related individuals Cases Controls At any one of these loci Caucasian like allele will be enriched in control samples Expression microarrays Genotyping by array Fig 11 8 Fig 1 13 1 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 Coding sequence array say with chemotherapeutic Fig 1 13 Fig 1 13 Coding sequence array Fig 1 13 Coding sequence array Fig 1 13 2 Coding sequence array Why measure expression of all genes at once expression expression expressed not expressed Fig 1 13 Regulon expression response Regulon expression response e g cortisol http www2 kenyon edu Depts BioEllipse courses biol114 Chap06 week08a files regulon gif http www mcb mcgill ca hallett GEP Lecture2 Image17 gif Oligo expression array soybean component Finding regulatory response on a large scale transcripts 3 Expression profiles Time since drug administered Expression profiles Time since drug administered Time since drug administered Expression profiles Expression effects of cancer Time since drug administered Each color is a regulon or cluster of coregulated genes Time since drug administered Cancer classification Cancer classification 4 Diagnosis via transcriptional profile Histological classification is finicky can we do better Diagnosis via transcriptional profile Diagnosis via transcriptional profile patient samples transcripts 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 5 Natural variation among normals Natural variation among normals 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 Genetic variation in mRNA levels G kinase TF TF Genetic variation in mRNA levels G TF ORF Many mRNA differences at once Likely to be a complex trait kinase TF TF TF ORF 6 Linkage mapping of mRNA levels Black 6 mouse x Linkage mapping of mRNA levels DBA mouse Black 6 mouse x DBA mouse 10 mRNA levels significantly different Linkage mapping of mRNA levels Black 6 mouse x Linkage mapping of mRNA levels DBA mouse Black 6 mouse 111 F2 progeny x DBA mouse 111 F2 progeny Microarray each F2 liver Linkage mapping of mRNA levels Black 6 mouse x Linkage mapping of mRNA levels DBA mouse Black 6 mouse 111 F2 progeny x DBA mouse 111 F2 progeny Microarray each F2 liver Microarray each F2 liver Genotype each F2 Genotype each F2 Looking for linkage coinheritance between marker and mRNA level 7 Marker is linked to polymorphism in expression regulation cascade Marker is linked to polymorphism in expression regulation cascade G G kinase kinase TF TF TF TF TF ORF TF ORF G G Marker is linked to polymorphism in expression regulation cascade Marker is linked to polymorphism in expression regulation cascade G G kinase kinase TF TF TF TF TF ORF G TF G G ORF One allele high mRNA the other low mRNA G Marker is linked to polymorphism in expression regulation cascade G Marker is linked to polymorphism in expression regulation cascade G kinase kinase TF TF TF TF ORF TF TF ORF 8 Marker is linked to polymorphism in expression regulation cascade G Marker is linked to polymorphism in expression regulation cascade G kinase kinase TF TF TF TF TF ORF TF ORF mRNA level shows linkage to locus of polymorphic regulator s mRNA level shows linkage to locus of polymorphic regulator s Locally acting polymorphisms Locally acting polymorphisms Locally acting polymorphisms Locally acting polymorphisms G kinase TF TF TF ORF Polymorphism responsible for mRNA difference is at the locus of the gene itself 9 Locally acting polymorphisms Locally acting polymorphisms G kinase TF TF TF ORF Polymorphism responsible for mRNA difference is at the locus of the gene itself Locally acting polymorphisms Nonlocal polymorphisms 25 of varying mRNAs are caused by locally acting polymorphism Polymorphism responsible for mRNA difference is at the locus of the gene itself Nonlocal polymorphisms Clinical applications Black 6 mouse x DBA mouse 111 F2 progeny One polymorphism in a key regulator can affect a regulon 100 s of related mRNAs Microarray each F2 liver Genotype each F2 Measure fat pad each F2 10 Clinical applications Clinical applications Colored curves fat mass at different body locations Clinical applications Finding polymorphism responsible for difference in macroscopic phenotype is hard Clinical applications Finding polymorphism responsible for difference in macroscopic phenotype is hard If mRNAs change too can learn mechanism from known function of encoded proteins Clinical applications Clinical applications 11 Clinical applications Clinical applications Counts allele 1 allele 2 cases 1 5 Counts allele 1 allele 2 controls Clinical applications Clinical applications Marker predicts quantitative expression level association Linkage of human transcripts Can we map expression traits first disease afterward 12 Linkage of human transcripts Association of human transcripts Association of human transcripts Association in multiple populations linkage families assoc unrelated European Americans in Utah Han Chinese and Japanese Association in multiple populations 13
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