http www twinsrealm com othrpics twins16 jpg http www twinsinsurance net images twins jpg NO progeny as extreme as diploid hybrid http www twinsrealm c om oth rpics sarahandsandra jpg http www sciam com media inline 15DD5B0E AB4123B8 2B1E53E8573428C5 1 jpg Heritability in humans MZ twins Mean each pair z i Each individual zij Total mean sq zij z 2 t2 h2 T Within pairs mean sq zij zi 2 w2 N Between pairs mean sq 2 zi z 2 b 2 b 2 w 2 t2 N 1 Three mutant genes From pathogenic strain From pathogenic strain Linked mutations of opposite effect From pathogenic strain Path Lab Alleles from the same strain at different genes loci can have different effects Why is distribution of progeny so skewed Very unlikely Why is distribution of progeny so skewed Hypothesis interaction between loci see problem set Lab parent Pathogenic parent Diploid hybrid 1 Golden mutation Fine mapping 85 kb slc24a5 mRNA Inject into golden larvae No truncation in humans but Correlates with human differences AA Note that this is not linkage analysis Individuals are unrelated AG GG No other species have the Thr allele what does this mean Could be deleterious just an accidental mutation Could be advantageous for some humans no other species What is a haplotype Genetic association studies Fig 11 25 2 What is a haplotype Fig 11 25 What is a haplotype Fig 11 25 What is a haplotype Fig 11 25 Association mapping qualitative Fig 11 26 What is a haplotype Fig 11 25 Association mapping qualitative Fig 11 26 3 Association mapping qualitative Fig 11 26 Association mapping qualitative Fig 11 26 Association mapping qualitative Association mapping qualitative Only have markers not true underlying disease mutation duh Fig 11 26 Fig 11 26 Linkage disequilibrium Linkage disequilibrium Marker alleles appear together in disease population more than you would expect 4 Association mapping qualitative In association we don t calculate a recombination fraction we aren t counting recombinants 2 test Association mapping qualitative In association we don t calculate a recombination fraction we aren t counting recombinants Each individual could represent a different number of generations and recomb since mutation arose Get markers by re sequencing Association scan qualitative Fine mapping osteoarthritis controls C s 141 797 G s 47 433 log 2 p value The association revolution rs377472 5 Beginnings of molecular confirmation Beginnings of molecular confirmation coding polymorphisms Another example qualitative Another example qualitative http www encyclopedia com t opic myasthenia gravis aspx Early onset Another example qualitative A promoter SNP at last Normal onset 6 Quantitative test for association Association scan quantitative http www nature com nrg journal v7 n10 full nrg1916 html AA AG GG Rice yield start with linkage Narrow down by backcross Nipponbare x Kasalath F1 F2 Transgenic test Association across 100 cultivars quant 7 Association across 100 cultivars quant Association vs linkage Conclude that these alleles are common across many cultivars not just in linkage cross Association vs linkage Unrelated individuals usually Association vs linkage Related individuals Unrelated individuals usually Related individuals Extreme of linkage study is one large family less likely that phenotype has multiple genetic causes locus heterogeneity Association vs linkage Unrelated individuals Association vs linkage Related individuals Strong easy to detect Unrelated individuals Related individuals Strong easy to detect but rare in population 8 Association vs linkage Unrelated individuals Association vs linkage Related individuals Unrelated individuals Related individuals Strong easy to detect but rare in population may not be reflective of common disease Strong easy to detect but rare in population may not be reflective of common disease Also hard to collect family data Association vs linkage Unrelated individuals Association vs linkage Related individuals Common but weak effects Strong easy to detect but rare in population may not be reflective of common disease Also hard to collect family data Unrelated individuals Related individuals Common but weak effects need 1000 s of samples to detect Strong easy to detect but rare in population may not be reflective of common disease Also hard to collect family data Association vs linkage Unrelated individuals Common but weak effects need 1000 s of samples to detect If no common cause can fail Related individuals Strong easy to detect but rare in population may not be reflective of common disease Also hard to collect family data Another key feature of association mapping resolution 9 Association vs linkage Association vs linkage many recombinations have happened since common ancestor shared region is small no signal for distant markers small number of generations individuals share big chunks of genome can get signal at distant markers many recombinations have happened since common ancestor shared region is small no signal for distant markers Association vs linkage Association vs linkage small number of generations individuals share big chunks of genome can get signal at distant markers many recombinations have happened since common ancestor shared region is small no signal for distant markers So you need very high density of markers to get signal in an association study but you get very high spatial resolution small number of generations individuals share big chunks of genome can get signal at distant markers many recombinations have happened since common ancestor shared region is small no signal for distant markers In the old days of sparse markers linkage analysis was the best strategy Diabetes in Native Americans But there is a pitfall of association tests population structure 10 Diabetes in Native Americans Diabetes in Native Americans Family studies indicate it is at least partly genetic not environmental 1971 Association mapping causal loci Typed IgG heavy chains with protein assay Phenotypes can serve as markers too 1971 Association mapping causal loci Typed IgG heavy chains with protein assay Phenotypes can serve as markers too Multiple proteins from chr 14 region haplotype Association mapping causal loci Association mapping causal loci diabetes control Gm 23 no Gm 1343 270 3284 11 Association mapping causal loci Association mapping causal loci Gm is protective against diabetes diabetes control Gm 23 no Gm 1343 diabetes control 270 Gm 3284 no Gm 1343 23 Association mapping causal loci Self identified
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