Presentation on theme: "Lab 13: Association Genetics. Goals Use a Mixed Model to determine genetic associations. Understand the effect of population structure and kinship on."— Presentation transcript:
Goals Use a Mixed Model to determine genetic associations. Understand the effect of population structure and kinship on associations. Use Trait Analysis by aSSociation, Evolution and Linkage (TASSEL) to calculate phenotype- genotype associations.
Mixed Model phenotype (response variable) of individual i effect of target SNP Family effect (Kinship coefficient) Population Effect (e.g., Admixture coefficient from Structure or values of Principal Components) effects of background SNPs
Population Structure Unequal distribution of alleles unrelated to disease between cases and controls. Any allele more common in diseased population may spuriously appear to be associated with disease. Cases Controls Genotype Pop 1 Pop 2 Pop 2 TT AT AA
Principal Component Analysis (PCA) PCA is a computationally efficient way to quantify population structure (Q). PCA reduces dimensionality of the data so that the correlated variables are transformed into uncorrelated variables called principal components. PC1 captures as much of the variation as possible and proceeds with PC2, PC3…. Requires elimination of monomorphic markers and imputation of missing values.
Imputing Missing Genotypes Typically accomplished with software such as IMPUTE, PLINK, MACH, BEAGLE, and fastPHASE From Isik and Wetten 2011 Workshop on Genomic Selection
Problem 1 (revised) Use the Tassel Tutorial Data to explore how to perform association genetic analyses for some commercially-important Maize phenotypes: flowering time, ear height, and ear width. A.Which traits have significant associations? Which chromosomes are associated with each trait? A.Are there any patterns to the locations of the significant SNPs within the gene or chromosomes (e.g., are the significant SNPs clustered or dispersed, where in the gene do they occur)? Do similar chromosomal regions show associations with different traits? What are some possible reasons for these patterns? A. How do the corrections for population structure and kinship change the associations? Why?