Date(s) - 26/11/2013
2:00 pm - 3:30 pm
We have two great talks on applied genetics/genomics. One from Dr Doug Speed (UCL, Understanding complex traits through heritability analysis) and Dr Jen Mollon (KCL, Exploring genetic control of plasma protein levels in a protein quantitative trait loci (pQTL) analysis)
Understanding complex traits through heritability analysis. Dr Doug Speed (UCL Genetics Institute, University College London)
GCTA is routinely used to estimate “chip heritability”, the variance explained by common SNPs. Here I will explain why you should instead be using LDAK! Primarily, LDAK provides more accurate heritability estimates by adjusting for linkage disequilibrium. But LDAK can also be used for regional and gene-based association testing, for testing the relative importance of SNPs based on function, for assessing overlap between and within traits, and for constructing linear prediction models.
I demonstrate the many uses of LDAK on human disease and mouse date, which includes constructing an empirical definition of “genic”, measuring the relative contributions of eQTLs and showing how prediction models derived through heritability analysis outperform other leading methods.
Exploring genetic control of plasma protein levels in a protein quantitative trait loci (pQTL) analysis. Dr Jen Mollon (NIHR BRC-MH Bioinformatics Core,KCL/IOP)
Over 6 million SNPs (genotyped & imputated) and a thousand proteins (in plasma) were measured on 297 individuals from the AddNeuroMed cohort. Significant novel associations between number of minor alleles carried by an individual and their protein levels were discovered in 100 SNP-protein combinations mapping to 88 unique proteins. Many of these associations are trans-effects, which have not been widely reported in other studies. Eighty-eight of the 100 associations had data available for replication in an independent cohort of 101 individuals. Depending on the significance threshold applied, 23 (Bonferonni-corrected), 33 (p<0.05) or 37 (p<0.10) of these associations replicated, including many trans-effects. There is interest in how genetic variants affect protein levels, but high-throughput methods for quantifying proteins have not previously been available. Most studies to date have measured small numbers of proteins using labour-intensive quantification methods such as mass spectrometry. In this talk I will describe the analysis and results of a study using an aptamer-based high-throughput protein assay from SomaLogic.