Bioinformatics Seminar
Time:
Venue: Na
8 August 2017
NaUniversity of Melbourne
David BaldingCentre for System Genomics
Re-evaluation of SNP Heritability in Complex Human Traits;Measuring heritability from SNPs genotyped in unrelated individuals has had a large impact on complex trait genetics since first introduced in 2010. The method has been used to show that common genetic markers carry a large fraction of heritability , distributed across many SNPs genome-wide , thus helping solve the missing heritability" problem. It has also been used to locate heritability in specific genomic regions ; as well as to identify substantial shared heritability across different traits.
By careful modelling and analysis of large genome-wide data sets for many traits we have shown that the mathematical model proposed in the foundational 2010 paper ; and widely used since ; does not match reality in key aspects. Specifically ; the standard model implicitly assigns the same heritability to every SNP a priori. We propose a revised model that uses empirically-supported adjustments based on the properties of the SNP: linkage disequilibrium ; population minor allele fraction and genotype quality. Using our revised model we found on average around a 40% increase in SNP-heritability compared with the standard model ; thus further reducing the missing heritability gap. However in some cases we found a dramatic reduction. A 2015 paper reported that 80% of heritability was concentrated in DNase Hypersensitivity Sites (DHS) ; a striking result that attracted much attention because DHS correspond to only about 18% of the genome. In contrast ; we estimate that only about 25% of heritability lies in DHS ; corresponding to an enrichment factor of about 1.4 ; slightly less than the 1.6 fold enrichment for genic SNPs.
Our revised model has implications that we will discuss for many other currently-popular methods in complex trait genetics ; including methods based on summary statistics rather than individual genotype data."
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