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Genome partitioning of genetic variation for complex traits using common SNPs
Authors:Yang Jian  Manolio Teri A  Pasquale Louis R  Boerwinkle Eric  Caporaso Neil  Cunningham Julie M  de Andrade Mariza  Feenstra Bjarke  Feingold Eleanor  Hayes M Geoffrey  Hill William G  Landi Maria Teresa  Alonso Alvaro  Lettre Guillaume  Lin Peng  Ling Hua  Lowe William  Mathias Rasika A  Melbye Mads  Pugh Elizabeth  Cornelis Marilyn C  Weir Bruce S  Goddard Michael E  Visscher Peter M
Institution:Queensland Statistical Genetics Laboratory, Queensland Institute of Medical Research, Brisbane, Australia.
Abstract:We estimate and partition genetic variation for height, body mass index (BMI), von Willebrand factor and QT interval (QTi) using 586,898 SNPs genotyped on 11,586 unrelated individuals. We estimate that ~45%, ~17%, ~25% and ~21% of the variance in height, BMI, von Willebrand factor and QTi, respectively, can be explained by all autosomal SNPs and a further ~0.5-1% can be explained by X chromosome SNPs. We show that the variance explained by each chromosome is proportional to its length, and that SNPs in or near genes explain more variation than SNPs between genes. We propose a new approach to estimate variation due to cryptic relatedness and population stratification. Our results provide further evidence that a substantial proportion of heritability is captured by common SNPs, that height, BMI and QTi are highly polygenic traits, and that the additive variation explained by a part of the genome is approximately proportional to the total length of DNA contained within genes therein.
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