Genome partitioning of genetic variation for complex traits using common SNPs

Jian Yang, Teri A. Manolio, Louis R. Pasquale, Eric Boerwinkle, Neil Caporaso, Julie M. Cunningham, Mariza De Andrade, Bjarke Feenstra, Eleanor Feingold, M. Geoffrey Hayes, William G. Hill, Maria Teresa Landi, Alvaro Alonso, Guillaume Lettre, Peng Lin, Hua Ling, William Lowe, Rasika A. Mathias, Mads Melbye, Elizabeth PughMarilyn C. Cornelis, Bruce S. Weir, Michael E. Goddard, Peter M. Visscher

Research output: Contribution to journalArticlepeer-review

566 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)519-525
Number of pages7
JournalNature genetics
Issue number6
StatePublished - Jun 2011

ASJC Scopus subject areas

  • Genetics


Dive into the research topics of 'Genome partitioning of genetic variation for complex traits using common SNPs'. Together they form a unique fingerprint.

Cite this