Genome partitioning of genetic variation for complex traits using common SNPs View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2011-06

AUTHORS

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 Pugh, Marilyn C Cornelis, Bruce S Weir, Michael E Goddard, Peter M Visscher

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. More... »

PAGES

519

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/ng.823

    DOI

    http://dx.doi.org/10.1038/ng.823

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1007907762

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/21552263


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