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

References to SciGraph publications

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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471 https://www.grid.ac/institutes/grid.4305.2 schema:alternateName University of Edinburgh
472 schema:name Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK.
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474 https://www.grid.ac/institutes/grid.4367.6 schema:alternateName Washington University in St. Louis
475 schema:name Human and Statistical Genetics Program, School of Medicine, Washington University, St. Louis, Missouri, USA.
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477 https://www.grid.ac/institutes/grid.452205.4 schema:alternateName Department of Environment, Land, Water and Planning
478 schema:name Biosciences Research Division, Department of Primary Industries, Bundoora, Victoria, Australia.
479 Department of Food and Agricultural Systems, University of Melbourne, Victoria, Australia.
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481 https://www.grid.ac/institutes/grid.48336.3a schema:alternateName National Cancer Institute
482 schema:name Division of Cancer Epidemiology and Genetics, NCI, Bethesda, Maryland, USA.
483 Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), Bethesda, Maryland, USA.
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485 https://www.grid.ac/institutes/grid.6203.7 schema:alternateName Statens Serum Institut
486 schema:name Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark.
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488 https://www.grid.ac/institutes/grid.66875.3a schema:alternateName Mayo Clinic
489 schema:name Department of Laboratory Medicine and Pathology, Mayo Clinic College of Medicine, Rochester, Minnesota, USA.
490 Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota, USA.
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