The effect of X-linked dosage compensation on complex trait variation

Quantitative genetics theory predicts that X-chromosome dosage compensation (DC) will have a detectable effect on the amount of genetic and therefore phenotypic trait variances at associated loci in males and females. Here, we systematically examine the role of DC in humans in 20 complex traits in a...

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Vydáno v:Nature communications Ročník 10; číslo 1; s. 3009 - 11
Hlavní autoři: Sidorenko, Julia, Kassam, Irfahan, Kemper, Kathryn E., Zeng, Jian, Lloyd-Jones, Luke R., Montgomery, Grant W., Gibson, Greg, Metspalu, Andres, Esko, Tonu, Yang, Jian, McRae, Allan F., Visscher, Peter M.
Médium: Journal Article
Jazyk:angličtina
Vydáno: London Nature Publishing Group UK 08.07.2019
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ISSN:2041-1723, 2041-1723
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Shrnutí:Quantitative genetics theory predicts that X-chromosome dosage compensation (DC) will have a detectable effect on the amount of genetic and therefore phenotypic trait variances at associated loci in males and females. Here, we systematically examine the role of DC in humans in 20 complex traits in a sample of more than 450,000 individuals from the UK Biobank and 1600 gene expression traits from a sample of 2000 individuals as well as across-tissue gene expression from the GTEx resource. We find approximately twice as much X-linked genetic variation across the UK Biobank traits in males (mean h 2 SNP  = 0.63%) compared to females (mean h 2 SNP  = 0.30%), confirming the predicted DC effect. Our DC estimates for complex traits and gene expression are consistent with a small proportion of genes escaping X-inactivation in a trait- and tissue-dependent manner. Finally, we highlight examples of biologically relevant X-linked heterogeneity between the sexes that bias DC estimates if unaccounted for. Dosage compensation (DC) on the X chromosome has predictable effects on genetic and phenotypic trait variance. Here, the authors use information for 20 quantitative traits in the UK Biobank and across-tissue gene expression to compare X-linked heritability and the effects of trait-associated SNPs between the sexes.
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ISSN:2041-1723
2041-1723
DOI:10.1038/s41467-019-10598-y