The phenome-wide distribution of genetic variance

Blows, Mark W., Allen, Scott L., Collet, Julie M., Chenoweth, Stephen F. and McGuigan, Katrina (2015) The phenome-wide distribution of genetic variance. American Naturalist, 186 1: 15-30. doi:10.1086/681645

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Author Blows, Mark W.
Allen, Scott L.
Collet, Julie M.
Chenoweth, Stephen F.
McGuigan, Katrina
Title The phenome-wide distribution of genetic variance
Journal name American Naturalist   Check publisher's open access policy
ISSN 0003-0147
1537-5323
Publication date 2015-07
Sub-type Article (original research)
DOI 10.1086/681645
Open Access Status File (Publisher version)
Volume 186
Issue 1
Start page 15
End page 30
Total pages 16
Place of publication Chicago, IL, United States
Publisher University of Chicago Press
Collection year 2016
Language eng
Formatted abstract
A general observation emerging from estimates of additive genetic variance in sets of functionally or developmentally related traits is that much of the genetic variance is restricted to few trait combinations as a consequence of genetic covariance among traits. While this biased distribution of genetic variance among functionally related traits is now well documented, how it translates to the broader phenome and therefore any trait combination under selection in a given environment is unknown. We show that 8,750 gene expression traits measured in adult male Drosophila serrata exhibit widespread genetic covariance among random sets of five traits, implying that pleiotropy is common. Ultimately, to understand the phenome-wide distribution of genetic variance, very large additive genetic variance-covariance matrices (G) are required to be estimated. We draw upon recent advances in matrix theory for completing high-dimensional matrices to estimate the 8,750-trait G and show that large numbers of gene expression traits genetically covary as a consequence of a single genetic factor. Using gene ontology term enrichment analysis, we show that the major axis of genetic variance among expression traits successfully identified genetic covariance among genes involved in multiple modes of transcriptional regulation. Our approach provides a practical empirical framework for the genetic analysis of high-dimensional phenome-wide trait sets and for the investigation of the extent of high-dimensional genetic constraint.
Keyword Genetic variance
G matrix
Pleiotropy
Gene expression
Matrix completion
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2016 Collection
School of Biological Sciences Publications
 
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