Literature DB >> 26098335

The phenome-wide distribution of genetic variance.

Mark W Blows1, Scott L Allen, Julie M Collet, Stephen F Chenoweth, Katrina McGuigan.   

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.

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Year:  2015        PMID: 26098335     DOI: 10.1086/681645

Source DB:  PubMed          Journal:  Am Nat        ISSN: 0003-0147            Impact factor:   3.926


  9 in total

1.  Why does allometry evolve so slowly?

Authors:  David Houle; Luke T Jones; Ryan Fortune; Jacqueline L Sztepanacz
Journal:  Integr Comp Biol       Date:  2019-11-01       Impact factor: 3.326

2.  Do traits separated by metamorphosis evolve independently? Concepts and methods.

Authors:  Julie Collet; Simon Fellous
Journal:  Proc Biol Sci       Date:  2019-04-10       Impact factor: 5.349

3.  Accounting for Sampling Error in Genetic Eigenvalues Using Random Matrix Theory.

Authors:  Jacqueline L Sztepanacz; Mark W Blows
Journal:  Genetics       Date:  2017-05-05       Impact factor: 4.562

4.  Uneven Distribution of Mutational Variance Across the Transcriptome of Drosophila serrata Revealed by High-Dimensional Analysis of Gene Expression.

Authors:  Emma Hine; Daniel E Runcie; Katrina McGuigan; Mark W Blows
Journal:  Genetics       Date:  2018-06-08       Impact factor: 4.562

5.  Genetic constraints on microevolutionary divergence of sex-biased gene expression.

Authors:  Scott L Allen; Russell Bonduriansky; Stephen F Chenoweth
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2018-10-05       Impact factor: 6.237

6.  EIGENVALUE DISTRIBUTIONS OF VARIANCE COMPONENTS ESTIMATORS IN HIGH-DIMENSIONAL RANDOM EFFECTS MODELS.

Authors:  Fan Zhou; Iain M Johnstone
Journal:  Ann Stat       Date:  2019-08-03       Impact factor: 4.028

7.  Mutational Pleiotropy and the Strength of Stabilizing Selection Within and Between Functional Modules of Gene Expression.

Authors:  Julie M Collet; Katrina McGuigan; Scott L Allen; Stephen F Chenoweth; Mark W Blows
Journal:  Genetics       Date:  2018-02-01       Impact factor: 4.562

Review 8.  Pleiotropy, constraint, and modularity in the evolution of life histories: insights from genomic analyses.

Authors:  Kimberly A Hughes; Jeff Leips
Journal:  Ann N Y Acad Sci       Date:  2016-12-09       Impact factor: 5.691

9.  Maintenance of quantitative genetic variance in complex, multitrait phenotypes: the contribution of rare, large effect variants in 2 Drosophila species.

Authors:  Emma Hine; Daniel E Runcie; Scott L Allen; Yiguan Wang; Stephen F Chenoweth; Mark W Blows; Katrina McGuigan
Journal:  Genetics       Date:  2022-09-30       Impact factor: 4.402

  9 in total

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