A sibling method for identifying vQTLs

Dalton Conley, Rebecca Johnson, Ben Domingue, Christopher Dawes, Jason Boardman, Mark Siegal

Research output: Contribution to journalArticle

Abstract

The propensity of a trait to vary within a population may have evolutionary, ecological, or clinical significance. In the present study we deploy sibling models to offer a novel and unbiased way to ascertain loci associated with the extent to which phenotypes vary (variancecontrolling quantitative trait loci, or vQTLs). Previous methods for vQTL-mapping either exclude genetically related individuals or treat genetic relatedness among individuals as a complicating factor addressed by adjusting estimates for non-independence in phenotypes. The present method uses genetic relatedness as a tool to obtain unbiased estimates of variance effects rather than as a nuisance. The family-based approach, which utilizes random variation between siblings in minor allele counts at a locus, also allows controls for parental genotype, mean effects, and non-linear (dominance) effects that may spuriously appear to generate variation. Simulations show that the approach performs equally well as two existing methods (squared Z-score and DGLM) in controlling type I error rates when there is no unobserved confounding, and performs significantly better than these methods in the presence of small degrees of confounding. Using height and BMI as empirical applications, we investigate SNPs that alter within-family variation in height and BMI, as well as pathways that appear to be enriched. One significant SNP for BMI variability, in the MAST4 gene, replicated. Pathway analysis revealed one gene set, encoding members of several signaling pathways related to gap junction function, which appears significantly enriched for associations with within-family height variation in both datasets (while not enriched in analysis of mean levels). We recommend approximating laboratory random assignment of genotype using family data and more careful attention to the possible conflation of mean and variance effects.

Original languageEnglish (US)
Article numbere0194541
JournalPLoS One
Volume13
Issue number4
DOIs
StatePublished - Apr 1 2018

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Genes
genetic relationships
Single Nucleotide Polymorphism
Genotype
Phenotype
phenotype
loci
gap junctions
genotype
Quantitative Trait Loci
Gap Junctions
methodology
dominance (genetics)
quantitative trait loci
genes
Alleles
alleles
Population

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)

Cite this

Conley, D., Johnson, R., Domingue, B., Dawes, C., Boardman, J., & Siegal, M. (2018). A sibling method for identifying vQTLs. PLoS One, 13(4), [e0194541]. https://doi.org/10.1371/journal.pone.0194541

A sibling method for identifying vQTLs. / Conley, Dalton; Johnson, Rebecca; Domingue, Ben; Dawes, Christopher; Boardman, Jason; Siegal, Mark.

In: PLoS One, Vol. 13, No. 4, e0194541, 01.04.2018.

Research output: Contribution to journalArticle

Conley, D, Johnson, R, Domingue, B, Dawes, C, Boardman, J & Siegal, M 2018, 'A sibling method for identifying vQTLs', PLoS One, vol. 13, no. 4, e0194541. https://doi.org/10.1371/journal.pone.0194541
Conley D, Johnson R, Domingue B, Dawes C, Boardman J, Siegal M. A sibling method for identifying vQTLs. PLoS One. 2018 Apr 1;13(4). e0194541. https://doi.org/10.1371/journal.pone.0194541
Conley, Dalton ; Johnson, Rebecca ; Domingue, Ben ; Dawes, Christopher ; Boardman, Jason ; Siegal, Mark. / A sibling method for identifying vQTLs. In: PLoS One. 2018 ; Vol. 13, No. 4.
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