Partitioning Phenotypic Variance Due to Parent-of-Origin Effects Using Genomic Relatedness Matrices

Laurin, Charles, Cuellar-Partida, Gabriel, Hemani, Gibran, Smith, George Davey, Yang, Jian and Evans, David M. (2017) Partitioning Phenotypic Variance Due to Parent-of-Origin Effects Using Genomic Relatedness Matrices. Behavior Genetics, 48 1: 67-79. doi:10.1007/s10519-017-9880-0


Author Laurin, Charles
Cuellar-Partida, Gabriel
Hemani, Gibran
Smith, George Davey
Yang, Jian
Evans, David M.
Title Partitioning Phenotypic Variance Due to Parent-of-Origin Effects Using Genomic Relatedness Matrices
Journal name Behavior Genetics   Check publisher's open access policy
ISSN 1573-3297
0001-8244
Publication date 2017-11-02
Year available 2017
Sub-type Article (original research)
DOI 10.1007/s10519-017-9880-0
Open Access Status DOI
Volume 48
Issue 1
Start page 67
End page 79
Total pages 13
Place of publication New York, NY United States
Publisher Springer New York
Abstract We propose a new method, G-REMLadp, to estimate the phenotypic variance explained by parent-of-origin effects (POEs) across the genome. Our method uses restricted maximum likelihood analysis of genome-wide genetic relatedness matrices based on individuals' phased genotypes. Genome-wide SNP data from parent child duos or trios is required to obtain relatedness matrices indexing the parental origin of offspring alleles, as well as offspring phenotype data to partition the trait variation into variance components. To calibrate the power of G-REMLadp to detect non-null POEs when they are present, we provide an analytic approximation derived from Haseman-Elston regression. We also used simulated data to quantify the power and Type I Error rates of G-REMLadp, as well as the sensitivity of its variance component estimates to violations of underlying assumptions. We subsequently applied G-REMLadp to 36 phenotypes in a sample of individuals from the Avon Longitudinal Study of Parents and Children (ALSPAC). We found that the method does not seem to be inherently biased in estimating variance due to POEs, and that substantial correlation between parental genotypes is necessary to generate biased estimates. Our empirical results, power calculations and simulations indicate that sample sizes over 10000 unrelated parent-offspring duos will be necessary to detect POEs explaining < 10% of the variance with moderate power. We conclude that POEs tagged by our genetic relationship matrices are unlikely to explain large proportions of the phenotypic variance (i.e. > 15%) for the 36 traits that we have examined.
Keyword ALSPAC
G-REML
GCTA
Imprinting
Parent-of-origin effects
Q-Index Code C1
Q-Index Status Provisional Code
Grant ID APP1085130
MC_UU_12013/4
092731
102215/2/13/2
FT130101709
Institutional Status UQ

 
Versions
Version Filter Type
Citation counts: Scopus Citation Count Cited 0 times in Scopus Article
Google Scholar Search Google Scholar
Created: Wed, 08 Nov 2017, 12:01:31 EST