Joint Modeling of EQTLs and Parent-of-Origin Effects Using an Orthogonal Framework with RNA-Seq Data

• Activity Number: 537 - Innovative Statistical Methods for Complex -Omics Data
• Type: Topic Contributed
• Date/Time: Thursday, August 6, 2020 : 1:00 PM to 2:50 PM
• Sponsor: International Chinese Statistical Association
• Author(s): Feifei Xiao* and Shirong Deng and James Hardin and Christopher I. Amos
• Companies: University of South Carolina and School of Mathematics and Statistics, Wuhan University and University of South Carolina and Baylor College of Medicine
• Keywords: Genomic imprinting; eQTL mapping; RNA sequencing data analysis; orthogonal model

Abstract

Studies of expression quantitative trait loci (eQTLs) offered promise for understanding of the processes of gene regulation.Genomic imprinting describes that the expression of certain genes depends on their allelic parent-of-origin which is known to play important roles in human complex diseases.However,traditional eQTL mapping approaches do not allow for the detection of imprinting or ignores the estimation of the dominant genetic effect.In this study,we proposed a statistical framework to test the additive and dominant genetic effects of the candidate eQTLs along with POE with an orthogonal model for RNA-seq data.We demonstrated the desirable power and Type I error and accurate estimation of the genetic parameters with simulations.Application to a HapMap project trio dataset validated the reported imprinted genes and discovered novel imprinted genes. We validated existing imprinting genes and discovered two novel imprinting genes with potential dominance genetic effect and RB1 and IGF1R genes.This study provides new insights into the next generation statistical modeling of eQTL mapping to understand the genetic architecture underlying the mechanism of gene expression regulation.