A generalized linear model for decomposing cis-regulatory, parent-of-origin, and maternal effects on allele-specific gene expression

TL;DR

This paper introduces a simple statistical method to decompose and quantify cis-regulatory, parent-of-origin, and maternal effects on allele-specific gene expression from RNA-seq data, revealing tissue-specific influences in mammals and flies.

Contribution

The authors develop a generalized linear model that effectively separates and quantifies three complex genetic and epigenetic effects on gene expression using reciprocal cross RNA-seq data.

Findings

Little PO and MG effects in adult Drosophila

Many genes with significant PO and MG effects in mouse tissues

More MG effects observed in mouse liver than in TSCs

Abstract

Joint quantification of genetic and epigenetic effects on gene expression is important for understanding the establishment of complex gene regulation systems in living organisms. In particular, genomic imprinting and maternal effects play important roles in the developmental process of mammals and flowering plants. However, the influence of these effects on gene expression are difficult to quantify because they act simultaneously with cis-regulatory mutations. Here we propose a simple method to decompose cis-regulatory (i.e., allelic genotype, AG), genomic imprinting (i.e., parent-of-origin, PO), and maternal (i.e., maternal genotype, MG) effects on allele-specific gene expression using RNA-seq data obtained from reciprocal crosses. We evaluated the efficiency of method using a simulated dataset and applied the method to whole-body Drosophila and mouse trophoblast stem cell (TSC) and liver RNA-seq data. Consistent with previous studies, we found little evidence of PO and MG effects in adult Drosophila samples. In contrast, we identified dozens and hundreds of mouse genes with significant PO and MG effects, respectively. Interestingly, a similar number of genes with significant PO effect were detect in mouse TSCs and livers, whereas more genes with significant MG effect were observed in livers. Further application of this method will clarify how these three effects influence gene expression levels in different tissues and developmental stages, and provide novel insight into the evolution of gene expression regulation.