Underestimation of Heritability across the Molecular Layers of the Gene Expression Process

Jihye Ryu,Chaeyoung Lee

doi:10.3390/pr9122144

Abstract

We investigated the extent of the heritability underestimation for molecules from an infinitesimal model in mixed model analysis. To this end, we estimated the heritability of transcription, ribosome occupancy, and translation in lymphoblastoid cell lines from Yoruba individuals. Upon considering all genome-wide nucleotide variants, a considerable underestimation in heritability was observed for mRNA transcription (−0.52), ribosome occupancy (−0.48), and protein abundance (−0.47). We employed a mixed model with an optimal number of nucleotide variants, which maximized heritability, and identified two novel expression quantitative trait loci (eQTLs; p < 1.0 × 10−5): rs11016815 on chromosome 10 that influences the transcription of SCP2, a trans-eGene on chromosome 1—whose expression increases in response to MGMT downregulation-induced apoptosis, the cis-eGene of rs11016815—and rs1041872 on chromosome 11 that influences the ribosome occupancy of CCDC25 on chromosome 8 and whose cis-eGene encodes ZNF215, a transcription factor that potentially regulates the translation speed of CCDC25. Our results suggest that an optimal number of nucleotide variants should be used in a mixed model analysis to accurately estimate heritability and identify eQTLs. Moreover, a heterogeneous covariance structure based on gene identity and the molecular layers of the gene expression process should be constructed to better explain polygenic effects and reduce errors in identifying eQTLs.

Highlights

We identified eQTLs using the following analytical model including random polygenic effects with genomic similarity matrix (GSM): y = μ1 + xβ + g + ε where μ is the overall mean, 1 is the vector of 10 s, β is the fixed minor allele effect of the nucleotide variant to be tested for association, and x is the vector with elements of 0, 1, and 2 for the homozygote of the major allele, the heterozygote, and the homozygote of the minor allele, respectively
We compared the heritability of mRNA transcription, ribosome occupancy, and protranscription and protein abundance, explained by expression quantitative trait loci
This study showed the gene expression heritability explained by eQTLs, considered for the polygenic covariance structure among individuals in a mixed model framework

Summary

Introduction

Gene expression is a critical process that links genetic information to phenotypes. Nucleotide sequence variants that are associated with gene expression are called expression quantitative trait loci (eQTLs), and genome-wide eQTL analyses help to dissect the genetic mechanism underlying gene regulation by generating cis- and trans-eQTL profiles for a gene [1]. A substantial proportion of gene expression variation was attributed to eQTLs [2,3]. The eQTLs were heterogeneous by ethnic groups [2], which indicates potential spurious genetic associations produced by the population structure [4]. The polygenic effects of gene expression have been largely observed [3], and a great concern for the accuracy of eQTLs was raised by ignoring polygenic effects in the eQTL analyses [5]

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