Genome-wide eQTLs and heritability for gene expression traits in unrelated individuals

BMC Genomics

Research Article

Ning Jiang¹  Shengjie Yang¹  Zewei Luo²  Yiyuan Liu³  Jing Chen⁴  Minghui Wang⁴  Lindsey Leach⁴ 

[1] Department of Biostatistics and Computational Biology, School of Life Sciences, Laboratory of Population & Quantitative Genetics, State Key Laboratory of Genetic Engineering, Fudan University, 200433, Shanghai, China;Department of Biostatistics and Computational Biology, School of Life Sciences, Laboratory of Population & Quantitative Genetics, State Key Laboratory of Genetic Engineering, Fudan University, 200433, Shanghai, China;School of Biosciences, The University of Birmingham, B15 2TT, Edgbaston, Birmingham, UK;Division of Cardiovascular & Diabetes Medicine, University of Dundee, DD1 9SY, Dundee, UK;School of Biosciences, The University of Birmingham, B15 2TT, Edgbaston, Birmingham, UK;

关键词: Microarray gene expression;    eQTLs;    Heritability;    Mixed model;    HapMap populations;    Epistasis;   

DOI  :  10.1186/1471-2164-15-13

 received in 2013-04-09, accepted in 2013-11-22,  发布年份 2014

来源: Springer

【 摘 要 】

BackgroundWhile the possible sources underlying the so-called ‘missing heritability’ evident in current genome-wide association studies (GWAS) of complex traits have been actively pursued in recent years, resolving this mystery remains a challenging task. Studying heritability of genome-wide gene expression traits can shed light on the goal of understanding the relationship between phenotype and genotype. Here we used microarray gene expression measurements of lymphoblastoid cell lines and genome-wide SNP genotype data from 210 HapMap individuals to examine the heritability of gene expression traits.ResultsHeritability levels for expression of 10,720 genes were estimated by applying variance component model analyses and 1,043 expression quantitative loci (eQTLs) were detected. Our results indicate that gene expression traits display a bimodal distribution of heritability, one peak close to 0% and the other summit approaching 100%. Such a pattern of the within-population variability of gene expression heritability is common among different HapMap populations of unrelated individuals but different from that obtained in the CEU and YRI trio samples. Higher heritability levels are shown by housekeeping genes and genes associated with cis eQTLs. Both cis and trans eQTLs make comparable cumulative contributions to the heritability. Finally, we modelled gene-gene interactions (epistasis) for genes with multiple eQTLs and revealed that epistasis was not prevailing in all genes but made a substantial contribution in explaining total heritability for some genes analysed.ConclusionsWe utilised a mixed effect model analysis for estimating genetic components from population based samples. On basis of analyses of genome-wide gene expression from four HapMap populations, we demonstrated detailed exploitation of the distribution of genetic heritabilities for expression traits from different populations, and highlighted the importance of studying interaction at the gene expression level as an important source of variation underlying missing heritability.

【 授权许可】

Unknown   
© Yang et al.; licensee BioMed Central Ltd. 2014. This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.