title: Genome-wide eQTLs and heritability for gene expression traits in unrelated individuals.
abstract: BACKGROUND
  While 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.
  
  
  RESULTS
  Heritability 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.
  
  
  CONCLUSIONS
  We 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.
authors.forename: Shengjie
authors.initials: S
authors.lastname: Yang
authors.forename: Yiyuan
authors.initials: Y
authors.lastname: Liu
authors.forename: Ning
authors.initials: N
authors.lastname: Jiang
authors.forename: Jing
authors.initials: J
authors.lastname: Chen
authors.forename: Lindsey
authors.initials: L
authors.lastname: Leach
authors.affiliation: Department of Biostatistics and Computational Biology, School of Life Sciences, Laboratory of Population & Quantitative Genetics, State Key Laboratory of Genetic Engineering, Fudan University, Shanghai 200433, China. zwluo@fudan.edu.cn.
authors.forename: Zewei
authors.initials: Z
authors.lastname: Luo
authors.forename: Minghui
authors.initials: M
authors.lastname: Wang
mesh_terms: D004843:Epistasis, Genetic; D015870:Gene Expression; D015894:Genome, Human; D055106:Genome-Wide Association Study; D005838:Genotype; D060148:HapMap Project; D006801:Humans; D008957:Models, Genetic; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide; D019655:Quantitative Trait, Heritable