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Genome-wide eQTLs and heritability for gene expression traits in unrelated individuals
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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4028055/ https://www.ncbi.nlm.nih.gov/pubmed/24405759 http://dx.doi.org/10.1186/1471-2164-15-13 |
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author | Yang, Shengjie Liu, Yiyuan Jiang, Ning Chen, Jing Leach, Lindsey Luo, Zewei Wang, Minghui |
author_facet | Yang, Shengjie Liu, Yiyuan Jiang, Ning Chen, Jing Leach, Lindsey Luo, Zewei Wang, Minghui |
author_sort | Yang, Shengjie |
collection | PubMed |
description | 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1471-2164-15-13) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4028055 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-40280552014-05-22 Genome-wide eQTLs and heritability for gene expression traits in unrelated individuals Yang, Shengjie Liu, Yiyuan Jiang, Ning Chen, Jing Leach, Lindsey Luo, Zewei Wang, Minghui BMC Genomics Research Article 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1471-2164-15-13) contains supplementary material, which is available to authorized users. BioMed Central 2014-01-09 /pmc/articles/PMC4028055/ /pubmed/24405759 http://dx.doi.org/10.1186/1471-2164-15-13 Text en © 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. |
spellingShingle | Research Article Yang, Shengjie Liu, Yiyuan Jiang, Ning Chen, Jing Leach, Lindsey Luo, Zewei Wang, Minghui Genome-wide eQTLs and heritability for gene expression traits in unrelated individuals |
title | Genome-wide eQTLs and heritability for gene expression traits in unrelated individuals |
title_full | Genome-wide eQTLs and heritability for gene expression traits in unrelated individuals |
title_fullStr | Genome-wide eQTLs and heritability for gene expression traits in unrelated individuals |
title_full_unstemmed | Genome-wide eQTLs and heritability for gene expression traits in unrelated individuals |
title_short | Genome-wide eQTLs and heritability for gene expression traits in unrelated individuals |
title_sort | genome-wide eqtls and heritability for gene expression traits in unrelated individuals |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4028055/ https://www.ncbi.nlm.nih.gov/pubmed/24405759 http://dx.doi.org/10.1186/1471-2164-15-13 |
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