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Human Genetics

, Volume 134, Issue 3, pp 343–358 | Cite as

A systematic heritability analysis of the human whole blood transcriptome

  • Tianxiao Huan
  • Chunyu Liu
  • Roby Joehanes
  • Xiaoling Zhang
  • Brian H. Chen
  • Andrew D. Johnson
  • Chen Yao
  • Paul Courchesne
  • Christopher J. O’Donnell
  • Peter J. Munson
  • Daniel Levy
Original Investigation

Abstract

Genome-wide expressio n quantitative trait locus (eQTL) mapping may reveal common genetic variants regulating gene expression. In addition to mapping eQTLs, we systematically evaluated the heritability of the whole blood transcriptome in 5,626 participants from the Framingham Heart Study. Of all gene expression measurements, about 40 % exhibit evidence of being heritable [\(h_{\text{geneExp}}^{ 2}\) > 0, (p < 0.05)], the average heritability was estimated to be 0.13, and 10 % display \(h_{\text{geneExp}}^{ 2}\) > 0.2. To identify the role of eQTLs in promoting phenotype differences and disease susceptibility, we investigated the proportion of cis/trans eQTLs in different heritability categories and discovered that genes with higher heritability are more likely to have cis eQTLs that explain large proportions of variance in the expression of the corresponding genes. Single cis eQTLs explain 0.33–0.53 of variance in transcripts on average, whereas single trans eQTLs only explain 0.02–0.07. The top cis eQTLs tend to explain more variance in the corresponding gene when its \(h_{\text{geneExp}}^{ 2}\) is greater. Taking body mass index (BMI) as a case study, we cross-linked cis/trans eQTLs with both GWAS SNPs and differentially expressed genes for BMI. We discovered that BMI GWAS SNPs in 16p11.2 (e.g., rs7359397) are associated with several BMI differentially expressed genes in a cis manner (e.g. SULT1A1, SPNS1, and TUFM). These BMI signature genes explain a much larger proportion of variance in BMI than do the GWAS SNPs. Our results shed light on the impact of eQTLs on the heritability of the human whole blood transcriptome and its relations to phenotype differences.

Keywords

False Discovery Rate Heritability Estimate Framingham Heart Study Metabolic Trait Offspring Cohort 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

D. L., C. L. and T.H. designed, directed, and supervised the project. D. L was responsible for funding of the project. T. H., C. L. and D. L. drafted the manuscript. P. C. organized the experiment material and data exchange. All authors participated in revising and editing the manuscripts. All authors have read and approved the final version of the manuscript.

Conflict of interest

The authors declare no conflict of interest.

Supplementary material

439_2014_1524_MOESM1_ESM.xlsx (1 mb)
Supplementary material 1 (XLSX 1044 kb)
439_2014_1524_MOESM2_ESM.docx (684 kb)
Supplementary material 2 (DOCX 683 kb)

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Copyright information

© Springer-Verlag Berlin Heidelberg (outside the USA) 2015

Authors and Affiliations

  • Tianxiao Huan
    • 1
    • 2
  • Chunyu Liu
    • 1
    • 2
  • Roby Joehanes
    • 1
    • 2
    • 3
    • 4
    • 5
  • Xiaoling Zhang
    • 1
    • 6
  • Brian H. Chen
    • 1
    • 2
  • Andrew D. Johnson
    • 1
    • 6
  • Chen Yao
    • 1
    • 2
  • Paul Courchesne
    • 1
    • 2
  • Christopher J. O’Donnell
    • 1
    • 6
  • Peter J. Munson
    • 3
  • Daniel Levy
    • 1
    • 2
  1. 1.Framingham Heart Study, Population Sciences BranchNational Heart, Lung and Blood InstituteFraminghamUSA
  2. 2.Division of Intramural Research, Population Sciences BranchNational Heart, Lung and Blood InstituteBethesdaUSA
  3. 3.Division of Computational Bioscience, Mathematical and Statistical Computing Laboratory, Center for Information TechnologyNational Institutes of HealthBethesdaUSA
  4. 4.Harvard Medical SchoolBostonUSA
  5. 5.Hebrew SeniorLifeBostonUSA
  6. 6.Division of Intramural Research, Cardiovascular Epidemiology and Human Genomics BranchNational Heart, Lung and Blood InstituteBethesdaUSA

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