Skip to main content

eQTL Analysis in Humans

  • Protocol
  • First Online:
Cardiovascular Genomics

Part of the book series: Methods in Molecular Biology™ ((MIMB,volume 573))

Abstract

Improving human health is a major aim of medical research, but it requires that variation between individuals be taken into account since each person carries a different combination of gene variants and is exposed to different environmental conditions, which can cause differences in susceptibility to diseases. With the advent of molecular markers in the 1980s, it became possible to genotype individuals (i.e., to detect the presence or absence of local DNA sequence variants at each of hundreds of genome positions). This DNA sequence variation could then be related to disease susceptibility by using pedigree data. Such linkage analyses proved to be difficult for more complex diseases. Recently, with the decreasing costs of genotyping, analyses of large natural populations of unrelated individuals became possible and resulted in the association of many genes (and genetic variants in these genes) with complex diseases. Unfortunately, for a considerable proportion of these genes and their proteins, it is not yet clear what their downstream effects are. Studying the expression of these genes and proteins can help to uncover the effects of these variants on the expression of these and other genes, proteins, metabolites, and phenotypes. In this chapter, we focus on the high-throughput and genome-wide measurement of gene expression in a natural population of unrelated humans, and on the subsequent association of variation in expression to “expression quantitative trait loci” (eQTLs) on DNA using oligonucleotide arrays with hundreds of thousands of single-nucleotide polymorphism (SNP) markers that capture most of the human genetic variation well. This strategy has been successfully applied to several diseases such as celiac disease (Hunt et al. 2008, Nat Genet 40, 395–402) and asthma (Moffatt et al. 2007, Nature 448, 470–473): associated genetic variants have been identified that affect levels of gene expression in cis or in trans, providing insight into the biological pathways affected by these diseases.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Protocol
USD 49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 109.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 139.00
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 199.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Dixon, AL, Liang, L, Moffatt, MF, et al. (2007) A genome-wide association study of global gene expression. Nat Genet 39, 1202–1207.

    Article  PubMed  CAS  Google Scholar 

  2. Goring, HH, Curran, JE, Johnson, MP, et al. (2007) Discovery of expression QTLs using large-scale transcriptional profiling in human lymphocytes. Nat Genet 39, 1208–1216.

    Article  PubMed  Google Scholar 

  3. Kwan, T, Benovoy, D, Dias, C, et al. (2008) Genome-wide analysis of transcript isoform variation in humans. Nat Genet 451, 359–362.

    Article  Google Scholar 

  4. Morley, M, Molony, CM, Weber, TM, et al. (2004) Genetic analysis of genome-wide variation in human gene expression. Nature 430, 743–747.

    Article  PubMed  CAS  Google Scholar 

  5. Stranger, BE, Forrest, MS, Dunning, M, et al. (2007) Relative impact of nucleotide and copy number variation on gene expression phenotypes. Science (New York, NY) 315, 848–853.

    Article  PubMed  CAS  Google Scholar 

  6. Stranger, BE, Nica, AC, Forrest, MS, et al. (2007) Population genomics of human gene expression. Nat Genet 39, 1217–1224.

    Article  PubMed  CAS  Google Scholar 

  7. Frazer, KA, Ballinger, DG, Cox, DR, et al. (2007) A second generation human haplotype map of over 3.1 million SNPs. Nature 449, 851–861.

    Article  PubMed  CAS  Google Scholar 

  8. Dai, M, Wang, P, Boyd, AD, et al. (2005) Evolving gene/transcript definitions significantly alter the interpretation of GeneChip data. Nucleic Acids Res 33, e175.

    Article  PubMed  Google Scholar 

  9. Bolstad, BM, Irizarry, RA, Astrand, M, et al. (2003) A comparison of normalization methods for high density oligonucleotide array data based on variance and bias. Bioinformatics (Oxford, England) 19, 185–193.

    Article  PubMed  CAS  Google Scholar 

  10. Hunt, KA, Zhernakova, A, Turner, G, et al. (2008) Newly identified genetic risk variants for celiac disease related to the immune response. Nat Genet 40, 395–402.

    Article  PubMed  CAS  Google Scholar 

  11. Moffatt, MF, Kabesch, M, Liang, L, et al. (2007) Genetic variants regulating ORMDL3 expression contribute to the risk of childhood asthma. Nature 448, 470–473.

    Article  PubMed  CAS  Google Scholar 

  12. Heap, GA, Trynka, G, Jansen, RC, et al. (2009) Complex nature of SNP genotype effects on gene expression in primary human leucocytes. BMC Med Genomics 7, 2:1.

    Google Scholar 

  13. Stranger, BE, Forrest, MS, Clark, AG, et al. (2005) Genome-wide associations of gene expression variation in humans. PLoS Genet 1, e78.

    Article  PubMed  Google Scholar 

  14. Alberts, R, Terpstra, P, Li, Y, et al. (2007) Sequence polymorphisms cause many false cis eQTLs. PLoS ONE 2, e622.

    Article  PubMed  Google Scholar 

  15. Franke, L, van Bakel, H, Fokkens, L. et al. (2006) Reconstruction of a functional human gene network, with an application for prioritizing positional candidate genes. Am J Hum Genet 78, 1011–1025.

    Article  PubMed  CAS  Google Scholar 

  16. Breitling, R, Li, Y, Tesson, BM, et al. (2008) Genetical genomics: spotlight on QTL Hotspots. PLoS Genet 10, e1000232.

    Article  Google Scholar 

  17. Myers, AJ, Gibbs, JR, Webster, JA, et al. (2007) A survey of genetic human cortical gene expression. Nat Genet 39, 1494–1499.

    Article  PubMed  CAS  Google Scholar 

  18. Whitlock, MC. (2005) Combining probability from independent tests: the weighted Z-method is superior to Fisher's approach. J Evol Biol 18, 1368–1373.

    Article  PubMed  CAS  Google Scholar 

  19. Marchini, J, Howie, B, Myers, S, et al. (2007) A new multipoint method for genome-wide association studies by imputation of genotypes. Nat Genet 39, 906–913.

    Article  PubMed  CAS  Google Scholar 

  20. Purcell, S, Neale, B, Todd-Brown, K, et al. (2007) PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet 81, 559–575.

    Article  PubMed  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Humana Press, a part of Springer Science+Business Media, LLC

About this protocol

Cite this protocol

Franke, L., Jansen, R.C. (2009). eQTL Analysis in Humans. In: DiPetrillo, K. (eds) Cardiovascular Genomics. Methods in Molecular Biology™, vol 573. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-60761-247-6_17

Download citation

  • DOI: https://doi.org/10.1007/978-1-60761-247-6_17

  • Published:

  • Publisher Name: Humana Press, Totowa, NJ

  • Print ISBN: 978-1-60761-246-9

  • Online ISBN: 978-1-60761-247-6

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics