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Cellular genomics for complex traits

Nature Reviews Genetics volume 13, pages 215–220 (2012)Cite this article

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Abstract

Recent developments in the collection and analysis of cellular multilayered data in large cohorts with extensive organismal phenotyping promise to reveal links between genetic variation and biological processes. The use of these cellular resources as models for human biology — known as 'cellular phenotyping' — is likely to transform our understanding of the genetic and long-term environmental influences on complex traits. I discuss the advantages and caveats of a deeper analysis of cellular phenotypes in large cohorts and assess the methodological advances, resource needs and prospects of this new approach.

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Figure 1: Analytical approaches made possible by using cellular phenotypes.
Figure 2: Challenges of dissecting genetic variance.

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References

  1. Gibson, G. The environmental contribution to gene expression profiles. Nature Rev. Genet. 9, 575–581 (2008).

    Article  CAS  Google Scholar 

  2. Idaghdour, Y., Storey, J. D., Jadallah, S. J. & Gibson, G. A genome-wide gene expression signature of environmental geography in leukocytes of Moroccan Amazighs. PLoS Genet. 4, e1000052 (2008).

    Article  Google Scholar 

  3. Dermitzakis, E. T. From gene expression to disease risk. Nature Genet. 40, 492–493 (2008).

    Article  CAS  Google Scholar 

  4. Cheung, V. G. et al. Mapping determinants of human gene expression by regional and genome-wide association. Nature 437, 1365–1369 (2005).

    Article  CAS  Google Scholar 

  5. Stranger, B. E. et al. Genome-wide associations of gene expression variation in humans. PLoS Genet. 1, e78 (2005).

    Article  Google Scholar 

  6. Foss, E. J. et al. Genetic basis of proteome variation in yeast. Nature Genet. 39, 1369–1375 (2007).

    Article  CAS  Google Scholar 

  7. Choy, E. et al. Genetic analysis of human traits in vitro: drug response and gene expression in lymphoblastoid cell lines. PLoS Genet. 4, e1000287 (2008).

    Article  Google Scholar 

  8. Loos, R. J. et al. Common variants near MC4R are associated with fat mass, weight and risk of obesity. Nature Genet. 40, 768–775 (2008).

    Article  CAS  Google Scholar 

  9. Montgomery, S. B., Lappalainen, T., Gutierrez-Arcelus, M. & Dermitzakis, E. T. Rare and common regulatory variation in population-scale sequenced human genomes. PLoS Genet. 7, e1002144 (2011).

    Article  CAS  Google Scholar 

  10. Caliskan, M., Cusanovich, D. A., Ober, C. & Gilad, Y. The effects of EBV transformation on gene expression levels and methylation profiles. Hum. Mol. Genet. 20, 1643–1652 (2011).

    Article  CAS  Google Scholar 

  11. McDaniell, R. et al. Heritable individual-specific and allele-specific chromatin signatures in humans. Science 328, 235–239 (2010).

    Article  CAS  Google Scholar 

  12. Yamanaka, S. Elite and stochastic models for induced pluripotent stem cell generation. Nature 460, 49–52 (2009).

    Article  CAS  Google Scholar 

  13. Gore, A. et al. Somatic coding mutations in human induced pluripotent stem cells. Nature 471, 63–67 (2011).

    Article  CAS  Google Scholar 

  14. Montgomery, S. B. & Dermitzakis, E. T. From expression QTLs to personalized transcriptomics. Nature Rev. Genet. 12, 277–282 (2011).

    Article  CAS  Google Scholar 

  15. Kasowski, M. et al. Variation in transcription factor binding among humans. Science 328, 232–235 (2010).

    Article  CAS  Google Scholar 

  16. Montgomery, S. B. et al. Transcriptome genetics using second generation sequencing in a Caucasian population. Nature 464, 773–777 (2010).

    Article  CAS  Google Scholar 

  17. Pickrell, J. K. et al. Understanding mechanisms underlying human gene expression variation with RNA sequencing. Nature 464, 768–772 (2010).

    Article  CAS  Google Scholar 

  18. Stranger, B. E. et al. Relative impact of nucleotide and copy number variation on gene expression phenotypes. Science 315, 848–853 (2007).

    Article  CAS  Google Scholar 

  19. Gaulton, K. J. et al. A map of open chromatin in human pancreatic islets. Nature Genet. 42, 255–259 (2010).

    Article  CAS  Google Scholar 

  20. Putoux, A. et al. KIF7 mutations cause fetal hydrolethalus and acrocallosal syndromes. Nature Genet. 43, 601–606 (2011).

    Article  CAS  Google Scholar 

  21. Kim, S. et al. Nde1-mediated inhibition of ciliogenesis affects cell cycle re-entry. Nature Cell Biol. 13, 351–360 (2011).

    Article  CAS  Google Scholar 

  22. Duan, S. et al. Expression and alternative splicing of folate pathway genes in HapMap lymphoblastoid cell lines. Pharmacogenomics 10, 549–563 (2009).

    Article  CAS  Google Scholar 

  23. Gamazon, E. R., Huang, R. S., Cox, N. J. & Dolan, M. E. Chemotherapeutic drug susceptibility associated SNPs are enriched in expression quantitative trait loci. Proc. Natl Acad. Sci. USA 107, 9287–9292 (2010).

    Article  CAS  Google Scholar 

  24. Smirnov, D. A., Morley, M., Shin, E., Spielman, R. S. & Cheung, V. G. Genetic analysis of radiation-induced changes in human gene expression. Nature 459, 587–591 (2009).

    Article  CAS  Google Scholar 

  25. Dimas, A. S. & Dermitzakis, E. T. Genetic variation of regulatory systems. Curr. Opin. Genet. Dev. 19, 586–590 (2009).

    Article  CAS  Google Scholar 

  26. Emilsson, V. et al. Genetics of gene expression and its effect on disease. Nature 452, 423–428 (2008).

    Article  CAS  Google Scholar 

  27. Schadt, E. E. Molecular networks as sensors and drivers of common human diseases. Nature 461, 218–223 (2009).

    Article  CAS  Google Scholar 

  28. Schadt, E. E. et al. An integrative genomics approach to infer causal associations between gene expression and disease. Nature Genet. 37, 710–717 (2005).

    Article  CAS  Google Scholar 

  29. Mackay, T. F., Stone, E. A. & Ayroles, J. F. The genetics of quantitative traits: challenges and prospects. Nature Rev. Genet. 10, 565–577 (2009).

    Article  CAS  Google Scholar 

  30. Suhre, K. et al. Human metabolic individuality in biomedical and pharmaceutical research. Nature 477, 54–60 (2011).

    Article  CAS  Google Scholar 

  31. Bell, J. T. et al. DNA methylation patterns associate with genetic and gene expression variation in HapMap cell lines. Genome Biol. 12, R10 (2011).

    Article  CAS  Google Scholar 

  32. Nica, A. C. et al. Candidate causal regulatory effects by integration of expression QTLs with complex trait genetic associations. PLoS Genet. 6, e1000895 (2010).

    Article  Google Scholar 

  33. Nicolae, D. L. et al. Trait-associated SNPs are more likely to be eQTLs: annotation to enhance discovery from GWAS. PLoS Genet. 6, e1000888 (2010).

    Article  Google Scholar 

  34. Lappalainen, T., Montgomery, S. B., Nica, A. C. & Dermitzakis, E. T. Epistatic selection between coding and regulatory variation in human evolution and disease. Am. J. Hum. Genet. 89, 459–463 (2011).

    Article  CAS  Google Scholar 

  35. Bouzakri, K. et al. Bimodal effect on pancreatic β-cells of secretory products from normal or insulin-resistant human skeletal muscle. Diabetes 60, 1111–1121 (2011).

    Article  CAS  Google Scholar 

Download references

Acknowledgements

The author would like to thank the Louis-Jeantet Foundation and the Swiss National Science Foundation for support.

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Authors and Affiliations

  1. Emmanouil T. Dermitzakis is at the Department of Genetic Medicine and Development, University of Geneva Medical School, 1 rue Michel-Servet, 1211 Geneva, Switzerland; and the Institute of Genetics and Genomics in Geneva (iGE3), Geneva, Switzerland.,

    Emmanouil T. Dermitzakis

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  1. Emmanouil T. Dermitzakis
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Correspondence to Emmanouil T. Dermitzakis.

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The author declares no competing financial interests.

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FURTHER INFORMATION

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Nature Reviews Genetics Series on Modelling

NIH Roadmap Genotype-Tissue Expression (GTEx) project

Glossary

Additive

In the context of a genetic effect, the linear relationship between the replacement of an allele and its effect on the phenotype.

Expression quantitative trait loci

(eQTLs). Loci at which genetic allelic variation is associated with variation in gene expression.

Induced pluripotent stem cells

(iPSCs). Cells that are derived from somatic cells by 'reprogramming' or de-differentiation that is triggered by the transfection of pluripotency genes, which alters the somatic cells to a state that is similar to that of embryonic stem cells.

Marginal effects

Also known as main effects, these are the effects of a variable assuming no dependency or conditionality of other variables.

Metabolomics

The directed use of quantitative analytical methods for analysing the entire metabolic content of a cell or organism (that is, the metabolome) at a given time.

Purifying natural selection

Natural selection that results in the reduction or elimination of the frequency of alleles with negative fitness effects.

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Dermitzakis, E. Cellular genomics for complex traits. Nat Rev Genet 13, 215–220 (2012). https://doi.org/10.1038/nrg3115

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