Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Opinion
  • Published:

Epistasis: too often neglected in complex trait studies?

Nature Reviews Genetics volume 5, pages 618–625 (2004)Cite this article

Abstract

Interactions among loci or between genes and environmental factors make a substantial contribution to variation in complex traits such as disease susceptibility. Nonetheless, many studies that attempt to identify the genetic basis of complex traits ignore the possibility that loci interact. We argue that epistasis should be accounted for in complex trait studies; we critically assess current study designs for detecting epistasis and discuss how these might be adapted for use in additional populations, including humans.

Access through your institution
Buy or subscribe

This is a preview of subscription content, access via your institution

Access options

Access through your institution

Buy this article

  • Purchase on SpringerLink
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Principles of individual quantitative trait loci and epistatic quantitative trait locus mapping.
Figure 2: Comparing the results of searches for epistatic and individual quantitative trait loci.
Figure 3: Proposed framework for acquiring confidence in quantitative trait loci.

Similar content being viewed by others

References

  1. Phillips P. C. The language of gene interaction. Genetics 149, 1167–1171 (1998).

    CAS  PubMed  PubMed Central  Google Scholar 

  2. Hummel, K. P. The inheritance and expression of Disorganization, an unusual mutation in the mouse. J. Exp. Zool. 137, 389–423 (1958).

    Article  CAS  PubMed  Google Scholar 

  3. Tiret, L. et al. Synergistic effects of angiotensin-converting enzyme and angiotensin-II type 1 receptor gene polymorphisms on risk of myocardial infarction. Lancet 344, 910–913 (1994).

    Article  CAS  PubMed  Google Scholar 

  4. Flint, J. & Mott, R. Finding the molecular basis of quantitative traits: successes and pitfalls. Nature Rev. Genet. 2, 437–445 (2001).

    Article  CAS  PubMed  Google Scholar 

  5. Barton, N. H. & Keightley, P. D. Understanding quantitative genetic variation. Nature Rev. Genet. 3, 11–21 (2002).

    Article  CAS  PubMed  Google Scholar 

  6. Doerge, R. W. Mapping and analysis of quantitative trait loci in experimental populations. Nature Rev. Genet. 3, 43–52 (2002).

    Article  CAS  PubMed  Google Scholar 

  7. Jansen, R. C. Studying complex biological systems using multifactorial perturbation. Nature Rev. Genet. 4, 145–151 (2003).

    Article  CAS  PubMed  Google Scholar 

  8. Hoh, J. & Ott, J. Mathematical multi-locus approaches to localizing complex human trait genes. Nature Rev. Genet. 4, 701–709 (2003).

    Article  CAS  PubMed  Google Scholar 

  9. Hirschhorn, J. N., Lohmueller, K., Byrne, E. & Hirschhorn, K. A comprehensive review of genetic association studies. Genet. Med. 4, 45–61 (2002).

    Article  CAS  PubMed  Google Scholar 

  10. Lander, E. S. & Botstein, D. Mapping Mendelian factors underlying quantitative traits using RFLP linkage maps. Genetics 121, 185–199 (1989).

    CAS  PubMed  PubMed Central  Google Scholar 

  11. Haseman, J. K. & Elston, R. C. The investigation of linkage between a quantitative trait and a marker locus. Behav. Genet. 2, 3–19 (1972).

    Article  CAS  PubMed  Google Scholar 

  12. Andersson, L. & Georges, M. Domestic-animal genomics: deciphering the genetics of complex traits. Nature Rev. Genet. 5, 202–212 (2004).

    Article  CAS  PubMed  Google Scholar 

  13. Mackay, T. F. Quantitative trait loci in Drosophila. Nature Rev. Genet. 1, 11–20 (2001).

    Article  Google Scholar 

  14. Grobet, L. et al. A deletion in the bovine myostatin gene causes the double-muscled phenotype in cattle. Nature Genet. 17, 71–74 (1997).

    Article  CAS  PubMed  Google Scholar 

  15. van Laere, A. S. et al. A regulatory mutation in IGF2 causes a major QTL effect on muscle growth in the pig. Nature 425, 832–836 (2003).

    Article  CAS  PubMed  Google Scholar 

  16. Fijneman, R. J., de Vries, S. S., Jansen, R. C. & Demant, P. Complex interactions of new quantitative trait loci, Sluc1, Sluc2, Sluc3, and Sluc4, that influence the susceptibility to lung cancer in the mouse. Nature Genet. 14, 465–467 (1996).

    Article  CAS  PubMed  Google Scholar 

  17. Long, A. D., Mullaney, S. L., Mackay, T. F. & Langley, C. H. Genetic interactions between naturally occurring alleles at quantitative trait loci and mutant alleles at candidate loci affecting bristle number in Drosophila melanogaster. Genetics 144, 1497–1510 (1996).

    CAS  PubMed  PubMed Central  Google Scholar 

  18. Li, Z., Pinson, S. R., Park, W. D., Paterson, A. H. & Stansel, J. W. Epistasis for three grain yield components in rice (Oryza sativa L.). Genetics 145, 453–465 (1997).

    CAS  PubMed  PubMed Central  Google Scholar 

  19. Shook, D. R. & Johnson, T. E. Quantitative trait loci affecting survival and fertility-related traits in Caenorhabditis elegans show genotype-environment interactions, pleiotropy and epistasis. Genetics 153, 1233–1243 (1999).

    CAS  PubMed  PubMed Central  Google Scholar 

  20. Morel, L. et al. Genetic reconstitution of systemic lupus erythematosus immunopathology with polycongenic murine strains. Proc. Natl Acad. Sci.USA 97, 6670–6675 (2000).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Stern M. P. et al. Evidence for linkage of regions on chromosomes 6 and 11 to plasma glucose concentrations in Mexican Americans. Genome Res. 6, 724–734 (1996).

    Article  CAS  PubMed  Google Scholar 

  22. Kao, C. -H., Zeng, Z. -B. & Teasdale, R. Multiple interval mapping for quantitative trait loci. Genetics 152, 1203–1216 (1999).

    CAS  PubMed  PubMed Central  Google Scholar 

  23. Sen, S. & Churchill, G. A. A statistical framework for quantitative trait mapping. Genetics 159, 371–387 (2001).

    CAS  PubMed  PubMed Central  Google Scholar 

  24. Carlborg, Ö. & Andersson, L. The use of randomisation testing for detection of multiple epistatic QTL. Genet. Res. 79, 175–184 (2002).

    Article  PubMed  Google Scholar 

  25. Yi, N., Xu, S. & Allison, D. B. Bayesian model choice and search strategies for mapping interacting quantitative trait loci. Genetics 165, 867–883 (2003).

    CAS  PubMed  PubMed Central  Google Scholar 

  26. Carlborg, Ö. et al. A global search reveals epistatic interaction between QTLs for early growth in the chicken. Genome Res. 13, 413–421 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Carlborg, Ö., Burt, D., Hocking, P. & Haley, C. S. Simultaneous mapping of epistatic QTL in chickens reveals clusters of QTL pairs with similar genetic effects on growth. Genet. Res. (in the press).

  28. Kim, J. H. et al. Genetic analysis of a new mouse model for non-insulin-dependent diabetes. Genomics 74, 273–286 (2001).

    Article  CAS  PubMed  Google Scholar 

  29. Shimomura, K. et al. Genome-wide epistatic interaction analysis reveals complex genetic determinants of circadian behavior in mice. Genome Res. 11, 959–980 (2001).

    Article  CAS  PubMed  Google Scholar 

  30. Sugiyama, F. et al. Concordance of murine quantitative trait loci for salt-induced hypertension with rat and human loci. Genomics 71, 70–77 (2001).

    Article  CAS  PubMed  Google Scholar 

  31. Peripato, A. C. et al. Quantitative trait loci for maternal performance for offspring survival in mice. Genetics 162, 1341–1353 (2002).

    CAS  PubMed  PubMed Central  Google Scholar 

  32. Ways, J. A., Cicila, G. T., Garrett, M. R. & Koch, L. G. A genome scan for loci associated with aerobic running capacity in rats. Genomics 80, 13–20 (2002).

    Article  CAS  PubMed  Google Scholar 

  33. Montooth, K. L., Marden, J. H. & Clark, A. G. Mapping determinants of variation in energy metabolism, respiration and flight in Drosophila. Genetics 165, 623–635 (2003).

    CAS  PubMed  PubMed Central  Google Scholar 

  34. Eshed, Y. & Zamir, D. Less-than-additive epistatic interactions of quantitative trait loci in tomato. Genetics 143, 1807–1817 (1996).

    CAS  PubMed  PubMed Central  Google Scholar 

  35. Flint, J., DeFries, J. C. & Henderson, N. D. Little epistasis for anxiety-related measures in the DeFries strains of laboratory mice. Mamm. Genome 15, 77–82 (2004).

    Article  PubMed  Google Scholar 

  36. Smith Richards, B. K. et al. QTL analysis of self-selected macronutrient diet intake: fat, carbohydrate, and total kilocalories. Physiol. Genomics 11, 205–217.

  37. Zeng, Z-. B. et al. Genetic architecture of a morphological shape difference between two Drosophila species. Genetics 154, 299–310 (2000).

    CAS  PubMed  PubMed Central  Google Scholar 

  38. Beavis, W. D. in Molecular Dissection of Complex Traits (ed. Paterson, A. H.) 145–162 (CRC, New York, 1998).

    Google Scholar 

  39. Cordell, H. J. et al. Statistical modeling of interlocus interactions in a complex disease: rejection of the multiplicative model of epistasis in type 1 diabetes. Genetics 158, 357–367 (2001).

    CAS  PubMed  PubMed Central  Google Scholar 

  40. Risch, N., Ghosh, S. & Todd, J. A. Statistical evaluation of multiple-locus linkage data in experimental species and its relevance to human studies: application to nonobese diabetic (NOD) mouse and human insulin-dependent diabetes mellitus (IDDM). Am. J. Hum. Genet. 53, 702–714 (1993).

    CAS  PubMed  PubMed Central  Google Scholar 

  41. Cheverud, J. M. et al. Genetic architecture of adiposity in the cross of LG/J and SM/J inbred mice. Mamm. Genome 12, 3–12 (2001).

    Article  CAS  PubMed  Google Scholar 

  42. Omholt, S. W., Plahte, E., Oyehaug, L. & Xiang, K. Gene regulatory networks generating the phenomena of additivity, dominance and epistasis. Genetics 155, 969–980 (2000).

    CAS  PubMed  PubMed Central  Google Scholar 

  43. Walling, G. A. et al. Combined analyses of data from QTL mapping studies: chromosome 4 effects on porcine growth and fatness. Genetics 155, 1369–1378 (2000).

    CAS  PubMed  PubMed Central  Google Scholar 

  44. Cordell, H. J., Todd, J. A., Bennett, S. T., Kawaguchi, Y. & Farrall, M. Two-locus maximum lod score analysis of a multifactorial trait: joint consideration of IDDM2 and IDDM4 with IDDM1 in type 1 diabetes. Am. J. Hum. Genet. 57, 920–934 (1995).

    CAS  PubMed  PubMed Central  Google Scholar 

  45. Cox, N. J. et al. Loci on chromosomes 2 (NIDDM1) and 15 interact to increase susceptibility to diabetes in Mexican Americans. Nature Genet. 21, 213–215 (1999).

    Article  CAS  PubMed  Google Scholar 

  46. Cho, J. H. et al. Identification of novel susceptibility loci for inflammatory bowel disease on chromosomes 1p, 3q, and 4q: evidence for epistasis between 1p and IBD1. Proc. Natl Acad. Sci. USA 95, 7502–7507 (1998).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. The International HapMap Consortium. The International HapMap Project. Nature 426, 789–796 (2003).

  48. Van Den Oord, E. J. & Neale, B. M. Will haplotype maps be useful for finding genes? Mol. Psychiatry 9, 227–236 (2004).

    Article  CAS  PubMed  Google Scholar 

  49. Blangero, J. & Almasy, L. Multipoint oligogenic linkage analysis of quantitative traits. Genet. Epidemiol. 14, 959–964 (1997).

    Article  CAS  PubMed  Google Scholar 

  50. Eaves, L. J. Effect of genetic architecture on the power of human linkage studies to resolve the contribution of quantitative trait loci. Heredity 72, 175–192 (1994).

    Article  PubMed  Google Scholar 

  51. Mitchell, B. D., Ghosh, S., Schneider, J. L., Birznieks, G. & Blangero, J. Power of variance component linkage analysis to detect epistasis. Genet. Epidemiol. 14, 1017–1022 (1997).

    Article  CAS  PubMed  Google Scholar 

  52. van den Oord, E. J. & Sullivan, P. F. False discoveries and models for gene discovery. Trends Genet. 19, 537–542 (2003).

    Article  CAS  PubMed  Google Scholar 

  53. Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. 57, 289–300 (1995).

    Google Scholar 

  54. Drawid, A. & Gerstein M. A Bayesian system integrating expression data with sequence patterns for localizing proteins: comprehensive application to the yeast genome. J. Mol. Biol. 301, 1059–1075 (2000).

    Article  CAS  PubMed  Google Scholar 

  55. Jenssen, T. K., Laegreid, A., Komorowski, J. & Hovig, E. A literature network of human genes for high-throughput analysis of gene expression. Nature Genet. 28, 21–28 (2001).

    CAS  PubMed  Google Scholar 

  56. Andersson, L. Genetic dissection of phenotypic diversity in farm animals. Nature Rev. Genet. 2, 130–138 (2001).

    Article  CAS  PubMed  Google Scholar 

  57. Kijas, J. M. et al. Melanocortin receptor 1 (MC1R) mutations and coat color in pigs. Genetics 150, 1177–1185 (1998).

    CAS  PubMed  PubMed Central  Google Scholar 

  58. Haley, C. S. & Knott, S. A. A simple regression method for mapping quantitative trait loci in line crosses using flanking markers. Heredity 69, 315–324 (1992).

    Article  CAS  PubMed  Google Scholar 

  59. Cheverud, J. M. & Routman, E. J. Epistasis and its contribution to genetic variance components. Genetics 139, 1455–1461 (1995).

    CAS  PubMed  PubMed Central  Google Scholar 

  60. Chase, K., Adler, F. R. & Lark, K. G. Epistat: a computer program for identifying and testing interactions between pairs of quantitative trait loci. Theor. Appl. Genet. 94, 724–730 (1997).

    Article  Google Scholar 

  61. Schaid, D. J. General score tests for associations of genetic markers with disease using cases and their parents. Genet. Epidemiol. 13, 423–449 (1996).

    Article  CAS  PubMed  Google Scholar 

  62. Umbach, D. M. & Weinberg, C. R. Designing and analysing case–control studies to exploit independence of genotype and exposure. Stat. Med. 16, 1731–1743 (1997).

    Article  CAS  PubMed  Google Scholar 

  63. Rabinowitz, D. A transmission disequilibrium test for quantitative trait loci. Hum. Hered. 47, 342–350 (1997).

    Article  CAS  PubMed  Google Scholar 

  64. Almasy, L. & Blangero, J. Multipoint quantitative-trait linkage analysis in general pedigrees. Am. J. Hum. Genet. 62, 1198–1211 (1998).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. George, V., Tiwari, H. K., Shu, Y., Zhu, X. & Elston, R. C. Linkage and association analyses of alcoholism using a regression-based transmission/disequilibrium test. Genet. Epidemiol. 17 (Suppl. 1), S157–S161 (1999).

    Article  PubMed  Google Scholar 

  66. Lunetta, K. L., Faraone, S. V., Biederman, J. & Laird, N. M. Family-based tests of association and linkage that use unaffected sibs, covariates, and interactions. Am. J. Hum. Genet. 66, 605–614 (2000).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Liu, Y., Tritchler, D. & Bull, S. B. A unified framework for transmission-disequilibrium test analysis of discrete and continuous traits. Genet. Epidemiol. 22, 26–40 (2002).

    Article  CAS  PubMed  Google Scholar 

  68. Carlborg, Ö., Andersson, L. & Kinghorn, B. The use of a genetic algorithm for simultaneous mapping of multiple interacting quantitative trait loci. Genetics 155, 2003–2010 (2000).

    CAS  PubMed  PubMed Central  Google Scholar 

  69. Ljungberg, K., Holmgren, S. & Carlborg, Ö. Efficient algorithms for quantitative trait loci mapping problems. J. Comput. Biol. 9, 793–804 (2002).

    Article  CAS  PubMed  Google Scholar 

  70. Ljungberg, K., Holmgren, S. & Carlborg Ö. Simultaneous search for multiple QTL using the global optimization algorithm DIRECT. Bioinformatics 25 Mar 2004 (doi:10.1093/bioinformatics/bth175).

  71. Churchill, G. A. & Doerge, R. W. Empirical threshold values for quantitative trait mapping. Genetics 138, 963–971 (1994).

    CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We are grateful to the Biotechnology and Biological Sciences Research Council and to the Knut and Alice Wallenberg Foundation for their support. We thank B. Hill, G. Plastow, J. Cheverud and two anonymous referees for some valuable comments on the manuscript and A. Peripato for helpful assistance with providing data.

Author information

Authors and Affiliations

  1. Linnaeus Centre for Bioinformatics, Uppsala University, BMC, Box 598, Uppsala, SE-751 24, Sweden

    Örjan Carlborg

  2. Department of Genetics and Biometry, Roslin Institute, Roslin, Midlothian, EH25 9PS, UK

    Chris S. Haley

Authors
  1. Örjan Carlborg
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Chris S. Haley
    View author publications

    You can also search for this author inPubMed Google Scholar

Corresponding author

Correspondence to Örjan Carlborg.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Related links

Related links

DATABASES

Entrez

ACE

AGTR1

KIT

MC1R

OMIM

type I diabetes

type II diabetes

FURTHER INFORMATION

Örjan Carlborg's web page

The Roslin Institute

Glossary

ASSOCIATION STUDIES

A set of methods that is used to identify correlations between genetic polymorphisms and expression of phenotypes, such as diseases, in populations.

BOMBAY PHENOTYPE

A rare ABO blood group (Oh) in which the genotype at a locus other than the ABO gene locus makes the individuals seem to have blood type 'O' even if the 'A' or 'B' enzymes are present.

CANDIDATE GENES

Genes in which functional variation is thought to affect the trait under consideration, often on the basis of their physiological role or their effects in other species.

F-PROFILE

A plot of the statistical support (measured by an F-test) for quantitative trait loci at regular intervals throughout the genome.

FALSE DISCOVERY RATE

(FDR). The proportion of false-positive test results out of all positive (significant) tests (note that the FDR is conceptually different to the significance level).

FIRST-ORDER GENETIC INTERACTIONS

Interactions between pairs of genes or quantitative trait loci.

FORWARD SELECTION

A statistical procedure in which a multi-dimensional genome scan is reduced to a series of sequential one-dimensional genome scans.

HAPLOTYPE

The allelic configuration of multiple genetic markers that are present on a single chromosome of a given individual.

MAJOR GENE

A gene that is part of a polygenic or oligogenic system but for which alternative alleles have a large influence on the phenotype.

MARKER-ASSISTED SELECTION

(MAS). Genetic markers are used to indirectly select for specific alleles at closely linked trait loci by directly selecting for the marker.

PENETRANCE

The proportion of individuals with a specific genotype who manifest the genotype at the phenotypic level. For example, if all individuals with a specific disease genotype show the disease phenotype, then the disease is said to be 'completely penetrant'.

QUANTITATIVE TRAIT

A continuously distributed measurable trait for which variation depends on a single gene or on the cumulative action of many genes and the environment. Common examples include height, weight and blood pressure.

QUANTITATIVE TRAIT LOCUS

(QTL). Genetic loci or chromosomal regions that contribute to variability in complex quantitative traits, as identified by statistical analysis. Quantitative traits are typically affected by several genes and by the environment.

RANDOMIZATION TEST

A statistical test in which statistical significance is judged by comparison to a distribution that is generated by repeated random permutations of the actual data.

RECOMBINANT INBRED LINE

A population of fully homozygous individuals that is obtained by repeated selfing from an F1 hybrid, and that comprises 50% of each parental genome in different combinations.

SIMULTANEOUS SCAN

A multi-dimensional genome scan in which several gene locations are selected simultaneously.

VARIANCE-COMPONENT APPROACH

Quantitative trait locus (QTL) analysis method, suited to complex family structures, in which variance that is attributable to a QTL is estimated rather than the mean effects of alternative genotypes.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Carlborg, Ö., Haley, C. Epistasis: too often neglected in complex trait studies?. Nat Rev Genet 5, 618–625 (2004). https://doi.org/10.1038/nrg1407

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1038/nrg1407

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing