Skip to main content
SpringerLink
Log in

Joint oligogenic segregation and linkage analysis using bayesian Markov chain Monte Carlo methods

  • Review
  • Published:
Molecular Biotechnology Aims and scope Submit manuscript

Abstract

One of the most challenging areas in human genetics is the dissection of quantitative traits. In this context, the efficient use of available data is important, including, when possible, use of large pedigrees and many markers for gene mapping. In addition, methods that jointly perform linkage analysis and estimation of the trait model are appealing because they combine the advantages of a model-based analysis with the advantages of methods that do not require prespecification of model parameters for linkage analysis. Here we review a Markov chain Monte Carlo approach for such joint linkage and segregation analysis, which allows analysis of oligogenic traits in the context of multipoint linkage analysis of large pedigrees. We provide an outline for practitioners of the salient features of the method, interpretation of the results, effect of violation of assumptions, and an example analysis of a two-locus trait to illustrate the method.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Elston, R., Buxbaum, S., Jacobs, K., and Olson, J. (2000) Haseman and Elston revisited. Genet. Epidemiol. 19, 1–17.

    Article  PubMed  CAS  Google Scholar 

  2. Amos, C. I. (1994) Robust variance-components approach for assessing genetic linkage in pedigrees. Am. J. Hum. Genet. 54, 535–543.

    PubMed  CAS  Google Scholar 

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

    Article  PubMed  CAS  Google Scholar 

  4. Forrest, W. and Feingold, E. (2000) Composite statistics for QTL mapping with moderately discordant sibling pairs. Am. J. Hum. Genet. 66, 1642–1660.

    Article  PubMed  CAS  Google Scholar 

  5. Bethony, J., Williams, J., Almasy, L., Correa-Oliveira, R., Blangero, J., and Williams-Blangero, S. (2001) Genetic analysis of quantitative traits in highly ascertained samples: total serum IgE in families with asthma. Genet. Epidemiol. 21(Suppl 1), S174-S179.

    PubMed  Google Scholar 

  6. Wijsman, E. M. and Amos, C. (1997) Genetic analysis of simulated oligogenic traits in nuclear and extended pedigrees: summary of GAW10 contributions. Genet. Epidemiol. 14, 719–735.

    Article  PubMed  CAS  Google Scholar 

  7. Atwood, L. and Heard-Costa, N. (2003) Limits of fine-mapping a quantitative trait. Genet. Epidemiol. 24, 99–106.

    Article  PubMed  Google Scholar 

  8. Morton, N. E. (1955) Sequential tests for the detection of linkage. Am. J. Hum. Genet. 7, 277–318.

    PubMed  CAS  Google Scholar 

  9. Schork, N. J., Boehnke, M., Terwilliger, J. D., and Ott, J. (1993) Two-trait-locus linkage analysis: a powerful strategy for mapping complex genetic traits. Am. J. Hum. Genet. 53, 1127–1136.

    PubMed  CAS  Google Scholar 

  10. Clerget-Darpoux, F., Bonaiti-Pellie, C., and Hochez, J. (1986) Effects of misspecifying genetic parameters in LOD score analysis. Biometrics 42, 393–399.

    Article  PubMed  CAS  Google Scholar 

  11. Risch, N. and Giuffra, L. (1992) Model misspecification and multipoint linkage analysis. Hum. Hered. 42, 77–92.

    PubMed  CAS  Google Scholar 

  12. Lander, E. S. and Green, P. (1987) Construction of multilocus genetic maps in humans. Proc. Nat. Acad. Sci. USA 84, 2363–2367.

    Article  PubMed  CAS  Google Scholar 

  13. Elston, R. C. and Stewart, J. (1971) A general model for the genetic analysis of pedigree data. Hum. Hered. 21, 523–542.

    PubMed  CAS  Google Scholar 

  14. Gagnon, F., Jarvik, G., Motulsky, A., Deeb, S., Brunzell, J., and Wijsman, E. (2003) Evidence of linkage of HDL level variation to APOC3 in two samples with different ascertainment. Hum. Genet. 113, 522–533.

    Article  PubMed  CAS  Google Scholar 

  15. Green, P. J. (1995) Reversible jump Markov chain Monte Carlo computation and Bayesian model determination. Biometrika 82, 711–732.

    Article  Google Scholar 

  16. Wijsman, E. M. (2002) Joint segregation and linkage analysis using Markov chain Monte Carlo methods. In Quantitative Trait Loci: Methods and Protocols, vol. 195 (Camp, N., and Cox, A., eds.). Humana, Totowa, NJ, pp. 139–161.

    Google Scholar 

  17. Heath, S. C., Snow, G. L., Thompson, E. A., Tseng, C., and Wijsman, E. M. (1997) MCMC segregation and linkage analysis. Genet. Epidemiol. 14, 1011–1016.

    Article  PubMed  CAS  Google Scholar 

  18. Thompson, E. (2000) MCMC estimation of multilocus genome sharing and multipoint gene location scores. Int. Stat. Rev. 68, 53–73.

    Article  Google Scholar 

  19. George, A., Basu, S., Li, N., Rothstein, J., Sieberts, S., Stewart, W., Wijsman, E., and Thompson, E. (2003) Approaches to mapping genetically correlated complex traits. BMC Genet. 4, 71.

    Article  Google Scholar 

  20. Uimari, P. and Sillanpaa, M. (2001) Bayesian oligogenic analysis of quantitative and qualitative traits in general pedigrees. Genet. Epidemiol. 21, 224–242.

    Article  PubMed  CAS  Google Scholar 

  21. Bink, M. (2002) On flexible finite polygenic models for multiple-trait evaluation. Genet. Res. 80, 245–256.

    Article  PubMed  CAS  Google Scholar 

  22. Heath, S. C. (1997) Markov Chain Monte Carlo Segregation and linkage analysis for oligogenic models. Am. J. Hum. Genet. 61, 748–760.

    PubMed  CAS  Google Scholar 

  23. Shmulewitz, D., and Health, S. C. (2001) Genome scans for Q1 and Q2 on general population replicates using Loki. Genet. Epidemiol. 21(Suppl 1), S686-S691.

    PubMed  Google Scholar 

  24. Daw, E. W., Heath, S. C., and Wijsman, E. M. (1999) Multipoint oligogenic analysis of age-at-onset data with applications to Alzheimer’s disease pedigrees. Am. J. Hum. Genet. 64, 839–851.

    Article  PubMed  CAS  Google Scholar 

  25. Yuan, B., Neuman, R., Duan, S., et al. (2000) Linkage of a gene for familial hypobetalipoproteinemia to chromosome 3p21.1-22. Am. J. Hum. Genet. 66, 1699–1704.

    Article  PubMed  CAS  Google Scholar 

  26. Knoblauch, H., Müller-Myhsok, B., Busjahn, A., et al. (2000) A cholesterol-lowering gene maps to chromosome 13q. Am. J. Hum. Genet. 66, 157–166.

    Article  PubMed  CAS  Google Scholar 

  27. Wijsman, E. (2003) Summary of group 8: development and extension of linkage methods. Genet. Epidemiol. 25(Suppl 1), S64-S71.

    Article  PubMed  Google Scholar 

  28. Sillanpaa, M. and Arjas, E. (1999) Bayesian mapping of multiple quantitative trait loci from incomplete outbred offspring data. Genetics 151, 1605–1619.

    PubMed  CAS  Google Scholar 

  29. Falconer, D. S. (1995) Introduction to quantitative genetics. Longman, Harlow, Essex, UK.

    Google Scholar 

  30. Haldane, J. B. S. (1919) The combination of linkage values, and the calculation of distance between the loci of linked factors. J. Genet. 8, 299–309.

    Article  Google Scholar 

  31. Sobel, E., Sengul, H., and Weeks, D. (2001) Multipoint estimation of identity-by-descent probabilities at arbitrary positions among marker loci on general pedigrees. Hum. Hered. 52, 121–131.

    Article  PubMed  CAS  Google Scholar 

  32. Göring, H., Williams, J., Dyer, T., and Blangero, J. (2003) On different approximations to multilocus identity-by-descent calculations and the resulting power of variance component-based linkage analysis. BMC Genet. 4(Suppl), 72.

    Article  Google Scholar 

  33. Hastings, W. K. (1970) Monte Carlo sampling methods using Markov chains and their applications. Biometrika 57, 97–109.

    Article  Google Scholar 

  34. Geman, S. and Geman, D. (1984) Stochastic relaxation, Gibbs distributions and the Bayesian restoration of images. IEEE Trans. Patt. Anal. Mach. Intell. 6, 721–741.

    Google Scholar 

  35. Gilks, W. R. (1996) Markov Chain Monte Carlo in practice. Chapman and Hall, New York.

    Google Scholar 

  36. Lin, S., Thompson, E. A., and Wijsman, E. (1993) Achieving irreducibility of the Markov chain Monte Carlo method applied to pedigree data. IMA J. Math. Appl. Med. Biol. 10, 1–17.

    Article  PubMed  CAS  Google Scholar 

  37. Thomspon, E. and Heath, S. (1999) Estimation of conditional multilocus gene identity among relatives. In 1998 Joint AMS-IMS-SIAM Summer Conference on Statistics in Molecular Biology, IMS Lecture Note-Monograph Series, vol. 33 (Seillier-Moiseiwitsch, F., ed.). Institute of Mathematical Statistics, Bethesda, MD, pp. 95–113.

    Google Scholar 

  38. George, A. and Thomspon, E. (2004) Discovering disease genes: multipoint linkage analysis via a new Markov chain Monte Carlo approach. Statistical Science, in press.

  39. Corder, E. H., Lannfelt, L., Bogdanovic, N., Fratiglioni, L., and Mori, H. (1998) The role of APOE polymorphisms in late-onset dementias. Cell. Mol. Life Sci. 54, 928–934.

    Article  PubMed  CAS  Google Scholar 

  40. Daw, E. W., Payami, H., Nemens, E. J., Nochlin, D., Bird, T. D., Schellenberg, G. D., and Wijsman, E. M. (2000) The number of trait loci in late-onset Alzheimer disease. Am. J. Hum. Genet. 66, 196–204.

    Article  PubMed  CAS  Google Scholar 

  41. Daw, E., Wijsman, E., and Thompson, E. (2003) A score for Bayesian genome screening. Genet. Epidemiol. 24, 181–190.

    Article  PubMed  Google Scholar 

  42. Kass, R. and Raftery, A. (1995) Bayes factors. J. Am. Stat. Assoc. 90, 773–795.

    Article  Google Scholar 

  43. Ott, J. (1992) Strategies for characterizing highly polymorphic markers in human gene mapping. Am. J. Hum. Genet. 51, 283–290.

    PubMed  CAS  Google Scholar 

  44. Buetow, K. (1991) Influence of aberrant observations on high-resolution linkage analysis outcomes. Am. J. Hum. Genet. 49, 985–994.

    PubMed  CAS  Google Scholar 

  45. Daw, E., Thompson, E., and Wijsman, E. (2000) Bias in multipoint linkage analysis arising from map misspecification. Genet. Epidemiol. 19, 336–380.

    Article  Google Scholar 

  46. Halpern, J. and Whittemore, A. S. (1999) Multipoint linkage analysis: A cautionary note. Hum. Hered. 49, 194–196.

    Article  PubMed  CAS  Google Scholar 

  47. Cherny, S., Abecasis, G., Cookson, W., Sham, P., and Cardon, L. (2001) The effect of genotype and pedigree error on linkage analysis. Genet. Epidemiol. 21(Suppl 1), S117-S122.

    PubMed  Google Scholar 

  48. Knapp, M., Seuchter, S., and Baur, M. (1993) The effect of misspecifying allele frequencies in incompletely typed families. Genet. Epidemiol. 10, 413–418.

    Article  PubMed  CAS  Google Scholar 

  49. Boehnke, M. and Cox, N. (1997) Accurate inference of relationships in sib-pair linkage studies. Am. J. Hum. Genet. 61, 423–429.

    PubMed  CAS  Google Scholar 

  50. Sieberts, S., Thompson, E., and Wijsman, E. (2002) Relationship inference from trios of individuals in the presence of typing error. Am. J. Hum. Genet. 70, 170–180.

    Article  PubMed  CAS  Google Scholar 

  51. Abecasis, G., Cherny, S., Cookson, W., and Cardon, L. (2002) Merlin-rapid analysis of dense genetic maps using sparse gene flow trees. Nat. Genet. 30, 97–101.

    Article  PubMed  CAS  Google Scholar 

  52. Rosenthal, E., and Wijsman, E. (2003) MCMC analysis of complex traits caused by multiallelic loci. Am. J. Hum. Genet. 73, 1935.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Division of Medical Genetics, University of Washington, Box 357720, 98195-7720, Seattle, WA

    Ellen M. Wijsman

  2. Department of Biostatistics, University of Washington, Box 357720, 98195-7720, Seattle, WA

    Ellen M. Wijsman & Dongmei Yu

Authors
  1. Ellen M. Wijsman
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Dongmei Yu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ellen M. Wijsman.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Wijsman, E.M., Yu, D. Joint oligogenic segregation and linkage analysis using bayesian Markov chain Monte Carlo methods. Mol Biotechnol 28, 205–226 (2004). https://doi.org/10.1385/MB:28:3:205

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1385/MB:28:3:205

Index Entries

Search

Navigation