Advertisement

Theoretical and Applied Genetics

, Volume 125, Issue 7, pp 1393–1402 | Cite as

Three-point appraisal of genetic linkage maps

  • W. R. GilksEmail author
  • S. J. Welham
  • J. Wang
  • S. J. Clark
  • G. J. King
Original Paper

Abstract

This paper develops a simple diagnostic for the investigation of uncertainty within genetic linkage maps using a Bayesian procedure. The method requires only the genotyping data and the proposed genetic map, and calculates the posterior probability for the possible orders of any set of three markers, accounting for the presence of genotyping error (mistyping) and for missing genotype data. The method uses a Bayesian approach to give insight into conflicts between the order in the proposed map and the genotype scores. The method can also be used to assess the accuracy of a genetic map at different genomic scales and to assess alternative potential marker orders. Simulation and two case studies were used to illustrate the method. In the first case study, the diagnostic revealed conflicts in map ordering for short inter-marker distances that were resolved at a distance of 8–12 cM, except for a set of markers at the end of the linkage group. In the second case study, the ordering did not resolve as distances increase, which could be attributed to regions of the map where many individuals were untyped.

Keywords

Linkage Group Posterior Probability Doubled Haploid Marker Order High Posterior Probability 
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

The authors are funded by the UK Biotechnology & Biological Sciences Research Council (BBSRC) with project funding to GJK and JW under BBE0177971, and SJW and GJK from Department for Environment Food and Rural Affairs project IF0144 (OREGIN). We would like to thank Jonathan Myles for wrapping our R functions into a package, and two anonymous referees for comments which led to improvements in the algorithm, paper and interpretation of our method.

References

  1. Broman K, Wu H, Sen S, Churchill G (2003) R/qtl: QTL mapping in experimental crosses. Bioinformatics 19:889–890PubMedCrossRefGoogle Scholar
  2. Cartwright D, Troggio M, Velasco R, Gutin A (2007) Genetic mapping in the presence of genotyping errors. Genetics 176:2521–2527. doi: 10.1534/genetics.106.063982 PubMedCrossRefGoogle Scholar
  3. Cheema J, Dicks J (2009) Computational approaches and software tools for genetic linkage map estimation in plants. Briefings Bioinf 10:595–608CrossRefGoogle Scholar
  4. de Givry S, Bouchez M, Chabrier P, Milan D, Schiex T (2005) CARTHAGENE: multipopulation integrated genetic and radiated hybrid mapping. Bioinformatics 21:1703–1704PubMedCrossRefGoogle Scholar
  5. Douglas J, Boehnke M, Lange K (2000) A multipoint method for detecting genotyping errors and mutations in sibling-pair linkage data. Am J Hum Genet 66:1287–1297PubMedCrossRefGoogle Scholar
  6. Ehm MG, Kimmel M, Cottingham J R W (1996) Error detection for genetic data, using likelihood methods. Am J Hum Genet 58:225–234PubMedGoogle Scholar
  7. Gasbarra D, Sillanpää M (2006) Constructing the parental linkage phase and the genetic map over distances <1 cM using pooled haploid DNA. Genetics 172:1325–1335. doi: 10.1534/genetics.105.044271 PubMedCrossRefGoogle Scholar
  8. George A (2005) A novel Markov chain Monte Carlo approach for constructing accurate meiotic maps. Genetics 171:791–801. doi: 10.1534/genetics.105.042705 PubMedCrossRefGoogle Scholar
  9. George A, Mengersen K, Davis G (1999) A Bayesian approach to ordering gene markers. Biometrics 55:419–429PubMedCrossRefGoogle Scholar
  10. Haldane J (1919) The combination of linkage values and the calculation of distance between the loci of linked factors. J Genet 8:299–309CrossRefGoogle Scholar
  11. Jansen J, de Jong A, van Ooijen J (2001) Constructing dense genetic linkage maps. Theor Appl Genet. 102:1113–1122. doi: 10.1007/s001220000489 CrossRefGoogle Scholar
  12. Lander ES, Green P, Abrahamson J, Barlow A, Daly M, Lincoln S, Newburg L (1987) MAPMAKER: an interactive computer package for constructing primary genetic linkage maps of experimental and natural populations. Genomics 1:174–181PubMedCrossRefGoogle Scholar
  13. Lincoln S, Lander E (1992) Systematic detection of errors in genetic linkage data. Genomics 14:604–610PubMedCrossRefGoogle Scholar
  14. Lister C, Dean C (1993) Recombinant inbred lines for mapping RFLP and phenotypic markers in Arabidopsis thaliana. Plant J 4:745–750CrossRefGoogle Scholar
  15. Neumann P (1991) Three-locus linkage analysis using recombinant inbred strains and Bayes’ theorem. Genetics 128:631–638PubMedGoogle Scholar
  16. Qiu D, Morgan C, Shi J, Long Y, Liu J, Li R, Zhuang X, Wang Y, Tan X, Dietrich E, Weihmann T, Everett C, Vanstraelen S, Beckett P, Fraser F, Trick M, Barnes S, Wilmer J, Schmidt R, Li J, Li D, Meng J, Bancroft I (2006) A comparative linkage map of oilseed rape and its use for QTL analysis of seed oil and erucic acid content. Theor Appl Genet 114:67–80PubMedCrossRefGoogle Scholar
  17. Rosa G, Yandell B, Gianola D (2002) A Bayesian approach for constructing genetic maps when markers are miscoded. Genet Sel Evol 34:353–369. doi: 10.1051/gse:2002012 PubMedCrossRefGoogle Scholar
  18. Schiex T, Gaspin C (1997) CarthaGene: constructing and joining maximum likelihood genetic maps. In: Proceedings of the international conference on intelligent systems for molecular biology. AAAI Press (http://www.aaai.org), pp 258–267
  19. Shi J, Li R, Qiu D, Jiang C, Long Y, Morgan C, Bancroft I, Zhao J, Meng J (2009) Unraveling the complex trait of crop yield with quantitative trait loci mapping in Brassica napus. Genetics 182:851–861PubMedCrossRefGoogle Scholar
  20. Sobel E, Papp J, Lange K (2002) Detection and integration of genotyping errors in statistical genetics. Am J Hum Genet 70:496–508PubMedCrossRefGoogle Scholar
  21. Stephens D, Smith A (1993) Bayesian inference in multipoint gene mapping. Ann Hum Genet 57:65–82PubMedCrossRefGoogle Scholar
  22. Stringham HM, Boehnke M (2001) Lod scores for gene mapping in the presence of marker map uncertainty. Genet Epidemiol 21:31–39PubMedCrossRefGoogle Scholar
  23. Van Ooijen J (2006) JoinMap 4. Software for the calculation of genetic linkage maps in experimental populations. Kyazma BV, Wageningen, NetherlandsGoogle Scholar
  24. Wang J, Lydiate D, Parkin I, Falentin C, Delourme R, Carion P, King G (2011) Integration of linkage maps for the amphidiploid Brassica napus and comparative mapping with Arabidopsis and Brassica rapa. BMC Genomics 12:1–20. doi: 10.1186/1471-2164-12-101 PubMedCrossRefGoogle Scholar
  25. Wu Y, Bhat P, Close T, Lonardi S (2008) Efficient and accurate construction of genetic linkage maps from the minimum spanning tree of a graph. PLOS Genetics 4:e1000,212. doi: 10.1371/journal.pgen.1000
  26. York T, Durrett R, Tanksley S, Nielsen R (2005) Bayesian and maximum likelihood estimation of genetic maps. Genet Res 85:159–168. doi: 10.1017/S0016672305007494 PubMedCrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  • W. R. Gilks
    • 1
    • 2
    Email author
  • S. J. Welham
    • 1
    • 3
  • J. Wang
    • 4
    • 5
  • S. J. Clark
    • 1
  • G. J. King
    • 4
    • 6
  1. 1.Department of Computational and Systems BiologyRothamsted ResearchHarpendenUK
  2. 2.Department of Statistics, School of MathematicsUniversity of LeedsLeedsUK
  3. 3.VSN International LtdHemel HempsteadUK
  4. 4.Plant Sciences, Rothamsted ResearchHarpendenUK
  5. 5.Centre for Haemato-Oncology, Institute of CancerBarts and the London School of Medicine and DentistryLondonUK
  6. 6.Southern Cross Plant ScienceSouthern Cross UniversityLismoreAustralia

Personalised recommendations