Hostname: page-component-586b7cd67f-t7czq Total loading time: 0 Render date: 2024-11-28T04:54:12.677Z Has data issue: false hasContentIssue false
  • English
  • Français

Models for mapping quantitative trait loci (QTL) in progeny of non-inbred parents and their behaviour in presence of distorted segregation ratios

Published online by Cambridge University Press:  14 April 2009

R. Schäfer-Pregl ,
F. Salamini  and
C. Gebhardt
R. Schäfer-Pregl*
Affiliation:
Max-Planck-Institut für Züchtungsforschung, Carl-v.-Linné-Weg 10, 50829 Köln, Germany
F. Salamini
Affiliation:
Max-Planck-Institut für Züchtungsforschung, Carl-v.-Linné-Weg 10, 50829 Köln, Germany
C. Gebhardt
Affiliation:
Max-Planck-Institut für Züchtungsforschung, Carl-v.-Linné-Weg 10, 50829 Köln, Germany
*
*To whom correspondence should be addressed.
Rights & Permissions [Opens in a new window]

Summary

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

In plants, models for mapping quantitative trait loci (QTL) based on flanking markers have been mainly developed for progenies of inbred lines. We propose twoflanking marker models for QTL mapping in F1 progenies of non-inbred parents. The first is based on the segregation of four different scorable alleles at a marker locus (the four-allele model) and the second (the commonallele model) on one scorable allele per marker locus segregating in both parents. These models are suitable for the majority of the allelic configurations which may occur in crosses between heterozygous parents. For both cases, when four scorable or one common-allele per marker locus segregate, additional algorithms were developed to estimate the recombination frequency between two marker loci. Tests carried out with simulated populations of various sizes indicate that the models provide a good estimate of QTL genotypic means and of recombination frequencies between flanking markers and between the marker loci and the QTL.The estimates of QTL genotypic means have a higher precision than the estimates of recombination frequencies. The four-allele model shows a higher ability to detect QTLs than the common-allele model. If segregation ratios are distorted, the power of both models and the precision of the estimates of recombination frequencies are reduced, whereas the accuracy of estimates of QTL genotype means is not affected by distorted segregation ratios. The power of the common-allele model is substantially reduced if QTL genotypic means depend on additive allelic interactions, whereas the four-allele model is less affected by the non-additive behaviour of QTL alleles.

Type
Research Article
Information
Genetics Research , Volume 67 , Issue 1 , February 1996 , pp. 43 - 54
Copyright
Copyright © Cambridge University Press 1996

References

East, E. M., (1916). Studies on size inheritance in Nicotinia. Genetics 1, 164–176.CrossRefGoogle Scholar
Edwards, M. D., Hellentjaris, T., Wright, S., & Stuber, C. W., (1992). Molecular-marker-facilitated investigations of quantitative trait loci in maize. 4. Analysis based on genome saturation with isozyme and restriction fragment length polymorphism markers. Theoretical and Applied Genetics 83, 765–774.CrossRefGoogle ScholarPubMed
Edwards, M. D., Stuber, C. W., & Wendel, J. F., (1987). Molecular-marker-facilitated investigations of quantitative-trait loci in maize. I. Numbers, genomic distribution and types of gene action. Genetics 116, 113–125.CrossRefGoogle Scholar
Gallant, R. A., (1987). Nonlinear Statistical Models. New York: John Wile. & Sons.CrossRefGoogle Scholar
Gebhardt, C., Ritter, E., Barone, A., Debener, T., Walkemeier, B., Schachtschabel, U., Kaufmann, H., Thompson, R. D., Bonierbale, M. W., Ganal, M. W., Tanksley, S. D., & Salamini, F., (1991). RFLP maps of potato and their alignment with the homologous tomato genome. Theoretical and Applied Genetics 83, 49–57.CrossRefGoogle Scholar
Gebhardt, C., Ritter, E., & Salamini, F., (1994). RFLP map of the potato. In DNA-based Markers in Plants (ed. Phillips, R. L. and Vasil, I. K.), pp. 271–285. The Netherlands: Kluwer Academic Publishers.CrossRefGoogle Scholar
Geldermann, H., (1975). Investigations on inheritance of quantitative characters in animals by gene markers. I. Methods. Theoretical and Applied Genetics 46, 319–330.CrossRefGoogle ScholarPubMed
Haley, C. S., Knott, S. A., & Elsen, J.-M., (1994). Mapping quantitative trait loci in crosses between outbred lines using least squares. Genetics 136, 1195–1207.Google ScholarPubMed
Jansen, R. C., (1992). A general mixture model for mapping quantitative trait loci by using molecular markers. Theoretical and Applied Genetics 85, 252–260.CrossRefGoogle ScholarPubMed
Knapp, S. J., (1989). Quasi mendelian analyses of quantitative traits using molecular marker linkage maps: an overview of parameter estimation methods. In Proc 12th Eucarpia Congr., Goettingen, FRG (ed. Roebellen, G.), pp. 51–67.Google Scholar
Knapp, S. J., (1994). Mapping quantitative trait loci. In DNA-based Markers in Plants (ed. Phillips, R. L. and Vasil, I. K.), pp. 271–285. The Netherlands: Kluwer Academic Publishers.Google Scholar
Knapp, S. J., & Bridges, W. C., (1990). Programs for mapping quantitative trait loci using flanking molecular markers and nonlinear models. Journal of Heredity 81, 234–235.CrossRefGoogle Scholar
Knapp, S. J., Bridges, W. C., & Birkes, D., (1990). Mapping quantitative trait loci using molecular marker linkage maps. Theoretical and Applied Genetics 79, 583–592.CrossRefGoogle ScholarPubMed
Lander, E. S., & Botstein, D., (1986). Strategies for studying heterogeneous genetic traits in humans by using a linkage map of restriction fragment length polymorphisms. Proceedings of the National Academy of Sciences, USA 83, 7353–7357.Google ScholarPubMed
Lander, E. S., & Botstein, D., (1989). Mapping mendelian factors underlying quantitative traits using RFLP linkage maps. Genetics 121, 185–199.CrossRefGoogle ScholarPubMed
Leonards-Schippers, C., Gieffers, W., Schäfer-Pregl, R., Ritter, E., Knapp, S. J., Salamini, F., & Gebhardt, C., (1994). Quantitative resistance to Phytophthora infestans in potato: a case study for QTL mapping in allogamous plant species. Genetics 137, 67–77.CrossRefGoogle ScholarPubMed
Martin, B., Niehuis, J., King, G., & Schaefer, A., (1989). Restriction fragment length polymorphisms associated with water use efficiency in tomato. Science 243, 1725–1728.CrossRefGoogle ScholarPubMed
Nilsson-Ehle, H., (1909). Kreuzungsuntersuchungen an Hafer und Weizen. Lund 1909.Google Scholar
Osborn, T. C, Alexander, D. C., & Forbes, J. F., (1987). Identification of restriction fragment length polymorphisms linked to genes controlling soluble solids content in tomato fruit. Theoretical and Applied Genetics 73, 350–356.CrossRefGoogle ScholarPubMed
Phillips, R. L., & Vasil, I. K. (eds.) (1994). DNA-based Markers in Plants, pp. 271–285. The Netherlands: Kluwer Academic Publishers.CrossRefGoogle Scholar
Rasmusson, J. M., (1933). A contribution to the theory of quantitative character inheritance. Hereditas 18, 245–261.CrossRefGoogle Scholar
Ritter, E., Gebhardt, C., & Salamini, F., (1990). Estimation of recombination frequencies and construction of RFLP linkage maps in plants from crosses between heterozygous plants. Genetics 125, 645–654.CrossRefGoogle Scholar
SAS Institute Inc. (1989). SAS/STAT Users Guide, Version 6, 4th edn, vol. 2, 1042 pp. Cary, NC: SAS Institute Inc.Google Scholar
SAS Institute Inc. (1990). SAS Language: Reference, Version 6, 4th edn, vol. 2, 846 pp. Cary, NC: SAS Institute Inc.Google Scholar
Sax, K., (1923). The association of size differences with seedcoat pattern and pigmentation in Phaseolus vulgaris. Genetics 8, 552–560.CrossRefGoogle ScholarPubMed
Soller, M., & Brody, T., (1976). On the power of experimental designs for the detection of linkage between marker loci and quantitative loci in crosses between inbred lines. Theoretical and Applied Genetics 47, 35–39.CrossRefGoogle ScholarPubMed
Soller, M., Brody, T., & Genizi, A., (1979). The expected distribution of marker-linked quantitative effects in crosses between inbred lines. Heredity 43, 170–190.CrossRefGoogle Scholar
Stuber, C. W., Edwards, M. D., & Wendel, J. F., (1987). Molecular marker-facilitated investigations of quantitative trait loci in maize. II. Factors influencing yield and its component traits. Crop Science 11, 639–648.CrossRefGoogle Scholar
Stuber, C. W., Lincoln, S. E., Wolff, D. W., Helentjaris, T., & Lander, E. S., (1992). Identification of genetic factors contributing to heterosis in a hybrid from two elite maize inbred lines using molecular markers. Genetics 132, 823–839.Google Scholar
Tanksley, S. D., & Hewitt, J., (1988). Use of molecular markers in breeding for soluble solids content in tomato — a re-examination. Theoretical and Applied Genetics 75, 811–823.Google Scholar
Vos, P., Hogers, R., Bleeker, M., Reijans, M., van der Lee, T., Homes, M., Freijters, A., Pot, J., Peleman, J., Kuiper, M., & Zabeau, M. AFLP: a new technique for DNA fingerprinting (in press).Google Scholar
Weller, J. I., (1986). Maximum likelihood techniques for the mapping and analysis of quantitative trait loci with the aid of genetic markers. Biometrics 42, 627–640.CrossRefGoogle ScholarPubMed
Weller, J. I., (1987). Mapping and analysis of quantitative trait loci in Lycopersicon (tomato) with the aid of genetic markers using approximate maximum likelihood methods. Heredity 59, 413–421.CrossRefGoogle Scholar