Methods for Genetic Analysis in the Triticeae

  • Abraham Korol
  • David Mester
  • Zeev Frenkel
  • Yefim Ronin
Chapter

Abstract

The objective of genetic analysis is to reveal genome structural and functional organization. One of the major tools developed at early stages of genetics was genetic mapping. Genetic maps are a very important tool in evolutionary genomics and numerous practical applications like breeding, medical genetics, and gene cloning. An important usage of multilocus maps is genetic dissection of quantitative traits, or mapping quantitative trait loci (QTL). Fine QTL mapping is a prerequisite for efficient marker-assisted selection and map-based cloning. However, the fine mapping challenge, especially if the target is a gene of weak or moderate effect, requires large sample sizes and dense maps. New array-based technologies (SNP and tilling arrays) partially solve this problem but at a very high project-wise genotyping cost. This is why despite some technical obstacles, genetic analysis based on selective genotyping and selective DNA pooling becomes very popular, especially in human genetics. In this chapter we consider methods for building genetic maps (Section 6.1), various versions of “multiple” approach for QTL mapping (Section 6.2), and a new cost-effective method for genetic mapping based on selective DNA pooling (Section 6.3). Whenever possible, the examples are based on Triticeae species.

References

  1. Ben-Dor, A., Chor, B., and Pelleg, D. (2000). RHO-Radiation hybrid ordering. Genome Res. 10: 365–378.PubMedCrossRefGoogle Scholar
  2. Boyko, E., Kalendar, R., Korzun, V., Fellers, J., Korol, A., Schulman, A.H., and Gill, B.S. (2002). A high-density cytogenetic map of the Aegilops tauschii genome incorporating retrotransposons and defense-related genes: insights into cereal chromosome structure and function. Plant Mol. Biol. 48: 767–790.PubMedCrossRefGoogle Scholar
  3. Brohede, J., Dunne, R., Mckay, J.D., and Hannan, G.N. (2005). PPC: an algorithm for accurate estimation of SNP allele frequencies in small equimolar pools of DNA using data from high density microarrays. Nucl. Acids Res. 33: e142.PubMedCrossRefGoogle Scholar
  4. Carleos, C., Baro, J.A., Canon, J., and Corral, N. (2003). Asymptotic variances of QTL estimators with selective DNA pooling. J. Hered 94: 175–179.PubMedCrossRefGoogle Scholar
  5. Churchill, G.A. and Doegre, R.W. (1994). Empirical threshold values for quantitative trait mapping. Genetics 138: 963–971.PubMedGoogle Scholar
  6. Darvasi, A. and Soller, M. (1994). Selective DNA pooling for determination of linkage between a molecular marker and a quantitative trait locus. Genetics 138: 1365–1373.PubMedGoogle Scholar
  7. Dekkers, J.C.M. (2000). Quantitative trait locus mapping based on selective DNA pooling. Anim. Breed. Genet. 117: 1–16.CrossRefGoogle Scholar
  8. Denell, R.E. and Keppy, D.O. (1979). The nature of genetic recombination near the third chromosome centromere of Drosophila melanogaster. Genetics 93: 117–130.PubMedGoogle Scholar
  9. Dobzhansky, T.H., Spassky, B., and Anderson, W. (1965). Bichromosomal synthetic semilethals in Drosophila pseudoobscura. Proc. Nat. Acad. Sci. USA 53: 345–348.CrossRefGoogle Scholar
  10. Eberhard, S.A. and Russel, W.A. (1966). Stability parameters for comparing varieties. Crop Sci. 6: 36–40.CrossRefGoogle Scholar
  11. Efron, B. (1979). Bootstrap method: another look at the jackknife. Ann. Stat. 7: 1–26.CrossRefGoogle Scholar
  12. Emrich, S.J., Aluru, S., Fu, Y., Wen, T.J., Narayanan, M., Guo, L., Ashlock, D.A., and Schnable, P.S. (2004). A strategy for assembling the masize (Zea mays L.) genome. Bioinformatics 20: 140–147.PubMedCrossRefGoogle Scholar
  13. Esch, E. and Weber, W.E. (2002). Investigation of crossover interference in barley (Hordeum vulgare L.) using the coefficient of coincidence. Theor. Appl. Genet. 104: 786–796.PubMedCrossRefGoogle Scholar
  14. Falk, C.T. (1992) Preliminary ordering of multiple linked loci using pairwise linkage data. Genet. Epidemiol. 9, 367–375.Google Scholar
  15. Finlay, K.W. and Wilkinson, G.N. (1963). The analysis of adaptation in a plant-breeding programme. Aust. J. Agric. Res. 14: 742–754.CrossRefGoogle Scholar
  16. Flint-Garcia, S.A., Thornsberry, J.M., and Buckler, E.S. (2003). Structure of linkage disequilibrium in plants. Annu. Rev. Plant Biol. 54: 357–374.PubMedCrossRefGoogle Scholar
  17. Givry, S., Bouchez, M., Chabrier, P., Milan, D., and Schiex, T. (2005). CarthaGene: multipopulation integrated genetic and radiation hybrid mapping. Bioinformatics 8: 1703–1704.Google Scholar
  18. Hayes, P.M., Liu, B.H., Knapp, S.J., Chen, F., Jones, B., Blake, T., Franckowiak, J., Rasmusson, D., Sorrels, M., Ullrich, S.E., Wesenberg, D., and Kleinhofs, A. (1993). Quantitative trait locus effects and environmental interaction in a sample of North American barley germplasm. Theor. Appl. Genet. 87: 392–401.CrossRefGoogle Scholar
  19. Hillel, J., Avner, R., Baxter-Jones, C., Dunnington, E.A., Cahaner, A. et al. (1990). DNA fingerprints from blood mixes in chickens and turkeys. Anim. Biotechnol. 2: 201–204.CrossRefGoogle Scholar
  20. Jansen, R.C. and Stam, P. (1994). High resolution of quantitative t1r4a5it5s.into multiple loci via interval mapping. Genetics 136: 1447–1455.PubMedGoogle Scholar
  21. Jansen, J., de Jong, A.G., and Ooijen, J.W. (2001). Constructing dense genetic linkage maps. Theor. Appl. Genet. 102: 1113–1122.CrossRefGoogle Scholar
  22. Jansen, R.C., Van Ooijen, J.M., Stam, P., Lister, C., and Dean, C. (1995). Genotype-by-environment interaction in genetic mapping of multiple quantitative trait loci. Theor. Appl. Genet. 91: 33–37.CrossRefGoogle Scholar
  23. Jiang, C. and Zeng, Z.-B. (1995). Multiple trait analysis and genetic mapping for quantitative trait loci. Genetics 140: 1111–1127.PubMedGoogle Scholar
  24. Johnson, T. (2005). Multipoint linkage disequilibrium mapping using multilocus allele frequency data. Ann. Hum. Genet. 69: 474–497.PubMedCrossRefGoogle Scholar
  25. Joppa, L.R., Nevo, E., and Beiles, A. (1995). Chromosome translocations in wild populations of tetraploid emmer wheat in Israel and Turkey. Theor. Appl. Genet. 91: 713–719.CrossRefGoogle Scholar
  26. Kao, C.-H., Zeng, Z.-B., and Teasdale, R.D. (1999). Multiple interval mapping for quantitative trait loci. Genetics 152: 1203–1216.PubMedGoogle Scholar
  27. Kearsey, M.J. (1998). The principles of QTL analysis (a minimal mathematics approach). J. Exp. Bot. 49: 1619–1623.CrossRefGoogle Scholar
  28. Klein, P.E., Klein, R.R., Cartinhour, S.W., Ulanch, P.E., Dong, J., et al. (2000). A High-throughput AFLP-based method for constructing integrated genetic and physical maps: progress toward a sorghum genome map. Genome Res. 10: 789–807.PubMedCrossRefGoogle Scholar
  29. Korol, A.B., Preygel, I.A., and Bocharnikova, N.I. (1987). Linkage between loci of quantitative characters and marker loci. 5. Combined analysis of several markers and quantitative characters. Genetika (USSR) 23: 1421–1431 (in Russian). English translation in Soviet Genetics 1988, 23: 996–1004 (Plenum Publ. Co., N.Y.).Google Scholar
  30. Korol, A.B., Preygel, I.A., and Preygel, S.I. (1994). Recombination Variability and Evolution. Chapman & Hall, London.Google Scholar
  31. Korol, A.B., Ronin, Y.I., and Kirzhner, V.M. (1995). Multitrait analysis in interval mapping of QTL. Genetics 140: 1137–1147.PubMedGoogle Scholar
  32. Korol, A., Ronin, Y., Tadmor, Y., Bar-Zur, A., Kirzhner, V.M., and Nevo, E. (1996). Estimating variance effect of QTL: An important prospect to increase the resolution power of interval mapping. Genet. Res. 67: 187–194.CrossRefGoogle Scholar
  33. Korol, A.B., Ronin, Y.I., and Nevo, E. (1998). Approximated analysis of QTL-environmental interaction with no limits on the number of environments. Genetics 148: 2015–1028.PubMedGoogle Scholar
  34. Korol, A., Ronin, Y., Itzcovich, A., and Nevo, E. (2001). Enhanced efficiency of QTL mapping analysis based on multivariate complexes of quantitative traits. Genetics 157: 1789–1803.PubMedGoogle Scholar
  35. Korol, A., Shirak, A., Cnaani, A., and Hallerman, E.M. (2007a). Detection and analysis of QTLs for economic traits in aquatic species. In: Liu, Z.J. (ed.), Aquaculture Genome Technologies. Blackwell, pp. 169–197.Google Scholar
  36. Korol, A., Frenkel, Z., Cohen, L., Lipkin, E., and Soller, M. (2007b). Fractioned DNA Pooling: A New Cost-Effective Strategy for Fine Mapping of Quantitative Trait Loci. Genetics 176: 2611–2623.Google Scholar
  37. Korzun, V., Malyshev, S., Voylokov, A.V., and Börner, A. (2001). A genetic map of rye (Secale cereale L.) combining RFLP, isozyme, protein, microsatellite and gene loci. Theor. Appl. Genet. 102:709–717.CrossRefGoogle Scholar
  38. Lacaze, X., Tanny, S., and Korol, A. (2009a). Transcriptional plasticity differing across genetic backgrounds: An epistatic mechanism in Arabidopsis thaliana (in revision).Google Scholar
  39. Lacaze, X. Hayes, P.M., and Korol, A. (2009b). Genetics of phenotypic plasticity: QTL analysis in barley, Hordeum vulgare. Heredity 102:163–173.Google Scholar
  40. Lander, E.S. and Botstein, D. (1989) Mapping mendelian factors underlying quantitative traits using RFLP linkage maps. Genetics 121, 185–199.Google Scholar
  41. Liu, B.H. (1998). Statistical Genomics: Linkage, Mapping, and QTL Analysis. CRC Press, New York.Google Scholar
  42. Liu, C.J., Devos, K.M., Chinoy, C.N., Atkinson, M.D., and Gale, M.D. (1992). Non- homoeologous translocations between group-4, 5 and 7 chromosomes in wheat and rye. Theor. Appl. Genet. 83: 305–312.CrossRefGoogle Scholar
  43. Mangin, B., Thoquet, P., and Grimsley, N. (1998). Pleiotropic QTL analysis. Biometrics 54: 88–99.CrossRefGoogle Scholar
  44. Menotti-Raymond, M., David, V.A., Chen, Z.Q., Menotti, K.A., Sun, S., Schaffer, A.A., Agarwala, R., Tomlin, J.F., O’Brien, S.J., and Murphy, W.J. (2003).Second-generation integrated genetic linkage/ radiation hybrid maps of the domestic cat (Felis catus). J. Hered. 94: 95–106.PubMedCrossRefGoogle Scholar
  45. Mester, D., Ronin, Y., Minkov, D., Nevo, E., and Korol, A. (2003a). Constructing large scale genetic maps using Evolutionary Strategy Algorithm. Genetics 165: 2269–2282.Google Scholar
  46. Mester, D., Ronin, Y., Hu, Y., Nevo, E. and Korol, A. (2003b). Efficient multipoint mapping: Making use of dominant repulsion-phase markers. Theor. Appl. Genet. 107, 1102–1112.Google Scholar
  47. Mester, D.I., Ronin, Y.I., Nevo, E., and Korol, A.B. (2004). Fast and high precision algorithms for optimization in large scale genomic problems. Comp Biol & Chemistry 28: 281–290.CrossRefGoogle Scholar
  48. Mester, D., Ronin, Y., Korostishevsky, M., Pikus, V., Glazman, A., and Korol, A.B. (2005). Multilocus consensus genetic maps (MCGM): Formulation, algorithms and results. Computat. Biol. Chem. 30: 12–20.CrossRefGoogle Scholar
  49. Michie, D. (1953). Affinity: a new genetic phenomenon in the house mouse. Nature 171: 26–27.PubMedCrossRefGoogle Scholar
  50. Morrell, P.L., Toleno, D.M., Lundy, K.E., and Clegg, M.T. (2005). Low levels of linkage disequilibrium in wild barley (Hordeum vulgare ssp spontaneum) despite high rates of self-fertilization. Proc. Natl. Acad. Sci. USA 102: 2442–2447.PubMedCrossRefGoogle Scholar
  51. Morrell, P.L., Toleno, D.M., Lundy, K.E., and Clegg, M.T. (2006). Estimating the contribution of mutation, recombination and gene conversion in the generation of haplotypic diversity. Genetics 173: 1705–1723.PubMedCrossRefGoogle Scholar
  52. Peng, J., Korol, A.B., Fahima, T., Roder, M.S., Ronin, Y.I., Li, Y.C., and Nevo, E. (2000). Molecular genetic maps in wild emmer wheat, Triticum dicoccoides: genome-wide coverage, massive negative interference, and putative quasi-linkage. Genome Res. 10: 1509–1531.PubMedCrossRefGoogle Scholar
  53. Peng, J., Ronin, Y., Fahima, T., Röder, M.S., Li, Y., Nevo, E., and Korol, A.B. (2003). Domestication quantitative trait loci in Triticum dicoccoides, the progenitor of wheat. Proc. Natl. Acad. Sci. USA 100: 2489–2494.CrossRefGoogle Scholar
  54. Plagnol, V., Padhukasahasram, B., Wall, J.D., Marjoram, P., and Nordborg, M. (2006). Relative influences of crossing over and gene conversion on the pattern of linkage disequilibrium in Arabidopsis thaliana. Genetics 172: 2441–2448.PubMedCrossRefGoogle Scholar
  55. Romagosa, I., Ullrich, S.E., Han, F., and Hayes, P.M. (1996). Use of additive main effects and multiplicative interaction model in QTL mapping for adaptation in barley. Theor. Appl. Genet. 93: 30–37.CrossRefGoogle Scholar
  56. Ronin, Y.I., Kirzhner, V.M., and Korol, A.B. (1995). Linkage between loci of quantitative traits and marker loci. Multitrait analysis with a single marker. Theor. Appl. Genet. 90: 776–786.CrossRefGoogle Scholar
  57. Ronin, Y.I., Korol, A.B., and Weller, J.I. (1998). Selective genotyping to detect quantitative trait loci affecting multiple traits: interval mapping analysis. Theor. Appl. Genet. 97: 1169–1178.CrossRefGoogle Scholar
  58. Ronin, Y., Korol, A., and Nevo, E. (1999). Single- and multiple-trait analysis of linked QTLs: some asymptotic analytical approximation. Genetics 151: 387–396.PubMedGoogle Scholar
  59. Sari-Gorla, M., Calinski, T., Kaczmarek, Z., and Krajewski, P. (1997). Detection of QTL-environment interaction in maize by a least squares interval mapping method. Heredity 78: 146–157.Google Scholar
  60. Schiex, T. and Gaspin, C. (1997). Carthagene: constructing and joining maximum likelihood genetic maps. ISMB 5: 258–267.PubMedGoogle Scholar
  61. Sinclair, D.A. (1975). Crossing over between closely linked markers spanning the centromere of chromosome 3 in Drosophila melanogaster. Genet. Res. 11: 173–185.CrossRefGoogle Scholar
  62. SØgaard, B. (1977). The localization of eceriferum loci in barley. V. Three point tests of genes on chromosome 1 and 3 in barley. Carlsberg Res. Commun. 42: 67–75.CrossRefGoogle Scholar
  63. Voudouris, C. (1997). Guided local search for combinatorial problems, Ph.D. thesis, Department of Computer Science, University of Essex, Colchester.Google Scholar
  64. Wang, J., Koehler, K.J., and Dekkers, J.C.M. (2007). Interval mapping of quantitative trait loci with selective DNA pooling data. Genet. Select. Evol. 39: 685–710.CrossRefGoogle Scholar
  65. Weeks, D. and Lange, K. (1987). Preliminary ranking procedures for multilocus ordering. Genomics 1: 236–242.PubMedCrossRefGoogle Scholar
  66. Weller, J.I., Kashi, Y., and Soller, M. (1990). Power of daughter and granddaughter designs for determining linkage between marker loci and quantitative trait loci in dairy-cattle. J. Dairy Sci. 73: 2525–2537.PubMedCrossRefGoogle Scholar
  67. Weller, J.I., Wiggans, G.R., Van Raden, P.M., and Ron, M. (1996). Application of a canonical transformation to detection of quantitative trait loci with the aid of genetic markers in a multi-trait experiment. Theor. Appl. Genet. 92: 998–1002.CrossRefGoogle Scholar
  68. West, M.A.L., Kim, K., Kliebenstein, D.J., van Leeuwen, H., Michelmore, R.W., Doerge, R.W., and St. Clair, D.A. (2007). Global eQTL mapping reveals the complex genetic architecture of transcript-level variation in Arabidopsis. Genetics 175: 1441–1450.PubMedCrossRefGoogle Scholar
  69. Yap, I., Schneider, D., Kleinberg, J., Matthews, D., Cartinhour, S., and McCouch, S. (2003). A graph-theoretic approach to comparing and integrating genetic, physical and sequence-based maps. Genetics 165: 2235–2247.PubMedGoogle Scholar
  70. Zeng, Z.-B. (1994). Precision mapping of quantitative trait loci. Genetics 136: 1457–1468.PubMedGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Abraham Korol
    • 1
  • David Mester
    • 2
  • Zeev Frenkel
    • 1
  • Yefim Ronin
    • 1
  1. 1.Institute of Evolution, Faculty of Science, University of HaifaIsrael
  2. 2.Department of Crop Genetics, John Innes CentreNorwich Research ParkUK

Personalised recommendations