Abstract
Computer simulations are useful tools to optimize marker-assisted breeding programs. The objective of our study was to investigate the closeness of computer simulations of the recurrent parent genome recovery with experimental data obtained in two marker-assisted backcrossing programs in rice (Orzya sativa L.). We simulated the breeding programs as they were practically carried out. In the simulations we estimated the frequency distributions of the recurrent parent genome proportion in the backcross populations. The simulated distributions were in good agreement with those obtained practically. The simulation results were also observed to be robust with respect to the choice of the mapping function and the accuracy of the linkage map. We conclude that computer simulations are a useful tool for pre-experiment estimation of selection response in marker-assisted backcrossing.
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References
Armitage P, Berry G (1994) Statistical methods in medical research, 3rd edn. Blackwell, Oxford
Frisch M (2005) Optimum design of marker-assisted backcross programs. In: Loerz H, Wenzel G (eds) Biotechnology in agriculture and forestry vol 55. Springer, Berlin, pp 319–334
Frisch M, Melchinger AE (2001a) Marker-assisted backcrossing for simultaneous introgression of two genes. Crop Sci 41:1716–1725
Frisch M, Melchinger AE (2001b) Marker-assisted backcrossing for introgression of a recessive gene. Crop Sci 41:1485–1494
Frisch M, Bohn M, Melchinger AE (1999) Minimum sample size and optimal positioning of flanking markers in marker-assisted backcrossing for transfer of a target gene. Crop Sci 39:967–975
Haldane JBS (1919) The combination of linkage values and the calculation of distance between the loci of linkage factors. J Genet 8:299–309
Hospital F (2005) Selection in backcross programmes. Phil Trans R Soc B 360:1503–1512
Hospital F, Charcosset A (1997) Marker-assisted introgression of quantitative trait loci. Genetics 147:1469–1485
Hospital F, Chevalet C, Mulsant P (1992) Using markers in gene introgression breeding programs. Genetics 132:1199–1210
Kosambi DD (1944) The estimation of map distances from recombination values. Ann Eugen 12:172–175
Lecomte L, Duffe P, Buret M, Servin B, Hospital F, Causse M (2004) Marker-assisted introgression of five QTLs controlling fruit quality traits into three tomato lines revealed interactions between QTLs and genetic backgrounds. Theor Appl Genet 109:658–668
Maurer HP, Melchinger AE, Frisch M (2008) Population genetic simulation and data analysis with Plabsoft. Euphytica (in press). doi:10.1007/s10681-007-9493-4
McCouch SR, Chen X, Panaud O, Temnykh S, Xu Y, Cho YG, Huang N, Ishii T, Blair M (1997) Microsatellite marker development, mapping and applications in rice genetics and breeding. Plant Mol Biol 35:89–99
McCouch SR, Teytelman L, Xu Y, Lobos KB, Clare K, Walton M, Fu B, Maghirang R, Li Z, Xing Y, Zhang Q, Kono I, Yano M, Fjellstrom R, DeClerck G, Schneider D, Cartinhour S, Ware D, Stein L (2002) Development and mapping of 2240 new SSR markers for rice (Oryza sativa L.). DNA Res 9:199–207
Neeraja CN, Maghirang-Rodriguez R, Pamplona A, Heuer S, Collard BCY, Septiningsih EM, Vergara G, Sanchez D, Ismail AM, Mackill DJ (2007) A marker-assisted backcross approach for developing submergence-tolerant rice cultivars. Theor Appl Genet 115:767–776
Ragot M, Biasiolli M, Delbut MF, Dell’Orco A, Malgarini L, Thevenin P, Vernoy J, Vivant J, Zimmermann R, Gay G (1995) Marker-assisted backcrossing: a practical example. In: Techniques et utilisations des marqueurs moleculaires. Montepellier, France. INRA, Paris, 29–31 March 1994
Ribaut J-M, Hoisington D (1998) Marker-assisted selection: new tools and strategies. Trends Plant Sci 3:236–239
Ribaut J-M, Jiang C, Hoisington D (2002) Simulation experiments on efficiencies of gene introgression by backcrossing. Crop Sci 42:557–565
Stam P (1979) Interference in genetic crossing over and chromosome mapping. Genetics 92:573–594
Stam P (1993) Construction of integrated genetic linkage maps by means of a new computer package: JoinMap. Plant J 3:739–744
Temnykh S, Park WD, Ayres N, Cartinhour S, Hauck N, Lipovich L, Cho YG, Ishii T, McCouch SR (2000) Mapping and genome organization of microsatellite sequences in rice (Oryza sativa L.). Theor Appl Genet 100:697–712
Xu K, Mackill DJ (1996) A major locus for submergence tolerance mapped on rice chromosome 9. Mol Breeding 2:219–224
Xu K, Xu X, Fukao T, Canlas P, Maghirang-Rodriguez R, Heuer S, Ismail AM, Mailey-Serres J, Ronald PC, Mackill DJ (2006) Sub1A is an ethylene-response-factor-like gene that confers submergence tolerance to rice. Nature 442:705–708
Acknowledgments
We thank Dr. E. M. Septiningsih, Dr. B. Collard, and Prof. B. S. Dhillon for helpfull comments on the manuscript and appreciate the editorial work of Dr. J. Muminović. We thank the anonymous reviewers for their comments and suggestions, which helped to improve the manuscript. The financial support from the Bundesministerium für Wirtschaftliche Zusammenarbeit (BMZ, Germany) is gratefully acknowledged.
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Communicated by D. A. Hoisington.
Vanessa Prigge and Hans Peter Maurer contributed equally to this work.
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Prigge, V., Maurer, H.P., Mackill, D.J. et al. Comparison of the observed with the simulated distributions of the parental genome contribution in two marker-assisted backcross programs in rice. Theor Appl Genet 116, 739–744 (2008). https://doi.org/10.1007/s00122-007-0707-x
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DOI: https://doi.org/10.1007/s00122-007-0707-x