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Modelling nitrogen stress with probe genotypes to assess genetic parameters and genetic determinism of winter wheat tolerance to nitrogen constraint

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Abstract

Environmental and economical constraints in Europe will favour low nitrogen (N) input systems and wheat varieties adapted to moderate N deficiency. In this context, we studied the dynamics of genetic parameters according to N stress intensity and characterized the genetic determinants for plant tolerance to N deficiency. Thus, we combined N stress modelling with a genetic approach. Two hundred and twenty-two doubled haploid lines were experimented in the field for a range of nitrogen conditions. Those conditions were characterized by the Nitrogen Nutrition Index (NNI) of Récital. Grain Yield (GY) and Kernel Number (KN) were assessed. For GY and KN, and for each line, factorial regressions using NNI of Récital as environmental index were performed. In addition, we assessed the sensitivity to N stress (slopes of the regression) and the performances under low N conditions (predicted values for a NNI of 0.5). QTL detection was performed on these parameters as well as on KN and GY measured in each environment. G × N variance increased with N stress intensity whereas heritability and genetic variance decreased. 11 QTL regions were detected: 3 were N supply-specific QTL (on linkage groups 2A2, 3A and 4B) while 4 contained QTL detected under N+ and under N (2D1, 4B and 5A1). Out of these four, 2 coincided with QTL for factorial regression parameters (2D1 and 4B). Finally, 4 QTL were specific for factorial regression parameters (3B, 5A2 and 7B2). The role of genes commonly used in breeding programs (rht-B1 on 4B, and Ppd1 on 2D1) in plant adaptation to nitrogen constraint was highlighted. Future studies should focus on grain protein yield, another target for low-N breeding scheme.

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References

  • Agrama HA, Zakaria AG, Said F, Tuinstra M (1999) Identification of quantitative trait loci for nitrogen use efficiency in maize. Mol Breeding 5:187–195

    Article  Google Scholar 

  • Bänziger M, Bertran FJ, Lafitte HR (1997) Efficiency of high-nitrogen selection environments for improving maize for low-nitrogen target environments. Crop Sci 37:1103–1109

    Article  Google Scholar 

  • Basten CJ, Weir BS, Zeng ZB (1994) Zmap-a QTL. cartographer. 22:65–66

    Google Scholar 

  • Basten CJ, Weir BS, Zeng ZB (2002) QTL Cartographer version 1.16

  • Bertin P, Gallais A (2000) Genetic variation for nitrogen use efficiency in a set of recombinant maize inbred lines. I. Agrophysiological results. Maydica 45:53–66

    Google Scholar 

  • Brancourt-Hulmel M (1999) Crop diagnosis and probe genotypes for interpreting genotype environment interaction in winter wheat trials. Theor Appl Genet 99:1018–1030

    Article  Google Scholar 

  • Brancourt-Hulmel M, Heumez E, Pluchard P, Beghin D, Depatureaux C, Giraud A, Le Gouis J (2005) Indirect versus direct selection of winter wheat for low input or high input levels. Crop Sci 45:1427–1431

    Article  Google Scholar 

  • Bush MG, Evans LT (1998) Growth and development in tall and dwarf isogenic lines of spring wheat. Field Crops Res 18:243–270

    Article  Google Scholar 

  • Campbell B, Bänziger PS, Eskridge KM, Budak H, Streck NA, Weiss A, Gill KS, Erayman M (2004) Using environmental covariates to explain genotype × environment and QTL × environment interactions for agronomic traits on chromosomes 3A of wheat. Crop Sci 44:620–627

    Google Scholar 

  • Churchill GA, Doerge RW (1994) Empirical threshold values for quantitative trait mapping. Genetics 138:963–971

    PubMed  CAS  Google Scholar 

  • Coque M, Bertin P, Hirel B, Gallais A (2006) Genetic variation and QTLs for 15N natural abondance in a set of maize recombinant lines. Field Crops Res 97:310–321

    Article  Google Scholar 

  • Denis J-B (1988) Two ways analysis using covariates. Statistics 19:123–132

    Article  Google Scholar 

  • Ellis MH, Rebetzke GR, Chandler P, Bonnett D, Spielmeyer W, Richards RA (2003) New dwarfing genes for wheat breeding in sub-optimal environments. Tenth international wheat genetics symposium, Paestum, Italy, Instituto Sperimentale per la Cerealicoltura

  • Finlay KW, Wilkinson GN (1963) The analysis of adaptation in plant-breeding programme. Aust J Agric Res 14:742–754

    Article  Google Scholar 

  • Gallais A, Coque M (2005) Genetic variation and selection for nitrogen use efficiency in maize: a synthesis. Maydica 50:521–547

    Google Scholar 

  • Jeuffroy M-H, Bouchard C (1999) Intensity and duration of nitrogen deficiency on wheat grain number. Crop Sci 39:1385–1393

    Article  Google Scholar 

  • Justes E, Jeuffroy M-H, Mary B (1997) Wheat, barley and Durum wheat. In: Lemaire G (eds) Diagnosis of the nitrogen status in crop. Springer-Verlag, Berlin Heidelerg New York, pp 73–84

    Google Scholar 

  • Justes E, Mary B, Meynard J, Machet J-M, Thelier-Huche L (1994) Determination of a critical nitrogen dilution curve for winter wheat crops. Ann Bot 74:397–407

    Article  CAS  Google Scholar 

  • Kjaer B, Jensen J (1995) The inheritance of nitrogen and phosphorus content in barley analysed by genetic markers. Hereditas 123:109–119

    Article  CAS  Google Scholar 

  • Lander ES, Green P, Abrahamson J, Barlow A, Daly M, Lincoln SE, Newburg L (1987) MAPMAKER: an interactive computer package for constructing primary genetic maps of experimental and natural populations. Genomics 1:174–181

    Article  PubMed  CAS  Google Scholar 

  • Laperche A, Brancourt-Hulmel M, Heumez E, Gardet O, Le Gouis J (2006a) Estimation of genetic parameters of a DH wheat population grown at different N stress levels characterized by probe genotypes. Theor Appl Genet 112:797–807

    Article  PubMed  CAS  Google Scholar 

  • Laperche A, Devienne-Barret F, Maury O, Le Gouis J, Ney B (2006b) A simplified conceptual model of carbon/nitrogen functioning for QTL analysis of winter wheat adaptation to nitrogen deficiency. Theor Appl Genet 113:1131–1146

    Article  PubMed  CAS  Google Scholar 

  • Le Gouis J, Béghin D, Heumez E, Pluchard P (2000) Genetic differences for nitrogen uptake and nitrogen utilisation efficiencies in winter wheat. Eur J Agron 12:163–173

    Article  CAS  Google Scholar 

  • Lewicki S, Chery J (1992) Eude de l’accumulation et de la remobilisation de l’azote chez l’orge (Hordeum vulgare L.): comparaisonde variétés possédant ou non le gène de semi-nanisme. Agronomie 12:235–245

    Article  Google Scholar 

  • McCaig TN, Morgan JA (1993) Root and shoot dry matter partitioning in near isogenic wheat lines differing in height. Can J Plant Sci 73:679–689

    Google Scholar 

  • Presterl T, Groh S, Landbeck M, Seitz G, Schmidt W, Geiger HH (2002) Nitorgen uptake and utilization efficiency of European maize hybrids developed under conditions of low and high nitrogen input. Plant Breeding 121:480–486

    Article  Google Scholar 

  • Presterl T, Seitz G, Landbeck M, Thiemt EM, Schmidt W, Geiger HH (2003) Improving nitrogen-use-efficiency in european maize: estimation of quantitative genetic parameters. Crop Sci 43:1259–1265

    Article  Google Scholar 

  • Quarrie SA, Steed A, Calestani C, Semikhodskii A, Lebreton C, Chinoy C, Steele N, Pljevljakusic D, Waterman E, Weyen J, Schondelmaier J, Habash DZ, Farmer P, Saker L, Clarkson DT, Abugalieva A, Yessimbekova M, Turuspekov Y, Abugalieva S, Tuberosa R, Sanguineti M-C, Hollington PA, Aragués R, Royo A, Dodig D (2005) A high-density genetic map of hexaploid wheat (L.) from the cross Chinese Spring × SQ1 and its use to compare QTLs for grain yield across a range of environments. Theor Appl Genet 110:865–880

    Article  PubMed  CAS  Google Scholar 

  • Rebetzke GJ, Rochards RA (2000) Gibberellic acide-sensitive dwarfing genes reduce plant height to increase kernel number and grain yield of wheat. Aust J Agric Res 51:235–245

    Article  CAS  Google Scholar 

  • Rémy J-C, Hébert J (1977) Le devenir des engrais dans le sol. C R Acad Agric Fr 63:700–710

    Google Scholar 

  • SAS Institute Inc. (1999) SAS/STAT User’s guide. Version 8. SAS Institute Inc., Cary, NC

    Google Scholar 

  • Worland A, Börner A, Korzun V, Li W, Petrovic S, Sayers E (1998) The influence of photoperiod genes on the adaptability of European winter wheats. Euphytica 100:385–394

    Article  CAS  Google Scholar 

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Correspondence to Anne Laperche.

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Laperche, A., Le Gouis, J., Hanocq, E. et al. Modelling nitrogen stress with probe genotypes to assess genetic parameters and genetic determinism of winter wheat tolerance to nitrogen constraint. Euphytica 161, 259–271 (2008). https://doi.org/10.1007/s10681-007-9433-3

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