Abstract
A recombinant inbred line (RIL) population was evaluated in seven field experiments representing four environments: water stress at flowering (WS) and well-watered (WW) conditions in Mexico and Zimbabwe. The QTLs were identified for each trait in each individual experiment (single-experiment analysis) as well as per environment, per water regime across locations and across all experiments (joint analyses). For the six target traits (male flowering, anthesis-to-silking interval, grain yield, kernel number, 100-kernel fresh weight and plant height) 81, 57, 51 and 34 QTLs were identified in the four step-wise analyses, respectively. Despite high values of heritability, the phenotypic variance explained by QTLs was reduced, indicating epistatic interactions. About 80, 60 and 6% of the QTLs did not present significant QTL-by-environment interactions (QTL × E) in the joint analyses per environment, per water regime and across all experiments. The expression of QTLs was quite stable across years at a given location and across locations under the same water regime. However, the stability of QTLs decreased drastically when data were combined across water regimes, reflecting a different genetic basis of the target traits in the drought and well-watered trials. Several clusters of QTLs for different traits were identified by the joint analyses of the WW (chromosomes 1 and 8) and WS (chromosomes 1, 3 and 5) treatments and across water regimes (chromosome 1). Those regions are clear targets for future marker-assisted breeding, and our results confirm that the best approach to breeding for drought tolerance includes selection under water stress.
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Agrama HAS, Moussa ME (1996) Mapping QTLs in breeding for drought tolerance in maize (Zea mays L). Euphytica 91:89–97
Agrama HAS, Zakaria AG, Said FB, Tuinstra M (1999) Identification of quantitative trait loci for nitrogen use efficiency in maize. Mol Breed 5:187–195
Austin DF, Lee M (1998) Detection of quantitative trait loci for grain yield and yield components in maize across generations in stress and nonstress environments. Crop Sci 38:1296–1308
Bahrun A, Jensen CR, Asch F, Mogensen VO (2002) Drought-induced changes in xylem pH, ionic composition, and ABA concentration act as early signals in field-grown maize (Zea mays L.). J Exp Bot 53:251–263
Bänziger M, Edmeades GO, Beck D, Bellon M (2000) Breeding for drought and nitrogen stress tolerance in maize: From theory to practice. CIMMYT, Mexico, DF
Beavis WD, Keim P (1996) Identification of QTL that are affected by environment. In: Kang MS, Gauch HG (eds) Genotype by environment interaction. CRC Press, Boca Raton, pp 123–149
Betrán FJ, Beck D, Bänziger M, Edmeades GO (2003) Genetic analysis of inbred and hybrid grain yield under stress and nonstress environments in tropical maize. Crop Sci 43:807–817
Bolaños J, Edmeades GO (1996) The importance of the anthesis-silking interval in breeding for drought tolerance in tropical maize. Field Crops Res 48:65–80
Bruce WB, Edmeades GO, Barker TC (2002) Molecular and physiological approaches to maize improvement for drought tolerance. J Exp Bot 53:13–25
Campos H, Cooper M, Habben JE, Edmeades GO, Schussler JR (2004) Improving drought tolerance in maize: a view from industry. Field Crops Res 90:19–34
Chardon F, Virlon B, Moreau L, Falque M, Joets J, Decousset L, Murigneux A, Charcosset A (2004) Genetic architecture of flowering time in maize as inferred from quantitative trait loci meta-analysis and synteny conservation with the rice genome. Genetics 168:2169–2185
Claassen MM, Shaw RH (1970) Water deficit effects on corn. 2. Grain components. Agron J 62:652–655
Cochard H (2002) Xylem embolism and drought-induced stomatal closure in maize. Planta 215:466–471
Colasanti J, Yuan Z, Sundaresan V (1998) The indeterminate gene encodes a zinc-finger protein and regulates a leaf-generated signal required for the transition to flowering in maize. Cell 93:593–603
Cooper M, van Eeuwijk FA, Chapman SC, Podlich DW, Löffler C (2006) Genotype-by-environment interactions under water-limited conditions. In: Ribaut J-M (ed) Drought adaptation in cereals. Haworth Press Inc., Binghampton, pp 51–96
Edmeades GO, Bolaños J, Chapman SC, Lafitte HR, Bänziger M (1999) Selection improves drought tolerance in tropical maize populations: I. Gains in biomass, grain yield, and harvest index. Crop Sci 39:1306–1315
Edmeades GO, Bolaños J, Elings A, Ribaut J-M, Bänziger M, Westgate ME (2000) The role and regulation of the anthesis-silking interval in maize. In: Westgate ME, Boote KJ (eds) CSSA Special Publication No. 29. CSSA, Madison, pp 43–73
Frankel WN, Schork NJ (1996) Who’s afraid of epistasis? Nat Genet 14:371–373
Gilmour AR, Gogel BJ, Cullis BR, Welham SJ, Thompson R (2002) ASReml user guide release 1.0. VSN International Ltd, Hemel Hempstead, HP1, 1ES, UK
Haldane JBS (1919) The combination of linkage values, and the calculation of distances between the loci of linked factors. J Genet 8:299–309
Hao ZF, Li XH, Xie CX, Li MS, Zhang DG, Bai L, Zhang SH (2008) Two consensus quantitative trait loci clusters controlling anthesis-silking interval, ear setting and grain yield might be related with drought tolerance in maize. Ann Appl Biol 153:73–83
Heisey PW, Edmeades GO (1999) Maize production in drought-stressed environments: Technical options and research resource allocation. Part 1 of CIMMYT 1997/98 World Maize Facts and Trends; maize production in drought-stressed environments: technical options and research resource allocation. CIMMYT, Mexico, DF
Heisey PW, Morris ML (2006) Economic impact of water-limited conditions on cereal grain production. In: Ribaut J-M (ed) Drought adaptation in cereals. Haworth Press Inc, Binghampton, pp 17–48
Hund A, Ruta N, Liedgens M (2008) Rooting depth and water use efficiency of tropical maize inbred lines, differing in drought tolerance. Plant Soil 318:311–325
IPCC (2007) Climate Change 2007: Impacts, adaptation and vulnerability. In: Parry ML, Canziani OF, Palutikof JP, van der Linden PJ, Hanson CE (eds) Contribution of working group II to the fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, pp 976
Jiang C, Zeng ZB (1995) Multiple trait analysis of genetic mapping for quantitative trait loci. Genetics 140:1111–1127
Lander ES, Green P, Abrahanson J, Barlow A, Daley M, Lincoln S, Newburg L (1987) MAPMAKER: an interactive computer package for constructing primary genetic linkage maps of experimental and natural populations. Genomics 1:174–181
Landi P, Sanguineti MC, Liu C, Li Y, Wang TY, Giuliani S, Bellotti M, Salvi S, Tuberosa R (2007) Root-ABA1 QTL affects root lodging, grain yield, and other agronomic traits in maize grown under well-watered and water-stressed conditions. J Exp Bot 58:319–326
Lawrence CJ, Harper LC, Schaeffer ML, Sen TZ, Seigfried TE, Campbell DA (2008) MaizeGDB: the maize model organism database for basic, translational, and applied research. Int J Plant Genomics. doi:10.1155/2008/496957
Li H, Ye G, Wang J (2007) A modifiend algorithm for the improvement of composite interval mapping. Genetics 175:361–374
Li H, Ribaut J-M, Li Z, Wang J (2008) Inclusive composite interval mapping (ICIM) for digenic epistasis of quantitative traits in biparental populations. Theor Appl Genet 116:243–260
Lima MDA, de Souza CL, Bento DAV, de Souza AP, Carlini-Garcia LA (2006) Mapping QTL for grain yield and plant traits in a tropical maize population. Mol Breed 17:227–239
Liu B-H (1998) Statistical genomics: linkage, mapping, and QTL analysis. CRC Press, Boca Raton
Lu GH, Tang JH, Yan JB, Ma XQ, Li JS, Chen SJ, Ma JC, Liu ZX, LZ E, Zhang YR, Dai JR (2006) Quantitative trait loci mapping of maize yield and its components under different water treatments at flowering time. J Integr Plant Biol 48:1233–1243
Malosetti M, Voltas J, Romagosa I, Ullrich SE, van Eeuwijk FA (2004) Mixed models including environmental covariables for studying QTL by environment interaction. Euphytica 137:139–145
Malosetti M, Ribaut J-M, Vargas M, Crossa J, van Eeuwijk FA (2008) A multi-trait multi-environment QTL mixed model with an application to drought and nitrogen stress trials in maize (Zea mays L.). Euphytica 161:241–257
Mittler R (2006) Abiotic stress, the field environment and stress combination. Trends Plant Sci 11:15–19
Monneveux P, Sánchez C, Beck D, Edmeades GO (2006) Drought tolerance improvement in tropical maize source populations: Evidence of progress. Crop Sci 46:180–191
Moreau L, Charcosset A, Gallais A (2004) Experimental evaluation of several cycles of marker-assisted selection in maize. Euphytica 137:111–118
R Development Core Team (2007) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. http://www.R-project.org
Ribaut J-M, Ragot M (2007) Marker-assisted selection to improve drought adaptation in maize: The backcross approach, perspectives, limitations, and alternatives. J Exp Bot 58:351–360
Ribaut J-M, Hoisington DA, Deutsch JA, Jiang C, González-de-León D (1996) Identification of quantitative trait loci under drought conditions in tropical maize. 1. Flowering parameters and the anthesis-silking interval. Theor Appl Genet 92:905–914
Ribaut J-M, Jiang C, González-de-León D, Edmeades GO, Hoisington DA (1997) Identification of quantitative trait loci under drought conditions in tropical maize. 2. Yield components and marker-assisted selection strategies. Theor Appl Genet 94:887–896
Ribaut J-M, Fracheboud Y, Monneveux P, Bänziger M, Vargas M, Jiang C (2007) Quantitative trait loci for yield and correlated traits under high and low soil nitrogen conditions in tropical maize. Mol Breed 20:15–29
Ribaut J-M, Betrán J, Monneveux P, Setter T (2008) Drought tolerance in maize. In: Bennetzen JL, Hake SC (eds) Handbook of maize: Its biology. Springer, The Netherlands, pp 311–344
Saini HS, Westgate ME (2000) Reproductive development in grain crops during drought. Adv Agron 68:59–96
Salter PJ, Goode JE (1967) Crop responses to water deficit at different stages of growth. Research Review No. 2. Commonwealth Agricultural Bureaux, Farnham Royal
Salvi S, Tuberosa R (2005) To clone or not to clone plant QTLs: present and future challenges. Trends Plant Sci 10:297–304
Sari-Gorla M, Krajewski P, Di Fonzo N, Villa M, Frova C (1999) Genetic analysis of drought tolerance in maize by molecular markers. II. Plant height and flowering. Theor Appl Genet 99:289–295
Schussler JR, Westgate ME (1995) Assimilate flux determines kernel set at low water potential in maize. Crop Sci 35:1074–1080
Sibov ST, De Souza CL, Garcia AAF, Silva AR, Garcia AF, Mangolin CA, Benchimol LL, De Souza AP (2003) Molecular mapping in tropical maize (Zea mays L) using microsatellite markers. 2. Quantitative trait loci (QTL) for grain yield, plant height, ear height and grain moisture. Hereditas 139:107–115
Sivakumar MVK, Das HP, Brunini O (2005) Impacts of present and future climate variability and change on agriculture and forestry in the arid and semi-arid tropics. Clim Change 70:31–72
Tuberosa R, Salvi S, Sanguineti MC, Landi P, Maccaferri M, Conti S (2002a) Mapping QTLs regulating morpho-physiological traits and yield: Case studies, shortcomings and perspectives in drought-stressed maize. Ann Bot 89:941–963
Tuberosa R, Sanguineti MC, Landi P, Giuliani MM, Salvi S, Conti S (2002b) Identification of QTLs for root characteristics in maize grown in hydroponics and analysis of their overlap with QTLs for grain yield in the field at two water regimes. Plant Mol Biol 48:697–712
Vargas M, van Eeuwijk FA, Crossa J, Ribaut J-M (2006) Mapping QTLs and QTL × environment interaction for CIMMYT maize drought stress program using factorial regression and partial least squares methods. Theor Appl Genet 112:1009–1023
Veldboom LR, Lee M (1996) Genetic mapping of quantitative trait loci in maize in stress and nonstress environments: II. Plant height and flowering. Crop Sci 36:1320–1327
Westgate ME, Boyer JS (1985) Carbohydrate reserves and reproductive development at low leaf water potentials in maize. Crop Sci 25:762–769
Zeng ZB (1994) Precision mapping of quantitative trait loci. Genetics 136:1457–1468
Zeng ZB, Wang T, Zou W (2005) Modeling quantitative trait loci and interpretation of models. Genetics 169:1711–1725
Zinselmeier C, Lauer MJ, Boyer JS (1995) Reversing drought-induced losses in grain yield: Sucrose maintains embryo growth in maize. Crop Sci 35:1390–1400
Acknowledgments
We are grateful to E. Huerta for her expert assistance in constructing the linkage map, to the CIMMYT field workers in Mexico and in Zimbabwe and to S. Pastrana for excellent management of the experiments in Mexico. We are also grateful to the anonymous reviewers and to M. Schönberg for helpfully reviewing the manuscript. This work was funded by the Swiss Agency for Development and Cooperation (SDC) and the North–South Centre (formerly the Swiss Centre for International Agriculture ZIL) of ETH Zurich.
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Communicated by F. van Eeuwijk.
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Messmer, R., Fracheboud, Y., Bänziger, M. et al. Drought stress and tropical maize: QTL-by-environment interactions and stability of QTLs across environments for yield components and secondary traits. Theor Appl Genet 119, 913–930 (2009). https://doi.org/10.1007/s00122-009-1099-x
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DOI: https://doi.org/10.1007/s00122-009-1099-x