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Meta-analysis of constitutive and adaptive QTL for drought tolerance in maize

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Abstract

The response of plants to drought stress is very complex and involves expression of a lot of genes and pathways for diverse mechanisms and interactions with environments. Many quantitative trait loci(QTL) mapping experiments have given heterogeneous results due to use of different genotypes and populations tested in various environments. Our purpose was to identify some important constitutive and adaptive QTL using meta-analysis and to find specific genes and their families for speculating on drought tolerance networks. A total of 239 QTL detected under water-stressed conditions and 160 detected under control conditions from 12 populations tested in 22 experiments were compiled and compared, resulting in identification of 39 consensus QTL under water stress, and 36 under control conditions. Of them, 32 consensus QTL were supposed to be adaptive while others were constitutive QTL. The consensus QTL on chromosomes 1, 2, 3, 5, 6 and 9 were highly overlapped with several different traits and could be identified under multiple environments, most of which were related to traits of high phenotypic variance. Moreover, 48 candidate genes related to stress tolerance were located in silico in these consensus QTL regions what should facilitate the construction of QTL networks and help to understand the mechanisms related to drought tolerance.

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References

  • Agrama HAS, Moussa M (1996) Mapping QTL in breeding for drought tolerance in maize (Zea mays L.). Euphytica 91:89–97

    Article  CAS  Google Scholar 

  • Arcade A, Labourdette A, Falque M, Mangin B, Chardon F, Charcosset A, Joets J (2004) BioMercator: integrating genetic maps and QTL towards discovery of candidate genes. Bioinformatics 20:2324–2326

    Article  CAS  PubMed  Google Scholar 

  • Ballini E, Morel J, Droc G, Price A, Courtois B, Notteghem J, Tharreau D (2008) A genome-wide meta-analysis of rice blast resistance genes and quantitative trait loci provided new insights into partial and complete resistance. Mol Plant Microbe Interact 21:859–868

    Article  CAS  PubMed  Google Scholar 

  • Beavis WD, Smith OS, Grant D, Fincher RR (1994) Identification of quantitative trait loci using a small sample of topcrossed and F4 progeny from maize. Crop Sci 34:882–896

    Google Scholar 

  • Bernardo R (2008) Molecular markers and selection for complex traits in plants: learning from the last 20 years. Crop Sci 48:1649–1664

    Article  Google Scholar 

  • Bernier J, Kumar A, Venuprasad R, Spaner D, Verulkar S, Mandal NP, Sinha PK, Peeraju P, Dongre PR, Mahto RN, Atlin G (2009) Characterization of the effect of a QTL for drought tolerance in rice, qtl2.1, over a range of environments in the Philippines and eastern India. Euphytica 166:207–217

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Chandler VL, Brendel V (2002) The maize genome sequencing project. Plant Physiol 130:1594–1597

    Article  CAS  PubMed  Google Scholar 

  • 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

    Article  CAS  PubMed  Google Scholar 

  • Collins NC, Tardieu F, Tuberosa R (2008) Quantitative trait loci and crop performance under abiotic stress: where do we stand? Plant Physiol 147:469–486

    Article  CAS  PubMed  Google Scholar 

  • Darvasi A, Soller M (1997) A simple method to calculate resolving power and confidence interval of QTL map location. Behav Genet 27:125–132

    Article  CAS  PubMed  Google Scholar 

  • Frova C, Krajewski P, Di Fonzo N, Villa M, Sari-Gorla M (1999) Genetic analysis of drought tolerance in maize by molecular markers I. Yield components. Theor Appl Genet 99:280–288

    Article  Google Scholar 

  • Glass GV (1976) Primary, secondary, and meta-analysis of research. Educ Res 5:3–8

    Google Scholar 

  • Goffinet B, Gerber S (2000) Quantitative trait loci: a meta-analysis. Genetics 155:463–473

    CAS  PubMed  Google Scholar 

  • Guingo E, Hébert Y, Charcosset A (1998) Genetic analysis of root traits in maize. Agronomie 18:225–235

    Article  Google Scholar 

  • Guo J, Su G, Zhang J, Wang G (2008) Genetic analysis and QTL mapping of maize yield and associate agronomic traits under semi-arid land condition. Afr J Biotechnol 7:1829–1838

    CAS  Google Scholar 

  • Hanocq E, Laperche A, Jaminon O, Lainé AL, Le Gouis J (2007) Most significant genome regions involved in the control of earliness traits in bread wheat, as revealed by QTL meta-analysis. Theor Appl Genet 114:569–584

    Article  CAS  PubMed  Google Scholar 

  • Hao Z, Li X, Xie C, Li M, Zhang D, Bai L, Zhang S (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

    Article  Google Scholar 

  • Hedges LV, Olkin I (1985) Statistical methods for meta-analysis. Academic Press, New York

    Google Scholar 

  • Kearsey MJ, Farquhar AGL (1998) QTL analysis in plants; where are we now? Heredity 80:137–142

    Article  PubMed  Google Scholar 

  • Khavkin E, Coe EH (1997) Mapped genomic locations for developmental functions and QTLs reflect concerted groups in maize (Zea mays L.). Theor Appl Genet 95:343–352

    Article  CAS  Google Scholar 

  • Khowaja FS, Norton GJ, Courtois B, Price AH (2009) Improved resolution in the position of drought-related QTLs in a single mapping population of rice by meta-analysis. BMC Genomics 10:276

    Article  PubMed  CAS  Google Scholar 

  • Landi P, Sanguineti MC, Salvi S, Giuliani S, Bellotti M, Maccaferri M, Conti S, Tuberosa R (2005) Validation and characterization of a major QTL affecting leaf ABA concentration in maize. Mol Breed 15:291–303

    Article  CAS  Google Scholar 

  • 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

    Article  CAS  PubMed  Google Scholar 

  • Lebreton C, Lazić-Jančić V, Steed A, Pekić S, Quarrie SA (1995) Identification of QTL for drought responses in maize and their use in testing causal relationships between traits. J Exp Bot 46:853–865

    Article  CAS  Google Scholar 

  • Li X, Li X, Hao Z, Tian Q, Zhang S (2005) Consensus map of the QTL relevant to drought tolerance of maize under drought conditions. Sci Agric Sin 38:882–890

    CAS  Google Scholar 

  • Liu S, Dall MD, Griffey CA, McKendry AL (2009) Meta-analysis of QTL associated with Fusarium head blight resistance in wheat. Crop Sci 49:1955–1968

    Article  CAS  Google Scholar 

  • Lu GH, Tang JH, Yan JB, Ma XQ, Li JS, Chen SJ, Ma JC, E LZ, Liu ZX, 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

    Article  CAS  Google Scholar 

  • Lv X, Li X, Xie C, Hao Z, Ji H, Shi L, Zhang S (2008) Comparative QTL mapping of resistance to sugarcane mosaic virus in maize based on bioinformatic. Hereditas 30:101–108

    PubMed  Google Scholar 

  • Moreau L, Charcosset A, Gallais A (2004) Experimental evaluation of several cycles of marker-assisted selection in maize. Euphytica 137:111–118

    Article  CAS  Google Scholar 

  • Pelleschi S, Guy S, Kim J, Pointe C, Mahé A, Barthes L, Leonardi A, Prioul J (1999) Ivr2, a candidate gene for a QTL of vacuolar invertase activity in maize leaves. Gene-specific expression under water stress. Plant Mol Biol 39:373–380

    Article  CAS  PubMed  Google Scholar 

  • Pennisi E (2008) The blue revolution, drop by drop, gene by gene. Science 320:171–173

    Article  CAS  PubMed  Google Scholar 

  • Ribaut JM, 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

    Article  CAS  PubMed  Google Scholar 

  • Ribaut JM, Hoisington DA, Deutsch JA, Jiang C, De Leon Gonzalez 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

    Article  CAS  Google Scholar 

  • Ribuat JM, Jiang C, De Leon Gonzalez 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

    Article  Google Scholar 

  • Ribuat JM, Betran J, Monneveux P, Setter T (2009) Drought tolerance in maize. In: Bennetzen JL, Hake SC (eds) Handbook of maize: its biology. Springer, Dordrecht, pp 311–344

    Chapter  Google Scholar 

  • Rong J, Feltus FA, Waghmare VN, Pierce GJ, Chee PW, Draye X, Saranga Y, Wright RJ, Wilkins TA, May OL, Smith CW, Gannaway JR, Wendel JF, Paterson AH (2007) Meta-analysis of polyploidy cotton QTL shows unequal contributions of subgenomes to a complex network of genes and gene clusters implicated in lint fiber development. Genetics 176:2577–2588

    Article  CAS  PubMed  Google Scholar 

  • Sanguineti MC, Tuberosa R, Landi P, Salvi S, Maccaferri M, Casarini E, Conti S (1999) QTL analysis of drought-related traits and grain yield in relation to genetic variation for leaf abscisic acid concentration in field-grown maize. J Exp Bot 50:1289–1297

    Article  CAS  Google Scholar 

  • 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

    Article  Google Scholar 

  • Shinozaki K, Yamaguchi-Shinozaki K (2007) Gene networks involved in drought stress response and tolerance. J Exp Bot 58:221–227

    Article  CAS  PubMed  Google Scholar 

  • Shulaev V, Cortes D, Miller G, Mittler R (2008) Metabolomics for plant stress response. Physiol Plant 132:199–208

    CAS  PubMed  Google Scholar 

  • Tuberosa R, Salvi S (2006) Genomics approaches to improve drought tolerance in crops. Trends Plant Sci 11:412–415

    Article  CAS  Google Scholar 

  • Tuberosa R, Salvi S (2009) QTL for agronomic traits in maize production. In: Bennetzen JL, Hake SC (eds) Handbook of maize: its biology. Springer, Dordrecht, pp 501–542

    Chapter  Google Scholar 

  • Tuberosa R, Sanguineti MC, Landi P, Salvi S, Casarini E, Conti S (1998) RFLP mapping of quantitative trait loci controlling abscisic acid concentration in leaves of drought-stressed maize (Zea mays L.). Theor Appl Genet 97:744–755

    Article  CAS  Google Scholar 

  • 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

    Article  CAS  PubMed  Google Scholar 

  • Tuberosa R, Sanguineti MC, Landi P, Giuliani MM, Salvi S, Conti M (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

    Article  CAS  PubMed  Google Scholar 

  • Umezawa T, Fujita M, Fujita Y, Yamaguchi-Shinozaki K, Shinozaki K (2006) Engineering drought tolerance in plants: discovering and tailoring genes to unlock the future. Curr Opin Biotechnol 17:113–122

    CAS  PubMed  Google Scholar 

  • Valliyodan B, Nguyen HT (2006) Understanding regulatory networks and engineering for enhanced drought tolerance in plants. Curr Opin Plant Biol 9:1–7

    Article  CAS  Google Scholar 

  • Van Zandt PA, Mopper S (1998) A meta-analysis of adaptive deme formation in phytophagous insect populations. Am Nat 152:595–604

    Article  CAS  PubMed  Google Scholar 

  • Vargas M, Van Eeuwijk FA, Crossa J, Ribaut JM (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

    Article  CAS  PubMed  Google Scholar 

  • Veldboom LR, Lee M (1996a) Genetic mapping of quantitative trait loci in maize in stress and nonstress environments: I. Grain yield and yield components. Crop Sci 36:1310–1319

    Article  CAS  Google Scholar 

  • Veldboom LR, Lee M (1996b) Genetic mapping of quantitative trait loci in maize in stress and nonstress environments: II. Plant height and flowering. Crop Sci 36:1320–1327

    CAS  Google Scholar 

  • Wang Y, Ji Y, Zhang Z, Zheng Y (2006) The comparative analysis based on maize integrated QTL map and meta-analysis of plant height QTLs. Chin Sci Bull 51:2219–2230

    Article  CAS  Google Scholar 

  • Welcker C, Bousssuge B, Bencivenni C, Ribaut JM, Tardieu F (2007) Are source and sink strengths genetically linked in maize plants subjected to water deficit? A QTL study of the responses of leaf growth and of anthesis-silking interval to water deficit. J Exp Bot 58:339–349

    Article  CAS  PubMed  Google Scholar 

  • Xu Y, Crouch JH (2008) Marker-assisted selection in plant breeding: from publications to practice. Crop Sci 48:391–407

    Article  Google Scholar 

Download references

Acknowledgements

The authors gratefully acknowledge Dr. Yunbi Xu from CIMMYT (International Wheat and Maize Improvement Center) for valuable comments and careful corrections to this manuscript and the finance support of the National Natural Science Foundation of China (30600394; 30721140554).

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Authors and Affiliations

  1. Institute of Crop Science, Chinese Academy of Agricultural Sciences, National Key Facilities for Crop Genetic Resources and Improvement, No. 12 Zhongguancun, South Street, Haidian District, Beijing, 100081, China

    Zhuanfang Hao, Xinhai Li, Xiulin Liu, Chuanxiao Xie, Mingshun Li, Degui Zhang & Shihuang Zhang

  2. International Maize and Wheat Improvement Center (CIMMYT), Apartado, Postal 6-641, Mexico, 06600, DF, Mexico

    Zhuanfang Hao

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  1. Zhuanfang Hao
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  2. Xinhai Li
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  3. Xiulin Liu
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  4. Chuanxiao Xie
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  6. Degui Zhang
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Correspondence to Shihuang Zhang.

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Hao, Z., Li, X., Liu, X. et al. Meta-analysis of constitutive and adaptive QTL for drought tolerance in maize. Euphytica 174, 165–177 (2010). https://doi.org/10.1007/s10681-009-0091-5

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