Cited by 397Genetic Mapping and Diversity in Plants and AnimalsGenetics and Plant BreedingCrop Yield and Soil Fertility

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Mapping QTLs Regulating Morpho-physiological Traits and Yield: Case Studies, Shortcomings and Perspectives in Drought-stressed Maize

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TUBEROSA, R.·2002·Annals of Botany

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Abstract

Comparative analysis of a number of studies in drought-stressed maize (Zea mays L.) reporting quantitative trait loci (QTLs) for abscisic acid concentration, root characteristics, other morpho-physiological traits (MPTs) and grain yield (GY) reveals their complex genetic basis and the influence of the genetic background and the environment on QTL effects. Chromosome regions (e.g. near umc11 on chromosome 1 and near csu133 on chromosome 2) with QTLs controlling a number of MPTs and GY across populations and conditions of different water supply have been identified. Examples are presented on the use of QTL information to elucidate the genetic and physiological bases of the association among MPTs and GY. The QTL approach allows us to develop hypotheses accounting for these associations which can be further tested by developing near isogenic lines (NILs) differing for the QTL alleles. NILs also allow for a more accurate assessment of the breeding value of MPTs and, in some cases, may allow for the map-based cloning of the gene(s) underlying the QTL. Although QTL analysis is still time-consuming and resource-demanding, its integration with genomics and post-genomics approaches (e.g. transcriptome, proteome and metabolome analyses) will play an increasingly important role for the identification and validation of candidate genes affecting MPTs and GY.

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Introduction to Quantitative Genetics.
Edwards, A. W. F., & Falconer, D. S. (1982) · Biometrics · doi:10.2307/2529912 · Cited by 21,447
AFLP: a new technique for DNA fingerprinting
Vos, P., Hogers, R. C. J., Bleeker, M., Reijans, M., van de Lee, T., Hornes, M., Frijters, A., Pot, J., Paleman, J., Kuiper, M. T. R., et al. (1995) · Nucleic Acids Research · doi:10.1093/nar/23.21.4407 · Cited by 12,405
Analysis of the genome sequence of the flowering plant Arabidopsis thaliana
Initiative, T. A. G. (2000) · Nature · doi:10.1038/35048692 · Cited by 9,301
Construction of a genetic linkage map in man using restriction fragment length polymorphisms.
Botstein, D., White, R. L., Skolnick, M. H., & Davis, R. W. (1980) · Europe PMC (PubMed Central) · Cited by 8,327
Genetics and Analysis of Quantitative Traits
(2002) · Journal of Animal Breeding and Genetics · doi:10.1046/j.1439-0388.2002.00356.x · Cited by 6,176
Mapping mendelian factors underlying quantitative traits using RFLP linkage maps.
Lander, E. S., & Botstein, D. (1989) · Genetics · doi:10.1093/genetics/121.1.185 · Cited by 5,236
Differential Display of Eukaryotic Messenger RNA by Means of the Polymerase Chain Reaction
Liang, P., & Pardee, A. B. (1992) · Science · doi:10.1126/science.1354393 · Cited by 4,964
Empirical threshold values for quantitative trait mapping.
Churchill, G. A., & Doerge, R. W. (1994) · Genetics · doi:10.1093/genetics/138.3.963 · Cited by 4,935
Identification of markers linked to disease-resistance genes by bulked segregant analysis: a rapid method to detect markers in specific genomic regions by using segregating populations.
Michelmore, R. W., Paran, I., & Kesseli, R. (1991) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.88.21.9828 · Cited by 4,551
Serial Analysis of Gene Expression
Velculescu, V. E., Zhang, L., Vogelstein, B., & Kinzler, K. W. (1995) · Science · doi:10.1126/science.270.5235.484 · Cited by 3,713

Show all 247 references

Research works printed but not linked: 15

Beavis WD. 1994. The power and deceit of QTL experiments: lessons from comparative QTL studies. Proceedings of the 49th Annual Corn and Sorghum Research Conference American Seed Trade Association, Washington, D.C., 250±266.
Bowen B, Luedtke R. 1997. Understanding maize through genomics. Proceedings of the 52nd American Seed Trade Association Corn Sorghum Research Conference, December 10±11, 1997, Chicago, Illinois. Washington, D.C.: American Seed Trade Association, 29± 43.
Conti S, Frascaroli E, Gherardi F, Landi P, Sanguineti MC, Stefanelli S, Tuberosa R. 1994. Accumulation of and response to abscisic acid in maize. In: Bianchi A et al., eds. Proceedings of the XVI Conference of the Eucarpia Maize and Sorghum Section, Bergamo, Italy, June 6±9, 1993, 212±223.
Crosbie TM. 1982. Changes in physiological traits associated with long- term breeding efforts to improve grain yield of maize. Proceedings of the 37th Annual Corn and Sorghum Research Conference American Seed Trade Association, Washington, D.C., 206±223.
Giuliani MM, Darrah LL, Salvi S, Sanguineti MC, Landi P, Conti S, Tuberosa R. 2000. Comparative QTL analysis in maize for vertical root pulling resistance in the ®eld and root traits in hydroponics. International Conference on Plant & Animal Genome VIII, January 9±12, San Diego, California, 114.
Harjes CE, Smith ME, McCouch SR, Tanksley SD. 1999. Advanced backcross QTL analysis and introgression of perennial teosinte (Zea diploperennis) alleles to maize. Plant & Animal Genome VII Conference, January 17±21, San Diego, California, 260.
Landi P, Giuliani MM, Darrah LL, Tuberosa R, Conti S, Sanguineti MC. 2001b. Variability for root and shoot traits in a maize population grown in hydroponics and in the ®eld and their relationships with vertical root pulling resistance. Maydica (in press).
Mugo SN, Ba Ènziger M, Edmeades GO. 2000. Prospects of using ABA in selection for drought tolerance in cereal crops. In: Ribaut JM, Poland D, eds. Molecular approaches for the genetic improvement of cereals for stable production in water-limited environments. A Strategic Planning Workshop held at CIMMYT, El Bata Ân, Mexico, June 21±25, 1999, 73±78.
Openshaw S, Frascaroli E. 1997. QTL detection and marker-assisted selection for complex traits in maize. Proceedings of the 52nd Annual Corn and Sorghum Research Conference American Seed Trade Association. Washington, D.C., 44±53.
Phillips RL, Kim TS, Kaeppler SM, Parentoni SN, Shaver DL, Stucker RI, Openshaw SJ. 1992. Genetic dissection of maturity using RFLPs. Proceedings of the 47th Annual Corn and Sorghum Research Conference American Seed Trade Association, Washington, D.C., 135±150.
Ragot M, Gay G, Muller JP, Durovray J. 2000. Ef®cient selection for adaptation to the environment through QTL mapping and manipulation in maize. In: Ribaut JM, Poland D, eds. Molecular approaches for the genetic improvement of cereals for stable production in water-limited environments. A Strategic Planning Workshop held at CIMMYT, El Bata Ân, Mexico, June 21±25, 1999, 128±130.
Salamini F. 1999. Plant breeding and sustainable agriculture ± introduction to the problem. Proceedings of the 1999 World Seed Conference, September 6±8, Cambridge, UK, 59±62.
Setter TL. 1997. Role of the phytohormone ABA in drought tolerance: potential utility as a selection tool. In: Edmeades GO, Ba Ènziger M, Mickelson HR, Pen Äa-Valdivia CB, eds. Developing drought-and low N-tolerant maize. Proceedings of a Symposium, March 25±29, 1996, CIMMYT, El Bata Ân, Mexico, 142±150.
Sullivan CY. 1983. Genetic variability in physiological mechanisms of drought resistance. Iowa State Journal of Research 57: 423±439.
Tuberosa R, Sanguineti MC, Ribaut JM, Landi P, Giuliani M, Salvi S, Conti S. 2000. QTL analysis of root characteristics in maize grown in hydroponics as related to ®eld performance under drought conditions. International Conference on Plant & Animal Genome VIII, January 9±12, 2000, San Diego, California, 5.

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Pestsova, E. G., Lichtblau, D. M., Wever, C., Presterl, T., Bolduan, T., Ouzunova, M., & Westhoff, P. (2015) · Euphytica · doi:10.1007/s10681-015-1625-7 · Cited by 33
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Malamy, J. E. (2009) · Wiley-Blackwell eBooks · doi:10.1002/9781444310023.ch4 · Cited by 35
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Jovanovic, M., Lefebvre, V., Laporte, P., Gonzalez‐Rizzo, S., Lelandais‐Brière, C., Frugier, F., Hartmann, C., & Crespi, M. D. (2007) · Advances in botanical research · doi:10.1016/s0065-2296(07)46002-5 · Cited by 33
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Balakrishnan, D., Robin, S., Rabindran, R., Senthil, N., Raveendran, M., & Joel, A. J. (2014) · Euphytica · doi:10.1007/s10681-014-1182-5 · Cited by 25
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Authors: TUBEROSA, R.
Affiliations: University of Bologna (IT)
Corresponding author: TUBEROSA, R.
ORCID: TUBEROSA, R.
Venue: Annals of Botany
Publisher: Oxford University Press (OUP)
Published: 2002-06-15
Volume: 89
Issue: 7
Pages: 941-963
ISSN: 0305-7364 (ISSN-L)
1095-8290
DOI: 10.1093/aob/mcf134
PMC: PMC4233811
OpenAlex: W2186350550
Cited by: 397
References: 247
Citations by year: 2026: 8 · 2025: 7 · 2024: 8 · 2023: 20 · 2022: 15 · 2021: 14 · 2020: 10 · 2019: 20 · 2018: 14 · 2017: 19 · 2016: 25 · 2015: 18 · 2014: 20 · 2013: 22 · 2012: 21
FWCI: 6.39
Type: journal article
Language: en
Open access: bronze
doi.org
Locations: Annals of Botany (publishedVersion)
Europe PMC (PubMed Central) (publishedVersion)
PubMed Central (publishedVersion)
PubMed (publishedVersion)
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
Life Sciences › Agricultural and Biological Sciences › Plant Science › Genetics and Plant Breeding
Life Sciences › Agricultural and Biological Sciences › Agronomy and Crop Science › Crop Yield and Soil Fertility
Keywords: drought stress, maize, quantitative trait loci, morpho-physiological traits, grain yield, abscisic acid, root traits, near-isogenic lines, positional cloning, candidate genes, genetic background effects, water supply
MeSH terms: Abscisic Acid, Alleles, Chromosome Mapping, Zea mays, Disasters, Environment, Morphogenesis, Seeds, Water, Plant Roots, Quantitative Trait, Heritable, Proteome, Genomics

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Mapping QTLs Regulating Morpho-physiological Traits and Yield: Case Studies, Shortcomings and Perspectives in Drought-stressed Maize

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