RFLP mapping of quantitative trait loci controlling abscisic acid concentration in leaves of drought-stressed maize (Zea mays L.)

Tuberosa, Roberto; Sanguineti, M. C.; Landi, Pierangelo; Salvi, Silvio; Casarini, Emanuela; Conti, Sergio

doi:10.1007/s001220050951

Cited by 111 publications

(64 citation statements)

References 38 publications

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“…ZmABI4 was mapped on the maize genome and found to be located on chromosome 6 (bin 5) (data not shown), which is a similar map location as that of rab17 (Frova et al, 1998). This region of chromosome 6 has been shown to be the location of significant quantitative trait loci in previous studies of yield under drought stress conditions (Ribaut et al, 1997;Quarrie et al, 1999), but it is not associated with leaf ABA content (Tuberosa et al, 1998).…”

Section: Discussionmentioning

confidence: 80%

Maize ABI4 Binds Coupling Element1 in Abscisic Acid and Sugar Response Genes

2002

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Significant progress has been made in elucidating the mechanism of abscisic acid (ABA)-regulated gene expression, including the characterization of an ABA-responsive element (ABRE), which is regulated by basic domain/Leu zipper transcription factors. In addition to the ABRE, a coupling element (CE1) has been demonstrated to be involved in ABAinduced expression. However, a trans factor that interacts with CE1 has yet to be characterized. We report the isolation of a seed-specific maize ABI4 homolog and demonstrate, using a PCR-based in vitro selection procedure, that the maize ABI4 protein binds to the CE-1 like sequence CACCG. Using electrophoretic mobility shift assays, we demonstrate that recombinant ZmABI4 protein binds to the CE1 element in a number of ABA-related genes. ZmABI4 also binds to the promoter of the sugar-responsive ADH1 gene, demonstrating the ability of this protein to regulate both ABA-and sugar-regulated pathways. ZmABI4 complements Arabidopsis ABI4 function, because abi4 mutant plants transformed with the ZmABI4 gene have an ABA-and sugar-sensitive phenotype. Identification of the maize ABI4 ortholog and the demonstration of its binding to a known ABA response element provide a link between ABA-mediated kernel development and the regulation of ABA response genes.

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Section: Discussionmentioning

confidence: 80%

Maize ABI4 Binds Coupling Element1 in Abscisic Acid and Sugar Response Genes

2002

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“…In rice, following the identification of four major QTLs influencing root traits (Courtois et al, 2000), markerassisted backcrossing (MABC) was used to introgress the alleles for greater root length from Azucena into Kalinga III, an upland variety (Steele et al, 2006(Steele et al, , 2007. In maize, a major QTL originally reported for leaf ABA concentration (Tuberosa et al, 1998) was later shown to affect root size and architecture (Giuliani et al, 2005b) and grain yield (Landi et al, 2007). Following its isogenization (Landi et al, 2005), the positional cloning of this QTL is under way at present (S. Salvi, unpublished data).…”

Section: Qtls For Drought Tolerancementioning

confidence: 99%

Quantitative Trait Loci and Crop Performance under Abiotic Stress: Where Do We Stand?: Table I.

Collins

Tardieu²,

Tuberosa³

2008

Plant Physiol.

492

330

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“…Keller et al (1999) found 16 QTLs of lodging in wheat (Triticum aestivum) but only five were common to three experiments. Tuberosa et al (1998) found 16 QTLs involved in leaf ABA concentration but only four were common to four experiments. Such an instability is not surprising because these traits strongly depend on environmental conditions.…”

Section: A Genetic Analysis Of the Response Of A Trait To Environmentmentioning

confidence: 99%

Combining Quantitative Trait Loci Analysis and an Ecophysiological Model to Analyze the Genetic Variability of the Responses of Maize Leaf Growth to Temperature and Water Deficit

et al. 2003

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Ecophysiological models predict quantitative traits of one genotype in any environment, whereas quantitative trait locus (QTL) models predict the contribution of alleles to quantitative traits under a limited number of environments. We have combined both approaches by dissecting into effects of QTLs the parameters of a model of maize (Zea mays) leaf elongation rate (LER; H. Ben Haj Salah, F. Tardieu [1997] Plant Physiol 114: 893-900). Response curves of LER to meristem temperature, water vapor pressure difference, and soil water status were established in 100 recombinant inbred lines (RILs) of maize in six experiments carried out in the field or in the greenhouse. All responses were linear and common to different experiments, consistent with the model. A QTL analysis was carried out on the slopes of these responses by composite interval mapping confirmed by bootstrap analysis. Most QTLs were specific of one response only. QTLs of abscisic acid concentration in the xylem sap colocalized with QTLs of response to soil water deficit and conferred a low response. Each parameter of the ecophysiological model was computed as the sum of QTL effects, allowing calculation of parameters for 11 new RILs and two parental lines. LERs were simulated and compared with measurements in a growth chamber experiment. The combined model accounted for 74% of the variability of LER, suggesting that it has a general value for any RIL under any environment.In an agricultural context, a plant that tolerates water deficit can produce a maximum harvested biomass under moderate water deficits. Involved mechanisms are not necessarily common with those underlying the ability of cells to survive tissue dehydration (e.g. Cushman and Bohnert, 2000; Seki et al., 2001). In maize (Zea mays), moderate water deficits usually cause no appreciable decrease in leaf water status because of an efficient stomatal control combining hydraulic and chemical messages (Tardieu and Davies, 1993;Wilkinson et al., 1998). A similar combination of messages allows maize plants to dramatically reduce leaf elongation rate (LER) under moderate water deficits sensed either in the soil or in the air, before that leaf water status is appreciably altered (Sharp et al., 2000;Tardieu et al., 2000). Reductions in stomatal conductance and in leaf expansion decrease transpiration rate, thereby saving soil water and maintaining leaf water potential at high values. They also reduce photosynthesis, growth, and yield, so optimum tolerance strategies cannot be common to different climatic scenarios. Plants with steepest responses might be most adapted to scenarios with most severe water deficits, whereas maintenance of growth and photosynthesis under deficit might be appropriate for scenarios with milder deficits. Therefore, identification of sources of variability in the responses to water deficit is necessary for designing plants adapted to a given climatic scenario.We aimed to identify and analyze the genetic variability of responses of leaf elongation to water deficits caused eit...

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RFLP mapping of quantitative trait loci controlling abscisic acid concentration in leaves of drought-stressed maize (Zea mays L.)

Cited by 111 publications

References 38 publications

Maize ABI4 Binds Coupling Element1 in Abscisic Acid and Sugar Response Genes

Maize ABI4 Binds Coupling Element1 in Abscisic Acid and Sugar Response Genes

Quantitative Trait Loci and Crop Performance under Abiotic Stress: Where Do We Stand?: Table I.

Combining Quantitative Trait Loci Analysis and an Ecophysiological Model to Analyze the Genetic Variability of the Responses of Maize Leaf Growth to Temperature and Water Deficit

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