Journal of Experimental Botany, Vol. 51, No. 342, pp. 99-106,
January 2000
© 2000 Oxford University Press
QTL: their place in engineering tolerance of rice to salinity
Plant Stress Unit, School of Biological Sciences, University of Sussex, Falmer, Brighton, Sussex BN1 9QG, UK
Received 19 January 1999; Accepted 24 June 1999
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Abstract |
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 Top Abstract IntroductionEffects of salinity on...Pyramiding of physiological...Quantitative trait loci and...Materials and methodsResults and discussionThe way forward?References |
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Secondary salinization and its relationship to irrigation are strong incentives to improve the tolerance of crops to salinity and to drought. Achieving this through the pyramiding of physiological traits (phenotypic selection without knowledge of genotype) is feasible. However, wide application of this approach is limited by the practicalities of assessing not only the parents, but also large numbers of individuals and families in segregating generations. Genotypic information is required in the form of markers for any quantitative trait loci involved (marker-assisted selection) or of direct knowledge of the genes. In the absence of adequate candidate genes for salt tolerance, a quantitative trait locus/marker-assisted selection approach has been used here. Putative markers for ion transport and selectivity, identified from analysis of amplified fragment length polymorphism, had been discovered within a custom-made mapping population of rice. Here it is reported that none of these markers showed any association with similar traits in a closely related population of recombinant inbred lines or in selections of a cultivar. Whilst markers will be of value in using élite lines from the mapping population in backcrossing, this has to be considered alongside the effort required to develop and map any given population. This result cautions against any expectation of a general applicability of markers for physiological traits. It is concluded that direct knowledge of the genes involved is needed. This cannot be achieved at present by positional cloning. The elucidation of candidate genes is required. Here the problem lies not in the analysis of gene expression but in devising protocols in which only those genes of interest are differentially affected by the experimental treatments.
Key words: salt tolerance, rice, Oryza sativa, plant breeding, QTL, marker-aided-selection.
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Introduction |
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TopAbstractIntroductionEffects of salinity on...Pyramiding of physiological...Quantitative trait loci and...Materials and methodsResults and discussionThe way forward?References |
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Much has been written about the extent of salt-affected land and its impact on agriculture, past, present and future. In the past, agricultural salinity is likely to have affected individuals and small communities, but there was enough good land to provide for food production on a regional scale (but see Jacobsen and Adams, 1958
). This may not continue to be the case in the future, due to the growth in world population and to the increasing area of land that is abandoned because of secondary salinization.
Irrigation is a common cause by which agricultural land is degraded, as salt dissolved in the irrigation water is left in the soil following evapotranspiration. The usual answer is to leach the salt through the soil profile (Hoffman, 1990) with yet more water. The additional water can itself become a problem if drainage is inadequate because the leaching solution collects in the groundwater. Paradoxically, overcoming lack of water through irrigation can lead to salinized, waterlogged land. In this context, altering the tolerance of plants to drought and salinity appear attractive propositions.
Attempts have been made over many years to change the salt tolerance of major crops. The rationale is that because salt tolerance has evolved among the families of flowering plants (halophytes), it should be possible to mimic this process. The success achieved in producing salt-tolerant varieties of crops has, however, been very limited. Over the years that records have been kept, only about 25 cultivars in just 12 species have been released for their salt tolerance (Flowers and Yeo, 1995; Shannon and Noble, 1990). Since 1993 there have only been four registrations additional to those recorded in 1995 (Flowers and Yeo, 1995), one for alfalfa (AlDoss and Smith, 1998), one for soybean (Owen et al., 1994) and two for rice (Oliver-Inciong, 1996). It was concluded (Flowers and Yeo, 1995) that the complexity of the task combined with a lack of real urgency lay behind the low success rate to date. Changes in population pressure are likely to increase the urgency with which combating salinization is viewed by countries and donor agencies. This urgency will not, however, make the task any easier. Effective methodologies will be needed for enhancing salt tolerance in a wide variety of crops. History suggests that it will not be easy to provide such protocols, although powerful new technologies with which to alter genes and their expression within plants are now available. Although these manipulative techniques are being applied widely to characteristics attributable to single genes, they have not been much used to enhance tolerance to abiotic stresses: this tolerance generally shows quantitative inheritance.
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Effects of salinity on plants |
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TopAbstractIntroductionEffects of salinity on...Pyramiding of physiological...Quantitative trait loci and...Materials and methodsResults and discussionThe way forward?References |
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Salinity affects virtually all aspects of a plant's physiology. The ability to survive in saline environments requires multiple adaptations of the plant. For example, in the halophyte Suaeda maritima tolerance requires tight coupling of growth and ion accumulation (Yeo and Flowers, 1986
). This is a process which is associated with an early development of the endodermis (Hajibagheri et al., 1985) and an ability to compartmentalize ions reaching the leaves (Flowers et al., 1986; Harvey et al., 1981). Compartmentation, in turn, requires adaptation of membranes (Leach et al., 1990a, b) and an ability to synthesize a compatible solute (Flowers et al., 1978; Hall et al., 1978). There are even adaptations at the level of protein synthesis to cope with the relatively low potassium concentration found in the mature mesophyll cytoplasm (Flowers and Dalmond, 1992). Given that evolutionary adaptation to salinity involves such a complex set of parameters, many of which presumably have still not been uncovered, then it is not surprising that attempts to change the salt tolerance of a crop are difficult to achieve (Yeo and Flowers, 1989). A critical question is how to determine what are the limiting factors or weak links in the chain of events that leads to resistance or sensitivity.
How might such limiting factors be detected? A comparative approach should, in principle, yield critical differences between sensitive and resistant plants. However, it is important that the differences that are detected are related to differences in tolerance and not to other differences between the plants being compared. Thus the closer, genetically, are the plants used for any such comparison the better. Historically, comparisons have been made both between and within species, with comparative physiology providing important information in many cases: for example, in the case of maize (Ashraf and McNeilly, 1989; Cerda et al., 1995; Cramer, 1992; Maiti et al., 1996), rice (Yeo et al., 1990) and wheat (Ahsan et al., 1996; Ashraf and O'Leary, 1997, 1996; Davenport et al., 1997; Dubcovsky et al., 1996; Gorham, 1990; Gorham et al., 1997). However, understanding physiological differences generally still leaves us a long way from understanding genetic differences, as the links between genes and physiology generally remain tenuous in plants. It is still necessary to make that jump to discovering the genetic basis of phenotypic differences in resistance.
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Pyramiding of physiological traits |
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TopAbstractIntroductionEffects of salinity on...Pyramiding of physiological...Quantitative trait loci and...Materials and methodsResults and discussionThe way forward?References |
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A number of crop plants have been the subject of extensive efforts to alter their tolerance to salinity. Rice is a particularly useful example, because of its requirement for irrigation for maximum yield, its sensitivity to salinity and its relatively small genome.
Investigations of the effects of salinity on rice have been underway for more than 50 years (Kapp, 1947; Pearson, 1959) and attempts to enhance the salt tolerance in rice through breeding date from the early 1970s (Akbar et al., 1972). In spite of considerable effort, through both international and national breeding programmes, progress in enhancing tolerance has been slow, with few new cultivars released (perhaps the most spectacular has been CSR10, developed at the Central Soil Salinity Research Institute in India). Initially the effort was made in screening collected germplasm for resistance to salinity at the seedling stage. This led to crossing programmes, but little enhancement in tolerance (Yeo et al., 1988). Resistance was associated with a tall habit and on dwarfing, to produce a plant with a reasonable harvest index, resistance tended to be lost. A vigorous plant is, undoubtedly, an important component of salt resistance in rice, but is not the whole answer. An ability to limit sodium uptake from the roots, to distribute ions in older rather than younger leaves and to tolerate the ions accumulated in the leaves are also important facets of resistance (Yeo et al., 1990).
An approach to enhancing resistance through selection of parents on the basis of physiological criteria and the subsequent combining of these traits, in a process termed pyramiding, was advocated (Yeo et al., 1990). This has led to the successful release of two cultivars with enhanced resistance to salt (IRRI, 1997) and shows that, in common with many successes in plant breeding, progress is possible by phenotypic selection in complete ignorance of the genes involved.
There are, however, important constraints to breeding for salt tolerance based upon physiological traits. Firstly there is a matter of statistics. The phenotype of a quantitative trait is a statistical property of a population, reflecting both the quantitative nature of the trait and the high level of genotype/environment interaction usual for such traits. By definition, a statistical property cannot be determined from the measurement of the phenotype of an individual. But it is with individual plants that breeders work.
Secondly, there is a matter of logistics. While the screening process can be used to select parents, it cannot generally be used to select individuals within the subsequent breeding populations. Physiological measurements that can be made on a few plants or tens of varieties in a laboratory experiment cannot generally be replicated with thousands of plants in the field, the size of just one typical F2 population. So, it is rarely possible to use physiological screening on a field scale.
Finally, there is the matter of the destructive nature of many physiological assays. For example, the whole plant may need to be sampled for measurement of an ion content. An additional constraint is that, in order to differentiate between stress-tolerant and -susceptible phenotypes it is often necessary to expose plants to salt concentrations that prove lethal to the sensitive genotype, as the expression of the resistant phenotype requires a relatively high salt concentration. Such a procedure may be consistent with making choices of parent lines where these are homozygous or near homozygous, but is inapplicable where individual plants need to be chosen.
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Quantitative trait loci and marker assisted selection |
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TopAbstractIntroductionEffects of salinity on...Pyramiding of physiological...Quantitative trait loci and...Materials and methodsResults and discussionThe way forward?References |
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All these problems might be overcome by the development of strategies that use markers (MAS: Marker Aided or Assisted Selection) to trace those quantitative trait loci (QTL) presumed to underlie physiological phenotypes. Initial mapping of the QTL is a protracted affair, but markers, once generated, can be used quickly and, conceivably, on various populations. Genotypic information overcomes the problem of statistics. Markers provide essentially ‘yes-no’ information on an individual, not probability information on a population. The markers have the potential to indicate unequivocally the genotype of a single plant. The sensitivity of assays of DNA also means that the procedure is non-destructive so far as an individual is concerned. Only a part of the plant needs to be sampled and, because the information sought is genotypic, it is not necessary to expose the plant to stress, as is the case in assessing the physiological phenotype. The use of DNA-based marker technology is becoming routine and capable of dealing with large numbers of samples. This trend seems certain to continue.
The logistics and difficulties of the procedures should not, however, be underestimated. Any mapping programme must contend with those logistical problems that disqualify the use of physiological screening within large breeding populations. Quantitative traits for stress tolerance, which are likely to be expressed only under stress and which show large environmental effects, need a screening procedure designed to cope with the expected degree of variation. This is particularly important, as the mapping is only as good as the quality of the quantitative phenotypic data. The scale of this type of phenotyping operation contrasts dramatically with scoring of visible characters, including traits such as resistance/susceptibility to pests and diseases. Phenotyping physiological traits constrains the size of a mapping population by practical considerations and this may take precedence over the ideals of statistical and genetical analysis. However, the size of the population remains important, as the more meiosis events are repeated in the population the more chance there is of finding a recombination event close to the gene of interest (the QTL). The more difficult a trait is to phenotype the more compromise may have to be made, but then the more difficult the trait is to phenotype the greater is the need for marker-assisted selection in plant breeding. It is suggested that a minimum of 100 lines is required for mapping a population of recombinant inbred line (RILs). There is no need for markers for a trait that a breeder can score by eye.
Given the effort involved in finding a marker it is important to know if its use is restricted to a single population or if it can be used more widely. Since QTL and putative markers in a custom-made mapping population (IR55178; Koyama, personal communication), have been found, four of these markers (for sodium and potassium transport and selectivity) in a closely related cross and in two near-isogenic lines of IR36 that differ in sodium transport to the shoot have been sought.
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Materials and methods |
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TopAbstractIntroductionEffects of salinity on...Pyramiding of physiological...Quantitative trait loci and...Materials and methodsResults and discussionThe way forward?References |
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Plant material
A four-way cross (IR59462) of Oryza sativa L was constructed at the International Rice Research Institute (IRRI) from land races and breeding lines (Nona Bokra/Pokkali//IR4630–22– 2-5–1-3/IR10167–129–3-4). Nona Bokra and Pokkali are traditional tall types that have good overall performance in saline soils, but poor performance in terms of those traits concerned with ion transport and compartmentation. The two breeding lines were used as potential donors of leaf compartmentation and tissue tolerance, as well as being of the dwarf plant type (Yeo et al., 1990
).
A population of RILs was produced at the University of Sussex from a random subsample (of about 20%) of the F2 (of about 3000) produced at IRRI (Garcia et al., 1995). Of the 599 seed originally planted, 371 plants produced seed within six months; those that failed to do so were rejected. From these plants an F7 population was produced by single-seed descent of which 150 lines were used in the current experiments.
Near-isogenic lines within IR36 were selected (Yeo et al., 1988) and shown to differ 2-fold in sodium transport while being similar for potassium transport, growth and water use efficiency (Yadav et al., 1996). These lines, designated ‘IR36-high’ and ‘IR36-low’ sodium were also used in our studies.
Growth of plants
IR59462 RILs:
Seed of each RIL was soaked for up to 2 d in water. Ten seeds of each line were planted in three 7x7x8 (deep) cm pots containing sand
(previously washed for 1 week with numerous changes of tap water). One pot of each line was placed at random in each of three 1 m2 plastic tanks, producing a replicated and completely randomized design. The pots were irrigated, four times per day with a nutrient solution, from a reservoir below the plants. The sodium salts in the solution (Yoshida et al., 1972) were replaced with potassium salts and the phosphate concentration reduced, because phosphate toxicity at high transpirational demand has often been observed. Theoretical and modelled (MINTEQA2, 1991) concentrations of the components of the solution have been published (Yeo et al., 1999).
Plants were grown in a greenhouse (minimum of 25 °C during the night and 28 °C during the day; automatic venting at 33±3 °C) with supplemental light for 12 h d-1 (400 W high pressure sodium lamps). The light flux density ranged from 350 µmol m-2 s-1 to 1000 µmol m-2 s-1: most commonly it was 400–500 µmol m-2 s-1.
The culture solution was salinized after 14 d, by slowly adding 5 M NaCl to each reservoir so that the concentration rose to 50 mol m-3. After a further 7 d the concentration was raised to 75 mol m-3 NaCl (an EC of between 10 and 11 dS m-1).
IR36 lines:
Plants of IR36-high and IR36-low were grown in potting compost in the glasshouse and used for the extraction of DNA and sodium uptake.
Phenotyping
IR59462:
Just prior to harvesting, the mean heights of plants in one tank were estimated. Then, 9 d after initial salinization, the shoots of five plants were sampled from each pot, the plants washed at least three times in a large excess of water, blotted and dried in an oven at 80 °C. Shoots were extracted in acetic acid (100 mol m-3) for 2 h at 90 °C. Sodium and potassium were determined in the extract by atomic absorption spectroscopy (Unicam 919). Results were calculated both as the concentration of various ions in the shoot on a dry weight basis and as the quantity of ions in the shoot (the product of concentration and dry weight).
IR36:
The plants used for DNA extraction (see below) were cut down to the level of the compost, which was leached with 50 mol m-3 NaCl. New growth was harvested after 10 d exposure to NaCl and sodium extracted as described above.
Genotyping
IR59462:
Following the harvest of IR59462, the remaining leaves were removed and the tanks and pots flushed with tap water, then water purified by reverse osmosis. After washing, fresh culture solution was introduced in the reservoirs and the plants allowed to regrow (rattoon) for a further 2 weeks, before they were harvested, wrapped in aluminium foil, plunged into liquid nitrogen and stored at -70 °C until required.
DNA was extracted from 2-week old leaves of plants as described by (Dellaporta et al., 1983). AFLP analysis was carried out following the method of Vos (Vos, 1995), using EcoRI and MseI restriction enzymes and adapted primers. Five additional bases were added in total to the core primer sequences during selective amplification, two on the EcoRI primer and three on the MseI primer. EcoRI primers were radioactively labelled with 33P-ATP for detection purposes. All products were run on a 6% denaturing polyacrylamide gel. After electrophoresis the gels were dried onto filter paper and exposed to film.
IR36:
Shoots were harvested and DNA extracted as described for IR59462.
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Results and discussion |
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TopAbstractIntroductionEffects of salinity on...Pyramiding of physiological...Quantitative trait loci and...Materials and methodsResults and discussionThe way forward?References |
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Using AFLPs a number of markers associated with QTL for various aspects of the presence of sodium and potassium in the shoots of rice have been located. RILs produced from parents showing extreme phenotypes for sodium and potassium transport (the cross of IR 4630- and IR 15324-, designated IR55178) were analysed and 16 QTL governing ion concentration in the shoot were identified on four chromosomes (ML Koyama, personal communication). Twelve of these affected shoot concentration through coincidence with QTL for dry weight production (vigour) and were therefore ambiguous—all of these were on one arm of chromosome 6. Four QTL were independent of vigour and are considered to reflect processes of uptake of ions in the root. One QTL for high sodium uptake (QNa) is on chromosome 1, two QTL for potassium (QK1, QK2) uptake are on chromosomes 9 and 6 (on the other arm than the dry weight QTL); a QTL for Na : K discrimination (QNaK) is on chromosome 4. Two other populations of rice were used to determine the value of the AFLP markers for QTL in populations others than those originally mapped: the cross IR54962 and the selections ‘high’ and ‘low’ of IR36.
The four-way-cross, IR59462, produced plants whose average height (39.6 cm) 23 d after planting was a little less than that of the tall salt-tolerant land race, Pokkali (43 cm). The dry weights of the lines of IR59462 were approximately normally distributed about the population mean, as were the potassium concentrations in the shoots (Fig. 1a, b). The distribution of sodium concentration was, on the other hand, skewed (Fig. 1c) with a small number of lines containing relatively high salt concentrations.
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Subsamples, initially of 23 lines and later increased to 55 lines, of IR59462 were selected to test whether the AFLP markers associated with high Na uptake (QNa), high K uptake (QK1 and QK2) and low Na : K ratio (QNaK) in IR55178 were also markers for the same traits in IR59462. The presence or absence of markers was tested in two subsamples of the IR59462 population in which one group (high) contained a quantity of sodium in its shoots of at least 1.8 times that of the other (low) sample using a contingency table (Table 1
). None of the four markers associated with salt tolerance in the mapping population (IR55178) was associated with either the ‘high’ or the ‘low’ subsets of IR59462. The marker QNaK had a very low incidence (Table 1).
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The presence or absence of the IR55178 marker QNa was also evaluated in two populations of the rice variety IR36 that had been previously selected (Yeo et al., 1988
) for differential sodium accumulation in the leaves. The concentration of sodium in leaves of the samples of the ‘high’ selection
(0.35±0.05 mmol g-1 dry weight) was more than double that of the ‘low’ (0.14±0.03 05 mmol g-1 dry weight) selection (Fig. 2). There was no significant association of QNa from IR55178 with average leaf sodium concentration in IR36 (4 plants of 20 in the high group contained the marker and 2 of 19 in the low population: 
2 of 0.465; 2critical of 3.84 with P=0.05).
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These data suggest that the AFLP marker for sodium transport discovered on chromosome 1 (ML Koyana, personal communication) of IR55178, as well as those markers for potassium uptake and selectivity, are specific to the cross in which they were mapped. The question yet to be answered is whether different QTL are involved in the different populations, or if there is a need only for a more robust marker, since there may be only 30–35% genetic (RFLP) polymorphism between parents (A Garcia, personal communication). At present, the value of the AFLP marker would be restricted to the introduction of the traits (such as low sodium transport) through a backcrossing programme from élite line(s) derived from the mapping cross (IR55178) as the donor parent. If AFLP-derived markers should prove to be cross-specific for physiological traits, then it must be admitted that their generation is an enormous effort for a backcrossing programme. Generating markers for quantitative traits, and generating them in agronomic as opposed to experimental populations, compounds the problem.
There are three major difficulties in mapping QTLs for physiological traits in an agronomically relevant genetic background: (1) phenotyping the mapping population is an investment of a completely different order from phenotyping a qualitative or visible trait; (2) difficulties in phenotyping constrain the size of any mapping population with corresponding decreases in confidence over QTL location and (3) the use of agronomically relevant parents may mean relatively low levels of polymorphism.
Furthermore, once mapped, these results then suggest any marker is likely to be of limited value as regards transferability to unrelated populations. Much of the difficulty may lie in the fact that these AFLPs are arbitrary markers, not in or necessarily even very near to the gene(s) that matter. The challenge must be to identify the genes.
There are two difficulties that must be faced in attempting to discern the nature of QTL governing physiological traits. The best confidence interval with which mapping can localize QTL, regardless of the size of the mapping population, is perhaps 10 cM (Kearsey, 1998; Kearsey and Farquhar, 1998). With a mapping population constrained by the difficulties of phenotyping it may be 20–30 cM. Under the most hopeful conditions (and in rice!) the best map location of a QTL is probably only to the nearest one hundred genes. This is an impossibly large window in which to look for a gene without some clear idea of what it might be.
A compromise would be to get the region of interest from a bacterial artificial chromosome (BAC) library and search for the BAC clone containing the QTL by transformation. The number of BAC clones corresponding to the window of confidence depends upon the relationship between cM and Kb and the size and degree of overlap of the clones. For a genome the size of rice (2 pg, Bennett and Smith, 1991) which is 430 Mb (Yano and Sasaki, 1997), the worst case scenario is about 100 and the best case about 20 clones. It is then necessary to screen all of these by transformation for their ability to complement the phenotype of the parents. Since it is unknown whether traits considered as salt-resistant will be dominant or recessive, it is necessary to perform reciprocal transformations. Since the characters being evaluated for a QTL are, by their definition, quantitative, the evaluation of the transformants must also be quantitative. Multiplying the number of transformants needed by the number of assays needed reveals the scale of the operation. Although sound in theory, the practicality of hunting for the QTL by transformation is daunting.
The real gap in our knowledge is of candidate genes for which to search. In the case of salt tolerance the minimum physiological requirements are a balance between growth rate and net ion transport combined with sufficient intracellular compartmentation to permit the leaf cytoplasm to function effectively at the ionic concentration needed in the vacuole to provide balanced water relations. This must be achieved at an acceptable cost in osmolyte/osmoprotectant synthesis. If any one of these components fail, the whole system fails, certainly in an agricultural context. A comparable (and never simple) list of minimum requirements could be drawn up for drought and other environmental stresses. The number of structural genes that must contribute to a tolerant phenotype are evidently legion. This brings us back to ask if it is not surprising that such small number of QTL is often found.
One answer to the discovery of a rather small number of QTL might be that they represent genes that sit high in a pathway that signals that a stress has been perceived. This signal results in the appearance of a co-ordinated response: a response which in the case of salinity includes the intracellular compartmentation of ions combined with the synthesis and intracellular compartmentation of an osmoprotectant, all three of which are essential and none of which is of any real value alone.
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The way forward? |
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TopAbstractIntroductionEffects of salinity on...Pyramiding of physiological...Quantitative trait loci and...Materials and methodsResults and discussionThe way forward?References |
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It is proposed that, at the moment, the way forward is to seek candidate genes by combining the available methods of detecting early differential gene expression with sound physiology. This would enable the detection of expression that is attributable to a tolerance response to the stress in question. This means designing protocols that enable the physiological distinction between, for example, salt stress and water stress, and certainly between ‘realistic’ stress, shock responses, and pathology. It is a foregone conclusion that the gene expression in a shocked or pathologically damaged plant will be greatly altered. It is also a foregone conclusion that most or all of these changes are nothing to do with adaptation. The quest may be for mRNAs of low abundance, which is typical of those encoding transcription factors, signal transduction components and membrane receptors (Scutt, 1997
), for which reason differential screening needs to be combined with techniques such as differential display (Heck and Fernandez, 1997) or subtractive hybridization (Harper, 1997). However, as discussed earlier, the real challenge is to develop material and experimental regimes that allow the dissection of a differential response that is associated with tolerance. Treatments that throw a cell into turmoil are certain to overwhelm any real signal with noise. The key responses may be those that occur days or weeks after exposure to a ‘realistic’ stress, not minutes after the imposition of a treatment which is ecologically irrelevant.
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Acknowledgments |
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We acknowledge the support of the BBSRC and of DFID in this research and of Lucille Goff for help with obtaining data on IR36. KPS acknowledges the support of a Rockefeller Fellowship and CS the receipt of a Commonwealth Fellowship. We would also like to acknowledge the help, over many years, of the late D Senadhira, without whose assistance in making crosses none of this research would come about.
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Notes |
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1 To whom correspondence should be addressed. Fax: +44 1273 678433. E-mail: t.j.flowers@sussex.ac.uk
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References |
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TopAbstractIntroductionEffects of salinity on...Pyramiding of physiological...Quantitative trait loci and...Materials and methodsResults and discussionThe way forward?References |
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