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Published online 1 July 2008
Published in Crop Sci 48:1382-1388 (2008)
© 2008 Crop Science Society of America
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Combining Ability of Salinity Tolerance on the Basis of NaCl-Induced K+ Flux from Roots of Barley

Zhonghua Chena, Sergey Shabalaa, Neville Mendhama, Ian Newmanb, Guoping Zhangc and Meixue Zhoud,*

a Tasmanian Institute of Agricultural Research and School of Agricultural Science, University of Tasmania, Private Bag 54, Hobart, TAS 7001, Australia
b School of Mathematics and Physics, University of Tasmania, Private Bag 37, Hobart, TAS 7001, Australia
c Agronomy Dep., Zhejiang University, Huajiachi Campus, Hangzhou 310029, China
d Tasmanian Institute of Agricultural Research and School of Agricultural Science, University of Tasmania, P.O. Box 46, Kings Meadows, TAS 7250, Australia

* Corresponding author (mzhou{at}utas.edu.au).


   ABSTRACT
TOP
 NOTES
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Salinity is a major abiotic stress affecting agricultural production. To understand the genetic behavior of salinity tolerance traits, a half-diallel cross was made among six barley cultivars (Hordeum vulgare L.), with contrasting levels of known tolerance, to study the combining ability of salinity tolerance on the basis of K+ loss from plant roots under saline conditions. The glasshouse pot experiments showed that the six parents were significantly different in salinity tolerance and those tolerances were highly correlated with the K+ flux measurements. The combining ability analysis showed that the variances of both general combining ability (GCA) and specific combining ability (SCA) were highly significant. Two tolerant cultivars, CM72 and Numar, showed significantly higher GCA for salinity tolerance (less K+ loss under salinity stress). Cultivars with medium GCA were YU6472 and Yan90260. Salinity tolerance was mainly controlled by additive effects with the tolerance allele showing partial dominance. High positive SCA was also found between two tolerant cultivars and between tolerant and medium-tolerant cultivars, indicating possible different tolerant genes or some minor genes in these cultivars. The combination of these genes from different sources of tolerant cultivars should produce cultivars with even greater tolerance.

Abbreviations: GCA, general combining ability • SCA, specific combining ability


   INTRODUCTION
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
SOIL SALINITY SEVERELY limits agricultural crop production worldwide. Increasing demand on the world food supply is intensifying the interest in developing salinity-tolerant crop varieties (Epstein et al., 1980). Tolerance to salinity and associated problems are certainly influenced by a number of physiological, morphological, and ontogenetic characters in plants. Salinity tolerance in glycophytes is mainly associated with the ability to maintain high K+/Na+ ratios in shoots (Greenway and Munns, 1980; Gorham et al., 1987; Maathuis and Amtmann, 1999). Plant ability to exclude Na+ from uptake (Tester and Davenport, 2003) and cell ability to retain K+ (Chen et al., 2005, 2007) may both contribute to this trait. Characters such as yield, survival, vigor, leaf damage, and plant height have been the most commonly used criteria for identifying salinity tolerance. None of these, however, is directly linked to the plant's ability to maintain an optimal cytosolic K+/Na+ ratio. More closely related indices of salinity tolerance have been proposed, such as Na+, K+, and Cl– concentrations and K+/Na+ tissue content ratio in shoots or roots, or the production of specific metabolites in various species (Gorham et al., 1990; Maathuis and Amtmann 1999; Shabala et al., 2003, 2005a; Cuin and Shabala, 2005). While being relatively straightforward and suitable for large-scale screening of hundreds—or even thousands—of plant samples, none of these characteristics is directly linked to ionic relations in the plant cytosol. For example, tissue Na+ analyses fail to take into account the cell's ability to sequester excessive Na+ in the vacuole. Hence, tolerant genotypes possessing efficient vacuolar Na+ compartmentation may be simply missed if screening is based on the above criterion. Similar criticism applies to most other characteristics. At the same time, direct estimation of cytosolic Na+ and K+ concentrations is not practical in breeding programs because of the high methodological difficulties in making such measurements (e.g., Cuin et al., 2003).

In our previous work using several barley cultivars (Hordeum vulgare L.) with contrasting salinity tolerance levels, we have shown a strong correlation between plant salinity tolerance (estimated as grain yield under saline conditions) and the NaCl-induced root K+ flux, measured non-invasively by ion-selective microelectrodes (the MIFE technique) from the surface of three to four day-old barley roots (Chen et al., 2005). As a follow-up of this work, 69 barley cultivars with a range of physical and agronomic traits were evaluated under glasshouse and laboratory conditions (Chen et al., 2007). Sixty two of these (ca 90%) followed a strong (r2 = 0.71) inverse relationship between K+ loss measured from four-day-old roots and plant salinity tolerance, estimated as overall ranking score on the basis of changes in six major physiological traits (relative grain yield, shoot biomass, plant height, CO2 assimilation, survival rate, and kernel weight).

So far, genetic studies have been conducted using various assessment criteria. Those include Na+ and K+ uptake in rice (Oryza sativa) (Gregorio and Senadhira, 1993), seed germination in barley (Mano and Takeda, 1997a,b), shoot growth in alfalfa (Medicago sativa L.) (Noble et al., 1984), shoot and root growth in pearl millet (Pennisetum americanum (L.) Leeke) (Ashraf and McNeilly, 1992), and root length of seedlings in several grass species (Ashraf et al., 1986). There has been no report of use of the plant's ability to maintain the optimal cytosolic K+/Na+ ratio as a criterion for salt tolerance. Mano and Takeda (1997a,b) found that salinity tolerance of barley at the germination stage was controlled by over-dominant alleles, and non-additive genetic variance was larger than additive genetic variance; while at the seedling stage, tolerance was predominantly controlled by additive genes, with also some effects of dominance. Similar results in rice were reported by Gregorio and Senadhira (1993), reporting both additive and dominant gene effects. Moeljopawiro and Ikehashi (1981) reported that, on the basis of divergent selection, the tolerance was a quantitative trait exhibiting additive, dominance, and overdominance gene effects and was under polygenic control.

Barley has a relatively high level of tolerance to salinity compared to wheat (Triticum spp.), maize (Zea mays L.) and rice (Lessani and Marschner, 1978; Shannon, 1997; Munns et al., 2006). Varietal differences in response of barley to high salinity have been reported by Donovan and Day (1969). To bring salinity tolerance into commercial barley varieties it is necessary to find salinity-tolerance genes in barley germplasm, to find a reliable screening method, and to investigate the genetic behavior of the tolerance. All of these aims can be achieved if the above "K+ efflux marker" can be shown to be a heritable trait. Thus, in this work, six barley varieties with different salinity tolerance were selected to make crosses in a half-diallel pattern to study the combining ability of salinity tolerance based on NaCl-induced root K+ loss.


   MATERIALS AND METHODS
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 REFERENCES
 
Plant Materials
Six barley cultivars, CM72, Numar, YU6472, Yan90260, Gairdner and Franklin, were obtained from either the Australian Winter Cereal Collection or the barley genotype collection of Yangzhou University (China). These cultivars differed in salt tolerance, with CM72 and Numar being the most tolerant and Gairdner and Franklin being the most sensitive (Tajbakhsh et al., 2006; Chen et al., 2007). These cultivars were used to make half-diallel crosses. F1 seeds were grown in the field at the Mt Pleasant Laboratories, Launceston, Tasmania, to produce 15 F2 populations.

Glasshouse experiments were performed at two locations, Hobart and Launceston (Tasmania), for the evaluation of the relative yield under saline conditions for the six parents, in the summers of 2004/05 and 2005/06, respectively. Both trials were conducted with a completely randomized design with three replicates at Launceston and four replicates at Hobart. For each replicate, ten seeds were sown (thinned to five uniform seedlings after germination) in a single 2-L pot. Each cultivar was grown in pots filled with potting mixture with or without NaCl added (cooking salt, Olsson Industries, Victoria, Australia). The amount of salt added was calculated to obtain 30 mS cm–1 electrical conductivity of a saturated paste extract (ECe) of the potting mix. The composition of the potting mix was as follows: 80% composted pine bark, 10% sand, and 10% coir peat, plus N:P:K (8:4:10) at 1 kg m–3; dolomite at 8 kg m–3; wetting agent at 0.75 kg m–3; sulfate of iron at 1 kg m–3; gypsum at 1 kg m–3; isobutylenediurea (IBDU) at 1 kg m–3; trace element mix at 0.75 kg m–3; zeolite at 0.75 kg m–3; pH 6.0. Yield per pot was measured after harvesting. A saucer was placed under each pot to retain salt and other nutrients. Control plants were watered daily. Plants grown under salt stress were watered according to the growth stages and individual requirements. During the early growth stages (plants did not show much difference in response to salt), equal amounts of water were applied and the salt solution was maintained at 1 cm deep in the saucers. When genotypes started to show differences in their salt tolerance, a different amount of water was applied to each pot to make sure that the salinity level in different pots was maintained as uniformly as possible.

Experimental Protocol for K+ Flux Measurements
Seeds of six barley cultivars and the F2 populations were surface sterilized with 3% H2O2 for 10 min and thoroughly rinsed with distilled water. Seeds were then germinated and seedlings were grown for 3 d in an aerated hydroponic solution (containing 0.5 mM KCl and 0.1 mM CaCl2) in a dark growth cabinet at 24 ± 1°C. Seedlings with root length 70 ± 10 mm of all the cultivars and F2 populations were used for K+ flux measurements. The K+ flux was measured non-invasively at the root mature zone ~10 mm from the root tip for 5 min following 1 h salt treatment, using ion-selective microelectrodes (the MIFE system; University of Tasmania, Hobart, Australia) as described in our previous publications (Shabala et al., 2003; Chen et al., 2005). One hour before measurement, a seedling was taken from the growth cabinet and placed in a 10-mL perspex measuring chamber with 10 mL 80 mM NaCl, which contained 0.5 mM KCl and 0.1 mM CaCl2. The root was centered within the chamber and fixed horizontally by immobilizing the root using moveable plastic cross-bars within the chamber. Electrode tips were filled with the ion-selective cocktail (ionophore K+ 60031, Fluka, Buchs, Switzerland), and their tips aligned and positioned 40 µm above the root surface. During measurements, electrodes were moved in a slow (10-s cycle, 40-µm amplitude) square-wave by a computer-driven micromanipulator (Patchman NP2, Eppendorf, Hamburg, Germany) between the two positions, close to (30–40 µm) and away from (70–80 µm) the root surface. Net ion fluxes were calculated from the measured difference in electrochemical potential for these ions between the two positions using cylindrical diffusion geometry (Shabala et al., 1997; Newman 2001). The K+ flux was the average value of the microelectrode ion flux from the root of a single seedling for the period of 5 min (the MIFE records ion flux every 10 s). The entire measurements were performed twice. For each replication, 50 seeds of each of the parent cultivars and up to 120 seeds of F2 populations were germinated and uniform and healthy seedlings (24–40 for parents and 21–90 for F2 populations) were selected to measure the K+ flux in a random order.

Statistical Analysis
Relative yields of the parents were calculated as the percentage yield of the stress-treated relative to controls (without salt treatment). Regression analyses were conducted between the relative yields of the six parents and flux measurements and between the average K+ flux of F2 populations and mid-parent values. The yield data of two years of glasshouse experiments and average K+ fluxes after salt treatment of parental lines and F2 populations from two replications were subjected to an analysis of variance. A student's t test was made to compare the K+ fluxes of the F2 populations with their mid-parent values. All of the above analyses were performed with MS Excel. Griffing's (1956) experimental method 2, Model I (fixed model) was employed to calculate the GCA effect for each parent and SCA effect for each cross. For the comparison of GCA effects, SE(gi–gj)=FormulaFormula2, where gi and gj are the GCA of ith and jth parent. For the comparison of SCA effects, SE(sij–sik)=FormulaFormula2, where sij and sjk are the SCA between ith and jth parent and SCA between ith and kth parent; SE(sij–slk)=FormulaFormula2,where sij and slk are the SCA between ith and jth parent and SCA between lth and kth parent. The variances of additive effects and dominance effects were calculated from the components of the variance of combining ability, and the relative importance of GCA and SCA was calculated according to Baker (1978).


   RESULTS
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 REFERENCES
 
Salinity Tolerance of Selected Parents
The glasshouse experiments confirmed our previous observations that CM72 and Numar are tolerant to salinity while Franklin and Gairdner are susceptible. Both YU6472 and Yan90260 were introduced from China and showed medium tolerance to salinity. The average grain yields of the six parents under salt stress were reduced from 34.8 to 10.3, 32.5 to 11.9, 29.5 to 2.1, 20.1 to 2.5, 34.3 to 0.4, and 30.1 to 0.1 g for CM72, Numar, YU6472, Yan90260, Gairdner, and Franklin, respectively. Compared to the controls, the percentages of yield loss under saline conditions were 66.3% for CM72, 66.5% for Numar, 86.6% for YU6472, 88.8% for Yan90260, 95.7% for Gairdner, and 97.8% for Franklin (Fig. 1 ). The combined ANOVA of the relative yield under salt stress from two sites/years showed that the differences among cultivars were very significant (F = 235.3, P < 0.0001). The difference in salinity tolerance for different cultivars in the early growth stage can be clearly seen in Fig. 2 , in which the tolerant cultivar CM72 was much healthier than the susceptible cultivar Franklin. The six parents also differed in K+ flux measured from the mature region of three-day-old roots after an hour pre-treatment in 80 mM NaCl (Table 1 ) and the root K+ flux measurements were closely related to the relative yield under saline conditions (Fig. 1). Figure 3 shows a typical K+ flux of each parent after salt treatment.


Figure 1
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  		Figure 1. Regression analyses between NaCl-induced net K+ flux (nmol m–2 s–1, inwards positive) measured from mature region of 3-d-old barley roots after an hour pre-treatment in 80 mM NaCl and the relative yield under salinity stress of six parents. Values in brackets are the actual yield of the control (g/pot).

 

Figure 2
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  		Figure 2. Effect of salinity on early growth of CM72 (left) Franklin (right). For each variety, plants in the right-hand pot are salt-treated.

 

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  		Table 1. K+ flux (nmol m–2 s–1) of the parents and F2 populations measured from the mature region of three-day-old barley roots after an hour pre-treatment in 80 mM NaCl.

 

Figure 3
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  		Figure 3. Steady-state net K+ fluxes (nmol m–2 s–1, inwards positive) of six parents after an hour pre-treatment in 80 mM NaCl. Each point is the average of 10 measurements.

 
Root K+ Flux after Salt Treatment
Table 1 shows the mean root K+ flux after salt treatment of six parents and their 15 F2 populations. Significant differences were found among different parents and F2 populations (F = 62.2, P < 0.001). There were no significant differences in K+ flux between CM72 (–108) and Numar (–133), between YU6472 (–210) and Yan90260 (–231), and between Gairdner (–397) and Franklin (–383). However, significant differences were found between the two tolerant cultivars and two medium tolerant ones as well as between medium-tolerant cultivars and sensitive ones (LSD0.05 = 51 and LSD0.01 = 61, calculated from the ANOVA of the average K+ fluxes of two replicates). The differences among different F2 populations were also significant. The regression analysis showed that the root K+ flux-values of F2 populations were significantly correlated with the mid-parent values (Fig. 4 ). The average values of root K+ flux of F2 populations were significantly higher (i.e., less K+ loss) than the mid-parent values (t = 6.40, P < 0.0001), indicating the dominance of salinity tolerance (Fig. 4).


Figure 4
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  		Figure 4. Correlations between the NaCl-induced net K+ flux (nmol m–2 s–1) of mid-parent values and their F2 populations.

 
Combining Ability of Salinity Tolerance on the Basis of NaCl-Induced Root K+ Loss
The variances of both GCA and SCA were highly significant (Tables 2 , 3 ). However, the relative importance of GCA was much greater, with a very high ratio (0.76) between the variance of additive effects and the variance of genotype effects (sum of additive and dominant effects) (Baker 1978), indicating that the tolerance was mainly controlled by additive effects. Of all the selected varieties, the salinity-tolerant cultivar CM72 had the highest GCA (67.4, lowest K+ loss), followed by the other tolerant cultivar Numar (47.4) and two medium-tolerant cultivars YU6472 (8.4) and Yan90260 (9.2). Both Gairdner (–71.5) and Franklin (–60.9) had very low GCAs in regard to NaCl induced root K+ flux. The SCA was significantly higher in some crosses. The average root K+ loss induced by NaCl in the F2 population of the cross between two tolerant cultivars was even lower than either parent. The tolerance gene, or genes, in the medium-tolerant cultivar YU6472 showed dominance over tolerance genes in one of the tolerant cultivars (SCA = –48.0 for the cross between Numar and YU6472). It also showed dominance over susceptibility genes in sensitive cultivars (SCA = 38.6 for the cross between YU6472 and Gairdner, and 33.7 for the cross between YU6472 and Franklin). The other medium-tolerant cultivar also showed higher SCA with the tolerant cultivar CM72.


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  		Table 2. ANOVA of combining ability in NaCl induced K+ flux (nmol m–2 s–1).

 

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  		Table 3. General combining ability (GCA) and special combining ability (SCA) of NaCl induced K+ flux (nmol m–2 s–1).{dagger}

 

   DISCUSSION
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
REFERENCES
 
Methods for Screening for Salinity Tolerance
The complexity of salinity tolerance, and difficulties in testing it for screening large populations, has led to the quest for ‘rapid screening techniques’ or ‘physiological markers’ as screening tools for salinity tolerance (Shannon, 1979). Any test must meet two criteria in addition to having adequate predictive value. First, the measured parameter must be directly related to the desired physiological trait. Second, the test must be relatively simple to use and allow large numbers of plants to be tested at low cost. Many screening methods have been reported. These include ranking of plants according to growth rate or yield (Greenway, 1962), plant survival at high salinity (Sayed, 1985), germination rate (von Well and Fossey, 1998, Tajbakhsh et al., 2006), leaf or root elongation rate (Cramer and Quarrie, 2002), leaf injury and reduction of CO2 assimilation (James et al., 2002), damage to the photosynthetic apparatus (Krishnaraj et al., 1993), Na+ exclusion (Garcia et al., 1995), Cl– exclusion (Rogers and Noble, 1992), and K+/Na+ tissue content ratio (Asch et al., 2000). Our previous work reported a strong correlation between known plant salinity tolerance and the NaCl-induced root K+ flux, measured by the MIFE technique (Chen et al., 2005, 2007). In the current work, the relative yields of the six selected parents were significantly correlated with NaCl-induced root K+ flux (Fig. 1), supporting the validity of using the MIFE technique as a screening tool. While demanding greater skill than most screening methods suggested so far, the MIFE technique has the unique advantage of evaluating combining ability of salinity tolerance at the cellular level. This not only makes it applicable to some specific breeding methods such as via cell culture (see Babourina et al. (2000), for an example of MIFE ion flux measurements from cultured cells), but also focuses more closely on those genes primarily involved in the salinity-tolerance trait in plants (eliminating the contribution of some genes expressed at later stages of development or those expressed in other tissues or organs). Thus, further genetic studies were conducted using MIFE measurements of K+ flux as an indicator of salinity tolerance.

Genetics of Salinity Tolerance on the Basis of NaCl-Induced Root K+ Flux
Diallel analysis showed that salinity tolerance based on NaCl-induced root K+ flux was mainly controlled by additive effects even though dominance effects made a significant contribution to the tolerance. In tomato, Foolad (1997) and Foolad and Jones (1991) also reported that more than 90% of the genetic variation among generations was due to additive genetic effects and that dominance and non-allelic interaction effects were minimal. The tolerance genes in barley showed partial dominance over sensitive genes, which is different from the results reported by Mano and Takeda (1997a), who indicated that barley salinity tolerance at germination was mainly controlled by recessive genes, and of Gregorio and Senadhira (1993) who reported overdominance effects for K+/Na+ discrimination in rice. The continuous distribution of salinity tolerance in F2 populations of crosses between tolerant and susceptible varieties indicated that the tolerance was likely to be controlled by several genes. This is hardly surprising, as about 5% of the entire Arabidopsis thaliana genome involves cation transporters (Mäser et al., 2002). Just for K+ transport, 75 genes from seven different families are known (Véry and Sentenac, 2002; Shabala 2003). Our previous electrophysiological studies suggested that at least several of them (particularly, K+-permeable outward rectifying channels and non-selective cation channels) could mediate NaCl-induced K+ efflux from plant tissues (Shabala et al., 2003, 2005a,b, 2006; Cuin and Shabala, 2005, 2007). This is not likely to be a full list. Our further studies will be focusing on the molecular identity of the candidate K+ channels and transporters that might be responsible for this NaCl-induced K+ efflux.

Breeding for Salinity Tolerance on the Basis of NaCl-Induced Root K+ Flux
For plant breeders to select salinity-tolerant cultivars, one of the key requirements is to have a reliable screening method. Despite being skill-demanding, the MIFE technique is a useful screening tool for salinity tolerance since the NaCl-induced K+ flux measured by the MIFE technique is highly correlated with relative grain yield, shoot biomass, plant height, net CO2 assimilation, survival rate, and seed weight measured in glasshouse experiments (Chen et al., 2007). However, as discussed previously (Chen et al., 2005), root K+ fluxes may reflect not only the plant's ability to respond to NaCl, but also reflect the general physiological status of the root and, hence, will depend on seedling age, root length, and healthiness. More studies need to be conducted on the factors affecting MIFE measurement to establish standardized testing conditions for use on heterozygous segregating populations. However, even though greater variations were found between the single measurements for both parents, the average value provides much better estimation of salinity tolerance. Thus, for the present, the method seems to be highly efficient when used on homozygous populations, such as doubled haploid lines. Further studies will be conducted on the doubled haploid population developed from the cross of CM72 and Gairdner to estimate the possible number of genes involved in the tolerance and to identify molecular markers associated with these genes.

The other key issue is the understanding of the genetic behavior of the tolerance, including the selection of the parental lines that provide it. No reports have been found for the combining ability of salinity tolerance in barley. In the current study, significant GCA and SCA were found for NaCl induced root K+ flux, one of the reliable indicators for salinity tolerance in barley. The salinity-tolerant cultivar CM72 showed the highest GCA, followed by the other tolerant cultivar Numar. Obviously, these two cultivars can be used as the major source of salinity tolerance. Moreover, the F2 population of the cross between two tolerant cultivars showed even lower K+ loss than either parent, indicating that different major or minor tolerance genes may exist in these two cultivars. The tolerance genes in the medium-tolerant cultivar YU6472 showed greater dominance both over tolerance genes in tolerant cultivars and over susceptibility genes in sensitive cultivars. The other medium-tolerant cultivar also showed higher SCA with the tolerant cultivar CM72. All the above indicates that the genes for tolerance or medium tolerance in the cultivars used in this study could be different. Thus it is possible to use NaCl induced root K+ flux as a screening criterion to combine different tolerance genes to strengthen the salinity tolerance of barley.


   ACKNOWLEDGMENTS
 
This work was supported by GRDC (UT8) and DEST grants to Meixue Zhou and Neville Mendham, ARC Discovery (DP0449856), and DEST grants to Sergey Shabala, and an ARC Discovery (A00105708) grant to Ian Newman.


   NOTES
TOP
 NOTES
ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
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Received for publication February 19, 2008.


   REFERENCES
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 





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