Abstract

Tolerance to drought is a quantitative trait, with a complex phenotype, often confounded by plant phenology. Breeding for drought tolerance is further complicated since several types of abiotic stress, such as high temperatures, high irradiance, and nutrient toxicities or deficiencies can challenge crop plants simultaneously. Although marker-assisted selection is now widely deployed in wheat, it has not contributed significantly to cultivar improvement for adaptation to low-yielding environments and breeding has relied largely on direct phenotypic selection for improved performance in these difficult environments. The limited success of the physiological and molecular breeding approaches now suggests that a careful rethink is needed of our strategies in order to understand better and breed for drought tolerance. A research programme for increasing drought tolerance of wheat should tackle the problem in a multi-disciplinary approach, considering interaction between multiple stresses and plant phenology, and integrating the physiological dissection of drought-tolerance traits and the genetic and genomics tools, such as quantitative trait loci (QTL), microarrays, and transgenic crops. In this paper, recent advances in the genetics and genomics of drought tolerance in wheat and barley are reviewed and used as a base for revisiting approaches to analyse drought tolerance in wheat. A strategy is then described where a specific environment is targeted and appropriate germplasm adapted to the chosen environment is selected, based on extensive definition of the morpho-physiological and molecular mechanisms of tolerance of the parents. This information was used to create structured populations and develop models for QTL analysis and positional cloning.

The complexity of drought tolerance

Drought tolerance is defined as the ability of a plant to live, grow, and reproduce satisfactorily with limited water supply or under periodic conditions of water deficit (Turner, 1979). Crop plants should not only have the ability to survive under drought but also the ability to produce a harvestable yield. Research into the molecular aspects of drought tolerance has tended to focus on plant survival at the expense of yield. However, severe water deficits are rare in viable agriculture, and asking how crops respond to or survive extreme drought is unlikely to have much of a practical impact (Passioura, 2002). The aim is not to ‘convert wheat to a cactus’ but to allow wheat to continue to grow and yield grain under water-limited conditions.

Drought tolerance is a quantitative trait, with complex phenotype and genetic control (McWilliam, 1989). Understanding the genetic basis of drought tolerance in crop plants is a prerequisite for developing superior genotypes through conventional breeding. Given the complexity of the genetic control of drought tolerance (multigenic, low-heritability, and high G×E interactions), marker assisted selection has not contributed significantly to cultivar improvement for dry environments and breeding has relied on direct phenotypic selection. There are additional problems in investigating the genomics of drought tolerance in species such as wheat: most pathways and candidates can be more effectively studied in model species with smaller and sequenced genomes such as Arabidopsis and even amongst the cereals there are more extensive data available for rice and maize when compared with wheat. However, recent technological advances and the imperative to ensure sustainable food production has driven research programmes to improve this crop genetically despite the size and complexity of the genome (bread wheat is hexaploid with 16 Gb; Feuillet et al., 2008).

Breeding for drought tolerance is further complicated by the fact that several types of abiotic stress can challenge crop plants simultaneously. High temperatures, high irradiance, scarcity of water, and nutrient deficiencies are commonly encountered under normal growing conditions but may not be amenable to management through traditional farm practices. Certain soil properties such as composition and structure can also affect the balance of these different stresses (examples reviewed by Whitmore and Whalley, 2009). Higher plants have evolved multiple, interconnected strategies that enable them to survive unpredictable environmental fluctuations. However, these strategies are not always well developed in the cereal cultivars grown by farmers. At the molecular scale, pathways and gene networks between abiotic stresses overlap; for example, about 40% of drought or high salinity inducible genes are also induced by cold stress in rice (Shinozaki and Yamaguchi-Shinozaki, 2007). Some biochemical mechanisms may have opposing effects under different stresses; therefore tackling tolerance to one stress may lead to sensitivity to another. For example, some plants avoid heat stress by increasing stomatal conductance and, consequently, evaporative cooling. However, closing the stomata helps to decrease the loss of water and maintain turgor under conditions of low soil water potential. The two mechanisms will conflict when high temperature and drought occur simultaneously, which is frequently the case in a Mediterranean climate. Moreover, the osmo-protectant amino acid proline has a toxic effect under heat stress and its accumulation may not be an appropriate tolerance mechanism in field conditions when heat and drought stresses are combined (Rizhsky et al., 2004; Salekdeh et al., 2009). Although the reductionist approach of studying isolated stress has considerably increased our knowledge of tolerance mechanisms, interaction between multiple stresses and stress combinations should be studied so as to make progress relevant to field conditions.

In addition to these confounding environmental factors, a drought research programme should also consider plant phenology. By completing its life cycle before the onset of severe water deficit, plants are often able to escape drought (Chaves et al., 2003). This mechanism of avoidance is deployed by rapid phenological development, developmental plasticity, and remobilization of pre-anthesis assimilates to grain (Turner, 1979). A short life cycle is particularly advantageous in environments with terminal drought stress or where physical or chemical barriers inhibit root growth (Turner, 1986; Blum, 1988; Bidinger and Witcombe, 1989). The plant's response to drought can be confounded by the environmental covariates as a result of differing phenology. Plant maturity strongly influences grain yield under dry conditions (Jiang and Zeng, 1995; Ouk et al., 2006). A further confounding factor is plant morphology, particularly plant height and tillering. Small plants with few tillers can show higher Water Use Efficiency (WUE, ratio of the volume of water consumed to the total biomass produced, or ratio of biomass to total evapotranspiration) than tall multi-tillered plants. Since the genotypic variation of WUE is mainly driven by variations in water use rather than by variations in plant assimilation, the selection for high WUE may result in smaller plants, instead of high yield under drought (Blum, 2005). Some QTLs for carbon isotope discrimination (a measurement of WUE) in wheat were actually associated with variation in heading date and plant height (Rebetzke et al., 2008). Breeding for a shortened crop life cycle has been a very successful strategy in Mediterranean conditions (Araus et al., 2002). However, in well-developed agricultural regions, crop flowering time has already been optimized by breeders so that the plant's phenology matches its environment (Passioura, 2007). Therefore research should now focus on optimizing vegetative development to manage biomass and ensure effective assimilates remobilization to grain when water supply becomes limiting.

QTLs of drought tolerance in wheat and barley

Most QTLs for drought tolerance in wheat and its close relative barley have been identified through yield and yield component measurements under water-limited conditions (Quarrie et al., 2006; Maccaferri et al., 2008; Mathews et al., 2008; von Korff et al., 2008; McIntyre et al., 2009). Although yield is the most relevant trait to breeders, it is very difficult to describe accurately with respect to water use and to identify candidate regions for positional cloning. Few studies have identified QTLs associated with specific components of drought response (Table 1). Although the development of gene-based molecular markers and genome sequencing should accelerate positional cloning (reviewed in Collins et al., 2008), the genomic regions associated with individual QTL are still very large and are usually unsuitable for screening in a breeding programme.

Table 1.

QTLs of physiological responses to drought stress identified in wheat and barley

Trait Species Drought condition Chromosome location Reference 
Water-soluble carbohydrate Wheat Rainfed field 1A, 1D, 2D, 4A, 6B, 7B, 7D Yang et al., 2007 
Carbon isotope ratio, osmotic potential, chlorophyll content, flag leaf rolling index Durum wheat Rainfed field 2B, 4A, 5A, 7B Peleg et al., 2009 
Grain carbon isotope discrimination Barley Mediterranean rainfed field 2H, 3H, 6H, 7H Teulat et al., 2002 
Relative water content Barley Mediterranean rainfed field 6HL Teulat et al., 2003 
Leaf osmotic potential, osmotic potential at full turgor, osmotic adjustment, carbon isotope discrimination Barley Water-deficit in growth chamber 6HL Teulat et al., 2001; Diab et al., 2004 
Water-soluble carbohydrate Barley Water-deficit in growth chamber 4H Diab et al., 2004 
Chlorophyll and chlorophyll fluorescence parameters Barley Post-flowering drought 2H, 4H, 6H, 7H Guo et al., 2008 
Relative water content Barley Water-withholding 1H, 2H, 6H Chen et al., 2010a 
Trait Species Drought condition Chromosome location Reference 
Water-soluble carbohydrate Wheat Rainfed field 1A, 1D, 2D, 4A, 6B, 7B, 7D Yang et al., 2007 
Carbon isotope ratio, osmotic potential, chlorophyll content, flag leaf rolling index Durum wheat Rainfed field 2B, 4A, 5A, 7B Peleg et al., 2009 
Grain carbon isotope discrimination Barley Mediterranean rainfed field 2H, 3H, 6H, 7H Teulat et al., 2002 
Relative water content Barley Mediterranean rainfed field 6HL Teulat et al., 2003 
Leaf osmotic potential, osmotic potential at full turgor, osmotic adjustment, carbon isotope discrimination Barley Water-deficit in growth chamber 6HL Teulat et al., 2001; Diab et al., 2004 
Water-soluble carbohydrate Barley Water-deficit in growth chamber 4H Diab et al., 2004 
Chlorophyll and chlorophyll fluorescence parameters Barley Post-flowering drought 2H, 4H, 6H, 7H Guo et al., 2008 
Relative water content Barley Water-withholding 1H, 2H, 6H Chen et al., 2010a 

Despite their importance in drought tolerance, reproductive organs and the root have attracted little attention in genetic studies. The effect of drought on reproductive processes has been extensively described in cereals (see review by Barnabas et al., 2008). Passioura (2007) suggested that floral infertility resulting from water deficit could be a promising target for improvement but no QTL studies for this trait have been published in wheat or barley. Improving the competence of the root systems to extract water from the soil also seems an obvious target for genetic analysis. A simulation analysis of root trait modification suggested that an extra 10 mm of water extracted during grain filling would increase yield by 500 kg ha−1, representing a 25% increase of the average wheat yield in Australia (∼2000 kg ha−1) (Manschadi et al., 2006). The identification of markers or genes associated with root growth and architecture would be particularly useful for breeding programmes to improve root traits by molecular marker-assisted selection. Few papers have described work on the identification of QTLs for root traits in wheat. Ma et al. (2005) found a QTL for root-growth rate under Al treatment. QTLs of root traits (primary/lateral root length and number, root dry matter) under control conditions and during nitrogen deficiency were identified in wheat (Laperche et al., 2006). Relative root growth was also used by Jefferies et al. (1999) to map QTL for tolerance to toxic levels of soil boron. However, QTLs corresponding to root architecture in dry environments are yet to be discovered in wheat and barley.

Over the past few years there have been several mapping studies that have targeted drought tolerance and other abiotic stress tolerance loci associated with performance in low yielding environments (Table 2). However, despite this substantial research effort the only markers that have found their way into practical plant breeding programmes are those for boron and aluminium tolerance (Gupta et al., 2010).

Table 2.

QTLs identified for tolerance to several abiotic stresses in wheat and barley (update of the review by Langridge et al. (2006) which covered studies earlier than 2006)

Stress Chromosome location Reference 
Wheat 
Drought 20 QTLs Kirigwi et al., 2007; Mathews et al., 2008; Salem et al., 2007 
Cold 5A, 1D Baga et al., 2007 
Copper toxicity 1AL, 2DS, 3DS, 4AL, 5AL, 5DL, 5BL, and 7DS Balint et al., 2007; Balint et al., 2009 
Aluminium toxicity 4DL, 3BL, 2A, 5AS, and 2DL Cai et al., 2008; Ma et al., 2006 
Salinity 47 QTLs Ma et al., 2007 
Heat 1B, 5B, and 7B Mohammadi et al., 2008b 
Nitrogen deficiency 2D, 4B, and 5A Laperche et al., 2008 
Barley 
Drought 38 QTLs von Korff et al., 2008 
Salinity 30 QTLs Witzel et al., 2010; Xue et al., 2009 
Water-logging 20 QTLs Li et al., 2008 
Aluminium toxicity 2H, 3H, and 4H Navakode et al., 2009 
Stress Chromosome location Reference 
Wheat 
Drought 20 QTLs Kirigwi et al., 2007; Mathews et al., 2008; Salem et al., 2007 
Cold 5A, 1D Baga et al., 2007 
Copper toxicity 1AL, 2DS, 3DS, 4AL, 5AL, 5DL, 5BL, and 7DS Balint et al., 2007; Balint et al., 2009 
Aluminium toxicity 4DL, 3BL, 2A, 5AS, and 2DL Cai et al., 2008; Ma et al., 2006 
Salinity 47 QTLs Ma et al., 2007 
Heat 1B, 5B, and 7B Mohammadi et al., 2008b 
Nitrogen deficiency 2D, 4B, and 5A Laperche et al., 2008 
Barley 
Drought 38 QTLs von Korff et al., 2008 
Salinity 30 QTLs Witzel et al., 2010; Xue et al., 2009 
Water-logging 20 QTLs Li et al., 2008 
Aluminium toxicity 2H, 3H, and 4H Navakode et al., 2009 

‘Omics of drought tolerance

The tools of genomics offer the means to produce comprehensive datasets on changes in gene expression, protein profiles, and metabolites that result from exposure to drought. Comparison of gene expression in Arabidopsis and rice showed that the two species share many common stress-inducible genes (Shinozaki and Yamaguchi-Shinozaki, 2007). Abiotic stress tolerance involves similar transcription factors in both dicotyledonous and monocotyledonous plants and some molecular mechanisms of drought tolerance have been extensively described (reviewed by Yamaguchi-Shinozaki and Shinozaki, 2006). It includes signal transduction cascade and activation/regulation of transcription, functional protection of proteins by late-embryogenesis abundant proteins (e.g. dehydrins) and chaperone proteins (e.g. heat shock proteins), accumulation of osmolytes (proline, glycine betaine, trehalose, mannitol, myo-inositol), induction of chemical antioxidants (ascorbic acid and glutathione), and enzymes reducing the toxicity of reactive oxygen species (superoxide dismutase, glutathione S-transferase). Homologous genes of these different classes were also identified in transcriptomic experiments comparing wheat lines grown under well-watered and water-stressed conditions (Xue et al., 2006; Mohammadi et al., 2007, 2008a; Aprile et al., 2009; Ergen and Budak, 2009; Ergen et al., 2009).

Despite the existence of common regulatory mechanisms across species, the conservation of the molecular response to dehydration across experiments (Mohammadi et al., 2007; Aprile et al., 2009) is low due to variation in stress dynamics, stage of development and tissue analysed. Interestingly, microarray assays revealed unexpected results such as a decrease in the expression of glutathione-related genes following withholding of water in a tolerant synthetic wheat line (Mohammadi et al., 2007), or the accumulation of proline in a drought-sensitive emmer wheat line (Ergen and Budak, 2009), suggesting that some pathways/mechanisms are dependent upon genotype and the duration, intensity, and type of stress applied.

Comparison of transcript profiles between tolerant and susceptible lines under water stress has revealed differences in regulatory pathways. A drought-tolerant emmer wheat genotype showed induction in bZIP and HD-ZIP gene expression (transcription factors known to be related to the ABA regulatory pathway) in response to shock-like drought stress, whereas the sensitive genotype induced some genes encoding transcription factors that bind to ethylene responsive elements. The two genotypes also showed differences in expression of the phospholipase C gene, involved in 1,4,5-triphosphate (IP3) signalling, and MAPK cascade elements (Ergen et al., 2009).

A direct link between gene expression profiles and specific physiological mechanisms has not been demonstrated, probably because the drought stress scenario and the germplasm used for microarrays and physiological experiments are seldom the same. Mohammadi et al. (2007) identified drought-responsive genes in the root of a synthetic hexaploid wheat line considered as a drought avoider. This line retained a higher net photosynthetic rate and relative water content compared with a sensitive line, Opata. However, these researchers could not establish a causal relationship between the transcripts and the maintenance of relative water content. In another experiment, the synthetic line showed higher cell membrane stability and a lower rate of water loss from excised leaves, longer roots, larger root:shoot ratios, and a larger number of seminal roots than Opata (Mohammadi et al., 2008a).

A broad strategy for studying the genetics of drought tolerance in low-yielding environments

Three major approaches for improving drought tolerance in wheat have been used for many years.

  • (1) The empirical selection for yield under water-limited condition. This has been widely used and the good performance of modern cultivars is testimony to the success of this approach. However, there are clear signs that the rates of gain are declining and are insufficient to meet demand (Tester and Langridge, 2010).

  • (2) Define physiological ideotypes for improved yield under water-limited conditions, identify sources of variation for these traits and introduce these traits into elite varieties (Reynolds et al., 2009; Richards et al., 2010). Although this approach has been followed for several decades it has met with only limited success. The use of carbon isotope discrimination to screen for WUE is probably the only trait to lead to new cultivars.

  • (3) Marker assisted selection based around screening for desirable alleles at QTL for drought tolerance. Despite many publications of QTL associated with drought tolerance (Table 2) a recent survey of molecular markers being deployed in wheat breeding programmes failed to identify a single case where a drought or drought-related marker was being implemented (Gupta et al., 2010). The survey found that almost 50 loci were currently being tracked with molecular markers but the only loci associated with performance in low-yielding environments were for tolerance to high soil boron (Bo1), aluminium toxicity (Almt-1), nematode resistance (cereal cyst and root lesion nematodes), and plant height. This strongly implies that the previous drought QTL studies have failed to identify loci of value to wheat breeding programmes.

The limited success of the physiological and molecular breeding approaches until now suggests a careful rethink is needed of our strategies for better understanding and breeding for drought tolerance. Some of the new plant genomic techniques and platforms may allow us to overcome the previous limitations but some may simply lead us further down the tried and failed paths.

A research programme for increasing drought tolerance of wheat should tackle the problem in a multi-disciplinary approach, integrating the physiological dissection of drought tolerance traits and the genetic and genomics tools, such as quantitative trait loci (QTL), microarrays, and transgenic crops. To do so, teams should include molecular biologists, physiologists, and breeders. This is the approach taken in major companies which have successfully demonstrated the application of patented technologies for drought tolerance in the field (Passioura, 2007). In this paper, a strategy is described where a specific environment is targeted, appropriate germplasm adapted to the given environment to create structured populations is selected, the morpho-physiological and molecular mechanisms of tolerance of the parents are described extensively, and this knowledge is combined in models for QTL analysis and positional cloning (Fig. 1). These various components of the drought genetics strategy are discussed below.

Fig. 1.

Schematic representation of the pathway from parental lines selection to gene discovery. The diagram shows the role of physiological analysis, population development, and phenotyping and the various ‘omics technologies in supporting a gene discovery path. Given the complexity and variability of the droughted environment, the first task is defining the type of drought regime or regimes that are being investigated. The second issue is selecting germplasm that will be suitable for the target environments and is likely to reveal major loci associated with tolerance. These lines are used to develop the segregating populations that form the base for the genetic analysis. Mathematical models of physiological traits and omics of parental and selected recombinant lines provide functional data to select candidate genes for the QTL. A further component in the process of defining target regions and candidates for drought tolerance in wheat is the use of the sequenced cereal genomes. The strong conservation of gene order between the grasses means that the rice and Brachypodium genomes provide a valuable resource in developing markers for fine mapping in a target region and for identifying candidate genes for the QTL.

Fig. 1.

Schematic representation of the pathway from parental lines selection to gene discovery. The diagram shows the role of physiological analysis, population development, and phenotyping and the various ‘omics technologies in supporting a gene discovery path. Given the complexity and variability of the droughted environment, the first task is defining the type of drought regime or regimes that are being investigated. The second issue is selecting germplasm that will be suitable for the target environments and is likely to reveal major loci associated with tolerance. These lines are used to develop the segregating populations that form the base for the genetic analysis. Mathematical models of physiological traits and omics of parental and selected recombinant lines provide functional data to select candidate genes for the QTL. A further component in the process of defining target regions and candidates for drought tolerance in wheat is the use of the sequenced cereal genomes. The strong conservation of gene order between the grasses means that the rice and Brachypodium genomes provide a valuable resource in developing markers for fine mapping in a target region and for identifying candidate genes for the QTL.

Target a realistic and specific environment

Firstly, if the strategy is to have practical relevance it should look at drought tolerance under field conditions. Molecular biologists have often reported the effect of genes on drought tolerance in unrealistic environments (dessication of detached leaves or of seedlings transferred from hydroponics to air, osmotic shock by applying polyethylene glycol) and rarely proved their phenotype in the field and their expected value in breeding (Blum, 2005; Passioura, 2007).

Secondly, it is clear that there are different types of drought and that plants have developed different morpho-physiological mechanisms to address them. For example, low water use by moderated growth is an advantage in dry land conditions of stored soil moisture (eastern Australia type) but might be detrimental in other environments where drought may develop at any time during the season (Western Australia type) (Blum, 2005). Plants have developed different root architecture to optimize the timing of water extraction from the soil depending on the drought conditions. A compact and deep root system with a uniform root branching pattern reduces water use early in the season but increases access to water during grain filling and increases yield in conditions of stored soil moisture (Manschadi et al., 2006). In the Mediterranean environment, with seasonal rainfall and terminal drought, a large and shallow root system allows water extraction early in the season in the top soil layers where the water is available (Manschadi et al., 2006).

Due to strong G×E interactions, a QTL can have positive, null or negative additive effects depending on the drought conditions (Collins et al., 2008). Many QTLs identified for response to drought are not ‘stable’ in different environments. Yang et al. (2007) found that seven out of 10 significantly additive QTLs for stem water-soluble carbohydrates content (compounds which are stored for further grain filling in dry conditions) in wheat interacted with the environment. Thus, a research programme on drought tolerance should first define a target drought scenario. Salekdeh et al. (2009) proposed the creation of a Minimum Information About Drought Experiment (MIADE) as a standard for the drought community, similar to the MIAME standard for transcriptomics data. The environment of South Australia, which is the focus of the strategy presented in this paper, is a Mediterranean-type of drought (Izanloo et al., 2008). Wheat production relies on rainfall during the growing season when precipitation decreases with the rise of temperature during spring. The availability of water is cyclic with a succession of precipitation and drought periods from anthesis to the grain-filling stages. The drought is combined with a cyclic heat stress between rainfall events. Additional stress factors such as high wind, high irradiance, low air humidity, hostile subsoil with salinity, boron toxicity, and nutrient deficiency are common in Southern Australia.

Population structure for the genetic study of drought tolerance

The size and structure of the population used for genetic analysis must be carefully assessed. Previous attempts by our group to use association mapping or multiparental populations to study the genetics of drought were not regarded as successful. These studies simply identified loci controlling phenology, largely maturity, height, and tillering, as the major components of the drought response. The loci identified were all previously known and had little practical relevance. As described below, our approach was to use several large populations based exclusively on parents adapted to our targeted environment but differing in drought responses.

Germplasm should be selected based on the likelihood that the lines will produce valuable new genetic combinations of direct and immediate relevance to breeding programmes developing cultivars for the target environment. Selection for drought tolerance should not have a significant negative effect on other selection targets in a breeding programme, such as maturity, height, disease resistance, and grain quality. The use of elite varieties in the targeted environment has some benefits: the lines can be used directly in a breeding programme. Moreover, alleles discovered in non-elite germplasm might not lead to improvement because it was already selected during the development of elite wheat cultivars (Collins et al., 2008).

Based around comprehensive field data generated during a severe drought in the 2001/2002 season, a genetics-based drought strategy was devised with Australian wheat breeders to select parental lines for the development of segregating populations. Elite cultivars and breeding lines were screened and assessed based on their grain yield under severe water limitation in a South Australian environment. A trait summary for the parental lines described below is presented in Table 3. The two lines Excalibur and RAC875 represent major sources of drought tolerance in the Southern Australian environment. RAC875 was also believed to show superior tolerance to heat stress during grain filling relative to other material in the breeding programmes. In the severe drought over the 2006 season where average yields at our field sites were only 0.8 t/ha, Excalibur and RAC875 were consistently higher yielding than other varieties (116% and 122% of the site means, respectively). Excalibur and RAC875 show similar behaviour under drought and out-yielded the variety Kukri, which was chosen as the drought-sensitive parent, by 10–40% under severe water stress. Figure 2 represents the percentage of yield production of four of the wheat cultivars on the basis of site means with an average grain yield below 3.0 t ha−1 (the data are based on the 2009 National Varietal trials and did not include RAC875). The parental line Drysdale was selected based on the carbon isotope discrimination screen, while Gladius is a new variety released in 2007 and is based on Excalibur and RAC875 (http://pbr.ipaustralia.plantbreeders.gov.au/). Gladius had been the highest yielding variety in the severe droughts of 2001/2002 and 2006/2007. Thus, this population will allow us to investigate the significance of the C-isotope discrimination trait relative to other factors and also allow confirmation of loci identified from the other two populations. Importantly, Gladius also shows the heat tolerance seen in RAC875. This is likely to be significant both in determining general tolerance to drought stress but may also be of importance in lifting yield and grain quality in irrigated environments.

Table 3.

Characteristics of wheat parents used for the drought mapping populations

Traits RAC875 Kukri Excalibur Drysdale Gladius 
Drought tolerance High Low High High High 
Heat tolerance High Low Intermediate Unknown High 
Boron uptake Low Intermediate Very high Intermediate–High Intermediate–High 
Sodium uptake Low–Intermediate Intermediate Low High Low–Intermediate 
Zn efficiency Low Low Intermediate–High Low Unknown 
Nematodes 
    Cereal cyst Unknown Susceptible Susceptible Susceptible Unknown 
    Root lesion Susceptible Susceptible Moderately resistant Susceptible Unknown 
High pH Intermediate Intermediate Intolerant Unknown Unknown 
Traits RAC875 Kukri Excalibur Drysdale Gladius 
Drought tolerance High Low High High High 
Heat tolerance High Low Intermediate Unknown High 
Boron uptake Low Intermediate Very high Intermediate–High Intermediate–High 
Sodium uptake Low–Intermediate Intermediate Low High Low–Intermediate 
Zn efficiency Low Low Intermediate–High Low Unknown 
Nematodes 
    Cereal cyst Unknown Susceptible Susceptible Susceptible Unknown 
    Root lesion Susceptible Susceptible Moderately resistant Susceptible Unknown 
High pH Intermediate Intermediate Intolerant Unknown Unknown 

The traits listed are expected to affect field performance of these lines under water limiting conditions.

Fig. 2.

Relative yield of mapping parents in low-yielding environments in 2009. The data are taken from the National Variety Trials (http://www.nvtonline.com.au/home.htm). The yields of the four varieties are expressed as a percentage of the site mean. RAC875 was not included in these trials.

Fig. 2.

Relative yield of mapping parents in low-yielding environments in 2009. The data are taken from the National Variety Trials (http://www.nvtonline.com.au/home.htm). The yields of the four varieties are expressed as a percentage of the site mean. RAC875 was not included in these trials.

For two populations, Excalibur×Kukri and RAC875×Kukri, doubled haploid (DH) populations (approximately 300 for each cross) and genetic maps have been generated, and seeds have been multiplied in Australia, India (DRW, Karnal), Mexico (CIMMYT) and Syria (ICARDA). Field data were collected from trials sown in Australia and Mexico in 2006, 2007, and 2008. Both crosses have also been used to generate large single seed descent populations (SSD or recombinant inbred lines, RILs) of 3000 lines, which have been taken to F5. For the population of Gladius×Drysdale, 5000 RILs have been produced, and a subset of 250 lines used for preparation of a preliminary map. In total, over 10 000 lines have been developed for the drought work. This represents a unique resource for studying the genetic control of drought tolerance in wheat. The nature of the populations means that they are of immediate relevance to wheat breeding programmes targeted to low-yielding Mediterranean type environments and they are being used directly for selecting new breeding lines.

The basic strategy for deploying these populations is to use the small doubled haploid populations and 250 randomly selected SSD lines for the Gladius×Drysdale for preliminary mapping of a wide range of drought-related traits under controlled greenhouse and field conditions. In addition, confounding factors such as boron and salinity tolerance and nematode resistance and tolerance (both cereal cyst and root lesion nematodes) have been assessed. Since the major loci controlling boron tolerance and nematode resistance are known (Gupta et al., 2010), these can be readily accounted for, but salt and nematode tolerance must be measured. The field data have been generated at multiple sites in Australia and at droughted and irrigated trials at the CIMMYT station at Obregon in Mexico.

The SSD populations are sufficiently large (3000 for each cross) to permit immediate transfer to positional cloning projects and detailed genetic dissection of traits. They also provide an opportunity to explore epistatic interactions. As loci influencing particular components of drought tolerance are identified, these will be used to divide the population for a second round of analysis. With populations of 3000 lines the behaviour of five or six loci alone or in combination can be explored. This will allow complex genetic interactions to be studied. In particular, this approach may permit analysis of genome interactions. Subsets of lines can also be selected to fix genes of major effect such as the flowering time genes Vrn or Ppd to overcome the confounding effect of maturity on other traits (Distelfeld et al., 2009).

Extensive description of the drought-tolerant and -sensitive parental lines

During the period of population development, detailed analyses of the parents can help define the physiological, biochemical, and molecular components of drought response and the difference in behaviour of parents. This information provides an opportunity for determining the relative significance and reliability of different phenotyping options in the segregating populations and also provides valuable resources to support gene discovery work.

The growth of the three key parents, Kukri, Excalibur, and RAC875 has been analysed in detail in controlled conditions and under a cyclic drought regime that reproduces the Southern Australian environment or Mediterranean type drought stress (Izanloo et al., 2008). Interestingly, Excalibur and RAC875 showed different strategies of tolerance to the same drought scenario. In the drought treatment, RAC875 produced fewer tillers, maintained a higher number of grains per tiller and showed moderate osmotic adjustment (Table 4). The mechanism of tolerance of RAC875 seemed more conservative: under both well-watered and dry conditions, plants stored more water-soluble carbohydrates in the stem, and leaves were more waxed and thicker, showing constitutive aspects of tolerance to drought. The genotype Excalibur showed higher osmotic adjustment, low ABA content, high stomatal conductance, and rapid recovery after stress. The plant morphology and yield component reflected this responsive mechanism: leaves rolled in dry conditions reducing radiation interception; a high number of tillers were produced and then aborted in water-limiting conditions; the plants were able to compensate for the tiller abortion by producing more grains per tiller after recovery. Excalibur showed a more responsive mechanism with a strong interaction with environmental conditions.

Table 4.

Characteristics of the ‘drought tolerant’ wheat genotypes RAC875 and Excalibur under a cyclic terminal drought regime

RAC875 Excalibur 
Lowest tiller number per se High tiller number, more tiller abortion under stress 
Thick green leaves Higher total biomass 
Stronger leaf waxiness Higher root-shoot ratio under water stress 
Stay-green phenotype  
Moderate osmotic adjustment Highest osmotic adjustment 
Low stomatal conductance Low ABA content under stress 
Slower recovery in stomatal aperture Highest stomatal conductance 
High water soluble carbohydrate Rapid recovery after re-watering 
RAC875 Excalibur 
Lowest tiller number per se High tiller number, more tiller abortion under stress 
Thick green leaves Higher total biomass 
Stronger leaf waxiness Higher root-shoot ratio under water stress 
Stay-green phenotype  
Moderate osmotic adjustment Highest osmotic adjustment 
Low stomatal conductance Low ABA content under stress 
Slower recovery in stomatal aperture Highest stomatal conductance 
High water soluble carbohydrate Rapid recovery after re-watering 

High water soluble carbohydrate

Another component of the parental analysis is the generation of molecular and biochemical data on the drought responses. ‘Omics profiles of the wheat parents Excalibur, RAC875, and Kukri have been developed during a cyclic drought under the same conditions as used for the morpho-physiological study by Izanloo et al. (2008). The Triticum aestivum 17 K oligo microarray, developed by the Genome Canada/Genome Prairie/Genome Quebec program Functional Genomics of Abiotic Stress (FGAS), the USDA-ARS-Genomics and Gene Discovery Research Unit, and the Australian Centre Plant Functional Genomics, was used. The probe sequences of the microchip were from cold-stressed cv. Norstar crown and leaf, cold- and salt-stressed root, unstressed controls, NSF-mapped ESTs, wheat zygotic and early embryo and ESTs of genes involved in cell-wall metabolism. Two treatments (cyclic drought and well-watered) of the three wheat lines, five sampling time-points (during development of drought, before and after rewatering) with five biological replicates per sampling time-point and three tissues per replicate (leaf, stem, and spike) generated more than 450 samples. Preliminary results of leaf samples showed a total of 6537 differentially expressed genes. A database, DroughtComparator, is being developed to support the analysis and interpretation of the data. This database will be publicly released on completion of the experiment. A cDNA series, for use in mRNA quantification by Q-PCR, is now being used to validate the gene expression profiles.

Metabolite profiles of leaves and grains have also been generated during the same experiment. The results showed significantly different responses to drought stress for RAC875, Kukri, and Excalibur. Interestingly, the control and water-stress data formed distinct clusters for Excalibur, the drought-responsive genotype. Other cell components such as fructans, betaines, lipids, and waxes are being measured. Detailed comparison with the transcript data should help us to understand the biochemical bases and regulation of the different tolerance mechanisms of Excalibur and RAC875.

Use of mathematical models for QTL analysis

A growing concept in biology is the use of mathematical models to understand complex traits such as yield during drought. The procedure consists of dissecting the phenotype and the response to environment into elementary and simpler responses (Reymond et al., 2003; Tardieu, 2003). Such modelling has been successfully used to study leaf growth in maize (Chenu et al., 2009). Manschadi et al., (2006) proposed the integration of physiological understanding with plant breeding to develop mechanistic crop models and design ideotypes to targeted environments.

The problem of non-stable QTL because of the differences of environmental conditions between experiments (Reymond et al., 2003) may be overcome by measuring accurately the environmental variables and using ecophysiological models. Combining QTL and ecophysiological models can help predict a phenotype from combinations of alleles by analysing the QTL for each parameter of the model. For example, the response of leaf growth to temperature and water deficit in maize has been broken down into traits such as intrinsic elongation rate (Reymond et al., 2003; Tardieu, 2003). The QTL for each trait did not coincide with the same regions of the genome suggesting that the traits were regulated by different genes. In this approach, the QTL correspond to well-defined functions, and hypotheses about the function of the genes underlying the QTL are likely to be more accurate and the number of candidate genes narrower than in conventional QTL mapping.

The gene networks are regulated and co-ordinated so that a plant reacts in a predictable way to a given environmental condition (Tardieu, 2003). The ‘omics datasets serve to help develop models of networks and pathways that are triggered in particular genotypes in response to drought. The network information can feed directly into building models of the relationship of specific pathways and processes to the physiological responses to drought. The comparison of gene regulatory networks and QTL for each parameter of the model could also help identify candidate genes for QTL cloning. By studying all possible aspects from molecular aspects to plant physiology in the same germplasm (RAC875, Excalibur, Kukri) and in a specific drought scenario (terminal drought of South Australia), it should be possible to dissect the phenotype from the gene to a plant mechanism and build the appropriate models. The approach is empowered by the use of the same germplasm for creating the genetic populations (DH and RIL) and allowing the analysis of different allelic combinations.

The QTL under fine-mapping at the ACPFG

Genetic maps using DArT and SSR markers have been constructed for Excalibur×Kukri, RAC875×Kukri, and Gladius×Drysdale populations. For each population, between 600 and 1000 markers have been included in the maps. The two Kukri populations were grown at more than ten sites in Southern Australian and at the CIMMYT field site in Obregon, for the past three years. There are now data available for over 20 sites per year. In addition to a standard assessment of lines during the growing season and recording of the detailed climatic data at each site, the soil at the field sites was sampled extensively and assessed for nutrient levels and the presence of soil pathogens and pests. The sites range from severe drought stress with average yields at below 0.5 t ha−1 to sites where average yields were around 7 t ha−1. The Excalibur×Kukri population has also been screened for tolerance to resistance to nematodes (both cereal cyst and root lesion), boron toxicity, sodium exclusion, and high pH using established laboratory-based hydroponic assays.

The first targets for positional cloning were common loci that appeared in both Kukri populations. For the target loci, around 6000 RILs are available to support fine mapping. Four loci have been identified for positional cloning: a locus on chromosome 1B associated with yield under drought, a locus on 3B associated with yield under heat stress and also canopy temperature suppression, a 6A locus that shows a correlation between flag leaf width and grain size and a 7A locus that shows increased spike length, higher grain number, and increased yield, particularly under severe drought stress (Izanloo et al., unpublished results). Loci of potential value to the breeding programmes will be confirmed using the larger RILs populations and through analysis of selected lines from the Gladius×Drysdale population. These will be made available to breeding programmes as rapidly as possible.

Moving forward to positional cloning of drought-tolerance QTLs

Fine mapping of a drought response may define a QTL to a region containing a large number of genes. Genes that show a drought-responsive expression pattern or may encode an enzyme or other protein involved in a metabolic pathway that responds to drought stress, would become strong candidates for further analysis. In maize, 22 differentially expressed genes were identified in a microarray experiment on four susceptible and tolerant recombinant inbred lines, co-located on the genetic map with QTLs for drought tolerance (Marino et al., 2009). A physical map of genes involved in drought tolerance has been attempted in wheat by Ramalingam et al. (2006) who assigned 259 EST (811 loci) to chromosome deletion bins of wheat. However, the analysis of transcript profiles in wheat is impaired by the absence of a genome sequence and knowledge of homeologous sequences. The comparison of QTL and microarray data is also difficult due to the low number of sequence-based markers in the wheat genetic map. To overcome the problem, an SNP database is under construction based on deep sequencing (over 1 million reads) of normalized full-length cDNA of the Australian parental lines described above. Preliminary results indicated that this work will generate around 30 000 SNPs per cross, which should greatly facilitate the fine-mapping of the QTL and the use of grass synteny to select candidate genes for cloning. It will also facilitate the genetic mapping of drought responsive genes in Excalibur and RAC875 identified by the microarray and reverse genetics programmes.

Major changes in gene expression, protein or metabolite profiles can be directly mapped onto the mapping populations. Coincidence of loci controlling gene expression (eQTL), protein (pQTL) or metabolite (mQTL) with physiological or yield-related loci, indicates possible biochemical processes underlying the physiological response. The co-localization of eQTL and physiological QTL for diverse traits showed that it may facilitate the identification of candidate genes and accelerate positional cloning (Kliebenstein, 2009). The gene expression profile of lines in a mapping population using Affymetrix microarrays successfully identified eQTL associated with seed development in wheat (Jordan et al., 2007) and resistance to leaf rust in barley (Chen et al., 2010b). This method also allows the identification of trans eQTL and provides valuable information on the regulatory network involved in different tolerance mechanisms. However, the cost of microarray analysis for a segregating population is prohibitive. To reduce the cost of such experiment, Xue et al. (2006) compared the transcript profiles of selected progeny lines showing difference in transpiration efficiency (carbon isotope discrimination). They identified 93 differentially expressed genes between high and low transpiration efficiency lines of a wheat progeny Quarrion/Genaro. In a similar approach, recombinant lines of the Excalibur/Kukri and RAC875/Kukri population will be selected based on the outcomes of field screening and will also feed into the metabolomics and transcription profiling projects.

Conclusions

Our knowledge of the mechanism of drought tolerance has been enhanced by research programmes targeting specific physiological, genetic or molecular aspects of the drought response. However, in wheat, these approaches have not led to an increase in tolerance over that already achieved by breeders using empirical selection. Although the idea of linking physiology, ‘omics and quantitative genetics have already been proposed, only a few research programmes have taken this integrative approach. The great strength of genetic and genomics analysis in wheat has been the ability to generate large populations and well-developed field phenotyping capabilities. However, genetic studies have often been too ambitious and not permitted effective dissection of the drought response or focused on specific drought scenarios or regimes. Analysis of the response to drought has been further complicated by the absence of a genome sequence and the generally poor genomics resources have been limiting. New developments in sequencing, marker development, and genome analysis have created the opportunity to revisit the way in which we structure populations for analysis and tackle specific components of drought tolerance. Phenotyping has now become the major cost and rate-limiting step in the genetic analysis of drought tolerance and many other traits, and the development of rapid and cheap procedures to characterize components of the drought response will be critical in improving genetic resolution.

We would like to thank Dr Ute Baumann and Dr Ali Izanloo for providing critical information on the parental lines used in this study. The work was supported through funding from the Australian Research Council, The Grains Research and Development Corporation, The Government of South Australia, and the Government of NSW.

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