QTLs for Drought-Adaptive Traits

On the discovery side, the past two decades have witnessed remarkable progress in several areas as shown also by the manuscripts in this special issue. The pivotal role of phenotyping in drought-related research is now universally recognized and receiving renewed attention (Tuberosa 2012; Araus and Cairns 2014). This revival in phenotyping has been sparked by the recent availability of new phenotyping technologies and highly automated platforms coupled with a better appreciation of the role of phenotyping in accelerating the response to selection for drought resistance, either through conventional or non-conventional approaches.

Dehydration avoidance and dehydration tolerance are the main mechanisms that contribute to maintain yielding ability under water-limited conditions (Blum 1988). Deep rooting and osmotic adjustment – classified under dehydration avoidance – enable the plant to maintain better hydration while other biochemical and physiological features (e.g. accumulation of molecular protectants, remobilization of stem water-soluble carbohydrates, etc.) classified under dehydration tolerance enable the plant to sustain metabolism even under severely dehydrated conditions. Notably, most genes induced under extreme dehydration have been shown to belong to metabolic pathways with doubtful functional significance under the water-limited field conditions encountered by wheat (Passioura 2007). Conversely, exploitation of naturally occurring variation for yield and/or drought-adaptive traits has allowed for slow albeit unequivocal progress in wheat performance under drought conditions (Reynolds and Tuberosa 2008).

Given the quantitative nature of abiotic stress tolerance, QTLs have been the main target of studies attempting to identify the loci regulating the adaptive response of crops to environmentally constrained conditions. In very few cases, major QTLs affecting yield and other drought-adaptive traits across a broad range of soil moisture conditions have been identified (Quarrie et al. 2005; Maccaferri et al. 2008).

QTLs for Root Architecture and Size Among the traits that affect the water balance of the plant, roots play a key role in conditions of limited soil moisture (Richards 2008). Roots show a high level of morphological and developmental plasticity, a peculiarity that allows plants to adapt to moisture-limited conditions (de Dorlodot et al. 2007; Den Herder et al. 2010). An example is provided by root aerenchyma and root angle, root features that are receiving increasing attention for their effects on the response to drought and other abiotic stresses (Christopher et al. 2013). Other root features remain much more challenging to investigate, particularly under field conditions, such as in the case of root depth, a trait that has repeatedly shown a key role in crop adaptation to drought conditions when residual moisture at maturity is mainly available in deeper soil layers (Blum 2009, 2011; Watt et al. 2013). In bread wheat, soil coring down to 2 m depth revealed a broad range of genetic variation in deep root traits and showed that root features of highperforming genotypes were superior to those of low-performing genotypes or commercial varieties (Wasson et al. 2014). Since direct measuring of root depth remains an unresolved challenge, large-scale phenotyping for this trait can only be addressed through the use of proxies (e.g. canopy temperature depression) that through aerial remote sensing allow for monitoring the water status of a large number of genotypes in the field (Lopes and Reynolds 2010; Lopes et al. 2014).

In wheat, root metaxylem diameter is another feature that has shown an association with yield under drought conditions (Schoppach et al. 2014). Notably, selection for higher water-use efficiency (WUE) has shown merits in Australian environments where the crop prevalently grows on moisture stored in the soil prior to planting. Under these conditions, a wheat plant using water conservatively is able to complete grain filling with greater amount of water available in the soil. The adoption of this conservative strategy led to the release of two cultivars ('Drysdale' and 'Rees'; Condon et al. 2004) characterized by yield increases of up to 23 % when compared with control cultivars. The final effects of root architecture and size on yield will depend on the distribution of soil moisture and the level of competition for water resources within the plant community.

A most challenging aspect is to define the most desirable root ideotype able to optimize yield according to the prevailing dynamics of soil moisture profile but also accounting for the concurrent presence of gradients in the soil profile for other abiotic factors (e.g. salinity, toxic elements, high pH, etc.) that may impair plant growth. Therefore, each root ideotype should be established based upon the prevailing soil features in the target environment, a good understanding of the root architectural features that limit water uptake, and the metabolic cost required to develop and functionally sustain the root system. Along this line, loci that affect root growth under particular abiotic (e.g. boron toxicity) and biotic (e.g. nematode resistance) constraints are interesting targets for MAS aimed at improving drought resistance through a more vigorous root system of wheat grown in problematic soils.

QTLs for Carbohydrate Accumulation and Relocation In wheat, the accumulation of carbohydrates and their relocation to the ear are key factors for optimizing yield under adverse environmental conditions (Blum 1998; Reynolds et al. 2009). In bread wheat, QTLs for stem reserve, water-soluble carbohydrates (WSC) remobilization and leaf senescence have been reported across well-watered and waterstressed conditions (Snape et al. 2007; Rebetzke et al. 2008; Bennett et al. 2012; Zhang et al. 2015). Although these studies showed an important role for WSC in assuring stable yield and grain size, Rebetzke et al. (2008) concluded that the small effects of many independent WSC QTLs may limit their direct use for MAS. A combined QTL analysis for yield of several wheat populations evaluated across different environments and seasons enabled Snape et al. (2007) to identify QTLs showing stable and differential expression across irrigated and non-irrigated conditions. Variation for stem water-soluble carbohydrate reserves was associated with the chr. 1RS arm of the 1BL/1RS translocated (from rye to wheat) chromosome, and was positively associated with yield under both irrigated and rainfed conditions, thus contributing to general adaptability (Snape et al. 2007). The beneficial role of this translocation on wheat performance under drought-stressed conditions has already been reported (Ehdaie et al. 2003).

QTLs for Other Traits of Interest for the Control of Water Balance Measurement of traits such as stomatal conductance, canopy temperature and leaf rolling provides indications of water extraction patterns and the water status of the plant. Therefore, measuring these traits together with soil moisture may help in selecting deep-rooted germplasm in environments where water is available at depth (Blum 1988; Reynolds et al. 2009). Stomatal conductance integrates important environmental and metabolic cues and allows the plant to modulate and optimize its transpiration and WUE (Brennan et al.2007). A study conducted on a series of successful bread wheat cultivars released from 1962 to 1988 showed a strong and positive correlation between stomatal conductance and grain yield (r = 0.94; Fischer et al. 1998), suggesting that the more modern cultivars extract more water from the soil. These results indicate the possibility of raising the yield potential using stomatal conductance as proxie and suggest the value of identifying the relevant QTLs. Canopy temperature is an integrative trait that reports on the water balance at the leaf and whole-plant level, thus providing a proxie of the capacity of the plant to extract soil moisture (Blum 1988, 2009; Reynolds and Tuberosa 2008). Canopy temperature depression (CTD) is mainly useful in hot and dry environments, with measurements preferably made on recently irrigated crops in cloudless and windless days at high vapour pressure deficits (Blum 1988; Reynolds et al. 2009). Under these circumstances, CTD can be a good predictor of grain yield in bread wheat (r varying from 0.6 to 0.8; Reynolds et al. 2009), where yield progress has been associated with cooler canopies, hence higher transpiration (Fischer et al. 1998). Genetic gains in yield have also been reported in response to direct selection for CTD (Reynolds et al. 2009).

QTLs for Yield Under Different Water Regimes As global climate change intensifies, the identification of loci with consistent per se effects on yield (i.e. not loci for flowering time) across a broad range of soil moisture regimes becomes increasingly important to raise yield potential (Maccaferri et al. 2008; Pinto et al. 2010; Reynolds et al. 2011; Turner et al. 2014). Major QTLs for grain yield and its components across a broad range of soil moisture regimes have all been reported in bread wheat (Quarrie et al. 2005; Kirigwi et al. 2007; Snape et al. 2007) with only one notable exception in durum wheat where Maccaferri et al. (2008) searched for QTLs for grain yield in RILs evaluated in 16 environments with a broad range in grain yield values (from 0.56 to 5.88 t ha−1), mainly consequent to different soil moisture availability. Two major QTLs on chr. 2BL and 3BS (QYld.idw-2B and QYld.idw-3B, respectively) showed highly significant and consistent effects in eight and seven environments, respectively. In both cases, an extensive overlap was observed between the LOD profiles for grain yield and plant height, but not with those for heading date, thus indicating that the effects of these two QTLs on yield were not due to escape from drought, a well-known factor in determining yield under terminal drought stress conditions that typically characterize Mediterranean environments (Araus et al. 2008). Accordingly, this population was originally chosen because it had shown limited variability in flowering time. For plant height and grain yield, a strong epistasis between QYld.idw-2B and QYld.idw-3B was detected across several environments, with the parental combinations providing the higher performance. These two QTLs evidenced significant additive and epistatic effects also on ear peduncle length and kernel weight (Graziani et al. 2014). As a prerequisie to positional cloning, progeny derived from the cross of isogenic lines have been evaluated for fine mapping of both QTLs (Maccaferri et al. unpublished).

 
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