Building knowledge and understanding

An 'explosion' in plant genetics and genom-ics research as well as the quantity of information about plant genome structure, has resulted in a 'technology gap'. Resource development has exceeded the ability to solve practical plant breeding problems using those resources. This gap is being closed by providing tools and methods to breeders to help them identify, and select, traits and underlying genes.

order to fully exploit these genetic mechanisms (Reynolds et al., 2005).

Developing new crop breeding strategies

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Generating

genetically

modified plants

Better understanding of adaptive change mechanisms

Example 6: A reduction in leaf water causes a passive loss in guard cell turgor, reducing photo-synthetic activity, and, with increased irradiance, an excess of reactive oxygen species (ROS). These are toxic to cellular metabolism. Plants produce chemical antioxidants such as ascorbic acid, glutathione and a-tocopherol as well as enzymes such as peroxidases and superoxide dismutases capable of detoxifying ROS. Turgor is managed by subcellular sequestration of ions such as Na+ and K+ into the vacuole and by synthesizing osmolytes (reviewed by Langridge et al., 2006).

Example 7: Identification of the disaccharide, trehalose, from desert resurrection species has helped to classify non-reducing disaccharides as osmoprotectants functionally important for drought tolerance. Understanding the physiology of trehalose accumulation has led to an improvement in drought tolerance of species such as rice, potato and tomato. These findings show that novel physiological traits can be used for selection (Almeida et al., 2007).

Fig. 12.2. How biotechnology helps breeding.

Understanding mechanisms and processes

Biotechnology helps us understand the effects of simultaneous multiple, complex stresses, such as drought, where multiple signalling pathways are activated and specific responses cannot always be assigned to an individual stress. Transcript profiling can be used to classify stress responses: for example osmotic stress responses can be initiated via either an abscisic acid (ABA)-dependent or an independent signalling pathway (Gosti et al., 1995; Ishitani et al., 1997).

Biotechnologies are tools used to identify, classify and select these traits.

Plant modelling

Plant breeding predicts phenotypes, based on genotypes, by measuring phenotypic performance in large segregating populations and then applying statistical procedures based on quantitative genetic theory.

Plant modelling can link phenotypic and physiological/molecular knowledge.

Example 8: Modelling of osmotic adjustment in sorghum identified the functional mode of action, and estimated yield advantages of up to 5% across multiple stress environments (Hammer et al., 1999). Plant modelling can be also used to develop alternative breeding strategies (Chapman et al., 2003). Kuchel et al. (2005) used computer simulation to design a genetically effective, economically efficient marker-assisted wheat breeding strategy. Significant genetic gains in yield, end-use quality and disease resistance resulted.

Gene network models, while less common, may predict the consequences of altering specific gene sequences and protein modifications.

It is unclear which physiological or molecular processes need to be modified, or selected for, to improve crop productivity under drought stress. There is controversy about the value of selection for osmotic adjustment and ABA response; a systematic trait orientated breeding approach is required in

Example 9: Flowering-time transition models in Arabidopsis (Koornneef et al., 1998; Welch et al., 2003) laid the foundation for gene-sequence-based predictive modelling, which is now applied to predict sorghum flowering time. The simulation model predicted grain yield, from two allelic variants of sorghum, for a number of specific environments (Hammer et al., 2008).

Yield potential and stability

Molecular processes underlying yield potential and stability have primarily targeted increasing source and sink strengths and the modifications of assimilate partitioning, plant architecture and development (Van Camp, 2005). Little progress has been made in quantitatively identifying genetic components that define yield.

Strategies to enhance yield per se may include:

1. Introducing more efficient C4-like photosynthesis from maize into C3 rice. So far, these approaches have not resulted in full C4 photosynthesis despite maize having a close evolutionary relatedness to rice. Combining the expression of two C4 enzymes (phos-phoenolpyruvate carboxylase and pyruvate orthophosphate dikinase) has, however, resulted in increases of 35% in photosyn-thetic capacity and 22% in yield (Ku et al., 2001).

2. Introducing variants of Rubisco, a key enzyme for carbon fixation, with a higher catalytic rate and/or better discrimination between gaseous substrates. Manipulating Rubisco activase by targeting the synthesis or degradation of inhibitors may modulate Rubisco activity and control its stability under stress. Some chimeric and mutant versions of Rubisco activase are less heat labile and, when reintroduced back into Arabidopsis, have improved photosynthesis and leaf growth under heat stress (Kurek et al., 2007; Portis et al., 2007).

3. Increased endosperm ADP-glucose pyro-phosphorylase activity. Yield enhancement of more than 20% occurred when wheat and rice were modified for this rate-limiting enzyme in endosperm starch synthesis, an important determinant of sink strength.

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