Approaches and Technologies for Genetic Improvement

Crop improvement needs to be appropriate for specific circumstances (local cultivation conditions and practices) as well as targeting specific crops and end uses of these crops. The traits involved in yield production and in efficient resource utilization are complex and involve many genes. The classical approach is breeding for phenotypes. Genetic analysis provides molecular markers to facilitate MAB and no knowledge of the precise mechanisms or specific genes controlling the traits is necessarily required. Ideally, however, these markers will be the specific genes/alleles making a major contribution to that trait. Identifying and modelling the important and relevant traits is a prerequisite to targeted identification of these key genes. Technologies for identifying new key genes will exploit facilities offered by genomics research including transcriptomics (Lu et al., 2005), traditional quantitative trait loci (QTL)-based approaches (Habash et al., 2007) and combinations of these technologies such as expression QTLs (eQTLs) (West et al., 2007). Traditional breeding, using these genes as markers, remains the key route to improvement, although the use of TILLING (Targeting Induced Local Lesions IN Genomes) (Parry et al., 2009) and gene transformation offer a rapid and targeted approach which will become important in the future. A huge wealth of genetic diversity exists even within many modern elite germplasms (e.g. see Fig. 8.3). However, research and breeding programmes are increasingly re-examining older varieties and landraces or even wild relatives in search of 'lost' alleles which may contribute to performance under the more stressed conditions that are anticipated.

Ideotypes may be defined for circumstances and improvement should be targeted to achieve these. The ideotypes may include traits targeted at resource capture, translation into yield or quality aspects. A net result will be increased yield and/or reduction in inputs, resulting in net decreased GHG emissions.

Low-input agricultural systems inevitably have lower emissions associated with them, although this may not always be the case and inefficiencies in terms of management or available germplasm should be targeted. Crop ideotypes will be quite specific for low-input systems and may include m E

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Varieties of wheat

Fig. 8.3. Ranked variation in NUtE (yield for N taken up) in different varieties grown in the Wheat Genetic Improvement Network trial at Rothamsted Research from 2004 to 2007 (least significant difference at 5% level 5.4) (data courtesy of Peter B. Barraclough).

Varieties of wheat

Fig. 8.3. Ranked variation in NUtE (yield for N taken up) in different varieties grown in the Wheat Genetic Improvement Network trial at Rothamsted Research from 2004 to 2007 (least significant difference at 5% level 5.4) (data courtesy of Peter B. Barraclough).

increasing resource capture efficiencies, particularly at low availability, for example, of water and fertilizers.

Many routes to crop improvement will be found by examining diversity in the widest possible range of germplasm. In some cases, as already noted, this may require re-examination of wild relatives and landraces. Bottlenecks in selection may have been introduced by continued selection in high-input situations, although this does not seem to be the case, at least in relation to N fertilizers and wheat (Ortiz-Monasterio et al., 1997). Beyond natural variation there may be circumstances where specific targeted gene intervention may have a major impact. Such an example would be the introduction of the alanine amino transferase gene under the control of a root epidermal promoter, which has an effect of improving N capture efficiency (Good et al., 2007; Shrawat et al., 2008).

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