Drought stress: molecular genetics and genomics approaches

Official URL: http://dx.doi.org/10.1016/B978-0-12-387692-8.00013-8

Agriculture faces a constant challenge to increase crop production annually in response to human population growth. As land and water resources become limiting, high-yielding crops even in environmentally stressful conditions will be essential. Drought is the single largest abiotic stress factor leading to reduced crop yields, and as such, has been a target of research for some decades. Recently, however, the rapid advance of molecular biological, transgenic and functional genomics technologies has facilitated significant progress in identifying some aspects of the drought response in plants. This chapter summarizes the current state of knowledge of the molecular events that take place when a plant is under drought stress, starting with the mechanisms by which the plant perceives drought and the intracellular signalling pathways that are engaged in initiating the drought response. Next, the functional importance of various biomolecules that are synthesized or activated to protect the plant from cellular damage during drought are considered. The differing capacity of varieties of the same species to respond to drought stress is associated with differing gene expression patterns, so the mechanisms by which drought-responsive gene expression is regulated are discussed at the transcriptional and post-transcriptional levels. A large number of genes and gene products have been implicated in the drought response, but identifying which are most useful for breeding drought-resistant crop varieties remains a significant technical challenge. The second half of the chapter, therefore, surveys the molecular methods that are currently in use for drought research, and ways in which they can be applied to accelerate breeding for drought resistance. Particular focus is given to post-genomic techniques-transcriptomics, proteomics and metabolomics-assessing the relative strengths and weaknesses of each approach and how to make use of the large datasets they produce.