Emerging trends in the functional genomics of the abiotic stress response in crop plants

Plant Biotechnol J. 2007 May;5(3):361-80. doi: 10.1111/j.1467-7652.2007.00239.x.

Abstract

Plants are exposed to different abiotic stresses, such as water deficit, high temperature, salinity, cold, heavy metals and mechanical wounding, under field conditions. It is estimated that such stress conditions can potentially reduce the yield of crop plants by more than 50%. Investigations of the physiological, biochemical and molecular aspects of stress tolerance have been conducted to unravel the intrinsic mechanisms developed during evolution to mitigate against stress by plants. Before the advent of the genomics era, researchers primarily used a gene-by-gene approach to decipher the function of the genes involved in the abiotic stress response. However, abiotic stress tolerance is a complex trait and, although large numbers of genes have been identified to be involved in the abiotic stress response, there remain large gaps in our understanding of the trait. The availability of the genome sequences of certain important plant species has enabled the use of strategies, such as genome-wide expression profiling, to identify the genes associated with the stress response, followed by the verification of gene function by the analysis of mutants and transgenics. Certain components of both abscisic acid-dependent and -independent cascades involved in the stress response have already been identified. Information originating from the genome-wide analysis of abiotic stress tolerance will help to provide an insight into the stress-responsive network(s), and may allow the modification of this network to reduce the loss caused by stress and to increase agricultural productivity.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Chromosome Mapping
  • Cloning, Molecular
  • Crops, Agricultural / genetics*
  • Crops, Agricultural / physiology
  • Gene Expression Profiling
  • Genes, Plant
  • Genome, Plant*
  • Genomics / trends*
  • Oligonucleotide Array Sequence Analysis
  • Plants, Genetically Modified / metabolism
  • Proteomics
  • Quantitative Trait Loci