Ionomic Approaches for Discovery of Novel Stress-Resilient Genes in Plants

Int J Mol Sci. 2021 Jul 2;22(13):7182. doi: 10.3390/ijms22137182.

Abstract

Plants, being sessile, face an array of biotic and abiotic stresses in their lifespan that endanger their survival. Hence, optimized uptake of mineral nutrients creates potential new routes for enhancing plant health and stress resilience. Recently, minerals (both essential and non-essential) have been identified as key players in plant stress biology, owing to their multifaceted functions. However, a realistic understanding of the relationship between different ions and stresses is lacking. In this context, ionomics will provide new platforms for not only understanding the function of the plant ionome during stresses but also identifying the genes and regulatory pathways related to mineral accumulation, transportation, and involvement in different molecular mechanisms under normal or stress conditions. This article provides a general overview of ionomics and the integration of high-throughput ionomic approaches with other "omics" tools. Integrated omics analysis is highly suitable for identification of the genes for various traits that confer biotic and abiotic stress tolerance. Moreover, ionomics advances being used to identify loci using qualitative trait loci and genome-wide association analysis of element uptake and transport within plant tissues, as well as genetic variation within species, are discussed. Furthermore, recent developments in ionomics for the discovery of stress-tolerant genes in plants have also been addressed; these can be used to produce more robust crops with a high nutritional value for sustainable agriculture.

Keywords: QTL mapping; abiotic stress; biotic stress; elemental analysis; gene identification; ionomics; omics.

Publication types

  • Review

MeSH terms

  • Adaptation, Biological / genetics
  • Crops, Agricultural / metabolism*
  • Ion Transport / genetics*
  • Ions
  • Metabolomics / trends*
  • Plants, Genetically Modified / metabolism*
  • Quantitative Trait Loci
  • Spectrum Analysis
  • Stress, Physiological / genetics*

Substances

  • Ions