OMICs, Epigenetics, and Genome Editing Techniques for Food and Nutritional Security

Abstract

The incredible success of crop breeding and agricultural innovation in the last century greatly contributed to the Green Revolution, which significantly increased yields and ensures food security, despite the population explosion. However, new challenges such as rapid climate change, deteriorating soil, and the accumulation of pollutants require much faster responses and more effective solutions that cannot be achieved through traditional breeding. Further prospects for increasing the efficiency of agriculture are undoubtedly associated with the inclusion in the breeding strategy of new knowledge obtained using high-throughput technologies and new tools in the future to ensure the design of new plant genomes and predict the desired phenotype. This article provides an overview of the current state of research in these areas, as well as the study of soil and plant microbiomes, and the prospective use of their potential in a new field of microbiome engineering. In terms of genomic and phenomic predictions, we also propose an integrated approach that combines high-density genotyping and high-throughput phenotyping techniques, which can improve the prediction accuracy of quantitative traits in crop species.

Keywords: epigenetics; epigenomics; genome sequencing; genomic prediction; omics; plant microbiome; site-directed mutagenesis; transcriptome.

Figure 1

Overview of an integrated approach using genome-wide association study (GWAS) and spectral information for dissection of complex traits in a crop species (adapted from Feng et al. [261]). (a) A traditional breeding population (e.g., association panel, progeny trials, inbreed lines, etc.) is evaluated based on primary traits (traits of interest such as grain yield, seed quality, plant height, protein content, antioxidant content, resistance to pests and diseases, etc.). Pedigree information, experimental design, and other information can be considered. (b) One or more high-throughput phenotyping (HTP) platforms can be used to improve gene discovery, such as remote sensing with Unmanned Aerial Vehicles (UAVs), handheld spectroradiometers, hyperspectral imaging systems, etc. Hyperspectral or spectral indices are modeled with the primary traits selected according to their predictive ability. (c) Plants are genotyped using genotyping platforms; genotype quality control is performed. (d) GWAS of hyperspectral and spectral indices and traditional traits is performed. SNP or haplotype data can be used for a better dissection of a complex trait. (e) Candidate gene identification is carried out based on GWAS results. This combined strategy could provide additional gene discovery capabilities, as Feng et al. (2017) reported [261].