Omics Under Elevated Night Temperature

A steady increase in global temperature as an immediate effect of climate change has raised maximum and minimum temperatures, altered day– night temperature balance, and, with minimal chances for radiant heat loss at night, led to elevated night-time temperatures. This unusual rise in night temperature (HNT) appears to negatively influence circadian rhythms, interfering with the normal functioning, growth, and development of a plant. This reduction in plant growth is mainly because of the disturbances at cellular, molecular, and genetic levels causing redox imbalance, fluctuation of enzyme activity, and disruption of biological function. Being sessile and immobile, plants have developed diversified evolutionary patterns that are effective in efficiently stabilizing the ill effects of HNT. To understand plant adaptations under HNT, studying multiple dimensions covering entire plant developmental regulations is necessary. This is where omics techniques such as genomics, transcriptomics, metabolomics, and phenomics come into play for the complete and comprehensive study of internal mechanisms within a plant. Genomics provides complete information about the plant genome, identifies key genes controlling stress tolerance, and helps in their functional analysis and characterization. Transcriptomic analysis reveals the expression levels of genes, their location, function, regulation, interaction, and degradation during stress. Metabolomic profiling provides qualitative and quantitative knowledge about putative metabolites regulating biochemical responses during stress and identifies modifications in metabolic pathways. Phenomics provides the phenotypic variation in plants under stress and helps to know modifications in morphological traits under stress. Combining these techniques in studying the effects of HNT gives a multidimensional view of regulatory mechanisms in plants. Further, these technologies help in understanding the mechanisms governing plant phenotypes under stress and allow us to identify biomarkers for future crop improvement studies.