MicroRNA and cDNA-Microarray as Potential Targets against Abiotic Stress Response in Plants: Advances and Prospects

Abstract

Abiotic stresses, such as temperature (heat and cold), salinity, and drought negatively affect plant productivity; hence, the molecular responses of abiotic stresses need to be investigated. Numerous molecular and genetic engineering studies have made substantial contributions and revealed that abiotic stresses are the key factors associated with production losses in plants. In response to abiotic stresses, altered expression patterns of miRNAs have been reported, and, as a result, cDNA-microarray and microRNA (miRNA) have been used to identify genes and their expression patterns against environmental adversities in plants. MicroRNA plays a significant role in environmental stresses, plant growth and development, and regulation of various biological and metabolic activities. MicroRNAs have been studied for over a decade to identify those susceptible to environmental stimuli, characterize expression patterns, and recognize their involvement in stress responses and tolerance. Recent findings have been reported that plants assign miRNAs as critical post-transcriptional regulators of gene expression in a sequence-specific manner to adapt to multiple abiotic stresses during their growth and developmental cycle. In this study, we reviewed the current status and described the application of cDNA-microarray and miRNA to understand the abiotic stress responses and different approaches used in plants to survive against different stresses. Despite the accessibility to suitable miRNAs, there is a lack of simple ways to identify miRNA and the application of cDNA-microarray. The elucidation of miRNA responses to abiotic stresses may lead to developing technologies for the early detection of plant environmental stressors. The miRNAs and cDNA-microarrays are powerful tools to enhance abiotic stress tolerance in plants through multiple advanced sequencing and bioinformatics techniques, including miRNA-regulated network, miRNA target prediction, miRNA identification, expression profile, features (disease or stress, biomarkers) association, tools based on machine learning algorithms, NGS, and tools specific for plants. Such technologies were established to identify miRNA and their target gene network prediction, emphasizing current achievements, impediments, and future perspectives. Furthermore, there is also a need to identify and classify new functional genes that may play a role in stress resistance, since many plant genes constitute an unexplained fraction.