From Classical to Modern Computational Approaches to Identify Key Genetic Regulatory Components in Plant Biology

Abstract

The selection of plant genotypes with improved productivity and tolerance to environmental constraints has always been a major concern in plant breeding. Classical approaches based on the generation of variability and selection of better phenotypes from large variant collections have improved their efficacy and processivity due to the implementation of molecular biology techniques, particularly genomics, Next Generation Sequencing and other omics such as proteomics and metabolomics. In this regard, the identification of interesting variants before they develop the phenotype trait of interest with molecular markers has advanced the breeding process of new varieties. Moreover, the correlation of phenotype or biochemical traits with gene expression or protein abundance has boosted the identification of potential new regulators of the traits of interest, using a relatively low number of variants. These important breakthrough technologies, built on top of classical approaches, will be improved in the future by including the spatial variable, allowing the identification of gene(s) involved in key processes at the tissue and cell levels.

Unveiling the Molecular Basis of Stem-Physical-Strength-Mediated-Resistance (SPSMR) Mechanism Against Sclerotinia sclerotiorum in Brassicaceae: A Comparative Transcriptome Analysis of Resistant and Susceptible Genotypes

“…Comparative transcriptomic analysis is a powerful tool in molecular biology and genetics for studying gene expression patterns and unraveling the molecular basis of disease resistance in plants. This approach offers valuable insights into the underlying mechanisms of resistance to pathogens, encompassing the identi cation of candidate genes, elucidation of signaling pathways and molecular networks associated with disease resistance, functional annotation of previously uncharacterized genes, identi cation of molecular markers linked to disease resistance traits, and understanding the regulatory mechanisms governing gene expression during the defense response (Acién et al 2023). By leveraging this comprehensive understanding, comparative transcriptomic analysis facilitates the development of resistant cultivars through targeted breeding and gene editing strategies.…”