Departament de Biologia, Bioquímica i Ciències Naturals, Universitat Jaume I, 12071 Castelló de la Plana, Spain.
Instituto de Bioingeniería, Universidad Miguel Hernández, 03202 Elche, Spain.
Int J Mol Sci. 2023 Jan 28;24(3):2526. doi: 10.3390/ijms24032526.
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.
选择具有提高生产力和环境胁迫耐受性的植物基因型一直是植物育种的主要关注点。基于变异的产生和从大量变异群体中选择更好表型的经典方法，由于分子生物学技术，特别是基因组学、下一代测序和其他组学（如蛋白质组学和代谢组学）的实施，已经提高了它们的功效和连续性。在这方面，利用分子标记在感兴趣的表型性状表现之前鉴定出有趣的变异体，加速了新品种的选育进程。此外，表型或生化性状与基因表达或蛋白质丰度的相关性，使用相对较少的变异体，促进了对感兴趣性状的潜在新调控因子的鉴定。这些重要的突破技术建立在经典方法的基础上，未来将通过包括空间变量来改进，从而可以在组织和细胞水平上鉴定参与关键过程的基因。
