Systems-Level Integration of Stress Signaling, Multi-Omics, and Predictive Breeding for Abiotic Stress Tolerance in Brassica Crops

Abstract

Climate change is increasing the frequency and severity of abiotic stresses, including drought, salinity, waterlogging, and temperature extremes, thereby threatening the productivity and quality of Brassica crops. This review synthesizes recent progress in abiotic stress tolerance from physiological, genetic, epigenetic, and multi-omics perspectives, with an emphasis on how mechanistic discoveries can be translated into breeding decisions. We first outline the signaling hierarchy that links stress perception at the plasma membrane and cell wall interface to Ca2+ signaling, MAPK cascades, hormone crosstalk, osmotic adjustment, ROS homeostasis, and metabolic reprogramming. We then examine the genetic architecture of stress tolerance through QTL mapping, GWAS, and functional genomics, highlighting how allopolyploidy, subgenome specialization, homoeologous gene divergence, and alternative splicing create both opportunities and complications for Brassica improvement. We further evaluate how transcriptomic, epigenomic, metabolomic, and microbiome-related data are revealing regulatory complexity but remain underused for prediction and causal inference. Major bottlenecks include the inefficient conversion of association signals into validated functional markers, the descriptive rather than predictive use of multi-omics datasets, limited mechanistic understanding of combined stresses, and insufficient field validation across genetic backgrounds. Finally, we discuss integrated breeding strategies, including marker-assisted selection, genomic selection, genome editing, wild germplasm utilization, microbiome-assisted approaches, and synthetic biology. By connecting stress biology with translational breeding, this review provides a framework for developing climate-resilient Brassica cultivars.