Molecular mechanisms and genic resources responsive to salinity stress and their applications in maize and other crop...

Soil salinization poses a global challenge to agricultural sustainability, crop productivity, and food security. In maize, salinity stress severely restricts root and shoot development, ultimately compromising yield and quality. Unlike the traditional descriptive structure, this review presents a method-validation-oriented workflow that summarizes the molecular and genetic basis of salinity tolerance and aims to integrate salt-responsive genic resources, mine candidate genes, and clarify their functional roles in maize. First, we synthesize independent studies on maize salinity tolerance and compile a curated set of reported salt-responsive genes. On this basis, we construct a regulatory network underlying plant responses to salinity stress, thereby outlining the evolving landscape of their genetic and molecular regulation. Second, we catalogue genic resources, including quantitative trait loci (QTLs), quantitative trait nucleotides (QTNs), and functionally validated genes, identify QTL/QTN hotspots, and validate a multi-omics integration strategy by mapping transcriptomic, proteomic, and metabolomic salt-responsive signals onto hotspot regions to prioritize candidate genes. Third, comparative collinearity analyses across maize, rice, wheat, and sorghum further reveal orthologous genes associated with salinity tolerance in maize. Through this workflow, we identify 19 previously uncharacterized genes involved in salinity stress responses, 14 of which are predicted to participate in three salt-responsive pathways: proline biosynthesis, ABA signaling, and the PEP bypass. Importantly, we further validate the practical utility of this review-derived prioritization by functionally testing two candidates using virus-induced gene silencing (VIGS). Collectively, this workflow provides a reusable, quality-controlled set of actionable targets for developing high-yielding, salt-tolerant maize and other crops through integrated genomics, systems biology, and advanced breeding technologies.