Salinization of cultivated soils may result in either high salt levels or alkaline conditions, both of which stress crops and reduce performance. We sampled genotypes included in the Northeast China soybean germplasm population (NECSGP) to identify possible genes that affect tolerance to alkaline soil conditions. In this study, 361 soybean accessions collected in Northeast China were tested under 220 mM NaHCO₃:Na₂CO₃ = 9:1 (pH = 9.8) to evaluate the alkali-tolerance (ATI) at the seedling stage in Mudanjiang, Heilongjiang, China. The restricted two-stage multi-locus model genome-wide association study (RTM-GWAS) with gene–allele sequences as markers (6503 GASMs) based on simplified genome resequencing (RAD-sequencing) was accomplished. From this analysis, 132 main effect candidate genes with 359 alleles and 35 Gene × Environment genes with 103 alleles were identified, explaining 90.93% and 2.80% of the seedling alkali-tolerance phenotypic variation, respectively. Genetic variability of ATI in NECSGP was observed primarily within subpopulations, especially in ecoregion B, from which 80% of ATI-tolerant accessions were screened out. The biological functions of 132 candidate genes were classified into eight functional categories (defense response, substance transport, regulation, metabolism-related, substance synthesis, biological process, plant development, and unknown function). From the ATI gene–allele system, six key genes–alleles were identified as starting points for further study on understanding the ATI gene network.

Introduction: Wall-associated receptor kinases (WAKs) are a family of receptor-like kinases (RLKs) that play important roles in the communication between the plant cell wall and the cytoplasm. WAKs have been identified in several plants. However, a comprehensive investigation of maize WAKs has not been performed yet.Methods: In this study, the maize WAK gene family was identified through whole-genome scanning. y -30The physicochemical characteristics, chromosomal locations, phylogenetic tree, gene structures, conserved motifs, gene duplication, collinearity, and cis-acting elements of maize WAKs were analyzed.Results: A total of 56 ZmWAKs were identified in the maize genome and divided into seven subgroups. Among these, 54 genes were successfully mapped to maize chromosomes. Gene duplication events were detected in 13 ZmWAKs, with nine segmental (SD) and two tandem duplication (TD) events. Maize WAKs exhibited zero, eight, 27, and 41 collinear links with the WAKs from Arabidopsis, soybean, rice, and sorghum, respectively. In the promoter regions of ZmWAKs, a total of 107 types of cis-acting elements were predicted. Among them, the functions of 82 elements are known. These elements are associated with plant growth and development and light, hormones, stress, and defense responses. The transcriptome data analysis showed that ZmWAKs displayed tissue-specific expression and are involved in the responses to various abiotic and biotic stresses, including cold, salt, drought, waterlogging, pathogens, and pests. ZmWAK9, ZmWAK15, ZmWAK27, ZmWAK41, and ZmWAK49 are significantly induced by multiple stress conditions, indicating their crucial roles in stress responses and potential value for further research.Discussion: Our results provide insights into the function of maize WAKs in response to abiotic and biotic stresses and offer a theoretical foundation for understanding their mechanisms of action.

In soybeans (Glycine max (L.) Merr.), their growth periods, DSF (days of sowing-to-flowering), and DFM (days of flowering-to-maturity) are determined by their required accumulative day-length (ADL) and active temperature (AAT). A sample of 354 soybean varieties from five world eco-regions was tested in four seasons in Nanjing, China. The ADL and AAT of DSF and DFM were calculated from daily day-lengths and temperatures provided by the Nanjing Meteorological Bureau. The improved restricted two-stage multi-locus genome-wide association study using gene–allele sequences as markers (coded GASM-RTM-GWAS) was performed. (i) For DSF and its related ADL_DSF and AAT_DSF, 130–141 genes with 384–406 alleles were explored, and for DFM and its related ADL_DFM and AAT_DFM, 124–135 genes with 362–384 alleles were explored, in a total of six gene–allele systems. DSF shared more ADL and AAT contributions than DFM. (ii) Comparisons between the eco-region gene–allele submatrices indicated that the genetic adaptation from the origin to the geographic sub-regions was characterized by allele emergence (mutation), while genetic expansion from primary maturity group (MG)-sets to early/late MG-sets featured allele exclusion (selection) without allele emergence in addition to inheritance (migration). (iii) Optimal crosses with transgressive segregations in both directions were predicted and recommended for breeding purposes, indicating that allele recombination in soybean is an important evolutionary drive. (iv) Genes of the six traits were mostly trait-specific involved in four categories of 10 groups of biological functions. GASM-RTM-GWAS showed potential in detecting directly causal genes with their alleles, identifying differential trait evolutionary drives, predicting recombination breeding potentials, and revealing population gene networks.

Soybean (Glycine max (L.) Merr.) is a typical short-day and thermophilic crop. This study aimed to reveal the required accumulative day length (ADL) and accumulative active temperature (AAT) for DSF (days of sowing to flowering) and DFM (days of flowering to maturity) in global soybeans. A sample consisted of 354 varieties from 27 countries in five geographic regions, which were tested in Nanjing, China in two spring-sowing and two summer-sowing seasons. The ADL and AAT were calculated from the climatological data provided by the Public Service of Nanjing Meteorological Bureau. The results showed that the average DSF and DFM of global soybeans were 41.0 d and 83.3 d, which required ADL_DSF of 606.6 d·h and AAT_DSF of 1185.9 d·°C, ADL_DFM of 1126.7 d·h and AAT_DFM of 2145.1 d·°C, respectively, all with a wide variation among/within geographic and MG(maturity-group)-set subpopulations. From the multiple regression of DSF and DFM on required ADL and AAT, the ADL, AAT and ADL×AAT contributed 38.5%, 44.79% and 17.10% to DSF variation and 86.98%, 11.42% and 0.54% to DFM variation, respectively, and their relative importance to DSF and DFM varied among the geographic and MG subpopulations. The geographic subpopulations matched only partially with the genomic marker clusters, indicating multiple genetic sources of each subpopulation and that genetic exchange happened among subpopulations.

Soil salinity severely constrains global soybean productivity, yet conventional gene discovery remains bottlenecked by the slow pace of forward genetics and the limited breeding relevance of reverse genetics. Here, we establish a translational genomics paradigm that integrates systematic gene family characterization with large-scale population mining to rapidly identify breeding-ready alleles. We first comprehensively analyzed the soybean GA oxidase (GmGAox) superfamily, revealing 48 genes that expanded via whole-genome and tandem duplications into four subclades with distinct regulatory architectures enriched for stress and hormone-responsive cis-elements. Transcriptome profiling and functional validation identified six C19-GmGA2ox members, particularly GmGA2ox16, as rapidly salt-inducible genes that enhance antioxidant capacity and confer stress tolerance in yeast and soybean hairy roots. By re-mining 2898 resequenced accessions, we uncovered two GmGA2ox16 haplotypes defined by non-synonymous SNPs (N31D, A182P) in conserved catalytic domains. The superior GmGA2ox16^-Hap1 allele exhibits strong domestication selection signatures (71.17% in landraces to 78.10% in improved cultivars). Phenotyping 102 accessions using a wilting index revealed GmGA2ox16^-Hap1 carriers exhibited significantly superior salt tolerance versus GmGA2ox16^-Hap2. This study provides a deployable functional marker that shortcuts the lengthy fine-mapping required for traditional QTL cloning, demonstrating a data-driven framework to accelerate climate-resilient crop breeding. Our work establishes a paradigm for rapidly translating public omics data into agronomically relevant genetic resources, accelerating the development of climate-resilient soybean cultivars.