Integrative genomic and transcriptomic analyses characterize the regulatory landscape of symbiotic nitrogen fixation...

Symbiotic nitrogen fixation (SNF) is essential for legume productivity and sustainable agriculture, yet the genetic and regulatory bases of its natural variation remain incompletely understood. Here, we implemented an integrative multi-omics framework to dissect SNF architecture in a diversity panel of 360 soybean accessions encompassing both wild and cultivated lineages. SNF-related traits exhibited extensive variation and strong environmental sensitivity. Genome-wide association studies (GWAS) detected only modest-effect loci, consistent with a polygenic and context-dependent genetic architecture. To resolve regulatory mechanisms underlying this complexity, we analyzed population-scale mature nodule transcriptomes using independent component analysis (ICA), identifying 136 expression modules, of which 15 were significantly associated with SNF traits and enriched for circadian rhythm, lipid metabolism, and defense response pathways. Transcriptome-wide association studies (TWAS) identified 1,453,806, and 178 significant gene-trait associations for nitrogen fixation per plant (NFP), nodule weight (NW), and nitrogen fixation efficiency (NFE), respectively. Among these, 185 transcription factors were identified, 39% overlapping selective sweeps, suggesting evolutionary selection on transcriptional regulation. Expression quantitative trait locus (eQTL) mapping further uncovered 4,654 significant regulatory variants (1,241 cis-, 2,505 trans-, and 908 mixed), including 38 trans-regulatory hotspots collectively influencing ~2,400 genes, nearly half of which are located in domestication-diverged genome regions. Functional validation confirmed that the circadian regulator GmLHY acts as a negative modulator of nodulation, while Dt2, a developmental transcription factor, exerts pleiotropic effects on nodule biomass and fixation efficiency. To facilitate community access, we developed SoySNFdb, an open database integrating all information for SNF in soybean, featuring AI-assisted querying for interactive exploration of regulatory networks. Together, our results suggest that, within this population and experimental context, natural diversity in SNF is associated with regulatory and expression-level variation rather than major-effect coding variants. This integrative framework and accompanying resources establish a basis for system-level dissection and predictive improvement of nitrogen fixation efficiency in legumes.