This study investigated the regulatory effects of sowing date on seed quality formation in the brewing sorghum cultivar Hongyingzi using integrated transcriptomic and metabolomic approaches. Three sowing dates (early, normal, and late) were applied, and seeds were collected at 19, 26, and 33 days after pollination. Sowing date interacted with seed development to significantly affect morphological characteristics, pericarp structure, and metabolite accumulation. Transcriptomic analysis identified 3651 shared differentially expressed genes (DEGs) mainly enriched in photosynthesis, starch and sucrose metabolism, and flavonoid biosynthesis. Metabolomic profiling detected 1105 differentially expressed metabolites (DEMs), which were involved in flavonoid and starch–sucrose metabolism. Integrated analysis confirmed these two pathways as key responses to sowing date. Weighted gene co-expression network analysis (WGCNA) identified 17 hub genes, five of which were upregulated and contained light-responsive elements. These findings reveal the molecular mechanism underlying sowing date-mediated seed quality formation and provide a theoretical basis for high-quality sorghum production.
Sweet corn is a globally important dual-purpose crop for both food and fresh vegetables. The plant architecture and ear-related traits directly determine its yield potential and field ecological adaptability. To elucidate the genetic architecture of these traits and identify superior alleles for breeding, we conducted a genome-wide association study (GWAS) on 11 agronomic traits using 30,597 high-quality SNP markers in a panel of 101 elite sweet corn inbred lines. Population genetic structure was analyzed using sparse non-negative matrix factorization (sNMF) and discriminant analysis of principal components (DAPC) algorithms, revealing three main clusters and six subpopulations. The clustering pattern was highly consistent with germplasm origin. Association mapping with the fixed and random Circulating Probability Unification (FarmCPU) model identified 16 significant marker–trait associations (MTAs), distributed across seven target agronomic traits. The phenotypic variance explained (PVE) by individual loci ranged from 8.0% to 16.0%. Among these, five stable MTAs across environments, a novel ERN locus (SNP25518) specific to sweet corn, and most association intervals overlapped with previously reported quantitative trait loci (QTLs). Within the ±0.15 Mb (defined by LD decay) flanking windows around the significant SNP loci, a total of 236 candidate genes were annotated, which are primarily involved in hormone signaling, carbon and nitrogen metabolism, cell division, and plant growth and development. In summary, this study dissected the genetic basis of key agronomic traits in sweet corn and provides a foundation for marker-assisted selection and functional validation.
Yanchao Du, Jingwen Xu, Huiming Li et al.· Plants· 0 citations