Researchers utilized multi-locus GWAS to uncover key QTNs and candidate genes associated with agronomic and yield-related traits in Ethiopian sorghum landraces, providing valuable insights for genomics-assisted breeding of resilient, high-yielding varieties.
This study identifies and validates new stable dw3 dwarfing alleles using sorghum pangenome data to improve genetic diversity and eliminate height revertants in U.S. grain sorghum breeding.
Research reveals that drought stress disrupts photosynthesis by down-regulating key genes in C3 (wheat) and C4 (sorghum) plants, with wheat exhibiting greater susceptibility, highlighting potential genetic targets for improving drought tolerance in crops.
The MGS1 gene in sorghum, encoding a MIKC-type MADS-box transcription factor, regulates the multiple-grain spikelet (MGS) trait, with natural mutations like mgs19E and mgs1BA45 significantly increasing grain yield by producing adjacent double-pistil primordia.
Sorghum, a high-biomass crop, shows promise for phytoremediation of cadmium (Cd)-contaminated soils, with Cd uptake and translocation largely influenced by genotype-specific expression of ABC transporter proteins, particularly SbABCB11.
Sorgoleone enhances arbuscular mycorrhizal fungi (AMF) colonization in sorghum, optimizing phosphorus uptake and plant growth, with 20 µM identified as the optimal concentration for symbiotic efficiency.
The Sequential SNP Prioritization Algorithm (SSPA) refines GWAS results by leveraging correlation-based feature engineering to prioritize SNPs associated with complex traits in sorghum, providing valuable insights for functional genomics research and enabling downstream machine learning applications.
