Abstract
Buckwheat (Fagopyrum spp.) is a pseudocereal with nutraceutical properties that offer several nutritional and health benefits. Buckwheat proteins are gluten-free and have balanced quantities of amino acids and micronutrients, with a higher content of health-promoting bioactive flavonoids that make it a golden crop of the future. In the present study, we conducted a genome-wide association study (GWAS) to investigate the genetic basis of nutraceutical traits in buckwheat. Using 132 diverse genotypes, we evaluated 10 key nutritional and nutraceutical traits: phenol, flavonoids, antioxidants, methionine, lysine, protein content, nitrogen, iron, zinc, and ascorbic acid. Fagopyrum tartaricum displayed higher levels of phenols, flavonoids, antioxidants, iron, zinc, and nitrogen, while Fagopyrum esculentum exhibited elevated methionine, lysine, protein, and ascorbic acid levels. Genotyping by sequencing identified 3,728,028 single-nucleotide polymorphisms (SNPs), with the highest density on chromosome 1. GWAS detected 46 significant SNPs associated with the studied traits, including an SNP on chromosome 6 linked to lysine with aphenotypic contribution of 49.62%. Candidate gene analysis identified 138 genes within 100 kb of significant quantitative trait loci (QTLs), involved in metabolic and biosynthetic pathways such as amino acid and carbohydrate metabolism. Population structure analysis grouped the genotypes into three populations, enhancing the reliability of marker-trait associations. Gene Ontology analysis highlighted key biological processes, including lipid transport, tryptophan metabolism, and protein phosphorylation, providing insights into the molecular mechanisms governing these traits. The present study emphasizes the potential of molecular breeding to enhance the nutritional quality of buckwheat and its role in addressing global malnutrition. The identified SNP markers and candidate genes offer a valuable foundation for developing high-yield, nutrient-rich buckwheat varieties through genome editing and marker-assisted selection.