Genome-wide SNP discovery and genotyping delineates potential QTLs underlying major yield-attributing traits in buckwheat.

Buckwheat (Fagopyrum spp.) is an important nutritional and nutraceutical-rich pseudo-cereal crop. Despite its obvious potential as a functional food, buckwheat has not been fully harnessed due to its low yield, self-incompatibility, increased seed cracking, limited seed set, lodging, and frost susceptibility. The inadequate availability of genomics resources in buckwheat is one of the major reasons for this. In the present study, genome-wide association mapping (GWAS) was conducted to identify loci associated with various morphological and yield-related traits in buckwheat. High throughput genotyping by sequencing led to the identification of 34,978 single nucleotide polymorphisms that were distributed across eight chromosomes. Population structure analysis grouped the genotypes into three sub-populations. The genotypes were also characterized for various qualitative and quantitative traits at two diverse locations, the analysis of which revealed a significant difference in the mean values. The association analysis revealed a total of 71 significant marker-trait associations across eight chromosomes. The candidate genes were identified near 100 Kb of quantitative trait loci (QTLs), providing insights into several metabolic and biosynthetic pathways. The integration of phenology and GWAS in the present study is useful to uncover the consistent genomic regions, related markers associated with various yield-related traits, and potential candidate genes having implications for being utilized in molecular breeding for the improvement of economically important traits in buckwheat. Moreover, the identified QTLs will assist in tracking the desirable alleles of target genes within the buckwheat breeding populations/germplasm.

Metabolic-GWAS provides insights into genetic architecture of seed metabolome in buckwheat.

BACKGROUND: Buckwheat (Fagopyrum spp.), belonging to the Polygonaceae family, is an ancient pseudo-cereal with high nutritional and nutraceutical properties. Buckwheat proteins are gluten-free and show balanced amino acid and micronutrient profiles, with higher content of health-promoting bioactive flavonoids that make it a golden crop of the future. Plant metabolome is increasingly gaining importance as a crucial component to understand the connection between plant physiology and environment and as a potential link between the genome and phenome. However, the genetic architecture governing the metabolome and thus, the phenome is not well understood. Here, we aim to obtain a deeper insight into the genetic architecture of seed metabolome in buckwheat by integrating high throughput metabolomics and genotyping-by-sequencing applying an array of bioinformatics tools for data analysis. RESULTS: High throughput metabolomic analysis identified 24 metabolites in seed endosperm of 130 diverse buckwheat genotypes. The genotyping-by-sequencing (GBS) of these genotypes revealed 3,728,028 SNPs. The Genome Association and Prediction Integrated Tool (GAPIT) assisted in the identification of 27 SNPs/QTLs linked to 18 metabolites. Candidate genes were identified near 100 Kb of QTLs, providing insights into several metabolic and biosynthetic pathways. CONCLUSIONS: We established the metabolome inventory of 130 germplasm lines of buckwheat, identified QTLs through marker trait association and positions of potential candidate genes. This will pave the way for future dissection of complex economic traits in buckwheat.