Background Sesame (Sesamum indicum L.) is one of the oldest oilseed crops. Its seeds accumulate lignans and antioxidants that determine their nutritional value. Global demand for sesame is rising rapidly, but climate change increasingly threatens sesame yields and seed quality. Here, we analyzed a worldwide panel of 300 sesame accessions to explore the genetic basis of key adaptive and quality traits, specifically flowering time, seed lignan content, and seed antioxidant capacity. Results Whole-genome resequencing revealed previously unreported genetic diversity, expanding the resources available for sesame breeding. By integrating k-mer-based genome-wide association analysis with a graph-based sesame genome, we identified structural variants associated with differences in flowering time and lignan accumulation. A 9.4-kb deletion on chromosome 6 that disrupted SIN_1018434 (an ortholog of Arabidopsis PHOTOPERIOD-INDEPENDENT EARLY FLOWERING 1) and a 6.2-kb Copia-type retrotransposon insertion upstream of SIN_1004470 on chromosome 11 were associated with early flowering. The intact alleles at both loci were associated with delayed flowering and were predominant in low-latitude accessions. High seed lignan content was associated with non-synonymous mutations and copy number variants in glycosyl hydrolase genes on chromosome 6 and an 8.2-kb deletion spanning SIN_1019378 on chromosome 13. Association signals for seed antioxidant traits coincided with loci involved in abiotic stress responses and seed-coat pigmentation. Conclusions These findings highlight the importance of exploring diverse germplasm to uncover previously unrecognized adaptive and quality-associated genomic variation. The loci identified here provide molecular targets for developing climate-adapted cultivars with improved seed quality.
Sookyeong Lee, S. Lee, J. Ahn et al.· bioRxiv· 0 citations
Faba bean is a globally adapted legume protein crop with a high yield potential. Currently, yield variation across environments limits more widespread cultivation, and the underlying genetics remain poorly understood. Here, we identify major QTL for faba bean yield and yield stability. We genotype the ProFaba diversity panel with high resolution and carry out coordinated multi-year/location trials across Europe. Based on these data, we identify more than one hundred loci associated with mean performance and stability for 14 complex traits, including yield. Experimental validation supports the involvement of the candidate gene Vfaba.Hedin2.R2.1g002122 in plant architecture, with gene expression significantly associated with first pod position and plant height. Furthermore, we introduce a method for integrating environmental data in the analysis of trait stability based on a random regression mixed model, which enables prediction of performance in untested environments. Our study provides insights into the genetic architecture of yield, yield stability, and genotype-by-environment interaction in faba bean. The genomic resources, candidate loci, and weather-informed analytical framework provide practical tools for predicting performance across environments and accelerating breeding of resilient, high-yielding protein crops.
Elesandro Bornhofen, Troels W. Mouritzen, Sheila Alves et al.· Genome Biology· 0 citations
Faba bean breeding and genomics have seen steady progress in recent years, supported by genome sequences and high-density genotyping platforms. These tools have been valuable for trait mapping, diversity assessment, and genomic research, but they have limited routine use in breeding programs due to their relatively high cost. Recent progress in establishing an optimized, cost-efficient genotyping-by-sequencing protocol tailored to the large and complex faba bean genome has created the foundation for a more accessible genotyping solution.
Using this approach, we explored the genetic diversity of faba bean germplasm from various panels, providing a comprehensive representation of the crop’s genetic landscape. From this dataset, we identified and selected a high-quality set of informative SNP markers that are evenly distributed across the genome. Building on these resources, we designed a breeder-friendly 10K SNP chip.
The 10K SNP chip delivers high accuracy, broad genomic coverage, and affordability. The chip was validated across diverse germplasm panels, demonstrating strong clustering performance, high reproducibility, and applicability to breeding-relevant germplasm.
This platform offers a cost-effective alternative to higher-density arrays, enabling its integration into genomic selection, marker-assisted breeding, and diversity monitoring, ultimately supporting accelerated genetic gain and the delivery of improved varieties to farmers.
Hyeonah Shim, Hailin Zhang, Thomas Groß et al.· Frontiers in Plant Science· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
