Genomic Analysis of Spanish Wheat Landraces Reveals Their Huge Potential for Breeding
Abstract Background One of the main goals for the XXI century breeding is the development of crop cultivars that can maintain current yields under unfavorable environments. Landraces that have been grown under varied local conditions include genetic diversity that will be essential to achieve this objective. The Center of Plant Genetic Resources of the Spanish Institute for Agriculture Research (CRF-INIA) holds a wide collection of wheat landraces. These accessions, locally adapted to a really wide diversity of eco-climatic conditions, represent a highly valuable material for breeding. However, their efficient use requires an exhaustive genetic characterization. The overall aim of this study was to assess the diversity and population structure of a selected set of 380 Spanish landraces and 52 reference varieties of bread and durum wheat by high-throughput genotyping. Results DArTseq GBS approach generated 10K SNPs and 40K DArT high-quality markers that were mapped against the currently available bread wheat reference genome. The markers with known location were distributed in all the chromosomes, having a relatively well-balanced genome-wide coverage. The genetic analysis showed that Spanish wheat landraces are clustered in different groups, thus representing genetic pools capable to provide different allelic variation. The subspecies had a major impact on the population structure of durum wheat landraces, identifying three different clusters that corresponded to subsps. durum, turgidum and dicoccon. The population structure of bread wheat landraces was more biased by geographic origin. Conclusions The results showed a wider genetic diversity in landraces when compared to a reference set that included commercial varieties, and a higher divergence between landraces and the reference set in durum wheat than in bread wheat. Some genomic regions with patterns of variation that differ between landraces and reference varieties could be detected, pointing out loci under selection during crop improvement that could help to target breeding efforts. The results obtained from this work will be highly valuable for future GWAS analysis.