Major chromosome rearrangements in intergeneric wheat × rye hybrids in compatible and incompatible crosses detected by GBS read coverage analysis.

The presence of incompatibility alleles in primary amphidiploids constitutes a reproductive barrier in newly synthesized wheat-rye hybrids. To overcome this barrier, the genome stabilization process includes large-scale chromosome rearrangements. In incompatible crosses resulting in fertile amphidiploids, the elimination of one of the incompatible alleles Eml-A1 or Eml-R1b can occur already in the somatic tissue of the wheat × rye hybrid embryo. We observed that the interaction of incompatible loci Eml-A1 of wheat and Eml-R1b of rye after overcoming embryo lethality leads to hybrid sterility in primary triticale. During subsequent seed reproductions (R1, R2 or R3) most of the chromosomes of A, B, D and R subgenomes undergo rearrangement or eliminations to increase the fertility of the amphidiploid by natural selection. Genotyping-by-sequencing (GBS) coverage analysis showed that improved fertility is associated with the elimination of entire and partial chromosomes carrying factors that either cause the disruption of plant development in hybrid plants or lead to the restoration of the euploid number of chromosomes (2n = 56) in the absence of one of the incompatible alleles. Highly fertile offspring obtained in compatible and incompatible crosses can be successfully adapted for the production of triticale pre-breeding stocks.

Genomic predictions to leverage phenotypic data across genebanks.

Genome-wide prediction is a powerful tool in breeding. Initial results suggest that genome-wide approaches are also promising for enhancing the use of the genebank material: predicting the performance of plant genetic resources can unlock their hidden potential and fill the information gap in genebanks across the world and, hence, underpin prebreeding programs. As a proof of concept, we evaluated the power of across-genebank prediction for extensive germplasm collections relying on historical data on flowering/heading date, plant height, and thousand kernel weight of 9,344 barley (Hordeum vulgare L.) plant genetic resources from the German Federal Ex situ Genebank for Agricultural and Horticultural Crops (IPK) and of 1,089 accessions from the International Center for Agriculture Research in the Dry Areas (ICARDA) genebank. Based on prediction abilities for each trait, three scenarios for predictive characterization were compared: 1) a benchmark scenario, where test and training sets only contain ICARDA accessions, 2) across-genebank predictions using IPK as training and ICARDA as test set, and 3) integrated genebank predictions that include IPK with 30% of ICARDA accessions as a training set to predict the rest of ICARDA accessions. Within the population of ICARDA accessions, prediction abilities were low to moderate, which was presumably caused by a limited number of accessions used to train the model. Interestingly, ICARDA prediction abilities were boosted up to ninefold by using training sets composed of IPK plus 30% of ICARDA accessions. Pervasive genotype × environment interactions (GEIs) can become a potential obstacle to train robust genome-wide prediction models across genebanks. This suggests that the potential adverse effect of GEI on prediction ability was counterbalanced by the augmented training set with certain connectivity to the test set. Therefore, across-genebank predictions hold the promise to improve the curation of the world's genebank collections and contribute significantly to the long-term development of traditional genebanks toward biodigital resource centers.

Combining focused identification of germplasm and core collection strategies to identify genebank accessions for central European soybean breeding.

Environmental adaptation of crops is essential for reliable agricultural production and an important breeding objective. Genebanks provide genetic variation for the improvement of modern varieties, but the selection of suitable germplasm is frequently impeded by incomplete phenotypic data. We address this bottleneck by combining a Focused Identification of Germplasm Strategy (FIGS) with core collection methodology to select soybean (Glycine max) germplasm for Central European breeding from a collection of >17,000 accessions. By focussing on adaptation to high-latitude cold regions, we selected an "environmental precore" of 3,663 accessions using environmental data and compared the Donor opulation of Environments (DPE) in Asia and the Target Population of Environments (TPE) in Central Europe in the present and 2070. Using single nucleotide polymorphisms, we reduced the precore into two diverse core collections of 183 and 366 accessions to serve as diversity panels for evaluation in the TPE. Genetic differentiation between precore and non-precore accessions revealed genomic regions that control maturity, and novel candidate loci for environmental adaptation, demonstrating the potential of diversity panels for studying adaptation. Objective-driven core collections have the potential to increase germplasm utilization for abiotic adaptation by breeding for a rapidly changing climate, or de novo adaptation of crops to expand cultivation ranges.