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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.

The use of wild plant species or their halophytic relatives has been considered in plant breeding programs to improve salt and drought tolerance in crop plants. Aeluropus littoralis serves as halophyte model for identification and isolation of novel stress adaptation genes. A. littoralis, a perennial monocot grass, grows in damp or arid areas, often salt-impregnated places and wasteland in cultivated areas, can survive periodically high water salinity, and tolerate high salt concentrations in the soil up to 1,100 mM sodium chloride. Therefore, it serves as valuable genetic resource to understand molecular mechanisms of stress-responses in monocots. The knowledge can potentially be used for improving tolerance to abiotic stresses in economically important crops. Several morphological, anatomical, ecological, and physiological traits of A. littoralis have been investigated so far. After watering with salt water the grass is able to excrete salt via its salt glands. Meanwhile, a number of ESTs (expressed sequence tag), genes and promoters induced by the salt and drought stresses were isolated, sequenced and annotated at a molecular level. Transfer of stress related genes to other species resulted in enhanced stress resistance. Here we describe the genome sequence and structure of A. littoralis analyzed by whole genome sequencing and histological analysis. The chromosome number was determined to be 20 (2n = 2x = 20). The genome size was calculated to be 354 Mb. This genomic information provided here, will support the functional investigation and application of novel genes improving salt stress resistance in crop plants. The utility of the sequence information is exemplified by the analysis of the DREB-transcription factor family.

Markers linked to agronomic traits are of the prerequisite for molecular breeding. Genotyping-by-sequencing (GBS) data enables to detect small polymorphisms including single nucleotide polymorphisms (SNPs) and short insertions or deletions (InDels) that can be used, for instance, for marker-assisted selection, population genetics, and genome-wide association studies (GWAS). Here, we aim at detecting large chromosomal modifications in barley and wheat based on GBS data. These modifications could be duplications, deletions, substitutions including introgressions as well as alterations of DNA methylation. We demonstrate that GBS coverage analysis is capable to detect Hordeum vulgare/Hordeum bulbosum introgression lines. Furthermore, we identify large chromosomal modifications in barley and wheat collections. Hence, large chromosomal modifications, including introgressions and copy number variations (CNV), can be detected easily and can be used as markers in research and breeding without additional wet-lab experiments.

Powdery mildew caused by Blumeria graminis f. sp. hordei is a foliar disease with highly negative impact on yield and grain quality in barley. Thus, breeding for powdery mildew resistance is an important goal and requires constantly the discovery of new sources of natural resistance. Here, we report the high resolution genetic and physical mapping of a dominant race-specific powdery mildew resistance locus, originating from an Ethiopian spring barley accession ‘HOR2573,’ conferring resistance to several modern mildew isolates. High-resolution genetic mapping narrowed down the interval containing the resistance locus to a physical span of 850 kb. Four candidate genes with homology to known disease resistance gene families were identified. The mapped resistance locus coincides with a previously reported resistance locus from Hordeum laevigatum, suggesting allelism at the same locus in two different barley lines. Therefore, we named the newly mapped resistance locus from HOR2573 as MlLa-H. The reported co-segregating and flanking markers may provide new tools for marker-assisted selection of this resistance locus in barley breeding.

Meiotic recombination is a fundamental mechanism to generate novel allelic combinations which can be harnessed by breeders to achieve crop improvement. The recombination landscape of many crop species, including the major crop barley, is characterized by a dearth of recombination in 65% of the genome. In addition, segregation distortion caused by selection on genetically linked loci is a frequent and undesirable phenomenon in double haploid populations which hampers genetic mapping and breeding. Here, we present an approach to directly investigate recombination at the DNA sequence level by combining flow-sorting of haploid pollen nuclei of barley with single-cell genome sequencing. We confirm the skewed distribution of recombination events toward distal chromosomal regions at megabase resolution and show that segregation distortion is almost absent if directly measured in pollen. Furthermore, we show a bimodal distribution of inter-crossover distances, which supports the existence of two classes of crossovers which are sensitive or less sensitive to physical interference. We conclude that single pollen nuclei sequencing is an approach capable of revealing recombination patterns in the absence of segregation distortion.