Genebank genomics highlights the diversity of a global barley collection

Harnessing Novel Diversity From Landraces to Improve an Elite Barley Variety

The Spanish Barley Core Collection (SBCC) is a source of genetic variability of potential interest for breeding, particularly for adaptation to Mediterranean environments. Two backcross populations (BC2F5) were developed using the elite cultivar Cierzo as the recurrent parent. The donor parents, namely SBCC042 and SBCC073, were selected from the SBCC lines due to their outstanding yield in drought environments. Flowering time, yield and drought-related traits were evaluated in two field trials in Zaragoza (Spain) during the 2014-15 and 2015-16 seasons and validated in the 2017-18 season. Two hundred sixty-four lines of each population were genotyped with the Barley Illumina iSelect 50k SNP chip. Genetic maps for each population were generated. The map for SBCC042 × Cierzo contains 12,893 SNPs distributed in 9 linkage groups. The map for SBCC073 × Cierzo includes 12,026 SNPs in 7 linkage groups. Both populations shared two QTL hotspots. There are QTLs for flowering time, thousand-kernel weight (TKW), and hectoliter weight on a segment of 23 Mb at ~515 Mb on chromosome 1H, which encompasses the HvFT3 gene. In both populations, flowering was accelerated by the landrace allele, which also increased the TKW. In the same region, better soil coverage was contributed by SBCC042 but coincident with a lower hectoliter weight. The second large hotspot was on chromosome 6H and contained QTLs with wide intervals for grain yield, plant height and TKW. Landrace alleles contributed to increased plant height and TKW and reduced grain yield. Only SBCC042 contributed favorable alleles for "green area," with three significant QTLs that increased ground coverage after winter, which might be exploited as an adaptive trait of this landrace. Some genes of interest found in or very close to the peaks of the QTLs are highlighted. Strategies to deploy the QTLs found for breeding and pre-breeding are proposed.

Prospects of pan-genomics in barley

The concept of a pan-genome refers to intraspecific diversity in genome content and structure, encompassing both genes and intergenic space. Pan-genomic studies employ a combination of de novo sequence assembly and reference-based alignment to discover and genotype structural variants. The large size and complex structure of Triticeae genomes were for a long time an obstacle for genomic research in barley and its relatives. Now that a reference genome is available, computational pipelines for high-quality sequence assembly are in place, and sequence costs continue to drop, investigations into the structural diversity of the barley genome seem within reach. Here, we review the recent progress on pan-genomics in the model grass Brachypodium distachyon, and the cereal crops rice and maize, and devise a multi-tiered strategy for a pan-genome project in barley. Our design involves: (1) the construction of high-quality de novo sequence assemblies for a small core set of representative genotypes, (2) short-read sequencing of a large diversity panel of genebank accessions to medium coverage and (3) the use of complementary methods such as chromosome-conformation capture sequencing and k-mer-based association genetics. The in silico representation of the barley pan-genome may inform about the mechanisms of structural genome evolution in the Triticeae and supplement quantitative genetics models of crop performance for better accuracy and predictive ability.

High Resolution Genetic and Physical Mapping of a Major Powdery Mildew Resistance Locus in Barley

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.

A Comparison of Mainstream Genotyping Platforms for the Evaluation and Use of Barley Genetic Resources

We compared the performance of two commonly used genotyping platforms, genotyping-by-sequencing (GBS) and single nucleotide polymorphism-arrays (SNP), to investigate the extent and pattern of genetic variation within a collection of 1,000 diverse barley genotypes selected from the German Federal ex situ GenBank hosted at IPK Gatersleben. Each platform revealed equivalent numbers of robust bi-allelic SNPs (39,733 and 37,930 SNPs for the 50K SNP-array and GBS datasets respectively). A small overlap of 464 SNPs was common to both platforms, indicating that the methodologies we used selectively access informative polymorphism in different portions of the barley genome. Approximately half of the GBS dataset was comprised of SNPs with minor allele frequencies (MAFs) below 1%, illustrating the power of GBS to detect rare alleles in diverse germplasm collections. While desired for certain applications, the highly robust calling of alleles at the same SNPs across multiple populations is an advantage of the SNP-array, allowing direct comparisons of data from related or unrelated studies. Overall MAFs and diversity statistics (π) were higher for the SNP-array data, potentially reflecting the conscious removal of markers with a low MAF in the ascertainment population. A comparison of similarity matrices revealed a positive correlation between both approaches, supporting the validity of using either for entire GenBank characterization. To explore the potential of each dataset for focused genetic analyses we explored the outcomes of their use in genome-wide association scans for row type, growth habit and non-adhering hull, and discriminant analysis of principal components for the drivers of sub-population differentiation. Interpretation of the results from both types of analysis yielded broadly similar conclusions indicating that choice of platform used for such analyses should be determined by the research question being asked, group preferences and their capabilities to extract and interpret the different types of output data easily and quickly. Access to the requisite infrastructure for running, processing, analyzing, querying, storing, and displaying either datatype is an additional consideration. Our investigations reveal that for barley the cost per genotyping assay is less for SNP-arrays than GBS, which translates to a cost per informative datapoint being significantly lower for the SNP-array.

Detecting Large Chromosomal Modifications Using Short Read Data From Genotyping-by-Sequencing

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.

Precision Phenotyping Reveals Novel Loci for Quantitative Resistance to Septoria Tritici Blotch

Accurate, high-throughput phenotyping for quantitative traits is a limiting factor for progress in plant breeding. We developed an automated image analysis to measure quantitative resistance to septoria tritici blotch (STB), a globally important wheat disease, enabling identification of small chromosome intervals containing plausible candidate genes for STB resistance. 335 winter wheat cultivars were included in a replicated field experiment that experienced natural epidemic development by a highly diverse but fungicide-resistant pathogen population. More than 5.4 million automatically generated phenotypes were associated with 13,648 SNP markers to perform the GWAS. We identified 26 chromosome intervals explaining 1.9-10.6% of the variance associated with four independent resistance traits. Sixteen of the intervals overlapped with known STB resistance intervals, suggesting that our phenotyping approach can identify simultaneously (i.e., in a single experiment) many previously defined STB resistance intervals. Seventeen of the intervals were less than 5 Mbp in size and encoded only 173 genes, including many genes associated with disease resistance. Five intervals contained four or fewer genes, providing high priority targets for functional validation. Ten chromosome intervals were not previously associated with STB resistance, perhaps representing resistance to pathogen strains that had not been tested in earlier experiments. The SNP markers associated with these chromosome intervals can be used to recombine different forms of quantitative STB resistance that are likely to be more durable than pyramids of major resistance genes. Our experiment illustrates how high-throughput automated phenotyping can accelerate breeding for quantitative disease resistance.

Unbalanced historical phenotypic data from seed regeneration of a barley ex situ collection

The scarce knowledge on phenotypic characterization restricts the usage of genetic diversity of plant genetic resources in research and breeding. We describe original and ready-to-use processed data for approximately 60% of ~22,000 barley accessions hosted at the Federal ex situ Genebank for Agricultural and Horticultural Plant Species. The dataset gathers records for three traits with agronomic relevance: flowering time, plant height and thousand grain weight. This information was collected for seven decades for winter and spring barley during the seed regeneration routine. The curated data represent a source for research on genetics and genomics of adaptive and yield related traits in cereals due to the importance of barley as model organism. This data could be used to predict the performance of non-phenotyped individuals in other collections through genomic prediction. Moreover, the dataset empowers the utilization of phenotypic diversity of genetic resources for crop improvement.