Interaction between Cauliflower Mosaic Virus Inclusion Body Protein and Capsid Protein: Implications for Viral Assembly

AbstractThe cauliflower mosaic virus (CaMV) inclusion body protein (pVI) is able to specifically interact with the viral capsid precursor protein (pIV). By using the yeast two-hybrid system and a blot assay, the pIV region required for the recognition of pVI was mapped to the lysine-rich domain. This region of only 48 amino acids when fused to dihydrofolate reductase (DHFR) mediated pVI and DNA bindingin vitro.Competition experiments confirmed that pVI and DNA bind to the same region of pIV. Since pVI is absent from the mature virus, models are discussed in which pVI plays an accessory role in CaMV assembly, in addition to its function in transactivating translation

BARLEX – the Barley Draft Genome Explorer

Colmsee C, Beier S, Himmelbach A, et al. BARLEX – the Barley Draft Genome Explorer. Molecular Plant. 2015;8(6):964-966

Allele Mining in Barley Genetic Resources Reveals Genes of Race-Non-Specific Powdery Mildew Resistance

Race-non-specific, or quantitative, pathogen resistance is of high importance to plant breeders due to its expected durability. However, it is usually controlled by multiple quantitative trait loci (QTL) and therefore difficult to handle in practice. Knowing the genes that underlie race-non-specific resistance (NR) would allow its exploitation in a more targeted manner. Here, we performed an association-genetic study in a customized worldwide collection of spring barley accessions for candidate genes of race-NR to the powdery mildew fungus Blumeria graminis f. sp. hordei (Bgh) and combined data with results from QTL mapping as well as functional-genomics approaches. This led to the identification of 11 associated genes with converging evidence for an important role in race-NR in the presence of the Mlo gene for basal susceptibility. Outstanding in this respect was the gene encoding the transcription factor WRKY2. The results suggest that unlocking plant genetic resources and integrating functional-genomic with genetic approaches can accelerate the discovery of genes underlying race-NR in barley and other crop plants

A Genome Assembly of the Barley 'Transformation Reference' Cultivar Golden Promise

Barley (Hordeum vulgare) is one of the most important crops worldwide and is also considered a research model for the large-genome small grain temperate cereals. Despite genomic resources improving all the time, they are limited for the cv. Golden Promise, the most efficient genotype for genetic transformation. We have developed a barley cv. Golden Promise reference assembly integrating Illumina paired-end reads, long mate-pair reads, Dovetail Chicago in vitro proximity ligation libraries and chromosome conformation capture sequencing (Hi-C) libraries into a contiguous reference assembly. The assembled genome of 7 chromosomes and 4.13Gb in size, has a super-scaffold N50 after Chicago libraries of 4.14Mb and contains only 2.2% gaps. Using BUSCO (benchmarking universal single copy orthologous genes) as evaluation the genome assembly contains 95.2% of complete and single copy genes from the plant database. A high-quality Golden Promise reference assembly will be useful and utilized by the whole barley research community but will prove particularly useful for CRISPR-Cas9 experiments

Genomic resources for a historical collection of cultivated two-row European spring barley genotypes

Barley genomic resources are increasing rapidly, with the publication of a barley pangenome as one of the latest developments. Two-row spring barley cultivars are intensely studied as they are the source of high-quality grain for malting and distilling. Here we provide data from a European two-row spring barley population containing 209 different genotypes registered for the UK market between 1830 to 2014. The dataset encompasses RNA-sequencing data from six different tissues across a range of barley developmental stages, phenotypic datasets from two consecutive years of field-grown trials in the United Kingdom, Germany and the USA; and whole genome shotgun sequencing from all cultivars, which was used to complement the RNA-sequencing data for variant calling. The outcomes are a filtered SNP marker file, a phenotypic database and a large gene expression dataset providing a comprehensive resource which allows for downstream analyses like genome wide association studies or expression associations.</p

A homolog of <i>blade-on-petiole</i> <i>1</i> and <i>2</i> (<i>BOP1/2</i>) controls internode length and homeotic changes of the barley inflorescence

Inflorescence architecture in small-grain cereals has a direct effect on yield and is an important selection target in breeding for yield improvement. We analyzed the recessive mutation laxatum-a (lax-a) in barley (Hordeum vulgare), which causes pleiotropic changes in spike development, resulting in (1) extended rachis internodes conferring a more relaxed inflorescence, (2) broadened base of the lemma awns, (3) thinner grains that are largely exposed due to reduced marginal growth of the palea and lemma, and (4) and homeotic conversion of lodicules into two stamenoid structures. Map-based cloning enforced by mapping-by-sequencing of the mutant lax-a locus enabled the identification of a homolog of BLADE-ON-PETIOLE1 (BOP1) and BOP2 as the causal gene. Interestingly, the recently identified barley uniculme4 gene also is a BOP1/2 homolog and has been shown to regulate tillering and leaf sheath development. While the Arabidopsis (Arabidopsis thaliana) BOP1 and BOP2 genes act redundantly, the barley genes contribute independent effects in specifying the developmental growth of vegetative and reproductive organs, respectively. Analysis of natural genetic diversity revealed strikingly different haplotype diversity for the two paralogous barley genes, likely affected by the respective genomic environments, since no indication for an active selection process was detected

TRITEX : chromosome-scale sequence assembly of Triticeae genomes with open-source tools

Chromosome-scale genome sequence assemblies underpin pan-genomic studies. Recent genome assembly efforts in the large-genome Triticeae crops wheat and barley have relied on the commercial closed-source assembly algorithm DeNovoMagic. We present TRITEX, an open-source computational workflow that combines paired-end, mate-pair, 10X Genomics linked-read with chromosome conformation capture sequencing data to construct sequence scaffolds with megabase-scale contiguity ordered into chromosomal pseudomolecules. We evaluate the performance of TRITEX on publicly available sequence data of tetraploid wild emmer and hexaploid bread wheat, and construct an improved annotated reference genome sequence assembly of the barley cultivar Morex as a community resource.Peer reviewe

Anchoring and ordering NGS contig assemblies by population sequencing (POPSEQ)

Peer reviewe

Exome sequencing of geographically diverse barley landraces and wild relatives gives insights into environmental adaptation

After domestication, during a process of widespread range extension, barley adapted to a broad spectrum of agricultural environments. To explore how the barley genome responded to the environmental challenges it encountered, we sequenced the exomes of a collection of 267 georeferenced landraces and wild accessions. A combination of genome-wide analyses showed that patterns of variation have been strongly shaped by geography and that variant-by-environment associations for individual genes are prominent in our data set. We observed significant correlations of days to heading (flowering) and height with seasonal temperature and dryness variables in common garden experiments, suggesting that these traits were major drivers of environmental adaptation in the sampled germplasm. A detailed analysis of known flowering-associated genes showed that many contain extensive sequence variation and that patterns of single- and multiple-gene haplotypes exhibit strong geographical structuring. This variation appears to have substantially contributed to range-wide ecogeographical adaptation, but many factors key to regional success remain unidentified.</p

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