An online database for einkorn wheat to aid in gene discovery and functional genomics studies.

Diploid A-genome wheat (einkorn wheat) presents a nutrition-rich option as an ancient grain crop and a resource for the improvement of bread wheat against abiotic and biotic stresses. Realizing the importance of this wheat species, reference-level assemblies of two einkorn wheat accessions were generated (wild and domesticated). This work reports an einkorn genome database that provides an interface to the cereals research community to perform comparative genomics, applied genetics and breeding research. It features queries for annotated genes, the use of a recent genome browser release, and the ability to search for sequence alignments using a modern BLAST interface. Other features include a comparison of reference einkorn assemblies with other wheat cultivars through genomic synteny visualization and an alignment visualization tool for BLAST results. Altogether, this resource will help wheat research and breeding. Database URL  https://wheat.pw.usda.gov/GG3/pangenome.

Einkorn genomics sheds light on history of the oldest domesticated wheat.

Einkorn (Triticum monococcum) was the first domesticated wheat species, and was central to the birth of agriculture and the Neolithic Revolution in the Fertile Crescent around 10,000 years ago1,2. Here we generate and analyse 5.2-Gb genome assemblies for wild and domesticated einkorn, including completely assembled centromeres. Einkorn centromeres are highly dynamic, showing evidence of ancient and recent centromere shifts caused by structural rearrangements. Whole-genome sequencing analysis of a diversity panel uncovered the population structure and evolutionary history of einkorn, revealing complex patterns of hybridizations and introgressions after the dispersal of domesticated einkorn from the Fertile Crescent. We also show that around 1% of the modern bread wheat (Triticum aestivum) A subgenome originates from einkorn. These resources and findings highlight the history of einkorn evolution and provide a basis to accelerate the genomics-assisted improvement of einkorn and bread wheat.

Pathogen-induced biosynthetic pathways encode defense-related molecules in bread wheat.

Wheat is a widely grown food crop that suffers major yield losses due to attack by pests and pathogens. A better understanding of biotic stress responses in wheat is thus of major importance. The recently assembled bread wheat genome coupled with extensive transcriptomic resources provides unprecedented new opportunities to investigate responses to pathogen challenge. Here, we analyze gene coexpression networks to identify modules showing consistent induction in response to pathogen exposure. Within the top pathogen-induced modules, we identify multiple clusters of physically adjacent genes that correspond to six pathogen-induced biosynthetic pathways that share a common regulatory network. Functional analysis reveals that these pathways, all of which are encoded by biosynthetic gene clusters, produce various different classes of compounds­namely, flavonoids, diterpenes, and triterpenes, including the defense-related compound ellarinacin. Through comparative genomics, we also identify associations with the known rice phytoalexins momilactones, as well as with a defense-related gene cluster in the grass model plant Brachypodium distachyon. Our results significantly advance the understanding of chemical defenses in wheat and open up avenues for enhancing disease resistance in this agriculturally important crop. They also exemplify the power of transcriptional networks to discover the biosynthesis of chemical defenses in plants with large, complex genomes.

Rust expression browser: an open source database for simultaneous analysis of host and pathogen gene expression profiles with expVIP.

BACKGROUND: Transcriptomics is being increasingly applied to generate new insight into the interactions between plants and their pathogens. For the wheat yellow (stripe) rust pathogen (Puccinia striiformis f. sp. tritici, Pst) RNA-based sequencing (RNA-Seq) has proved particularly valuable, overcoming the barriers associated with its obligate biotrophic nature. This includes the application of RNA-Seq approaches to study Pst and wheat gene expression dynamics over time and the Pst population composition through the use of a novel RNA-Seq based surveillance approach called "field pathogenomics". As a dual RNA-Seq approach, the field pathogenomics technique also provides gene expression data from the host, giving new insight into host responses. However, this has created a wealth of data for interrogation. RESULTS: Here, we used the field pathogenomics approach to generate 538 new RNA-Seq datasets from Pst-infected field wheat samples, doubling the amount of transcriptomics data available for this important pathosystem. We then analysed these datasets alongside 66 RNA-Seq datasets from four Pst infection time-courses and 420 Pst-infected plant field and laboratory samples that were publicly available. A database of gene expression values for Pst and wheat was generated for each of these 1024 RNA-Seq datasets and incorporated into the development of the rust expression browser ( http://www.rust-expression.com ). This enables for the first time simultaneous 'point-and-click' access to gene expression profiles for Pst and its wheat host and represents the largest database of processed RNA-Seq datasets available for any of the three Puccinia wheat rust pathogens. We also demonstrated the utility of the browser through investigation of expression of putative Pst virulence genes over time and examined the host plants response to Pst infection. CONCLUSIONS: The rust expression browser offers immense value to the wider community, facilitating data sharing and transparency and the underlying database can be continually expanded as more datasets become publicly available.

A haplotype-led approach to increase the precision of wheat breeding.

Crop productivity must increase at unprecedented rates to meet the needs of the growing worldwide population. Exploiting natural variation for the genetic improvement of crops plays a central role in increasing productivity. Although current genomic technologies can be used for high-throughput identification of genetic variation, methods for efficiently exploiting this genetic potential in a targeted, systematic manner are lacking. Here, we developed a haplotype-based approach to identify genetic diversity for crop improvement using genome assemblies from 15 bread wheat (Triticum aestivum) cultivars. We used stringent criteria to identify identical-by-state haplotypes and distinguish these from near-identical sequences (~99.95% identity). We showed that each cultivar shares ~59 % of its genome with other sequenced cultivars and we detected the presence of extended haplotype blocks containing hundreds to thousands of genes across all wheat chromosomes. We found that genic sequence alone was insufficient to fully differentiate between haplotypes, as were commonly used array-based genotyping chips due to their gene centric design. We successfully used this approach for focused discovery of novel haplotypes from a landrace collection and documented their potential for trait improvement in modern bread wheat. This study provides a framework for defining and exploiting haplotypes to increase the efficiency and precision of wheat breeding towards optimising the agronomic performance of this crucial crop.

Multiple wheat genomes reveal global variation in modern breeding.

Advances in genomics have expedited the improvement of several agriculturally important crops but similar efforts in wheat (Triticum spp.) have been more challenging. This is largely owing to the size and complexity of the wheat genome1, and the lack of genome-assembly data for multiple wheat lines2,3. Here we generated ten chromosome pseudomolecule and five scaffold assemblies of hexaploid wheat to explore the genomic diversity among wheat lines from global breeding programs. Comparative analysis revealed extensive structural rearrangements, introgressions from wild relatives and differences in gene content resulting from complex breeding histories aimed at improving adaptation to diverse environments, grain yield and quality, and resistance to stresses4,5. We provide examples outlining the utility of these genomes, including a detailed multi-genome-derived nucleotide-binding leucine-rich repeat protein repertoire involved in disease resistance and the characterization of Sm16, a gene associated with insect resistance. These genome assemblies will provide a basis for functional gene discovery and breeding to deliver the next generation of modern wheat cultivars.

Optimizing Rhizobium-legume symbioses by simultaneous measurement of rhizobial competitiveness and N2 fixation in nodules.

Legumes tend to be nodulated by competitive rhizobia that do not maximize nitrogen (N2) fixation, resulting in suboptimal yields. Rhizobial nodulation competitiveness and effectiveness at N2 fixation are independent traits, making their measurement extremely time-consuming with low experimental throughput. To transform the experimental assessment of rhizobial competitiveness and effectiveness, we have used synthetic biology to develop reporter plasmids that allow simultaneous high-throughput measurement of N2 fixation in individual nodules using green fluorescent protein (GFP) and barcode strain identification (Plasmid ID) through next generation sequencing (NGS). In a proof-of-concept experiment using this technology in an agricultural soil, we simultaneously monitored 84 different Rhizobium leguminosarum strains, identifying a supercompetitive and highly effective rhizobial symbiont for peas. We also observed a remarkable frequency of nodule coinfection by rhizobia, with mixed occupancy identified in ∼20% of nodules, containing up to six different strains. Critically, this process can be adapted to multiple Rhizobium-legume symbioses, soil types, and environmental conditions to permit easy identification of optimal rhizobial inoculants for field testing to maximize agricultural yield.

A roadmap for gene functional characterisation in crops with large genomes: Lessons from polyploid wheat.

Understanding the function of genes within staple crops will accelerate crop improvement by allowing targeted breeding approaches. Despite their importance, a lack of genomic information and resources has hindered the functional characterisation of genes in major crops. The recent release of high-quality reference sequences for these crops underpins a suite of genetic and genomic resources that support basic research and breeding. For wheat, these include gene model annotations, expression atlases and gene networks that provide information about putative function. Sequenced mutant populations, improved transformation protocols and structured natural populations provide rapid methods to study gene function directly. We highlight a case study exemplifying how to integrate these resources. This review provides a helpful guide for plant scientists, especially those expanding into crop research, to capitalise on the discoveries made in Arabidopsis and other plants. This will accelerate the improvement of crops of vital importance for food and nutrition security.

The NLR-Annotator Tool Enables Annotation of the Intracellular Immune Receptor Repertoire.

Disease resistance genes encoding nucleotide-binding and leucine-rich repeat (NLR) intracellular immune receptor proteins detect pathogens by the presence of pathogen effectors. Plant genomes typically contain hundreds of NLR-encoding genes. The availability of the hexaploid wheat (Triticum aestivum) cultivar Chinese Spring reference genome allows a detailed study of its NLR complement. However, low NLR expression and high intrafamily sequence homology hinder their accurate annotation. Here, we developed NLR-Annotator, a software tool for in silico NLR identification independent of transcript support. Although developed for wheat, we demonstrate the universal applicability of NLR-Annotator across diverse plant taxa. We applied our tool to wheat and combined it with a transcript-validated subset of genes from the reference gene annotation to characterize the structure, phylogeny, and expression profile of the NLR gene family. We detected 3,400 full-length NLR loci, of which 1,560 were confirmed as expressed genes with intact open reading frames. NLRs with integrated domains mostly group in specific subclades. Members of another subclade predominantly locate in close physical proximity to NLRs carrying integrated domains, suggesting a paired helper function. Most NLRs (88%) display low basal expression (in the lower 10 percentile of transcripts). In young leaves subjected to biotic stress, we found up-regulation of 266 of the NLRs To illustrate the utility of our tool for the positional cloning of resistance genes, we estimated the number of NLR genes within the intervals of mapped rust resistance genes. Our study will support the identification of functional resistance genes in wheat to accelerate the breeding and engineering of disease-resistant varieties.

A Co-Expression Network in Hexaploid Wheat Reveals Mostly Balanced Expression and Lack of Significant Gene Loss of Homeologous Meiotic Genes Upon Polyploidization.

Polyploidization has played an important role in plant evolution. However, upon polyploidization, the process of meiosis must adapt to ensure the proper segregation of increased numbers of chromosomes to produce balanced gametes. It has been suggested that meiotic gene (MG) duplicates return to a single copy following whole genome duplication to stabilize the polyploid genome. Therefore, upon the polyploidization of wheat, a hexaploid species with three related (homeologous) genomes, the stabilization process may have involved rapid changes in content and expression of MGs on homeologous chromosomes (homeologs). To examine this hypothesis, sets of candidate MGs were identified in wheat using co-expression network analysis and orthology informed approaches. In total, 130 RNA-Seq samples from a range of tissues including wheat meiotic anthers were used to define co-expressed modules of genes. Three modules were significantly correlated with meiotic tissue samples but not with other tissue types. These modules were enriched for GO terms related to cell cycle, DNA replication, and chromatin modification and contained orthologs of known MGs. Overall, 74.4% of genes within these meiosis-related modules had three homeologous copies which was similar to other tissue-related modules. Amongst wheat MGs identified by orthology, rather than co-expression, the majority (93.7%) were either retained in hexaploid wheat at the same number of copies (78.4%) or increased in copy number (15.3%) compared to ancestral wheat species. Furthermore, genes within meiosis-related modules showed more balanced expression levels between homeologs than genes in non-meiosis-related modules. Taken together, our results do not support extensive gene loss nor changes in homeolog expression of MGs upon wheat polyploidization. The construction of the MG co-expression network allowed identification of hub genes and provided key targets for future studies.

Global transcriptome analysis uncovers the gene co-expression regulation network and key genes involved in grain development of wheat (Triticum aestivum L.).

Wheat grain development is a robust biological process that largely determines grain quality and yield. In this study, we investigated the grain transcriptome of winter wheat cv. Xiaoyan-6 at four developmental stages (5, 10, 15, and 20 days post-anthesis), using high-throughput RNA sequencing (RNA-Seq). We identified 427 grain-specific transcription factors (TFs) and 1653 differentially expressed TFs during grain development as well as a grain co-expression regulation network (GrainNet) of the TFs and their predicted co-expressed genes. Our study identified ten putative key TFs and the predicted regulatory genes of these TFs in wheat grain development of Xiaoyan-6. The analysis was given a firm basis through the study of additional wheat tissues, including root, stem, leaf, flag leaf, grain, spikes (from wheat plants at booting or heading stages) to provide a dataset of 92,478 high-confidence protein-coding genes that were mostly evenly distributed among subgenomes, but unevenly distributed across each of the chromosomes or each of the seven homeologous groups. Within this larger framework of the transcriptomes, we identified 4659 grain-specific genes (SEGs) and 26,500 differentially expressed genes (DEGs) throughout grain development stages tested. The SEGs identified mainly associate with regulation and signaling-related biological processes, while the DEGs mainly involve in cellular component organization or biogenesis and nutrient reservoir activity during grain development of Xiaoyan-6. This study establishes new targets for modifying genes related to grain development and yield, to fine-tune expression in different varieties and environments.

BrAPI-an application programming interface for plant breeding applications.

MOTIVATION: Modern genomic breeding methods rely heavily on very large amounts of phenotyping and genotyping data, presenting new challenges in effective data management and integration. Recently, the size and complexity of datasets have increased significantly, with the result that data are often stored on multiple systems. As analyses of interest increasingly require aggregation of datasets from diverse sources, data exchange between disparate systems becomes a challenge. RESULTS: To facilitate interoperability among breeding applications, we present the public plant Breeding Application Programming Interface (BrAPI). BrAPI is a standardized web service API specification. The development of BrAPI is a collaborative, community-based initiative involving a growing global community of over a hundred participants representing several dozen institutions and companies. Development of such a standard is recognized as critical to a number of important large breeding system initiatives as a foundational technology. The focus of the first version of the API is on providing services for connecting systems and retrieving basic breeding data including germplasm, study, observation, and marker data. A number of BrAPI-enabled applications, termed BrAPPs, have been written, that take advantage of the emerging support of BrAPI by many databases. AVAILABILITY AND IMPLEMENTATION: More information on BrAPI, including links to the specification, test suites, BrAPPs, and sample implementations is available at https://brapi.org/. The BrAPI specification and the developer tools are provided as free and open source.

Hotspots in the genomic architecture of field drought responses in wheat as breeding targets.

Wheat can adapt to most agricultural conditions across temperate regions. This success is the result of phenotypic plasticity conferred by a large and complex genome composed of three homoeologous genomes (A, B, and D). Although drought is a major cause of yield and quality loss in wheat, the adaptive mechanisms and gene networks underlying drought responses in the field remain largely unknown. Here, we addressed this by utilizing an interdisciplinary approach involving field water status phenotyping, sampling, and gene expression analyses. Overall, changes at the transcriptional level were reflected in plant spectral traits amenable to field-level physiological measurements, although changes in photosynthesis-related pathways were found likely to be under more complex post-transcriptional control. Examining homoeologous genes with a 1:1:1 relationship across the A, B, and D genomes (triads), we revealed a complex genomic architecture for drought responses under field conditions, involving gene homoeolog specialization, multiple gene clusters, gene families, miRNAs, and transcription factors coordinating these responses. Our results provide a new focus for genomics-assisted breeding of drought-tolerant wheat cultivars.

Genome-Wide Transcription During Early Wheat Meiosis Is Independent of Synapsis, Ploidy Level, and the Ph1 Locus.

Polyploidization is a fundamental process in plant evolution. One of the biggest challenges faced by a new polyploid is meiosis, particularly discriminating between multiple related chromosomes so that only homologous chromosomes synapse and recombine to ensure regular chromosome segregation and balanced gametes. Despite its large genome size, high DNA repetitive content and similarity between homoeologous chromosomes, hexaploid wheat completes meiosis in a shorter period than diploid species with a much smaller genome. Therefore, during wheat meiosis, mechanisms additional to the classical model based on DNA sequence homology, must facilitate more efficient homologous recognition. One such mechanism could involve exploitation of differences in chromosome structure between homologs and homoeologs at the onset of meiosis. In turn, these chromatin changes, can be expected to be linked to transcriptional gene activity. In this study, we present an extensive analysis of a large RNA-seq data derived from six different genotypes: wheat, wheat-rye hybrids and newly synthesized octoploid triticale, both in the presence and absence of the Ph1 locus. Plant material was collected at early prophase, at the transition leptotene-zygotene, when the telomere bouquet is forming and synapsis between homologs is beginning. The six genotypes exhibit different levels of synapsis and chromatin structure at this stage; therefore, recombination and consequently segregation, are also different. Unexpectedly, our study reveals that neither synapsis, whole genome duplication nor the absence of the Ph1 locus are associated with major changes in gene expression levels during early meiotic prophase. Overall wheat transcription at this meiotic stage is therefore highly resilient to such alterations, even in the presence of major chromatin structural changes. Further studies in wheat and other polyploid species will be required to reveal whether these observations are specific to wheat meiosis.

Speed breeding in growth chambers and glasshouses for crop breeding and model plant research.

'Speed breeding' (SB) shortens the breeding cycle and accelerates crop research through rapid generation advancement. SB can be carried out in numerous ways, one of which involves extending the duration of plants' daily exposure to light, combined with early seed harvest, to cycle quickly from seed to seed, thereby reducing the generation times for some long-day (LD) or day-neutral crops. In this protocol, we present glasshouse and growth chamber-based SB approaches with supporting data from experimentation with several crops. We describe the conditions that promote the rapid growth of bread wheat, durum wheat, barley, oat, various Brassica species, chickpea, pea, grass pea, quinoa and Brachypodium distachyon. Points of flexibility within the protocols are highlighted, including how plant density can be increased to efficiently scale up plant numbers for single-seed descent (SSD). In addition, instructions are provided on how to perform SB on a small scale in a benchtop growth cabinet, enabling optimization of parameters at a low cost.

Impact of transposable elements on genome structure and evolution in bread wheat.

BACKGROUND: Transposable elements (TEs) are major components of large plant genomes and main drivers of genome evolution. The most recent assembly of hexaploid bread wheat recovered the highly repetitive TE space in an almost complete chromosomal context and enabled a detailed view into the dynamics of TEs in the A, B, and D subgenomes. RESULTS: The overall TE content is very similar between the A, B, and D subgenomes, although we find no evidence for bursts of TE amplification after the polyploidization events. Despite the near-complete turnover of TEs since the subgenome lineages diverged from a common ancestor, 76% of TE families are still present in similar proportions in each subgenome. Moreover, spacing between syntenic genes is also conserved, even though syntenic TEs have been replaced by new insertions over time, suggesting that distances between genes, but not sequences, are under evolutionary constraints. The TE composition of the immediate gene vicinity differs from the core intergenic regions. We find the same TE families to be enriched or depleted near genes in all three subgenomes. Evaluations at the subfamily level of timed long terminal repeat-retrotransposon insertions highlight the independent evolution of the diploid A, B, and D lineages before polyploidization and cases of concerted proliferation in the AB tetraploid. CONCLUSIONS: Even though the intergenic space is changed by the TE turnover, an unexpected preservation is observed between the A, B, and D subgenomes for features like TE family proportions, gene spacing, and TE enrichment near genes.

An improved assembly and annotation of the allohexaploid wheat genome identifies complete families of agronomic genes and provides genomic evidence for chromosomal translocations.

Advances in genome sequencing and assembly technologies are generating many high-quality genome sequences, but assemblies of large, repeat-rich polyploid genomes, such as that of bread wheat, remain fragmented and incomplete. We have generated a new wheat whole-genome shotgun sequence assembly using a combination of optimized data types and an assembly algorithm designed to deal with large and complex genomes. The new assembly represents >78% of the genome with a scaffold N50 of 88.8 kb that has a high fidelity to the input data. Our new annotation combines strand-specific Illumina RNA-seq and Pacific Biosciences (PacBio) full-length cDNAs to identify 104,091 high-confidence protein-coding genes and 10,156 noncoding RNA genes. We confirmed three known and identified one novel genome rearrangements. Our approach enables the rapid and scalable assembly of wheat genomes, the identification of structural variants, and the definition of complete gene models, all powerful resources for trait analysis and breeding of this key global crop.

Uncovering hidden variation in polyploid wheat.

Comprehensive reverse genetic resources, which have been key to understanding gene function in diploid model organisms, are missing in many polyploid crops. Young polyploid species such as wheat, which was domesticated less than 10,000 y ago, have high levels of sequence identity among subgenomes that mask the effects of recessive alleles. Such redundancy reduces the probability of selection of favorable mutations during natural or human selection, but also allows wheat to tolerate high densities of induced mutations. Here we exploited this property to sequence and catalog more than 10 million mutations in the protein-coding regions of 2,735 mutant lines of tetraploid and hexaploid wheat. We detected, on average, 2,705 and 5,351 mutations per tetraploid and hexaploid line, respectively, which resulted in 35-40 mutations per kb in each population. With these mutation densities, we identified an average of 23-24 missense and truncation alleles per gene, with at least one truncation or deleterious missense mutation in more than 90% of the captured wheat genes per population. This public collection of mutant seed stocks and sequence data enables rapid identification of mutations in the different copies of the wheat genes, which can be combined to uncover previously hidden variation. Polyploidy is a central phenomenon in plant evolution, and many crop species have undergone recent genome duplication events. Therefore, the general strategy and methods developed herein can benefit other polyploid crops.

Genome sequence and genetic diversity of European ash trees.

Ash trees (genus Fraxinus, family Oleaceae) are widespread throughout the Northern Hemisphere, but are being devastated in Europe by the fungus Hymenoscyphus fraxineus, causing ash dieback, and in North America by the herbivorous beetle Agrilus planipennis. Here we sequence the genome of a low-heterozygosity Fraxinus excelsior tree from Gloucestershire, UK, annotating 38,852 protein-coding genes of which 25% appear ash specific when compared with the genomes of ten other plant species. Analyses of paralogous genes suggest a whole-genome duplication shared with olive (Olea europaea, Oleaceae). We also re-sequence 37 F. excelsior trees from Europe, finding evidence for apparent long-term decline in effective population size. Using our reference sequence, we re-analyse association transcriptomic data, yielding improved markers for reduced susceptibility to ash dieback. Surveys of these markers in British populations suggest that reduced susceptibility to ash dieback may be more widespread in Great Britain than in Denmark. We also present evidence that susceptibility of trees to H. fraxineus is associated with their iridoid glycoside levels. This rapid, integrated, multidisciplinary research response to an emerging health threat in a non-model organism opens the way for mitigation of the epidemic.

Host Subtraction, Filtering and Assembly Validations for Novel Viral Discovery Using Next Generation Sequencing Data.

The use of next generation sequencing (NGS) to identify novel viral sequences from eukaryotic tissue samples is challenging. Issues can include the low proportion and copy number of viral reads and the high number of contigs (post-assembly), making subsequent viral analysis difficult. Comparison of assembly algorithms with pre-assembly host-mapping subtraction using a short-read mapping tool, a k-mer frequency based filter and a low complexity filter, has been validated for viral discovery with Illumina data derived from naturally infected liver tissue and simulated data. Assembled contig numbers were significantly reduced (up to 99.97%) by the application of these pre-assembly filtering methods. This approach provides a validated method for maximizing viral contig size as well as reducing the total number of assembled contigs that require down-stream analysis as putative viral nucleic acids.