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.

Plant disease resistance is often conferred by genes with nucleotide binding site (NBS) and leucine-rich repeat (LRR) or serine/threonine protein kinase (S/TPK) domains. Much less is known about mechanisms of susceptibility, particularly to necrotrophic fungal pathogens. The pathogens that cause the diseases tan spot and Stagonospora nodorum blotch on wheat produce effectors (host-selective toxins) that induce susceptibility in wheat lines harboring corresponding toxin sensitivity genes. The effector ToxA is produced by both pathogens, and sensitivity to ToxA is governed by the Tsn1 gene on wheat chromosome arm 5BL. Here, we report the cloning of Tsn1 , which was found to have disease resistance gene-like features, including S/TPK and NBS-LRR domains. Mutagenesis revealed that all three domains are required for ToxA sensitivity, and hence disease susceptibility. Tsn1 is unique to ToxA-sensitive genotypes, and insensitive genotypes are null. Sequencing and phylogenetic analysis indicated that Tsn1 arose in the B-genome diploid progenitor of polyploid wheat through a gene-fusion event that gave rise to its unique structure. Although Tsn1 is necessary to mediate ToxA recognition, yeast two-hybrid experiments suggested that the Tsn1 protein does not interact directly with ToxA. Tsn1 transcription is tightly regulated by the circadian clock and light, providing further evidence that Tsn1 -ToxA interactions are associated with photosynthesis pathways. This work suggests that these necrotrophic pathogens may thrive by subverting the resistance mechanisms acquired by plants to combat other pathogens.

OBITUARY Heinrich Rohrer, pioneer of scanning tunnelling microscopy, remembered p.30 GENES US Supreme Court patent rulings set a higher bar for innovation p.29 ART Exhibition revels in the power of unconstrained thought p.28 SPACE An elegy for the disappearing dark, banished by science p.26 Feeding the future We must mine the biodiversity in seed banks to help to overcome food shortages, urge Susan McCouch and colleagues. The International Center for Tropical Agriculture in Colombia holds 65,000 crop samples from 141 countries.

Plants have developed effective mechanisms to recognize and respond to infections caused by pathogens. Plant resistance gene analogs (RGAs), as resistance (R) gene candidates, have conserved domains and motifs that play specific roles in pathogens’ resistance. Well-known RGAs are nucleotide binding site leucine rich repeats, receptor like kinases, and receptor like proteins. Others include pentatricopeptide repeats and apoplastic peroxidases. RGAs can be detected using bioinformatics tools based on their conserved structural features. Thousands of RGAs have been identified from sequenced plant genomes. High-density genome-wide RGA genetic maps are useful for designing diagnostic markers and identifying quantitative trait loci (QTL) or markers associated with plant disease resistance. This review focuses on recent advances in structures and mechanisms of RGAs, and their identification from sequenced genomes using bioinformatics tools. Applications in enhancing fine mapping and cloning of plant disease resistance genes are also discussed.

BackgroundResistance gene analogs (RGAs), such as NBS-encoding proteins, receptor-like protein kinases (RLKs) and receptor-like proteins (RLPs), are potential R-genes that contain specific conserved domains and motifs. Thus, RGAs can be predicted based on their conserved structural features using bioinformatics tools. Computer programs have been developed for the identification of individual domains and motifs from the protein sequences of RGAs but none offer a systematic assessment of the different types of RGAs. A user-friendly and efficient pipeline is needed for large-scale genome-wide RGA predictions of the growing number of sequenced plant genomes.ResultsAn integrative pipeline, named RGAugury, was developed to automate RGA prediction. The pipeline first identifies RGA-related protein domains and motifs, namely nucleotide binding site (NB-ARC), leucine rich repeat (LRR), transmembrane (TM), serine/threonine and tyrosine kinase (STTK), lysin motif (LysM), coiled-coil (CC) and Toll/Interleukin-1 receptor (TIR). RGA candidates are identified and classified into four major families based on the presence of combinations of these RGA domains and motifs: NBS-encoding, TM-CC, and membrane associated RLP and RLK. All time-consuming analyses of the pipeline are paralleled to improve performance. The pipeline was evaluated using the well-annotated Arabidopsis genome. A total of 98.5, 85.2, and 100 % of the reported NBS-encoding genes, membrane associated RLPs and RLKs were validated, respectively. The pipeline was also successfully applied to predict RGAs for 50 sequenced plant genomes. A user-friendly web interface was implemented to ease command line operations, facilitate visualization and simplify result management for multiple datasets.ConclusionsRGAugury is an efficiently integrative bioinformatics tool for large scale genome-wide identification of RGAs. It is freely available at Bitbucket: https://bitbucket.org/yaanlpc/rgaugury.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-3197-x) contains supplementary material, which is available to authorized users.

physical euthanasia, and less control over performing euthanasia. Poorer professional quality of life was also seen in personnel working as trainers, at universities, and longer hours. This study contributes important empirical data that may provide guidance for developing interventions (e.g., improved social support, decreased animal stress, increased animal enrichment diversity/frequency, greater control over euthanasia) to improve laboratory animal personnel's professional quality of life.

BackgroundFlax, Linum usitatissimum L., is an important crop whose seed oil and stem fiber have multiple industrial applications. Flax seeds are also well-known for their nutritional attributes, viz., omega-3 fatty acids in the oil and lignans and mucilage from the seed coat. In spite of the importance of this crop, there are few molecular resources that can be utilized toward improving seed traits. Here, we describe flax embryo and seed development and generation of comprehensive genomic resources for the flax seed.ResultsWe describe a large-scale generation and analysis of expressed sequences in various tissues. Collectively, the 13 libraries we have used provide a broad representation of genes active in developing embryos (globular, heart, torpedo, cotyledon and mature stages) seed coats (globular and torpedo stages) and endosperm (pooled globular to torpedo stages) and genes expressed in flowers, etiolated seedlings, leaves, and stem tissue. A total of 261,272 expressed sequence tags (EST) (GenBank accessions LIBEST_026995 to LIBEST_027011) were generated. These EST libraries included transcription factor genes that are typically expressed at low levels, indicating that the depth is adequate for in silico expression analysis. Assembly of the ESTs resulted in 30,640 unigenes and 82% of these could be identified on the basis of homology to known and hypothetical genes from other plants. When compared with fully sequenced plant genomes, the flax unigenes resembled poplar and castor bean more than grape, sorghum, rice or Arabidopsis. Nearly one-fifth of these (5,152) had no homologs in sequences reported for any organism, suggesting that this category represents genes that are likely unique to flax. Digital analyses revealed gene expression dynamics for the biosynthesis of a number of important seed constituents during seed development.ConclusionsWe have developed a foundational database of expressed sequences and collection of plasmid clones that comprise even low-expressed genes such as those encoding transcription factors. This has allowed us to delineate the spatio-temporal aspects of gene expression underlying the biosynthesis of a number of important seed constituents in flax. Flax belongs to a taxonomic group of diverse plants and the large sequence database will allow for evolutionary studies as well.

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