Wheat genetic loci conferring resistance to stripe rust in the face of genetically diverse races of the fungus Puccinia striiformis f. sp. tritici.

KEY MESSAGE: Analysis of a wheat multi-founder population identified 14 yellow rust resistance QTL. For three of the four most significant QTL, haplotype analysis indicated resistance alleles were rare in European wheat. Stripe rust, or yellow rust (YR), is a major fungal disease of wheat (Triticum aestivum) caused by Puccinia striiformis Westend f. sp. tritici (Pst). Since 2011, the historically clonal European Pst races have been superseded by the rapid incursion of genetically diverse lineages, reducing the resistance of varieties previously showing durable resistance. Identification of sources of genetic resistance to such races is a high priority for wheat breeding. Here we use a wheat eight-founder multi-parent population genotyped with a 90,000 feature single nucleotide polymorphism array to genetically map YR resistance to such new Pst races. Genetic analysis of five field trials at three UK sites identified 14 quantitative trait loci (QTL) conferring resistance. Of these, four highly significant loci were consistently identified across all test environments, located on chromosomes 1A (QYr.niab-1A.1), 2A (QYr.niab-2A.1), 2B (QYr.niab-2B.1) and 2D (QYr.niab-2D.1), together explaining ~ 50% of the phenotypic variation. Analysis of these four QTL in two-way and three-way combinations showed combinations conferred greater resistance than single QTL, and genetic markers were developed that distinguished resistant and susceptible alleles. Haplotype analysis in a collection of wheat varieties found that the haplotypes associated with YR resistance at three of these four major loci were rare (≤ 7%) in European wheat, highlighting their potential utility for future targeted improvement of disease resistance. Notably, the physical interval for QTL QYr.niab-2B.1 contained five nucleotide-binding leucine-rich repeat candidate genes with integrated BED domains, of which two corresponded to the cloned resistance genes Yr7 and Yr5/YrSp.

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.

Potential for re-emergence of wheat stem rust in the United Kingdom.

Wheat stem rust, a devastating disease of wheat and barley caused by the fungal pathogen Puccinia graminis f. sp. tritici, was largely eradicated in Western Europe during the mid-to-late twentieth century. However, isolated outbreaks have occurred in recent years. Here we investigate whether a lack of resistance in modern European varieties, increased presence of its alternate host barberry and changes in climatic conditions could be facilitating its resurgence. We report the first wheat stem rust occurrence in the United Kingdom in nearly 60 years, with only 20% of UK wheat varieties resistant to this strain. Climate changes over the past 25 years also suggest increasingly conducive conditions for infection. Furthermore, we document the first occurrence in decades of P. graminis on barberry in the UK . Our data illustrate that wheat stem rust does occur in the UK and, when climatic conditions are conducive, could severely harm wheat and barley production.

BED-domain-containing immune receptors confer diverse resistance spectra to yellow rust.

Crop diseases reduce wheat yields by ~25% globally and thus pose a major threat to global food security1. Genetic resistance can reduce crop losses in the field and can be selected through the use of molecular markers. However, genetic resistance often breaks down following changes in pathogen virulence, as experienced with the wheat yellow (stripe) rust fungus Puccinia striiformis f. sp. tritici (Pst)2. This highlights the need to (1) identify genes that, alone or in combination, provide broad-spectrum resistance, and (2) increase our understanding of the underlying molecular modes of action. Here we report the isolation and characterization of three major yellow rust resistance genes (Yr7, Yr5 and YrSP) from hexaploid wheat (Triticum aestivum), each having a distinct recognition specificity. We show that Yr5, which remains effective to a broad range of Pst isolates worldwide, is closely related yet distinct from Yr7, whereas YrSP is a truncated version of Yr5 with 99.8% sequence identity. All three Yr genes belong to a complex resistance gene cluster on chromosome 2B encoding nucleotide-binding and leucine-rich repeat proteins (NLRs) with a non-canonical N-terminal zinc-finger BED domain3 that is distinct from those found in non-NLR wheat proteins. We developed diagnostic markers to accelerate haplotype analysis and for marker-assisted selection to expedite the stacking of the non-allelic Yr genes. Our results provide evidence that the BED-NLR gene architecture can provide effective field-based resistance to important fungal diseases such as wheat yellow rust.

A saturated SNP linkage map for the orange wheat blossom midge resistance gene Sm1.

KEY MESSAGE: SNP markers were developed for the OWBM resistance gene Sm1 that will be useful for MAS. The wheat Sm1 region is collinear with an inverted syntenic interval in B. distachyon. Orange wheat blossom midge (OWBM, Sitodiplosis mosellana Géhin) is an important insect pest of wheat (Triticum aestivum) in many growing regions. Sm1 is the only described OWBM resistance gene and is the foundation of managing OWBM through host genetics. Sm1 was previously mapped to wheat chromosome arm 2BS relative to simple sequence repeat (SSR) markers and the dominant, sequence characterized amplified region (SCAR) marker WM1. The objectives of this research were to saturate the Sm1 region with markers, develop improved markers for marker-assisted selection (MAS), and examine the synteny between wheat, Brachypodium distachyon, and rice (Oryza sativa) in the Sm1 region. The present study mapped Sm1 in four populations relative to single nucleotide polymorphisms (SNPs), SSRs, Diversity Array Technology (DArT) markers, single strand conformation polymorphisms (SSCPs), and the SCAR WM1. Numerous high quality SNP assays were designed that mapped near Sm1. BLAST delineated the syntenic intervals in B. distachyon and rice using gene-based SNPs as query sequences. The Sm1 region in wheat was inverted relative to B. distachyon and rice, which suggests a chromosomal rearrangement within the Triticeae lineage. Seven SNPs were tested on a collection of wheat lines known to carry Sm1 and not to carry Sm1. Sm1-flanking SNPs were identified that were useful for predicting the presence or absence of Sm1 based upon haplotype. These SNPs will be a major improvement for MAS of Sm1 in wheat breeding programs.

Using the UK reference population Avalon × Cadenza as a platform to compare breeding strategies in elite Western European bread wheat.

Wheat breeders select for qualitative and quantitative traits, the latter often detected as quantitative trait loci (QTL). It is, however, a long procedure from QTL discovery to the successful introduction of favourable alleles into new elite varieties and finally into farmers' crops. As a proof of principle for this process, QTL for grain yield (GY), yield components, plant height (PH), ear emergence (EM), solid stem (SS) and yellow rust resistance (Yr) were identified in segregating UK bread wheat reference population, Avalon × Cadenza. Among the 163 detected QTL were several not reported before: 17 for GY, the major GY QTL on 2D; a major SS QTL on 3B; and Yr6 on 7B. Common QTL were identified on ten chromosomes, most interestingly, grain number (GN) was found to be associated with Rht-D1b; and GY and GN with a potential new allele of Rht8. The interaction of other QTL with GY and yield components was discussed in the context of designing a UK breeding target genotype. Desirable characteristics would be: similar PH and EM to Avalon; Rht-D1b and Vrn-A1b alleles; high TGW and GN; long and wide grains; a large root system, resistance to diseases; and maximum GY. The potential of the identified QTL maximising transgressive segregation to produce a high-yielding and resilient genotype was demonstrated by simulation. Moreover, simulating breeding strategies with F2 enrichment revealed that the F2-DH procedure was superior to the RIL and the modified SSD procedure to achieve that genotype. The proposed strategies of parent selection and breeding methodology can be used as guidance for marker-assisted wheat breeding.

RNA-Seq bulked segregant analysis enables the identification of high-resolution genetic markers for breeding in hexaploid wheat.

The identification of genetic markers linked to genes of agronomic importance is a major aim of crop research and breeding programmes. Here, we identify markers for Yr15, a major disease resistance gene for wheat yellow rust, using a segregating F2 population. After phenotyping, we implemented RNA sequencing (RNA-Seq) of bulked pools to identify single-nucleotide polymorphisms (SNP) associated with Yr15. Over 27 000 genes with SNPs were identified between the parents, and then classified based on the results from the sequenced bulks. We calculated the bulk frequency ratio (BFR) of SNPs between resistant and susceptible bulks, selecting those showing sixfold enrichment/depletion in the corresponding bulks (BFR > 6). Using additional filtering criteria, we reduced the number of genes with a putative SNP to 175. The 35 SNPs with the highest BFR values were converted into genome-specific KASP assays using an automated bioinformatics pipeline (PolyMarker) which circumvents the limitations associated with the polyploid wheat genome. Twenty-eight assays were polymorphic of which 22 (63%) mapped in the same linkage group as Yr15. Using these markers, we mapped Yr15 to a 0.77-cM interval. The three most closely linked SNPs were tested across varieties and breeding lines representing UK elite germplasm. Two flanking markers were diagnostic in over 99% of lines tested, thus providing a reliable haplotype for marker-assisted selection in these breeding programmes. Our results demonstrate that the proposed methodology can be applied in polyploid F2 populations to generate high-resolution genetic maps across target intervals.