Single amino acid change alters specificity of the multi-allelic wheat stem rust resistance locus SR9

Most rust resistance genes thus far isolated from wheat have a very limited number of functional alleles. Here, we report the isolation of most of the alleles at wheat stem rust resistance gene locus SR9. The seven previously reported resistance alleles (Sr9a, Sr9b, Sr9d, Sr9e, Sr9f, Sr9g, and Sr9h) are characterised using a synergistic strategy. Loss-of-function mutants and/or transgenic complementation are used to confirm Sr9b, two haplotypes of Sr9e (Sr9e_h1 and Sr9e_h2), Sr9g, and Sr9h. Each allele encodes a highly related nucleotide-binding site leucine-rich repeat (NB-LRR) type immune receptor, containing an unusual long LRR domain, that confers resistance to a unique spectrum of isolates of the wheat stem rust pathogen. The only SR9 protein effective against stem rust pathogen race TTKSK (Ug99), SR9H, differs from SR9B by a single amino acid. SR9B and SR9G resistance proteins are also distinguished by only a single amino acid. The SR9 allelic series found in the B subgenome are orthologs of wheat stem rust resistance gene Sr21 located in the A subgenome with around 85% identity in protein sequences. Together, our results show that functional diversification of allelic variants at the SR9 locus involves single and multiple amino acid changes that recognize isolates of wheat stem rust.

A pathogen-induced putative NAC transcription factor mediates leaf rust resistance in barley

Leaf rust, caused by Puccinia hordei, is one of the most widespread and damaging foliar diseases affecting barley. The barley leaf rust resistance locus Rph7 has been shown to have unusually high sequence and haplotype divergence. In this study, we isolate the Rph7 gene using a fine mapping and RNA-Seq approach that is confirmed by mutational analysis and transgenic complementation. Rph7 is a pathogen-induced, non-canonical resistance gene encoding a protein that is distinct from other known plant disease resistance proteins in the Triticeae. Structural analysis using an AlphaFold2 protein model suggests that Rph7 encodes a putative NAC transcription factor with a zinc-finger BED domain with structural similarity to the N-terminal DNA-binding domain of the NAC transcription factor (ANAC019) from Arabidopsis. A global gene expression analysis suggests Rph7 mediates the activation and strength of the basal defence response. The isolation of Rph7 highlights the diversification of resistance mechanisms available for engineering disease control in crops.

Surface frustration re-patterning underlies the structural landscape and evolvability of fungal orphan candidate effectors

Pathogens secrete effector proteins to subvert host physiology and cause disease. Effectors are engaged in a molecular arms race with the host resulting in conflicting evolutionary constraints to manipulate host cells without triggering immune responses. The molecular mechanisms allowing effectors to be at the same time robust and evolvable remain largely enigmatic. Here, we show that 62 conserved structure-related families encompass the majority of fungal orphan effector candidates in the Pezizomycotina subphylum. These effectors diversified through changes in patterns of thermodynamic frustration at surface residues. The underlying mutations tended to increase the robustness of the overall effector protein structure while switching potential binding interfaces. This mechanism could explain how conserved effector families maintained biological activity over long evolutionary timespans in different host environments and provides a model for the emergence of sequence-unrelated effector families with conserved structures.

High-quality wild barley genome assemblies and annotation with Nanopore long reads and Hi-C sequencing data

Wild barley, from "Evolution Canyon (EC)" in Mount Carmel, Israel, are ideal models for cereal chromosome evolution studies. Here, the wild barley EC_S1 is from the south slope with higher daily temperatures and drought, while EC_N1 is from the north slope with a cooler climate and higher relative humidity, which results in a differentiated selection due to contrasting environments. We assembled a 5.03 Gb genome with contig N50 of 3.53 Mb for wild barley EC_S1 and a 5.05 Gb genome with contig N50 of 3.45 Mb for EC_N1 using 145 Gb and 160.0 Gb Illumina sequencing data, 295.6 Gb and 285.35 Gb Nanopore sequencing data and 555.1 Gb and 514.5 Gb Hi-C sequencing data, respectively. BUSCOs and CEGMA evaluation suggested highly complete assemblies. Using full-length transcriptome data, we predicted 39,179 and 38,373 high-confidence genes in EC_S1 and EC_N1, in which 93.6% and 95.2% were functionally annotated, respectively. We annotated repetitive elements and non-coding RNAs. These two wild barley genome assemblies will provide a rich gene pool for domesticated barley.

Impact and mechanism of sulphur-deficiency on modern wheat farming nitrogen-related sustainability and gliadin content

Two challenges that the global wheat industry is facing are a lowering nitrogen-use efficiency (NUE) and an increase in the reporting of wheat-protein related health issues. Sulphur deficiencies in soil has also been reported as a global issue. The current study used large-scale field and glasshouse experiments to investigate the sulphur fertilization impacts on sulphur deficient soil. Here we show that sulphur addition increased NUE by more than 20% through regulating glutamine synthetase. Alleviating the soil sulphur deficiency highly significantly reduced the amount of gliadin proteins indicating that soil sulphur levels may be related to the biosynthesis of proteins involved in wheat-induced human pathologies. The sulphur-dependent wheat gluten biosynthesis network was studied using transcriptome analysis and amino acid metabolomic pathway studies. The study concluded that sulphur deficiency in modern farming systems is not only having a profound negative impact on productivity but is also impacting on population health.

Hierarchical clustering of MS/MS spectra from the firefly metabolome identifies new lucibufagin compounds

Metabolite identification is the greatest challenge when analysing metabolomics data, as only a small proportion of metabolite reference standards exist. Clustering MS/MS spectra is a common method to identify similar compounds, however interrogation of underlying signature fragmentation patterns within clusters can be problematic. Previously published high-resolution LC-MS/MS data from the bioluminescent beetle (Photinus pyralis) provided an opportunity to mine new specialized metabolites in the lucibufagin class, compounds important for defense against predation. We aimed to 1) provide a workflow for hierarchically clustering MS/MS spectra for metabolomics data enabling users to cluster, visualise and easily interrogate the identification of underlying cluster ion profiles, and 2) use the workflow to identify key fragmentation patterns for lucibufagins in the hemolymph of P. pyralis. Features were aligned to their respective MS/MS spectra, then product ions were dynamically binned and resulting spectra were hierarchically clustered and grouped based on a cutoff distance threshold. Using the simplified visualization and the interrogation of cluster ion tables the number of lucibufagins was expanded from 17 to a total of 29.