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Background Gene annotation in eukaryotes is a non-trivial task that requires meticulous analysis of accumulated transcript data. Challenges include transcriptionally active regions of the genome that contain overlapping genes, genes that produce numerous transcripts, transposable elements and numerous diverse sequence repeats. Currently available gene annotation software applications depend on pre-constructed full-length gene sequence assemblies which are not guaranteed to be error-free. The origins of these sequences are often uncertain, making it difficult to identify and rectify errors in them. This hinders the creation of an accurate and holistic representation of the transcriptomic landscape across multiple tissue types and experimental conditions. Therefore, to gauge the extent of diversity in gene structures, a comprehensive analysis of genome-wide expression data is imperative. Results We present FINDER, a fully automated computational tool that optimizes the entire process of annotating genes and transcript structures. Unlike current state-of-the-art pipelines, FINDER automates the RNA-Seq pre-processing step by working directly with raw sequence reads and optimizes gene prediction from BRAKER2 by supplementing these reads with associated proteins. The FINDER pipeline (1) reports transcripts and recognizes genes that are expressed under specific conditions, (2) generates all possible alternatively spliced transcripts from expressed RNA-Seq data, (3) analyzes read coverage patterns to modify existing transcript models and create new ones, and (4) scores genes as high- or low-confidence based on the available evidence across multiple datasets. We demonstrate the ability of FINDER to automatically annotate a diverse pool of genomes from eight species. Conclusions FINDER takes a completely automated approach to annotate genes directly from raw expression data. It is capable of processing eukaryotic genomes of all sizes and requires no manual supervision—ideal for bench researchers with limited experience in handling computational tools.

Plant disease resistance often occurs upon direct or indirect recognition of pathogen effectors by host nucleotide-binding leucine-rich-repeat (NLR) receptors. The barley powdery mildew fungus,Blumeria graminisf. sp.hordei(Bgh), secretes hundreds of candidate secreted effector proteins (CSEPs) to facilitate pathogen infection and colonization. One of these, CSEP0008, is directly recognized by the barley NLR, MLA1, and therefore designated AVRA1. Here we show that AVRA1and the sequence-unrelatedBgheffector BEC1016 (CSEP0491) suppress immunity in barley cells. We then used yeast 2-hybrid next-generation-interaction screens (Y2H-NGIS), followed by binary Y2H and bimolecular fluorescence complementation, to identify a common barley target of AVRA1and BEC1016, the endoplasmic reticulum (ER)-localized J-domain protein,HvERdj3B. This is an ER protein quality control (ERQC) protein and silencing it increased theBghpenetration rate in barley.HvERdj3B is localized to the ER lumen, and AVRA1and BEC106 translocation into the ER was confirmed using a split GFP system. Together, these results suggest that the barley innate immunity, preventingBghentry into epidermal cells, is dependent on ERQC, which in turn is regulated by J-domain proteinHvERdj3B and the two effectors. Previous work has shown that AVRA1is directly recognized in the cytosol by the immune receptor, MLA1. We speculate whether the AVRA1J-domain target being inside the ER, where it is inapproachable by NLRs, has forced the plant to evolve this challenging direct recognition.

The barley MLA nucleotide-binding leucine-rich-repeat (NLR) receptor and its orthologs confer recognition specificity to many fungal diseases, including powdery mildew, stem-, and stripe rust. We used interolog inference to construct a barley protein interactome (Hordeum vulgare predicted interactome, HvInt) comprising 66,133 edges and 7,181 nodes, as a foundation to explore signaling networks associated with MLA. HvInt was compared with the experimentally validated Arabidopsis interactome of 11,253 proteins and 73,960 interactions, verifying that the 2 networks share scale-free properties, including a power-law distribution and small-world network. Then, by successive layering of defense-specific “omics” datasets, HvInt was customized to model cellular response to powdery mildew infection. Integration of HvInt with expression quantitative trait loci (eQTL) enabled us to infer disease modules and responses associated with fungal penetration and haustorial development. Next, using HvInt and infection–time–course RNA sequencing of immune signaling mutants, we assembled resistant and susceptible subnetworks. The resulting differentially coexpressed (resistant – susceptible) interactome is essential to barley immunity, facilitates the flow of signaling pathways and is linked to mildew resistance locus a (Mla) through trans eQTL associations. Lastly, we anchored HvInt with new and previously identified interactors of the MLA coiled coli + nucleotide-binding domains and extended these to additional MLA alleles, orthologs, and NLR outgroups to predict receptor localization and conservation of signaling response. These results link genomic, transcriptomic, and physical interactions during MLA-specified immunity.

The Mla (Mildew resistance locus a) of barley (Hordeum vulgare L.) is an effective model for cereal immunity against fungal pathogens. Like many resistance proteins, variants of the MLA coiled-coil nucleotide-binding leucine-rich repeat (CC-NLR) receptor often require the HRS complex (HSP90, RAR1, and SGT1) to function. However, functional analysis of Sgt1 has been particularly difficult, as deletions are often lethal. Recently, we identified rar3 (required for Mla6 resistance 3), an in-frame Sgt1ΔKL308-309 mutation in the SGT1-specific domain, that alters resistance conferred by MLA but without lethality. Here, we use autoactive MLA6 and recombinant yeast-two-hybrid strains with stably integrated HvRar1 and HvHsp90 to determine that this mutation weakens but does not entirely disrupt the interaction between SGT1 and MLA. This causes a concomitant reduction in MLA6 protein accumulation below the apparent threshold required for effective resistance. The ΔKL308-309 deletion had a lesser effect on intramolecular interactions than alanine or arginine substitutions, and MLA variants that display diminished interactions with SGT1 appear to be disproportionately affected by the SGT1ΔKL308-309 mutation. We hypothesize that those dimeric plant CC-NLRs that appear unaffected by Sgt1 silencing are those with the strongest intermolecular interactions with it. Combining our data with recent work in CC-NLRs, we propose a cyclical model of the MLA-HRS resistosome interactions. [Formula: see text] The author(s) have dedicated the work to the public domain under the Creative Commons CC0 “No Rights Reserved” license by waiving all of his or her rights to the work worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law, 2022.

The barley MLA nucleotide-binding, leucine-rich-repeat (NLR) receptor and its orthologs confer recognition specificity to many cereal diseases, including powdery mildew, stem and stripe rust, Victoria blight, and rice blast. We used interolog inference to construct a barley protein interactome (HvInt) comprising 66133 edges and 7181 nodes, as a foundation to explore signaling networks associated with MLA. HvInt was compared to the experimentally validated Arabidopsis interactome of 11253 proteins and 73960 interactions, verifying that the two networks share scale-free properties, including a power-law distribution and small-world network. Then, by successive layering of defense-specific ‘omics’ datasets, HvInt was customized to model cellular response to powdery mildew infection. Integration of HvInt with expression quantitative trait loci (eQTL) enabled us to infer disease modules and responses associated with fungal penetration and haustorial development. Next, using HvInt and an infection-time-course transcriptome, we assembled resistant (R) and susceptible (S) subnetworks. The resulting differentially co-expressed (R-S) interactome is essential to barley immunity, facilitates the flow of signaling pathways and is linked to Mla through trans eQTL associations. Lastly, next-generation, yeast-two-hybrid screens identified fifteen novel MLA interactors, which were incorporated into HvInt, to predict receptor localization, and signaling response. These results link genomic, transcriptomic, and physical interactions during MLA-specified immunity.AUTHOR SUMMARYPowdery mildew fungi infect more than 9,500 agronomic and horticultural plant species. In order to prevent economic loss due to diseases caused by pathogens, plant breeders incorporate resistance genes into varieties that are grown for food, feed, fuel and fiber. One of these resistance genes encodes the barley MLA immune receptor, an ancestral cereal protein that confers recognition to powdery mildew, stem and stripe rust, rice blast and Victoria blight. However, in order to function properly, these immune receptors must interact with additional proteins and protein complexes during the different stages of fungal infection and plant defense. We used a combination of computational- and laboratory-based methods to predict over 66,000 possible protein-protein interactions in barley. This network of proteins was then integrated with various defense-specific datasets to assemble the molecular building blocks associated with resistance to the powdery mildew pathogen, in addition to those proteins that interact with the MLA immune receptor. Our application of genome-scale, protein-protein interaction data provides a foundation to decipher the complex molecular components that control immune responses in crops.

Background Plants encounter pathogenic and non-pathogenic microorganisms on a nearly constant basis. Small RNAs such as siRNAs and miRNAs/milRNAs influence pathogen virulence and host defense responses. We exploited the biotrophic interaction between the powdery mildew fungus, Blumeria graminis f. sp. hordei (Bgh), and its diploid host plant, barley (Hordeum vulgare) to explore fungal and plant sRNAs expressed during Bgh infection of barley leaf epidermal cells. Results RNA was isolated from four fast-neutron immune-signaling mutants and their progenitor over a time course representing key stages of Bgh infection, including appressorium formation, penetration of epidermal cells, and development of haustorial feeding structures. The Cereal Introduction (CI) 16151 progenitor carries the resistance allele Mla6, while Bgh isolate 5874 harbors the AVRa6 avirulence effector, resulting in an incompatible interaction. Parallel Analysis of RNA Ends (PARE) was used to verify sRNAs with likely transcript targets in both barley and Bgh. Bgh sRNAs are predicted to regulate effectors, metabolic genes, and translation-related genes. Barley sRNAs are predicted to influence the accumulation of transcripts that encode auxin response factors, NAC transcription factors, homeodomain transcription factors, and several splicing factors. We also identified phasing small interfering RNAs (phasiRNAs) in barley that overlap transcripts that encode receptor-like kinases (RLKs) and nucleotide-binding, leucine-rich domain proteins (NLRs). Conclusions These data suggest that Bgh sRNAs regulate gene expression in metabolism, translation-related, and pathogen effectors. PARE-validated targets of predicted Bgh milRNAs include both EKA (effectors homologous to AVRk1 and AVRa10) and CSEP (candidate secreted effector protein) families. We also identified barley phasiRNAs and miRNAs in response to Bgh infection. These include phasiRNA loci that overlap with a significant proportion of receptor-like kinases, suggesting an additional sRNA control mechanism may be active in barley leaves as opposed to predominant R-gene phasiRNA overlap in many eudicots. In addition, we identified conserved miRNAs, novel miRNA candidates, and barley genome mapped sRNAs that have PARE validated transcript targets in barley. The miRNA target transcripts are enriched in transcription factors, signaling-related proteins, and photosynthesis-related proteins. Together these results suggest both barley and Bgh control metabolism and infection-related responses via the specific accumulation and targeting of genes via sRNAs. Electronic supplementary material The online version of this article (10.1186/s12864-019-5947-z) contains supplementary material, which is available to authorized users.

The Pseudomonas syringae cysteine protease AvrPphB activates the Arabidopsis resistance protein RPS5 by cleaving a second host protein, PBS1. AvrPphB induces defense responses in other plant species, but the genes and mechanisms mediating AvrPphB recognition in those species have not been defined. Here, we show that AvrPphB induces defense responses in diverse barley cultivars. We also show that barley contains two PBS1 orthologs, that their products are cleaved by AvrPphB, and that the barley AvrPphB response maps to a single locus containing a nucleotide-binding leucine-rich repeat (NLR) gene, which we termed AvrPphB Response 1 (Pbr1). Transient coexpression of PBR1 with wild-type AvrPphB but not with a protease inactive mutant triggered defense responses, indicating that PBR1 detects AvrPphB protease activity. Additionally, PBR1 coimmunoprecipitated with barley and Nicotiana benthamiana PBS1 proteins, suggesting mechanistic similarity to detection by RPS5. Lastly, we determined that wheat cultivars also recognize AvrPphB protease activity and contain two putative Pbr1 orthologs. Phylogenetic analyses showed, however, that Pbr1 is not orthologous to RPS5. Our results indicate that the ability to recognize AvrPphB evolved convergently and imply that selection to guard PBS1-like proteins occurs across species. Also, these results suggest that PBS1-based decoys may be used to engineer protease effector recognition–based resistance in barley and wheat.

Protein-protein interaction networks are one of the most effective representations of cellular behavior. In order to build these models, high-throughput techniques are required. Next-generation interaction screening (NGIS) protocols that combine yeast two-hybrid (Y2H) with deep sequencing are promising approaches to generate interactome networks in any organism. However, challenges remain to mining reliable information from these screens and thus, limit its broader implementation. Here, we present a computational framework, designated Y2H-SCORES, for analyzing high-throughput Y2H screens. Y2H-SCORES considers key aspects of NGIS experimental design and important characteristics of the resulting data that distinguish it from RNA-seq expression datasets. Three quantitative ranking scores were implemented to identify interacting partners, comprising: 1) significant enrichment under selection for positive interactions, 2) degree of interaction specificity among multi-bait comparisons, and 3) selection of in-frame interactors. Using simulation and an empirical dataset, we provide a quantitative assessment to predict interacting partners under a wide range of experimental scenarios, facilitating independent confirmation by one-to-one bait-prey tests. Simulation of Y2H-NGIS enabled us to identify conditions that maximize detection of true interactors, which can be achieved with protocols such as prey library normalization, maintenance of larger culture volumes and replication of experimental treatments. Y2H-SCORES can be implemented in different yeast-based interaction screenings, with an equivalent or superior performance than existing methods. Proof-of-concept was demonstrated by discovery and validation of novel interactions between the barley nucleotide-binding leucine-rich repeat (NLR) immune receptor MLA6, and fourteen proteins, including those that function in signaling, transcriptional regulation, and intracellular trafficking., Author summary Organisms respond to their environment through networks of interacting proteins and other biomolecules. In order to investigate these interacting proteins, many in vitro and in vivo techniques have been used. Among these, yeast two-hybrid (Y2H) has been integrated with next generation sequencing (NGS) to approach protein-protein interactions on a genome-wide scale. The fusion of these two methods has been termed next-generation-interaction screening, abbreviated as Y2H-NGIS. However, the diverse data sets resulting from this technology have presented unique challenges to analysis. To address these challenges, we optimized the computational and statistical evaluation of Y2H-NGIS to provide metrics to identify high-confidence interacting proteins under a variety of dataset scenarios. Our proposed framework can be extended to different yeast-based interaction settings, utilizing the general principles of enrichment, specificity, and in-frame prey selection to accurately assemble interactome networks. Lastly, we showed how the pipeline works experimentally, by identifying and validating novel interactions between the barley powdery mildew resistance protein, MLA6, and fourteen targets, including proteins involved in signaling, transcriptional regulation, and intracellular trafficking. Y2H-SCORES software is available at GitHub repository https://github.com/Wiselab2/Y2H-SCORES/tree/master/Software.

Barley (Hordeum vulgare L.) Mla (Mildew resistance locus a) and its nucleotide-binding, leucine-rich-repeat receptor (NLR) orthologs protect many cereal crops from diseases caused by fungal pathogens. However, large segments of the Mla pathway and its mechanisms remain unknown. To further characterize the molecular interactions required for NLR-based immunity, we used fast-neutron mutagenesis to screen for plants compromised in MLA-mediated response to the powdery mildew fungus, Blumeria graminis f. sp. hordei. One variant, m11526, contained a novel mutation, designated rar3 (required for Mla6 resistance3), that abolishes race-specific resistance conditioned by the Mla6, Mla7, and Mla12 alleles, but does not compromise immunity mediated by Mla1, Mla9, Mla10, and Mla13. This is analogous to, but unique from, the differential requirement of Mla alleles for the co-chaperone Rar1 (required for Mla12 resistance1). We used bulked-segregant-exome capture and fine mapping to delineate the causal mutation to an in-frame Lys-Leu deletion within the SGS domain of SGT1 (Suppressor of G-two allele of Skp1, Sgt1ΔKL308–309), the structural region that interacts with MLA proteins. In nature, mutations to Sgt1 usually cause lethal phenotypes, but here we pinpoint a unique modification that delineates its requirement for some disease resistances, while unaffecting others as well as normal cell processes. Moreover, the data indicate that the requirement of SGT1 for resistance signaling by NLRs can be delimited to single sites on the protein. Further study could distinguish the regions by which pathogen effectors and host proteins interact with SGT1, facilitating precise editing of effector incompatible variants.

Mapping protein–protein interactions at a proteome scale is critical to understanding how cellular signaling networks respond to stimuli. Since eukaryotic genomes encode thousands of proteins, testing their interactions one-by-one is a challenging prospect. High-throughput yeast-two hybrid (Y2H) assays that employ next-generation sequencing to interrogate complementary DNA (cDNA) libraries represent an alternative approach that optimizes scale, cost and effort. We present NGPINT, a robust and scalable software to identify all putative interactors of a protein using Y2H in batch culture. NGPINT combines diverse tools to align sequence reads to target genomes, reconstruct prey fragments and compute gene enrichment under reporter selection. Central to this pipeline is the identification of fusion reads containing sequences derived from both the Y2H expression plasmid and the cDNA of interest. To reduce false positives, these fusion reads are evaluated as to whether the cDNA fragment forms an in-frame translational fusion with the Y2H transcription factor. NGPINT successfully recognized 95% of interactions in simulated test runs. As proof of concept, NGPINT was tested using published data sets and it recognized all validated interactions. NGPINT can process interaction data from any biosystem with an available genome or transcriptome reference, thus facilitating the discovery of protein–protein interactions in model and non-model organisms.

An important yet challenging step of genome annotation is the process of finding the location of genes and transcripts within chromosomes. Complexities in eukaryotic genomes, like the presence of transposable elements, make the job of annotation difficult. To complicate matters even more, there are genes that produce numerous transcripts and also overlap with other genes. Perfect annotation of genes, originating from such complicated loci, is possible with full-length transcripts obtained from long-read sequencing platforms like PacBio or Nanopore. Unfortunately, these platforms require specialized library preps, produce high number of errors and are less cost-effective as sequencing on platforms like Illumina. Prevalence of complexities in the genome hinders accurate reconstructing of full-length transcripts from short Illumina reads, thereby impeding the progress of novel gene discovery and precise genome annotation. Reduction in sequencing costs have enabled numerous small labs to undertake whole genome expression studies to understand their respective biosystems better. These studies have been extended to non-model organisms for which a comprehensive gene annotation is often lacking. Absence of gene models and partially annotated genes lead to false negatives in differential expression study thereby preventing a holistic understanding of the biosystem. Correct identification of transcription start sites and proper construction of gene structures is pivotal to downstream applications (e.g. promoter mining, protein interaction study, etc.) making genome annotation extremely relevant. Annotation approaches undertaken by tools like BRAKER2 and MAKER2 involve predicting protein-coding genes from mapped RNA-Seq data. MAKER2 also allows users to enter EST sequences for annotation. These pipelines implement statistical gene predictors like SNAP and Augustus to annotate coding regions of genes. The approach of annotating only protein-coding regions lead to partial gene structures that interfere with epigenetic analysis which directly impacts about 13,000 transcripts in the well-annotated Arabidopsis thaliana genome since those transcripts have 5' UTR of length greater than 250 bp. Most BRAKER2 gene models have only one transcript thereby causing a plunge in transcript sensitivity. Also, BRAKER2 does not predict any non-coding genes. To overcome the shortcomings of previous genome annotators, we have designed a pipeline called FINDER which integrates predicted gene models with assembled expressed transcript models. FINDER performs optimized read mapping with STAR and uses PsiCLASS to conduct meta-assembly. The pipeline is designed to assess each gene model based on expression coverage and modify transcript boundaries to better comply with the expression pattern. Finally, FINDER incorporates predicted gene models from BRAKER2 if those do not overlap with assembled models and have some representation in the provided proteome. Arabidopsis thaliana is a model organism with one of the best gene annotations making it ideal to validate and evaluate gene annotation pipelines. We compared our assembled gene models with predicted models from BRAKER2 and in all the categories PsiCLASS gene models were superior. Most approaches use Stringtie and/or Scallop to generate assemblies and then merge those using Stringtie merge. PsiCLASS meta-assembler was able to generate much better transcript models recoding the highest F1 score. Some transcript assemblies generated by PsiCLASS represent merged genes and exhibit exon extension for overlapping genes on the opposite strand. Signals present in expression profiles are utilized through changepoint detection to split up merged gene models. This improved the transcript F1 score from 42.37 to 49.28. Finally, gene models predicted by BRAKER2 that have high similarity with proteins and do not overlap with the assembled transcripts are included in the final annotations boosting the F1 score to 50.03. FINDER executes OLEGO - an aligner optimized to detect micro-exons that further improves gene predictions. Our results demonstrate that overall FINDER generates better and more consistent gene and transcript models. BRAKER2 is designed to annotate only the protein-coding regions of genes thereby generating incomplete gene models impacting epigenetics research. Annotating only a portion of a gene and reporting very few transcripts per gene reduces the sensitivity of BRAKER2. Stringtie and Scallop are popular assemblers and are widely used to generate assemblies. Stringtie merge is used to combine individual assemblies giving rise to a meta-assembly. Stringtie merge produces poor meta assemblies, because it does not take into account the expression profile of the transcripts. Changepoint detection implemented to refine PsiCLASS assemblies improves the overall gene structures showing the importance of expression profiles in redefining transcript boundaries. We are confident that FINDER will pave the way for better gene structure annotation in the future.

Interactomes embody one of the most effective representations of cellular behavior by revealing function through protein associations. In order to build these models at the organism scale, high-throughput techniques are required to identify interacting pairs of proteins. Next-generation interaction screening (NGIS) protocols that combine yeast two-hybrid (Y2H) with deep sequencing are promising approaches to generate protein-protein interaction networks in any organism. However, challenges remain to mining reliable information from these screens and thus, limit its broader implementation. Here, we describe a statistical framework, designated Y2H-SCORES, for analyzing high-throughput Y2H screens that considers key aspects of experimental design, normalization, and controls. Three quantitative ranking scores were implemented to identify interacting partners, comprising: 1) significant enrichment under selection for positive interactions, 2) degree of interaction specificity among multi-bait comparisons, and 3) selection of in-frame interactors. Using simulation and an empirical dataset, we provide a quantitative assessment to predict interacting partners under a wide range of experimental scenarios, facilitating independent confirmation by one-to-one bait-prey tests. Simulation of Y2H-NGIS identified conditions that maximize detection of true interactors, which can be achieved with protocols such as prey library normalization, maintenance of larger culture volumes and replication of experimental treatments. Y2H-SCORES can be implemented in different yeast-based interaction screenings, accelerating the biological interpretation of experimental results. Proof-of-concept was demonstrated by discovery and validation of a novel interaction between the barley powdery mildew effector, AVRA13, with the vesicle-mediated thylakoid membrane biogenesis protein, HvTHF1.Author SummaryOrganisms respond to their environment through networks of interacting proteins and other biomolecules. In order to investigate these interacting proteins, many in vitro and in vivo techniques have been used. Among these, yeast two-hybrid (Y2H) has been integrated with next generation sequencing (NGS) to approach protein-protein interactions on a genome-wide scale. The fusion of these two methods has been termed next-generation-interaction screening, abbreviated as Y2H-NGIS. However, the massive and diverse data sets resulting from this technology have presented unique challenges to analysis. To address these challenges, we optimized the computational and statistical evaluation of Y2H-NGIS to provide metrics to identify high-confidence interacting proteins under a variety of dataset scenarios. Our proposed framework can be extended to different yeast-based interaction settings, utilizing the general principles of enrichment, specificity, and in-frame prey selection to accurately assemble protein-protein interaction networks. Lastly, we showed how the pipeline works experimentally, by identifying and validating a novel interaction between the barley powdery mildew effector AVRA13 and the barley vesicle-mediated thylakoid membrane biogenesis protein, HvTHF1. Y2H-SCORES software is available at GitHub repository https://github.com/Wiselab2/Y2H-SCORES.

Powdery mildew pathogens colonize over 9500 plant species, causing critical yield loss. The Ascomycete fungus, Blumeria graminis f. sp. hordei (Bgh), causes powdery mildew disease in barley (Hordeum vulgare L.). Successful infection begins with penetration of host epidermal cells, culminating in haustorial feeding structures, facilitating delivery of fungal effectors to the plant and exchange of nutrients from host to pathogen. We used expression Quantitative Trait Locus (eQTL) analysis to dissect the temporal control of immunity-associated gene expression in a doubled haploid barley population challenged with Bgh. Two highly significant regions possessing trans eQTL were identified near the telomeric ends of chromosomes (Chr) 2HL and 1HS. Within these regions reside diverse resistance loci derived from barley landrace H. laevigatum (MlLa) and H. vulgare cv. Algerian (Mla1), which associate with the altered expression of 961 and 3296 genes during fungal penetration of the host and haustorial development, respectively. Regulatory control of transcript levels for 299 of the 961 genes is reprioritized from MlLa on 2HL to Mla1 on 1HS as infection progresses, with 292 of the 299 alternating the allele responsible for higher expression, including Adaptin Protein-2 subunit μ AP2M and Vesicle Associated Membrane Protein VAMP72 subfamily members VAMP721/722. AP2M mediates effector-triggered immunity (ETI) via endocytosis of plasma membrane receptor components. VAMP721/722 and SNAP33 form a Soluble N-ethylmaleimide-sensitive factor Attachment Protein REceptor (SNARE) complex with SYP121 (PEN1), which is engaged in pathogen associated molecular pattern (PAMP)-triggered immunity via exocytosis. We postulate that genes regulated by alternate chromosomal positions are repurposed as part of a conserved immune complex to respond to different pathogen attack scenarios.

Cereal crops pose a substantial challengeto gene discovery. Except for rice and sor-ghum, most have large, complex genomes,the bulk of which consist of repetitive se-quences and retrotransposons (7,53). Thus,much of the early research relating to themolecular study of plant disease resistancehas occurred in species with smallgenomes, such as Arabidopsis, rice, andtomato. The knowledge acquired fromthese model species has facilitated similarefforts in cereal crops. The goal of thisreport is to summarize the current toolsavailable and to outline selected exampleswhere these tools have been useful for theinvestigation of disease resistance in barley(Hordeum vulgare L.). Because molecularinvestigations have focused primarily onfungal pathogens, they will be the subjectof this review.

Copy-number alterations are widespread in animal and plant genomes, but their immediate impact on gene expression is still unclear. In animals, copy-number alterations usually exhibit dosage effects, except for sex chromosomes which tend to be dosage compensated. In plants, genes within small duplications (50 Mb) are more often dosage compensated. However, little or nothing is known about expression in moderately-sized (1–50 Mb) segmental duplications, and about the response of small RNAs to dosage change. Here, we compared maize (Zea mays) plants with two, three, and four doses of a 14.6-Mb segment of chromosome 1 that contains ∼300 genes. Plants containing the duplicated segment exhibit dosage-dependent effects on ear length and flowering time. Transcriptome analyses using GeneChip and RNA-sequencing methods indicate that most expressed genes and unique small RNAs within the duplicated segments exhibit dosage-dependent transcript levels. We conclude that dosage effect is the predominant regulatory response for both genes and unique small RNA transcripts in the segmental dosage series we tested. To our knowledge this is the first analysis of small RNA expression in plant gene dosage variants. Because segmental duplications comprise a significant proportion of eukaryotic genomes, these findings provide important new insight into the regulation of genes and small RNAs in response to dosage changes.

The

The Pseudomonas syringae cysteine protease AvrPphB activates the Arabidopsis resistance protein RPS5 by cleaving a second host protein, PBS1. AvrPphB induces defense responses in other plant species, but the genes and mechanisms mediating AvrPphB recognition in those species have not been defined. Here, we show that AvrPphB induces defense responses in diverse barley cultivars. We show also that barley contains two PBS1 orthologs, that their products are cleaved by AvrPphB, and that the barley AvrPphB response maps to a single locus containing a nucleotide-binding leucine-rich repeat (NLR) gene, which we termed AvrPphB Resistance 1 (Pbr1). Transient co-expression of PBR1 with wild-type AvrPphB, but not a protease inactive mutant, triggered defense responses, indicating that PBR1 detects AvrPphB protease activity. Additionally, PBR1 co-immunoprecipitated with barley and N. benthamiana PBS1 proteins, suggesting mechanistic similarity to detection by RPS5. Lastly, we determined that wheat cultivars also recognize AvrPphB protease activity and contain a Pbr1 ortholog. Phylogenetic analyses showed however that Pbr1 is not orthologous to RPS5. Our results indicate that the ability to recognize AvrPphB evolved convergently, and imply that selection to guard PBS1-like proteins is ancient. Also, the results suggest that PBS1-based decoys may be used to engineer protease effector recognition-based resistance in barley and wheat.

This letter describes a newly discovered confounding effect of bacterial titer in a previously published type III delivery-based assay of the fungal effector BEC1019. The original publication (Whigham et al. 2015) has been retracted as a consequence of this discovery. Here, we tabulate the affected and unaffected figures and conclusions in the original publication and briefly reflect on potential pitfalls to bear in mind when designing experiments that use bacterial type III secretion to characterize eukaryotic effectors.

Over the last 100 years, research in barley disease resistance has progressed from classical genetic approaches up to molecular genetics and genome-wide functional profiling. Along the way, a multitude of well-characterized genetic resources have paved the way for mechanistic investigations into barley immunity. Seminal discoveries in barley have been translated to other crops, thus proving it to be an excellent system for plant disease research. Recent access to high-quality barley and pathogen genomes has empowered large-scale functional studies and facilitated the development of new technologies to associate traits with genes. Continued integration of existing germplasm with anchored sequence data promises to expedite mapping and functional characterization of important disease traits. In this chapter, we offer a genomic view of barley biotic stress with a focus on different types of resistance, current genomic approaches to dissect immune responses, and future prospects for the field.

Summary Barley (Hordeum vulgare L.) possesses a large and highly repetitive genome of 5.1 Gb that has hindered the development of a complete sequence. In 2012, the International Barley Sequencing Consortium released a resource integrating whole‐genome shotgun sequences with a physical and genetic framework. However, because only 6278 bacterial artificial chromosome (BACs) in the physical map were sequenced, fine structure was limited. To gain access to the gene‐containing portion of the barley genome at high resolution, we identified and sequenced 15 622 BACs representing the minimal tiling path of 72 052 physical‐mapped gene‐bearing BACs. This generated ~1.7 Gb of genomic sequence containing an estimated 2/3 of all Morex barley genes. Exploration of these sequenced BACs revealed that although distal ends of chromosomes contain most of the gene‐enriched BACs and are characterized by high recombination rates, there are also gene‐dense regions with suppressed recombination. We made use of published map‐anchored sequence data from Aegilops tauschii to develop a synteny viewer between barley and the ancestor of the wheat D‐genome. Except for some notable inversions, there is a high level of collinearity between the two species. The software HarvEST:Barley provides facile access to BAC sequences and their annotations, along with the barley–Ae. tauschii synteny viewer. These BAC sequences constitute a resource to improve the efficiency of marker development, map‐based cloning, and comparative genomics in barley and related crops. Additional knowledge about regions of the barley genome that are gene‐dense but low recombination is particularly relevant., Significance Statement We provide new genome sequence resources for barley and related species, to improve the efficiency of marker development, map‐based cloning, comparative genomics studies, and to provide insights into genome architecture. Notably, some of the gene‐rich islands in the barley genome deviate markedly from assumption that gene density and high recombination frequency are correlated.

Genes encoding early signaling events in pathogen defense often are identified only by their phenotype. Such genes involved in barley-powdery mildew interactions include Mla, specifying race-specific resistance; Rar1 (Required for Mla12-specified resistance1), and Rom1 (Restoration of Mla-specified resistance1). The HSP90-SGT1-RAR1 complex appears to function as chaperone in MLA-specified resistance, however, much remains to be discovered regarding the precise signaling underlying plant immunity. Genetic analyses of fast-neutron mutants derived from CI 16151 (Mla6) uncovered a novel locus, designated Rar3 (Required for Mla6-specified resistance3). Rar3 segregates independent of Mla6 and Rar1, and rar3 mutants are susceptible to Blumeria graminis f. sp. hordei (Bgh) isolate 5874 (AVRa6), whereas, wild-type progenitor plants are resistant. Comparative expression analyses of the rar3 mutant vs. its wild-type progenitor were conducted via Barley1 GeneChip and GAIIx paired-end RNA-Seq. Whereas Rar1 affects transcription of relatively few genes; Rar3 appears to influence thousands, notably in genes controlling ATP binding, catalytic activity, transcription, and phosphorylation; possibly membrane bound or in the nucleus. eQTL analysis of a segregating doubled haploid population identified over two-thousand genes as being regulated by Mla (q value/FDR=0.00001), a subset of which are significant in Rar3 interactions. The intersection of datasets derived from mla-loss-of-function mutants, Mla-associated eQTL, and rar3-mediated transcriptome reprogramming are narrowing the focus on essential genes required for Mla-specified immunity.

Obligate biotrophic pathogens of plants must circumvent or counteract defenses to guarantee accommodation inside the host. To do so, they secrete a variety of effectors that regulate host immunity and facilitate the establishment of pathogen feeding structures called haustoria. The barley powdery mildew fungus Blumeria graminis f. sp. hordei produces a large number of proteins predicted to be secreted from haustoria. Fifty of these Blumeria effector candidates (BEC) were screened by host-induced gene silencing (HIGS), and eight were identified that contribute to infection. One shows similarity to β-1,3 glucosyltransferases, one to metallo-proteases, and two to microbial secreted ribonucleases; the remainder have no similarity to proteins of known function. Transcript abundance of all eight BEC increases dramatically in the early stages of infection and establishment of haustoria, consistent with a role in that process. Complementation analysis using silencing-insensitive synthetic cDNAs demonstrated that the ribonuclease-like BEC 1011 and 1054 are bona fide effectors that function within the plant cell. BEC1011 specifically interferes with pathogen-induced host cell death. Both are part of a gene superfamily unique to the powdery mildew fungi. Structural modeling was consistent, with BEC1054 adopting a ribonuclease-like fold, a scaffold not previously associated with effector function. Pathogenic microbes are able to infect plant cells by producing arrays of effectors that manipulate host metabolism and immunity (Dodds and Rathjen 2010). These effectors are usually secreted proteins that act at the host cell surface (Stergiopoulos

Disease-resistance genes encoding intracellular nucleotide-binding domain and leucine-rich repeat proteins (NLRs) are key components of the plant innate immune system and typically detect the presence of isolate-specific avirulence (AVR) effectors from pathogens. NLR genes define the fastest-evolving gene family of flowering plants and are often arranged in gene clusters containing multiple paralogs, contributing to copy number and allele-specific NLR variation within a host species. Barley mildew resistance locus a (Mla) has been subject to extensive functional diversification, resulting in allelic resistance specificities each recognizing a cognate, but largely unidentified, AVRa gene of the powdery mildew fungus, Blumeria graminis f. sp. hordei (Bgh). We applied a transcriptome-wide association study among 17 Bgh isolates containing different AVRa genes and identified AVRa1 and AVRa13, encoding candidate-secreted effectors recognized by Mla1 and Mla13 alleles, respectively. Transient expression of the effector genes in barley leaves or protoplasts was sufficient to trigger Mla1 or Mla13 allele-specific cell death, a hallmark of NLR receptor-mediated immunity. AVRa1 and AVRa13 are phylogenetically unrelated, demonstrating that certain allelic MLA receptors evolved to recognize sequence-unrelated effectors. They are ancient effectors because corresponding loci are present in wheat powdery mildew. AVRA1 recognition by barley MLA1 is retained in transgenic Arabidopsis, indicating that AVRA1 directly binds MLA1 or that its recognition involves an evolutionarily conserved host target of AVRA1. Furthermore, analysis of transcriptome-wide sequence variation among the Bgh isolates provides evidence for Bgh population structure that is partially linked to geographic isolation.

WRKY proteins represent a large family of transcription factors (TF), involved in plant development and defense. In all, 60 unique barley TF have been annotated that contain the WRKY domain; 26 of these are represented on the Barley1 GeneChip. Time-course expression profiles of these 26 HvWRKY TF were analyzed to investigate their role in mildew locus a (Mla)-mediated immunity to Blumeria graminis f. sp. hordei, causal agent of powdery mildew disease. Inoculation-responsive, Mla-specified interactions with B. graminis f. sp. hordei revealed that 12 HvWRKY were differentially expressed: 10 highly upregulated and two significantly downregulated. Barley stripe mosaic virus-induced gene silencing of HvWRKY10, HvWRKY19, and HvWRKY28 compromised resistance-gene-mediated defense to powdery mildew in genotypes harboring both Rar1-dependent and Rar1-independent Mla alleles, indicating that these WRKY TF play key roles in effector-triggered immunity. Comprehensive yeast two-hybrid analyses, however, did not reveal a direct interaction between these three nuclear-localized WRKY TF and MLA. Transient overexpression of all three WRKY TF in single cells expressing Mlo, which encodes a negative regulator of penetration resistance, significantly decreased susceptibility. Taken together, these loss- and gain-of-function studies demonstrate that HvWRKY10, HvWRKY19, and HvWRKY28 positively regulate the barley transcriptome in response to invasion by B. graminis f. sp. hordei.

The use of DNA markers in public sector plant breeding is now the norm. Such markers are common across breeding programs and this commonality enables and enhances collaboration. Therefore, large collaborative research projects that measure several phenotypes across multiple environments coupled with the expanding amount of genotype data attainable with current marker technologies are on the rise and these projects demand effi cient data delivery. However, development of computational tools for advanced data integration, visualization, and analysis is still a bottleneck, even though these resources have the greatest potential impact for users who are extracting and developing hypothesis-based solutions. The Hordeum Toolbox (THT) was developed as a data resource for the Barley Coordinated Agricultural Project (CAP) with the novel capability of constructing user-defi ned downloadable sets of phenotype and/or genotype data for downstream analysis. Internal tools in THT enable users to create clusters of a selected group of lines based on genotype data, parse pedigrees, and select germplasm based on haplotype, phenotype, and agronomic properties. The Hordeum Toolbox can be adapted to breeding programs or collaborations to assist researchers in germplasm selection, genotype data visualization, and the integration of complex data sets for statistical analysis. T RADITIONALLY, plant breeders have collected phenotype data from breeding populations and used it to select for superior genotypes. Data access was limited to individual programs via spreadsheets or in-house databases. Th is approach has been successful in developing novel germplasm and varieties. However, with the exception of the few lines being grown in regional nurseries, the only scientists that had access to these extensive datasets were those that were intimately associated with the programs that generated the data. Th erefore, there was little understanding of the relationship of germplasm between programs, and the ability to share germplasm between programs in an intelligent manner was restricted. Webaccessible databases that contain data on all germplasm within a breeding program provide the opportunity

PLEXdb (http://www.plexdb.org), in partnership with community databases, supports comparisons of gene expression across multiple plant and pathogen species, promoting individuals and/or consortia to upload genome-scale data sets to contrast them to previously archived data. These analyses facilitate the interpretation of structure, function and regulation of genes in economically important plants. A list of Gene Atlas experiments highlights data sets that give responses across different developmental stages, conditions and tissues. Tools at PLEXdb allow users to perform complex analyses quickly and easily. The Model Genome Interrogator (MGI) tool supports mapping gene lists onto corresponding genes from model plant organisms, including rice and Arabidopsis. MGI predicts homologies, displays gene structures and supporting information for annotated genes and full-length cDNAs. The gene list-processing wizard guides users through PLEXdb functions for creating, analyzing, annotating and managing gene lists. Users can upload their own lists or create them from the output of PLEXdb tools, and then apply diverse higher level analyses, such as ANOVA and clustering. PLEXdb also provides methods for users to track how gene expression changes across many different experiments using the Gene OscilloScope. This tool can identify interesting expression patterns, such as up-regulation under diverse conditions or checking any gene's suitability as a steady-state control.

Cytoplasmic male sterility (CMS) is a maternally inherited inability to produce functional pollen. In Texas (T)-cytoplasm maize (Zea mays L.), CMS results from the action of the URF13 mitochondrial pore-forming protein encoded by the unique T-urf13 mitochondrial gene. Full or partial restoration of fertility to T-cytoplasm maize is mediated by the Rf2a nuclear gene in combination with one of three other genes: Rf1, Rf8, or Rf*. Rf2a encodes a mitochondrial aldehyde dehydrogenase whereas Rf1, Rf8, and Rf* are associated with the accumulation of distinctive T-urf13 mitochondrial transcripts. Rf8-associated RNA processing activity was mapped to a 4.55-Mbp region on chromosome 2L that contains 10 pentatricopeptide repeat (PPR) encoding genes in the B73 5b.60 genome assembly. Genetic linkage analysis also indicated that Rf* is positioned within this PPR cluster as well as Rf3, which restores USDA (S)-cytoplasm maize. Partially male-fertile plants segregated for the presence or absence of the Rf8-associated T-urf13 1.42- and 0.42-kbp transcripts, indicating that the RNA processing event associated with these transcripts is not necessary for anther exsertion. In addition, a statistically signifi cant delay in fl owering was observed between partially male-fertile and mostly male-fertile plants. Taken together, these new results indicate that Rf8-mediated male fertility is under the control of more than one nuclear locus. C YTOPLASMIC MALE STERILITY (CMS) is caused by a

Barley Mildew resistance locus a (Mla) is a major determinant of immunity to the powdery mildew pathogen, Blumeria graminis f. sp. hordei. Alleles of Mla encode cytoplasmic- and membrane-localized coiled-coil, nucleotide binding site, leucine-rich repeat proteins that mediate resistance when complementary avirulence effectors (AVRa) are present in the pathogen. Presence of an appropriate AVRa protein triggers nuclear relocalization of MLA, in which MLA binds repressing host transcription factors. Timecourse expression profiles of plants harboring Mla1, Mla6, and Mla12 wild-type alleles versus paired loss-of-function mutants were compared to discover conserved transcriptional targets of MLA and downstream signaling cascades. Pathogen-dependent gene expression was equivalent or stronger in susceptible plants at 20 h after inoculation (HAI) and was attenuated at later timepoints, whereas resistant plants exhibited a time-dependent strengthening of the transcriptional response, increasing in both fold change and the number of genes differentially expressed. Deregulation at 20 HAI implicated 16 HAI as a crucial point in determining the future trajectory of this interaction and was interrogated by quantitative analysis. In total, 28 potential transcriptional targets of the MLA regulon were identified. These candidate targets possess a diverse set of predicted functions, suggesting that multiple pathways are required to mediate the hypersensitive reaction.

The lemma, palea, and awn of a barley (Hordeum vulgare L.) spike are photosynthetic organs that supply the developing seed with carbohydrates. The lemma and palea also enclose the seed and protect it from pathogens and insects. Despite the important roles they play, little information exists on gene expression in these organs that identifi es their function. In this study, we compared gene expression among the lemma, palea, awn, and developing seed of barley during grain fi lling using the Barley1 Genome Array to identify highly expressed genes involved in the primary function of these organs. Hierarchical clustering and mixed model analysis revealed that the lemma and palea have closely related gene expression patterns. In addition, the lemma and palea overexpressed defense-related genes compared with the awn. The awn preferentially expressed genes for photosynthesis, the biosynthesis of chlorophyll and carotenoids, and reactive oxygen species scavenging. This suggests the lemma and palea are mainly protective organs whereas the awn is primarily a photosynthetic structure. The seed was enriched with genes for the biosynthesis of starch, storage proteins, enzyme inhibitors, and cell proliferation. GRAIN FILLING IN CEREALS is characterized by rapid synthesis, transport, and storage of carbohydrates, fatty acids, and proteins in the endosperm (Vicente-Carbajosa and Carbonero, 2005). Carbohydrates for grain fi lling come from three sources: spike (infl orescence) photosynthates, fl ag leaf photosynthates, and reserve mobilization from the stem (Tambussi et al., 2007). Th e contribution of each to the fi nal seed dry weight varies between species, genotypes, and growth conditions. In wheat (Triticum aestivum L.), reserve mobilization accounts for 15 to 30% of seed dry weight (Gebbing and Schnyder, 1999), while in barley (Hordeum vulgare L.) its contribution is less than 8% (Bidinger and Musgrave, 1977; Langer and Hill, 1991). In barley, the major source of carbohydrate for grain fi lling is spike photosynthesis, which accounts for as much as 76% of the seed dry weight (Frey-Wyssling and Buttrose, 1959; Duff us and Cochrane, 1993). Cereal spikes are composed of numerous spikelets, each consisting of multiple fl orets (fl owers). In barley, each fl oret contains a pair of glumes, a lemma, a palea, a pair of lodicules, three stamens and a pistil (Briggs, 1978). Th e palea (on the inside) and the lemma (on the outside, partially enclosing the palea) cover the seed and become a husk when the seed is matured (Fig. 1). Th e lemma has a long slender extension, the awn. Th e lemma, palea and awn are photosynthetic organs and supply the developing seed with carbohydrates (Duff us and Cochrane, 1993). In addition, since the lemma and palea Published in The Plant Genome 2:247–259. Published 5 Nov. 2009. doi: 10.3835/plantgenome2009.07.0019 © Crop Science Society of America 677 S. Segoe Rd., Madison, WI 53711 USA An open-access publication All rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Permission for printing and for reprinting the material contained herein has been obtained by the publisher. T. Abebe, Dep. of Biology, Univ. of Northern Iowa, 191 McCollum Science Hall, Cedar Falls, IA 50614; R.P. Wise, USDA-ARS Corn Insects and Crop Genetics Research, and Dep. of Plant Pathology, Iowa State Univ., 411 Bessey Hall, Ames, IA 50011; R.W. Skadsen, USDA-ARS, Cereal Crops Research Unit, 502 Walnut St., Madison, WI 53726. Received 16 July 2009. *Corresponding author (Tilahun.

The architecture of grass genomes varies on multiple levels. Large long terminal repeat retrotransposon clusters occupy significant portions of the intergenic regions, and islands of protein-encoding genes are interspersed among the repeat clusters. Hence, advanced assembly techniques are required to obtain completely finished genomes as well as to investigate gene and transposable element distributions. To characterize the organization and distribution of repeat clusters and gene islands across large grass genomes, we present 961- and 594-kb contiguous sequence contigs associated with the rf1 (for restorer of fertility1) locus in the near-centromeric region of maize (Zea mays) chromosome 3. We present two methods for computational finishing of highly repetitive bacterial artificial chromosome clones that have proved successful to close all sequence gaps caused by transposable element insertions. Sixteen repeat clusters were observed, ranging in length from 23 to 155 kb. These repeat clusters are almost exclusively long terminal repeat retrotransposons, of which the paleontology of insertion varies throughout the cluster. Gene islands contain from one to four predicted genes, resulting in a gene density of one gene per 16 kb in gene islands and one gene per 111 kb over the entire sequenced region. The two sequence contigs, when compared with the rice (Oryza sativa) and sorghum (Sorghum bicolor) genomes, retain gene colinearity of 50% and 71%, respectively, and 70% and 100%, respectively, for high-confidence gene models. Collinear genes on single gene islands show that while most expansion of the maize genome has occurred in the repeat clusters, gene islands are not immune and have experienced growth in both intragene and intergene locations.

Plant processes resulting from primary or secondary metabolism have been hypothesized to contribute to defense against microbial attack. Barley chorismate synthase (HvCS), anthranilate synthase α subunit 2 (HvASa2), and chorismate mutase 1 (HvCM1) occupy pivotal branch points downstream of the shikimate pathway leading to the synthesis of aromatic amino acids. Here, we provide functional evidence that these genes contribute to penetration resistance to Blumeria graminis f. sp. hordei, the causal agent of powdery mildew disease. Single-cell transient-induced gene silencing of HvCS and HvCM1 in mildew resistance locus a (Mla) compromised cells resulted in increased susceptibility. Correspondingly, overexpression of HvCS, HvASa2, and HvCM1 in lines carrying mildew resistance locus o (Mlo), a negative regulator of penetration resistance, significantly decreased susceptibility. Barley stripe mosaic virus–induced gene silencing of HvCS, HvASa2, and HvCM1 significantly increased B. graminis f. sp. hordei penetration into epidermal cells, followed by formation of haustoria and secondary hyphae. However, sporulation of B. graminis f. sp. hordei was not detected on the silenced host plants up to 3 weeks after inoculation. Taken together, these results establish a previously unrecognized role for the influence of HvCS, HvASa2, and HvCM1 on penetration resistance and on the rate of B. graminis f. sp. hordei development in Mla-mediated, barley–powdery mildew interactions.

Archaeological evidence indicates that barley ( Hordeum vulgare ) and wheat ( Triticum aestivum ) were domesticated 10,000 years ago in the Fertile Crescent ([Zohary and Hopf, 2001][1]). Among the cereals, barley currently ranks fourth after maize ( Zea mays ), rice ( Oryza sativa ), and wheat in

Plants have evolved complex regulatory mechanisms to control the defense response against microbial attack. Both temporal and spatial gene expression are tightly regulated in response to pathogen ingress, modulating both positive and negative control of defense. BLUFENSIN1 (BLN1), a small peptide belonging to a novel family of proteins in barley (Hordeum vulgare), is highly induced by attack from the obligate biotrophic fungus Blumeria graminis f. sp. hordei (Bgh), casual agent of powdery mildew disease. Computational interrogation of the Bln1 gene family determined that members reside solely in the BEP clade of the Poaceae family, specifically, barley, rice (Oryza sativa), and wheat (Triticum aestivum). Barley stripe mosaic virus-induced gene silencing of Bln1 enhanced plant resistance in compatible interactions, regardless of the presence or absence of functional Mla coiled-coil, nucleotide-binding site, Leu-rich repeat alleles, indicating that BLN1 can function in an R-gene-independent manner. Likewise, transient overexpression of Bln1 significantly increased accessibility toward virulent Bgh. Moreover, silencing in plants harboring the Mlo susceptibility factor decreased accessibility to Bgh, suggesting that BLN1 functions in parallel with or upstream of MLO to modulate penetration resistance. Collectively, these data suggest that the grass-specific Bln1 negatively impacts basal defense against Bgh.