Since the first reported crop pangenome in 2014, advances in high‐throughput and cost‐effective DNA sequencing technologies facilitated multiple such studies including the pangenomes of oilseed rape (Brassica napus L.), soybean [Glycine max (L.) Merr.], rice (Oryza sativa L.), wheat (Triticum aestivum L.), and barley (Hordeum vulgare L.). Compared with single‐reference genomes, pangenomes provide a more accurate representation of the genetic variation present in a species. By combining the genomic data of multiple accessions, pangenomes allow for the detection and annotation of complex DNA polymorphisms such as structural variations (SVs), one of the major determinants of genetic diversity within a species. In this review we summarize the current literature on crop pangenomics, focusing on their application to find candidate SVs involved in traits of agronomic interest. We then highlight the potential of pangenomes in the discovery and functional characterization of noncoding regulatory sequences and their variations. We conclude with a summary and outlook on innovative data structures representing the complete content of plant pangenomes including annotations of coding and noncoding elements and outcomes of transcriptomic and epigenomic experiments.

The hemibiotrophic fungus Magnaporthe oryzae (Mo) is the causative agent of rice blast and can infect aerial and root tissues of a variety of Poaceae, including the model Brachypodium distachyon (Bd). To gain insight in gene regulation processes occurring at early disease stages, we comparatively analyzed fungal and plant mRNA and sRNA expression in leaves and roots. A total of 310 Mo genes were detected consistently and differentially expressed in both leaves and roots. Contrary to Mo, only minor overlaps were observed in plant differentially expressed genes (DEGs), with 233 Bd-DEGs in infected leaves at 2 days post inoculation (DPI), compared to 4978 at 4 DPI, and 138 in infected roots. sRNA sequencing revealed a broad spectrum of Mo-sRNAs that accumulated in infected tissues, including candidates predicted to target Bd mRNAs. Conversely, we identified a subset of potential Bd-sRNAs directed against fungal cell wall components, virulence genes and transcription factors. We also show a requirement of operable RNAi genes from the DICER-like (DCL) and ARGONAUTE (AGO) families for fungal virulence. Overall, our work elucidates the extensive reprogramming of transcriptomes and sRNAs in both plant host (Bd) and fungal pathogen (Mo), further corroborating the critical role played by sRNA species in the establishment of the interaction and its outcome.

Small RNA (sRNA) molecules are key factors in the communication between hosts and their interacting pathogens, where they function as effectors that can modulate both host defense and microbial virulence/pathogenicity through a mechanism termed cross-kingdom RNA interference (ck-RNAi). Consistent with this recent knowledge, sRNAs and their double-stranded RNA precursor have been adopted to control diseases in crop plants, demonstrating a straight forward application of the new findings to approach agricultural problems. Despite the great interest in natural ck-RNAi, it is astonishing to find just a few additional examples in the literature since the first report was published in 2013. One reason might be that the identification of sRNA effectors is hampered both by technical challenges and lack of routine bioinformatics application strategies. Here, we suggest a practical procedure to find, characterize, and validate sRNA effectors in plant–microbe interaction. The aim of this review is not to present and discuss all possible tools, but to give guidelines toward the best established software available for the analysis.

Arbuscular mycorrhiza (AM) is one of the most spread symbiosis established between 80% of land plants and soil fungi belonging to the Glomeromycota. Molecular determinants involved in the formation of arbuscular mycorrhizas are still poorly understood. It has been demonstrated that in both Legumes and rice plants, several GRAS transcription factors are directly involved in both mycorrhizal signaling and colonization, namely NSP1, NSP2, RAM1, DELLA, DELLA-interacting protein (DIP1) and RAD1. Here, we focused on a rice GRAS protein, named Arbuscular Mycorrhizal 18 (OsAM18), previously identified as specifically expressed in rice mycorrhizal roots, and considered as an AM-specific gene. Phylogenetic analysis revealed that OsAM18 had a peculiar amino acid sequence, which clustered with putative SCARECROW proteins, even though it formed a separate branch. Allelic osma18 mutant displayed a drastic reduction in mycorrhizal colonization intensity and in arbuscule abundance, as mirrored by OsPT11 expression level. Non-mycorrhizal osam18 plants displayed a comparable plant development and root apparatus compared with the WT, while mycorrhizal osam18 mutants showed a reduction of plant biomass compared with mycorrhizal WT plants. The results suggest that OsAM18 is a rice protein, which is likely to have an impact not only on the colonization process and AM functionality, but also on the systemic effects of the AM symbiosis.

Background Beneficial associations between plants and microbes are widespread in nature and have been studied extensively in the microbial-dominant environment of the rhizosphere. Such associations are highly advantageous for the organisms involved, benefiting soil microbes by providing them access to plant metabolites, while plant growth and development are enhanced through the promotion of nutrient uptake and/or protection against (a)biotic stresses. While the establishment and maintenance of mutualistic associations have been shown to require genetic and epigenetic reprogramming, as well as an exchange of effector molecules between microbes and plants, whether short RNAs are able to effect such changes is currently unknown. Here, we established an interaction between the model grass species Brachypodium distachyon (Bd, Pooideae) and the beneficial fungal root endophyte Serendipita indica (Si, syn. Piriformospora indica, Sebacinales) to elucidate RNA interference-based regulatory changes in gene expression and small (s)RNA profiles that occurred during establishment of a Sebacinalean symbiosis. Results Colonization of Bd roots with Si resulted in higher grain yield, confirming the mutualistic character of this interaction. Resequencing of the Si genome using the Oxford Nanopore technique, followed by de novo assembly yielded in 57 contigs and 9441 predicted genes, including putative members of several families involved in sRNA production. Transcriptome analysis at an early stage of the mutualistic interaction identified 2963 differentially expressed genes (DEG) in Si and 317 in Bd line 21-3. The fungal DEGs were largely associated with carbohydrate metabolism, cell wall degradation, and nutrient uptake, while plant DEGs indicated modulation of (a)biotic stress responses and defense pathways. Additionally, 10% of the upregulated fungal DEGs encode candidate protein effectors, including six DELD proteins typical for Sebacinales. Analysis of the global changes in the sRNA profiles of both associated organisms revealed several putative endogenous plant sRNAs expressed during colonization belonging to known micro (mi)RNA families involved in growth and developmental regulation. Among Bd- and Si-generated sRNAs with putative functions in the interacting organism, we identified transcripts for proteins involved in circadian clock and flowering regulation as well as immunity as potential targets of fungal sRNAs, reflecting the beneficial activity of Si. Conclusions We detected beneficial effects of Si colonization on Bd growth and development, and established a novel plant-mutualist interaction model between these organisms. Together, the changes in gene expression and identification of interaction-induced sRNAs in both organisms support sRNA-based regulation of defense responses and plant development in Bd, as well as nutrient acquisition and cell growth in Si. Our data suggests that a Sebacinalean symbiosis involves reciprocal sRNA targeting of genes during the interaction.

26Microbial pathogens secrete small RNA (sRNA) effectors into plant hosts to aid infection by 27 silencing transcripts of immunity and signaling-related genes through RNA interference (RNAi). 28 Similarly, sRNAs from plant hosts have been shown to contribute to plant defense against microbial 29 pathogens by targeting transcripts involved in virulence. This phenomenon is called bidirectional 30 RNA communication or cross kingdom RNAi (ckRNAi). How far this RNAi-mediated mechanism 31 is evolutionarily conserved is the subject of controversial discussions. We examined the 32 bidirectional accumulation of sRNAs in the interaction of the hemibiotrophic rice blast fungus 33 Magnaporthe oryzae (Mo) with the grass model plant Brachypodium distachyon (Bd). By 34 comparative deep sequencing of sRNAs and mRNAs from axenic fungal cultures and infected leaves 35and roots, we found a wide range of fungal sRNAs that accumulated exclusively in infected tissues. 36Amongst those, 20-21 nt candidate sRNA effectors were predicted in silico by selecting those Mo 37 reads that had complementary mRNA targets in Bd. Many of those mRNAs predicted to be targeted 38 by Mo sRNAs were differentially expressed, particularly in the necrotrophic infection phase, 39 including gene transcripts involved in plant defense responses and signaling. Vice versa, by applying 40 the same strategy to identify Bd sRNA effectors, we found that Bd produced sRNAs targeting a 41 variety of fungal transcripts, encoding fungal cell wall components, virulence genes and 42 transcription factors. Consistent with function as effectors of these Bd sRNAs, their predicted fungal 43 targets were significantly down-regulated in the infected tissues compared to axenic cultures, and 44 deletion mutants for some of these target genes showed heavily impaired virulence phenotypes. 45Overall, this study provides the first experimentally-based evidence for bidirectional ckRNAi in a 46 grass-fungal pathosystem, paving the way for further validation of identified sRNA-target duplexes 47 and contributing to the emerging research on naturally occurring cross-kingdom communication and 48 its implications for agriculture on staple crops.In the present work, we provide first experimental evidence for bidirectional RNA communication 53 in a grass-fungal pathosystem. We deployed the monocotyledonous plant Brachypodium distachyon, 54 which is a genetic model for the staple crops wheat and rice, to investigate the interaction-related 55 sRNAs for their role in RNA communication. By applying a previously published bioinformatics 56 pipeline for the detection of sRNA effectors we identified potential plant targets for fungal sRNAs 57 and vice versa, fungal targets for plant sRNAs. Inspection of the respective targets confirmed their 58 downregulation in infected relative to uninfected tissues and fungal axenic cultures, respectively. 59 By focusing on potential fungal targets, we identified several genes encoding fungal cell wall 60 components, virulence proteins and transcription ...

RNA interference (RNAi) is a biological process in which small RNAs regulate gene silencing at the transcriptional or posttranscriptional level. The trigger for gene silencing is double-stranded RNA generated from an endogenous genomic locus or a foreign source, such as a transgene or virus. In addition to regulating endogenous gene expression, RNAi provides the mechanistic basis for small RNA-mediated communication between plant hosts and interacting pathogenic microbes, known as cross-kingdom RNAi. Two core protein components, Argonaute (AGO) and Dicer (DCL), are central to the RNAi machinery of eukaryotes. Plants encode for several copies of AGO and DCL genes; in Arabidopsis thaliana, the AGO protein family contains 10 members, and the DCL family contains four. Little is known about the conservation and specific roles of these proteins in monocotyledonous plants, which account for the most important food staples. Here, we utilized in silico tools to investigate the structure and related functions of AGO and DCL proteins from the model grass Brachypodium distachyon. Based on the presence of characteristic domains, 16 BdAGO- and 6 BdDCL-predicted proteins were identified. Phylogenetic analysis showed that both protein families were expanded in Brachypodium as compared with Arabidopsis. For BdDCL proteins, both plant species contain a single copy of DCL1 and DCL4; however, Brachypodium contains two copies each of DCL2 and DCL3. Members of the BdAGO family were placed in all three functional clades of AGO proteins previously described in Arabidopsis. The greatest expansion occurred in the AtAGO1/5/10 clade, which contains nine BdAGOs (BdAGO5/6/7/9/10/11/12/15/16). The catalytic tetrad of the AGO P-element-induced wimpy testis domain (PIWI), which is required for endonuclease activity, is conserved in most BdAGOs, with the exception of BdAGO1, which lacks the last D/H residue. Three-dimensional modeling of BdAGO proteins using tertiary structure prediction software supported the phylogenetic classification. We also predicted a provisional interactome network for BdAGOs, their localization within the cell, and organ/tissue-specific expression. Exploring the specifics of RNAi machinery proteins in a model grass species can serve as a proxy for agronomically important cereals such as barley and wheat, where the development of RNAi-based plant protection strategies is of great interest.

Structural variations (SVs) are larger polymorphisms (>50 bp in length), which consist of insertions, deletions, inversions, duplications, and translocations. They can have a strong impact on agronomical traits and play an important role in environmental adaptation. The development of long-read sequencing technologies, including Oxford Nanopore, allows for comprehensive SV discovery and characterization even in complex polyploid crop genomes. However, many of the SV discovery pipeline benchmarks do not include complex plant genome datasets. In this study, we benchmarked popular long-read alignment-based SV detection tools for crop plant genomes. We used real and simulated Oxford Nanopore reads for two crops, allotetraploid Brassica napus (oilseed rape) and diploid Solanum lycopersicum (tomato), and evaluated several read aligners and SV callers across 5x, 10x, and 20x coverages typically used in re-sequencing studies. Our benchmarks provide a useful guide for designing Oxford Nanopore re-sequencing projects and SV discovery pipelines for crop plants.