Conserved secreted effectors contribute to endophytic growth and multihost plant compatibility in a vascular wilt fungus.

Fungal interactions with plant roots, either beneficial or detrimental, have a crucial impact on agriculture and ecosystems. The cosmopolitan plant pathogen Fusarium oxysporum (Fo) provokes vascular wilts in more than a hundred different crops. Isolates of this fungus exhibit host-specific pathogenicity, which is conferred by lineage-specific Secreted In Xylem (SIX) effectors encoded on accessory genomic regions. However, such isolates also can colonize the roots of other plants asymptomatically as endophytes or even protect them against pathogenic strains. The molecular determinants of endophytic multihost compatibility are largely unknown. Here, we characterized a set of Fo candidate effectors from tomato (Solanum lycopersicum) root apoplastic fluid; these early root colonization (ERC) effectors are secreted during early biotrophic growth on main and alternative plant hosts. In contrast to SIX effectors, ERCs have homologs across the entire Fo species complex as well as in other plant-interacting fungi, suggesting a conserved role in fungus-plant associations. Targeted deletion of ERC genes in a pathogenic Fo isolate resulted in reduced virulence and rapid activation of plant immune responses, while ERC deletion in a nonpathogenic isolate led to impaired root colonization and biocontrol ability. Strikingly, some ERCs contribute to Fo infection on the nonvascular land plant Marchantia polymorpha, revealing an evolutionarily conserved mechanism for multihost colonization by root infecting fungi.

proGenomes3: approaching one million accurately and consistently annotated high-quality prokaryotic genomes.

The interpretation of genomic, transcriptomic and other microbial 'omics data is highly dependent on the availability of well-annotated genomes. As the number of publicly available microbial genomes continues to increase exponentially, the need for quality control and consistent annotation is becoming critical. We present proGenomes3, a database of 907 388 high-quality genomes containing 4 billion genes that passed stringent criteria and have been consistently annotated using multiple functional and taxonomic databases including mobile genetic elements and biosynthetic gene clusters. proGenomes3 encompasses 41 171 species-level clusters, defined based on universal single copy marker genes, for which pan-genomes and contextual habitat annotations are provided. The database is available at http://progenomes.embl.de/.

Convergent Loss of an EDS1/PAD4 Signaling Pathway in Several Plant Lineages Reveals Coevolved Components of Plant Immunity and Drought Response.

Plant innate immunity relies on nucleotide binding leucine-rich repeat receptors (NLRs) that recognize pathogen-derived molecules and activate downstream signaling pathways. We analyzed the variation in NLR gene copy number and identified plants with a low number of NLR genes relative to sister species. We specifically focused on four plants from two distinct lineages, one monocot lineage (Alismatales) and one eudicot lineage (Lentibulariaceae). In these lineages, the loss of NLR genes coincides with loss of the well-known downstream immune signaling complex ENHANCED DISEASE SUSCEPTIBILITY 1 (EDS1)/PHYTOALEXIN DEFICIENT 4 (PAD4). We expanded our analysis across whole proteomes and found that other characterized immune genes were absent only in Lentibulariaceae and Alismatales. Additionally, we identified genes of unknown function that were convergently lost together with EDS1/PAD4 in five plant species. Gene expression analyses in Arabidopsis (Arabidopsis thaliana) and Oryza sativa revealed that several homologs of the candidates are differentially expressed during pathogen infection, drought, and abscisic acid treatment. Our analysis provides evolutionary evidence for the rewiring of plant immunity in some plant lineages, as well as the coevolution of the EDS1/PAD4 pathway and drought responses.

An Improved Assembly of the Albugo candida Ac2V Genome Reveals the Expansion of the "CCG" Class of Effectors.

Albugo candida is an obligate oomycete pathogen that infects many plants in the Brassicaceae family. We resequenced the genome of isolate Ac2V using PacBio long reads and constructed an assembly augmented by Illumina reads. The Ac2VPB genome assembly is 10% larger and more contiguous compared with a previous version. Our annotation of the new assembly, aided by RNA-sequencing information, revealed a 175% expansion (40 to 110) in the CHxC effector class, which we redefined as "CCG" based on motif analysis. This class of effectors consist of arrays of phylogenetically related paralogs residing in gene sparse regions, and shows signatures of positive selection and presence/absence polymorphism. This work provides a resource that allows the dissection of the genomic components underlying A. candida adaptation and, particularly, the role of CCG effectors in virulence and avirulence on different hosts.[Formula: see text] Copyright © 2021 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.

An improved assembly and annotation of the allohexaploid wheat genome identifies complete families of agronomic genes and provides genomic evidence for chromosomal translocations.

Advances in genome sequencing and assembly technologies are generating many high-quality genome sequences, but assemblies of large, repeat-rich polyploid genomes, such as that of bread wheat, remain fragmented and incomplete. We have generated a new wheat whole-genome shotgun sequence assembly using a combination of optimized data types and an assembly algorithm designed to deal with large and complex genomes. The new assembly represents >78% of the genome with a scaffold N50 of 88.8 kb that has a high fidelity to the input data. Our new annotation combines strand-specific Illumina RNA-seq and Pacific Biosciences (PacBio) full-length cDNAs to identify 104,091 high-confidence protein-coding genes and 10,156 noncoding RNA genes. We confirmed three known and identified one novel genome rearrangements. Our approach enables the rapid and scalable assembly of wheat genomes, the identification of structural variants, and the definition of complete gene models, all powerful resources for trait analysis and breeding of this key global crop.

The influence of the local sequence environment on RNA loop structures.

RNA folding is assumed to be a hierarchical process. The secondary structure of an RNA molecule, signified by base-pairing and stacking interactions between the paired bases, is formed first. Subsequently, the RNA molecule adopts an energetically favorable three-dimensional conformation in the structural space determined mainly by the rotational degrees of freedom associated with the backbone of regions of unpaired nucleotides (loops). To what extent the backbone conformation of RNA loops also results from interactions within the local sequence context or rather follows global optimization constraints alone has not been addressed yet. Because the majority of base stacking interactions are exerted locally, a critical influence of local sequence on local structure appears plausible. Thus, local loop structure ought to be predictable, at least in part, from the local sequence context alone. To test this hypothesis, we used Random Forests on a nonredundant data set of unpaired nucleotides extracted from 97 X-ray structures from the Protein Data Bank (PDB) to predict discrete backbone angle conformations given by the discretized η/θ-pseudo-torsional space. Predictions on balanced sets with four to six conformational classes using local sequence information yielded average accuracies of up to 55%, thus significantly better than expected by chance (17%-25%). Bases close to the central nucleotide appear to be most tightly linked to its conformation. Our results suggest that RNA loop structure does not only depend on long-range base-pairing interactions; instead, it appears that local sequence context exerts a significant influence on the formation of the local loop structure.

Sequence-structure relationships in RNA loops: establishing the basis for loop homology modeling.

The specific function of RNA molecules frequently resides in their seemingly unstructured loop regions. We performed a systematic analysis of RNA loops extracted from experimentally determined three-dimensional structures of RNA molecules. A comprehensive loop-structure data set was created and organized into distinct clusters based on structural and sequence similarity. We detected clear evidence of the hallmark of homology present in the sequence-structure relationships in loops. Loops differing by <25% in sequence identity fold into very similar structures. Thus, our results support the application of homology modeling for RNA loop model building. We established a threshold that may guide the sequence divergence-based selection of template structures for RNA loop homology modeling. Of all possible sequences that are, under the assumption of isosteric relationships, theoretically compatible with actual sequences observed in RNA structures, only a small fraction is contained in the Rfam database of RNA sequences and classes implying that the actual RNA loop space may consist of a limited number of unique loop structures and conserved sequences. The loop-structure data sets are made available via an online database, RLooM. RLooM also offers functionalities for the modeling of RNA loop structures in support of RNA engineering and design efforts.

Lost in folding space? Comparing four variants of the thermodynamic model for RNA secondary structure prediction.

BACKGROUND: Many bioinformatics tools for RNA secondary structure analysis are based on a thermodynamic model of RNA folding. They predict a single, "optimal" structure by free energy minimization, they enumerate near-optimal structures, they compute base pair probabilities and dot plots, representative structures of different abstract shapes, or Boltzmann probabilities of structures and shapes. Although all programs refer to the same physical model, they implement it with considerable variation for different tasks, and little is known about the effects of heuristic assumptions and model simplifications used by the programs on the outcome of the analysis. RESULTS: We extract four different models of the thermodynamic folding space which underlie the programs RNAFOLD, RNASHAPES, and RNASUBOPT. Their differences lie within the details of the energy model and the granularity of the folding space. We implement probabilistic shape analysis for all models, and introduce the shape probability shift as a robust measure of model similarity. Using four data sets derived from experimentally solved structures, we provide a quantitative evaluation of the model differences. CONCLUSIONS: We find that search space granularity affects the computed shape probabilities less than the over- or underapproximation of free energy by a simplified energy model. Still, the approximations perform similar enough to implementations of the full model to justify their continued use in settings where computational constraints call for simpler algorithms. On the side, we observe that the rarely used level 2 shapes, which predict the complete arrangement of helices, multiloops, internal loops and bulges, include the "true" shape in a rather small number of predicted high probability shapes. This calls for an investigation of new strategies to extract high probability members from the (very large) level 2 shape space of an RNA sequence. We provide implementations of all four models, written in a declarative style that makes them easy to be modified. Based on our study, future work on thermodynamic RNA folding may make a choice of model based on our empirical data. It can take our implementations as a starting point for further program development.

Modeling RNA loops using sequence homology and geometric constraints.

SUMMARY: RNA loop regions are essential structural elements of RNA molecules influencing both their structural and functional properties. We developed RLooM, a web application for homology-based modeling of RNA loops utilizing template structures extracted from the PDB. RLooM allows the insertion and replacement of loop structures of a desired sequence into an existing RNA structure. Furthermore, a comprehensive database of loops in RNA structures can be accessed through the web interface. AVAILABILITY AND IMPLEMENTATION: The application was implemented in Python, MySQL and Apache. A web interface to the database and loop modeling application is freely available at http://rloom.mpimp-golm.mpg.de CONTACT: schudoma@mpimp-golm.mpg.de; may@mpimp-golm.mpg.de; walther@mpimp-golm.mpg.de

An accessible, efficient and global approach for the large-scale sequencing of bacterial genomes.

We have developed an efficient and inexpensive pipeline for streamlining large-scale collection and genome sequencing of bacterial isolates. Evaluation of this method involved a worldwide research collaboration focused on the model organism Salmonella enterica, the 10KSG consortium. Following the optimization of a logistics pipeline that involved shipping isolates as thermolysates in ambient conditions, the project assembled a diverse collection of 10,419 isolates from low- and middle-income countries. The genomes were sequenced using the LITE pipeline for library construction, with a total reagent cost of less than USD$10 per genome. Our method can be applied to other large bacterial collections to underpin global collaborations.

Detection and characterization of 3D-signature phosphorylation site motifs and their contribution towards improved phosphorylation site prediction in proteins.

BACKGROUND: Phosphorylation of proteins plays a crucial role in the regulation and activation of metabolic and signaling pathways and constitutes an important target for pharmaceutical intervention. Central to the phosphorylation process is the recognition of specific target sites by protein kinases followed by the covalent attachment of phosphate groups to the amino acids serine, threonine, or tyrosine. The experimental identification as well as computational prediction of phosphorylation sites (P-sites) has proved to be a challenging problem. Computational methods have focused primarily on extracting predictive features from the local, one-dimensional sequence information surrounding phosphorylation sites. RESULTS: We characterized the spatial context of phosphorylation sites and assessed its usability for improved phosphorylation site predictions. We identified 750 non-redundant, experimentally verified sites with three-dimensional (3D) structural information available in the protein data bank (PDB) and grouped them according to their respective kinase family. We studied the spatial distribution of amino acids around phosphorserines, phosphothreonines, and phosphotyrosines to extract signature 3D-profiles. Characteristic spatial distributions of amino acid residue types around phosphorylation sites were indeed discernable, especially when kinase-family-specific target sites were analyzed. To test the added value of using spatial information for the computational prediction of phosphorylation sites, Support Vector Machines were applied using both sequence as well as structural information. When compared to sequence-only based prediction methods, a small but consistent performance improvement was obtained when the prediction was informed by 3D-context information. CONCLUSION: While local one-dimensional amino acid sequence information was observed to harbor most of the discriminatory power, spatial context information was identified as relevant for the recognition of kinases and their cognate target sites and can be used for an improved prediction of phosphorylation sites. A web-based service (Phos3D) implementing the developed structure-based P-site prediction method has been made available at (http://phos3d.mpimp-golm.mpg.de).

Comparison of efficiency and specificity of CRISPR-associated (Cas) nucleases in plants: An expanded toolkit for precision genome engineering.

Molecular tools adapted from bacterial CRISPR (Clustered Regulatory Interspaced Short Palindromic Repeats) systems for adaptive immunity have become widely used for plant genome engineering, both to investigate gene functions and to engineer desirable traits. A number of different Cas (CRISPR-associated) nucleases are now used but, as most studies performed to date have engineered different targets using a variety of plant species and molecular tools, it has been difficult to draw conclusions about the comparative performance of different nucleases. Due to the time and effort required to regenerate engineered plants, efficiency is critical. In addition, there have been several reports of mutations at sequences with less than perfect identity to the target. While in some plant species it is possible to remove these so-called 'off-targets' by backcrossing to a parental line, the specificity of genome engineering tools is important when targeting specific members of closely-related gene families, especially when recent paralogues are co-located in the genome and unlikely to segregate. Specificity is also important for species that take years to reach sexual maturity or that are clonally propagated. Here, we directly compare the efficiency and specificity of Cas nucleases from different bacterial species together with engineered variants of Cas9. We find that the nucleotide content of the target correlates with efficiency and that Cas9 from Staphylococcus aureus (SaCas9) is comparatively most efficient at inducing mutations. We also demonstrate that 'high-fidelity' variants of Cas9 can reduce off-target mutations in plants. We present these molecular tools as standardised DNA parts to facilitate their re-use.

Dominant integration locus drives continuous diversification of plant immune receptors with exogenous domain fusions.

BACKGROUND: The plant immune system is innate and encoded in the germline. Using it efficiently, plants are capable of recognizing a diverse range of rapidly evolving pathogens. A recently described phenomenon shows that plant immune receptors are able to recognize pathogen effectors through the acquisition of exogenous protein domains from other plant genes. RESULTS: We show that plant immune receptors with integrated domains are distributed unevenly across their phylogeny in grasses. Using phylogenetic analysis, we uncover a major integration clade, whose members underwent repeated independent integration events producing diverse fusions. This clade is ancestral in grasses with members often found on syntenic chromosomes. Analyses of these fusion events reveals that homologous receptors can be fused to diverse domains. Furthermore, we discover a 43 amino acid long motif associated with this dominant integration clade which is located immediately upstream of the fusion site. Sequence analysis reveals that DNA transposition and/or ectopic recombination are the most likely mechanisms of formation for nucleotide binding leucine rich repeat proteins with integrated domains. CONCLUSIONS: The identification of this subclass of plant immune receptors that is naturally adapted to new domain integration will inform biotechnological approaches for generating synthetic receptors with novel pathogen "baits."

Cloning of the wheat Yr15 resistance gene sheds light on the plant tandem kinase-pseudokinase family.

Yellow rust, caused by Puccinia striiformis f. sp. tritici (Pst), is a devastating fungal disease threatening much of global wheat production. Race-specific resistance (R)-genes are used to control rust diseases, but the rapid emergence of virulent Pst races has prompted the search for a more durable resistance. Here, we report the cloning of Yr15, a broad-spectrum R-gene derived from wild emmer wheat, which encodes a putative kinase-pseudokinase protein, designated as wheat tandem kinase 1, comprising a unique R-gene structure in wheat. The existence of a similar gene architecture in 92 putative proteins across the plant kingdom, including the barley RPG1 and a candidate for Ug8, suggests that they are members of a distinct family of plant proteins, termed here tandem kinase-pseudokinases (TKPs). The presence of kinase-pseudokinase structure in both plant TKPs and the animal Janus kinases sheds light on the molecular evolution of immune responses across these two kingdoms.

Plant immune and growth receptors share common signalling components but localise to distinct plasma membrane nanodomains.

Cell surface receptors govern a multitude of signalling pathways in multicellular organisms. In plants, prominent examples are the receptor kinases FLS2 and BRI1, which activate immunity and steroid-mediated growth, respectively. Intriguingly, despite inducing distinct signalling outputs, both receptors employ common downstream signalling components, which exist in plasma membrane (PM)-localised protein complexes. An important question is thus how these receptor complexes maintain signalling specificity. Live-cell imaging revealed that FLS2 and BRI1 form PM nanoclusters. Using single-particle tracking we could discriminate both cluster populations and we observed spatiotemporal separation between immune and growth signalling platforms. This finding was confirmed by visualising FLS2 and BRI1 within distinct PM nanodomains marked by specific remorin proteins and differential co-localisation with the cytoskeleton. Our results thus suggest that signalling specificity between these pathways may be explained by the spatial separation of FLS2 and BRI1 with their associated signalling components within dedicated PM nanodomains.

blastjs: a BLAST+ wrapper for Node.js.

BACKGROUND: To cope with the ever-increasing amount of sequence data generated in the field of genomics, the demand for efficient and fast database searches that drive functional and structural annotation in both large- and small-scale genome projects is on the rise. The tools of the BLAST+ suite are the most widely employed bioinformatic method for these database searches. Recent trends in bioinformatics application development show an increasing number of JavaScript apps that are based on modern frameworks such as Node.js. Until now, there is no way of using database searches with the BLAST+ suite from a Node.js codebase. RESULTS: We developed blastjs, a Node.js library that wraps the search tools of the BLAST+ suite and thus allows to easily add significant functionality to any Node.js-based application. CONCLUSION: blastjs is a library that allows the incorporation of BLAST+ functionality into bioinformatics applications based on JavaScript and Node.js. The library was designed to be as user-friendly as possible and therefore requires only a minimal amount of code in the client application. The library is freely available under the MIT license at https://github.com/teammaclean/blastjs.

Assessment of drought tolerance and its potential yield penalty in potato.

Climate models predict an increased likelihood of seasonal droughts for many areas of the world. Breeding for drought tolerance could be accelerated by marker-assisted selection. As a basis for marker identification, we studied the genetic variance, predictability of field performance and potential costs of tolerance in potato (Solanum tuberosum L.). Potato produces high calories per unit of water invested, but is drought-sensitive. In 14 independent pot or field trials, 34 potato cultivars were grown under optimal and reduced water supply to determine starch yield. In an artificial dataset, we tested several stress indices for their power to distinguish tolerant and sensitive genotypes independent of their yield potential. We identified the deviation of relative starch yield from the experimental median (DRYM) as the most efficient index. DRYM corresponded qualitatively to the partial least square model-based metric of drought stress tolerance in a stress effect model. The DRYM identified significant tolerance variation in the European potato cultivar population to allow tolerance breeding and marker identification. Tolerance results from pot trials correlated with those from field trials but predicted field performance worse than field growth parameters. Drought tolerance correlated negatively with yield under optimal conditions in the field. The distribution of yield data versus DRYM indicated that tolerance can be combined with average yield potentials, thus circumventing potential yield penalties in tolerance breeding.

A bioinformatics approach to distinguish plant parasite and host transcriptomes in interface tissue by classifying RNA-Seq reads.

BACKGROUND: The genus Cuscuta is a group of parasitic plants that are distributed world-wide. The process of parasitization starts with a Cuscuta plant coiling around the host stem. The parasite's haustorial organs then establish a vascular connection allowing for access to the phloem content. The host and the parasite form new cellular connections, suggesting coordination of developmental and biochemical processes. Simultaneous monitoring of gene expression in the parasite's and host's tissues may shed light on the complex events occurring between the parasitic and host cells and may help to overcome experimental limitations (i.e. how to separate host tissue from Cuscuta tissue at the haustorial connection). A novel approach is to use bioinformatic analysis to classify sequencing reads as either belonging to the host or to the parasite and to characterize the expression patterns. Owing to the lack of a comprehensive genomic dataset from Cuscuta spp., such a classification has not been performed previously. RESULTS: We first classified RNA-Seq reads from an interface region between the non-model parasitic plant Cuscuta japonica and the non-model host plant Impatiens balsamina. Without established reference sequences, we classified reads as originating from either of the plants by stepwise similarity search against de novo assembled transcript sets of C. japonica and I. balsamina, unigene sets of the same genus, and cDNA sequences of the same family. We then assembled de novo transcriptomes from the classified read sets. We assessed the quality of the classification by mapping reads to contigs of both plants, achieving a misclassification rate low enough (0.22-0.39%) to be used reliably for differential gene expression analysis. Finally, we applied our read classification method to RNA-Seq data from the interface between the non-model parasitic plant C. japonica and the model host plant Glycine max. Analysis of gene expression profiles at 5 parasitizing stages revealed differentially expressed genes from both C. japonica and G. max, and uncovered the coordination of cellular processes between the two plants. CONCLUSIONS: We demonstrated that reliable identification of differentially expressed transcripts in undissected interface region of the parasite-host association is feasible and informative with respect to differential-expression patterns.

Endogenous Arabidopsis messenger RNAs transported to distant tissues.

The concept that proteins and small RNAs can move to and function in distant body parts is well established. However, non-cell-autonomy of small RNA molecules raises the question: To what extent are protein-coding messenger RNAs (mRNAs) exchanged between tissues in plants? Here we report the comprehensive identification of 2,006 genes producing mobile RNAs in Arabidopsis thaliana. The analysis of variant ecotype transcripts that were present in heterografted plants allowed the identification of mRNAs moving between various organs under normal or nutrient-limiting conditions. Most of these mobile transcripts seem to follow the phloem-dependent allocation pathway transporting sugars from photosynthetic tissues to roots via the vasculature. Notably, a high number of transcripts also move in the opposite, root-to-shoot direction and are transported to specific tissues including flowers. Proteomic data on grafted plants indicate the presence of proteins from mobile RNAs, allowing the possibility that they may be translated at their destination site. The mobility of a high number of mRNAs suggests that a postulated tissue-specific gene expression profile might not be predictive for the actual plant body part in which a transcript exerts its function.

Give It AGO: The Search for miRNA-Argonaute Sorting Signals in Arabidopsis thaliana Indicates a Relevance of Sequence Positions Other than the 5'-Position Alone.

The specific recognition of miRNAs by Argonaute (AGO) proteins, the effector proteins of the RNA-induced silencing complex, constitutes the final step of the biogenesis of miRNAs and is crucial for their target interaction. In the genome of Arabidopsis thaliana (Ath), 10 different AGO proteins are encoded and the sorting decision, which miRNA associates with which AGO protein, was reported to depend exclusively on the identity of the 5'-sequence position of mature miRNAs. Hence, with only four different bases possible, a 5'-position-only sorting signal would not suffice to specifically target all 10 different AGOs individually or would suggest redundant AGO action. Alternatively, other and as of yet unidentified sorting signals may exist. We analyzed a dataset comprising 117 Ath-miRNAs with clear sorting preference to either AGO1, AGO2, or AGO5 as identified in co-immunoprecipitation experiments combined with sequencing. While mutual information analysis did not identify any other single position but the 5'-nucleotide to be informative for the sorting at sufficient statistical significance, significantly better than random classification results using Random Forests nonetheless suggest that additional positions and combinations thereof also carry information with regard to the AGO sorting. Positions 2, 6, 9, and 13 appear to be of particular importance. Furthermore, uracil bases at defined positions appear to be important for the sorting to AGO2 and AGO5, in particular. No predictive value was associated with miRNA length or base pair binding pattern in the miRNA:miRNA* duplex. From inspecting available AGO gene expression data in Arabidopsis, we conclude that the temporal and spatial expression profile may also contribute to the fine-tuning of miRNA sorting and function.