Endophytic fungi related to the ash dieback causal agent encode signatures of pathogenicity on European ash.

Tree diseases constitute a significant threat to biodiversity worldwide. Pathogen discovery in natural habitats is of vital importance to understanding current and future threats and prioritising efforts towards developing disease management strategies. Ash dieback is a fungal disease of major conservational concern that is infecting common ash trees, Fraxinus excelsior, in Europe. The disease is caused by a non-native fungal pathogen, Hymenoscyphus fraxineus. Other dieback causing-species have not previously been identified in the genus Hymenoscyphus. Here, we discover the pathogenicity potential of two newly identified related species of Asian origin, H. koreanus and H. occultus, and one Europe-native related species, H. albidus. We sequence the genomes of all three Hymenoscyphus species and compare them to that of H. fraxineus. Phylogenetic analysis of core eukaryotic genes identified H. albidus and H. koreanus as sister species, whilst H. occultus diverged prior to these and H. fraxineus. All four Hymenoscyphus genomes are of comparable size (55-62 Mbp) and GC contents (42-44%) and encode for polymorphic secretomes. Surprisingly, 1133 predicted secreted proteins are shared between the ash dieback pathogen H. fraxineus and the three related Hymenoscyphus endophytes. Amongst shared secreted proteins are cell death-inducing effector candidates, such as necrosis, and ethylene-inducing peptide 1-like proteins, Nep1-like proteins, that are upregulated during in planta growth of all Hymenoscyphus species. Indeed, pathogenicity tests showed that all four related Hymenoscyphus species develop pathogenic growth on European ash stems, with native H. albidus being the least virulent. Our results identify the threat Hymenoscypohus species pose to the survival of European ash trees, and highlight the importance of promoting pathogen surveillance in environmental landscapes. Identifying new pathogens and including them in the screening for durable immunity of common ash trees is key to the long-term survival of ash in Europe.

Profile of the in silico secretome of the palm dieback pathogen, Fusarium oxysporum f. sp. albedinis, a fungus that puts natural oases at risk.

Understanding biotic changes that occur alongside climate change constitute a research priority of global significance. Here, we address a plant pathogen that poses a serious threat to life on natural oases, where climate change is already taking a toll and severely impacting human subsistence. Fusarium oxysporum f. sp. albedinis is a pathogen that causes dieback disease on date palms, a tree that provides several critical ecosystem services in natural oases; and consequently, of major importance in this vulnerable habitat. Here, we assess the current state of global pathogen spread, we annotate the genome of a sequenced pathogen strain isolated from the native range and we analyse its in silico secretome. The palm dieback pathogen secretes a large arsenal of effector candidates including a variety of toxins, a distinguished profile of secreted in xylem proteins (SIX) as well as an expanded protein family with an N-terminal conserved motif [SG]PC[KR]P that could be involved in interactions with host membranes. Using agrobiodiversity as a strategy to decrease pathogen infectivity, while providing short term resilient solutions, seems to be widely overcome by the pathogen. Hence, the urgent need for future mechanistic research on the palm dieback disease and a better understanding of pathogen genetic diversity.

Bakta: rapid and standardized annotation of bacterial genomes via alignment-free sequence identification.

Command-line annotation software tools have continuously gained popularity compared to centralized online services due to the worldwide increase of sequenced bacterial genomes. However, results of existing command-line software pipelines heavily depend on taxon-specific databases or sufficiently well annotated reference genomes. Here, we introduce Bakta, a new command-line software tool for the robust, taxon-independent, thorough and, nonetheless, fast annotation of bacterial genomes. Bakta conducts a comprehensive annotation workflow including the detection of small proteins taking into account replicon metadata. The annotation of coding sequences is accelerated via an alignment-free sequence identification approach that in addition facilitates the precise assignment of public database cross-references. Annotation results are exported in GFF3 and International Nucleotide Sequence Database Collaboration (INSDC)-compliant flat files, as well as comprehensive JSON files, facilitating automated downstream analysis. We compared Bakta to other rapid contemporary command-line annotation software tools in both targeted and taxonomically broad benchmarks including isolates and metagenomic-assembled genomes. We demonstrated that Bakta outperforms other tools in terms of functional annotations, the assignment of functional categories and database cross-references, whilst providing comparable wall-clock runtimes. Bakta is implemented in Python 3 and runs on MacOS and Linux systems. It is freely available under a GPLv3 license at https://github.com/oschwengers/bakta. An accompanying web version is available at https://bakta.computational.bio.

Fusarium graminearum DICER-like-dependent sRNAs are required for the suppression of host immune genes and full virulence.

In filamentous fungi, gene silencing by RNA interference (RNAi) shapes many biological processes, including pathogenicity. Recently, fungal small RNAs (sRNAs) have been shown to act as effectors that disrupt gene activity in interacting plant hosts, thereby undermining their defence responses. We show here that the devastating mycotoxin-producing ascomycete Fusarium graminearum (Fg) utilizes DICER-like (DCL)-dependent sRNAs to target defence genes in two Poaceae hosts, barley (Hordeum vulgare, Hv) and Brachypodium distachyon (Bd). We identified 104 Fg-sRNAs with sequence homology to host genes that were repressed during interactions of Fg and Hv, while they accumulated in plants infected by the DCL double knock-out (dKO) mutant PH1-dcl1/2. The strength of target gene expression correlated with the abundance of the corresponding Fg-sRNA. Specifically, the abundance of three tRNA-derived fragments (tRFs) targeting immunity-related Ethylene overproducer 1-like 1 (HvEOL1) and three Poaceae orthologues of Arabidopsis thaliana BRI1-associated receptor kinase 1 (HvBAK1, HvSERK2 and BdSERK2) was dependent on fungal DCL. Additionally, RNA-ligase-mediated Rapid Amplification of cDNA Ends (RLM-RACE) identified infection-specific degradation products for the three barley gene transcripts, consistent with the possibility that tRFs contribute to fungal virulence via targeted gene silencing.

EDGAR3.0: comparative genomics and phylogenomics on a scalable infrastructure.

The EDGAR platform, a web server providing databases of precomputed orthology data for thousands of microbial genomes, is one of the most established tools in the field of comparative genomics and phylogenomics. Based on precomputed gene alignments, EDGAR allows quick identification of the differential gene content, i.e. the pan genome, the core genome, or singleton genes. Furthermore, EDGAR features a wide range of analyses and visualizations like Venn diagrams, synteny plots, phylogenetic trees, as well as Amino Acid Identity (AAI) and Average Nucleotide Identity (ANI) matrices. During the last few years, the average number of genomes analyzed in an EDGAR project increased by two orders of magnitude. To handle this massive increase, a completely new technical backend infrastructure for the EDGAR platform was designed and launched as EDGAR3.0. For the calculation of new EDGAR3.0 projects, we are now using a scalable Kubernetes cluster running in a cloud environment. A new storage infrastructure was developed using a file-based high-performance storage backend which ensures timely data handling and efficient access. The new data backend guarantees a memory efficient calculation of orthologs, and parallelization has led to drastically reduced processing times. Based on the advanced technical infrastructure new analysis features could be implemented including POCP and FastANI genomes similarity indices, UpSet intersecting set visualization, and circular genome plots. Also the public database section of EDGAR was largely updated and now offers access to 24,317 genomes in 749 free-to-use projects. In summary, EDGAR 3.0 provides a new, scalable infrastructure for comprehensive microbial comparative gene content analysis. The web server is accessible at http://edgar3.computational.bio.

SIGS vs HIGS: a study on the efficacy of two dsRNA delivery strategies to silence Fusarium FgCYP51 genes in infected host and non-host plants.

CYP3RNA, a double-stranded (ds)RNA designed to concomitantly target the two sterol 14α-demethylase genes FgCYP51A and FgCYP51B and the fungal virulence factor FgCYP51C, inhibits the growth of the ascomycete fungus Fusarium graminearum (Fg) in vitro and in planta. Here we compare two different methods (setups) of dsRNA delivery, viz. transgene expression (host-induced gene silencing, HIGS) and spray application (spray-induced gene silencing, SIGS), to assess the activity of CYP3RNA and novel dsRNA species designed to target one or two FgCYP51 genes. Using Arabidopsis and barley, we found that dsRNA designed to target two FgCYP51 genes inhibited fungal growth more efficiently than dsRNA targeting a single gene, although both dsRNA species reduced fungal infection. Either dsRNA delivery method reduced fungal growth stronger than anticipated from previous mutational knock-out (KO) strategies, where single gene KO had no significant effect on fungal viability. Consistent with the strong inhibitory effects of the dsRNAs on fungal development in both setups, we detected to a large extent dsRNA-mediated co-silencing of respective non-target FgCYP51 genes. Together, our data further support the valuation that dsRNA applications have an interesting potential for pesticide target validation and gene function studies, apart from their potential for crop protection.

A Bioinformatics Pipeline for the Analysis and Target Prediction of RNA Effectors in Bidirectional Communication During Plant-Microbe Interactions.

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.

An RNAi-Based Control of Fusarium graminearum Infections Through Spraying of Long dsRNAs Involves a Plant Passage and Is Controlled by the Fungal Silencing Machinery.

Meeting the increasing food and energy demands of a growing population will require the development of ground-breaking strategies that promote sustainable plant production. Host-induced gene silencing has shown great potential for controlling pest and diseases in crop plants. However, while delivery of inhibitory noncoding double-stranded (ds)RNA by transgenic expression is a promising concept, it requires the generation of transgenic crop plants which may cause substantial delay for application strategies depending on the transformability and genetic stability of the crop plant species. Using the agronomically important barley-Fusarium graminearum pathosystem, we alternatively demonstrate that a spray application of a long noncoding dsRNA (791 nt CYP3-dsRNA), which targets the three fungal cytochrome P450 lanosterol C-14α-demethylases, required for biosynthesis of fungal ergosterol, inhibits fungal growth in the directly sprayed (local) as well as the non-sprayed (distal) parts of detached leaves. Unexpectedly, efficient spray-induced control of fungal infections in the distal tissue involved passage of CYP3-dsRNA via the plant vascular system and processing into small interfering (si)RNAs by fungal DICER-LIKE 1 (FgDCL-1) after uptake by the pathogen. We discuss important consequences of this new finding on future RNA-based disease control strategies. Given the ease of design, high specificity, and applicability to diverse pathogens, the use of target-specific dsRNA as an anti-fungal agent offers unprecedented potential as a new plant protection strategy.

DistAMo: A Web-Based Tool to Characterize DNA-Motif Distribution on Bacterial Chromosomes.

Short DNA motifs are involved in a multitude of functions such as for example chromosome segregation, DNA replication or mismatch repair. Distribution of such motifs is often not random and the specific chromosomal pattern relates to the respective motif function. Computational approaches which quantitatively assess such chromosomal motif patterns are necessary. Here we present a new computer tool DistAMo (Distribution Analysis of DNA Motifs). The algorithm uses codon redundancy to calculate the relative abundance of short DNA motifs from single genes to entire chromosomes. Comparative genomics analyses of the GATC-motif distribution in γ-proteobacterial genomes using DistAMo revealed that (i) genes beside the replication origin are enriched in GATCs, (ii) genome-wide GATC distribution follows a distinct pattern, and (iii) genes involved in DNA replication and repair are enriched in GATCs. These features are specific for bacterial chromosomes encoding a Dam methyltransferase. The new software is available as a stand-alone or as an easy-to-use web-based server version at http://www.computational.bio.uni-giessen.de/distamo.

Genome analysis of the sugar beet pathogen Rhizoctonia solani AG2-2IIIB revealed high numbers in secreted proteins and cell wall degrading enzymes.

BACKGROUND: Sugar beet (Beta vulgaris) is a crop cultivated for its high content in sugar, but it is vulnerable to many soil-borne pathogens. One of them is the basidiomycete Rhizoctonia solani. This fungal species has a compatibility system regulating hyphal fusions (anastomosis). Consequently, R. solani species are categorized in anastomosis groups (AGs). AG2-2IIIB isolates are most aggressive on sugar beet. In the present study, we report on the draft genome of R. solani AG2-2IIIB using the Illumina technology. Genome analysis, interpretation and comparative genomics of five sequenced R. solani isolates were carried out. RESULTS: The draft genome of R. solani AG2-2IIIB has an estimated size of 56.02 Mb. In addition, two normalized EST libraries were sequenced. In total 20,790 of 21,980 AG2-2IIIB isotigs (transcript isoforms) were mapped on the genome with more than 95 % sequence identity. The genome of R. solani AG2-2IIIB was predicted to harbor 11,897 genes and 4908 were found to be isolate-specific. R. solani AG2-2IIIB was predicted to contain 1142 putatively secreted proteins and 473 of them were found to be unique for this isolate. The R. solani AG2-2IIIB genome encodes a high number of carbohydrate active enzymes. The highest numbers were observed for the polysaccharide lyases family 1 (PL-1), glycoside hydrolase family 43 (GH-43) and carbohydrate estarase family 12 (CE-12). Transcription analysis of selected genes representing different enzyme clades revealed a mixed pattern of up- and down-regulation six days after infection on sugar beets featuring variable levels of resistance compared to mycelia of the fungus grown in vitro. CONCLUSIONS: The established R. solani AG2-2IIIB genome and EST sequences provide important information on the gene content, gene structure and transcriptional activity for this sugar beet pathogen. The enriched genomic platform provides an important platform to enhance our understanding of R. solani biology.

Comparison of Acceleration Techniques for Selected Low-Level Bioinformatics Operations.

Within the recent years clock rates of modern processors stagnated while the demand for computing power continued to grow. This applied particularly for the fields of life sciences and bioinformatics, where new technologies keep on creating rapidly growing piles of raw data with increasing speed. The number of cores per processor increased in an attempt to compensate for slight increments of clock rates. This technological shift demands changes in software development, especially in the field of high performance computing where parallelization techniques are gaining in importance due to the pressing issue of large sized datasets generated by e.g., modern genomics. This paper presents an overview of state-of-the-art manual and automatic acceleration techniques and lists some applications employing these in different areas of sequence informatics. Furthermore, we provide examples for automatic acceleration of two use cases to show typical problems and gains of transforming a serial application to a parallel one. The paper should aid the reader in deciding for a certain techniques for the problem at hand. We compare four different state-of-the-art automatic acceleration approaches (OpenMP, PluTo-SICA, PPCG, and OpenACC). Their performance as well as their applicability for selected use cases is discussed. While optimizations targeting the CPU worked better in the complex k-mer use case, optimizers for Graphics Processing Units (GPUs) performed better in the matrix multiplication example. But performance is only superior at a certain problem size due to data migration overhead. We show that automatic code parallelization is feasible with current compiler software and yields significant increases in execution speed. Automatic optimizers for CPU are mature and usually no additional manual adjustment is required. In contrast, some automatic parallelizers targeting GPUs still lack maturity and are limited to simple statements and structures.

Development of a Rhizoctonia solani AG1-IB Specific Gene Model Enables Comparative Genome Analyses between Phytopathogenic R. solani AG1-IA, AG1-IB, AG3 and AG8 Isolates.

Rhizoctonia solani, a soil-born plant pathogenic basidiomycetous fungus, affects various economically important agricultural and horticultural crops. The draft genome sequence for the R. solani AG1-IB isolate 7/3/14 as well as a corresponding transcriptome dataset (Expressed Sequence Tags--ESTs) were established previously. Development of a specific R. solani AG1-IB gene model based on GMAP transcript mapping within the eukaryotic gene prediction platform AUGUSTUS allowed detection of new genes and provided insights into the gene structure of this fungus. In total, 12,616 genes were recognized in the genome of the AG1-IB isolate. Analysis of predicted genes by means of different bioinformatics tools revealed new genes whose products potentially are involved in degradation of plant cell wall components, melanin formation and synthesis of secondary metabolites. Comparative genome analyses between members of different R. solani anastomosis groups, namely AG1-IA, AG3 and AG8 and the newly annotated R. solani AG1-IB genome were performed within the comparative genomics platform EDGAR. It appeared that only 21 to 28% of all genes encoded in the draft genomes of the different strains were identified as core genes. Based on Average Nucleotide Identity (ANI) and Average Amino-acid Identity (AAI) analyses, considerable sequence differences between isolates representing different anastomosis groups were identified. However, R. solani isolates form a distinct cluster in relation to other fungi of the phylum Basidiomycota. The isolate representing AG1-IB encodes significant more genes featuring predictable functions in secondary metabolite production compared to other completely sequenced R. solani strains. The newly established R. solani AG1-IB 7/3/14 gene layout now provides a reliable basis for post-genomics studies.

Improved genome sequence of the phytopathogenic fungus Rhizoctonia solani AG1-IB 7/3/14 as established by deep mate-pair sequencing on the MiSeq (Illumina) system.

The phytopathogenic fungus Rhizoctonia solani AG1-IB of the phylum Basidiomycota affects various economically important crops comprising bean, rice, soybean, figs, cabbage and lettuce. The R. solani isolate 7/3/14 of the anastomosis group AG1-IB was deeply resequenced on the Illumina MiSeq system applying the mate-pair mode to improve its genome sequence. Assembly of obtained sequence reads significantly reduced the amount of scaffolds and improved the genome sequence of the isolate compared to the previous sequencing approach. The genome sequence of the AG1-IB isolate 7/3/14 now provides an up-graded basis to analyze genome features predicted to play a role in pathogenesis and for the development of strategies to antagonize the pathogenic impact of this fungus.

Transcriptome analysis of the phytopathogenic fungus Rhizoctonia solani AG1-IB 7/3/14 applying high-throughput sequencing of expressed sequence tags (ESTs).

Rhizoctonia solani is a soil-borne plant pathogenic fungus of the phylum Basidiomycota. It affects a wide range of agriculturally important crops and hence is responsible for economically relevant crop losses. Transcriptome analysis of the bottom rot pathogen R. solani AG1-1B (isolate 7/3/14) by applying high-throughput sequencing and bioinformatics methods addressing Expressed Sequence Tag (EST) data interpretation provided new insights in expressed genes of this fungus. Two normalized cDNA libraries representing different cultivation conditions of the fungus were sequenced on the 454 FLX (Roche) system. Subsequent to cDNA sequence assembly and quality control, ESTs were analysed applying advanced bioinformatics methods. More than 14 000 transcript isoforms originating from approximately 10 000 predictable R. solani AG1-IB 7/3/14 genes are represented in each dataset. Comparative analyses revealed several differentially expressed genes depending on the growth conditions applied. Determinants with predicted functions in recognition processes between the fungus and the host plant were identified. Moreover, many R. solani AG1-IB ESTs were predicted to encode putative cellulose, pectin, and lignin degrading enzymes. Furthermore, genes playing a possible role in mitogen-activated protein (MAP) kinase cascades, 4-aminobutyric acid (GABA) metabolism, melanin synthesis, plant defence antagonism, phytotoxin, and mycotoxin synthesis were detected.

Effector candidates in the secretome of Piriformospora indica, a ubiquitous plant-associated fungus.

One of the emerging systems in plant-microbe interaction is the study of proteins, referred to as effectors, secreted by microbes in order to modulate host cells function and structure and to promote microbial growth on plant tissue. Current knowledge on fungal effectors derives mainly from biotrophic and hemibiotrophic plant fungal pathogens that have a limited host range. Here, we focus on effectors of Piriformospora indica, a soil borne endophyte forming intimate associations with roots of a wide range of plant species. Complete genome sequencing provides an opportunity to investigate the role of effectors during the interaction of this mutualistic fungus with plants. We describe in silico analyses to predict effectors of P. indica and we explore effector features considered here to mine a high priority protein list for functional analysis.

Establishment and interpretation of the genome sequence of the phytopathogenic fungus Rhizoctonia solani AG1-IB isolate 7/3/14.

Anastomosis group AG1-IB isolates of the anamorphic basidiomycetous fungus Rhizoctonia solani Kühn affect various agricultural and horticultural important crops including bean, rice, soybean, figs, hortensia, cabbage and lettuce. To gain insights into the genome structure and content, the first draft genome sequence of R. solani AG1-IB isolate 7/3/14 was established. Four complete runs on the Genome Sequencer (GS) FLX platform (Roche Applied Science) yielding approx. a 25-fold coverage of the R. solani genome were accomplished. Assembly of the sequence reads by means of the gsAssembler software version 2.6 applying the heterozygotic mode resulted in numerous contigs and scaffolds and a predicted size of 87.1 Mb for the diploid status of the genome. 'Contig-length vs. read-count' analysis revealed that the assembled contigs can be classified into five different groups. Detailed BLAST-analysis revealed that most contigs of group II feature high-scoring matches to other contigs of the same group suggesting that distinguishable allelic variants exist for many genes. Due to the supposed diploid and heterokaryotic nature of R. solani AG1-IB 7/3/14, this result has been anticipated. However, the heterokaryotic character of the isolate is not really supported by sequencing data obtained for the isolate R. solani AG1-IB 7/3/14. Coverage of group III contigs is twice as high as for group II contigs which can also be explained by the diploid status of the genome and indistinguishable alleles on homologous chromosomes. Assembly of sequence data led to the identification of the rRNA unit (group V contigs) and the mitochondrial (mt) genome (group IV contigs) which is a circular molecule of 162,751 bp in size featuring a GC-content of 36.4%. The R. solani 7/3/14 mt-genome is one of the largest fungal mitochondrial genomes known to date. Its large size essentially is due to the presence of numerous non-conserved hypothetical ORFs and introns. Gene prediction for the R. solani AG1-IB 7/3/14 genome was conducted by the Augustus Gene Prediction Software for Eukaryotes (version 2.6.) applying the parameter set for the fungus Coprinopsis cinerea okayama 7#130. Gene prediction and annotation provided first insights into the R. solani AG1-IB 7/3/14 gene structure and content. In total, 12,422 genes were predicted. The average number of exons per gene is five. Exons have a mean length of 214 bp, whereas introns on average are 66 bp in length. Annotation of the genome revealed that 4169 of 12,422 genes could be assigned to KOG functional categories.