EVENTS aims to investigate both the positive and negative impacts of endogenous viral elements (EVEs) on plant metabolism. EVEs are viral sequences that are integrated in the genomes of their hosts. In plants, most characterized EVEs originate from viruses in the families Caulimoviridae and Geminiviridae, which have DNA genomes, following passive horizontal gene transfer (HGT). Members of the project team recently showed that DNA from ancestral viruses in the family Caulimoviridae were captured within the genomes of a wide range of angiosperms, including economically important crops (rice, sorghum, citrus, grape, apple, pear, strawberry, eucalyptus, poplar, tomato, potato, cucumber, cotton). A new genus, tentatively named Florendovirus, was proposed to accommodate these viruses. Several endogenous florendoviruses could potentially be replication competent and, therefore, infective, although this hypothesis has not yet been tested. Different members of the project team have also discovered new geminivirus-like elements (EGVs) in the genome of yams and demonstrated that these EGVs represent transcriptionally active endogenous geminiviral sequences that may be functionally expressed in their respective host plants. Building on this pioneering work, EVENTS focuses on the role of caulimovirid and geminivirid EVEs in virus evolution and their functions in plants. EVENTS will create automated computational tools to search for these EVEs in plant genomes and will implement these tools in a large-scale plant EVE discovery program, providing access to viral sequences that were integrated millions to tens of millions of years ago. These EVEs will be used to reconstruct accurate time-scaled evolutionary histories of entire viral lineages across unprecedented time-spans, helping to refine predictive models of viral emergence. EVENTS will investigate the contributions of caulimovirid and geminivirid EVEs to viral diversity. A range of antigenic and molecular detection tools will be created and used to screen germplasm collections and collected samples for viral particles and infective genomes of as yet undescribed geminiviruses and florendoviruses with EVE counterparts. Graft experiments will be carried out to confirm infective status. The project will also explore synergistic interactions between endogenous viruses and exogenous viruses encoding suppressors of silencing, in order to investigate the role of silencing in the regulation of EVE gene expression in plants. The contribution of caulimovirid and geminivirid EVEs to genetic and epigenetic regulation of plant gene expression will be investigated in silico through the systematic search for fused (viral/plant) open reading frames, alternative promoters, intron splicing sites and premature terminations of transcription. Immunological and molecular approaches will be designed and used to search for and characterize EVE-derived proteins and/or RNAs expressed in host plants. Experimental approaches using recombinant infective viral clones expressing EVE sequences will be designed and implemented to evaluate potential antiviral resistance in plants conferred by EVEs acting as natural viral transgenes. By developing novel integrated and multidisciplinary approaches to illuminate the diversity of EVEs in plant genomes, their roles in viral evolution, their functions and potentially beneficial roles within their host plants, EVENTS stands at the forefront of an emerging research field. We anticipate that the project will contribute significantly to societal issues such as the control of viral diseases and the advancement of plant biotechnology. EVENTS brings together leading groups with complementary expertise in virology, bioinformatics and molecular systematics working in France, South Africa and Australia. Partners have a proven record of collaboration and joint publications that demonstrate their ability to meet project goals and deliver results in ground-breaking research domains.

Agronomy and biodiversity shall address several major societal, economical, and environmental challenges. However, data are being produced in such big volume and at such high pace, it questions our ability to transform them into knowledge and enable, for instance, translational agriculture i.e., rapidly and efficiently transferring results from agronomy research into the farms (“bench to farmside”). Semantic interoperability enables data integration and fosters new scientific discoveries by exploiting various data acquired from different perspectives and domains. D2KAB’s primary objective is to create a framework to turn agronomy and biodiversity data into –semantically described, interoperable, actionable, open– knowledge, along with investigating scientific methods and tools to exploit this knowledge for applications in science and agriculture. We will adopt an interdisciplinary semantic data science approach that will provide the means –ontologies and linked open data– to produce and exploit FAIR (Findable, Accessible, Interoperable, and Re-usable) data. To do so, we will develop original approaches and algorithms to address the specificities of our domain of interests, but also rely on existing tools and methods. D2KAB involves a multidisciplinary (and international) research consortium of three computer science labs (UM-LIRMM, CNRS-I3S, STANFORD-BMIR), four bioinformatics, biology, agronomy and agriculture labs (INRA-URGI, INRA-MaIAGE, INRA-IATE, IRSTEA-TSCF), two ecology and ecosystems labs (CNRS-CEFE, INRA-URFM), one scientific & technical information unit (INRA-DIST), and one association of agriculture stakeholders (ACTA). The consortium’s expertise ranges from ontologies and metadata, semantic Web, linked data, ontology alignment, knowledge reasoning and extraction, natural language processing to bioinformatics, agronomy, food science, ecosystems, biodiversity and agriculture. The project is structured with three work-packages of research and development in informatics and two work-packages of driving scenarios. WP1 will focus on ontologies/ vocabularies and turn the AgroPortal prototype into a reference platform that addresses the community needs and reaches a high level of quality regarding both content and services offered e.g., SKOS compliance, semantic search over linked data, text annotation, interoperability with other repositories. WP2 will focus on the critical issue of ontology alignment and develop new functionalities and state-of-the-art algorithms in AgroPortal using background knowledge methods validated in ag & biodiv. WP3 will design the methods and tools to reconcile the scenarios' heterogeneous ag & biodiv data sources and turn them into linked data within D2KAB distributed knowledge graph. It will also investigate exploitation of this graph through novel visualization, navigation and search methods. WP4 includes four interdisciplinary research driving scenarios implementing translational agriculture. For instances, an ontology-driven decision support system to select the most appropriate food packaging or an augmented semantic reader for Plant Health Bulletins. We will provide a unique scientific knowledge base for wheat phenotypes and offer the first agricultural data resource empowered by linked open data. WP5 will develop semantic resources for the annotation of ecosystem experiments data and functional biogeography observations. A plant trait-environment-relationships study will be conducted to understand the impacts of climatic changes on vegetation of the Mediterranean Basin. Within a dedicated work-package, we will focus on maximizing the impact of our research. Each of the project driving scenarios will produce concrete outcomes for ag & biodiv scientific communities and stakeholders in agriculture. We have planned multiple dissemination actions and events where we will use our driving scenarios as demonstrators of the potential of semantic technologies in agronomy and biodiversity.

While a global food crisis threatens, 20 % of crops are eaten by insects. Providing knowledge on insect pest genomes, and on the ability of insects to adapt to different host-plants and to diversify may help deciphering new crop plant protection strategies. One such pest is the Lepidoptera Spodoptera frugiperda, the fall armyworm (FAW). It exists as two different host-plant strains, one mostly associated to corn (C strain) whereas the other is mostly associated to rice (R strain). The two strains are morphologically indistinguishable but they exhibit pheromone and behavioral differences, and some degree of genetic incompatibility. The first aim of the project is to record all sources of genetic variation between the two strains by comparing the whole genomes of both lab strains, but also by measuring levels of host-based genetic divergence and of genes flow between field individuals on different host-plants. The second aim of the project is to identify genes involved in adaptation to the host-plant and their regulation, and to determine if adaptation to the host-plant has a role in speciation. We will start the project from the already available full genome assembly and genes annotation of the C strain genome(from Genoscope), and the whole genome assembly of the R strain (from one/two laboratory individuals in each case) as well as from transcriptomic data of both strains and of a 300 microsatellites markers based genetic map. The project will include: - A complete structural annotation of both laboratory strains recording all orthologs, and mutations (SNP, rearrangements, TE insertions) that make heterogeneity between the two genomes. Candidate genes under divergent selection or under the direct influence of positive selection will be listed. - A functional annotation of the two genomes. It will be performed by comparing transcriptomes (mRNAs and small ncRNAs) of the two strains on two host-plants at larval and adult stages. Genes with modulated expression will be identified and their epigenetic regulators (histones modifications and small ncRNAs) will be analyzed on the same samples. Analysis of these data will rely on bioinformatic data integration effort. - A set of 50 genes chosen among divergent and differentially expressed genes will be further analyzed. We will focus on gene families possibly involved in host-plant adaptation. We will check on field individuals if the modulated expression variation is found also associated to the host-plant, or if divergent alleles are enriched in natural populations on the cognate host-plants. We will also follow the expression level and sequence of these genes in laboratory individuals upon 12 successive host-plant choice trials in order to check whether they are subject to microevolution. - A measurement of host-based genetic divergence and genes flow between individuals on different host-plants at a local scale. We will perform a phylogeographic analysis in order to describe population structure and measure strain divergence at a regional scale. The consortium includes four partners. The DGIMI’s coordinator lab is expert in genomics, transcriptomics and epigenomics of insects. The URGI lab is expert in de novo detection of Transposable Elements (TE) in genomes and their classification, Symbiose lab is expert in bioinformatic treatment and analysis of genomic and post-genomic data, whereas CBGP lab is expert in population genetics and phylogeography of insects. . None of the partner would have been able to conduct such a project alone, and the complementary expertises in genomics, genetics, evolution and bio-informatics will constitute a major strength for this joint scientific innovative

Root-knot and cyst forming nematodes are important pathogens. Nematicides were means in nematode control, but since they threatened environment and human health they were banned (EC directive 2007/619/EC). Natural plant resistance is an available and safe option, but strongly limited by the number of available genotypes and the occurrence of resistance breaking nematode populations. Furthermore, climate change positively regulates the nematode infection capacity inducing more intense infestations and greater risks to European agriculture. Therefore novel strategies must be developed. Molecular mechanisms of plant resistance to pathogens have been extensively studied and are now applied in pest management but knowledge of plant susceptibility and disease development is still limited. It is now well established that pathogens corrupt elementary plant functions and influence defence responses. Identification of plant genes which are essential for pathogens to exploit the host opens a perspective to develop new approaches to plant resistance. Members of this consortium already performed genome-wide expression profiling in Arabidopsis and tomato demonstrating that essential plant functions are manipulated during feeding site development induced by root-knot nematodes (RKN) and beet cyst nematodes (BCN). Morever, functional analysis of differentially expressed genes identify key genes essential for the development of feeding site and RKN or BCN. The NESTOR project will combine the efforts of 5 public research labs and 4 private companies to (i) discover and characterize Arabidopsis genes which are essential for disease susceptibility towards RKN and BCN and (ii) to discover target sequences in crops based on a set of genes for which an important role in feeding cell development has been shown, to generate novel resistance sources in crop plants. Orthologs of Arabidopis genes will be identified in tomato, cucumber, and sugar beet. New alleles will be generated by TILLING or Eco TILLING and tested for enhanced nematode resistance. Those with increased resistance without affecting plant development will be selected as targets. The nematology labs will first define plant susceptibility genes based on microarrays results and Arabidopsis mutant phenotyping. TILLING platforms will identify mutant lines in crops, while private companies will identify orthologues of Arabidopsis susceptibility genes in crop plant candidates and will genotype and phenotype these plants. NESTOR will increase our knowledge on plant-pathogen interactions and will generate resistance towards a large spectrum of nematode species on tomato, cucumber and sugar beet. The expected results of the project will be released to the public domain in the form of as scientific publications. They will have direct implication and application for the production of safer and healthier food by a novel approach replacing banned chemical nematicides.

Parasites are able to evolve rapidly and overcome host defence mechanisms, but the molecular basis of this adaptation remains poorly understood. Identifying polymorphisms under selection in pathogenic fungal populations will help understanding the evolutionary processes underlying the adaptation to host-plant. Fungal genes may qualitatively determine whether a plant genotype can be infected or not (i.e. host specialization and/or virulence/avirulence) or may quantitatively determine the ability of the fungus to overcome the basal defence of the host plant species (i.e. aggressiveness). Recently, it has been proposed that the same molecular mechanisms could in fact underlie these seemingly different fungal traits. Taking advantage of the advance of Next Generation Sequencing technologies, GANDALF proposes to use a population genomics approach (i.e. without any a priori on the genes involved in host adaptation) for addressing the processes of adaptation in the ecological/agronomic gradient from host-plant specialization to quantitative adaptation to host-plant resistance. GANDALF is bringing together scientists from different laboratories and institutions having internationally recognized expertise in plant pathology, genomics, bioinformatics, evolutionary genetics and modelling (all ranked A by AERES, 4 being A+). Nine different pathosystems have been chosen, covering a large range of life history traits (e.g. biotophic vs necrotrophic, fungi vs oomycetes, etc.) and with genome sequences already available. Depending on the system, offspring of controlled crosses or natural populations will be analyzed. A first step aims at characterising strains for traits associated with host adaptation (phenotyping, Task 1). Re-sequencing of phenotyped strains will allow assembling, mapping and SNP discovery (Task 2). Genome-wide polymorphism data will be analysed following either a genome-wide association (Task 3) or a genome scan approach (Task 5). Since pathogens are prone to demographic and spatial variations, a method able to infer demographic parameters on populations will be developed in order to build a powerful tool of selection detection under complex population models (Task 4). Using this new tool, genome scan will be performed in order to detect loci under selection (Task 5). The candidate loci identified in tasks 3 and 5 will be validated by further genotyping on natural populations or collections available in laboratories. The genetic bases of host adaptation will be compared among fungal species and along the host specialization / cultivar specificity / aggressiveness continuum. This project not only will bring new insights into the understanding of genomic basis of fungal plant pathogens, but also will contribute to maintain the scientific excellence of the GANDALF partners by accelerating the integration of NGS technologies into their research program.