Pesticides are of limited use against bacterial diseases in crops due to a lack of effective and non-toxic molecules. Thus, genetic selection of resistant crops remains the most effective approach to control bacterial pathogens. Resistance breeding requires a conceptual jump to efficiently design significant and durable resistance to a large variety of pathogens in a large number of crops simultaneously. The CROpTAL project aims at identifying plant susceptibility hubs in major crops (cereals, citrus, legumes and brassicaceae) targeted by Xanthomonas virulence-promoting TAL (Transcription Activator-Like) type III effectors. These conserved susceptibility targets could then be used for marker-assisted breeding of loss-of-susceptibility by selection of inactive variants of those hubs. These results will contribute to the development of durable resistance to a broad range of bacterial pathogens in the selected crops.

Vanilla is an emblematic patrimonial and endemic resource for tropical EU regions and combines a high socio-economic value with a natural image due to its traditional and sustainable mode of production and process. Tropical EU regions offer a unique opportunity to study the genus in its global biodiversity. The stake of vanilla sustainability relies on three capacities: Our capacity to protect the wild vanilla species through their conservation and study, our capacity to exploit our knowledge of this biodiversity to diversify the quality of the vanilla product, and our capacity to improve cultivated vanilla (aroma, disease resistance, agronomy). The five regions involved (Reunion, French Polynesia, Guadeloupe, French Guiana, Mayotte) will share Vanilla genetic resources and biodiversity management and development skills as well as scientific expertise (together with IBP/Paris) to develop these capacities to reach two objectives: The main research objectives of the project are first to improve our scientific knowledge to implement actions in the preservation of vanilla wild genetic resources in tropical UE (both ex situ and in situ) and subsequently, to identify what services wild species can offer for the improvement of cultivated species and the sustainability of vanilla crop production. We will inventory and characterise (genetic, phenotypic and mechanisms of evolution and diversification) the wide range of Vanilla genetic resources both cultivated and natural in tropical EU to protect and value endemic species and resources. We will also assess important agronomical traits in these species (aroma, resistance to viruses and fusarioses), and how these traits can be combined through hybrid breeding (V. xtahitensis x V. pompona). Innovative candidate gene markers from a collaborative international metagenomic project will be used to implement genome enabled improvement strategies for vanilla. The direct participation of biodiversity management and sustainable development stakeholder partners will allow implementing the results with regards to these two aspects, for each region involved. VaBiome is a highly structuring project which will contribute to build the future and long term international conservation of the genus diversity as well as the aromatic exploitation of this beloved product.

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.

In order to better control current diseases of plants and prevent future epidemics, it is crucial to develop an improved understanding of the factors underlying pathogen emergence, adaptation and spread. Recent methodological developments in molecular epidemiology now allow tackling such question through fine reconstruction of disease dynamics in space and time. To date, essentially all studies on plant pathogens have focused on “contemporary” individuals sampled over a fairly limited period of time (around 30 years at a maximum) but recent developments in DNA sequencing technology now make possible reconstructing historical genomes dating back to previous centuries. As illustrated by the detailed reconstruction of the 19th-century potato-blight epidemic that triggered the Irish potato famine, isolation of pathogen ancient DNA (aDNA) can provide unique insight into their origins and can illuminate their phenotypic evolution, such as for instance their virulence. The aim of the MUSEOBACT project is to retrieve genomic data of historical crop pathogenic bacteria from both herbarium material and lyophilized collections. We also intend to improve the required statistical methods to reconstruct the emergence and spread of pathogens through space and time. The theoretical and empirical work will allow us to elucidate the history and evolution of some of the most devastating crop pathogenic bacteria currently in action, and to highlight the likely causes that led to their emergence and spread. As proof of concept, we attempted and succeeded in retrieving genomic data from both herbarium and bacterial lyophilized collection material. We will focus our work on several Xanthomonas pathovars and Xylella fastidiosa, two major crop bacterial pathogen complex species causing several important crop diseases and representing a huge agronomical and economical constraint in tropical, subtropical and temperate areas. The case of Xylella fastidiosa is particularly worrisome because recent emergences in Europe represent a significant threat to French and European agriculture. The major novelty of the MUSEOBACT project lies in the reconstruction of complete genomes from herbarium dried plant specimens, as this task has never been achieved for any bacterial species yet, as well as in their analyses with sophisticated and dedicated population genetics methods. This project will enable major advances in molecular epidemiology of plant infectious diseases, through both innovative molecular and statistical approaches. By i) elucidating the causes leading to crop disease emergences, ii) reconstructing pathogen invasion routes and iii) inferring key evolutionary and epidemiological parameters, our project will directly help developing new efficient disease surveillance and management strategies to prevent current/future epidemics. To ensure the success of our project, all the required skills in ancient genomics, bioinformatics, Bayesian and computational population genomics, evolutionary biology, epidemiology and phytopathology have been gathered within the MUSEOBACT scientific consortium.

In a just published Opinion paper in Trends in Ecology & Evolution, we advocate that a next-generation, global-scale, ecological approach to biomonitoring will emerge in the coming decade, which can detect ecosystem change accurately, cheaply and generically. Next-generation sequencing (NGS) of DNA sampled from the Earth’s environments, would provide data for the relative abundance of operational taxonomic units or ecological functions. Machine-learning methods would then be used to reconstruct the ecological networks of interactions implicit in the raw NGS data in order to detect and predict ecosystem change. In this Next Generation Biomonitoring (NGB) project, we will examine whether NGS samples from five distinct ecosystems undergoing global change can be used to reconstruct hypothetical networks of interaction using machine learning. We will then compare these reconstructed networks with the current state of knowledge for these systems to test whether NGS and machine learning approaches can be used to reconstruct valid ecological networks. These tests will include examining the NGS networks for specific, established interactions through to detailed comparisons against already-known ecological networks, built using classic network construction approaches. The five systems we will work on represent a cross-section of the organisational scales, drivers of change and data quality we would expect that a NGB approach could be applied to. From microbial interaction networks to macro-biome networks of interacting invertebrates, and across drivers of change such as invasion, disease, conservation, management and climate, the project will determine whether ecosystem change can be detected using an NGB approach. We will troubleshoot many of the technical, methodological and ecological problems facing the development of an NGB approach, such as the variable quality of NGS databases, taxa biases, identification errors, zero-rich data and asymmetric abundance distributions, and develop statistical approaches for detecting change and determining the size and power of biomonitoring programs. Ultimately, we envision the development of autonomous samplers that would sample nucleic acids and upload NGS sequence data to the cloud for network reconstruction, using methods that we will develop in the project. Large numbers of these samplers, in a global array, would allow sensitive automated biomonitoring of the Earth’s major ecosystems at high spatial and temporal resolution, revolutionising our understanding of ecosystem change.