e-infrastructure Roadmap for Open Science in Agriculture

A bibliometric study

The e-ROSA project seeks to build a shared vision of a future sustainable e-infrastructure for research and education in agriculture in order to promote Open Science in this field and as such contribute to addressing related societal challenges. In order to achieve this goal, e-ROSA’s first objective is to bring together the relevant scientific communities and stakeholders and engage them in the process of coelaboration of an ambitious, practical roadmap that provides the basis for the design and implementation of such an e-infrastructure in the years to come.

This website highlights the results of a bibliometric analysis conducted at a global scale in order to identify key scientists and associated research performing organisations (e.g. public research institutes, universities, Research & Development departments of private companies) that work in the field of agricultural data sources and services. If you have any comment or feedback on the bibliometric study, please use the online form.

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Transcriptomic changes in the plant pathogenic fungus Rhizoctonia solani AG-3 in response to the antagonistic bacteria Serratia proteamaculans and Serratia plymuthica


Background: Improved understanding of bacterial-fungal interactions in the rhizosphere should assist in the successful application of bacteria as biological control agents against fungal pathogens of plants, providing alternatives to chemicals in sustainable agriculture. Rhizoctonia solani is an important soil-associated fungal pathogen and its chemical treatment is not feasible or economic. The genomes of the plant-associated bacteria Serratia proteamaculans S4 and Serratia plymuthica AS13 have been sequenced, revealing genetic traits that may explain their diverse plant growth promoting activities and antagonistic interactions with R. solani. To understand the functional response of this pathogen to different bacteria and to elucidate whether the molecular mechanisms that the fungus exploits involve general stress or more specific responses, we performed a global transcriptome profiling of R. solani Rhs1AP anastomosis group 3 (AG-3) during interaction with the S4 and AS13 species of Serratia using RNA-seq. Results: Approximately 104,504 million clean 75-100 bp paired-end reads were obtained from three libraries, each in triplicate (AG3-Control, AG3-S4 and AG3-AS13). Transcriptome analysis revealed that approximately 10 % of the fungal transcriptome was differentially expressed during challenge with Serratia. The numbers of S4- and AS13-specific differentially expressed genes (DEG) were 866 and 292 respectively, while there were 1035 common DEGs in the two treatment groups. Four hundred and sixty and 242 genes respectively had values of log(2) fold-change > 3 and for further analyses this cut-off value was used. Functional classification of DEGs based on Gene Ontology enrichment analysis and on KEGG pathway annotations revealed a general shift in fungal gene expression in which genes related to xenobiotic degradation, toxin and antioxidant production, energy, carbohydrate and lipid metabolism and hyphal rearrangements were subjected to transcriptional regulation. Conclusions: This RNA-seq profiling generated a novel dataset describing the functional response of the phytopathogen R. solani AG3 to the plant-associated Serratia bacteria S4 and AS13. Most genes were regulated in the same way in the presence of both bacterial isolates, but there were also some strain-specific responses. The findings in this study will be beneficial for further research on biological control and in depth exploration of bacterial-fungal interactions in the rhizosphere.

  • SE
  • US
  • Swedish_Univ_Agr_Sci_SLU (SE)
  • N_Carolina_State_Univ (US)
Data keywords
  • ontology
Agriculture keywords
  • agriculture
Data topic
  • big data
Document type

Inappropriate format for Document type, expected simple value but got array, please use list format

Institutions 10 co-publis
  • Swedish_Univ_Agr_Sci_SLU (SE)
  • N_Carolina_State_Univ (US)
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e-ROSA - e-infrastructure Roadmap for Open Science in Agriculture has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 730988.
Disclaimer: The sole responsibility of the material published in this website lies with the authors. The European Union is not responsible for any use that may be made of the information contained therein.