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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Assembly and Characterization of the European Hazelnut 'Jefferson' Transcriptome


European hazelnut (Corylus avellana L.) is of worldwide agricultural significance, with breeding efforts focused on combining high nut yield and nut quality with resistance to diseases such as eastern filbert blight (EFB), a cause of severe crop loss in much of the United States. Oregon State University recently released a resistant cultivar, 'Jefferson' (OSU 703.007), that was chosen for transcriptome sequencing to establish further genomic resources for C. avellana L. We used Illumina ribonucleic acid sequencing (RNA-seq) to characterize complementary DNA (cDNA) libraries from four hazelnut tissues, including leaves, catkins, bark, and whole seedlings. The 6.8 Gb of hazelnut transcriptome data was assembled de novo into 28,255 contigs with an average length of 532 bp and an N50 (the minimum contig length necessary such that all contigs of equal or greater length will equal half of the bases of the assembly) of 961 bp. Sequence comparisons using BLASTX and gene ontology (GO) classifications were used to generate automated descriptive function annotations. High similarity of the predicted proteins to sequences in related plants demonstrates the validity of the transcript contigs, with 80.8% having similarity to grape (Vitis vinifera L.), poplar (Populus trichocarpa Torr. & A. Gray), and castor bean (Ricinus communis L.) sequences in the public domain. A survey of GO terms enriched among tissue-specific transcripts further validates the assembly. A basic local alignment search tool (BLAST) portal and web resources (http://hazelnut.cgrb.oregonstate.edu [accessed 8 Jan. 2010]) are available and will be of importance to breeders for marker-assisted breeding efforts.

  • US
  • Oregon_State_Univ (US)
  • Univ_Missouri_Columbia (US)
  • Donald_Danforth_Plant_Sci_Ctr (US)
Data keywords
  • ontology
Agriculture keywords
  • agriculture
Data topic
  • big data
  • information systems
  • semantics
Document type

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

Institutions 10 co-publis
  • Oregon_State_Univ (US)
  • Univ_Missouri_Columbia (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.