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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A genome wide scan highlights differences in the genetic architecture of fat and protein contents in dairy sheep


A genome wide scan using the Illumina Ovine beadChip 50 K was performed on DNA of 100 dairy sheep to identify key genes affecting milk fat and protein content. The markers with allele frequency significantly different between the high fat content and the low fat content sheep (62 markers) were different from the markers discriminating the sheep on the basis of milk protein percentage (207 markers). The genes in proximity of these markers were explored in the Ovine Genome Assembly OARv3.1, then mapped to known pathways of the Gene Ontology to determine which ones were most represented. Our results indicated that the genes influencing protein content were mainly involved in basic cellular processes, like regulation of transcription, RNA metabolic processes and nucleoside binding, and were many more (641) than the genes (165) which potentially affect fat content, which were mainly represented in the lipid binding, the macromolecule processing and in the plasma membrane categories. No significant markers affecting protein content were detected in proximity of the previously reported QTL on chromosome 6; on the other hand, significant markers were identified on chromosome 3 which might support the previously identified QTL on chromosome 3. (C) 2015 Elsevier B.V. All rights reserved.

  • IT
  • CREA_Council_Agr_Res_&_Agr_Economics (IT)
Data keywords
  • ontology
Agriculture keywords
    Data topic
    • big data
    • information systems
    Document type

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

    Institutions 10 co-publis
    • CREA_Council_Agr_Res_&_Agr_Economics (IT)
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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.