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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An Integrated Quantitative Trait Locus Map of Oil Content in Soybean, Glycine max (L.) Merr., Generated Using a Meta-Analysis Method for Mining Genes


Soybean is a major cash crop in the world, and its oil content was one of the very important traits. Therefore, the study of gene mapping for oil content in soybean is very important for breeding application. At present, at least 130 QTL loci for soybean oil content have been published; however, the mapping results of oil content were dispersed and a coalescent public map should be established to integrate the published QTLs, and to more efficiently mine genes based on the meta-analysis method of the bioinformatics tools. This study was to construct an integrated map of QTLs for soybean oil content and accelerate the application of bioinformation resource related to oil content improvement in the practice of soybean breeding. We collected information of 130 QTLs reported over the past 20 yr for soybean oil content and used the Software BioMercator 2.1 to project QTLs from their own maps onto a reference map, which was an early-integrated map constructed by Song (2004) for oil-content quantitative trait loci (QTLs) in soybean. Gene mining was performed based on the meta-analysis by running the local ver. GENSCAN and InterProScan. The confidence interval of QTLs was efficaciously narrowed using the meta-analysis method, and 25 consensus QTLs were mapped on the reference map. Using a local version of GENSCAN, 12 805 sequences in the consensus QTL intervals were predicted. With BLAST, these predicted sequences were aligned to gene sequences from the International Protein Index database using InterProScan locally. Thirteen predicted genes were in the class of the geme ontology (GO) accession (0006631), which were involved in the fatty acid metabolic process. These genes were analyzed using BLAST at the NCBI website to examine whether they were related to oil content. Six genes were found in the oil-synthesis pathway. Twenty-five consensus QTLs and six genes were found in the oil-synthesis pathway. These results would lay the foundation for marker-assisted selection and mapping QTL precisely, and these genes will facilitate the researches on the gene mining of oil synthesis and molecular breeding in soybean.

  • CN
  • NE_Agr_Univ (CN)
  • CAAS_China_Acad_Agr_Sci (CN)
Data keywords
  • ontology
Agriculture keywords
    Data topic
    • big data
    • semantics
    Document type

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

    Institutions 10 co-publis
    • NE_Agr_Univ (CN)
    • CAAS_China_Acad_Agr_Sci (CN)
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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.