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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Genome-wide association study on growth traits in Colombian creole breeds and crossbreeds with Zebu cattle


Whole genome selection represents an important tool for improving parameters related to the production of livestock. In order to build genomic selection indexes within a particular breed, it is important to identify polymorphisms that have the most significant association with a desired trait. A genome-wide marker association approach based on the Illumina BovineSNP50 BeadChip (TM) was used to identify genomic regions affecting birth weight (BW), weaning weight (WW), and daily weight gain (DWG) in purebred and crossbred creole cattle populations. We genotyped 654 individuals of Blanco Orejinegro (BON), Romosinuano (ROMO) and Cebu breeds and the crossbreeds BON x Cebu and ROMO x Cebu, and tested 5 genetic control models. In total, 85 single nucleotide polymorphisms (SNPs) were related (P < 0.05) to the 3 evaluated traits; BW was associated with the highest number of SNPs. For statistical false-positive correction, Bonferroni correction was used. From the results, we identified 7, 6, and 4 SNPs with strong associations with BW, WW, and DWG, respectively. Many of these SNPs were located on important coding regions of the bovine genome; their ontology and interactions are discussed herein. The results could contribute to the identification of genes involved in the physiology of beef cattle growth and the development of new strategies for breeding management via genomic selection to improve the productivity of creole cattle herds.

  • CO
    Data keywords
    • ontology
    Agriculture keywords
    • cattle
    • livestock
    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
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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.