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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Differential gene expression in pre-laying and laying period ovaries of Sichuan White geese (Anser cygnoides)


Geese are an economically important poultry species worldwide. Their superior meat production performance and meat quality make them a popular food. However, they are not bred worldwide because their poor laying capacity increases farming costs. To gain a global view of the genes that are differentially expressed between prelaying (P) and laying (L) periods and to develop a database for further studies, we performed large-scale transcriptome sequencing of ovarian tissue collected from Anser cygnoides. In total, 30,151,422 raw reads, with an average length of 151 bp and a total length of 4,552,864,722 bp, were obtained. After primers and adaptors were removed, 19,167,132 clean reads, with an average length of 134.5 bp and a total length of 2,577,297,281 bp, were obtained, among which 1,268,906,694 bp and 1,308,390,587 bp were from L and P ovarian tissue, respectively. The 16,605 assembled sequences were further functionally annotated by comparing their sequences to different protein and functional domain databases and assigning gene ontology (GO) terms. Of these, 511 assembled sequences were considered differentially expressed based on the 2-fold method, among which 396 were assigned at least one GO term. Digital expression analysis using the Kyoto encyclopedia of genes and genomes annotation identified 121 genes that were differentially expressed in the P vs L periods. Five of these are of special interest for further investigation of their roles in determining high reproductive performance. This study provides valuable information and sequence resources for uncovering genes determining high egg-laying performance and for future functional genomics analysis of geese.

  • CN
  • NE_Agr_Univ (CN)
Data keywords
  • ontology
Agriculture keywords
  • farming
Data topic
  • information systems
  • 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)
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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.