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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Title

Transcriptional profiling of cattle infected with Trypanosoma congolense highlights gene expression signatures underlying trypanotolerance and trypanosusceptibility

en
Abstract

Background: African animal trypanosomiasis (AAT) caused by tsetse fly-transmitted protozoa of the genus Trypanosoma is a major constraint on livestock and agricultural production in Africa and is among the top ten global cattle diseases impacting on the poor. Here we show that a functional genomics approach can be used to identify temporal changes in host peripheral blood mononuclear cell (PBMC) gene expression due to disease progression. We also show that major gene expression differences exist between cattle from trypanotolerant and trypanosusceptible breeds. Using bovine long oligonucleotide microarrays and real time quantitative reverse transcription PCR (qRT-PCR) validation we analysed PBMC gene expression in naive trypanotolerant and trypanosusceptible cattle experimentally challenged with Trypanosoma congolense across a 34-day infection time course. Results: Trypanotolerant N'Dama cattle displayed a rapid and distinct transcriptional response to infection, with a ten-fold higher number of genes differentially expressed at day 14 post-infection compared to trypanosusceptible Boran cattle. These analyses identified coordinated temporal gene expression changes for both breeds in response to trypanosome infection. In addition, a panel of genes were identified that showed pronounced differences in gene expression between the two breeds, which may underlie the phenomena of trypanotolerance and trypanosusceptibility. Gene ontology (GO) analysis demonstrate that the products of these genes may contribute to increased mitochondrial mRNA translational efficiency, a more pronounced B cell response, an elevated activation status and a heightened response to stress in trypanotolerant cattle. Conclusion: This study has revealed an extensive and diverse range of cellular processes that are altered temporally in response to trypanosome infection in African cattle. Results indicate that the trypanotolerant N'Dama cattle respond more rapidly and with a greater magnitude to infection compared to the trypanosusceptible Boran cattle. Specifically, a subset of the genes analyzed by real time qRT-PCR, which display significant breed differences, could collectively contribute to the trypanotolerance trait in N'Dama.

en
Year
2009
en
Country
  • IE
  • US
  • KE
  • GB
Organization
  • Natl_Univ_Ireland (IE)
  • Michigan_State_Univ (US)
  • Univ_Liverpool (UK)
  • Trinity_Coll_Dublin (IE)
Data keywords
  • ontology
en
Agriculture keywords
  • cattle
  • agriculture
  • livestock
en
Data topic
  • information systems
  • semantics
en
SO
BMC GENOMICS
Document type

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

Institutions 10 co-publis
  • Natl_Univ_Ireland (IE)
  • Michigan_State_Univ (US)
uid:/M9G8429R
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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.