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.
You can access and play with the graphs:
- Evolution of the number of publications between 2005 and 2015
- Map of most publishing countries between 2005 and 2015
- Network of country collaborations
- Network of institutional collaborations (+10 publications)
- Network of keywords relating to data - Link
Transcriptome profiling of muscle by RNA-Seq reveals significant differences in digital gene expression profiling between Angus and Luxi cattle
The development of massively parallel sequencing technologies enables the sequencing of total cDNA to identify unigene expression and to discover novel regions of transcription. Here, we report the first use of RNA sequencing (RNA-Seq) to find the digital gene expression profiles (DGEs) associated with the growth and development of muscle in Chinese Luxi and Angus beef cattle. More than 9243921 clean reads were found in samples of muscle tissue. We found 232 DGEs between Luxi cattle and Angus cattle (false discovery ratio 0.001 and log2 ratio 1). Among the DGEs, we determined that 147 genes were downregulated and 85 genes were upregulated. Gene Ontology and KEGG Pathway analyses were performed to analyse the biological role of the DGEs and determine their contribution to the differences seen in muscle growth and development between local Chinese Luxi cattle and the introduced Angus cattle. The results suggest that RNA-Seq is a useful tool for predicting differences in gene expression between Luxi and Angus beef cattle; moreover, our results provides unprecedented resolution of mRNAs that are expressed across the two breeds.
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