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
Candidate genes and biological pathways associated with carcass quality traits in beef cattle
The objective of this study was to use the candidate gene approach to identify the genes associated with carcass quality traits in beef cattle steers at the University of Alberta Ranch at Kinsella, Canada. This approach involved identifying positional candidate genes and prioritizing them according to their functions into functional candidate genes before performing statistical association analysis. The positional candidate genes and single nucleotide polymorphisms (SNP) were identified from previously reported quantitative trait loci for component traits including body weight, average daily gain, metabolic weight, feed efficiency and energy balance. Positional candidate genes were then prioritized into functional candidate genes according to the associated gene ontology terms and their functions. A total of 116 genes were considered functional candidate genes and 117 functional SNPs were genotyped and used for multiple marker association analysis using ASReml (R). Seven SNPs were significantly associated with various carcass quality traits (P <= 0.005). The significant genes were associated with biological processes such as fat, glucose, protein and steroid metabolism, growth, energy utilization and DNA transcription and translation as inferred from the protein knowledgebase (UniprotKB). Gene network analysis indicated significant involvement of biological processes related to fat and steroid metabolism and regulation of transcription and translation of DNA.
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