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
Identification of Candidate Genes Associated with Beef Marbling Using QTL and Pathway Analysis in Hanwoo (Korean Cattle)
Marbling from intramuscular fat is an important trait of meat quality and has an economic benefit for the beef industry. Quantitative trait loci (QTL) fine mapping was performed to identify the marbling trait in 266 Hanwoo steers using a 10K single nucleotide polymorphism panel with the combined linkage and linkage disequilibrium method. As a result, we found nine putative QTL regions for marbling: three on BTA6, two on BTA17, two on BTA22, and two on BTA29. We detected candidate genes for marbling within 1 cM of either side of the putative QTL regions. Additionally, to understand the functions of these candidate genes at the molecular level, we conducted a functional categorization using gene ontology and pathway analyses for those genes involved in lipid metabolism or fat deposition. In these putative QTL regions, we found 95 candidate genes for marbling. Using these candidate genes, we found five genes that had a direct interaction with the candidate genes. We also found SCARB1 as a putative candidate gene for marbling that involves fat deposition related to cholesterol transport.
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