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
Genome-wide identification of differentially expressed genes under water deficit stress in upland cotton (Gossypium hirsutum L.)
Background: Cotton is the world's primary fiber crop and is a major agricultural commodity in over 30 countries. Like many other global commodities, sustainable cotton production is challenged by restricted natural resources. In response to the anticipated increase of agricultural water demand, a major research direction involves developing crops that use less water or that use water more efficiently. In this study, our objective was to identify differentially expressed genes in response to water deficit stress in cotton. A global expression analysis using cDNA-Amplified Fragment Length Polymorphism was conducted to compare root and leaf gene expression profiles from a putative drought resistant cotton cultivar grown under water deficit stressed and well watered field conditions. Results: We identified a total of 519 differentially expressed transcript derived fragments. Of these, 147 transcript derived fragment sequences were functionally annotated according to their gene ontology. Nearly 70 percent of transcript derived fragments belonged to four major categories: 1) unclassified, 2) stress/defense, 3) metabolism, and 4) gene regulation. We found heat shock protein-related and reactive oxygen species-related transcript derived fragments to be among the major parts of functional pathways induced by water deficit stress. Also, twelve novel transcripts were identified as both water deficit responsive and cotton specific. A subset of differentially expressed transcript derived fragments was verified using reverse transcription-polymerase chain reaction. Differential expression analysis also identified five pairs of duplicated transcript derived fragments in which four pairs responded differentially between each of their two homologues under water deficit stress. Conclusions: In this study, we detected differentially expressed transcript derived fragments from water deficit stressed root and leaf tissues in tetraploid cotton and provided their gene ontology, functional/biological distribution, and possible roles of gene duplication. This discovery demonstrates complex mechanisms involved with polyploid cotton's transcriptome response to naturally occurring field water deficit stress. The genes identified in this study will provide candidate targets to manipulate the water use characteristics of cotton at the molecular level.
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