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 pyrethroid resistant and susceptible mosquitoes in the malaria vector, Anopheles sinensis
Background: Anopheles sinensis is a major malaria vector in China and other Southeast Asian countries, and it is becoming increasingly resistant to the insecticides used for agriculture, net impregnation, and indoor residual spray. Very limited genomic information on this species is available, which has hindered the development of new tools for resistance surveillance and vector control. We used the 454 GS FLX system and generated expressed sequence tag (EST) databases of various life stages of An. sinensis, and we determined the transcriptional differences between deltamethrin resistant and susceptible mosquitoes. Results: The 454 GS FLX transcriptome sequencing yielded a total of 624,559 reads (average length of 290 bp) with the pooled An. sinensis mosquitoes across various development stages. The de novo assembly generated 33,411 contigs with average length of 493 bp. A total of 8,057 ESTs were generated with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) annotation. A total of 2,131 ESTs were differentially expressed between deltamethrin resistant and susceptible mosquitoes collected from the same field site in Jiangsu, China. Among these differentially expressed ESTs, a total of 294 pathways were mapped to the KEGG database, with the predominant ESTs belonging to metabolic pathways. Furthermore, a total of 2,408 microsatellites and 15,496 single nucleotide polymorphisms (SNPs) were identified. Conclusions: The annotated EST and transcriptome databases provide a valuable genomic resource for further genetic studies of this important malaria vector species. The differentially expressed ESTs associated with insecticide resistance identified in this study lay an important foundation for further functional analysis. The identified microsatellite and SNP markers will provide useful tools for future population genetic and comparative genomic analyses of malaria vectors.
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