e-infrastructure Roadmap for Open Science in Agriculture

A bibliometric study

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.

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Comparative analyses of stress-responsive genes in Arabidopsis thaliana: insight from genomic data mining, functional enrichment, pathway analysis and phenomics


Biotic and abiotic stresses adversely affect agriculture by reducing crop growth and productivity worldwide. To investigate the abiotic stress-responsive genes in Arabidopsis thaliana, we compiled a dataset of stress signals and differentially upregulated genes (>= 2.5 fold change) from Stress-responsive transcription Factors DataBase (STIFDB) with additional set of stress signals and genes curated from PubMed and Gene Expression Omnibus. A dataset of 3091 genes differentially upregulated due to 14 different stress signals (abscisic acid, aluminum, cold, cold-drought-salt, dehydration, drought, heat, iron, light, NaCl, osmotic stress, oxidative stress, UV-B and wounding) were curated and used for the analysis. Details about stress-responsive enriched genes and their association with stress signals can be obtained from STIFDB2 database http://caps.ncbs.res.in/stifdb2. The gene-stress-signal data were analyzed using an enrichment-based meta-analysis framework consisting of two different ontologies (Gene Ontology and Plant Ontology), biological pathway and functional domain annotations. We found several shared and distinct biological processes, cellular components and molecular functions associated with stress-responsive genes. Pathway analysis revealed that stress-responsive genes perturbed the pathways under the "Metabolic pathways'' category. We also found several shared and stress-signal specific protein domains, suggesting functional mechanisms regulating stress-response. Phenomic characteristics of abiotic stress-responsive genes were ascertained for several stresses and found to be shared by multiple stresses in both anatomy and temporal categories of Plant Ontology. We found several constitutive stress-responsive genes that are differentially upregulated due to perturbation of different stress signals, for example a gene (AT1G68440) involved in phenylpropanoid metabolism and polyamine catabolism as responsive to seven different stress signals. We also performed structure-function prediction of five genes associated responsive to multiple abiotic stress signals. We envisage that results from our analysis that provide insight into functional repertoire, metabolic pathways and phenomic characteristics common and specifically associated with stress signals would help to understand abiotic stress regulome in Arabidopsis thaliana and may also help to develop an improved plant variety using molecular breeding and genetic engineering techniques that are rapidly stress-responsive and tolerant.

  • IN
  • Univ_Agr_Sci_Bangalore (IN)
Data keywords
  • ontology
Agriculture keywords
  • agriculture
Data topic
  • big data
Document type

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Institutions 10 co-publis
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    e-ROSA - e-infrastructure Roadmap for Open Science in Agriculture has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 730988.
    Disclaimer: The sole responsibility of the material published in this website lies with the authors. The European Union is not responsible for any use that may be made of the information contained therein.