PlantPReS: a database for plant proteome response to stress

Seyed Ahmad Mousavi, Farhad Movahedi Pouya, Mohammad Reza Ghaffari, Mehdi Mirzaei, Akram Ghaffari, Mehdi Alikhani, Mohammad Ghareyazie, Setsuko Komatsu, Paul A. Haynes, Ghasem Hosseini Salekdeh*

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    34 Citations (Scopus)


    About 75% of plant yield potential has been estimated to be lost to environmental stresses, even in developed agricultures. To facilitate the biotechnological improvement of crop productivity, genes and proteins that control crop adaptation to a wide range of environments will need to be identified. Due to the challenges faced in text/data mining, there is a large gap between the data available to researchers and the hundreds of published plant stress proteomics articles. Plant stress proteome database (PlantPReS; is an open online proteomic database, which currently (as of October 2015) comprises > 20,413 entries from 456 manually curated articles, and contains > 10,600 unique stress responsive proteins. Since every aspect of the experiments, including protein name, accession number, plant type, tissue, stress types, organelles, and developmental stage has been digitized, experimental data can be rapidly accessed and integrated. Furthermore, PlantPReS enables researchers to perform multiple analyses on the database using the filtration mode, and the results of each query indicate a series of proteins for which a set of selected criteria is met. The query results can be displayed in either text or graphical format. Significance The promise of text and data mining to facilitate and enhance research fundamentally has not yet been achieved, mainly because great numbers of stress-associated proteins are not deposited in databases. PlantPReS is a valuable database for the vast majority of researchers working in proteomics and plant stress areas. It has a user-friendly interface with a number of useful features, including a search engine, analysis tools, gene ontology, a function for cross-referencing useful external databases, and the expression pattern of stress associated proteins.

    Original languageEnglish
    Pages (from-to)69-72
    Number of pages4
    JournalJournal of Proteomics
    Publication statusPublished - 30 Jun 2016


    • Database
    • Plant stress
    • Proteomics
    • GENES


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