Manually curated database of rice proteins

Abstract

‘Manually Curated Database of Rice Proteins’ (MCDRP) available at http://www.genomeindia.org/biocuration is a unique curated database based on published experimental data. Semantic integration of scientific data is essential to gain a higher level of understanding of biological systems. Since the majority of scientific data is available as published literature, text mining is an essential step before the data can be integrated and made available for computer-based search in various databases. However, text mining is a tedious exercise and thus, there is a large gap in the data available in curated databases and published literature. Moreover, data in an experiment can be perceived from several perspectives, which may not reflect in the text-based curation. In order to address such issues, we have demonstrated the feasibility of digitizing the experimental data itself by creating a database on rice proteins based on in-house developed data curation models. Using these models data of individual experiments have been digitized with the help of universal ontologies. Currently, the database has data for over 1800 rice proteins curated from >4000 different experiments of over 400 research articles. Since every aspect of the experiment such as gene name, plant type, tissue and developmental stage has been digitized, experimental data can be rapidly accessed and integrated.

Prioritization of candidate genes in QTL regions based on associations between traits and biological processes

“…Further comparison with experimental data was performed using two large scale datasets. First, data from a rice database defining associations between in total 637 traits and 239 genes [ 59 ] were used. Most of these associations are not based on QTL fine-mapping but on e.g.…”

“… a Genes prioritized for traits based on overrepresentation of biological processes in QTL regions for the trait for which validation is available based on literature results [ 59 ]. …”

“…Especially in case of agricultural crops, knowledge of what all the genes predicted to be present in the genome are actually doing, is scarce [ 82 ]. For example, existing databases describing rice gene functions only contain relatively small number of cases [ 59 , 83 ]. Having a large set of high-quality gene function predictions [ 34 ] results in much higher numbers of significant associations between traits and biological processes compared to using existing annotations.…”

Differentially expressed seed aging responsive heat shock protein OsHSP18.2 implicates in seed vigor, longevity and improves germination and seedling establishment under abiotic stress

“…Full length CDS and 5′ upstream sequence of OsHSP18.2 (LOC_Os01g08860) was obtained from Ensembl plant O. sativa indica group database available at http://ensembl.gramene.org and GenomeIndia’s manually curated database of rice proteins respectively ( Gour et al, 2014 ). Complete ORF was amplified based on the primers designed from these sequences (Supplementary Table S1 ) from O. sativa indica var.…”

PlantPReS: A database for plant proteome response to stress

“…However, 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. Although there are several databases containing plant stress information such as RiceSRTFDB [8], QlicRice [9], PRGdb [10], STIFDB2 [11], PSRGC [12],MCDRP [13], and PSPDB [14], these databases do not provide sufficient information about stress responsive proteins available in literature. The only plant stress protein database, PSPDB, retrieved proteins from UniProt [15] Fig.…”