Investigation into the miRNA/5' isomiRNAs function and drought-mediated miRNA processing in rice.

MicroRNAs lie at the core of biological regulatory networks in plants. The recent discovery of isomiRs that are length variants of the annotated mature miRNAs has further unveiled the complexity of miRNome. Delineation of their functional relevance is critical to understand the complete functional spectrum of the miRNome. To apprehend the role of 5' isomiRs in rice, we performed a comprehensive analysis of the annotated miRNA pool using 8 deep-sequencing datasets from flag leaf and spikelet tissues from two cultivars of rice viz. N22 and PB1 grown under control and drought conditions. The products of the 5' start site variability termed as "5' isomiRs" were found to be widespread in all the datasets. It was possible to identify several 5' isomiRs that were highly distinct and abundant and supported by more than 90% of the tags that map in the region. Majority of miRNA/5' isomiR pair share similar tissue and drought-mediated expression dynamics. Analysis of the degradome data identified targets for several of these 5' isomiRs, thereby confirming their biological activity. Since the isomiRs are length variants at the 5' end, the target sites were found to be accordingly shifted as compared to the target site of the annotated miRNA. Further we also observed that drought affects the processing accuracy of several miRNAs across all tissues of both the cultivars leading to differential accumulation of 5' isomiR/miRNA pair.

Manually curated database of rice proteins.

'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.