Ramamani Tripathy
ABSTRACT
Rice is the major growing crop in South and Southeast Asia and half of the world population takes rice as staple food. But rice production hampered because of rice tungro disease caused by two viruses. MicroRNA(miRNA) act major role in plant resistance against viruses. miRNAs are short around 22 nucleotides RNA molecules found in eukaryotic cells that regulate gene expression by translational inhibition or cleavage of complementary mRNAs. The present work emphasizes on different string matching algorithms such as Boyer-Moore, Knuth-Morris, Rabin-Karp to elucidate the potentiality of rice miRNAs target against rice plant infecting tungro viruses of both Rice Tungro Spherical Virus (RTSV) and Rice Tungro Baciliform Virus (RTBV). 581 number of miRNA sequence from miRBase has been collected and target rice tungro viruses genes like coat proteins CP1,CP2,CP3, poly-protein of RTSV and ORF1, ORF2, ORF3, P12, P24, P46 and P194 of RTBV considered for simulation. The potential endogenous rice miRNAs targeted found by three different algorithms in our approach also compared with the web based sever psRNATarget. The novel target site findings of rice miRNAs and tungro virus will be helpful to manipulate in new biotechnological approaches for enhance rice production.
- Hull, R. 2002. Matthews' Plant Virology (Academic, London).Google Scholar
- Azzam, O., Chancellor, T. 2002. The biology, epidemiology, and management of rice tungro disease in Asia. Plant Dis.? 86. 88--100.Google Scholar
- Mew, T., Leung, H., Savary, S., Cruz, C., Leach, J. 2004. Looking ahead in rice disease research and management. Crit. Rev. Plant. Sci. 23. 103--127.Google Scholar
- Periasamy, M., Niazi, F. R., Malathi, V. G.2006. Multiplex RT-PCR, a novel technique for the simultaneous detection of the DNA and RNA viruses causing rice tungro disease. J. Virol. Methods. 134, 230--236.Google ScholarCross Ref
- Dasgupta, I. 1991. Rice tungro bacilliform virus DNA independently infects rice after Agrobacterium-mediated transfer. J. Gen. Virol. 72, 1215--1221.Google ScholarCross Ref
- Cullen., B. R. 2004. Transcription and processing of human microRNA precursors; Mol. Cell 16 861--865.Google Scholar
- Kim, S. K., Nam, J. W., Rhee, J. K., Lee, W. J., Zhang, B. T. 2006. miTarget: microRNA target gene prediction using a support vector machine. BMC Bioinformatics. 7. 411.Google Scholar
- Griffiths-Jones, S., Grocock, R. J., Van, D. S., Bateman, A. 2006. Enright AJ miRBase: microRNA sequences, targets and gene nomenclature. Nucleic Acid Research. 34, D140--D144.Google ScholarCross Ref
- Yoon, S., Micheli, G. D. 2006. Computational identification of microRNAs and their targets. Birth Defects Research Part C: Embryo Today: Reviews. 78, 2. 118--128.Google ScholarCross Ref
- Pérez-Quintero, L. A., Neme, R., Zapata, A., López, C., 2010. plant microRNAs and their role in defense against viruses: a bioinformatics approach. BMC. Plant Biology, 10. 138.Google ScholarCross Ref
- Dai, X., Zhao, X. P. 2011. psRNATarget: a plant small RNA targetanalysis server. Nucleic Acids Research. Web Server issue, Vol. 39. 155--159.Google Scholar
- Zhang, Y., Verbeek, J. F. 2010. Comparison and Integration of Target Prediction Algorithms for microRNA Studies, Journal of Integrative Bioinformatics, 7(3). 127.Google ScholarCross Ref
- Tyagi, H., Rajasubramaniam, S., Venkat Rajam, M., Dasgupta, I 2008. RNA-interference in rice against Rice tungro bacilliform viruresults in its decreased accumulation in inoculated rice plants. Transgenic Res.17. 897--904.Google Scholar
- Warthmann, N., Chen, H., Ossowski, S., Weigel, D., Herve, P. 2008. Highly Specific Gene Silencing by Artificial miRNAs in Rice. PLoS ONE. 3, 3. e1829.Google ScholarCross Ref
- Zhang, B., Pan, X., Wang, Q., Cobb, G. P., Anderson, T. A. 2006. Computational identification of microRNAs and their targets. Comput. Biol. Chem.30. 395--407. Google ScholarDigital Library
- Tripathy, R., Mishra, D., Nayak, R. K. 2012. A Computational Approach of Rice (Oryza Sativa) Plant miRNA Target Prediction against Tungro Virus, ICMOC-2012(Accepted).Google Scholar
- Crochemore, M., Hancart, C. 1999. Pattern Matching in Strings, in Algorithms and Theory of Computation Handbook, M.J. Atallah ed., Chapter 11, CRC Press Inc., Boca Raton, FL. 11-1--11-28Google Scholar
- www.ncbi.nlm.nih.gov.Google Scholar
- http://microrna.sanger.ac.uk.Google Scholar
- www.wikipedia.orgGoogle Scholar
Index Terms
- Endogenous rice (Oryza Sativa) miRNAs and their potential targets against Rice Tungro Virus using various string matching algorithms
Recommendations
Hyperspectral characteristics and growth monitoring of rice Oryza sativa under asymmetric warming
Climate warming shows great diurnal variation, with a higher warming rate at night-time, and consequently causes significant impacts on rice growth and development. Soil and plant analyser development SPAD values and leaf area index LAI are important ...
In silico analysis of motifs in promoters of Differentially Expressed Genes in rice (Oryza sativa L.) under anoxia
The aim of this study was to characterise the molecular mechanisms of transcriptional regulation of Differentially Expressed Genes (DEGs) in rice coleoptiles under anoxia by identifying motifs that are common in the promoter region of co-regulated ...
Application of GOCI-derived vegetation index profiles to estimation of paddy rice yield using the GRAMI rice model
Feasibility study of the GOCI satellite for rice yield simulation with GRAMI model.Advantages of GOCI with high temporal resolution to simulate rice growth and development.Method to calculate rice phenology based on the BRDF-adjusted reflectance with ...
Comments