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Computational prediction of microRNAs from Oil Palm (Elaeis guineensis Jacq.)expressed sequence tags

Nadirah Md Nasaruddin, and Harikrishna, K., and Rofina Yasmin Othman, and Lim, S.H., and Harikrishna, Jennifer Ann, (2007) Computational prediction of microRNAs from Oil Palm (Elaeis guineensis Jacq.)expressed sequence tags. Asia Pacific Journal of Molecular Biology & Biotechnology, 15 (3). pp. 107-113.

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Affiliations

Sime Darby Technology Centre Sdn Bhd
Sime Darby Technology Centre Sdn Bhd
University of Malaya. Faculty of Science. Institute of Biological Sciences
Malaysia University of Science and Technology
University of Malaya. Faculty of Science. Institute of Biological Sciences

Abstract

MicroRNAs (miRNAs) are defined as ~22nt non-coding RNAs derived from one arm of longer hairpin stem-loop precursors through the action of Dicer, that are capable of silencing gene activities at the transcriptional or post-transcriptional level. miRNA plays important regulatory roles in animal and plant development and as such the identification of miRNA encoding regions of genomes is an important part of gene annotation and functional genomics. A total of ���7,284 Elaeis guineensis Jacq. expressed sequence tags (EST) were compared to previously known Arabidopsis thaliana and Oryza sativa miRNA, to search for novel miRNA from oil palm. Twenty-five EST contigs with homology to previously known miRNAs were identified. After predicting the RNA secondary structure, five new potential miRNA were identified in oil palm. One of the most promising potential miRNA was miR160 which has very strong characteristics of an miRNA precursor structure and 100% identity with the mature miR160 from other plant species.

Item Type:Journal
Keywords:miRNA, oil palm, Elaeis guineensis Jacq., expressed sequence tags
Subjects:Q Science, Computer Science
ID Code:3688

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