Abstract
The recent publication of the Chinese hamster ovary (CHO) genome has heralded the beginning of an exciting new era of research in this industrially important cell line. Advances in our understanding of CHO at the molecular level have the potential to facilitate the development of modified cell lines and biomarkers to increase the efficiency of recombinant protein production processes. In recent years there has been growing interest in the function of small non-coding RNA molecules, known as microRNAs (miRNAs), as targets to enable multigene CHO cell engineering. To date, miRNAs have been shown to be dysregulated in a number of processes including cell growth and apoptosis.
Bioinformatics has proven to be an essential supporting technology for miRNA based studies. In this chapter, we review a new class of miRNA specific in-silico tool developed to predict which mRNAs a particular miRNA targets in order to determine the impact of a miRNA on biological function. A range of popular miRNA target prediction algorithms are presented, their underlying principles described and performance assessed. In addition, publically available repositories of miRNA sequence, expression profiling and target data are highlighted. Finally, examples of the utilisation of these tools to study CHO cells are presented.
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This work was supported by funding from Science Foundation Ireland (SFI) grant number 07/IN.1/B1323.
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Clarke, C., Barron, N., Gallagher, M., Henry, M., Meleady, P., Clynes, M. (2012). Target Prediction Algorithms and Bioinformatics Resources for miRNA Studies. In: Barron, N. (eds) MicroRNAs as Tools in Biopharmaceutical Production. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-5128-6_3
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