Computational analysis of small RNAs and the RNA degradome with application to plant water stress

Folkes, Leighton (2014) Computational analysis of small RNAs and the RNA degradome with application to plant water stress. Doctoral thesis, University of East Anglia.

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Abstract

Water shortage is one of the most important environmental stress factors that affects plants, limiting crop yield in large areas worldwide. Plants can survive water stress by regulating gene expression at several levels. One of the recently discovered regulatory mechanisms involves small RNAs (sRNAs), which can regulate gene expression by targeting messenger RNAs (mRNAs) and directing endonucleolytic cleavage resulting in mRNA degradation.
A snapshot of an mRNA degradation profile (degradome) can be captured through a new high-throughput technique called Parallel Analysis of RNA Ends (PARE) by using next generation sequencing technologies. In this thesis we describe a new user friendly degradome analysis software tool called PAREsnip that we have used for the rapid genome-wide discovery of sRNA/target interactions evidenced through the degradome. In addition to PAREsnip and based upon PAREsnip’s rapid capability, we also present a new software tool for the construction, analysis and visualisation of sRNA regulatory interaction networks. The two new tools were used to analyse PARE datasets obtained fromMedicago truncatula and Arabidopsis thaliana.
In particular, we have used PAREsnip for the high-throughput analysis of PARE data obtained from Medicago when subjected to dehydration and found several sRNA/mRNA interactions that are potentially responsive to water stress. We also present how we used our new network visualisation and analysis tool with PARE datasets obtained from Arabidopsis and discovered several novel sRNA regulatory interaction networks. In building tools and using them for this kind of analysis, we gain a better understanding of the processes and mechanisms involved in sRNA mediated gene regulation and how plants respond to water stress which could lead to new strategies in improving stress tolerance.

Item Type:	Thesis (Doctoral)
Faculty \ School:	Faculty of Science > School of Computing Sciences
Depositing User:	Users 2593 not found.
Date Deposited:	27 Jan 2015 16:20
Last Modified:	24 Nov 2015 01:38
URI:	https://ueaeprints.uea.ac.uk/id/eprint/52038
DOI:

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