The root system of a plant serves to anchor a plant to its terrain, to take up water and nutrients and to provide resistance to various biotic and abiotic stresses. Understanding the mechanisms dictating root, and lateral root (LR) development is crucial for work towards global food security. In the last two decades, microRNAs have been found to play crucial roles in many plant developmental processes. Up to now, no global expression profiling has focused specifically on Arabidopsis thaliana LR development. This study utilised mRNA and small RNA sequencing in order to build two large datasets. RNA was taken from developing LR primordia at selected stages and sequenced. The two datasets were validated and found to be of great depth and quality. They were complimented by an Affymetrix dataset (Voβ et al., 2015). A large number of differentially expressed, known microRNAs were identified as were a large number of targets. In many cases, expression of miRNAs and their targets during LR development revealed seemingly reciprocal expression patterns including a number which have previously been linked to LR development. In some cases, miRNA/target couples were highlighted as having a potential, unreported, role in LR development. This study focused particularly on the potential role of the miR159 family and one if its targets, the transcription factor MYB33. This study reports a dramatic LR defect in a miR159ab double mutant and a miR159 target mimic line and discusses a potential regulatory role of this miRNA and this target during LR initiation. As well as this, ten novel microRNAs were identified and validated. Putative targets were identified for a number of these microRNAs. This study produced overexpression lines for two of these microRNAs though no phenotype was identified. No significant developmental defects were identified in the roots of mutants for a number of the putative targets. This study presents the first comprehensive analysis of global expression profiling during LR development and has resulted in the production of two high quality datasets.
Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:689816 |
Date | January 2016 |
Creators | Denyer, Tom |
Publisher | University of Nottingham |
Source Sets | Ethos UK |
Detected Language | English |
Type | Electronic Thesis or Dissertation |
Source | http://eprints.nottingham.ac.uk/32619/ |
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