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Title: Deciphering the regulatory mechanisms of small RNAs in plants
Author: Mohorianu, Irina-Ioana
ISNI:       0000 0004 2740 2018
Awarding Body: University of East Anglia
Current Institution: University of East Anglia
Date of Award: 2012
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Small RN As (sRNAs) are 20-25 nucleotides long non-coding RN As that act as guides for the highly sequence-specific regulatory mechanism in eukary- otes known as RNA silencing. Plants are known to produce a highly complex and diverse population of regulatory sRNAs involved in different processes, such as transcriptional and post-transcriptional regulation of gene expres- sion levels, genome maintenance and defense against pathogens. Until now the computational methods have mainly focused on the identifica- tion and description of a special class of sRNAs, called miRNAs. However, it has been shown that plants can produce various other classes of sRNAs such as ta-siRNAs, nat-si RNAs, hcRNAs and probably others. These sR- NAs have special properties and response patterns to variation of gene ex- pression level which are not yet well understood. In this thesis we propose computational methods to study the regulatory roles of plant sRNAs such as unsupervised learning of sRNA expression patterns (clustering), identification of putative interactions between sR- NAs and mRNAs based on correlation between (simplified) expression levels (FiRePat and SimCarr) and a pattern based approach for the prediction of sRNA loci (CaLlde). To characterize sRNAsj sRNA loci we corroborate information such as their expression profiles, nucleotide composition, size, abundance, location on the genome and annotations, the expression profiles and description of the genes that these might regulate. We develop tech- niques to analyze data coming from large and small scale experiments such as high throughput sequencing and northern blots for sRNAs, and microar- rays and RT-qPCR for messenger RNA. The different layers of information help with assigning functions to the sRN As and organizing the large num- ber of sRNA reads into smaller, manageable sets, some of which validated in wet-lab experiments. 1
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available