The identification and characterization of novel RNAs in the mouse transcriptome

Darren Korbie (2011). The identification and characterization of novel RNAs in the mouse transcriptome PhD Thesis, Institute for Molecular Bioscience, The University of Queensland.

       
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Author Darren Korbie
Thesis Title The identification and characterization of novel RNAs in the mouse transcriptome
School, Centre or Institute Institute for Molecular Bioscience
Institution The University of Queensland
Publication date 2011-03
Thesis type PhD Thesis
Total pages 205
Total colour pages 74
Total black and white pages 131
Language eng
Subjects 06 Biological Sciences
Abstract/Summary The eukaryotic transcriptome is populated by many RNAs, and the abundance and diversity of the transcriptome suggests that many novel transcripts remain to be identified. Moreover, since such transcripts can be expressed at low levels, or in a tissue specific or developmentally regulated manner, standard next-generation sequencing (NGS) methodologies are unlikely to detect them. With this in mind, this thesis has explored custom microarray, bioinformatic, and next-generation sequencing strategies to identify and characterize these novel RNA species. An evaluation of the sequence diversity in publicly available next-generation libraries demonstrated that the sequencing output can be dominated by a small number of sequences, which in turn prohibits novel transcript discovery. For this reason a custom array platform based on 40nt LNA probes was initially employed to identify unannotated 20-300nt RNAs in a dataset of 1.7 million stem-loop structures from the mouse genome. The results of that analysis identified candidates that exhibited tissue-specific expression, many of which occurred in ~70-130nt range. From this it was extrapolated that 1% of the original dataset (170,000) may produce small RNAs, and suggests that there are more small RNAs to be found – a conclusion supported by the continued reports of new RNA classes in the literature. Another method to generate transcriptional diversity is through posttranscriptional modification and processing. In particular, posttranscriptional cleavage of RNA can generate a range of small and large transcripts. To this end a detailed analysis of CAGE tags, sequencing libraries, and histone and PolII ChIP-Seq data demonstrated that the vast majority of intraexonic CAGE tags were derived from posttranscriptional processing and represent stable transcripts, in a process that is developmental-stage and tissue-specific. A similar analysis of the 3’ untranslated regions (3’UTRs) of eukaryotic genes also demonstrated that 3’UTRs undergo processing to produce transcripts expressed independently from their full-length mRNAs. The final portion of this thesis represents a synthesis of the concepts established in the first two chapters. Through the use of array-based RNA Capture-Seq I investigate the 30-300 nt fraction of RNA to identify small 3’UTR associated RNAs (uaRNAs) processed from 3’UTRs. The final high-confidence set of uaRNAs identified 4414 small RNAs derived from the 3’UTRs of 1655 genes, many of which exhibited expression that differed markedly from their coding regions. Moreover, some of these candidates incorporated validated miRNA binding regions, which potentially links alternative 3’UTR expression, uaRNA biogenesis, and miRNA interactions together. As well, at least two validated candidates form predicted tRNA-like structures, pointing to a potential role of the RNAse Z/P processing enzymes in their biogenesis, a phenomenon alluded to elsewhere in the literature. In summary, this thesis has employed a variety of methodologies for transcriptome analysis in an attempt to characterize the hidden transcriptional landscape that underlies metazoan cellular complexity. The outcomes of this research expands our understanding of the eukaryotic transcriptome, shows that many of these transcriptional products result from the processing of larger intermediates, and suggests that we have only just begun to appreciate the sophisticated RNA pathways that underlie metazoan complexity.
Keyword ncRNA
noncoding RNA
Capture-Seq
Next-generation sequencing
3' untranslated regions
Additional Notes Colour 3-4,6,49,51,67,71-81,83-90,92-103,105-108,110-112,114,117-120,132,136,138-140,145,152,153,174-178,182,187-192,194,197,202,205 Landscape 106,110,115,132

 
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Created: Mon, 16 Jan 2012, 14:10:48 EST by Mr Darren Korbie on behalf of Library - Information Access Service