The nucleolus of eukaryotic cells contain a number of the intron-coding small nucleolar RNAs (snoRNAs), which functions are related to covalent modification of pre-rRNAs. The snoRNA that from long, phylogenetically conserved sequence complementarity to 28S, 18S, 5.8S and 5S rRNAs are designated as 28S, 18S, 5.8S and 5S snoRNAs, respectively. In the present study, studying on human 5S snoRNAs had been carried out. The human genome encoding candidate 5S snoRNAs were searched using database mining. The transcripts of 5S snoRNA genes were identified by RT-PCR analyses and DNA sequencing. No appreciable diversities of 5S snoRNA genes were observed as evidenced by single strand conformation polymorphism (SSCP) and high resolution agarose gel. Moreover, sequence conservation of 5S snoRNAs reflects a requirement for maintaining their secondary structure on exerting their function. The results of RT-PCR analyses revealed a tissue-specific transcription of 5S snoRNAs. A 5S snoRNA designated as N117 was identified to be highly expressed in normal brain. On the contrary, its expression markly decreased in brain tumor (meningioma). This seems to be associated with the expression of host gene, which encodes a protein similar to synapsin III protein. Consequently, this may implicate that the use of snoRNA as a potential index for the transcription of its host gene.

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Despite the existence of various molecular marker systems there are still limitations in distinguishing between closely related species based on molecular divergence, especially when hybridization events have occurred in the past. The characterisation of plant small nucleolar RNA (snoRNA) genes and their organisation into multigene clusters provides a potential nuclear marker system which could help in resolving the phylogenetic history of plants and might be applicable in DNA barcoding. Using closely and distantly related Senecio species, I investigated a combination of fragment length and sequence variation of snoRNA genes/snoRNA gene clusters to assess the utility of this marker system for barcoding and resolving species relationships. SnoRNA gene and gene cluster sequences identified in Arabidopsis thaliana were used to find homologues in other species and subsequently used for the design of universal primers. Most of the universal primer pairs designed were successful in amplifying snoRNA fragments in most Senecio species and fragment length variation between and within species could be detected. Furthermore, the combination of some fragment length datasets produced by different primer pairs enabled the separation of species and the detection of reticulate evolution indicating a high potential of snoRNA gene/gene cluster fragment length polymorphisms (SRFLPs) for phylogenetic reconstructions in Senecio and other plant genera. Most of the examined gene clusters showed a similar gene order in Senecio and Arabidopsis. However, the majority of these clusters appeared to exhibit more copies in Senecio, some of which were distinguishable by a combined sequencing/fragment profiling approach, and shown to be putative single copy regions with the potential to be used as co-dominant markers. However, a high number of paralogues and possible differences in copy number between species excludes these regions from being used in DNA barcoding. This is because specific primers would have to be developed for specific copies which would preclude development of a universal application for barcoding. None of the regions showed enough sequence variation to delimit distinctly closely related Senecio species and were therefore also considered to be unsuitable for DNA barcoding. Although most snoRNA genes and gene clusters might be inapplicable for DNA barcoding, they are likely to be valuable for phylogenetic studies of species groups, genera and families. On this scale, specific primers might act universally and the number of paralogous copies is likely to be equal across the species group of interest.

Genome sequencing has yielded unparalleled insights into fundamental biological processes and the genetics that guide them. In contrast to expectations that protein-coding genes would be the primary output of eukaryotic genomes, however, it is now clear that the vast majority of transcription is devoted to noncoding RNAs (ncRNAs). Although originally regarded as 'transcriptional noise', it is now clear that these transcripts are essential regulators of genetic activity. In this thesis I build upon the hypothesis that the genomes of eukaryotes encode a regulatory 'RNA machine' dominated by ncRNAs. In the Introduction (Chapter 1) I discuss how prior gene models may have inadvertently prevented a full understanding of ncRNAs, review the transcriptional landscape of eukaryotes, and examine the biogenesis and function of small regulatory RNAs. In support of a role for ncRNAs in complex metazoa, Chapter 2 presents data showing a positive correlation between the proportion of non-protein-coding DNA and biological complexity, suggesting that the evolutionary trajectory of intricate developmental phenotypes may have been facilitated by ncRNAs. In the following chapters two more 'gears' are added to the RNA machine. Chapter 3 details the discovery of snoRNA-derived RNAs - an evolutionarily ancient class of Argonaute-assocaited RNA whose biogenesis overlaps with microRNAs (miRNAs) and silencing RNAs (siRNAs). Likewise, Chapter 4 reports a new class of ~18 nt transcription initiation RNAs (tiRNAs) derived from regions proximal to transcription start sites. tiRNAs are enriched at GC-rich promoters and regions of active transcription, implicating them in transcriptional regulation. Chapter 5 presents evidence that tiRNAs are restricted to metazoa, and describes a model of RNA Polymerase II dependent tiRNA biogenesis. This thesis concludes with a general discussion of the implications of these findings, and the potential development of RNA therapeutics. Gathering evidence suggests that eukaryotic genomes are driven by a complex and interwoven network of RNA regulatory feedback loops. This thesis takes a small step towards developing a complete picture of this system.

Genome sequencing has yielded unparalleled insights into fundamental biological processes and the genetics that guide them. In contrast to expectations that protein-coding genes would be the primary output of eukaryotic genomes, however, it is now clear that the vast majority of transcription is devoted to noncoding RNAs (ncRNAs). Although originally regarded as 'transcriptional noise', it is now clear that these transcripts are essential regulators of genetic activity. In this thesis I build upon the hypothesis that the genomes of eukaryotes encode a regulatory 'RNA machine' dominated by ncRNAs. In the Introduction (Chapter 1) I discuss how prior gene models may have inadvertently prevented a full understanding of ncRNAs, review the transcriptional landscape of eukaryotes, and examine the biogenesis and function of small regulatory RNAs. In support of a role for ncRNAs in complex metazoa, Chapter 2 presents data showing a positive correlation between the proportion of non-protein-coding DNA and biological complexity, suggesting that the evolutionary trajectory of intricate developmental phenotypes may have been facilitated by ncRNAs. In the following chapters two more 'gears' are added to the RNA machine. Chapter 3 details the discovery of snoRNA-derived RNAs - an evolutionarily ancient class of Argonaute-assocaited RNA whose biogenesis overlaps with microRNAs (miRNAs) and silencing RNAs (siRNAs). Likewise, Chapter 4 reports a new class of ~18 nt transcription initiation RNAs (tiRNAs) derived from regions proximal to transcription start sites. tiRNAs are enriched at GC-rich promoters and regions of active transcription, implicating them in transcriptional regulation. Chapter 5 presents evidence that tiRNAs are restricted to metazoa, and describes a model of RNA Polymerase II dependent tiRNA biogenesis. This thesis concludes with a general discussion of the implications of these findings, and the potential development of RNA therapeutics. Gathering evidence suggests that eukaryotic genomes are driven by a complex and interwoven network of RNA regulatory feedback loops. This thesis takes a small step towards developing a complete picture of this system.