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Title
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Computational identification and analysis of non-coding RNAs in large-scale biological data
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Creator
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Lei, Jikai
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Date
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2015
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Collection
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Electronic Theses & Dissertations
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Description
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Non-protein-coding RNAs (ncRNAs) are RNA molecules that function directly at the level of RNA without translating into protein. They play important biological functions in all three domains of life, i.e. Eukarya, Bacteria and Archaea. To understand the working mechanisms and the functions of ncRNAs in various species, a fundamental step is to identify both known and novel ncRNAs from large-scale biological data.Large-scale genomic data includes both genomic sequence data and NGS sequencing...
Show moreNon-protein-coding RNAs (ncRNAs) are RNA molecules that function directly at the level of RNA without translating into protein. They play important biological functions in all three domains of life, i.e. Eukarya, Bacteria and Archaea. To understand the working mechanisms and the functions of ncRNAs in various species, a fundamental step is to identify both known and novel ncRNAs from large-scale biological data.Large-scale genomic data includes both genomic sequence data and NGS sequencing data. Both types of genomic data provide great opportunity for identifying ncRNAs. For genomic sequence data, a lot of ncRNA identification tools that use comparative sequence analysis have been developed. These methods work well for ncRNAs that have strong sequence similarity. However, they are not well-suited for detecting ncRNAs that are remotely homologous. Next generation sequencing (NGS), while it opens a new horizon for annotating and understanding known and novel ncRNAs, also introduces many challenges. First, existing genomic sequence searching tools can not be readily applied to NGS data because NGS technology produces short, fragmentary reads. Second, most NGS data sets are large-scale. Existing algorithms are infeasible on NGS data because of high resource requirements. Third, metagenomic sequencing, which utilizes NGS technology to sequence uncultured, complex microbial communities directly from their natural inhabitants, further aggravates the difficulties. Thus, massive amount of genomic sequence data and NGS data calls for efficient algorithms and tools for ncRNA annotation.In this dissertation, I present three computational methods and tools to efficiently identify ncRNAs from large-scale biological data. Chain-RNA is a tool that combines both sequence similarity and structure similarity to locate cross-species conserved RNA elements with low sequence similarity in genomic sequence data. It can achieve significantly higher sensitivity in identifying remotely conserved ncRNA elements than sequence based methods such as BLAST, and is much faster than existing structural alignment tools. miR-PREFeR (miRNA PREdiction From small RNA-Seq data) utilizes expression patterns of miRNA and follows the criteria for plant microRNA annotation to accurately predict plant miRNAs from one or more small RNA-Seq data samples. It is sensitive, accurate, fast and has low-memory footprint. metaCRISPR focuses on identifying Clustered Regularly Interspaced Short Palindromic Repeats (CRISPRs) from large-scale metagenomic sequencing data. It uses a kmer hash table to efficiently detect reads that belong to CRISPRs from the raw metagonmic data set. Overlap graph based clustering is then conducted on the reduced data set to separate different CRSIPRs. A set of graph based algorithms are used to assemble and recover CRISPRs from the clusters.
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Title
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The role of microRNA and serine palmitoyltransferase in Alzheimer's disease
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Creator
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Geekiyanage, Hirosha
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Date
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2012
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Collection
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Electronic Theses & Dissertations
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Description
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THE ROLE OF MICRORNA AND SERINE PALMITOYLTRANSFERASE IN ALZHEIMER'S DISEASEByHirosha GeekiyanageThe mechanism by which early-on-set Alzheimer's disease (AD) manifests is well understood. However, little is known about the molecular mechanisms contributing to late-on-set AD, which accounts for >95% of AD cases. Research thus far invariably suggests that elevated ceramide, a sphingolipid, may be a risk factor for AD. Serine palmitoyltransferase (SPT) is not only the first rate limiting enzyme...
Show moreTHE ROLE OF MICRORNA AND SERINE PALMITOYLTRANSFERASE IN ALZHEIMER'S DISEASEByHirosha GeekiyanageThe mechanism by which early-on-set Alzheimer's disease (AD) manifests is well understood. However, little is known about the molecular mechanisms contributing to late-on-set AD, which accounts for >95% of AD cases. Research thus far invariably suggests that elevated ceramide, a sphingolipid, may be a risk factor for AD. Serine palmitoyltransferase (SPT) is not only the first rate limiting enzyme in the de novo synthesis of ceramide but varying SPT levels are consistently associated with varying ceramide levels. I observed that increased ceramide levels in AD are directly regulated by increased SPT levels. I also observed that SPT directly regulates amyloid beta (Aâ) levels through the post-transcriptional regulation of miR-137,-181c,-9 and -29a/b, suggesting SPT and the respective miRNAs are potential therapeutic targets for AD. Therefore, I investigated the use of SPT inhibition as a potential therapeutic strategy for AD. I administered a SPT inhibitor subcutaneously through surgically implanted osmotic pumps into an AD mouse model. I observed that the inhibition of SPT and thus ceramide, reduced cortical Aâ and hyperphosphorylated tau levels, major hallmarks of AD, with statistically significant correlations between SPT, ceramide and Aâ levels. With nominal toxic side effects observed, inhibition of SPT is suggested as a safe potential therapeutic strategy to ameliorate the AD pathology. In addition, I have identified that the afore mentioned miRNAs are reduced in the blood sera of probable AD and amnestic mild cognitive impaired patients, suggesting a potential use for these circulating miRNAs as non-invasive diagnostic biomarkers. In the AD mouse model studied, I observed that these miRNAs show positive correlations between their expressions in the brain cortices and presence in the sera, further suggesting a potential diagnostic role for these circulating miRNAs. A positive correlation was also observed between cortical and sera Aâ levels, providing further insights into the search of blood biomarkers.
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