14 research outputs found

    Doctor of Philosophy

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    dissertationPost-transcriptional RNA modifications provide new structural and functional features to modified RNA molecules. Extensive research in the past has resulted in isolation of over 100 distinct nucleotide modifications from different organisms and in different RNA species. These modified nucleotides are distributed within the entire transcriptome comprising the cellular epitranscriptome. The ultimate goal of the research in the field is to address what the specific functions of specific modifications are, and also the impact of each on cellular physiology. However, the first question to be addressed is how these > 100 modified nucleotides are distributed within the transcriptome. RNA modification profiling using conventional techniques has provided a great body of knowledge about the distribution of many modifications in RNAs. However, these findings remained limited mostly to tRNAs and rRNAs, the two most abundant and also highly modified RNA species in different organisms. This is partly because of the lower sensitivity of applied classical technologies. Here in this dissertation, in Chapter 2, we are reporting an optimized new RNA bisulfite protocol suitable for high-throughput RNA cytosine methylation profiling. We present the results of application of this technique for 5-methyl-cytosine (m5C) profiling in mouse embryonic fibroblasts (MEFs) RNAs, isolated from wt and dnmt2-/- mice to explore the target specificity of DNA methyltransferase 2 (DNMT2) enzyme. In Chapter 3, we present a substantially novel technique: Aza-IP, for enrichment and identification of the direct targets of RNA cytosine methyltransferases (m5C-RMTs) as well as iv determination of the exact modified bases in the same experiment. We provide the results of the Aza-IP technique for two human m5C-RMTs; DNMT2 and NSUN2, representing their known and novel RNA targets/modified bases. In Chapter 4 we discuss how similar technologies to both of the RNA bisulfite sequencing and Aza-IP techniques as well as other methodologies can be applied and extended for transcriptome-wide profiling of RNA modifications other than m5C. In Chapter 5 we present the future directions of the work focused on cataloguing the direct targets of all human m5C-RMTs in human cultured cells in mouse and fish model systems, to elucidate the functions of cytosine methylation in RNA molecules

    Denoising Opponents Position in Partial Observation Environment

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    The RoboCup competitions hold various leagues, and the Soccer Simulation 2D League is a major among them. Soccer Simulation 2D (SS2D) match involves two teams, including 11 players and a coach for each team, competing against each other. The players can only communicate with the Soccer Simulation Server during the game. Several code bases are released publicly to simplify team development. So researchers can easily focus on decision-making and implementing machine learning methods. SS2D actions and behaviors are only partially accurate due to different challenges, such as noise and partial observation. Therefore, one strategy is to implement alternative denoising methods to tackle observation inaccuracy. Our idea is to predict opponent positions while they have yet to be seen in a finite number of cycles using machine learning methods to make more accurate actions such as pass. We will explain our position prediction idea powered by Long Short-Term Memory models (LSTM) and Deep Neural Networks (DNN). The results show that the LSTM and DNN predict the opponents' position more accurately than the standard algorithm, such as the last-seen method

    The biopsy samples.

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    <p>Mutations known for each sample are listed. SSP-1 to SSP-8 are exome sequenced. Mutations in other samples are tested by OncoCarta3. BRAF-V600E mutation and KRAS codon 12 and 13 mutations are tested by PCR-sequencing in all samples.</p

    Gene expression profiling of colon samples.

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    <p>Hierarchical clustering and sample-to-sample distance heatmap of the expression of protein coding genes. SSP samples are clustered together, FAP samples also clustered together. Gene expression in TSA-2 that has both APC and BRAF mutation is more similar to the pattern of SSP expression cluster. The gene expression pattern of FAP show about 50% similarity to the gene expression of SSP, although the DNA methylation patterns of these two polyp types differ significantly. Therefore studying the DNA methylation marker can lead to detect SSP more specifically than studying the gene expression.</p

    Global methylation changes in SSP and FAP.

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    <p><b>(a)</b> Comparison of FAP with normal samples shows only few DNA methylation changes. From 395,899 CpGs tested on the Infinium array, only 52 CpGs show more than 2 fold increase in methylation in FAP compared to normal colon tissue and 6 CpGs show more than 2 fold reduction in methylation (p-value <0.05). <b>(b)</b> In contrast comparison of SSP with normal samples shows significant DNA methylation changes. From 395,899 CpGs tested on the Infinium array, 42,965 (10.85%) show more than 2 fold increase in methylation in SSP compared to normal colon tissue and 19,019 (4.80%) show more than 2 fold reduction in methylation (p-value <0.05).</p
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