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1
Russell, Rodney S. "Novel RNA and protein sequences involved in dimerization and packaging of HIV-1 genomic RNA." Thesis, McGill University, 2004. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=85092.
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During HIV-1 assembly, the Gag structural protein specifically encapsidates two copies of viral genomic RNA in the form of a dimer. An RNA stem-loop structure (SL1) in the 5' untranslated region, known as the dimerization initiation site (DIS), is important for dimerization and packaging of HIV-1 genomic RNA; however, the mechanisms involved are not fully understood. The major goal of this PhD study was to further understand HIV-1 RNA dimerization, and to study the role of the Gag protein in the dimerization and packaging processes. Despite the known involvement of the DIS in RNA dimerization, DIS-mutated viruses still contain significant levels of dimerized RNA, and electron microscopy studies suggest that the RNA molecules are linked at the extreme 5' end. We show here that RNA sequences on both sides of the DIS are also required for HIVA genome dimerization, suggesting that multiple RNA elements are involved. We have also examined the contribution of specific amino acids within Gag to the dimerization and packaging processes. Previous work showed that partial deletion of the DIS impacted on viral replication capacity, but could largely be corrected by compensatory point mutations within Gag. To further elucidate the mechanism(s) of these compensatory mutations, we generated DIS mutants lacking the entire SL1, or only the SL1 loop sequences, and combined these deletions with various combinations of compensatory mutations. Analysis of virion-derived RNA showed that the relevant mutant viruses contained increased levels of spliced viral RNA compared to wild type, indicating that a defect in genome packaging specificity was present. However, this defect was corrected by our compensatory mutations, and a T121 substitution in p2 was shown to be solely responsible for this activity. These results suggest that the p2 spacer peptide plays a critical role in the specific packaging of viral genomic RNA. In summary, these findings provide new insig
2
O'Hanlon, Karen Ann. "Studies on the enzyme DNA-dependent RNA polymerase." Thesis, University of Reading, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.266340.
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鄭隆峰 and Lung-fung Cheng. "Modelling and sequence analysis of the collagen triple helix." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2001. http://hub.hku.hk/bib/B31969914.
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4
Cheng, Lung-fung. "Modelling and sequence analysis of the collagen triple helix." Hong Kong : University of Hong Kong, 2001. http://sunzi.lib.hku.hk/hkuto/record.jsp?B2373615X.
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5
Millar, N. S. "Molecular cloning and sequence analysis of Newcastle disease virus." Thesis, University of Newcastle Upon Tyne, 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.380750.
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6
Coco, Joseph. "PARSES: A Pipeline for Analysis of RNA-Sequencing Exogenous Sequences." ScholarWorks@UNO, 2011. http://scholarworks.uno.edu/td/1297.
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RNA-Sequencing (RNA-Seq) has become one of the most widely used techniques to interrogate the transcriptome of an organism since the advent of next generation sequencing technologies [1]. A plethora of tools have been developed to analyze and visualize the transcriptome data from RNA-Seq experiments, solving the problem of mapping reads back to the host organism's genome [2] [3]. This allows for analysis of most reads produced by the experiments, but these tools typically discard reads that do not match well with the reference genome. This additional information could reveal important insight into the experiment and possible contributing factors to the condition under consideration. We introduce PARSES, a pipeline constructed from existing sequence analysis tools, which allows the user to interrogate RNA-Sequencing experiments for possible biological contamination or the presence of exogenous sequences that may shed light on other factors influencing an organism's condition.
7
Giorgini, Flaviano. "Functional analysis of the murine sequence-specific RNA binding protein MSY4 /." Thesis, Connect to this title online; UW restricted, 2002. http://hdl.handle.net/1773/10293.
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8
Mohamed, Maizan. "Sequence analysis of the small (s) RNA segment of viruses in the genus Orthobunyavirus." Thesis, St Andrews, 2007. http://hdl.handle.net/10023/434.
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9
Fortino, Vittorio. "Sequence analysis in bioinformatics: methodological and practical aspects." Doctoral thesis, Universita degli studi di Salerno, 2013. http://hdl.handle.net/10556/985.
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2011 - 2012My PhD research activities has focused on the development of new computational methods for biological sequence analyses. To overcome an intrinsic problem to protein sequence analysis, whose aim was to infer homologies in large biological protein databases with short queries, I developed a statistical framework BLAST-based to detect distant homologies conserved in transmembrane domains of different bacterial membrane proteins. Using this framework, transmembrane protein domains of all Salmonella spp. have been screened and more than five thousands of significant homologies have been identified. My results show that the proposed framework detects distant homologies that, because of their conservation in distinct bacterial membrane proteins, could represent ancient signatures about the existence of primeval genetic elements (or mini-genes) coding for short polypeptides that formed, through a primitive assembly process, more complex genes. Further, my statistical framework lays the foundation for new bioinformatics tools to detect homologies domain-oriented, or in other words, the ability to find statistically significant homologies in specific target-domains. The second problem that I faced deals with the analysis of transcripts obtained with RNA-Seq data. I developed a novel computational method that combines transcript borders, obtained from mapped RNA-Seq reads, with sequence features based operon predictions to accurately infer operons in prokaryotic genomes. Since the transcriptome of an organism is dynamic and condition dependent, the RNA-Seq mapped reads are used to determine a set of confirmed or predicted operons and from it specific transcriptomic features are extracted and combined with standard genomic features to train and validate three operon classification models (Random Forests - RFs, Neural Networks – NNs, and Support Vector Machines - SVMs). These classifiers have been exploited to refine the operon map annotated by DOOR, one of the most used database of prokaryotic operons. This method proved that the integration of genomic and transcriptomic features improve the accuracy of operon predictions, and that it is possible to predict the existence of potential new operons. An inherent limitation of using RNA-Seq to improve operon structure predictions is that it can be not applied to genes not expressed under the condition studied. I evaluated my approach on different RNA-Seq based transcriptome profiles of Histophilus somni and Porphyromonas gingivalis. These transcriptome profiles were obtained using the standard RNA-Seq or the strand-specific RNA-Seq method. My experimental results demonstrate that the three classifiers achieved accurate operon maps including reliable predictions of new operons. [edited by author]
XI n.s.
10
Wang, Suyue. "Characterization of a Human 28S Ribosomal RNA Retropseudogene and Other Repetitive DNA Sequence Elements Isolated from a Human X Chromosome-Specific Library." Thesis, University of North Texas, 1994. https://digital.library.unt.edu/ark:/67531/metadc278083/.
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Three genomic clones encompassing human DNA segments (designated LhX-3, LhX-4, and LhX5) were isolated from an X chromosome-specific library and subjected to analysis by physical mapping and DNA sequencing. It was found that these three clones are very rich in repetitive DNA sequence elements and retropseudogenes.
11
McCann, Eamon Martin. "Analysis of the role of the HIV-2 leader sequence in genomic RNA packaging." Thesis, University of Cambridge, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.627112.
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Lundmark, Per Erik. "Genetic and Genomic Analysis of DNA Sequence Variation." Doctoral thesis, Uppsala universitet, Molekylär medicin, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-158486.
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The studies in this thesis describe the application of genotyping and allele specific expression analysis to genetic studies. The role of the gene NPC1 in Triglyceride metabolism was explored in mouse models and in humans on the population level in study I. NPC1 was found to affect hepatic triglyceride metabolism, and to be relevant for controlling serum triglyceride levels in mice and potentially in humans. In study II the utility of the HapMap CEU samples was investigated for tagSNP selection in six European populations. The HapMap CEU was found to be representative for tagSNP selection in all populations while allele frequencies differed significantly in the sample from Kuusamo, Finland. In study III the power of Allele specific expression as a tool for the mapping of cis-regulatory variation was compared to standard eQTL analysis, ASE was found to be the more powerful type of analysis for a similar sample size. Finally ASE mapping was applied to regions reported to harbour long non-coding RNAs and associated SNPs were compared to published trait-associations. This revealed strong cis-regulatory SNPs of long non-coding RNAs with reported trait or disease associations.
13
Freyhult, Eva. "A Study in RNA Bioinformatics : Identification, Prediction and Analysis." Doctoral thesis, Uppsala : Acta Universitatis Upsaliensis Acta Universitatis Upsaliensis, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-8305.
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Warwick, Simon. "Analysis of ribosomal RNA sequence from actinomycetes and production of probes from commercially important strains." Thesis, University of East London, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.264411.
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15
Gersappe, Anand. "An analysis of genetic determinants that govern exon definition and alternative splicing of minute virus of mice (MVM) pre-mRNAs." free to MU campus, to others for purchase, 1998. http://wwwlib.umi.com/cr/mo/fullcit?p9904842.
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16
Batra, Sushil Baker Erich J. Lee Myeongwoo. "Identification of phenotypes in Caenorabhditis elegans on the basis of sequence similarity." Waco, Tex. : Baylor University, 2009. http://hdl.handle.net/2104/5325.
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Fasold, Mario. "Hybridization biases of microarray expression data - A model-based analysis of RNA quality and sequence effects." Doctoral thesis, Universitätsbibliothek Leipzig, 2013. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-116957.
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Modern high-throughput technologies like DNA microarrays are powerful
tools that are widely used in biomedical research. They target a
variety of genomics applications ranging from gene expression
profiling over DNA genotyping to gene regulation studies. However, the
recent discovery of false positives among prominent research findings
indicates a lack of awareness or understanding of the non-biological
factors negatively affecting the accuracy of data produced using these
technologies. The aim of this thesis is to study the origins, effects
and potential correction methods for selected methodical biases in
microarray data.
The two-species Langmuir model serves as the basal physicochemical
model of microarray hybridization describing the fluorescence signal
response of oligonucleotide probes. The so-called hook method allows
to estimate essential model parameters and to compute summary
parameters characterizing a particular microarray sample. We show that
this method can be applied successfully to various types of
microarrays which share the same basic mechanism of multiplexed
nucleic acid hybridization.
Using appropriate modifications of the model we study RNA quality and
sequence effects using publicly available data from Affymetrix
GeneChip expression arrays. Varying amounts of hybridized RNA result
in systematic changes of raw intensity signals and appropriate
indicator variables computed from these. Varying RNA quality strongly
affects intensity signals of probes which are located at the 3\' end of
transcripts. We develop new methods that help assessing the RNA
quality of a particular microarray sample. A new metric for
determining RNA quality, the degradation index, is proposed which
improves previous RNA quality metrics. Furthermore, we present a
method for the correction of the 3\' intensity bias. These
functionalities have been implemented in the freely available program
package AffyRNADegradation.
We show that microarray probe signals are affected by sequence effects
which are studied systematically using positional-dependent
nearest-neighbor models. Analysis of the resulting sensitivity
profiles reveals that specific sequence patterns such as runs of
guanines at the solution end of the probes have a strong impact on the
probe signals. The sequence effects differ for different chip- and
target-types, probe types and hybridization modes. Theoretical and
practical solutions for the correction of the introduced sequence bias
are provided.
Assessment of RNA quality and sequence biases in a representative
ensemble of over 8000 available microarray samples reveals that RNA
quality issues are prevalent: about 10% of the samples have
critically low RNA quality. Sequence effects exhibit considerable
variation within the investigated samples but have limited impact on
the most common patterns in the expression space. Variations in RNA
quality and quantity in contrast have a significant impact on the
obtained expression measurements.
These hybridization biases should be considered and controlled in
every microarray experiment to ensure reliable results. Application of
rigorous quality control and signal correction methods is strongly
advised to avoid erroneous findings. Also, incremental refinement of
physicochemical models is a promising way to improve signal
calibration paralleled with the opportunity to better understand the
fundamental processes in microarray hybridization.
18
Oguchi, Chizoba. "A Comparison of Sensitive Splice Aware Aligners in RNA Sequence Data Analysis in Leaping towards Benchmarking." Thesis, Högskolan i Skövde, Institutionen för biovetenskap, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-18513.
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Bioinformatics, as a field, rapidly develops and such development requires the design ofalgorithms and software. RNA-seq provides robust information on RNAs, both alreadyknown and new, hence the increased study of the RNA. Alignment is an important step indownstream analyses and the ability to map reads across splice junctions is a requirement ofan aligner to be suitable for mapping RNA-seq reads. Therefore, the necessity for a standardsplice-aware aligner. STAR, Rsubread and HISAT2 have not been singly studied for thepurpose of benchmarking one of them as a standard aligner for spliced RNA-seq reads. Thisstudy compared these aligners, found to be sensitive to splice sites, with regards to theirsensitivity to splice sites, performance with default parameter settings and the resource usageduring the alignment process. The aligners were matched with featureCounts. The resultsshow that STAR and Rsubread outperform HISAT2 in the aspects of sensitivity and defaultparameter settings. Rsubread was more sensitive to splice junctions than STAR butunderperformed with featureCounts. STAR had a consistent performance, with more demandon the memory and time resource, but showed it could be more sensitive with real data.
19
Nindo, Fredrick Nzabanyi. "Exploring the phylodynamics, genetic reassortment and RNA secondary structure formation patterns of orthomyxoviruses by comparative sequence analysis." Doctoral thesis, Faculty of Health Sciences, 2019. https://hdl.handle.net/11427/31729.
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RNA viruses are among the most virulent microorganisms that threaten the health of humans and livestock. Among the most socio-economically important of the known RNA viruses are those found in the family Orthomyxovirus. In this era of rapid low-cost genome sequencing and advancements in computational biology techniques, many previously difficult research questions relating to the molecular epidemiology and evolutionary dynamics of these viruses can now be answered with ease. Using sequence data together with associated meta-data, in chapter two of this dissertation I tested the hypothesis that the Influenza A/H1N1 2009 pandemic virus was introduced multiple times into Africa, and subsequently dispersed heterogeneously across the continent. I further tested to what degree factors such as road distances and air travel distances impacted the observed pattern of spread of this virus in Africa using a generalised linear modelbased approach. The results suggested that their were multiple simultaneous introductions of 2009 pandemic A/H1N1 into Africa, and geographical distance and human mobility through air travel played an important role towards dissemination. In chapter three, I set out to test two hypotheses: (1) that there is no difference in the frequency of reassortments among the segments that constitute influenza virus genomes; and (2) that there is epochal temporal reassortment among influenza viruses and that all geographical regions are equally likely sources of epidemiologically important influenza virus reassortant lineages. The findings suggested that surface segments are more frequently exchanges than internal genes and that North America/Asia, Oceania, and Asia could be the most likely source locations for reassortant Influenza A, B and C virus lineages respectively. In chapter four of this thesis, I explored the formation of RNA secondary structures within the genomes of orthomyxoviruses belonging to five genera: Influenza A, B and C, Infectious Salmon Anaemia Virus and Thogotovirus using in silico RNA folding predictions and additional molecular evolution and phylogenetic tests to show that structured regions may be biologically functional. The presence of some conserved structures across the five genera is likely a reflection of the biological importance of these structures, warranting further investigation regarding their role in the evolution and possible development of antiviral resistance. The studies herein demonstrate that pathogen genomics-based analytical approaches are useful both for understanding the mechanisms that drive the evolution and spread of rapidly evolving viral pathogens such as orthomyxoviruses, and for illuminating how these approaches could be leveraged to improve the management of these pathogens.
20
Ohlson, Johan. "Novel sites of A-to-I RNA editing in the mammalian brain." Doctoral thesis, Stockholm : Department of Molecular Biology and Functional Genomics, Stockholm University, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-7045.
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21
Ajuh, Paul Munya. "28S ribosomal RNA in Xenopus : gene sequence analysis and secondary structure probing of in vitro and in vivo transcripts." Thesis, University of Liverpool, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.304878.
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22
Herman, Joseph L. "Multiple sequence analysis in the presence of alignment uncertainty." Thesis, University of Oxford, 2014. http://ora.ox.ac.uk/objects/uuid:88a56d9f-a96e-48e3-b8dc-a73f3efc8472.
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Sequence alignment is one of the most intensely studied problems in bioinformatics, and is an important step in a wide range of analyses. An issue that has gained much attention in recent years is the fact that downstream analyses are often highly sensitive to the specific choice of alignment. One way to address this is to jointly sample alignments along with other parameters of interest. In order to extend the range of applicability of this approach, the first chapter of this thesis introduces a probabilistic evolutionary model for protein structures on a phylogenetic tree; since protein structures typically diverge much more slowly than sequences, this allows for more reliable detection of remote homologies, improving the accuracy of the resulting alignments and trees, and reducing sensitivity of the results to the choice of dataset. In order to carry out inference under such a model, a number of new Markov chain Monte Carlo approaches are developed, allowing for more efficient convergence and mixing on the high-dimensional parameter space. The second part of the thesis presents a directed acyclic graph (DAG)-based approach for representing a collection of sampled alignments. This DAG representation allows the initial collection of samples to be used to generate a larger set of alignments under the same approximate distribution, enabling posterior alignment probabilities to be estimated reliably from a reasonable number of samples. If desired, summary alignments can then be generated as maximum-weight paths through the DAG, under various types of loss or scoring functions. The acyclic nature of the graph also permits various other types of algorithms to be easily adapted to operate on the entire set of alignments in the DAG. In the final part of this work, methodology is introduced for alignment-DAG-based sequence annotation using hidden Markov models, and RNA secondary structure prediction using stochastic context-free grammars. Results on test datasets indicate that the additional information contained within the DAG allows for improved predictions, resulting in substantial gains over simply analysing a set of alignments one by one.
23
Hu, Haiyang [Verfasser]. "Computational and Statistical Analysis of Sequence and Expression Features of MicroRNA and Long Noncoding RNA in Primate Brains / Haiyang Hu." Berlin : Freie Universität Berlin, 2016. http://d-nb.info/1093404175/34.
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Mwinyi, Adina, Achim Meyer, Christoph Bleidorn, Bernhard Lieb, Thomas Bartolomaeus, and Lars Podsiadlowski. "Mitochondrial genome sequence and gene order of Sipunculus nudus give additional support for an inclusion of Sipuncula into Annelida." Universität Potsdam, 2009. http://opus.kobv.de/ubp/volltexte/2010/4491/.
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Background:
Mitochondrial genomes are a valuable source of data for analysing phylogenetic
relationships. Besides sequence information, mitochondrial gene order may add phylogenetically useful information, too. Sipuncula are unsegmented marine worms, traditionally placed in their own phylum. Recent molecular and morphological findings suggest a close affinity to the segmented Annelida.
Results:
The first complete mitochondrial genome of a member of Sipuncula, Sipunculus nudus, is presented. All 37 genes characteristic for metazoan mtDNA were detected and are encoded on the same strand. The mitochondrial gene order (protein-coding and ribosomal RNA genes) resembles that of annelids, but shows several derivations so far found only in Sipuncula. Sequence based phylogenetic analysis of mitochondrial protein-coding genes results in significant bootstrap
support for Annelida sensu lato, combining Annelida together with Sipuncula, Echiura, Pogonophora and Myzostomida.
Conclusion:
The mitochondrial sequence data support a close relationship of Annelida and
Sipuncula. Also the most parsimonious explanation of changes in gene order favours a derivation from the annelid gene order. These results complement findings from recent phylogenetic analyses of nuclear encoded genes as well as a report of a segmental neural patterning in Sipuncula.
25
Bajak, Edyta Zofia. "Genotoxic stress: novel biomarkers and detection methods : uncovering RNAs role in epigenetics of carcinogenesis /." Stockholm, 2005. http://diss.kib.ki.se/2005/91-7140-415-5/.
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Hodges, Emily Carol. "High resolution genomic tools for the discovery of protein function in mammalian cells /." Stockholm, 2006. http://diss.kib.ki.se/2006/91-7140-775-8/.
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Henriksson, William. "High dimensional data clustering; A comparative study on gene expressions : Experiment on clustering algorithms on RNA-sequence from tumors with evaluation on internal validation." Thesis, Högskolan i Skövde, Institutionen för informationsteknologi, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-17492.
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In cancer research, class discovery is the first process for investigating a new dataset for which hidden groups there are by similar attributes. However datasets from gene expressions, RNA microarray or RNA-sequence, are high-dimensional. Which makes it hard to perform clusteranalysis and to get clusters that are well separated. Well separated clusters are wanted because that tells that objects are most likely not placed in wrong clusters. This report investigate in an experiment whether using K-Means and hierarchical are suitable for clustering gene expressions in RNA-sequence data from various tumors. Dimensionality reduction methods are also applied to see whether that helps create well-separated clusters. The results tell that well separated clusters are only achieved by using PCA as dimensionality reduction and K-Means on correlation. The main contribution of this paper is determining that using K-Means or hierarchical clustering on the full natural dimensionality of RNA-sequence data returns unwanted silhouette average width, under 0,4.
28
Buchholz, Frank, Anja Nitzsche, Maciej Paszkowski-Rogacz, Filomena Matarese, Eva M. Janssen-Megens, Nina C. Hubner, Herbert Schulz, et al. "RAD21 Cooperates with Pluripotency Transcription Factors in the Maintenance of Embryonic Stem Cell Identity." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2016. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-191596.
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For self-renewal, embryonic stem cells (ESCs) require the expression of specific transcription factors accompanied by a particular chromosome organization to maintain a balance between pluripotency and the capacity for rapid differentiation. However, how transcriptional regulation is linked to chromosome organization in ESCs is not well understood. Here we show that the cohesin component RAD21 exhibits a functional role in maintaining ESC identity through association with the pluripotency transcriptional network. ChIP-seq analyses of RAD21 reveal an ESC specific cohesin binding pattern that is characterized by CTCF independent co-localization of cohesin with pluripotency related transcription factors Oct4, Nanog, Sox2, Esrrb and Klf4. Upon ESC differentiation, most of these binding sites disappear and instead new CTCF independent RAD21 binding sites emerge, which are enriched for binding sites of transcription factors implicated in early differentiation. Furthermore, knock-down of RAD21 causes expression changes that are similar to expression changes after Nanog depletion, demonstrating the functional relevance of the RAD21 - pluripotency transcriptional network association. Finally, we show that Nanog physically interacts with the cohesin or cohesin interacting proteins STAG1 and WAPL further substantiating this association. Based on these findings we propose that a dynamic placement of cohesin by pluripotency transcription factors contributes to a chromosome organization supporting the ESC expression program.
29
Fasold, Mario [Verfasser], Hans [Akademischer Betreuer] Binder, Peter [Gutachter] Stadler, and Andrew [Gutachter] Harrison. "Hybridization biases of microarray expression data - A model-based analysis of RNA quality and sequence effects / Mario Fasold ; Gutachter: Peter Stadler, Andrew Harrison ; Betreuer: Hans Binder." Leipzig : Universitätsbibliothek Leipzig, 2013. http://d-nb.info/1238367623/34.
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30
Roy, Christian K. "Putting the Pieces Together: Exons and piRNAs: A Dissertation." eScholarship@UMMS, 2014. https://escholarship.umassmed.edu/gsbs_diss/726.
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Analysis of gene expression has undergone a technological revolution. What was impossible 6 years ago is now routine. High-throughput DNA sequencing machines capable of generating hundreds of millions of reads allow, indeed force, a major revision toward the study of the genome’s functional output—the transcriptome. This thesis examines the history of DNA sequencing, measurement of gene expression by sequencing, isoform complexity driven by alternative splicing and mammalian piRNA precursor biogenesis. Examination of these topics is framed around development of a novel RNA-templated DNA-DNA ligation assay (SeqZip) that allows for efficient analysis of abundant, complex, and functional long RNAs. The discussion focuses on the future of transcriptome analysis, development and applications of SeqZip, and challenges presented to biomedical researchers by extremely large and rich datasets.
31
Roy, Christian K. "Putting the Pieces Together: Exons and piRNAs: A Dissertation." eScholarship@UMMS, 2005. http://escholarship.umassmed.edu/gsbs_diss/726.
Full textAbstract:
Analysis of gene expression has undergone a technological revolution. What was impossible 6 years ago is now routine. High-throughput DNA sequencing machines capable of generating hundreds of millions of reads allow, indeed force, a major revision toward the study of the genome’s functional output—the transcriptome. This thesis examines the history of DNA sequencing, measurement of gene expression by sequencing, isoform complexity driven by alternative splicing and mammalian piRNA precursor biogenesis. Examination of these topics is framed around development of a novel RNA-templated DNA-DNA ligation assay (SeqZip) that allows for efficient analysis of abundant, complex, and functional long RNAs. The discussion focuses on the future of transcriptome analysis, development and applications of SeqZip, and challenges presented to biomedical researchers by extremely large and rich datasets.
32
Jiang, Li. "Systematic Experimental Determination of Functional Constraints on Proteins and Adaptive Potential of Mutations: A Dissertation." eScholarship@UMMS, 2016. https://escholarship.umassmed.edu/gsbs_diss/854.
Full textAbstract:
Sequence-function relationship is a fundamental question for many branches of modern biomedical research. It connects the primary sequence of proteins to the function of proteins and fitness of organisms, holding answers for critical questions such as functional consequences of mutations identified in whole genome sequencing and adaptive potential of fast evolving pathogenic viruses and microbes. Many different approaches have been developed to delineate the genotype-phenotype map for different proteins, but are generally limited by their throughput or precision. To systematically quantify the fitness of large numbers of mutations, I modified a novel high throughput mutational scanning approach (EMPIRIC) to investigate the fitness landscape of mutations in important regions of essential proteins from the yeast or RNA viruses. Using EMPIRIC, I analyzed the interplay of the expression level and sequence of Hsp90 on the yeast growth and revealed latent effect of mutations at reduced expression levels of Hsp90. I also examined the functional constraint on the receptor binding site of the Env of Human Immunodeficiency Virus (HIV) and uncovered enhanced receptor binding capacity as a common pathway for adaptation of HIV to laboratory conditions. Moreover, I explored the adaptive potential of neuraminidase (NA) of influenza A virus to a NA inhibitor, oseltamivir, and identified novel oseltamivir resistance mutations with distinct molecular mechanisms. In summary, I applied a high throughput functional genomics approach to map the sequence-function relationship in various systems and examined the evolutionary constraints and adaptive potential of essential proteins ranging from molecular chaperones to drug-targetable viral proteins.
33
Jiang, Li. "Systematic Experimental Determination of Functional Constraints on Proteins and Adaptive Potential of Mutations: A Dissertation." eScholarship@UMMS, 2005. http://escholarship.umassmed.edu/gsbs_diss/854.
Full textAbstract:
Sequence-function relationship is a fundamental question for many branches of modern biomedical research. It connects the primary sequence of proteins to the function of proteins and fitness of organisms, holding answers for critical questions such as functional consequences of mutations identified in whole genome sequencing and adaptive potential of fast evolving pathogenic viruses and microbes. Many different approaches have been developed to delineate the genotype-phenotype map for different proteins, but are generally limited by their throughput or precision. To systematically quantify the fitness of large numbers of mutations, I modified a novel high throughput mutational scanning approach (EMPIRIC) to investigate the fitness landscape of mutations in important regions of essential proteins from the yeast or RNA viruses. Using EMPIRIC, I analyzed the interplay of the expression level and sequence of Hsp90 on the yeast growth and revealed latent effect of mutations at reduced expression levels of Hsp90. I also examined the functional constraint on the receptor binding site of the Env of Human Immunodeficiency Virus (HIV) and uncovered enhanced receptor binding capacity as a common pathway for adaptation of HIV to laboratory conditions. Moreover, I explored the adaptive potential of neuraminidase (NA) of influenza A virus to a NA inhibitor, oseltamivir, and identified novel oseltamivir resistance mutations with distinct molecular mechanisms. In summary, I applied a high throughput functional genomics approach to map the sequence-function relationship in various systems and examined the evolutionary constraints and adaptive potential of essential proteins ranging from molecular chaperones to drug-targetable viral proteins.
34
Buchholz, Frank, Anja Nitzsche, Maciej Paszkowski-Rogacz, Filomena Matarese, Eva M. Janssen-Megens, Nina C. Hubner, Herbert Schulz, et al. "RAD21 Cooperates with Pluripotency Transcription Factors in the Maintenance of Embryonic Stem Cell Identity." Public Library of Science, 2011. https://tud.qucosa.de/id/qucosa%3A29134.
Full textAbstract:
For self-renewal, embryonic stem cells (ESCs) require the expression of specific transcription factors accompanied by a particular chromosome organization to maintain a balance between pluripotency and the capacity for rapid differentiation. However, how transcriptional regulation is linked to chromosome organization in ESCs is not well understood. Here we show that the cohesin component RAD21 exhibits a functional role in maintaining ESC identity through association with the pluripotency transcriptional network. ChIP-seq analyses of RAD21 reveal an ESC specific cohesin binding pattern that is characterized by CTCF independent co-localization of cohesin with pluripotency related transcription factors Oct4, Nanog, Sox2, Esrrb and Klf4. Upon ESC differentiation, most of these binding sites disappear and instead new CTCF independent RAD21 binding sites emerge, which are enriched for binding sites of transcription factors implicated in early differentiation. Furthermore, knock-down of RAD21 causes expression changes that are similar to expression changes after Nanog depletion, demonstrating the functional relevance of the RAD21 - pluripotency transcriptional network association. Finally, we show that Nanog physically interacts with the cohesin or cohesin interacting proteins STAG1 and WAPL further substantiating this association. Based on these findings we propose that a dynamic placement of cohesin by pluripotency transcription factors contributes to a chromosome organization supporting the ESC expression program.
35
Bellora, Pereyra Nicolás. "In silico analysis of regulatory motifs in gene promoters." Doctoral thesis, Universitat Pompeu Fabra, 2010. http://hdl.handle.net/10803/7202.
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Regulation of gene transcription is a complex process involving many different proteins, some of which bind in a sequence-specific manner to DNA motifs in the gene promoter. The need to maintain specific interactions between transcription factors and proteins involved in the RNA polymerase II complex is expected to impose constrains on the relative position and spacing of the interacting DNA motifs. The present work includes the development of a novel approach to identify motifs that show a preferential location in DNA sequences and the implementation of a public web application called PEAKS. We investigated if the arrangement and nature of the most common motifs depended on the breath of expression of the gene. We found differences that serve to illustrate that many key specific regulatory signals may be present in the proximal promoter region in mammalian genes. We also apply other methods for the identification of specific transcription factors (TFs) involved in the co-regulation of a set of genes. Data from experimentally-verified transcription factors binding sites (TFBSs) support the biological relevance of our findings.La regulació de la transcripció dels gens és un procés complex que implica moltes proteïnes diferents, algunes de les quals s'unexien a motius específics d'ADN localitzats a la regió promotora dels gens. S'espera que la necessitat de mantenir les interaccions específiques entre els factors de transcripció i les proteïnes implicades en el complex de la ARN polimerasa II imposi limitacions en la posició relativa i l'espaiat dels motius d'interacció amb l'ADN. La feina presentada en aquesta tesi inclou el desenvolupament d'un nou metode per l'identificació de motius que mostren una localització preferencial en seqüències d'ADN i l'implementació d'una aplicació web pública anomenada PEAKS. Hem investigat si la col·locació i la naturalesa de la majoria dels motius comuns depen del rang d'expresió del gen. Hem trobat diferències que serveixen per il·lustrar el fet que moltes senyals clau de regulació gènica poden estar presents en la regió proximal del promotor dels gens de mamífers. També hem aplicat altres mètodes per a l'identificació de factors de transcripció (TFs) específics involucrats en la co-regulació d'un grup de gens. Dades de llocs d'unio dels TFs (TFBSs) verificats experimentalment recolzen la rellevància biològica dels nostres resultats.
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Wang, Pan. "Transcriptomic and metatranscriptomic approaches to characterizing genes coding for fiber digestion within the rumen ecosystem." Thesis, Lethbridge, Alta. : University of Lethbridge, Dept. of Biological Sciences, 2013. http://hdl.handle.net/10133/3459.
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The rumen microbiome constitutes a unique genetic resource of plant fiber degrading microbial enzymes that could be used for agricultural and industrial purposes. Anaeromyces mucronatus is a poorly characterized anaerobic lignocellulolytic fungus in the rumen. This thesis aimed at better understanding A. mucronatus YE505 and the particle associated rumen microbiota based on transcriptomic and metatranscriptomic approaches. High quality RNA was isolated from the fiber-associated rumen sample based on an improved RNA extraction method. A transcriptomic study was performed to investigate the expression of the fiber degrading system of A. mucronatus YE505, and the functional diversity of the fiber-associated eukaryotes from the rumen of muskoxen (Ovibos moschatus) was explored by a metatranscriptomic study. Much carbohydrate degradation related protein modules were detected. This study established effective approaches to characterizing the functional contents of rumen eukaryotic microbiome as well as rumen fungi, and identified several candidate genes that merit further investigation.xiv leaves : ill. (some col.) ; 29 cm
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URGESE, GIANVITO. "Computational Methods for Bioinformatics Analysis and Neuromorphic Computing." Doctoral thesis, Politecnico di Torino, 2016. http://hdl.handle.net/11583/2646486.
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The latest biological discoveries and the exponential growth of more and more sophisticated biotechnologies led in the current century to a revolution that totally reshaped the concept of genetic study. This revolution, which began in the last decades, is still continuing thanks to the introduction of new technologies capable of producing a huge amount of biological data in a relatively short time and at a very low price with respect to some decades ago. These new technologies are known as Next Generation Sequencing (NGS). These platforms perform massively parallel sequencing of both RNA and DNA molecules, thus allowing to retrieve the nucleic acid sequence of millions of fragments of DNA or RNA in a single machine run. The introduction of such technologies rapidly changed the landscape of genetic research, providing the ability to answer questions with heretofore unimaginable accuracy and speed. Moreover, the advent of NGS with the consequent need for ad-hoc strategies for data storage, sharing, and analysis is transforming genetics in a big data research field. Indeed, the large amount of data coming from sequencing technologies and the complexity of biological processes call for novel computational tools (Bioinformatics tools) and informatics resources to exploit this kind of information and gain novel insights into human beings, living organisms, and pathologies mechanisms. At the same time, a new scientific discipline called Neuromorphic Computing has been established to develop SW/HW systems having brain-specific features, such as high degree of parallelism and low power consumption. These platforms are usually employed to support the simulation of the nervous system, thus allowing the study of the mechanisms at the basis of the brain functioning.
In this scenario, my research program focused on the development of optimized HW/SW algorithms and tools to process the biological information from Bioinformatics and Neuromorphic studies.
The main objective of the methodologies proposed in this thesis consisted in achieving a high level of sensitivity and specificity in data analysis while minimizing the computational time. To reach these milestones, then, some bottlenecks identified in the state-of-the-art tools have been solved through a careful design of three new optimised algorithms.
The work that led to this thesis is part of three collaborative projects. Two concerning the design of Bioinformatics sequence alignment algorithms and one aimed at optimizing the resources usage of a Neuromorphic platform. In the next paragraphs, the projects are briefly introduced.
Dynamic Gap Selector Project
This project concerned the design and implementation of a new gap model implemented in the dynamic programming sequence alignment algorithms. Smith-Waterman (S-W) and Needleman-Wunsch (N-W) are widespread methods to perform Local and Global alignments of biological sequences such as proteins, DNA and RNA molecules that are represented such as sequences of letters. Both the algorithms make use of scoring procedures to evaluate matches and errors that can be encountered during the sequence alignment process. These scoring strategies are designed to consider insertions and deletions through the identification of gaps in the aligned sequences.
The Affine gap model is considered the most accurate model for the alignment of biomolecules. However, its application to S-W and N-W algorithms is quite expensive both in terms of computational time as well as in terms of memory requirements when compared to other less demanding models as the Linear gap one.
In order to overcome these drawbacks, an optimised version of the Affine gap model called Dynamic Gap Selector (DGS) has been developed. The alignment scores computed using DGS are very similar to those computed using the gold standard Affine gap model. However, the implementation of this novel gap model during the S-W and N-W alignment procedures leads to the reduction of the memory requirements by a factor of 3. Moreover, the DGS model application accounts for a reduction by a factor of 2 in the number of operations required with respect to the standard Affine gap model.
isomiR-SEA Project
One of the most attractive research fields that is currently investigated by several interdisciplinary research teams is the study of small and medium RNA sequences with regulatory functions on the production of proteins. These RNA molecules are respectively called microRNAs (miRNAs) and long non-coding RNAs (lncRNAs). In the second project, an alignment algorithm specific for miRNAs detection and characterization have been designed and implemented.
miRNAs are a class of short RNAs (18-25 bases) that play essential roles in a variety of cellular processes such as development, metabolism, regulation of immunological response and tumor genesis.
Several tools have been developed in the last years to align and analyse the huge amount of data coming from the sequencing of short RNA molecules. However, these tools still lack accuracy and completeness because they use general alignment procedures that do not take into account the structural characteristics of miRNA molecules. Moreover, they are not able to detect specific miRNA variants, called isomiRs, that have recently been found to be relevant for miRNA targets regulation.
To overcome these limitations, a miRNA-based alignment algorithm has been designed and developed. The isomiR-SEA algorithm is specifically tailored to detect different miRNAs variants (isomiRs) in the RNA-Seq data and to provide users with a detailed picture of the isomiRs spectrum characterizing the sample under investigation.
The accuracy proper of the implemented alignment policy is reflected in the precise miRNAs and isomiRs quantification, and in the detailed profiling of miRNAtarget mRNA interaction sites. This information, hidden in raw miRNA sequencing data, can be very useful to properly characterize miRNAs and to adopt them as reliable biomarkers able to describe multifactorial pathologies such as cancer.
SNN Partitioning and Placement Project
In the Neuromorphic Computing field, SpiNNaker is one of the state-of-the-art massively parallel neuromorphic platform. It is designed to simulate Spiking Neural Networks (SNN) but it is characterized by several bottlenecks in the neuron partitioning and placement phases executed during the simulation configuration.
In this activity, related to the European Flagship project Human Brain Project, a top-down methodology has been developed to improve the scalability and reliability of SNN simulations on massively many-core and densely interconnected platforms. In this context, SNNs mimic the brain activity by emulating spikes sent among neurons populations.
Many-core platforms are emerging computing resources to achieve real-time SNNs simulations. Neurons are mapped to parallel cores and spikes are sent in the form of packets over the on-chip and off-chip network. However, due to the heterogeneity and complexity of neuron populations activity, achieving an efficient exploitation of platforms resources is a challenge, often impacting simulation reliability and limiting the biological network size.
To address this challenge, the proposed methodology makes use of customized SNN configurations capable of extracting detailed profiling information about network usage of on-chip and off-chip resources. Thus, allowing to recognize the bottlenecks in the spike propagation system.
These bottlenecks have been then considered during the SNN Partitioning and Placement of a graph describing the SNN interconnection on chips and cores available on the SpiNNaker board.
The advantages of the proposed SNN Partitioning and Placement applied to the SpiNNaker has been evaluated in terms of traffic reduction and consequent simulation reliability. The results demonstrate that it is possible to consistently reduce packet traffic and improve simulation reliability by means of an effective neuron placement.
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Montenegro, Marilia Moreira. "Estudo do transcriptoma na síndrome de Bloom." Universidade de São Paulo, 2017. http://www.teses.usp.br/teses/disponiveis/5/5144/tde-03052017-151125/.
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A síndrome de Bloom (SB) é uma síndrome de instabilidade cromossômica rara, transmitida por herança autossômica recessiva. Caracteriza-se por deficiência de crescimento pré e pós-natal, microcefalia, hipoplasia malar, eritema telangiectásico em face e comprometimento do sistema imunológico, entre outras manifestações clínicas. Os pacientes com SB apresentam predisposição aumentada para o desenvolvimento de neoplasias em idade precoce, sendo esta, a principal causa de óbito. Ao estudo citogenético observa-se aumento de quebras cromossômicas espontâneas e trocas entre cromátides irmãs (TCI), que são utilizadas como marcador diagnóstico para a SB. Além disso, a literatura mostra que a maioria dos pacientes também apresenta mutações no gene BLM, que estão relacionadas a defeitos no mecanismo de reparo do DNA. No entanto, os mecanismos fisiopatológicos não são completamente compreendidos. Nesse sentido estudamos o transcriptoma de duas pacientes portadoras da síndrome de Bloom e de três controles utilizando a metodologia RNA-seq (Illumina, Inc., San Diego, CA). A análise de expressão diferencial revelou 216 genes diferencialmente expressos relacionados a vias relacionadas à resposta imune como replicação negativa da regulação da replicação do genoma viral, regulação positiva da proliferação de células B, via de sinalização mediada por interferon gama, ativação de células B, resposta a vírus, resposta imune adaptativa e processo efetor imune, e nenhuma diferença da expressão em genes de reparo de DNA. Concomitantemente, observamos a hiperexpressão do gene BLM para ambas as pacientes, contribuindo para a desestabilização de genes envolvidos em vias imunológicas, fenômeno também observado em alguns tumores. Dessa forma, sugerimos que a combinação de defeitos de proliferação linfocitária e defeitos de sinalização celular somados a outros, como perda celular e expressão alterada do gene BLM, podem contribuir diretamente para as principais características observadas na síndrome de Bloom, como a deficiência de crescimento e o elevado risco de câncer. Futuramente, o estudo do transcriptoma, aplicado a outros portadores da SB e outras síndromes de instabilidade, possibilitará uma análise mais acurada das interações gênicas relevantes para a desestabilização do genomaBloom Syndrome (BS) is a rare chromosome instability syndrome, with recessive autosomal inheritance. The main clinical manifestations are pre and postnatal growth deficiency, microcephaly, malar hypoplasia, telangiectasic facial erythema and compromised immune system, among others. Patients with BS present increased risk to the development of neoplasias at an early age, which is the main cause of death. Cytogenetic test is used as a diagnostic marker for BS since the patient\'s cells present increase in spontaneous chromosomal breaks and sister chromatid exchange (SCE). In addition, the literature reveals that most patients also present mutations in the BLM gene, which are related to defects in the DNA repair mechanism; however, it is still not completely understood. In this sense, we studied the transcriptome of two patients with Bloom\'s syndrome and three controls using the RNA-seq methodology (Illumina, Inc., San Diego, CA). Differential expression analysis revealed 216 differentially expressed genes related to immunological pathways such as: negative replication of the regulation of the viral genome replication, positive regulation of B cells proliferation, gama-interferon mediated signalization pathway, B cells activation, virus response, adaptive immune response and immune effector process, and absence of difference of DNA repair genes expression. At the same time, we observed the hyperexpression of the BLM gene for both patients contributing for the destabilization of genes involved in immunological pathways, a phenomenon also observed in some tumors. Thus, we suggest that the combination of lymphoid proliferation defects and cell signaling defects added to others such as cell loss and altered expression of the BLM gene may contribute directly to the main characteristics observed in Bloom\'s syndrome, such as growth failure and high risk of cancer. In the future, the study of the transcriptome applied to other BS carriers and other instability syndromes, will allow a more accurate analysis of the relevant gene interactions to the destabilization of the genome
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Lajoie, Bryan R. "Computational Approaches for the Analysis of Chromosome Conformation Capture Data and Their Application to Study Long-Range Gene Regulation: A Dissertation." eScholarship@UMMS, 2016. http://escholarship.umassmed.edu/gsbs_diss/833.
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Over the last decade, development and application of a set of molecular genomic approaches based on the chromosome conformation capture method (3C), combined with increasingly powerful imaging approaches have enabled high resolution and genome-wide analysis of the spatial organization of chromosomes. The aim of this thesis is two-fold; 1), to provide guidelines for analyzing and interpreting data obtained from genome-wide 3C methods such as Hi-C and 3C-seq and 2), to leverage the 3C technology to solve genome function, structure, assembly, development and dosage problems across a broad range of organisms and disease models.
First, through the introduction of cWorld, a toolkit for manipulating genome structure data, I accelerate the pace at which *C experiments can be performed, analyzed and biological insights inferred. Next I discuss a set of practical guidelines one should consider while planning an experiment to study the structure of the genome, a simple workflow for data processing unique to *C data and a set of considerations one should be aware of while attempting to gain insights from the data.
Next, I apply these guidelines and leverage the cWorld toolkit in the context of two dosage compensation systems. The first is a worm condensin mutant which shows a reduction in dosage compensation in the hermaphrodite X chromosomes. The second is an allele-specific study consisting of genome wide Hi-C, RNA-Seq and ATAC-Seq which can measure the state of the active (Xa) and inactive (Xi) X chromosome. Finally I turn to studying specific gene – enhancer looping interactions across a panel of ENCODE cell-lines.
These studies, when taken together, further our understanding of how genome structure relates to genome function.
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West, Claire Louise. "Computational discovery and analysis of rDNA sequence heterogeneity in yeast." Thesis, University of East Anglia, 2013. https://ueaeprints.uea.ac.uk/48753/.
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Ribosomal RNA genes, known as ribosomal DNA or rDNA, are commonly found in tandem arrays of hundreds of repeating units. The sequences of each unit in an array were thought to be near-identical but it is now known that frequent mutations may occur, causing heterogeneity amongst units. Opposing these divergent mutational processes, unit sequences are homogenised through concerted evolutionary processes such as unequal sister chromatid exchange (USCE) and gene conversion (GC). In this study Perl software has been used to uncover rDNA sequence variation in the yeast Saccharomyces paradoxus, using data derived from the Saccharomyces Genome Resequencing Project. This analysis, in conjunction with a reanalysis of the Saccharomyces cerevisiae data from the same project, has provided detailed information regarding rDNA sequence heterogeneity in two contrasting, yet closelyrelated yeast species. Additionally, the rDNA flanking sequences of four yeast strains have been characterised via an analysis of new next generation sequencing reads, adding to our knowledge of concerted evolutionary processes in these genomic regions. Partial Single Nucleotide Polymorphisms (pSNPs) within these datasets are shown to reflect genome mosaicism within a population, and to identify strains with signs of genome hybridisation undetectable by other means. This information provides further insights into the dynamics of the rDNA region in the two yeast species. In particular, examination of the percentage occupancies of pSNPs reveals U-shaped distributions which differ between the two species. Further investigations of rDNA evolutionary dynamics through the development of two Java simulation tools (SIMPLEX and CONCERTINA), which model USCE and GC events, follow the fate of both single and multiple pSNPs in one or more rDNA arrays. Initial simulations show the distribution of pSNPs varies depending upon the balance between mutations and concerted evolutionary events, and provide a framework to investigate the mechanisms involved in altered rDNA dynamics in various cellular processes.
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Pabbaraju, Kanti. "Analysis of intervening sequences in the 23S ribosomal RNA genes of Salmonella species." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape2/PQDD_0018/MQ49650.pdf.
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Bao, Yu. "Identification and Analysis of Critical Sites in RNA/Protein Sequences and Biological Networks." Kyoto University, 2018. http://hdl.handle.net/2433/235113.
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Marsiglia, Júlia Daher Carneiro. "Estudo genético de pacientes portadores de cardiomiopatia hipertrófica." Universidade de São Paulo, 2013. http://www.teses.usp.br/teses/disponiveis/5/5166/tde-01112013-112638/.
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Introdução: A cardiomiopatia hipertrófica (CH) é uma doença genética cardíaca primária, caracterizada por hipertrofia do ventrículo esquerdo, sem dilatação, geralmente assimétrica e predominantemente septal, com prevalência estimada em 1:500. Atualmente já foram descobertos 20 genes associados à doença, mas os genes mais frequentemente relacionados são o da Cadeia Pesada da ?-miosina (MYH7), Proteína C de Ligação da Miosina (MYBPC3) e Troponina T (TNNT2). O diagnóstico molecular dos pacientes é importante e custo-efetivo do ponto de vista de saúde pública, além de recomendado pela Sociedade Europeia de Cardiologia. Entretanto, o custo inicial do exame é muito alto, de forma que estudos tentam reduzir esse custo. Uma das propostas descritas utilizou o RNA extraído de leucócitos para sequenciamento com sucesso para o gene MYBPC3. Este trabalho tem como objetivo testar a metodologia de sequenciamento de RNA em larga escala e testar a aplicabilidade da mesma para os genes MYH7 e TNNT2, estimar as principais mutações envolvidas nos pacientes do estudo e estabelecer correlações entre os diferentes genótipos avaliados e os fenótipos dos grupos familiares portadores da doença. Métodos: Os sujeitos incluídos no estudo são portadores de cardiomiopatia hipertrófica nos quais foi feita uma coleta de sangue para extração de DNA e RNA. Foi utilizada nested PCR para amplificação do cDNA e PCR convencional para amplificação de DNA e posterior sequenciamento em sequenciador automático. As análises estatísticas dos dados clínicos foram realizadas utilizando-se ANOVA para comparação de médias e teste exato de Fisher para comparação de frequências. Resultados: O sequenciamento de RNA se mostrou problemático, com baixa taxa de amplificação, falsos positivos e possíveis falsos negativos, de forma que optou-se por utilizar o sequenciamento de DNA para identificação das alterações. Dos 268 pacientes estudados foi identificada uma mutação em 131 deles (48,8%). Das mutações encontradas, 78 (59,5%) estavam no gene MYH7, 50 (38,2%) no gene MYBPC3 e 3 (2,3%) no gene TNNT2. Foram identificadas 69 mutações diferentes, 24 delas ainda não descritas. Pacientes com mutação identificada possuíam em média idade de diagnóstico e idade atual menores, maior frequência cardíaca média e maior frequência de pacientes com taquicardia ventricular não sustentada quando comparados ao grupo sem mutação identificada. Pacientes com mutação no gene MYH7 possuíam maior tamanho de átrio esquerdo, maior frequência de fibrilação atrial e maior frequência de histórico familiar da doença do que pacientes com mutação em MYBPC3. Conclusões: A técnica sequenciamento de RNA extraído de leucócitos não é adequada para uma rotina de rastreamento em larga escala para CH devido à alta frequência de falsos positivos, possibilidade de falsos negativos e baixa taxa de amplificação, mas o sequenciamento de DNA, embora trabalhoso, se mostrou muito sensível para a análise. A identificação de uma mutação específica ainda não pode ser usada para prognóstico de gravidade da CH, mas as comparações de genótipo e fenótipo mostraram algumas relações interessantes que devem ser melhor avaliadas nos pacientes. Este é o primeiro trabalho a caracterizar a epidemiologia molecular da CH em pacientes brasileiros para os genes MYH7, MYBPC3 e TNNT2Introduction: Hypertrophic cardiomyopathy (HC) is a primary genetic cardiac disease characterized by left ventricular hypertrophy without dilation, usually asymmetric and predominantly septal, with an estimated prevalence of 1:500. There are 20 genes associated to the HC, but the ones more often related to the disease are ?-myosin heavy chain (MYH7), myosin binding protein C (MYBPC3) and troponin T (TNNT2). The molecular diagnosis of patients is important and cost-effective from the standpoint of public health, and recommended by the European Society of Cardiology. However, the initial cost of the exam is very high, so several studies are attempting to reduce it. One of the proposals described used the RNA extracted from leukocytes for sequencing successfully to the MYBPC3 gene. The present study aims to test the methodology for large-scale sequencing and test it\'s applicability to the MYH7 and TNNT2 genes, to estimate the main mutations involved in the studied patients and establish correlations between their genotypes and phenotypes. Methods: The subjects included in the study were patients previously diagnosed with hypertrophic cardiomyopathy in whom a blood sample was collected to DNA and RNA extraction. It was used nested PCR for cDNA amplification and conventional PCR for DNA amplification for posterior sequencing on an automatic sequencer. Statistical analyzes of clinical data were performed using ANOVA to compare means and Fisher\'s exact test for frequencies comparison. Results: The RNA sequencing was problematic with low rate of amplification, false positives and possible false negatives, so was used DNA sequencing to identify the mutations. Of the 268 patients studied a mutation was identified in 131 of them (48.8%). Among the mutations found, 78 (59.5%) were in the MYH7 gene, 50 (38.2%) in the MYBPC3 gene and three (2.3%) in the TNNT2 gene. We have identified 69 different mutations, 24 of them not yet described. Patients with an identified mutation had an average smaller age of diagnosis and current age, higher average cardiac frequency and higher frequency of patients with nonsustained ventricular tachycardia compared to those without an identified mutation. Patients with mutations in the MYH7 gene had larger left atrium size, higher frequency of atrial fibrillation and higher frequency of family history of the disease than patients with a mutation in the MYBPC3 gene. Conclusions: The technique of sequencing RNA extracted from leucocytes is not suitable for large scale routine screening for CH due to the high frequency of false positives, possibility of false negatives and low rate of amplification, but the DNA sequencing, though laborious, was very sensitive to the analysis. Identification of a specific mutation cannot yet be used for prognosis of the disease\'s severity, but comparisons of genotype and phenotype have shown some interesting relationships that should be further evaluated. The presente study is the first one to characterize the molecular epidemiology of hypertrophic cardiomyopathy in Brazilian patients for those three more important genes mentioned above
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Boonyakiat, Yingmanee. "Analysis of human parechovirus 1 and coxsackievirus A9 sequences involved in attachment to host cells." Thesis, University of Essex, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.313095.
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Tran, Anh-Nhi. "A Genetic Survey of the Pathogenic Parasite Trypanosoma cruzi." Doctoral thesis, Uppsala : Acta Universitatis Upsaliensis : Univ.-bibl. [distributör], 2003. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-3425.
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Wallerö, Emma. "Automatic morphological analysis of L-verbs in Palula." Thesis, Stockholms universitet, Institutionen för lingvistik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-182528.
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This study is exploring the possibilities of automatic morphological analysis of L-verbs in the Palula language by the help from Finite-state technology and two-level morphology along with supervised machine learning. The type of machine learning used are neural Sequence to Sequence models. A morphological transducer is made with the Helsinki Finite-State Transducer Technology, HFST, toolkit covering the L-verbs of the Palula Language. Several Sequence to Sequence models are trained on sets of L-verbs along with morphological tagging annotation. One model is trained with a small amount of manually annotated data and four models are trained with different amounts of training examples generated by the Finite-State Transducer. The efficiency and accuracy of these methods are investigated. The Sequence to Sequence model trained on solely manually annotated data did not perform as well as the other models. A Sequence to Sequence model trained with training examples generated by the transducer performed the best recall, accuracy and F1-score, while the Finite-State Transducer performed the best precision score.Denna studie undersöker möjligheterna för en automatisk morfologisk analys av L-verb i språket Palula med hjälp av finit tillståndsteknik och två-nivå-morfologi samt övervakad maskininlärning. Den typ av maskininlärning som används i studien är neurala Sekvens till Sekvens-modeller. En morfologisk transduktor är skapad med verktyget Helsinki Finite-State Transducer Technology, HFST, som täcker L-verben i Palula. Flera Sekvens till Sekvens-modeller tränas på set av L-verb med morfologisk taggningsannotation. En modell tränas på ett litet set av manuellt annoterade data och fyra modeller tränas på olika mängder träningsdata som genererats av den finita tillstånds-transduktorn. Effektiviteten och noggrannheten för dessa modeller undersöks. Sekvens till Sekvens-modellen som tränats med bara manuellt annoterade data presterade inte lika bra som de andra modellerna i studien. En Sekvens till Sekvens-modell tränad med träningsdata bestående av genereringar producerade av transduktorn gav bästa svarsfrekvens, noggrannhet och F1-poäng, medan den finita tillstånds-transduktorn gav bästa precision.
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Cardoso-Silva, Cláudio Benício 1982. "Análise do transcriptoma e de sequências genômicas de variedades comerciais de cana-de-açúcar = Transcriptome and genomic sequences analysis of commercial sugarcane varieties." [s.n.], 2015. http://repositorio.unicamp.br/jspui/handle/REPOSIP/316503.
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Orientadores: Anete Pereira de Souza, Renato Vicentini dos SantosTese (doutorado) - Universidade Estadual de Campinas, Instituto de Biologia
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Resumo: A cana-de-açúcar é uma das espécies de maior importância econômica no mundo devido ao seu potencial bioenergético. No entanto, o seu alto nível de complexidade genética é um desafio para a aplicação de ferramentas moleculares no melhoramento. Os recentes avanços das tecnologias de sequenciamento e genotipagem indicam o potencial de aumentar o nosso entendimento sobre a genética e a biologia molecular desta espécie. As sequências genômicas e de transcriptomas são valiosa fonte de informação para o desenvolvimento de ferramentas moleculares que permitam a identificação de regiões no genoma que estejam relacionadas com características de interesse para o melhoramento. O uso das novas tecnologias de sequenciamento de alto desempenho tem grande potencial de impacto nestas pesquisas. A presente tese objetivou analisar o transcriptoma de seis variedades comerciais e dados genômico da variedade R570, com a finalidade de identificar genes potencialmente úteis para o desenvolvimento de marcadores moleculares. A partir do método RNA-Seq, foram geradas mais de 400 milhões de sequências, as quais permitiram obter um total de 72.269 transcritos representados por uma única isoforma montados com auxílio do programa Trinity. Estes transcritos foram alinhados com sequências de Viridiplantae, gramíneas, e exclusivamente contra proteínas de sorgo, arroz, milho e transcriptoma de cana-de-açúcar, depositados em banco de dados público. Esta análise permitiu identificar o conjunto de genes de cana-de-açúcar compartilhados com outras gramíneas, bem como levou à identificação de novos transcritos que não haviam sido catalogados para cana-de-açúcar, além de longos RNAs não codificantes. Os transcritos foram anotados no Cluster of Orthologous Groups (COG) e no Gene Ontology (GO), com posterior análise de enriquecimento dos termos GO, a partir da qual foram anotados os transcritos, possivelmente relacionados a genes que conferem características de importância agronômica. No transcriptoma foram identificados mais de 700 mil SNPs e aproximadamente cinco mil regiões microssatélites. Analisando um total de 32 Mbp de sequências genômicas da variedade R570 foram identificados 4.342 microssatélites, com frequência média de sete SSR/Kb. As sequências geradas e exploradas neste trabalho são valiosa fonte de informações para entender a arquitetura genética da cana-de-açúcar, principalmente para o desenvolvimento de marcadores moleculares, os quais podem ser utilizados no mapeamento genético
Abstract: The sugarcane is one of the most economically important species in the world, due to their energy potential. However, high level of genetic complexity has been a major challenge for the use of molecular tools applied to improvement of this crop. Recent advances in sequencing and genotyping technologies indicate the potential to increase our understanding of the genetics and molecular biology of this specie. The genomic and transcriptomic are valuable sources of information for the molecular tools development that allow identification of regions in the genome that are related to characteristics of interest for the improvement. The high-throughput sequencing technologies have great impact of this research. This thesis aimed to analyze the transcriptome of six commercial varieties and genomic sequencing from R570 variety, in order to identify genes potentially useful for the molecular markers development. From RNA-Seq method were generated over 400 million sequences, which allowed obtain a total of 72,268 transcripts representing a single isoform assembled by Trinity. These transcripts were aligned against Viridiplantae, grasses, and exclusively against sorghum, rice and maize proteins, and sugarcane transcriptome available in the public database. This analysis allowed identifying a set of shared genes with other grasses, new transcripts that had not yet been cataloged for sugarcane and long non-coding RNAs. The transcripts were also annotated using the COG (Cluster of Orthologous Groups) and GO (Gene Ontology) database, followed by enrichment analysis for GO terms, from which it was possible to identify genes that play roles, possibly related to traits of agronomic importance. In the transcriptome were identified over 700 thousands SNPs and five thousands microsatellites regions. In the genomic sequences from R570 variety, in a total of 32 Mbp were identified 4,342 microsatellites, with an average frequency of seven SSR / Kb. The sequences generated and explored in this work is a valuable source to understand the genetic architecture of the sugarcane, mainly for molecular markers development, which can be used in genetic mapping
Doutorado
Genetica Vegetal e Melhoramento
Doutor em Genetica e Biologia Molecular
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Pinal, Fernández Iago. "Transcriptome profiling and longitudinal cohort studies of myositis subsets." Doctoral thesis, Universitat Oberta de Catalunya, 2020. http://hdl.handle.net/10803/673293.
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Inflammatory myopathies are a heterogeneous family of rare autoimmune diseases affecting multiple organs and systems, including the skin, the lungs, the muscles and/or the joints. Accurately defining their pathogenesis and classifying them correctly are key for understanding and managing these diseases. In this doctoral thesis we explored specific autoantibody-defined myositis subsets and quantitatively compared the ability of autoantibodies to the 2017 EULAR/ACR classification standard to predict the phenotype of patients with myositis. We also performed RNA sequencing on 119 muscle biopsies of patients with different types of myositis and 20 controls. We studied the differential expression, performed pathway analysis and developed exploratory machine learning pipelines to define the specific expression profiles and pathogenic pathways in each disease subgroup. With these studies we determined that the autoantibodies outperform current clinical criteria to predict the phenotype of myositis patients and discovered unique expression profiles in the muscle tissue of patients with different types of myositis.Las miopatías inflamatorias son una familia heterogénea de enfermedades autoinmunes raras que afectan a múltiples órganos y sistemas, incluidos los músculos, la piel, los pulmones y/o las articulaciones. Definir con precisión su patogenia y clasificarlas correctamente es clave para comprender y manejar estas enfermedades. En esta tesis doctoral exploramos subconjuntos específicos de miositis definidas por autoanticuerpos y comparamos cuantitativamente la capacidad de los autoanticuerpos con la clasificación EULAR/ACR de 2017 para predecir el fenotipo de pacientes con miositis. Además, realizamos la secuenciación de ARN en 119 biopsias musculares de pacientes con diferentes tipos de miositis y 20 controles. Estudiamos la expresión diferencial, realizamos análisis de vías y desarrollamos procesos de aprendizaje automático exploratorios para definir los perfiles de expresión específicos y las vías patogénicas en cada subgrupo de enfermedades. Con estos estudios determinamos que los autoanticuerpos superan los criterios clínicos actuales para predecir el fenotipo de los pacientes con miositis y descubrimos perfiles de expresión únicos en el tejido muscular de pacientes con diferentes tipos de miositis.
Les miopaties inflamatòries són una família heterogènia de malalties autoimmunes rares que afecten múltiples òrgans i sistemes, inclosos els músculs, la pell, els pulmons i/o les articulacions. Definir-ne amb precisió la patogènia i classificar-les correctament és clau per comprendre i manejar aquestes malalties. En aquesta tesi doctoral explorem subconjunts específics de miositis definides per autoanticossos i comparem quantitativament la capacitat dels autoanticossos amb la classificació EULAR/ACR de 2017 per predir el fenotip de pacients amb miositis. A més, realitzem la seqüenciació d'ARN en 119 biòpsies musculars de pacients amb diferents tipus de miositis i 20 controls. Estudiem l'expressió diferencial, fem anàlisis de vies i desenvolupem processos d'aprenentatge automàtic exploratoris per definir els perfils específics d'expressió i les vies patogèniques a cada subgrup de malalties. Amb aquests estudis determinem que els autoanticossos superen els criteris clínics actuals per predir el fenotip dels pacients amb miositis i descobrim perfils d'expressió únics al teixit muscular de pacients amb diferents tipus de miositis.
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Godwin, Michael Jason. "Molecular Mapping of Disease-Related Expressed Sequence Tags and Resistance Gene Analogues in Soybean." Thesis, Virginia Tech, 2003. http://hdl.handle.net/10919/35550.
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Soybean has become one of the most important crops to the United States, resulting in a need to improve its disease resistance. The objectives of this study were to 1) design primers and develop PCR-based markers from disease-related expressed sequence tags (ESTs) and resistance gene analogues (RGAs), 2) assess the utility of such markers by diversity analysis of 12 soybean parental lines, and 3) search for possible association of the markers with known disease resistance genes by constructing a linkage map. The diversity analysis will allow this study to determine how well each marker can distinguish genotypes in soybean. Identifying the location of our markers in the soybean genome with the linkage map, will allow those related to disease resistance to be selected. A total of 202 simple sequence length polymorphism (SSLP) markers were constructed using a set of 1218 disease-related ESTs. Furthermore, 22 markers were constructed using previously identified RGA sequences. Both sets of markers were able to detect polymorphism in the diversity analysis. Also, 48 of the SSLPs, five of the RGAs, and 150 molecular markers were used to construct a soybean linkage map using 114 recombinant inbred lines (RILs). Several markers mapped to chromosomal regions known to contain disease resistance genes. This study has created a framework map, which will be useful for identifying the location of resistance genes, marker-assisted selection for resistance, discovering novel resistance genes, and understanding genome organization of resistance pathways in soybean. An effective approach to develop "candidate gene" markers has been demonstrated.Master of Science
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Zhu, Jing Yun Alice. "Beyond the one-sequence-one-structure dogma : predicting and analysing transient and alternative RNA secondary structures that are evolutionarily conserved." Thesis, University of British Columbia, 2015. http://hdl.handle.net/2429/54739.
Full textAbstract:
State-of-the-art methods in RNA secondary structure prediction focus on predicting the final, functional structure. However, ample experimental and statistical evidence indicates that structure formation starts immediately during transcription and this co-transcriptional folding influences the resultant final RNA structure. Thus, identifying the transient structures that are formed co-transcriptionally may bring insight into understanding how co-transcriptional folding leads to the final conformation in vivo. As RNA secondary structures are currently best predicted by comparative approaches, we therefore investigated whether homologous RNA genes not only assume the same final structure, but also share structural features during the co-transcriptional folding in vivo. For this, we compiled a non-redundant data set of 32 transcripts deriving from six different RNA families which constitutes the most comprehensive data set with experimentally confirmed transient and alternative RNA structures so far. We present statistical evidence that homologous RNA genes from related organisms fold co-transcriptionally in a similar way. In particular, we show that some transient structures are highly conserved with levels similar to those of the final, functional structure. Moreover, we find that the predicted co-transcriptional folding pathways of homologous sequences encounter similar transient structure features, which often coincide with known transient features. We thus also predict candidates for these evolutionarily conserved transient features of co-transcriptional folding pathways in silico.
We further expand 4 alignments from the aforementioned dataset by searching via covariance model and manual curation in order to share them with the RNA community. These alignments either update the existing Rfam datasets with annotation of transient structures, or introduce new RNA family: (1) Trp operon leader, where alternative structures are coordinated to regulate the operon transcription in response to tryptophan abundance (2) HDV ribozyme, where the self-cleavage activity is modulated via transient structures involving the extended 5’ flanking sequence (3) 5’ UTR of Levivirus maturation protein, where a transient structure temporarily postpones the formation of the final structure that inhibits the translation of maturation protein (4) SAM riboswitch, where the downstream gene expression is regulated by alternative structures upon binding of SAM.Science, Faculty of
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