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Hvidsten, Torgeir R. "Predicting Function of Genes and Proteins from Sequence, Structure and Expression Data." Doctoral thesis, Uppsala : Acta Universitatis Upsaliensis : Univ.-bibl. [distributör], 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-4490.
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Dodda, Srinivasa Rao. "Improvements and extensions of a web-tool for finding candidate genes associated with rheumatoid arthritis." Thesis, University of Skövde, School of Humanities and Informatics, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-26.
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<p>QuantitativeTraitLocus (QTL) is a statistical method used to restrict genomic regions contributing to specific phenotypes. To further localize genes in such regions a web tool called “Candidate Gene Capture” (CGC) was developed by Andersson et al. (2005). The CGC tool was based on the textual description of genes defined in the human phenotype database OMIM. Even though the CGC tool works well, the tool was limited by a number of inconsistencies in the underlying database structure, static web pages and some gene descriptions without properly defined function in the OMIM database. Hence, in this work the CGC tool was improved by redesigning its database structure, adding dynamic web pages and improving the prediction of unknown gene function by using exon analysis. The changes in database structure diminished the number of tables considerably, eliminated redundancies and made data retrieval more efficient. A new method for prediction of gene function was proposed, based on the assumption that similarity between exon sequences is associated with biochemical function. Using Blast with 20380 exon protein sequences and a threshold E-value of 0.01, 639 exon groups were obtained with an average of 11 exons per group. When estimating the functional similarity, it was found that on the average 72% of the exons in a group had at least one Gene Ontology (GO) term in common.</p>
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Jia, Yizhen, and 贾亦真. "Bioinformatics study of the lineage and tissue specificity of genes and gene expression." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2010. http://hub.hku.hk/bib/B45540652.
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Muhammad, Ashfaq. "Design and Development of a Database for the Classification of Corynebacterium glutamicum Genes, Proteins, Mutants and Experimental Protocols." Thesis, University of Skövde, School of Humanities and Informatics, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-23.
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<p>Coryneform bacteria are largely distributed in nature and are rod like, aerobic soil bacteria capable of growing on a variety of sugars and organic acids. Corynebacterium glutamicum is a nonpathogenic species of Coryneform bacteria used for industrial production of amino acids. There are three main publicly available genome annotations, Cg, Cgl and NCgl for C. glutamicum. All these three annotations have different numbers of protein coding genes and varying numbers of overlaps of similar genes. The original data is only available in text files. In this format of genome data, it was not easy to search and compare the data among different annotations and it was impossible to make an extensive multidimensional customized formal search against different protein parameters. Comparison of all genome annotations for construction deletion, over-expression mutants, graphical representation of genome information, such as gene locations, neighboring genes, orientation (direct or complementary strand), overlapping genes, gene lengths, graphical output for structure function relation by comparison of predicted trans-membrane domains (TMD) and functional protein domains protein motifs was not possible when data is inconsistent and redundant on various publicly available biological database servers. There was therefore a need for a system of managing the data for mutants and experimental setups. In spite of the fact that the genome sequence is known, until now no databank providing such a complete set of information has been available. We solved these problems by developing a standalone relational database software application covering data processing, protein-DNA sequence extraction and</p><p>management of lab data. The result of the study is an application named, CORYNEBASE, which is a software that meets our aims and objectives.</p>
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Basile, Walter. "Orphan Genes Bioinformatics : Identification and properties of de novo created genes." Doctoral thesis, Stockholms universitet, Institutionen för biokemi och biofysik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-149168.
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Even today, many genes are without any known homolog. These "orphans" are found in all species, from Viruses to Prokaryotes and Eukaryotes. For a portion of these genes, we might simply not have enough data to find homologs yet. Some of them are imported from taxonomically distant organisms via lateral transfer; others have homologs, but mutated beyond the point of recognition. However, a sizeable fraction of orphan genes is unambiguously created via "de novo" mechanisms. The study of such novel genes can contribute to our understanding of the emergence of functional novelty and the adaptation of species to new ecological niches. In this work, we first survey the field of orphan studies, and illustrate some of the common issues. Next, we analyze some of the intrinsic properties of orphans proteins, including secondary structure elements and Intrinsic Structural Disorder; specifically, we observe that in young proteins the relationship between these properties and the G+C content of their coding sequence is stronger than in older proteins. We then tackle some of the methodological problems often found in orphan studies. We find that using evolutionarily close species, and sensitive, state-of-the art homology recognition methods is instrumental to the identification of a set of orphans enriched in de novo created ones. Finally, we compare how intrinsic disorder is distributed in bacteria versus eukaryota. Eukaryotic proteins are longer and more disordered; the difference is to be attributed primarily to eukaryotic-specific domains and linker regions. In these sections of the proteins, a higher frequency of the disorder-promoting amino acid Serine can be observed in Eukaryotes.<br><p>At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 3: Submitted. Paper 4: Manuscript.</p>
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Andersson, Malin. "A method for identification of putatively co-regulated genes." Thesis, University of Skövde, Department of Computer Science, 2002. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-705.
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<p>The genomes of several organisms have been sequenced and the need for methods to analyse the data is growing. In this project a method is described that tries to identify co-regulated genes. The method identifies transcription factor binding sites, documented in TRANSFAC, in the non-coding regions of genes. The algorithm counts the number of common binding sites and the number of unique binding sites for each pair of genes and decides if the genes are co-regulated. The result of the method is compared with the correlation between the gene expression patterns of the genes. The method is tested on 21 gene pairs from the genome of Saccharomyces cerevisiae. The algorithm first identified binding sites from all organisms. The accuracy of the program was very low in this case. When the algorithm was modified to only identify binding sites found in plants the accuracy was much improved, from 52% to 76% correct predictions.</p>
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Karjalainen, Merja. "Analysing subsets of gene expression data to find putatively co-regulated genes." Thesis, University of Skövde, Department of Computer Science, 2002. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-712.
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<p>This project is an investigation of whether analysing subsets of time series gene expression data can give additional information about putatively co-regulated genes, compared to only using the whole time series. The original gene expression data set was partitioned into subsets and similarity was computed for both the whole timed series and subsets. Pearson correlation was used as similarity measure between gene expression profiles. The results indicate that analysing co-expression in subsets of gene expression data derives true-positive connections, with respect to co-regulation, that are not detected by only using the whole time series data. Unfortunately, with the actual data set, chosen similarity measure and partitioning of the data, randomly generated connections have the same amount of true-positives as the ones derived by the applied analysis. However, it is worth to continue further analysis of the subsets of gene expression data, which is based on the multi-factorial nature of gene regulation. E.g. other similarity measures, data sets and ways of partitioning the data set should be tried.</p>
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Podowski, Raf M. "Applied bioinformatics for gene characterization /." Stockholm, 2006. http://diss.kib.ki.se/2006/91-7140-818-5/.
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Schaller, Susanne. "Identification of Housekeeping Genes in Human Embryonic Stem Cells." Thesis, University of Skövde, School of Life Sciences, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-3508.
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Ganesan, Abhishekapriya. "The role of RFX-target genes in neurodevelopmental and psychiatric disorders." Thesis, Uppsala universitet, Institutionen för biologisk grundutbildning, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-445493.
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Neurodevelopmental disorders such as autism spectrum disorder (ASD) and psychiatric disorders, for example, schizophrenia (SCZ) represent a large spectrum of disorders that manifest through cognitive and behavioural problems. ASD and SCZ are both highly heritable, and some phenotypic similarities between ASD and SCZ have sparked an interest in understanding their genetic commonalities. The genetics of both disorders exhibit significant heterogeneity. Developments in genomics and systems biology, continually increases people’s understanding of these disorders. Recently, pathogenic genetic variants in the regulatory factor X (RFX) family of transcription factors have been identified in a number of ASD cases. In this thesis, common genetic variants and expression patterns of genes identified to have a conserved promotor X-Box motif region, a binding site of RFX factors, are studied. Significant common variants identified through expression quantitative trait loci (eQTLs) and genome wide association studies (GWAS) are mapped to the regulatory regions of these genes and analysed for putative enrichment. In addition, single-cell RNA sequencing data is utilised to examine enrichment of cell types having high X-Box gene expression in the developing human cortex. Through the study, genes that have eQTLs or SNPs in the genomic regulatory regions of the X-Box genes have been identified. While there were no eQTLs or GWAS SNPs in the X-Box motifs, in the X-Box promoter regions some common variants were found. By hypergeometric distribution testing and the subsequent p-values obtained, all of these distributions are statistically under-enriched. Further, major cell types in the cortical region with increased expression of the X-Box genes and most expressed genes among these enriched cell types have been identified. Among the 11 cell types seven were found to be enriched for X-Box genes and many of the most expressed genes in these cell-types were similar. A further study into the cell types and genes identified, along with additional systems biological data analysis, could reveal a larger list of X-Box genes involved in ASD and SCZ and the specific roles of these genes.
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Jantscher, Yvonne. "Identification of miRNAs and their target genes in stem cell derived cardiomyocytes." Thesis, Högskolan i Skövde, Institutionen för vård och natur, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-5164.
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Stem cell research, especially the one dealing with human embryonic stem cells, is a major topic nowadays. In the last few years studies about human embryonic stem cell derived cardiomyocytes highlighted the importance of those, as their characteristics are almost identical as of the cardiomyocytes in the heart (i.e. the contraction of those cells). The studies concentrate on the ability of using cardiomyocytes in the drug development for cardiac diseases or in regenerative medicine and cell replacement therapies. In contrast some researchers concentrate on microRNAs (miRNAs) as regulators in the development of cardiomyocytes. This study combines both research topics as it deals with stem cells and miRNAs (as well as their target mRNAs). A main objective is to find differentially expressed genes by using Significance Analysis of Microarrays (SAM) as method. Furthermore miRNA target prediction is applied and the identified targets are compared with the ones found by SAM. With an intersection approach we derived 41 targets of up-regulated miRNAs and 25 targets of down-regulated miRNAs, which can be the basis for further studies (i.e. knock-out experiments).
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Haughey, Caitlin, Lauri Mesilaakso, Erik Berner-Wik, Emma Östlund, Jonatan Ulfsparre, and Hampus Olin. "Probes for ESBL : A Method for Production of Probe Targets in Antibiotic Resistant Genes." Thesis, Uppsala universitet, Institutionen för biologisk grundutbildning, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-323686.
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This project aimed to find a method for producing potential probe targets for identification of ESBL (Extended Spectrum Beta Lactamase) genes in bacteria. ESBLs are a type of enzymes responsible for antibiotic resistance in many bacteria. The result we developed was a semi-automated pipeline that utilises several Perl scripts to download gene sequences, identify sequence subgroups based on sequence similarity, find common target sequences among them and screen the target sequences against a background database. These target sequences should work with padlock probes and therefore had specific requirements regarding length and highest number of allowed mismatches. This report includes descriptions of the scripts and ideas for future improvements, as well as an ethical analysis about aspects relevant to research on antibiotic resistance.
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Kandoth, Cyriac. "A quantitative study of gene identification techniques based on evolutionary rationales." Diss., Rolla, Mo. : University of Missouri-Rolla, 2007. http://scholarsmine.mst.edu/thesis/pdf/Kandoth_09007dcc804902b3.pdf.
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Thesis (M.S.)--University of Missouri--Rolla, 2007.<br>Vita. The entire thesis text is included in file. Title from title screen of thesis/dissertation PDF file (viewed February 6, 2008) Includes bibliographical references (p. 36).
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Veanes, Margus. "Identification of novel loss of heterozygosity collateral lethality genes for potential applications in cancer." Thesis, Uppsala universitet, Institutionen för biologisk grundutbildning, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-433768.
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Over the course of this project, I demonstrate the utility of a 4-phase analysis pipeline in the context of cancer therapy and the associated search for antineoplastic drug candidates. I showcase a repeatable means for generating lists of potential targets which may be used in conjunction with methods like small molecule screening as part of a search for broadly effective antineoplastic agents. By using publicly available variant call format (VCF) data sourced from the 1000 genomes project, global human population-wide data for non-sex chromosomes was filtered and transformed in a 4-phase process to obtain high population frequency, heterozygotic, nonsynonymous single nucleotide variants (nsSNVs) residing in functional domains of proteins. Through manual filtration combined with software-assisted annotation, I obtained a ranked list of 50 top scoring annotated variants across the human autosome, all residing in known protein domains. Additionally, a single top variant was selected for proof-of-concept structure prediction and visualization. When the methodology outlined herein is coupled to additional loss-of-heterozygosity (LOH) prevalence data across cancer genomes, it may be used to identify candidate variants which collectively represent potential loss-of-heterozygosity based collateral lethalities (CL) in the underlying cancer. Furthermore, under the assumption that subsequent methods like small molecule screening succeed in finding molecule(s) targeting a structural aspect of one of these variants, any subsequently developed therapeutic approaches may possess broader therapeutic utility dependent upon the strictness of the initial heterozygotic filtering threshold applied at the onset of the project pipeline. When combined with additional cancer data, the recreation of such gene lists at other degrees of heterozygotic thresholding can allow for the creation of lists of autosomal loss-of-heterozygosity gene candidates, representing potential collateral lethality targets with varied degrees of utility dependent upon the strictness of the initial filtration threshold.
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Lagervik, Öster Alice. "Probability calculations of orthologous genes." Thesis, University of Skövde, School of Humanities and Informatics, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-972.
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<p>The aim of this thesis is to formulate and implement an algorithm that calculates the probability for two genes being orthologs, given a gene tree and a species tree. To do this, reconciliations between the gene tree and the species trees are used. A birth and death process is used to model the evolution, and used to calculate the orthology probability. The birth and death parameters are approximated with a Markov Chain Monte Carlo (MCMC). A MCMC framework for probability calculations of reconciliations written by Arvestad et al. (2003) is used. Rules for orthologous reconciliations are developed and implemented to calculate the probability for the reconciliations that have two genes as orthologs. The rules where integrated with the Arvestad et al. (2003) framework, and the algorithm was then validated and tested.</p>
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Paramonov, Ida. "Deriving a refined set of housekeeping genes in differentiating human embryonic stem cells." Thesis, University of Skövde, School of Humanities and Informatics, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-1053.
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<p>In this thesis project housekeeping genes in differentiating human embryonic stem cells were investigated. Housekeeping genes are involved in basic functions in the cells and are assumed to be expressed at relatively constant levels across different cell types and experimental conditions. Based on these features, housekeeping genes are frequently used as controls in calibration of gene expression data. Commonly used housekeeping genes in somatic tissues have shown to vary notably in human embryonic stem cells and are therefore inappropriate as reference genes in this unique cell type. In the present work a novel set of gene expression data obtained by profiling of undifferentiated and early differentiating cardiac cells, was analyzed. Stably expressed genes were identified in this data set and were subsequently intersected with a previously proposed set of 292 stable genes in human embryonic stem cells. A resulting set of 73 genes show stability across all investigated cell lines and experimental conditions. These genes are suggested as a more reliable set of reference genes in differentiating human embryonic stem cells than frequently used housekeeping genes in somatic tissue. In addition, a novel set of 20 genes was identified as very stably expressed during the differentiation towards the cardiac lineage. After further validation of stability with RT-PCR, these genes could be useful as controls in studies of human embryonic stem cells that differentiate towards the cardiac lineage.</p>
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Wang, Tianyuan. "Identifying Transcription Factor Targets and Studying Human Complex Disease Genes." NCSU, 2009. http://www.lib.ncsu.edu/theses/available/etd-03132009-120540/.
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Transcription factors (TFs) have been characterized as mediators of human complex disease processes. The target genes of TFs also may be associated with disease. Identification of potential TF targets could further our understanding of gene-gene interactions underlying complex disease. We focused on two TFs, USF1 and ZNF217, because of their biological importance, especially their known genetic association with coronary artery disease (CAD), and the availability of chromatin immunoprecipitation microarray (ChIP-chip) results. First, we used USF1 ChIP-chip data as a training dataset to develop and evaluate several kernel logistic regression prediction models. Our most accurate predictor significantly outperformed standard PWM-based prediction methods. This novel prediction method enables a more accurate and efficient genome-scale identification of USF1 binding and associated target genes. Second, the results from independent linkage and gene expression studies suggest that ZNF217 also may be a candidate gene for CAD. We further investigated the role of ZNF217 for CAD in three independent CAD samples with different phenotypes. Our association studies of ZNF217 identified three SNPs having consistent association with CAD in three samples. Aorta expression profiling indicated that the proportion of the aorta with raised lesions was also positively correlated to ZNF217 expression. The combined evidence suggests that ZNF217 is a novel susceptibility gene for CAD. Finally, we applied our previously developed TF binding site (TFBS) prediction method to ZNF217. The performance of the prediction models of ZNF217 and USF1 are very similar. We demonstrated that our TFBS prediction method can be extended to other TFs. In summary, the results of this dissertation research are (1) evaluation of two TFs, USF1 and ZNF217, as susceptibility factors for CAD; (2) development of a generalized method for TFBS prediction; (3) prediction of TFBSs and target genes of two TFs, and identification of SNPs within TFBSs. This research allows for the development of study design to access TF based interactions in genetic susceptibility to human complex disease.
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Tahseen, Yahia Keelani Ahlam. "Genes involved in inflammation are within celiac disease risk loci show differential mRNA expression." Thesis, Högskolan i Skövde, Institutionen för biovetenskap, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-16292.
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Celiac disease (CD) is a chronic autoimmune disease, caused by the consumption of gluten in genetically predisposed individuals. Celiac patients develop many clinical features include; weight loss, diarrhea, and Intestinal damage, and if left untreated, CD patient may face an increased risk of malignancies. Materials and methods403 patient were admitted to the study. These patients were divided into three groups; celiac cases, controls, and latent celiac cases. Gene expression analysis was performed for intestinal biopsies and blood samples (leukocytes) using a quantitative PCR technique. The second section of the study was studying the effect of PRODH enzyme on Drosophila Melanogaster intestines. To achieve that PRODH enzyme and different amino acids were added to the fly food. One way ANOVA and Wilcoxon tests were applied to find out the significant genes. ResultsMost of the differentially expressed genes in celiac disease are involved in the inflammatory response. However, many genes have significantly altered expression in the latent celiac group but not altered significantly in CD group. These genes are CXCL1, IL15RA, IL2RB, MAPK11, and TGM2. They are involved in the TNF signaling pathway and in inflammatory cytokines. It was noticed that in celiac disease there is a significant alteration in PRODH expression in the intestines, and the addition of PRODH enzyme to glutamine has a similar effect on the intestinal gene expression as gluten does. ConclusionWe can conclude that Non-HLA genes are important in activating the immune system, increasing proline level, and developing the clinical features of celiac disease. Secondly, Proline metabolism has an important role in tumor suppression and in augmenting tumor growth, which makes it an important therapeutic target in tumor therapy.
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Zhang, Li. "Statistical Methods for Identifying X-linked Genes Associated with Complex Phenotypes." NCSU, 2007. http://www.lib.ncsu.edu/theses/available/etd-10232007-163904/.
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Genetic association studies aim to detect association between one or more genetic polymorphisms and complex traits, which might be some quantitative characteristic or a qualitative attribute of disease. In Chapter 1, we introduce the development of methods for association mapping in the past decades and present the rationale behind our X-linked method development. Family-based association methods have been well developed for autosomes, but unique features of X-linked markers have received little attention. In Chapter 2, we propose a likelihood approach (X-LRT) to estimate genetic risks and test association using a case-parents design. The method uses nuclear families with a single affected proband, and allows additional siblings and missing parental genotypes. We also extend X-LRT from a single-marker test to a multiple-marker haplotype analysis. Our X-LRT offers great flexibility for testing different penetrance relationships within and between sexes. In addition, estimation of relative risks provides a measure of the magnitude of X-linked genetic effects on complex disorders. In Chapter 3 and 4, we fill the methodological gaps by developing two approaches (X-QTL and X-HQTL) to test association between X-linked marker alleles/haplotypes and quantitative traits in nuclear family design. We adopt the orthogonal decomposition which provides consistent estimates of the additive genetic values of marker alleles/haplotypes. Joint estimation of the linkage variance component in the association model reduces type I errors to nominal expectations. Dosage compensation models provide a simple relationship of X-linked additive effects between sexes. In Chapter 2, 3, and 4, our simulation results demonstrate the validity and substantially higher power of our approaches compared with other existing programs. We also apply our methods to MAOA & MAOB candidate-gene studies of family data with Parkinson disease. In Chapter 5, we discuss some issues relevant to the design and execution of our X-linked family-based association studies.
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Mesilaakso, Lauri. "Bioinformatic approaches for detecting homologous genes in the genomes of non-model organisms : A case study of wing development genes in insect genomes." Thesis, Uppsala universitet, Evolutionsbiologi, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-398072.
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Identifying homologous genes, that is genes from a common ancestor, is important in comparative genomic studies for understanding gene annotation and the predicted function of a gene. Several pieces of software, of which the most well-known is BLAST, have been developed for identifying homologues, but this can be challenging in non-model organisms where sometimes poor quality of genome assemblies and lack of annotation make it difficult to robustly identify homologues. The aim of this project was to build a bioinformatic framework for homology detection using genomes from non-model organisms. The approach developed used genome annotations, annotated polypeptide sequences and genome assembly sequences to detect homologous genes.The framework was applied to identify Drosophila melanogaster homologous wing development genes in the genomes of nine other insect species with the aim to understand the evolution of loss of wings. To identify changes related to wing loss, the homologous protein sequences obtained were aligned and phylogenetic trees were built from them. The aim of creating the multiple protein alignments and phylogenetic trees was to shed light on whether changes in gene sequences can be related to presence or absence of wings. From the set of 21 candidate wing development genes identified with literature and subsequent database searches, I tested eight and was successful in identifying homologues for all of them in eight of the 10 in sectgenomes. This was done using a combination of text searches in genome annotations, searches with Exonerate v. 2.4.0 alignment program in annotated polypeptide sequences and in genome assemblies. The eight genes chosen for testing the framework were based on initial finding of putative homologues in the eight insect genomes when using the first two steps of the framework. For the set of homologous wing development genes examined I was not able to identify any conclusive pattern of potential protein coding changes that correlated with loss of wings in these species. Improvement to the current pipeline could include using query sequences from closer relatives of the 8 test species than D. melanogaster and, of course, testing of the remaining wing development genes as well as further literature study of wing development genes. Together these could improve future studies on the evolution of wing loss in insects.
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Chan, Simon Kit. "A bioinformatics meta-analysis of differentially expressed genes in colorectal cancer." Thesis, University of British Columbia, 2007. http://hdl.handle.net/2429/379.
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BACKGROUND: Elucidation of candidate colorectal cancer biomarkers often begins by comparing the expression profiles of cancerous and normal tissue by performing high throughput gene expression profiling. While many such studies have been performed, the resulting lists of differentially expressed genes tend to be inconsistent with each other, suggesting that there are some false positives and negatives. One logical solution to this problem is to determine the intersection of the lists of differentially expressed genes from independent studies. It is expected that genes that are biologically relevant to cancer tumorigenesis will be reported most often, while sporadically reported genes are due to the inherent biases and limitations of each of the profiling platforms used. However, the statistical significance of the observed intersection among many independent studies is usually not considered. PURPOSE: To address these issues, we developed a computational meta-analysis method that ranked differentially expressed genes based on the following criteria, which are presented in order of importance: the amount of intersection among studies, total tissue sample sizes, and average fold change in expression. We applied this meta-analysis method to 25 independent colorectal cancer profiling studies that compared cancer versus normal, adenoma versus normal, and cancer versus adenoma tissues.
RESULTS: We observed that some genes were consistently reported as differentially expressed with a statistically significant frequency (P <.0001) in the cancer versus normal and adenoma versus normal comparisons, but not in the cancer versus adenoma comparison. We performed a review of some of the high ranking candidates and determined that some have previously been shown to have diagnostic and/or prognostic utility in colorectal cancer. More interestingly, the meta-analysis method also identified genes that had yet to be tested and validated as biomarkers. Thus, these candidates are currently being validated at the protein level on colorectal tissue microarrays.
CONCLUSION: Our meta-analysis method identified genes that were consistently reported as differentially expressed. Besides identifying new biomarker candidates, our meta-analysis method also provides another filter to remove false positive genes from further consideration. In conclusion, the genes presented here will aid in the identification of highly sensitive and specific biomarkers in colorectal cancer.
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Kondratowicz, Andrew Steven. "A bioinformatics approach to identifying novel genes involved in ebolavirus entry." Diss., University of Iowa, 2011. https://ir.uiowa.edu/etd/5003.
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Ebolavirus (EBOV) is a negative sense, single stranded RNA virus that causes Ebola hemorrhagic fever. This disease causes substantial morbidity and mortality in humans, with death occurring in 50-90% of cases. Despite years of intensive research, much of the molecular mechanism underlying the entry of EBOV remains unknown. We performed a bioinformatics screen to identify novel entry cofactors by correlating mRNA expression in a panel of human cancer cell lines with permissivity to the EBOV entry glycoprotein. This assay identified several known EBOV entry cofactors such as actin and the tyrosine kinase Axl. In addition, several genes involved in macropinocytosis and endosomal maturation were also correlated with EBOV permissivity.
Subsequent evaluation of plasma membrane proteins correlated by this screen showed T-cell immunoglobulin and mucin domain-1 (TIM-1) mRNA expression correlated extremely well with EBOV pseudovirion transduction. Depletion of TIM-1 from highly-permissive cells inhibits EBOV pseudovirion transduction. Conversely, expression of TIM-1 in poorly-permissive cells significantly and specifically enhances EBOV pseudovirion transduction and infection. TIM-1 binds to EBOV GP and this binding is important in the initial interaction between the virus and the host cell. ARD5, a TIM-1 mAb, significantly inhibits EBOV GP-mediated entry into several cell lines and primary human airway epithelia in a dose and time-dependent manner. Therefore, TIM-1 is the first receptor identified for EBOV.
Additionally, AMP-activated protein kinase (AMPK) mRNA correlated strongly with EBOV pseudovirion transduction. Compound C, a specific AMPK inhibitor, inhibited EBOV pseudovirion transduction and infection in a time and dose-dependent manner into several cell lines and primary human monocyte derived macrophages. Mouse embryonic fibroblasts (MEFs) lacking functional AMPK were significantly less permissive to EBOV GP-mediated infection that WT MEFs. Visualization of virus entry into these cells revealed that EBOV causes actin polymerization independently of AMPK, but AMPK-/- cells do not form lamellipodia in the presence of EBOV and, consequently, cannot internalize virus into cells by macropinocytosis.
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Bakhtiyari, Elnaz. "Analysis of differentially expressed genes (DEGs) in neuronal cells from the cerebral cortex of Alzheimer’s disease mouse model." Thesis, Högskolan i Skövde, Institutionen för biovetenskap, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-19218.
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Alzheimer’s disease (AD) is an aging-related neurodegenerative disorder with large implications for society and individuals. AD is a multi-factor disorder, with these factors having a direct or indirect correlation with each other. Despite many studies with different aspects on molecular and cellular pathways, there is still no specific treatment for AD. Identification of potential pathogenic factors can be done by transcriptomic studies of differentially expressed genes (DEGs), but the outcomes have been contradictory. Using both bioinformatics and meta-analysis methods can be useful for removing such inconsistencies. A useful and common approach for a better understanding of neurodegenerative disease is to assess its molecular causes, by comparing the gene expression levels in healthy and disease tissues. Next-generation RNA-sequencing is a valuable method for analyzing both coding and non-coding regions of RNA, and it has made it possible to identify differentially expressed genes in large-scale data. The aim of the current study was to get a better understanding of the transcriptional changes in AD models, and identify differentially expressed genes between healthy and AD individuals from the adult mouse brain model as well as detecting AD pathways. In this study, the transcriptomes of purified neuron, astrocyte and microglia cells from mouse brains were analyzed using publicly available RNA-seq datasets. The DEGs were identified for all three mentioned cell types using DESeq2 and EdgeR packages. All statistical analyses were performed by R software and the DEGs detected by DESeq2 and edgeR, respectively, were compared using Venn diagrams. Additionally, analyzing the AD pathway was performed using GOrilla tool for visualizing the enriched gene ontology (GO) terms in the list of ranked genes. From this project, it was found that there were very few significantly DEGs between AD and healthy samples in neuron cells, while there were more DEGs in astrocyte and microglia cells. In conclusion, comparing DESeq2 and egeR packages using Venn diagrams showed a slight advantage of DESeq2 in detection accuracy, since it was able to identify more DEGs than edgeR. Moreover, analyzing AD pathway using GOrilla tool indicated that identified enriched GO terms by each cell type differed from each other. For astrocytes, more enriched GO terms were identified than for microglia cells, while no significant enriched GO terms were detected for neuron cells.
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Loo, Lit-Hsin Kam Moshe. "Identifying differentially expressed genes in DNA microarray data /." Philadelphia, Pa. : Drexel University, 2004. http://dspace.library.drexel.edu/handle/1860/375.
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Erten, Mehmet Sinan. "Network Based Prioritization of Disease Genes." Cleveland, Ohio : Case Western Reserve University, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=case1258743578.
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Thesis(M.S.)--Case Western Reserve University, 2009<br>Title from PDF (viewed on 2010-01-28) Department of Electrical Engineering and Computer Science -- Computer and Information Sciences Includes abstract Includes bibliographical references and appendices Available online via the OhioLINK ETD Center
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Ahmed, Ashraf. "Investigation of immunity related genes in a disease host using applied bioinformatics." Thesis, University of Sheffield, 2017. http://etheses.whiterose.ac.uk/18247/.
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Bailey, Christopher Michael. "A Bioinformatics Analysis of Bacterial Type-III Secretion System Genes and Proteins." Thesis, University of Birmingham, 2010. http://etheses.bham.ac.uk//id/eprint/1300/.
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Type-III secretion systems (T3SSs) are responsible for the biosynthesis of flagella, and the interaction of many animal and plant pathogens with eukaryotic cells. T3SSs consist of multiple proteins which assemble to form an apparatus capable of exporting proteins through both membranes of Gram-negative bacteria in one step. Proteins conserved amongst T3SSS can be used for analysis of these systems using computational homology searching. By using tools including BLAST and HMMER in conjunction phylogenetic analysis this thesis examines the range of T3SSs, both in terms of the proteins they contain, and also the bacteria which contain them. In silico analysis of several of the conserved components of T3SSs shows similarities between them and other secretion systems, as well as components of ATPases. Use of conserved components allows for identification of T3SS loci in diverse bacteria, in order to assess in the different proteins used by different T3SSs, and to see where, in evolutionary space, these differences arose. Analysis of homology data also allows for comprehensive re-annotation of T3SS loci within Desulfovibrio, Lawsonia and Hahella, and subsequent comparison of these T3SSs with related Yersinial T3SSs, and also (in conjunction with in vitro assays) for identification of many novel effectors in E. coli.
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Özdogan, Alper. "Clustering Genes by Using Different Types of Genomic Data and Self-Organizing Maps." Thesis, University of Skövde, School of Life Sciences, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-2265.
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<p>The aim of the project was to identify biologically relevant novel gene clusters by using combined genomic data instead of using only gene expression data in isolation. The clustering algorithm based on self-organizing maps (Kasturi et al., 2005) was extended and implemented in order to use gene location data together with the gene expression and the motif occurrence data for gene clustering. A distance function was defined to be used with gene location data. The algorithm was also extended in order to use vector angle distance for gene expression data. <em>Arabidopsis thaliana</em> is chosen as a data source to evaluate the developed algorithm. A test data set was created by using 100 Arabidopsis genes that have gene expression data with seven different time points during cold stress condition, motif occurrence data which indicates the occurrence frequency of 614 different motifs and the chromosomal location data of each gene. Gene Ontology (http://www.geneontology.org) and TAIR (http://arabidopsis.org) databases were used to find the <em>molecular function</em> and <em>biological process</em> information of each gene in order to examine the biological accuracy of newly discovered clusters after using combined genomic data. The biological evaluation of the results showed that using combined genomic data to cluster genes resulted in new biologically relevant clusters.</p>
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Lupindo, Bukiwe. "Prevalence and frequency spectra of single nucleotide polymorphisms at exon-intron junctions of human genes." Master's thesis, University of Cape Town, 2008. http://hdl.handle.net/11427/4289.
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Includes bibliographical references (leaves 92-112).<br>In humans and other higher eukaryotes the observation of multiple splice isoforms for a given gene is common. However it is not clear whether all of these alternatively spliced isoforms are a product of true alternative splicing or some are due to DNA sequence variations in human populations. Genetic variations that affect splicing have been shown to cause variation in splicing patterns and potentially are an important source of phenotypic variability among humans. Furthermore, variation in disease susceptibility and manifestation between individuals is often associated with genetic polymorphisms that determine the way in which genes are spliced. Hence, identification of genetic polymorphisms that might affect the way in which pre-mRNAs are spliced is an area of great interest.
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Gómez-Porras, Judith Lucia. "In silico identification of genes regulated by abscisic acid in Arabidopsis thaliana (L.) Heynh." Phd thesis, Universität Potsdam, 2005. http://opus.kobv.de/ubp/volltexte/2006/740/.
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Abscisic acid (ABA) is a major plant hormone that plays an important role during plant growth and development. During vegetative growth ABA mediates (in part) responses to various environmental stresses such as cold, drought and high salinity. The response triggered by ABA includes changes in the transcript level of genes involved in stress tolerance. The aim of this project was the In silico identification of genes putatively regulated by ABA in A. thaliana. In silico predictions were combined with experimental data in order to evaluate the reliability of computational predictions.<br><br>
Taking advantage of the genome sequence of <i>A. thaliana</i> publicly available since 2000, 1 kb upstream sequences were screened for combinations of cis-elements known to be involved in the regulation of ABA-responsive genes. It was found that around 10 to 20 percent of the genes of <i>A. thaliana</i> might be regulated by ABA.<br><br>
Further analyses of the predictions revealed that certain combinations of cis-elements that confer ABA-responsiveness were significantly over-represented compared with results in random sequences and with random expectations. In addition, it was observed that other combinations that confer ABA-responsiveness in monocotyledonous species might not be functional in A. thaliana. It is proposed that ABA-responsive genes in <i>A. thaliana</i> show pairs of ABRE (abscisic acid responsive element) with MYB binding sites, DRE (dehydration responsive element) or with itself.<br><br>
The analysis of the distances between pairs of cis-elements suggested that pairs of ABREs are bound by homodimers of ABRE binding proteins. In contrast, pairs between MYB binding sites and ABRE, or DRE and ABRE showed a distance between cis-elements that suggested that the binding proteins interact through protein complexes and not directly.<br><br>
The comparison of computational predictions with experimental data confirmed that the regulatory mechanisms leading to the induction or repression of genes by ABA is very incompletely understood. It became evident that besides the cis-elements proposed in this study to be present in ABA-responsive genes, other known and unknown cis-elements might play an important role in the transcriptional regulation of ABA-responsive genes. For example, auxin-related cis elements, or the cis-elements recognized by the NAM-family of transcription factors (Non-Apical meristem).<br><br>
This work documents the use of computational and experimental approaches to analyse possible interactions between cis-elements involved in the regulation of ABA-responsive genes. The computational predictions allowed the distinction between putatively relevant combinations of cis-elements from irrelevant combinations of cis-elements in ABA-responsive genes. The comparison with experimental data allowed to identify certain cis-elements that have not been previously associated to the ABA-mediated transcriptional regulation, but that might be present in ABA-responsive genes (e.g. auxin responsive elements). Moreover, the efforts to unravel the gene regulatory network associated with the ABA-signalling pathway revealed that NAM-transcription factors and their corresponding binding sequences are important components of this network.<br>Pflanzen reagieren auf aeußere Stresseinwirkung (z.B. Trockenheit oder Hitze) u.a. mit der Bildung bestimmter Hormone. Diese Hormone wiederum bewirken eine Vielzahl komplexer Reaktionen (z.B. im Stoffwechsel und in der Genexpression), die zum Ziel haben, die Pflanzen widerstandsfaehiger gegen die Stresssituation zu machen. Ein wichtiges Stresshormon ist die Abzisinsaeure (ABA, fuer engl. „abscisic acid“). Experimentell koennen Pflanzen durch die Gabe von ABA zu Reaktionen gezwungen werden, die normalerweise nur unter Stressbedingungen beobachtet werden. Hierzu zaehlen vor allem eine Reduktion der Spaltoeffnungen in den Blaettern, um den Wasserverlust infolge von Transpiration zu minimieren, und eine massive Umprogrammierung der Genexpression.<br><br>
In der vorliegenden Arbeit wurde der Einfluss von ABA auf die Genexpression in der Modellpflanze <i>Arabidopsis thaliana</i> untersucht. Hierzu wurden bioinformatorische und experimentelle Ansaetze verknuepft. Die bioinformatorischen Ansaetze bedienten sich der bekannten Sequenz des Genoms von <i>A. thaliana</i>. Mit Hilfe verschiedener geeigneter Computerprogramme wurden im Genom Gene identifiziert, deren Expression potentiell durch ABA reguliert wird. Die so erhaltenen Vorhersagen der verschiedenen Programme wurden miteinander und mit eigenen als auch mit publizierten experimentellen Daten verglichen, um die Qualitaet der Vorhersagen zu beurteilen. <br><br>
Die wichtigste Schlussfolgerung aus den Ergebnissen dieser Arbeit ist, dass gegenwaertig bioinformatorische Ansaetze allein nicht ausreichen, um biologische Prozesse zufriedenstellend zu analysieren. In der vorliegenden Arbeit ermoeglichte erst eine Kombination aus bioinformatorischen und experimentellen Ansaetzen die Generierung neuer, abgesicherter Hypothesen zur ABA-induzierten Umprogrammierung der Genexpression.
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Münzner, Ulrike. "Gene fishing in Cataglyphis fortis – Identification of genes inthe desert ant." Thesis, Linköping University, Department of Physics, Chemistry and Biology, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-20455.
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<p>The desert ant Cataglyphis fortis lives in the Sahara desert where it is exposed to extreme temperatures up to 70° C. In other words, the organism is considered as a thermophile. Until now the genome remains unknown but the fact that C. fortis provides heat stable proteins makes it very interesting in the field of protein studies and maybe even therapeutical research later on. This thesis focuses on trying to find genes that are expressed in C. fortis. Different genes were chosen and capable primers designed. After fishing for the enzyme GAPDH a fragment was found and sequenced. The sequence showed 31% homology on amino acid level with protein disulfide isomerase (PDI) in Apis mellifera (honey bee) and Drosophila melanogaster (fruitfly). The received sequence can be used to design new primers that match exactly. Gene fishing can also be continued by using the other primers that were designed during this project.</p>
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Savelkoul, Elizabeth Jennings. "Molecular evolution of meiosis genes in fungi." Diss., University of Iowa, 2013. https://ir.uiowa.edu/etd/6635.
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Meiosis as a general process is prevalent across the eukaryotes, as are the orthologs of many genes encoding proteins known to function in meiosis. However, many organisms have experienced derived losses of otherwise well-conserved meiosis genes without losing meiosis and sexual reproduction. Although this general conservation of meiosis genes and precedent for derived meiosis gene losses has been previously established, questions remain about the frequency of and evolutionary forces contributing to these trends. This work sought (i) to characterize the phylogenetic distribution of 15 meiosis genes (most of which are known to function only in meiosis) in the exemplar eukaryotic kingdom Fungi and (ii) to use this dataset to investigate evolutionary processes contributing to the loss and retention of these genes.
Orthologs of 15 meiosis genes (Rad51, Rad21, Spo11, Rec8, Dmc1, Hop2, Mnd1, Sae3/Swi5, Mei5/Sfr1, Pch2, Hop1, Msh4, Msh5, Mer3, Zip3) were identified by BLAST-based techniques and phylogenetically validated in most of the 109 publicly available sequenced fungal genomes investigated, but numerous putative derived losses were also detected. Rad51, Rad21, Rec8, and Spo11 were nearly universally conserved; the remaining genes were each undetectable or independently pseudogenized multiple times within fungi, particularly often for Pch2. Genes with previously known functional interactions tended to show parallel presence, absence, or pseudogenization patterns. Although this work primarily established the conserved presence of meiosis gene orthologs at the DNA level, examination of expressed sequence tags (ESTs) showed that many species--including some not previously known to undergo sexual reproduction--were competent to transcribe (and often splice) mRNA from the identified meiosis genes.
Factors potentially influencing derived meiosis gene losses were investigated in two ways. First, degenerate PCR was used to amplify loci expected to contain orthologs of Msh4, Msh5, Pch2, and Zip3 in various Aspergillus species closely related to Aspergillus nidulans (a species with undetected or pseudogenized orthologs of these four genes.) The loss of Pch2 substantially predated the pseudogenization of Msh4, Msh5, and Zip3. Evolutionary rate analyses using the Ka/Ks ratio found no change in nonsynonymous substitution patterns in Msh4 and Msh5 in species that had lost Pch2 compared to those retaining Pch2. Elevated Zip3 Ka/Ks values were found in species with pseudogenized Msh4 and Msh5, suggesting possible obligate functional interactions of Zip3 with Msh4 and Msh5. Second, phylogenetically independent contrasts (PIC) analyses were performed on species from the 109-taxon inventory with published chromosome number and chromosome size estimates to investigate whether changes in either parameter were consistently associated with changes in the presence or absence of meiosis genes. Many analyses had low statistical power, neither detecting nor being able to exclude an association between gene loss and the tested variables. However, several comparisons did detect significant or nearly significant trends: for example, fungi that had lost genes related to crossover interference (Msh4, Msh5, or Pch2) tended to have fewer and/or larger chromosomes than their closest relatives without gene loss.
A final objective was to determine the distribution of meiosis genes in lichenized fungi and green algae to see whether this form of symbiosis was associated with differences in the presence or molecular evolution of meiosis genes. Rad51, Dmc1, and Mnd1 were each amplified by degenerate PCR from multiple lichenized fungi that lacked sequenced genomes, and no systematic difference in evolutionary rate was found between examined lichenized fungi compared to other examined classes in phylum Ascomycota. Bioinformatic analyses of meiosis gene distribution in green algae revealed not only no obvious increased tendency for derived gene losses in examined lichenized green algae but also very few derived meiosis gene losses in green algae in general. This suggests that lichenization may not be associated with consistent differences in the evolution of meiosis genes in either fungal or green algal symbionts. The green algal results also illustrate the need to investigate the extent to which eukaryotes as a whole exhibit the same trends of meiosis gene evolution described here for fungi: frequent derived losses of meiosis genes, genes encoding proteins with function interactions showing similar distributions, likely roles for post-transcriptional regulation of meiosis gene transcripts, and loss of crossover distribution-related genes potentially being associated with constraints on chromosome size and/or haploid chromosome number.
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Chen, Jing. "Computational Selection and Prioritization of Disease Candidate Genes." University of Cincinnati / OhioLINK, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1211228557.
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Alles, Marie Chehani Clinical School St Vincent's Hospital Faculty of Medicine UNSW. "A bioinformatics approach to discovery of estrogen-responsive genetic pathways in breast cancer." Awarded by:University of New South Wales. Clinical School - St Vincent's Hospital, 2008. http://handle.unsw.edu.au/1959.4/41513.
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Breast cancers fall into two major classes depending on their estrogen receptor (ER) status. ER+ and ER- tumors have very different molecular phenotypes, and may have distinct cells of origin. ER- tumors generally fail to respond to endocrine therapy and have a poorer prognosis. To develop a comprehensive understanding of the gene networks active in ER+ compared to ER- breast cancers, we performed a meta-analysis of Grade 3 breast cancers from five published datasets. A measure of association with ER status taking into account intra- and inter-study variability was calculated for every probe set. The meta-analysis revealed that ER-/Grade 3 tumors show increased expression of proliferation-associated functional categories when compared to ER+/Grade 3 tumors. Using Gene Set Enrichment Analysis we show that transcript levels of direct transcriptional targets of ER are lower in ER- tumors, but that expression of other estrogen-induced genes is higher in ER- tumors. Transcript levels of both direct and other targets of the estrogen-regulated MYC gene and the E2F family of genes are significantly higher in ER- tumors. The increased expression of targets of MYC and E2F is particularly pronounced in the "basal" subgroup of ER- tumors. This suggests that a study assessing the association of these genes with clinical outcome in ER- patients is warranted, but is not currently feasible due to lack of suitable publicly available data. The contribution of genes regulated or bound by estrogen, MYC or E2F to increased risk of relapse in ER+ tamoxifen-treated patients was assessed in a pilot study using Cox proportional hazards models and Gene Set Enrichment Analysis. The high expression of several gene sets containing genes induced by estrogen and/or MYC and direct targets of MYC and E2F was correlated with poor outcome in these patients. We conclude that over-expression or constitutive activation of MYC, possibly in conjunction with elevated E2F activity, may lead to the induction of a set of genes characteristic of the estrogen response thereby contributing to increased proliferation in ER- breast tumors, particularly in the basal subgroup. A pilot survival study indicated that MYC- and E2F-activity may play a role in tamoxifen-resistance.
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Thorburn, Henrik. "Applying Bioinformatic Techniques to Identify Cold-associated Genes in Oat." Thesis, University of Skövde, Department of Computer Science, 2002. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-728.
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<p>As the interest in biological sequence analysis increases, more efficient techniques to sequence, map and analyse genome data are needed. One frequently used technique is EST sequencing, which has proven to be a fast and cheap method to extract genome data. An EST sequencing generates large numbers of low-quality sequences which have to be managed and analysed further.</p><p>Performing complete searches and finding guaranteed results are very time consuming. This dissertation project presents a method that can be used to perform rapid gene prediction of function-specific genes in EST data, as well as the results and an estimation of the accuracy of the method.</p><p>This dissertation project applies various methods and techniques on actual data, attempting to identify genes involved in cold-associative processes in plants. The presented method consists of three steps. First, a database with genes known to have cold-associated properties is assembled. These genes are extracted from other, already sequenced and analysed organisms. Secondly, this database is used to identify homologues in an unanalysed EST dataset, generating a candidate-list of cold-associated genes. Last, each of the identified candidate cold-associative genes are verified, both to estimate the accuracy of the rapid gene prediction and also to support the removal of candidates which are not cold-associative.</p><p>The method was applied to a previously unanalysed Avena sativa EST dataset, and was able to identify 135 candidate genes from approximately 9500 EST's. Out of these, 103 were verified as cold-associated genes.</p>
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Carr, Nicole. "Data Pooling to Identify Differentially Expressed Genes in Lung Cancer of Nonsmokers." University of Toledo Health Science Campus / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=mco1461881266.
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Saripalli, Chandrasekhar. "ANNOTATION OF WHITEFLY EXPRESSED SEQUENCE TAGS AND VALIDATION OF GENES WITH POTENTIAL SIGNIFICANCE TO BEGOMOVIRUS TRANSMISSION." Thesis, The University of Arizona, 2008. http://hdl.handle.net/10150/193455.
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The whitefly Bemisia tabaci (Gennadius) (Hemiptera) complex is the sole arthropod vector of the genus, Begomovirus (family, Geminiviridae), which causes debilitating diseases of plants, worldwide. Virus-vector specificity is conferred through co-evolved, whitefly vector-viral capsid protein-protein interactions. Membrane-bound receptors are thought to facilitate virion passage across the gut-hemolymph and hemolymph-salivary gland interfaces, and virion circulation is expected to elicit innate defense and stress-related proteins. Our goal was to select and validate genes involved in whitefly-mediated transmission. Whitefly expressed sequence tags (ESTs) from a previous study were re-annotated, taking advantage of newly available insect EST, UniGene, and Protein sequences. Six whitefly genes and transcripts, actin, cyclophilin, GBLP, GAPDH 3, knottin, and whitefly endosymbiont HSP60, representing three gene ontology (GO) categories, were analyzed using PCR or RT- PCR, respectively, followed by cloning and DNA sequencing. Analysis confirmed the presence of all six whitefly genes and five transcripts, with the knottin transcript being undetectable.
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Bebek, Gurkan. "Functional Characteristics of Cancer Driver Genes in Colorectal Cancer." Case Western Reserve University School of Graduate Studies / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=case1495012693440067.
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Mannino, Frank Vincent. "Site-to-site rate variation in protein coding genes." NCSU, 2006. http://www.lib.ncsu.edu/theses/available/etd-03272006-140300/.
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The ability to realistically model gene evolution improved dramatically with the rejection of the assumption that rates are constant across sites. Rate heterogeneity models allow for better estimates of parameters and site specific inferences such as the detection of positive selection. Recently developed models of codon evolution allow for both synonymous and nonsynonymous rates to vary independently according to discretized gamma distributions. I applied this model to mitochondrial genomes and concluded that synonymous rate variation is present in many genes, and is of appreciable magnitude relative to the amount of nonsynonymous heterogeneity. I then extending this model to allow for the two rates to vary according to a dependent bivariate distribution, permitting tests for the significance of correlation of rates within a gene. I present here the algorithm to discretize this bivariate distribution and the application of the model to many real data sets. Significant correlation between synonymous and nonsynonymous rates exists in roughly half of the data sets that I examined, and the correlation is typically positive. These data sets range over a wide group of taxa and genes, implying that the trend of correlation is general. Finally, I performed a thorough investigation of the statistical properties of using discretized gamma distributions to model rate variation, looking at the bias and variance in parameter estimates. These discretized distributions are common in modeling heterogeneity, but have weaknesses that must be well understood before making inferences.
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Kristinsson, Vilhelm Yngvi. "The effect of normalization methods on the identification of differentially expressed genes in microarray data." Thesis, University of Skövde, School of Humanities and Informatics, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-38.
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<p>In this thesis the effect of normalization methods on the identification of differentially expressed genes is investigated. A zebrafish microarray dataset called Swirl was used in this thesis work. First the Swirl dataset was extracted and visualized to view if the robust spline and print tip loess normalization methods are appropriate to normalize this dataset. The dataset was then normalized with the two normalization methods and the differentially expressed genes were identified with the LimmaGUI program. The results were then evaluated by investigating which genes overlap after applying different normalization methods and which ones are identified uniquely after applying the different methods. The results showed that after the normalization methods were applied the differentially expressed genes that were identified by the LimmaGUI program did differ to some extent but the difference was not considered to be major. Thus the main conclusion is that the choice of normalization method does not have a major effect on the resulting list of differentially expressed genes.</p>
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Bjarnadóttir, Þóra Kristín. "The Gene Repertoire of G protein-coupled Receptors : New Genes, Phylogeny, and Evolution." Doctoral thesis, Uppsala University, Department of Neuroscience, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-6627.
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<p>The superfamily of G protein-coupled receptors (GPCRs) is one of the largest protein families of mammalian genomes and can be divided into five main families; <i>Glutamate</i>, <i>Rhodopsin</i>, <i>Adhesion</i>, <i>Frizzled</i>, and <i>Secretin</i>. GPCRs participate in most major physiological functions, contributing to the fact that they are important targets in drug discovery. In paper I we mined the human and mouse genomes for new <i>Adhesion</i> GPCR genes. We found two new human genes (GPR133 and GPR144) and 17 mouse <i>Adhesion</i> genes, bringing the number up to 33 human and 31 mouse genes. In paper II we describe 53 new splice variants for human <i>Adhesion</i> receptors supported by expressed sequence tags (EST) data. 29 of these variants seem to code for functional proteins, several of which lack one or more functional domains in the N-termini. Lack of certain domains is likely to affect ligand binding or interaction with other proteins. Paper III describes the <i>Glutamate</i> GPCR in human, mouse, <i>Fugu</i>, and zebrafish. We gathered a total of 22 human, 79 mouse, 30 <i>Fugu</i>, and 32 zebrafish sequences and grouped these into eight clans using phylogenetic methods. The report provides an overview of the expansion or deletions among the different branches of the <i>Glutamate</i> receptor family. Paper IV focuses on the trace amine (TA) clan of <i>Rhodopsin</i> GPCRs. We identified 18 new rodent genes, 57 zebrafish genes, and eight <i>Fugu</i> genes belonging to the clan. Chromosomal mapping together with phylogenetic relationships suggests that the family arose through several mechanisms involving tetraploidisation, block duplications, and local duplication events. Paper V provides a comprehensive dataset of the GPCR superfamily of human and mouse containing 495 mouse and 400 human non-olfactory GPCRs. Phylogenetic analyses showed that 329 of the receptors are found in one-to-one orthologous pairs, whereas other receptors may have originated from species-specific expansions.</p>
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Ertel, Adam M. T̈ozeren Aydin. "Annotation and function of switch-like genes in health and disease /." Philadelphia, Pa. : Drexel University, 2008. http://hdl.handle.net/1860/2813.
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Davids, Muneera. "Single nucleotide polymorphism association studies of ABCA13 and ABHD11 genes and the bioinformatics analysis of the autism candidate genes localized on chromosome 7." University of the Western Cape, 2016. http://hdl.handle.net/11394/4977.
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Magister Scientiae - MSc<br>Autism, Aspergers Syndrome and Pervasive Developmental Delay-Not Otherwise Specified (PDD-NOS), among others, fall under an umbrella of disorders known as Autism Spectrum Disorder. Twin studies show that autism is a highly heritable disorder. More than 100 genes have been implicated in the aetiology of autism, each of which is involved in numerous biological processes and a variety of molecular interactions. William-Beuren syndrome is a multisystem developmental disorder caused by the deletion of contiguous genes at the 7q11.23 position. The aims of this study were (i) to genotype three SNPs (rs10279013, rs2293484 and rs17060) in the ABHD11 and ABCA13 genes, respectively, using Taqman® SNP Genotyping assays to detect association with autism in three distinct South African (SA) ethnic groups (Black, Caucasian and Mixed), and (ii) to ascertain common pathways or regulating transcription factors for genes on chromosome 7 that may attribute to it being an “autism hotspot”. Chapter 3 objectives were to identify potential candidate genes using STRING analysis and the Gene Cards database. The Taqman® study indicated significant association for SNP rs2293484 in the South African Caucasian group, as well as for the G allele in the South African Mixed group, where p<0.001. STRING analysis yielded 2 new candidate genes, FZD1 and FZD9. It was also found that the Wnt pathway in mammals plays a significant role in both ASDs and cancer, and there is a definite link between genes regulating cancer, and genes implicated in autism. The study provides evidence for not only the association of the investigated SNP in a South African population, but also provides evidence for the co-morbidity of several neurological and psychological disorders such as depression and bipolar disorder with autism.
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Gonzalez, Galarza Faviel. "The development of a database and bioinformatics applications for the investigation of immune genes." Thesis, University of Liverpool, 2011. http://livrepository.liverpool.ac.uk/4973/.
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The extensive allelic variability observed in several genes related to the immune response and its significance in transplantation, disease association studies and diversity in human populations has led the scientific community to analyse these variants among individuals. This thesis is focussed on the development of a database and software applications for the investigation of several immune genes and the frequencies of their corresponding alleles in worldwide human populations. The approach presented in this thesis includes the design of a relational database, a web interface, the design of models for data exchange and the development of online searching mechanisms for the analysis of allele, haplotype and genotype frequencies. At present, the database contains data from more than 1000 populations covering more than four million unrelated individuals. The repertory of datasets available in the database encompasses different polymorphic regions such as Human Leukocyte Antigens (HLA), Killer-cell Immunoglobulin-like Receptors (KIR), Major histocompatibility complex Class I chain-related (MIC) genes and a number of cytokine gene polymorphisms. The work presented in this document has been shown to be a valuable resource for the medical and scientific societies. Acting as a primary source for the consultation of immune gene frequencies in worldwide populations, the database has been widely used in a variety of contexts by scientists, including histocompatibility, immunology, epidemiology, pharmacogenetics and population genetics among many others. In the last year (August 2010 to August 2011), the website was accessed by 15,784 distinct users from 2,758 cities in 136 countries and has been cited in 168 peer-reviewed publications demonstrating its wide international use.
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Larsson, Pontus. "Computational Approaches to the Identification and Characterization of Non-Coding RNA Genes." Doctoral thesis, Uppsala universitet, Institutionen för cell- och molekylärbiologi, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-9518.
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Non-coding RNAs (ncRNAs) have emerged as highly diverse and powerful key players in the cell, the range of capabilities spanning from catalyzing essential processes in all living organisms, e.g. protein synthesis, to being highly specific regulators of gene expression. To fully understand the functional significance of ncRNAs, it is of critical importance to identify and characterize the repertoire of ncRNAs in the cell. Practically every genome-wide screen to identify ncRNAs has revealed large numbers of expressed ncRNAs and often identified species-specific ncRNA families of unknown function. Recent years' advancement in high-throughput sequencing techniques necessitates efficient and reliable methods for computational identification and annotation of genes. A major aim in the work underlying this thesis has been to develop and use computational tools for the identification and characterization of ncRNA genes. We used computational approaches in combination with experimental methods to study the ncRNA repertoire of the model organism Dictyostelium discoideum. We report ncRNA genes belonging to well-characterized gene families as well as previously unknown and potentially species-specific ncRNA families. The complicated task of de novo ncRNA gene prediction was successfully addressed by developing a method for nucleotide composition-based gene prediction using maximal-scoring partial sums and considering overlapping dinucleotides. We also report a substantial heterogeneity among human spliceosomal snRNAs. Northern blot analysis and cDNA cloning, as well as bioinformatical analysis of publicly available microarray data, revealed a large number of expressed snRNAs. In particular, U1 snRNA variants with several nucleotide substitutions that could potentially have dramatic effects on splice site recognition were identified. In conclusion, we have by using computational approaches combined with experimental analysis identified a rich and diverse ncRNA repertoire in the eukaryotes D. discoideum and Homo sapiens. The surprising diversity among the snRNAs in H. sapiens suggests a functional involvement in recognition of non-canonical introns and regulation of messenger RNA splicing.
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Duong, An Duy. "Investigation of Pantoea stewartii Quorum-Sensing Controlled Regulators and Genes Important for Infection of Corn." Diss., Virginia Tech, 2018. http://hdl.handle.net/10919/93208.
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Bacteria interact with their eukaryotic hosts using a variety of mechanisms that range from being beneficial to detrimental. This dissertation focuses on Pantoea stewartii subspecies stewartii (P. stewartii), an endosymbiont in the corn flea beetle gut that causes Stewart's wilt disease in corn. Gaining insights into the interactions occurring between this bacterial pathogen and its plant host may lead to informed intervention strategies. This phytopathogen uses quorum sensing (QS) to coordinate cell density-dependent gene expression and successfully colonize corn leading to wilt disease. Prior to the research presented in this dissertation, the QS master regulator EsaR was shown to regulate two major virulence factors of P. stewartii, capsule production and surface motility. However, the function and integration of EsaR downstream targets in P. stewartii were still largely undefined. Moreover, only a draft genome of a reference strain of P. stewartii was publicly available for researchers, limiting bioinformatics and genome-scale genetic approaches with the organism. The work described in this dissertation has now addressed these important issues.
The function of two EsaR direct targets, LrhA and RcsA, was explored (Chapter Two) and the existence of integration in the regulation between them was discovered (Chapters Two and Four). RcsA and LrhA are transcription factors controlling capsule production and surface motility in P. stewartii, respectively. In Chapter Two, the RcsA and LrhA regulons were investigated using RNA-Seq. This led to the discovery of a potential regulatory interaction between them that was confirmed by qRT-PCR and transcriptional gene fusion assays. The involvement of LrhA in surface motility and virulence was also established in this project. A direct interaction between LrhA and promoter of rcsA was defined in Chapter Four. Additional direct regulatory targets of LrhA were also identified.
A project to generate a complete assembly of the P. stewartii genome (Chapter Three) enabled more thorough genome-wide analysis and revealed the existence of a previous unknown 66-kb region in the P. stewartii genome believed to contain genes important for motility and virulence. In addition, completion of the genome sequence permitted genes for two distinctive Type III secretion systems, used for interactions with corn or the corn flea beetle, to be placed on two mega-plasmids. Furthermore, the complete genome sequence facilitated a Tn-Seq approach (Chapter Five). Tn-Seq is a potent tool used to identify bacterial genes required for certain environmental test conditions. This project is a pioneering utilization of a Tn-Seq analysis in planta to investigate genes important for colonization and survival of P. stewartii within its corn host. It was discovered that OmpC and Lon are important to in planta growth and OmpA plays a role in plant virulence.
In conclusion, these studies have broadened our understanding about the role of the QS regulon and other genes important for the pathogenesis of this phytopathogen. This knowledge may now be applied toward the development of future disease intervention strategies against P. stewartii and other wilt-disease causing plant pathogens.<br>PHD
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Quiroz, Alejandro. "Deciphering the Biological Mechanisms Driving the Phenotype of Interest." Thesis, Harvard University, 2012. http://dissertations.umi.com/gsas.harvard:10708.
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The two key concepts of Neo-Darwinian evolution theory are genotype and phenotype. Genotype is defined as the genetic constitution of an organism and phenotype refers to the observable characteristics of that organism. Schematically the relationship between genotype and phenotype can be settled as Genotype + Environment + Random Variation \(\underrightarrow{\text{yields}}\) Phenotype. This schematic representation has led to the fundamental problem of given the interactions of the genes and environment, up to what extent is possible to establish a relationship between gene structure and function to the phenotype (Weatherall, D. J., et. al., (2001)). Since R. A. Fisher establishing the basis of quantitative trait loci up to the work of Subramanian, et. al., (1995) gene set enrichment analysis, several statistical methods have been devoted to answer this question, some with more success and scientific repercussion than others. In this work we attempt to answer to this question by delineating the biological mechanisms driven by the genes that are characterize the differences and actions of the phenotypes of interest. Our contribution resides on two pillars: we present an alternative way to conceive gene expression measurements and the use of functional gene set annotation systems as guided prior knowledge of the biological mechanisms that drive the phenotype of interest. Based on these two pillars we propose a method to infer the Functional Network Inference and an alternative method to perform expression Quantitative Trait Loci analysis. (eQTL) From the Functional Network Inference method we are able to identify what mechanisms describe the behavior of most of the, there fore establishing its importance. The alternative method to perform eQTL analysis that we present, is more direct way to associated variations at a sequence level and the biological mechanisms it affects. With this proposal we attempt to address two important issues of traditional eQTL analysis: statistical power and biological implications.
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Samocha, Kaitlin E. "Modeling Rare Protein-Coding Variation to Identify Mutation-Intolerant Genes With Application to Disease." Thesis, Harvard University, 2016. http://nrs.harvard.edu/urn-3:HUL.InstRepos:33493508.
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Sequencing exomes—the 1% of the genome that codes for proteins—has increased the rate at which the genetic basis of a patient’s disease is determined. Unfortunately, when a patient does not carry a well-established pathogenic variant, it is extremely challenging to establish which of the tens of thousands of variants identified in that individual is contributing to their disease. In these situations, variants must be prioritized to make further investigation more manageable. In this thesis, we have focused on creating statistical frameworks and models to aid in the interpretation of rare variants and towards establishing gene-level metrics for variant prioritization.
We developed a sensitive and specific workflow to detect newly arising (de novo) variants from exome sequencing data of parent-child trios, and created a sequence-context based mutational. This mutational model was the basis of a rigorous statistical framework to evaluate the significance of de novo variant burden not only globally, but also per gene. When we applied this framework to de novo variants identified in patients with an autism spectrum disorder, we found a global excess of de novo loss-of-function variants as well as two genes that harbored significantly more de novo loss-of-function variants than expected.
We also used the mutational model to predict the expected number of rare (minor allele frequency < 0.1%) variants in exome sequencing datasets of reference individuals. We found a significant depletion of missense and loss-of-function variants in a subset of genes, indicating that these genes are under strong evolutionary constraint. Specifically, we identified 3,230 genes that are intolerant of loss-of-function variation and that set of genes is enriched for established dominant and haploinsufficient disease genes. Similarly, we searched for regions within genes that were intolerant of missense variation. The most missense depleted 15% of the exome contains 83% of reported pathogenic variants found in haploinsufficient disease genes that cause severe disease. Additionally, both gene-level and region-level constraint metrics highlight a set of de novo variants from patients with a neurodevelopmental disorder that are more likely to be pathogenic, supporting the utility of these metrics when interpreting rare variants within the context of disease.<br>Medical Sciences
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McSweeny, Andrew J. "Identification of Candidate Genes within Blood Pressure QTL Containing Regions Using Gene Expression Data." University of Toledo Health Science Campus / OhioLINK, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=mco1212501779.
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Hall, Andrew Brantley. "Identification and Characterization of Y Chromosome and M Locus Genes in Anopheles and Aedes Mosquitoes Using the Chromosome Quotient Method." Diss., Virginia Tech, 2016. http://hdl.handle.net/10919/78883.
Full textAbstract:
In mosquitoes, sex determination is initiated by a dominant male-determining factor located on the Y chromosome in Anopheles mosquitoes or in a small Y-like region called the M locus in Aedes mosquitoes. Before my research, not a single gene from the Anopheles Y or Aedes M locus had ever been discovered.
During the course of my undergraduate research in the Tu lab, I developed the chromosome quotient (CQ) method which identifies Y chromosome/M locus sequences by comparing the ratio of alignments from separate pools of female and male Illumina sequencing data. The focus of my dissertation is using the CQ method to identify potential male-determining factors in Aedes and Anopheles mosquitoes.
First, we identified a novel gene tightly-linked to the M locus in Aedes aegypti called myo-sex. Myo-sex encodes a myosin heavy chain protein that is highly expressed in the pupa and adult male. Myo-sex is generally only found in males, but can sporadically be found in females due to a rare recombination. The fact that myo-sex can be found in females combined with a lack of early-embryonic expression suggests that myo-sex is not the male-determining factor.
Next, we identified a gene in Aedes aegypti, Nix, which appeared to be persistently linked to the M locus and was expressed in the early embryo. Nix shows distant similarity at the amino acid level to Transformer2, a gene involved in the sex determination pathway of Drosophila melanogaster. Nix knockout with CRISPR/Cas9 resulted in feminization of genetic males and the production of the female isoforms of doublesex and fruitless, two key regulators of downstream sexual differentiation. Ectopic expression of Nix resulted in masculinization of genetic females. Based on these results, we concluded that Nix is a male-determining factor in Aedes aegypti.
We also characterized large portions of the Anopheles gambiae Y chromosome using PacBio sequencing and the CQ method. We discovered that 92.3 percent of predicted Y sequences fell into two classes, the zanzibar amplified region (ZAR) and the satellite amplified region (SAR). This analysis fills in a large piece of the Anopheles gambiae genome missing since 2002.<br>Ph. D.