Dissertations / Theses on the topic 'Gene-For-Gene interaction'
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1
Assareh, Amin. "OPTIMIZING DECISION TREE ENSEMBLES FOR GENE-GENE INTERACTION DETECTION." Kent State University / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=kent1353971575.
2
Bendahmane, Abdelhafid. "Analysis of a gene-for-gene interaction associated with Rx-mediated resistance to potato virus X." Thesis, University of East Anglia, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.389350.
3
Aleknonytė-Resch, Milda [Verfasser], Astrid [Akademischer Betreuer] Dempfle, and Hinrich [Gutachter] Schulenburg. "The Validity and Statistical Power of the Case-Only Study Design for Interaction Analysis : Gene-Gene Interaction and the Role of Genotype Imputation in Gene-Environment Interaction / Milda Aleknonytė-Resch ; Gutachter: Hinrich Schulenburg ; Betreuer: Astrid Dempfle." Kiel : Universitätsbibliothek Kiel, 2021. http://d-nb.info/1229916962/34.
4
Elisson, Hanna. "Uncertainty in Genetic Mapping and Gene Interaction for Diabetes in Rats." Thesis, Uppsala University, Department of Mathematics, 2000. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-122559.
5
MacGowan, Alice Laura. "Embryonic retinoid deficiency and congenital malformation : evidence for gene-environment interaction." Thesis, University of Sheffield, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.398657.
6
Thi, Cam Thach Doan. "A GRAPHICAL USER INTERFACE FOR LARGE-SCALE GENE EXPRESSION ANALYSIS." Thesis, Högskolan i Borås, Institutionen Handels- och IT-högskolan, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:hb:diva-20870.
Abstract:
Recently, the whole-genome expression analysis – which is analyzing most or all of the genes in biological systems, and is a rich and powerful way to discover gene pathway - has become increasingly affordable because of the increasing amount of microarray data available in public databases. Additionally, due to the enormously available information content in these repositories, researchers have to spend large amount of time to decide on the right information to proceed. There should be an application to assist biological researchers reducing the time in finding good data sets to analyze. In this project, a thorough study in HCI, Information Visualization, interaction design and development methodologies are carried out in order to build a web-based user interface that enables searching and browsing gene expression data and their correlation (web-based). Findings from literature review are applied to create a web-based user interface in large-gene expression analysis. Then, a survey is carried out to collect and analyze pilot users‟ feedback. The questionnaire shows that the users are very interested in using the system and they would like to spend more time interacting with it. They give positive feedbacks about interactive data visualization in the website help them to save time on viewing, navigating and interpreting complicated data. Besides, it is easy to navigate and learn how to use the system to achieve interesting findings in biology. The questionnaire shows that the author is successful in applying findings from literature review to build the website. Besides, from the results there are suggestions for improvement such as the flexibility in the website by automatically recognizing the alias gene names from different databases, filling-in gene symbols using first few characters, narrowing down a search to a particular species such as human or rat, etc.Program: Masterutbildning i Informatik
7
Korkmaz, Gulberal Kircicegi Yoksul. "Mining Microarray Data For Biologically Important Gene Sets." Phd thesis, METU, 2012. http://etd.lib.metu.edu.tr/upload/12614266/index.pdf.
Abstract:
Microarray technology enables researchers to measure the expression levels of thousands
of genes simultaneously to understand relationships between genes, extract
pathways, and in general understand a diverse amount of biological processes such
as diseases and cell cycles. While microarrays provide the great opportunity of revealing
information about biological processes, it is a challenging task to mine the huge
amount of information contained in the microarray datasets. Generally, since an accurate
model for the data is missing, first a clustering algorithm is applied and then the
resulting clusters are examined manually to find genes that are related with the biological
process under inspection. We need automated methods for this analysis which
can be used to eliminate unrelated genes from data and mine for biologically important
genes. Here, we introduce a general methodology which makes use of traditional
clustering algorithms and involves integration of the two main sources of biological
information, Gene Ontology and interaction networks, with microarray data for eliminating
unrelated information and find a clustering result containing only genes related
with a given biological process. We applied our methodology successfully on a number
of different cases and on different organisms. We assessed the results with Gene Set Enrichment Analysis method and showed that our final clusters are highly enriched.
We also analyzed the results manually and found that most of the genes that are in
the final clusters are actually related with the biological process under inspection.
8
Piqueras, Matias. "HERITABILITY FOR SOCIAL TRUST ACROSS SOCIOECONOMIC STATUS: : Is There a Gene-Environment Interaction?" Thesis, Uppsala universitet, Statsvetenskapliga institutionen, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-394876.
Abstract:
In political science literature, the development of social trust is often explained in terms of the influence of different environmental factors, socioeconomic status (SES) being one of the most important. Yet, even though there is empirical support of a genetic component in the expression of social trust, less is known about its interaction with environmental factors. The present study aims to explore heritability of social trust across socioeconomic status using a twin-design that tests potential gene-environment (GxE) interactions. Moreover, the study explicitly tests the hypothesis that different levels of SES may moderate the influence of genetic and environmental effects on social trust. Data comes from the Swedish Twin Registry and consist of 1535 twin pairs born between 1943–1959. Social trust was measured through self-report on a scale of 1–10. Socioeconomic status was assessed as a dichotomized variable of high/low SES, determined on the basis of the father’s occupation during the twin’s childhood or adolescence. To test whether SES interacted with genetic and environmental effects for social trust, I used structural equation modeling (SEM). Results from the best fitting model show that social trust has a significant genetic component, with an estimated heritability of 0.41 in low SES and 0.33 in high SES. Results showed no evidence for a significant difference in heritability between low and high SES. Accordingly, it can be concluded that the results of the study do not support the hypothesis that SES moderate the influence of genetic effects on social trust.
9
Cai, Yu. "Molecular Characterization of the mop2, a Gene Required for Epigenetic Silencing." Diss., The University of Arizona, 2006. http://hdl.handle.net/10150/195361.
Abstract:
The mop2 gene is required for epigenetic silencing; it was originally defined as a mutation, Mop2-1, which when dominant prevented paramutation at b1. Paramutation is an allele communication that causes a mitotically and meiotically heritable change in gene expression. Mop2-1 was subsequently shown to be involved in maintaining the silenced paramutant state and to prevent dsRNA-mediated transcriptional gene silencing (activities revealed only when the mutation is homozygous). Understanding the product encoded by mop2 will help dissect the underlying mechanisms involved in paramutation and dsRNA-mediated transcriptional silencing. This dissertation describes map-based cloning and candidate gene approaches directed toward the eventual goal of identification of mop2.Initial mapping of mop2 placed it within a region delineated by the markers umc1823 and eks1. On the maize physical map this region contains 21 BAC (Bacteria Artificial Chromosome) clones, representing 2.9 Mb. Skim sequencing identified additional markers for mapping and revealed the gene content. Extensive candidate gene examinations, including gene sequencing, expression profiling with microarrays and RT-PCR, and complementation tests with mutant alleles did not identify any of the four chromatin and RNAi-related genes as mop2.The new markers developed from the skim sequence enabled further mapping and molecular genotyping, which revealed that the Mop2-1 mutation was unstable. Approxi¬mately 10% of phenotypic heterozygous plants were actually genotypic homozygous. Further mapping using only Mop2-1 homozygous plants reduced the mop2 interval to a region of nine BACs, containing 57 genes.The mop2 region is highly syntenic to a rice region of 1.25 Mb on chromosome 4. The gene alignment and repetitive sequence analyses between the syntenic regions in these two species revealed both syntenic and non-syntenic blocks of sequences. Analyses suggested several potential mechanisms for the collinearity breakage, including, but not limited to, tandem duplications of genes in one species but not the other and the presence of gene fragments in maize, but not in rice.The research described herein provides the basis for continued efforts to clone mop2. Fine-structure mapping with new markers and a larger population, as well as candidate gene sequencing in the Mop2-1 BAC library, should be pursued to clone mop2.
10
Mietzsch, Mario [Verfasser]. "Adeno-Associated Virus Vectors for Gene Therapy : From Scalable Production Systems via Serotype-Specific Glycan Interaction Patterns to Gene Transfer Applications / Mario Mietzsch." Berlin : Freie Universität Berlin, 2014. http://d-nb.info/1055942203/34.
11
Sadie, Hanel. "Interaction of SF-1 and Nur77 proteins from a gonadotrope cell line with the promoter of the GnRH receptor gene : implications for gene regulation." Thesis, Stellenbosch : Stellenbosch University, 2001. http://hdl.handle.net/10019.1/52307.
Abstract:
Thesis (MSc)--Stellenbosch University, 2001.ENGLISH ABSTRACT: The regulation of gonadotropin releasing hormone (GnRH) receptor numbers in the pituitary is a crucial control point in reproduction. Pituitary sensitivity to GnRH can be directly correlated with GnRH receptor levels, which can be regulated at transcriptional and post-transcriptional level. The proximal promoter of the mouse GnRH receptor gene contains two cis elements bearing the consensus sequence for a Steroidogenic Factor-l (SF -1) binding site. The distal site has previously been shown to be involved in basal and tissue-specific transcriptional regulation, whereas the function of the proximal site was not established. SF-I, a member of the nuclear receptor superfamily of transcription factors, is involved in the transcriptional regulation of a large number of genes involved in steroidogenesis and reproduction. The consensus SF-I binding site can serve as a binding site for several members of the nuclear receptor superfamily. The aim of this study was to investigate the binding of SF-I protein from the aT3-1 gonadotrope cell line to the two putative SF-I binding sites in the mouse GnRH receptor promoter in vitro, in order to provide supporting evidence for their functional roles in GnRH receptor gene regulation. It was shown by Western blotting that SF-I and Nur77, another nuclear receptor transcription factor, are both expressed in aT3-1 cells, in a manner that is influenced by cell culture conditions. Gel mobility shift assays using specific antibodies showed that both SF-I and Nur77 protein in aT3-1 nuclear extracts bind to both sites in a mutually exclusive fashion. As shown by competition assays using mutated versions of the two sites, Nur77 protein had different base pair requirements than that of SF-I protein for binding to the sites. Additionally, SF-I mRNA was shown by Northern blotting to be increased in aT3-1 cells in response to stimulation of the Protein Kinase A (PKA) pathway by forskolin. These results highlight unexpected degeneracy in so-called "consensus" nuclear receptor binding sites. Furthermore, since Nur77 protein is involved in the stress response of the hypothalamic-pituitary-adrenal (HPA) axis, the unexpected presence of Nur77 protein in a gonadotrope cell line has potentially important implications for cross-talk between the HPA and hypothalamic-pituitary-gonadal (HPG) axes.
AFRIKAANSE OPSOMMING: Daar bestaan 'n direkte verband tussen pituïtêre sensitiwiteit vir gonadotropien-vrystellingshormoon (GnRH) en GnRH-reseptorvlakke Die regulering van GnRH-reseptorvlakke op transkripsionele en post-transkripsionele vlak in die pituïtêre klier is belangrik by die beheer van voortplantingsfunksies. Die proksimale promotor van die GnRH-reseptorgeen in die muis bevat twee cis elemente met die konsensus volgorde vir 'n Steroidogenic Factor-l (SF-I) bindingsetel. Die distale element is betrokke by basale en weefsel-spesifieke transkripsionele regulering, maar die funksie van die proksimale element is nog nie vasgestel nie. SF-1 is 'n lid van die superfamilie van selkernreseptore en is betrokke by die transkripsionele regulering van gene verantwoordelik vir steroïedogenese en voortplanting. Die konsensus SF-I bindingsvolgorde kan dien as bindingsetel vir verskeie selkernreseptore. Ten einde 'n beter insig ten opsigte van die regulering van die GnRH reseptorgeen te verkry, is ondersoek ingestel na die binding van SF-I-proteïen, afkomstig van die aT3-1 pituïtêre gonadotroopsellyn, aan die twee moontlike SF-l bindingsetels in die GnRH-reseptor promotor, in vitro. Die Western-klad metode het getoon dat beide SF-l en Nur77, 'n ander selkernreseptor-transkripsiefaktor, in die aT3-1 sellyn uitgedruk word. Die uitdrukking is afhanklik van selkultuurtoestande. Elektroforetiese mobiliteitsessais met spesifieke antiliggame het getoon dat SF-l en Nur77 proteïene in aT3-1 selkernproteïenekstraksies eksklusief aan beide bindingsetels bind. Nur77 proteïen benodig ander basispare as SF-l proteïen om aan die bindingsetels te bind. Hierdie resultate dui op onverwagse degenerasie in sogenaamde "konsensus" selkernreseptor-bindingsvolgordes. Die Northern-kladmetode het ook getoon dat SF-l mRNA vlakke in aT3-1 selle styg wanneer die proteïenkinase A (PKA) pad gestimuleer word met forskolin. Aangesien Nur77 proteïen betrokke is by die stres-respons van die hipotalamus-pituïtêre klier-adrenale (HP A) aksis, hou die onverwagse teenwoordigheid van Nur77 proteïen in 'n gonadotroop-sellyn potensieel belangrike inplikasies in vir kommunikasie tussen die HPA-aksis en die hipotalamus-pituïtêre klier-gonadale (HPG) aksis.
12
Dafas, Panagiotis A. "Frequency rule mining for effective protein-protein interaction inference from gene expression and protein structures." Thesis, City University London, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.492255.
Abstract:
The experimental measurement of gene expression levels has produced preliminary results on the regulation, pathways and networks of genes in cells. Furthermore, the number of available three-dimensional folded structures of proteins increases on a daily basis. The ultimate aim of both genomics and proteomics froni the perspective of bioinformatics, is to map out all the circuits of energy and information processing in life by terms of molecular interactions in a system~tic way with minimal human intervention. In this thesis we propose a new rule mining framework for ill silico inference of protein-protein interactions and an effective class of techniques that identify domain-domain interactions from multiple domain protein structures. The above two approaches allow molecular biologists to use both gene expression data and three dimensional folded protein structures to efficiently predict or validate potential protein-protein interactions. A novel temporal rule mining technique is used to infer rules that relate local expression patterns across a set of genes. The set of these rules is associated to a set of potential interacting pairs of proteins. . I Probable protein-protein interactions can be validated against a network of protein domain interactions that are computed by considering interacting domains in known multiple domain protein structures. We introduce efficient algorithms that can effectively identify protein domain-domain interactions in multiple protein domain structures which are solved and publicly available. To analyse the vast amount of interactions between all the protein domains classified to superf~milies we propose a new graphtheoretic measure which is able to rank protein superfamilies by incorporating information about the topology of the whole network. To summarise, the work in this thesis consists of a new temporal rule mining framework applied .' to gene expression data analysis and furthermore, a novel class of algorithms that effectively identify ' domain-domain interactions from known protein structures.
13
Singh, Lovepreet. "Characterization of new sources and superior gene combinations for durable resistance to leaf rust in barley." Thesis, The University of Sydney, 2021. https://hdl.handle.net/2123/24783.
Abstract:
One hundred fourteen barley lines were screened with diverse pathotypes (pts) of Puccinia hordei in the greenhouse (GH) and field to characterize resistance. The GH tests revealed the presence of all stage resistance (ASR) genes Rph1, Rph2, Rph3, Rph12 and Rph19 either individually or in combination, whereas field tests revealed the presence of adult plant resistance (APR) in 74.5% of the test lines. Molecular markers linked to known genes demonstrated presence of Rph15 (3 lines), Rph20 (5 lines), Rph23 (8 lines), Rph24 (19 lines), and the combinations Rph20+Rph23 or Rph20+Rph24 or Rph23+Rph24 (8 lines). The remaining 49 resistant lines probably carry new uncharacterized ASR and/or APR genes. Genome wide association studies (GWAS) detected a total of 15 QTL that were strongly associated with markers. Among them, QTL MTA8_R2 (chromosome 7H) has the largest effect in controlling leaf rust.
Temperature and interaction studies revealed that the expression of Rph1.a, Rph2.b, Rph4.d and Rph10.o altered with temperature, whereas the expression of genes Rph3.c, Rph5.e, Rph6.f, Rph12 (9.z), Rph13.x and Rph15.ad was concluded to be non-sensitive to temperature. Amongst a selection of lines carrying Rph20 (Flagship), Rph23 (Yerong) and Rph24 (ND24260), only seedlings of Flagship showed improved resistance with lower temperatures against pt 200 P-, whereas seedlings of Yerong and ND24260 showed high IT at all three temperatures with pt 5457 P+. When RphASR genes were combined with the APR gene Rph20, combinations Rph2.b+Rph20, Rph4.d+Rph20, Rph5.e+Rph20, Rph9.i+Rph20 and Rph15.ad+Rph20 showed an enhanced level of resistance. Seedlings carrying the combination Rph5.e+Rph20 remained resistant even when challenged with the Rph5.e-virulent pt 220 P+ + Rph13, suggesting a residual or ghost effect of Rph5.e when present in combination with Rph20. This study was the first to demonstrate that several ASR Rph genes interact with the APR gene Rph20 in an additive manner.
14
Ackerman-Alexeeff, Stacey Elizabeth. "Measurement error in environmental exposures: Statistical implications for spatial air pollution models and gene environment interaction tests." Thesis, Harvard University, 2013. http://dissertations.umi.com/gsas.harvard:11077.
Abstract:
Measurement error is an important issue in studies of environmental epidemiology. We considered the effects of measurement error in environmental covariates in several important settings affecting current public health research. Throughout this dissertation, we investigate the impacts of measurement error and consider statistical methodology to fix that error.
15
Pelliccia, M. "STRATEGIES FOR ENHANCING VIRAL GENE TRANSFER AND THE THERMOSTABILITY OF VIRAL VECTORS IN VACCINE APPLICATIONS." Doctoral thesis, Università degli Studi di Milano, 2015. http://hdl.handle.net/2434/265518.
Abstract:
At the most basic level viruses are biological nano-containers constituted by genetic material enclosed in a protein shell, capsid. A peculiar feature of viruses, both bacterial and some eukaryotic viruses, lies in the high packaging density of the genome in order to fit itself in the small capsid and hence the high internal osmotic pressure. Virus is a relatively stable particle equipped with fascinating mechanical properties of the capsid that are crucial for the virus lifecycle. Viruses have only one purpose: infect a host cell for reproducing themselves in order to generate new viral progeny (Roos et al. 2007). Therefore, the first and foremost consideration arising from the concept of virus reflects its pathogenesis and virulence that can ultimately result in many important infectious diseases such as common cold, influenza, hepatitis, rabies, measles, cancer and AIDS. As a consequence, pathogenic viruses represent a heavy hurdle for the global health and there is a strong need for developing robust strategies such as vaccines or antiviral drugs against virus infections (Baram- Pinto et al. 2010). On the other hand, viruses in the course of evolution have become efficient specialized gene delivery agents. Therefore they represent powerful tools in biomedicine for gene therapy and vaccine purposes (Schaffer et al. 2008). For successful gene therapy and immunization programs, the efficiency and stability of viral vectors are fundamental aspects (Jorio et al. 2006).
To address this challenge, in the present research project we have investigated the interaction between viruses and nanomaterials. In the last years materials on the nanoscale for their unique properties have provided a broad range of potential biomedical uses (Verma et al. 2008) and for that reason we decided to explore their application with viruses. More specifically, we have examined three types of sulfonate- functionalized gold nanoparticles (AuNPs), namely, MUS:OT, MUS and MUS:brOT NPs, which are less than 5 nm in size, negatively charged and poorly cytotoxic (Verma et al. 2008). The NPs are coated with self-assembled monolayer (SAM) of thiolated organic molecules and one of the ligand is a sulfonated molecule, MUS (Verma et al. 2008). The MUS ligand itself was tested in our experiments as well. As virus models we focused on human recombinant adenovirus type 5 (Ad), one of the most promising viral vector as vaccine and gene therapy carrier and two picornaviruses of the genus enterovirus, namely, EV1 and CVB3, important human pathogens associated with several infectious diseases (e.g. myocarditis, aseptic meningitis, encephalitis, paralysis)(Kossila et al. 2002)(Marjomäki et al. 2014a). In spite of their medical impact, there are no therapeutic treatments available against picornavirus infections and the only vaccine products are against three types of poliovirus and hepatitis A virus (Merilahti et al. 2012).
Two sets of experiments were carried out: (1) Short-term incubation of Ad with nanomaterials for 1 h at 37°C prior
transducing HeLa cells or before in vivo administration in zebrafish and mice. The results demonstrated that Ad shortly pre-treated with nanomaterials showed a significant increase in the gene expression in vitro and in vivo The NPs’enhanced adenovirus transduction aims to reduce Ad vector doses in vivo thereby minimizing the adverse reactions of the immune response due to high vector dosage; (2) Long-term thermostabilization studies of Ad, EV1 and CVB3 in vitro in the presence and in the absence of our nanomaterials and other substances such as sugars (sucrose, glucose, glycerol) and Polyethylene glycol (PEG) molecules at 37°C or room temperature for extensive periods of time. Our results showed the capability of the nanomaterials and sucrose to increase substantially the heat stability of the viruses. In order to elucidate the thermal inactivation mechanism of viral particles and the stabilizing effect provided by some compounds on viruses we set out to formulate an analytical theory. This line of research fits in the context of developing more thermo-stable viral vector preparations for vaccine purposes that do not require the maintenance of the challenging cold chain system in order to preserve the effectiveness of viral vaccines during the storage, shipment and administration to the patients and hence to ensure the success of global immunization programs (Alcock et al. 2010).
16
Pizzato, Massimo. "Retroviral vectors for gene therapy : characterisation of vector particle-cell interaction and development of novel packaging cell lines." Thesis, Institute of Cancer Research (University Of London), 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.313365.
17
Rubin, Joel Edward. "Locus control region activity by 5'HS3 requires a functional interaction with ß-globin gene regulatory elements, identification of effective ß/[gamma]-globin minigenes for gene therapy of the ß-chain hemoglobinopathies." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape2/PQDD_0025/MQ50431.pdf.
18
Armando, Marco. "Psychotic like experiences and 22q11 microdeletion syndrome : two possible models for the investigation of gene-enviroment interaction in psychotic onset." Thesis, University of Birmingham, 2013. http://etheses.bham.ac.uk//id/eprint/3940/.
Abstract:
Psychotic disorders can be defined as disorders of adaptation to social context. Although heritability is often emphasized, onset must be considered as the end-point of a pathway which involves: 1) genetic heritability; 2) environmental factors; 3) psychopathological factors. Therefore, the current challenge consists in combining different scientific fields aiming at a deeper comprehension of psychotic disorders. Taking off these considerations, this thesis will present research conducted in Rome (Children Hospital Bambino Gesù) and in Birmingham (Department of Psychology, University of Birmingham) by the Author during his PhD. These research are focused on two possible models which can help to better understand the role played by gene/enviroment interaction in the pathogenesis of psychotic disorders. The first model concerns the so-called psychotic-like experiences and is therefore situated in the sphere of the psychopathological factors involved in the pathway to psychosis. The second model concerns 22q11 microdeletion syndrome, a genetic syndrome with high prevalence of psychotic disorders. The thesis starts with a comprehensive review of these topics. Subsequently, the main findings of the research conducted during the PhD will be described and analyzed. Implications are explored, in terms of clinical practice, aetiological pathways, potential treatments and intervention strategies.
19
Mota, Lúcio Flávio Macêdo. "Estimation of genotype-environment interaction using genomic reaction norm and analysis of gene network for reproductive traits in Nellore cattle /." Jaboticabal, 2019. http://hdl.handle.net/11449/181612.
Abstract:
Orientador: Lucia Galvão de AlbuquerqueBanca: Mário Luiz Santana Júnior
Banca: Fernando Sebastian Baldi Rey
Banca: Ana Fabrícia Braga Magalhães
Banca: Roberto Carvalheiro
Abstract: Genotype-environment (GxE) interactions could be an important source of variation in reproductive traits with a striking effect on the onset of animal puberty. Thus, the objectives of the present study were: i) to assess the GxE interaction in Nellore sexual precocity indicator traits under different environmental conditions (EC) and ii) to identify, genomic regions and biological pathways associated to Nellore sexual precocity indicator traits and to investigate whether their effects changes according to EC levels. Phenotypic records for age at first calving (AFC), heifer early pregnancy (HP), heifer rebreeding (HR) and scrotal circumference (SC) were collected on 128,994; 85,339; 90,831 and 151,053 animals, respectively. From those, 1800 heifers, 3050 young bulls, and 800 sires were genotyped with BovineHD BeadChip. A reaction norm model was used to estimate the animal's response to environmental conditions changes. To assess the predictive ability the younger scheme and environment-specific scheme were used. For genome-wide scan, the SNP effects for reproductive traits were estimated in three EC levels: Low (EC = -3.0), Medium (EC = 0.0) and High (EC = 3.0) using a linear transformation of the genomic breeding values. The pleiotropic regions associated to reproductive traits (AFC, SC, HP and HR) in three EC levels, were identified using the statistical combination of the single-trait GWAS results and considered significant when -log10(p-valor)>6.0. The inclusion of genomic... (Complete abstract click electronic access below)
Resumo: A interação genótipo-ambiente (GxE) pode ser uma importante fonte de variação em características reprodutivas com um efeito notável no início da puberdade animal. Desta forma, os objetivos do presente estudo foram: i) Avaliar a interação GxE em características indicadores de precocidade sexual em animais da raça Nelore em diferentes condições ambientais (EC) e ii) identificar regiões genômicas e vias biológicas associadas a características indicadores de precocidade sexual e verificar se seus efeitos mudam de acordo com os níveis de EC. Informações fenotípicas para idade ao primeiro parto (AFC), ocorrência de prenhez precoce (HP), reconcepção de novilhas (HR) e perímetro escrotal (SC), foram coletados em 128.994, 85.339, 90.831 e 151.053 animais, respectivamente. Destes, 1800 novilhas, 3050 touros jovens e 800 touros foram genotipados com BovineHD BeadChip. Um modelo de norma de reação foi usado para estimar a resposta do animal às mudanças nas condições ambientais. Para avaliar a capacidade preditiva, foram utilizados os esquemas de validação em animais jovens e em ambiente específico. Para varredura genômica ampla os efeitos dos marcadores SNP para as características reprodutivas foram estimados em três níveis de EC Baixo (EC = -3.0), Médio (EC = 0.0) e Alto (EC = 3.0) usando uma transformação linear dos valores genômicos genéticos. As regiões pleiotrópicas associadas com características reprodutivas (AFC, SC, HP e HR) em três EC foram identificadas utilizando a combinação ... (Resumo completo, clicar acesso eletrônico abaixo)
Doutor
20
Burbanks, Samuel IV. "Gene-Culture Interaction and its Effect on Cognitive Flexibility Among People of African and European Descent: Providing a Rational for Culturally Centered Pedagogy." University of Cincinnati / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1511881054307915.
21
Du, Shenxiu [Verfasser]. "Functional Characterizations of the Reciprocal Interaction of the Circadian Clock gene Time for coffee (TIC) with Stress and Energy in Arabidopsis / Shenxiu Du." Bonn : Universitäts- und Landesbibliothek Bonn, 2017. http://d-nb.info/1130704610/34.
22
Martin, Isabelle. "Étude du déterminisme moléculaire des Interactions compatibles et incompatibles Vitis vinifera-Nepovirus-Nicotiana occidentalis (InViNNo)." Thesis, Strasbourg, 2018. http://www.theses.fr/2018STRAJ102.
Abstract:
Le Grapevine fanleaf virus (genre Nepovirus) est l'agent principal du court-noué de la vigne. Il induit des symptômes très variables. Ce travail présente une étude mécanistique de la symptomatologie du GFLV sur un hôte herbacé et sur l'hôte d’intérêt agronomique. Par détection de marqueurs biochimiques et moléculaires j'ai montré que le GFLV-F13 induit une réponse hypersensible (HR) sur N. occidentalis et une restriction partielle du virus. J'ai identifié puis cartographié le déterminant viral de cette HR en utilisant des réassortants, des recombinants et des variants naturels du virus. Sur vigne, sur un dispositif expérimental unique en son genre, j'ai mené une approche sans a priori d’étude transcriptomique par RNA-Seq. J'ai comparé des vignes du cépage gewurztraminer mono-infectées par une souche sévère induisant des symptômes de rabougrissement et par une souche plus modérée. 1 023 gènes sont spécifiquement dérégulés par la souche sévère parmi lesquels des gènes impliqués dans la régulation de la HR. Ce résultat permet de proposer pour la première fois qu'une HR pourrait être mise en place dans la vigne en réponse à une infection viraleGrapevine fanleaf virus (genus Nepovirus) the causative agent of fanleaf degeneration, induces variable symptoms. This manuscript presents a mechanistic study of GFLV symptomatology on both an herbaceous model plant and an agronomically important crop plant.On N. occidentalis, I demonstrated that GFLV-F13 induces a reaction exhibiting hallmarks of a hypersensitive response (HR), partially restricting virus spread. Using reassortants, recombinants and natural variants of the virus, I could identify and map the viral determinant of this HR. On grapevine, I took advantage of a unique experimental set-up and used RNA-Seq to compare the transcriptoms of Gewurztraminer plants infected with two different GFLV strains, one of which induced stunting symptoms and the other mild symptoms. 1,023 genes among which genes involved in the regulation of HR, were specifically regulated by the more severe strain This is the first hint of a HR taking place in grapevine in response to a virus infection
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Louet, Clémentine. "Analyses évolutive et moléculaire des déterminants génétiques impliqués dans l’interaction entre l’agent de la rouille du peuplier et son hôte." Electronic Thesis or Diss., Université de Lorraine, 2021. http://www.theses.fr/2021LORR0264.
Abstract:
Melampsora larici-populina (Basidiomycète, Pucciniales) est un champignon biotrophe obligatoire qui infecte successivement deux hôtes, le peuplier et le mélèze, et qui produit cinq types de spores au cours de son cycle de vie. Ce dernier est l’agent causal de la rouille du peuplier, la principale contrainte sanitaire dans les peupleraies européennes. Un des objectifs de l’UMR Interactions Arbres/Microorganismes est de caractériser les déterminants moléculaires impliqués dans l’interaction entre le peuplier et M. larici-populina et d’étudier leur évolution. Cette thèse, reposant sur la mobilisation d’expertises diversifiées allant de la génétique des populations à la biochimie des protéines, a permis de mener à bien trois projets de recherche. Premièrement, une étude, alliant des approches moléculaires et la génétique des populations, a identifié une association significative entre l’évolution du gène d’avirulence candidat AvrMlp7 et le contournement de la résistance qualitative RMlp7 du peuplier. L’association et la coexistence de deux altérations au locus candidat confèrent la virulence, fournissant pour la première fois des déterminants génétiques expliquant un évènement de contournement chez cet agent pathogène. Deuxièmement, un effort a porté sur le développement d’approches fonctionnelles sur ce pathosystème. L’expression de l’effecteur candidat AvrMlp7 dans le système hétérologue Nicotiana benthamiana a notamment permis de mettre en évidence sa localisation chloroplastique, suggérant un rôle potentiel dans la modulation de fonctions associées à cet organite. Le caractère d’avirulence de ce gène candidat reste néanmoins encore à démontrer fonctionnellement. Troisièmement, sur la base de données transcriptomiques, des familles de facteurs de transcription ont pu être associées à des transitions biologiques spécifiques du cycle de vie de M. larici-populina. Ainsi, la famille des cold-shock protéines (CSP) est plus particulièrement associée à la levée de dormance et à la production de basides et de basidiospores à partir de télies, à la sortie de l’hiver. Cette étude identifie pour la première fois des acteurs régulant des processus fondamentaux de la biologie des Pucciniales au-delà des seuls processus infectieux. De manière générale, les travaux réalisés dans cette thèse ouvrent de nouvelles perspectives quant à la plus-value d’associer plusieurs disciplines pour améliorer notre compréhension des interactions hôtes-pathogènesMelampsora larici-populina (Basidiomycete, Pucciniales) is an obligate biotrophic plant pathogen that successively infects two hosts, poplar and larch, and produces five spore types during its life cycle. This fungus is the causal agent of poplar rust, the main sanitary constraint in European poplar cultures. One of the objectives of the UMR Tree/Microorganism Interactions is to characterize the molecular determinants involved in the interaction between poplar and M. larici-populina and to study their evolution. This thesis which relied on diverse research fields, ranging from population genetics to protein biochemistry, led to the development of three projects. First, a study, combining molecular approaches and population genetics, identified a significant association between the evolution of the candidate avirulence gene AvrMlp7 and the breakdown of the RMlp7-mediated resistance carried by some poplar cultivars. The association and coexistence of two alterations at the candidate locus confer virulence, providing for the first time insights on the genetic determinants responsible for a breakdown event in this pathogen. Second, an effort was made to develop functional approaches on this pathosystem. The expression of the candidate effector AvrMlp7 in the heterologous system Nicotiana benthamiana highlighted its chloroplastic localization, suggesting its potential role in modulating functions associated with this organelle. However, despite extensive functional investigations, the avirulence function of this candidate gene has not yet been formally demonstrated. Third, based on transcriptomic data, families of transcription factors could be associated with specific biological transitions along the life cycle of M. larici-populina. The cold-shock protein (CSP) family was found to be tightly associated with the exit of dormancy and the production of basidia and basidiospores from telia following an overwintering period. This study identifies for the first time factors regulating fundamental biological processes in Pucciniales, beyond the predominantly studied infection processes. In perspective, thanks to the added-values of combining several research fields, this thesis work opens new avenues in our attempt to understanding host-pathogen interactions
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Tellier, AureÌlien. "A theory of polymorphism in gene-for-gene interactions." Thesis, University of East Anglia, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.439932.
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Schmid, Ramona [Verfasser], and Roland [Akademischer Betreuer] Eils. "Analyzing Compounds’ Mode of Action - A Use Case for New Approaches Utilizing Protein Interaction Networks and Prior Knowledge to Complement State-of-the-Art Gene Expression Analyses / Ramona Schmid ; Betreuer: Roland Eils." Heidelberg : Universitätsbibliothek Heidelberg, 2012. http://d-nb.info/1179786343/34.
26
Sanders, Chelsea L. "Gene-Environment Interaction: Brain-Derived Neurotrophic Factor (BDNF) as a Moderating Factor for the Effects of Exercise and Diet on Cognitive and Mental Health: The Cache County Study on Memory in Aging." DigitalCommons@USU, 2018. https://digitalcommons.usu.edu/etd/7163.
Abstract:
The Cache County Study on Memory in Aging, funded by the National Institute on Aging, studied longitudinal changes in memory and aging over 12 years’ follow-up in a population-based sample of 5,092 older adults in semirural Cache County, UT. Among the extensive interview procedures, researchers collected information regarding the participants’ demographics, health, genetic factors, diet, physical activity, and cognitive abilities. This study has allowed researchers to investigate how genetic and modifiable lifestyle factors interact to predict health, cognitive function, and psychological wellbeing in older adults.
Diet and exercise are important lifestyle factors in maintaining cognitive health and psychological wellbeing throughout the lifespan, including late-life. The current investigation primarily focused on the link between these lifestyle factors and specific genes in predicting cognitive decline and risk for depression among older adults. Older adults are at risk for cognitive and mood changes as they age and certain genes may increase their vulnerability to these changes. However, it is possible that an older adult’s lifestyle behaviors regarding dietary pattern and physical activity may be protective against such genetic vulnerabilities. The genes investigated in this study are related to the production of a protein in the brain that promotes cell growth and survival. A better understanding of the relationship between lifestyle and genetic factors in late-life cognitive decline and depression may offer a better conceptualization of healthy aging and lead to more targeted diet and exercise recommendations. The present study found that engagement in moderate-vigorous physical activity was associated with slower cognitive decline whereas vigorous physical activity was associated with reduced risk for depression. Further, a specific gene was related to worse cognitive functioning among sedentary individuals. Alternatively, greater adherence to the dietary pattern investigated in our study did not reduce risk for depression and was beneficial for cognition in males only.
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Deodhar, Sushamna Shriniwas. "Using Grammatical Evolution Decision Trees for Detecting Gene-Gene Interactions in Genetic Epidemiology." NCSU, 2009. http://www.lib.ncsu.edu/theses/available/etd-10302009-181439/.
Abstract:
A major goal of human genetics is the discovery and validation of genetic polymorphisms that predict common, complex diseases. It is hypothesized that complex diseases are due to a myriad of factors including environmental exposures and complex genetic models. This etiological complexity, coupled with rapid advances in genotyping technology present enormous theoretical and practical concerns for statistical and computational analysis. Specifically, the challenge presented by epistasis, or gene-gene interactions, has sparked the development of a multitude of statistical techniques over the years. Subsequently, pattern matching and machine learning approaches have been explored to overcome the limitations of traditional computational methods. Grammatical Evolution Neural Networks (GENN) uses grammatical evolution to optimize neural network architectures and better detect and analyze gene-gene interactions. Motivated by good results shown by GENN to identify epistasis in complex datasets, we have developed a new method of Grammatical Evolution Decision Trees (GEDT). GEDT replaces the black-box approach of neural networks with the white-box approach of decision trees improving understandability and interpretability. We provide a detailed technical understanding of coupling Grammatical Evolution with Decision Tress using Backus Naur Form (BNF) grammar. Further, the GEDT system has been analyzed for power results on simulated datasets. Finally, we show the results of using GEDT on two different epistatis models and discuss the direction it would take in the future.
28
Vardarajan, Badri N. "Identification of gene-gene interactions for Alzheimer's disease using co-operative game theory." Thesis, Boston University, 2013. https://hdl.handle.net/2144/12868.
Abstract:
Thesis (Ph.D.)--Boston UniversityThe multifactorial nature of Alzheimer's Disease suggests that complex gene-gene interactions are present in AD pathways. Contemporary approaches to detect such interactions in genome-wide data are mathematically and computationally challenging. We investigated gene-gene interactions for AD using a novel algorithm based on cooperative game theory in 15 genome-wide association study (GWAS) datasets comprising of a total of 11,840 AD cases and 10,931 cognitively normal elderly controls from the Alzheimer Disease Genetics Consortium (ADGC). We adapted this approach, which was developed originally for solving multi-dimensional problems in economics and social sciences, to compute a Shapely value statistic to identify genetic markers that contribute most to coalitions of SNPs in predicting AD risk. Treating each GWAS dataset as independent discovery, markers were ranked according to their contribution to coalitions formed with other markers. Using a backward elimination strategy, markers with low Shapley values were eliminated and the statistic was recalculated iteratively. We tested all two-way interactions between top Shapley markers in regression models which included the two SNPs (main effects) and a term for their interaction. Models yielding a p-value<0.05 for the interaction term were evaluated in each of the other datasets and the results from all datasets were combined by meta-analysis. Statistically significant interactions were observed with multiple marker combinations in the APOE regions. My analyses also revealed statistically strong interactions between markers in 6 regions; CTNNA3-ATP11A (p=4.1E-07), CSMD1-PRKCQ (p=3.5E-08), DCC-UNC5CL (p=5.9e-8), CNTNAP2-RFC3 (p=1.16e-07), AACS-TSHZ3 (p=2.64e-07) and CAMK4-MMD (p=3.3e-07). The Shapley value algorithm outperformed Chi-Square and ReliefF in detecting known interactions between APOE and GAB2 in a previously published GWAS dataset. It was also more accurate than competing filtering methods in identifying simulated epistastic SNPs that are additive in nature, but its accuracy was low in identifying non-linear interactions. The game theory algorithm revealed strong interactions between markers in novel genes with weak main effects, which would have been overlooked if only markers with strong marginal association with AD were tested. This method will be a valuable tool for identifying gene-gene interactions for complex diseases and other traits.
29
Schmitt, Dominique [Verfasser], Michael [Gutachter] Sendtner, and Erich [Gutachter] Buchner. "Initial characterization of mouse Syap1 in the nervous system: Search for interaction partners, effects of gene knockdown and knockout, and tissue distribution with focus on the adult brain / Dominique Schmitt ; Gutachter: Michael Sendtner, Erich Buchner." Würzburg : Universität Würzburg, 2017. http://d-nb.info/1130588033/34.
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Dang, Hoang Viet. "Identification of gene-gene and gene-environment interactions for flowering time and grain yield using a multi-parental mapping population in barley." Thesis, Dang, Hoang Viet (2021) Identification of gene-gene and gene-environment interactions for flowering time and grain yield using a multi-parental mapping population in barley. PhD thesis, Murdoch University, 2021. https://researchrepository.murdoch.edu.au/id/eprint/62713/.
Abstract:
Grain yield improvement is considered the key target for many cereal breeding programs. In barley, grain yield is closely associated with flowering time, which provides crops with the opportunity to avoid stress and to best utilise available environmental resources. In this study, major genes associated with flowering time were identified using a multiparent advanced generation intercross (MAGIC) population constructed from four commercial barley cultivars (Compass, GrangeR, La Trobe and Lockyer). Gene-specific markers were developed for fast-screening of phenology genes in 1,919 MAGIC recombinant inbred lines using Kompetitive allele-specific PCR (KASP) assays. Sequencing data revealed a novel mutation in the Gibberellin 20 oxidase 2 (HvGA20ox2) region in cv. Lockyer, which showed similar impacts on flowering time and plant height compared to the well-known semi-dwarf 1 (sdw1) gene. Analyses using gene-specific genotype data and phenotype data from field trials with differing sowing locations and times confirmed the association of the major genes HvGA20ox2, Photoperiod 1 (HvPPD-H1), Dense and erect panicle 1 (HvDEP1) and Flowering locus T 1 (HvFT1) with flowering time. Different combinations of these phenology genes showed a broader range in flowering time compared to the four parental lines. Novel gene combinations showed up to 7 days earlier in flowering time compared to the earliest parental cultivar (La Trobe), and 5 days later than the latest parental cultivar (Lockyer). The phenotype data from Corrigin and Esperance trials suggested that gene combinations for optimal flowering time might differ in these locations. Optimal gene combinations are estimated to result in up to 24% improved grain yield compared to the parental cultivars. The results from this study will benefit the development of higher-yielding and better-adapted barley cultivars for various growing conditions across Australia.
31
Win, Joe. "Molecular Quest for Avirulence Factors in Venturia inaequalis." Thesis, University of Auckland, 2004. http://hdl.handle.net/2292/397.
Abstract:
The molecular basis for the gene-for-gene relationship of Vm-resistance in apple to Venturia inaequalis was investigated. Incompatible reactions involved a hypersensitive response (HR), which was accompanied by the accumulation of dark brown pigments and autofluorescent materials in epidermal and mesophyll cells at the site of invasion. Cell-free culture filtrates of the avirulent isolate elicited an HR in the Vm host (h5) leaves, but not in the susceptible host (h1). The elicitor activity was resistant to boiling but was abolished by proteinase K digestion. Elicitation of HR was used to monitor purification of the avirulence factor, AVRVm, from liquid cultures of the avirulent isolate following ultrafiltration, acetone precipitation and ion-exchange chromatography. The purest fraction contained three major proteins all with low isoelectric points (pI 3.0-4.5). The fraction also elicited HR on the differential host h4, but not on other resistant hosts (h2, h3 and h6) tested. Three candidate AVRVm proteins were identified and amino acid sequences were obtained using Edman degradation and mass spectrometry. Nucleotide sequences corresponding to these proteins were found in databases of V. inaequalis expressed sequence tags. There were no polymorphisms evident between avirulent and virulent isolates (representing races 1 and 5 respectively) either at genomic DNA or cDNA level of the full open reading frames. RT-PCR revealed that all genes were expressed in both avirulent and virulent isolates during in vitro and in planta growth. All three genes showed similar levels of expression between avirulent and virulent isolates during their in vitro growth. However, preliminary RT-PCR experiments showed that two of these genes were likely to be expressed at lower levels in the virulent compared with the avirulent isolate during compatible infection. Implications of this difference in expression and the future experiments to identify the genuine AvrVm gene were discussed.
32
Alavi, Hajar Karimi. "Development of mechanistic mathematical models for gene-mediated drug-drug interactions." Thesis, University of Manchester, 2016. https://www.research.manchester.ac.uk/portal/en/theses/development-of-mechanistic-mathematical-models-for-genemediated-drugdrug-interactions(b38da88a-bb2a-4667-9809-21a09c8feeeb).html.
Abstract:
The glucocorticoid receptor (GR) is a member of the nuclear hormone receptors family and has been shown to exert significant effects on the induction of cytochrome P450 (CYP) enzymes responsible for the metabolism of many xenobiotics. CYP3A4/5 and CYP2C9 are important CYP enzymes which metabolise more that 60% of drugs. Induction or inhibition of the enzymatic activity and the levels of these enzymes can have significant effects on drug metabolism. Understanding the role of GR and other nuclear receptors, pregnane X receptor (PXR) and the constitutive androstane receptor (CAR), in the mechanisms effecting CYP3A4/5 and CYP2C9 levels and activity can aid in the development of in vitro and in vivo models which have become a target for scientists in the clinic and the industry. The commonly prescribed synthetic glucocorticoid (GC) drug, dexamethasone (Dex), can induce GR, PXR and CAR and was used in this study to analyse its effects on the CYP enzymes studied. The hypothesis of this project was that changes in CYP3A4/5 and CYP2C9 gene expression affect drug metabolism and changes in gene expression of these CYP enzymes was under GR, PXR and CAR control, thus affecting the concentration and therapeutic activity of drugs metabolized by these enzymes during chronic use of GCs in conditions such as rheumatoid arthritis and asthma. This study aimed to measure mRNA, protein, ROS and enzymatic activity levels in human HepG2 hepatocytes treated with Dex for 120 h and analyze the results for various time points to produce a mathematical model. Our study has shown that changes in mRNA, protein and enzymatic activity levels of CYP3A4/5 and CYP2C9 in HepG2 cells were induced by Dex at sub-micromolar (0.1 µM) and supra-micromolar (1.5 mM) concentrations. The induction of CYP3A4/5 and CYP2C9 enzymes during 120 h treatment with Dex may be affected by the NRs studied; GR, phosphorylated GR, PXR and CAR protein levels were also shown to be induced by Dex. The efflux transporter, P-gp’s protein levels were also induced by 0.1 µM Dex, highlighting the importance of considering bioavailability of other drugs co-administered with Dex. The results of some of these laboratory experiments have been used to produce mechanistic mathematical models by MATLAB software with reference to previous studies in rats concentrating on the effects of steroids on GR. The models developed were not effective at the lower Dex concentration of 0.1 µM but were better modelled at the higher Dex concentration of 1.5 mM. The basic mechanistic models developed using HepG2 cells in this study can be utilised to design and conduct drug-drug interaction (DDI) analyses of the induction of CYP3A4/5 and CYP2C9 in other human liver cells and starting pre-clinical studies in animals to aid in drug development.
33
Dameh, Mustafa, and n/a. "Insights into gene interactions using computational methods for literature and sequence resources." University of Otago. Department of Anatomy & Structural Biology, 2008. http://adt.otago.ac.nz./public/adt-NZDU20090109.095349.
Abstract:
At the beginning of this century many sequencing projects were finalised. As a result, overwhelming amount of literature and sequence data have been available to biologist via online bioinformatics databases. This biological data lead to better understanding of many organisms and have helped identify genes. However, there is still much to learn about the functions and interactions of genes.
This thesis is concerned with predicting gene interactions using two main online resources: biomedical literature and sequence data. The biomedical literature is used to explore and refine a text mining method, known as the "co-occurrence method", which is used to predict gene interactions. The sequence data are used in an analysis to predict an upper bound of the number of genes involved in gene interactions.
The co-occurrence method of text mining was extensively explored in this thesis. The effects of certain computational parameters on influencing the relevancy of documents in which two genes co-occur were critically examined. The results showed that indeed some computational parameters do have an impact on the outcome of the co-occurrence method, and if taken into consideration, can lead to better identification of documents that describe gene interactions. To explore the co-occurrence method of text mining, a prototype system was developed, and as a result, it contains unique functions that are not present in currently available text mining systems.
Sequence data were used to predict the upper bound of the number of genes involved in gene interactions within a tissue. A novel approach was undertaken that used an analysis of SAGE and EST sequence libraries using ecological estimation methods. The approach proves that the species accumulation theory used in ecology can be applied to tag libraries (SAGE or EST) to predict an upper bound to the number of mRNA transcript species in a tissue.
The novel computational analysis provided in this study can be used to extend the body of knowledge and insights relating to gene interactions and, hence, provide better understanding of genes and their functions.
34
Mickler, Frauke Martina. "Live-cell imaging elucidates cellular interactions of gene nanocarriers for cancer therapy." Diss., Ludwig-Maximilians-Universität München, 2013. http://nbn-resolving.de/urn:nbn:de:bvb:19-165829.
35
Golding, Pauline Lindsay. "Development of a statistical method for the identification of gene-environment interactions." Thesis, University of Edinburgh, 2012. http://hdl.handle.net/1842/6520.
Abstract:
In order to understand common, complex disease it is necessary to consider not just genetic risks and environmental risks, but also the interplay between them. This thesis aims to develop methodology for the detection of gene-environment interactions specifically; both by looking at the strengths and weaknesses of traditional approaches and through the development and testing of a novel statistical method. Developments in genotyping technology enable researchers to collect large volumes of polymorphisms in human genes, yet very few statistical methods are able to handle the volume, variation and complexity of this data, especially in combination with environmental risk factors. Interactions between genes and the environment are often subject to the curse of dimensionality, with each new variable increasing the potential number of interactions exponentially, leading to low power and a high false positive rate. The Mixed Tree Method (MTM) exploits the differences between environmental and genetic variables, by selecting the most appropriate features from conventional methods (including recursive partitioning, random forests and logistic regression) and combining them with new comparison algorithms which rank the genetic variables by the likelihood that they interact with the environmental variable under study. Results show the MTM to be as effective as the most successful current method for identification of interactions, but maintaining a much lower false positive rate and computational burden. As the number of SNPs in the dataset increases, the success of MTM compared to other methods becomes greater while the comparator approaches exhibit computational problems and rapidly increasing processing times. The MTM is also applied to a colorectal cancer dataset to show its use in a practical setting. The results together suggest that MTM could be a useful strategy for identifying gene environment interactions in future studies into complex disease.
36
Tamburino, Alex M. "A Gene-Centered Method For Mapping 3’UTR-RBP Interactions: A Dissertation." eScholarship@UMMS, 2015. https://escholarship.umassmed.edu/gsbs_diss/793.
Abstract:
Interactions between 3´ untranslated regions (UTRs) and RNA-binding proteins (RBPs) play critical roles in post-transcriptional gene regulation. Metazoan genomes encode hundreds of RBPs and thousands of 3’ UTRs have been experimentally identified, yet the spectrum of interactions between 3´UTRs and RBPs remains largely unknown. Several methods are available to map these interactions, including protein-centered methods such as RBP immunoprecipitation (RIP) and cross-link immunoprecipitation (CLIP), yeast three-hybrid assays and RNAcompete. However, there is a paucity of RNA-centered approaches for assaying an RNA element of interest against multiple RBPs in a parallel, scalable manner.
Here, I present a strategy for delineating protein-RNA interaction networks using a gene centered approach. This approach includes annotating RBPs and identifying physical interactions between an RNA of interest and these RBPs using the Protein-RNA Interaction Mapping Assay (PRIMA). Few RBPs have been experimentally determined in most eukaryotic organisms. Therefore I show that existing RBP annotations can be supplemented using computational predictions of RNA binding domains (RBD) from protein sequences. A single RNA of interest can be tested using PRIMA against a library of RBPs constructed from these annotations. PRIMA utilizes the green fluorescent protein (GFP) in yeast as a reporter.
PRIMA is based on reconstitution of the interaction between the 5´ and 3´ ends of an mRNA, which increases mRNA stability and enhances translation. PRIMA recapitulates known and uncovers new interactions involving RBPs from human, Caenorhabditis elegans and bacteriophage with short RNA fragments and full-length 3´UTRs. The development of RBP prey libraries will enable the testing of 3´UTRs against the hundreds of RBPs, which is essential to gain broad insights into post-transcriptional gene regulation at a systems level.
37
Tamburino, Alex M. "A Gene-Centered Method For Mapping 3’UTR-RBP Interactions: A Dissertation." eScholarship@UMMS, 2008. http://escholarship.umassmed.edu/gsbs_diss/793.
Abstract:
Interactions between 3´ untranslated regions (UTRs) and RNA-binding proteins (RBPs) play critical roles in post-transcriptional gene regulation. Metazoan genomes encode hundreds of RBPs and thousands of 3’ UTRs have been experimentally identified, yet the spectrum of interactions between 3´UTRs and RBPs remains largely unknown. Several methods are available to map these interactions, including protein-centered methods such as RBP immunoprecipitation (RIP) and cross-link immunoprecipitation (CLIP), yeast three-hybrid assays and RNAcompete. However, there is a paucity of RNA-centered approaches for assaying an RNA element of interest against multiple RBPs in a parallel, scalable manner.
Here, I present a strategy for delineating protein-RNA interaction networks using a gene centered approach. This approach includes annotating RBPs and identifying physical interactions between an RNA of interest and these RBPs using the Protein-RNA Interaction Mapping Assay (PRIMA). Few RBPs have been experimentally determined in most eukaryotic organisms. Therefore I show that existing RBP annotations can be supplemented using computational predictions of RNA binding domains (RBD) from protein sequences. A single RNA of interest can be tested using PRIMA against a library of RBPs constructed from these annotations. PRIMA utilizes the green fluorescent protein (GFP) in yeast as a reporter.
PRIMA is based on reconstitution of the interaction between the 5´ and 3´ ends of an mRNA, which increases mRNA stability and enhances translation. PRIMA recapitulates known and uncovers new interactions involving RBPs from human, Caenorhabditis elegans and bacteriophage with short RNA fragments and full-length 3´UTRs. The development of RBP prey libraries will enable the testing of 3´UTRs against the hundreds of RBPs, which is essential to gain broad insights into post-transcriptional gene regulation at a systems level.
38
van, der Aa Eveline Maria. "Synthesis and Characterization of Nucleobase-Containing Polyelectrolytes for Gene Delivery." Thesis, Virginia Tech, 2010. http://hdl.handle.net/10919/33008.
Abstract:
Wide literature precedence exists for polymers containing electrostatic interactions and
polymers containing hydrogen bonding motifs, however the combination of electrostatic
and hydrogen bonding interactions is not widely investigated in current literature.
Polyelectrolytes containing hydrogen bonding groups are expected to exhibit properties
of both classes of supramolecular interactions. A series of adenine- and thyminecontaining
PDMAEMA and tert-butyl acrylate copolymers were synthesized to
investigate the effect of incorporating hydrogen bonding groups into a polyelectrolyte.
Incorporation of the styrenic nucleobases significantly affected the solubility of these
copolymers on aqueous solutions and showed salt-triggerability with higher contents of
these groups. Polyelectrolytes are capable of binding and condensing DNA through
electrostatic interactions with the negatively charged phosphate groups of the DNA
backbone; however a high degree of cytotoxicity is also often observed for these gene
delivery systems. The high level of cytotoxicity is attributed to high degree of cationic
character for the polyplexes formed with these systems according to the proton-sponge
hypothesis. One method of reducing the overall cationic character for these systems is
incorporation of non-electrostatic binding mechanisms such as hydrogen bonding. A
series of nucleobase-containing PDMAEMA copolymers were utilized in order to
investigate the effect of incorporation of these groups on the cell viability, binding
efficiency, and transfection efficiency of PDMAEMA.Master of Science
39
Taha, May. "Probing sequence-level instructions for gene expression." Thesis, Montpellier, 2018. http://www.theses.fr/2018MONTT096/document.
Abstract:
La régulation des gènes est fortement contrôlée afin d’assurer une large variété de types cellulaires ayant des fonctions spécifiques. Ces contrôles prennent place à différents niveaux et sont associés à différentes régions génomiques régulatrices. Il est donc essentiel de comprendre les mécanismes à la base des régulations géniques dans les différents types cellulaires, dans le but d’identifier les régulateurs clés. Plusieurs études tentent de mieux comprendre les mécanismes de régulation en modulant l’expression des gènes par des approches épigénétiques. Cependant, ces approches sont basées sur des données expérimentales limitées à quelques échantillons, et sont à la fois couteuses et chronophages. Par ailleurs, les constituants nécessaires à la régulation des gènes au niveau des séquences ne peut pas être capturées par ces approches. L’objectif principal de cette thèse est d’expliquer l’expression des ARNm en se basant uniquement sur les séquences d’ADN.Dans une première partie, nous utilisons le modèle de régression linéaire avec pénalisation Lasso pour prédire l’expression des gènes par l’intermédiaire des caractéristique de l’ADN comme la composition nucléotidique et les sites de fixation des facteurs de transcription. La précision de cette approche a été mesurée sur plusieurs données provenant de la base de donnée TCGA et nous avons trouvé des performances similaires aux modèles ajustés aux données expérimentales. Nous avons montré que la composition nucléotidique a un impact majeur sur l’expression des gènes. De plus, l’influence de chaque régions régulatrices est évaluée et l’effet du corps de gène, spécialement les introns semble être clé dans la prédiction de l’expression. En second partie, nous présentons une tentative d’amélioration des performances du modèle. D’abord, nous considérons inclure dans le modèles les interactions entres les différents variables et appliquer des transformations non linéaires sur les variables prédictives. Cela induit une légère augmentation des performances du modèles. Pour aller plus loin, des modèles d’apprentissage profond sont étudiés. Deux types de réseaux de neurones sont considérés : Les perceptrons multicouches et les réseaux de convolutions.Les paramètres de chaque neurone sont optimisés. Les performances des deux types de réseaux semblent être plus élevées que celles du modèle de régression linéaire pénalisée par Lasso. Les travaux de cette thèse nous ont permis (i) de démontrer l’existence des instructions au niveau de la séquence en relation avec l’expression des gènes, et (ii) de fournir différents cadres de travail basés sur des approches complémentaires. Des travaux complémentaires sont en cours en particulier sur le deep learning, dans le but de détecter des informations supplémentaires présentes dans les séquencesGene regulation is tightly controlled to ensure a wide variety of cell types and functions. These controls take place at different levels and are associated with different genomic regulatory regions. An actual challenge is to understand how the gene regulation machinery works in each cell type and to identify the most important regulators. Several studies attempt to understand the regulatory mechanisms by modeling gene expression using epigenetic marks. Nonetheless, these approaches rely on experimental data which are limited to some samples, costly and time-consuming. Besides, the important component of gene regulation based at the sequence level cannot be captured by these approaches. The main objective of this thesis is to explain mRNA expression based only on DNA sequences features. In a first work, we use Lasso penalized linear regression to predict gene expression using DNA features such as transcription factor binding site (motifs) and nucleotide compositions. We measured the accuracy of our approach on several data from the TCGA database and find similar performance as that of models fitted with experimental data. In addition, we show that nucleotide compositions of different regulatory regions have a major impact on gene expression. Furthermore, we rank the influence of each regulatory regions and show a strong effect of the gene body, especially introns.In a second part, we try to increase the performances of the model. We first consider adding interactions between nucleotide compositions and applying non-linear transformations on predictive variables. This induces a slight increase in model performances.To go one step further, we then learn deep neuronal networks. We consider two types of neural networks: multilayer perceptrons and convolution networks. Hyperparameters of each network are optimized. The performances of both types of networks appear slightly higher than those of a Lasso penalized linear model. In this thesis, we were able to (i) demonstrate the existence of sequence-level instructions for gene expression and (ii) provide different frameworks based on complementary approaches. Additional work is ongoing, in particular with the last direction based on deep learning, with the aim of detecting additional information present in the sequence
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Altarawy, Doaa Abdelsalam Ahmed Mohamed. "DeTangle: A Framework for Interactive Prediction and Visualization of Gene Regulatory Networks." Diss., Virginia Tech, 2017. http://hdl.handle.net/10919/85504.
Abstract:
With the abundance of biological data, computational prediction of gene regulatory networks (GRNs) from gene expression data has become more feasible. Although incorporating other
prior knowledge (PK), along with gene expression, greatly improves prediction accuracy, the accuracy remains low. PK in GRN inference can be categorized into noisy and curated.
Several algorithms were proposed to incorporate noisy PK, but none address curated PK. Another challenge is that much of the PK is not stored in databases or not in a unified structured format to be accessible by inference algorithms. Moreover, no GRN inference method exists that supports post-prediction PK.
This thesis addresses those limitations with three solutions: PEAK algorithm for integrating both curated and noisy PK, Online-PEAK for post-prediction interactive feedback, and DeTangle for visualization and navigation of GRNs. PEAK integrates both curated as well as noisy PK in GRN inference. We introduce a novel method for GRN inference, CurInf, to effectively integrate curated PK, and we use the previous method, Modified Elastic Net, for noisy PK, and we call it NoisInf. Using 100% curated PK, CurInf improves the AUPR accuracy score over NoisInf by 27.3% in synthetic data, 86.5% in E. coli data, and 31.1% in S. cerevisiae data. Moreover, we developed an online algorithm, online-PEAK, that enables the biologist to interact with the inference algorithm, PEAK, through a visual interface to add their domain experience about the structure of the GRN as a feedback to the system. We experimentally verified the ability of online-PEAK to achieve incremental accuracy when PK is added by the user, including true and false PK. Even when the noise in PK is 10 times more than true PK, online-PEAK performs better than inference without any PK.
Finally, we present DeTangle, a Web server for interactive GRN prediction and visualization. DeTangle provides a seamless analysis of GRN starting from uploading gene expression, GRN inference, post-prediction feedback using online-PEAK, and visualization and navigation of the predicted GRN. More accurate prediction of GRN can facilitate studying complex molecular interactions, understanding diseases, and aiding drug design.Ph. D.
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Rauschhuber, Christina. "Analysis of Adenovirus-Host Interactions to Improve Recombinant Adenoviral Vectors for Gene Therapy." Diss., lmu, 2011. http://nbn-resolving.de/urn:nbn:de:bvb:19-128560.
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Ucar, Duygu. "Constructing and Analyzing Biological Interaction Networks for Knowledge Discovery." The Ohio State University, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=osu1250656196.
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Harpe, Anke von. "Polyethylenimine derivatives for gene transfer : Polymer synthesis, coupling of ligands and interactions with DNA /." Marburg : Görich & Weiershäuser, 2000. http://www.gbv.de/dms/bs/toc/319704181.pdf.
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Thorén, Per. "Membrane interactions of arginine-rich peptides for the intracellular delivery of gene-targeted drugs /." Göteborg : Chalmers Univ. of Technology, 2003. http://www.gbv.de/dms/bs/toc/37405925X.pdf.
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Broc, Camilo. "Variable selection for data aggregated from different sources with group of variable structure." Thesis, Pau, 2019. http://www.theses.fr/2019PAUU3048.
Abstract:
Durant les dernières décennies, la quantité de données disponibles en génétique a consi-dérablement augmenté. D’une part, une amélioration des technologies de séquençage demolécules a permis de réduire fortement le coût d’extraction du génome humain. D’autrepart, des consortiums internationaux d’institutions ont permis la mise en commun de lacollecte de données sur de larges populations. Cette quantité de données nous permetd’espérer mieux comprendre les mécanismes régissant le fonctionnement de nos cellules.Dans ce contexte, l’épidémiologie génétique est un domaine cherchant à déterminer larelation entre des caractéristiques génétiques et l’apparition d’une maladie. Des méthodesstatistiques spécifiques à ce domaine ont dû être développées, en particulier à cause desdimensions que les données présentent : en génétique, l’information est contenue dans unnombre de variables grand par rapport au nombre d’observations.Dans cette dissertation, deux contributions sont présentées. Le premier projet appeléPIGE (Pathway-Interaction Gene Environment) développe une méthode pour déterminerdes interactions gène-environnement. Le second projet vise à développer une méthode desélection de variables adaptée à l’analyse de données provenant de différentes études etprésentant une structure de groupe de variables.Le document est divisé en six parties. Le premier chapitre met en relief le contexte,d’un point de vue à la fois biologique et mathématique. Le deuxième chapitre présente lesmotivations de ce travail et la mise en œuvre d’études en épidémiologie génétique. Le troi-sième chapitre aborde les questions relatives à l’analyse d’interactions gène-environnementet la première contribution de la thèse y est présentée. Le quatrième chapitre traite desproblématiques de méta-analyses. Le développement d’une nouvelle méthode de réductionde dimension répondant à ces questions y est présenté. Le cinquième chapitre met en avantla pertinence de la méthode dans des cas de pleiotropie. Enfin, le sixième et dernier chapitredresse un bilan du travail présenté et dresse des perspectives pour le futurDuring the last decades, the amount of available genetic data on populations has growndrastically. From one side, a refinement of chemical technologies have made possible theextraction of the human genome of individuals at an accessible cost. From the other side,consortia of institutions and laboratories around the world have permitted the collectionof data on a variety of individuals and population. This amount of data raised hope onour ability to understand the deepest mechanisms involved in the functioning of our cells.Notably, genetic epidemiology is a field that studies the relation between the geneticfeatures and the onset of a disease. Specific statistical methods have been necessary forthose analyses, especially due to the dimensions of available data: in genetics, informationis contained in a high number of variables compared to the number of observations.In this dissertation, two contributions are presented. The first project called PIGE (Pathway-Interaction Gene Environment) deals with gene-environment interaction assessments.The second one aims at developing variable selection methods for data which has groupstructures in both the variables and the observations.The document is divided into six chapters. The first chapter sets the background of this work,where both biological and mathematical notations and concepts are presented and gives ahistory of the motivation behind genetics and genetic epidemiology. The second chapterpresent an overview of the statistical methods currently in use for genetic epidemiology.The third chapter deals with the identification of gene-environment interactions. It includesa presentation of existing approaches for this problem and a contribution of the thesis. Thefourth chapter brings off the problem of meta-analysis. A definition of the problem and anoverview of the existing approaches are presented. Then, a new approach is introduced.The fifth chapter explains the pleiotropy studies and how the method presented in theprevious chapter is suited for this kind of analysis. The last chapter compiles conclusionsand research lines for the future
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Gerson, Rosalind J. "The Interaction Between Sir3 and Sir4 is Dispensable for Silent Chromatin Spreading in Budding Yeast." Thesis, Université d'Ottawa / University of Ottawa, 2015. http://hdl.handle.net/10393/32232.
Abstract:
In Saccharomyces cerevisiae, telomeric and HM silencing requires the histone deacetylase Sir2 and the chromatin binding proteins Sir3 and Sir4, which interact to form the SIR complex. Silent chromatin formation begins with a nucleation step, followed by spreading of Sir proteins along chromatin. Overexpression of Sir3 extends silent chromatin domains, however the role of Sir protein interactions within silent chromatin extensions remains unknown. Here, we generated the Sir3 mutant, Sir3-4A, which cannot interact with Sir4 but is capable of forming silent chromatin extensions when overexpressed. Within extended silent domains, Sir2 and Sir4 enrichments are similar whether Sir3 or Sir3-4A is overexpressed, suggesting that silent chromatin extensions require Sir4 but not the interaction between Sir3 and Sir4. Tethering Sir3-4A at an HMR silencer cannot nucleate silencing in the absence of Sir3, suggesting that in addition to Sir3 recruitment, the Sir3-Sir4 interaction has at least one other function during silent chromatin nucleation.
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Skaggs, Hollie Suzanne. "IMPLICATIONS FOR THE INTERACTION BETWEEN THE HEAT SHOCK TRANSCRIPTION FACTORS AND THE TRANSLOCATED PROMOTER REGION PROTEIN." UKnowledge, 2007. http://uknowledge.uky.edu/gradschool_diss/503.
Abstract:
The heat-shock response is one of the many complex physiological systems that organisms have developed in order to protect their cells against stress. This response is initiated by the binding of heat shock factor 1 (HSF1) to the promoters of genes containing heat-shock elements (HSEs,) which results in the expression of several proteins, among them the proteo-protective inducible heat-shock protein (hsp70i). Due to HSF1s critical role in this process, an active area of research is trying to understand of how HSF1 executes its function. Considering the rapidity with which the field of cell biology is expanding, in particular the sub-field of nuclear compartmentalization, this study seeks to understand how nuclear structure affects the function of HSF1. Specifically, this study investigates the potential role for the interaction between HSF1 and the translocated promoter region protein (Tpr,) a structural component of the nuclear pore, an interaction initially identified by yeast two-hybrid analysis, in the transcription of hsp70i. Due to Tprs location and its putative function in nucleo-cytoplasmic trafficking, this works seeks to answer to the question, Does Tpr play a role in the export of HSF1-driven mRNAs? In a similar vein, heat-shock transcription factor 2 (HSF2,) a less well-understood member of the heat-shock transcription factor family, also interacts with Tpr in the yeast two-hybrid assay. HSF2 has recently been shown to have an active role during mitosis, when the hsp70i gene is being bookmarked for potential expression that might be needed in early G1, when most genes are unable to be expressed. This body of work also seeks to answer the question of, Does the Tpr/HSF2 interaction have a role in positioning the gene in relation to the nuclear pore after mitosis? This study was performed using both novel and standard in vivo and in vitro molecular biology techniques. It ultimately aims to clarify the less understood, although much broader, subject of how does transcription occur in the three-dimensional space of the nucleus.
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Huttner, Nadja. "Adeno-associated virus type 2 as vector for human gene therapy: Characterization of virus-host interactions." Diss., lmu, 2003. http://nbn-resolving.de/urn:nbn:de:bvb:19-14207.
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duVerle, David Alexander. "Building a Machine-Learning Framework for Protein Interactions: Calpain Cleavage Prediction and Gene Regulatory Network Inference." 京都大学 (Kyoto University), 2012. http://hdl.handle.net/2433/157921.
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Bankers, Laura. "Parasites, ploidy, and sex: implications for gene expression and adaptive molecular evolution in Potamopyrgus antipodarum." Diss., University of Iowa, 2017. https://ir.uiowa.edu/etd/5709.
Abstract:
The trajectory of evolutionary adaptation can be influenced both by the interactions of organisms with their environments as well as by the biological characteristics of the organisms themselves. My dissertation research uses the New Zealand freshwater snail Potamopyrgus antipodarum to 1) gain important insight into how coevolutionary interactions between hosts and parasites influence patterns of gene expression and genetic differentiation of hosts and, 2) evaluate how reproductive mode, and ploidy level affect patterns of adaptive molecular evolution.
Coevolutionary interactions between hosts and parasites are a primary source of strong natural selection that can lead to rapid evolutionary change. Here, I used evaluation of patterns of gene expression and genetic differentiation to take critical steps towards characterizing the genomic basis of coevolutionary interactions between P. antipodarum and Microphallus livelyi. I found that M. livelyi-infected P. antipodarum exhibit systematic downregulation of genes relative to uninfected P. antipodarum. The specific genes involved in response to parasites differ markedly across lakes, consistent with population-specific host-parasite interactions leading to population-specific evolutionary trajectories. I also identified a set of rapidly evolving loci that represent promising candidates for targets of parasite-mediated selection across lakes as well as within each lake population. These results constitute the first genomic evidence for population-specific responses to coevolving infection in the P. antipodarum-M. livelyi interaction and provide new insights into the genomic basis of coevolutionary interactions in nature. I also generated and characterized the first transcriptomic resources for Microphallus parasites collected from two species of Potamopyrgus snails (P. antipodarum and P. estuarinus). These data both revealed that these parasites appear to represent distinct genetic lineages, which is interesting in light of the tight coevolutionary interactions between P. antipodarum and M. livelyi, and lay the groundwork for future research.
Polyploidy has the potential to facilitate adaptive evolution by providing redundant genome copies that are free to evolve new functions. By contrast, asexuality, with which polyploidy is often associated, is expected to restrict adaptive evolution by decreasing the efficacy of natural selection and access to new genetic variation. I evaluated whether and how ploidy level and reproductive mode influence patterns of adaptive molecular evolution in P. antipodarum to assess 1) the potential evolutionary genomic benefits of recent polyploidy, and 2) how patterns of adaptive molecular evolution in asexuals are influenced by polyploidy. I compared patterns of positive selection in 60 genes across 27 P. antipodarum lineages (10 diploid sexuals, 12 triploid asexuals, 5 tetraploid asexuals) and a diploid sexual outgroup, Potamopyrgus estuarinus. I found little evidence that ploidy level and/or reproductive mode influence patterns of positive selection in P. antipodarum. Even so, this study provides initial steps in evaluating whether ploidy level and reproductive mode influence patterns of adaptive molecular evolution. Taken together, my dissertation work contributes new insights to the field of host-parasite coevolutionary interactions and will inform future studies into how ploidy level and reproductive mode influence patterns of adaptive molecular evolution.