Dissertations / Theses on the topic 'Complex Traits Genetics'
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Bell, Jordana Tzenova. "Epistasis in complex human traits." Thesis, University of Oxford, 2006. http://ora.ox.ac.uk/objects/uuid:547db446-c84c-4a6c-8b5c-ce960f7765c5.
Full textNelson, Vicki R. "Transgenerational Genetic Effects In Mouse Models Of Complex Traits." Case Western Reserve University School of Graduate Studies / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=case1278706008.
Full textGoddard, Katrina Blouke. "Study design issues in the analysis of complex genetic traits /." Thesis, Connect to this title online; UW restricted, 1999. http://hdl.handle.net/1773/9565.
Full textJoshi, Peter K. "Exploring the inheritance of complex traits in humans." Thesis, University of Edinburgh, 2015. http://hdl.handle.net/1842/21118.
Full textAllchin, Lorraine Doreen May. "Statistical methods for mapping complex traits." Thesis, University of Oxford, 2014. http://ora.ox.ac.uk/objects/uuid:65f392ba-1b64-4b00-8871-7cee98809ce1.
Full textLuo, Yuqun. "Incorporation of genetic marker information in estimating model parameters for complex traits with data from large complex pedigrees /." The Ohio State University, 2002. http://rave.ohiolink.edu/etdc/view?acc_num=osu1486549482668451.
Full textBigdeli, T. Bernard. "Quantitative Genetic Methods to Dissect Heterogeneity in Complex Traits." VCU Scholars Compass, 2012. http://scholarscompass.vcu.edu/etd/2651.
Full textAshbrook, David. "A systems-genetics analyses of complex phenotypes." Thesis, University of Manchester, 2015. https://www.research.manchester.ac.uk/portal/en/theses/a-systemsgenetics-analyses-of-complex-phenotypes(a3e7ad8e-b23b-40fd-821e-26a6c1a63d38).html.
Full textValenzuela, Robert Keams. "Predictive Modeling for Complex Traits: Normal Human Pigmentation Variation." Diss., The University of Arizona, 2011. http://hdl.handle.net/10150/145309.
Full textUricchio, Lawrence Hart. "Models and forward simulations of selection, human demography, and complex traits." Thesis, University of California, San Francisco, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=3681226.
Full textEvolutionary forces such as recombination, demography, and selection can shape patterns of genetic diversity within populations and contribute to phenotypic variation. While theoretical models exist for each of these forces independently, mathematically modeling their joint impact on patterns of genetic diversity remains very challenging. Fortunately, it is possible to perform forward-in-time computer simulations of DNA sequences that incorporate all of these forces simultaneously. Here, I show that there are trade-offs between computational efficiency and accuracy for simulations of a widely investigated model of recurrent positive selection. I develop a theoretical model to explain this trade-off, and a simple algorithm that obtains the best possible computational performance for a given error tolerance. I then pivot to develop a framework for simulations of human DNA sequences and genetically complex phenotypes, incorporating recently inferred demographic models of human continental groups and selection on genes and non-coding elements. I use these simulations to investigate the power of rare variant association tests in the context of rampant selection and non-equilibrium demography. I show that the power of rare variant association tests is in some cases quite sensitive to underlying assumptions about the relationship between selection and effect sizes. This work highlights both the challenge and the promise of applying forward simulations in genetic studies that seek to infer the parameters of evolutionary models and detect statistical associations.
Johansson, Åsa. "Genome Variation in Human Populations : Exploring the Effects of Demographic History and the Potential for Mapping of Complex Traits." Doctoral thesis, Uppsala University, Department of Genetics and Pathology, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-7293.
Full textA major challenge in human genetics is to understand the genetic variation underlying common diseases. In this thesis, I focus on forces creating differences between individuals and genomic regions, methods for characterizing genomic variation, and the association between genomic and phenotypic variation. Genetic markers are widely used to locate genes associated with different phenotypes. In my first paper, I describe novel algorithms for automatic genotype determination of microsatellite markers, a procedure which is currently both time-consuming and error prone.
The co-segregation of genetic markers in a population leads to non-random association of alleles at different loci - linkage disequilibrium (LD). LD varies throughout the genome and differs between populations due to factors such as their demographic history. In my second paper, I discuss the increased power, for mapping of human traits, that results from studying a population with appreciable levels of LD such as is found in the Swedish Sami population.
Lately, large-scale analyses of single nucleotide polymorphisms (SNPs) have become available and efforts have been made to identify a set of SNPs, which captures most of the genome variation in a population (tagSNPs). In my third paper, I describe the limitations of this approach when applied to data from an independent population sample of randomly ascertained SNPs. The transferability of tagSNPs between populations is poor, presumably due to variation in allele frequencies and the bias towards common SNPs used in most studies.
The level of genomic variation is influenced by population structure, recombination and mutation rate, as well as natural selection. During the exodus from Africa, humans have adapted to new environmental conditions. In my fourth paper, I describe a new method for identifying genomic regions carrying signatures of recent positive selection and apply this to an available dataset of millions of SNPs.
Ndungu, Anne. "Rare genetic variants and susceptibility to severe bacterial diseases." Thesis, University of Oxford, 2015. https://ora.ox.ac.uk/objects/uuid:9c5745f9-50f9-469a-8771-2e49e75db7ac.
Full textChen, Anlu. "Applying Forward Genetic Approaches to Rare Mendelian Disorders and Complex Traits." Case Western Reserve University School of Graduate Studies / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=case1532522241487661.
Full textBaud, Amelie. "Fine-mapping complex traits in heterogeneous stock rats." Thesis, University of Oxford, 2013. http://ora.ox.ac.uk/objects/uuid:c762c1af-c899-478f-93e1-305775d5a6f4.
Full textTuke, Marcus Aelred. "Exploring the role of low-frequency and structural genetic variation in human complex traits." Thesis, University of Exeter, 2016. http://hdl.handle.net/10871/23687.
Full textHall, Lynsey Sylvia. "Identifying endophenotypes for depression in Generation Scotland : a Scottish family health study." Thesis, University of Edinburgh, 2017. http://hdl.handle.net/1842/28737.
Full textHerzig, Anthony Francis. "Studying the genetic architecture of complex traits in a population isolate." Thesis, Sorbonne Paris Cité, 2019. http://www.theses.fr/2019USPCC110.
Full textMy thesis project is concerned with tapping the potential of population isolates for the dissection of complex trait architecture. Specifically, isolates can aid the identification of variants that are usually rare in other populations. This thesis principally contains in depth investigations into genetic imputation and heritability analysis in isolates. We approached both of these studies from two main angles; first from a methodological standpoint where we created extensive simulation datasets in order to investigate how the specificities of an isolate should determine strategies for analyses. Secondly, we demonstrated such concepts through analysis of genetic data in the known isolate of Cilento. Imputation is a crucial step to performing association analyses in an isolate and represents a cost-efficient method for gaining dense genetic data for the population. The effectiveness of imputation is of course dependent on its accuracy. Hence, we investigated the wide range of possible strategies to gain maximal imputation accuracy in an isolate. We showed that software using algorithms which specifically evoke known characteristics of isolates were, unexpectedly, not as successful as those designed for general populations. We also demonstrated a very small study specific imputation reference panel performing very strongly in an isolate; particularly for rare variants. For many complex traits, there exist discordances between estimates of heritabilities from studies in closely related individuals and from studies on unrelated individuals. In particular, we noted that most researchers consider dominant (non-additive) genetic effects as unlikely to play a significant role despite contrasting results from previous studies on isolates. Our second analysis revealed possible mechanisms to explain such disparate published heritability estimates between isolated populations and general populations. This allowed us to make interesting deductions from our own heritability analyses of the Cilento dataset, including an indication of a non-null dominance component involved in the distribution of low-density lipoprotein level measurements (LDL). This led us to perform genome-wide association analyses of additive and non-additive components for LDL in Cilento and we were able to identify genes that had been previously linked to the trait in other studies. In the contexts of both of our studies, we observed the importance of retaining genotype uncertainty (genotype dosage following imputation or genotype likelihoods from sequencing data). As a prospective of this thesis, we have proposed ways to incorporate this uncertainty into certain methods used in this project. Our findings for imputation strategies and heritability analysis will be highly valuable for the continued study of the isolate of Cilento but will also be instructive to researchers working on other isolated populations and also applicable to the study of complex diseases in general
Rossin, Elizabeth Jeffries. "The Proteomic Landscape of Human Disease: Construction and Evaluation of Networks Associated to Complex Traits." Thesis, Harvard University, 2012. http://dissertations.umi.com/gsas.harvard:10514.
Full textXin, Xiachi. "Architecture of human complex trait variation." Thesis, University of Edinburgh, 2018. http://hdl.handle.net/1842/31549.
Full textChan, Ying Leong. "Leveraging genetic association data to investigate the polygenic architecture of human traits and diseases." Thesis, Harvard University, 2014. http://dissertations.umi.com/gsas.harvard:11372.
Full textBernhardsson, Carolina. "Molecular population genetics of inducible defense genes in Populus tremula." Doctoral thesis, Umeå universitet, Institutionen för ekologi, miljö och geovetenskap, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-54361.
Full textInteraktioner mellan växter och herbivorer är bland de vanligaste ekologiska interaktionerna och det är därför inte förvånande att växter har utvecklat flera olika mekanismer för att försvara sig. Dessa försvarsmekanismer består både av konstitutiva kemiska och fysiska barriärer så väl som inducerade försvar som bara är uttryckta efter att en växt har blivit skadad genom betning. Herbivorerna å sin sida svarar på dessa försvar genom att utveckla motanpassningar som gör växternas försvar mindre effektiva eller till och med verkningslösa. Dessa anpassningar kan ske över olika geografiska skalor beroende på om de samevolutionära interaktionerna varierar i ett rumsligt heterogent landskap. Genom att studera de underliggande gener som kontrollerar dessa försvarsegenskaper tillsammans med herbivorrelaterade fenotypiska egenskaper är det möjligt att undersöka den samevolutionära historien av interaktionerna mellan växter och herbivorer. Här använder jag mig av molekylärpopulationsgenetiska verktyg för att undersöka den evolutionära historien i flera inducerade försvarsgener hos asp (Populus tremula) i Sverige. Två gener, som tillhör genfamiljen Polyphenol-oxidaser (PPO1 och PPO2), uppvisar ett frekvensmönster som man förväntar sig vid positiv selektion. Detta mönster kan också ses i dessa geners diversitet samt i divergens från en utgrupp (Uppsats II). 71 ”single nucleotide polymorphisms” (SNPar) från 7 inducerade försvarsgener (PPO1-PPO3, TI2-TI5) visar förhöjda nivåer av populationsdifferentiering jämfört med kontrollgener (gener som inte är involverade i trädens försvar), och 10 av dessa försvars-SNPar visar även tecken på naturlig selektion (Uppsats III). Dessa 71 försvars-SNPar delar in ett urval av svenska aspar i tre distinkta geografiska grupper som beskriver ett sydligt, centralt och nordligt kluster som inte förekommer hos kontroll-SNPar (Uppsats III). Samma geografiska mönster, med ett distinkt nordligt kluster, återfinns däremot i ett antal fenotypiska egenskaper som är relaterade till herbivori i ett odlingsförsök utanför Sävar (Uppsats IV). Dessa fenotypiska egenskaper visar tecken på lokal felanpassning hos herbivorsamhället till den lokala värdpopulationen, vilket kan indikera förekomsten av ett ”samevolutionärt informationsutbyte” mellan växter och herbivorer (Uppsats IV). 15 unika försvars-SNPar påvisar också signifikanta associationer med 8 olika fenotypiska egenskaper, men om dessa har en verklig effekt eller inte är svårt att säga på grund av den geografiska strukturen som förekommer både hos de underliggande generna och hos de fenotypiska egenskaperna. Att denna populationsstruktur förekommer hos både försvarsgener och egenskaper som är förknippade med herbivorsamhället kan däremot vara ett resultat av historiska händelser som skett under aspens post-glaciala återkolonisation av Sverige.
Benchek, Penelope H. "How Extensive of a Role do Gene-gene Interactions Play in the GeneticArchitecture of Complex Traits?" Case Western Reserve University School of Graduate Studies / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=case1485511511496427.
Full textStahl, Bethany A. "Regressive Evolution of Pigmentation in the Blind Mexican Cavefish Astyanax mexicanus." University of Cincinnati / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1439281730.
Full textSmallbone, Willow. "The impact of Major Histocompatibility Complex composition on fitness and life history traits of a vertebrate model, the guppy (Poecilia reticulata)." Thesis, Cardiff University, 2017. http://orca.cf.ac.uk/108113/.
Full textFreudenthal, Jan Alexander [Verfasser], and Thomas [Gutachter] Schmitt. "Quantitative genetics from genome assemblies to neural network aided omics-based prediction of complex traits / Jan Alexander Freudenthal ; Gutachter: Thomas Schmitt." Würzburg : Universität Würzburg, 2020. http://d-nb.info/1204831718/34.
Full textBlomquist, Thomas M. "Development of Bimodal Gene Expression Analysis and Allele-Specific Competitive PCR for Investigation of Complex Genetic Traits, Lung Cancer Risk." University of Toledo Health Science Campus / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=mco1277151230.
Full textJoshi, Shreyas. "IDENTIFICATION OF NOVEL SLEEP RELATED GENES FROM LARGE SCALE PHENOTYPING EXPERIMENTS IN MICE." UKnowledge, 2017. http://uknowledge.uky.edu/biology_etds/42.
Full textFinucane, Hilary Kiyo. "Functional and cross-trait genetic architecture of common diseases and complex traits." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/112906.
Full textCataloged from PDF version of thesis.
Includes bibliographical references (pages 201-245).
In this thesis, I introduce new methods for learning about diseases and traits from genetic data. First, I introduce a method for partitioning heritability by functional annotation from genome-wide association summary statistics, and I apply it to 17 diseases and traits and many different functional annotations. Next, I show how to apply this method to use gene expression data to identify diseaserelevant tissues and cell types. I next introduce a method for estimating genetic correlation from genome-wide association summary statistics and apply it to estimate genetic correlations between all pairs of 24 diseases and traits. Finally, I consider a model of disease subtypes and I show how to determine a lower bound on the sample size required to distinguish between two disease subtypes as a function of several parameters.
by Hilary Kiyo Finucane.
Ph. D.
Ph.D. Massachusetts Institute of Technology, Department of Mathematics
Forsberg, Simon. "Complex Trait Genetics : Beyond Additivity." Doctoral thesis, Uppsala universitet, Institutionen för medicinsk biokemi och mikrobiologi, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-307837.
Full textHemani, Gibran. "Dissecting genetic interactions in complex traits." Thesis, University of Edinburgh, 2012. http://hdl.handle.net/1842/6472.
Full textSaint, Pierre Aude. "Méthodes d'analyse génétique de traits quantitatifs corrélés : application à l'étude de la densité minérale osseuse." Phd thesis, Université Paris Sud - Paris XI, 2011. http://tel.archives-ouvertes.fr/tel-00633981.
Full textSharma, Pankaj. "Genetic dissection of complex traits : essential hypertension." Thesis, University of Cambridge, 1998. https://www.repository.cam.ac.uk/handle/1810/275234.
Full textGroves-Kirkby, Nick. "Genetic analysis of variation in complex traits." Thesis, University of Oxford, 2016. https://ora.ox.ac.uk/objects/uuid:4541c4e4-4538-4348-bb4b-0df6673344d2.
Full textNorth, Teri-Louise. "Genetic epidemiological and population genetic studies of complex ageing traits." Thesis, University of Bristol, 2015. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.685359.
Full textTang, Ling-fung Paul, and 鄧凌鋒. "Dissecting the genetics of complex trait in mouse: an attempt using public resources and in-houseknockout." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2010. http://hub.hku.hk/bib/B43572170.
Full textModin, Helena. "Multiple sclerosis : linkage analysis and DNA variation in a complex trait /." Stockholm, 2004. http://diss.kib.ki.se/2004/91-7349-792-4/.
Full textWu, Song. "A robust approach for genetic mapping of complex traits." [Gainesville, Fla.] : University of Florida, 2008. http://purl.fcla.edu/fcla/etd/UFE0022399.
Full textMacdonald, Stuart J. "Evolutionary and genomic analyses of complex traits in Drosophila." Thesis, University of Oxford, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.365832.
Full textSalfati, Elias Levy Itshak. "Genetic determinants of cardiovascular disease : heritability and genetic risk score." Thesis, Paris 5, 2014. http://www.theses.fr/2014PA05S014/document.
Full textComplex diseases such as cardiovascular disease (CVD) are influenced by both genetic and environmental factors. Estimation of an individual’s cardiovascular risk usually involves measurement of risk factors correlated with risk of CVD (e.g. age, sex, smoking, blood pressure, and total cholesterol). Lately, several biomarkers have been evaluated for their ability to improve prediction of cardiovascular disease beyond traditional risk factors. The interest in novel loci is propelled notably by emerging discoveries from the advent of genome-Wide association studies (GWAS) of genetic variants associated with risk for common diseases. GWAS has greatly enhanced our knowledge of the genetic architecture of cardiovascular disease, yielding over 50 variants confirmed to be associated with CVD to date, as well as over 200 associated with traditional cardiovascular risk factors (e.g. lipids, blood pressure, body mass index, and type 2 diabetes mellitus). This recent and continuing success in discovering increasing numbers of robustly associated genetic markers has led to reassessment of whether genetic data can provide clinically useful information by refining risk prediction and moderating disease risk through a more efficient application of prevention strategies. In this thesis, we first address novel approach to survey the genetic architecture of hypertension (i.e. major risk factor for premature CVD), then construct risk prediction models for coronary artery disease (CAD; i.e. most common type of CVD) and finally establish a common genetic basis of the strongest predictor of clinical complications of CAD, subclinical atherosclerosis, to add incremental prognostic value above traditional risk scores across a range of ages. We show that, for first visit measurements, the heritability is ~25%/~45% and ~30%/~37% for systolic (SBP) and diastolic blood pressure (DBP) in European (N=8,901) and African (N=2,860) ancestry individuals from the Atherosclerosis Risk in Communities (ARIC) cohort, respectively, in accord with prior studies. Then we present a means to combine a polygenic risk score - genetic effects among an ensemble of markers - with an independent assessment of clinical risk using a log-Link function. We apply the method to the prediction of coronary heart disease (CHD) in the ARIC cohort. The addition of a genetic risk score (GRS) to a clinical risk score (CRS) improves both discrimination and calibration for CHD in ARIC and subsequently reveal how this genetic information influences risk assessment and thus potentially clinical management. Finally, Among 1561 cases and 5068 controls, from several clinical and genetic datasets available through the NCBI's database of Genotypes and Phenotypes (dbGAP), we found a one SD increase in the genetic risk score of 49 CAD SNPs was associated with a 28% increased risk of having advanced subclinical coronary atherosclerosis (p = 1.43 x 10-16). This increase in risk was significant in every 15-Year age stratum (.01 > p > 9.4 x 10-7) and was remarkably similar across all age strata (p test of heterogeneity = 0.98). We obtained near identical results and levels of significance when we restricted the genetic risk score to 32 SNPs not associated with traditional risk factors. Accordingly, common variation largely recapitulates the known heritability of blood pressure traits. The vast majority of this heritability varies by chromosome, depending on its length, and is largely concentrated in intronic and intergenic regions of the genome but widely distributed across the common allele frequency spectrum. Respectively, our proposed method to combine genetic information at established susceptibility loci with a nongenetic risk prediction tool facilitates the standardized incorporation of a GRS in risk assessment. (...)
Abecasis, G. R. "Methods for fine mapping complex traits in human pedigrees." Thesis, University of Oxford, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.365700.
Full textMahjani, Behrang. "Methods from Statistical Computing for Genetic Analysis of Complex Traits." Doctoral thesis, Uppsala universitet, Avdelningen för beräkningsvetenskap, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-284378.
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Besnier, Francois. "Development of Variance Component Methods for Genetic Dissection of Complex Traits." Doctoral thesis, Uppsala universitet, Centrum för bioinformatik, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-101399.
Full textCabrera, Cárdenas Claudia Paola. "Bioinformatics tools for the genetic dissection of complex traits in chickens." Thesis, University of Edinburgh, 2009. http://hdl.handle.net/1842/3864.
Full textLangley, Sarah Raye. "Modelling genetic and genomic interactions underlying gene expression and complex traits." Thesis, Imperial College London, 2013. http://hdl.handle.net/10044/1/10925.
Full textOnkamo, Päivi. "Genetic mapping of complex traits : the case of Type 1 diabetes." Helsinki : University of Helsinki, 2002. http://ethesis.helsinki.fi/julkaisut/mat/rolfn/vk/onkamo/.
Full textBroadley, Simon Andrew. "The genetic analysis of a complex trait : multiple sclerosis." Thesis, University of Cambridge, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.620291.
Full textO'Connor, Christine. "Dissecting the Genetic Architecture of Complex Traits in the Nematode Caenorhabditis remanei." Thesis, University of Oregon, 2018. http://hdl.handle.net/1794/23756.
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Manet, Caroline. "Genetic control of susceptibility to Zika virus in the mouse using strains of the Collaborative Cross." Thesis, Paris, Institut agronomique, vétérinaire et forestier de France, 2019. http://www.theses.fr/2019IAVF0029.
Full textZika virus (ZIKV) is a mosquito-transmitted flavivirus responsible for worldwide epidemics and constitutes a major public health threat. The majority of ZIKV infections in humans are either asymptomatic or result in a mild febrile illness. However, some patients develop a more severe, sometimes life-threatening, form of the disease. Recent evidence showed that ZIKV infection can trigger Guillain-Barré syndrome and encephalitis in adults, as well as congenital malformations such as microcephaly. The severity of ZIKV disease in humans depends on many factors, likely including host genetic determinants.We investigated how genome-wide variants could impact the susceptibility to ZIKV infection in mice. To this end, we used mouse strains of the Collaborative Cross (CC), a new genetic reference population encompassing a genetic diversity as broad as that of human populations.First, we described that the susceptibility of Ifnar1 (receptor to type I interferon) knockout mice is largely influenced by their genetic background. We then showed that the genetic diversity of CC mice, which IFNAR was blocked by anti-IFNAR antibody, expressed phenotypes ranging from complete resistance to severe symptoms and death with large variations in the peak and rate of decrease of plasma viral load, in brain viral load, in brain histopathology and in viral replication rate in infected cells. Differences of susceptibility between CC strains were correlated between Zika, Dengue and West Nile viruses. We identified highly susceptible and resistant CC strains as new models to investigate the mechanisms of human ZIKV disease and other flavivirus infections. Genetic analyses revealed that phenotypic variations were driven by multiple genes with small effects, reflecting the complexity of ZIKV disease susceptibility in human population. Notably, our results also ruled out a role of the Oas1b gene in the susceptibility to ZIKV.In a second part, we searched for genes which modify the susceptibility of Ifnar1 knockout mice in an F2 cross between C57BL/6J and 129S2/SvPas mice harboring the mutation. Genetic analysis revealed two Quantitative Trait Locus (QTL) controlling either the peak viremia or the mouse survival. Although these QTLs critical intervals contained hundreds of genes, data mining led us to identify a few candidate causal genes.Then, we investigated how host genetic factors influence viral replication in infected cells using Mouse Embryonic Fibroblasts (MEFs) derived from a series of CC strains with contrasted phenotypes observed in response to ZIKV infection in vivo. MEFs from CC071 strain displayed unique features of increased viral replication rate in late infection. Using transcriptomic analysis, we demonstrated that the phenotype of CC071 infected MEFs resulted from a delayed induction of the type I interferon (IFN) response. Genetic analyses ruled out single gene deficiencies but rather suggested combined effects of multiple factors in the type I IFN induction signaling pathway.Finally, we characterized the ZIKV-induced type I IFN response in MEFs and primary neurons derived from C57BL/6J mouse strain. Primary neurons were less capable than MEFs to control the viral replication due to a delayed IFN response. We later showed that host genetic factors also play a critical role in this context as ZIKV-infected CC071 primary neurons displayed an extreme phenotype compared to neurons from strains that are more resistant.Altogether, our work has unraveled the role of host genes in the pathogeny of ZIKV infection and illustrates the potential of CC mouse strains for genetic studies and as new models of infectious diseases. Extensive analysis of CC strains with extreme phenotypes help us elucidate how genetic variants affect susceptibility as well as immune responses to flaviviral infection and will provide deeper understanding of the pathophysiology of human ZIKV disease
Luo, Yuqun. "Incorporation of Genetic Marker Information in Estimating Modelparameters for Complex Traits with Data From Large Complex Pedigrees." The Ohio State University, 2002. http://rave.ohiolink.edu/etdc/view?acc_num=osu1039109696.
Full textDahlgren, Andreas. "Analysis of Complex Genetic Traits in Population Cohorts using High-throughput Genotyping Technology." Doctoral thesis, Uppsala : Acta Universitatis Upsaliensis : Universitetsbiblioteket [distributör], 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-8291.
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