Thèses : « Genomic analysi »

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DI, CANITO ALESSANDRA. « Genomic and functional analysis of Rhodococcus strains to identify genes and degradative functions for soil quality evaluation ». Doctoral thesis, Università degli Studi di Milano-Bicocca, 2019. http://hdl.handle.net/10281/241307.

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La qualità del suolo è una delle principali problematiche ambientali degli ultimi decenni a causa dell’aumento dell’inquinamento antropico. In condizioni di stress, i microrganismi del suolo subiscono alterazioni che attraverso tecnologie molecolari possono essere usate come parametro per il monitoraggio dei siti contaminati. I batteri appartenenti al genere Rhodococcus hanno un ruolo importante nella degradazione dei composti più recalcitranti. Sono versatili ed ampiamente distribuiti in natura; essi degradano diversi composti organici, tra cui idrocarburi alifatici ed aromatici, eterociclici, nitrili, sulfuri ed erbicidi. Inoltre, essi possono sopravvivere in presenza di composti tossici, carenza di carbonio, irradiazione UV e stress osmotico. Questa versatilità è correlata alla complessità dei loro genomi, i quali contengono molteplici geni catabolici, ridondanza genica e un sofisticato network regolatorio. L’obiettivo di questo progetto è ottenere nuovi tools molecolari da ceppi di Rhodococcus da usare come marcatori per valutare la qualità dei suoli, mediante analisi dei pathway metabolici e dei cluster genici coinvolti nella degradazione dei contaminanti ambientali. In questo lavoro, l’attenzione è stata rivolta verso i genomi dei ceppi: R. opacus R7, R. aetherivorans BCP1 e R. erythropolis MI2. Un’analisi fenotipica ha permesso di valutare il potenziale metabolico e la risposta allo stress dei ceppi R7 e BCP1; sono stati testati diversi contaminanti (idrocarburi alifatici e cicloalcani, aromatici, policiclici aromatici, acidi naftenici ed altri acidi carbossilici) e varie condizioni di stress (alta osmolarità, differenti valori di pH, composti tossici, antibiotici). Un approccio genomico ha permesso di correlare le abilità metaboliche a determinanti genici, coinvolti nei diversi metabolismi (naftalene, o-xilene, n-alcani, acidi naftenici, fenoli, ftalato) e nella persistenza ambientale. In particolare, sono stati esaminati i pathway degradativi dell’o-xilene e degli acidi naftenici di R. opacus R7. Analisi bioinformatiche e molecolari hanno permesso di valutare il coinvolgimento di diversi geni nei pathway degradativi. R7 è in grado di degradare l’o-xilene inducendo la trascrizione dei geni akb (sistema diossigenasico) formando il diidrodiolo. Tuttavia, la ridondanza di monossigenasi e idrossilasi (prmA and pheA1A2A3), ha suggerito l’attivazione di altri sistemi convergenti, strategia utilizzata dai rhodococci per degradare composti recalcitranti e persistere in ambienti contaminati. I pathway degradativi degli acidi naftenici (NAs) non sono ancora noti ma sono state proposte due possibili vie: i) aromatizzazione dell’anello del cicloesano ii) attivazione come CoA tioestere. I risultati delle RT e RT-qPCR hanno mostrato che R7 degrada l’acido cicloesanocarbossilico (CHCA), attraverso una cicloesano carbossilato-CoA ligasi (aliA). L’applicazione di questo lavoro è stata dimostrata in esperimenti di microcosmo simulando condizioni reali con sabbia bioaugmentata con R7. Le capacità dei batteri autoctoni e di R7 di degradare il CHCA sono state comparate e i risultati mostrano che R7 degrada il contaminante più velocemente rispetto alla comunità microbica e che il suo contributo aumenta la velocità di degradazione del CHCA, seguita monitorando l’espressione del gene aliA mediante esperimenti di RT e RT-qPCR. Un’applicazione biotecnologica di questo lavoro è stata valutata in R. erythropolis MI2, studiando il pathway di degradazione del 4,4’- acido disolfuro ditiobutirrico (DTDB), un promettente substrato per la sintesi dei politioesteri poiché il suo intermedio metabolico, acido 4-mercaptobutirrico ne è un precursore. L’obiettivo di questo studio è stato perseguito generando mutanti di delezione del ceppo MI2 per i geni coinvolti nelle reazioni finali del pathway di degradazione.
Soil quality has been one of the major issues of the last decades, because of the increase of anthropogenic pollution. Soil contains organisms involved in vital functions (nutrient/hydrological cycles and degradation of toxic compounds). Under stress conditions, soil microorganisms undergo several alterations so molecular technologies use microbial communities as an ecological parameter in monitoring polluted sites. Bacteria belonging to Rhodococcus genus have an important role in recalcitrant compound degradations. It is a metabolically versatile genus, widely distributed in nature. Rhodococcus spp. can degrade a wide range of organic compounds (aliphatic/aromatic hydrocarbons, heterocyclic, nitriles, sulfuric, herbicides) and to survive in presence of toxic compounds, carbon starvation, UV irradiation and osmotic stress. In line with their catabolic diversity, they possess large and complex genomes, containing a multiplicity of catabolic genes, high genetic redundancy and a sophisticated regulatory network. The aim of this project is to obtain molecular tools to use as "marker" sequences for soil assessment, through analysis of metabolic pathways and catabolic gene clusters involved in the degradation of the most diffused environmental contaminants. In particular, this work focused the attention on three Rhodococcus strain genomes: R. opacus R7, R. aetherivorans BCP1 and R. erythropolis MI2. A Phenotype Microarray approach was used to evaluate R7 and BCP1 strains metabolic potential and their stress response. Also, the capability to utilize various contaminants (aliphatic hydrocarbons and cycloalkanes, aromatic compounds, polycyclic aromatic compounds, naphthenic acids and other carboxylic acids) and to persist under stress conditions (high osmolarity, pH stress, toxic compounds, antibiotics) was tested. A genome-based approach was used to relate their abilities to genetic determinants involved in the analysed metabolisms (naphthalene, o-xylene, n-alkanes, naphthenic acids, phenols, phthalate) and in their environmental persistence. In particular, o-xylene and naphthenic acids degradations were investigated in R. opacus R7. Computational and molecular analyses revealed the putative involvement of several genes in these degradation pathways. R7 can degrade o-xylene by the induction of the akb genes (deoxygenation) producing the corresponding dihydrodiol. Likewise, the redundancy of sequences encoding for monooxygenases/hydroxylases (prmA and pheA1A2A3), supports the involvement of other genes that induce the formation of phenols, converging to the phenol oxidation path. The activation of converging oxygenase systems represents a strategy in Rhodococcus genus to degrade recalcitrant compounds and to persist in contaminated environments. NAs degradation pathway is not fully clear but two main routes have been proposed: i) aromatization of the cyclohexane ring ii) activation as CoA thioester. RT and RT-qPCR results showed that R. opacus R7 degrade cyclohexanecarboxylic acid (CHCA) molecule (used as a model) by a cyclohexane carboxylate CoA ligase (aliA). An application of this work was demonstrated by a microcosm approach, simulating a bioaugmentation process with R7 strain. Autochthone bacteria and R7 capabilities to degrade CHCA were evaluated and compared; results indicated that R7 can degrade the contaminant faster than the microbial community and that its contribute increased CHCA degradation rate. The degradation rate was followed by RT and RT-qPCR, monitoring the expression of the aliA gene. Moreover, a biotechnological application was investigated in R. erythropolis MI2, studying the disulfide 4,4-dithiodibutyric acid (DTDB) degradation pathway. DTDB is a promising substrate for polythioester (PTE) synthesis; indeed, its degradation produces the PTE building block 4-mercaptobutyric acid. The aim was pursued generating R. erythropolis MI2 marker-free deletion mutants for genes involved in the final steps of the pathway.

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Wong, Chi-fat, et 黃志發. « Genome sequencing and comparative genomic analysis of Pseudomonas mendocina DLHK ». Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2012. http://hdl.handle.net/10722/197162.

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Nitrogen oxides are targeted as important gas pollutants to be eliminated. Biological removal of nitrogen oxides, like the use of bio-trickling reactor, is gaining popularity over conventional methods. A bacterium isolated from a bio-trickling reactor showing high performance in removing nitrogen oxides was identified to be Pseudomonas mendocina. The genome of this isolate was sequenced using 454 pyrosequencing technology to a high level of completeness with 33 contigs and N50 contig length of 273 kbp. The genome was annotated by Prokaryotic Genome Automatic Annotaion Pipeline (PGAAP)and the strain was named P. mendocina DLHK. Examination of P. mendocina DLHK genome annotation found nitrate reductase but not nitrite reductase, nitric oxide reductase and nitrous oxide reductase. Novel genes or pathways might be available in P. mendocina DLHK contributingits denitrification function in the bio-trickling reactor. To better understand the evolution of Pseudomonas, a comprehensive comparative study was performed. Genomes of the Pseudomonasgenus were reannotated. Core genes were extracted to construct a phylogenomic tree using supermatrix approach. Effectiveness of using single phylogenetic marker in constructing phylogeny of Pseudomonas was evaluated using rpoB gene marker. Both methods generated phylogenetic trees of very similar topology, suggesting that rpoB gene can be a very effective marker in the rapid construction of Pseudomonas phylogeny.It is surprising to note that Azotobacter vinelandii DJ was included in the large clade of Pseudomonas and have the closest relationship with P. stutzeri in both phylogenetic trees, providing evidence that this species should be reclassified into the genus Pseudomonas. Cluster of Orthologous Groups (COG)category distribution of all pseudomonads were analysed for physiological significance. The large amount of gene categorised into the COG for amino acid metabolism and transcription may imply the importance for these 2 functions on the survival of pseudomonads. It is again surprising to note the COG distribution pattern of A. vinelandii DJ is different from other pseudomonads, especially to its closest phylogenetic neighbour P. stutzeri. Horizontal gene transfer events inpseudomonads were investigated because of its importance in prokaryotic evolution. The high congruence of the phylogemonic tree to most core genes suggests that the phylogenomic tree is a good piece of evidence describing the evolution of pseudomonads. It is a bit surprising to observe that quite a number of core genes may have exhibited horizontal gene transfer which show incongruence of the gene tree to the core genes. The impact of horizontal gene transfer events on the functionality and evolution of pseudomonads remains to be investigated.
published_or_final_version
Biological Sciences
Master
Master of Philosophy

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Bertoldi, Loris. « Bioinformatics for personal genomics : development and application of bioinformatic procedures for the analysis of genomic data ». Doctoral thesis, Università degli studi di Padova, 2018. http://hdl.handle.net/11577/3421950.

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In the last decade, the huge decreasing of sequencing cost due to the development of high-throughput technologies completely changed the way for approaching the genetic problems. In particular, whole exome and whole genome sequencing are contributing to the extraordinary progress in the study of human variants opening up new perspectives in personalized medicine. Being a relatively new and fast developing field, appropriate tools and specialized knowledge are required for an efficient data production and analysis. In line with the times, in 2014, the University of Padua funded the BioInfoGen Strategic Project with the goal of developing technology and expertise in bioinformatics and molecular biology applied to personal genomics. The aim of my PhD was to contribute to this challenge by implementing a series of innovative tools and by applying them for investigating and possibly solving the case studies included into the project. I firstly developed an automated pipeline for dealing with Illumina data, able to sequentially perform each step necessary for passing from raw reads to somatic or germline variant detection. The system performance has been tested by means of internal controls and by its application on a cohort of patients affected by gastric cancer, obtaining interesting results. Once variants are called, they have to be annotated in order to define their properties such as the position at transcript and protein level, the impact on protein sequence, the pathogenicity and more. As most of the publicly available annotators were affected by systematic errors causing a low consistency in the final annotation, I implemented VarPred, a new tool for variant annotation, which guarantees the best accuracy (>99%) compared to the state-of-the-art programs, showing also good processing times. To make easy the use of VarPred, I equipped it with an intuitive web interface, that allows not only a graphical result evaluation, but also a simple filtration strategy. Furthermore, for a valuable user-driven prioritization of human genetic variations, I developed QueryOR, a web platform suitable for searching among known candidate genes as well as for finding novel gene-disease associations. QueryOR combines several innovative features that make it comprehensive, flexible and easy to use. The prioritization is achieved by a global positive selection process that promotes the emergence of the most reliable variants, rather than filtering out those not satisfying the applied criteria. QueryOR has been used to analyze the two case studies framed within the BioInfoGen project. In particular, it allowed to detect causative variants in patients affected by lysosomal storage diseases, highlighting also the efficacy of the designed sequencing panel. On the other hand, QueryOR simplified the recognition of LRP2 gene as possible candidate to explain such subjects with a Dent disease-like phenotype, but with no mutation in the previously identified disease-associated genes, CLCN5 and OCRL. As final corollary, an extensive analysis over recurrent exome variants was performed, showing that their origin can be mainly explained by inaccuracies in the reference genome, including misassembled regions and uncorrected bases, rather than by platform specific errors.
Nell’ultimo decennio, l’enorme diminuzione del costo del sequenziamento dovuto allo sviluppo di tecnologie ad alto rendimento ha completamente rivoluzionato il modo di approcciare i problemi genetici. In particolare, il sequenziamento dell’intero esoma e dell’intero genoma stanno contribuendo ad un progresso straordinario nello studio delle varianti genetiche umane, aprendo nuove prospettive nella medicina personalizzata. Essendo un campo relativamente nuovo e in rapido sviluppo, strumenti appropriati e conoscenze specializzate sono richieste per un’efficiente produzione e analisi dei dati. Per rimanere al passo con i tempi, nel 2014, l’Università degli Studi di Padova ha finanziato il progetto strategico BioInfoGen con l’obiettivo di sviluppare tecnologie e competenze nella bioinformatica e nella biologia molecolare applicate alla genomica personalizzata. Lo scopo del mio dottorato è stato quello di contribuire a questa sfida, implementando una serie di strumenti innovativi, al fine di applicarli per investigare e possibilmente risolvere i casi studio inclusi all’interno del progetto. Inizialmente ho sviluppato una pipeline per analizzare i dati Illumina, capace di eseguire in sequenza tutti i processi necessari per passare dai dati grezzi alla scoperta delle varianti sia germinali che somatiche. Le prestazioni del sistema sono state testate mediante controlli interni e tramite la sua applicazione su un gruppo di pazienti affetti da tumore gastrico, ottenendo risultati interessanti. Dopo essere state chiamate, le varianti devono essere annotate al fine di definire alcune loro proprietà come la posizione a livello del trascritto e della proteina, l’impatto sulla sequenza proteica, la patogenicità, ecc. Poiché la maggior parte degli annotatori disponibili presentavano errori sistematici che causavano una bassa coerenza nell’annotazione finale, ho implementato VarPred, un nuovo strumento per l’annotazione delle varianti, che garantisce la migliore accuratezza (>99%) comparato con lo stato dell’arte, mostrando allo stesso tempo buoni tempi di esecuzione. Per facilitare l’utilizzo di VarPred, ho sviluppato un’interfaccia web molto intuitiva, che permette non solo la visualizzazione grafica dei risultati, ma anche una semplice strategia di filtraggio. Inoltre, per un’efficace prioritizzazione mediata dall’utente delle varianti umane, ho sviluppato QueryOR, una piattaforma web adatta alla ricerca all’interno dei geni causativi, ma utile anche per trovare nuove associazioni gene-malattia. QueryOR combina svariate caratteristiche innovative che lo rendono comprensivo, flessibile e facile da usare. La prioritizzazione è raggiunta tramite un processo di selezione positiva che fa emergere le varianti maggiormente significative, piuttosto che filtrare quelle che non soddisfano i criteri imposti. QueryOR è stato usato per analizzare i due casi studio inclusi all’interno del progetto BioInfoGen. In particolare, ha permesso di scoprire le varianti causative dei pazienti affetti da malattie da accumulo lisosomiale, evidenziando inoltre l’efficacia del pannello di sequenziamento sviluppato. Dall’altro lato invece QueryOR ha semplificato l’individuazione del gene LRP2 come possibile candidato per spiegare i soggetti con un fenotipo simile alla malattia di Dent, ma senza alcuna mutazione nei due geni precedentemente descritti come causativi, CLCN5 e OCRL. Come corollario finale, è stata effettuata un’analisi estensiva su varianti esomiche ricorrenti, mostrando come la loro origine possa essere principalmente spiegata da imprecisioni nel genoma di riferimento, tra cui regioni mal assemblate e basi non corrette, piuttosto che da errori piattaforma-specifici.

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Mungall, Christopher. « Next-generation information systems for genomics ». Thesis, University of Edinburgh, 2011. http://hdl.handle.net/1842/5020.

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The advent of next-generation sequencing technologies is transforming biology by enabling individual researchers to sequence the genomes of individual organisms or cells on a massive scale. In order to realize the translational potential of this technology we will need advanced information systems to integrate and interpret this deluge of data. These systems must be capable of extracting the location and function of genes and biological features from genomic data, requiring the coordinated parallel execution of multiple bioinformatics analyses and intelligent synthesis of the results. The resulting databases must be structured to allow complex biological knowledge to be recorded in a computable way, which requires the development of logic-based knowledge structures called ontologies. To visualise and manipulate the results, new graphical interfaces and knowledge acquisition tools are required. Finally, to help understand complex disease processes, these information systems must be equipped with the capability to integrate and make inferences over multiple data sets derived from numerous sources. RESULTS: Here I describe research, design and implementation of some of the components of such a next-generation information system. I first describe the automated pipeline system used for the annotation of the Drosophila genome, and the application of this system in genomic research. This was succeeded by the development of a flexible graphoriented database system called Chado, which relies on the use of ontologies for structuring data and knowledge. I also describe research to develop, restructure and enhance a number of biological ontologies, adding a layer of logical semantics that increases the computability of these key knowledge sources. The resulting database and ontology collection can be accessed through a suite of tools. Finally I describe how the combination of genome analysis, ontology-based database representation and powerful tools can be combined in order to make inferences about genotype-phenotype relationships within and across species. CONCLUSION: The large volumes of complex data generated by high-throughput genomic and systems biology technology threatens to overwhelm us, unless we can devise better computing tools to assist us with its analysis. Ontologies are key technologies, but many existing ontologies are not interoperable or lack features that make them computable. Here I have shown how concerted ontology, tool and database development can be applied to make inferences of value to translational research.

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Chen, Yuansha. « Comparative genomic analysis of Vibrio cholerae O31 capsule, O-antigen, pathogenesis and genome / ». College Park, Md. : University of Maryland, 2006. http://hdl.handle.net/1903/4112.

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Thesis (Ph. D.) -- University of Maryland, College Park, 2006.
Thesis research directed by: Marine-Estuarine-Environmental Sciences. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.

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Danks, Jacob R. « Algorithm Optimizations in Genomic Analysis Using Entropic Dissection ». Thesis, University of North Texas, 2015. https://digital.library.unt.edu/ark:/67531/metadc804921/.

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In recent years, the collection of genomic data has skyrocketed and databases of genomic data are growing at a faster rate than ever before. Although many computational methods have been developed to interpret these data, they tend to struggle to process the ever increasing file sizes that are being produced and fail to take advantage of the advances in multi-core processors by using parallel processing. In some instances, loss of accuracy has been a necessary trade off to allow faster computation of the data. This thesis discusses one such algorithm that has been developed and how changes were made to allow larger input file sizes and reduce the time required to achieve a result without sacrificing accuracy. An information entropy based algorithm was used as a basis to demonstrate these techniques. The algorithm dissects the distinctive patterns underlying genomic data efficiently requiring no a priori knowledge, and thus is applicable in a variety of biological research applications. This research describes how parallel processing and object-oriented programming techniques were used to process larger files in less time and achieve a more accurate result from the algorithm. Through object oriented techniques, the maximum allowable input file size was significantly increased from 200 mb to 2000 mb. Using parallel processing techniques allowed the program to finish processing data in less than half the time of the sequential version. The accuracy of the algorithm was improved by reducing data loss throughout the algorithm. Finally, adding user-friendly options enabled the program to use requests more effectively and further customize the logic used within the algorithm.

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Sinha, Amit U. « Discovery and analysis of genomic patterns applications to transcription factor binding and genome rearrangement / ». Cincinnati, Ohio : University of Cincinnati, 2008. http://www.ohiolink.edu/etd/view.cgi?1204227723.

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Thesis (Ph.D.)--University of Cincinnati, 2008.
Advisor: Raj Bhatnagar. Title from electronic thesis title page (viewed April 24, 2008). Keywords: computational biology; bioinformatics; transcription factor; genome rearrangement. Includes abstract. Includes bibliographical references.

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Morlot, Jean-Baptiste. « Annotation of the human genome through the unsupervised analysis of high-dimensional genomic data ». Thesis, Paris 6, 2017. http://www.theses.fr/2017PA066641/document.

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Le corps humain compte plus de 200 types cellulaires différents possédant une copie identique du génome mais exprimant un ensemble différent de gènes. Le contrôle de l'expression des gènes est assuré par un ensemble de mécanismes de régulation agissant à différentes échelles de temps et d'espace. Plusieurs maladies ont pour cause un dérèglement de ce système, notablement les certains cancers, et de nombreuses applications thérapeutiques, comme la médecine régénérative, reposent sur la compréhension des mécanismes de la régulation géniques. Ce travail de thèse propose, dans une première partie, un algorithme d'annotation (GABI) pour identifier les motifs récurrents dans les données de séquençage haut-débit. La particularité de cet algorithme est de prendre en compte la variabilité observée dans les réplicats des expériences en optimisant le taux de faux positif et de faux négatif, augmentant significativement la fiabilité de l'annotation par rapport à l'état de l'art. L'annotation fournit une information simplifiée et robuste à partir d'un grand ensemble de données. Appliquée à une base de données sur l'activité des régulateurs dans l'hématopoieïse, nous proposons des résultats originaux, en accord avec de précédentes études. La deuxième partie de ce travail s'intéresse à l'organisation 3D du génome, intimement lié à l'expression génique. Elle est accessible grâce à des algorithmes de reconstruction 3D à partir de données de contact entre chromosomes. Nous proposons des améliorations à l'algorithme le plus performant du domaine actuellement, ShRec3D, en permettant d'ajuster la reconstruction en fonction des besoins de l'utilisateur
The human body has more than 200 different cell types each containing an identical copy of the genome but expressing a different set of genes. The control of gene expression is ensured by a set of regulatory mechanisms acting at different scales of time and space. Several diseases are caused by a disturbance of this system, notably some cancers, and many therapeutic applications, such as regenerative medicine, rely on understanding the mechanisms of gene regulation. This thesis proposes, in a first part, an annotation algorithm (GABI) to identify recurrent patterns in the high-throughput sequencing data. The particularity of this algorithm is to take into account the variability observed in experimental replicates by optimizing the rate of false positive and false negative, increasing significantly the annotation reliability compared to the state of the art. The annotation provides simplified and robust information from a large dataset. Applied to a database of regulators activity in hematopoiesis, we propose original results, in agreement with previous studies. The second part of this work focuses on the 3D organization of the genome, intimately linked to gene expression. This structure is now accessible thanks to 3D reconstruction algorithm from contact data between chromosomes. We offer improvements to the currently most efficient algorithm of the domain, ShRec3D, allowing to adjust the reconstruction according to the user needs

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SINHA, AMIT U. « Discovery and Analysis of Genomic Patterns : Applications to Transcription Factor Binding and Genome Rearrangement ». University of Cincinnati / OhioLINK, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1204227723.

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Schiavo, Giuseppina <1986&gt. « Analysis of the pig genome for the identification of genomic regions affecting production traits ». Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2015. http://amsdottorato.unibo.it/6919/1/Schiavo_Giuseppina_Tesi_Dottorato_XVII_ciclo.pdf.

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The aim of this work was to identify markers associated with production traits in the pig genome using different approaches. We focused the attention on Italian Large White pig breed using Genome Wide Association Studies (GWAS) and applying a selective genotyping approach to increase the power of the analyses. Furthermore, we searched the pig genome using Next Generation Sequencing (NSG) Ion Torrent Technology to combine selective genotyping approach and deep sequencing for SNP discovery. Other two studies were carried on with a different approach. Allele frequency changes for SNPs affecting candidate genes and at Genome Wide level were analysed to identify selection signatures driven by selection program during the last 20 years. This approach confirmed that a great number of markers may affect production traits and that they are captured by the classical selection programs. GWAS revealed 123 significant or suggestively significant SNP associated with Back Fat Thickenss and 229 associated with Average Daily Gain. 16 Copy Number Variant Regions resulted more frequent in lean or fat pigs and showed that different copies of those region could have a limited impact on fat. These often appear to be involved in food intake and behavior, beside affecting genes involved in metabolic pathways and their expression. By combining NGS sequencing with selective genotyping approach, new variants where discovered and at least 54 are worth to be analysed in association studies. The study of groups of pigs undergone to stringent selection showed that allele frequency of some loci can drastically change if they are close to traits that are interesting for selection schemes. These approaches could be, in future, integrated in genomic selection plans.

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Schiavo, Giuseppina <1986&gt. « Analysis of the pig genome for the identification of genomic regions affecting production traits ». Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2015. http://amsdottorato.unibo.it/6919/.

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The aim of this work was to identify markers associated with production traits in the pig genome using different approaches. We focused the attention on Italian Large White pig breed using Genome Wide Association Studies (GWAS) and applying a selective genotyping approach to increase the power of the analyses. Furthermore, we searched the pig genome using Next Generation Sequencing (NSG) Ion Torrent Technology to combine selective genotyping approach and deep sequencing for SNP discovery. Other two studies were carried on with a different approach. Allele frequency changes for SNPs affecting candidate genes and at Genome Wide level were analysed to identify selection signatures driven by selection program during the last 20 years. This approach confirmed that a great number of markers may affect production traits and that they are captured by the classical selection programs. GWAS revealed 123 significant or suggestively significant SNP associated with Back Fat Thickenss and 229 associated with Average Daily Gain. 16 Copy Number Variant Regions resulted more frequent in lean or fat pigs and showed that different copies of those region could have a limited impact on fat. These often appear to be involved in food intake and behavior, beside affecting genes involved in metabolic pathways and their expression. By combining NGS sequencing with selective genotyping approach, new variants where discovered and at least 54 are worth to be analysed in association studies. The study of groups of pigs undergone to stringent selection showed that allele frequency of some loci can drastically change if they are close to traits that are interesting for selection schemes. These approaches could be, in future, integrated in genomic selection plans.

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Olivares, Chauvet Pedro. « Multi-scale analysis of chromosome and nuclear architecture ». Thesis, University of Manchester, 2013. https://www.research.manchester.ac.uk/portal/en/theses/multiscale-analysis-of-chromosome-and-nuclear-architecture(32a7b634-035b-4c6b-83f9-735f83bc73fb).html.

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Mammalian nuclear function depends on the complex interaction of genetic and epi-genetic elements coordinated in space and time. Structure and function overlap to such a degree that they are usually considered as being inextricably linked. In this work I combine an experimental approach with a computational one in order to answer two main questions in the field of mammalian chromosome organization. In the first section of this thesis, I attempted to answer the question, to what extent does chromatin from different chromosome territories share the same space inside the nucleus? This is a relatively open question in the field of chromosome territories. It is well-known and accepted that interphase chromosomes are spatially constrained inside the nucleus and that they occupy their own territory, however, the degree of spatial interaction between neighbouring chromosomes is still under debate. Using labelling methods that directly incorporate halogenated DNA precursors into newly replicated DNA without the need for immuno-detection or in situ hybridization, we show that neighbouring chromosome territories colocalise at very low levels. We also found that the native structure of DNA foci is partially responsible for constraining the interaction of chromosome territories as disruption of the innate architecture of DNA foci by treatment with TSA resulted in increased colocalisation signal between adjacent chromosomes territories. The second major question I attempted to answer concerned the correlation between nuclear function and the banding pattern observed in human mitotic chromosomes. Human mitotic chromosomes display characteristic patterns of light and dark bands when visualized under the light microscope using specific chemical dyes such as Giemsa. Despite the long standing use of the Giemsa banding pattern in human genetics for identifying chromosome abnormalities and mapping genes, little is known about the molecular mechanisms that generate the Giemsa banding pattern or its biological relevance. The recent availability of many genetic and epigenetic features mapped to the human genome permit a high-resolution investigation of the molecular correlates of Giemsa banding. Here I investigate the relationship of more than 50 genomic and epigenomic features with light (R) and dark (G) bands. My results confirm many classical results, such as the low gene density of the most darkly staining G bands and their late replication time, using genome-wide data. Surprisingly, I found that for virtually all features investigated, R bands show intermediate properties between the lightest and darkest G bands, suggesting that many R bands contain G-like sequences within them. To identify R bands that show properties of G bands, I employed an unsupervised learning approach to classify R bands on their genomic and epigenomic properties and show that the smallest R bands show a tendency to have characteristics typical of G bands. I revisit the evidence supporting the boundaries of G and R bands in the current cytogenomic map and conclude that inaccurate placement of weakly supported band boundaries can explain the intermediate pattern of R bands. Finally, I propose an approach based on aggregating data from multiple genomic and epigenomic features to improve the positioning of band boundaries in the human cytogenomic map. My results suggest that contiguous domains showing a high degree of uniformity in the ratio of heterochromatin and euchromatin sub-domains define the Giemsa banding pattern in human chromosomes.

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Ng, Esther. « Integration of genetic data and genomic annotation in the analysis of genome wide association studies ». Thesis, University of Oxford, 2017. https://ora.ox.ac.uk/objects/uuid:fd0d2dab-d52c-4d8c-9321-5e88628bf528.

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This thesis explored the utility of genome wide association studies (GWAS) and meta-analysis to identify variants associated with serum pollutants levels and metabolic phenotypes. The secondary aims of these thesis were to annotate these variants with regulatory information from databases and to investigate the role of copy number variation in influencing gene expression and phenotype. In the second and third chapters, we identified single nucleotide polymorphisms (SNPs) associated with pollutant and metabolic phenotypes. An example of a novel association was the relationship between SNPs in the ABCG2 gene and octachlorodibenzo-p-dioxin (OCDD). In the third chapter, we identified associations between metabolic phenotypes and SNPs. An example of an identified association was that between serum apolipoprotein B levels and rs7412, which is consistent with other GWAS. To fine map these loci and assign functional annotation, I created Bayesian credible sets and checked for overlap between SNPs in these credible sets and regulatory marks in the Encyclopaedia of DNA Elements (ENCODE) database. Annotating these credible set SNPs with functional information revealed various histone modifications and transcription factors that overlapped. This study was also successful in identifying copy number variants (CNVs) from the PIVUS cohort. There were moderately strong associations between CNVs and some of the phenotypes studied. These associations did not appear to be mediated by the SNP within the CNVs, as the latter had higher P values of associations. In addition, I identified several clinically relevant CNV-expression quantitative trait loci (CNV-eQTL) associations a separate cohort of healthy individuals. Some of these associations were cell specific and/or context specific. Many of these CNVs contained SNPs which are lead SNPs in GWAS studies on a variety of different phenotypes. In conclusion, this thesis was successful in identifying SNPs and CNVs associated with phenotypes, as well as annotating some of these variants with regulatory information. Further work is needed to clarify the mechanisms of regulation.

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Santos-Silva, Alan Roger 1981. « Analise das caracteristicas clinico-patologicas e da ploidia do DNA em pacientes jovens com carcinoma espinocelular de lingua : um estudo colaborativo internacional ». [s.n.], 2010. http://repositorio.unicamp.br/jspui/handle/REPOSIP/287850.

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Orientador: Marcio Ajudarte Lopes
Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Odontologia de Piracicaba
Made available in DSpace on 2018-08-15T17:55:17Z (GMT). No. of bitstreams: 1 Santos-Silva_AlanRoger_D.pdf: 1071923 bytes, checksum: 996d56a5e4895653ebcd0b9e1636e7e2 (MD5) Previous issue date: 2010
Resumo: Predominantemente, o carcinoma espinocelular (CEC) de boca afeta pacientes idosos e com frequência se desenvolve em associação com o consumo de fumo e álcool. Todavia, evidências científicas têm sugerido o aumento da incidência desta malignidade em pacientes com menos de 40 anos de idade e não expostos aos tradicionais fatores de risco. Informações disponíveis referentes ao câncer de boca em pacientes jovens são escassas e controversas, dificultando a compreensão da patogênese, do comportamento biológico e do prognóstico destes tumores. Como consequência, seu tratamento tem sido baseado principalmente na experiência profissional de cada centro médico. Este trabalho teve como objetivos estudar as características demográficas, os fatores de risco e os aspectos clínicos no momento do diagnóstico, além do perfil biológico de CECs de língua em pacientes com até 40 anos. Foi realizada uma análise retrospectiva multiinstitucional a fim de se investigar gênero, cor da pele, consumo de tabaco e álcool, tamanho dos tumores, metástase regional e à distância, diferenciação histológica e ploidia do DNA dos tumores por meio de citometria por imagem. Os resultados mostraram que tumores em pacientes jovens foram frequentemente detectados em mulheres e pacientes não fumantes e não etilistas, enquanto em pacientes idosos foram detectados, predominantemente, em homens fumantes e etilistas. Além disso, constatou-se que CECs de língua em jovens não se distinguem quanto ao tamanho, a metástases regionais ou à distância e nem quanto ao grau de diferenciação histológica quando comparados com idosos. Ressalta-se, entretanto, que tumores em jovens apresentaram maiores incidências de aneuploidia, tetraploidia e de outros parâmetros de anormalidades da ploidia do DNA. Concluindo, pacientes jovens com CEC de língua apresentaram perfil clínico e biológico peculiares, favorecendo a hipótese de que pacientes jovens com CEC de boca possuem instabilidade genômica aumentada e indicando uma possível natureza genética diferente entre os CECs de língua de jovens e de idosos
Abstract: Oral squamous cell carcinoma (SCC) predominately affects elderly patients and frequently develops in association with tobacco and alcohol consumption. However, an increasing of this malignant disease has been observed in patients younger than 40 years of age, who are not exposed to the traditional risk factors. Data regarding oral cancer in young patients are scarce and controversial, making the determination of the pathogenesis, biological behaviour and prognosis of these tumours difficult. As a consequence, treatment has been mainly based on the professional experience of each medical centre. The aims of this work were to study demographic features, risk factors and clinical aspects at the moment of diagnosis as well as the biologic profile of patients of less than 40 years of age with tongue SCC. A multi-centre retrospective analysis was performed to investigate gender, race, tobacco consumption and alcohol intake, size of the tumour, regional and distant metastasis, histological differentiation and DNA ploidy of tumours through image cytometry. Tumours in young patients were frequently detected in females and nonsmoking and non-drinking patients while older patients were predominantly smoking and drinking males. In addition, tongue SCC in young patients did not differ in size, regional and distant metastasis or tumour grade of differentiation when compared to those in older patients. This study highlighted that tumours from young patients presented higher incidences of aneuploidy, tetraploidy and other parameters related to DNA ploidy abnormalities. In conclusion, young patients with tongue SCC presented a distinct clinical and biological profile, favouring the hypothesis that young patients with oral SCC may have an increased genomic instability and indicating the possibility of underlying genetic differences between TSCC in young and older patients
Doutorado
Patologia
Doutor em Estomatopatologia

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Jiang, Sheng. « Application of nested PCR, whole genome amplification and comparative genomic hybridisation for single cell genetic analysis ». Thesis, University of Glasgow, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.366140.

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Glen, McGillivary. « Comparative Genomic Analysis Between the Haemophilus influenzae biogroup aegyptius Brazilian Purpuric Fever Invasive Strain F3031 and the Haemophilus influenzae biogroup aegyptius Non-invasive Strain F1947 ». Miami University / OhioLINK, 2004. http://rave.ohiolink.edu/etdc/view?acc_num=miami1088607238.

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Kittler, Ralf. « Functional genomic analysis of cell cycle progression in human tissue culture cells ». Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2006. http://nbn-resolving.de/urn:nbn:de:swb:14-1161253856455-48321.

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The eukaryotic cell cycle orchestrates the precise duplication and distribution of the genetic material, cytoplasm and membranes to daughter cells. In multicellular eukaryotes, cell cycle regulation also governs various organisatorial processes ranging from gametogenesis over multicellular development to tissue formation and repair. Consequently, defects in cell cycle regulation provoke a variety of human cancers. A global view of genes and pathways governing the human cell cycle would advance many research areas and may also deliver novel cancer targets. Therefore this work aimed on the genome-wide identification and systematic characterisation of genes required for cell cycle progression in human cells. I developed a highly specific and efficient RNA interference (RNAi) technology to realize the potential of RNAi for genome-wide screening of the genes essential for cell cycle progression in human tissue culture cells. This approach is based on the large-scale enzymatic digestion of long dsRNAs for the rapid and cost-efficient generation of libraries of highly complex pools of endoribonuclease-prepared siRNAs (esiRNAs). The analysis of the silencing efficiency and specificity of esiRNAs and siRNAs revealed that esiRNAs are as efficient for mRNA degradation as chemically synthesized siRNA designed with state-of-the-art design algorithms, while exhibiting a markedly reduced number of off-target effects. After demonstrating the effectiveness of this approach in a proof-of-concept study, I screened a genome-wide esiRNA library and used three assays to generate a quantitative and reproducible multi-parameter profile for the 1389 identified genes. The resulting phenotypic signatures were used to assign novel cell cycle functions to genes by combining hierarchical clustering, bioinformatics and proteomic data mining. This global perspective on gene functions in the human cell cycle presents a framework for the systematic documentation necessary for the understanding of cell cycle progression and its misregulation in diseases. The identification of novel genes with a role in human cell cycle progression is a starting point for an in-depth analysis of their specific functions, which requires the validation of the observed RNAi phenotype by genetic rescue, the study of the subcellular localisation and the identification of interaction partners of the expressed protein. One strategy to achieve these experimental goals is the expression of RNAi resistant and/or tagged transgenes. A major obstacle for transgenesis in mammalian tissue culture cells is the lack of efficient homologous recombination limiting the use of cultured mammalian cells as a real genetic system like yeast. I developed a technology circumventing this problem by expressing an orthologous gene from a closely related species including its regulatory sequences carried on a bacterial artificial chromosome (BAC). This technology allows physiological expression of the transgene, which cannot be achieved with conventional cDNA expression constructs. The use of the orthologous gene from a closely related species confers RNAi resistance to the transgene allowing the depletion of the endogenous gene by RNAi. Thus, this technology mimics homologous recombination by replacing an endogenous gene with a transgene while maintaining normal gene expression. In combination with recombineering strategies this technology is useful for RNAi rescue experiments, protein localisation and the identification of protein interaction partners in mammalian tissue culture cells. In summary, this thesis presents a major technical advance for large-scale functional genomic studies in mammalian tissue culture cells and provides novel insights into various aspects of cell cycle progression. (Die Druckexemplare enthalten jeweils eine CD-ROM als Anlagenteil: 217 MB: Movies, Rohdaten - Nutzung: Referat Informationsvermittlung der SLUB)

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Selman, Mohammed. « Genomic Analysis of Encephalitozoon Species ». Thèse, Université d'Ottawa / University of Ottawa, 2013. http://hdl.handle.net/10393/30314.

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Microsporidia are obligate intracellular pathogens of medical and ecological importance whose genomes have been studied extensively over the last decade. Their parasitic lifestyle has lead them to lose a great number of genes and, thus, biochemical pathways capacities, but these reductive processes have been often offset by the acquisition of several genes by means of horizontal gene transfer (HGT). First, in this thesis, we will describe the complete genomes of Encephalitozoon hellem and Encephalitozoon romaleae. Both species also were found to harbor a number of protein-coding genes absent in other microsporidia, which products assembled complete metabolic pathways. All these genes are functionally related to DNA and folate metabolism, and all appear to have been acquired from HGT events from different eukaryotic and prokaryotic donors. Interestingly in E. romaleae genes involved in de novo synthesis of folate are all pseudogenes, highlighting the transient nature of transferred genes. Secondly, we took a closer look at the ploidy and sexual status of Encephalitozoon cuniculi, a vertebrate pathogen, by mapping Illumina sequence reads against the genomes of four strains of this species. We identified the presence of low level of heterozygosity in all strains investigated; a feature that revealed the diploid nuclear state of the species. This reductive intra-individual genetic diversity could result from the long-term propagation of these strains under laboratory conditions, but we propose that it could also reflect an intrinsic capacity of these vertebrate pathogens to self-reproduce. Overall, the work presented in this thesis resulted in a much greater understanding of the genome evolution of a medically and economically important group of parasites.

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Tam, Mandy Chi-Mun. « Genomic analysis of mouse tumorigenesis ». Thesis, Massachusetts Institute of Technology, 2006. http://hdl.handle.net/1721.1/37454.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Biology, 2006.
Includes bibliographical references.
The availability of the human and mouse genome sequences has spurred a growing interest in analyzing mouse models of human cancer using genomic techniques. Comparative genomic studies on mouse and human tumors can be valuable in two major ways: in validating mouse models and in identifying genes that are common to mouse and human tumorigenesis. Many analytic tools have emerged in recent years for human genome mining. Some of these tools have been translated to the murine versions. The work in this thesis described the application of two new whole-genome analytic techniques to study mouse tumorigensis: Representational Oligonucleotide Microarray Analysis (ROMA) for tumor DNA copy number asessment and single nucleotide polymorphism (SNP) genotyping using the SNaPshotM system (Applied Biosystems) to detect loss of heterozygosity (LOH) in mouse tumors. The murine version of ROMA was tested on DNA from early-stage KrasGJ2D-derived lung cancers and metastatic retinoblastoma in mice with retinal-specific Rb and p130 deletions. We were interested in identifying the additional genetic lesions that got positively selected during tumorigenesis of these mice.
(cont.) Several recurrent chromosomal copy number gains and losses were observed in the DNA of KrasGJ2D-derived lung tumors. In addition, a focal amplification of the murine N-Myc locus was detected in the metastatic retinoblastomas, demonstrating the capability of ROMA to detect copy number changes at a single-gene resolution. For genome-wide allelotyping, a panel of 147 mouse SNPs were individually validated in 129S4/SvJae vs. C57BL/6J strains and were chosen as markers in the genotyping panel. We worked out a multiplex protocol to genotype the SNPs in an efficient manner. Through this protocol, we generated low-density global LOH maps of lung tumors from mice expressing KrasG12D. LOH that spanned entire chromosomes was seen in a subset of the tumors. A loss of the wild-type p53 allele was also observed in some cases.
by Mandy Chi-Mun Tam.
Ph.D.

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Revilla, Sánchez Manuel. « Genomic and functional genomic analysis of fatty acid composition in swine ». Doctoral thesis, Universitat Autònoma de Barcelona, 2017. http://hdl.handle.net/10803/405710.

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El cerdo es una de las principales fuentes de carne consumida por el hombre y las preferencias de los consumidores hacia productos de alta calidad han aumentado durante los últimos años. Por lo tanto, conocer los mecanismos moleculares que afectan a la producción y a la calidad de esta carne ayudaría a la selección de estos caracteres. La calidad de la carne está determinada en gran medida por la composición de los ácidos grasos (AG) y la comprensión de los procesos moleculares subyacentes a éstos son el objetivo general de esta tesis. En este trabajo, se han identificado QTLs en el cromosoma 8 porcino (SSC8) para la composición de AG en grasa dorsal (GD) y se han identificado dos regiones cromosómicas con SNPs asociados, localizadas a 93 y 119 Mb. Las señales estadísticamente más significativas para ambas regiones se observaron para el ácido palmitoleico y los índices C18:0/C16:0 y C18:1(n-7)/C16:1(n-7). Los genes MAML3 y SETD7 fueron estudiados como genes candidatos posicionales para la región localizada a 93 Mb. Los dos nuevos microsatélites analizados en el gen MAML3 y el SNP del gen SETD7 (SETD7:c.700G>T) no mostraron las asociaciones más significativas en esta región, descartando estos polimorfismos como las mutaciones causales. Además, en la región localizada a 119 Mb, el SNP ELOVL6:c.-533C>T mostró la asociación más significativa con el porcentaje de los ácidos palmítico y palmitoleico y los índices de elongación en GD. Los resultados obtenidos para el gen ELOVL6, gen candidato posicional del QTL localizado a 119 Mb refuerzan la hipótesis de su efecto pleiotrópico sobre la composición de AG en GD y en músculo, y su papel en la determinación del QTL del SSC8 para el perfil de AG. Por otra parte, se utilizaron datos del genoma completo de cerdos ibéricos y landrace para identificar 1.279 variaciones en el número de copias (CNV), las cuales se fusionaron en 540 regiones de CNVs (CNVRs). El impacto de cuatro de ellas fue estudiado para caracteres de crecimiento y composición de AG. Se encontró asociación con la longitud de la canal y la composición de AG en grasa intramuscular y GD para el CNVR112. Este CNVR contiene el gen GPAT2 que cataliza la biosíntesis de triglicéridos y glicerofosfolípidos. Los resultados obtenidos subrayan la importancia de los CNVRs en la determinación de caracteres económicamente importantes en el cerdo. Finalmente, se analizó la expresión de 44 genes candidatos relacionados con el metabolismo lipídico en 115 animales. El estudio de asociación genómico con los datos de expresión (eGWAS) identificó 193 eSNPs localizados en 19 eQTLs. Tres de los eQTLs correspondientes a los genes ACSM5, FABP4 y FADS2 se clasificaron como cis-eQTLs; mientras que los 16 eQTLs restantes mostraron efectos reguladores en trans. Estos hallazgos, junto con los polimorfismos evaluados para alguno de estos genes, mejoran nuestro conocimiento sobre los mecanismos funcionales implicados en la variación de los caracteres relacionados con la calidad de la carne porcina.
Pork is one of the main sources of human-consumed meat and consumer’s preference towards high quality meat is increasing. Hence, understanding the molecular mechanisms affecting meat production and quality would help in the selection of these traits. Meat quality is determined largely by its fatty acid (FA) composition and understanding the underlying molecular processes of FA composition is the general objective of this thesis. We analyzed quantitative trait loci (QTL) on porcine chromosome 8 (SCC8) for FA composition in backfat, identifying two trait-associated SNP regions at 93 Mb and 119 Mb. The strongest statistical signals for both regions were observed for palmitoleic acid and, C18:0/C16:0 and C18:1(n-7)/C16:1(n-7) elongation ratios. MAML3 and SETD7 genes were analyzed as positional candidate genes in the 93 Mb region. The two novel microsatellites analyzed in the MAML3 gene, and the SETD7:c.700G>T SNP in the SETD7 gene did not show the strongest signal in this region, discarding these polymorphisms as the causal mutations. Furthermore, in the 119 Mb region, the ELOVL6:c.-533C>T SNP showed a strong association with the percentage of palmitic and palmitoleic acids and elongation ratios in backfat. These results for ELOVL6 gene, support the hypothesis that it has a pleiotropic effect in backfat and muscle for the 119 Mb QTL, and reinforce this gene as a strong candidate for the SSC8 QTL for FA composition. Moreover, whole genome sequence (WGS) data from Iberian and Landrace pigs were used to identify 1,279 copy number variations (CNVs), merging into 540 swine CNV regions (CNVRs). The impact of four of them in growth and FA composition in intramuscular fat and backfat was studied. Association with carcass length and FA composition in backfat and intramuscular fat was showed for the CNVR112, containing the GPAT2 gene which catalyse the biosynthesis of triglycerides and glycerophospholipids. These results underline the importance of CNVRs affecting economically important traits in pigs. Finally, the adipose tissue mRNA expression of 44 candidate genes related with lipid metabolism was analyzed in 115 animals. The expression genome-wide association (eGWAS) identified 193 eSNPs located in 19 expression QTLs (eQTLs). Three out of 19 eQTLs corresponding to ACSM5, FABP4, and FADS2 were classified as cis-acting eQTLs, whereas the remaining 16 eQTLs had trans-regulatory effects. These findings and the polymorphisms evaluated for some of these genes provide new data to further understand the functional mechanisms implicated in the variation of meat quality traits in pigs.

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Lorentzen, Marc. « Diversity and genomic characteristics of Oenococcus oeni ». Thesis, Bordeaux, 2018. http://www.theses.fr/2018BORD0428.

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Oenococcus oeni est une espèce de bactérie lactique adaptée à l'environnement hostile de la fermentation du vin. Elle montre un degré de spécialisation remarquable face au stress provoqué par le faible pH et la forte teneur en éthanol, ce qui lui permet de proliférer là où la plupart des bactéries ne survivent pas. Cette bactérie est très importante dans la production de vin, car elle réalise la fermentation malolactique, qui se produit après la fermentation alcoolique, et au cours de laquelle l'acide malique est métabolisé en acide lactique et où le vin est désacidifié. L'espèce accumule des mutations plus vite que les autres espèces de bactéries lactiques, ce qui a probablement accéléré le processus de domestication. Son degré de spécialisation a été démontré par la présence de populations spécifiques adaptées aux vins rouges ou aux vins blancs dans la même région. Dans cette étude, nous avons utilisé des approches de séquençage haut débit et de génomique pour élucider la diversité des souches d’O. oeni, identifier leurs caractéristiques génomiques et mesurer leur dispersion dans différents environnements ainsi que leur dynamique au cours des fermentations. En raison de son importance pour la vinification, plusieurs centaines de souches ont été isolées et séquencées. Dans ce travail, nous avons augmenté la collection de génomes en séquençant des souches de cidre et de kombucha et en effectuant des analyses phylogénétiques afin de clarifier la structure de la population de l'espèce. En calculant un pangénome à l'échelle de l'espèce, nous avons effectué une analyse génomique comparative afin d'explorer des gènes spécifiques à une ou plusieurs sous-populations. Avec le séquençage de nouvelle génération, nous avons produit des génomes entièrement circularisés à partir des principales sous-populations et analysé leurs arrangements génomiques. Ces nouveaux génomes ont été annotés avec de nouveaux pipelines automatiques et une curation manuelle pour la première fois depuis la publication du génome de référence PSU-1. L’évolution des communautés bactériennes au cours de la fermentation, du moût de raisin au vin fini, a été examinée par le séquençage de fragments 16S dans quatre exploitations du bordelais. À l’aide d’amorces universelles et spécifiques, nous avons comparé la biodiversité des espèces dans des vins issus d’agriculture biologique ou conventionnelle. De plus, en se basant sur les groupes phylogénétiques de souches d’O. oeni nouvellement définis, nous avons développé une méthode de qPCR pour analyser la dispersion des groupes de souches d’O. oeni et leur dynamique au cours des fermentations. Cette nouvelle méthode a également été utilisée pour analyser la diversité des souches d’O. oeni dans les vins de base de Cognac et au cours de la production de cidre, deux produits qui se distinguent des productions de vins traditionnels par la non-utilisation de sulfites. Les deux autres espèces du genre Oenococcus, O. kitaharae et O. alcoholitolerans, se retrouvent également dans les environnements de boissons fermentées. O. kitaharae ne possède pas de gène malolactique fonctionnel, mais O. alcoholitolerans, découvert plus récemment, serait capable de réaliser la réaction malolactique. Nous l’avons caractérisée, ainsi que sa tolérance aux facteurs de stress de l'environnement vin. Constatant qu'elle était incapable de survivre dans le vin, nous avons produit un génome entièrement circularisé d'O. alcoholitolerans et effectué une analyse de génomique comparative afin d'identifier les gènes d'O. oeni lui permettant de tolérer le pH et l'éthanol, ce qui manque à O. alcoholitolerans et à O. kitaharae. En conclusion, nous avons utilisé les nouvelles technologies de séquençage de nouvelle génération pour produire des génomes de haute qualité et effectuer des analyses comparatives approfondies à l’échelle de l’espèce qui nous ont permis d’identifier des gènes susceptibles d’expliquer l’adaptation d’O. oeni à l’environnement
Oenococcus oeni is a lactic acid bacteria species adapted to the inhospitable environment of fermenting wine, where it shows a remarkable degree of specialization to the stress of low pH and high ethanol that allows it to proliferate where most bacteria fail to survive. The bacteria is supremely important in wine production, because it carries out malolactic fermentation, a process that occurs after alcoholic fermentation, where malic acid is metabolised into lactic acid and the pH of the wine is raised. The species has only a small genome and accumulates mutations several orders of magnitude faster than other lactic acid bacteria due to a loss of DNA mismatch repair genes. This has likely sped up the process of domestication to wine. The degree of specialization has been demonstrated by finding specific populations adapted to red or white wines in the same region. In this study, we used high throughput sequencing and genomics approaches to elucidate the diversity of O. oeni strains, to identify their genomic characteristics and measure their dispersion in different environments as well as their dynamics during fermentation. Because of its importance to wine-making, several hundred strains have been isolated and sequenced. In this work, we have expanded upon the collection of genomes by sequencing strains from cider and kombucha and performing phylogenetic analyses to clarify the population structure of the species. By calculating a species-wide pangenome, we performed comparative genomics to explore gene clusters that were specific to one or more sub-populations. With next generation sequencing, we produced fully circularized genomes from the major sub-populations and analysed their genomic arrangements. These new genomes were annotated with new, automatic pipelines and manual curation for the first time since the publication of the reference genome PSU-1. The evolution of bacterial communities over the course of fermentation, from grape must to finished wine, was examined with 16S amplicon sequencing in four Bordeaux wineries. Using a universal and a specific primer-set, we compared the biodiversity in wines resulting from organic or conventional farming practices. In addition, with the newly defined phylogenetic groups, we developed a qPCR experiment to detail the composition of O. oeni in the fermentations and cemented the dispersal of even rarely isolated strain sub-populations in grape must. This new method was also used to analyse the diversity of O. oeni strains in the base wines of Cognac and during the production of cider, two products that are distinguished from traditional wine production by not using sulfite. The two other species in the Oenococcus genus, kitaharae and alcoholitolerans, are also found in the environments of fermenting beverages. O. kitaharae does not have a functional malolactic gene, but the more recently discovered O. alcoholitolerans was thought capable of performing the malolactic reaction. We characterized this, as well as the species tolerance for the stressors of the wine environment. Finding it unable to survive in wine, we produced a fully circularized genome of O. alcoholitolerans and performed a comparative genomics analysis to identify the O. oeni genes that enable it to tolerate the pH and ethanol, which O. alcoholitolerans and O. kitaharae lacks. In conclusion, we have used the new technologies of next generation sequencing to produce high-quality genomes and performed extensive, species-wide comparative analyses that allowed us to identify patterns in gene presence that provide likely explanations for environmental adaptation

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Roberts, Nicola Diane. « Patterns of somatic genome rearrangement in human cancer ». Thesis, University of Cambridge, 2018. https://www.repository.cam.ac.uk/handle/1810/275454.

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Cancer development is driven by somatic genome alterations, ranging from single point mutations to larger structural variants (SV) affecting kilobases to megabases of one or more chromosomes. Studies of somatic rearrangement have previously been limited by a paucity of whole genome sequencing data, and a lack of methods for comprehensive structural classification and downstream analysis. The ICGC project on the Pan-Cancer Analysis of Whole Genomes provides an unprecedented opportunity to analyse somatic SVs at base-pair resolution in more than 2500 samples from 30 common cancer types. In this thesis, I build on a recently developed SV classification pipeline to present a census of rearrangement across the pan-cancer cohort, including chromoplexy, replicative two-jumps, and templated insertions connecting as many as eight distant loci. By identifying the precise structure of individual breakpoint junctions and separating out complex clusters, the classification scheme empowers detailed exploration of all simple SV properties and signatures. After illustrating the various SV classes and their frequency across cancer types and samples, Chapter 2 focuses on structural properties including event size and breakpoint homology. Then, in Chapter 3, I consider the SV distribution across the genome, and show patterns of association with various genome properties. Upon examination of rearrangement hotspot loci, I describe tissue-specific fragile site deletion patterns, and a variety of SV profiles around known cancer genes, including recurrent templated insertion cycles affecting TERT and RB1. Turning to co-occurring alteration patterns, Chapter 4 introduces the Hierarchical Dirichlet Process as a non-parametric Bayesian model of mutational signatures. After developing methods for consensus signature extraction, I detour to the domain of single nucleotide variants to test the HDP method on real and simulated data, and to illustrate its utility for simultaneous signature discovery and matching. Finally, I return to the PCAWG SV dataset, and extract SV signatures delineated by structural class, size, and replication timing. In Chapter 5, I move on to the complex SV clusters (largely set aside throughout Chapters 2—4) , and develop an improved breakpoint clustering method to subdivide the complex rearrangement landscape. I propose a raft of summary metrics for groups of five or more breakpoint junctions, and explore their utility for preliminary classification of chromothripsis and other complex phenomena. This comprehensive study of somatic genome rearrangement provides detailed insight into SV patterns and properties across event classes, genome regions, samples, and cancer types. To extrapolate from the progress made in this thesis, Chapter 6 suggests future strategies for addressing unanswered questions about complex SV mechanisms, annotation of functional consequences, and selection analysis to discover novel drivers of the cancer phenotype.

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Polke, James. « Functional genomics in the stroke-prone spontaneously hypertensive rat genome wide and candidate gene analysis / ». Connect to e-thesis, 2008. http://theses.gla.ac.uk/258/.

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Thesis (Ph.D.) - University of Glasgow, 2008.
Ph.D. thesis submitted to the Faculty of Medicine, Division of Cardiovascular and Medical Sciences, University of Glasgow, 2008. Includes bibliographical references. Print version also available.

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Polke, James M. « Functional genomics in the stroke-prone spontaneously hypertensive rat : genome wide and candidate gene analysis ». Thesis, University of Glasgow, 2008. http://theses.gla.ac.uk/258/.

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The stroke-prone spontaneously hypertensive rat (SHRSP) is an inbred model of hypertension. Renal microarrays and functional genomic strategies investigated chromosome 2 candidate hypertension genes, focussing on the oxidative-stress defence gene, glutathione s-transferse mu type 1 (Gstm1). Ingenuity pathway analysis of renal microarrays in 5 and 16-week SHRSP, normotensive Wistar Kyoto (WKY) and chromosome 2 congenic rats identified differential expression of several glutathione cycling genes. The Gstm1 promoter was investigated by luciferase and Transfac bioinformatic analysis, implicating two polymorphism clusters and several transcription factors in reduced SHRSP Gstm1 expression. Recombinant adenoviruses expressing Gstm1 and short-hairpin RNA-interference sequences to reduce Gstm family expression were produced. In-vivo overexpression of Gstm1 did not improve endothelial nitric-oxide bioavailability in SHRSP carotid arteries. Bacterial artificial chromosome and linear expression constructs were purified for production of Gstm1 transgenic rats, putative transgenic rats were screened by PCR. The strategies developed in this project are an example of thorough functional genomic analysis in experimental hypertension research.

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Tennant, Peter Andrew. « Genome editing using site-specific nucleases : targeting highly expressed genomic regions for robust transgene expression and genetic analysis ». Thesis, University of Edinburgh, 2016. http://hdl.handle.net/1842/22857.

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Integration and expression of exogenous genetic material – in particular, transgenes – into the genomes of model organisms, cell lines or patients is widely used for the creation of genetically modified experimental systems and gene therapy. However, loss of transgene expression due to silencing is still a major hurdle which remains to be overcome. Judicious selection of integration loci can help alleviate the risk of silencing; in recent years the ability to efficiently and specifically target transgene integration has been improved by the advent of site-specific nucleases (SSNs). SSNs can be used to generate double strand breaks (DSBs) in a targeted manner, which increases the efficiency of homologous recombination (HR) mediated transgene integration into predetermined loci. In this work I investigate four human genomic loci for their potential to act as transgene integration sites which will support robust long term expression: the adeno-associated virus (AAV) integration site 1 (AAVS1); the human homologue of the mouse Rosa26 locus (hROSA26); the inosine monophosphate dehydrogenase 2 (IMPDH2) gene and the eukaryotic translation elongation factor 1 alpha 1 (EEF1A1) gene. I also investigate the potential of creating a novel drug-selectable transgene integration system at the IMPDH2 locus to allow for rapid and specific selection of correctly inserted transgenes. In addition to their ability to drive targeted transgene integration, SSNs can be harnessed to specifically disrupt gene function through indel formation following erroneous repair of the induced DSB. Using this strategy, I aimed to answer some important biological questions about eukaryotic translation elongation factor 1 alpha (eEF1A); eEF1A is responsible for providing aminoacylated tRNAs to the ribosome during the elongation phase of protein synthesis. Humans and other vertebrates express two isoforms, eEF1A1 and eEF1A2 (encoded by EEF1A1 and EEF1A2 respectively). During development eEF1A1 is replaced by eEF1A2 in some tissues. The reasons for this remain elusive, but one explanation may lie in the moonlighting functions of eEF1A1, which may not be shared by eEF1A2. Additionally, eEF1A2 can act as an oncogene, while there is no evidence that eEF1A1 is overexpressed in tumours. To begin to untangle these issues I targeted EEF1A1 using SSNs with the aim of making a cell line expressing only the eEF1A2 isoform. This work suggests that eEF1A1 may be essential even in the presence of eEF1A2, though further studies will be required to confirm this.

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Shaw, Daniel 1993. « Streamlining minimal bacterial genomes : Analysis of the pan bacterial essential genome, and a novel strategy for random genome deletions in Mycoplasma pneumoniae ». Doctoral thesis, Universitat Pompeu Fabra, 2019. http://hdl.handle.net/10803/668244.

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Understanding what constitutes a true Minimal Cell is a key challenge in synthetic biology. In this work, we present two new tools to aid in this endeavour. i) A novel methodology for minimising the Mycoplasma pneumoniae genome via random deletions of genetic material. This protocol utilises the Cre Lox system coupled with random transposon mutagenesis to create a population with random lox sites dispersed around the genome. This allows for a population of cells containing a high variability of large and small-scale deletions ranging from 50bp to 25Kb within M. pneumoniae. ii) The first large scale analysis of the essentiality of genes from multiple bacterial species, and how the composition and function of the essential genome of a bacterium changes based on the genome’s complexity.
Discernir cuales son los componentes que podrían constituir una célula mínima es un desafío clave para la Biología Sintética. En esta tesis, se presentan dos nuevas herramientas para facilitar esta tarea. (i) Una nueva metodología para minimizar el genoma de Mycoplasma pneumoniae mediante la deleción aleatoria de material genético. Esta técnica combina el sistema Cre/lox con la mutagénesis aleatoria mediada por transposones para generar poblaciones bacterianas en las que los sitios lox están distribuidos de manera aleatoria a lo largo de su genoma. Esto permite la generación de poblaciones bacterianas en las que el tamaño de las deleciones efectuadas varia desde 50 pb hasta 25 kb. (ii) El primer análisis a gran escala de la esencialidad genética en múltiples especies bacterianas, y cómo la composición y función del grupo de genes esenciales de una bacteria cambia en función de la complejidad de su genoma.

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Stranneheim, Henrik. « Enabling massive genomic and transcriptomic analysis ». Doctoral thesis, KTH, Genteknologi, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-45957.

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In recent years there have been tremendous advances in our ability to rapidly and cost-effectively sequence DNA. This has revolutionized the fields of genetics and biology, leading to a deeper understanding of the molecular events in life processes. The rapid advances have enormously expanded sequencing opportunities and applications, but also imposed heavy strains on steps prior to sequencing, as well as the subsequent handling and analysis of the massive amounts of sequence data that are generated, in order to exploit the full capacity of these novel platforms. The work presented in this thesis (based on six appended papers) has contributed to balancing the sequencing process by developing techniques to accelerate the rate-limiting steps prior to sequencing, facilitating sequence data analysis and applying the novel techniques to address biological questions. Papers I and II describe techniques to eliminate expensive and time-consuming preparatory steps through automating library preparation procedures prior to sequencing. The automated procedures were benchmarked against standard manual procedures and were found to substantially increase throughput while maintaining high reproducibility. In Paper III, a novel algorithm for fast classification of sequences in complex datasets is described. The algorithm was first optimized and validated using a synthetic metagenome dataset and then shown to enable faster analysis of an experimental metagenome dataset than conventional long-read aligners, with similar accuracy. Paper IV, presents an investigation of the molecular effects on the p53 gene of exposing human skin to sunlight during the course of a summer holiday. There was evidence of previously accumulated persistent p53 mutations in 14% of all epidermal cells. Most of these mutations are likely to be passenger events, as the affected cell compartments showed no apparent growth advantage. An annual rate of 35,000 novel sun-induced persistent p53 mutations was estimated to occur in sun-exposed skin of a human individual. Paper V, assesses the effect of using RNA obtained from whole cell extracts (total RNA) or cytoplasmic RNA on quantifying transcripts detected in subsequent analysis. Overall, more differentially detected genes were identified when using the cytoplasmic RNA. The major reason for this is related to the reduced complexity of cytoplasmic RNA, but also apparently due (at least partly) to the nuclear retention of transcripts with long, structured 5’- and 3’-untranslated regions or long protein coding sequences. The last paper, VI, describes whole-genome sequencing of a large, consanguineous family with a history of Leber hereditary optic neuropathy (LHON) on the maternal side. The analysis identified new candidate genes, which could be important in the aetiology of LHON. However, these candidates require further validation before any firm conclusions can be drawn regarding their contribution to the manifestation of LHON.
QC 20111115

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Ao, Sio-iong. « Data mining algorithms for genomic analysis ». Click to view the E-thesis via HKUTO, 2007. http://sunzi.lib.hku.hk/hkuto/record/B38319822.

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Ao, Sio-iong, et 區小勇. « Data mining algorithms for genomic analysis ». Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2007. http://hub.hku.hk/bib/B38319822.

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Williamson, Daniel. « Genomic and expression analysis of Rhabdomysarcoma ». Thesis, Institute of Cancer Research (University Of London), 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.406321.

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Raab, R. Michael. « Genomic analysis of hepatic insulin resistance ». Thesis, Massachusetts Institute of Technology, 2005. http://hdl.handle.net/1721.1/33762.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, February 2006.
Includes bibliographical references (leaves 159-191).
Type II Diabetes mellitus is a genetically complex disease characterized by insulin resistance in peripheral tissues, which results in simultaneous hyperglycemia and hyperinsulinemia. Because of the prevalence of type II diabetes, many researchers are investigating the genetics of glucose homeostasis, however, traditional mapping techniques have not been successful in determining all of the genes that regulate glycemia. To complement these efforts, we used DNA microarrays to find differentially expressed genes and combinatorial siRNA screening to investigate the effects of hepatic gene transcription during periods of high and low glucose production. This strategy provides a new approach to studying the molecular mechanisms of disease pathogenesis. Our investigations focused on discovering new genes that influence hepatic metabolism and glucose production. Hepatocytes help maintain whole body glycemia by providing glucose and other substrates during non-feeding periods. DNA microarrays containing 17,000 unique gene probes were used to study hepatic gene transcription during normal, insulin resistant, and fasting states in C57/BL/6J mice. We analyzed this data set using a combination of statistical and multivariate techniques to determine 41 different, genes that are differentially expressed and highly discriminatory of the treatment groups.
(cont.) Hepatocytes perform many physiological roles, thus to investigate which genes from the microarray analysis affected hepatic metabolism, we developed combinatorial RNA-interference (RNAi) based gene silencing techniques. Using combinatorial siRNA screening, we silenced genes that were over-expressed within the microarray data set to study loss of function effects on hepatic metabolism, which was quantified by measuring intracellular metabolite concentrations in relevant metabolic pathways. Based upon the metabolite dependent clustering of experimental and control samples using Fisher Discriminant Analysis, four of the silenced genes had a significant effect on key metabolites involved in hepatic glucose output. Of these four genes, three were shown to influence hepatic glucose output in our primary cell model.
by R. Michael Raab.
Ph.D.

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Alqahtani, Khaled Mubarek A. « Survival analysis based on genomic profiles ». Thesis, University of Leeds, 2016. http://etheses.whiterose.ac.uk/16471/.

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Accurate survival prediction is critical in the management of cancer patients’ care and well-being. Previous studies have shown that copy number alterations (CNA) in some key genes are individually associated with disease phenotypes and patients’ prognosis. However, in many complex diseases like cancer, it is expected that a large number of genes with such an association span the genome. Furthermore, genome-wide CNA profiles are person-specific. Each patient has their own profile and any differences in the profile between patients may help to explain the differences in the patients’ survival. Hence, extracting the relevant information in the genome-wide CNA profile is critical in the prediction of cancer patients’ survival. It is currently a modelling challenge to incorporate the genome-wide CNA profiles, in addition to the patients’ clinical information, to predict cancer patients survival. Therefore, the focus of this thesis is to establish or develop statistical methods that are able to include CNA (ultra-high dimensional data) in survival Analysis. In order to address this objective, we go throw two main parts. The first part of the thesis concentrates on CNA estimation. CNA can be estimated using the ratio of a tumour sample to a normal sample. Therefore, we investigate the approximations of the distribution of the ratio of two Poisson random variables. In the second part of the thesis, we extend the Cox proportional hazard (PH) model for prediction of patients survival probability by incorporating the genome-wide CNA profiles as random predictors. The patients clinical information remains as fixed predictors in the model. In this part three types of distribution of random effect are investigated. First, the random effects are assumed to be normally distributed with mean zero and diagonal structure covariance matrix which has equal variances and covariances of zero. The diagonal structure of covariance matrix is the simplest possible structure for a variance-covariance matrix. This structure indicates independence between neighbouring genomic windows. However, CNAs have dependencies between neighbouring genomic windows, and spatial characteristics which are ignored with such a covariance structure. We address the spatial dependence structure of CNAs. In order to achieve this, we start first by discussing other structures of variance-covariance matrices of random effects ( Compound symmetry covariance matrix , and Inverse of covariance matrix). Then, we impose smoothness using first and second differences of random effects. Specifically, the random effects are assumed to be correlated random effects that follow a mixture of two distributions, normal and Cauchy, for the first or second differences (SCox). Our approach in these two scenario was a genome-wide approach, in the sense that we took into account all of the CNA information in the genome. In this regard, the model does not include a variable selection mechanism. Third, as the previous methods employ all predictors regardless of their relevance, which make it difficult to interpret the results, we introduce a novel algorithm based on Sparse-smoothed Cox model (SSCox) within a random effects model-frame work to model the survival time using the patients’ clinical characteristics as fixed effects and CNA profiles as random effects. We assumed CNA coefficients to be correlated random effects that follow a mixture of three distributions: normal (to achieve shrinkage around the mean values), Cauchy for the second-order differences (to gain smoothness), and Laplace (to achieve sparsity). We illustrate each method with a real dataset from a lung cancer cohort as well as simulated data. For the simulation studies, we find that our SSCox method generally preformed better than the sparse partial leastsquare methods in prediction performance. Our estimator had smaller mean square error, and mean absolute error than its main competitors. For the real data set, we find that the SSCox model is suitable and has enabled a survival probability prediction based on the patients clinical information and CNA profiles. The results indicate that cancer T- and N-staging are significant factors in affecting the patients survival, and the estimates of random effects allow us to examine the contribution to the survival of some genomic regions across the genome.

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Pratas, Diogo. « Compression and analysis of genomic data ». Doctoral thesis, Universidade de Aveiro, 2016. http://hdl.handle.net/10773/16286.

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Doutoramento em Informática
Genomic sequences are large codi ed messages describing most of the structure of all known living organisms. Since the presentation of the rst genomic sequence, a huge amount of genomics data have been generated, with diversi ed characteristics, rendering the data deluge phenomenon a serious problem in most genomics centers. As such, most of the data are discarded (when possible), while other are compressed using general purpose algorithms, often attaining modest data reduction results. Several speci c algorithms have been proposed for the compression of genomic data, but unfortunately only a few of them have been made available as usable and reliable compression tools. From those, most have been developed to some speci c purpose. In this thesis, we propose a compressor for genomic sequences of multiple natures, able to function in a reference or reference-free mode. Besides, it is very exible and can cope with diverse hardware speci cations. It uses a mixture of nite-context models (FCMs) and eXtended FCMs. The results show improvements over state-of-the-art compressors. Since the compressor can be seen as a unsupervised alignment-free method to estimate algorithmic complexity of genomic sequences, it is the ideal candidate to perform analysis of and between sequences. Accordingly, we de ne a way to approximate directly the Normalized Information Distance, aiming to identify evolutionary similarities in intra- and inter-species. Moreover, we introduce a new concept, the Normalized Relative Compression, that is able to quantify and infer new characteristics of the data, previously undetected by other methods. We also investigate local measures, being able to locate speci c events, using complexity pro les. Furthermore, we present and explore a method based on complexity pro les to detect and visualize genomic rearrangements between sequences, identifying several insights of the genomic evolution of humans. Finally, we introduce the concept of relative uniqueness and apply it to the Ebolavirus, identifying three regions that appear in all the virus sequences outbreak but nowhere in the human genome. In fact, we show that these sequences are su cient to classify di erent sub-species. Also, we identify regions in human chromosomes that are absent from close primates DNA, specifying novel traits in human uniqueness.
As sequências genómicas podem ser vistas como grandes mensagens codificadas, descrevendo a maior parte da estrutura de todos os organismos vivos. Desde a apresentação da primeira sequência, um enorme número de dados genómicos tem sido gerado, com diversas características, originando um sério problema de excesso de dados nos principais centros de genómica. Por esta razão, a maioria dos dados é descartada (quando possível), enquanto outros são comprimidos usando algoritmos genéricos, quase sempre obtendo resultados de compressão modestos. Têm também sido propostos alguns algoritmos de compressão para sequências genómicas, mas infelizmente apenas alguns estão disponíveis como ferramentas eficientes e prontas para utilização. Destes, a maioria tem sido utilizada para propósitos específicos. Nesta tese, propomos um compressor para sequências genómicas de natureza múltipla, capaz de funcionar em modo referencial ou sem referência. Além disso, é bastante flexível e pode lidar com diversas especificações de hardware. O compressor usa uma mistura de modelos de contexto-finito (FCMs) e FCMs estendidos. Os resultados mostram melhorias relativamente a compressores estado-dearte. Uma vez que o compressor pode ser visto como um método não supervisionado, que não utiliza alinhamentos para estimar a complexidade algortímica das sequências genómicas, ele é o candidato ideal para realizar análise de e entre sequências. Em conformidade, definimos uma maneira de aproximar directamente a distância de informação normalizada (NID), visando a identificação evolucionária de similaridades em intra e interespécies. Além disso, introduzimos um novo conceito, a compressão relativa normalizada (NRC), que é capaz de quantificar e inferir novas características nos dados, anteriormente indetectados por outros métodos. Investigamos também medidas locais, localizando eventos específicos, usando perfis de complexidade. Propomos e exploramos um novo método baseado em perfis de complexidade para detectar e visualizar rearranjos genómicos entre sequências, identificando algumas características da evolução genómica humana. Por último, introduzimos um novo conceito de singularidade relativa e aplicamo-lo ao Ebolavirus, identificando três regiões presentes em todas as sequências do surto viral, mas ausentes do genoma humano. De facto, mostramos que as três sequências são suficientes para classificar diferentes sub-espécies. Também identificamos regiões nos cromossomas humanos que estão ausentes do ADN de primatas próximos, especificando novas características da singularidade humana.

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Wang, Yehong. « Analysis of heterochromatin-associated genomic instability ». Diss., [Riverside, Calif.] : University of California, Riverside, 2009. http://proquest.umi.com/pqdweb?index=0&did=1957340941&SrchMode=2&sid=1&Fmt=2&VInst=PROD&VType=PQD&RQT=309&VName=PQD&TS=1268763263&clientId=48051.

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Thesis (Ph. D.)--University of California, Riverside, 2009.
Includes abstract. Available via ProQuest Digital Dissertations. Title from first page of PDF file (viewed March 16, 2010). Includes bibliographical references. Also issued in print.

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Adhikari, Bishwo. « Genomic Analysis of Nematode-Environment Interaction ». BYU ScholarsArchive, 2010. https://scholarsarchive.byu.edu/etd/2578.

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The natural environments of organisms present a multitude of biotic and abiotic challenges that require both short-term ecological and long-term evolutionary responses. Though most environmental response studies have focused on effects at the ecosystem, community and organismal levels, the ultimate controls of these responses are located in the genome of the organism. Soil nematodes are highly responsive to, and display a wide variety of responses to changing environmental conditions, making them ideal models for the study of organismal interactions with their environment. In an attempt to examine responses to environmental stress (desiccation and freezing), genomic level analyses of gene expression during anhydrobiosis of the Antarctic nematode Plectus murrayi was undertaken. An EST library representative of the desiccation induced transcripts was established and the transcripts differentially expressed during desiccation stress were identified. The expressed genome of P. murrayi showed that desiccation survival in nematodes involves differential expression of a suite of genes from diverse functional areas, and constitutive expression of a number of stress related genes. My study also revealed that exposure to slow desiccation and freezing plays an important role in the transcription of stress related genes, improves desiccation and freezing survival of nematodes. Deterioration of traits essential for biological control has been recognized in diverse biological control agents including insect pathogenic nematodes. I studied the genetic mechanisms behind such deterioration using expression profiling. My results showed that trait deterioration of insect pathogenic nematode induces substantial overall changes in the nematode transcriptome and exhibits a general pattern of metabolic shift causing massive changes in metabolic and other processes. Finally, through field observations and molecular laboratory experiments the validity of the growth rate hypothesis in natural populations of Antarctic nematodes was tested. My results indicated that elemental stoichiometry influences evolutionary adaptations in gene expression and genome evolution. My study, in addition to providing immediate insight into the mechanisms by which multicellular animals respond to their environment, is transformative in its potential to inform other fundamental ecological and evolutionary questions, such as the evolution of life-history patterns and the relationship between community structure and ecological function in ecosystems.

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Sambo, Francesco. « Advanced Algorithms for Genomic Data Analysis ». Doctoral thesis, Università degli studi di Padova, 2010. http://hdl.handle.net/11577/3426964.

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The object of this thesis is to develop new algorithmic techniques for the inference of causal relations among the genes of an organism from DNA microarray experiments. Cause-effect relations between genes can be inferred from microarray data (Reverse Engineering) and summarized in a Gene Regulatory Network, a graph in which nodes represent genes and edges represent causal relations among genes: this thesis presents three novel Reverse Engineering algorithms, tailored to tackle differend kinds of DNA microarray experiments and for different levels of detail in the description of the biological systems, and two studies on the difficulty of inferring Gene Regulatory Networks. The first original contribution of the thesis is the application of the Qualitative Reasoning approach to steady state measurements of systematic gene perturbation experiments, i.e. experiments in which the expression of each gene is altered in turn and one sample of the expression is taken each time the system reaches a steady state. The second proposed algorithm, CNET, is based on a heuristic scoring function designed to identify causal relations from time course experiments, i.e. repeated observations of the same biological system at subsequent temporal instants. The algorithm is tailored to recognize causal relations even in the presence of noise and variable regulatory delays. We then present two original in-depth studies, the first on the relations between the performance of two network inference algorithms and the topological and structural properties of oriented Gene Regulatory Networks and the second on the fitness landscape around the optimal parameters configuration, when a class of nonlinear differential equations systems, known as Dynamic Recurrent Neural Networks, are fit to time course data. Both studies provide original and useful knowledge on the difficulty of inferring Gene Regulatory Networks from DNA microarray data. Finally, we present a novel discrete/continuous optimization algorithm for fitting systems of nonlinear differential equations to small scale time course experiments, composed of two interacting modules: an Iterated Local Search procedure to explore the discrete space of network structures and a continuous optimization procedure to identify optimal system parameters. The performance of the three proposed algorithms is assessed both on simulated data and, in some cases, on real DNA microarray data: the methods proved to be competitive with the state of the art of Reverse Engineering algorithms.
Obiettivo del presente lavoro di tesi è lo sviluppo di tecniche algoritmiche innovative per l’identificazione di relazioni causali fra i geni di un organismo a partire da esperimenti di DNA microarray. Le relazioni causa-effetto fra i geni possono essere apprese a partire dai dati di microarray (Reverse Engineering) e riassunte in una Rete di Regolazione Genica, un grafo i cui nodi rappresentano i geni e i cui archi rappresentano le relazioni causali fra i geni: questa tesi presenta tre algoritmi innovativi di Reverse Engineering, progettati per elaborare diversi tipi di esperimenti di microarray e con diversi livelli di dettaglio nella descrizione dei sistemi biologici, e due studi sulla difficoltà nell'inferire le Reti di Regolazione Genica. Il primo contributo originale della tesi è l'applicazione del Ragionamento Qualitativo all’elaborazione di misurazioni in stato stazionario di esperimenti di perturbazione sistematica dei geni, vale a dire esperimenti nei quali l’espressione di ogni gene a turno viene alterata e un solo campione dell’espressione genica viene misurato ogni volta che il sistema raggiunge lo stato stazionario. Il secondo algoritmo proposto, CNET, è basato su una funzione euristica progettata per identificare relazioni causali a partire da serie temporali di espressione genica, cioè osservazioni ripetute dello stesso sistema biologico in istanti temporali consecutivi. L'algoritmo è costruito in modo tale da riconoscere le relazioni causali anche in presenza di rumore e di ritardi variabili nella regolazione. Successivamente vengono presentati due studi approfonditi, il primo sulle relazioni fra la performance di due algoritmi di Reverse Engineering e le proprietà strutturali e topologiche della Rete di Regolazione Genica da inferire e il secondo sul panorama di fitness attorno alla configurazione ottima dei parametri di una particolare classe di sistemi dinamici non lineari, le Reti Neurali Dinamiche Ricorsive, che descriva un insieme di serie temporali di espressione genica. Entrambi gli studi hanno consentito di ottenere informazioni utili e originali sulla difficoltà nell'inferire Reti di Regolazione Genica a partire da dati di DNA microarray. Infine, viene presentato un algoritmo innovativo di ottimizzazione mista (continua e discreta) per il fit di sistemi di equazioni differenziali non lineari a esperimenti contenenti serie temporali di espressione genica su piccola scala, composto di due moduli interagenti: una procedura di ricerca locale per esplorare lo spazio discreto delle strutture di rete e una procedura di ottimizzazione continua per l’idenficazione dei parametri ottimi del sistema. La performance dei tre algoritmi proposti viene analizzata sia su dati simulati sia, in certi casi, su dati reali di DNA microarray: i metodi si dimostrano competitivi con lo stato dell’arte degli algoritmi di Reverse Engineering.

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Schlueter, Shannon Dwayne. « Plant genome informatics evaluation and analysis of genomic DNA features involved in the transcriptional processing of protein coding genes / ». [Ames, Iowa : Iowa State University], 2006.

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Ji, Boyang. « Comparative and Functional Genome Analysis of Magnetotactic Bacteria ». Thesis, Aix-Marseille, 2013. http://www.theses.fr/2013AIXM4065.

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Les bactéries magnétotactiques (MTB) appartiennent à différents phyla procaryotes et ont la capacité de synthétiser des magnetosomes (cristaux de magnétite entourés par une membrane). Durant la thèse, nous avons procédé à l’analyse génomique de 2 bactéries magnétotactiques: Magnetospira sp. QH-2 et Magnetococcus MO-1. La synthénie et la correlation génique des gènes impliqués dans la formation des magnétosomes montrent que l'insertion de cet îlot chez QH-2 a eu lieu après la divergence entre les Magnetospirillum sp et Magnetospira sp. L'analyse comparative a mis en évidence trois groupes distincts de MTB : Groupe I, comprenant les souches Magnetospirillum spp. et Magnetospira; Groupe II avec MO-1 et M. marinus MC-1 et le Groupe III, avec D. magneticus RS-1. QH-2 montre aussi une évolution adaptative distincte par comparaison aux souches marines ou d'eau douce. L'analyse comparative des réseaux métaboliques révèle une très grande similitude intra-Groupe et une importante variabilité inter-Groupe. Cela est probablement dû aux enzymes impliqués dans les voies métaboliques anoxiques, qui représentent ainsi la contrainte à une distribution taxonomique large des MTB. Ces enzymes permettent ainsi de prédire le phénotype métabolique nécessaire à la production des magnétosomes. Différentes analyses (des protéines ribosomales au genome entier) indiquent une composition taxonomique chimérique des gènes de MO-1 et MC-1, et peut représenter une nouvelle lignée taxonomique chez les Protéobactéries. J’ai aussi participé à l'analyse des génomes de deux bactéries piezophiles, d’une bactérie photosynthétique pourpre et l’analyse phylogénomique des tyrosine-Kinases bactériennes
Magnetotactic bacteria (MTB) are a diverse group of aquatic prokaryotes, which synthesize membrane-Enclosed magnetic crystals known as magnetosomes. In this thesis, the genome sequences of two marine MTB strains, Magnetospira sp. QH-2 and magneto-Ovoid strain MO-1 were analyzed. The magnetosome gene cluster synteny and mam gene correlation indicate that the insertion of the magnetosome island into QH-2 chromosome occurred after divergence between freshwater and marine magnetospirilla. Comparative genomic analysis revealed three distinct groups of sequenced MTB strains: Group I with Magnetospirillum spp. strains and Magnetospira strain, Group II with MO-1 strain and M. marinus MC-1, and Group III including Desulfovibrio magneticus RS-1. In addition, it shows an adaptive evolution of two marine MTB strains to marine sediments in comparison with closely related freshwater species. Moreover, comparative metabolic network analysis reveals high level of intra-Group similarity and inter-Group variety in MTB. With anoxic network enzymes, potential “MTB” strains are predicted, and are consistent with recently isolated MTB strains. It suggested that the anoxic metabolic network might be one restricted constraint for MTB distribution in bacterial lineages. Interestingly, analyses from ribosomal proteins to the whole MTB genome strongly support a taxonomic chimeric nature of MO-1 and MC-1 genes, and may represent a novel Proteobacteria lineage. Additionally, I also participate to genome analyses of piezophilic Desulfovibrio and Phaeospirillum molischianum strains as well as genome-Wide analysis of bacterial tyrosine kinases

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Håfström, Therese. « Genome closure and bioinformatic analysis of the parallel sequenced bacterium Brachyspira intermedia PWS/AT ». Thesis, Uppsala universitet, Institutionen för biologisk grundutbildning, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-164335.

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Brachyspira species are bacteria that colonize the intestines of some mammalian and avian species with different degrees of pathogenicity. Brachyspira intermedia is a mild pig and bird pathogen with an unknown genomic sequence. In this project, we completed the genome of Brachyspira intermedia PWS/AT and did a comparative genomic analysis between B. intermedia PWS/AT and the already completed genomes of B. hyodysenteriae WA1, B. murdochii 56-150T and B. pilosicoli 95/1000. A table containing 15 classes of unique and shared genes was developed and analyzed in order to gain a better understanding of species-specific traits and clues behind the different degree of pathogenicity. Our result shows that genes are overall poorly annotated and further studies are of great importance for understanding different and shared properties. The largest number of unique features was found in B. intermedia and B. murdochii. B. hyodysenteriae and B. pilosicoli has most likely developed independently towards different biological niches and B. pilosicoli has undergone a major reductive evolution. One plasmid and six prophages were found in B. intermedia, where two of the phages appear to be capable of horizontal gene transfer. Further genome sequencing of more strains will probably increase the understanding of species-specific traits even more.

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Feng, Yuanjian. « Detection and Characterization of Multilevel Genomic Patterns ». Diss., Virginia Tech, 2010. http://hdl.handle.net/10919/38577.

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DNA microarray has become a powerful tool in genetics, molecular biology, and biomedical research. DNA microarray can be used for measuring the genotypes, structural changes, and gene expressions of human genomes. Detection and characterization of multilevel, high-throughput microarray genomic data pose new challenges to statistical pattern recognition and machine learning research. In this dissertation, we propose novel computational methods for analyzing DNA copy number changes and learning the trees of phenotypes using DNA microarray data. DNA copy number change is an important form of structural variations in human genomes. The copy number signals measured by high-density DNA microarrays usually have low signal-to-noise ratios and complex patterns due to inhomogeneous composition of tissue samples. We propose a robust detection method for extracting copy number changes in a single signal profile and consensus copy number changes in the signal profiles of a population. We adapt a solution-path algorithm to efficiently solve the optimization problems associated with the proposed method. We tested the proposed method on both simulation and real CGH and SNP microarray datasets, and observed competitively improved performance as compared to several widely-adopted copy number change detection methods. We also propose a chromosome instability measure to summarize the extracted copy number changes for assessing chromosomal instabilities of tumor genomes. The proposed measure demonstrates distinct patterns between different subtypes of ovarian serous carcinomas and normal samples. Among active research on complex human diseases using genomic data, little effort and progress have been made in discovering the relational structural information embedded in the molecular data. We propose two stability analysis based methods to learn stable and highly resolved trees of phenotypes using microarray gene expression data of heterogeneous diseases. In the first method, we use a hierarchical, divisive visualization approach to explore the tree of phenotypes and a leave-one-out cross validation to select stable tree structures. In the second method, we propose a node bandwidth constraint to construct stable trees that can balance the descriptive power and reproducibility of tree structures. Using a top-down merging procedure, we modify the binary tree structures learned by hierarchical group clustering methods to achieve a given node bandwidth. We use a bootstrap based stability analysis to select stable tree structures under different node bandwidth constraints. The experimental results on two microarray gene expression datasets of human diseases show that the proposed methods can discover stable trees of phenotypes that reveal the relationships between multiple diseases with biological plausibility.
Ph. D.

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Eversley, Chevonne D. Threadgill David W. « Integrative genomic analysis of sporadic colorectal cancer ». Chapel Hill, N.C. : University of North Carolina at Chapel Hill, 2009. http://dc.lib.unc.edu/u?/etd,2874.

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Thesis (Ph. D.)--University of North Carolina at Chapel Hill, 2009.
Title from electronic title page (viewed Jun. 4, 2010). "... in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Curriculum in Genetics and Molecular Biology." Discipline: Genetics and Molecular Biology; Department/School: Medicine.

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Koerner, Henrike. « Analysis of genomic alterations in malignant melanoma ». Diss., lmu, 2007. http://nbn-resolving.de/urn:nbn:de:bvb:19-77810.

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Santani, Avni Bhawan. « Genomic analysis of the horse Y chromosome ». Texas A&M University, 2004. http://hdl.handle.net/1969.1/1494.

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Stallion fertility is of significant economic importance in the multibillion dollar equine industry. Presently, the underlying genetic causes of infertility in stallions are unknown. Analysis of the human genome has shown that in more than 25% of cases, male infertility is associated with deletions/rearrangements in the Y chromosome. Presently there is no gene map for the Y chromosome in the horse. Therefore, the primary aim of this study is to build a detailed physical map of the chromosome with a long-term aim to identify and analyze Y-specific factors affecting fertility in stallions. To materialize this, we constructed the first radiation hybrid and FISH map of the euchromatic region of the horse Y chromosome. This basic map was used to obtain Y-specific BAC clones that provided new STS markers from the end sequences. Chromosome walking provided 73 BACs comprising 7 contigs that were built across the euchromatic region using 124 markers for content mapping. The results were validated by restriction fingerprinting and Fiber FISH. The map is presently the most informative among the domestic species and second to only human and mouse Y chromosome maps. The construction of this map will pave the way for isolation and functional characterization of genes critical for normal male fertility and reproduction and will in the future lead to the development of a diagnostic test to facilitate early identification of deletions/rearrangements on the Y chromosome of potentially affected foals/stallions. The second part of the study comprised the first extended investigation to assess genetic variation in the horse Y chromosome. Approximately 4.5Mb of the euchromatic region was screened for polymorphic microsatellite markers. Of the 27 markers that were characterized and screened for polymorphism in 14 breeds of the domestic horse and eight extant equids, only one was polymorphic in the domestic horse, suggesting a low level of genetic variation on the chromosome. However, 21 of the markers showed noteworthy variation (on average four alleles/marker) among the eight equids. These markers will be vital in future studies aimed at elucidating the genetic relationships between the various equids through phylogenetic analysis.

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Clifford, Raphael. « Indexed strings for large scale genomic analysis ». Thesis, Imperial College London, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.268368.

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Duangsonk, Kwanjit. « Genomic and genetic analysis of Burkholderia pseudomallei ». Thesis, University of Liverpool, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.437528.

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Frampton, Garrett M. « Genomic analysis of control of cell type ». Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/62777.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Biology, 2011.
Cataloged from PDF version of thesis.
Includes bibliographical references.
In mammalian development, a single fertilized egg grows into a complex organism, comprised of organs and tissues made up of hundreds of different specialized cell types. All of these cells contain the same genome, but express distinct sets of genes and proteins, which give the cells their specialized functions. Understanding how this process occurs is one of the fundamental goals of biology. Research using new technology for high-resolution genome-wide location analysis and gene expression profiling has allowed characterization of the transcriptional regulatory circuitry of cells in unprecedented detail. From this research emerges an improved understanding of how these cells work, how they malfunction in disease, and several general principles. This thesis describes several studies designed to understand the transcriptional regulatory circuitry of three different medically important cell types; embryonic stem cells, regulatory T cells and MLL leukemia cells.
by Garrett M. Frampton.
Ph.D.

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Pengelly, Reuben. « Genomic data analysis : populations, patients & ; pipelines ». Thesis, University of Southampton, 2015. https://eprints.soton.ac.uk/397102/.

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Methods for the ascertainment of genotype data have become more cost efficient by orders of magnitude with the use of high-density genotyping arrays and the advent of next generation sequencing (NGS). The resulting deluge of data has required ever advancing analytical approaches in order for the maximal information to be gleaned from these extensive data. In this work, many application of NGS to clinical research are discussed. This includes the application of targeted gene sequencing to a cohort of 83 patients with chronic kidney disease, whole-exome investigations of eight families with cleft lip/palate phenotypes, as well as five cases where analytical lessons can be learned from exome sequenced cases harbouring pathogenic variants refractory to identification. Additionally, a novel QC tool for the unambiguous tracking of samples undergoing exome sequencing is presented. Furthermore, work is presented investigating the linkage disequilibrium (LD) patterns in populations applying the Malecot-Morton model. We demonstrate that array genotyping is insufficient for the accurate determination of ne LD patterns in the human genome, with whole-genome sequencing providing more representative LD maps. Finally, we apply similar methods to Gallus gallus, generating the highest resolution maps of LD presented to date, showing that the patterns are highly discordant between commercial lines, and define features associated with recombination. Overall, we highlight the diversity of ways in which genetic data can be utilised effectively in the age of genomic `big data', and present tools which may be of benefit to other researchers utilising these technologies.

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Liu, Yiding. « Technologies for Proteomic and Genomic Biomarker Analysis ». Cleveland State University / OhioLINK, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=csu1229461302.

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Tennant, Richard Kenneth. « Genomic analysis of microfossils in lake sediments ». Thesis, University of Exeter, 2015. http://hdl.handle.net/10871/20649.

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Botryococcus braunii is a microscopic, colonial green alga that may be found in fresh and brackish waters throughout the globe. B. braunii is unique in that it constitutively synthesises and secretes copious amounts of various long-chain (C23-C40) hydrocarbons, generically termed “botryococcenes”. Botryococcanes, the hydrogenated forms of botryococcenes, comprise 1% of the fossil hydrocarbons found in petroleum deposits and in oil-shales. Microfossils identified as Botryococcus by optical and scanning electron microscopy are also abundant in these strata, but the actual identity and precise relationship between these microfossils and extant Botryococcus species is not known. In this investigation, the relationship between living Botryococcus algae and microfossils identified as Botryococcus using traditional palaeontological analysis and light-microscopy was investigated by analysis of ancient DNA (aDNA). The material used was identified in sediments from Boswell Lake (British Columbia, Canada), a Holocene lake that had remained undisturbed since the glacial retreat. New flow-cytometry methods were developed to rapidly purify enough of the relevant microfossils, from which aDNA was extracted and sequenced. Pollen grains were purified using the same flow-cytometry method and from the same horizons as the Botryococcus microfossils and used to age the sedimentary horizons by 14C radiocarbon dating. Samples of the purified microfossils were imaged by scanning electron microscopy for comparison with published images of fossils identified as Botryococcus from kerogens. In addition, metaDNA from the relevant horizons was extracted and sequenced by NGS, and a chemical analysis for botryococcene derivatives performed using two-dimensional gas chromatography (2D-GC). The genomic analyses show that the sub-fossils identified in Boswell Lake are likely to be representatives of B. braunii, race B. The geochemical analysis identified hydrocarbons that migrate as botryococcenes on 2D-GC in the strata whence the sub-fossils were purified. The SEM images indicate that the microfossils purified from Boswell Lake have similar morphologies to those found in kerogens. Taken together, these data strongly support the proposition that petroleum and kerogen deposits are unusually rich in B. braunii and that these algae have a lineage potentially dating 500 million years. The metagenomic analysis enabled similar conclusions to be reached regarding the presence of B. braunii within the sediment, without the need for targeted microfossil purification. While this analysis was less precise due to the under-representation of algal genomes in the public sequence databases, the metagenomics approach employed was particularly well suited to the temporal analysis of prokaryotic microcosms within Lake Boswell, the succession of which could be associated with periods of climatic variation. The analytical methods described herein are generally applicable to understanding microbial systems over geological periods, and may be used to generate important insights into the cause and effect relationships between microbial populations and environmental perturbation.

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Manser, Paul. « Methods for Integrative Analysis of Genomic Data ». VCU Scholars Compass, 2014. http://scholarscompass.vcu.edu/etd/3638.

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In recent years, the development of new genomic technologies has allowed for the investigation of many regulatory epigenetic marks besides expression levels, on a genome-wide scale. As the price for these technologies continues to decrease, study sizes will not only increase, but several different assays are beginning to be used for the same samples. It is therefore desirable to develop statistical methods to integrate multiple data types that can handle the increased computational burden of incorporating large data sets. Furthermore, it is important to develop sound quality control and normalization methods as technical errors can compound when integrating multiple genomic assays. DNA methylation is a commonly studied epigenetic mark, and the Infinium HumanMethylation450 BeadChip has become a popular microarray that provides genome-wide coverage and is affordable enough to scale to larger study sizes. It employs a complex array design that has complicated efforts to develop normalization methods. We propose a novel normalization method that uses a set of stable methylation sites from housekeeping genes as empirical controls to fit a local regression hypersurface to signal intensities. We demonstrate that our method performs favorably compared to other popular methods for the array. We also discuss an approach to estimating cell-type admixtures, which is a frequent biological confound in these studies. For data integration we propose a gene-centric procedure that uses canonical correlation and subsequent permutation testing to examine correlation or other measures of association and co-localization of epigenetic marks on the genome. Specifically, a likelihood ratio test for general association between data modalities is performed after an initial dimension reduction step. Canonical scores are then regressed against covariates of interest using linear mixed effects models. Lastly, permutation testing is performed on weighted correlation matrices to test for co-localization of relationships to physical locations in the genome. We demonstrate these methods on a set of developmental brain samples from the BrainSpan consortium and find substantial relationships between DNA methylation, gene expression, and alternative promoter usage primarily in genes related to axon guidance. We perform a second integrative analysis on another set of brain samples from the Stanley Medical Research Institute.

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