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INDEPENDENT ORIGINATION OF FLORAL ZYGOMORPHY, A PREDICTED ADAPTIVE RESPONSE TO POLLINATORS: DEVELOPMENTAL AND GENETIC MECHANISMSBukhari, Ghadeer, Zhang, Wenheng 01 January 2016 (has links)
Observations of floral development indicate that floral organ initiation in pentapetalous flowers more commonly results in a medially positioned abaxial petal (MAB) than in a medially positioned adaxial petal (MAD), where the medial plane is defined by the stem and the bract during early floral development. It was proposed that the dominant MAB petal initiation might impose a developmental constraint that leads to the evolution of limited patterns of floral zygomorphy in Asteridae, a family in which the floral zygomorphy develops along the medial plane and results in a central ventral (CV) petal in mature flowers. Here, I investigate whether the pattern of floral organ initiation may limit patterns of floral zygomorphy to evolve in pentapetalous angiosperms. I analyzed floral diagrams representing 405 species in 330 genera of pentapetalous angiosperms to reconstruct the evolution of floral organ initiation and the evolution of developmental processes that give rise to floral zygomorphy on a phylogenetic framework. Results indicate that MAB petal initiation is the most common; it occupies 86.2% of diversity and represents the ancestral state of floral organ initiation in pentapetalous angiosperms. The MAD petal initiation evolved 28 times independently from the ancestral MAB petal initiation. Among the 34 independent originations of floral zygomorphy, 76.5% of these clades represent MAB petal initiation, among which only 47% of the clades result a CV petal in mature flowers. The discrepancy is explained by the existence of developmental processes that result in floral zygomorphy along oblique planes of floral symmetry in addition to along the medial plane. Findings suggest that although the early floral organ initiation plays a constraining role to the evolution of patterns of floral zygomorphy, the constraint diverges along phylogenetically distantly related groups that allow the independent originations of floral zygomorphy through distinct development processes in pentapetalous angiosperms. In additional study, the butterfly-like flowers of Schizanthus are adapted to pollination by bees, hummingbirds, and moths. I investigated the genetic basis of the zygomorphic corolla, for which development is key to the explosive pollen release mechanism found in the species of Schizanthus adapted to bee pollinators. I examined differential gene expression profiles across the zygomorphic corolla of Schizanthus pinnatus, a bee-pollinated species, by analyzing RNA transcriptome sequencing (RNA- seq). Data indicated that CYC2 is not expressed in the zygomorphic corolla of Sc. pinnatus, suggesting CYC2 is not involved in the development of floral zygomorphy in Schizanthus (Solanaceae). The data also indicated that a number of genes are differentially expressed across the corolla.
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Integrating Human Population Genetics And Genomics To Elucidate The Etiology Of Brain DisordersSulovari, Arvis 01 January 2017 (has links)
Brain disorders present a significant burden on affected individuals, their families and society at large. Existing diagnostic tests suffer from a lack of genetic biomarkers, particularly for substance use disorders, such as alcohol dependence (AD). Numerous studies have demonstrated that AD has a genetic heritability of 40-60%. The existing genetics literature of AD has primarily focused on linkage analyses in small family cohorts and more recently on genome-wide association analyses (GWAS) in large case-control cohorts, fueled by rapid advances in next generation sequencing (NGS). Numerous AD-associated genomic variations are present at a common frequency in the general population, making these variants of public health significance. However, known AD-associated variants explain only a fraction of the expected heritability. In this dissertation, we demonstrate that systems biology applications that integrate evolutionary genomics, rare variants and structural variation can dissect the genetic architecture of AD and elucidate its heritability.
We identified several complex human diseases, including AD and other brain disorders, as potential targets of natural selection forces in diverse world populations. Further evidence of natural selection forces affecting AD was revealed when we identified an association between eye color, a trait under strong selection, and AD. These findings provide strong support for conducting GWAS on brain disorder phenotypes. However, with the ever-increasing abundance of rare genomic variants and large cohorts of multi-ethnic samples, population stratification becomes a serious confounding factor for GWAS. To address this problem, we designed a novel approach to identify ancestry informative single nucleotide polymorphisms (SNPs) for population stratification adjustment in association analyses. Furthermore, to leverage untyped variants from genotyping arrays – particularly rare variants – for GWAS and meta-analysis through rapid imputation, we designed a tool that converts genotype definitions across various array platforms.
To further elucidate the genetic heritability of brain disorders, we designed approaches aimed at identifying Copy Number Variations (CNVs) and viral insertions into the human genome. We conducted the first CNV-based whole genome meta-analysis for AD. We also designed an integrated approach to estimate the sensitivity of NGS-based methods of viral insertion detection. For the first time in the literature, we identified herpesvirus in NGS data from an Alzheimer’s disease brain sample.
The work in this dissertation represents a three-faceted advance in our understanding of brain disease etiology: 1) evolutionary genomic insights, 2) novel resources and tools to leverage rare variants, and 3) the discovery of disease-associated structural genomic aberrations. Our findings have broad implications on the genetics of complex human disease and hold promise for delivering clinically useful knowledge and resources.
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Apport du séquençage haut débit dans l'amélioration de la prise en charge des maladies monogéniquesLacoste Deixonne, Caroline 12 December 2016 (has links)
La diffusion du séquençage haut débit (ou NGS pour Next Generation Sequencing) représente un tel changement d’échelle par rapport aux méthodes classiques de séquençage que les indications et l’organisation du diagnostic moléculaire s’en trouvent profondément modifiées. Le NGS permet à la fois de raccourcir le temps d’analyse et de rendu de résultat et d'élargir considérablement le nombre de gènes testés. Il promet donc d’augmenter la proportion de diagnostics posés et de faciliter l'identification de nouveaux variants et de nouveaux gènes impliqués en pathologie. Cependant dans tous les cas, il génère une quantité de données importante, données qui doivent être analysées et interprétées à l’aide d’outils bioinformatiques spécifiques.Dans la première partie de ce travail, les stratégies existantes ainsi que les difficultés et les enjeux du séquençage haut débit pour le diagnostic moléculaire des maladies génétiques sont discutés. Dans la deuxième partie, la mise en place et la validation technique de cette approche diagnostique sont décrites au sein du laboratoire de Génétique Moléculaire de la Timone à Marseille et illustrées par trois exemples concrets de diagnostics moléculaires posés grâce à la technique de séquençage à haut débit. Dans le domaine spécifique des maladies rares, ces nouvelles technologies sont porteuses d’un réel espoir pour les patients atteints de maladie génétique, permettant d'améliorer globalement leur prise en charge et d'accélérer les progrès dans le domaine de la recherche. / The diffusion of Next Generation Sequencing (NGS) technologies induces an important change that modifies molecular diagnostics indications and prompts laboratories to re-think their diagnostic strategies, up-to-now based on Sanger sequencing routine. Several high throughput approaches are available from the sequencing of a gene panel, to a whole exome, or even a whole genome. In all cases, a tremendous amount of data are generated, that have to be filtered, interpreted and analyzed by the use of powerful bioinformatics tools.In part 1, existing strategies and the difficulties and challenges of high-throughput sequencing for molecular diagnosis in genetic diseases are discussed. In part 2, the set up and the technical validation of this diagnostic approach in the Molecular Genetics’ Laboratory of the Timone Hospital in Marseille is presented and illustrated by 3 examples of complex diagnostics solved thanks to NGS. NGS promises to shorten significantly the time of analysis and results reporting, and to expand the number of tested genes. It also promises to increase the proportion of positive diagnoses. Finally, the NGS can identify new variants and new genes involved in human pathology, thus will globally improve patient clinical care.
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Employing Limited Next Generation Sequence Data for the Development of Genetic Loci of Phylogenetic and Population Genetic UtilityEvenstone, Lauren 02 July 2015 (has links)
Massively parallel high throughput sequencers are transforming the scientific research by reducing the cost and time necessary to sequence entire genomes. The goal of this project is to produce preliminary genome assemblies of calliphorid flies using Life Technologies’ Ion Torrent sequencing and Illumina’s MiSeq sequencing. I located, assembled, and annotated a novel mitochondrial genome for one such fly, the little studied Chrysomya pacifica that is central to one hypothesis about blow fly evolution. With sequencing data from Chrysomya megacephala, its forensically relevant sister species, much insight can be gained by alignments, sequence and protein analysis, and many more tools within the CLC Genomics Workbench software program. I present these analyses here of these recently diverged species.
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Séquençage ciblé en tant qu'outil diagnostique et pronostique dans le lymphome à cellules du manteau / Targeted deep sequencing as a diagnostic and prognostic tool in mantle cell lymphomaBertrand, Sarah 13 July 2017 (has links)
Le lymphome est un cancer des ganglions lymphatiques, lieu de prolifération et différenciation des cellules immunitaires en particulier des lymphocytes B qui sont des cellules productrices d'anticorps. Les lymphomes résultent de l’accumulation de mutations génétiques dans le génome d’une cellule B normale contribuant à la transformation en cellule B maligne. Cette cellule B dite transformée prolifère alors pour engendrer un clone de cellules B malignes qui s’accumulent au niveau des ganglions lymphatiques, formant alors une tumeur appelée ‘lymphome B’ (pour cancer lymphoïde issu de la transformation maligne des lymphocytes B). Le ganglion lymphatique normal a une structure histologique qui se décompose ainsi, du centre à la périphérie : le centre germinatif, la zone du manteau et la zone marginale. Les lymphomes B sont classés en différents sous-types histologiques en fonction de leur origine topographique au niveau du ganglion lymphatique et de leurs caractéristiques bio cliniques spécifiques. Parmi ces sous-types, une forme particulièrement agressive peut être distinguée : le lymphome à cellules du manteau. Ce sous-type de lymphome est caractérisé par des rechutes successives et une survie qui est généralement courte (médiane de survie de 4 à 5 ans) même si certains patients, avec des formes plus indolentes de lymphomes à cellules du manteau, présentent des survies prolongées (médiane de survie de 7 à 10 ans). Des biomarqueurs prédictifs de la courte survie manquent aujourd’hui, ce qui rend difficile la prise en charge optimisée des patients. Ce projet s’intéresse à cette question. Plus précisément, nous nous proposons de rechercher des mutations génétiques associées à la résistance thérapeutique. Notre approche sera basée sur le séquençage ciblé à haut débit du génome de cellules B tumorales issus de patients présentant des cas classiques du lymphomes à cellules du manteau mais aussi des cas plus particuliers comme ceux présentant des résistances thérapeutiques précoces, par exemple. Par cette approche dite de ‘cartographie’ à l’échelle du génome, nous espérons identifier des nouveaux prédicteurs moléculaires de la survie chez ces patients atteints de lymphome à cellules du manteau et également apporter de nouvelles connaissances dans l’interconnexion entre la génétique et l’épigénétique dans cette maladie. / Lymphoma is a cancer of the lymph nodes which are organs in which immune cells, particularly the antibody producing B cells, proliferate and differentiate before circulating in the blood and tissues to fight infection. B cell lymphoid cancers – ‘B cell lymphoma’ arise as a consequence of the occurrence of gene mutations in B cells. By affecting the functions of key B cell genes, these mutations drive the malignant transformation of the affected B cells which then begin to divide abnormally eventually destroying normal lymph node organization and function. The lymph node is divided into distinct micro-anatomical compartments or zones which are called (from the inner to outer most compartment – germinal centre, mantle zone, and marginal zone). B cell lymphoma classification follows this general organization and classifies tumours depending on the compartment of origin of the particular tumour B cell population. This classification thus defines lymphoma according to a ‘histological subtype’ with defined clinic-biological features. Among these subtypes, mantle cell lymphoma (MCL) is a particularly aggressive form of B lymphoid cancer. This type of lymphoma is characterised by successive relapses and short survival (median is 4 to 5 years), although some patients can show long survival. Predictive biomarkers of this clinical behavior are lacking. This project aims to address this question. More specifically we propose to perform whole ‘exome’ sequencing – i.e. sequencing of all protein coding sections of all known protein coding genes in the genome – of the tumour B cell DNA from patients who show refractory or early relapsing disease compared to patients who show relatively long survival. By doing this genome scale study we hope to identify new gene mutations that can serve as molecular predictors of survival and bring new knowledges in the understanding between genetics and epigenetics in MCL.
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Improved Error Correction of NGS DataAlic, Andrei Stefan 15 July 2016 (has links)
[EN] The work done for this doctorate thesis focuses on error correction of Next Generation Sequencing (NGS) data in the context of High Performance Computing (HPC).
Due to the reduction in sequencing cost, the increasing output of the sequencers and the advancements in the biological and medical sciences, the amount of NGS data has increased tremendously.
Humans alone are not able to keep pace with this explosion of information, therefore computers must assist them to ease the handle of the deluge of information generated by the sequencing machines.
Since NGS is no longer just a research topic (used in clinical routine to detect cancer mutations, for instance), requirements in performance and accuracy are more stringent.
For sequencing to be useful outside research, the analysis software must work accurately and fast.
This is where HPC comes into play.
NGS processing tools should leverage the full potential of multi-core and even distributed computing, as those platforms are extensively available.
Moreover, as the performance of the individual core has hit a barrier, current computing tendencies focus on adding more cores and explicitly split the computation to take advantage of them.
This thesis starts with a deep analysis of all these problems in a general and comprehensive way (to reach out to a very wide audience), in the form of an exhaustive and objective review of the NGS error correction field.
We dedicate a chapter to this topic to introduce the reader gradually and gently into the world of sequencing.
It presents real problems and applications of NGS that demonstrate the impact this technology has on science.
The review results in the following conclusions: the need of understanding of the specificities of NGS data samples (given the high variety of technologies and features) and the need of flexible, efficient and accurate tools for error correction as a preliminary step of any NGS postprocessing.
As a result of the explosion of NGS data, we introduce MuffinInfo.
It is a piece of software capable of extracting information from the raw data produced by the sequencer to help the user understand the data.
MuffinInfo uses HTML5, therefore it runs in almost any software and hardware environment.
It supports custom statistics to mould itself to specific requirements.
MuffinInfo can reload the results of a run which are stored in JSON format for easier integration with third party applications.
Finally, our application uses threads to perform the calculations, to load the data from the disk and to handle the UI.
In continuation to our research and as a result of the single core performance limitation, we leverage the power of multi-core computers to develop a new error correction tool.
The error correction of the NGS data is normally the first step of any analysis targeting NGS.
As we conclude from the review performed within the frame of this thesis, many projects in different real-life applications have opted for this step before further analysis.
In this sense, we propose MuffinEC, a multi-technology (Illumina, Roche 454, Ion Torrent and PacBio -experimental), any-type-of-error handling (mismatches, deletions insertions and unknown values) corrector.
It surpasses other similar software by providing higher accuracy (demonstrated by three type of tests) and using less computational resources.
It follows a multi-steps approach that starts by grouping all the reads using a k-mers based metric.
Next, it employs the powerful Smith-Waterman algorithm to refine the groups and generate Multiple Sequence Alignments (MSAs).
These MSAs are corrected by taking each column and looking for the correct base, determined by a user-adjustable percentage.
This manuscript is structured in chapters based on material that has been previously published in prestigious journals indexed by the Journal of Citation Reports (on outstanding positions) and relevant congresses. / [ES] El trabajo realizado en el marco de esta tesis doctoral se centra en la corrección de errores en datos provenientes de técnicas NGS utilizando técnicas de computación intensiva.
Debido a la reducción de costes y el incremento en las prestaciones de los secuenciadores, la cantidad de datos disponibles en NGS se ha incrementado notablemente. La utilización de computadores en el análisis de estas muestras se hace imprescindible para poder dar respuesta a la avalancha de información generada por estas técnicas. El uso de NGS transciende la investigación con numerosos ejemplos de uso clínico y agronómico, por lo que aparecen nuevas necesidades en cuanto al tiempo de proceso y la fiabilidad de los resultados. Para maximizar su aplicabilidad clínica, las técnicas de proceso de datos de NGS deben acelerarse y producir datos más precisos. En este contexto es en el que las técnicas de comptuación intensiva juegan un papel relevante. En la actualidad, es común disponer de computadores con varios núcleos de proceso e incluso utilizar múltiples computadores mediante técnicas de computación paralela distribuida. Las tendencias actuales hacia arquitecturas con un mayor número de núcleos ponen de manifiesto que es ésta una aproximación relevante.
Esta tesis comienza con un análisis de los problemas fundamentales del proceso de datos en NGS de forma general y adaptado para su comprensión por una amplia audiencia, a través de una exhaustiva revisión del estado del arte en la corrección de datos de NGS. Esta revisión introduce gradualmente al lector en las técnicas de secuenciación masiva, presentando problemas y aplicaciones reales de las técnicas de NGS, destacando el impacto de esta tecnología en ciencia. De este estudio se concluyen dos ideas principales: La necesidad de analizar de forma adecuada las características de los datos de NGS, atendiendo a la enorme variedad intrínseca que tienen las diferentes técnicas de NGS; y la necesidad de disponer de una herramienta versátil, eficiente y precisa para la corrección de errores.
En el contexto del análisis de datos, la tesis presenta MuffinInfo. La herramienta MuffinInfo es una aplicación software implementada mediante HTML5. MuffinInfo obtiene información relevante de datos crudos de NGS para favorecer el entendimiento de sus características y la aplicación de técnicas de corrección de errores, soportando además la extensión mediante funciones que implementen estadísticos definidos por el usuario. MuffinInfo almacena los resultados del proceso en ficheros JSON. Al usar HTML5, MuffinInfo puede funcionar en casi cualquier entorno hardware y software. La herramienta está implementada aprovechando múltiples hilos de ejecución por la gestión del interfaz.
La segunda conclusión del análisis del estado del arte nos lleva a la oportunidad de aplicar de forma extensiva técnicas de computación de altas prestaciones en la corrección de errores para desarrollar una herramienta que soporte múltiples tecnologías (Illumina, Roche 454, Ion Torrent y experimentalmente PacBio). La herramienta propuesta (MuffinEC), soporta diferentes tipos de errores (sustituciones, indels y valores desconocidos). MuffinEC supera los resultados obtenidos por las herramientas existentes en este ámbito. Ofrece una mejor tasa de corrección, en un tiempo muy inferior y utilizando menos recursos, lo que facilita además su aplicación en muestras de mayor tamaño en computadores convencionales. MuffinEC utiliza una aproximación basada en etapas multiples. Primero agrupa todas las secuencias utilizando la métrica de los k-mers. En segundo lugar realiza un refinamiento de los grupos mediante el alineamiento con Smith-Waterman, generando contigs. Estos contigs resultan de la corrección por columnas de atendiendo a la frecuencia individual de cada base.
La tesis se estructura por capítulos cuya base ha sido previamente publicada en revistas indexadas en posiciones dest / [CAT] El treball realitzat en el marc d'aquesta tesi doctoral se centra en la correcció d'errors en dades provinents de tècniques de NGS utilitzant tècniques de computació intensiva.
A causa de la reducció de costos i l'increment en les prestacions dels seqüenciadors, la quantitat de dades disponibles a NGS s'ha incrementat notablement. La utilització de computadors en l'anàlisi d'aquestes mostres es fa imprescindible per poder donar resposta a l'allau d'informació generada per aquestes tècniques. L'ús de NGS transcendeix la investigació amb nombrosos exemples d'ús clínic i agronòmic, per la qual cosa apareixen noves necessitats quant al temps de procés i la fiabilitat dels resultats. Per a maximitzar la seua aplicabilitat clínica, les tècniques de procés de dades de NGS han d'accelerar-se i produir dades més precises. En este context és en el que les tècniques de comptuación intensiva juguen un paper rellevant. En l'actualitat, és comú disposar de computadors amb diversos nuclis de procés i inclús utilitzar múltiples computadors per mitjà de tècniques de computació paral·lela distribuïda. Les tendències actuals cap a arquitectures amb un nombre més gran de nuclis posen de manifest que és esta una aproximació rellevant.
Aquesta tesi comença amb una anàlisi dels problemes fonamentals del procés de dades en NGS de forma general i adaptat per a la seua comprensió per una àmplia audiència, a través d'una exhaustiva revisió de l'estat de l'art en la correcció de dades de NGS. Esta revisió introduïx gradualment al lector en les tècniques de seqüenciació massiva, presentant problemes i aplicacions reals de les tècniques de NGS, destacant l'impacte d'esta tecnologia en ciència. D'este estudi es conclouen dos idees principals: La necessitat d'analitzar de forma adequada les característiques de les dades de NGS, atenent a l'enorme varietat intrínseca que tenen les diferents tècniques de NGS; i la necessitat de disposar d'una ferramenta versàtil, eficient i precisa per a la correcció d'errors.
En el context de l'anàlisi de dades, la tesi presenta MuffinInfo. La ferramenta MuffinInfo és una aplicació programari implementada per mitjà de HTML5. MuffinInfo obté informació rellevant de dades crues de NGS per a afavorir l'enteniment de les seues característiques i l'aplicació de tècniques de correcció d'errors, suportant a més l'extensió per mitjà de funcions que implementen estadístics definits per l'usuari. MuffinInfo emmagatzema els resultats del procés en fitxers JSON. A l'usar HTML5, MuffinInfo pot funcionar en gairebé qualsevol entorn maquinari i programari. La ferramenta està implementada aprofitant múltiples fils d'execució per la gestió de l'interfície.
La segona conclusió de l'anàlisi de l'estat de l'art ens porta a l'oportunitat d'aplicar de forma extensiva tècniques de computació d'altes prestacions en la correcció d'errors per a desenrotllar una ferramenta que suport múltiples tecnologies (Illumina, Roche 454, Ió Torrent i experimentalment PacBio). La ferramenta proposada (MuffinEC), suporta diferents tipus d'errors (substitucions, indels i valors desconeguts). MuffinEC supera els resultats obtinguts per les ferramentes existents en este àmbit. Oferix una millor taxa de correcció, en un temps molt inferior i utilitzant menys recursos, la qual cosa facilita a més la seua aplicació en mostres més gran en computadors convencionals. MuffinEC utilitza una aproximació basada en etapes multiples. Primer agrupa totes les seqüències utilitzant la mètrica dels k-mers. En segon lloc realitza un refinament dels grups per mitjà de l'alineament amb Smith-Waterman, generant contigs. Estos contigs resulten de la correcció per columnes d'atenent a la freqüència individual de cada base.
La tesi s'estructura per capítols la base de la qual ha sigut prèviament publicada en revistes indexades en posicions destacades de l'índex del Journal of Citation Repor / Alic, AS. (2016). Improved Error Correction of NGS Data [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/67630 / TESIS
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Zpracování unikátních molekulárních indexů bez mapování k referenčnímu genomu / Processing of Unique Molecular Identifiers without Mapping to a Reference GenomeBarilíková, Lujza January 2020 (has links)
Hlavným cieľom tejto práce je návrh nového algoritmu k spracovaniu unikátnych molekulárnych indexov bez mapovania na referenčný genóm. O tieto náhodné oligonukleotidové sekvencie neustále vzrastá záujem, pretože uľahčujú rozpoznávať PCR chyby a skresľovanie údajov. Keďže používanie technológií sekvenovania novej generácie neustále rastie, je vynaložené veľké úsilie vyvíjať nástroje pre analýzu produkovaných dát. V súčasnosti sú nástroje na riešenie týchto chýb relatívne časovo náročné a zložité z dôvodu výpočtovo náročného zarovnania. Najdôležitejšie obmedzenie týchto nástrojov spočíva v skutočnosti, že pri spracovávaní duplikátov sú povolené multi-mapované čítania. Tieto čítania sú zvyčajne ignorované, čo môže viesť k zníženiu kvantitatívnej presnosti a spôsobiť zavádzajúcu interpretáciu výsledkov daného sekvenovania. V snahe vyriešiť tento problém je v tejto práci uvedený nový prístup, ktorý umožňuje odhad absolútneho počtu jedinečných molekúl s relatívne rýchlym a spoľahlivým spôsobom.
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Diferenciální exprese genů na zakladě negativního binomického modelu / Differential Gene expression using a negative binomial modelJanáková, Tereza January 2014 (has links)
Hlavním cílem této diplomové práce je analýza diferenciální exprese genů na základě negativního binomického modelu. Úvodní část je věnována teoretickému základu, pojednává o sekvenování RNA, sekvenování nové generace, výhodách a možném využití, formátu fastQ aj. Následující část už se zabývá samotnou praktickou částí, zde byl vybrán vhodný set genů, které budou později analyzovány a příslušná data byla stažena. Tato data byla zarovnána k lidskému genomu verze 37 Burrowsovou-Wheelerovou transformací s využitím bowtie mapovače, byly tak vytvořeny soubory ve formátu SAM. Toto soubory dat byly později setříděny pomocí nástroje SAMtools. Následně byly v programovém prostředí Matlab (verze R2013b) vytvořeny anotované objekty genů s využitím služby Ensembl´s BioMart. Dále byla určena genová exprese a byly odhadnuty faktory velikosti knihovny. Na závěr byly odhadnuty parametry negativního binomického rozložení a byla vyhodnocena diferenciální exprese genů.
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Porovnání eukaryotních genomů / Eucaryotic Genomes ComparisonPuterová, Janka January 2015 (has links)
Main motive of this master thesis was the need of good bioinformatics tools for genome comparison and improvement of one of the existing tools - RepeatExplorer. This work offers an overview of transposable elements in DNA, existing tools for identification and analysis of repetitions in sequenced genomes, summary of currently used genome sequencing methods. This work describes shortcomings of RepeatExplorer tool with focus on comparative analysis of genomes. Two solutions to remove these problems were designed and implemented. The first solution is designed for comparing pairs of genomes. The principle of this solution is based on comparison of similarity of distribution of contigs coverages using Kolmogorov-Smirnov test, thanks to which we are able to determine different parts in the genomes.The second solution, which is used to compare multiple genomes, is based on the method of mapping reads from compared genomes to the reference genome contigs and provides contigs coverage graphs, by which we are able to determine the variability of the repeats.Their functionality was verified on real NGS data of organism Silene latifolia.
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Caractérisation génomique des anomalies de la pigmentation cutanée en mosaïque / Genomic characterization of mosaic cutaneous pigmentary disordersSorlin, Arthur 04 November 2019 (has links)
Introduction : Les dyschromies cutanées en mosaïque ont fait suspecter de longue date l’implication d’un mosaïcisme génétique sous-jacent. Ces évènements post-zygotiques sont cependant difficilement détectables par les techniques conventionnelles. Ainsi, les bases génétiques des dyschromies en mosaïque étaient restées mal connues. Matériel et méthodes : la cohorte M.U.S.T.A.R.D rassemble des échantillons d’ADN de biopsies cutanées de patients porteurs d’un mosaïcisme pigmentaire. Après une analyse phénotypique spécialisée, ces échantillons sont étudiés en séquençage à forte profondeur, d’exome (ES) en trio, ou ciblé. Les données sont analysées à l’aide d’un pipeline dédié, permettant la détection de variations ponctuelles en mosaïque (mSNV) mais également de diverses anomalies chromosomiques en mosaïque. Résultats : De 2013 à 2019, 101 patients ont été inclus. Un ES a été réalisé pour 56 patients, identifiant un mSNV chez 12 patients, dans 7 gènes dont 4 nouveaux (RHOA, DOCK1, GNA13, TFE3), et une anomalie chromosomique chez 17 patients. Une étude ciblée de ces gènes chez 40 autres patients était positive pour 17, soit un rendement diagnostique global à 55% (46/84). Conclusion : Ce travail illustre l’importance d’une approche bioinformatique polyvalente, combinée à une expertise clinique, pour la détermination des causes génétiques des dyschromies cutanées en mosaïque. Il a également mis en évidence le rôle de la voie de signalisation dépendant des Rho GTPases, faisant progresser notre compréhension de la physiopathologie des dyschromies en mosaïque, une étape nécessaire à l’amélioration de la prise en charge de ces patients porteurs de maladies rares et complexes. / Introduction: Mosaic cutaneous dyschromia is strongly evocative of an underlying genetic mosaicism. These post-zygotic events are challenging for conventional diagnostic tools. Thus, genetic basis of mosaic cutaneous dyschromia still remained poorly understood. Materials and Methods: The M.U.S.T.A.R.D. cohort gathers DNA from skin biopsies of patients with mosaic cutaneous dyschromia. After a specialised phenotype analysis, they are referred to either trio exome sequencing (ES) at 200X, or targeted ultra-deep sequencing (60,000X) of candidate genes. Data are analysed with a tailored pipeline, allowing detection of both low-rate nucleotidic variations or chromosomal events. Results: From 2013 to 2019, 101 patients were included. ES was performed for 56, with identification of mosaic SNV in 12 patients in 7 new genes, including 4 new genes (RHOA, DOCK1, GNA13, TFE3), and mosaic chromosomal anomalies in 17 patients. A targeted sequencing of these genes was performed for 40 more patients, with a confirmed mosaic SNV in 17, and a global diagnostic yield of 55% (46/84). Conclusion: This work highlights the importance of a versatile bioinformatic approach combined to a clinical expertise, to decipher the chromosomal and molecular aetiologies of developmental anomalies with mosaic cutaneous dyschromia. It also pinpoints the role of the Rho GTPase pathway, which will help enhancing our understanding of mosaic cutaneous dyschromia, and may ultimately result in better patients’ care.
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