Dissertations / Theses on the topic 'High throughput sequencing (NGS)'
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Kawalia, Amit [Verfasser], Peter [Gutachter] Nürnberg, and Michael [Gutachter] Nothnagel. "Addressing NGS Data Challenges: Efficient High Throughput Processing and Sequencing Error Detection / Amit Kawalia ; Gutachter: Peter Nürnberg, Michael Nothnagel." Köln : Universitäts- und Stadtbibliothek Köln, 2016. http://d-nb.info/112370368X/34.
Full textBisseux, Maxime. "Dynamique de la circulation des Entérovirus de l'homme à l'environnement : Etude par séquençage haut débit." Thesis, Université Clermont Auvergne (2017-2020), 2017. http://www.theses.fr/2017CLFAS013.
Full textEnterovirus (EV) are Picornaviruses (non-enveloped, positive-sense RNA viruses), characterized by a large genetic and antigenic diversity (116 types classified within 4 taxonomic species EV-A to D) and rapid evolution. Human infections are frequent, highly contagious from stools and occur as outbreaks. The infections are mainly asymptomatic or benign but severe or fatal cases can be reported in young children. Poliomyelitis is the model EV infection. Combined with clinical and virological surveillance, mass vaccination is closer than ever to achieve the WHO program of the Global Polio Eradication Initiative. However, the detection of wild type polioviruses in polio-free countries and the recent worldwide emergence of non-polio enteroviruses (EV-A71, EV-D68) associated with severe clinical manifestations underscore the importance of surveilling EV circulation in the general population. The aim of the PhD thesis was the detection and identification of EV strains in wastewater treated in the sewage treatment plant at Clermont-Ferrand (France). The viral data were compared with those reported through clinical surveillance to obtain a comprehensive picture of the viral circulation in the local population. A method was developed to concentrate viruses from raw and treated wastewater and molecular assays were used to detect EVs and 6 other human enteric viruses. The viral genomes were detected in all samples from October 2014 to October 2015, with a median of 6 and 4 different viruses in raw and treated wastewater respectively. Phylogenetic analysis of viral sequences (EV, hepatitis A and E viruses) determined in wastewater and reported in patients during the sampling period, showed the efficiency of the method for surveilling enteric viruses in the community. The EV diversity in raw wastewater was analyzed by sequencing of amplicons with the Illumina high throughput technology (metabarcoding). The analysis revealed a large viral diversity and the silent circulation of 25 types not detected from hospital data (in particular 9 EV-C, of which sequences of vaccine poliovirus 1). The phylogenetic analyses of intra-typic variants showed different epidemic patterns in the predominant EV types circulating over the study period. The data demonstrate the feasibility and sensitivity of the strategy developed for the detection and characterization of EV in wastewater and provide a future prospect for the implementation of environmental surveillance of non-polio EV infections in epidemiological studies, epidemic prevention, and for health alert. Combining the surveillance of enteric viruses in the environment and in the clinical setting allows a better understanding of their prevalence. This global approach of virus circulation and ecological health represents an important investment for laboratories, which will require integration in national and international collaboration networks beyond the scope of enterovirus surveillance
Nemoz, Benjamin. "Exploration longitudinale à haut débit et en cellule unique du répertoire d'anticorps neutralisants à large spectre chez un neutraliseur d'élite du VIH-1." Electronic Thesis or Diss., Université Grenoble Alpes, 2024. http://www.theses.fr/2024GRALV012.
Full textHuman Immunodeficiency Virus type 1 (HIV-1) infection remains a major global health concern, with an estimated 37.7 million people living with the virus worldwide and new contaminations above a million cases yearly. Efficient anti-retroviral therapies are available, allowing a sustained relief for infected individuals. These therapeutics have also contributed to a better prevention and helped curb the epidemic, notably in high-income countries. However, a vaccine is still highly awaited for controlling this epidemic, especially in lower-income regions and precarious settings.The protective role of neutralizing antibodies (NAbs) has been unequivocally demonstrated in both animal models of HIV infection and in human settings. Consequently, the development of a B-cell-based vaccine capable of eliciting antibodies (Abs) with the ability to neutralize the majority of circulating viruses, namely broadly NAbs (bNAbs), could be foreseen as an answer to the HIV pandemic.The investigation of bNAb development in HIV-1 elite neutralizers provides valuable insights to inform the design of such vaccines. To date, most of the undertaken studies have relied on conventional single B-cell FACS sorting to isolate bNAbs. In the present study, we have used the Chromium Single Cell Immune Profiling approach to conduct a high-throughput longitudinal single-cell exploration of the B-cell repertoire in an HIV-1 elite neutralizer. Importantly, this novel method enables the use of a much greater number of HIV envelope glycoprotein (Env) baits compared to regular FACS-based Ab isolation studies, providing a more comprehensive view of the anti-Env Ab repertoire. In addition, this approach yields a wealth of information on the nature of the specific Abs identified and the corresponding B-cells.The study enabled the uncovering of the sequence of 12,130 putative HIV Env specific Abs. Antibodies from 39 lineages were produced and tested for neutralization, revealing 21 distinct neutralizing lineages. The results thus demonstrated the ability of the method to explore large antigen-specific Ab repertoires from longitudinal samples. The neutralizing activity of Abs from four neutralizing lineages together recapitulated the serum activity of the donor, achieving neutralization against 62.4 % of a large predictive panel of 126 pseudoviruses. One of these neutralizing Ab lineages was shown to target the gp120 high-mannose patch supersite with great breadth and potency; Abs from this lineage were sensitive to the presence of a glycan in position N332. A single of those Abs achieved most of the neutralization breadth (51.1 %) with a high potency (mean IC50 of 91.1 ng.mL-1). This Ab exhibited a 23 AA-long CDRH3 and 20 % somatic hypermutation (SMH). The lineage showed continuous evolution over 6.5 years of maturation, with observed SHM rates ranging from 2.0 % to 30.6 % for the heavy chain, without any insertions or deletions.Conventional FACS-based sorting was previously used to isolate bNAbs from the same donor. In comparison, the single cell high-throughput approach made possible the isolation of orders of magnitude more Abs. Furthermore, the newly isolated NAbs were overall more potent and broader than those isolated previously, indicating the superiority of the novel method in recovering neutralizing lineages. Ongoing structural studies will elucidate the epitopes responsible for the broad neutralization observed in this donor. Together, the findings may help the design of reverse vaccine approaches, which show promise in the development of an effective AIDS vaccine
Horton, Dean J. "Using molecular techniques to investigate soil invertebrate communities in temperate forests." Kent State University / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=kent1448799316.
Full textRoguski, Łukasz 1987. "High-throughput sequencing data compression." Doctoral thesis, Universitat Pompeu Fabra, 2017. http://hdl.handle.net/10803/565775.
Full textGràcies als avenços en el camp de les tecnologies de seqüenciació, en els darrers anys la recerca biomèdica ha viscut una revolució, que ha tingut com un dels resultats l'explosió del volum de dades genòmiques generades arreu del món. La mida típica de les dades de seqüenciació generades en experiments d'escala mitjana acostuma a situar-se en un rang entre deu i cent gigabytes, que s'emmagatzemen en diversos arxius en diferents formats produïts en cada experiment. Els formats estàndards actuals de facto de representació de dades genòmiques són en format textual. Per raons pràctiques, les dades necessiten ser emmagatzemades en format comprimit. En la majoria dels casos, aquests mètodes de compressió es basen en compressors de text de caràcter general, com ara gzip. Amb tot, no permeten explotar els models d'informació especifícs de dades de seqüenciació. És per això que proporcionen funcionalitats limitades i estalvi insuficient d'espai d'emmagatzematge. Això explica per què operacions relativament bàsiques, com ara el processament, l'emmagatzematge i la transferència de dades genòmiques, s'han convertit en un dels principals obstacles de processos actuals d'anàlisi. Per tot això, aquesta tesi se centra en mètodes d'emmagatzematge i compressió eficients de dades generades en experiments de sequenciació. En primer lloc, proposem un compressor innovador d'arxius FASTQ de propòsit general. A diferència de gzip, aquest compressor permet reduir de manera significativa la mida de l'arxiu resultant del procés de compressió. A més a més, aquesta eina permet processar les dades a una velocitat alta. A continuació, presentem mètodes de compressió que fan ús de l'alta redundància de seqüències present en les dades de seqüenciació. Aquests mètodes obtenen la millor ratio de compressió d'entre els compressors FASTQ del marc teòric actual, sense fer ús de cap referència externa. També mostrem aproximacions de compressió amb pèrdua per emmagatzemar dades de seqüenciació auxiliars, que permeten reduir encara més la mida de les dades. En últim lloc, aportem un sistema flexible de compressió i un format de dades. Aquest sistema fa possible generar de manera semi-automàtica solucions de compressió que no estan lligades a cap mena de format específic d'arxius de dades genòmiques. Per tal de facilitar la gestió complexa de dades, diversos conjunts de dades amb formats heterogenis poden ser emmagatzemats en contenidors configurables amb l'opció de dur a terme consultes personalitzades sobre les dades emmagatzemades. A més a més, exposem que les solucions simples basades en el nostre sistema poden obtenir resultats comparables als compressors de format específic de l'estat de l'art. En resum, les solucions desenvolupades i descrites en aquesta tesi poden ser incorporades amb facilitat en processos d'anàlisi de dades genòmiques. Si prenem aquestes solucions conjuntament, aporten una base sòlida per al desenvolupament d'aproximacions completes encaminades a l'emmagatzematge i gestió eficient de dades genòmiques.
Mozere, M. "High-throughput sequencing analysis pipeline." Thesis, University College London (University of London), 2016. http://discovery.ucl.ac.uk/1528797/.
Full textDurif, Ghislain. "Multivariate analysis of high-throughput sequencing data." Thesis, Lyon, 2016. http://www.theses.fr/2016LYSE1334/document.
Full textThe statistical analysis of Next-Generation Sequencing data raises many computational challenges regarding modeling and inference, especially because of the high dimensionality of genomic data. The research work in this manuscript concerns hybrid dimension reduction methods that rely on both compression (representation of the data into a lower dimensional space) and variable selection. Developments are made concerning: the sparse Partial Least Squares (PLS) regression framework for supervised classification, and the sparse matrix factorization framework for unsupervised exploration. In both situations, our main purpose will be to focus on the reconstruction and visualization of the data. First, we will present a new sparse PLS approach, based on an adaptive sparsity-inducing penalty, that is suitable for logistic regression to predict the label of a discrete outcome. For instance, such a method will be used for prediction (fate of patients or specific type of unidentified single cells) based on gene expression profiles. The main issue in such framework is to account for the response to discard irrelevant variables. We will highlight the direct link between the derivation of the algorithms and the reliability of the results. Then, motivated by questions regarding single-cell data analysis, we propose a flexible model-based approach for the factorization of count matrices, that accounts for over-dispersion as well as zero-inflation (both characteristic of single-cell data), for which we derive an estimation procedure based on variational inference. In this scheme, we consider probabilistic variable selection based on a spike-and-slab model suitable for count data. The interest of our procedure for data reconstruction, visualization and clustering will be illustrated by simulation experiments and by preliminary results on single-cell data analysis. All proposed methods were implemented into two R-packages "plsgenomics" and "CMF" based on high performance computing
Langenberger, David. "High-throughput sequencing and small non-coding RNAs." Doctoral thesis, Universitätsbibliothek Leipzig, 2013. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-112876.
Full textZhang, Xuekui. "Mixture models for analysing high throughput sequencing data." Thesis, University of British Columbia, 2011. http://hdl.handle.net/2429/35982.
Full textRoberts, Adam. "Ambiguous fragment assignment for high-throughput sequencing experiments." Thesis, University of California, Berkeley, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=3616509.
Full textAs the cost of short-read, high-throughput DNA sequencing continues to fall rapidly, new uses for the technology have been developed aside from its original purpose in determining the genome of various species. Many of these new experiments use the sequencer as a digital counter for measuring biological activities such as gene expression (RNA-Seq) or protein binding (ChIP-Seq).
A common problem faced in the analysis of these data is that of sequenced fragments that are "ambiguous", meaning they resemble multiple loci in a reference genome or other sequence. In early analyses, such ambiguous fragments were ignored or were assigned to loci using simple heuristics. However, statistical approaches using maximum likelihood estimation have been shown to greatly improve the accuracy of downstream analyses and have become widely adopted Optimization based on the expectation-maximization (EM) algorithm are often employed by these methods to find the optimal sets of alignments, with frequent enhancements to the model. Nevertheless, these improvements increase complexity, which, along with an exponential growth in the size of sequencing datasets, has led to new computational challenges.
Herein, we present our model for ambiguous fragment assignment for RNA-Seq, which includes the most comprehensive set of parameters of any model introduced to date, as well as various methods we have explored for scaling our optimization procedure. These methods include the use of an online EM algorithm and a distributed EM solution implemented on the Spark cluster computing system. Our advances have resulted in the first efficient solution to the problem of fragment assignment in sequencing.
Furthermore, we are the first to create a fully generalized model for ambiguous fragment assignment and present details on how our method can provide solutions for additional high-throughput sequencing assays including ChIP-Seq, Allele-Specific Expression (ASE), and the detection of RNA-DNA Differences (RDDs) in RNA-Seq.
Hoffmann, Steve. "Genome Informatics for High-Throughput Sequencing Data Analysis." Doctoral thesis, Universitätsbibliothek Leipzig, 2014. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-152643.
Full textDiese Arbeit stellt drei verschiedene algorithmische und statistische Strategien für die Analyse von Hochdurchsatz-Sequenzierungsdaten vor. Zuerst führen wir eine auf enhanced Suffixarrays basierende heuristische Methode ein, die kurze Sequenzen mit grossen Genomen aligniert. Die Methode basiert auf der Idee einer fehlertoleranten Traversierung eines Suffixarrays für Referenzgenome in Verbindung mit dem Konzept der Matching-Statistik von Chang und einem auf Bitvektoren basierenden Alignmentalgorithmus von Myers. Die vorgestellte Methode unterstützt Paired-End und Mate-Pair Alignments, bietet Methoden zur Erkennung von Primersequenzen und zum trimmen von Poly-A-Signalen an. Auch in unabhängigen Benchmarks zeichnet sich das Verfahren durch hohe Sensitivität und Spezifität in simulierten und realen Datensätzen aus. Für eine große Anzahl von Sequenzierungsprotokollen erzielt es bessere Ergebnisse als andere bekannte Short-Read Alignmentprogramme. Zweitens stellen wir einen auf dynamischer Programmierung basierenden Algorithmus für das spliced alignment problem vor. Der Vorteil dieses Algorithmus ist seine Fähigkeit, nicht nur kollineare Spleiß- Ereignisse, d.h. Spleiß-Ereignisse auf dem gleichen genomischen Strang, sondern auch zirkuläre und andere nicht-kollineare Spleiß-Ereignisse zu identifizieren. Das Verfahren zeichnet sich durch eine hohe Genauigkeit aus: während es bei der Erkennung kollinearer Spleiß-Varianten vergleichbare Ergebnisse mit anderen Methoden erzielt, schlägt es die Wettbewerber mit Blick auf Sensitivität und Spezifität bei der Vorhersage nicht-kollinearer Spleißvarianten. Die Anwendung dieses Algorithmus führte zur Identifikation neuer Isoformen. In unserer Publikation berichten wir über eine neue Isoform des Tumorsuppressorgens p53. Da dieses Gen eines der am besten untersuchten Gene des menschlichen Genoms ist, könnte die Anwendung unseres Algorithmus helfen, eine Vielzahl weiterer Isoformen bei weniger prominenten Genen zu identifizieren. Drittens stellen wir ein datenadaptives Modell zur Identifikation von Single Nucleotide Variations (SNVs) vor. In unserer Arbeit zeigen wir, dass sich unser auf empirischen log-likelihoods basierendes Modell automatisch an die Qualität der Sequenzierungsexperimente anpasst und eine \"Entscheidung\" darüber trifft, welche potentiellen Variationen als SNVs zu klassifizieren sind. In unseren Simulationen ist diese Methode auf Augenhöhe mit aktuell eingesetzten Verfahren. Schließlich stellen wir eine Auswahl biologischer Ergebnisse vor, die mit den Besonderheiten der präsentierten Alignmentverfahren in Zusammenhang stehen
Duggett, Nicholas A. "High-throughput sequencing of the chicken gut microbiome." Thesis, University of Birmingham, 2016. http://etheses.bham.ac.uk//id/eprint/6678/.
Full textChiang, HyoJin Rosaria. "Examination of mammalian microRNAs by high-throughput sequencing." Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/65289.
Full textCataloged from PDF version of thesis.
Includes bibliographical references.
Small non-coding RNAs play an important role in a wide range of cellular events. MicroRNAs (miRNAs) are an abundant class of small RNAs that post-transcriptionally repress expression of their target genes. Since miRNA targeting is based on its sequence, accurate and comprehensive annotation of miRNA genes is fundamental to understanding miRNA gene regulation. Advances in high-throughput sequencing technology have led to discoveries of novel small RNA genes and identifications of their properties. We describe a method for construction of small-RNA library for Illumina sequencing platform that improves upon previous efforts. Sequencing data from small-RNA libraries constructed using this protocol can be used to profile small RNAs from a broad range of samples. In particular, we sequenced 60 million small RNAs from mouse brain, ovary, testes, embryonic stem cells, three embryonic stages, and whole newborns. The analysis of the data provide a substantially revised list of confidently identified murine miRNAs, thereby providing a more accurate picture of the general features of mammalian miRNAs and their abundance in the genome. In addition, our results revealed new aspects of miRNA biogenesis and modification, including tissue-specific strand preferences, sequential Dicer cleavage of a metazoan pre-miRNA, cases of consequential 5' heterogeneity, newly identified instances of miRNA editing, and widespread pre-miRNA uridylation reminiscent of Lin28-like miRNA regulation.
by HyoJin Rosaria Chiang.
Ph.D.
Stromberg, Michael Peter. "Enabling high-throughput sequencing data analysis with MOSAIK." Thesis, Boston College, 2010. http://hdl.handle.net/2345/1332.
Full textDuring the last few years, numerous new sequencing technologies have emerged that require tools that can process large amounts of read data quickly and accurately. Regardless of the downstream methods used, reference-guided aligners are at the heart of all next-generation analysis studies. I have developed a general reference-guided aligner, MOSAIK, to support all current sequencing technologies (Roche 454, Illumina, Applied Biosystems SOLiD, Helicos, and Sanger capillary). The calibrated alignment qualities calculated by MOSAIK allow the user to fine-tune the alignment accuracy for a given study. MOSAIK is a highly configurable and easy-to-use suite of alignment tools that is used in hundreds of labs worldwide. MOSAIK is an integral part of our genetic variant discovery pipeline. From SNP and short-INDEL discovery to structural variation discovery, alignment accuracy is an essential requirement and enables our downstream analyses to provide accurate calls. In this thesis, I present three major studies that were formative during the development of MOSAIK and our analysis pipeline. In addition, I present a novel algorithm that identifies mobile element insertions (non-LTR retrotransposons) in the human genome using split-read alignments in MOSAIK. This algorithm has a low false discovery rate (4.4 %) and enabled our group to be the first to determine the number of mobile elements that differentially occur between any two individuals
Thesis (PhD) — Boston College, 2010
Submitted to: Boston College. Graduate School of Arts and Sciences
Discipline: Biology
Xing, Zhengrong. "Poisson multiscale methods for high-throughput sequencing data." Thesis, The University of Chicago, 2016. http://pqdtopen.proquest.com/#viewpdf?dispub=10195268.
Full textIn this dissertation, we focus on the problem of analyzing data from high-throughput sequencing experiments. With the emergence of more capable hardware and more efficient software, these sequencing data provide information at an unprecedented resolution. However, statistical methods developed for such data rarely tackle the data at such high resolutions, and often make approximations that only hold under certain conditions.
We propose a model-based approach to dealing with such data, starting from a single sample. By taking into account the inherent structure present in such data, our model can accurately capture important genomic regions. We also present the model in such a way that makes it easily extensible to more complicated and biologically interesting scenarios.
Building upon the single-sample model, we then turn to the statistical question of detecting differences between multiple samples. Such questions often arise in the context of expression data, where much emphasis has been put on the problem of detecting differential expression between two groups. By extending the framework for a single sample to incorporate additional group covariates, our model provides a systematic approach to estimating and testing for such differences. We then apply our method to several empirical datasets, and discuss the potential for further applications to other biological tasks.
We also seek to address a different statistical question, where the goal here is to perform exploratory analysis to uncover hidden structure within the data. We incorporate the single-sample framework into a commonly used clustering scheme, and show that our enhanced clustering approach is superior to the original clustering approach in many ways. We then apply our clustering method to a few empirical datasets and discuss our findings.
Finally, we apply the shrinkage procedure used within the single-sample model to tackle a completely different statistical issue: nonparametric regression with heteroskedastic Gaussian noise. We propose an algorithm that accurately recovers both the mean and variance functions given a single set of observations, and demonstrate its advantages over state-of-the art methods through extensive simulation studies.
de, Lange Katrina Melanie. "Understanding inflammatory bowel disease using high-throughput sequencing." Thesis, University of Cambridge, 2017. https://www.repository.cam.ac.uk/handle/1810/265370.
Full textSchwartz, Jerrod Joseph. "Technologies for high throughput single molecule DNA sequencing /." May be available electronically:, 2009. http://proquest.umi.com/login?COPT=REJTPTU1MTUmSU5UPTAmVkVSPTI=&clientId=12498.
Full textSiragusa, Enrico [Verfasser]. "Approximate string matching for high-throughput sequencing / Enrico Siragusa." Berlin : Freie Universität Berlin, 2015. http://d-nb.info/1074404882/34.
Full textKeebler, Jonathan Edward Myers. "Spontaneous Mutation Discovery via High-Throughput Sequencing of Pedigrees." NCSU, 2010. http://www.lib.ncsu.edu/theses/available/etd-03312010-151914/.
Full textWeese, David [Verfasser]. "Indices and Applications in High-Throughput Sequencing / David Weese." Berlin : Freie Universität Berlin, 2013. http://d-nb.info/1036130150/34.
Full textPerson, Kerry P. (Kerry Patrick). "Operational streamlining in a high-throughput genome sequencing center." Thesis, Massachusetts Institute of Technology, 2006. http://hdl.handle.net/1721.1/37248.
Full textIncludes bibliographical references (p. 83-84).
Advances in medicine rely on accurate data that is rapidly provided. It is therefore critical for the Genome Sequencing platform of the Broad Institute of MIT and Harvard to continually strive to reduce cost, improve throughput, and increase the quality of its data output. In the past, new technology in the form of both chemistry improvements and robotics has allowed the Institute to achieve these goals in a step-wise manner. However, as the rate of technology progression in sequencing has slowed, the Institute has been forced to look to continuous, incremental improvement in order to achieve its goals. The Core Sequencing/Detection group handles the high-throughput sequencing duties at the Broad Institute. Through the use of robotics and cutting edge biology, they are able to process and sequence upwards of 50 billion bases of DNA per year. The work that this thesis was based on took place primarily in this automated production area. This thesis utilizes a number of lean concepts, including the 7 Wastes and pull production control.
(cont.) Kanban systems, workflow changes, and a 5S implementation were used to bring these concepts to life at the Broad Institute. In order to correctly size the kanban system, process buildup diagrams and discrete event simulation were used. Each of these tools helped to drive the process towards the Institute's goals of reducing cost and improving quality and throughput.
by Kerry P. Person.
S.M.
M.B.A.
Fritz, Markus Hsi-Yang. "Exploiting high throughput DNA sequencing data for genomic analysis." Thesis, University of Cambridge, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.610819.
Full textWoolford, Julie Ruth. "Statistical analysis of small RNA high-throughput sequencing data." Thesis, University of Cambridge, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.610375.
Full textPérez, Cantalapiedra Carlos. "Accessing genetic variability in Spanish barleys through high-throughput sequencing." Doctoral thesis, Universitat Autònoma de Barcelona, 2016. http://hdl.handle.net/10803/399850.
Full textLa cebada es un cultivo importante en la región mediterránea, caracterizada por escasas e irregulares precipitaciones. En la Península Ibérica, ha sido cultivada durante miles de años, surgiendo adaptaciones específicas a estrés. Estas características, presentes en las variedades locales españolas, permanecen sin ser explotadas en mejora. La secuenciación de alto rendimiento (HTS, por sus siglas en inglés) ha revolucionado la investigación. Ha hecho posible secuenciar los genomas de múltiples organismos. El mapa físico de cebada, con secuencias asociadas, fue publicado a finales de 2012. Para sacar partido de estos recursos, había que facilitar el acceso a dicho recurso a genetistas y mejoradores. Este fue el objetivo que nos llevó a desarrollar Barleymap, una herramienta informática que permite localizar marcadores genéticos en el genoma de cebada. La aplicación integra y localiza marcadores de distintas plataformas de genotipado de cebada ampliamente utilizadas. Otra ventaja de la HTS es que se pueden llevar a cabo distintos tipos de experimentos con distintos objetivos de investigación. Nosotros utilizamos la secuenciación del exoma para mapeo fino de un QTL de resistencia a oidio de una variedad local española. A partir de una gran población de mapeo, fuimos capaces de acotar la posición del QTL a un solo contig físico. Además, pudimos identificar, y ensamblar parcialmente, un gene candidato que se expresa. Para conseguir esto, una serie de enfoques bioinformáticos fueron aplicados para diferenciar variación de presencia-ausencia, en un grupo de genes relacionados de la familia NBS-LRR. Otra aplicación poderosa de la HTS es RNAseq, que permite secuenciar transcriptomas completos, y llevar a cabo ensayos de expresión con una resolución sin precedente. Ensamblamos de novo los transcriptomas de un cultivar de cebada susceptible a sequía y de una variedad local española resistente. Comparamos los cambios de expresión, en hojas e inflorescencias en desarrollo de ambos genotipos, bajo tratamientos de sequía. Se revelaron grandes diferencias en sus respuestas a estrés. La comparación con otros trabajos de sequía en cebada, y el análisis de los factores de transcripción y elementos reguladores implicados proporcionó nuevos datos sobre la compleja red de expresión génica de cebada bajo estrés. En resumen, la HTS trae muchas nuevas posibilidades. Para aprovecharla totalmente, se debe fomentar colaboración de bioinformáticos y genetistas, para adaptar los nuevos recursos genómicos a necesidades específicas.
Barley is an important crop in the Mediterranean region, characterized by scarce and irregular rainfalls. In the Iberian Peninsula, it has been cultivated for thousands of years, leading to specific adaptations to prevalent biotic and abiotic stresses. These features, present in Spanish barley landraces, remain to be exploited in breeding. High-throughput sequencing (HTS) has revolutionized plant research. It has made it possible to sequence the genomes of multiple organisms. The sequence-enriched physical map of barley was published in late 2012. A first step to exploit barley genomics, for practical purposes, was facilitating geneticists and breeders access to the barley physical map. This was the aim which led us to the development of Barleymap, a software tool which allows locating genetic markers in the barley physical-genetic map. This application effectively integrates and maps markers from different widely used barley genotyping platforms, and, in general, any marker with sequence information. Another advantage of HTS is that diverse experimental setups can be used with different research objectives. Here, we used exome sequencing to fine-map a powdery mildew resistance QTL from a Spanish barley landrace. Exploiting a large mapping population, we were able to narrow down the position of the QTL to a single physical contig. Moreover, we could identify, and partially assemble, an expressed candidate gene. To achieve this, an array of bioinformatics approaches was applied to differentiate presence-absence variation, within a cluster of closely related genes of the NBS-LRR family. Another powerful application of HTS is RNAseq, which allows sequencing whole transcriptomes, and gene expression assays can be performed with unprecedented power. We de novo assembled the transcriptomes of a drought susceptible elite barley cultivar and a drought resistant Spanish barley landrace. Then, we compared the expression changes, in leaves and developing inflorescences from both genotypes, under drought treatments. This revealed large differences in their responses to stress. A comparison with other drought gene expression studies on barley, and an analysis of transcription factors and cis¬-regulatory elements involved, provided new insights into the complex barley gene expression network under stress. In summary, HTS has brought many new possibilities to plant research. To take full advantage of it, crosstalk between bioinformatics and genetics must be fostered to adapt the new genomic resources to specific needs.
Kircher, Martin. "Understanding and improving high-throughput sequencing data production and analysis." Doctoral thesis, Universitätsbibliothek Leipzig, 2011. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-71102.
Full textAnandhakumar, Chandran. "Advancing Synthetic Gene Regulators Development with High-Throughput Sequencing Technologies." 京都大学 (Kyoto University), 2015. http://hdl.handle.net/2433/202663.
Full textMohamadi, Hamid. "Parallel algorithms and software tools for high-throughput sequencing data." Thesis, University of British Columbia, 2017. http://hdl.handle.net/2429/62072.
Full textScience, Faculty of
Graduate
Stokowy, Tomasz, Markus Eszlinger, Michał Świerniak, Krzysztof Fujarewicz, Barbara Jarząb, Ralf Paschke, and Kurt Krohn. "Analysis options for high-throughput sequencing in miRNA expression profiling." Universitätsbibliothek Leipzig, 2014. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-144393.
Full textAinsworth, David. "Computational approaches for metagenomic analysis of high-throughput sequencing data." Thesis, Imperial College London, 2016. http://hdl.handle.net/10044/1/44070.
Full textWan, Ji. "Global analysis of alternative polyadenylation regulation using high-throughput sequencing." Diss., University of Iowa, 2012. https://ir.uiowa.edu/etd/3548.
Full textMammana, Alessandro [Verfasser]. "Patterns and algorithms in high-throughput sequencing count data / Alessandro Mammana." Berlin : Freie Universität Berlin, 2016. http://d-nb.info/1108270956/34.
Full textLove, Michael I. [Verfasser]. "Statistical analysis of high-throughput sequencing count data / Michael I. Love." Berlin : Freie Universität Berlin, 2013. http://d-nb.info/1043197842/34.
Full textWignall-Fleming, Elizabeth Bowie. "Investigations into the dynamics of paramyxovirus infections by high-throughput sequencing." Thesis, University of Glasgow, 2019. http://theses.gla.ac.uk/40905/.
Full textBallinger, Tracy J. "Analysis of genomic rearrangements in cancer from high throughput sequencing data." Thesis, University of California, Santa Cruz, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=3729995.
Full textIn the last century cancer has become increasingly prevalent and is the second largest killer in the United States, estimated to afflict 1 in 4 people during their life. Despite our long history with cancer and our herculean efforts to thwart the disease, in many cases we still do not understand the underlying causes or have successful treatments. In my graduate work, I’ve developed two approaches to the study of cancer genomics and applied them to the whole genome sequencing data of cancer patients from The Cancer Genome Atlas (TCGA). In collaboration with Dr. Ewing, I built a pipeline to detect retrotransposon insertions from paired-end high-throughput sequencing data and found somatic retrotransposon insertions in a fifth of cancer patients.
My second novel contribution to the study of cancer genomics is the development of the CN-AVG pipeline, a method for reconstructing the evolutionary history of a single tumor by predicting the order of structural mutations such as deletions, duplications, and inversions. The CN-AVG theory was developed by Drs. Haussler, Zerbino, and Paten and samples potential evolutionary histories for a tumor using Markov Chain Monte Carlo sampling. I contributed to the development of this method by testing its accuracy and limitations on simulated evolutionary histories. I found that the ability to reconstruct a history decays exponentially with increased breakpoint reuse, but that we can estimate how accurately we reconstruct a mutation event using the likelihood scores of the events. I further designed novel techniques for the application of CN-AVG to whole genome sequencing data from actual patients and applied these techniques to search for evolutionary patterns in glioblastoma multiforme using sequencing data from TCGA. My results show patterns of two-hit deletions, as we would expect, and amplifications occurring over several mutational events. I also find that the CN-AVG method frequently makes use of whole chromosome copy number changes following by localized deletions, a bias that could be mitigated through modifying the cost function for an evolutionary history.
Sibthorp, Christopher. "Analysis of the Aspergillus nidulans transcriptome using high-throughput RNA sequencing." Thesis, University of Liverpool, 2012. http://livrepository.liverpool.ac.uk/9973/.
Full textGlaus, Peter. "Bayesian methods for gene expression analysis from high-throughput sequencing data." Thesis, University of Manchester, 2014. https://www.research.manchester.ac.uk/portal/en/theses/bayesian-methods-for-gene-expression-analysis-from-highthroughput-sequencing-data(cf9680e0-a3f2-4090-8535-a39f3ef50cc4).html.
Full textSolayman, Md. "High-Throughput Sequencing Based Probing of Protein/RNA Structures and Functions." Thesis, Griffith University, 2022. http://hdl.handle.net/10072/416290.
Full textThesis (PhD Doctorate)
Doctor of Philosophy (PhD)
Institute for Glycomics
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Paicu, Claudia. "miRNA detection and analysis from high-throughput small RNA sequencing data." Thesis, University of East Anglia, 2016. https://ueaeprints.uea.ac.uk/63738/.
Full textBista, Iliana-Aglaia. "Defining a high throughput sequencing identification framework for freshwater ecosystem biomonitoring." Thesis, Bangor University, 2016. https://research.bangor.ac.uk/portal/en/theses/defining-a-high-throughput-sequencing-identification-framework-for-freshwater-ecosystem-biomonitoring(133e53f8-e300-495b-89e9-c1b3188d8acb).html.
Full textGIANGREGORIO, TANIA. "High throughput sequencing analysis for the molecular diagnosis of Inherited Thrombocytopenias." Doctoral thesis, Università degli Studi di Trieste, 2019. http://hdl.handle.net/11368/2962379.
Full textBarquist, Lars. "High-throughput experimental and computational studies of bacterial evolution." Thesis, University of Cambridge, 2014. https://www.repository.cam.ac.uk/handle/1810/245138.
Full textGhazanfar, Shila. "Statistical approaches to harness high throughput sequencing data in diverse biological systems." Thesis, The University of Sydney, 2017. http://hdl.handle.net/2123/17268.
Full textEsteve, Codina Anna. "Characterization of the Iberian pig genome and transcriptome using high throughput sequencing." Doctoral thesis, Universitat Autònoma de Barcelona, 2012. http://hdl.handle.net/10803/134673.
Full textOkonechnikov, Konstantin [Verfasser]. "High-throughput RNA sequencing: a step forward in transcriptome analysis / Konstantin Okonechnikov." Berlin : Freie Universität Berlin, 2016. http://d-nb.info/1084634686/34.
Full textRubelt, Florian [Verfasser]. "Investigations into the human immunoglobulin repertoire utilizing high-throughput sequencing / Florian Rubelt." Berlin : Freie Universität Berlin, 2012. http://d-nb.info/1030488894/34.
Full textChao, Yuanqing, and 晁元卿. "Studies of biofilm development by advanced microscopic techniques and high-throughput sequencing." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2013. http://hub.hku.hk/bib/B50899922.
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Civil Engineering
Doctoral
Doctor of Philosophy
Chen, Nanhua. "Application of high-throughput sequencing for the analyses of PRRSV-host interactions." Diss., Kansas State University, 2014. http://hdl.handle.net/2097/18664.
Full textDepartment of Diagnostic Medicine and Pathobiology
Raymond R. R. Rowland
Porcine Reproductive and Respiratory Syndrome Virus (PRRSV) is the most costly virus to the swine industry, worldwide. This study explored the application of deep sequencing techniques to understand better the virus-host interaction. On the virus side, PRRSV exists as a quasispecies. The first application of deep sequencing was to investigate amino acid substitutions in hypervariable regions during acute infection and after virus rebound. The appearance and disappearance of mutations, especially the generation of a new N-glycosylation site in GP5, indicated they are likely the result of immune selection. The second application of deep sequencing was to investigate the quasispecies makeup in pigs with severe combined immunodeficiency (SCID) that lack B and T cells. The results showed the same pattern of amino acid substitutions in SCID and normal littermates and no different mutations were identified between SCID and normal littermates. This suggests the mutations that appear during the early stages of infection are the product of the virus becoming adapted to replication in pigs. The third application of deep sequencing was to investigate the locations of recombination events between GFP-expressing PRRSV infectious clones. The results identified different cross-over occurred within three conserved regions between EGFP and GFPm genes. And finally, the fourth goal was applied to develop a set of sequencing tools for analyzing the host antibody repertoire. A simple method was developed to amplify swine VDJ repertoires. Shared and abundant VDJ sequences that are likely expressed by PRRSV-activated B cells were determined in pigs that had different neutralization activities. These sequences are potentially correlated with different antibody responses.
Bellos, Evangelos. "Statistical methods for elucidating copy number variation in high-throughput sequencing studies." Thesis, Imperial College London, 2014. http://hdl.handle.net/10044/1/24867.
Full textOral, Münevver. "Insights into isogenic clonal fish line development using high-throughput sequencing technologies." Thesis, University of Stirling, 2016. http://hdl.handle.net/1893/24909.
Full textBeckers, Matthew. "Quality checking and expression analysis of high-throughput small RNA sequencing data." Thesis, University of East Anglia, 2015. https://ueaeprints.uea.ac.uk/58581/.
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