Bibliographies thématiques / High throughput sequencing (NGS)

Littérature scientifique sur le sujet « High throughput sequencing (NGS) »

Auteur : Grafiati
Publié le 27 juillet 2024
Mis à jour le 29 juillet 2024

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Articles de revues sur le sujet "High throughput sequencing (NGS)"

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Montmayeur, Anna M., Terry Fei Fan Ng, Alexander Schmidt, Kun Zhao, Laura Magaña, Jane Iber, Christina J. Castro et al. « High-Throughput Next-Generation Sequencing of Polioviruses ». Journal of Clinical Microbiology 55, no 2 (7 décembre 2016) : 606–15. http://dx.doi.org/10.1128/jcm.02121-16.

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ABSTRACTThe poliovirus (PV) is currently targeted for worldwide eradication and containment. Sanger-based sequencing of the viral protein 1 (VP1) capsid region is currently the standard method for PV surveillance. However, the whole-genome sequence is sometimes needed for higher resolution global surveillance. In this study, we optimized whole-genome sequencing protocols for poliovirus isolates and FTA cards using next-generation sequencing (NGS), aiming for high sequence coverage, efficiency, and throughput. We found that DNase treatment of poliovirus RNA followed by random reverse transcription (RT), amplification, and the use of the Nextera XT DNA library preparation kit produced significantly better results than other preparations. The average viral reads per total reads, a measurement of efficiency, was as high as 84.2% ± 15.6%. PV genomes covering >99 to 100% of the reference length were obtained and validated with Sanger sequencing. A total of 52 PV genomes were generated, multiplexing as many as 64 samples in a single Illumina MiSeq run. This high-throughput, sequence-independent NGS approach facilitated the detection of a diverse range of PVs, especially for those in vaccine-derived polioviruses (VDPV), circulating VDPV, or immunodeficiency-related VDPV. In contrast to results from previous studies on other viruses, our results showed that filtration and nuclease treatment did not discernibly increase the sequencing efficiency of PV isolates. However, DNase treatment after nucleic acid extraction to remove host DNA significantly improved the sequencing results. This NGS method has been successfully implemented to generate PV genomes for molecular epidemiology of the most recent PV isolates. Additionally, the ability to obtain full PV genomes from FTA cards will aid in facilitating global poliovirus surveillance.
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Li, Niannian, Kairang Jin, Yanmin Bai, Haifeng Fu, Lin Liu et Bin Liu. « Tn5 Transposase Applied in Genomics Research ». International Journal of Molecular Sciences 21, no 21 (6 novembre 2020) : 8329. http://dx.doi.org/10.3390/ijms21218329.

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The development of high-throughput sequencing (next-generation sequencing technology (NGS)) and the continuous increase in experimental throughput require the upstream sample processing steps of NGS to be as simple as possible to improve the efficiency of the entire NGS process. The transposition system has fast “cut and paste” and “copy and paste” functions, and has been innovatively applied to the NGS field. For example, the Assay for Transposase-Accessible Chromatin with high throughput sequencing (ATAC-Seq) uses high-throughput sequencing to detect chromatin regions accessible by Tn5 transposase. Linear Amplification via Transposon Insertion (LIANTI) uses Tn5 transposase for linear amplification, haploid typing, and structural variation detection. Not only is it efficient and simple, it effectively shortens the time for NGS sample library construction, realizes large-scale and rapid sequencing, improves sequencing resolution, and can be flexibly modified for more technological innovation.
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Suravajhala, Prashanth, et Alexey Goltsov. « Three Grand Challenges in High Throughput Omics Technologies ». Biomolecules 12, no 9 (4 septembre 2022) : 1238. http://dx.doi.org/10.3390/biom12091238.

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Saeed, Muhammad, Zainab Jamil, Tayyab Shehzad, Syed Zia ul Hasan, Riffat Bibi, Safia Naureen Malik, Hafiz Matee-ur-Rehman et Raees Ahmed. « Role of Next Generation Sequencing (NGS) in Plant Disease Management : A Review ». Journal of Applied Research in Plant Sciences 4, no 01 (23 février 2023) : 512–17. http://dx.doi.org/10.38211/joarps.2023.04.01.61.

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A high throughput technique used to determine a part of the nucleotide sequence of an organism’s genome is called next generation sequencing (NGS). NGS has been Proven revolutionary in genomics. Clinical diagnostics, Plant diseases diagnostic and other aspects of medical are now made possible by sequencing. Techniques of NGS: there are different techniques of NGS which are being used in real life sciences i.e., Illumina sequencing, Pyrosequencing, Roche 454 sequencing and Ion torrent sequencing. All vintage methods like culturing in bacterial, fungal, and viral samples are being suppressed by next generation sequencing. The potential for random metagenomic sequencing of sick samples to find potential pathogens has surfaced with the development of next-generation high-throughput parallel sequencing technology. NGS enables highly efficient, rapid, low-cost DNA or RNA high-throughput sequencing of plant virus and viroids genomes, as well as specific small RNAs generated during infection. Although this technique is not so much familiar in the field of plant diseases. However, its widespread application in agronomic sciences will make it possible to create solutions to future food-related challenges that involve biotic stress.
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Williams, Gareth Haydn, Robert Paul Thatcher, Tiffany Eira Haddow, Keeda-Marie Hardisty et Marco Loddo. « Immunofocus-PD-L1 high throughput quantitative next generation sequencing assay. » Journal of Clinical Oncology 38, no 15_suppl (20 mai 2020) : e13521-e13521. http://dx.doi.org/10.1200/jco.2020.38.15_suppl.e13521.

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e13521 Background: Immunohistochemical (IHC) assays are presently used as the gold standard predictive tests for immunotherapy but are compromised due to a number of potential variables. Comparative studies have demonstrated differing levels of PD-L1 staining between assays which appears independent of the antibody binding epitope. Secondly, inter-reader reliability even between expert pathologists is problematic particularly for assessment of PD-L1 positive immune cell populations. Methods: To improve predictive testing for anti PD-L1/PD1 immunotherapies we have developed and validated a Next Generation Sequencing Platform, Immunofocus, able to perform high-throughput quantitative PD-L1 gene expression levels in routine diagnostic PWET biopsies. We applied Immunofocus to a cohort of 130 NSCLCs and compared PD-L1 gene expression levels with PD-L1 IHC scores generated using the VENTANA PD-L1 (SP142) Assay. The PD-L1 IHC assessment was carried out double blinded by an independent laboratory. PD-L1 IHC scores were calculated using an algorithm combining tumour proportion score (TPS) with a PD-L1 positive immune cell (IC) score and immune cell area. Results: An exceptionally high degree of correlation was observed between the NGS PD-L1 levels with the combined PD-L1 IHC scores (P < 0.001). Therapeutic cut points for NGS PD-L1 levels were identified corresponding to PD-L1 IHC defined clinical cut points. Notably, ~20% of patients with negative PD-L1 IHC scores showed high NGS PD-L1 expression levels. We hypothesize that these cases represent false negatives and identify a cohort of patients who have shown significant response rates to anti-PD-L1/PD-directed immunotherapies. Conclusions: The Immunofocus NGS PD-L1 assay has potential to greatly improve patient selection for immunotherapy by removing the IHC assay variables and inter-reader variability which compromise current PD-L1 IHC tests while also providing standardized high throughput in the clinical setting. Immunofocus is able to integrate gene expression with somatic mutation analysis allowing capture of networks regulating the immune-checkpoint including for example adaptive and innate resistance pathways, JAK1/2 pathways, differential MHC expression, TEFF gene signature, neoantigen surrogates such as DDR defects and TMB. The integration of NGS PD-L1 expression with other putative biomarkers of response is presently ongoing to further improve prediction of response.
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Kechin, Andrey, Viktoria Borobova, Ulyana Boyarskikh, Evgeniy Khrapov, Sergey Subbotin et Maxim Filipenko. « NGS-PrimerPlex : High-throughput primer design for multiplex polymerase chain reactions ». PLOS Computational Biology 16, no 12 (30 décembre 2020) : e1008468. http://dx.doi.org/10.1371/journal.pcbi.1008468.

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Multiplex polymerase chain reaction (PCR) has multiple applications in molecular biology, including developing new targeted next-generation sequencing (NGS) panels. We present NGS-PrimerPlex, an efficient and versatile command-line application that designs primers for different refined types of amplicon-based genome target enrichment. It supports nested and anchored multiplex PCR, redistribution among multiplex reactions of primers constructed earlier, and extension of existing NGS-panels. The primer design process takes into consideration the formation of secondary structures, non-target amplicons between all primers of a pool, primers and high-frequent genome single-nucleotide polymorphisms (SNPs) overlapping. Moreover, users of NGS-PrimerPlex are free from manually defining input genome regions, because it can be done automatically from a list of genes or their parts like exon or codon numbers. Using the program, the NGS-panel for sequencing the LRRK2 gene coding regions was created, and 354 DNA samples were studied successfully with a median coverage of 97.4% of target regions by at least 30 reads. To show that NGS-PrimerPlex can also be applied for bacterial genomes, we designed primers to detect foodborne pathogens Salmonella enterica, Escherichia coli O157:H7, Listeria monocytogenes, and Staphylococcus aureus considering variable positions of the genomes.
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Wang, Qi, Lijuan Cao, Guangying Sheng, Hongjie Shen, Jing Ling, Jundan Xie, Zhenni Ma et al. « Application of High-Throughput Sequencing in the Diagnosis of Inherited Thrombocytopenia ». Clinical and Applied Thrombosis/Hemostasis 24, no 9_suppl (13 août 2018) : 94S—103S. http://dx.doi.org/10.1177/1076029618790696.

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Inherited thrombocytopenia is a group of hereditary diseases with a reduction in platelet count as the main clinical manifestation. Clinically, there is an urgent need for a convenient and rapid diagnosis method. We introduced a high-throughput, next-generation sequencing (NGS) platform into the routine diagnosis of patients with unexplained thrombocytopenia and analyzed the gene sequencing results to evaluate the value of NGS technology in the screening and diagnosis of inherited thrombocytopenia. From a cohort of 112 patients with thrombocytopenia, we screened 43 patients with hereditary features. For the blood samples of these 43 patients, a gene sequencing platform for hemorrhagic and thrombotic diseases comprising 89 genes was used to perform gene detection using NGS technology. When we combined the screening results with clinical features and other findings, 15 (34.9%) of 43patients were diagnosed with inherited thrombocytopenia. In addition, 19 pathogenic variants, including 8 previously unreported variants, were identified in these patients. Through the use of this detection platform, we expect to establish a more effective diagnostic approach to such disorders.
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Wang, Jia-Wang, Wenxiu Zhang, Yan Zhang, Jiajia Zhou, Jing Li, Min Zhang, Shanshan Wen et al. « Reproducible and high sample throughput isomiR next-generation sequencing for cancer diagnosis. » Journal of Clinical Oncology 42, no 16_suppl (1 juin 2024) : e15013-e15013. http://dx.doi.org/10.1200/jco.2024.42.16_suppl.e15013.

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e15013 Background: Next-generation sequencing (NGS) can produce up to 6 Tb of data per run with single-nucleotide accuracy, making it ideal for quantifying isomiRs, which encompass both canonical miRNAs and their variants, for clinical applications. However, NGS has poor reproducibility and low sample throughput in quantifying circulating isomiRs due to significant technical variations and the limitations of the multiplex strategy, as evidenced by the fact that no isomiR NGS technique has been successfully used to diagnose cancer. Methods: To address these challenges, a library construction method including a dual unique-dual-index (DUDI) technology was developed. DUDI uses a pair of Inner UDI (IUDI) and outer UDI (OUDI) to label a sample. Twelve independent batches of isomiR NGS were carried out, including three repeated batches. Each batch included 100 gastric cancer and 100 control plasma samples. Batch effect, correlation coefficient (R), and principal component (PCA) analyses were used to evaluate technical reproducibility. Machine learning binary classification was used to assess biological reproducibility, with each pair of batch data serving interchangeably as both training and testing data. Results: In this multicenter study, over 700G of isomiR data were generated from 402 gastric cancer and 498 control samples, with a maximum error rate of 1 in 7 million isomiRs being assigned to wrong samples. The PCA plot indicates high technical reproducibility across the three repeated batches, shown by the extensive intermingling of data points from each batch and the lack of distinct batch-wise clustering. This observation is reinforced by that the R value for each of 239 isomiRs between the repeated batches are close to 1. While the mutual machine learning validations between the repeated batches yielded ~95% accuracy, indicating high biological reproducibility. The accuracies of the validations between the different batches of different samples range from 70% to 82%. The lower accuracy is as expected, given the high genetic heterogeneity of cancer and the small sample size. Furthermore, the IsomiR differentiated expression profiles from the current NGS study closely match those from prior qPCR studies. Conclusions: The DUDI library construction method can produce reproducible high sample throughput NGS data, yet it is cost-effective and straightforward. The maximum number of samples that can be multiplexed in an NGS project is almost one million, i.e., 976 * 976, as IUDI and OUDI can be any of the 976 designed DUDIs. This number far exceeds the high sample throughput requirements of any NGS application. While the capability to distinguish true biological variations of IsomiRs from technical noise, demonstrated by the high technical and biological reproducibility and concordance with the qPCR data, enables the development of robust machine learning algorithms for cancer diagnostics.
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Tripathi, Pooja, Jyotsna Singh, Jonathan A. Lal et Vijay Tripathi. « Next-Generation Sequencing : An Emerging Tool for Drug Designing ». Current Pharmaceutical Design 25, no 31 (14 novembre 2019) : 3350–57. http://dx.doi.org/10.2174/1381612825666190911155508.

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Background: With the outbreak of high throughput next-generation sequencing (NGS), the biological research of drug discovery has been directed towards the oncology and infectious disease therapeutic areas, with extensive use in biopharmaceutical development and vaccine production. Method: In this review, an effort was made to address the basic background of NGS technologies, potential applications of NGS in drug designing. Our purpose is also to provide a brief introduction of various Nextgeneration sequencing techniques. Discussions: The high-throughput methods execute Large-scale Unbiased Sequencing (LUS) which comprises of Massively Parallel Sequencing (MPS) or NGS technologies. The Next geneinvolved necessarily executes Largescale Unbiased Sequencing (LUS) which comprises of MPS or NGS technologies. These are related terms that describe a DNA sequencing technology which has revolutionized genomic research. Using NGS, an entire human genome can be sequenced within a single day. Conclusion: Analysis of NGS data unravels important clues in the quest for the treatment of various lifethreatening diseases and other related scientific problems related to human welfare.
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Chae, H., S. Rhee, K. P. Nephew et S. Kim. « BioVLAB-MMIA-NGS : microRNA-mRNA integrated analysis using high-throughput sequencing data ». Bioinformatics 31, no 2 (29 septembre 2014) : 265–67. http://dx.doi.org/10.1093/bioinformatics/btu614.

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Thèses sur le sujet "High throughput sequencing (NGS)"

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Kawalia, Amit [Verfasser], Peter [Gutachter] Nürnberg et 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.

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Bisseux, 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.

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Les entérovirus (EV) sont des Picornavirus (virus nus à génome ARN positif), caractérisés par une grande diversité génétique et antigénique (116 types classés en 4 espèces taxonomiques EV-A à D) et une évolution rapide. Les infections humaines sont très fréquentes, hautement contagieuses à partir des selles et épidémiques. La plupart des infections sont asymptomatiques ou bénignes ; elles peuvent être graves voire mortelles, en particulier chez les jeunes enfants. La poliomyélite, modèle d’infection à EV, est en voie d’éradication grâce aux programmes de vaccination et de surveillance sous l’égide de l’OMS. La détection de poliovirus sauvages dans des pays déclarés exempts de polio depuis plusieurs années et l’émergence récente de plusieurs EV non poliomyélitiques (EV-A71, EV-D68) associés à des manifestations cliniques sévères dans plusieurs régions du monde montrent l’importance de surveiller la circulation des EV dans la population humaine. Le but de la thèse était de rechercher et caractériser les EV dans les eaux usées de l’agglomération de Clermont-Ferrand et de comparer les données à celles de la surveillance clinique pour avoir une image plus complète de la circulation virale dans la population générale. Une méthode de concentration virale à partir des eaux usées prélevées en entrée (eaux usées brutes) et sortie (eaux usées traitées) de station d’épuration a été mise au point, permettant la détection moléculaire des EV et de 6 autres virus entériques humains. La présence de génomes viraux a été détectée dans tous les échantillons d’octobre 2014 à octobre 2015, avec une médiane de 6 virus différents en entrée de station et de 4 virus en sortie. L’analyse phylogénétique des séquences d’EV et des virus des hépatites A et E présents dans les eaux usées et les prélèvements cliniques des patients hospitalisés au CHU de Clermont-Ferrand pendant la même période, a validé l’approche mise en place pour surveiller la circulation communautaire d’un virus entérique. La diversité des EV présents dans les eaux usées brutes a été analysée par séquençage d’amplicons avec une technique haut débit Illumina (metabarcoding). Les résultats montrent la présence d’une grande diversité d’EV et la circulation silencieuse de 25 types (notamment 9 EV-C, dont des séquences de poliovirus 1 vaccinal) dans la population générale. L’analyse phylogénétique des variants intra-typiques a mis en évidence plusieurs profils épidémiques parmi les principaux types ayant circulé pendant la période d’étude. Les données obtenues montrent la faisabilité et la sensibilité de la stratégie développée pour détecter et caractériser les EV présents dans les eaux usées. Ils permettent de discuter la place de la surveillance environnementale dans la surveillance des infections à EV non polio (études épidémiologiques, prévention des épidémies, alertes sanitaires). Surveiller conjointement les virus entériques dans l’environnement et chez les patients permet une meilleure compréhension de leur prévalence. Cette approche globale de la circulation virale et de l’écologie de la santé représente un engagement important de la part des laboratoires et nécessitera une intégration dans des réseaux structurés de collaboration nationales et internationales dépassant la seule surveillance des EV
Enterovirus (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
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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.

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L'infection par le virus de l'immunodéficience humaine de type 1 (VIH-1) reste un problème majeur de santé publique à l'échelle mondiale, avec environ 37,7 millions de personnes vivant avec le virus et de nouvelles contaminations dépassant le million de cas par an. Des antirétroviraux efficaces permettent maintenant de traiter durablement les personnes infectées. Ces thérapies contribuent également à améliorer la prévention et à ralentir la progression de l'épidémie. Cependant, un vaccin reste nécessaire, en particulier pour contrôler l'épidémie dans les régions à faible revenu et les environnements précaires.Le rôle protecteur des anticorps neutralisants (AcN) a été démontré sans équivoque dans les modèles animaux d'infection par le VIH et chez l'homme. Par conséquent, le développement d'un vaccin visant à la production, par les cellules B, d'anticorps (Ac) capables de neutraliser la majorité des virus en circulation, à savoir des AcN à large spectre (AcNLS), pourrait être envisagé comme une réponse à la pandémie de VIH.L'étude du développement des AcNLS chez certains individus, dénommés neutraliseurs d’élite du VIH-1, fournit des informations précieuses pour la conception de tels vaccins. Jusqu'à présent, la plupart des études entreprises se sont appuyées sur le tri conventionnel de cellules B uniques par cytométrie en flux (FACS) pour isoler les AcNLS. Dans la présente étude, nous avons utilisé l'approche "Chromium Single Cell Immune Profiling" à haut débit sur cellules uniques (scRNA-seq) pour réaliser une exploration longitudinale du répertoire des cellules B chez un neutraliseur d'élite du VIH-1. Cette méthode permet d'utiliser comme appâts pour l'identification des cellules B spécifiques un nombre beaucoup plus important de glycoprotéines d’enveloppe (Env) du VIH par rapport aux approches d'isolement d'Ac basées sur le FACS, ce qui permet d'obtenir une analyse plus complète du répertoire en Ac anti-Env. En outre, cette approche fournit une multitude d'informations sur la nature des Ac spécifiques identifiés et sur les cellules B correspondantes.Notre étude a permis d'identifier la séquence de 12 130 anticorps spécifiques de la protéine Env du VIH. Des Ac de 39 lignées ont été produits et testés pour leurs capacités de neutralisation, révélant 21 lignées neutralisantes. Ces résultats démontrent la capacité de la méthode à explorer de vastes répertoires spécifiques d'antigènes à partir d'échantillons longitudinaux. L'activité neutralisante des Ac de quatre lignées récapitulait l'activité sérique du donneur, permettant de neutraliser 62,4 % d'un large panel prédictif de 126 pseudovirus. Une de ces lignées neutralisantes ciblait la région riche en mannose de la gp120. Par ailleurs, les Ac de cette lignée étaient sensibles à la présence d'un glycane en position N332. Un seul de ces Ac était responsable de la plus grande partie de cette neutralisation (51,1 %) avec une activité à faible concentration (IC50 moyenne de 91,1 ng.mL-1). Cet Ac possède un CDRH3 de 23 AA de long et 20 % d'hypermutation somatique (SMH). La lignée a montré une maturation continue sur 6,5 ans, avec des taux de SMH observés de 2,0 % à 30,6 % pour la chaîne lourde, sans insertion ou délétion.Un tri conventionnel basé sur la méthode FACS avait été utilisé précédemment pour isoler des AcNLS du même donneur. En comparaison, l'approche scRNA-seq a permis d'isoler des Ac en nombre bien supérieur. En outre, les AcN nouvellement isolés étaient globalement plus neutralisants et de plus large spectre que ceux isolés précédemment, ce qui indique la supériorité de la nouvelle méthode pour l'identification de lignées neutralisantes. Les études structurales en cours permettront d'élucider les épitopes responsables de la neutralisation observée chez ce donneur. L'ensemble de ces résultats pourrait contribuer à la conception d'approches de "vaccinologie inverse", qui représentent à l'heure actuelle un espoir pour la mise au point d'un vaccin contre le VIH
Human 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
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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.

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Roguski, Łukasz 1987. « High-throughput sequencing data compression ». Doctoral thesis, Universitat Pompeu Fabra, 2017. http://hdl.handle.net/10803/565775.

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Thanks to advances in sequencing technologies, biomedical research has experienced a revolution over recent years, resulting in an explosion in the amount of genomic data being generated worldwide. The typical space requirement for storing sequencing data produced by a medium-scale experiment lies in the range of tens to hundreds of gigabytes, with multiple files in different formats being produced by each experiment. The current de facto standard file formats used to represent genomic data are text-based. For practical reasons, these are stored in compressed form. In most cases, such storage methods rely on general-purpose text compressors, such as gzip. Unfortunately, however, these methods are unable to exploit the information models specific to sequencing data, and as a result they usually provide limited functionality and insufficient savings in storage space. This explains why relatively basic operations such as processing, storage, and transfer of genomic data have become a typical bottleneck of current analysis setups. Therefore, this thesis focuses on methods to efficiently store and compress the data generated from sequencing experiments. First, we propose a novel general purpose FASTQ files compressor. Compared to gzip, it achieves a significant reduction in the size of the resulting archive, while also offering high data processing speed. Next, we present compression methods that exploit the high sequence redundancy present in sequencing data. These methods achieve the best compression ratio among current state-of-the-art FASTQ compressors, without using any external reference sequence. We also demonstrate different lossy compression approaches to store auxiliary sequencing data, which allow for further reductions in size. Finally, we propose a flexible framework and data format, which allows one to semi-automatically generate compression solutions which are not tied to any specific genomic file format. To facilitate data management needed by complex pipelines, multiple genomic datasets having heterogeneous formats can be stored together in configurable containers, with an option to perform custom queries over the stored data. Moreover, we show that simple solutions based on our framework can achieve results comparable to those of state-of-the-art format-specific compressors. Overall, the solutions developed and described in this thesis can easily be incorporated into current pipelines for the analysis of genomic data. Taken together, they provide grounds for the development of integrated approaches towards efficient storage and management of such data.
Gràcies 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.
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Mozere, M. « High-throughput sequencing analysis pipeline ». Thesis, University College London (University of London), 2016. http://discovery.ucl.ac.uk/1528797/.

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High-throughput sequencing methods were developed to increase the productivity of processing data from genomic DNA. Sequencing platforms are generating massive amounts of genetic variation data which makes it difficult to pinpoint a small subset of functionally important variants. The focus has now shifted from generating sequences to searching for the critical differences that separate normal variants from disease ones. Our High-throughput Sequencing Analysis Pipeline (HSAP) is a multistep analysis software designed to annotate and filter variants in a top-down fashion from Variant Calling Format (VCF) files in order to find disease causing variants in the patients. It is designed in Linux medium and is composed of a collection of interacting task-specific modules written in different programming languages (such as Python, C++) and shell scripts. Each module is designed to perform a specific task, such as: annotate variants with their functional characterisation, zygosity status, allele frequencies within population; filter variants depending on the inherited disease model, read depth, call quality, physical location and other criteria. The output is added to the universal VCF format file, which contains annotated and filtered genomic variants. The pipeline was verified by identifying/confirming a specific disease-causing mutation for a single-gene disorder. HSAP is designed as an open-source locally self-contained bootable software that uses only information from publicly available databases. It has a user-friendly offline web-interface that allows to select different modules and chain them together to create unique filtering arrangements in order to adapt the pipeline as needed.
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Durif, Ghislain. « Multivariate analysis of high-throughput sequencing data ». Thesis, Lyon, 2016. http://www.theses.fr/2016LYSE1334/document.

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L'analyse statistique de données de séquençage à haut débit (NGS) pose des questions computationnelles concernant la modélisation et l'inférence, en particulier à cause de la grande dimension des données. Le travail de recherche dans ce manuscrit porte sur des méthodes de réductions de dimension hybrides, basées sur des approches de compression (représentation dans un espace de faible dimension) et de sélection de variables. Des développements sont menés concernant la régression "Partial Least Squares" parcimonieuse (supervisée) et les méthodes de factorisation parcimonieuse de matrices (non supervisée). Dans les deux cas, notre objectif sera la reconstruction et la visualisation des données. Nous présenterons une nouvelle approche de type PLS parcimonieuse, basée sur une pénalité adaptative, pour la régression logistique. Cette approche sera utilisée pour des problèmes de prédiction (devenir de patients ou type cellulaire) à partir de l'expression des gènes. La principale problématique sera de prendre en compte la réponse pour écarter les variables non pertinentes. Nous mettrons en avant le lien entre la construction des algorithmes et la fiabilité des résultats.Dans une seconde partie, motivés par des questions relatives à l'analyse de données "single-cell", nous proposons une approche probabiliste pour la factorisation de matrices de comptage, laquelle prend en compte la sur-dispersion et l'amplification des zéros (caractéristiques des données single-cell). Nous développerons une procédure d'estimation basée sur l'inférence variationnelle. Nous introduirons également une procédure de sélection de variables probabiliste basée sur un modèle "spike-and-slab". L'intérêt de notre méthode pour la reconstruction, la visualisation et le clustering de données sera illustré par des simulations et par des résultats préliminaires concernant une analyse de données "single-cell". Toutes les méthodes proposées sont implémentées dans deux packages R: plsgenomics et CMF
The 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
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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.

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In this thesis the processing mechanisms of short non-coding RNAs (ncRNAs) is investigated by using data generated by the current method of high-throughput sequencing (HTS). The recently adapted short RNA-seq protocol allows the sequencing of RNA fragments of microRNA-like length (∼18-28nt). Thus, after mapping the data back to a reference genome, it is possible to not only measure, but also visualize the expression of all ncRNAs that are processed to fragments of this specific length. Short RNA-seq data was used to show that a highly abundant class of small RNAs, called microRNA-offset-RNAs (moRNAs), which was formerly detected in a basal chordate, is also produced from human microRNA precursors. To simplify the search, the blockbuster tool that automatically recognizes blocks of reads to detect specific expression patterns was developed. By using blockbuster, blocks from moRNAs were detected directly next to the miR or miR* blocks and could thus easily be registered in an automated way. When further investigating the short RNA-seq data it was realized that not only microRNAs give rise to short ∼22nt long RNA pieces, but also almost all other classes of ncRNAs, like tRNAs, snoRNAs, snRNAs, rRNAs, Y-RNAs, or vault RNAs. The formed read patterns that arise after mapping these RNAs back to a reference genome seem to reflect the processing of each class and are thus specific for the RNA transcripts of which they are derived from. The potential of this patterns in classification and identification of non-coding RNAs was explored. Using a random forest classifier which was trained on a set of characteristic features of the individual ncRNA classes, it was possible to distinguish three types of ncRNAs, namely microRNAs, tRNAs, and snoRNAs. To make the classification available to the research community, the free web service ‘DARIO’ that allows to study short read data from small RNA-seq experiments was developed. The classification has shown that read patterns are specific for different classes of ncRNAs. To make use of this feature, the tool deepBlockAlign was developed. deepBlockAlign introduces a two-step approach to align read patterns with the aim of quickly identifying RNAs that share similar processing footprints. In order to find possible exceptions to the well-known microRNA maturation by Dicer and to identify additional substrates for Dicer processing the small RNA sequencing data of a Dicer knockdown experiment in MCF-7 cells was re-evaluated. There were several Dicer-independent microRNAs, among them the important tumor supressor mir-663a. It is known that many aspects of the RNA maturation leave traces in RNA sequencing data in the form of mismatches from the reference genome. It is possible to recover many well- known modified sites in tRNAs, providing evidence that modified nucleotides are a pervasive phenomenon in these data sets.
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Zhang, Xuekui. « Mixture models for analysing high throughput sequencing data ». Thesis, University of British Columbia, 2011. http://hdl.handle.net/2429/35982.

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The goal of my thesis is to develop methods and software for analysing high-throughput sequencing data, emphasizing sonicated ChIP-seq. For this goal, we developed a few variants of mixture models for genome-wide profiling of transcription factor binding sites and nucleosome positions. Our methods have been implemented into Bioconductor packages, which are freely available to other researchers. For profiling transcription factor binding sites, we developed a method, PICS, and implemented it into a Bioconductor package. We used a simulation study to confirm that PICS compares favourably to rival methods, such as MACS, QuEST, CisGenome, and USeq. Using published GABP and FOXA1 data from human cell lines, we then show that PICS predicted binding sites were more consistent with computationally predicted binding motifs than the alternative methods. For motif discovery using transcription binding sites, we combined PICS with two other existing packages to create the first complete set of Bioconductor tools for peak-calling and binding motif analysis of ChIP-Seq and ChIP-chip data. We demonstrate the effectiveness of our pipeline on published human ChIP-Seq datasets for FOXA1, ER, CTCF and STAT1, detecting co-occurring motifs that were consistent with the literature but not detected by other methods. For nucleosome positioning, we modified PICS into a method called PING. PING can handle MNase-Seq and MNase- or sonicated-ChIP-Seq data. It compares favourably to NPS and TemplateFilter in scalability, accuracy and robustness to low read density. To demonstrate that PING predictions from sonicated data can have sufficient spatial resolution to be biologically meaningful, we use H3K4me1 data to detect nucleosome shifts, discriminate functional and non-functional transcription factor binding sites, and confirm that Foxa2 associates with the accessible major groove of nucleosomal DNA. All of the above uses single-end sequencing data. At the end of the thesis, we briefly discuss the issue of processing paired-end data, which we are currently investigating.
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Roberts, Adam. « Ambiguous fragment assignment for high-throughput sequencing experiments ». Thesis, University of California, Berkeley, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=3616509.

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As 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.

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Livres sur le sujet "High throughput sequencing (NGS)"

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Kwon, Young Min, et Steven C. Ricke, dir. High-Throughput Next Generation Sequencing. Totowa, NJ : Humana Press, 2011. http://dx.doi.org/10.1007/978-1-61779-089-8.

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Rodríguez-Ezpeleta, Naiara, Michael Hackenberg et Ana M. Aransay, dir. Bioinformatics for High Throughput Sequencing. New York, NY : Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-0782-9.

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Rodríguez-Ezpeleta, Naiara, Michael Hackenberg et Ana M. Aransay. Bioinformatics for high throughput sequencing. New York, NY : Springer, 2012.

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R, Mitchelson Keith, dir. New high throughput technologies for DNA sequencing and genomics. Amsterdam : Elsevier, 2007.

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Aransay, Ana M., et José Luis Lavín Trueba, dir. Field Guidelines for Genetic Experimental Designs in High-Throughput Sequencing. Cham : Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-31350-4.

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author, Belazzougui Djamal, Cunial Fabio author et Tomescu Alexandru I. author, dir. Genome-scale algorithm design : Biological sequence analysis in the era of high-throughput sequencing. Cambridge, United Kingdom : University Printing House, 2015.

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Cunha, Monica V., et João Inácio. Veterinary infection biology : Molecular diagnostics and high-throughput strategies. New York : Humana Press, 2015.

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Rodríguez-Ezpeleta, Naiara, Ana M. Aransay et Michael Hackenberg. Bioinformatics for High Throughput Sequencing. Springer, 2014.

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Rodríguez-Ezpeleta, Naiara, Ana M. Aransay et Michael Hackenberg. Bioinformatics for High Throughput Sequencing. Springer, 2011.

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Lee, Eric, et T. W. Tan. Beginners Guide to Bioinformatics for High Throughput Sequencing. WORLD SCIENTIFIC, 2018. http://dx.doi.org/10.1142/10720.

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Chapitres de livres sur le sujet "High throughput sequencing (NGS)"

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Tombuloğlu, Güzin, et Hüseyin Tombuloğlu. « High-Throughput Transcriptome Analysis of Plant Stress Responses ». Dans Advances in the Understanding of Biological Sciences Using Next Generation Sequencing (NGS) Approaches, 195–209. Cham : Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-17157-9_12.

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Habyarimana, Ephrem, et Sofia Michailidou. « Genomics Data ». Dans Big Data in Bioeconomy, 69–76. Cham : Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-71069-9_6.

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AbstractIn silico prediction of plant performance is gaining increasing breeders’ attention. Several statistical, mathematical and machine learning methodologies for analysis of phenotypic, omics and environmental data typically use individual or a few data layers. Genomic selection is one of the applications, where heterogeneous data, such as those from omics technologies, are handled, accommodating several genetic models of inheritance. There are many new high throughput Next Generation Sequencing (NGS) platforms on the market producing whole-genome data at a low cost. Hence, large-scale genomic data can be produced and analyzed enabling intercrosses and fast-paced recurrent selection. The offspring properties can be predicted instead of manually evaluated in the field . Breeders have a short time window to make decisions by the time they receive data, which is one of the major challenges in commercial breeding. To implement genomic selection routinely as part of breeding programs, data management systems and analytics capacity have therefore to be in order. The traditional relational database management systems (RDBMS), which are designed to store, manage and analyze large-scale data, offer appealing characteristics, particularly when they are upgraded with capabilities for working with binary large objects. In addition, NoSQL systems were considered effective tools for managing high-dimensional genomic data. MongoDB system, a document-based NoSQL database, was effectively used to develop web-based tools for visualizing and exploring genotypic information. The Hierarchical Data Format (HDF5), a member of the high-performance distributed file systems family, demonstrated superior performance with high-dimensional and highly structured data such as genomic sequencing data.
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Deng, Xiangyu, Lee S. Katz, Patricia I. Fields et Wei Zhang. « High-Throughput Sequencing ». Dans DNA Methods in Food Safety, 65–83. Chichester, UK : John Wiley & Sons, Ltd, 2014. http://dx.doi.org/10.1002/9781118278666.ch4.

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Woods, Douglas W., Matthew R. Capriotti, Madison Pilato, Carolyn A. Doyle, Christopher J. McDougle, Beth Springate, Deborah Fein et al. « High-Throughput Sequencing ». Dans Encyclopedia of Autism Spectrum Disorders, 1508. New York, NY : Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-1698-3_100671.

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Elumalai, Elakkiya, et Krishna Kant Gupta. « High-Throughput Sequencing Technologies ». Dans Bioinformatics in Rice Research, 283–304. Singapore : Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-3993-7_13.

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Goya, Rodrigo, Irmtraud M. Meyer et Marco A. Marra. « Applications of High-Throughput Sequencing ». Dans Bioinformatics for High Throughput Sequencing, 27–53. New York, NY : Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4614-0782-9_3.

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Myllykangas, Samuel, Jason Buenrostro et Hanlee P. Ji. « Overview of Sequencing Technology Platforms ». Dans Bioinformatics for High Throughput Sequencing, 11–25. New York, NY : Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4614-0782-9_2.

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Kaya, Kamer, Ayat Hatem, Hatice Gülçin Özer, Kun Huang et Ümit V. Çatalyürek. « High-Performance Computing In High-Throughput Sequencing ». Dans Biological Knowledge Discovery Handbook, 981–1002. Hoboken, New Jersey : John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118617151.ch43.

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Rodríguez-Ezpeleta, Naiara, et Ana M. Aransay. « Introduction ». Dans Bioinformatics for High Throughput Sequencing, 1–9. New York, NY : Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4614-0782-9_1.

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Young, Matthew D., Davis J. McCarthy, Matthew J. Wakefield, Gordon K. Smyth, Alicia Oshlack et Mark D. Robinson. « Differential Expression for RNA Sequencing (RNA-Seq) Data : Mapping, Summarization, Statistical Analysis, and Experimental Design ». Dans Bioinformatics for High Throughput Sequencing, 169–90. New York, NY : Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4614-0782-9_10.

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Actes de conférences sur le sujet "High throughput sequencing (NGS)"

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Chanyshev, M. D., N. V. Vlasenko, I. A. Kotov, K. F. Khafizov et V. G. Akimkin. « HIGH THROUGHPUT DNA SEQUENCING OF HEPATITIS B VIRUS ». Dans X Международная конференция молодых ученых : биоинформатиков, биотехнологов, биофизиков, вирусологов и молекулярных биологов — 2023. Novosibirsk State University, 2023. http://dx.doi.org/10.25205/978-5-4437-1526-1-266.

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It was shown that Hepatitis B Virus (HBV) genotype and individual mutations influence the course of the disease. There is a need for a simple and reliable method for sequencing the entire genome of hepatitis B virus. We have developed an NGS amplification panel for hepatitis B virus genome sequencing. The panel was validated using Sanger sequencing. More than 300 HBV samples were sequenced and genotypes and mutations described in the literature were identified.
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Chaabane, Mohamed, Eric C. Rouchka et Juw Won Park. « Circular RNA Detection from High-throughput Sequencing ». Dans RACS '17 : International Conference on Research in Adaptive and Convergent Systems. New York, NY, USA : ACM, 2017. http://dx.doi.org/10.1145/3129676.3129734.

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Mangul, Serghei, et Alex Zelikovsky. « Poster : Haplotype discovery from high-throughput sequencing data ». Dans 2011 IEEE 1st International Conference on Computational Advances in Bio and Medical Sciences (ICCABS). IEEE, 2011. http://dx.doi.org/10.1109/iccabs.2011.5729908.

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Holt, James, Shunping Huang, Leonard McMillan et Wei Wang. « Read Annotation Pipeline for High-Throughput Sequencing Data ». Dans BCB'13 : ACM-BCB2013. New York, NY, USA : ACM, 2013. http://dx.doi.org/10.1145/2506583.2506645.

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Kuroshu, Reginaldo M. « Non-overlapping clone pooling for high-throughput sequencing ». Dans the ACM Conference. New York, New York, USA : ACM Press, 2012. http://dx.doi.org/10.1145/2382936.2382947.

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White, Brian S., Abdullah Ozer, John T. Lis et David Shalloway. « Abstract LB-97 : Optimizing SELEX with high-throughput sequencing ». Dans Proceedings : AACR 103rd Annual Meeting 2012‐‐ Mar 31‐Apr 4, 2012 ; Chicago, IL. American Association for Cancer Research, 2012. http://dx.doi.org/10.1158/1538-7445.am2012-lb-97.

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Hoobin, Christopher, Trey Kind, Christina Boucher et Simon J. Puglisi. « Fast and efficient compression of high-throughput sequencing reads ». Dans BCB '15 : ACM International Conference on Bioinformatics, Computational Biology and Biomedicine. New York, NY, USA : ACM, 2015. http://dx.doi.org/10.1145/2808719.2808753.

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Rakova, Irina, Maria Kapetanaki, Kusum Pandit, Lara Chensny, Kevin Gibson, Elodie Ghedin et Naftali Kaminski. « High-Throughput Sequencing Of MicroRNA In Idiopathic Pulmonary Fibrosis ». Dans American Thoracic Society 2011 International Conference, May 13-18, 2011 • Denver Colorado. American Thoracic Society, 2011. http://dx.doi.org/10.1164/ajrccm-conference.2011.183.1_meetingabstracts.a5538.

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Tsui, Stephen Kwok-Wing. « High-throughput DNA sequencing and bioinformatics : Bottlenecks and opportunities ». Dans 2009 IEEE International Conference on Granular Computing (GRC). IEEE, 2009. http://dx.doi.org/10.1109/grc.2009.5255117.

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Bozdag, Doruk, Catalin C. Barbacioru et Umit V. Catalyurek. « Parallel short sequence mapping for high throughput genome sequencing ». Dans Distributed Processing (IPDPS). IEEE, 2009. http://dx.doi.org/10.1109/ipdps.2009.5161075.

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Rapports d'organisations sur le sujet "High throughput sequencing (NGS)"

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Lu, X. An integrated multiple capillary array electrophoresis system for high-throughput DNA sequencing. Office of Scientific and Technical Information (OSTI), mars 1998. http://dx.doi.org/10.2172/348901.

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Cooney, Kathleen A. High Throughput Sequencing of Germline and Tumor from Men With Early-Onset Metastatic Prostate Cancer. Fort Belvoir, VA : Defense Technical Information Center, octobre 2014. http://dx.doi.org/10.21236/ada611828.

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Cooney, Kathleen A. High-Throughput Sequencing of Germline and Tumor From Men with Early-Onset Metastatic Prostate Cancer. Fort Belvoir, VA : Defense Technical Information Center, octobre 2015. http://dx.doi.org/10.21236/ada624260.

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Novikova, Irina, James Evans, Lye Meng Markillie et Hugh Mitchell. Validation and functional characterization of transcription factors in wheat using cell-free protein expression and high-throughput sequencing technologies. Office of Scientific and Technical Information (OSTI), novembre 2022. http://dx.doi.org/10.2172/1976176.

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Zhang, Yonghua. High Throughput Sample Preparation and Analysis for DNA Sequencing, PCR and Combinatorial Screening of Catalysis Based on Capillary Array Technique. Office of Scientific and Technical Information (OSTI), janvier 2000. http://dx.doi.org/10.2172/804158.

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Xue, Gang. High-Throughput Analysis With 96-Capillary Array Electrophoresis and Integrated Sample Preparation for DNA Sequencing Based on Laser Induced Fluorescence Detection. Office of Scientific and Technical Information (OSTI), janvier 2001. http://dx.doi.org/10.2172/803101.

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Gao, David. A new sieving matrix for DNA sequencing, genotyping and mutation detection and high-throughput genotyping with a 96-capillary array system. Office of Scientific and Technical Information (OSTI), novembre 1999. http://dx.doi.org/10.2172/754779.

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Gur, Amit, Edward Buckler, Joseph Burger, Yaakov Tadmor et Iftach Klapp. Characterization of genetic variation and yield heterosis in Cucumis melo. United States Department of Agriculture, janvier 2016. http://dx.doi.org/10.32747/2016.7600047.bard.

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Project objectives: 1) Characterization of variation for yield heterosis in melon using Half-Diallele (HDA) design. 2) Development and implementation of image-based yield phenotyping in melon. 3) Characterization of genetic, epigenetic and transcriptional variation across 25 founder lines and selected hybrids. The epigentic part of this objective was modified during the course of the project: instead of characterization of chromatin structure in a single melon line through genome-wide mapping of nucleosomes using MNase-seq approach, we took advantage of rapid advancements in single-molecule sequencing and shifted the focus to Nanoporelong-read sequencing of all 25 founder lines. This analysis provides invaluable information on genome-wide structural variation across our diversity 4) Integrated analyses and development of prediction models Agricultural heterosis relates to hybrids that outperform their inbred parents for yield. First generation (F1) hybrids are produced in many crop species and it is estimated that heterosis increases yield by 15-30% globally. Melon (Cucumismelo) is an economically important species of The Cucurbitaceae family and is among the most important fleshy fruits for fresh consumption Worldwide. The major goal of this project was to explore the patterns and magnitude of yield heterosis in melon and link it to whole genome sequence variation. A core subset of 25 diverse lines was selected from the Newe-Yaar melon diversity panel for whole-genome re-sequencing (WGS) and test-crosses, to produce structured half-diallele design of 300 F1 hybrids (MelHDA25). Yield variation was measured in replicated yield trials at the whole-plant and at the rootstock levels (through a common-scion grafted experiments), across the F1s and parental lines. As part of this project we also developed an algorithmic pipeline for detection and yield estimation of melons from aerial-images, towards future implementation of such high throughput, cost-effective method for remote yield evaluation in open-field melons. We found extensive, highly heritable root-derived yield variation across the diallele population that was characterized by prominent best-parent heterosis (BPH), where hybrids rootstocks outperformed their parents by 38% and 56 % under optimal irrigation and drought- stress, respectively. Through integration of the genotypic data (~4,000,000 SNPs) and yield analyses we show that root-derived hybrids yield is independent of parental genetic distance. However, we mapped novel root-derived yield QTLs through genome-wide association (GWA) analysis and a multi-QTLs model explained more than 45% of the hybrids yield variation, providing a potential route for marker-assisted hybrid rootstock breeding. Four selected hybrid rootstocks are further studied under multiple scion varieties and their validated positive effect on yield performance is now leading to ongoing evaluation of their commercial potential. On the genomic level, this project resulted in 3 layers of data: 1) whole-genome short-read Illumina sequencing (30X) of the 25 founder lines provided us with 25 genome alignments and high-density melon HapMap that is already shown to be an effective resource for QTL annotation and candidate gene analysis in melon. 2) fast advancements in long-read single-molecule sequencing allowed us to shift focus towards this technology and generate ~50X Nanoporesequencing of the 25 founders which in combination with the short-read data now enable de novo assembly of the 25 genomes that will soon lead to construction of the first melon pan-genome. 3) Transcriptomic (3' RNA-Seq) analysis of several selected hybrids and their parents provide preliminary information on differentially expressed genes that can be further used to explain the root-derived yield variation. Taken together, this project expanded our view on yield heterosis in melon with novel specific insights on root-derived yield heterosis. To our knowledge, thus far this is the largest systematic genetic analysis of rootstock effects on yield heterosis in cucurbits or any other crop plant, and our results are now translated into potential breeding applications. The genomic resources that were developed as part of this project are putting melon in the forefront of genomic research and will continue to be useful tool for the cucurbits community in years to come.
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Bacharach, Eran, W. Ian Lipkin et Avigdor Eldar. Identification of the etiological agent of tilapia disease in the Lake of Galillee. United States Department of Agriculture, janvier 2013. http://dx.doi.org/10.32747/2013.7597932.bard.

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Background to the topic. Tilapines serve as the second most important group of farmed fish worldwide. Massive mortality of wild and cultured tilapia has been observed recently in Israel but the pathogen of this disease has not been identified. We proposed to identify the agent responsible for disease.  Major conclusions, solutions, achievements. We characterized the lesions in diseased fish and found that the brain was one of the affected organs. We found conditions to isolate from brains of diseased fish the etiological agent of the tilapia disease and to propagate it in cell culture. This led to the identification of the pathogen as a novel RNA virus, which we named Tilapia Lake Virus (TiLV). Electron microscopy of TiLV revealed virion-like particles and ether/chloroform-sensitivity assays demonstrated that TiLV is enveloped. Low passage TiLV, injected intra-peritoneally to tilapia, induced a disease with over 80% mortality. Cohabitation of healthy with diseased fish demonstrated that the disease is contagious, and that mortalities occur within few days. Fish surviving initial mortality were immune to further TiLV infections, suggesting the mounting of protective immune response. Screening cDNA libraries and high throughput sequencing determined the sequence of TiLV genome. This demonstrated that TiLV is indeed a novel virus and allowed the design of a PCRbased diagnostic test.  Implications, both scientific and agricultural. The characterization of a novel, emerging RNA virus that imposes major threat to the tilapia industry, enables the specific identification of the virus in tilapines. This allows prompt screening and surveillance of TiLV, epidemiological studies, and disease containment. This also potentially opens the way for the development of vaccines against TiLV.
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Joel, Daniel M., Steven J. Knapp et Yaakov Tadmor. Genomic Approaches for Understanding Virulence and Resistance in the Sunflower-Orobanche Host-Parasite Interaction. United States Department of Agriculture, août 2011. http://dx.doi.org/10.32747/2011.7592655.bard.

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Oroginal Objectives: (i) identify DNA markers linked to the avirulence (Avr) locus and locate the Avr locus through genetic mapping with an inter-race Orobanche cumana population; (ii) develop high-throughput fingerprint DNA markers for genotypingO. cumana races; (iii) identify nucleotide binding domain leucine rich repeat (NB-LRR) genes encoding R proteins conferring resistance to O. cumana in sunflower; (iv) increase the resolution of the chromosomal segment harboring Or₅ and related R genes through genetic and physical mapping in previously and newly developed mapping populations of sunflower; and (v) develop high-throughput DNA markers for rapidly and efficiently identifying and transferring sunflower R genes through marker-assisted selection. Revisions made during the course of project: Following changes in O. cumana race distribution in Israel, the newly arrived virulent race H was chosen for further analysis. HA412-HO, which was primarily chosen as a susceptible sunflower cultivar, was more resistant to the new parasite populations than var. Shemesh, thus we shifted sunflower research into analyzing the resistance of HA412-HO. We exceeded the deliverables for Objectives #3-5 by securing funding for complete physical and high-density genetic mapping of the sunflower genome, in addition to producing a complete draft sequence of the sunflower genome. We discovered limited diversity between the parents of the O. cumana population developed for the mapping study. Hence, the developed DNA marker resources were insufficient to support genetic map construction. This objective was beyond the scale and scope of the funding. This objective is challenging enough to be the entire focus of follow up studies. Background to the topic: O. cumana, an obligate parasitic weed, is one of the most economically important and damaging diseases of sunflower, causes significant yield losses in susceptible genotypes, and threatens production in Israel and many other countries. Breeding for resistance has been crucial for protecting sunflower from O. cumana, and problematic because new races of the pathogen continually emerge, necessitating discovery and deployment of new R genes. The process is challenging because of the uncertainty in identifying races in a genetically diverse parasite. Major conclusions, solutions, achievements: We developed a small collection of SSR markers for genetic mapping in O. cumana and completed a diversity study to lay the ground for objective #1. Because DNA sequencing and SNPgenotyping technology dramatically advanced during the course of the study, we recommend shifting future work to SNP discovery and mapping using array-based approaches, instead of SSR markers. We completed a pilot study using a 96-SNP array, but it was not large enough to support genetic mapping in O.cumana. The development of further SNPs was beyond the scope of the grant. However, the collection of SSR markers was ideal for genetic diversity analysis, which indicated that O. cumanapopulations in Israel considerably differ frompopulations in other Mediterranean countries. We supplied physical and genetic mapping resources for identifying R-genes in sunflower responsible for resistance to O. cumana. Several thousand mapped SNP markers and a complete draft of the sunflower genome sequence are powerful tools for identifying additional candidate genes and understanding the genomic architecture of O. cumana-resistanceanddisease-resistance genes. Implications: The OrobancheSSR markers have utility in sunflower breeding and genetics programs, as well as a tool for understanding the heterogeneity of races in the field and for geographically mapping of pathotypes.The segregating populations of both Orobanche and sunflower hybrids are now available for QTL analyses.
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