Relevant bibliographies by topics / Very high throughput sequencing

Academic literature on the topic 'Very high throughput sequencing'

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Published: 7 July 2024

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Journal articles on the topic "Very high throughput sequencing":

1

Bray, Paul F., Paolo M. Fortina, Srikanth Nagalla, Kathleen Delgrosso, Adam Ertel, Isidore Rigoutsos, and Steven E. McKenzie. "High-Throughput Sequencing of the Human Platelet Transcriptome." Blood 116, no. 21 (November 19, 2010): 481. http://dx.doi.org/10.1182/blood.v116.21.481.481.

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Abstract Abstract 481 Most successful DNA-based genome wide association studies identify genomic regions, not genes themselves, and the findings are often devoid of context or mechanism. To identify the genetic basis of disease and disease traits, it is imperative to characterize the quantity and forms of the genes that are expressed in the tissue of interest. It is not feasible to use primary megakaryocytes to profile mRNA from large numbers of subjects, but platelet RNA is easy to obtain. Others and we have previously surveyed genome-wide platelet RNA expression using microarrays, an approach that has had a major impact on systems biology. However, microarrays have a number of limitations, including the use of probes only to known transcripts, a limited dynamic range for quantifying very low and high levels of transcripts, high background levels from cross-hybridization, and complicated normalization schemes to compare expression levels across experiments. Novel high-throughput sequencing approaches that overcome the limitations of microarrays have recently become available. RNA sequencing (RNAseq) has a remarkable ability to quantify mRNAs and provide information about transcript sequence variations, including single nucleotide changes and alternately spliced exons. The goal of these studies was to apply RNAseq to capture platelet transcriptome complexity. Total RNA was prepared using leukocyte-depleted platelets (LDP; less than 1 WBC per 5 million platelets) from 4 donors; 2 were studied twice each. Analysis of this material showed that compared to nucleated cells (HeLa, Meg-01), platelets had 50%-90% less ribosomal RNA, and high levels of messenger and small RNAs (Agilent 2100). The major reduction in platelet rRNA was confirmed by RNA gel analysis. The platelet whole transcriptomes were analyzed via the Applied Biosystems (AB) SOLiD 3Plus next generation sequencing protocols and platform. A typical sequence run generated ∼250 million reads of 50 bp each. We observed more than 30,000 independent platelet mRNA-coding transcripts from about 10,000 genes, demonstrating substantial numbers of variant isoforms. The increased sensitivity of RNAseq for low copy number is clear from these results, because prior platelet transcriptome studies using microarrays have identified only 1500–6000 expressed genes. As an example, the platelet-specific transcript, ITGA2B, showed very high copy number in platelets, but no expression in HeLa cells and modest expression in the megakaryocyte cell line, Meg-01. As is expected for RNA-Seq data, the density of mapped reads varies by exon and local sequence. We also provide examples of newly discovered SNPs that encode non-conservative amino acid changes (AKT2 1209A/T; PIK3CB 837C/G) and alter consensus exon/intron splice junction sites (P2YR12 nt 65 G/A). We have also identified a major difference in the ratio of two splice variants of the FcRg chain, 4:1 in one human platelet donor and 49:1 in another. In summary, we have demonstrated that RNAseq can accurately and sensitively determine the quantity and quality of variations in individual platelet transcriptomes. It appears that the the platelet transcriptome is approximately 10 times more complex than previously thought. The major relative reduction in platelet rRNA may be an advantage for characterizing functional platelet transcripts. RNAseq should permit better understanding of the molecular mechanisms regulating platelet physiology and identify novel genetic variants that contribute to disorders of thrombosis and hemostasis. Disclosures: No relevant conflicts of interest to declare.
2

Hoffman, Joseph I., Fraser Simpson, Patrice David, Jolianne M. Rijks, Thijs Kuiken, Michael A. S. Thorne, Robert C. Lacy, and Kanchon K. Dasmahapatra. "High-throughput sequencing reveals inbreeding depression in a natural population." Proceedings of the National Academy of Sciences 111, no. 10 (February 28, 2014): 3775–80. http://dx.doi.org/10.1073/pnas.1318945111.

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Proxy measures of genome-wide heterozygosity based on approximately 10 microsatellites have been used to uncover heterozygosity fitness correlations (HFCs) for a wealth of important fitness traits in natural populations. However, effect sizes are typically very small and the underlying mechanisms remain contentious, as a handful of markers usually provides little power to detect inbreeding. We therefore used restriction site associated DNA (RAD) sequencing to accurately estimate genome-wide heterozygosity, an approach transferrable to any organism. As a proof of concept, we first RAD sequenced oldfield mice (Peromyscus polionotus) from a known pedigree, finding strong concordance between the inbreeding coefficient and heterozygosity measured at 13,198 single-nucleotide polymorphisms (SNPs). When applied to a natural population of harbor seals (Phoca vitulina), a weak HFC for parasite infection based on 27 microsatellites strengthened considerably with 14,585 SNPs, the deviance explained by heterozygosity increasing almost fivefold to a remarkable 49%. These findings arguably provide the strongest evidence to date of an HFC being due to inbreeding depression in a natural population lacking a pedigree. They also suggest that under some circumstances heterozygosity may explain far more variation in fitness than previously envisaged.
3

Chen, Yanwu, Bin Wu, Cheng Zhang, Zhiqi Fan, Ying Chen, Bingmu Xin, and Qiong Xie. "Current Progression: Application of High-Throughput Sequencing Technique in Space Microbiology." BioMed Research International 2020 (June 22, 2020): 1–13. http://dx.doi.org/10.1155/2020/4094191.

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During a spaceflight, astronauts need to live in a spacecraft on orbit for a long time, and the relationship between humans and microorganisms in the closed environment of space is not the same as on the ground. The dynamic study of microorganisms in confined space shows that with the extension of the isolation time, harmful bacteria gradually accumulate. Monitoring and controlling microbial pollution in a confined environment system are very important for crew health and the sustainable operation of a space life support system. Culture-based assays have been used traditionally to assess the microbial loads in a spacecraft, and uncultured-based techniques are already under way according to the NASA global exploration roadmap. High-throughput sequencing technology has been used generally to study the communities of the environment and human on the ground and shows its broad prospects applied onboard. We here review the recent application of high-throughput sequencing on space microbiology and analyze its feasibility and potential as an on-orbit detection technology.
4

Drees, Alissa, and Markus Fischer. "High-Throughput Selection and Characterisation of Aptamers on Optical Next-Generation Sequencers." International Journal of Molecular Sciences 22, no. 17 (August 25, 2021): 9202. http://dx.doi.org/10.3390/ijms22179202.

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Aptamers feature a number of advantages, compared to antibodies. However, their application has been limited so far, mainly because of the complex selection process. ‘High-throughput sequencing fluorescent ligand interaction profiling’ (HiTS–FLIP) significantly increases the selection efficiency and is consequently a very powerful and versatile technology for the selection of high-performance aptamers. It is the first experiment to allow the direct and quantitative measurement of the affinity and specificity of millions of aptamers simultaneously by harnessing the potential of optical next-generation sequencing platforms to perform fluorescence-based binding assays on the clusters displayed on the flow cells and determining their sequence and position in regular high-throughput sequencing. Many variants of the experiment have been developed that allow automation and in situ conversion of DNA clusters into base-modified DNA, RNA, peptides, and even proteins. In addition, the information from mutational assays, performed with HiTS–FLIP, provides deep insights into the relationship between the sequence, structure, and function of aptamers. This enables a detailed understanding of the sequence-specific rules that determine affinity, and thus, supports the evolution of aptamers. Current variants of the HiTS–FLIP experiment and its application in the field of aptamer selection, characterisation, and optimisation are presented in this review.
5

Zheng, Huiquan, Dehuo Hu, Ruping Wei, Shu Yan, and Runhui Wang. "Chinese Fir Breeding in the High-Throughput Sequencing Era: Insights from SNPs." Forests 10, no. 8 (August 12, 2019): 681. http://dx.doi.org/10.3390/f10080681.

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Knowledge on population diversity and structure is of fundamental importance for conifer breeding programs. In this study, we concentrated on the development and application of high-density single nucleotide polymorphism (SNP) markers through a high-throughput sequencing technique termed as specific-locus amplified fragment sequencing (SLAF-seq) for the economically important conifer tree species, Chinese fir (Cunninghamia lanceolata). Based on the SLAF-seq, we successfully established a high-density SNP panel consisting of 108,753 genomic SNPs from Chinese fir. This SNP panel facilitated us in gaining insight into the genetic base of the Chinese fir advance breeding population with 221 genotypes for its genetic variation, relationship and diversity, and population structure status. Overall, the present population appears to have considerable genetic variability. Most (94.15%) of the variability was attributed to the genetic differentiation of genotypes, very limited (5.85%) variation occurred on the population (sub-origin set) level. Correspondingly, low FST (0.0285–0.0990) values were seen for the sub-origin sets. When viewing the genetic structure of the population regardless of its sub-origin set feature, the present SNP data opened a new population picture where the advanced Chinese fir breeding population could be divided into four genetic sets, as evidenced by phylogenetic tree and population structure analysis results, albeit some difference in membership of the corresponding set (cluster vs. group). It also suggested that all the genetic sets were admixed clades revealing a complex relationship of the genotypes of this population. With a step wise pruning procedure, we captured a core collection (core 0.650) harboring 143 genotypes that maintains all the allele, diversity, and specific genetic structure of the whole population. This generalist core is valuable for the Chinese fir advanced breeding program and further genetic/genomic studies.
6

Bao, Ergude, Fei Xie, Changjin Song, and Dandan Song. "FLAS: fast and high-throughput algorithm for PacBio long-read self-correction." Bioinformatics 35, no. 20 (March 21, 2019): 3953–60. http://dx.doi.org/10.1093/bioinformatics/btz206.

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Abstract Motivation The third generation PacBio long reads have greatly facilitated sequencing projects with very large read lengths, but they contain about 15% sequencing errors and need error correction. For the projects with long reads only, it is challenging to make correction with fast speed, and also challenging to correct a sufficient amount of read bases, i.e. to achieve high-throughput self-correction. MECAT is currently among the fastest self-correction algorithms, but its throughput is relatively small (Xiao et al., 2017). Results Here, we introduce FLAS, a wrapper algorithm of MECAT, to achieve high-throughput long-read self-correction while keeping MECAT’s fast speed. FLAS finds additional alignments from MECAT prealigned long reads to improve the correction throughput, and removes misalignments for accuracy. In addition, FLAS also uses the corrected long-read regions to correct the uncorrected ones to further improve the throughput. In our performance tests on Escherichia coli, Saccharomyces cerevisiae, Arabidopsis thaliana and human long reads, FLAS can achieve 22.0–50.6% larger throughput than MECAT. FLAS is 2–13× faster compared to the self-correction algorithms other than MECAT, and its throughput is also 9.8–281.8% larger. The FLAS corrected long reads can be assembled into contigs of 13.1–29.8% larger N50 sizes than MECAT. Availability and implementation The FLAS software can be downloaded for free from this site: https://github.com/baoe/flas. Supplementary information Supplementary data are available at Bioinformatics online.
7

Bokulich, Nicholas A., and David A. Mills. "Improved Selection of Internal Transcribed Spacer-Specific Primers Enables Quantitative, Ultra-High-Throughput Profiling of Fungal Communities." Applied and Environmental Microbiology 79, no. 8 (February 1, 2013): 2519–26. http://dx.doi.org/10.1128/aem.03870-12.

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ABSTRACTUltra-high-throughput sequencing (HTS) of fungal communities has been restricted by short read lengths and primer amplification bias, slowing the adoption of newer sequencing technologies to fungal community profiling. To address these issues, we evaluated the performance of several common internal transcribed spacer (ITS) primers and designed a novel primer set and work flow for simultaneous quantification and species-level interrogation of fungal consortia. Primer comparison and validation were predictedin silicoand by sequencing a “mock community” of mixed yeast species to explore the challenges of amplicon length and amplification bias for reconstructing defined yeast community structures. The amplicon size and distribution of this primer set are smaller than for all preexisting ITS primer sets, maximizing sequencing coverage of hypervariable ITS domains by very-short-amplicon, high-throughput sequencing platforms. This feature also enables the optional integration of quantitative PCR (qPCR) directly into the HTS preparatory work flow by substituting qPCR with these primers for standard PCR, yielding quantification of individual community members. The complete work flow described here, utilizing any of the qualified primer sets evaluated, can rapidly profile mixed fungal communities and capably reconstructed well-characterized beer and wine fermentation fungal communities.
8

Christoff, Ana P., Aline FR Sereia, Camila Hernandes, and Luiz FV de Oliveira. "Uncovering the hidden microbiota in hospital and built environments: New approaches and solutions." Experimental Biology and Medicine 244, no. 6 (January 7, 2019): 534–42. http://dx.doi.org/10.1177/1535370218821857.

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Microorganisms are widely distributed all over the Earth, inhabiting very diverse natural ecosystems, from the human body to inanimate indoor environments. Until recently, the methods most commonly used to study microbes have been culture-dependent approaches relying on the phenotypic evaluation of isolates that can grow in laboratory conditions. Given the advances in molecular biology and high-throughput DNA sequencing methodologies, scientists could expand their microbiome knowledge to microorganisms that do not grow well in the laboratory or have been considered too difficult and laborious to be cultivated. Culture-independent methods such as direct DNA sequencing can be performed for many samples at once, revealing the entire microbial profile of the samples and making possible the rapid characterization of the whole environmental microbiome. Investigating the microbiome profile of indoor environments such as hospitals, houses, offices and other buildings is of major concern because it could include a number of opportunistic, pathogenic or nosocomial microbes. Additionally, these environments could serve as reservoirs of virulence or antimicrobial resistance, which could be spread by humans or other vectors. High-throughput DNA sequencing has enabled large-scale microbiome screening for multiple indoor areas in a single analysis. Using this approach, we can easily track microorganisms in the environment and monitor microbiome composition related to hygiene processes or environment quality. Gaining such information and resolution regarding indoor microbiome analysis can lend very important assistance for epidemiological surveillance. Impact statement Research concerning the microbiome of indoor environments like hospitals, houses or buildings could have several implications for human health. Today, there is an ongoing shift in the paradigm of microbial analysis, from single isolated bacterial samples to entire microbiome profiles using high-throughput DNA sequencing methods. The use of sequencing methods in several studies has revealed an unprecedented microbial diversity in indoor environments, leading to a larger comprehension of the entire microbiome context. Here, we present a review of these microbiome studies using high-throughput DNA sequencing, including some new approaches and ideas that can be broadly applied in microbial tracking and epidemiological surveillance of indoor environments.
9

Schorderet, Daniel F., Alexandra Iouranova, Tatiana Favez, Leila Tiab, and Pascal Escher. "IROme, a New High-Throughput Molecular Tool for the Diagnosis of Inherited Retinal Dystrophies." BioMed Research International 2013 (2013): 1–9. http://dx.doi.org/10.1155/2013/198089.

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The molecular diagnosis of retinal dystrophies is difficult because of the very important number of genes implicated and is rarely helped by genotype-phenotype correlations. This prompted us to develop IROme, a custom designed in solution-based targeted exon capture assay (SeqCap EZ Choice library, Roche NimbleGen) for 60 retinitis pigmentosa-linked genes and three candidate genes (942 exons). Pyrosequencing was performed on a Roche 454 GS Junior benchtop high-throughput sequencing platform. In total, 23 patients affected by retinitis pigmentosa were analyzed. Per patient, 39.6 Mb were generated, and 1111 sequence variants were detected on average, at a median coverage of 17-fold. After data filtering and sequence variant prioritization, disease-causing mutations were identified inABCA4,CNGB1,GUCY2D,PROM1,PRPF8,PRPF31,PRPH2,RHO,RP2, andTULP1for twelve patients (55%), ten mutations having never been reported previously. Potential mutations were identified in 5 additional patients, and in only 6 patients no molecular diagnosis could be established (26%). In conclusion, targeted exon capture and next-generation sequencing are a valuable and efficient approach to identify disease-causing sequence variants in retinal dystrophies.
10

Zhao, Lili, Hongbo Li, Zhenbin Liu, Liangbin Hu, Dan Xu, Xiaolin Zhu, and Haizhen Mo. "Quality Changes and Fungal Microbiota Dynamics in Stored Jujube Fruits: Insights from High-Throughput Sequencing for Food Preservation." Foods 13, no. 10 (May 10, 2024): 1473. http://dx.doi.org/10.3390/foods13101473.

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Postharvest rot is an urgent problem affecting the storage of winter jujube. Therefore, the development of new technologies for efficient and safe preservation is very important. This study aimed to elucidate the fungal microbiota found on the epidermis of jujube during the storage period using high-throughput sequencing, as well as to monitor the changes in quality indexes throughout this period. Through internal transcribed spacer (ITS) sequencing, we identified two phyla (Basidiomycota and Ascomycota) and six genera (Cryptococcus, Bulleromyces, Sporidiobolus, Alternaria, Pseudozyma, and Sporobolomyces), which potentially contribute to the spoilage and deterioration of jujube, referred to as “core fungal taxa”. A high correlation was further found between preservation indices (including decay rate, firmness, and total soluble solids) and the growth of multiple core fungi over time. These findings will provide insights and a theoretical basis for further research on preservation techniques related to biological control during date fruit storage.
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Journal articles Dissertations / Theses Books

Dissertations / Theses on the topic "Very high throughput sequencing":

1

Koreki, Axelle. "Recherche de déterminants génétiques de la résistance aux herbicides auxiniques chez le Coquelicot (Papaver rhoeas L.) dans un but de diagnostic." Electronic Thesis or Diss., Bourgogne Franche-Comté, 2024. http://www.theses.fr/2024UBFCK005.

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Le coquelicot (Papaver rhoeas) est une adventice cosmopolite très répandue dans les cultures de céréales d’hiver en Europe qui présente un haut potentiel d’invasion et de propagation dans les cultures. Il est principalement contrôlé par les herbicides inhibiteurs de l’ALS et les herbicides auxiniques. L’utilisation intensive de ces deux modes d’action à conduit à l’évolution de la résistance dans de nombreuses populations de coquelicot à travers l’Europe. La résistance aux herbicides implique deux catégories de mécanismes : la résistance liée à la cible (RLC) et la résistance non liée à la cible (RNLC). Chez le coquelicot, seuls des mécanismes de RNLC ont été identifiés, mais les gènes spécifiques restent inconnus. Ce travail de thèse a donc plusieurs objectifs : (i) identifier et potentiellement valider les déterminants génétiques de la résistance aux herbicides auxiniques chez le coquelicot et (ii) évaluer la présence de résistance aux herbicides auxiniques dans des populations françaises de Coquelicot. Dans une première partie, nous avons caractérisé phénotypiquement le matériel végétal disponible via des tests biologiques de sensibilités aux herbicides (Chapitre 1) pour évaluer la situation de la résistance des coquelicots aux herbicides auxiniques en France. Nous avons montré que la résistance au 2,4-D en France était répandue, voire très bien installée dans certaines zones. Nous avons également identifié deux parcelles en Italie et en Grèce où des plantes résistantes à l’halauxifène-méthyl ont été détecté, suggérant un début d’évolution de la résistance à ce nouvel herbicide de synthèse. Les populations avec un ratio équilibré d’individus résistants et sensibles ont été utilisées pour la production de matériel végétal pour les approches de biologie moléculaire de la deuxième partie.Dans une deuxième partie, nous avons étudié la résistance constitutive au 2,4-D et à l’halauxifène-méthyl parmi 14 populations via le séquençage de l’ARN (RNAseq) (Chapitre 2). Nous avons montré que les profils d’expression des plantes sensibles et résistantes étaient propres à chaque population. Parmi les gènes différentiellement exprimés chez les plantes résistantes, certaines familles de gènes potentiellement impliqués dans la métabolisation des herbicides (CYP450, GST, transporteurs ABCs etc.) ou des cascades de régulation (facteurs de transcription, protéines kinases) ont été identifiées. Sur la base de ces résultats, le niveau d’expression de ces gènes à été validé via une approche de RT-qPCR à partir d’un échantillon plus large de plantes. L’ensemble des résultats indiquent qu’il existe potentiellement une grande variété de mécanismes de résistance inter- et intra-population. Le deuxième RNAseq (Chapitre 3) visait à étudier la réponse transcriptomique des plantes résistantes et sensibles entre 4h et 48h après l’application du 2,4-D dans deux populations. Nous avons identifié une grande diversité de gènes et de familles de gènes spécifiquement induits chez les plantes résistantes des deux populations, mais leur rôle dans la résistance n’a pas pu être vérifié. Comme dans la résistance constitutive, il peut potentiellement s’agir d’enzymes de détoxication, de transporteurs, voire de potentiels gènes cibles de l’auxine ou de gènes associés à la réponse générale au stress. De plus, le 2,4-D induit une réponse rapide qui est détectable dans les 4h suivant le traitement quels que soient le phénotype et la population. Enfin, la comparaison des gènes différentiellement exprimés de façon constitutive entre les deux approches de RNAseq démontre que l’absence de gènes communs est potentiellement due à une diversité élevée de mécanismes de résistance intra- et -inter populations, ou au fait que les mécanismes qui contribuent le plus à la résistance sont dû à des mutations de structure
Corn poppy (Papaver rhoeas) is a very widespread cosmopolitan weed in winter crops cereal in Europe which has a high potential for invasion and spread in crops. It is mainly controlled by ALS inhibitor herbicides and auxin herbicides. The intensive use of these two modes of action has led to the evolution of resistance in many poppy populations across Europe. Herbicide resistance involves two categories of mechanisms: target-site-based resistance (TSR) and non-target-site-based resistance (NTSR). In poppy, only NTSR mechanisms have been identified, but the specific genes remain unknown. This work therefore has several goals: (i) identify and potentially validate the genetic determinants of resistance to auxin herbicides in corn poppy and (ii) evaluate resistance status to auxin herbicides in French poppy populations.In a first part, we phenotypically characterized the plant material available using herbicides sensitivity bioassays (Chapter 1) to assess the resistance status of poppies to auxin herbicides in France. We have shown that resistance to 2,4-D in France was widespread, even very well established in certain areas. We also identified two areas in Italy and Greece where resistant plants to halauxifen-methyl were detected, suggesting the beginning of the evolution of resistance to this new synthetic herbicide. Populations with a balanced ratio of resistant and sensitive individuals were used for plant material production for the molecular biology approaches of the second part.In a second part, we studied constitutive resistance to 2,4-D and halauxifen-methyl among 14 populations via RNA sequencing (RNAseq) (Chapter 2). We showed that the expression profiles of sensitive and resistant plants were specific to each population. Among the genes differentially expressed in resistant plants, some gene families potentially involved in the metabolism of herbicides (CYP450, GST, ABC transporters, etc.) or regulatory cascades (transcription factors, protein kinases) have been identified. Based on these results, the expression level of these genes was validated via an RT-qPCR approach using a larger sample of plants. All the results indicate that there is potentially a wide variety of inter- and intra-population resistance mechanisms.The second RNAseq (Chapter 3) aimed to study the transcriptomic response of resistant and sensitive plants between 4h and 48h after the application of 2,4-D in two populations. We identified a large diversity of genes and gene families specifically induced in resistant plants from both populations, but their role in resistance could not be verified. As in constitutive resistance, these can potentially be detoxification enzymes, transporters, or even potential auxin target genes or genes associated with the general stress response. In addition, 2,4-D induces a rapid response which is detectable within 4 hours following treatment regardless of the phenotype and population.Finally, the comparison of constitutively differentially expressed genes between the two RNAseq approaches demonstrates that the absence of common genes is potentially due to a high diversity of intra- and -inter population resistance mechanisms, or to the fact that the mechanisms that contribute the most to resistance are due to structural mutations
2

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.
3

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.
4

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
5

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.
6

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.
7

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.

8

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.

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This thesis introduces three different algorithmical and statistical strategies for the analysis of high-throughput sequencing data. First, we introduce a heuristic method based on enhanced suffix arrays to map short sequences to larger reference genomes. The algorithm builds on the idea of an error-tolerant traversal of the suffix array for the reference genome in conjunction with the concept of matching statistics introduced by Chang and a bitvector based alignment algorithm proposed by Myers. The algorithm supports paired-end and mate-pair alignments and the implementation offers methods for primer detection, primer and poly-A trimming. In our own benchmarks as well as independent bench- marks this tool outcompetes other currently available tools with respect to sensitivity and specificity in simulated and real data sets for a large number of sequencing protocols. Second, we introduce a novel dynamic programming algorithm for the spliced alignment problem. The advantage of this algorithm is its capability to not only detect co-linear splice events, i.e. local splice events on the same genomic strand, but also circular and other non-collinear splice events. This succinct and simple algorithm handles all these cases at the same time with a high accuracy. While it is at par with other state- of-the-art methods for collinear splice events, it outcompetes other tools for many non-collinear splice events. The application of this method to publically available sequencing data led to the identification of a novel isoform of the tumor suppressor gene p53. Since this gene is one of the best studied genes in the human genome, this finding is quite remarkable and suggests that the application of our algorithm could help to identify a plethora of novel isoforms and genes. Third, we present a data adaptive method to call single nucleotide variations (SNVs) from aligned high-throughput sequencing reads. We demonstrate that our method based on empirical log-likelihoods automatically adjusts to the quality of a sequencing experiment and thus renders a \"decision\" on when to call an SNV. In our simulations this method is at par with current state-of-the-art tools. Finally, we present biological results that have been obtained using the special features of the presented alignment algorithm
Diese 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
9

Duggett, Nicholas A. "High-throughput sequencing of the chicken gut microbiome." Thesis, University of Birmingham, 2016. http://etheses.bham.ac.uk//id/eprint/6678/.

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The chicken (\(Gallus\) \(gallus\) \(domesticus\)) is the most abundant and widely distributed livestock animal with a global population of over 21 bill ion. A newly hatched broiler chick increases its body weight by 25% overnight and 50-fold over five weeks. The symbiotic, complex and variable community of the microbiome forms an important part of the gastrointestinal tract (gut). It is involved in gut development, biochemistry, immunology, physiology and non-specific resistance to infection. This study investigated the chicken gut microbiota using high-throughput 16S rRNA sequencing and culture-based techniques. There was specific interest in the proventriculus of which there is limited research currently in the literature and the caecum because it contains the highest density of bacterial cells in the gut at 10\(^1\)\(^1\) per gram. The results showed no significant difference in the first stages of the gut which shared a low-diversity microbiota dominated by a few \(Lactobacillus\) species. The microbiota becomes more diverse in the latter pa1ts of the small intestine where \(C/ostridiales\) and \(Enterobacteriaceae\) were present in higher numbers. The caecum was the most diverse organ with the majority of species belonging to Ruminococcaceae, Lachnospiraceae and \(Alistipes\). A number of novel species were isolated from the chicken gut and six of these were whole-genome sequenced.
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Chiang, HyoJin Rosaria. "Examination of mammalian microRNAs by high-throughput sequencing." Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/65289.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Biology, 2011.
Cataloged 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.
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Books on the topic "Very high throughput sequencing":

1

Kwon, Young Min, and Steven C. Ricke, eds. 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, and Ana M. Aransay, eds. 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, and Ana M. Aransay. Bioinformatics for high throughput sequencing. New York, NY: Springer, 2012.

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Ricke, Steven C., and Young Min Kwon. High-throughput next generation sequencing: Methods and applications. New York: Springer, 2011.

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Aransay, Ana M., and José Luis Lavín Trueba, eds. 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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Mäkinen, Veli. 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., and 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, and Michael Hackenberg. Bioinformatics for High Throughput Sequencing. Springer, 2014.

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

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Lee, Eric, and 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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Book chapters on the topic "Very high throughput sequencing":

1

Chen, Yuan-Jyue, and Georg Seelig. "Scaling Up DNA Computing with Array-Based Synthesis and High-Throughput Sequencing." In Natural Computing Series, 281–93. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-9891-1_16.

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AbstractIt was 40 years ago today, when Ned taught DNA to play [32]. When Ned Seeman began laying the theoretical foundations of what is now DNA nanotechnology, he likely did not imagine the entire diversity and scale of molecular structures, machines, and computing devices that would be enabled by his work. While there are many reasons for the success of the field, not least the creativity shown by Ned and the community he helped build, such progress would not have been possible without breakthroughs in DNA synthesis and molecular analysis technology. Here, we argue that the technologies that will enable the next generation of DNA nanotechnology have already arrived but that we have not yet fully taken advantage of them. Specifically, we believe that it will become possible, in the near future, to dramatically scale up DNA nanotechnology through the use of array-synthesized DNA and high-throughput DNA sequencing. In this article, we provide an example of how DNA logic gates and circuits can be produced through enzymatic processing of array-synthesized DNA and can be read out by sequencing in a massively parallel format. We experimentally demonstrate processing and readout of 380 molecular gates in a single reaction. We further speculate that in the longer term, very large-scale DNA computing will find applications in the context of molecular diagnostics and, in particular, DNA data storage.
2

Deng, Xiangyu, Lee S. Katz, Patricia I. Fields, and Wei Zhang. "High-Throughput Sequencing." In 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." In 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, and Krishna Kant Gupta. "High-Throughput Sequencing Technologies." In 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, and Marco A. Marra. "Applications of High-Throughput Sequencing." In 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, and Hanlee P. Ji. "Overview of Sequencing Technology Platforms." In 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, and Ümit V. Çatalyürek. "High-Performance Computing In High-Throughput Sequencing." In 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, and Ana M. Aransay. "Introduction." In 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, and Mark D. Robinson. "Differential Expression for RNA Sequencing (RNA-Seq) Data: Mapping, Summarization, Statistical Analysis, and Experimental Design." In 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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Hackenberg, Michael. "MicroRNA Expression Profiling and Discovery." In Bioinformatics for High Throughput Sequencing, 191–208. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4614-0782-9_11.

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Conference papers on the topic "Very high throughput sequencing":

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Taher, Ahmed, Ben Jones, Peter Peumans, and Liesbet Lagae. "A Simplified Model for Species Transport in Very Large Scale Microfluidic Networks." In ASME 2018 16th International Conference on Nanochannels, Microchannels, and Minichannels. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/icnmm2018-7663.

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A novel modeling technique for fluid flow and species transport in very large scale microfluidic networks is developed with applications to massively parallelized microreactors. Very large scale integration (VLSI) of microfluidic circuits presents an attractive solution for many biological testing applications such as gene expression, DNA sequencing and drug screening, which require massive parallelization of reactions to increase throughput and decrease time-to-result. However, the design and modeling of VLSI microfluidics remains challenging with conventional 2D or 3D computational fluid dynamic (CFD) techniques due to the large computational resources required. Using simplified models is crucial to reduce simulation time on existing computational resources. Many microfluidic networks can be solved using resistance based networks similar to electrical circuits; however, simplified models for species transport (diffusion plus advection) in microfluidic networks has received much less attention. Here, we introduce a simplified model based on resistance network based modeling for flow dynamics and couple it with a one-dimensional discretization of the advection-diffusion transport equation. The developed model was validated against CFD simulations using ANSYS Fluent for a flow network consisting of a 4 by 4 array of microreactors. It showed good agreement with 2D CFD simulations with less than 6% error in total pressure drop across the network for channels with a length to width ratio of 10. The error was only 3% for a channel length to width ratio of 20. The developed model was then used to optimize the design of a 100-microreactors network used for high purity cyclical loading of reagents. The reactor configuration with a minimum cycle time for reagent loading and unloading and minimum operating pressure were evaluated with the code. In theory, the simulation can be scaled to much larger reactor arrays after further optimizations of the code and utilizing parallel processing.
2

Chaabane, Mohamed, Eric C. Rouchka, and Juw Won Park. "Circular RNA Detection from High-throughput Sequencing." In 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, and Alex Zelikovsky. "Poster: Haplotype discovery from high-throughput sequencing data." In 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, and Wei Wang. "Read Annotation Pipeline for High-Throughput Sequencing Data." In 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." In the ACM Conference. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2382936.2382947.

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Chanyshev, M. D., N. V. Vlasenko, I. A. Kotov, K. F. Khafizov, and V. G. Akimkin. "HIGH THROUGHPUT DNA SEQUENCING OF HEPATITIS B VIRUS." In 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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White, Brian S., Abdullah Ozer, John T. Lis, and David Shalloway. "Abstract LB-97: Optimizing SELEX with high-throughput sequencing." In 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, and Simon J. Puglisi. "Fast and efficient compression of high-throughput sequencing reads." In 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, and Naftali Kaminski. "High-Throughput Sequencing Of MicroRNA In Idiopathic Pulmonary Fibrosis." In 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." In 2009 IEEE International Conference on Granular Computing (GRC). IEEE, 2009. http://dx.doi.org/10.1109/grc.2009.5255117.

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Reports on the topic "Very high throughput sequencing":

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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), March 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, October 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, October 2015. http://dx.doi.org/10.21236/ada624260.

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Dhere, N. G. High Throughput, Low Toxic Processing of Very Thin, High Efficiency CIGSS Solar Cells: Final Report, December 2008. Office of Scientific and Technical Information (OSTI), April 2009. http://dx.doi.org/10.2172/951811.

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Novikova, Irina, James Evans, Lye Meng Markillie, and 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), November 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), January 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), January 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), November 1999. http://dx.doi.org/10.2172/754779.

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Cohen, Yuval, Christopher A. Cullis, and Uri Lavi. Molecular Analyses of Soma-clonal Variation in Date Palm and Banana for Early Identification and Control of Off-types Generation. United States Department of Agriculture, October 2010. http://dx.doi.org/10.32747/2010.7592124.bard.

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Date palm (Phoenix dactylifera L.) is the major fruit tree grown in arid areas in the Middle East and North Africa. In the last century, dates were introduced to new regions including the USA. Date palms are traditionally propagated through offshoots. Expansion of modern date palm groves led to the development of Tissue Culture propagation methods that generate a large number of homogenous plants, have no seasonal effect on plant source and provide tools to fight the expansion of date pests and diseases. The disadvantage of this procedure is the occurrence of off-type trees which differ from the original cultivar. In the present project we focused on two of the most common date palm off-types: (1) trees with reduced fruit setting, in which most of the flowers turn into three-carpel parthenocarpic fruits. In a severe form, multi-carpel flowers and fruitlets (with up to six or eight carpels instead of the normal three-carpel flowers) are also formed. (2) dwarf trees, having fewer and shorter leaves, very short trunk and are not bearing fruits at their expected age, compared to the normal trees. Similar off-types occur in other crop species propagated by tissue culture, like banana (mainly dwarf plants) or oil palm (with a common 'Mantled' phenotype with reduced fruit setting and occurrence of supernumerary carpels). Some off-types can only be detected several years after planting in the fields. Therefore, efficient methods for prevention of the generation of off-types, as well as methods for their detection and early removal, are required for date palms, as well as for other tissue culture propagated crops. This research is aimed at the understanding of the mechanisms by which off-types are generated, and developing markers for their early identification. Several molecular and genomic approaches were applied. Using Methylation Sensitive AFLP and bisulfite sequencing, we detected changes in DNA methylation patterns occurring in off-types. We isolated and compared the sequence and expression of candidate genes, genes related to vegetative growth and dwarfism and genes related to flower development. While no sequence variation were detected, changes in gene expression, associated with the severity of the "fruit set" phenotype were detected in two genes - PdDEF (Ortholog of rice SPW1, and AP3 B type MADS box gene), and PdDIF (a defensin gene, highly homologous to the oil palm gene EGAD). We applied transcriptomic analyses, using high throughput sequencing, to identify genes differentially expressed in the "palm heart" (the apical meristem and the region of embryonic leaves) of dwarf vs. normal trees. Among the differentially expressed genes we identified genes related to hormonal biosynthesis, perception and regulation, genes related to cell expansion, and genes related to DNA methylation. Using Representation Difference Analyses, we detected changes in the genomes of off-type trees, mainly chloroplast-derived sequences that were incorporated in the nuclear genome and sequences of transposable elements. Sequences previously identified as differing between normal and off-type trees of oil palms or banana, successfully identified variation among date palm off-types, suggesting that these represent highly labile regions of monocot genomes. The data indicate that the date palm genome, similarly to genomes of other monocot crops as oil palm and banana, is quite unstable when cells pass through a cycle of tissue culture and regeneration. Changes in DNA sequences, translocation of DNA fragments and alteration of methylation patterns occur. Consequently, patterns of gene expression are changed, resulting in abnormal phenotypes. The data can be useful for future development of tools for early identification of off-type as well as for better understanding the phenomenon of somaclonal variation during propagation in vitro.
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Gur, Amit, Edward Buckler, Joseph Burger, Yaakov Tadmor, and Iftach Klapp. Characterization of genetic variation and yield heterosis in Cucumis melo. United States Department of Agriculture, January 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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