Le cancer résulte de la prolifération excessive de cellules qui dérivent toutes de la même cellule initiatrice et suivent un processus Darwinien de diversification et de sélection. Ce processus est défini par l'accumulation d'altérations génétiques et épigénétiques dont la caractérisation est un élément majeur pour pouvoir proposer une thérapie ciblant spécifiquement les cellules tumorales. L'avènement des nouvelles technologies de séquençage haut débit permet cette caractérisation à un niveau moléculaire. Cette révolution technologique a entraîné le développement de nombreuses méthodes bioinformatiques. Dans cette thèse, nous nous intéressons particulièrement au développement de nouvelles méthodes computationnelles d'analyse de données de séquençage d'échantillons tumoraux permettant une identification précise d'altérations spécifiques aux tumeurs et une description fine des sous populations tumorales. Dans le premier chapitre, il s'agît d'étudier des méthodes d'identification d'altérations ponctuelles dans le cadre de séquençage ciblé, appliquées à une cohorte de patientes atteintes du cancer du sein. Nous décrivons deux nouvelles méthodes d'analyse, chacune adaptée à une technologie de séquençage, spécifiquement Roche 454 et Pacifique Biosciences.Dans le premier cas, nous avons adapté des approches existantes au cas particulier de séquences de transcrits. Dans le second cas, nous avons été confronté à un bruit de fond élevé entraînant un fort taux de faux positifs lors de l'utilisation d'approches classiques. Nous avons développé une nouvelle méthode, MICADo, basée sur les graphes de De Bruijn et permettant une distinction efficace entre les altérations spécifiques aux patients et les altérations communes à la cohorte, ce qui rend les résultats exploitables dans un contexte clinique. Le second chapitre aborde l'identification d'altérations de nombre de copies. Nous décrivons l'approche mise en place pour leur identification efficace à partir de données de très faible couverture. L'apport principal de ce travail consiste en l'élaboration d'une stratégie d'analyse statistique afin de mettre en évidence des changements locaux et globaux au niveau du génome survenus durant le traitement administré à des patientes atteintes de cancer du sein. Notre méthode repose sur la construction d'un modèle linéaire permettant d'établir des scores de différences entre les échantillons avant et après traitement. Dans le troisième chapitre, nous nous intéressons au problème de reconstruction clonale. Cette problématique récente est actuellement en plein essor, mais manque cependant d'un cadre formel bien établi. Nous proposons d'abord une formalisation du problème de reconstruction clonale. Ensuite nous utilisons ce formalisme afin de mettre en place une méthode basée sur les modèles de mélanges Gaussiens. Cette méthode utilise les altérations ponctuelles et de nombre de copies - comme celles abordées dans les deux chapitres précédents - afin de caractériser et quantifier les différentes populations clonales présentes dans un échantillon tumoral. / Cancer results from the excessive proliferation of cells decending from the same founder cell and following a Darwinian process of diversification and selection. This process is defined by the accumulation of genetic and epigenetic alterations whose characterization is a key element for establishing a therapy that would specifically target tumor cells. The advent of new high-throughput sequencing technologies enables this characterization at the molecular level. This technological revolution has led to the development of numerous bioinformatics methods. In this thesis, we are particularly interested in the development of new computational methods for the analysis of sequencing data of tumor samples allowing precise identification of tumor-specific alterations and an accurate description of tumor subpopulations. In the first chapter, we explore methods for identifying single nucleotide alterations in targeted sequencing data and apply them to a cohort of breast cancer patients. We introduce two new methods of analysis, each tailored to a particular sequencing technology, namely Roche 454 and Pacific Biosciences. In the first case, we adapted existing approaches to the particular case of transcript sequencing. In the second case, when using conventional approaches, we were confronted with a high background noise resulting in a high rate of false positives. We have developed a new method, MICADo, based on the De Bruijn graphs and making possible an effective distinction between patient-specific alterations and alterations common to the cohort, which makes the results usable in a clinical context. Second chapter deals with the identification of copy number alterations. We describe the approach put in place for their efficient identification from very low coverage data. The main contribution of this work is the development of a strategy for statistical analysis in order to emphasise local and global changes in the genome that occurred during the treatment administered to patients with breast cancer. Our method is based on the construction of a linear model to establish scores of differences between samples before and after treatment. In the third chapter, we focus on the problem of clonal reconstruction. This problem has recently gathered a lot of interest, but it still lacks a well-established formal framework. We first propose a formalization of the clonal reconstruction problem. Then we use this formalism to put in place a method based on Gaussian mixture models. Our method uses single nucleotide and copy number alterations - such as those discussed in the previous two chapters - to characterize and quantify different clonal populations present in a tumor sample.

Le PTGS (post-transcriptional gene silencing) est un mécanisme de défense qui cible les acides nucléiques invasifs d’origines endogènes (transposons) ou exogènes (pathogènes, transgènes). Des mutations dans les gènes JMJ14 et NAC52 ont été isolées lors d’un crible génétique visant à identifier des mutants déficients en PTGS. JMJ14 code une histone déméthylase ciblant la lysine 4 bi- ou tri-méthylée de l’histone H3, tandis que NAC52 code un facteur de transcription. Ces deux protéines forment un complexe qui régule la transcription de centaines de gènes endogènes. Toutefois, le rôle de ce complexe chromatinien dans l’expression des transgènes et surtout dans le PTGS reste incompris. JMJ14 interagit avec NAC52 mais aussi avec une protéine de type guanine exchange factor de la famille RCC1. Des mutations dans l’un ou l’autre des membres du complexe RCC1-JMJ14-NAC52 réduisent la transcription des transgènes. JMJ14 se fixe au promoteur de façon indépendante de NAC52, tandis que NAC52 a besoin de JMJ14 pour se fixer à la région transcrite. Toutefois, JMJ14 et NAC52 ne semblent pas requis pour la transcription proprement dite. En effet, un niveau normal de transcription est restauré chez le double mutant jmj14 drm2, indiquant que le rôle du complexe RCC1-JMJ14-NAC52 semble être d’empêcher la méthylation de novo du promoteur par DRM2.L’effet des mutations jmj14 et nac52 sur la transcription des transgènes ne peut expliquer leur effet sur certaines formes de PTGS. En effet, les mutations jmj14 et nac52 n’affectent pas le PTGS induit constitutivement. Par contre, elles empêchent la systémie du PTGS induit localement. Des mutations dans le gène SPCL45 codant une Serine Carboxy Peptidase-Like qui interagit avec NAC52, mais pas JMJ14, ont le même effet. En revanche, la mutation rcc1 n’affecte pas la systémie du PTGS, suggérant que c’est au sein d’un complexe JMJ14-NAC2-SPCL45 que JMJ14 et NAC52 contrôlent le PTGS systémique. Ce complexe pourrait agir directement sur la chromatine du transgène pour permettre d’enclencher le PTGS en réponse à la perception du signal systémique, ou indirectement en contrôlant l’expression d’un gène endogène codant une protéine régulant la systémie du PTGS. Afin de mieux comprendre le rôle de JMJ14 dans la systémie du PTGS, un crible génétique visant à isoler des suppresseurs de la mutation jmj14 a été réalisé. Seize mutants correspondants à sept gènes codant des protéines ayant un rapport avec la chromatine et une action antagoniste à JMJ14 ont été caractérisés. Les mutations dans ces sept gènes pourraient supprimer l’effet de jmj14 en augmentant la transcription du transgène cible et donc la quantité du signal systémique de PTGS. Un 17ème mutant pourrait quant à lui affecter qualitativement le signal systémique de PTGS ou la perception du signal dans les cellules qui le reçoivent. Le gène correspondant reste à identifier. / Post-transcriptional gene silencing (PTGS) is a defense mechanism that targets invading nucleic acids from endogenous (transposons) or exogenous (pathogens, transgenes) origins. Mutations in JMJ14 and NAC52 have been retrieved from a genetic screen aiming to identify PTGS deficient mutants. JMJ14 encodes an histone demethylase targeting the bi- or tri-methylated lysine 4 of histone H3, while NAC52 encodes a transcription factor. Both act in a complex that regulates the transcription of hundreds endogenous genes. However, the function of this chromatin complex in transgene expression and in PTGS is not known. JMJ14 interacts with NAC52 but also with a guanine exchange factor of the RCC1 family. Mutations in any member of the RCC1-JMJ14-NAC52 complex reduce transgene transcription. JMJ14 binds to the transgene promoter independently of NAC52, whereas NAC52 requires JMJ14 to bind on the transcribed region. However, JMJ14 and NAC52 do not seem to be required for transcription itself. Indeed, a wild-type level of transcription is restored in the jmj14 drm2 double mutant, suggesting that the complex RCC1-JMJ14-NAC52 prevents de novo DNA methylation of the promoter by DRM2. The effects of jmj14 and nac52 mutations on transgene transcription cannot explain their specific effect on some forms of PTGS. Indeed, jmj14 and nac52 do not affect constitutively-induced PTGS, but prevent the systemic spreading of locally-induced PTGS. Mutations in SCPL45, encoding a Serine-Carboxy Peptidase-Like that interacts with NAC52, but not JMJ14, have the same effect. In contrast, rcc1 does not affect the systemic PTGS, suggesting that a JMJ14-NAC52-SCPL45 complex is involved in the control of systemic PTGS. This complex could act directly on transgene chromatin to trigger PTGS in response to the PTGS signal, or indirectly by controlling the expression of an endogenous gene encoding a protein regulating systemic PTGS. To better understand the function of JMJ14 in systemic PTGS, a genetic screen aiming to identify suppressors of jmj14 have been performed. Sixteen mutants corresponding to seven genes encoding proteins related to chromatin and having an antagonist function to JMJ14, have been characterized. Mutations in theses seven genes could suppress jmj14 by increasing transgene transcription and consequently the quantity of the PTGS systemic signal. A seventeenth mutant could have a qualitative effect on the PTGS systemic signal or could affect the perception of this signal in recipient cells. The corresponding gene remains to identify.

With the development of economy, more and more cars appear in the roads. Many drivers ignore thedanger about driving after drinking so that drunk driving causes a large number of traffic accidents allaround the world. By now, alcohol has killed a lot of people in the world. To reduce accidents causedby drunk driving, make certain the alcohol content in driver's body would help a lot, and it is related toalcohol concentration measuring and relevant instrument.In this thesis work, the design of a simple alcohol meter was present. The designed system iscomposed of a gas sensor (TGS-822) working circuit, microcontroller PIC16F690 and LCD display.The system collects the electronic signals caused by resistance changes in gas sensor (TGS-822) froma built-in Analog-to-Digital Converter (A/D) in microcontroller PIC16F690, programs withPIC16F690, and displays alcohol concentration in LCD display finally. The measuring concentrationrange of the designed alcohol meter is from 50PPM to 5000PPM. This paper describes the datacollection, processing and display of the designed alcohol meter in detail. And lastly, the authordiscussed about the advantages and disadvantages of the designed alcohol meter, it could beconsidered as a guideline for further work.

No description available.

With the rapidly increasing demand for energy and the increasing prices for oil and gas, the role of unconventional gas reservoirs (UGRs) as energy sources is becoming more important throughout the world. Because of high risks and uncertainties associated with UGRs, their profitable development requires experts to be involved in the most critical development stages, such as drilling, completion, stimulation, and production. However, many companies operating UGRs lack this expertise. The advisory system we developed will help them make efficient decisions by providing insight from analogous basins that can be applied to the wells drilled in target basins. In North America, UGRs have been in development for more than 50 years. The petroleum literature has thousands of papers describing best practices in management of these resources. If we can define the characteristics of the target basin anywhere in the world and find an analogous basin in North America, we should be able to study the best practices in the analogous basin or formation and provide the best practices to the operators. In this research, we have built an advisory system that we call the Unconventional Gas Reservoir (UGR) Advisor. UGR Advisor incorporates three major modules: BASIN, PRISE and Drilling & Completion (D&C) Advisor. BASIN is used to identify the reference basin and formations in North America that are the best analogs to the target basin or formation. With these data, PRISE is used to estimate the technically recoverable gas volume in the target basin. Finally, by analogy with data from the reference formation, we use D&C Advisor to find the best practice for drilling and producing the target reservoir. To create this module, we reviewed the literature and interviewed experts to gather the information required to determine best completion and stimulation practices as a function of reservoir properties. We used these best practices to build decision trees that allow the user to take an elementary data set and end up with a decision that honors the best practices. From the decision trees, we developed simple computer algorithms that streamline the process.

In this master´s thesis various types of gas sensors, their characteristics, principle, active layer and structure are described. This work is focused on semiconductor gas sensors. In the experimental part gas test station is used to measure the main characteristic of commercial sensor Figaro TGS 822 and own SnO2 gas sensors and reaction to oxygen. Both sensors and measurement results are compared with each other.

No description available.

RNA interference (RNAi) is one of the key mechanisms that are involved in many biological processes such as control of plant gene expression, influence on chromatin arrangement or providing protection against invasive DNA or RNA transposons, viruses and transgenes. In plants, RNAi is triggered by double stranded RNA (dsRNA) that is cleaved by DICER LIKE (DCL) proteins to small RNAs (sRNAs). The size of these sRNAs is in range of 21 - 24 nucleotides (nt). Small RNA acts in the place of origin and they are also a mobile signal which in plants can move to a short distance through plasmodesmata and to a long distance trough phloem. sRNA and Argonaute (AGO) protein form RNA-induced silencing complex (RISC). Together, they recognize the target RNA molecule and contribute to an efficient RNAi phase which may be exhibited by gene silencing at posttranscriptional level (PTGS) or transcriptional level (TGS). The purpose of this study was to compare the effects of silencing constructs, witch in a controlled way differently trigger RNAi directed against the expression of the GFP reporter gene in the model organism Arabidopsis thaliana. Silencing constructs were placed under an inducible promoter activated by the presence of 17-β-estradiol (XVE system). They differed in the way of the dsRNA formation and in the...

[EN] The work done for this doctorate thesis focuses on error correction of Next Generation Sequencing (NGS) data in the context of High Performance Computing (HPC). Due to the reduction in sequencing cost, the increasing output of the sequencers and the advancements in the biological and medical sciences, the amount of NGS data has increased tremendously. Humans alone are not able to keep pace with this explosion of information, therefore computers must assist them to ease the handle of the deluge of information generated by the sequencing machines. Since NGS is no longer just a research topic (used in clinical routine to detect cancer mutations, for instance), requirements in performance and accuracy are more stringent. For sequencing to be useful outside research, the analysis software must work accurately and fast. This is where HPC comes into play. NGS processing tools should leverage the full potential of multi-core and even distributed computing, as those platforms are extensively available. Moreover, as the performance of the individual core has hit a barrier, current computing tendencies focus on adding more cores and explicitly split the computation to take advantage of them. This thesis starts with a deep analysis of all these problems in a general and comprehensive way (to reach out to a very wide audience), in the form of an exhaustive and objective review of the NGS error correction field. We dedicate a chapter to this topic to introduce the reader gradually and gently into the world of sequencing. It presents real problems and applications of NGS that demonstrate the impact this technology has on science. The review results in the following conclusions: the need of understanding of the specificities of NGS data samples (given the high variety of technologies and features) and the need of flexible, efficient and accurate tools for error correction as a preliminary step of any NGS postprocessing. As a result of the explosion of NGS data, we introduce MuffinInfo. It is a piece of software capable of extracting information from the raw data produced by the sequencer to help the user understand the data. MuffinInfo uses HTML5, therefore it runs in almost any software and hardware environment. It supports custom statistics to mould itself to specific requirements. MuffinInfo can reload the results of a run which are stored in JSON format for easier integration with third party applications. Finally, our application uses threads to perform the calculations, to load the data from the disk and to handle the UI. In continuation to our research and as a result of the single core performance limitation, we leverage the power of multi-core computers to develop a new error correction tool. The error correction of the NGS data is normally the first step of any analysis targeting NGS. As we conclude from the review performed within the frame of this thesis, many projects in different real-life applications have opted for this step before further analysis. In this sense, we propose MuffinEC, a multi-technology (Illumina, Roche 454, Ion Torrent and PacBio -experimental), any-type-of-error handling (mismatches, deletions insertions and unknown values) corrector. It surpasses other similar software by providing higher accuracy (demonstrated by three type of tests) and using less computational resources. It follows a multi-steps approach that starts by grouping all the reads using a k-mers based metric. Next, it employs the powerful Smith-Waterman algorithm to refine the groups and generate Multiple Sequence Alignments (MSAs). These MSAs are corrected by taking each column and looking for the correct base, determined by a user-adjustable percentage. This manuscript is structured in chapters based on material that has been previously published in prestigious journals indexed by the Journal of Citation Reports (on outstanding positions) and relevant congresses. / [ES] El trabajo realizado en el marco de esta tesis doctoral se centra en la corrección de errores en datos provenientes de técnicas NGS utilizando técnicas de computación intensiva. Debido a la reducción de costes y el incremento en las prestaciones de los secuenciadores, la cantidad de datos disponibles en NGS se ha incrementado notablemente. La utilización de computadores en el análisis de estas muestras se hace imprescindible para poder dar respuesta a la avalancha de información generada por estas técnicas. El uso de NGS transciende la investigación con numerosos ejemplos de uso clínico y agronómico, por lo que aparecen nuevas necesidades en cuanto al tiempo de proceso y la fiabilidad de los resultados. Para maximizar su aplicabilidad clínica, las técnicas de proceso de datos de NGS deben acelerarse y producir datos más precisos. En este contexto es en el que las técnicas de comptuación intensiva juegan un papel relevante. En la actualidad, es común disponer de computadores con varios núcleos de proceso e incluso utilizar múltiples computadores mediante técnicas de computación paralela distribuida. Las tendencias actuales hacia arquitecturas con un mayor número de núcleos ponen de manifiesto que es ésta una aproximación relevante. Esta tesis comienza con un análisis de los problemas fundamentales del proceso de datos en NGS de forma general y adaptado para su comprensión por una amplia audiencia, a través de una exhaustiva revisión del estado del arte en la corrección de datos de NGS. Esta revisión introduce gradualmente al lector en las técnicas de secuenciación masiva, presentando problemas y aplicaciones reales de las técnicas de NGS, destacando el impacto de esta tecnología en ciencia. De este estudio se concluyen dos ideas principales: La necesidad de analizar de forma adecuada las características de los datos de NGS, atendiendo a la enorme variedad intrínseca que tienen las diferentes técnicas de NGS; y la necesidad de disponer de una herramienta versátil, eficiente y precisa para la corrección de errores. En el contexto del análisis de datos, la tesis presenta MuffinInfo. La herramienta MuffinInfo es una aplicación software implementada mediante HTML5. MuffinInfo obtiene información relevante de datos crudos de NGS para favorecer el entendimiento de sus características y la aplicación de técnicas de corrección de errores, soportando además la extensión mediante funciones que implementen estadísticos definidos por el usuario. MuffinInfo almacena los resultados del proceso en ficheros JSON. Al usar HTML5, MuffinInfo puede funcionar en casi cualquier entorno hardware y software. La herramienta está implementada aprovechando múltiples hilos de ejecución por la gestión del interfaz. La segunda conclusión del análisis del estado del arte nos lleva a la oportunidad de aplicar de forma extensiva técnicas de computación de altas prestaciones en la corrección de errores para desarrollar una herramienta que soporte múltiples tecnologías (Illumina, Roche 454, Ion Torrent y experimentalmente PacBio). La herramienta propuesta (MuffinEC), soporta diferentes tipos de errores (sustituciones, indels y valores desconocidos). MuffinEC supera los resultados obtenidos por las herramientas existentes en este ámbito. Ofrece una mejor tasa de corrección, en un tiempo muy inferior y utilizando menos recursos, lo que facilita además su aplicación en muestras de mayor tamaño en computadores convencionales. MuffinEC utiliza una aproximación basada en etapas multiples. Primero agrupa todas las secuencias utilizando la métrica de los k-mers. En segundo lugar realiza un refinamiento de los grupos mediante el alineamiento con Smith-Waterman, generando contigs. Estos contigs resultan de la corrección por columnas de atendiendo a la frecuencia individual de cada base. La tesis se estructura por capítulos cuya base ha sido previamente publicada en revistas indexadas en posiciones dest / [CAT] El treball realitzat en el marc d'aquesta tesi doctoral se centra en la correcció d'errors en dades provinents de tècniques de NGS utilitzant tècniques de computació intensiva. A causa de la reducció de costos i l'increment en les prestacions dels seqüenciadors, la quantitat de dades disponibles a NGS s'ha incrementat notablement. La utilització de computadors en l'anàlisi d'aquestes mostres es fa imprescindible per poder donar resposta a l'allau d'informació generada per aquestes tècniques. L'ús de NGS transcendeix la investigació amb nombrosos exemples d'ús clínic i agronòmic, per la qual cosa apareixen noves necessitats quant al temps de procés i la fiabilitat dels resultats. Per a maximitzar la seua aplicabilitat clínica, les tècniques de procés de dades de NGS han d'accelerar-se i produir dades més precises. En este context és en el que les tècniques de comptuación intensiva juguen un paper rellevant. En l'actualitat, és comú disposar de computadors amb diversos nuclis de procés i inclús utilitzar múltiples computadors per mitjà de tècniques de computació paral·lela distribuïda. Les tendències actuals cap a arquitectures amb un nombre més gran de nuclis posen de manifest que és esta una aproximació rellevant. Aquesta tesi comença amb una anàlisi dels problemes fonamentals del procés de dades en NGS de forma general i adaptat per a la seua comprensió per una àmplia audiència, a través d'una exhaustiva revisió de l'estat de l'art en la correcció de dades de NGS. Esta revisió introduïx gradualment al lector en les tècniques de seqüenciació massiva, presentant problemes i aplicacions reals de les tècniques de NGS, destacant l'impacte d'esta tecnologia en ciència. D'este estudi es conclouen dos idees principals: La necessitat d'analitzar de forma adequada les característiques de les dades de NGS, atenent a l'enorme varietat intrínseca que tenen les diferents tècniques de NGS; i la necessitat de disposar d'una ferramenta versàtil, eficient i precisa per a la correcció d'errors. En el context de l'anàlisi de dades, la tesi presenta MuffinInfo. La ferramenta MuffinInfo és una aplicació programari implementada per mitjà de HTML5. MuffinInfo obté informació rellevant de dades crues de NGS per a afavorir l'enteniment de les seues característiques i l'aplicació de tècniques de correcció d'errors, suportant a més l'extensió per mitjà de funcions que implementen estadístics definits per l'usuari. MuffinInfo emmagatzema els resultats del procés en fitxers JSON. A l'usar HTML5, MuffinInfo pot funcionar en gairebé qualsevol entorn maquinari i programari. La ferramenta està implementada aprofitant múltiples fils d'execució per la gestió de l'interfície. La segona conclusió de l'anàlisi de l'estat de l'art ens porta a l'oportunitat d'aplicar de forma extensiva tècniques de computació d'altes prestacions en la correcció d'errors per a desenrotllar una ferramenta que suport múltiples tecnologies (Illumina, Roche 454, Ió Torrent i experimentalment PacBio). La ferramenta proposada (MuffinEC), suporta diferents tipus d'errors (substitucions, indels i valors desconeguts). MuffinEC supera els resultats obtinguts per les ferramentes existents en este àmbit. Oferix una millor taxa de correcció, en un temps molt inferior i utilitzant menys recursos, la qual cosa facilita a més la seua aplicació en mostres més gran en computadors convencionals. MuffinEC utilitza una aproximació basada en etapes multiples. Primer agrupa totes les seqüències utilitzant la mètrica dels k-mers. En segon lloc realitza un refinament dels grups per mitjà de l'alineament amb Smith-Waterman, generant contigs. Estos contigs resulten de la correcció per columnes d'atenent a la freqüència individual de cada base. La tesi s'estructura per capítols la base de la qual ha sigut prèviament publicada en revistes indexades en posicions destacades de l'índex del Journal of Citation Repor / Alic, AS. (2016). Improved Error Correction of NGS Data [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/67630 / TESIS

RNA interference (RNAi) is a process mediated by small RNAs (sRNA), which is significantly involved in the regulation of gene expression in plants. Diverse RNAi pathways can be divided into two basic mechanisms, which are post-transcriptional and transcriptional gene silencing (PTGS and TGS). Production of sRNAs is dependent on the presence of a double-stranded RNA molecule (dsRNA), which is cleaved by one of DCL proteins to produce sRNAs usually of 21-24 nt in length. One strand of the sRNA is subsequently loaded onto AGO protein. During PTGS, the AGO-sRNA complex interacts with the target RNA based on its sequence complementarity to the sRNA and cleaves it or blocks its translation. In the case of TGS, AGO interacts with plant-specific RNA Pol V and its transcripts, which are again complementary to the sRNA. This interaction allows assembling of a protein complex facilitating DNA and histone methylation inhibiting RNA Pol II transcription. There are numerous ways the dsRNA can arise. A significant part of dsRNA cell production is dependent on synthesising the complementary strand of the dsRNA by RDR6 (RNA-dependent RNA polymerase 6). RDR6 is also involved in the process of the secondary sRNA formation. The significance of RDR6 during PTGS was examined using a GFP reporter gene either during...