Malignant tumors remain one of the leading causes of mortality with over 8.2 million deaths worldwide in 2012. Over the last two decades, high-throughput profiling of the human transcriptome has become an essential tool to investigate molecular processes involved in carcinogenesis. In this thesis I explore how gene expression profiling (GEP) can be used in multiple aspects of cancer research, including prevention, patient stratification and subtype discovery. The first part details how GEP could be used to supplement or even replace the current gold standard assay for testing the carcinogenic potential of chemicals. This toxicogenomic approach coupled with a Random Forest algorithm allowed me to build models capable of predicting carcinogenicity with an area under the curve of up to 86.8% and provided valuable insights into the underlying mechanisms that may contribute to cancer development. The second part describes how GEP could be used to stratify heterogeneous populations of lymphoma patients into therapeutically relevant disease sub-classes, with a particular focus on diffuse large B-cell lymphoma (DLBCL). Here, I successfully translated established biomarkers from the Affymetrix platform to the clinically relevant Nanostring nCounter© assay. This translation allowed us to profile custom sets of transcripts from formalin-fixed samples, transforming these biomarkers into clinically relevant diagnostic tools. Finally, I describe my effort to discover tumor samples dependent on altered metabolism driven by oxidative phosphorylation (OxPhos) across multiple tissue types. This work was motivated by previous studies that identified a therapeutically relevant OxPhos sub-type in DLBCL, and by the hypothesis that this stratification might be applicable to other solid tumor types. To that end, I carried out a transcriptomics-based pan-cancer analysis, derived a generalized PanOxPhos gene signature, and identified mTOR as a potential regulator in primary tumor samples. High throughput GEP coupled with statistical machine learning methods represent an important toolbox in modern cancer research. It provides a cost effective and promising new approach for predicting cancer risk associated to chemical exposure, it can reduce the cost of the ever increasing drug development process by identifying therapeutically actionable disease subtypes, and it can increase patients’ survival by matching them with the most effective drugs. / 2016-12-01T00:00:00Z

abstract: Aromatic compounds have traditionally been generated via petroleum feedstocks and have wide ranging applications in a variety of fields such as cosmetics, food, plastics, and pharmaceuticals. Substantial improvements have been made to sustainably produce many aromatic chemicals from renewable sources utilizing microbes as bio-factories. By assembling and optimizing native and non-native pathways to produce natural and non-natural bioproducts, the diversity of biochemical aromatics which can be produced is constantly being improved upon. One such compound, 2-Phenylethanol (2PE), is a key molecule used in the fragrance and food industries, as well as a potential biofuel. Here, a novel, non-natural pathway was engineered in Escherichia coli and subsequently evaluated. Following strain and bioprocess optimization, accumulation of inhibitory acetate byproduct was reduced and 2PE titers approached 2 g/L – a ~2-fold increase over previously implemented pathways in E. coli. Furthermore, a recently developed mechanism to allow E. coli to consume xylose and glucose, two ubiquitous and industrially relevant microbial feedstocks, simultaneously was implemented and systematically evaluated for its effects on L-phenylalanine (Phe; a precursor to many microbially-derived aromatics such as 2PE) production. Ultimately, by incorporating this mutation into a Phe overproducing strain of E. coli, improvements in overall Phe titers, yields and sugar consumption in glucose-xylose mixed feeds could be obtained. While upstream efforts to improve precursor availability are necessary to ultimately reach economically-viable production, the effect of end-product toxicity on production metrics for many aromatics is severe. By utilizing a transcriptional profiling technique (i.e., RNA sequencing), key insights into the mechanisms behind styrene-induced toxicity in E. coli and the cellular response systems that are activated to maintain cell viability were obtained. By investigating variances in the transcriptional response between styrene-producing cells and cells where styrene was added exogenously, better understanding on how mechanisms such as the phage shock, heat-shock and membrane-altering responses react in different scenarios. Ultimately, these efforts to diversify the collection of microbially-produced aromatics, improve intracellular precursor pools and further the understanding of cellular response to toxic aromatic compounds, give insight into methods for improved future metabolic engineering endeavors. / Dissertation/Thesis / Doctoral Dissertation Chemical Engineering 2019

Indiana University-Purdue University Indianapolis (IUPUI) / Regulatory protein families such as transcription factors (TFs) and RNA Binding Proteins (RBPs) are increasingly being appreciated for their role in regulating the respective targeted genomic/transcriptomic elements resulting in dynamic transcriptional (TRNs) and post-transcriptional regulatory networks (PTRNs) in higher eukaryotes. The mechanistic understanding of these two regulatory network types require a high resolution tissue-specific functional annotation of both the proteins as well as their target sites. This dissertation addresses the need to uncover the tissue-specific regulatory networks in development and disease. This work establishes multiple computational genomics based approaches to further enhance our understanding of regulatory circuits and decipher the associated mechanisms at several layers of biological processes. This study potentially contributes to the research community by providing valuable resources including novel methods, web interfaces and software which transforms our ability to build high-quality regulatory binding maps of RBPs and TFs in a tissue specific manner using multi-omics datasets. The study deciphered the broad spectrum of temporal and evolutionary dynamics of the transcriptome and their regulation at transcriptional and post transcriptional levels. It also advances our ability to functionally annotate hundreds of RBPs and their RNA binding sites across tissues in the human genome which help in decoding the role of RBPs in the context of disease phenotype, networks, and pathways. The approaches developed in this dissertation is scalable and adaptable to further investigate the tissue specific regulators in any biological systems. Overall, this study contributes towards accelerating the progress in molecular diagnostics and drug target identification using regulatory network analysis method in disease and pathophysiology.

No description available.

No description available.

Opioid use disorder is a chronic, relapsing disease, with more than 85% of individuals experiencing a relapse episode within one year. One common reason patients relapse is due to intense cravings, which are defined as the compulsive urge to use the drug. In fact, craving was recently added to the DSM criteria for substance use disorder diagnosis. Counterintuitively, cravings intensify over the course of extended abstinence, especially in response to drug-paired cues, a phenomenon known as “incubation of craving”. This contributes to difficulty in maintaining long-term sobriety. The mesocorticolimbic reward pathway facilitates self-administration and cue-induced incubation of craving for drugs of abuse and natural rewards, such as sucrose. In particular, the shell sub-region of the nucleus accumbens is a critical brain region involved in context/cue-mediated reward seeking. In the experiments described here, we utilized an incubation of craving model, in which male and female rats self-administered opioids (morphine or heroin) or sucrose for 10 days. Sucrose served as an important control for delineating drug-induced changes from those caused in response to natural rewards, which are not the intended target of potential treatments. Reward delivery was paired with a cue light that was later used to elicit craving. After self-administration, rats underwent brief (one day) or extended (30 days) forced abstinence. One or 30 days later, they were returned to the chambers for a “cue test”, in which responses on the previously reward-associated lever triggered cue presentation, but no contingent reward. We used this model to further delineate behavioral and affective changes that accompany increased opioid craving in late abstinence, as well as molecular alterations underlying craving in rats that did not undergo a cue test. We found an opioid-specific behavioral signature in which peak opioid craving is accompanied by decreased grooming and hyperactivity in both sexes. We tracked the female estrous cycle throughout, as these fluctuations in reproductive hormones (akin to the menstrual cycle) are shown to affect cocaine- and nicotine-related behaviors. We found no differences between females in different phases of the estrous cycle in terms of self-administration, nor craving. RNA sequencing of the nucleus accumbens shell revealed robust changes in gene expression that occurred across extended abstinence, though the genes themselves were altered in a sex- and reinforcer-specific manner. In general, we found many behavioral and molecular changes that were unique to sex and reinforcer (sucrose versus opioids). This is promising in terms of identifying opioid-specific targets that are unlikely to affect the natural reward system in both sexes. Changes in gene expression in the brain are mediated in part by epigenetic processes that influence access of transcriptional machinery to DNA. Acetylation of histone tails, the proteins around which DNA is wrapped and packaged in the nucleus, have been identified as permissive marks that facilitate long-lasting changes in transcriptomics in response to environmental insults. Opioids promote increased acetylation, which may contribute to some of the reported changes here. We tested the efficacy of JQ1, a treatment that interferes with the read-out of opioid-induced acetylated marks, at attenuating heroin self-administration. When administered as an intracerebroventricular microinjection on self-administration day 11, JQ1 had no effect on subsequent heroin taking in either sex, suggesting that it may not be suitable as a systemic treatment at the dose given. These studies lay the groundwork for future studies to administer other treatments throughout abstinence, based on the opioid-specific genes and pathways identified here, to reduce cue-induced heroin craving and the accompanying suite of behaviors in males and females. / Psychology

The chicken bursa of Fabricius is a primary lymphoid tissue important for B-cell development. Our long-term goal is to understand the role of bursal microenvironment in an early B-cell differentiation event initiating repertoire development through immunoglobulin gene-conversion in the chick embryo. We hypothesize that early bursal B-cell differentiation is guided by signals through cytokine receptors. Our theory is based on previous evidence for expression of the receptor tyrosine kinase superfamily members and interleukin receptors in unseparated populations of bursal B-cells and bursal tissue. Knowledge of the expressed genes that are responsible for B-cell differentiation is a prerequisite for understanding the bursal microenvironment’s function. This project uses transcriptomic analysis to examine gene expression across an early B-cell differentiation event. RNA-seq was performed with total RNA isolated from developing B-cells at embryonic day (ED) 16 and ED 19 (n=3). Approximately 90 million high quality clean reads where obtained from the cDNA libraries. The analysis revealed differentially expressed genes involved in Wnt signaling pathway, Jak-STAT pathway, metabolic pathways, tyrosine metabolism, Toll-like receptor signaling pathway, MAPK signaling pathway, and cellhesion molecules. The transcripts for surface receptors, signal transduction and transcription factors identified in this study represent gene candidates for controlling B-cell differentiation in response to bursal microenvironmental factors.

Bacterial pathogens are a major cause of diseases in human, agricultural plants and farm animals. Even after decades of research they remain a challenge to health care as they are known to rapidly evolve and develop resistance to the existing drugs. Systems biology is an emerging area of research where all of the components of the system, their interactions, and the dynamics can be studied in a comprehensive, quantitative, and integrative fashion to generate predictive models. When applied to bacterial pathogenesis, systems biology approaches will help identify potential novel molecular targets for drug discovery. A pre-requisite for conducting systems analysis is the identification of the building blocks of the system i.e. individual components of the system (structural annotation), identification of their functions (functional annotation) and identification of the interactions among the individual components (interaction prediction). In the context of bacterial pathogenesis, it is necessary to identify the host-pathogen interactions. This dissertation work describes computational resources that enable comprehensive systems level study of host pathogen system to enhance our understanding of bacterial pathogenesis. It specifically focuses on improving the structural and functional annotation of pathogen genomes as well as identifying host-pathogen interactions at a genome scale. The novel contributions of this dissertation towards systems biology of bacterial pathogens include three computational tools/resources. “TAAPP” (Tiling array analysis pipeline for prokaryotes) is a web based tool for the analysis of whole genome tiling array data for bacterial pathogens. TAAPP helps improve the structural annotation of bacterial genomes. “ISO-IEA” (Inferred from sequence orthology - Inferred from electronic annotation) is a tool that can be used for the functional annotation of any sequenced genome. “HPIDB” (Host pathogen interaction database) is developed with data a mining capability that includes host-pathogen interaction prediction. The new knowledge gained due to the implementation of these tools is the description of the non coding RNA as well as a computationally predicted host-pathogen interaction network for the human respiratory pathogen Streptococcus pneumoniae. In summary, the computation tools and resources developed in this dissertation study will enable building systems biology models of bacterial pathogens.

<p>  </p> <p>Shikonin is 1,4-naphthoquinones produced exclusively in Boraginaceae species. The compound and its derivatives are predominantly made in roots where they function in mediating plant-plant (allelopathic) and plant-microbe interactions. Moreover, this compound has been a target for drug development due to its strong anti-cancer properties. Our genome assembly and analysis of <em>Lithospermum erythrorhizon</em> uncovered metabolic innovation events that contributed to the evolution of the shikonin biosynthesis. This metabolic innovation also reveals the evolutionary link between shikonin biosynthesis and ubiquinone biosynthesis, one of the central metabolism functions in aerobic cellular respiration. To explore additional links between these two pathways, we used a transcriptome-based network analysis which uncovered a shikonin gene network model that predicts strong associations between primary metabolic pathway genes and known shikonin biosynthesis genes, as well as links with uncharacterized genes. <em>L. erythrorhizon</em> geranyldiphosphate (GPP) synthase (<em>LeGPPS</em>) is one of the candidates predicted by the network analysis, of which encodes a cytoplasmic enzyme shown in vitro to produce GPP. Knocking down of <em>LeGPPS</em> in <em>L. erythrorhizon </em>hairy roots (<em>LeGPPSi </em>lines) results in reduced shikonin content. This result provides functional evidence that cytoplasmic LeGPPS supplies GPP precursor to the shikonin biosynthesis. <em>LeGPPSi </em>lines also increased ubiquinone content, further supporting our hypothesis on the metabolic and evolutionary connection between shikonin and ubiquinone biosynthesis. Further RNA-seq analysis of the <em>LeGPPSi</em> line showed that downregulating <em>LeGPPS</em> significantly reduces the expression of benzenoid/phenylpropanoid genes, indicating the presence of factors that coordinately regulate the pathways providing the 4-hydroxybenzoic acid and GPP precursors to the shikonin pathway. In addition to <em>LeGPPS</em>, we also found<em> ubiquinone biosynthesis protein COQ4-like </em>gene (<em>LeCOQ4-L</em>) which provided another evolutionary link between shikonin and ubiquinone biosynthesis. The enzymatic activity of canonical COQ4 is unknown. In yeast, the protein is essential for ubiquinone biosynthesis and its metabolon formation. With the existing connections between shikonin and ubiquinone biosynthesis, if LeCOQ4 functions in the same manner as yeast COQ4, it is possible that <em>LeCOQ4-L </em>has an analogous function in shikonin biosynthesis as a structural protein for stabilizing biosynthesis metabolon. This leads us to the characterization of<em> COQ4</em> ortholog in Arabidopsis (<em>AtCOQ4</em>) to gain insight into its functional mechanism. Characterization of <em>atcoq4 </em>T-DNA mutant line showed that reduced <em>AtCOQ4</em> expression resulted in reduced ubiquinone. Further subcellular localization study revealed that AtCOQ4 and <em>LeCOQ4-L</em> localize in mitochondria without conventional transit peptide. We also performed pull-down assay to identify AtCOQ4 interactors which might be the missing enzymes that cannot be identified based on homology. 80 potential AtCOQ4 interactors were found including proteins like AtCHLM, GRIM-19, and AtSSLs. However, further study is needed to verify the protein interactions captured by pull-down assay. Taken all together, our study sheds light on the metabolic innovations that give rise to shikonin biosynthesis from ubiquinone biosynthesis and provide insight into the dynamics of the metabolic networks.</p>

[ES] Uno de los aspectos más apasionantes de la transcripción es la plasticidad transcriptómica y proteómica mediada por los procesos de regulación post-transcripcional (PTR). Los mecanismos PTR como el splicing alternativo (AS) y la poliadenilación alternativa (APA) han emergido como procesos estrechamente regulados que juegan un papel clave en la generación de la complejidad transcriptómica y están asociados con la coordinación de la diferenciación celular o el desarrollo de tejidos. Sin embargo nuestro conocimiento sobre cómo estos mecanismos regulan las propiedades de los productos resultantes para definir el fenotipo es aún muy reducido. La cantidad de variantes existentes y el amplio rango de posibles consecuencias funcionales, hacen su validación funcional una tarea impracticable si se realiza caso por caso. Además, la falta de herramientas para la evaluación funcional orientada a isoformas ha provocado que gran parte del trabajo computacional haya empleado pipelines ad-hoc aplicadas a sistemas biológicos específicos o simplemente hayan confiado en análisis de enriquecimiento GO, los cuales no son informativos del impacto en las propiedades de las isoformas que hay detrás de la regulación PTR. De hecho, a pesar de las más de sesenta mil publicaciones relativas al AS, muy pocas isoformas se han asociado con propiedades específicas, mientras que el número de nuevas variantes AS/APA con function desconocida crece exponencialmente debido a las técnicas de secuenciación de segunda generación (NGS). Además, y debido a limitaciones técnicas de las NGS para reconstruir la estructura de los transcritos, las tecnologías de secuenciación de tercera generación (TGS) están definiendo una nueva era en la que, por primera vez, es posible conocer la secuencia de elementos estructurales y funcionales en los mRNAs. En esta tesis se han abordado tres propósitos principales para poder avanzar en el estudio funcional de las isoformas. En primer lugar, con las TGS siendo cada vez más utilizadas, la evaluación de la calidad de los transcriptomas \textit{de novo} es esencial para asegurar la fiabilidad de la diversidad transcriptómica encontrada. La falta de análisis de calidad orientados a secuencias largas ha motivado el desarrollo de SQANTI, una pipeline automatizado para la exhaustiva evaluación de TGS transcriptomas. En segundo lugar, la información a nivel de gen de la mayoría de bases de datos funcionales sigue siendo el principal escollo para el estudio de la variabilidad entre isoformas, especialmente en el caso de las isoformas nuevas, en las que las bases de datos estáticas impiden su caracterización. Así, hemos diseñado IsoAnnot, que construye una base de datos de anotaciones funcionales con resolución a nivel de isoformas integrando información diseminada por múltiples bases de datos y métodos de predicción. Finalmente, la indisponibilidad de métodos para estudiar el impacto funcional de la regulación de isoformas, nos ha motivado a desarrollar tappAS, una herramienta dinámica, flexible y diseñada para facilitar el abordaje de este tipo de estudios. Por lo tanto, durante esta tesis hemos desarrollado una infraestructura que resuelve los retos principales del análisis funcional de isoformas, proporcionando un conjunto de nuevos métodos y herramientas que ofrecen una oportunidad única para explorar cómo el fenotipo se especifica post-transcripcionalmente, mediante la alteración de las propiedades funcionales de las isoformas expresadas. La aplicación de nuestro análisis a un doble sistema de diferenciación neuronal en ratón definió el efecto de la regulación de isoformas entre la diferenciación de motoneuronas y oligodendrocitos para múltiples elementos funcionales. Entre ellos, hemos descubierto regiones transmembrana que son diferencialmente incluidas en las isoformas expresadas entre ambos tipos celulares y cuya regulación podría estar contribuyendo al control de / [CA] Un dels aspectes més emocionants de la biologia del transcriptoma és l'adaptabilitat contextual de transcriptomes i proteomes eucariotes mitjançant la regulació post-transcripcional (PTR). Els mecanismes PTR, com el splicing alternatiu (AS) i la poliadenilació alternativa (APA), s'han convertit en processos molt regulats que juguen un paper clau en la generació de la complexitat del transcriptoma i en la coordinació de la diferenciació cel·lular o del desenvolupament de teixits. No obstant això, el nostre coneixement de com aquests mecanismes imprimeixen característiques funcionals diferents al conjunt resultant d'isoformes per definir el fenotip observat és encara escàs. El nombre de variants de PTR i les seues conseqüències potencialment funcionals fa que la validació funcional sigui una tasca poc pràctica si es fa cas per cas. A més, la manca d'enfocaments funcionals orientats a isoformes ha fet que gran part del treballs computacionals per esbrinar qüestions funcionals a nivell de transcriptoma siguen estratègies computacionals ad hoc aplicades a sistemes biològics específics o bé basats en un simple anàlisi d'enriquiment GO, que no aporten informació sobre l'impacte de la PTR sobre les propietats de les isoformes. Així, malgrat les més de 60.000 publicacions existents sobre AS, poques de les isoformes existents s'han associat a propietats específiques, mentre que el nombre de noves variants AS/APA amb funcions desconegudes i fins i tot inexplorades augmenta de manera exponencial gràcies a la seqüenciació de nova generació (NGS). A causa de les limitacions tècniques del NGS per reconstruir l'estructura dels transcrits, la seqüenciació d'alt rendiment de transcrits de longitud completa mitjançant tecnologies de tercera generació (TGS) obre una nova era en la transcriptòmica, ja que millora la definició dels models genètics i, per primera vegada, permet associar amb precisió esdeveniments funcionals dins de la molècula d'ARN. Aquesta tesi aborda tres grans reptes per a progressar en l'estudi de la funció de les isoformes. En primer lloc, amb l'aparició i la popularitat creixent del TGS, la definició precisa i la caracterització completa dels transcriptomes de novo són essencials per garantir la qualitat de qualsevol conclusió sobre la diversitat del transcriptoma. La manca d'anàlisis de qualitat orientats a lectures llargues va motivar el desenvolupament de SQANTI (https://bitbucket.org/ ConesaLab / sqanti), una estratègia computacional automatitzada per a la caracterització estructural i l'avaluació de la qualitat dels transcriptomes de longitud completa. En segon lloc, els recursos funcionals existents centrats en el gen suposen una gran limitació per a l'estudi extensiu de la variabilitat funcional de les isoformes, especialment en les noves isoformes, que no es poden caracteritzar per bases de dades estàtiques. Per tant, vam dissenyar IsoAnnot, que construeix dinàmicament una base de dades amb anotacions funcionals a nivell d'isoforma, que utilitza com a informació d'entrada les seqüències dels transcrits i integra informació de diverses bases de dades i mètodes de predicció. Finalment, com no hi havia cap mètode per interrogar l'impacte funcional del PTR, vam desenvolupar nous enfocaments i eines fàcils d'utilitzar, com ara tappAS (http://tappas.org/), dissenyada per facilitar als investigadors els estudis funcionals de transcriptoma complet i de regulació d'isoformes en contexts específics. Per tant, aquesta tesi descriu el desenvolupament d'un marc d'anàlisi que aborda els reptes fonamentals de l'anàlisi funcional d'isoformes. Aplicada a un sistema de diferenciació neuronal murina, vam descobrir regions transmembrana específiques d'isoformes, la modulació de les quals per PTR podria contribuir a controlar la dinàmica mitocondrial específica del tipus cel·lular durant la determinació del destí neuronal. / [EN] One of the most exciting aspects of transcriptome biology is the contextual adaptability of eukaryotic transcriptomes and proteomes by post-transcriptional regulation (PTR). PTR mechanisms such as alternative splicing (AS) and alternative polyadenylation (APA) have emerged as tightly regulated processes playing a key role in generating transcriptome complexity and coordinating cell differentiation or tissue development. However, how these mechanisms imprint distinct functional characteristics on the resulting set of isoforms to define the observed phenotype remains poorly understood. The number of PTR variants and their resulting range of potentially functional consequences makes their functional validation an impractical task if done on a case-by-case basis. Besides, the lack of isoform-oriented functional profiling approaches has made that much of the computational work done to elucidate transcriptome-wide functional questions has either involved ad hoc computational pipelines applied to specific biological systems or has relied on simple GO-enrichment analysis that are not informative about the PTR impact on isoform properties. Thus, even though more than 60,000 publications on AS, a few number of existing isoforms have been associated with specific properties while the number of novel AS/APA variants with unknown and even unexplored functions is exponentially increasing thanks to the use of next-generation sequencing (NGS). Due to the technical limitations of NGS to reconstruct the transcript structure, high-throughput sequencing of full-length transcripts using third-generation technologies (TGS) is opening up a new transcriptomics era that enhances the definition of gene models and, for the first time, enables to precisely associate functional events within the RNA molecule. This thesis addresses three major challenges to the progression of the study of isoform function. First, with the emergence and increasing popularity of TGS, the accurate definition and comprehensive characterisation of de novo transcriptomes is essential to ensure the quality of any conclusions on transcriptome diversity drawn from these data. The lack of long-read oriented quality aware analysis motivated the development of SQANTI \url{(https://bitbucket.org/ConesaLab/sqanti)}, an automated pipeline for the structural characterization and quality assessment of full-length transcriptomes. Secondly, the gene-centric nature of functional resources remained the major limitation to the extended study of functional isoform variability, especially for novel isoforms, which cannot be characterised by static databases. Thus, we designed IsoAnnot, which dynamically constructs an isoform-resolved rich database of functional annotations by using as input transcript sequences and integrating information disseminated across several databases and prediction methods. Finally, because no methods to interrogate the functional impact of PTR were available, we developed novel approaches and user-friendly tools such as tappAS \url{(http://tappas.org/)}, designed to facilitate researchers the transcriptome-wide functional study of context-specific isoform regulation. Thereby, this thesis describes the development of an analysis framework that tackles the fundamental challenges of the isoform functional analysis by providing a set of novel methods and tools that offer an unique opportunity to explore how the phenotype is specified by altering the functional characteristics of expressed isoforms. Applied to a murine neural differentiation system, our pipeline profiled the effect of isoform regulation on the inclusion of several functional elements within transcripts between motor-neuron and oligodendrocyte differentiation systems and specifically, we discovered isoform-specific transmembrane regions whose modulation by PTR might contribute to control cell type-specific mitochondrial dynamics during neural fate determination. / This work was funded by the following grants: From 2014 to 2018. FPU: Training programme for Academic Staff. Spanish Ministry of Education, FPU2013/02348. From 2016 to 2019. NOVELSEQ: Novel methods for new challenges in the analysis of high-throughput sequencing data. MINECO, BIO2015-1658-R. From 2014 to 2017. DEANN: Developing a European American NGS Network. EU Marie Curie IRSES, GA-612583. / Fuente Lorente, LDL. (2019). Development of a bioinformatics approach for the functional analysis of alternative splicing [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/124974 / TESIS