Amphibian metamorphosis is facilitated solely by thyroid hormones (THs), L-thyroxine (T4) and 3,5,3’-triiodothyronine (T3). TH modulates the remodeling of many different organs and systems in the body of developing tadpoles, including the immune system. Previous research found evidence of T4 action on direct-response genes in outer ring deiodinase-poor premetamorphic tadpole tail fin and liver without the required conversion to T3 described by current TH dogma. The mechanisms of environmental endocrine disrupting chemicals (EDCs) may be better understood by expanding our understanding of the transcriptomic effects of both forms of THs and how they relate to estrogen signaling. Furthermore, analysis of TH-modulation of the immune system may enable a greater understanding of the devastating effects of amphibian pathogens such as Ranavirus. Premetamorphic Rana (Lithobates) catesbeiana tadpoles were exposed to physiological concentrations of T4, T3, or 17-beta-estradiol (E2) through water bath immersion. qPCR analysis was performed to assess the response of canonical TH-responsive genes thra, thrb, and thibz to these hormones in the liver and tail fin tissues of bullfrog tadpoles. E2 treatment did not elicit a response in these gene transcripts in either tissue. T3 treatment in the tail fin elicited an overall stronger response than T4, while T4 treatment in the liver recapitulated results consistent with non-genomic mechanisms of T4 signaling for thrb and thibz transcripts. Illumina Hiseq2500 was used to sequence RNA isolated from hormone-treated premetamorphic tadpole liver and tail fin tissues to assess differential transcriptomic responses and identify TH-responsive immune system-associated transcripts. The impact of TH-treatment on the general immune system in the liver and tail fin transcriptomes was also analyzed using RNA-seq data. We found that E2 modulates at least some shared TH pathways in the liver, but none in the tail fin and that the tail fin transcriptome is more affected by T3, while the liver transcriptome is more affected by T4. Additionally, evidence of immune system modulation by both THs was found in both the liver and tail fin transcriptomes. Antimicrobial peptides (AMPs) are an important component of the amphibian immune response. Details regarding the regulation, synthesis, and expression of AMPs remain obscure, although evidence of TH-modulation of specific AMPs has been identified, as well as evidence of increased expression of AMPs throughout metamorphosis. Frog skin is a prolific source of AMPs that may prove useful in the quest for alternative antimicrobial agents in the face of antibiotic resistance. Identification of new AMPs is hindered by the practical limitations of classical protein-based discovery approaches. By using known AMP characteristics and common ¬AMP properties, we developed a high throughput bioinformatics approach predicated on the use of R. catesbeiana genome resources. We mined these resources and identified novel and known AMPs that exhibited verified antimicrobial activity against various bacterial organisms. This thesis sought to elucidate the differential and modulatory effects of both forms of TH on a transcriptomic level and in the context of immunity, and to examine the utility of the bullfrog transcriptome and genomics resources in identifying and characterizing novel bullfrog-derived AMPs and elucidating aspects of AMP expression. / Graduate / 2018-12-08

Les mammites sont des inflammations de la mamelle provoquées principalement par des bactéries. Elles représentent un problème majeur en élevage laitier. Elles sont caractérisées par de fortes augmentations de la concentration des cellules somatiques (CCS) dans le lait. Le score des CCS (SCS) est fortement corrélé à la présence d'infections mammaires, ainsi il est utilisé en sélection pour améliorer la résistance aux mammites. Pour comprendre les mécanismes mis en place lors d'une sélection sur les SCS, deux lignées divergentes de brebis ont été produites à partir de géniteurs ayant des valeurs extrêmes de cet index. Le principal objectif de ce travail est d'identifier et de comprendre les mécanismes qui confèrent une plus grande résistance ou sensibilité aux mammites provoquées par des staphylocoques. Nos travaux ont porté principalement sur des analyses transcriptomiques de trois types cellulaires majeurs, après contact avec des staphylocoques : les cellules inflammatoires du lait recueillies après infection, principalement composées de neutrophiles, les cellules dendritiques, comme cellules présentatrices d'antigènes et les cellules épithéliales mammaires, première barrière de défense contre l'infection. Nous avons montré que la migration des cellules immunitaires et les processus inflammatoires se traduisent par des activations de voies différentes chez les brebis des deux lignées divergentes. Nous avons aussi identifié des gènes fonctionnels candidats pour expliquer la différence de sensibilité aux mammites. En parallèle, nous avons étudié l'association entre le polymorphisme de l'ADN et la présence d'abcès mammaires liés aux mammites dans un dispositif cas-contrôle visant à détecter des gènes à effet majeur. Les études ont permis de mettre en évidence une zone chromosomique d'intérêt située sur le chromosome OAR5. Les deux approches de génétique moléculaire (analyses du transcriptome et du polymorphisme du génome) ont permis d'identifier des gènes fonctionnels et positionnels candidats pour comprendre les mécanismes associés à la résistance aux mammites / Mastitis is udder inflammation. It is one of the major health issues in dairy cattle and sheep as they produce economic losses for the dairy industry. Mastitis is characterized by an increase in milk inflammatory somatic cells. The somatic cell score (SCS) is well correlated to clinical and subclinical mastitis. To enhance insights into the genetic mechanisms involved in such a selection on SCS, two divergent lines of sheep were generated based on extreme breeding values for SCS. The main objective of this work was to identify and improve the understanding of mechanisms that are responsible for a better resistance to Staphylococcus mastitis. Our study was based on transcriptomic analysis of three cell types after Staphylococcus contact: milk inflammatory cells, mainly composed of neutrophils, dendritic cells and mammary epithelial cells. We showed that immune cell migration and inflammatory processes were activated by different pathways in the two divergent lines. We also identified functional candidate genes that may partly explain the differences of mastitis susceptibility. In parallel, we analysed the association of DNA polymorphism with the presence of mammary abscesses caused by mastitis. The study highlighted a chromosomal region on OAR5 that is associated to the presence of mammary abscesses. Both approaches of molecular genetics as transcriptomics and genomics analyses enabled identification of candidate functional and positional genes for the better understanding of the mechanisms associated to mastitis resistance

Long intergenic non-coding RNAs (lincRNAs) are an abundant and functionally diverse class of eukaryotic transcripts. Reported lincRNA repertoires in mammals vary, but are commonly in the thousands to tens of thousands of transcripts, covering similar to 90% of the genome. In addition to elucidating function, there is particular interest in understanding the origin and evolution of lincRNAs. Aside from mammals, lincRNA populations have been sparsely sampled, precluding evolutionary analyses focused on their emergence and persistence. Here we present Evolinc, a two-module pipeline designed to facilitate lincRNA discovery and characterize aspects of lincRNA evolution. The first module (Evolinc-I) is a lincRNA identification workflow that also facilitates downstream differential expression analysis and genome browser visualization of identified lincRNAs. The second module (Evolinc-II) is a genomic and transcriptomic comparative analysis workflow that determines the phylogenetic depth to which a lincRNA locus is conserved within a user-defined group of related species. Here we validate lincRNA catalogs generated with Evolinc-I against previously annotated Arabidopsis and human lincRNA data. Evolinc-I recapitulated earlier findings and uncovered an additional 70 Arabidopsis and 43 human lincRNAs. We demonstrate the usefulness of Evolinc-II by examining the evolutionary histories of a public dataset of 5,361 Arabidopsis lincRNAs. We used Evolinc-II to winnow this dataset to 40 lincRNAs conserved across species in Brassicaceae. Finally, we show how Evolinc-II can be used to recover the evolutionary history of a known lincRNA, the human telomerase RNA (TERC). These latter analyses revealed unexpected duplication events as well as the loss and subsequent acquisition of a novel TERC locus in the lineage leading to mice and rats. The Evolinc pipeline is currently integrated in CyVerse's Discovery Environment and is free for use by researchers.

We established that acute adrenergic receptor stimulation in β-cells suppresses oxidative metabolism. This effect provides the basis for understanding how CAs reduce cell proliferation. Furthermore, the effects of acute CA on Min6 cells were distinguished from chronic CA culture using proteomics. Together, the RNAseq, qPCR and proteomic studies support a role for adrenergic receptor signaling in the regulation of proliferaton in β-cells. This work describes the genetic and proteomic profile underlying chronic adrenergic signaling and identifies CA independent suppression of β-cell growth and metabolism. Through the use of multiple models and comparative bioinformatics, we refined the list of molecular dysfunctions associated with the IUGR pathology to a set of specific and testable adrenergic targets.

[EN] Transcriptomics is one of the most important and relevant areas of bioinformatics. It allows detecting the genes that are expressed at a particular moment in time to explore the relation between genotype and phenotype. Transcriptomic analysis has been historically performed using microarrays until 2008 when high-throughput RNA sequencing (RNA-Seq) was launched on the market, replacing the old technique. However, despite the clear advantages over microarrays, it was necessary to understand factors such as the quality of the data, reproducibility and replicability of the analyses and potential biases. The first section of the thesis covers these studies. First, an R package called NOISeq was developed and published in the public repository "Bioconductor", which includes a set of tools to better understand the quality of RNA-Seq data, minimise the impact of noise in any posterior analyses and implements two new methodologies (NOISeq and NOISeqBio) to overcome the difficulties of comparing two different groups of samples (differential expression). Second, I show our contribution to the Sequencing Quality Control (SEQC) project, a continuation of the Microarray Quality Control (MAQC) project led by the US Food and Drug Administration (FDA, United States) that aims to assess the reproducibility and replicability of any RNA-Seq analysis. One of the most effective approaches to understand the different factors that influence the regulation of gene expression, such as the synergic effect of transcription factors, methylation events and chromatin accessibility, is the integration of transcriptomic with other omics data. To this aim, a file that contains the chromosomal position where the events take place is required. For this reason, in the second chapter, we present a new and easy to customise tool (RGmatch) to associate chromosomal positions to the exons, transcripts or genes that could regulate the events. Another aspect of great interest is the study of non-coding genes, especially long non-coding RNAs (lncRNAs). Not long ago, these regions were thought not to play a relevant role and were only considered as transcriptional noise. However, they represent a high percentage of the human genes and it was recently shown that they actually play an important role in gene regulation. Due to these motivations, in the last chapter we focus, first, in trying to find a methodology to find out the generic functions of every lncRNA using publicly available data and, second, we develop a new tool (spongeScan) to predict the lncRNAs that could be involved in the sequestration of micro-RNAs (miRNAs) and therefore altering their regulation task. / [ES] La transcriptómica es una de las áreas más importantes y destacadas en bioinformática, ya que permite ver qué genes están expresados en un momento dado para poder explorar la relación existente entre genotipo y fenotipo. El análisis transcriptómico se ha realizado históricamente mediante el uso de microarrays hasta que, en el año 2008, la secuenciación masiva de ARN (RNA-Seq) fue lanzada al mercado y comenzó a desplazar poco a poco su uso. Sin embargo, a pesar de las ventajas evidentes frente a los microarrays, resultaba necesario entender factores como la calidad de los datos, reproducibilidad y replicabilidad de los análisis así como los potenciales sesgos. La primera parte de la tesis aborda precisamente estos estudios. En primer lugar, se desarrolla un paquete de R llamado NOISeq, publicado en el repositorio público "Bioconductor", el cual incluye un conjunto de herramientas para entender la calidad de datos de RNA-Seq, herramientas de procesado para minimizar el impacto del ruido en posteriores análisis y dos nuevas metodologías (NOISeq y NOISeqBio) para abordar la problemática de la comparación entre dos grupos (expresión diferencial). Por otro lado, presento nuestra contribución al proyecto Sequencing Quality Control (SEQC), una continuación del proyecto Microarray Quality Control (MAQC) liderado por la US Food and Drug Administration (FDA) que pretende evaluar precisamente la reproducibilidad y replicabilidad de los análisis realizados sobre datos de RNA-Seq. Una de las estrategias más efectivas para entender los diferentes factores que influyen en la regulación de la expresión génica, como puede ser el efecto sinérgico de los factores de transcripción, eventos de metilación y accesibilidad de la cromatina, es la integración de la transcriptómica con otros datos ómicos. Para ello se necesita generar un fichero que indique las posiciones cromosómicas donde se producen estos eventos. Por este motivo, en el segundo capítulo de la tesis presentamos una nueva herramienta (RGmatch) altamente customizable que permite asociar estas posiciones cromosómicas a los posibles genes, transcritos o exones a los que podría estar regulando cada uno de estos eventos. Otro de los aspectos de gran interés en este campo es el estudio de los genes no codificantes, especialmente los ARN largos no codificantes (lncRNAs). Hasta no hace mucho, se pensaba que estos genes no jugaban ningún papel fundamental y se consideraban como simple ruido transcripcional. Sin embargo, suponen un alto porcentaje de los genes del ser humano y se ha demostrado que juegan un papel crucial en la regulación de otros genes. Por este motivo, en el último capítulo nos centramos, en un primer lugar, en intentar obtener una metodología que permita averiguar las funciones generales de cada lncRNA haciendo uso de datos ya publicados y, en segundo lugar, generamos una nueva herramienta (spongeScan) que permite predecir qué lncRNAs podrían estar secuestrando determinados micro-RNAs (miRNAs), alterando así la regulación llevada a cabo por estos últimos. / [CA] La transcriptòmica és una de les àrees més importants i destacades en bioinformàtica, ja que permet veure quins gens s'expressen en un moment donat per a poder explorar la relació existent entre genotip i fenotip. L'anàlisi transcriptòmic s'ha fet històricament per mitjà de l'ús de microarrays fins l'any 2008 quan la tècnica de seqüenciació massiva d'ARN (RNA-Seq) es va fer pública i va començar a desplaçar a poc a poc el seu ús. No obstant això, a pesar dels avantatges evidents enfront dels microarrays, resultava necessari entendre factors com la qualitat de les dades, reproducibilitat i replicabilitat dels anàlisis, així com els possibles caires introduïts. La primera part de la tesi aborda precisament estos estudis. En primer lloc, es va programar un paquet de R anomenat NOISeq publicat al repositori públic "Bioconductor", el qual inclou un conjunt d'eines per a entendre la qualitat de les dades de RNA-Seq, eines de processat per a minimitzar l'impact del soroll en anàlisis posteriors i dos noves metodologies (NOISeq i NOISeqBio) per a abordar la problemàtica de la comparació entre dos grups (expressió diferencial). D'altra banda, presente la nostra contribució al projecte Sequencing Quality Control (SEQC), una continuació del projecte Microarray Quality Control (MAQC) liderat per la US Food and Drug Administration (FDA) que pretén avaluar precisament la reproducibilitat i replicabilitat dels anàlisis realitzats sobre dades de RNA-Seq. Una de les estratègies més efectives per a entendre els diferents factors que influïxen a la regulació de l'expressió gènica, com pot ser l'efecte sinèrgic dels factors de transcripció, esdeveniments de metilació i accessibilitat de la cromatina, és la integració de la transcriptómica amb altres dades ómiques. Per això es necessita generar un fitxer que indique les posicions cromosòmiques on es produïxen aquests esdeveniments. Per aquest motiu, en el segon capítol de la tesi presentem una nova eina (RGmatch) altament customizable que permet associar aquestes posicions cromosòmiques als possibles gens, transcrits o exons als que podria estar regulant cada un d'aquests esdeveniments regulatoris. Altre dels aspectes de gran interés en aquest camp és l'estudi dels genes no codificants, especialment dels ARN llargs no codificants (lncRNAs). Fins no fa molt, encara es pensava que aquests gens no jugaven cap paper fonamental i es consideraven com a simple soroll transcripcional. No obstant això, suposen un alt percentatge dels gens de l'ésser humà i s'ha demostrat que juguen un paper crucial en la regulació d'altres gens. Per aquest motiu, en l'últim capítol ens centrem, en un primer lloc, en intentar obtenir una metodologia que permeta esbrinar les funcions generals de cada lncRNA fent ús de dades ja publicades i, en segon lloc, presentem una nova eina (spongeScan) que permet predeir quins lncRNAs podríen estar segrestant determinats micro-RNAs (miRNAs), alterant així la regulació duta a terme per aquests últims. / Furió Tarí, P. (2020). Development of bioinformatic tools for massive sequencing analysis [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/152485 / TESIS

The human gut microbiome is a vast ecosystem of microorganisms that play an important role in human metabolism, immunological function, and even inflammatory gut diseases. Metagenomics research on the human gut microbiome has demonstrated the presence of DNA from dietary yeast species like Saccharomyces cerevisiae. However, it is unknown if the S. cerevisiae detected in metagenomics studies is solely from dead dietary sources or if they can live and colonize the human gut like their close relative Candida albicans. While S. cerevisiae can adapt to low oxygen and acidic environments, it has yet to be explored whether it can metabolize mucin, the primary carbon source found in the mucus layer of the human gut. Mucins are large, gel-forming, highly glycosylated proteins that make up a majority of carbohydrate sources in the gut mucosa. This work determined that S. cerevisiae can utilize mucin as their main carbon source which results in a significant reduction in cell size. Additionally, an aspartyl protease named Yps7, part of a family containing known homologues to mucin-degrading C. albicans proteins in S. cerevisiae, is important for growth on mucin media. To further identify biological pathways required to grow optimally in mucin, both a transcriptome analysis on wild type cells (BY4743) and a chemogenomics screen was performed. In total, 2131 genes demonstrated significant differential expression in mucin media, and 30 genes upon their deletion impacted their growth on mucin. Both these screens suggest that mitochondrial function is required for proper growth in mucin, which was further elucidated by the change in mitochondrial morphology and oxygen consumption in yeast cells upon mucin treatment. Indeed, the uncharacterized open reading frame YCR095W-A is required for growth on mucin as the deletion mutant showed dysfunction in mitochondrial morphology and cellular respiration, further suggesting a potential role in mitochondrial function. Importantly, this project serves as the initial step towards establishing if our most common dietary fungus can survive in the mucus environment of the human gut.

High-throughput transcriptomic profiling has become a ubiquitous tool to assay an organism transcriptome and to characterize gene expression patterns in different cellular states or disease conditions, as well as in response to molecular and pharmacologic perturbations. Refinements to data preparation techniques have enabled integration of transcriptomic profiling into large-scale biomedical studies, generally devised to elucidate phenotypic factors contributing to transcriptional differences across a cohort of interest. Understanding these factors and the mechanisms through which they contribute to disease is a principal objective of numerous projects, such as The Cancer Genome Atlas and the Cancer Cell Line Encyclopedia. Additionally, transcriptomic profiling has been applied in toxicogenomic screening studies, which profile molecular responses of chemical perturbations in order to identify environmental toxicants and characterize their mechanisms-of-action. Further adoption of high-throughput transcriptomic profiling requires continued effort to improve and lower the costs of implementation. Accordingly, my dissertation work encompasses both the development and assessment of cost-effective RNA sequencing platforms, and of novel machine learning techniques applicable to the analyses of large-scale transcriptomic data sets. The utility of these techniques is evaluated through their application to a toxicogenomic screen in which our lab profiled exposures of adipocytes to metabolic disrupting chemicals. Such exposures have been implicated in metabolic dyshomeostasis, the predominant cause of obesity pathogenesis. Considering that an estimated 10% of the global population is obese, understanding the role these exposures play in disrupting metabolic balance has the potential to help combating this pervasive health threat. This dissertation consists of three sections. In the first section, I assess data generated by a highly-multiplexed RNA sequencing platform developed by our section, and report on its significantly better quality relative to similar platforms, and on its comparable quality to more expensive platforms. Next, I present the analysis of a toxicogenomic screen of metabolic disrupting compounds. This analysis crucially relied on novel supervised and unsupervised machine learning techniques which I specifically developed to take advantage of the experimental design we adopted for data generation. Lastly, I describe the further development, evaluation, and optimization of one of these methods, K2Taxonomer, into a computational tool for unsupervised molecular subgrouping of bulk and single-cell gene expression data, and for the comprehensive in-silico annotation of the discovered subgroups.

No description available.

We developed a spatially-tracked single neuron transcriptomics map of an intrinsic cardiac ganglion, the right atrial ganglionic plexus (RAGP) that is a critical mediator of sinoatrial node (SAN) activity. This 3D representation of RAGP used neuronal tracing to extensively map the spatial distribution of the subset of neurons that project to the SAN. RNA-seq of laser capture microdissected neurons revealed a distinct composition of RAGP neurons compared to the central nervous system and a surprising finding that cholinergic and catecholaminergic markers are coexpressed, suggesting multipotential phenotypes that can drive neuroplasticity within RAGP. High-throughput qPCR of hundreds of laser capture microdissected single neurons confirmed these findings and revealed a high dimensionality of neuromodulatory factors that contribute to dynamic control of the heart. Neuropeptide-receptor coexpression analysis revealed a combinatorial paracrine neuromodulatory network within RAGP informing follow-on studies on the vagal control of RAGP to regulate cardiac function in health and disease.

Corals are critical to marine biodiversity and human welfare. Coral reefs cover <1% of the seafloor but support ~1/3 of all marine species. Approximately 1.5 billion people live within 100 km of coral reefs, relying upon them for food, income from tourism, and protection from storms. Their economic value has been estimated at $375 billion annually. The foundation of coral reefs is the intracellular symbiosis between corals and photosynthetic dinoflagellates of the family Symbiodiniaceae. Tropical corals satisfy up to 95% of their nutritional requirements through photosynthesis, and their ability to construct reefs is biochemically coupled to photosynthesis. While permitting corals to thrive, photosymbiosis also increases their exposure to environmental stressors and vulnerability to climate change. Reliance on photosynthesis restricts reef-building corals to shallow, clear, tropical waters, where they experience higher temperatures and UV exposure. The generation of reactive oxygen species by the symbiont also exposes corals to greater oxidative stress. The symbiosis is particularly sensitive to climate change: all of the mass coral bleaching events have occurred since 1982, driven by elevated ocean temperatures. Molecular cross-talk between host and symbiont impacts resilience of the coral holobiont and resistance to bleaching. Unfortunately, we know little about how photosymbiosis impacts expression or activity of coral genes. Tropical corals engage in an obligate symbiosis with Symbiodiniaceae, so we cannot study their gene expression in a stable aposymbiotic state. However, the northern star coral, Astrangia poculata, engages in a facultative symbiosis with Symbiodiniaceae. I used RNA sequencing to investigate how symbiosis impacts gene expression in A. poculata, focusing on genes implicated in photosymbiosis: antioxidant enzymes (specifically superoxide dismutases) and the NF-κB signaling pathway. From an improved transcriptome assembly, I recovered core elements of a primitively simple NF-κB signaling pathway and a rich complement of SOD proteins. 273 coral transcripts—many associated with protein metabolism and vesicle-mediated transport— were differentially expressed in symbiotic versus aposymbiotic corals. Unlike in the facultatively symbiotic sea anemone Exaiptasia, symbiosis was not associated with depressed NF-κB transcript levels. IKKε, a potential positive regulator of NF-κB activity, was strongly up-regulated, as was one particular superoxide dismutase.