Cancer progression is accompanied with alterations in the cell biomechanical phenotype, including changes in cell structure, morphology, and responses to microenvironmental stress. These alterations result in an increased deformability of transformed cells and reduced resistance to mechanical stimuli, enabling motility and invasion. Therefore, single cell biomechanical properties could be served as a powerful label-free biomarker for effective characterization and early detection of single cancer cells. Advances and innovations in microsystems and nanotechnology have facilitated interrogation of the biomechanical properties of single cells to predict their tumorigenicity, metastatic potential, and health state. This dissertation utilized Atomic Force Microscopy (AFM) for the cell biomechanical phenotyping for cancer diagnosis and early detection, efficacy screening of potential chemotherapeutic agents, and also cancer stem-like/tumor initiating cells (CSC/TICs) characterization as the critical topics received intensive attention in the search for effective cancer treatment. Our findings demonstrated the capability of exogenous sphingosine to revert the aberrant biomechanics of aggressive cells and showed a unique, mechanically homogeneous, and extremely soft characteristic of CSC/TICs, suitable for their targeted isolation. To make full use of cell biomechanical cues, this dissertation also considered the application of nonlinear viscoelastic models such as Fractional Zener and Generalized Maxwell models for the naturally complex, heterogeneous, and nonlinear structure of living cells. The emerging need for a high-throughput clinically relevant alternative for evaluating biomechanics of individual cells led us to the development of a microfluidic system. Therefore, a high-throughput, label-free, automated microfluidic chip was developed to investigate the biophysical (biomechanical-bioelectrical) markers of normal and malignant cells. Most importantly, this dissertation also explored the biomechanical response of cells upon a dynamic loading instead of a typical transient stress. Notably, metastatic and non-metastatic cells subjected to a pulsed stress regimen exerted by AFM exhibited distinct biomechanical responses. While non-metastatic cells showed an increase in their resistance against deformation and resulted in strain-stiffening behavior, metastatic cells responded by losing their resistance and yielded slight strain-softening. Ultimately, a second generation microfluidic chip called an iterative mechanical characteristics (iMECH) analyzer consisting of a series of constriction channels for simulating the dynamic stress paradigm was developed which could reproduce the same stiffening/softening trends of non-metastatic and metastatic cells, respectively. Therefore, for the first time, the use of dynamic loading paradigm to evaluate cell biomechanical responses was used as a new signature to predict malignancy or normalcy at a single-cell level with a high (~95%) confidence level. / Ph. D.

Bioimpedance presents a versatile, label-free means of monitoring biological cells and their responses to physical, chemical and biological stimuli. Breast cancer is the second most common type of cancer among women in the United States. Although significant progress has been made in diagnosis and treatment of this disease, there is a need for robust, easy-to-use technologies that can be used for the identification and discrimination of critical subtypes of breast cancer in biopsies obtained from patients. This dissertation makes contributions in three major areas towards addressing the goal. First, we developed miniaturized bioimpedance sensors using MEMS and microfluidics technology that have the requisite traits for clinical use including reliability, ease-of-use, low-cost and disposability. Here, we designed and fabricated two types of bioimpedance sensors. One was based on electric cell-substrate impedance sensing (ECIS) to monitor cell adhesion based events and the other was a microfluidic device with integrated microelectrodes to examine the biophysical properties of single cells. Second, we examined a panel of triple negative breast cancer (TNBC) cell lines and a hormone therapy resistant model of breast cancer in order to improve our understanding of the bioimpedance spectra of breast cancer subtypes. Third, we explored strategies to improve the sensitivity of the microelectrodes to bioimpedance measurements from breast cancer cells. We investigated nano-scale coatings on the surface of the electrode and geometrical variations in a branched electrode design to accomplish this. This work demonstrates the promise of bioimpedance technologies in monitoring diseased cells and their responses to pharmaceutical agents, and motivates further research in customization of this technique for use in personalized medicine. / Ph. D.

Gene expression regulation is dynamic and specific to various factors such as developmental stages, environmental conditions, and stimulation of pathogens. Nowadays, a tremendous amount of transcriptome data sets are available from diverse species. This trend enables us to perform comparative transcriptome analysis that identifies conserved or diverged gene expression responses across species using transcriptome data. The goal of this dissertation is to develop and apply approaches of comparative transcriptomics to transfer knowledge from model species to non-model species with the hope that such an approach can contribute to the improvement of crop yield and human health. First, we presented a comprehensive method to identify cross-species modules between two plant species. We adapted the unsupervised network-based module finding method to identify conserved patterns of co-expression and functional conservation between Arabidopsis, a model species, and soybean, a crop species. Second, we compared drought-responsive genes across Arabidopsis, soybean, rice, corn, and Populus in order to explore the genomic characteristics that are conserved under drought stress across species. We identified hundreds of common gene families and conserved regulatory motifs between monocots and dicots. We also presented a BLS-based clustering method which takes into account evolutionary relationships among species to identify conserved co-expression genes. Last, we analyzed single-cell RNA-seq data from monocytes to attempt to understand regulatory mechanism of innate immune system under low-grade inflammation. We identified novel subpopulations of cells treated with lipopolysaccharide (LPS), that show distinct expression patterns from pro-inflammatory genes. The data revealed that a promising therapeutic reagent, sodium 4-phenylbutyrate, masked the effect of LPS. We inferred the existence of specific cellular transitions under different treatments and prioritized important motifs that modulate the transitions using feature selection by a random forest method. There has been a transition in genomics research from bulk RNA-seq to single-cell RNA-seq, and scRNA-seq has become a widely used approach for transcriptome analysis. With the experience we gained by analyzing scRNA-seq data, we plan to conduct comparative single-cell transcriptome analysis across multiple species. / Doctor of Philosophy / All cells in an organism have the same set of genes, but there are different cell types, tissues, organs with different functions as the organism ages or under different conditions. Gene expression regulation is one mechanism that modulates complex, dynamic, and specific changes in tissues or cell types for any living organisms. Understanding gene regulation is of fundamental importance in biology. With the rapid advancement of sequencing technologies, there is a tremendous amount of gene expression data (transcriptome) from individual species in public repositories. However, major studies have been reported from several model species and research on non-model species have relied on comparison results with a few model species. Comparative transcriptome analysis across species will help us to transform knowledge from model species to non-model species and such knowledge transfer can contribute to the improvement of crop yields and human health. The focus of my dissertation is to develop and apply approaches for comparative transcriptome analysis that can help us better understand what makes each species unique or special, and what kinds of common functions across species have been passed down from ancestors (evolutionarily conserved functions). Three research chapters are presented in this dissertation. First, we developed a method to identify groups of genes that are commonly co-expressed in two species. We chose seed development data from soybean with the hope to contribute to crop improvement. Second, we compared gene expression data across five plant species including soybean, rice, and corn to provide new perspectives about crop plants. We chose drought stress to identify conserved functions and regulatory factors across species since drought stress is one of the major stresses that negatively impact agricultural production. We also proposed a method that groups genes with evolutionary relationships from an unlimited number of species. Third, we analyzed single-cell RNA-seq data from mouse monocytes to understand the regulatory mechanism of the innate immune system under low-grade inflammation. We observed how innate immune cells respond to inflammation that could cause no symptoms but persist for a long period of time. Also, we reported an effect of a promising therapeutic reagent (sodium 4-phenylbutyrate) on chronic inflammatory diseases. The third project will be extended to comparative single-cell transcriptome analysis with multiple species.

[ES] La introducción de la secuenciación de ARN a nivel de célula única (scRNA-seq) en el ámbito de la transcriptómica ha redefinido nuestro entendimiento de la diversidad celular, arrojando luz sobre los mecanismos subyacentes a la heterogeneidad tisular. No obstante, al inicio de esta tesis, las limitaciones de a esta tecnología obstaculizaban su aplicación en el estudio de procesos complejos, entre ellos el splicing alternativo. A pesar de ello, los patrones de splicing a nivel celular planteaban incógnitas que esta tecnología tenía el potencial de resolver: ¿es posible observar, a nivel celular, la misma diversidad de isoformas que se detecta mediante RNA-seq a nivel de tejido? ¿Qué función desempeñan las isoformas alternativas en la constitución de la identidad celular? El objetivo de esta tesis es desbloquear el potencial del scRNA-seq para el análisis de isoformas, abordando sus dificultades técnicas y analíticas mediante el desarrollo de nuevas metodologías computacionales. Para lograrlo, se trazó una hoja de ruta con tres objetivos. Primero, se establecieron cuatro requisitos para el estudio de las isoformas mediante scRNA-seq, llevando a cabo una revisión de la literatura existente para evaluar su cumplimiento. Tras completar este marco con simulaciones computacionales, se identificaron las debilidades y fortalezas de los métodos de scRNA-seq y las herramientas computacionales disponibles. Durante la segunda etapa de la investigación, estos conocimientos se utilizaron para diseñar un protocolo óptimo de procesamiento de datos de scRNA-seq. En concreto, se integraron datos de lecturas largas a nivel de tejido con datos de scRNA-seq para garantizar una identificación adecuada de las isoformas así como su cuantificación a nivel celular. Este proceso permitió ampliar las estrategias computacionales disponibles para la reconstrucción de transcriptomas a partir de lecturas largas, mejoras que fueron implementadas en SQANTI3, software de referencia en transcriptómica. Por último, los datos procesados se utilizaron para desarrollar un nuevo método de análisis de co-expresión de isoformas a fin de desentrañar redes de regulación del splicing alternativo implicadas en la constitución de la identidad celular. Dada la elevada variabilidad de los datos de scRNA-seq, este método se basa en la utilización de una estrategia de correlación basada en percentiles que atenúa el ruido técnico y permite la identificación de grupos de isoformas co-expresadas. Una vez configurada la red de co-expresión, se introdujo una nueva estrategia de análisis para la detección de patrones de co-utilización de isoformas que suceden de forma independiente a la expresión a nivel de gen, denominada co-Differential Isoform Usage. Este enfoque facilita la identificación de una capa de regulación de la identidad celular atribuible únicamente a mecanismos post-transcripcionales. Para una interpretación biológica más profunda, se aplicó una estrategia de anotación computacional de motivos y dominios funcionales en las isoformas definidas con lecturas largas, revelando las propiedades biológicas de las isoformas involucradas en la red de co-expresión. Estas investigaciones culminan en el lanzamiento de acorde, un paquete de R que encapsula las diferentes metodologías desarrolladas en esta tesis, potenciando la reproducibilidad de sus resultados y proporcionando una nueva herramienta para explorar la biología de las isoformas alternativas a nivel de célula única. En resumen, esta tesis describe una serie de esfuerzos destinados a desbloquear el potencial de los datos de scRNA-seq para avanzar en la comprensión del splicing alternativo. Desde un contexto de escasez de herramientas y conocimiento previo, se han desarrollado soluciones de análisis innovadoras que permiten la aplicación de scRNA-seq al estudio de las isoformas alternativas, proporcionando recursos innovadores para profundizar en la regulación post-transcripcional y la función celular. / [CA] La introducció de la seqüenciació d'ARN a escala de cèl·lula única (scRNA-seq) en l'àmbit de la transcriptòmica ha redefinit el nostre enteniment de la diversitat cel·lular, projectant llum sobre els mecanismes subjacents a l'heterogeneïtat tissular. Malgrat les limitacions inicials d'aquesta tecnologia, especialment en el context de processos complexos com l'splicing alternatiu, els patrons d'splicing a escala cel·lular plantejaven incògnites amb potencial de resolució: és possible observar, a escala cel·lular, la mateixa diversitat d'isoformes que es detecta mitjançant RNA-seq en teixits? Quina funció tenen les isoformes alternatives en la constitució de la identitat cel·lular? L'objectiu d'aquesta tesi és desbloquejar el potencial del scRNA-seq per a l'anàlisi d'isoformes alternatives, abordant les seues dificultats tècniques i analítiques amb noves metodologies computacionals. Per a això, es va traçar una ruta amb tres objectius. Primerament, es van establir quatre requisits per a l'estudi de les isoformes mitjançant scRNA-seq, amb una revisió de la literatura existent per avaluar-ne el compliment. Després de completar aquest marc amb simulacions computacionals, es van identificar les debilitats i fortaleses dels mètodes de scRNA-seq i de les eines computacionals disponibles. Durant la segona etapa de la investigació, aquests coneixements es van utilitzar per dissenyar un protocol òptim de processament de dades de scRNA-seq. En concret, es van integrar dades de lectures llargues a escala de teixit amb dades de scRNA-seq per a garantir una identificació adequada de les isoformes així com la seua quantificació a escala cel·lular. Aquest procés va permetre ampliar les estratègies computacionals disponibles per a la reconstrucció de transcriptomes a partir de lectures llargues, millores que van ser implementades en SQANTI3, un programari de referència en transcriptòmica. Finalment, les dades processades es van fer servir per a desenvolupar un nou mètode d'anàlisi de coexpressió d'isoformes amb l'objectiu de desentranyar xarxes de regulació de l'splicing alternatiu implicades en la constitució de la identitat cel·lular. Donada l'elevada variabilitat de les dades de scRNA-seq, aquest mètode es basa en la utilització d'una estratègia de correlació basada en percentils que minimitza el soroll tècnic i permet la identificació de grups d'isoformes coexpressades. Un cop configurada la xarxa de coexpressió, es va introduir una nova estratègia d'anàlisi per a la detecció de patrons de co-utilització d'isoformes que succeeixen de forma independent a l'expressió del seu gen, denominada co-Differential Isoform Usage. Aquest enfocament facilita la identificació d'una capa de regulació de la identitat cel·lular atribuïble únicament a mecanismes post-transcripcionals. Per a una interpretació biològica més profunda, es va aplicar una estratègia d'anotació computacional de motius i dominis funcionals en les isoformes definides amb lectures llargues, revelant les propietats biològiques de les isoformes involucrades en la xarxa de coexpressió. Aquestes investigacions culminen en el llançament d'acorde, un paquet de R que encapsula les diferents metodologies desenvolupades en aquesta tesi, potenciant la reproducibilitat dels seus resultats i proporcionant una nova eina per a explorar la biologia de les isoformes alternatives a escala de cèl·lula única. En resum, aquesta tesi descriu una sèrie d'esforços destinats a desbloquejar el potencial de les dades de scRNA-seq per a avançar en la comprensió de l'splicing alternatiu. Des d'un context de manca d'eines i coneixement previ, s'han desenvolupat solucions d'anàlisi innovadores que permeten l'aplicació de scRNA-seq a l'estudi de les isoformes alternatives, proporcionant recursos innovadors per a aprofundir en la regulació post-transcripcional i la funció cel·lular. / [EN] In the world of transcriptomics, the emergence of single-cell RNA sequencing (scRNA-seq) ignited a revolution in our understanding of cellular diversity, unraveling novel mechanisms in tissue heterogeneity, development and disease. However, when this thesis began, using scRNA-seq to understand Alternative Splicing (AS) was a challenging frontier due the inherent limitations of the technology. In spite of this research gap, pertinent questions persisted regarding cell-level AS patterns, particularly concerning the recapitulation of isoform diversity observed in bulk RNA-seq data at the cellular level and the roles played by cell and cell type-specific isoforms. The work conducted in the present thesis aims to harness the potential of scRNA-seq for alternative isoform analysis, outlining technical and analytical challenges and designing computational methods to overcome them. To achieve this, we established a roadmap with three main aims. First, we set requirements for studying isoforms using scRNA-seq and conducted an extensive review of existing research, interrogating whether these requirements were met. Combining this acquired knowledge with several computational simulations allowed us to delineate the strengths and pitfalls of available data generation methods and computational tools. During the second research stage, this insight was used to design a suitable data processing pipeline, in which we jointly employed bulk long-read and short-read scRNA-seq sequenced from full-length cDNAs to ensure adequate isoform reconstruction as well as sensitive cell-level isoform quantification. Additionally, we refined available transcriptome curation strategies, introducing them as innovative modules in the transcriptome quality control software SQANTI3. Lastly, we harnessed single-cell isoform expression data and the rich biological diversity inherent in scRNA-seq, encompassing various cell types, in the design of a novel isoform co-expression analysis method. Percentile correlations effectively mitigated single-cell noise, unveiling clusters of co-expressed isoforms and exposing a layer of regulation in cellular identity that operated independently of gene expression. We additionally introduced co-Differential Isoform Usage (coDIU) analysis, enhancing our ability to interpret isoform cluster networks. This endeavour, combined with the computational annotation of functional sites and domains in the long read-defined isoform models, unearthed a distinctive functional signature in coDIU genes. This research effort materialized in the release of acorde, an R package that encapsulates all analyses functionalities developed throughout this thesis, providing a reproducible means for the scientific community to further explore the depths of alternative isoform biology within single-cell transcriptomics. This thesis describes a complex journey aimed at unlocking the potential of scRNA-seq data for investigating AS and isoforms: from a landscape marked by the scarcity of tools and guidelines, towards the development of novel analysis solutions and the acquisition of valuable biological insight. In a swiftly evolving field, our methodological contributions constitute a significant leap forward in the application of scRNA-seq to the study of alternative isoform expression, providing innovative resources for delving deeper into the intricacies of post-transcriptional regulation and cellular function through the lens of single-cell transcriptomics. / The research project was funded by the BIO2015-71658 and BES-2016-076994 grants awarded by the Spanish Ministry of Science and Innovation / Arzalluz Luque, Á. (2024). Understanding Isoform Expression and Alternative Splicing Biology through Single-Cell RNAseq [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/203888

Fluid suspended biological particles (bioparticles) flowing through a non-uniform electric field are actuated by the induced dielectrophoretic (DEP) force, known to be dependent upon the bioparticles’ dielectric phenotypes. In this work: a 10-1000 kHz DEP actuation potential applied to a co-planar microelectrode array (MEA) induces a DEP force, altering passing bioparticle trajectories as monitored using: (1) an optical assay, in which the lateral bioparticle velocities are estimated from digital video; and (2) a capacitive cytometer, in which a 1.478 GHz capacitance sensor measures the MEA capacitance perturbations induced by passing bioparticles, which is sensitive to the bioparticles’ elevations. The experimentally observed and simulated lateral velocity profiles of actuated polystyrene microspheres (PSS) and viable and heat shocked Saccharomyces cerevisiae cells verify that the bioparticles’ dielectric phenotypes can be inferred from the resultant trajectories due to the balance between the DEP force and the viscous fluid drag force.

Fluid suspended biological particles (bioparticles) flowing through a non-uniform electric field are actuated by the induced dielectrophoretic (DEP) force, known to be dependent upon the bioparticles’ dielectric phenotypes. In this work: a 10-1000 kHz DEP actuation potential applied to a co-planar microelectrode array (MEA) induces a DEP force, altering passing bioparticle trajectories as monitored using: (1) an optical assay, in which the lateral bioparticle velocities are estimated from digital video; and (2) a capacitive cytometer, in which a 1.478 GHz capacitance sensor measures the MEA capacitance perturbations induced by passing bioparticles, which is sensitive to the bioparticles’ elevations. The experimentally observed and simulated lateral velocity profiles of actuated polystyrene microspheres (PSS) and viable and heat shocked Saccharomyces cerevisiae cells verify that the bioparticles’ dielectric phenotypes can be inferred from the resultant trajectories due to the balance between the DEP force and the viscous fluid drag force.

No description available.

Ziel dieser Doktorarbeit ist eine umfassende Untersuchung der Heterogenität von Mikroglia aus morphologischer, elektrophysiologischer und transkriptioneller Perspektive mit dem Schwerpunkt auf Unterschiede zwischen weißer und grauer Substanz. Im ersten Kapitel diskutiere ich die morphologische Heterogenität von Mikroglia mit dem Fokus auf Satelliten- und Parenchymale-Mikroglia. Wir führten eine eingehende Analyse mehrerer Hirnareale durch und quantifizierten die Anzahl der Satellitenmikroglia, die mit verschiedenen neuronalen Subtypen in Kontakt stehen. Wir fanden heraus, dass die Anzahl der Satellitenmikroglia stark mit der neuronalen Dichte eines bestimmten Bereichs korreliert. Im zweiten Kapitel dieser Arbeit untersuche ich die transkriptionelle Heterogenität von Mikroglia aus weißer und grauer Substanz, wobei ich die in Gliazellen neu etablierte Patch-seq-Methode anwende. Diese Methode ermöglicht es eine Kombination aus morphologischen, lektrophysiologischen und transkriptionellen Profilen einzelner Zellen zu erhalten, die es erlauben, zelluläre Unterschiede zu charakterisieren. Wir identifizieren einen zellulären Subtyp, wenn wir den Patch-seq-Datensatz mit FACS-basierter Einzelzell-RNA-seq-Datensätzen vergleichen. Dieser Subtyp gehört eindeutig zu dissoziierten Gewebeproben und ist durch die Expression von Stress-assoziierten Genen charakterisiert. Im dritten Kapitel wende ich mich der Frage zu, wie Transkripte mittels SLAM-seq nachverfolgt werden können, die während der Dissoziation des Gewebes entstehen. Das Verfahren ermöglicht es mRNA, die während der Dissoziation der Probe entsteht, metabolisch zu markieren, rechnerisch zu identifizieren und zu entfernen. Indem wir die markierten Transkripte aus dem Mikroglia “entfernen”, beobachten wir, dass ein „aktivierter Mikroglia“-Subtyp zur allgemeinen Mikroglia-Population gehört. / The aim of this doctoral work is to provide a comprehensive study and overview on the topic of the heterogeneity of microglia in the normal adult mouse brain from the morphological, electrophysiological and transcriptional perspective with the focus on differences between white and grey matters. In the first Chapter, I discuss the morphological heterogeneity of microglia in the brain with the focus on two morphologically distinct classes: satellite and parenchymal microglia. We performed an in-depth analysis of multiple brain areas and quantified the number of satellite microglia which is in contact with different neuronal subtypes. We found that satellite microglia numbers are highly correlated with neuronal densities of a certain area, while showing no preferences for any of the neuronal types. In Chapter two of this work, I study transcriptional heterogeneity of microglia from white and grey matters. For this I am employing Patch-seq, which we newly established in glial cells. This method allows a combination of morphological, electrophysiological and transcriptional profiles of single cells to assess their differences. When comparing Patch-seq dataset to the previously published FACS isolated single cell RNA-seq microglia datasets, we find a subtype of cells which uniquely belongs to FACS sample and is characterized by expression of stress-associated genes. This finding points out to the fact of dissociation-related artifacts in the single cell RNA-seq data which are not present in situ. In the third chapter, I identified transcripts which are induced during the dissociation of the tissue by employing the SLAM-seq method. This procedure allows to metabolically label newly transcribed mRNA and computationally remove transcripts from the sample. By removing the labeled transcripts from the dataset of cells isolated from the hippocampus via enzymatic dissociation, we observe that an “activated microglia” subtype merges with the general microglia population.

Transkription är stokastisk, där utbrottsmässiga episoder av RNA-transkription genererar RNA-molekyler. Trots att detta är en kärndel av eukaryotiskt liv, är lite känt om hur DNA-bindande transkriptionsfaktorer och transkriptionella kofaktorer formar gen-specifik transkriptionell utbrottskinetik. Syftet med detta examensarbete var att tyda rollerna hos kofaktorerna Med14 och P300/CBP inom transkriptionell utbrottskinetik. För detta ändamål användes Auxin inducible degron systemet för snabb nedbrytning av Med14 eller P300/CBP-proteiner i HCT116-celler, följt av Smart-seq3xpress single cell-RNA-sekvensering. Ett särskild fokus i denna avhandling var även att utvärdera förmågan att härleda direkta  genuttrycksförändringar genom analys av introniska reads – detta då introner ko-transkriptionellt splitsas och dess nyttjande skulle fånga effekter av mycket närliggande transkription. Resultaten visar en tidsberoende minskning av introniskt innehåll och en nedreglering av genuttryck för majoriteten av generna i de behandlade cellinjerna, medan opåverkade kontroller inte visar sådana trender. Utbrottskinetikresultaten indikerar att det inte finns någon korrelation mellan P300/CBP-pertuberade cellers geners ursprungliga utbrottsstorlek och några trender i genuttryckets relativa förändring, medan detsamma kan sägas för Med14-pertuberade cellers geners utbrottsfrekvens. Svaga trender från P300/CBP-påverkade cellers utbrottskinetik och uttrycksändring kan antyda att deras utbrottsfrekvens och inte utbrottsstorlek har påverkats. Resultaten antyder att perturbationen var framgångsrik och att P300/CBP inte påverkar utbrottsstorlek samt att Med14 kan reglera utbrottsfrekvensen för alla påverkade gener i lika hög grad. Vidare forskning behövs inom utbrottskinetikdata för att utöka vår förståelse av denna studies implikationer gällande Med14:s och P300/CBP:s reglerande roller på transkriptionella utbrott. / Transcription is stochastic with episodes of RNA transcription generating bursts of RNA molecules. Despite being a core part of eukaryotic life, little is known about how DNA-binding transcription factors and transcriptional co-factors shape gene-specific transcriptional bursting kinetics. The aim of this thesis was to decipher the roles of the co-factors Med14 and P300/CBP in transcriptional burst kinetics. To this end, the Auxin inducible degron system was used for rapid Med14 or P300/CBP protein degradation in HCT116 cells, followed by Smart-seq3xpress single-cell RNA-sequencing. A particular focus of this thesis was to evaluate the abilities to infer direct gene expression changes by analysis of intronic reads – since introns are co-transcriptionally spliced and would capture very recent transcription. Results show a time dependent decrease of intronic contents and a downregulation in gene expression for a majority of genes in the perturbed cell lines, while unperturbed controls show no such trends. Bursting kinetics results indicate that there is no correlation between P300/CBP perturbed cells’ gene’s original bursting size and any trends in gene expression fold change while the same can be said for Med14 perturbed cell’s gene’s burst frequency. Weak trends from P300/CBP perturbed cells’ bursting kinetics and expression fold change could imply that their bursting frequency and not bursting size has been affected. The results imply that the perturbation was successful and that P300/CBP does not affect bursting size as well as that Med14 could regulate bursting frequency for all affected genes to an equal degree. Further research is needed into the bursting kinetics data to expand our understanding of this study’s implications regarding regulatory roles of Med14 and P300/CBP on transcriptional bursting.

Preimplantation genetic diagnosis (PGD) refers to the testing of embryos produced through in vitro fertilization (IVF) in order to identify those unaffected by a specific genetic disorder or chromosomal abnormality. In this study, different methodologies were examined and developed for performance of PGD. Investigation of various whole genome amplification (WGA) methods identified multiple displacement amplification as a reliable method for genotyping single cells. Furthermore, this technology was shown to be compatible with subsequent analysis using single nucleotide polymorphism (SNP) microarrays. Compared to conventional methods used in this study to perform single cell diagnosis (e.g. multiplex PCR), WGA techniques were found to be advantageous since they streamline the development of PGD protocols for couples at high risk of transmitting an inherited disorder and simultaneously offer the possibility of comprehensive chromosome screening (CCS). This study also aimed to develop a widely applicable protocol for accurate typing of the human leukocyte antigen (HLA) region with the purpose of identifying embryos that will be HLA-identical to an existing sibling affected by a disorder that requires haematopoietic stem cell transplantation. Additionally, a novel microarray platform was developed that, apart from accurate CCS, was capable of reliably determining the relative quantity of mitochondrial DNA in polar bodies removed from oocytes and single cells biopsied from embryos. Mitochondria are known to play an important role in oogenesis and preimplantation embryogenesis and their measurement may therefore be of clinical relevance. Moreover, real-time PCR was used for development of protocols for CCS, DNA fingerprinting of sperm samples and embryos and the relative quantitation of telomere length in embryos (since shortened telomeres might be associated with reduced viability). As well as considering the role of genetics in terms of oocyte and embryo viability assessment and the diagnosis of inherited genetic disorders, attention was given to a specific gene (Phospholipase C zeta) of relevance to male infertility. A novel mutation affecting the function of the resulting protein was discovered highlighting the growing importance of DNA sequence variants in the diagnosis and treatment of infertility.