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Johnson, Travis Steele. "Integrative approaches to single cell RNA sequencing analysis." The Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1586960661272666.
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Borgström, Erik. "Technologies for Single Cell Genome Analysis." Doctoral thesis, KTH, Genteknologi, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-181059.
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During the last decade high throughput DNA sequencing of single cells has evolved from an idea to one of the most high profile fields of research. Much of this development has been possible due to the dramatic reduction in costs for massively parallel sequencing. The four papers included in this thesis describe or evaluate technological advancements for high throughput DNA sequencing of single cells and single molecules. As the sequencing technologies improve, more samples are analyzed in parallel. In paper 1, an automated procedure for preparation of samples prior to massively parallel sequencing is presented. The method has been applied to several projects and further development by others has enabled even higher sample throughputs. Amplification of single cell genomes is a prerequisite for sequence analysis. Paper 2 evaluates four commercially available kits for whole genome amplification of single cells. The results show that coverage of the genome differs significantly among the protocols and as expected this has impact on the downstream analysis. In Paper 3, single cell genotyping by exome sequencing is used to confirm the presence of fat cells derived from donated bone marrow within the recipients’ fat tissue. Close to hundred single cells were exome sequenced and a subset was validated by whole genome sequencing. In the last paper, a new method for phasing (i.e. determining the physical connection of variant alleles) is presented. The method barcodes amplicons from single molecules in emulsion droplets. The barcodes can then be used to determine which variants were present on the same original DNA molecule. The method is applied to two variable regions in the bacterial 16S gene in a metagenomic sample. Thus, two of the papers (1 and 4) present development of new methods for increasing the throughput and information content of data from massively parallel sequencing. Paper 2 evaluates and compares currently available methods and in paper 3, a biological question is answered using some of these tools.QC 20160127
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La, Forest Divonne Sébastien De. "Caractérisation constitutive et en condition d'infection bactérienne des populations hémocytaires par une approche intégrative cytologiques, transcriptomiques et fonctionnelles chez l'huitre creuse Crassostrea (Magallana) gigas." Electronic Thesis or Diss., Perpignan, 2024. http://www.theses.fr/2024PERP0025.
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L'huître du Pacifique, Crassostrea (Magallana) gigas, est un mollusque bivalve d'une importance écologique et économique majeure, et constitue désormais une espèce modèle émergente dans l'étude de l'immunité innée des bivalves. Ces dernières années, les élevages d'huîtres ont été confrontés à des épisodes de mortalités massives, exacerbés par le changement climatique et les activités anthropiques. Ces mortalités, bien que multifactorielles, partagent un point commun : la capacité des pathogènes (virus et bactéries) à échapper aux défenses immunitaires des huîtres, entraînant des septicémies souvent fatales. Alors que chez les vertébrés, et particulièrement l'Homme, les cellules immunitaires sont bien caractérisées, la diversité et la spécialisation fonctionnelle des hémocytes chez C. gigas restent encore une boite noire apprement débattue au sein de la communauté scientifique. Ce manque de connaissances entrave la compréhension des interactions hôte-pathogènes, limitant ainsi le développement de stratégies pour réduire les mortalités en ostréiculture. Dans ce contexte, l'objectif principal de mon projet de thèse a été de caractériser les types hémocytaires circulants de C. gigas, en utilisant des approches cytologiques, fonctionnelles et de transcriptomique sur cellules uniques (scRNA-seq). Ces méthodes ont permis dans un premier temps d'identifier sept types hémocytaires distincts constitutifs chez les animaux naifs. Ces populations hémocytaires ont été caractérisées par leurs propriétés morphologiques, leurs profils d'expression génique et leurs fonctions biologiques spécifiques. De plus, nous avons établi une ontologie des hémocytes, suggérant des voies potentielles de différenciation des lignages cellulaires. Grâce à cet atlas hémocytaire, nous avons alors pu évaluer l'impact différentiel d'une infection par Vibrio aestuarianus sur les populations hémocytaires, à la fois du point de vue cytologique et transcriptomique, révélant des altérations dépendantes de la charge bactérienne circulante. Ces travaux apportent une contribution significative à la compréhension de l'immunité chez C. gigas, en permettant une définition précise des types hémocytaires. Nos résultats proposent un atlas hémocytaire de référence et soulignent l'importance de l'étude de l'homéostasie hémocytaire des mollusques pour mieux comprendre et anticiper les crises ostréicoles lors d'épisodes de mortalitéThe Pacific oyster, Crassostrea (Magallana) gigas, is a bivalve mollusk of significant ecological and economic importance, and it has recently emerged as a model species for studying the innate immunity of bivalves. In recent years, oyster farming has been confronted with episodes of massive mortality, exacerbated by climate change and human activities. These mortalities, though multifactorial, share a common factor: the ability of pathogens (viruses and bacteria) to evade the oysters' immune defenses, often leading to fatal septicemia. While immune cells in vertebrates, particularly humans, are well characterized, the diversity and functional specialization of hemocytes in C. gigas remain a black box and are hotly debated within the scientific community. This knowledge gap hampers our understanding of host-pathogen interactions, thus limiting the development of strategies to reduce oyster mortality in aquaculture. In this context, the main objective of my thesis project was to characterize the circulating hemocyte types in C. gigas using cytological, functional, and single-cell transcriptomic approaches (scRNA-seq). These methods first allowed us to identify seven distinct constitutive hemocyte types in naïve animals. These hemocyte populations were characterized based on their morphological properties, gene expression profiles, and specific biological functions. Furthermore, we established a hemocyte ontology, suggesting potential differentiation pathways for the cell lineages. Using this hemocyte atlas, we then assessed the differential impact of Vibrio aestuarianus infection on hemocyte populations, both from a cytological and transcriptomic perspective, revealing alterations dependent on the circulating bacterial load. This work provides a significant contribution to the understanding of immunity in C. gigas, by offering a precise definition of hemocyte types. Our results propose a reference hemocyte atlas and emphasize the importance of studying hemocyte homeostasis in mollusks to better understand and anticipate oyster mortality crises during epizootic episodes
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Raoux, Corentin. "Review and Analysis of single-cell RNA sequencing cell-type identification and annotation tools." Thesis, KTH, Skolan för kemi, bioteknologi och hälsa (CBH), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-297852.
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Single-cell RNA-sequencing makes possible to study the gene expression at the level of individual cells. However, one of the main challenges of the single-cell RNA-sequencing analysis today, is the identification and annotation of cell types. The current method consists in manually checking the expression of genes using top differentially expressed genes and comparing them with related cell-type markers available in scientific publications. It is therefore time-consuming and labour intensive. Nevertheless, in the last two years,numerous automatic cell-type identification and annotation tools which use different strategies have been created. But, the lack of specific comparisons of those tools in the literature and especially for immuno-oncologic and oncologic purposes makes difficult for laboratories and companies to know objectively what are the best tools for annotating cell types. In this project, a review of the current tools and an evaluation of R tools were carried out.The annotation performance, the computation time and the ease of use were assessed. After this preliminary results, the best selected R tools seem to be ClustifyR (fast and rather precise) and SingleR (precise) for the correlation-based tools, and SingleCellNet (precise and rather fast) and scPred (precise but a lot of cell types remains unassigned) for the supervised classificationtools. Finally, for the marker-based tools, MAESTRO and SCINA are rather robust if they are provided with high quality markers.
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Kindblom, Marie, and Hakim Ezeddin Al. "Phylogenetic fatemapping: estimating allelic dropout probability in single cell genomic sequencing." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-186453.
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Single-cell genomic sequencing is a rapidly developing field that will play a vital role in human biology and science in the future. As of now, next-generation sequencing is accelerating in speed and decreasing in cost more quickly than Moore's law. Studies have shown that all cells in the human body have with very high probability a unique genomic signature, due to the somatic evolution which have accumulated mutations starting from the zygotic state. The possible reconstruction of phylogenetic lineage trees would be of vital importance to several fields in medicine, such as the stem cell research field. However, state-of-the-art methods for amplification such as WGA currently suffers from extensive allelic dropout which is troublesome when reconstructing phylogenetic trees. We have constructed a statistical model that can be used to predict site specific allelic dropout. Our results suggests that logistic regression is a suitable method for modelling allelic dropout, and that there is a non-linear relationship between the read depth and distance.
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Henao, Diaz Emanuela. "Towards single-cell exome sequencing with spatial resolution in tissue sections." Thesis, KTH, Skolan för bioteknologi (BIO), 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-150564.
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Evrony, Gilad David. "Single-cell Sequencing Studies of Somatic Mutation in the Human Brain." Thesis, Harvard University, 2013. http://dissertations.umi.com/gsas.harvard:10747.
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A major unanswered question in neuroscience is whether there exists genomic variability between individual neurons of the brain, contributing to functional diversity or to an unexplained burden of neurologic disease. To address this question, we developed methods to amplify genomes of single neurons from human brains, achieving >80% genome coverage of single-cells and allowing study of a wide-range of somatic mutation types.
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Ke, Rongqin. "Detection and Sequencing of Amplified Single Molecules." Doctoral thesis, Uppsala universitet, Molekylära verktyg, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-183141.
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Improved analytical methods provide new opportunities for both biological research and medical applications. This thesis describes several novel molecular techniques for nucleic acid and protein analysis based on detection or sequencing of amplified single molecules (ASMs). ASMs were generated from padlock probe assay and proximity ligation assay (PLA) through a series of molecular processes. In Paper I, a simple colorimetric readout strategy for detection of ASMs generated from padlock probe assay was used for highly sensitive detection of RNA virus, showing the potential of using padlock probes in the point-of-care diagnostics. In Paper II, digital quantification of ASMs, which were generated from padlock probe assay and PLA through circle-to-circle amplification (C2CA), was used for rapid and sensitive detection of nucleic acids and proteins, aiming for applications in biodefense. In Paper III, digital quantification of ASMs that were generated from PLA without C2CA was shown to be able to improve the precision and sensitivity of PLA when compared to the conventional real-time PCR readout. In Paper IV, a non-optical approach for detection of ASMs generated from PLA was used for sensitive detection of bacterial spores. ASMs were detected through sensing oligonucleotide-functionalized magnetic nanobeads that were trapped within them. Finally, based on in situ sequencing of ASMs generated via padlock probe assay, a novel method that enabled sequencing of individual mRNA molecules in their natural context was established and presented in Paper V. Highly multiplex detection of mRNA molecules was also achieved based on in situ sequencing. In situ sequencing allows studies of mRNA molecules from different aspects that cannot be accessed by current in situ hybridization techniques, providing possibilities for discovery of new information from the complexity of transcriptome. Therefore, it has a great potential to become a useful tool for gene expression research and disease diagnostics.
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Tu, Ang A. (Ang Andy). "Recovery of T cell receptor variable sequences from 3' barcoded single-cell RNA sequencing libraries." Thesis, Massachusetts Institute of Technology, 2020. https://hdl.handle.net/1721.1/127888.
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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Biological Engineering, May, 2020Cataloged from PDF version of thesis.
Includes bibliographical references (pages 107-112).
Heterogeneity of the immune system has increasingly necessitated the use of high-resolution techniques, including flow cytometry, RNA-seq, and mass spectrometry, to decipher the immune underpinnings of various diseases such as cancer and autoimmune disorders. In recent years, high-throughput single-cell RNA sequencing (scRNA-seq) has gained popularity among immunologists due to its ability to effectively characterize thousands of individual immune cells from tissues. Current techniques, however, are limited in their ability to elucidate essential immune cell features, including variable sequences of T cell antigen receptors (TCRs) that confer antigen specificity. Incorporation of TCR sequencing into scRNA-seq data could identify cells with shared antigen-recognition, further elucidating dynamics of antigen-specific immune responses in T cells.
In the first part of this thesis work, we develop a strategy that enables simultaneous analysis of TCR sequences and corresponding full transcriptomes from 32 barcoded scRNA-seq samples. This approach is compatible with common 32 scRNA-seq methods, and adaptable to processed samples post hoc. We applied the technique to identify transcriptional signatures associated with clonal T cells from murine and human samples. In both cases, we observed preferential phenotypes among subsets of expanded T cell clones, including cytotoxic T cell states associated with immunization against viral peptides. In the second part of the thesis, we apply the strategy to a 12-patient study of peanut food allergy to characterize T helper cell responses to oral immunotherapy (OIT). We identified clonal T cells associated with distinct subsets of T helper cells, including Teff, Treg, and Tfh, as well as Th1, Th2, and Th17 signatures.
We found that though the TCR repertoires of the patients were remarkably stable, regardless of their clinical outcomes, Th1 and Th2 clonotypes were phenotypically suppressed while Tfh clonotypes were not affected by therapy. Furthermore, we observed that highly activated clones were less likely to be suppressed by OIT than less activated clones. Our work represents one of the most detailed transcriptomic profiles of T helper cells in food allergy. In the last part of the thesis, we leverage the simplicity and adaptability of the method to recover TCR sequences from previously processed scRNA-seq samples derived from HIV patients and a nonhuman primate model of TB. In the HIV study, we recovered expanded clonotypes associated with activated T cells from longitudinal samples from patients with acute HIV infections. In the TB study, we modified the primers used in the method to T cells from TB granulomas of cynomolgus macaques.
We identified not only expanded clonotypes associated with cytotoxic functions, but also clonotypes shared by clusters of activated T cells. In total, these results demonstrate the utility of our method when studying diseases in which clonotype-driven responses are critical to understanding the underlying biology.
by Ang A. Tu.
Ph. D.
Ph.D. Massachusetts Institute of Technology, Department of Biological Engineering
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Lefebvre, Keely. "Resolving the Taxonomy and Phylogenetics of Benthic Diatoms from Single Cell Sequencing." Thesis, Université d'Ottawa / University of Ottawa, 2016. http://hdl.handle.net/10393/34553.
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Benthic diatoms are often used as indicators of water quality and past environmental conditions. This depends entirely on a reliable taxonomic system. With the advent of DNA techniques, genetic analyses can now be used in tandem with traditional microscopy in order to improve taxonomy and determine evolutionary relationships. This thesis examined a speciose genus of diatoms Neidium (> 300 species) and, using sequence data from molecular markers as well as traditional morphological analyses, investigated phylogenetic relationships. Fresh benthic samples from aquatic ecosystems in Eastern North America were collected; Neidium taxa were examined using light and scanning electron microscopy then compared to the original specimen types. A total of 124 individual cells were retrieved, amplified, and sequenced for four molecular markers (rbcL, 18S, psbA, and psbC). Phylogenetic reconstructions were completed using Maximum likelihood and Bayesian analyses; when compared with morphological analyses this led to the delineation of several novel Neidium species.
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Ziegenhain, Christoph [Verfasser], and Wolfgang [Akademischer Betreuer] Enard. "Improving & applying single-cell RNA sequencing / Christoph Ziegenhain ; Betreuer: Wolfgang Enard." München : Universitätsbibliothek der Ludwig-Maximilians-Universität, 2017. http://d-nb.info/1151818372/34.
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Vieth, Beate [Verfasser], and Wolfgang [Akademischer Betreuer] Enard. "Statistical power analysis for single-cell RNA-sequencing / Beate Vieth ; Betreuer: Wolfgang Enard." München : Universitätsbibliothek der Ludwig-Maximilians-Universität, 2020. http://d-nb.info/1225683033/34.
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Ross, Edith. "Inferring tumour evolution from single-cell and multi-sample data." Thesis, University of Cambridge, 2018. https://www.repository.cam.ac.uk/handle/1810/274604.
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Tumour development has long been recognised as an evolutionary process during which cells accumulate mutations and evolve into a mix of genetically distinct cell subpopulations. The resulting genetic intra-tumour heterogeneity poses a major challenge to cancer therapy, as it increases the chance of drug resistance. To study tumour evolution in more detail, reliable approaches to infer the life histories of tumours are needed. This dissertation focuses on computational methods for inferring trees of tumour evolution from single-cell and multi-sample sequencing data. Recent advances in single-cell sequencing technologies have promised to reveal tumour heterogeneity at a much higher resolution, but single-cell sequencing data is inherently noisy, making it unsuitable for analysis with classic phylogenetic methods. The first part of the dissertation describes OncoNEM, a novel probabilistic method to infer clonal lineage trees from noisy single nucleotide variants of single cells. Simulation studies are used to validate the method and to compare its performance to that of other methods. Finally, OncoNEM is applied in two case studies. In the second part of the dissertation, a comprehensive collection of existing multi-sample approaches is used to infer the phylogenies of metastatic breast cancers from ten patients. In particular, shallow whole-genome, whole exome and targeted deep sequencing data are analysed. The inference methods comprise copy number and point mutation based approaches, as well as a method that utilises a combination of the two. To improve the copy number based inference, a novel allele-specific multi-sample segmentation algorithm is presented. The results are compared across methods and data types to assess the reliability of the different methods. In summary, this thesis presents substantial methodological advances to understand tumour evolution from genomic profiles of single cells or related bulk samples.
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Svensson, Valentine. "Probabilistic modelling of cellular development from single-cell gene expression." Thesis, University of Cambridge, 2017. https://www.repository.cam.ac.uk/handle/1810/267937.
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The recent technology of single-cell RNA sequencing can be used to investigate molecular, transcriptional, changes in cells as they develop. I reviewed the literature on the technology, and made a large scale quantitative comparison of the different implementations of single cell RNA sequencing to identify their technical limitations. I investigate how to model transcriptional changes during cellular development. The general forms of expression changes with respect to development leads to nonparametric regression models, in the forms of Gaussian Processes. I used Gaussian process models to investigate expression patterns in early embryonic development, and compared the development of mice and humans. When using in vivo systems, ground truth time for each cell cannot be known. Only a snapshot of cells, all being in different stages of development can be obtained. In an experiment measuring the transcriptome of zebrafish blood precursor cells undergoing the development from hematopoietic stem cells to thrombocytes, I used a Gaussian Process Latent Variable model to align the cells according to the developmental trajectory. This way I could investigate which genes were driving the development, and characterise the different patterns of expression. With the latent variable strategy in mind, I designed an experiment to study a rare event of murine embryonic stem cells entering a state similar to very early embryos. The GPLVM can take advantage of the nonlinear expression patterns involved with this process. The results showed multiple activation events of genes as cells progress towards the rare state. An essential feature of cellular biology is that precursor cells can give rise to multiple types of progenitor cells through differentiation. In the immune system, naive T-helper cells differentiate to different sub-types depending on the infection. For an experiment where mice were infected by malaria, the T-helper cells develop into two cell types, Th1 and Tfh. I model this branching development using an Overlapping Mixture of Gaussian Processes, which let me identify both which cells belong to which branch, and learn which genes are involved with the different branches. Researchers have now started performing high-throughput experiments where spatial context of gene expression is recorded. Similar to how I identify temporal expression patterns, spatial expression patterns can be identified nonparametrically. To enable researchers to make use of this technique, I developed a very fast method to perform a statistical test for spatial dependence, and illustrate the result on multiple data sets.
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Subramanian, Parimalam Sangamithirai. "Dissecting gene expression of single cells ｗith reduced perturbation." Doctoral thesis, Kyoto University, 2021. http://hdl.handle.net/2433/263616.
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Kinchen, James. "Intestinal stromal cell types in health and inflammatory bowel disease uncovered by single-cell transcriptomics." Thesis, University of Oxford, 2017. http://ora.ox.ac.uk/objects/uuid:1bf9d8f0-6d09-46f5-9d1e-3c9e0b826618.
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Colonic stromal cells provide critical structural support but also regulate immunity, tolerance and inflammatory responses in the mucosa. Substantial variability and plasticity of mucosal stromal cells has been reported but a paucity of distinct marker genes exist to identify distinct cell states. Here single-cell RNA-sequencing is used to document heterogeneity and subtype specific markers of individual colonic stromal cells in human and mouse. Marker-free transcriptional clustering of fibroblast-like cells derived from healthy human tissue reveals distinct populations corresponding to myofibroblasts and three transcriptionally and functionally dissimilar populations of fibroblasts. A SOX6 high fibroblast subset occupies a position adjacent to the epithelial basement membrane and expresses multiple epithelial morphogens including WNT5A and BMP2. Additional fibroblast subtypes show specific enrichment for chemokine signalling and prostaglandin E2 synthesis respectively. In ulcerative colitis, substantial remodelling occurs with depletion of the SOX6 high population and emergence of an immune enriched population expressing genes associated with fibroblastic reticular cells including CCL19, CCL21 and IL33. A large murine dataset comprising over 7,000 colonic mesenchymal cells from an acute colitis model and matched healthy controls reveals strong preservation of the SOX6 high and myofibroblast transcriptional signatures. Unsupervised pseudotemporal ordering is used to relate fibroblast subsets to one another producing a branched developmental hierarchy that includes a potential progenitor population with mesothelial characteristics at its origin. This work provides a molecular basis for re-classification of colonic stromal cells and identifies pathological changes in these cells underpinning inflammation in UC.
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Chwastek, Damian. "Elucidating the Contribution of Stroke-Induced Changes to Neural Stem and Progenitor Cells Associated with a Neuronal Fate." Thesis, Université d'Ottawa / University of Ottawa, 2021. http://hdl.handle.net/10393/41839.
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Following stroke there is a robust increase in the proliferation of neural stem and progenitor cells (NSPCs) that ectopically migrate from the subventricular zone (SVZ) to surround the site of damage induced by stroke (infarct). Previous in vivo studies by our lab and others have shown that a majority of migrating NSPCs when labelled prior to stroke become astrocytes surrounding the infarct. In contrast, our lab has shown that the majority of NSPCs when labelled after stroke become neurons surrounding the infarct. This thesis aims to elucidate the contributions of intrinsic changes that can alter the temporal fate of the NSPCs. The NSPCs were fate mapped in this study using the nestin-CreERT2 mouse model and strokes were induced using the photothrombosis model within the cortex. In alignment with our previous findings, fate-mapping the NSPCs using a single injection of tamoxifen treatment revealed a temporal-specific switch in neuronal fate when NSPCs were labeled at timepoints greater than 7 days following stroke. Single cell RNA sequencing and histological analysis identified significant differences in the proportion of populations of NSPCs and their progeny labeled at the SVZ in the absence or presence of a stroke. NSPCs labelled after stroke were comprised of a reduced proportion of quiescent neural stem cells alongside an accompanied increase in doublecortin-expressing neuroblasts. The RNA transcriptional profile of the NSPCs labelled also revealed NSPCs and their progeny labeled after stroke had an overall enrichment for a neuronal transcription profile in all of the labeled cells with a reduction in astrocytic gene expression in quiescent and activated neural stem cells. Furthermore, we highlight the presence of perturbed transcriptional dynamics of neuronal genes, such as doublecortin following stroke. Altogether, our study reveals following a stroke there is a sustained intrinsic regulated neuronal-fated response in the NSPCs that reside in the SVZ that may not be exclusive from extrinsic regulation. This work raises the challenge to learn how to harness the potential of this response to improve recovery following stroke through examining their contributions to recovery.
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Reiser, Anita [Verfasser], and Joachim [Akademischer Betreuer] Rädler. "Single-cell time courses of mRNA transport and translation kinetics / Anita Reiser ; Betreuer: Joachim Rädler." München : Universitätsbibliothek der Ludwig-Maximilians-Universität, 2019. http://d-nb.info/1214593194/34.
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CAPRIOLI, CHIARA. "INTEGRATED SINGLE-CELL MUTATION, GENE EXPRESSION AND ISOFORM ANALYSIS TO DECONVOLVE ACUTE MYELOID LEUKEMIA HETEROGENEITY." Doctoral thesis, Università degli Studi di Milano, 2022. https://hdl.handle.net/2434/946325.
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Acute myeloid leukemia (AML) is an aggressive cancer arising from the hematopoietic stem cell (HSC). As other tumor types, AMLs are characterized by multiple and interconnected levels of intra-tumor heterogeneity, including genetic (DNA mutations), phenotypic (transcriptional patterns) and ecological (interactions with host immune-cells) diversity. Emerging evidence suggest that intra-tumor heterogeneity impacts directly on leukemogenesis, disease prognosis and sensitivity/resistance to available treatments. How the different layers of intra-tumoral heterogeneity interact with each other and shape the different leukemia phenotypes at single-cell level, however, is still missing. One major limit is the lack of technologies allowing ecosystem-wide characterization of tumor samples, including the simultaneous multiomic analyses of both malignant and immune populations at single-cell level. In this work, we have developed a novel high-throughput multiomics approach to integrate gene mutation, expression and isoform information at single-cell resolution. SCM-seq (Single Cell and Molecule sequencing) combines high- throughput droplet-based scRNA-seq to Nanopore single-molecule sequencing of full- length whole transcriptome and enriched mutated transcripts. This technology allows the integration at single cell-level of expression profiles and lineage-imputation (from scRNA-seq data) with mutation burden and transcript isoform diversity (from Nanopore data). We have applied this methodology to the analysis of three AML samples sharing a mutation in a spliceosome factor, with the aim to investigate how phenotypic heterogeneity is related to genetic complexity in both the malignant and immune compartments of a coherent AML subgroup. Results showed that SCM-seq allows multiomic characterization at single-cell level with sufficiently high throughput to represent sample complexity. We identified mutations at cell-level with high sensitivity and were able to stratify groups of cells based on their genetic complexity and mutations co-occurrences. For selected variants, we were also able to genotype both mutant and wild-type cells, which is the premise to investigate genotype-phenotype interactions. HSC/progenitor-like AML cells accumulated higher numbers of mutations and shared specific transcriptional features, including leukemia stem cell properties, thus enabling the identification of the putative malignant compartment of the AML samples. We found, however, that mutant cells were also represented in all remaining hematopoietic lineages, including differentiated myeloid cells and lymphocytes, recapitulating the genetic hierarchy observed in HSCs. Increasing genetic complexity in HSC/progenitor-like AML cells was associated to increasing transcriptional heterogeneity and correlated with the expression of genes and signatures related to cell cycle control, proliferation, stress response, RNA splicing regulation, MTORC1 signaling and MYC targets. Moreover, HSC/ progenitor-like AML cells with high mutation burden displayed limited isoform abundance, as related to the number of expressed genes, indicating a progressively restricted repertoire of isoforms in the presence of increasing genetic complexity. In all lineages, the presence of the SRSF2 mutation was associated to increased isoforms diversity, with mutated cells carrying significantly higher proportions of genes expressed with more than one isoform or expressing novel or alternative transcripts, as compared to AML SRSF2-wild-type cells. Together, these preliminary data show the capability of our method to integrate different sources of AML heterogeneity and their relevance within the tumor ecosystem.
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Ma, Sai. "Microfluidics for Genetic and Epigenetic Analysis." Diss., Virginia Tech, 2017. http://hdl.handle.net/10919/78187.
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Microfluidics has revolutionized how molecular biology studies are conducted. It permits profiling of genomic and epigenomic features for a wide range of applications. Microfluidics has been proven to be highly complementary to NGS technology with its unique capabilities for handling small volumes of samples and providing platforms for automation, integration, and multiplexing. In this thesis, we focus on three projects (diffusion-based PCR, MID-RRBS, and SurfaceChIP-seq), which improved the sensitivities of conventional assays by coupling with microfluidic technology. MID-RRBS and SurfaceChIP-seq projects were designed to profiling genome-wide DNA methylation and histone modifications, respectively. These assays dramatically improved the sensitivities of conventional approaches over 1000 times without compromising genomic coverages. We applied these assays to examine the neuronal/glial nuclei isolated from mouse brain tissues. We successfully identified the distinctive epigenomic signatures from neurons and glia. Another focus of this thesis is applying electrical field to investigate the intracellular contents. We report two projects, drug delivery to encapsulated bacteria and mRNA extraction under ultra-high electrical field intensity. We envision rapid growth in these directions, driven by the needs for testing scarce primary cells samples from patients in the context of precision medicine.Ph. D.
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MAHMOUD, NADY ABDELMOEZ ATTA. "On-chip Electrophoretic Fractionation of Cytoplasmic and Nuclear RNA from Single Cells." Kyoto University, 2019. http://hdl.handle.net/2433/244546.
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Hu, Bo. "Analysis of cellular drivers of zebrafish heart regeneration by single-cell RNA sequencing and high-throughput lineage tracing." Doctoral thesis, Humboldt-Universität zu Berlin, 2021. http://dx.doi.org/10.18452/23324.
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Das Herz eines Zebrafishs ist bemerkenswert, da es sich nach einer Verletzung vollständig regenerieren kann. Der Regenerationsprozess wird von Fibrose begleitet - der Bildung von überschüssigem Gewebe der extrazellulären Matrix (ECM). Anders als bei Säugetieren ist die Fibrose im Zebrafish nur transient. Viele Signalwege wurden identifiziert, die an der Herzregeneration beteiligt sind. Allerdings sind die Zelltypen, insbesondere Nicht-Kardiomyozyten, die für die Regulation des Regenerationsprozesses verantwortlich sind, weitgehend unbekannt. In dieser Arbeit haben wir systematisch alle Zelltypen des gesunden und des verletzten Zebrafischherzens mithilfe einer auf Mikrofluidik basierenden Hoch-Durchsatz- Einzelzell-RNA-Sequenzierung bestimmt. Wir fanden eine große Heterogenität von ECM-produzierenden Zellen, einschließlich einer Reihe neuer Fibroblasten, die nach einer Verletzung mit unterschiedlicher Dynamik auftreten. Wir konnten aktivierte Fibroblasten beschreiben und Fibroblasten-Subtypen mit einer pro-regenerativen Funktion identifizieren.
Darüber hinaus haben wir eine Methode entwickelt, um die Transkriptomanalyse und die Rekonstruktion von Zell-Verwandtschaften auf Einzelzellebene zu kombinieren. Unter Verwendung der CRISPR-Cas9-Technologie führten wir zufällige Mutationen in bekannte und ubiquitär transkribierte DNA-Loci während der Embryonalentwicklung von Zebrafischen ein. Diese Mutationen dienten als zellspezifische, permanente und vererbbare “Barcodes”, die zu einem späteren Zeitpunkt erfasst werden konnten. Mit maßgeschneiderten Analysealgorithmen konnten wir dann Stammbäume der sequenzierten Einzelzellen erstellen. Mit dieser neuen Methode haben wir gezeigt, dass im sich regenerierenden Zebrafischherz ECM-produzierende Zellpopulationen entweder mit dem Epi- oder mit dem Endokardium verwandt sind. Zusätzlich entdeckten wir, dass vom Endokardium abgeleitete Zelltypen vom Wnt-Signalweg abhängig sind.The zebrafish heart has the remarkable capacity to fully regenerate after injury. The regeneration process is accompanied by fibrosis - the formation of excess extracellular matrix (ECM) tissue, at the injury site. Unlike in mammals, the fibrosis of the zebrafish heart is only transient. While many pathways involved in heart regeneration have been identified, the cell types, especially non-myocytes, responsible for the regulation of the regenerative process have largely remained elusive. Here, we systematically determined all different cell types of both the healthy and cryo-injured zebrafish heart in its regeneration process using microfluidics based high-throughput single-cell RNA sequencing. We found a considerable heterogeneity of ECM producing cells, including a number of novel fibroblast cell types which appear with different dynamics after injury. We could describe activated fibroblasts that extensively switch on gene modules for ECM production and identify fibroblast sub- types with a pro-regenerative function. Furthermore, we developed a method that is capable of combining transcriptome analysis with lineage tracing on the single-cell level. Using CRISPR-Cas9 technology, we introduced random mutations into known and ubiquitously transcribed DNA loci during the zebrafish embryonic development. These mutations served as cell-unique, permanent, and heritable barcodes that could be captured at a later stage simultaneously with the transcriptome by high-throughput single-cell RNA sequencing. With custom tailored analysis algorithms, we were then able to build a developmental lineage tree of the sequenced single cells. Using this new method, we revealed that in the regenerating zebrafish heart, ECM contributing cell populations derive either from the epi- or the endocardium. Additionally, we discovered in a functional experiment that endocardial derived cell types are Wnt signaling dependent.
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Cherbonneau, Francois. "Development of new engineering methodologies for cell sequencing landscape : unbiased mRNA sampling of living cells by TRanscriptomic Analysis Captured in Extracellular vesicles (TRACE)." Thesis, Université de Paris (2019-....), 2021. https://wo.app.u-paris.fr/cgi-bin/WebObjects/TheseWeb.woa/wa/show?t=4387&f=28882.
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L’Hétérogénéité cellulaire et les expressions génétiques fluctuantes dans un microenvironnement spécifique restent mal comprises. Ainsi, afin d’apporter un début de réponse à toutes ces questions, beaucoup de paradigmes scientifiques ont été développés, permettant de toujours repousser plus loin les limites du possible. Ainsi, l'objectif de ce premier projet de thèse fut de développer une méthode innovante pour l'analyse épigénétique multiplexée de cellules à une résolution cellulaire unique. En reliant la protéine transposon Tn5 à des anticorps ciblant des facteurs épigénétiques clés, il pourrait être possible d'identifier le site de liaison de facteurs de transcription spécifiques à l'échelle du génome. Néanmoins, en raison de la relative concurrence dans le développement d’une nouvelle technologie dans ce domaine, cet outil très prometteur fut breveté par une autre entreprise et ce projet de thèse a donc été interrompu au profit d’un autre projet dans cette même thématique. Ainsi, beaucoup de progrès importants en biologie sont fortement corrélés avec de nouvelles méthodologies toujours plus innovantes et qui permettent de définir le destin cellulaire au niveau moléculaire. Mais une grande majorité d'entre elles nécessite l'utilisation de procédures destructrices. Pour ces raisons, nous avons développé une nouvelle technologie permettant une analyse transcriptomique dans le temps sans aucune destruction cellulaire. Nommée TRACE pour l'analyse «TRanslatomique» par capture dans des vésicules extracellulaires, elle est caractérisée par l’expression d’un transgène fournissant une translation d'une partie représentative du transcriptome cellulaire à l'intérieur des vésicules extracellulaires. Ainsi, ce «translatome» des cellules qui expriment TRACE peut être suivi dans le temps de manière non destructrice in vitro et in vivo, ce qui est un outil puissant pour de nombreux domaines de recherches fondamentale et translationnelleCell heterogeneity and fluctuant genetic expression in specific microenvironments remain poorly understood. Thus, to address a beginning of answer to all of these general questions, a lot of new scientific paradigms were developed and enable to push the limits of the possible. Thus, the goal of this first thesis project was to develop a highly innovative method for multiplexed epigenetic analysis of cells at a single cell resolution. By linking the Tn5 transposon protein with antibodies targeting key epigenetic factors, it could be possible to identify the binding site of specific transcription factors at a genome wide level. Nevertheless, due to the relative competition to develop a new technology in the field, this very promising tool has been patented by another company, thus the decision was taken to abort this project and focus on another one. A lot of progress and discovery in Biology is strongly correlated with new methodologies that provide the ability to define cell fate at molecular level, but a large majority of them require the use of destructive procedures. For these reasons, the second research project was to develop a new technology allowing transcriptomic analysis over time without any cell destruction. Named TRACE for “TRanslatomic” Analysis Captured in Extracellular vesicles, it is characterized by a cell-type specific transgene expression providing a translation of a representative part of the cell transcriptome inside Extracellular vesicles. Thus, “Translatome” of cells which express TRACE can be followed over time by non-destructive manner in vitro as well as in vivo, which is a powerful tool for many fields of fundamental and translational research
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El, Bardisy Shaheer [Verfasser]. "Development of a High-Throughput Single-Cell Sequencing Platform for the Discovery of Shared-Antigen and Neoepitope-Specific T-Cell Receptors / Shaheer El Bardisy." Mainz : Universitätsbibliothek Mainz, 2020. http://d-nb.info/1211519929/34.
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Tatsuoka, Hisato. "Single-cell Transcriptome Analysis Dissects the Replicating Process of Pancreatic Beta Cells in Partial Pancreatectomy Model." Doctoral thesis, Kyoto University, 2021. http://hdl.handle.net/2433/263543.
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Lu, Sijia. "Label-Free Optical Imaging of Chromophores and Genome Analysis at the Single Cell Level." Thesis, Harvard University, 2012. http://dissertations.umi.com/gsas.harvard:10563.
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Since the emergence of biology as a quantitative science in the past century, a lot of biological discoveries have been driven by milestone technical advances such as X-ray crystallography, fluorescence microscopy and high-throughput sequencing. Fluorescence microscopy is widely used to explore the nanoscale cellular world because of its superb sensitivity and spatial resolution. However, many species (e.g. lipids, small proteins) are non-fluorescent and are difficult to label without disturbing their native functions. In the first part of the dissertation, we explore using three different contrast mechanisms for label-free imaging of these species – absorption and stimulated emission (Chapter 2), heat generation and diffusion (Chapter 3) and nonlinear scattering (Chapter 4). We demonstrate label-free imaging of blood vessels, cytochromes, drugs for photodynamic therapy, and muscle and brain tissues with three dimensional optical sectioning capability. With the rapid development of high throughput genotyping techniques, genome analysis is currently routinely done genome-wide with single nucleotide resolution. However, a large amount of starting materials are often required for whole genome analysis. The dynamic changes in DNA molecules generate intra-sample heterogeneity. Even with the same genome content, different cells often have very different transcriptome profiles in a functional organism. Such intra-sample heterogeneities in the genome and transcriptome are often masked by ensemble analysis. In this second part of the dissertation, we first introduce a whole genome amplification method with high coverage in sequencing single human cells (Chapter 6). We then use the technique to study meiotic recombinations in sperm cells from an individual (Chapter 7). We further develop a technique that enables digital counting of genome fragments and whole genome haplotyping in single cells (Chapter 8). And we introduce our ongoing efforts on single cell transcriptome analysis (Chapter 9). In the end, we introduce our initial effort in exploring the genome accessibility at the single cell level (Chapter 9). Through the development of techniques probing the single cell genome, transcriptome and possibly epigenome, we hope to provide a toolbox for studying biological processes with genome-wide and single cell resolution.Chemistry and Chemical Biology
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Vuong, Nhung. "Molecular Mechanisms by Which Estrogen Causes Ovarian Epithelial Cell Dysplasia." Thesis, Université d'Ottawa / University of Ottawa, 2018. http://hdl.handle.net/10393/37286.
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The initiating events of ovarian cancer remain unknown, but an established risk factor is use of estrogen therapy by post-menopausal women where there is a positive correlation between duration of use and risk for disease. Mouse models of ovarian cancer have shown that exposure to exogenous 17β-estradiol (E2) accelerates tumour onset so this study aims to investigate the E2 signalling mechanisms responsible for sensitizing ovarian epithelial cells to transformation. By developing model systems that are responsive to E2 manipulation, we showed that E2 induces the formation of epithelial dysplasias both in vitro and in vivo. microRNA microarray was used to discover that E2 up-regulates microRNA-378 via the ESR1 pathway, resulting in the down-regulation of a tumour suppressor gene called Disabled-2 (Dab2). E2 suppression of Dab2 was found to result in increased proliferation, loss of contact inhibition, epithelial dysplasia, and increased sensitivity to transformation. This mechanism was also found to be active in mouse fallopian tube epithelium and human ovarian cancer cells. Single-cell RNA sequencing and trajectory analysis was subsequently used to explore additional signalling mechanisms that might contribute to the emergence of dysplastic lesions induced by E2. Multiple molecular signalling pathways dysregulated by E2 were identified and this revealed several possible biomarkers to be investigated for early detection of ovarian cancer. In the context of a current lack of strategies for ovarian cancer prevention or early detection, this work represents a significant advance in our understanding of how E2 promotes ovarian cancer initiation.
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Hu, Bo [Verfasser]. "Analysis of cellular drivers of zebrafish heart regeneration by single-cell RNA sequencing and high-throughput lineage tracing / Bo Hu." Berlin : Humboldt-Universität zu Berlin, 2021. http://nbn-resolving.de/urn:nbn:de:kobv:11-110-18452/24021-9.
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Sarma, Mimosa. "Microfluidic platforms for Transcriptomics and Epigenomics." Diss., Virginia Tech, 2019. http://hdl.handle.net/10919/90294.
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A cell, the building block of all life, stores a plethora of information in its genome, epigenome, and transcriptome which needs to be analyzed via various Omic studies. The heterogeneity in a seemingly similar group of cells is an important factor to consider and it could lead us to better understand processes such as cancer development and resistance to treatment, fetal development, and immune response. There is an ever growing demand to be able to develop more sensitive, accurate and robust ways to study Omic information and to analyze subtle biological variation between samples even with limited starting material obtained from a single cell. Microfluidics has opened up new and exciting possibilities that have revolutionized how we study and manipulate the contents of the cell like the DNA, RNA, proteins, etc. Microfluidics in conjunction with Next Gen Sequencing has provided ground-breaking capabilities for handling small sample volumes and has also provided scope for automation and multiplexing. In this thesis, we discuss a number of platforms for developing low-input or single cell Omic technologies. The first part talks about the development of a novel microfluidic platform to carry out single-cell RNA-sequencing in a one-pot method with a diffusion-based reagent swapping scheme. This platform helps to overcome the limitations of conventional microfluidic RNA seq methods reported in literature that use complicated multiple-chambered devices. It also provides good quality data that is comparable to state-of-the-art scRNA-seq methods while implementing a simpler device design that permits multiplexing. The second part talks about studying the transcriptome of innate leukocytes treated with varying levels of LPS and using RNA-seq to observe how innate immune cells undergo epigenetic reprogramming to develop phenotypes of memory cells. The third part discusses a low-cost alternative to produce tn5 enzyme which low-cost NGS studies. And finally, we discuss a microfluidic approach to carrying out low-input epigenomic studies for studying transcription factors. Today, single-cell or low-input Omic studies are rapidly moving into the clinical setting to enable studies of patient samples for personalized medicine. Our approaches and platforms will no doubt be important for transcriptomic and epigenomic studies of scarce cell samples under such settings.Doctor of Philosophy
This is the era of personalized medicine which means that we are no longer looking at one-size-fits-all therapies. We are rather focused on finding therapies that are tailormade to every individual’s personal needs. This has become more and more essential in the context of serious diseases like cancer where therapies have a lot of side-effects. To provide tailor-made therapy to patients, it is important to know how each patient is different from another. This difference can be found from studying how the individual is unique or different at the cellular level i.e. by looking into the contents of the cell like DNA, RNA, and chromatin. In this thesis, we discussed a number of projects which we can contribute to advancement in this field of personalized medicine. Our first project, MID-RNA-seq offers a new platform for studying the information contained in the RNA of a single cell. This platform has enough potential to be scaled up and automated into an excellent platform for studying the RNA of rare or limited patient samples. The second project discussed in this thesis involves studying the RNA of innate immune cells which defend our bodies against pathogens. The RNA data that we have unearthed in this project provides an immense scope for understanding innate immunity. This data provides our biologist collaborators the scope to test various pathways in innate immune cells and their roles in innate immune modulation. Our third project discusses a method to produce an enzyme called ‘Tn5’ which is necessary for studying the sequence of DNA. This enzyme which is commercially available has a very high cost associated with it but because we produced it in the lab, we were able to greatly reduce costs. The fourth project discussed involves the study of chromatin structure in cells and enables us to understand how our lifestyle choices change the expression or repression of genes in the cell, a study called epigenetics. The findings of this study would enable us to study epigenomic profiles from limited patient samples. Overall, our projects have enabled us to understand the information from cells especially when we have limited cell numbers. Once we have all this information we can compare how each patient is different from others. The future brings us closer to putting this into clinical practice and assigning different therapies to patients based on such data.
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Ferraioli, Anna. "Comparison of cell types across life cycle stages of the hydrozoan Clytia hemisphaerica." Electronic Thesis or Diss., Sorbonne université, 2022. http://www.theses.fr/2022SORUS497.
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L'Hydrozoaire Clytia hemisphaerica présente un cycle de vie triphasique, typique des hydrozoaires, comprenant une colonie de polypes à propagation végétative et une forme nageant librement, la méduse qui est se reproduisent de façon sexuée. Les méduses mâles et femelles se reproduisent quotidiennement, déclenchées par la lumière et environ un jour après la fécondation, une larve planula ciliée se forme. Après trois jours, la planula se fixe sur le substrat et se métamorphose pour donner naissance à un polype fondateur de la colonie, destiné pour l’alimentation, le gastrozooïde. La colonie se propage par extension du stolon et un deuxième type de polype, le gonozooïde, libère des méduses par bourgeonnement. L'analyse du génome et des transcriptomes à travers les trois principaux stades de vie de Clytia ont révélé des programmes d'expression génique spécifiques à chaque étape (Leclère et al. 2019, Nat Eco & Evo). Nous étendons maintenant cette comparaison au niveau des types cellulaire en utilisant la technologie du Single Cell RNA-seq chez la méduse et la larve de Clytia. Avec L. Leclère et S. Chevalier (LBDV), nous avons généré un atlas cellulaire de la méduse femelle en collaboration avec T. Chari et J. Gehring du laboratoire de L. Pachter et B. Weissbourd du laboratoire de D. Anderson à Caltech (Chari et al. 2021, Science Advances). L'analyse de l'atlas cellulaire de la méduse a révélé huit classes cellulaires, dont l'épiderme et le gastroderme, les cellules bioluminescentes, les ovocytes et les cellules souches multipotentes (I-Cells) des hydrozoaires et leurs dérivés tels que les cellules neurales, les nématocytes et les cellules glandulaires. L'analyse par hybridation in situ des profils d'expression ont révélé des sous-types non caractérisés auparavant, dont 14 sous-populations neuronales. L'analyse de la trajectoire de la lignée des nématocystes a révélé deux programmes transcriptionnels distincts au sein de cette classe cellulaire, une phase "nématoblaste", caractérisée par la production de la capsule du nématocyste, et la phase de différenciation du nématocyste, caractérisée par la production du nématocil.L’obtention du ScRNAseq pour la planula Clytia a nécessité l'optimisation des protocoles de dissociation, de fixation et de sélection des cellules (collaboration avec le groupe d'Arnau Sébé-Pedros, Barcelone). L’atlas cellulaire de la planula est constitué de 4370 cellules regroupées en 19 clusters cellulaires. Après une analyse des profils d'expression par hybridation in situ de gènes connus et nouveaux à trois stades de développement de la planula, nous avons pu attribuer des identités cellulaires et combiner les 19 clusters en 8 grandes classes cellulaires. Celles-ci correspondent aux deux couches de tissu épithélial classic chez les cnidaires, l'épiderme et le gastroderme, les cellules souches hydrozoaires (I-Cells), les nématocytes (cellules urticantes), les cellules neurales, les cellules neurosécrétrices aborales et des populations distinctes de cellules sécrétrices, les cellules muqueuses et les cellules excrétrices putatives (PEC).Cet atlas des types cellulaires de la planula de Clytia représente le premier atlas cellulaire d'une larve d'hydrozoaire et fournit la caractérisation de populations cellulaires non décrites auparavant ainsi que des informations supplémentaires sur les types cellulaires déjà connus. L'analyse comparative des deux atlas cellulaires a révélé des programmes transcriptionnels de nématocytes similaires entre les stades, indiquant que les deux étapes du développement des nématocytes persiste pendant les transitions du cycle de vie. Nous avons également pu identifier des types cellulaires exprimant les mêmes gènes chez les deux stades. Parmi ces gènes partagés, des sous-types cellulaires ont été trouvés uniquement dans la méduse. L'analyse des programmes d'expression génique a également révélé la présence de types cellulaires supposément spécifiques à chaque stadeThe hydrozoan Clytia hemisphaerica displays a typical tri-phasic hydrozoan life cycle including a vegetatively propagating polyp colony and free-swimming medusa form as the sexually reproductive life stage. Male and female jellyfish spawn daily, triggered by light and after fertilisation a ciliated planula larva forms in about one day. After three days the planula settles and metamorphoses to give rise to a primary feeding polyp, the gastrozooid, founder of the polyp colony. The colony propagates by stolon extension and a second type of polyp, the gonozooid, releases medusa by budding. Analysis of the genome and the bulk transcriptome across the three life stages revealed specific gene expression programs for each stage (Leclère et al. 2019, Nature Ecology & Evolution). We are now extending this comparison to the level of individual cell types via single-cell RNA transcriptomics of Clytia medusa and larva. Together with L. Leclère and S. Chevalier (LBDV), we generated a female medusa cell atlas in collaboration with T. Chari and J. Gehring from L. Pachter’s lab and B. Weissbourd from D. Anderson’s lab at Caltech (Chari et al. 2021, Science Advances). Analysis of the medusa cell atlas revealed eight broad cell type classes including epidermis and gastrodermis, bioluminescent cells, oocytes and the hydrozoan multipotent stem cells (i cells) and their derivatives such as neurons, nematocytes and gland cells. In situ hybridisation analysis of expression patterns revealed previously uncharacterized subtypes including 14 neuronal subpopulations. Trajectory analysis of the nematocyte lineage revealed two distinct transcriptional programs within this cell class, a “nematoblast” phase, characterised by the production of the typical nematocyte capsule, and the nematocyte differentiation phase, characterised by the production of the nematocil apparatus. ScRNAseq for the Clytia planula required refinement of cell dissociation, fixation and sorting protocols (collaboration with Arnau Sebé-Pedros’ group, Barcelona). Our planula Cell Atlas consists of 4370 cells grouped in 19 cell clusters. Following in situ hybridisation expression patterns analysis of known and novel genes at three planula developmental stages we could assign cell identities and combine the 19 clusters in 8 broad cell classes. These correspond to the two cnidarian epithelial tissue layers, the epidermis and the gastrodermis, the hydrozoan stem cells (I-cells), the nematocytes (stinging cells), neural cells, aboral neurosecretory cells and distinct population of secretory cells, mucous cells and putative excretory cells (PEC). This Clytia planula Cell Types Atlas represents the first cell atlas of an hydrozoan larva and provides characterization of previously undescribed cell populations as well as further information on already known cell types. Comparison analysis of the two Cell Atlases revealed similar nematocyte transcriptional programs between stages indicating that the two distinct developmental programs persist during life cycle transitions. We could identify shared gene expression at the cell type level between life stages. Among those, further subtypes were only found in the adult. Analysis of gene expression programs also revealed the presence of putative stage specific cell types
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STEINFELDER, ROBERT SEBASTIAN. "Development and implementation of novel applications of massively parallel sequencing in precision medicine." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2016. http://hdl.handle.net/10281/114589.
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Next-generation sequencing (NGS) based on “sequencing by synthesis”, such as Illumina’s MiSeq, NextSeq500 or HiSeq instruments has reached a state where consistency, throughput and quality make it a mature technology to use for cancer genome research, such as single-cell sequencing or in clinical diagnostics. Within the scope of this thesis, we designed and tested three protocols to mobilise high-throughput sequencing for precision medicine to provide optimal solutions for doctors to help with understanding, diagnosing and determining states of human cancer cells. Targeted re-sequencing of clinically relevant cancer genes using NGS ensures an economical use of tissue, by only doing one experiment for testing many drug-resistance tests. In collaboration with oncologists, three protocols are introduced and discussed depending on the respective use case. First, a comprehensive cancer panel based on targeted bait capture technology was developed, for a quick and in-depth genetic variant detection of 69 commonly examined cancer genes. After designing, over 300 clinical formalin-fixed and paraffin-embedded (FFPE) samples from patients, with known mutations in KRAS, NRAS, BRAF and EGFR at varying rates were sequenced. Sequencing data was collected and analysed in-depth to define assay properties and to determine sensitivity, specificity and overall reliability. Input material was evaluated by measuring DNA integrity (DIN) scores for each sample and correlated with overall performance. In doing so, we were able to set precise input criteria to ensure experimental success. The second step was the development of a diagnostic cancer panel of nine genes, based on enzymatic digestion and target amplification for a rapid and cost-effective testing of multiple genetic markers, who have an immediate impact on doctor’s decision on cancer drug therapies. The method introduces a novel approach by adding a molecular barcode to each molecular fragment sequenced, which is supposed to increase sensitivity as it allows removal of PCR artefacts and sequencing errors. The new panel was tested on 48 clinical FFPE samples that were previously genotyped on common cancer mutation hotspots with validated pyrosequencing. Strengths and imitations of this library-preparation method could be identified and considered. The third protocol describes a method to quickly extract and prepare DNA from thousands of individual cells simultaneously by capturing each cell in water droplets in an emulsion. Each droplet contains a collection of barcoded primer pairs that allows not only-barcoding individual fragments, but entire cells. The system has been tested by mixing mouse NIH3T3 cells with human KRAS insert, which carries a heterozygous mutation and human K562 cells with no known mutation in KRAS in an 80:20 ratio. Cells were emulsified with barcoded primer, a polymerase chain reaction amplified exons two and three, added cell-specific barcodes and prepared a library for sequencing in one step. After emulsion-breaking and clean-up and a second PCR, library was ready for sequencing. Around ten percent of a standard MiSeq run is enough to genotype over 10,000 cells. A developed script extracts barcodes from the sequencing data, which is then aligned with a standard alignment software, such as Burroughs-Wheeler-Aligner (BWA). Subsequently the introduced single-cell barcodes clustered according to cellular sub-populations to give deep insight into heterogeneity of the prepared cell population. This will prove a valuable tool in the assessment of diversity amongst cells in a variety of disease backgrounds and contribute to the development of precision medicine through informing patient-specific, personalised diagnostic approaches.
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Kuut, Gunnar [Verfasser], and Veit [Akademischer Betreuer] Hornung. "Using RNA barcoding and sequencing to study cellular differentiation on a single-cell and population level / Gunnar Kuut ; Betreuer: Veit Hornung." München : Universitätsbibliothek der Ludwig-Maximilians-Universität, 2021. http://d-nb.info/123801707X/34.
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Reddy, Devulapally Praneeth [Verfasser]. "High-throughput sequencing of human B cell receptor repertoires at single-cell level with preservation of the native antibody heavy and light chain pairs / Praneeth Reddy Devulapally." Berlin : Freie Universität Berlin, 2017. http://d-nb.info/1143596021/34.
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Muench, David. "Gfi1-controlled transcriptional circuits in normal and malignant hematopoiesis." University of Cincinnati / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1553250015825734.
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Genga, Ryan M. "Towards Understanding the Molecular Basis of Human Endoderm Development Using CRISPR-Effector and Single-Cell Technologies." eScholarship@UMMS, 2019. https://escholarship.umassmed.edu/gsbs_diss/1008.
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The definitive endoderm gives rise to several specialized organs, including the thymus. Improper development of the definite endoderm or its derivatives can lead to human disease; in the case of the thymus, immunodeficiency or autoimmune disorders. Human pluripotent stem cells (hPSCs) have emerged as a system to model human development, as study of their differentiation allows for elucidation of the molecular basis of cell fate decisions, under both healthy and impaired conditions. Here, we first developed a CRISPR-effector system to control endogenous gene expression in hPSCs, a novel approach to manipulating hPSC state. Next, the human-specific, loss-of-function phenotypes of candidate transcription factors driving hPSC-to-definitive endoderm differentiation were analyzed through combined CRISPR-perturbation and single-cell RNA-sequencing. This analysis revealed the importance of TGFβ mediators in human definitive endoderm differentiation as well as identified an unappreciated role for FOXA2 in human foregut development. Finally, as the differentiation of definitive endoderm to thymic epithelial progenitors (TEPs) is of particular interest, a single-cell transcriptomic atlas of murine thymus development was generated in anticipation of identifying factors driving later stages of TEP differentiation. Taken together, this dissertation establishes a CRISPR-effector system to interrogate gene and regulatory element function in hPSC differentiation strategies, details the role of specific transcription factors in human endoderm differentiation, and sets the groundwork for future investigations to characterize hPSC-derived TEPs and the factors driving their differentiation.
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Chen, Huiyi. "System-Wide Studies of Gene Expression in Escherichia coli by Fluorescence Microscopy and High Throughput Sequencing." Thesis, Harvard University, 2011. http://dissertations.umi.com/gsas.harvard:10044.
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Gene expression is a fundamental process in the cell and is made up of two parts – the information flow from DNA to RNA, and from RNA to protein. Here, we examined specific sub-processes in Escherichia coli gene expression using newly available tools that permit genome-wide analysis. We begin our studies measuring mRNA and protein abundances in single cells by single-molecule fluorescence microscopy, and then focus our attention to studying RNA generation and degradation by high throughput sequencing. The details of the dynamics of gene expression can be observed from fluctuations in mRNA and protein copy numbers in a cell over time, or the variations in copy numbers in an isogenic cell population. We constructed a yellow fluorescent fusion protein library in E. coli and measured protein and mRNA abundances in single cells. At below ten proteins per cell, a simple model of gene expression is sufficient to explain the observed distributions. At higher expression levels, the distributions are dominated by extrinsic noise, which is the systematic heterogeneity between cells. Unlike proteins which can be stable over many hours, mRNA is made and degraded on the order of minutes in E. coli. To measure the dynamics of RNA generation and degradation, we developed a protocol using high throughput sequencing to measure steady-state RNA abundances, RNA polymerase elongation rates and RNA degradation rates simultaneously with high nucleotide-resolution genome-wide. Our data shows that RNA has similar lifetime at all positions throughout the length of the transcript. We also find that our polymerase elongation rates measured in vivo on a chromosome are generally slower than rates measured on plasmids by other groups. Studying nascent RNA will allow further understanding of RNA generation and degradation. To this end, we have developed a labeling protocol with a nucleoside analog that is compatible with high throughput sequencing.
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Lavagi, Ilaria Verfasser], and Eckhard [Akademischer Betreuer] [Wolf. "Analysis of blastomere of bovine embryos during genome activation by evaluation of single-cell RNA sequencing data / Ilaria Lavagi ; Betreuer: Eckhard Wolf." München : Universitätsbibliothek der Ludwig-Maximilians-Universität, 2018. http://d-nb.info/1167160541/34.
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Lee, Jiyoung. "Computational Analysis of Gene Expression Regulation from Cross Species Comparison to Single Cell Resolution." Diss., Virginia Tech, 2020. http://hdl.handle.net/10919/99878.
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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.
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Reinsborough, Calder. "Search for Novel DNA Modifications in Saccharomyces cerevisiae mtDNA using Single Molecule Real Time Sequencing and Effects of Mitochondrial Metabolic Dynamics on Gene Expression." Thesis, Icahn School of Medicine at Mount Sinai, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=1569125.
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In the past five years, Single Molecule Real Time (SMRT) sequencing technology has been found to be a reliable indicator of certain epigenetic modifications in bacterial genomes. The genome of the model organism Saccharomyces cerevisiae has long been thought to be free of DNA level modification, but literature surrounding this subject is conflicting. Additionally, the mitochondria of S. cerevisiae control the transition between three distinct chronological life phases – exponential, postdiauxic, and stationary - as defined by their main metabolic processes. This study attempted to identify base modifications to mtDNA using PacBio sequencing while additionally establishing gene expression changes as a result of altered mitochondrial metabolic capabilities. PacBio results showed intriguing results but statistical analysis proved experimentation with improved protocols were necessary. Multiple genes with unknown or uncharacterized function were also shown to have significant differential expression between metabolic life phases.
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Petrany, Michael J. "Consequences of Cell Fusion and Multinucleation for Skeletal Muscle Development and Disease." University of Cincinnati / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1595847866440328.
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Wu, Zhiyuan [Verfasser], Lars [Akademischer Betreuer] Mägdefessel, Hendrik [Gutachter] Sager, and Lars [Gutachter] Mägdefessel. "Single-Cell RNA Sequencing Analysis Revealed Cellular Heterogeneity of Human Abdominal Aortic Aneurysm / Zhiyuan Wu ; Gutachter: Hendrik Sager, Lars Mägdefessel ; Betreuer: Lars Mägdefessel." München : Universitätsbibliothek der TU München, 2021. http://d-nb.info/1240384114/34.
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Hirabayashi, Shigeki. "APOBEC3B is preferentially expressed at the G2/M phase of cell cycle." Doctoral thesis, Kyoto University, 2021. http://hdl.handle.net/2433/264663.
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京都大学新制・課程博士
博士(医学)
甲第23382号
医博第4751号
新制||医||1052(附属図書館)
京都大学大学院医学研究科医学専攻
(主査)教授 伊藤 貴浩, 教授 滝田 順子, 教授 江藤 浩之
学位規則第4条第1項該当
Doctor of Medical Science
Kyoto University
DFAM
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Teufel, Lotte. "Cyclins and their roles in cell cycle progression, transcriptional regulation and osmostress adaptation in Saccharomyces cerevisiae. A transcriptome-wide and single cell approach." Doctoral thesis, Humboldt-Universität zu Berlin, 2020. http://dx.doi.org/10.18452/21205.
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Der eukaryotische Zellzyklus ist ein streng regulierter Prozess, für dessen zeitlichen Ablauf unter anderem oszillierende Genexpression notwendig ist.
Die Regulation und die zeitliche Koordination des Zellzyklus sind nach wie vor fundamentale Fragen der Zellbiologie. Spezifische Ereignisse, wie DNA Replikation und Zellkernteilung, können vier Zellzyklusphasen zugeordnet werden, welche durch Cyclin-abhängige Kinasen, Cycline und deren Inhibitoren reguliert werden. Während in Saccharomyces cerevisiae Cyclin-abhängige Kinasen (Cdc28, Pho85) über den gesamten Zellzyklus zu Verfügung stehen, werden Cycline und ihre Inhibitoren nur in spezifischen Phasen exprimiert. In S. cerevisiae sind drei wichtige G1-Cycline (Cln1-Cln3) in die oszillierende Genexpression involviert.
In dieser Arbeit wurde die zeitaufgelöste, transkriptomweite Genexpression im Wildtyp und in Cyclindeletionsmutanten gemessen. Um die Rolle der G1-Cycline für die Feinabstimmung des Zellzykluses zu verstehen, wurden Gene nach charakteristischen Expressionsprofilen geclustert, Expressionsmaxima detektiert, ein Transkriptionsfaktornetzwerk integriert und Zellzyklusphasendauern bestimmt. Um Unterschiede zwischen der Rolle der Cycline zu verstehen, wurden die Zellen zusätzlich Osmostress ausgesetzt.
Des Weiteren wurde mit Hilfe von RNA-Fluorescence In Situ Hybridization (FISH) die Expression zweier Cycline (PCL1 und PCL9), die an Pho85 binden, auf Einzelzellniveau gemessen. Um die Expression in spezifischen Zellzyklusphasen zu quantifizieren, wurden einzelne Zellen mithilfe von Zellzyklusmarkern spezifischen Zellzyklusphasen zugeordnet. Nachdem die Expression unter normalen Wachstumsbedingungen gemessen wurde, wurde zusätzlich Osmostress angewandt.
Durch die Kombination einer Einzelzellquantifizierung und einer transkriptomweiten Methode konnten spezifische Aufgaben der Cycline, Cln1, Cln2 und Cln3, erforscht werden. Zusätzlich konnten backup Mechanismen für die Zellzyklusregulation entschlüsselt werden.The eukaryotic cell cycle is a highly ordered process. For its timing and progression, oscillating gene expression is crucial. The stability of cell cycle regulation and the exact timing is still a fundamental question in cell biology. Specific events, like DNA replication and nuclear division can be assigned to four distinct phases. These events are regulated by cyclin-dependent kinases, cyclins and their inhibitors. In Saccharomyces cerevisiae cyclin-dependent kinases (Cdc28, Pho85) are present throughout the cell cycle, while cyclins and their inhibitors are only expressed and active during specific phases. The G1 cyclins Cln1-3 are essential players to induce oscillating gene expression and are thereby involved in the fine-tuning of the cell cycle. To understand the role of the G1 cyclins for exact cell cycle timing and oscillating gene expression, time-resolved, transcriptome-wide gene expression in wild type and cyclin deletion mutants were measured. Characteristic expression profiles were clustered, precise peak times for each gene were estimated, a transcription factor network was integrated and cell cycle phase durations were defined. To further understand the role and differences of each cyclin osmostress was applied. Furthermore the expression of two cyclins (PCL1 and PCL9) corresponding to the cyclin-dependent kinase Pho85 was measured in single cells. Using RNA-Fluorescence In Situ Hybridization (FISH) and cell cycle progression markers, high and low expression phases and absolute numbers of mRNAs were obtained. Gene expression was quantified under normal and osmostressed growth conditions to understand the necessity of the cyclins for osmostress adaptation in different cell cycle phases. By the combination of a single cell and a transcriptome-wide approach distinct roles of G1 cyclins Cln1, Cln2 and Cln3 were deciphered and an insight in the backup mechanisms during cell cycle progression for normal and osmostressed growth conditions were proposed.
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Yuan, Xiao. "Graph neural networks for spatial gene expression analysis of the developing human heart." Thesis, Uppsala universitet, Institutionen för biologisk grundutbildning, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-427330.
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Single-cell RNA sequencing and in situ sequencing were combined in a recent study of the developing human heart to explore the transcriptional landscape at three developmental stages. However, the method used in the study to create the spatial cellular maps has some limitations. It relies on image segmentation of the nuclei and cell types defined in advance by single-cell sequencing. In this study, we applied a new unsupervised approach based on graph neural networks on the in situ sequencing data of the human heart to find spatial gene expression patterns and detect novel cell and sub-cell types. In this thesis, we first introduce some relevant background knowledge about the sequencing techniques that generate our data, machine learning in single-cell analysis, and deep learning on graphs. We have explored several graph neural network models and algorithms to learn embeddings for spatial gene expression. Dimensionality reduction and cluster analysis were performed on the embeddings for visualization and identification of biologically functional domains. Based on the cluster gene expression profiles, locations of the clusters in the heart sections, and comparison with cell types defined in the previous study, the results of our experiments demonstrate that graph neural networks can learn meaningful representations of spatial gene expression in the human heart. We hope further validations of our clustering results could give new insights into cell development and differentiation processes of the human heart.
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Sivertsson, Åsa. "Detection and analysis of genetic alterations in normal skin and skin tumours." Doctoral thesis, KTH, Biotechnology, 2002. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-3432.
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The investigation of genetic alterations in cancer-relatedgenes is useful for research, prognostic and therapeuticpurposes. However, the genetic heterogeneity that often occursduring tumour progression can make correct analysischallenging. The objective of this work has been to develop,evaluate and apply techniques that are sufficiently sensitiveand specific to detect and analyse genetic alterations in skintumours as well as in normal skin.
Initially, a method based on laser-assisted microdissectionin combination with conventional dideoxy sequencing wasdeveloped and evaluated for the analysis of the p53 tumoursuppressor gene in small tissue samples. This method was shownto facilitate the analysis of single somatic cells fromhistologic tissue sections. In two subsequent studies themethod was used to analyse single cells to investigate theeffects of ultraviolet (UV) light on normal skin. Single p53immunoreactive and nonimmunoreactive cells from differentlayers of sunexposed skin, as well as skin protected fromexposure, were analysed for mutations in the p53 gene. Theresults revealed the structure of a clandestine p53 clone andprovided new insight into the possible events involved innormal differentiation by suggesting a role for allele dropout.The mutational effect of physiological doses of ultravioletlight A (UVA) on normal skin was then investigated by analysingthe p53 gene status in single immunoreactive cells at differenttime-points. Strong indications were found that UVA (even atlow doses) is indeed a mutagen and that its role should not bedisregarded in skin carcinogenesis.
After slight modifications, the p53 mutation analysisstrategy was thenused to complement an x-chromosomeinactivation assay for investigation of basal cell cancer (BCC)clonality. The conclusion was that although the majority ofBCCs are of monoclonal origin, an occasional tumour withapparently polyclonal origin exists. Finally, apyrosequencing-based mutation detection method was developedand evaluated for detection of hot-spot mutations in the N-rasgene of malignant melanoma. More than 80 melanoma metastasissamples were analysed by the standard approach of single strandconformation polymorphism analysis (SSCP)/DNA sequencing and bythis pyrosequencing strategy. Pyrosequencing was found to be agood alternative to SSCP/DNA sequencing and showed equivalentreproducibility and sensitivity in addition to being a simpleand rapid technique.
Keywords:single cell, DNA sequencing, p53, mutation,UV, BCC, pyrosequencing, malignant melanoma, N-ras
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LUONGO, RAFFAELE. "TOWARDS PATIENT-SPECIFIC MODELS IN HIGH GRADE SEROUS OVARIAN CANCER (HGSOC): LINKING EPIGENETIC TRACING OF CELL OF ORIGIN WITH ACTIONABLE ORGANOID MODELS." Doctoral thesis, Università degli Studi di Milano, 2021. http://hdl.handle.net/2434/883835.
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Ovarian Cancer (OC) is a major cause of cancer-related mortality, due to the late-stage diagnosis and failure of surgery and chemotherapy to fully eradicate the disease, that is reflected in a high rate of tumor relapse after treatments. Patients with high-grade serous ovarian cancer (HGSOC), representing the largest majority of OC (~70%), have not experienced significant improvement in overall survival in last decades (1), pointing to the acute need to identify new predictive biomarkers and therapeutic targets for clinical settings.
This unresolved emergency derives from our poor understanding of HGSOC biology combined with the recognized lack of suitable clinically relevant models for this disease, as the available models fail to relate molecular aberrations to clinical histories (2). Moreover, one major challenge that sets HGSOC apart from all other solid tumors, that has witnessed significant progress in recent years, is the persistent uncertainty about its cell of origin and the consequent lack of molecular signatures for the unequivocal assignment of specific samples to either an ovarian surface epithelium (OSE) or a fallopian tube fimbrial epithelium (FI) origin, the two candidate tissues still debated in literature (3, 4). Altogether, these aspects have hampered the dissection of pathogenic mechanisms and the identification of targets for improved clinical care of patients, driving us towards the embracement of new paradigms for effective advancements in the clinical setting.
To overcome these issues, in the past few years, in the lab, we have devoted our efforts to the identification of the cell of origin of the tumor and the development of a clinical model allowing the study of this disease. Our applications aimed at brought a valid boost towards those precision oncology approaches that promises to transform cancer care by delivering personalized treatments tailored to the genetic and epigenetic specificities of patients’ tumors, whose remarkable heterogeneity characterizes even seemingly homogeneous histotypes.
This level of complexity urged the need to develop and validate patient-derived cancer models that recapitulate to a meaningful extent the features of primary or metastatic tumors, both for efficient drug development and for guiding therapeutic strategies. Among new technologies, patient-derived organoid cultures are emerging as powerful models able to recapitulate in a meaningful extent the features of primary tumors (5, 6). Their value was proved both in guiding therapeutic decision for broadly curable tumors (7) and in gaining new insights for intractable tumors such as pancreatic adenocarcinoma (8). OC studies have started to benefit from these advanced models only recently (9–11), and a huge part of this PhD work regards the generation of organoids models from both HGSOC and normal samples of FI and OSE, in order to encompass all kind of tissues useful for the study of the pathology. Indeed, while tumor organoids represent an in vitro proxy of OC at an advanced stage, normal organoids from healthy tissues can be used as control but also as an indefinitely expandable cellular model in which investigate tumor alterations in the context of a normal tissue. This is really significant also in light of our recent publications on the cell of origin of HGSOC (12), where we showed the establishment of a method that is able to stratify HGSOC tumors through an approach based on methylomics and transcriptomics that:
i) allows to distinguish OSE- from FI- derived tumors;
ii) allows to identify for each tumor subtype the specific transcriptomic alterations that could drive the tumorigenic process;
iii) reveals a prognostic value for the tissue of origin of this disease.
Taken together, these two sets of information could help in define the molecular mechanisms governing the disease at an unprecedented resolution, setting a paradigm for harnessing patient-specific cancer models in the complementary goal of dissecting pathogenic mechanisms and extracting their actionable features.
The extrapolation of information from organoids taking in consideration the cell of origin, through both the increase of our knowledge of the pathology and the identification of new markers and targets to be used as novel drug therapies, will prospectively pave the way to the improve the clinical care of patients with HGSOC.
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Buchet, Samuel. "Vérification formelle et apprentissage logique pour la modélisation qualitative à partir de données single-cell." Thesis, Ecole centrale de Nantes, 2022. http://www.theses.fr/2022ECDN0011.
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La compréhension des mécanismes cellulaires à l’œuvre au sein des organismes vivants repose généralement sur l’étude de leur expression génétique. Cependant, les gènes sont impliqués dans des processus de régulation complexes et leur mesureest difficile à réaliser. Dans ce contexte, la modélisation qualitative des réseaux de régulation génétique vise à établir la fonction de chaque gène à partir de la modélisation discrète d’un réseau d’interaction dynamique. Dans cette thèse, nous avons pour objectif de mettre en place cette approche de modélisation à partir des données de séquençage single-cell. Ces données se révèlent en effet intéressantes pour la modélisation qualitative, car elles apportent une grande précision et peuvent être interprétées de manière dynamique. Nous développons ainsi une méthode d’inférence de modèles qualitatifs basée sur l’apprentissage automatique de programmes logiques. Cette méthode est mise en œuvre sur des données single-cell et nous proposons plusieurs approches pour interpréter les modèles résultants en les confrontant avec des connaissances préétabliesThe understanding of cellular mechanisms occurring inside human beings usually depends on the study of its gene expression.However, genes are implied in complex regulatory processes and their measurement is difficult to perform. In this context, the qualitative modeling of gene regulatory networks intends to establish the function of each gene from the discrete modeling of a dynamical interaction network. In this thesis, our goal is to implement this modeling approach from single-cell sequencing data. These data prove to be interesting for qualitative modeling since they bring high precision, and they can be interpreted in a dynamical way. Thus, we develop a method for the inference of qualitative models based on the automatic learning of logic programs. This method is applied on a single-cell dataset, and we propose several approaches to interpret the resulting models by comparing them with existing knowledge
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Bampalikis, Dimitrios. "Recognizing biological and technical differences in scRNAseq : A comparison of two protocols." Thesis, Uppsala universitet, Institutionen för biologisk grundutbildning, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-366169.
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Recent advances in sequencing technology have given access to information extracted on a single cell level. Single cell RNA sequencing enables for transcriptomes to be sequenced, allowing for studies within and between cell types. A recently developed protocol, based on Smart-seq2, and the Proximity ligation essay, allows for the detection of protein data from single cells, in parallel with RNA. The combination of the transcriptomic and proteomic data will enhance researchers’ ability to explore cell states. In this study, we are comparing a new pulldown protocol with the widely-used Smart-seq2, as well as against FACS sorted cells. Our results show differences in the RNA sequenced between the two protocols, as well the prediction of cell cycle state based on their data. Using RNA extracted from the pulldown protocol in different time points, we also calculate the direction of development for the cells. We expect that the incorporation of proteomic data will shed light to relevant biological questions related to the cell function.
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Sandberg, Julia. "Massively parallel analysis of cells and nucleic acids." Doctoral thesis, KTH, Genteknologi, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-45671.
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Recent proceedings in biotechnology have enabled completely new avenues in life science research to be explored. By allowing increased parallelization an ever-increasing complexity of cell samples or experiments can be investigated in shorter time and at a lower cost. This facilitates for example large-scale efforts to study cell heterogeneity at the single cell level, by analyzing cells in parallel that also can include global genomic analyses. The work presented in this thesis focuses on massively parallel analysis of cells or nucleic acid samples, demonstrating technology developments in the field as well as use of the technology in life sciences. In stem cell research issues such as cell morphology, cell differentiation and effects of reprogramming factors are frequently studied, and to obtain information on cell heterogeneity these experiments are preferably carried out on single cells. In paper I we used a high-density microwell device in silicon and glass for culturing and screening of stem cells. Maintained pluripotency in stem cells from human and mouse was demonstrated in a screening assay by antibody staining and the chip was furthermore used for studying neural differentiation. The chip format allows for low sample volumes and rapid high-throughput analysis of single cells, and is compatible with Fluorescence Activated Cell Sorting (FACS) for precise cell selection. Massively parallel DNA sequencing is revolutionizing genomics research throughout the life sciences by constantly producing increasing amounts of data from one sequencing run. However, the reagent costs and labor requirements in current massively parallel sequencing protocols are still substantial. In paper II-IV we have focused on flow-sorting techniques for improved sample preparation in bead-based massive sequencing platforms, with the aim of increasing the amount of quality data output, as demonstrated on the Roche/454 platform. In paper II we demonstrate a rapid alternative to the existing shotgun sample titration protocol and also use flow-sorting to enrich for beads that carry amplified template DNA after emulsion PCR, thus obtaining pure samples and with no downstream sacrifice of DNA sequencing quality. This should be seen in comparison to the standard 454-enrichment protocol, which gives rise to varying degrees of sample purity, thus affecting the sequence data output of the sequencing run. Massively parallel sequencing is also useful for deep sequencing of specific PCR-amplified targets in parallel. However, unspecific product formation is a common problem in amplicon sequencing and since these shorter products may be difficult to fully remove by standard procedures such as gel purification, and their presence inevitably reduces the number of target sequence reads that can be obtained in each sequencing run. In paper III a gene-specific fluorescent probe was used for target-specific FACS enrichment to specifically enrich for beads with an amplified target gene on the surface. Through this procedure a nearly three-fold increase in fraction of informative sequences was obtained and with no sequence bias introduced. Barcode labeling of different DNA libraries prior to pooling and emulsion PCR is standard procedure to maximize the number of experiments that can be run in one sequencing lane, while also decreasing the impact of technical noise. However, variation between libraries in quality and GC content affects amplification efficiency, which may result in biased fractions of the different libraries in the sequencing data. In paper IV barcode specific labeling and flow-sorting for normalization of beads with different barcodes on the surface was used in order to weigh the proportion of data obtained from different samples, while also removing mixed beads, and beads with no or poorly amplified product on the surface, hence also resulting in an increased sequence quality. In paper V, cell heterogeneity within a human being is being investigated by low-coverage whole genome sequencing of single cell material. By focusing on the most variable portion of the human genome, polyguanine nucleotide repeat regions, variability between different cells is investigated and highly variable polyguanine repeat loci are identified. By selectively amplifying and sequencing polyguanine nucleotide repeats from single cells for which the phylogenetic relationship is known, we demonstrate that massively parallel sequencing can be used to study cell-cell variation in length of these repeats, based on which a phylogenetic tree can be drawn.QC 20111031
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Weinberger, Michael. "Epicardial heterogeneity during zebrafish heart development." Thesis, University of Oxford, 2017. http://ora.ox.ac.uk/objects/uuid:3f26b933-5f17-4fe3-bd86-9211af69a558.
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The epicardium, a cell layer enveloping the heart muscle, drives embryonic heart development and heart repair in the adult zebrafish. Previous studies found the epicardium to consist of multiple cell populations with distinct phenotypes and functions. Here, I investigated epicardial heterogeneity in the developing zebrafish heart, focusing on the developmental gene program that is also reactivated during adult heart regeneration. Transcription factor 21 (Tcf21), T-box 18 (Tbx18) and Wilms' tumor suppressor 1b (Wt1b) are often used interchangeably to identify the zebrafish epicardium. Analyzing newly generated reporter lines and endogenous gene expression, I showed that the epicardial expression of tcf21, tbx18 and wt1b during development is heterogeneous. I then collected epicardial cells from newly generated reporter lines at 5 days-post-fertilization and performed single-cell RNA sequencing. I identified three distinct epicardial subpopulations with specific gene expression profiles. The first subpopulation expressed tcf21, tbx18 and wt1b and appeared to represent the main epicardial layer. The second subpopulation expressed tbx18, but not tcf21 or wt1b. Instead, it expressed smooth muscle markers and seemed restricted to the bulbus arteriosus. The third epicardial subpopulation only expressed tcf21 and resided within the epicardial layer. I compared the single-cell subpopulations with transcriptomic bulk data and visualized the expression of marker genes to investigate their spatial distribution. Using ATAC sequencing, I additionally identified open regulatory regions located in proximity to subpopulation-specific marker genes and showed subpopulation-specific activity in vivo. My results detail distinct cell populations in the developing zebrafish epicardium, likely to fulfil distinct and specific cellular functions. Future experiments will involve targeting signature genes enriched within each epicardial subpopulation, such as those encoding Adrenomedullin a (first subpopulation), Alpha Smooth Muscle Actin (second subpopulation) and Claudin 11a (third subpopulation), employing cell type-specific genome editing to test whether and how the identified heterogeneity underlies distinct epicardial cell fates and functions. Taken together, my work adds significantly to the understanding of the cellular and molecular basis of epicardial development and can offer novel insights in the context of heart regeneration.