Single-cell RNA sequencing (scRNA-seq) is the leading technique for characterizing cellular heterogeneity in biological samples. Various scRNA-seq protocols have been developed that can measure the transcriptome from thousands of cells in a single experiment. With these methods readily available, the ability to transform raw data into biological understanding of complex systems is now a rate-limiting step. In this dissertation, I introduce novel computational software and tools which enhance preprocessing and clustering of scRNA-seq data and evaluate their performance compared to existing methods. First, I present scruff, an R/Bioconductor package that preprocesses data generated from scRNA-seq protocols including CEL-Seq or CEL-Seq2 and reports comprehensive data quality metrics and visualizations. scruff rapidly demultiplexes, aligns, and counts the reads mapped to genomic features with deduplication of unique molecular identifier (UMI) tags and provides novel and extensive functions to visualize both pre- and post-alignment data quality metrics for cells from multiple experiments. Second, I present Celda, a novel Bayesian hierarchical model that can perform simultaneous co-clustering of genes into transcriptional modules and cells into subpopulations for scRNA-seq data. Celda identified novel cell subpopulations in a publicly available peripheral blood mononuclear cell (PBMC) dataset and outperformed a PCA-based approach for gene clustering on simulated data. Third, I extend the application of Celda by developing a multimodal clustering method that utilizes both mRNA and protein expression information generated from single-cell sequencing datasets with multiple modalities, and demonstrate that Celda multimodal clustering captured meaningful biological patterns which are missed by transcriptome- or protein-only clustering methods. Collectively, this work addresses limitations present in the computational analyses of scRNA-seq data by providing novel methods and solutions that enhance scRNA-seq data preprocessing and clustering.

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.

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.

BACKGROUND: Previous work has shown that follicular dendritic cells (FDCs) play an important role in selecting B cells such that antigens are responded to in a specific manner. FcγRΙΙB (CD32) is an antibody constant-region receptor found on FDCs and mutation of this receptor in humans is associated with Systemic Lupus Erythematosus (SLE). In addition, previous work has demonstrated that autoreactive germinal centers are the product of expression of interferon alpha (ΙFNα) by FDCs, so FcγRIIB signaling may involve modulation of IFNα signaling. OBJECTIVE: Because FcγRIIB mutation is associated with SLE and FDCs have been shown to be important in orchestrating B cell responses, understanding FcγRIIB on FDCs helps characterize B cell repertoire development in response to antigen—whether the antigen is foreign or self, as is the case in autoimmunity. Better characterization of the role of FcγRIIB could have consequences for autoimmune and cancer therapy. This study seeks to determine the role of FcγRΙΙB on FDCs in germinal center B cell selection dynamics within single, autoreactive germinal centers. METHODS: This study compares transplanted wild-type (B6) B cells—that are driven to be autoimmune by simultaneously transplanted autoimmune B cells—in two stromal cell settings: first, in germinal centers containing wild-type FDCs and second, in germinal centers containing FcγRIIB-knockout FDCs. Transplanted B6 B cell populations express photoactivatable protein, which allows for sorting of B cells from individual germinal centers. B cell sequences from single germinal centers were analyzed to determine how focused each germinal center response was and how the B cells differ in maturity and affinity for antigen. Finally, mice expressing a lineage-tracing system were treated with IFNα in order to observe the cytokine’s effect on B cell selection. RESULTS: Cells sorted from germinal centers containing FcγRIIB-knockout FDCs contain a distinguished population of less-developed B cells, as quantified by population-based analysis of their variable heavy chain genes. Overall, the IgM sequences from B cells sorted from germinal centers (GCs) containing FcγRIIB-knockout follicular dendritic cells displayed lower levels of somatic hypermutation (SHM) (p<.05) and shorter hypervariable regions (CDR3) (p<.05) compared to other B cell populations. Values computed to summarize how many different B cell lineages were present in a GC—its “clonality”—did not vary between the two mouse populations, although FcγRIIB-knockout FDC germinal centers displayed a correlation between clonality and immunoglobulin (Ig) isotype expression (R2= .85). Finally, lineage tracing mice receiving injections of interferon alpha (IFNα) displayed no difference in GC clonality compared to those receiving vehicle and assays of IFNα downstream signaling genes also displayed no change. CONCLUSIONS: FcγRIIB encourages more stringent selection of immature B cells in germinal centers as evidenced by survival of less developed B cells as defined by degree of somatic hypermutation and CDR3 length in GCs comprising FcγRIIB-knockout FDCs. In spite of this, sequence-based measures of germinal center clonality as completed here may fail to capture the functional results of B cell selection. In addition, the link between FcγRIIB and IFNα requires further investigation. / 2019-07-03T00:00:00Z

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.

Clustering of single-cell RNA sequencing data is often used to show what states and subtypes cells have. Using this technique, striatal cells were clustered into subtypes using different clustering algorithms. Previously known subtypes were confirmed and new subtypes were found. One of them is a third medium spiny neuron subtype. Using the observed heterogeneity, as a second task, this project questions whether or not differences in individual neurons have an impact on the network dynamics. By clustering spiking activity from a neural network model, inconclusive results were found. Both algorithms indicating low heterogeneity, but by altering the quantity of a subtype between a low and high number, and clustering the network activity in each case, results indicate that there is an increase in the heterogeneity. This project shows a list of potential striatal subtypes and gives reasons to keep giving attention to biologically observed heterogeneity.

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

Die Alzheimer-Krankheit ist eine gewaltige Bedrohung für eine alternde Gesellschaft. Millionen von Menschen leben weltweit mit der Alzheimer-Krankheit, für die es keine aktuelle Behandlung gibt. Die Amyloidkaskaden-Hypothese (AKH) ist die aktuell am meisten akzeptierte Hypothese zur Ursache der Alzheimer-Krankheit. Die AKH bietet eine mechanistische Sicht auf die pathologische Kaskade, ausgehend von der Amyloid-Aggregation über die chronische Entzündung bis hin zur TAU-Pathologie. Die Medikamente, die auf der Grundlage der AKH entwickelt wurden, konnten Amyloid-Plaques bei Alzheimer-Patienten entfernen, brachten aber keine Verbesserung der kognitiven Fähigkeiten. Diese Misserfolge legen nahe, dass die Alzheimer-Krankheit nicht nur theoretisch im Rahmen der AKH betrachtet werden kann. Neuere Hypothesen kulminieren die Auswirkungen verschiedener Zelltypen (z.B. neurale Stammzellen, Astrozyten, Oligodendrozyten) auf den Ausbruch der Alzheimer-Erkrankung. Komplexe Rückkopplungs- und Feed-Forward-Mechanismen sind in der Pathophysiologie der Alzheimer-Demenz wahrscheinlich. Das Zusammenspiel zwischen der Pathologie und der Beteiligung anderer Zelltypen macht diese Krankheit multifaktoriell und komplex. Kürzlich zeigten zwei Studien (Moreno-Jimenez et al., 2019; Tobin et al., 2019), dass die Produktion neuer Neuronen im menschlichen Gehirn bei der Alzheimer-Erkrankung dramatisch abnimmt. Eine interessante Hypothese wurde durch diese Studien gestützt: Die pathologisch induzierte Erzeugung neuer Neuronen (regenerative Neurogenese) bei Alzheimer-Patienten könnte helfen, die Pathologie der Alzheimer-Erkrankung rückgängig zu machen. Da die Regenerationsfähigkeit bei Säugetieren entwicklungsmäßig wenig ausgeprägt ist (Tanaka und Ferretti, 2009), kann uns die Untersuchung der Neurodegeneration in einem Modellorganismus mit Regenerationsfähigkeit daher lehren, wie man die Proliferation und Neurogenese neuraler Stammzellen unter pathologischen Bedingungen induzieren kann. Für diese spezielle Frage können uns Modellorganismen mit natürlicher Regenerationsfähigkeit zeigen, wie man Proliferation und Neurogenese unter den pathologischen Bedingungen der Alzheimer-Erkrankung induzieren kann. Der Zebrafisch bietet eine beispiellose Möglichkeit, die Neurodegeneration und Regeneration zu modellieren, um die molekularen Mechanismen zu untersuchen, wie anhand der Neurogenese in Wirbeltiergehirnen die Alzheimer-Krankheit verbessert werden kann. Dies wurde in unserem Labor bereits in mehreren Publikationen gezeigt. Aus diesem Grund habe ich in meiner Doktorarbeit Zebrafische verwendet, um die Plastizität neuraler Stammzellen (NSZ) zu untersuchen. Besonders interessierte mich die Heterogenität von NSZ-Populationen in Bezug auf ihre molekularen Programme und die molekulare Grundlage der regenerativen Neurogenese von NSZ auf das Amyloid-β-42 (Aβ42) und TAU-Pathologien.

Tfap2a gehört zur Familie der AP-2-Transkriptionsfaktoren. Heterozygote Mutationen von TFAP2A im Menschen führen zum Branchio-Okulo-Fazialen-Syndrom (BOFS) und sind mit Nierenanomalien assoziiert. Molekulare Mechanismen, die zu diesen BOFS-assoziierten Nierenanomalien führen, sind noch unbekannt. In diesem Projekt wurde die Expression von Mitgliedern der AP-2-Familie in neugeborenen und erwachsenen Wildtyp-Mäusen analysiert. Tfap2a wurde in der Ureterknospe und der distalen Region des S-förmigen Körpers in den Nieren neugeborener Mäuse exprimiert. Die Expression blieb in ausgereiften distalen Tubuli und Sammelrohren erhalten. Tfap2b, ein zweites Mitglied der AP-2-Familie, das in der Niere exprimiert wird und mit Zystenbildung assoziiert ist, wurde im aufsteigenden Ast der Henleschen Schleife sowie in den distalen Tubuli und dem in der Nierenrinde liegenden Sammelrohr exprimiert. Um die Rolle von Tfap2a in der Niere zu untersuchen, wurden Mäuse mit einer sammelrohrspezifischen Deletion von Tfap2a (Tfap2a-KO) erzeugt. Phänotypische und morphologische Analysen ergaben, dass Tfap2a-KO-Mäuse mäßig reduzierte Nierengewichte und eine fortschreitende Dilatation der äußeren medullären Sammelrohre aufwiesen. Einzelkern- und RNA-Sequenzierung der Nieren adulter Mäuse zeigte eine deregulierte Expression von Genen, die mit der Organisation von Aktinfilamenten, Zelladhäsion, Wnt-Signalen und anderen Signalwegen der Nierenentwicklung in Verbindung stehen. In einem isolierten Modell von kultivierten Sammelrohrzellen mit einer Deletion von Tfap2a waren ähnliche Signalwege dereguliert. Insgesamt deutet diese Studie darauf hin, dass Tfap2a für die Differenzierung des Sammelrohrepithels und die Regulierung des Durchmessers des Tubuluslumens erforderlich ist. Dies ermöglicht Einblicke in die molekularen Grundlagen der beim BOFS beobachteten Nierenfehlbildungen. / The transcriptional regulator Tfap2a is part of the AP-2 transcription factor family. Heterozygous mutations of TFAP2A in humans lead to branchio-oculo-facial syndrome (BOFS) and are associated with renal anomalies. Molecular mechanisms leading to BOFS-associated renal anomalies are still unknown. In this project, expression patterns of AP-2 family members were analyzed in newborn and adult wildtype mice. Tfap2a was expressed in the ureteric bud and distal region of the S-shaped body in kidneys of newborn mice. Expression was maintained in mature distal tubules and collecting ducts. Tfap2b, a second AP-2 family member expressed in the kidney and associated with cyst formation, was found in the ascending limb and showed overlapping expression with Tfap2a in distal tubules and the cortical collecting duct. To investigate the role of Tfap2a in the kidney, mice with a collecting duct-specific deletion of Tfap2a (Tfap2a-KO) were generated by crossing mice carrying a Cre-recombinase under the Hoxb7 promotor and mice with floxed Tfap2a alleles. Phenotypic and morphological analyses revealed that Tfap2a-KO mice displayed moderately reduced kidney weights and a progressive dilation of outer medullary collecting ducts. Single-nucleus and bulk RNA sequencing of kidneys of three months old Tfap2a-KO mice and littermate controls indicated deregulated expression of genes associated with actin filament organization, cell adhesion, Wnt signaling, and other kidney developmental pathways. Genes deregulated in Tfap2a-deficient mice included several genes previously implicated in the development of congenital anomalies of the kidney and urinary tract. In an isolated model of cultured collecting duct cells carrying a Tfap2a knockout similar pathways were deregulated. Taking together, this study indicates that Tfap2a is required for collecting duct epithelium differentiation and tubular lumen diameter regulation, providing insights into the molecular basis of renal defects observed in BOFS.

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