30,566 research outputs found

    Biochemical Dissection of Mer2 in Meiotic DNA Double-Strand Break Formation

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    Meiotic cell division is a critical step in sexual reproduction that leads to the formation of haploid gametes from a diploid cell. During genome reduction, the homologous chromosomes are segregated into daughter cells. To avoid missegregation, the chromosomes have to be physically linked via homologous recombination. This linkage is enabled by the repair of programmed double-stranded DNA breaks (DSBs) using the homologous chromosome as a repair template rather than the sister chromatid. Introducing DSBs in the genome is precarious and has to be strictly controlled to avoid irreparable damage to the organism itself and its offspring. The break site is localized by an H3K4me3 mark on nucleosomes, which is recognized by the PHD domain-containing protein Spp1. Spp1 interacts with the protein Mer2, which connects the break site with the break machinery, localized in the proximity of the chromosomal axis, via its binding to the axial proteins Hop1 and Red1. These interactions must take place at the right position in the chromosome at the right time in the cell cycle to form breaks. Although the mechanism of DSB control has been studied for many years, its underlying molecular details remain to be deciphered. To reveal the essential molecular elements involved in this process, I used Saccharomyces cerevisiae as a model organism and adopted an in vitro approach combining biochemical and structural methods on purified recombinant proteins. The DSB control was first explored by interaction experiments with Spp1, a nucleosome mark reader, and Mer2, a chromosomal axis interactor. The results demonstrate that they form a constitutive complex with 2:4 stoichiometry at low nanomolar affinity. Dimerization of Spp1 by Mer2 strengthens its interaction with the nucleosome. Moreover, not only Spp1 but also Mer2 is a novel nucleosome binder, forming a stable complex with recombinant nucleosomes in solution. The interaction of Mer2 with nucleosomes provides additional stability to the assembly, where Spp1 provides the specificity of the interaction and Mer2 the strength. Once the future DNA break site is localized via its interaction with Spp1 and Mer2, it must interact with the chromosomal axis formed by Hop1-Red1 and cohesin, where the break machinery is. My data reveal that the conserved C-terminal region of Mer2 specifically interacts with an axis-bound Hop1 to ensure that breaks are made only when the chromosomal axis is properly formed. An additional level of control is provided by the conserved N-terminal region of Mer2, which is crucial for DSB formation. The N-terminal region establishes a previously undescribed connection with protein Mre11, which is responsible for resection of the DSBs, thus demonstrating that the factors both to create DNA break and repair it have to be in place before the break occurs. Collectively, these findings reveal that Mer2 serves as an interaction platform for proteins involved in the control of DSBs, rendering it an essential component of proper DSB formation and resection. Moreover, they provide insights into the molecular details of DSB control and serve as a foundation for further studies of meiotic DSB formation. Illuminating previously unnoticed levels of DSB control significantly extends our understanding of the process of homologous recombination and, ultimately, meiosis as a whole.Die Dissertation ist gesperrt bis zum 01.05.2024

    Genomic and microscopic dissection of large-scale chromatin compaction

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    Large-scale chromatin compaction varies across the human genome, and these variations correlate with differences in transcriptional activity in a limited number of model systems. However, without validated genome-wide methods directly measuring large-scale chromatin compaction, the degree to which this level of chromatin organization correlates with defined features of genome organization remains unknown. Existing methods assess chromatin compaction indirectly, based on, for example, the accessibility of DNA to enzymes or susceptibility to mechanical shear, and probe lower--level chromatin organization, primarily at the nucleosome level. Therefore, these existing measures of chromatin compaction may not translate to measurements of large-scale chromatin compaction. In this dissertation I explore new methods for measuring large-scale chromatin compaction using genomic and microcopic tools. I have developed a new genomic method, based on TSA-seq, to measure chromatin compaction. TSA-Seq is a genomic method that directly probes the average physical distances of chromosome loci relative to different nuclear structures. Here I use the first derivative, or slope, of the TSA-Seq signal to identify unusually decondensed large-scale chromatin domains (DLCDs). These DLCDs have an average size of ~70 kb and correlate with nearby enrichment of active chromatin marks, enhancers and especially super-enhancers, and cohesin and CTCF binding sites. They map closely to a large fraction of genome organization domain boundaries identified by Hi-C, LAD/innerLAD boundaries defined by lamin B1 DamID, and rapid transitions in the Hi-C principal eigenvector signal. Moreover, cluster analysis reveals DLCDs map most frequently to divisions between chromatin domains of varying epigenetic marks. To validate the existence of DLCDs, I have created a digital image processing package, Angler, for analyzing DNA--FISH experiments with minimal supervision using established computer vision algorithms. Angler can measure spatial properties of FISH loci in a high throughput manner. In conclusion, my results demonstrate the non-random placement of large-scale chromatin decondensed regions, which may contribute to the functional division of the genome into discrete and independently-regulated chromatin domains.U of I OnlyAuthor requested U of Illinois access only (OA after 2yrs) in Vireo ETD syste

    Studying the interplay between ageing and Parkinson's disease using the zebrafish model

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    Parkinson’s disease (PD) is a neurodegenerative disorder characterised by the loss of dopaminergic neurons in the substantia nigra. Ageing is the major risk factor for developing PD but the interplay between ageing and PD remains elusive. To investigate the effect of ageing on PD-relevant pathological mechanisms, zebrafish mutant lines harbouring mutations in ageing-associated genes (klotho-/-, sirt1-/-, satb1a-/-, satb1b-/- and satb1a-/-;satb1b-/-) were generated, using CRISPR/Cas9 gene editing. Likewise, a chemical model for SIRT1 deficiency was utilised. klotho-/- zebrafish displayed an accelerated ageing phenotype at 3mpf and reduced survival to 6mpf. Dopaminergic neuron number, MPP+ susceptibility and microglial number were unaffected in klotho-/- larvae. NAD+ levels were decreased in 6mpf klotho-/- brains. However, ATP levels and DNA damage were unaffected. sirt1-/- zebrafish did not display a phenotype through adulthood. il-1β and il-6 were not upregulated in sirt1-/- larvae, and chemical inhibition of sirt1 did not increase microglial number. cdkn1a, il-1β and il-6 were not upregulated in satb1a-/- and satb1b-/- larvae. Dopaminergic neuron number and MPP+ susceptibility were unaffected in satb1a-/- larvae. However, satb1b-/- larvae demonstrated a moderate decrease in dopaminergic neuron number but equal susceptibility to MPP+ as satb1b+/+ larvae. Adult satb1a-/- but not adult satb1b-/- zebrafish were emaciated. satb1a-/-;satb1b-/- zebrafish did not display a phenotype through adulthood. Transgenic zebrafish expressing human wildtype α-Synuclein (Tg(eno2:hsa.SNCA-ires-EGFP)) were crossed with klotho-/- and sirt1-/- zebrafish, and treated with a sirt1-specific inhibitor. Neither genetic cross affected survival. The klotho mutation did not increase microglial number in Tg(eno2:hsa.SNCA-ires-EGFP) larvae. Likewise, sirt1 inhibition did not induce motor impairment or cell death in Tg(eno2:hsa.SNCA-ires-EGFP) larvae. In conclusion, the suitability of zebrafish for studying ageing remains elusive, as only 1 ageing-associated mutant line displayed accelerated ageing. However, zebrafish remain an effective model for studying PD-relevant pathological mechanisms due to the availability of CRISPR/Cas9 gene editing, neuropathological and neurobehavioral tools

    Using machine learning to predict pathogenicity of genomic variants throughout the human genome

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    Geschätzt mehr als 6.000 Erkrankungen werden durch Veränderungen im Genom verursacht. Ursachen gibt es viele: Eine genomische Variante kann die Translation eines Proteins stoppen, die Genregulation stören oder das Spleißen der mRNA in eine andere Isoform begünstigen. All diese Prozesse müssen überprüft werden, um die zum beschriebenen Phänotyp passende Variante zu ermitteln. Eine Automatisierung dieses Prozesses sind Varianteneffektmodelle. Mittels maschinellem Lernen und Annotationen aus verschiedenen Quellen bewerten diese Modelle genomische Varianten hinsichtlich ihrer Pathogenität. Die Entwicklung eines Varianteneffektmodells erfordert eine Reihe von Schritten: Annotation der Trainingsdaten, Auswahl von Features, Training verschiedener Modelle und Selektion eines Modells. Hier präsentiere ich ein allgemeines Workflow dieses Prozesses. Dieses ermöglicht es den Prozess zu konfigurieren, Modellmerkmale zu bearbeiten, und verschiedene Annotationen zu testen. Der Workflow umfasst außerdem die Optimierung von Hyperparametern, Validierung und letztlich die Anwendung des Modells durch genomweites Berechnen von Varianten-Scores. Der Workflow wird in der Entwicklung von Combined Annotation Dependent Depletion (CADD), einem Varianteneffektmodell zur genomweiten Bewertung von SNVs und InDels, verwendet. Durch Etablierung des ersten Varianteneffektmodells für das humane Referenzgenome GRCh38 demonstriere ich die gewonnenen Möglichkeiten Annotationen aufzugreifen und neue Modelle zu trainieren. Außerdem zeige ich, wie Deep-Learning-Scores als Feature in einem CADD-Modell die Vorhersage von RNA-Spleißing verbessern. Außerdem werden Varianteneffektmodelle aufgrund eines neuen, auf Allelhäufigkeit basierten, Trainingsdatensatz entwickelt. Diese Ergebnisse zeigen, dass der entwickelte Workflow eine skalierbare und flexible Möglichkeit ist, um Varianteneffektmodelle zu entwickeln. Alle entstandenen Scores sind unter cadd.gs.washington.edu und cadd.bihealth.org frei verfügbar.More than 6,000 diseases are estimated to be caused by genomic variants. This can happen in many possible ways: a variant may stop the translation of a protein, interfere with gene regulation, or alter splicing of the transcribed mRNA into an unwanted isoform. It is necessary to investigate all of these processes in order to evaluate which variant may be causal for the deleterious phenotype. A great help in this regard are variant effect scores. Implemented as machine learning classifiers, they integrate annotations from different resources to rank genomic variants in terms of pathogenicity. Developing a variant effect score requires multiple steps: annotation of the training data, feature selection, model training, benchmarking, and finally deployment for the model's application. Here, I present a generalized workflow of this process. It makes it simple to configure how information is converted into model features, enabling the rapid exploration of different annotations. The workflow further implements hyperparameter optimization, model validation and ultimately deployment of a selected model via genome-wide scoring of genomic variants. The workflow is applied to train Combined Annotation Dependent Depletion (CADD), a variant effect model that is scoring SNVs and InDels genome-wide. I show that the workflow can be quickly adapted to novel annotations by porting CADD to the genome reference GRCh38. Further, I demonstrate the integration of deep-neural network scores as features into a new CADD model, improving the annotation of RNA splicing events. Finally, I apply the workflow to train multiple variant effect models from training data that is based on variants selected by allele frequency. In conclusion, the developed workflow presents a flexible and scalable method to train variant effect scores. All software and developed scores are freely available from cadd.gs.washington.edu and cadd.bihealth.org

    Studies on genetic and epigenetic regulation of gene expression dynamics

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    The information required to build an organism is contained in its genome and the first biochemical process that activates the genetic information stored in DNA is transcription. Cell type specific gene expression shapes cellular functional diversity and dysregulation of transcription is a central tenet of human disease. Therefore, understanding transcriptional regulation is central to understanding biology in health and disease. Transcription is a dynamic process, occurring in discrete bursts of activity that can be characterized by two kinetic parameters; burst frequency describing how often genes burst and burst size describing how many transcripts are generated in each burst. Genes are under strict regulatory control by distinct sequences in the genome as well as epigenetic modifications. To properly study how genetic and epigenetic factors affect transcription, it needs to be treated as the dynamic cellular process it is. In this thesis, I present the development of methods that allow identification of newly induced gene expression over short timescales, as well as inference of kinetic parameters describing how frequently genes burst and how many transcripts each burst give rise to. The work is presented through four papers: In paper I, I describe the development of a novel method for profiling newly transcribed RNA molecules. We use this method to show that therapeutic compounds affecting different epigenetic enzymes elicit distinct, compound specific responses mediated by different sets of transcription factors already after one hour of treatment that can only be detected when measuring newly transcribed RNA. The goal of paper II is to determine how genetic variation shapes transcriptional bursting. To this end, we infer transcriptome-wide burst kinetics parameters from genetically distinct donors and find variation that selectively affects burst sizes and frequencies. Paper III describes a method for inferring transcriptional kinetics transcriptome-wide using single-cell RNA-sequencing. We use this method to describe how the regulation of transcriptional bursting is encoded in the genome. Our findings show that gene specific burst sizes are dependent on core promoter architecture and that enhancers affect burst frequencies. Furthermore, cell type specific differential gene expression is regulated by cell type specific burst frequencies. Lastly, Paper IV shows how transcription shapes cell types. We collect data on cellular morphologies, electrophysiological characteristics, and measure gene expression in the same neurons collected from the mouse motor cortex. Our findings show that cells belonging to the same, distinct transcriptomic families have distinct and non-overlapping morpho-electric characteristics. Within families, there is continuous and correlated variation in all modalities, challenging the notion of cell types as discrete entities

    Structural and mechanistic insights into the DNA glycosylase AAG-mediated base excision in nucleosome

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    Abstract The engagement of a DNA glycosylase with a damaged DNA base marks the initiation of base excision repair. Nucleosome-based packaging of eukaryotic genome obstructs DNA accessibility, and how DNA glycosylases locate the substrate site on nucleosomes is currently unclear. Here, we report cryo-electron microscopy structures of nucleosomes bearing a deoxyinosine (DI) in various geometric positions and structures of them in complex with the DNA glycosylase AAG. The apo nucleosome structures show that the presence of a DI alone perturbs nucleosomal DNA globally, leading to a general weakening of the interface between DNA and the histone core and greater flexibility for the exit/entry of the nucleosomal DNA. AAG makes use of this nucleosomal plasticity and imposes further local deformation of the DNA through formation of the stable enzyme–substrate complex. Mechanistically, local distortion augmentation, translation/rotational register shift and partial opening of the nucleosome are employed by AAG to cope with substrate sites in fully exposed, occluded and completely buried positions, respectively. Our findings reveal the molecular basis for the DI-induced modification on the structural dynamics of the nucleosome and elucidate how the DNA glycosylase AAG accesses damaged sites on the nucleosome with different solution accessibility

    Transient drought during flowering modifies the grain proteome of bread winter wheat

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    Drought is among the most limiting factors for sustainable agricultural production. Water shortage at the onset of flowering severely affects the quality and quantity of grain yield of bread wheat (Triticum aestivum). Herein, we measured oxidative stress and photosynthesis-related parameters upon applying transient drought on contrasting wheat cultivars at the flowering stage of ontogenesis. The sensitive cultivar (Darunok Podillia) showed ineffective water management and a more severe decline in photosynthesis. Apparently, the tolerant genotype (Odeska 267) used photorespiration to dissipate excessive light energy. The tolerant cultivar sooner induced superoxide dismutase and showed less inhibited photosynthesis. Such a protective effect resulted in less affected yield and spectrum of seed proteome. The tolerant cultivar had a more stable gluten profile, which defines bread-making quality, upon drought. Water deficit caused the accumulation of medically relevant proteins: (i) components of gluten in the sensitive cultivar and (ii) metabolic proteins in the tolerant cultivar. We propose specific proteins for further exploration as potential markers of drought tolerance for guiding efficient breeding: thaumatin-like protein, 14-3-3 protein, peroxiredoxins, peroxidase, FBD domain protein, and Ap2/ERF plus B3 domain protein
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