Project description:The developing brain has a complex and well-organized anatomical structure comprising different types of neural and non-neural cells. Stem cells, progenitors, and newborn neurons tightly interact with their neighbouring cells and tissue microenvironment, and this intricate interplay ultimately shapes the output of neurogenesis. Given the relevance of spatial cues during brain development, we acknowledge the necessity for a transcriptomics atlas within the tissue context accessible to the neurodevelopmental community. To fulfil this need, we offer an open-access spatial gene expression browser of the embryonic mouse brain at the peak of neurogenesis. Using 10x Visium technology, we generated spatially-resolved RNAseq data from E13.5 embryonic brain sections. Unsupervised clustering reliably defined specific cell type populations of diverse lineages and maturational states. Differential expression analysis revealed unique transcriptional signatures across specific embryonic brain areas, uncovering novel features inherent to particular anatomical domains. Furthermore, we integrated single-cell RNAseq data from E13.5 mouse brains into our Spatial Transcriptomics data, adding tissue context to single-cell resolution. In summary, we provide a valuable tool that enables the exploration and discovery of unforeseen molecular players involved in neurogenesis, particularly in the crosstalk between different cell types.
Project description:Protein kinase signalling is a major mechanism by which embryonic stem cell pluripotency and differentiation is controlled. However, the pathways and components that regulate embryonic stem cell identity have not been systematically defined. Here, we employ FGF4 signalling as a model system to investigate phosphoproteome dynamics in differentiating mouse embryonic stem cells. We report identification and quantitation of more than 10,000 phosphopeptides, of which hundreds of phosphophoylation sites are regulated more than 2-fold by acute FGF4 stimulation. We hypothesise that phosphorylation sites in this dataset are relevant for regulating the transition of mouse embryonic stem cells from pluripotency towards lineage specific differentiation.
Project description:Genome-wide transcriptome analyses have allowed for systems- level insights into gene regulatory networks. Due to the limited depth of quantitative proteomics, however, our understanding of post-transcriptional gene regulation and its effects on protein complex stoichiometry are lagging behind. Here, we employ deep sequencing and iTRAQ technology to determine transcript and protein expression changes of a Drosophila brain tumour model at near genome-wide resolution. In total, we quantify more than 6,200 tissue-specific proteins, corresponding to about 70% of all transcribed protein-coding genes. Using our integrated data set, we demonstrate that post-transcriptional gene regulation varies considerably with biological function and is surprisingly high for genes regulating transcription. We combine our quantitative data with protein-protein interaction data and show that post-transcriptional mechanisms significantly enhance co-regulation of protein complex subunits beyond transcriptional co-regulation. Interestingly, our results suggest that only about 11% of the annotated Drosophila protein complexes are co-regulated in the brain. Finally, we refine the composition of some of these core protein complexes by analysing the co-regulation of potential subunits. Our comprehensive transcriptome and proteome data provide a rich resource for quantitative biology and offer novel insights into understanding post- transcriptional gene regulation in a tumour model. Transcriptomes of 1-3 day old adult female Drosophila melanogaster heads of control and brat mutant were generated by deep sequencing, in triplicate, using Illumina GAIIx.
Project description:Chickarmane2006 - Stem cell switch reversible
Kinetic modeling approach of the transcriptional dynamics of the embryonic stem cell switch.
This model is described in the article:
Transcriptional dynamics of the embryonic stem cell switch.
Chickarmane V, Troein C, Nuber UA, Sauro HM, Peterson C
PLoS Computational Biology. 2006; 2(9):e123
Abstract:
Recent ChIP experiments of human and mouse embryonic stem cells have elucidated the architecture of the transcriptional regulatory circuitry responsible for cell determination, which involves the transcription factors OCT4, SOX2, and NANOG. In addition to regulating each other through feedback loops, these genes also regulate downstream target genes involved in the maintenance and differentiation of embryonic stem cells. A search for the OCT4-SOX2-NANOG network motif in other species reveals that it is unique to mammals. With a kinetic modeling approach, we ascribe function to the observed OCT4-SOX2-NANOG network by making plausible assumptions about the interactions between the transcription factors at the gene promoter binding sites and RNA polymerase (RNAP), at each of the three genes as well as at the target genes. We identify a bistable switch in the network, which arises due to several positive feedback loops, and is switched on/off by input environmental signals. The switch stabilizes the expression levels of the three genes, and through their regulatory roles on the downstream target genes, leads to a binary decision: when OCT4, SOX2, and NANOG are expressed and the switch is on, the self-renewal genes are on and the differentiation genes are off. The opposite holds when the switch is off. The model is extremely robust to parameter changes. In addition to providing a self-consistent picture of the transcriptional circuit, the model generates several predictions. Increasing the binding strength of NANOG to OCT4 and SOX2, or increasing its basal transcriptional rate, leads to an irreversible bistable switch: the switch remains on even when the activating signal is removed. Hence, the stem cell can be manipulated to be self-renewing without the requirement of input signals. We also suggest tests that could discriminate between a variety of feedforward regulation architectures of the target genes by OCT4, SOX2, and NANOG.
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