Search bioRxivSearch

bioRxiv · 10.1101/2019.12.30.891168

Induction of Recurrent Break Cluster Genes in Neural Progenitor Cells Differentiated from Embryonic Stem Cells In Culture

Abstract

Mild replication stress enhances appearance of dozens of robust recurrent genomic break clusters, termed RDCs, in cultured primary mouse neural stem and progenitor cells (NSPCs). Robust RDCs occur within genes ("RDC-genes") that are long and have roles in neural cell communications and/or have been implicated in neuropsychiatric diseases or cancer. We sought to develop an in vitro approach to determine whether specific RDC formation is associated with neural development. For this purpose, we adapted a system to induce neural progenitor cell (NPC) development from mouse embryonic stem cell (ESC) lines deficient for XRCC4 plus p53, a genotype that enhances DNA double-strand break (DSB) persistence to enhance detection. We tested for RDCs by our genome wide DSB identification approach that captures DSBs genome-wide via their ability to join to specific genomic Cas9/sgRNA-generated bait DSBs. In XRCC4/p53-deficient ES cells, we detected 7 RDCs, which were in genes, with two RDCs being robust. In contrast, in NPCs derived from these ES cell lines, we detected 29 RDCs, a large fraction of which were robust and associated with long, transcribed neural genes that were also robust RDC-genes in primary NSPCs. These studies suggest that many RDCs present in NSPCs are developmentally influenced to occur in this cell type and indicate that induced development of NPCs from ES cells provides an approach to rapidly elucidate mechanistic aspects of NPC RDC formation. SIGNIFICANCE STATEMENTWe previously discovered a set of long neural genes susceptible to frequent DNA breaks in primary mouse brain progenitor cells. We termed these genes RDC-genes. RDC-gene breakage during brain development might alter neural gene function and contribute to neurological diseases and brain cancer. To provide an approach to characterize the unknown mechanism of neural RDC-gene breakage, we asked whether RDC-genes appear in neural progenitors differentiated from embryonic stem cells in culture. Indeed, robust RDC-genes appeared in neural progenitors differentiated in culture and many overlapped with robust RDC-genes in primary brain progenitors. These studies indicate that in vitro development of neural progenitors provides a model system for elucidating how RDC-genes are formed.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Tena, A., Zhang, Y., Kyritsis, N., Devorak, A., Zurita, J., Wei, P.-C., Alt, F. W.. 2019-12-30. Induction of Recurrent Break Cluster Genes in Neural Progenitor Cells Differentiated from Embryonic Stem Cells In Culture. https://doi.org/10.1101/2019.12.30.891168

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

The Unreasonable Effectiveness of Cell Types in Describing Neuronal Physiological Features

Single-cell RNA sequencing (scRNA-seq) captures detailed gene expression profiles at scale, while patch-clamp recordings measure intrinsic neuronal electrophysiological properties. Modeling the relations between these two modalities remains a challenge. Here, we compare how well electrophysiological features can be predicted by traditional transcriptomic cell type classification, representations derived from a foundational model (scGPT) pretrained on large-scale scRNA-seq datasets, ion channel-coding genes, and highly variable genes. Using paired transcriptomic and electrophysiological patch-sequencing data from 495 human neurons from neurosurgical tissue, we find that cluster-level cell type representations consistently outperform highly variable gene selection, ion channel gene selection, and context-enriched scGPT embeddings. Notably, performance varies across model architectures and initializations, and the best results are obtained by combining the outputs of separate cell type and scGPT-based models. Together, these findings suggest that traditional discrete cellular classification is highly effective in predicting physiological features. For maximum performance it can be complemented by pretrained transformer models.

neuroscience

A nonlinear inhibition pathway underlying cortical responses to tuned holographic optogenetic perturbations

Optogenetics enables causal manipulation of cortical activity. Perturbation responses can be counterintuitive due to network interactions, making theory essential for predicting them. Existing approaches often rely on linear approximations, which fail for many biologically relevant perturbations. Here we develop a nonlinear theory of responses to holographic perturbations in cell-type-specific recurrent networks with structured connectivity. We fit a nonlinear model to mouse V1 data, which shows cotuned-ensemble suppression: perturbing spatially clustered neurons with similar preferred orientations yields markedly stronger short-range suppression than perturbing untuned ensembles. We show that cotuned-ensemble suppression arises from a feature-tuned, nonlinear inhibition pathway implicating somatostatin-positive (SST) interneurons. The theory predicts that cotuned ensembles suppress parvalbumin-positive (PV) neurons but facilitate SST neurons, and links the degree of cotuned-ensemble suppression or facilitation to the variance of the SST response. This framework identifies mechanisms by which nonlinear inhibition sculpts cortical dynamics and establishes a predictive basis for targeted optogenetic interventions.

neuroscience

Proteomic signatures of APOE ε4 across human tissues and cell types in Alzheimers disease

The apolipoprotein E {varepsilon}4 (APOE {varepsilon}4) allele is the strongest genetic risk factor for late-onset Alzheimers disease (AD). However, the underlying molecular mechanisms remain unclear. This study included 1691 participants from the Religious Orders Study and Rush Memory and Aging Project (ROSMAP), 1226 participants from the Accelerating Medicines Partnership - Alzheimers Disease (AMP-AD) Diverse Cohorts Study, and 735 participants from the Alzheimers Disease Neuroimaging Initiative (ADNI). To characterise APOE {varepsilon}4 molecular effects, we analysed proteomic data from plasma, cerebrospinal fluid (CSF), and induced pluripotent stem cell (iPSC)-derived astrocytes and neurons, as well as transcriptomic and proteomic data from multiple brain regions. The association of APOE {varepsilon}4 with AD neuropathology was also examined. APOE {varepsilon}4 carriers shared a plasma proteomic signature enriched for immune processes, irrespective of AD diagnosis. A machine learning classifier trained on this signature discriminated APOE {varepsilon}4 carriers from non-carriers in an independent cohort using CSF proteomics. APOE {varepsilon}4 carriage was associated with higher Braak stages and Consortium to Establish a Registry for Alzheimers Disease (CERAD) score. However, only limited APOE {varepsilon}4-associated transcriptomic and proteomic changes were observed in bulk brain tissue, with poor cross-layer concordance. Proteomic analyses of iPSC-derived astrocytes and neurons further revealed cell-type-specific APOE {varepsilon}4-associated changes. APOE {varepsilon}4 is associated with a consistent proteomic signature across plasma and CSF. Its molecular effects in the brain differ across cell types, brain regions and molecular layers. These findings support the need for cell-type-resolved multi-omic studies to elucidate how APOE {varepsilon}4 confers AD risk.

neuroscience