Biology subjects

Eliscu, R.

Publications and source records attributed to Eliscu, R..

4 recordsLinked to original sources

bioRxiv2026

OMICON: a community resource for studying gene coexpression networks in normal and neoplastic human brain samples

Genome-wide coexpression analysis of intact tissue samples is a powerful approach for identifying reproducible signatures of cell types and states, since it can survey vast numbers of individuals, cells, and transcripts. However, it can be difficult to optimize gene coexpression network construction and compare results from independent analyses. To address these challenges, we developed OMICON (theomicon.ucsf.edu) for research on human brain gene coexpression networks. OMICON contains gene expression data from >17K normal and neoplastic human brain samples with standardized metadata. Systematic analysis of independent datasets identified >250K gene coexpression modules, which were characterized and compared via enrichment analysis with >40K gene sets. All modules are discoverable via an advanced search engine that can filter by genes, metadata, and enrichment results. Analyses can also be browsed with an interactive workflow visualization tool, and users can communicate within OMICON using @mention functionality to support communal research on human brain gene coexpression networks.

neuroscience↗

bioRxiv2026

A Neuronal Gene Expression Program Underlying Sustained Network Activity

Neurons function within interconnected networks and must continuously adjust their firing properties to maintain stable network activity. Although these adjustments require long-lasting molecular changes, the neuronal gene expression programs that support sustained network activity remain largely unknown. To address this, we developed CalTRAP-seq, a method for profiling gene expression in active neurons via calcium-dependent ribosome tagging. Applying CalTRAP-seq to primary neurons exhibiting synchronous network bursting revealed a gene expression program distinct from stimulus-induced immediate early gene responses, instead enriched for regulators of neuronal excitability. This program was accompanied by widespread alternative splicing of synaptic genes. Notably, neurons participating in network activity exhibited increased nuclear speckle formation, condensates implicated in splicing regulation. Disruption of nuclear speckles impaired synchronous burst dynamics. Together, these findings identify a gene expression program associated with sustained network activity that is complementary to stimulus-responsive gene expression, providing insight into how neurons coordinate gene expression to support stable network function.

neuroscience↗

bioRxiv2023

Clarifying the Transcriptional Profiles of Malignant Clones through Multiscale and Multiomic Analysis of Individual Tumors

Tumors may contain billions of cells including distinct malignant clones and nonmalignant cell types. Clarifying the evolutionary histories, prevalence, and defining molecular features of these cells is essential for improving clinical outcomes, since intratumoral heterogeneity provides fuel for acquired resistance to targeted therapies. Here we present a statistically motivated strategy for deconstructing intratumoral heterogeneity through multiomic and multiscale analysis of serial tumor sections (MOMA). By combining deep sampling of IDH-mutant astrocytomas with integrative analysis of single-nucleotide variants, copy-number variants, and gene expression, we reconstruct and validate the phylogenies, spatial distributions, and transcriptional profiles of distinct malignant clones. By genotyping nuclei analyzed by single-nucleus RNA-seq for truncal mutations, we further show that commonly used algorithms for identifying cancer cells from single-cell transcriptomes may be inaccurate. We also demonstrate that correlating gene expression with tumor purity in bulk samples can reveal optimal markers of malignant cells and use this approach to identify a core set of genes that is consistently expressed by astrocytoma truncal clones, including AKR1C3, whose expression is associated with poor outcomes in several types of cancer. In summary, MOMA provides a robust and flexible strategy for precisely deconstructing intratumoral heterogeneity and clarifying the core molecular properties of distinct cellular populations in solid tumors.

cancer biology↗

bioRxiv2022

Bulk and Mosaic Deletions of Egfr Reveal Regionally Defined Gliogenesis in the Developing Mouse Forebrain

The Epidermal growth factor receptor (EGFR) plays a role in cell proliferation and differentiation during healthy development and tumor growth, however its requirement for brain development remains unclear. Here we used a conditional mouse allele for Egfr to examine its contributions to perinatal forebrain development at the tissue level. Subtractive bulk ventral and dorsal forebrain deletions of Egfr uncovered significant and permanent decreases in oligodendrogenesis and myelination in the cortex and corpus callosum. Additionally, an increase in astrogenesis or reactive astrocytes in effected regions was evident in response to cortical scarring. Sparse deletion using Mosaic Analysis with Double Markers (MADM) surprisingly revealed a regional requirement for EGFR in rostrodorsal, but not ventrocaudal glial lineages including both astrocytes and oligodendrocytes. The EGFR-independent ventral glial progenitors may compensate for the missing EGFR-dependent dorsal glia in the bulk Egfr-deleted forebrain, potentially exposing a regenerative population of gliogenic progenitors in the mouse forebrain.

neuroscience↗