Javaid, T. | bioRxiv Science

bioRxiv2026

Psi represses EGFR signalling in the neural stem cell niche to inhibit neuroblast proliferation in the Drosophila brain

In mammals, neural stem cells (NSCs) generate the neurons and glia essential to brain development, while defective NSCs drive brain cancer (glioma). NSC fate is not only controlled cell intrinsically, but also relies on signalling from the cellular microenvironment, or stem cell niche. Defective communication between NSCs and their niche can, therefore, drive stem cell renewal over differentiation to promote glioma. Here, we demonstrate that the orthologue of glioma-driver mutation FUBP1, Drosophila Psi, is essential in the cortex glia, the NSC niche, for preventing NSC overproliferation. We further demonstrate that Psi controls NSC fate through direct transcriptional repression of EGFR ligands, spitz (spi) and gurken (grk); with spi required cell intrinsically to enable proliferative growth of cortex glia, while grk functions cell extrinsically to control NSC fate. These observations highlight the complexity of EGFR function in modulating communication between NSCs and their niche. Our findings demonstrate the importance of understanding the nuances of intrinsic and extrinsic control of NSC fate, mechanisms of cell-cell communication critical to animal development that will provide insight into FUBP1/EGFR-driven glioma.

developmental biology↗

bioRxiv2024

High-Accuracy RNA Integrity Definition for Unbiased Transcriptome Comparisons with INDEGRA

RNA sample integrity variability introduces biases and obscures natural RNA degradation, posing a significant challenge in transcriptomics. To address this, we developed the Direct Transcriptome Integrity (DTI) measure, a universal and robust RNA integrity metric based on nanopore sequencing. By accurately modeling RNA fragmentation, DTI provides a reliable assessment of sample quality. Integrated into the INDEGRA package (freely available at https://github.com/Arnaroo/INDEGRA), we provide tools to correct false discoveries and enable precise differential expression and RNA degradation analyses, even for challenging sample types. INDEGRA software can be used to accurately measure RNA DTI stability metric, isolate biological component of RNA degradation from technical biases, compare biological RNA stability transcriptome-wide and suppress false degradation-induced differential gene expression hits to allow broad comparisons across samples of different quality DTI offers a straightforward and accurate method for assessing RNA degradation, characterizing both overall sample integrity and transcript-specific degradation rates using direct RNA sequencing (DRS) data. Calculated through INDEGRA, DTI reveals inter- and intra-transcript variability in degradation, while INDEGRA separates RNA degradation from mapping inaccuracies, and connects degradation profiles to RNA fragmentation rates. By leveraging INDEGRA, researchers can minimize false differential transcript abundance findings caused by variations in overall sample integrity, while preserving genuine transcript-specific differences in stability and degradation. INDEGRA supports integration with widely used differential transcript abundance tools like DESeq2, limma-voom, and edgeR, enabling seamless analysis pipelines. INDEGRA enhances the accuracy and reliability of RNA quantification in high-throughput data and simplifies comparisons across diverse transcriptomic datasets, including those derived from different tissues, species, or experimental protocols.

bioinformatics↗