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Engineering Artificial Factors to Specifically Manipulate Alternative Splicing in Human Cells
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Reverse engineering neuron-type-specific and type-orthogonal splicing-regulatory networks using diverse cellular

Daniel F Moakley1, Melissa Campbell1, Miquel Anglada-Girotto2

  • 1Department of Systems Biology, Columbia University, New York, NY 10032, USA; Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10032, USA; Center for Motor Neuron Biology and Disease, Columbia University, New York, NY 10032, USA.

Cell Reports
|June 25, 2025
PubMed
Summary
This summary is machine-generated.

This study maps RNA-binding protein (RBP) regulation of alternative splicing (AS) across 133 mouse neocortical cell types. We identified key RBPs, like Elavl2, driving cell-type-specific splicing patterns in neurons.

Keywords:
CP: Molecular biologyCP: NeuroscienceElavl2RNA splicing regulationRNA-binding proteinsnetwork inferenceneuronal subtypes

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Area of Science:

  • Neuroscience
  • Molecular Biology
  • Computational Biology

Background:

  • Alternative splicing (AS) generates diverse gene isoforms crucial for neuron type-specific functions.
  • Existing research on RNA-binding proteins (RBPs) and AS is limited to a few neuron types, necessitating comprehensive analysis.

Purpose of the Study:

  • To create a holistic map of the alternative splicing regulatory landscape across 133 mouse neocortical cell types.
  • To identify RNA-binding proteins (RBPs) and their cell-type-specific activities that control alternative splicing (AS).

Main Methods:

  • Network reverse engineering was applied to pseudobulk transcriptomes from single-cell RNA sequencing data.
  • Inferred regulons of 350 RBPs and their cell-type-specific activities.
  • Validated Elavl2's role in medial ganglionic eminence (MGE)-specific splicing using an in vitro embryonic stem cell (ESC) differentiation system.

Main Results:

  • A comprehensive map of the neuron-type-specific AS regulatory landscape was generated for 133 mouse neocortical cell types.
  • The regulons and cell-type-specific activities of 350 RBPs were inferred.
  • Elavl2 was validated as a key RBP for MGE-specific splicing in GABAergic interneurons.
  • A module of exons and candidate regulators specific to long- and short-projection neurons was identified.

Conclusions:

  • This study provides a valuable resource for understanding splicing regulatory programs that contribute to neuronal molecular diversity.
  • The findings reveal splicing regulation that may not be captured by gene expression-based classifications.
  • Identified RBPs and splicing modules offer insights into the mechanisms driving neuronal heterogeneity.