Dataset Information

Multiomic Analysis of Neurons with Divergent Projection Patterns Identifies Novel Regulators of Axon Pathfinding.

ABSTRACT: Axon pathfinding is a key step in neural circuits formation. However, the transcriptional mechanisms regulating its progression remain poorly understood. The binary decision of crossing or avoiding the midline taken by some neuronal axons during development represents a robust model to investigate the mechanisms that control the selection of axonal trajectories. Here, to identify novel regulators of axon guidance, this work compares the transcriptome and chromatin occupancy profiles of two neuronal subpopulations, ipsilateral (iRGC) and contralateral retinal ganglion cells (cRGC), with similar functions but divergent axon trajectories. These analyses retrieved a number of genes encoding for proteins not previously implicated in axon pathfinding. In vivo functional experiments confirm the implication of some of these candidates in axonal navigation. Among the candidate genes, γ-synuclein is identified as essential for inducing midline crossing. Footprint and luciferase assays demonstrate that this small-sized protein is regulated by the transcription factor (TF) Pou4f1 in cRGCs. It is also shown that Lhx2/9 are specifically expressed in iRGCs and control a program that partially overlaps with that regulated by Zic2, previously described as essential for iRGC specification. Overall, the analyses identify dozens of new molecules potentially involved in axon guidance and reveal the regulatory logic behind the selection of axonal trajectories.

SUBMITTER: Fernandez-Nogales M

PROVIDER: S-EPMC9561852 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature

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Multiomic Analysis of Neurons with Divergent Projection Patterns Identifies Novel Regulators of Axon Pathfinding.

Fernández-Nogales Marta M López-Cascales Maria Teresa MT Murcia-Belmonte Verónica V Escalante Augusto A Fernández-Albert Jordi J Muñoz-Viana Rafael R Barco Angel A Herrera Eloísa E

Advanced science (Weinheim, Baden-Wurttemberg, Germany) 20220821 29

Axon pathfinding is a key step in neural circuits formation. However, the transcriptional mechanisms regulating its progression remain poorly understood. The binary decision of crossing or avoiding the midline taken by some neuronal axons during development represents a robust model to investigate the mechanisms that control the selection of axonal trajectories. Here, to identify novel regulators of axon guidance, this work compares the transcriptome and chromatin occupancy profiles of two neuro ...[more]

PMID: 35988153

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Project description:Projection neurons are the commonest neuronal type in the mammalian forebrain and their individual characterization is a crucial step to understand how neural circuitry operates. These cells have an axon whose arborizations extend over long distances, branching in complex patterns and/or in multiple brain regions. Axon length is a principal estimate of the functional impact of the neuron, as it directly correlates with the number of synapses formed by the axon in its target regions; however, its measurement by direct 3D axonal tracing is a slow and labor-intensive method. On the contrary, axon length estimations have been recently proposed as an effective and accessible alternative, allowing a fast approach to the functional significance of the single neuron. Here, we analyze the accuracy and efficiency of the most used length estimation tools-design-based stereology by virtual planes or spheres, and mathematical correction of the 2D projected-axon length-in contrast with direct measurement, to quantify individual axon length. To this end, we computationally simulated each tool, applied them over a dataset of 951 3D-reconstructed axons (from NeuroMorpho.org), and compared the generated length values with their 3D reconstruction counterparts. The evaluated reliability of each axon length estimation method was then balanced with the required human effort, experience and know-how, and economic affordability. Subsequently, computational results were contrasted with measurements performed on actual brain tissue sections. We show that the plane-based stereological method balances acceptable errors (~5%) with robustness to biases, whereas the projection-based method, despite its accuracy, is prone to inherent biases when implemented in the laboratory. This work, therefore, aims to provide a constructive benchmark to help guide the selection of the most efficient method for measuring specific axonal morphologies according to the particular circumstances of the conducted research.

Dataset Information

Multiomic Analysis of Neurons with Divergent Projection Patterns Identifies Novel Regulators of Axon Pathfinding.

Publications

Multiomic Analysis of Neurons with Divergent Projection Patterns Identifies Novel Regulators of Axon Pathfinding.

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