Date of Award

1-1-2022

Degree Type

Thesis

Degree Name

Master of Science in Interdisciplinary Neurosciences

Department

Interdisciplinary Neuroscience

First Advisor

Ying Zhang

Abstract

Neurons have been shown to undergo structural and functional plasticity in response to salient experiences. For example, motor skill learning induces plasticity of neurons in the primary motor cortex (M1). Specifically, layer 2/3 glutamatergic neurons (L2/3) exhibit high plasticity during early learning of a motor task, adding and retracting spines on the order of days. With the advance of single-cell and single-nucleus sequencing (sc- and snRNA-seq), studies have been able to further explore the transcriptomic changes underlying neural plasticity and learning in various brain regions. However, it remains to identify the plasticity states and their accompanying gene expression profiles that emerge during motor learning in M1. In our collaborative project MEMOry from NETwork (MEMONET), we aimed to uncover the transcriptomic signatures of motor skill learning in mouse M1 L2/3 neurons. We performed snRNA-seq on mouse M1 after 3 days of learning a lever press task. We found a set of genes that separate neurons from the “train” and “control” group with high accuracy. Unsupervised clustering using the gene set generated 6 distinct clusters with different coregulation patterns of the genes. We used differential expression and gene ontology analyses to infer the plasticity phenotypes represented by the clusters in response to motor training, including baseline low activity, recent activity and long term potentiation/depression, and reactivation and dendritic spine morphogenesis. Single-cell trajectory analysis indicates a sequential transition between the clusters, flowing from baseline to recent activity and reactivation. We also characterized a cluster exhibiting neural activity and high expression of norepinephrine receptor and metabolic genes, indicating that there may be an arousal component that plays a role in shaping plasticity. The plasticity phenotypes characterized here will help future studies to better understand the molecular mechanisms underlying plasticity phases and how transitions between phases are regulated.

Creative Commons License

Creative Commons Attribution-Noncommercial 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License

SupplementaryData1.xlsx (14031 kB)
Supplementary Data (1)

SupplementaryData2.xlsx (4452 kB)
Supplementary Data (2)

SupplementaryData3.xlsx (696 kB)
Supplementary Data (3)

Available for download on Sunday, January 12, 2025

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