DOI: 10.5061/dryad.dr7sqvbc0
title: Myelin is repaired by constitutive differentiation of oligodendrocyte progenitors

description: Oligodendrocytes form myelin sheaths around axons to enable rapid
 signaling within neural circuits. The generation of new oligodendrocytes
 through differentiation of oligodendrocyte precursor cells (OPCs) promotes
 myelin plasticity and repair in the adult brain. Here, we performed
 genetic interrogation and in vivo analysis of OPCs in order to determine
 their differentiation dynamics. Our results show that OPCs attempt to
 differentiate throughout the adult CNS with spatial and temporal
 regularity. The differentiation rate was not influenced by myelin demand
 or oligodendrocyte loss, and declined with age and in response to acute
 inflammation. The results suggest that OPC differentiation is governed
 primarily by constitutive processes and might be negatively influenced by
 aging and inflammation.
description: # Myelin is repaired by constitutive differentiation of oligodendrocyte
 progenitors Dataset DOI:
 [10.5061/dryad.dr7sqvbc0](https://doi.org/10.5061/dryad.dr7sqvbc0) ##
 Description of the data and file structure ### Files and variables ####
 File: CHST3_floxflox_genomic_sequence.dna **Description:**  This is a
 Snapgene file of the annotated genomic sequence of a *Chst3 flox/flox*
 mouse described in the associated publication  #### File:
 CHST3_floxflox_genomic_sequence_text_version_ODT.odt **Description:** 
 This is a raw genomic sequence of a *Chst3 flox/flox* mouse described in
 the publication #### File: Chase_in_pTRE_tight_sequence.dna
 **Description:**  This is a Snapgene file of annotated genomic sequence of
 a *ChaseR-TRE* mouse described in the publication #### File:
 Chase_in_pTRE_tight_sequence_text_format_ODT.odt **Description:**  This is
 a raw genomic sequence of a *ChaseR-TRE* mouse described in the
 publication #### File: Terminator_full_sequence.dna **Description:**  This
 is a Snapgene file of annotated genomic sequence of an *OPC-Terminator*
 *^fl/+^* mouse described in the publication #### File:
 Terminator_full_sequence_text_format_ODT.odt **Description:**  This is a
 raw genomic sequence of an *OPC-Terminator* *^fl/+^* mouse described in
 the publication #### File: DangDACSCounting_v2.m **Description:** 
 DACSCounting.mat is used to annotate all OPCs, proliferating OPCs, and
 DACS in 2D images. The code is annotated. #### File: DangDACSAlign_v2.m
 **Description:**  DACSAlign.mat is used to display the six nearest OPCs to
 each DACS, as well as the closest proliferating OPC and its distance to
 the center of the DACS. The code is annotated.  #### File:
 get_OPC_metadata.py **Description:**  Please place in the same folder with
 analysis and registration files. For a test set can use use
 test_xml, test_set_edges.csv, test_set_spots.csv #### File:
 OPC_cell_class.py **Description:**  Please place in the same folder with
 analysis and registration files #### File:
 parse_MaMuT_Mironova_et_al_2025.py **Description:**  Please use this code
 for analysis of your MaMuT annotated in vivo imaging datasets. Please note
 that this code is written specifically for parsing two-photon in vivo
 time-lapse imaging of the oligodendrocyte lineage, however, it can be
 potentially modified for other cell types. The code is annotated. ####
 File: preprocess.py **Description:**  Please place in the same folder with
 analysis and registration files. #### File: registration_functions.py
 **Description:**  Please place in the same folder with analysis and
 registration files. #### File: plot_functions_OPC.py **Description:** 
 Please place in the same folder with analysis and registration files. ####
 File: register_timepoints_Matn4_YM.py **Description:**  Please use for
 registration of xyzt hyperstacks to the vasculature channel. Please
 use registration_test_set.tif as a sample dataset.  #### File:
 Test_set.xml **Description:**  This is a metadata file to test if
 parse_MaMuT_Mironova_et_al_2025.py and get_OPC_metadata.py pipelines run
 well. This xml file is generated by a BigDataViewer plugin in Fiji -
 please consult the MaMuT manual (link below) for more details on how this
 file can be generated from your data. #### File: test_set_edges.csv
 **Description:**  This is an edges csv output generated from cell tracking
 in MaMuT. For your own experiments, you can generate this file by opening
 your MaMuT annotation and in the MaMuT viewer click Track tables - edges -
 export as csv (UTF-8). Please consult the MaMuT manual (link below) on how
 to generate your own MaMuT annotation. Please use this file to test if
 parse_MaMuT_Mironova_et_al_2025.py and get_OPC_metadata.py pipelines run
 well. Please disregard NaN values as they don't influence the
 analysis in this sample dataset. ##### Variables * LABEL: Label
 "d" denotes cells that disappear on the following frame, label
 "OL" denotes cells that differentiate into an oligodendrocyte in
 the following frame.  * TRACK_ID: * SPOT_SOURCE_ID: * SPOT_TARGET_ID: *
 LINK_COST: * DIRECTIONAL_CHANGE_RATE: * SPEED: * DISPLACEMENT: *
 EDGE_TIME: * EDGE_X_LOCATION: * EDGE_Y_LOCATION: * EDGE_Z_LOCATION: *
 MANUAL_EDGE_COLOR: For information on how these variables are generated,
 please consult a MaMuT plugin getting started (a link below).  #### File:
 test_set_spots.csv **Description:**  This is an spots csv output generated
 from cell tracking in MaMuT. For your own experiments, you can generate
 this file by opening your MaMuT annotation and in the MaMuT viewer click
 Spot table - export as csv (UTF-8). Please consult the MaMuT manual (link
 below) on how to generate your own MaMuT annotation. Please use this file
 to test if parse_MaMuT_Mironova_et_al_2025.py and get_OPC_metadata.py
 pipelines run well. Please disregard NaN values as they don't
 influence the analysis in this sample dataset. ##### Variables *
 LABEL: Label "d" denotes cells that disappear on the following
 frame, label "OL" denotes cells that differentiate into an
 oligodendrocyte in the following frame.  * ID: * TRACK_ID: * QUALITY: *
 POSITION_X: * POSITION_Y: * POSITION_Z: * POSITION_T: * FRAME: * RADIUS: *
 VISIBILITY: * CELL_DIVISION_TIME: * SOURCE_ID: * MANUAL_SPOT_COLOR: *
 MEAN_INTENSITY_CH1: * MEDIAN_INTENSITY_CH1: * MIN_INTENSITY_CH1: *
 MAX_INTENSITY_CH1: * TOTAL_INTENSITY_CH1: * STD_INTENSITY_CH1: *
 CONTRAST_CH1: * SNR_CH1: For additional information on how these variables
 are generated, please consult a MaMuT plugin getting started (a link
 below).  #### File: registration_test_set.tif **Description:**  This is a
 sample in hypterstack image of time-lapse two-photon in vivo imaging of
 oligodendrocyte precursor cells and vasculature that can be use to test if
 register_timepoints_Matn4_YM.py pipeline runs well.  #### File:
 Raw_values_Mironova_et_al_2025_updated.xlsx **Description:**  Values as
 reported in figures within the associated publication. Each sheet is
 labeled with a figure number and if there is more than one dataset per
 sheet, they are labeled with "A" "B" "C" etc
 according to how it is organized in the publication. All statistical
 values and units are reported in figure legends or in the main text of the
 publication. #### File: Raw_absolute_values_Mironova_2025.xlsx
 **Description:**  Absolute values for the data reported in the publication
 where normalized data were reported, with sheets organized by figure
 numbers similar to "Raw_values_Mironova_et_al_2025".  ###
 Code/software For Python code: 1\) Create and activate an environment
 (conda recommended): ``` conda create -n opc python=3.10 -y conda activate
 opc ``` 2\) Install Python dependencies: `pip install numpy matplotlib
 natsort tifffile scikit-image pandas seaborn# 3) (Registration) Install
 ITKElastix (easiest path)` `pip install itk-elastix` For more
 tutorials/info, see --&gt;
 [https://github.com/InsightSoftwareConsortium/ITKElastix/tree/master/examples](https://github.com/InsightSoftwareConsortium/ITKElastix/tree/master/examples) Please note - Python code was written for Linux. For .dna files - Snapgene Viewer or any DNA sequence viewer software For .xlsx files - any software compatible with a .xlsx format For .mat files - MATLAB (basic MATLAB functions) For generation of your own MaMuT annotated datasets - MaMuT plugin in Fiji [https://imagej.net/plugins/mamut/getting-started](https://imagej.net/plugins/mamut/getting-started)