OSCR

DNA damage burden causes selective CUX2 neuron loss in neuroinflammation.

Code ↔ Paper

5 matches between paragraphs of the paper and lines of its authors' code, computed by the harvester (lexical-v1). Click a colored paragraph or line to see its counterpart.

The 5 matches · 4 of them tie a paragraph to a whole file, not to given lines: weak matches, whose lines are not tinted
  1. [1] § L2/3EN DDR failure in MS mouse models ↔ snRNAseq/Cux2/Fig3_popko_svlnplot.R, the whole file · a weak match · score 0.81 · Trp53bp1, Rad23b, Hdac9, Actb, Apex1, Parp1
  2. [2] § DNA damage burden in MS L2/3ENs ↔ snRNAseq/Cux2/Fig1_plot_Lucas_splitV.R, the whole file · a weak match · score 0.80 · TP53BP1, HSPA1A, RAD23B, ACTB, APEX1, PARP1
  3. [3] § DNA damage burden in MS L2/3ENs ↔ snRNAseq/Cux2/Fig3_popko_svlnplot.R, the whole file · a weak match · score 0.72 · Hspa1a, Rad23b, ACTB, APEX1, PARP1, XRCC6
  4. [4] § L2/3EN DDR failure in MS mouse models ↔ snRNAseq/Cux2/Fig1_plot_Lucas_splitV.R, the whole file · a weak match · score 0.68 · RAD23B, Hdac9, Actb, Apex1, Parp1, Xrcc6
  5. [5] § IFNγ induces selective loss of L2/3ENs ↔ snRNAseq/utils/splitviolin_plot_base.R, lines 31–68 · score 0.53 · Wilcoxon rank sum, Split violin, gene

Paper

Loaded from Europe PMC by your browser, not stored by OSCR: doi.org · Europe PMC

The paper is loaded when this pane is shown.

The authors' code

R · 49 lines · 2.1 KB · no license · 2 matches

  2. # Set working directory
  3. setwd("/Users/xuz3/Library/CloudStorage/OneDrive-Cedars-SinaiHealthSystem/Documents/Code/work_related/Bioinfo/single_cell_python/Cux2_Atf4_paper_code/Cux2")
  4. source('../utils/splitviolin_plot_base.R')
  5. # Load Seurat object
  6. seurat_object <- readRDS('./data/Popko_EN-L2-3.rds')
  8. # Subset Seurat object
  9. seurat_subset <- subset(seurat_object, subset= age %in% c("W5/7", "W17","W27/29","W41/44"))
  12. # Add module scores for DDR, UPR, ISR, and AAT
  13. seurat_subset <- add_module_score(seurat_subset, '../utils/DDR_list_final.csv', 'DDR')
  14. seurat_subset <- add_module_score(seurat_subset, '../utils/IFN_sorted.csv', 'IFN')
  15. seurat_subset <- add_module_score(seurat_subset, '../utils/UPR_list.csv', 'UPR')
  16. seurat_subset <- add_module_score(seurat_subset, '../utils/ISR_list.csv', 'ISR')
  17. # seurat_subset <- add_module_score(seurat_subset, '../utils/AAT.csv', 'AAT')
  18. # seurat_subset <- add_module_score(seurat_subset, '../utils/PACT.csv', 'PACT')
  19. # seurat_subset <- add_module_score(seurat_subset, '../utils/NRF2.csv', 'NRF2')
  21. # Prepare metadata for plotting
  22. metadata <- [email hidden]
  23. plot_data <- metadata[c( 'DDR1','IFN1', 'age', 'Condition','UPR1','ISR1')]
  25. # List of genes to plot
  26. gl_to_plot <- c('DDR1','UPR1','ISR1','IFN1')#,
  28. # Generate plots
  29. # for (tglname in gl_to_plot) {
  30. # plot_split_violin(plot_data, tglname,'age','Condition','_Popko_ENL2-3',fsizeh=4,fsizew=8)
  32. # }
  33. genes_to_plot <- c('Atf4','Cux2','Hdac9','Actb','Gpx4','2900097C17Rik','Apex1','Rad23b','Trp53bp1', 'Xrcc6')
  34. #=================
  35. # genes_to_plot <-c('2900097C17Rik','Cux2', 'Atf4', 'Actb', 'Hspa1a', 'Gpx4',
  36. # 'Apex1', 'Parp1', 'Rad23b', 'Hdac9', 'Atm', 'Trp53bp1', 'Xrcc6','Xrcc5')
  37. # genes_to_plot <- c('Rpa3','2900097C17Rik', 'Cux2', 'Atf4')
  38. plot_data2 <- FetchData(seurat_subset, vars = c(genes_to_plot))
  39. plot_data3 <- cbind(plot_data,plot_data2)
  41. for (tglname in genes_to_plot) {
  42. plot_split_violin(plot_data3, tglname,'age','Condition','_Popko_ENL2-3',fsizeh=4,fsizew=8)
  43. }
  46. # genes_to_plot <- c('DDR1','IFN1','Rpa3','2900097C17Rik', 'Cux2', 'Atf4','Xrcc5')
  47. for (tglname in genes_to_plot) {
  48. summarize_group_stats(plot_data3, tglname,'age','Condition','Popko_ENL2-3')
  49. }

Fig3_popko_svlnplot.R at commit 0f33176, no license · at the source

Overview

Authors: Laura Morcom1,2,3,4, Wenlong Xia5, Zhaoyang Xu1,3,6,7, Yashika Awasthi8, Celine Geywitz9, Matthew O. Ellis2,4, Tomas Noli9, Amel Zulji9, Daniel Yamamoto1,3, Gemma C. Girdler1,3, Li Kai8, Keying Zhu5, Mingming Wei5, Xiao-Yan Tang5, Kimberly K. Hoi5, Julio Gonzalez-Maya5, Greg J. Duncan10, Adrien M. Vaquie1,3, Diana Gold Diaz1,3, Riki Kawaguchi11,12
and 18 other authorsErdong Liu8, Yu Sun2,4, Denny Yang2,4, Gregory D. Jordan1,3, I-Ling Lu13,14, Staffan Holmqvist1,3, Theresa Bartels1,3, Katherine Ridley1,3, Jennifer Ja-Yoon Choi15, Santos J. Franco16, Eric J. Huang15, Ben Emery17, Daniel Geschwind12,18,19, Lucas Schirmer9,20,21, Gabriel Balmus2,4,22, Brian Popko8, Stephen P. J. Fancy5, David H. Rowitch1,3,6,7,13,14
ORCID iDs: Laura Morcom, Celine Geywitz, Tomas Noli, Amel Zulji, Keying Zhu, Greg J. Duncan, Riki Kawaguchi, Yu Sun, I-Ling Lu, Staffan Holmqvist, Theresa Bartels, Eric J. Huang, Ben Emery, Daniel Geschwind, Lucas Schirmer, Brian Popko, Stephen P. J. Fancy, David H. Rowitch
22 affiliations
  1. Cambridge Stem Cell Institute, University of Cambridge,Cambridge, UK
  2. UK Dementia Research Institute at the University of Cambridge, University of Cambridge,Cambridge, UK
  3. Department of Paediatrics, University of Cambridge,Cambridge, UK
  4. Department of Clinical Neurosciences, University of Cambridge,Cambridge, UK
  5. Division of Neuroimmunology and Glial Biology, Department of Neurology, University of California San Francisco,San Francisco, CA USA
  6. Department of Pediatrics, Cedars-Sinai Guerin Children’s, Los Angeles, CA USA
  7. Department of Neurosurgery, Cedars-Sinai Guerin Children’s, Los Angeles, CA USA
  8. Department of Neurology, Feinberg School of Medicine, Northwestern University,Chicago, IL USA
  9. Division of Neuroimmunology, Department of Neurology, Medical Faculty Mannheim, Heidelberg University,Mannheim, Germany
  10. Department of Neurology, Jungers Center for Neurosciences Research, Oregon Health & Science University,Portland, OR USA
  11. Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles,Los Angeles, CA USA
  12. Department of Neurology, University of California Los Angeles,Los Angeles, CA USA
  13. The Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California San Francisco,San Francisco, CA USA
  14. Department of Pediatrics, Division of Neonatology, University of California San Francisco,San Francisco, CA USA
  15. Department of Pathology, University of California San Francisco,San Francisco, CA USA
  16. Department of Pediatrics, Section of Developmental Biology, University of Colorado—Anschutz Medical Campus,Denver, CO USA
  17. Jungers Center for Neurosciences Research, Department of Neurology, Oregon Health & Science University,Portland, OR USA
  18. Program in Neurogenetics, Departments of Neurology and Human Genetics, Institute of Precision Health, David Geffen School of Medicine, University of California Los Angeles,Los Angeles, CA USA
  19. Center for Autism Research and Treatment, Department of Psychiatry and Semel Institute, University of California Los Angeles,Los Angeles, CA USA
  20. Interdisciplinary Center for Neurosciences, Heidelberg University,Heidelberg, Germany
  21. Center for Translational Neuroscience and Institute for Innate Immunoscience, Medical Faculty Mannheim, Heidelberg University,Mannheim, Germany
  22. Department of Molecular Neuroscience, Transylvanian Institute of Neuroscience, Cluj-Napoca, Romania
Institutions: University of Cambridge (United Kingdom); University of California, San Francisco (United States); Northwestern University (United States); Heidelberg University (Germany); Oregon Health & Science University (United States); University of California, Los Angeles (United States); University of Colorado Anschutz (United States)
Journal: Nature, volume 653, issue 8115, pages 809-818
Dates: received 30 April 2025; accepted 20 February 2026; published online 1 April 2026; in print 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.1038/s41586-026-10310-3 · PMID 41922773 · PMCID PMC13190333 · OpenAlex W7147276421
Open access: hybrid, a free copy (OpenAlex)
Status: code verified
Categories: human (organism), mouse (organism), multiple sclerosis (population), cellular / molecular (subfield)
Methods: Spectral & time-frequency, Statistics, Connectivity, Evoked potentials
Keywords: Multiple sclerosis, Experimental models of disease
MeSH: DNA Damage*, Homeodomain Proteins*, Neuroinflammatory Diseases*, Neurons*, Animals, Cell Death, Disease Models, Animal, DNA Breaks, Double-Stranded, DNA Repair, Female, Humans, Interferon-gamma, Male, Mice, Multiple Sclerosis, Reactive Oxygen Species (* major topic)
Topic: Amyotrophic Lateral Sclerosis Research (Neurology, Medicine), according to OpenAlex
Funding: National Institute for Health Research (NIHR) (NIHR203312); NINDS NIH HHS (R01 NS120981, P01 NS083513); European Research Council (789054, 950584)
Citations: cited by 3 papers (Europe PMC); 73 references in the paper

Abstract

Neurodegeneration shows regional and cell-type-specific patterns in ageing and disease1, but the underlying mechanisms for cell-type-specific neuronal losses remain poorly understood. Previous studies have shown that upper cortical layer thinning occurs in progressive human multiple sclerosis (MS) and that cortical layer 2 and layer 3 (L2/3) excitatory neurons (L2/3ENs) that express CUT-like homeobox 2 (CUX2) are selectively vulnerable to degeneration2. Here we report that L2/3ENs within MS cortical lesions have an elevated DNA damage burden. DNA damage and selective loss of L2/3ENs were recapitulated in diverse mouse models of demyelination and pan-cortical inflammation, confirming their intrinsic vulnerability. Functions of Cux2 and activating transcription factor 4 (Atf4) were essential for resilience of L2/3ENs during postnatal neuroinflammation, acting in neurons to enhance DNA double-strand break repair. Interferon-γ, a cytokine implicated in MS pathogenesis3,4, was sufficient to elevate levels of reactive oxygen species, leading to DNA damage-mediated neuronal death in vitro, and caused selective depletion of L2/3 neurons in mice. These findings indicate that DNA damage burden and inadequate repair in CUX2+ L2/3ENs contributes to selective vulnerability in neuroinflammatory injury.

Reproduced under the paper's license (CC BY), from the paper cited above.

Repository

Its files are read in the Code ↔ Paper reader above, with 5 matches between paragraphs and lines of code.

RowitchLab/Code_for_Cux2_Atf4_paper

License: none: the authors keep all their rights
State: the link answers, verified on 28 September 2026
Evidence: files inventoried
Commit: 0f331768401b9725c98987f67383d64f670cfc8e, 6 February 2026
Languages: Python (7), R (6)
Size: 24 files, 13 scripts
Software Heritage: not archived
Found in: “Code availability”
Holds: README
Not found: license file, CITATION.cff, environment file, tests, continuous integration, documentation
Tools: Seurat (7 files), ggplot2 (6 files), pandas (5 files), rpy2 (4 files), Scanpy (4 files), anndata (3 files), NumPy (3 files), SciPy (3 files), tidyverse (2 files), cowplot (1 file), ggpubr (1 file), Matplotlib (1 file), patchwork (1 file), reshape2 (1 file), seaborn (1 file)
Availability: 1 check, the latest on 28 September 2026: the link answers
  • 28 September 2026: the link answers
14 files
At the source: github.com/RowitchLab/Code_for_Cux2_Atf4_paper

Code availability

Source code is available at GitHub (https://github.com/RowitchLab/Code_for_Cux2_Atf4_paper).

Reproduced under the paper's license (CC BY), from the paper cited above.

Tracing map

Proposed by the machine: these links were found in the paper and verified at the source, without human review. The map will receive a Zenodo DOI once one of the paper's authors has validated it with their ORCID.

What the map holds:

  • 1 repository of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
  • 13 scripts, each with its path and the digest of its content;
  • 5 matches between paragraphs of the paper and lines of the code (method lexical-v1);
  • neither the text of the paper nor the code itself.

Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.

Data

Datasets cited

Data availability

snRNA-seq data for E18.5 mice generated in this study are available in the GEO database under the accession number GSE314471 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE314471). The snRNA-seq dataset of excitatory neurons from P26 Cux2cre mice is available at Zenodo72 (10.5281/zenodo.18489557). snRNA-seq data of neurons from the DTA mice can be accessed at Zenodo73 (10.5281/zenodo.18022784). Human sequencing data generated previously2 are available in the Sequence Read Archive (SRA) under accession number PRJNA544731 (https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA544731) and are viewable on the UCSF Cell Browser (https://cells.ucsc.edu/?ds=ms). Source data are provided with this paper.

Reproduced under the paper's license (CC BY), from the paper cited above.

Versions

The history of this record: each version stored by the harvester or made by a correction of its authors or of the maintainers of its code, and what changed in its facts. The texts of the paper (its abstract, its availability statements) are not part of it; versions that changed only those are not listed.

Version 2, 28 September 2026

  • Publisher: n/a → Nature Portfolio

Version 1, 28 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 38 authors, 2 keywords, 16 MeSH terms, 3 funders, 71 references.

Cite

This paper

Morcom, L., Xia, W., Xu, Z., Awasthi, Y., Geywitz, C., Ellis, M. O., Noli, T., Zulji, A., Yamamoto, D., Girdler, G. C., Kai, L., Zhu, K., Wei, M., Tang, X.-Y., Hoi, K. K., Gonzalez-Maya, J., Duncan, G. J., Vaquie, A. M., Gold Diaz, D., . . . Rowitch, D. H. (2026). DNA damage burden causes selective CUX2 neuron loss in neuroinflammation. Nature, 653(8115), 809-818. https://doi.org/10.1038/s41586-026-10310-3

BibTeX

@article{morcom2026dna,
author = {Morcom, Laura and Xia, Wenlong and Xu, Zhaoyang and Awasthi, Yashika and Geywitz, Celine and Ellis, Matthew O. and Noli, Tomas and Zulji, Amel and Yamamoto, Daniel and Girdler, Gemma C. and Kai, Li and Zhu, Keying and Wei, Mingming and Tang, Xiao-Yan and Hoi, Kimberly K. and Gonzalez-Maya, Julio and Duncan, Greg J. and Vaquie, Adrien M. and Gold Diaz, Diana and Kawaguchi, Riki and Liu, Erdong and Sun, Yu and Yang, Denny and Jordan, Gregory D. and Lu, I-Ling and Holmqvist, Staffan and Bartels, Theresa and Ridley, Katherine and Choi, Jennifer Ja-Yoon and Franco, Santos J. and Huang, Eric J. and Emery, Ben and Geschwind, Daniel and Schirmer, Lucas and Balmus, Gabriel and Popko, Brian and Fancy, Stephen P. J. and Rowitch, David H.},
title = {{DNA damage burden causes selective CUX2 neuron loss in neuroinflammation}},
journal = {Nature},
year = {2026},
month = apr,
volume = {653},
number = {8115},
pages = {809--818},
publisher = {Nature Portfolio},
issn = {0028-0836},
doi = {10.1038/s41586-026-10310-3},
url = {https://doi.org/10.1038/s41586-026-10310-3},
pmid = {41922773},
pmcid = {PMC13190333}
}

RIS

TY - JOUR
AU - Morcom, Laura
AU - Xia, Wenlong
AU - Xu, Zhaoyang
AU - Awasthi, Yashika
AU - Geywitz, Celine
AU - Ellis, Matthew O.
AU - Noli, Tomas
AU - Zulji, Amel
AU - Yamamoto, Daniel
AU - Girdler, Gemma C.
AU - Kai, Li
AU - Zhu, Keying
AU - Wei, Mingming
AU - Tang, Xiao-Yan
AU - Hoi, Kimberly K.
AU - Gonzalez-Maya, Julio
AU - Duncan, Greg J.
AU - Vaquie, Adrien M.
AU - Gold Diaz, Diana
AU - Kawaguchi, Riki
AU - Liu, Erdong
AU - Sun, Yu
AU - Yang, Denny
AU - Jordan, Gregory D.
AU - Lu, I-Ling
AU - Holmqvist, Staffan
AU - Bartels, Theresa
AU - Ridley, Katherine
AU - Choi, Jennifer Ja-Yoon
AU - Franco, Santos J.
AU - Huang, Eric J.
AU - Emery, Ben
AU - Geschwind, Daniel
AU - Schirmer, Lucas
AU - Balmus, Gabriel
AU - Popko, Brian
AU - Fancy, Stephen P. J.
AU - Rowitch, David H.
TI - DNA damage burden causes selective CUX2 neuron loss in neuroinflammation
T2 - Nature
J2 - Nature
PY - 2026
DA - 2026/04/01
VL - 653
IS - 8115
SP - 809
EP - 818
SN - 0028-0836
PB - Nature Portfolio
DO - 10.1038/s41586-026-10310-3
UR - https://doi.org/10.1038/s41586-026-10310-3
LA - en
ER -

CSL-JSON

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