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Epigenetic lockdown of type I interferon sensing and signalling in human pluripotent cells.

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Paper

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The authors' code

Python · 98 lines · 3.8 KB · no license

  1. import sys
  2. import subprocess
  3. import pandas as pd
  4. import numpy as np
  5. from scipy import stats
  6. import tempfile
  7. import os
  8. import time
  10. def run_bedtools_intersect(bed1, bed2):
  11. intersect_cmd = f"bedtools intersect -a {bed1} -b {bed2} -wa"
  12. result = subprocess.run(intersect_cmd, shell=True, capture_output=True, text=True)
  13. return result.stdout
  15. def count_intersections(bedtools_output):
  16. return len(bedtools_output.strip().split('\n'))
  18. def prepare_gene_bed(gene_bed):
  19. with tempfile.NamedTemporaryFile(mode='w', delete=False, suffix='.bed') as temp_file:
  20. with open(gene_bed, 'r') as f:
  21. for line in f:
  22. fields = line.strip().split('\t')
  23. if len(fields) >= 4:
  24. temp_file.write('\t'.join(fields[:4]) + '\n')
  25. return temp_file.name
  27. def perform_permutations(bed1, gene_bed, num_permutations, num_bed2_lines):
  28. perm_results = []
  30. simplified_gene_bed = prepare_gene_bed(gene_bed)
  32. start_time = time.time()
  33. for i in range(num_permutations):
  34. with tempfile.NamedTemporaryFile(mode='w', delete=False, suffix='.bed') as temp_shuffled:
  35. subprocess.run(f"shuf -n {num_bed2_lines} {simplified_gene_bed} > {temp_shuffled.name}", shell=True)
  36. random_overlap = run_bedtools_intersect(bed1, temp_shuffled.name)
  37. os.unlink(temp_shuffled.name)
  39. count = count_intersections(random_overlap)
  40. perm_results.append(count)
  42. if (i+1) % 10 == 0:
  43. elapsed_time = time.time() - start_time
  44. avg_time_per_iter = elapsed_time / (i+1)
  45. estimated_total_time = avg_time_per_iter * num_permutations
  46. estimated_remaining_time = estimated_total_time - elapsed_time
  47. print(f"Completed {i+1} permutations. Current count: {count}")
  48. print(f"Elapsed time: {elapsed_time:.2f} seconds")
  49. print(f"Estimated total time: {estimated_total_time:.2f} seconds")
  50. print(f"Estimated time remaining: {estimated_remaining_time:.2f} seconds")
  51. print("--------------------")
  53. os.unlink(simplified_gene_bed)
  54. return perm_results
  56. def calculate_enrichment(actual_count, perm_results, num_permutations):
  57. mean_perm = np.mean(perm_results)
  58. std_perm = np.std(perm_results)
  59. p_value = (np.sum(np.array(perm_results) >= actual_count) + 1) / (num_permutations + 1)
  60. enrichment = actual_count / mean_perm if mean_perm > 0 else np.inf
  62. return pd.DataFrame([{
  63. "Actual_Count": actual_count,
  64. "Mean_Perm_Count": mean_perm,
  65. "SD_Perm_Count": std_perm,
  66. "Enrichment": enrichment,
  67. "P_Value": p_value
  68. }])
  70. def main(bed1, bed2, gene_bed, num_permutations):
  71. print(f"Starting TE intersection enrichment analysis with {num_permutations} permutations")
  72. print(f"Input files: TE bed: {bed1}, Gene bed: {bed2}, All genes: {gene_bed}")
  74. actual_overlap = run_bedtools_intersect(bed1, bed2)
  75. actual_count = count_intersections(actual_overlap)
  77. print(f"Actual intersection count: {actual_count}")
  79. num_bed2_lines = sum(1 for line in open(bed2))
  81. print(f"Performing {num_permutations} permutations...")
  82. perm_results = perform_permutations(bed1, gene_bed, num_permutations, num_bed2_lines)
  84. pd.DataFrame({"Intersection_Counts": perm_results}).to_csv("permutation_results.tsv", sep="\t", index=False)
  85. print(f"Permutation results saved to permutation_results.tsv")
  87. stats_df = calculate_enrichment(actual_count, perm_results, num_permutations)
  89. stats_df.to_csv("enrichment_results.tsv", sep="\t", index=False)
  90. print("Final results:")
  91. print(stats_df)
  93. if __name__ == "__main__":
  94. if len(sys.argv) != 5:
  95. print("Usage: python scriptname.py bed1 bed2 genebed iters")
  96. sys.exit(1)
  98. main(sys.argv[1], sys.argv[2], sys.argv[3], int(sys.argv[4]))

count_all_intersects_then_shuffle.py at commit dd224a3, no license · at the source

Overview

Authors: James H Holt1, Rocio Enriquez-Gasca1,2, Rachel P Wilson1, Elena G Bochukova1, Pierre V Maillard1, Helen M Rowe1
ORCID iDs: James H Holt, Rocio Enriquez-Gasca, Pierre V Maillard, Helen M Rowe
  1. Centre for Immunobiology and Infection, Blizard Institute, Queen Mary University of London, London, UK
  2. Present Address: The Francis Crick Institute, London, UK
Institutions: Queen Mary University of London (United Kingdom); Blizard Institute (United Kingdom); The Francis Crick Institute (United Kingdom)
Journal: Nature communications, volume 17, issue 1, article 7660
Dates: received 29 September 2025; accepted 27 May 2026; published online 16 June 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.1038/s41467-026-74147-0 · PMID 42303602 · PMCID PMC13434735 · OpenAlex W4415600681
Open access: gold, a free copy (OpenAlex)
Preprint: doi:10.1101/2025.10.27.684762
Status: code verified
Categories: human (organism), cellular / molecular (subfield)
Methods: Statistics
Keywords: RIG-I-like receptors, Induced pluripotent stem cells, Gene silencing, DNA transposable elements
MeSH: Epigenesis, Genetic*, Induced Pluripotent Stem Cells*, Interferon Type I*, Signal Transduction*, Cell Differentiation, Humans, Long Interspersed Nucleotide Elements, Neural Stem Cells (* major topic)
Topic: interferon and immune responses (Immunology, Immunology and Microbiology), according to OpenAlex
Funding: European Research Council (678350); Rosetrees Trust (CF-2023-I-2\107)
Citations: cited by 1 paper (Europe PMC); 77 references in the paper

Abstract

The Human Silencing Hub (HUSH) complex safeguards genome integrity in human somatic cells, repressing transposable elements and regulating type I interferon (IFN-I) induction. Here, we use depletion of MPP8 in human induced pluripotent stem cells (iPSCs) as a tool to investigate epigenetic control of the IFN-I system in early development. We confirmed that human iPSCs display an attenuated IFN-I pathway, whereas iPSC-derived neural progenitor cells (NPCs) respond robustly to IFN-I pathway agonists. We found that, in iPSCs, depletion of MPP8 was sufficient to induce expression of young LINE-1 elements and genes linked to the IFN-I system including double-stranded RNA sensors and interferon-stimulated genes (ISGs). ISG upregulation occurred without IFN-I signalling, suggesting that, in contrast to differentiated cells, this ISG regulation is uncoupled from nucleic acid sensing specifically in early development. Chromatin profiling confirmed MPP8 enrichment at HUSH-regulated ISGs and revealed a bimodal binding profile of MPP8 to both ISGs and non-ISGs, the latter largely driven by young LINE-1 elements. We propose that shutdown of the IFN-I system in pluripotent stem cells is essential to prevent lethality from unwarranted self-nucleic acid sensing. This shutdown is achieved through a triple-layer of epigenetic lockdown targeting ligands, sensors, and effectors across the IFN-I pathway.

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

Repository

Its files are read in the Code ↔ Paper reader above.

RoweLab/TE-Enrichment

License: none: the authors keep all their rights
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Commit: dd224a36d0c3c15b3faf50fc6e11908ad1506b49, 21 April 2026
Languages: Python (4)
Size: 5 files, 4 scripts
Software Heritage: not archived
Found in: “Code availability”
Not found: README, license file, CITATION.cff, environment file, tests, continuous integration, documentation
Tools: BEDTools (4 files), NumPy (4 files), pandas (4 files), SciPy (4 files)
Availability: 1 check, the latest on 27 September 2026: the link answers
  • 27 September 2026: the link answers
4 files
At the source: github.com/RoweLab/TE-Enrichment

Code availability

Custom scripts are available at https://github.com/RoweLab/TE-Enrichment

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;
  • 4 scripts, each with its path and the digest of its content;
  • no match between paragraphs and code yet;
  • 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

RNA-seq and CUT & Tag data from this study are available in the Gene Expression Omnibus database. GSE318471 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE318471) https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE318471 (total RNA sequencing) and GSE318510 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE318510) https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE318510 (CUT & Tag). Lists of studied genes and peaks are provided with this paper in the accompanying source data. Source data are provided in 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 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 6 authors, 4 keywords, 8 MeSH terms, 2 funders, 76 references.

Cite

This paper

Holt, J. H., Enriquez-Gasca, R., Wilson, R. P., Bochukova, E. G., Maillard, P. V., & Rowe, H. M. (2026). Epigenetic lockdown of type I interferon sensing and signalling in human pluripotent cells. Nature communications, 17(1), 7660. https://doi.org/10.1038/s41467-026-74147-0

BibTeX

@article{holt2026epigenetic,
author = {Holt, James H and Enriquez-Gasca, Rocio and Wilson, Rachel P and Bochukova, Elena G and Maillard, Pierre V and Rowe, Helen M},
title = {{Epigenetic lockdown of type I interferon sensing and signalling in human pluripotent cells}},
journal = {Nature communications},
year = {2026},
month = jun,
volume = {17},
number = {1},
pages = {7660},
publisher = {Nature Publishing Group},
issn = {2041-1723},
doi = {10.1038/s41467-026-74147-0},
url = {https://doi.org/10.1038/s41467-026-74147-0},
pmid = {42303602},
pmcid = {PMC13434735}
}

RIS

TY - JOUR
AU - Holt, James H
AU - Enriquez-Gasca, Rocio
AU - Wilson, Rachel P
AU - Bochukova, Elena G
AU - Maillard, Pierre V
AU - Rowe, Helen M
TI - Epigenetic lockdown of type I interferon sensing and signalling in human pluripotent cells
T2 - Nature communications
J2 - Nat Commun
PY - 2026
DA - 2026/06/16
VL - 17
IS - 1
SP - 7660
SN - 2041-1723
PB - Nature Publishing Group
DO - 10.1038/s41467-026-74147-0
UR - https://doi.org/10.1038/s41467-026-74147-0
LA - en
ER -

CSL-JSON

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"id": "10.1038/s41467-026-74147-0",
"type": "article-journal",
"title": "Epigenetic lockdown of type I interferon sensing and signalling in human pluripotent cells",
"container-title": "Nature communications",
"author": [
{
"family": "Holt",
"given": "James H"
},
{
"family": "Enriquez-Gasca",
"given": "Rocio"
},
{
"family": "Wilson",
"given": "Rachel P"
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{
"family": "Bochukova",
"given": "Elena G"
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}
],
"container-title-short": "Nat Commun",
"volume": "17",
"issue": "1",
"page": "7660",
"DOI": "10.1038/s41467-026-74147-0",
"PMID": "42303602",
"PMCID": "PMC13434735",
"ISSN": "2041-1723",
"publisher": "Nature Publishing Group",
"URL": "https://doi.org/10.1038/s41467-026-74147-0",
"language": "en",
"issued": {
"date-parts": [
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2026,
6,
16
]
]
}
}

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