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Subnuclear genome compartmentalization controls bivalent chromatin activity.

Code ↔ Paper

7 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 7 matches · 3 of them tie a paragraph to a whole file, not to given lines: weak matches, whose lines are not tinted
  1. [1] § Methods › Domain and peak calling ↔ SPAD_SEACRcode.py, the whole file · a weak match · score 0.83 · kb bin, bedgraph format, blacklisted regions, SEACR, stringent, scores
  2. [2] § Methods › GO-CaRT, CUT&RUN and CUT&Tag data processing and domain calling ↔ SPAD_SEACRcode.py, the whole file · a weak match · score 0.70 · bamCompare, downsampled, match, Picard, score, hg38
  3. [3] § Methods › Integration of published GRO-seq data ↔ GRO-seq_analysis_manuscript.Rmd, lines 259–322 · score 0.68 · GRO seq, gene body, shorter, strand, bp, TSS
  4. [4] § Methods › Gene expression analyses ↔ RNAseq_analysis_manuscript.Rmd, lines 3445–3594 · score 0.64 · featureCounts, GTF, GENCODE, STAR, fastq, RSEM
  5. [5] § Methods › GO-CaRT, CUT&RUN and CUT&Tag data processing and domain calling ↔ SPAD_AlignmentResults.R, the whole file · a weak match · score 0.58 · alignment, histone, Picard, depth, Bowtie2, duplicates
  6. [6] § LAD bivalent genes have low expression ↔ RNAseq_analysis_manuscript.Rmd, lines 4362–4449 · score 0.55 · Fold change, interquartile range, LAD loss, LAD gain, bivalent, NPCs
  7. [7] § Pol II cofactors are excluded from the lamina ↔ GRO-seq_analysis_manuscript.Rmd, lines 259–322 · score 0.51 · GRO seq, gene bodies, elongating, NPCs, LADs

Paper

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

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The authors' code

Python · 28 lines · 1.5 KB · no license · 2 matches

  1. #Downsampling based on scaling factor
  2. #scaling factor = total UniqueFragNum (Sample)/UniqueFragNum (IgG)
  3. #UniqueFragNum stored in alignDupSummary
  4. java -jar picard.jar DownsampleSam I=input.bam O=downsampled.bam P=scaling_factor
  6. #Converting bam to bigwig
  7. bamCompare -b1 treatment.bam -b2 control.bam -o log2ratio.bw
  9. ##Dividng each chromosome into 100kb size bins
  10. bedtools makewindows -w 100000 -g hg38.chrom.sizes.txt > hg38.chrom.sizes_100kb.bed
  12. ##converting bigwig to bedgraph format
  13. bigWigToBedGraph log2ratio.bw log2ratio.bedgraph
  15. ##Deleting lines listing "chrEBV" since this is not included in the human genome. Should not affect other chromosomes.
  16. grep -v "chrEBV" log2ratio.bedgraph > log2ratio.clean.bedgraph
  18. ##Sorting the lines to match the chromosome order in the genome file
  19. bedtools sort -i .log2ratio.clean.bedgraph -g hg38.chrom.sizes.txt > log2ratio.sort.bedgraph
  21. ##Calculating the average score of the bedgraph across 100kb bins, as defined by the hg38.chrom.sizes_100kb.bed file from earlier
  22. bedtools map -a hg38.chrom.sizes_100kb.bed -b log2ratio.sort.bedgraph -c 4 -o mean -g hg38.chrom.sizes.txt > log2ratio.sort.100kb.bedgraph
  24. ##running SEACR in "non" and "stringent" mode with
  25. bash SEACR_1.3.sh log2ratio.sort.100kb.bedgraph 0.25 non stringent log2ratio.sort.100kb.SEACR
  27. #remove blacklisted regions (ENCFF356LFX_blacklist.bed)
  28. bedtools subtract -a log2ratio.sort.100kb.SEACR.stringent.bed -b ENCFF356LFX_blacklist.bed > log2ratio.sort.100kb.SEACR.stringent.clean.bed

SPAD_SEACRcode.py at commit c4e2292, no license · at the source

Overview

Authors: Sajad Hamid Ahanger1,2, Evan R. Semenza1,2,3, Chujing Zhang1,2, Eugene Gil1,2, Mitchel A. Cole1,2,3,4, Serena Huei-An Lu1,2,3, Li Wang2,5, Arnold R. Kriegstein2,5, Daniel A. Lim1,2,6
ORCID iDs: Sajad Hamid Ahanger, Evan R. Semenza, Mitchel A. Cole, Serena Huei-An Lu, Li Wang, Arnold R. Kriegstein, Daniel A. Lim
  1. Department of Neurological Surgery, University of California, San Francisco,San Francisco, CA USA
  2. Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco,San Francisco, CA USA
  3. Biomedical Sciences Graduate Program, University of California, San Francisco,San Francisco, CA USA
  4. Medical Scientist Training Program, University of California, San Francisco,San Francisco, CA USA
  5. Department of Neurology, University of California, San Francisco,San Francisco, CA USA
  6. San Francisco Veterans Affairs Health Care System,San Francisco, CA USA
Institutions: University of California, San Francisco (United States); San Francisco VA Health Care System (United States)
Journal: Nature, volume 657, issue 8131, pages 539-548
Dates: received 3 July 2024; accepted 21 June 2026; published online 22 July 2026; in print 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.1038/s41586-026-10832-w · PMID 42486990 · PMCID PMC13558055 · OpenAlex W7170070475
Open access: hybrid, a free copy (OpenAlex)
Status: code verified
Categories: human (organism)
Methods: Connectivity, Statistics, Evoked potentials
Keywords: Epigenetics in the nervous system, Nuclear envelope
MeSH: Cell Nucleus*, Chromatin*, Genome, Human*, Cerebral Cortex, Chromatin Assembly and Disassembly, Histones, Humans, Methylation, Neurogenesis, Neurons, Nuclear Lamina, Transcription, Genetic (* major topic)
Topic: Genomics and Chromatin Dynamics (Molecular Biology, Biochemistry, Genetics and Molecular Biology), according to OpenAlex
Funding: NIDDK NIH HHS (P30 DK063720); NIH HHS (S10 OD021822); NINDS NIH HHS (R01 NS112357, R35 NS137344); BLRD VA (I01 BX000252); NIGMS NIH HHS (T32 GM141323)
Citations: not cited yet (Europe PMC); 47 references in the paper
Research resources: The UCSF Parnassus Flow CoLab RRID:SCR_018206

Abstract

The nuclear genome is spatially organized into a three-dimensional architecture by physical association of large chromosomal domains with subnuclear compartments including the nuclear lamina at the radial periphery and nuclear speckles within the nucleoplasm1–5. However, how higher-order spatial genome architecture regulates human development has been overlooked, and the interplay between chromatin state and subnuclear genome compartmentalization is poorly understood. Here we generate high-resolution maps of genomic interactions with the lamina and speckles in cells of the neurogenic lineage isolated from mid-gestational human cortex, identifying an intimate association between subnuclear genome compartmentalization, chromatin state and transcription. During cortical neurogenesis, subnuclear genome compartmentalization is extensively remodelled, relocating hundreds of neuronal genes from the lamina to speckles, including key neurodevelopmental genes bivalent for trimethylation of histone H3 at Lys27 (H3K27me3) and Lys4 (H3K4me3). At the lamina, bivalent genes have exceptionally low expression, and relocation to speckles enhances resolution of bivalent chromatin to H3K4me3 monovalency and increases transcription more than eightfold. We further demonstrate that proximity to the nuclear periphery—not the presence of H3K27me3—maintains the lowly expressed, poised state of bivalent genes embedded in the lamina. We find that the repressive environment of the lamina is associated with spatial segregation of the transcriptional elongation machinery from the nuclear periphery. Our results establish a paradigm in which knowing the spatial location of a gene is necessary for understanding its epigenomic regulation.

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 7 matches between paragraphs and lines of code.

eugene-gil/LADs-SPADs-HumanCortex

License: none: the authors keep all their rights
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Commit: c4e22920399862b44ae12139d506f186239df292, 23 April 2026
Languages: R (3), Python (2)
Size: 5 files, 5 scripts
Software Heritage: not archived
Found in: “Code availability”
Holds: 2 notebooks
Not found: README, license file, CITATION.cff, environment file, tests, continuous integration, documentation
Tools: BEDTools (3 files), STAR (2 files), tidyverse (2 files), deepTools (1 file), DESeq2 (1 file), FastQC (1 file), ggplot2 (1 file), NumPy (1 file), pandas (1 file), pheatmap (1 file), PyTorch (1 file), SAMtools (1 file), Subread (featureCounts) (1 file)
Availability: 1 check, the latest on 27 September 2026: the link answers
  • 27 September 2026: the link answers
5 files
At the source: github.com/eugene-gil/LADs-SPADs-HumanCortex

Code availability

All of the software used in this study are listed in the Reporting Summary and Supplementary Table 2. The code used for data analysis is available at GitHub (https://github.com/eugene-gil/LADs-SPADs-HumanCortex).

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;
  • 5 scripts, each with its path and the digest of its content;
  • 7 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

Raw and processed sequencing data for human cell lines, along with processed data from human fetal brain samples, have been deposited at the GEO under accession numbers GSE274038 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE274038) and GSE274039 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE274039) and are publicly available. Raw sequencing data from human fetal brain tissue are available under controlled access through the NIH database of Genotypes and Phenotypes (dbGaP; phs000989.v7.p1 (https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000989.v7.p1)) to protect donor privacy and comply with the terms of informed consent. Access requests should be submitted via the dbGaP authorized access portal (https://dbgap.ncbi.nlm.nih.gov) to the JAAMH data access committee and require local IRB approval and execution of a data use certification limiting use to health/medical/biomedical research (HMB-IRB). Data access requests are typically processed within 2 weeks. No additional restrictions on downstream reuse or authorship apply beyond those specified in the data use certification. Gene expression data from human fetal cortex used in this study are available through the NeMO archive (https://assets.nemoarchive.org/dat-uioqy8b). fastGRO-seq datasets analysed in this study were obtained from GSE143844 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE143844).

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, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 9 authors, 2 keywords, 12 MeSH terms, 5 funders, 47 references, 1 RRID.

Cite

This paper

Ahanger, S. H., Semenza, E. R., Zhang, C., Gil, E., Cole, M. A., Lu, S. H.-A., Wang, L., Kriegstein, A. R., & Lim, D. A. (2026). Subnuclear genome compartmentalization controls bivalent chromatin activity. Nature, 657(8131), 539-548. https://doi.org/10.1038/s41586-026-10832-w

BibTeX

@article{ahanger2026subnuclear,
author = {Ahanger, Sajad Hamid and Semenza, Evan R. and Zhang, Chujing and Gil, Eugene and Cole, Mitchel A. and Lu, Serena Huei-An and Wang, Li and Kriegstein, Arnold R. and Lim, Daniel A.},
title = {{Subnuclear genome compartmentalization controls bivalent chromatin activity}},
journal = {Nature},
year = {2026},
month = jul,
volume = {657},
number = {8131},
pages = {539--548},
publisher = {Nature Portfolio},
issn = {0028-0836},
doi = {10.1038/s41586-026-10832-w},
url = {https://doi.org/10.1038/s41586-026-10832-w},
pmid = {42486990},
pmcid = {PMC13558055}
}

RIS

TY - JOUR
AU - Ahanger, Sajad Hamid
AU - Semenza, Evan R.
AU - Zhang, Chujing
AU - Gil, Eugene
AU - Cole, Mitchel A.
AU - Lu, Serena Huei-An
AU - Wang, Li
AU - Kriegstein, Arnold R.
AU - Lim, Daniel A.
TI - Subnuclear genome compartmentalization controls bivalent chromatin activity
T2 - Nature
J2 - Nature
PY - 2026
DA - 2026/07/22
VL - 657
IS - 8131
SP - 539
EP - 548
SN - 0028-0836
PB - Nature Portfolio
DO - 10.1038/s41586-026-10832-w
UR - https://doi.org/10.1038/s41586-026-10832-w
LA - en
ER -

CSL-JSON

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