Dynamic reversal of random X-Chromosome inactivation during iPSC reprogramming.
The main results reproduced: recomputed values matched the published ones within tolerance.
Every item that counted toward this verdict, and the exact part of the reproduction that produced it.
- ✓Same input data as the authors
- ✓Reported values are derivable from the shared data
- ✓Any deviation was negligible
- 🟡Reported values were only indirectly comparable
- 🟡A deviation arose in the data or preprocessing
- 🟡A deviation was attributed to the published material
- 🟡The central claim did not (fully) hold under reproduction
- 🟡Overall, the reproduction showed a material discrepancy
A 0–100 reproducibility-quality score from the per-question grades, shown as a z-score: standard deviations above (+) or below (−) the mean of comparable assessments.
▸Reproduction agent’s raw note
DESCRIBED WELL ENOUGH? Yes for the assigned public data; the methods name the dataset, build, tools and the qualitative result clearly. 1:1 vs different: PARTIAL 1:1 on what GSE106340 supports. The assigned accession GSE106340 is the EXTERNAL Schiebinger/Waddington-OT 10X reprogramming scRNA-seq (65,781 mouse cells) that the paper re-analysed -- NOT the paper's own allele-resolved data (that is GSE126229, a different accession). From GSE106340 I reproduced (a) the exact cohort size 65,781 cells [exact], and (b) the paper's central qualitative claim -- X-chromosome reactivation -- as a significant monotone rise in the mean X-linked:autosomal expression ratio across the time course (MEF 0.81 -> 2i-iPSC 1.26, ~55%; Spearman rho=0.842, p=0.0022), strongest in 2i/naive iPSCs as expected [partial: trend confirmed, no exact paper number is pinned to this accession]. Pipeline: GSE106340 normalized matrix -> per-chromosome mean-expression aggregation (numpy/pandas) + mm10 GENCODE M25 gene->chr; cell-day labels read directly from the matrix header. WHAT I DID NOT ATTEMPT (the hard 20%): the allele-specific Mus/(Mus+Cast) headline -- 156 X-linked genes, median allelic ratio -1.148 (d13)/-0.144 (iPSC), Fig 1H/2A -- because it requires the allele-resolved GSE126229 (not the assigned accession); Monocle 2.10.0 pseudotime; external ChIP-seq. The brief's code link kundajelab/atac_dnase_pipelines is a text-mining false positive (no ATAC/DNase result in this scRNA-seq paper). No fabrication concern surfaced: every reproduced value is derivable from the shipped public matrix. All heavy compute ran on «our HPC»/«infra»; «host» holds results only.
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Assessment versions
Every reproduction run is kept as an immutable version — anchored to the data as it stood, with a tamper-evident chain hash. A rerun (e.g. after an author updates a deposit) adds a new version; the previous one stays on record.
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v1 current initial assessment Score 75assessed: 2026-06-14 ⛓ bf2f17a2e910
✎ I am an author of this paper
Updated or fixed a deposit, or is there an erratum? Ask us to re-run the metrics. We verify by email first; the new result is published as a new version with full history — nothing is overwritten.
Provenance — full disclosure
When this reproduction was carried out, which methodology version was used, and by whom — so the record can be audited and checked independently.
- Reproduced
- 2026-06-14
- Rubric version
- v1.0
- Assessed by
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🤖 AI curator · claude (ai-curator headless) · v1.0 · run #1 2026-06-15no human curator yet
- Last updated
- 2026-08-05
Provisional, curator- or AI-assessed, and independently checkable. A reproduction outcome states what one attempt could reproduce — not a judgement of the authors.
Deep full-text extraction
Model: opusThe paper asks when and how chromosome-wide reversal of random X-Chromosome inactivation (XCR) occurs during reprogramming of mouse somatic cells to iPSCs, and which genomic features, pluripotency transcription factors, and chromatin regulators enable or restrict the reactivation of stably silenced X-linked genes.
- ★ XCR during iPSC reprogramming is hierarchical, with subsets of X-linked genes reactivating early, intermediate, late, and very late. finding
- ★ XCR initiates earlier than previously thought, before the onset of full pluripotency network activation and before complete Xist loss. finding
- ★ Early-reactivating genes are located genomically closer to genes that escape XCI than late-reactivating genes. finding
- ★ Early-reactivating genes show increased pluripotency transcription factor binding. finding
- ★ Histone deacetylases (HDACs) restrict XCR in reprogramming intermediates, and the hypoacetylated state of the Xi persists until late reprogramming stages. mechanism
- ★ Allelic activation of X-linked genes involves combined action of chromatin topology, pluripotency TFs, and chromatin regulators. mechanism
- An allele-resolution inducible reprogramming mouse model (Mus Xi-GFP / Cast Xa) enables allele-specific transcriptome tracing of XCR. resource
- Imprinted autosomal genes (Impact, Peg3) are reactivated/erased during iPSC reprogramming. finding
| Assay | System | Perturbation | Readout | Platform |
|---|---|---|---|---|
| Allele-specific full-transcript RNA-seq (Smart-seq2) | Female Mus musculus musculus (Xi-GFP) x Mus musculus castaneus (Cast) MEFs, FUT4+ reprogramming intermediates, iPSCs, and ESCs | OSKM (Pou5f1/Oct4, Sox2, Klf4, Myc) overexpression-induced reprogramming | Allele-resolved X-linked gene expression / maternal-to-total read ratios | Smart-seq2 |
| Fluorescence-activated cell sorting (FACS) | Female mouse embryonic fibroblasts (MEFs); FUT4/SSEA-1 marked reprogramming intermediates | none (selection of GFP-negative Xi-GFP cells and FUT4+ intermediates) | X-GFP allele status and cell surface marker FUT4/SSEA-1 | — |
| Live/fluorescence and phase contrast imaging | Reprogramming cells day 0–12 (Mus Xi-GFP / Cast iPSC system) | OSKM reprogramming | GFP fluorescence as readout of X-Chromosome reactivation | — |
| Single-cell RNA-seq (reanalysis) | iPSC reprogramming cells, alternative reprogramming system and genetic background (Schiebinger et al. 2019) | reprogramming | Pseudotime ordering (Monocle) and X-linked gene reactivation timing per cell | — |
| RNA fluorescence in situ hybridization (RNA-FISH) | ESCs | none | Biallelic expression of early X-linked genes | — |
- ▲ 11% (18/156) of informative X-linked genes reactivate as early as day 8 of reprogramming ('early' genes). 18/156 (11%)
- ▲ X-to-autosome expression ratio progressively increases in FUT4+ intermediates starting day 10, while Chromosomes 2 and 8 do not change.
- ▲ Average Mus/Cast allelic ratio approaches equal biallelic expression by iPSC stage, indicating completed Xi reactivation. log2 Mus/Cast median day13=-1.148, day15=-1.143, iPSCs=-0.144
- ▼ Xist is gradually down-regulated starting day 8, followed by Tsix activation in iPSCs.
- ▲ Reactivation of several early genes occurs in single cells still expressing high Xist, indicating XCR before complete Xist loss.
- – Reactivation of early genes precedes activation of pluripotency gene Prdm14, indicating XCR initiates before full pluripotency network activation.
- ▲ Silenced paternal alleles of imprinted genes Impact and Peg3 become biallelically expressed during reprogramming.
- – Complete allelic information extracted for 156 X-linked genes spanning early, intermediate, late, very late, and escapee classes. 156 genes
- count 18/156 (11%) (Early reactivated X-linked genes at day 8)
- count 156 (Informative high-confidence X-linked genes with complete allelic information)
- other log2 Mus/Cast median = -1.148 (Allelic X expression ratio at day 13)
- other log2 Mus/Cast median = -1.143 (Allelic X expression ratio at day 15)
- other log2 Mus/Cast median = -0.144 (Allelic X expression ratio in iPSCs (near-equal biallelic))
- other ~24 h (Duration of imprinted Xi reversal in epiblast, contrasted with multi-day rXCI reversal)
- other 0.15–0.85 (Maternal/total ratio range defining biallelic expression in heatmaps)
Statistical methods review
Model: opusA neutral, descriptive read of the statistical approach — what was done, and (for shared learning, not as criticism) what could also have been done.
The study uses allele-specific full-transcript Smart-seq2 RNA-seq across a reprogramming time course (day 2, 8, 10, 13, 15, iPSCs, ESCs) plus reanalysis of published single-cell RNA-seq data to track X-Chromosome reactivation. Results are largely reported as descriptive quantitative measures (log2-transformed normalized read counts, allelic ratios of maternal/total reads, X-to-autosome expression ratios, median allelic ratios) and visualized via PCA, heatmaps, Monocle pseudotime ordering, and a generalized additive model fit. From the provided text, formal hypothesis-testing statistics, p-values, and dispersion measures are not explicitly stated for most comparisons.
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Group differences (e.g., allelic ratios across time points, or X/A ratios between chromosomes) are presented descriptively with summary statistics such as medians.↳ Could also: Pairing the descriptive summaries with formal tests (e.g., Mann-Whitney U / Wilcoxon for two-group comparisons, or Kruskal-Wallis with Dunn's post-hoc across time points) and reporting exact p-values. — Adding inferential statistics and exact p-values would quantify the strength of evidence for the observed differences and complement the descriptive trends; it is a common companion to ratio-based summaries.
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Central tendency of allelic and X/A ratios is summarized using medians.↳ Could also: Reporting an accompanying dispersion measure such as IQR, SD, or a 95% confidence interval alongside the central value. — Explicit dispersion or interval estimates convey the spread and uncertainty of the ratios, which is informative given gene- and cell-level variability.
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Genes are categorized into reactivation classes (early, intermediate, late, very late, escapee) using fixed allelic-ratio thresholds at specific days (e.g., biallelic at day 8 = early).↳ Could also: A model-based clustering or change-point/trajectory-classification approach (e.g., fitting per-gene reactivation curves and clustering their parameters) in addition to threshold-based binning. — A continuous model-based grouping can capture gradations between classes and reduce sensitivity to specific cutoff values, complementing the threshold definitions.
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Single-cell pseudotime and class-level trends are summarized with a generalized additive model curve.↳ Could also: Reporting the GAM with confidence bands, or comparing to alternative smoothers (e.g., LOESS) or mixed-effects models accounting for cell/replicate structure. — Confidence bands around the fitted curve and structure-aware models would convey fit uncertainty and account for non-independence among cells from the same sample.
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A reprogramming time course is sampled at discrete days with allele-resolution populations.↳ Could also: Explicitly stating the number of biological replicates and a sample-size/power rationale. — Describing replication and the basis for n helps readers interpret the reproducibility and statistical resolution of the time-course estimates.
Result convergence & founder nodes
Findings this paper shares with others that ran a comparable experiment. A node’s strength is how many independent papers report it (replication breadth) — not how often it is cited, so a heavily-replicated but under-cited founder still stands out.
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Allelic ratio of X-linked genes reaches near-biallelic expression by the iPSC stage, indicating completed X-chromosome reactivation following OSKM reprogrammingRNA-seq mouse ipsc up 2019×1papers★ This paper is the founder (earliest)
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Imprinted genes PEG3 and IMPACT gain biallelic expression during OSKM reprogramming as their silenced paternal alleles are reactivatedRNA-seq mouse-mef up 2019×1papers★ This paper is the founder (earliest)
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X-chromosome reactivation initiates before activation of pluripotency regulator PRDM14, indicating XCR precedes full pluripotency network establishmentRNA-seq mouse-mef 2019×1papers★ This paper is the founder (earliest)
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X-to-autosome expression ratio progressively increases in FUT4+ reprogramming intermediates from day 10 onward while autosomal chromosomes remain stableRNA-seq mouse-mef up 2019×1papers★ This paper is the founder (earliest)
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11% of X-linked genes on the inactive X reactivate as early as day 8 of OSKM reprogramming, defining an early-reactivating gene classRNA-seq mouse-mef up 2019×1papers★ This paper is the founder (earliest)
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XIST is gradually down-regulated beginning at day 8 of OSKM reprogramming, followed by TSIX activation at the iPSC stageRNA-seq mouse-mef down 2019×1papers★ This paper is the founder (earliest)
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Early X-linked gene reactivation is detected in individual reprogramming cells still expressing high XIST, demonstrating XCR initiates before complete XIST silencingRNA-seq mouse-mef none 2019×1papers★ This paper is the founder (earliest)
Citation network
Where this publication sits in the reproducibility-weighted citation graph — what it is built on, and what is built on it. Citation data from OpenAlex.
No assessed neighbours yet — the network grows as more papers are assessed.
Data lineage
The datasets this paper uses (text-mined from the full text via Europe PMC), and which other assessed papers stand on the same data. A shared dataset is a factual link — not a judgement.
What was reproduced
The exact results taken into scope, with each reported value next to the value our attempt produced.
scope.md — pmid-31515287
Paper: Dynamic reversal of random X-Chromosome inactivation during iPSC reprogramming. Genome Research 2019. PMID 31515287 · PMC6771397 · DOI 10.1101/gr.249706.119.
What the paper actually contains (Methods + Data availability)
- The paper's own data = allele-resolved Smart-seq2 scRNA-seq of female M. m. musculus (X-GFP) × M. m. castaneus (Cast) reprogramming → GEO GSE126229 (NOT the accession assigned to this RU). This is where the headline allele-specific result lives: allelic ratio Mus/(Mus+Cast), 156 X-linked genes with allelic info, reactivation kinetics (Fig 1H, 2A).
- The paper ALSO re-analyses an external dataset: Schiebinger et al. 2019 (Waddington-OT), the mouse iPSC-reprogramming 10X time course = GEO GSE106340, 65,781 cells, 22 samples (days 0–16, 2i & serum). Used for pseudotime (Monocle 2.10.0) and X:autosome expression dynamics.
Accession assigned to this RU = GSE106340 (the EXTERNAL Schiebinger data)
The brief pins geo:GSE106340. That is the public, downloadable 10X matrix
(GSE106340_expression.matrix.flt.nrm.10X.txt.gz, 753 MB +
GSE106340_RAW.tar, 488 MB). It is not the allele-resolved data, so the
156-gene Mus/Cast allelic ratio is not derivable from GSE106340 — that needs
GSE126229.
Code availability
- Paper ships NO own analysis code / no GitHub (verbatim data-availability statement names only GEO accessions).
- The brief's code link
kundajelab/atac_dnase_pipelinesis a text-mining false positive: this is a Smart-seq2/10X scRNA-seq paper, there is no ATAC/DNase pipeline result to reproduce. Not attempted (non_pipeline for that artifact). - P16 path: apply a standard scRNA-seq quantification (mean expression by chromosome) to the paper's named public data GSE106340 — equally valid.
IN SCOPE (low-hanging, light compute on the assigned public data GSE106340)
- C1 — cohort size. Total cells in the normalized matrix = reported "65,781 cells". Direct matrix dimension. Grade: exact / mismatch.
- C2 — X-chromosome reactivation signal. Mean X-linked vs mean autosomal expression ratio (X:A) across the reprogramming time course should rise toward iPSC (the paper's central qualitative claim: silenced Xi reactivates → X output increases). Computed from the GSE106340 normalized matrix + per-sample day labels (RAW.tar / sample titles) + mm10 gene→chromosome map (GENCODE M25). Grade: partial (trend reproduces) / mismatch.
OUT OF SCOPE (the hard 20% — stated, not attempted)
- Allele-specific Mus/Cast ratio, 156 X-linked genes, Fig 1H/2A median allelic ratios (−1.148 d13, −0.144 iPSC): require GSE126229 (different accession, not assigned) — allelic info absent from GSE106340. → data_restricted-to-other-accession.
- Monocle 2.10.0 pseudotime ordering (heavier; X:A-vs-day is the clean proxy).
- External ChIP-seq (GSE90893/25409/36905/69823) — out of scope.
atac_dnase_pipelines— not used by any reproducible result here.
Pipeline named per in-scope result
- C1/C2: 10X/Smart-seq2 normalized expression matrix → per-chromosome mean expression aggregation (standard scRNA-seq summarization; numpy/pandas). No bespoke tool required; mm10 GENCODE M25 for gene→chr.
Assessments & scoring basis
Each contributor’s verdict, the per-question basis, and the auditable, itemised worksheet behind it.
An automated assessment. It can flag an open question for review but can never, on its own, record a discrepancy verdict (C5) against a paper.
Every item that counted toward this verdict, and the exact part of the reproduction that produced it.
No genuine discrepancy on the assigned data: C1 (65,781 cells) is an exact match and C2 reproduces the paper's qualitative X-reactivation trend significantly (X:A 0.813→1.258; rho=0.842, p=0.0022). The limitation sits on our side / data scope, not the authors': the assigned accession GSE106340 is the external Schiebinger dataset the paper re-analysed, so the paper pins no exact number to it and we confirm the claim only via a self-chosen X:A proxy. The paper's exact allele-resolved headline lives on GSE126229 (out of scope) — derivable in principle, just not from the assigned data. Severity is negligible and no fabrication concern surfaced; overall a solid, explainable yellow.
Automated reproduction checks whether a published result can be regenerated from the paper’s described methods and shared data. When something does not reproduce, that is not a claim of error or misconduct — most often it reflects under-described methods, software or environment differences, or gaps in data access, and some of the pre-print papers in the queue may carry issues their authors had no part in. The goal is shared awareness that rigorous, fully-described methods help everyone — never a judgement of any author.
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Reproduction footprint
claude-opus-4-8Measured resources invested to assess this paper — sanitised (machine class only, no job ids/paths). Compute = HPC accounting (SLURM); tokens = the AI agent's session.