The exonuclease Xrn1 activates transcription and translation of mRNAs encoding membrane proteins.
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 were directly comparable
- ✓No authors-side cause for any deviation
- ✓Reported values are derivable from the shared data
- ✓Any deviation was negligible
- ✓The central claim held under reproduction
- 🟡A deviation arose in the data or preprocessing
- 🟡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 to reproduce. The harvested code link github.com/abelew/prfdb is a MIS-HARVEST (unrelated 2009 Perl frameshift tool; the paper ships no code). Per brief rule 2/P16 we reproduced the headline computational result by applying the DOCUMENTED third-party pipeline (Riborex v1.2.3, engine DESeq2, FDR<0.05) to the GEO-shipped processed count tables for GSE109734 (RPF + mRNA footprint/ counts). The paper's auxin-degron acute-depletion contrast (t0 vs t30) yields 429 translationally-activated and 585 repressed genes vs the reported 445 / 597 -- within ~2-4%, same direction and magnitude => within-tol, NO fabrication signal. The alternative steady-state WT-vs-D208A(catalytic-dead) contrast gives 1030/1059 (not the paper's basis). NOT attempted (out of 80/20 primary scope): R2 membrane-protein GO enrichment (2.09x, needs gProfileR+REViGO) and R3 5'UTR-length comparison (needs UTR annotation); both are secondary. Verdict is automated/provisional; a human must confirm. Key infra hurdle solved: Bioconductor data CDN (mghp.osn.xsede.org) is unreachable from «our HPC», breaking genomeinfodbdata's conda post-link -- fixed by repointing dataURLs.json to the TU-Dortmund Bioconductor mirror + CONDA_SAFETY_CHECKS=disabled.
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Assessment versions
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v1 current initial assessment Score 85assessed: 2026-06-16 ⛓ d1ebec816788
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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
- 2026-06-16
- Rubric version
- v1.0
- Assessed by
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🤖 AI curator · claude (ai-curator room) · v1.0 · run #1 2026-06-16no 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 authors test whether the 5'–3' exonuclease Xrn1, known to couple nuclear transcription to cytoplasmic mRNA decay, has an additional regulatory role in mRNA translation—specifically whether it promotes translation of a defined group of transcripts encoding membrane proteins.
- ★ Xrn1 promotes translation of a specific group of mRNAs encoding membrane/secretome proteins, acting at translation initiation. finding
- ★ Xrn1-dependence for translation is mediated by a physical, RNase-resistant interaction of the Xrn1 C-terminal domain with the translation initiation factor eIF4G. mechanism
- ★ For membrane-protein mRNAs, Xrn1 coordinately stimulates transcription, translation, decay, and ER localization, linking the three major stages of gene expression. finding
- ★ Xrn1's translational role is specific and not simply due to its 5'-3' exonuclease activity, since cytoplasmic Rat1∆NLS rescues decay/growth but not translation. finding
- ★ Xrn1-dependent translation is linked to mRNAs with long, highly structured 5'UTRs that provide poor contexts for translation initiation. mechanism
- The BMV RNA2/yeast system and ribosome-profiling with an auxin-inducible degron (AID) were used to define Xrn1-dependent translation. method
- A Rat1∆NLS-XC chimera (Rat1 N-terminal domain fused to Xrn1 C-terminal tail) gains eIF4G interaction and rescues RNA2 translation, a gain-of-function demonstration. method
| Assay | System | Perturbation | Readout | Platform |
|---|---|---|---|---|
| Western blot + Northern blot (steady-state protein 2a and viral RNA2) | S. cerevisiae WT and xrn1∆ strains expressing BMV RNA2 from GAL1 promoter | XRN1 deletion (KO); UTR/CDS swaps (GAL1 5'UTR, ADH1 3'UTR, GFP CDS) | 2a protein and RNA2 levels; translatability (Δprotein/ΔRNA) | — |
| Luciferase assay (2a-Rluc) with cycloheximide chase | yeast WT and xrn1∆ | XRN1 deletion; cycloheximide translation block | Rluc activity / protein turnover and translatability | — |
| Polysome profiling (sucrose gradient 10–50%) + Northern blot | yeast WT and xrn1∆ expressing RNA2 | XRN1 deletion; EDTA treatment control | distribution of RNA2 across ribosomal fractions; rRNA UV profile at 260 nm | — |
| Polysome profiling + Western blot (Xrn1 cofractionation) | yeast WT cells | none | Xrn1, S8 (40S), L1 (60S) protein distribution across fractions | — |
| Auxin-inducible degron depletion + RT-qPCR + luciferase | yeast with AID-tagged genomic XRN1 and plasmid RNA2-Rluc (GAL1) | auxin-induced Xrn1-AID degradation; galactose induction | Xrn1-AID protein level, RNA2-Rluc RNA, 2a-Rluc protein over time | — |
| mRNA stability / decay time-course (transcription shut-off) + growth curves | xrn1∆ cells expressing WT Xrn1, Rat1∆NLS, or empty plasmid | glucose-induced GAL1 shut-off; Rat1∆NLS or chimera expression | RNA2 levels over time; cell growth | — |
| Co-immunoprecipitation + Western blot (eIF4F interaction) | yeast strains with genomic GFP-tagged eIF4G/eIF4A/eIF4E + plasmid FLAG-Xrn1 or FLAG-Rat1∆NLS / Rat1∆NLS-XC | ±RNase A treatment; GFP-trap pulldown | co-precipitation of Xrn1/Rat1 with eIF4G/eIF4A/eIF4E | GFP-trap beads; anti-GFP and anti-FLAG antibodies |
| Ribosome profiling (RPF deep-sequencing) + parallel RNA-seq | yeast Xrn1-AID strain | auxin treatment (30 min) for Xrn1 knock-down | genome-wide translational efficiency (mRNA vs ribosome occupancy log2FC), GO enrichment | — |
- ▼ Xrn1 depletion (xrn1∆) increased steady-state RNA2 level but substantially decreased 2a protein; translatability in xrn1∆ was only 0.4% of WT. 0.4% of WT (0.5% considering only capped RNA2)
- – Most RNA2 molecules are capped in the cells analyzed. 77%
- – The 5'UTR is the most Xrn1-responsive region for translatability; 3'UTR swap had no effect and CDS swap had modest effect.
- ▼ Xrn1 deletion shifted RNA2 from polysomes toward monosomal, 60S and 40S fractions, indicating an initiation defect; Xrn1 co-sediments with free 40S subunits.
- – Xrn1, but not Rat1∆NLS, co-immunoprecipitated with eIF4G in an RNase-resistant manner; neither interacted with eIF4A; both showed RNase-sensitive eIF4E interaction.
- ▲ Rat1∆NLS-XC chimera gained eIF4G interaction and increased viral 2a expression relative to Rat1∆NLS while RNA2 levels stayed similar. twofold (2x) increase in 2a
- – Ribosome profiling identified a set of genes translationally activated (445) or repressed (597) by Xrn1; activated/buffered mRNAs enriched for glycosylation, membrane and ER GO terms. 445 activated, 597 repressed
- – Rat1∆NLS fully rescued RNA2 decay and growth in xrn1∆ but only marginally recovered 2a protein, showing translation requires an Xrn1-specific function.
- other 0.4% (translatability of RNA2 in xrn1∆ relative to WT (100%))
- count 77% (fraction of RNA2 molecules that are capped)
- fold_change twofold (increase in viral 2a expression with Rat1∆NLS-XC vs Rat1∆NLS)
- count 445 activated / 597 repressed (genes translationally activated or repressed by Xrn1 (ribosome profiling))
- pvalue FDR < 0.05 (Riborex threshold for significant translational efficiency changes)
- other (log2 fold change) < 0.433 (~±35%) (threshold for considering mRNA levels stable/buffered)
- count n = 3 (biological replicates/colonies for western/northern quantifications)
- count n = 2 (replicates per condition for ribosome-profiling RPF/RNAseq libraries)
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 combines transcriptome-wide ribosome-profiling (RPF + parallel RNAseq) with targeted molecular assays (western/northern blots, RT-qPCR, luciferase, polysome profiling, co-immunoprecipitation). Genome-wide translational-efficiency changes were called with the Riborex R-package (FDR < 0.05) using DESeq2-derived log2 fold changes, with replicate quality assessed by principal-component analysis and functional groups characterized by GO/GSEA enrichment. Low-throughput experiments were typically summarized as mean ± SEM from n = 3 independent colonies/biological replicates, with individual data points overlaid.
| Test | Applied to | n | Assumptions |
|---|---|---|---|
| Riborex differential translational-efficiency analysis (assessing whether RPF/ribosome-occupancy changes exceed mRNA-level changes) | genome-wide identification of translationally activated (445) / repressed (597) genes upon Xrn1 knock-down (Fig. 5b) | n = 2 biological replicates per condition (RPF and RNAseq libraries) | not stated |
| DESeq2 (log2 fold-change estimation for mRNA and RPF levels) | computing log2FC used to classify gene groups (Fig. 5b) | n = 2 biological replicates per condition | not stated |
| Gene ontology enrichment / GSEA (Biological Process and Cellular Component), with Revigo redundancy removal | functional enrichment of translationally regulated gene groups (Fig. 5c) | — | na |
| Principal-component analysis (clustering of replicates) | quality assessment of RPF and RNAseq libraries (Supplementary Fig. 9) | n = 2 per condition | na |
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Genome-wide differential translational-efficiency testing was performed with n = 2 biological replicates per condition.↳ Could also: Including additional biological replicates (e.g., n = 3 or more) per condition would also be a standard choice. — More replicates would increase the precision of dispersion estimates used by DESeq2/Riborex and is often preferred for stabilizing variance estimation in count-based RNA/RPF data.
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Low-throughput quantifications were summarized as mean ± SEM from n = 3.↳ Could also: Reporting the standard deviation or a 95% confidence interval alongside the individual points would also convey the data spread. — SD or a CI communicates the variability of the observations themselves rather than the precision of the mean, which many style guides favor for small n; the authors' practice of overlaying individual data points already supports this transparency.
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The FDR threshold (FDR < 0.05) was used to call significance for genome-wide hits, with the specific procedure not named in the provided text.↳ Could also: Explicitly stating the multiple-testing method (e.g., Benjamini-Hochberg) and reporting adjusted p-values per gene would also be a common approach. — Naming the correction and providing per-gene adjusted values aids reproducibility and lets readers evaluate the family-wise/false-discovery control applied.
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Group comparisons (e.g., WT vs xrn1∆ for blot/luciferase quantifications) are presented with descriptive means and SEM.↳ Could also: Pairing these descriptive summaries with a stated inferential test (e.g., a t-test or Mann-Whitney U for small n) and reported effect sizes would also be an option. — An explicitly named test with exact p-values and effect sizes would let readers gauge both statistical and biological magnitude for each comparison.
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GO/GSEA enrichment terms were reported ordered by p-value after Revigo redundancy removal.↳ Could also: Reporting the enrichment adjusted p-values (and the background gene set used) would also be standard. — Documenting the background universe and the multiplicity adjustment for the enrichment family helps readers interpret and reproduce the functional-enrichment results.
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Randomization and blinding were not described.↳ Could also: Stating whether sample processing/quantification was blinded or the order randomized would also be a common reporting practice. — Explicit statements about blinding/randomization (even when 'not applicable') improve transparency for quantitative image- and assay-based measurements.
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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XRN1 deletion shifts BMV RNA2 from polysomes to monosomal/40S/60S fractions indicating a translation initiation defect; Xrn1 co-sediments with free 40S subunits.other saccharomyces cerevisiae down 2019×1papers★ This paper is the founder (earliest)
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77% of BMV RNA2 molecules are 5'-capped in yeast, confirming the Xrn1 translational effect operates predominantly on capped mRNA.other saccharomyces cerevisiae 2019×1papers★ This paper is the founder (earliest)
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Genome-wide ribosome profiling shows Xrn1 depletion translationally represses 445 mRNAs enriched for membrane, ER, and glycosylation functions while activating 597 others.other saccharomyces cerevisiae mixed 2019×1papers★ This paper is the founder (earliest)
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XRN1 deletion reduces BMV 2a protein translatability to 0.4% of wild-type despite elevated RNA2 steady-state levels, indicating a severe translation defect.western-blot saccharomyces cerevisiae down 2019×1papers★ This paper is the founder (earliest)
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Rat1∆NLS rescues BMV RNA2 mRNA stability in xrn1∆ but fails to restore 2a protein translation, revealing an Xrn1-specific translational function distinct from its decay activity.western-blot saccharomyces cerevisiae none 2019×1papers★ This paper is the founder (earliest)
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Rat1∆NLS chimera bearing the Xrn1 C-terminus gains eIF4G interaction and restores 2a protein expression approximately 2-fold relative to Rat1∆NLS alone at similar RNA2 levels.western-blot saccharomyces cerevisiae up 2019×1papers★ This paper is the founder (earliest)
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The 5'UTR of BMV RNA2 is the primary Xrn1-responsive element for translational activation; 3'UTR swap has no effect and CDS swap has only modest effect.western-blot saccharomyces cerevisiae 2019×1papers★ This paper is the founder (earliest)
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Xrn1 co-immunoprecipitates with eIF4G in an RNase-resistant manner, indicating a direct protein-protein interaction independent of RNA bridging.western-blot saccharomyces cerevisiae 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.
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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 — pmid-30899024 (Blasco-Moreno et al. 2019, Nat Commun)
"The exonuclease Xrn1 activates transcription and translation of mRNAs encoding membrane proteins."
Code/data availability (verbatim findings)
- Data availability (paper): "Ribosome Profiling and Genomic Run-On (GRO) raw data are available under accession GSE109734 and GSE123326 at Gene Expression Omnibus (GEO)."
- Code availability (paper): NONE present. No GitHub URL in the paper.
- Harvested code link
github.com/abelew/prfdbis a MIS-HARVEST: it is a 2009–2016 Perl tool ("scripts to search genomic data for significant secondary structures", prfdb = Programmed Ribosomal Frameshift DB, Belew/Dinman lab) — unrelated to this Xrn1 transcription/translation paper. Do NOT use it. Reproduction proceeds per P16: apply the documented third-party pipeline to the paper's own data.
Pipeline (from Methods, well-specified)
- Aligner: Bowtie
-S -t -p 30 -n 1 -m 1 -l 25 --norcto sacCer3 transcriptome (SGD). - Ribo-seq: footprints filtered to 28–32 nt.
- Differential translation: Riborex R-package v1.2.3 (FDR < 0.05) — the core tool.
- DESeq2 for moderated log2 fold changes.
- GO: gProfileR (FDR, moderate hierarchical filtering) + REViGO.
IN SCOPE (pipeline-derived, attempted)
- R1 (headline): # genes translationally activated by Xrn1 = 445 (FDR<0.05);
translationally repressed = 597 (FDR<0.05). Reproduce by running Riborex on the
GEO processed count tables (GSE109734_raw_counts_RPF.tsv.gz,GSE109734_raw_counts_mRNA.tsv.gz) with the paper's contrast. 80/20 PRIMARY TARGET.
IN SCOPE (secondary, if time)
- R2: 2.09-fold enrichment of membrane proteins among activated transcripts (GO/gProfileR).
- R3: 5'UTR length 80 nt (activated) vs 52 nt (background).
OUT OF SCOPE (wet-lab / not pipeline / external)
- Auxin-degron western blots, GRO transcription-rate wet measurements, polysome profiles, microscopy/ER-localization imaging, half-life (mRNA stability ±0.433 log2FC) is borderline — derived from decay measurements, attempt only if a count/decay table is shipped.
Data
- GSE109734: yeast S. cerevisiae, Ribo-seq + RNA-seq, auxin-inducible Xrn1 degron, t0 vs t30 (30 min auxin), WT + Xrn1-D208A strains, 20 GSM samples. SRA: SRP131527.
- Processed count tables shipped as series supplementary → enables count-based repro.
Assessments & scoring basis
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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.
The headline claims reproduce cleanly: 445→429 (−3.6%) activated and 597→585 (−2.0%) repressed genes on the correct auxin-degron t0→t30 contrast, derivable from the public GEO GSE109734 count tables with the documented Riborex pipeline — no fabrication signal. The small gap sits on the input/preprocessing side (unspecified gene-filtering and DESeq2 independent-filtering defaults), and we had to self-select the matching contrast (the alternative WT-vs-D208A gives 1030/1059). The registry code link is a mis-harvest, so the run used the documented third-party tool, not authors' code. Overall a solid, core-confirming reproduction with minor explainable deviations; secondary claims R2 (2.09× membrane enrichment) and R3 (5′UTR length) were out of scope and unchecked.
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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.