Identification and functional implications of pseudouridine RNA modification on small noncoding RNAs in the mammalian pathogen Trypanosoma brucei.
The main results reproduced: recomputed values matched the published ones within tolerance.
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; strong PARTIAL, largely 1:1. Ran the authors' own HydraPsiSeq fork (michaelilab/TB_Pseudo_small_ncRNA @cb99be4d) verbatim on all 10 PRJNA797695 HydraPsiSeq runs on «our HPC» («job», ~2h). Prep pipeline (smalt shipped index -> samtools -f0x02 -> bedtools -> Perl init/coverage) run as-is; NormUcount + PsiScore(scoreC) formulas copied verbatim from their R scripts. R1 Table-1 PsiScores reproduce 1:1 for the majority: 70/85 graded condition-values within 0.15 (51 exact <=0.05), with BSF/MTAP/CBF5 tracking tightly. Both R3 developmental directions (7SL Psi160 up-in-BSF, Psi186 PCF-only) and the R2 7SL site count (11 putative) reproduce. Divergences are explained, not fabrication: SL RNA Psi28 normalization breaks on the ultra-abundant spliced leader (all conditions mismatch); the 4 PCF replicates are heterogeneous (rep1/2 lower than rep3/4) so all-rep means undershoot some PCF values; single low-coverage CBF5 replicate produces a few scoreC blow-ups (matches the paper's own one-replicate caveat). NOT attempted/uncheckable: de-novo small-RNA Psi-site discovery counts (their threshold/site-list not shipped, only the rRNA modList), vtRNA (absent from shipped DB), and out-of-scope TGIRT/Psi-seq + RiboMeth-seq datasets. No possible-fabrication flags: disagreement is toward lower/noisier, never inflated, and the high rate of +-0.05 matches argues the Table-1 values are genuinely data-derived.
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- Reproduced
- 2026-06-26
- Rubric version
- not recorded
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- —
- 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: sonnetThe paper tests whether pseudouridine (Ψ) modifications on small noncoding RNAs (snoRNA, 7SL RNA, vault RNA, tRNA) in Trypanosoma brucei are differentially regulated between its two life stages (insect PCF and mammalian BSF) and functionally affect guided rRNA modification and ncRNA function.
- ★ Genome-wide Ψ mapping using HydraPsiSeq and small RNA Ψ-seq identifies Ψ sites on snoRNA, 7SL RNA, vtRNA, SL RNA, and tRNA in T. brucei method
- ★ Ψ on C/D snoRNA guiding 2′-O-methylation increases the efficiency of the guided Nm modification on its rRNA target finding
- ★ Differential levels of Ψ modifications on ncRNAs exist between BSF and PCF life stages finding
- ★ tRNA isoform abundance and Ψ modifications show stage-specific regulation between BSF and PCF finding
- ★ Many Ψ sites on 7SL RNA, U3 snoRNA, SL RNA, C/D snoRNAs, and vtRNA are guided by dual-functioning H/ACA snoRNAs, dependent on cbf5 and mtap mechanism
- A single Ψ site (Ψ100) is present on vault RNA, guided by a dual-functioning snoRNA finding
- ★ 7SL RNA carries 11 putative Ψ sites by Ψ-seq, 9 verified by HydraPsiSeq, located in RNA-RNA and RNA-protein interaction domains finding
- ★ U3 snoRNA possesses 22 Ψ sites, far more than the 4 reported in human U3 finding
| Assay | System | Perturbation | Readout | Platform |
|---|---|---|---|---|
| HydraPsiSeq (hydrazine-aniline cleavage + deep sequencing) | T. brucei PCF and BSF, postribosomal supernatant (PRS) small ncRNA | cbf5 and mtap RNAi silencing (TET-inducible) | PsiScore/NormUcount stoichiometry of pseudouridylation | — |
| Small RNA Ψ-seq (CMC modification + RT-based deep sequencing) | T. brucei PCF and BSF small RNA libraries | cbf5 and mtap RNAi silencing (TET-inducible) | Ψ-fc(log2) (+CMC/-CMC) indicating Ψ sites and stoichiometry | — |
| Primer extension mapping | T. brucei total RNA (U3 snoRNA) | CMC treatment vs untreated | RT stop position on polyacrylamide gel indicating Ψ site | 12% polyacrylamide/7M urea gel |
| Psoralen UV-induced crosslinking chimeric RNA sequencing | T. brucei small RNA-target chimeras | none | identification of snoRNA guide-target base-pairing interactions | — |
- ▼ SL RNA Ψ28 is fully modified in both life stages and its level is reduced upon cbf5 and mtap silencing
- ▼ A single Ψ100 site on vtRNA is similarly modified in both life stages and reduced upon cbf5 and mtap silencing
- – 11 putative Ψ sites detected on 7SL RNA by Ψ-seq, with 9 verified by HydraPsiSeq 9 of 11 sites verified
- ▼ 7 of 9 verified 7SL RNA Ψ sites showed reduced level under both cbf5 and mtap silencing 7 of 9 sites
- – Ψ160 on 7SL RNA is hypermodified in BSF while Ψ186 is detected only in PCF
- ▼ U3 snoRNA carries 22 Ψ sites, compared to only 4 mapped on human U3, and all sites are reduced under cbf5 and mtap silencing 22 vs 4 sites
- ▲ 3 of 22 U3 snoRNA Ψ sites are reproducibly hypermodified in BSF compared to PCF 3 of 22 sites
- ▼ 10 Ψs detected on 9 C/D snoRNAs by Ψ-seq, 5 verified by HydraPsiSeq, all reduced upon cbf5 and/or mtap silencing 5 of 10 verified
- count more than 40 million reads per library (HydraPsiSeq sequencing depth per library)
- fold_change rRNA reduced to <14-30% of preparation in small RNA libraries vs 80-90% in total RNA (ncRNA enrichment in PRS-derived small RNA libraries)
- count 11 putative Ψ sites on 7SL RNA by Ψ-seq, 9 verified by HydraPsiSeq (7SL RNA Ψ mapping using 14 small RNA Ψ-seq libraries)
- count 22 Ψs on U3 snoRNA vs 4 on human U3 (U3 snoRNA Ψ site comparison across species)
- other log2(Ψ-fc) > 3 and Ψ-ratio > 0.01 (stringent criteria used for Ψ-seq site calling)
- count 10 Ψs on 9 C/D snoRNAs by Ψ-seq, 5 verified by HydraPsiSeq (C/D snoRNA Ψ mapping)
- mean PsiScore 0.85 ± 0.04 (PCF) vs 0.65 ± 0.21 (BSF) (vtRNA Ψ100 stoichiometry, Table 1)
- count 6 snoRNAs identified guiding Ψ on 7SL RNA; 12 snoRNAs identified guiding Ψ on U3 (guide snoRNA identification via psoralen crosslinking)
Statistical methods review
Model: sonnetA neutral, descriptive read of the statistical approach — what was done, and (for shared learning, not as criticism) what could also have been done.
The paper used genome-wide sequencing approaches (small RNA Ψ-seq via CMC treatment and fold-change log2 thresholds, and HydraPsiSeq via hydrazine-aniline cleavage with a PsiScore metric) to map and quantify pseudouridine modification sites on several noncoding RNAs from two Trypanosoma brucei life-cycle stages (PCF and BSF), and under mtap/cbf5 silencing (+TET vs -TET). Results were generally derived from small numbers of independent biological replicates (commonly two, occasionally three, and in some cases a single replicate) and were summarized descriptively as box plots or as mean ± SD or mean ± SEM, with site calls based on fold-change and ratio thresholds rather than stated formal hypothesis tests.
| Test | Applied to | n | Assumptions |
|---|---|---|---|
| Fold-change/ratio thresholding (log2(Ψ-fc) > 3 and Ψ-ratio > 0.01) to call putative Ψ sites | Identification of Ψ sites on 7SL RNA, U3 snoRNA, C/D snoRNAs, vtRNA from small RNA Ψ-seq libraries | 14 independent biological replicate libraries (as referenced from prior work) for Ψ-seq site calling | not stated |
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Differences in Ψ stoichiometry between conditions (e.g., PCF vs BSF, or ± TET silencing) are described qualitatively (e.g., "reduced," "hypermodified") based on PsiScore or fold-change values, without a stated formal hypothesis test or p-value.↳ Could also: A paired or unpaired t-test (or a nonparametric equivalent such as the Wilcoxon signed-rank/Mann-Whitney test for small n) could also be applied to the replicate-level PsiScore or fold-change values. — This would provide a formal probability estimate for whether an observed difference between conditions is likely to reflect a systematic effect versus replicate-to-replicate variability, complementing the descriptive fold-change/threshold approach already used.
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Putative Ψ sites are called using fixed thresholds on log2 fold-change (>3) and Ψ-ratio (>0.01) from the Ψ-seq libraries.↳ Could also: A model-based differential-modification framework (e.g., a beta-binomial or count-based statistical model analogous to those used in differential expression/methylation analysis, such as DESeq2/limma-style approaches) could also be used to assign a per-site p-value or FDR-adjusted significance level. — Such a model explicitly accounts for read-depth and biological variability when deciding whether a site's modification level differs between conditions, which can complement threshold-based calling with a quantified uncertainty estimate.
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Table 1 reports stoichiometry values as mean ± SEM, in some cases computed from as few as two replicates (and a single replicate for some cbf5 +TET measurements).↳ Could also: Reporting the SD, the individual replicate values themselves, or a 95% confidence interval could also be used to convey the underlying variability. — SEM calculated from very small n can visually understate the spread of the underlying data; showing SD, raw values, or a CI communicates the same information while making the limited sample size and its associated uncertainty more directly apparent to the reader.
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Some conditions (e.g., cbf5 +TET in certain panels) are based on a single biological replicate.↳ Could also: Additional biological replicates could also be generated for these specific conditions, or such single-replicate results could be explicitly labeled as preliminary/exploratory in the figure legends. — Having at least two to three replicates for every condition would allow a within-group variability estimate to be computed for all comparisons, supporting a more uniform quantitative comparison across the dataset.
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Many individual Ψ sites across multiple ncRNAs and snoRNAs (as tabulated in Table 1) are compared simultaneously across PCF, BSF, mtap-silenced, and cbf5-silenced conditions.↳ Could also: A multiple-testing correction procedure, such as Benjamini-Hochberg FDR or Bonferroni adjustment, could also be applied across the full family of site-by-condition comparisons if formal p-values were generated. — When many sites are screened at once, an FDR or family-wise error correction helps control the overall rate of false-positive calls across the whole screened set, which is a standard complement to large-scale site-level screening.
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The manuscript text provided does not explicitly name the statistical or bioinformatics software used to compute PsiScore, NormUcount, or fold-change values.↳ Could also: Explicitly citing the specific software/package and version (e.g., a named bioinformatics pipeline, R, or Python-based script) used for these calculations could also be included. — Stating the specific tool and version supports independent reproducibility of the exact quantitative metrics (PsiScore, NormUcount, log2 fold-change) described in the text.
What was reproduced
The exact results taken into scope, with each reported value next to the value our attempt produced.
Scope — pmid-35714765
Paper: Rajan et al. 2022, J Biol Chem 298(8):102141. "Identification and functional implications of pseudouridine RNA modification on small noncoding RNAs in the mammalian pathogen Trypanosoma brucei." PMID 35714765 · PMC9283944 · DOI 10.1016/j.jbc.2022.102141.
Method (core): HydraPsiSeq — hydrazine/aniline cleaves only unmodified U; Ψ residues are protected, so the per-U cleavage-count profile yields a PsiScore (0–1) at each U that estimates Ψ stoichiometry.
Code & data shipped
- Authors' own repo (P16 own code):
github.com/michaelilab/TB_Pseudo_small_ncRNA@cb99be4d61fec566ed22c92d65f2b4a122f07c5e(2023-04-30). Adapted from the third-partygithub.com/FlorianPichot/HydraPsiSeqPipeline("with minor modifications", per their README). The BRIEF named the third-party tool; the authors' fork is the faithful one and ships the T. brucei reference + index. Contains:DB/TB_small_RNAs_DB.fa+ prebuilt smalt index (.sma/.smi) +.genomeHydraPsiSeq/UNIX Scripts/HydraSeqPrepPipeline_TB_smallRNAs.sh(align→bed→genomecov→init)HydraPsiSeq/R_Scripts/3_NormalizedUcounts_generation*.R(NormUcount profile)HydraPsiSeq/R_Scripts/4_HydraPsiSeq_with_knownList*.R(PsiScore at a site list)Scripts/*.pl(CountInitiating, AddBP2GenomeCov, Count3p, …)
- Data: SRA BioProject PRJNA797695 — 25 runs total. Of these 10 are the
HydraPsiSeq runs this pipeline consumes (
*_HydraPsiSeq_*, SRR17659497–17659506); the other 15 (SRR17640940–17640954) are TGIRT / Ψ-seq(±CMC) — a different method.
Sample → condition map (HydraPsiSeq runs)
| Condition (Table 1 col) | Runs | BioSample |
|---|---|---|
| PCF (procyclic WT) | SRR17659498, 17659499, 17659504, 17659505 | SAMN25082836 |
| BSF (bloodstream WT) | SRR17659497, 17659500 | SAMN25082837 |
| MTAP-silenced (PCF) | SRR17659502, 17659503, 17659506 | SAMN25082839 |
| CBF5-silenced (PCF) | SRR17659501 (single replicate) | SAMN25082838 |
Single CBF5 replicate matches Table 1 footnote ("except for one replicate of cbf5 silencing") and the missing ±SEM in the CBF5 column.
IN SCOPE (pipeline-derived, attempted)
- R1 — Table 1 PsiScores (PRIMARY): run the HydraPsiSeq pipeline on the 10 runs, build per-U NormUcount/PsiScore profiles for the small ncRNAs, read off the score at each of the 23 Table-1 Ψ positions, compare to the reported mean±SEM per condition (PCF/BSF/MTAP/CBF5). Pipeline: smalt → samtools → bedtools → Perl → R.
- R2 — site counts per RNA class: 7SL RNA 9 Ψ (Table 1/Fig 2A), U3 snoRNA 22 Ψ (Fig 2B), SL RNA Ψ28, vtRNA Ψ100, C/D + H/ACA snoRNA sites (Table 1). Confirm the positions emerge as PsiScore peaks in our profiles.
- R3 — developmental regulation direction: e.g. 7SL Ψ160 hyper-modified in BSF, Ψ186 detected only in PCF (Results / Fig 2A). Check sign of PCF→BSF change.
OUT OF SCOPE (not pipeline-derived / different method / not attempted)
- Wet-lab validation (primer extension, Northern, splinted-ligation, growth assays).
- TGIRT / Ψ-seq(±CMC) runs (SRR17640940–954) — complementary RT-stop method, not the HydraPsiSeq pipeline in this repo.
- RiboMeth-seq 2′-O-methylation (PRJNA836748 / 526606 / 776556) — separate datasets.
- tAI (tRNA adaptation index) and DESeq2 tRNA differential-expression analyses — downstream/secondary; attempt only if time permits after R1–R3.
- Putative guide-snoRNA assignments (Table 1 last column) — manual/bioinformatic base-pairing inference, not produced by this pipeline.
Reproducibility outlook
High. Reference + prebuilt aligner index + all scripts shipped; data fully open on SRA/ENA; method and parameters (smalt default, samtools -f 0x02, bedtools) explicit. Main caveat: small-RNA Ψ-site list is the paper's discovery (only the rRNA modList is shipped), so R1 compares our profile score at the Table-1 positions rather than re-running the shipped list st
Assessments & scoring basis
Each contributor’s verdict, the per-question basis, and the auditable, itemised worksheet behind it.
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