Free circular introns with an unusual branchpoint in neuronal projections.
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 relevant deviation in data/preprocessing
- ✓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
- ✓Overall, the reproduction was clean
- Every checked point held up.
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.
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When this reproduction was carried out, which methodology version was used, and by whom — so the record can be audited and checked independently.
- Reproduced
- 2026-06-19
- Rubric version
- v1.0
- Assessed by
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🤖 AI curator · claude (ai-curator room) · v1.0 · run #1 2026-06-18no human curator yet
- Last updated
- 2026-07-29
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: opusWhich RNAs—particularly intron sequences (both retained and excised)—are localized to neuronal projections, as systematically identified by sequencing total (rRNA-depleted) RNA rather than polyadenylated RNA from primary rat hippocampal neurons.
- ★ A set of free circular introns with a non-canonical (C) branchpoint is enriched in distal neuronal projections; these appear to be tailless lariats that escape debranching. finding
- ★ These free circular introns lack ribosome occupancy, sequence conservation, and known localization signals, and their function is unknown. finding
- ★ Total RNAseq of physically dissected neuro-glial projections versus whole cells reliably distinguishes and quantifies projection-localized versus nuclear-localized RNAs. method
- ★ Hundreds of intron regions (retained and excised) are localized to projections, and 1632 intron regions show reliable coverage in projections. finding
- ★ Contrary to prior reports, no Kcnma1 introns are retained or localized to projections; only spliced Kcnma1 isoforms are detected in projections. finding
- Ribosomal protein mRNAs and mitochondrial transcripts are enriched in neuronal projections. finding
- ★ A culture system using semipermeable membranes with 1 μm pores physically separates neuro-glial projections from cell bodies/nuclei for compartment-specific RNA sequencing. method
- Sequenced datasets (total RNAseq, PASseq, ribosome profiling, polyA+ RNAseq) constitute a resource for studying RNA localization in neurons (GSE129924). resource
| Assay | System | Perturbation | Readout | Platform |
|---|---|---|---|---|
| rRNA-depleted total RNAseq (paired-end) | primary rat hippocampal neuro-glial cultures on 1 μm pore membranes (projection and whole cell) | DNA replication inhibitor to block glial division; physical fractionation | RNA abundance (TPM) of polyA+ and polyA- long RNAs; intron region coverage | Illumina, 100–125 nt reads, ~200 nt insert |
| PolyA-site sequencing (PASseq) | primary rat hippocampal cultures (projection and whole cell) | none | polyadenylation sites (to distinguish retained introns from intronic polyA) | — |
| Ribosome profiling | cytoplasmic (nuclei-depleted) fraction of primary rat hippocampal neurons on plates | none | ribosome occupancy / coding exon identification | — |
| PolyA+ selected RNAseq | cytoplasmic (nuclei-depleted) fraction of primary rat hippocampal neurons on plates | none | coding exon identification | — |
| single-molecule FISH (smFISH, RNAScope) | primary rat hippocampal neurons | none | subcellular localization of mRNAs, exons, and introns | RNAScope probe sets |
| Immunofluorescence imaging | primary rat hippocampal neuro-glial cultures on membranes | none | MAP2/DAPI/GFAP/Vimentin localization confirming projection separation | — |
| Microcapillary electrophoresis (Bioanalyzer RNA pico) | total RNA from whole cells and projections | none | RNA size distribution | Bioanalyzer |
- ▲ 1440 transcripts significantly enriched in projections, including Pabpc1, Map2, Dlg4, Gfap fold-change >1.5, q<0.01
- ▼ 1486 genes significantly depleted from projections, including nuclear ncRNAs Xist, Malat1, Meg3, snoRNAs, scaRNAs >1.5 fold, q<0.01
- ▲ 70 annotated ribosomal protein mRNA isoforms enriched in projections >2-fold
- – Of 190,180 intron regions, 57,432 reliably covered in whole cells but only 1632 in projections 1632 of 190,180
- – Classification of 1632 projection intron regions: 385 unannotated alt 5'SS/polyA (high EI), 320 alt 3'SS/TSS (high IE), 428 retained introns (high EI+IE)
- – smFISH confirmed Creld1 free intron detectable in distal projections, not colocalizing with Creld1 exons
- – No Kcnma1 introns retained/localized to projections; only spliced isoforms detected
- – Calm2 intron-retaining isoform abundant in both compartments with no selective enrichment
- count 190,180 intron regions total (genomic intron regions analyzed)
- count 57,432 reliably covered in whole cell; 1632 in projection (intron region detectability across 5 biological replicates)
- count 1440 enriched, 1486 depleted in projections; 16,899 no significant enrichment (differential expression of 19,815 transcripts)
- correlation Spearman ≥0.83 (projection), ≥0.88 (whole cell) (replicate TPM correlation)
- fold_change >1.5 fold, q<0.01 (significance threshold for projection enrichment/depletion)
- fold_change >2-fold (70 RP mRNA isoforms enriched in projections)
- count 30–80 million mate pairs per sample (total RNAseq depth, 5 replicates/10 samples)
- other projection:whole cell TPM — Pabpc1 40:12, Rpl4 297:96, Srsf5 18:37, Ubc 162:146, Ppib 43:50, Polr2a 2:4 (smFISH-validated mRNA ratios)
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 study physically dissected neuronal projections from whole cells in primary rat hippocampal cultures and compared RNA content using rRNA-depleted total RNA-seq (n=5 biological replicates per condition). Transcript abundance was quantified with Kallisto and differential expression between projections and whole cells was tested with Sleuth, using a combined q-value <0.01 and fold-change >1.5 significance threshold. Intron-region coverage was assessed via fixed count-density thresholds rather than a formal statistical test, and selected genes were validated by smFISH. Replicate reproducibility was summarized using Spearman's correlation on TPM values.
| Test | Applied to | n | Assumptions |
|---|---|---|---|
| Sleuth differential expression test (Wald test with FDR q-value) on Kallisto TPM quantifications | Projection versus whole-cell comparison across 19,815 annotated RNA transcripts | 5 biological replicates per condition (10 samples total) | not stated |
| Spearman's rank correlation coefficient | Pairwise biological replicate reproducibility within whole-cell and projection RNAseq datasets (TPM values) | 5 biological replicates per condition | not stated |
| Gene ontology enrichment analysis (specific test not named) | Genes significantly enriched in projections or whole cells | — | not stated |
| Fixed coverage threshold filtering (≥1 read per replicate and mean read density >0.005 reads/nt) | 190,180 intron regions screened for reliable coverage in projection and whole-cell libraries | 5 biological replicates | na |
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Differential expression was assessed using Kallisto pseudo-alignments fed into Sleuth↳ Could also: DESeq2 or edgeR (via tximport to import Kallisto count estimates) could also be used for projection vs. whole-cell differential expression — DESeq2 and edgeR are extensively benchmarked negative-binomial frameworks for small-n RNA-seq; running them alongside Sleuth would provide a sensitivity check on findings, as the three methods can yield different results for low-count features
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Intron-region enrichment in projections was identified using fixed read-density thresholds rather than a formal statistical test↳ Could also: A count-based differential analysis on intron bins (e.g., DEXSeq, or featureCounts + DESeq2) could also formally test enrichment across the 190,180 intron regions with FDR correction — A model-based approach would provide calibrated error rates across the full set of tested intron regions, complementing the threshold-filtering strategy
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Replicate reproducibility was summarized pairwise using Spearman's correlation on TPM values↳ Could also: Principal component analysis (PCA) or multidimensional scaling on sample-level counts could also be used for quality control — PCA simultaneously visualizes variance structure and potential outliers across all samples, providing a global view that pairwise correlations summarize but do not display
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Results are reported as fold-change values without accompanying uncertainty estimates↳ Could also: Shrinkage-based log-fold-change estimation (e.g., DESeq2 lfcShrink with apeglm) could also be reported alongside nominal fold-changes — Shrinkage estimators reduce variance inflation for low-count features, producing more stable rankings of enriched transcripts and making effect sizes more comparable across the abundance range
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The gene ontology enrichment test method and background gene set were not specified↳ Could also: Standard approaches such as a hypergeometric test or Fisher's exact test with FDR correction (e.g., clusterProfiler, topGO, or g:Profiler) with an explicit background could also be named — Specifying the background set and correction method allows readers to assess the scope of the multiple-testing correction applied across GO terms and to reproduce the enrichment analysis
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smFISH validation was assessed qualitatively by visual inspection of spot distributions in cell bodies versus projections↳ Could also: Quantitative per-cell spot counting in soma versus projection compartments, summarized with a ratio and tested with a paired or mixed-effects model, could also be used — Quantitative spot counts would provide a numerical enrichment estimate with dispersion, enabling a direct statistical comparison between smFISH-derived ratios and RNAseq TPM projection:whole-cell ratios
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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CRELD1 free intron is detectable in distal neuronal projections by smFISH and does not colocalize with CRELD1 exons, indicating it exists as a free intron species independent of the host mRNAimaging rat hippocampal-neuron 2019×1papers★ This paper is the founder (earliest)
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CALM2 intron-retaining isoform is abundant in both neuronal cell bodies and projections with no selective enrichment in either compartmentRNA-seq rat hippocampal-neuron none 2019×1papers★ This paper is the founder (earliest)
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Of 1632 projection intron regions, 385 show elevated exon-to-intron ratios (free or alt-5'SS), 320 show elevated intron-to-exon ratios (free or alt-3'SS), and 428 are retained intronsRNA-seq rat hippocampal-neuron 2019×1papers★ This paper is the founder (earliest)
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Only 1632 of 190,180 intron regions are reliably detected in rat hippocampal neuron projections, indicating intronic RNA is severely depleted from the axonal/dendritic compartment relative to whole cellsRNA-seq rat hippocampal-neuron down 2019×1papers★ This paper is the founder (earliest)
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KCNMA1 introns are absent from projections; only spliced isoforms are detected, serving as a negative control for selective free intron localizationRNA-seq rat hippocampal-neuron none 2019×1papers★ This paper is the founder (earliest)
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1440 transcripts including PABPC1, MAP2, DLG4, and GFAP mRNAs are significantly enriched (>1.5-fold, q<0.01) in rat hippocampal neuron projections relative to whole cellsRNA-seq rat hippocampal-neuron up 2019×1papers★ This paper is the founder (earliest)
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1486 genes including nuclear ncRNAs XIST, MALAT1, MEG3, snoRNAs, and scaRNAs are significantly depleted (>1.5-fold, q<0.01) from rat hippocampal neuron projectionsRNA-seq rat hippocampal-neuron down 2019×1papers★ This paper is the founder (earliest)
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70 annotated ribosomal protein mRNA isoforms are enriched >2-fold in rat hippocampal neuron projectionsRNA-seq rat hippocampal-neuron up 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-31697236
Paper: Saini H, Bicknell AA, Eddy SR, Moore MJ. "Free circular introns with an unusual branchpoint in neuronal projections." eLife 2019;8:e47809. PMCID PMC6879206 · DOI 10.7554/eLife.47809.
Listed code: https://github.com/marvin-jens/find_circ (a third-party tool — find_circ, Memczak 2013 — used by the authors, per P16 equally valid). Data: GEO GSE129924 / SRA PRJNA533159 (22 samples; Rattus norvegicus). Author supplement (key): http://eddylab.org/publications/Saini19/Saini19-supplement.tar.gz — ships the analysis code (R notebooks, Perl/Python) AND intermediate inputs (kallisto abundances for all 10 total-RNAseq samples; source-data tables for Figs 2 & 3). This makes most of the pipeline-derived results reproducible deterministically without re-aligning raw reads.
Pipelines used in the paper
- kallisto 0.44.0 (transcript quant, Rnor_6.0.91 cDNA+ncRNA+Xist, 100 boots,
--rf-stranded) → sleuth 0.30.0 (R 3.5.1) DE: whole-cell (CB) vs projections (P), Wald test onconditionP. → Figure 2. - Custom intron-region pipeline (TopHat2/Bowtie2 align to Rnor_6.0 Ensembl 81;
exon2intron_dexseqgff.pl + dexseq_prepare_annotation.py to define 190,180 intron
regions; per-region coverage, exon-intron (EI) / intron-exon (IE) junction reads,
PASseq polyA reads, ribosome-profiling reads) → intron classification (Figs 3–4).
Counting logic is in
Rscript_plots_Saini_et_al_2019.Rmdoperating on the shippedFigure3-SourceData1_All_Introns.tsv(190,180 rows × 73 cols). - find_circ (Memczak 2013; bowtie2 → unmapped2anchors → find_circ.py) on the
projection total-RNAseq → circularly-permuted (circular intron) junction reads;
per-intron
circ_num_pcolumn feeds Fig 5. Branchpoint analysis (Fig 6) from RT mismatches in circularly-permuted reads. - cleanUpdTseq (PASseq polyA-site calling) — supporting.
In scope (pipeline-derived → attempted)
| # | Result | Pipeline | How reproduced |
|---|---|---|---|
| A1 | Fig 2 DE table + projection-enriched / -depleted transcript counts | kallisto→sleuth | re-run sleuth 0.30.0 on shipped kallisto outputs; cross-check vs shipped Fig2 source data |
| A2 | 190,180 intron regions; 1,632 P-covered; 57,432 CB-covered; EI/IE classes 385/320/428/499; free 499→96 polyA / 221 ribo / 278 free | custom intron pipeline (downstream classification) | recompute deterministically from shipped All_Introns source table using the exact Rmd filter logic (validates numbers are derivable from shipped data → anti-fabrication check) |
| B | circular introns in projections (circ_num_p≥2, enriched) + branchpoint count (14; 12 C / 2 G) |
find_circ on projection RNA-seq | run find_circ on the 5 projection total-RNAseq libraries (SRR8919670–674); compare detected circular-intron set to the All_Introns circ_num_p column and the paper's branchpoint result |
Out of scope (not pipeline-derived / not attempted)
- Wet-lab: RNase-R/RNase-H validation, RT-PCR, Northern blots, branchpoint sequencing of individual introns, microscopy (Figs 1, 6A/B, 7).
- Manual curation steps (e.g. manual selection of RP genes from GO:0005840; manual branchpoint inspection of the 14 introns).
- GO-term enrichment (Fig 3/4 supplements) — depends on an external GO service snapshot; low priority.
- PASseq cleanUpdTseq polyA-site calling — supporting, raw-data heavy; not primary.
Reproduction strategy
A2 first (fast, deterministic, confirms ~10 reported numbers). A1 next (genuine re-run of the statistical pipeline from shipped intermediates). B last (heaviest; the named repo tool on raw reads). 80% floor = A1+A2; B is the harder reach.
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.
This is essentially a 1:1 computational reproduction: the authors shipped both their analysis code and intermediate inputs, and 14/16 claims reproduce exactly — counts recomputed deterministically from the All_Introns table and the DE counts (1440) re-run in sleuth with cor(b)=cor(qval)=1.0. The only numeric deviation is C14 (1488 vs 1486, 0.13%), two transcripts flipping across the q=0.01 cutoff under R 3.6.3 vs 3.5.1 — a technical version effect, not a methodology or authors' defect. The one flagged anomaly (C11's mislabeled # 221 code comment) is a stale comment, not fabrication, since the reported 96/221/278 partition is internally consistent and fully derivable; C16 (12C/2G branchpoint) is simply out of computational scope (wet-lab RT-mismatch). Overall quality is green.
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Reproduction footprint
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