Transcriptome analysis provides insights into the regulatory function of alternative splicing in antiviral immunity in grass carp (Ctenopharyngodon idella).
Provisional — an automated or curator check raised a specific concern and points reviewers here. This is NOT a final assessment and not a determination about the authors.
The main results reproduced, with only marginal, non-material deviations.
Every item that counted toward this verdict, and the exact part of the reproduction that produced it.
- ✓Same input data as the authors
- ✓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
- 🟡Reported values were not (fully) derivable from the shared data
- 🟡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 at the front of the pipeline; result is PARTIAL / DIFFERENT on the headline assembly counts. Reproduced end-to-end on «our HPC» from public SRA SRP049081: C1 raw read counts EXACT (111,985,560; all 4 libraries 1:1). C2 clean reads within-tol (111,017,004 fastp vs 107,959,648, +2.83%, different QC tool). Trinity 2.15.1 de novo assembly completed (139,034/139,118 partitions; 84 degenerate partitions pruned = 0.06%; --no_salmon). C4 N50 reproduces within ~6% (2,486 vs 2,350 bp) and C5 remap is 96.3-96.5% per library (paper's >83% claim met). BUT the transcript/gene counts are ~3.7x the reported values (374,039 vs 101,812 transcripts; 206,429 vs 55,199 genes) and total bases 2.9x (439.8 vs 149.64 Mb) = MISMATCH, attributable to the Trinity version gap (2.15.1 vs r2013-02-25), the paper's unspecified unigene-clustering step, and --no_salmon (no isoform filtering). The reported numbers are internally consistent (1,470 bp x 101,812 = 149.6 Mb), so this is a legitimate method/version difference, NOT fabrication. NOT ATTEMPTED (out of scope, see scope.md): DEG counts (RSEM+edgeR on authors' unigene set + pooled-contrast design), alternative-splicing event typing, GO/KEGG enrichment numbers (need authors' unshipped BLAST2GO annotation; Goatools is only the enrichment engine). All grades provisional; a human reviewer signs off.
These records describe the outcome of reproduction attempts carried out autonomously by brainbox using large language models (LLMs). They are not peer review, not an audit, and not a determination of error or misconduct by any author. A verdict reflects what one attempt could or could not reproduce — which may depend on data access, undocumented parameters, the computing environment, or the depth of effort — and not a judgement of the people who did the work. We can be wrong, and we correct mistakes quickly: every record carries a “report an error” button.
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: 2026-06-16 ⛓ 7ae64052e4a9
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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
- 2026-06-29
- 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: sonnetThe study investigates the transcriptomic response of grass carp (Ctenopharyngodon idella) head-kidney and spleen to grass carp reovirus (GCRV) infection, testing whether alternative splicing (AS) plays a regulatory role in antiviral immunity.
- ★ AS events, including differentially-expressed-transcript-containing genes (DETs), are ubiquitous in head-kidney and spleen transcriptomes of C. idella finding
- ★ Splicing transcripts of IL-12p40 and IL-1R1 are differentially expressed and play diverse/adverse roles in the antiviral response of fishes finding
- ★ 217 unigenes are differentially expressed (fold-change ≥4) between resistant and susceptible fish in both head-kidney and spleen finding
- ★ The immune response of spleen is more intense than that of head-kidney finding
- ★ De novo assembly yielded a complete C. idella transcriptome (55,199 unigenes) as a resource for gene annotation, DEG analysis, and AS identification resource
- c-Fos and IκBαLA may play important regulatory roles in immune response mediation via MAPK/TLR/RLR/TCR/BCR/NF-κB pathways mechanism
- ★ IL-12p40α and IL-12p40β splice variants may polymerize with different monomers to play adverse (positive vs negative) regulatory roles in immune responses mechanism
- ★ RNA-seq expression data show a positive linear relationship with RT-qPCR data, validating assembly quality method
| Assay | System | Perturbation | Readout | Platform |
|---|---|---|---|---|
| RNA-seq (Illumina MiSeq, de novo transcriptome assembly) | head-kidney and spleen tissue, C. idella (grass carp) | GCRV infection (resistant vs susceptible fish) | transcript abundance, differential gene expression, unigene assembly | Illumina MiSeq 2x250bp |
| RT-qPCR | head-kidney and spleen tissue, C. idella | GCRV infection (resistant vs susceptible fish) | expression levels of 38 genes (36 DEGs plus RAG1/RAG2) normalized to 18S rRNA and EF1α | real-time PCR |
| PCR amplification and rapid-amplification of cDNA ends (RACE) with Sanger sequencing | C. idella genomic DNA and cDNA (IL-12p40, IL-1R1, ILLR1-4) | none | splicing transcript structure/number, exon-intron boundaries | Sanger sequencing |
| Bioinformatic AS event classification | assembled unisequences/unigenes from head-kidney and spleen transcriptomes | GCRV infection | type of AS event (alternative donor/acceptor, exon skipping, intron retention) | — |
| Protein structure prediction | IL-12p40α and IL-12p40β predicted proteins, C. idella | none | predicted protein tertiary structure/configuration | SCRATCH protein predictor |
| Protein-protein interaction network analysis | c-Fos and IκBαLA interactome, C. idella | none | predicted interacting molecules (e.g., JunD) | STRING database |
| Hierarchical clustering of immune gene expression | 128 immune-related genes, head-kidney and spleen, C. idella | GCRV infection | expression pattern clusters across 4 libraries | — |
| GO/KEGG/COG functional annotation and pathway enrichment | 101,812 unisequences / 55,199 unigenes, C. idella | GCRV infection | functional category and pathway enrichment ratios | BLAST-based annotation pipelines |
- – 217 unigenes differentially expressed between resistant and susceptible fish in both head-kidney and spleen; 36 validated by RT-qPCR fold-change ≥4
- – 1,025 DEGs identified in head-kidney (296 up-regulated, 729 down-regulated) comparing resistant vs susceptible 296 up / 729 down
- – 871 DEGs identified in spleen (476 up-regulated, 395 down-regulated) comparing resistant vs susceptible 476 up / 395 down
- – 11,811 unigenes (21.4%) contain multiple transcripts, indicating possible AS regulation 21.4%
- – 322 DETs (including 69 novel genes) contained both up- and down-regulated spliced transcripts across head-kidney and spleen libraries 322 DETs
- ▲ IL-12p40a expression was higher in KR vs KS by RT-qPCR and RNA-seq 8.3-fold (RT-qPCR); 25.5-fold (RNA-seq)
- – IL-1R1 gene contains 12 splicing transcripts, categorized into distinct C-terminal and N-terminal structural forms 12 transcripts
- – Over 20% of C. idella genes are alternatively spliced during GCRV infection, comparable to zebrafish (17.0%) but lower than medaka, stickleback, puffer fish, and human >20% (vs 17.0% in D. rerio)
- count 55,199 unigenes; average length 1,470 bp; N50 2,350 bp (de novo assembly of C. idella transcriptome)
- count 217 unigenes differentially expressed (fold-change ≥4) (resistant vs susceptible fish, both head-kidney and spleen)
- count 1,025 DEGs in head-kidney (296 up, 729 down) (P<0.05, FDR<0.05, resistant vs susceptible)
- count 871 DEGs in spleen (476 up, 395 down) (P<0.05, FDR<0.05, resistant vs susceptible)
- fold_change 8.3-fold higher (RT-qPCR), 25.5-fold higher (RNA-seq) (IL-12p40a expression in KR vs KS)
- count 11,811 unigenes (21.4%) contain multiple transcripts (putative AS-regulated genes)
- count 322 DETs including 69 novel genes (differentially-expressed-transcript-containing genes with both up- and down-regulated transcripts)
- pvalue P > 0.05 (t-test) (no significant difference between RNA-seq and RT-qPCR expression data for 38 genes)
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.
This is an RNA-seq study in which four cDNA libraries (head-kidney and spleen, from resistant and susceptible GCRV-challenged grass carp) were sequenced on Illumina MiSeq, de novo assembled, and analyzed for differentially expressed genes (DEGs) and differentially expressed transcripts. Differential expression was assessed by fold-change thresholds combined with a significance cutoff (P < 0.05, FDR < 0.05), and a subset of genes was validated by RT-qPCR. Agreement between RNA-seq and RT-qPCR was evaluated with a t-test, and immune-gene expression patterns were explored with hierarchical clustering.
| Test | Applied to | n | Assumptions |
|---|---|---|---|
| differential expression test reported as P < 0.05 with FDR < 0.05 plus a fold-change threshold (specific test/statistic not named) | DEGs between resistant and susceptible samples in head-kidney and spleen (Supplementary Data 2/3, Fig. S4); also the 36/38 genes selected for RT-qPCR (fold-change ≥8) | — | not stated |
| t-test (type not specified) | comparison between RNA-seq and RT-qPCR expression datasets (reported P > 0.05) | — | not stated |
| hierarchical cluster analysis | 128 immune-related genes across the four libraries (Fig. 3, heat map) | — | na |
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The four sequencing libraries correspond to single tissue × phenotype conditions, and no biological replicate count or power calculation is described.↳ Could also: A design with biological replicates per condition could also be used, paired with a count-based model such as DESeq2 or edgeR. — Replication lets a model estimate within-group biological variance and dispersion, which is what those tools use to gauge how reproducible an observed fold-change is.
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DEGs were defined using a significance threshold (P < 0.05, FDR < 0.05) together with a fixed fold-change cutoff (≥4 or ≥8), with the underlying test not named.↳ Could also: A negative-binomial GLM framework (DESeq2 Wald/LRT or edgeR) that jointly models counts and yields shrunken fold-change estimates could also be applied, and the specific test could be named explicitly. — Naming the test and using a model-based estimate makes the criterion fully reproducible and can stabilize fold-change estimates for low-count genes.
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An FDR threshold was applied to control multiplicity, but the specific correction procedure is not named.↳ Could also: The exact method (e.g., Benjamini-Hochberg) could also be stated, and exact adjusted p-values reported per gene. — Specifying the procedure and reporting adjusted values lets readers reproduce the gene list and see how close each gene sits to the cutoff.
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Concordance between RNA-seq and RT-qPCR was summarized with a t-test (P > 0.05) and described as a positive linear relationship.↳ Could also: A correlation/regression metric (Pearson or Spearman r with a confidence interval, or Lin's concordance) could also be reported. — A correlation or concordance coefficient directly quantifies agreement and its precision, whereas a non-significant t-test indicates the means do not differ but not how tightly the platforms track each other.
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Expression values and validation results are presented largely as fold-changes and FPKM ratios without stated measures of dispersion or confidence intervals.↳ Could also: Reporting SD/SEM or 95% confidence intervals alongside point estimates, and exact p-values, could also be done. — Showing spread and exact values conveys the uncertainty around each estimate, which is especially informative when few samples underlie a comparison.
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Relationships among the 128 immune-related genes were explored with hierarchical clustering of the four libraries.↳ Could also: Complementary unsupervised approaches such as PCA, or reporting the distance metric and linkage with bootstrap support for clusters, could also be used. — These additions make the grouping structure reproducible and give a sense of how stable the observed clusters are.
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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IL12B (IL-12p40a) is 8.3-fold upregulated in GCRV-resistant vs susceptible head-kidney but 8.3-fold downregulated in resistant vs susceptible spleen.qPCR grass carp head-kidney and spleen mixed 2015×1papers★ This paper is the founder (earliest)
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2,782 differentially expressed transcripts identified after GCRV challenge; 322 genes show opposing up- and down-regulation of spliced isoforms; 21.4% of unigenes harbor multiple transcripts.RNA-seq grass carp head-kidney and spleen mixed 2015×1papers★ This paper is the founder (earliest)
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1,025 DEGs (296 up, 729 down) in head-kidney and 871 DEGs (476 up, 395 down) in spleen between GCRV-resistant and -susceptible grass carp.RNA-seq grass carp head-kidney and spleen mixed 2015×1papers★ This paper is the founder (earliest)
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Intron retention is the dominant alternative splicing event type (48.7%) among immune-related genes in GCRV-challenged grass carp, followed by alternative donor site (30.8%), exon skipping (12.8%), and alternative acceptor site (7.7%).RNA-seq grass carp head-kidney and spleen 2015×1papers★ This paper is the founder (earliest)
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217 unigenes (59 up, 158 down, ≥4-fold) are differentially expressed between GCRV-resistant and -susceptible grass carp in both head-kidney and spleen.RNA-seq grass carp head-kidney and spleen mixed 2015×1papers★ This paper is the founder (earliest)
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Innate immunity-related gene expression is on average higher in spleen than head-kidney following GCRV challenge in grass carp.RNA-seq grass carp spleen up 2015×1papers★ 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-26248502
Paper: Transcriptome analysis provides insights into the regulatory function of alternative splicing in antiviral immunity in grass carp (Ctenopharyngodon idella). Sci Rep 2015. PMCID PMC4528194 · DOI 10.1038/srep12946.
Design: Grass carp challenged with grass carp reovirus (GCRV, 097 strain). Four pooled cDNA libraries — SS1 (susceptible spleen), SR2 (resistant spleen), KS3 (susceptible head-kidney), KR4 (resistant head-kidney) — sequenced on Illumina MiSeq 2×250 bp. SRA BioProject SRP049081.
Pipeline reported in Methods
- QC/trimming of raw reads → "clean reads".
- De novo transcriptome assembly with Trinity (trinityrnaseq-r2013-02-25, default k=25) → unigenes/unisequences.
- Bowtie remap of clean reads to the assembly (assembly validation; >83%).
- ORF prediction; BLAST+ / BLAST2GO functional annotation (NR, NT, STRING, COG, KEGG).
- RSEM 1.2.7 quantification + edgeR 3.8.2 differential expression → DEGs.
- Alternative-splicing analysis (multi-transcript unigenes; AS event typing).
- GO/KEGG enrichment — Goatools 0.4.7 (the linked "code" artifact) + KOBAS 2.0.
In scope (pipeline-derived, clearly specified → attempted)
| id | result | reported | why in scope |
|---|---|---|---|
| C1 | Raw reads per library | SS1 32.86M / SR2 19.49M / KS3 24.45M / KR4 35.18M | count downloaded FASTQ directly; deterministic |
| C2 | Total clean reads | 107,959,648 | re-run QC (fastp); tool differs → tolerance expected |
| C3 | # Trinity unigenes / unisequences | 55,199 unigenes / 101,812 unisequences | core de novo result; recompute with Trinity 2.x |
| C4 | Assembly N50 / mean length / total bases | N50 2,350 bp / mean 1,470 bp / 149.64 Mb | TrinityStats |
| C5 | Remap rate to assembly | >83% per library | bowtie2 remap of clean reads |
Out of scope / not attempted (the hard ~20%, per 80/20 rule)
- DEG counts (1,025 head-kidney; 871 spleen) — needs RSEM+edgeR on the authors' exact unigene set + contrast definitions; assembly-dependent and the per-fish pooling/contrast design is not fully pinned.
- Alternative-splicing event typing (30.8/7.7/12.8/48.7 % donor/acceptor/skip/ retention; 11,811 multi-transcript unigenes) — depends on the exact Trinity isoform graph + an unspecified AS-classification step; not robustly reproducible.
- GO/KEGG enrichment numbers (8,856 GO terms; 317 KEGG pathways; specific enriched categories) — Goatools is just the enrichment engine; its input is the authors' BLAST2GO gene→GO table + DEG foreground, neither shipped. Re-deriving the annotation is a separate large pipeline → out of scope.
- All wet-lab results (RT-qPCR validation, fish challenge survival).
Note on the "code" artifact (P16)
The linked repo (tanghaibao/Goatools) is a third-party GO-enrichment library, not the authors' pipeline. Per the brief this is acceptable, but Goatools sits at the end of the pipeline and consumes annotation tables the paper does not ship. The faithful, low-hanging reproduction is therefore the front of the pipeline: read counts → Trinity de novo assembly → remap validation, which is exactly the "transcriptome analysis" the title claims and is fully specified from public SRA data.
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.
Data identity is clean: SRP049081 is public and the four libraries' deposited read counts match the paper exactly (total 111,985,560 raw) — no fabrication signal. However, the reproduction is incomplete on our side: the Trinity env was still building when the job was finalized, so clean reads (107,959,648), unigenes (55,199/101,812), N50 (2,350 bp) and remap rate (>83%) were never computed, and all downstream AS/DEG/GO analyses underpinning the central conclusion were out of scope. No deviation was observed (q6 green), but the core analytic claim was not actually tested (q7 yellow), and any future assembly comparison carries expected Trinity-version drift. Overall a faithful but partial reproduction — defect is operational incompleteness, not the authors or data.
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.