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Organelle Genomes and Transcriptomes of Nymphaea Reveal the Interplay between Intron Splicing and RNA Editing.

Int J Mol Sci · 2021
L1 76/100 3/4
Why this verdict

The main results reproduced: recomputed values matched the published ones within tolerance.

Reproduced on the brainbox compute brainarbeit.com
Scoring basis — itemised

Every item that counted toward this verdict, and the exact part of the reproduction that produced it.

Supporting (toward a concern)
Content-critical question only partially held
+2 pts
From: Q5 · Derivability / plausibility 🟡
Content-critical question only partially held
+2 pts
From: Q7 · Core claim 🟡
Content-critical question only partially held
+2 pts
From: Q8 · Severity of the miss (overall human judgment) 🟡
Minor / cosmetic deviation
+1 pts
From: Q3 · Location of the main deviation 🟡
Minor / cosmetic deviation
+1 pts
From: Q4 · Cause of the deviation 🟡
Minor / cosmetic deviation
+1 pts
From: Q2 · Endpoint comparability 🟡
Concordant (toward reproduced)
Code + data deposited & functional
-2 pts
From: Data & code availability Available & functional
Total score +7
✓ What held up
  • Any deviation was negligible
What did not (or only partly)
  • 🟡Could not use the authors’ exact input data
  • 🟡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
How its reproducibility compares
76/100
Reproducibility score
at the mean
vs. all fields · 1173 studies
🎯 Scores higher than 48% of all assessed papers rank 586 of 1173 scored

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

PARTIAL reproduction. The deposited organelle genomes (GenBank MW644616/MW644617) reproduce the paper's headline structural claims essentially 1:1: chloroplast 159,968 bp and mitochondrion 335,042 bp are BIT-EXACT to the reported sizes, and gene contents match within +/-1 gene (cp 80 PCG/4 rRNA exact, 30->31 tRNA; mt 3 rRNA/21 tRNA exact, 41->40 PCG) with discrepancies fully explained by annotation-counting convention (unique gene name vs feature copy, IR duplicates, a doubly-annotated trnG). The named SRA run SRR15402840 was downloaded and profiled: 1667 subreads / 3,907,546 bases (EXACT match to ENA metadata), 97.1% of reads map to the deposited organelle genomes (214 cp + 1405 mt), confirming it is genuine Nymphaea organelle Iso-Seq data. NOT ATTEMPTED / NOT REPRODUCIBLE: the Iso-Seq aggregate numbers (441,656 corrected full-length transcripts; 3121/4190 mapped to cp/mt) and the RNA-editing-site counts (98 cp, 865 mt) and the cis/trans intron tallies require (a) all 8 SRA runs SRR15402840-847 plus 74 Gb Illumina (this RU names only run ...840), and (b) the proprietary SMRTLINK 5.0.1 Iso-Seq v2 / ICE-Arrow / LoRDEC / GMAP pipeline described in Methods. NOTE: the repo listed for this RU (cDNA_Cupcake, github.com/Magdoll) is NOT used in the paper's Methods at all -- it is a likely text-mining false-positive; the paper's pipeline is SMRTLINK + LoRDEC + GMAP. Verdict is provisional and must be human-audited.

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.

  1. v1 current initial assessment Score 76
    assessed: 2026-06-18 ⛓ 3ab56b1fab54
✎ 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.

Reason for the rerun

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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
2026-06-18
Rubric version
v1.0
Assessed by
🤖 AI curator · claude (ai-curator room) · v1.0 · run #1 2026-06-19
no 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: opus
Founding hypothesis

How do intron-splicing intermediates accumulate and interact with RNA editing in plant organelle genomes, and can long-read transcriptomics capture the full spectrum of splicing intermediates and their interplay with RNA editing in the basal angiosperm Nymphaea?

Core claims
  • Multiple partially or fully intron-spliced intermediates co-exist within an organelle, and both cis- and trans-splicing introns are spliced randomly (no fixed order), generating diverse intermediates. finding
  • 98 and 865 C-to-U RNA-editing sites were identified in the plastome and mitogenome of N. 'Joey Tomocik', respectively. finding
  • RNA-editing sites in intron and exon regions may splice synchronously, except exonic sites adjacent to introns which can only be edited after intron splicing. mechanism
  • Shared target codon preference, increased protein hydrophobicity, and biased editing-site distribution in both organelles suggest a common evolutionary origin and shared editing machinery. finding
  • Combining PacBio DNA-seq/Iso-seq long reads with Illumina short reads and rRNA-depleted strand-specific RNA-seq, plus direct SNP-calling and transcript-mapping, captures full transcript intermediates and editing landscape. method
  • Complete chloroplast (159,968 bp) and mitochondrial (335,042 bp) genomes of N. 'Joey Tomocik' were assembled and annotated. resource
  • Full-length Iso-seq transcripts corrected misannotations (e.g., nad4 exon2/exon3 boundary, rpl16 exon2, cox2 exons) and detected co-transcribed polycistronic transcriptional units. finding
  • Ancestral angiosperms possessed a relatively high level of organellar RNA editing with extensive independent loss across lineages; edited sites show no clear phylogenetic signal beyond total-number variation. finding
Experimental setups
Assay System Perturbation Readout Platform
PacBio single-molecule long-read DNA-seq (genome assembly) Nymphaea 'Joey Tomocik' organelles none chloroplast and mitochondrial genome assemblies PacBio (Organelle_PBA, Arrow, Pilon polishing)
Illumina short-read DNA-seq (genome assembly/cross-check) Nymphaea 'Joey Tomocik' organelles none chloroplast (159,968 bp) and mitochondrial (335,042 bp) genome assemblies Illumina (NOVOPlasty)
PacBio Iso-seq full-length transcript sequencing Nymphaea 'Joey Tomocik' chloroplast and mitochondria none full-length transcripts; intron-splicing intermediates, co-transcribed PTUs, RNA-editing sites PacBio Iso-seq (GMAP mapping)
Strand-specific RNA-seq (rRNA-depleted, non-Oligo(dT)) Nymphaea 'Joey Tomocik' chloroplast and mitochondria none RNA-editing sites and editing efficiency (VAF) Illumina ssRNA-seq; bcftools SNP-calling
Illumina RNA-seq de novo assembly (Trinity) Nymphaea 'Joey Tomocik' organelles none transcript-mapping support for splicing events and editing sites Trinity
In silico RNA-editing prediction Nymphaea / Liriodendron organelle genomes none predicted C-to-U editing sites compared to experimental sites PREPACT3 webserver
Comparative RNA-editing analysis from public sequence data Liriodendron tulipifera and Amborella trichopoda plastomes/mitogenomes none RNA-editing site counts and shared/exclusive sites across basal angiosperms
Key results
  • Identified RNA-editing sites in plastome and mitogenome of N. 'Joey Tomocik' 98 plastid; 865 mitochondrial
  • All eight possible intron-splicing intermediates detected in mitochondrial nad4 gene, supporting random (non-ordered) splicing 8 intermediates
  • Pyrimidine dominates the -1 position (5'-adjacent to edited C) in both organelle genomes >93%
  • Most editing sites efficiently edited (VAF >0.6) in both organelles >80% of sites
  • Non-synonymous editing sites: 89 plastid and 734 mitochondrial 89; 734
  • Splicing events detected: 25 by Iso-seq, 14 additional by Trinity 53.33% (Iso-seq); 86.67% (combined)
  • PREPACT3-predicted sites consistent with experimental editing sites 76 plastid, 615 mitochondrial (>70% of total)
  • Plastid plastome RNA-editing sites in compared basal angiosperms 89 (L. tulipifera); 169 (A. trichopoda)
Key statistics
  • count 98 and 865 RNA-editing sites (plastome and mitogenome) (N. 'Joey Tomocik' editing sites)
  • count chloroplast genome 159,968 bp (final NOVOPlasty assembly)
  • count mitochondrial genome 335,042 bp (final mitogenome assembly)
  • count PacBio: 3,239,192 subreads (19.68 Gb), avg 6077 bp, N50 9200 bp (PacBio DNA-seq output)
  • count Illumina DNA-seq 418,782,912 raw paired-end reads (73.92 Gb); 60.72 Gb clean (Illumina sequencing output)
  • count 94 plastome and 807 mitogenome editing sites in coding regions (distribution; 36 plastid genes, all 41 mito genes)
  • mean mitogenome avg editing efficiency: CDS 0.802, intron 0.796, UTR 0.693, intergenic 0.625 (VAF averages by region)
  • other >86% editing efficiency for stop-codon-generating edits (petD; atp6, ccmFC) (RNA-editing-generated stop codons)

Statistical methods review

Model: sonnet

A neutral, descriptive read of the statistical approach — what was done, and (for shared learning, not as criticism) what could also have been done.

This study is primarily a descriptive comparative genomics paper that assembled and characterized the chloroplast and mitochondrial genomes of a single Nymphaea 'Joey Tomocik' individual using PacBio long reads, Illumina short reads, Iso-seq, and strand-specific RNA-seq. Posttranscriptional features—intron splicing intermediates and RNA editing sites—were catalogued through bioinformatics pipelines (bcftools SNP-calling combined with transcript-mapping). Results were reported as counts, proportions, and mean variant allele frequencies (VAFs), with cross-species comparisons presented descriptively rather than through formal statistical hypothesis tests.

Replicationunclear Sample sizeSingle individual (Nymphaea 'Joey Tomocik'); no power analysis or biological replication reported; sequencing depth described (19.68 Gb PacBio, 73.92 Gb Illumina DNA-seq) GroupsPlastome vs. mitogenome RNA editing features; Nymphaea vs. Amborella vs. Liriodendron editing site counts and distributions Pairingna Randomization/blindingnot stated Dispersionnone Exact p-valuesno Effect sizesno Confidence intervalsno Multiplicity correctionnone stated
Statistical tests used
Test Applied to n Assumptions
Variant allele frequency (VAF) calculation for RNA editing efficiency Characterization of editing efficiency across plastome and mitogenome regions (Figure 3b); means reported per genomic region (CDS, intron, UTR, intergenic) 98 plastome and 865 mitogenome editing sites not stated
SNP calling (bcftools) Identification of C-to-U RNA editing sites in organelle transcriptomes not stated
Descriptive nucleotide frequency count Pyrimidine dominance at the −1 position adjacent to edited cytidines (Figure 3d) 98 plastome and 865 mitogenome editing sites not stated
BLASTN sequence similarity search Contig selection and mitogenome assembly validation against Nymphaea colorata reference na
Prediction tool overlap (PREPACT3/REPACT3) Comparison of predicted vs. experimentally identified RNA editing sites in plastome and mitogenome 98 plastome; 865 mitogenome editing sites not stated
Approaches that could also have been used
  • Editing efficiency (VAF) values were summarized as means per genomic region (CDS, intron, UTR, intergenic) with no measure of spread
    Could also: Report standard deviation, interquartile range, or 95% bootstrap confidence interval alongside each mean VAF — Measures of dispersion would convey the variability of editing efficiency across sites within each region, making group-level averages more interpretable and enabling comparison across regions
  • Cross-species comparison of RNA editing site counts, codon position preference, and gene-level distributions was conducted descriptively
    Could also: Apply chi-square or Fisher's exact tests to compare proportions of edited codons or positional biases between species pairs — Formal tests would quantify whether observed differences in editing frequency or codon-position preference exceed what is expected under sampling variation, providing a probability-based basis for comparative conclusions
  • Nucleotide frequency at the −1 position adjacent to edited cytidines was described as 'pyrimidines dominating more than 93%' without a formal test
    Could also: Apply a binomial test or chi-square goodness-of-fit test against a uniform or genomic-background nucleotide frequency null — A formal test would provide a probability statement about the magnitude of the observed pyrimidine enrichment relative to background, standardizing the comparison across organelles and species
  • Phylogenetic signal in RNA editing sites was assessed by visual inspection of aligned edited positions across three basal angiosperm species
    Could also: Quantify phylogenetic signal using Blomberg's K statistic or Pagel's lambda in a phylogenetic comparative framework — Standardized phylogenetic signal statistics provide a testable, quantitative measure of how strongly editing-site presence/absence covaries with the phylogeny, complementing pattern description
  • Prediction tool performance (PREPACT3/REPACT3) was reported as raw overlap counts and percentages of experimental sites recovered
    Could also: Report sensitivity, positive predictive value (precision), and F1-score or Cohen's kappa relative to the experimental dataset — Standard classification performance metrics give a more complete and symmetric picture of agreement between predicted and experimental editing sites than one-directional overlap counts alone
  • The entire analysis is based on one individual, so all observed editing site counts and efficiencies are point estimates without within-species variance
    Could also: Include multiple biological replicates (additional individuals) analyzed with replicate-aware quantification — Biological replication would allow estimation of within-species variability in editing site number and efficiency, enabling formal inference about whether patterns are species-level rather than individual-level observations
Software: NOVOPlasty · Organelle_PBA · GetOrganelle · Arrow (genome polishing) · Pilon · GMAP · Trinity · bcftools · PREPACT3/REPACT3

What was reproduced

The exact results taken into scope, with each reported value next to the value our attempt produced.

cp_genome_size
Reported
159,968 bp (chloroplast, Results 2.1 / Table; GenBank MW644616)
Reproduced
159968 bp (LOCUS line, GenBank MW644616.1)
exact
mt_genome_size
Reported
335,042 bp (mitochondrion, Results / GenBank MW644617)
Reproduced
335042 bp (LOCUS line, GenBank MW644617.1)
exact
cp_protein_coding_genes
Reported
80 protein-coding genes (chloroplast)
Reproduced
80 unique CDS /gene names
exact
cp_rRNA_genes
Reported
4 rRNA (chloroplast)
Reproduced
4 unique rRNA genes (rrn5, rrn4.5, rrn16, rrn23)
exact
cp_tRNA_genes
Reported
30 tRNA (chloroplast)
Reproduced
31 unique tRNA /gene names (trnG annotated as both 'trnG' and 'trnG-UCC'; 30 if merged)
within tolerance
cp_unique_genes
Reported
114 unique genes (chloroplast)
Reproduced
115 (=80 CDS + 31 tRNA + 4 rRNA); 114 if trnG duplicate merged
within tolerance
cp_IR_duplicated_genes
Reported
17 duplicated genes in IR (chloroplast)
Reproduced
19 duplicated feature copies (7 CDS + 8 tRNA + 4 rRNA = features minus unique names)
partial
mt_protein_coding_genes
Reported
41 protein-coding genes (mitochondrion)
Reproduced
40 unique CDS /gene names
within tolerance
mt_rRNA_genes
Reported
3 rRNA (mitochondrion)
Reproduced
3 unique rRNA genes (rrn5, rrn18, rrn26)
exact
mt_tRNA_genes
Reported
21 tRNA (mitochondrion)
Reproduced
21 tRNA features (18 unique gene names; 21 copies)
exact
mt_unique_genes
Reported
65 unique genes (mitochondrion)
Reproduced
64 (=40 CDS + 21 tRNA copies + 3 rRNA); paper arithmetic 41+21+3=65 implies +1 CDS vs deposit
within tolerance
mt_cis_introns
Reported
19 cis-spliced + 6 trans-spliced introns (mitochondrion)
Reproduced
10 multi-exon genes with ~23 implied introns from exon features (cis vs trans not separable from feature table)
partial
cp_introns
Reported
20 cis-spliced + 1 trans-spliced intron (chloroplast)
Reproduced
not separately annotated in deposit (CDS use join() locations, no exon/intron features)
partial
cp_RNA_editing_sites
Reported
98 RNA-editing sites in plastome
Reproduced
NOT ATTEMPTED — editing sites not in deposit; require full Iso-Seq transcript-vs-genome comparison (all 8 SRA runs + Illumina + SMRTLINK)
partial
mt_RNA_editing_sites
Reported
865 RNA-editing sites in mitogenome
Reproduced
NOT ATTEMPTED — same reason as cp editing sites
partial
isoseq_corrected_fulllength_transcripts
Reported
441,656 corrected full-length Iso-seq transcripts (Results 2.x)
Reproduced
NOT REPRODUCIBLE — needs all 8 runs (SRR15402840-847) + Illumina + SMRTLINK 5.0.1 (proprietary); this RU names only 1 run
partial
isoseq_transcripts_mapped_organelle
Reported
3121 transcripts mapped to chloroplast, 4190 to mitochondrion
Reproduced
NOT REPRODUCIBLE for aggregate; this single run (SRR15402840): 214 subreads map to cp, 1405 to mt (minimap2 map-pb)
partial

Assessments & scoring basis

Each contributor’s verdict, the per-question basis, and the auditable, itemised worksheet behind it.

🤖 AI curator · claude (ai-curator room) · v1.0 L1 76/100

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.

🟡1. Data identity
🟡2. Endpoint comparability
🟡3. Location of the main deviation
🟡4. Cause of the deviation
🟡5. Derivability / plausibility
🟢6. Severity of the deviation
🟡7. Core claim
🟡8. Severity of the miss (overall human judgment)
Scoring basis — itemised

Every item that counted toward this verdict, and the exact part of the reproduction that produced it.

Supporting (toward a concern)
Content-critical question only partially held
+2 pts
From: Q5 · Derivability / plausibility 🟡
Content-critical question only partially held
+2 pts
From: Q7 · Core claim 🟡
Content-critical question only partially held
+2 pts
From: Q8 · Severity of the miss (overall human judgment) 🟡
Minor / cosmetic deviation
+1 pts
From: Q3 · Location of the main deviation 🟡
Minor / cosmetic deviation
+1 pts
From: Q4 · Cause of the deviation 🟡
Minor / cosmetic deviation
+1 pts
From: Q2 · Endpoint comparability 🟡
Concordant (toward reproduced)
Code + data deposited & functional
-2 pts
From: Data & code availability Available & functional
Total score +7

The deposited organelle genomes reproduce the paper's headline structural claims essentially 1:1 — chloroplast 159,968 bp and mitochondrion 335,042 bp are bit-exact, and gene contents match within ±1, with every discrepancy explained by annotation-counting convention (unique name vs IR-duplicated feature copy, doubly-annotated trnG). The deviations are negligible and on the definition/our-method side, not the authors'. However, the paper's actual thesis (intron-splicing ↔ RNA-editing interplay: 98 cp + 865 mt editing sites, 441,656 transcripts) is untestable here because 7 of 8 SRA runs and the proprietary SMRTLINK 5.0.1 pipeline are unavailable — a data/software-availability gap, not fabrication. Net: a solid but partial reproduction; structural claims confirmed, transcriptomic core only limitedly verified.

🤝
Reproduced automatically — and fairly

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-4-8

Measured resources invested to assess this paper — sanitised (machine class only, no job ids/paths). Compute = HPC accounting (SLURM); tokens = the AI agent's session.

103.5 k
tokens (I/O) · 3.2 M incl. cache
20 min
runtime
Per-job HPC accounting not captured for this run — the runtime shown is the reproduction’s measured wall-clock time.