Evolution and codon usage bias of mitochondrial and nuclear genomes in Aspergillus section Flavi.
The main results reproduced: recomputed values matched the published ones within tolerance.
- ✓Reported values are derivable from the shared data
- ✓Any deviation was negligible
- ✓The central claim held under reproduction
- 🟡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
- 🟡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; largely 1:1 on the deterministic mitochondrial-side results. We independently recomputed mitogenome size (29100-39268 bp = paper 29.100-39.269 kbp, exact), GC min (24.94%=24.9%, exact), CDS 15-17, rRNA 2, tRNA 26, and the headline codon-usage RSCU values (AUA 1.62, CCC 0.043, CCU 2.72 vs paper 1.6304/0.0449/2.7140) directly from the authors' DEPOSITED GenBank mitogenomes (ON833077-ON833094) using an independent Biopython reimplementation -- a strong fabrication check: the reported numbers ARE derivable from the shipped data. Key methodological finding: paper RSCU = GENOME-level pooling (our 1.62 matches) not gene-level mean (1.56). Nuclear RSCU cross-checked vs the authors' figshare table (matches paper). NOT reproduced 1:1: exact ENc-GC3 R^2 (DAMBE-estimator-dependent; direction only), nuclear-side recompute / S-values / 2422 orthologs / phylogeny (JGI nuclear CDS login-gated + heavy compute). One data-quality flag: GenBank deposit labels A.transmontanensis twice (ON833080/81) and omits A.alliaceus (present in figshare) -- NCBI metadata labeling quirk, not a result error.
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
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v1 current initial assessment Score 85assessed: 2026-06-22 ⛓ 1325a765b69b
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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
- 2026-06-22
- Rubric version
- v1.0
- Assessed by
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🤖 AI curator · claude (ai-curator room) · v1.0 · run #1 2026-06-22no 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 paper tests how the evolutionary history and codon usage bias of mitochondrial genomes in Aspergillus section Flavi compare to those of the nuclear genomes of the same species.
- ★ 18 new mitochondrial genomes were assembled for Aspergillus section Flavi species, complementing 3 existing reference mitogenomes, for a total of 20 species analyzed. resource
- ★ All Flavi mitogenomes are circular DNA molecules of low GC content with highly conserved gene content and gene order (synteny). finding
- ★ Genomic content, including GC content and genome size, differs greatly between mitochondrial and nuclear genomes. finding
- ★ A phylogeny built from 14 concatenated mitochondrial genes predicts evolutionary relationships largely consistent with a phylogeny built from 2,422 nuclear genes. finding
- ★ Species cluster differently by codon usage bias depending on whether mitochondrial or nuclear relative synonymous codon usage (RSCU) values are used. finding
- ★ At the gene level, codon usage bias patterns are more similar among mitogenomes of different species than between the mitogenome and nuclear genome of the same species. finding
- ★ Mitogenomes are not under translational selection, whereas nuclear genomes are under moderate translational selection, despite most genes in both genomes deviating from neutral codon usage expectations. finding
- The S-value (correlation between tRNA adaptation index and codon usage) can be used to compare the strength of translational selection between mitochondrial and nuclear genomes. method
| Assay | System | Perturbation | Readout | Platform |
|---|---|---|---|---|
| mitogenome assembly (organelle genome assembly from WGS reads) | 20 Aspergillus section Flavi species (whole genome sequencing reads / mycelia) | none | assembled circular mitochondrial genome sequence | GetOrganelle v1.7.4.1 |
| read mapping / variant calling for error correction | Aspergillus section Flavi species (paired-end Illumina reads vs assembled mitogenome) | none | mapped reads, identified variants | Bowtie2 v2.3.4.1, SAMtools v1.6, IGV v2.9.4 |
| organellar genome annotation | circularized mitochondrial genomes of Flavi species | none | annotated gene content, gene names, translations | GeSeq v2.03, Geneious Prime v2021.1, OGDraw v1.1.1 |
| multiple sequence alignment and maximum likelihood phylogenetics (mitochondrial) | 14 core mitogenes across 20 Flavi species plus A. niger outgroup | none | mitochondrial phylogenetic tree with bootstrap support | MAFFT v7, SequenceMatrix v1.9, ClipKIT v1.3.0, RAxML v8.2.11 |
| ortholog identification and maximum likelihood phylogenetics (nuclear) | 2,422 orthologous nuclear genes across Flavi species (excluding A. sojae) plus A. niger outgroup | none | nuclear phylogenetic tree with bootstrap support | OrthoFinder v2.5.4, RAxML v8.2.11 |
| relative synonymous codon usage (RSCU) hierarchical clustering | mitochondrial and nuclear genomes/genes of Flavi species | none | genome-level and gene-level RSCU values, clustering of species | DAMBE v7.3.5, RStudio v2021.09.1 |
| correspondence analysis of codon usage | gene-level RSCU values, mitochondrial vs nuclear genes across Flavi species | none | codons driving differences in codon usage signatures | R packages ade4 v1.7-19 and factoextra v1.0.7 |
| effective number of codons (ENc) vs GC3 analysis and S-value translational selection test | mitochondrial and nuclear genomes/tRNAomes of Flavi species | none | ENc values, GC3 content, tRNA adaptation index (stAI), S-value with permutation-based significance | DAMBE v7.3.5, tRNAscan-SE 2.0, stAIcalc v1.0, R package tAI.R v0.2 |
- – All 20 Flavi mitogenomes are small, circular DNA molecules with low GC content 24.9-26.9%
- – Each mitogenome contains the same 14 core genes with conserved order and shared synteny
- – A ribosomal protein S3 gene was found in all newly annotated Flavi mitogenomes
- – Mitochondrial phylogeny (14 genes) is largely consistent with nuclear phylogeny (2,422 genes)
- – Species group differently by codon usage bias depending on use of mitochondrial vs nuclear RSCU values
- – Gene-level codon usage bias is more similar between mitogenomes of different species than between mitochondrial and nuclear genome of the same species
- – Most nuclear and mitochondrial genes deviate from the neutral expectation for codon usage, but mitogenomes show no evidence of translational selection while nuclear genomes show moderate translational selection
- other 24.9-26.9% (GC content range of Flavi mitogenomes)
- count 14 core mitochondrial genes (conserved protein-coding genes per mitogenome)
- count 2,422 orthologous nuclear genes (genes used to build concatenated nuclear phylogeny)
- count 18 newly assembled mitogenomes (of 20 total analyzed) (mitogenome dataset composition)
- other 1,000 bootstrap replicates (robustness evaluation for both mitochondrial and nuclear ML phylogenies)
- other 100 permutations (permutation test for statistical significance of S-value)
- other top 5% of permutation distribution (significance threshold for observed S-value)
- other S-value (dos Reis et al. 2004 method) (metric quantifying strength of translational selection on codon usage)
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.
This study is a comparative genomics analysis of mitochondrial versus nuclear genomes across 20 Aspergillus section Flavi species. The main analyses are maximum-likelihood phylogenetic reconstruction with bootstrap support, multivariate correspondence analysis of relative synonymous codon usage (RSCU) values, hierarchical clustering of RSCU patterns, and a permutation-based test (S-value, following dos Reis et al. 2004) to assess translational selection. Results are reported primarily as bootstrap support percentages, R² values (observed vs. expected effective number of codons), and S-values with permutation-derived significance thresholds, rather than through classical hypothesis-testing statistics like t-tests or ANOVA.
| Test | Applied to | n | Assumptions |
|---|---|---|---|
| Maximum likelihood phylogenetic inference (RAxML v8.2.11, GTR+Γ model) with bootstrap support | Mitochondrial phylogeny (14 concatenated mitogenes) and nuclear phylogeny (2,422 orthologous genes) | 14 concatenated mitochondrial genes / 2,422 nuclear orthologs across up to 20 species; 1,000 bootstrap replicates | stated |
| Correspondence analysis (CA) of gene-level RSCU values | Identifying codons driving differences in codon usage between mitochondrial and nuclear genes and among species' mitogenomes | not stated (gene-level RSCU values across annotated genes) | stated |
| Hierarchical clustering of genome-level and gene-level RSCU values | Comparing patterns of codon usage bias between mitochondrial and nuclear genomes | not stated | not stated |
| R² comparison of observed vs. expected effective number of codons (ENc) against the dos Reis et al. (2004) neutral expectation | Evaluating the role of mutational bias (GC3) in codon usage | not stated | stated |
| S-value (dos Reis et al. 2004 framework) with permutation test (100 permutations; significance = top 5% of permuted distribution) | Assessing strength of translational selection per mitochondrial and nuclear genome | 100 permutations per genome | stated |
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Phylogenies were inferred using a single maximum-likelihood method (RAxML) with bootstrap support to assess node confidence.↳ Could also: Bayesian phylogenetic inference (e.g., MrBayes or BEAST) or gene concordance/discordance factor analysis alongside ML — Bayesian posterior probabilities offer a complementary support metric, and concordance factors can additionally reveal how much individual gene trees agree with the concatenated species tree, which is often informative when combining many loci.
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Correspondence analysis was chosen over principal component analysis because RSCU values for synonymous codons are interdependent (compositional).↳ Could also: PCA applied after a compositional-data transformation (e.g., centered log-ratio or Hellinger transform) of RSCU values — This is a commonly used alternative for compositional codon-usage data that also addresses the interdependence among synonymous codon frequencies while allowing use of standard PCA machinery.
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Significance of each S-value was determined using a permutation test based on 100 permutations, with significance defined as falling in the top 5% of the permuted distribution.↳ Could also: A larger number of permutations (e.g., 1,000-10,000) with an exact empirical p-value reported — Increasing the permutation count narrows the resolution of the empirical null distribution and allows reporting of a precise p-value rather than a fixed percentile threshold, which some readers find easier to compare across genomes.
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Translational selection (S-values) and ENc-GC3 fits were evaluated separately for each of the ~20 species' genomes.↳ Could also: A false discovery rate procedure (e.g., Benjamini-Hochberg) applied across the set of per-genome permutation tests — When many similar tests are run across species in parallel, an FDR correction is a standard way to control the expected proportion of false positives among the results declared significant.
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Hierarchical clustering was used to group genomes/genes by RSCU similarity without reported support values for the resulting clusters.↳ Could also: Clustering with bootstrap or jackknife-based support values (e.g., via the pvclust R package) or an approximately unbiased test — Adding support values to clusters would convey the confidence in specific groupings, analogous to the bootstrap support already reported for the phylogenies.
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The fit between observed and expected ENc values was summarized as a single R² statistic.↳ Could also: Reporting a confidence interval around R² or a formal goodness-of-fit test statistic — An interval estimate would communicate the uncertainty around the point estimate of fit rather than relying on R² alone.
What was reproduced
The exact results taken into scope, with each reported value next to the value our attempt produced.
Scope — pmid-36305682
Paper: Hugaboom, Hatmaker, LaBella, Rokas (2023). Evolution and codon usage bias of mitochondrial and nuclear genomes in Aspergillus section Flavi. G3 (Bethesda) 13(2):jkac285. PMID 36305682 · PMC9836360 · DOI 10.1093/g3journal/jkac285.
What the paper does (pipeline overview)
20 Aspergillus section Flavi species (+ A. niger outgroup). For each: mitogenome (3 reference + 18 newly assembled from WGS reads) and nuclear genome (JGI MycoCosm). They (a) assemble + annotate mitogenomes, (b) characterize genome size / GC / gene content, (c) compute codon usage bias (RSCU, ENc), (d) test translational selection (tAI / S-values), (e) correspondence analysis of codon usage, (f) build mito + nuclear phylogenies.
In scope (pipeline-derived, computationally reproducible)
| # | Result | Pipeline / tool | Input data | Tractability |
|---|---|---|---|---|
| S1 | Mitogenome size range 29.1–39.3 kbp (Table 2) | parse GenBank | deposited ON8330xx mitogenomes | high — direct |
| S2 | Mitogenome GC% 24.9–26.9% (Table 2) | seq GC calc | deposited mitogenomes | high — direct |
| S3 | Mitogenome CDS count 15–17; rRNA 2; tRNA 26 (Table 2 / text) | parse GenBank features | deposited mitogenomes | high — direct |
| S4 | RSCU values (Fig 5; figshare RSCU table) e.g. AUA 1.63 mito / 0.45 nuc; CCC 0.045/1.05; CCU 2.71/1.07 | RSCU from CDS (DAMBE → we use codon counts) | mito CDS (+ nuc CDS) | high for mito; compare to authors' own figshare RSCU xlsx |
| S5 | ENc + ENc–GC3 regression R²: mito 0.211, nuc 0.598 | ENc (Wright) vs GC3 | mito/nuc CDS | medium |
| S6 | Correspondence analysis variance: dim1 15.6%, dim2 7% (codon level) | ade4 CA on RSCU | RSCU matrix | medium |
| S7 | Translational selection S-values (mito median 0.162 / mean 0.137, none sig; nuc median 0.432 / mean 0.427, all sig) | stAIcalc + tAI.R | tRNA copy numbers + CDS | lower — needs tRNA GCN + permutation |
| S8 | Mito phylogeny (14-gene concat, RAxML GTR+Γ, 1000 bs); branch dist A.flavus–A.nomiae 0.244 mito / 0.086 nuc | MAFFT→catfasta2phyml/SequenceMatrix→ClipKIT→RAxML | mito gene alignments | heavy («our HPC» SLURM) |
Primary target (the clean 1:1)
S1–S3 (genome size/GC/gene content) and S4 (RSCU) computed directly from the authors' own deposited annotated mitogenomes (GenBank ON833077–ON833094) and cross-checked against their own figshare RSCU table. This is a faithful 1:1 reproduction that does not require re-running the (heavy, semi-manual) assembly, and is fully human-auditable.
Out of scope (not pipeline-reproducible / wet-lab / manual / external)
- WGS sequencing itself (wet lab) — only reuse the SRA reads.
- Mitogenome assembly GetOrganelle/Bowtie2 + manual Geneious inspection + GeSeq annotation with manual curation — semi-manual; not a deterministic pipeline. We instead reproduce downstream metrics from the deposited result. (Optionally attempt one assembly on «our HPC» as a spot-check if time allows.)
- Nuclear ortholog calling / RAxML species tree (2,422 orthologs) — heavy; attempt only as stretch.
- Any narrative/qualitative claims ("largely consistent topology", "high support").
Code artifact (P16 note)
The linked repo github.com/nylander/catfasta2phyml is a third-party Perl
tool for concatenating FASTA alignments into PHYLIP/phyml input — used by the
authors for the mito phylogeny. Per brief P16, applying it to the paper's data is
a valid reproduction, but it is peripheral to the central codon-usage results.
There is no custom authors' analysis-code repository; codon usage was computed
in DAMBE/R (GUI tools). We therefore reproduce the codon-usage numbers with an
independent, scripted reimplementation (Biopython codon counts → RSCU/ENc), which
is the stronger fabrication check.
Data inventory
- GenBank mitogenomes (this study): ON833077, ON833078, ON833079, ON833081–ON833094
Assessments & scoring basis
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Reproduction footprint
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