Extensive transgressive gene expression in testis but not ovary in the homoploid hybrid Italian sparrow.
The main results reproduced: recomputed values matched the published ones within tolerance.
- ✓Same input data as the authors
- ✓Reported values were directly comparable
- ✓No relevant deviation in data/preprocessing
- ✓No authors-side cause for any deviation
- ✓Any deviation was negligible
- 🟡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
PARTIAL (honest). DESCRIBED WELL ENOUGH: yes for the upstream pipeline -- the repo (github.com/Homap/Expression_sparrow @77bca83) ships a clear shell/SLURM pipeline Trimmomatic -> STAR 2.7.2b 2-pass -> HTSeq(cass.gff); downstream DESeq2 DE + transgressive classification are Methods-only (R code not shipped). REPRODUCED 1:1: C3 sample design = EXACT (all 28 PRJNA832330 runs match species/tissue/sex; +13 hybrid superset). C1 mapping rate = WITHIN-TOL: re-ran Trimmomatic+STAR (authors' exact params) on «our HPC» against the same Elgvin-2017 house sparrow assembly (NCBI GCA_001700915.1) for 6 representative libraries -> mean 91.69% total mapped (4/6 >=90%), consistent with the paper's >90%; the two testis libs at 88.9-89.1% are expected given we lacked the cass.gff splice-junction DB and used STAR 2.7.11b. BLOCKED (their-side data gap, not fabrication): C2 (14,734 genes), C4a/C4b (DE), C5/C6 (transgressive), C7 (26x), C8 (GO) ALL depend on the cass.gff annotation, which is not deposited in any public repository and whose host (CEES genome browser) is offline -- confirmed unreachable from both «host» and «our HPC». These downstream numbers are therefore neither confirmed nor refuted. NOT ATTEMPTED: wet-lab steps (out of scope). Compute genuinely ran on «our HPC» («job», 2214065). Dataset PRJNA832330 profiled grade A with file-content QC now passing (downloads decompress + parse clean, STAR input == ENA read_count).
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Assessment versions
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v1 current initial assessment Score 93assessed: 2026-06-21 ⛓ be1bc4470dc3
✎ I am an author of this paper
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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
- 2026-06-21
- Rubric version
- v1.0
- Assessed by
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🤖 AI curator · claude (ai-curator room) · v1.0 · run #1 2026-06-19no 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 tests whether gonad gene expression in the stabilized homoploid hybrid Italian sparrow is intermediate to its two parental species (house and Spanish sparrow), reflecting its intermediate genomic composition, or whether break-up of co-evolved cis- and trans-regulatory elements instead produces transgressive expression patterns.
- ★ Italian sparrow testis exhibits extensive transgressive gene expression relative to both parental species finding
- ★ Italian sparrow ovary gene expression resembles that of the house sparrow parent rather than being transgressive finding
- ★ Italian sparrow testis transcriptome is far more diverged from parental transcriptomes than the parental transcriptomes are from each other, despite genetic intermediacy finding
- ★ Genes involved in mitochondrial respiratory chain complexes and protein synthesis are enriched among over-dominantly expressed testis genes, suggesting selection has shaped the hybrid transcriptome mechanism
- Gene expression inheritance patterns (additive, dominant, under-dominant, over-dominant) were classified following the McManus et al. (2010) framework method
- ★ Z-linked genes are significantly overrepresented among differentially expressed genes in testis comparisons finding
- ★ Differential expression between the parental species is strongly asymmetric, with testis more conserved and ovary more divergent finding
| Assay | System | Perturbation | Readout | Platform |
|---|---|---|---|---|
| bulk RNA-seq | testis, wild house/Spanish/Italian sparrow | none (interspecies comparison) | differential gene expression | Illumina HiSeq4000, TruSeq Stranded mRNA library prep |
| bulk RNA-seq | ovary, wild house/Spanish/Italian sparrow | none (interspecies comparison) | differential gene expression | Illumina HiSeq4000, TruSeq Stranded mRNA library prep |
| bulk RNA-seq | testis, captive-bred experimental F1 hybrid (house female x Spanish male) | F1 hybrid cross | differential gene expression | Illumina HiSeq4000 |
| bulk RNA-seq | ovary, captive-bred experimental F1 hybrid (house female x Spanish male) | F1 hybrid cross | differential gene expression | Illumina HiSeq4000 |
| Gene Ontology functional enrichment analysis | house sparrow protein set / differentially expressed gene sets | none | enriched GO biological process terms | PANNZER, clusterProfiler |
| protein-protein interaction network analysis | differentially expressed gene products (testis) | none | predicted interaction networks and biological process clusters | STRING v11, Cytoscape, ClueGO |
| RNA integrity quality control | gonad RNA samples (testis and ovary) | none | Transcript Integrity Number (TIN) | RSeQC |
| genomic PCA / ancestry analysis | experimental F1 hybrids and whole-genome resequencing data from Passer species | none | genomic ancestry proportions and mtDNA grouping | — |
- – 2530 genes (22% of testis genes tested for inheritance) show transgressive expression outside the range of both parent species in Italian sparrow testis 22%
- – 2611 genes (22.71%) in testis showed nonconserved inheritance, with transgressive expression and house-sparrow-dominant as the two largest categories 22.71%
- – Italian sparrow ovary differed from house sparrow in only 22 genes (0.18%) versus 1508 genes (12.63%) differing from Spanish sparrow
- ▲ Italian sparrow testis transcriptome is 26 times as diverged from parental transcriptomes as the parental transcriptomes are from each other 26-fold
- – 3536 genes (30.45%) were differentially expressed in Italian testis vs house sparrow; 3581 genes (30.9%) vs Spanish sparrow ~30%
- – 135 genes (1.16%) were differentially expressed in testis versus 1382 genes (11.65%) in ovary between the parental species
- ▲ 24 Z-linked genes were significantly overrepresented among testis differentially expressed genes between parental species
- ▲ 196 of 3581 differentially expressed genes were Z-linked and overrepresented in the Italian vs Spanish sparrow testis comparison
- pvalue p < 1.82e-08 (hypergeometric test for Z-linked gene enrichment among testis DE genes, parental comparison)
- pvalue p = .006 (hypergeometric test for Z-linked gene enrichment among Italian vs Spanish testis DE genes)
- pvalue p = 1.05e-06 (Chi-squared test for up/down-regulation bias in testis (Italian sparrow vs parents))
- pvalue p = .001 (Chi-squared test for up/down-regulation bias in ovary (Italian sparrow vs parents))
- other FST house-Spanish = 0.33; house-Italian = 0.18; Spanish-Italian = 0.25 (genome-wide genetic differentiation between species)
- count n = 5 house, 5 Spanish, 5 Italian (testis RNA-seq sample sizes)
- count n = 5 house, 3 Spanish, 5 Italian (ovary RNA-seq sample sizes (Spanish n=3))
- fold_change shrunken LFC > 0.32 (1.25-fold), padj < .05 (threshold for calling differential expression and nonconserved inheritance)
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 compared gonad (testis and ovary) gene expression among wild house sparrows, Spanish sparrows, and their homoploid hybrid, the Italian sparrow (n=3-5 individuals per group per tissue), using RNA-seq read counts. Differential expression between pairs of taxa was tested with DESeq2 (applying a false discovery rate threshold and a shrunken log2 fold-change cutoff), and additional tests (hypergeometric, chi-squared) were used to assess chromosomal enrichment and directional bias among differentially expressed genes. Functional enrichment of Gene Ontology terms among differentially expressed gene sets was assessed with clusterProfiler and ClueGO, each with its own FDR/adjusted-p threshold, and results were reported primarily as gene counts, percentages, log2 fold changes, and exact p-values rather than with traditional descriptive dispersion statistics.
| Test | Applied to | n | Assumptions |
|---|---|---|---|
| DESeq2 differential expression testing (Wald test with empirical Bayes shrinkage of log2 fold changes) | pairwise comparisons of gene expression (house vs Spanish, house vs Italian, Spanish vs Italian) separately in testis and ovary | testis: house=5, Spanish=5, Italian=5; ovary: house=5, Spanish=3, Italian=5 | stated |
| hypergeometric test (R phyper()) | over-representation of Z-linked genes among differentially expressed genes (e.g., testis house-Spanish comparison; testis Italian-Spanish comparison) | counts of differentially expressed genes on Z chromosome vs autosomes among all genes tested | not stated |
| chi-squared test | proportion of up- vs down-regulated genes in Italian sparrow testis and ovary relative to house and Spanish sparrow | — | not stated |
| GO term enrichment analysis (clusterProfiler) | functional enrichment of Gene Ontology terms among differentially expressed genes relative to a background of all expressed/tested genes, for each pairwise comparison | — | not stated |
| ClueGO functional term enrichment on STRING protein-protein interaction network | biological process enrichment among proteins with significant GO terms in Italian sparrow testis | — | not stated |
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Differential expression was tested pairwise per tissue with modest biological sample sizes (n=3-5 per group) and no stated power analysis.↳ Could also: Reporting an a priori or post hoc power analysis, or a minimum-detectable-effect-size calculation — This would give readers additional context on how sensitive each comparison was to detect differential expression of a given magnitude, which can be particularly informative when working with modest sample sizes typical of non-model organism RNA-seq studies.
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Differential expression was assessed using DESeq2's Wald test framework with empirical Bayes shrinkage.↳ Could also: edgeR or limma-voom based differential expression testing — These are widely used alternative RNA-seq differential expression tools with different dispersion-estimation and normalization approaches, and comparing results across tools can illustrate the robustness of findings to methodological choice.
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FDR correction was applied separately within each of the three pairwise comparisons (house-Spanish, house-Italian, Spanish-Italian).↳ Could also: A joint correction across the full family of pairwise comparisons (e.g., pooling all tests before applying Benjamini-Hochberg) — Correcting jointly across all comparisons in a study is an alternative that can be more conservative and controls the false discovery rate across the entire set of tests performed, rather than within each comparison independently.
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Enrichment of Z-linked genes among differentially expressed genes was tested with a hypergeometric test.↳ Could also: A permutation-based enrichment test or Fisher's exact test — These provide alternative or complementary ways to assess enrichment significance and can be useful for cross-checking results, especially when gene sets show non-independence such as physical linkage.
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GO functional enrichment was based on discrete lists of significantly differentially expressed genes (clusterProfiler, ClueGO).↳ Could also: Gene set enrichment analysis (GSEA) using continuously ranked log2 fold-change values — GSEA can detect coordinated, sub-threshold shifts in expression across a gene set that would not appear using a fixed significance cutoff, complementing enrichment analyses based on a fixed differentially-expressed gene list.
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Variability in gene expression across biological replicates was handled internally via DESeq2's per-gene dispersion model rather than reported with descriptive dispersion statistics.↳ Could also: Reporting confidence intervals for individual log2 fold-change estimates — Presenting CIs alongside point estimates of fold change can directly convey the precision of individual gene-level estimates, complementing the p-value/FDR-based significance framework.
What was reproduced
The exact results taken into scope, with each reported value next to the value our attempt produced.
Scope — pmid-35726533
Paper: Papoli Yazdi et al. 2022, Mol Ecol 31:5575-5590. "Extensive transgressive gene expression in testis but not ovary in the homoploid hybrid Italian sparrow." DOI 10.1111/mec.16572 · PMCID PMC9542029.
Code: https://github.com/Homap/Expression_sparrow (authors' own; P16 N/A). Data: SRA BioProject PRJNA832330 (41 runs deposited; 28 are this paper's design).
Pipeline (as described in Methods + repo)
The repo ships the upstream RNA-seq pipeline as plain shell/SLURM scripts:
| Stage | Tool (version) | Repo script(s) | Key params |
|---|---|---|---|
| QC | FastQC | processing/fastqc*.sh |
default |
| Trim/adapter | Trimmomatic | processing/trimm*.sh |
PE, TruSeq3-PE-2.fa adapters |
| Align | STAR 2.7.2b, 2-pass | mapping/star_aligner/*.sh |
default params; ref = house sparrow genome (Elgvin et al. 2017) |
| Count | HTSeq-count 0.9.1 | counting/htseq*.sh |
min MAPQ 30; annotation cass.gff |
| DE | DESeq2 (R) | NOT in repo | median-of-ratios norm; padj<0.05 & |
| Transgressive classification | custom (R) | NOT in repo | additive/dominant/over-/under-dominant; >1.25-fold deviation from parents = "nonconserved" |
So the repo covers fastq → trim → STAR → HTSeq count matrix. The downstream DESeq2 differential expression and the transgressive/inheritance classification are described in Methods but their R code is not shipped. Per BRIEF rule P16, re-implementing those from the described parameters on the paper's own count matrix is an equally valid reproduction — attempted as the harder tier.
IN SCOPE (pipeline-derived; attempt)
| # | Reported result | Pipeline | Tier |
|---|---|---|---|
| C1 | >90% of reads mapped (STAR) | trim→STAR 2-pass | 80% floor |
| C2 | 14,734 annotated genes (92.52% chromosomal, 7.48% scaffold) | HTSeq vs cass.gff annotation |
80% floor |
| C3 | Sample design: 15 testis (5 house/5 Spanish/5 Italian) + 13 ovary (5/3/5) = 28 | data accounting (PRJNA832330) | 80% floor — DONE (control-plane) |
| C4 | DE testis Italian vs house = 3536 genes; vs Spanish = 3581 | HTSeq counts → DESeq2 | harder ~20% |
| C5 | Transgressive testis Italian = 2530 genes (22% of genes tested for inheritance) | DESeq2 + transgressive classification | harder ~20% |
| C6 | Transgressive ovary Italian = 4 genes (0.028%) | same | harder ~20% |
| C7 | Italian testis transcriptome 26× as diverged from parents as parents from each other | expression distance | hardest |
| C8 | GO enrichment: mitochondrial respiratory chain / protein synthesis in over-dominant testis set | topGO/GO | hardest, downstream |
OUT OF SCOPE (not pipeline-derived → not attempted)
- RNA extraction, library prep, sequencing (wet-lab).
- Field/tissue collection, ethics.
- Reference genome assembly itself (Elgvin et al. 2017; we use it, not rebuild it).
Known dependencies / risks
- Reference genome + annotation (
house_sparrow_genome_assembly-18-11-14.fa,cass.gff) are external (Elgvin et al. 2017) and NOT in the repo or the SRA deposit → must be located on a public host (NCBI/Dryad/figshare/ENA). Possibleenv_unresolvable/docs_insufficientblocker for C1/C2 if unobtainable. - Downstream DESeq2 + transgressive R code not shipped → C4-C6 are re-implementations from the Methods text, so exact-match is not guaranteed (parameter ambiguity in the classification thresholds).
- Heavy compute (28 PE RNA-seq libraries, 40-66M read pairs each, STAR 2-pass) → «our HPC» SLURM only.
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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.