Identification of the Wheat (Triticum aestivum) IQD Gene Family and an Expression Analysis of Candidate Genes Associated with Seed Dormancy and Germination
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.
- ✓Reported values were directly comparable
- ✓Reported values are derivable from the shared data
- 🟡Could not use the authors’ exact input data
- 🟡A deviation arose in the data or preprocessing
- 🟡A deviation was attributed to the published material
- 🟡The deviation was non-trivial in magnitude
- 🟡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
Plant gene-family identification paper (wheat TaIQD). Described well enough to reproduce the deterministic, pipeline-derived numbers from public data (Ensembl Plants r51, IWGSC RefSeq v2.1 -- pinned via the TraesCS..02G.. ID format in Table 1). RESULT = largely 1:1 for the deterministic core: chromosomal distribution EXACT (18 chr, group-6 absent, per-chr counts) and per-gene ExPASy/ProtParam physicochemistry (MW/pI/aliphatic/GRAVY/instability) reproduced to within tight tolerance (MW sub-Dalton) for 67/73 genes whose reported gene model still exists in r51; the other 6 are annotation-version drift (older IWGSC v1.1 models), NOT fabrication. DIFFERENT/partial for the family-size headline (73): a naive PF00612 domain scan gives 86 with only 36 overlap because PF00612 is not IQD-specific -- the paper's 73 is a BLASTP-anchored curated count we did not replicate (the optional hard 20%). Exon counts only 34/73 (isoform/GSDS-sensitive). Flagged two internal prose-vs-Table-1 inconsistencies (text MW max 69213.26 vs table 69491.65; text pI min 9.38 vs table 9.56) as likely proofreading errors, not fabrication. NOT attempted: qRT-PCR, GFP localization, germination %, MEGA group assignment, MEME/PlantCARE descriptions, Ka/Ks, and the GSE12508/GSE49821 expression heatmaps (wet-lab / subjective / web-GUI / interpretive).
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.
-
v1 current initial assessment Score 78assessed: 2026-06-15 ⛓ cecc21f71677
✎ 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.
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
- 2026-06-15
- Rubric version
- v1.0
- Assessed by
-
🤖 AI curator · claude (ai-curator room) · v1.0 · run #1 2026-06-15no 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: opusThis study asks whether IQ67 Domain (IQD) genes exist in the wheat genome and which TaIQD members are involved in regulating seed dormancy and germination, hypothesizing that specific TaIQDs act through the abscisic acid (ABA)-signaling pathway.
- ★ 73 IQD gene family members (TaIQD1-73) were identified in the wheat genome and phylogenetically divided into six major groups. finding
- ★ Seven genes (TaIQD4/-28/-32/-58/-64/-69/-71) likely participate in seed dormancy and germination through the ABA-signaling pathway. finding
- ★ Segmental duplications (not tandem) drove TaIQD expansion, and the family underwent strong purifying selection (Ka/Ks < 1). mechanism
- ★ TaIQD4/-32/-58/-64/-69/-71 are more highly transcribed in low-dormancy varieties while TaIQD28 shows the opposite trend. finding
- TaIQD promoters contain abundant hormone, light, and abiotic stress response cis-elements (e.g. ABRE, G-box, TGACG-motif). finding
- Bioinformatic identification and characterization of the wheat IQD family provides a resource for cloning candidate dormancy/germination genes. resource
- TaIQD4-GFP localizes to cell membranes, whereas TaIQD58-GFP and TaIQD64-GFP localize to nuclei and cell membranes. finding
- ★ Exogenous ABA inhibits germination and downregulates TaIQD4/-32/-58/-64/-69/-71 while upregulating TaIQD28. mechanism
| Assay | System | Perturbation | Readout | Platform |
|---|---|---|---|---|
| Genome-wide bioinformatic gene family identification (HMMER/Pfam PF00612) | Triticum aestivum (Chinese Spring) genome | none | IQD gene/protein members and physicochemical properties (ORF, aa, pI, MW, AI, GRAVY) | — |
| Phylogenetic / conserved motif & gene structure analysis (MEME, multiple sequence alignment) | TaIQD, AtIQD, ZmIQD, OsIQD protein sequences | none | phylogenetic groups, conserved motifs, exon-intron structure | MEME |
| Synteny / duplication and Ka/Ks evolutionary analysis | wheat vs Ae. tauschii, Z. mays, T. dicoccoides, O. sativa | none | collinear gene pairs, Ka/Ks and Ks values | — |
| Cis-acting element prediction | 2 kb promoter regions of 73 TaIQD genes | none | light, hormone, abiotic stress cis-elements | PlantCARE database |
| Microarray tissue expression profiling | 13 wheat developmental tissues (GEO GSE12508) | none | expression levels of 50 TaIQDs | GEO GSE12508 microarray |
| Transcriptome (RNA-seq) expression analysis during imbibition | JM20 seeds (GSE49821) and HMC21 & J411 seeds with contrasting dormancy | water imbibition timecourse (0-48 h; 6/9/12 h) | differential TaIQD expression | GEO GSE49821 |
| Quantitative real-time PCR (qRT-PCR) | six wheat varieties (HMC21, YXM, YM16, J411, ZY9507, ZM895) with contrasting dormancy; HMC21 & J411 for ABA assay | seed imbibition (0/12 h) and 50 µM exogenous ABA vs distilled water control | relative transcript levels of 15 (and 7) TaIQD genes; germination rate/index | — |
| Subcellular localization (GFP fusion) | rice protoplasts | transient overexpression of TaIQD4/58/64-GFP fusion vectors vs 35S-GFP control | GFP localization (membrane/nucleus) | — |
- – 73 IQD proteins identified in wheat, distributed unevenly across 18 of 21 chromosomes (none on 6A/6B/6D) 73 members; 25/25/23 in A/B/D sub-genomes
- – 111 duplicated gene pairs detected, all segmental (no tandem), all with Ka/Ks < 1 (purifying selection) 111 pairs; Ks 0.0476-1.1249; divergence ~26.92 Mya
- ▲ TaIQD28/-32/-58/-64/-69/-71 highly expressed in germinated seeds and endosperm
- – TaIQD4/-32/-58/-64/-69/-71 more highly transcribed in three low-dormancy than three high-dormancy varieties; TaIQD28 opposite
- – After 12 h imbibition, dormant varieties showed 0% germination vs 98% for non-dormant varieties 0% vs 98%
- ▼ 50 µM ABA reduced germination index to 53% (HMC21) and 82% (J411), and downregulated TaIQD4/-32/-58/-64/-69/-71 while upregulating TaIQD28 germination index 53% / 82%
- – TaIQD ORFs ranged 1020-1881 bp encoding 339-626 aa proteins with MW 37,096-69,213 Da 339-626 aa
- – During JM20 imbibition, 15 genes increased and 14 genes decreased in expression over time 15 up / 14 down
- count 73 IQD proteins (TaIQD members identified in wheat genome)
- count 111 gene pairs (duplicated TaIQD gene pairs, all segmental)
- other Ks 0.0476-1.1249, concentration near 0.35 (Ks of TaIQD duplicated pairs; divergence ~26.92 Mya)
- mean pI > 9.38, average 10.35 (isoelectric points of TaIQD proteins)
- other germination index 53% (HMC21) and 82% (J411) (after 50 µM ABA treatment at 24 h)
- count germination 0% (dormant) vs 98% (non-dormant) (average germination rate after 12 h imbibition)
- other Ks averages 0.374 (Ta-Aet), 0.693 (Ta-Zm), 0.379 (Ta-Td), 0.659 (Ta-Os) (synteny Ks between wheat and four gramineous species)
- other AI 48.27-78.18 (aliphatic/thermal stability index range of TaIQD proteins)
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 bioinformatics-focused study identified 73 TaIQD genes in wheat through domain-based protein screening and characterized them using phylogenetic reconstruction, Ka/Ks-based evolutionary analysis, cis-element prediction, and publicly available microarray and transcriptome data mining. Fifteen candidate genes were validated by qRT-PCR across six wheat varieties with contrasting dormancy phenotypes at two imbibition time points and under exogenous ABA treatment, with expression differences described as 'significant' without specifying an underlying statistical test. Results were reported primarily as descriptive comparisons of expression patterns and germination percentages, with no dispersion measures or p-values provided.
| Test | Applied to | n | Assumptions |
|---|---|---|---|
| Ka/Ks ratio comparison to threshold of 1 (no formal hypothesis test stated) | Evolutionary constraint analysis of 111 intra-wheat duplicated TaIQD gene pairs (Figure 3b, Table S3) and collinear gene pairs with four other gramineous species (Figure 4b, Table S4) | 111 intra-wheat gene pairs; 89–161 interspecies collinear pairs depending on species | not stated |
| Phylogenetic tree construction with bootstrap support values (algorithm not named in available text) | Phylogenetic grouping of IQD proteins from wheat, Arabidopsis, rice, and maize (Figure 1a, Figure 2a) | 159 IQD proteins across four species (73 TaIQD plus AtIQD, ZmIQD, OsIQD) | not stated |
| Transcriptome differential expression analysis (specific statistical method not stated) | Identification of 15 significantly differentially expressed TaIQD genes from GEO datasets GSE49821 (JM20, 5 time points) and a study-generated HMC21/J411 dataset at 6, 9, and 12 h imbibition (Figure 7, Tables S7–S8) | null | not stated |
| qRT-PCR relative expression comparison (statistical test not stated; significance asserted descriptively) | Expression of 15 TaIQD genes in 6 wheat varieties at 0 h and 12 h imbibition, and ABA vs. distilled-water treatment in HMC21 and J411 (Figures 8–9) | 6 wheat varieties (3 dormant, 3 non-dormant); biological replicate number per variety not stated | not stated |
-
qRT-PCR expression differences between dormant and non-dormant varieties were described as 'significant' without naming the statistical test↳ Could also: A Student's t-test (or Mann-Whitney U for non-normal distributions) could be applied to compare mean relative expression between the two groups, with the test name and resulting p-values reported — Naming the test and reporting exact p-values allows readers to assess the strength of evidence independently and makes the analysis reproducible
-
Fifteen genes were evaluated for differential expression across six varieties and two treatment conditions without any multiplicity correction↳ Could also: A Benjamini-Hochberg false discovery rate (FDR) correction could be applied across the family of comparisons for the 15 candidate genes — Simultaneously testing multiple genes increases the expected number of false positives; an FDR correction calibrates that expectation and helps distinguish robust candidates from chance findings
-
qRT-PCR results were reported without any measure of within-group variability↳ Could also: Standard deviation (SD) or standard error of the mean (SEM) alongside the mean, displayed as error bars in figures — Reporting dispersion conveys within-group variability, supports visual assessment of overlap between groups, and is especially informative when the number of replicates per group is small
-
Ka/Ks ratios were compared informally to the neutral-evolution threshold of 1 to infer purifying selection, without a formal statistical test↳ Could also: A likelihood-ratio test using branch-site models (e.g., in PAML/codeml) could formally test the null hypothesis of Ka/Ks = 1 for each gene pair — A formal test yields a p-value for each gene pair's deviation from neutrality, enabling stronger and more granular inference about selective pressure rather than a global directional observation
-
Differential expression from public transcriptome datasets was described as 'significant' without stating the processing pipeline, normalization method, or significance thresholds used↳ Could also: Standard RNA-seq differential expression tools such as DESeq2, edgeR, or limma-voom, with explicitly stated FDR thresholds and log2 fold-change cutoffs, could be documented — Stating the pipeline and thresholds makes the candidate gene filtering criteria reproducible and allows readers to judge the stringency of the selection
-
Phylogenetic branch support was reported via bootstrap values, with the tree-building algorithm not named in the available text↳ Could also: Bayesian phylogenetic inference (e.g., MrBayes or IQ-TREE with ultrafast bootstrap) producing posterior probability values or ultrafast bootstrap support could also be used, with the substitution model explicitly stated — Reporting the algorithm, substitution model selection procedure, and support metric makes the phylogeny reproducible and allows comparison with future analyses as more sequences become available
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.
No assessed neighbours yet — the network grows as more papers are assessed.
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-35456910
Paper: Liu et al. 2022, Identification of the Wheat (Triticum aestivum) IQD Gene Family and an Expression Analysis of Candidate Genes Associated with Seed Dormancy and Germination. Int J Mol Sci 23(8):4093. PMID 35456910 / PMC9025732 / doi:10.3390/ijms23084093.
"Code" (P16): https://github.com/CJ-Chen/TBtools — TBtools v1.098, a third-party GUI bioinformatics toolkit. The paper applies TBtools + standard web/CLI tools (BLASTP, PFAM/HMM, MEGA 6.0 NJ, MEME, ExPASy ProtParam, GSDS, MCScanX, PlantCARE) to public wheat genome data. Per the brief's P16 rule, applying a third-party tool to the paper's data is a fully valid reproduction.
Genome data pin: "Wheat genomic data were downloaded from Ensembl Plants … accessed
on 24 July 2021." The Table 1 gene IDs use the TraesCS#A02G###### format =
IWGSC RefSeq v2.1 annotation, which Ensembl Plants shipped from release 51
(July 2021). Reproduction targets Ensembl Plants release-51 Triticum aestivum
(assembly IWGSC, annotation v2.1): pep.all, cds.all, gff3.
IN SCOPE (pipeline-derived, deterministic or near-deterministic)
| id | result | reported | pipeline | feasibility |
|---|---|---|---|---|
| C1 | family size | 73 TaIQD genes | BLASTP(e<1e-5)+PFAM PF00612 vs wheat proteome; we use hmmsearch PF00612 + domain verify, collapse to gene | HIGH (count may differ with thresholds/HC-vs-all) |
| C2 | protein length range | 339–626 aa | ExPASy ProtParam on the 73 proteins | HIGH (deterministic per sequence) |
| C3 | MW range | 37096.08–69213.26 Da (text); table max = 69491.65 (TaIQD38) — internal text↔table mismatch | ProtParam | HIGH |
| C4 | pI range | 9.38–11.47, avg 10.35 (text); table min = 9.56 (TaIQD11) — text↔table mismatch | ProtParam | HIGH |
| C5 | per-gene physchem (aa, MW, pI, instability, aliphatic, GRAVY) | Table 1, 73 rows | ProtParam vs Table 1, per gene | HIGH — the core auditable check |
| C6 | ORF length (bp) | Table 1 orf_bp per gene | CDS length from cds.all | HIGH |
| C7 | exon count | Table 1 exons (2–6) | count exons per representative mRNA in GFF3 | MEDIUM (isoform choice) |
| C8 | chromosomal distribution | 18 chromosomes; absent from 6A/6B/6D | parse chr from gene IDs / GFF3 | HIGH |
| C9 | instability | all "Unstable" | ProtParam instability index > 40 | HIGH |
OUT OF SCOPE (not attempted — wet-lab / manual / subjective / unshipped data)
- qRT-PCR validation (6 varieties, TaActin, CFX96) — wet lab.
- Subcellular localization GFP in rice protoplasts — wet lab.
- Germination percentages, ABA 50 µM treatment — wet lab.
- Phylogenetic grouping into 6/7 groups (MEGA NJ) — tree built but group assignment is subjective; we may build the tree as a soft check but will not grade group sizes.
- MEME 10-motif description, PlantCARE cis-elements — qualitative, web-GUI, not graded.
- Ka/Ks + 111 duplication pairs (MCScanX) — possible but lower priority (80/20: optional).
- Expression heatmaps from GSE12508 (microarray, 13 tissues) / GSE49821 — the paper says "FPKM log2(1+)" for a microarray series, which is itself questionable; probe→gene mapping for 73 wheat genes is fiddly and the candidate-gene narrative is interpretive. Treated as optional / likely not graded.
80/20 plan
Primary deliverable = C5/C2/C3/C4/C6/C9 (deterministic per-gene ProtParam on the 73 Table-1 genes pulled from Ensembl Plants r51 v2.1) + C8 (chromosomal map) + C1 (independent family identification via PF00612). Everything else optional.
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.
The deterministic core of this wheat IQD gene-family paper reproduces strongly: chromosomal distribution is EXACT (18 chromosomes, group-6 absent, per-chromosome counts) and Table 1 physicochemistry reproduces to sub-Dalton for the 67/73 genes whose models persist in Ensembl r51 — strong evidence the table was computed, not invented. The notable deviations are on our methodology / data-version side: the 73-gene headline only partially reproduces (86 via a naive PF00612 scan, 36/73 overlap) because we did not replicate the paper's BLASTP curation, and 6 genes show annotation-version drift, not fabrication. Two prose-vs-Table-1 inconsistencies (MW 69213.26 vs 69491.65; pI 9.38 vs 9.56) are minor proofreading slips. Overall solid with explainable deviations, no fabrication indicated.
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.
Are you an author? We would genuinely like to hear from you — to clarify the record, add data or code, re-run the pipeline after an accession update, and publish your response right next to the assessment. Everything here is open and auditable.
🚩 Report an error in this record
Spotted something wrong — a verdict you’d contest, a data or value error, or a private detail that slipped through? Tell us, with a short justification. Authors and readers are equally welcome to write in; we review every report.
Prefer email, or the form below not working? Contact us at support@doesitreproduce.com.
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.