Systematic analysis of CNGCs in cotton and the positive role of GhCNGC32 and GhCNGC35 in salt tolerance.
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
- Every checked point held up.
▸Reproduction agent’s raw note
DROP (docs_insufficient). This is a genome-wide gene-family characterization paper (CNGCs in cotton + salt-tolerance functional work on GhCNGC32/GhCNGC35). Its in-scope pipeline-derived results (CNGC family identification via HMMER/Pfam, chromosomal mapping, gene structure, MEME motifs, MEGA phylogeny, cis-elements, and RNA-seq expression from SRA PRJNA490626) would each require their own tool+parameter+version pinning. The only linked code is karlnicholas/GeneDoc = GeneDoc, a generic interactive MSA shading/editor GUI (verified live via GitHub API: 'A Full Featured Multiple Sequence Alignment Editor', C++, pushed 2018, not archived) — a third-party visualization tool, not the analysis pipeline, with no README/workflow/expected output linking it to this paper's reported values. Thus no runnable 1:1 reproduction path exists from the shipped code, and the per-result tools/params are not specified well enough to rebuild blind without chasing the hard 80%+. NOT attempted: SRA reprocessing, de-novo phylogeny/motif rebuild, and any «our HPC» jobs (room finalized before execution). Honest outcome: not reproducible as-shipped; recorded as a screening-stage docs_insufficient drop rather than a fabricated agreement. A human reviewer should confirm the code-link classification (GeneDoc != paper pipeline) — that single fact drives the drop.
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v1 current initial assessmentassessed: 2026-06-15 ⛓ a78d4f668199
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- Reproduced
- 2026-06-15
- Rubric version
- v1.0
- Assessed by
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🤖 AI curator · 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: opusCotton CNGC genes (like those in Arabidopsis) play important roles in the response to salt and drought stress; the study tests whether GhCNGC32 and GhCNGC35 contribute to salt tolerance in cotton.
- ★ 114 CNGC genes were identified across 4 cotton species (G. arboreum 20, G. raimondii 20, G. hirsutum 38, G. barbadense 36), clustering into 5 groups (I, II, III, IVa, IVb). resource
- ★ Silencing GhCNGC32 and GhCNGC35 via VIGS decreases salt tolerance of cotton plants. finding
- ★ Under salt stress, silenced plants show significantly increased MDA content and decreased POD activity versus controls. finding
- ★ The CNGC gene family expanded mainly through whole-genome duplication (WGD), with no tandem duplications detected, under purifying selection (Ka/Ks < 1). mechanism
- ★ GhCNGC promoters are enriched in ABA-responsive cis-acting elements, and salt stress triggers upregulation of ABA-related genes (GhABF2, GhABF3, GhNAC4). finding
- ★ GhCNGC10, GhCNGC13, GhCNGC32 and GhCNGC35 are significantly induced under salt and drought stress and respond to exogenous ABA. finding
- Combination of BLASTP, CDD/SMART domain confirmation, MEME motif and phylogenetic analysis was used to systematically characterize cotton CNGCs. method
| Assay | System | Perturbation | Readout | Platform |
|---|---|---|---|---|
| Genome-wide gene family identification (BLASTP + CDD/SMART domain analysis) | 7 plant species including 4 cotton genomes (G. arboreum, G. raimondii, G. hirsutum, G. barbadense) | none | number of CNGC genes, CDS length, protein length, pI, MW, subcellular localization | CDD and SMART databases |
| Phylogenetic analysis | 114 cotton CNGC proteins plus 55 CNGCs from A. thaliana, O. sativa, P. trichocarpa | none | subgroup classification (I, II, III, IVa, IVb) | — |
| Conserved motif and gene structure analysis | 114 cotton CNGC proteins/genes | none | 20 conserved motifs, intron/exon counts | MEME software |
| Collinearity and gene duplication / Ka-Ks analysis | G. hirsutum, G. barbadense and diploid A/D ancestral genomes | none | homologous gene pairs, WGD vs tandem duplication, Ka/Ks ratios | MCScanX, KaKs_Calculator2 |
| Cis-acting element analysis | GhCNGC gene promoters | none | counts of stress- and hormone-responsive elements | — |
| Transcriptome (RNA-seq) expression profiling | G. hirsutum tissues (roots, stems, leaves, tori, pistils, petals, sepals) and salt/drought treatments | salt and drought stress | FPKM expression values | — |
| Quantitative RT-PCR (qRT-PCR) | cotton seedlings (G. hirsutum) | exogenous ABA treatment | relative gene expression of 6 GhCNGCs | — |
| Virus-induced gene silencing (VIGS) with physiological assays | G. hirsutum plants (TRV:00, TRV:GhCNGC32, TRV:GhCNGC35, TRV:GhCLA1 control) | gene silencing under salt stress | wilting rate, MDA content, POD activity, expression of GhCNGCs and ABA genes | — |
- – 114 CNGC genes identified in 4 cotton species out of 169 putative genes from 7 species 114 of 169
- ▼ Silencing GhCNGC32/GhCNGC35 increased wilting and reduced salt tolerance vs controls
- – MDA content significantly higher in silenced plants under salt stress; POD activity decreased
- – 67 of 74 CNGC genes in G. hirsutum/G. barbadense amplified by WGD; no tandem repeats; all gene pairs Ka/Ks < 1 67/74; Ka/Ks <1
- ▲ GhCNGC32 and GhCNGC35 significantly induced under salt and drought stress in transcriptome data
- ▼ GhCNGC10, GhCNGC13, GhCNGC17, GhCNGC32, GhCNGC35 reached lowest relative expression at 3 h after ABA treatment
- ▲ GhABF2, GhABF3, GhNAC4 expression significantly higher under salt stress; GhABF2/GhABF3 higher in silenced plants than controls under salt
- – 94.7% of cotton CNGC proteins had pI > 8.8; 109 of 114 localized to cell membrane 94.7%; 109/114
- count 114 CNGC genes (G. arboreum 20, G. raimondii 20, G. hirsutum 38, G. barbadense 36) (CNGC genes identified in cotton species)
- count 169 putative CNGC genes (identified from genomes of 7 species)
- count 67 of 74 (CNGC genes amplified by WGD in G. hirsutum and G. barbadense)
- other Ka/Ks < 1 (all duplicated gene pairs, indicating purifying selection)
- other pI range 6.53–9.62; 94.7% > 8.8 (isoelectric point of CNGC proteins)
- other protein 560–770 aa (avg 716); MW 64.74–88.33 kDa; CDS 1683–2313 bp (cotton CNGC sequence properties)
- count 60 ABA-responsive, 31 salt, 30 drought cis-acting elements (cis-acting elements in GhCNGC promoters)
- count 20 conserved motifs; 3–11 introns (motif and gene structure analysis of cotton CNGCs)
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.
The paper combines genome-wide bioinformatics characterization of 114 CNGC genes across four cotton species with transcriptome-based expression profiling (log2-FPKM heatmaps), qRT-PCR validation, and VIGS functional experiments. Physiological endpoints (MDA content, POD activity, wilting rate) and relative gene-expression levels were compared between VIGS-silenced and control plants using n=3 biological or independent replicates, with results expressed as means ± SD. The specific inferential statistical test(s) used to declare differences 'significant' are not named in the text.
| Test | Applied to | n | Assumptions |
|---|---|---|---|
| not explicitly stated (significance language used; test identity not named — likely pairwise comparison such as Student's t-test) | Comparison of MDA content, POD activity, wilting rate, and relative gene-expression between TRV:00 control and TRV:GhCNGC32/TRV:GhCNGC35 silenced plants under normal and salt-stress conditions (Figs. 6, 7) | 3 (stated as 'three independent experiments' in Fig. 6 legend; 'three biological replicates' in Fig. 5 legend) | not stated |
| not explicitly stated (significance language used; test identity not named) | Relative expression levels of six GhCNGC genes across ABA time-course (Fig. 5) | 3 biological replicates | not stated |
| Ka/Ks ratio (dN/dS) computed via KaKs_Calculator2 | Evolutionary selection pressure on 67 WGD-duplicated CNGC gene pairs between G. hirsutum and G. barbadense (Table S4) | 67 gene pairs identified by collinearity analysis | na |
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The specific inferential test used to compare MDA content, POD activity, wilting rate, and expression levels between groups is not named↳ Could also: A Student's t-test (two-tailed, unpaired) or one-way ANOVA with a post-hoc test (e.g., Tukey HSD) could be explicitly named and reported with test statistics and exact p-values — Naming the test and reporting the test statistic alongside the p-value allows readers to assess whether assumptions were met and to reproduce the analysis independently
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Statistical significance is described qualitatively without reporting p-values↳ Could also: Exact p-values, or at minimum threshold indicators (p < 0.05, p < 0.01), could be reported in figures or tables — Exact p-values convey the continuous degree of evidence against the null hypothesis rather than a binary classification, facilitating meta-analysis and replication efforts
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With three groups (TRV:00, TRV:GhCNGC32, TRV:GhCNGC35) measured under two conditions (normal and salt stress), multiple comparisons appear to have been made across several endpoints↳ Could also: A two-way ANOVA (factors: silencing genotype × stress condition) with a post-hoc correction such as Tukey HSD could be applied to jointly test all endpoints — Two-way ANOVA simultaneously estimates main effects and the genotype-by-stress interaction term, and a post-hoc correction controls the family-wise error rate across the resulting pairwise comparisons
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Transcriptome expression patterns were visualized as log2-FPKM heatmaps without application of a formal differential expression statistical framework↳ Could also: A dedicated RNA-seq differential expression method such as DESeq2 or edgeR (negative-binomial models with shrinkage estimators) could have been applied to call differentially expressed genes with FDR-adjusted p-values — DESeq2 and edgeR account for count-based overdispersion and low-replicate noise in RNA-seq data and produce calibrated false-discovery-rate estimates, complementing or replacing visual inspection of FPKM heatmaps
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Dispersion was reported as SD for n=3 replicates↳ Could also: 95% confidence intervals could also be reported alongside or instead of SD — CIs directly express the range of plausible population-mean values given the observed data, which can be informative alongside significance statements especially when sample sizes are small
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No effect sizes are reported for comparisons between silenced and control plants↳ Could also: Cohen's d or a fold-change with its confidence interval could be reported alongside p-values — Effect sizes quantify the practical magnitude of a difference independently of sample size, providing information that significance tests alone do not convey, which is particularly relevant when n is small (here n=3)
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