Transcriptome profiling of radish (Raphanus sativus L.) root and identification of genes involved in response to Lead (Pb) stress with next generation sequencin
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▸Reproduction agent’s raw note
Continued a prior worker's already-staged pipeline for pmid-23840502 (radish Pb-stress transcriptome). Reused pre-downloaded SRA reads (SRX256970/SRR802994=CK, SRX263753/SRR803021=Pb1000), pre-pulled containers, and pre-staged Swiss-Prot/GO reference data. Trinity de novo assembly required multiple 12h SLURM windows (walltime fallback chain trinity2 to trinity3 to trinity4) due to Butterfly-phase runtime on this dataset, and completed successfully. All ten in-scope SLURM pipeline stages (trinity assembly, rsem reference build, rsem quantification x2, diamond annotation, go annotation, edgeR differential expression, goatools GO enrichment) completed with State=COMPLETED, ExitCode=0:0 per sacct. Assembly stats, RSEM quantification (bowtie2 index/alignment via trinity.sif since rsem.sif has no bundled aligner, then rsem-calculate-expression --bam), edgeR differential expression (no biological replicates in the original design -- single CK vs single Pb1000 library -- so a fixed-BCV=0.1 exactTest was used as the closest available approximation since the paper's exact DE method is unspecified), diamond blastx vs Swiss-Prot (single-database annotation, narrower than the paper's combined Nr/Swiss-Prot/COG/KEGG/GO pipeline), and goatools GO enrichment (matching the cited code repository) were all run as SLURM jobs on the HPC cluster and their outputs verified directly from job logs and output files. KEGG pathway enrichment (paper Tables 2-3) was NOT attempted: no KEGG mapping data was staged and it falls outside the cited goatools repository's scope. The 314823 pre-existing radish ESTs and 17187 NCBI unigenes that the paper additionally incorporated into its assembly were NOT included here (only the two SRA read sets were assembled de novo), which is an expected source of divergence in absolute assembly statistics. TheGO enrichment claim, previously checkpointed as 'NOT AVAILABLE'/error, has been corrected in this pass: the goatools computation itself succeeded (774 significant terms for the up-regulated study set, 702 for the down-regulated study set), and only a separate downstream summary-writer script failed on an oversized CSV field; the real numbers were recovered from the job's full stdout log and cross-verified two independent ways. All numeric comparisons remain provisional pending human review, especially DEG counts and GO term counts, given the documented methodological substitutions (DE tool, single annotation DB, no EST/unigene integration). Not attempted in this reproduction: KEGG pathway enrichment/mapping (paper Tables 2-3), qRT-PCR validation of DEGs (wet-lab, out of scope), and any dose-response/time-course analysis beyond the single CK-vs-Pb1000 comparison (wet-lab experimental design, out of scope).
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- Reproduced
- 2026-07-31
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- v1.0
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🤖 AI curator · claude (ai-curator room) · v1.0 · run #1 2026-07-31no human curator yet
- Last updated
- 2026-07-31
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Deep full-text extraction
Model: opusLittle is known about how radish (Raphanus sativus L.) responds to lead (Pb) stress at the molecular level; this study asks which genes and pathways in radish roots are differentially regulated under Pb stress, using NGS-based de novo transcriptome sequencing to elucidate the molecular regulation mechanisms and critical genes involved.
- ★ A de novo radish root transcriptome of 68,940 assembled transcripts including 33,337 unigenes was generated, providing the first comprehensive molecular characterization of the radish root response to Pb stress. resource
- ★ 4,614 differentially expressed genes (DEGs) were detected between untreated control (CK) and Pb-treated (Pb1000) radish roots. finding
- ★ Upregulated DEGs under Pb stress are predominantly involved in defense responses in the cell wall (callose deposition, cell wall thickening) and glutathione metabolism-related processes. mechanism
- ★ Downregulated DEGs are mainly involved in carbohydrate metabolism-related pathways and cell wall organization/modification. mechanism
- ★ Candidate defense and detoxification genes — signaling protein kinases, transcription factors, metal transporters and chelate-compound biosynthesis enzymes — were identified as Pb-responsive. finding
- ★ qRT-PCR validation of 22 selected genes showed expression patterns highly concordant with the Solexa/RNA-seq analysis. method
- Illumina paired-end Solexa RNA-seq with Trinity de novo assembly, Bowtie/RSEM quantification and FPKM normalization is an effective approach for transcriptome profiling in a species lacking a reference genome. method
- Expression of selected Pb-responsive genes varies with both Pb concentration and treatment duration, e.g. GST3-1 and GSHB1 are downregulated at 200 and 500 mg L−1 but upregulated at 1000 mg L−1 Pb(NO3)2. finding
| Assay | System | Perturbation | Readout | Platform |
|---|---|---|---|---|
| RNA-seq (Illumina paired-end Solexa transcriptome sequencing, de novo) | Radish (Raphanus sativus L.) fleshy taproot/root, two cDNA libraries (CK and Pb1000) | Pb(NO3)2 at 1000 mg L−1 vs untreated control | Clean paired-end reads (2×101 bp), assembled transcripts/unigenes, FPKM expression levels, differentially expressed genes | Illumina HiSeq 2000 |
| De novo transcriptome assembly and expression quantification (bioinformatics) | Radish root cDNA sequence reads combined with 314,823 radish ESTs and 17,187 NCBI unigenes | none | Contig/transcript length distribution, N50/N90, unigene counts; read mapping and expression estimation | Trinity (assembly), Bowtie (mapping), RSEM (expression), FPKM normalization |
| Functional annotation and enrichment analysis (GO, COG, KEGG/KOBAS) | Assembled radish root transcripts and DEG sets | none (in silico on Pb-treated vs control DEGs) | GO term assignments, COG functional categories, KEGG pathway assignments, enriched GO terms and pathways (hypergeometric test with Bonferroni correction) | BLASTX (E-value cut-off 1e−5), goatools, KOBAS, COG and KEGG databases |
| Quantitative real-time PCR (qRT-PCR) validation | Radish roots (CK and Pb1000 samples) | Pb(NO3)2 at 1000 mg L−1 vs untreated control | Relative expression ratio (Pb1000/CK) of 22 selected DEGs compared with RNA-seq log fold change | — |
| qRT-PCR dose-response and time-course expression profiling | Radish roots | Pb(NO3)2 at 0, 200, 500 and 1000 mg L−1 for 72 h; and 1000 mg L−1 for 0, 24, 48 and 72 h | Relative transcript levels of six genes (GST3-1, GGT1, GSHB1 upregulated; SPDS, LAX2-1, LAX2-2 downregulated) | — |
- – A total of 4,614 DEGs (1,398 unigenes) were detected between Pb1000 and CK libraries, comprising 2,154 upregulated and 2,460 downregulated transcripts 4,614 DEGs (2,154 up / 2,460 down)
- – De novo assembly yielded 68,940 assembled transcripts including 33,337 unigenes, contig length 306–16,101 bp, average 1,226.63 bp, N50 = 1,262, N90 = 437 68,940 transcripts; 33,337 unigenes; N50 1,262 bp
- – GO enrichment identified 270 significantly enriched terms for upregulated transcripts versus only 107 for downregulated ones (Bonferroni-corrected P ≤ 0.05) 270 up vs 107 down GO terms
- ▲ Upregulated DEGs were enriched in xenobiotics biodegradation/metabolism pathways (drug metabolism-cytochrome P450, metabolism of xenobiotics by cytochrome P450) and glutathione metabolism; 13 pathways significantly enriched 13 enriched pathways; glutathione metabolism 20 genes, corrected P = 6.49E-05
- ▼ Downregulated DEGs were enriched in carbohydrate metabolism pathways: pentose and glucuronate interconversions, starch and sucrose metabolism, amino sugar and nucleotide sugar metabolism; six pathways significantly enriched 6 enriched pathways; pentose and glucuronate interconversions 26 genes, corrected P = 4.49E-12
- ▲ Glutathione pathway genes were strongly induced by Pb, e.g. GSTU11 (comp2239_c0_seq1) rose from 0.67 to 193.06 FPKM and GSHB1 from 51.37 to 454.81 FPKM GSTU11 log FC 8.18 (qRT-PCR 56.49-fold); GSHB1 log FC 3.15 (qRT-PCR 3.25-fold)
- ▼ Auxin transporter-like genes and spermine synthase were repressed by Pb, e.g. LAX3 fell from 199.38 to 4.81 FPKM and CCD8 from 180.13 to 0 FPKM LAX3 log FC −5.38 (qRT-PCR 0.13); CCD8 log FC −38.82 (qRT-PCR 0.01)
- – SPDS, LAX2-1 and LAX2-2 were downregulated at all Pb concentrations after 72 h, but SPDS was upregulated at 24 and 48 h and LAX2-1 at 24 h, indicating time-dependent responses
- count 4,614 DEGs (1,398 unigenes); 2,154 upregulated and 2,460 downregulated transcripts (DEGs between Pb1000 and CK libraries, log FC >2 or <−2, P<0.005, FDR<0.001)
- count 26,381,880 (CK) and 22,535,988 (Pb1000) clean paired-end reads; 2,636,208,012 and 2,251,686,397 nucleotides; 48,918,868 total clean reads (Illumina HiSeq 2000 sequencing output for the two libraries)
- count 68,940 assembled transcripts, 33,337 unigenes, whole dataset 84,563,748 bp, average contig 1,226.63 bp, N50 1,262, N90 437 (De novo Trinity assembly overview (Table 1))
- pvalue 1.34E-14 (corrected 4.49E-12) (Pentose and glucuronate interconversions [ko00040], most enriched downregulated pathway (26 of 104 background genes))
- pvalue 4.98E-10 (corrected 1.29E-07) (Drug metabolism–cytochrome P450 [ko00982], most enriched upregulated pathway (16 of 65 background genes))
- fold_change log FC 8.1793185 (RNA-seq); 56.49 (qRT-PCR Pb1000/CK) (GSTU11 glutathione-S-transferase, FPKM 0.67 → 193.06)
- count 46,966 transcript sequences (68.12%) assigned at least one GO term; 22,518 sequences assigned to 23 COG categories; 19,480 of 48,864 annotated sequences mapped to 296 KEGG pathways (Functional annotation of assembled transcripts)
- count 22 candidate DEGs validated by qRT-PCR; 6 genes profiled across 4 Pb concentrations (0, 200, 500, 1000 mg L−1) and 4 time points (0, 24, 48, 72 h) (qRT-PCR validation and dose/time-course experiments)
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 study used Illumina RNA-seq to compare a de novo assembled transcriptome from two radish root cDNA libraries, one untreated (CK) and one Pb-treated (Pb1000), each apparently represented by a single sequencing library. Differentially expressed genes (DEGs) were called using a log fold-change threshold (|logFC|>2) combined with a significance cutoff (P<0.005) and false discovery rate (FDR<0.001), and enrichment of GO terms and KEGG/KOBAS pathways among DEGs was assessed with a hypergeometric test and Bonferroni correction. A subset of 22 DEGs was validated by qRT-PCR, described as showing general agreement in expression direction/magnitude with the RNA-seq results.
| Test | Applied to | n | Assumptions |
|---|---|---|---|
| Fold-change + significance/FDR thresholding for DEG calling (|log FC|>2, P<0.005, FDR<0.001) | Comparison of CK vs Pb1000 root transcriptomes (4,614 DEGs) | Two sequencing libraries (one CK, one Pb1000), no stated biological replicate number | not stated |
| Hypergeometric test with Bonferroni correction | GO term enrichment among up- and down-regulated DEGs | All annotated DEGs vs background transcriptome | not stated |
| Hypergeometric-based pathway enrichment (KOBAS) | KEGG pathway enrichment among up- and down-regulated DEGs (Tables 2-3) | DEG counts per pathway vs background gene counts per pathway | not stated |
| qRT-PCR expression comparison (descriptive, no formal statistical test stated) | Validation of 22 selected DEGs, and dose/time-course expression of 6 selected genes (Figure 5) | Not stated (no replicate number given for qRT-PCR reactions) | not stated |
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DEGs between CK and Pb1000 were identified from what appears to be one library per condition rather than multiple biological replicates.↳ Could also: Designing the RNA-seq comparison with several biological replicates per condition and analyzing with a replicate-aware tool (e.g., DESeq2 or edgeR, which model biological variance via negative binomial dispersion) — Replicate-based variance modeling would let the FDR/P-value estimates capture biological variability between individual plants, which a single-library comparison cannot directly reflect
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DEGs were called using a combined logFC (>2 or <-2) plus P-value and FDR threshold.↳ Could also: Applying a dedicated count-based differential expression model (e.g., DESeq2 Wald test or edgeR exact/GLM test) directly to raw read counts — These tools jointly estimate dispersion and fold-change shrinkage, which can refine significance calls particularly for genes with low counts or high variance
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GO term enrichment used a hypergeometric test with Bonferroni correction.↳ Could also: Using a Benjamini-Hochberg FDR correction for GO enrichment — Because GO terms are hierarchically related and tests are non-independent, an FDR-based correction is often preferred over the more conservative Bonferroni approach for controlling the proportion of false discoveries while retaining more true positives
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qRT-PCR validation of 22 genes was described narratively as showing general agreement with RNA-seq, without a stated formal statistical comparison.↳ Could also: Reporting a quantitative concordance measure, such as a Pearson or Spearman correlation coefficient between RNA-seq and qRT-PCR fold-changes, or a paired t-test/Wilcoxon signed-rank test on paired fold-change values — A quantitative correlation or paired test would give a numerical summary of agreement between the two platforms in addition to the qualitative description
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Expression levels (FPKM, fold-change) are reported as single point estimates without measures of dispersion.↳ Could also: Reporting variability (e.g., SD or CI) from biological replicates, or bootstrap/posterior credible intervals from a count-based DE model — Dispersion measures would convey the uncertainty around each expression estimate alongside the point value
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The dose-response and time-course qRT-PCR data (Figure 5) are presented descriptively.↳ Could also: A two-way ANOVA (dose x time) or mixed-effects model with post-hoc comparisons — Such a model would allow formal statistical testing of dose and time effects and their interaction across the multiple treatment combinations shown in Figure 5
What was reproduced
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All ten in-scope pipeline stages completed cleanly (sacct ExitCode 0:0), but no reported number was matched 1:1: 104011 vs 68940 transcripts, 56894 vs 33337 unigenes, N50 1539 vs 1262 bp, 25169 vs 4614 DE features, 774/702 vs 270/107 GO terms. The deviations sit overwhelmingly on the input and method side — the paper's assembly incorporated 314823 ESTs and 17187 NCBI unigenes that were never deposited, its read-cleaning and DE tool are unspecified (forcing a fixed-BCV=0.1 no-replicate exactTest), and annotation here used Swiss-Prot alone (67.14 percent) against the paper's five-database 70.88 percent. This is a shared defect: our substitutions are the proximate cause, but the paper's underspecification is what made them necessary, so the numbers are not derivable from the deposited data without being fabrication-suspect. The qualitative core — a large Pb-responsive, GO-enrichable DE set skewed toward down-regulation — survives, so q7 is limited rather than refuted; KEGG (Tables 2-3) and qRT-PCR were not tested at all.
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