Chromosome-scale genome sequencing, assembly and annotation of six genomes from subfamily Leishmaniinae.
The main results reproduced: recomputed values matched the published ones within tolerance.
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
REPRODUCED (1:1 on the deposited data products). This Sci Data descriptor prints no per-genome stat table, so ground-truth = the six deposited NCBI chromosome-scale assemblies + their GFF annotations. On «our HPC» (2 SLURM jobs, conda on «infra») I downloaded all 6 genomes and independently recomputed every reported statistic: assembly size, #scaffolds, scaffold N50, #contigs (independent N-gap split), chromosome count (=36) and GC% via seqkit; gene counts via AGAT (the paper's named tool) on the deposited GFF; and BUSCO completeness (euglenozoa_odb10). Result: 36/42 exact + 6/42 within-tol (GC%, <=0.5% of NCBI's rounded value) + 6 BUSCO completeness reproduced (96.9-100%, graded partial as the paper shows BUSCO only as Fig.4). 0 mismatches. AGAT gene counts equal NCBI's annotation gene_counts exactly for all 6 genomes; assembly metrics match NCBI exactly. NOT attempted: full de-novo re-assembly from raw reads and the raw MinION read-N50 (both out of scope / heavy; the deposited products they produce were verified instead). Datasets profiled: assemblies grade A (complete, BUSCO-complete, every metric matched); raw-read deposit grade B (present and a superset of Table 3's runs, but FASTQ content not parsed).
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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
- 2026-06-25
- Rubric version
- not recorded
- Assessed by
- —
- 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: sonnet- ★ Chromosome-scale genomes of six Leishmaniinae species (five L. (Mundinia) species and one Porcisia species) were sequenced, assembled and annotated, providing genome, proteome, transcriptome and GFF outputs for taxa previously lacking public reference genomes resource
- ★ De novo assembly used Nanopore long reads for chromosome scaffolding, followed by mapping of Illumina short reads to correct erroneous base calls method
- ★ Chromosome order and orientation in each assembly was confirmed by synteny analysis (MUMmer) against the closest relative identified in TriTrypDB via BLAST+/wordcloud finding
- Repeat regions were identified, classified and masked using RepeatModeller, TEclass and RepeatMasker method
- ★ Gene prediction and functional annotation were performed with MAKER2 (evidence-based plus ab initio AUGUSTUS rounds) followed by Uniprot/Pfam annotation via BLAST+ and InterProScan method
- Contamination/vector-origin sequences were screened via BLAST+ against UniVec and removed without affecting assembly integrity finding
- ★ Prior to this study only two L. Mundinia genomes and no Porcisia genomes had been sequenced, so these six assemblies substantially expand genomic resources for the subfamily finding
- A reproducible Snakemake analysis pipeline was deposited on GitHub and Zenodo, intended to be adaptable for sequencing further related parasite genomes resource
| Assay | System | Perturbation | Readout | Platform |
|---|---|---|---|---|
| Nanopore long-read sequencing | six Leishmaniinae isolates (L. martiniquensis, L. orientalis, L. enriettii, L. sp. Ghana, L. sp. Namibia, Porcisia hertigi) | none | long reads for de novo chromosome scaffold assembly | MinION FLO-MIN106 flow cells, SQK-LSK109 ligation kit |
| Illumina short-read sequencing | same six Leishmaniinae isolates | none | short reads used to correct base-calling errors in Nanopore assemblies | Illumina HiSeq 4000, HiSeq 2500 and MiSeq (BGI Genomics and Aberystwyth University) |
| De novo genome assembly (Flye) with Illumina consensus correction (minimap2/SAMtools) and gap polishing (Pilon) | six isolate genomic DNA | none | polished chromosome-scale genome assemblies | — |
| BLAST+ contamination/vector screening | polished genome assemblies | none | identification and removal of contaminant/vector-origin sequence at contig ends | UniVec database |
| Synteny/dotplot alignment (MUMmer) | each assembled genome vs its wordcloud-predicted closest TriTrypDB relative | none | confirmation of chromosome order and orientation | TriTrypDB release-47 |
| Repeat element identification and classification | polished genome assemblies | none | stratified repeat content (simple, low complexity, DNA, LTR, LINE, RNA, RC, satellite, SINE, retroposon) | RepeatModeller, TEclass, RepeatMasker |
| Gene prediction and functional annotation (MAKER2, AUGUSTUS, InterProScan/BLAST+) | repeat-masked genome assemblies | none | gene/feature counts, Annotation Edit Distance (AED) scores, Uniprot/Pfam functional assignments | MAKER2 pipeline; L. tarentolae as AUGUSTUS training model |
| gDNA quantification and quality assessment | extracted genomic DNA from all six isolates | none | DNA concentration and Nanopore read N50 as measures of DNA integrity/quality | Qubit dsDNA HS Assay Kit (ThermoFisher); FastQC; pycoQC; MultiQC |
- – Total sequencing output across all six genomes was 139.33 GB of file data, 58.70 GB of bases, from 23.71 GigaReads 139.327 GB file size; 58.698 GB bases; 23.708 GigaReads
- – N50 of Nanopore MinION long reads indicated high molecular weight gDNA across samples 12.07–22.92 kb
- – Chromosome order and orientation of each assembly matched that of its closest TriTrypDB relative
- – Repeat content of the L. martiniquensis genome was predominantly non-repetitive, with simple repeats the largest repeat class 94.4% none; 4.11% simple repeats
- – All detected contaminant sequences occurred only at contig ends and were removed with no effect on assembly integrity
- – AED scores were calculated and plotted for both evidence-based and ab initio annotation rounds across all assemblies
- – Extracted gDNA concentrations were consistent and sufficient for sequencing across all isolates 68.2–120 ng/µL
- – The six deposited genomes represent new genomic resources, including the first Porcisia genome and additional L. Mundinia genomes beyond the two previously available
- count 6 genomes (number of Leishmaniinae genomes assembled and annotated in this study)
- other 23.708 GigaReads / 58.698 GigaBases / 139.327 Gigabytes (grand total sequencing reads, bases and file size across all six samples)
- other 68.2–120 ng/µL (range of extracted genomic DNA concentrations across isolates)
- other 12.07–22.92 kb (range of N50 values for Nanopore MinION long reads across isolates)
- other none 94.4%, simple 4.11%, low complexity 0.655%, DNA 0.419%, unknown 0.161%, LTR 0.110%, LINE 0.052%, RNA 0.027%, RC 0.019%, satellite 0.010%, retroposon 0.005%, SINE 0.004% (repeat class proportions in the L. martiniquensis genome)
- count 18 species (number of Leishmania species known to infect humans)
- count 98 species (sandfly species suspected or confirmed as Leishmania vectors)
- count 58 genomes (publicly available Leishmania genomes prior to this study)
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 is a genome data-descriptor paper reporting chromosome-scale de novo assembly and annotation of six Leishmaniinae genomes (one specimen per species), combining Nanopore long-read scaffolding with Illumina short-read correction. It does not employ inferential statistical hypothesis testing; instead it reports assembly/annotation quality via descriptive metrics (read/base/file-size totals, DNA concentration and N50 ranges, BUSCO completeness, MUMmer synteny/dotplots, and Annotation Edit Distance (AED) score distributions plotted as cumulative curves). Results are presented as tables, bar/pie charts, dotplots and cumulative line plots rather than as formal statistical comparisons between groups.
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DNA concentration and Nanopore read N50 are each summarized only as a range (min-max) across the six samples↳ Could also: Reporting the median or mean alongside the range, or as an IQR — A range alone conveys spread but not central tendency; adding a median/mean gives readers a quick sense of the 'typical' value alongside the extremes, which is often preferred when the underlying number of samples is small
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Assembly completeness was assessed with BUSCO as a single completeness benchmark per genome↳ Could also: Complementing BUSCO with additional contiguity/accuracy metrics (e.g., QUAST-style N50/L50, k-mer-based accuracy such as Merqury) reported together in one table — Combining several standard, complementary QC metrics can give a fuller picture of assembly quality alongside single-copy orthologue completeness, since each metric captures a different aspect (completeness vs contiguity vs base-level accuracy)
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Annotation Edit Distance (AED) scores for the evidence-based and ab initio annotation rounds are shown as cumulative percentage line plots (Fig. 5) without an accompanying summary statistic↳ Could also: Reporting summary values (e.g., median AED, or proportion of genes below a chosen AED threshold) for each round alongside the cumulative plot — A summary statistic can make it easier to compare annotation rounds numerically at a glance, complementing the visual cumulative-distribution comparison already shown
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Closest-relative genome selection from TriTrypDB was guided by a wordcloud visualization of BLAST+ hit frequencies↳ Could also: Supplementing this with a quantitative similarity metric such as average nucleotide identity (ANI) or a phylogenetic distance measure — A numeric similarity score can provide a directly comparable value alongside the qualitative wordcloud summary, which some readers may find useful for reproducing or extending the relatedness assessment
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Repeat element content is presented as proportions in a single pie chart per genome (Fig. 4), without a measure of uncertainty↳ Could also: Reporting repeat-class proportions with a note on assembly-length dependence, or comparing across genomes in one combined table — Since repeat proportions are computed from a single assembly per species, presenting them side-by-side across the six genomes in a shared table could make cross-species comparison more direct than six separate pie charts
What was reproduced
The exact results taken into scope, with each reported value next to the value our attempt produced.
Scope — pmid-34489462
Paper: Almutairi et al. 2021, Scientific Data. "Chromosome-scale genome sequencing, assembly and annotation of six genomes from subfamily Leishmaniinae." This is a data descriptor — it presents six new genomes, not hypothesis tests.
Key fact that shapes scope
The paper text/tables report almost no per-genome quantitative results:
- Table 1 = sample/BioProject IDs; Table 2 = tool list; Table 3 = read/base counts.
- The only in-text numbers are read counts (Table 3) and a MinION read N50 range (12.07–22.92 kb). BUSCO completeness and MAKER2 AED appear only as figures (Figs 4–5), with no printed values. The quantitative ground-truth is therefore the six deposited NCBI Assembly records (GCA_017916305/325/335.1, GCA_017918215/225/235.1 = the paper's Data Records, refs 99–104) and their Lancaster-submitted GFF annotations.
In scope (pipeline-derived; attempted)
For each of the 6 genomes, recompute the deposited assembly + annotation statistics and check internal consistency with the NCBI metadata:
| Result | Pipeline / tool | How reproduced |
|---|---|---|
| Assembly total length, #scaffolds, scaffold N50, GC% | Flye→Pilon→RaGOO (assembly) | seqkit stats -a on deposited genome FASTA |
| #contigs | (same; gaps = N-runs) | independent N-gap split (python) |
| Chromosome count (=36, "chromosome-scale") | RaGOO scaffolding | count role=assembled-molecule in seq report |
| Annotated gene count | AGAT (the paper's named code) + MAKER2 | agat_sp_statistics.pl on deposited GFF |
| Annotation completeness | BUSCO | BUSCO 5.7.1, euglenozoa_odb10, protein mode |
AGAT is the exact tool the Methods name for "the number of genes and other features", so running it on the deposited GFF reproduces the authors' stated annotation-stats step (P16: applying the named third-party tool to the paper's own data is a valid reproduction).
Out of scope (not attempted, with reason)
- De-novo re-assembly + re-annotation from raw reads (full Flye→minimap2/Pilon→ funannotate→RaGOO→RepeatMasker→MAKER2 Snakemake pipeline). Enormous compute; the paper ships the pipeline and the outputs, and the descriptor's reproducible claim is the deposited data products, which we verify directly. A full re-run would be a separate, much larger effort and would not change the reported statistics.
- MinION read N50 (12.07–22.92 kb) — needs the raw Nanopore FASTQ; raw reads not downloaded (heavy, and the assemblies derived from them were verified instead).
- Synteny / MUMmer plots, wordcloud closest-relative — figure-only, qualitative.
- Wet-lab steps (DNA extraction, sequencing) — inherently not computational.
Ground-truth caveat (auditor note)
Because the paper prints no stat table, "reported_value" in claims.tsv = the NCBI deposited metadata. NCBI's own assembly stats and annotation gene_counts are computed from the same deposited FASTA/GFF we parse, so exact agreement primarily confirms (a) the deposit is internally consistent and (b) our independent re-derivation (seqkit, custom gap-split, AGAT, BUSCO) reproduces those official numbers. It does not re-derive the assemblies from reads. Graded provisionally; a human signs off.
Assessments & scoring basis
Each contributor’s verdict, the per-question basis, and the auditable, itemised worksheet behind it.
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