Evidence map›Paper›PMID 39465511›Full record

ArticleMolecular ecology resources2025

A Snakemake Toolkit for the Batch Assembly, Annotation and Phylogenetic Analysis of Mitochondrial Genomes and Ribosomal Genes From Genome Skims of Museum Collections.

Oliver W White, Andie Hall, Ben W Price, Suzanne T Williams, Matthew D Clark

Abstract read
In one paragraph

Article in Molecular ecology resources, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Unveiling the Genomic Landscape of Yan Goose (Animals : an open access journal from MDPI · 2026
    Article
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Oliver W WhiteThe Natural History Museum, London, UK.ORCID https://orcid.org/0000-0001-6444-0310
Andie HallThe Natural History Museum, London, UK.ORCID https://orcid.org/0000-0001-5546-7255
Ben W PriceThe Natural History Museum, London, UK.ORCID https://orcid.org/0000-0001-5497-4087
Suzanne T WilliamsThe Natural History Museum, London, UK.ORCID https://orcid.org/0000-0003-2995-5823
Matthew D ClarkThe Natural History Museum, London, UK.ORCID https://orcid.org/0000-0002-8049-5423

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Low coverage 'genome-skims' are often used to assemble organelle genomes and ribosomal gene sequences for cost-effective phylogenetic and barcoding studies. Natural history collections hold invaluable biological information, yet poor preservation resulting in degraded DNA often hinders polymerase chain reaction-based analyses. However, it is possible to generate libraries and sequence the short fragments typical of degraded DNA to generate genome-skims from museum collections. Here we introduce a snakemake toolkit comprised of three pipelines skim2mito, skim2rrna and gene2phylo, designed to unlock the genomic potential of historical museum specimens using genome skimming. Specifically, skim2mito and skim2rrna perform the batch assembly, annotation and phylogenetic analysis of mitochondrial genomes and nuclear ribosomal genes, respectively, from low-coverage genome skims. The third pipeline gene2phylo takes a set of gene alignments and performs phylogenetic analysis of individual genes, partitioned analysis of concatenated alignments and a phylogenetic analysis based on gene trees. We benchmark our pipelines with simulated data, followed by testing with a novel genome skimming dataset from both recent and historical solariellid gastropod samples. We show that the toolkit can recover mitochondrial and ribosomal genes from poorly preserved museum specimens of the gastropod family Solariellidae, and the phylogenetic analysis is consistent with our current understanding of taxonomic relationships. The generation of bioinformatic pipelines that facilitate processing large quantities of sequence data from the vast repository of specimens held in natural history museum collections will greatly aid species discovery and exploration of biodiversity over time, ultimately aiding conservation efforts in the face of a changing planet.

Indexed as

Genome, MitochondrialMuseumsPhylogenyAnimalsComputational BiologyGastropodaMolecular Sequence AnnotationSequence Analysis, DNAassemblybioinformaticsDNA barcodegenome skimiBOLmuseomicsphylogeneticssnakemake

Identifiers

PMID39465511
PMCPMC11646300

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.