Evidence map›Paper›PMID 42319209›Full record

ArticleMolecular ecology resources2026

BeeGees: A High-Throughput Protein-Coding DNA Barcode Recovery Pipeline Tailored for Genome Skims of Museum Specimens.

Daniel A J Parsons, Rutger A Vos, Benjamin W Price

Abstract read
In one paragraph

Article in Molecular ecology resources, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

The trial behind it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. 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

3 authors.

Daniel A J ParsonsNatural History Museum, London, UK.ORCID https://orcid.org/0000-0002-5246-0725
Rutger A VosNaturalis Biodiversity Center, Leiden, the Netherlands.ORCID https://orcid.org/0000-0001-9254-7318
Benjamin W PriceNatural History Museum, London, UK.ORCID https://orcid.org/0000-0001-5497-4087

Funding

European Commission 101059492Swiss State Secretariat for Education, Research and Innovation 22.00173Swiss State Secretariat for Education, Research and Innovation 24.00054UK Research and Innovation
6 · The paper itself

Abstract

Natural history collections are unparalleled archives of global biodiversity, yet most specimens remain molecularly uncharacterised due to the technical challenges of historical DNA (hDNA), including degradation, low endogenous content and contamination. Genome skimming offers a scalable alternative to PCR-based barcoding, but existing bioinformatic workflows are not optimised for the heterogeneous, metagenomic nature of museum-derived data. Here we present BeeGees (Barcode Extraction and Evaluation from Genome Skims), a high-performance computing (HPC) integrated, Snakemake-based workflow designed for protein-guided recovery and validation of mitochondrial and plastid barcode genes from degraded short-read genome sequences. BeeGees integrates dual read pre-processing, systematic per-sample parameter sweeps, sequential consensus cleaning to remove contaminant sequences and rigorous structural and taxonomic validation against curated reference databases. We benchmarked BeeGees on 1518 museum specimen-derived genome skims spanning eight phyla. The workflow completed in approximately 120 h (< 5 min per sample) on HPC infrastructure. When excluding sequencing failures (< 1 M reads), validated COI barcodes were recovered for 73.2% of specimens (1050/1435). Barcode recovery success was influenced by endogenous content, preservation quality and parameter choice rather than raw read count alone, highlighting the importance of systematic parameter optimisation. Sequential consensus cleaning eliminated ambiguous bases and reduced chimeric artefacts, proving essential for robust museomic analyses. BeeGees provides a reproducible, scalable framework for high-throughput barcode recovery and biodiversity genomics and reference gap-filling initiatives from natural history collections. The BeeGees pipeline is available at: https://github.com/bge-barcoding/BeeGees/.

Indexed as

Computational BiologyDNA Barcoding, TaxonomicHigh-Throughput Nucleotide SequencingMetagenomicsAnimalsMuseumsWorkflowbarcodingbiodiversity genomicsgenome skimshistorical DNAmuseomics

Identifiers

PMID42319209
PMCPMC13281686

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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.