Skip to content
DraconiticResearch
Search Sources API
203,234 studies31 sourcesUpdated 47 min ago
PreprintCC BYbioRxiv

PIGSTI: a modular, reproducible pipeline for detecting species identity, pathogens, and microbes from animal palaeogenomic data

23 more authors
  1. 1UCD School of Agriculture and Food Science, University College Dublin, Belfield, Ireland

Abstract

Ancient genomics has enabled discovery of diverse pathogens across various time periods, host species, and material types. However, existing palaeogenomic pipelines predominantly focus on screening data from human hosts, or do not incorporate microbial screening methodologies. We present PIGSTI (Pathogen anImal Genome Sequence ToolkIt), a bioinformatic pipeline specifically designed for both the initial screening and subsequent detection of pathogens in shotgun sequencing data from ancient animal remains. PIGSTI's integrated Snakemake workflow performs both host detection, genome mapping and pathogen identification, generating outputs suitable for population genetics and phylogenetic analyses. Testing on 952 newly sequenced and publicly available animal palaeogenomic datasets, we identified ~15 ancient zoonotic and animal pathogens with high confidence, including the first documented case of Rickettsia felis and Leptospira borgpetersenii in an ancient animal. Our results demonstrate PIGSTI's utility for screening pathogen diversity in ancient animal hosts and reconstructing historical host-pathogen relationships.

Related

  1. A Reproducible MRI‐Based Pipeline for Longitudinal Tracking of Laser‐Assisted Bioprinted Cells in Three‐Dimensional Constructs
    Mina Medojević, Charles Handschin, Ayako Washio +5
    NMR in BiomedicinePeer-reviewedPublisher termsFull textSystems & synthetic biologyMaterials & polymersHAL
  2. A Reproducible Cortical Model of Focal Epileptiform Activity with a Multi-Biomarker Analysis Pipeline
    C. Lopez-Cabezon, T. A. Gener, A. Polo-Rodriguez +1
    bioRxivPreprintCC BY-NC-NDFull textNeurosciencebioRxiv
  3. EXCON: a scalable, reproducible Nextflow pipeline for CAFE-based gene EXpansion and CONtraction analysis
    C. D. R. Wyatt, F. Duarte, A. Cerqueira De Araujo +3
    bioRxivPreprintCC BYFull textEvolutionary biologybioRxiv
  4. BCell-Epitope-Prediction: A local, reproducible pipeline for multi-epitope vaccine design: integration and structural validation against a panel of PDB antigen-antibody complexes
    E. L. E. Sierra Vera, B. Pueche Granados, C. E. Gomez +1
    bioRxivPreprintCC BY-NCFull textBioinformatics & computational biologybioRxiv
  5. multiomeR: a pipeline for reproducible analysis of large-scale single-nucleus Epi Multiome datasets
    T. G. Koefoed, S. He, M. Thodberg +6
    bioRxivPreprintCC BYFull textBioinformatics & computational biologybioRxiv
BibTeX
@misc{lhote2026pigsti,
  title = {{PIGSTI: a modular, reproducible pipeline for detecting species identity, pathogens, and microbes from animal palaeogenomic data}},
  author = {L. L'Hote and C. Butt and A. Halpin and L. Sacristan and V. Mattiangeli and P. Bangsgaard and L. Yeomans and M. Zeder and M. Mashkour and H. Davoudi and S. Hansen and D. Decruyenaere and M. Kennedy and A. Vautrin and A. Begmatov and A. B. Belinskiy and A. Berdimuradov and G. Bogomolov and J. Bruno and A. Kalmykov and J. McMahon and J. Mirzaakhmedov and S. Pollock and R. Rante and S. Reinhold and T. Richter and A. Sandiboev and E. Sauer and L. Strolin and H. Teramura and H. Thomas and J. A. M. Erven and S. Nakagome and D. G. Bradley and K. G. Daly},
  howpublished = {bioRxiv},
  year = {2026},
  month = sep,
  doi = {10.64898/2026.09.01.748539},
  url = {https://www.biorxiv.org/content/10.64898/2026.09.01.748539v1},
  note = {CC BY},
}
RIS
TY  - UNPB
TI  - PIGSTI: a modular, reproducible pipeline for detecting species identity, pathogens, and microbes from animal palaeogenomic data
AU  - L. L'Hote
AU  - C. Butt
AU  - A. Halpin
AU  - L. Sacristan
AU  - V. Mattiangeli
AU  - P. Bangsgaard
AU  - L. Yeomans
AU  - M. Zeder
AU  - M. Mashkour
AU  - H. Davoudi
AU  - S. Hansen
AU  - D. Decruyenaere
AU  - M. Kennedy
AU  - A. Vautrin
AU  - A. Begmatov
AU  - A. B. Belinskiy
AU  - A. Berdimuradov
AU  - G. Bogomolov
AU  - J. Bruno
AU  - A. Kalmykov
AU  - J. McMahon
AU  - J. Mirzaakhmedov
AU  - S. Pollock
AU  - R. Rante
AU  - S. Reinhold
AU  - T. Richter
AU  - A. Sandiboev
AU  - E. Sauer
AU  - L. Strolin
AU  - H. Teramura
AU  - H. Thomas
AU  - J. A. M. Erven
AU  - S. Nakagome
AU  - D. G. Bradley
AU  - K. G. Daly
PY  - 2026
DA  - 2026/09/01
PB  - bioRxiv
DO  - 10.64898/2026.09.01.748539
UR  - https://www.biorxiv.org/content/10.64898/2026.09.01.748539v1
AB  - Ancient genomics has enabled discovery of diverse pathogens across various time periods, host species, and material types. However, existing palaeogenomic pipelines predominantly focus on screening data from human hosts, or do not incorporate microbial screening methodologies. We present PIGSTI (Pathogen anImal Genome Sequence ToolkIt), a bioinformatic pipeline specifically designed for both the initial screening and subsequent detection of pathogens in shotgun sequencing data from ancient animal remains. PIGSTI's integrated Snakemake workflow performs both host detection, genome mapping and pathogen identification, generating outputs suitable for population genetics and phylogenetic analyses. Testing on 952 newly sequenced and publicly available animal palaeogenomic datasets, we identified ~15 ancient zoonotic and animal pathogens with high confidence, including the first documented case of Rickettsia felis and Leptospira borgpetersenii in an ancient animal. Our results demonstrate PIGSTI's utility for screening pathogen diversity in ancient animal hosts and reconstructing historical host-pathogen relationships.
ER  -