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Peer-reviewedCC BY 4.0PLOS Computational Biology

Hunting for microsatellite instability in long-read data with Owl

  • Zev Kronenberg1
  • Byunggil Yoo2
  • Khi Pin Chua3
  • Mark J. P. Chaisson4
  • Lisa Lansdon5
  • William J. Rowell6
  • Guilherme de Sena Brandine7
  • Jocelyne Bruand8
  • Egor Dolzhenko9
  • Kobe Ikegami10
  • Jay Sarthy
  • Kie Kyon Huang
10 more authors
  • Patrick Tan
  • Shruti Bhise
  • Everett Fan
  • Mark Mendoza
  • Emily O’Donnell
  • Tomi Pastinen
  • Elizabeth R. Lawlor
  • Scott N. Furlan
  • Midhat S. Farooqi
  • Michael A. Eberle
10 affiliations
  1. 1PacBio, Menlo Park, California, United States of America
  2. 2Children’s Mercy Hospital, University of Missouri-Kansas City School of Medicine, Kansas City, Missouri, United States of America
  3. 3University of Southern California, Los Angeles, California, United States of America
  4. 4Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, California, United States of America
  5. 5Fred Hutch Cancer Center, Seattle, Washington, United States of America
  6. 6Duke-NUS Medical School, Singapore, Singapore
  7. 7Genome Institute of Singapore, Singapore, Singapore
  8. 8Precision Health Research Singapore, Singapore, Singapore
  9. 9Ben Towne Center for Childhood Cancer and Blood Disorders Research, Seattle Children’s Research Institute, Seattle, Washington, United States of America
  10. 10Department of Pediatrics, University of Washington, Seattle, Washington, United States of America
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Abstract

Microsatellite instability (MSI) is a key biomarker of mismatch repair deficiency and response to immunotherapy, yet most existing genomic detection methods are optimized for short-read sequencing and rely on a panel of homopolymer markers, limiting the ability to characterize genome-wide and motif-specific patterns of instability. Here we present Owl, a bioinformatic tool for quantifying MSI from long-read (PacBio) genomic data. Owl leverages a genome-wide marker set of more than 140,000 microsatellite repeats ranging from 1–6 bp in length to measure MSI across a phased genome. Using a wrap-around alignment algorithm, Owl constructs repeat-length distributions at each marker site and flags somatic instability using the coefficient of variation. We applied Owl to screen for markers with stable coverage, phasing, and baseline variation across 131 diverse genomes from the Human Pangenome Reference Consortium, where Owl scores ranged from 1.4% to 5.4% of markers exceeding the instability threshold. When applied to cancer cell lines and one diffuse astrocytoma tumor-normal pair, Owl identified six MSI genomes with 10–27% unstable markers and showed close concordance with an Illumina DRAGEN MSI assay for the astrocytoma sample. Motif-level analyses revealed shared enrichment of short homopolymer and dinucleotide (A- and AT-rich) repeats across MSI cancers. Owl is implemented in Rust and integrated into the PacBio HiFi Somatic workflow, providing a scalable framework for MSI analysis from long-read sequencing focused on repeat instability specifically in tumor samples.

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Cite

BibTeXRIS
BibTeX
@article{kronenberg2026hunting,
  title = {{Hunting for microsatellite instability in long-read data with Owl}},
  author = {Zev Kronenberg and Byunggil Yoo and Khi Pin Chua and Mark J. P. Chaisson and Lisa Lansdon and William J. Rowell and Guilherme de Sena Brandine and Jocelyne Bruand and Egor Dolzhenko and Kobe Ikegami and Jay Sarthy and Kie Kyon Huang and Patrick Tan and Shruti Bhise and Everett Fan and Mark Mendoza and Emily O’Donnell and Tomi Pastinen and Elizabeth R. Lawlor and Scott N. Furlan and Midhat S. Farooqi and Michael A. Eberle},
  journal = {PLOS Computational Biology},
  year = {2026},
  month = sep,
  doi = {10.1371/journal.pcbi.1014423},
  url = {https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1014423},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - Hunting for microsatellite instability in long-read data with Owl
AU  - Zev Kronenberg
AU  - Byunggil Yoo
AU  - Khi Pin Chua
AU  - Mark J. P. Chaisson
AU  - Lisa Lansdon
AU  - William J. Rowell
AU  - Guilherme de Sena Brandine
AU  - Jocelyne Bruand
AU  - Egor Dolzhenko
AU  - Kobe Ikegami
AU  - Jay Sarthy
AU  - Kie Kyon Huang
AU  - Patrick Tan
AU  - Shruti Bhise
AU  - Everett Fan
AU  - Mark Mendoza
AU  - Emily O’Donnell
AU  - Tomi Pastinen
AU  - Elizabeth R. Lawlor
AU  - Scott N. Furlan
AU  - Midhat S. Farooqi
AU  - Michael A. Eberle
PY  - 2026
DA  - 2026/09/02
JO  - PLOS Computational Biology
DO  - 10.1371/journal.pcbi.1014423
UR  - https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1014423
AB  - Microsatellite instability (MSI) is a key biomarker of mismatch repair deficiency and response to immunotherapy, yet most existing genomic detection methods are optimized for short-read sequencing and rely on a panel of homopolymer markers, limiting the ability to characterize genome-wide and motif-specific patterns of instability. Here we present Owl, a bioinformatic tool for quantifying MSI from long-read (PacBio) genomic data. Owl leverages a genome-wide marker set of more than 140,000 microsatellite repeats ranging from 1–6 bp in length to measure MSI across a phased genome. Using a wrap-around alignment algorithm, Owl constructs repeat-length distributions at each marker site and flags somatic instability using the coefficient of variation. We applied Owl to screen for markers with stable coverage, phasing, and baseline variation across 131 diverse genomes from the Human Pangenome Reference Consortium, where Owl scores ranged from 1.4% to 5.4% of markers exceeding the instability threshold. When applied to cancer cell lines and one diffuse astrocytoma tumor-normal pair, Owl identified six MSI genomes with 10–27% unstable markers and showed close concordance with an Illumina DRAGEN MSI assay for the astrocytoma sample. Motif-level analyses revealed shared enrichment of short homopolymer and dinucleotide (A- and AT-rich) repeats across MSI cancers. Owl is implemented in Rust and integrated into the PacBio HiFi Somatic workflow, providing a scalable framework for MSI analysis from long-read sequencing focused on repeat instability specifically in tumor samples.
SN  - 1553-7358
ER  -