Hunting for microsatellite instability in long-read data with Owl

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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Publication Details

Journal
PLoS Computational Biology
Published
2026-09-02
DOI
https://doi.org/10.1371/journal.pcbi.1014423
Citations
2
Primary Topic
Genetic factors in colorectal cancer
Type
article
Field-Weighted Citation Impact
12.03

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article

Hunting for microsatellite instability in long-read data with Owl

Michael A. Eberle, Everett T Fan, Elizabeth R. Lawlor, Kie Kyon Huang et al.
2 citations
PLoS Computational Biology
Genetic factors in colorectal cancer
12.03
article

Hunting for microsatellite instability in long-read data with Owl

Michael A. Eberle, Everett T Fan, Elizabeth R. Lawlor, Kie Kyon Huang, Kobe Ikegami, Guilherme De Sena Brandine, Midhat S. Farooqi, Byunggil Yoo, Zev Kronenberg, Jocelyne Bruand, Tomi Pastinen, Emily O’Donnell, Lisa Lansdon, William J. Rowell, Khi Pin Chua, Jay Sarthy, Scott N. Furlan, Shruti Bhise, Mark J. P. Chaisson, Mark Mendoza, Everett Fan, Egor Dolzhenko
article en
2 citations

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.

PLoS Computational BiologyVol. 22(9)
University of Southern California (US), University of Washington (US), California Southern University (US), Fred Hutch Cancer Center (US), Duke-NUS Medical School (SG), Precision Research (United States) (US), Genome Institute of Singapore (SG), Pacific Biosciences (United States) (US), University of Missouri–Kansas City (US)
Seattle Children's Research Institute, Children’s Hospital of Wisconsin Research Institute, National Research Foundation, National Research Foundation Singapore, Medical Research Council, National Medical Research Council, National Human Genome Research Institute
Openalex Percentile: Top 2%
Genetic factors in colorectal cancer
12.03
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