Severus detects somatic structural variation and complex rearrangements in cancer genomes using long-read sequencing.

Document Type

Article

Publication Date

2-2026

Identifier

DOI: 10.1038/s41587-025-02618-8; PMCID: PMC12483193

Abstract

For the detection of somatic structural variation (SV) in cancer genomes, long-read sequencing is advantageous over short-read sequencing with respect to mappability and variant phasing. However, most current long-read SV detection methods are not developed for the analysis of tumor genomes characterized by complex rearrangements and heterogeneity. Here, we present Severus, a breakpoint graph-based algorithm for somatic SV calling from long-read cancer sequencing. Severus works with matching normal samples, supports unbalanced cancer karyotypes, can characterize complex multibreak SV patterns and produces haplotype-specific calls. On a comprehensive multitechnology cell line panel, Severus consistently outperforms other long-read and short-read methods in terms of SV detection F1 score (harmonic mean of the precision and recall). We also illustrate that compared to long-read methods, short-read sequencing systematically misses certain classes of somatic SVs, such as insertions or clustered rearrangements. We apply Severus to several clinical cases of pediatric leukemia/lymphoma, revealing clinically relevant cryptic rearrangements missed by standard genomic panels.

Journal Title

Nature biotechnology

Volume

44

Issue

2

First Page

247

Last Page

257

MeSH Keywords

Humans; Neoplasms; Algorithms; Genome, Human; High-Throughput Nucleotide Sequencing; Gene Rearrangement; Sequence Analysis, DNA; Genomic Structural Variation; Software; Cell Line, Tumor

PubMed ID

40185952

Keywords

Neoplasms; Algorithms; Human Genome; High-Throughput Nucleotide Sequencing; Gene Rearrangement; DNA Sequence Analysis; Genomic Structural Variation; Software; Tumor Cell Line

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