Luo, Can; Zhou, Zimeng Jamie; Liu, Yichen Henry; Zhou, Xin Maizie. (2025). FocalSV enables target region–based structural variant assembly and refinement using single-molecule long-read sequencing data. Genome Research, 35(10), 2252-2272. https://doi.org/10.1101/gr.280282.124
Structural variants (SVs)—large changes in the structure of DNA, such as deletions, insertions, or rearrangements—are important contributors to human genetic diversity and can influence health and disease. Detecting these variants accurately is essential for progress in precision medicine, which aims to tailor treatments to individual genetic profiles.
Although long-read DNA sequencing technologies have improved our ability to study SVs, pinpointing their exact breakpoints (the locations where DNA is altered) and fully identifying their sequences remains difficult. Existing methods have limitations: tools that rely on aligning sequencing reads to a reference genome often miss or misplace breakpoints, while methods that reconstruct entire genomes from scratch are accurate but require heavy computing power, making them impractical for focused, region-specific studies.
To overcome these challenges, researchers developed FocalSV, a new framework for detecting structural variants in specific areas of the genome. FocalSV combines two key approaches—assembly-based and alignment-based analyses—to achieve both precision and efficiency. It allows users to define target regions of interest and can automatically expand these regions when potential variants are detected, ensuring more complete analysis.
Tests of FocalSV on ten germline (inherited) and two paired normal-tumor cancer data sets showed that it outperforms existing tools in both accuracy and computational efficiency, providing a more effective way to detect complex DNA variations that matter for human health.
