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A Differential Depth Sequencing Method, SPRE-Seq, for Enhancing Targeted Region Coverage in Hybridization

Hui-Juan Chen1,2, Bing Wang3, Yi-Ran Zhang4

  • 1Beijing CapitalBio MedLab Co., Ltd Beijing P.R. China.

Engineering in Life Sciences
|October 27, 2025
PubMed
Summary
This summary is machine-generated.

SPRE-Seq, a novel differential sequencing method, optimizes sequencing depth for targeted regions in next-generation sequencing (NGS). This approach effectively reduces data volume by half while maintaining high accuracy for homologous recombination deficiency (HRD) analysis.

Keywords:
hybridization capture‐based next‐generation sequencingoligonucleotide probessequencing depth

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Area of Science:

  • Genomics and Bioinformatics
  • Molecular Diagnostics

Background:

  • Sequencing depth is critical for accurate variant detection in next-generation sequencing (NGS).
  • Capture-based targeted NGS faces limitations balancing sequencing breadth and depth.
  • Homologous recombination deficiency (HRD) analysis requires precise sequencing of specific genomic regions.

Purpose of the Study:

  • To introduce SPRE-Seq, a differential depth sequencing method for targeted NGS panels.
  • To evaluate SPRE-Seq's performance in homologous recombination repair (HRR) and HRD region analysis.
  • To assess SPRE-Seq's efficiency in reducing sequencing data volume without compromising accuracy.

Main Methods:

  • Developed and implemented SPRE-Seq, a method enabling variable sequencing depths across targeted regions.
  • Validated SPRE-Seq using a custom-designed HRD assay with HRD reference standards and clinical samples.
  • Compared SPRE-Seq performance against regular capture methods in terms of data volume and accuracy.

Main Results:

  • SPRE-Seq achieved required sequencing depths for HRR and HRD regions in reference standards using 50% less data (6 GB vs. 12 GB).
  • 100% concordance was observed between SPRE-Seq results and expected outcomes for HRR genes and HRD status.
  • Clinical sample analysis showed significantly higher effective depth in HRR regions with SPRE-Seq at 6 GB compared to regular capture at 12 GB, with no significant difference at 6 GB.

Conclusions:

  • SPRE-Seq is a feasible and reliable method for determining HRD status and HRR somatic variants.
  • The approach significantly reduces sequencing data volume while ensuring adequate sequencing depth.
  • SPRE-Seq offers a cost-effective solution for targeted NGS applications requiring precise depth control.