PanSVR: Pan-Genome Augmented Short Read Realignment for Sensitive Detection of Structural Variations

Area of Science:

• Genomics
• Bioinformatics
• Computational Biology

Background:

• Accurate discovery of structure variations (SVs) is crucial for genomics studies.
• High-throughput sequencing generates short reads, posing challenges for precise SV detection with current tools.
• Existing SV callers struggle with reference bias and incompleteness inherent in single-reference genomes.

Purpose of the Study:

• To develop an effective computational approach leveraging pan-genomes for improved SV calling.
• To address the limitations of short read alignment in SV detection.
• To enhance the sensitivity and accuracy of SV detection, particularly in challenging genomic regions.

Main Methods:

• Proposed PanSVR (Pan-genome augmented Structure Variation calling tool with read Re-alignment), a novel pan-genome-based SV calling approach.
• Implemented tailored methods for precise re-alignment of SV-spanning reads against a comprehensive pan-genome reference.
• Utilized organized pan-genome references rich in known SVs to facilitate SV signature generation.

Main Results:

• PanSVR significantly improves the quality of short read alignments.
• Generated clear and homogenous SV signatures, aiding in SV calling.
• Demonstrated substantial improvements in SV calling sensitivity compared to state-of-the-art methods on real sequencing data.

Conclusions:

• PanSVR effectively utilizes pan-genome references to overcome short read alignment bottlenecks.
• The tool shows particular strength in detecting SVs in repeat-rich regions and novel insertions.
• PanSVR represents a significant advancement in SV discovery from high-throughput sequencing data.