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INSurVeyor: improving insertion calling from short read sequencing data
Ramesh Rajaby1,2, Dong-Xu Liu3,4, Chun Hang Au1
1Hong Kong Genome Institute, Hong Kong Science Park, Shatin, Hong Kong, China.
Nature Communications
|June 5, 2023
Summary
INSurVeyor significantly improves the detection of DNA insertions, a common structural variation. This new method is more sensitive than existing tools and enables the creation of more complete genomic insertion catalogs.
Area of Science:
- Genomics
- Bioinformatics
- Molecular Biology
Background:
- Insertions, defined as additions of 50+ nucleotides to DNA, are key structural variations.
- Existing methods for detecting insertions from next-generation sequencing (NGS) short reads often lack sensitivity.
Purpose of the Study:
- To introduce INSurVeyor, a novel method for sensitive and precise detection of insertions from NGS paired-end data.
- To generate comprehensive insertion catalogs for human and Arabidopsis thaliana genomes using INSurVeyor.
Main Methods:
- Development and application of INSurVeyor, a new computational tool for insertion detection.
- Validation using benchmark datasets from human and non-human organisms.
- Cataloging insertions in 1001 Genomes Project (Arabidopsis thaliana) and 1000 Genomes Project (human) datasets.
Main Results:
- INSurVeyor demonstrates superior sensitivity and precision compared to individual and combined existing callers.
- Its performance approaches that of long-read callers for most insertion types.
- Generated insertion catalogs are more complete and accurate than current resources, identifying missed insertions.
Conclusions:
- INSurVeyor represents a significant advancement in insertion detection from NGS data.
- The generated genomic catalogs enhance our understanding of structural variations in humans and plants.
- The method addresses limitations in current insertion detection, improving genomic resource completeness.
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