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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
PubMed
Summary
This summary is machine-generated.

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.

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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.