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Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
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Detection and visualization of complex structural variants from long reads.

Zachary Stephens1, Chen Wang2, Ravishankar K Iyer1

  • 1Coordinated Science Lab, University of Illinois at Urbana-Champaign, Urbana, IL, USA.

BMC Bioinformatics
|December 23, 2018
PubMed
Summary

Detecting complex structural variations (SVs) in the human genome is crucial for personalized medicine. CORGi, a new method using long-read sequencing, accurately identifies and visualizes complex genomic rearrangements, improving SV detection sensitivity.

Keywords:
Complex rearrangementLong readStructural variation

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Area of Science:

  • Genomics
  • Bioinformatics
  • Molecular Biology

Background:

  • Understanding human genome structural variation (SVs) is vital for personalized medicine, impacting cancer research, drug metabolism, and disease etiology.
  • Short-read sequencing technologies face limitations in accurately detecting complex SVs, especially those with multiple overlapping or nested rearrangements.
  • Longer reads from platforms like Pacific Biosciences offer improved resolution for identifying multiple breakpoints, enhancing confidence in SV detection.

Purpose of the Study:

  • To present CORGi (COmplex Rearrangement detection with Graph-search), a novel method for detecting and visualizing complex local genomic rearrangements.
  • To leverage long-read sequencing capabilities for unraveling intricate SVs that are challenging to resolve with existing methods.

Main Methods:

  • CORGi utilizes long reads that span multiple breakpoints to analyze complex structural variants.
  • The method employs graph-search algorithms on pairwise alignments to identify and characterize rearrangements.
  • Validation was performed using simulated long reads and real sequencing data from two distinct long-read technologies.

Main Results:

  • CORGi accurately identifies breakpoints in synthetic data and detects/plots SVs from NA12878 germline data with 88.4% concordance.
  • The method reveals complexity patterns in SVs consistent with known DNA replication and formation mechanisms.
  • CORGi automatically labels complex SVs using intuitive reference transformation combinations.

Conclusions:

  • CORGi is an effective method for analyzing genomic regions with suspected local rearrangements using long-read sequencing.
  • The tool generates labels and visualizations for local SVs of any complexity through pairwise alignments and graph search.