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Blackbird: structural variant detection using synthetic and low-coverage long-reads.

Dmitry Meleshko1,2, Rui Yang1, Salil Maharjan2

  • 1Tri-Institutional PhD Program in Computational Biology and Medicine, Weill Cornell Medical College, 10021, New York, USA.

Biorxiv : the Preprint Server for Biology
|November 28, 2024
PubMed
Summary

Blackbird, a new algorithm, improves structural variant (SV) detection using synthetic long reads (SLR) and low-coverage long reads. This hybrid approach achieves high accuracy at reduced costs, outperforming existing methods at lower coverages.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Short-read sequencing struggles with medium-range structural variants (SVs) in the human genome.
  • Long-read sequencing offers better SV detection but incurs high costs and DNA input requirements.
  • Current long-read SV callers perform poorly below 10× coverage, limiting cost reduction.

Purpose of the Study:

  • To develop a hybrid algorithm, Blackbird, for improved SV detection and assembly using synthetic long reads (SLR) and low-coverage long reads.
  • To overcome the limitations of existing SV detection methods regarding cost and coverage requirements.
  • To enable accurate detection of smaller structural variations (<50 kbp) using SLR technology.

Main Methods:

  • Proposed a novel hybrid algorithm, Blackbird, integrating alignment and local assembly.
  • Utilized a sliding window approach and barcode information from SLR for segment assembly.
  • Employed long reads for enhanced gap closing and contig assembly, avoiding whole-genome assembly.
  • Evaluated Blackbird on simulated and real human genome datasets, including the HG002 GIAB benchmark.

Main Results:

  • Blackbird demonstrated comparable SV detection results to state-of-the-art long-read tools in hybrid mode.
  • Achieved high F1 scores (0.835 for deletions, 0.808 for insertions) at only 5× long-read coverage.
  • Performance was similar to PBSV (0.856, 0.812) and Sniffles2 (0.839, 0.804) which require 10× coverage.
  • Successfully utilized SLR and low-coverage long reads for accurate SV detection and assembly.

Conclusions:

  • Blackbird offers a cost-effective and efficient solution for structural variant detection.
  • The hybrid approach significantly improves SV detection accuracy at reduced sequencing coverage.
  • Blackbird provides a viable alternative for high-accuracy SV detection in genomics research.