HolistIC: leveraging Hi-C and whole genome shotgun sequencing for double minute chromosome discovery

Matthew Hayes1, Angela Nguyen2, Rahib Islam2

  • 1Department of Physics and Computer Science, Xavier University of Louisiana, New Orleans, LA 70125, USA.

Abstract

Insights

We developed HolistIC, an algorithm that integrates Whole Genome Shotgun sequencing and Hi-C data to accurately detect double minute (DM) chromosomes in cancer genomes. This method improves upon existing techniques by resolving overlapping amplicon coordinates, crucial for cancer treatment.

Area of Science:

  • Genomics
  • Cancer Biology
  • Bioinformatics

Background:

  • Double minute (DM) chromosomes are extrachromosomal DNA elements frequently found in cancer cells.
  • DMs contain amplified oncogenes and drug-resistance genes, posing challenges for cancer therapy.
  • The evolution of DMs leads to overlapping amplicon coordinates, complicating their algorithmic discovery using only Whole Genome Shotgun (WGS) sequencing.

Purpose of the Study:

  • To develop a novel algorithm for accurate prediction of double minute (DM) chromosomes in tumor genomes.
  • To address the limitations of existing methods in handling DMs with overlapping amplicon coordinates.

Main Methods:

  • Integration of Whole Genome Shotgun (WGS) sequencing and Hi-C data.
  • Development and implementation of the HolistIC algorithm.
  • Testing the algorithm on three cancer datasets and one simulated dataset.

Main Results:

  • HolistIC successfully predicted DMs by integrating both WGS and Hi-C data on cancer datasets.
  • The algorithm accurately distinguished DMs with overlapping amplicon coordinates in simulated data.
  • This represents an advancement over methods relying solely on WGS data.

Conclusions:

  • The HolistIC algorithm effectively predicts double minute (DM) chromosomes by combining WGS and Hi-C sequencing data.
  • HolistIC overcomes the challenge of overlapping amplicon coordinates, improving DM detection in cancer genomes.
  • The developed software is publicly available for use in cancer research and treatment development.

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