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Related Experiment Video

Updated: Jul 9, 2026

gDNA Enrichment by a Transposase-based Technology for NGS Analysis of the Whole Sequence of BRCA1, BRCA2, and 9 Genes Involved in DNA Damage Repair

gDNA Enrichment by a Transposase-based Technology for NGS Analysis of the Whole Sequence of BRCA1, BRCA2, and 9 Genes Involved in DNA Damage Repair

Published on: October 6, 2014

Detecting and reconstructing breakage-fusion-bridge cycles from long-read sequencing using BFBArchitect.

Chaohui Li¹, Siavash Raeisi Dehkordi¹, Daniel Muliaditan²

¹Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA 92093, United States.

Bioinformatics (Oxford, England)

|July 7, 2026

Summary

This summary is machine-generated.

BFBArchitect accurately distinguishes breakage-fusion-bridge (BFB) events from extrachromosomal DNA (ecDNA) using long-read sequencing. This computational tool reconstructs BFB sequences, offering insights into tumor progression and therapy resistance.

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Capturing Common Fragile Site Breaks by Native γH2A.X ChIP

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Capturing Common Fragile Site Breaks by Native γH2A.X ChIP

Capturing Common Fragile Site Breaks by Native γH2A.X ChIP

Published on: January 24, 2025

Area of Science:

Genomics
Computational Biology
Cancer Research

Background:

Focal oncogene amplification drives tumor progression, with extrachromosomal DNA (ecDNA) and intrachromosomal amplifications having distinct impacts.
ecDNA amplifications are linked to tumor heterogeneity, therapy resistance, and poor prognosis.
Intrachromosomal amplifications often result from breakage-fusion-bridge (BFB) cycles, leading to stable, rearranged chromosomes.

Purpose of the Study:

To develop a computational method for distinguishing BFB from ecDNA using long-read sequencing data.
To provide sequence-level reconstructions of BFB events for mechanistic insights.

Main Methods:

Developed BFBArchitect, a computational tool leveraging long-read Oxford Nanopore data.
Utilized a novel combinatorial characterization of BFB leading to integer linear programming (ILP) optimization.
BFBArchitect analyzes copy number and structural variations to identify BFB sequences.

Main Results:

BFBArchitect achieves near-perfect accuracy in distinguishing BFB from non-BFB structures in simulations and validated tumor samples.
The tool generates sequence-level BFB reconstructions, revealing insights into repair mechanisms, template switching, and telomere recapture.
Successfully applied to 18 validated tumor samples.

Conclusions:

BFBArchitect is a robust computational tool for identifying and characterizing BFB events.
The method aids in understanding the mechanisms of BFB formation and its role in cancer.
Distinguishing BFB from ecDNA is crucial for understanding tumor progression and developing targeted therapies.