Rapid, low-cost detection of genomic aberrations with Flongle

The extensive role of gene fusions in malignancies is well recognised, ranging from the characteristic BCR-ABL1 gene fusion found in breast tumours to the diverse range of FGFR2 fusions seen in certain liver cancers1 . Consequently, gene fusion detection is central to the diagnosis and treatment of many tumours. Jeck and colleagues at Duke University Medical Center, US, have been evaluating ways to improve how fusions can be detected and assessed2.

A commonly used method for fusion detection employs fluorescence in situ hybridisation (FISH), which provides relatively quick results, but is limited to the detection of a single gene target2. Similarly, quantitative RT-PCR requires prior knowledge of fusion partners2. Short-read sequencing technology is capable of simultaneously surveying numerous targets, whilst often providing the resolution to determine fusion breakpoints and partners. However, doubts over the economic viability of such short-read sequencing tests exist; Jeck et al. note that ‘a full sequencing run on most devices is excessive for the testing of a single patient’. Although multiplexing reduces costs, it may greatly extend turnaround times and, in many cases, time to action is critical for successful outcomes. To that end, the researchers evaluated the potential utility of the Oxford Nanopore Flongle device for fusion detection; at only $90 per flow cell, costs were greatly reduced compared to commonly used methods*.

"Flongle is a promising platform for single specimen fusion identification2"

Moreover, in terms of detecting fusions, results obtained via the Flongle sequencing pipeline implemented by the team showed ‘excellent concordance’ with those obtained using a short-read-based approach. Flongle also outshone the selected short-read sequencing technology for detecting an aberration within a 3.3 kb tandem repeat, highlighting the benefits of long nanopore sequencing reads. The team stated that Flongle was ‘particularly strong in identifying notoriously difficult to detect CIC-DUX4 translocations’

* Oxford Nanopore Technologies products are not intended for use for health assessment or to diagnose, treat, mitigate, cure, or prevent any disease or condition.

Figure 1 A demonstration of fusion detection using long nanopore sequencing reads. Taken from the Oxford Nanopore Technologies cDNA applications poster, this image shows a sequence alignment of long nanopore reads to the EWSR1 gene, associated with various forms of cancer, which enabled both the breakpoint junction and the fusion partner to be identified. Read poster: nanoporetech.com/poster-cdna-biology

Also leveraging the Flongle for its ‘low per-run unit cost’, Watson et al. based at St James’s University Hospital in Leeds, UK, assessed the performance of nanopore sequencing to identify a PMS2 insertion-deletion mutation associated with Lynch syndrome3, a genetic predisposition to different cancer types. The variant under study proved difficult to validate using Sanger sequencing due to the complexity of the surrounding genomic sequence. Watson and colleagues demonstrated 100% sequence identity following pairwise comparison between a verified benchmark sequence and consensus assembly of nanopore reads. Furthermore, results from the bioinformatic analysis were much ‘simpler to interpret’ than the chromatograms generated using orthogonal techniques. Taken together, Watson et al. concluded that long-read capable devices, such as the Flongle are, in the future, ‘likely to become essential tools in diagnostic genetics’*.

* Oxford Nanopore Technologies products are not intended for use for health assessment or to diagnose, treat, mitigate, cure, or prevent any disease or condition

Figure 2 Flongle is an adapter for MinION and GridION devices that enables cost-effective, real-time sequencing on smaller, single-use flow cells.


1. Arai, Y. et al. Hepatology. 59, 1427-1434 (2014).

2. Jeck, W., Iafrate, A. and Nardi, V. The Journal of Molecular Diagnostics. 23(5):630-636 (2021).

3. Watson, C. et al. Cancer Genetics. 256-257:122-126 (2021).