BALTIMORE – Researchers in Italy have demonstrated the effectiveness of long-read nanopore sequencing for the real-time detection of copy number variants (CNVs) in patients with genetic disorders.
The team, led by Alberto Magi of the University of Florence, applied nanopore sequencing to a cohort of seven patients with known pathogenic CNVs and compared the method’s performance with that of traditional molecular karyotyping techniques.
The results, published in the Journal of Molecular Diagnostics last month, showed that nanopore sequencing has the potential to achieve fast, real-time detection of various large and small CNVs while providing insights into mosaic events that cannot be easily discerned by conventional cytogenetics methods.
"The identification and detection of copy number variants is very important for medicine," said Magi, a professor of bioengineering at the University of Florence and the lead investigator of the study. Representing a significant portion of human genetic mutations, CNVs are linked to a plethora of illnesses, Magi said, including cardiovascular disease, neurodevelopmental disorders, and cancer.
Currently, conventional cytogenetics techniques and chromosomal microarray analysis remain the major workhorses for detecting large and small CNVs, respectively, he said. In addition, next-generation sequencing is also able to identify CNVs, although the method is not as ubiquitous due to its high cost, he added.
However, Magi said all of these methods are constrained by their laborious experimental protocols and relatively slow turnaround time, delaying the time to diagnosis by three to 15 days. While conventional cytogenetics is limited to detecting large CNVs, microarray and NGS-based assays can detect smaller CNVs, but the low specificity of these methods prevent them from discerning mosaicism in CNVs, meaning the portion of cells harboring the variants.
Moreover, with existing molecular and sequencing-based methods, people have to wait until the end of the experiment to obtain results, Magi said. In contrast, nanopore sequencing offers researchers the opportunity to detect CNVs in real time, promising to "drastically" reduce the test’s turnaround time.
For the published study, the researchers extracted genomic DNA from seven patients with previously identified CNVs of different sizes and levels of mosaicism. Their nanopore sequencing libraries were prepared and sequenced on a GridIon device from Oxford Nanopore Technologies for up to 48 hours using the R9.4.1 flow cell. According to Magi, the wet-lab workflow from DNA extraction to loading the flow cell took around two hours, and the samples underwent shallow sequencing with mostly 5X to 6X coverage.
To achieve real-time analysis of the data, the researchers deployed Nano-Gladiator, a software previously developed by Magi’s team, to detect copy number alterations from the sequencing reads at multiple time points from 30 minutes to 48 hours after the start of the run. They also compared the sample-to-result time of nanopore sequencing with that of the state-of-the-art array-based comparative genomic hybridization (aCGH) method.
The results showed that just 30 minutes into the sequencing run, nanopore data can pick out large chromosomal anomalies, which usually take several days from sample processing to data analysis with the conventional karyotyping approach, according to the study.
As the sequencing carried on, the resolution of the assay continued to improve, Magi said. Specifically, the data indicated that microdeletions and microduplications of approximately 1 Mb became detectable within six to nine hours of sequencing, after 500,000 to 1 million reads had been generated.
However, Magi said the team observed a data plateau after 24 hours, when nearly 90 percent of the sequencing reads had been generated. Still, small CNVs of less than 500 kb could be observed after 30 hours of sequencing, resulting in a sample-to-diagnosis turnaround time of approximately two days. This is shorter than aCGH, which requires at least three days to reach a diagnosis, the researchers noted.
Importantly, Magi said, with aCGH, it is "nearly impossible" to study mosaicism because of its resolution, whereas nanopore sequencing was able to accurately profile mosaic events by identifying the exact percentage of the cells that have the alteration, an advantage he considers "very revolutionary."
The study also identified "a very small number" of false positive events, Magi noted, which were categorized as CNVs obtained from nanopore sequencing that had no overlap with aCGH findings. The false positive rate increased with the time of sequencing, mainly after six hours, and correlated with the window size used for analysis detection, Magi said. He pointed out that there were no false positives at the beginning of the sequencing run, when large CNVs were detected.
Magi cautioned that because the results were compared with aCGH, which has a "limited resolution" and cannot detect all CNVs, it is hard to say if the false positive events identified in this study were truly false positive.
"I think it's a solid paper," said Winston Timp, a biomedical engineering professor at Johns Hopkins University. The researchers were "really trying to push the envelope" of what people can do with nanopore sequencing when it comes to practical clinic applications, he added.
Compared with conventional cytogenetic techniques, Timp said, sequencing-based methods have the capability to reveal more layers of genetic information in addition to just identifying CNVs. "By virtue of having the sequence information, you can get yet more detailed information about where [the CNV] is, what's going on, and how the CNV is structured," he said, adding that the technology also has the potential to become "a one-stop shop," offering "very deep detailed information on a couple of different facets of the genomic state of the patient."
While the study is part of a broader movement in the field to push forward applications of portable, low-capital-investment sequencing devices represented by Oxford Nanopore to answer questions in the clinic, Timp emphasized that it is also important to be cognizant of costs.
"In addition to speed, hands-on time, and labor, we also need to consider questions about cost," he said. "I think the field is moving towards using sequencing more for diagnostic approaches, but I think that we really need to keep in mind the issues of keeping these things affordable."
Echoing Timp’s point, Magi said that one of the current limitations of using nanopore sequencing for CNV detection in the clinic is cost. An average aCGH experiment costs around $100, he said, while the consumables cost for a nanopore run can cost roughly $500. "There is a gap that needs to be reduced," Magi said, adding that one of the future directions for the team is to continue reducing the test’s cost.
Beyond that, moving forward, Magi said his team aims to test the method on a much larger cohort of at least 100 patients by the end of the year, although he said it has been "very difficult to find well-characterized samples with predefined copy number variants."
Furthermore, Magi said his group also considers expanding the coverage of the assay. Currently, with shallow sequencing, the method can detect duplications and deletions. However, Magi said his lab is hoping to receive a PromethIon 2 Solo — a newer version of Oxford Nanopore's high-throughput sequencer — this fall and plans to experiment with increasing the whole-genome sequencing depth to at least 30X.
"At that level of coverage, we can not only identify copy number variants but the entire spectrum of structural variants, inversions, deletions, duplications, insertions, and translocations," he said.