Despite advances in genetic testing, half of all rare genetic diseases remain undiagnosed. Many patients—often children—spend years undergoing multiple tests in search of answers, a delay that can prevent timely and effective treatment. Researchers at the University of California, Santa Cruz (UC Santa Cruz) are demonstrating how long-read sequencing can accelerate the diagnostic process, providing more comprehensive genetic insights in a single test and at a lower cost than traditional methods.
A new study published in The American Journal of Human Genetics shows that long-read sequencing improves diagnostic rates and reduces the time needed for a diagnosis from years to days. The research, led by UC Santa Cruz Genomics Institute members Benedict Paten and Karen Miga, along with former postdoctoral scholar Jean Monlong, highlights the advantages of this technology for identifying disease-causing genetic variants.
A More Comprehensive Approach to Genetic Diagnosis
Genetic diseases are typically diagnosed by searching for variants—differences in genes that may disrupt their function. Current clinical testing predominantly uses short-read sequencing, a method that reads DNA in fragments of 150–250 base pairs at a time. While useful, this approach struggles with regions of the genome containing complex structural variations or long repetitive sequences. It also lacks the ability to determine which variants are inherited from each parent, a process known as phasing.
Long-read sequencing, in contrast, sequences much longer DNA fragments, eliminating gaps and providing additional information about genetic variations. It also captures epigenetic markers, such as DNA methylation, which influence gene expression and may contribute to disease.
“Rare diseases are something that people have been struggling to diagnose for so many years, and if we have a sequencing technology which streamlines diagnostic testing, I think that will be a huge contribution—and that is what we tested as part of this paper,” said first author Shloka Negi, a Ph.D. student in biomolecular engineering at UC Santa Cruz.
Applying Long-Read Sequencing to Rare Disease Cases
The researchers worked with clinicians to analyze the genomes of 42 patients with rare diseases, some of whom had previously received diagnoses through short-read sequencing or other specialized tests, while others remained undiagnosed. The team sequenced the patients’ genomes using nanopore sequencing, a long-read method developed at UC Santa Cruz, at a cost of approximately $1,000 per sample. They then used computational tools developed in Paten’s lab to identify genetic variants, phasing data, and methylation patterns within a single analytical pipeline known as Napu. The entire analysis process took about a day and cost roughly $100.
The results demonstrated that long-read sequencing provided a richer dataset than short-read methods, offering additional genetic insights for all patients in the study. In 11 cases, long-read sequencing delivered a definitive diagnosis. This included four cases of congenital adrenal hypoplasia, a condition affecting adrenal gland function. The gene responsible for this disorder is located in a challenging genomic region that short-read sequencing cannot accurately analyze, while the current clinical test is cumbersome and incomplete.
“To solve these cases, we developed a new pangenomic tool that integrates new high-quality assemblies like the 'telomere-to-telomere' reference genome,” said Monlong, now at INSERM in France. “We were excited to see that we could find and phase the pathogenic variants of all four patients suffering from this disease in our cohort.”
Other successfully diagnosed cases included two patients with disorders of sex development, one case of Leydig cell hypoplasia affecting male sexual development, and four neurodevelopmental disorders—each representing long and difficult diagnostic journeys.
A Step Toward Faster, More Accurate Genetic Testing
While long-read sequencing is not yet standard in clinical settings, its potential to serve as a primary diagnostic tool is clear. The method can reduce the need for multiple tests, streamline genetic evaluations, and uncover previously undetectable variants.
“Long read sequencing is likely the next best test for unsolved cases with either compelling variants in a single gene or a clear phenotype,” Negi said. “It can serve as a single diagnostic test, reducing the need for multiple clinical visits and transforming a years-long diagnostic journey into a matter of hours.”
The study also reinforced the advantages of using complete reference genomes for analysis. Miga noted that applying a “telomere-to-telomere” reference genome substantially improved the benefits of long-read sequencing, and she anticipates that pangenomes—reference datasets incorporating diverse human genomic variation—will further enhance the method’s effectiveness.
“There’s so much more of the genome that the long reads can unlock,” Negi said. “But it will take some time until we can fully interpret this new information. This data has been absent from our clinical databases, which were built using short-read analysis and mapping to the standard reference.”
On average, each patient in the study had 280 genes, including some linked to Mendelian diseases, with significant protein-coding regions covered exclusively by long reads—regions that short-read sequencing could not access. The researchers estimate that long-read sequencing captures about 5.8% more of the complete genome than short-read methods.
With its ability to provide comprehensive genetic data in a single, rapid, and cost-effective test, long-read sequencing is poised to improve the diagnostic journey for patients with rare diseases. While further refinement and clinical validation are needed, this study marks a significant step toward making genetic testing faster and more accessible for those who need it most.
Publication Details
Negi, Shloka, et al. "Advancing long-read nanopore genome assembly and accurate variant calling for rare disease detection." The American Journal of Human Genetics (2025). DOI: 10.1016/j.ajhg.2025.01.002