June 1, 2026
Within the human genome’s approximately 3 billion base pairs, certain regions remain difficult to fully interpret due to high repetitiveness, strong sequence homology, or complex structural features. Collectively, they are often referred to as genomic “dark”[1]1 and may harbor critical variants closely linked to genetic disease2,3[2][3].
In rare disease research, what sits in these blind spots can be especially consequential. Many patients with long-undiagnosed conditions may have already gone through conventional genetic testing or short-read whole-genome sequencing (WGS), yet still lack a clear molecular diagnosis.
Dr. Tao-Ming Niu, a pediatric rare disease expert at Taipei Veterans General Hospital, has spent more than two decades studying genetic diseases and advancing the clinical application of genomic medicine. He believes that WGS will become a cornerstone of future precision medicine. Its value lies not only in delivering a one-time diagnostic result, but also in creating a lifelong genomic data asset that can be stored, revisited, and reanalyzed as analytical tools, disease databases, and clinical knowledge continue to improve.
In Dr. Niu’s view, future clinical care may require physicians to review a patient’s WGS data alongside imaging studies and laboratory results as part of long-term clinical assessment. To support this vision, his team developed Magic Bison, a rapid, real-time WGS analysis system, and has accumulated experience from several thousand WGS samples.
Yet even with this experience, Dr. Niu noted that certain regions remain difficult to resolve using next-generation sequencing (NGS). Genomic dark regions, repetitive sequences, highly homologous regions, and complex structural variants often become major bottlenecks in long-unsolved rare disease cases. Encounters like these have reinforced his team’s belief that more advanced genomic technologies with higher resolution power are needed to make further progress in rare disease research.
Expanding the boundaries of what can be interpreted
Long-read sequencing technologies have created new opportunities to uncover dark regions. But cost, workflow complexity, and scalability have remained challenging for clinical researchers looking to transform vast volumes of data into meaningful insights.
Against this backdrop, the Illumina team explored how to introduce long-range genomic information using existing sequencing platforms—enabling short reads to become more than isolated fragments and instead be reassembled into more continuous structural insights. This led to the launch of TruPath Genome, designed to help researchers build a more complete view of genomic regions associated with inherited disease.
Built on proximity mapped read technology, the solution integrates spatial information between DNA fragments on top of short-read sequencing data. This enables researchers to reconstruct long-range genomic context and improve the resolution of challenging genomic regions.
At the same time, data analysis is a critical part of this workflow. By combining DRAGEN™ secondary analysis with Emedgene™ tertiary analysis, researchers can further improve efficiency from raw data processing and variant calling through clinical correlation analysis. Signals once scattered across large-scale datasets can be more systematically organized and deeply interpreted.
During a recent forum hosted by Illumina, Dr. Niu shared his team’s progress with biotechnology industry partners. The results showed that TruPath Genome demonstrated strong potential across diverse rare disease research settings.
A skeletal disorder that opened a new research path
One pediatric case with skeletal developmental abnormalities had long remained without a clear diagnosis. Using TruPath Genome for comprehensive analysis, Dr. Niu’s team narrowed the search to a region associated with certain gene translocation alterations. It was akin to enlarging a blurry roadmap until a critical intersection finally comes into view.
TruPath analysis revealed that the chromosomal rearrangement does not simply change the structure of the chromosome, it also disrupts a regulatory region important for skeletal development. This region contains non-coding RNA elements known to participate in cartilage formation, bone growth, and bone remodeling. Therefore, the finding helps connect the genomic rearrangement with the observed skeletal abnormalities in this case.
The finding also led the team to propose a new research hypothesis: the cause may not lie solely in the gene itself, but also in non-coding RNA and microRNA involved in regulating gene activity. This means the test not only narrowed the diagnostic search, but also opened a new direction for understanding skeletal developmental disorders.
The newborn with “strawberry milk” blood
In another case, a newborn presented with severe hypertriglyceridemia (abnormally high levels of triglycerides). The blood sample showed a rare “strawberry milk” appearance. Dr. Niu’s team initially suspected familial lipoprotein lipase deficiency, but multiple tests failed to explain the cause. The team then applied the TruPath Genome workflow combined with Emedgene AI analysis to detect a deletion in the APOC4-APOC2 region.
“An integrated testing and analysis workflow allows hidden clues in the data to become clearer, while helping us investigate disease signals more systematically,” says Dr. Niu. “For patients and families, reducing the need to undergo multiple rounds of testing may also help ease the financial and emotional burden that often comes with uncertainty. TruPath Genome has broadened our perspective and brought new hope for uncovering the causes of more complex rare diseases. I believe its value will continue to be validated through more real-world studies.”
Bringing rare diseases into focus
“In rare disease research, genomic information provides an important starting point,” says Dr. Niu. “Looking ahead, integrating additional layers of biological data could help researchers build a more systematic understanding of disease mechanisms, while creating new opportunities to investigate long-unsolved cases.”
From resolving genomic dark regions to understanding the deeper biology behind diseases, technological advances continue to expand the boundaries of what can be interpreted in rare disease research. Every clearer signal and every newly revealed variant give researchers a greater opportunity to connect fragments of evidence in challenging cases—helping advance rare disease research toward a more precise understanding.
References
1 Defined as the “dark-by-MAPQ” regions in Ebbert et al2, in which 90% of the reads covering the region have a mapping quality (MAPQ) less than 10.
2 Ebbert MTW, Jensen TD, Jansen-West K, et al. Systematic analysis of dark and camouflaged genes reveals diseaserelevant genes hiding in plain sight. Genome Biol. 2019;20(1):97. Published 2019 May 20. doi:10.1186/s13059-019-1707-2
3 Ryan NM, Corvin A. Investigating the dark-side of the genome: a barrier to human disease variant discovery?. Biol Res. 2023;56(1):42. Published 2023 Jul 20. doi:10.1186/s40659-023- 00455-0
