Advancing the Clinical Translation of Single-Cell Genomic Testing
Recently, a joint research team from Macau University of Science and Technology (MUST) and Southern Medical University (SMU) reported significant progress in single-cell copy number variation (CNV) detection. Addressing clinical demands for CNV profiling at the single-cell genomic level, the team developed a medium-throughput single-cell CNV sequencing approach that combines high analytical accuracy with strong cost-effectiveness, providing a practical tool for reproductive medicine and precision oncology. The work, entitled “A medium throughput approach for single cell copy number variation sequencing towards efficient application in clinics,” was released online as an advance publication in November 2025 in the international journal Journal of Advanced Research (CAS Category I; Impact Factor = 13).
Overview
CNVs represent large-scale genomic alterations that affect human development, hereditary disorders, and tumor initiation and progression. In clinical practice, CNV testing is an essential component of third-generation in vitro fertilization (IVF) workflows for preimplantation genetic testing (PGT), prenatal genetic diagnosis based on amniotic fluid or chorionic villus samples, and the assessment of residual disease—particularly via circulating tumor cell (CTC) analysis. In reproductive genetics, accurate CNV detection facilitates early identification of chromosomal abnormalities, reduces the risk of congenital and inherited diseases, and improves embryo implantation success. In oncology, CNV-based sequencing of CTCs enables objective, longitudinal monitoring of tumor progression and can reveal key clonal evolution events in a timely manner, thereby supporting individualized precision management at the genome-wide level. However, most existing single-cell CNV sequencing methods rely on whole-genome preamplification and often require specialized instrumentation; they also face challenges such as complex workflows, high cost, amplification bias, limited throughput, and difficulties in traceability—making them poorly suited to clinical settings where samples are precious, target cells are rare, and each specimen must yield a sufficiently reliable report.
To address these clinical bottlenecks, Prof. Xinghua Pan’s team proposed and validated a medium-throughput single-cell CNV sequencing method, termed msCNVS. msCNVS employs an engineered, barcode-carrying Tn5 transposase to achieve simultaneous “tagging + fragmentation” of single-cell genomes at an early experimental stage. Subsequently, barcoded single cells are pooled into a single tube, and library construction is completed via standard steps (e.g., adding library indices), without the need for whole-genome preamplification. Testing across a series of clinical specimens and reference cell lines demonstrated that this workflow upgrades conventional low-throughput, cell-by-cell library preparation (from amplification through library construction) into a medium-throughput process, enabling flexible, single-tube library preparation for several samples, dozens of samples, 48 or 96 samples, or more. This substantially improves operational efficiency and reduces cost. Experimental results showed that, provided the cellular genome is intact, each cell can consistently yield satisfactory outputs that meet clinical requirements. Benchmarking further indicated that the method surpasses other competing technologies currently available in terms of efficiency and output quality for CNV sequencing of rare cells.
In parallel, the team developed a two-dimensional fitting algorithm and implemented an accompanying software pipeline. By optimizing single-cell whole-genome signals in a two-dimensional space defined by a “ploidy scaling coefficient” and a “baseline offset,” the method enables accurate copy-number inference without pre-specifying ploidy. In addition, uncertainty is quantified through metrics such as a “fuzzy zone,” thereby improving confidence in CNV calls. Notably, leveraging the precision of msCNVS at both experimental and analytical levels, the study provides reliable, direct single-cell evidence for CNV mosaicism in discarded blastocysts. The authors also observed strong CNV homogeneity among CTCs within the same individual across a batch of samples, while demonstrating pronounced CNV heterogeneity across individuals with the same tumor type (e.g., small cell lung cancer).
The article additionally presents a medium-throughput CNV sequencing method for micro-populations of cells (mCNVS), suitable for scenarios involving more than one but fewer than 200 cells—such as trophectoderm samples from preimplantation blastocysts (typically 5–10 cells). While maintaining high operational efficiency, mCNVS achieves better output quality than single-cell testing in terms of sequencing coverage, signal fluctuation, and CNV resolution. The authors further propose a path to upgrade the approach to high-throughput implementations, offering a convenient, reliable, and efficient tool for studies requiring large-scale single-cell profiling. Commentators in the field consider this work to have substantial translational potential and to serve as a model effort toward the clinical deployment of single-cell technologies.
Application Potential in Clinics
About the Research Team
This study was jointly conducted by research teams at MUST and SMU, with support from multiple funding sources including the Macau Science and Technology Development Fund, MUST Faculty Research Grants, the Natural Science Foundation of Guangdong Province, and the National Natural Science Foundation of China. The work was led by Prof. Xinghua Pan and Director Paul Tam from the Precision Regenerative Medicine Research Center, Faculty of Medicine, MUST, together with Prof. Hao Zhu at SMU. Prof. Xinghua Pan served as the lead corresponding author.
Reference: https://doi.org/10.1016/j.jare.2025.11.005
