L26/P-657 High-precision reconstruction of structural variations via one-step integrated analysis based on 3D genome

Abstract Study question Chromosomal abnormalities are a major cause of failed conception and pregnancy loss. Current detection methods suffer from low accuracy or high cost. Summary answer We developed a structural variation detection method based on 3D genomics, enabling comprehensive detection of chromosomal abnormalities at high resolution through one sequencing run. What is known already Structural variations (SVs), including copy number variations (CNVs), are frequently observed in the human genome and may lead to genetic disorders, developmental abnormalities, or reproductive failure. The accurate detection of SVs is fundamental to subsequent diagnosis, treatment, and assisted reproductive technologies. Existing technologies can typically address certain aspects of variant detection. For instance, karyotyping can identify large SVs exceeding 5 Mb, while CNV-seq can detect CNVs across the genome. However, single approaches still face challenges in simultaneously detecting CNVs, uniparental disomies (UPDs), small-scale SVs, and complex SVs at low cost, limiting its application in widespread screening. Study design, size, duration We analyzed over 1,500 clinical samples, obtaining information across various dimensions including variation types, locations, orientations, and breakpoints. Variant types include deletions, duplications, insertions, balanced translocations, unbalanced translocations, Robertsonian translocations, inversions, and complex SVs formed by combinations or nested arrangements of the above variants—such as sequences from other sources inserted within inverted segments. The results of different methods are validated through comparative analysis. Participants/materials, setting, methods We developed a chromosome conformation based molecular karyotyping analysis (C-MoKa) method using 3D genome, enabling the acquisition of genomic spatial contact data at the three-dimensional scale from a single sequencing run. When the genomic structure of a sample changes, its corresponding 3D conformation inevitably undergoes corresponding alterations. By detecting these 3D-scale changes, we can conversely infer the variations in its genomic structure, as these two aspects are directly correlated. Main results and the role of chance In the analysis results, our method demonstrated precise fragment resolution (100 kb) and breakpoint resolution (5 kb). By comparing results obtained through different methods, we identified 85 cases where C-MoKa detected additional SVs compared to karyotyping. These included karyotyping’s failure to detect small-fragment SVs, misclassification of complex SVs, and incorrect identification of SV types. In terms of detection performance for CNVs and UPDs, C-MoKa is comparable to CNV-seq and chromosomal microarray analysis (CMA). At the level of fine-scale chromosomal abnormality and complex SV analysis, karyotyping, CNV-seq, and CMA are all impractical. Therefore, we chose to compare C-MoKa with optical genome mapping (OGM) and long-read sequencing (LRS), demonstrating comparable performance across the tested samples. Due to the high cost and low automation of OGM and LRS, C-MoKa’s exceptional ability to resolve complex SVs makes it the most cost-effective technology currently available for high-precision chromosomal analysis, facilitating its application in large-scale screening. Limitations, reasons for caution Genomic repetitive regions are unsuitable for 3D genome analysis because sequences there are difficult to map to the reference genome. Therefore, C-MoKa cannot detect inversion polymorphisms or SVs in heterochromatic regions. Furthermore, variations occurring at positions with inherently strong spatial contacts are more difficult to detect. Wider implications of the findings Our findings indicate that C-MoKa holds potential practical value for accurately resolving genomic variations in clinical settings, which will significantly impact subsequent clinical decision-making. Furthermore, this method can be used for haplotype phasing and applied to preimplantation genetic screening. Trial registration number No