Completely resolved structural variants by optical genome mapping with adaptive sampling from CNV discovery

Completely resolved structural variants by optical genome mapping with adaptive sampling from CNV discovery | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Completely resolved structural variants by optical genome mapping with adaptive sampling from CNV discovery Li Fu, Chong Ae Kim, Masatoshi Tokita, Yohane Miyata, Nobuhiko Okamoto, and 31 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7371701/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 26 Mar, 2026 Read the published version in npj Genomic Medicine → Version 1 posted 11 You are reading this latest preprint version Abstract Structural variants (SVs), including duplications, deletions, inversions, translocations, and insertions, contribute to human phenotypic diversity but are often challenging to identify due to their size variability and complex configurations. Optical genome mapping (OGM) uses ultra-high molecular weight DNA (> 150 kb) fluorescently labeled at a specific six-nucleotide sequence, enabling comprehensive SVs detection by analyzing labeling patterns along long DNA molecules. This study aimed to fully characterize SVs using OGM. OGM was applied to 30 cases with exome sequencing-based copy number variants (16 deletions, seven duplications, and seven deletions and duplications). Additionally, targeted Oxford Nanopore long-read sequencing with adaptive sampling was used to determine breakpoints of SVs. This approach revealed undetected SVs in 14 cases (46.7%), and disclosed gene disruptions or copy number alterations explaining clinical features in eight cases (26.7%). Even complex SVs involving numerous chromosomal segments and breakpoints were resolved efficiently, highlighting the power of combining OGM and long-read sequencing. Biological sciences/Biological techniques Biological sciences/Computational biology and bioinformatics Biological sciences/Genetics Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Structural variations (SVs)—defined as genomic alterations larger than 50 base pairs (bp) and including duplications, deletions, inversions, translocations, and insertions—constitute the majority of variable nucleotides in the human genome and contribute significantly to phenotypic diversity 1 . Although exome sequencing (ES) enables the detection of copy number variants (CNVs) 2 , it frequently fails to capture SV breakpoints, primarily because of the limited coverage of capture regions and technical limitations such as polymerase chain reaction (PCR) and hybridization biases in GC-rich regions, as well as poor alignment in low-complexity regions. Even with genome sequencing, SV detection remains challenging because of the wide range of SV types and sizes and their frequent localization within repetitive genomic regions. These complexities hinder both sensitivity and specificity in SV calling, especially for structurally complex and repetitive regions. As a result, many pathogenic SVs likely remain undetected, and the reliable identification of such variants from short-read sequencing data continues to be a major technical and computational challenge 3 , 4 . Several methodologies have been used for SV detection, including conventional karyotyping, fluorescence in situ hybridization (FISH), chromosomal microarray analysis, and long-read sequencing. More recently, optical genome mapping (OGM) has emerged as a promising technique for the comprehensive analysis of SVs. Unlike sequencing-based methods, OGM uses high-resolution fluorescence imaging of ultra-high molecular weight DNA to detect structural changes without nucleotide-level sequencing. Long-read sequencing produces reads typically ranging from 10 to 100 kilobases (kb), whereas OGM analyzes DNA molecules exceeding 150 kb, providing broader genome coverage (> 80×) albeit at lower breakpoint resolution 3 , 5 , 6 . OGM identifies SVs through the de novo assembly of fluorescently labeled DNA molecules using a specific six-base sequence motif (CTTAAG), which occurs on average every 5 kb across the genome 7 – 9 . This method enables the detection of a wide range of structural alterations, including insertions and deletions (> 500 bp), duplications (> 50 kb), inversions and translocations (> 50–70 kb), chromosomal aneuploidy, absence of heterozygosity (AOH), triploidy, and copy-neutral events 10 , 11 . In this regard, OGM may outperform traditional sequencing-based platforms for identifying large and complex SVs. In the present study, we aimed to use OGM to comprehensively characterize constitutional SVs that were initially identified as CNVs using ES. Furthermore, we used targeted Oxford Nanopore long-read sequencing with adaptive sampling (AS) to resolve the breakpoint structures of these newly discovered SVs at nucleotide resolution. Results We applied OGM to 30 cases (Tables 1 and S1) and identified only the expected ES-identified CNVs in 16 cases (Cases 1, 2, 3, 4, 5, 8, 9, 10, 11, 12, 13, 14, 16, 19, 25, and 28). By contrast, previously undetected SVs were revealed in the remaining 14 cases (Fig. S1 , Tables 2 and 3 ). The newly discovered SVs in the latter 14 cases included: three translocations (Cases 15 , 17, and 26), three tandem duplications (Cases 7, 18, and 24), one duplication with inversion (Case 6), two inverted duplications (Cases 23 and 27 ), three intrachromosomal translocations with inverted duplications (Cases 20 , 21, and 22), one complex intrachromosomal rearrangement involving translocation, inversion, and additional translocation (Case 29), and one chromothripsis (Case 30). To further characterize the SVs in all 30 cases, we used Oxford Nanopore targeted long-read sequencing with AS (Table S2 ). This approach allowed us to precisely determine the SV breakpoints at the nucleotide level and generate dot-plots to visualize the identified SVs. Detailed results for the 30 cases are provided in the following sections. Deletions (Cases 1, 2, 3, 4, 5, 8, 9, 10, 11, 12, 13, 14, 16, 19, and 25) We performed OGM in 16 cases with ES-based deletions, and detected only simple (expected) deletions in 15 cases; however, a complex chromosomal rearrangement was identified in one case (Case 29) (Table 2 ). Subsequent targeted long-read sequencing enabled the detailed investigation of haploinsufficient genes involved in these deletions (Tables 2 and S3). Breakpoints at nucleotide resolution were successfully determined in 11 of the 15 cases with simple deletions: interstitial deletions in Cases 3, 8, 9, 10, 11, 12, 14, 16, 19, and 25, and a deletion involving 4q telomeric sequences (TTAGGG) in Case 2 (Figs. S2 and S3, Table S4). Among these 11 cases, ES-based analysis did not identify haploinsufficient genes, although we identified SUMO1 (pHaplo score = 0.900 12 ) in Case 12 and COL11A1 (pHaplo score = 0.894 12 ) in Case 25 (Table S3 13 ). SUMO1 deletion causes orofacial cleft (OMIM# 613705) and SUMO1 haploinsufficiency has been associated with cleft lip and palate, consistent with the phenotype observed in Case 12 14,15 . In Case 25, ES had already identified KCNA2 (OMIM# 616366) as a cause of seizures and global developmental delay 16 , 17 . Our analysis additionally revealed COL11A1 , whose haploinsufficiency causes Marshall (OMIM# 154780) and Stickler (OMIM# 604841) syndromes, both of which are associated with abnormal facial shape, failure to thrive, and short stature, as observed in Case 25 18,19 . CTBP1 was disrupted by the deletion breakpoint in Case 2 (Table 2 ). CTBP1 aberration is associated with hypotonia, ataxia, developmental delay, and tooth enamel defect syndrome (OMIM# 617915) in an autosomal dominant fashion, and may influence the neurological features observed in this case 20 . In Cases 1, 4, 5, and 13, although deletions were identified using OGM (Tables 2 and S4), the breakpoint determination of deletions using long-read sequencing was unsuccessful. In these cases, segmental duplications of approximately 247 kb (Case 1), 161–163 kb (Case 4), 218 kb (Case 5), and 39–42 kb (Case 13) were exactly mapped to deletion breakpoints (Fig. S4). Because N50 in the long-read sequencing data of Cases 1, 4, 5, and 13 were 4551, 6483, 7813, and 23790 bp, respectively, long-read sequencing cannot cover these segmental duplications. Using Blast Like Alignment Tool (BLAT; https://genome.ucsc.edu/cgi-bin/hgBlat ) 21 to analyze the sequence homology of the pairs of segmental duplications mapped to the deletion breakpoints in Cases 1, 4, 5, and 13, high sequence homology was identified: 99.7%, 99.1%, 99.6%, and 98.9% for the 40-, 10-, 20-, and 39-kb segmental duplications, respectively (Fig. S4b, d, f, and h). Therefore, although precise breakpoint determination was not possible, the involvement of non-allelic homologous recombination (NAHR) is strongly indicated as a mechanism for generating these deletions 22 , 23 . OGM, which analyzes DNA molecules exceeding 150 kb, is therefore advantageous for mapping relatively large segmental duplications compared with long-read sequencing. Duplication (Case 28) We identified an ES-based duplication in Case 28. OGM detected the expected duplication at the terminal region of chromosome 2q, as identified using ES (Fig. S5a). However, we were unable to fully characterize the duplication using OGM (Fig. S5b, Table S4), even when referring to the telomere-to-telomere (T2T) reference genome (instead of GRCh38). Long-read sequencing also failed to confirm a duplication at the 2q terminal region. This was likely because of the presence of many repetitive sequences such as DNA transposons, long terminal repeat (LTR) retrotransposons, and short interspersed nuclear elements (SINE), as well as long interspersed nuclear elements (LINE) of non-LTR retrotransposons at around the breakpoint, which hampered the mappability of the duplication breakpoint (Fig. S5b). Notably, the OGM-detected duplication did not include any known triplosensitive genes associated with the clinical features of this case (Table S3). Unbalanced reciprocal translocations (Cases , 17, and 26) In Cases 15 , 17, and 26, unbalanced reciprocal translocations—characterized by combined terminal duplications and deletions—were detected using ES. OGM also identified unbalanced translocations in these three cases. Case 15 presented clinically with West syndrome, hypoplasia of the corpus callosum, and aortic regurgitation. In this case, unbalanced translocation was detected using OGM and AS, with a 3.5-Mb deletion at 1p36.33–p36.32 and a 3.8-Mb duplication at 17p13.3–p13.2 (Fig. 1 a, 1 b, Tables 2 and S4). The deletion encompassed GABRD (pHaplo score = 0.807 12 ), which is associated with generalized epilepsy with febrile seizures plus (OMIM# 613060) (Table 1 ). Although no known triplosensitive genes were initially identified within the 17p13.3–p13.2 duplication, precise mapping using OGM identified that this duplication also encompassed PAFAH1B1 , with pTriplo score = 0.998 12 (Table S3). Duplications of PAFAH1B1 have been linked to West syndrome 24 , seizures, and a range of structural brain anomalies including abnormalities of the corpus callosum, cerebellum, posterior fossa, and skull 25 . Thus, the duplicated PAFAH1B1 might account at least in part for the brain abnormalities observed in this patient. To confirm the origin of this unbalanced translocation, breakpoint-spanning PCR was performed using long-read sequencing data (primers listed in Table S5); this confirmed its paternal origin (Fig. 1 d and e). Sanger sequencing of the translocation breakpoints further identified a 3-bp insertion on der(1) and a 2-bp insertion on der(17) (Fig. 1 f). Although one gene was disrupted by a translocation (Table 2 ), none of the affected genes were associated with the clinical features observed in Case 15 . In Case 17, characterized by Klippel–Feil syndrome, cleft lip and palate, dysphagia, hearing impairment, and esotropia, OGM with AS identified an unbalanced translocation with a 6.7-Mb deletion at 21q22.2–q22.3 and a 9.9-Mb duplication at 14q32.13–q32.33 (Fig. S6a–c and Table S4). To investigate the origin of this unbalanced rearrangement, breakpoint-spanning PCR was performed using available maternal DNA (primers listed in Table S6). This analysis confirmed the absence of a maternal origin for this rearrangement (Fig. S6d). Furthermore, Sanger sequencing of the breakpoint PCR products revealed a simple unbalanced translocation (Fig. S6f). No known genes associated with the clinical symptoms observed in Case 17 were disrupted, deleted, or duplicated by this translocation (Tables 2 and S3). In Case 26, presenting with seizures, global developmental delay, abnormal facial features, cerebral hemorrhage, laryngomalacia, low-set ears, atresia of the external auditory canal, and impaired ocular abduction, we identified an unbalanced reciprocal translocation using OGM with AS (Fig. S7a–c and Table S4). This translocation included a 4.6-Mb duplication at 5p15.33–p15.32 and a 7.4-Mb deletion at 18q22.3–q23. Initial attempts to detect the breakpoint using dnarrange ( https://github.com/mcfrith/dnarrange 26 ) with long-read sequencing data were unsuccessful. We subsequently performed the manual inspection of soft-clipped reads at the 5p15.32 and 18q22.3 regions using Integrative Genomics Viewer (IGV) (Fig. S7d and e). However, many soft-clipped reads originating from chromosomes 5 and 18 mapped to chromosome 4 and another region of chromosome 5, as shown in the supplementary alignments (Fig. S7f). At the chromosome 18 breakpoint, several soft-clipped reads were also aligned to chromosomes 2, 9, and 14 (Fig. S7e and g). These regions contained repetitive sequences such as LTR retrotransposons and LINE of non-LTR retrotransposons. The presence of these repeats likely contributed to the mapping ambiguity, complicating accurate breakpoint identification despite moderate to very high long-read coverage, with mapping quality scores ranging from 21–60 27 . Interestingly, the lengths of these mismapped long reads ranged from approximately 11–37 kb, whereas the repetitive sequences in the supplementary alignment regions ranged from approximately 0.2–6 kb. This discrepancy indicates that the read lengths were sufficient to span the unique sequences flanking the repetitive regions. These findings imply that OGM, which analyzes relatively long DNA molecules (~ 150 kb), may provide superior breakpoint resolution in genomic regions containing complex repetitive sequences. No known genes associated with the clinical symptoms observed in Case 26 were affected by the copy-number changes resulting from the unbalanced translocation (Table S3), and no genes were disrupted by the translocation itself (Table 2 ). Tandem duplications (Cases 7, 18, and 24) OGM identified tandem duplications in three cases (Figs. 1 g, 1 h, S8a, S8b, S8f, and S8g), which had previously been detected by ES. Long-read sequencing data confirmed the breakpoints in these cases (Figs. 1 i, S8c, and S8h) and enabled the reconstruction of tandem duplications through dot-plots (Figs. 1 j, S8d, and S8i). Case 7, who was clinically suspected of having Coffin–Siris syndrome, exhibited a 2.2-Mb tandem duplication at 8p23.1 by OGM with AS (Fig. S8b, Tables 2 and S4). This duplication, previously identified using ES, encompasses SOX7 (pTriplo score = 0.421 12 ) and GATA4 (pTriplo score = 0.916 12 ), and is consistent with 8p21.3 duplication syndrome (Table S3), which is associated with developmental delay, dysmorphism, hypotonia, visual impairment, and congenital heart disease 28 (Table 1 ). These findings align with the clinical presentation of the patient, and no additional aberrant genes relevant to the phenotype were detected using OGM. Although one gene was disrupted by the tandem duplication breakpoint (Table 2 ), it has not been associated with any of the clinical features observed in Case 7. In Case 18, OGM with AS identified a 1.5-Mb tandem duplication at 2q24.3 (Fig. 1 h, Tables 2 and S4) that encompassed key sodium channel genes such as SCN1A, SCN2A, SCN3A, SCN7A , and SCN9A , all of which had been previously detected using ES (Tables 1 and S3). The clustering of these sodium channel genes at 2q24.3 is strongly associated with early infantile epileptic spasms 29 , in line with the clinical phenotype observed in this case. OGM did not reveal any additional aberrant genes that would further explain the patient’s clinical symptoms. SCN7A was observed to be disrupted by the tandem duplication (Table 2 ). In Case 24, OGM detected a 606-kb tandem duplication at 19q13.33 (Fig. S8g, Tables 2 and S4) that encompassed PRR12 (pTriplo score = 0.999 12 ) (Table S3). PRR12 abnormality is implicated in neuro-ocular syndrome (OMIM# 619539), an autosomal dominant condition that is characterized by microcephaly, facial abnormalities, congenital heart defects, global developmental delay, and intellectual disability 30 . Although this finding potentially explains part of the patient’s phenotype (Table 1 ), its precise contribution remains uncertain because of a lack of corroborating evidence. Two genes were disrupted by a tandem duplication (Table 2 ) but neither was associated with the observed clinical features. Inversion and duplication (Case 6) In Case 6, we newly identified a 6.2-Mb inversion at 21q22.2–q22.3 and a 218-kb duplication at 21q22.2 using OGM with AS. The duplication had previously been detected using ES (Tables 2 and S4). OGM analysis revealed that the inversion was located immediately downstream of the duplication (Fig. 2 a and b), thus highlighting a limitation of ES, which typically fails to detect breakpoints outside coding regions. Long-read sequencing data further illustrated these SVs through dot-plot reconstruction (Fig. 2 c and d). However, no aberrant triplosensitive genes associated with hereditary spastic paraplegia or autism were identified within these regions (Table S3). Although two genes were disrupted by the SVs (Table 2 ), neither has been associated with hereditary spastic paraplegia or autism. Inverted duplications (Cases 23 and 27) OGM identified inverted duplications in Cases 23 and 27 , involving complex rearrangements that combined deletions and duplications (Figs. 2 f, 2 g, S9a, and S9b). Long-read sequencing successfully confirmed the breakpoints in both cases (Figs. 2 h, S9c and S9d). In Case 23, who was clinically suspected to have Cornelia de Lange syndrome, OGM revealed a 14.3-Mb deletion and an 851-kb duplication at 9p22.3, resulting in inverted duplication (Tables 2 and S4). Notably, NFIB (pHaplo score = 0.999 12 ) was disrupted at intron 1 by the SV (Fig. 2 g, Tables 2 and S3). Haploinsufficiency of NFIB causes macrocephaly with impaired intellectual development (OMIM# 618286) as well as intellectual disability and dysmorphic features 31 , 32 . These clinical features are consistent with those observed in Case 23, including intellectual disability and dysmorphic features. Case 27 involved an inverted duplication rearrangement detected by OGM with AS (Tables 2 and S4), similar to a previously reported case 33 . Within the 18.5-Mb deletion at 9p22.1–24.3, both NFIB and SMARCA2 were identified (Fig. S9b and Table S3). As previously mentioned, NFIB haploinsufficiency can contribute to intellectual impairment, dysmorphic facial features, and a high palate (Table 1 ). SMARCA2 (pHaplo score = 0.999 12 ) is associated with blepharophimosis-impaired intellectual development syndrome (OMIM# 619293) and Nicolaides–Baraitser syndrome (OMIM# 601358) in an autosomal dominant manner, and its intragenic deletions reportedly cause intellectual disability, seizures, and dysmorphic features 34 , 35 . Although SMARCA2 deletion has not been clearly established as a distinct deletion syndrome, it has been previously reported with limited clinical information 36 . By contrast, the adjacent 19.7-Mb duplication did not contain any known genes associated with human diseases (Table S3). Notably, although one gene was disrupted by inverted duplication in each of Cases 23 and 27 (Table 2 ), neither gene was associated with the clinical features observed in these cases. Intrachromosomal translocations and inverted duplications (Cases 20 –22) Using OGM with AS, we identified novel intrachromosomal translocations and inverted duplications in three cases (Cases 20 –22) in whom duplications or combined deletions and duplications had initially been detected by ES. OGM revealed a range of complex structural rearrangements in these cases. Case 20 involved an inverted duplication deletion and intrachromosomal translocation (Fig. 3 a and b, Tables 2 and S4). In Case 21, an inverted duplication and two intrachromosomal translocations were identified (Fig. S10a and b, Tables 2 and S4). Case 22 exhibited an inverted duplication and intrachromosomal translocation (Fig. S10h and i, Tables 2 and S4). Regarding these chromosomal rearrangements, Case 20 included an 8.4-Mb duplication at Xq21.33–q22.3, whereas Case 21 harbored a 439-kb duplication at Xq22.2, as detected by OGM. Notably, the intrachromosomal translocations in these cases were positioned adjacent to their respective duplications, a feature that was missed by ES because of the copy-neutral nature of these SVs (Figs. 3 b, 3 f, S10b, and S10g). Importantly, Case 20 had been previously diagnosed with PCDH19 -related epilepsy syndrome, and PCDH19 is located within the duplicated region detected by ES 2 , 37 (Tables 1 and S3). In Case 21, PLP1 (which causes Pelizaeus–Merzbacher disease) was identified within the Xq22.2 duplication, consistent with earlier reports of complex PLP1 rearrangements, including triplications and inverted duplications 38 , 39 (Tables 1 and S3). However, in both cases, the newly resolved SVs identified by OGM and long-read sequencing did not reveal any additional pathogenic variants that might explain the patients’ clinical features (Table S3). Although two and one genes were disrupted by SVs in each case (Table 2 ), none of the genes were associated with the observed clinical features of Cases 20 and 21. By contrast, Case 22 exhibited a more complex pattern involving a 10.8-Mb duplication at 18p11.32–p11.22, a 2.8-Mb duplication at 18q21.31–21.33, and an 18.9-Mb deletion at 18q21.33–q23 (Fig. S10i and m). Within the deleted 18q21.33–q23 region, ES identified TSHZ1 and NFATC1 , which have been associated with auricular deformities, hearing impairment 40 , 41 , and congenital heart disease 42 , 43 (Tables 1 and S3). Nevertheless, in the newly characterized SVs using OGM and long-read sequencing, no additional candidate pathogenic genes were identified that might account for the patient’s clinical presentation, which included features potentially resembling Cornelia de Lange syndrome (Table S3). Additionally, PIEZO2 , which is associated with Marden–Walker syndrome (OMIM# 248700) through an autosomal dominant mechanism, was disrupted by SVs in Case 22 (Table 2 ). PIEZO2 has also been reported as associated with Cornelia de Lange syndrome 44 , and may be involved in the phenotype observed in this case. Intrachromosomal translocation, inversion, and interchromosomal translocation in Case 29 In Case 29, who presented with Ehlers–Danlos syndrome, joint laxity, arthritis, and mild intellectual disability, ES previously identified a 5.2-Mb deletion at 12q21.1–q21.2. OGM further revealed an intrachromosomal translocation and inversion within chromosome 12, an inversion within chromosome 14, and an interchromosomal translocation between chromosomes 12 and 14 (Fig. 4 a–c). Long-read sequencing precisely determined all of the breakpoints (Fig. 4 d–i), confirming a complex reciprocal translocation between chromosomes 12 and 14 (Fig. 4 j–l and Table S4). The complex rearrangement involved chromosomes 12 and 14, with reciprocal inverted insertions, partial deletions, and inversion of multiple segments. Despite the complex rearrangement, no clearly haploinsufficient gene associated with the patient’s phenotype was identified within the deleted region (Table S3). Two genes were disrupted by a reciprocal translocation (Table 2 ), but neither was associated with the clinical features observed in Case 29. The derivative chromosome 12 harbored the 5.2-Mb deletion at 12q21.1–q21.2, which was joined to chromosome 14 without a copy number change. Therefore, although the deletion was detectable by ES-based CNV analysis, the reciprocal translocation itself was not identified. Because the deleted region did not encompass any previously known disease-associated genes that would explain the clinical features, this case clearly demonstrates the limitations of ES for detecting complex SVs and highlights the added value of OGM and long-read sequencing in cases with no apparent clinical features. Chromothripsis (Case 30) In Case 30, who presented with vitreoretinal degeneration, short stature, growth delay, abnormal facial shape, calcified skin lesions, and ventricular septal defect, ES detected eight duplications in chromosome 22, implying chromothripsis (Fig. 5 a). Based on ES data, the CNV sizes of the eight duplications at 22q12.1–q13.33 ranged from 107–437 kb. OGM analysis revealed six intrachromosomal translocations, one deletion, one inversion, and one inverted duplication with 46,XY,(22q)cth at 22q11.21–q13.33 (Figs. 5 b, S11 and Table 3 ). Although we attempted to reconstruct the full spectrum of SVs based on the OGM results, the SVs identified by OGM did not completely match those detected by dnarrange using long-read sequencing data. We therefore manually evaluated the breakpoint sequences using long-read sequencing data, considering the orientations of the SVs and CNVs called using OGM (Fig. 5 c). The CNV sizes of the eight duplications in a dot-plot of long-read sequencing data were 390 kb at 22q11.21, 419 kb at 22q12.1–q12.2, 460 kb at 22q12.2, 238 kb at 22q12.3, 884 kb at 22q13.1, 335 kb at 22q13.1, 466 kb at 22q13.1, and 625 kb at 22q13.31. These regions included six, nine, seven, four, 31, 15, 14, and seven genes, respectively (Table S3); however, none of the genes were associated with known phenotypes. In addition, six genes were disrupted by the chromothripsis (Table 3 ), but none of these were associated with the clinical features observed in Case 30. Ultimately, the combined analysis of OGM and targeted long-read sequencing provided a comprehensive and accurate identification of the chromothripsis (Table S4). Discussion We identified novel SVs using OGM with AS in 14 of 30 cases (Cases 6, 7, 15 , 17, 18, 20 –24, 26, 27 , 29, and 30) in whom CNVs had previously been detected using ES. These SVs were undetectable by ES alone because of unstable genomic coverage, limited fragment size, and analytical limitations. ES typically misses SVs with breakpoints outside coding regions and cannot resolve the configuration of duplications or unbalanced translocations inferred from telomeric CNVs. By contrast, OGM uses ultra-high molecular weight DNA and genome-wide mapping to detect large and complex SVs—including inversions, inverted duplications, and intrachromosomal translocations—outside ES target regions (Cases 6 and 20 –22) and within repetitive regions (Case 26). Importantly, OGM with AS revealed disruptions (Cases 2 and 22) and copy number changes (Cases 12, 15 , 23, 24, 25, and 27 ) in genes that are likely associated with clinical features (Tables 2 and S3) (8/30 cases, 26.7%), clearly demonstrating the utility of OGM with AS following CNV detection. Most novel SVs were observed in cases involving duplications (Cases 6, 7, 15 , 17, 18, 20 –24, 26, 27 , and 30), with only one additional SV found in a deletion case (Case 29). Notably, in cases in whom ES detected both duplication and deletion, OGM clarified the underlying events as unbalanced translocations (Cases 15 , 17, and 26) or inverted duplications (Cases 23 and 27 ), which were undetected by ES. These findings suggest that such CNV patterns should raise a suspicion of hidden SVs, warranting further investigation with OGM. OGM also enables CNV detection through molecule coverage-based analysis, to identify CNVs larger than 500 kb 45 . In the present study, OGM detected CNVs ranging from 238 kb to 18.9 Mb. Although pathogenic genes were identified within these CNVs in six cases (Cases 12, 15 , 23, 24, 25, and 27 ), they had already been detected by ES, suggesting that ES can capture certain pathogenic CNVs if they are covered by baits. OGM and long-read sequencing detect SVs through fundamentally different mechanisms. Although long-read sequencing provides single-nucleotide resolution and accurate breakpoint determination, it is constrained by physical read lengths (10–100 kb), often requiring multiple reads to reconstruct complex SVs 6 . By contrast, OGM analyzes molecules spanning hundreds of kilobases, enabling the better characterization of biallelic CNVs and phasing of copy number changes 46 . For complex rearrangements with multiple breakpoints—such as intrachromosomal translocations and inverted duplications (Cases 20 –22) or chromothripsis (Case 30)—OGM was valuable for structural delineation, with long-read sequencing used for precise breakpoint resolution. In Case 30, discrepancies in breakpoint orientation and copy number between OGM and long-read sequencing illustrated the difficulty of resolving such events with sequencing alone. The genome-wide view of OGM and its ability to detect both CNVs and SVs are particularly advantageous for analyzing chromoanagenesis, including chromothripsis 47 . All 14 SVs detected using OGM were validated with high accuracy. However, the resolution limit (~ 5 kb) of OGM means that smaller variants may be missed 6 , 48 . Breakpoint positions between OGM and long-read sequencing differed by 0.5–385.5 kb (Tables 2 and 3 ), often because of unmapped regions in OGM data. Larger unmapped regions correlated with greater discrepancies. Conversely, smaller gaps allowed near-precise breakpoint localization. In Case 26, in whom all reads included repetitive sequences, OGM accurately detected SVs, whereas long-read sequencing yielded mismapped reads, failing to detect the true breakpoints. This highlights the strength of OGM in repetitive and complex regions, leveraging long-range DNA molecules without sequence-based alignment 11 , 49 . Despite its advantages, OGM cannot fully resolve SVs in centromeres and telomeres 11 . Whole-arm rearrangements such as Robertsonian translocations or isodicentric chromosomes remain challenging because of repetitive elements and gaps in the reference genome 3 , 45 , 47 . Additionally, telomere fusions may obscure insertion sites 45 . However, complete chromosome assemblies (e.g., of the X chromosome) are becoming feasible via the integration of T2T reference genomes and OGM 50 , 51 . In conclusion, duplications or duplication–deletion patterns detected using ES should prompt the suspicion of hidden SVs, particularly when CNVs do not fully explain the phenotype. Highly complex SVs, which are often unresolvable by sequencing alone, can be effectively characterized by combining OGM and long-read sequencing. OGM is thus a powerful tool for identifying complex chromosomal rearrangements within its resolution range. Methods Patients The study was performed on 30 patients with different disease profiles (Table 1 ). All patients were clinically evaluated and referred to our laboratory from July 2015 to August 2022. ES had been performed on the patients using the method described in the following section and all 30 patients had CNVs identified using ES. The ethnicities of patients were Japanese (25 patients) and Brazilian (five patients). The study protocol was approved by the institutional review boards and written informed consent was obtained from patients or their guardians. CNV analysis using whole ES Genomic DNA was extracted from peripheral blood leukocytes using a QuickGene-610L kit (Fujifilm, Tokyo, Japan), according to the manufacturer’s instructions. Genomic DNA samples were sequenced on either the NovaSeq 6000 (Illumina, San Diego, CA, USA) using 150-bp paired-end reads after the enrichment of exonic regions using the Twist Human Comprehensive Exome (Twist BioScience, San Francisco, CA, USA) or the HiSeq2000 or HiSeq2500 (Illumina) with 101-bp paired-end reads after capture using the SureSelect Human All Exon kit (Agilent Technologies, Santa Clara, CA, USA). Exome data processing was performed as previously described 52 . Reads were aligned to GRCh37 using Novoalign ( http://www.novocraft.com/ ), and PCR duplicates were eliminated using Picard ( https://broadinstitute.github.io/picard/ ). The Genome Analysis Toolkit (GATK) ( https://gatk.broadinstitute.org/hc/en-us ) was used to realign indels and recalibrate base quality scores. CNVs were detected from the ES data using XHMM, a statistical tool for copy number analysis 2 , 53 , 54 . In brief, XHMM detects CNVs by analyzing normalized raw exome read depth data with principal component analysis of the complete coding regions. In Case 30, principal component analysis-normalized and filtered z-scores for the whole read depth were obtained, and SignalMap Version 1.9.0.05 (Roche Nimblegen, Madison, WI, USA) was used for visualization purposes. All CNVs were confirmed using quantitative PCR analysis of patients and their unaffected parents, and inheritance was confirmed to be assumed de novo or uniparental (Table 1 ). Genomic DNA was extracted from peripheral blood leukocytes using a QuickGene-610L kit (Fujifilm, Tokyo, Japan), according to the manufacturer’s instructions. Genomic DNA samples were sequenced on either the NovaSeq 6000 (Illumina, San Diego, CA, USA) using 150-bp paired-end reads after the enrichment of exonic regions using the Twist Human Comprehensive Exome (Twist BioScience, San Francisco, CA, USA) or the HiSeq2000 or HiSeq2500 (Illumina) with 101-bp paired-end reads after capture using the SureSelect Human All Exon kit (Agilent Technologies, Santa Clara, CA, USA). Exome data processing was performed as previously described 52 . Reads were aligned to GRCh37 using Novoalign ( http://www.novocraft.com/ ), and PCR duplicates were eliminated using Picard ( https://broadinstitute.github.io/picard/ ). The Genome Analysis Toolkit (GATK) ( https://gatk.broadinstitute.org/hc/en-us ) was used to realign indels and recalibrate base quality scores. CNVs were detected from the ES data using XHMM, a statistical tool for copy number analysis 2 , 53 , 54 . In brief, XHMM detects CNVs by analyzing normalized raw exome read depth data with principal component analysis of the complete coding regions. In Case 30, principal component analysis-normalized and filtered z-scores for the whole read depth were obtained, and SignalMap Version 1.9.0.05 (Roche Nimblegen, Madison, WI, USA) was used for visualization purposes. All CNVs were confirmed using quantitative PCR analysis of patients and their unaffected parents, and inheritance was confirmed to be assumed de novo or uniparental (Table 1 ). OGM Ultra-high molecular weight DNA was extracted from 1.5 million lymphoblastoid cell lines using the SP-G2 Blood and Cell Culture DNA Isolation Kit (Bionano Genomics, San Diego, CA, USA) following the manufacturer’s instructions 55 . DNA was labeled using the DLS-G2 Labeling Kit (Bionano Genomics) for the attachment of fluorophores to a specific six-nucleotide sequence (CTTAAG). The labeled DNA was loaded on a Saphyr chip G3.2 and run on a Saphyr instrument (Bionano Genomics) for an output of 400 Gb, targeting 80× effective coverage, with > 70% of molecules > 150 kb aligning (map rate) at N50 (N50 is defined as the length of the shortest molecule for which equal and longer molecules make up 50% of the total data) of > 230 kb 8 (Table S1 ). De novo assembly, alignment to the GRCh38 reference, and variant annotation of OGM data were performed using Bionano Solve 3.8.1. Visualization by Circos plot and genome browser, filtering, and interpretation of the identified SVs were conducted using Bionano Access 1.8.1. Standard filter settings were adjusted to select only the variants present in the regions of interest identified by previous standard diagnostic tests and in < 1% of control samples. In Case 28, OGM data were analyzed using the T2T reference genome in addition to GRCh38 to observe any differences. Targeted long-read sequencing using AS with GridION Here, 3 µg of the ultra-high molecular weight DNA used in OGM was fragmented to a target size of 50 kb using a Megaruptor 3 DNAFluid Kit (Diagenode, Seraing, Belgium). In cases in which the remaining amount of ultra-high molecular weight DNA was low, 5 µg of genomic DNA extracted from peripheral blood leukocytes was fragmented to a target size of 40 kb using a Megaruptor 3 Shearing Kit (Diagenode). The sheared DNA was used to construct sequencing libraries using an Oxford Nanopore Ligation Sequencing Kit (SQK-LSK114) (Oxford Nanopore Technologies, Oxford, UK), largely following the manufacturer’s instructions 52 , 56 except that enzyme incubation times were doubled, with the final AMPure purification incubation for 10 minutes at 37°C. Approximately 25 fmol of the library was loaded onto a flow cell (FLO-MIN114, R10.4.1) on a GridION (Oxford Nanopore Technologies). Target regions comprising 0.24–0.98% of the whole genome were enriched using the AS option 57 of GridION Mk1 with a BED file that assigned regions of CNVs detected by ES and each of the surrounding total 7.3–29.5 Mb regions (Table S2 ). Sequencing was performed for approximately 3 days, with one additional library loading after nuclease flushing of a flow cell. In cases in which the amount of data was insufficient, new flow cells were used for additional analysis as appropriate. The data were base-called with super accuracy mode and processed into a BAM file using Dorado v.0.7.2 (Oxford Nanopore Technologies) with GRCh38 as a reference. The depth of coverage was calculated using mosdepth v0.3.1 ( https://github.com/brentp/mosdepth ). The mean depth of the target region was 11.72×–47.38× (Table S2 ). dnarrange was used to detect SVs and extract patient-specific SVs by referencing 29 control datasets 55 , 58 . Control datasets were not used in the analysis if dnarrange excluded breakpoints of interest. Subsequently, using lamassemble ( https://gitlab.com/mcfrith/lamassemble ), each group of overlapping SV reads was merged into a consensus sequence and realigned to the reference genome. Next, dnarrange created a dot-plot representation of SV breakpoints. In dot-plots, lines show the alignment to the reference sequence and are drawn in red and blue to denote forward and reverse orientations to the reference genome, respectively. To understand entire SVs, we used the algorithm dnarrange-link to infer the order and orientation of multiple rearrangements 59 . Declarations Acknowledgments We express our gratitude to the families for their involvement in this research. We further acknowledge the great technical assistance provided by Mr. Takafumi Miyama, Ms. Sayaka Sugimoto, Ms. Mai Sato, Ms. Nobuko Watanabe, and Ms. Kaori Takabe at the Department of Human Genetics, Yokohama City University Graduate School of Medicine. We also thank Bronwen Gardner, PhD, from Edanz (https://jp.edanz.com/ac) for editing a draft of this manuscript. The Japan Society for the Promotion of Science (JSPS) KAKENHI Grant-in-Aid for Scientific Research [grant numbers JP22K15901 (A.F.), JP23H02829 (S.M.), JP23H02877 (T.M.), JP23K07229 (Y.U.), JP23K15353 (N.T.), and JP24K02230 (N.M.)]; the Takeda Science Foundation (T.M. and N.M.); the Japan Agency for Medical Research and Development (AMED) [grant numbers JP25ek0109674, JP25ek0109760, JP25ek0109617, JP25ek0109648 and JP25ek0109677 (N.M.)]; and Kawano Masanori Memorial Public Interest Incorporated Foundation for Promotion of Pediatrics (S.M.) provided support for this work. Author contributions L.F. conceptualized and designed the study, reviewed the literature, analyzed the data, and drafted the manuscript; C.A.K., M.T., Y.Miy., N.O., Y.Ma., H.O., A.F., A.D., J.N., N.U., S.H., K.D., M.F., H.M., M.A., J.O., Y.Mis, J.K., T.S., H.A., R.S., H.H., S.Mit., S.O., K.S., Y.I., K.H., N.T., Y.U., E.K., S.Miy., T.M., A.I. analyzed the data and revised the manuscript; A.F. and N.M. supervised all aspects of the study and revised the manuscript. Data availability The datasets for this article are not publicly available because of concerns regarding patients’ anonymity. Requests to access the datasets from qualified researchers should be directed to the corresponding author. There are restrictions on a qualified researcher accessing the data (non-commercial use only and requiring a Data Usage Agreement). Code availability All computational tools used in this study are available as open-source software, and their download links are presented in Methods. 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Supplementary Files SupplementaryDataTableS3.xlsx SupplementaryDataFigS111TableS16.pdf Tables.docx Cite Share Download PDF Status: Published Journal Publication published 26 Mar, 2026 Read the published version in npj Genomic Medicine → Version 1 posted Editorial decision: Revision requested 23 Oct, 2025 Reviews received at journal 13 Oct, 2025 Reviews received at journal 09 Oct, 2025 Reviews received at journal 03 Oct, 2025 Reviewers agreed at journal 01 Oct, 2025 Reviewers agreed at journal 16 Sep, 2025 Reviewers agreed at journal 14 Sep, 2025 Reviewers invited by journal 14 Sep, 2025 Editor assigned by journal 13 Sep, 2025 Submission checks completed at journal 22 Aug, 2025 First submitted to journal 14 Aug, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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1","display":"","copyAsset":false,"role":"figure","size":412267,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eResults of OGM and long-read sequencing in Cases 15 (a–f) and 18 (g–k).\u003c/strong\u003e (a) Circos plot of OGM shows unbalanced translocation involving Chr 17 and 1. (b) OGM results in the genome browser. In Chr 17, a large duplication is visualized as a blue bar in the CNV call track; \u003cem\u003ePAFAH1B1 \u003c/em\u003ewas located in the duplication. Translocation breakpoints are shown in purple on the sample map between two matching chromosomes. Deletion of Chr 1 should have been shown as a red bar in the CNV call track, but is not shown in this case despite copy number losses of 0.9–1.1. The numbers are the breakpoint positions. Arrows A and B indicate that these maps are the forward orientations to the reference genome. (c) Dot-plot of the consensus sequence from long-read sequencing data. Red lines show the forward orientation to the reference sequences. Vertical pale stripes show annotations in the reference genome with different colors: transposable elements (pale blue, reverse-strand; pale pink, forward-strand), tandem repeats (purple), protein-coding sequences (dark green), and exons (green). The numbers below the dot-plot are breakpoint positions. (d) Electrophoresis image of polymerase chain reaction products. (e) Scheme of translocation and primers. (f) Upper and lower diagrams show Sanger sequencing electropherograms of der(1) and der(17), respectively, at breakpoints. Rearrangement junction sequence (middle line) and matching reference sequence (top and bottom lines) are shown in pink and sky blue. der(1) includes a 3-bp insertion and der(17) includes a 2-bp insertion, shown in black. (g) Duplication is indicated as a purple dot in the SV track and a blue line in the CNV track of the Circos plot. (h) Large duplication is visualized as a blue bar in the CNV call track and a blue line in the SV call track in the genome browser. (i) Dot-plot of the consensus sequence from long-read sequencing data. (j) Dot-plot containing tandem duplication region created from long-read sequencing data using dnarrange. (k) Scheme of tandem duplication. Molecular karyotypes in the two cases are described in Table S4. Chr, chromosome; CNV, copy number variant; SV, structural variant.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7371701/v1/d9c479c82f28e31878280b55.png"},{"id":91959657,"identity":"aada816f-4086-409c-8312-8f2152757228","added_by":"auto","created_at":"2025-09-23 07:39:58","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":342781,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eResults of OGM and long-read sequencing in Cases 6 (a–e) and 23 (f–i).\u003c/strong\u003e (a) Circos plot of Chr 21 in OGM shows duplication as a blue line in the CNV track and inversion as a light blue dot in the SV track. (b) OGM results in the genome browser. Large duplication is visualized as a blue bar in the CNV call track and inversion is visualized at the end of arrow B. Downstream of the inversion (21q22.3–qter) shows copy number losses of 0.9–1.74 in the genome browser, and the 3′ end of the inversion is the end of the long arm of Chr 21. (c) Dot-plot of the consensus sequence from long-read sequencing data. Red and blue lines show the forward and reverse orientations to the reference sequences, respectively. (d) Dot-plot of duplication and inversion regions created from long-read sequencing data using dnarrange. (e) Scheme of SVs. (f) Circos plot of Chr 9 shows deletion and duplication as red and blue lines, respectively, in the CNV track; duplication is indicated as a purple dot in the SV track. (g) The entire Chr 9 (upper diagram) and its enlargement within the dotted square (lower diagram) in the genome browser. Large deletion and duplication are visualized as red and blue bars, respectively, in the CNV call track. Inverted duplication is indicated by a blue line in the SV call track and is shown in the sample map below. \u003cem\u003eNFIB\u003c/em\u003eis located at the boundary between deletion and duplication. (h) Dot-plot of the consensus sequence from long-read sequencing data. (i) Scheme of the inverted duplication. Molecular karyotypes of the two cases are described in Table S4. Chr, chromosome; CNV, copy number variant; SV, structural variant.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7371701/v1/1b14d5eb34497a88eff11dc0.png"},{"id":91959661,"identity":"fcd05b5a-aea1-4ebd-aaca-44d1b009c710","added_by":"auto","created_at":"2025-09-23 07:39:58","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":203365,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eResults of \u0026nbsp;OGM and long-read sequencing in Case 20.\u003c/strong\u003e (a) Circos plot in Chr X shows a large inverted duplication. This large inverted duplication was detected as an intrachromosomal translocation indicated by a magenta line, with the large duplication as a blue line in the CNV track, and a small duplication as a purple dot in the SV track at the edge of the large duplication. (b) Large duplication is visualized as a blue bar in the CNV call track and inverted duplication is visualized as a blue line in the SV call track of the genome browser. The numbers are the breakpoint positions. Arrow A’ indicates inverted duplication and arrow A’ to B indicates intrachromosomal translocation. (c and d) Dot-plots of the consensus sequence from long-read sequencing data. (e) Dot-plot containing inverted duplication and intrachromosomal translocation regions created from long-read sequencing data using dnarrange. (f) Scheme of SVs. Molecular karyotype is described in Table S4. Chr, chromosome; CNV, copy number variant; SV, structural variant.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7371701/v1/eff672df71c5a78527cd2668.png"},{"id":91963378,"identity":"6b500fa3-bcdc-47b4-8c4e-dfc2ae90194d","added_by":"auto","created_at":"2025-09-23 08:03:58","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":401493,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eResults of OGM and long-read sequencing in Case 29.\u003c/strong\u003e(a) Circos plot of translocations of Chr 12 and 14. Magenta lines indicate one intrachromosomal\u003c/p\u003e\n\u003cp\u003etranslocation in Chr 12 and two reciprocal translocations between Chr 12 and 14. A deletion is shown as a red line in the CNV track of Chr 12, and three inversions are shown as light blue dots in the SV tracks of both chromosomes. (b) Genome browser in Chr 12. Large deletion is visualized as a red bar in the CNV call track and inversion is visualized as blue lines in the SV call track at both ends of the deletion. Arrow C’ in the sample map is a fragment of arrow C in the reference. Arrow B indicates inversion and arrows B and C indicate intrachromosomal translocation. Yellow sample maps lead to maps of Chr 14 (shown in Fig. 4c). (c) The genome browser in Chr 14. Arrow D indicates inversion, shown as blue lines in the SV call track. Yellow sample maps lead to maps of Chr 12 (shown in Fig. 4b). (d–i) Dot-plot of the consensus sequence from long-read sequencing data. (j and k) Dot-plots in derivative Chr 12 (j) or 14 (k) created from long-read sequencing data using dnarrange. Arrows C–D and F–G indicate reciprocal translocation between Chr 12 and 14. (l) Scheme of reciprocal translocation. Molecular karyotype is described in Table S4. Chr, chromosome; CNV, copy number variant; OGM, optical genome mapping; SV, structural variant.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7371701/v1/4f68341a447198549f7c1392.png"},{"id":91959665,"identity":"f61fd377-c113-4501-8249-77e832f10e36","added_by":"auto","created_at":"2025-09-23 07:39:58","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":308712,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eResults of the CNV analysis using ES data, OGM, and long-read sequencing in Case 30. \u003c/strong\u003e(a) CNV analysis of XHMM using ES data detected eight duplications in Chr 22, indicated by blue bars (Ⅰ–Ⅷ).\u003cstrong\u003e \u003c/strong\u003eThe x-axis shows physical positions and the y-axis shows z-scores. \u003cstrong\u003e(\u003c/strong\u003eb) Circos plot of Chr 22 in OGM. Intrachromosomal translocations are indicated by magenta lines with numbers 1, 2, 4, and 6–8. An inversion is indicated as a light blue dot with the number 3, and an inverted duplication is indicated as a purple dot with the number 5 in the SV track. Blue lines in the CNV track indicate five duplications (Ⅱ, Ⅲ, Ⅴ, Ⅶ, and Ⅷ), one of which contains a different duplication (Ⅵ), making a total of six duplications that correspond to those in (a). Two duplications (Ⅰ and Ⅳ) should have been originally shown as blue bars in the CNV call track, but these two duplications are not shown in this case despite copy number gains of 2.58–2.94 and 2.36–2.62, respectively. (c) Dot-plot of chromothripsis manually connected from long-read sequencing data using dnarrange. The top of the dot-plot shows genes located in this region, and the six genes in red squares were disrupted by the chromothripsis. The blue areas (Ⅰ–Ⅷ) show eight duplications that correspond to those in (a). The sizes of the eight duplications from the long-read sequencing data are shown below the dot-plot. Molecular karyotype is described in Table S4. Chr, chromosome; CNV, copy number variant; ES, exome sequencing; OGM, optical genome mapping; SV, structural variant.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7371701/v1/cbb7b26e69ef5ddcc2af3838.png"},{"id":105754816,"identity":"0c4d49d7-10b2-4ddb-ad3b-1d12cb14d72b","added_by":"auto","created_at":"2026-03-30 16:22:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2954188,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7371701/v1/9901aafe-1be1-4121-b471-b1540da93ac1.pdf"},{"id":91960679,"identity":"6f7c29ca-1341-44c1-addf-fd87577d4095","added_by":"auto","created_at":"2025-09-23 07:47:58","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":31844,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryDataTableS3.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7371701/v1/29c8d27cce18a54fafeacd50.xlsx"},{"id":91959682,"identity":"57dbe576-f4a7-4249-9df3-43d3bb0fa7af","added_by":"auto","created_at":"2025-09-23 07:39:58","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":3680634,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryDataFigS111TableS16.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7371701/v1/72c1924b4f14d6d70fd0b4b5.pdf"},{"id":91959660,"identity":"b4067793-972c-4d74-9973-bdeb0d5890b8","added_by":"auto","created_at":"2025-09-23 07:39:58","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":190743,"visible":true,"origin":"","legend":"","description":"","filename":"Tables.docx","url":"https://assets-eu.researchsquare.com/files/rs-7371701/v1/4856e0f7ffffec4ce474141b.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Completely resolved structural variants by optical genome mapping with adaptive sampling from CNV discovery","fulltext":[{"header":"Introduction","content":"\u003cp\u003eStructural variations (SVs)\u0026mdash;defined as genomic alterations larger than 50 base pairs (bp) and including duplications, deletions, inversions, translocations, and insertions\u0026mdash;constitute the majority of variable nucleotides in the human genome and contribute significantly to phenotypic diversity \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Although exome sequencing (ES) enables the detection of copy number variants (CNVs) \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e, it frequently fails to capture SV breakpoints, primarily because of the limited coverage of capture regions and technical limitations such as polymerase chain reaction (PCR) and hybridization biases in GC-rich regions, as well as poor alignment in low-complexity regions.\u003c/p\u003e\u003cp\u003eEven with genome sequencing, SV detection remains challenging because of the wide range of SV types and sizes and their frequent localization within repetitive genomic regions. These complexities hinder both sensitivity and specificity in SV calling, especially for structurally complex and repetitive regions. As a result, many pathogenic SVs likely remain undetected, and the reliable identification of such variants from short-read sequencing data continues to be a major technical and computational challenge \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eSeveral methodologies have been used for SV detection, including conventional karyotyping, fluorescence \u003cem\u003ein situ\u003c/em\u003e hybridization (FISH), chromosomal microarray analysis, and long-read sequencing. More recently, optical genome mapping (OGM) has emerged as a promising technique for the comprehensive analysis of SVs. Unlike sequencing-based methods, OGM uses high-resolution fluorescence imaging of ultra-high molecular weight DNA to detect structural changes without nucleotide-level sequencing. Long-read sequencing produces reads typically ranging from 10 to 100 kilobases (kb), whereas OGM analyzes DNA molecules exceeding 150 kb, providing broader genome coverage (\u0026gt;\u0026thinsp;80\u0026times;) albeit at lower breakpoint resolution \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eOGM identifies SVs through the \u003cem\u003ede novo\u003c/em\u003e assembly of fluorescently labeled DNA molecules using a specific six-base sequence motif (CTTAAG), which occurs on average every 5 kb across the genome \u003csup\u003e\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. This method enables the detection of a wide range of structural alterations, including insertions and deletions (\u0026gt;\u0026thinsp;500 bp), duplications (\u0026gt;\u0026thinsp;50 kb), inversions and translocations (\u0026gt;\u0026thinsp;50\u0026ndash;70 kb), chromosomal aneuploidy, absence of heterozygosity (AOH), triploidy, and copy-neutral events \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. In this regard, OGM may outperform traditional sequencing-based platforms for identifying large and complex SVs.\u003c/p\u003e\u003cp\u003eIn the present study, we aimed to use OGM to comprehensively characterize constitutional SVs that were initially identified as CNVs using ES. Furthermore, we used targeted Oxford Nanopore long-read sequencing with adaptive sampling (AS) to resolve the breakpoint structures of these newly discovered SVs at nucleotide resolution.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eWe applied OGM to 30 cases (Tables \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e and S1) and identified only the expected ES-identified CNVs in 16 cases (Cases 1, 2, 3, 4, 5, 8, 9, 10, 11, 12, 13, 14, 16, 19, 25, and 28). By contrast, previously undetected SVs were revealed in the remaining 14 cases (Fig. \u003cspan class=\"InternalRef\"\u003eS1\u003c/span\u003e, Tables \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). The newly discovered SVs in the latter 14 cases included: three translocations (Cases \u003cspan class=\"InternalRef\"\u003e15\u003c/span\u003e, 17, and 26), three tandem duplications (Cases 7, 18, and 24), one duplication with inversion (Case 6), two inverted duplications (Cases 23 and \u003cspan class=\"InternalRef\"\u003e27\u003c/span\u003e), three intrachromosomal translocations with inverted duplications (Cases \u003cspan class=\"InternalRef\"\u003e20\u003c/span\u003e, 21, and 22), one complex intrachromosomal rearrangement involving translocation, inversion, and additional translocation (Case 29), and one chromothripsis (Case 30).\u003c/p\u003e\n\u003ctable id=\"Tab1\" border=\"1\"\u003e\u003c/table\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003eTo further characterize the SVs in all 30 cases, we used Oxford Nanopore targeted long-read sequencing with AS (Table \u003cspan class=\"InternalRef\"\u003eS2\u003c/span\u003e). This approach allowed us to precisely determine the SV breakpoints at the nucleotide level and generate dot-plots to visualize the identified SVs. Detailed results for the 30 cases are provided in the following sections.\u003ctable id=\"Tab3\" border=\"1\"\u003e\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eDeletions (Cases 1, 2, 3, 4, 5, 8, 9, 10, 11, 12, 13, 14, 16, 19, and 25)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe performed OGM in 16 cases with ES-based deletions, and detected only simple (expected) deletions in 15 cases; however, a complex chromosomal rearrangement was identified in one case (Case 29) (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Subsequent targeted long-read sequencing enabled the detailed investigation of haploinsufficient genes involved in these deletions (Tables \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e and S3). Breakpoints at nucleotide resolution were successfully determined in 11 of the 15 cases with simple deletions: interstitial deletions in Cases 3, 8, 9, 10, 11, 12, 14, 16, 19, and 25, and a deletion involving 4q telomeric sequences (TTAGGG) in Case 2 (Figs. S2 and S3, Table S4).\u003c/p\u003e\n\u003cp\u003eAmong these 11 cases, ES-based analysis did not identify haploinsufficient genes, although we identified \u003cem\u003eSUMO1\u003c/em\u003e (pHaplo score\u0026thinsp;=\u0026thinsp;0.900 \u003csup\u003e12\u003c/sup\u003e) in Case 12 and \u003cem\u003eCOL11A1\u003c/em\u003e (pHaplo score\u0026thinsp;=\u0026thinsp;0.894 \u003csup\u003e12\u003c/sup\u003e) in Case 25 (Table S3 \u003csup\u003e13\u003c/sup\u003e). \u003cem\u003eSUMO1\u003c/em\u003e deletion causes orofacial cleft (OMIM# 613705) and \u003cem\u003eSUMO1\u003c/em\u003e haploinsufficiency has been associated with cleft lip and palate, consistent with the phenotype observed in Case 12 \u003csup\u003e14,15\u003c/sup\u003e. In Case 25, ES had already identified \u003cem\u003eKCNA2\u003c/em\u003e (OMIM# 616366) as a cause of seizures and global developmental delay \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Our analysis additionally revealed \u003cem\u003eCOL11A1\u003c/em\u003e, whose haploinsufficiency causes Marshall (OMIM# 154780) and Stickler (OMIM# 604841) syndromes, both of which are associated with abnormal facial shape, failure to thrive, and short stature, as observed in Case 25 \u003csup\u003e18,19\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCTBP1\u003c/em\u003e was disrupted by the deletion breakpoint in Case 2 (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). \u003cem\u003eCTBP1\u003c/em\u003e aberration is associated with hypotonia, ataxia, developmental delay, and tooth enamel defect syndrome (OMIM# 617915) in an autosomal dominant fashion, and may influence the neurological features observed in this case \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eIn Cases 1, 4, 5, and 13, although deletions were identified using OGM (Tables \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e and S4), the breakpoint determination of deletions using long-read sequencing was unsuccessful. In these cases, segmental duplications of approximately 247 kb (Case 1), 161\u0026ndash;163 kb (Case 4), 218 kb (Case 5), and 39\u0026ndash;42 kb (Case 13) were exactly mapped to deletion breakpoints (Fig. S4). Because N50 in the long-read sequencing data of Cases 1, 4, 5, and 13 were 4551, 6483, 7813, and 23790 bp, respectively, long-read sequencing cannot cover these segmental duplications. Using Blast Like Alignment Tool (BLAT; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://genome.ucsc.edu/cgi-bin/hgBlat\u003c/span\u003e\u003c/span\u003e) \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e to analyze the sequence homology of the pairs of segmental duplications mapped to the deletion breakpoints in Cases 1, 4, 5, and 13, high sequence homology was identified: 99.7%, 99.1%, 99.6%, and 98.9% for the 40-, 10-, 20-, and 39-kb segmental duplications, respectively (Fig. S4b, d, f, and h). Therefore, although precise breakpoint determination was not possible, the involvement of non-allelic homologous recombination (NAHR) is strongly indicated as a mechanism for generating these deletions \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. OGM, which analyzes DNA molecules exceeding 150 kb, is therefore advantageous for mapping relatively large segmental duplications compared with long-read sequencing.\u003c/p\u003e\n\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003eDuplication (Case 28)\u003c/h2\u003e\n \u003cp\u003eWe identified an ES-based duplication in Case 28. OGM detected the expected duplication at the terminal region of chromosome 2q, as identified using ES (Fig. S5a). However, we were unable to fully characterize the duplication using OGM (Fig. S5b, Table S4), even when referring to the telomere-to-telomere (T2T) reference genome (instead of GRCh38).\u003c/p\u003e\n \u003cp\u003eLong-read sequencing also failed to confirm a duplication at the 2q terminal region. This was likely because of the presence of many repetitive sequences such as DNA transposons, long terminal repeat (LTR) retrotransposons, and short interspersed nuclear elements (SINE), as well as long interspersed nuclear elements (LINE) of non-LTR retrotransposons at around the breakpoint, which hampered the mappability of the duplication breakpoint (Fig. S5b). Notably, the OGM-detected duplication did not include any known triplosensitive genes associated with the clinical features of this case (Table S3).\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eUnbalanced reciprocal translocations (Cases , 17, and 26)\u003c/h3\u003e\n\u003cp\u003eIn Cases \u003cspan class=\"InternalRef\"\u003e15\u003c/span\u003e, 17, and 26, unbalanced reciprocal translocations\u0026mdash;characterized by combined terminal duplications and deletions\u0026mdash;were detected using ES. OGM also identified unbalanced translocations in these three cases.\u003c/p\u003e\n\u003cp\u003eCase 15 presented clinically with West syndrome, hypoplasia of the corpus callosum, and aortic regurgitation. In this case, unbalanced translocation was detected using OGM and AS, with a 3.5-Mb deletion at 1p36.33\u0026ndash;p36.32 and a 3.8-Mb duplication at 17p13.3\u0026ndash;p13.2 (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ea, \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eb, Tables \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e and S4). The deletion encompassed \u003cem\u003eGABRD\u003c/em\u003e (pHaplo score\u0026thinsp;=\u0026thinsp;0.807 \u003csup\u003e12\u003c/sup\u003e), which is associated with generalized epilepsy with febrile seizures plus (OMIM# 613060) (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eAlthough no known triplosensitive genes were initially identified within the 17p13.3\u0026ndash;p13.2 duplication, precise mapping using OGM identified that this duplication also encompassed \u003cem\u003ePAFAH1B1\u003c/em\u003e, with pTriplo score\u0026thinsp;=\u0026thinsp;0.998 \u003csup\u003e12\u003c/sup\u003e (Table S3). Duplications of \u003cem\u003ePAFAH1B1\u003c/em\u003e have been linked to West syndrome \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e, seizures, and a range of structural brain anomalies including abnormalities of the corpus callosum, cerebellum, posterior fossa, and skull \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. Thus, the duplicated \u003cem\u003ePAFAH1B1\u003c/em\u003e might account at least in part for the brain abnormalities observed in this patient. To confirm the origin of this unbalanced translocation, breakpoint-spanning PCR was performed using long-read sequencing data (primers listed in Table S5); this confirmed its paternal origin (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ed and e). Sanger sequencing of the translocation breakpoints further identified a 3-bp insertion on der(1) and a 2-bp insertion on der(17) (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ef). Although one gene was disrupted by a translocation (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e), none of the affected genes were associated with the clinical features observed in Case \u003cspan class=\"InternalRef\"\u003e15\u003c/span\u003e.\u003c/p\u003e\n\u003cp\u003eIn Case 17, characterized by Klippel\u0026ndash;Feil syndrome, cleft lip and palate, dysphagia, hearing impairment, and esotropia, OGM with AS identified an unbalanced translocation with a 6.7-Mb deletion at 21q22.2\u0026ndash;q22.3 and a 9.9-Mb duplication at 14q32.13\u0026ndash;q32.33 (Fig. S6a\u0026ndash;c and Table S4).\u003c/p\u003e\n\u003cp\u003eTo investigate the origin of this unbalanced rearrangement, breakpoint-spanning PCR was performed using available maternal DNA (primers listed in Table S6). This analysis confirmed the absence of a maternal origin for this rearrangement (Fig. S6d). Furthermore, Sanger sequencing of the breakpoint PCR products revealed a simple unbalanced translocation (Fig. S6f). No known genes associated with the clinical symptoms observed in Case 17 were disrupted, deleted, or duplicated by this translocation (Tables \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e and S3).\u003c/p\u003e\n\u003cp\u003eIn Case 26, presenting with seizures, global developmental delay, abnormal facial features, cerebral hemorrhage, laryngomalacia, low-set ears, atresia of the external auditory canal, and impaired ocular abduction, we identified an unbalanced reciprocal translocation using OGM with AS (Fig. S7a\u0026ndash;c and Table S4). This translocation included a 4.6-Mb duplication at 5p15.33\u0026ndash;p15.32 and a 7.4-Mb deletion at 18q22.3\u0026ndash;q23.\u003c/p\u003e\n\u003cp\u003eInitial attempts to detect the breakpoint using dnarrange (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/mcfrith/dnarrange\u003c/span\u003e\u003c/span\u003e \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e) with long-read sequencing data were unsuccessful. We subsequently performed the manual inspection of soft-clipped reads at the 5p15.32 and 18q22.3 regions using Integrative Genomics Viewer (IGV) (Fig. S7d and e). However, many soft-clipped reads originating from chromosomes 5 and 18 mapped to chromosome 4 and another region of chromosome 5, as shown in the supplementary alignments (Fig. S7f).\u003c/p\u003e\n\u003cp\u003eAt the chromosome 18 breakpoint, several soft-clipped reads were also aligned to chromosomes 2, 9, and 14 (Fig. S7e and g). These regions contained repetitive sequences such as LTR retrotransposons and LINE of non-LTR retrotransposons. The presence of these repeats likely contributed to the mapping ambiguity, complicating accurate breakpoint identification despite moderate to very high long-read coverage, with mapping quality scores ranging from 21\u0026ndash;60 \u003csup\u003e27\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eInterestingly, the lengths of these mismapped long reads ranged from approximately 11\u0026ndash;37 kb, whereas the repetitive sequences in the supplementary alignment regions ranged from approximately 0.2\u0026ndash;6 kb. This discrepancy indicates that the read lengths were sufficient to span the unique sequences flanking the repetitive regions. These findings imply that OGM, which analyzes relatively long DNA molecules (~\u0026thinsp;150 kb), may provide superior breakpoint resolution in genomic regions containing complex repetitive sequences. No known genes associated with the clinical symptoms observed in Case 26 were affected by the copy-number changes resulting from the unbalanced translocation (Table S3), and no genes were disrupted by the translocation itself (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eTandem duplications (Cases 7, 18, and 24)\u003c/h3\u003e\n\u003cp\u003eOGM identified tandem duplications in three cases (Figs. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eg, \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eh, S8a, S8b, S8f, and S8g), which had previously been detected by ES. Long-read sequencing data confirmed the breakpoints in these cases (Figs. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ei, S8c, and S8h) and enabled the reconstruction of tandem duplications through dot-plots (Figs. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ej, S8d, and S8i).\u003c/p\u003e\n\u003cp\u003eCase 7, who was clinically suspected of having Coffin\u0026ndash;Siris syndrome, exhibited a 2.2-Mb tandem duplication at 8p23.1 by OGM with AS (Fig. S8b, Tables \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e and S4). This duplication, previously identified using ES, encompasses \u003cem\u003eSOX7\u003c/em\u003e (pTriplo score\u0026thinsp;=\u0026thinsp;0.421 \u003csup\u003e12\u003c/sup\u003e) and \u003cem\u003eGATA4\u003c/em\u003e (pTriplo score\u0026thinsp;=\u0026thinsp;0.916 \u003csup\u003e12\u003c/sup\u003e), and is consistent with 8p21.3 duplication syndrome (Table S3), which is associated with developmental delay, dysmorphism, hypotonia, visual impairment, and congenital heart disease \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). These findings align with the clinical presentation of the patient, and no additional aberrant genes relevant to the phenotype were detected using OGM. Although one gene was disrupted by the tandem duplication breakpoint (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e), it has not been associated with any of the clinical features observed in Case 7.\u003c/p\u003e\n\u003cp\u003eIn Case 18, OGM with AS identified a 1.5-Mb tandem duplication at 2q24.3 (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eh, Tables \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e and S4) that encompassed key sodium channel genes such as \u003cem\u003eSCN1A, SCN2A, SCN3A, SCN7A\u003c/em\u003e, and \u003cem\u003eSCN9A\u003c/em\u003e, all of which had been previously detected using ES (Tables \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e and S3). The clustering of these sodium channel genes at 2q24.3 is strongly associated with early infantile epileptic spasms \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e, in line with the clinical phenotype observed in this case. OGM did not reveal any additional aberrant genes that would further explain the patient\u0026rsquo;s clinical symptoms. \u003cem\u003eSCN7A\u003c/em\u003e was observed to be disrupted by the tandem duplication (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eIn Case 24, OGM detected a 606-kb tandem duplication at 19q13.33 (Fig. S8g, Tables \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e and S4) that encompassed \u003cem\u003ePRR12\u003c/em\u003e (pTriplo score\u0026thinsp;=\u0026thinsp;0.999 \u003csup\u003e12\u003c/sup\u003e) (Table S3). \u003cem\u003ePRR12\u003c/em\u003e abnormality is implicated in neuro-ocular syndrome (OMIM# 619539), an autosomal dominant condition that is characterized by microcephaly, facial abnormalities, congenital heart defects, global developmental delay, and intellectual disability \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. Although this finding potentially explains part of the patient\u0026rsquo;s phenotype (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e), its precise contribution remains uncertain because of a lack of corroborating evidence. Two genes were disrupted by a tandem duplication (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e) but neither was associated with the observed clinical features.\u003c/p\u003e\n\u003ch3\u003eInversion and duplication (Case 6)\u003c/h3\u003e\n\u003cp\u003eIn Case 6, we newly identified a 6.2-Mb inversion at 21q22.2\u0026ndash;q22.3 and a 218-kb duplication at 21q22.2 using OGM with AS. The duplication had previously been detected using ES (Tables \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e and S4). OGM analysis revealed that the inversion was located immediately downstream of the duplication (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ea and b), thus highlighting a limitation of ES, which typically fails to detect breakpoints outside coding regions. Long-read sequencing data further illustrated these SVs through dot-plot reconstruction (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ec and d). However, no aberrant triplosensitive genes associated with hereditary spastic paraplegia or autism were identified within these regions (Table S3). Although two genes were disrupted by the SVs (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e), neither has been associated with hereditary spastic paraplegia or autism.\u003c/p\u003e\n\u003ch3\u003eInverted duplications (Cases 23 and 27)\u003c/h3\u003e\n\u003cp\u003eOGM identified inverted duplications in Cases 23 and \u003cspan class=\"InternalRef\"\u003e27\u003c/span\u003e, involving complex rearrangements that combined deletions and duplications (Figs. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ef, \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eg, S9a, and S9b). Long-read sequencing successfully confirmed the breakpoints in both cases (Figs. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eh, S9c and S9d).\u003c/p\u003e\n\u003cp\u003eIn Case 23, who was clinically suspected to have Cornelia de Lange syndrome, OGM revealed a 14.3-Mb deletion and an 851-kb duplication at 9p22.3, resulting in inverted duplication (Tables \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e and S4). Notably, \u003cem\u003eNFIB\u003c/em\u003e (pHaplo score\u0026thinsp;=\u0026thinsp;0.999 \u003csup\u003e12\u003c/sup\u003e) was disrupted at intron 1 by the SV (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eg, Tables \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e and S3). Haploinsufficiency of \u003cem\u003eNFIB\u003c/em\u003e causes macrocephaly with impaired intellectual development (OMIM# 618286) as well as intellectual disability and dysmorphic features \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e31\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. These clinical features are consistent with those observed in Case 23, including intellectual disability and dysmorphic features.\u003c/p\u003e\n\u003cp\u003eCase 27 involved an inverted duplication rearrangement detected by OGM with AS (Tables \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e and S4), similar to a previously reported case \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. Within the 18.5-Mb deletion at 9p22.1\u0026ndash;24.3, both \u003cem\u003eNFIB\u003c/em\u003e and \u003cem\u003eSMARCA2\u003c/em\u003e were identified (Fig. S9b and Table S3). As previously mentioned, \u003cem\u003eNFIB\u003c/em\u003e haploinsufficiency can contribute to intellectual impairment, dysmorphic facial features, and a high palate (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). \u003cem\u003eSMARCA2\u003c/em\u003e (pHaplo score\u0026thinsp;=\u0026thinsp;0.999 \u003csup\u003e12\u003c/sup\u003e) is associated with blepharophimosis-impaired intellectual development syndrome (OMIM# 619293) and Nicolaides\u0026ndash;Baraitser syndrome (OMIM# 601358) in an autosomal dominant manner, and its intragenic deletions reportedly cause intellectual disability, seizures, and dysmorphic features \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e34\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. Although \u003cem\u003eSMARCA2\u003c/em\u003e deletion has not been clearly established as a distinct deletion syndrome, it has been previously reported with limited clinical information \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. By contrast, the adjacent 19.7-Mb duplication did not contain any known genes associated with human diseases (Table S3). Notably, although one gene was disrupted by inverted duplication in each of Cases 23 and \u003cspan class=\"InternalRef\"\u003e27\u003c/span\u003e (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e), neither gene was associated with the clinical features observed in these cases.\u003c/p\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003eIntrachromosomal translocations and inverted duplications (Cases \u003cspan class=\"InternalRef\"\u003e20\u003c/span\u003e\u0026ndash;22)\u003c/h2\u003e\n \u003cp\u003eUsing OGM with AS, we identified novel intrachromosomal translocations and inverted duplications in three cases (Cases \u003cspan class=\"InternalRef\"\u003e20\u003c/span\u003e\u0026ndash;22) in whom duplications or combined deletions and duplications had initially been detected by ES. OGM revealed a range of complex structural rearrangements in these cases.\u003c/p\u003e\n \u003cp\u003eCase 20 involved an inverted duplication deletion and intrachromosomal translocation (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ea and b, Tables \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e and S4). In Case 21, an inverted duplication and two intrachromosomal translocations were identified (Fig. S10a and b, Tables \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e and S4). Case 22 exhibited an inverted duplication and intrachromosomal translocation (Fig. S10h and i, Tables \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e and S4).\u003c/p\u003e\n \u003cp\u003eRegarding these chromosomal rearrangements, Case \u003cspan class=\"InternalRef\"\u003e20\u003c/span\u003e included an 8.4-Mb duplication at Xq21.33\u0026ndash;q22.3, whereas Case 21 harbored a 439-kb duplication at Xq22.2, as detected by OGM. Notably, the intrachromosomal translocations in these cases were positioned adjacent to their respective duplications, a feature that was missed by ES because of the copy-neutral nature of these SVs (Figs. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eb, \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ef, S10b, and S10g). Importantly, Case \u003cspan class=\"InternalRef\"\u003e20\u003c/span\u003e had been previously diagnosed with \u003cem\u003ePCDH19\u003c/em\u003e-related epilepsy syndrome, and \u003cem\u003ePCDH19\u003c/em\u003e is located within the duplicated region detected by ES \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e (Tables \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e and S3). In Case 21, \u003cem\u003ePLP1\u003c/em\u003e (which causes Pelizaeus\u0026ndash;Merzbacher disease) was identified within the Xq22.2 duplication, consistent with earlier reports of complex \u003cem\u003ePLP1\u003c/em\u003e rearrangements, including triplications and inverted duplications \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e38\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e (Tables \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e and S3). However, in both cases, the newly resolved SVs identified by OGM and long-read sequencing did not reveal any additional pathogenic variants that might explain the patients\u0026rsquo; clinical features (Table S3). Although two and one genes were disrupted by SVs in each case (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e), none of the genes were associated with the observed clinical features of Cases \u003cspan class=\"InternalRef\"\u003e20\u003c/span\u003e and 21.\u003c/p\u003e\n \u003cp\u003eBy contrast, Case 22 exhibited a more complex pattern involving a 10.8-Mb duplication at 18p11.32\u0026ndash;p11.22, a 2.8-Mb duplication at 18q21.31\u0026ndash;21.33, and an 18.9-Mb deletion at 18q21.33\u0026ndash;q23 (Fig. S10i and m). Within the deleted 18q21.33\u0026ndash;q23 region, ES identified \u003cem\u003eTSHZ1\u003c/em\u003e and \u003cem\u003eNFATC1\u003c/em\u003e, which have been associated with auricular deformities, hearing impairment \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e40\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e, and congenital heart disease \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e42\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e (Tables \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e and S3). Nevertheless, in the newly characterized SVs using OGM and long-read sequencing, no additional candidate pathogenic genes were identified that might account for the patient\u0026rsquo;s clinical presentation, which included features potentially resembling Cornelia de Lange syndrome (Table S3). Additionally, \u003cem\u003ePIEZO2\u003c/em\u003e, which is associated with Marden\u0026ndash;Walker syndrome (OMIM# 248700) through an autosomal dominant mechanism, was disrupted by SVs in Case 22 (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). \u003cem\u003ePIEZO2\u003c/em\u003e has also been reported as associated with Cornelia de Lange syndrome \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e, and may be involved in the phenotype observed in this case.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eIntrachromosomal translocation, inversion, and interchromosomal translocation in Case 29\u003c/h3\u003e\n\u003cp\u003eIn Case 29, who presented with Ehlers\u0026ndash;Danlos syndrome, joint laxity, arthritis, and mild intellectual disability, ES previously identified a 5.2-Mb deletion at 12q21.1\u0026ndash;q21.2. OGM further revealed an intrachromosomal translocation and inversion within chromosome 12, an inversion within chromosome 14, and an interchromosomal translocation between chromosomes 12 and 14 (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003ea\u0026ndash;c). Long-read sequencing precisely determined all of the breakpoints (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003ed\u0026ndash;i), confirming a complex reciprocal translocation between chromosomes 12 and 14 (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003ej\u0026ndash;l and Table S4).\u003c/p\u003e\n\u003cp\u003eThe complex rearrangement involved chromosomes 12 and 14, with reciprocal inverted insertions, partial deletions, and inversion of multiple segments. Despite the complex rearrangement, no clearly haploinsufficient gene associated with the patient\u0026rsquo;s phenotype was identified within the deleted region (Table S3). Two genes were disrupted by a reciprocal translocation (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e), but neither was associated with the clinical features observed in Case 29. The derivative chromosome 12 harbored the 5.2-Mb deletion at 12q21.1\u0026ndash;q21.2, which was joined to chromosome 14 without a copy number change. Therefore, although the deletion was detectable by ES-based CNV analysis, the reciprocal translocation itself was not identified. Because the deleted region did not encompass any previously known disease-associated genes that would explain the clinical features, this case clearly demonstrates the limitations of ES for detecting complex SVs and highlights the added value of OGM and long-read sequencing in cases with no apparent clinical features.\u003c/p\u003e\n\u003ch3\u003eChromothripsis (Case 30)\u003c/h3\u003e\n\u003cp\u003eIn Case 30, who presented with vitreoretinal degeneration, short stature, growth delay, abnormal facial shape, calcified skin lesions, and ventricular septal defect, ES detected eight duplications in chromosome 22, implying chromothripsis (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003ea). Based on ES data, the CNV sizes of the eight duplications at 22q12.1\u0026ndash;q13.33 ranged from 107\u0026ndash;437 kb. OGM analysis revealed six intrachromosomal translocations, one deletion, one inversion, and one inverted duplication with 46,XY,(22q)cth at 22q11.21\u0026ndash;q13.33 (Figs. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003eb, S11 and Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). Although we attempted to reconstruct the full spectrum of SVs based on the OGM results, the SVs identified by OGM did not completely match those detected by dnarrange using long-read sequencing data. We therefore manually evaluated the breakpoint sequences using long-read sequencing data, considering the orientations of the SVs and CNVs called using OGM (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003ec). The CNV sizes of the eight duplications in a dot-plot of long-read sequencing data were 390 kb at 22q11.21, 419 kb at 22q12.1\u0026ndash;q12.2, 460 kb at 22q12.2, 238 kb at 22q12.3, 884 kb at 22q13.1, 335 kb at 22q13.1, 466 kb at 22q13.1, and 625 kb at 22q13.31. These regions included six, nine, seven, four, 31, 15, 14, and seven genes, respectively (Table S3); however, none of the genes were associated with known phenotypes. In addition, six genes were disrupted by the chromothripsis (Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e), but none of these were associated with the clinical features observed in Case 30. Ultimately, the combined analysis of OGM and targeted long-read sequencing provided a comprehensive and accurate identification of the chromothripsis (Table S4).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eWe identified novel SVs using OGM with AS in 14 of 30 cases (Cases 6, 7, \u003cspan refid=\"FPar1\" class=\"InternalRef\"\u003e15\u003c/span\u003e, 17, 18, \u003cspan refid=\"FPar4\" class=\"InternalRef\"\u003e20\u003c/span\u003e–24, 26, \u003cspan refid=\"FPar3\" class=\"InternalRef\"\u003e27\u003c/span\u003e, 29, and 30) in whom CNVs had previously been detected using ES. These SVs were undetectable by ES alone because of unstable genomic coverage, limited fragment size, and analytical limitations. ES typically misses SVs with breakpoints outside coding regions and cannot resolve the configuration of duplications or unbalanced translocations inferred from telomeric CNVs. By contrast, OGM uses ultra-high molecular weight DNA and genome-wide mapping to detect large and complex SVs—including inversions, inverted duplications, and intrachromosomal translocations—outside ES target regions (Cases 6 and \u003cspan refid=\"FPar4\" class=\"InternalRef\"\u003e20\u003c/span\u003e–22) and within repetitive regions (Case 26). Importantly, OGM with AS revealed disruptions (Cases 2 and 22) and copy number changes (Cases 12, \u003cspan refid=\"FPar1\" class=\"InternalRef\"\u003e15\u003c/span\u003e, 23, 24, 25, and \u003cspan refid=\"FPar3\" class=\"InternalRef\"\u003e27\u003c/span\u003e) in genes that are likely associated with clinical features (Tables\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and S3) (8/30 cases, 26.7%), clearly demonstrating the utility of OGM with AS following CNV detection.\u003c/p\u003e\u003cp\u003eMost novel SVs were observed in cases involving duplications (Cases 6, 7, \u003cspan refid=\"FPar1\" class=\"InternalRef\"\u003e15\u003c/span\u003e, 17, 18, \u003cspan refid=\"FPar4\" class=\"InternalRef\"\u003e20\u003c/span\u003e–24, 26, \u003cspan refid=\"FPar3\" class=\"InternalRef\"\u003e27\u003c/span\u003e, and 30), with only one additional SV found in a deletion case (Case 29). Notably, in cases in whom ES detected both duplication and deletion, OGM clarified the underlying events as unbalanced translocations (Cases \u003cspan refid=\"FPar1\" class=\"InternalRef\"\u003e15\u003c/span\u003e, 17, and 26) or inverted duplications (Cases 23 and \u003cspan refid=\"FPar3\" class=\"InternalRef\"\u003e27\u003c/span\u003e), which were undetected by ES. These findings suggest that such CNV patterns should raise a suspicion of hidden SVs, warranting further investigation with OGM.\u003c/p\u003e\u003cp\u003eOGM also enables CNV detection through molecule coverage-based analysis, to identify CNVs larger than 500 kb \u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e. In the present study, OGM detected CNVs ranging from 238 kb to 18.9 Mb. Although pathogenic genes were identified within these CNVs in six cases (Cases 12, \u003cspan refid=\"FPar1\" class=\"InternalRef\"\u003e15\u003c/span\u003e, 23, 24, 25, and \u003cspan refid=\"FPar3\" class=\"InternalRef\"\u003e27\u003c/span\u003e), they had already been detected by ES, suggesting that ES can capture certain pathogenic CNVs if they are covered by baits.\u003c/p\u003e\u003cp\u003eOGM and long-read sequencing detect SVs through fundamentally different mechanisms. Although long-read sequencing provides single-nucleotide resolution and accurate breakpoint determination, it is constrained by physical read lengths (10–100 kb), often requiring multiple reads to reconstruct complex SVs \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. By contrast, OGM analyzes molecules spanning hundreds of kilobases, enabling the better characterization of biallelic CNVs and phasing of copy number changes \u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eFor complex rearrangements with multiple breakpoints—such as intrachromosomal translocations and inverted duplications (Cases \u003cspan refid=\"FPar4\" class=\"InternalRef\"\u003e20\u003c/span\u003e–22) or chromothripsis (Case 30)—OGM was valuable for structural delineation, with long-read sequencing used for precise breakpoint resolution. In Case 30, discrepancies in breakpoint orientation and copy number between OGM and long-read sequencing illustrated the difficulty of resolving such events with sequencing alone. The genome-wide view of OGM and its ability to detect both CNVs and SVs are particularly advantageous for analyzing chromoanagenesis, including chromothripsis \u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eAll 14 SVs detected using OGM were validated with high accuracy. However, the resolution limit (~ 5 kb) of OGM means that smaller variants may be missed \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e. Breakpoint positions between OGM and long-read sequencing differed by 0.5–385.5 kb (Tables\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), often because of unmapped regions in OGM data. Larger unmapped regions correlated with greater discrepancies. Conversely, smaller gaps allowed near-precise breakpoint localization.\u003c/p\u003e\u003cp\u003eIn Case 26, in whom all reads included repetitive sequences, OGM accurately detected SVs, whereas long-read sequencing yielded mismapped reads, failing to detect the true breakpoints. This highlights the strength of OGM in repetitive and complex regions, leveraging long-range DNA molecules without sequence-based alignment \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eDespite its advantages, OGM cannot fully resolve SVs in centromeres and telomeres \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Whole-arm rearrangements such as Robertsonian translocations or isodicentric chromosomes remain challenging because of repetitive elements and gaps in the reference genome \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e,\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e. Additionally, telomere fusions may obscure insertion sites \u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e. However, complete chromosome assemblies (e.g., of the X chromosome) are becoming feasible via the integration of T2T reference genomes and OGM \u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e,\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eIn conclusion, duplications or duplication–deletion patterns detected using ES should prompt the suspicion of hidden SVs, particularly when CNVs do not fully explain the phenotype. Highly complex SVs, which are often unresolvable by sequencing alone, can be effectively characterized by combining OGM and long-read sequencing. OGM is thus a powerful tool for identifying complex chromosomal rearrangements within its resolution range.\u003c/p\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003cdiv id=\"Sec13\" class=\"Section3\"\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Methods","content":"\u003ch2\u003ePatients\u003c/h2\u003e\u003cp\u003eThe study was performed on 30 patients with different disease profiles (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). All patients were clinically evaluated and referred to our laboratory from July 2015 to August 2022. ES had been performed on the patients using the method described in the following section and all 30 patients had CNVs identified using ES. The ethnicities of patients were Japanese (25 patients) and Brazilian (five patients). The study protocol was approved by the institutional review boards and written informed consent was obtained from patients or their guardians.\u003c/p\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eCNV analysis using whole ES\u003c/h2\u003e\u003cp\u003eGenomic DNA was extracted from peripheral blood leukocytes using a QuickGene-610L kit (Fujifilm, Tokyo, Japan), according to the manufacturer’s instructions. Genomic DNA samples were sequenced on either the NovaSeq 6000 (Illumina, San Diego, CA, USA) using 150-bp paired-end reads after the enrichment of exonic regions using the Twist Human Comprehensive Exome (Twist BioScience, San Francisco, CA, USA) or the HiSeq2000 or HiSeq2500 (Illumina) with 101-bp paired-end reads after capture using the SureSelect Human All Exon kit (Agilent Technologies, Santa Clara, CA, USA). Exome data processing was performed as previously described \u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e. Reads were aligned to GRCh37 using Novoalign (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.novocraft.com/\u003c/span\u003e\u003cspan address=\"http://www.novocraft.com/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), and PCR duplicates were eliminated using Picard (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://broadinstitute.github.io/picard/\u003c/span\u003e\u003cspan address=\"https://broadinstitute.github.io/picard/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The Genome Analysis Toolkit (GATK) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://gatk.broadinstitute.org/hc/en-us\u003c/span\u003e\u003cspan address=\"https://gatk.broadinstitute.org/hc/en-us\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) was used to realign indels and recalibrate base quality scores.\u003c/p\u003e\u003cp\u003eCNVs were detected from the ES data using XHMM, a statistical tool for copy number analysis \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e,\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e. In brief, XHMM detects CNVs by analyzing normalized raw exome read depth data with principal component analysis of the complete coding regions. In Case 30, principal component analysis-normalized and filtered z-scores for the whole read depth were obtained, and SignalMap Version 1.9.0.05 (Roche Nimblegen, Madison, WI, USA) was used for visualization purposes. All CNVs were confirmed using quantitative PCR analysis of patients and their unaffected parents, and inheritance was confirmed to be assumed \u003cem\u003ede novo\u003c/em\u003e or uniparental (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cp\u003eGenomic DNA was extracted from peripheral blood leukocytes using a QuickGene-610L kit (Fujifilm, Tokyo, Japan), according to the manufacturer’s instructions. Genomic DNA samples were sequenced on either the NovaSeq 6000 (Illumina, San Diego, CA, USA) using 150-bp paired-end reads after the enrichment of exonic regions using the Twist Human Comprehensive Exome (Twist BioScience, San Francisco, CA, USA) or the HiSeq2000 or HiSeq2500 (Illumina) with 101-bp paired-end reads after capture using the SureSelect Human All Exon kit (Agilent Technologies, Santa Clara, CA, USA). Exome data processing was performed as previously described \u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e. Reads were aligned to GRCh37 using Novoalign (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.novocraft.com/\u003c/span\u003e\u003cspan address=\"http://www.novocraft.com/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), and PCR duplicates were eliminated using Picard (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://broadinstitute.github.io/picard/\u003c/span\u003e\u003cspan address=\"https://broadinstitute.github.io/picard/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The Genome Analysis Toolkit (GATK) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://gatk.broadinstitute.org/hc/en-us\u003c/span\u003e\u003cspan address=\"https://gatk.broadinstitute.org/hc/en-us\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) was used to realign indels and recalibrate base quality scores.\u003c/p\u003e\u003cp\u003eCNVs were detected from the ES data using XHMM, a statistical tool for copy number analysis \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e,\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e. In brief, XHMM detects CNVs by analyzing normalized raw exome read depth data with principal component analysis of the complete coding regions. In Case 30, principal component analysis-normalized and filtered z-scores for the whole read depth were obtained, and SignalMap Version 1.9.0.05 (Roche Nimblegen, Madison, WI, USA) was used for visualization purposes. All CNVs were confirmed using quantitative PCR analysis of patients and their unaffected parents, and inheritance was confirmed to be assumed \u003cem\u003ede novo\u003c/em\u003e or uniparental (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003ch2\u003eOGM\u003c/h2\u003e\u003cp\u003eUltra-high molecular weight DNA was extracted from 1.5\u0026nbsp;million lymphoblastoid cell lines using the SP-G2 Blood and Cell Culture DNA Isolation Kit (Bionano Genomics, San Diego, CA, USA) following the manufacturer’s instructions \u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e. DNA was labeled using the DLS-G2 Labeling Kit (Bionano Genomics) for the attachment of fluorophores to a specific six-nucleotide sequence (CTTAAG). The labeled DNA was loaded on a Saphyr chip G3.2 and run on a Saphyr instrument (Bionano Genomics) for an output of 400 Gb, targeting 80× effective coverage, with \u0026gt; 70% of molecules \u0026gt; 150 kb aligning (map rate) at N50 (N50 is defined as the length of the shortest molecule for which equal and longer molecules make up 50% of the total data) of \u0026gt; 230 kb \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). \u003cem\u003eDe novo\u003c/em\u003e assembly, alignment to the GRCh38 reference, and variant annotation of OGM data were performed using Bionano Solve 3.8.1. Visualization by Circos plot and genome browser, filtering, and interpretation of the identified SVs were conducted using Bionano Access 1.8.1. Standard filter settings were adjusted to select only the variants present in the regions of interest identified by previous standard diagnostic tests and in \u0026lt; 1% of control samples. In Case 28, OGM data were analyzed using the T2T reference genome in addition to GRCh38 to observe any differences.\u003c/p\u003e\u003ch2\u003eTargeted long-read sequencing using AS with GridION\u003c/h2\u003e\u003cp\u003eHere, 3 µg of the ultra-high molecular weight DNA used in OGM was fragmented to a target size of 50 kb using a Megaruptor 3 DNAFluid Kit (Diagenode, Seraing, Belgium). In cases in which the remaining amount of ultra-high molecular weight DNA was low, 5 µg of genomic DNA extracted from peripheral blood leukocytes was fragmented to a target size of 40 kb using a Megaruptor 3 Shearing Kit (Diagenode). The sheared DNA was used to construct sequencing libraries using an Oxford Nanopore Ligation Sequencing Kit (SQK-LSK114) (Oxford Nanopore Technologies, Oxford, UK), largely following the manufacturer’s instructions \u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e,\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e except that enzyme incubation times were doubled, with the final AMPure purification incubation for 10 minutes at 37°C. Approximately 25 fmol of the library was loaded onto a flow cell (FLO-MIN114, R10.4.1) on a GridION (Oxford Nanopore Technologies). Target regions comprising 0.24–0.98% of the whole genome were enriched using the AS option \u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e of GridION Mk1 with a BED file that assigned regions of CNVs detected by ES and each of the surrounding total 7.3–29.5 Mb regions (Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e). Sequencing was performed for approximately 3 days, with one additional library loading after nuclease flushing of a flow cell. In cases in which the amount of data was insufficient, new flow cells were used for additional analysis as appropriate.\u003c/p\u003e\u003cp\u003eThe data were base-called with super accuracy mode and processed into a BAM file using Dorado v.0.7.2 (Oxford Nanopore Technologies) with GRCh38 as a reference. The depth of coverage was calculated using mosdepth v0.3.1 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/brentp/mosdepth\u003c/span\u003e\u003cspan address=\"https://github.com/brentp/mosdepth\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The mean depth of the target region was 11.72×–47.38× (Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e). dnarrange was used to detect SVs and extract patient-specific SVs by referencing 29 control datasets \u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e,\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e. Control datasets were not used in the analysis if dnarrange excluded breakpoints of interest. Subsequently, using lamassemble (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://gitlab.com/mcfrith/lamassemble\u003c/span\u003e\u003cspan address=\"https://gitlab.com/mcfrith/lamassemble\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), each group of overlapping SV reads was merged into a consensus sequence and realigned to the reference genome. Next, dnarrange created a dot-plot representation of SV breakpoints. In dot-plots, lines show the alignment to the reference sequence and are drawn in red and blue to denote forward and reverse orientations to the reference genome, respectively. To understand entire SVs, we used the algorithm dnarrange-link to infer the order and orientation of multiple rearrangements \u003csup\u003e\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe express our gratitude to the families for their involvement in this research. We further acknowledge the great technical assistance provided by Mr. Takafumi Miyama, Ms. Sayaka Sugimoto, Ms. Mai Sato, Ms. Nobuko Watanabe, and Ms. Kaori Takabe at the Department of Human Genetics, Yokohama City University Graduate School of Medicine. We also thank Bronwen Gardner, PhD, from Edanz (https://jp.edanz.com/ac) for editing a draft of this manuscript. The Japan Society for the Promotion of Science (JSPS) KAKENHI Grant-in-Aid for Scientific Research [grant numbers JP22K15901 (A.F.), JP23H02829 (S.M.), JP23H02877 (T.M.), JP23K07229 (Y.U.), JP23K15353 (N.T.), and JP24K02230 (N.M.)]; the Takeda Science Foundation (T.M. and N.M.); the Japan Agency for Medical Research and Development (AMED) [grant numbers JP25ek0109674, JP25ek0109760, JP25ek0109617, JP25ek0109648 and JP25ek0109677 (N.M.)]; and Kawano Masanori Memorial Public Interest Incorporated Foundation for Promotion of Pediatrics (S.M.) provided support for this work.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;L.F. conceptualized and designed the study, reviewed the literature, analyzed the data, and drafted the manuscript; C.A.K., M.T., Y.Miy., N.O., Y.Ma., H.O., A.F., A.D., J.N., N.U., S.H., K.D., M.F., H.M., M.A., J.O., Y.Mis, J.K., T.S., H.A., R.S., H.H., S.Mit., S.O., K.S., Y.I., K.H., N.T., Y.U., E.K., S.Miy., T.M., A.I. analyzed the data and revised the manuscript; A.F. and N.M. supervised all aspects of the study and revised the manuscript.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets for this article are not publicly available because of concerns regarding patients\u0026rsquo; anonymity. Requests to access the datasets from qualified researchers should be directed to the corresponding author. There are restrictions on a qualified researcher accessing the data (non-commercial use only and requiring a Data Usage Agreement).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eCode availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll computational tools used in this study are available as open-source software, and their download links are presented in Methods. Software used are: Dorado v.0.7.2 (https://github.com/nanoporetech/dorado), mosdepth v0.3.1 (https://github.com/brentp/mosdepth), lamassemble 1.4.2 (https://gitlab.com/mcfrith/lamassemble), and dnarrange (https://github.com/mcfrith/dnarrange) for Targeted long-read sequencing using AS with GridION.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no conflicts of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSudmant, P. 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A pipeline for complete characterization of complex germline rearrangements from long DNA reads. \u003cem\u003eGenome medicine\u003c/em\u003e \u003cstrong\u003e12\u003c/strong\u003e, 67, doi:10.1186/s13073-020-00762-1 (2020).\u003c/li\u003e\n\u003cli\u003eLei, M.\u003cem\u003e et al.\u003c/em\u003e Long-read DNA sequencing fully characterized chromothripsis in a patient with Langer-Giedion syndrome and Cornelia de Lange syndrome-4. \u003cem\u003eJournal of human genetics\u003c/em\u003e \u003cstrong\u003e65\u003c/strong\u003e, 667-674, doi:10.1038/s10038-020-0754-6 (2020).\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"npj-genomic-medicine","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"npjgenmed","sideBox":"Learn more about [npj Genomic Medicine](http://www.nature.com/npjgenmed/)","snPcode":"41525","submissionUrl":"https://mts-npjgenmed.nature.com/","title":"npj Genomic Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7371701/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7371701/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eStructural variants (SVs), including duplications, deletions, inversions, translocations, and insertions, contribute to human phenotypic diversity but are often challenging to identify due to their size variability and complex configurations. Optical genome mapping (OGM) uses ultra-high molecular weight DNA (\u0026gt;\u0026thinsp;150 kb) fluorescently labeled at a specific six-nucleotide sequence, enabling comprehensive SVs detection by analyzing labeling patterns along long DNA molecules. This study aimed to fully characterize SVs using OGM.\u003c/p\u003e\u003cp\u003eOGM was applied to 30 cases with exome sequencing-based copy number variants (16 deletions, seven duplications, and seven deletions and duplications). Additionally, targeted Oxford Nanopore long-read sequencing with adaptive sampling was used to determine breakpoints of SVs. This approach revealed undetected SVs in 14 cases (46.7%), and disclosed gene disruptions or copy number alterations explaining clinical features in eight cases (26.7%).\u003c/p\u003e\u003cp\u003eEven complex SVs involving numerous chromosomal segments and breakpoints were resolved efficiently, highlighting the power of combining OGM and long-read sequencing.\u003c/p\u003e","manuscriptTitle":"Completely resolved structural variants by optical genome mapping with adaptive sampling from CNV discovery","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-23 07:39:53","doi":"10.21203/rs.3.rs-7371701/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-23T20:11:22+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-13T10:04:52+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-09T21:37:13+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-03T20:36:09+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"309129128083745046997737186991273047186","date":"2025-10-01T15:13:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"208770653781392089507671158564356302108","date":"2025-09-16T12:30:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"13440236132343665287599192541696273387","date":"2025-09-15T01:08:19+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-15T00:49:38+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-14T03:32:19+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-22T07:27:06+00:00","index":"","fulltext":""},{"type":"submitted","content":"npj Genomic Medicine","date":"2025-08-14T08:36:42+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"npj-genomic-medicine","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"npjgenmed","sideBox":"Learn more about [npj Genomic Medicine](http://www.nature.com/npjgenmed/)","snPcode":"41525","submissionUrl":"https://mts-npjgenmed.nature.com/","title":"npj Genomic Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"664a80c3-44da-4e8a-a5a4-c156b76f12aa","owner":[],"postedDate":"September 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":54822992,"name":"Biological sciences/Biological techniques"},{"id":54822993,"name":"Biological sciences/Computational biology and bioinformatics"},{"id":54822994,"name":"Biological sciences/Genetics"}],"tags":[],"updatedAt":"2026-03-30T16:16:20+00:00","versionOfRecord":{"articleIdentity":"rs-7371701","link":"https://doi.org/10.1038/s41525-026-00561-4","journal":{"identity":"npj-genomic-medicine","isVorOnly":false,"title":"npj Genomic Medicine"},"publishedOn":"2026-03-26 16:09:03","publishedOnDateReadable":"March 26th, 2026"},"versionCreatedAt":"2025-09-23 07:39:53","video":"","vorDoi":"10.1038/s41525-026-00561-4","vorDoiUrl":"https://doi.org/10.1038/s41525-026-00561-4","workflowStages":[]},"version":"v1","identity":"rs-7371701","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7371701","identity":"rs-7371701","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}