Comprehensive Analysis of the NF1 gene Using Long-Read Sequencing Improved Neurofibromatosis type 1 Molecular Diagnosis

Comprehensive Analysis of the NF1 gene Using Long-Read Sequencing Improved Neurofibromatosis type 1 Molecular Diagnosis | 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 Research Article Comprehensive Analysis of the NF1 gene Using Long-Read Sequencing Improved Neurofibromatosis type 1 Molecular Diagnosis Yu Zheng, Miaomiao Chen, Shuju Zhang, Yu Peng, Xinghan Wu, Danni Guo, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5382766/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Clinical diagnosing Neurofibromatosis type 1 (NF1) in pediatrics are facing challenges because of limited presence of age-dependent phenotypes, and the limited detection rate by current approaches for the complexity of the NF1 gene. Here we developed a comprehensive analysis of NF1 (CANF1) combining 14 long-range locus-specific PCR, 25 gap primers and long-read sequencing (LRS) for sequence analysis of the NF1 gene. In this blind retrospective study, the clinical utility of CANF1 was evaluated in 191 samples (181 pediatric probands, 10 NF1 parents) by comparing to the control methods, mainly next generation sequencing (NGS). The results exhibited 176 probands (176/181 = 97.2%) having concordant results, and the other 5 probands (2.8%) with improved findings including: one was established a new diagnosis (c.5812 + 332A > G in deep intron) and four were improved with precise CNV breakpoints. In 127 pediatric NF1 probands with limited clinical manifestations, this assay received a detection rate of 92.9%, which is higher than NGS. In conclusion, this study constructed a comprehensive analysis of NF1 employing LRS, which can reliably identify various type variants of the NF1 gene in one assay. This CANF1 assay can help in screening NF1 with more precise molecular diagnosis than conventional methods, particularly for individuals with unfulfilling NF1 diagnosis solely by clinical phenotypes. Neurofibromatosis 1 NF1 long-read sequencing genetic testing precise diagnosis Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Neurofibromatosis type 1 (NF1, OMIM: 162200) is an autosomal dominant genetic disease occurs in approximately 1/3000 births (Evans et al., 2010 ; Lammert, Friedman, Kluwe, & Mautner, 2005 ; Uusitalo et al., 2015 ). NF1 have cutaneous, ocular, or osseous manifestations, which exhibit both tissue-related and age-related diversity. Café au lait macules (CALMs) are the most common manifestations in NF1 from infancy, and other manifestations before adolescence can help in NF1 clinical diagnosis including: skinfold freckling or neurofibroma, osseous lesion such as congenital pseudarthrosis (CP), ocular abnormalities such as Lisch nodules or optic pathway glioma (Gutmann et al., 2017 ; Legius et al., 2021 ). Dysplasia of a long bone typically tibial CP (CPT) is found in ~ 2% of children with NF1, which is intractable in pediatric orthopedics (Gutmann et al., 2017 ; Hefti et al., 2000 ; O'Donnell et al., 2017 ; Vander Have, Hensinger, Caird, Johnston, & Farley, 2008 ). Up to 84% of CP participants present NF1, while others do not manifest NF1 (non-NF1) with unknown etiology (Neurofibromatosis, 1988 ; Van Royen, Brems, Legius, Lammens, & Laumen, 2016 ). CALMs with high morbidity in children which require differential diagnosis, an earlier screening and precise molecular diagnosis are necessary. For children unfulfilling the current clinical diagnostic criteria who meet only one of the criteria, without molecular diagnosis, it’s challenging to make a clinical diagnosis of Neurofibromatosis type 1 (NF1) in early childhood. NF1 is caused by the haploinsufficiency of the NF1 gene. The NF1 gene is located on human chromosome 17q11.2, with a genomic length of 370 Kb. It has two full-length transcript isoforms: NM_000267.3 (57 exons) and NM_001042492.3 (58 exons). The NM_001042492.3 is the MANE (Matched Annotation from the NCBI and EMBL-EBI) selected isoform, with a length of 12.4 Kb. Due to its large size, NF1 is associated with multiple types of variations such as SNVs, Indels, large segmental deletion or duplication, NF1 microdeletion, insertion, inversion, microsatellite, low faction of mosaicism or somatic second-hit variants. These variations originate either from coding regions, or non-coding regions such as introns, 5’UTR, upstream regulating regions. To date (by 1th May, 2024), there were 4462 variants recorded in the professional version of the Human Genome Mutation Database (HGMD, https://www.hgmd.cf.ac.uk/ac/ ), and 4579 pathogenic or likely pathogenic variations in NF1 have been recorded in ClinVar database ( https://www.ncbi.nlm.nih.gov/clinvar/ ). Generally, these pathogenic variants are diverse and lack of mutation hotspots. Moreover, the detection of NF1 variants is complicated by the presence of the pseudogene NF1P1 , which shares a high sequence similarity with some exons of NF1 . These increased the difficulty and complexity in precisely detecting the variants affecting NF1 . Currently, multiple genetic testing technologies are used to detect NF1 variants, and a multi­step approach is required to analysis of blood genomic DNA and mRNA to obtain a higher detection rate. Primarily, next generation sequencing (NGS) based technologies are commonly employed, such as exome sequencing (ES), clinical exome sequencing and genome sequencing (GS) including low-depth sequencing for copy number variations (CNV-seq), ultra high amplicon sequencing. Other technologies maybe supplemented to facilitate the testing, including multiplex ligation-dependent probe amplification (MLPA), quantitative PCR, fish fluorescence in situ hybridization (FISH) or Sanger sequencing. The diagnostic rate using genomic DNA (gDNA) was approximately 60–90% (Cali et al., 2017 ; Pasmant et al., 2015 ; van Minkelen et al., 2014 ; Zhang et al., 2015 ). It was reported that using both gDNA and cDNA the combination molecular diagnostic rate of NF1 could close to 95% (Evans et al., 2016 ; Sabbagh et al., 2013 ; Valero et al., 2011 ). In addition, less than 1% of the NF1 patients were found abnormal chromosomal karyotype (Messiaen et al., 2000 ). In general, current genetic testing methods for NF1 can detect limited types of variation, and multiple PCR reactions and library preparations are usually required before sequencing, as well as follow-up MLPA testing for whole NF1 or intragenic exon copy number variants (CNVs) (D. Bianchessi et al., 2015 ; D. A.-O. Bianchessi et al., 2020 ; Summerer et al., 2019 ; L. Zhu et al., 2016 ). Additionally, NGS-based methods generate a vast amount of sequence data, but they are unable to detect inversions or translocations. Thus, to obtain a higher diagnostic rate and more precise genetic diagnosis, a more comprehensive method needs to be developed. Recently, with the rapid development of long-read sequencing (LRS), this technology has been able to provide more comprehensive and accurate sequence data in a single step because of longer reads, more even sequence coverage, and avoidance of PCR amplification bias. Targeted-LRS has been successfully applied in the genetic diagnosis of thalassemia, congenital adrenal hyperplasia, fragile X syndrome, hemophilia A, and spinal muscular atrophy (Chen et al., 2023 ; Liang et al., 2023 ; Liang et al., 2022 ; Liu et al., 2022 ; Liu et al., 2023 ; Wang et al., 2024 ). In this study, we developed a locus-specific PCR approach combined with LRS to analyze the NF1 gene. This method allows for the simultaneous analysis of SNVs, Indels, mosaicism, CNVs and structural variations in one assay. Here, we retrospectively analyzed 191 clinical samples of NF1 participants, using either blood or tissue samples. The results demonstrated that comprehensive analysis of NF1 (CANF1) has high clinical utility with feasibility of improving NF1 diagnosis. Methods Study participants This study was approved by the Ethics Committee of Hunan Children's Hospital (Approval No. HCHLL-2024-56). The samples were obtained with appropriate informed consent from all participants or their legal guardians. Children less than 18 years old from Chinese mainland with CALMs or CPs performed genetic testing were initially collected. In this retrospective study, a total of 191 individuals from Chinese mainland were recruited, including 181 probands with clinical presentations of NF1 or CP and 10 samples from NF1 family members. These participants underwent ES and or GS. Among them, 36 participants had a family history of NF1 (including two monozygotic twins) (Supplemental Table 1). The clinical diagnostic criteria of NF1 included the following: more than 6 Café au lait macules (CALMs) with a diameter greater than 5 mm; freckling in the axillary or inguinal region; more than 2 neurofibromas or one plexiform neurofibroma; optic pathway glioma; more than 2 iris Lisch nodules or more than 2 choroidal abnormalities; a distinctive osseous lesion such as congenital pseudarthrosis of the tibia; and NF1 family history. Individuals who meet two or more of above-mentioned clinical characteristics can be diagnosed as NF1. According to the clinical criteria for NF1, 137 samples fulfilled the NF1 clinical diagnosis including 127 probands and 10 NF1 family members, and 54 samples presented with CP but unfulfilling the NF1 clinical criteria (non-NF1-CP). As for the sample source, 138 blood samples (132 having NF1) and 53 tissue samples (5 having NF1) were used (Table S1). Peripheral blood samples were collected into EDTA tubes and gDNA was also extracted using the DNease Blood & Tissue Kit (Qiagen). Periosteum at the pseudoarthrosis site were cut into small pieces to ensure more efficient lysis and were preserved in liquid nitrogen. gDNA in periosteum was extracted using the following steps: (1) All samples were digested in 180 µl Buffer ATL (Qiagen) and 20 µl of Proteinase K at 56°C C until the tissues were completely lysed. (2) DNA was extracted from each sample following the protocol of Qiagen DNeasy Blood & Tissue Kit (Qiagen). (3) DNA concentrations (ng/μl) were measured using the dsDNA High Sensitivity kit on a Qubit Fluorometer 2.0 (ThermoFisher Scientific). (4) To visualize DNA extractions, gel electrophoresis was performed on 1% agarose gels stained with SYBR Safe DNA Gel Stain (Invitrogen). Multiplex long-range PCR and PacBio sequencing Multiplex long-range PCR were conducted with two sets of primers in one reaction. One set of primers was designed to identify SNVs/Indels of NF1 though amplifying 14 DNA fragments which were consisted of 58 exon regions and flanking intron regions (Fig.1A and Fig.1B). Another set of primers included 25 gap primers covering targeted region of 30-kb upstream and 30-kb downstream of NF1 to detect large deletions (Fig.1A). Specific DNA fragments were amplified by according to gap primers for samples with variants caused by large deletions. In summary, CANF1 covered all the exons of NF1 , and the majority of the known SNVs/indels reported by HGMD professional (https://www.hgmd.cf.ac.uk) and or ClinVar (https://www.ncbi.nlm.nih.gov/clinvar/) databases. Genomic DNA was extracted using DNease Blood & Tissue Kit (Qiagen). Multiplex long-range PCR were conducted using KOD FX Neo (Toyobo Co. Ltd., Osaka, Japan) in 50-μL reactions containing 10-100 ng of genomic DNA, 1 x PCR buffer for KOD FX Neo, 0.4 mM of each dNTP, 1 μM of primer mixture and 1 μL of KOD FX Neo (TOYOBO). The amplification procedure was as follows: pre-denaturation at 94°C for 5 min; 32 cycles (denaturation at 98°C for 15 s and extension at 68°C for 12 min); and extension at 68°C for 10 min. Amplicons generated from long-range PCR were sequenced by long-read sequencing. The pre-libraries of single-molecule real-time (SMRT) sequencing (PacBio) were prepared and specific barcodes were added. The Sequel Binding Kit 2.0 (PacBio) was used to generate the SMRTbell @ library and sequencing was generated on the Sequel II platform (PacBio). PacBio data analysis and variant calling The raw data were processed to obtain highly accurate circular consensus sequencing (CCS) reads, and then the filtered and debarcoded CCS reads were aligned to human GRCh38/hg38 genome sequences using pbmn2 of the SMRT Link analysis software (PacBio). SNVs/Indels were identified using FreeBayes 1.3.4. The deletions in the targeted region containing 30 kb upstream and downstream of NF1 were analyzed through alignment with the reference genome GRCh38/hg38. The exact breakpoints of deletions were determined and displayed using the Integrative Genomics Viewer (IGV). The haplotype analysis of 14 DNA fragments amplified using exon primers mentioned above was conducted. Fourteen fragments each carrying one haplotype suggested the samples had NF1 microdeletion, and subsequent CNV-seq was used to identify the NF1 microdeletion. Results The Strategy of Comprehensive Analysis of NF1 The strategy of comprehensive analysis of NF1(CANF1) was constructed in this study. Multiplex long-range PCR was performed using two sets of primers in one reaction. Fourteen DNA fragments covering 58 exons and flanking intron regions were generated using primer set 1 to identify SNVs/Indels and intragenic copy number variants of the NF1 gene (Figure. 1A-B). Twenty-five gap primers (primer set 2) covering a targeted region of 30 kb upstream and 30 kb downstream of the NF1 gene were designed to identify intragenic CNV (Fig. 1A). The flowchart of molecular genetic diagnosis of NF1 using CANF1 was shown in Fig. 1C. Fourteen amplicons, each containing only one haplotype, can give a clue to the presentation of large deletions including NF1 and its flanking regions, so-called NF1 microdeletion, which was confirmed by CNV-seq. The Precise Genetic Diagnosis of NF1 by CANF1 A total of 191 clinical samples were enrolled, and they were classified into 127 NF1 probands, 54 CP probands and 10 NF1 family members according to the NF1 diagnostic criteria (Fig.2, Supplemental Table 2). The detailed information and genetic diagnosis results were listed in Supplemental Table 1. Both CANF1 and the control method were performed in 181 probands and 10 family members. Comparative analysis indicated that 176 probands (97.2%) exhibited concordant results, and the other 5 probands (2.8%) showed discordant results (Fig.2). Out of 176 probands with concordant results, 122 probands (69.3%) carried pathogenic variants and 3 probands (1.7%) had variants of uncertain significance (VUS) and the remaining 51 probands (29.0%) harbored no variants. Of the 5 discordant results, one was established a new diagnosis and 4 probands were improved diagnosis by CANF1 (Fig.2). The probands with discordant results between CANF1 and the control method were exhibited in Table 1. In P77 proband, CANF1 identified a deep intron variant NM_001042492.3:c.5812+332A>G which was not detected by ES. The variant was also confirmed by Sanger sequencing (Supplemental Fig.1A). In other 4 probands, precise diagnosis was conducted by CANF1 and the results of the control method were improved by CANF1. In P51 proband, a VUS c.1527+1346G>C located at the deep intron region of NF1 was solely identified by CANF1, not by the control method ES (Supplemental Fig.1B). In proband P71, peripheral blood and tissue were used for genetic diagnosis. Both CANF1 and ES identified one disease-causing variant c.4330A>G when using a peripheral blood sample, and two pathogenic variants, c.653delA and c.4330A>G, when using tissue sample. Nevertheless, Table 1 Discordant results between CANF1 and the control method. Sample ID Gender Dignosis by clinical findings Control method Results of Control method * CANF1 Outcomes cDNA * Exon * Variant Type P77 Male NF1 ES NA c.5812+332A>G Intron 39 Intron variant A new diagnosis detected by CANF1 P51 Male CPT ES NA c.1527+1346G>C Intron 13 Intron variant A VUS in intron detected by CANF1 P71 (Tissue) Female NF1 ES c.653delA, c.4330A>G c.653delA/c.4330A>G Exon 6/ Exon 32 Frameshift/ missense A trans configuration detected by CANF1 P172 Female NF1 ES E37-E40 del 21025 bp (chr17:31314007-31335032) E37-E40 del 25799bp ins 94bp (chr17:31309477-31335275 ins 94bp ) E37-E40 del Intragenic deletion A precise deletion and breakpoint detected by CANF1 P90 Male NF1 ES E13-E18 del, E49-E58 del 42932 bp (chr17:31349099-31392031) E49-E58 del 53004bp ins 306bp (chr17:31349202-31402205 ins 306bp) E49-E58 del Intragenic deletion A precise deletion and breakpoint detected by CANF1 * E: exon, Del: deletion, ins: insertion, NA: not found. CANF1 identified that these two variants were in trans-configuration through customized specific genetic testing by overlapping DNA fragments (Supplemental Fig.1C). An intragenic deletion was identified both by CANF1 and the control method (enhanced ES with exon-based CNV analysis) in proband P172. CANF1 detected a 25.8 kb deletion, rather than a 21.0 kb deletion detected by ES. This variant was confirmed by gap PCR through agarose gel electrophoresis (Fig.3A). The breakpoints of this intragenic deletion were also identified by CANF1 and were exhibited by IGV plots (Fig.3A). This highlighted that CANF1 has higher resolution. In proband P90, ES indicated that this proband had a heterozygous exon E49 to E58 deletion, and a heterozygous exon E13 to E18 deletion. However, the haplotype analysis of CANF1 confirmed the breakpoints and exact length of the deletion of exon E49 to E58, but revealed that there was no deletion in the exon 13 to 18 region (Fig.3B). In addition, 14 amplicons each containing only one haplotype illustrated NF1 microdeletion which was also identified by control methods ES and CNV-seq. A total of 7 probands had only one haplotype in every fragment, which were also tested by CNV-seq (Supplemental Table 3). Among them, 6 (85.7%) had NF1 microdeletion, while the rest one (14.3%) had no variants (Table S3). For instance, in proband P134, both CANF1 haplotype analysis and CNV-seq exhibited that the 1.24Mb microdeletion expanding from CRLF3 gene to SUZ12 gene (Supplemental Fig.2), while ES detected a smaller size of 1.006Mb microdeletion (Table S1). The Variants Distribution in Clinical NF1 Group and Clinical CP Group The enrolled 181 probands were divided into clinical NF1 and CP groups according to NF1 clinical diagnostic criteria, and CP groups included probands not fulfilling the NF1 diagnostic criteria (non-NF1-CP). The results of CANF1 showed the frequency of NF1 variants in clinical NF1 and CP groups was 93.7% and 20.4%, respectively (Fig.4A). In 127 probands in the clinical NF1 group, 117 (92.9%) probands were identified as carrying pathogenic or likely pathogenic variants of NF1 by CANF1. Two (1.6%) probands had VUS variants, and 8 probands (6.3%) were without variants of the NF1 gene. Nine out of 54 CP probands (16.7%) were identified as carrying pathogenic or likely pathogenic variants of the NF1 gene. Two probands (3.7%) had VUS variants, and 43 probands (79.6%) were without variants of the NF1 gene. In the clinical NF1 group, the most frequent variants were pathogenic SNVs/Indels, accounting for 91.6%, followed by 4.2% NF1 microdeletions (Fig.4B). In the clinical CP group, 3 types of variants were identified, including 8 pathogenic SNVs/Indels (72.7%), 2 VUS (18.2%) and 1 somatic mosaicism (9.1%) (Fig.4B). The Spectrum of Variants Detected by CANF1 The variants detected in this study were listed in Supplemental Table 4. A total of 132 variants were identified by CANF1. Among them, 94.7% were SNVs/indels, 1.5% were intragenic variants, and 3.8% were NF1 microdeletion. The most frequent variant was c.1541_1542delAG (3.8%, found in 5 probands), followed by c.1885G>A (3.0%, found in 4 probands). c.574C>T, c.2034delinsCA and the recurrent 1.24 Mb NF1 microdeletion were found in 3 probands (2.3%) respectively. The most frequent variant type was frameshift (32.6%), followed by nonsense (29.5%), missense (15.9%) and intron variants (15.9%). The differential testing of NF1 with CALMs In our single-center collected 217 children with CALMs performed genetic testing, 50% (109/217) of the probands were obtained genetic diagnosis and the causing genes including NF1, PTPN11 , SPRED1 , and TSC2. The NF1 gene occupied the vast majority of them (97/109=89%), followed by PTPN11 (3/109=2.8%), SPRED1 (1/109=0.9%), and TSC2 (1/109=0.9%). Overall, 44.7% (97/217) out of the 217 CALMs patients were detected NF1 pathogenic variants. In the enrolled 181 probands performed CANF1 assay, 126 with CALMs and NF1 clinical diagnosis and 92.1% (116/126) of which were obtained NF1 genetic diagnosis. Two of the 126 cases were found NF1 VUS variants. Discussion We developed CANF1 assay as a comprehensive method to detect variants in the NF1 gene using gDNA of NF1 or suspecting NF1 participants. The assay covered all exons of the NF1 gene and 30 kb both upstream and downstream for intragenic CNVs, and achieved a higher detection rate and accuracy than conventional approaches, which will help in screening and differential diagnosis of NF1 in pediatrics. Conventional approaches had limitations in diagnostic accuracy, cost, and convenience. For instance, targeted NGS received a detection rate of 88% in 279 NF1 patients (Pasmant et al., 2015 ), and ES received a detection rate of 74.5% in 55 NF1 patients(G. Zhu et al., 2019 ). The combination of gDNA and cDNA sequence analysis using multi-step NGS, MLPA, and chromosomal microarray analysis (CMA) or karyotyping could detect variants in approximately 95% of NF1 patients. However, this often requires multiple techniques and sample types. Moreover, NF1 is a multisystem disorder with variable expression and various phenotypes, affecting multiple system such cutaneous, ophthalmic, skeletal, nervous systems. Due to the complexity of clinical manifestations, differential diagnosis is usually needed in clinic. Here, CANF1 assay received a detection rate of 92.9% in 127 NF1 probands using gDNA merely in one assay. In addition to the concordance rate of 97.2% compared with NGS, this CANF1 assay targeting NF1 variants using long-read sequencing improved the detection rate of 2.8%, which will aid in making a more precise diagnosis of NF1. Compared to conventional NGS, CANF1 assay established a new diagnosis, and/or improved the diagnosis of certain samples by providing more accurate genetic diagnosis, including identifying trans-configuration and breakpoints of deletion. The intron variant c.5812 + 332A > G in participant P77 was unidentified by ES as it was outside the targeted region. In P51, the variant c.1527 + 1346G > C from deep intron region was only detected by CANF1, which was classified as VUS based on ACMG criteria as it was predicted not affecting splicing. Through genetic analysis of blood and tissue in P71, the germline NF1 pathogenic variant c.4330A > G in all samples and a second-hit pathogenic NF1 variant c.653delA in tissue. Both NF1 variants were located on different alleles resulting in somatic mosaicism for a biallelic NF1 inactivation. The intragenic CNV in P90 carried a deletion of 53,004bp from exon 49 to 58 and an insertion of 306bp, with the 3’ breakpoint located in intron 1 of the downstream gene RAB11FIP4. The breakpoints were identified by CANF1, whereas routine ES could only provide a rough range of affected exons. In addition, ES suggested a deletion of exon 13 to 18 in a region interfered by a pseudogene, but the CANF1 assay demonstrated that this was a false deletion. In Proband P172, the CANF1 detected a more precise region of deletion, with 25.8 kb rather than 21.03 kb deletion suggested by exon capture-based ES. Therefore, firstly, the CANF1 assay can cover a wideer and more precise range of variation, particularly in non-coding region. Secondly, the CANF1 assay provides deeper sequencing depth than ES and GS with less sequencing data, and it has capacity to found variants more accurately that could be missed by sequencing with depth of 30-120X. Above all, the LRS-based CANF1 assay enables the efficient identification of various variations, including SNVs/Indels, small deletions/insertions, large deletions, NF1 microdeletion and gene conversions in one assay with reduced costs compared to traditional approaches. As the molecular testing for NF1 was included as one of the seven criteria in the recently revised NF1 diagnostic criteria in 2021, this CANF1 assay can facilitate earlier and more precise diagnosis of NF1. NF1 manifestations have age-dependent, with CALMs in the cutaneous system usually being the first onset. However, relying solely on clinical manifestations, approximately 46% of sporadic NF1 patients do not meet the diagnostic criteria by the age of one year (Ly & Blakeley, 2019 ). Previous studies have revealed that 97% of children with at least one feature of NF1 eventually meet the diagnostic criteria by the age of 8 years. Precise diagnosis contributes to timely and appropriate treatment for patients. Moreover, for those individuals lacking characteristic cutaneous findings or with mosaic involvement, ES and multigene panel testing based on NGS was mainly applied in clinical molecular diagnosis. Ultradeep sequencing was used to identify somatic mosaicism using tissues of probands. By traditional gDNA targeted sequencing, 60–90% of the NF1 patients could found NF1 variants (D. A.-O. Bianchessi et al., 2020 ; Cali et al., 2017 ; Maruoka et al., 2014 ; Pasmant et al., 2015 ; van Minkelen et al., 2014 ; Zhang et al., 2015 ). Here, the CANF1 assay provided an all-in-one approach and identified disease-causing NF1 variants in 92.9% clinical NF1 participants. As mentioned previously, approximately 21% of non-NF1-CP were found to have somatic mono-allelic NF1 disease-causing variants(Zheng et al., 2022 ), while 16.7% of non-NF1-CP were identified as having NF1 disease-causing variants. In conclusion, this study developed CANF1 assay as a comprehensive, accurate and more efficient approach than current approaches. This advancement will be highly beneficial for establishing an earlier molecular diagnosis of NF1 and will aid in genetic counseling and disease management for participants. Additionally, as one of the NF1 diagnostic criteria, high quality LRS of the NF1 gene would become a considerably important tool for molecular diagnosis in near future. Abbreviations NF1, Neurofibromatosis type 1; CANF1, comprehensive analysis of NF1; CALM, Café au lait macules; CPT, congenital pseudarthrosis of the tibia; CP, congenital pseudarthrosis; non-NF1-CP, participants with congenital pseudarthrosis but unfulfilling the NF1 clinical criteria; PCR, polymerase chain reaction; CNV, copy number variations; NGS, next-generation sequencing; ES, exome sequencing; GS, genome sequencing; CNV-seq, low-depth sequencing for copy number variations; MLPA, multiplex ligation-dependent probe amplification; LRS, long-read sequencing; VUS, variants of uncertain significance; SNVs, single nucleotide variations; Indels, small insertions and deletions; IGV, Integrative Genomics Viewer. Declarations Competing interests The authors declare that they have no competing interests. Ethics Approval This study was approved by the Ethics Committee of Hunan Children's Hospital (Approval No. HCHLL-2024-56). Consent to participate Informed consent was obtained from all individual participants or their parents included in the study. Funding This work was supported by the Hunan Province Natural Science Foundation of China (2023JJ30330), the Clinical Medical Research Center for Hereditary Birth Defects and Rare Diseases in Hunan Province (2023SK4053), and the special fund of Hunan Provincial Key Laboratory of Pediatric Orthopedics (2023TP1019). Author Contribution All authors contributed to the study conception, design and resources collection. Supervision: Hua Wang. Material preparation, data collection and analysis were performed by Yu Zheng, Danhua Li, Tiantian Xie, Guanghui Zhu, Yaoxi Liu, Haibo Mei. Funding acquisition: Hua Wang, Yu Zheng and Guanghui Zhu. The first draft of the manuscript was written by Yu Zheng and all authors reviewed and commented on the manuscript. All authors read and approved the final manuscript. Acknowledgement We appreciate the Hunan Province Natural Science Foundation of China (2023JJ30330), the Clinical Medical Research Center for Hereditary Birth Defects and Rare Diseases in Hunan Province (2023SK4053), and the special fund of Hunan Provincial Key Laboratory of Pediatric Orthopedics (2023TP1019). We thank Berry Genomics Corporation supported this study. We also express our sincere gratitude to participants and all who helped us in this study. Data Availability The novel variants found in this study will submit to ClinVar. Other datasets used during the current study are available from the corresponding authors on reasonable request. References Bianchessi, D., Morosini, S., Saletti, V., Ibba, M. C., Natacci, F., Esposito, S., . . . Eoli, M. (2015). 126 novel mutations in Italian patients with neurofibromatosis type 1. Mol Genet Genomic Med, 3 (6), 513-525. doi:10.1002/mgg3.161 Bianchessi, D. A.-O., Ibba, M. C., Saletti, V., Blasa, S. A.-O. X., Langella, T., Paterra, R., . . . Eoli, M. A.-O. (2020). Simultaneous Detection of NF1, SPRED1, LZTR1, and NF2 Gene Mutations by Targeted NGS in an Italian Cohort of Suspected NF1 Patients. Genes, 11(6):671 (2073-4425 (Electronic)). doi:10.3390/genes11060671 Cali, F., Chiavetta, V., Ruggeri, G., Piccione, M., Selicorni, A., Palazzo, D., . . . Romano, V. (2017). Mutation spectrum of NF1 gene in Italian patients with neurofibromatosis type 1 using Ion Torrent PGM platform. Eur J Med Genet, 60 (2), 93-99. doi:10.1016/j.ejmg.2016.11.001 Chen, X., Harting, J., Farrow, E., Thiffault, I., Kasperaviciute, D., Genomics England Research, C., . . . Eberle, M. A. (2023). Comprehensive SMN1 and SMN2 profiling for spinal muscular atrophy analysis using long-read PacBio HiFi sequencing. Am J Hum Genet, 110 (2), 240-250. doi:10.1016/j.ajhg.2023.01.001 Evans, D. G., Bowers, N., Burkitt-Wright, E., Miles, E., Garg, S., Scott-Kitching, V., . . . Huson, S. M. (2016). Comprehensive RNA Analysis of the NF1 Gene in Classically Affected NF1 Affected Individuals Meeting NIH Criteria has High Sensitivity and Mutation Negative Testing is Reassuring in Isolated Cases With Pigmentary Features Only. EBioMedicine, 7 , 212-220. doi:10.1016/j.ebiom.2016.04.005 Evans, D. G., Howard, E., Giblin, C., Clancy, T., Spencer, H., Huson, S. M., & Lalloo, F. (2010). Birth incidence and prevalence of tumor-prone syndromes: estimates from a UK family genetic register service. Am J Med Genet A, 152A (2), 327-332. doi:10.1002/ajmg.a.33139 Gutmann, D. H., Ferner, R. E., Listernick, R. H., Korf, B. R., Wolters, P. L., & Johnson, K. J. (2017). Neurofibromatosis type 1. Nat Rev Dis Primers, 3 , 17004. doi:10.1038/nrdp.2017.4 Hefti, F., Bollini, G., Dungl, P., Fixsen, J., Grill, F., Ippolito, E., . . . Wientroub, S. (2000). Congenital pseudarthrosis of the tibia: history, etiology, classification, and epidemiologic data. J Pediatr Orthop B, 9 (1), 11-15. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/10647103 Lammert, M., Friedman, J. M., Kluwe, L., & Mautner, V. F. (2005). Prevalence of neurofibromatosis 1 in German children at elementary school enrollment. Arch Dermatol, 141 (1), 71-74. doi:10.1001/archderm.141.1.71 Legius, E., Messiaen, L., Wolkenstein, P., Pancza, P., Avery, R. A., Berman, Y., . . . Plotkin, S. R. (2021). Revised diagnostic criteria for neurofibromatosis type 1 and Legius syndrome: an international consensus recommendation. Genet Med, 23 (8), 1506-1513. doi:10.1038/s41436-021-01170-5 Liang, Q., He, J., Li, Q., Zhou, Y., Liu, Y., Li, Y., . . . Wu, L. (2023). Evaluating the Clinical Utility of a Long-Read Sequencing-Based Approach in Prenatal Diagnosis of Thalassemia. Clin Chem, 69 (3), 239-250. doi:10.1093/clinchem/hvac200 Liang, Q., Liu, Y., Liu, Y., Duan, R., Meng, W., Zhan, J., . . . Wu, L. (2022). Comprehensive Analysis of Fragile X Syndrome: Full Characterization of the FMR1 Locus by Long-Read Sequencing. Clin Chem, 68 (12), 1529-1540. doi:10.1093/clinchem/hvac154 Liu, Y., Chen, M., Liu, J., Mao, A., Teng, Y., Yan, H., . . . Wu, L. (2022). Comprehensive Analysis of Congenital Adrenal Hyperplasia Using Long-Read Sequencing. Clin Chem, 68 (7), 927-939. doi:10.1093/clinchem/hvac046 Liu, Y., Li, D., Yu, D., Liang, Q., Chen, G., Li, F., . . . Liang, D. (2023). Comprehensive Analysis of Hemophilia A (CAHEA): Towards Full Characterization of the F8 Gene Variants by Long-Read Sequencing. Thromb Haemost, 123 (12), 1151-1164. doi:10.1055/a-2107-0702 Ly, K. I., & Blakeley, J. O. (2019). The Diagnosis and Management of Neurofibromatosis Type 1. Med Clin North Am, 103 (6), 1035-1054. doi:10.1016/j.mcna.2019.07.004 Maruoka, R., Takenouchi, T., Torii, C., Shimizu, A., Misu, K., Higasa, K., . . . Kosaki, K. (2014). The use of next-generation sequencing in molecular diagnosis of neurofibromatosis type 1: a validation study. Genet Test Mol Biomarkers, 18 (11), 722-735. doi:10.1089/gtmb.2014.0109 Messiaen, L. M., Callens, T., Mortier, G., Beysen, D., Vandenbroucke, I., Van Roy, N., . . . Paepe, A. D. (2000). Exhaustive mutation analysis of the NF1 gene allows identification of 95% of mutations and reveals a high frequency of unusual splicing defects. Hum Mutat, 15 (6), 541-555. doi:10.1002/1098-1004(200006)15:63.0.CO;2-N Neurofibromatosis. (1988). National Institutes of Health Consensus Development Conference. Conference statement. Arch Neurol, 45 , 575-578. O'Donnell, C., Foster, J., Mooney, R., Beebe, C., Donaldson, N., & Heare, T. (2017). Congenital Pseudarthrosis of the Tibia. JBJS Rev, 5 (4), e3. doi:10.2106/JBJS.RVW.16.00068 Pasmant, E., Parfait, B., Luscan, A., Goussard, P., Briand-Suleau, A., Laurendeau, I., . . . Vidaud, D. (2015). Neurofibromatosis type 1 molecular diagnosis: what can NGS do for you when you have a large gene with loss of function mutations? Eur J Hum Genet, 23 (5), 596-601. doi:10.1038/ejhg.2014.145 Sabbagh, A., Pasmant, E., Imbard, A., Luscan, A., Soares, M., Blanche, H., . . . Wolkenstein, P. (2013). NF1 molecular characterization and neurofibromatosis type I genotype-phenotype correlation: the French experience. Hum Mutat, 34 (11), 1510-1518. doi:10.1002/humu.22392 Summerer, A., Schafer, E., Mautner, V. F., Messiaen, L., Cooper, D. N., & Kehrer-Sawatzki, H. (2019). Ultra-deep amplicon sequencing indicates absence of low-grade mosaicism with normal cells in patients with type-1 NF1 deletions. Hum Genet, 138 (1), 73-81. doi:10.1007/s00439-018-1961-5 Uusitalo, E., Leppavirta, J., Koffert, A., Suominen, S., Vahtera, J., Vahlberg, T., . . . Peltonen, S. (2015). Incidence and mortality of neurofibromatosis: a total population study in Finland. J Invest Dermatol, 135 (3), 904-906. doi:10.1038/jid.2014.465 Valero, M. C., Martin, Y., Hernandez-Imaz, E., Marina Hernandez, A., Melean, G., Valero, A. M., . . . Hernandez-Chico, C. (2011). A highly sensitive genetic protocol to detect NF1 mutations. J Mol Diagn, 13 (2), 113-122. doi:10.1016/j.jmoldx.2010.09.002 van Minkelen, R., van Bever, Y., Kromosoeto, J. N., Withagen-Hermans, C. J., Nieuwlaat, A., Halley, D. J., & van den Ouweland, A. M. (2014). A clinical and genetic overview of 18 years neurofibromatosis type 1 molecular diagnostics in the Netherlands. Clin Genet, 85 (4), 318-327. doi:10.1111/cge.12187 Van Royen, K., Brems, H., Legius, E., Lammens, J., & Laumen, A. (2016). Prevalence of neurofibromatosis type 1 in congenital pseudarthrosis of the tibia. Eur J Pediatr, 175 (9), 1193-1198. doi:10.1007/s00431-016-2757-z Vander Have, K. L., Hensinger, R. N., Caird, M., Johnston, C., & Farley, F. A. (2008). Congenital pseudarthrosis of the tibia. J Am Acad Orthop Surg, 16 (4), 228-236. Wang, N., Jiao, K., He, J., Zhu, B., Cheng, N., Sun, J., . . . Zhu, W. (2024). Diagnosis of Challenging Spinal Muscular Atrophy Cases with Long-Read Sequencing. J Mol Diagn, 26 (5), 364-373. doi:10.1016/j.jmoldx.2024.02.004 Zhang, J., Tong, H., Fu, X., Zhang, Y., Liu, J., Cheng, R., . . . Yao, Z. (2015). Molecular Characterization of NF1 and Neurofibromatosis Type 1 Genotype-Phenotype Correlations in a Chinese Population. Sci Rep, 5 (2045-2322 (Electronic)), 11291. doi:10.1038/srep11291 Zheng, Y., Zhu, G., Liu, Y., Zhao, W., Yang, Y., Luo, Z., . . . Hu, Z. (2022). Case series of congenital pseudarthrosis of the tibia unfulfilling neurofibromatosis type 1 diagnosis: 21% with somatic NF1 haploinsufficiency in the periosteum. Hum Genet, 141 (8), 1371-1383. doi:10.1007/s00439-021-02429-2 Zhu, G., Zheng, Y., Liu, Y., Yan, A., Hu, Z., Yang, Y., . . . Mei, H. (2019). Identification and characterization of NF1 and non-NF1 congenital pseudarthrosis of the tibia based on germline NF1 variants: genetic and clinical analysis of 75 patients. Orphanet J Rare Dis, 14 (1), 221. doi:10.1186/s13023-019-1196-0 Zhu, L., Zhang, Y., Tong, H., Shao, M., Gu, Y., Du, X., . . . Zhang, G. (2016). Clinical and Molecular Characterization of NF1 Patients: Single-Center Experience of 32 Patients From China. Medicine (Baltimore), 95 (10), e3043. doi:10.1097/MD.0000000000003043 Additional Declarations No competing interests reported. Supplementary Files FigureS1SNVs.tif Supplemental Fig.1 The Integrative Genomics Viewer (IGV) plots showing the discordant results for SNVs/Indels. FigureS2v1CNVseq.tif Supplemental Fig.2 The Integrative Genomics Viewer (IGV) plots showing the discordant results for the 1.24Mb microdeletion CNV of proband P134. TableS1allsampleinfo.xlsx TableS2sampleStat.xlsx TableS37CNV.xlsx TableS4varFreq.xlsx Cite Share Download PDF Status: Posted Version 1 posted 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5382766","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":377047858,"identity":"a6b414e7-ad7c-44ab-bb5f-453740b2ca98","order_by":0,"name":"Yu Zheng","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAvUlEQVRIiWNgGAWjYNACA5sEMJ1QQLyWtAQGNpAWA+KtOQzRwkCMFoMbOWaSPwrO5/HLdyd+eGDAIM8vdoCwFgkJg9vFkm28myWADjOcOTuBCC0GBrcTNxzj3QDSkmBwmxgtCQbnQFo2/yBeywGDAyAt24izRfLMs2LLBoPkxJltudssEgwkCPuF73jyxps//tgl9jOf3XzzR4WNPL80AS0KBzhMJJD4EjhVwoF8A/vjD4SVjYJRMApGwYgGAKAZROVyOVFNAAAAAElFTkSuQmCC","orcid":"","institution":"The Affiliated Children's Hospital of Xiangya School of Medicine, Hunan Children's Hospital, Central South University","correspondingAuthor":true,"prefix":"","firstName":"Yu","middleName":"","lastName":"Zheng","suffix":""},{"id":377047859,"identity":"60f88abe-5bda-4f33-8698-14c3879044d8","order_by":1,"name":"Miaomiao Chen","email":"","orcid":"","institution":"The Affiliated Children's Hospital of Xiangya School of Medicine, Hunan Children's Hospital, Central South University","correspondingAuthor":false,"prefix":"","firstName":"Miaomiao","middleName":"","lastName":"Chen","suffix":""},{"id":377047860,"identity":"4441adee-c1b2-4ad2-b122-3897b7ba3c1e","order_by":2,"name":"Shuju Zhang","email":"","orcid":"","institution":"The Affiliated Children's Hospital of Xiangya School of Medicine, Hunan Children's Hospital, Central South University","correspondingAuthor":false,"prefix":"","firstName":"Shuju","middleName":"","lastName":"Zhang","suffix":""},{"id":377047861,"identity":"6c932d93-e903-4a7c-85ad-a589d4c24960","order_by":3,"name":"Yu Peng","email":"","orcid":"","institution":"The Affiliated Children's Hospital of Xiangya School of Medicine, Hunan Children's Hospital, Central South University","correspondingAuthor":false,"prefix":"","firstName":"Yu","middleName":"","lastName":"Peng","suffix":""},{"id":377047862,"identity":"f043df8f-465e-4412-9b98-62710078ca57","order_by":4,"name":"Xinghan Wu","email":"","orcid":"","institution":"The Affiliated Children's Hospital of Xiangya School of Medicine, Hunan Children's Hospital, Central South University","correspondingAuthor":false,"prefix":"","firstName":"Xinghan","middleName":"","lastName":"Wu","suffix":""},{"id":377047863,"identity":"9b0e498f-49e3-40f4-a308-bc5f02444019","order_by":5,"name":"Danni Guo","email":"","orcid":"","institution":"The Affiliated Children's Hospital of Xiangya School of Medicine, Hunan Children's Hospital, Central South University","correspondingAuthor":false,"prefix":"","firstName":"Danni","middleName":"","lastName":"Guo","suffix":""},{"id":377047864,"identity":"76001235-7397-4202-ac44-2789d9ed73c9","order_by":6,"name":"Yaoxi Liu","email":"","orcid":"","institution":"The Affiliated Children's Hospital of Xiangya School of Medicine, Hunan Children's Hospital, Central South University","correspondingAuthor":false,"prefix":"","firstName":"Yaoxi","middleName":"","lastName":"Liu","suffix":""},{"id":377047865,"identity":"8bd5e798-97d9-4e56-9daa-69dd6badaa20","order_by":7,"name":"Aiping Mao","email":"","orcid":"","institution":"Department of Research and Development, Berry Genomics Corporation","correspondingAuthor":false,"prefix":"","firstName":"Aiping","middleName":"","lastName":"Mao","suffix":""},{"id":377047866,"identity":"a22e1e9e-d07f-4dc9-9c12-d4adae4d9250","order_by":8,"name":"Danhua Li","email":"","orcid":"","institution":"Department of Research and Development, Berry Genomics Corporation","correspondingAuthor":false,"prefix":"","firstName":"Danhua","middleName":"","lastName":"Li","suffix":""},{"id":377047867,"identity":"45f341fc-767c-42a8-9f21-5d75081e2408","order_by":9,"name":"Tiantian Xie","email":"","orcid":"","institution":"Department of Research and Development, Berry Genomics Corporation","correspondingAuthor":false,"prefix":"","firstName":"Tiantian","middleName":"","lastName":"Xie","suffix":""},{"id":377047868,"identity":"b43908ed-71bb-4d7f-93c4-5e32013ec31c","order_by":10,"name":"Haibo Mei","email":"","orcid":"","institution":"The Affiliated Children's Hospital of Xiangya School of Medicine, Hunan Children's Hospital, Central South University","correspondingAuthor":false,"prefix":"","firstName":"Haibo","middleName":"","lastName":"Mei","suffix":""},{"id":377047869,"identity":"cfbeaabb-7693-4a11-8cea-9f6fa5450105","order_by":11,"name":"Guanghui Zhu","email":"","orcid":"","institution":"The Affiliated Children's Hospital of Xiangya School of Medicine, Hunan Children's Hospital, Central South University","correspondingAuthor":false,"prefix":"","firstName":"Guanghui","middleName":"","lastName":"Zhu","suffix":""},{"id":377047870,"identity":"4144d26f-aabf-4f3e-ba4e-a652adc8c129","order_by":12,"name":"Hua Wang","email":"","orcid":"","institution":"The Affiliated Children's Hospital of Xiangya School of Medicine, Hunan Children's Hospital, Central South University","correspondingAuthor":false,"prefix":"","firstName":"Hua","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2024-11-03 15:38:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5382766/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5382766/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":70956414,"identity":"98c29001-6b63-466f-b6c4-058caf5cd2da","added_by":"auto","created_at":"2024-12-09 14:24:14","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":220945,"visible":true,"origin":"","legend":"\u003cp\u003eThe strategy of comprehensive analysis of NF1. (A) The location of primers and 14 amplicons amplified in this study. (B) Agarose gel electrophoresis images showing the generated 14 DNA amplicons. (C) The flowchart of molecular genetic diagnosis of NF1 using LRS. The blue arrow indicates 14 intragenic primers (primer set 1) and the amplicons generated using these primers were shown by blue squares. The red arrow indicates 25 gap primers (primer set 2).\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-5382766/v1/6d602571547e4a63b89fd55e.png"},{"id":70956796,"identity":"8fe82d6f-3296-4b49-8831-b4cd1cbac7a8","added_by":"auto","created_at":"2024-12-09 14:32:13","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":270834,"visible":true,"origin":"","legend":"\u003cp\u003eThe Schematic representation of participant cohort and comparison analysis results.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-5382766/v1/5b9edb9fa0828b2d8fee9363.png"},{"id":70956795,"identity":"588d4628-e9df-42a4-8603-ca49a1030d4c","added_by":"auto","created_at":"2024-12-09 14:32:13","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":124438,"visible":true,"origin":"","legend":"\u003cp\u003eThe IGV plots showing the discordant results for intragenic deletion. E: exon.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-5382766/v1/a270a2907953695e393697a1.png"},{"id":70956415,"identity":"ce4d1f80-e4d8-4996-9a07-bd5e04ac2891","added_by":"auto","created_at":"2024-12-09 14:24:14","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":149918,"visible":true,"origin":"","legend":"\u003cp\u003eThe distribution of variants detected. (A) The percentage of \u003cem\u003eNF1\u003c/em\u003e variants in clinical NF1 group and clinical CP group. (B) The distribution of \u003cem\u003eNF1 \u003c/em\u003evariants in clinical NF1 group. (C) The distribution of \u003cem\u003eNF1\u003c/em\u003e variants in clinical CP group.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-5382766/v1/cfff2df63bd6db3d9315dc91.png"},{"id":71432818,"identity":"ae5c277f-6076-412b-92bc-c127ac300bb8","added_by":"auto","created_at":"2024-12-15 07:31:25","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1297089,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5382766/v1/b8015ea7-195e-49bf-9d3c-773053e162ec.pdf"},{"id":70956419,"identity":"5cf62c08-96b5-4dc3-8d0c-1d3f9a7cf4b1","added_by":"auto","created_at":"2024-12-09 14:24:14","extension":"tif","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":8566188,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplemental Fig.1\u003c/strong\u003e The Integrative Genomics Viewer (IGV) plots showing the discordant results for SNVs/Indels.\u003c/p\u003e","description":"","filename":"FigureS1SNVs.tif","url":"https://assets-eu.researchsquare.com/files/rs-5382766/v1/0343847b223563875e7d7a73.tif"},{"id":70956418,"identity":"38281423-abbf-4c08-9f2f-58cd48d088f0","added_by":"auto","created_at":"2024-12-09 14:24:14","extension":"tif","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":9127076,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplemental Fig.2 \u003c/strong\u003eThe Integrative Genomics Viewer (IGV) plots showing the discordant results for the 1.24Mb microdeletion CNV of proband P134.\u003c/p\u003e","description":"","filename":"FigureS2v1CNVseq.tif","url":"https://assets-eu.researchsquare.com/files/rs-5382766/v1/bef582b262a517d55770a278.tif"},{"id":70956412,"identity":"54540016-6d69-4383-890d-6a736abada68","added_by":"auto","created_at":"2024-12-09 14:24:13","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":30261,"visible":true,"origin":"","legend":"","description":"","filename":"TableS1allsampleinfo.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-5382766/v1/2f27ac7cac5c3fbcdba13324.xlsx"},{"id":70956797,"identity":"91e87a78-26e9-4331-856a-d227f39866ff","added_by":"auto","created_at":"2024-12-09 14:32:14","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":11064,"visible":true,"origin":"","legend":"","description":"","filename":"TableS2sampleStat.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-5382766/v1/f1fb9577cfa632bcf39c36e2.xlsx"},{"id":70956410,"identity":"53548f46-f3c5-4cca-b6dd-33d2b034b754","added_by":"auto","created_at":"2024-12-09 14:24:13","extension":"xlsx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":10378,"visible":true,"origin":"","legend":"","description":"","filename":"TableS37CNV.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-5382766/v1/45fd150272532c034218d5f3.xlsx"},{"id":70956417,"identity":"c9031415-c5a2-430f-8b3e-84a2864dfe34","added_by":"auto","created_at":"2024-12-09 14:24:14","extension":"xlsx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":20649,"visible":true,"origin":"","legend":"","description":"","filename":"TableS4varFreq.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-5382766/v1/cafa0f5242f5d6f57c24cd38.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Comprehensive Analysis of the NF1 gene Using Long-Read Sequencing Improved Neurofibromatosis type 1 Molecular Diagnosis","fulltext":[{"header":"Introduction","content":"\u003cp\u003eNeurofibromatosis type 1 (NF1, OMIM: 162200) is an autosomal dominant genetic disease occurs in approximately 1/3000 births (Evans et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Lammert, Friedman, Kluwe, \u0026amp; Mautner, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Uusitalo et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). NF1 have cutaneous, ocular, or osseous manifestations, which exhibit both tissue-related and age-related diversity. Caf\u0026eacute; au lait macules (CALMs) are the most common manifestations in NF1 from infancy, and other manifestations before adolescence can help in NF1 clinical diagnosis including: skinfold freckling or neurofibroma, osseous lesion such as congenital pseudarthrosis (CP), ocular abnormalities such as Lisch nodules or optic pathway glioma (Gutmann et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Legius et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Dysplasia of a long bone typically tibial CP (CPT) is found in ~\u0026thinsp;2% of children with NF1, which is intractable in pediatric orthopedics (Gutmann et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Hefti et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; O'Donnell et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Vander Have, Hensinger, Caird, Johnston, \u0026amp; Farley, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Up to 84% of CP participants present NF1, while others do not manifest NF1 (non-NF1) with unknown etiology (Neurofibromatosis, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e1988\u003c/span\u003e; Van Royen, Brems, Legius, Lammens, \u0026amp; Laumen, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). CALMs with high morbidity in children which require differential diagnosis, an earlier screening and precise molecular diagnosis are necessary. For children unfulfilling the current clinical diagnostic criteria who meet only one of the criteria, without molecular diagnosis, it\u0026rsquo;s challenging to make a clinical diagnosis of Neurofibromatosis type 1 (NF1) in early childhood.\u003c/p\u003e \u003cp\u003eNF1 is caused by the haploinsufficiency of the \u003cem\u003eNF1\u003c/em\u003e gene. The \u003cem\u003eNF1\u003c/em\u003e gene is located on human chromosome 17q11.2, with a genomic length of 370 Kb. It has two full-length transcript isoforms: NM_000267.3 (57 exons) and NM_001042492.3 (58 exons). The NM_001042492.3 is the MANE (Matched Annotation from the NCBI and EMBL-EBI) selected isoform, with a length of 12.4 Kb. Due to its large size, NF1 is associated with multiple types of variations such as SNVs, Indels, large segmental deletion or duplication, \u003cem\u003eNF1\u003c/em\u003e microdeletion, insertion, inversion, microsatellite, low faction of mosaicism or somatic second-hit variants. These variations originate either from coding regions, or non-coding regions such as introns, 5\u0026rsquo;UTR, upstream regulating regions. To date (by 1th May, 2024), there were 4462 variants recorded in the professional version of the Human Genome Mutation Database (HGMD, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.hgmd.cf.ac.uk/ac/\u003c/span\u003e\u003cspan address=\"https://www.hgmd.cf.ac.uk/ac/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), and 4579 pathogenic or likely pathogenic variations in \u003cem\u003eNF1\u003c/em\u003e have been recorded in ClinVar database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/clinvar/\u003c/span\u003e\u003cspan address=\"https://www.ncbi.nlm.nih.gov/clinvar/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Generally, these pathogenic variants are diverse and lack of mutation hotspots. Moreover, the detection of \u003cem\u003eNF1\u003c/em\u003e variants is complicated by the presence of the pseudogene \u003cem\u003eNF1P1\u003c/em\u003e, which shares a high sequence similarity with some exons of \u003cem\u003eNF1\u003c/em\u003e. These increased the difficulty and complexity in precisely detecting the variants affecting \u003cem\u003eNF1\u003c/em\u003e.\u003c/p\u003e \u003cp\u003eCurrently, multiple genetic testing technologies are used to detect \u003cem\u003eNF1\u003c/em\u003e variants, and a multi\u0026shy;step approach is required to analysis of blood genomic DNA and mRNA to obtain a higher detection rate. Primarily, next generation sequencing (NGS) based technologies are commonly employed, such as exome sequencing (ES), clinical exome sequencing and genome sequencing (GS) including low-depth sequencing for copy number variations (CNV-seq), ultra high amplicon sequencing. Other technologies maybe supplemented to facilitate the testing, including multiplex ligation-dependent probe amplification (MLPA), quantitative PCR, fish fluorescence in situ hybridization (FISH) or Sanger sequencing. The diagnostic rate using genomic DNA (gDNA) was approximately 60\u0026ndash;90% (Cali et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Pasmant et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; van Minkelen et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Zhang et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). It was reported that using both gDNA and cDNA the combination molecular diagnostic rate of NF1 could close to 95% (Evans et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Sabbagh et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Valero et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). In addition, less than 1% of the NF1 patients were found abnormal chromosomal karyotype (Messiaen et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2000\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn general, current genetic testing methods for NF1 can detect limited types of variation, and multiple PCR reactions and library preparations are usually required before sequencing, as well as follow-up MLPA testing for whole \u003cem\u003eNF1\u003c/em\u003e or intragenic exon copy number variants (CNVs) (D. Bianchessi et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; D. A.-O. Bianchessi et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Summerer et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; L. Zhu et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Additionally, NGS-based methods generate a vast amount of sequence data, but they are unable to detect inversions or translocations. Thus, to obtain a higher diagnostic rate and more precise genetic diagnosis, a more comprehensive method needs to be developed. Recently, with the rapid development of long-read sequencing (LRS), this technology has been able to provide more comprehensive and accurate sequence data in a single step because of longer reads, more even sequence coverage, and avoidance of PCR amplification bias. Targeted-LRS has been successfully applied in the genetic diagnosis of thalassemia, congenital adrenal hyperplasia, fragile X syndrome, hemophilia A, and spinal muscular atrophy (Chen et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Liang et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Liang et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Liu et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Liu et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Wang et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In this study, we developed a locus-specific PCR approach combined with LRS to analyze the \u003cem\u003eNF1\u003c/em\u003e gene. This method allows for the simultaneous analysis of SNVs, Indels, mosaicism, CNVs and structural variations in one assay. Here, we retrospectively analyzed 191 clinical samples of NF1 participants, using either blood or tissue samples. The results demonstrated that comprehensive analysis of NF1 (CANF1) has high clinical utility with feasibility of improving NF1 diagnosis.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eStudy participants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Ethics Committee of Hunan Children\u0026apos;s Hospital (Approval No. HCHLL-2024-56). The samples were obtained with appropriate informed consent from all participants or their legal guardians. Children less than 18 years old from Chinese mainland with CALMs or CPs performed genetic testing were initially collected. In this retrospective study, a total of 191 individuals from Chinese mainland were recruited, including 181 probands with clinical presentations of NF1 or CP and 10 samples from NF1 family members. These participants underwent ES and or GS. Among them, 36 participants had a family history of NF1 (including two monozygotic twins) (Supplemental Table 1). The clinical diagnostic criteria of NF1 included the following: more than 6 Caf\u0026eacute; au lait macules (CALMs) with a diameter greater than 5 mm; freckling in the axillary or inguinal region; more than 2 neurofibromas or one plexiform neurofibroma; optic pathway glioma; more than 2 iris Lisch nodules or more than 2 choroidal abnormalities; a distinctive osseous lesion such as congenital pseudarthrosis of the tibia; and NF1 family history. Individuals who meet two or more of above-mentioned clinical characteristics can be diagnosed as NF1. According to the clinical criteria for NF1, 137 samples fulfilled the NF1 clinical diagnosis including 127 probands and 10 NF1 family members, and 54 samples presented with CP but unfulfilling the NF1 clinical criteria (non-NF1-CP).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAs for the sample source, 138 blood samples (132 having NF1) and 53 tissue samples (5 having NF1) were used (Table S1). Peripheral blood samples were collected into EDTA tubes and gDNA was also extracted using the DNease Blood \u0026amp; Tissue Kit (Qiagen). Periosteum at the pseudoarthrosis site were cut into small pieces to ensure more efficient lysis and were preserved in liquid nitrogen. gDNA in periosteum was extracted using the following steps: (1) All samples were digested in 180 \u0026micro;l Buffer ATL (Qiagen) and 20 \u0026micro;l of Proteinase K at 56\u0026deg;C C until the tissues were completely lysed. (2) DNA was extracted from each sample following the protocol of Qiagen DNeasy Blood \u0026amp; Tissue Kit (Qiagen). (3) DNA concentrations (ng/\u0026mu;l) were measured using the dsDNA High Sensitivity kit on a Qubit Fluorometer 2.0 (ThermoFisher Scientific). (4) To visualize DNA extractions, gel electrophoresis was performed on 1% agarose gels stained with SYBR Safe DNA Gel Stain (Invitrogen). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMultiplex long-range PCR and PacBio sequencing\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMultiplex long-range PCR were conducted with two sets of primers in one reaction. One set of primers was designed to identify SNVs/Indels of \u003cem\u003eNF1\u003c/em\u003e though amplifying 14 DNA fragments which were consisted of 58 exon regions and flanking intron regions (Fig.1A and Fig.1B). Another set of primers included 25 gap primers covering targeted region of 30-kb upstream and 30-kb downstream of \u003cem\u003eNF1\u003c/em\u003e to detect large deletions (Fig.1A). Specific DNA fragments were amplified by according to gap primers for samples with variants caused by large deletions. In summary, CANF1 covered all the exons of \u003cem\u003eNF1\u003c/em\u003e, and the majority of the known SNVs/indels reported by HGMD professional (https://www.hgmd.cf.ac.uk) and or ClinVar (https://www.ncbi.nlm.nih.gov/clinvar/) databases.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGenomic DNA was extracted using DNease Blood \u0026amp; Tissue Kit (Qiagen). Multiplex long-range PCR were conducted using KOD FX Neo (Toyobo Co. Ltd., Osaka, Japan) in 50-\u0026mu;L reactions containing 10-100 ng of genomic DNA, 1 x PCR buffer for KOD FX Neo, 0.4 mM of each dNTP, 1 \u0026mu;M of primer mixture and 1 \u0026mu;L of KOD FX Neo (TOYOBO). The amplification procedure was as follows: pre-denaturation at 94\u0026deg;C for 5 min; 32 cycles (denaturation at 98\u0026deg;C for 15 s and extension at 68\u0026deg;C for 12 min); and extension at 68\u0026deg;C for 10 min. Amplicons generated from long-range PCR were sequenced by long-read sequencing. The pre-libraries of single-molecule real-time (SMRT) sequencing (PacBio) were prepared and specific barcodes were added. The Sequel Binding Kit 2.0 (PacBio) was used to generate the SMRTbell\u003csup\u003e@\u003c/sup\u003e library and sequencing was generated on the Sequel II platform (PacBio).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePacBio data analysis and variant calling\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe raw data were processed to obtain highly accurate circular consensus sequencing (CCS) reads, and then the filtered and debarcoded CCS reads were aligned to human GRCh38/hg38 genome sequences using pbmn2 of the SMRT Link analysis software (PacBio). SNVs/Indels were identified using FreeBayes 1.3.4. The deletions in the targeted region containing 30 kb upstream and downstream of \u003cem\u003eNF1\u003c/em\u003e were analyzed through alignment with the reference genome GRCh38/hg38. The exact breakpoints of deletions were determined and displayed using the Integrative Genomics Viewer (IGV). The haplotype analysis of 14 DNA fragments amplified using exon primers mentioned above was conducted. Fourteen fragments each carrying one haplotype suggested the samples had \u003cem\u003eNF1\u003c/em\u003e microdeletion, and subsequent CNV-seq was used to identify the\u003cem\u003e\u0026nbsp;NF1\u003c/em\u003e microdeletion.\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eThe Strategy of Comprehensive Analysis of NF1\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe strategy of comprehensive analysis of NF1(CANF1) was constructed in this study. Multiplex long-range PCR was performed using two sets of primers in one reaction. Fourteen DNA fragments covering 58 exons and flanking intron regions were generated using primer set 1 to identify SNVs/Indels and intragenic copy number variants of the \u003cem\u003eNF1\u003c/em\u003e gene (Figure. 1A-B). Twenty-five gap primers (primer set 2) covering a targeted region of 30 kb upstream and 30 kb downstream of the \u003cem\u003eNF1\u003c/em\u003e gene were designed to identify intragenic CNV (Fig. 1A). The flowchart of molecular genetic diagnosis of NF1 using CANF1 was shown in Fig. 1C. Fourteen amplicons, each containing only one haplotype, can give a clue to the presentation of large deletions including \u003cem\u003eNF1\u003c/em\u003e and its flanking regions, so-called \u003cem\u003eNF1\u003c/em\u003e microdeletion, which was confirmed by CNV-seq. \u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe Precise Genetic Diagnosis of NF1 by CANF1\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 191 clinical samples were enrolled, and they were classified into 127 NF1 probands, 54 CP probands and 10 NF1 family members according to the NF1 diagnostic criteria (Fig.2, Supplemental Table 2). The detailed information and genetic diagnosis results were listed in Supplemental Table 1. Both CANF1 and the control method were performed in 181 probands and 10 family members. Comparative analysis indicated that 176 probands (97.2%) exhibited concordant results, and the other 5 probands (2.8%) showed discordant results (Fig.2). Out of 176 probands with concordant results, 122 probands (69.3%) carried pathogenic variants and 3 probands (1.7%) had variants of uncertain significance (VUS) and the remaining 51 probands (29.0%) harbored no variants. Of the 5 discordant results, one was established a new diagnosis and 4 probands were improved diagnosis by CANF1 (Fig.2).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe probands with discordant results between CANF1 and the control method were exhibited in Table 1. In P77 proband, CANF1 identified a deep intron variant NM_001042492.3:c.5812+332A\u0026gt;G which was not detected by ES. The variant was also confirmed by Sanger sequencing (Supplemental Fig.1A). In other 4 probands, precise diagnosis was conducted by CANF1 and the results of the control method were improved by CANF1. In P51 proband, a VUS c.1527+1346G\u0026gt;C located at the deep intron region of \u003cem\u003eNF1\u003c/em\u003e was solely identified by CANF1, not by the control method ES (Supplemental Fig.1B). In proband P71, peripheral blood and tissue were used for genetic diagnosis. Both CANF1 and ES identified one disease-causing variant c.4330A\u0026gt;G when using a peripheral blood sample, and two pathogenic variants, c.653delA and c.4330A\u0026gt;G, when using tissue sample. Nevertheless,\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1 Discordant results between CANF1 and the control method.\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 7%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSample ID\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 7%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 8%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDignosis by clinical findings\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 7%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eControl method\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 13%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eResults of Control method\u003c/strong\u003e\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 40%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCANF1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 17%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOutcomes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ecDNA\u003c/strong\u003e\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eExon\u003c/strong\u003e\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariant Type\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 7%;\"\u003e\n \u003cp\u003eP77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7%;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003eNF1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7%;\"\u003e\n \u003cp\u003eES\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18%;\"\u003e\n \u003cp\u003ec.5812+332A\u0026gt;G\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9%;\"\u003e\n \u003cp\u003eIntron 39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12%;\"\u003e\n \u003cp\u003eIntron variant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17%;\"\u003e\n \u003cp\u003eA new diagnosis detected by CANF1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 7%;\"\u003e\n \u003cp\u003eP51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7%;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003eCPT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7%;\"\u003e\n \u003cp\u003eES\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18%;\"\u003e\n \u003cp\u003ec.1527+1346G\u0026gt;C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9%;\"\u003e\n \u003cp\u003eIntron 13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12%;\"\u003e\n \u003cp\u003eIntron variant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17%;\"\u003e\n \u003cp\u003eA VUS in intron detected by CANF1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 7%;\"\u003e\n \u003cp\u003eP71\u003c/p\u003e\n \u003cp\u003e(Tissue)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7%;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003eNF1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7%;\"\u003e\n \u003cp\u003eES\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003ec.653delA, c.4330A\u0026gt;G\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18%;\"\u003e\n \u003cp\u003ec.653delA/c.4330A\u0026gt;G\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9%;\"\u003e\n \u003cp\u003eExon 6/ Exon 32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12%;\"\u003e\n \u003cp\u003eFrameshift/ missense\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17%;\"\u003e\n \u003cp\u003eA trans configuration detected by CANF1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 7%;\"\u003e\n \u003cp\u003eP172\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7%;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003eNF1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7%;\"\u003e\n \u003cp\u003eES\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003eE37-E40 del 21025 bp\u003c/p\u003e\n \u003cp\u003e(chr17:31314007-31335032)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18%;\"\u003e\n \u003cp\u003eE37-E40 del 25799bp ins 94bp\u0026nbsp;\u003cbr\u003e\u0026nbsp;(chr17:31309477-31335275 ins 94bp )\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9%;\"\u003e\n \u003cp\u003eE37-E40 del\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12%;\"\u003e\n \u003cp\u003eIntragenic deletion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17%;\"\u003e\n \u003cp\u003eA precise deletion and breakpoint detected by CANF1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 7%;\"\u003e\n \u003cp\u003eP90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7%;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8%;\"\u003e\n \u003cp\u003eNF1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7%;\"\u003e\n \u003cp\u003eES\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13%;\"\u003e\n \u003cp\u003eE13-E18 del, E49-E58 del 42932 bp\u003c/p\u003e\n \u003cp\u003e(chr17:31349099-31392031)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18%;\"\u003e\n \u003cp\u003eE49-E58 del 53004bp ins 306bp\u0026nbsp;\u003cbr\u003e\u0026nbsp;(chr17:31349202-31402205 ins 306bp)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9%;\"\u003e\n \u003cp\u003eE49-E58 del\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12%;\"\u003e\n \u003cp\u003eIntragenic deletion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17%;\"\u003e\n \u003cp\u003eA precise deletion and breakpoint detected by CANF1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003e*\u003c/sup\u003eE: exon, Del: deletion, ins: insertion, NA: not found.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCANF1 identified that these two variants were in trans-configuration through customized specific genetic testing\u0026nbsp;by\u0026nbsp;overlapping DNA fragments (Supplemental\u0026nbsp;Fig.1C).\u003c/p\u003e\n\u003cp\u003eAn intragenic deletion was identified both by CANF1 and the control method (enhanced ES with exon-based CNV analysis) in proband P172. CANF1 detected a 25.8 kb deletion, rather than a 21.0 kb deletion detected by ES. This variant was confirmed by gap PCR through agarose gel electrophoresis (Fig.3A). The breakpoints of this intragenic deletion were also identified by CANF1 and were exhibited by IGV plots (Fig.3A). This highlighted that CANF1 has higher resolution. In proband P90, ES indicated that this proband had a heterozygous exon E49 to E58 deletion, and a heterozygous exon E13 to E18 deletion. However, the haplotype analysis of CANF1 confirmed the breakpoints and exact length of the deletion of exon E49 to E58, but revealed that there was no deletion in the exon 13 to 18 region (Fig.3B).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn addition, 14 amplicons each containing only one haplotype illustrated \u003cem\u003eNF1\u003c/em\u003e microdeletion which was also identified by control methods ES and CNV-seq. A total of 7 probands had only one haplotype in every fragment, which were also tested by CNV-seq (Supplemental Table 3). Among them, 6 (85.7%) had \u003cem\u003eNF1\u003c/em\u003e microdeletion, while the rest one (14.3%) had no variants (Table S3). For instance, in proband P134, both CANF1 haplotype analysis and CNV-seq exhibited that the 1.24Mb microdeletion expanding from \u003cem\u003eCRLF3\u003c/em\u003e gene to \u003cem\u003eSUZ12\u003c/em\u003e gene (Supplemental Fig.2), while ES detected a smaller size of 1.006Mb microdeletion (Table S1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe Variants Distribution in Clinical NF1 Group and Clinical CP Group\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe enrolled 181 probands were divided into clinical NF1 and CP groups according to NF1 clinical diagnostic criteria, and CP groups included probands not fulfilling the NF1 diagnostic criteria (non-NF1-CP). The results of CANF1 showed the frequency of \u003cem\u003eNF1\u003c/em\u003e variants in clinical NF1 and CP groups was 93.7% and 20.4%, respectively (Fig.4A). In 127 probands in the clinical NF1 group, 117 (92.9%) probands were identified as carrying pathogenic or likely pathogenic variants of \u003cem\u003eNF1\u003c/em\u003e by CANF1. Two (1.6%) probands had VUS variants, and 8 probands (6.3%) were without variants of the \u003cem\u003eNF1\u003c/em\u003e gene. Nine out of 54 CP probands (16.7%) were identified as carrying pathogenic or likely pathogenic variants of the \u003cem\u003eNF1\u0026nbsp;\u003c/em\u003egene. Two probands (3.7%) had VUS variants, and 43 probands (79.6%) were without variants of the \u003cem\u003eNF1\u003c/em\u003e gene.\u003c/p\u003e\n\u003cp\u003eIn the clinical NF1 group, the most frequent variants were pathogenic SNVs/Indels, accounting for 91.6%, followed by 4.2% \u003cem\u003eNF1\u003c/em\u003e microdeletions (Fig.4B). In the clinical CP group, 3 types of variants were identified, including 8 pathogenic SNVs/Indels (72.7%), 2 VUS (18.2%) and 1 somatic mosaicism (9.1%) (Fig.4B).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe Spectrum of Variants Detected by CANF1\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe variants detected in this study were listed in Supplemental Table 4. A total of 132 variants were identified by CANF1. Among them, 94.7% were SNVs/indels, 1.5% were intragenic variants, and 3.8% were \u003cem\u003eNF1\u003c/em\u003e microdeletion. The most frequent variant was c.1541_1542delAG (3.8%, found in 5 probands), followed by c.1885G\u0026gt;A (3.0%, found in 4 probands). c.574C\u0026gt;T, c.2034delinsCA and the recurrent 1.24 Mb \u003cem\u003eNF1\u003c/em\u003e microdeletion were found in 3 probands (2.3%) respectively. The most frequent variant type was frameshift (32.6%), followed by nonsense (29.5%), missense (15.9%) and intron variants (15.9%).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe differential testing of \u003cem\u003eNF1\u003c/em\u003e with CALMs\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn our single-center collected 217 children with CALMs performed genetic testing, 50% (109/217) of the probands were obtained genetic diagnosis and the causing genes including \u003cem\u003eNF1, PTPN11\u003c/em\u003e, \u003cem\u003eSPRED1\u003c/em\u003e, and \u003cem\u003eTSC2.\u0026nbsp;\u003c/em\u003eThe \u003cem\u003eNF1\u003c/em\u003e gene occupied the vast majority of them (97/109=89%), followed by \u003cem\u003ePTPN11\u0026nbsp;\u003c/em\u003e(3/109=2.8%), \u003cem\u003eSPRED1\u0026nbsp;\u003c/em\u003e(1/109=0.9%), and \u003cem\u003eTSC2\u0026nbsp;\u003c/em\u003e(1/109=0.9%). Overall, 44.7% (97/217) out of the 217 CALMs patients were detected \u003cem\u003eNF1\u003c/em\u003e pathogenic variants. In the enrolled 181 probands performed CANF1 assay, 126 with CALMs and NF1 clinical diagnosis and 92.1% (116/126) of which were obtained \u003cem\u003eNF1\u003c/em\u003e genetic diagnosis. Two of the 126 cases were found \u003cem\u003eNF1\u003c/em\u003e VUS variants.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eWe developed CANF1 assay as a comprehensive method to detect variants in the \u003cem\u003eNF1\u003c/em\u003e gene using gDNA of NF1 or suspecting NF1 participants. The assay covered all exons of the \u003cem\u003eNF1\u003c/em\u003e gene and 30 kb both upstream and downstream for intragenic CNVs, and achieved a higher detection rate and accuracy than conventional approaches, which will help in screening and differential diagnosis of NF1 in pediatrics. Conventional approaches had limitations in diagnostic accuracy, cost, and convenience. For instance, targeted NGS received a detection rate of 88% in 279 NF1 patients (Pasmant et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), and ES received a detection rate of 74.5% in 55 NF1 patients(G. Zhu et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The combination of gDNA and cDNA sequence analysis using multi-step NGS, MLPA, and chromosomal microarray analysis (CMA) or karyotyping could detect variants in approximately 95% of NF1 patients. However, this often requires multiple techniques and sample types. Moreover, NF1 is a multisystem disorder with variable expression and various phenotypes, affecting multiple system such cutaneous, ophthalmic, skeletal, nervous systems. Due to the complexity of clinical manifestations, differential diagnosis is usually needed in clinic. Here, CANF1 assay received a detection rate of 92.9% in 127 NF1 probands using gDNA merely in one assay. In addition to the concordance rate of 97.2% compared with NGS, this CANF1 assay targeting \u003cem\u003eNF1\u003c/em\u003e variants using long-read sequencing improved the detection rate of 2.8%, which will aid in making a more precise diagnosis of NF1.\u003c/p\u003e \u003cp\u003eCompared to conventional NGS, CANF1 assay established a new diagnosis, and/or improved the diagnosis of certain samples by providing more accurate genetic diagnosis, including identifying trans-configuration and breakpoints of deletion. The intron variant c.5812\u0026thinsp;+\u0026thinsp;332A\u0026thinsp;\u0026gt;\u0026thinsp;G in participant P77 was unidentified by ES as it was outside the targeted region. In P51, the variant c.1527\u0026thinsp;+\u0026thinsp;1346G\u0026thinsp;\u0026gt;\u0026thinsp;C from deep intron region was only detected by CANF1, which was classified as VUS based on ACMG criteria as it was predicted not affecting splicing. Through genetic analysis of blood and tissue in P71, the germline \u003cem\u003eNF1\u003c/em\u003e pathogenic variant c.4330A\u0026thinsp;\u0026gt;\u0026thinsp;G in all samples and a second-hit pathogenic \u003cem\u003eNF1\u003c/em\u003e variant c.653delA in tissue. Both \u003cem\u003eNF1\u003c/em\u003e variants were located on different alleles resulting in somatic mosaicism for a biallelic \u003cem\u003eNF1\u003c/em\u003e inactivation. The intragenic CNV in P90 carried a deletion of 53,004bp from exon 49 to 58 and an insertion of 306bp, with the 3\u0026rsquo; breakpoint located in intron 1 of the downstream gene \u003cem\u003eRAB11FIP4.\u003c/em\u003e The breakpoints were identified by CANF1, whereas routine ES could only provide a rough range of affected exons. In addition, ES suggested a deletion of exon 13 to 18 in a region interfered by a pseudogene, but the CANF1 assay demonstrated that this was a false deletion. In Proband P172, the CANF1 detected a more precise region of deletion, with 25.8 kb rather than 21.03 kb deletion suggested by exon capture-based ES. Therefore, firstly, the CANF1 assay can cover a wideer and more precise range of variation, particularly in non-coding region. Secondly, the CANF1 assay provides deeper sequencing depth than ES and GS with less sequencing data, and it has capacity to found variants more accurately that could be missed by sequencing with depth of 30-120X.\u003c/p\u003e \u003cp\u003eAbove all, the LRS-based CANF1 assay enables the efficient identification of various variations, including SNVs/Indels, small deletions/insertions, large deletions, \u003cem\u003eNF1\u003c/em\u003e microdeletion and gene conversions in one assay with reduced costs compared to traditional approaches. As the molecular testing for \u003cem\u003eNF1\u003c/em\u003e was included as one of the seven criteria in the recently revised NF1 diagnostic criteria in 2021, this CANF1 assay can facilitate earlier and more precise diagnosis of NF1. NF1 manifestations have age-dependent, with CALMs in the cutaneous system usually being the first onset. However, relying solely on clinical manifestations, approximately 46% of sporadic NF1 patients do not meet the diagnostic criteria by the age of one year (Ly \u0026amp; Blakeley, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Previous studies have revealed that 97% of children with at least one feature of NF1 eventually meet the diagnostic criteria by the age of 8 years. Precise diagnosis contributes to timely and appropriate treatment for patients. Moreover, for those individuals lacking characteristic cutaneous findings or with mosaic involvement, ES and multigene panel testing based on NGS was mainly applied in clinical molecular diagnosis. Ultradeep sequencing was used to identify somatic mosaicism using tissues of probands. By traditional gDNA targeted sequencing, 60\u0026ndash;90% of the NF1 patients could found \u003cem\u003eNF1\u003c/em\u003e variants (D. A.-O. Bianchessi et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Cali et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Maruoka et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Pasmant et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; van Minkelen et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Zhang et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Here, the CANF1 assay provided an all-in-one approach and identified disease-causing NF1 variants in 92.9% clinical NF1 participants. As mentioned previously, approximately 21% of non-NF1-CP were found to have somatic mono-allelic NF1 disease-causing variants(Zheng et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), while 16.7% of non-NF1-CP were identified as having NF1 disease-causing variants.\u003c/p\u003e \u003cp\u003eIn conclusion, this study developed CANF1 assay as a comprehensive, accurate and more efficient approach than current approaches. This advancement will be highly beneficial for establishing an earlier molecular diagnosis of NF1 and will aid in genetic counseling and disease management for participants. Additionally, as one of the NF1 diagnostic criteria, high quality LRS of the \u003cem\u003eNF1\u003c/em\u003e gene would become a considerably important tool for molecular diagnosis in near future.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eNF1, Neurofibromatosis type 1; CANF1, comprehensive analysis of NF1; CALM, Caf\u0026eacute; au lait macules; CPT, congenital pseudarthrosis of the tibia; CP, congenital pseudarthrosis; non-NF1-CP, participants with congenital pseudarthrosis but unfulfilling the NF1 clinical criteria; PCR, polymerase chain reaction; CNV, copy number variations; NGS, next-generation sequencing; ES, exome sequencing; GS, genome sequencing; CNV-seq, low-depth sequencing for copy number variations; MLPA, multiplex ligation-dependent probe amplification; LRS, long-read sequencing; VUS, variants of uncertain significance; SNVs, single nucleotide variations; Indels, small insertions and deletions; IGV, Integrative Genomics Viewer.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eCompeting interests\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003ch2\u003eEthics Approval\u003c/h2\u003e\n\u003cp\u003eThis study was approved by the Ethics Committee of Hunan Children\u0026apos;s Hospital (Approval No. HCHLL-2024-56).\u003c/p\u003e\n\u003ch2\u003eConsent to participate\u003c/h2\u003e\n\u003cp\u003eInformed consent was obtained from all individual participants or their parents included in the study.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThis work was supported by the Hunan Province Natural Science Foundation of China (2023JJ30330), the Clinical Medical Research Center for Hereditary Birth Defects and Rare Diseases in Hunan Province (2023SK4053), and the special fund of Hunan Provincial Key Laboratory of Pediatric Orthopedics (2023TP1019).\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eAll authors contributed to the study conception, design and resources collection. Supervision: Hua Wang. Material preparation, data collection and analysis were performed by Yu Zheng, Danhua Li, Tiantian Xie, Guanghui Zhu, Yaoxi Liu, Haibo Mei. Funding acquisition: Hua Wang, Yu Zheng and Guanghui Zhu. The first draft of the manuscript was written by Yu Zheng and all authors reviewed and commented on the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgement\u003c/h2\u003e\n\u003cp\u003eWe appreciate the Hunan Province Natural Science Foundation of China (2023JJ30330), the Clinical Medical Research Center for Hereditary Birth Defects and Rare Diseases in Hunan Province (2023SK4053), and the special fund of Hunan Provincial Key Laboratory of Pediatric Orthopedics (2023TP1019). We thank Berry Genomics Corporation supported this study. We also express our sincere gratitude to participants and all who helped us in this study.\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eThe novel variants found in this study will submit to ClinVar. Other datasets used during the current study are available from the corresponding authors on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eBianchessi, D., Morosini, S., Saletti, V., Ibba, M. C., Natacci, F., Esposito, S., . . . Eoli, M. (2015). 126 novel mutations in Italian patients with neurofibromatosis type 1. \u003cem\u003eMol Genet Genomic Med, 3\u003c/em\u003e(6), 513-525. doi:10.1002/mgg3.161\u003c/li\u003e\n \u003cli\u003eBianchessi, D. A.-O., Ibba, M. C., Saletti, V., Blasa, S. A.-O. X., Langella, T., Paterra, R., . . . Eoli, M. A.-O. (2020). Simultaneous Detection of NF1, SPRED1, LZTR1, and NF2 Gene Mutations by Targeted NGS in an Italian Cohort of Suspected NF1 Patients. \u003cem\u003eGenes, 11(6):671\u003c/em\u003e(2073-4425 (Electronic)). doi:10.3390/genes11060671\u003c/li\u003e\n \u003cli\u003eCali, F., Chiavetta, V., Ruggeri, G., Piccione, M., Selicorni, A., Palazzo, D., . . . Romano, V. (2017). Mutation spectrum of NF1 gene in Italian patients with neurofibromatosis type 1 using Ion Torrent PGM platform. \u003cem\u003eEur J Med Genet, 60\u003c/em\u003e(2), 93-99. doi:10.1016/j.ejmg.2016.11.001\u003c/li\u003e\n \u003cli\u003eChen, X., Harting, J., Farrow, E., Thiffault, I., Kasperaviciute, D., Genomics England Research, C., . . . Eberle, M. A. (2023). Comprehensive SMN1 and SMN2 profiling for spinal muscular atrophy analysis using long-read PacBio HiFi sequencing. \u003cem\u003eAm J Hum Genet, 110\u003c/em\u003e(2), 240-250. doi:10.1016/j.ajhg.2023.01.001\u003c/li\u003e\n \u003cli\u003eEvans, D. G., Bowers, N., Burkitt-Wright, E., Miles, E., Garg, S., Scott-Kitching, V., . . . Huson, S. M. (2016). Comprehensive RNA Analysis of the NF1 Gene in Classically Affected NF1 Affected Individuals Meeting NIH Criteria has High Sensitivity and Mutation Negative Testing is Reassuring in Isolated Cases With Pigmentary Features Only. \u003cem\u003eEBioMedicine, 7\u003c/em\u003e, 212-220. doi:10.1016/j.ebiom.2016.04.005\u003c/li\u003e\n \u003cli\u003eEvans, D. G., Howard, E., Giblin, C., Clancy, T., Spencer, H., Huson, S. M., \u0026amp; Lalloo, F. (2010). Birth incidence and prevalence of tumor-prone syndromes: estimates from a UK family genetic register service. \u003cem\u003eAm J Med Genet A, 152A\u003c/em\u003e(2), 327-332. doi:10.1002/ajmg.a.33139\u003c/li\u003e\n \u003cli\u003eGutmann, D. H., Ferner, R. E., Listernick, R. H., Korf, B. R., Wolters, P. L., \u0026amp; Johnson, K. J. (2017). Neurofibromatosis type 1. \u003cem\u003eNat Rev Dis Primers, 3\u003c/em\u003e, 17004. doi:10.1038/nrdp.2017.4\u003c/li\u003e\n \u003cli\u003eHefti, F., Bollini, G., Dungl, P., Fixsen, J., Grill, F., Ippolito, E., . . . Wientroub, S. (2000). Congenital pseudarthrosis of the tibia: history, etiology, classification, and epidemiologic data. \u003cem\u003eJ Pediatr Orthop B, 9\u003c/em\u003e(1), 11-15. Retrieved from\u0026nbsp;\u003ca href=\"http://www.ncbi.nlm.nih.gov/pubmed/10647103\"\u003ehttp://www.ncbi.nlm.nih.gov/pubmed/10647103\u003c/a\u003e\u003c/li\u003e\n \u003cli\u003eLammert, M., Friedman, J. M., Kluwe, L., \u0026amp; Mautner, V. F. (2005). Prevalence of neurofibromatosis 1 in German children at elementary school enrollment. \u003cem\u003eArch Dermatol, 141\u003c/em\u003e(1), 71-74. doi:10.1001/archderm.141.1.71\u003c/li\u003e\n \u003cli\u003eLegius, E., Messiaen, L., Wolkenstein, P., Pancza, P., Avery, R. A., Berman, Y., . . . Plotkin, S. R. (2021). Revised diagnostic criteria for neurofibromatosis type 1 and Legius syndrome: an international consensus recommendation. \u003cem\u003eGenet Med, 23\u003c/em\u003e(8), 1506-1513. doi:10.1038/s41436-021-01170-5\u003c/li\u003e\n \u003cli\u003eLiang, Q., He, J., Li, Q., Zhou, Y., Liu, Y., Li, Y., . . . Wu, L. (2023). Evaluating the Clinical Utility of a Long-Read Sequencing-Based Approach in Prenatal Diagnosis of Thalassemia. \u003cem\u003eClin Chem, 69\u003c/em\u003e(3), 239-250. doi:10.1093/clinchem/hvac200\u003c/li\u003e\n \u003cli\u003eLiang, Q., Liu, Y., Liu, Y., Duan, R., Meng, W., Zhan, J., . . . Wu, L. (2022). Comprehensive Analysis of Fragile X Syndrome: Full Characterization of the FMR1 Locus by Long-Read Sequencing. \u003cem\u003eClin Chem, 68\u003c/em\u003e(12), 1529-1540. doi:10.1093/clinchem/hvac154\u003c/li\u003e\n \u003cli\u003eLiu, Y., Chen, M., Liu, J., Mao, A., Teng, Y., Yan, H., . . . Wu, L. (2022). Comprehensive Analysis of Congenital Adrenal Hyperplasia Using Long-Read Sequencing. \u003cem\u003eClin Chem, 68\u003c/em\u003e(7), 927-939. doi:10.1093/clinchem/hvac046\u003c/li\u003e\n \u003cli\u003eLiu, Y., Li, D., Yu, D., Liang, Q., Chen, G., Li, F., . . . Liang, D. (2023). Comprehensive Analysis of Hemophilia A (CAHEA): Towards Full Characterization of the F8 Gene Variants by Long-Read Sequencing. \u003cem\u003eThromb Haemost, 123\u003c/em\u003e(12), 1151-1164. doi:10.1055/a-2107-0702\u003c/li\u003e\n \u003cli\u003eLy, K. I., \u0026amp; Blakeley, J. O. (2019). The Diagnosis and Management of Neurofibromatosis Type 1. \u003cem\u003eMed Clin North Am, 103\u003c/em\u003e(6), 1035-1054. doi:10.1016/j.mcna.2019.07.004\u003c/li\u003e\n \u003cli\u003eMaruoka, R., Takenouchi, T., Torii, C., Shimizu, A., Misu, K., Higasa, K., . . . Kosaki, K. (2014). The use of next-generation sequencing in molecular diagnosis of neurofibromatosis type 1: a validation study. \u003cem\u003eGenet Test Mol Biomarkers, 18\u003c/em\u003e(11), 722-735. doi:10.1089/gtmb.2014.0109\u003c/li\u003e\n \u003cli\u003eMessiaen, L. M., Callens, T., Mortier, G., Beysen, D., Vandenbroucke, I., Van Roy, N., . . . Paepe, A. D. (2000). Exhaustive mutation analysis of the NF1 gene allows identification of 95% of mutations and reveals a high frequency of unusual splicing defects. \u003cem\u003eHum Mutat, 15\u003c/em\u003e(6), 541-555. doi:10.1002/1098-1004(200006)15:6\u0026lt;541::AID-HUMU6\u0026gt;3.0.CO;2-N\u003c/li\u003e\n \u003cli\u003eNeurofibromatosis. (1988). National Institutes of Health Consensus Development Conference. Conference statement. \u003cem\u003eArch Neurol, 45\u003c/em\u003e, 575-578.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eO\u0026apos;Donnell, C., Foster, J., Mooney, R., Beebe, C., Donaldson, N., \u0026amp; Heare, T. (2017). Congenital Pseudarthrosis of the Tibia. \u003cem\u003eJBJS Rev, 5\u003c/em\u003e(4), e3. doi:10.2106/JBJS.RVW.16.00068\u003c/li\u003e\n \u003cli\u003ePasmant, E., Parfait, B., Luscan, A., Goussard, P., Briand-Suleau, A., Laurendeau, I., . . . Vidaud, D. (2015). Neurofibromatosis type 1 molecular diagnosis: what can NGS do for you when you have a large gene with loss of function mutations? \u003cem\u003eEur J Hum Genet, 23\u003c/em\u003e(5), 596-601. doi:10.1038/ejhg.2014.145\u003c/li\u003e\n \u003cli\u003eSabbagh, A., Pasmant, E., Imbard, A., Luscan, A., Soares, M., Blanche, H., . . . Wolkenstein, P. (2013). NF1 molecular characterization and neurofibromatosis type I genotype-phenotype correlation: the French experience. \u003cem\u003eHum Mutat, 34\u003c/em\u003e(11), 1510-1518. doi:10.1002/humu.22392\u003c/li\u003e\n \u003cli\u003eSummerer, A., Schafer, E., Mautner, V. F., Messiaen, L., Cooper, D. N., \u0026amp; Kehrer-Sawatzki, H. (2019). Ultra-deep amplicon sequencing indicates absence of low-grade mosaicism with normal cells in patients with type-1 NF1 deletions. \u003cem\u003eHum Genet, 138\u003c/em\u003e(1), 73-81. doi:10.1007/s00439-018-1961-5\u003c/li\u003e\n \u003cli\u003eUusitalo, E., Leppavirta, J., Koffert, A., Suominen, S., Vahtera, J., Vahlberg, T., . . . Peltonen, S. (2015). Incidence and mortality of neurofibromatosis: a total population study in Finland. \u003cem\u003eJ Invest Dermatol, 135\u003c/em\u003e(3), 904-906. doi:10.1038/jid.2014.465\u003c/li\u003e\n \u003cli\u003eValero, M. C., Martin, Y., Hernandez-Imaz, E., Marina Hernandez, A., Melean, G., Valero, A. M., . . . Hernandez-Chico, C. (2011). A highly sensitive genetic protocol to detect NF1 mutations. \u003cem\u003eJ Mol Diagn, 13\u003c/em\u003e(2), 113-122. doi:10.1016/j.jmoldx.2010.09.002\u003c/li\u003e\n \u003cli\u003evan Minkelen, R., van Bever, Y., Kromosoeto, J. N., Withagen-Hermans, C. J., Nieuwlaat, A., Halley, D. J., \u0026amp; van den Ouweland, A. M. (2014). A clinical and genetic overview of 18 years neurofibromatosis type 1 molecular diagnostics in the Netherlands. \u003cem\u003eClin Genet, 85\u003c/em\u003e(4), 318-327. doi:10.1111/cge.12187\u003c/li\u003e\n \u003cli\u003eVan Royen, K., Brems, H., Legius, E., Lammens, J., \u0026amp; Laumen, A. (2016). Prevalence of neurofibromatosis type 1 in congenital pseudarthrosis of the tibia. \u003cem\u003eEur J Pediatr, 175\u003c/em\u003e(9), 1193-1198. doi:10.1007/s00431-016-2757-z\u003c/li\u003e\n \u003cli\u003eVander Have, K. L., Hensinger, R. N., Caird, M., Johnston, C., \u0026amp; Farley, F. A. (2008). Congenital pseudarthrosis of the tibia. \u003cem\u003eJ Am Acad Orthop Surg, 16\u003c/em\u003e(4), 228-236.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eWang, N., Jiao, K., He, J., Zhu, B., Cheng, N., Sun, J., . . . Zhu, W. (2024). Diagnosis of Challenging Spinal Muscular Atrophy Cases with Long-Read Sequencing. \u003cem\u003eJ Mol Diagn, 26\u003c/em\u003e(5), 364-373. doi:10.1016/j.jmoldx.2024.02.004\u003c/li\u003e\n \u003cli\u003eZhang, J., Tong, H., Fu, X., Zhang, Y., Liu, J., Cheng, R., . . . Yao, Z. (2015). Molecular Characterization of NF1 and Neurofibromatosis Type 1 Genotype-Phenotype Correlations in a Chinese Population. \u003cem\u003eSci Rep, 5\u003c/em\u003e(2045-2322 (Electronic)), 11291. doi:10.1038/srep11291\u003c/li\u003e\n \u003cli\u003eZheng, Y., Zhu, G., Liu, Y., Zhao, W., Yang, Y., Luo, Z., . . . Hu, Z. (2022). Case series of congenital pseudarthrosis of the tibia unfulfilling neurofibromatosis type 1 diagnosis: 21% with somatic NF1 haploinsufficiency in the periosteum. \u003cem\u003eHum Genet, 141\u003c/em\u003e(8), 1371-1383. doi:10.1007/s00439-021-02429-2\u003c/li\u003e\n \u003cli\u003eZhu, G., Zheng, Y., Liu, Y., Yan, A., Hu, Z., Yang, Y., . . . Mei, H. (2019). Identification and characterization of NF1 and non-NF1 congenital pseudarthrosis of the tibia based on germline NF1 variants: genetic and clinical analysis of 75 patients. \u003cem\u003eOrphanet J Rare Dis, 14\u003c/em\u003e(1), 221. doi:10.1186/s13023-019-1196-0\u003c/li\u003e\n \u003cli\u003eZhu, L., Zhang, Y., Tong, H., Shao, M., Gu, Y., Du, X., . . . Zhang, G. (2016). Clinical and Molecular Characterization of NF1 Patients: Single-Center Experience of 32 Patients From China. \u003cem\u003eMedicine (Baltimore), 95\u003c/em\u003e(10), e3043. doi:10.1097/MD.0000000000003043\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Neurofibromatosis 1, NF1, long-read sequencing, genetic testing, precise diagnosis","lastPublishedDoi":"10.21203/rs.3.rs-5382766/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5382766/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eClinical diagnosing Neurofibromatosis type 1 (NF1) in pediatrics are facing challenges because of limited presence of age-dependent phenotypes, and the limited detection rate by current approaches for the complexity of the \u003cem\u003eNF1\u003c/em\u003e gene. Here we developed a comprehensive analysis of NF1 (CANF1) combining 14 long-range locus-specific PCR, 25 gap primers and long-read sequencing (LRS) for sequence analysis of the \u003cem\u003eNF1\u003c/em\u003e gene. In this blind retrospective study, the clinical utility of CANF1 was evaluated in 191 samples (181 pediatric probands, 10 NF1 parents) by comparing to the control methods, mainly next generation sequencing (NGS). The results exhibited 176 probands (176/181\u0026thinsp;=\u0026thinsp;97.2%) having concordant results, and the other 5 probands (2.8%) with improved findings including: one was established a new diagnosis (c.5812\u0026thinsp;+\u0026thinsp;332A\u0026thinsp;\u0026gt;\u0026thinsp;G in deep intron) and four were improved with precise CNV breakpoints. In 127 pediatric NF1 probands with limited clinical manifestations, this assay received a detection rate of 92.9%, which is higher than NGS. In conclusion, this study constructed a comprehensive analysis of NF1 employing LRS, which can reliably identify various type variants of the \u003cem\u003eNF1\u003c/em\u003e gene in one assay. This CANF1 assay can help in screening NF1 with more precise molecular diagnosis than conventional methods, particularly for individuals with unfulfilling NF1 diagnosis solely by clinical phenotypes.\u003c/p\u003e","manuscriptTitle":"Comprehensive Analysis of the NF1 gene Using Long-Read Sequencing Improved Neurofibromatosis type 1 Molecular Diagnosis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-12-09 14:24:09","doi":"10.21203/rs.3.rs-5382766/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1c9fb6d9-55a5-4ca8-b7fa-bbb2544dbecd","owner":[],"postedDate":"December 9th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-12-15T07:23:18+00:00","versionOfRecord":[],"versionCreatedAt":"2024-12-09 14:24:09","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5382766","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5382766","identity":"rs-5382766","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}