Targeted long-read sequencing enables higher diagnostic yield of ADPKD by accurate PKD1 genetic analysis in an assisted reproductive center

Targeted long-read sequencing enables higher diagnostic yield of ADPKD by accurate PKD1 genetic analysis in an assisted reproductive center | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Targeted long-read sequencing enables higher diagnostic yield of ADPKD by accurate PKD1 genetic analysis in an assisted reproductive center Yuan Gao, Qian Sun, Peiwen Xu, Aiping Mao, Sexin Huang, Jie Li, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5235348/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 11 Mar, 2025 Read the published version in npj Genomic Medicine → Version 1 posted 11 You are reading this latest preprint version Abstract Autosomal dominant polycystic kidney disease (ADPKD) is mainly caused by disease-causing variants in two large multi-exon genes of PKD1 and PKD2. Genetic diagnosis of ADPKD has been challenging due to the variant heterogeneity, presence of duplicated segments, and high GC content of exon 1 in PKD1. In our reproductive center, a total of 312 patients with ADPKD phenotype have been genetically tested using a next-generation sequencing (NGS) panel. Among all the cases, 40 patients were either genetically undiagnosed or diagnosed without single-nucleotide resolution. Therefore, a combination of long-rang PCR and long-read sequencing (LRS) approach for PKD1 and PKD2 was performed on these 40 ADPKD patients. LRS additionally identified 10 pathogenic or likely pathogenic PKD1 variants, including eight single-nucleotide variants (SNVs) and insertions/deletions (indels) and two large deletions. Among the eight SNV/indels, LRS identified four patients with microgene conversion (c.160_166dup, c.2180T>C, and c.8161+1G>A) between PKD1 and its pseudogenes, three patients with indels (c.-49_43del, c.2985+2_2985+4del, and c.10709_10760dup), and one patient with likely pathogenic deep intronic variant c.2908-107G>A. In addition, LRS identified nine PKD1 CNVs including eight large deletions and one duplication, and meanwhile LRS can precisely determine the breakpoints; while NGS had failed to identify two of these CNVs. In conclusion, target LRS enables higher diagnostic yield of ADPKD by accurate and precise PKD1 genetic analysis, which could provide significant benefits for genetic counseling and assisted reproductive treatments. Autosomal dominant polycystic kidney disease PKD1 pseudogene microgene conversion long-read sequencing genetic diagnosis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Autosomal dominant polycystic kidney disease (ADPKD), with an incidence of approximately 0.1%-0.25% worldwide, is one of the most common inherited kidney disorders and responsible for 5%-10% of end-stage renal disease. 1,2 Disease-causing variants in PKD1 and PKD2 account for approximately 85% and 15% of ADPKD, respectively. 3 In general, ADPKD is clinically diagnosed by ultrasonography based on age-related criteria. 4 However, the diagnosis made by imaging may be uncertain, particularly in young individuals less than 30 years old. 4 Therefore, molecular genetic testing is required to achieve a definite diagnosis. 5 The Genetic diagnosis of ADPKD can provide significant benefits for patients who seek for genetic counseling during the assisted reproductive treatments and reduce the possibility of at-risk pregnancies. 6 However, the genetic diagnosis of ADPKD has been particularly challenging due to several factors. First, PKD1 gene has a large size and contains 46 exons spanning 47.2-kb of genomic DNA. 5 Second, genetic analysis for PKD1 is complicated by the presence of 39.9-kb duplicated segment that encompasses exons 1-33 and shares 98% sequence similarity to six pseudogenes ( PKD1P1 to PKD1P6 ). 7,8 Microgene conversions between PKD1 and its pseudogenes can be caused by the transfer of sequences from high homology pseudogenes to functional genes, which has been reported to be associated with ADPKD. 9 , 10,11 Third, the high GC content of exon 1 in PKD1 makes it difficult to amplify and sequence using standard sequencing methods 2 . Last, a high level of allelic heterogeneity has been observed in disease-causing variants of PKD1 and PKD2 , including more than one thousand pathogenic or likely pathogenic single-nucleotide variants (SNVs) and insertions/deletions (indels), and the majority of these variants are exclusive to a single pedigree. 12 In addition, approximately 2%-6% of ADPKD are caused by copy number variants (CNVs), which consist of single to multiple exon deletions or duplications. 5,13-15 Currently, a few genetic testing methods such as long-range PCR, next-generation sequencing (NGS) and multiplex ligation-dependent probe amplification (MLPA) have been used in the diagnosis of ADPKD. 16-20 Due to high sequence homology between PKD1 and its pseudogenes, NGS approaches could lead to false positive or false negative genotyping due to the incorrect calling of variants from pseudogenes. 21-23 Although targeted NGS combined with long-range PCR for locus-specific PKD1 provides a robust approach for ADPKD genetic testing, extra input for exon 1 in PKD1 is required to achieve balanced sequencing depth due to GC bias during NGS. 24 MLPA can only be employed to detect large deletions and duplications in PKD1 and PKD2 , which could increase the turnaround time and diagnostic cost. 15,24 These traditional methods have limitations in accurately detecting all types of variants in PKD1 and PKD2 , particularly in the duplicated regions of PDK1 . This has led to a significant diagnostic gap in ADPKD genetic testing, with some patients remaining undiagnosed or incompletely diagnosed despite a clear clinical phenotype. At present, the diagnostic rate in ADPKD is approximately 80% to 90%. 1,20,25-28 Therefore, it is necessary to improve the diagnosis for ADPKD patients, especially when they are looking for assisted reproductive treatments. In recent years, single-molecule GC-unbiased long-read sequencing (LRS) has emerged as a promising approach to overcome these challenges, and improved genetic diagnosis for diseases with complicated molecular genetics such as thalassemia, 29,30 congenital adrenal hyperplasia, 31,32 spinal muscular atrophy, 33,34 fragile-X syndrome, 35 hemophilia A, 36 and ADPKD. 27 LRS-based approach enables to generate reads spanning large genomic regions of PKD1 and PKD2 , improves detection of structural variants and better resolution of repetitive sequences, and makes incremental diagnostic rate compared to LR-PCR, NGS and MLPA combined approach. 27 In this study, we aimed to evaluate the effectiveness of LRS-based approach in improving the genetic diagnosis of ADPKD, particularly for patients who had remained undiagnosed or incompletely diagnosed after conventional NGS testing. Methods Study participants From January 2016 to December 2023, 312 patients with clinical diagnosis of ADPKD have undergone genetic testing at our assisted reproductive center using a targeted NGS panel, which included thousands of kidney disease-related genes such as PKD1 , PKD2 , PKHD1 and HNF1B . The pathogenicity of SNV/indels was classified according to the American College of Medical Genetics and Genomics guidelines. 37 From this cohort, a total of 272 patients were genetically diagnosed with pathogenic (P) or likely pathogenic (LP) SNVs/indels, including 239 cases with variants in PKD1 , 30 cases with variants in PKD2 , and 3 cases with variants in HNF1B ( Figure 1 ). The remaining 40 patients were either genetically undiagnosed or diagnosed without single-nucleotide resolution at the time of enrollment in our study, which included 18 cases with variants of uncertain significance (VUS) in PKD1 , 7 cases with PKD1 CNVs, and 15 cases with no identified variants ( Figure 1 ). Genomic DNA from these 40 patients were sent to Berry Genomics Corporation for genetic analysis of PKD1 and PKD2 with a targeted LRS approach ( Figure 2 ). This study adhered to the Declaration of Helsinki, and was approved by the institutional review board of Center for Reproductive Medicine at Shandong University. Informed written consent was obtained from all the participants. ADPKD genetic diagnosis by NGS Genomic DNA from peripheral blood was extracted using the Blood DNA extraction kits (ZEESAN, China). Targeted NGS, with IDT xGen Exome Research Panel (Integrated DNA Technologies, USA), was performed using xGen NGS Hybridization Capture (Integrated DNA Technologies, USA) and sequencing was performed on the NovaSeq 6000 platform (Illumina, USA). High-quality sequencing reads were selected and aligned to the reference genome hg19 using the BWA algorithm with default settings. 38 SNVs and indels were called by GATK. 39 Copy-number variations (CNVs) were determined as previously described. 40 For samples with SNVs/indels identified by NGS, Sanger sequencing was performed to confirm the variants. For samples with CNVs in PKD1 and PKD2 identified by NGS, MLPA analysis was performed to confirm the CNVs (MRC-Holland, the Netherlands) using probemix P351 and P352 PKD1 - PKD2 . ADPKD genetic diagnosis by LRS Targeted LRS for PKD1 and PKD2 genetic analysis was performed similarly as previously described. 27 Genomic DNA was subjected to multiplex LR-PCR 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, Japan). PCR cycling conditions were 94°C for 5 min (1 cycle); 98°C for 15 s and 68°C for 12 min (32 cycles) and 68°C for 10 min (1 cycle). The PacBio single-molecule real-time dumbbell (SMRTbell) libraries were prepared by a one-step end-repair and ligation reaction to add barcoded adaptors, followed by digestion with exonucleases to remove failed ligated DNA. The uniquely barcoded libraries were purified, quantified and then pooled with equal mass. SMRTbell sequencing library was prepared using the Sequel II Binding Kit 3.2 (Pacific Biosciences, USA) and sequenced under circular consensus sequencing (CCS) mode with Sequel IIe platform (Pacific Biosciences, USA) for 30 h. After sequencing, the raw subreads were converted to high-fidelity CCS reads, debarcoded and aligned to reference genome build hg38 in the SMRT Link analysis software suite (Pacific Biosciences, USA). The aligned CCS reads were then subjected to an in-house developed bioinformatics pipeline to identify SNVs/indels, deletions and duplications ( Figure 2A and 2B ). 27 The CCS reads of representative variants were displayed in the Integrative Genomics Viewer (IGV). Validation of variants additionally detected by LRS Sanger sequencing was performed to validate discordant SNVs/indels between LRS and NGS, with primers listed in Supplemental Table 1 . Moreover, MLPA was utilized to confirm the CNVs additionally identified by LRS. Identification of splicing junctions by RT-PCR sequencing For participants with variants that could potentially disrupt mRNA splicing, total RNA was extracted from peripheral blood using RNAiso Plus (Takara, Japan). cDNA was synthesized using PrimeScript™ II 1st Strand cDNA Synthesis Kit (Takara, Japan) according to the manufacturer’s instructions. PCR amplification was performed using primers flanking the putative splicing junctions, and products were analyzed by Sanger sequencing to identify the exact junction sites ( Supplemental Table 1 ). Results Improvement of diagnostic yield in PKD1 and PKD2 by LRS A total of 40 clinically diagnosed ADPKD patients without fully genetic characterization by NGS, were retrospectively enrolled in this study (Figure 1). The cohort included 28 male and 12 female patients, with a mean age of 25.8±5.5 years. Targeted LRS for PKD1 and PKD2 genetic analysis were performed for all the 40 patients. LRS identified 9 P/LP and 17 VUS SNVs/indels in PKD1 , as well as 9 P/LP CNVs in PKD1 ( Figure 1 , Table 1 ). Compared to NGS panel-based diagnostic workflow, LRS approach identified pathogenic or likely pathogenic PKD1 variants in ten more patients, which increased the genetic diagnosis rate from 20.0% (8/40) to 45.0% (18/40) and the variant detection rate from 62.5% (25/40) to 87.5% (35/40). This represents a significant improvement in diagnostic yield for this challenging subset of patients. LRS detections for PKD1 and PKD2 SNVs/indels Eight patients were found to have pathogenic or likely pathogenic SNVs/indels in PKD1 using targeted LRS approach. These eight variants included four microgene conversions between PKD1 and its pseudogenes, three indels, and one deep intronic variant ( Table 1 ). All the eight variants were confirmed by Sanger sequencing ( Supplemental Figure 1 and 2 ). Among the four patients with microgene conversions, two patients harbored the same frameshift variant PKD1 :c.160_166dup, which was a duplication of 7 nucleotides in exon 1 and existed in four pseudogenes ( PKD1P1/3/5/6 ) ( Figure 3A ). Patient KPK003 had a missense variant PKD1 :c.2180T>C in exon 11, and this variant also located in five pseudogenes ( PKD1P1/2/3/4/5 ) ( Figure 3B ). The splice site variant PKD1 :c.8161+1G>A, identified in patient KPK004, was affecting intron 22 and located in three pseudogenes ( PKD1P1/3/4 ) ( Figure 3C ). These microgene conversions can occur in large segments of PKD1 gene that are identical to the pseudogenes. Using short-read NGS, variants could be missed due to the alignment of these large segments to their pseudogenes ( Table 1 ). However, LRS can discriminate PKD1 and its pseudogenes by sequencing large segments of genomic DNA with several to ten thousand nucleotides, and enable accurate recognition of these pseudogene-driven variants. LRS also detected two small deletions of PKD1 :c.-49_+43del and PKD1 :c.2985+2_2985+4del, and one small duplication of PKD1 :c.10709_10760dup in three individual samples ( Figure 4A to 4C ). These three variants were missed by traditional NGS due to limited read length or low coverage in the specific regions. Of note, LRS also identified a benign 34-bp duplication of PKD1 :c.11713-30_11713-63dup in sample KPK007 ( Figure 4C ). Further analysis showed that this region had a variable number of tandem repeat and occurred in 92.5% (37/40) of the samples ( Supplemental 2D ). In addition, LRS identified two deep intronic variants, PKD1 :c.1607-76C>T in patient KPK036 and PKD1 :c.2908-107G>A in patient KPK008 ( Figure 4D ). RT-PCR sequencing proved that PKD1 :c.1607-76C>T did not affect the splicing and was a likely benign variant ( Supplemental Figure 2G ). However, RT-PCR analysis revealed that PKD1 :c.2908-107G>A created a new splice acceptor site, leading to the inclusion of a 111-nucleotide pseudoexon. This aberrant splicing event results in an inframe insertion of 37 amino acids and premature termination codon ( Figure 4E and 4F ). Moreover, pedigree analysis of 15 family members from three-generations showed PKD1 :c.2908-107G>A was likely pathogenic because the variant was co-segregated with ADPKD phenotype within the family ( Figure 4G ). Both LRS and NGS identified the - variant PKD1 :c.12048C>T in patient KPK035 ( Table 1 ). Although this was synonymous variant, RT-PCR analysis showed the variant affected splicing by creating a new exonic splice enhancer site. This led to a 92-bp deletion transcript, and resulted in a frameshift ( Supplemental Figure 3A and 3B ). In addition, this variant was also co-segregated with ADPKD phenotype through pedigree analysis ( Supplemental Figure 3C ). Thus, PKD1 :c.12048C>T was reclassified as a pathogenic variant by considering the newly added evidence. LRS can perform the phasing analysis for SNVs/indels. In patient KPK009, the variants of PKD1 :c.10984C>T and c.11712+81_11713-100del were found to locate on one allele, while variant c.12408G>T was located on the other allele ( Figure 4H ). LRS also determined variants PKD1 :c.8949-14C>G, c.9193G>A and c.9789G>T were in cis-configuration in patient KPK010 ( Figure 4I ), which has been reported in another ADPKD patient. 27 Considering the effect of hypomorphic variants in PKD1 gene, the compound heterozygous variants generally cause more severe manifestations. 41,42 Therefore, phasing analysis can enrich the mutational spectrum of ADPKD genes and serve as a reference for future patients. LRS detections for large deletions and duplications in PKD1 Six large deletions in PKD1 were identified by NGS and confirmed by MLPA ( Table 1, Supplemental Figure 4A to 4F ). Besides these six deletions ( Figure 5A to 5C ), LRS identified two more deletions in two samples ( Figure 5D and 5E ), which were also confirmed by MLPA ( Supplemental Figure 4G and 4H ). Moreover, LRS was able to precisely determine the breakpoints of these eight large deletions in CNVs. NGS and MLPA can detect the duplication of exon 43 and 44 in PKD1 ( Figure 6A ). However, the exact sequence and inserted position of these duplications cannot be determined by traditional sequencing methods. LRS demonstrated that the duplication was a 578-bp sequence (hg38 chr16:2,090,688-2,091,265) encompassing partial intron 42, exon 43, intron 43, and partial exon 44 ( Figure 6B and 6C ). The breakpoint of duplication was validated by Sanger sequencing ( Figure 6D ). RT-PCR analysis showed that the duplication led to an alternative transcript with duplication of exon 43 and thus an in-frame insertion of 97 amino acids with skipping the duplicated partial exon 44 ( Figure 6C, 6E and 6F ). Therefore, LRS can directly detect large duplications in PKD1 at single-nucleotide resolution. In addition, this duplication was found to co-segregate with ADPKD phenotype in a three-generation pedigree ( Figure 6G ). Discussion For the past eight years, our assisted reproductive center has utilized NGS panel for genetic testing of 312 ADPKD patients. Compared to NGS panel, targeted LRS additionally identified eight P/LP SNVs/indels and two P/LP CNVs in PKD1 , as well as determined single-nucleotide information for all the CNVs. Our study demonstrated the significant advantages of using long-read sequencing for the genetic diagnosis of ADPKD, particularly in cases where conventional NGS approaches have failed to provide a definitive diagnosis. The ability of LRS to span large genomic regions and resolve complex structural variations has allowed us to identify a spectrum of variants that were previously undetectable or difficult to characterize. The improved diagnostic yield of LRS for ADPKD patients is particularly important for assisted reproductive treatments since genetic diagnosis is required for those who seek for preimplantation genetic testing for monogenetic diseases (PGT-M) to lower the pregnancy risk. The identification of microgene conversions between PKD1 and its pseudogenes is particularly noteworthy to utilize LRS approach. These events, which involve the transfer of genetic information from pseudogenes to the functional PKD1 gene, can be easily missed by short-read sequencing technologies due to the high sequence similarity between PKD1 and its pseudogenes. 7 In the past, microgene conversions were generally detected by short PCR followed by Sanger sequencing, which could lead to drop-out of variants with microgene conversions. In this study, LRS was used to identify four microgene conversions ranging from 200 to 1000 bp that were missed by NGS. Our results highlighted the importance of considering such mechanisms in the pathogenesis of ADPKD and underscored the requirement for sequencing technologies that can accurately distinguish between the functional gene and its pseudogenes. Although various bioinformatics pipelines have been developed to call SNVs/indels from NGS data, accurate detection of indels over 50 bp is still very challenging. 27,43,44 Many partially mapped reads of these large indels can be lost in unmatched fragments. 27,43,44 In this cohort study, NGS panel failed to detect two intermediate sizes of indels including PKD1 :c.-49_43del and PKD1 :c.10709_10760dup. Surprisingly, NGS also failed to detect a 3-bp deletion PKD1 :c.2985+2_c.2985+4del. Manual inspection on the original NGS data suggested the presence of 3-bp deletion variant. However, the sequencing depth was only 15x in this specific area, and 20x sequencing depth is generally required to make a call in the bioinformatics pipeline, which is a common issue for large NGS panels. In NGS, the quality control for average sequencing depth is usually acceptable, but it does not guarantee the sequencing depth in each specific locus. The targeted LRS assay utilized full-length reads of each amplicon to do variant calling, therefore all the regions within the coverage can be successfully analyzed with adequate depth. In recent years, more and more disease-causing deep intronic variants were discovered due to rapid development of sequencing technologies. 45,46 Such variants can be easily overlooked by exon-focused sequencing approaches but may have significant implications for disease pathogenesis. 47 Therefore, the characterization of deep intronic variants demands comprehensive gene coverage in the genetic testing for ADPKD. In this study, LRS identified two novel deep intronic variants PKD1 :c.1607-76C>T and PKD1 :c.2908-107G>A that were undetectable in NGS panel. RT-PCR analysis showed that PKD1 :c.1607-76C>T did not affect the splicing, but PKD1 :c.2908-107G>A led to the inclusion of a 111-nucleotide pseudoexon with an inframe insertion of 37 amino acids. Pedigree analysis proved PKD1 :c.2908-107G>A was co-segregated with ADPKD phenotype and was a likely pathogenic variant. The identification of the c.2908-107G>A variant and its effect on splicing illustrated the potential of LRS to expand our understanding of the mutational spectrum in ADPKD. Since the majority of PKD1 and PKD2 variants are exclusive to single families, novel and VUS variants can be identified in a cohort of ADPKD patients. 25-27 Precise genetic diagnosis is required for PGT-M to select embryos without disease-causing variants, therefore functional and pedigree analysis are critical to accumulate evidence to determine the pathogenicity of each variant according to the AMCG guidelines. Here we found that the synonymous variant PKD1 :c.12048C>T caused a 62-bp deletion transcript and thus frameshift of translation by RT-PCR. In combination of co-segregation analysis, the pathogenicity of this variant was upgraded from VUS to pathogenic. Moreover, LRS can determine the cis and trans-configuration of variants within the same PCR amplicon without the need of pedigree analysis. Besides SNVs/indels, NGS has been gradually and widely used for CNV analysis. 48,49 In our study, LRS identified two more PKD1 CNVs compared to NGS, including one deletion encompassing exon 44 to 46 and another deletion encompassing exon 1 to upstream regions. This highlighted the superior sensitivity of LRS for CNV detection in complex genomic regions. The improved detection of CNVs by LRS addressed a significant limitation of NGS-based approaches. NGS typically relies on read depth analysis to infer CNVs, which can be challenging in regions with pseudogenes or repetitive sequences. 50 In addition, the precise determination of breakpoints by LRS offered valuable insights into the molecular mechanisms underlying these variants, which is crucial for understanding genotype-phenotype correlations and may have implications for predicting disease severity. 51 The improved diagnostic yield achieved by LRS in our study (25% of previously undiagnosed cases) has significant clinical implications. Precise genetic counseling to patients and their families can allow for informed decision-making regarding family planning and genetic testing of at-risk relatives. 52 Furthermore, preimplantation genetic testing for couples undergoing assisted reproduction can potentially reduce the transmission of ADPKD to future generations. 53 Despite these advantages, it is important to acknowledge the current limitations of LRS technology. These include higher error rates compared to short-read sequencing and higher costs associated with the technology. 54 However, ongoing improvements in LRS accuracy and decreasing costs are likely to mitigate these limitations in the near future. Future applications of LRS technology should focus on several directions. First, integrating LRS into routine clinical genetic testing for ADPKD, including the development of standardized protocols and bioinformatics pipelines optimized for PKD1 and PKD2 analysis. Second, investigating the utility of LRS in other genetically complex disorders, particularly those involving large genes, pseudogenes, or repetitive regions. Third, developing improved methods for functional characterization of novel variants identified by LRS, including high-throughput assays for assessing the impact of deep intronic or regulatory variants. Conclusion Our study demonstrated that targeted long-read sequencing enabled a higher diagnostic yield for ADPKD through accurate and precise genetic analysis of SNVs, indels, and CNVs in PKD1 and PKD2 . This approach has significant implications for improving genetic diagnosis, particularly in cases where conventional sequencing methods have been inconclusive. As LRS technologies continue to evolve and become more accessible, their integration into routine clinical practice has the potential to improve genetic counseling and offer preimplantation genetic testing for more ADPKD patients. Declarations DATA AVAILABILITY All other data and materials are available from the corresponding authors upon reasonable request. CODE AVAILABILITY PacBio ccs is available at https://github.com/PacificBiosciences/ccs. PacBio lima is available at https://github.com/PacificBiosciences/barcoding. PacBio pbmn2 is available at https://github.com/PacificBiosciences/pbmm2. FreeBayes1.3.4 is available at https://github.com/freebayes/freebayes. IGV v.2.17.4 is available at https://software.broadinstitute.org/software/igv/download ACKOWLEDGMENTS This study was supported by the National Key Research and Development Program of China (2022YFC2703200, 2021YFC2700600, 2021YFC2700500, 2023YFC2705500), Key Construction Project of Shandong (2023ZLGX02) and Medical and Health Development Program of Shandong Province (202201030242). We thank all the patients and their families for their participation in this study. AUTHOR CONTRIBUTIONS Y.G., X.G. and J. Y. involved in the study concept and design. A.M. and L.C. acquired the data. Q.S., P.X., S.H. and L.J. analyzed and interpreted the data. H.K. and J.H. performed the experiments for variant confirmation. W.J. performed the bioinformatics analysis. J.L. and D.S. recruited the participants. Q.S. and P.X. drafted the original manuscript. All authors reviewed and approved the final article. 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May 2013;24(6):1006-1013. doi:10.1681/asn.2012070650 Chebib FT, Torres VE. Autosomal Dominant Polycystic Kidney Disease: Core Curriculum 2016. American journal of kidney diseases : the official journal of the National Kidney Foundation . May 2016;67(5):792-810. doi:10.1053/j.ajkd.2015.07.037 De Rycke M, Goossens V, Kokkali G, Meijer-Hoogeveen M, Coonen E, Moutou C. ESHRE PGD Consortium data collection XIV-XV: cycles from January 2011 to December 2012 with pregnancy follow-up to October 2013. Human reproduction (Oxford, England) . Oct 1 2017;32(10):1974-1994. doi:10.1093/humrep/dex265 Logsdon GA, Vollger MR, Eichler EE. Long-read human genome sequencing and its applications. Nature reviews Genetics . Oct 2020;21(10):597-614. doi:10.1038/s41576-020-0236-x Table 1 Table 1. PKD1 variants identified by LRS and NGS in the 40 ADPKD probands. Sample NGS LRS Concordance analysis Nucleotide Nucleotide Amino acid Region Type Pathogenicity Novel KPK001 ND c.160_166dup p.L56Pfs*60 Exon1 Frameshift P No Discordant KPK002 ND c.160_166dup p.L56Pfs*60 Exon1 Frameshift P No Discordant KPK003 ND c.2180T>C p.L727P Exon11 Missense LP No Discordant KPK004 ND c.8161+1G>A NA Intron22 Splicing P No Discordant KPK005 ND c.-49_43del NA Exon1 Start codon loss P Yes Discordant KPK006 ND c.2985+2_2985+4del NA Intron12 Splicing P Yes Discordant KPK007 ND c.10709_10760dup p.W3588Gfs*56 Exon36 Frameshift P Yes Discordant KPK008 ND c.2098-107G>A NA Intron10 Splicing VUS Yes Discordant KPK009 c.10984C>T, c.12408G>T c.11712+81_11713-100del, c.10984C>T/ c.12408G>T NA p.R3662C, p.R4136S Intron42 Exon37, Exon45 Splicing Missense, Missense VUS VUS, VUS Yes Yes, Yes Concordant* KPK010 c.8949-14C>G, c.9193G>A, c.9789G>T c.8949-14C>G, c.9193G>A, c.9789G>T NA p.V3065M, p.W3263C Intron24, Exon25, Exon29 Splicing, Missense, Missense VUS, VUS, VUS No Concordant* KPK011 ND Del40.9kb (chr16:2,132,723-2,173,682) NA Upstream-Intron1 Deletion P Yes Discordant KPK012 ND Del2.1kb (chr16:2,088,749-2,090,850) NA Exon44-Intron46 Deletion P Yes Discordant KPK013 Del(Upstream, E3,5-7,9-14) Del39.9kb (chr16:2,112,048-2,151,914) NA Upstream-Intron14 Deletion P Yes Concordant* KPK014 Del(E1-14) Del39.9kb (chr16:2,112,048-2,151,914) NA Upstream-Intron14 Deletion P Yes Concordant* KPK015 Del(Upstream,E3,5-7,9-15) Del90.6kb (chr16:2,109,835-2,200,473) NA Upstream-Exon15 Deletion P Yes Concordant* KPK016 Del(E10-11) Del2.4kb (chr16:2,113,448-2,115,805) NA Intron9-Intron11 Deletion P Yes Concordant* KPK017 Del(E15) Del3.2kb (chr16:2,108,095-2,111,259) NA Exon15-Intron15 Deletion P Yes Concordant* KPK018 Del(E31-34) Del1.7kb (chr16:2,096,810-2,098,505) NA Intron30-Intron34 Deletion P Yes Concordant* KPK019 Dup(E43-44) Dup612bp (chr16:2,090,688-2,091,265, chr16:2,091,204-2,091,237) NA Intron42-Exon44 Duplication P Yes Concordant* KPK020 c.191G>C c.191G>C p.R64P Exon1 Missense VUS No Concordant KPK021 c.386G>A c.386G>A p.C129Y Exon4 Missense VUS Yes Concordant KPK022 c.1386-11C>G c.1386-11C>G NA Intron6 Splicing VUS Yes Concordant KPK023 c.1676C>T c.1676C>T p.P559L Exon8 Missense VUS No Concordant KPK024 c.1781T>C c.1781T>C p.F594S Exon9 Missense VUS No Concordant KPK025 c.2153A>C c.2153A>C p.Q718P Exon11 Missense VUS Yes Concordant KPK026 c.4573G>T c.4573G>T p.V1525F Exon15 Missense VUS Yes Concordant KPK027 c.4999A>C c.4999A>C p.T1667P Exon15 Missense VUS Yes Concordant KPK028 c.6170T>A c.6170T>A p.V2057D Exon15 Missense VUS Yes Concordant KPK029 c.7587G>C c.7587G>C p.K2529N Exon19 Missense VUS Yes Concordant KPK030 c.8501T>C c.8501T>C p.F2834S Exon23 Missense VUS Yes Concordant KPK031 c.9559G>A c.9559G>A p.D3187N Exon27 Missense VUS Yes Concordant KPK032 c.9758T>C c.9758T>C p.L3253P Exon29 Missense VUS Yes Concordant KPK033 c.10785C>G c.10785C>G p.S3595R Exon36 Missense VUS Yes Concordant KPK034 c.11588T>C c.11588T>C p.L3863P Exon42 Missense VUS Yes Concordant KPK035 c.12048C>T c.12048C>T p.G4016= Exon44 Splicing VUS→P No Concordant KPK036 ND c.1607-76C>T NA Intron7 Splicing LB Yes Concordant KPK037 ND ND NA NA NA NA NA Concordant KPK038 ND ND NA NA NA NA NA Concordant KPK039 ND ND NA NA NA NA NA Concordant KPK040 ND ND NA NA NA NA NA Concordant ND, not detected; NA, not applicable; P, pathogenic; LP, likely pathogenic; VUS, variants of uncertain significance; LB, likely benign; *, LRS determined the phasing or had single-nucleotide resolution; reference build, GRCh38/hg38; PKD1 transcript, NM_001009944.3. Additional Declarations (Not answered) Supplementary Files SupplementalTable1.xlsx Supplementary Table 1 SupplementalFigure1.pdf Supplementary Figure 1 SupplementalFigure2.pdf Supplementary Figure 2 SupplementalFigure3.pdf Supplementary Figure 3 SupplementalFigure4.pdf Supplementary Figure 4 Cite Share Download PDF Status: Published Journal Publication published 11 Mar, 2025 Read the published version in npj Genomic Medicine → Version 1 posted Editorial decision: revise 29 Nov, 2024 Review # 2 received at journal 28 Nov, 2024 Review # 1 received at journal 24 Nov, 2024 Review # 3 received at journal 14 Nov, 2024 Reviewer # 3 agreed at journal 04 Nov, 2024 Reviewer # 2 agreed at journal 31 Oct, 2024 Reviewer # 1 agreed at journal 31 Oct, 2024 Reviewers invited by journal 30 Oct, 2024 Submission checks completed at journal 18 Oct, 2024 First submitted to journal 09 Oct, 2024 Editor assigned by journal 09 Oct, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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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-5235348","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":372276962,"identity":"6e99125b-56fa-40f2-bf81-afab94b002a2","order_by":0,"name":"Yuan 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1","display":"","copyAsset":false,"role":"figure","size":223842,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFlowchart of study design. \u003c/strong\u003e*, the variant \u003cem\u003ePKD1\u003c/em\u003e:c.12048C\u0026gt;T in KPK035 was classified as VUS at the time of enrollment, and was upgraded to pathogenic with added evidence in this study.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-5235348/v1/be3f3bac967d8b6bdc66f58d.png"},{"id":69443368,"identity":"d1bd982d-d47f-49cb-bb7f-5e2fc789fc99","added_by":"auto","created_at":"2024-11-20 11:37:19","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":226512,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDesign of multiplex long-range PCR primers for \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003ePKD1\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e and \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003ePKD2\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e.\u003c/strong\u003e (A) PCR design for \u003cem\u003ePKD1\u003c/em\u003e and alignment of six pseudogenes (\u003cem\u003ePKD1P1\u003c/em\u003e-P6) to \u003cem\u003ePKD1\u003c/em\u003e. The \u003cem\u003ePKD1P1\u003c/em\u003e-\u003cem\u003eP6\u003c/em\u003e were individually aligned to \u003cem\u003ePKD1\u003c/em\u003e to show the sequence difference, as indicated by vertical horizontal lines. The green, red, blue, orange, and purple vertical lines represented A, T, C, G, and insertions, respectively. The horizontal lines represented deletions. (B) PCR design for \u003cem\u003ePKD2\u003c/em\u003e. GF, forward gap primer; GR, reverse gap primer.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-5235348/v1/e1b7100debcc5ba836186323.png"},{"id":69442759,"identity":"95bd4f33-f323-45d5-98f0-f73cf97528b5","added_by":"auto","created_at":"2024-11-20 11:29:19","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":201846,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLRS additionally identified four \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003ePKD1\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eSNVs/indels caused by microgene conversion between \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003ePKD1\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e and pseudogenes. \u003c/strong\u003e(A-C) IGV plots of CCS reads showing \u003cem\u003ePKD1\u003c/em\u003e:c.160_166dup (A), \u003cem\u003ePKD1\u003c/em\u003e:c.2180T\u0026gt;C (B), and \u003cem\u003ePKD1\u003c/em\u003e:c.8161+1G\u0026gt;A (C). Pseudogenes were aligned to \u003cem\u003ePKD1\u003c/em\u003e and those homologous to the displayed region were shown in the IGV plots. The dotted boxes highlighted regions with microgene conversion.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-5235348/v1/d7b09aa343038c2e04f430e4.png"},{"id":69442755,"identity":"db77ef7a-4435-4407-934c-f8557964467a","added_by":"auto","created_at":"2024-11-20 11:29:19","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":642432,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLRS additionally identified three indels and two deep intronic variants in \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003ePKD1\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e. \u003c/strong\u003e(A-C) IGV plots of CCS reads showing \u003cem\u003ePKD1\u003c/em\u003e:c.-49_43del (A), \u003cem\u003ePKD1\u003c/em\u003e:c.2985+2_2985+4del (B), and \u003cem\u003ePKD1\u003c/em\u003e:c.10709_10760dup (C). (D) IGV plots of CCS reads showing two deep intronic variants, \u003cem\u003ePKD1\u003c/em\u003e:c.1607-76C\u0026gt;T and \u003cem\u003ePKD1\u003c/em\u003e:c.2908-107G\u0026gt;A. (E) Amplification of cDNA showing the existence of an alternative transcript caused by the variant \u003cem\u003ePKD1\u003c/em\u003e:c.2908-107G\u0026gt;A. (F) Diagram showing the transcription of 111-bp pseudoexon led to inframe insertion of 37 amino acids caused by the variant \u003cem\u003ePKD1\u003c/em\u003e:c.2908-107G\u0026gt;A. (G) The pedigree, phenotypes and genotypes of the family of KPK008 with the variant \u003cem\u003ePKD1\u003c/em\u003e:c.2908-107G\u0026gt;A. (H-I) IGV plots of CCS reads showing the phasing the three variants in KPK009 (H) and KPK010 (I).\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-5235348/v1/d0ff472d93eab96524107ac0.png"},{"id":69442758,"identity":"30b10f9a-7a58-4773-bef9-31e35643f57b","added_by":"auto","created_at":"2024-11-20 11:29:19","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":254612,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLRS identified eight large deletions in \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003ePKD1\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e. \u003c/strong\u003e(A-E) IGV plots of CCS reads showing the deletions in KPK013, KPK014, and KPK015 (A), KPK016 and KPK017 (B), KPK018 (C), KPK011 (D), and KPK012 (E). The purple and blue boxes represented two alleles, and the purple alleles contained the deletions.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-5235348/v1/26431b28a9f148f0c4bb8907.png"},{"id":69442756,"identity":"84d30bd2-3f8f-4697-914c-d3f1a003d88e","added_by":"auto","created_at":"2024-11-20 11:29:19","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":880770,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLRS identified a large duplication in \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003ePKD1\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e. \u003c/strong\u003e(A) MLPA showing the duplication of probes targeting exon 43 and 44 of \u003cem\u003ePKD1\u003c/em\u003e in KPK019. (B) IGV plots of CCS reads showing the 578-bp deletion (chr16:2,090,688-2,091,265) encompassing partial intron 42, exon 43, intron 43 and partial exon 44 in KPK019. (C) Diagram showing the duplication arrangement. The arrows indicated the design of primers of cDNA analysis. (D) Sanger sequencing validated the breakpoints of duplication identified by LRS. (E) Amplification of cDNA showing the existence of an alternative transcript caused by the 578-bp duplication. (F) Sanger sequencing of the cDNA showing the duplicated transcription of exon 43, and the partially duplicated exon 44 was skipped. (G) The pedigree, phenotypes and genotypes of the family of KPK019 with the 578-bp duplication\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-5235348/v1/37c055f1e03eb6c4fcea6126.png"},{"id":78330119,"identity":"91101628-f0f3-454b-89d1-49e6e29346fa","added_by":"auto","created_at":"2025-03-12 07:06:35","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3420529,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5235348/v1/e657eebf-12a1-4d59-a497-ade522321110.pdf"},{"id":69443369,"identity":"d2f57a8e-d37a-4f9d-a350-856f2bd1a942","added_by":"auto","created_at":"2024-11-20 11:37:19","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":10806,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Table 1\u003c/p\u003e","description":"","filename":"SupplementalTable1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-5235348/v1/616cf3b24c01dd9f4655d688.xlsx"},{"id":69442751,"identity":"242d7e52-4bc1-410e-9ee6-1148eaea4aba","added_by":"auto","created_at":"2024-11-20 11:29:19","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":562819,"visible":true,"origin":"","legend":"Supplementary Figure 1","description":"","filename":"SupplementalFigure1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5235348/v1/b375534a43b765625059b780.pdf"},{"id":69442752,"identity":"3b36f174-b25b-4fb3-a656-3860596a5d95","added_by":"auto","created_at":"2024-11-20 11:29:19","extension":"pdf","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":1065157,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Figure 2\u003c/p\u003e","description":"","filename":"SupplementalFigure2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5235348/v1/c05e88442239a9ec0794b82e.pdf"},{"id":69442754,"identity":"07c54811-2653-4d05-9960-558d09a9ba54","added_by":"auto","created_at":"2024-11-20 11:29:19","extension":"pdf","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":779571,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Figure 3\u003c/p\u003e","description":"","filename":"SupplementalFigure3.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5235348/v1/f7795a64fc3f667244fc168b.pdf"},{"id":69442760,"identity":"248c0963-f010-42f1-a714-893face959cb","added_by":"auto","created_at":"2024-11-20 11:29:19","extension":"pdf","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":34747785,"visible":true,"origin":"","legend":"Supplementary Figure 4","description":"","filename":"SupplementalFigure4.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5235348/v1/9bbc4a1d730a6d96a390bc5e.pdf"}],"financialInterests":"(Not answered)","formattedTitle":"Targeted long-read sequencing enables higher diagnostic yield of ADPKD by accurate PKD1 genetic analysis in an assisted reproductive center","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAutosomal dominant polycystic kidney disease (ADPKD), with an incidence of approximately 0.1%-0.25% worldwide, is one of the most common inherited kidney disorders and responsible for 5%-10% of end-stage renal disease.\u003csup\u003e1,2\u003c/sup\u003e Disease-causing variants in \u003cem\u003ePKD1\u003c/em\u003e and \u003cem\u003ePKD2\u003c/em\u003e account for approximately 85% and 15% of ADPKD, respectively.\u003csup\u003e3\u003c/sup\u003e In general, ADPKD is clinically diagnosed by ultrasonography based on age-related criteria.\u003csup\u003e4\u003c/sup\u003e However, the diagnosis made by imaging may be uncertain, particularly in young individuals less than 30 years old.\u003csup\u003e4\u003c/sup\u003e Therefore, molecular genetic testing is required to achieve a definite diagnosis.\u003csup\u003e5\u003c/sup\u003e The Genetic diagnosis of ADPKD can provide significant benefits for patients who seek for genetic counseling during the assisted reproductive treatments and reduce the possibility of at-risk pregnancies.\u003csup\u003e6\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHowever, the genetic diagnosis of ADPKD has been particularly challenging due to several factors. First, \u003cem\u003ePKD1\u003c/em\u003e gene has a large size and contains 46 exons spanning 47.2-kb of genomic DNA.\u003csup\u003e5\u003c/sup\u003e Second, genetic analysis for \u003cem\u003ePKD1\u003c/em\u003e is complicated by the presence of 39.9-kb duplicated segment that encompasses exons 1-33 and shares 98% sequence similarity to six pseudogenes (\u003cem\u003ePKD1P1\u003c/em\u003e to \u003cem\u003ePKD1P6\u003c/em\u003e).\u003csup\u003e7,8\u003c/sup\u003e Microgene conversions between \u003cem\u003ePKD1\u003c/em\u003e and its pseudogenes can be caused by the transfer of sequences from high homology pseudogenes to functional genes, which has been reported to be associated with ADPKD.\u003csup\u003e9\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e10,11\u003c/sup\u003e Third, the high GC content of exon 1 in \u003cem\u003ePKD1\u003c/em\u003e makes it difficult to amplify and sequence using standard sequencing methods\u003csup\u003e2\u003c/sup\u003e. Last, a high level of allelic heterogeneity has been observed in disease-causing variants of \u003cem\u003ePKD1\u003c/em\u003e and \u003cem\u003ePKD2\u003c/em\u003e, including more than one thousand pathogenic or likely pathogenic single-nucleotide variants (SNVs) and insertions/deletions (indels), and the majority of these variants are exclusive to a single pedigree.\u003csup\u003e12\u003c/sup\u003e In addition, approximately 2%-6% of ADPKD are caused by copy number variants (CNVs), which consist of single to multiple exon deletions or duplications.\u003csup\u003e5,13-15\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eCurrently, a few genetic testing methods such as long-range PCR, next-generation sequencing (NGS) and multiplex ligation-dependent probe amplification (MLPA) have been used in the diagnosis of ADPKD.\u003csup\u003e16-20\u003c/sup\u003e Due to high sequence homology between \u003cem\u003ePKD1\u003c/em\u003e and its pseudogenes, NGS approaches could lead to false positive or false negative genotyping due to the incorrect calling of variants from pseudogenes.\u003csup\u003e21-23\u003c/sup\u003e Although targeted NGS combined with long-range PCR for locus-specific \u003cem\u003ePKD1\u003c/em\u003e provides a robust approach for ADPKD genetic testing, extra input for exon 1 in \u003cem\u003ePKD1\u003c/em\u003e is required to achieve balanced sequencing depth due to GC bias during NGS.\u003csup\u003e24\u003c/sup\u003e MLPA can only be employed to detect large deletions and duplications in \u003cem\u003ePKD1\u003c/em\u003e and \u003cem\u003ePKD2\u003c/em\u003e, which could increase the turnaround time and diagnostic cost.\u003csup\u003e15,24\u003c/sup\u003e These traditional methods have limitations in accurately detecting all types of variants in \u003cem\u003ePKD1\u003c/em\u003e and \u003cem\u003ePKD2\u003c/em\u003e, particularly in the duplicated regions of \u003cem\u003ePDK1\u003c/em\u003e. This has led to a significant diagnostic gap in ADPKD genetic testing, with some patients remaining undiagnosed or incompletely diagnosed despite a clear clinical phenotype. At present, the diagnostic rate in ADPKD is approximately 80% to 90%.\u003csup\u003e1,20,25-28\u003c/sup\u003e Therefore, it is necessary to improve the diagnosis for ADPKD patients, especially when they are looking for assisted reproductive treatments.\u003c/p\u003e\n\u003cp\u003eIn recent years, single-molecule GC-unbiased long-read sequencing (LRS) has emerged as a promising approach to overcome these challenges, and improved genetic diagnosis for diseases with complicated molecular genetics such as thalassemia,\u003csup\u003e29,30\u003c/sup\u003e congenital adrenal hyperplasia,\u003csup\u003e31,32\u003c/sup\u003e spinal muscular atrophy,\u003csup\u003e33,34\u003c/sup\u003e fragile-X syndrome,\u003csup\u003e35\u003c/sup\u003e hemophilia A,\u003csup\u003e36\u003c/sup\u003e and ADPKD.\u003csup\u003e27\u003c/sup\u003e LRS-based approach enables to generate reads spanning large genomic regions of \u003cem\u003ePKD1\u0026nbsp;\u003c/em\u003eand\u003cem\u003e\u0026nbsp;PKD2\u003c/em\u003e, improves detection of structural variants and better resolution of repetitive sequences, and makes incremental diagnostic rate compared to LR-PCR, NGS and MLPA combined approach.\u003csup\u003e27\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eIn this study, we aimed to evaluate the effectiveness of LRS-based approach in improving the genetic diagnosis of ADPKD, particularly for patients who had remained undiagnosed or incompletely diagnosed after conventional NGS testing.\u0026nbsp;\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eStudy participants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFrom January 2016 to December 2023, 312 patients with clinical diagnosis of ADPKD have undergone genetic testing at our assisted reproductive center using a targeted NGS panel, which included thousands of kidney disease-related genes such as \u003cem\u003ePKD1\u003c/em\u003e, \u003cem\u003ePKD2\u003c/em\u003e, \u003cem\u003ePKHD1\u003c/em\u003e and \u003cem\u003eHNF1B\u003c/em\u003e. The pathogenicity of SNV/indels was classified according to the American College of Medical Genetics and Genomics guidelines.\u003csup\u003e37\u003c/sup\u003e From this cohort, a total of 272 patients were genetically diagnosed with pathogenic (P) or likely pathogenic (LP) SNVs/indels, including 239 cases with variants in \u003cem\u003ePKD1\u003c/em\u003e, 30 cases with variants in \u003cem\u003ePKD2\u003c/em\u003e, and 3 cases with variants in \u003cem\u003eHNF1B\u003c/em\u003e (\u003cstrong\u003eFigure 1\u003c/strong\u003e). The remaining 40 patients were either genetically undiagnosed or diagnosed without single-nucleotide resolution at the time of enrollment in our study, which included 18 cases with variants of uncertain significance (VUS) in \u003cem\u003ePKD1\u003c/em\u003e, 7 cases with \u003cem\u003ePKD1\u003c/em\u003e CNVs, and 15 cases with no identified variants (\u003cstrong\u003eFigure 1\u003c/strong\u003e). Genomic DNA from these 40 patients were sent to Berry Genomics Corporation for genetic analysis of \u003cem\u003ePKD1\u003c/em\u003e and \u003cem\u003ePKD2\u0026nbsp;\u003c/em\u003ewith a targeted LRS approach (\u003cstrong\u003eFigure 2\u003c/strong\u003e). This study adhered to the Declaration of Helsinki, and was approved by the institutional review board of Center for Reproductive Medicine at Shandong University. Informed written consent was obtained from all the participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eADPKD genetic diagnosis by NGS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGenomic DNA from peripheral blood was extracted using the Blood DNA extraction kits (ZEESAN, China). Targeted NGS, with IDT xGen Exome Research Panel (Integrated DNA Technologies, USA), was performed using xGen NGS Hybridization Capture (Integrated DNA Technologies, USA) and sequencing was performed on the NovaSeq 6000 platform (Illumina, USA). High-quality sequencing reads were selected and aligned to the reference genome hg19 using the BWA algorithm with default settings.\u003csup\u003e38\u003c/sup\u003e SNVs and indels were called by GATK.\u003csup\u003e39\u003c/sup\u003e Copy-number variations (CNVs) were determined as previously described.\u003csup\u003e40\u003c/sup\u003e For samples with SNVs/indels identified by NGS, Sanger sequencing was performed to confirm the variants. For samples with CNVs\u003cem\u003e\u0026nbsp;\u003c/em\u003ein \u003cem\u003ePKD1\u003c/em\u003e and \u003cem\u003ePKD2\u003c/em\u003e identified by NGS, MLPA analysis was performed to confirm the CNVs (MRC-Holland, the Netherlands) using probemix P351 and P352 \u003cem\u003ePKD1\u003c/em\u003e-\u003cem\u003ePKD2\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eADPKD genetic diagnosis by LRS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTargeted LRS for \u003cem\u003ePKD1\u003c/em\u003e and \u003cem\u003ePKD2\u003c/em\u003e genetic analysis was performed similarly as previously described.\u003csup\u003e27\u003c/sup\u003e Genomic DNA was subjected to multiplex LR-PCR 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\u0026nbsp;\u0026mu;M of primer mixture and 1\u0026nbsp;\u0026mu;L of KOD FX Neo (Toyobo, Japan). PCR cycling conditions were 94\u0026deg;C for 5 min (1 cycle); 98\u0026deg;C for 15 s and 68\u0026deg;C for 12 min (32 cycles) and 68\u0026deg;C for 10 min (1 cycle). The PacBio single-molecule real-time dumbbell (SMRTbell) libraries were prepared by a one-step end-repair and ligation reaction to add barcoded adaptors, followed by digestion with exonucleases to remove failed ligated DNA. The uniquely barcoded libraries were purified, quantified and then pooled with equal mass. SMRTbell sequencing library was prepared using the Sequel II Binding Kit 3.2 (Pacific Biosciences, USA) and sequenced under circular consensus sequencing (CCS) mode with Sequel IIe platform (Pacific Biosciences, USA) for 30 h. After sequencing, the raw subreads were converted to high-fidelity CCS reads, debarcoded and aligned to reference genome build hg38 in the SMRT Link analysis software suite (Pacific Biosciences, USA). The aligned CCS reads were then subjected to an in-house developed bioinformatics pipeline to identify SNVs/indels, deletions and duplications (\u003cstrong\u003eFigure 2A and 2B\u003c/strong\u003e).\u003csup\u003e27\u003c/sup\u003e The CCS reads of representative variants were displayed in the Integrative Genomics Viewer (IGV).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eValidation of variants additionally detected by LRS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSanger sequencing was performed to validate discordant SNVs/indels between LRS and NGS, with primers listed in \u003cstrong\u003eSupplemental Table 1\u003c/strong\u003e. Moreover, MLPA was utilized to confirm the CNVs additionally identified by LRS.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIdentification of splicing junctions by RT-PCR sequencing\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor participants with variants that could potentially disrupt mRNA splicing, total RNA was extracted from peripheral blood using RNAiso Plus (Takara, Japan). cDNA was synthesized using PrimeScript\u0026trade; II 1st Strand cDNA Synthesis Kit (Takara, Japan) according to the manufacturer\u0026rsquo;s instructions. PCR amplification was performed using primers flanking the putative splicing junctions, and products were analyzed by Sanger sequencing to identify the exact junction sites (\u003cstrong\u003eSupplemental Table 1\u003c/strong\u003e).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eImprovement of diagnostic yield in \u003cem\u003ePKD1\u003c/em\u003e and \u003cem\u003ePKD2\u003c/em\u003e by LRS\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 40 clinically diagnosed ADPKD patients without fully genetic characterization by NGS, were retrospectively enrolled in this study (Figure 1). The cohort included 28 male and 12 female patients, with a mean age of 25.8\u0026plusmn;5.5 years. Targeted LRS for \u003cem\u003ePKD1\u003c/em\u003e and \u003cem\u003ePKD2\u003c/em\u003e genetic analysis were performed for all the 40 patients. LRS identified 9 P/LP and 17 VUS SNVs/indels in \u003cem\u003ePKD1\u003c/em\u003e, as well as 9 P/LP CNVs in \u003cem\u003ePKD1\u003c/em\u003e (\u003cstrong\u003eFigure 1\u003c/strong\u003e, \u003cstrong\u003eTable 1\u003c/strong\u003e). Compared to NGS panel-based diagnostic workflow, LRS approach identified pathogenic or likely pathogenic \u003cem\u003ePKD1\u003c/em\u003e variants in ten more patients, which increased the genetic diagnosis rate from 20.0% (8/40) to 45.0% (18/40) and the variant detection rate from 62.5% (25/40) to 87.5% (35/40). This represents a significant improvement in diagnostic yield for this challenging subset of patients.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLRS detections for \u003cem\u003ePKD1\u003c/em\u003e and \u003cem\u003ePKD2\u003c/em\u003e SNVs/indels\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEight patients were found to have pathogenic or likely pathogenic SNVs/indels in PKD1 using targeted LRS approach. These eight variants included four microgene conversions between \u003cem\u003ePKD1\u003c/em\u003e and its pseudogenes, three indels, and one deep intronic variant (\u003cstrong\u003eTable 1\u003c/strong\u003e). All the eight variants were confirmed by Sanger sequencing (\u003cstrong\u003eSupplemental Figure 1 and 2\u003c/strong\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAmong the four patients with microgene conversions, two patients harbored the same frameshift variant \u003cem\u003ePKD1\u003c/em\u003e:c.160_166dup, which was a duplication of 7 nucleotides in exon 1 and existed in four pseudogenes (\u003cem\u003ePKD1P1/3/5/6\u003c/em\u003e) (\u003cstrong\u003eFigure 3A\u003c/strong\u003e). Patient KPK003 had a missense variant \u003cem\u003ePKD1\u003c/em\u003e:c.2180T\u0026gt;C in exon 11, and this variant also located in five pseudogenes (\u003cem\u003ePKD1P1/2/3/4/5\u003c/em\u003e) (\u003cstrong\u003eFigure 3B\u003c/strong\u003e). The splice site variant \u003cem\u003ePKD1\u003c/em\u003e:c.8161+1G\u0026gt;A, identified in patient KPK004, was affecting intron 22 and located in three pseudogenes (\u003cem\u003ePKD1P1/3/4\u003c/em\u003e) (\u003cstrong\u003eFigure 3C\u003c/strong\u003e). These microgene conversions can occur in large segments of \u003cem\u003ePKD1\u003c/em\u003e gene that are identical to the pseudogenes. Using short-read NGS, variants could be missed due to the alignment of these large segments to their pseudogenes (\u003cstrong\u003eTable 1\u003c/strong\u003e). However, LRS can discriminate \u003cem\u003ePKD1\u003c/em\u003e and its pseudogenes by sequencing large segments of genomic DNA with several to ten thousand nucleotides, and enable accurate recognition of these pseudogene-driven variants.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLRS also detected two small deletions of \u003cem\u003ePKD1\u003c/em\u003e:c.-49_+43del and \u003cem\u003ePKD1\u003c/em\u003e:c.2985+2_2985+4del, and one small duplication of \u003cem\u003ePKD1\u003c/em\u003e:c.10709_10760dup in three individual samples (\u003cstrong\u003eFigure 4A to 4C\u003c/strong\u003e). These three variants were missed by traditional NGS due to limited read length or low coverage in the specific regions. Of note, LRS also identified a benign 34-bp duplication of \u003cem\u003ePKD1\u003c/em\u003e:c.11713-30_11713-63dup in sample KPK007 (\u003cstrong\u003eFigure 4C\u003c/strong\u003e). Further analysis showed that this region had a variable number of tandem repeat and occurred in 92.5% (37/40) of the samples (\u003cstrong\u003eSupplemental 2D\u003c/strong\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn addition, LRS identified two deep intronic variants, \u003cem\u003ePKD1\u003c/em\u003e:c.1607-76C\u0026gt;T in patient KPK036 and \u003cem\u003ePKD1\u003c/em\u003e:c.2908-107G\u0026gt;A in patient KPK008 (\u003cstrong\u003eFigure 4D\u003c/strong\u003e). RT-PCR sequencing proved that \u003cem\u003ePKD1\u003c/em\u003e:c.1607-76C\u0026gt;T did not affect the splicing and was a likely benign variant (\u003cstrong\u003eSupplemental Figure 2G\u003c/strong\u003e). However, RT-PCR analysis revealed that \u003cem\u003ePKD1\u003c/em\u003e:c.2908-107G\u0026gt;A created a new splice acceptor site, leading to the inclusion of a 111-nucleotide pseudoexon. This aberrant splicing event results in an inframe insertion of 37 amino acids and premature termination codon (\u003cstrong\u003eFigure 4E and 4F\u003c/strong\u003e). Moreover, pedigree analysis of 15 family members from three-generations showed \u003cem\u003ePKD1\u003c/em\u003e:c.2908-107G\u0026gt;A was likely pathogenic because the variant was co-segregated with ADPKD phenotype within the family (\u003cstrong\u003eFigure 4G\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003eBoth LRS and NGS identified the - variant \u003cem\u003ePKD1\u003c/em\u003e:c.12048C\u0026gt;T in patient KPK035 (\u003cstrong\u003eTable 1\u003c/strong\u003e). Although this was synonymous variant, RT-PCR analysis showed the variant affected splicing by creating a new exonic splice enhancer site. This led to a 92-bp deletion transcript, and resulted in a frameshift (\u003cstrong\u003eSupplemental Figure 3A and 3B\u003c/strong\u003e). In addition, this variant was also co-segregated with ADPKD phenotype through pedigree analysis (\u003cstrong\u003eSupplemental Figure 3C\u003c/strong\u003e). Thus, \u003cem\u003ePKD1\u003c/em\u003e:c.12048C\u0026gt;T was reclassified as a pathogenic variant by considering the newly added evidence.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLRS can perform the phasing analysis for SNVs/indels. In patient KPK009, the variants of \u003cem\u003ePKD1\u003c/em\u003e:c.10984C\u0026gt;T and c.11712+81_11713-100del were found to locate on one allele, while variant c.12408G\u0026gt;T was located on the other allele (\u003cstrong\u003eFigure 4H\u003c/strong\u003e). LRS also determined variants \u003cem\u003ePKD1\u003c/em\u003e:c.8949-14C\u0026gt;G, c.9193G\u0026gt;A and c.9789G\u0026gt;T were in cis-configuration in patient KPK010 (\u003cstrong\u003eFigure 4I\u003c/strong\u003e), which has been reported in another ADPKD patient.\u003csup\u003e27\u003c/sup\u003e Considering the effect of hypomorphic variants in \u003cem\u003ePKD1\u003c/em\u003e gene, the compound heterozygous variants generally cause more severe manifestations.\u003csup\u003e41,42\u003c/sup\u003e Therefore, phasing analysis can enrich the mutational spectrum of ADPKD genes and serve as a reference for future patients.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLRS detections for large deletions and duplications in \u003cem\u003ePKD1\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSix large deletions in \u003cem\u003ePKD1\u003c/em\u003e were identified by NGS and confirmed by MLPA (\u003cstrong\u003eTable 1, Supplemental Figure 4A to 4F\u003c/strong\u003e). Besides these six deletions (\u003cstrong\u003eFigure 5A to 5C\u003c/strong\u003e), LRS identified two more deletions in two samples (\u003cstrong\u003eFigure 5D and 5E\u003c/strong\u003e), which were also confirmed by MLPA (\u003cstrong\u003eSupplemental Figure 4G and 4H\u003c/strong\u003e). Moreover, LRS was able to precisely determine the breakpoints of these eight large deletions in CNVs.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNGS and MLPA can detect the duplication of exon 43 and 44 in \u003cem\u003ePKD1\u003c/em\u003e (\u003cstrong\u003eFigure 6A\u003c/strong\u003e). However, the exact sequence and inserted position of these duplications cannot be determined by traditional sequencing methods. LRS demonstrated that the duplication was a 578-bp sequence (hg38 chr16:2,090,688-2,091,265) encompassing partial intron 42, exon 43, intron 43, and partial exon 44 (\u003cstrong\u003eFigure 6B and 6C\u003c/strong\u003e). The breakpoint of duplication was validated by Sanger sequencing (\u003cstrong\u003eFigure 6D\u003c/strong\u003e). RT-PCR analysis showed that the duplication led to an alternative transcript with duplication of exon 43 and thus an in-frame insertion of 97 amino acids with skipping the duplicated partial exon 44 (\u003cstrong\u003eFigure 6C, 6E and 6F\u003c/strong\u003e). Therefore, LRS can directly detect large duplications in \u003cem\u003ePKD1\u003c/em\u003e at single-nucleotide resolution. In addition, this duplication was found to co-segregate with ADPKD phenotype in a three-generation pedigree (\u003cstrong\u003eFigure 6G\u003c/strong\u003e).\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eFor the past eight years, our assisted reproductive center has utilized NGS panel for genetic testing of 312 ADPKD patients. Compared to NGS panel, targeted LRS additionally identified eight P/LP SNVs/indels and two P/LP CNVs in \u003cem\u003ePKD1\u003c/em\u003e, as well as determined single-nucleotide information for all the CNVs. Our study demonstrated the significant advantages of using long-read sequencing for the genetic diagnosis of ADPKD, particularly in cases where conventional NGS approaches have failed to provide a definitive diagnosis. The ability of LRS to span large genomic regions and resolve complex structural variations has allowed us to identify a spectrum of variants that were previously undetectable or difficult to characterize. The improved diagnostic yield of LRS for ADPKD patients is particularly important for assisted reproductive treatments since genetic diagnosis is required for those who seek for\u0026nbsp;preimplantation genetic testing for monogenetic diseases (PGT-M)\u0026nbsp;to lower the pregnancy risk.\u003c/p\u003e\n\u003cp\u003eThe identification of microgene conversions between \u003cem\u003ePKD1\u003c/em\u003e and its pseudogenes is particularly noteworthy to utilize LRS approach. These events, which involve the transfer of genetic information from pseudogenes to the functional \u003cem\u003ePKD1\u003c/em\u003e gene, can be easily missed by short-read sequencing technologies due to the high sequence similarity between \u003cem\u003ePKD1\u003c/em\u003e and its pseudogenes.\u003csup\u003e7\u003c/sup\u003e In the past, microgene conversions were generally detected by short PCR followed by Sanger sequencing, which could lead to drop-out of variants with microgene conversions. In this study, LRS was used to identify four microgene conversions ranging from 200 to 1000 bp that were missed by NGS. Our results highlighted the importance of considering such mechanisms in the pathogenesis of ADPKD and underscored the requirement for sequencing technologies that can accurately distinguish between the functional gene and its pseudogenes.\u003c/p\u003e\n\u003cp\u003eAlthough various bioinformatics pipelines have been developed to call SNVs/indels from NGS data, accurate detection of indels over 50 bp is still very challenging.\u003csup\u003e27,43,44\u003c/sup\u003e Many partially mapped reads of these large indels can be lost in unmatched fragments.\u003csup\u003e27,43,44\u003c/sup\u003e In this cohort study, NGS panel failed to detect two intermediate sizes of indels including \u003cem\u003ePKD1\u003c/em\u003e:c.-49_43del and \u003cem\u003ePKD1\u003c/em\u003e:c.10709_10760dup. Surprisingly, NGS also failed to detect a 3-bp deletion \u003cem\u003ePKD1\u003c/em\u003e:c.2985+2_c.2985+4del. Manual inspection on the original NGS data suggested the presence of 3-bp deletion variant. However, the sequencing depth was only 15x in this specific area, and 20x sequencing depth is generally required to make a call in the bioinformatics pipeline, which is a common issue for large NGS panels. In NGS, the quality control for average sequencing depth is usually acceptable, but it does not guarantee the sequencing depth in each specific locus. The targeted LRS assay utilized full-length reads of each amplicon to do variant calling, therefore all the regions within the coverage can be successfully analyzed with adequate depth.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn recent years, more and more disease-causing deep intronic variants were discovered due to rapid development of sequencing technologies.\u003csup\u003e45,46\u003c/sup\u003e Such variants can be easily overlooked by exon-focused sequencing approaches but may have significant implications for disease pathogenesis.\u003csup\u003e47\u003c/sup\u003e Therefore, the characterization of deep intronic variants demands comprehensive gene coverage in the genetic testing for ADPKD. In this study, LRS identified two novel deep intronic variants \u003cem\u003ePKD1\u003c/em\u003e:c.1607-76C\u0026gt;T and \u003cem\u003ePKD1\u003c/em\u003e:c.2908-107G\u0026gt;A that were undetectable in NGS panel. RT-PCR analysis showed that \u003cem\u003ePKD1\u003c/em\u003e:c.1607-76C\u0026gt;T did not affect the splicing, but \u003cem\u003ePKD1\u003c/em\u003e:c.2908-107G\u0026gt;A led to the inclusion of a 111-nucleotide pseudoexon with an inframe insertion of 37 amino acids. Pedigree analysis proved \u003cem\u003ePKD1\u003c/em\u003e:c.2908-107G\u0026gt;A was co-segregated with ADPKD phenotype and was a likely pathogenic variant. The identification of the c.2908-107G\u0026gt;A variant and its effect on splicing illustrated the potential of LRS to expand our understanding of the mutational spectrum in ADPKD.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSince the majority of \u003cem\u003ePKD1\u003c/em\u003e and \u003cem\u003ePKD2\u003c/em\u003e variants are exclusive to single families, novel and VUS variants can be identified in a cohort of ADPKD patients.\u003csup\u003e25-27\u003c/sup\u003e Precise genetic diagnosis is required for PGT-M to select embryos without disease-causing variants, therefore functional and pedigree analysis are critical to accumulate evidence to determine the pathogenicity of each variant according to the AMCG guidelines. Here we found that the synonymous variant \u003cem\u003ePKD1\u003c/em\u003e:c.12048C\u0026gt;T caused a 62-bp deletion transcript and thus frameshift of translation by RT-PCR. In combination of co-segregation analysis, the pathogenicity of this variant was upgraded from VUS to pathogenic. Moreover, LRS can determine the cis and trans-configuration of variants within the same PCR amplicon without the need of pedigree analysis.\u003c/p\u003e\n\u003cp\u003eBesides SNVs/indels, NGS has been gradually and widely used for CNV analysis.\u003csup\u003e48,49\u003c/sup\u003eIn our study, LRS identified two more \u003cem\u003ePKD1\u003c/em\u003e CNVs compared to NGS, including one deletion encompassing exon 44 to 46 and another deletion encompassing exon 1 to upstream regions. This highlighted the superior sensitivity of LRS for CNV detection in complex genomic regions. The improved detection of CNVs by LRS addressed a significant limitation of NGS-based approaches. NGS typically relies on read depth analysis to infer CNVs, which can be challenging in regions with pseudogenes or repetitive sequences.\u003csup\u003e50\u003c/sup\u003e In addition, the precise determination of breakpoints by LRS offered valuable insights into the molecular mechanisms underlying these variants, which is crucial for understanding genotype-phenotype correlations and may have implications for predicting disease severity.\u003csup\u003e51\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe improved diagnostic yield achieved by LRS in our study (25% of previously undiagnosed cases) has significant clinical implications. Precise genetic counseling to patients and their families can allow for informed decision-making regarding family planning and genetic testing of at-risk relatives.\u003csup\u003e52\u003c/sup\u003e Furthermore, preimplantation genetic testing for couples undergoing assisted reproduction can potentially reduce the transmission of ADPKD to future generations.\u003csup\u003e53\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDespite these advantages, it is important to acknowledge the current limitations of LRS technology. These include higher error rates compared to short-read sequencing and higher costs associated with the technology.\u003csup\u003e54\u003c/sup\u003e However, ongoing improvements in LRS accuracy and decreasing costs are likely to mitigate these limitations in the near future.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFuture applications of LRS technology should focus on several directions. First, integrating LRS into routine clinical genetic testing for ADPKD, including the development of standardized protocols and bioinformatics pipelines optimized for \u003cem\u003ePKD1\u003c/em\u003e and \u003cem\u003ePKD2\u003c/em\u003e analysis. Second, investigating the utility of LRS in other genetically complex disorders, particularly those involving large genes, pseudogenes, or repetitive regions. Third, developing improved methods for functional characterization of novel variants identified by LRS, including high-throughput assays for assessing the impact of deep intronic or regulatory variants.\u0026nbsp;\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur study demonstrated that targeted long-read sequencing enabled a higher diagnostic yield for ADPKD through accurate and precise genetic analysis of SNVs, indels, and CNVs in \u003cem\u003ePKD1\u003c/em\u003e and \u003cem\u003ePKD2\u003c/em\u003e. This approach has significant implications for improving genetic diagnosis, particularly in cases where conventional sequencing methods have been inconclusive. As LRS technologies continue to evolve and become more accessible, their integration into routine clinical practice has the potential to improve genetic counseling and offer preimplantation genetic testing for more ADPKD patients.\u003c/p\u003e\n"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eDATA AVAILABILITY\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll other data and materials are available from the corresponding authors upon reasonable request.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eCODE AVAILABILITY\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePacBio ccs is available at https://github.com/PacificBiosciences/ccs. PacBio lima is available at https://github.com/PacificBiosciences/barcoding. PacBio pbmn2 is available at https://github.com/PacificBiosciences/pbmm2. FreeBayes1.3.4 is available at https://github.com/freebayes/freebayes. IGV v.2.17.4 is available at https://software.broadinstitute.org/software/igv/download\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eACKOWLEDGMENTS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by the National Key Research and Development Program of China (2022YFC2703200, 2021YFC2700600, 2021YFC2700500, 2023YFC2705500), Key Construction Project of Shandong (2023ZLGX02) and Medical and Health Development Program of Shandong Province (202201030242). We thank all the patients and their families for their participation in this study.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eAUTHOR CONTRIBUTIONS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eY.G., X.G. and J. Y. involved in the study concept and design. A.M. and L.C. acquired the data. Q.S., P.X., S.H. and L.J. analyzed and interpreted the data. H.K. and J.H. performed the experiments for variant confirmation. W.J. performed the bioinformatics analysis. J.L. and D.S. recruited the participants. Q.S. and P.X. drafted the original manuscript. All authors reviewed and approved the final article.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eCOMPETING INTERESTS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA.M and L.C. are employees of Berry Genomics Corporation. The other authors declare no conflict of interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eHarris PC, Rossetti S. Molecular diagnostics for autosomal dominant polycystic kidney disease. \u003cem\u003eNature reviews Nephrology\u003c/em\u003e. Apr 2010;6(4):197-206. doi:10.1038/nrneph.2010.18\u003c/li\u003e\n\u003cli\u003eLanktree MB, Haghighi A, di Bari I, Song X, Pei Y. Insights into Autosomal Dominant Polycystic Kidney Disease from Genetic Studies. \u003cem\u003eClinical journal of the American Society of Nephrology : CJASN\u003c/em\u003e. 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Comprehensive Analysis of Spinal Muscular Atrophy: SMN1 Copy Number, Intragenic Mutation, and 2 + 0 Carrier Analysis by Third-Generation Sequencing. \u003cem\u003eThe Journal of molecular diagnostics : JMD\u003c/em\u003e. Sep 2022;24(9):1009-1020. doi:10.1016/j.jmoldx.2022.05.001\u003c/li\u003e\n\u003cli\u003eLi S, Han X, Zhang L, et al. An Effective and Universal Long-Read Sequencing-Based Approach for SMN1 2 + 0 Carrier Screening through Family Trio Analysis. \u003cem\u003eClinical chemistry\u003c/em\u003e. Nov 2 2023;69(11):1295-1306. doi:10.1093/clinchem/hvad152\u003c/li\u003e\n\u003cli\u003eLiang Q, Liu Y, Liu Y, et al. Comprehensive Analysis of Fragile X Syndrome: Full Characterization of the FMR1 Locus by Long-Read Sequencing. \u003cem\u003eClinical chemistry\u003c/em\u003e. Dec 6 2022;68(12):1529-1540. doi:10.1093/clinchem/hvac154\u003c/li\u003e\n\u003cli\u003eLiu Y, Li D, Yu D, et al. Comprehensive Analysis of Hemophilia A (CAHEA): Towards Full Characterization of the F8 Gene Variants by Long-Read Sequencing. \u003cem\u003eThrombosis and haemostasis\u003c/em\u003e. Dec 2023;123(12):1151-1164. doi:10.1055/a-2107-0702\u003c/li\u003e\n\u003cli\u003eRichards S, Aziz N, Bale S, et al. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. \u003cem\u003eGenetics in medicine : official journal of the American College of Medical Genetics\u003c/em\u003e. May 2015;17(5):405-424. doi:10.1038/gim.2015.30\u003c/li\u003e\n\u003cli\u003eLi H, Durbin R. Fast and accurate long-read alignment with Burrows-Wheeler transform. \u003cem\u003eBioinformatics (Oxford, England)\u003c/em\u003e. Mar 1 2010;26(5):589-595. doi:10.1093/bioinformatics/btp698\u003c/li\u003e\n\u003cli\u003eMcKenna A, Hanna M, Banks E, et al. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. \u003cem\u003eGenome research\u003c/em\u003e. Sep 2010;20(9):1297-1303. doi:10.1101/gr.107524.110\u003c/li\u003e\n\u003cli\u003eShang X, Peng Z, Ye Y, et al. Rapid Targeted Next-Generation Sequencing Platform for Molecular Screening and Clinical Genotyping in Subjects with Hemoglobinopathies. \u003cem\u003eEBioMedicine\u003c/em\u003e. Sep 2017;23:150-159. doi:10.1016/j.ebiom.2017.08.015\u003c/li\u003e\n\u003cli\u003eDurkie M, Chong J, Valluru MK, Harris PC, Ong ACM. Biallelic inheritance of hypomorphic PKD1 variants is highly prevalent in very early onset polycystic kidney disease. \u003cem\u003eGenetics in medicine : official journal of the American College of Medical Genetics\u003c/em\u003e. Apr 2021;23(4):689-697. doi:10.1038/s41436-020-01026-4\u003c/li\u003e\n\u003cli\u003eGilbert RD, Sukhtankar P, Lachlan K, Fowler DJ. Bilineal inheritance of PKD1 abnormalities mimicking autosomal recessive polycystic disease. \u003cem\u003ePediatric nephrology (Berlin, Germany)\u003c/em\u003e. Nov 2013;28(11):2217-2220. doi:10.1007/s00467-013-2484-x\u003c/li\u003e\n\u003cli\u003eCraven KE, Fischer CG, Jiang L, Pallavajjala A, Lin MT, Eshleman JR. Optimizing Insertion and Deletion Detection Using Next-Generation Sequencing in the Clinical Laboratory. \u003cem\u003eThe Journal of molecular diagnostics : JMD\u003c/em\u003e. Dec 2022;24(12):1217-1231. doi:10.1016/j.jmoldx.2022.08.006\u003c/li\u003e\n\u003cli\u003eShigemizu D, Miya F, Akiyama S, et al. IMSindel: An accurate intermediate-size indel detection tool incorporating de novo assembly and gapped global-local alignment with split read analysis. \u003cem\u003eScientific reports\u003c/em\u003e. Apr 4 2018;8(1):5608. doi:10.1038/s41598-018-23978-z\u003c/li\u003e\n\u003cli\u003eZhang C, Yan Y, Zhou B, et al. Identification of deep intronic variants of PAH in phenylketonuria using full-length gene sequencing. \u003cem\u003eOrphanet journal of rare diseases\u003c/em\u003e. May 26 2023;18(1):128. doi:10.1186/s13023-023-02742-1\u003c/li\u003e\n\u003cli\u003eLuo X, Wang R, Sun Y, et al. Deep Intronic PAH Variants Explain Missing Heritability in Hyperphenylalaninemia. \u003cem\u003eThe Journal of molecular diagnostics : JMD\u003c/em\u003e. May 2023;25(5):284-294. doi:10.1016/j.jmoldx.2023.02.001\u003c/li\u003e\n\u003cli\u003eVaz-Drago R, Cust\u0026oacute;dio N, Carmo-Fonseca M. Deep intronic mutations and human disease. \u003cem\u003eHuman genetics\u003c/em\u003e. Sep 2017;136(9):1093-1111. doi:10.1007/s00439-017-1809-4\u003c/li\u003e\n\u003cli\u003eFromer M, Moran JL, Chambert K, et al. Discovery and statistical genotyping of copy-number variation from whole-exome sequencing depth. \u003cem\u003eAmerican journal of human genetics\u003c/em\u003e. Oct 5 2012;91(4):597-607. doi:10.1016/j.ajhg.2012.08.005\u003c/li\u003e\n\u003cli\u003eGambin T, Akdemir ZC, Yuan B, et al. Homozygous and hemizygous CNV detection from exome sequencing data in a Mendelian disease cohort. \u003cem\u003eNucleic acids research\u003c/em\u003e. Feb 28 2017;45(4):1633-1648. doi:10.1093/nar/gkw1237\u003c/li\u003e\n\u003cli\u003eZarrei M, MacDonald JR, Merico D, Scherer SW. A copy number variation map of the human genome. \u003cem\u003eNature reviews Genetics\u003c/em\u003e. Mar 2015;16(3):172-183. doi:10.1038/nrg3871\u003c/li\u003e\n\u003cli\u003eCornec-Le Gall E, Audr\u0026eacute;zet MP, Chen JM, et al. Type of PKD1 mutation influences renal outcome in ADPKD. \u003cem\u003eJournal of the American Society of Nephrology : JASN\u003c/em\u003e. May 2013;24(6):1006-1013. doi:10.1681/asn.2012070650\u003c/li\u003e\n\u003cli\u003eChebib FT, Torres VE. Autosomal Dominant Polycystic Kidney Disease: Core Curriculum 2016. \u003cem\u003eAmerican journal of kidney diseases : the official journal of the National Kidney Foundation\u003c/em\u003e. May 2016;67(5):792-810. doi:10.1053/j.ajkd.2015.07.037\u003c/li\u003e\n\u003cli\u003eDe Rycke M, Goossens V, Kokkali G, Meijer-Hoogeveen M, Coonen E, Moutou C. ESHRE PGD Consortium data collection XIV-XV: cycles from January 2011 to December 2012 with pregnancy follow-up to October 2013. \u003cem\u003eHuman reproduction (Oxford, England)\u003c/em\u003e. Oct 1 2017;32(10):1974-1994. doi:10.1093/humrep/dex265\u003c/li\u003e\n\u003cli\u003eLogsdon GA, Vollger MR, Eichler EE. Long-read human genome sequencing and its applications. \u003cem\u003eNature reviews Genetics\u003c/em\u003e. Oct 2020;21(10):597-614. doi:10.1038/s41576-020-0236-x\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table 1","content":"\u003cp\u003eTable 1. \u003cem\u003ePKD1\u003c/em\u003e variants identified by LRS and NGS in the 40 ADPKD probands.\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"782\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSample\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNGS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"6\" style=\"width: 520px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLRS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eConcordance analysis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNucleotide\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNucleotide\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAmino acid\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRegion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eType\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePathogenicity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNovel\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003eKPK001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003ec.160_166dup\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003ep.L56Pfs*60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003eExon1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eFrameshift\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eDiscordant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003eKPK002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003ec.160_166dup\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003ep.L56Pfs*60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003eExon1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eFrameshift\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eDiscordant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003eKPK003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003ec.2180T\u0026gt;C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003ep.L727P\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003eExon11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eMissense\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eLP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eDiscordant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003eKPK004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003ec.8161+1G\u0026gt;A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003eIntron22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eSplicing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eDiscordant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003eKPK005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003ec.-49_43del\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003eExon1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eStart codon loss\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eDiscordant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003eKPK006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003ec.2985+2_2985+4del\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003eIntron12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eSplicing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eDiscordant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003eKPK007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003ec.10709_10760dup\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003ep.W3588Gfs*56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003eExon36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eFrameshift\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eDiscordant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003eKPK008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003ec.2098-107G\u0026gt;A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003eIntron10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eSplicing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eVUS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eDiscordant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003eKPK009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003ec.10984C\u0026gt;T,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003ec.12408G\u0026gt;T\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003ec.11712+81_11713-100del,\u003c/p\u003e\n \u003cp\u003ec.10984C\u0026gt;T/\u003c/p\u003e\n \u003cp\u003ec.12408G\u0026gt;T\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003cp\u003ep.R3662C,\u003c/p\u003e\n \u003cp\u003ep.R4136S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003eIntron42\u003c/p\u003e\n \u003cp\u003eExon37,\u003c/p\u003e\n \u003cp\u003eExon45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eSplicing\u003c/p\u003e\n \u003cp\u003eMissense,\u003c/p\u003e\n \u003cp\u003eMissense\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eVUS\u003c/p\u003e\n \u003cp\u003eVUS,\u003c/p\u003e\n \u003cp\u003eVUS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eYes,\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eConcordant*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003eKPK010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003ec.8949-14C\u0026gt;G,\u003c/p\u003e\n \u003cp\u003ec.9193G\u0026gt;A,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003ec.9789G\u0026gt;T\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003ec.8949-14C\u0026gt;G,\u003c/p\u003e\n \u003cp\u003ec.9193G\u0026gt;A,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003ec.9789G\u0026gt;T\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eNA\u003cbr\u003e\u0026nbsp;p.V3065M,\u003cbr\u003e\u0026nbsp;p.W3263C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003eIntron24,\u003c/p\u003e\n \u003cp\u003eExon25,\u003c/p\u003e\n \u003cp\u003eExon29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eSplicing,\u003c/p\u003e\n \u003cp\u003eMissense,\u003c/p\u003e\n \u003cp\u003eMissense\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eVUS,\u003c/p\u003e\n \u003cp\u003eVUS,\u003c/p\u003e\n \u003cp\u003eVUS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eConcordant*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003eKPK011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003eDel40.9kb (chr16:2,132,723-2,173,682)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003eUpstream-Intron1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eDeletion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eDiscordant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003eKPK012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003eDel2.1kb (chr16:2,088,749-2,090,850)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003eExon44-Intron46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eDeletion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eDiscordant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003eKPK013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eDel(Upstream, E3,5-7,9-14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003eDel39.9kb (chr16:2,112,048-2,151,914)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003eUpstream-Intron14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eDeletion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eConcordant*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003eKPK014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eDel(E1-14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003eDel39.9kb (chr16:2,112,048-2,151,914)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003eUpstream-Intron14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eDeletion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eConcordant*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003eKPK015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eDel(Upstream,E3,5-7,9-15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003eDel90.6kb (chr16:2,109,835-2,200,473)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003eUpstream-Exon15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eDeletion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eConcordant*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003eKPK016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eDel(E10-11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003eDel2.4kb (chr16:2,113,448-2,115,805)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003eIntron9-Intron11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eDeletion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eConcordant*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003eKPK017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eDel(E15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003eDel3.2kb (chr16:2,108,095-2,111,259)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003eExon15-Intron15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eDeletion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eConcordant*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003eKPK018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eDel(E31-34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003eDel1.7kb (chr16:2,096,810-2,098,505)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003eIntron30-Intron34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eDeletion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eConcordant*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003eKPK019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eDup(E43-44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003eDup612bp (chr16:2,090,688-2,091,265,\u003c/p\u003e\n \u003cp\u003echr16:2,091,204-2,091,237)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003eIntron42-Exon44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eDuplication\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eConcordant*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003eKPK020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003ec.191G\u0026gt;C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003ec.191G\u0026gt;C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003ep.R64P\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003eExon1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eMissense\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eVUS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eConcordant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003eKPK021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003ec.386G\u0026gt;A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003ec.386G\u0026gt;A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003ep.C129Y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003eExon4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eMissense\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eVUS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eConcordant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003eKPK022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003ec.1386-11C\u0026gt;G\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003ec.1386-11C\u0026gt;G\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003eIntron6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eSplicing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eVUS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eConcordant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003eKPK023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003ec.1676C\u0026gt;T\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003ec.1676C\u0026gt;T\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003ep.P559L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003eExon8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eMissense\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eVUS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eConcordant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003eKPK024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003ec.1781T\u0026gt;C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003ec.1781T\u0026gt;C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003ep.F594S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003eExon9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eMissense\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eVUS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eConcordant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003eKPK025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003ec.2153A\u0026gt;C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003ec.2153A\u0026gt;C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003ep.Q718P\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003eExon11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eMissense\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eVUS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eConcordant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003eKPK026\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003ec.4573G\u0026gt;T\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003ec.4573G\u0026gt;T\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003ep.V1525F\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003eExon15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eMissense\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eVUS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eConcordant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003eKPK027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003ec.4999A\u0026gt;C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003ec.4999A\u0026gt;C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003ep.T1667P\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003eExon15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eMissense\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eVUS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eConcordant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003eKPK028\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003ec.6170T\u0026gt;A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003ec.6170T\u0026gt;A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003ep.V2057D\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003eExon15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eMissense\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eVUS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eConcordant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003eKPK029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003ec.7587G\u0026gt;C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003ec.7587G\u0026gt;C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003ep.K2529N\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003eExon19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eMissense\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eVUS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eConcordant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003eKPK030\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003ec.8501T\u0026gt;C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003ec.8501T\u0026gt;C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003ep.F2834S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003eExon23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eMissense\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eVUS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eConcordant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003eKPK031\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003ec.9559G\u0026gt;A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003ec.9559G\u0026gt;A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n 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style=\"width: 63px;\"\u003e\n \u003cp\u003eKPK038\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003eND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eConcordant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003eKPK039\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n 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\u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eConcordant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;ND, not detected; NA, not applicable; P, pathogenic; LP, likely pathogenic; VUS, variants of uncertain significance; LB, likely benign; *, LRS determined the phasing or had single-nucleotide resolution; reference build, GRCh38/hg38; \u003cem\u003ePKD1\u0026nbsp;\u003c/em\u003etranscript, NM_001009944.3.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"npj-genomic-medicine","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"npjgenmed","sideBox":"Learn more about [npj Genomic Medicine](http://www.nature.com/npjgenmed/)","snPcode":"41525","submissionUrl":"https://mts-npjgenmed.nature.com/","title":"npj Genomic Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Autosomal dominant polycystic kidney disease, PKD1, pseudogene, microgene conversion, long-read sequencing, genetic diagnosis","lastPublishedDoi":"10.21203/rs.3.rs-5235348/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5235348/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Autosomal dominant polycystic kidney disease (ADPKD) is mainly caused by disease-causing variants in two large multi-exon genes of PKD1 and PKD2. Genetic diagnosis of ADPKD has been challenging due to the variant heterogeneity, presence of duplicated segments, and high GC content of exon 1 in PKD1. In our reproductive center, a total of 312 patients with ADPKD phenotype have been genetically tested using a next-generation sequencing (NGS) panel. Among all the cases, 40 patients were either genetically undiagnosed or diagnosed without single-nucleotide resolution. Therefore, a combination of long-rang PCR and long-read sequencing (LRS) approach for PKD1 and PKD2 was performed on these 40 ADPKD patients. LRS additionally identified 10 pathogenic or likely pathogenic PKD1 variants, including eight single-nucleotide variants (SNVs) and insertions/deletions (indels) and two large deletions. Among the eight SNV/indels, LRS identified four patients with microgene conversion (c.160_166dup, c.2180T\u003eC, and c.8161+1G\u003eA) between PKD1 and its pseudogenes, three patients with indels (c.-49_43del, c.2985+2_2985+4del, and c.10709_10760dup), and one patient with likely pathogenic deep intronic variant c.2908-107G\u003eA. In addition, LRS identified nine PKD1 CNVs including eight large deletions and one duplication, and meanwhile LRS can precisely determine the breakpoints; while NGS had failed to identify two of these CNVs. In conclusion, target LRS enables higher diagnostic yield of ADPKD by accurate and precise PKD1 genetic analysis, which could provide significant benefits for genetic counseling and assisted reproductive treatments.","manuscriptTitle":"Targeted long-read sequencing enables higher diagnostic yield of ADPKD by accurate PKD1 genetic analysis in an assisted reproductive center","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-20 11:29:14","doi":"10.21203/rs.3.rs-5235348/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"revise","date":"2024-11-29T18:46:17+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"This content is not available.","date":"2024-11-28T14:44:32+00:00","index":2,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2024-11-24T20:15:51+00:00","index":1,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2024-11-14T17:16:00+00:00","index":3,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2024-11-04T13:13:47+00:00","index":3,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2024-10-31T15:04:23+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2024-10-31T12:33:38+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2024-10-30T14:39:31+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-10-18T17:50:04+00:00","index":"","fulltext":""},{"type":"submitted","content":"npj Genomic Medicine","date":"2024-10-10T00:15:34+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-10-10T00:15:34+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"npj-genomic-medicine","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"npjgenmed","sideBox":"Learn more about [npj Genomic Medicine](http://www.nature.com/npjgenmed/)","snPcode":"41525","submissionUrl":"https://mts-npjgenmed.nature.com/","title":"npj Genomic Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6f047032-54f1-46b4-8dc8-bf1770be8cd2","owner":[],"postedDate":"November 20th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-03-12T07:06:28+00:00","versionOfRecord":{"articleIdentity":"rs-5235348","link":"https://doi.org/10.1038/s41525-025-00477-5","journal":{"identity":"npj-genomic-medicine","isVorOnly":false,"title":"npj Genomic Medicine"},"publishedOn":"2025-03-11 04:00:00","publishedOnDateReadable":"March 11th, 2025"},"versionCreatedAt":"2024-11-20 11:29:14","video":"","vorDoi":"10.1038/s41525-025-00477-5","vorDoiUrl":"https://doi.org/10.1038/s41525-025-00477-5","workflowStages":[]},"version":"v1","identity":"rs-5235348","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5235348","identity":"rs-5235348","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}