Clinical Application of an Asian Screening Array-Based Preimplantation Genetic Testing Workflow for Various Genetic Disorders

Clinical Application of an Asian Screening Array-Based Preimplantation Genetic Testing Workflow for Various Genetic Disorders | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Clinical Application of an Asian Screening Array-Based Preimplantation Genetic Testing Workflow for Various Genetic Disorders Cuiting Peng, Jun Ren, Fan Zhou, Han Chen, Hong Yang, Yutong Li, and 11 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9047233/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Preimplantation genetic testing for monogenic disorders (PGT-M) represents a critical clinical strategy for preventing the transmission of hereditary diseases from carriers to offspring, with its diagnostic efficacy heavily dependent on the accuracy and coverage of detection platforms. Genome-wide SNP array such as the Asian Screening Array (ASA), has demonstrated favorable performance in haplotype analysis for PGT-M. Here, we systematically evaluated the efficiency of the Asian Screening Array-based PGT workflow in PGT application for different genetic disorders. Methods We conducted a retrospective analysis by reviewing 377 pedigrees underwent PGT-M preclinical work-up and 367 PGT-M clinical cycles (1677 embryos in total) based on the Asian Screening Array. We established detection strategies combining ASA haplotyping analysis and individualized direct mutation detection based on different genetic patterns. Long-read sequencing or single-sperm haplotyping strategy was applied for families with de novo pathogenic variants or lacking family member samples. Individualized direct mutation detection methods such as Gap-PCR, RP-PCR, PCR-RFLP were adopted for different cases. Results Results indicated the clinical validity of our ASA-based PGT workflow, integrating linkage analysis, direct mutation detection, and chromosomal CNV screening. The number of SNPs available for linkage analysis in the upstream and downstream regions of target genes/regions is sufficient for most of the cases. Individualized direct mutation detection methods for different cases also validated the ASA haplotyping results. In haplotype analysis, the method based on long-read sequencing is more effective than single-sperm haplotyping strategy. Detailed haplotyping strategy for families with microdeletions and tandem duplications was established based on ASA. A total of 636 embryos were ultimately deemed suitable for transfer after undergoing linkage analysis and CNV detection. Conclusion This study validated the feasibility and superiority of ASA-based approach in PGT, also provided a standardized and reliable technical solution for the clinical prevention of different genetic disorders. Preimplantation Genetic Testing Asian Screening Array Monogenic disorder Microdeletion/Microduplication Haplotyping analysis Figures Figure 1 Figure 2 Figure 3 1.Introduction Preimplantation Genetic Testing (PGT) is an innovative approach designed to screen for and diagnose genetic abnormalities in early embryos prior to transfer[ 1 , 2 ]. It not only provides a reliable avenue for couples at high risk of genetic disorders to have healthy children but also optimizes the outcomes of assisted reproductive therapies[ 3 ]. With the increasing global prevalence of genetic disorders, the demand for accurate and efficient PGT methodologies has become increasingly urgent[ 4 ]. With the continuous development and innovation of detection technologies, such as next generation sequencing (NGS), single-nucleotide polymorphism (SNP) array, long-read sequencing, the detection efficiency and application scope of PGT have been significantly enhanced[ 5 , 6 ]. As for preimplantation genetic testing for monogenic defects (PGT-M), haplotyping analysis combined with direct mutation detection has proven to be an effective strategy to improve test accuracy[ 7 ]. Genome-wide SNP array represented by Karyomapping and the Asian Screening Array, has demonstrated favorable performance in haplotype analysis for PGT-M[ 8 – 10 ]. The Asian Screening Array (ASA) integrates high-density SNP loci with enhanced coverage of Asian-specific pathogenic variants, thus serving as a specialized array for East and Southeast Asian populations in linkage analysis and detection of population-specific genetic variants[ 11 ]. In recent years, more and more integrated PGT detection protocols which achieves simultaneous SNP linkage analysis, chromosomal aneuploidy screening (PGT-A), and chromosomal structural rearrangement detection (PGT-SR), has been extensively developed and applied[ 12 – 14 ]. However, it still suffers from drawbacks such as high costs, complexity of data analysis and limited detection efficacy in low-coverage regions. Thus, despite the requirement for an additional PGT-A assay, the SNP array-based linkage analysis protocol still retains considerable clinical utility, owing to its high accuracy in monogenic disorder detection and controllable costs. Moreover, the integration of ASA with advanced technologies such as long-read sequencing and single sperm haplotyping has opened new avenues for addressing complex scenarios in PGT, such as de novo pathogenic variants and lack of family member samples [ 15 – 17 ]. Long-read sequencing represented by Oxford nanopore sequencing technologies (ONT, UK) could generates ultra-long genomic reads and thus holds considerable potential for precise breakpoint detection and direct haplotype phasing[ 18 , 19 ]. Meanwhile, the adaptive sampling model of nanopore sequencing can enrich regions of interest by rejecting off-target regions, thereby reducing the generation of redundant data and lowering the detection costs[ 20 ]. Based on the haplotype analysis results derived from single sperm or long-read sequencing, combined with the ASA array results of healthy spouses and embryos, the presence of risk haplotypes in embryos can be determined[ 16 , 21 ]. The purpose of this study is to evaluate the efficiency of ASA-based PGT-M approach using a large clinical cohort, including 377 pedigrees and 1677 embryos with various monogenic diseases or small pathogenic CNVs. We established individualized detection strategy based on pedigree genetic patterns. The performance of the ASA combined with different mutation detection methods was comprehensively evaluated from both technical (detection accuracy and specificity) and clinical (embryo detection efficiency) perspectives. This study aims to validate the feasibility and superiority of ASA-based approach in PGT, providing a standardized, efficient, and reliable technical solution for the clinical prevention of different genetic disorders. 2.Materials and methods 2.1 Patients inclusion This study included all the pedigrees underwent PGT-M preclinical (377 families) and clinical work-up (367 cycles) based on Asian Screening Array at West China Second University Hospital, Sichuan University, from August 2022 to July 2025. The pedigree members including prospective parents and close relatives with known disease status for linkage analysis. Pedigrees with de novo pathogenic variant(s) or lack of positive family members were also included. The present study was approved by the Ethics Committee of West China Second University Hospital of Sichuan University and performed in accordance with the Declaration of Helsinki. Informed consent was obtained from all the participants included in the study. 2.2 Sample collection In preclinical work-up stage, sample types include peripheral blood samples, fetal tissue samples, amniotic fluid cell samples or single sperm cells et al . Genomic DNA were extracted from those samples according to the manufacturer’s instructions (QIGEN, QIAamp DNA Micro Kit). For long-read sequencing, high-molecular weight genomic DNA were extracted and purified using QIAGEN Gentra Puregene Blood Kit. In PGT-M clinial work-up stage, Ovarian stimulation, in vitro fertilization and trophectoderm (TE) biopsy were conducted in the reproductive medical center according to the standard protocol[ 22 , 23 ]. Whole-genome amplification (WGA) were conducted for biopsied TE cells or single sperm cells using the Multiple Displacement Amplification method (MDA, QIAGEN) or the multiple annealing and looping-based amplification cycles (MALBAC, Yikon genomics) [ 24 ]. Whole genome products were purified using DNA Clean-up Kit (CWBIO). 2.3 SNPs detection and linkage analysis based on Asian Screening Array For linkage analysis, SNPs were detected based on Infinium Asian Screening Array. Briefly, DNA samples were hybridized to Infinium Asian Screening Array-24 v1.0 BeadChips for extension and staining after amplified and fragmented. Then, BeadChips were scanned and imaged by iScan System (Illumina). Data was analyzed and SNPs or genotype calling was conducted on ChromGo (Yikon Genomics). Informative SNPs which were heterozygous in the affected/carrier parent and homozygous in the spouse were selected for linkage analysis. At least three informative SNPs proximal and distal to the region of interest were recommended for linkage analysis. Particularly, SNPs inside the microdeletion/microduplication region may provide useful information in some cases. For affected male participants with de novo pathogenic variant, single-sperm cell samples could be applied as phasing references to directly distinguish haplotypes. 2.4 Long read sequencing and direct haplotype phasing by Oxford nanopore technology For cases lacking of phasing references, direct haplotype phasing by long-read sequencing was recommended. The extracted high-molecular-weight genomic DNA of the affected/carrier parent was applied to sequence on GridION (Oxford Nanopore Technologies). The DNA sequencing library was prepared as described in our previous study [ 16 ]. The prepared DNA libraries were sequenced under adaptive sampling model to enrich regions of interest, usually 10 Mb flanking the target genes or regions, by rejecting off-target regions with no additional library preparation. Data processing and analysis workflow referred to our previous study. Usually, A depth of 30× is required for direct haplotye phasing. The mean quality score of base-calling and frequency of nucleotide in reads was also evaluated. The high-risk haplotype linked with pathogenic variant could be directly distinguished after data processing. 2.5 Sanger sequencing validation Targeted PCR amplification and Sanger sequencing were conducted on pedigree members and embryos with point mutations as well as small insertions, deletions, and duplications (indels). Specific primers were designed to amplify targeted segments containing mutation sites (Primer 5.0 software) and synthesized (TsingkeBiotechnologyCo., Ltd.). PCR amplifications were performed on a 96 Well Thermal Cycler Veriti DX (Life Technologies) with suitable PCR conditions. Subsequent Sanger sequencing was performed and data was analyzed using ChromasPro software. 2.6 Repeat-Primed PCR and fragment length analysis for repeat expansion disorders For cases with abnormal expansion of trinucleotide repeats in HTT, ATXN1 , ATXN2 , ATXN3 and FMR1 genes in this study, Repeat-Primed PCR (RP-PCR) combined with downstream size separation and analysis was conducted for direct expansion detection[ 25 , 26 ]. Briefly, a fluorescently labeled upstream primer, a universal primer and a tail primer that includes repeat sequences were used to amplify repeats of varying sizes by PCR. Then, the amplified DNA fragments were separated and analyzed using capillary electrophoresis on ABI 3500 Dx Generic Analyzer. Data was viewed and processed on GeneMapper 6 to calculate the numbers of trinucleotide repeats for each sample. 2.7 Gap-PCR validation for common large deletional mutations of α-globin gene cluster For deletional alpha-thalassemia cases such as the Southeast Asian type (-- SEA ), the Thai type (-- THAI ), -α 3.7 and -α 4.2 , Gap-PCR analysis was needed for direct mutation detection[ 27 , 28 ]. In our study, 8 pairs of primer named P1-F/R P2-F/R to P8-F/R flanking or within the deletion region were applied for gap-PCR. Thus, embryos carrying deletion-type mutations could be distinguished from normal or carrier embryos via gap-PCR combined with agarose gel electrophoresis. 2.8 PCR-restriction fragment length polymorphism (PCR-RFLP) to identify homozygous deletion of exon 7 or 8 in SMN1 Owing to the presence of the SMN2 gene, which is highly homologous to the SMN1 gene, accurate diagnosis of exon 7/8 deletions in the SMN1 gene requires first conducting differential diagnosis between the SMN1 and SMN2 genes. For the differentiation of exon 7 between the two genes, a specific primer pair (G1-F/R) was used to introduce a mismatched site into exon 7 of the SMN2 gene through PCR amplification, which resulted in the formation of a specific DraI restriction enzyme site in the PCR product. As for exon 8, direct PCR amplification was performed using the G2-F/R primer pair to amplify the inherent DdeI restriction enzyme site within exon 8 of the SMN2 gene. Subsequent restriction enzyme digestion of the product enabled the differentiation of exon 7/8 between SMN1 and SMN2 . A high-resolution agarose (MetaPhor Agrose, Lonza Bioscience) was adopted for agarose gel electrophoresis. 2.9 Copy number variation (CNVs) analysis In our study, embryos were performed low-depth whole-genome sequencing on Illumina platform to fulfill prospective chromosome analysis. DNA sequencing libraries of both MALBAC and MDA products were prepared and sequenced with no modifications as previously described [ 29 ]. Data analysis was conducted on the localized platform of ChromGO (Yikon Genomics). For participants with positive results from initial linkage analysis and direct mutation analysis, subsequent copy number variation analysis can be omitted. 3.Results 3.1 Overall information of PGT-M preclinical work-up A total of 377 families that underwent preclinical work-up for PGT-M using the Asian Screening Array were included in this study, 34 families of which received PGT-M for two genes concurrently. The mean age was 31.4 and 33.2 years for female and male participants, respectively. In total, 150 distinct genes and 8 pathogenic copy number variations (CNVs) were involved in this PGT-M testing (see supplementary materials). The most frequently tested gene within this dataset was GJB2 , with 45 cases accounting for 10.9% of the total enrolled. Next in frequency were the HBA1/2 (31 cases), PKD1 (31 cases), DMD (25 cases) and HBB (25 cases) genes. Among them, cases of thalassemia, including both α-thalassemia and β-thalassemia, account for as high as 13.6% of the total cases. Other common genes include NF1 , SMN1 , ABCD1 , G6PD , BRCA1 , EXT2 , F8 , HTT and PKD2 (Fig. 1 A). It is worth noting that the top two CNV Syndromes involved are X-linked ichthyosis (XLI) and DiGeorge syndrome, with deletion in regions of Xp22.31 and 22q11.21, respectively. In addition, cases involving other relatively rare genes or regions also account for nearly half of the total, which indicates that rare genetic disorders constitute an extremely large and clinically important group for PGT-M. Among all cases, autosomal recessive (AR) inheritance accounts for the largest proportion, reaching 48% (Fig. 1 B). Then, cases of autosomal dominant (AD) inheritance account for 30%, with the ratio of male patients to female patients being 1.34:1 (71/53). Cases of X-linked (XL) inheritance include DMD (Duchenne Muscular Dystrophy, 25 cases), ABCD1 (associated with adrenoleukodystrophy, 6 cases), G6PD (associated with G6PD deficiency, 6 cases), F8 (associated with Hemophilia A, 4 cases) and other conditions, most of which are X-linked recessive. In addition, a total of 18 cases with microdeletion/microduplication (MD/MD) was involved in this study to evaluate the feasibility of the PGT strategy based on linkage analysis with the ASA for small CNVs. 3.2 Genetic diagnosis for different inherited disorders In this study, whole-exome sequencing (WES) confirmed the genetic diagnosis in 243 cases, accounting for approximately 61% of the total cases and 89.5% of those with autosomal dominant inheritance (Fig. 1 C and Fig. 1 D). Additionally, 15% of at-risk couples (ARCs) are detected when both phenotypically normal partners are found to carry a pathogenic or likely pathogenic (P/LP) variant in the same autosomal recessive gene, or when females carry X-linked variants, through expanded carrier screening (ECS) or carrier screening based on WES. The remaining cases were diagnosed via conventional genetic testing methods, including Gap-PCR/PCR-Reverse Dot Blot (PCR-RDB) for thalassemia (12%), PCR and capillary electrophoresis for dynamic mutation genes testing (3%), multiplex ligation-dependent probe amplification (MLPA) testing for Duchenne/Becker muscular dystrophy (DMD/BMD) (5%) and Spinal Muscular Atrophy (SMA). Moreover, cases involving microdeletions or microduplications were diagnosed via copy number variation (CNV) testing based on Chromosomal Microarray Analysis (CMA) or next-generation sequencing (NGS). 3.3 PGT strategy for different genetic disorders In our study, we performed linkage analysis using SNPs detected by the ASA for different genetic disorders (Table 1 ). For most of the cases, the number of SNPs available for linkage analysis in the upstream and downstream regions of target genes/regions is sufficient. However, for a subset of genes such as HBA1/HBA2 , NF1, SMN1 or genes located on the X chromosome (e.g., F8 , DMD, ABCD1 ), insufficient SNPs or recombination events in the target genomic regions may lead to the failure of linkage analysis. Direct mutation detection for embryos is therefore particularly crucial as a complementary approach to linkage analysis. Table 1 PGT strategy for microdeletions or microduplications and other genetic disorders. Types Regions/genes Number of Cases Related CNV Syndromes/Regions Sizes/Mutation sites PGT strategy* Microdeletion/ Microduplication Xp22.31 5 X-linked ichthyosis (XLI) 0.79Mb/1.68Mb ASA/ PGT-A 22q11.21 4 22q11 deletion syndrome (Velocardiofacial/DiGeorge syndrome) 3.15Mb/2.18Mb 16p11.2 2 16p11.2 recurrent region (proximal, BP4-BP5) (includes TBX6) 0.22Mb/0.6Mb 17q12 2 17q12 recurrent (RCAD syndrome) region (includes HNF1B) 1.38Mb/1.48Mb 1q21.1q21.2 2 1q21.1 recurrent region (distal, BP3-BP4) (includes GJA5) 3.54Mb 2q13 1 2q13 recurrent region (proximal) (includes NPHP1) 0.12Mb Xp22.2p22.12 1 N/A 4.51Mb Xp22.33 1 Leri-Weill dyschondrostosis (LWD) - SHOX deletion 2.36Mb trinucleotide repeat expansions HTT 4 Huntington disease expanded CAG/CGG repeats ASA/ RP-PCR/ PGT-A ATXN1 3 Spinocerebellar ataxia 1 ATXN3 2 Spinocerebellar Ataxia Type 3 FMR1 2 Fragile X syndrome ATXN2 1 Spinocerebellar ataxia 2 deletional alpha-thalassemia HBA1/2 33 Thalassemias, alpha- -- SEA , -α 3.7 , -α 4.2 ASA/Gap/ PGT-A special genes SMN1 8 Spinal muscular atrophy Exon 7/8 del ASA/ PCR-RFLP/ PGT-A *RP-PCR: repeat-primed PCR and capillary electrophoresis; PCR-RFLP: PCR-restriction fragment length polymorphism. For cases with deletional alpha-thalassemia such as -- SEA , -α3.7 and -α4.2, gap-PCR analysis for all the embryos was conducted and deletion-carrying embryos can be directly identified via agarose gel electrophoresis ( Figure S1 and Figure S2A-B ). The gap-PCR results for all the 99 embryos from 20 PGT-M cycles were not contradictory to those of linkage analysis, and 50 embryos were selected as suitable candidates for transfer. For the SMN1 gene, no usable SNPs were available within the 1 Mb upstream of the gene for linkage analysis since no probes were designed within this region. Therefore, we additionally employed PCR-restriction fragment length polymorphism (PCR-RFLP) to further confirm whether homozygous deletions of exon 7 or 8 were present in the embryo samples ( Figure S3A-B ). No cases inconsistent with the linkage analysis results have been identified. In addition, repeat-primed PCR (RP-PCR) and fragment length analysis was conducted for cases with repeat expansion disorders (related genes like ATXN1 , ATXN2 , ATXN3 , FMR1 , HTT ). Combining linkage analysis and direct expansion mutation detection enabled accurate diagnosis of the carrier status of each embryo. Among the cases involving trinucleotide repeat expansions, 24 out of 65 embryos from 12 PGT-M cycles were eligible for transfer. 3.4 PGT strategy and outcomes for de novo pathogenic variant(s) In conventional PGT-M, linkage analysis typically relies on positive family members. However, for cases involving de novo variants or lack of family members, we perform haplotype analysis directly using single spermatozoa, or construct haplotypes for carriers via long-read sequencing (LRS). Here, we enrolled 18 families with different de novo variants in 14 genes including NF1 (neurofibromatosis, 3 cases), FBN1 (Marfan syndrome, 2 cases), PKD1 (polycystic kidney disease 1, 2 cases) and others (Table 2 ). Haplotypes were successfully constructed for all cases, enabling the accurate differentiation between the high-risk haplotype and low-risk haplotype in the affected individual or mutation carriers. However, for the 5 families using the single sperm haplotype methodology, more than 30 single spermatozoa were isolated per family and the single spermatozoa successfully validated for haplotype construction exhibited a relatively low detection rate and accuracy following analysis on the ASA ( Figure S4A-B ). For the other 13 families, direct haplotype construction was performed for the affected individual using long-read sequencing. Combined with the results of ASA analysis for the couple and embryos, the final SNPs applicable for linkage analysis in PGT-M clinical cycle were identified. Meanwhile, long-read sequencing allows for precise breakpoint detection in deletion cases such as exon46-51 deletion in DMD gene and exon3-47 deletion in FLNA gene ( Figure S5A-B ). Targeted Sanger sequencing for directly mutation detection is also essential for the identification of carrier status for embryos. Here, A total of 53 embryos from 12 PGT-M cycles were included in this study. And 18 non-carrier and euploid embryos were selected for transfer. Table 2 PGT strategy for de novo pathogenic variants or lack of family members. Genes Number of Cases Related diseases Mutation sites PGT strategy* NF1 3 Neurofibromatosis, type 1 c.1062 + 2T > C LRS/ASA/Sanger/PGT-A c.5380C > T SPH/ASA/Sanger/PGT-A c.5546G > A(NM_000267.3) LRS/ASA/Sanger/PGT-A FBN1 2 Marfan syndrome c.4205G > T SPH/ASA/Sanger/PGT-A c.4930C > T(NM_000138.5) LRS/ASA/Sanger/PGT-A PKD1 2 Polycystic kidney disease 1 c.8327_8343dup SPH/ASA/Sanger/PGT-A exon22 del (NM_001009944.3) LRS/ASA/Gap/PGT-A APC 1 Gastric adenocarcinoma and proximal polyposis of the stomach c.3497_3501del (NM_000038.6) LRS/ASA/Sanger/PGT-A BCOR 1 Microphthalmia, syndromic 2 c.1873_1876delinsTTC (NM_017745.6) LRS/ASA/Sanger/PGT-A BRCA2 1 Breast-ovarian cancer, familial, 2 c.3109C > T(NM_000059.4) LRS/ASA/Sanger/PGT-A DMD 1 Duchenne muscular dystrophy exon46-51 del (NM_004006.2) LRS/ASA/PGT-A EXT1 1 Exostoses, multiple, type 1 c.797T > C(NM_000127.3) LRS/ASA/Sanger/PGT-A FGFR1 1 Hartsfield syndrome c.809G > T(NM_145239.3) LRS/ASA/Sanger/PGT-A FLNA 1 Otopalatodigital syndrome exon3-47 del (NM_001456.4) LRS/ASA/PGT-A FOXL2 1 Blepharophimosis, epicanthus inversus, and ptosis, types 1 and 2 c.843_859dup (NM_023067.4) SPH/ASA/Sanger/PGT-A KRT5 1 Epidermolysis bullosa simplex exon7-8 del (NM_000424.4) SPH/ASA/Sanger/PGT-A TP63 1 Limb-mammary syndrome c.1986_2028dup (NM_000053.4) LRS/ASA/Sanger/PGT-A TSC2 1 Tuberous sclerosis-2 c.3377del (NM_000548.5) LRS/ASA/Sanger/PGT-A *LRS: long-read sequencing; ASA:the Asian Screening array; Sanger: targeted Sanger sequencing; SPH: Single sperm haplotyping; Gap: Gap-PCR 3.5 PGT strategy and outcomes for microdeletions or microduplications Due to the limited resolution of conventional PGT for aneuploidy or structural rearrangement (PGT-A/SR) (typically detects > 4 Mb fragments), the PGT strategy based on SNP haplotyping is more applicable for prospective parent with small pathogenic copy number variants. Here, 18 families with microdeletions or microduplications (< 4Mb) were performed SNP haplotyping analysis based on the Asian Screening Array (Table 1 ). Informative SNPs flanking or within the target region were selected for linkage analysis to establish haplotypes of prospective parents. Notably, within the deletion region, SNPs that are inconsistent with the carrier and homozygous in the unaffected spouse can be regarded as informative markers (Fig. 2 A-B). And for tandem duplications, the homozygous SNPs in the unaffected spouse and affected proband within duplication region can be selected for linkage analysis (Fig. 2 C). In PGT clinical work-up, those informative SNPs detected by the ASA can assist in distinguishing the carrier status of embryos. A total of 23 embryo testing cycles were performed for those families with microdeletions or microduplications. After undergoing linkage analysis and CNV detection, 30 embryos out of 98 were ultimately deemed suitable for transfer. Successful pregnancies have been achieved in 8 families as of July 2025. 3.6 Overall chromosomal abnormalities in PGT-M Overall, 1677 embryos obtained from 367 PGT-M cycles were included in this study, with an average of 4–5 embryos retrieved per cycle. A total of 1267 embryos underwent chromosomal abnormality detection. Among these embryos, euploid embryos accounted for 61.16% (775/1267), while embryos with aneuploidy (including whole-chromosome mosaicism) accounted for 23.76% (301/1267), and those with only chromosomal segment abnormalities (including segmental mosaicism) accounted for 14.21% (183/1267) (Fig. 3 A). When analyzing the subset of embryos with numerical chromosomal abnormalities, we found that roughly 37% of them were mosaic for whole chromosomes (111/301). The additional 1% of embryos represented test-failed embryos, which might be attributed to biopsy failure, amplification failure, or detection failure. Additionally, the transfer-eligible embryo rates were 35%, 45%, and 35% for autosomal dominant (AD), autosomal recessive (AR), and X-linked (XL) inheritance patterns, respectively, following linkage analysis and chromosomal abnormality testing (Fig. 3 B). 4.Discussion Although blastocyst trophectoderm biopsy is currently adopted in most PGT-M clinical application, there remains a risk of allele drop-out (ADO) in direct locus-specific testing due to the limited DNA quantity[ 30 , 31 ]. Therefore, indirect haplotype analysis is indispensable for the accurate diagnosis of embryos[ 4 , 32 ]. Genome-wide SNP array- or NGS-based haplotyping strategies have demonstrated more advantages, such as cost-effectiveness, high throughput, and a greater number of informative SNPs, over conventional targeted amplification strategies[ 10 ]. We also demonstrated the applicability of the ASA in the Chinese population for PGT-M in our previous study[ 9 ]. Here, we have summarized the PGT-M cases based on the ASA over the past three years, proposed and analyzed the clinical utility of PGT-M strategies tailored to different genetic disorders, thereby providing insights for a broader range of clinical scenarios. In recent years, PGT technology has brought new hope to families affected by genetic or chromosomal disorders, particularly those carrying rare monogenic mutations or complex chromosomal rearrangements[ 33 ]. With the widespread application of clinical genetic testing methods such as WES and ECS, an increasing number of rare genetic diseases have been diagnosed[ 34 , 35 ]. In our study, genetic diagnoses in more than 76% of cases were confirmed by WES and ECS, highlighting the clinical utility of WES in the diagnosis of genetic disorders and ECS in identifying potential genetic disorders. Regarding the amplification method for TE cells, typically, 5–10 TE cells were subjected to whole-genome amplification (WGA) via either MDA or MALBAC, depending on the mutation type and the complexity of the gene locus[ 36 , 37 ]. Our experience indicates that both methods exhibited comparable performance in detecting SNVs or small indels for most genes. While, MDA can significantly improve the amplification success rate of regions with high GC content and high-repeat sequences. Therefore, for mutations in PKD1 , HBA1/2 , SMN1 and trinucleotide repeat genes, we consistently select MDA for amplification with high amplification yield and long fragment output. For other genetic conditions, during the PGT-M preclinical stage, we first evaluated the efficiency of MALBAC in amplifying and mutations detecting on oral mucosal cells. If MALBAC exhibits insufficient efficiency, MDA amplification is an alternative option, thereby finalizing the amplification strategy for TE cells. And no significant variation was observed in the detection performance of the ASA for MDA versus MALBAC amplification products. Following whole-genome amplification (WGA), the amplified samples underwent both direct locus-specific testing and linkage analysis simultaneously. In our study, we summarized several distinct locus-specific detection methods for different genetic conditions. For SNVs or small indels, target-specific amplification and Sanger sequencing was applied for direct mutation detection of the embryos. When combined with linkage analysis results, ADO still occurs occasionally in direct mutation detection which may be attributed to suboptimal quality of biopsy samples or inefficient WGA or locus-specific amplification. The SMN1 gene represents another special case. Although it cannot distinguish between normal embryos and carrier embryos, PCR-RFLP still serves as a reliable supplementary method for identifying embryos with SMN1 homozygous deletion when valid SNPs are lacking on the ASA. For deletional alpha-thalassemia or large deletion mutations with known breakpoints, gap-PCR combined with agarose gel electrophoresis enable the identification of embryos with homozygous deletion. By employing these distinct mutation validation methods combined with linkage analysis, the two approaches cross-validate each other to ensure the accuracy of embryo detection results. The Asian Screening Array, which harbors approximately 700,000 SNP loci specific to East and Southeast Asian populations, offers a scalable and cost-effective approach for linkage analysis of most genetic variants[ 38 ]. In our study, ASA provided a robust solution for linkage analysis across more than 150 genes and multiple microdeletion regions involved in the research. A sufficient number of valid SNPs were present both upstream, downstream, and within the genes, ensuring the accuracy of linkage analysis, except for genes with special genomic locations, such as SMN1, F8 . We also summarized specialized linkage analysis methodologies for de novo mutations based on single sperm or long-read sequencing. However, the single sperm haplotype methodology is usually labor and cost consuming because of the high technical demand for single sperm selection and validation. Long-read sequencing offers a more optimal strategy attributed to its high accuracy and efficiency in PGT-M haplotype phasing involving de novo mutations. Notably, long-read sequencing allows for precise breakpoint detection in deletion cases, which in turn supports direct mutation detection for embryos. Meanwhile, linkage analysis based on informative SNPs flanking or within the target regions is an effective PGT strategy for couples with small CNVs, including tandem duplications[ 39 , 40 ]. Overall, the PGT methods based on ASA established in this study provides an efficient and feasible technical solution for the clinical application of PGT under different disease types and genetic backgrounds. Although, in comparison with many currently developed comprehensive PGT methods[ 41 – 43 ], the SNP array-based linkage analysis protocol requires an additional detection of chromosomal numerical or structural abnormalities. Nonetheless, this method is characterized by its distinct advantages such as high specificity for monogenic disorder screening, stable technical performance, and cost-effectiveness. In addition, for embryos in which the pathogenic variants have been clearly identified via linkage analysis or direct mutation testing, patients can choose to skip the detection of chromosomal anomalies, thereby reducing the overall testing costs. 5.Conclusion In conclusion, based on comprehensive PGT-M datasets accumulated over three years in our center (involving 377 pedigrees and 1677 embryos), our findings systematically illustrate the performance of the ASA-based PGT workflow that synergizes linkage analysis, direct mutation testing, and chromosomal CNV screening. For diverse genetic conditions, we developed customized PGT testing strategies and assessed their clinical performance. Our results provided data support and practical references for the individualized clinical application of PGT-M technology. Declarations Ethics approval and consent to participate The present study was approved by the Ethics Committee of West China Second Hospital of Sichuan University. All patients provided written informed consent. Availability of data and materials: The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation. Competing interests The authors declare that they have no conflicts of interest in this article. Funding This work was supported by National Key Research and Development Plan (2022YFC2703302). Authors' contributions Cuiting Peng: Conceptualization, Data curation and original draft writing; Jun Ren: Validation and Methodology; Fan Zhou: Supervision, Validation; Han Chen, Hong Yang, Yutong Li and Yuezhi Keqie: Data curation, Formal analysis and Validation; Xu Zhao and Zhushu Liu: sample collection and data visualization; Ting Hu and Xuemei Zhang: Supervision; Taoli Ding and Ji Yang: Software and TGS data analysis. Shan Luo and Wei Fan: embryo biopsy; Xinlian Chen and Shanling Liu: Funding acquisition and review & editing. Acknowledgements We thank all the participants for their cooperation and participation. We thank the embryology team at the Center of Reproductive Medicine for help with sample preparation. We also thank Mengnan Huang and Teng Zhang from Yikon Genomics for technical help for data analysis. References De Rycke M, Berckmoes V. Preimplantation genetic testing for monogenic disorders. Genes. 2020;11:871. Handyside AH, Kontogianni EH, Hardy K, et al. Pregnancies from biopsied human preimplantation embryos sexed by y-specific DNA amplification. Nature. 1990;344:768–70. Poulton A, Menezes M, Hardy T et al. Clinical outcomes following preimplantation genetic testing for monogenic conditions: A systematic review of observational studies. Am J Obstet Gynecol, 2024. Group EP-MW, Carvalho F, Moutou C et al. , . Eshre pgt consortium good practice recommendations for the detection of monogenic disorders. Human reproduction open, 2020, 2020: hoaa018 Chen S, Yin X, Zhang S, et al. 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Allele dropout in sequential pcr and fish analysis of single cells (cell recycling). J Assist Reprod Genet. 1996;13:115–24. Wilton L, Thornhill A, Traeger-Synodinos J, et al. The causes of misdiagnosis and adverse outcomes in pgd. Hum Reprod. 2009;24:1221–8. Treff NR, Zimmerman RS. Advances in preimplantation genetic testing for monogenic disease and aneuploidy. Annu Rev Genom Hum Genet. 2017;18:189–200. Liu D, Chen C, Huang Q, et al. Preimplantation genetic testing for complex chromosomal rearrangements: Clinical outcomes and potential risk factors. Front Genet. 2024;15:1401549. Grody WW, Thompson BH, Gregg AR, et al. Acmg position statement on prenatal/preconception expanded carrier screening. Obstet Gynecol Surv. 2013;68:785–7. Lu J, Chen J, Mei L et al. Clinical application of expanded carrier screening based on next-generation sequencing in the chinese population. Arch Gynecol Obstet, 2025, 1–9. Zhou X, Xu Y, Zhu L, et al. Comparison of multiple displacement amplification (mda) and multiple annealing and looping-based amplification cycles (malbac) in limited DNA sequencing based on tube and droplet. Micromachines. 2020;11:645. Chen M, Song P, Zou D, et al. Comparison of multiple displacement amplification (mda) and multiple annealing and looping-based amplification cycles (malbac) in single-cell sequencing. PLoS ONE. 2014;9:e114520. Zhang S, Zhao D, Zhang J, et al. Basephasing: A highly efficient approach for preimplantation genetic haplotyping in clinical application of balanced translocation carriers. BMC Med Genomics. 2019;12:52. Hu X, Wang W, Luo K, JingZhang. YiWan, ZhenxingHe, WenbinZhang, ShuopingYang, LanlinTan, QinLi, WenZhang, QianjunGong, FeiLu, GuangxiuTan, Yue-QiuLin, GeDu, Juan. Extended application of pgt-m strategies for small pathogenic cnvs. J Assist Reprod Genet. 2024;41:739–50. Peng C, Chen H, Zhou F, et al. Molecular diagnosis and preimplantation genetic testing for chromosome 1q21. 1 recurrent microduplication. Front Genet. 2025;16:1522406. Bao X, Yang Y, Niu W, et al. Comprehensive analysis of chromosome abnormalities by chromosome conformation based karyotyping (c-moka) in patients with conception failure and pregnancy loss. Clin Chim Acta. 2025;567:120089. Xiong L, Huang L, Tian F, et al. Bayesian model for accurate marsala (mutated allele revealed by sequencing with aneuploidy and linkage analyses). J Assist Reprod Genet. 2019;36:1263–71. Xie P, Pang R, Zeng L et al. , . Accurate identification of abnormal ploidy using an artificial intelligence model in preimplantation genetic testing. Human Reproduction Open, 2025, 2025: hoaf054 Supplementary Files Testedgenesandregions.xlsx Supplementary materials: Tested genes and regions FigureS1.tif FigureS2.tif FigureS3.tif FigureS4.tif FigureS5.tif Supp.FigureLegends.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9047233","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":607092567,"identity":"48537e02-e410-44e7-9869-84be6a67301d","order_by":0,"name":"Cuiting 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Hospital","correspondingAuthor":false,"prefix":"","firstName":"Shanling","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2026-03-06 07:14:36","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9047233/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9047233/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104996088,"identity":"7727b251-cc08-4831-9955-04f2ee5c0091","added_by":"auto","created_at":"2026-03-19 16:11:25","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":268861,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eOverall information of PGT-M preclinical work-up.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA\u003c/strong\u003e. The top 20 genes most frequently tested in PGT-M cases. The number of detection cases is labeled on the bar chart for each gene. \u003cstrong\u003eB\u003c/strong\u003e. The cases number and ratio for different inheritance patterns. AD: autosomal dominant; AR: autosomal dominant; XL: X-linked inheritance patterns including XLR, XLD and XL; MD/MD: microdeletion/microduplication. Genetic diagnosis method and the ratio for all cases (\u003cstrong\u003eC) \u003c/strong\u003eand for\u003cstrong\u003e \u003c/strong\u003eautosomal dominant cases (\u003cstrong\u003eD\u003c/strong\u003e). WES: cases diagnosed by whole-exome sequencing; ECS: cases diagnosed by carrier screening; Cases diagnosed via conventional genetic testing methods for thalassemia gene including Gap-PCR and PCR-RDB, MLPA for Duchenne/Becker muscular dystrophy (DMD/BMD), PCR and capillary electrophoresis for dynamic mutation genes \u003cem\u003eet.al\u003c/em\u003e. Others represent cases diagnosed by CMA, low-depth high throughput sequencing and so on.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-9047233/v1/f9d804aeedcacc3b29f64173.png"},{"id":104996163,"identity":"d83c7c43-4ddb-4389-b636-7ed3fdbbc921","added_by":"auto","created_at":"2026-03-19 16:11:31","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1272040,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHaplotyping analysis for microdeletions (B) and tandem microduplications (C).\u003c/strong\u003e \u003cstrong\u003eA\u003c/strong\u003e. Pedigree chat with microdeletions or tandem microduplications in Mother (І-1) and proband (Ⅱ-1). \u003cstrong\u003eB\u003c/strong\u003e. F0/F1 represents the two haplotypes for healthy spouse; M0 and M1 represents the low-risk and high-risk haplotypes for the carrier respectively. The SNPs in the green dashed box represented the informative SNPs within the deletion region for embryo haplotyping analysis. \u003cstrong\u003eC\u003c/strong\u003e. The chart depicts the distribution pattern of heterozygous SNP (A/G detected by ASA) in carriers located within the duplication region. Only the homozygous SNPs in the unaffected spouse and affected proband within duplication region can be selected for linkage analysis (green dashed box).\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-9047233/v1/fdce3e8fc225914d0669a46d.png"},{"id":104996165,"identity":"30a6d0ee-f9ed-4f1c-ba45-567661201922","added_by":"auto","created_at":"2026-03-19 16:11:32","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1394687,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eOverall chromosomal abnormalities in PGT-M clinical work-up (A) and transfer-eligible embryos for different inheritance patterns (B).\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA\u003c/strong\u003e. Euploid embryos accounted for 76% of the total. Aneuploid embryos accounted for 24% of the total, of which aneuploid embryos and embryos with whole-chromosome mosaicism accounted for 63% and 37%, respectively. Those with only chromosomal segment abnormalities (including segmental mosaicism) accounted for 14.21%. The additional 1% of embryos represented test-failed embryos. \u003cstrong\u003eB\u003c/strong\u003e. The whole obtained embryos (numbers are labeled next to the bars) and transfer-eligible embryos (dark purple) for different inheritance patterns.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-9047233/v1/dcd222e54624ab4990fceb13.png"},{"id":108007276,"identity":"79b72662-e61c-49bb-874d-a66037e34477","added_by":"auto","created_at":"2026-04-28 12:59:18","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3164799,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9047233/v1/9fd2efbc-ed6f-4aef-863d-79b0583aa1cf.pdf"},{"id":104996045,"identity":"169ae384-81cf-4b6b-90b9-4299eec8c227","added_by":"auto","created_at":"2026-03-19 16:11:17","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":12941,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary materials:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTested genes and regions\u003c/p\u003e","description":"","filename":"Testedgenesandregions.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-9047233/v1/44cd203b305769ea5800daae.xlsx"},{"id":104996160,"identity":"c8080887-621c-4f33-963a-c80f77687144","added_by":"auto","created_at":"2026-03-19 16:11:31","extension":"tif","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":285764,"visible":true,"origin":"","legend":"","description":"","filename":"FigureS1.tif","url":"https://assets-eu.researchsquare.com/files/rs-9047233/v1/8d81174c89c812a660f7143e.tif"},{"id":104996072,"identity":"baac07e9-34af-4987-934e-6ec8a8aee01f","added_by":"auto","created_at":"2026-03-19 16:11:20","extension":"tif","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":3342684,"visible":true,"origin":"","legend":"","description":"","filename":"FigureS2.tif","url":"https://assets-eu.researchsquare.com/files/rs-9047233/v1/563469cbd616667272fd9605.tif"},{"id":104996084,"identity":"0e65749b-a727-4b74-9e1b-32c0029df943","added_by":"auto","created_at":"2026-03-19 16:11:24","extension":"tif","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":3371248,"visible":true,"origin":"","legend":"","description":"","filename":"FigureS3.tif","url":"https://assets-eu.researchsquare.com/files/rs-9047233/v1/ce80599293e3d880c96b533e.tif"},{"id":104996158,"identity":"5c88f625-6891-449d-a47c-923eac8463cd","added_by":"auto","created_at":"2026-03-19 16:11:31","extension":"tif","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":1541564,"visible":true,"origin":"","legend":"","description":"","filename":"FigureS4.tif","url":"https://assets-eu.researchsquare.com/files/rs-9047233/v1/1aae7bc8079e1b661e6d6954.tif"},{"id":104996174,"identity":"5ce19832-399a-4cb3-acfc-e841a3eeece5","added_by":"auto","created_at":"2026-03-19 16:11:33","extension":"tif","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":3408620,"visible":true,"origin":"","legend":"","description":"","filename":"FigureS5.tif","url":"https://assets-eu.researchsquare.com/files/rs-9047233/v1/744e85e8629f30c77d27a5c3.tif"},{"id":104996043,"identity":"809f85e3-8b37-47ec-ad69-dc2900f78c82","added_by":"auto","created_at":"2026-03-19 16:11:17","extension":"docx","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":15369,"visible":true,"origin":"","legend":"","description":"","filename":"Supp.FigureLegends.docx","url":"https://assets-eu.researchsquare.com/files/rs-9047233/v1/0d4011bbb2b09d58f858b077.docx"}],"financialInterests":"","formattedTitle":"Clinical Application of an Asian Screening Array-Based Preimplantation Genetic Testing Workflow for Various Genetic Disorders","fulltext":[{"header":"1.Introduction","content":"\u003cp\u003ePreimplantation Genetic Testing (PGT) is an innovative approach designed to screen for and diagnose genetic abnormalities in early embryos prior to transfer[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. It not only provides a reliable avenue for couples at high risk of genetic disorders to have healthy children but also optimizes the outcomes of assisted reproductive therapies[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. With the increasing global prevalence of genetic disorders, the demand for accurate and efficient PGT methodologies has become increasingly urgent[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWith the continuous development and innovation of detection technologies, such as next generation sequencing (NGS), single-nucleotide polymorphism (SNP) array, long-read sequencing, the detection efficiency and application scope of PGT have been significantly enhanced[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. As for preimplantation genetic testing for monogenic defects (PGT-M), haplotyping analysis combined with direct mutation detection has proven to be an effective strategy to improve test accuracy[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Genome-wide SNP array represented by Karyomapping and the Asian Screening Array, has demonstrated favorable performance in haplotype analysis for PGT-M[\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The Asian Screening Array (ASA) integrates high-density SNP loci with enhanced coverage of Asian-specific pathogenic variants, thus serving as a specialized array for East and Southeast Asian populations in linkage analysis and detection of population-specific genetic variants[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn recent years, more and more integrated PGT detection protocols which achieves simultaneous SNP linkage analysis, chromosomal aneuploidy screening (PGT-A), and chromosomal structural rearrangement detection (PGT-SR), has been extensively developed and applied[\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. However, it still suffers from drawbacks such as high costs, complexity of data analysis and limited detection efficacy in low-coverage regions. Thus, despite the requirement for an additional PGT-A assay, the SNP array-based linkage analysis protocol still retains considerable clinical utility, owing to its high accuracy in monogenic disorder detection and controllable costs. Moreover, the integration of ASA with advanced technologies such as long-read sequencing and single sperm haplotyping has opened new avenues for addressing complex scenarios in PGT, such as de novo pathogenic variants and lack of family member samples [\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eLong-read sequencing represented by Oxford nanopore sequencing technologies (ONT, UK) could generates ultra-long genomic reads and thus holds considerable potential for precise breakpoint detection and direct haplotype phasing[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Meanwhile, the adaptive sampling model of nanopore sequencing can enrich regions of interest by rejecting off-target regions, thereby reducing the generation of redundant data and lowering the detection costs[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Based on the haplotype analysis results derived from single sperm or long-read sequencing, combined with the ASA array results of healthy spouses and embryos, the presence of risk haplotypes in embryos can be determined[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe purpose of this study is to evaluate the efficiency of ASA-based PGT-M approach using a large clinical cohort, including 377 pedigrees and 1677 embryos with various monogenic diseases or small pathogenic CNVs. We established individualized detection strategy based on pedigree genetic patterns. The performance of the ASA combined with different mutation detection methods was comprehensively evaluated from both technical (detection accuracy and specificity) and clinical (embryo detection efficiency) perspectives. This study aims to validate the feasibility and superiority of ASA-based approach in PGT, providing a standardized, efficient, and reliable technical solution for the clinical prevention of different genetic disorders.\u003c/p\u003e"},{"header":"2.Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Patients inclusion\u003c/h2\u003e \u003cp\u003eThis study included all the pedigrees underwent PGT-M preclinical (377 families) and clinical work-up (367 cycles) based on Asian Screening Array at West China Second University Hospital, Sichuan University, from August 2022 to July 2025. The pedigree members including prospective parents and close relatives with known disease status for linkage analysis. Pedigrees with \u003cem\u003ede novo\u003c/em\u003e pathogenic variant(s) or lack of positive family members were also included. The present study was approved by the Ethics Committee of West China Second University Hospital of Sichuan University and performed in accordance with the Declaration of Helsinki. Informed consent was obtained from all the participants included in the study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Sample collection\u003c/h2\u003e \u003cp\u003eIn preclinical work-up stage, sample types include peripheral blood samples, fetal tissue samples, amniotic fluid cell samples or single sperm cells \u003cem\u003eet al\u003c/em\u003e. Genomic DNA were extracted from those samples according to the manufacturer\u0026rsquo;s instructions (QIGEN, QIAamp DNA Micro Kit). For long-read sequencing, high-molecular weight genomic DNA were extracted and purified using QIAGEN Gentra Puregene Blood Kit. In PGT-M clinial work-up stage, Ovarian stimulation, in vitro fertilization and trophectoderm (TE) biopsy were conducted in the reproductive medical center according to the standard protocol[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Whole-genome amplification (WGA) were conducted for biopsied TE cells or single sperm cells using the Multiple Displacement Amplification method (MDA, QIAGEN) or the multiple annealing and looping-based amplification cycles (MALBAC, Yikon genomics) [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Whole genome products were purified using DNA Clean-up Kit (CWBIO).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 SNPs detection and linkage analysis based on Asian Screening Array\u003c/h2\u003e \u003cp\u003eFor linkage analysis, SNPs were detected based on Infinium Asian Screening Array. Briefly, DNA samples were hybridized to Infinium Asian Screening Array-24 v1.0 BeadChips for extension and staining after amplified and fragmented. Then, BeadChips were scanned and imaged by iScan System (Illumina). Data was analyzed and SNPs or genotype calling was conducted on ChromGo (Yikon Genomics). Informative SNPs which were heterozygous in the affected/carrier parent and homozygous in the spouse were selected for linkage analysis. At least three informative SNPs proximal and distal to the region of interest were recommended for linkage analysis. Particularly, SNPs inside the microdeletion/microduplication region may provide useful information in some cases. For affected male participants with \u003cem\u003ede novo\u003c/em\u003e pathogenic variant, single-sperm cell samples could be applied as phasing references to directly distinguish haplotypes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Long read sequencing and direct haplotype phasing by Oxford nanopore technology\u003c/h2\u003e \u003cp\u003eFor cases lacking of phasing references, direct haplotype phasing by long-read sequencing was recommended. The extracted high-molecular-weight genomic DNA of the affected/carrier parent was applied to sequence on GridION (Oxford Nanopore Technologies). The DNA sequencing library was prepared as described in our previous study [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The prepared DNA libraries were sequenced under adaptive sampling model to enrich regions of interest, usually 10 Mb flanking the target genes or regions, by rejecting off-target regions with no additional library preparation. Data processing and analysis workflow referred to our previous study. Usually, A depth of 30\u0026times; is required for direct haplotye phasing. The mean quality score of base-calling and frequency of nucleotide in reads was also evaluated. The high-risk haplotype linked with pathogenic variant could be directly distinguished after data processing.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Sanger sequencing validation\u003c/h2\u003e \u003cp\u003eTargeted PCR amplification and Sanger sequencing were conducted on pedigree members and embryos with point mutations as well as small insertions, deletions, and duplications (indels). Specific primers were designed to amplify targeted segments containing mutation sites (Primer 5.0 software) and synthesized (TsingkeBiotechnologyCo., Ltd.). PCR amplifications were performed on a 96 Well Thermal Cycler Veriti DX (Life Technologies) with suitable PCR conditions. Subsequent Sanger sequencing was performed and data was analyzed using ChromasPro software.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Repeat-Primed PCR and fragment length analysis for repeat expansion disorders\u003c/h2\u003e \u003cp\u003eFor cases with abnormal expansion of trinucleotide repeats in \u003cem\u003eHTT, ATXN1\u003c/em\u003e, \u003cem\u003eATXN2\u003c/em\u003e, \u003cem\u003eATXN3\u003c/em\u003e and \u003cem\u003eFMR1\u003c/em\u003e genes in this study, Repeat-Primed PCR (RP-PCR) combined with downstream size separation and analysis was conducted for direct expansion detection[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Briefly, a fluorescently labeled upstream primer, a universal primer and a tail primer that includes repeat sequences were used to amplify repeats of varying sizes by PCR. Then, the amplified DNA fragments were separated and analyzed using capillary electrophoresis on ABI 3500 Dx Generic Analyzer. Data was viewed and processed on GeneMapper 6 to calculate the numbers of trinucleotide repeats for each sample.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.7 Gap-PCR validation for common large deletional mutations of α-globin gene cluster\u003c/h2\u003e \u003cp\u003eFor deletional alpha-thalassemia cases such as the Southeast Asian type (--\u003csup\u003eSEA\u003c/sup\u003e), the Thai type (--\u003csup\u003eTHAI\u003c/sup\u003e), -α\u003csup\u003e3.7\u003c/sup\u003e and -α\u003csup\u003e4.2\u003c/sup\u003e, Gap-PCR analysis was needed for direct mutation detection[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. In our study, 8 pairs of primer named P1-F/R P2-F/R to P8-F/R flanking or within the deletion region were applied for gap-PCR. Thus, embryos carrying deletion-type mutations could be distinguished from normal or carrier embryos via gap-PCR combined with agarose gel electrophoresis.\u003c/p\u003e \u003cp\u003e \u003cb\u003e2.8 PCR-restriction fragment length polymorphism (PCR-RFLP) to identify homozygous deletion of exon 7 or 8 in SMN1\u003c/b\u003e \u003c/p\u003e \u003cp\u003eOwing to the presence of the \u003cem\u003eSMN2\u003c/em\u003e gene, which is highly homologous to the \u003cem\u003eSMN1\u003c/em\u003e gene, accurate diagnosis of exon 7/8 deletions in the \u003cem\u003eSMN1\u003c/em\u003e gene requires first conducting differential diagnosis between the \u003cem\u003eSMN1\u003c/em\u003e and \u003cem\u003eSMN2\u003c/em\u003e genes. For the differentiation of exon 7 between the two genes, a specific primer pair (G1-F/R) was used to introduce a mismatched site into exon 7 of the \u003cem\u003eSMN2\u003c/em\u003e gene through PCR amplification, which resulted in the formation of a specific DraI restriction enzyme site in the PCR product. As for exon 8, direct PCR amplification was performed using the G2-F/R primer pair to amplify the inherent DdeI restriction enzyme site within exon 8 of the \u003cem\u003eSMN2\u003c/em\u003e gene. Subsequent restriction enzyme digestion of the product enabled the differentiation of exon 7/8 between \u003cem\u003eSMN1\u003c/em\u003e and \u003cem\u003eSMN2\u003c/em\u003e. A high-resolution agarose (MetaPhor Agrose, Lonza Bioscience) was adopted for agarose gel electrophoresis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.9 Copy number variation (CNVs) analysis\u003c/h2\u003e \u003cp\u003eIn our study, embryos were performed low-depth whole-genome sequencing on Illumina platform to fulfill prospective chromosome analysis. DNA sequencing libraries of both MALBAC and MDA products were prepared and sequenced with no modifications as previously described [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Data analysis was conducted on the localized platform of ChromGO (Yikon Genomics). For participants with positive results from initial linkage analysis and direct mutation analysis, subsequent copy number variation analysis can be omitted.\u003c/p\u003e \u003c/div\u003e"},{"header":"3.Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Overall information of PGT-M preclinical work-up\u003c/h2\u003e \u003cp\u003eA total of 377 families that underwent preclinical work-up for PGT-M using the Asian Screening Array were included in this study, 34 families of which received PGT-M for two genes concurrently. The mean age was 31.4 and 33.2 years for female and male participants, respectively. In total, 150 distinct genes and 8 pathogenic copy number variations (CNVs) were involved in this PGT-M testing (see supplementary materials). The most frequently tested gene within this dataset was \u003cem\u003eGJB2\u003c/em\u003e, with 45 cases accounting for 10.9% of the total enrolled. Next in frequency were the \u003cem\u003eHBA1/2\u003c/em\u003e (31 cases), \u003cem\u003ePKD1\u003c/em\u003e (31 cases), \u003cem\u003eDMD\u003c/em\u003e (25 cases) and \u003cem\u003eHBB\u003c/em\u003e (25 cases) genes. Among them, cases of thalassemia, including both α-thalassemia and β-thalassemia, account for as high as 13.6% of the total cases. Other common genes include \u003cem\u003eNF1\u003c/em\u003e, \u003cem\u003eSMN1\u003c/em\u003e, \u003cem\u003eABCD1\u003c/em\u003e, \u003cem\u003eG6PD\u003c/em\u003e, \u003cem\u003eBRCA1\u003c/em\u003e, \u003cem\u003eEXT2\u003c/em\u003e, \u003cem\u003eF8\u003c/em\u003e, \u003cem\u003eHTT\u003c/em\u003e and \u003cem\u003ePKD2\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). It is worth noting that the top two CNV Syndromes involved are X-linked ichthyosis (XLI) and DiGeorge syndrome, with deletion in regions of Xp22.31 and 22q11.21, respectively. In addition, cases involving other relatively rare genes or regions also account for nearly half of the total, which indicates that rare genetic disorders constitute an extremely large and clinically important group for PGT-M.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAmong all cases, autosomal recessive (AR) inheritance accounts for the largest proportion, reaching 48% (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). Then, cases of autosomal dominant (AD) inheritance account for 30%, with the ratio of male patients to female patients being 1.34:1 (71/53). Cases of X-linked (XL) inheritance include \u003cem\u003eDMD\u003c/em\u003e (Duchenne Muscular Dystrophy, 25 cases), \u003cem\u003eABCD1\u003c/em\u003e (associated with adrenoleukodystrophy, 6 cases), \u003cem\u003eG6PD\u003c/em\u003e (associated with G6PD deficiency, 6 cases), \u003cem\u003eF8\u003c/em\u003e (associated with Hemophilia A, 4 cases) and other conditions, most of which are X-linked recessive. In addition, a total of 18 cases with microdeletion/microduplication (MD/MD) was involved in this study to evaluate the feasibility of the PGT strategy based on linkage analysis with the ASA for small CNVs.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Genetic diagnosis for different inherited disorders\u003c/h2\u003e \u003cp\u003eIn this study, whole-exome sequencing (WES) confirmed the genetic diagnosis in 243 cases, accounting for approximately 61% of the total cases and 89.5% of those with autosomal dominant inheritance (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC and Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD). Additionally, 15% of at-risk couples (ARCs) are detected when both phenotypically normal partners are found to carry a pathogenic or likely pathogenic (P/LP) variant in the same autosomal recessive gene, or when females carry X-linked variants, through expanded carrier screening (ECS) or carrier screening based on WES. The remaining cases were diagnosed via conventional genetic testing methods, including Gap-PCR/PCR-Reverse Dot Blot (PCR-RDB) for thalassemia (12%), PCR and capillary electrophoresis for dynamic mutation genes testing (3%), multiplex ligation-dependent probe amplification (MLPA) testing for Duchenne/Becker muscular dystrophy (DMD/BMD) (5%) and Spinal Muscular Atrophy (SMA). Moreover, cases involving microdeletions or microduplications were diagnosed via copy number variation (CNV) testing based on Chromosomal Microarray Analysis (CMA) or next-generation sequencing (NGS).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.3 PGT strategy for different genetic disorders\u003c/h2\u003e \u003cp\u003eIn our study, we performed linkage analysis using SNPs detected by the ASA for different genetic disorders (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). For most of the cases, the number of SNPs available for linkage analysis in the upstream and downstream regions of target genes/regions is sufficient. However, for a subset of genes such as \u003cem\u003eHBA1/HBA2\u003c/em\u003e, \u003cem\u003eNF1, SMN1\u003c/em\u003e or genes located on the X chromosome (e.g., \u003cem\u003eF8\u003c/em\u003e, \u003cem\u003eDMD, ABCD1\u003c/em\u003e), insufficient SNPs or recombination events in the target genomic regions may lead to the failure of linkage analysis. Direct mutation detection for embryos is therefore particularly crucial as a complementary approach to linkage analysis.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePGT strategy for microdeletions or microduplications and other genetic disorders.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTypes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRegions/genes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNumber of Cases\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRelated CNV Syndromes/Regions\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSizes/Mutation sites\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePGT strategy*\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"7\" rowspan=\"8\"\u003e \u003cp\u003eMicrodeletion/\u003c/p\u003e \u003cp\u003eMicroduplication\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eXp22.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eX-linked ichthyosis (XLI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.79Mb/1.68Mb\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"7\" rowspan=\"8\"\u003e \u003cp\u003eASA/\u003c/p\u003e \u003cp\u003ePGT-A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22q11.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22q11 deletion syndrome (Velocardiofacial/DiGeorge syndrome)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.15Mb/2.18Mb\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16p11.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16p11.2 recurrent region (proximal, BP4-BP5) (includes TBX6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.22Mb/0.6Mb\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17q12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17q12 recurrent (RCAD syndrome) region (includes HNF1B)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.38Mb/1.48Mb\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1q21.1q21.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1q21.1 recurrent region (distal, BP3-BP4) (includes GJA5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.54Mb\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2q13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2q13 recurrent region (proximal) (includes NPHP1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.12Mb\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eXp22.2p22.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.51Mb\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eXp22.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLeri-Weill dyschondrostosis (LWD) - SHOX deletion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.36Mb\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003etrinucleotide repeat expansions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eHTT\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHuntington disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eexpanded CAG/CGG repeats\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eASA/ RP-PCR/ PGT-A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eATXN1\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSpinocerebellar ataxia 1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eATXN3\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSpinocerebellar Ataxia Type 3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eFMR1\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFragile X syndrome\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eATXN2\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSpinocerebellar ataxia 2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003edeletional alpha-thalassemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eHBA1/2\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eThalassemias, alpha-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e--\u003csup\u003eSEA\u003c/sup\u003e, -α\u003csup\u003e3.7\u003c/sup\u003e, -α\u003csup\u003e4.2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eASA/Gap/\u003c/p\u003e \u003cp\u003ePGT-A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003especial genes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eSMN1\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSpinal muscular atrophy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eExon 7/8 del\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eASA/\u003c/p\u003e \u003cp\u003ePCR-RFLP/ PGT-A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e*RP-PCR: repeat-primed PCR and capillary electrophoresis; PCR-RFLP: PCR-restriction fragment length polymorphism.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFor cases with deletional alpha-thalassemia such as --\u003csup\u003eSEA\u003c/sup\u003e, -α3.7 and -α4.2, gap-PCR analysis for all the embryos was conducted and deletion-carrying embryos can be directly identified via agarose gel electrophoresis (\u003cb\u003eFigure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e and \u003cb\u003eFigure S2A-B\u003c/b\u003e). The gap-PCR results for all the 99 embryos from 20 PGT-M cycles were not contradictory to those of linkage analysis, and 50 embryos were selected as suitable candidates for transfer.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFor the \u003cem\u003eSMN1\u003c/em\u003e gene, no usable SNPs were available within the 1 Mb upstream of the gene for linkage analysis since no probes were designed within this region. Therefore, we additionally employed PCR-restriction fragment length polymorphism (PCR-RFLP) to further confirm whether homozygous deletions of exon 7 or 8 were present in the embryo samples (\u003cb\u003eFigure S3A-B\u003c/b\u003e). No cases inconsistent with the linkage analysis results have been identified.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn addition, repeat-primed PCR (RP-PCR) and fragment length analysis was conducted for cases with repeat expansion disorders (related genes like \u003cem\u003eATXN1\u003c/em\u003e, \u003cem\u003eATXN2\u003c/em\u003e, \u003cem\u003eATXN3\u003c/em\u003e, \u003cem\u003eFMR1\u003c/em\u003e, \u003cem\u003eHTT\u003c/em\u003e). Combining linkage analysis and direct expansion mutation detection enabled accurate diagnosis of the carrier status of each embryo. Among the cases involving trinucleotide repeat expansions, 24 out of 65 embryos from 12 PGT-M cycles were eligible for transfer.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.4 PGT strategy and outcomes for de novo pathogenic variant(s)\u003c/h2\u003e \u003cp\u003eIn conventional PGT-M, linkage analysis typically relies on positive family members. However, for cases involving \u003cem\u003ede novo\u003c/em\u003e variants or lack of family members, we perform haplotype analysis directly using single spermatozoa, or construct haplotypes for carriers via long-read sequencing (LRS). Here, we enrolled 18 families with different \u003cem\u003ede novo\u003c/em\u003e variants in 14 genes including \u003cem\u003eNF1\u003c/em\u003e (neurofibromatosis, 3 cases), \u003cem\u003eFBN1\u003c/em\u003e (Marfan syndrome, 2 cases), \u003cem\u003ePKD1\u003c/em\u003e (polycystic kidney disease 1, 2 cases) and others (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Haplotypes were successfully constructed for all cases, enabling the accurate differentiation between the high-risk haplotype and low-risk haplotype in the affected individual or mutation carriers. However, for the 5 families using the single sperm haplotype methodology, more than 30 single spermatozoa were isolated per family and the single spermatozoa successfully validated for haplotype construction exhibited a relatively low detection rate and accuracy following analysis on the ASA (\u003cb\u003eFigure S4A-B\u003c/b\u003e). For the other 13 families, direct haplotype construction was performed for the affected individual using long-read sequencing. Combined with the results of ASA analysis for the couple and embryos, the final SNPs applicable for linkage analysis in PGT-M clinical cycle were identified. Meanwhile, long-read sequencing allows for precise breakpoint detection in deletion cases such as exon46-51 deletion in \u003cem\u003eDMD\u003c/em\u003e gene and exon3-47 deletion in \u003cem\u003eFLNA\u003c/em\u003e gene (\u003cb\u003eFigure S5A-B\u003c/b\u003e). Targeted Sanger sequencing for directly mutation detection is also essential for the identification of carrier status for embryos. Here, A total of 53 embryos from 12 PGT-M cycles were included in this study. And 18 non-carrier and euploid embryos were selected for transfer.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePGT strategy for de novo pathogenic variants or lack of family members.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGenes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of Cases\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRelated diseases\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMutation sites\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePGT strategy*\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eNF1\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNeurofibromatosis, type 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ec.1062\u0026thinsp;+\u0026thinsp;2T\u0026thinsp;\u0026gt;\u0026thinsp;C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLRS/ASA/Sanger/PGT-A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ec.5380C\u0026thinsp;\u0026gt;\u0026thinsp;T\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSPH/ASA/Sanger/PGT-A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ec.5546G\u0026thinsp;\u0026gt;\u0026thinsp;A(NM_000267.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLRS/ASA/Sanger/PGT-A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eFBN1\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMarfan syndrome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ec.4205G\u0026thinsp;\u0026gt;\u0026thinsp;T\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSPH/ASA/Sanger/PGT-A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ec.4930C\u0026thinsp;\u0026gt;\u0026thinsp;T(NM_000138.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLRS/ASA/Sanger/PGT-A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePKD1\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePolycystic kidney disease 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ec.8327_8343dup\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSPH/ASA/Sanger/PGT-A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eexon22 del (NM_001009944.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLRS/ASA/Gap/PGT-A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAPC\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGastric adenocarcinoma and proximal polyposis of the stomach\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ec.3497_3501del (NM_000038.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLRS/ASA/Sanger/PGT-A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eBCOR\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMicrophthalmia, syndromic 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ec.1873_1876delinsTTC (NM_017745.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLRS/ASA/Sanger/PGT-A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eBRCA2\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBreast-ovarian cancer, familial, 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ec.3109C\u0026thinsp;\u0026gt;\u0026thinsp;T(NM_000059.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLRS/ASA/Sanger/PGT-A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eDMD\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDuchenne muscular dystrophy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eexon46-51 del (NM_004006.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLRS/ASA/PGT-A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eEXT1\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eExostoses, multiple, type 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ec.797T\u0026thinsp;\u0026gt;\u0026thinsp;C(NM_000127.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLRS/ASA/Sanger/PGT-A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eFGFR1\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHartsfield syndrome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ec.809G\u0026thinsp;\u0026gt;\u0026thinsp;T(NM_145239.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLRS/ASA/Sanger/PGT-A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eFLNA\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOtopalatodigital syndrome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eexon3-47 del (NM_001456.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLRS/ASA/PGT-A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eFOXL2\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBlepharophimosis, epicanthus inversus, and ptosis, types 1 and 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ec.843_859dup (NM_023067.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSPH/ASA/Sanger/PGT-A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eKRT5\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEpidermolysis bullosa simplex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eexon7-8 del (NM_000424.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSPH/ASA/Sanger/PGT-A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eTP63\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLimb-mammary syndrome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ec.1986_2028dup (NM_000053.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLRS/ASA/Sanger/PGT-A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eTSC2\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTuberous sclerosis-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ec.3377del (NM_000548.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLRS/ASA/Sanger/PGT-A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e*LRS: long-read sequencing; ASA:the Asian Screening array; Sanger: targeted Sanger sequencing; SPH: Single sperm haplotyping; Gap: Gap-PCR\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.5 PGT strategy and outcomes for microdeletions or microduplications\u003c/h2\u003e \u003cp\u003eDue to the limited resolution of conventional PGT for aneuploidy or structural rearrangement (PGT-A/SR) (typically detects\u0026thinsp;\u0026gt;\u0026thinsp;4 Mb fragments), the PGT strategy based on SNP haplotyping is more applicable for prospective parent with small pathogenic copy number variants. Here, 18 families with microdeletions or microduplications (\u0026lt;\u0026thinsp;4Mb) were performed SNP haplotyping analysis based on the Asian Screening Array (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Informative SNPs flanking or within the target region were selected for linkage analysis to establish haplotypes of prospective parents. Notably, within the deletion region, SNPs that are inconsistent with the carrier and homozygous in the unaffected spouse can be regarded as informative markers (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e2\u003c/span\u003eA-B). And for tandem duplications, the homozygous SNPs in the unaffected spouse and affected proband within duplication region can be selected for linkage analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). In PGT clinical work-up, those informative SNPs detected by the ASA can assist in distinguishing the carrier status of embryos. A total of 23 embryo testing cycles were performed for those families with microdeletions or microduplications. After undergoing linkage analysis and CNV detection, 30 embryos out of 98 were ultimately deemed suitable for transfer. Successful pregnancies have been achieved in 8 families as of July 2025.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.6 Overall chromosomal abnormalities in PGT-M\u003c/h2\u003e \u003cp\u003eOverall, 1677 embryos obtained from 367 PGT-M cycles were included in this study, with an average of 4\u0026ndash;5 embryos retrieved per cycle. A total of 1267 embryos underwent chromosomal abnormality detection. Among these embryos, euploid embryos accounted for 61.16% (775/1267), while embryos with aneuploidy (including whole-chromosome mosaicism) accounted for 23.76% (301/1267), and those with only chromosomal segment abnormalities (including segmental mosaicism) accounted for 14.21% (183/1267) (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). When analyzing the subset of embryos with numerical chromosomal abnormalities, we found that roughly 37% of them were mosaic for whole chromosomes (111/301). The additional 1% of embryos represented test-failed embryos, which might be attributed to biopsy failure, amplification failure, or detection failure. Additionally, the transfer-eligible embryo rates were 35%, 45%, and 35% for autosomal dominant (AD), autosomal recessive (AR), and X-linked (XL) inheritance patterns, respectively, following linkage analysis and chromosomal abnormality testing (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e3\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4.Discussion","content":"\u003cp\u003eAlthough blastocyst trophectoderm biopsy is currently adopted in most PGT-M clinical application, there remains a risk of allele drop-out (ADO) in direct locus-specific testing due to the limited DNA quantity[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Therefore, indirect haplotype analysis is indispensable for the accurate diagnosis of embryos[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Genome-wide SNP array- or NGS-based haplotyping strategies have demonstrated more advantages, such as cost-effectiveness, high throughput, and a greater number of informative SNPs, over conventional targeted amplification strategies[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. We also demonstrated the applicability of the ASA in the Chinese population for PGT-M in our previous study[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Here, we have summarized the PGT-M cases based on the ASA over the past three years, proposed and analyzed the clinical utility of PGT-M strategies tailored to different genetic disorders, thereby providing insights for a broader range of clinical scenarios.\u003c/p\u003e \u003cp\u003eIn recent years, PGT technology has brought new hope to families affected by genetic or chromosomal disorders, particularly those carrying rare monogenic mutations or complex chromosomal rearrangements[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. With the widespread application of clinical genetic testing methods such as WES and ECS, an increasing number of rare genetic diseases have been diagnosed[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. In our study, genetic diagnoses in more than 76% of cases were confirmed by WES and ECS, highlighting the clinical utility of WES in the diagnosis of genetic disorders and ECS in identifying potential genetic disorders.\u003c/p\u003e \u003cp\u003eRegarding the amplification method for TE cells, typically, 5\u0026ndash;10 TE cells were subjected to whole-genome amplification (WGA) via either MDA or MALBAC, depending on the mutation type and the complexity of the gene locus[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Our experience indicates that both methods exhibited comparable performance in detecting SNVs or small indels for most genes. While, MDA can significantly improve the amplification success rate of regions with high GC content and high-repeat sequences. Therefore, for mutations in \u003cem\u003ePKD1\u003c/em\u003e, \u003cem\u003eHBA1/2\u003c/em\u003e, \u003cem\u003eSMN1\u003c/em\u003e and trinucleotide repeat genes, we consistently select MDA for amplification with high amplification yield and long fragment output. For other genetic conditions, during the PGT-M preclinical stage, we first evaluated the efficiency of MALBAC in amplifying and mutations detecting on oral mucosal cells. If MALBAC exhibits insufficient efficiency, MDA amplification is an alternative option, thereby finalizing the amplification strategy for TE cells. And no significant variation was observed in the detection performance of the ASA for MDA versus MALBAC amplification products.\u003c/p\u003e \u003cp\u003eFollowing whole-genome amplification (WGA), the amplified samples underwent both direct locus-specific testing and linkage analysis simultaneously. In our study, we summarized several distinct locus-specific detection methods for different genetic conditions. For SNVs or small indels, target-specific amplification and Sanger sequencing was applied for direct mutation detection of the embryos. When combined with linkage analysis results, ADO still occurs occasionally in direct mutation detection which may be attributed to suboptimal quality of biopsy samples or inefficient WGA or locus-specific amplification. The \u003cem\u003eSMN1\u003c/em\u003e gene represents another special case. Although it cannot distinguish between normal embryos and carrier embryos, PCR-RFLP still serves as a reliable supplementary method for identifying embryos with \u003cem\u003eSMN1\u003c/em\u003e homozygous deletion when valid SNPs are lacking on the ASA. For deletional alpha-thalassemia or large deletion mutations with known breakpoints, gap-PCR combined with agarose gel electrophoresis enable the identification of embryos with homozygous deletion. By employing these distinct mutation validation methods combined with linkage analysis, the two approaches cross-validate each other to ensure the accuracy of embryo detection results.\u003c/p\u003e \u003cp\u003eThe Asian Screening Array, which harbors approximately 700,000 SNP loci specific to East and Southeast Asian populations, offers a scalable and cost-effective approach for linkage analysis of most genetic variants[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. In our study, ASA provided a robust solution for linkage analysis across more than 150 genes and multiple microdeletion regions involved in the research. A sufficient number of valid SNPs were present both upstream, downstream, and within the genes, ensuring the accuracy of linkage analysis, except for genes with special genomic locations, such as \u003cem\u003eSMN1, F8\u003c/em\u003e. We also summarized specialized linkage analysis methodologies for \u003cem\u003ede novo\u003c/em\u003e mutations based on single sperm or long-read sequencing. However, the single sperm haplotype methodology is usually labor and cost consuming because of the high technical demand for single sperm selection and validation. Long-read sequencing offers a more optimal strategy attributed to its high accuracy and efficiency in PGT-M haplotype phasing involving \u003cem\u003ede novo\u003c/em\u003e mutations. Notably, long-read sequencing allows for precise breakpoint detection in deletion cases, which in turn supports direct mutation detection for embryos. Meanwhile, linkage analysis based on informative SNPs flanking or within the target regions is an effective PGT strategy for couples with small CNVs, including tandem duplications[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOverall, the PGT methods based on ASA established in this study provides an efficient and feasible technical solution for the clinical application of PGT under different disease types and genetic backgrounds. Although, in comparison with many currently developed comprehensive PGT methods[\u003cspan additionalcitationids=\"CR42\" citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e], the SNP array-based linkage analysis protocol requires an additional detection of chromosomal numerical or structural abnormalities. Nonetheless, this method is characterized by its distinct advantages such as high specificity for monogenic disorder screening, stable technical performance, and cost-effectiveness. In addition, for embryos in which the pathogenic variants have been clearly identified via linkage analysis or direct mutation testing, patients can choose to skip the detection of chromosomal anomalies, thereby reducing the overall testing costs.\u003c/p\u003e"},{"header":"5.Conclusion","content":"\u003cp\u003eIn conclusion, based on comprehensive PGT-M datasets accumulated over three years in our center (involving 377 pedigrees and 1677 embryos), our findings systematically illustrate the performance of the ASA-based PGT workflow that synergizes linkage analysis, direct mutation testing, and chromosomal CNV screening. For diverse genetic conditions, we developed customized PGT testing strategies and assessed their clinical performance. Our results provided data support and practical references for the individualized clinical application of PGT-M technology.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe present study was approved by the Ethics Committee of West China Second Hospital of Sichuan University. All patients provided written informed consent.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no conflicts of interest in this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by\u0026nbsp;National Key Research and Development Plan (2022YFC2703302).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCuiting Peng: Conceptualization, Data curation and original draft writing; Jun Ren: Validation and Methodology; Fan Zhou: Supervision, Validation; Han Chen, Hong Yang, Yutong Li and Yuezhi Keqie: Data curation, Formal analysis and Validation; Xu Zhao and Zhushu Liu: sample collection and data visualization; Ting Hu and Xuemei Zhang: Supervision; Taoli Ding and Ji Yang: Software and TGS data analysis. Shan Luo and Wei Fan: embryo biopsy; Xinlian Chen and Shanling Liu: Funding acquisition and review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank all the participants for their cooperation and participation. We thank the embryology team at the Center of Reproductive Medicine for help with sample preparation. We also thank Mengnan Huang and Teng Zhang from Yikon Genomics for technical help for data analysis.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eDe Rycke M, Berckmoes V. Preimplantation genetic testing for monogenic disorders. Genes. 2020;11:871.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHandyside AH, Kontogianni EH, Hardy K, et al. Pregnancies from biopsied human preimplantation embryos sexed by y-specific DNA amplification. 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J Assist Reprod Genet. 2019;36:1263\u0026ndash;71.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXie P, Pang R, Zeng L et al. ,\u003cem\u003e. Accurate identification of abnormal ploidy using an artificial intelligence model in preimplantation genetic testing. Human Reproduction Open, 2025, 2025: hoaf054\u003c/em\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Preimplantation Genetic Testing, Asian Screening Array, Monogenic disorder, Microdeletion/Microduplication, Haplotyping analysis","lastPublishedDoi":"10.21203/rs.3.rs-9047233/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9047233/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003ePreimplantation genetic testing for monogenic disorders (PGT-M) represents a critical clinical strategy for preventing the transmission of hereditary diseases from carriers to offspring, with its diagnostic efficacy heavily dependent on the accuracy and coverage of detection platforms. Genome-wide SNP array such as the Asian Screening Array (ASA), has demonstrated favorable performance in haplotype analysis for PGT-M. Here, we systematically evaluated the efficiency of the Asian Screening Array-based PGT workflow in PGT application for different genetic disorders.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe conducted a retrospective analysis by reviewing 377 pedigrees underwent PGT-M preclinical work-up and 367 PGT-M clinical cycles (1677 embryos in total) based on the Asian Screening Array. We established detection strategies combining ASA haplotyping analysis and individualized direct mutation detection based on different genetic patterns. Long-read sequencing or single-sperm haplotyping strategy was applied for families with de novo pathogenic variants or lacking family member samples. Individualized direct mutation detection methods such as Gap-PCR, RP-PCR, PCR-RFLP were adopted for different cases.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eResults indicated the clinical validity of our ASA-based PGT workflow, integrating linkage analysis, direct mutation detection, and chromosomal CNV screening. The number of SNPs available for linkage analysis in the upstream and downstream regions of target genes/regions is sufficient for most of the cases. Individualized direct mutation detection methods for different cases also validated the ASA haplotyping results. In haplotype analysis, the method based on long-read sequencing is more effective than single-sperm haplotyping strategy. Detailed haplotyping strategy for families with microdeletions and tandem duplications was established based on ASA. A total of 636 embryos were ultimately deemed suitable for transfer after undergoing linkage analysis and CNV detection.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThis study validated the feasibility and superiority of ASA-based approach in PGT, also provided a standardized and reliable technical solution for the clinical prevention of different genetic disorders.\u003c/p\u003e","manuscriptTitle":"Clinical Application of an Asian Screening Array-Based Preimplantation Genetic Testing Workflow for Various Genetic Disorders","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-19 16:10:23","doi":"10.21203/rs.3.rs-9047233/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"bf60a615-1dae-478d-a264-fa6159b8ca3f","owner":[],"postedDate":"March 19th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-27T22:35:17+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-19 16:10:23","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9047233","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9047233","identity":"rs-9047233","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}