Low-Pass Genome Sequencing

Genome sequencing in the prenatal diagnosis of structural malformations in the fetus

Prenatal genetic diagnosis has undergone two pivotal paradigm shifts, initially with the introduction of chromosomal microarray and subsequently with the advent of next-generation sequencing technologies (NGS). NGS technology has given rise to a multitude of applications, with gene panels, exome sequencing (ES), and genome sequencing (GS) emerging as highly promising tests for prenatal genetic investigations. These advanced approaches have demonstrated superior diagnostic rates when compared to conventional testing methods, showcasing the evolution and enhancement of prenatal genetic screening and diagnostic capabilities. With these ground-breaking innovations, NGS technologies have the potential to replace current standard practice in prenatal diagnosis. With the increasing use of prenatal sequencing, the need for better education and guidance on their applications grows. This chapter aims to illustrate the detection scope and feasibility of various NGS-based methods that are currently used in prenatal diagnosis.

Low-pass whole genome sequencing as a cost-effective alternative to chromosomal microarray analysis for low- and middle-income countries

Low-pass whole genome sequencing (LP-WGS) has been applied as alternative method to detect copy number variants (CNVs) in the clinical setting. Compared with chromosomal microarray analysis (CMA), the sequencing-based approach provides a similar resolution of CNV detection at a lower cost. In this study, we assessed the efficiency and reliability of LP-WGS as a more affordable alternative to CMA. A total of 1363 patients with unexplained neurodevelopmental delay/intellectual disability, autism spectrum disorders, and/or multiple congenital anomalies were enrolled. Those patients were referred from 15 nonprofit organizations and university centers located in different states in Brazil. The analysis of LP-WGS at 1x coverage (>50kb) revealed a positive testing result in 22% of the cases (304/1363), in which 219 and 85 correspond to pathogenic/likely pathogenic (P/LP) CNVs and variants of uncertain significance (VUS), respectively. The 16% (219/1363) diagnostic yield observed in our cohort is comparable to the 15%-20% reported for CMA in the literature. The use of commercial software, as demonstrated in this study, simplifies the implementation of the test in clinical settings. Particularly for countries like Brazil, where the cost of CMA presents a substantial barrier to most of the population, LP-WGS emerges as a cost-effective alternative for investigating copy number changes in cytogenetics.

Antisense oligonucleotides and their applications in rare neurological diseases

Rare diseases affect almost 500 million people globally, predominantly impacting children and often leading to significantly impaired quality of life and high treatment costs. While significant contributions have been made to develop effective treatments for those with rare diseases, more rapid drug discovery strategies are needed. Therapeutic antisense oligonucleotides can modulate target gene expression with high specificity through various mechanisms determined by base sequences and chemical modifications; and have shown efficacy in clinical trials for a few rare neurological conditions. Therefore, this review will focus on the applications of antisense oligonucleotides, in particular splice-switching antisense oligomers as promising therapeutics for rare neurological diseases, with key examples of Duchenne muscular dystrophy and spinal muscular atrophy. Challenges and future perspectives in developing antisense therapeutics for rare conditions including target discovery, antisense chemical modifications, animal models for therapeutic validations, and clinical trial designs will also be briefly discussed.

Focused Exome Sequencing Gives a High Diagnostic Yield in the Indian Subcontinent

The genetically isolated yet heterogeneous and highly consanguineous Indian population has shown a higher prevalence of rare genetic disorders. However, there is a significant socioeconomic burden for genetic testing to be accessible to the general population. In the current study, we analyzed next-generation sequencing data generated through focused exome sequencing from individuals with different phenotypic manifestations referred for genetic testing to achieve a molecular diagnosis. Pathogenic or likely pathogenic variants are reported in 280 of 833 cases with a diagnostic yield of 33.6%. Homozygous sequence and copy number variants were found as positive diagnostic findings in 131 cases (15.7%) because of the high consanguinity in the Indian population. No relevant findings related to reported phenotype were identified in 6.2% of the cases. Patients referred for testing due to metabolic disorder and neuromuscular disorder had higher diagnostic yields. Carrier testing of asymptomatic individuals with a family history of the disease, through focused exome sequencing, achieved positive diagnosis in 54 of 118 cases tested. Copy number variants were also found in trans with single-nucleotide variants and mitochondrial variants in a few of the cases. The diagnostic yield and the findings from this study signify that a focused exome test is a good lower-cost alternative for whole-exome and whole-genome sequencing and as a first-tier approach to genetic testing.

Validation of low-pass genome sequencing for prenatal diagnosis

OBJECTIVE

Chromosomal microarray (CMA), while considered the gold standard for detecting copy number variants (CNVs) in prenatal diagnostics, has its limitations, including the necessity to replace aging microarray equipment, low throughput, a static design, and an inefficient multi-day workflow. This study evaluates the feasibility of low-pass genome sequencing (LP-GS) as a potential replacement for CMA in prenatal diagnostics.

METHODS

We comprehensively compared LP-GS at 10x and 5x average depths with CMA in a prenatal laboratory. We examined parameters, including concordance, sensitivity, specificity, workflow efficiency, and cost-effectiveness.

RESULTS

We found a high degree of agreement between LP-GS and CMA for detecting CNVs and absence of heterozygosity. Furthermore, compared to CMA, LP-GS increased workflow efficiency and proved to be cost-neutral at 10x and cost-effective at 5x.

CONCLUSION

Our study suggests that LP-GS is a promising alternative to CMA in prenatal diagnostics, offering advantages, including a more efficient workflow and scalability for larger testing volumes. Importantly, for clinical laboratories that have adopted next-generation sequencing in a separate capacity, LP-GS facilitates a unified NGS-centric approach, enabling workflow consolidation. By offering a single, streamlined platform for detecting a broad range of genetic variants, LP-GS may represent a critical step toward enhancing the diagnostic capabilities of prenatal laboratories.

Low-pass whole genome sequencing is a reliable and cost-effective approach for copy number variant analysis in the clinical setting

INTRODUCTION

Next generation sequencing technology has greatly reduced the cost and time required for sequencing a genome. An approach that is rapidly being adopted as an alternative method for CNV analysis is the low-pass whole genome sequencing (LP-WGS). Here, we evaluated the performance of LP-WGS to detect copy number variants (CNVs) in clinical cytogenetics.

MATERIALS AND METHODS

DNA samples with known CNVs detected by chromosomal microarray analyses (CMA) were selected for comparison and used as positive controls; our panel included 44 DNA samples (12 prenatal and 32 postnatal), comprising a total of 55 chromosome imbalances. The selected cases were chosen to provide a wide range of clinically relevant CNVs, the vast majority being associated with intellectual disability or recognizable syndromes. The chromosome imbalances ranged in size from 75 kb to 90.3 Mb, including aneuploidies and two cases of mosaicism.

RESULTS

All CNVs were successfully detected by LP-WGS, showing a high level of consistency and robust performance of the sequencing method. Notably, the size of chromosome imbalances detected by CMA and LP-WGS were compatible between the two different platforms, which indicates that the resolution and sensitivity of the LP-WGS approach are at least similar to those provided by CMA.

DISCUSSION

Our data show the potential use of LP-WGS to detect CNVs in clinical diagnosis and confirm the method as an alternative for chromosome imbalances detection. The diagnostic effectiveness and feasibility of LP-WGS, in this technical validation study, were evidenced by a clinically representative dataset of CNVs that allowed a systematic assessment of the detection power and the accuracy of the sequencing approach. Further, since the software used in this study is commercially available, the method can easily be tested and implemented in a routine diagnostic setting.

Evidence from 2100 index cases supports genome sequencing as a first-tier genetic test

PURPOSE

Genome sequencing (GS) is one of the most comprehensive assays that interrogate single-nucleotide variants, copy number variants, mitochondrial variants, repeat expansions, and structural variants in a single assay. Despite the clear technical superiority, the full clinical utility of GS has yet to be determined.

METHODS

We systematically evaluated 2100 clinical GS index cases performed in our laboratory to explore the diagnostic yield of GS as first-tier and as follow-up testing.

RESULTS

The overall diagnostic yield was 28% (585/2100). The diagnostic yield for GS as the first-tier test was 26% (294/1146). Among cases with prior non-diagnostic genetic tests, GS provided a diagnosis for 27% (247/910) of cases, including 56 cases with prior exome sequencing (ES). Although re-analysis of previous ES might have resolved the diagnosis in 29 cases, diagnoses for 27 cases would have been missed because of the technical inferiority of ES. Moreover, GS further disclosed additional genetic etiology in 3 out of 44 cases with existing partial diagnosis.

CONCLUSION

We present the largest-to-date GS data set of a clinically heterogeneous cohort from a single clinical laboratory. Our data demonstrate that GS should be considered as the first-tier genetic test that has the potential to shorten the diagnostic odyssey.

Improving CNV Detection Performance in Microarray Data Using a Machine Learning-Based Approach

Copy number variation (CNV) is a primary source of structural variation in the human genome, leading to several disorders. Therefore, analyzing neonatal CNVs is crucial for managing CNV-related chromosomal disabilities. However, genomic waves can hinder accurate CNV analysis. To mitigate the influences of the waves, we adopted a machine learning approach and developed a new method that uses a modified log R ratio instead of the commonly used log R ratio. Validation results using samples with known CNVs demonstrated the superior performance of our method. We analyzed a total of 16,046 Korean newborn samples using the new method and identified CNVs related to 39 genetic disorders were identified in 342 cases. The most frequently detected CNV-related disorder was Joubert syndrome 4. The accuracy of our method was further confirmed by analyzing a subset of the detected results using NGS and comparing them with our results. The utilization of a genome-wide single nucleotide polymorphism array with wave offset was shown to be a powerful method for identifying CNVs in neonatal cases. The accurate screening and the ability to identify various disease susceptibilities offered by our new method could facilitate the identification of CNV-associated chromosomal disease etiologies.

GIInger predicts homologous recombination deficiency and patient response to PARPi treatment from shallow genomic profiles

Homologous recombination deficiency (HRD) is a predictive biomarker for poly(ADP-ribose) polymerase 1 inhibitor (PARPi) sensitivity. Routine HRD testing relies on identifying BRCA mutations, but additional HRD-positive patients can be identified by measuring genomic instability (GI), a consequence of HRD. However, the cost and complexity of available solutions hamper GI testing. We introduce a deep learning framework, GIInger, that identifies GI from HRD-induced scarring observed in low-pass whole-genome sequencing data. GIInger seamlessly integrates into standard BRCA testing workflows and yields reproducible results concordant with a reference method in a multisite study of 327 ovarian cancer samples. Applied to a BRCA wild-type enriched subgroup of 195 PAOLA-1 clinical trial patients, GIInger identified HRD-positive patients who experienced significantly extended progression-free survival when treated with PARPi. GIInger is, therefore, a cost-effective and easy-to-implement method for accurately stratifying patients with ovarian cancer for first-line PARPi treatment.

Structural and non-coding variants increase the diagnostic yield of clinical whole genome sequencing for rare diseases

BACKGROUND

Whole genome sequencing is increasingly being used for the diagnosis of patients with rare diseases. However, the diagnostic yields of many studies, particularly those conducted in a healthcare setting, are often disappointingly low, at 25-30%. This is in part because although entire genomes are sequenced, analysis is often confined to in silico gene panels or coding regions of the genome.

METHODS

We undertook WGS on a cohort of 122 unrelated rare disease patients and their relatives (300 genomes) who had been pre-screened by gene panels or arrays. Patients were recruited from a broad spectrum of clinical specialties. We applied a bioinformatics pipeline that would allow comprehensive analysis of all variant types. We combined established bioinformatics tools for phenotypic and genomic analysis with our novel algorithms (SVRare, ALTSPLICE and GREEN-DB) to detect and annotate structural, splice site and non-coding variants.

RESULTS

Our diagnostic yield was 43/122 cases (35%), although 47/122 cases (39%) were considered solved when considering novel candidate genes with supporting functional data into account. Structural, splice site and deep intronic variants contributed to 20/47 (43%) of our solved cases. Five genes that are novel, or were novel at the time of discovery, were identified, whilst a further three genes are putative novel disease genes with evidence of causality. We identified variants of uncertain significance in a further fourteen candidate genes. The phenotypic spectrum associated with RMND1 was expanded to include polymicrogyria. Two patients with secondary findings in FBN1 and KCNQ1 were confirmed to have previously unidentified Marfan and long QT syndromes, respectively, and were referred for further clinical interventions. Clinical diagnoses were changed in six patients and treatment adjustments made for eight individuals, which for five patients was considered life-saving.

CONCLUSIONS

Genome sequencing is increasingly being considered as a first-line genetic test in routine clinical settings and can make a substantial contribution to rapidly identifying a causal aetiology for many patients, shortening their diagnostic odyssey. We have demonstrated that structural, splice site and intronic variants make a significant contribution to diagnostic yield and that comprehensive analysis of the entire genome is essential to maximise the value of clinical genome sequencing.

Validation and depth evaluation of low-pass genome sequencing in prenatal diagnosis using 387 amniotic fluid samples

BACKGROUND

Low-pass genome sequencing (LP GS) is an alternative to chromosomal microarray analysis (CMA). However, validations of LP GS as a prenatal diagnostic test for amniotic fluid are rare. Moreover, sequencing depth of LP GS in prenatal diagnosis has not been evaluated.

OBJECTIVE

The diagnostic performance of LP GS was compared with CMA using 375 amniotic fluid samples. Then, sequencing depth was evaluated by downsampling.

RESULTS

CMA and LP GS had the same diagnostic yield (8.3%, 31/375). LP GS showed all copy number variations (CNVs) detected by CMA and six additional variant of uncertain significance CNVs (>100 kb) in samples with negative CMA results; CNV size influenced LP GS detection sensitivity. CNV detection was greatly influenced by sequencing depth when the CNV size was small or the CNV was located in the azoospermia factor c (AZFc) region of the Y chromosome. Large CNVs were less affected by sequencing depth and more stably detected. There were 155 CNVs detected by LP GS with at least a 50% reciprocal overlap with CNVs detected by CMA. With 25 M uniquely aligned high-quality reads (UAHRs), the detection sensitivity for the 155 CNVs was 99.14%. LP GS using samples with 25 M UAHRs showed the same performance as LP GS using total UAHRs. Considering the detection sensitivity, cost and interpretation workload, 25 M UAHRs are optimal for detecting most aneuploidies and microdeletions/microduplications.

CONCLUSION

LP GS is a promising, robust alternative to CMA in clinical settings. A total of 25 M UAHRs are sufficient for detecting aneuploidies and most microdeletions/microduplications.

Detection of Mosaic Absence of Heterozygosity (AOH) Using Low-Pass Whole Genome Sequencing in Prenatal Diagnosis: A Preliminary Report

Objective: Mosaicism is a common biological phenomenon in organisms and has been reported in many types of chromosome abnormalities, including the absence of heterozygosity (AOH). Due to the detection limitations of the sequencing approach, mosaic AOH events are rarely assessed in clinical cases. Herein, we report the performance of mosaic AOH identification using a low-pass (5~8-fold) WGS method (termed 'CMA-seq', an abbreviation for 'Chromosome Analysis by Sequencing') in fetal genetic diagnosis. Methods: Thirty AOH-negative, eleven constitutional AOH, and three mosaic AOH samples were collected as training data sets to develop the algorithm and evaluate the suitable thresholds for distinguishing mosaic AOH. Twenty-four new chromosomal aberrant cases, along with sixteen constitutional AOH samples, which were previously ascertained via the SNP-array-based method, were used as a validation data set to measure the performance in terms of sensitivity and specificity of this algorithm. Results: A new statistic, 'D-value', was implemented to identify and distinguish constitutional and mosaic AOH events. The reporting thresholds for constitutional and mosaic AOH were also established. In the validation set consisting of 24 new cases, seven constitutional AOH cases and 1 mosaic AOH case were successfully identified, indicating that the results were consistent with those of the SNP-array-based method. The results of all sixteen constitutional AOH validation samples also met the threshold requirements. Conclusions: In this study, we developed a new bioinformatic algorithm to accurately distinguish mosaic AOH from constitutional AOH by low-pass WGS. However, due to the small sample size of the training data set, the algorithm proposed in this manuscript still needs further refinements.

At-Risk Genomic Findings for Pediatric-Onset Disorders From Genome Sequencing vs Medically Actionable Gene Panel in Proactive Screening of Newborns and Children

Importance

Although the clinical utility of genome sequencing for critically ill children is well recognized, its utility for proactive pediatric screening is not well explored.

Objective

To evaluate molecular findings from screening ostensibly healthy children with genome sequencing compared with a gene panel for medically actionable pediatric conditions.

Design, Setting, and Participants

This case series study was conducted among consecutive, apparently healthy children undergoing proactive genetic screening for pediatric disorders by genome sequencing (n = 562) or an exome-based panel of 268 genes (n = 606) from March 1, 2018, through July 31, 2022.

Exposures

Genetic screening for pediatric-onset disorders using genome sequencing or an exome-based panel of 268 genes.

Main Outcomes and Measures

Molecular findings indicative of genetic disease risk.

Results

Of 562 apparently healthy children (286 girls [50.9%]; median age, 29 days [IQR, 9-117 days]) undergoing screening by genome sequencing, 46 (8.2%; 95% CI, 5.9%-10.5%) were found to be at risk for pediatric-onset disease, including 22 children (3.9%) at risk for high-penetrance disorders. Sequence analysis uncovered molecular diagnoses among 32 individuals (5.7%), while copy number variant analysis uncovered molecular diagnoses among 14 individuals (2.5%), including 4 individuals (0.7%) with chromosome scale abnormalities. Overall, there were 47 molecular diagnoses, with 1 individual receiving 2 diagnoses; of the 47 potential diagnoses, 22 (46.8%) were associated with high-penetrance conditions. Pathogenic variants in medically actionable pediatric genes were found in 6 individuals (1.1%), constituting 12.8% (6 of 47) of all diagnoses. At least 1 pharmacogenomic variant was reported for 89.0% (500 of 562) of the cohort. In contrast, of 606 children (293 girls [48.3%]; median age, 26 days [IQR, 10-67 days]) undergoing gene panel screening, only 13 (2.1%; 95% CI, 1.0%-3.3%) resulted in potential childhood-onset diagnoses, a significantly lower rate than those screened by genome sequencing (P < .001).

Conclusions and Relevance

In this case series study, genome sequencing as a proactive screening approach for children, due to its unrestrictive gene content and technical advantages in comparison with an exome-based gene panel for medically actionable childhood conditions, uncovered a wide range of heterogeneous high-penetrance pediatric conditions that could guide early interventions and medical management.

Low-Pass Genome Sequencing-Based Detection of Paternity: Validation in Clinical Cytogenetics

Submission of a non-biological parent together with a proband for genetic diagnosis would cause a misattributed parentage (MP), possibly leading to misinterpretation of the pathogenicity of genomic variants. Therefore, a rapid and cost-effective paternity/maternity test is warranted before genetic testing. Although low-pass genome sequencing (GS) has been widely used for the clinical diagnosis of germline structural variants, it is limited in paternity/maternity tests due to the inadequate read coverage for genotyping. Herein, we developed rapid paternity/maternity testing based on low-pass GS with trio-based and duo-based analytical modes provided. The optimal read-depth was determined as 1-fold per case regardless of sequencing read lengths, modes, and library construction methods by using 10 trios with confirmed genetic relationships. In addition, low-pass GS with different library construction methods and 1-fold read-depths were performed for 120 prenatal trios prospectively collected, and 1 trio was identified as non-maternity, providing a rate of MP of 0.83% (1/120). All results were further confirmed via quantitative florescent PCR. Overall, we developed a rapid, cost-effective, and sequencing platform-neutral paternity/maternity test based on low-pass GS and demonstrated the feasibility of its clinical use in confirming the parentage for genetic diagnosis.

Mucopolysaccharidosis Type I Presenting with Persistent Neonatal Respiratory Distress: A Case Report

Mucopolysaccharidosis type I (MPS I) is a rare inherited autosomal recessive lysosomal storage disorder. Despite several reports on MPS I-related neonatal interstitial lung disease, it is still considered to be an under-recognized disease manifestation. Thus, further study of MPS I is required to improve specific therapies and management strategies. The current report describes a late preterm baby (36 weeks gestational age) with neonatal onset of interstitial lung disease eventually diagnosed as MPS I. The neonate required prolonged respiratory support and oxygen supplementation that further escalated the likely diagnosis of inherited disorders of pulmonary surfactant dysfunction. Whole-exome sequencing confirmed the diagnosis of MPS I, following the observation of low levels of the enzyme α-L-iduronidase. The results highlight the necessity of considering MPS I-related pulmonary involvement in newborns with persistent respiratory insufficiency.

Perinatal outcomes and genomic characteristics of fetal copy number variants: An individual record linkage study of 713 pregnancies

OBJECTIVE

To determine the perinatal outcomes of fetuses diagnosed with a pathogenic copy number variant (CNV) or variant of uncertain significance (VUS); and to characterize these variants in terms of testing indication, genomic location, size, and inheritance.

METHODS

Retrospective study of singleton pregnancies with a pathogenic CNV or VUS from a single laboratory during 2012-2018. Probabilistic record linkage between the prenatal diagnosis dataset and perinatal outcome data for births from 20 weeks gestation was performed. If no birth record was found, this implied a pregnancy loss <20 weeks.

RESULTS

We included 6945 prenatal microarray results; a pathogenic CNV was detected in 230 (3.3%, 95% CI: 2.9%-3.8%) and a VUS in 483 (7.0%, 95% CI: 6.4%-7.6%). Of pregnancies with a pathogenic CNV, 20.0% (95% CI: 15.3%-25.6%) had a live birth, 3.0% (95% CI: 1.5%-6.2%) had a perinatal death (stillbirth or neonatal death), and 77% (95% CI: 71.1%-81.9%) had no birth record. Of those with a VUS, 64.4% (95% CI: 60.0%-68.5%) had a live birth, 1.8% (95% CI: 1.0%-3.5%) had a perinatal death, and no birth record was found for 33.7% (95% CI: 29.7%-38.1%). Most pathogenic CNVs (61.1%) were <7 Mb in size. The most common microdeletion syndromes were DiGeorge, Wolf-Hirschhorn, and Cri-du-chat syndromes.

CONCLUSION

This study provides an overview of perinatal outcomes and frequency of recurrent CNVs observed in the prenatal microarray era.

Evaluation and Analysis of Absence of Homozygosity (AOH) Using Chromosome Analysis by Medium Coverage Whole Genome Sequencing (CMA-seq) in Prenatal Diagnosis

OBJECTIVE

Absence of homozygosity (AOH) is a genetic characteristic known to cause human diseases mainly through autosomal recessive or imprinting mechanisms. The importance and necessity of accurate AOH detection has become more clinically significant in recent years. However, it remains a challenging task for sequencing-based methods thus far.

METHODS

In this study, we developed and optimized a new bioinformatic algorithm based on the assessment of minimum sequencing coverage, optimal bin size, the Z-score threshold of four types of allele count and the frequency for accurate genotyping using 28 AOH negative samples, and redefined the AOH detection cutoff value. We showed the performance of chromosome analysis by five-fold coverage whole genome sequencing (CMA-seq) for AOH identification in 27 typical prenatal/postnatal AOH positive samples, which were previously confirmed by chromosomal microarray analysis with single nucleotide polymorphism array (CMA/SNP array).

RESULTS

The blinded study indicated that for all three forms of AOH, including whole genomic AOH, single chromosomal AOH and segmental AOH, and all kinds of sample types, including chorionic villus sampling, amniotic fluid, cord blood, peripheral blood and abortive tissue, CMA-seq showed equivalent detection power to that of routine CMA/SNP arrays (750K). The subtle difference between the two methods is that CMA-seq is prone to detect small inconsecutive AOHs, while CMA/SNP array reports it as a whole.

CONCLUSION

Based on our newly developed bioinformatic algorithm, it is feasible to detect clinically significant AOH using CMA-seq in prenatal diagnosis.

Clinical Practice Guidelines for the Immunological Management of Chromosome 22q11.2 Deletion Syndrome and Other Defects in Thymic Development

Current practices vary widely regarding the immunological work-up and management of patients affected with defects in thymic development (DTD), which include chromosome 22q11.2 microdeletion syndrome (22q11.2del) and other causes of DiGeorge syndrome (DGS) and coloboma, heart defect, atresia choanae, retardation of growth and development, genital hypoplasia, ear anomalies/deafness (CHARGE) syndrome. Practice variations affect the initial and subsequent assessment of immune function, the terminology used to describe the condition and immune status, the accepted criteria for recommending live vaccines, and how often follow-up is needed based on the degree of immune compromise. The lack of consensus and widely varying practices highlight the need to establish updated immunological clinical practice guidelines. These guideline recommendations provide a comprehensive review for immunologists and other clinicians who manage immune aspects of this group of disorders.

Molecular Diagnosis of Duchenne Muscular Dystrophy Using Single NGS-Based Assay

Duchenne Muscular Dystrophy (DMD) is an X-linked inherited neuromuscular disorder caused by pathogenic variants in the dystrophin gene (DMD; locus Xp21.2). The variant spectrum of DMD is unique in that 65% of causative mutations are intragenic deletions, with intragenic duplications and point mutations (along with other sequence variants) accounting for 6% to 10% and 30% to 35%, respectively. The traditional strategy for molecular diagnostic testing for DMD involves initial screening for deletions/duplications using microarray-based comparative genomic hybridization followed by a full-sequence analysis of DMD for sequence variants. This traditional strategy is expensive and time-consuming due to the involvement of two separate tests to detect all types of variants in the DMD gene. Recent advancements in next-generation sequencing (NGS) technology and improvements in analysis algorithms related to copy number variant detection ultimately resulted in the development of a single NGS-based assay to detect all variant types, including deletions/duplications and sequence variants. This article initially discusses the strategic algorithm for establishing a molecular diagnosis of DMD and later provides detailed molecular diagnostic protocols for DMD, including an NGS-based sequencing assay with sequence and copy number variant analysis. © 2023 Wiley Periodicals LLC. Basic Protocol: Next-generation sequencing of the entire genomic sequence of the DMD gene using IDT xGen Lockdown Probes.

Evaluating Genetic Disorders in the Neonate: The Role of Exome Sequencing in the NICU

With recent advances in the technologies used for genetic diagnosis as well as our understanding of the genetic basis of disease, a growing list of options is available for providers when caring for a newborn with features suggesting an underlying genetic etiology. The choice of the most appropriate genetic test for a specific situation includes clinical considerations such as the phenotypic features and type of genetic abnormality suspected, as well as practical considerations such as cost and turnaround time. In this review, we discuss clinical exome sequencing in the context of genetic evaluation of newborns, including technical considerations, variant interpretation, and incidental/secondary findings. Strengths and limitations of exome sequencing are discussed and compared with those of other commonly known tests such as karyotype analysis, fluorescence in situ hybridization, chromosomal microarray, and sequencing panels, along with integration of results from prenatal testing if available. We also review future directions including genome sequencing and other emerging technologies that are starting to be used in clinical settings.

Trio-Based Low-Pass Genome Sequencing Reveals Characteristics and Significance of Rare Copy Number Variants in Prenatal Diagnosis

Background: Low-pass genome sequencing (GS) detects clinically significant copy number variants (CNVs) in prenatal diagnosis. However, detection at improved resolutions leads to an increase in the number of CNVs identified, increasing the difficulty of clinical interpretation and management.

Methods: Trio-based low-pass GS was performed in 315 pregnancies undergoing invasive testing. Rare CNVs detected in the fetuses were investigated. The characteristics of rare CNVs were described and compared to curated CNVs in other studies.

Results: A total of 603 rare CNVs, namely, 597 constitutional and 6 mosaic CNVs, were detected in 272 fetuses (272/315, 86.3%), providing 1.9 rare CNVs per fetus (603/315). Most CNVs were smaller than 1 Mb (562/603, 93.2%), while 1% (6/603) were mosaic. Forty-six de novo (7.6%, 46/603) CNVs were detected in 11.4% (36/315) of the cases. Eighty-four CNVs (74 fetuses, 23.5%) involved disease-causing genes of which the mode of inheritance was crucial for interpretation and assessment of recurrence risk. Overall, 31 pathogenic/likely pathogenic CNVs were detected, among which 25.8% (8/31) were small (<100 kb; n = 3) or mosaic CNVs (n = 5).

Conclusion: We examined the landscape of rare CNVs with parental inheritance assignment and demonstrated that they occur frequently in prenatal diagnosis. This information has clinical implications regarding genetic counseling and consideration for trio-based CNV analysis.

Evaluation of low-pass genome sequencing in polygenic risk score calculation for Parkinson's disease

Background

Low-pass sequencing (LPS) has been extensively investigated for applicability to various genetic studies due to its advantages over genotype array data including cost-effectiveness. Predicting the risk of complex diseases such as Parkinson’s disease (PD) using polygenic risk score (PRS) based on the genetic variations has shown decent prediction accuracy. Although ultra-LPS has been shown to be effective in PRS calculation, array data has been favored to the majority of PRS analysis, especially for PD.

Results

Using eight high-coverage WGS, we assessed imputation approaches for downsampled LPS data ranging from 0.5 × to 7.0 × . We demonstrated that uncertain genotype calls of LPS diminished imputation accuracy, and an imputation approach using genotype likelihoods was plausible for LPS. Additionally, comparing imputation accuracies between LPS and simulated array illustrated that LPS had higher accuracies particularly at rare frequencies. To evaluate ultra-low coverage data in PRS calculation for PD, we prepared low-coverage WGS and genotype array of 87 PD cases and 101 controls. Genotype imputation of array and downsampled LPS were conducted using a population-specific reference panel, and we calculated risk scores based on the PD-associated SNPs from an East Asian meta-GWAS. The PRS models discriminated cases and controls as previously reported when both LPS and genotype array were used. Also strong correlations in PRS models for PD between LPS and genotype array were discovered.

Conclusions

Overall, this study highlights the potentials of LPS under 1.0 × followed by genotype imputation in PRS calculation and suggests LPS as attractive alternatives to genotype array in the area of precision medicine for PD.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40246-021-00357-w.

A single NGS-based assay covering the entire genomic sequence of the DMD gene facilitates diagnostic and newborn screening confirmatory testing

Molecular diagnosis for Duchenne and Becker muscular dystrophies (DMD/BMD) involves a two-tiered approach for detection of deletions/duplications using MLPA or array CGH, followed by sequencing of coding and flanking intronic regions to detect sequence variants, which is time-consuming and expensive. We have developed a comprehensive next-generation sequencing (NGS)-based single-step assay to sequence the entire 2.2 Mb of the DMD gene to detect all copy number and sequence variants in both index males and carrier females. Assay validation was 100% concordant with other methodologies. A total of 772 samples have been tested, of which 62% (N = 480) were index cases with a clinical suspicion of DMD. Carrier testing females account for 38% (N = 292). Molecular diagnosis was confirmed in 86% (N = 413) of the index cases. Intragenic deletions and duplications (single-exon or multi-exon) were detected in 60% (N = 247) and 14% (N = 58) of the index cases, respectively. Full-sequence analysis of the entire gene allows for detection of deep intronic pathogenic variants and accurate breakpoint detection of CNVs involving similar exons, which could have an impact on the outcome of clinical trials. This comprehensive assay is highly sensitive for diagnostic testing for DMD and is also suitable for confirmatory testing for newborn screening for DMD.

Integrated CNV-seq, karyotyping and SNP-array analyses for effective prenatal diagnosis of chromosomal mosaicism

BACKGROUND

Emerging studies suggest that low-coverage massively parallel copy number variation sequencing (CNV-seq) more sensitive than chromosomal microarray analysis (CMA) for detecting low-level mosaicism. However, a retrospective back-to-back comparison evaluating accuracy, efficacy, and incremental yield of CNV-seq compared with CMA is warranted.

METHODS

A total of 72 mosaicism cases identified by karyotyping or CMA were recruited to the study. There were 67 mosaic samples co-analysed by CMA and CNV-seq, comprising 40 with sex chromosome aneuploidy, 22 with autosomal aneuploidy and 5 with large cryptic genomic rearrangements.

RESULTS

Of the 67 positive mosaic cases, the levels of mosaicism defined by CNV-seq ranged from 6 to 92% compared to the ratio from 3 to 90% by karyotyping and 20% to 72% by CMA. CNV-seq not only identified all 43 chromosomal aneuploidies or large cryptic genomic rearrangements detected by CMA, but also provided a 34.88% (15/43) increased yield compared with CMA. The improved yield of mosaicism detection by CNV-seq was largely due to the ability to detect low level mosaicism below 20%.

CONCLUSION

In the context of prenatal diagnosis, CNV-seq identified additional and clinically significant mosaicism with enhanced resolution and increased sensitivity. This study provides strong evidence for applying CNV-seq as an alternative to CMA for detection of aneuploidy and mosaic variants.

Intronic Breakpoint Signatures Enhance Detection and Characterization of Clinically Relevant Germline Structural Variants

The relevance of large copy number variants (CNVs) to hereditary disorders has been long recognized, and population sequencing efforts have chronicled many common structural variants (SVs). However, limited data are available on the clinical contribution of rare germline SVs. Here, a detailed characterization of SVs identified using targeted next-generation sequencing was performed. Across 50 genes associated with hereditary cancer and cardiovascular disorders, a minimum of 828 unique SVs were reported, including 584 fully characterized SVs. Almost 40% of CNVs were <5 kb, with one in three deletions impacting a single exon. Additionally, 36 mid-range deletions/duplications (50 to 250 bp), 21 mobile element insertions, 6 inversions, and 27 complex rearrangements were detected. This data set was used to model SV detection in a bioinformatics pipeline solely relying on read depth, which revealed that genome sequencing (30×) allows detection of 71%, a 500× panel only targeting coding regions 53%, and exome sequencing (100×) <20% of characterized SVs. SVs accounted for 14.1% of all unique pathogenic variants, supporting the importance of SVs in hereditary disorders. Robust SV detection requires an ensemble of variant-calling algorithms that utilize sequencing of intronic regions. These algorithms should use distinct data features representative of each class of mutational mechanism, including recombination between two sequences sharing high similarity, covariants inserted between CNV breakpoints, and complex rearrangements containing inverted sequences.

Preimplantation Genetic Testing for Chromosomal Abnormalities: Aneuploidy, Mosaicism, and Structural Rearrangements

There is a high incidence of chromosomal abnormalities in early human embryos, whether they are generated by natural conception or by assisted reproductive technologies (ART). Cells with chromosomal copy number deviations or chromosome structural rearrangements can compromise the viability of embryos; much of the naturally low human fecundity as well as low success rates of ART can be ascribed to these cytogenetic defects. Chromosomal anomalies are also responsible for a large proportion of miscarriages and congenital disorders. There is therefore tremendous value in methods that identify embryos containing chromosomal abnormalities before intrauterine transfer to a patient being treated for infertility—the goal being the exclusion of affected embryos in order to improve clinical outcomes. This is the rationale behind preimplantation genetic testing for aneuploidy (PGT-A) and structural rearrangements (-SR). Contemporary methods are capable of much more than detecting whole chromosome abnormalities (e.g., monosomy/trisomy). Technical enhancements and increased resolution and sensitivity permit the identification of chromosomal mosaicism (embryos containing a mix of normal and abnormal cells), as well as the detection of sub-chromosomal abnormalities such as segmental deletions and duplications. Earlier approaches to screening for chromosomal abnormalities yielded a binary result of normal versus abnormal, but the new refinements in the system call for new categories, each with specific clinical outcomes and nuances for clinical management. This review intends to give an overview of PGT-A and -SR, emphasizing recent advances and areas of active development.