Diagnostic Yield of Whole Genome Sequencing After Nondiagnostic Exome Sequencing or Gene Panel in Developmental and Epileptic Encephalopathies

ObjectiveTo assess the benefits and limitations of whole genome sequencing (WGS) compared to exome sequencing (ES) or multigene panel (MGP) in the molecular diagnosis of developmental and epileptic encephalopathies (DEE).MethodsWe performed WGS of 30 comprehensively phenotyped DEE patient trios that were undiagnosed after first-tier testing, including chromosomal microarray and either research ES (n = 15) or diagnostic MGP (n = 15).ResultsEight diagnoses were made in the 15 individuals who received prior ES (53%): 3 individuals had complex structural variants; 5 had ES-detectable variants, which now had additional evidence for pathogenicity. Eleven diagnoses were made in the 15 MGP-negative individuals (68%); the majority (n = 10) involved genes not included in the panel, particularly in individuals with postneonatal onset of seizures and those with more complex presentations including movement disorders, dysmorphic features, or multiorgan involvement. A total of 42% of diagnoses were autosomal recessive or X-chromosome linked.ConclusionWGS was able to improve diagnostic yield over ES primarily through the detection of complex structural variants (n = 3). The higher diagnostic yield was otherwise better attributed to the power of re-analysis rather than inherent advantages of the WGS platform. Additional research is required to assist in the assessment of pathogenicity of novel noncoding and complex structural variants and further improve diagnostic yield for patients with DEE and other neurogenetic disorders.

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Whole genome sequencing provides better diagnostic yield and future value than whole exome sequencing

The Medical Journal of Australia ◽

10.5694/mja17.01176 ◽

2018 ◽

Vol 209 (5) ◽

pp. 197-199 ◽

Cited By ~ 10

Author(s):

John S Mattick ◽

Marcel Dinger ◽

Nicole Schonrock ◽

Mark Cowley

Keyword(s):

Whole Genome Sequencing ◽

Exome Sequencing ◽

Whole Exome Sequencing ◽

Genome Sequencing ◽

Diagnostic Yield ◽

Whole Genome ◽

Whole Exome ◽

Future Value

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The Efficacy of Whole Genome Sequencing and RNA-Seq in the Diagnosis of Whole Exome Sequencing Negative Patients with Complex Neurological Phenotypes

Journal of Pediatric Genetics ◽

10.1055/s-0041-1736610 ◽

2021 ◽

Author(s):

Bianca Blake ◽

Lauren I. Brady ◽

Nicholas A. Rouse ◽

Peter Nagy ◽

Mark A. Tarnopolsky

Keyword(s):

Whole Genome Sequencing ◽

Exome Sequencing ◽

Whole Exome Sequencing ◽

Genome Sequencing ◽

Diagnostic Yield ◽

Whole Genome ◽

Rna Seq ◽

Complete Coverage ◽

Whole Exome ◽

Chromosome Microarray

AbstractWhole-genome sequencing (WGS) is being increasingly utilized for the diagnosis of neurological disease by sequencing both the exome and the remaining 98 to 99% of the genetic code. In addition to more complete coverage, WGS can detect structural variants (SVs) and intronic variants (SNVs) that cannot be identified by whole exome sequencing (WES) or chromosome microarray (CMA). Other multi-omics tools, such as RNA sequencing (RNA-Seq), can be used in conjunction with WGS to functionally validate certain variants by detecting changes in gene expression and splicing. The objective of this retrospective study was to measure the diagnostic yield of duo/trio-based WGS and RNA-Seq in a cohort of 22 patients (20 families) with pediatric onset neurological phenotypes and negative or inconclusive WES results in lieu of reanalysis. WGS with RNA-Seq resulted in a definite diagnosis of an additional 25% of cases. Sixty percent of these solved cases arose from the identification of variants that were missed by WES. Variants that could not be unequivocally proven to be causative of the patients' condition were identified in an additional 5% of cases.

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Whole Genome Sequencing in the Evaluation of Fetal Structural Anomalies: A Parallel Test with Chromosomal Microarray Plus Whole Exome Sequencing

Genes ◽

10.3390/genes12030376 ◽

2021 ◽

Vol 12 (3) ◽

pp. 376

Author(s):

Jia Zhou ◽

Ziying Yang ◽

Jun Sun ◽

Lipei Liu ◽

Xinyao Zhou ◽

...

Keyword(s):

Prenatal Diagnosis ◽

Whole Genome Sequencing ◽

Exome Sequencing ◽

Whole Exome Sequencing ◽

Genome Sequencing ◽

Chromosomal Microarray ◽

Whole Genome ◽

Significant Information ◽

Whole Exome ◽

Structural Anomalies

Whole genome sequencing (WGS) is a powerful tool for postnatal genetic diagnosis, but relevant clinical studies in the field of prenatal diagnosis are limited. The present study aimed to prospectively evaluate the utility of WGS compared with chromosomal microarray (CMA) and whole exome sequencing (WES) in the prenatal diagnosis of fetal structural anomalies. We performed trio WGS (≈40-fold) in parallel with CMA in 111 fetuses with structural or growth anomalies, and sequentially performed WES when CMA was negative (CMA plus WES). In comparison, WGS not only detected all pathogenic genetic variants in 22 diagnosed cases identified by CMA plus WES, yielding a diagnostic rate of 19.8% (22/110), but also provided additional and clinically significant information, including a case of balanced translocations and a case of intrauterine infection, which might not be detectable by CMA or WES. WGS also required less DNA (100 ng) as input and could provide a rapid turnaround time (TAT, 18 ± 6 days) compared with that (31 ± 8 days) of the CMA plus WES. Our results showed that WGS provided more comprehensive and precise genetic information with a rapid TAT and less DNA required than CMA plus WES, which enables it as an alternative prenatal diagnosis test for fetal structural anomalies.

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P4649Whole exome sequencing and whole genome sequencing improves genetic diagnosis of fetals with heterotaxy syndrome revealed by prenatal ultrasound

European Heart Journal ◽

10.1093/eurheartj/ehz745.1031 ◽

2019 ◽

Vol 40 (Supplement_1) ◽

Author(s):

T Yi ◽

H Sun ◽

Y Fu ◽

J Wang ◽

Y He

Keyword(s):

Whole Genome Sequencing ◽

Exome Sequencing ◽

Genome Sequencing ◽

Left Atrial ◽

Congenital Heart ◽

Clinical Phenotype ◽

Diagnostic Yield ◽

Right Atrial ◽

Whole Genome ◽

Atrial Isomerism

Abstract Background Heterotaxy (Htx) syndrome is an congenital disorders resulting from incorrectly establishment of left-right patterning during embryogenesis. Over 96% of patients with Htx exhibit some form of congenital heart disease (CHD),and has relatively poor survival. Multiple lines of evidence support genetic contributions to the etiology of Htx. As a specific genetic etiology is currently identifiable in only a minority of patients, there remains enormous potential for novel gene and pathway discovery. Purpose The aim of this study was to investigate the diagnostic yield of whole-exome sequencing (WES) and whole-genome sequencing (WGS) in fetuses with the pathogenesis of Htx, to explore candidate genes for Htx and to expand the clinical phenotype of known genetic conditions. Method WES and WGS were performed on specimens from 46 fetuses diagnosed with Htx and their parents. The single-nucleotide variants (SNVs) and copy-number variants (CNVs) were filtered and annotated by standard analysis process. All reported variants were classified according to he American College of Medical Genetics and Genomics guidelines. Results In the 46 fetuses, the detection rates of pathogenic and likely pathogenic variations were21.7% (10/46) and 10.9% (5/46) respectively. Ten pathogenic variations were identified on genes of CCDC114, DNAH11, ARMC4, STRA6, PQBP1 (hemizygote), HYDIN, RAI1 (Alagille Syndrome), ZFMP2 and Del(22q11.2) Syndrome. Five likely pathogenic variation were on DNAAF1 (Holshner syndrome), NF1, NEXN, NOTCH3 and FOXC1. Of 30 fetuses with prenatally diagnosed right atrial isomerism (RAI), the main intracardiac anomalies were atrioventricular canal (AV canal), isomerism of right atrial appendages, pulmonary stenosis or atresia (PS & PA) and right aortic arch. In 16 fetuses diagnosed left atrial isomerism (LAI) the main intracardiac anomalies were isomerism of left atrial appendages, interrupted IVC and azygos vein continuation. Of the 10 positive cases, 8 fetus were diagnosed of RAI and 2 were diagnosed of LAI by prenatal ultrasonic examination or fetal autopsy. The detection rate was 8/30 (26.7%) for RAI and 2/16 (12.5%) for LAI. Conclusion This study outlines the way for a substantial improvement in the diagnostic yield of prenatal genetic disorders in Htx through WES and WGS. Our experience also expanded the knowledge of the clinical phenotype of known genetic conditions. Our results indicate that the proportion of SNV in Htx of prenatal cases was significantly higher than that in patients with other congenital heart abnormalities, and the recessive inheritance occurred in a higher proportion in Htx. Our results have important implications for clinical management and genetic counseling of Htx. Acknowledgement/Funding Ministry of Science and Technology of the People's Republic of China

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Complex Structural Variants Resolved by Short-Read and Long-Read Whole Genome Sequencing in Mendelian Disorders

10.1101/281683 ◽

2018 ◽

Cited By ~ 2

Author(s):

Alba Sanchis-Juan ◽

Jonathan Stephens ◽

Courtney E French ◽

Nicholas Gleadall ◽

Karyn Mégy ◽

...

Keyword(s):

Whole Genome Sequencing ◽

Genome Sequencing ◽

De Novo ◽

Genomic Variation ◽

Mendelian Disease ◽

Whole Genome ◽

Structural Variants ◽

Short Read ◽

Long Read ◽

Complex Structural

AbstractComplex structural variants (cxSVs) are genomic rearrangements comprising multiple structural variants, typically involving three or more breakpoint junctions. They contribute to human genomic variation and can cause Mendelian disease, however they are not typically considered during genetic testing. Here, we investigate the role of cxSVs in Mendelian disease using short-read whole genome sequencing (WGS) data from 1,324 individuals with neurodevelopmental or retinal disorders from the NIHR BioResource project. We present four cases of individuals with a cxSV affecting Mendelian disease-associated genes. Three of the cxSVs are pathogenic: a de novo duplication-inversion-inversion-deletion affecting ARID1B in an individual with Coffin-Siris syndrome, a deletion-inversion-duplication affecting HNRNPU in an individual with intellectual disability and seizures, and a homozygous deletion-inversion-deletion affecting CEP78 in an individual with cone-rod dystrophy. Additionally, we identified a de novo duplication-inversion-duplication overlapping CDKL5 in an individual with neonatal hypoxic-ischaemic encephalopathy. Long-read sequencing technology used to resolve the breakpoints demonstrated the presence of both a disrupted and an intact copy of CDKL5 on the same allele; therefore, it was classified as a variant of uncertain significance. Analysis of sequence flanking all breakpoint junctions in all the cxSVs revealed both microhomology and longer repetitive sequences, suggesting both replication and homology based processes. Accurate resolution of cxSVs is essential for clinical interpretation, and here we demonstrate that long-read WGS is a powerful technology by which to achieve this. Our results show cxSVs are an important although rare cause of Mendelian disease, and we therefore recommend their consideration during research and clinical investigations.

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Estimating sequencing error rates using families

BioData Mining ◽

10.1186/s13040-021-00259-6 ◽

2021 ◽

Vol 14 (1) ◽

Author(s):

Kelley Paskov ◽

Jae-Yoon Jung ◽

Brianna Chrisman ◽

Nate T. Stockham ◽

Peter Washington ◽

...

Keyword(s):

Whole Genome Sequencing ◽

Exome Sequencing ◽

Genome Sequencing ◽

Variant Calling ◽

Error Rates ◽

Sequencing Error ◽

Whole Genome ◽

Sequencing Data ◽

Sequencing Platform ◽

Whole Exome

Abstract Background As next-generation sequencing technologies make their way into the clinic, knowledge of their error rates is essential if they are to be used to guide patient care. However, sequencing platforms and variant-calling pipelines are continuously evolving, making it difficult to accurately quantify error rates for the particular combination of assay and software parameters used on each sample. Family data provide a unique opportunity for estimating sequencing error rates since it allows us to observe a fraction of sequencing errors as Mendelian errors in the family, which we can then use to produce genome-wide error estimates for each sample. Results We introduce a method that uses Mendelian errors in sequencing data to make highly granular per-sample estimates of precision and recall for any set of variant calls, regardless of sequencing platform or calling methodology. We validate the accuracy of our estimates using monozygotic twins, and we use a set of monozygotic quadruplets to show that our predictions closely match the consensus method. We demonstrate our method’s versatility by estimating sequencing error rates for whole genome sequencing, whole exome sequencing, and microarray datasets, and we highlight its sensitivity by quantifying performance increases between different versions of the GATK variant-calling pipeline. We then use our method to demonstrate that: 1) Sequencing error rates between samples in the same dataset can vary by over an order of magnitude. 2) Variant calling performance decreases substantially in low-complexity regions of the genome. 3) Variant calling performance in whole exome sequencing data decreases with distance from the nearest target region. 4) Variant calls from lymphoblastoid cell lines can be as accurate as those from whole blood. 5) Whole-genome sequencing can attain microarray-level precision and recall at disease-associated SNV sites. Conclusion Genotype datasets from families are powerful resources that can be used to make fine-grained estimates of sequencing error for any sequencing platform and variant-calling methodology.

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Abstract 343: Bayesian Selection of Modifier Genes in Hypertrophic Cardiomyopathy Through Whole Genome Sequencing

Circulation Research ◽

10.1161/res.117.suppl_1.343 ◽

2015 ◽

Vol 117 (suppl_1) ◽

Author(s):

Matthew Wheeler ◽

Daryl Waggott ◽

Megan Grove ◽

Frederick Dewey ◽

Cuiping Pan ◽

...

Keyword(s):

Hypertrophic Cardiomyopathy ◽

Whole Genome Sequencing ◽

Genome Sequencing ◽

A Priori ◽

Copy Number Variants ◽

Whole Genome Sequence ◽

Monogenic Disease ◽

Whole Genome ◽

Genetic Modifiers ◽

Structural Variants

Background: Technological advances have greatly reduced the cost of whole genome sequencing. For single individuals clinical application is apparent, while exome sequencing in tens of thousands of people has allowed a more global view of genetic variation that can inform interpretation of specific variants in individuals. We hypothesized that genome sequencing of patients with monogenic cardiomyopathy would facilitate discovery of genetic modifiers of phenotype. Methods and Results: We identified 48 individuals diagnosed with cardiomyopathy and with putative mutations in MYH7, the gene encoding beta myosin heavy chain. We carried out whole genome sequencing and applied a newly developed analytical pipeline optimized for discovery of genes modifying severity of clinical presentation and outcomes. Using a combination of external priors and rare variant burden tests we scored genes as potential modifiers. There were 96 genes that reached a modifier score of 6 out of 12 or better (9=2, 8=8, 7=17, 6=69). We identified NCKAP1, a gene that regulates actin filament dynamics, and CAMSAP1, a calmodulin regulate gene that regulates microtubule dynamics, as top scoring modifiers of hypertrophic cardiomyopathy phenotypes (score=9) while LDB2, RYR2, FBN1 and ATP1A2 had modifier scores of 8. Of the top scoring genes, 21 out of 96 were identified as candidates a priori. Our candidate prioritization scheme identified the previously described modifiers of cardiomyopathy phenotype, FHOD3 and MYBPC3, as top scoring genes. We identified structural variants in 21 clinically sequenced cardiomyopathy associated genes, 13 of which were at less than 10% frequency. Copy number variants in ILK and CSRP3 were nominally associated with ejection fraction (p=0.03), while 8 genes showed copy gains (GLA, FKTN, SGCD, TTN, SOS1, ANKRD1, VCL and NEBL). Structural variants were found in CSRP3, MYL3 and TNNC1, all of which have been implicated as causative for HCM. Conclusion: Evaluation of the whole genome sequence, even in the case of putatively monogenic disease, leads to important diagnostic and scientific insights not revealed by panel-based sequencing.

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