Unanticipated results from exome sequencing/whole genome sequencing: The sky won't fall

2012 ◽  
Vol 158A (10) ◽  
pp. 2643-2644 ◽  
Author(s):  
Holly K. Tabor ◽  
Michael J. Bamshad
Keyword(s):  
Whole Genome Sequencing ◽  
Exome Sequencing ◽  
Genome Sequencing ◽  
Whole Genome

scholarly journals Estimating sequencing error rates using families

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.

scholarly journals Whole-genome sequencing offers additional but limited clinical utility compared with reanalysis of whole-exome sequencing

2018 ◽  
Vol 20 (11) ◽  
pp. 1328-1333 ◽  
Author(s):  
Ahmed Alfares ◽  
Taghrid Aloraini ◽  
Lamia Al subaie ◽  
Abdulelah Alissa ◽  
Ahmed Al Qudsi ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Genome Sequencing ◽  
Clinical Utility ◽  
Whole Genome ◽  
Whole Exome

scholarly journals Novel Discoveries in Immune Dysregulation in Inborn Errors of Immunity

2021 ◽  
Vol 12 ◽  
Author(s):  
Anwen Ren ◽  
Wei Yin ◽  
Heather Miller ◽  
Lisa S. Westerberg ◽  
Fabio Candotti ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Exome Sequencing ◽  
Genome Sequencing ◽  
Immune Dysregulation ◽  
Genetic Mutation ◽  
Disease Monitoring ◽  
Whole Genome ◽  
Inborn Errors ◽  
Inborn Errors Of Immunity ◽  
Whole Exome

With the expansion of our knowledge on inborn errors of immunity (IEI), it gradually becomes clear that immune dysregulation plays an important part. In some cases, autoimmunity, hyperinflammation and lymphoproliferation are far more serious than infections. Thus, immune dysregulation has become significant in disease monitoring and treatment. In recent years, the wide application of whole-exome sequencing/whole-genome sequencing has tremendously promoted the discovery and further studies of new IEI. The number of discovered IEI is growing rapidly, followed by numerous studies of their pathogenesis and therapy. In this review, we focus on novel discovered primary immune dysregulation diseases, including deficiency of SLC7A7, CD122, DEF6, FERMT1, TGFB1, RIPK1, CD137, TET2 and SOCS1. We discuss their genetic mutation, symptoms and current therapeutic methods, and point out the gaps in this field.

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

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.

Whole Genome and Exome Sequencing Defines The Genetic Landscape Of Hepatosplenic T-Cell Lymphoma

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 842-842
Author(s):  
Paula Scotland ◽  
Philippe Gaulard ◽  
Cassandra L Love ◽  
Virginie Fataccioli ◽  
Marion Travert ◽  
...  
Keyword(s):  
T Cell ◽  
Whole Genome Sequencing ◽  
Exome Sequencing ◽  
Genome Sequencing ◽  
Cell Lymphoma ◽  
T Cell Lymphoma ◽  
Chromosome 7 ◽  
Whole Genome ◽  
Hepatosplenic T Cell Lymphoma ◽  
Isochromosome 7Q

Abstract Background Hepatosplenic T-cell lymphoma (HSTL) is a rare form of lymphoma, comprising less than 1% of the cases. However, HSTL extracts a highly disproportionate toll on patients with a median age of diagnosis of 35 years and an expected median survival of less than two years. The vast majority of HSTL patients eventually succumb to their disease. The genetic basis of the disease is largely unknown. Although abnormalities of chromosome 7, including isochromosome 7q occur commonly in the disease, the role of specific genes and genetic mutations to the disease remains essentially unknown. Methods In this study, we sought to define the genetic features of HSTL through the whole genome sequencing and exome sequencing of 32 HSTL tumors and germline DNA (where available) from the same patients. Exome enrichment of DNA was carried out using the Agilent solution-based system of exon capture, which uses RNA baits to target all protein coding genes as well as ∼700 human microRNAs. Both whole genome and exome sequencing were performed using the Illumina platform. Results We identified 28 candidate cancer genes that were recurrently mutated in HSTL. Commonly implicated biological processes comprising these genes included signal transduction (e.g. PIK3CD, KRAS) and chromatin modification (e.g. TET1, SETD2 and MLL3), accounting for 16% and 23% of the total genetic events, respectively. Nearly all of these genes have been implicated in HSTL for the first time and provide new insights into the pathogenesis of the disease and potential targets for therapy. Whole genome sequencing confirmed isochromosome 7q as the most common recurrent chromosomal abnormality in HSTL and additional structural genetic alterations in chromosome 7. Conclusion Our study provides the most comprehensive genetic portrait of HSTL to date, and is a significant step in defining the genetic causes of this disease. Disclosures: No relevant conflicts of interest to declare.

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