scholarly journals Clinical and Genetic Features in 31 Serial Chinese Children With Gitelman Syndrome

2021 ◽  
Vol 9 ◽  
Author(s):  
Lingxia Zhang ◽  
Ke Huang ◽  
Shugang Wang ◽  
Haidong Fu ◽  
Jingjing Wang ◽  
...  
Keyword(s):  
Early Diagnosis ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Muscle Weakness ◽  
Growth Retardation ◽  
Gitelman Syndrome ◽  
Compound Heterozygous ◽  
Whole Genome ◽  
Whole Exome ◽  
Laboratory Test Results

Gitelman syndrome (GS, OMIM 263800) is a genetic congenital tubulopathy associated with salt loss, which is characterized by hypokalemic metabolic toxicity, hypocalciuria, and hypomagnesemia. GS, which is typically detected in adolescence or adulthood, has long been considered a benign tubular lesion; however, the disease is associated with a significant decrease in the quality of life. In this study, we assessed the genotype–phenotype correlations based on the medical histories, clinical symptoms, laboratory test results, and whole-exome sequencing profiles from pediatric patients with GS. Between January 2014 and December 2020, all 31 consecutively enrolled patients complained of fatigue, salt craving, and muscle weakness. Sixteen patients demonstrated growth retardation, and five patients presented with nocturia and constipation. All patients presented with hypokalemic metabolic alkalosis, normal blood pressure, hyperaldosteronism, and a preserved glomerular filtration rate, and 24 of the 31 (77.4%) patients had hypomagnesemia. Homozygous, compound heterozygous, and heterozygous mutations in SLC12A3 were detected in 4, 24, and 3 patients, respectively. GS patients often present with muscle weakness and fatigue caused by hypokalemia and hypomagnesemia. Therefore, early diagnosis of GS is important in young children to reduce the possibility of growth retardation, tetany, and seizures. Next-generation sequencing such as whole-exome or whole-genome sequencing provides a practical tool for the early diagnosis and improvement of GS prognosis. Further whole-genome sequencing is expected to reveal more variants in SLC123A among GS patients with single heterozygous mutations.

scholarly journals Novel Compound Heterozygous Mutation in TRAPPC9 Gene: The Relevance of Whole Genome Sequencing

Genes ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 557
Author(s):  
Maria Isabel Alvarez-Mora ◽  
Jordi Corominas ◽  
Christian Gilissen ◽  
Aurora Sanchez ◽  
Irene Madrigal ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Missense Variant ◽  
Autism Spectrum ◽  
Compound Heterozygous Mutation ◽  
Heterozygous Mutation ◽  
Compound Heterozygous ◽  
Whole Genome ◽  
Whole Exome ◽  
Considerable Impact

Advances in high-throughput technologies and its implementation worldwide have had a considerable impact on the elucidation of the molecular causes underlying neurodevelopmental psychiatric disorders, especially for autism spectrum disorder and intellectual disability (ID). Nevertheless, etiology remains elusive in close to 50% of cases, even in those families with multiple affected individuals, strongly hinting at a genetic cause. Here we present a case report of two siblings affected with severe ID and other comorbidities, who embarked on a genetic testing odyssey until diagnosis was reached by using whole genome sequencing (WGS). WGS identified a maternally inherited novel missense variant (NM_031466.7:c.1037G > A; p.Gly346Glu) and a paternally inherited 90 kb intragenic deletion in TRAPPC9 gene. This report demonstrates the clinical utility of WGS in patients who remain undiagnosed after whole exome sequencing.

scholarly journals Effective variant filtering and expected candidate variant yield in studies of rare human disease

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Brent S. Pedersen ◽  
Joe M. Brown ◽  
Harriet Dashnow ◽  
Amelia D. Wallace ◽  
Matt Velinder ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Rare Disease ◽  
Genome Sequencing ◽  
Autosomal Dominant ◽  
De Novo ◽  
Autosomal Dominant Inheritance ◽  
Compound Heterozygous ◽  
Whole Genome ◽  
Dominant Inheritance ◽  
Family Based

AbstractIn studies of families with rare disease, it is common to screen for de novo mutations, as well as recessive or dominant variants that explain the phenotype. However, the filtering strategies and software used to prioritize high-confidence variants vary from study to study. In an effort to establish recommendations for rare disease research, we explore effective guidelines for variant (SNP and INDEL) filtering and report the expected number of candidates for de novo dominant, recessive, and autosomal dominant modes of inheritance. We derived these guidelines using two large family-based cohorts that underwent whole-genome sequencing, as well as two family cohorts with whole-exome sequencing. The filters are applied to common attributes, including genotype-quality, sequencing depth, allele balance, and population allele frequency. The resulting guidelines yield ~10 candidate SNP and INDEL variants per exome, and 18 per genome for recessive and de novo dominant modes of inheritance, with substantially more candidates for autosomal dominant inheritance. For family-based, whole-genome sequencing studies, this number includes an average of three de novo, ten compound heterozygous, one autosomal recessive, four X-linked variants, and roughly 100 candidate variants following autosomal dominant inheritance. The slivar software we developed to establish and rapidly apply these filters to VCF files is available at https://github.com/brentp/slivar under an MIT license, and includes documentation and recommendations for best practices for rare disease analysis.

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 Systematic dissection of biases in whole-exome and whole-genome sequencing reveals major determinants of coding sequence coverage

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Yury A. Barbitoff ◽  
Dmitrii E. Polev ◽  
Andrey S. Glotov ◽  
Elena A. Serebryakova ◽  
Irina V. Shcherbakova ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Whole Genome ◽  
Sequence Coverage ◽  
Coding Sequence ◽  
Whole Exome

scholarly journals Readability of informed consent forms for whole-exome and whole-genome sequencing

2017 ◽  
Vol 9 (2) ◽  
pp. 143-151 ◽  
Author(s):  
Emilia Niemiec ◽  
Danya F. Vears ◽  
Pascal Borry ◽  
Heidi Carmen Howard
Keyword(s):  
Informed Consent ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Whole Genome ◽  
Consent Forms ◽  
Whole Exome

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

Genetics of neuropsychiatric disease

2020 ◽  
pp. 127-140
Author(s):  
Stefania Bruno ◽  
Nayana Lahiri
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Genetic Disorders ◽  
Single Gene ◽  
Diagnostic Techniques ◽  
Genetic Influences ◽  
Whole Genome ◽  
Neuropsychiatric Disease ◽  
Genomic Technologies ◽  
Whole Exome

To better understand the intricacies of genetic influences on neuropsychiatric disease, it is important first to have a grounding in the models of human inheritance and current diagnostic techniques. This chapter covers the fundamentals of genetic disorders, giving insights into chromosomal, single-gene, and mitochondrial disorders. Moreover, it explores the changing applications of genomic technologies, such as whole exome and whole genome sequencing, through the lens of their implications for neuropsychiatry. Clinical examples are provided to give an idea of the genetic underpinnings of Alzheimer’s disease, Parkinson’s disease, and other familiar disorders.

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