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.

scholarly journals Best practices for the analytical validation of clinical whole-genome sequencing intended for the diagnosis of germline disease

2020 ◽  
Vol 5 (1) ◽  
Author(s):  
Christian R. Marshall ◽  
◽  
Shimul Chowdhury ◽  
Ryan J. Taft ◽  
Mathew S. Lebo ◽  
...  
Keyword(s):  
Best Practices ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Test Performance ◽  
Genetic Disorders ◽  
Chromosomal Microarray ◽  
Chromosomal Microarray Analysis ◽  
Whole Genome ◽  
Analytical Validation ◽  
Whole Exome

Abstract Whole-genome sequencing (WGS) has shown promise in becoming a first-tier diagnostic test for patients with rare genetic disorders; however, standards addressing the definition and deployment practice of a best-in-class test are lacking. To address these gaps, the Medical Genome Initiative, a consortium of leading healthcare and research organizations in the US and Canada, was formed to expand access to high-quality clinical WGS by publishing best practices. Here, we present consensus recommendations on clinical WGS analytical validation for the diagnosis of individuals with suspected germline disease with a focus on test development, upfront considerations for test design, test validation practices, and metrics to monitor test performance. This work also provides insight into the current state of WGS testing at each member institution, including the utilization of reference and other standards across sites. Importantly, members of this initiative strongly believe that clinical WGS is an appropriate first-tier test for patients with rare genetic disorders, and at minimum is ready to replace chromosomal microarray analysis and whole-exome sequencing. The recommendations presented here should reduce the burden on laboratories introducing WGS into clinical practice, and support safe and effective WGS testing for diagnosis of germline disease.

scholarly journals Sekwencjonowanie genomu/eksomu człowieka - aspekt bioetyczny

2014 ◽  
Vol 12 (1) ◽  
pp. 29-38
Author(s):  
Andrzej Kochański
Keyword(s):  
Genome Sequencing ◽  
Genetic Disorders ◽  
Single Gene ◽  
Genetic Data ◽  
Short Review ◽  
Clinical Genetics ◽  
Whole Genome ◽  
Ethical Challenges ◽  
Whole Exome ◽  
Change Of Perspective

In recent years we have observed a technological revolution in genetics. For years molecular diagnostics in genetic disorders were limited to a single gene or to a group of genes. The technological breakdown in molecular genetics relies on the change of perspective from the analysis of a single gene to the whole genome sequencing (WGS) or whole-exome sequencing (WES). The exome is defined as a coding part of the genome consisting of the coding parts (exons) of all genes. Thus, at present geneticists have access to the whole genome instead of separate/selected genes. Clinical genetics in the era of genomic sequencing has to cope with new challenges concerning the confidentiality of genetic data, genetic discrimination, genetic and clinical determinism, or incidental findings detected in genome analysis. This short review attempts to demonstrate the ethical challenges faced in the era of genome sequencing.

scholarly journals Meeting summary: ethical aspects of whole exome and whole genome sequencing studies (WES/WGS) in rare diseases, Tel Aviv, Israel, January 2013

2013 ◽  
Vol 95 (2-3) ◽  
pp. 53-56 ◽  
Author(s):  
LUBA FARBEROV ◽  
AVITAL GILAM ◽  
OFER ISAKOV ◽  
NOAM SHOMRON
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Rare Diseases ◽  
Genetic Basis ◽  
Diagnostic Tools ◽  
Whole Genome ◽  
Ethical Aspects ◽  
Genomic Technologies ◽  
Whole Exome ◽  
Sequencing Studies

SummaryA recent E-Rare workshop reviewed the ethical aspects of whole exome and whole genome-sequencing studies (WES and WGS, respectively) in rare diseases. Leveraging new genomic technologies, which output vast amounts of known and novel genetic variants, researchers are learning more about the genetic basis and mechanisms involved in rare diseases. In some cases, these findings are translated into diagnostic tools for the benefit of rare disease patients. Among the disclosed data, which can assist in treatment management, incidental findings await, bringing with them ethical concerns for the clinicians, researchers and patients.

scholarly journals Development and Validation of Clinical Whole-Exome and Whole-Genome Sequencing for Detection of Germline Variants in Inherited Disease

2017 ◽  
Vol 141 (6) ◽  
pp. 798-805 ◽  
Author(s):  
Madhuri Hegde ◽  
Avni Santani ◽  
Rong Mao ◽  
Andrea Ferreira-Gonzalez ◽  
Karen E. Weck ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Single Gene ◽  
Whole Genome ◽  
Inherited Disease ◽  
Inherited Disorders ◽  
Quality Control Program ◽  
Germline Variants ◽  
Clinical Laboratories ◽  
Whole Exome

Context.— With the decrease in the cost of sequencing, the clinical testing paradigm has shifted from single gene to gene panel and now whole-exome and whole-genome sequencing. Clinical laboratories are rapidly implementing next-generation sequencing–based whole-exome and whole-genome sequencing. Because a large number of targets are covered by whole-exome and whole-genome sequencing, it is critical that a laboratory perform appropriate validation studies, develop a quality assurance and quality control program, and participate in proficiency testing. Objective.— To provide recommendations for whole-exome and whole-genome sequencing assay design, validation, and implementation for the detection of germline variants associated in inherited disorders. Data Sources.— An example of trio sequencing, filtration and annotation of variants, and phenotypic consideration to arrive at clinical diagnosis is discussed. Conclusions.— It is critical that clinical laboratories planning to implement whole-exome and whole-genome sequencing design and validate the assay to specifications and ensure adequate performance prior to implementation. Test design specifications, including variant filtering and annotation, phenotypic consideration, guidance on consenting options, and reporting of incidental findings, are provided. These are important steps a laboratory must take to validate and implement whole-exome and whole-genome sequencing in a clinical setting for germline variants in inherited disorders.

scholarly journals Comparison of three variant callers for human whole genome sequencing

2018 ◽  
Author(s):  
Anna Supernat ◽  
Oskar Valdimar Vidarsson ◽  
Vidar M. Steen ◽  
Tomasz Stokowy
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Single Gene ◽  
Reference Sample ◽  
Variant Calling ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Sequencing Data ◽  
Whole Exome ◽  
Indel Calling

ABSTRACTTesting of patients with genetics-related disorders is in progress of shifting from single gene assays to gene panel sequencing, whole-exome sequencing (WES) and whole-genome sequencing (WGS). Since WGS is unquestionably becoming a new foundation for molecular analyses, we decided to compare three currently used tools for variant calling of human whole genome sequencing data. We tested DeepVariant, a new TensorFlow machine learning-based variant caller, and compared this tool to GATK 4.0 and SpeedSeq, using 30×, 15× and 10× WGS data of the well-known NA12878 DNA reference sample.According to our comparison, the performance on SNV calling was almost similar in 30× data, with all three variant callers reaching F-Scores (i.e. harmonic mean of recall and precision) equal to 0.98. In contrast, DeepVariant was more precise in indel calling than GATK and SpeedSeq, as demonstrated by F-Scores of 0.94, 0.90 and 0.84, respectively.We conclude that the DeepVariant tool has great potential and usefulness for analysis of WGS data in medical genetics.

scholarly journals Micro-costing diagnostics in oncology: from single-gene testing to whole genome sequencing

2021 ◽  
Author(s):  
Clémence TB Pasmans ◽  
Bastiaan BJ Tops ◽  
Elisabeth MP Steeghs ◽  
Veerle MH Coupé ◽  
Katrien Grünberg ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Single Gene ◽  
Whole Genome ◽  
Gene Testing

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
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