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基因组与变异循证手册

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21 个章节

  1. 01Evaluation of in silico algorithms for use with ACMG/AMP clinical variant interpretation guidelines.Background The American College of Medical Genetics and American College of Pathologists (ACMG/AMP) variant classification guidelines for clinical reporting are widely used in diagnostic laboratories for variant interpretation. The ACMG/AMP guidelines recommend complete concordance of predictions among all in silico algorithms used without specifying the number or types of algorithms. The subjective nature of this recommendation contributes to discordance of variant classification among clinical laboratories and prevents definitive classification of variants. Results Using 14,819 benign or pathogenic missense variants from the ClinVar database, we compared performance of 25 algorithms across datasets differing in distinct biological and technical variables. There was wide variability in concordance among different combinations of algorithms with particularly low concordance for benign variants. We also identify a previously unreported source of error in variant interpretation (false co
  2. 02Whole genome sequencing for the diagnosis of neurological repeat expansion disorders in the UK: a retrospective diagnostic accuracy and prospective clinical validation study.Background Repeat expansion disorders affect about 1 in 3000 individuals and are clinically heterogeneous diseases caused by expansions of short tandem DNA repeats. Genetic testing is often locus-specific, resulting in underdiagnosis of people who have atypical clinical presentations, especially in paediatric patients without a previous positive family history. Whole genome sequencing is increasingly used as a first-line test for other rare genetic disorders, and we aimed to assess its performance in the diagnosis of patients with neurological repeat expansion disorders. Methods We retrospectively assessed the diagnostic accuracy of whole genome sequencing to detect the most common repeat expansion loci associated with neurological outcomes (AR, ATN1, ATXN1, ATXN2, ATXN3, ATXN7, C9orf72, CACNA1A, DMPK, FMR1, FXN, HTT, and TBP) using samples obtained within the National Health Service in England from patients who were suspected of having neurological disorders; previous PCR test results
  3. 03Liquid biopsy: current technology and clinical applications.Liquid biopsies are increasingly used for cancer molecular profiling that enables a precision oncology approach. Circulating extracellular nucleic acids (cell-free DNA; cfDNA), circulating tumor DNA (ctDNA), and circulating tumor cells (CTCs) can be isolated from the blood and other body fluids. This review will focus on current technologies and clinical applications for liquid biopsies. ctDNA/cfDNA has been isolated and analyzed using many techniques, e.g., droplet digital polymerase chain reaction, beads, emulsion, amplification, and magnetics (BEAMing), tagged-amplicon deep sequencing (TAm-Seq), cancer personalized profiling by deep sequencing (CAPP-Seq), whole genome bisulfite sequencing (WGBS-Seq), whole exome sequencing (WES), and whole genome sequencing (WGS). CTCs have been isolated using biomarker-based cell capture, and positive or negative enrichment based on biophysical and other properties. ctDNA/cfDNA and CTCs are being exploited in a variety of clinical applications: dif
  4. 04SpliceAI-visual: a free online tool to improve SpliceAI splicing variant interpretation.SpliceAI is an open-source deep learning splicing prediction algorithm that has demonstrated in the past few years its high ability to predict splicing defects caused by DNA variations. However, its outputs present several drawbacks: (1) although the numerical values are very convenient for batch filtering, their precise interpretation can be difficult, (2) the outputs are delta scores which can sometimes mask a severe consequence, and (3) complex delins are most often not handled. We present here SpliceAI-visual, a free online tool based on the SpliceAI algorithm, and show how it complements the traditional SpliceAI analysis. First, SpliceAI-visual manipulates raw scores and not delta scores, as the latter can be misleading in certain circumstances. Second, the outcome of SpliceAI-visual is user-friendly thanks to the graphical presentation. Third, SpliceAI-visual is currently one of the only SpliceAI-derived implementations able to annotate complex variants (e.g., complex delins). We
  5. 05Comprehensive evaluation of structural variation detection algorithms for whole genome sequencing.Background Structural variations (SVs) or copy number variations (CNVs) greatly impact the functions of the genes encoded in the genome and are responsible for diverse human diseases. Although a number of existing SV detection algorithms can detect many types of SVs using whole genome sequencing (WGS) data, no single algorithm can call every type of SVs with high precision and high recall. Results We comprehensively evaluate the performance of 69 existing SV detection algorithms using multiple simulated and real WGS datasets. The results highlight a subset of algorithms that accurately call SVs depending on specific types and size ranges of the SVs and that accurately determine breakpoints, sizes, and genotypes of the SVs. We enumerate potential good algorithms for each SV category, among which GRIDSS, Lumpy, SVseq2, SoftSV, Manta, and Wham are better algorithms in deletion or duplication categories. To improve the accuracy of SV calling, we systematically evaluate the accuracy of over
  6. 06Benchmarking of long-read assemblers for prokaryote whole genome sequencing.Background: Data sets from long-read sequencing platforms (Oxford Nanopore Technologies and Pacific Biosciences) allow for most prokaryote genomes to be completely assembled - one contig per chromosome or plasmid. However, the high per-read error rate of long-read sequencing necessitates different approaches to assembly than those used for short-read sequencing. Multiple assembly tools (assemblers) exist, which use a variety of algorithms for long-read assembly. Methods: We used 500 simulated read sets and 120 real read sets to assess the performance of eight long-read assemblers (Canu, Flye, Miniasm/Minipolish, NECAT, NextDenovo/NextPolish, Raven, Redbean and Shasta) across a wide variety of genomes and read parameters. Assemblies were assessed on their structural accuracy/completeness, sequence identity, contig circularisation and computational resources used. Results: Canu v2.1 produced reliable assemblies and was good with plasmids, but it performed poorly with circularisation and
  7. 07Implementation of next generation sequencing into pediatric hematology-oncology practice: moving beyond actionable alterations.Background Molecular characterization has the potential to advance the management of pediatric cancer and high-risk hematologic disease. The clinical integration of genome sequencing into standard clinical practice has been limited and the potential utility of genome sequencing to identify clinically impactful information beyond targetable alterations has been underestimated. Methods The Precision in Pediatric Sequencing (PIPseq) Program at Columbia University Medical Center instituted prospective clinical next generation sequencing (NGS) for pediatric cancer and hematologic disorders at risk for treatment failure. We performed cancer whole exome sequencing (WES) of patient-matched tumor-normal samples and RNA sequencing (RNA-seq) of tumor to identify sequence variants, fusion transcripts, relative gene expression, and copy number variation (CNV). A directed cancer gene panel assay was used when sample adequacy was a concern. Constitutional WES of patients and parents was performed whe
  8. 08Implementing Whole Genome Sequencing (WGS) in Clinical Practice: Advantages, Challenges, and Future Perspectives.The integration of whole genome sequencing (WGS) into all aspects of modern medicine represents the next step in the evolution of healthcare. Using this technology, scientists and physicians can observe the entire human genome comprehensively, generating a plethora of new sequencing data. Modern computational analysis entails advanced algorithms for variant detection, as well as complex models for classification. Data science and machine learning play a crucial role in the processing and interpretation of results, using enormous databases and statistics to discover new and support current genotype-phenotype correlations. In clinical practice, this technology has greatly enabled the development of personalized medicine, approaching each patient individually and in accordance with their genetic and biochemical profile. The most propulsive areas include rare disease genomics, oncogenomics, pharmacogenomics, neonatal screening, and infectious disease genomics. Another crucial application o
  9. 09dbNSFP v4: a comprehensive database of transcript-specific functional predictions and annotations for human nonsynonymous and splice-site SNVs.Whole exome sequencing has been increasingly used in human disease studies. Prioritization based on appropriate functional annotations has been used as an indispensable step to select candidate variants. Here we present the latest updates to dbNSFP (version 4.1), a database designed to facilitate this step by providing deleteriousness prediction and functional annotation for all potential nonsynonymous and splice-site SNVs (a total of 84,013,093) in the human genome. The current version compiled 36 deleteriousness prediction scores, including 12 transcript-specific scores, and other variant and gene-level functional annotations. The database is available at http://database.liulab.science/dbNSFP with a downloadable version and a web-service.
  10. 10Pathogenic variant burden in the ExAC database: an empirical approach to evaluating population data for clinical variant interpretation.Background The frequency of a variant in the general population is a key criterion used in the clinical interpretation of sequence variants. With certain exceptions, such as founder mutations, the rarity of a variant is a prerequisite for pathogenicity. However, defining the threshold at which a variant should be considered "too common" is challenging and therefore diagnostic laboratories have typically set conservative allele frequency thresholds. Methods Recent publications of large population sequencing data, such as the Exome Aggregation Consortium (ExAC) database, provide an opportunity to characterize with accuracy and precision the frequency distributions of very rare disease-causing alleles. Allele frequencies of pathogenic variants in ClinVar, as well as variants expected to be pathogenic through the nonsense-mediated decay (NMD) pathway, were analyzed to study the burden of pathogenic variants in 79 genes of clinical importance. Results Of 1364 BRCA1 and BRCA2 variants that a
  11. 11SARS-CoV-2 Spike Mutations, L452R, T478K, E484Q and P681R, in the Second Wave of COVID-19 in Maharashtra, India.As the global severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic expands, genomic epidemiology and whole genome sequencing are being used to investigate its transmission and evolution. Against the backdrop of the global emergence of "variants of concern" (VOCs) during December 2020 and an upsurge in a state in the western part of India since January 2021, whole genome sequencing and analysis of spike protein mutations using sequence and structural approaches were undertaken to identify possible new variants and gauge the fitness of the current circulating strains. Phylogenetic analysis revealed that newly identified lineages B.1.617.1 and B.1.617.2 were predominantly circulating. The signature mutations possessed by these strains were L452R, T478K, E484Q, D614G and P681R in the spike protein, including within the receptor-binding domain (RBD). Of these, the mutations at residue positions 452, 484 and 681 have been reported in other globally circulating lineages. The
  12. 12Calibration of computational tools for missense variant pathogenicity classification and ClinGen recommendations for PP3/BP4 criteria.Recommendations from the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) for interpreting sequence variants specify the use of computational predictors as "supporting" level of evidence for pathogenicity or benignity using criteria PP3 and BP4, respectively. However, score intervals defined by tool developers, and ACMG/AMP recommendations that require the consensus of multiple predictors, lack quantitative support. Previously, we described a probabilistic framework that quantified the strengths of evidence (supporting, moderate, strong, very strong) within ACMG/AMP recommendations. We have extended this framework to computational predictors and introduce a new standard that converts a tool's scores to PP3 and BP4 evidence strengths. Our approach is based on estimating the local positive predictive value and can calibrate any computational tool or other continuous-scale evidence on any variant type. We estimate thresholds (score i
  13. 13PulseNet International: Vision for the implementation of whole genome sequencing (WGS) for global food-borne disease surveillance.PulseNet International is a global network dedicated to laboratory-based surveillance for food-borne diseases. The network comprises the national and regional laboratory networks of Africa, Asia Pacific, Canada, Europe, Latin America and the Caribbean, the Middle East, and the United States. The PulseNet International vision is the standardised use of whole genome sequencing (WGS) to identify and subtype food-borne bacterial pathogens worldwide, replacing traditional methods to strengthen preparedness and response, reduce global social and economic disease burden, and save lives. To meet the needs of real-time surveillance, the PulseNet International network will standardise subtyping via WGS using whole genome multilocus sequence typing (wgMLST), which delivers sufficiently high resolution and epidemiological concordance, plus unambiguous nomenclature for the purposes of surveillance. Standardised protocols, validation studies, quality control programmes, database and nomenclature dev
  14. 14Sarek: A portable workflow for whole-genome sequencing analysis of germline and somatic variants.Whole-genome sequencing (WGS) is a fundamental technology for research to advance precision medicine, but the limited availability of portable and user-friendly workflows for WGS analyses poses a major challenge for many research groups and hampers scientific progress. Here we present Sarek, an open-source workflow to detect germline variants and somatic mutations based on sequencing data from WGS, whole-exome sequencing (WES), or gene panels. Sarek features (i) easy installation, (ii) robust portability across different computer environments, (iii) comprehensive documentation, (iv) transparent and easy-to-read code, and (v) extensive quality metrics reporting. Sarek is implemented in the Nextflow workflow language and supports both Docker and Singularity containers as well as Conda environments, making it ideal for easy deployment on any POSIX-compatible computers and cloud compute environments. Sarek follows the GATK best-practice recommendations for read alignment and pre-processing
  15. 15Integration of whole genome sequencing into a healthcare setting: high diagnostic rates across multiple clinical entities in 3219 rare disease patients.Background We report the findings from 4437 individuals (3219 patients and 1218 relatives) who have been analyzed by whole genome sequencing (WGS) at the Genomic Medicine Center Karolinska-Rare Diseases (GMCK-RD) since mid-2015. GMCK-RD represents a long-term collaborative initiative between Karolinska University Hospital and Science for Life Laboratory to establish advanced, genomics-based diagnostics in the Stockholm healthcare setting. Methods Our analysis covers detection and interpretation of SNVs, INDELs, uniparental disomy, CNVs, balanced structural variants, and short tandem repeat expansions. Visualization of results for clinical interpretation is carried out in Scout-a custom-developed decision support system. Results from both singleton (84%) and trio/family (16%) analyses are reported. Variant interpretation is done by 15 expert teams at the hospital involving staff from three clinics. For patients with complex phenotypes, data is shared between the teams. Results Overall,
  16. 16Accurate genomic variant detection in single cells with primary template-directed amplification.Improvements in whole genome amplification (WGA) would enable new types of basic and applied biomedical research, including studies of intratissue genetic diversity that require more accurate single-cell genotyping. Here, we present primary template-directed amplification (PTA), an isothermal WGA method that reproducibly captures >95% of the genomes of single cells in a more uniform and accurate manner than existing approaches, resulting in significantly improved variant calling sensitivity and precision. To illustrate the types of studies that are enabled by PTA, we developed direct measurement of environmental mutagenicity (DMEM), a tool for mapping genome-wide interactions of mutagens with single living human cells at base-pair resolution. In addition, we utilized PTA for genome-wide off-target indel and structural variant detection in cells that had undergone CRISPR-mediated genome editing, establishing the feasibility for performing single-cell evaluations of biopsies from edited
  17. 17Clinical implementation of RNA sequencing for Mendelian disease diagnostics.Background Lack of functional evidence hampers variant interpretation, leaving a large proportion of individuals with a suspected Mendelian disorder without genetic diagnosis after whole genome or whole exome sequencing (WES). Research studies advocate to further sequence transcriptomes to directly and systematically probe gene expression defects. However, collection of additional biopsies and establishment of lab workflows, analytical pipelines, and defined concepts in clinical interpretation of aberrant gene expression are still needed for adopting RNA sequencing (RNA-seq) in routine diagnostics. Methods We implemented an automated RNA-seq protocol and a computational workflow with which we analyzed skin fibroblasts of 303 individuals with a suspected mitochondrial disease that previously underwent WES. We also assessed through simulations how aberrant expression and mono-allelic expression tests depend on RNA-seq coverage. Results We detected on average 12,500 genes per sample inclu
  18. 18The Ensembl Variant Effect Predictor.The Ensembl Variant Effect Predictor is a powerful toolset for the analysis, annotation, and prioritization of genomic variants in coding and non-coding regions. It provides access to an extensive collection of genomic annotation, with a variety of interfaces to suit different requirements, and simple options for configuring and extending analysis. It is open source, free to use, and supports full reproducibility of results. The Ensembl Variant Effect Predictor can simplify and accelerate variant interpretation in a wide range of study designs.
  19. 19VarSome: the human genomic variant search engine.Summary VarSome.com is a search engine, aggregator and impact analysis tool for human genetic variation and a community-driven project aiming at sharing global expertise on human variants. Availability and implementation VarSome is freely available at http://varsome.com. Supplementary information Supplementary data are available at Bioinformatics online.
  20. 20Recommendations for application of the functional evidence PS3/BS3 criterion using the ACMG/AMP sequence variant interpretation framework.Background The American College of Medical Genetics and Genomics (ACMG)/Association for Molecular Pathology (AMP) clinical variant interpretation guidelines established criteria for different types of evidence. This includes the strong evidence codes PS3 and BS3 for "well-established" functional assays demonstrating a variant has abnormal or normal gene/protein function, respectively. However, they did not provide detailed guidance on how functional evidence should be evaluated, and differences in the application of the PS3/BS3 codes are a contributor to variant interpretation discordance between laboratories. This recommendation seeks to provide a more structured approach to the assessment of functional assays for variant interpretation and guidance on the use of various levels of strength based on assay validation. Methods The Clinical Genome Resource (ClinGen) Sequence Variant Interpretation (SVI) Working Group used curated functional evidence from ClinGen Variant Curation Expert Pa
  21. 21The Mount Sinai cohort of large-scale genomic, transcriptomic and proteomic data in Alzheimer's disease.Alzheimer's disease (AD) affects half the US population over the age of 85 and is universally fatal following an average course of 10 years of progressive cognitive disability. Genetic and genome-wide association studies (GWAS) have identified about 33 risk factor genes for common, late-onset AD (LOAD), but these risk loci fail to account for the majority of affected cases and can neither provide clinically meaningful prediction of development of AD nor offer actionable mechanisms. This cohort study generated large-scale matched multi-Omics data in AD and control brains for exploring novel molecular underpinnings of AD. Specifically, we generated whole genome sequencing, whole exome sequencing, transcriptome sequencing and proteome profiling data from multiple regions of 364 postmortem control, mild cognitive impaired (MCI) and AD brains with rich clinical and pathophysiological data. All the data went through rigorous quality control. Both the raw and processed data are publicly avail
基因组与变异循证手册 · GeniOmics