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Central resources of variant discovery and annotation and its role in precision medicine

Hashim Halim-Fikri
Hashim Halim-Fikri
, 
Sharifah-Nany Rahayu-Karmilla Syed-Hassan
Sharifah-Nany Rahayu-Karmilla Syed-Hassan
, 
Wan-Khairunnisa Wan-Juhari
Wan-Khairunnisa Wan-Juhari
, 
Mat Ghani Siti Nor Assyuhada
Mat Ghani Siti Nor Assyuhada
, 
Yetti Hernaningsih
Yetti Hernaningsih
, 
Narazah Mohd Yusoff
Narazah Mohd Yusoff
, 
Amir Feisal Merican
Amir Feisal Merican
 et 
Bin Alwi Zilfalil
Bin Alwi Zilfalil
   | 01 août 2023
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Article Category: Mini review
Publié en ligne: 01 août 2023
Pages: 285 - 298
DOI: https://doi.org/10.2478/abm-2022-0032
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© 2023 Hashim Halim-Fikri et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.

Figure 1.

The 5 variant classifications of ACMG Guidelines [58].
The 5 variant classifications of ACMG Guidelines [58].

Figure 2.

Parameters required for variant annotation in hemoglobinopathies.
Parameters required for variant annotation in hemoglobinopathies.

Selected resources, valuable information, and analysis tools available for variant annotation

Resource Brief description Features References
Database
1 dbVar dbVar is an archive of large-scale genomic variants (generally >50 bp) including insertions, deletions, duplications, inversions, mobile elements, translocations, and complex variants.The current number of submitted variants in the database is more than 6 million from over 190 studies including large international projects such as 1000 Genome Project, gnomAD, the CNV Global Population Survey, and clinical resources, which are ClinVar and ClinGen. To date, the total in the dbVar database of 190 studies consists of 6 million regions and 36 million variants. dbVar continues to make it easier to find and use structural variation data by making selected datasets available on TrackHub for viewing in the NCBI GDV and other genome browsers, such as the UCSC browser. Tracks are available for the structural variants imported from ClinVar (https://www.ncbi.nlm.nih.gov/dbvar/content/clinvar_summary/#homepage) and for the NCBI Curated Common Structural Variants (nstd186). [23, 24, 25]
2 HGMD A thorough assortment of published germline mutations in nuclear genes that entail, or are firmly connected with, human acquired disease. HGMD has been supported over the years by commercial partnerships with various industry leading biomedical research companies.A stand-alone web application has been made available under license from BIOBASE GmbH.The latest version of HGMD (2020.2) contains 289,346 different mutations in 11,076 genes (more than ClinVar & OMIM).Articles identified as potential sources of mutation data are assessed by a team of experienced curators (with an average of more than 12 years’ experience in curation).Academic or non-profit users without a subscription may utilize the public version of HGMD (http://www.hgmd.org). However, this version is provided in a basic form that is searchable only by gene symbol or disease name, is only updated twice annually, is maintained permanently at least 3 years out of date, and does not contain any of the additional annotations or extra features present in HGMD Professional.Another challenge is that an increasing number of journals do not appear to be systematically indexed by Medline, at least not immediately upon publication. [26] http://www.hgmd.cf.ac.uk/ac/index.php
3 LOVD The purpose of LOVD is to provide a flexible and freely available tool for genomic variant and phenotype collection, display, and curation. LOVD allows both patient-centered and gene-centered views as it is open sourced and released under the GPL license. LOVD is actively being improved. Using Leiden server, LOVD offers free hosting and support of LOVD-powered gene variant databases. [27, 28] https://www.lovd.nl/3.0/publiclist
4 gnomAD An asset created by a global alliance of specialists, with the objective of amassing and blending both exome and genome sequencing information from a wide assortment of huge scope sequencing researches and making rundown information accessible for the more extensive academic local area. The data released by gnomAD are available free of restrictions and proved to be fertile ground for testing new approaches to variant interpretation.Major limitations on analysis is the quality and size of the available reference databases of normal genetic variation and the data is only focused entirely on small variants. http://gnomad.broadinstitute.org
5 dbSNP An information base of short genetic variants that list variations with population-genetic annotations, file germline variants for both rare mutation and polymorphism, and give alleles, genotypes, and their individual frequencies based on their population. Data within dbSNP are available freely and in a variety of forms.There is no requirement or assumption about minimum allele frequencies or functional neutrality for the polymorphisms in the database.The validation code in the SNP record provides some limited information on how the SNP was identified and on the experimental evidence confirming its existence.The quality of the data found on dbSNP has been questioned by many research groups, which suspect high false positive rates due to genotyping and base-calling errors. [29] http://www.ncbi.nlm.nih.gov/snp
6 GenBank A public database that contains 9.9 trillion base pairs from over 2.1 billion nucleotide sequences for 478,000 formally described species. A public database in which nucleotide sequences are available for 400,000 formally described species, and which handles large sequence records.Daily data exchange with the Europe Nucleotide Archive and the DNA Data Bank of Japan ensures worldwide coverage. [30, 31]
7 ClinGen Makes an assembly of organization assets to reform our perception of genomic variants and perk up its use in clinical thought with related data set in ClinVar. The ClinGen variant curation process combines clinical, genetic, population, and functional evidence with expert review to classify variants into 1 of 5 categories, which are pathogenic, likely pathogenic, uncertain, likely benign, and benign according to the ACMG guidelines. [32] https://clinicalgenome.org/
8 ClinVar Totals data on variation of sequence and its association to human wellbeing and giving affirmations of variation that are of clinical significance. In December 2019, ClinVar reached the milestone of 1 million submitted records, representing more than half a million variants. ClinVar allows a user to “follow” a particular variant and be notified if the overall clinical interpretation in ClinVar changes, for example from a pathogenic category to a non-pathogenic one. This feature makes it easier for a laboratory to become aware of variants that may need to be re-evaluated, and for clinicians to know when they should contact their clinical testing laboratory, patient, or both with new information. [7, 23] http://www.ncbi.nlm.nih.gov/clinvar
Tools
1 Phenotype Based Gene Analyzer (Phenolyzer) An instrument zeroing in on finding genes dependent on client explicit disease or phenotype terms. Phenolyzer includes 5 components and works based on an intuitive approach.Phenolyzer exhibits superior performance over competing methods for prioritizing Mendelian and complex disease genes, based on disease or phenotype terms entered as free text.Compared to wANNOVAR, Phenolyzer is better at prioritizing candidate genes for Mendelian diseases and complex diseases. [33] http://phenolyzer.wglab.org/
2 VarAFT software Provides annotation and determines human disease-causing mutations by accessing various levels of data. It combines information from the dbNSFP and ANNOVAR, OMIM, HPO, Gene Ontology, pathways (Reactome), KEGG, PID, predictions from UMD-Predictor, and HSF.The filtration features the prioritization of candidate mutations and it is a freely available software. [34] http://varaft.eu
3 Ensembl A product framework of genome data sets for vertebrates and other eukaryotic species, which delivers and keeps up programed annotation on chosen eukaryotic genomes The framework indicates the role played by variant effect prediction (VEP) “plugins” in expanding variant functionality, and the plugins considered include Missense Tolerance Ratio (MTR) and Rare Exome Variant Ensemble Learner (REVEL); additionally, the variant data integration from NCBI dbSNP and European Variation Archive (EVA) is considered, as well as the population frequency data from Genome Aggregation Database (gnomAD).It displays variant locations on experimentally derived 3D protein structures. [35, 36, 37] http://www.ensembl.org
4 SNPnexus An online variant annotation instrument intended to improve and aid the determination and prioritization of known and novel genomic alterations It applies DeepSEA scoring algorithm for non-coding variants and CGI for identification of somatic alterations.Genes are linked to associated pathways using Reactome. [38, 39]https://www.snp-nexus.org/v4/
5 UCSC genome browser An online instrument for rapidly showing a mentioned segment of a genome at any magnitude, joined by a progression of aligned annotation “tracks” Researchers are able to customize their annotation track based on the track hubs available in the genome browser.The framework allows a broad selection of annotation track; for example, GTEx Gene track, which is used to display gene expression levels across various tissue types; NCBI RefSeq tracks; and gnomAD, which is used for whole genome and whole exome datasets. [40, 41, 42, 43, 44] http://www.genome.ucsc.edu/
6 COSMIC A worldwide asset infiltrating the world literature on somatic mutations in human cancer It provides functional descriptions of cancer genes and consists of 2 tiers of CGC to classify genes based on their strength of evidence associated to their role in cancer.A new platform of COSMIC-3D, for understanding of cancer mutations in 3D protein structure [45, 46, 47] http://www.sanger.ac.uk/perl/genetics/CGP/cosmic
7 ITHANET A global site devoted to thalassemia and different hemoglobinopathies, which gives free admittance to data sets and devices applicable to various parts of hemoglobinopathies, for example, sequence variations, epidemiology, and phenotype The website provides the most recent content update with its friendly user interface and is easy to navigate. It provides multiple external links to other databases. [48, 49] https://www.ithanet.eu/
8 Genenames.org The HGNC based at EMBL-EBI assigns unique symbols and names to human genes. It contains almost 42,000 approved gene symbols, over 19,000 of which represent protein-coding genes, and displays all approved nomenclature within Symbol Reports that contain data curated by HGNC editors and links to related genomic, phenotypic, and proteomic information.It is accessible via https://www.genenames.org [50, 51, 52]
Consortium
1 ICGC The ICGC is a global initiative to build a comprehensive catalog of mutational abnormalities in the major tumor types. ICGC's Data Portal is a user-friendly platform for efficient visualization, analysis, and interpretation of large, diverse cancer datasets. The portal currently consists of data from 84 worldwide cancer projects, collectively representing about 77 million somatic mutations and molecular data from over 20,000 contributors.The ICGC dataset comprises several high-level data types, including donor, gene, mutation, and cancer drug. To support fast, simultaneous querying of these entities and their relationships, the ICGC developed a sophisticated search framework based on the document-oriented indexing technology Elasticsearch (https://www.elastic.co/), a distributed search and analytics engine that features fast query speed, massive scalability, and flexible JSON schemas. It takes ~100 ms in a search across the 77 million ICGC mutations to retrieve the 10 most frequent mutations found in brain cancer donors and those that occur within genes cataloged in the COSMIC CGC (https://cancer.sanger.ac.uk/census). [53]
Project
1 100,000 Genome Project The biggest worldwide coordinated effort, which has sequenced 100,000 genomes from around 85,000 NHS patients influenced by an uncommon disease, or malignant growth The 100,000 Genomes Project aims to sequence 100,000 genomes from NHS patients with cancer and rare diseases. Data collected from the 100,000 Genomes Project can inform research on rare diseases, or benefit patient care potentially by streamlining the diagnostic process and tailoring care to the individual.The project was established to sequence 100,000 genomes from around 85,000 NHS patients affected by a rare disease, or cancer.The Project would also create a new genomic medicine service for the NHS – transforming the way people are cared for and bringing advanced diagnosis and personalized treatments to all those who need them.The 100,000 Genomes Project improves the field of molecular medicine through the improvement of diagnosis of disease, earlier detection of genetic predispositions to disease, rational drug design, gene therapy, and control systems for drugs and pharmacogenomics “custom drugs.”The Human Genome Project could help with the diagnosis and prevention of human disease, which allow to modify medication for more effective treatment cycles, improve criminal justice proceedings, helped to boost the economy and can help more than just humans.The Human Genome Project may cause a loss in human diversity, by developing a trend in “designer” humans. Its information could be used to form new biological weapons and could become the foundation of genetic racism as it would be most accessible to wealthy cultures. [54] https://www.genomicseng-land.co.uk/about-genomics-england/the-100000-genomes-project/
2 GENCODE A project to identify and classify all gene features in the human and mouse genomes with high accuracy based on biological evidence, and to release these annotations for the benefit of biomedical research and genome interpretation The project annotates human and mouse genes and transcripts supported by experimental data with high accuracy, providing a foundational resource that supports genome biology and clinical genomics.GenCode annotation is accessible via Ensembl, the UCSC Genome Browser, and https://www.gencodegenes.org [55, 56, 57]
Guidelines
1 ACMG Guidelines An established guidance for the interpretation of sequence variants. It provides the guidelines of variant classification, namely “pathogenic,” “likely pathogenic,” “uncertain significance,” “likely benign,” and “benign,” based on criteria using typical types of variant evidence (population data, computational data, functional data, segregation data, etc.).These 5 features are applied to the ClinVar database. [58] https://www.acmg.net/docs/standards_guidelines_for_the_interpretation_of_sequence_variants.pdf
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