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      TBProfiler for automated calling of the association with drug resistance of variants in Mycobacterium tuberculosis

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          Abstract

          Following a huge global effort, the first World Health Organization (WHO)-endorsed catalogue of 17,356 variants in the Mycobacterium tuberculosis complex along with their classification as associated with resistance (interim), not associated with resistance (interim) or uncertain significance was made public In June 2021. This marks a critical step towards the application of next generation sequencing (NGS) data for clinical care. Unfortunately, the variant format used makes it difficult to look up variants when NGS data is generated by other bioinformatics pipelines. Furthermore, the large number of variants of uncertain significance in the catalogue hamper its useability in clinical practice. We successfully converted 98.3% of variants from the WHO catalogue format to the standardized HGVS format. We also created TBProfiler version 4.4.0 to automate the calling of all variants located in the tier 1 and 2 candidate resistance genes along with their classification when listed in the WHO catalogue. Using a representative sample of 339 clinical isolates from South Africa containing 691 variants in a tier 1 or 2 gene, TBProfiler classified 105 (15%) variants as conferring resistance, 72 (10%) as not conferring resistance and 514 (74%) as unclassified, with an average of 29 unclassified variants per isolate. Using a second cohort of 56 clinical isolates from a TB outbreak in Spain containing 21 variants in the tier 1 and 2 genes, TBProfiler classified 13 (61.9%) as unclassified, 7 (33.3%) as not conferring resistance, and a single variant (4.8%) classified as conferring resistance. Continued global efforts using standardized methods for genotyping, phenotyping and bioinformatic analyses will be essential to ensure that knowledge on genomic variants translates into improved patient care.

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          Standards and Guidelines for the Interpretation of Sequence Variants: A Joint Consensus Recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology

          The American College of Medical Genetics and Genomics (ACMG) previously developed guidance for the interpretation of sequence variants. 1 In the past decade, sequencing technology has evolved rapidly with the advent of high-throughput next generation sequencing. By adopting and leveraging next generation sequencing, clinical laboratories are now performing an ever increasing catalogue of genetic testing spanning genotyping, single genes, gene panels, exomes, genomes, transcriptomes and epigenetic assays for genetic disorders. By virtue of increased complexity, this paradigm shift in genetic testing has been accompanied by new challenges in sequence interpretation. In this context, the ACMG convened a workgroup in 2013 comprised of representatives from the ACMG, the Association for Molecular Pathology (AMP) and the College of American Pathologists (CAP) to revisit and revise the standards and guidelines for the interpretation of sequence variants. The group consisted of clinical laboratory directors and clinicians. This report represents expert opinion of the workgroup with input from ACMG, AMP and CAP stakeholders. These recommendations primarily apply to the breadth of genetic tests used in clinical laboratories including genotyping, single genes, panels, exomes and genomes. This report recommends the use of specific standard terminology: ‘pathogenic’, ‘likely pathogenic’, ‘uncertain significance’, ‘likely benign’, and ‘benign’ to describe variants identified in Mendelian disorders. Moreover, this recommendation describes a process for classification of variants into these five categories based on criteria using typical types of variant evidence (e.g. population data, computational data, functional data, segregation data, etc.). Because of the increased complexity of analysis and interpretation of clinical genetic testing described in this report, the ACMG strongly recommends that clinical molecular genetic testing should be performed in a CLIA-approved laboratory with results interpreted by a board-certified clinical molecular geneticist or molecular genetic pathologist or equivalent.
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            A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3.

            We describe a new computer program, SnpEff, for rapidly categorizing the effects of variants in genome sequences. Once a genome is sequenced, SnpEff annotates variants based on their genomic locations and predicts coding effects. Annotated genomic locations include intronic, untranslated region, upstream, downstream, splice site, or intergenic regions. Coding effects such as synonymous or non-synonymous amino acid replacement, start codon gains or losses, stop codon gains or losses, or frame shifts can be predicted. Here the use of SnpEff is illustrated by annotating ~356,660 candidate SNPs in ~117 Mb unique sequences, representing a substitution rate of ~1/305 nucleotides, between the Drosophila melanogaster w(1118); iso-2; iso-3 strain and the reference y(1); cn(1) bw(1) sp(1) strain. We show that ~15,842 SNPs are synonymous and ~4,467 SNPs are non-synonymous (N/S ~0.28). The remaining SNPs are in other categories, such as stop codon gains (38 SNPs), stop codon losses (8 SNPs), and start codon gains (297 SNPs) in the 5'UTR. We found, as expected, that the SNP frequency is proportional to the recombination frequency (i.e., highest in the middle of chromosome arms). We also found that start-gain or stop-lost SNPs in Drosophila melanogaster often result in additions of N-terminal or C-terminal amino acids that are conserved in other Drosophila species. It appears that the 5' and 3' UTRs are reservoirs for genetic variations that changes the termini of proteins during evolution of the Drosophila genus. As genome sequencing is becoming inexpensive and routine, SnpEff enables rapid analyses of whole-genome sequencing data to be performed by an individual laboratory.
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              HGVS Recommendations for the Description of Sequence Variants: 2016 Update.

              The consistent and unambiguous description of sequence variants is essential to report and exchange information on the analysis of a genome. In particular, DNA diagnostics critically depends on accurate and standardized description and sharing of the variants detected. The sequence variant nomenclature system proposed in 2000 by the Human Genome Variation Society has been widely adopted and has developed into an internationally accepted standard. The recommendations are currently commissioned through a Sequence Variant Description Working Group (SVD-WG) operating under the auspices of three international organizations: the Human Genome Variation Society (HGVS), the Human Variome Project (HVP), and the Human Genome Organization (HUGO). Requests for modifications and extensions go through the SVD-WG following a standard procedure including a community consultation step. Version numbers are assigned to the nomenclature system to allow users to specify the version used in their variant descriptions. Here, we present the current recommendations, HGVS version 15.11, and briefly summarize the changes that were made since the 2000 publication. Most focus has been on removing inconsistencies and tightening definitions allowing automatic data processing. An extensive version of the recommendations is available online, at http://www.HGVS.org/varnomen.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: SoftwareRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: SoftwareRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: InvestigationRole: MethodologyRole: SoftwareRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                PLOS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                30 December 2022
                2022
                : 17
                : 12
                : e0279644
                Affiliations
                [1 ] Torch Consortium FAMPOP Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
                [2 ] ADReM Data Lab, Department of Computer Science, University of Antwerp, Antwerp, Belgium
                [3 ] Faculty of Infectious and Tropical Diseases, Department of Infection Biology, London School of Hygiene and Tropical Medicine, London, United Kingdom
                Newcastle University, UK, UNITED KINGDOM
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0002-5647-5852
                https://orcid.org/0000-0001-8323-7019
                Article
                PONE-D-22-28354
                10.1371/journal.pone.0279644
                9803136
                36584023
                4f20ba4c-5ee5-40e2-9090-6334086b3534
                © 2022 Verboven et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 13 October 2022
                : 12 December 2022
                Page count
                Figures: 8, Tables: 3, Pages: 15
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100003130, Fonds Wetenschappelijk Onderzoek;
                Award ID: 1SB4519N
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100003130, Fonds Wetenschappelijk Onderzoek;
                Award ID: G0F8316N
                Award Recipient :
                LV, 1SB4519N, Fonds Wetenschappelijk Onderzoek, https://www.fwo.be/ AVR, G0F8316N, Fonds Wetenschappelijk Onderzoek, https://www.fwo.be/.
                Categories
                Research Article
                Computer and Information Sciences
                Library Science
                Catalogs
                Biology and Life Sciences
                Biochemistry
                Nucleotides
                Biology and Life Sciences
                Organisms
                Bacteria
                Actinobacteria
                Mycobacterium Tuberculosis
                Medicine and Health Sciences
                Medical Conditions
                Infectious Diseases
                Bacterial Diseases
                Tuberculosis
                Extensively Drug-Resistant Tuberculosis
                Medicine and Health Sciences
                Medical Conditions
                Tropical Diseases
                Tuberculosis
                Extensively Drug-Resistant Tuberculosis
                Biology and Life Sciences
                Genetics
                Genomics
                Medicine and Health Sciences
                Diagnostic Medicine
                Tuberculosis Diagnosis and Management
                Biology and life sciences
                Genetics
                DNA
                DNA structure
                Sense Strands
                Biology and life sciences
                Biochemistry
                Nucleic acids
                DNA
                DNA structure
                Sense Strands
                Biology and life sciences
                Molecular biology
                Macromolecular structure analysis
                DNA structure
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                Biology and Life Sciences
                Genetics
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