Allele Nomenclature Research Articles

PharmVar GeneFocus: CYP4F2.

The Pharmacogene Variation Consortium (PharmVar) serves as a global repository providing star (*) allele nomenclature for the polymorphic human CYP4F2 gene. CYP4F2 genetic variation impacts the metabolism of vitamin K, which is associated with warfarin dose requirements, and the metabolism of drugs, such as imatinib or fingolimod, and certain endogenous compounds including vitamin E and eicosanoids. This GeneFocus provides a comprehensive overview and summary of CYP4F2 genetic variation including the characterization of 14 novel star alleles, CYP4F2*4 through *17. A description of how haplotype information cataloged by PharmVar is utilized by the Pharmacogenomics Knowledgebase (PharmGKB) and the Clinical Pharmacogenetics Implementation Consortium (CPIC) is also provided.

Contradiction in Star-Allele Nomenclature of Pharmacogenes between Common Haplotypes and Rare Variants.

The nomenclature of star alleles has been widely used in pharmacogenomics to enhance treatment outcomes, predict drug response variability, and reduce adverse reactions. However, the discovery of numerous rare functional variants through genome sequencing introduces complexities into the star-allele system. This study aimed to assess the nature and impact of the rapid discovery of numerous rare functional variants in the traditional haplotype-based star-allele system. We developed a new method to construct haplogroups, representing a common ancestry structure, by iteratively excluding rare and functional variants of the 25 representative pharmacogenes using the 2504 genomes from the 1000 Genomes Project. In total, 192 haplogroups and 288 star alleles were identified, with an average of 7.68 ± 4.2 cross-ethnic haplogroups per gene. Most of the haplogroups (70.8%, 136/192) were highly aligned with their corresponding classical star alleles (VI = 1.86 ± 0.78), exhibiting higher genetic diversity than the star alleles. Approximately 41.3% (N = 119) of the star alleles in the 2504 genomes did not belong to any of the haplogroups, and most of them (91.3%, 105/116) were determined by a single variant according to the allele-definition table provided by CPIC. These functional single variants had low allele frequency (MAF < 1%), high evolutionary conservation, and variant deleteriousness, which suggests significant negative selection. It is suggested that the traditional haplotype-based naming system for pharmacogenetic star alleles now needs to be adjusted by balancing both traditional haplotyping and newly emerging variant-sequencing approaches to reduce naming complexity.

Mouse Genome Informatics: an integrated knowledgebase system for the laboratory mouse.

Mouse Genome Informatics (MGI) is a federation of expertly curated information resources designed to support experimental and computational investigations into genetic and genomic aspects of human biology and disease using the laboratory mouse as a model system. The Mouse Genome Database (MGD) and the Gene Expression Database (GXD) are core MGI databases that share data and system architecture. MGI serves as the central community resource of integrated information about mouse genome features, variation, expression, gene function, phenotype, and human disease models acquired from peer-reviewed publications, author submissions, and major bioinformatics resources. To facilitate integration and standardization of data, biocuration scientists annotate using terms from controlled metadata vocabularies and biological ontologies (e.g. Mammalian Phenotype Ontology, Mouse Developmental Anatomy, Disease Ontology, Gene Ontology, etc.), and by applying international community standards for gene, allele, and mouse strain nomenclature. MGI serves basic scientists, translational researchers, and data scientists by providing access to FAIR-compliant data in both human-readable and compute-ready formats. The MGI resource is accessible at https://informatics.jax.org. Here, we present an overview of the core data types represented in MGI and highlight recent enhancements to the resource with a focus on new data and functionality for MGD and GXD.

Allelic Variations in Vernalization (Vrn) Genes in Triticum spp.

Rapid climate changes, with higher warming rates during winter and spring seasons, dramatically affect the vernalization requirements, one of the most critical processes for the induction of wheat reproductive growth, with severe consequences on flowering time, grain filling, and grain yield. Specifically, the Vrn genes play a major role in the transition from vegetative to reproductive growth in wheat. Recent advances in wheat genomics have significantly improved the understanding of the molecular mechanisms of Vrn genes (Vrn-1, Vrn-2, Vrn-3, and Vrn-4), unveiling a diverse array of natural allelic variations. In this review, we have examined the current knowledge of Vrn genes from a functional and structural point of view, considering the studies conducted on Vrn alleles at different ploidy levels (diploid, tetraploid, and hexaploid). The molecular characterization of Vrn-1 alleles has been a focal point, revealing a diverse array of allelic forms with implications for flowering time. We have highlighted the structural complexity of the different allelic forms and the problems linked to the different nomenclature of some Vrn alleles. Addressing these issues will be crucial for harmonizing research efforts and enhancing our understanding of Vrn gene function and evolution. The increasing availability of genome and transcriptome sequences, along with the improvements in bioinformatics and computational biology, offers a versatile range of possibilities for enriching genomic regions surrounding the target sites of Vrn genes, paving the way for innovative approaches to manipulate flowering time and improve wheat productivity.

Distributed genotyping and clustering of Neisseria strains reveal continual emergence of epidemic meningococcus over a century

Core genome multilocus sequence typing (cgMLST) is commonly used to classify bacterial strains into different types, for taxonomical and epidemiological applications. However, cgMLST schemes require central databases for the nomenclature of new alleles and sequence types, which must be synchronized worldwide and involve increasingly intensive calculation and storage demands. Here, we describe a distributed cgMLST (dcgMLST) scheme that does not require a central database of allelic sequences and apply it to study evolutionary patterns of epidemic and endemic strains of the genus Neisseria. We classify 69,994 worldwide Neisseria strains into multi-level clusters that assign species, lineages, and local disease outbreaks. We divide Neisseria meningitidis into 168 endemic lineages and three epidemic lineages responsible for at least 9 epidemics in the past century. According to our analyses, the epidemic and endemic lineages experienced very different population dynamics in the past 100 years. Epidemic lineages repetitively emerged from endemic lineages, disseminated worldwide, and apparently disappeared rapidly afterward. We propose a stepwise model for the evolutionary trajectory of epidemic lineages in Neisseria, and expect that the development of similar dcgMLST schemes will facilitate epidemiological studies of other bacterial pathogens.

Revised fission yeast gene and allele nomenclature guidelines for machine readability.

Standardized nomenclature for genes, gene products, and isoforms is crucial to prevent ambiguity and enable clear communication of scientific data, facilitating efficient biocuration and data sharing. Standardized genotype nomenclature, which describes alleles present in a specific strain that differ from those in the wild-type reference strain, is equally essential to maximize research impact and ensure that results linking genotypes to phenotypes are Findable, Accessible, Interoperable, and Reusable (FAIR). In this publication, we extend the fission yeast clade gene nomenclature guidelines to support the curation efforts at PomBase (www.pombase.org), the Schizosaccharomyces pombe Model Organism Database. This update introduces nomenclature guidelines for noncoding RNA genes, following those set forth by the Human Genome Organisation Gene Nomenclature Committee. Additionally, we provide a significant update to the allele and genotype nomenclature guidelines originally published in 1987, to standardize the diverse range of genetic modifications enabled by the fission yeast genetic toolbox. These updated guidelines reflect a community consensus between numerous fission yeast researchers. Adoption of these rules will improve consistency in gene and genotype nomenclature, and facilitate machine-readability and automated entity recognition of fission yeast genes and alleles in publications or datasets. In conclusion, our updated guidelines provide a valuable resource for the fission yeast research community, promoting consistency, clarity, and FAIRness in genetic data sharing and interpretation.

Abstract 14: The impact of genetic background on cancer phenotypes of mouse models

Abstract The laboratory mouse is the premier animal model system for in vivo studies of the genetic and genomic basis of cancer in humans. Although thousands of mouse models have been generated, finding relevant data and knowledge about these models is complicated by a general lack of compliance in the published literature with nomenclature and annotation standards for genes, alleles, mouse strains, and cancer types. The Mouse Models of Human Cancer database (MMHCdb; tumor.informatics.jax.org) is an expertly curated knowledgebase of cancer phenotypes reported for diverse types of mouse models of human cancer such as inbred mouse strains, genetically engineered mouse models (GEMMs), Patient Derived Xenografts (PDXs), and mouse genetic diversity panels (e.g., the Collaborative Cross). MMHCdb includes data on more than 60,000 mouse models for over 1200 tumor classifications curated from more than 25,000 peer-reviewed publications. One of the primary goals of the MMHCdb is to highlight the impact of genetic background on the incidence and presentation of different tumor types in mice. The same allele on different backgrounds can result in very different cancer characteristics and, therefore, impact the appropriateness of a model for a specific research application. In MMHCdb, users can review the impact of genetic background on the frequency of spontaneous tumors for inbred mouse strains using an interactive table generated from different published and unpublished data sources. In addition, color-coded tabular summaries of individual papers are available that allow researchers to quickly assess how genetic background affects cancer phenotypes in the mouse models reported in a specific publication. We will highlight examples of how genetic background can profoundly change the types and frequencies of tumor types that can be expected in mouse models of human cancer. MMHCdb is supported by NCI R01 CA089713 Citation Format: Dale A. Begley, Debra M. Krupke, Steven B. Neuhauser, Emily L. Jocoy, John P. Sundberg, Carol J. Bult. The impact of genetic background on cancer phenotypes of mouse models [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 14.

The Mouse Models of Human Cancer database (MMHCdb)

The laboratory mouse has served for decades as an informative animal model system for investigating the genetic and genomic basis of cancer in humans. Although thousands of mouse models have been generated, compiling and aggregating relevant data and knowledge about these models is hampered by a general lack of compliance, in the published literature, with nomenclature and annotation standards for genes, alleles, mouse strains and cancer types. The Mouse Models of Human Cancer database (MMHCdb) is an expertly curated, comprehensive knowledgebase of diverse types of mouse models of human cancer, including inbred mouse strains, genetically engineered mouse models, patient-derived xenografts, and mouse genetic diversity panels such as the Collaborative Cross. The MMHCdb is a FAIR-compliant knowledgebase that enforces nomenclature and annotation standards, and supports the completeness and accuracy of searches for mouse models of human cancer and associated data. The resource facilitates the analysis of the impact of genetic background on the incidence and presentation of different tumor types, and aids in the assessment of different mouse strains as models of human cancer biology and treatment response.

Antibody Sequence and Structure Analyses Using IMGT®: 30 Years of Immunoinformatics.

IMGT®, the international ImMunoGeneTics information system®, http://www.imgt.org , the global reference in immunogenetics and immunoinformatics, was created in 1989 by Marie-Paule Lefranc (Université de Montpellier and CNRS) to manage the huge diversity of the antigen receptors, immunoglobulins (IG) or antibodies, and T cell receptors (TR) of the adaptive immune responses. The founding of IMGT® marked the advent of immunoinformatics, which emerged at the interface between immunogenetics and bioinformatics. IMGT® standardized analysis of the IG, TR, and major histocompatibility (MH) genes and proteins bridges the gap between sequences and three-dimensional (3D) structures, for all jawed vertebrates from fish to humans. This is achieved through the IMGT Scientific chart rules, based on the IMGT-ONTOLOGY axioms, and primarily CLASSIFICATION (IMGT gene and allele nomenclature) and NUMEROTATION (IMGT unique numbering and IMGT Colliers de Perles). IMGT® comprises seven databases (IMGT/LIGM-DB for nucleotide sequences, IMGT/GENE-DB for genes and alleles, etc.), 17 tools (IMGT/V-QUEST, IMGT/JunctionAnalysis, IMGT/HighV-QUEST for NGS, etc.), and more than 20,000 Web resources. In this chapter, the focus is on the tools for amino acid sequences per domain (IMGT/DomainGapAlign and IMGT/Collier-de-Perles), and on the databases for receptors (IMGT/2Dstructure-DB and IMGT/3D-structure-DB) described per receptor, chain, and domain and, for 3D, with contact analysis, paratope, and epitope. The IMGT/mAb-DB is the query interface for monoclonal antibodies (mAb), fusion proteins for immune applications (FPIA), composite proteins for clinical applications (CPCA), and related proteins of interest (RPI) with links to IMGT® 2D and 3D databases and to the World Health Organization (WHO) International Nonproprietary Names (INN) program lists. The chapter includes the human IG allotypes and antibody engineered variants for effector properties used in the description of therapeutical mAb.

An ambiguous sequence-based allele of SE33

SE33 was a well-known autosomal short tandem repeat (STR) marker that was high polymorphic and therefore was high discrimination power. The sequence structure of STR markers has been increasingly explored with next-generation sequencing (NGS) technology. The sequencing resulted in the development of a new locus designation and allele nomenclature that was also backward compatible with the conventional capillary electrophoresis. SE33 was one of the STR markers that had been coamplified by Forenseq™ Signature Prep Kit (Verogen) but were not analyzed and illustrated in the Universal Analysis Software (UAS) (Verogen). This study reported an ambiguous sequence-based allele 16.3 of the SE33 locus. This allele was observed while analyzed by STRait Razor 3.0. The configuration file was modified from the previous studies to include 15 bp of 5′ flanking region and 24 bp of 3′ flanking region. The ambiguous allele was called 16.3 (106 bp) with a read count of 2070. However, the sequence of the repeat region cannot be designated as allele 16.3. Several possible scenarios for allele designation were presented and discussed.

International Society of Blood Transfusion Working Party on Red Cell Immunogenetics and Blood Group Terminology Report of Basel and three virtual business meetings: Update on blood group systems.

Under the ISBT, the Working Party (WP) for Red Cell Immunogenetics and Blood Group Terminology is charged with ratifying blood group systems, antigens and alleles. This report presents the outcomes from four WP business meetings, one located in Basel in 2019 and three held as virtual meetings during the COVID-19 pandemic in 2020 and 2021. As in previous meetings, matters pertaining to blood group antigen nomenclature were discussed. New blood group systems and antigens were approved and named according to the serologic, genetic, biochemical and cell biological evidence presented. Seven new blood group systems, KANNO (defined numerically as ISBT 037), SID (038), CTL2 (039), PEL (040), MAM (041), EMM (042) and ABCC1 (043) were ratified. Two (039 and 043) were de novo discoveries, and the remainder comprised reported antigens where the causal genes were previously unknown. A further 15 blood group antigens were added to the existing blood group systems: MNS (002), RH (004), LU (005), DI (010), SC (013), GE (020), KN (022), JMH (026) and RHAG (030). The ISBT now recognizes 378 antigens, of which 345 are clustered within 43 blood group systems while 33 still have an unknown genetic basis. The ongoing discovery of new blood group systems and antigens underscores the diverse and complex biology of the red cell membrane. The WP continues to update the blood group antigen tables and the allele nomenclature tables. These can be found on the ISBT website (http://www.isbtweb.org/working-parties/red-cell-immunogenetics-and-blood-group-terminology/).

PharmVar GeneFocus: SLCO1B1.

The Pharmacogene Variation Consortium (PharmVar) is now providing star (*) allele nomenclature for the highly polymorphic human SLCO1B1 gene encoding the organic anion transporting polypeptide 1B1 (OATP1B1) drug transporter. Genetic variation within the SLCO1B1 gene locus impacts drug transport, which can lead to altered pharmacokinetic profiles of several commonly prescribed drugs. Variable OATP1B1 function is of particular importance regarding hepatic uptake of statins and the risk of statin-associated musculoskeletal symptoms. To introduce this important drug transporter gene into the PharmVar database and serve as a unified reference of haplotype variation moving forward, an international group of gene experts has performed an extensive review of all published SLCO1B1 star alleles. Previously published star alleles were self-assigned by authors and only loosely followed the star nomenclature system that was first developed for cytochrome P450 genes. This nomenclature system has been standardized by PharmVar and is now applied to other important pharmacogenes such as SLCO1B1. In addition, data from the 1000 Genomes Project and investigator-submitted data were utilized to confirm existing haplotypes, fill knowledge gaps, and/or define novel star alleles. The PharmVar-developed SLCO1B1 nomenclature has been incorporated by the Clinical Pharmacogenetics Implementation Consortium (CPIC) 2022 guideline on statin-associated musculoskeletal symptoms.

Abstract 1190: MMHCdb: A knowledgebase for the evolving landscape of mouse models of human cancer

Abstract The laboratory mouse is the premier mammalian model organism for interrogating the genetic and molecular basis of human cancer and for preclinical investigations into targets for the prevention and treatment of cancer. The distributed and heterogenous nature of information about these model systems makes it difficult for researchers to integrate and interpret the information to determine the state of the field and to identify the most relevant models for basic and preclinical research. The Mouse Models of Human Cancer database (http://tumor.informatics.jax.org) is an expertly curated knowledgebase about genetically defined mouse strains and Patient Derived Xenograft (PDX) models of human cancer. Data in MMHCdb are obtained from peer-reviewed scientific publications and direct data submissions from individual investigators and large-scale programs. MMHCdb is built on FAIR data management principles (Findable, Accessible, Interoperable, Reusable). The enforcement of metadata standards and official gene, allele and strain nomenclature ensure accurate and comprehensive search results for cancer models. MMHCdb has long represented data from spontaneous or endogenously induced tumors from genetically defined mice and for PDXs which have been the foundation of basic cancer research and preclinical studies for decades. MMHCdb has expanded to include cancer models such as Diversity Outbred and Collaborative Cross mice which are ideally suited for research into the relationship of genetic variation with cancer susceptibility and for modeling the genetics of variability in treatment responses. The MMHCdb contains over 109,266 curated tumor frequency records for over 8,275 mouse strains. Tumor types in the database have been indexed to over 21,000 literature citations. PDX models and data available in MMHCdb are also accessible from the Patient Derived Cancer Models resource at EMBL-EBI which currently provides information for over 4,000 PDXs (https://cancermodels.org).MMHCdb is supported by NCI R01 CA089713 Citation Format: Dale A. Begley, Debbie M. Krupke, Steven Neuhauser, John Sundberg, Carol J. Bult. MMHCdb: A knowledgebase for the evolving landscape of mouse models of human cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1190.

PharmVar GeneFocus: CYP3A5.

The Pharmacogene Variation Consortium (PharmVar) catalogs star (*) allele nomenclature for the polymorphic human CYP3A5 gene. Genetic variation within the CYP3A5 gene locus impacts the metabolism of several clinically important drugs, including the immunosuppressants tacrolimus, sirolimus, cyclosporine, and the benzodiazepine midazolam. Variable CYP3A5 activity is of clinical importance regarding tacrolimus metabolism. This GeneFocus provides a CYP3A5 gene summary with a focus on aspects regarding standardized nomenclature. In addition, this review also summarizes recent changes and updates, including the retirement of several allelic variants and provides an overview of how PharmVar CYP3A5 star allele nomenclature is utilized by the Pharmacogenomics Knowledgebase (PharmGKB) and the Clinical Pharmacogenetics Implementation Consortium (CPIC).

CYP2C8, CYP2C9, and CYP2C19 Characterization Using Next-Generation Sequencing and Haplotype Analysis: A GeT-RM Collaborative Project

Pharmacogenetic tests typically target selected sequence variants to identify haplotypes that are often defined by star (∗) allele nomenclature. Due to their design, these targeted genotyping assays are unable to detect novel variants that may change the function of the gene product and thereby affect phenotype prediction and patient care. In the current study, 137 DNA samples that were previously characterized by the Genetic Testing Reference Material (GeT-RM) program using a variety of targeted genotyping methods were recharacterized using targeted and whole genome sequencing analysis. Sequence data were analyzed using three genotype calling tools to identify star allele diplotypes for CYP2C8, CYP2C9, and CYP2C19. The genotype calls from next-generation sequencing (NGS) correlated well to those previously reported, except when novel alleles were present in a sample. Six novel alleles and 38 novel suballeles were identified in the three genes due to identification of variants not covered by targeted genotyping assays. In addition, several ambiguous genotype calls from a previous study were resolved using the NGS and/or long-read NGS data. Diplotype calls were mostly consistent between the calling algorithms, although several discrepancies were noted. This study highlights the utility of NGS for pharmacogenetic testing and demonstrates that there are many novel alleles that are yet to be discovered, even in highly characterized genes such as CYP2C9 and CYP2C19.

IMGT/3Dstructure-DB: T-Cell Receptor TR Paratope and Peptide/Major Histocompatibility pMH Contact Sites and Epitope.

T-cell receptors (TR), the antigen receptors of T cells, specifically recognize peptides presented by the major histocompatibility (MH) proteins, as peptide/MH (pMH), on the cell surface. The structure characterization of the trimolecular TR/pMH complexes is crucial to the fields of immunology, vaccination, and immunotherapy. IMGT/3Dstructure-DB is the three-dimensional (3-D) structure database of IMGT®, the international ImMunoGenetics information system®. By its creation, IMGT® marks the advent of immunoinformatics, which emerged at the interface between immunogenetics and bioinformatics. The IMGT® immunoglobulin (IG) and TR gene and allele nomenclature (CLASSIFICATION axiom) and the IMGT unique numbering and IMGT/Collier-de-Perles (NUMEROTATION axiom) are the two founding breakthroughs of immunoinformatics. IMGT-ONTOLOGY concepts and IMGT Scientific chart rules generated from these axioms allowed IMGT® bridging genes, structures, and functions. IMGT/3Dstructure-DB contains 3-D structures of IG or antibodies, TR and MH proteins of the adaptive immune responses of jawed vertebrates (gnathostomata), IG or TR complexes with antigens (IG/Ag, TR/pMH), related proteins of the immune system of any species belonging to the IG and MH superfamilies, and fusion proteins for immune applications. The focus of this chapter is on the TR V domains and MH G domains and the contact analysis comparison in TR/pMH interactions. Standardized molecular characterization includes "IMGT pMH contact sites" for peptide and MH groove interactions and "IMGT paratopes and epitopes" for TR/pMH complexes. Data are available in the IMGT/3Dstructure database, at the IMGT Home page http://www.imgt.org .

Hanges in the occurrence of alleles of the EAB-locus of blood groups in cattle of the kholmogorsky breed due to holsteinization

The aim of the research was to analyze the allele pool and its changes in the EAB locus of blood groups of cattle of the Kholmogory breed using absorption crosses with bulls of the Holstein breed. The study was carried out by the method of immunological testing according to the agglutination reaction. The choice of locus is not accidental, because it is currently the most informative in terms of the nomenclature of alleles. The predominance of alleles of the Kholmogory breed (A2'O', E3'G'G'') is noted with an increase in the frequency of occurrence (G2Y2E1'Q') and the appearance of new alleles specific of the Holstein breed (O1A'2J'2K'O', B2Q 'G'G”, E'3G'Q', B1O2B', O4Y2A2', O4D'E3'F2'G'O'G”). Over the past 5 years, the index of genetic similarity between herds of Kholmogory cattle in the Komi Republic has twofold. It was revealed that in the population of Komi Republic introduced new alleles of the Holstein breed, but at the same time, part of the alleles of Kholmogory cattle, originally obtained from the breeding reserve, are conserved. Such alleles are transfered between generations of animals and may indicate the preservation of the genome structure of the original mother breed under conditions of intensive selection. As well as alleles are transmitted when using purebred, as well as Holsteinized sires of the Pechora type of breed. The gene pool of the native Kholmogory breed is unique and requires further study. Groups of antigens form a unique genetic structure of herds, which can serve to identify animals by relationship, as well as breed affiliation, as it is similarly made by microsatellite loci and SNP markers (ISAG standard). Testing was carried out as sires in the amount of &gt;30 heads, and their breeding reserve for more than 5 years (&gt;5925 cows of breeding herds). Groups of antigens make it possible to evaluate the change in the genetic structure of the population of the Kholmogory breed and other breeds of cattle in time slices and obtain information about the breeder's actions when focusing on specific genetic traits and their genetic variability, breeding traits and evaluate inbreeding (antigenic similarity), and not only to determine the relationship of animals

Prediction of the CYP2D6 enzymatic activity based on investigating of the CYP2D6 genotypes around the vivax malaria patients in Yunnan Province, China

BackgroundIn recent years, the incidence rate of vivax malaria recurrence still had 3.1% in Yunnan Province population after eradication therapy using primaquine (PQ). In order to understand the specific failure reasons for preventing vivax malaria relapses, a preliminary exploration on the CYP2D6 enzyme activity was carried out in the vivax malaria patients in Yunnan Province population by analysing mutational polymorphism in the coding region of CYP2D6 gene.MethodsBlood samples were collected from vivax malaria patients with suspected relapse (SR) and non-relapsed (NR) malaria in Yunnan Province. The DNA fragments containing 9 exons regions of human CYP2D6 gene were amplified by performing PCR and sequenced. The sequencing results were aligned by using DNAStar 11.0 to obtain the coding DNA sequence (CDS) of CYP2D6 gene. DnaSP 6.11.01 software was used to identify mutant polymorphisms and haplotypes of the CDS chain. The waterfall function of GenVisR package in R was utilized to visualize the mutational landscape. The alleles of CYP2D6 gene were identified according to the criteria prescribed by Human Cytochrome P450 (CYP) Allele Nomenclature Committee Database and the CYP2D6 enzyme activity was predicted based on diploid genotype.ResultsA total of 320 maternal CDS chains, including 63 from SR group and 257 from NR group, were obtained. Twelve mutant loci, including c.31 (rs769259), c.100 (rs1065852), c.271 (rs28371703), c.281 (rs28371704), c.294 (rs28371705), c.297 (rs200269944), c.336 (rs1081003), c.408 (rs1058164), c.505 (rs5030865), c.801 (rs28371718), c.886 (rs16947), and c.1,457 (rs1135840) were observed on the 640 CDS chains (including 320 maternal and 320 paternal chains). The high-frequency mutation at rs1135840 (0.703) and low-frequency mutation, such as rs28371703, were detected only in the SR group. The frequency of mutant rs1058164 and rs1135840 were significantly increased in the SR group ({x}^{2}= 4.468, 5.889, P < 0.05), as opposed to the NR group. Of the 23 haplotypes (from Hap_1 to Hap_23), the nomenclatures of 11 allelic forms could be found: Hap_3 was non-mutant, Hap_2 accounted for the highest frequency (36.9%, 236/640), and Hap_9 had the most complex sequence structure, containing 7 loci mutations. Allele *10 was the most frequent among these genotypes (0.423). Among the allele *10 standard named genotypes, *1/*10, *1/*1 and *2/*10 were significantly more frequent in the NR group ({x}^{2}= 3.911, P < 0.05) and all showed uncompromised enzyme activity; the impaired genotype *10/*39 was more frequent in the SR group ({x}^{2}= 10.050, P < 0.05), and genotype *4/*4was detected only in the SR group.ConclusionIn the patients receiving PQ dosage in Yunnan Province population, both rs1135840 single nucleotide polymorphism and *10 allele form was common in the CYP2D6 gene. Low-frequency mutation sites, such as rs28371703, were only presented in patients with vivax malaria relapse.

Establishment of a Publicly Available Core Genome Multilocus Sequence Typing Scheme for Clostridium perfringens.

ABSTRACTClostridium perfringens is a spore-forming anaerobic pathogen responsible for a variety of histotoxic and intestinal infections in humans and animals. High-resolution genotyping aiming to identify bacteria at strain level has become increasingly important in modern microbiology to understand pathogen transmission pathways and to tackle infection sources. This study aimed at establishing a publicly available genome-wide multilocus sequence-typing (MLST) scheme for C. perfringens. A total of 1,431 highly conserved core genes (1.34 megabases; 50% of the reference genome genes) were indexed for a core genome-based MLST (cgMLST) scheme for C. perfringens. The scheme was applied to 282 ecologically and geographically diverse genomes, showing that the genotyping results of cgMLST were highly congruent with the core genome-based single-nucleotide-polymorphism typing in terms of resolution and tree topology. In addition, the cgMLST provided a greater discrimination than classical MLST methods for C. perfringens. The usability of the scheme for outbreak analysis was confirmed by reinvestigating published outbreaks of C. perfringens-associated infections in the United States and the United Kingdom. In summary, a publicly available scheme and an allele nomenclature database for genomic typing of C. perfringens have been established and can be used for broad-based and standardized epidemiological studies.IMPORTANCE Global epidemiological surveillance of bacterial pathogens is enhanced by the availability of standard tools and sharing of typing data. The use of whole-genome sequencing has opened the possibility for high-resolution characterization of bacterial strains down to the clonal and subclonal levels. Core genome multilocus sequence typing is a robust system that uses highly conserved core genes for deep genotyping. The method has been successfully and widely used to describe the epidemiology of various bacterial species. Nevertheless, a cgMLST typing scheme for Clostridium perfringens is currently not publicly available. In this study, we (i) developed a cgMLST typing scheme for C. perfringens, (ii) evaluated the performance of the scheme on different sets of C. perfringens genomes from different hosts and geographic regions as well as from different outbreak situations, and, finally, (iii) made this scheme publicly available supported by an allele nomenclature database for global and standard genomic typing.

Mouse Genome Informatics (MGI): latest news from MGD and GXD

The Mouse Genome Informatics (MGI) database system combines multiple expertly curated community data resources into a shared knowledge management ecosystem united by common metadata annotation standards. MGI’s mission is to facilitate the use of the mouse as an experimental model for understanding the genetic and genomic basis of human health and disease. MGI is the authoritative source for mouse gene, allele, and strain nomenclature and is the primary source of mouse phenotype annotations, functional annotations, developmental gene expression information, and annotations of mouse models with human diseases. MGI maintains mouse anatomy and phenotype ontologies and contributes to the development of the Gene Ontology and Disease Ontology and uses these ontologies as standard terminologies for annotation. The Mouse Genome Database (MGD) and the Gene Expression Database (GXD) are MGI’s two major knowledgebases. Here, we highlight some of the recent changes and enhancements to MGD and GXD that have been implemented in response to changing needs of the biomedical research community and to improve the efficiency of expert curation. MGI can be accessed freely at http://www.informatics.jax.org.