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This article provides nomenclature recommendations developed by an international workgroup to increase transparency and standardization of pharmacogenetic (PGx) result reporting. Presently, sequence variants identified by PGx tests are described using different nomenclature systems. In addition, PGx analysis may detect different sets of variants for each gene, which can affect interpretation of results. This practice has caused confusion and may thereby impede the adoption of clinical PGx testing. Standardization is critical to move PGx forward. [ABSTRACT FROM AUTHOR]

Abstract Previously, the majority of the human genome was thought to be 'junk' DNA with no functional purpose. Over the past decade, the field of RNA research has rapidly expanded, with a concomitant increase in the number of non-protein coding RNA (ncRNA) genes identified in this 'junk'. Many of the encoded ncRNAs have already been shown to be essential for a variety of vital functions, and this wealth of annotated human ncRNAs requires standardised naming in order to aid effective communication. The HUGO Gene Nomenclature Committee (HGNC) is the only organisation authorised to assign standardised nomenclature to human genes. Of the 30,000 approved gene symbols currently listed in the HGNC database (http://www.genenames.org/search), the majority represent protein-coding genes; however, they also include pseudogenes, phenotypic loci and some genomic features. In recent years the list has also increased to include almost 3,000 named human ncRNA genes. HGNC is actively engaging with the RNA research community in order to provide unique symbols and names for each sequence that encodes an ncRNA. Most of the classical small ncRNA genes have now been provided with a unique nomenclature, and work on naming the long (> 200 nucleotides) non-coding RNAs (lncRNAs) is ongoing.

Abstract The first 'Gene Nomenclature Across Species' meeting was held on 12th and 13th October 2009, at the Møller Centre in Cambridge, UK. This meeting, organised and hosted by the HUGO Gene Nomenclature Committee (HGNC), brought together invited experts from the fields of gene nomenclature, phylogenetics and genome assembly and annotation. The central aim of the meeting was to discuss the issues of coordinating gene naming across vertebrates, culminating in the publication of recommendations for assigning nomenclature to genes across multiple species.

Abstract The HUGO Gene Nomenclature Committee (HGNC) assigns approved gene symbols to human loci. There are currently over 33,000 approved gene symbols, the majority of which represent protein-coding genes, but we also name other locus types such as non-coding RNAs, pseudogenes and phenotypic loci. Where relevant, the HGNC organise these genes into gene families and groups. The HGNC website http://www.genenames.org/ is an online repository of HGNC-approved gene nomenclature and associated resources for human genes, and includes links to genomic, proteomic and phenotypic information. In addition to this, we also have dedicated gene family web pages and are currently expanding and generating more of these pages using data curated by the HGNC and from information derived from external resources that focus on particular gene families. Here, we review our current online resources with a particular focus on our gene family data, using it to highlight our new Gene Symbol Report and gene family data downloads.

Abstract Background The homeobox genes are a large and diverse group of genes, many of which play important roles in the embryonic development of animals. Increasingly, homeobox genes are being compared between genomes in an attempt to understand the evolution of animal development. Despite their importance, the full diversity of human homeobox genes has not previously been described. Results We have identified all homeobox genes and pseudogenes in the euchromatic regions of the human genome, finding many unannotated, incorrectly annotated, unnamed, misnamed or misclassified genes and pseudogenes. We describe 300 human homeobox loci, which we divide into 235 probable functional genes and 65 probable pseudogenes. These totals include 3 genes with partial homeoboxes and 13 pseudogenes that lack homeoboxes but are clearly derived from homeobox genes. These figures exclude the repetitive DUX1 to DUX5 homeobox sequences of which we identified 35 probable pseudogenes, with many more expected in heterochromatic regions. Nomenclature is established for approximately 40 formerly unnamed loci, reflecting their evolutionary relationships to other loci in human and other species, and nomenclature revisions are proposed for around 30 other loci. We use a classification that recognizes 11 homeobox gene 'classes' subdivided into 102 homeobox gene 'families'. Conclusion We have conducted a comprehensive survey of homeobox genes and pseudogenes in the human genome, described many new loci, and revised the classification and nomenclature of homeobox genes. The classification scheme may be widely applicable to homeobox genes in other animal genomes and will facilitate comparative genomics of this important gene superclass.

Rare genetic diseases affect millions, and identifying causal DNA variants is essential for patient care. Therefore, it is imperative to estimate the effect of each independent variant and improve their pathogenicity classification. Our study of 140 214 unrelated UK Biobank (UKB) participants found that each of them carries a median of 7 variants previously reported as pathogenic or likely pathogenic. We focused on 967 diagnostic-grade gene (DGG) variants for rare bleeding, thrombotic, and platelet disorders (BTPDs) observed in 12 367 UKB participants. By association analysis, for a subset of these variants, we estimated effect sizes for platelet count and volume, and odds ratios for bleeding and thrombosis. Variants causal of some autosomal recessive platelet disorders revealed phenotypic consequences in carriers. Loss-of-function variants in MPL, which cause chronic amegakaryocytic thrombocytopenia if biallelic, were unexpectedly associated with increased platelet counts in carriers. We also demonstrated that common variants identified by genome-wide association studies (GWAS) for platelet count or thrombosis risk may influence the penetrance of rare variants in BTPD DGGs on their associated hemostasis disorders. Network-propagation analysis applied to an interactome of 18 410 nodes and 571 917 edges showed that GWAS variants with large effect sizes are enriched in DGGs and their first-order interactors. Finally, we illustrate the modifying effect of polygenic scores for platelet count and thrombosis risk on disease severity in participants carrying rare variants in TUBB1 or PROC and PROS1, respectively. Our findings demonstrate the power of association analyses using large population datasets in improving pathogenicity classifications of rare variants., (© 2023 by The American Society of Hematology. Licensed under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0), permitting only noncommercial, nonderivative use with attribution. All other rights reserved.)

The Orthology Benchmark Service (https://orthology.benchmarkservice.org) is the gold standard for orthology inference evaluation, supported and maintained by the Quest for Orthologs consortium. It is an essential resource to compare existing and new methods of orthology inference (the bedrock for many comparative genomics and phylogenetic analysis) over a standard dataset and through common procedures. The Quest for Orthologs Consortium is dedicated to maintaining the resource up to date, through regular updates of the Reference Proteomes and increasingly accessible data through the OpenEBench platform. For this update, we have added a new benchmark based on curated orthology assertion from the Vertebrate Gene Nomenclature Committee, and provided an example meta-analysis of the public predictions present on the platform., (© The Author(s) 2022. Published by Oxford University Press on behalf of Nucleic Acids Research.)

This commentary is written in response to the recent article from Herring et al., discussing the eradication of the offensive term "retardation" from gene nomenclature. We discuss the work of the HUGO (Human Genome Organisation) Gene Nomenclature Committee (HGNC) and outline the steps already taken to remove this term from our gene names. We also highlight the latest nomenclature changes made as a result of discussions with the authors and agreement with the European Fragile X Network.

Syntenic genomic loci on human chromosome 8 and mouse chromosome 15 (mChr15) code for LY6/Ly6 (lymphocyte Ag 6) family proteins. The 23 murine Ly6 family genes include eight genes that are flanked by the murine Ly6e and Ly6l genes and form an Ly6 subgroup referred to in this article as the Ly6a subfamily gene cluster. Ly6a , also known as Stem Cell Ag-1 and T cell-activating protein , is a member of the Ly6a subfamily gene cluster. No LY6 genes have been annotated within the syntenic LY6E to LY6L human locus. We report in this article on LY6S , a solitary human LY6 gene that is syntenic with the murine Ly6a subfamily gene cluster, and with which it shares a common ancestry. LY6S codes for the IFN-inducible GPI-linked LY6S-iso1 protein that contains only 9 of the 10 consensus LY6 cysteine residues and is most highly expressed in a nonclassical spleen cell population. Its expression leads to distinct shifts in patterns of gene expression, particularly of genes coding for inflammatory and immune response proteins, and LY6S-iso1-expressing cells show increased resistance to viral infection. Our findings reveal the presence of a previously unannotated human IFN-stimulated gene, LY6S , which has a 1:8 ortholog relationship with the genes of the Ly6a subfamily gene cluster, is most highly expressed in spleen cells of a nonclassical cell lineage, and whose expression induces viral resistance and is associated with an inflammatory phenotype and with the activation of genes that regulate immune responses., (Copyright © 2022 The Authors.)

Background: Olfactory receptors (ORs) are G protein-coupled receptors with a crucial role in odor detection. A typical mammalian genome harbors ~ 1000 OR genes and pseudogenes; however, different gene duplication/deletion events have occurred in each species, resulting in complex orthology relationships. While the human OR nomenclature is widely accepted and based on phylogenetic classification into 18 families and further into subfamilies, for other mammals different and multiple nomenclature systems are currently in use, thus concealing important evolutionary and functional insights., Results: Here, we describe the Mutual Maximum Similarity (MMS) algorithm, a systematic classifier for assigning a human-centric nomenclature to any OR gene based on inter-species hierarchical pairwise similarities. MMS was applied to the OR repertoires of seven mammals and zebrafish. Altogether, we assigned symbols to 10,249 ORs. This nomenclature is supported by both phylogenetic and synteny analyses. The availability of a unified nomenclature provides a framework for diverse studies, where textual symbol comparison allows immediate identification of potential ortholog groups as well as species-specific expansions/deletions; for example, Or52e5 and Or52e5b represent a rat-specific duplication of OR52E5. Another example is the complete absence of OR subfamily OR6Z among primate OR symbols. In other mammals, OR6Z members are located in one genomic cluster, suggesting a large deletion in the great ape lineage. An additional 14 mammalian OR subfamilies are missing from the primate genomes. While in chimpanzee 87% of the symbols were identical to human symbols, this number decreased to ~ 50% in dog and cow and to ~ 30% in rodents, reflecting the adaptive changes of the OR gene superfamily across diverse ecological niches. Application of the proposed nomenclature to zebrafish revealed similarity to mammalian ORs that could not be detected from the current zebrafish olfactory receptor gene nomenclature., Conclusions: We have consolidated a unified standard nomenclature system for the vertebrate OR superfamily. The new nomenclature system will be applied to cow, horse, dog and chimpanzee by the Vertebrate Gene Nomenclature Committee and its implementation is currently under consideration by other relevant species-specific nomenclature committees.

The most widely appreciated role of DNA is to encode protein, yet the exact portion of the human genome that is translated remains to be ascertained. We previously developed PhyloCSF, a widely used tool to identify evolutionary signatures of protein-coding regions using multispecies genome alignments. Here, we present the first whole-genome PhyloCSF prediction tracks for human, mouse, chicken, fly, worm, and mosquito. We develop a workflow that uses machine learning to predict novel conserved protein-coding regions and efficiently guide their manual curation. We analyze more than 1000 high-scoring human PhyloCSF regions and confidently add 144 conserved protein-coding genes to the GENCODE gene set, as well as additional coding regions within 236 previously annotated protein-coding genes, and 169 pseudogenes, most of them disabled after primates diverged. The majority of these represent new discoveries, including 70 previously undetected protein-coding genes. The novel coding genes are additionally supported by single-nucleotide variant evidence indicative of continued purifying selection in the human lineage, coding-exon splicing evidence from new GENCODE transcripts using next-generation transcriptomic data sets, and mass spectrometry evidence of translation for several new genes. Our discoveries required simultaneous comparative annotation of other vertebrate genomes, which we show is essential to remove spurious ORFs and to distinguish coding from pseudogene regions. Our new coding regions help elucidate disease-associated regions by revealing that 118 GWAS variants previously thought to be noncoding are in fact protein altering. Altogether, our PhyloCSF data sets and algorithms will help researchers seeking to interpret these genomes, while our new annotations present exciting loci for further experimental characterization., (© 2019 Mudge et al.; Published by Cold Spring Harbor Laboratory Press.)

The HUGO Gene Nomenclature Committee (HGNC) based at EMBL's European Bioinformatics Institute (EMBL-EBI) assigns unique symbols and names to human genes. There are over 40 000 approved gene symbols in our current database of which over 19 000 are for protein-coding genes. The Vertebrate Gene Nomenclature Committee (VGNC) was established in 2016 to assign standardized nomenclature in line with human for vertebrate species that lack their own nomenclature committees. The VGNC initially assigned nomenclature for over 15000 protein-coding genes in chimpanzee. We have extended this process to other vertebrate species, naming over 14000 protein-coding genes in cow and dog and over 13 000 in horse to date. Our HGNC website https://www.genenames.org has undergone a major design update, simplifying the homepage to provide easy access to our search tools and making the site more mobile friendly. Our gene families pages are now known as 'gene groups' and have increased in number to over 1200, with nearly half of all named genes currently assigned to at least one gene group. This article provides an overview of our online data and resources, focusing on our work over the last two years.

We present here an exploration of the evolution of three well-established, web-based resources dedicated to the dissemination of information related to olfactory receptors (ORs) and their functional ligands, odorants. These resources are: the Olfactory Receptor Database (ORDB), the Human Olfactory Data Explorer (HORDE) and ODORactor. ORDB is a repository of genomic and proteomic information related to ORs and other chemosensory receptors, such as taste and pheromone receptors. Three companion databases closely integrated with ORDB are OdorDB, ORModelDB and OdorMapDB; these resources are part of the SenseLab suite of databases (http://senselab.med.yale.edu). HORDE (http://genome.weizmann.ac.il/horde/) is a semi-automatically populated database of the OR repertoires of human and several mammals. ODORactor (http://mdl.shsmu.edu.cn/ODORactor/) provides information related to OR-odorant interactions from the perspective of the odorant. All three resources are connected to each other via web-links.Database URL: http://senselab.med.yale.edu; http://genome.weizmann.ac.il/horde/; http://mdl.shsmu.edu.cn/ODORactor/., (© The Author(s) 2016. Published by Oxford University Press.)

Short-chain dehydrogenases/reductases (SDR) constitute one of the largest enzyme superfamilies with presently over 46,000 members. In phylogenetic comparisons, members of this superfamily show early divergence where the majority have only low pairwise sequence identity, although sharing common structural properties. The SDR enzymes are present in virtually all genomes investigated, and in humans over 70 SDR genes have been identified. In humans, these enzymes are involved in the metabolism of a large variety of compounds, including steroid hormones, prostaglandins, retinoids, lipids and xenobiotics. It is now clear that SDRs represent one of the oldest protein families and contribute to essential functions and interactions of all forms of life. As this field continues to grow rapidly, a systematic nomenclature is essential for future annotation and reference purposes. A functional subdivision of the SDR superfamily into at least 200 SDR families based upon hidden Markov models forms a suitable foundation for such a nomenclature system, which we present in this paper using human SDRs as examples.

At the FASEB summer research conference on "Arf Family GTPases", held in Il Ciocco, Italy in June, 2007, it became evident to researchers that our understanding of the family of Arf GTPase activating proteins (ArfGAPs) has grown exponentially in recent years. A common nomenclature for these genes and proteins will facilitate discovery of biological functions and possible connections to pathogenesis. Nearly 100 researchers were contacted to generate a consensus nomenclature for human ArfGAPs. This article describes the resulting consensus nomenclature and provides a brief description of each of the 10 subfamilies of 31 human genes encoding proteins containing the ArfGAP domain.

Chromosome 11, although average in size, is one of the most gene- and disease-rich chromosomes in the human genome. Initial gene annotation indicates an average gene density of 11.6 genes per megabase, including 1,524 protein-coding genes, some of which were identified using novel methods, and 765 pseudogenes. One-quarter of the protein-coding genes shows overlap with other genes. Of the 856 olfactory receptor genes in the human genome, more than 40% are located in 28 single- and multi-gene clusters along this chromosome. Out of the 171 disorders currently attributed to the chromosome, 86 remain for which the underlying molecular basis is not yet known, including several mendelian traits, cancer and susceptibility loci. The high-quality data presented here--nearly 134.5 million base pairs representing 99.8% coverage of the euchromatic sequence--provide scientists with a solid foundation for understanding the genetic basis of these disorders and other biological phenomena.

HSP90 proteins are important molecular chaperones. Transcriptome and genome analyses revealed that the human HSP90 family includes 17 genes that fall into four classes. A standardized nomenclature for each of these genes is presented here. Classes HSP90AA, HSP90AB, HSP90B, and TRAP contain 7, 6, 3, and 1 genes, respectively. HSP90AA genes mapped onto chromosomes 1, 3, 4, and 11; HSP90AB genes mapped onto 3, 4, 6, 13 and 15; HSP90B genes mapped onto 1, 12, and 15; and the TRAP1 gene mapped onto 16. Six genes, HSP90AA1, HSP90AA2, HSP90N, HSP90AB1, HSP90B1 and TRAP1, were recognized as functional, and the remaining 11 genes were considered putative pseudogenes. Amino acid polymorphic variants were detected for genes HSP90AA1, HSP90AA2, HSP90AB1, HSP90B1, and TRAP1. The structures of these genes and the functional motifs and polymorphic variants of their proteins were documented and the features and functions of their proteins were discussed. Phylogenetic analyses based on both nucleotide and protein data demonstrated that HSP90(AA+AB+B) formed a monophyletic clade, whereas TRAP is a relatively distant paralogue of this clade.

The advent of the genome projects has provided new avenues to explore the question of how DNA sequence information is used appropriately by mammalian cells. Regulation of transcription is not the only, but is certainly a very important, mechanism involved in this process. We can now identify all the genes encoding transcription factors belonging to a certain class and study their biological functions in unprecedented detail through the use of an array of biomolecular tools. It is important to use rigorous and uniform definitions for the classification of transcription factors, because this helps us to comprehend the functions of transcription factor families in biological networks. Here, we propose an unambiguous nomenclature for the members of the Specificity Protein/Krüppel-like Factor (SP/KLF) transcription factor family.

The human genome sequence defines our inherent biological potential; the realization of the biology encoded therein requires knowledge of the function of each gene. Currently, our knowledge in this area is still limited. Several lines of investigation have been used to elucidate the structure and function of the genes in the human genome. Even so, gene prediction remains a difficult task, as the varieties of transcripts of a gene may vary to a great extent. We thus performed an exhaustive integrative characterization of 41,118 full-length cDNAs that capture the gene transcripts as complete functional cassettes, providing an unequivocal report of structural and functional diversity at the gene level. Our international collaboration has validated 21,037 human gene candidates by analysis of high-quality full-length cDNA clones through curation using unified criteria. This led to the identification of 5,155 new gene candidates. It also manifested the most reliable way to control the quality of the cDNA clones. We have developed a human gene database, called the H-Invitational Database (H-InvDB; http://www.h-invitational.jp/). It provides the following: integrative annotation of human genes, description of gene structures, details of novel alternative splicing isoforms, non-protein-coding RNAs, functional domains, subcellular localizations, metabolic pathways, predictions of protein three-dimensional structure, mapping of known single nucleotide polymorphisms (SNPs), identification of polymorphic microsatellite repeats within human genes, and comparative results with mouse full-length cDNAs. The H-InvDB analysis has shown that up to 4% of the human genome sequence (National Center for Biotechnology Information build 34 assembly) may contain misassembled or missing regions. We found that 6.5% of the human gene candidates (1,377 loci) did not have a good protein-coding open reading frame, of which 296 loci are strong candidates for non-protein-coding RNA genes. In addition, among 72,027 uniquely mapped SNPs and insertions/deletions localized within human genes, 13,215 nonsynonymous SNPs, 315 nonsense SNPs, and 452 indels occurred in coding regions. Together with 25 polymorphic microsatellite repeats present in coding regions, they may alter protein structure, causing phenotypic effects or resulting in disease. The H-InvDB platform represents a substantial contribution to resources needed for the exploration of human biology and pathology., Competing Interests: The authors have declared that no conflicts of interest exist.

Bardet-Biedl syndrome (BBS) is a clinically and genetically heterogeneous autosomal recessive disorder characterized by retinitis pigmentosa, polydactyly, obesity, hypogenitalism, mental retardation, and renal anomalies. To detect linkage to BBS loci, 29 BBS families, of mixed but predominantly European ethnic origin, were typed with 37 microsatellite markers on chromosomes 2, 3, 11, 15, 16, and 17. The results show that an estimated 36-56% of the families are linked to the 11q13 chromosomal site (BBS1) previously described by M. Leppert et al. (1994, Nature Genet. 7, 108-112), with the gene order cen-D11S480-5 cM-BBS1-3 cM-D11S913/D11S987-qter. A further 32-35% of the families are linked to the BBS4 locus, reported by R. Carmi et al. (1995, Hum. Mol. Genet. 4, 9-13) in chromosomal region 15q22.3-q23, with the gene order cen-D15S125-5 cM-BBS4-2 cM-D15S131/D15S204-qter. Three consanguineous BBS families are homozygous for three adjacent chromosome 15 markers, consistent with identity by descent for this region. In one of these families haplotype analysis supports a localization for BBS4 between D15S131 and D15S114, a distance of about 2 cM. Weak evidence of linkage to the 16q21 (BBS2) region reported by A. E. Kwitek-Black et al. (1993, Nature Genet. 5, 392-396) was observed in 24-27% of families with the gene order cen-D16S408-2 cM-BBS2-5 cM-D16S400. A fourth group of families, estimated at 8%, are unlinked to all three of the above loci, showing that at least one other BBS locus remains to be found. No evidence of linkage was found to markers on chromosome 3, corresponding to the BBS3 locus, reported by V. C. Sheffield et al. (1994, Hum. Mol. Genet. 3, 1331-1335), or on chromosome 2 or 17, arguing against the involvement of a BBS locus in a patient with a t(2;17) translocation.

We describe a detailed physical map of human chromosome 11, extending from the distal part of p13 through the entirety of p14 to proximal p15.1. The primary level of mapping is based on chromosome breakpoints that divide the region into 20 intervals. At higher resolution YACs cover approximately 12 Mb of the region, and in many places overlapping cosmids are ordered in contiguous arrays. The map incorporates 18 known genes, including precise localization of the GTF2H1 gene encoding the 62-kDa subunit of TFIIH. We have also localized four expressed sequences of unknown function. The physical map incorporates genetic markers that allow relationships between physical and genetic distance to be examined, and similarly includes markers from a radiation hybrid map of 11. The cytogenetic location of cosmids has been examined on high-resolution banded chromosomes by fluorescence in situ hybridization, and FLpter values have been determined. The map therefore fully integrates physical, genic, genetic, and cytogenetic information and should provide a robust framework for the rapid and accurate assignment of new markers at a high level of resolution in this region of 11p.