The Molecular Signatures Database (MSigDB) is one of the most widely used and comprehensive databases of gene sets for performing gene set enrichment analysis. Since its creation, MSigDB has grown beyond its roots in metabolic disease and cancer to include >10,000 gene sets. These better represent a wider range of biological processes and diseases, but the utility of the database is reduced by increased redundancy across, and heterogeneity within, gene sets. To address this challenge, here we use a combination of automated approaches and expert curation to develop a collection of “hallmark” gene sets as part of MSigDB. Each hallmark in this collection consists of a “refined” gene set, derived from multiple “founder” sets, that conveys a specific biological state or process and displays coherent expression. The hallmarks effectively summarize most of the relevant information of the original founder sets and, by reducing both variation and redundancy, provide more refined and concise inputs for gene set enrichment analysis.

https://www.cell.com/cell-systems/pdf/S2405-4712(15)00218-5.pdf

The Molecular Signatures Database Hallmark Gene Set Collection

The RefSeq project at the National Center for Biotechnology Information (NCBI) maintains and curates a publicly available database of annotated genomic, transcript, and protein sequence records (http://www.ncbi.nlm.nih.gov/refseq/). The RefSeq project leverages the data submitted to the International Nucleotide Sequence Database Collaboration (INSDC) against a combination of computation, manual curation, and collaboration to produce a standard set of stable, non-redundant reference sequences. The RefSeq project augments these reference sequences with current knowledge including publications, functional features and informative nomenclature. The database currently represents sequences from more than 55,000 organisms (>4800 viruses, >40,000 prokaryotes and >10,000 eukaryotes; RefSeq release 71), ranging from a single record to complete genomes. This paper summarizes the current status of the viral, prokaryotic, and eukaryotic branches of the RefSeq project, reports on improvements to data access and details efforts to further expand the taxonomic representation of the collection. We also highlight diverse functional curation initiatives that support multiple uses of RefSeq data including taxonomic validation, genome annotation, comparative genomics, and clinical testing. We summarize our approach to utilizing available RNA-Seq and other data types in our manual curation process for vertebrate, plant, and other species, and describe a new direction for prokaryotic genomes and protein name management.

Reference sequence (RefSeq) database at NCBI: current status, taxonomic expansion, and functional annotation

COSMIC, the Catalogue Of Somatic Mutations In Cancer (https://cancer.sanger.ac.uk) is the most detailed and comprehensive resource for exploring the effect of somatic mutations in human cancer. The latest release, COSMIC v86 (August 2018), includes almost 6 million coding mutations across 1.4 million tumour samples, curated from over 26 000 publications. In addition to coding mutations, COSMIC covers all the genetic mechanisms by which somatic mutations promote cancer, including non-coding mutations, gene fusions, copy-number variants and drug-resistance mutations. COSMIC is primarily hand-curated, ensuring quality, accuracy and descriptive data capture. Building on our manual curation processes, we are introducing new initiatives that allow us to prioritize key genes and diseases, and to react more quickly and comprehensively to new findings in the literature. Alongside improvements to the public website and data-download systems, new functionality in COSMIC-3D allows exploration of mutations within three-dimensional protein structures, their protein structural and functional impacts, and implications for druggability. In parallel with COSMIC's deep and broad variant coverage, the Cancer Gene Census (CGC) describes a curated catalogue of genes driving every form of human cancer. Currently describing 719 genes, the CGC has recently introduced functional descriptions of how each gene drives disease, summarized into the 10 cancer Hallmarks.

/pdf/cosmic-the-catalogue-of-somatic-mutations-in-cancer-351kesiecq.pdf

COSMIC: the Catalogue Of Somatic Mutations In Cancer

ClinVar (https://www.ncbi.nlm.nih.gov/clinvar/) is a freely available, public archive of human genetic variants and interpretations of their significance to disease, maintained at the National Institutes of Health. Interpretations of the clinical significance of variants are submitted by clinical testing laboratories, research laboratories, expert panels and other groups. ClinVar aggregates data by variant-disease pairs, and by variant (or set of variants). Data aggregated by variant are accessible on the website, in an improved set of variant call format files and as a new comprehensive XML report. ClinVar recently started accepting submissions that are focused primarily on providing phenotypic information for individuals who have had genetic testing. Submissions may come from clinical providers providing their own interpretation of the variant ('provider interpretation') or from groups such as patient registries that primarily provide phenotypic information from patients ('phenotyping only'). ClinVar continues to make improvements to its search and retrieval functions. Several new fields are now indexed for more precise searching, and filters allow the user to narrow down a large set of search results.

/pdf/clinvar-improving-access-to-variant-interpretations-and-4rcjjp3d7w.pdf

ClinVar: improving access to variant interpretations and supporting evidence.

Long noncoding RNAs (lncRNAs) are emerging as important regulators of tissue physiology and disease processes including cancer. To delineate genome-wide lncRNA expression, we curated 7,256 RNA sequencing (RNA-seq) libraries from tumors, normal tissues and cell lines comprising over 43 Tb of sequence from 25 independent studies. We applied ab initio assembly methodology to this data set, yielding a consensus human transcriptome of 91,013 expressed genes. Over 68% (58,648) of genes were classified as lncRNAs, of which 79% were previously unannotated. About 1% (597) of the lncRNAs harbored ultraconserved elements, and 7% (3,900) overlapped disease-associated SNPs. To prioritize lineage-specific, disease-associated lncRNA expression, we employed non-parametric differential expression testing and nominated 7,942 lineage- or cancer-associated lncRNA genes. The lncRNA landscape characterized here may shed light on normal biology and cancer pathogenesis and may be valuable for future biomarker development.

The landscape of long noncoding RNAs in the human transcriptome

The HUGO Gene Nomenclature Committee (HGNC) based at the European Bioinformatics Institute (EMBL-EBI) assigns unique symbols and names to human genes. To date the HGNC have assigned over 39 000 gene names and, representing an increase of over 5000 entries in the past two years. As well as increasing the size of our database, we have continued redesigning our website http://www.genenames.org and have modified, updated and improved many aspects of the site including a faster and more powerful search, a vastly improved HCOP tool and a REST service to increase the number of ways users can retrieve our data. This article provides an overview of our current online data and resources, and highlights the changes we have made in recent years.

/pdf/genenames-org-the-hgnc-resources-in-2015-1bc3xlirlu.pdf

Genenames.org: the HGNC resources in 2015

The HUGO Gene Nomenclature Committee (HGNC) based at the European Bioinformatics Institute (EMBL-EBI) assigns unique symbols and names to human genes Currently the HGNC database contains almost 40 000 approved gene symbols, over 19 000 of which represent protein-coding genes In addition to naming genomic loci we manually curate genes into family sets based on shared characteristics such as homology, function or phenotype We have recently updated our gene family resources and introduced new improved visualizations which can be seen alongside our gene symbol reports on our primary website http://wwwgenenamesorg In 2016 we expanded our remit and formed the Vertebrate Gene Nomenclature Committee (VGNC) which is responsible for assigning names to vertebrate species lacking a dedicated nomenclature group Using the chimpanzee genome as a pilot project we have approved symbols and names for over 14 500 protein-coding genes in chimpanzee, and have developed a new website http://vertebrategenenamesorg to distribute these data Here, we review our online data and resources, focusing particularly on the improvements and new developments made during the last two years

Genenames.org: the HGNC and VGNC resources in 2017

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.

Genenames.org: the HGNC and VGNC resources in 2019.

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 42,000 approved gene symbols in our current database of which over 19 000 are for protein-coding genes. While we still update placeholder and problematic symbols, we are working towards stabilizing symbols where possible; over 2000 symbols for disease associated genes are now marked as stable in our symbol reports. All of our data is available at the HGNC website https://www.genenames.org. The Vertebrate Gene Nomenclature Committee (VGNC) was established to assign standardized nomenclature in line with human for vertebrate species lacking their own nomenclature committee. In addition to the previous VGNC core species of chimpanzee, cow, horse and dog, we now name genes in cat, macaque and pig. Gene groups have been added to VGNC and currently include two complex families: olfactory receptors (ORs) and cytochrome P450s (CYPs). In collaboration with specialists we have also named CYPs in species beyond our core set. All VGNC data is available at https://vertebrate.genenames.org/. This article provides an overview of our online data and resources, focusing on updates over the last two years.

Genenames.org: the HGNC and VGNC resources in 2021.

Multiple resources currently exist that predict orthologous relationships between genes. These resources differ both in the methodologies used and in the species they make predictions for. The HGNC Comparison of Orthology Predictions (HCOP) search tool integrates and displays data from multiple ortholog prediction resources for a specified human gene or set of genes. An indication of the reliability of a prediction is provided by the number of resources that support it. HCOP was originally designed to show orthology predictions between human and mouse but has been expanded to include data from a current total of 20 selected vertebrate and model organism species. The HCOP pipeline used to fetch and integrate the information from the disparate ortholog and nomenclature data resources has recently been rewritten, both to enable the inclusion of new data and to take advantage of modern web technologies. Data from HCOP are used extensively in our work naming genes as the Vertebrate Gene Nomenclature Committee (https://vertebrate.genenames.org).

Bethan Yates

Papers

Genenames.org: the HGNC resources in 2015

Genenames.org: the HGNC and VGNC resources in 2017

Genenames.org: the HGNC and VGNC resources in 2019.

Genenames.org: the HGNC and VGNC resources in 2021.

Updates to HCOP: the HGNC comparison of orthology predictions tool