The neXtProt knowledgebase in 2020: data, tools and usability improvements.

The neXtProt knowledgebase (https://www.nextprot.org) is an integrative resource providing both data on human protein and the tools to explore these. In order to provide comprehensive and up-to-date data, we evaluate and add new data sets. We describe the incorporation of three new data sets that provide expression, function, protein-protein binary interaction, post-translational modifications (PTM) and variant information. New SPARQL query examples illustrating uses of the new data were added. neXtProt has continued to develop tools for proteomics. We have improved the peptide uniqueness checker and have implemented a new protein digestion tool. Together, these tools make it possible to determine which proteases can be used to identify trypsin-resistant proteins by mass spectrometry. In terms of usability, we have finished revamping our web interface and completely rewritten our API. Our SPARQL endpoint now supports federated queries. All the neXtProt data are available via our user interface, API, SPARQL endpoint and FTP site, including the new PEFF 1.0 format files. Finally, the data on our FTP site is now CC BY 4.0 to promote its reuse.

The Feature-Viewer: a visualization tool for positional annotations on a sequence.

SUMMARY: The Feature-Viewer is a lightweight library for the visualization of biological data mapped to a protein or nucleotide sequence. It is designed for ease of use while allowing for a full customization. The library is already used by several biological data resources and allows intuitive visual mapping of a full spectra of sequence features for different usages. AVAILABILITY AND IMPLEMENTATION: The Feature-Viewer is open source, compatible with state-of-the-art development technologies and responsive, also for mobile viewing. Documentation and usage examples are available online.

A new bioinformatics tool to help assess the significance of BRCA1 variants.

BACKGROUND: Germline pathogenic variants in the breast cancer type 1 susceptibility gene BRCA1 are associated with a 60% lifetime risk for breast and ovarian cancer. This overall risk estimate is for all BRCA1 variants; obviously, not all variants confer the same risk of developing a disease. In cancer patients, loss of BRCA1 function in tumor tissue has been associated with an increased sensitivity to platinum agents and to poly-(ADP-ribose) polymerase (PARP) inhibitors. For clinical management of both at-risk individuals and cancer patients, it would be important that each identified genetic variant be associated with clinical significance. Unfortunately for the vast majority of variants, the clinical impact is unknown. The availability of results from studies assessing the impact of variants on protein function may provide insight of crucial importance. RESULTS AND CONCLUSION: We have collected, curated, and structured the molecular and cellular phenotypic impact of 3654 distinct BRCA1 variants. The data was modeled in triple format, using the variant as a subject, the studied function as the object, and a predicate describing the relation between the two. Each annotation is supported by a fully traceable evidence. The data was captured using standard ontologies to ensure consistency, and enhance searchability and interoperability. We have assessed the extent to which functional defects at the molecular and cellular levels correlate with the clinical interpretation of variants by ClinVar submitters. Approximately 30% of the ClinVar BRCA1 missense variants have some molecular or cellular assay available in the literature. Pathogenic variants (as assigned by ClinVar) have at least some significant functional defect in 94% of testable cases. For benign variants, 77% of ClinVar benign variants, for which neXtProt Cancer variant portal has data, shows either no or mild experimental functional defects. While this does not provide evidence for clinical interpretation of variants, it may provide some guidance for variants of unknown significance, in the absence of more reliable data. The neXtProt Cancer variant portal ( https://www.nextprot.org/portals/breast-cancer ) contains over 6300 observations at the molecular and/or cellular level for BRCA1 variants.

The neXtProt knowledgebase on human proteins: 2017 update.

The neXtProt human protein knowledgebase (https://www.nextprot.org) continues to add new content and tools, with a focus on proteomics and genetic variation data. neXtProt now has proteomics data for over 85% of the human proteins, as well as new tools tailored to the proteomics community.Moreover, the neXtProt release 2016-08-25 includes over 8000 phenotypic observations for over 4000 variations in a number of genes involved in hereditary cancers and channelopathies. These changes are presented in the current neXtProt update. All of the neXtProt data are available via our user interface and FTP site. We also provide an API access and a SPARQL endpoint for more technical applications.

The neXtProt peptide uniqueness checker: a tool for the proteomics community.

SUMMARY: The neXtProt peptide uniqueness checker allows scientists to define which peptides can be used to validate the existence of human proteins, i.e. map uniquely versus multiply to human protein sequences taking into account isobaric substitutions, alternative splicing and single amino acid variants. AVAILABILITY AND IMPLEMENTATION: The pepx program is available at https://github.com/calipho-sib/pepx and can be launched from the command line or through a cgi web interface. Indexing requires a sequence file in FASTA format. The peptide uniqueness checker tool is freely available on the web at https://www.nextprot.org/tools/peptide-uniqueness-checker and from the neXtProt API at https://api.nextprot.org/. CONTACT: lydie.lane@sib.swiss.

Annotation of functional impact of voltage-gated sodium channel mutations.

Voltage-gated sodium channels are pore-forming transmembrane proteins that selectively allow sodium ions to flow across the plasma membrane according to the electro-chemical gradient thus mediating the rising phase of action potentials in excitable cells and playing key roles in physiological processes such as neurotransmission, skeletal muscle contraction, heart rhythm, and pain sensation. Genetic variations in the nine human genes encoding these channels are known to cause a large range of diseases affecting the nervous and cardiac systems. Understanding the molecular effect of genetic variations is critical for elucidating the pathologic mechanisms of known variations and in predicting the effect of newly discovered ones. To this end, we have created a Web-based tool, the Ion Channels Variants Portal, which compiles all variants characterized functionally in the human sodium channel genes. This portal describes 672 variants each associated with at least one molecular or clinical phenotypic impact, for a total of 4,658 observations extracted from 264 different research articles. These data were captured as structured annotations using standardized vocabularies and ontologies, such as the Gene Ontology and the Ion Channel ElectroPhysiology Ontology. All these data are available to the scientific community via neXtProt at https://www.nextprot.org/portals/navmut.

The neXtProt knowledgebase on human proteins: current status.

neXtProt (http://www.nextprot.org) is a human protein-centric knowledgebase developed at the SIB Swiss Institute of Bioinformatics. Focused solely on human proteins, neXtProt aims to provide a state of the art resource for the representation of human biology by capturing a wide range of data, precise annotations, fully traceable data provenance and a web interface which enables researchers to find and view information in a comprehensive manner. Since the introductory neXtProt publication, significant advances have been made on three main aspects: the representation of proteomics data, an extended representation of human variants and the development of an advanced search capability built around semantic technologies. These changes are presented in the current neXtProt update.

neXtProt: organizing protein knowledge in the context of human proteome projects.

About 5000 (25%) of the ~20400 human protein-coding genes currently lack any experimental evidence at the protein level. For many others, there is only little information relative to their abundance, distribution, subcellular localization, interactions, or cellular functions. The aim of the HUPO Human Proteome Project (HPP, www.thehpp.org ) is to collect this information for every human protein. HPP is based on three major pillars: mass spectrometry (MS), antibody/affinity capture reagents (Ab), and bioinformatics-driven knowledge base (KB). To meet this objective, the Chromosome-Centric Human Proteome Project (C-HPP) proposes to build this catalog chromosome-by-chromosome ( www.c-hpp.org ) by focusing primarily on proteins that currently lack MS evidence or Ab detection. These are termed "missing proteins" by the HPP consortium. The lack of observation of a protein can be due to various factors including incorrect and incomplete gene annotation, low or restricted expression, or instability. neXtProt ( www.nextprot.org ) is a new web-based knowledge platform specific for human proteins that aims to complement UniProtKB/Swiss-Prot ( www.uniprot.org ) with detailed information obtained from carefully selected high-throughput experiments on genomic variation, post-translational modifications, as well as protein expression in tissues and cells. This article describes how neXtProt contributes to prioritize C-HPP efforts and integrates C-HPP results with other research efforts to create a complete human proteome catalog.

Bringing science to the public in the light of evolution.

Evolution stands as a foundational pillar within modern biology, shaping our understanding of life. Studies related to evolution, for example constructing phylogenetic trees, are often carried out using DNA or protein sequences. These data, readily accessible from public databases, represent a treasure trove of resources that can be harnessed to create engaging activities with the public. At the heart of our project lies a collection of "stories" about evolution, each rooted in genuine scientific publications that furnish both biological context and supporting evidence. These narratives serve as the focal point of our LightOfEvolution.org website. Each story is accompanied by a dedicated "Your Turn to Play" section. Within this section, we furnish user-friendly activities and step-by-step guidelines, equipping visitors with the means to replicate analyses showcased in the highlighted publications. For example, the website OhMyGenes.org, relying on authentic scientific data, provides the capability to compute the proportion of shared genes across different species. Here, visitors can address the captivating question: "How many genes do we share with a banana?" To extend the educational reach, we have developed a series of modular activities, also related to the stories. These activities have been thoughtfully designed to be adaptable for face-to-face workshops held in classrooms or presented during public events. We aim to create stories and activities that resonate with participants, offering a tangible and enjoyable experience. By providing opportunities that reflect real-world scientific practices, we seek to offer participants valuable insights into the current workings of scientists "in the light of evolution."

Functionathon: a manual data mining workflow to generate functional hypotheses for uncharacterized human proteins and its application by undergraduate students.

About 10% of human proteins have no annotated function in protein knowledge bases. A workflow to generate hypotheses for the function of these uncharacterized proteins has been developed, based on predicted and experimental information on protein properties, interactions, tissular expression, subcellular localization, conservation in other organisms, as well as phenotypic data in mutant model organisms. This workflow has been applied to seven uncharacterized human proteins (C6orf118, C7orf25, CXorf58, RSRP1, SMLR1, TMEM53 and TMEM232) in the frame of a course-based undergraduate research experience named Functionathon organized at the University of Geneva to teach undergraduate students how to use biological databases and bioinformatics tools and interpret the results. C6orf118, CXorf58 and TMEM232 were proposed to be involved in cilia-related functions; TMEM53 and SMLR1 were proposed to be involved in lipid metabolism and C7orf25 and RSRP1 were proposed to be involved in RNA metabolism and gene expression. Experimental strategies to test these hypotheses were also discussed. The results of this manual data mining study may contribute to the project recently launched by the Human Proteome Organization (HUPO) Human Proteome Project aiming to fill gaps in the functional annotation of human proteins. Database URL: http://www.nextprot.org.

Identifying orthologs with OMA: A primer.

The Orthologous Matrix (OMA) is a method and database that allows users to identify orthologs among many genomes. OMA provides three different types of orthologs: pairwise orthologs, OMA Groups and Hierarchical Orthologous Groups (HOGs). This Primer is organized in two parts. In the first part, we provide all the necessary background information to understand the concepts of orthology, how we infer them and the different subtypes of orthology in OMA, as well as what types of analyses they should be used for. In the second part, we describe protocols for using the OMA browser to find a specific gene and its various types of orthologs. By the end of the Primer, readers should be able to (i) understand homology and the different types of orthologs reported in OMA, (ii) understand the best type of orthologs to use for a particular analysis; (iii) find particular genes of interest in the OMA browser; and (iv) identify orthologs for a given gene.  The data can be freely accessed from the OMA browser at https://omabrowser.org.

MyHits: improvements to an interactive resource for analyzing protein sequences.

The MyHits web site (http://myhits.isb-sib.ch) is an integrated service dedicated to the analysis of protein sequences. Since its first description in 2004, both the user interface and the back end of the server were improved. A number of tools (e.g. MAFFT, Jacop, Dotlet, Jalview, ESTScan) were added or updated to improve the usability of the service. The MySQL schema and its associated API were revamped and the database engine (HitKeeper) was separated from the web interface. This paper summarizes the current status of the server, with an emphasis on the new services.

A hands-on introduction to querying evolutionary relationships across multiple data sources using SPARQL.

The increasing use of Semantic Web technologies in the life sciences, in particular the use of the Resource Description Framework (RDF) and the RDF query language SPARQL, opens the path for novel integrative analyses, combining information from multiple data sources. However, analyzing evolutionary data in RDF is not trivial, due to the steep learning curve required to understand both the data models adopted by different RDF data sources, as well as the equivalent SPARQL constructs required to benefit from this data - in particular, recursive property paths. In this article, we provide a hands-on introduction to querying evolutionary data across several data sources that publish orthology information in RDF, namely: The Orthologous MAtrix (OMA), the European Bioinformatics Institute (EBI) RDF platform, the Database of Orthologous Groups (OrthoDB) and the Microbial Genome Database (MBGD). We present four protocols in increasing order of complexity. In these protocols, we demonstrate through SPARQL queries how to retrieve pairwise orthologs, homologous groups, and hierarchical orthologous groups. Finally, we show how orthology information in different data sources can be compared, through the use of federated SPARQL queries.

Rapid evolution of cancer/testis genes on the X chromosome.

BACKGROUND: Cancer/testis (CT) genes are normally expressed only in germ cells, but can be activated in the cancer state. This unusual property, together with the finding that many CT proteins elicit an antigenic response in cancer patients, has established a role for this class of genes as targets in immunotherapy regimes. Many families of CT genes have been identified in the human genome, but their biological function for the most part remains unclear. While it has been shown that some CT genes are under diversifying selection, this question has not been addressed before for the class as a whole. RESULTS: To shed more light on this interesting group of genes, we exploited the generation of a draft chimpanzee (Pan troglodytes) genomic sequence to examine CT genes in an organism that is closely related to human, and generated a high-quality, manually curated set of human:chimpanzee CT gene alignments. We find that the chimpanzee genome contains homologues to most of the human CT families, and that the genes are located on the same chromosome and at a similar copy number to those in human. Comparison of putative human:chimpanzee orthologues indicates that CT genes located on chromosome X are diverging faster and are undergoing stronger diversifying selection than those on the autosomes or than a set of control genes on either chromosome X or autosomes. CONCLUSION: Given their high level of diversifying selection, we suggest that CT genes are primarily responsible for the observed rapid evolution of protein-coding genes on the X chromosome.

MyHits: a new interactive resource for protein annotation and domain identification.

The MyHits web server (http://myhits.isb-sib.ch) is a new integrated service dedicated to the annotation of protein sequences and to the analysis of their domains and signatures. Guest users can use the system anonymously, with full access to (i) standard bioinformatics programs (e.g. PSI-BLAST, ClustalW, T-Coffee, Jalview); (ii) a large number of protein sequence databases, including standard (Swiss-Prot, TrEMBL) and locally developed databases (splice variants); (iii) databases of protein motifs (Prosite, Interpro); (iv) a precomputed list of matches ('hits') between the sequence and motif databases. All databases are updated on a weekly basis and the hit list is kept up to date incrementally. The MyHits server also includes a new collection of tools to generate graphical representations of pairwise and multiple sequence alignments including their annotated features. Free registration enables users to upload their own sequences and motifs to private databases. These are then made available through the same web interface and the same set of analytical tools. Registered users can manage their own sequences and annotations using only web tools and freeze their data in their private database for publication purposes.

Use of the chicken lysozyme 5' matrix attachment region to generate high producer CHO cell lines.

Scaffold or matrix attachment region (S/MAR) genetic elements have previously been proposed to insulate transgenes from repressive effects linked to their site of integration within the host cell genome. We have evaluated their use in various stable transfection settings to increase the production of recombinant proteins such as monoclonal antibodies from Chinese hamster ovary (CHO) cell lines. Using the green fluorescent protein coding sequence, we show that S/MAR elements mediate a dual effect on the population of transfected cells. First, S/MAR elements almost fully abolish the occurrence of cell clones that express little transgene that may result from transgene integration in an unfavorable chromosomal environment. Second, they increase the overall expression of the transgene over the whole range of expression levels, allowing the detection of cells with significantly higher levels of transgene expression. An optimal setting was identified as the addition of a S/MAR element both in cis (on the transgene expression vector) and in trans (co-transfected on a separate plasmid). When used to express immunoglobulins, the S/MAR element enabled cell clones with high and stable levels of expression to be isolated following the analysis of a few cell lines generated without transgene amplification procedures.