Providing gene-to-variant and variant-to-gene database identifier mappings to use with BridgeDb mapping services.

Introduction

Many bioinformatics software tools rely on database identifier mapping, for instance for 1) recognition and mapping of identifiers used in experimental data to the corresponding identifiers present in secondary sources like pathways or ontology classes or 2) simply to combine data from different sources that use different identifiers. BridgeDb is a database identifier mapping tool that is available as a Java framework and as an installable web service (van Iersel et al., 2010). Tools that integrate BridgeDb are for instance: the community curated pathway resource WikiPathways (Slenter et al., 2018), the modular pathway editor and pathway analysis tool PathVisio (Kutmon et al., 2015), and the network tool Cytoscape used to visualize, extend and evaluate biological networks. Depending on the available mappings BridgeDb can provide the mapping between identifiers from various data sources, also when these link to different molecular levels, e.g. gene to protein. BridgeDb can also be deployed as a web service. Moreover, it is available in a semantic web version, the Identifier Mapping Service (IMS), which can be used inside the Open PHACTS platform but can also be deployed from a software container (Gray et al., 2014) (link to tutorial and link to GitHub). Mappings for BridgeDb are already available for gene products for many species (produced from the respective Ensembl genome annotations (Aken et al., 2017)), for metabolite identifiers (produced from HMDB (Wishart et al., 2013)) and ChEBI (Hastings et al., 2013)), and for reaction identifiers (produced from Rhea (Morgat et al., 2017)).

The BridgeDb mapping databases are linking pins between tools that support genetic variants, genes, and pathways analysis helping to visualize a complex biological context such those typical of the multifaceted (genetic) diseases. Gene-to-variant mapping was not yet available for BridgeDb. Such mappings can be especially useful to work with genetic variations, for instance when evaluating traits with a complicated genetic background like blood pressure, susceptibility to heart failure, or diabetes type 2 development. Single nucleotide polymorphism (SNP) can be responsible for phenotypic variations. In extreme cases this can be the cause of rare genetic disorders. For example, several SNPs in the human DMD gene can cause Duchenne muscular dystrophy (DMD), a severe congenital disorder which leads to severe physical impairment (Magri et al., 2011). Since BridgeDb can stack mappings, the combination of the new gene-to-variant mapping database with the collection that was already available offers versatile mappings for variants to a large set of different human gene and gene product identifiers.

The main objective of this work was to provide mappings between gene identifiers and variant identifiers in both directions. The steps needed to achieve this were: 1) select the best source for the mappings, 2) collect data from the selected source, 3) annotate the result with provenance data about the process, the source, and the source version, and 4) finally to release the new BridgeDb mapping database and integrate that in the regular BridgeDb mapping database update schedule.

Target users for the resulting mappings are 1) bioinformaticians and developers, working on new approaches for data integration, if these use human genetic (variant) information; 2) members and users of ELIXIR data interoperability services, including the implementations in the tools mentioned that perform analyses based on human genetic variant data, for instance for the analysis of common multifaceted genetic diseases or in the rare disease field; and 3) researchers who access and query molecular data resulting from the analysis above.

Methods

The gene-to-variant database uses mappings between Ensembl and dbSNP (Kitts et al., 2013). The Ensembl gene-to-dbSNP variant mappings present in Ensembl were used as the source. The released database is based on Ensembl r91, dbSNP b150, and the human genome assembly GRCh38. Although Ensembl provides more genetic variation from different sources, we focused on dbSNP as this variation database is regularly updated and adjusted to the actual Ensembl genome built. We compared both sources (Ensembl and dbSNP) and made sure that Ensembl provides all dbSNP available variants. So, we are able to rely only on the Ensembl API as a source for the extraction of the data necessary for creation of this mapping database. To prevent problems introduced by the user interfaces we used database dumps for this comparison.

The data dump was obtained from the Ensembl ftp server (link for download). For the first version, we used Ensembl 91, gene annotation with Gencode 27. The vcf (variant call format) file is the one relevant for our mapping. It contains the dbSNP identifier with its additional attributes and the associated Ensembl transcript identifier. By querying the Ensembl platform web service, we can access the gene identifier of the transcript. Combined, this leads to mappings between variants and genes. The size of the complete mapping database exceeded 150 Gb (for Ensembl 91), so we decided to create several different subsets: exonic variants, missense variants, protein truncating variants (PTV), PTV and missense variants, and variants with a PolyPhen score >0.908 indicating “Probably Damaging”. Other selections can be created easily on individual demand.

The created database contains the link between the Ensembl gene identifiers and the dbSNP variant identifiers including a selection of attributes (MAF (minor allele frequency), chromosome, variant alleles, and chromosome position start/end).

For the rare cases where a variation is associated to more than one gene, the variant is also associated to these genes in the BridgeDb database. For example, rs199773918 overlaps in the exons of two genes (ENSG00000173366 and ENSG00000239732), and in the exonic variant BridgeDb mapping both genes show up. Nevertheless, in our selection of variants it may happen that not all of them show up due to different variant effect classifications in the different genes. As an example, rs199773918 is a variant that overlaps in the following genes: TPR (ENSG00000047410) and PRG4 (ENSG00000116690). This variant is a “3’ prime UTR variant” of TPR and a “missense variant” of PRG4. It can be found in both genes variant tables but due to our selection it will show up only once in the missense variant dataset.

Implementation

Database creation. An open-source Java program to create the gene-to-variant database is available on GitHub. After downloading the vcf file from Ensembl, users create a configuration file with several parameters. Then the database creation program will parse the vcf file, retrieve additional information through the Ensembl web service and create the BridgeDb mapping database. Due to the large amount of mappings, the tool commits the mappings to the database in batches to keep the required memory low.

Operation. The database creation workflow is depicted in Figure 1. The vcf file can be downloaded from the Ensembl FTP. The “Homo_sapiens_incl_consequences.vcf.gz” file is used.

Figure 1. Database creation workflow.

The gene-variant mapping database is built on the variant call format (vcf) file provided by Ensembl. After running the database creation tool, the database can be used in all the different use cases.

System requirements. The database creation tool runs with Java and requires more memory than usually given to a Java process. We advise users to allocate 3–4GB of memory at least when running the database creation tool (-Xmx4G).

Results

The resulting BridgeDb mapping databases are available as a Derby database from here. The new mappings are available for all the BridgeDb implementations mentioned above (PathVisio, Cytoscape, R package, web service, and the IMS). The mapping databases are freely available for download under CC-BY license. Application examples of the use of the variant BridgeDb database are given in the following section. We created gene-to-variant mapping databases for the variant classes given in Table 1. Any other subset of variant classes can be created on demand using the tool described in the Methods section.

Use cases

To test and demonstrate the application of the variant BridgeDb database, we downloaded the database from BridgeDb. The gene-to-variant (and variant-to-gene) queries are shown in four different tools: R command line (Team, 2014), PathVisio (Kutmon et al., 2015), Cytoscape (Shannon et al., 2003) and the local IMS installation using Docker, in order to provide an overview of the flexibility of the mapping database in different environments. A genetic variant of the rare disease Duchenne muscular dystrophy (DMD) was selected from the gene-disease association database DisGeNET (Piñero et al., 2017). The rs104894790 (Lenk et al., 1993) SNP was chosen because it presented a high number of citations and a stop gain damaging effect on the gene’s protein product.

PathVisio

We used PathVisio (version 3.3.0) (Figure 2), a biological pathway analysis tool that allows drawing, editing and analyzing biological pathways, to demonstrate how the new gene-variant database can be used to evaluate variants in a pathway context. PathVisio, like Cytoscape, has the BridgeDb functionality integrated in the core. For the purpose of the demonstration, we first selected pathways that contain the DMD gene from the R example. Five pathways were found: two striated muscle contraction pathways (WP3795 and WP383), Ectoderm differentiation (WP2858), Extracellular matrix organization (WP2703) and Arrhythmogenic right ventricular cardiomyopathy (WP2118). In principle, a new PathVisio plugin could now be developed that searches pathways that contain genes with selected variants automatically, or the plugin could show all variants from an analysis sets on a given pathway. For the example, one of the striated muscle contraction pathways (WP383) was selected and visualized. Next, the BridgeDb variant database was loaded, using the BridgeDbConfig plugin. After selecting a gene in the pathway, the backpage tab of the right hand side panel now shows the list of hyperlinks obtained from the BridgeDb database that point to different information sources linked to the gene selected. Figure 2 shows the backpage with the list of the 720 SNPs (from the BridgeDb with a PolyPhen score > 0.908, file SNP_r91_PolyPhen.bridge) for the selected DMD gene. All the SNPs in the backpage have a hyperlink to the corresponding dbSNP page.

Figure 2. PathVisio shows the diagram of the pathway WP383 from WikiPathways collection in the left panel of the tool.

When the DMD gene is selected a list of hyperlinks from different sources are displayed in the back page of the left panel. In this case, a list of SNPs located in the gene is visualized.

Cytoscape

An alternative gene-to-variant visualization is provided using Cytoscape (version 3.6.1), a popular tool for (biological) network analysis and visualization (Figure 3). The BridgeDb app for Cytoscape is available here. A node with the Ensembl gene identifier of DMD was created and the 720 SNPs were mapped to the gene using the BridgeDb app interface. A gene-variant network was created using the list of variants mapped. Moreover, the app can be used to configure the selection of several attribute columns related to the variant nodes such as: chromosome location, minor allele frequency, and variant allele. In this example figure, we visualize the PolyPhen score as the node fill color of the variants. For simplicity, the rs-numbers are not displayed.

Figure 3. Gene-variant network in Cytoscape.

Using the BridgeDb app for Cytoscape, a gene-variant network for the DMD gene (blue rounded rectangle) and its 720 probably damaging variants (PolyPhen score > 0.908) was created. The node color of the variants represents the PolyPhen score as a gradient (white-red), the darker the red, the higher the PolyPhen score.

Discussion

The BridgeDb toolset provides several apps and tools designed for different purposes, while mapping databases are available to link different database IDs for genes and gene products, metabolites, and reactions and interactions. A mapping database in the BridgeDb software environment, capable of linking genes to their variants and vice versa, was not yet available. The new database is expected to be useful to enhance the biological interpretation of genetic variant data (as shown with the example of the DMD gene) for instance when using apps that evaluate biological pathways, use the classification of genes according to ontology terms, or in the R environment when performing gene and variant related statistical evaluation.

With this newly created mapping database and the transitivity function of BridgeDb, the user can map between three different layers: e.g. variant-gene-protein. This approach can support multi-omics analysis for various biomedical applications, and tools like Cytoscape and PathVisio can be used immediately to benefit from this.

We intend to keep the content up-to-date by regular updates. The human variant mapping database is already incorporated into the quarterly BridgeDb mapping database update. Also other variant sets including more than only the currently included protein truncating and missense variants can be created on user community (or individual) demand.

Data availability

The new gene-to-variant mapping databases are available here: http://bridgedb.org/data/gene_database/

Available under a Apache 2.0 licence (http://www.apache.org/licenses/LICENSE-2.0.html)

Software availability

Source code for making of the mapping databases is available from GitHub: https://github.com/BiGCAT-UM/BridgeDbVariantDatabase

Archived source code at time of publication: http://doi.org/10.5281/zenodo.1326514 (Willighagen & Melius, 2018)

License: Apache 2.0