The COVID-19 pandemic has drawn attention to the human host genes associated with SARS-CoV-2 entry and to the elements that regulate expression of these genes. At NCBI, we have prioritized curation of experimentally validated regulatory elements for these genes in the RefSeq Functional Elements project. Our annotations include several enhancers, promoters, cis-regulatory elements and protein binding sites, among other feature types. We have annotated 236 regulatory features for 27 distinct biological regions in the latest human Annotation Release (109.20200522) including regulatory elements for the ABO, ACE2, ANPEP, CD209, CLEC4G, CLEC4M, CTSL, DPP4,and TMPRSS2genes.
You can view our regulatory element to target gene linkages in the regulatory interactions track using our new track hub that we recently announced. You can also see the biological regions and features tracks. These have functional and descriptive metadata, including biological region summaries, experimental evidence types, publication support and more.
The example in Figure 1 shows RefSeq Functional Element feature annotation in NCBI’s Genome Data Viewer (GDV) for the ABO gene region (GRCh38, NW_009646201.1: 73,864-103,789) the determiner of the human ABO blood group. A genome-wide association study recently identified non-coding ABO variants associated with COVID-19 disease severity (PMID:32558485), which map to some of the RefSeq Functional Elements in this region.Figure 1. The human ABO gene region in the NCBI GDV displaying the RefSeq Functional Element features. The biological regions aggregate track shows underlying feature annotation for an ABO upstream enhancer (LOC112637023), promoter region (LOC112679202), +5.8 intron 1 enhancer (LOC112679198), a 3′ regulatory region (LOC112639999), and a +36.0 downstream enhancer (LOC112637025). Functional Element features include numerous enhancers, promoters, cis-regulatory elements and protein / transcription factor binding sites.
We have more information about RefSeq Functional Elements on our website, including data download and extraction options. Stay tuned to NCBI Insights and other NCBI social media for future announcements about RefSeq Functional Elements!
You can now view SNP variation data for many commonly studied animals and plants – including mouse, cow, Drosophila, Arabidopsis, maize, cabbage, and many more – in the Genome Data Viewer (GDV) and other graphical sequence viewers. This data is streamed from the European Variation Archive (EVA) at the European Bioinformatics Institute (EBI).
On any NCBI graphical sequence view you can use the Configure Tracks menu and the Track Configuration Panel to add the track for the EVA RefSNP data. This track is available through the left-hand tab for Remote Variation Data (Figure 1). The EVA RefSNP track displayed on the pig (Sus scrofa) chromosome 12 graphical view is shown in Figure 2.
Figure 1. The Track Configuration panel showing the Remote Variation Data tab and he EVA RefSNP Release 1 track. Select the track checkbox and click Configure to load the track.
Figure 2. The graphical sequence viewer showing the region of the growth hormone gene on pig chromosome 12 (NC_010454.4) with the EVA RefSNP Release 1 track at the bottom. The track header has an (R) and a green highlight to indicate that it is remote data streamed from an external website. NCBI is not responsible for the content or availability of these data.
Please contact us using the Feedback link on the graphical view to let us know what you think and how we can further improve your experience with the NCBI genome browsers and graphical sequence viewers
dbVar, NCBI’s database of large-scale genetic variants, has a new track hub for viewing and downloading structural variation (SV) data in popular genome browsers. Initial tracks include Clinical and Common SV datasets. dbVar’s new track hub can be viewed using NCBI’s Genome Data Viewer through the “User Data and Track Hubs” feature (Figure 1) and other genome browsers by selecting “dbVar Hub” from the list of public tracks or by specifying the following URL.
Next week, NCBI staff will attend AGBT in Marco Island, Florida. On Tuesday, February 25, 2020, three posters from NCBI staff will be on display from 4:40 p.m. – 6:10 p.m. during the Poster Session and Wine Reception in the Banyan and Calusa Ballroom Foyers, Levels 1 and 3. Read on to learn a little bit about what we’ll be presenting.
Check out the latest videos on YouTube to learn how to best use NCBI graphical viewers, SRA, PGAP, and other resources.
Genome Data Viewer: Analyzing Remote BAM Alignment Files and Other Tips
This video shows you how to upload remote BAM files, and succinctly demonstrates handy viewer settings, such as Pileup display options, and highlights the very helpful tooltips in the Genome Data Viewer (GDV). There’s also a brief blog post on the same topic.
You now have access to bulk settings options for track hubs in the Genome Data Viewer (GDV) and Sequence Viewer. These settings allow you to pick the default tracks that load into the viewer from your chosen track hub. You can access the bulk options menu for by clicking on the collapsed menu or “hamburger” icon (stack of horizontal bars) at the right end of the track grouping in the Configure Track Hubs dialog (Figure 1).Figure 1. The Configure Track Hubs dialog in GDV. You can activate the bulk settings menu for a connected track hub by clicking on hamburger icon at the right of the track grouping. Clicking Select Default tracks checks on all of the tracks in that grouping, Smoothed PhyloCSF in this case. Continue reading “Bulk track hub settings now in Genome Data Viewer”→
On June 18, 2019, NCBI’s Sanjida Rangwala will demonstrate the rich data visualization capabilities of NCBI’s genome browser at a conference that is part of the Rocky Mountain Genomics Hackcon. As mentioned in a previous post, NCBI staff will also participate in an NCBI-style Hackathon as part of the larger event. The genome browser presentation and demonstration will show you how to create visuals that provide insights and show connections among genes, transcripts, variation, epigenomics and GWAS data from NCBI sources. You will also see how you can upload your own data and embed NCBI viewers on your own pages.