Ensembl Genomes 2018: an integrated omics infrastructure for non-vertebrate species

Abstract

Ensembl Genomes (http://www.ensemblgenomes.org) is an integrating resource for genome-scale data from non-vertebrate species, complementing the resources for vertebrate genomics developed in the Ensembl project (http://www.ensembl.org). Together, the two resources provide a consistent set of programmatic and interactive interfaces to a rich range of data including genome sequence, gene models, transcript sequence, genetic variation, and comparative analysis. This paper provides an update to the previous publications about the resource, with a focus on recent developments and expansions. These include the incorporation of almost 20 000 additional genome sequences and over 35 000 tracks of RNA-Seq data, which have been aligned to genomic sequence and made available for visualization. Other advances since 2015 include the release of the database in Resource Description Framework (RDF) format, a large increase in community-derived curation, a new high-performance protein sequence search, additional cross-references, improved annotation of non-protein-coding genes, and the launch of pre-release and archival sites. Collectively, these changes are part of a continuing response to the increasing quantity of publicly-available genome-scale data, and the consequent need to archive, integrate, annotate and disseminate these using automated, scalable methods.

Figure 1.

Data discovery and visualisation of alignment data in Ensembl Plants. While browsing the genome, a user can follow the ‘Custom tracks’ option in the left-hand menu (panel A). This gives access to a menu that searches the track hub registry for hubs that are anchored on this genome and match a specified metadata search term (panel B). Having selected a hub, the user is led through to a second menu where the tracks contained in the hub can be figured for display (panel C). When the configuration is complete, the selected tracks appear in the browser as selected (panel D).

Figure 2.

Hidden Markov Model search integrated into Ensembl Genomes. Results from a protein search using Hidden Markov Models, implemented using HMMer3, in Ensembl Genomes. Various options are available in a tabbed display including (i) a description of the domain architecture of the query sequence, and a graphical summary of the distribution of the significance scores of matches against the library (panel A) (ii) a breakdown of matching library sequences ordered by domain architecture (panel B).