Ensembl comparative genomics resources

By Javier Herrero, Matthieu Muffato, Kathryn M Beal, Stephen Fitzgerald, Leo Gordon, Miguel Pignatelli, Albert J. Vilella, S. Searle, R. Amode, Simon Brent and 4 more. 2016

432 citations recorded by the source corpus.

Evolution provides the unifying framework with which to understand biology. The coherent investigation of genic and genomic data often requires comparative genomics analyses based on whole-genome alignments, sets of homologous genes and other relevant datasets in order to evaluate and answer evolutionary-related questions. However, the complexity and computational requirements of producing such data are substantial: this has led to only a small number of reference resources that are used for most comparative analyses. The Ensembl comparative genomics resources are one such reference set that facilitates comprehensive and reproducible analysis of chordate genome data. Ensembl computes pairwise and multiple whole-genome alignments from which large-scale synteny, per-base conservation scores and constrained elements are obtained. Gene alignments are used to define Ensembl Protein Families, GeneTrees and homologies for both protein-coding and non-coding RNA genes. These resources are updated frequently and have a consistent informatics infrastructure and data presentation across all supported species. Specialized web-based visualizations are also available including synteny displays, collapsible gene tree plots, a gene family locator and different alignment views. The Ensembl comparative genomics infrastructure is extensively reused for the analysis of non-vertebrate species by other projects including Ensembl Genomes and Gramene and much of the information here is relevant to these projects. The consistency of the annotation across species and the focus on vertebrates makes Ensembl an ideal system to perform and support vertebrate comparative genomic analyses. We use robust software and pipelines to produce reference comparative data and make it freely available. Database URL: http://www.ensembl.org.

Subfields: Genetics, Molecular Biology, Plant Science

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Citations in the corpus

CADD v1.7: using protein language models, regulatory CNNs and other nucleotide-level scores to improve genome-wide variant predictions (2024, background): “The proxy-neutral set consists of more than 14 million human lineage derived sequence alterations (14 million SNVs and 1.7 million InDels up to 50 bp), inferred from primate whole genome alignments ( 41 ).”
The Gene Ontology of eukaryotic cilia and flagella (2017, methodology): “dataset [26] was obtained from CilDB [27] and the resulting list of Ensembl protein identifiers were converted to gene symbols in Ensembl biomart (version 86) [28].”
The functional landscape of the human phosphoproteome (2019, methodology): “Protein sequences, alignments, and phylogenetic trees were all downloaded from Ensembl Compara v86 (Zerbino et al. 2018; Herrero et al. 2016).”
Ensembl core software resources: storage and programmatic access for DNA sequence and genome annotation (2016, methodology): “Other Ensembl resources such as GeneTrees and Ensembl Protein Families also use stable identifiers with procedures adapted to the specific data types (3).”
Exploring autophagy with Gene Ontology (2016, methodology): “26 Most of these annotations will be transferred automatically to orthologous proteins from other species by the Ensembl Compara pipeline, 93 and tagged with the IEA (Inferred from Electronic Annotation) evidence code.”
Gene3D: Extensive prediction of globular domains in proteins (2017, methodology): “For the second example, we show the mouse Trpt1 protein (Ensembl gene: ENSMUSG00000047656), a regulator of kinase activity, along with other genes from its Ensembl Compara gene family.”