We’re fortunate to be part of the EMBL European Bioinformatics Institute (EBI), which puts us alongside stellar bioinformaticians and resources in every discipline. From this, great collaborations can grow. We’ve already worked with our colleagues at Gene Expression Atlas and Reactome to embed widgets in Ensembl for viewing baseline gene expression and biochemical pathways respectively, but our latest collaboration is with the Protein Data Bank in Europe (PDBe) to show genetic variation on protein structures.

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Joannella Morales, Jane Loveland and Adam Frankish contributed to this post.

Back in October, we introduced you to our new joint initiative with the NCBI — the Matched Annotation from the NCBI and EMBL-EBI (MANE) transcript set. We are now pleased to update you on our progress so far.

The goal of this project is to share annotation and converge on a high-confidence, genome-wide transcript set, with a matched transcript in both RefSeq and Ensembl/GENCODE. We are doing this in two phases. During phase 1, we will release the “MANE Select” transcript set to include one well-supported transcript for every protein-coding locus. We envision the adoption of the MANE Select set as a default set across genomics resources. In phase 2, we intend to release an expanded set (“MANE Plus”) to include additional transcripts per locus that are well-supported or of particular user interest.

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One of the biggest highlights of the new Ensembl Plants release 40 is the inclusion of the new Wheat (RefSeq v1.0) genome from the International Wheat Genome Sequencing Consortium (IWGSC).

The path to sequencing the wheat genome has been no easy ride, due to its large and highly repetitive genome. This new assembly from the IWGSC bridges many gaps from the initial genome sequencing effort. Read on to find out more about this exciting new genome assembly!

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Since release 81, Ensembl has provided the gene annotations in GFF3 files alongside the already existing GTF ones. While GTF uses its own controlled vocabulary to classify features, GFF3 takes advantage of sequence ontology. In the initial release, we attempted to map all existing Ensembl biotypes to equivalent SO terms.

This has proven unsatisfactory for several reasons:

  • not all biotypes have an equivalent SO term
  • there are too many levels of granularity, with 25 terms for genes and another 25 for transcripts
  • some SO mappings do not respect the parent-child relationship expected between gene and transcript SO terms
  • some SO mappings are inaccurate, missing or wrong
  • it is mostly redundant with the biotypes which are also provided as an attribute
  • there can be confusion when most features have identical values in the third column (the SO term) and the biotype attribute, yet a handful do not

For all these reasons, our SO term mapping has undergone a major overhaul to take advantage of the functionality sequence ontologies offer. This new mapping, which will be used from release 90 onwards, attempts to provide general biotype groupings that match the ones used on the website. As a result, all gene biotypes are mapped to one of these three groups, coding, non-coding or pseudogene. Meanwhile, transcript biotypes are mapped to one of five main groups: mRNA, pseudogenic_transcript, long non coding RNAs, short non coding RNAs and IG biotypes.

Additionally, the groupings remove some of the previous granularity that can still be explored via the biotype and the assigned terms respect the gene-transcript relationship where possible.

To see the full extent of those changes, as they will be reflected in the GFF3 files provided from release 90 onwards, please check these files on the FTP.
We hope this improvement will help our users take better advantage of the GFF3 format.