A joint NCBI and EMBL-EBI transcript set for clinical genomics and research

Joannella Morales, Shashikant Pujar, Jane E. Loveland, Alex Astashyn, Ruth Bennett, Andrew Berry, Eric Cox, Claire Davidson, Olga Ermolaeva, Catherine M. Farrell, Reham Fatima, Laurent Gil, Tamara Goldfarb, Jose M. Gonzalez, Diana Haddad, Matthew Hardy, Toby Hunt, John Jackson, Vinita S. Joardar, Michael Kay, Vamsi K. Kodali, Kelly M. McGarvey, Aoife McMahon, Jonathan M. Mudge, Daniel N. Murphy, Michael R. Murphy, Bhanu Rajput, Sanjida H. Rangwala, Lillian D. Riddick, Françoise Thibaud-Nissen, Glen Threadgold, Anjana R. Vatsan, Craig Wallin, David Webb, Paul Flicek, Ewan Birney, Kim D. Pruitt, Adam Frankish, Fiona Cunningham and Terence D. Murphy ()
Additional contact information
Joannella Morales: European Bioinformatics Institute, Wellcome Genome Campus
Shashikant Pujar: National Library of Medicine, National Institutes of Health
Jane E. Loveland: European Bioinformatics Institute, Wellcome Genome Campus
Alex Astashyn: National Library of Medicine, National Institutes of Health
Ruth Bennett: European Bioinformatics Institute, Wellcome Genome Campus
Andrew Berry: European Bioinformatics Institute, Wellcome Genome Campus
Eric Cox: National Library of Medicine, National Institutes of Health
Claire Davidson: European Bioinformatics Institute, Wellcome Genome Campus
Olga Ermolaeva: National Library of Medicine, National Institutes of Health
Catherine M. Farrell: National Library of Medicine, National Institutes of Health
Reham Fatima: European Bioinformatics Institute, Wellcome Genome Campus
Laurent Gil: European Bioinformatics Institute, Wellcome Genome Campus
Tamara Goldfarb: National Library of Medicine, National Institutes of Health
Jose M. Gonzalez: European Bioinformatics Institute, Wellcome Genome Campus
Diana Haddad: National Library of Medicine, National Institutes of Health
Matthew Hardy: European Bioinformatics Institute, Wellcome Genome Campus
Toby Hunt: European Bioinformatics Institute, Wellcome Genome Campus
John Jackson: National Library of Medicine, National Institutes of Health
Vinita S. Joardar: National Library of Medicine, National Institutes of Health
Michael Kay: European Bioinformatics Institute, Wellcome Genome Campus
Vamsi K. Kodali: National Library of Medicine, National Institutes of Health
Kelly M. McGarvey: National Library of Medicine, National Institutes of Health
Aoife McMahon: European Bioinformatics Institute, Wellcome Genome Campus
Jonathan M. Mudge: European Bioinformatics Institute, Wellcome Genome Campus
Daniel N. Murphy: European Bioinformatics Institute, Wellcome Genome Campus
Michael R. Murphy: National Library of Medicine, National Institutes of Health
Bhanu Rajput: National Library of Medicine, National Institutes of Health
Sanjida H. Rangwala: National Library of Medicine, National Institutes of Health
Lillian D. Riddick: National Library of Medicine, National Institutes of Health
Françoise Thibaud-Nissen: National Library of Medicine, National Institutes of Health
Glen Threadgold: European Bioinformatics Institute, Wellcome Genome Campus
Anjana R. Vatsan: National Library of Medicine, National Institutes of Health
Craig Wallin: National Library of Medicine, National Institutes of Health
David Webb: National Library of Medicine, National Institutes of Health
Paul Flicek: European Bioinformatics Institute, Wellcome Genome Campus
Ewan Birney: European Bioinformatics Institute, Wellcome Genome Campus
Kim D. Pruitt: National Library of Medicine, National Institutes of Health
Adam Frankish: European Bioinformatics Institute, Wellcome Genome Campus
Fiona Cunningham: European Bioinformatics Institute, Wellcome Genome Campus
Terence D. Murphy: National Library of Medicine, National Institutes of Health

Nature, 2022, vol. 604, issue 7905, 310-315

Abstract: Abstract Comprehensive genome annotation is essential to understand the impact of clinically relevant variants. However, the absence of a standard for clinical reporting and browser display complicates the process of consistent interpretation and reporting. To address these challenges, Ensembl/GENCODE1 and RefSeq2 launched a joint initiative, the Matched Annotation from NCBI and EMBL-EBI (MANE) collaboration, to converge on human gene and transcript annotation and to jointly define a high-value set of transcripts and corresponding proteins. Here, we describe the MANE transcript sets for use as universal standards for variant reporting and browser display. The MANE Select set identifies a representative transcript for each human protein-coding gene, whereas the MANE Plus Clinical set provides additional transcripts at loci where the Select transcripts alone are not sufficient to report all currently known clinical variants. Each MANE transcript represents an exact match between the exonic sequences of an Ensembl/GENCODE transcript and its counterpart in RefSeq such that the identifiers can be used synonymously. We have now released MANE Select transcripts for 97% of human protein-coding genes, including all American College of Medical Genetics and Genomics Secondary Findings list v3.0 (ref. 3) genes. MANE transcripts are accessible from major genome browsers and key resources. Widespread adoption of these transcript sets will increase the consistency of reporting, facilitate the exchange of data regardless of the annotation source and help to streamline clinical interpretation.

Date: 2022
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DOI: 10.1038/s41586-022-04558-8

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