Author
Listed:
- 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)
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.
Suggested Citation
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 , 2022.
"A joint NCBI and EMBL-EBI transcript set for clinical genomics and research,"
Nature, Nature, vol. 604(7905), pages 310-315, April.
Handle:
RePEc:nat:nature:v:604:y:2022:i:7905:d:10.1038_s41586-022-04558-8
DOI: 10.1038/s41586-022-04558-8
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