The GENCODE Genes track (version 30, Apr 2019) shows high-quality manual annotations merged with evidence-based automated annotations across the entire human genome generated by the GENCODE project. The GENCODE gene set presents a full merge between HAVANA manual annotation process and Ensembl automatic annotation pipeline. Priority is given to the manually curated HAVANA annotation using predicted Ensembl annotations when there are no corresponding manual annotations. The 30 annotation was carried out on genome assembly GRCh38 (hg38).
The Ensembl human and mouse data sets are the same gene annotations as GENCODE for the corresponding release.
This track is a multi-view composite track that contains differing data sets (views). Instructions for configuring multi-view tracks are here. To show only selected subtracks, uncheck the boxes next to the tracks that you wish to hide.
Views available on this track are:Filtering is available for the items in the GENCODE Basic, Comprehensive and Pseudogene tracks using the following criteria:
Coloring for the gene annotations is based on the annotation type:
The GENCODE project aims to annotate all evidence-based gene features on the human and mouse reference sequence with high accuracy by integrating computational approaches (including comparative methods), manual annotation and targeted experimental verification. This goal includes identifying all protein-coding loci with associated alternative variants, non-coding loci which have transcript evidence, and pseudogenes. For a detailed description of the methods and references used, see Harrow et al. (2006).
GENCODE Basic Set selection: The GENCODE Basic Set is intended to provide a simplified subset of the GENCODE transcript annotations that will be useful to the majority of users. The goal was to have a high-quality basic set that also covered all loci. Selection of GENCODE annotations for inclusion in the basic set was determined independently for the coding and non-coding transcripts at each gene locus.
Non-coding transcript categorization: Non-coding transcripts are categorized using their Biotype and the following criteria:
Transcription Support Level (TSL): It is important that users understand how to assess transcript annotations that they see in GENCODE. While some transcript models have a high level of support through the full length of their exon structure, there are also transcripts that are poorly supported and that should be considered speculative. The Transcription Support Level (TSL) is a method to highlight the well-supported and poorly-supported transcript models for users. The method relies on the primary data that can support full-length transcript structure: mRNA and EST alignments supplied by UCSC and Ensembl.
The mRNA and EST alignments are compared to the GENCODE transcripts and the transcripts are scored according to how well the alignment matches over its full length. The GENCODE TSL provides a consistent method of evaluating the level of support that a GENCODE transcript annotation is actually expressed in mouse. Mouse transcript sequences from the International Nucleotide Sequence Database Collaboration (GenBank, ENA, and DDBJ) are used as the evidence for this analysis. Exonerate RNA alignments from Ensembl, BLAT RNA and EST alignments from the UCSC Genome Browser Database are used in the analysis. Erroneous transcripts and libraries identified in lists maintained by the Ensembl, UCSC, HAVANA and RefSeq groups are flagged as suspect. GENCODE annotations for protein-coding and non-protein-coding transcripts are compared with the evidence alignments.
Annotations in the MHC region and other immunological genes are not evaluated, as automatic alignments tend to be very problematic. Methods for evaluating single-exon genes are still being developed and they are not included in the current analysis. Multi-exon GENCODE annotations are evaluated using the criteria that all introns are supported by an evidence alignment and the evidence alignment does not indicate that there are unannotated exons. Small insertions and deletions in evidence alignments are assumed to be due to polymorphisms and not considered as differing from the annotations. All intron boundaries must match exactly. The transcript start and end locations are allowed to differ.
The following categories are assigned to each of the evaluated annotations:
APPRIS is a system to annotate alternatively spliced transcripts based on a range of computational methods. It provides value to the annotations of the human, mouse, zebrafish, rat, and pig genomes. APPRIS has selected a single CDS variant for each gene as the 'PRINCIPAL' isoform. Principal isoforms are tagged with the numbers 1 to 5, with 1 being the most reliable.
Selected transcript models are verified experimentally by RT-PCR amplification followed by sequencing. Those experiments can be found at GEO:
See Harrow et al. (2006) for information on verification techniques.
GENCODE version 30 corresponds to Ensembl 96.
See also: The GENCODE Project
This GENCODE release is the result of a collaborative effort among the following laboratories: (contact: GENCODE at the Sanger Institute)
| Lab/Institution | Contributors |
| GENCODE Principal Investigator, EMBL European Bioinformatics Institute, Cambridge, UK | Paul Flicek |
| GENCODE Co-Principal Investigator, EMBL European Bioinformatics Institute, Cambridge, UK | Adam Frankish |
| GENCODE Co-Principal Investigator, Wellcome Trust Sanger Institute (WTSI), Cambridge, UK | Bronwen Aken |
| Kings College, London, UK | Tim Hubbard |
| HAVANA manual annotation group, EMBL European Bioinformatics Institute, Cambridge, UK | Timothy Cutts, Jyoti Choudhary, Ed Griffiths, Ewan Birney, Jose Manuel Gonzalez, Stephen Fitzgerald, Andrew Berry, Alexandra Bignell, Claire Davidson, Gloria Despacio-Reyes, Mike Kay, Deepa Manthravadi, Gaurab Mukherjee, Gemma Barson, Matt Hardy, Angela Macharia |
| Ensembl, EMBL European Bioinformatics Institute, Cambridge, UK | Carlos Garcia, Fergal Martin, Osagie Izuogu |
| Centre de Regulació Genòmica (CRG), Barcelona, Spain | Roderic Guigó, Julien Lagarde, Barbara Uszczyńska |
| UC Santa Cruz Genomics Institute, University of California Santa Cruz (UCSC), USA | David Haussler, Mark Diekhans, Benedict Paten, Joel Armstrong, Ian Fiddes |
| Computer Science and Artificial Intelligence Lab,Broad Institute of MIT and Harvard, USA | Manolis Kellis, Irwin Jungreis |
| Computational Biology and Bioinformatics, Yale University (Yale), USA | Mark Gerstein, Ekta Khurana, Cristina Sisu, Baikang Pei, Yan Zhang, Mihali Felipe |
| Center for Integrative Genomics,University of Lausanne, Switzerland | Alexandre Reymond, Cedric Howald, Anne-Maud Ferreira, Jacqueline Chrast |
| Structural Computational Biology Group, Centro Nacional de Investigaciones Oncologicas (CNIO), Madrid, Spain | Alfonso Valencia, Michael Tress, José Manuel Rodríguez, Victor de la Torre |
| Former members of the GENCODE project | Jennifer Harrow, James Gilbert, Electra Tapanari, Stephen Searle, Rachel Harte, Daniel Barrell, Felix Kokocinski, Veronika Boychenko, Toby Hunt, Catherine Snow, Gary Saunders, Sarah Grubb, Thomas Derrien, Andrea Tanzer, Gang Fang, Mihali Felipe, Joanne Howes, Reena Halai, Pablo Roman-Garcia, Michael Brent, Randall Brown, Jeltje van Baren |
Harrow J, Frankish A, Gonzalez JM, Tapanari E, Diekhans M, Kokocinski F, Aken BL, Barrell D, Zadissa A, Searle S et al. GENCODE: the reference human genome annotation for The ENCODE Project. Genome Res. 2012 Sep;22(9):1760-74. PMID: 22955987; PMC: PMC3431492
Harrow J, Denoeud F, Frankish A, Reymond A, Chen CK, Chrast J, Lagarde J, Gilbert JG, Storey R, Swarbreck D et al. GENCODE: producing a reference annotation for ENCODE. Genome Biol. 2006;7 Suppl 1:S4.1-9. PMID: 16925838; PMC: PMC1810553
A full list of GENCODE publications are available at The GENCODE Project web site.
GENCODE data are available for use without restrictions.