GENCODE


GENCODE is a scientific project in genome research and part of the ENCODE scale-up project.
The GENCODE consortium was initially formed as part of the pilot phase of the ENCODE project to identify and map all protein-coding genes within the ENCODE regions. Given the initial success of the project, GENCODE now aims to build an “Encyclopedia of genes and genes variants” by identifying all gene features in the human and mouse genome using a combination of computational analysis, manual annotation, and experimental validation, and annotating all evidence-based gene features in the entire human genome at a high accuracy.
The result will be a set of annotations including all protein-coding loci with alternatively transcribed variants, non-coding loci with transcript evidence, and pseudogenes.

Current progress

GENCODE is currently progressing towards its goals in Phase 2 of the project, which are:
The most recent release of the Human geneset annotations is Gencode 32, with a freeze date of September 2019. This release utilises the latest GRCh38 human reference genome assembly.
The latest release for the mouse geneset annotations is Gencode M23, also with a freeze date of September 2019.
Since September 2009, GENCODE has been the human gene set used by the Ensembl project and each new GENCODE release corresponds to an Ensembl release.

History

2003 September

The National Human Genome Research Institute launched a public research consortium named ENCODE, the Encyclopedia Of DNA Elements, in September 2003, to carry out a project to identify all functional elements in the human genome sequence. The project was designed with three phases - Pilot, Technology development and Production phase.
The pilot stage of the ENCODE project aimed to investigate in great depth, computationally and experimentally, 44 regions totaling 30 Mb of sequence representing approximately 1% of the human genome. As part of this stage, the GENCODE consortium was formed to identify and map all protein-coding genes within the ENCODE regions. It was envisaged that the results of the first two phases will be used to determine the best path forward for analysing the remaining 99% of the human genome in a cost-effective and comprehensive production phase.
2005 April

The first release of the annotation of the 44 ENCODE regions was frozen on 29 April 2005 and was used in the first ENCODE Genome Annotation Assessment Project workshop. GENCODE Release 1 contained 416 known loci, 26 novel CDS loci, 82 novel transcript loci, 78 putative loci, 104 processed pseudogenes and 66 unprocessed pseudogenes.
2005 October

A second version was frozen on 14 October 2005, containing updates following discoveries from experimental validations using RACE and RT-PCR techniques. GENCODE Release 2 contained 411 known loci, 30 novel CDS loci, 81 novel transcript loci, 83 putative loci, 104 processed pseudogenes and 66 unprocessed pseudogenes.
2007 June

The conclusions from the pilot project were published in June 2007. The findings highlighted the success of the pilot project to create a feasible platform and new technologies to characterise functional elements in the human genome, which paves the way for opening research into genome-wide studies.
2007 October

After a successful pilot phase on 1% of the genome, the Wellcome Trust Sanger Institute was awarded a grant from the US National Human Genome Research Institute to carry out a scale-up of the GENCODE project for integrated annotation of gene features.
This new funding was part of NHGRI's endeavour to scale-up the ENCODE Project to a production phase on the entire genome along with additional pilot-scale studies.
2012 September

In September 2012, The GENCODE consortium published a major paper discussing the results from a major release – GENCODE Release 7, which was frozen in December 2011. The GENCODE 7 release used a combination of manual gene annotation from the Human and Vertebrate Analysis and Annotation group and full new release of the automatic gene annotation from Ensembl. At the time of release, GENCODE Release 7 had the most comprehensive annotation of long noncoding RNA loci publicly available with the predominant transcript form consisting of two exons.
2013 - 2017

Having been involved in successfully delivering the definitive annotation of functional elements in the human genome, the GENCODE group were awarded a second grant in 2013 in order to continue their human genome annotation work and expand GENCODE to include annotation of the mouse genome. It is envisaged that the mouse annotation data will allow comparative studies between the human and mouse genomes, to improve annotation quality in both genomes.

Key Participants

The key participants of the GENCODE project have remained relatively consistent throughout its various phases, with the Wellcome Trust Sanger Institute now leading the overall efforts of the project.
A summary of key participating institutions of each phase is listed below:
GENCODE Phase 2 GENCODE Scale-up PhaseGENCODE Pilot Phase-
Wellcome Trust Sanger Institute, Cambridge, UKWellcome Trust Sanger Institute, Cambridge, UKWellcome Trust Sanger Institute, Cambridge, UK
  • Team 16: Population and Comparative Genomics
  • Team 71: Informatics
-
Centre de Regulació Genòmica, Barcelona, Catalonia, SpainCentre de Regulació Genòmica, Barcelona, Catalonia, SpainInstitut Municipal d'Investigació Mèdica, Barcelona, Catalonia, Spain
The University of Lausanne, SwitzerlandThe University of Lausanne, SwitzerlandUniversity of Geneva, Switzerland-
University of California, Santa Cruz, California, USAUniversity of California, Santa Cruz, USAWashington University, St Louis, USA-
Massachusetts Institute of Technology, Boston, USAMassachusetts Institute of Technology, Boston, USAUniversity of California, Berkeley, USA-
Yale University, New Haven, USAYale University, New Haven, USAEuropean Bioinformatics Institute, Hinxton, UK
Spanish National Cancer Research Centre, Madrid, SpainSpanish National Cancer Research Centre, Madrid, Spain-
Washington University, St Louis, USA-
  • *

    Key Statistics

  • Since its inception, GENCODE has released 20 versions of the Human gene set annotations.
    The key summary statistics of the most recent GENCODE Human gene set annotation, which is the first version that utilises the latest version of the Human Genome Assembly, is shown below:
    CategoriesTotalCategoriesTotal
    Total No of Genes58,688Total No of Transcripts194,334
    Protein-coding genes19,942Protein-coding transcripts79,460
    Long non-coding RNA genes14,470- full length protein-coding:54,447
    Small non-coding RNA genes9,519- partial length protein-coding:25,013
    Pseudogenes14,363Nonsense mediated decay transcripts13,229
    - processed pseudogenes:10,736Long non-coding RNA loci transcripts24,489
    - unprocessed pseudogenes:3,202
    - unitary pseudogenes:171
    - polymorphic pseudogenes:26
    - pseudogenes:2
    Immunoglobulin/T-cell receptor gene segments618Total No of distinct translations59,575
    - protein coding segments:392Genes that have more than one distinct translations13,579
    - pseudogenes:226

    Refer to the and for more details on the classification of the above gene set.
    Through advancements in sequencing technologies, increased coverage from manual annotations, and improvements to automatic annotation algorithms using Ensembl, the accuracy and completeness of GENCODE annotations have been continuously refined through its iteration of releases.
    A comparison of key statistics from 3 major GENCODE releases is shown below. It is evident that although the coverage, in terms of total number of genes discovered, is steady increasing, the number of protein-coding genes has actually decreased. This is mostly attributed to new experimental evidence obtained using Cap Analysis Gene Expression clusters, annotated PolyA sites, and peptide hits.
    The general process to create an annotation for GENCODE involves manual curation, different computational analysis and targeted experimental approaches. Putative loci can be verified by wet-lab experiments and computational predictions are analysed manually.
    Currently, to ensure a set of annotation covers the complete genome rather than just the regions that have been manually annotated, a merged data set is created using manual annotations from HAVANA, together with automatic annotations from the Ensembl automatically annotated gene set. This process also adds unique full-length CDS predictions from the Ensembl protein coding set into manually annotated genes, to provide the most complete and up-to-date annotation of the genome possible.

    Automatic annotation (Ensembl)

    Ensembl transcripts are products of the Ensembl automatic gene annotation system, termed the Ensembl gene build. All Ensembl transcripts are based on experimental evidence and thus the automated pipeline relies on the mRNAs and protein sequences deposited into public databases from the scientific community. Moreover, Protein levels 1 and 2 from UniProt, untranslated regions, long intergenic noncoding RNA genes, short non-coding RNAs are included.

    Manual Annotation (HAVANA group)

    The main approach to manual gene annotation is to annotate transcripts aligned to the genome and take the genomic sequences as the reference rather than the cDNAs. The finished genomic sequence is analyzed using a modified Ensembl pipeline, and BLAST results of cDNAs/ESTs and proteins, along with various ab initio predictions, can be analyzed manually in the annotation browser tool Otterlace. Thus, more alternative spliced variants can be predicted compared with cDNA annotation. Moreover, genomic annotation produces a more comprehensive analysis of pseudogenes.
    There are several analysis groups in the GENCODE consortium that run pipelines that aid the manual annotators in producing models in unannotated regions, and to identify potential missed or incorrect manual annotation, including completely missing loci, missing alternative isoforms, incorrect splice sites and incorrect biotypes. These are fed back to the manual annotators using the AnnoTrack tracking system. Some of these pipelines use data from other ENCODE subgroups including RNASeq data, histone modification and CAGE and Ditag data. RNAseq data is an important new source of evidence, but generating complete gene models from it is a difficult problem. As part of GENCODE, a competition was run to assess the quality of predictions produced by various RNAseq prediction pipelines. To confirm uncertain models, GENCODE also has an experimental validation pipeline using RNA sequencing and RACE

    Ensembl/HAVANA Gene Merge process

    During the merge process, all HAVANA and Ensembl transcripts models are compared, first by clustering overlapped coding exons on a same strand, and then by pairwise comparisons of each exon in a cluster of transcripts. The module used to merge the gene set is HavanaAdder. Additional steps are required prior to running the HavanaAdder code. If annotation described in external data sets is missing from the manual set, then this is stored in the AnnoTrack system to be reviewed.

    Assessing quality

    For GENCODE 7, transcript models are assigned a high or low level of support based on a new method developed to score the quality of transcripts. This method relies on 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 the alignment over its full length. A summary of support levels for each chromosome in GENCODE Release 7 is shown in the figure on the right. The annotations are partitioned into those produced by the automated process, manual method and the merged annotations, where both processes result in the same annotation.

    General methods used for GENCODE 7

    Amplification, sequencing, mapping and validation exon–exon junction
    Double-stranded cDNA of eight human tissues were generated with a cDNA amplification, and the purified DNA was directly used to generate a sequencing library with the ‘‘Genomic DNA sample prep kit’’. This library was subsequently sequenced on an Illumina Genome Analyzer 2 platform. Then, reads were mapped on to the reference human genome and the predicted spliced amplicons with Bowtie software. Only uniquely mapping reads with no mismatch were considered to validate a splice site. Splice junctions were validated if a minimum of 10 reads with the following characteristics spanned the predicted splice junctions. For 35- and 75-nt-long reads, it required at least 4 and 8 nt on each side of the breakpoints, respectively.
    Comparison of RefSeq, UCSC, AceView, and GENCODE transcripts
    Transcripts belonging to four different data sets were compared to assess to which extent these data sets overlap. Releases compared were GENCODE 7, RefSeq and UCSC Genes freeze July 2011, and AceView 2010 release. The overlaps between different data set combinations were graphically represented as three-way Venn diagrams using the Vennerable R package and edited manually.
    PhyloCSF analysis
    PhyloCSF was used to identify potential novel coding genes in RNA-seq transcript models based on evolutionary signatures. For each transcript model generated from the Illumina HBM data using either Exonerate or Scripture, a mammalian alignment was generated by extracting the alignment of each exon from UCSC’s vertebrate alignments.
    APPRIS
    APPRIS is a system that deploys a range of computational methods to provide value to the annotations of the human genome. APPRIS also selects one of the CDS for each gene as the principal isoform. Moreover, it defines the principal variant by combining protein structural and functional information and information from the conservation of related species. The APPRIS server has been used in the context of the scale up of the ENCODE project to annotate the Human genome but APPRIS is being used for other species. The pipeline is made up of separate modules that combine protein structure and function information and evolutionary evidence. Each module has been implemented as a separate web service.

    Usage/Access

    The current GENCODE Human gene set version includes annotation files, FASTA files and METADATA files associated with the GENCODE annotation on all genomic regions. The annotation data is referred on reference chromosomes and stored in separated files which include: Gene annotation, PolyA features annotated by HAVANA, pseudogenes predicted by the Yale & UCSC pipelines, but not by HAVANA, long non-coding RNAs, and tRNA structures predicted by tRNA-Scan.
    Some examples of the lines in the GTF format are shown below:
    The columns within the GENCODE GTF file formats are described below.
    Format description of GENCODE GTF file. TAB-separated standard GTF columns
    Description of key-value pairs in 9th column of the GENCODE GTF file

    Level definition

    Each gene in the GENCODE data set are classified into three levels according to their type of annotation:
    Level 1 :
    Includes transcripts that have been manually annotated and experimentally validated by RT-PCR-seq, and pseudogenes that have been validated by three different methodologies.
    Level 2 :
    Highlights transcripts that have been manually annotated by HAVANA only, and also includes transcripts that have been merged with models produced by the Ensembl automatic pipeline.
    Level 3 :
    Indicates transcripts and pseudogene predictions resulting from Ensembl’s automated annotation pipeline.

    Gene/Transcript status definition

    Genes & transcripts are assigned the status ‘‘known,’’ ‘‘novel,’’ or ‘‘putative’’ depending on their presence in other major databases and the evidence used to build their component transcripts.
    Known:
    Represented in the HUGO Gene Nomenclature Committee database and RefSeq.
    Novel:
    Not currently represented in HGNC or RefSeq databases, but are well supported by either locus specific transcript evidence or evidence from a paralogous or orthologous locus.
    Putative:
    Not currently represented in HGNC or RefSeq databases, but are supported by shorter, more sparse transcript evidence.

    Biodalliance Genome Browser

    Also, the GENCODE website contains a Genome Browser for human and mouse where you can reach any genomic region by giving the chromosome number and start-end position, as well as by ENS transcript id , ENS gene id and gene name. The browser is powered by Biodalliance.

    Challenges

    Definition of a "gene"

    The definition of a "gene" has never been a trivial issue, with numerous definitions and notions proposed throughout the years since the discovery of the human genome. First, genes were conceived in the 1900s as discrete units of heredity, then it was thought as the blueprint for protein synthesis, and in more recent times, it was being defined as genetic code that is transcribed into RNA. Although the definition of a gene has evolved greatly over the last century, it has remained a challenging and controversial subject for many researchers. With the advent of the ENCODE/GENCODE project, even more problematic aspects of the definition have been uncovered, including alternative splicing, intergenic transcriptions, and the complex patterns of dispersed regulation, together with non-genic conservation and the abundance of noncoding RNA genes. As GENCODE endeavours to build an encyclopaedia of genes and gene variants, these problems presented a mounting challenge for the GENCODE project to come up with an updated notion of a gene.

    Pseudogenes

    Pseudogenes have DNA sequences which are similar to functional protein-coding genes, however their transcripts are usually identified with a frameshift or deletion, and are generally annotated as a byproduct of protein-coding gene annotation in most genetic databases. However, recent analysis of retrotransposed pseudogenes have found some retransposed pseudogenes to be expressed and functional and to have major biological/regulatory impacts on human biology. To deal with the unknowns and complexities of pseudogenes, GENCODE has created a pseudogene ontology using a combination of automated, manual, and experimental methods to associate a variety of biological properties—such as sequence features, evolution, and potential biological functions to pseudogenes.

    Related Projects

    ENCODE

    The Encyclopedia Of DNA Elements is a public research consortium launched by the National Human Genome Research Institute, in September 2003. The goal of ENCODE is to build a comprehensive parts list of functional elements in the human genome, including elements that act at the protein and RNA levels, and regulatory elements that control cells and circumstances in which a gene is active.
    Data analysis during the pilot phase was coordinated by the Ensembl group, a joint project of EBI and the Wellcome Trust Sanger Institute. During the initial pilot and technology development phases of the project, 44 regions—approximately 1% of the human genome—were targeted for analysis using a variety of experimental and computational methods.
    All data produced by ENCODE investigators and the results of ENCODE analysis projects from 2003 to 2012 are hosted in the UCSC Genome browser and database. ENCODE results from 2013 and later are freely available for download and analysis from the ENCODE Project Portal. To annotate all evidence-based gene features in the entire human genome at a high accuracy, ENCODE consortium create the subproject GENCODE.

    Human Genome Project

    The Human Genome Project was an international research effort to determine the sequence of the human genome and identify the genes that it contains. The Project was coordinated by the National Institutes of Health and the U.S. Department of Energy. Additional contributors included universities across the United States and international partners in the United Kingdom, France, Germany, Japan, and China. The Human Genome Project formally began in 1990 and was completed in 2003, 2 years ahead of its original schedule.
    Following the release of the completed human genome sequence in April 2003, the scientific community intensified its efforts to mine the data for clues about how the body works in health and in disease. A basic requirement for this understanding of human biology is the ability to identify and characterize sequence-based functional elements through experimentation and computational analysis. In September 2003, the NHGRI introduced the ENCODE project to facilitate the identification and analysis of the complete set of functional elements in the human genome sequence.

    Sub Projects

    Ensembl

    is part of the GENCODE project, and it has played a critical role to provide automatic annotation on the human reference genome assembly and to merge this annotation with manual annotation from the HAVANA team. The gene set provided by Ensembl for human is the GENCODE gene set

    lncRNA Expression Microarray Design

    A key research area of the GENCODE project was to investigate the biological significance of long non-coding RNAs. To better understand the lncRNA expression in Humans, a sub project was created by GENCODE to develop custom microarray platforms capable of quantifying the transcripts in the GENCODE lncRNA annotation. A number of designs have been created using the Agilent Technologies eArray system, and these designs are available in a standard custom Agilent format.

    [|RGASP]

    The RNA-seq Genome Annotation Assessment Project project is designed to assess the effectiveness of various computational methods for high quality RNA-sequence data analysis. The primary goals of RGASP are to provide an unbiased evaluation for RNA-seq alignment, transcript characterisation software, and to determine the feasibility of automated genome annotations based on transcriptome sequencing.
    RGASP is organised in a consortium framework modelled after the EGASP gene prediction workshop, and two rounds of workshops have been conducted to address different aspects of RNA-seq analysis as well as changing sequencing technologies and formats. One of the main discoveries from rounds 1 & 2 of the project was the importance of read alignment on the quality of gene predictions produced. Hence, a third round of RGASP workshop is currently being conducted to focus primarily on read mapping to the genome.