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 (approx. 1% of Human genome).[2] Given the initial success of the project, GENCODE now aims to build an “Encyclopedia of genes and genes variants”.[2]
GENCODE is currently progressing towards its goals in Phase 2 of the project.[6]
The most recent release of the Human geneset annotations is Gencode 36, with a freeze date of December 2020. This release utilises the latest GRCh38 human reference genome assembly.[7]
The latest release for the mouse geneset annotations is Gencode M25, also with a freeze date December 2020.[7]
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.[8]
History
Timeline of the GENCODE project
2003 September
The project was designed with three phases - Pilot, Technology development and Production phase.[9] 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.[2] 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.[9]
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 (E-GASP) workshop.[2] GENCODE Release 1 contained 416 known loci, 26 novel (coding DNA sequence) CDS loci, 82 novel transcript loci, 78 putative loci, 104 processed pseudogenes and 66 unprocessed pseudogenes.
2005 October A second version (release 02) was frozen on 14 October 2005, containing updates following discoveries from experimental validations using RACE and RT-PCR techniques.[2] 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.[10] 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 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.[11]
2018 In 2018, one of the latest additions to the GENCODE project was the CRISPR/Cas9 track on human and model organism assemblies. CRISPR is a genome editing technique that uses sequences of RNA that successfully bind to the region edited with high specificity. The new track was designed to assist in the search for appropriate guide sentences by listing potential binding sites for the CRISPR/Cas9 complex that are next to transcribed regions, or within 200 bp of one. For each site, the track provides possible guide sequences along with a collection of predicted efficiency and specificity scores for those guide sequences. It also provides information about potential off-targets, grouped by the number of missmatches between the off-target and the guide.[11]
2020 Among other achievements, it has been completed the first pass manual annotation of the mouse reference genome, it has started a cooperation with RefSeq and Uniprot reference annotation databases toward achieving annotation convergence, and the annotation of lncRNAs has been improved via the discovery of novel loci and novel transcripts at existing loci. Also, given the COVID-19 pandemic during 2020, there has been an urge to support research responding to the situation, so GENCODE has reviewed and improved the annotation for a set of protein-coding genes associated with SARSCoV-2 infection.[12]
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:[6][13]
Benedict Paten (PI), University of California, Santa Cruz, CA, USA
Michael Tress, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
Jyoti Choudhary, Institute of Cancer Research (ICR), London, UK
Key Statistics
Since its inception, GENCODE has released 36 versions of the Human gene set annotations (excluding minor updates).
The key summary statistics of the most recent GENCODE Human gene set annotation (Release 36, December 2020 freeze) is shown below:[14]
Categories
Total
Categories
Total
Total No of Genes
60,660
Total No of Transcripts
232,117
Protein-coding genes
19,962
Protein-coding transcripts
85,269
Long non-coding RNA genes
17,958
- full length protein-coding:
59,269
Small non-coding RNA genes
7,569
- partial length protein-coding:
26,000
Pseudogenes
14,761
Nonsense mediated decay transcripts
17,378
- processed pseudogenes:
10,669
Long non-coding RNA loci transcripts
48,734
- unprocessed pseudogenes:
3,554
- unitary pseudogenes:
236
- polymorphic pseudogenes:
48
- pseudogenes:
18
Immunoglobulin/T-cell receptor gene segments
645
Total No of distinct translations
63,058
- protein coding segments:
409
Genes that have more than one distinct translations
13,685
- pseudogenes:
236
Through advancements in sequencing technologies (such as RT-PCR-seq), increased coverage from manual annotations (HAVANA group), 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 until 2014 is shown below.[14] 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 (CAGE) clusters, annotated PolyA sites, and peptide hits.[11]
Version 7 (December 2010 freeze, GRCh37) - Ensembl 62
Version 10 (July 2011 freeze, GRCh37) - Ensembl 65
Version 20 (April 2014 freeze, GRCh38) - Ensembl 76
Comparison of GENCODE Human versions (Transcripts)
Comparison of GENCODE Human versions (Genes)
Comparison of GENCODE Human versions (Translations)
Methodology
GENCODE pipeline diagram. The schema shows the flow of data between manual annotation and automated annotation through specialized prediction pipelines to provide hints to first-pass annotation and quality control (QC). Annotated gene models are subject to experimental validation, and the AnnoTrack tracking system contains data from all these sources and is used to highlight differences, coordinate QC, and track outcomes. Manual and automated annotation processes produce the GENCODE data set and also used to QC the completed annotation.
Putative loci can be verified by wet-lab experiments and computational predictions are analysed manually.[15] 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.[16]
Automatic annotation (Ensembl)
Ensembl transcripts are products of the Ensembl automatic gene annotation system (a collection of gene annotation pipelines), 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.[17]
Manual Annotation (HAVANA group)
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.[18] 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 (Refer to RGASP below). To confirm uncertain models, GENCODE also has an experimental validation pipeline using RNA sequencing and RACE.[16]
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.[2]
Usage/Access
The current GENCODE Human gene set version (GENCODE Release 20) includes annotation files (in GTF and GFF3 formats), FASTA files and METADATA files associated with the GENCODE annotation on all genomic regions (reference-chromosomes/patches/scaffolds/haplotypes). The annotation data is referred on reference chromosomes and stored in separated files which include: Gene annotation, PolyA features annotated by HAVANA, (Retrotransposed) 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:
GTF file example where it is shown TAB-separated standard GTF columns (1-9)
The columns within the GENCODE GTF file formats are described below.
Format description of GENCODE GTF file. TAB-separated standard GTF columns
indicates the biological position of the exon in the transcript
exon_id
ENSEXXXXXXXXXXX
level
(verified loci),
(manually annotated loci),
(automatically annotated loci)
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 (e.g. 22:30,700,000..30,900,000), as well as by ENS transcript id (with/without version), ENS gene id (with/without version) and gene name. The browser is powered by Biodalliance.[19]
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 (where a series of exons are separated by introns), 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.[20]
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.[21]
A key research area of the GENCODE project was to investigate the biological significance of long non-coding RNAs (lncRNA). 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.[4] A number of designs have been created using the Agilent Technologies eArray system, and these designs are available in a standard custom Agilent format.[4]
RGASP
The RNA-seq Genome Annotation Assessment Project (RGASP) 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 (discovery, reconstruction and quantification) software, and to determine the feasibility of automated genome annotations based on transcriptome sequencing.[23]
RGASP is organised in a consortium framework modelled after the EGASP (ENCODE Genome Annotation Assessment Project) 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 (in 2014) to focus primarily on read mapping to the genome.[23]
The human genome is a complete set of nucleic acid sequences for humans, encoded as the DNA within each of the 24 distinct chromosomes in the cell nucleus. A small DNA molecule is found within individual mitochondria. These are usually treated separately as the nuclear genome and the mitochondrial genome. Human genomes include both protein-coding DNA sequences and various types of DNA that does not encode proteins. The latter is a diverse category that includes DNA coding for non-translated RNA, such as that for ribosomal RNA, transfer RNA, ribozymes, small nuclear RNAs, and several types of regulatory RNAs. It also includes promoters and their associated gene-regulatory elements, DNA playing structural and replicatory roles, such as scaffolding regions, telomeres, centromeres, and origins of replication, plus large numbers of transposable elements, inserted viral DNA, non-functional pseudogenes and simple, highly repetitive sequences. Introns make up a large percentage of non-coding DNA. Some of this non-coding DNA is non-functional junk DNA, such as pseudogenes, but there is no firm consensus on the total amount of junk DNA.
Pseudogenes are nonfunctional segments of DNA that resemble functional genes. Most arise as superfluous copies of functional genes, either directly by gene duplication or indirectly by reverse transcription of an mRNA transcript. Pseudogenes are usually identified when genome sequence analysis finds gene-like sequences that lack regulatory sequences needed for transcription or translation, or whose coding sequences are obviously defective due to frameshifts or premature stop codons. Pseudogenes are a type of junk DNA.
In computational biology, gene prediction or gene finding refers to the process of identifying the regions of genomic DNA that encode genes. This includes protein-coding genes as well as RNA genes, but may also include prediction of other functional elements such as regulatory regions. Gene finding is one of the first and most important steps in understanding the genome of a species once it has been sequenced.
The Encyclopedia of DNA Elements (ENCODE) is a public research project which aims "to build a comprehensive parts list of functional elements in the human genome."
GeneMark is a generic name for a family of ab initio gene prediction algorithms and software programs developed at the Georgia Institute of Technology in Atlanta. Developed in 1993, original GeneMark was used in 1995 as a primary gene prediction tool for annotation of the first completely sequenced bacterial genome of Haemophilus influenzae, and in 1996 for the first archaeal genome of Methanococcus jannaschii. The algorithm introduced inhomogeneous three-periodic Markov chain models of protein-coding DNA sequence that became standard in gene prediction as well as Bayesian approach to gene prediction in two DNA strands simultaneously. Species specific parameters of the models were estimated from training sets of sequences of known type. The major step of the algorithm computes for a given DNA fragment posterior probabilities of either being "protein-coding" in each of six possible reading frames or being "non-coding". The original GeneMark was an HMM-like algorithm; it could be viewed as approximation to known in the HMM theory posterior decoding algorithm for appropriately defined HMM model of DNA sequence.
60S ribosomal protein L36 is a protein that in humans is encoded by the RPL36 gene.
40S ribosomal protein S24 is a protein that in humans is encoded by the RPS24 gene.
28S ribosomal protein L42, mitochondrial is a protein that in humans is encoded by the MRPL42 gene.
39S ribosomal protein L11, mitochondrial is a protein that in humans is encoded by the MRPL11 gene.
The Reference Sequence (RefSeq) database is an open access, annotated and curated collection of publicly available nucleotide sequences and their protein products. RefSeq was introduced in 2000. This database is built by National Center for Biotechnology Information (NCBI), and, unlike GenBank, provides only a single record for each natural biological molecule for major organisms ranging from viruses to bacteria to eukaryotes.
39S ribosomal protein L20, mitochondrial is a protein that in humans is encoded by the MRPL20 gene.
39S ribosomal protein L24, mitochondrial is a protein that in humans is encoded by the MRPL24 gene.
28S ribosomal protein S21, mitochondrial is a protein that in humans is encoded by the MRPS21 gene.
39S ribosomal protein L10, mitochondrial is a protein that in humans is encoded by the MRPL10 gene.
The Vertebrate Genome Annotation (VEGA) database is a biological database dedicated to assisting researchers in locating specific areas of the genome and annotating genes or regions of vertebrate genomes. The VEGA browser is based on Ensembl web code and infrastructure and provides a public curation of known vertebrate genes for the scientific community. The VEGA website is updated frequently to maintain the most current information about vertebrate genomes and attempts to present consistently high-quality annotation of all its published vertebrate genomes or genome regions. VEGA was developed by the Wellcome Trust Sanger Institute and is in close association with other annotation databases, such as ZFIN, the Havana Group and GenBank. Manual annotation is currently more accurate at identifying splice variants, pseudogenes, polyadenylation features, non-coding regions and complex gene arrangements than automated methods.
GeneCards is a database of human genes that provides genomic, proteomic, transcriptomic, genetic and functional information on all known and predicted human genes. It is being developed and maintained by the Crown Human Genome Center at the Weizmann Institute of Science, in collaboration with LifeMap Sciences.
In molecular biology and genetics, DNA annotation or genome annotation is the process of describing the structure and function of the components of a genome, by analyzing and interpreting them in order to extract their biological significance and understand the biological processes in which they participate. Among other things, it identifies the locations of genes and all the coding regions in a genome and determines what those genes do.
The Consensus Coding Sequence (CCDS) Project is a collaborative effort to maintain a dataset of protein-coding regions that are identically annotated on the human and mouse reference genome assemblies. The CCDS project tracks identical protein annotations on the reference mouse and human genomes with a stable identifier, and ensures that they are consistently represented by the National Center for Biotechnology Information (NCBI), Ensembl, and UCSC Genome Browser. The integrity of the CCDS dataset is maintained through stringent quality assurance testing and on-going manual curation.
WormBase is an online biological database about the biology and genome of the nematode model organism Caenorhabditis elegans and contains information about other related nematodes. WormBase is used by the C. elegans research community both as an information resource and as a place to publish and distribute their results. The database is regularly updated with new versions being released every two months. WormBase is one of the organizations participating in the Generic Model Organism Database (GMOD) project.
ANNOVAR is a bioinformatics software tool for the interpretation and prioritization of single nucleotide variants (SNVs), insertions, deletions, and copy number variants (CNVs) of a given genome.
1 2 "GENCODE – Statistics". GENCODE. Wellcome Trust Sanger Institute. c. 2014. Archived from the original on 19 June 2018. Retrieved 20 December 2020.{{cite web}}: CS1 maint: bot: original URL status unknown (link)
↑ "GENCODE – Goals". GENCODE. Wellcome Trust Sanger Institute. c. 2013. Retrieved 5 September 2014.
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