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Journal ArticleDOI

GENCODE: The reference human genome annotation for The ENCODE Project

TL;DR: This work has examined the completeness of the transcript annotation and found that 35% of transcriptional start sites are supported by CAGE clusters and 62% of protein-coding genes have annotated polyA sites, and over one-third of GENCODE protein-Coding genes aresupported by peptide hits derived from mass spectrometry spectra submitted to Peptide Atlas.
Abstract: The GENCODE Consortium aims to identify all gene features in the human genome using a combination of computational analysis, manual annotation, and experimental validation. Since the first public release of this annotation data set, few new protein-coding loci have been added, yet the number of alternative splicing transcripts annotated has steadily increased. The GENCODE 7 release contains 20,687 protein-coding and 9640 long noncoding RNA loci and has 33,977 coding transcripts not represented in UCSC genes and RefSeq. It also has the most comprehensive annotation of long noncoding RNA (lncRNA) loci publicly available with the predominant transcript form consisting of two exons. We have examined the completeness of the transcript annotation and found that 35% of transcriptional start sites are supported by CAGE clusters and 62% of protein-coding genes have annotated polyA sites. Over one-third of GENCODE protein-coding genes are supported by peptide hits derived from mass spectrometry spectra submitted to Peptide Atlas. New models derived from the Illumina Body Map 2.0 RNA-seq data identify 3689 new loci not currently in GENCODE, of which 3127 consist of two exon models indicating that they are possibly unannotated long noncoding loci. GENCODE 7 is publicly available from gencodegenes.org and via the Ensembl and UCSC Genome Browsers.

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Citations
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Journal ArticleDOI
TL;DR: The Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure outperforms other aligners by a factor of >50 in mapping speed.
Abstract: Motivation Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. Results To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. Availability and implementation STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.

30,684 citations

Journal ArticleDOI
06 Sep 2012-Nature
TL;DR: The Encyclopedia of DNA Elements project provides new insights into the organization and regulation of the authors' genes and genome, and is an expansive resource of functional annotations for biomedical research.
Abstract: The human genome encodes the blueprint of life, but the function of the vast majority of its nearly three billion bases is unknown. The Encyclopedia of DNA Elements (ENCODE) project has systematically mapped regions of transcription, transcription factor association, chromatin structure and histone modification. These data enabled us to assign biochemical functions for 80% of the genome, in particular outside of the well-studied protein-coding regions. Many discovered candidate regulatory elements are physically associated with one another and with expressed genes, providing new insights into the mechanisms of gene regulation. The newly identified elements also show a statistical correspondence to sequence variants linked to human disease, and can thereby guide interpretation of this variation. Overall, the project provides new insights into the organization and regulation of our genes and genome, and is an expansive resource of functional annotations for biomedical research.

13,548 citations

Journal Article
01 Jan 2012-Nature
TL;DR: The Encyclopedia of DNA Elements project provides new insights into the organization and regulation of the authors' genes and genome, and is an expansive resource of functional annotations for biomedical research.
Abstract: The human genome encodes the blueprint of life, but the function of the vast majority of its nearly three billion bases is unknown. The Encyclopedia of DNA Elements (ENCODE) project has systematically mapped regions of transcription, transcription factor association, chromatin structure and histone modification. These data enabled us to assign biochemical functions for 80% of the genome, in particular outside of the well-studied protein-coding regions. Many discovered candidate regulatory elements are physically associated with one another and with expressed genes, providing new insights into the mechanisms of gene regulation. The newly identified elements also show a statistical correspondence to sequence variants linked to human disease, and can thereby guide interpretation of this variation. Overall, the project provides new insights into the organization and regulation of our genes and genome, and is an expansive resource of functional annotations for biomedical research.

8,106 citations

Journal ArticleDOI
12 Aug 2015-eLife
TL;DR: It is shown that recently reported non-canonical sites do not mediate repression despite binding the miRNA, which indicates that the vast majority of functional sites are canonical.
Abstract: Proteins are built by using the information contained in molecules of messenger RNA (mRNA). Cells have several ways of controlling the amounts of different proteins they make. For example, a so-called ‘microRNA’ molecule can bind to an mRNA molecule to cause it to be more rapidly degraded and less efficiently used, thereby reducing the amount of protein built from that mRNA. Indeed, microRNAs are thought to help control the amount of protein made from most human genes, and biologists are working to predict the amount of control imparted by each microRNA on each of its mRNA targets. All RNA molecules are made up of a sequence of bases, each commonly known by a single letter—‘A’, ‘U’, ‘C’ or ‘G’. These bases can each pair up with one specific other base—‘A’ pairs with ‘U’, and ‘C’ pairs with ‘G’. To direct the repression of an mRNA molecule, a region of the microRNA known as a ‘seed’ binds to a complementary sequence in the target mRNA. ‘Canonical sites’ are regions in the mRNA that contain the exact sequence of partner bases for the bases in the microRNA seed. Some canonical sites are more effective at mRNA control than others. ‘Non-canonical sites’ also exist in which the pairing between the microRNA seed and mRNA does not completely match. Previous work has suggested that many non-canonical sites can also control mRNA degradation and usage. Agarwal et al. first used large experimental datasets from many sources to investigate microRNA activity in more detail. As expected, when mRNAs had canonical sites that matched the microRNA, mRNA levels and usage tended to drop. However, no effect was observed when the mRNAs only had recently identified non-canonical sites. This suggests that microRNAs primarily bind to canonical sites to control protein production. Based on these results, Agarwal et al. further developed a statistical model that predicts the effects of microRNAs binding to canonical sites. The updated model considers 14 different features of the microRNA, microRNA site, or mRNA—including the mRNA sequence around the site—to predict which sites within mRNAs are most effectively targeted by microRNAs. Tests showed that Agarwal et al.'s model was as good as experimental approaches at identifying the effective target sites, and was better than existing computational models. The model has been used to power the latest version of a freely available resource called TargetScan, and so could prove a valuable resource for researchers investigating the many important roles of microRNAs in controlling protein production.

5,365 citations


Cites methods from "GENCODE: The reference human genome..."

  • ...…have longer tandem isoforms, we extended them accordingly, using additional annotations provided by (i) the ‘comprehensive’ set of Gencode gene models (Harrow et al., 2012), (ii) all mRNAs in the RefSeq database (Pruitt et al., 2012), downloaded from the refGene database through the UCSC table…...

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  • ...Prior to use, our PCT scores were updated to take advantage of improvements in both mouse and human 3′-UTR annotations (Harrow et al., 2012; Flicek et al., 2014), the additional sequenced vertebrate genomes aligned to the mouse and human genomes (Karolchik et al., 2014), and our expanded set of…...

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  • ...The human and mouse databases started with Gencode annotations (Harrow et al., 2012), for which 3′ UTRs were extended, when possible, using RefSeq annotations (Pruitt et al., 2012), recently identified long 3′-UTR isoforms (Miura et al., 2013), and 3P-seq clusters marking more distal cleavage and…...

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  • ...…We updated human PCT scores using the following datasets: (i) 3′ UTRs derived from 19,800 human protein-coding genes annotated in Gencode version 19 (Harrow et al., 2012), and (ii) 3′-UTR multiple sequence alignments (MSAs) across 84 vertebrate species derived from the 100-way multiz alignments in…...

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  • ...3′-UTR profiles for TargetScan7 predictions To build databases of human and mouse 3′-UTR profiles, we began with the ‘basic’ set of proteincoding gene models deposited in Gencode v19 (human hg19 assembly) and Gencode vM3 (mouse mm10 assembly), respectively (Harrow et al., 2012)....

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Journal ArticleDOI
TL;DR: The Ensembl Variant Effect Predictor can simplify and accelerate variant interpretation in a wide range of study designs.
Abstract: The Ensembl Variant Effect Predictor is a powerful toolset for the analysis, annotation, and prioritization of genomic variants in coding and non-coding regions. It provides access to an extensive collection of genomic annotation, with a variety of interfaces to suit different requirements, and simple options for configuring and extending analysis. It is open source, free to use, and supports full reproducibility of results. The Ensembl Variant Effect Predictor can simplify and accelerate variant interpretation in a wide range of study designs.

4,658 citations


Cites background from "GENCODE: The reference human genome..."

  • ...There are two major sources of Homo sapiens annotation: GENCODE [17] and Reference Sequence (RefSeq) [18] at the National Center for Biotechnology Information (NCBI)....

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  • ...For Homo sapiens and Mus musculus this is the GENCODE gene set, which denotes that it is a full merge of Ensembl’s evidence-based transcript predictions with manual annotation to create the most extensive set of transcript isoforms for these species [36]....

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  • ...For example, in H. sapiens and M. musculus the filtered GENCODE Basic transcript set includes the vast majority of transcripts identified as dominantly expressed [36] and consensus coding sequence (CCDS) annotation highlights transcripts having the same CDS in both RefSeq and Ensembl....

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  • ...GENCODE’s aim is to create a comprehensive transcript set to represent expression of each isoform across any tissue and stage of development and, as a result, there are, on average, nearly four transcript isoforms per protein-coding gene....

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  • ...There are differences in how the transcript sets are produced: GENCODE annotation is genome-based while RefSeq transcripts are independent of the reference genome....

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References
More filters
Journal ArticleDOI
TL;DR: A new criterion for triggering the extension of word hits, combined with a new heuristic for generating gapped alignments, yields a gapped BLAST program that runs at approximately three times the speed of the original.
Abstract: The BLAST programs are widely used tools for searching protein and DNA databases for sequence similarities. For protein comparisons, a variety of definitional, algorithmic and statistical refinements described here permits the execution time of the BLAST programs to be decreased substantially while enhancing their sensitivity to weak similarities. A new criterion for triggering the extension of word hits, combined with a new heuristic for generating gapped alignments, yields a gapped BLAST program that runs at approximately three times the speed of the original. In addition, a method is introduced for automatically combining statistically significant alignments produced by BLAST into a position-specific score matrix, and searching the database using this matrix. The resulting Position-Specific Iterated BLAST (PSIBLAST) program runs at approximately the same speed per iteration as gapped BLAST, but in many cases is much more sensitive to weak but biologically relevant sequence similarities. PSI-BLAST is used to uncover several new and interesting members of the BRCT superfamily.

70,111 citations


"GENCODE: The reference human genome..." refers methods in this paper

  • ...The finished genomic sequence is analyzed using a modified Ensembl pipeline (Searle et al. 2004), and BLAST results of cDNAs/ ESTs and proteins, along with various ab initio predictions, can be analyzed manually in the annotation browser tool Otterlace (http:// www.sanger.ac.uk/resources/software/otterlace/)....

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  • ...These data were aligned to the individual BAC clones that make up the reference genome sequence using BLAST (Altschul et al. 1997) with a subsequent realignment of transcript data by Est2Genome (Mott 1997)....

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Journal ArticleDOI
TL;DR: The goals of the PDB are described, the systems in place for data deposition and access, how to obtain further information and plans for the future development of the resource are described.
Abstract: The Protein Data Bank (PDB; http://www.rcsb.org/pdb/ ) is the single worldwide archive of structural data of biological macromolecules. This paper describes the goals of the PDB, the systems in place for data deposition and access, how to obtain further information, and near-term plans for the future development of the resource.

34,239 citations


"GENCODE: The reference human genome..." refers background in this paper

  • ...• Matador3D is locally installed and checks for structural homologs for each transcript in the PDB (Berman et al. 2000)....

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  • ...Twenty-six thousand nine hundred fifty-five isoforms (31.9% of all isoforms or 42.3% of alternative isoforms) would have lost or damaged structural domains, based on alignments with Protein Data Bank (PDB) structures, and 16,540 isoforms (19.6% of all isoforms or 26% of alternative isoforms) would lose functionally important residues....

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Journal ArticleDOI
TL;DR: Bowtie extends previous Burrows-Wheeler techniques with a novel quality-aware backtracking algorithm that permits mismatches and can be used simultaneously to achieve even greater alignment speeds.
Abstract: Bowtie is an ultrafast, memory-efficient alignment program for aligning short DNA sequence reads to large genomes. For the human genome, Burrows-Wheeler indexing allows Bowtie to align more than 25 million reads per CPU hour with a memory footprint of approximately 1.3 gigabytes. Bowtie extends previous Burrows-Wheeler techniques with a novel quality-aware backtracking algorithm that permits mismatches. Multiple processor cores can be used simultaneously to achieve even greater alignment speeds. Bowtie is open source http://bowtie.cbcb.umd.edu.

20,335 citations


Additional excerpts

  • ...Mapping and validation of amplified exon–exon junction Thirty-five- or 75-nucleotide (nt)-long reads were mapped both on to the reference human genome (hg19) and the predicted spliced amplicons with Bowtie 0.12.5 (Langmead et al. 2009)....

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Journal ArticleDOI
TL;DR: The definition and use of family-specific, manually curated gathering thresholds are explained and some of the features of domains of unknown function (also known as DUFs) are discussed, which constitute a rapidly growing class of families within Pfam.
Abstract: Pfam is a widely used database of protein families and domains. This article describes a set of major updates that we have implemented in the latest release (version 24.0). The most important change is that we now use HMMER3, the latest version of the popular profile hidden Markov model package. This software is approximately 100 times faster than HMMER2 and is more sensitive due to the routine use of the forward algorithm. The move to HMMER3 has necessitated numerous changes to Pfam that are described in detail. Pfam release 24.0 contains 11,912 families, of which a large number have been significantly updated during the past two years. Pfam is available via servers in the UK (http://pfam.sanger.ac.uk/), the USA (http://pfam.janelia.org/) and Sweden (http://pfam.sbc.su.se/).

14,075 citations


"GENCODE: The reference human genome..." refers background or methods in this paper

  • ...(Finn et al. 2010) or with damaged Pfam domains with respect to the constitutional variant for the same gene....

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  • ...• SPADE uses a locally installed version of the program Pfamscan (Finn et al. 2010) to identify the conservation of protein functional domains....

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  • ...Once the correct transcript structure had been ascertained, the protein-coding potential of the transcript was determined on the basis of similarity to known protein sequences, the sequences of orthologous and paralogous proteins, the presence of Pfam functional domains (Finn et al. 2010), possible alternativeORFs, the presence of retained intronic sequence, and the likely susceptibility of the transcript to NMD (Lewis et al....

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Journal ArticleDOI
TL;DR: Pfam as discussed by the authors is a widely used database of protein families, containing 14 831 manually curated entries in the current version, version 27.0, and has been updated several times since 2012.
Abstract: Pfam, available via servers in the UK (http://pfam.sanger.ac.uk/) and the USA (http://pfam.janelia.org/), is a widely used database of protein families, containing 14 831 manually curated entries in the current release, version 27.0. Since the last update article 2 years ago, we have generated 1182 new families and maintained sequence coverage of the UniProt Knowledgebase (UniProtKB) at nearly 80%, despite a 50% increase in the size of the underlying sequence database. Since our 2012 article describing Pfam, we have also undertaken a comprehensive review of the features that are provided by Pfam over and above the basic family data. For each feature, we determined the relevance, computational burden, usage statistics and the functionality of the feature in a website context. As a consequence of this review, we have removed some features, enhanced others and developed new ones to meet the changing demands of computational biology. Here, we describe the changes to Pfam content. Notably, we now provide family alignments based on four different representative proteome sequence data sets and a new interactive DNA search interface. We also discuss the mapping between Pfam and known 3D structures.

9,415 citations


"GENCODE: The reference human genome..." refers background or methods in this paper

  • ...Once the correct transcript structure had been ascertained, the protein-coding potential of the transcript was determined on the basis of similarity to known protein sequences, the sequences of orthologous and paralogous proteins, the presence of Pfam functional domains (Finn et al. 2010), possible alternative ORFs, the presence of retained intronic sequence, and the likely susceptibility of the transcript to NMD (Lewis et al....

    [...]

  • ...(Finn et al. 2010) or with damaged Pfam domains with respect to the constitutional variant for the same gene....

    [...]

  • ...• SPADE uses a locally installed version of the program Pfamscan (Finn et al. 2010) to identify the conservation of protein functional domains....

    [...]

  • ...…the basis of similarity to known protein sequences, the sequences of orthologous and paralogous proteins, the presence of Pfam functional domains (Finn et al. 2010), possible alternative ORFs, the presence of retained intronic sequence, and the likely susceptibility of the transcript to NMD…...

    [...]

  • ...…as translated in the GENCODE 7 release, 30,148 (35.7% of all transcripts or 47.3% of alternative transcripts) would generate protein isoforms either with fewer Pfam functional domains (Finn et al. 2010) or with damaged Pfam domains with respect to the constitutional variant for the same gene....

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