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1. RNA modifications in structure prediction – Status quo and future challenges

Author

Ronny Lorenz, Ivo L. Hofacker, and Andrea Tanzer

Subjects
Adenosine, Base pair, Computational biology, Methylation, General Biochemistry, Genetics and Molecular Biology, Transcriptome, 03 medical and health sciences, RNA, Transfer, RNA, Small Nuclear, Animals, Humans, Nucleotide, RNA, Messenger, RNA Processing, Post-Transcriptional, Base Pairing, Molecular Biology, Gene, 030304 developmental biology, chemistry.chemical_classification, 0303 health sciences, Base Sequence, Sequence Analysis, RNA, Chemistry, 030302 biochemistry & molecular biology, RNA, Ribosomal RNA, Inosine, MicroRNAs, genomic DNA, RNA, Ribosomal, Transfer RNA, Nucleic Acid Conformation
Abstract

Chemical modifications of RNA nucleotides change their identity and characteristics and thus alter genetic and structural information encoded in the genomic DNA. tRNA and rRNA are probably the most heavily modified genes, and often depend on derivatization or isomerization of their nucleobases in order to correctly fold into their functional structures. Recent RNomics studies, however, report transcriptome wide RNA modification and suggest a more general regulation of structuredness of RNAs by this so called epitranscriptome. Modification seems to require specific substrate structures, which in turn are stabilized or destabilized and thus promote or inhibit refolding events of regulatory RNA structures. In this review, we revisit RNA modifications and the related structures from a computational point of view. We discuss known substrate structures, their properties such as sub-motifs as well as consequences of modifications on base pairing patterns and possible refolding events. Given that efficient RNA structure prediction methods for canonical base pairs have been established several decades ago, we review to what extend these methods allow the inclusion of modified nucleotides to model and study epitranscriptomic effects on RNA structures.

Published
2019
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2. Comparative Analysis of the Transcriptome across Distant Species

Author

Gang Fang, LaDeana W. Hillier, Brenton R. Graveley, Ali Mortazavi, Norbert Perrimon, Nathan Boley, Jingyi Jessica Li, William C. Spencer, James B. Brown, Chau Huynh, Roger A. Hoskins, Mark Gerstein, Ann S. Hammonds, Sarah Djebali, Sonali Jha, Kenneth H. Wan, Cédric Howald, Raymond K. Auerbach, Chenghai Xue, Haiyan Huang, Jorg Drenkow, Elise A. Feingold, Julien Lagarde, Daifeng Wang, Dmitri D. Pervouchine, Thomas R. Gingeras, Guilin Wang, Peter Cherbas, Brent Ewing, Chao Di, Gary Saunders, Benjamin W. Booth, Joel Rozowsky, Yan Zhang, Anastasia Samsonova, Dionna M. Kasper, Cristina Sisu, Marcus H. Stoiber, Jiayu Wen, Michael O. Duff, Felix Schlesinger, Gennifer E. Merrihew, Sara Olson, Susan E. Celniker, Burak H. Alver, Chao Cheng, Gemma E. May, Alexandre Reymond, Carrie A. Davis, Alexander Dobin, Max E. Boeck, Roger P. Alexander, Michael J. Pazin, Peter J. Park, Adam Frankish, Lucy Cherbas, Zhi Lu, Kevin Y. Yip, Henry Zheng, Owen Thompson, Jing Leng, Kathie L. Watkins, Andrea Tanzer, Valerie Reinke, Rebecca McWhirter, Eric C. Lai, Steven E. Brenner, Robert H. Waterston, Koon-Kiu Yan, Masaomi Kato, Roderic Guigó, Huaien Wang, Kimberly Bell, Pnina Strasbourger, Baikang Pei, Jen Harrow, Long Hu, Chris Zaleski, Rabi Murad, Thomas C. Kaufman, Erik Ladewig, Robert R. Kitchen, Anurag Sethi, Kejia Wen, Guanjun Gao, Arif Harmanci, Megan Fastuca, Brian Oliver, Frank J. Slack, David M. Miller, Tim Hubbard, Garrett Robinson, Peter J. Good, Peter J. Bickel, Michael J. MacCoss, and Li Yang

Subjects
RNA, Untranslated, Caenorhabditis elegans -- Embriologia, Genome, Transcriptome, Histones, 0302 clinical medicine, Models, Cluster Analysis, Developmental, Drosòfila -- Genètica, Promoter Regions, Genetic, Genetics, 0303 health sciences, Multidisciplinary, biology, Pupa, Untranslated, Gene Expression Regulation, Developmental, Chromatin, Molecular Sequence Annotation, Drosophila melanogaster, Larva, Sequence Analysis, Biotechnology, animal structures, General Science & Technology, Computational biology, ENCODE, Article, Promoter Regions, 03 medical and health sciences, Genetic, Regulació genètica, Animals, Humans, Transcriptomics, Caenorhabditis elegans, 030304 developmental biology, Comparative genomics, Models, Genetic, Phylum, Sequence Analysis, RNA, Gene Expression Profiling, fungi, Human Genome, biology.organism_classification, Gene expression profiling, Gene Expression Regulation, RNA, Generic health relevance, 030217 neurology & neurosurgery
Abstract

The transcriptome is the readout of the genome. Identifying common features in it across distant species can reveal fundamental principles. To this end, the ENCODE and modENCODE consortia have generated large amounts of matched RNA-sequencing data for human, worm and fly. Uniform processing and comprehensive annotation of these data allow comparison across metazoan phyla, extending beyond earlier within-phylum transcriptome comparisons and revealing ancient, conserved features1, 2, 3, 4, 5, 6. Specifically, we discover co-expression modules shared across animals, many of which are enriched in developmental genes. Moreover, we use expression patterns to align the stages in worm and fly development and find a novel pairing between worm embryo and fly pupae, in addition to the embryo-to-embryo and larvae-to-larvae pairings. Furthermore, we find that the extent of non-canonical, non-coding transcription is similar in each organism, per base pair. Finally, we find in all three organisms that the gene-expression levels, both coding and non-coding, can be quantitatively predicted from chromatin features at the promoter using a ‘universal model’ based on a single set of organism-independent parameters. In particular, this work was funded by a contract from the National Human Genome Research Institute modENCODE Project, contract U01 HG004271 and U54 HG006944, to S.E.C. (principal investigator) and P.C., T.R.G., R.A.H. and B.R.G. (co-principal investigators) with additional support from R01 GM076655 (S.E.C.) both under Department of Energy contract no. DE-AC02-05CH11231, and U54 HG007005 to B.R.G. J.B.B.’s work was supported by NHGRI K99 HG006698 and DOE DE-AC02-05CH11231. Work in P.J.B.’s group was supported by the modENCODE DAC sub award 5710003102, 1U01HG007031-01 and the ENCODE DAC 5U01HG004695-04. Work in M.B.G.’s group was supported by NIH grants HG007000 and HG007355. Work in Bloomington was supported in part by the Indiana METACyt Initiative of Indiana University, funded by an award from the Lilly Endowment, Inc. Work in E.C.L.’s group was supported by U01-HG004261 and RC2-HG005639. P.J.P. acknowledges support from the National Institutes of Health (grant no. U01HG004258). We thank the HAVANA team for providing annotation of the human reference genome, whose work is supported by National Institutes of Health (grant no. 5U54HG004555), the Wellcome Trust (grant no. WT098051). R.G. acknowledges support from the Spanish Ministry of Education (grant BIO2011-26205). We also acknowledge use of the Yale University Biomedical High Performance Computing Center. R.W.'s lab was supported by grant no. U01 HG 004263.

Published
2014

3. 2D Meets 4G: G-Quadruplexes in RNA Secondary Structure Prediction

Author

Christian Höner zu Siederdissen, Ronny Lorenz, Jing Qin, Fabian Amman, Peter F. Stadler, Ivo L. Hofacker, Andrea Tanzer, Stephan H. Bernhart, and Publica

Subjects
ViennaRNA Package, RNA Folding, Sequence analysis, Genomics, Sequence alignment, Computational biology, Biology, Dynamic programming, G-quadruplex, chemistry.chemical_compound, Genetics, Humans, heterocyclic compounds, RNA, Messenger, Base Sequence, Sequence Analysis, RNA, Applied Mathematics, Computational Biology, RNA, G-Quadruplexes, chemistry, Nucleic acid, RNA, Messenger/chemistry, Nucleic Acid Conformation, Thermodynamics, Human genome, 5' Untranslated Regions, Sequence Alignment, DNA, Biotechnology
Abstract

G-quadruplexes are abundant locally stable structural elements in nucleic acids. The combinatorial theory of RNA structures and the dynamic programming algorithms for RNA secondary structure prediction are extended here to incorporate G-quadruplexes using a simple but plausible energy model. With preliminary energy parameters, we find that the overwhelming majority of putative quadruplex-forming sequences in the human genome are likely to fold into canonical secondary structures instead. Stable G-quadruplexes are strongly enriched, however, in the 5ÊUTR of protein coding mRNAs.

Published
2013
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4. Extension of human lncRNA transcripts by RACE coupled with long-read high-throughput sequencing (RACE-Seq)

Author

Electra Tapanari, Alicia Vela-Boza, Roderic Guigó, Andrea Tanzer, Antonio Rueda, Francisco J. López-Domingo, Javier Santoyo-Lopez, Julien Lagarde, Jonathan M. Mudge, Jacqueline Chrast, Joaquín Dopazo, Laurens G. Wilming, Jennifer Harrow, José M. González, Barbara Uszczynska-Ratajczak, Charles A. Steward, Cédric Howald, and Alexandre Reymond

Subjects
0301 basic medicine, RNA splicing, Science, General Physics and Astronomy, Computational biology, Biology, Bioinformatics, Polymerase Chain Reaction, Proof of Concept Study, General Biochemistry, Genetics and Molecular Biology, DNA sequencing, Article, Transcriptome, 03 medical and health sciences, Exon, Rapid amplification of cDNA ends, Humans, Protein Isoforms, RNA, Messenger, Transcriptomics, Gene, Multidisciplinary, Sequence Analysis, RNA, Alternative splicing, High-Throughput Nucleotide Sequencing, Molecular Sequence Annotation, General Chemistry, Exons, 030104 developmental biology, Sequence annotation, Genetic Loci, Organ Specificity, Long non-coding RNAs, RNA, Long Noncoding, RNA Splice Sites
Abstract

Long non-coding RNAs (lncRNAs) constitute a large, yet mostly uncharacterized fraction of the mammalian transcriptome. Such characterization requires a comprehensive, high-quality annotation of their gene structure and boundaries, which is currently lacking. Here we describe RACE-Seq, an experimental workflow designed to address this based on RACE (rapid amplification of cDNA ends) and long-read RNA sequencing. We apply RACE-Seq to 398 human lncRNA genes in seven tissues, leading to the discovery of 2,556 on-target, novel transcripts. About 60% of the targeted loci are extended in either 5′ or 3′, often reaching genomic hallmarks of gene boundaries. Analysis of the novel transcripts suggests that lncRNAs are as long, have as many exons and undergo as much alternative splicing as protein-coding genes, contrary to current assumptions. Overall, we show that RACE-Seq is an effective tool to annotate an organism's deep transcriptome, and compares favourably to other targeted sequencing techniques., Long non-coding RNAs are increasingly recognised to be important factors in regulating cellular processes and comprise a large faction of the transcriptome, however most are uncharacterised. Here the authors present RACE-Seq, a tool to improve and extend the annotation of low-expression transcripts.

Published
2016
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5. Paired-End Mapping Reveals Extensive Structural Variation in the Human Genome

Author

Fengtang Yang, Jason P. Affourtit, Michael Egholm, Brian C. Godwin, Nigel P. Carter, Bruce E. Taillon, Philip M. Kim, Michael Snyder, Andrea Tanzer, Alexander E. Urban, A. C. Eugenia Saunders, Jan Fredrik Simons, Zhoutao Chen, Sherman M. Weissman, Matthew E. Hurles, Lei Du, Jianxiang Chi, Fabian Grubert, Nicholas Carriero, Jan O. Korbel, Mark Gerstein, Timothy T. Harkins, and Dean Palejev

Subjects
Retroelements, Genomic Structural Variation, Computational biology, Biology, Genome, Article, Structural variation, Humans, Gene, Oligonucleotide Array Sequence Analysis, Repetitive Sequences, Nucleic Acid, Sequence Deletion, Chromosomal inversion, Recombination, Genetic, Genetics, Multidisciplinary, Genome, Human, Breakpoint, Chromosome Mapping, Computational Biology, Genetic Variation, Sequence Analysis, DNA, Mutagenesis, Insertional, Chromosome Inversion, Mutation, Female, Human genome, Gene Fusion, Reference genome
Abstract

Structural variation of the genome involves kilobase- to megabase-sized deletions, duplications, insertions, inversions, and complex combinations of rearrangements. We introduce high-throughput and massive paired-end mapping (PEM), a large-scale genome-sequencing method to identify structural variants (SVs) ∼3 kilobases (kb) or larger that combines the rescue and capture of paired ends of 3-kb fragments, massive 454 sequencing, and a computational approach to map DNA reads onto a reference genome. PEM was used to map SVs in an African and in a putatively European individual and identified shared and divergent SVs relative to the reference genome. Overall, we fine-mapped more than 1000 SVs and documented that the number of SVs among humans is much larger than initially hypothesized; many of the SVs potentially affect gene function. The breakpoint junction sequences of more than 200 SVs were determined with a novel pooling strategy and computational analysis. Our analysis provided insights into the mechanisms of SV formation in humans.

Published
2007
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6. Enhanced transcriptome maps from multiple mouse tissues reveal evolutionary constraint in gene expression

Author

Lei Hoon See, Jean Monlong, Huaien Wang, Dmitri D. Pervouchine, Alessandra Breschi, Alexander Dobin, Julien Lagarde, Cedric Notredame, Michael A. Beer, Suganthi Balasubramanian, Thomas R. Gingeras, Arif Harmanci, Meagan Fastuca, Chris Zaleski, Baikang Pei, Roderic Guigó, Pablo Prieto Barja, Mark Gerstein, Jorg Drenkow, Andrea Tanzer, Sarah Djebali, Giovanni Bussotti, and Carrie A. Davis

Subjects
Evolution, General Physics and Astronomy, Computational biology, Biology, Ratolins -- Genètica, Genome, Article, General Biochemistry, Genetics and Molecular Biology, Cell Line, Epigenesis, Genetic, Evolution, Molecular, Histones, Transcriptome, Mice, 03 medical and health sciences, 0302 clinical medicine, Regulació genètica, Gene expression, Genetics, Animals, Humans, Epigenetics, Gene, Gene Library, 030304 developmental biology, Regulation of gene expression, 0303 health sciences, Multidisciplinary, Models, Genetic, Sequence Analysis, RNA, Gene Expression Profiling, Alternative splicing, General Chemistry, Oligonucleotides, Antisense, Biological Evolution, Mice, Inbred C57BL, Gene expression profiling, Alternative Splicing, Biological sciences, Phenotype, Gene Expression Regulation, 030217 neurology & neurosurgery
Abstract

Mice have been a long-standing model for human biology and disease. Here we characterize, by RNA sequencing, the transcriptional profiles of a large and heterogeneous collection of mouse tissues, augmenting the mouse transcriptome with thousands of novel transcript candidates. Comparison with transcriptome profiles in human cell lines reveals substantial conservation of transcriptional programmes, and uncovers a distinct class of genes with levels of expression that have been constrained early in vertebrate evolution. This core set of genes captures a substantial fraction of the transcriptional output of mammalian cells, and participates in basic functional and structural housekeeping processes common to all cell types. Perturbation of these constrained genes is associated with significant phenotypes including embryonic lethality and cancer. Evolutionary constraint in gene expression levels is not reflected in the conservation of the genomic sequences, but is associated with conserved epigenetic marking, as well as with characteristic post-transcriptional regulatory programme, in which sub-cellular localization and alternative splicing play comparatively large roles., The analysis of mammalian transcriptomes could provide new insights into human biology. Here the authors carry out RNA sequencing in a large collection of mouse tissues and compare these data to human transcriptome profiles, identifying a set of constrained genes that carry out basic cellular functions with remarkably constant expression levels across tissues and species.

Published
2015
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7. Enhanced Transcriptome Maps from Multiple Mouse Tissues Reveal Evolutionary Constraint in Gene Expression for Thousands of Genes

Author

Lei Hoon See, Cedric Notredame, Arif Harmanci, Dmitri D. Pervouchine, Pablo Prieto Barja, Jean Monlong, Michael A. Beer, Alexander Dobin, Mark Gerstein, Alessandra Breschi, Huaien Wang, Andrea Tanzer, Baikang Pei, Meagan Fastuca, Jorg Drenkow, Suganthi Balasubramanian, Chris Zaleski, Thomas R. Gingeras, Julien Lagarde, Roderic Guigó, Sarah Djebali, Giovanni Bussotti, and Carrie A. Davis

Subjects
Transcriptome, Genetics, Cell type, Alternative splicing, Gene expression, Computational biology, Epigenetics, Biology, Gene, Embryonic stem cell, Phenotype
Abstract

We characterized by RNA-seq the transcriptional profiles of a large and heterogeneous collection of mouse tissues, augmenting the mouse transcriptome with thousands of novel transcript candidates. Comparison with transcriptome profiles obtained in human cell lines reveals substantial conservation of transcriptional programs, and uncovers a distinct class of genes with levels of expression across cell types and species, that have been constrained early in vertebrate evolution. This core set of genes capture a substantial and constant fraction of the transcriptional output of mammalian cells, and participates in basic functional and structural housekeeping processes common to all cell types. Perturbation of these constrained genes is associated with significant phenotypes including embryonic lethality and cancer. Evolutionary constraint in gene expression levels is not reflected in the conservation of the genomic sequences, but it is associated with strong and conserved epigenetic marking, as well as to a characteristic post-transcriptional regulatory program in which sub-cellular localization and alternative splicing play comparatively large roles.

Published
2014
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8. The GENCODE pseudogene resource

Author

Jennifer Harrow, Alexandre Reymond, Suganthi Balasubramanian, Rachel A. Harte, Lukas Habegger, Baikang Pei, Tim Hubbard, Adam Frankish, Andrea Tanzer, Xinmeng Jasmine Mu, Mark Diekhans, Cristina Sisu, Mark Gerstein, and Cédric Howald

Subjects
Primates, Transcription, Genetic, Pseudogene, Computational biology, Regulatory Sequences, Nucleic Acid, Biology, ENCODE, Genome, 03 medical and health sciences, 0302 clinical medicine, Animals, Humans, Selection, Genetic, 1000 Genomes Project, Phylogeny, 030304 developmental biology, Genetics, 0303 health sciences, Binding Sites, Models, Statistical, Models, Genetic, Genome, Human, GENCODE, Research, Molecular Sequence Annotation, Sequence Analysis, DNA, Chromatin, 030220 oncology & carcinogenesis, Human genome, RNA Polymerase II, Functional genomics, Pseudogenes, Transcription Factors
Abstract

BACKGROUND: Pseudogenes have long been considered as nonfunctional genomic sequences. However, recent evidence suggests that many of them might have some form of biological activity, and the possibility of functionality has increased interest in their accurate annotation and integration with functional genomics data. RESULTS: As part of the GENCODE annotation of the human genome, we present the first genome-wide pseudogene assignment for protein-coding genes, based on both large-scale manual annotation and in silico pipelines. A key aspect of this coupled approach is that it allows us to identify pseudogenes in an unbiased fashion as well as untangle complex events through manual evaluation. We integrate the pseudogene annotations with the extensive ENCODE functional genomics information. In particular, we determine the expression level, transcription-factor and RNA polymerase II binding, and chromatin marks associated with each pseudogene. Based on their distribution, we develop simple statistical models for each type of activity, which we validate with large-scale RT-PCR-Seq experiments. Finally, we compare our pseudogenes with conservation and variation data from primate alignments and the 1000 Genomes project, producing lists of pseudogenes potentially under selection. CONCLUSIONS: At one extreme, some pseudogenes possess conventional characteristics of functionality; these may represent genes that have recently died. On the other hand, we find interesting patterns of partial activity, which may suggest that dead genes are being resurrected as functioning non-coding RNAs. The activity data of each pseudogene are stored in an associated resource, psiDR, which will be useful for the initial identification of potentially functional pseudogenes.

Published
2012

9. Landscape of transcription in human cells

Author

Tyler Alioto, Colin Kingswood, Lorian Schaffer, Sylvain Foissac, Kimberly Bell, Diane Trout, Wei Lin, Nathalie Walters, Thomas R. Gingeras, Oscar Junhong Luo, Pedro G. Ferreira, Atif Shahab, Assaf Gordon, Kata Fejes-Toth, Joao Curado, Jacqueline Chrast, Thomas Derrien, Georgi K. Marinov, Hazuki Takahashi, Alexander Dobin, Nadav Bar, Lei-Hoon See, Morgan C. Giddings, Erica Dumais, Michael Sammeth, Philipp Kapranov, Jainab Khatun, Meagan Fastuca, Jørgen Skancke, Ian Bell, Emilie Falconnet, Roderic Guigó, Huaien Wang, Kimberly Persaud, Alexandre Reymond, Carrie A. Davis, Xiaoan Ruan, Rehab F. Abdelhamid, Daniel Robyr, Joel Rozowsky, Ana Maria Suzuki, Sonali Jha, Marion S. Röder, Sudipto K. Chakrabortty, Brian A. Risk, Hagen Tilgner, Eddie Park, Stylianos E. Antonarakis, Piero Carninci, Hui Gao, Sarah Djebali, Timo Lassmann, Andrea Tanzer, Philippe Batut, Cédric Howald, Yanbao Yu, Ali Mortazavi, Felix Kokocinski, Jennifer Harrow, Mark Gerstein, Melissa J. Fullwood, Chenghai Xue, Gregory J. Hannon, Xian Chen, Igor Antoshechkin, Yoshihide Hayashizaki, Brian A. Williams, Chris Zaleski, John A. Wrobel, Radha Duttagupta, Barbara J. Wold, Julien Lagarde, David Gonzalez, Yijun Ruan, Tim Hubbard, Angelika Merkel, Rory Johnson, Jonathan B. Preall, Jorg Drenkow, Brandon King, Paolo Ribeca, Harsha P. Gunawardena, Jacqueline Dumais, Felix Schlesinger, Michael T. Baer, Centre for Genomic Regulation, Barcelona Institute of Science and Technology (BIST), Universitat Pompeu Fabra [Barcelona] (UPF), Cold Spring Harbor Laboratory, Riken Yokohama Institute, California Institute of Technology (CALTECH), University of California [Irvine] (UCI), University of California, Boise State University, Yale University [New Haven], The Wellcome Trust Sanger Institute [Cambridge], Centro Nacional de Analisis Genomico [Barcelona] (CNAG), Norwegian University of Science and Technology [Trondheim] (NTNU), Norwegian University of Science and Technology (NTNU), Affymetrix Inc., University of North Carolina [Chapel Hill] (UNC), University of North Carolina System (UNC), Université de Lausanne (UNIL), Laboratoire de Génétique Cellulaire (LGC), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, University of Geneva [Switzerland], (IGE3 Inst Genet & Genom Geneva), University of Geneva Medical School, Genome Institute of Singapore (GIS), St Laurent Institut, Falconnet, Emilie, Robyr, Daniel, Reymond, Alexandre, Antonarakis, Stylianos, Universitat Pompeu Fabra [Barcelona], Ecole Nationale Vétérinaire de Toulouse (ENVT), and Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Recherche Agronomique (INRA)

Subjects
Encyclopedias as Topic, Repetitive Sequences, Nucleic Acid/genetics, Polyadenylation, [SDV]Life Sciences [q-bio], Genoma humà, Genome, Repetitive Sequences, RNA Editing/genetics, 0302 clinical medicine, Exons/genetics, Protein Isoforms, RNA/biosynthesis/genetics, ddc:576.5, RNA Splicing/genetics, Genetics, 0303 health sciences, Multidisciplinary, Exons, Genomics, Transcriptome/genetics, Long non-coding RNA, Enhancer Elements, Genetic, 030220 oncology & carcinogenesis, Sequence Analysis, Transcription, Human, Enhancer Elements, General Science & Technology, 1.1 Normal biological development and functioning, RNA Splicing, DNA, Intergenic/genetics, Computational biology, DNA/genetics, Biology, Article, Cell Line, 03 medical and health sciences, Genetic, Underpinning research, Protein Isoforms/genetics, map, expression, Humans, Genes/genetics, genome, Gene, Alleles, Transcription, Genetic/genetics, 030304 developmental biology, Intergenic, Nucleic Acid, small rnas, Sequence Analysis, RNA, Gene Expression Profiling, Human Genome, RNA, Molecular Sequence Annotation, DNA, Regulatory Sequences, Nucleic Acid/genetics, Gene expression profiling, Genes, Genome, Human/genetics, Polyadenylation/genetics, RNA/biosynthesis, RNA/genetics, enhancer, identification, Human genome, Generic health relevance, RNA Editing, Transcriptome, Regulatory Sequences, Genètica
Abstract

Eukaryotic cells make many types of primary and processed RNAs that are found either in specific subcellular compartments or throughout the cells. A complete catalogue of these RNAs is not yet available and their characteristic subcellular localizations are also poorly understood. Because RNA represents the direct output of the genetic information encoded by genomes and a significant proportion of a cell's regulatory capabilities are focused on its synthesis, processing, transport, modification and translation, the generation of such a catalogue is crucial for understanding genome function. Here we report evidence that three-quarters of the human genome is capable of being transcribed, as well as observations about the range and levels of expression, localization, processing fates, regulatory regions and modifications of almost all currently annotated and thousands of previously unannotated RNAs. These observations, taken together, prompt a redefinition of the concept of a gene. This work was supported by the National Human Genome Research Institute (NHGRI) production grants U54HG004557, U54HG004555, U54HG004576 and U54HG004558, and by the NHGRI pilot grant R01HG003700. It was also supported by the NHGRI ARRA stimulus grant 1RC2HG005591, the National Science Foundation (SNF) grant 127375, the European Research Council (ERC) grant/n249968, a research grant for the RIKEN Omics Science Center from the Japanese Ministry of Education, Culture, Sports, Science and Technology, and grants BIO2011-26205, CSD2007-00050 and INB GNV-1 from the Spanish Ministry of Science

Published
2012
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10. A User's Guide to the Encyclopedia of DNA Elements (ENCODE)

Author

Zhi Lu, Giltae Song, Troy W. Whitfield, Vishwanath R. Iyer, Teresa Vales, Angelika Merkel, Max Libbrecht, David Haussler, Ting Wang, Kristen Lee, Lingyun Song, Richard M. Myers, Alfonso Valencia, Rachel A. Harte, Xiaoqin Xu, Lucas D. Ward, Hazuki Takahashi, Nathan C. Sheffield, Thomas Derrien, Georgi K. Marinov, Eric D. Nguyen, Bernard B. Suh, Brian J. Raney, Richard Sandstrom, Thomas D. Tullius, Benoit Miotto, Alexander Dobin, Youhan Xu, Lukas Habegger, Ian Dunham, Brian A. Risk, Paul G. Giresi, Morgan C. Giddings, Hualin Xi, Anshul Kundaje, Robert S. Harris, Devin Absher, Peter J. Bickel, Yanbao Yu, Browen Aken, Colin Kingswood, Bryan R. Lajoie, Peter J. Good, Katrina Learned, Laura Elnitski, Shirley Pepke, Brandon King, Piero Carninci, Xinqiong Yang, Ghia Euskirchen, Kathryn Beal, Christelle Borel, Michael Muratet, Robert L. Grossman, David G. Knowles, Zarmik Moqtaderi, Veronika Boychenko, Steven P. Wilder, Michael L. Tress, Florencia Pauli, Alan P. Boyle, Andrea Tanzer, Philipp Kapranov, Serafim Batzoglou, Audra K. Johnson, Jun Neri, Nitin Bhardwaj, Elise A. Feingold, Venkat S. Malladi, Michael M. Hoffman, William Stafford Noble, Andrea Sboner, Mark Gerstein, Stephanie L. Parker, Jacqueline Dumais, Felix Schlesinger, Deborah R. Winter, Randall H. Brown, Thanh Truong, Rebecca F. Lowdon, Paolo Ribeca, Brooke Rhead, Peggy J. Farnham, Krista Thibeault, Terrence S. Furey, Donna Karolchik, Alec Victorsen, Xiaoan Ruan, Rehab F. Abdelhamid, Amy S. Nesmith, Jing Wang, Nicholas M. Luscombe, Alina R. Cao, Diane Trout, Teri Slifer, Peter E. Newburger, Cricket A. Sloan, Dimitra Lotakis, Stephen M. J. Searle, Ali Mortazavi, Alexandra Bignell, Alex Reynolds, Orion J. Buske, Chris Zaleski, Theresa K. Canfield, Ian Bell, Jin Lian, Vanessa K. Swing, Katalin Toth Fejes, Catherine Ucla, Robert E. Thurman, Jacqueline Chrast, Wei Lin, Tim Hubbard, Gary Saunders, Minyi Shi, Vihra Sotirova, Sherman M. Weissman, Jason D. Lieb, Richard Humbert, Kevin M. Bowling, Assaf Gordon, Tarjei S. Mikkelsen, Jing Leng, Thomas R. Gingeras, Fabian Grubert, Nader Jameel, Jost Vielmetter, Hannah Monahan, Preti Jain, Lindsay L. Waite, Tony Shafer, Joel Rozowsky, Michael Coyne, Brian Reed, M. Kay, Harsha P. Gunawardena, Ross C. Hardison, Gavin Sherlock, Alexandra Charos, Joseph D. Fleming, Ann S. Zweig, Jason Gertz, Rajinder Kaul, Xianjun Dong, Alexandre Reymond, Carrie A. Davis, Haiyan Huang, Chao Cheng, Marco Mariotti, Phil Lacroute, Jason A. Dilocker, Kenneth McCue, R. Robilotto, Stylianos E. Antonarakis, Sridar V. Chittur, Justin Jee, Barbara J. Wold, Sudipto K. Chakrabortty, Erica Dumais, Amartya Sanyal, Nathan Boley, Tianyuan Wang, Julien Lagarde, Anthony Kirilusha, Jonathan B. Preall, Kevin Roberts, Erika Giste, Hugo Y. K. Lam, Alvis Brazma, Gregory J. Hannon, Eric Rynes, Philippe Batut, Kevin Struhl, Margus Lukk, Manching Ku, Suganthi Balasubramanian, Sonali Jha, Jorg Drenkow, W. James Kent, Michael Snyder, Jie Wang, Anna Battenhouse, Charles B. Epstein, Rami Rauch, Christopher Shestak, John A. Stamatoyannopoulos, Gaurab Mukherjee, Cédric Howald, Tanya Kutyavin, Huaien Wang, Scott A. Tenenbaum, Wan Ting Poh, Kate R. Rosenbloom, Manolis Kellis, Pauline A. Fujita, Linfeng Wu, Anita Bansal, Molly Weaver, Linda L. Grasfeder, Peter J. Sabo, Qiang Li, Melissa S. Cline, Robert M. Kuhn, Darin London, Seth Frietze, Atif Shahab, Shane Neph, Damian Keefe, James B. Brown, Mark Diekhans, Webb Miller, Katherine Aylor Fisher, Jiang Du, Hadar H. Sheffer, Sarah Djebali, Frank Doyle, Nathan Lamarre-Vincent, Chia-Lin Wei, Laura A.L. Dillon, Jennifer Harrow, Robert C. Altshuler, Tyler Alioto, Raymond K. Auerbach, Adam Frankish, Rebekka O. Sprouse, Patrick J. Collins, E. Christopher Partridge, Zheng Liu, Yoichiro Shibata, Elliott H. Margulies, Abigail K. Ebersol, Kimberly A. Showers, Eric D. Green, Krishna M. Roskin, Job Dekker, Barbara N. Pusey, Ekta Khurana, Gilberto DeSalvo, Yijun Ruan, Hao Wang, Jainab Khatun, Henriette O'Geen, Alexej Abyzov, Brian Williams, Ryan M. McDaniell, Maya Kasowski, Manoj Hariharan, Felix Kokocinski, Gloria Despacio-Reyes, Zhancheng Zhang, Subhradip Karmakar, Ewan Birney, Koon-Kiu Yan, Xian Chen, Shinny Vong, Daniel Sobral, Nick Bild, Seul K.C. Kim, Timo Lassmann, Li Wang, Minerva E. Sanchez, Vaughan Roach, Theodore Gibson, Stephen C. J. Parker, Michael F. Lin, Patrick A. Navas, Laurence R. Meyer, Luiz O. F. Penalva, Bradley E. Bernstein, Kevin P. White, Emilie Aït Yahya Graison, Juan M. Vaquerizas, Sushma Iyengar, Kimberly M. Newberry, Akshay Bhinge, Xiaolan Zhang, Kim Bell, Yoshihide Hayashizaki, Lucas Lochovsky, Noam Shoresh, Hagen Tilgner, Philip Cayting, Dorrelyn Patacsil, Timothy E. Reddy, Eric Haugen, Katherine E. Varley, M. van Baren, Nathan D. Trinklein, Bum Kyu Lee, Tristan Frum, Marianne Lindahl-Allen, Timothy Durham, Roderic Guigó, Christopher W. Maier, Micha Sammeth, Debasish Raha, Timothy R. Dreszer, Benedict Paten, Robbyn Issner, Michael R. Brent, Kevin Y. Yip, Kim Blahnik, Jason Ernst, Zhiping Weng, Henry Amrhein, Arend Sidow, Javier Herrero, Hui Gao, Stephen G. Landt, Pouya Kheradpour, Galt P. Barber, Gregory E. Crawford, Toby Hunt, HudsonAlpha Institute for Biotechnology [Huntsville, AL], ENCODE Project Consortium : Myers RM, Stamatoyannopoulos J, Snyder M, Dunham I, Hardison RC, Bernstein BE, Gingeras TR, Kent WJ, Birney E, Wold B, Crawford GE, Bernstein BE, Epstein CB, Shoresh N, Ernst J, Mikkelsen TS, Kheradpour P, Zhang X, Wang L, Issner R, Coyne MJ, Durham T, Ku M, Truong T, Ward LD, Altshuler RC, Lin MF, Kellis M, Gingeras TR, Davis CA, Kapranov P, Dobin A, Zaleski C, Schlesinger F, Batut P, Chakrabortty S, Jha S, Lin W, Drenkow J, Wang H, Bell K, Gao H, Bell I, Dumais E, Dumais J, Antonarakis SE, Ucla C, Borel C, Guigo R, Djebali S, Lagarde J, Kingswood C, Ribeca P, Sammeth M, Alioto T, Merkel A, Tilgner H, Carninci P, Hayashizaki Y, Lassmann T, Takahashi H, Abdelhamid RF, Hannon G, Fejes-Toth K, Preall J, Gordon A, Sotirova V, Reymond A, Howald C, Graison E, Chrast J, Ruan Y, Ruan X, Shahab A, Ting Poh W, Wei CL, Crawford GE, Furey TS, Boyle AP, Sheffield NC, Song L, Shibata Y, Vales T, Winter D, Zhang Z, London D, Wang T, Birney E, Keefe D, Iyer VR, Lee BK, McDaniell RM, Liu Z, Battenhouse A, Bhinge AA, Lieb JD, Grasfeder LL, Showers KA, Giresi PG, Kim SK, Shestak C, Myers RM, Pauli F, Reddy TE, Gertz J, Partridge EC, Jain P, Sprouse RO, Bansal A, Pusey B, Muratet MA, Varley KE, Bowling KM, Newberry KM, Nesmith AS, Dilocker JA, Parker SL, Waite LL, Thibeault K, Roberts K, Absher DM, Wold B, Mortazavi A, Williams B, Marinov G, Trout D, Pepke S, King B, McCue K, Kirilusha A, DeSalvo G, Fisher-Aylor K, Amrhein H, Vielmetter J, Sherlock G, Sidow A, Batzoglou S, Rauch R, Kundaje A, Libbrecht M, Margulies EH, Parker SC, Elnitski L, Green ED, Hubbard T, Harrow J, Searle S, Kokocinski F, Aken B, Frankish A, Hunt T, Despacio-Reyes G, Kay M, Mukherjee G, Bignell A, Saunders G, Boychenko V, Van Baren M, Brown RH, Khurana E, Balasubramanian S, Zhang Z, Lam H, Cayting P, Robilotto R, Lu Z, Guigo R, Derrien T, Tanzer A, Knowles DG, Mariotti M, James Kent W, Haussler D, Harte R, Diekhans M, Kellis M, Lin M, Kheradpour P, Ernst J, Reymond A, Howald C, Graison EA, Chrast J, Tress M, Rodriguez JM, Snyder M, Landt SG, Raha D, Shi M, Euskirchen G, Grubert F, Kasowski M, Lian J, Cayting P, Lacroute P, Xu Y, Monahan H, Patacsil D, Slifer T, Yang X, Charos A, Reed B, Wu L, Auerbach RK, Habegger L, Hariharan M, Rozowsky J, Abyzov A, Weissman SM, Gerstein M, Struhl K, Lamarre-Vincent N, Lindahl-Allen M, Miotto B, Moqtaderi Z, Fleming JD, Newburger P, Farnham PJ, Frietze S, O'Geen H, Xu X, Blahnik KR, Cao AR, Iyengar S, Stamatoyannopoulos JA, Kaul R, Thurman RE, Wang H, Navas PA, Sandstrom R, Sabo PJ, Weaver M, Canfield T, Lee K, Neph S, Roach V, Reynolds A, Johnson A, Rynes E, Giste E, Vong S, Neri J, Frum T, Johnson EM, Nguyen ED, Ebersol AK, Sanchez ME, Sheffer HH, Lotakis D, Haugen E, Humbert R, Kutyavin T, Shafer T, Dekker J, Lajoie BR, Sanyal A, James Kent W, Rosenbloom KR, Dreszer TR, Raney BJ, Barber GP, Meyer LR, Sloan CA, Malladi VS, Cline MS, Learned K, Swing VK, Zweig AS, Rhead B, Fujita PA, Roskin K, Karolchik D, Kuhn RM, Haussler D, Birney E, Dunham I, Wilder SP, Keefe D, Sobral D, Herrero J, Beal K, Lukk M, Brazma A, Vaquerizas JM, Luscombe NM, Bickel PJ, Boley N, Brown JB, Li Q, Huang H, Gerstein M, Habegger L, Sboner A, Rozowsky J, Auerbach RK, Yip KY, Cheng C, Yan KK, Bhardwaj N, Wang J, Lochovsky L, Jee J, Gibson T, Leng J, Du J, Hardison RC, Harris RS, Song G, Miller W, Haussler D, Roskin K, Suh B, Wang T, Paten B, Noble WS, Hoffman MM, Buske OJ, Weng Z, Dong X, Wang J, Xi H, Tenenbaum SA, Doyle F, Penalva LO, Chittur S, Tullius TD, Parker SC, White KP, Karmakar S, Victorsen A, Jameel N, Bild N, Grossman RL, Snyder M, Landt SG, Yang X, Patacsil D, Slifer T, Dekker J, Lajoie BR, Sanyal A, Weng Z, Whitfield TW, Wang J, Collins PJ, Trinklein ND, Partridge EC, Myers RM, Giddings MC, Chen X, Khatun J, Maier C, Yu Y, Gunawardena H, Risk B, Feingold EA, Lowdon RF, Dillon LA, Good PJ, Harrow J, Searle S., Becker, Peter B, Broad Institute of MIT and Harvard, Lincoln Laboratory, Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology. Department of Physics, Kellis, Manolis, Epstein, Charles B., Bernstein, Bradley E., Shoresh, Noam, Ernst, Jason, Mikkelsen, Tarjei Sigurd, Kheradpour, Pouya, Zhang, Xiaolan, Wang, Li, Issner, Robbyn, Coyne, Michael J., Durham, Timothy, Ku, Manching, Truong, Thanh, Ward, Lucas D., Altshuler, Robert Charles, Lin, Michael F., ENCODE Project Consortium, Antonarakis, Stylianos, and Miotto, Benoit

Subjects
RNA, Messenger/genetics, [SDV]Life Sciences [q-bio], Messenger, Genoma humà, Genome, Medical and Health Sciences, 0302 clinical medicine, Models, ddc:576.5, Biology (General), Conserved Sequence, Genetics, 0303 health sciences, General Neuroscience, RNA-Binding Proteins, Genomics, Biological Sciences, Chromatin, 3. Good health, [SDV] Life Sciences [q-bio], DNA-Binding Proteins, Gene Components, 030220 oncology & carcinogenesis, DNA methylation, Encyclopedia, HIV/AIDS, Proteïnes de la sang -- Aspectes genètics, General Agricultural and Biological Sciences, Databases, Nucleic Acid, Human, Research Article, Quality Control, Process (engineering), QH301-705.5, 1.1 Normal biological development and functioning, Computational biology, Biology, ENCODE, General Biochemistry, Genetics and Molecular Biology, Chromatin/metabolism, Vaccine Related, 03 medical and health sciences, Databases, Genetic, Underpinning research, Humans, RNA, Messenger, RNA-Binding Proteins/genetics/metabolism, Vaccine Related (AIDS), Gene, 030304 developmental biology, Internet, General Immunology and Microbiology, Nucleic Acid, Agricultural and Veterinary Sciences, Base Sequence, Models, Genetic, Genome, Human, Prevention, Human Genome, Computational Biology, DNA Methylation, ENCODE Project Consortium, Gene Expression Regulation, DNA-Binding Proteins/genetics/metabolism, RNA, Human genome, Immunization, Generic health relevance, Developmental Biology
Abstract

The mission of the Encyclopedia of DNA Elements (ENCODE) Project is to enable the scientific and medical communities to interpret the human genome sequence and apply it to understand human biology and improve health. The ENCODE Consortium is integrating multiple technologies and approaches in a collective effort to discover and define the functional elements encoded in the human genome, including genes, transcripts, and transcriptional regulatory regions, together with their attendant chromatin states and DNA methylation patterns. In the process, standards to ensure high-quality data have been implemented, and novel algorithms have been developed to facilitate analysis. Data and derived results are made available through a freely accessible database. Here we provide an overview of the project and the resources it is generating and illustrate the application of ENCODE data to interpret the human genome., National Human Genome Research Institute (U.S.), National Institutes of Health (U.S.)

Published
2011
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11. Nucleotide-resolution analysis of structural variants using BreakSeq and a breakpoint library

Author

Adrian M. Stütz, Mark Gerstein, Michael Snyder, Xinmeng Jasmine Mu, Andrea Tanzer, Philip Cayting, Hugo Y. K. Lam, Jan O. Korbel, and Philip M. Kim

Subjects
Primates, Biomedical Engineering, Non-allelic homologous recombination, Chromosome Breakpoints, Bioengineering, Computational biology, Biology, Applied Microbiology and Biotechnology, Genome, Article, Bias, Phylogenetics, Animals, Humans, Genomic library, Genotyping, Phylogeny, Gene Library, Genetics, Nucleotides, Breakpoint, Chromosome Mapping, Genetic Variation, Sequence Analysis, DNA, Genetic Loci, Molecular Medicine, Sequence motif, Biotechnology
Abstract

Structural variants (SVs) are a major source of human genomic variation; however, characterizing them at nucleotide resolution remains challenging. Here we assemble a library of breakpoints at nucleotide resolution from collating and standardizing ~2,000 published SVs. For each breakpoint, we infer its ancestral state (through comparison to primate genomes) and its mechanism of formation (e.g., non-allelic homologous recombination, NAHR). We characterize breakpoint sequences with respect to genomic landmarks, chromosomal location, sequence motifs and physical properties, finding that the occurrence of insertions and deletions is more balanced than previously reported and that NAHR-formed breakpoints are associated with relatively rigid, stable DNA helices. Finally, we demonstrate an approach, BreakSeq, for scanning the reads from short-read sequenced genomes against our breakpoint library to accurately identify previously overlooked SVs, which we then validate by PCR. As new data become available, we expect our BreakSeq approach will become more sensitive and facilitate rapid SV genotyping of personal genomes.

Published
2009

12. Identification and analysis of functional elements in 1% of the human genome by the ENCODE pilot project

Author

Nan Jiang, Alfonso Valencia, Rachel A. Harte, Abigail Woodroffe, Michael Seringhaus, Andrew Haydock, Eugene Davydov, Todd M. Lowe, Peggy J. Farnham, Robert E. Thurman, Tyler Alioto, Adam Ameur, Morgan Park, Roderic Guigó, Archana Thakkapallayil, Philipp Kapranov, Francis S. Collins, Donna Karolchik, Stefan Washietl, Kerstin Lindblad-Toh, Michael L. Tress, Barbara E. Stranger, Gregory M. Cooper, Kun Wang, Thomas R. Gingeras, Serafim Batzoglou, Peter D. Ellis, Annie Yang, Stylianos E. Antonarakis, Jonghwan Kim, Robert M. Andrews, W. James Kent, Kuo Ping Chiu, Madhavan Ganesh, Jason D. Lieb, Shane Neph, Albin Sandelin, Michael Hawrylycz, Eric S. Lander, Matthew T. Weirauch, Nick Goldman, Alexander E. Urban, Ian Bell, Anason S. Halees, Jan Komorowski, Webb Miller, Kandhadayar G. Srinivasan, Evelyn Cheung, David B. Jaffe, Peter J. Good, Gregory Lefebvre, Yuko Yoshinaga, Sylvain Foissac, Alexander W. Bruce, Mark Dickson, Christoph M. Koch, Antigone S. Dimas, Zhengdong D. Zhang, Matthew J. Oberley, Paul I.W. de Bakker, Arend Sidow, Xueqing Zhang, Molly Weaver, Jane Rogers, Jacquelyn R. Idol, Jeff Goldy, Haiyan Huang, William Stafford Noble, Angie S. Hinrichs, Sandeep Patel, David A. Nix, Lluís Armengol, Siew Woh Choo, Hong Sain Ooi, Sara Van Calcar, Ivan Adzhubei, Job Dekker, Sara J. Cooper, Hari Tammana, Valerie Maduro, Jason A. Greenbaum, Bing Ren, Sharon L. Squazzo, Jennifer C. McDowell, Chikatoshi Kai, Ivo L. Hofacker, Ian Dunham, Peter J. Bickel, Nancy Holroyd, Eduardo Eyras, Julien Lagarde, Fei Yao, Man Yu, Piero Carninci, Chia-Lin Wei, Alice C. Young, Yong Yu, Daryl J. Thomas, George Asimenos, Xiaoqin Xu, Galt P. Barber, Andrea Tanzer, Juan I. Montoya-Burgos, Sujit Dike, Nathan Day, Gregory E. Crawford, Michele Clamp, Todd Richmond, Nuria Lopez-Bigas, Vishwanath R. Iyer, Ewan Birney, Richard Humbert, Gary C. Hon, David Swarbreck, Xiaobin Guan, Sarah Wilcox, Nate Heintzman, Josep F. Abril, Elaine R. Mardis, Stefan Enroth, Charlie W.H. Lee, Nicholas Matthews, Benedict Paten, Robert Castelo, Michael A. Singer, Mousheng Xu, Chiou Yu Choo, Nancy F. Hansen, Elizabeth Rosenzweig, Patrick A. Navas, Jacqueline Chrast, Brett E. Johnson, Jan O. Korbel, Simon Whelan, Stephen Hartman, Ulas Karaoz, Ingileif B. Hallgrímsdóttir, David Haussler, Michael R. Brent, Jill Cheng, Gonçalo R. Abecasis, Ann S. Zweig, Sherman M. Weissman, Michael O. Dorschner, Jin Lian, Vinsensius B. Vega, Cordelia Langford, Alexandre Reymond, Mark Gerstein, Pawandeep Dhami, Ola Wallerman, Huaiyang Jiang, Lior Pachter, James Taylor, Eric A. Stone, David R. Inman, Yijun Ruan, Peter E. Newburger, Roland Green, Ari Löytynoja, Shelley Force Aldred, Alvaro Rada-Iglesias, Baishali Maskeri, Joel Rozowsky, Jorg Drenkow, Colin N. Dewey, Srinka Ghosh, Yutao Fu, Kayla E. Smith, Xavier Estivill, Donna M. Muzny, Christine P. Bird, Tim Hubbard, Jana Hertel, Kristin Missal, Neerja Karnani, Ericka M. Johnson, Nan Zhang, Zhou Zhu, Stephen C. J. Parker, Minmei Hou, Charlotte N. Henrichsen, Heather A. Hirsch, Caroline Manzano, Laura A. Liefer, Kim C. Worley, Robert Baertsch, Mark S. Guyer, Ross C. Hardison, Zheng Lian, Hiram Clawson, Leah O. Barrera, Manja Lindemeyer, James Cuff, Chunxu Qu, Jun Kawai, Jennifer Hillman-Jackson, Eric D. Green, Robert W. Blakesley, Abel Ureta-Vidal, Rhona K. Stuart, Fabio Pardi, Peter J. Sabo, Edward A. Sekinger, John S. Mattick, Ankit Malhotra, Taane G. Clark, James G. R. Gilbert, James C. Mullikin, Deyou Zheng, Robert M. Kuhn, Tae Hoon Kim, M. Geoff Rosenfeld, Kirsten Lee, Jörg Hackermüller, Oliver M. Dovey, Deanna M. Church, Kyle J. Munn, Peter F. Stadler, Phillippe Couttet, Claudia Fried, Jaafar N. Haidar, Kris A. Wetterstrand, Wing-Kin Sung, Paul G. Giresi, Jia Qian Wu, Ruth Taylor, David A. Wheeler, Zarmik Moqtaderi, Adam Siepel, Michael Snyder, Ian Holmes, Jun Liu, Olof Emanuelsson, Kevin Struhl, Saurabh Asthana, Akshay Bhinge, Adam Frankish, Yoshihide Hayashizaki, Ghia Euskirchen, Joel D. Martin, Robert S. Fulton, Ugrappa Nagalakshmi, Heike Fiegler, Gayle K. Clelland, Shane C. Dillon, Fidencio Neri, Elliott H. Margulies, Sean Davis, Mark Bieda, Tristan Frum, Michael S. Kuehn, Heather Trumbower, Pamela J. Thomas, Kazutoyo Osoegawa, Richard A. Gibbs, Emmanouil T. Dermitzakis, Julian L. Huppert, Richard K. Wilson, Tina Graves, Zhiping Weng, Anthony Shafer, Baoli Zhu, Christopher K. Glass, Patrick J. Boyle, Hennady P. Shulha, Maxim Koriabine, Christoph Flamm, David Vetrie, Nigel P. Carter, Patrick Ng, Peter Kraus, John A. Stamatoyannopoulos, George M. Weinstock, Tim Massingham, Jane M. Lin, Damian Keefe, Jean L. Chang, Shamil R. Sunyaev, Sergey Nikolaev, Kate R. Rosenbloom, Carine Wyss, Hua Cao, Keith D. James, Michael C. Zody, Gerard G. Bouffard, Atif Shahab, Nathan D. Trinklein, James B. Brown, Erica Sodergren, Xiaodong Zhao, Rosa Luna, Sante Gnerre, Paul Flicek, Joanna C. Fowler, Andrew D. Kern, Jakob Skou Pedersen, David C. King, Anindya Dutta, Elise A. Feingold, Richard M. Myers, Richard Sandstrom, Catherine Ucla, Thomas D. Tullius, Mikhail Nefedov, Claes Wadelius, Jennifer Harrow, Christopher M. Taylor, Xiaoling Zhang, Pieter J. de Jong, Dermitzakis, Emmanouil, and Reymond, Alexandre

Subjects
DNA Replication, RNA, Messenger/genetics, Chromatin Immunoprecipitation, Heterozygote, RNA, Untranslated, Transcription, Genetic, Systems biology, Histones/metabolism, RNA, Untranslated/genetics, Pilot Projects, Genomics, Computational biology, Regulatory Sequences, Nucleic Acid, Biology, ENCODE, Genome, Article, DNase-Seq, Histones, Evolution, Molecular, Exons/genetics, Humans, ddc:576.5, Transcription Factors/metabolism, RNA, Messenger, Conserved Sequence, Chromatin/genetics/metabolism, Genetics, Transcription, Genetic/ genetics, Multidisciplinary, Genome, Human, GENCODE, Genetic Variation, Exons, Chromatin, Genetic Variation/genetics, Regulatory Sequences, Nucleic Acid/ genetics, Human genome, Conserved Sequence/genetics, Transcription Initiation Site, Functional genomics, Genome, Human/ genetics, Transcription Factors, Protein Binding
Abstract

We report the generation and analysis of functional data from multiple, diverse experiments performed on a targeted 1% of the human genome as part of the pilot phase of the ENCODE Project. These data have been further integrated and augmented by a number of evolutionary and computational analyses. Together, our results advance the collective knowledge about human genome function in several major areas. First, our studies provide convincing evidence that the genome is pervasively transcribed, such that the majority of its bases can be found in primary transcripts, including non-protein-coding transcripts, and those that extensively overlap one another. Second, systematic examination of transcriptional regulation has yielded new understanding about transcription start sites, including their relationship to specific regulatory sequences and features of chromatin accessibility and histone modification. Third, a more sophisticated view about chromatin structure has emerged, including its interrelationship with DNA replication and transcriptional regulation. Finally, integration of these new sources of information, in particular with respect to mammalian evolution based on inter- and intra-species sequence comparisons, has yielded novel mechanistic and evolutionary insights about the functional landscape of the human genome. Together, these studies are defining a path forward to pursue a more-comprehensive characterisation of human genome function.

Published
2007
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13. Structured RNAs in the ENCODE selected regions of the human genome

Author

Stefan Washietl, Jakob S. Pedersen, Jan O. Korbel, Claudia Stocsits, Andreas R. Gruber, Jörg Hackermüller, Jana Hertel, Manja Lindemeyer, Kristin Reiche, Andrea Tanzer, Catherine Ucla, Carine Wyss, Stylianos E. Antonarakis, France Denoeud, Julien Lagarde, Jorg Drenkow, Philipp Kapranov, Thomas R. Gingeras, Roderic Guigó, Michael Snyder, Mark B. Gerstein, Alexandre Reymond, Ivo L. Hofacker, Peter F. Stadler, and Publica

Subjects
RNA, Messenger/genetics, Letter, RNA, Untranslated, Transcription, Genetic, Molecular Sequence Data, Quantitative Trait Loci, Context (language use), Computational biology, Biology, Genome, Conserved sequence, Genetics, Humans, RNA, Messenger, 3' Untranslated Regions, Genetics (clinical), ddc:616, Genètica humana, Tiling array, Base Sequence, GENCODE, Genome, Human, Reverse Transcriptase Polymerase Chain Reaction, RNA, Untranslated/ genetics, RNA, Non-coding RNA, GC Rich Sequence, ARN, Human genome
Abstract

Functional RNA structures play an important role both in the context of noncoding RNA transcripts as well as regulatory elements in mRNAs. Here we present a computational study to detect functional RNA structures within the ENCODE regions of the human genome. Since structural RNAs in general lack characteristic signals in primary sequence, comparative approaches evaluating evolutionary conservation of structures are most promising. We have used three recently introduced programs based on either phylogenetic-stochastic context-free grammar (EvoFold) or energy directed folding (RNAz and AlifoldZ), yielding several thousand candidate structures (corresponding to approximately 2.7% of the ENCODE regions). EvoFold has its highest sensitivity in highly conserved and relatively AU-rich regions, while RNAz favors slightly GC-rich regions, resulting in a relatively small overlap between methods. Comparison with the GENCODE annotation points to functional RNAs in all genomic contexts, with a slightly increased density in 3'-UTRs. While we estimate a significant false discovery rate of approximately 50%-70% many of the predictions can be further substantiated by additional criteria: 248 loci are predicted by both RNAz and EvoFold, and an additional 239 RNAz or EvoFold predictions are supported by the (more stringent) AlifoldZ algorithm. Five hundred seventy RNAz structure predictions fall into regions that show signs of selection pressure also on the sequence level (i.e., conserved elements). More than 700 predictions overlap with noncoding transcripts detected by oligonucleotide tiling arrays. One hundred seventy-five selected candidates were tested by RT-PCR in six tissues, and expression could be verified in 43 cases (24.6%).

Published
2007
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14. RNAs everywhere: genome-wide annotation of structured RNAs

Author

Christoph Flamm, Guido Fritzsch, Claudia Fried, Peter F. Stadler, Dominic Rose, Axel Mosig, Rolf Backofen, Stefan Washietl, Stephan H. Bernhart, Jörg Hackermüller, Sonja J. Prohaska, Jana Hertel, Ivo L. Hofacker, Andrea Tanzer, Kristin Missal, Sebastian Will, and Publica

Subjects
Genetics, Genome, mRNA, Central field, RNA, Computational Biology, Computational biology, Biological evolution, Biology, Biological Evolution, Annotation, Molecular Medicine, small RNA, Animal Science and Zoology, Ecology, Evolution, Behavior and Systematics, Developmental Biology
Abstract

Starting with the discovery of microRNAs and the advent of genome-wide transcriptomics, non-protein-coding transcripts have moved from a fringe topic to a central field research in molecular biology. In this contribution we review the state of the art of "computational RNomics", i.e., the bioinformatics approaches to genome-wide RNA annotation. Instead of rehashing results from recently published surveys in detail, we focus here on the open problem in the field, namely (functional) annotation of the plethora of putative RNAs. A series of exploratory studies are used to provide non-trivial examples for the discussion of some of the difficulties.

Published
2006

15. Evolution of MicroRNAs

Author

Andrea Tanzer and Peter F. Stadler

Subjects
Large class, Phylogenetics, microRNA, Consensus sequence, RNA, Computational biology, Biology, Gene, Organism, Sequence (medicine)
Abstract

MicroRNAs (miRNAs) form a large class of small regulatory RNAs in eukaryotes. Although they share a common processing pathway and certain structural features, in general, there is no detectable sequence similarity among miRNAs from a given organism. On the other hand, many miRNAs are members of a family of a few, often very similar, paralogs. It is, thus, of interest to trace the evolutionary history of individual miRNAs, to identify the timing of gene duplications, and to study relationships between the histories of different miRNA families. Some miRNAs are transcribed from polycistronic primary transcripts. In these cases, we will study the evolution of entire clusters.

Published
2006
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16. Evolutionary patterns of non-coding RNAs

Author

Bärbel M. R. Stadler, Axel Mosig, Ivo L. Hofacker, Christina Witwer, Christoph Flamm, Sonja J. Prohaska, Andrea Tanzer, Kristin Missal, Peter F. Stadler, Bettina Müller, Athanasius F. Bompfünewerer, Jörg Lehmann, Guido Fritzsch, Stefan Washietl, and Claudia Fried

Subjects
Statistics and Probability, Genetics, ddc:572.88, Applied Mathematics, Intron, RNA, Computational biology, Biology, Non-coding RNA, Long non-coding RNA, RNA silencing, RNA editing, evolution, non-coding RNA, mRNA, rRNA, snRNA, Small nucleolar RNA, Ecology, Evolution, Behavior and Systematics, Small nuclear RNA
Abstract

A plethora of new functions of non-coding RNAs have been discovered in past few years. In fact, RNA is emerging as the central player in cellular regulation, taking on active roles in multiple regulatory layers from transcription, RNA maturation, and RNA modification to translational regulation. Nevertheless, very little is known about the evolution of this \Modern RNA World' and its components. In this contribution we attempt to provide at least a cursory overview of the diversity of non-coding RNAs and functional RNA motifs in non-translated regions of regular messenger RNAs (mRNAs) with an emphasis on evolutionary questions. This survey is complemented by an in-depth analysis of examples from different classes of RNAs focusing mostly on their evolution in the vertebrate lineage. We present a survey of Y RNA genes in vertebrates, studies of the molecular evolution of the U7 snRNA, the snoRNAs E1/U17, E2, and E3, the Y RNA family, the let-7 microRNA family, and the mRNA-like evf-1 gene. We furthermore discuss the statistical distribution of microRNAs in metazoans, which suggests an explosive increase in the microRNA repertoire in vertebrates. The analysis of the transcription of non-coding RNAs (ncRNAs) suggests that small RNAs in general are genetically mobile in the sense that their association with a hostgene (e.g. when transcribed from introns of a mRNA) can change on evolutionary time scales. The let-7 family demonstrates, that even the mode of transcription (as intron or as exon) can change among paralogous ncRNA.

Published
2005

17. Comparative promoter region analysis powered by CORG

Author

Martin Vingron, Andrea Tanzer, Stefan Röpcke, Peter F. Stadler, Peter F. Arndt, Christoph Dieterich, Steffen Grossmann, and MDC Library

Subjects
Untranslated region, Transcription, Genetic, Genetic Databases, Nucleic Acid Sequence Homology, Mice, Databases, Genetic, Promoter Regions, Genetic, Phylogeny, Zebrafish, Regulation of gene expression, Genetics, Expressed Sequence Tags, Genome, Genetic Transcription, Chromosome Mapping, Exons, Regulatory sequence, DNA microarray, Technology Platforms, Algorithms, Biotechnology, Transcription Start Site, Transcription Factor Binding Site, Internal Ribosome Entry Site, Fugu, Serum Response Factor, lcsh:QH426-470, Genetic Promoter Regions, lcsh:Biotechnology, Molecular Sequence Data, 570 Life Sciences, Computational biology, Biology, Database, 610 Medical Sciences, Medicine, Species Specificity, lcsh:TP248.13-248.65, Sequence Homology, Nucleic Acid, Humans, Animals, Transcription factor, Gene, Internet, Genetic Models, Binding Sites, Models, Genetic, Base Sequence, Computational Biology, Promoter, Rats, DNA binding site, lcsh:Genetics, MicroRNAs, Gene Expression Regulation, RNA, 5' Untranslated Regions, Software, Transcription Factors
Abstract

Background Promoters are key players in gene regulation. They receive signals from various sources (e.g. cell surface receptors) and control the level of transcription initiation, which largely determines gene expression. In vertebrates, transcription start sites and surrounding regulatory elements are often poorly defined. To support promoter analysis, we present CORG http://corg.molgen.mpg.de, a framework for studying upstream regions including untranslated exons (5' UTR). Description The automated annotation of promoter regions integrates information of two kinds. First, statistically significant cross-species conservation within upstream regions of orthologous genes is detected. Pairwise as well as multiple sequence comparisons are computed. Second, binding site descriptions (position-weight matrices) are employed to predict conserved regulatory elements with a novel approach. Assembled EST sequences and verified transcription start sites are incorporated to distinguish exonic from other sequences. As of now, we have included 5 species in our analysis pipeline (man, mouse, rat, fugu and zebrafish). We characterized promoter regions of 16,127 groups of orthologous genes. All data are presented in an intuitive way via our web site. Users are free to export data for single genes or access larger data sets via our DAS server http://tomcat.molgen.mpg.de:8080/das. The benefits of our framework are exemplarily shown in the context of phylogenetic profiling of transcription factor binding sites and detection of microRNAs close to transcription start sites of our gene set. Conclusion The CORG platform is a versatile tool to support analyses of gene regulation in vertebrate promoter regions. Applications for CORG cover a broad range from studying evolution of DNA binding sites and promoter constitution to the discovery of new regulatory sequence elements (e.g. microRNAs and binding sites).

Published
2005

18. Combining RT-PCR-seq and RNA-seq to catalog all genic elements encoded in the human genome

Author

Thibaut Hourlier, Jacqueline Chrast, Roderic Guigó, Cédric Howald, Nathalie Walters, Adam Frankish, José M. González, Stephen M. J. Searle, Jan-Hinnerk Vogel, Jennifer Harrow, Bronwen Aken, Thomas Derrien, Simon D. M. White, Andrea Tanzer, Alexandre Reymond, Felix Kokocinski, and Tim Hubbard

Subjects
Pseudogene, Method, RNA-Seq, Biology, ENCODE, Genoma humà, Genome, Sensitivity and Specificity, Open Reading Frames, Genetics, RNA Isoforms, Humans, natural sciences, RNA, Messenger, Genetics (clinical), GENCODE, Genome, Human, Reverse Transcriptase Polymerase Chain Reaction, Gene Expression Profiling, Intron, Computational Biology, High-Throughput Nucleotide Sequencing, Reproducibility of Results, Molecular Sequence Annotation, Exons, Introns, Gene expression profiling, Human genome, Expressió gènica -- Mètodes, Transcriptome
Abstract

Within the ENCODE Consortium, GENCODE aimed to accurately annotate all protein-coding genes, pseudogenes, and noncoding transcribed loci in the human genome through manual curation and computational methods. Annotated transcript structures were assessed, and less well-supported loci were systematically, experimentally validated. Predicted exon-exon junctions were evaluated by RT-PCR amplification followed by highly multiplexed sequencing readout, a method we called RT-PCR-seq. Seventy-nine percent of all assessed junctions are confirmed by this evaluation procedure, demonstrating the high quality of the GENCODE gene set. RT-PCR-seq was also efficient to screen gene models predicted using the Human Body Map (HBM) RNA-seq data. We validated 73% of these predictions, thus confirming 1168 novel genes, mostly noncoding, which will further complement the GENCODE annotation. Our novel experimental validation pipeline is extremely sensitive, far more than unbiased transcriptome profiling through RNA sequencing, which is becoming the norm. For example, exon-exon junctions unique to GENCODE annotated transcripts are five times more likely to be corroborated with our targeted approach than with extensive large human transcriptome profiling. Data sets such as the HBM and ENCODE RNA-seq data fail sampling of low-expressed transcripts. Our RT-PCR-seq targeted approach also has the advantage of identifying novel exons of known genes, as we discovered unannotated exons in 11% of assessed introns. We thus estimate that at least 18% of known loci have yet-unannotated exons. Our work demonstrates that the cataloging of all of the genic elements encoded in the human genome will necessitate a coordinated effort between unbiased and targeted approaches, like RNA-seq and RT-PCR-seq. This work was funded by National Human Genome Research Institute (NHGRI)/National Institutes of Health (NIH) grants to GENCODE (U54 HG004555) and Cold Spring Harbor Laboratories (U54 HG004557) subgroups of the ENCODE project. We acknowledge grants from the Swiss National Science Foundation to A.R., from the Spanish Ministry of Science (RD07/0067/0012, BIO2006-03380, and CSD2007-00050) to R.G., and from the Wellcome Trust (WT077198/Z/05/Z) to J.H., A.F., J.M.G., F.K., and T.J.H.

19. The GENCODE v7 catalog of human long noncoding RNAs: analysis of their gene structure, evolution, and expression

Author

Cedric Notredame, Timo Lassmann, Carrie A. Davis, Thomas Derrien, Roderic Guigó, Tim Hubbard, Sarah Djebali, Julien Lagarde, Giovanni Bussotti, Gregory Guernec, Jennifer Harrow, José M. González, Yijun Ruan, Ramin Shiekhattar, Xiaoan Ruan, Angelika Merkel, Hagen Tilgner, David C. Martin, Mark G. Thomas, James B. Brown, Leonard Lipovich, Rory Johnson, Lavanya Veeravalli, Thomas R. Gingeras, Piero Carninci, Andrea Tanzer, David G. Knowles, Bioinformatics and Genomics, Centre for Genomic Regulation (CRG), Universitat Pompeu Fabra [Barcelona], Laboratoire de Physiologie et Génomique des Poissons (LPGP), Institut National de la Recherche Agronomique (INRA)-Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ), Institut Fédératif de Recherche - Génétique Fonctionnelle Agronomie et Santé (IFR 140 GFAS), Plateforme bioinformatique GenOuest [Rennes], Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Plateforme Génomique Santé Biogenouest®-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Université de Bretagne Sud (UBS)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-Télécom Bretagne-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-CentraleSupélec-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Rennes (ENS Rennes)-Télécom Bretagne-CentraleSupélec, Agency for Science, Technology and Research, Genome, Genome Institute of Singapore (GIS), Agency for Science, Technology and Research Genome, Riken Omics Science Center, Riken Yokohama Institute, Department of Statistics, University of California, Center for Molecular Medicine and Genetics, Wayne State University, Wellcome Trust Genome Campus, The Wellcome Trust Sanger Institute [Cambridge], Cold Spring Harbor, Cold Spring Harbor Laboratory, The Wistar Institute, Departament de Ciencies Experimentals i de la Salut, Universitat Pompeu Fabra [Barcelona] (UPF), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Plateforme Génomique Santé Biogenouest®-Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-GESTION DES DONNÉES ET DE LA CONNAISSANCE (IRISA-D7), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), CentraleSupélec-Télécom Bretagne-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de Recherche en Informatique et en Automatique (Inria)-École normale supérieure - Rennes (ENS Rennes)-Université de Bretagne Sud (UBS)-Centre National de la Recherche Scientifique (CNRS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-CentraleSupélec-Télécom Bretagne-Université de Rennes 1 (UR1), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-CentraleSupélec-Télécom Bretagne-École normale supérieure - Rennes (ENS Rennes)-Université de Bretagne Sud (UBS)-Centre National de la Recherche Scientifique (CNRS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA), Wayne State University [Detroit], Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique )-Institut National de la Recherche Agronomique (INRA), Université de Rennes (UNIV-RENNES)-CentraleSupélec-Plateforme Génomique Santé Biogenouest®-Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria), Université de Rennes (UR)-Plateforme Génomique Santé Biogenouest®-Inria Rennes – Bretagne Atlantique, Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), and University of California (UC)

Subjects
Primates, Resource, Transcription, Genetic, Computational biology, Biology, Evolution, Molecular, Histones, Open Reading Frames, 03 medical and health sciences, 0302 clinical medicine, Databases, Genetic, Genetics, Animals, Cluster Analysis, Humans, RNA, Messenger, RNA Processing, Post-Transcriptional, Selection, Genetic, Gene, [SDV.BDD]Life Sciences [q-bio]/Development Biology, Genètica -- Bases de dades, Genetics (clinical), 030304 developmental biology, Cell Nucleus, Regulation of gene expression, 0303 health sciences, GENCODE, Gene Expression Profiling, Alternative splicing, Intron, Molecular Sequence Annotation, Exons, RNA no missatgers, Gene expression profiling, Alternative Splicing, Gene Expression Regulation, Organ Specificity, 030220 oncology & carcinogenesis, RNA splicing, RNA, Long Noncoding, Human genome, RNA Splice Sites
Abstract

The human genome contains many thousands of long noncoding RNAs (lncRNAs). While several studies have demonstrated compelling biological and disease roles for individual examples, analytical and experimental approaches to investigate these genes have been hampered by the lack of comprehensive lncRNA annotation. Here, we present and analyze the most complete human lncRNA annotation to date, produced by the GENCODE consortium within the framework of the ENCODE project and comprising 9277 manually annotated genes producing 14,880 transcripts. Our analyses indicate that lncRNAs are generated through pathways similar to that of protein-coding genes, with similar histone-modification profiles, splicing signals, and exon/intron lengths. In contrast to protein-coding genes, however, lncRNAs display a striking bias toward two-exon transcripts, they are predominantly localized in the chromatin and nucleus, and a fraction appear to be preferentially processed into small RNAs. They are under stronger selective pressure than neutrally evolving sequences-particularly in their promoter regions, which display levels of selection comparable to protein-coding genes. Importantly, about one-third seem to have arisen within the primate lineage. Comprehensive analysis of their expression in multiple human organs and brain regions shows that lncRNAs are generally lower expressed than protein-coding genes, and display more tissue-specific expression patterns, with a large fraction of tissue-specific lncRNAs expressed in the brain. Expression correlation analysis indicates that lncRNAs show particularly striking positive correlation with the expression of antisense coding genes. This GENCODE annotation represents a valuable resource for future studies of lncRNAs. This work has been carried out under grants RD07/0067/0012, BIO2006-03380, and CSD2007-00050 from the Spanish Ministry of Science, grant SGR-1430 from the Catalan Government, grants 1U54HG004557-01 and 1U54HG004555-01 from the National Institutes of Health, and INBISCIII from Instituto de Salud Carlos III and FEDER. This research project has been cofinanced by the European Commission, within the 7th Framework Programme, Grant Agreement KBBE-2A-222664 (‘‘Quantomics’’). C.N. is financed by the Plan Nacional BFU2008-00419. G.B. is supported by the La Caixa Ph.D. program

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20. GENCODE: the reference human genome annotation for The ENCODE Project

Author

Electra Tapanari, Veronika Boychenko, Jeena Rajan, Gary Saunders, Mark Gerstein, Michael F. Lin, Michael L. Tress, Mark Diekhans, Suganthi Balasubramanian, Daniel Barrell, If H. A. Barnes, Cédric Howald, Bronwen Aken, Nathalie Walters, Thomas Derrien, M. Kay, Felix Kokocinski, Adam Frankish, Alexandra Bignell, Jacqueline Chrast, Amonida Zadissa, Iakes Ezkurdia, Jose Manuel Rodriguez, Charles A. Steward, Baikang Pei, Andrea Tanzer, Roderic Guigó, Gloria Despacio-Reyes, Jennifer Harrow, Manolis Kellis, Michael R. Brent, Jeltje Van Baren, José M. González, Stephen M. J. Searle, Tim Hubbard, Alexandre Reymond, Alfonso Valencia, Rachel A. Harte, Gaurab Mukherjee, Toby Hunt, David Haussler, Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science, Lin, Michael F., and Kellis, Manolis

Subjects
Models, Molecular, Quality Control, Resource, Genòmica -- Mètodes, DNA, Complementary, Pseudogene, Biology, ENCODE, Genoma humà, Genome, Evolution, Molecular, Open Reading Frames, Untranslated Regions, Databases, Genetic, Genetics, RefSeq, Animals, Humans, Ensembl, Genètica -- Bases de dades, Genetics (clinical), Internet, Genome, Human, GENCODE, Computational Biology, Reproducibility of Results, Molecular Sequence Annotation, Exons, Genomics, Genetic Loci, RNA, Long Noncoding, Human genome, RNA Splice Sites, Pseudogenes
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., National Institutes of Health (U.S.) (Grant 5U54HG004555), Wellcome Trust (London, England) (Grant WT098051)

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