ALBERT

Description: Advances in high-throughput mass spectrometry are making proteomics an increasingly important tool in genome annotation projects. Peptides detected in mass spectrometry experiments can be used to validate gene models and verify the translation of putative coding sequences (CDSs). Here, we have identified peptides that cover 35% of the genes annotated by the GENCODE consortium for the human genome as part of a comprehensive analysis of experimental spectra from two large publicly available mass spectrometry databases. We detected the translation to protein of "novel" and "putative" protein-coding transcripts as well as transcripts annotated as pseudogenes and nonsense-mediated decay targets. We provide a detailed overview of the population of alternatively spliced protein isoforms that are detectable by peptide identification methods. We found that 150 genes expressed multiple alternative protein isoforms. This constitutes the largest set of reliably confirmed alternatively spliced proteins yet discovered. Three groups of genes were highly overrepresented. We detected alternative isoforms for 10 of the 25 possible heterogeneous nuclear ribonucleoproteins, proteins with a key role in the splicing process. Alternative isoforms generated from interchangeable homologous exons and from short indels were also significantly enriched, both in human experiments and in parallel analyses of mouse and Drosophila proteomics experiments. Our results show that a surprisingly high proportion (almost 25%) of the detected alternative isoforms are only subtly different from their constitutive counterparts. Many of the alternative splicing events that give rise to these alternative isoforms are conserved in mouse. It was striking that very few of these conserved splicing events broke Pfam functional domains or would damage globular protein structures. This evidence of a strong bias toward subtle differences in CDS and likely conserved cellular function and structure is remarkable and strongly suggests that the translation of alternative transcripts may be subject to selective constraints.

Description: The Vertebrate Genome Annotation (VEGA) database ( http://vega.sanger.ac.uk ), initially designed as a community resource for browsing manual annotation of the human genome project, now contains five reference genomes (human, mouse, zebrafish, pig and rat). Its introduction pages have been redesigned to enable the user to easily navigate between whole genomes and smaller multi-species haplotypic regions of interest such as the major histocompatibility complex. The VEGA browser is unique in that annotation is updated via the Human And Vertebrate Analysis aNd Annotation (HAVANA) update track every 2 weeks, allowing single gene updates to be made publicly available to the research community quickly. The user can now access different haplotypic subregions more easily, such as those from the non-obese diabetic mouse, and display them in a more intuitive way using the comparative tools. We also highlight how the user can browse manually annotated updated patches from the Genome Reference Consortium (GRC).

Description: Genome-sequencing studies indicate that all humans carry many genetic variants predicted to cause loss of function (LoF) of protein-coding genes, suggesting unexpected redundancy in the human genome. Here we apply stringent filters to 2951 putative LoF variants obtained from 185 human genomes to determine their true prevalence and properties. We estimate that human genomes typically contain ~100 genuine LoF variants with ~20 genes completely inactivated. We identify rare and likely deleterious LoF alleles, including 26 known and 21 predicted severe disease-causing variants, as well as common LoF variants in nonessential genes. We describe functional and evolutionary differences between LoF-tolerant and recessive disease genes and a method for using these differences to prioritize candidate genes found in clinical sequencing studies.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3299548/" target="_blank"〉〈img src="https://static.pubmed.gov/portal/portal3rc.fcgi/4089621/img/3977009" border="0"〉〈/a〉   〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3299548/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉MacArthur, Daniel G -- Balasubramanian, Suganthi -- Frankish, Adam -- Huang, Ni -- Morris, James -- Walter, Klaudia -- Jostins, Luke -- Habegger, Lukas -- Pickrell, Joseph K -- Montgomery, Stephen B -- Albers, Cornelis A -- Zhang, Zhengdong D -- Conrad, Donald F -- Lunter, Gerton -- Zheng, Hancheng -- Ayub, Qasim -- DePristo, Mark A -- Banks, Eric -- Hu, Min -- Handsaker, Robert E -- Rosenfeld, Jeffrey A -- Fromer, Menachem -- Jin, Mike -- Mu, Xinmeng Jasmine -- Khurana, Ekta -- Ye, Kai -- Kay, Mike -- Saunders, Gary Ian -- Suner, Marie-Marthe -- Hunt, Toby -- Barnes, If H A -- Amid, Clara -- Carvalho-Silva, Denise R -- Bignell, Alexandra H -- Snow, Catherine -- Yngvadottir, Bryndis -- Bumpstead, Suzannah -- Cooper, David N -- Xue, Yali -- Romero, Irene Gallego -- 1000 Genomes Project Consortium -- Wang, Jun -- Li, Yingrui -- Gibbs, Richard A -- McCarroll, Steven A -- Dermitzakis, Emmanouil T -- Pritchard, Jonathan K -- Barrett, Jeffrey C -- Harrow, Jennifer -- Hurles, Matthew E -- Gerstein, Mark B -- Tyler-Smith, Chris -- 085532/Wellcome Trust/United Kingdom -- 090532/Wellcome Trust/United Kingdom -- 090532/Z/09/Z/Wellcome Trust/United Kingdom -- 098051/Wellcome Trust/United Kingdom -- BB/I02593X/1/Biotechnology and Biological Sciences Research Council/United Kingdom -- RG/09/012/28096/British Heart Foundation/United Kingdom -- U54 HG003273/HG/NHGRI NIH HHS/ -- New York, N.Y. -- Science. 2012 Feb 17;335(6070):823-8. doi: 10.1126/science.1215040.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Wellcome Trust Sanger Institute, Hinxton, UK. macarthur@atgu.mgh.harvard.edu〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/22344438" target="_blank"〉PubMed〈/a〉

Description: 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 features. 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.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4155737/" target="_blank"〉〈img src="https://static.pubmed.gov/portal/portal3rc.fcgi/4089621/img/3977009" border="0"〉〈/a〉   〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4155737/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Gerstein, Mark B -- Rozowsky, Joel -- Yan, Koon-Kiu -- Wang, Daifeng -- Cheng, Chao -- Brown, James B -- Davis, Carrie A -- Hillier, LaDeana -- Sisu, Cristina -- Li, Jingyi Jessica -- Pei, Baikang -- Harmanci, Arif O -- Duff, Michael O -- Djebali, Sarah -- Alexander, Roger P -- Alver, Burak H -- Auerbach, Raymond -- Bell, Kimberly -- Bickel, Peter J -- Boeck, Max E -- Boley, Nathan P -- Booth, Benjamin W -- Cherbas, Lucy -- Cherbas, Peter -- Di, Chao -- Dobin, Alex -- Drenkow, Jorg -- Ewing, Brent -- Fang, Gang -- Fastuca, Megan -- Feingold, Elise A -- Frankish, Adam -- Gao, Guanjun -- Good, Peter J -- Guigo, Roderic -- Hammonds, Ann -- Harrow, Jen -- Hoskins, Roger A -- Howald, Cedric -- Hu, Long -- Huang, Haiyan -- Hubbard, Tim J P -- Huynh, Chau -- Jha, Sonali -- Kasper, Dionna -- Kato, Masaomi -- Kaufman, Thomas C -- Kitchen, Robert R -- Ladewig, Erik -- Lagarde, Julien -- Lai, Eric -- Leng, Jing -- Lu, Zhi -- MacCoss, Michael -- May, Gemma -- McWhirter, Rebecca -- Merrihew, Gennifer -- Miller, David M -- Mortazavi, Ali -- Murad, Rabi -- Oliver, Brian -- Olson, Sara -- Park, Peter J -- Pazin, Michael J -- Perrimon, Norbert -- Pervouchine, Dmitri -- Reinke, Valerie -- Reymond, Alexandre -- Robinson, Garrett -- Samsonova, Anastasia -- Saunders, Gary I -- Schlesinger, Felix -- Sethi, Anurag -- Slack, Frank J -- Spencer, William C -- Stoiber, Marcus H -- Strasbourger, Pnina -- Tanzer, Andrea -- Thompson, Owen A -- Wan, Kenneth H -- Wang, Guilin -- Wang, Huaien -- Watkins, Kathie L -- Wen, Jiayu -- Wen, Kejia -- Xue, Chenghai -- Yang, Li -- Yip, Kevin -- Zaleski, Chris -- Zhang, Yan -- Zheng, Henry -- Brenner, Steven E -- Graveley, Brenton R -- Celniker, Susan E -- Gingeras, Thomas R -- Waterston, Robert -- 1U01HG007031-01/HG/NHGRI NIH HHS/ -- 5U01HG004695-04/HG/NHGRI NIH HHS/ -- 5U54HG004555/HG/NHGRI NIH HHS/ -- HG007000/HG/NHGRI NIH HHS/ -- HG007355/HG/NHGRI NIH HHS/ -- K99 HG006698/HG/NHGRI NIH HHS/ -- P30 CA045508/CA/NCI NIH HHS/ -- R01 GM076655/GM/NIGMS NIH HHS/ -- RC2-HG005639/HG/NHGRI NIH HHS/ -- T15 LM007056/LM/NLM NIH HHS/ -- T32 HD060555/HD/NICHD NIH HHS/ -- U01 HG 004263/HG/NHGRI NIH HHS/ -- U01 HG004261/HG/NHGRI NIH HHS/ -- U01 HG004271/HG/NHGRI NIH HHS/ -- U01 HG007031/HG/NHGRI NIH HHS/ -- U01-HG004261/HG/NHGRI NIH HHS/ -- U01HG004258/HG/NHGRI NIH HHS/ -- U41 HG007000/HG/NHGRI NIH HHS/ -- U41 HG007234/HG/NHGRI NIH HHS/ -- U41 HG007355/HG/NHGRI NIH HHS/ -- U54 HG004555/HG/NHGRI NIH HHS/ -- U54 HG006944/HG/NHGRI NIH HHS/ -- U54 HG006994/HG/NHGRI NIH HHS/ -- U54 HG007004/HG/NHGRI NIH HHS/ -- U54 HG007005/HG/NHGRI NIH HHS/ -- U54HG007005/HG/NHGRI NIH HHS/ -- WT098051/Wellcome Trust/United Kingdom -- ZIA DK015600-18/Intramural NIH HHS/ -- Howard Hughes Medical Institute/ -- England -- Nature. 2014 Aug 28;512(7515):445-8. doi: 10.1038/nature13424.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉1] Program in Computational Biology and Bioinformatics, Yale University, Bass 432, 266 Whitney Avenue, New Haven, Connecticut 06520, USA [2] Department of Molecular Biophysics and Biochemistry, Yale University, Bass 432, 266 Whitney Avenue, New Haven, Connecticut 06520, USA [3] Department of Computer Science, Yale University, 51 Prospect Street, New Haven, Connecticut 06511, USA [4] [5]. ; 1] Program in Computational Biology and Bioinformatics, Yale University, Bass 432, 266 Whitney Avenue, New Haven, Connecticut 06520, USA [2] Department of Molecular Biophysics and Biochemistry, Yale University, Bass 432, 266 Whitney Avenue, New Haven, Connecticut 06520, USA [3]. ; 1] Department of Genetics, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire 03755, USA [2] Institute for Quantitative Biomedical Sciences, Norris Cotton Cancer Center, Geisel School of Medicine at Dartmouth, Lebanon, New Hampshire 03766, USA [3]. ; 1] Department of Genome Dynamics, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA [2] Department of Statistics, University of California, Berkeley, 367 Evans Hall, Berkeley, California 94720-3860, USA [3]. ; 1] Functional Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724, USA [2]. ; 1] Department of Genome Sciences and University of Washington School of Medicine, William H. Foege Building S350D, 1705 Northeast Pacific Street, Box 355065 Seattle, Washington 98195-5065, USA [2]. ; 1] Department of Statistics, University of California, Berkeley, 367 Evans Hall, Berkeley, California 94720-3860, USA [2] Department of Statistics, University of California, Los Angeles, California 90095-1554, USA [3] Department of Human Genetics, University of California, Los Angeles, California 90095-7088, USA [4]. ; 1] Department of Genetics and Developmental Biology, Institute for Systems Genomics, University of Connecticut Health Center, 400 Farmington Avenue, Farmington, Connecticut 06030, USA [2]. ; 1] Centre for Genomic Regulation, Doctor Aiguader 88, 08003 Barcelona, Catalonia, Spain [2] Departament de Ciencies Experimentals i de la Salut, Universitat Pompeu Fabra, 08003 Barcelona, Catalonia, Spain [3]. ; 1] Program in Computational Biology and Bioinformatics, Yale University, Bass 432, 266 Whitney Avenue, New Haven, Connecticut 06520, USA [2] Department of Molecular Biophysics and Biochemistry, Yale University, Bass 432, 266 Whitney Avenue, New Haven, Connecticut 06520, USA. ; Center for Biomedical Informatics, Harvard Medical School, 10 Shattuck Street, Boston, Massachusetts 02115, USA. ; Functional Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724, USA. ; Department of Statistics, University of California, Berkeley, 367 Evans Hall, Berkeley, California 94720-3860, USA. ; Department of Genome Sciences and University of Washington School of Medicine, William H. Foege Building S350D, 1705 Northeast Pacific Street, Box 355065 Seattle, Washington 98195-5065, USA. ; 1] Department of Genome Dynamics, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA [2] Department of Biostatistics, University of California, Berkeley, 367 Evans Hall, Berkeley, California 94720-3860, USA. ; Department of Genome Dynamics, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA. ; 1] Department of Biology, Indiana University, 1001 East 3rd Street, Bloomington, Indiana 47405-7005, USA [2] Center for Genomics and Bioinformatics, Indiana University, 1001 East 3rd Street, Bloomington, Indiana 47405-7005, USA. ; MOE Key Lab of Bioinformatics, School of Life Sciences, Tsinghua University, Beijing 100084, China. ; National Human Genome Research Institute, National Institutes of Health, 5635 Fishers Lane, Bethesda, Maryland 20892-9307, USA. ; Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK. ; 1] Centre for Genomic Regulation, Doctor Aiguader 88, 08003 Barcelona, Catalonia, Spain [2] Departament de Ciencies Experimentals i de la Salut, Universitat Pompeu Fabra, 08003 Barcelona, Catalonia, Spain. ; 1] Center for Integrative Genomics, University of Lausanne, Genopode building, Lausanne 1015, Switzerland [2] Swiss Institute of Bioinformatics, Genopode building, Lausanne 1015, Switzerland. ; 1] Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK [2] Medical and Molecular Genetics, King's College London, London WC2R 2LS, UK. ; Department of Genetics, Yale University School of Medicine, New Haven, Connecticut 06520-8005, USA. ; Department of Molecular, Cellular and Developmental Biology, PO Box 208103, Yale University, New Haven, Connecticut 06520, USA. ; Department of Biology, Indiana University, 1001 East 3rd Street, Bloomington, Indiana 47405-7005, USA. ; Sloan-Kettering Institute, 1275 York Avenue, Box 252, New York, New York 10065, USA. ; 1] Department of Genetics and Developmental Biology, Institute for Systems Genomics, University of Connecticut Health Center, 400 Farmington Avenue, Farmington, Connecticut 06030, USA [2] Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213 USA. ; Department of Cell and Developmental Biology, Vanderbilt University, 465 21st Avenue South, Nashville, Tennessee 37232-8240, USA. ; 1] Developmental and Cell Biology, University of California, Irvine, California 92697, USA [2] Center for Complex Biological Systems, University of California, Irvine, California 92697, USA. ; Section of Developmental Genomics, Laboratory of Cellular and Developmental Biology, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland 20892, USA. ; Department of Genetics and Developmental Biology, Institute for Systems Genomics, University of Connecticut Health Center, 400 Farmington Avenue, Farmington, Connecticut 06030, USA. ; 1] Department of Genetics and Drosophila RNAi Screening Center, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, Massachusetts 02115, USA [2] Howard Hughes Medical Institute, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, Massachusetts 02115, USA. ; Center for Integrative Genomics, University of Lausanne, Genopode building, Lausanne 1015, Switzerland. ; 1] Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK [2] European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK. ; 1] Bioinformatics and Genomics Programme, Center for Genomic Regulation, Universitat Pompeu Fabra (CRG-UPF), 08003 Barcelona, Catalonia, Spain [2] Institute for Theoretical Chemistry, Theoretical Biochemistry Group (TBI), University of Vienna, Wahringerstrasse 17/3/303, A-1090 Vienna, Austria. ; 1] Department of Genetics and Developmental Biology, Institute for Systems Genomics, University of Connecticut Health Center, 400 Farmington Avenue, Farmington, Connecticut 06030, USA [2] Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China. ; 1] Hong Kong Bioinformatics Centre, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong [2] 5 CUHK-BGI Innovation Institute of Trans-omics, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong. ; 1] Department of Molecular and Cell Biology, University of California, Berkeley, California 94720, USA [2] Department of Plant and Microbial Biology, University of California, Berkeley, California 94720, USA [3]. ; 1] Department of Genome Dynamics, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA [2].〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/25164755" target="_blank"〉PubMed〈/a〉

Description: Pseudogenes are degraded fossil copies of genes. Here, we report a comparison of pseudogenes spanning three phyla, leveraging the completed annotations of the human, worm, and fly genomes, which we make available as an online resource. We find that pseudogenes are lineage specific, much more so than protein-coding genes, reflecting...

Description: Determining the full complement of protein-coding genes is a key goal of genome annotation. The most powerful approach for confirming protein-coding potential is the detection of cellular protein expression through peptide mass spectrometry (MS) experiments. Here, we mapped peptides detected in seven large-scale proteomics studies to almost 60% of the protein-coding genes in the GENCODE annotation of the human genome. We found a strong relationship between detection in proteomics experiments and both gene family age and cross-species conservation. Most of the genes for which we detected peptides were highly conserved. We found peptides for 〉96% of genes that evolved before bilateria. At the opposite end of the scale, we identified almost no peptides for genes that have appeared since primates, for genes that did not have any protein-like features or for genes with poor cross-species conservation. These results motivated us to describe a set of 2001 potential non-coding genes based on features such as weak conservation, a lack of protein features, or ambiguous annotations from major databases, all of which correlated with low peptide detection across the seven experiments. We identified peptides for just 3% of these genes. We show that many of these genes behave more like non-coding genes than protein-coding genes and suggest that most are unlikely to code for proteins under normal circumstances. We believe that their inclusion in the human protein-coding gene catalogue should be revised as part of the ongoing human genome annotation effort.

Description: The Consensus Coding Sequence (CCDS) project ( http://www.ncbi.nlm.nih.gov/CCDS/ ) is a collaborative effort to maintain a dataset of protein-coding regions that are identically annotated on the human and mouse reference genome assemblies by the National Center for Biotechnology Information (NCBI) and Ensembl genome annotation pipelines. Identical annotations that pass quality assurance tests are tracked with a stable identifier (CCDS ID). Members of the collaboration, who are from NCBI, the Wellcome Trust Sanger Institute and the University of California Santa Cruz, provide coordinated and continuous review of the dataset to ensure high-quality CCDS representations. We describe here the current status and recent growth in the CCDS dataset, as well as recent changes to the CCDS web and FTP sites. These changes include more explicit reporting about the NCBI and Ensembl annotation releases being compared, new search and display options, the addition of biologically descriptive information and our approach to representing genes for which support evidence is incomplete. We also present a summary of recent and future curation targets.