G2Cdb::Gene report

Gene id
G00002119
Gene symbol
BM948371
Species
Homo sapiens
Description
Orthologue
G00000870 (Mus musculus)

Databases (6)

Curated Gene
OTTHUMG00000029030 (Vega human gene)
Gene
ENSG00000183092 (Ensembl human gene)
57596 (Entrez Gene)
472 (G2Cdb plasticity & disease)
Protein Expression
2899 (human protein atlas)
Protein Sequence
Q9BUH8 (UniProt)

Literature (9)

Pubmed - other

  • Toward a confocal subcellular atlas of the human proteome.

    Barbe L, Lundberg E, Oksvold P, Stenius A, Lewin E, Björling E, Asplund A, Pontén F, Brismar H, Uhlén M and Andersson-Svahn H

    Department of Biotechnology, AlbaNova University Center, Royal Institute of Technology, SE-106 91 Stockholm, Sweden.

    Information on protein localization on the subcellular level is important to map and characterize the proteome and to better understand cellular functions of proteins. Here we report on a pilot study of 466 proteins in three human cell lines aimed to allow large scale confocal microscopy analysis using protein-specific antibodies. Approximately 3000 high resolution images were generated, and more than 80% of the analyzed proteins could be classified in one or multiple subcellular compartment(s). The localizations of the proteins showed, in many cases, good agreement with the Gene Ontology localization prediction model. This is the first large scale antibody-based study to localize proteins into subcellular compartments using antibodies and confocal microscopy. The results suggest that this approach might be a valuable tool in conjunction with predictive models for protein localization.

    Molecular & cellular proteomics : MCP 2008;7;3;499-508

  • Global, in vivo, and site-specific phosphorylation dynamics in signaling networks.

    Olsen JV, Blagoev B, Gnad F, Macek B, Kumar C, Mortensen P and Mann M

    Center for Experimental BioInformatics, Department of Biochemistry and Molecular Biology, University of Southern Denmark, DK-5230 Odense, Denmark.

    Cell signaling mechanisms often transmit information via posttranslational protein modifications, most importantly reversible protein phosphorylation. Here we develop and apply a general mass spectrometric technology for identification and quantitation of phosphorylation sites as a function of stimulus, time, and subcellular location. We have detected 6,600 phosphorylation sites on 2,244 proteins and have determined their temporal dynamics after stimulating HeLa cells with epidermal growth factor (EGF) and recorded them in the Phosida database. Fourteen percent of phosphorylation sites are modulated at least 2-fold by EGF, and these were classified by their temporal profiles. Surprisingly, a majority of proteins contain multiple phosphorylation sites showing different kinetics, suggesting that they serve as platforms for integrating signals. In addition to protein kinase cascades, the targets of reversible phosphorylation include ubiquitin ligases, guanine nucleotide exchange factors, and at least 46 different transcriptional regulators. The dynamic phosphoproteome provides a missing link in a global, integrative view of cellular regulation.

    Cell 2006;127;3;635-48

  • A probability-based approach for high-throughput protein phosphorylation analysis and site localization.

    Beausoleil SA, Villén J, Gerber SA, Rush J and Gygi SP

    Department of Cell Biology, Harvard Medical School, 240 Longwood Ave., Boston, Massachusetts 02115, USA.

    Data analysis and interpretation remain major logistical challenges when attempting to identify large numbers of protein phosphorylation sites by nanoscale reverse-phase liquid chromatography/tandem mass spectrometry (LC-MS/MS) (Supplementary Figure 1 online). In this report we address challenges that are often only addressable by laborious manual validation, including data set error, data set sensitivity and phosphorylation site localization. We provide a large-scale phosphorylation data set with a measured error rate as determined by the target-decoy approach, we demonstrate an approach to maximize data set sensitivity by efficiently distracting incorrect peptide spectral matches (PSMs), and we present a probability-based score, the Ascore, that measures the probability of correct phosphorylation site localization based on the presence and intensity of site-determining ions in MS/MS spectra. We applied our methods in a fully automated fashion to nocodazole-arrested HeLa cell lysate where we identified 1,761 nonredundant phosphorylation sites from 491 proteins with a peptide false-positive rate of 1.3%.

    Funded by: NHGRI NIH HHS: HG03456; NIGMS NIH HHS: GM67945

    Nature biotechnology 2006;24;10;1285-92

  • A protein-protein interaction network for human inherited ataxias and disorders of Purkinje cell degeneration.

    Lim J, Hao T, Shaw C, Patel AJ, Szabó G, Rual JF, Fisk CJ, Li N, Smolyar A, Hill DE, Barabási AL, Vidal M and Zoghbi HY

    Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA.

    Many human inherited neurodegenerative disorders are characterized by loss of balance due to cerebellar Purkinje cell (PC) degeneration. Although the disease-causing mutations have been identified for a number of these disorders, the normal functions of the proteins involved remain, in many cases, unknown. To gain insight into the function of proteins involved in PC degeneration, we developed an interaction network for 54 proteins involved in 23 inherited ataxias and expanded the network by incorporating literature-curated and evolutionarily conserved interactions. We identified 770 mostly novel protein-protein interactions using a stringent yeast two-hybrid screen; of 75 pairs tested, 83% of the interactions were verified in mammalian cells. Many ataxia-causing proteins share interacting partners, a subset of which have been found to modify neurodegeneration in animal models. This interactome thus provides a tool for understanding pathogenic mechanisms common for this class of neurodegenerative disorders and for identifying candidate genes for inherited ataxias.

    Funded by: NICHD NIH HHS: HD24064; NINDS NIH HHS: NS27699

    Cell 2006;125;4;801-14

  • Towards a proteome-scale map of the human protein-protein interaction network.

    Rual JF, Venkatesan K, Hao T, Hirozane-Kishikawa T, Dricot A, Li N, Berriz GF, Gibbons FD, Dreze M, Ayivi-Guedehoussou N, Klitgord N, Simon C, Boxem M, Milstein S, Rosenberg J, Goldberg DS, Zhang LV, Wong SL, Franklin G, Li S, Albala JS, Lim J, Fraughton C, Llamosas E, Cevik S, Bex C, Lamesch P, Sikorski RS, Vandenhaute J, Zoghbi HY, Smolyar A, Bosak S, Sequerra R, Doucette-Stamm L, Cusick ME, Hill DE, Roth FP and Vidal M

    Center for Cancer Systems Biology and Department of Cancer Biology, Dana-Farber Cancer Institute, Harvard Medical School, 44 Binney Street, Boston, Massachusetts 02115, USA.

    Systematic mapping of protein-protein interactions, or 'interactome' mapping, was initiated in model organisms, starting with defined biological processes and then expanding to the scale of the proteome. Although far from complete, such maps have revealed global topological and dynamic features of interactome networks that relate to known biological properties, suggesting that a human interactome map will provide insight into development and disease mechanisms at a systems level. Here we describe an initial version of a proteome-scale map of human binary protein-protein interactions. Using a stringent, high-throughput yeast two-hybrid system, we tested pairwise interactions among the products of approximately 8,100 currently available Gateway-cloned open reading frames and detected approximately 2,800 interactions. This data set, called CCSB-HI1, has a verification rate of approximately 78% as revealed by an independent co-affinity purification assay, and correlates significantly with other biological attributes. The CCSB-HI1 data set increases by approximately 70% the set of available binary interactions within the tested space and reveals more than 300 new connections to over 100 disease-associated proteins. This work represents an important step towards a systematic and comprehensive human interactome project.

    Funded by: NCI NIH HHS: R33 CA132073; NHGRI NIH HHS: P50 HG004233, R01 HG001715, RC4 HG006066, U01 HG001715; NHLBI NIH HHS: U01 HL098166

    Nature 2005;437;7062;1173-8

  • The status, quality, and expansion of the NIH full-length cDNA project: the Mammalian Gene Collection (MGC).

    Gerhard DS, Wagner L, Feingold EA, Shenmen CM, Grouse LH, Schuler G, Klein SL, Old S, Rasooly R, Good P, Guyer M, Peck AM, Derge JG, Lipman D, Collins FS, Jang W, Sherry S, Feolo M, Misquitta L, Lee E, Rotmistrovsky K, Greenhut SF, Schaefer CF, Buetow K, Bonner TI, Haussler D, Kent J, Kiekhaus M, Furey T, Brent M, Prange C, Schreiber K, Shapiro N, Bhat NK, Hopkins RF, Hsie F, Driscoll T, Soares MB, Casavant TL, Scheetz TE, Brown-stein MJ, Usdin TB, Toshiyuki S, Carninci P, Piao Y, Dudekula DB, Ko MS, Kawakami K, Suzuki Y, Sugano S, Gruber CE, Smith MR, Simmons B, Moore T, Waterman R, Johnson SL, Ruan Y, Wei CL, Mathavan S, Gunaratne PH, Wu J, Garcia AM, Hulyk SW, Fuh E, Yuan Y, Sneed A, Kowis C, Hodgson A, Muzny DM, McPherson J, Gibbs RA, Fahey J, Helton E, Ketteman M, Madan A, Rodrigues S, Sanchez A, Whiting M, Madari A, Young AC, Wetherby KD, Granite SJ, Kwong PN, Brinkley CP, Pearson RL, Bouffard GG, Blakesly RW, Green ED, Dickson MC, Rodriguez AC, Grimwood J, Schmutz J, Myers RM, Butterfield YS, Griffith M, Griffith OL, Krzywinski MI, Liao N, Morin R, Morrin R, Palmquist D, Petrescu AS, Skalska U, Smailus DE, Stott JM, Schnerch A, Schein JE, Jones SJ, Holt RA, Baross A, Marra MA, Clifton S, Makowski KA, Bosak S, Malek J and MGC Project Team

    The National Institutes of Health's Mammalian Gene Collection (MGC) project was designed to generate and sequence a publicly accessible cDNA resource containing a complete open reading frame (ORF) for every human and mouse gene. The project initially used a random strategy to select clones from a large number of cDNA libraries from diverse tissues. Candidate clones were chosen based on 5'-EST sequences, and then fully sequenced to high accuracy and analyzed by algorithms developed for this project. Currently, more than 11,000 human and 10,000 mouse genes are represented in MGC by at least one clone with a full ORF. The random selection approach is now reaching a saturation point, and a transition to protocols targeted at the missing transcripts is now required to complete the mouse and human collections. Comparison of the sequence of the MGC clones to reference genome sequences reveals that most cDNA clones are of very high sequence quality, although it is likely that some cDNAs may carry missense variants as a consequence of experimental artifact, such as PCR, cloning, or reverse transcriptase errors. Recently, a rat cDNA component was added to the project, and ongoing frog (Xenopus) and zebrafish (Danio) cDNA projects were expanded to take advantage of the high-throughput MGC pipeline.

    Funded by: PHS HHS: N01-C0-12400

    Genome research 2004;14;10B;2121-7

  • Synaptic and nuclear localization of brain-enriched guanylate kinase-associated protein.

    Yao I, Iida J, Nishimura W and Hata Y

    Department of Medical Biochemistry, Graduate School of Medicine, Tokyo Medical and Dental University, Bunkyo-ku, Tokyo 113-8519, Japan.

    Brain-enriched guanylate kinase-associated protein (BEGAIN) interacts with postsynaptic density (PSD)-95/synapse-associated protein (SAP) 90. In immunohistochemistry and immunocytochemistry, BEGAIN was detected in nuclei and at synapses in neurons. Nuclear localization was also confirmed through subcellular fractionation. BEGAIN was localized exclusively in nuclei when expressed in epithelial cells. These findings led us to analyze the mechanism to determine the subcellular localization of BEGAIN in neurons. Green fluorescent protein (GFP)-tagged BEGAIN appeared first in nuclei and subsequently accumulated at dendrites. Approximately 75 and 90% of GFP-BEGAIN clusters were colocalized with synaptophysin and PSD-95/SAP90, respectively. GFP-protein containing only the N-terminal region also formed foci in nuclei and clusters at dendrites. The N-terminal BEGAIN was not precisely targeted to synapses, although it was partially localized at synapses, possibly through dimer formation with endogenous BEGAIN. The truncated form of PSD-95/SAP90 containing the guanylate kinase domain blocked synaptic targeting of BEGAIN but did not affect cluster formation at dendrites. NMDA receptor antagonists blocked localization of GFP-BEGAIN at synapses but did not affect recruitment to dendrites. These results suggest that BEGAIN is recruited to dendrites by the N-terminal region independently of NMDA receptor activity and that synaptic targeting of BEGAIN depends on NMDA receptor activity and may be mediated by interaction with PSD-95/SAP90.

    The Journal of neuroscience : the official journal of the Society for Neuroscience 2002;22;13;5354-64

  • Prediction of the coding sequences of unidentified human genes. XVII. The complete sequences of 100 new cDNA clones from brain which code for large proteins in vitro.

    Nagase T, Kikuno R, Ishikawa K, Hirosawa M and Ohara O

    Kazusa DNA Research Institute, Kisarazu, Chiba, Japan. nagase@kazusa.or.jp

    To provide information regarding the coding sequences of unidentified human genes, we have conducted a sequencing project of human cDNAs which encode large proteins. We herein present the entire sequences of 100 cDNA clones of unknown human genes, named KIAA1444 to KIAA1543, from two sets of size-fractionated human adult and fetal brain cDNA libraries. The average sizes of the inserts and corresponding open reading frames of cDNA clones analyzed here were 4.4 kb and 2.6 kb (856 amino acid residues), respectively. Database searches of the predicted amino acid sequences classified 53 predicted gene products into the following five functional categories: cell signaling/communication, nucleic acid management, cell structure/motility, protein management and metabolism. It was also revealed that homologues for 32 KIAA gene products were detected in the databases, which were similar in sequence through almost their entire regions. Additionally, the chromosomal loci of the genes were determined by using human-rodent hybrid panels unless their chromosomal loci were already assigned in the public databases. The expression levels of the genes were monitored in spinal cord, fetal brain and fetal liver, as well as in 10 human tissues and 8 brain regions, by reverse transcription-coupled polymerase chain reaction, products of which were quantified by enzyme-linked immunosorbent assay.

    DNA research : an international journal for rapid publication of reports on genes and genomes 2000;7;2;143-50

  • BEGAIN (brain-enriched guanylate kinase-associated protein), a novel neuronal PSD-95/SAP90-binding protein.

    Deguchi M, Hata Y, Takeuchi M, Ide N, Hirao K, Yao I, Irie M, Toyoda A and Takai Y

    Takai Biotimer Project, ERATO, Japan Science and Technology Corporation, c/o JCR Pharmaceuticals Co. Ltd., 2-2-10 Murotani, Nishi-ku, Kobe 651-2241, Japan.

    PSD-95/SAP90 is a synaptic membrane-associated guanylate kinase with three PDZ, one SH3, and one guanylate kinase (GK) domain. PSD-95/SAP90 binds various proteins through the PDZ domains and organizes synaptic junctions. PSD-95/SAP90 also interacts with the postsynaptic density (PSD) fraction-enriched protein, named SAPAP (also called GKAP and DAP), through the GK domain. SAPAP is Triton X-100-insoluble and recruits PSD-95/SAP90 into the Triton X-100-insoluble fraction in the transfected cells, suggesting that SAPAP may fix PSD-95/SAP90 to the PSD. Here we report a novel protein interacting with the GK domain of PSD-95/SAP90, BEGAIN. BEGAIN is specifically expressed in brain and enriched in the PSD fraction. BEGAIN is Triton X-100-soluble in the transfected cells but is recruited to the Triton X-100-insoluble fraction by SAPAP when coexpressed with PSD-95/SAP90. BEGAIN may be a novel PSD component associated with the core complex of PSD-95/SAP90 and SAPAP.

    The Journal of biological chemistry 1998;273;41;26269-72

Gene lists (6)

Gene List Source Species Name Description Gene count
L00000009 G2C Homo sapiens Human PSD Human orthologues of mouse PSD adapted from Collins et al (2006) 1080
L00000016 G2C Homo sapiens Human PSP Human orthologues of mouse PSP adapted from Collins et al (2006) 1121
L00000049 G2C Homo sapiens TAP-PSD-95-CORE TAP-PSD-95 pull-down core list (ortho) 120
L00000061 G2C Homo sapiens BAYES-COLLINS-MOUSE-PSD-CONSENSUS Mouse cortex PSD consensus (ortho) 984
L00000069 G2C Homo sapiens BAYES-COLLINS-HUMAN-PSD-FULL Human cortex biopsy PSD full list 1461
L00000071 G2C Homo sapiens BAYES-COLLINS-MOUSE-PSD-FULL Mouse cortex PSD full list (ortho) 1556
© G2C 2014. The Genes to Cognition Programme received funding from The Wellcome Trust and the EU FP7 Framework Programmes:
EUROSPIN (FP7-HEALTH-241498), SynSys (FP7-HEALTH-242167) and GENCODYS (FP7-HEALTH-241995).

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