G2Cdb::Gene report

Gene id
G00002434
Gene symbol
DYNLL2 (HGNC)
Species
Homo sapiens
Description
dynein, light chain, LC8-type 2
Orthologue
G00001185 (Mus musculus)

Databases (7)

Gene
ENSG00000121083 (Ensembl human gene)
140735 (Entrez Gene)
1177 (G2Cdb plasticity & disease)
DYNLL2 (GeneCards)
Literature
608942 (OMIM)
Marker Symbol
HGNC:24596 (HGNC)
Protein Sequence
Q96FJ2 (UniProt)

Synonyms (4)

  • DNCL1B
  • Dlc2
  • MGC17810
  • RSPH22

Literature (14)

Pubmed - other

  • Defining the human deubiquitinating enzyme interaction landscape.

    Sowa ME, Bennett EJ, Gygi SP and Harper JW

    Department of Pathology, Harvard Medical School, Boston, MA 02115, USA.

    Deubiquitinating enzymes (Dubs) function to remove covalently attached ubiquitin from proteins, thereby controlling substrate activity and/or abundance. For most Dubs, their functions, targets, and regulation are poorly understood. To systematically investigate Dub function, we initiated a global proteomic analysis of Dubs and their associated protein complexes. This was accomplished through the development of a software platform called CompPASS, which uses unbiased metrics to assign confidence measurements to interactions from parallel nonreciprocal proteomic data sets. We identified 774 candidate interacting proteins associated with 75 Dubs. Using Gene Ontology, interactome topology classification, subcellular localization, and functional studies, we link Dubs to diverse processes, including protein turnover, transcription, RNA processing, DNA damage, and endoplasmic reticulum-associated degradation. This work provides the first glimpse into the Dub interaction landscape, places previously unstudied Dubs within putative biological pathways, and identifies previously unknown interactions and protein complexes involved in this increasingly important arm of the ubiquitin-proteasome pathway.

    Funded by: NIA NIH HHS: AG085011, R01 AG011085, R01 AG011085-16; NIGMS NIH HHS: GM054137, GM67945, R01 GM054137, R01 GM054137-14, R01 GM067945

    Cell 2009;138;2;389-403

  • Large-scale mapping of human protein-protein interactions by mass spectrometry.

    Ewing RM, Chu P, Elisma F, Li H, Taylor P, Climie S, McBroom-Cerajewski L, Robinson MD, O'Connor L, Li M, Taylor R, Dharsee M, Ho Y, Heilbut A, Moore L, Zhang S, Ornatsky O, Bukhman YV, Ethier M, Sheng Y, Vasilescu J, Abu-Farha M, Lambert JP, Duewel HS, Stewart II, Kuehl B, Hogue K, Colwill K, Gladwish K, Muskat B, Kinach R, Adams SL, Moran MF, Morin GB, Topaloglou T and Figeys D

    Protana, Toronto, Ontario, Canada.

    Mapping protein-protein interactions is an invaluable tool for understanding protein function. Here, we report the first large-scale study of protein-protein interactions in human cells using a mass spectrometry-based approach. The study maps protein interactions for 338 bait proteins that were selected based on known or suspected disease and functional associations. Large-scale immunoprecipitation of Flag-tagged versions of these proteins followed by LC-ESI-MS/MS analysis resulted in the identification of 24,540 potential protein interactions. False positives and redundant hits were filtered out using empirical criteria and a calculated interaction confidence score, producing a data set of 6463 interactions between 2235 distinct proteins. This data set was further cross-validated using previously published and predicted human protein interactions. In-depth mining of the data set shows that it represents a valuable source of novel protein-protein interactions with relevance to human diseases. In addition, via our preliminary analysis, we report many novel protein interactions and pathway associations.

    Molecular systems biology 2007;3;89

  • Diversification of transcriptional modulation: large-scale identification and characterization of putative alternative promoters of human genes.

    Kimura K, Wakamatsu A, Suzuki Y, Ota T, Nishikawa T, Yamashita R, Yamamoto J, Sekine M, Tsuritani K, Wakaguri H, Ishii S, Sugiyama T, Saito K, Isono Y, Irie R, Kushida N, Yoneyama T, Otsuka R, Kanda K, Yokoi T, Kondo H, Wagatsuma M, Murakawa K, Ishida S, Ishibashi T, Takahashi-Fujii A, Tanase T, Nagai K, Kikuchi H, Nakai K, Isogai T and Sugano S

    Life Science Research Laboratory, Central Research Laboratory, Hitachi, Ltd., Kokubunji, Tokyo, 185-8601, Japan.

    By analyzing 1,780,295 5'-end sequences of human full-length cDNAs derived from 164 kinds of oligo-cap cDNA libraries, we identified 269,774 independent positions of transcriptional start sites (TSSs) for 14,628 human RefSeq genes. These TSSs were clustered into 30,964 clusters that were separated from each other by more than 500 bp and thus are very likely to constitute mutually distinct alternative promoters. To our surprise, at least 7674 (52%) human RefSeq genes were subject to regulation by putative alternative promoters (PAPs). On average, there were 3.1 PAPs per gene, with the composition of one CpG-island-containing promoter per 2.6 CpG-less promoters. In 17% of the PAP-containing loci, tissue-specific use of the PAPs was observed. The richest tissue sources of the tissue-specific PAPs were testis and brain. It was also intriguing that the PAP-containing promoters were enriched in the genes encoding signal transduction-related proteins and were rarer in the genes encoding extracellular proteins, possibly reflecting the varied functional requirement for and the restricted expression of those categories of genes, respectively. The patterns of the first exons were highly diverse as well. On average, there were 7.7 different splicing types of first exons per locus partly produced by the PAPs, suggesting that a wide variety of transcripts can be achieved by this mechanism. Our findings suggest that use of alternate promoters and consequent alternative use of first exons should play a pivotal role in generating the complexity required for the highly elaborated molecular systems in humans.

    Genome research 2006;16;1;55-65

  • Cytoplasmic dynein nomenclature.

    Pfister KK, Fisher EM, Gibbons IR, Hays TS, Holzbaur EL, McIntosh JR, Porter ME, Schroer TA, Vaughan KT, Witman GB, King SM and Vallee RB

    Department of Cell Biology, University of Virginia School of Medicine, Charlottesville, VA 22908, USA. kkp9w@virginia.edu

    A variety of names has been used in the literature for the subunits of cytoplasmic dynein complexes. Thus, there is a strong need for a more definitive consensus statement on nomenclature. This is especially important for mammalian cytoplasmic dyneins, many subunits of which are encoded by multiple genes. We propose names for the mammalian cytoplasmic dynein subunit genes and proteins that reflect the phylogenetic relationships of the genes and the published studies clarifying the functions of the polypeptides. This nomenclature recognizes the two distinct cytoplasmic dynein complexes and has the flexibility to accommodate the discovery of new subunits and isoforms.

    Funded by: NIGMS NIH HHS: R01 GM030626, R01 GM060560, R01 GM060560-05

    The Journal of cell biology 2005;171;3;411-3

  • 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

  • Transcriptome characterization elucidates signaling networks that control human ES cell growth and differentiation.

    Brandenberger R, Wei H, Zhang S, Lei S, Murage J, Fisk GJ, Li Y, Xu C, Fang R, Guegler K, Rao MS, Mandalam R, Lebkowski J and Stanton LW

    Geron Corporation, Menlo Park, California 94025, USA. rbrandenberger@geron.com

    Human embryonic stem (hES) cells hold promise for generating an unlimited supply of cells for replacement therapies. To characterize hES cells at the molecular level, we obtained 148,453 expressed sequence tags (ESTs) from undifferentiated hES cells and three differentiated derivative subpopulations. Over 32,000 different transcripts expressed in hES cells were identified, of which more than 16,000 do not match closely any gene in the UniGene public database. Queries to this EST database revealed 532 significantly upregulated and 140 significantly downregulated genes in undifferentiated hES cells. These data highlight changes in the transcriptional network that occur when hES cells differentiate. Among the differentially regulated genes are several components of signaling pathways and transcriptional regulators that likely play key roles in hES cell growth and differentiation. The genomic data presented here may facilitate the derivation of clinically useful cell types from hES cells.

    Nature biotechnology 2004;22;6;707-16

  • Localization of dynein light chains 1 and 2 and their pro-apoptotic ligands.

    Day CL, Puthalakath H, Skea G, Strasser A, Barsukov I, Lian LY, Huang DC and Hinds MG

    Department of Biochemistry, University of Otago, Dunedin, New Zealand.

    The dynein and myosin V motor complexes are multi-protein structures that function to transport molecules and organelles within the cell. DLC (dynein light-chain) proteins, found as components of both dynein and myosin V motor complexes, connect the complexes to their cargoes. One of the roles of these motor complexes is to selectively sequester the pro-apoptotic 'BH3-only' (Bcl-2 homology 3-only) proteins, Bim (Bcl-2-interacting mediator of cell death) and Bmf (Bcl-2-modifying factor), and so regulate their cell death-inducing function. In vivo DLC2 is found exclusively as a component of the myosin V motor complex and Bmf binds DLC2 selectively. On the other hand, Bim interacts with DLC1 (LC8), an integral component of the dynein motor complex. The two DLCs share 93% sequence identity yet show unambiguous in vivo specificity for their respective BH3-only ligands. To investigate this specificity the three-dimensional solution structure of DLC2 was elucidated using NMR spectroscopy. In vitro structural and mutagenesis studies show that Bmf and Bim have identical binding characteristics to recombinant DLC2 or DLC1. Thus the selectivity shown by Bmf and Bim for binding DLC1 or DLC2, respectively, does not reside in their DLC-binding domains. Remarkably, mutational analysis of DLC1 and DLC2 indicates that a single surface residue (residue 41) determines the specific localization of DLCs with their respective motor complexes. These results suggest a molecular mechanism for the specific compartmentalization of DLCs and their pro-apoptotic cargoes and implicate other protein(s) in defining the specificity between the cargoes and the DLC proteins.

    Funded by: NCI NIH HHS: CA 80188

    The Biochemical journal 2004;377;Pt 3;597-605

  • JNK phosphorylation of Bim-related members of the Bcl2 family induces Bax-dependent apoptosis.

    Lei K and Davis RJ

    Howard Hughes Medical Institute and Program in Molecular Medicine, University of Massachusetts Medical School, Worcester, MA 01605, USA.

    The c-Jun NH(2)-terminal kinase (JNK) is activated when cells are exposed to environmental stress, including UV radiation. Gene disruption studies demonstrate that JNK is essential for UV-stimulated apoptosis mediated by the mitochondrial pathway by a Bax/Bak-dependent mechanism. Here, we demonstrate that JNK phosphorylates two members of the BH3-only subgroup of Bcl2-related proteins (Bim and Bmf) that are normally sequestered by binding to dynein and myosin V motor complexes. Phosphorylation by JNK causes release from the motor complexes. These proapoptotic BH3-only proteins therefore provide a molecular link between the JNK signal transduction pathway and the Bax/Bak-dependent mitochondrial apoptotic machinery.

    Proceedings of the National Academy of Sciences of the United States of America 2003;100;5;2432-7

  • Gephyrin interacts with Dynein light chains 1 and 2, components of motor protein complexes.

    Fuhrmann JC, Kins S, Rostaing P, El Far O, Kirsch J, Sheng M, Triller A, Betz H and Kneussel M

    Max-Planck-Institute for Brain Research, Department of Neurochemistry, D-60528 Frankfurt/Main, Germany.

    The clustering of glycine receptors and major subtypes of GABA(A) receptors at inhibitory synapses is mediated by the tubulin-binding protein gephyrin. In an attempt to identify additional components of inhibitory postsynaptic specializations, we performed a yeast two-hybrid screen using gephyrin as bait. Multiple positive clones encoded either the dynein light chain-1 (Dlc-1), also known as dynein LC8 and protein inhibitor of neuronal nitric oxide synthase, or its homolog Dlc-2. Dlc-1 protein bound efficiently to gephyrin in in vitro binding assays and colocalized with gephyrin during coexpression in HEK293 cells. The binding site for Dlc was mapped to a fragment of 63 amino acids within the central linker domain of gephyrin. In hippocampal neurons, endogenous Dlc protein was enriched at synaptic sites identified by synaptophysin and gephyrin immunostaining. Immunoelectron microscopy in spinal cord sections revealed Dlc immunoreactivity at the edges of postsynaptic differentiations, in close contact with cytoskeletal structures and at the periphery of the Golgi apparatus. Because Dlc-1 and Dlc-2 have been described as stoichiometric components of cytoplasmic dynein and myosin-Va complexes, our results suggest that motor proteins are involved in the subcellular localization of gephyrin.

    The Journal of neuroscience : the official journal of the Society for Neuroscience 2002;22;13;5393-402

  • Bmf: a proapoptotic BH3-only protein regulated by interaction with the myosin V actin motor complex, activated by anoikis.

    Puthalakath H, Villunger A, O'Reilly LA, Beaumont JG, Coultas L, Cheney RE, Huang DC and Strasser A

    The Walter and Eliza Hall Institute of Medical Research, Melbourne, P.O. Royal Melbourne Hospital, 3050 VIC, Australia.

    Bcl-2 family members bearing only the BH3 domain are essential inducers of apoptosis. We identified a BH3-only protein, Bmf, and show that its BH3 domain is required both for binding to prosurvival Bcl-2 proteins and for triggering apoptosis. In healthy cells, Bmf is sequestered to myosin V motors by association with dynein light chain 2. Certain damage signals, such as loss of cell attachment (anoikis), unleash Bmf, allowing it to translocate and bind prosurvival Bcl-2 proteins. Thus, at least two mammalian BH3-only proteins, Bmf and Bim, function to sense intracellular damage by their localization to distinct cytoskeletal structures.

    Funded by: NCI NIH HHS: CA 80188; NIDCD NIH HHS: R29 DC003299

    Science (New York, N.Y.) 2001;293;5536;1829-32

  • The hDLG-associated protein DAP interacts with dynein light chain and neuronal nitric oxide synthase.

    Haraguchi K, Satoh K, Yanai H, Hamada F, Kawabuchi M and Akiyama T

    Laboratory of Molecular and Genetic Information, Institute for Molecular and Cellular Biosciences, The University of Tokyo, Japan.

    Background: Postsynaptic density (PSD)-95 interacts with and mediates clustering of the N-methyl-D-aspartate-receptors (NMDA-R). PSD-95 also interacts with the hDLG-associated protein DAP, which is also called Synapse-associated protein 90-associated protein (SAPAP), and Guanylate kinase-associated protein (GKAP).

    Results: DAP interacted directly with the dynein light chain (DLC) family of proteins. DLC was contained in the NMDA-R-PSD-95-DAP-neuronal nitric oxide synthase (nNOS) complex. Furthermore, DAP interacted with nNOS and recruited it into the Triton X-100-insoluble fraction of transfected cells.

    Conclusion: DAP interacts directly with DLC and nNOS, and links these proteins to the NMDA-R-PSD-95 complex.

    Genes to cells : devoted to molecular & cellular mechanisms 2000;5;11;905-911

  • Interaction of the postsynaptic density-95/guanylate kinase domain-associated protein complex with a light chain of myosin-V and dynein.

    Naisbitt S, Valtschanoff J, Allison DW, Sala C, Kim E, Craig AM, Weinberg RJ and Sheng M

    Howard Hughes Medical Institute, Department of Neurobiology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts 02114, USA.

    NMDA receptors interact directly with postsynaptic density-95 (PSD-95), a scaffold protein that organizes a cytoskeletal- signaling complex at the postsynaptic membrane. The molecular mechanism by which the PSD-95-based protein complex is trafficked to the postsynaptic site is unknown but presumably involves specific motor proteins. Here we demonstrate a direct interaction between the PSD-95-associated protein guanylate kinase domain-associated protein (GKAP) and dynein light chain (DLC), a light chain subunit shared by myosin-V (an actin-based motor) and cytoplasmic dynein (a microtubule-based motor). A yeast two-hybrid screen with GKAP isolated DLC2, a novel protein 93% identical to the previously cloned 8 kDa dynein light chain (DLC1). A complex containing PSD-95, GKAP, DLC, and myosin-V can be immunoprecipitated from rat brain extracts. DLC colocalizes with PSD-95 and F-actin in dendritic spines of cultured neurons and is enriched in biochemical purifications of PSD. Immunogold electron microscopy reveals a concentration of DLC in the postsynaptic compartment of asymmetric synapses of brain in which it is associated with the PSD and the spine apparatus. We discuss the possibility that the GKAP/DLC interaction may be involved in trafficking of the PSD-95 complex by motor proteins.

    Funded by: NINDS NIH HHS: NS29879, NS33184, NS35050

    The Journal of neuroscience : the official journal of the Society for Neuroscience 2000;20;12;4524-34

Gene lists (5)

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
L00000059 G2C Homo sapiens BAYES-COLLINS-HUMAN-PSD-CONSENSUS Human cortex PSD consensus 748
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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