G2Cdb::Gene report

Gene id
G00002503
Gene symbol
MYO1D (HGNC)
Species
Homo sapiens
Description
myosin ID
Orthologue
G00001254 (Mus musculus)

Databases (7)

Gene
ENSG00000176658 (Ensembl human gene)
4642 (Entrez Gene)
1195 (G2Cdb plasticity & disease)
MYO1D (GeneCards)
Literature
606539 (OMIM)
Marker Symbol
HGNC:7598 (HGNC)
Protein Sequence
O94832 (UniProt)

Synonyms (2)

  • KIAA0727
  • myr4

Literature (7)

Pubmed - other

  • Prefrontal cortex shotgun proteome analysis reveals altered calcium homeostasis and immune system imbalance in schizophrenia.

    Martins-de-Souza D, Gattaz WF, Schmitt A, Rewerts C, Maccarrone G, Dias-Neto E and Turck CW

    Laboratório de Neurociências, Instituto de Psiquiatria, Universidade de São Paulo, Rua. Dr. Ovidio Pires de Campos, no 785, Consolação, São Paulo, SP 05403-010, Brazil.

    Schizophrenia is a complex disease, likely to be caused by a combination of serial alterations in a number of genes and environmental factors. The dorsolateral prefrontal cortex (Brodmann's Area 46) is involved in schizophrenia and executes high-level functions such as working memory, differentiation of conflicting thoughts, determination of right and wrong concepts and attitudes, correct social behavior and personality expression. Global proteomic analysis of post-mortem dorsolateral prefrontal cortex samples from schizophrenia patients and non-schizophrenic individuals was performed using stable isotope labeling and shotgun proteomics. The analysis resulted in the identification of 1,261 proteins, 84 of which showed statistically significant differential expression, reinforcing previous data supporting the involvement of the immune system, calcium homeostasis, cytoskeleton assembly, and energy metabolism in schizophrenia. In addition a number of new potential markers were found that may contribute to the understanding of the pathogenesis of this complex disease.

    European archives of psychiatry and clinical neuroscience 2009;259;3;151-63

  • High density SNP association study of a major autism linkage region on chromosome 17.

    Stone JL, Merriman B, Cantor RM, Geschwind DH and Nelson SF

    Department of Human Genetics, University of California, Los Angeles, CA 90095, USA.

    A region on chromosome 17 has recently been highlighted as linked to autism (MIM[209850]) in multiple studies and evidence has accumulated suggesting that male-only families (those families that have produced only affected males) provide the major contribution to linkage at this locus. In an attempt to comprehensively test for association of common variants to autism within the region on chromosome 17 defined in Stone et al. (Stone, J.L., Merriman, B., Cantor, R.M., Yonan, A.L., Gilliam, T.C., Geschwind, D.H. and Nelson, S.F. (2004) Evidence for sex-specific risk alleles in autism spectrum disorder. Am. J. Hum. Genet., 75, 1117-1123), a dense panel of single nucleotide polymorphisms (SNPs) was selected across the linkage peak and analyzed in a trio-based study design. SNPs were genotyped in 219 independent trios at an average intermarker distance of 6.1 kb across the 13.7 Mb interval. This provided ~80% coverage of common HapMap variation present in Caucasians, testing exonic, intronic, promoter and intergenic regions, as knowledge of important functional regions within the genome is currently limited. In this comprehensive association study of a linkage region in autism, no single SNP or haplotype association was sufficient to account for the initial linkage signal. Nominally significant single SNP and/or haplotype-based association results were detected in 15 genes, of which, MYO1D, ACCN1 and LASP1 stand out as genes with autism risk alleles requiring further study, with potential GRRs in the range of 1.34-2.29.

    Funded by: NIMH NIH HHS: MH64547

    Human molecular genetics 2007;16;6;704-15

  • 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

  • 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

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

    Nagase T, Ishikawa K, Suyama M, Kikuno R, Miyajima N, Tanaka A, Kotani H, Nomura N and Ohara O

    Kazusa DNA Research Institute, Kisarazu, Chiba, Japan.

    In our series of projects for accumulating sequence information on the coding sequences of unidentified human genes, we have newly determined the sequences of 100 cDNA clones from a set of size-fractionated human brain cDNA libraries, and predicted the coding sequences of the corresponding genes, named KIAA0711 to KIAA0810. These cDNA clones were selected according to their coding potentials of large proteins (50 kDa and more) in vitro. The average sizes of the inserts and corresponding open reading frames were 4.3 kb and 2.6 kb (869 amino acid residues), respectively. Sequence analyses against the public databases indicated that the predicted coding sequences of 78 genes were similar to those of known genes, 64% of which (50 genes) were categorized as proteins functionally related to cell signaling/communication, cell structure/motility and nucleic acid management. As additional information concerning genes characterized in this study, the chromosomal locations of the clones were determined by using human-rodent hybrid panels and the expression profiles among 10 human tissues were examined by reverse transcription-coupled polymerase chain reaction which was substantially improved by enzyme-linked immunosorbent assay.

    DNA research : an international journal for rapid publication of reports on genes and genomes 1998;5;5;277-86

  • Mapping of unconventional myosins in mouse and human.

    Hasson T, Skowron JF, Gilbert DJ, Avraham KB, Perry WL, Bement WM, Anderson BL, Sherr EH, Chen ZY, Greene LA, Ward DC, Corey DP, Mooseker MS, Copeland NG and Jenkins NA

    Department of Biology, Yale University, New Haven, Connecticut 06520, USA.

    Myosins are molecular motors that move along filamentous actin. Seven classes of myosin are expressed in vertebrates: conventional myosin, or myosin-II, as well as the 6 unconventional myosin classes-I, -V, -VI, -VII, -IX, and -X. We have mapped in mouse 22 probes encompassing all known unconventional myosins and, as a result, have identified 16 potential unconventional myosin genes. These genes include 7 myosins-I, 2 myosins-V, 1 myosin-VI, 3 myosins-VII, 2 myosins-IX, and 1 myosin-X. The map location of 5 of these genes was identified in human chromosomes by fluorescence in situ hybridization.

    Funded by: NIDDK NIH HHS: DK25387, DK38979; NINDS NIH HHS: NS33689

    Genomics 1996;36;3;431-9

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