G2Cdb::Gene report

Gene id
G00002041
Gene symbol
PHACTR1 (HGNC)
Species
Homo sapiens
Description
phosphatase and actin regulator 1
Orthologue
G00000792 (Mus musculus)

Databases (8)

Curated Gene
OTTHUMG00000014270 (Vega human gene)
Gene
ENSG00000112137 (Ensembl human gene)
221692 (Entrez Gene)
1282 (G2Cdb plasticity & disease)
PHACTR1 (GeneCards)
Literature
608723 (OMIM)
Marker Symbol
HGNC:20990 (HGNC)
Protein Sequence
Q9C0D0 (UniProt)

Synonyms (2)

  • KIAA1733
  • dJ257A7.2

Literature (8)

Pubmed - other

  • Genome-wide association of early-onset myocardial infarction with single nucleotide polymorphisms and copy number variants.

    Myocardial Infarction Genetics Consortium, Kathiresan S, Voight BF, Purcell S, Musunuru K, Ardissino D, Mannucci PM, Anand S, Engert JC, Samani NJ, Schunkert H, Erdmann J, Reilly MP, Rader DJ, Morgan T, Spertus JA, Stoll M, Girelli D, McKeown PP, Patterson CC, Siscovick DS, O'Donnell CJ, Elosua R, Peltonen L, Salomaa V, Schwartz SM, Melander O, Altshuler D, Ardissino D, Merlini PA, Berzuini C, Bernardinelli L, Peyvandi F, Tubaro M, Celli P, Ferrario M, Fetiveau R, Marziliano N, Casari G, Galli M, Ribichini F, Rossi M, Bernardi F, Zonzin P, Piazza A, Mannucci PM, Schwartz SM, Siscovick DS, Yee J, Friedlander Y, Elosua R, Marrugat J, Lucas G, Subirana I, Sala J, Ramos R, Kathiresan S, Meigs JB, Williams G, Nathan DM, MacRae CA, O'Donnell CJ, Salomaa V, Havulinna AS, Peltonen L, Melander O, Berglund G, Voight BF, Kathiresan S, Hirschhorn JN, Asselta R, Duga S, Spreafico M, Musunuru K, Daly MJ, Purcell S, Voight BF, Purcell S, Nemesh J, Korn JM, McCarroll SA, Schwartz SM, Yee J, Kathiresan S, Lucas G, Subirana I, Elosua R, Surti A, Guiducci C, Gianniny L, Mirel D, Parkin M, Burtt N, Gabriel SB, Samani NJ, Thompson JR, Braund PS, Wright BJ, Balmforth AJ, Ball SG, Hall A, Wellcome Trust Case Control Consortium, Schunkert H, Erdmann J, Linsel-Nitschke P, Lieb W, Ziegler A, König I, Hengstenberg C, Fischer M, Stark K, Grosshennig A, Preuss M, Wichmann HE, Schreiber S, Schunkert H, Samani NJ, Erdmann J, Ouwehand W, Hengstenberg C, Deloukas P, Scholz M, Cambien F, Reilly MP, Li M, Chen Z, Wilensky R, Matthai W, Qasim A, Hakonarson HH, Devaney J, Burnett MS, Pichard AD, Kent KM, Satler L, Lindsay JM, Waksman R, Knouff CW, Waterworth DM, Walker MC, Mooser V, Epstein SE, Rader DJ, Scheffold T, Berger K, Stoll M, Huge A, Girelli D, Martinelli N, Olivieri O, Corrocher R, Morgan T, Spertus JA, McKeown P, Patterson CC, Schunkert H, Erdmann E, Linsel-Nitschke P, Lieb W, Ziegler A, König IR, Hengstenberg C, Fischer M, Stark K, Grosshennig A, Preuss M, Wichmann HE, Schreiber S, Hólm H, Thorleifsson G, Thorsteinsdottir U, Stefansson K, Engert JC, Do R, Xie C, Anand S, Kathiresan S, Ardissino D, Mannucci PM, Siscovick D, O'Donnell CJ, Samani NJ, Melander O, Elosua R, Peltonen L, Salomaa V, Schwartz SM and Altshuler D

    Cardiovascular Research Center and Cardiology Division, Massachusetts General Hospital, Boston, Massachusetts 02114, USA. skathiresan1@partners.org

    We conducted a genome-wide association study testing single nucleotide polymorphisms (SNPs) and copy number variants (CNVs) for association with early-onset myocardial infarction in 2,967 cases and 3,075 controls. We carried out replication in an independent sample with an effective sample size of up to 19,492. SNPs at nine loci reached genome-wide significance: three are newly identified (21q22 near MRPS6-SLC5A3-KCNE2, 6p24 in PHACTR1 and 2q33 in WDR12) and six replicated prior observations (9p21, 1p13 near CELSR2-PSRC1-SORT1, 10q11 near CXCL12, 1q41 in MIA3, 19p13 near LDLR and 1p32 near PCSK9). We tested 554 common copy number polymorphisms (>1% allele frequency) and none met the pre-specified threshold for replication (P < 10(-3)). We identified 8,065 rare CNVs but did not detect a greater CNV burden in cases compared to controls, in genes compared to the genome as a whole, or at any individual locus. SNPs at nine loci were reproducibly associated with myocardial infarction, but tests of common and rare CNVs failed to identify additional associations with myocardial infarction risk.

    Funded by: British Heart Foundation; Medical Research Council: G0802320; NCRR NIH HHS: U54 RR020278; NHLBI NIH HHS: R01 HL056931, R01 HL056931-02, R01 HL056931-03, R01 HL056931-04, R01HL056931; NICHD NIH HHS: N01HD013107; NIDDK NIH HHS: K24 DK080140; NIEHS NIH HHS: P30ES007033; Wellcome Trust: 076113, 089061

    Nature genetics 2009;41;3;334-41

  • Genome-wide association with bone mass and geometry in the Framingham Heart Study.

    Kiel DP, Demissie S, Dupuis J, Lunetta KL, Murabito JM and Karasik D

    Hebrew SeniorLife Institute for Aging Research and Harvard Medical School, Boston, MA, USA. kiel@hrca.harvard.edu

    Background: Osteoporosis is characterized by low bone mass and compromised bone structure, heritable traits that contribute to fracture risk. There have been no genome-wide association and linkage studies for these traits using high-density genotyping platforms.

    Methods: We used the Affymetrix 100K SNP GeneChip marker set in the Framingham Heart Study (FHS) to examine genetic associations with ten primary quantitative traits: bone mineral density (BMD), calcaneal ultrasound, and geometric indices of the hip. To test associations with multivariable-adjusted residual trait values, we used additive generalized estimating equation (GEE) and family-based association tests (FBAT) models within each sex as well as sexes combined. We evaluated 70,987 autosomal SNPs with genotypic call rates > or =80%, HWE p > or = 0.001, and MAF > or =10% in up to 1141 phenotyped individuals (495 men and 646 women, mean age 62.5 yrs). Variance component linkage analysis was performed using 11,200 markers.

    Results: Heritability estimates for all bone phenotypes were 30-66%. LOD scores > or =3.0 were found on chromosomes 15 (1.5 LOD confidence interval: 51,336,679-58,934,236 bp) and 22 (35,890,398-48,603,847 bp) for femoral shaft section modulus. The ten primary phenotypes had 12 associations with 100K SNPs in GEE models at p < 0.000001 and 2 associations in FBAT models at p < 0.000001. The 25 most significant p-values for GEE and FBAT were all less than 3.5 x 10(-6) and 2.5 x 10(-5), respectively. Of the 40 top SNPs with the greatest numbers of significantly associated BMD traits (including femoral neck, trochanter, and lumbar spine), one half to two-thirds were in or near genes that have not previously been studied for osteoporosis. Notably, pleiotropic associations between BMD and bone geometric traits were uncommon. Evidence for association (FBAT or GEE p < 0.05) was observed for several SNPs in candidate genes for osteoporosis, such as rs1801133 in MTHFR; rs1884052 and rs3778099 in ESR1; rs4988300 in LRP5; rs2189480 in VDR; rs2075555 in COLIA1; rs10519297 and rs2008691 in CYP19, as well as SNPs in PPARG (rs10510418 and rs2938392) and ANKH (rs2454873 and rs379016). All GEE, FBAT and linkage results are provided as an open-access results resource at http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007 webcite.

    Conclusion: The FHS 100K SNP project offers an unbiased genome-wide strategy to identify new candidate loci and to replicate previously suggested candidate genes for osteoporosis.

    Funded by: NCRR NIH HHS: 1S10RR163736-01A1; NHLBI NIH HHS: N01-HC-25195, N01HC25195; NIA NIH HHS: R01 AR/AG 41398; NIAMS NIH HHS: R01 AR041398, R01 AR041398-15, R01 AR050066

    BMC medical genetics 2007;8 Suppl 1;S14

  • 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

  • Phactrs 1-4: A family of protein phosphatase 1 and actin regulatory proteins.

    Allen PB, Greenfield AT, Svenningsson P, Haspeslagh DC and Greengard P

    Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06508, USA. patrick.allen@yale.edu

    Protein phosphatase 1 (PP1) is a multifunctional enzyme with diverse roles in the nervous system, including regulation of synaptic activity and dendritic morphology. PP1 activity is controlled via association with a family of regulatory subunits that govern subcellular localization and substrate specificity. A previously undescribed class of PP1-binding proteins was detected by interaction cloning. Family members were also found to bind to cytoplasmic actin via Arg, Pro, Glu, and Leu repeat-containing sequences. The prototypical member of this family, phosphatase and actin regulator (phactr) 1 was a potent modulator of PP1 activity in vitro. Phactr-1 protein is selectively expressed in brain, where high levels were found in cortex, hippocampus, and striatum, with enrichment of the protein at synapses. Additional family members displayed highly distinct mRNA transcript expression patterns within rat brain. The current findings present a mechanism by which PP1 may be directed toward neuronal substrates associated with the actin cytoskeleton.

    Funded by: NIDA NIH HHS: DA10044, P01 DA010044; NIMH NIH HHS: MH40899, P01 MH040899

    Proceedings of the National Academy of Sciences of the United States of America 2004;101;18;7187-92

  • Complete sequencing and characterization of 21,243 full-length human cDNAs.

    Ota T, Suzuki Y, Nishikawa T, Otsuki T, Sugiyama T, Irie R, Wakamatsu A, Hayashi K, Sato H, Nagai K, Kimura K, Makita H, Sekine M, Obayashi M, Nishi T, Shibahara T, Tanaka T, Ishii S, Yamamoto J, Saito K, Kawai Y, Isono Y, Nakamura Y, Nagahari K, Murakami K, Yasuda T, Iwayanagi T, Wagatsuma M, Shiratori A, Sudo H, Hosoiri T, Kaku Y, Kodaira H, Kondo H, Sugawara M, Takahashi M, Kanda K, Yokoi T, Furuya T, Kikkawa E, Omura Y, Abe K, Kamihara K, Katsuta N, Sato K, Tanikawa M, Yamazaki M, Ninomiya K, Ishibashi T, Yamashita H, Murakawa K, Fujimori K, Tanai H, Kimata M, Watanabe M, Hiraoka S, Chiba Y, Ishida S, Ono Y, Takiguchi S, Watanabe S, Yosida M, Hotuta T, Kusano J, Kanehori K, Takahashi-Fujii A, Hara H, Tanase TO, Nomura Y, Togiya S, Komai F, Hara R, Takeuchi K, Arita M, Imose N, Musashino K, Yuuki H, Oshima A, Sasaki N, Aotsuka S, Yoshikawa Y, Matsunawa H, Ichihara T, Shiohata N, Sano S, Moriya S, Momiyama H, Satoh N, Takami S, Terashima Y, Suzuki O, Nakagawa S, Senoh A, Mizoguchi H, Goto Y, Shimizu F, Wakebe H, Hishigaki H, Watanabe T, Sugiyama A, Takemoto M, Kawakami B, Yamazaki M, Watanabe K, Kumagai A, Itakura S, Fukuzumi Y, Fujimori Y, Komiyama M, Tashiro H, Tanigami A, Fujiwara T, Ono T, Yamada K, Fujii Y, Ozaki K, Hirao M, Ohmori Y, Kawabata A, Hikiji T, Kobatake N, Inagaki H, Ikema Y, Okamoto S, Okitani R, Kawakami T, Noguchi S, Itoh T, Shigeta K, Senba T, Matsumura K, Nakajima Y, Mizuno T, Morinaga M, Sasaki M, Togashi T, Oyama M, Hata H, Watanabe M, Komatsu T, Mizushima-Sugano J, Satoh T, Shirai Y, Takahashi Y, Nakagawa K, Okumura K, Nagase T, Nomura N, Kikuchi H, Masuho Y, Yamashita R, Nakai K, Yada T, Nakamura Y, Ohara O, Isogai T and Sugano S

    Helix Research Institute, 1532-3 Yana, Kisarazu, Chiba 292-0812, Japan.

    As a base for human transcriptome and functional genomics, we created the "full-length long Japan" (FLJ) collection of sequenced human cDNAs. We determined the entire sequence of 21,243 selected clones and found that 14,490 cDNAs (10,897 clusters) were unique to the FLJ collection. About half of them (5,416) seemed to be protein-coding. Of those, 1,999 clusters had not been predicted by computational methods. The distribution of GC content of nonpredicted cDNAs had a peak at approximately 58% compared with a peak at approximately 42%for predicted cDNAs. Thus, there seems to be a slight bias against GC-rich transcripts in current gene prediction procedures. The rest of the cDNAs unique to the FLJ collection (5,481) contained no obvious open reading frames (ORFs) and thus are candidate noncoding RNAs. About one-fourth of them (1,378) showed a clear pattern of splicing. The distribution of GC content of noncoding cDNAs was narrow and had a peak at approximately 42%, relatively low compared with that of protein-coding cDNAs.

    Nature genetics 2004;36;1;40-5

  • The DNA sequence and analysis of human chromosome 6.

    Mungall AJ, Palmer SA, Sims SK, Edwards CA, Ashurst JL, Wilming L, Jones MC, Horton R, Hunt SE, Scott CE, Gilbert JG, Clamp ME, Bethel G, Milne S, Ainscough R, Almeida JP, Ambrose KD, Andrews TD, Ashwell RI, Babbage AK, Bagguley CL, Bailey J, Banerjee R, Barker DJ, Barlow KF, Bates K, Beare DM, Beasley H, Beasley O, Bird CP, Blakey S, Bray-Allen S, Brook J, Brown AJ, Brown JY, Burford DC, Burrill W, Burton J, Carder C, Carter NP, Chapman JC, Clark SY, Clark G, Clee CM, Clegg S, Cobley V, Collier RE, Collins JE, Colman LK, Corby NR, Coville GJ, Culley KM, Dhami P, Davies J, Dunn M, Earthrowl ME, Ellington AE, Evans KA, Faulkner L, Francis MD, Frankish A, Frankland J, French L, Garner P, Garnett J, Ghori MJ, Gilby LM, Gillson CJ, Glithero RJ, Grafham DV, Grant M, Gribble S, Griffiths C, Griffiths M, Hall R, Halls KS, Hammond S, Harley JL, Hart EA, Heath PD, Heathcott R, Holmes SJ, Howden PJ, Howe KL, Howell GR, Huckle E, Humphray SJ, Humphries MD, Hunt AR, Johnson CM, Joy AA, Kay M, Keenan SJ, Kimberley AM, King A, Laird GK, Langford C, Lawlor S, Leongamornlert DA, Leversha M, Lloyd CR, Lloyd DM, Loveland JE, Lovell J, Martin S, Mashreghi-Mohammadi M, Maslen GL, Matthews L, McCann OT, McLaren SJ, McLay K, McMurray A, Moore MJ, Mullikin JC, Niblett D, Nickerson T, Novik KL, Oliver K, Overton-Larty EK, Parker A, Patel R, Pearce AV, Peck AI, Phillimore B, Phillips S, Plumb RW, Porter KM, Ramsey Y, Ranby SA, Rice CM, Ross MT, Searle SM, Sehra HK, Sheridan E, Skuce CD, Smith S, Smith M, Spraggon L, Squares SL, Steward CA, Sycamore N, Tamlyn-Hall G, Tester J, Theaker AJ, Thomas DW, Thorpe A, Tracey A, Tromans A, Tubby B, Wall M, Wallis JM, West AP, White SS, Whitehead SL, Whittaker H, Wild A, Willey DJ, Wilmer TE, Wood JM, Wray PW, Wyatt JC, Young L, Younger RM, Bentley DR, Coulson A, Durbin R, Hubbard T, Sulston JE, Dunham I, Rogers J and Beck S

    The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK. ajm@sanger.ac.uk

    Chromosome 6 is a metacentric chromosome that constitutes about 6% of the human genome. The finished sequence comprises 166,880,988 base pairs, representing the largest chromosome sequenced so far. The entire sequence has been subjected to high-quality manual annotation, resulting in the evidence-supported identification of 1,557 genes and 633 pseudogenes. Here we report that at least 96% of the protein-coding genes have been identified, as assessed by multi-species comparative sequence analysis, and provide evidence for the presence of further, otherwise unsupported exons/genes. Among these are genes directly implicated in cancer, schizophrenia, autoimmunity and many other diseases. Chromosome 6 harbours the largest transfer RNA gene cluster in the genome; we show that this cluster co-localizes with a region of high transcriptional activity. Within the essential immune loci of the major histocompatibility complex, we find HLA-B to be the most polymorphic gene on chromosome 6 and in the human genome.

    Nature 2003;425;6960;805-11

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

    Nagase T, Kikuno R, Hattori A, Kondo Y, Okumura K and Ohara O

    Kazusa DNA Research Institute, Kisarazu, Chiba, Japan.

    As an extension of our human cDNA project for accumulating sequence information on the coding sequences of unidentified genes, we here present the entire sequences of 100 cDNA clones of unidentified genes, named KIAA1673-KIAA1772, from three sets of size-fractionated cDNA libraries derived from human adult whole brain, hippocampus, and fetal whole brain. The average sizes of the inserts and corresponding open reading frames of cDNA clones analyzed here were 4.9 kb and 2.7 kb (corresponding to 895 amino acid residues), respectively. By computer-assisted analysis of the deduced amino acid sequences, 44 predicted gene products were classified into five functional categories of proteins relating to cell signaling/communication, nucleic acid management, cell structure/motility, protein management, and metabolism. Furthermore, the expression profiles of the genes were also studied in 10 human tissues, 8 brain regions, spinal cord, fetal brain and fetal liver by reverse-transcription-coupled polymerase chain reaction, the 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;6;347-55

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
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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