G2Cdb::Gene report

Gene id
Gene symbol
Homo sapiens
formin-like 3
G00001182 (Mus musculus)

Databases (6)

ENSG00000161791 (Ensembl human gene)
91010 (Entrez Gene)
1042 (G2Cdb plasticity & disease)
FMNL3 (GeneCards)
Marker Symbol
HGNC:23698 (HGNC)
Protein Sequence
Q9NSL0 (UniProt)

Synonyms (3)

  • DKFZp762B245
  • MGC45819
  • WBP3

Literature (5)

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

  • Functional proteomics mapping of a human signaling pathway.

    Colland F, Jacq X, Trouplin V, Mougin C, Groizeleau C, Hamburger A, Meil A, Wojcik J, Legrain P and Gauthier JM

    Hybrigenics SA, 75014 Paris, France. fcolland@hybrigenics.fr

    Access to the human genome facilitates extensive functional proteomics studies. Here, we present an integrated approach combining large-scale protein interaction mapping, exploration of the interaction network, and cellular functional assays performed on newly identified proteins involved in a human signaling pathway. As a proof of principle, we studied the Smad signaling system, which is regulated by members of the transforming growth factor beta (TGFbeta) superfamily. We used two-hybrid screening to map Smad signaling protein-protein interactions and to establish a network of 755 interactions, involving 591 proteins, 179 of which were poorly or not annotated. The exploration of such complex interaction databases is improved by the use of PIMRider, a dedicated navigation tool accessible through the Web. The biological meaning of this network is illustrated by the presence of 18 known Smad-associated proteins. Functional assays performed in mammalian cells including siRNA knock-down experiments identified eight novel proteins involved in Smad signaling, thus validating this integrated functional proteomics approach.

    Genome research 2004;14;7;1324-32

  • 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

  • Identification and characterization of human FMNL1, FMNL2 and FMNL3 genes in silico.

    Katoh M and Katoh M

    M&M Medical BioInformatics, Narashino 275-0022, Japan.

    FMNL (NM_005892.2) is a 5'-truncated partial cDNA encoding a Formin-homology protein related to DAAM1, DAAM2, DIAPH1 and DIAPH2. Here, we identified three members of FMNL gene family in the human genome by using bioinformatics. FMNL1 gene, corresponding to 5'-truncated KW-13 and FMNL cDNAs, was located within reference genomic contig NT_010748.9 (nucleotide position 100576-125849, forward orientation). FMNL2 gene, corresponding to KIAA1902 and FHOD2 cDNAs, was located within NT_005151.10 (nucleotide position 122465-436828, forward orientation). FMNL3 gene, corresponding to 5'-truncated DKFZp762B245 and KIAA2014 cDNAs, was located within NT_026397.10 (nucleotide position 209769-279037, reverse orientation). FMNL1, FMNL2 and FMNL3 genes encode A and B isoforms with the C-terminal divergence due to alternative splicing (cassette splicing of exon 26). FMNL1A (1100 aa), FMNL1B (1114 aa), FMNL2A (1087 aa), FMNL2B (1093 aa), FMNL3A (1028 aa) and FMNL3B (1027 aa) consist of FDD, FH1 and FH2 domains. Total amino-acid identity were as follows: FMNL1A vs. FMNL2A, 59.3%; FMNL1A vs. FMNL3A, 56.1%; FMNL2A vs. FMNL3A, 68.6%. FMNL1 gene was mapped to human chromosome 17q21. FMNL2 gene was linked to FNBP3/HYPA gene on chromosome 2q23.3, while FMNL3 gene was linked to FNBP3L/HYPC gene on chromosome 12q13. FMNL1 mRNA was expressed in natural killer cells, Burkitt lymphoma, pancreatic cancer, prostate cancer, and lung large cell carcinoma, FMNL2 mRNA in several normal tissues, diffuse-type gastric cancer, breast cancer, chondrosarcoma, melanoma, and glioblastoma, and FMNL3 mRNA in gastric cancer. FMNL1, FMNL2 and FMNL3 might be implicated in polarity control, invasion, migration, or metastasis through regulation of the Rho-related signaling pathway.

    International journal of oncology 2003;22;5;1161-8

  • FBP WW domains and the Abl SH3 domain bind to a specific class of proline-rich ligands.

    Bedford MT, Chan DC and Leder P

    Department of Genetics, Harvard Medical School, Howard Hughes Medical Institute, Boston, MA 02115, USA.

    WW domains are conserved protein motifs of 38-40 amino acids found in a broad spectrum of proteins. They mediate protein-protein interactions by binding proline-rich modules in ligands. A 10 amino acid proline-rich portion of the morphogenic protein, formin, is bound in vitro by both the WW domain of the formin-binding protein 11 (FBP11) and the SH3 domain of Abl. To explore whether the FBP11 WW domain and Abl SH3 domain bind to similar ligands, we screened a mouse limb bud expression library for putative ligands of the FBP11 WW domain. In so doing, we identified eight ligands (WBP3 through WBP10), each of which contains a proline-rich region or regions. Peptide sequence comparisons of the ligands revealed a conserved motif of 10 amino acids that acts as a modular sequence binding the FBP11 WW domain, but not the WW domain of the putative signal transducing factor, hYAP65. Interestingly, the consensus ligand for the FBP11 WW domain contains residues that are also required for binding by the Abl SH3 domain. These findings support the notion that the FBP11 WW domain and the Abl SH3 domain can compete for the same proline-rich ligands and suggest that at least two subclasses of WW domains exist, namely those that bind a PPLP motif, and those that bind a PPXY motif.

    The EMBO journal 1997;16;9;2376-83

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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