Sui Et Al Supplementary Figures
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Supplemental Figure 1. Vimentin
Double mutant specific genes Transcript gene_assignment Gene Symbol RefSeq FDR Fold- FDR Fold- FDR Fold- ID (single vs. Change (double Change (double Change wt) (single vs. wt) (double vs. single) (double vs. wt) vs. wt) vs. single) 10485013 BC085239 // 1110051M20Rik // RIKEN cDNA 1110051M20 gene // 2 E1 // 228356 /// NM 1110051M20Ri BC085239 0.164013 -1.38517 0.0345128 -2.24228 0.154535 -1.61877 k 10358717 NM_197990 // 1700025G04Rik // RIKEN cDNA 1700025G04 gene // 1 G2 // 69399 /// BC 1700025G04Rik NM_197990 0.142593 -1.37878 0.0212926 -3.13385 0.093068 -2.27291 10358713 NM_197990 // 1700025G04Rik // RIKEN cDNA 1700025G04 gene // 1 G2 // 69399 1700025G04Rik NM_197990 0.0655213 -1.71563 0.0222468 -2.32498 0.166843 -1.35517 10481312 NM_027283 // 1700026L06Rik // RIKEN cDNA 1700026L06 gene // 2 A3 // 69987 /// EN 1700026L06Rik NM_027283 0.0503754 -1.46385 0.0140999 -2.19537 0.0825609 -1.49972 10351465 BC150846 // 1700084C01Rik // RIKEN cDNA 1700084C01 gene // 1 H3 // 78465 /// NM_ 1700084C01Rik BC150846 0.107391 -1.5916 0.0385418 -2.05801 0.295457 -1.29305 10569654 AK007416 // 1810010D01Rik // RIKEN cDNA 1810010D01 gene // 7 F5 // 381935 /// XR 1810010D01Rik AK007416 0.145576 1.69432 0.0476957 2.51662 0.288571 1.48533 10508883 NM_001083916 // 1810019J16Rik // RIKEN cDNA 1810019J16 gene // 4 D2.3 // 69073 / 1810019J16Rik NM_001083916 0.0533206 1.57139 0.0145433 2.56417 0.0836674 1.63179 10585282 ENSMUST00000050829 // 2010007H06Rik // RIKEN cDNA 2010007H06 gene // --- // 6984 2010007H06Rik ENSMUST00000050829 0.129914 -1.71998 0.0434862 -2.51672 -
Impairments in Contractility and Cytoskeletal Organisation Cause Nuclear Defects in Nemaline Myopathy
bioRxiv preprint doi: https://doi.org/10.1101/518522; this version posted January 28, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Impairments in contractility and cytoskeletal organisation cause nuclear defects in nemaline myopathy Jacob A Ross1, Yotam Levy1, Michela Ripolone2, Justin S Kolb3, Mark Turmaine4, Mark Holt5, Maurizio Moggio2, Chiara Fiorillo6, Johan Lindqvist3, Nicolas Figeac5, Peter S Zammit5, Heinz Jungbluth5,7,8, John Vissing9, Nanna Witting9, Henk Granzier3, Edmar Zanoteli10, Edna C Hardeman11, Carina Wallgren- Pettersson12, Julien Ochala1,5. 1. Centre for Human & Applied Physiological Sciences, School of Basic & Medical Biosciences, Faculty of Life Sciences & Medicine, Guy’s Campus, King’s College London, SE1 1UL, UK 2. Neuromuscular and Rare Diseases Unit, Department of Neuroscience, Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico, Milan 20122, Italy 3. Department of Cellular and Molecular Medicine, University of Arizona, Tucson, Arizona, 85721, USA 4. Division of Biosciences, University College London, Gower Street, London WC1E 6BT, UK 5. Randall Centre for Cell and Molecular Biophysics, School of Basic & Medical Biosciences, Faculty of Life Sciences & Medicine, Guy’s Campus, King’s College London, SE1 1UL, UK 6. Molecular Medicine, IRCCS Fondazione Stella Maris, Pisa and Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genova, Genoa, Italy 7. Department of Paediatric Neurology, Neuromuscular Service, Evelina's Children Hospital, Guy's and St Thomas' Hospital National Health Service Foundation Trust, London, SE1 9RT, UK 8. Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology & Neuroscience, King's College, London, SE1 1UL, UK 9. -
Assembly and Maintenance of Sarcomere Thin Filaments and Associated Diseases
International Journal of Molecular Sciences Review Assembly and Maintenance of Sarcomere Thin Filaments and Associated Diseases Kendal Prill and John F. Dawson * Centre for Cardiovascular Investigations, Department of Molecular and Cellular Biology, University of Guelph, Guelph, ON N1G 2W1, Canada; [email protected] * Correspondence: [email protected] Received: 17 December 2019; Accepted: 12 January 2020; Published: 15 January 2020 Abstract: Sarcomere assembly and maintenance are essential physiological processes required for cardiac and skeletal muscle function and organism mobility. Over decades of research, components of the sarcomere and factors involved in the formation and maintenance of this contractile unit have been identified. Although we have a general understanding of sarcomere assembly and maintenance, much less is known about the development of the thin filaments and associated factors within the sarcomere. In the last decade, advancements in medical intervention and genome sequencing have uncovered patients with novel mutations in sarcomere thin filaments. Pairing this sequencing with reverse genetics and the ability to generate patient avatars in model organisms has begun to deepen our understanding of sarcomere thin filament development. In this review, we provide a summary of recent findings regarding sarcomere assembly, maintenance, and disease with respect to thin filaments, building on the previous knowledge in the field. We highlight debated and unknown areas within these processes to clearly define open research questions. Keywords: sarcomere assembly; sarcomere maintenance; sarcomere thin filaments; thin filament assembly; thin filament maintenance; thin filament turnover; actin turnover; chaperone; sarcomere; myopathy 1. Introduction Striated muscle requires the coordination of hundreds of proteins not only for cellular function but also for assembly of the contractile sarcomere units within the myofibril. -
Myosin Myth4-FERM Structures Highlight Important Principles of Convergent Evolution
Myosin MyTH4-FERM structures highlight important principles of convergent evolution Vicente José Planelles-Herreroa,b, Florian Blanca,c, Serena Sirigua, Helena Sirkiaa, Jeffrey Clausea, Yannick Souriguesa, Daniel O. Johnsrudd, Beatrice Amiguesa, Marco Cecchinic, Susan P. Gilberte, Anne Houdussea,1,2, and Margaret A. Titusd,1,2 aStructural Motility, Institut Curie, CNRS, UMR 144, PSL Research University, F-75005 Paris, France; bUPMC Université de Paris 6, Institut de Formation Doctorale, Sorbonne Universités, 75252 Paris Cedex 05, France; cLaboratoire d’Ingénierie des Fonctions Moléculaires, Institut de Science et d’Ingénierie Supramoléculaires, UMR 7006 CNRS, Université de Strasbourg, F-67083 Strasbourg Cedex, France; dDepartment of Genetics, Cell Biology and Development, University of Minnesota, Minneapolis, MN 55455; and eDepartment of Biological Sciences, Rensselaer Polytechnic Institute, Troy, NY 12180 Edited by James A. Spudich, Stanford University School of Medicine, Stanford, CA, and approved March 31, 2016 (received for review January 15, 2016) Myosins containing MyTH4-FERM (myosin tail homology 4-band (Fig. 1). These MF myosins are widespread and likely quite an- 4.1, ezrin, radixin, moesin, or MF) domains in their tails are found cient because they are found in many different branches of the in a wide range of phylogenetically divergent organisms, such as phylogenetic tree (5, 6), including Opisthokonts (which includes humans and the social amoeba Dictyostelium (Dd). Interestingly, Metazoa, unicellular Holozoa, and Fungi), Amoebozoa, and the evolutionarily distant MF myosins have similar roles in the exten- SAR (Stramenopiles, Alveolates, and Rhizaria) (Fig. 1 A and B). sion of actin-filled membrane protrusions such as filopodia and Over the course of hundreds of millions years of parallel evolution bind to microtubules (MT), suggesting that the core functions of the MF myosins have acquired or maintained roles in the formation these MF myosins have been highly conserved over evolution. -
Mass Spectrometry-Based Proteomics Techniques and Their Application in Ovarian Cancer Research Agata Swiatly, Szymon Plewa, Jan Matysiak and Zenon J
Swiatly et al. Journal of Ovarian Research (2018) 11:88 https://doi.org/10.1186/s13048-018-0460-6 REVIEW Open Access Mass spectrometry-based proteomics techniques and their application in ovarian cancer research Agata Swiatly, Szymon Plewa, Jan Matysiak and Zenon J. Kokot* Abstract Ovarian cancer has emerged as one of the leading cause of gynecological malignancies. So far, the measurement of CA125 and HE4 concentrations in blood and transvaginal ultrasound examination are essential ovarian cancer diagnostic methods. However, their sensitivity and specificity are still not sufficient to detect disease at the early stage. Moreover, applied treatment may appear to be ineffective due to drug-resistance. Because of a high mortality rate of ovarian cancer, there is a pressing need to develop innovative strategies leading to a full understanding of complicated molecular pathways related to cancerogenesis. Recent studies have shown the great potential of clinical proteomics in the characterization of many diseases, including ovarian cancer. Therefore, in this review, we summarized achievements of proteomics in ovarian cancer management. Since the development of mass spectrometry has caused a breakthrough in systems biology, we decided to focus on studies based on this technique. According to PubMed engine, in the years 2008–2010 the number of studies concerning OC proteomics was increasing, and since 2010 it has reached a plateau. Proteomics as a rapidly evolving branch of science may be essential in novel biomarkers discovery, therapy decisions, progression predication, monitoring of drug response or resistance. Despite the fact that proteomics has many to offer, we also discussed some limitations occur in ovarian cancer studies. -
Defining Functional Interactions During Biogenesis of Epithelial Junctions
ARTICLE Received 11 Dec 2015 | Accepted 13 Oct 2016 | Published 6 Dec 2016 | Updated 5 Jan 2017 DOI: 10.1038/ncomms13542 OPEN Defining functional interactions during biogenesis of epithelial junctions J.C. Erasmus1,*, S. Bruche1,*,w, L. Pizarro1,2,*, N. Maimari1,3,*, T. Poggioli1,w, C. Tomlinson4,J.Lees5, I. Zalivina1,w, A. Wheeler1,w, A. Alberts6, A. Russo2 & V.M.M. Braga1 In spite of extensive recent progress, a comprehensive understanding of how actin cytoskeleton remodelling supports stable junctions remains to be established. Here we design a platform that integrates actin functions with optimized phenotypic clustering and identify new cytoskeletal proteins, their functional hierarchy and pathways that modulate E-cadherin adhesion. Depletion of EEF1A, an actin bundling protein, increases E-cadherin levels at junctions without a corresponding reinforcement of cell–cell contacts. This unexpected result reflects a more dynamic and mobile junctional actin in EEF1A-depleted cells. A partner for EEF1A in cadherin contact maintenance is the formin DIAPH2, which interacts with EEF1A. In contrast, depletion of either the endocytic regulator TRIP10 or the Rho GTPase activator VAV2 reduces E-cadherin levels at junctions. TRIP10 binds to and requires VAV2 function for its junctional localization. Overall, we present new conceptual insights on junction stabilization, which integrate known and novel pathways with impact for epithelial morphogenesis, homeostasis and diseases. 1 National Heart and Lung Institute, Faculty of Medicine, Imperial College London, London SW7 2AZ, UK. 2 Computing Department, Imperial College London, London SW7 2AZ, UK. 3 Bioengineering Department, Faculty of Engineering, Imperial College London, London SW7 2AZ, UK. 4 Department of Surgery & Cancer, Faculty of Medicine, Imperial College London, London SW7 2AZ, UK. -
Circmyo10 Promotes Osteosarcoma Progression by Regulating Mir-370
Chen et al. Molecular Cancer (2019) 18:150 https://doi.org/10.1186/s12943-019-1076-1 RESEARCH Open Access CircMYO10 promotes osteosarcoma progression by regulating miR-370-3p/ RUVBL1 axis to enhance the transcriptional activity of β-catenin/LEF1 complex via effects on chromatin remodeling Junxin Chen1†, Gang Liu1†, Yizheng Wu1†, Jianjun Ma1†, Hongfei Wu2, Ziang Xie1, Shuai Chen1, Yute Yang1, Shengyu Wang1, Panyang Shen1, Yifan Fang3, Shunwu Fan1, Shuying Shen1* and Xiangqian Fang1* Abstract Background: CircMYO10 is a circular RNA generated by back-splicing of gene MYO10 and is upregulated in osteosarcoma cell lines, but its functional role in osteosarcoma is still unknown. This study aimed to clarify the mechanism of circMYO10 in osteosarcoma. Methods: CircMYO10 expression in 10 paired osteosarcoma and chondroma tissues was assessed by quantitative reverse transcription polymerase chain reaction (PCR). The function of circMYO10/miR-370-3p/RUVBL1 axis was assessed regarding two key characteristics: proliferation and endothelial–mesenchymal transition (EMT). Bioinformatics analysis, western blotting, real-time PCR, fluorescence in situ hybridization, immunoprecipitation, RNA pull-down assays, luciferase reporter assays, chromatin immunoprecipitation, and rescue experiments were used to evaluate the mechanism. Stably transfected MG63 cells were injected via tail vein or subcutaneously into nude mice to assess the role of circMYO10 in vivo. Results: CircMYO10 was significantly upregulated, while miR-370-3p was downregulated, in osteosarcoma cell lines and human osteosarcoma samples. Silencing circMYO10 inhibited cell proliferation and EMT in vivo and in vitro. Mechanistic investigations revealed that miR-370-3p targets RUVBL1 directly, and inhibits the interaction between RUVBL1 and β-catenin/LEF1 complex while circMYO10 showed a contrary effect via the inhibition of miR-370-3p. -
A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus
Page 1 of 781 Diabetes A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus Robert N. Bone1,6,7, Olufunmilola Oyebamiji2, Sayali Talware2, Sharmila Selvaraj2, Preethi Krishnan3,6, Farooq Syed1,6,7, Huanmei Wu2, Carmella Evans-Molina 1,3,4,5,6,7,8* Departments of 1Pediatrics, 3Medicine, 4Anatomy, Cell Biology & Physiology, 5Biochemistry & Molecular Biology, the 6Center for Diabetes & Metabolic Diseases, and the 7Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; 2Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202; 8Roudebush VA Medical Center, Indianapolis, IN 46202. *Corresponding Author(s): Carmella Evans-Molina, MD, PhD ([email protected]) Indiana University School of Medicine, 635 Barnhill Drive, MS 2031A, Indianapolis, IN 46202, Telephone: (317) 274-4145, Fax (317) 274-4107 Running Title: Golgi Stress Response in Diabetes Word Count: 4358 Number of Figures: 6 Keywords: Golgi apparatus stress, Islets, β cell, Type 1 diabetes, Type 2 diabetes 1 Diabetes Publish Ahead of Print, published online August 20, 2020 Diabetes Page 2 of 781 ABSTRACT The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray datasets generated using human islets from donors with diabetes and islets where type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated. -
Tropomodulin Isoform-Specific Regulation of Dendrite Development and Synapse Formation
This Accepted Manuscript has not been copyedited and formatted. The final version may differ from this version. Research Articles: Cellular/Molecular Tropomodulin Isoform-Specific Regulation of Dendrite Development and Synapse Formation Omotola F. Omotade1,3, Yanfang Rui1,3, Wenliang Lei1,3, Kuai Yu1, H. Criss Hartzell1, Velia M. Fowler4 and James Q. Zheng1,2,3 1Department of Cell Biology, Emory University School of Medicine, Atlanta, GA 30322. 2Department of Neurology 3Center for Neurodegenerative Diseases, Emory University School of Medicine, Atlanta, GA 30322. 4Department of Molecular Medicine, Scripps Research Institute, La Jolla, CA 92037 DOI: 10.1523/JNEUROSCI.3325-17.2018 Received: 22 November 2017 Revised: 25 September 2018 Accepted: 2 October 2018 Published: 9 October 2018 Author contributions: O.F.O. and J.Q.Z. designed research; O.F.O., Y.R., W.L., and K.Y. performed research; O.F.O. and J.Q.Z. analyzed data; O.F.O. and J.Q.Z. wrote the paper; Y.R., H.C.H., V.M.F., and J.Q.Z. edited the paper; V.M.F. contributed unpublished reagents/analytic tools. Conflict of Interest: The authors declare no competing financial interests. This research project was supported in part by research grants from National Institutes of Health to JQZ (GM083889, MH104632, and MH108025), OFO (5F31NS092437-03), VMF (EY017724) and HCH (EY014852, AR067786), as well as by the Emory University Integrated Cellular Imaging Microscopy Core of the Emory Neuroscience NINDS Core Facilities grant (5P30NS055077). We would like to thank Dr. Kenneth Myers for his technical expertise and help throughout the project. We also thank Drs. -
4-6 Weeks Old Female C57BL/6 Mice Obtained from Jackson Labs Were Used for Cell Isolation
Methods Mice: 4-6 weeks old female C57BL/6 mice obtained from Jackson labs were used for cell isolation. Female Foxp3-IRES-GFP reporter mice (1), backcrossed to B6/C57 background for 10 generations, were used for the isolation of naïve CD4 and naïve CD8 cells for the RNAseq experiments. The mice were housed in pathogen-free animal facility in the La Jolla Institute for Allergy and Immunology and were used according to protocols approved by the Institutional Animal Care and use Committee. Preparation of cells: Subsets of thymocytes were isolated by cell sorting as previously described (2), after cell surface staining using CD4 (GK1.5), CD8 (53-6.7), CD3ε (145- 2C11), CD24 (M1/69) (all from Biolegend). DP cells: CD4+CD8 int/hi; CD4 SP cells: CD4CD3 hi, CD24 int/lo; CD8 SP cells: CD8 int/hi CD4 CD3 hi, CD24 int/lo (Fig S2). Peripheral subsets were isolated after pooling spleen and lymph nodes. T cells were enriched by negative isolation using Dynabeads (Dynabeads untouched mouse T cells, 11413D, Invitrogen). After surface staining for CD4 (GK1.5), CD8 (53-6.7), CD62L (MEL-14), CD25 (PC61) and CD44 (IM7), naïve CD4+CD62L hiCD25-CD44lo and naïve CD8+CD62L hiCD25-CD44lo were obtained by sorting (BD FACS Aria). Additionally, for the RNAseq experiments, CD4 and CD8 naïve cells were isolated by sorting T cells from the Foxp3- IRES-GFP mice: CD4+CD62LhiCD25–CD44lo GFP(FOXP3)– and CD8+CD62LhiCD25– CD44lo GFP(FOXP3)– (antibodies were from Biolegend). In some cases, naïve CD4 cells were cultured in vitro under Th1 or Th2 polarizing conditions (3, 4). -
Identification of the Key Micrornas and Mirna- Mrna Interaction Networks During the Ovarian Development of Hens
Article Identification of the Key microRNAs and miRNA- mRNA Interaction Networks During the Ovarian Development of Hens Jing Li †, Chong Li †, Qi Li, Wen-Ting Li, Hong Li, Guo-Xi Li, Xiang-Tao Kang, Xiao-Jun Liu and Ya-Dong Tian * College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, China; [email protected] (J.L.); [email protected] (C.L.); [email protected] (Q.L.); [email protected] (W.-T.L.); [email protected] (H.L.); [email protected] (G.-X.L.); [email protected] (X.-T.K.); [email protected] (X.-J.L.) * Correspondence: [email protected] † These two authors contributed equally to this work. Received: 27 July 2020; Accepted: 15 September 2020; Published: date Supplementary Material Animals 2020, 10, x; doi: www.mdpi.com/journal/animals Animals 2020, 10, x 2 of 24 Table 1. The list of the interaction network, the expression levels and Pearson’s correlation coefficient of DE miRNAs and DE mRNAs. Expression Level ( TPM) Expression Level ( FPKM) sRNA Transcript Id Gene Id Gene Name Correlatio 15W 20W 30W 68W 15W 20W 30W 68W gga-miR-1560-3p 3.253 6.030 4.295 2.565 ENSGALT00000087050 ENSGALG00000005902 RAB7A 17.832 0.031 6.674 0.077 -0.324 gga-miR-143-3p 25118.987 49390.256 87681.664 32277.275 ENSGALT00000069072 ENSGALG00000041760 CLTCL1 2.189 0.000 1.321 1.252 -0.268 gga-miR-7472-5p 0.054 0.264 0.466 0.000 ENSGALT00000066785 ENSGALG00000014582 CADM1 6.810 2.342 0.000 0.000 -0.394 gga-miR-7472-5p 0.054 0.264 0.466 0.000 ENSGALT00000033172 ENSGALG00000008121 CYP17A1 722.987 -
Supplemental Tables4.Pdf
Yano_Supplemental_Table_S4 Gene ontology – Biological process 1 of 9 Fold List Pop Pop GO Term Count % PValue Bonferroni Benjamini FDR Genes Total Hits Total Enrichment DLC1, CADM1, NELL2, CLSTN1, PCDHGA8, CTNNB1, NRCAM, APP, CNTNAP2, FERT2, RAPGEF1, PTPRM, MPDZ, SDK1, PCDH9, PTPRS, VEZT, NRXN1, MYH9, GO:0007155~cell CTNNA2, NCAM1, NCAM2, DDR1, LSAMP, CNTN1, 50 5.61 2.14E-08 510 311 7436 2.34 4.50E-05 4.50E-05 3.70E-05 adhesion ROR2, VCAN, DST, LIMS1, TNC, ASTN1, CTNND2, CTNND1, CDH2, NEO1, CDH4, CD24A, FAT3, PVRL3, TRO, TTYH1, MLLT4, LPP, NLGN1, PCDH19, LAMA1, ITGA9, CDH13, CDON, PSPC1 DLC1, CADM1, NELL2, CLSTN1, PCDHGA8, CTNNB1, NRCAM, APP, CNTNAP2, FERT2, RAPGEF1, PTPRM, MPDZ, SDK1, PCDH9, PTPRS, VEZT, NRXN1, MYH9, GO:0022610~biological CTNNA2, NCAM1, NCAM2, DDR1, LSAMP, CNTN1, 50 5.61 2.14E-08 510 311 7436 2.34 4.50E-05 4.50E-05 3.70E-05 adhesion ROR2, VCAN, DST, LIMS1, TNC, ASTN1, CTNND2, CTNND1, CDH2, NEO1, CDH4, CD24A, FAT3, PVRL3, TRO, TTYH1, MLLT4, LPP, NLGN1, PCDH19, LAMA1, ITGA9, CDH13, CDON, PSPC1 DCC, ENAH, PLXNA2, CAPZA2, ATP5B, ASTN1, PAX6, ZEB2, CDH2, CDH4, GLI3, CD24A, EPHB1, NRCAM, GO:0006928~cell CTTNBP2, EDNRB, APP, PTK2, ETV1, CLASP2, STRBP, 36 4.04 3.46E-07 510 205 7436 2.56 7.28E-04 3.64E-04 5.98E-04 motion NRG1, DCLK1, PLAT, SGPL1, TGFBR1, EVL, MYH9, YWHAE, NCKAP1, CTNNA2, SEMA6A, EPHA4, NDEL1, FYN, LRP6 PLXNA2, ADCY5, PAX6, GLI3, CTNNB1, LPHN2, EDNRB, LPHN3, APP, CSNK2A1, GPR45, NRG1, RAPGEF1, WWOX, SGPL1, TLE4, SPEN, NCAM1, DDR1, GRB10, GRM3, GNAQ, HIPK1, GNB1, HIPK2, PYGO1, GO:0007166~cell RNF138, ROR2, CNTN1,