Overview Gene List Target Scan Vs DIANA Group a Group B Group A

Total Page:16

File Type:pdf, Size:1020Kb

Overview Gene List Target Scan Vs DIANA Group a Group B Group A Overview Gene list Target scan vs DIANA Group A Group B Group A hsa-miR-181a hsa-miR-323 hsa-miR-326 Target scan Diana microT Overlap Target scan Diana microT Overlap Target scan SEPT3 SEPT3 SEPT3 SEPT7 ADARB1 HPCAL4 ABHD2 ABL2 ABHD13 ACVR2A ADCYAP1R1 AKAP13 PDPK1 ACRBP ACAN ABI1 ADAMTS1 ALAD APOBR ACVRL1 ACCN2 ABLIM1 ADAMTSL1 ANKRD52 ATXN1 ADAM19 ACER3 ACSL1 AKAP7 ARID2 C18orf23,RNF165 ADAM33 ACVR2A ACTN2 ANKRD43 ARL3 C20orf29 ADAMTS2 ADAMTS1 ACVR2A AP1S3 ARRB1 CACNG4 AHCYL2 ADAMTS18 ACVR2B ARID2 BBC3 CCNJL ALOX15B ADAMTS5 ADAM11 ATP11A BTG1 CYP2E1 ANK1 ADAMTSL1 ADAM22 ATXN1 C18orf62 GNB1L ANKS6 ADARB1 ADAMTS1 B4GALT1 C1orf21 GPR61 APBA1 AFAP1 ADAMTS6 BAG4 CADM4 GTSE1 ARCN1 AFTPH ADAMTSL1 BAI3 CALML4 HPCAL4 ARHGEF37 AK3 ADCY9 BNC2 CAPN6 KIAA0152 ARID3B AKAP7 ADRBK1 BRD1 CBFA2T2 KIF1A ARL8A ANAPC16 AFF2 BRWD1 CEBPA MACF1 ATP2B2 ANK1 AHCTF1,AHCTF1PBTBD3 CHD1 MYO1D ATP6V1G2 ANKRD12 AKAP2,PALM2 C13orf23 CIT PCNT AUP1 ANKRD33B AKAP6 C14orf43 CLASP2 PDPK1 BCL2L2 ANKRD43 AKAP7 CAPRIN1 CLCN5 PLEKHG4B BHLHE40 ANKRD44 AKAP9 CARM1 CLIP3 PPARA BTBD3 ANKRD52 AKT3 CBX4 COL5A2 PRB1,PRB2,PRB4 BTRC AP1S3 ALG9 CCDC117 CTNS PTPRT C10orf26 APBA1 ANKRD13C CCNJ DCTN4 PYCR1 C14orf1 APLP2 ANKRD20B CDH13 DCUN1D4 RAPGEF1 C16orf45 APOO ANKRD43 CDON DDB1 SRCAP C16orf54 ARID2 ANKRD50 CDYL DDX39B TMEM63C C1orf106 ARL3 AP1G1 CEP350 DIP2C C1orf27 ARRDC3 AP1S3 CHD7 DNAJB3 C22orf29 ATF7 API5 CHIC1 EEPD1 C9orf3 ATG2B ARFGEF2 CLIP1 EIF2C1 CACNA1E ATG7 ARHGAP12 CNOT6L ELFN2 CAPN12 ATP11A ARHGAP26 CNR1 ELK1 CASKIN1 ATP2B3 ARHGAP29 CNTN4 FAM172A CBFA2T3 ATP8B2 ARHGEF3 CNTNAP2 FBXW2 CBLL1 ATXN1 ARID2 CREBL2 FOXP4 CBX6 ATXN7 ARL5A CRIM1 FRMPD4 CD247 B4GALT1 ARL5B CTDSPL GABARAP CD34 BAG4 ARL6IP2 CTTNBP2NL GALNT10 CDC20B BAI3 ARNT2 CUL3 GANAB CDH22 BCL2 ARSJ DDX3X GAPDH CDK12 BCL9 ASAH2B DDX3Y GDE1 CDX1 BCR ASTN1 DERL1 GNAI3 CEBPA BHLHE40 ATF2 DIP2B GNAL CHL1 BMF ATG5 DLGAP2 GOT1 CHRDL1 BNC2 ATM DMXL2 GPM6B CLCN4 BRD1 ATP11A DOCK7 GPR173 CLCN6 BRWD1 ATP11C EIF4A2 GRIK2 CLDN8 BTBD3 ATP1B1 ELAVL4 HNRNPA2B1 CLMN C10orf46 ATP2B1 EN1 HPCAL4 CLU C11orf30 ATP2B2 EN2 HPN COPS7B C11orf75 ATP6V1C2 ENAH IGLON5 CORO2B C12orf68 ATP8A1 ENOX2 ILDR2 CPLX2 C13orf23 ATP8A2 EPB41 INSM2 CRHR1 C13orf30 ATRN EPB41L3 IPPK CRTAP C14orf43 ATRNL1 EPC2 JOSD1 CRY2 C17orf63 ATXN1 ESR1 KLF12 CSNK1G1 C1GALT1 ATXN3 ETS1 KLF6 CSNK2A1 C3orf43 B3GNT5 FAM105B KLHDC10 CSRNP1 C3orf62 B4GALT1 FAM135A KLHL24 CUEDC2 C6orf192 B4GALT6 FBXO33 KPNA3 DAGLA C6orf35 BACH2 FOXK1 KPNA6 DDI2 CACNA2D2 BAG4 G3BP2 KSR2 DDT CALR BAI3 GABRA1 LOXL3 DFNB31 CAMSAP1L1 BAT2D1 GABRA4 LRRTM4 DIEXF CAMTA2 BAZ2B GPD2 LTBP2 DLGAP2 CAPRIN1 BCL11A GRB10 LYRM4 DRD2 CARM1 BIRC4 GRIK2 MAP3K3 DTNB CASP10 BIRC6 HAND2 MARK2 DTX4 CBFA2T3 BMPR2 HIC2 MDGA2 DYRK2 CBLB BNC2 HMBS MECR E2F2 CBLL1 BPTF HOXA11 MED19 ECM1 CBX4 BRD1 HOXC8 MED26 EFNB1 CBX5 BRWD1 HS2ST1 MIER3 EGR3 CCDC117 BTBD14A KCNA1 MMP16 EGR4 CCDC141 BTBD3 KCNH8 MRPL42 ELFN1 CCDC17 BTRC KCTD10 MTDH ELFN2 CCDC6 C10orf131 KIAA0247 MTUS2 ELK1 CCDC64 C10orf22 KIAA1244 MXD4 ELMO2 CCDC90A C10orf38 KIAA1715 MYBL1 ELOF1 CCL8 C10orf79 KIAA2022 MYH10 EML2 CCNG1 C11orf56 KITLG MYLK2 EMX1 CCNJ C12orf5 KLHDC5 NEK8 EPB41L1 CCNK C13orf23 KLHL29 NFASC ERBB4 CCNT2 C14orf129 KLHL5 NNAT ERC1 CD4 C14orf32 LARP4 NOS2 FAM126B CD69 C14orf43 LBR NPTX1 FAM155B CDC27 C15orf2 LCORL NRK FAM164A CDC73 C15orf29 LIN7C OLFM3 FAM167B CDH13 C16orf75 LMO1 PAQR3 FAM53C CDK8 C17orf39 LMO3 PARP8 FANCE CDKL2 C1orf161 LPP PCBP2 FBRS CDON C1orf27 LRRK2 PDPK1 FBXL16 CDYL C20orf121 MAMDC2 PKD2 FBXL20 CEBPA C21orf25 MAP2K1 PLXNB2 FBXO21 CELSR3 C21orf66 MARK1 PPAPDC2 FBXO41 CEP350 C21orf91 MBNL2 PPP2R5D FGD3 CHD1 C3orf59 MEF2A PSD2 FGF9 CHD7 C4orf15 METAP1 PSEN1 FGFR1 CHD9 C5orf13 MEX3B PSMF1 FNDC3A CHIC1 C5orf30 MFAP3L QSER1 FSCN1 CHMP1B C5orf5 MINK1 RBBP4 FUCA1 CLCC1 C6orf89 MTF1 RBFOX2 FZD5 CLIP1 CABC1 MTMR12 RDX GAB1 CLMN CALB1 MTMR9 REEP3 GABBR2 CLVS1 CALCR MTPN RHBDF1 GADL1 CNKSR2 CAMK2G MYH10 SDK2 GDF11 CNKSR3 CAND1 NAALADL2 SEC24A GLIS2 CNOT6L CAP1 NEGR1 SENP1 GOLGA7B CNR1 CAPRIN1 NFAT5 SLAMF1 GPCPD1 CNTN4 CARM1 NFIB SLC25A1 GPRC5B CNTNAP2 CASC5 NLK SLC4A5 GRIPAP1 COL5A1 CBX4 NLN SLC6A1 GRPEL2 COMMD6 CBX6,NPTXR NOL4 SP3 HAVCR2 COPS2 CBX7 NOTCH2 SPEG HDAC8 CPD CCAR1 NPTN SPOP HEYL CPT1A CCDC117 NR1D2 SPRY4 HNRNPA1 CREBL2 CCDC126 NR2C2 SRRM4 HNRNPA2B1 CRIM1 CCDC14 NR3C1 SRSF5 HNRNPUL2 CRISPLD1 CCDC4 NR6A1 SSPN HTR2C CSNK1G3 CCNJ ONECUT2 ST13 HTR7 CSRNP3 CCNL2 OTUD4 STIM1 IGF2BP1 CTDSPL CD302 PAG1 SYNPO2L INADL CTIF CDH13 PAK7 TAPT1 INO80D CTTNBP2NL CDON PAN3 TBC1D8B ITPK1 CUL3 CDYL PAPD5 TLE4 JAKMIP3 CUL4A CEBPG PARK2 TMED10 KCMF1 CXADR CENTB2 PAWR TMEM40 KCNH1 CYLD Cep110 PBX3 TOMM6 KCNIP2 DCP1A CEP350 PCGF2 TP53I11 KIAA0513 DCP2 CERKL PDAP1 TRPS1 KLF1 DDIT4 CETN3 PDPK1 TULP4 KLF3 DDX3X CGGBP1 PDXDC1 UBE2K KLHL6 DDX3Y CHD7 PHACTR2 UBTF KSR2 DEPTOR CHIC1 PI4K2A ULK3 LARP1 DERL1 CHMP2B PJA2 USP14 LIN7C DGCR2 CKAP5 PLEKHA3 UVRAG LMX1B DIP2A CLASP1 PODXL VPS39 LOC388630 DIP2B CLCN5 POU2F1 XKR6 LPHN1 DIP2C CLIP1 PPP1CB ZFP91 LPIN2 DLG2 CLOCK PPP1R2 ZMIZ1 LRRC20 DLGAP2 CNOT1 PPP2R5E ZNF609 LZTR1 DMXL2 CNOT6L PRICKLE2 ZNF740 MAP1A DNAJA4 CNR1 PRKCD ZXDC MAVS DNAL1 CNTN4 PTPN9 ZYX MMAA DOCK7 CNTNAP2 PTPRE MTMR9 DTNA CNTNAP3 RAD23B NHLRC1 DUSP5 CNTNAP3B RAP1B NKAIN1 DYRK2 COL16A1 RBM47 NKX2-8 EDAR COL19A1 RCOR1 NRAS EGR2 COLQ RNF169 NRGN EGR3 CPEB4 RNF34 NTN1 EIF4A2 CPNE2 ROD1 NXF1 ELAVL4 CPOX RPS6KA3 OXSR1 EML1 CREB1 RPS6KB1 P2RY2 EN1 CREB5 RRP15 PABPC1L2A EN2 CREBL2 RSPO2 PABPC1L2B ENAH CRIM1 SCD PARP11 ENOX2 CSNK1G1 SCHIP1 PARVA EPB41 CTDSPL SEL1L PCDH1 EPB41L3 CTTNBP2NL SEMA3C PDK2 EPB41L4B CUGBP2 SERTAD2 PFKFB4 EPB49 CUL3 SH3GLB1 PHF21A EPC2 CUL5 SHE PHOX2A EPHA5 CYP26B1 SIN3B PKIA ERG CYR61 SIX2 PLEC ERMN DCLK1 SLAIN2 POLR2F ESR1 DCN SLC19A2 PPARGC1B ETNK1 DCUN1D1 SLC25A25 PPME1 ETS1 DDX3X SLC25A37 PPP2R5B EVI2A DDX3Y SLC35F1 PPP4R1 EYA3 DDX52 SLC38A2 PRAF2 FAM105B DENND1A SLC9A8 PRICKLE2 FAM122B DEPDC6 SLITRK1 PRR18 FAM135A DERL1 SMAD2 PRSS23 FAM160A2 DGKH SS18L1 PSKH1 FAM171A1 DIP2B ST8SIA4 PTPN14 FAM179B DLGAP1 TARDBP PURB FAM19A2 DLGAP2 TBC1D1 RAB5B FAM49A DMRT3 TBC1D4 RALGPS2 FBXO33 DMXL2 TBL1X RAP2A FBXO45 DNAJB1 TCERG1 RASL10B FGD4 DNAJC13 TLL1 RASSF1 FGFR3 DNAJC21 TMEM64 RBBP4 FIGNL2 DOCK10 TNFAIP1 RBFOX2 FLT1 DOCK4 TNFRSF11B RGL3 FNBP4 DOCK7 TNPO1 RHOBTB2 FOXK1 DPY19L2 TNRC6B RIT1 FRYL DPY19L2P1 TOM1L1 RNF182 FUZ DR1 TSC22D2 RNF185 G3BP2 DYNC1LI2 UBE2B SAC3D1 GABRA1 E2F7 USP9X SCN2B GABRA4 EDG1 VANGL1 SCNM1 GATC EFHA2 WDFY3 SDC3 GCC2 EIF4A2 WHSC1 SDK2 GIGYF1 EIF4G3 YOD1 SEMA3G GLI2 ELAVL2 YTHDC1 SESN2 GNAO1 ELAVL4 YTHDF2 SEZ6 GPD2 ELOVL6 YTHDF3 SH2B3 GPR26 EN1 ZADH2 SH3BGR GRB10 EN2 ZBTB33 SH3BP4 GRIA2 ENAH ZBTB4 SH3PXD2A GRID1 ENDOD1 ZCCHC14 SH3TC2 GRIK2 ENOX2 ZNF236 SLC27A4 GRIK3 ENTPD6 ZNF563 SLC2A1 GRM1 EPB41 ZNF654 SLC35A4 GXYLT1 EPB41L3 SLC4A3 H3F3B EPC2 SLC5A9 HAND2 EPHA4 SLC7A14 HAPLN1 EPHB1 SLCO3A1 HAUS3 EPS8 SMCR7L HCN1 ERLIN2 SNCB HECW2 ESR1 SNX30 HEMGN ETF1 SOX12 HEXIM1 ETS1 SPATS2L HIC2 EXDL1 SPRY3 HIPK2 EXOC2 SPRYD3 HLF F5 SRPR HMBS FAM102A ST3GAL3 HOXA11 FAM105B STK11 HOXB8 FAM123A STK35 HOXC8 FAM126B STMN3 HS2ST1 FAM135A STX1B HS6ST3 FAM46C SYNGAP1 HSP90B1 FBN2 SYNPO2L HSPC159 FBXL3 TANC2 HTT FBXO11 TCHP HYOU1 FBXO33 TLE3 IGDCC3 FBXO34 TMEM63C IGF2BP3 FCMD TNC ILF3 FIGN TNFAIP8L2-SCNM1 IPMK FKBP1A TOMM40L IPO5 FKBP1C TRAF3 IQCJ-SCHIP1 FMNL2 TREML2 ITGA3 FNDC3A TSPAN14 ITGA6 FNDC3B TSPAN18 KALRN FOS TYSND1 KANK1 FOXK1 UBE2G1 KBTBD7 FOXP1 UROC1 KCMF1 FOXP2 UVRAG KCNA1 FRMD8 VAMP2 KCNH8 FSD1L VPS39 KCNJ10 G3BP1 WSCD1 KCNN3 G3BP2 XYLT1 KCTD10 GABRA1 YBX2 KDM5A GABRA4 ZBTB12 KHSRP GABRG1 ZBTB44 KIAA0226 GALNT3 ZDHHC3 KIAA0247 GAPVD1 ZDHHC9 KIAA0664 GATM ZMIZ1 KIAA1244 GDA ZNF3 KIAA1324L GHITM ZNF609 KIAA1462 GK5 ZNF629 KIAA1467 GLS ZNF704 KIAA1549 GNA12 ZSCAN22 KIAA1715 GOLGA8A ZSWIM5 KIAA2022 GOLGA8B KIF1C GOLGA8E,GOLGA8F KITLG GOLGA8G KLF15 GOT2 KLF3 GPBP1 KLHDC5 GPCPD1 KLHL15 GPD1L KLHL2 GPD2 KLHL29 GPR3 KLHL5 GPSM1 KREMEN1 GRB10 L1CAM GREM1 LAMC1 GRIK2 LARP4 GRIN2A LBR GRK7 LCOR HAND2 LCORL HECA LGI2 HEPHL1 LHFPL3 HEY2 LIMCH1 HFM1 LIMS1 HIC2 LIN7C HISPPD1 LMBRD2 HMBS LMO1 HMGB2 LMO3 HOOK1 LMX1A HOXA11 LNX2 HOXB5 LOC100507421 HOXC8 LPCAT1 HOXD1 LPGAT1 HPGAP1 LPP HRB LPPR4 HS2ST1 LRBA HS3ST3A1 LRP12 HSPA1L LRP6 HTR2C LRRC32 ID4 LRRK2 IL18R1 LTN1 IL1A LUZP1 IL1RAP LYPLA2 IL2 MADD INOC1 MAEA IPO8 MAMDC2 IPPK MAP1A IRS2 MAP2K1 ITGB1 MAP3K10 ITGB8 MAP3K3 IYD MAP3K9 JARID1A MAP4K4 JARID2 MAPK1IP1L JAZF1 MARCKS KCNA1 MARK1 KCND3 MBD2 KCNH8 MBNL1 KCNMA1 MBNL2 KCNMB2 MCART6 KCNQ5 MCC KCTD10 MCL1 KIAA0182 MECP2 KIAA0195 MEF2A KIAA0247 METAP1 KIAA0286 MEX3A KIAA0408 MEX3B KIAA0423 MFAP3L KIAA0528 MGA KIAA0802 MINK1 KIAA1024 MIP KIAA1128 MKNK2 KIAA1199 MKRN1 KIAA1219 MMP14 KIAA1239 MNX1 KIAA1244 MOBKL2B KIAA1546 MOSPD1 KIAA1553 MSL2 KIAA1715 MTF1 KIAA2022 MTF2 KIF3A MTMR10 KIF3B MTMR12 KITLG MTMR9 KLHDC5 MTPN KLHL29 MYBL1 KLHL5 MYCBP KPNA1 MYCBP2 KPNA4 MYH10 KPNB1 MYNN KRAS MYO1E LARP4 NAA50 LBR NAALADL2 LCORL NAB1 LGALSL NACC2 LHX6 NAP1L5 LIFR NBEA LIN28B NCOA2 LIN7C NDRG2 LMAN1 NEGR1 LMO1 NEO1 LMO3 NFAT5 LONRF2 NFIB LPP NKX3-2 LRRC8D NLK LRRIQ2 NLN LRRK2 NMNAT2 LRRN1 NOL4 MAB21L2 NOTCH2 MAF NPTN MAMDC2 NR1D2 MAP1B NR2C2 MAP2K1 NR3C1 MAP3K8 NR6A1 MAPK1 NRP1 MARK1 NRXN1 MBNL2 NUDT12 MBOAT2 NUFIP2 MEF2A ONECUT2 MEGF10 OTUD4 MEGF9 PAFAH1B1 METAP1 PAFAH1B2 METAP2 PAG1 MEX3B PAK7 MEX3C PAN3 MFAP3L PANK3 MIER3 PAPD5 MINA PAPOLG MINK1 PARK2 MKLN1 PAWR MLF1 PBMUCL1 MLL PBX1 MLL5 PBX3 MLLT10 PCGF2 MOXD1 PDAP1 MPP5 PDE10A MPP7 PDPK1 MPZL3 PDXDC1 MSL2L1 PEAK1 MTF1 PGR MTMR12 PHACTR2 MTMR6 PHC3 MTMR9 PHF2 MTPN PHIP MUC7 PHKA1 MYH10 PHLDA1 NAALADL2 PHLPP2 NAPB PHTF2 NCALD PI4K2A NEBL PIP4K2B NEGR1 PJA2 NEK7 PKDCC NFAT5 PLAU NFATC2 PLCXD3 NFIB PLEKHA3 NIPAL4 PNRC2 NIPBL PODXL NLK POU2F1 NLN PPAP2B NMT2 PPARA NOL4 PPIP5K2
Recommended publications
  • Title a New Centrosomal Protein Regulates Neurogenesis By
    Title A new centrosomal protein regulates neurogenesis by microtubule organization Authors: Germán Camargo Ortega1-3†, Sven Falk1,2†, Pia A. Johansson1,2†, Elise Peyre4, Sanjeeb Kumar Sahu5, Loïc Broic4, Camino De Juan Romero6, Kalina Draganova1,2, Stanislav Vinopal7, Kaviya Chinnappa1‡, Anna Gavranovic1, Tugay Karakaya1, Juliane Merl-Pham8, Arie Geerlof9, Regina Feederle10,11, Wei Shao12,13, Song-Hai Shi12,13, Stefanie M. Hauck8, Frank Bradke7, Victor Borrell6, Vijay K. Tiwari§, Wieland B. Huttner14, Michaela Wilsch- Bräuninger14, Laurent Nguyen4 and Magdalena Götz1,2,11* Affiliations: 1. Institute of Stem Cell Research, Helmholtz Center Munich, German Research Center for Environmental Health, Munich, Germany. 2. Physiological Genomics, Biomedical Center, Ludwig-Maximilian University Munich, Germany. 3. Graduate School of Systemic Neurosciences, Biocenter, Ludwig-Maximilian University Munich, Germany. 4. GIGA-Neurosciences, Molecular regulation of neurogenesis, University of Liège, Belgium 5. Institute of Molecular Biology (IMB), Mainz, Germany. 6. Instituto de Neurociencias, Consejo Superior de Investigaciones Científicas and Universidad Miguel Hernández, Sant Joan d’Alacant, Spain. 7. Laboratory for Axon Growth and Regeneration, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany. 8. Research Unit Protein Science, Helmholtz Centre Munich, German Research Center for Environmental Health, Munich, Germany. 9. Protein Expression and Purification Facility, Institute of Structural Biology, Helmholtz Center Munich, German Research Center for Environmental Health, Munich, Germany. 10. Institute for Diabetes and Obesity, Monoclonal Antibody Core Facility, Helmholtz Center Munich, German Research Center for Environmental Health, Munich, Germany. 11. SYNERGY, Excellence Cluster of Systems Neurology, Biomedical Center, Ludwig- Maximilian University Munich, Germany. 12. Developmental Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, USA 13.
    [Show full text]
  • Bioinformatics Identi Cation of Prognostic Factors Associated With
    Bioinformatics Identication of Prognostic Factors Associated with Breast Cancer Ying Wei Sichuan University https://orcid.org/0000-0001-8178-4705 Shipeng Zhang College of Pharmacy, North Sichuan Medical College Li Xiao West China School of Basic Medical Sciences and Forensic Medicine Jing Zou West China School of Basic Medical Sciences and Forensic Medicine Yingqing Fu West China School of Basic Medical Sciences and Forensic Medicine Yi Ye West China School of Basic Medical Sciences and Forensic Medicine Linchuan Liao ( [email protected] ) West China School of Basic Medical Sciences and Forensic Medicine https://orcid.org/0000-0003-3700-8471 Research Keywords: Breast cancer, Differentially expressed genes, miRNAs, Transcription factors, Bioinformatic analysis Posted Date: December 2nd, 2020 DOI: https://doi.org/10.21203/rs.3.rs-117477/v1 License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Page 1/23 Abstract Background: Breast cancer (BRCA) remains one of the most common forms of cancer and is the most prominent driver of cancer-related death among women. The mechanistic basis for BRCA, however, remains incompletely understood. In particular, the relationships between driver mutations and signaling pathways in BRCA are poorly characterized, making it dicult to identify reliable clinical biomarkers that can be employed in diagnostic, therapeutic, or prognostic contexts. Methods: First, we downloaded publically available BRCA datasets (GSE45827, GSE42568, and GSE61304) from the Gene Expression Omnibus (GEO) database. We then compared gene expression proles between tumor and control tissues in these datasets using Venn diagrams and the GEO2R analytical tool. We further explore the functional relevance of BRCA-associated differentially expressed genes (DEGs) via functional and pathway enrichment analyses using the DAVID tool, and we then constructed a protein-protein interaction network incorporating DEGs of interest using the Search Tool for the Retrieval of Interacting Genes (STRING) database.
    [Show full text]
  • Detailed Review Paper on Retinoid Pathway Signalling
    1 1 Detailed Review Paper on Retinoid Pathway Signalling 2 December 2020 3 2 4 Foreword 5 1. Project 4.97 to develop a Detailed Review Paper (DRP) on the Retinoid System 6 was added to the Test Guidelines Programme work plan in 2015. The project was 7 originally proposed by Sweden and the European Commission later joined the project as 8 a co-lead. In 2019, the OECD Secretariat was added to coordinate input from expert 9 consultants. The initial objectives of the project were to: 10 draft a review of the biology of retinoid signalling pathway, 11 describe retinoid-mediated effects on various organ systems, 12 identify relevant retinoid in vitro and ex vivo assays that measure mechanistic 13 effects of chemicals for development, and 14 Identify in vivo endpoints that could be added to existing test guidelines to 15 identify chemical effects on retinoid pathway signalling. 16 2. This DRP is intended to expand the recommendations for the retinoid pathway 17 included in the OECD Detailed Review Paper on the State of the Science on Novel In 18 vitro and In vivo Screening and Testing Methods and Endpoints for Evaluating 19 Endocrine Disruptors (DRP No 178). The retinoid signalling pathway was one of seven 20 endocrine pathways considered to be susceptible to environmental endocrine disruption 21 and for which relevant endpoints could be measured in new or existing OECD Test 22 Guidelines for evaluating endocrine disruption. Due to the complexity of retinoid 23 signalling across multiple organ systems, this effort was foreseen as a multi-step process.
    [Show full text]
  • ZNF652, a Novel Zinc Finger Protein, Interacts with the Putative Breast Tumor Suppressor CBFA2T3 to Repress Transcription
    ZNF652, A Novel Zinc Finger Protein, Interacts with the Putative Breast Tumor Suppressor CBFA2T3 to Repress Transcription Raman Kumar,1 Jantina Manning,1 Hayley E. Spendlove,3 Gabriel Kremmidiotis,4 Ross McKirdy,1 Jaclyn Lee,1 David N. Millband,1 Kelly M. Cheney,1 Martha R. Stampfer,5 Prem P. Dwivedi,2 Howard A. Morris,2 and David F. Callen1 1Breast Cancer Genetics Group, Dame Roma Mitchell Cancer Research Laboratories, Department of Medicine, University of Adelaide and Hanson Institute; 2Endocrine Bone Laboratory, Hanson Institute, Adelaide, South Australia, Australia; 3Department of Laboratory Genetics, Women’s and Children’s Hospital, North Adelaide, South Australia, Australia; 4Bionomics, Ltd., Thebarton, South Australia, Australia; and 5Lawrence Berkeley National Laboratory, Berkeley, California Abstract gene effector zinc finger proteins may specifically The transcriptional repressor CBFA2T3is a putative interact with one or more of the ETO proteins to generate breast tumor suppressor. To define the role of CBFA2T3, a defined range of transcriptional repressor complexes. we used a segment of this protein as bait in a yeast (Mol Cancer Res 2006;4(9):655–65) two-hybrid screen and identified a novel uncharacterized protein, ZNF652. In general, primary tumors and cancer Introduction cell lines showed lower expression of ZNF652 than Tumor growth, characterized by unchecked cell division, normal tissues. Together with the location of this gene results from both the overexpression of growth-promoting on the long arm of chromosome 17q, a region of frequent oncogenes and the reduced expression of growth-inhibiting loss of heterozygosity in cancer, these results suggest tumor suppressor genes. These genes often encode proteins that In silico a possible role of ZNF652 in tumorigenesis.
    [Show full text]
  • Table S1 the Four Gene Sets Derived from Gene Expression Profiles of Escs and Differentiated Cells
    Table S1 The four gene sets derived from gene expression profiles of ESCs and differentiated cells Uniform High Uniform Low ES Up ES Down EntrezID GeneSymbol EntrezID GeneSymbol EntrezID GeneSymbol EntrezID GeneSymbol 269261 Rpl12 11354 Abpa 68239 Krt42 15132 Hbb-bh1 67891 Rpl4 11537 Cfd 26380 Esrrb 15126 Hba-x 55949 Eef1b2 11698 Ambn 73703 Dppa2 15111 Hand2 18148 Npm1 11730 Ang3 67374 Jam2 65255 Asb4 67427 Rps20 11731 Ang2 22702 Zfp42 17292 Mesp1 15481 Hspa8 11807 Apoa2 58865 Tdh 19737 Rgs5 100041686 LOC100041686 11814 Apoc3 26388 Ifi202b 225518 Prdm6 11983 Atpif1 11945 Atp4b 11614 Nr0b1 20378 Frzb 19241 Tmsb4x 12007 Azgp1 76815 Calcoco2 12767 Cxcr4 20116 Rps8 12044 Bcl2a1a 219132 D14Ertd668e 103889 Hoxb2 20103 Rps5 12047 Bcl2a1d 381411 Gm1967 17701 Msx1 14694 Gnb2l1 12049 Bcl2l10 20899 Stra8 23796 Aplnr 19941 Rpl26 12096 Bglap1 78625 1700061G19Rik 12627 Cfc1 12070 Ngfrap1 12097 Bglap2 21816 Tgm1 12622 Cer1 19989 Rpl7 12267 C3ar1 67405 Nts 21385 Tbx2 19896 Rpl10a 12279 C9 435337 EG435337 56720 Tdo2 20044 Rps14 12391 Cav3 545913 Zscan4d 16869 Lhx1 19175 Psmb6 12409 Cbr2 244448 Triml1 22253 Unc5c 22627 Ywhae 12477 Ctla4 69134 2200001I15Rik 14174 Fgf3 19951 Rpl32 12523 Cd84 66065 Hsd17b14 16542 Kdr 66152 1110020P15Rik 12524 Cd86 81879 Tcfcp2l1 15122 Hba-a1 66489 Rpl35 12640 Cga 17907 Mylpf 15414 Hoxb6 15519 Hsp90aa1 12642 Ch25h 26424 Nr5a2 210530 Leprel1 66483 Rpl36al 12655 Chi3l3 83560 Tex14 12338 Capn6 27370 Rps26 12796 Camp 17450 Morc1 20671 Sox17 66576 Uqcrh 12869 Cox8b 79455 Pdcl2 20613 Snai1 22154 Tubb5 12959 Cryba4 231821 Centa1 17897
    [Show full text]
  • Potassium Channels in Epilepsy
    Downloaded from http://perspectivesinmedicine.cshlp.org/ on September 28, 2021 - Published by Cold Spring Harbor Laboratory Press Potassium Channels in Epilepsy Ru¨diger Ko¨hling and Jakob Wolfart Oscar Langendorff Institute of Physiology, University of Rostock, Rostock 18057, Germany Correspondence: [email protected] This review attempts to give a concise and up-to-date overview on the role of potassium channels in epilepsies. Their role can be defined from a genetic perspective, focusing on variants and de novo mutations identified in genetic studies or animal models with targeted, specific mutations in genes coding for a member of the large potassium channel family. In these genetic studies, a demonstrated functional link to hyperexcitability often remains elusive. However, their role can also be defined from a functional perspective, based on dy- namic, aggravating, or adaptive transcriptional and posttranslational alterations. In these cases, it often remains elusive whether the alteration is causal or merely incidental. With 80 potassium channel types, of which 10% are known to be associated with epilepsies (in humans) or a seizure phenotype (in animals), if genetically mutated, a comprehensive review is a challenging endeavor. This goal may seem all the more ambitious once the data on posttranslational alterations, found both in human tissue from epilepsy patients and in chronic or acute animal models, are included. We therefore summarize the literature, and expand only on key findings, particularly regarding functional alterations found in patient brain tissue and chronic animal models. INTRODUCTION TO POTASSIUM evolutionary appearance of voltage-gated so- CHANNELS dium (Nav)andcalcium (Cav)channels, Kchan- nels are further diversified in relation to their otassium (K) channels are related to epilepsy newer function, namely, keeping neuronal exci- Psyndromes on many different levels, ranging tation within limits (Anderson and Greenberg from direct control of neuronal excitability and 2001; Hille 2001).
    [Show full text]
  • Genetic Variability in the Italian Heavy Draught Horse from Pedigree Data and Genomic Information
    Supplementary material for manuscript: Genetic variability in the Italian Heavy Draught Horse from pedigree data and genomic information. Enrico Mancin†, Michela Ablondi†, Roberto Mantovani*, Giuseppe Pigozzi, Alberto Sabbioni and Cristina Sartori ** Correspondence: [email protected] † These two Authors equally contributed to the work Supplementary Figure S1. Mares and foal of Italian Heavy Draught Horse (IHDH; courtesy of Cinzia Stoppa) Supplementary Figure S2. Number of Equivalent Generations (EqGen; above) and pedigree completeness (PC; below) over years in Italian Heavy Draught Horse population. Supplementary Table S1. Descriptive statistics of homozygosity (observed: Ho_obs; expected: Ho_exp; total: Ho_tot) in 267 genotyped individuals of Italian Heavy Draught Horse based on the number of homozygous genotypes. Parameter Mean SD Min Max Ho_obs 35,630.3 500.7 34,291 38,013 Ho_exp 35,707.8 64.0 35,010 35,740 Ho_tot 50,674.5 93.8 49,638 50,714 1 Definitions of the methods for inbreeding are in the text. Supplementary Figure S3. Values of BIC obtained by analyzing values of K from 1 to 10, corresponding on the same amount of clusters defining the proportion of ancestry in the 267 genotyped individuals. Supplementary Table S2. Estimation of genomic effective population size (Ne) traced back to 18 generations ago (Gen. ago). The linkage disequilibrium estimation, adjusted for sampling bias was also included (LD_r2), as well as the relative standard deviation (SD(LD_r2)). Gen. ago Ne LD_r2 SD(LD_r2) 1 100 0.009 0.014 2 108 0.011 0.018 3 118 0.015 0.024 4 126 0.017 0.028 5 134 0.019 0.031 6 143 0.021 0.034 7 156 0.023 0.038 9 173 0.026 0.041 11 189 0.029 0.046 14 213 0.032 0.052 18 241 0.036 0.058 Supplementary Table S3.
    [Show full text]
  • Analysis and Characterisation of the Mouse Hic2 Gene
    Aus dem Institut für Entwicklungsgenetik des GSF-Forschungszentrums für Umwelt und Gesundheit, GmbH Direktor: Prof. Dr. Wolfgang Wurst Anfertigung unter der Leitung von Prof. Dr. Jochen Graw Vorgelegt über den Lehrstuhl für Molekulare Tierzucht und Biotechnologie Der Tierärztlichen Fakultät der Ludwig-Maximilians-Universität München Vorstand: Prof. Dr. Eckhard Wolf Untersuchung und Charakterisierung des Hic2-Gens der Maus Inaugural-Dissertation Zur Erlangung der tiermedizinischen Doktorwürde der Tierärztlichen Fakultät der Ludwig-Maximilians-Universität München von Aleksandra Terzic aus Sarajevo/Bosnia und Herzegowina München 2004 II Aus dem Institut für Entwicklungsgenetik des GSF-Forschungszentrums für Umwelt und Gesundheit, GmbH Direktor: Prof. Dr. Wolfgang Wurst Anfertigung unter der Leitung von Prof. Dr. Jochen Graw Vorgelegt über den Lehrstuhl für Molekulare Tierzucht und Biotechnologie Der Tierärztlichen Fakultät der Ludwig-Maximilians-Universität München Vorstand: Prof. Dr. Eckhard Wolf Analysis and characterisation of the mouse Hic2 gene Inaugural-Dissertation Zur Erlangung der tiermedizinischen Doktorwürde der Tierärztlichen Fakultät der Ludwig-Maximilians-Universität München von Aleksandra Terzic aus Sarajevo/Bosnia und Herzegowina München 2004 III Gedruckt mit Genehmigung der Tierärztlichen Fakultät der Ludwig-Maximilians-Universität München Dekan: Univ.-Prof. Dr. A.Stolle Referent: Univ.-Prof. Dr. E. Wolf Korreferent: Univ.-Prof. Dr. K. Heinritzi Tag der Promotion: 13. Februar 2004 IV List of contents 1 INTRODUCTION.............................................................................................................1
    [Show full text]
  • Broad and Thematic Remodeling of the Surface Glycoproteome on Isogenic
    bioRxiv preprint doi: https://doi.org/10.1101/808139; this version posted October 17, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Broad and thematic remodeling of the surface glycoproteome on isogenic cells transformed with driving proliferative oncogenes Kevin K. Leung1,5, Gary M. Wilson2,5, Lisa L. Kirkemo1, Nicholas M. Riley2,4, Joshua J. Coon2,3, James A. Wells1* 1Department of Pharmaceutical Chemistry, UCSF, San Francisco, CA, USA Departments of Chemistry2 and Biomolecular Chemistry3, University of Wisconsin- Madison, Madison, WI, 53706, USA 4Present address Department of Chemistry, Stanford University, Stanford, CA, 94305, USA 5These authors contributed equally *To whom correspondence should be addressed bioRxiv preprint doi: https://doi.org/10.1101/808139; this version posted October 17, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Abstract: The cell surface proteome, the surfaceome, is the interface for engaging the extracellular space in normal and cancer cells. Here We apply quantitative proteomics of N-linked glycoproteins to reveal how a collection of some 700 surface proteins is dramatically remodeled in an isogenic breast epithelial cell line stably expressing any of six of the most prominent proliferative oncogenes, including the receptor tyrosine kinases, EGFR and HER2, and downstream signaling partners such as KRAS, BRAF, MEK and AKT.
    [Show full text]
  • 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.
    [Show full text]
  • Transcriptomic Analysis of Native Versus Cultured Human and Mouse Dorsal Root Ganglia Focused on Pharmacological Targets Short
    bioRxiv preprint doi: https://doi.org/10.1101/766865; this version posted September 12, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license. Transcriptomic analysis of native versus cultured human and mouse dorsal root ganglia focused on pharmacological targets Short title: Comparative transcriptomics of acutely dissected versus cultured DRGs Andi Wangzhou1, Lisa A. McIlvried2, Candler Paige1, Paulino Barragan-Iglesias1, Carolyn A. Guzman1, Gregory Dussor1, Pradipta R. Ray1,#, Robert W. Gereau IV2, # and Theodore J. Price1, # 1The University of Texas at Dallas, School of Behavioral and Brain Sciences and Center for Advanced Pain Studies, 800 W Campbell Rd. Richardson, TX, 75080, USA 2Washington University Pain Center and Department of Anesthesiology, Washington University School of Medicine # corresponding authors [email protected], [email protected] and [email protected] Funding: NIH grants T32DA007261 (LM); NS065926 and NS102161 (TJP); NS106953 and NS042595 (RWG). The authors declare no conflicts of interest Author Contributions Conceived of the Project: PRR, RWG IV and TJP Performed Experiments: AW, LAM, CP, PB-I Supervised Experiments: GD, RWG IV, TJP Analyzed Data: AW, LAM, CP, CAG, PRR Supervised Bioinformatics Analysis: PRR Drew Figures: AW, PRR Wrote and Edited Manuscript: AW, LAM, CP, GD, PRR, RWG IV, TJP All authors approved the final version of the manuscript. 1 bioRxiv preprint doi: https://doi.org/10.1101/766865; this version posted September 12, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.
    [Show full text]
  • The P53/P73 - P21cip1 Tumor Suppressor Axis Guards Against Chromosomal Instability by Restraining CDK1 in Human Cancer Cells
    Oncogene (2021) 40:436–451 https://doi.org/10.1038/s41388-020-01524-4 ARTICLE The p53/p73 - p21CIP1 tumor suppressor axis guards against chromosomal instability by restraining CDK1 in human cancer cells 1 1 2 1 2 Ann-Kathrin Schmidt ● Karoline Pudelko ● Jan-Eric Boekenkamp ● Katharina Berger ● Maik Kschischo ● Holger Bastians 1 Received: 2 July 2020 / Revised: 2 October 2020 / Accepted: 13 October 2020 / Published online: 9 November 2020 © The Author(s) 2020. This article is published with open access Abstract Whole chromosome instability (W-CIN) is a hallmark of human cancer and contributes to the evolvement of aneuploidy. W-CIN can be induced by abnormally increased microtubule plus end assembly rates during mitosis leading to the generation of lagging chromosomes during anaphase as a major form of mitotic errors in human cancer cells. Here, we show that loss of the tumor suppressor genes TP53 and TP73 can trigger increased mitotic microtubule assembly rates, lagging chromosomes, and W-CIN. CDKN1A, encoding for the CDK inhibitor p21CIP1, represents a critical target gene of p53/p73. Loss of p21CIP1 unleashes CDK1 activity which causes W-CIN in otherwise chromosomally stable cancer cells. fi Vice versa 1234567890();,: 1234567890();,: Consequently, induction of CDK1 is suf cient to induce abnormal microtubule assembly rates and W-CIN. , partial inhibition of CDK1 activity in chromosomally unstable cancer cells corrects abnormal microtubule behavior and suppresses W-CIN. Thus, our study shows that the p53/p73 - p21CIP1 tumor suppressor axis, whose loss is associated with W-CIN in human cancer, safeguards against chromosome missegregation and aneuploidy by preventing abnormally increased CDK1 activity.
    [Show full text]