Sarkar Et Al. SUPPLEMENTAL INFORMATION

Total Page:16

File Type:pdf, Size:1020Kb

Sarkar Et Al. SUPPLEMENTAL INFORMATION Sarkar et al. SUPPLEMENTAL INFORMATION Figure S1 A 10 20 30 40 50 MADKRKLQGE IDRCLKKVSE GVEQFEDIWQ KLHNAANANQ KEKYEADLKK 60 70 80 90 100 EIKKLQRLRD QIKTWVASNE IKDKRQLIEN RKLIETQMER FKVVERETKT Predicted 110 120 130 140 150 coiled-coil KAYSKEGLGL AQKVDPAQKE KEEVGQWLTN TIDTLNMQVD QFESEVESLS domain 160 170 180 190 200 (1-241) VQTRKKKGDK DKQDRIEGLK RHIEKHRYHV RMLETILRML DNDSILVDAI 210 220 230 240 250 RKIKDDVEYY VDSSQDPDFE ENEFLYDDLD LEDIPQALVA TSPPSHSHME 260 270 280 290 300 DEIFNQSSST PTSTTSSSPI PPSPANCTTE NSEDDKKRGR ST* DSEVSQSP * 310 320 330 340 350 AKNGSKPVHS NQHPQSPAVP PTYPSGPPPT TSALSSTPGN NGASTPAAPT 360 370 380 390 400 SALGPKASPA PSHNSGTPAP YAQAVAPPNA SGPSNAQPRP PSAQPSGGSG 410 420 430 440 450 Intrinsically GGSGGSSSNS NSGTGGGAGK QNGATSYSSV VADSPAEVTL SSSGGSSASS disordered region 460 470 480 490 500 (242-605) QALGPTSGPH NPAPSTSKES STAAPSGAGN VASGSGNNSG GPSLLVPLPV 510 520 530 540 550 NPPSSPTPSF SEAKAAGTLL NGPPQFSTTP EIKAPEPLSS LKSMAERAAI 560 570 580 590 600 SSGIEDPVPT LHLTDRDIIL SSTSAPPTSS QPPLQLSEVN IPLSLGVCPL 610 620 630 640 650 GPVSLTKEQL YQQAMEEAAW HHMPHPSDSE RIRQYLPRNP CPTPPYHHQM 660 670 680 690 700 NAR/CS PPPHSDTVEF YQRLSTETLF FIFYYLEGTK AQYLAAKALK KQSWRFHTKY 710 720 730 740 750 NOT box (654-751) MMWFQRHEEP KTITDEFEQG TYIYFDYEKW GQRKKEGFTF EYRYLEDRDLQ B 2 Supplementary Figure 1: A. Sequence of the mouse CNOT3 protein (UNIPROT Q8K0V4). Vertical blue lines delineate the domains of the protein that are shown in Figure 1B. The green-shaded box indicates the the NOT box region, which is required for the interaction between CNOT3 and Aurora B (Figure 1C). Aurora B consensus phosphorylation sites are underlined. The red box and text indicate the putative nuclear localization sequence. * indicates residues 292 and 294, which were mutated in this study. B. Phosphorylation sites detected on the CNOT3 protein by in vivo proteomic discovery mass pectrometry. Data was obtained from PhosphoSite® (Hornbeck et al., 2015). Data is shown for the human CNOT3 protein, which is 95% identical to mouse CNOT3. With the exception of one residue (E79), all of the residues that vary between human and mouse are located within the intrinsically disordered region between residues 329 and 604 of the mouse sequence. Blue circles indicate phosphorylated residues. The y-axis shows the number of records where the modification was assigned using proteomic discovery mass spectrometry. The numbered residues show a phosphorylation hotspot in the region extending from positions 291-299. 3 Figure S2 A B WT Clone 1 110bp ssODN Clone 2 Cnot3 Exon 10 C WT-DMSO WT-AZD1152 WT-AZD1152 24h 48h Counts Counts Counts PI PI PI D E G2/M CNOT3-DM S * ** NS G1 NS ** ** Counts * NS NS Percent of cells PI WT-DMSO CNOT3-DM WT-AZD1152WT-AZD1152 24h 48h 4 Supplementary Figure 2: Identification of Aurora B phosphorylation sites in the CNOT3 protein A. MS/MS fragmentation spectrum generated by ion trap collision-induced dissociation (CID) of doubly charged precursor ion with m/z 658.27 identifying CNOT3 tryptic peptide 291-302 (STDSEVSQSPAK). The spectrum presented two fragments which were as follows: Left panel: query number 2609 with assigned b- and y-ions; MASCOT score: -5 54; expectation value: 1.8x10 ; neutral loss of H3PO4 (-97.98 Da) from precursor ion detected at m/z 609.49; localisation probability for phosphorylation of Ser291: 3.0%, Thr292: 3.0%, Ser294 is 93.9%. Right panel: query number 2608 with assigned b- and y-ions; MASCOT score: 53; expectation value: 3.6x10-5; localisation probability for phosphorylation of Ser291: 25.6%, Thr292: 25.6%, Ser294: 48.4%. B. Left panel: Schematic representation showing use of CRISPR/Cas9 targeting of Cnot3 in exon 10 to mutate Threonine 292 and Serine 294 to alanine, using the guide RNA described in Methods and a 110 bp single-stranded donor oligonucleotides (ssODN) carrying the mutations. Right panel: Sequence images showing the wild-type (WT) sequence and the mutated sequences obtained from two CRISPR generated clones. C. FACS analysis of the cell cycle profiles of ESCs incubated for 24 and 48 hours with the Aurora B inhibitor AZD1152 or with vehicle (DMSO) and stained with propidium iodide (PI). D. FACS analysis of the cell cycle profile of Cnot3-DM ESCs. E. Histograms showing the percentage of cells measured at different phases of the cell cycle in (c) and (d). Mean ± SEM; P values (with respect to WT-DMSO) calculated by unpaired t-test, ns = non-significant, n=3. 5 Figure S3 A DAPI OTX2 WT CNOT3-DM B DAPI NESTIN DAPI -SMA DAPI FOXA2 + WT WT WT CNOT3-DM CNOT3-DM CNOT3-DM Ectoderm Mesoderm Endoderm Ectoderm Mesoderm Endoderm ns ns *** SURVIVAL RATIO SURVIVAL SURVIVAL RATIO SURVIVAL SURVIVAL RATIO SURVIVAL WT WT WT CNOT3 CNOT3 CNOT3 -DM -DM -DM Supplementary Figure 3: Differentiation of Cnot3-DM ESCs into the three germ layers A. Representative confocal images of 8-day embryoid bodies (EBs) derived from wild- type (WT) and Cnot3-DM ESCs and subjected to immunostaining for the ectodermal marker OTX2 (green). Nuclei were counterstained with DAPI; scale bar: 100 µm. B. Top panels: Representative confocal images of differentiation of WT and Cnot3-DM ESCs into ectoderm (3 days; immunostained for Nestin (green)), Activin A induced mesoderm (3 days; immunostained for a-SMA (green)) and FGF2+retinoic acid induced endoderm (3 days; immunostained for FOXA2 (green). Nuclei were counterstained with 6 DAPI; scale bar: 12 µm. (See Methods). Bottom panels: Graphs represent the ratio of suriving Cnot3-DM cells versus WT cells after 3 days of differentiation into each lineage. Cell survival was measured using WST-1 reagent (see Methods). Mean ± SEM; (P values calculated by unpaired t-test, ***P<0.001. ns = non-significant, n=3). 7 Figure S4 A DAPI BRACHURY FOXA2 MERGED DAPI SMA WT CNOT3-DM 8 days mesendoderm differentiation DAPI BRACHURY GATA4 MERGED B CNOT3-DM WT Clone 2 Clone 3 WT 8 days mesendoderm differentiation CNOT3-DM 8 days mesendoderm differentiation C D WT CNOT3-DM WT CNOT3-DM Counts Counts *** *** SURVIVAL RATIO SURVIVAL * BMP4+FGF2 + - - PI PI ACTIVIN A - + - WNT3 - - + G2/M ns S G1 Percent of cells WT CNOT3-DM 8 Supplementary Figure 4: CNOT3-T292/S294 phosphorylation promotes survival of differentiating mesendodermal cells. A. Representative immunofluorescence analysis images of ME cells by inducing differentiation of WT and Cnot3-DM ESCs with BMP4 + FGF2 for 8 days (left panel: scale bar: 100 µm). Staining was for the mesodermal marker Brachury (red) and endodermal marker FOXA2 (green) (top) or GATA4 (bottom), merged images show dual staining of the mesendodermal cells. Immunofluorescence was also performed for the mesodermal marker a-SMA (right panel; scale bar: 60 µm). Nuclei were counterstained with DAPI. B. Crystal violet staining showing the efficiency of BMP4+FGF2 induced mesendoderm (ME) differentiation of wild-type (WT) ESCs and two additional clones of Cnot3-DM ESCs after 4 days of differentiation. C. Cell cycle analysis of ME cells obtained by inducing differentiation of WT and Cnot3- DM ESCs with BMP4 + FGF2 for 4 days. Histograms represent the percentage of cells at different phases of the cell cycle. Mean ± SEM; P values calculated by unpaired t-test, ns = non-significant, n=3. D. Survival of WT and Cnot3-DM ESCs over 4 days of differentiation induced in the presence of BMP4+FGF2 or Activin A or Wnt3 and the cell survival was determined using WST-1 reagent on day 4 of the differentiation. Histograms show survival ratios calculated relative to the values obtained for wild-type (WT) cells treated with BMP4+FGF2, which was assigned a value of 1. Mean ± SEM, significance calculated using unpaired t-test *P<0.05, ***P<0.001, n=3. 9 Figure S5 A B P adj< 0.05 WT CNOT3-DM NON SIG WT CNOT3-DM PC2 : 22.69 % VARIANCE P VALUE P 10 log - PC1 : 40.13 % VARIANCE -log2 FOLD CHANGE C D ENRICHED GENE ONTOLOGY TERMS (DOWNREGULATED) ENRICHED GENE ONTOLOGY TERMS (UPREGULATED) Cell adhesion Epithelium development Developmental processes Signal transducer activity Mesenchymal cell development Molecular transducer activity Embryonic placenta development Signaling receptor activity Negative regulation of Wnt signaling pathway Cell surface receptor signaling pathway Apoptotic process involved in morphogenesis Growth factor binding Regulation of programmed cell death Regulation of cell proliferation Positive regulation of kinase activity -log P VALUE 10 Multicellular organism development Regulation of MAPK cascade -log P VALUE E 10 10 Supplementary Figure 5: Transcriptome profiling by RNA sequencing in differentiating wild-type and Cnot3-DM mesendoderm cells. A. and B. RNA-seq analysis was used to compare gene expression patterns of ME cells obtained by differentiating wild-type (WT) and Cnot3-DM ESCs for 4 days with BMP4 + FGF2, we performed RNA sequencing (RNA-seq) analysis on the wild-type and Cnot3- DM cells after 4 days of mesendoderm differentiation. A. Volcano plot of RNA-Seq transcriptome data showing differentially expressed genes after 4 days of BMP4 + FGF2 induced mesendoderm differentiation of WT and Cnot3-DM ESCs. Fold change ratio >1.5; adjusted P value <0.05. Three biological replicates for each were analyzed. B. Principal component plot of the RNA-seq data showing PC1 and PC2 and the percent variance obtained for each. This reveals separate clustering of the genes that are differentially expressed between the WT and Cnot3-DM-derived 4-day differentiated mesendodermal cells. C. and D. Selected gene ontology (GO) profiles obtained out using the GOSeq Bioconductor package and showing upregulated genes (C) and downregulated genes (D), which are involved in signalling pathways that have key roles in developmental processes. Adjusted P value <0.05. e. GSEA analysis showing Hallmark gene sets that were significantly altered in the differentiated cells. See also Supplementary Tables 2A and S2B for the differentially regulated genes. The GO and GSEA analysis both showed that expression of genes involved in cell death and apoptosis was upregulated (C and E).
Recommended publications
  • Sarkar Et Al. SUPPLEMENTAL INFORMATION
    Sarkar et al. SUPPLEMENTAL INFORMATION Figure S1 A 10 20 30 40 50 MADKRKLQGE IDRCLKKVSE GVEQFEDIWQ KLHNAANANQ KEKYEADLKK 60 70 80 90 100 EIKKLQRLRD QIKTWVASNE IKDKRQLIEN RKLIETQMER FKVVERETKT Predicted 110 120 130 140 150 coiled-coil KAYSKEGLGL AQKVDPAQKE KEEVGQWLTN TIDTLNMQVD QFESEVESLS domain 160 170 180 190 200 (1-241) VQTRKKKGDK DKQDRIEGLK RHIEKHRYHV RMLETILRML DNDSILVDAI 210 220 230 240 250 RKIKDDVEYY VDSSQDPDFE ENEFLYDDLD LEDIPQALVA TSPPSHSHME 260 270 280 290 300 DEIFNQSSST PTSTTSSSPI PPSPANCTTE NSEDDKKRGR ST* DSEVSQSP * 310 320 330 340 350 AKNGSKPVHS NQHPQSPAVP PTYPSGPPPT TSALSSTPGN NGASTPAAPT 360 370 380 390 400 SALGPKASPA PSHNSGTPAP YAQAVAPPNA SGPSNAQPRP PSAQPSGGSG 410 420 430 440 450 Intrinsically GGSGGSSSNS NSGTGGGAGK QNGATSYSSV VADSPAEVTL SSSGGSSASS disordered region 460 470 480 490 500 (242-605) QALGPTSGPH NPAPSTSKES STAAPSGAGN VASGSGNNSG GPSLLVPLPV 510 520 530 540 550 NPPSSPTPSF SEAKAAGTLL NGPPQFSTTP EIKAPEPLSS LKSMAERAAI 560 570 580 590 600 SSGIEDPVPT LHLTDRDIIL SSTSAPPTSS QPPLQLSEVN IPLSLGVCPL 610 620 630 640 650 GPVSLTKEQL YQQAMEEAAW HHMPHPSDSE RIRQYLPRNP CPTPPYHHQM 660 670 680 690 700 NAR/CS PPPHSDTVEF YQRLSTETLF FIFYYLEGTK AQYLAAKALK KQSWRFHTKY 710 720 730 740 750 NOT box (654-751) MMWFQRHEEP KTITDEFEQG TYIYFDYEKW GQRKKEGFTF EYRYLEDRDLQ B 2 Supplementary Figure 1: A. Sequence of the mouse CNOT3 protein (UNIPROT Q8K0V4). Vertical blue lines delineate the domains of the protein that are shown in Figure 1B. The green-shaded box indicates the the NOT box region, which is required for the interaction between CNOT3 and Aurora B (Figure 1C). Aurora B consensus phosphorylation sites are underlined. The red box and red text indicate the putative nuclear localization sequence. * indicates residues 292 and 294, which were mutated in this study. B. Phosphorylation sites detected on the CNOT3 protein by in vivo proteomic discovery mass pectrometry.
    [Show full text]
  • The CCR4-NOT Complex Contributes to Repression of Major
    www.nature.com/scientificreports OPEN The CCR4-NOT complex contributes to repression of Major Histocompatibility Complex class II Received: 20 January 2017 Accepted: 3 May 2017 transcription Published: xx xx xxxx Alfonso Rodríguez-Gil 1, Olesja Ritter1, Vera V. Saul1, Jochen Wilhelm2, Chen-Yuan Yang3, Rudolf Grosschedl3, Yumiko Imai4, Keiji Kuba4, Michael Kracht5 & M. Lienhard Schmitz1 The multi-subunit CCR4 (carbon catabolite repressor 4)-NOT (Negative on TATA) complex serves as a central coordinator of all different steps of eukaryotic gene expression. Here we performed a systematic and comparative analysis of cells where the CCR4-NOT subunits CNOT1, CNOT2 or CNOT3 were individually downregulated using doxycycline-inducible shRNAs. Microarray experiments showed that downregulation of either CNOT subunit resulted in elevated expression of major histocompatibility complex class II (MHC II) genes which are found in a gene cluster on chromosome 6. Increased expression of MHC II genes after knock-down or knock-out of either CNOT subunit was seen in a variety of cell systems and also in naïve macrophages from CNOT3 conditional knock-out mice. CNOT2-mediated repression of MHC II genes occurred also in the absence of the master regulator class II transactivator (CIITA) and did not cause detectable changes of the chromatin structure at the chromosomal MHC II locus. CNOT2 downregulation resulted in an increased de novo transcription of mRNAs whereas tethering of CNOT2 to a regulatory region governing MHC II expression resulted in diminished transcription. These results expand the known repertoire of CCR4-NOT members for immune regulation and identify CNOT proteins as a novel group of corepressors restricting class II expression.
    [Show full text]
  • NIH Public Access Author Manuscript Cell
    NIH Public Access Author Manuscript Cell. Author manuscript; available in PMC 2013 September 14. NIH-PA Author ManuscriptPublished NIH-PA Author Manuscript in final edited NIH-PA Author Manuscript form as: Cell. 2012 September 14; 150(6): 1274–1286. doi:10.1016/j.cell.2012.04.040. Circuitry and dynamics of human transcription factor regulatory networks Shane Neph1,*, Andrew B. Stergachis1,*, Alex Reynolds1, Richard Sandstrom1, Elhanan Borenstein1,2,3,¥, and John A. Stamatoyannopoulos1,4,¥ 1Department of Genome Sciences, University of Washington, Seattle, WA 98195 2Department of Computer Science and Engineering, University of Washington, Seattle, WA 98195 3Santa Fe Institute, Santa Fe, NM 87501 4Department of Medicine, University of Washington, Seattle, WA 98195 SUMMARY The combinatorial cross-regulation of hundreds of sequence-specific transcription factors defines a regulatory network that underlies cellular identity and function. Here we use genome-wide maps of in vivo DNaseI footprints to assemble an extensive core human regulatory network comprising connections among 475 sequence-specific transcription factors, and to analyze the dynamics of these connections across 41 diverse cell and tissue types. We find that human transcription factor networks are highly cell-selective and are driven by cohorts of factors that include regulators with previously unrecognized roles in control of cellular identity. Moreover, we identify many widely expressed factors that impact transcriptional regulatory networks in a cell-selective manner. Strikingly, in spite of their inherent diversity, all cell type regulatory networks independently converge on a common architecture that closely resembles the topology of living neuronal networks. Together, our results provide the first description of the circuitry, dynamics, and organizing principles of the human transcription factor regulatory network.
    [Show full text]
  • Transcriptional Regulator CNOT3 Defines an Aggressive Colorectal Cancer Subtype
    Published OnlineFirst November 29, 2016; DOI: 10.1158/0008-5472.CAN-16-1346 Cancer Tumor and Stem Cell Biology Research Transcriptional Regulator CNOT3 Defines an Aggressive Colorectal Cancer Subtype Paloma Cejas1,2,3, Alessia Cavazza1,2, C.N. Yandava1, Victor Moreno3, David Horst4, Juan Moreno-Rubio3, Emilio Burgos5, Marta Mendiola3,5, Len Taing1, Ajay Goel6, Jaime Feliu3, and Ramesh A. Shivdasani1,2 Abstract Cancer cells exhibit dramatic alterations of chromatin organi- primarily to genes whose expression was affected by CNOT3 loss, zation at cis-regulatory elements, but the molecular basis, extent, and also at sites modulated in certain types of colorectal cancers. and impact of these alterations are still being unraveled. Here, we These target genes were implicated in ESC and cancer self-renewal identify extensive genome-wide modification of sites bearing the and fell into two distinct groups: those dependent on CNOT3 and active histone mark H3K4me2 in primary human colorectal MYC for optimal transcription and those repressed by CNOT3 cancers, as compared with corresponding benign precursor ade- binding and promoter hypermethylation. Silencing CNOT3 in nomas. Modification of certain colorectal cancer sites highlighted colorectal cancer cells resulted in replication arrest. In clinical þ the activity of the transcription factor CNOT3, which is known to specimens, early-stage tumors that included >5% CNOT3 cells control self-renewal of embryonic stem cells (ESC). In primary exhibited a correlation to worse clinical outcomes compared with colorectal cancer cells, we observed a scattered pattern of CNOT3 tumors with little to no CNOT3 expression. Together, our findings expression, as might be expected for a tumor-initiating cell mark- implicate CNOT3 in the coordination of colonic epithelial cell er.
    [Show full text]
  • High-Resolution Genome-Wide DNA Methylation Maps of Mouse Primary
    Chatterjee et al. Epigenetics & Chromatin 2014, 7:35 http://www.epigeneticsandchromatin.com/content/7/1/35 RESEARCH Open Access High-resolution genome-wide DNA methylation maps of mouse primary female dermal fibroblasts and keratinocytes Raghunath Chatterjee1,2†, Ximiao He1†, Di Huang3, Peter FitzGerald4, Andrew Smith5 and Charles Vinson1* Abstract Background: Genome-wide DNA methylation at a single nucleotide resolution in different primary cells of the mammalian genome helps to determine the characteristics and functions of tissue-specific hypomethylated regions (TS-HMRs). We determined genome-wide cytosine methylation maps at 91X and 36X coverage of newborn female mouse primary dermal fibroblasts and keratinocytes and compared with mRNA-seq gene expression data. Results: These high coverage methylation maps were used to identify HMRs in both cell types. A total of 2.91% of the genome are in keratinocyte HMRs, and 2.15% of the genome are in fibroblast HMRs with 1.75% being common. Half of the TS-HMRs are extensions of common HMRs, and the remaining are unique TS-HMRs. Four levels of CG methylation are observed: 1) total unmethylation for CG dinucleotides in HMRs in CGIs that are active in all tissues; 2) 10% to 40% methylation for TS-HMRs; 3) 60% methylation for TS-HMRs in cells types where they are not in HMRs; and 4) 70% methylation for the nonfunctioning part of the genome. SINE elements are depleted inside the TS-HMRs, while highly enriched in the surrounding regions. Hypomethylation at the last exon shows gene repression, while demethylation toward the gene body positively correlates with gene expression.
    [Show full text]
  • Functional Characterization of CNOT3 Variants Identified in Familial Adenomatous Polyposis Adenomas
    www.oncotarget.com Oncotarget, 2019, Vol. 10, (No. 39), pp: 3939-3951 Research Paper Functional characterization of CNOT3 variants identified in familial adenomatous polyposis adenomas Richard Glenn C. Delacruz1, Imelda T. Sandoval1, Kyle Chang2,7, Braden N. Miller1,8, Laura Reyes-Uribe2, Ester Borras2, Patrick M. Lynch3,6, Melissa W. Taggart4, Ernest T. Hawk2, Eduardo Vilar2,5,6,7,* and David A. Jones1,* 1Functional and Chemical Genomics, Oklahoma Medical Research Foundation, Oklahoma City, OK, USA 2Department of Clinical Cancer Prevention, The University of Texas UTHealth MD Anderson Cancer Center, Houston, TX, USA 3Department of Gastroenterology, Hepatology and Nutrition, The University of Texas UTHealth MD Anderson Cancer Center, Houston, TX, USA 4Department of Pathology, The University of Texas UTHealth MD Anderson Cancer Center, Houston, TX, USA 5Department of GI Medical Oncology, The University of Texas UTHealth MD Anderson Cancer Center, Houston, TX, USA 6Clinical Genetics Program, The University of Texas UTHealth MD Anderson Cancer Center, Houston, TX, USA 7Graduate School of Biomedical Sciences, The University of Texas UTHealth MD Anderson Cancer Center, Houston, TX, USA 8College of Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA *These authors contributed equally to this work Correspondence to: David A. Jones, email: [email protected] Eduardo Vilar, email: [email protected] Keywords: familial adenomatous polyposis; colon cancer; APC; CNOT3; CtBP1 Received: April 16, 2019 Accepted: May 20, 2019 Published: June 11, 2019 Copyright: Delacruz et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License 3.0 (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
    [Show full text]
  • 13300 CNOT3 (E1L9S) Rabbit Mab
    Revision 1 C 0 2 - t CNOT3 (E1L9S) Rabbit mAb a e r o t S Orders: 877-616-CELL (2355) [email protected] 0 Support: 877-678-TECH (8324) 0 3 Web: [email protected] 3 www.cellsignal.com 1 # 3 Trask Lane Danvers Massachusetts 01923 USA For Research Use Only. Not For Use In Diagnostic Procedures. Applications: Reactivity: Sensitivity: MW (kDa): Source/Isotype: UniProt ID: Entrez-Gene Id: WB, IP H Endogenous 105 Rabbit IgG O75175 4849 Product Usage Information 4. Zheng, X. et al. (2012) Stem Cells 30, 910-22. 5. Takahashi, A. et al. (2012) Biochem Biophys Res Commun 419, 268-73. Application Dilution 6. Venturini, G. et al. (2012) PLoS Genet 8, e1003040. 7. De Keersmaecker, K. et al. (2013) Nat Genet 45, 186-90. Western Blotting 1:1000 Immunoprecipitation 1:50 Storage Supplied in 10 mM sodium HEPES (pH 7.5), 150 mM NaCl, 100 µg/ml BSA, 50% glycerol and less than 0.02% sodium azide. Store at –20°C. Do not aliquot the antibody. Specificity / Sensitivity CNOT3 (E1L9S) Rabbit mAb recognizes endogenous levels of total CNOT3 protein. Species Reactivity: Human Species predicted to react based on 100% sequence homology: Mouse, Rat Source / Purification Monoclonal antibody is produced by immunizing animals with a synthetic peptide corresponding to residues surrounding Leu638 of human CNOT3 protein. Background The evolutionarily conserved CCR4-NOT (CNOT) complex regulates mRNA metabolism in eukaryotic cells (1). This regulation occurs at different levels of mRNA synthesis and degradation, including transcription initiation, elongation, deadenylation, and degradation (1). Multiple components, including CNOT1, CNOT2, CNOT3, CNOT4, CNOT6, CNOT6L, CNOT7, CNOT8, CNOT9, and CNOT10 have been identified in this complex (2).
    [Show full text]
  • A Novel Mutation in PRPF31, Causative of Autosomal Dominant Retinitis Pigmentosa, Using the BGISEQ-500 Sequencer
    Int J Ophthalmol, Vol. 11, No. 1, Jan.18, 2018 www.ijo.cn Tel:8629-82245172 8629-82210956 Email:[email protected] ·Basic Research· A novel mutation in PRPF31, causative of autosomal dominant retinitis pigmentosa, using the BGISEQ-500 sequencer Yu Zheng1,2,3, Hai-Lin Wang4, Jian-Kang Li2,3, Li Xu4, Laurent Tellier2,3, Xiao-Lin Li4, Xiao-Yan Huang1,2,3, Wei Li2,3, Tong-Tong Niu4, Huan-Ming Yang2,5, Jian-Guo Zhang2,3, Dong-Ning Liu4 1BGI Education Center, University of Chinese Academy of probands, as well as upon other family members. This Sciences, Shenzhen 518083, China novel, pathogenic genotype co-segregated with retinitis 2 BGI-Shenzhen, Shenzhen 518083, China pigmentosa phenotype in these two families. 3 China National GeneBank, BGI-Shenzhen, Shenzhen 518120, ● CONCLUSION: ADRP is a subtype of retinitis pigmentosa, China defined by its genotype, which accounts for 20%-40% 4 The Fourth People's Hospital of Shenyang, Shenyang 110031, of the retinitis pigmentosa patients. Our study thus Liaoning Province, China expands the spectrum of PRPF31 mutations known to 5 James D. Watson Institute of Genome Sciences, Hangzhou occur in ADRP, and provides further demonstration of the 310058, China applicability of the BGISEQ500 sequencer for genomics Co-first authors: Yu Zheng and Hai-Lin Wang research. Correspondence to: Dong-Ning Liu. The Fourth People's ● KEYWORDS: retinitis pigmentosa; PRPF31; BGISEQ-500 Hospital of Shenyang, Shenyang 110031, Liaoning Province, DOI:10.18240/ijo.2018.01.06 China. [email protected]; Jian-Guo Zhang. China National GeneBank, BGI-Shenzhen, Shenzhen 518120, China. Citation: Zheng Y, Wang HL, Li JK, Xu L, Tellier L, Li XL, Huang [email protected] XY, Li W, Niu TT, Yang HM, Zhang JG, Liu DN.
    [Show full text]
  • Dominant PRPF31 Mutations Are Hypostatic to a Recessive CNOT3 Polymorphism in Retinitis Pigmentosa: a Novel Phenomenon of “Linked Trans-Acting Epistasis”
    Short Communication doi: 10.1111/ahg.12042 Dominant PRPF31 Mutations Are Hypostatic to a Recessive CNOT3 Polymorphism in Retinitis Pigmentosa: A Novel Phenomenon of “Linked Trans-Acting Epistasis” Anna M. Rose1 ∗,AmnaZ.Shah1, Giulia Venturini2, Carlo Rivolta2, Geoffrey E. Rose3 and Shomi S. Bhattacharya1 1Department of Genetics, UCL Institute of Ophthalmology, London, United Kingdom 2Department of Medical Genetics, University of Lausanne, Lausanne, Switzerland 3BRC, NIHR Institute of Ophthalmology, London, United Kingdom Summary Mutations in PRPF31 are responsible for autosomal dominant retinitis pigmentosa (adRP, RP11 form) and affected families show nonpenetrance. Differential expression of the wildtype PRPF31 allele is responsible for this phenomenon: coinheritance of a mutation and a higher expressing wildtype allele provide protection against development of disease. It has been suggested that a major modulating factor lies in close proximity to the wildtype PRPF31 gene on Chromosome 19, implying that a cis-acting factor directly alters PRPF31 expression. Variable expression of CNOT3 is one determinant of PRPF31 expression. This study explored the relationship between CNOT3 (a trans-acting factor) and its paradoxical cis-acting nature in relation to RP11. Linkage analysis on Chromosome 19 was performed in mutation-carrying families, and the inheritance of the wildtype PRPF31 allele in symptomatic–asymptomatic sibships was assessed—confirming that differential inheritance of wildtype chromosome 19q13 determines the clinical phenotype
    [Show full text]
  • Human Ccr4 and Caf1 Deadenylases Regulate Proliferation and Tumorigenicity of Human Gastric Cancer Cells Via Modulating Cell Cycle Progression
    cancers Article Human Ccr4 and Caf1 Deadenylases Regulate Proliferation and Tumorigenicity of Human Gastric Cancer Cells via Modulating Cell Cycle Progression Xiao-Hui Song 1,† , Xiao-Yan Liao 1,†, Xu-Ying Zheng 1, Jia-Qian Liu 1, Zhe-Wei Zhang 1, Li-Na Zhang 2,* and Yong-Bin Yan 1,* 1 State Key Laboratory of Membrane Biology, School of Life Sciences, Tsinghua University, Beijing 100084, China; [email protected] (X.-H.S.); [email protected] (X.-Y.L.); [email protected] (X.-Y.Z.); [email protected] (J.-Q.L.); [email protected] (Z.-W.Z.) 2 College of Life Science and Chemistry, Faculty of Environment and Life, Beijing University of Technology, Beijing 100124, China * Correspondence: [email protected] (L.-N.Z.); [email protected] (Y.-B.Y.); Tel.: +86-10-6739-6342 (L.-N.Z.); +86-10-6278-3477 (Y.-B.Y.) † These authors contributed equally to this work. Simple Summary: Cancer cells generally reprogram their gene expression profiles to satisfy continu- ous growth, proliferation, and metastasis. Most eukaryotic mRNAs are degraded in a deadenylation- dependent pathway, in which deadenylases are the key enzymes. We found that human Ccr4 (hCcr4a/b) and Caf1 (hCaf1a/b), the dominant cytosolic deadenylases, were dysregulated in several Citation: Song, X.-H.; Liao, X.-Y.; types of cancers including stomach adenocarcinoma. Stably knocking down hCaf1a/b or hCcr4a/b Zheng, X.-Y.; Liu, J.-Q.; Zhang, Z.-W.; blocks cell cycle progression by enhancing the levels of cell cycle inhibitors and by inhibiting the Zhang, L.-N.; Yan, Y.-B.
    [Show full text]
  • Functional Analysis of CCR4-NOT Complex in Pancreatic Β Cell
    Functional Analysis of CCR4-NOT Complex in Pancreatic β Cell Author Dina Mostafa Degree Conferral 2020-02-29 Date Degree Doctor of Philosophy Degree Referral 38005甲第43号 Number Copyright (C) 2020 The Author. Information URL http://doi.org/10.15102/1394.00001210 Okinawa Institute of Science and Technology Graduate University Thesis submitted for the degree Doctor of Philosophy Functional Analysis of CCR4-NOT Complex in Pancreatic β Cell by Dina Mostafa Under the Supervision of: Prof. Dr. Tadashi Yamamoto February 2020 i Declaration of Original and Sole Authorship I, Dina Mostafa Abdel Azim Mostafa, declare that this thesis entitled “Functional analysis of CCR4-NOT complex in pancreatic β cell” and the data presented in it are original and my own work. I confirm that: • This work was done solely while a candidate for the research degree at the Okinawa Institute of Science and Technology Graduate University, Japan. • No part of this work has previously been submitted for a degree at this or any other university. • References to the work of others have been clearly attributed. Quotations from the work of others have been clearly indicated and attributed to them. • In cases where others have contributed to part of this work, such contribution has been clearly acknowledged and distinguished from my own work. • None of this work has been previously published elsewhere with the exception of the following: Dina Mostafa, Akinori Takahashi, Akiko Yanagiya, Tomokazu Yamaguchi, Takaya Abe, Taku Kureha, Keiji Kuba, Yumi Kanegae, Yasuhide Furuta, Tadashi Yamamoto and Toru Suzuki. Essential functions of the CNOT7/8 catalytic subunits of the CCR4-NOT complex in mRNA regulation and cell viability.
    [Show full text]
  • Proteomic Analysis Uncovers Measles Virus Protein C
    bioRxiv preprint doi: https://doi.org/10.1101/2020.05.08.084418; this version posted May 9, 2020. 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. Proteomic Analysis Uncovers Measles Virus Protein C Interaction with p65/iASPP/p53 Protein Complex Alice Meignié1,2*, Chantal Combredet1*, Marc Santolini 3,4, István A. Kovács4,5,6, Thibaut Douché7, Quentin Giai Gianetto 7,8, Hyeju Eun9, Mariette Matondo7, Yves Jacob10, Regis Grailhe9, Frédéric Tangy1**, and Anastassia V. Komarova1, 10** 1 Viral Genomics and Vaccination Unit, Department of Virology, Institut Pasteur, CNRS UMR-3569, 75015 Paris, France 2 Université Paris Diderot, Sorbonne Paris Cité, Paris, France 3 Center for Research and Interdisciplinarity (CRI), Université de Paris, INSERM U1284 4 Network Science Institute and Department of Physics, Northeastern University, Boston, MA 02115, USA 5 Department of Physics and Astronomy, Northwestern University, Evanston, IL 60208-3109, USA 6 Department of Network and Data Science, Central European University, Budapest, H-1051, Hungary 7 Proteomics platform, Mass Spectrometry for Biology Unit (MSBio), Institut Pasteur, CNRS USR 2000, Paris, France. 8 Bioinformatics and Biostatistics Hub, Computational Biology Department, Institut Pasteur, CNRS USR3756, Paris, France 9 Technology Development Platform, Institut Pasteur Korea, Seongnam-si, Republic of Korea 10 Laboratory of Molecular Genetics of RNA Viruses, Institut Pasteur, CNRS UMR-3569,
    [Show full text]