DOCSLIB.ORG

List of Primer Oligos for Qpcr Analysis Gene Forward

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
List of Primer Oligos for Qpcr Analysis Gene Forward SUPPLEMENTARY DATA Supplementary Table 1: List of Primer Oligos for qPCR analysis Gene Forward (5’->3’) Reverse (5’->3’) HPRT1 GAAAAGGACCCCACGAAGTGT AGTCAAGGGCATATCCTACAA B2M TGTCTTTCAGCAAGGACTGG AGCAAGCAAGCAGAATTTGG RPLP0 TGTTTCATTGTGGGAGCAGA GAACACAAAGCCCACATTCC GAPDH TGCACCACCAACTGCTTAGC GGCATGGACTGTGGTCATGAG DAPK3 AATCTGAGGAGCTGGGTTGC TCCAGGGAAAGTGCAGTCAC ATP2A3 AGTGCTCCGAAGACAACCC GTTCTCCGAGACGCTGTTG PPIB ATGTAGGCCGGGTGATCTTT CATCTCCCCTGGTGAAGTCT TBP AGTTCTGGGATTGTACCGCA TATATTCGGCGTTTCGGGCA mRNA was harvested from cultured myotubesusing a kit (E.Z.N.A. Total RNA Kit 1, Omega bio-tek, Norcross, GA). Reverse transcription and quantitative PCR were carried out using MultiScribe Reverse Transcriptase and Fast SYBR Green Master Mix, respectively (Thermo Fisher Scientific). Gene expression of ATP2A3, DAPK3, and reference genes (PPIB, TBP) was assessed using self-designed oligonucleotides (Sigma-Aldrich). ©2016 American Diabetes Association. Published online at http://diabetes.diabetesjournals.org/lookup/suppl/doi:10.2337/db16-0882/-/DC1 SUPPLEMENTARY DATA Supplementary Table 2: List of Antibodies used for Western-blot analysis Target Vendor Product Number PKB p-Thr-308 Cell Signaling (Danvers, MA) 4056 PKB total Cell Signaling 9272 TBC1D4 p-Ser-318 Cell Signaling 8619 TBC1D4 total Merck Millipore (Billerica, MA) 07-741 p62 Sigma-Aldrich P0067 LC3 Sigma-Aldrich L8918 GAPDH Santa Cruz Biotechnology (Dallas, TX) sc-257758 Myotube lysates were diluted in Laemmli buffer (60 mMtris base at pH 6.8, 2% w/v SDS, 10% v/v glycerol, 0.01% w/v bromophenol blue, 1.25% v/v β-mercaptoethanol). SDS-PAGE was conducted using pre-cast tris-HCl and tris-bis gels with tris/glycine/SDS or 2-(N-morpholino)ethanesulfonic acid running buffers, respectively (Bio-Rad). Proteins were transferred to Immobilon-P PVDF membranes (Merck Millipore). Equal loading of protein between samples was assessed by Ponceau staining (Sigma- Aldrich) or fluorescent-detection in the case of stain-free gels (Bio-Rad). Membranes were washed in tris-buffered saline (TBS) with Tween-20 (Sigma-Aldrich) (TBST) (20 mMtris at pH 7.6, 137 mMNaCl, 0.02% v/v Tween-20). Membranes were blocked in 7.5% non-fat dry milk, washed again in TBST, then incubated with primary antibodies overnight at 4°C (1:1000 in TBS with 0.1% w/v bovine serum albumin, 0.1% w/v NaN3). Membranes were washed again in TBST, incubated with horseradish peroxidase-conjugated secondary antibodies (1:25000 in TBST with 4% NFDM; Thermo Fisher Scientific) for 1-2 hours at room temperature and then washed in TBST. Immunolabeled bands were visualized using extended chemiluminescence reagents (GE Healthcare) and autoradiograms were quantitated by scanning densitometry using Image Lab software (Bio-Rad). ©2016 American Diabetes Association. Published online at http://diabetes.diabetesjournals.org/lookup/suppl/doi:10.2337/db16-0882/-/DC1 SUPPLEMENTARY DATA Supplementary Table 3: t-tests (unpaired & paired, 2-sided Gene Name RELATION_TO_ M value Beta value name of the UCSC_CPG_ISLA target_ID difference difference p_unpaired p_paired closest gene UCSC_REFGENE_GROUP UCSC_CPG_ISLANDS_NAME ND cg03312587 -0.2728 0.0361 0.0122 0.0207 A2BP1 5'UTR;5'UTR;5'UTR cg20307184 0.6291 -0.0475 0.0287 0.0113 ABCA13 Body cg07372195 0.9867 -0.0462 0.0111 0.0239 ABCA5 5'UTR;1stExon;5'UTR cg14647845 0.4657 -0.0323 0.0181 0.0040 ABLIM2 Body;Body;Body;Body;Body;Body;Body cg20497635 1.0417 -0.0930 0.0345 0.0094 ABR Body;Body;Body cg13686847 -0.4127 0.0310 0.0203 0.0239 ACACB Body cg06698843 -0.5306 0.0403 0.0314 0.0164 ACADS Body chr12:121177115-121177341 N_Shelf cg07343187 -0.8390 0.0336 0.0399 0.0498 ACAN Body;Body cg16380285 -0.6346 0.0318 0.0106 0.0139 ACAP3 3'UTR chr1:1228780-1230163 N_Shore cg04854749 -0.2989 0.0420 0.0002 0.0006 ACIN1 Body;Body;Body;Body;Body chr14:23528360-23528582 S_Shore cg22402043 0.7627 -0.0487 0.0272 0.0044 ACP6 Body chr1:147141842-147142918 N_Shelf cg17541674 -0.3461 0.0661 0.0095 0.0113 ACPT Body chr19:51294876-51295098 S_Shore TSS1500;TSS1500;TSS1500;TSS1500;TSS150 cg07665222 0.5427 -0.0509 0.0032 0.0095 ACRV1 0;TSS1500;TSS1500;TSS1500;TSS1500 cg04252928 0.4396 -0.0412 0.0491 0.0049 ACSF3 Body;Body;Body chr16:89167116-89167482 S_Shore cg02009395 0.3747 -0.0423 0.0490 0.0246 ACSM1 TSS200 cg03369957 0.5781 -0.0794 0.0448 0.0469 ACTL6B Body chr7:100253782-100254150 N_Shore cg18862171 0.7014 -0.0449 0.0088 0.0009 ACTN3 TSS200;TSS1500 chr11:66314207-66314455 Island cg04738270 0.7167 -0.0537 0.0053 0.0172 ACTR1A Body chr10:104262224-104262524 N_Shore cg21577356 -0.4103 0.0406 0.0038 0.0046 ACTR3C TSS1500;5'UTR;5'UTR chr7:150019950-150020752 S_Shore cg04892170 0.7435 -0.0300 0.0232 0.0108 ADAM12 1stExon;5'UTR;5'UTR;1stExon chr10:128076155-128077482 Island cg05847038 0.7683 -0.0500 0.0405 0.0247 ADAM7 Body cg16451601 0.7209 -0.0577 0.0234 0.0446 ADAMTS2 Body;Body cg01260219 -0.3110 0.0414 0.0019 0.0295 ADAMTS8 TSS1500 chr11:130297401-130298517 S_Shore cg21170978 0.7111 -0.0340 0.0454 0.0314 ADAMTSL1 Body cg01629749 0.4718 -0.0651 0.0323 0.0262 ADAP1 Body chr7:959724-959959 Island cg04233620 -0.8087 0.0847 0.0106 0.0195 ADARB1 Body;Body;Body;Body;Body;Body;Body cg00615654 0.8293 -0.0706 0.0081 0.0201 ADARB2 Body chr10:1382500-1383006 N_Shore cg11637718 -0.4758 0.0424 0.0004 0.0063 ADCY9 Body chr16:4029157-4029413 Island ©2016 American Diabetes Association. Published online at http://diabetes.diabetesjournals.org/lookup/suppl/doi:10.2337/db16-0882/-/DC1 SUPPLEMENTARY DATA cg16230755 -0.3191 0.0309 0.0243 0.0312 ADD3 5'UTR;5'UTR;5'UTR cg05727225 -0.3990 0.0446 0.0207 0.0274 ADM Body chr11:10327013-10329831 Island cg25320816 -0.3776 0.0529 0.0130 0.0168 ADPRHL1 5'UTR;Body chr13:114096050-114096317 S_Shelf cg11367939 -0.4440 0.0361 0.0099 0.0220 ADRA2A 3'UTR;1stExon chr10:112835990-112839303 Island cg22275864 0.7223 -0.0492 0.0303 0.0395 ADRB3 Body chr8:37822486-37824008 Island cg16389474 0.5792 -0.0369 0.0241 0.0009 ADRM1 5'UTR;5'UTR chr20:60877499-60879008 Island cg10028549 -0.3009 0.0419 0.0319 0.0136 AFAP1 TSS1500;TSS1500 chr4:7940563-7941853 S_Shore cg02441982 0.6113 -0.0419 0.0234 0.0015 AFMID Body;TSS1500;Body;Body chr17:76183077-76183449 S_Shore cg27436044 -0.3079 0.0301 0.0104 0.0095 AGA Body chr4:178363239-178363708 N_Shelf cg13018278 -0.1426 0.0359 0.0461 0.0030 AGAP1 Body;Body chr2:237028848-237029121 Island cg22199080 -0.5048 0.0814 0.0437 0.0293 AGAP2 1stExon chr12:58130870-58132047 S_Shelf cg01338043 -0.4313 0.0608 0.0176 0.0379 AGFG2 TSS1500 chr7:100136448-100136919 N_Shore cg20352108 0.5140 -0.0536 0.0270 0.0010 AGPAT4 5'UTR cg03120284 -0.8278 0.0888 0.0464 0.0191 AGRN Body chr1:990274-990694 N_Shelf cg09745307 0.5330 -0.0353 0.0040 0.0250 AGXT2 TSS1500 cg04911680 0.5029 -0.0316 0.0216 0.0013 AHDC1 5'UTR chr1:27894927-27895524 Island cg21267167 0.3733 -0.0387 0.0094 0.0034 AJAP1 Body;Body cg17181543 0.5245 -0.0303 0.0451 0.0229 AK5 TSS1500 chr1:77747314-77748224 N_Shore cg27090975 0.2071 -0.0339 0.0223 0.0156 AKAP8L Body chr19:15512025-15512393 S_Shelf cg24455383 -0.3794 0.0748 0.0257 0.0052 AKT3 Body;Body cg14469290 1.0575 -0.1133 0.0332 0.0092 ALAD TSS1500 chr9:116163208-116163848 S_Shore cg16086130 -0.9008 0.0976 0.0047 0.0043 ALDH1A3 TSS1500 chr15:101419261-101421133 Island cg02946394 -0.3862 0.0407 0.0423 0.0431 ALOXE3 Body;Body chr17:8012474-8012846 N_Shore cg11441891 0.7929 -0.0395 0.0192 0.0019 ALS2CL TSS1500;Body cg02562052 1.6860 -0.1228 0.0044 0.0270 ALS2CR4 TSS200;TSS1500 chr2:202507139-202508270 S_Shore cg16893614 0.7877 -0.0554 0.0199 0.0398 ALX3 TSS1500 chr1:110610265-110613303 S_Shore cg00268840 -1.0339 0.0505 0.0249 0.0359 ALX4 TSS1500 chr11:44332314-44332757 Island cg21101750 0.6357 -0.0596 0.0334 0.0231 AMBRA1 TSS1500 chr11:46615197-46615664 N_Shore cg01636354 -0.4430 0.0731 0.0046 0.0421 AMOTL2 Body chr3:134080390-134080596 N_Shore cg12756093 -0.4006 0.0754 0.0015 0.0065 AMPD1 TSS1500 cg24435741 -0.4782 0.0454 0.0246 0.0204 AMPD3 TSS1500 chr11:10472000-10472857 N_Shore Body;5'UTR;1stExon;3'UTR;1stExon;1stExon cg02251567 -0.3202 0.0745 0.0044 0.0271 AMT ;5'UTR;5'UTR;1stExon;5'UTR ©2016 American Diabetes Association. Published online at http://diabetes.diabetesjournals.org/lookup/suppl/doi:10.2337/db16-0882/-/DC1 SUPPLEMENTARY DATA cg01186212 0.6372 -0.0340 0.0421 0.0175 ANK3 Body cg14455319 0.2916 -0.0431 0.0375 0.0181 ANKK1 Body chr11:113258443-113258821 S_Shore cg04035353 -0.6295 0.0497 0.0055 0.0178 ANKRD11 Body chr16:89334574-89335088 S_Shore cg13718961 0.3988 -0.0332 0.0200 0.0188 ANKRD13B Body chr17:27939298-27940770 N_Shore cg01635821 0.5661 -0.0347 0.0476 0.0114 ANKRD46 5'UTR chr8:101571515-101572104 N_Shore cg00515408 0.6839 -0.0569 0.0034 0.0258 ANKS1B 5'UTR;1stExon chr12:100378243-100378582 N_Shore cg14938313 -0.4778 0.0431 0.0337 0.0176 ANO1 Body;Body cg15476875 0.6279 -0.0463 0.0054 0.0222 ANO4 Body cg00363845 0.5519 -0.0836 0.0162 0.0446 ANO8 TSS1500 chr19:17443965-17444633 S_Shore cg05998672 0.4527 -0.0316 0.0426 0.0030 AP2A2 Body cg01632240 -0.1981 0.0307 0.0155 0.0067 AP3M2 TSS1500;TSS1500 chr8:42009723-42011098 N_Shore cg14907738 0.3881 -0.0316 0.0092 0.0207 APC2 Body chr19:1456077-1456347 Island cg03624661 -0.7388 0.0314 0.0005 0.0159 APH1B TSS1500;TSS1500 chr15:63569296-63570100 Island cg16353361 -0.5892 0.0507 0.0143 0.0123 APLN TSS1500 chrX:128788003-128789195 S_Shore cg13880303 0.4886 -0.1007 0.0280 0.0195 APOC1 TSS200 cg20691580 -0.5979 0.0348 0.0093 0.0495 APOC3 5'UTR cg04006839 -0.5281 0.0373 0.0152 0.0237 APOH 1stExon cg19599611 0.5928 -0.0369 0.0274 0.0423 AQR 3'UTR cg09120188 0.6820 -0.0357 0.0227 0.0275 ARHGAP23 Body cg15368044 -0.2989 0.0409 0.0408 0.0050
Load more

Recommended publications
  • Evolution, Expression and Meiotic Behavior of Genes Involved in Chromosome Segregation of Monotremes
    G C A T T A C G G C A T genes Article Evolution, Expression and Meiotic Behavior of Genes Involved in Chromosome Segregation of Monotremes Filip Pajpach , Linda Shearwin-Whyatt and Frank Grützner * School of Biological Sciences, The University of Adelaide, Adelaide, SA 5005, Australia; fi[email protected] (F.P.); [email protected] (L.S.-W.) * Correspondence: [email protected] Abstract: Chromosome segregation at mitosis and meiosis is a highly dynamic and tightly regulated process that involves a large number of components. Due to the fundamental nature of chromosome segregation, many genes involved in this process are evolutionarily highly conserved, but duplica- tions and functional diversification has occurred in various lineages. In order to better understand the evolution of genes involved in chromosome segregation in mammals, we analyzed some of the key components in the basal mammalian lineage of egg-laying mammals. The chromosome passenger complex is a multiprotein complex central to chromosome segregation during both mitosis and meio- sis. It consists of survivin, borealin, inner centromere protein, and Aurora kinase B or C. We confirm the absence of Aurora kinase C in marsupials and show its absence in both platypus and echidna, which supports the current model of the evolution of Aurora kinases. High expression of AURKBC, an ancestor of AURKB and AURKC present in monotremes, suggests that this gene is performing all necessary meiotic functions in monotremes. Other genes of the chromosome passenger complex complex are present and conserved in monotremes, suggesting that their function has been preserved Citation: Pajpach, F.; in mammals.
    [Show full text]
  • Detection Rate. FC: Fold Change. GO: Gene Ontology. AUC: Area Under
    Figure S1. Flow chart of the study. DR: detection rate. FC: fold change. GO: Gene Ontology. AUC: area under curve. KEGG: Kyoto Encyclopedia of Genes and Genomes. GEO: Gene Expression Omnibus. Figure S2. Independent validation of miRNAs and the classifier. A, ΔCt of 6 selected miRNAs in the independent cohort. *, P < 0.05. **, P < 0.01. ***, P < 0.001. B, Receiver operating curve of the classifier in the independent cohort. AUC: area under curve. Figure S3. Venn of predicted target genes from 3 platforms. Figure S4. GO enrichment analysis. GO: Gene Ontology. Table S1. miRNA expression profile in screening stage. Table S2. miRNA expression profile in validation stage. Table S3. Efficacy of the classifier. Table S4. miRNA expression profile in independent validation stage. Table S5. Predicted target genes. Table S6a. KEGG enrichment analysis. KEGG: Kyoto Encyclopedia of Genes and Genomes. Table S6b. GO_BP enrichment analysis. GO: Gene Ontology. BP: Biological Process. Table S6c. GO_CC enrichment analysis. CC: Cellular Component. Table S6d. GO_MF enrichment analysis. MF: Molecular Function. Table S7. GEO expression array datasets involved in this study. GEO: Gene Expression Omnibus. Table S8a. Predicted target genes covered by the selected GEO datasets. GEO: Gene Expression Omnibus. 1 Table S8b. Expression profiles of predicted target genes of hsa-miR-26b-5p in GEO datasets. Table S8c. Expression profiles of predicted target genes of hsa-miR-146b-5p in GEO datasets. Table S8d. Expression profiles of predicted target genes of hsa-miR-191-5p in GEO datasets. Table S8e. Expression profiles of predicted target genes of hsa-miR-484 in GEO datasets.
    [Show full text]
  • Flotillin 1 Antibody (R31142)
    Flotillin 1 Antibody (R31142) Catalog No. Formulation Size R31142 0.5mg/ml if reconstituted with 0.2ml sterile DI water 100 ug Bulk quote request Availability 1-3 business days Species Reactivity Human, Mouse, Rat Format Antigen affinity purified Clonality Polyclonal (rabbit origin) Isotype Rabbit IgG Purity Antigen affinity Buffer Lyophilized from 1X PBS with 2.5% BSA and 0.025% sodium azide/thimerosal UniProt O75955 Applications Western blot : 0.5-1ug/ml Limitations This Flotillin 1 antibody is available for research use only. Western blot testing of Flotillin 1 antbody; Lane 1: rat lung; 2: (r) brain; 3: (r) ovary; 4: human SMMC-7721; 5: (h) MFC-7 cell lysate. Expected/observed molecular weight ~49kDa. Description Flotillin 1 is a protein that in humans is encoded by the FLOT1 gene. The International Radiation Hybrid Mapping Consortium mapped the gene to chromosome 6. Bickel et al.(1997) found that mouse Flot1 behaves as a resident integral membrane protein of caveolae. It consistently copurified with Flot2 and with caveolin-1 in the purification of caveolin-rich membranes. Hazarika et al.(1999) found that stable transfection of Flot1, which they called ESA/flotillin-2, in COS-1 cells induced filopodia formation and changed the epithelial morphology to that of neuronal cells. Santamaria et al.(2005) found that prostate tumor overexpressed gene-1 interacted with Flotillin1 in detergent-insoluble membrane fractions. Flotillin1 colocalized with PTOV1 at the plasma membrane and in the nucleus, and it entered the nucleus concomitant with PTOV1 shortly before initiation of S phase. Application Notes The stated application concentrations are suggested starting amounts.
    [Show full text]
  • Snipa Snpcard
    SNiPAcard Block annotations Block info genomic range chr6:29,970,960-30,792,117 block size 821,158 bp variant count 107 variants Basic features Conservation/deleteriousness Linked genes μ = -0.141 [-3.802 – ABCF1 , AL662797.1 , AL662800.2 , ATAT1 , C6orf136 , DHX16 , FLOT1 4.141] , GNL1 , HCG17 , HCG18 , HCG19P , HCG20 , HCG4P3 , HLA-J , HLA-L , HLA-N , IER3 , LINC00243 , MDC1 , MICC , MRPS18B , NRM , PAIP1P1 , PPP1R10 , PPP1R11 , PPP1R18 , PTMAP1 , RN7SL353P , phyloP gene(s) hit or close-by RNF39 , RPP21 , SUCLA2P1 , TRIM10 , TRIM15 , TRIM26 , TRIM26BP , TRIM31 , TRIM31-AS1 , TRIM39 , TRIM39-RPP21 , TRIM40 , TUBB , UBQLN1P1 , XXbac-BPG252P9.10 , XXbac-BPG252P9.9 , XXbac-BPG283O16.9 , Y_RNA , ZNRD1 , ZNRD1-AS1 , ZNRD1-AS1_3 μ = 0.130 [0 – 1] BTN3A2 , BTN3A3 , C2 , CCHCR1 , CFB , FLOT1 , GABBR1 , HCG17 , HCG20 , HCG22 , HCP5 , HIST1H3I , HLA-A , HLA-B , HLA-C , HLA-F- AS1 , HLA-G , HLA-H , HLA-J , HLA-K , HLA-L , HLA-U , HLA-V , IER3 phastCons eQTL gene(s) , LINC00243 , MICB , NDUFS1 , OR5V1 , PPP1R18 , PSORS1C1 , RNF39 , RPP21 , TMEM154 , TRIM26BP , TRIM31 , TRIM39-RPP21 , VARS2 , WASF5P , ZFP57 , ZNRD1 , ZNRD1-AS1_3 μ = -0.462 [-9.98 – 5.1] ATAT1 , ATAT1 , ATAT1 , ATAT1 , ATAT1 , ATAT1 , ATAT1 , DDR1 , DDR1 , DDR1 , DDR1 , DDR1 , DDR1 , DDR1 , FLOT1 , FLOT1 , FLOT1 , FLOT1 , FLOT1 , FLOT1 , FLOT1 , FLOT1 , HCG19P , HCG19P potentially regulated , HCG19P , HCG19P , HCG19P , HCG19P , HCG19P , NRM , NRM , GERP++ gene(s) NRM , NRM , NRM , NRM , NRM , RNF39 , RNF39 , RNF39 , RNF39 , RNF39 , RNF39 , RNF39 , RNF39 , TRIM26 , TRIM26 , TRIM26
    [Show full text]
  • Evolutionarily Conserved Intercalated Disc Protein Tmem65 Regulates Cardiac Conduction and Connexin 43 Function
    ARTICLE Received 11 Aug 2014 | Accepted 18 Aug 2015 | Published 25 Sep 2015 DOI: 10.1038/ncomms9391 Evolutionarily conserved intercalated disc protein Tmem65 regulates cardiac conduction and connexin 43 function Parveen Sharma1,*, Cynthia Abbasi1,*, Savo Lazic2, Allen C.T. Teng1, Dingyan Wang1, Nicole Dubois3, Vladimir Ignatchenko4, Victoria Wong5, Jun Liu6, Toshiyuki Araki4, Malte Tiburcy7, Cameron Ackerley8, Wolfram H. Zimmermann7, Robert Hamilton8,11, Yu Sun6, Peter P. Liu9, Gordon Keller3, Igor Stagljar5, Ian C. Scott2,8,11, Thomas Kislinger4,10 & Anthony O. Gramolini1,11 Membrane proteins are crucial to heart function and development. Here we combine cationic silica-bead coating with shotgun proteomics to enrich for and identify plasma membrane-associated proteins from primary mouse neonatal and human fetal ventricular cardiomyocytes. We identify Tmem65 as a cardiac-enriched, intercalated disc protein that increases during development in both mouse and human hearts. Functional analysis of Tmem65 both in vitro using lentiviral shRNA-mediated knockdown in mouse cardiomyocytes and in vivo using morpholino-based knockdown in zebrafish show marked alterations in gap junction function and cardiac morphology. Molecular analyses suggest that Tmem65 interaction with connexin 43 (Cx43) is required for correct localization of Cx43 to the intercalated disc, since Tmem65 deletion results in marked internalization of Cx43, a shorter half-life through increased degradation, and loss of Cx43 function. Our data demonstrate that the membrane protein Tmem65 is an intercalated disc protein that interacts with and functionally regulates ventricular Cx43. 1 Department of Physiology, University of Toronto, Toronto General Hospital Research Institute, Toronto, Ontario, Canada M5G 1L7. 2 Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada M5S 1A8.
    [Show full text]
  • Fibroblasts from the Human Skin Dermo-Hypodermal Junction Are
    cells Article Fibroblasts from the Human Skin Dermo-Hypodermal Junction are Distinct from Dermal Papillary and Reticular Fibroblasts and from Mesenchymal Stem Cells and Exhibit a Specific Molecular Profile Related to Extracellular Matrix Organization and Modeling Valérie Haydont 1,*, Véronique Neiveyans 1, Philippe Perez 1, Élodie Busson 2, 2 1, 3,4,5,6, , Jean-Jacques Lataillade , Daniel Asselineau y and Nicolas O. Fortunel y * 1 Advanced Research, L’Oréal Research and Innovation, 93600 Aulnay-sous-Bois, France; [email protected] (V.N.); [email protected] (P.P.); [email protected] (D.A.) 2 Department of Medical and Surgical Assistance to the Armed Forces, French Forces Biomedical Research Institute (IRBA), 91223 CEDEX Brétigny sur Orge, France; [email protected] (É.B.); [email protected] (J.-J.L.) 3 Laboratoire de Génomique et Radiobiologie de la Kératinopoïèse, Institut de Biologie François Jacob, CEA/DRF/IRCM, 91000 Evry, France 4 INSERM U967, 92260 Fontenay-aux-Roses, France 5 Université Paris-Diderot, 75013 Paris 7, France 6 Université Paris-Saclay, 78140 Paris 11, France * Correspondence: [email protected] (V.H.); [email protected] (N.O.F.); Tel.: +33-1-48-68-96-00 (V.H.); +33-1-60-87-34-92 or +33-1-60-87-34-98 (N.O.F.) These authors contributed equally to the work. y Received: 15 December 2019; Accepted: 24 January 2020; Published: 5 February 2020 Abstract: Human skin dermis contains fibroblast subpopulations in which characterization is crucial due to their roles in extracellular matrix (ECM) biology.
    [Show full text]
  • Network Impact of the SERT Ala56 Coding Variant
    fnmol-13-00089 June 8, 2020 Time: 16:4 # 1 ORIGINAL RESEARCH published: 08 June 2020 doi: 10.3389/fnmol.2020.00089 Ex vivo Quantitative Proteomic Analysis of Serotonin Transporter Interactome: Network Impact of the SERT Ala56 Coding Variant Meagan A. Quinlan1,2,3, Matthew J. Robson4, Ran Ye2, Kristie L. Rose5, Kevin L. Schey5 and Randy D. Blakely2,6* 1 Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, United States, 2 Department of Pharmacology, Vanderbilt University, Nashville, TN, United States, 3 Department of Biomedical Science, Charles E. Schmidt College of Medicine, Florida Atlantic University, Jupiter, FL, United States, 4 Division of Pharmaceutical Sciences, James L. Winkle College of Pharmacy, University of Cincinnati, Cincinnati, OH, United States, 5 Department of Biochemistry, Vanderbilt University, Nashville, TN, United States, 6 Brain Institute, Florida Atlantic University, Jupiter, FL, United States Altered serotonin (5-HT) signaling is associated with multiple brain disorders, including major depressive disorder (MDD), obsessive-compulsive disorder (OCD), and autism spectrum disorder (ASD). The presynaptic, high-affinity 5-HT transporter (SERT) tightly regulates 5-HT clearance after release from serotonergic neurons in the brain and enteric nervous systems, among other sites. Accumulating evidence suggests that SERT is dynamically regulated in distinct activity states as a result of environmental and Edited by: Raul R. Gainetdinov, intracellular stimuli, with regulation perturbed by disease-associated coding variants. Saint Petersburg State University, Our lab identified a rare, hypermorphic SERT coding substitution, Gly56Ala, in Russia subjects with ASD, finding that the Ala56 variant stabilizes a high-affinity outward- Reviewed by: facing conformation (SERT∗) that leads to elevated 5-HT uptake in vitro and in vivo.
    [Show full text]
  • Table S1 Genes with Coefficients of Variation (CV) Ratios (CVGHS/CVSD) in the Upper and Lower 10% of for Expression in Genetic Hypercalciuric Stone-Forming (GHS) And
    Table S1 Genes with coefficients of variation (CV) ratios (CVGHS/CVSD) in the upper and lower 10% of for expression in Genetic Hypercalciuric Stone-forminG (GHS) and Sprague-Dawley (SD) rats, assayed usinG Affymetrix Rat Genome 230 GeneChips. The location of the microsatellite or quantitative trait locus (QTL) position (Loc) in base pairs (bp), gene initiation base pair (BP), chromosomal banding position and RGD or GenBank name are given.Rat Genome Database (RGD) (www.rgd.mcw.edu), GenBank (http://www.ncbi.nlm.nih.gov/Genbank/) and Entrez (http://www.ncbi.nlm.nih.gov/sites/entrez). Variance in gene expression was ranked according to CVGHS/CVSD ratio for all renal (8846 genes, Pctl, Renal) and duodenal genes (9038 genes, Pctl, Duod). Gene Pctl, Pctl, QTL Gene (GenBank) Renal Duod BP GenBank/RGD Description D1Mit95 Riok2 (BG371773) 91.3 52.4 55,897,246 RIO kinase 2 66,832,211 Tmc4 (BF545988) - 93.6 63,582,715 transmembrane channel-like gene family 4 Isoc2b (BM385414) 2.3 - 67,689,183 Isochorismatase domain containing 2b Suv420h2 (AW525235) 69.9 97.3 67,815,980 suppressor of variegation 4-20 homolog 2 (Drosophila) Lilrb4 (BF282961) 95.5 - 69,165,497 leukocyte immunoglobulin-like receptor, subfamily B, member 4 Zbtb45 (BI289556) - 10.0 72,912,203 zinc finger and BTB domain containing 45 Sepw1 (NM_013027) 7.5 - 76,249,869 selenoprotein W, muscle 1 Chmp2a (AW434104) 0.1 86.9 72,889,348 chromatin modifying protein 2a Tmem160 (AWS25031) 97.6 2.2 76,716,254 transmembrane protein Pnmal2 (BI282311) 99.6 - 77,277,341 PNMA-like 2 Dmpk (AI044427) 98.9 7.3 78,449,323 dystrophia myotonica-protein kinase; serine-threonine kinase Vasp (AW520792) 99.3 - 78,621,478 vasodilator-stimulated phosphoprotein Ercc1 (AA892791) 90.6 - 78,711,248 excision repair cross-complementing rodent repair deficiency, complementation G.
    [Show full text]
  • Plant Flotillins Are Required for Infection by Nitrogen-Fixing Bacteria
    Plant flotillins are required for infection by nitrogen-fixing bacteria Cara H. Haney and Sharon R. Long1 Department of Biology, Stanford University, Stanford, CA 94305-5020 Edited by Robert Haselkorn, University of Chicago, Chicago, IL, and approved November 12, 2009 (received for review September 2, 2009) To establish compatible rhizobial-legume symbioses, plant roots ponents of the proposed NF entry receptor pathway are currently support bacterial infection via host-derived infection threads (ITs). limited to NIN and LYK3; how LYK3 signaling is perceived and Here, we report the requirement of plant flotillin-like genes (FLOTs) translated into IT initiation is unknown. in Sinorhizobium meliloti infection of its host legume Medicago trun- Sinorhizobium meliloti, the nitrogen-fixing symbiont of Medi- catula. Flotillins in other organisms have roles in viral pathogenesis, cago (the alfalfa genus), is a close relative of the animal pathogen fi endocytosis, and membrane shaping. We identi ed seven FLOT Brucella. Sinorhizobium and Brucella have common genes re- genes in the M. truncatula genome and show that two, FLOT2 and quired for infection and invasion of their hosts (9). Given these FLOT4, are strongly up-regulated during early symbiotic events. This common features, we asked whether eukaryotic host-cell factors up-regulation depends on bacterial Nod Factor and the plant's ability required for infection might also be shared across kingdoms. to perceive Nod Factor. Microscopy data suggest that M. truncatula Upon uptake into host cells, Brucella remains surrounded by a FLOT2 and FLOT4 localize to membrane microdomains. Upon rhizo- fl bial inoculation, FLOT4 uniquely becomes localized to the tips of host-derived membrane, which contains the protein otillin (10).
    [Show full text]
  • Random Splicing of Several Exons Caused by a Single Base Change in the Target Exon of CRISPR/Cas9 Mediated Gene Knockout
    cells Article Random Splicing of Several Exons Caused by a Single Base Change in the Target Exon of CRISPR/Cas9 Mediated Gene Knockout Marcel Kapahnke, Antje Banning and Ritva Tikkanen * Institute of Biochemistry, Medical Faculty, University of Giessen, Friedrichstrasse 24, D-35392 Giessen, Germany; [email protected] (M.K.); [email protected] (A.B.) * Correspondence: [email protected]; Tel.: +49-641-9947-420 Academic Editor: Alexander E. Kalyuzhny Received: 20 October 2016; Accepted: 9 December 2016; Published: 14 December 2016 Abstract: The clustered regularly interspaced short palindromic repeats (CRISPR)-associated sequence 9 (CRISPR/Cas9) system is widely used for genome editing purposes as it facilitates an efficient knockout of a specific gene in, e.g. cultured cells. Targeted double-strand breaks are introduced to the target sequence of the guide RNAs, which activates the cellular DNA repair mechanism for non-homologous-end-joining, resulting in unprecise repair and introduction of small deletions or insertions. Due to this, sequence alterations in the coding region of the target gene frequently cause frame-shift mutations, facilitating degradation of the mRNA. We here show that such CRISPR/Cas9-mediated alterations in the target exon may also result in altered splicing of the respective pre-mRNA, most likely due to mutations of splice-regulatory sequences. Using the human FLOT-1 gene as an example, we demonstrate that such altered splicing products also give rise to aberrant protein products. These may potentially function as dominant-negative proteins and thus interfere with the interpretation of the data generated with these cell lines.
    [Show full text]
  • Analysis of Genomic Regions of Increased Gene Expression (RIDGE)S in Immune Activation
    Analysis of genomic Regions of IncreaseD Gene Expression (RIDGE)s in immune activation Lena Hansson Doctor of Philosophy Institute for Adaptive and Neural Computation School of Informatics and Division of Pathway Medicine Medical School University of Edinburgh 2009 Abstract A RIDGE (Region of IncreaseD Gene Expression), as defined by previous studies, is a con- secutive set of active genes on a chromosome that span a region around 110 kbp long. This study investigated RIDGE formation by focusing on the well-defined, immunological impor- tant MHC locus. Macrophages were assayed for gene expression levels using the Affymetrix MG-U74Av2 chip are were either 1) uninfected, 2) primed with IFN-g, 3) viral activated with mCMV, or 4) both primed and viral activated. Gene expression data from these conditions was studied using data structures and new software developed for the visualisation and handling of structured functional genomic data. Specifically, the data was used to study RIDGE structures and investigate whether physically linked genes were also functionally related, and exhibited co-expression and potentially co-regulation. A greater number of RIDGEs with a greater number of members than expected by chance were found. Observed RIDGEs featured functional associations between RIDGE members (mainly explored via GO, UniProt, and Ingenuity), shared upstream control elements (via PROMO, TRANSFAC, and ClustalW), and similar gene expression profiles. Furthermore RIDGE formation cannot be explained by sequence duplication events alone. When the analysis was extended to the entire mouse genome, it became apparent that known genomic loci (for example the protocadherin loci) were more likely to contain more and longer RIDGEs.
    [Show full text]
  • Membrane Partitioning by Flotillin-1 Facilitates Amphetamine-Induced Dopamine Transporter Activity
    Membrane partitioning by Flotillin-1 facilitates amphetamine-induced dopamine transporter activity Wendy Mei Fong Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy under the Executive Committee of the Graduate School of Arts and Sciences COLUMBIA UNIVERSITY 2017 © 2017 Wendy Mei Fong All rights reserved ABSTRACT Membrane partitioning by Flotillin-1 facilitates amphetamine-induced dopamine transporter activity Wendy Mei Fong Cellular membranes were once considered static and passive structures, but are now appreciated as a fluidic and dynamic assembly of macromolecules that play an active role in cellular function. Membrane composition has been proposed to play a critical role in modulating protein function by affecting everything from post-translational modifications to conformation, but the physiologic relevance of the relationship between protein and membrane has been difficult to establish. For example, membrane-associated proteins such as Flotillin-1 (Flot1) have been implicated to scaffold proteins into cholesterol-rich membranes, as well as play a role in a wide array of functions such as endocytosis and axon pathfinding; however, genetic elimination of Flot1 expression had little to no reported consequence, leaving to question the physiologic importance of scaffolding proteins to membrane microdomains. Using genetic and biochemical approaches, I sought to understand how the immediate lipid environment can influence the function of a transmembrane protein, and how this might impact brain function. Specifically, I examined how a cholesterol-rich environment can affect the function of the cell surface neurotransmitter transporter for dopamine, the dopamine transporter (DAT), and how this interaction may influence the ability of an organism to respond to the psychostimulant amphetamine (AMPH).
    [Show full text]