Multiparameter Functional Diversity of Human C2H2 Zinc Finger Proteins
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Figure 2S 4 7 A - C 080125 CSCs 080418 CSCs - + IFN-a 48 h + IFN-a 48 h + IFN-a 72 h 6 + IFN-a 72 h 3 5 MRFI 4 2 3 2 1 1 0 0 MHC I MHC II MICA MICB ULBP-1 ULBP-2 ULBP-3 ULBP-4 MHC I MHC II MICA MICB ULBP-1 ULBP-2 ULBP-3 ULBP-4 7 B 13 080125 FBS - D 080418 FBS - + IFN-a 48 h 12 + IFN-a 48 h + IFN-a 72 h + IFN-a 72 h 6 080125 FBS 11 10 5 9 8 4 7 6 3 MRFI 5 4 2 3 2 1 1 0 0 MHC I MHC II MICA MICB ULBP-1 ULBP-2 ULBP-3 ULBP-4 MHC I MHC II MICA MICB ULBP-1 ULBP-2 ULBP-3 ULBP-4 Molecule Molecule FIGURE 4S FIGURE 5S Panel A Panel B FIGURE 6S A B C D Supplemental Results Table 1S. Modulation by IFN-α of APM in GBM CSC and FBS tumor cell lines. Molecule * Cell line IFN-α‡ HLA β2-m# HLA LMP TAP1 TAP2 class II A A HC§ 2 7 10 080125 CSCs - 1∞ (1) 3 (65) 2 (91) 1 (2) 6 (47) 2 (61) 1 (3) 1 (2) 1 (3) + 2 (81) 11 (80) 13 (99) 1 (3) 8 (88) 4 (91) 1 (2) 1 (3) 2 (68) 080125 FBS - 2 (81) 4 (63) 4 (83) 1 (3) 6 (80) 3 (67) 2 (86) 1 (3) 2 (75) + 2 (99) 14 (90) 7 (97) 5 (75) 7 (100) 6 (98) 2 (90) 1 (4) 3 (87) 080418 CSCs - 2 (51) 1 (1) 1 (3) 2 (47) 2 (83) 2 (54) 1 (4) 1 (2) 1 (3) + 2 (81) 3 (76) 5 (75) 2 (50) 2 (83) 3 (71) 1 (3) 2 (87) 1 (2) 080418 FBS - 1 (3) 3 (70) 2 (88) 1 (4) 3 (87) 2 (76) 1 (3) 1 (3) 1 (2) + 2 (78) 7 (98) 5 (99) 2 (94) 5 (100) 3 (100) 1 (4) 2 (100) 1 (2) 070104 CSCs - 1 (2) 1 (3) 1 (3) 2 (78) 1 (3) 1 (2) 1 (3) 1 (3) 1 (2) + 2 (98) 8 (100) 10 (88) 4 (89) 3 (98) 3 (94) 1 (4) 2 (86) 2 (79) * expression of APM molecules was evaluated by intracellular staining and cytofluorimetric analysis; ‡ cells were treatead or not (+/-) for 72 h with 1000 IU/ml of IFN-α; # β-2 microglobulin; § β-2 microglobulin-free HLA-A heavy chain; ∞ values are indicated as ratio between the mean of fluorescence intensity of cells stained with the selected mAb and that of the negative control; bold values indicate significant MRFI (≥ 2). -
Small Cell Ovarian Carcinoma: Genomic Stability and Responsiveness to Therapeutics
Gamwell et al. Orphanet Journal of Rare Diseases 2013, 8:33 http://www.ojrd.com/content/8/1/33 RESEARCH Open Access Small cell ovarian carcinoma: genomic stability and responsiveness to therapeutics Lisa F Gamwell1,2, Karen Gambaro3, Maria Merziotis2, Colleen Crane2, Suzanna L Arcand4, Valerie Bourada1,2, Christopher Davis2, Jeremy A Squire6, David G Huntsman7,8, Patricia N Tonin3,4,5 and Barbara C Vanderhyden1,2* Abstract Background: The biology of small cell ovarian carcinoma of the hypercalcemic type (SCCOHT), which is a rare and aggressive form of ovarian cancer, is poorly understood. Tumourigenicity, in vitro growth characteristics, genetic and genomic anomalies, and sensitivity to standard and novel chemotherapeutic treatments were investigated in the unique SCCOHT cell line, BIN-67, to provide further insight in the biology of this rare type of ovarian cancer. Method: The tumourigenic potential of BIN-67 cells was determined and the tumours formed in a xenograft model was compared to human SCCOHT. DNA sequencing, spectral karyotyping and high density SNP array analysis was performed. The sensitivity of the BIN-67 cells to standard chemotherapeutic agents and to vesicular stomatitis virus (VSV) and the JX-594 vaccinia virus was tested. Results: BIN-67 cells were capable of forming spheroids in hanging drop cultures. When xenografted into immunodeficient mice, BIN-67 cells developed into tumours that reflected the hypercalcemia and histology of human SCCOHT, notably intense expression of WT-1 and vimentin, and lack of expression of inhibin. Somatic mutations in TP53 and the most common activating mutations in KRAS and BRAF were not found in BIN-67 cells by DNA sequencing. -
Ingenuity Pathway Analysis of Differentially Expressed Genes Involved in Signaling Pathways and Molecular Networks in Rhoe Gene‑Edited Cardiomyocytes
INTERNATIONAL JOURNAL OF MOleCular meDICine 46: 1225-1238, 2020 Ingenuity pathway analysis of differentially expressed genes involved in signaling pathways and molecular networks in RhoE gene‑edited cardiomyocytes ZHONGMING SHAO1*, KEKE WANG1*, SHUYA ZHANG2, JIANLING YUAN1, XIAOMING LIAO1, CAIXIA WU1, YUAN ZOU1, YANPING HA1, ZHIHUA SHEN1, JUNLI GUO2 and WEI JIE1,2 1Department of Pathology, School of Basic Medicine Sciences, Guangdong Medical University, Zhanjiang, Guangdong 524023; 2Hainan Provincial Key Laboratory for Tropical Cardiovascular Diseases Research and Key Laboratory of Emergency and Trauma of Ministry of Education, Institute of Cardiovascular Research of The First Affiliated Hospital, Hainan Medical University, Haikou, Hainan 571199, P.R. China Received January 7, 2020; Accepted May 20, 2020 DOI: 10.3892/ijmm.2020.4661 Abstract. RhoE/Rnd3 is an atypical member of the Rho super- injury and abnormalities, cell‑to‑cell signaling and interaction, family of proteins, However, the global biological function and molecular transport. In addition, 885 upstream regulators profile of this protein remains unsolved. In the present study, a were enriched, including 59 molecules that were predicated RhoE‑knockout H9C2 cardiomyocyte cell line was established to be strongly activated (Z‑score >2) and 60 molecules that using CRISPR/Cas9 technology, following which differentially were predicated to be significantly inhibited (Z‑scores <‑2). In expressed genes (DEGs) between the knockout and wild‑type particular, 33 regulatory effects and 25 networks were revealed cell lines were screened using whole genome expression gene to be associated with the DEGs. Among them, the most signifi- chips. A total of 829 DEGs, including 417 upregulated and cant regulatory effects were ‘adhesion of endothelial cells’ and 412 downregulated, were identified using the threshold of ‘recruitment of myeloid cells’ and the top network was ‘neuro- fold changes ≥1.2 and P<0.05. -
A Flexible Microfluidic System for Single-Cell Transcriptome Profiling
www.nature.com/scientificreports OPEN A fexible microfuidic system for single‑cell transcriptome profling elucidates phased transcriptional regulators of cell cycle Karen Davey1,7, Daniel Wong2,7, Filip Konopacki2, Eugene Kwa1, Tony Ly3, Heike Fiegler2 & Christopher R. Sibley 1,4,5,6* Single cell transcriptome profling has emerged as a breakthrough technology for the high‑resolution understanding of complex cellular systems. Here we report a fexible, cost‑efective and user‑ friendly droplet‑based microfuidics system, called the Nadia Instrument, that can allow 3′ mRNA capture of ~ 50,000 single cells or individual nuclei in a single run. The precise pressure‑based system demonstrates highly reproducible droplet size, low doublet rates and high mRNA capture efciencies that compare favorably in the feld. Moreover, when combined with the Nadia Innovate, the system can be transformed into an adaptable setup that enables use of diferent bufers and barcoded bead confgurations to facilitate diverse applications. Finally, by 3′ mRNA profling asynchronous human and mouse cells at diferent phases of the cell cycle, we demonstrate the system’s ability to readily distinguish distinct cell populations and infer underlying transcriptional regulatory networks. Notably this provided supportive evidence for multiple transcription factors that had little or no known link to the cell cycle (e.g. DRAP1, ZKSCAN1 and CEBPZ). In summary, the Nadia platform represents a promising and fexible technology for future transcriptomic studies, and other related applications, at cell resolution. Single cell transcriptome profling has recently emerged as a breakthrough technology for understanding how cellular heterogeneity contributes to complex biological systems. Indeed, cultured cells, microorganisms, biopsies, blood and other tissues can be rapidly profled for quantifcation of gene expression at cell resolution. -
Association of Gene Ontology Categories with Decay Rate for Hepg2 Experiments These Tables Show Details for All Gene Ontology Categories
Supplementary Table 1: Association of Gene Ontology Categories with Decay Rate for HepG2 Experiments These tables show details for all Gene Ontology categories. Inferences for manual classification scheme shown at the bottom. Those categories used in Figure 1A are highlighted in bold. Standard Deviations are shown in parentheses. P-values less than 1E-20 are indicated with a "0". Rate r (hour^-1) Half-life < 2hr. Decay % GO Number Category Name Probe Sets Group Non-Group Distribution p-value In-Group Non-Group Representation p-value GO:0006350 transcription 1523 0.221 (0.009) 0.127 (0.002) FASTER 0 13.1 (0.4) 4.5 (0.1) OVER 0 GO:0006351 transcription, DNA-dependent 1498 0.220 (0.009) 0.127 (0.002) FASTER 0 13.0 (0.4) 4.5 (0.1) OVER 0 GO:0006355 regulation of transcription, DNA-dependent 1163 0.230 (0.011) 0.128 (0.002) FASTER 5.00E-21 14.2 (0.5) 4.6 (0.1) OVER 0 GO:0006366 transcription from Pol II promoter 845 0.225 (0.012) 0.130 (0.002) FASTER 1.88E-14 13.0 (0.5) 4.8 (0.1) OVER 0 GO:0006139 nucleobase, nucleoside, nucleotide and nucleic acid metabolism3004 0.173 (0.006) 0.127 (0.002) FASTER 1.28E-12 8.4 (0.2) 4.5 (0.1) OVER 0 GO:0006357 regulation of transcription from Pol II promoter 487 0.231 (0.016) 0.132 (0.002) FASTER 6.05E-10 13.5 (0.6) 4.9 (0.1) OVER 0 GO:0008283 cell proliferation 625 0.189 (0.014) 0.132 (0.002) FASTER 1.95E-05 10.1 (0.6) 5.0 (0.1) OVER 1.50E-20 GO:0006513 monoubiquitination 36 0.305 (0.049) 0.134 (0.002) FASTER 2.69E-04 25.4 (4.4) 5.1 (0.1) OVER 2.04E-06 GO:0007050 cell cycle arrest 57 0.311 (0.054) 0.133 (0.002) -
WO 2019/079361 Al 25 April 2019 (25.04.2019) W 1P O PCT
(12) INTERNATIONAL APPLICATION PUBLISHED UNDER THE PATENT COOPERATION TREATY (PCT) (19) World Intellectual Property Organization I International Bureau (10) International Publication Number (43) International Publication Date WO 2019/079361 Al 25 April 2019 (25.04.2019) W 1P O PCT (51) International Patent Classification: CA, CH, CL, CN, CO, CR, CU, CZ, DE, DJ, DK, DM, DO, C12Q 1/68 (2018.01) A61P 31/18 (2006.01) DZ, EC, EE, EG, ES, FI, GB, GD, GE, GH, GM, GT, HN, C12Q 1/70 (2006.01) HR, HU, ID, IL, IN, IR, IS, JO, JP, KE, KG, KH, KN, KP, KR, KW, KZ, LA, LC, LK, LR, LS, LU, LY, MA, MD, ME, (21) International Application Number: MG, MK, MN, MW, MX, MY, MZ, NA, NG, NI, NO, NZ, PCT/US2018/056167 OM, PA, PE, PG, PH, PL, PT, QA, RO, RS, RU, RW, SA, (22) International Filing Date: SC, SD, SE, SG, SK, SL, SM, ST, SV, SY, TH, TJ, TM, TN, 16 October 2018 (16. 10.2018) TR, TT, TZ, UA, UG, US, UZ, VC, VN, ZA, ZM, ZW. (25) Filing Language: English (84) Designated States (unless otherwise indicated, for every kind of regional protection available): ARIPO (BW, GH, (26) Publication Language: English GM, KE, LR, LS, MW, MZ, NA, RW, SD, SL, ST, SZ, TZ, (30) Priority Data: UG, ZM, ZW), Eurasian (AM, AZ, BY, KG, KZ, RU, TJ, 62/573,025 16 October 2017 (16. 10.2017) US TM), European (AL, AT, BE, BG, CH, CY, CZ, DE, DK, EE, ES, FI, FR, GB, GR, HR, HU, ΓΕ , IS, IT, LT, LU, LV, (71) Applicant: MASSACHUSETTS INSTITUTE OF MC, MK, MT, NL, NO, PL, PT, RO, RS, SE, SI, SK, SM, TECHNOLOGY [US/US]; 77 Massachusetts Avenue, TR), OAPI (BF, BJ, CF, CG, CI, CM, GA, GN, GQ, GW, Cambridge, Massachusetts 02139 (US). -
HHS Public Access Author Manuscript
HHS Public Access Author manuscript Author Manuscript Author ManuscriptNature. Author ManuscriptAuthor manuscript; Author Manuscript available in PMC 2015 June 11. Published in final edited form as: Nature. 2014 December 11; 516(7530): 242–245. doi:10.1038/nature13760. An evolutionary arms race between KRAB zinc finger genes 91/93 and SVA/L1 retrotransposons Frank MJ Jacobs1,§,*, David Greenberg1,2,¶,*, Ngan Nguyen1,3, Maximilian Haeussler1, Adam D Ewing1,¥, Sol Katzman1, Benedict Paten1, Sofie R Salama1,4, and David Haussler1,4,# 1Center for Biomolecular Science and Engineering, University of California Santa Cruz, Santa Cruz, California, United States of America 2Molecular, Cell and Developmental Biology, of California Santa Cruz, Santa Cruz, California, United States of America 3Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, California, United States of America 4Howard Hughes Medical Institute, University of California Santa Cruz, Santa Cruz, California, United States of America Summary Throughout evolution, primate genomes have been modified by waves of retrotransposon insertions1,2,3. For each wave, the host eventually finds a way to repress retrotransposon transcription and prevent further insertions. In mouse embryonic stem cells (mESCs), transcriptional silencing of retrotransposons requires TRIM28 (KAP1) and it’s repressive complex, which can be recruited to target sites by KRAB zinc finger proteins such as murine- specific ZFP809 which binds to integrated murine leukemia virus DNA elements and recruits -
The Function and Evolution of C2H2 Zinc Finger Proteins and Transposons
The function and evolution of C2H2 zinc finger proteins and transposons by Laura Francesca Campitelli A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy Department of Molecular Genetics University of Toronto © Copyright by Laura Francesca Campitelli 2020 The function and evolution of C2H2 zinc finger proteins and transposons Laura Francesca Campitelli Doctor of Philosophy Department of Molecular Genetics University of Toronto 2020 Abstract Transcription factors (TFs) confer specificity to transcriptional regulation by binding specific DNA sequences and ultimately affecting the ability of RNA polymerase to transcribe a locus. The C2H2 zinc finger proteins (C2H2 ZFPs) are a TF class with the unique ability to diversify their DNA-binding specificities in a short evolutionary time. C2H2 ZFPs comprise the largest class of TFs in Mammalian genomes, including nearly half of all Human TFs (747/1,639). Positive selection on the DNA-binding specificities of C2H2 ZFPs is explained by an evolutionary arms race with endogenous retroelements (EREs; copy-and-paste transposable elements), where the C2H2 ZFPs containing a KRAB repressor domain (KZFPs; 344/747 Human C2H2 ZFPs) are thought to diversify to bind new EREs and repress deleterious transposition events. However, evidence of the gain and loss of KZFP binding sites on the ERE sequence is sparse due to poor resolution of ERE sequence evolution, despite the recent publication of binding preferences for 242/344 Human KZFPs. The goal of my doctoral work has been to characterize the Human C2H2 ZFPs, with specific interest in their evolutionary history, functional diversity, and coevolution with LINE EREs. -
Whole Genome Sequencing of Familial Non-Medullary Thyroid Cancer Identifies Germline Alterations in MAPK/ERK and PI3K/AKT Signaling Pathways
biomolecules Article Whole Genome Sequencing of Familial Non-Medullary Thyroid Cancer Identifies Germline Alterations in MAPK/ERK and PI3K/AKT Signaling Pathways Aayushi Srivastava 1,2,3,4 , Abhishek Kumar 1,5,6 , Sara Giangiobbe 1, Elena Bonora 7, Kari Hemminki 1, Asta Försti 1,2,3 and Obul Reddy Bandapalli 1,2,3,* 1 Division of Molecular Genetic Epidemiology, German Cancer Research Center (DKFZ), D-69120 Heidelberg, Germany; [email protected] (A.S.); [email protected] (A.K.); [email protected] (S.G.); [email protected] (K.H.); [email protected] (A.F.) 2 Hopp Children’s Cancer Center (KiTZ), D-69120 Heidelberg, Germany 3 Division of Pediatric Neurooncology, German Cancer Research Center (DKFZ), German Cancer Consortium (DKTK), D-69120 Heidelberg, Germany 4 Medical Faculty, Heidelberg University, D-69120 Heidelberg, Germany 5 Institute of Bioinformatics, International Technology Park, Bangalore 560066, India 6 Manipal Academy of Higher Education (MAHE), Manipal, Karnataka 576104, India 7 S.Orsola-Malphigi Hospital, Unit of Medical Genetics, 40138 Bologna, Italy; [email protected] * Correspondence: [email protected]; Tel.: +49-6221-42-1709 Received: 29 August 2019; Accepted: 10 October 2019; Published: 13 October 2019 Abstract: Evidence of familial inheritance in non-medullary thyroid cancer (NMTC) has accumulated over the last few decades. However, known variants account for a very small percentage of the genetic burden. Here, we focused on the identification of common pathways and networks enriched in NMTC families to better understand its pathogenesis with the final aim of identifying one novel high/moderate-penetrance germline predisposition variant segregating with the disease in each studied family. -
Supplementary Table 1 Genes Tested in Qrt-PCR in Nfpas
Supplementary Table 1 Genes tested in qRT-PCR in NFPAs Gene Bank accession Gene Description number ABI assay ID a disintegrin-like and metalloprotease with thrombospondin type 1 motif 7 ADAMTS7 NM_014272.3 Hs00276223_m1 Rho guanine nucleotide exchange factor (GEF) 3 ARHGEF3 NM_019555.1 Hs00219609_m1 BCL2-associated X protein BAX NM_004324 House design Bcl-2 binding component 3 BBC3 NM_014417.2 Hs00248075_m1 B-cell CLL/lymphoma 2 BCL2 NM_000633 House design Bone morphogenetic protein 7 BMP7 NM_001719.1 Hs00233476_m1 CCAAT/enhancer binding protein (C/EBP), alpha CEBPA NM_004364.2 Hs00269972_s1 coxsackie virus and adenovirus receptor CXADR NM_001338.3 Hs00154661_m1 Homo sapiens Dicer1, Dcr-1 homolog (Drosophila) (DICER1) DICER1 NM_177438.1 Hs00229023_m1 Homo sapiens dystonin DST NM_015548.2 Hs00156137_m1 fms-related tyrosine kinase 3 FLT3 NM_004119.1 Hs00174690_m1 glutamate receptor, ionotropic, N-methyl D-aspartate 1 GRIN1 NM_000832.4 Hs00609557_m1 high-mobility group box 1 HMGB1 NM_002128.3 Hs01923466_g1 heterogeneous nuclear ribonucleoprotein U HNRPU NM_004501.3 Hs00244919_m1 insulin-like growth factor binding protein 5 IGFBP5 NM_000599.2 Hs00181213_m1 latent transforming growth factor beta binding protein 4 LTBP4 NM_001042544.1 Hs00186025_m1 microtubule-associated protein 1 light chain 3 beta MAP1LC3B NM_022818.3 Hs00797944_s1 matrix metallopeptidase 17 MMP17 NM_016155.4 Hs01108847_m1 myosin VA MYO5A NM_000259.1 Hs00165309_m1 Homo sapiens nuclear factor (erythroid-derived 2)-like 1 NFE2L1 NM_003204.1 Hs00231457_m1 oxoglutarate (alpha-ketoglutarate) -
S41467-019-13840-9.Pdf
ARTICLE https://doi.org/10.1038/s41467-019-13840-9 OPEN Accurate quantification of circular RNAs identifies extensive circular isoform switching events Jinyang Zhang 1,2, Shuai Chen1, Jingwen Yang1 & Fangqing Zhao1,2,3* Detection and quantification of circular RNAs (circRNAs) face several significant challenges, including high false discovery rate, uneven rRNA depletion and RNase R treatment efficiency, and underestimation of back-spliced junction reads. Here, we propose a novel algorithm, fi 1234567890():,; CIRIquant, for accurate circRNA quanti cation and differential expression analysis. By con- structing pseudo-circular reference for re-alignment of RNA-seq reads and employing sophisticated statistical models to correct RNase R treatment biases, CIRIquant can provide more accurate expression values for circRNAs with significantly reduced false discovery rate. We further develop a one-stop differential expression analysis pipeline implementing two independent measures, which helps unveil the regulation of competitive splicing between circRNAs and their linear counterparts. We apply CIRIquant to RNA-seq datasets of hepa- tocellular carcinoma, and characterize two important groups of linear-circular switching and circular transcript usage switching events, which demonstrate the promising ability to explore extensive transcriptomic changes in liver tumorigenesis. 1 Computational Genomics Lab, Beijing Institutes of Life Science, Chinese Academy of Sciences, 100101 Beijing, China. 2 University of Chinese Academy of Sciences, 100049 Beijing, China. -
Cytogenetic and Molecular Characterization of the Macro- And
University of Ulm Department of Human Genetics Prof. Dr. med. Walther Vogel Cytogenetic and Molecular Characterization of the Macro- and Micro-inversions, which Distinguish the Human and the Chimpanzee Karyotypes - from Speciation to Polymorphism Thesis Applying for the Degree of Doctor of Human Biology (Dr. hum. biol.) Faculty of Medicine University of Ulm Presented by Justyna Monika Szamalek from Wrze śnia in Poland 2006 Amtierender Dekan: Prof. Dr. Klaus-Michael Debatin 1. Berichterstatter: Prof. Dr. med. Horst Hameister 2. Berichterstatter: Prof. Dr. med. Konstanze Döhner Tag der Promotion: 28.07.2006 Content Content 1. Introduction ...................................................................................................................7 1.1. Primate phylogeny........................................................................................................7 1.2. Africa as the place of human origin and the living area of the present-day chimpanzee populations .................................................................9 1.3. Cytogenetic and molecular differences between human and chimpanzee genomes.............................................................................................10 1.4. Cytogenetic and molecular differences between common chimpanzee and bonobo genomes................................................................................17 1.5. Theory of speciation .....................................................................................................18 1.6. Theory of selection