Gene Duplication and Neofunctionalization: POLR3G and POLR3GL
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DEPs in osteosarcoma cells comparing to osteoblastic cells Biological Process Protein Percentage of Hits metabolic process (GO:0008152) 29.3 29.3% cellular process (GO:0009987) 20.2 20.2% localization (GO:0051179) 9.4 9.4% biological regulation (GO:0065007) 8 8.0% developmental process (GO:0032502) 7.8 7.8% response to stimulus (GO:0050896) 5.6 5.6% cellular component organization (GO:0071840) 5.6 5.6% multicellular organismal process (GO:0032501) 4.4 4.4% immune system process (GO:0002376) 4.2 4.2% biological adhesion (GO:0022610) 2.7 2.7% apoptotic process (GO:0006915) 1.6 1.6% reproduction (GO:0000003) 0.8 0.8% locomotion (GO:0040011) 0.4 0.4% cell killing (GO:0001906) 0.1 0.1% 100.1% Genes 2179Hits 3870 biological adhesion apoptotic process … reproduction (GO:0000003) , 0.8% (GO:0022610) , 2.7% locomotion (GO:0040011) ,… immune system process cell killing (GO:0001906) , 0.1% (GO:0002376) , 4.2% multicellular organismal process (GO:0032501) , metabolic process 4.4% (GO:0008152) , 29.3% cellular component organization (GO:0071840) , 5.6% response to stimulus (GO:0050896), 5.6% developmental process (GO:0032502) , 7.8% biological regulation (GO:0065007) , 8.0% cellular process (GO:0009987) , 20.2% localization (GO:0051179) , 9. -
POLR2L Antibody Cat
POLR2L Antibody Cat. No.: XW-7445 POLR2L Antibody Specifications HOST SPECIES: Chicken SPECIES REACTIVITY: Human, Mouse, Rat IMMUNOGEN: 1-67 TESTED APPLICATIONS: WB POLR2L antibody can be used for the detection of POLR2L by Western blot, may also work APPLICATIONS: for IHC and ICC. PREDICTED MOLECULAR 7.6 kDa (calculated) WEIGHT: Properties PURIFICATION: Antigen affinity-purified CLONALITY: Polyclonal CONJUGATE: Unconjugated PHYSICAL STATE: Liquid BUFFER: Phosphate-Buffered Saline. No preservatives added. CONCENTRATION: 1 mg/mL October 1, 2021 1 https://www.prosci-inc.com/polr2l-antibody-7445.html POLR2L antibody can be stored at 4˚C for short term (weeks). Long term storage should STORAGE CONDITIONS: be at -20˚C. As with all antibodies care should be taken to avoid repeated freeze thaw cycles. Antibodies should not be exposed to prolonged high temperatures. Additional Info OFFICIAL SYMBOL: POLR2L DNA-directed RNA polymerases I, II, and III subunit RPABC5, DNA-directed RNA ALTERNATE NAMES: polymerase III subunit L, RNA polymerases I, and III subunit ABC5, RBP10, RPB10, RPABC5, RPB7.6, hRPB7.6, RPB10beta, POLR2L ACCESSION NO.: NP_066951.1 PROTEIN GI NO.: 10863925 GENE ID: 5441 USER NOTE: Optimal dilutions for each application to be determined by the researcher. Background and References DNA directed RNA polymerase II polypeptide L; polymerase (RNA) II (DNA directed) polypeptide L (7.6kD); RNA polymerase II subunit. This protein is a subunit of RNA polymerase II, the polymerase responsible for synthesizing messenger RNA in eukaryotes. BACKGROUND: It contains four conserved cysteines characteristic of an atypical zinc-binding domain. Like its counterpart in yeast, this subunit may be shared by the other two DNA-directed RNA polymerases. -
Investigation of Key Genes and Pathways in Inhibition of Oxycodone on Vincristine-Induced Microglia Activation by Using Bioinformatics Analysis
Hindawi Disease Markers Volume 2019, Article ID 3521746, 10 pages https://doi.org/10.1155/2019/3521746 Research Article Investigation of Key Genes and Pathways in Inhibition of Oxycodone on Vincristine-Induced Microglia Activation by Using Bioinformatics Analysis Wei Liu,1 Jishi Ye,2 and Hong Yan 1 1Department of Anesthesiology, the Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430014, China 2Department of Anesthesiology, Renmin Hospital of Wuhan University, Wuhan, 430060 Hubei, China Correspondence should be addressed to Hong Yan; [email protected] Received 2 November 2018; Accepted 31 December 2018; Published 10 February 2019 Academic Editor: Hubertus Himmerich Copyright © 2019 Wei Liu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Introduction. The neurobiological mechanisms underlying the chemotherapy-induced neuropathic pain are only partially understood. Among them, microglia activation was identified as the key component of neuropathic pain. The aim of this study was to identify differentially expressed genes (DEGs) and pathways associated with vincristine-induced neuropathic pain by using bioinformatics analysis and observe the effects of oxycodone on these DEG expressions in a vincristine-induced microglia activation model. Methods. Based on microarray profile GSE53897, we identified DEGs between vincristine-induced neuropathic pain rats and the control group. Using the ToppGene database, the prioritization DEGs were screened and performed by gene ontology (GO) and signaling pathway enrichment. A protein-protein interaction (PPI) network was used to explore the relationship among DEGs. -
A Network Propagation Approach to Prioritize Long Tail Genes in Cancer
bioRxiv preprint doi: https://doi.org/10.1101/2021.02.05.429983; this version posted February 8, 2021. 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. A Network Propagation Approach to Prioritize Long Tail Genes in Cancer Hussein Mohsen1,*, Vignesh Gunasekharan2, Tao Qing2, Sahand Negahban3, Zoltan Szallasi4, Lajos Pusztai2,*, Mark B. Gerstein1,5,6,3,* 1 Computational Biology & Bioinformatics Program, Yale University, New Haven, CT 06511, USA 2 Breast Medical Oncology, Yale School of Medicine, New Haven, CT 06511, USA 3 Department of Statistics & Data Science, Yale University, New Haven, CT 06511, USA 4 Children’s Hospital Informatics Program, Harvard-MIT Division of Health Sciences and Technology, Harvard Medical School, Boston, MA 02115, USA 5 Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06511, USA 6 Department of Computer Science, Yale University, New Haven, CT 06511, USA * Corresponding author Abstract Introduction. The diversity of genomic alterations in cancer pose challenges to fully understanding the etiologies of the disease. Recent interest in infrequent mutations, in genes that reside in the “long tail” of the mutational distribution, uncovered new genes with significant implication in cancer development. The study of these genes often requires integrative approaches with multiple types of biological data. Network propagation methods have demonstrated high efficacy in uncovering genomic patterns underlying cancer using biological interaction networks. Yet, the majority of these analyses have focused their assessment on detecting known cancer genes or identifying altered subnetworks. -
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. -
Proteomics Provides Insights Into the Inhibition of Chinese Hamster V79
www.nature.com/scientificreports OPEN Proteomics provides insights into the inhibition of Chinese hamster V79 cell proliferation in the deep underground environment Jifeng Liu1,2, Tengfei Ma1,2, Mingzhong Gao3, Yilin Liu4, Jun Liu1, Shichao Wang2, Yike Xie2, Ling Wang2, Juan Cheng2, Shixi Liu1*, Jian Zou1,2*, Jiang Wu2, Weimin Li2 & Heping Xie2,3,5 As resources in the shallow depths of the earth exhausted, people will spend extended periods of time in the deep underground space. However, little is known about the deep underground environment afecting the health of organisms. Hence, we established both deep underground laboratory (DUGL) and above ground laboratory (AGL) to investigate the efect of environmental factors on organisms. Six environmental parameters were monitored in the DUGL and AGL. Growth curves were recorded and tandem mass tag (TMT) proteomics analysis were performed to explore the proliferative ability and diferentially abundant proteins (DAPs) in V79 cells (a cell line widely used in biological study in DUGLs) cultured in the DUGL and AGL. Parallel Reaction Monitoring was conducted to verify the TMT results. γ ray dose rate showed the most detectable diference between the two laboratories, whereby γ ray dose rate was signifcantly lower in the DUGL compared to the AGL. V79 cell proliferation was slower in the DUGL. Quantitative proteomics detected 980 DAPs (absolute fold change ≥ 1.2, p < 0.05) between V79 cells cultured in the DUGL and AGL. Of these, 576 proteins were up-regulated and 404 proteins were down-regulated in V79 cells cultured in the DUGL. KEGG pathway analysis revealed that seven pathways (e.g. -
H4K16 Acetylation Marks Active Genes and Enhancers of Embryonic Stem Cells, but Does Not Alter Chromatin Compaction
Downloaded from genome.cshlp.org on October 5, 2021 - Published by Cold Spring Harbor Laboratory Press H4K16 acetylation marks active genes and enhancers of embryonic stem cells, but does not alter chromatin compaction Gillian Taylor1, Ragnhild Eskeland2, Betül Hekimoglu-Balkan1, Madapura M. Pradeepa1* and Wendy A Bickmore1* 1 MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine at University of Edinburgh, Crewe Road, Edinburgh EH4 2XU, UK 2Current address: Department of Molecular Biosciences, University of Oslo, N-0316 Oslo, Norway *Correspondence to: W. Bickmore or M.M. Pradeepa, MRC Human Genetics Unit, MRC IGMM, Crewe Road, Edinburgh EH4 2XU, UK Tel: +44 131 332 2471 Fax: +44 131 467 8456 Email:[email protected] or [email protected] Running head: H4K16 acetylation and long-range genome regulation Keywords: Chromatin compaction, embryonic stem cells, fluorescence in situ hybridization, histone acetylation, long-range regulation, 1 Downloaded from genome.cshlp.org on October 5, 2021 - Published by Cold Spring Harbor Laboratory Press Abstract Compared with histone H3, acetylation of H4 tails has not been well studied, especially in mammalian cells. Yet, H4K16 acetylation is of particular interest because of its ability to decompact nucleosomes in vitro and its involvement in dosage compensation in flies. Here we show that, surprisingly, loss of H4K16 acetylation does not alter higher-order chromatin compaction in vivo in mouse embryonic stem cells (ESCs). As well as peaks of acetylated H4K16 and Kat8/MOF histone acetyltransferase at the transcription start sites of expressed genes, we report that acetylation of H4K16 is a new marker of active enhancers in ESCs and that some enhancers are marked by H3K4me1, Kat8 and H4K16ac but not by acetylated H3K27 or p300/EP300, suggesting that they are novel EP300 independent regulatory elements. -
Supplemental Table 1. Complete Gene Lists and GO Terms from Figure 3C
Supplemental Table 1. Complete gene lists and GO terms from Figure 3C. Path 1 Genes: RP11-34P13.15, RP4-758J18.10, VWA1, CHD5, AZIN2, FOXO6, RP11-403I13.8, ARHGAP30, RGS4, LRRN2, RASSF5, SERTAD4, GJC2, RHOU, REEP1, FOXI3, SH3RF3, COL4A4, ZDHHC23, FGFR3, PPP2R2C, CTD-2031P19.4, RNF182, GRM4, PRR15, DGKI, CHMP4C, CALB1, SPAG1, KLF4, ENG, RET, GDF10, ADAMTS14, SPOCK2, MBL1P, ADAM8, LRP4-AS1, CARNS1, DGAT2, CRYAB, AP000783.1, OPCML, PLEKHG6, GDF3, EMP1, RASSF9, FAM101A, STON2, GREM1, ACTC1, CORO2B, FURIN, WFIKKN1, BAIAP3, TMC5, HS3ST4, ZFHX3, NLRP1, RASD1, CACNG4, EMILIN2, L3MBTL4, KLHL14, HMSD, RP11-849I19.1, SALL3, GADD45B, KANK3, CTC- 526N19.1, ZNF888, MMP9, BMP7, PIK3IP1, MCHR1, SYTL5, CAMK2N1, PINK1, ID3, PTPRU, MANEAL, MCOLN3, LRRC8C, NTNG1, KCNC4, RP11, 430C7.5, C1orf95, ID2-AS1, ID2, GDF7, KCNG3, RGPD8, PSD4, CCDC74B, BMPR2, KAT2B, LINC00693, ZNF654, FILIP1L, SH3TC1, CPEB2, NPFFR2, TRPC3, RP11-752L20.3, FAM198B, TLL1, CDH9, PDZD2, CHSY3, GALNT10, FOXQ1, ATXN1, ID4, COL11A2, CNR1, GTF2IP4, FZD1, PAX5, RP11-35N6.1, UNC5B, NKX1-2, FAM196A, EBF3, PRRG4, LRP4, SYT7, PLBD1, GRASP, ALX1, HIP1R, LPAR6, SLITRK6, C16orf89, RP11-491F9.1, MMP2, B3GNT9, NXPH3, TNRC6C-AS1, LDLRAD4, NOL4, SMAD7, HCN2, PDE4A, KANK2, SAMD1, EXOC3L2, IL11, EMILIN3, KCNB1, DOK5, EEF1A2, A4GALT, ADGRG2, ELF4, ABCD1 Term Count % PValue Genes regulation of pathway-restricted GDF3, SMAD7, GDF7, BMPR2, GDF10, GREM1, BMP7, LDLRAD4, SMAD protein phosphorylation 9 6.34 1.31E-08 ENG pathway-restricted SMAD protein GDF3, SMAD7, GDF7, BMPR2, GDF10, GREM1, BMP7, LDLRAD4, phosphorylation -
Psychosis: a Convergent Functional Genomics Approach Identifying a Series of Candidate Genes for Mania
Identifying a series of candidate genes for mania and psychosis: a convergent functional genomics approach ALEXANDER B. NICULESCU, III, DAVID S. SEGAL, RONALD KUCZENSKI, THOMAS BARRETT, RICHARD L. HAUGER and JOHN R. KELSOE Physiol. Genomics 4:83-91, 2000. You might find this additional information useful... This article cites 52 articles, 15 of which you can access free at: http://physiolgenomics.physiology.org/cgi/content/full/4/1/83#BIBL This article has been cited by 4 other HighWire hosted articles: Evaluation of common gene expression patterns in the rat nervous system S. Kaiser and L. K. Nisenbaum Physiol Genomics, December 16, 2003; 16 (1): 1-7. [Abstract] [Full Text] [PDF] Microarray Technology: A Review of New Strategies to Discover Candidate Vulnerability Downloaded from Genes in Psychiatric Disorders W. E. Bunney, B. G. Bunney, M. P. Vawter, H. Tomita, J. Li, S. J. Evans, P. V. Choudary, R. M. Myers, E. G. Jones, S. J. Watson and H. Akil Am. J. Psychiatry, April 1, 2003; 160 (4): 657-666. [Abstract] [Full Text] [PDF] Biomarker Identification by Feature Wrappers physiolgenomics.physiology.org M. Xiong, X. Fang and J. Zhao Genome Res., November 1, 2001; 11 (11): 1878-1887. [Abstract] [Full Text] [PDF] GRK3 mediates desensitization of CRF1 receptors: a potential mechanism regulating stress adaptation F. M. Dautzenberg, S. Braun and R. L. Hauger Am J Physiol Regulatory Integrative Comp Physiol, April 1, 2001; 280 (4): R935-946. [Abstract] [Full Text] Medline items on this article's topics can be found at http://highwire.stanford.edu/lists/artbytopic.dtl on the following topics: on August 11, 2005 Immunology . -
Mir-17-92 Fine-Tunes MYC Expression and Function to Ensure
ARTICLE Received 31 Mar 2015 | Accepted 22 Sep 2015 | Published 10 Nov 2015 DOI: 10.1038/ncomms9725 OPEN miR-17-92 fine-tunes MYC expression and function to ensure optimal B cell lymphoma growth Marija Mihailovich1, Michael Bremang1, Valeria Spadotto1, Daniele Musiani1, Elena Vitale1, Gabriele Varano2,w, Federico Zambelli3, Francesco M. Mancuso1,w, David A. Cairns1,w, Giulio Pavesi3, Stefano Casola2 & Tiziana Bonaldi1 The synergism between c-MYC and miR-17-19b, a truncated version of the miR-17-92 cluster, is well-documented during tumor initiation. However, little is known about miR-17-19b function in established cancers. Here we investigate the role of miR-17-19b in c-MYC-driven lymphomas by integrating SILAC-based quantitative proteomics, transcriptomics and 30 untranslated region (UTR) analysis upon miR-17-19b overexpression. We identify over one hundred miR-17-19b targets, of which 40% are co-regulated by c-MYC. Downregulation of a new miR-17/20 target, checkpoint kinase 2 (Chek2), increases the recruitment of HuR to c- MYC transcripts, resulting in the inhibition of c-MYC translation and thus interfering with in vivo tumor growth. Hence, in established lymphomas, miR-17-19b fine-tunes c-MYC activity through a tight control of its function and expression, ultimately ensuring cancer cell homeostasis. Our data highlight the plasticity of miRNA function, reflecting changes in the mRNA landscape and 30 UTR shortening at different stages of tumorigenesis. 1 Department of Experimental Oncology, European Institute of Oncology, Via Adamello 16, Milan 20139, Italy. 2 Units of Genetics of B cells and lymphomas, IFOM, FIRC Institute of Molecular Oncology Foundation, Milan 20139, Italy. -
ARTICLE Complex Inheritance Pattern Resembling Autosomal Recessive Inheritance Involving a Microdeletion in Thrombocytopenia– Absent Radius Syndrome
ARTICLE Complex Inheritance Pattern Resembling Autosomal Recessive Inheritance Involving a Microdeletion in Thrombocytopenia– Absent Radius Syndrome Eva Klopocki,* Harald Schulze,* Gabriele Strauß, Claus-Eric Ott, Judith Hall, Fabienne Trotier, Silke Fleischhauer, Lynn Greenhalgh, Ruth A. Newbury-Ecob, Luitgard M. Neumann, Rolf Habenicht, Rainer Ko¨nig, Eva Seemanova, Andre´ Megarbane, Hans-Hilger Ropers, Reinhard Ullmann, Denise Horn, and Stefan Mundlos Thrombocytopenia–absent radius (TAR) syndrome is characterized by hypomegakaryocytic thrombocytopenia and bi- lateral radial aplasia in the presence of both thumbs. Other frequent associations are congenital heart disease and a high incidence of cow’s milk intolerance. Evidence for autosomal recessive inheritance comes from families with several affected individuals born to unaffected parents, but several other observations argue for a more complex pattern of inheritance. In this study, we describe a common interstitial microdeletion of 200 kb on chromosome 1q21.1 in all 30 investigated patients with TAR syndrome, detected by microarray-based comparative genomic hybridization. Analysis of the parents revealed that this deletion occurred de novo in 25% of affected individuals. Intriguingly, inheritance of the deletion along the maternal line as well as the paternal line was observed. The absence of this deletion in a cohort of control individuals argues for a specific role played by the microdeletion in the pathogenesis of TAR syndrome. We hypothesize that TAR syndrome is associated with a deletion on chromosome 1q21.1 but that the phenotype develops only in the presence of an additional as-yet-unknown modifier (mTAR). Thrombocytopenia–absent radius (TAR) syndrome (MIM Cow’s milk allergy or intolerance appears to be relatively 274000) is a clinically well-characterized malformation common among patients with TAR syndrome and may syndrome. -
Supporting Information
Supporting Information Pratilas et al. 10.1073/pnas.0900780106 SI Text HER2) xenografts. In each of these analyses, all noncontrol Determination of Sensitivity to MEK Inhibition. Drug sensitivity probes (n ϭ 22,215) were rank-ordered according to the mag- assays were performed by using a 96-well plate and the Alamar nitude of their difference in expression after MEK inhibition Blue reagent (Invitrogen) as reported (1). The cells were treated compared with DMSO-treated controls, as measured by SAM- with PD0325901 (Pfizer) in a range of concentrations from 0.1 derived d-scores. The positions of the output genes in this signed to 500 nM (Fig. S1). ranking were then scored in a manner similar to that described by the Connectivity Map (2). This empirical and nonparametric Enrichment Analysis Over a Time Course of MEK Inhibition. Af- Kolmogorov-Smirnov-based statistic reflects an enrichment fymetrix U133A 2.0 array analysis of V600EBRAF, SkMel-28 cells, score that ranges from ϩ1toϪ1, where a score of 0 is a lack of at 0, 2, 8, and 24 h after MEK inhibition was completed as enrichment in either direction of expression, or graphically, a described (see Experimental Procedures). Robust multiarray av- random distribution of the output profile genes. Those with erage (RMA) was used to estimate the expression of probe sets. enrichment scores nearer to 1 indicated increasing correlation Each time point from2hto24wascompared with 0 h, and in between the output profile and the rank-ordered gene set from each comparison, we considered only probe sets with an expres- the experimental comparison.