Identification of a Panel of MYC and Tip60 Co-Regulated Genes Functioning Primarily in Cell Cycle and DNA Replication – Zhao Et Al
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An Atpase Domain Common to Prokaryotic Cell Cycle Proteins
Proc. Natl. Acad. Sci. USA Vol. 89, pp. 7290-7294, August 1992 Biochemistry An ATPase domain common to prokaryotic cell cycle proteins, sugar kinases, actin, and hsp7O heat shock proteins (structural comparison/property pattern/remote homology) PEER BORK, CHRIS SANDER, AND ALFONSO VALENCIA European Molecular Biology Laboratory, D-6900 Heidelberg, Federal Republic of Germany Communicated by Russell F. Doolittle, March 6, 1992 ABSTRACT The functionally diverse actin, hexokinase, and hsp7O protein families have in common an ATPase domain of known three-dimensional structure. Optimal superposition ofthe three structures and alignment ofmany sequences in each of the three families has revealed a set of common conserved residues, distributed in five sequence motifs, which are in- volved in ATP binding and in a putative interdomain hinge. From the multiple sequence aliment in these motifs a pattern of amino acid properties required at each position is defined. The discriminatory power of the pattern is in part due to the use of several known three-dimensional structures and many sequences and in part to the "property" method ofgeneralizing from observed amino acid frequencies to amino acid fitness at each sequence position. A sequence data base search with the pattern significantly matches sugar kinases, such as fuco-, glucono-, xylulo-, ribulo-, and glycerokinase, as well as the prokaryotic cell cycle proteins MreB, FtsA, and StbA. These are predicted to have subdomains with the same tertiary structure as the ATPase subdomains Ia and Ha of hexokinase, actin, and Hsc7O, a very similar ATP binding pocket, and the capacity for interdomain hinge motion accompanying func- tional state changes. -
NCAPD3 Antibody (C-Term) Affinity Purified Rabbit Polyclonal Antibody (Pab) Catalog # AP16786B
10320 Camino Santa Fe, Suite G San Diego, CA 92121 Tel: 858.875.1900 Fax: 858.622.0609 NCAPD3 Antibody (C-term) Affinity Purified Rabbit Polyclonal Antibody (Pab) Catalog # AP16786B Specification NCAPD3 Antibody (C-term) - Product Information Application WB,E Primary Accession P42695 Other Accession NP_056076.1 Reactivity Human Host Rabbit Clonality Polyclonal Isotype Rabbit Ig Calculated MW 168891 Antigen Region 1050-1078 NCAPD3 Antibody (C-term) - Additional Information NCAPD3 Antibody (C-term) (Cat. Gene ID 23310 #AP16786b) western blot analysis in K562 cell line lysates (35ug/lane).This Other Names Condensin-2 complex subunit D3, Non-SMC demonstrates the NCAPD3 antibody detected condensin II complex subunit D3, hCAP-D3, the NCAPD3 protein (arrow). NCAPD3, CAPD3, KIAA0056 Target/Specificity NCAPD3 Antibody (C-term) - Background This NCAPD3 antibody is generated from rabbits immunized with a KLH conjugated Condensin complexes I and II play essential synthetic peptide between 1050-1078 roles in amino acids from the C-terminal region of mitotic chromosome assembly and human NCAPD3. segregation. Both condensins contain 2 invariant structural maintenance of Dilution chromosome (SMC) WB~~1:1000 subunits, SMC2 (MIM 605576) and SMC4 (MIM 605575), but they contain Format different sets of non-SMC subunits. NCAPD3 is Purified polyclonal antibody supplied in PBS 1 of 3 non-SMC with 0.09% (W/V) sodium azide. This subunits that define condensin II (Ono et al., antibody is purified through a protein A 2003 [PubMed column, followed by peptide affinity 14532007]). purification. NCAPD3 Antibody (C-term) - References Storage Maintain refrigerated at 2-8°C for up to 2 Rose, J.E., et al. -
A Commercial Antibody to the Human Condensin II Subunit NCAPH2 Cross-Reacts with a SWI/SNF Complex Component
bioRxiv preprint doi: https://doi.org/10.1101/2020.11.07.372599; this version posted November 9, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license. A commercial antibody to the human condensin II subunit NCAPH2 cross-reacts with a SWI/SNF complex component Erin E. Cutts1*, Gillian C Taylor2*, Mercedes Pardo1, Lu Yu1, Jimi C Wills3, Jyoti S. Choudhary1, Alessandro Vannini1#, Andrew J Wood2# 1 Division of Structural Biology, The Institute of Cancer Research, London SW7 3RP, United Kingdom 2 MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, The University of Edinburgh, Edinburgh, EH4 2XU, UK. 3 Cancer Research UK Edinburgh Centre, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK. * Equal contribution # correspondence to: [email protected], [email protected]. Summary Condensin complexes compact and disentangle chromosomes in preparation for cell division. Commercially available antibodies raised against condensin subunits have been widely used to characterise their cellular interactome. Here we have assessed the specificity of a polyclonal antibody (Bethyl A302- 276A) that is commonly used as a probe for NCAPH2, the kleisin subunit of condensin II, in mammalian cells. We find that, in addition to its intended target, this antibody cross-reacts with one or more components of the SWI/SNF family of chromatin remodelling complexes in an NCAPH2- independent manner. This cross-reactivity with an abundant chromatin- associated factor is likely to affect the interpretation of protein and chromatin immunoprecipitation experiments that make use of this antibody probe. -
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. -
Supplementary Materials
Supplementary Materials Figure S1. Differentially abundant spots between the mid-log phase cells grown on xylan or xylose. Red and blue circles denote spots with increased and decreased abundance respectively in the xylan growth condition. The identities of the circled spots are summarized in Table 3. Figure S2. Differentially abundant spots between the stationary phase cells grown on xylan or xylose. Red and blue circles denote spots with increased and decreased abundance respectively in the xylan growth condition. The identities of the circled spots are summarized in Table 4. S2 Table S1. Summary of the non-polysaccharide degrading proteins identified in the B. proteoclasticus cytosol by 2DE/MALDI-TOF. Protein Locus Location Score pI kDa Pep. Cov. Amino Acid Biosynthesis Acetylornithine aminotransferase, ArgD Bpr_I1809 C 1.7 × 10−4 5.1 43.9 11 34% Aspartate/tyrosine/aromatic aminotransferase Bpr_I2631 C 3.0 × 10−14 4.7 43.8 15 46% Aspartate-semialdehyde dehydrogenase, Asd Bpr_I1664 C 7.6 × 10−18 5.5 40.1 17 50% Branched-chain amino acid aminotransferase, IlvE Bpr_I1650 C 2.4 × 10−12 5.2 39.2 13 32% Cysteine synthase, CysK Bpr_I1089 C 1.9 × 10−13 5.0 32.3 18 72% Diaminopimelate dehydrogenase Bpr_I0298 C 9.6 × 10−16 5.6 35.8 16 49% Dihydrodipicolinate reductase, DapB Bpr_I2453 C 2.7 × 10−6 4.9 27.0 9 46% Glu/Leu/Phe/Val dehydrogenase Bpr_I2129 C 1.2 × 10−30 5.4 48.6 31 64% Imidazole glycerol phosphate synthase Bpr_I1240 C 8.0 × 10−3 4.7 22.5 8 44% glutamine amidotransferase subunit Ketol-acid reductoisomerase, IlvC Bpr_I1657 C 3.8 × 10−16 -
Genetic Association with Overall Survival of Taxane-Treated Lung
Genetic association with overall survival of taxane-treated lung cancer patients - a genome-wide association study in human lymphoblastoid cell lines followed by a clinical association study The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. Citation Niu, Nifang et al. “Genetic Association with Overall Survival of Taxane-treated Lung Cancer Patients - a Genome-wide Association Study in Human Lymphoblastoid Cell Lines Followed by a Clinical Association Study.” BMC Cancer 12.1 (2012): 422. CrossRef. Web. As Published http://dx.doi.org/10.1186/1471-2407-12-422 Publisher BioMed Central Ltd. Version Final published version Citable link http://hdl.handle.net/1721.1/77191 Terms of Use Creative Commons Attribution Detailed Terms http://creativecommons.org/licenses/by/2.0 Genetic variations and paclitaxel response Supplementary Figure 1. Imputation analysis for 8 SNPs associated with both paclitaxel IC50 in LCLs and overall survival in lung cancer patients. SNPs within 200kb up-/downstream of those 8 SNPs were imputed. Black circles indicate SNPs observed by genotyping, while red triangles indicate imputed SNPs. The y-axis represents –log10(p-value) for the association of each SNP with paclitaxel IC50, and the x-axis represents the chromosomal locations of the SNPs. Genetic variations in paclitaxel response 1 Supplementary Table 1. Top 1415 SNPs that were associated with paclitaxel IC50 with p-values <10-3 and top 147 SNPs that were significantly associated with paclitaxel IC50 -
Table S1. List of Oligonucleotide Primers Used
Table S1. List of oligonucleotide primers used. Cla4 LF-5' GTAGGATCCGCTCTGTCAAGCCTCCGACC M629Arev CCTCCCTCCATGTACTCcgcGATGACCCAgAGCTCGTTG M629Afwd CAACGAGCTcTGGGTCATCgcgGAGTACATGGAGGGAGG LF-3' GTAGGCCATCTAGGCCGCAATCTCGTCAAGTAAAGTCG RF-5' GTAGGCCTGAGTGGCCCGAGATTGCAACGTGTAACC RF-3' GTAGGATCCCGTACGCTGCGATCGCTTGC Ukc1 LF-5' GCAATATTATGTCTACTTTGAGCG M398Arev CCGCCGGGCAAgAAtTCcgcGAGAAGGTACAGATACGc M398Afwd gCGTATCTGTACCTTCTCgcgGAaTTcTTGCCCGGCGG LF-3' GAGGCCATCTAGGCCATTTACGATGGCAGACAAAGG RF-5' GTGGCCTGAGTGGCCATTGGTTTGGGCGAATGGC RF-3' GCAATATTCGTACGTCAACAGCGCG Nrc2 LF-5' GCAATATTTCGAAAAGGGTCGTTCC M454Grev GCCACCCATGCAGTAcTCgccGCAGAGGTAGAGGTAATC M454Gfwd GATTACCTCTACCTCTGCggcGAgTACTGCATGGGTGGC LF-3' GAGGCCATCTAGGCCGACGAGTGAAGCTTTCGAGCG RF-5' GAGGCCTGAGTGGCCTAAGCATCTTGGCTTCTGC RF-3' GCAATATTCGGTCAACGCTTTTCAGATACC Ipl1 LF-5' GTCAATATTCTACTTTGTGAAGACGCTGC M629Arev GCTCCCCACGACCAGCgAATTCGATagcGAGGAAGACTCGGCCCTCATC M629Afwd GATGAGGGCCGAGTCTTCCTCgctATCGAATTcGCTGGTCGTGGGGAGC LF-3' TGAGGCCATCTAGGCCGGTGCCTTAGATTCCGTATAGC RF-5' CATGGCCTGAGTGGCCGATTCTTCTTCTGTCATCGAC RF-3' GACAATATTGCTGACCTTGTCTACTTGG Ire1 LF-5' GCAATATTAAAGCACAACTCAACGC D1014Arev CCGTAGCCAAGCACCTCGgCCGAtATcGTGAGCGAAG D1014Afwd CTTCGCTCACgATaTCGGcCGAGGTGCTTGGCTACGG LF-3' GAGGCCATCTAGGCCAACTGGGCAAAGGAGATGGA RF-5' GAGGCCTGAGTGGCCGTGCGCCTGTGTATCTCTTTG RF-3' GCAATATTGGCCATCTGAGGGCTGAC Kin28 LF-5' GACAATATTCATCTTTCACCCTTCCAAAG L94Arev TGATGAGTGCTTCTAGATTGGTGTCggcGAAcTCgAGCACCAGGTTG L94Afwd CAACCTGGTGCTcGAgTTCgccGACACCAATCTAGAAGCACTCATCA LF-3' TGAGGCCATCTAGGCCCACAGAGATCCGCTTTAATGC RF-5' CATGGCCTGAGTGGCCAGGGCTAGTACGACCTCG -
Ncapd3 CRISPR/Cas9 KO Plasmid (M): Sc-429692
SANTA CRUZ BIOTECHNOLOGY, INC. Ncapd3 CRISPR/Cas9 KO Plasmid (m): sc-429692 BACKGROUND APPLICATIONS The Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) and Ncapd3 CRISPR/Cas9 KO Plasmid (m) is recommended for the disruption of CRISPR-associated protein (Cas9) system is an adaptive immune response gene expression in mouse cells. defense mechanism used by archea and bacteria for the degradation of foreign genetic material (4,6). This mechanism can be repurposed for other 20 nt non-coding RNA sequence: guides Cas9 functions, including genomic engineering for mammalian systems, such as to a specific target location in the genomic DNA gene knockout (KO) (1,2,3,5). CRISPR/Cas9 KO Plasmid products enable the U6 promoter: drives gRNA scaffold: helps Cas9 identification and cleavage of specific genes by utilizing guide RNA (gRNA) expression of gRNA bind to target DNA sequences derived from the Genome-scale CRISPR Knock-Out (GeCKO) v2 library developed in the Zhang Laboratory at the Broad Institute (3,5). Termination signal Green Fluorescent Protein: to visually REFERENCES verify transfection CRISPR/Cas9 Knockout Plasmid CBh (chicken β-Actin 1. Cong, L., et al. 2013. Multiplex genome engineering using CRISPR/Cas hybrid) promoter: drives systems. Science 339: 819-823. 2A peptide: expression of Cas9 allows production of both Cas9 and GFP from the 2. Mali, P., et al. 2013. RNA-guided human genome engineering via Cas9. same CBh promoter Science 339: 823-826. Nuclear localization signal 3. Ran, F.A., et al. 2013. Genome engineering using the CRISPR-Cas9 system. Nuclear localization signal SpCas9 ribonuclease Nat. Protoc. 8: 2281-2308. -
Towards Relating the Evolution of the Gene Repertoire in Mammals to Tissue Specialisation
Towards Relating the Evolution of the Gene Repertoire in Mammals to Tissue Specialisation Shiri Freilich Wolfson College This dissertation is submitted to the University of Cambridge for the degree of Doctor of Philosophy 21 December 2006 To Leon, who was the wind blowing in my sails, in the deep blue sea of this journey of ours. This Thesis is the result of my own work and includes nothing which is the outcome of work done in collaboration except where specifically indicated in the text. This Thesis does not exceed the specified length limit of 300 pages as defined by the Biology Degree Committee. This Thesis has been typeset in 12pt font according to the specifications defined by the Board of Graduate Studies and the Biology Degree Committee. 3 Summary: Towards Relating the Evolution of the Gene Repertoire in Mammals to Tissue Specialisation The sequencing efforts of recent years have provided a rich source of data for investigating how gene content determines similarity and uniqueness in a species’ phenotype. Work described in this PhD Thesis attempts to relate innovations in the gene repertoire along the mammalian lineage to the most obvious phenotypic characteristic of animals: the appearance of highly differentiated tissue types. Several different approaches, outlined below, have been followed to address some aspects of this problem. Initially, a comprehensive study of the pattern of expansion of the complement of enzymes in various species was performed in order to obtain a better view of the principles underlying the expansion of the gene repertoire in mammals. Although several studies have described a tendency toward an increase in sequence redundancy in mammals, not much is known about the way such sequence redundancy reflects functional redundancy. -
Supplementary Table S4. FGA Co-Expressed Gene List in LUAD
Supplementary Table S4. FGA co-expressed gene list in LUAD tumors Symbol R Locus Description FGG 0.919 4q28 fibrinogen gamma chain FGL1 0.635 8p22 fibrinogen-like 1 SLC7A2 0.536 8p22 solute carrier family 7 (cationic amino acid transporter, y+ system), member 2 DUSP4 0.521 8p12-p11 dual specificity phosphatase 4 HAL 0.51 12q22-q24.1histidine ammonia-lyase PDE4D 0.499 5q12 phosphodiesterase 4D, cAMP-specific FURIN 0.497 15q26.1 furin (paired basic amino acid cleaving enzyme) CPS1 0.49 2q35 carbamoyl-phosphate synthase 1, mitochondrial TESC 0.478 12q24.22 tescalcin INHA 0.465 2q35 inhibin, alpha S100P 0.461 4p16 S100 calcium binding protein P VPS37A 0.447 8p22 vacuolar protein sorting 37 homolog A (S. cerevisiae) SLC16A14 0.447 2q36.3 solute carrier family 16, member 14 PPARGC1A 0.443 4p15.1 peroxisome proliferator-activated receptor gamma, coactivator 1 alpha SIK1 0.435 21q22.3 salt-inducible kinase 1 IRS2 0.434 13q34 insulin receptor substrate 2 RND1 0.433 12q12 Rho family GTPase 1 HGD 0.433 3q13.33 homogentisate 1,2-dioxygenase PTP4A1 0.432 6q12 protein tyrosine phosphatase type IVA, member 1 C8orf4 0.428 8p11.2 chromosome 8 open reading frame 4 DDC 0.427 7p12.2 dopa decarboxylase (aromatic L-amino acid decarboxylase) TACC2 0.427 10q26 transforming, acidic coiled-coil containing protein 2 MUC13 0.422 3q21.2 mucin 13, cell surface associated C5 0.412 9q33-q34 complement component 5 NR4A2 0.412 2q22-q23 nuclear receptor subfamily 4, group A, member 2 EYS 0.411 6q12 eyes shut homolog (Drosophila) GPX2 0.406 14q24.1 glutathione peroxidase -
Antigen-Specific Memory CD4 T Cells Coordinated Changes in DNA
Downloaded from http://www.jimmunol.org/ by guest on September 24, 2021 is online at: average * The Journal of Immunology The Journal of Immunology published online 18 March 2013 from submission to initial decision 4 weeks from acceptance to publication http://www.jimmunol.org/content/early/2013/03/17/jimmun ol.1202267 Coordinated Changes in DNA Methylation in Antigen-Specific Memory CD4 T Cells Shin-ichi Hashimoto, Katsumi Ogoshi, Atsushi Sasaki, Jun Abe, Wei Qu, Yoichiro Nakatani, Budrul Ahsan, Kenshiro Oshima, Francis H. W. Shand, Akio Ametani, Yutaka Suzuki, Shuichi Kaneko, Takashi Wada, Masahira Hattori, Sumio Sugano, Shinichi Morishita and Kouji Matsushima J Immunol Submit online. Every submission reviewed by practicing scientists ? is published twice each month by Author Choice option Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts http://jimmunol.org/subscription Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html Freely available online through http://www.jimmunol.org/content/suppl/2013/03/18/jimmunol.120226 7.DC1 Information about subscribing to The JI No Triage! Fast Publication! Rapid Reviews! 30 days* Why • • • Material Permissions Email Alerts Subscription Author Choice Supplementary The Journal of Immunology The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2013 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. This information is current as of September 24, 2021. Published March 18, 2013, doi:10.4049/jimmunol.1202267 The Journal of Immunology Coordinated Changes in DNA Methylation in Antigen-Specific Memory CD4 T Cells Shin-ichi Hashimoto,*,†,‡ Katsumi Ogoshi,* Atsushi Sasaki,† Jun Abe,* Wei Qu,† Yoichiro Nakatani,† Budrul Ahsan,x Kenshiro Oshima,† Francis H. -
A Yeast Phenomic Model for the Influence of Warburg Metabolism on Genetic Buffering of Doxorubicin Sean M
Santos and Hartman Cancer & Metabolism (2019) 7:9 https://doi.org/10.1186/s40170-019-0201-3 RESEARCH Open Access A yeast phenomic model for the influence of Warburg metabolism on genetic buffering of doxorubicin Sean M. Santos and John L. Hartman IV* Abstract Background: The influence of the Warburg phenomenon on chemotherapy response is unknown. Saccharomyces cerevisiae mimics the Warburg effect, repressing respiration in the presence of adequate glucose. Yeast phenomic experiments were conducted to assess potential influences of Warburg metabolism on gene-drug interaction underlying the cellular response to doxorubicin. Homologous genes from yeast phenomic and cancer pharmacogenomics data were analyzed to infer evolutionary conservation of gene-drug interaction and predict therapeutic relevance. Methods: Cell proliferation phenotypes (CPPs) of the yeast gene knockout/knockdown library were measured by quantitative high-throughput cell array phenotyping (Q-HTCP), treating with escalating doxorubicin concentrations under conditions of respiratory or glycolytic metabolism. Doxorubicin-gene interaction was quantified by departure of CPPs observed for the doxorubicin-treated mutant strain from that expected based on an interaction model. Recursive expectation-maximization clustering (REMc) and Gene Ontology (GO)-based analyses of interactions identified functional biological modules that differentially buffer or promote doxorubicin cytotoxicity with respect to Warburg metabolism. Yeast phenomic and cancer pharmacogenomics data were integrated to predict differential gene expression causally influencing doxorubicin anti-tumor efficacy. Results: Yeast compromised for genes functioning in chromatin organization, and several other cellular processes are more resistant to doxorubicin under glycolytic conditions. Thus, the Warburg transition appears to alleviate requirements for cellular functions that buffer doxorubicin cytotoxicity in a respiratory context.