Fhl1p Protein, a Positive Transcription Factor in Pichia Pastoris, Enhances
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Ovulation-Selective Genes: the Generation and Characterization of an Ovulatory-Selective Cdna Library
531 Ovulation-selective genes: the generation and characterization of an ovulatory-selective cDNA library A Hourvitz1,2*, E Gershon2*, J D Hennebold1, S Elizur2, E Maman2, C Brendle1, E Y Adashi1 and N Dekel2 1Division of Reproductive Sciences, Department of Obstetrics and Gynecology, University of Utah Health Sciences Center, Salt Lake City, Utah 84132, USA 2Department of Biological Regulation, Weizmann Institute of Science, Rehovot, Israel (Requests for offprints should be addressed to N Dekel; Email: [email protected]) *(A Hourvitz and E Gershon contributed equally to this paper) (J D Hennebold is now at Division of Reproductive Sciences, Oregon National Primate Research Center, Oregon Health and Science University, Beaverton, Oregon 97006, USA) Abstract Ovulation-selective/specific genes, that is, genes prefer- (FAE-1) homolog, found to be localized to the inner entially or exclusively expressed during the ovulatory periantral granulosa and to the cumulus granulosa cells of process, have been the subject of growing interest. We antral follicles. The FAE-1 gene is a -ketoacyl-CoA report herein studies on the use of suppression subtractive synthase belonging to the fatty acid elongase (ELO) hybridization (SSH) to construct a ‘forward’ ovulation- family, which catalyzes the initial step of very long-chain selective/specific cDNA library. In toto, 485 clones were fatty acid synthesis. All in all, the present study accom- sequenced and analyzed for homology to known genes plished systematic identification of those hormonally with the basic local alignment tool (BLAST). Of those, regulated genes that are expressed in the ovary in an 252 were determined to be nonredundant. -
18S Rrna Is a Reliable Normalisation Gene for Real Time PCR Based On
Kuchipudi et al. Virology Journal 2012, 9:230 http://www.virologyj.com/content/9/1/230 METHODOLOGY Open Access 18S rRNA is a reliable normalisation gene for real time PCR based on influenza virus infected cells Suresh V Kuchipudi1*, Meenu Tellabati1, Rahul K Nelli1, Gavin A White2, Belinda Baquero Perez1, Sujith Sebastian1, Marek J Slomka3, Sharon M Brookes3, Ian H Brown3, Stephen P Dunham1 and Kin-Chow Chang1 Abstract Background: One requisite of quantitative reverse transcription PCR (qRT-PCR) is to normalise the data with an internal reference gene that is invariant regardless of treatment, such as virus infection. Several studies have found variability in the expression of commonly used housekeeping genes, such as beta-actin (ACTB) and glyceraldehyde-3-phosphate dehydrogenase (GAPDH), under different experimental settings. However, ACTB and GAPDH remain widely used in the studies of host gene response to virus infections, including influenza viruses. To date no detailed study has been described that compares the suitability of commonly used housekeeping genes in influenza virus infections. The present study evaluated several commonly used housekeeping genes [ACTB, GAPDH, 18S ribosomal RNA (18S rRNA), ATP synthase, H+ transporting, mitochondrial F1 complex, beta polypeptide (ATP5B) and ATP synthase, H+ transporting, mitochondrial Fo complex, subunit C1 (subunit 9) (ATP5G1)] to identify the most stably expressed gene in human, pig, chicken and duck cells infected with a range of influenza A virus subtypes. Results: The relative expression stability of commonly used housekeeping genes were determined in primary human bronchial epithelial cells (HBECs), pig tracheal epithelial cells (PTECs), and chicken and duck primary lung-derived cells infected with five influenza A virus subtypes. -
Supplementary Materials: Evaluation of Cytotoxicity and Α-Glucosidase Inhibitory Activity of Amide and Polyamino-Derivatives of Lupane Triterpenoids
Supplementary Materials: Evaluation of cytotoxicity and α-glucosidase inhibitory activity of amide and polyamino-derivatives of lupane triterpenoids Oxana B. Kazakova1*, Gul'nara V. Giniyatullina1, Akhat G. Mustafin1, Denis A. Babkov2, Elena V. Sokolova2, Alexander A. Spasov2* 1Ufa Institute of Chemistry of the Ufa Federal Research Centre of the Russian Academy of Sciences, 71, pr. Oktyabrya, 450054 Ufa, Russian Federation 2Scientific Center for Innovative Drugs, Volgograd State Medical University, Novorossiyskaya st. 39, Volgograd 400087, Russian Federation Correspondence Prof. Dr. Oxana B. Kazakova Ufa Institute of Chemistry of the Ufa Federal Research Centre of the Russian Academy of Sciences 71 Prospeсt Oktyabrya Ufa, 450054 Russian Federation E-mail: [email protected] Prof. Dr. Alexander A. Spasov Scientific Center for Innovative Drugs of the Volgograd State Medical University 39 Novorossiyskaya st. Volgograd, 400087 Russian Federation E-mail: [email protected] Figure S1. 1H and 13C of compound 2. H NH N H O H O H 2 2 Figure S2. 1H and 13C of compound 4. NH2 O H O H CH3 O O H H3C O H 4 3 Figure S3. Anticancer screening data of compound 2 at single dose assay 4 Figure S4. Anticancer screening data of compound 7 at single dose assay 5 Figure S5. Anticancer screening data of compound 8 at single dose assay 6 Figure S6. Anticancer screening data of compound 9 at single dose assay 7 Figure S7. Anticancer screening data of compound 12 at single dose assay 8 Figure S8. Anticancer screening data of compound 13 at single dose assay 9 Figure S9. Anticancer screening data of compound 14 at single dose assay 10 Figure S10. -
Systematic Identification of Housekeeping Genes Possibly Used As References in Caenorhabditis Elegans by Large-Scale Data Integration
cells Article Systematic Identification of Housekeeping Genes Possibly Used as References in Caenorhabditis elegans by Large-Scale Data Integration 1, 1, 1 1 1 1 1 Jingxin Tao y, Youjin Hao y, Xudong Li , Huachun Yin , Xiner Nie , Jie Zhang , Boying Xu , Qiao Chen 2 and Bo Li 1,* 1 College of Life Sciences, Chongqing Normal University, Chongqing 401331, China; [email protected] (J.T.); [email protected] (Y.H.); [email protected] (X.L.); [email protected] (H.Y.); [email protected] (X.N.); [email protected] (J.Z.); [email protected] (B.X.) 2 Scientific Research Office, Chongqing Normal University, Chongqing 401331, China; [email protected] * Correspondence: [email protected]; Tel.: +86-23-6591-0315 These authors contributed equally to this work. y Received: 24 January 2020; Accepted: 11 March 2020; Published: 24 March 2020 Abstract: For accurate gene expression quantification, normalization of gene expression data against reliable reference genes is required. It is known that the expression levels of commonly used reference genes vary considerably under different experimental conditions, and therefore, their use for data normalization is limited. In this study, an unbiased identification of reference genes in Caenorhabditis elegans was performed based on 145 microarray datasets (2296 gene array samples) covering different developmental stages, different tissues, drug treatments, lifestyle, and various stresses. As a result, thirteen housekeeping genes (rps-23, rps-26, rps-27, rps-16, rps-2, rps-4, rps-17, rpl-24.1, rpl-27, rpl-33, rpl-36, rpl-35, and rpl-15) with enhanced stability were comprehensively identified by using six popular normalization algorithms and RankAggreg method. -
Analysis of Gene Expression Data for Gene Ontology
ANALYSIS OF GENE EXPRESSION DATA FOR GENE ONTOLOGY BASED PROTEIN FUNCTION PREDICTION A Thesis Presented to The Graduate Faculty of The University of Akron In Partial Fulfillment of the Requirements for the Degree Master of Science Robert Daniel Macholan May 2011 ANALYSIS OF GENE EXPRESSION DATA FOR GENE ONTOLOGY BASED PROTEIN FUNCTION PREDICTION Robert Daniel Macholan Thesis Approved: Accepted: _______________________________ _______________________________ Advisor Department Chair Dr. Zhong-Hui Duan Dr. Chien-Chung Chan _______________________________ _______________________________ Committee Member Dean of the College Dr. Chien-Chung Chan Dr. Chand K. Midha _______________________________ _______________________________ Committee Member Dean of the Graduate School Dr. Yingcai Xiao Dr. George R. Newkome _______________________________ Date ii ABSTRACT A tremendous increase in genomic data has encouraged biologists to turn to bioinformatics in order to assist in its interpretation and processing. One of the present challenges that need to be overcome in order to understand this data more completely is the development of a reliable method to accurately predict the function of a protein from its genomic information. This study focuses on developing an effective algorithm for protein function prediction. The algorithm is based on proteins that have similar expression patterns. The similarity of the expression data is determined using a novel measure, the slope matrix. The slope matrix introduces a normalized method for the comparison of expression levels throughout a proteome. The algorithm is tested using real microarray gene expression data. Their functions are characterized using gene ontology annotations. The results of the case study indicate the protein function prediction algorithm developed is comparable to the prediction algorithms that are based on the annotations of homologous proteins. -
Allele-Specific Expression of Ribosomal Protein Genes in Interspecific Hybrid Catfish
Allele-specific Expression of Ribosomal Protein Genes in Interspecific Hybrid Catfish by Ailu Chen A dissertation submitted to the Graduate Faculty of Auburn University in partial fulfillment of the requirements for the Degree of Doctor of Philosophy Auburn, Alabama August 1, 2015 Keywords: catfish, interspecific hybrids, allele-specific expression, ribosomal protein Copyright 2015 by Ailu Chen Approved by Zhanjiang Liu, Chair, Professor, School of Fisheries, Aquaculture and Aquatic Sciences Nannan Liu, Professor, Entomology and Plant Pathology Eric Peatman, Associate Professor, School of Fisheries, Aquaculture and Aquatic Sciences Aaron M. Rashotte, Associate Professor, Biological Sciences Abstract Interspecific hybridization results in a vast reservoir of allelic variations, which may potentially contribute to phenotypical enhancement in the hybrids. Whether the allelic variations are related to the downstream phenotypic differences of interspecific hybrid is still an open question. The recently developed genome-wide allele-specific approaches that harness high- throughput sequencing technology allow direct quantification of allelic variations and gene expression patterns. In this work, I investigated allele-specific expression (ASE) pattern using RNA-Seq datasets generated from interspecific catfish hybrids. The objective of the study is to determine the ASE genes and pathways in which they are involved. Specifically, my study investigated ASE-SNPs, ASE-genes, parent-of-origins of ASE allele and how ASE would possibly contribute to heterosis. My data showed that ASE was operating in the interspecific catfish system. Of the 66,251 and 177,841 SNPs identified from the datasets of the liver and gill, 5,420 (8.2%) and 13,390 (7.5%) SNPs were identified as significant ASE-SNPs, respectively. -
Analysis of the Stability of 70 Housekeeping Genes During Ips Reprogramming Yulia Panina1,2*, Arno Germond1 & Tomonobu M
www.nature.com/scientificreports OPEN Analysis of the stability of 70 housekeeping genes during iPS reprogramming Yulia Panina1,2*, Arno Germond1 & Tomonobu M. Watanabe1 Studies on induced pluripotent stem (iPS) cells highly rely on the investigation of their gene expression which requires normalization by housekeeping genes. Whether the housekeeping genes are stable during the iPS reprogramming, a transition of cell state known to be associated with profound changes, has been overlooked. In this study we analyzed the expression patterns of the most comprehensive list to date of housekeeping genes during iPS reprogramming of a mouse neural stem cell line N31. Our results show that housekeeping genes’ expression fuctuates signifcantly during the iPS reprogramming. Clustering analysis shows that ribosomal genes’ expression is rising, while the expression of cell-specifc genes, such as vimentin (Vim) or elastin (Eln), is decreasing. To ensure the robustness of the obtained data, we performed a correlative analysis of the genes. Overall, all 70 genes analyzed changed the expression more than two-fold during the reprogramming. The scale of this analysis, that takes into account 70 previously known and newly suggested genes, allowed us to choose the most stable of all genes. We highlight the fact of fuctuation of housekeeping genes during iPS reprogramming, and propose that, to ensure robustness of qPCR experiments in iPS cells, housekeeping genes should be used together in combination, and with a prior testing in a specifc line used in each study. We suggest that the longest splice variants of Rpl13a, Rplp1 and Rps18 can be used as a starting point for such initial testing as the most stable candidates. -
Supplementary Figures 1-14 and Supplementary References
SUPPORTING INFORMATION Spatial Cross-Talk Between Oxidative Stress and DNA Replication in Human Fibroblasts Marko Radulovic,1,2 Noor O Baqader,1 Kai Stoeber,3† and Jasminka Godovac-Zimmermann1* 1Division of Medicine, University College London, Center for Nephrology, Royal Free Campus, Rowland Hill Street, London, NW3 2PF, UK. 2Insitute of Oncology and Radiology, Pasterova 14, 11000 Belgrade, Serbia 3Research Department of Pathology and UCL Cancer Institute, Rockefeller Building, University College London, University Street, London WC1E 6JJ, UK †Present Address: Shionogi Europe, 33 Kingsway, Holborn, London WC2B 6UF, UK TABLE OF CONTENTS 1. Supplementary Figures 1-14 and Supplementary References. Figure S-1. Network and joint spatial razor plot for 18 enzymes of glycolysis and the pentose phosphate shunt. Figure S-2. Correlation of SILAC ratios between OXS and OAC for proteins assigned to the SAME class. Figure S-3. Overlap matrix (r = 1) for groups of CORUM complexes containing 19 proteins of the 49-set. Figure S-4. Joint spatial razor plots for the Nop56p complex and FIB-associated complex involved in ribosome biogenesis. Figure S-5. Analysis of the response of emerin nuclear envelope complexes to OXS and OAC. Figure S-6. Joint spatial razor plots for the CCT protein folding complex, ATP synthase and V-Type ATPase. Figure S-7. Joint spatial razor plots showing changes in subcellular abundance and compartmental distribution for proteins annotated by GO to nucleocytoplasmic transport (GO:0006913). Figure S-8. Joint spatial razor plots showing changes in subcellular abundance and compartmental distribution for proteins annotated to endocytosis (GO:0006897). Figure S-9. Joint spatial razor plots for 401-set proteins annotated by GO to small GTPase mediated signal transduction (GO:0007264) and/or GTPase activity (GO:0003924). -
1 AGING Supplementary Table 2
SUPPLEMENTARY TABLES Supplementary Table 1. Details of the eight domain chains of KIAA0101. Serial IDENTITY MAX IN COMP- INTERFACE ID POSITION RESOLUTION EXPERIMENT TYPE number START STOP SCORE IDENTITY LEX WITH CAVITY A 4D2G_D 52 - 69 52 69 100 100 2.65 Å PCNA X-RAY DIFFRACTION √ B 4D2G_E 52 - 69 52 69 100 100 2.65 Å PCNA X-RAY DIFFRACTION √ C 6EHT_D 52 - 71 52 71 100 100 3.2Å PCNA X-RAY DIFFRACTION √ D 6EHT_E 52 - 71 52 71 100 100 3.2Å PCNA X-RAY DIFFRACTION √ E 6GWS_D 41-72 41 72 100 100 3.2Å PCNA X-RAY DIFFRACTION √ F 6GWS_E 41-72 41 72 100 100 2.9Å PCNA X-RAY DIFFRACTION √ G 6GWS_F 41-72 41 72 100 100 2.9Å PCNA X-RAY DIFFRACTION √ H 6IIW_B 2-11 2 11 100 100 1.699Å UHRF1 X-RAY DIFFRACTION √ www.aging-us.com 1 AGING Supplementary Table 2. Significantly enriched gene ontology (GO) annotations (cellular components) of KIAA0101 in lung adenocarcinoma (LinkedOmics). Leading Description FDR Leading Edge Gene EdgeNum RAD51, SPC25, CCNB1, BIRC5, NCAPG, ZWINT, MAD2L1, SKA3, NUF2, BUB1B, CENPA, SKA1, AURKB, NEK2, CENPW, HJURP, NDC80, CDCA5, NCAPH, BUB1, ZWILCH, CENPK, KIF2C, AURKA, CENPN, TOP2A, CENPM, PLK1, ERCC6L, CDT1, CHEK1, SPAG5, CENPH, condensed 66 0 SPC24, NUP37, BLM, CENPE, BUB3, CDK2, FANCD2, CENPO, CENPF, BRCA1, DSN1, chromosome MKI67, NCAPG2, H2AFX, HMGB2, SUV39H1, CBX3, TUBG1, KNTC1, PPP1CC, SMC2, BANF1, NCAPD2, SKA2, NUP107, BRCA2, NUP85, ITGB3BP, SYCE2, TOPBP1, DMC1, SMC4, INCENP. RAD51, OIP5, CDK1, SPC25, CCNB1, BIRC5, NCAPG, ZWINT, MAD2L1, SKA3, NUF2, BUB1B, CENPA, SKA1, AURKB, NEK2, ESCO2, CENPW, HJURP, TTK, NDC80, CDCA5, BUB1, ZWILCH, CENPK, KIF2C, AURKA, DSCC1, CENPN, CDCA8, CENPM, PLK1, MCM6, ERCC6L, CDT1, HELLS, CHEK1, SPAG5, CENPH, PCNA, SPC24, CENPI, NUP37, FEN1, chromosomal 94 0 CENPL, BLM, KIF18A, CENPE, MCM4, BUB3, SUV39H2, MCM2, CDK2, PIF1, DNA2, region CENPO, CENPF, CHEK2, DSN1, H2AFX, MCM7, SUV39H1, MTBP, CBX3, RECQL4, KNTC1, PPP1CC, CENPP, CENPQ, PTGES3, NCAPD2, DYNLL1, SKA2, HAT1, NUP107, MCM5, MCM3, MSH2, BRCA2, NUP85, SSB, ITGB3BP, DMC1, INCENP, THOC3, XPO1, APEX1, XRCC5, KIF22, DCLRE1A, SEH1L, XRCC3, NSMCE2, RAD21. -
Anti-MRPS17 Monoclonal Antibody, Clone FQS23694 (DCABH-6110) This Product Is for Research Use Only and Is Not Intended for Diagnostic Use
Anti-MRPS17 monoclonal antibody, clone FQS23694 (DCABH-6110) This product is for research use only and is not intended for diagnostic use. PRODUCT INFORMATION Product Overview Rabbit monoclonal to MRPS17 Antigen Description Mammalian mitochondrial ribosomal proteins are encoded by nuclear genes and help in protein synthesis within the mitochondrion. Mitochondrial ribosomes (mitoribosomes) consist of a small 28S subunit and a large 39S subunit. They have an estimated 75% protein to rRNA composition compared to prokaryotic ribosomes, where this ratio is reversed. Another difference between mammalian mitoribosomes and prokaryotic ribosomes is that the latter contain a 5S rRNA. Among different species, the proteins comprising the mitoribosome differ greatly in sequence, and sometimes in biochemical properties, which prevents easy recognition by sequence homology. This gene encodes a 28S subunit protein that belongs to the ribosomal protein S17P family. The encoded protein is moderately conserved between human mitochondrial and prokaryotic ribosomal proteins. Pseudogenes corresponding to this gene are found on chromosomes 1p, 3p, 6q, 14p, 18q, and Xq. Immunogen Recombinant fragment within Human MRPS17. The exact sequence is proprietary.Database link: Q9Y2R5 Isotype IgG Source/Host Rabbit Species Reactivity Human Clone FQS23694 Purity Tissue culture supernatant Conjugate Unconjugated Applications IHC-P, WB, ICC/IF, IP Positive Control HeLa, HepG2 and U937 cell lysate; Human kidney and liver tissue; HeLa cells Format Liquid Size 100 μl Buffer pH: 7.2; Preservative: 0.01% Sodium azide; Constituents: 49% PBS, 0.05% BSA, 50% Glycerol 45-1 Ramsey Road, Shirley, NY 11967, USA Email: [email protected] Tel: 1-631-624-4882 Fax: 1-631-938-8221 1 © Creative Diagnostics All Rights Reserved Preservative 0.01% Sodium Azide Storage Store at +4°C short term (1-2 weeks). -
Micrornas Mediated Regulation of the Ribosomal Proteins and Its Consequences on the Global Translation of Proteins
cells Review microRNAs Mediated Regulation of the Ribosomal Proteins and Its Consequences on the Global Translation of Proteins Abu Musa Md Talimur Reza 1,2 and Yu-Guo Yuan 1,3,* 1 Jiangsu Co-Innovation Center of Prevention and Control of Important Animal Infectious Diseases and Zoonoses, College of Veterinary Medicine, Yangzhou University, Yangzhou 225009, China; [email protected] 2 Institute of Biochemistry and Biophysics, Polish Academy of Sciences, Pawi´nskiego5a, 02-106 Warsaw, Poland 3 Jiangsu Key Laboratory of Zoonosis/Joint International Research Laboratory of Agriculture and Agri-Product Safety, The Ministry of Education of China, Yangzhou University, Yangzhou 225009, China * Correspondence: [email protected]; Tel.: +86-514-8797-9228 Abstract: Ribosomal proteins (RPs) are mostly derived from the energy-consuming enzyme families such as ATP-dependent RNA helicases, AAA-ATPases, GTPases and kinases, and are important structural components of the ribosome, which is a supramolecular ribonucleoprotein complex, composed of Ribosomal RNA (rRNA) and RPs, coordinates the translation and synthesis of proteins with the help of transfer RNA (tRNA) and other factors. Not all RPs are indispensable; in other words, the ribosome could be functional and could continue the translation of proteins instead of lacking in some of the RPs. However, the lack of many RPs could result in severe defects in the biogenesis of ribosomes, which could directly influence the overall translation processes and global expression of the proteins leading to the emergence of different diseases including cancer. While microRNAs (miRNAs) are small non-coding RNAs and one of the potent regulators of the post-transcriptional 0 gene expression, miRNAs regulate gene expression by targeting the 3 untranslated region and/or coding region of the messenger RNAs (mRNAs), and by interacting with the 50 untranslated region, Citation: Reza, A.M.M.T.; Yuan, Y.-G. -
A Common Analgesic Enhances the Anti-Tumour Activity of 5-Aza-2’- Deoxycytidine Through Induction of Oxidative Stress
bioRxiv preprint doi: https://doi.org/10.1101/2020.03.31.017947; this version posted April 1, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. A common analgesic enhances the anti-tumour activity of 5-aza-2’- deoxycytidine through induction of oxidative stress Hannah J. Gleneadie1,10, Amy H. Baker1, Nikolaos Batis2, Jennifer Bryant2, Yao Jiang3, Samuel J.H. Clokie4, Hisham Mehanna2, Paloma Garcia5, Deena M.A. Gendoo6, Sally Roberts5, Alfredo A. Molinolo7, J. Silvio Gutkind8, Ben A. Scheven1, Paul R. Cooper1, Farhat L. Khanim9 and Malgorzata Wiench1, 5,*. 1School of Dentistry, Institute of Clinical Studies, College of Medical and Dental Sciences, The University of Birmingham, Birmingham, B5 7EG, UK; 2Institute of Head and Neck Studies and Education (InHANSE), The University of Birmingham, Birmingham, B15 2TT, UK; 3School of Biosciences, The University of Birmingham, Birmingham, B15 2TT, UK; 4West Midlands Regional Genetics Laboratory, Birmingham Women’s and Children’s Hospital, Birmingham, B15 2TG, UK; 5Institute of Cancer and Genomic Sciences, College of Medical and Dental Sciences, The University of Birmingham, Birmingham, B15 2TT, UK; 6Centre for Computational Biology, Institute of Cancer and Genomic Sciences, The University of Birmingham, Birmingham, B15 2TT, UK; 7Moores Cancer Center and Department of Pathology, University of California San Diego, La Jolla, CA 92093, USA; 8Department of Pharmacology and Moores Cancer