Nutrient-Dependent Control of RNA Polymerase II Elongation Rate Regulates Specific Gene Expression Programs by Alternative Polyadenylation
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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. -
Regulation of Components of the Pseudomonas Aeruginosa Phosphate-Starvation-Inducible Regulon in Escherichia Coii
Molecular Microbiology (1988) 2(3), 347-352 Regulation of components of the Pseudomonas aeruginosa phosphate-starvation-inducible regulon in Escherichia coii R. J. Siehnel, E. A. Worobec and R. E. W. Hancock* of the structural elements of the Pho regulon since, in such Department ot Microbioiogy, University ot British mutants, another regulatory gene product, PhoM, will tran- Columbia, Vancouver, British Columbia, Canada scriptionally activate PhoB. The PhoM activator is not con- V6T1W5. trolled by changes in phosphate levels and is repressed when PhoR is functional. Summary Conditions of low environmental phosphate stimulate the co-induction, in E. coli, of an outer membrane porin Plasmids pPBP and pRS-XP containing the cloned (PhoE), a periplasmic phosphate-binding protein (PhoS), genes for the Pseudomonas aeruginosa phosphate- and a periplasmic alkaline phosphatase (PhoA). JUephoB starvation-inducible periplasmic phosphate-binding gene product appears to activate the transcription of each protein and outer membrane porin P {oprP), respec- of these genes by interacting with specific regulation tively, were introduced into various Escherichia coti sequences located in analogous regions upstream from Pho-regulon regulatory mutants. Using Western the structural genes. These sequences are highly hom- immunoblots and specific antisera, the production of ologous and have been termed the 'Pho box' (Shinagawa both gene products was observed to be under the etai., 1987). control of regulatory elements of the E. coti Pho regu- Phosphate transport has been examined in several other lon. Sequencing of the region upstream of the trans- bacterial species and recent evidence suggests that a lationai start site of the oprP gene revealed a 'Pho phosphate-starvation-inducible regulon, similar to that box' with strong homology to the E. -
A Computational and Evolutionary Approach to Understanding Cryptic Unstable Transcripts in Yeast
A Computational and Evolutionary Approach to Understanding Cryptic Unstable Transcripts in Yeast By Jessica M. Vera B.S. University of Wisconsin-Madison, 2007 A thesis submitted to the Faculty of the Graduate School in partial fulfillment of the requirements for the degree of Doctor of Philosophy Department of Molecular, Cellular, and Developmental Biology 2015 This thesis entitled: A Computational and Evolutionary Approach to Understanding Cryptic Unstable Transcripts in Yeast written by Jessica M. Vera has been approved for the Department of Molecular, Cellular, and Developmental Biology Tom Blumenthal Robin Dowell Date The final copy of this thesis has been examined by the signatories, and we find that both the content and the form meet acceptable presentation standards of scholarly work in the above mentioned discipline iii Vera, Jessica M. (Ph.D., Molecular, Cellular and Developmental Biology) A Computational and Evolutionary Approach to Understanding Cryptic Unstable Transcripts in Yeast Thesis Directed by Robin Dowell Cryptic unstable transcripts (CUTs) are a largely unexplored class of nuclear exosome degraded, non-coding RNAs in budding yeast. It is highly debated whether CUT transcription has a functional role in the cell or whether CUTs represent noise in the yeast transcriptome. I sought to ascertain the extent of conserved CUT expression across a variety of Saccharomyces yeast strains to further understand and characterize the nature of CUT expression. To this end I designed a Hidden Markov Model (HMM) to analyze strand-specific RNA sequencing data from nuclear exosome rrp6Δ mutants to identify and compare CUTs in four different yeast strains: S288c, Σ1278b, JAY291 (S.cerevisiae) and N17 (S.paradoxus). -
PAR-CLIP Data Indicate That Nrd1-Nab3
Webb et al. Genome Biology 2014, 15:R8 http://genomebiology.com/2014/15/1/R8 RESEARCH Open Access PAR-CLIP data indicate that Nrd1-Nab3-dependent transcription termination regulates expression of hundreds of protein coding genes in yeast Shaun Webb2, Ralph D Hector1, Grzegorz Kudla3 and Sander Granneman1,2* Abstract Background: Nrd1 and Nab3 are essential sequence-specific yeast RNA binding proteins that function as a heterodimer in the processing and degradation of diverse classes of RNAs. These proteins also regulate several mRNA coding genes; however, it remains unclear exactly what percentage of the mRNA component of the transcriptome these proteins control. To address this question, we used the pyCRAC software package developed in our laboratory to analyze CRAC and PAR-CLIP data for Nrd1-Nab3-RNA interactions. Results: We generated high-resolution maps of Nrd1-Nab3-RNA interactions, from which we have uncovered hundreds of new Nrd1-Nab3 mRNA targets, representing between 20 and 30% of protein-coding transcripts. Although Nrd1 and Nab3 showed a preference for binding near 5′ ends of relatively short transcripts, they bound transcripts throughout coding sequences and 3′ UTRs. Moreover, our data for Nrd1-Nab3 binding to 3′ UTRs was consistent with a role for these proteins in the termination of transcription. Our data also support a tight integration of Nrd1-Nab3 with the nutrient response pathway. Finally, we provide experimental evidence for some of our predictions, using northern blot and RT-PCR assays. Conclusions: Collectively, our data support the notion that Nrd1 and Nab3 function is tightly integrated with the nutrient response and indicate a role for these proteins in the regulation of many mRNA coding genes. -
RNA Polymerase II CTD Phosphatase Rtr1 Fine-Tunes Transcription Termination
PLOS GENETICS RESEARCH ARTICLE RNA Polymerase II CTD phosphatase Rtr1 fine-tunes transcription termination 1☯ 1☯ 1 Jose F. VictorinoID , Melanie J. FoxID , Whitney R. Smith-KinnamanID , Sarah A. Peck 1 1 1 1 1 JusticeID , Katlyn H. BurrissID , Asha K. Boyd , Megan A. Zimmerly , Rachel R. Chan , 1 2,3 1,3¤ Gerald O. Hunter , Yunlong LiuID , Amber L. MosleyID * 1 Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, Indiana, United States of America, 2 Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, United States of America, 3 Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, Indiana, United States of America a1111111111 a1111111111 ☯ These authors contributed equally to this work. a1111111111 ¤ Current address: Amber L. Mosley, Department of Biochemistry and Molecular Biology, Indiana University a1111111111 School of Medicine, Indianapolis, Indiana, United States of America a1111111111 * [email protected] Abstract OPEN ACCESS RNA Polymerase II (RNAPII) transcription termination is regulated by the phosphorylation Citation: Victorino JF, Fox MJ, Smith-Kinnaman status of the C-terminal domain (CTD). The phosphatase Rtr1 has been shown to regulate WR, Peck Justice SA, Burriss KH, Boyd AK, et al. serine 5 phosphorylation on the CTD; however, its role in the regulation of RNAPII termina- (2020) RNA Polymerase II CTD phosphatase Rtr1 tion has not been explored. As a consequence of RTR1 deletion, interactions within the ter- fine-tunes transcription termination. PLoS Genet mination machinery and between the termination machinery and RNAPII were altered as 16(3): e1008317. https://doi.org/10.1371/journal. -
Phosphate Uptake by the Phosphonate Transport System Phncde Raffaele Stasi†, Henrique Iglesias Neves† and Beny Spira*
Stasi et al. BMC Microbiology (2019) 19:79 https://doi.org/10.1186/s12866-019-1445-3 RESEARCH ARTICLE Open Access Phosphate uptake by the phosphonate transport system PhnCDE Raffaele Stasi†, Henrique Iglesias Neves† and Beny Spira* Abstract Background: Phosphate is a fundamental nutrient for all creatures. It is thus not surprising that a single bacterium carries different transport systems for this molecule, each usually operating under different environmental conditions. The phosphonate transport system of E. coli K-12 is cryptic due to an 8 bp insertion in the phnE ORF. Results: Here we report that an E. coli K-12 strain carrying the triple knockout pitA pst ugp reverted the phnE mutation when plated on complex medium containing phosphate as the main phosphorus source. It is also shown that PhnCDE takes up orthophosphate with transport kinetics compatible with that of the canonical transport system PitA and that Pi-uptake via PhnCDE is sufficient to enable bacterial growth. Ugp, a glycerol phosphate transporter, is unable to take up phosphate. Conclusions: The phosphonate transport system, which is normally cryptic in E. coli laboratory strains is activated upon selection in rich medium and takes up orthophosphate in the absence of the two canonical phosphate-uptake systems. Based on these findings, the PhnCDE system can be considered a genuine phosphate transport system. Keywords: Phosphonates, Phosphate, Phn, PHO regulon Background phosphatase (AP). Genes belonging to the PHO regu- Phosphorus is a macronutrient of utmost importance to lon are synchronously induced by Pi-shortage [2]. For the all living beings. It is thus not surprising that bacte- sake of simplicity, the operons pstSCAB-phoU, ugpBAEC, ria developed several different mechanisms of phospho- phnCDEFGHIJKLMNOP will be respectively shortened to rus acquisition. -
Aneuploidy: Using Genetic Instability to Preserve a Haploid Genome?
Health Science Campus FINAL APPROVAL OF DISSERTATION Doctor of Philosophy in Biomedical Science (Cancer Biology) Aneuploidy: Using genetic instability to preserve a haploid genome? Submitted by: Ramona Ramdath In partial fulfillment of the requirements for the degree of Doctor of Philosophy in Biomedical Science Examination Committee Signature/Date Major Advisor: David Allison, M.D., Ph.D. Academic James Trempe, Ph.D. Advisory Committee: David Giovanucci, Ph.D. Randall Ruch, Ph.D. Ronald Mellgren, Ph.D. Senior Associate Dean College of Graduate Studies Michael S. Bisesi, Ph.D. Date of Defense: April 10, 2009 Aneuploidy: Using genetic instability to preserve a haploid genome? Ramona Ramdath University of Toledo, Health Science Campus 2009 Dedication I dedicate this dissertation to my grandfather who died of lung cancer two years ago, but who always instilled in us the value and importance of education. And to my mom and sister, both of whom have been pillars of support and stimulating conversations. To my sister, Rehanna, especially- I hope this inspires you to achieve all that you want to in life, academically and otherwise. ii Acknowledgements As we go through these academic journeys, there are so many along the way that make an impact not only on our work, but on our lives as well, and I would like to say a heartfelt thank you to all of those people: My Committee members- Dr. James Trempe, Dr. David Giovanucchi, Dr. Ronald Mellgren and Dr. Randall Ruch for their guidance, suggestions, support and confidence in me. My major advisor- Dr. David Allison, for his constructive criticism and positive reinforcement. -
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. -
From Prokaryotic to Eukaryotic Cells
This is a repository copy of Pi sensing and signaling: from prokaryotic to eukaryotic cells. White Rose Research Online URL for this paper: http://eprints.whiterose.ac.uk/95967/ Version: Accepted Version Article: Wanjun, QI, Baldwin, SA, Muench, SP orcid.org/0000-0001-6869-4414 et al. (1 more author) (2016) Pi sensing and signaling: from prokaryotic to eukaryotic cells. Biochemical Society Transactions, 44 (3). pp. 766-773. ISSN 0300-5127 https://doi.org/10.1042/BST20160026 © 2016, The Author(s). Published by Portland Press Limited on behalf of the Biochemical Society. This is an author produced version of a paper published in Biochemical Society Transactions. Uploaded in accordance with the publisher's self-archiving policy. Reuse Unless indicated otherwise, fulltext items are protected by copyright with all rights reserved. The copyright exception in section 29 of the Copyright, Designs and Patents Act 1988 allows the making of a single copy solely for the purpose of non-commercial research or private study within the limits of fair dealing. The publisher or other rights-holder may allow further reproduction and re-use of this version - refer to the White Rose Research Online record for this item. Where records identify the publisher as the copyright holder, users can verify any specific terms of use on the publisher’s website. Takedown If you consider content in White Rose Research Online to be in breach of UK law, please notify us by emailing [email protected] including the URL of the record and the reason for the withdrawal -
Measuring Gene Expression Part 3 Key Steps in Microarray Analysis
Measuring Gene Expression Part 3 David Wishart Bioinformatics 301 [email protected] Key Steps in Microarray Analysis • Quality Control (checking microarrays for errors or problems) • Image Processing – Gridding – Segmentation (peak picking) – Data Extraction (intensity, QC) • Data Analysis and Data Mining Comet Tailing • Often caused by insufficiently rapid immersion of the slides in the succinic anhydride blocking solution. Uneven Spotting/Blotting • Problems with print tips or with overly viscous solution • Problems with humidity in spottiing chamber High Background • Insufficient Blocking • Precipitation of labelled probe Gridding Errors Spotting errors Uneven hybridization Gridding errors Key Steps in Microarray Analysis • Quality Control (checking microarrays for errors or problems) • Image Processing – Gridding – Segmentation (spot picking) – Data Extraction (intensity, QC) • Data Analysis and Data Mining Microarray Scanning PMT Pinhole Detector lens Laser Beam-splitter Objective Lens Dye Glass Slide Microarray Principles Laser 1 Laser 2 Green channel Red channel Scan and detect with overlay images Image process confocal laser system and normalize and analyze Microarray Images • Resolution – standard 10µm [currently, max 5µm] – 100µm spot on chip = 10 pixels in diameter • Image format – TIFF (tagged image file format) 16 bit (64K grey levels) – 1cm x 1cm image at 16 bit = 2Mb (uncompressed) – other formats exist i.e. SCN (Stanford University) • Separate image for each fluorescent sample – channel 1, channel 2, etc. Image -
Signal Transduction in the Control of Phosphate-Regulated Genes of Escherichia Coli
Kidney International, Vol. 49 (1996), pp. 964—967 Signal transduction in the control of phosphate-regulated genes of Escherichia coli BARRY L. WANNER Department of Biological Sciences, Purdue University, West Lafayette, Indiana, USA Bacteria such as Escherichia co/i regulate the synthesis of aunique proteins with signatures of a sensor kinase (transmitter) large number of proteins in response to extracellular inorganicdomain and 170 with signatures of a receiver domain have been phosphate (P) levels by activating transcription of co-regulatedidentified on the basis of sequence similarities at the protein level genes. More than 80 proteins are synthesized in increased(as determined from searching DNA databases for homologous amounts in response to P. limitation in the gram-negative bacte-proteins). Analogous signaling systems exist in eucaryotic cells rium E. co/i [1—3]. Many of these proteins are the products of a set including Saccharomyces cerevisiae [6—8], Arabidopsis thaliana [9], of co-regulated genes known as the phosphate (Pho) regulon.and Neurospora crassa [10]. In yeast, a two-component system Altogether 38 Pho regulon genes have now been characterized (by(SLN1 and SSK1) can provide signaling input to a MAP kinase cloning, sequencing, mutational analysis, and/or examination ofcascade that is responsive to small molecules [7, 11]. MAP kinase their gene products) in E. co/i, or the closely related bacteriacascades are extremely important in signaling; they are key Enterobacter aerogenes and Sa/monella typhimurium [4]. Thesecomponents of convergent signal transduction pathways in mam- genes are arranged in eight (or more) transcriptional units, andmalian cells [12, 13]. Although histidine phosphorylation has also their gene products probably all have a role in the assimilation ofbeen recently found in human cells [14], the phosphorylation alternative phosphorus (P) sources from the environment. -
Molecular Mechanisms of Phosphate Sensing, Transport and Signalling in Streptomyces and Related Actinobacteria
International Journal of Molecular Sciences Review Molecular Mechanisms of Phosphate Sensing, Transport and Signalling in Streptomyces and Related Actinobacteria Juan Francisco Martín * and Paloma Liras Department of Molecular Biology, Microbiology Section, University of León, 24071 León, Spain; [email protected] * Correspondence: [email protected] Abstract: Phosphorous, in the form of phosphate, is a key element in the nutrition of all living beings. In nature, it is present in the form of phosphate salts, organophosphates, and phosphonates. Bacteria transport inorganic phosphate by the high affinity phosphate transport system PstSCAB, and the low affinity PitH transporters. The PstSCAB system consists of four components. PstS is the phosphate binding protein and discriminates between arsenate and phosphate. In the Streptomyces species, the PstS protein, attached to the outer side of the cell membrane, is glycosylated and released as a soluble protein that lacks its phosphate binding ability. Transport of phosphate by the PstSCAB system is drastically regulated by the inorganic phosphate concentration and mediated by binding of phosphorylated PhoP to the promoter of the PstSCAB operon. In Mycobacterium smegmatis, an additional high affinity transport system, PhnCDE, is also under PhoP regulation. Additionally, Streptomyces have a duplicated low affinity phosphate transport system encoded by the pitH1–pitH2 genes. In this system phosphate is transported as a metal-phosphate complex in simport with protons. Expression of pitH2, but not that of pitH1 in Streptomyces coelicolor, is regulated by PhoP. Interestingly, in many Streptomyces species, three gene clusters pitH1–pstSCAB–ppk (for a polyphosphate kinase), are linked in a supercluster formed by nine genes related to phosphate metabolism.