Mouse Acsm3 Conditional Knockout Project (CRISPR/Cas9)
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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. -
Content Based Search in Gene Expression Databases and a Meta-Analysis of Host Responses to Infection
Content Based Search in Gene Expression Databases and a Meta-analysis of Host Responses to Infection A Thesis Submitted to the Faculty of Drexel University by Francis X. Bell in partial fulfillment of the requirements for the degree of Doctor of Philosophy November 2015 c Copyright 2015 Francis X. Bell. All Rights Reserved. ii Acknowledgments I would like to acknowledge and thank my advisor, Dr. Ahmet Sacan. Without his advice, support, and patience I would not have been able to accomplish all that I have. I would also like to thank my committee members and the Biomed Faculty that have guided me. I would like to give a special thanks for the members of the bioinformatics lab, in particular the members of the Sacan lab: Rehman Qureshi, Daisy Heng Yang, April Chunyu Zhao, and Yiqian Zhou. Thank you for creating a pleasant and friendly environment in the lab. I give the members of my family my sincerest gratitude for all that they have done for me. I cannot begin to repay my parents for their sacrifices. I am eternally grateful for everything they have done. The support of my sisters and their encouragement gave me the strength to persevere to the end. iii Table of Contents LIST OF TABLES.......................................................................... vii LIST OF FIGURES ........................................................................ xiv ABSTRACT ................................................................................ xvii 1. A BRIEF INTRODUCTION TO GENE EXPRESSION............................. 1 1.1 Central Dogma of Molecular Biology........................................... 1 1.1.1 Basic Transfers .......................................................... 1 1.1.2 Uncommon Transfers ................................................... 3 1.2 Gene Expression ................................................................. 4 1.2.1 Estimating Gene Expression ............................................ 4 1.2.2 DNA Microarrays ...................................................... -
Canonical Correlation Analysis for Gene-Based Pleiotropy Discovery
Canonical Correlation Analysis for Gene-Based Pleiotropy Discovery Jose A. Seoane1*, Colin Campbell2, Ian N. M. Day1, Juan P. Casas3, Tom R. Gaunt1,4 1 School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom, 2 Intelligent Systems Laboratory, University of Bristol, Bristol, United Kingdom, 3 Department of Non-communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom, 4 MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom Abstract Genome-wide association studies have identified a wealth of genetic variants involved in complex traits and multifactorial diseases. There is now considerable interest in testing variants for association with multiple phenotypes (pleiotropy) and for testing multiple variants for association with a single phenotype (gene-based association tests). Such approaches can increase statistical power by combining evidence for association over multiple phenotypes or genetic variants respectively. Canonical Correlation Analysis (CCA) measures the correlation between two sets of multidimensional variables, and thus offers the potential to combine these two approaches. To apply CCA, we must restrict the number of attributes relative to the number of samples. Hence we consider modules of genetic variation that can comprise a gene, a pathway or another biologically relevant grouping, and/or a set of phenotypes. In order to do this, we use an attribute selection strategy based on a binary genetic algorithm. Applied to a UK-based prospective cohort study of 4286 women (the British Women’s Heart and Health Study), we find improved statistical power in the detection of previously reported genetic associations, and identify a number of novel pleiotropic associations between genetic variants and phenotypes. -
Title: a Yeast Phenomic Model for the Influence of Warburg Metabolism on Genetic
bioRxiv preprint doi: https://doi.org/10.1101/517490; this version posted January 15, 2019. 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 4.0 International license. 1 Title Page: 2 3 Title: A yeast phenomic model for the influence of Warburg metabolism on genetic 4 buffering of doxorubicin 5 6 Authors: Sean M. Santos1 and John L. Hartman IV1 7 1. University of Alabama at Birmingham, Department of Genetics, Birmingham, AL 8 Email: [email protected], [email protected] 9 Corresponding author: [email protected] 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 1 bioRxiv preprint doi: https://doi.org/10.1101/517490; this version posted January 15, 2019. 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 4.0 International license. 26 Abstract: 27 Background: 28 Saccharomyces cerevisiae represses respiration in the presence of adequate glucose, 29 mimicking the Warburg effect, termed aerobic glycolysis. We conducted yeast phenomic 30 experiments to characterize differential doxorubicin-gene interaction, in the context of 31 respiration vs. glycolysis. The resulting systems level biology about doxorubicin 32 cytotoxicity, including the influence of the Warburg effect, was integrated with cancer 33 pharmacogenomics data to identify potentially causal correlations between differential 34 gene expression and anti-cancer efficacy. -
Regulatory Genetics of Single Nucleotide Polymorphisms
UNIVERSITY OF CALIFORNIA, SAN DIEGO In Silico, In Vitro, In Vivo and In Populo: Regulatory Genetics of Single Nucleotide Polymorphisms in the Phenylethanolamine N-Methyltransferase Promoter A Dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Bioinformatics by Juan Lorenzo Rodriguez Flores Committee in charge: Professor Daniel T. O’Connor, Chair Professor Vineet Bafna Professor Shankar Subramanian Professor Glenn Tesler Professor Wei Wang Professor Michael Ziegler 2009 Copyright Juan Lorenzo Rodriguez Flores, 2009 All rights reserved. The Dissertation of Juan Lorenzo Rodriguez Flores is approved, and it is acceptable in quality and form for publication on microfilm and electronically: ___________________________________________________ ___________________________________________________ ___________________________________________________ ___________________________________________________ ___________________________________________________ ___________________________________________________ Chair University of California, San Diego 2009 iii DEDICATION I dedicate this dissertation to my family. The Rodriguez, Flores, Quesada and Forastieri of Puerto Rico, a tribe whose history, accomplishments and adventures constantly remind me of who I am, where I came from and what I am capable of. I also dedicate this dissertation to Tatiana, who first danced with me the day I advanced to candidacy and who shortly after became my soulmate and the love of my life. She provided infinite support, motivation and nourishment for my graduation. iv EPIGRAPH We have been told we cannot do this by a chorus of cynics who will only grow louder and more dissonant in the weeks to come. We've been asked to pause for a reality check. We've been warned against offering ... false hope. But in the unlikely story that is America, there has never been anything false about hope... -
Expression-Based GWAS Identifies Variants, Gene Interactions and Key
www.nature.com/scientificreports OPEN Expression-based GWAS identifies variants, gene interactions and key regulators affecting intramuscular Received: 12 February 2016 Accepted: 26 July 2016 fatty acid content and composition Published: 18 August 2016 in porcine meat Anna Puig-Oliveras1,2, Manuel Revilla1,2, Anna Castelló1,2, Ana I. Fernández3, Josep M. Folch1,2 & Maria Ballester1,2,4 The aim of this work is to better understand the genetic mechanisms determining two complex traits affecting porcine meat quality: intramuscular fat (IMF) content and its fatty acid (FA) composition. With this purpose, expression Genome-Wide Association Study (eGWAS) of 45 lipid-related genes associated with meat quality traits in swine muscle (Longissimus dorsi) of 114 Iberian × Landrace backcross animals was performed. The eGWAS identified 241 SNPs associated with 11 genes:ACSM5, CROT, FABP3, FOS, HIF1AN, IGF2, MGLL, NCOA1, PIK3R1, PLA2G12A and PPARA. Three expression Quantitative Trait Loci (eQTLs) for IGF2, ACSM5 and MGLL were identified, showingcis -acting effects, whereas 16 eQTLs had trans regulatory effects. A polymorphism in theACSM5 promoter region associated with its expression was identified. In addition, strong candidate genes regulatingACSM5, FOS, PPARA, PIK3R1, PLA2G12A and HIF1AN gene expression were also seen. Notably, the analysis highlighted the NR3C1 transcription factor as a strong candidate gene involved in the regulation of the 45 genes analysed. Finally, the IGF2, MGLL, MC2R, ARHGAP6, and NR3C1 genes were identified as potential regulators co-localizing within QTLs for fatness and growth traits in the IBMAP population. The results obtained increase our knowledge in the functional regulatory mechanisms involved in these complex traits. Pork-meat cuts and their derived products are paid according to the lean percentage in pork carcasses and meat quality, since they determine better acceptance for consumers1. -
Accurate Mutation Annotation and Functional Prediction Enhance the Applicability of -Omics Data in Precision Medicine
The Texas Medical Center Library DigitalCommons@TMC The University of Texas MD Anderson Cancer Center UTHealth Graduate School of The University of Texas MD Anderson Cancer Biomedical Sciences Dissertations and Theses Center UTHealth Graduate School of (Open Access) Biomedical Sciences 5-2016 Accurate mutation annotation and functional prediction enhance the applicability of -omics data in precision medicine Tenghui Chen Follow this and additional works at: https://digitalcommons.library.tmc.edu/utgsbs_dissertations Part of the Bioinformatics Commons, Computational Biology Commons, Genomics Commons, and the Medicine and Health Sciences Commons Recommended Citation Chen, Tenghui, "Accurate mutation annotation and functional prediction enhance the applicability of -omics data in precision medicine" (2016). The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences Dissertations and Theses (Open Access). 666. https://digitalcommons.library.tmc.edu/utgsbs_dissertations/666 This Dissertation (PhD) is brought to you for free and open access by the The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences at DigitalCommons@TMC. It has been accepted for inclusion in The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences Dissertations and Theses (Open Access) by an authorized administrator of DigitalCommons@TMC. For more information, please contact [email protected]. ACCURATE MUTATION ANNOTATION AND FUNCTIONAL PREDICTION -
A Two-Color Haploid Genetic Screen Identifies Novel Host Factors Involved in HIV Latency
bioRxiv preprint doi: https://doi.org/10.1101/2021.01.20.427543; this version posted January 22, 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 4.0 International license. A two-color haploid genetic screen identifies novel host factors involved in HIV latency Running Title: Identification of novel HIV latency host factors. Authors: Michael D Röling1, Mahsa Mollapour Sisakht1#, Enrico Ne1#, Panagiotis Moulos2#, Mateusz Stoszko1, Elisa De Crignis1, Helen Bodmer1, Tsung Wai Kan1, Maryam Akbarzadeh1, Vaggelis Harokopos2, Pantelis Hatzis2, Robert-Jan Palstra1*, Tokameh Mahmoudi1* # authors contributed equally Affiliations: 1 Department of Biochemistry, Erasmus University Medical Center, Ee634 PO Box 2040 3000CA Rotterdam, the Netherlands 2 Institute for Fundamental Biomedical Research, Biomedical Sciences Research Center, Alexander Fleming', Fleming, Fleming Street 34, 16672, Vari, Greece * Correspondence to: Tokameh Mahmoudi: [email protected], Phone N: +31 (0)107043324, Fax N: +31(0)10704747 Robert-Jan Palstra: [email protected] Phone N: +31 (0)107043323, Fax N: +31(0)10704747 1 bioRxiv preprint doi: https://doi.org/10.1101/2021.01.20.427543; this version posted January 22, 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 4.0 International license. Abstract To identify novel host factors as putative targets to reverse HIV latency, we performed an insertional mutagenesis genetic screen in a latently HIV-1-infected pseudo-haploid KBM7 cell line (Hap-Lat). -
Identification and Interaction Analysis of Key Genes and Micrornas In
Mou et al. World Journal of Surgical Oncology (2017) 15:63 DOI 10.1186/s12957-017-1127-2 RESEARCH Open Access Identification and interaction analysis of key genes and microRNAs in hepatocellular carcinoma by bioinformatics analysis Tong Mou†, Di Zhu†, Xufu Wei, Tingting Li, Daofeng Zheng, Junliang Pu, Zhen Guo and Zhongjun Wu* Abstract Background: Hepatocellular carcinoma (HCC) is the most common liver malignancy worldwide. However, present studies of its multiple gene interaction and cellular pathways still could not explain the initiation and development of HCC perfectly. To find the key genes and miRNAs as well as their potential molecular mechanisms in HCC, microarray data GSE22058, GSE25097, and GSE57958 were analyzed. Methods: The microarray datasets GSE22058, GSE25097, and GSE57958, including mRNA and miRNA profiles, were downloaded from the GEO database and were analyzed using GEO2R. Functional and pathway enrichment analyses were performed using the DAVID database, and the protein–protein interaction (PPI) network was constructed using the Cytoscape software. Finally, miRDB was applied to predict the targets of the differentially expressed miRNAs (DEMs). Results: A total of 115 differentially expressed genes (DEGs) were found in HCC, including 52 up-regulated genes and 63 down-regulated genes. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses from DAVID showed that up-regulated genes were significantly enriched in chromosome segregation and cell division, while the down-regulated genes were mainly involved in complement activation, protein activation cascades, carboxylic acid metabolic processes, oxoacid metabolic processes, and the immune response. From the PPI network, the 18 nodes with the highest degree were screened as hub genes. -
Thioesterase Induction by 2,3,7,8-Tetrachlorodibenzo-P-Dioxin
www.nature.com/scientificreports OPEN Thioesterase induction by 2,3, 7,8 ‑te tra chl orodib enz o‑ p ‑dioxin results in a futile cycle that inhibits hepatic β‑oxidation Giovan N. Cholico1,2, Russell R. Fling2,3, Nicholas A. Zacharewski1, Kelly A. Fader1,2, Rance Nault1,2 & Timothy R. Zacharewski1,2* 2,3,7,8‑Tetrachlorodibenzo‑p‑dioxin (TCDD), a persistent environmental contaminant, induces steatosis by increasing hepatic uptake of dietary and mobilized peripheral fats, inhibiting lipoprotein export, and repressing β‑oxidation. In this study, the mechanism of β‑oxidation inhibition was investigated by testing the hypothesis that TCDD dose‑dependently repressed straight‑chain fatty acid oxidation gene expression in mice following oral gavage every 4 days for 28 days. Untargeted metabolomic analysis revealed a dose‑dependent decrease in hepatic acyl‑CoA levels, while octenoyl‑ CoA and dicarboxylic acid levels increased. TCDD also dose‑dependently repressed the hepatic gene expression associated with triacylglycerol and cholesterol ester hydrolysis, fatty acid binding proteins, fatty acid activation, and 3‑ketoacyl‑CoA thiolysis while inducing acyl‑CoA hydrolysis. Moreover, octenoyl‑CoA blocked the hydration of crotonyl‑CoA suggesting short chain enoyl‑CoA hydratase (ECHS1) activity was inhibited. Collectively, the integration of metabolomics and RNA‑seq data suggested TCDD induced a futile cycle of fatty acid activation and acyl‑CoA hydrolysis resulting in incomplete β‑oxidation, and the accumulation octenoyl‑CoA levels that inhibited the activity of short chain enoyl‑CoA hydratase (ECHS1). Although the liver is the largest internal organ, it is second to adipose tissue in regard to lipid storage capacity. Approximately 15–25% (fasted vs fed state, respectively) are derived from chylomicron remnants, 5–30% (fasted vs fed state, respectively) from de novo lipogenesis, and 5–30% from visceral fat tissues 1. -
Chromosome 16 Update: Surfing Transcriptomics Landscapes
Chromosome 16 Update: Surfing transcriptomics landscapes. A step beyond the annotaon of Chr-16 proteome Fernando J Corrales, Concha Gil, Juan P Albar & Chr16-Spanish HPP ProteoRed-ISCIII, Spain SpHPP!Consortium! Spanish Human! Proteome Project ! Chromosome1! 6! AIMS • Chromosome 16 annotation. • Selection of 3 cell lines based on published transcriptomic profiles for maximum chromosome 16 coverage • Transcriptomic analysis of the selected cell lines. • Shotgun proteomic analysis of the selected cell lines. • Development of SRM methods for 200 proteins/year. • Expression of missing proteins and development of SRM methods. 32 research units organized in 5 WG: WG1. Protein expression and purification. Peptides. Transcriptomics. WG2. Development of quantitative S/MRM assays. WG3. Shotgun proteomics. Molecular profiles and PTMs. WG4. Bioinformatics WG5. Biology and disease. Neurodegenerative, cardiovascular, infectious, cancer, obesity, Rheumatic disorders. SpHPP!Consortium! Spanish Human! Proteome Project ! Chromosome1! 6! AIMS • Chromosome 16 annotation. • Selection of 3 cell lines based on published transcriptomic profiles for maximum chromosome 16 coverage • Transcriptomic analysis of the selected cell lines. • Shotgun proteomic analysis of the selected cell lines. • Development of SRM methods for 200 proteins/year. • Expression of missing proteins and development of SRM methods. Chromosome 16 known and missing proteins 484 HPA an=bodies for Chr16 proteins, 51 for unknown ENSEMBL v70 110 OMIM hits 2316 genes neXtProt Nov 2012 Obesity 886 -
Biomedical Informatics
BIOMEDICAL INFORMATICS Abstract GENE LIST AUTOMATICALLY DERIVED FOR YOU (GLAD4U): DERIVING AND PRIORITIZING GENE LISTS FROM PUBMED LITERATURE JEROME JOURQUIN Thesis under the direction of Professor Bing Zhang Answering questions such as ―Which genes are related to breast cancer?‖ usually requires retrieving relevant publications through the PubMed search engine, reading these publications, and manually creating gene lists. This process is both time-consuming and prone to errors. We report GLAD4U (Gene List Automatically Derived For You), a novel, free web-based gene retrieval and prioritization tool. The quality of gene lists created by GLAD4U for three Gene Ontology terms and three disease terms was assessed using ―gold standard‖ lists curated in public databases. We also compared the performance of GLAD4U with that of another gene prioritization software, EBIMed. GLAD4U has a high overall recall. Although precision is generally low, its prioritization methods successfully rank truly relevant genes at the top of generated lists to facilitate efficient browsing. GLAD4U is simple to use, and its interface can be found at: http://bioinfo.vanderbilt.edu/glad4u. Approved ___________________________________________ Date _____________ GENE LIST AUTOMATICALLY DERIVED FOR YOU (GLAD4U): DERIVING AND PRIORITIZING GENE LISTS FROM PUBMED LITERATURE By Jérôme Jourquin Thesis Submitted to the Faculty of the Graduate School of Vanderbilt University in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE in Biomedical Informatics May, 2010 Nashville, Tennessee Approved: Professor Bing Zhang Professor Hua Xu Professor Daniel R. Masys ACKNOWLEDGEMENTS I would like to express profound gratitude to my advisor, Dr. Bing Zhang, for his invaluable support, supervision and suggestions throughout this research work.