Glomerular Expression Pattern of Long Non-Coding Rnas in the Type 2
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PARSANA-DISSERTATION-2020.Pdf
DECIPHERING TRANSCRIPTIONAL PATTERNS OF GENE REGULATION: A COMPUTATIONAL APPROACH by Princy Parsana A dissertation submitted to The Johns Hopkins University in conformity with the requirements for the degree of Doctor of Philosophy Baltimore, Maryland July, 2020 © 2020 Princy Parsana All rights reserved Abstract With rapid advancements in sequencing technology, we now have the ability to sequence the entire human genome, and to quantify expression of tens of thousands of genes from hundreds of individuals. This provides an extraordinary opportunity to learn phenotype relevant genomic patterns that can improve our understanding of molecular and cellular processes underlying a trait. The high dimensional nature of genomic data presents a range of computational and statistical challenges. This dissertation presents a compilation of projects that were driven by the motivation to efficiently capture gene regulatory patterns in the human transcriptome, while addressing statistical and computational challenges that accompany this data. We attempt to address two major difficulties in this domain: a) artifacts and noise in transcriptomic data, andb) limited statistical power. First, we present our work on investigating the effect of artifactual variation in gene expression data and its impact on trans-eQTL discovery. Here we performed an in-depth analysis of diverse pre-recorded covariates and latent confounders to understand their contribution to heterogeneity in gene expression measurements. Next, we discovered 673 trans-eQTLs across 16 human tissues using v6 data from the Genotype Tissue Expression (GTEx) project. Finally, we characterized two trait-associated trans-eQTLs; one in Skeletal Muscle and another in Thyroid. Second, we present a principal component based residualization method to correct gene expression measurements prior to reconstruction of co-expression networks. -
Mir-379 Deletion Ameliorates Features of Diabetic Kidney Disease By
ARTICLE https://doi.org/10.1038/s42003-020-01516-w OPEN miR-379 deletion ameliorates features of diabetic kidney disease by enhancing adaptive mitophagy via FIS1 ✉ Mitsuo Kato 1,8 , Maryam Abdollahi 1,8, Ragadeepthi Tunduguru1, Walter Tsark2, Zhuo Chen 1, 1234567890():,; Xiwei Wu3, Jinhui Wang3, Zhen Bouman Chen 1,4, Feng-Mao Lin1, Linda Lanting1, Mei Wang1, Janice Huss5, ✉ Patrick T Fueger 5,6, David Chan7 & Rama Natarajan 1,4 Diabetic kidney disease (DKD) is a major complication of diabetes. Expression of members of the microRNA (miRNA) miR-379 cluster is increased in DKD. miR-379, the most upstream 5′-miRNA in the cluster, functions in endoplasmic reticulum (ER) stress by targeting EDEM3. However, the in vivo functions of miR-379 remain unclear. We created miR-379 knockout (KO) mice using CRISPR-Cas9 nickase and dual guide RNA technique and characterized their phenotype in diabetes. We screened for miR-379 targets in renal mesangial cells from WT vs. miR-379KO mice using AGO2-immunopreciptation and CLASH (cross-linking, ligation, sequencing hybrids) and identified the redox protein thioredoxin and mitochondrial fission-1 protein. miR-379KO mice were protected from features of DKD as well as body weight loss associated with mitochondrial dysfunction, ER- and oxidative stress. These results reveal a role for miR-379 in DKD and metabolic processes via reducing adaptive mitophagy. Strate- gies targeting miR-379 could offer therapeutic options for DKD. 1 Department of Diabetes Complications and Metabolism, Diabetes and Metabolism Research Institute, Beckman Research Institute of City of Hope, 1500 East Duarte Road, Duarte, CA 91010, USA. -
Identification of the Binding Partners for Hspb2 and Cryab Reveals
Brigham Young University BYU ScholarsArchive Theses and Dissertations 2013-12-12 Identification of the Binding arP tners for HspB2 and CryAB Reveals Myofibril and Mitochondrial Protein Interactions and Non- Redundant Roles for Small Heat Shock Proteins Kelsey Murphey Langston Brigham Young University - Provo Follow this and additional works at: https://scholarsarchive.byu.edu/etd Part of the Microbiology Commons BYU ScholarsArchive Citation Langston, Kelsey Murphey, "Identification of the Binding Partners for HspB2 and CryAB Reveals Myofibril and Mitochondrial Protein Interactions and Non-Redundant Roles for Small Heat Shock Proteins" (2013). Theses and Dissertations. 3822. https://scholarsarchive.byu.edu/etd/3822 This Thesis is brought to you for free and open access by BYU ScholarsArchive. It has been accepted for inclusion in Theses and Dissertations by an authorized administrator of BYU ScholarsArchive. For more information, please contact [email protected], [email protected]. Identification of the Binding Partners for HspB2 and CryAB Reveals Myofibril and Mitochondrial Protein Interactions and Non-Redundant Roles for Small Heat Shock Proteins Kelsey Langston A thesis submitted to the faculty of Brigham Young University in partial fulfillment of the requirements for the degree of Master of Science Julianne H. Grose, Chair William R. McCleary Brian Poole Department of Microbiology and Molecular Biology Brigham Young University December 2013 Copyright © 2013 Kelsey Langston All Rights Reserved ABSTRACT Identification of the Binding Partners for HspB2 and CryAB Reveals Myofibril and Mitochondrial Protein Interactors and Non-Redundant Roles for Small Heat Shock Proteins Kelsey Langston Department of Microbiology and Molecular Biology, BYU Master of Science Small Heat Shock Proteins (sHSP) are molecular chaperones that play protective roles in cell survival and have been shown to possess chaperone activity. -
Seq2pathway Vignette
seq2pathway Vignette Bin Wang, Xinan Holly Yang, Arjun Kinstlick May 19, 2021 Contents 1 Abstract 1 2 Package Installation 2 3 runseq2pathway 2 4 Two main functions 3 4.1 seq2gene . .3 4.1.1 seq2gene flowchart . .3 4.1.2 runseq2gene inputs/parameters . .5 4.1.3 runseq2gene outputs . .8 4.2 gene2pathway . 10 4.2.1 gene2pathway flowchart . 11 4.2.2 gene2pathway test inputs/parameters . 11 4.2.3 gene2pathway test outputs . 12 5 Examples 13 5.1 ChIP-seq data analysis . 13 5.1.1 Map ChIP-seq enriched peaks to genes using runseq2gene .................... 13 5.1.2 Discover enriched GO terms using gene2pathway_test with gene scores . 15 5.1.3 Discover enriched GO terms using Fisher's Exact test without gene scores . 17 5.1.4 Add description for genes . 20 5.2 RNA-seq data analysis . 20 6 R environment session 23 1 Abstract Seq2pathway is a novel computational tool to analyze functional gene-sets (including signaling pathways) using variable next-generation sequencing data[1]. Integral to this tool are the \seq2gene" and \gene2pathway" components in series that infer a quantitative pathway-level profile for each sample. The seq2gene function assigns phenotype-associated significance of genomic regions to gene-level scores, where the significance could be p-values of SNPs or point mutations, protein-binding affinity, or transcriptional expression level. The seq2gene function has the feasibility to assign non-exon regions to a range of neighboring genes besides the nearest one, thus facilitating the study of functional non-coding elements[2]. Then the gene2pathway summarizes gene-level measurements to pathway-level scores, comparing the quantity of significance for gene members within a pathway with those outside a pathway. -
Transcriptomic Analysis of the Aquaporin (AQP) Gene Family
Pancreatology 19 (2019) 436e442 Contents lists available at ScienceDirect Pancreatology journal homepage: www.elsevier.com/locate/pan Transcriptomic analysis of the Aquaporin (AQP) gene family interactome identifies a molecular panel of four prognostic markers in patients with pancreatic ductal adenocarcinoma Dimitrios E. Magouliotis a, b, Vasiliki S. Tasiopoulou c, Konstantinos Dimas d, * Nikos Sakellaridis d, Konstantina A. Svokos e, Alexis A. Svokos f, Dimitris Zacharoulis b, a Division of Surgery and Interventional Science, Faculty of Medical Sciences, UCL, London, UK b Department of Surgery, University of Thessaly, Biopolis, Larissa, Greece c Faculty of Medicine, School of Health Sciences, University of Thessaly, Biopolis, Larissa, Greece d Department of Pharmacology, Faculty of Medicine, School of Health Sciences, University of Thessaly, Biopolis, Larissa, Greece e The Warren Alpert Medical School of Brown University, Providence, RI, USA f Riverside Regional Medical Center, Newport News, VA, USA article info abstract Article history: Background: This study aimed to assess the differential gene expression of aquaporin (AQP) gene family Received 14 October 2018 interactome in pancreatic ductal adenocarcinoma (PDAC) using data mining techniques to identify novel Received in revised form candidate genes intervening in the pathogenicity of PDAC. 29 January 2019 Method: Transcriptome data mining techniques were used in order to construct the interactome of the Accepted 9 February 2019 AQP gene family and to determine which genes members are differentially expressed in PDAC as Available online 11 February 2019 compared to controls. The same techniques were used in order to evaluate the potential prognostic role of the differentially expressed genes. Keywords: PDAC Results: Transcriptome microarray data of four GEO datasets were incorporated, including 142 primary Aquaporin tumor samples and 104 normal pancreatic tissue samples. -
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. -
Discovery of the First Genome-Wide Significant Risk Loci for ADHD
bioRxiv preprint doi: https://doi.org/10.1101/145581; this version posted June 3, 2017. 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. Discovery of the first genome-wide significant risk loci for ADHD Ditte Demontis,1,2,3† Raymond K. Walters,4,5† Joanna Martin,5,6,7 Manuel Mattheisen,1,2,3,8,9 Thomas D. Als,1,2,3 Esben Agerbo,1,10,11 Rich Belliveau,5 Jonas Bybjerg-Grauholm,1,12 Marie Bækvad-Hansen,1,12 Felecia Cerrato,5 Kimberly Chambert,5 Claire Churchhouse,4,5,13 Ashley Dumont,5 Nicholas Eriksson,14 Michael Gandal,15,16,17,18 Jacqueline Goldstein,4,5,13 Jakob Grove,1,2,3,19 Christine S. Hansen,1,12,20 Mads E. Hauberg,1,2,3 Mads V. Hollegaard,1,12 Daniel P. Howrigan,4,5 Hailiang Huang,4,5 Julian Maller,5,21 Alicia R. Martin,4,5,13 Jennifer Moran,5 Jonatan Pallesen,1,2,3 Duncan S. Palmer,4,5 Carsten B. Pedersen,1,10,11 Marianne G. Pedersen,1,10,11 Timothy Poterba,4,5,13 Jesper B. Poulsen,1,12 Stephan Ripke,4,5,13,22 Elise B. Robinson,4,23 Kyle F. Satterstrom,4,5,13 Christine Stevens,5 Patrick Turley,4,5 Hyejung Won,15,16 ADHD Working Group of the Psychiatric Genomics Consortium (PGC), Early Lifecourse & Genetic Epidemiology (EAGLE) Consortium, 23andMe Research Team, Ole A. -
Supplementary Materials
1 Supplementary Materials: Supplemental Figure 1. Gene expression profiles of kidneys in the Fcgr2b-/- and Fcgr2b-/-. Stinggt/gt mice. (A) A heat map of microarray data show the genes that significantly changed up to 2 fold compared between Fcgr2b-/- and Fcgr2b-/-. Stinggt/gt mice (N=4 mice per group; p<0.05). Data show in log2 (sample/wild-type). 2 Supplemental Figure 2. Sting signaling is essential for immuno-phenotypes of the Fcgr2b-/-lupus mice. (A-C) Flow cytometry analysis of splenocytes isolated from wild-type, Fcgr2b-/- and Fcgr2b-/-. Stinggt/gt mice at the age of 6-7 months (N= 13-14 per group). Data shown in the percentage of (A) CD4+ ICOS+ cells, (B) B220+ I-Ab+ cells and (C) CD138+ cells. Data show as mean ± SEM (*p < 0.05, **p<0.01 and ***p<0.001). 3 Supplemental Figure 3. Phenotypes of Sting activated dendritic cells. (A) Representative of western blot analysis from immunoprecipitation with Sting of Fcgr2b-/- mice (N= 4). The band was shown in STING protein of activated BMDC with DMXAA at 0, 3 and 6 hr. and phosphorylation of STING at Ser357. (B) Mass spectra of phosphorylation of STING at Ser357 of activated BMDC from Fcgr2b-/- mice after stimulated with DMXAA for 3 hour and followed by immunoprecipitation with STING. (C) Sting-activated BMDC were co-cultured with LYN inhibitor PP2 and analyzed by flow cytometry, which showed the mean fluorescence intensity (MFI) of IAb expressing DC (N = 3 mice per group). 4 Supplemental Table 1. Lists of up and down of regulated proteins Accession No. -
1 UST College of Science Department of Biological Sciences
UST College of Science Department of Biological Sciences 1 Pharmacogenomics of Myofascial Pain Syndrome An Undergraduate Thesis Submitted to the Department of Biological Sciences College of Science University of Santo Tomas In Partial Fulfillment of the Requirements for the Degree of Bachelor of Science in Biology Jose Marie V. Lazaga Marc Llandro C. Fernandez May 2021 UST College of Science Department of Biological Sciences 2 PANEL APPROVAL SHEET This undergraduate research manuscript entitled: Pharmacogenomics of Myofascial Pain Syndrome prepared and submitted by Jose Marie V. Lazaga and Marc Llandro C. Fernandez, was checked and has complied with the revisions and suggestions requested by panel members after thorough evaluation. This final version of the manuscript is hereby approved and accepted for submission in partial fulfillment of the requirements for the degree of Bachelor of Science in Biology. Noted by: Asst. Prof. Marilyn G. Rimando, PhD Research adviser, Bio/MicroSem 602-603 Approved by: Bio/MicroSem 603 panel member Bio/MicroSem 603 panel member Date: Date: UST College of Science Department of Biological Sciences 3 DECLARATION OF ORIGINALITY We hereby affirm that this submission is our own work and that, to the best of our knowledge and belief, it contains no material previously published or written by another person nor material to which a substantial extent has been accepted for award of any other degree or diploma of a university or other institute of higher learning, except where due acknowledgement is made in the text. We also declare that the intellectual content of this undergraduate research is the product of our work, even though we may have received assistance from others on style, presentation, and language expression. -
Review Article PTEN Gene: a Model for Genetic Diseases in Dermatology
The Scientific World Journal Volume 2012, Article ID 252457, 8 pages The cientificWorldJOURNAL doi:10.1100/2012/252457 Review Article PTEN Gene: A Model for Genetic Diseases in Dermatology Corrado Romano1 and Carmelo Schepis2 1 Unit of Pediatrics and Medical Genetics, I.R.C.C.S. Associazione Oasi Maria Santissima, 94018 Troina, Italy 2 Unit of Dermatology, I.R.C.C.S. Associazione Oasi Maria Santissima, 94018 Troina, Italy Correspondence should be addressed to Carmelo Schepis, [email protected] Received 19 October 2011; Accepted 4 January 2012 Academic Editors: G. Vecchio and H. Zitzelsberger Copyright © 2012 C. Romano and C. Schepis. 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. PTEN gene is considered one of the most mutated tumor suppressor genes in human cancer, and it’s likely to become the first one in the near future. Since 1997, its involvement in tumor suppression has smoothly increased, up to the current importance. Germline mutations of PTEN cause the PTEN hamartoma tumor syndrome (PHTS), which include the past-called Cowden, Bannayan- Riley-Ruvalcaba, Proteus, Proteus-like, and Lhermitte-Duclos syndromes. Somatic mutations of PTEN have been observed in glioblastoma, prostate cancer, and brest cancer cell lines, quoting only the first tissues where the involvement has been proven. The negative regulation of cell interactions with the extracellular matrix could be the way PTEN phosphatase acts as a tumor suppressor. PTEN gene plays an essential role in human development. A recent model sees PTEN function as a stepwise gradation, which can be impaired not only by heterozygous mutations and homozygous losses, but also by other molecular mechanisms, such as transcriptional regression, epigenetic silencing, regulation by microRNAs, posttranslational modification, and aberrant localization. -
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). -
Análise Integrativa De Perfis Transcricionais De Pacientes Com
UNIVERSIDADE DE SÃO PAULO FACULDADE DE MEDICINA DE RIBEIRÃO PRETO PROGRAMA DE PÓS-GRADUAÇÃO EM GENÉTICA ADRIANE FEIJÓ EVANGELISTA Análise integrativa de perfis transcricionais de pacientes com diabetes mellitus tipo 1, tipo 2 e gestacional, comparando-os com manifestações demográficas, clínicas, laboratoriais, fisiopatológicas e terapêuticas Ribeirão Preto – 2012 ADRIANE FEIJÓ EVANGELISTA Análise integrativa de perfis transcricionais de pacientes com diabetes mellitus tipo 1, tipo 2 e gestacional, comparando-os com manifestações demográficas, clínicas, laboratoriais, fisiopatológicas e terapêuticas Tese apresentada à Faculdade de Medicina de Ribeirão Preto da Universidade de São Paulo para obtenção do título de Doutor em Ciências. Área de Concentração: Genética Orientador: Prof. Dr. Eduardo Antonio Donadi Co-orientador: Prof. Dr. Geraldo A. S. Passos Ribeirão Preto – 2012 AUTORIZO A REPRODUÇÃO E DIVULGAÇÃO TOTAL OU PARCIAL DESTE TRABALHO, POR QUALQUER MEIO CONVENCIONAL OU ELETRÔNICO, PARA FINS DE ESTUDO E PESQUISA, DESDE QUE CITADA A FONTE. FICHA CATALOGRÁFICA Evangelista, Adriane Feijó Análise integrativa de perfis transcricionais de pacientes com diabetes mellitus tipo 1, tipo 2 e gestacional, comparando-os com manifestações demográficas, clínicas, laboratoriais, fisiopatológicas e terapêuticas. Ribeirão Preto, 2012 192p. Tese de Doutorado apresentada à Faculdade de Medicina de Ribeirão Preto da Universidade de São Paulo. Área de Concentração: Genética. Orientador: Donadi, Eduardo Antonio Co-orientador: Passos, Geraldo A. 1. Expressão gênica – microarrays 2. Análise bioinformática por module maps 3. Diabetes mellitus tipo 1 4. Diabetes mellitus tipo 2 5. Diabetes mellitus gestacional FOLHA DE APROVAÇÃO ADRIANE FEIJÓ EVANGELISTA Análise integrativa de perfis transcricionais de pacientes com diabetes mellitus tipo 1, tipo 2 e gestacional, comparando-os com manifestações demográficas, clínicas, laboratoriais, fisiopatológicas e terapêuticas.