Identification of Pain Genes Contributing to Ciguatoxin-Induced Pain Using Haplotype-Based Computational Genetic Mapping in Mice
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Screening and Identification of Key Biomarkers in Clear Cell Renal Cell Carcinoma Based on Bioinformatics Analysis
bioRxiv preprint doi: https://doi.org/10.1101/2020.12.21.423889; this version posted December 23, 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 The copyright holder for this preprint (which was not certified by peer review) is the author/funder.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. Screening and identification of key biomarkers in clear cell renal cell carcinoma based on bioinformatics analysis Basavaraj Vastrad1, Chanabasayya Vastrad*2 , Iranna Kotturshetti 1. Department of Biochemistry, Basaveshwar College of Pharmacy, Gadag, Karnataka 582103, India. 2. Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karanataka, India. 3. Department of Ayurveda, Rajiv Gandhi Education Society`s Ayurvedic Medical College, Ron, Karnataka 562209, India. * Chanabasayya Vastrad [email protected] Ph: +919480073398 Chanabasava Nilaya, Bharthinagar, Dharwad 580001 , Karanataka, India bioRxiv preprint doi: https://doi.org/10.1101/2020.12.21.423889; this version posted December 23, 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 The copyright holder for this preprint (which was not certified by peer review) is the author/funder.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. Abstract Clear cell renal cell carcinoma (ccRCC) is one of the most common types of malignancy of the urinary system. The pathogenesis and effective diagnosis of ccRCC have become popular topics for research in the previous decade. In the current study, an integrated bioinformatics analysis was performed to identify core genes associated in ccRCC. An expression dataset (GSE105261) was downloaded from the Gene Expression Omnibus database, and included 26 ccRCC and 9 normal kideny samples. Assessment of the microarray dataset led to the recognition of differentially expressed genes (DEGs), which was subsequently used for pathway and gene ontology (GO) enrichment analysis. -
Bayesian Hierarchical Modeling of High-Throughput Genomic Data with Applications to Cancer Bioinformatics and Stem Cell Differentiation
BAYESIAN HIERARCHICAL MODELING OF HIGH-THROUGHPUT GENOMIC DATA WITH APPLICATIONS TO CANCER BIOINFORMATICS AND STEM CELL DIFFERENTIATION by Keegan D. Korthauer A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Statistics) at the UNIVERSITY OF WISCONSIN–MADISON 2015 Date of final oral examination: 05/04/15 The dissertation is approved by the following members of the Final Oral Committee: Christina Kendziorski, Professor, Biostatistics and Medical Informatics Michael A. Newton, Professor, Statistics Sunduz Kele¸s,Professor, Biostatistics and Medical Informatics Sijian Wang, Associate Professor, Biostatistics and Medical Informatics Michael N. Gould, Professor, Oncology © Copyright by Keegan D. Korthauer 2015 All Rights Reserved i in memory of my grandparents Ma and Pa FL Grandma and John ii ACKNOWLEDGMENTS First and foremost, I am deeply grateful to my thesis advisor Christina Kendziorski for her invaluable advice, enthusiastic support, and unending patience throughout my time at UW-Madison. She has provided sound wisdom on everything from methodological principles to the intricacies of academic research. I especially appreciate that she has always encouraged me to eke out my own path and I attribute a great deal of credit to her for the successes I have achieved thus far. I also owe special thanks to my committee member Professor Michael Newton, who guided me through one of my first collaborative research experiences and has continued to provide key advice on my thesis research. I am also indebted to the other members of my thesis committee, Professor Sunduz Kele¸s,Professor Sijian Wang, and Professor Michael Gould, whose valuable comments, questions, and suggestions have greatly improved this dissertation. -
NEDD4L Regulates the Proliferation and Metastasis of Non-Small-Cell Lung Cancer by Mediating CPNE1 Ubiquitination
NEDD4L Regulates the Proliferation and Metastasis of Non-small-cell Lung Cancer by Mediating CPNE1 Ubiquitination Ruochen Zhang Institute of Resporatory Diseases, soochow University Yuanyuan Zeng Institute of Respiratory Diseases, Soochow University. Weijie Zhang Soochow University Yue Li Soochow University Jieqi Zhou Soochow University Yang Zhang Soochow University Anqi Wang Soochow University Yantian Lv Soochow University Jianjie Zhu First Aliated Hospital of Soochow University Zeyi Liu ( [email protected] ) First Aliated Hospital of Soochow University https://orcid.org/0000-0003-2528-6909 Jian-an Huang First Aliated Hospital of Soochow University Research Keywords: NSCLC, CPNE1, NEDD4L, ubiquitination, degradation Posted Date: February 26th, 2021 DOI: https://doi.org/10.21203/rs.3.rs-250598/v1 License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Page 1/18 Abstract High expression of CPNE1 is positively correlated with the occurrence, TNM stage, lymph node metastasis, and distant metastasis of non-small-cell lung cancer (NSCLC), suggesting that CPNE1 may be an effective target for the treatment of NSCLC. No direct role of post-translational modication of CPNE1 in NSCLC has been reported. This study conrms that CPNE1 is degraded by two pathways: the ubiquitin-proteasome pathway and the autophagy- lysosome pathway. CPNE1 binds with the ubiquitin molecule via its K157 residue. Moreover, we determine that the ubiquitin ligase NEDD4L can mediate the ubiquitination of CPNE1 and promote its degradation. In addition, we nd that NEDD4L knockout promotes the proliferation and metastasis of NSCLC cells by regulating CPNE1. This study aims to further investigate the mechanism of CPNE1 ubiquitination in the occurrence and development of NSCLC and provide a new potential target for NSCLC treatment. -
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. -
NEDD4 2 (NEDD4L) (NM 001144964) Human Tagged ORF Clone Product Data
OriGene Technologies, Inc. 9620 Medical Center Drive, Ste 200 Rockville, MD 20850, US Phone: +1-888-267-4436 [email protected] EU: [email protected] CN: [email protected] Product datasheet for RC227866 NEDD4 2 (NEDD4L) (NM_001144964) Human Tagged ORF Clone Product data: Product Type: Expression Plasmids Product Name: NEDD4 2 (NEDD4L) (NM_001144964) Human Tagged ORF Clone Tag: Myc-DDK Symbol: NEDD4L Synonyms: hNEDD4-2; NEDD4-2; NEDD4.2; PVNH7; RSP5 Vector: pCMV6-Entry (PS100001) E. coli Selection: Kanamycin (25 ug/mL) Cell Selection: Neomycin This product is to be used for laboratory only. Not for diagnostic or therapeutic use. View online » ©2021 OriGene Technologies, Inc., 9620 Medical Center Drive, Ste 200, Rockville, MD 20850, US 1 / 6 NEDD4 2 (NEDD4L) (NM_001144964) Human Tagged ORF Clone – RC227866 ORF Nucleotide >RC227866 representing NM_001144964 Sequence: Red=Cloning site Blue=ORF Green=Tags(s) TTTTGTAATACGACTCACTATAGGGCGGCCGGGAATTCGTCGACTGGATCCGGTACCGAGGAGATCTGCC GCCGCGATCGCC ATGGAGCGACCCTATACATTTAAGGACTTTCTCCTCAGACCAAGAAGTCATAAGTCTCGAGTTAAGGGAT TTTTGCGATTGAAAATGGCCTATATGCCAAAAAATGGAGGTCAAGATGAAGAAAACAGTGACCAGAGGGA TGACATGGAGCATGGATGGGAAGTTGTTGACTCAAATGACTCGGCTTCTCAGCACCAAGAGGAACTTCCT CCTCCTCCTCTGCCTCCCGGGTGGGAAGAAAAAGTGGACAATTTAGGCCGAACTTACTATGTCAACCACA ACAACCGGACCACTCAGTGGCACAGACCAAGCCTGATGGACGTGTCCTCGGAGTCGGACAATAACATCAG ACAGATCAACCAGGAGGCAGCACACCGGCGCTTCCGCTCCCGCAGGCACATCAGCGAAGACTTGGAGCCC GAGCCCTCGGAGGGCGGGGATGTCCCCGAGCCTTGGGAGACCATTTCAGAGGAAGTGAATATCGCTGGAG ACTCTCTCGGTCTGGCTCTGCCCCCACCACCGGCCTCCCCAGGATCTCGGACCAGCCCTCAGGAGCTGTC -
1 Supporting Information for a Microrna Network Regulates
Supporting Information for A microRNA Network Regulates Expression and Biosynthesis of CFTR and CFTR-ΔF508 Shyam Ramachandrana,b, Philip H. Karpc, Peng Jiangc, Lynda S. Ostedgaardc, Amy E. Walza, John T. Fishere, Shaf Keshavjeeh, Kim A. Lennoxi, Ashley M. Jacobii, Scott D. Rosei, Mark A. Behlkei, Michael J. Welshb,c,d,g, Yi Xingb,c,f, Paul B. McCray Jr.a,b,c Author Affiliations: Department of Pediatricsa, Interdisciplinary Program in Geneticsb, Departments of Internal Medicinec, Molecular Physiology and Biophysicsd, Anatomy and Cell Biologye, Biomedical Engineeringf, Howard Hughes Medical Instituteg, Carver College of Medicine, University of Iowa, Iowa City, IA-52242 Division of Thoracic Surgeryh, Toronto General Hospital, University Health Network, University of Toronto, Toronto, Canada-M5G 2C4 Integrated DNA Technologiesi, Coralville, IA-52241 To whom correspondence should be addressed: Email: [email protected] (M.J.W.); yi- [email protected] (Y.X.); Email: [email protected] (P.B.M.) This PDF file includes: Materials and Methods References Fig. S1. miR-138 regulates SIN3A in a dose-dependent and site-specific manner. Fig. S2. miR-138 regulates endogenous SIN3A protein expression. Fig. S3. miR-138 regulates endogenous CFTR protein expression in Calu-3 cells. Fig. S4. miR-138 regulates endogenous CFTR protein expression in primary human airway epithelia. Fig. S5. miR-138 regulates CFTR expression in HeLa cells. Fig. S6. miR-138 regulates CFTR expression in HEK293T cells. Fig. S7. HeLa cells exhibit CFTR channel activity. Fig. S8. miR-138 improves CFTR processing. Fig. S9. miR-138 improves CFTR-ΔF508 processing. Fig. S10. SIN3A inhibition yields partial rescue of Cl- transport in CF epithelia. -
Inherited Renal Tubulopathies—Challenges and Controversies
G C A T T A C G G C A T genes Review Inherited Renal Tubulopathies—Challenges and Controversies Daniela Iancu 1,* and Emma Ashton 2 1 UCL-Centre for Nephrology, Royal Free Campus, University College London, Rowland Hill Street, London NW3 2PF, UK 2 Rare & Inherited Disease Laboratory, London North Genomic Laboratory Hub, Great Ormond Street Hospital for Children National Health Service Foundation Trust, Levels 4-6 Barclay House 37, Queen Square, London WC1N 3BH, UK; [email protected] * Correspondence: [email protected]; Tel.: +44-2381204172; Fax: +44-020-74726476 Received: 11 February 2020; Accepted: 29 February 2020; Published: 5 March 2020 Abstract: Electrolyte homeostasis is maintained by the kidney through a complex transport function mostly performed by specialized proteins distributed along the renal tubules. Pathogenic variants in the genes encoding these proteins impair this function and have consequences on the whole organism. Establishing a genetic diagnosis in patients with renal tubular dysfunction is a challenging task given the genetic and phenotypic heterogeneity, functional characteristics of the genes involved and the number of yet unknown causes. Part of these difficulties can be overcome by gathering large patient cohorts and applying high-throughput sequencing techniques combined with experimental work to prove functional impact. This approach has led to the identification of a number of genes but also generated controversies about proper interpretation of variants. In this article, we will highlight these challenges and controversies. Keywords: inherited tubulopathies; next generation sequencing; genetic heterogeneity; variant classification. 1. Introduction Mutations in genes that encode transporter proteins in the renal tubule alter kidney capacity to maintain homeostasis and cause diseases recognized under the generic name of inherited tubulopathies. -
Noelia Díaz Blanco
Effects of environmental factors on the gonadal transcriptome of European sea bass (Dicentrarchus labrax), juvenile growth and sex ratios Noelia Díaz Blanco Ph.D. thesis 2014 Submitted in partial fulfillment of the requirements for the Ph.D. degree from the Universitat Pompeu Fabra (UPF). This work has been carried out at the Group of Biology of Reproduction (GBR), at the Department of Renewable Marine Resources of the Institute of Marine Sciences (ICM-CSIC). Thesis supervisor: Dr. Francesc Piferrer Professor d’Investigació Institut de Ciències del Mar (ICM-CSIC) i ii A mis padres A Xavi iii iv Acknowledgements This thesis has been made possible by the support of many people who in one way or another, many times unknowingly, gave me the strength to overcome this "long and winding road". First of all, I would like to thank my supervisor, Dr. Francesc Piferrer, for his patience, guidance and wise advice throughout all this Ph.D. experience. But above all, for the trust he placed on me almost seven years ago when he offered me the opportunity to be part of his team. Thanks also for teaching me how to question always everything, for sharing with me your enthusiasm for science and for giving me the opportunity of learning from you by participating in many projects, collaborations and scientific meetings. I am also thankful to my colleagues (former and present Group of Biology of Reproduction members) for your support and encouragement throughout this journey. To the “exGBRs”, thanks for helping me with my first steps into this world. Working as an undergrad with you Dr. -
Targeting PH Domain Proteins for Cancer Therapy
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 12-2018 Targeting PH domain proteins for cancer therapy Zhi Tan Follow this and additional works at: https://digitalcommons.library.tmc.edu/utgsbs_dissertations Part of the Bioinformatics Commons, Medicinal Chemistry and Pharmaceutics Commons, Neoplasms Commons, and the Pharmacology Commons Recommended Citation Tan, Zhi, "Targeting PH domain proteins for cancer therapy" (2018). The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences Dissertations and Theses (Open Access). 910. https://digitalcommons.library.tmc.edu/utgsbs_dissertations/910 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]. TARGETING PH DOMAIN PROTEINS FOR CANCER THERAPY by Zhi Tan Approval page APPROVED: _____________________________________________ Advisory Professor, Shuxing Zhang, Ph.D. _____________________________________________ -
Knowledge Management Enviroments for High Throughput Biology
Knowledge Management Enviroments for High Throughput Biology Abhey Shah A Thesis submitted for the degree of MPhil Biology Department University of York September 2007 Abstract With the growing complexity and scale of data sets in computational biology and chemoin- formatics, there is a need for novel knowledge processing tools and platforms. This thesis describes a newly developed knowledge processing platform that is different in its emphasis on architecture, flexibility, builtin facilities for datamining and easy cross platform usage. There exist thousands of bioinformatics and chemoinformatics databases, that are stored in many different forms with different access methods, this is a reflection of the range of data structures that make up complex biological and chemical data. Starting from a theoretical ba- sis, FCA (Formal Concept Analysis) an applied branch of lattice theory, is used in this thesis to develop a file system that automatically structures itself by it’s contents. The procedure of extracting concepts from data sets is examined. The system also finds appropriate labels for the discovered concepts by extracting data from ontological databases. A novel method for scaling non-binary data for use with the system is developed. Finally the future of integrative systems biology is discussed in the context of efficiently closed causal systems. Contents 1 Motivations and goals of the thesis 11 1.1 Conceptual frameworks . 11 1.2 Biological foundations . 12 1.2.1 Gene expression data . 13 1.2.2 Ontology . 14 1.3 Knowledge based computational environments . 15 1.3.1 Interfaces . 16 1.3.2 Databases and the character of biological data . -
Identification of Candidate Parkinson Disease Genes by Integrating Genome-Wide Association Study, Expression, and Epigenetic Data Sets
Research JAMA Neurology | Original Investigation Identification of Candidate Parkinson Disease Genes by Integrating Genome-Wide Association Study, Expression, and Epigenetic Data Sets Demis A. Kia, MBBS; David Zhang, MSc; Sebastian Guelfi, PhD; Claudia Manzoni, PhD; Leon Hubbard, PhD; Regina H. Reynolds, MSc; Juan Botía, PhD; Mina Ryten, MD; Raffaele Ferrari, PhD; Patrick A. Lewis, PhD; Nigel Williams, PhD; Daniah Trabzuni, PhD; John Hardy, PhD; Nicholas W. Wood, PhD; for the United Kingdom Brain Expression Consortium (UKBEC) and the International Parkinson’s Disease Genomics Consortium (IPDGC) Supplemental content IMPORTANCE Substantial genome-wide association study (GWAS) work in Parkinson disease (PD) has led to the discovery of an increasing number of loci shown reliably to be associated with increased risk of disease. Improved understanding of the underlying genes and mechanisms at these loci will be key to understanding the pathogenesis of PD. OBJECTIVE To investigate what genes and genomic processes underlie the risk of sporadic PD. DESIGN AND SETTING This genetic association study used the bioinformatic tools Coloc and transcriptome-wide association study (TWAS) to integrate PD case-control GWAS data published in 2017 with expression data (from Braineac, the Genotype-Tissue Expression [GTEx], and CommonMind) and methylation data (derived from UK Parkinson brain samples) to uncover putative gene expression and splicing mechanisms associated with PD GWAS signals. Candidate genes were further characterized using cell-type specificity, weighted gene coexpression networks, and weighted protein-protein interaction networks. MAIN OUTCOMES AND MEASURES It was hypothesized a priori that some genes underlying PD loci would alter PD risk through changes to expression, splicing, or methylation. -
4 Understanding the Role of GNA13 Deregulation in Lymphomagenesis
Integrative Genomics Reveals a Role for GNA13 in Lymphomagenesis by Adrienne Greenough University Program in Genetics and Genomics Duke University Approved: ___________________________ Sandeep Dave, Supervisor ___________________________ Fred Dietrich ___________________________ Jack Keene ___________________________ Yuan Zhuang Dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the University Program in Genetics and Genomics in the Graduate School of Duke University 2014 i v ABSTRACT Integrative Genomics Reveals a Role for GNA13 in Lymphomagenesis by Adrienne Greenough University Program in Genetics and Genomics Duke University Approved: ___________________________ Sandeep Dave, Supervisor ___________________________ Fred Dietrich ___________________________ Jack Keene ___________________________ Yuan Zhuang An abstract of a dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the University Program in Genetics and Genomics in the Graduate School of Duke University 2014 Copyright by Adrienne Greenough 2014 Abstract Lymphomas comprise a diverse group of malignancies derived from immune cells. High throughput sequencing has recently emerged as a powerful and versatile method for analysis of the cancer genome and transcriptome. As these data continue to emerge, the crucial work lies in sorting through the wealth of information to hone in on the critical aspects that will give us a better understanding of biology and new insight for how to treat disease. Finding the important signals within these large data sets is one of the major challenges of next generation sequencing. In this dissertation, I have developed several complementary strategies to describe the genetic underpinnings of lymphomas. I begin with developing a better method for RNA sequencing that enables strand-specific total RNA sequencing and alternative splicing profiling in the same analysis.