Transcriptome Analysis of Rumen Epithelium and Meta-Transcriptome
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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. -
Stelios Pavlidis3, Matthew Loza3, Fred Baribaud3, Anthony
Supplementary Data Th2 and non-Th2 molecular phenotypes of asthma using sputum transcriptomics in UBIOPRED Chih-Hsi Scott Kuo1.2, Stelios Pavlidis3, Matthew Loza3, Fred Baribaud3, Anthony Rowe3, Iaonnis Pandis2, Ana Sousa4, Julie Corfield5, Ratko Djukanovic6, Rene 7 7 8 2 1† Lutter , Peter J. Sterk , Charles Auffray , Yike Guo , Ian M. Adcock & Kian Fan 1†* # Chung on behalf of the U-BIOPRED consortium project team 1Airways Disease, National Heart & Lung Institute, Imperial College London, & Biomedical Research Unit, Biomedical Research Unit, Royal Brompton & Harefield NHS Trust, London, United Kingdom; 2Department of Computing & Data Science Institute, Imperial College London, United Kingdom; 3Janssen Research and Development, High Wycombe, Buckinghamshire, United Kingdom; 4Respiratory Therapeutic Unit, GSK, Stockley Park, United Kingdom; 5AstraZeneca R&D Molndal, Sweden and Areteva R&D, Nottingham, United Kingdom; 6Faculty of Medicine, Southampton University, Southampton, United Kingdom; 7Faculty of Medicine, University of Amsterdam, Amsterdam, Netherlands; 8European Institute for Systems Biology and Medicine, CNRS-ENS-UCBL, Université de Lyon, France. †Contributed equally #Consortium project team members are listed under Supplementary 1 Materials *To whom correspondence should be addressed: [email protected] 2 List of the U-BIOPRED Consortium project team members Uruj Hoda & Christos Rossios, Airways Disease, National Heart & Lung Institute, Imperial College London, UK & Biomedical Research Unit, Biomedical Research Unit, Royal -
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. -
Senescence Induced by RECQL4 Dysfunction Contributes to Rothmund–Thomson Syndrome Features in Mice
Citation: Cell Death and Disease (2014) 5, e1226; doi:10.1038/cddis.2014.168 OPEN & 2014 Macmillan Publishers Limited All rights reserved 2041-4889/14 www.nature.com/cddis Senescence induced by RECQL4 dysfunction contributes to Rothmund–Thomson syndrome features in mice HLu1, EF Fang1, P Sykora1, T Kulikowicz1, Y Zhang2, KG Becker2, DL Croteau1 and VA Bohr*,1 Cellular senescence refers to irreversible growth arrest of primary eukaryotic cells, a process thought to contribute to aging- related degeneration and disease. Deficiency of RecQ helicase RECQL4 leads to Rothmund–Thomson syndrome (RTS), and we have investigated whether senescence is involved using cellular approaches and a mouse model. We first systematically investigated whether depletion of RECQL4 and the other four human RecQ helicases, BLM, WRN, RECQL1 and RECQL5, impacts the proliferative potential of human primary fibroblasts. BLM-, WRN- and RECQL4-depleted cells display increased staining of senescence-associated b-galactosidase (SA-b-gal), higher expression of p16INK4a or/and p21WAF1 and accumulated persistent DNA damage foci. These features were less frequent in RECQL1- and RECQL5-depleted cells. We have mapped the region in RECQL4 that prevents cellular senescence to its N-terminal region and helicase domain. We further investigated senescence features in an RTS mouse model, Recql4-deficient mice (Recql4HD). Tail fibroblasts from Recql4HD showed increased SA-b-gal staining and increased DNA damage foci. We also identified sparser tail hair and fewer blood cells in Recql4HD mice accompanied with increased senescence in tail hair follicles and in bone marrow cells. In conclusion, dysfunction of RECQL4 increases DNA damage and triggers premature senescence in both human and mouse cells, which may contribute to symptoms in RTS patients. -
DNA Polymerase : a Unique Multifunctional End-Joining Machine
G C A T T A C G G C A T genes Review DNA Polymerase θ: A Unique Multifunctional End-Joining Machine Samuel J. Black, Ekaterina Kashkina, Tatiana Kent and Richard T. Pomerantz * Fels Institute for Cancer Research, Department of Medical Genetics and Molecular Biochemistry, Temple University Lewis Katz School of Medicine, Philadelphia, PA 19140, USA; [email protected] (S.J.B); [email protected] (E.K.); [email protected] (T.K.) * Correspondence: [email protected]; Tel.: +1-215-707-8991 Academic Editor: Paolo Cinelli Received: 11 August 2016; Accepted: 8 September 2016; Published: 21 September 2016 Abstract: The gene encoding DNA polymerase θ (Polθ) was discovered over ten years ago as having a role in suppressing genome instability in mammalian cells. Studies have now clearly documented an essential function for this unique A-family polymerase in the double-strand break (DSB) repair pathway alternative end-joining (alt-EJ), also known as microhomology-mediated end-joining (MMEJ), in metazoans. Biochemical and cellular studies show that Polθ exhibits a unique ability to perform alt-EJ and during this process the polymerase generates insertion mutations due to its robust terminal transferase activity which involves template-dependent and independent modes of DNA synthesis. Intriguingly, the POLQ gene also encodes for a conserved superfamily 2 Hel308-type ATP-dependent helicase domain which likely assists in alt-EJ and was reported to suppress homologous recombination (HR) via its anti-recombinase activity. Here, we review our current knowledge of Polθ-mediated end-joining, the specific activities of the polymerase and helicase domains, and put into perspective how this multifunctional enzyme promotes alt-EJ repair of DSBs formed during S and G2 cell cycle phases. -
Appendix 2. Significantly Differentially Regulated Genes in Term Compared with Second Trimester Amniotic Fluid Supernatant
Appendix 2. Significantly Differentially Regulated Genes in Term Compared With Second Trimester Amniotic Fluid Supernatant Fold Change in term vs second trimester Amniotic Affymetrix Duplicate Fluid Probe ID probes Symbol Entrez Gene Name 1019.9 217059_at D MUC7 mucin 7, secreted 424.5 211735_x_at D SFTPC surfactant protein C 416.2 206835_at STATH statherin 363.4 214387_x_at D SFTPC surfactant protein C 295.5 205982_x_at D SFTPC surfactant protein C 288.7 1553454_at RPTN repetin solute carrier family 34 (sodium 251.3 204124_at SLC34A2 phosphate), member 2 238.9 206786_at HTN3 histatin 3 161.5 220191_at GKN1 gastrokine 1 152.7 223678_s_at D SFTPA2 surfactant protein A2 130.9 207430_s_at D MSMB microseminoprotein, beta- 99.0 214199_at SFTPD surfactant protein D major histocompatibility complex, class II, 96.5 210982_s_at D HLA-DRA DR alpha 96.5 221133_s_at D CLDN18 claudin 18 94.4 238222_at GKN2 gastrokine 2 93.7 1557961_s_at D LOC100127983 uncharacterized LOC100127983 93.1 229584_at LRRK2 leucine-rich repeat kinase 2 HOXD cluster antisense RNA 1 (non- 88.6 242042_s_at D HOXD-AS1 protein coding) 86.0 205569_at LAMP3 lysosomal-associated membrane protein 3 85.4 232698_at BPIFB2 BPI fold containing family B, member 2 84.4 205979_at SCGB2A1 secretoglobin, family 2A, member 1 84.3 230469_at RTKN2 rhotekin 2 82.2 204130_at HSD11B2 hydroxysteroid (11-beta) dehydrogenase 2 81.9 222242_s_at KLK5 kallikrein-related peptidase 5 77.0 237281_at AKAP14 A kinase (PRKA) anchor protein 14 76.7 1553602_at MUCL1 mucin-like 1 76.3 216359_at D MUC7 mucin 7, -
Gene Section Review
Atlas of Genetics and Cytogenetics in Oncology and Haematology OPEN ACCESS JOURNAL INIST-CNRS Gene Section Review EEF1G (Eukaryotic translation elongation factor 1 gamma) Luigi Cristiano Aesthetic and medical biotechnologies research unit, Prestige, Terranuova Bracciolini, Italy; [email protected] Published in Atlas Database: March 2019 Online updated version : http://AtlasGeneticsOncology.org/Genes/EEF1GID54272ch11q12.html Printable original version : http://documents.irevues.inist.fr/bitstream/handle/2042/70656/03-2019-EEF1GID54272ch11q12.pdf DOI: 10.4267/2042/70656 This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 2.0 France Licence. © 2020 Atlas of Genetics and Cytogenetics in Oncology and Haematology Abstract Keywords EEF1G; Eukaryotic translation elongation factor 1 Eukaryotic translation elongation factor 1 gamma, gamma; Translation; Translation elongation factor; alias eEF1G, is a protein that plays a main function protein synthesis; cancer; oncogene; cancer marker in the elongation step of translation process but also covers numerous moonlighting roles. Considering its Identity importance in the cell it is found frequently Other names: EF1G, GIG35, PRO1608, EEF1γ, overexpressed in human cancer cells and thus this EEF1Bγ review wants to collect the state of the art about EEF1G, with insights on DNA, RNA, protein HGNC (Hugo): EEF1G encoded and the diseases where it is implicated. Location: 11q12.3 Figure. 1. Splice variants of EEF1G. The figure shows the locus on chromosome 11 of the EEF1G gene and its splicing variants (grey/blue box). The primary transcript is EEF1G-001 mRNA (green/red box), but also EEF1G-201 variant is able to codify for a protein (reworked from https://www.ncbi.nlm.nih.gov/gene/1937; http://grch37.ensembl.org; www.genecards.org) Atlas Genet Cytogenet Oncol Haematol. -
1 Novel Expression Signatures Identified by Transcriptional Analysis
ARD Online First, published on October 7, 2009 as 10.1136/ard.2009.108043 Ann Rheum Dis: first published as 10.1136/ard.2009.108043 on 7 October 2009. Downloaded from Novel expression signatures identified by transcriptional analysis of separated leukocyte subsets in SLE and vasculitis 1Paul A Lyons, 1Eoin F McKinney, 1Tim F Rayner, 1Alexander Hatton, 1Hayley B Woffendin, 1Maria Koukoulaki, 2Thomas C Freeman, 1David RW Jayne, 1Afzal N Chaudhry, and 1Kenneth GC Smith. 1Cambridge Institute for Medical Research and Department of Medicine, Addenbrooke’s Hospital, Hills Road, Cambridge, CB2 0XY, UK 2Roslin Institute, University of Edinburgh, Roslin, Midlothian, EH25 9PS, UK Correspondence should be addressed to Dr Paul Lyons or Prof Kenneth Smith, Department of Medicine, Cambridge Institute for Medical Research, Addenbrooke’s Hospital, Hills Road, Cambridge, CB2 0XY, UK. Telephone: +44 1223 762642, Fax: +44 1223 762640, E-mail: [email protected] or [email protected] Key words: Gene expression, autoimmune disease, SLE, vasculitis Word count: 2,906 The Corresponding Author has the right to grant on behalf of all authors and does grant on behalf of all authors, an exclusive licence (or non-exclusive for government employees) on a worldwide basis to the BMJ Publishing Group Ltd and its Licensees to permit this article (if accepted) to be published in Annals of the Rheumatic Diseases and any other BMJPGL products to exploit all subsidiary rights, as set out in their licence (http://ard.bmj.com/ifora/licence.pdf). http://ard.bmj.com/ on September 29, 2021 by guest. Protected copyright. 1 Copyright Article author (or their employer) 2009. -
Molecular Targeting and Enhancing Anticancer Efficacy of Oncolytic HSV-1 to Midkine Expressing Tumors
University of Cincinnati Date: 12/20/2010 I, Arturo R Maldonado , hereby submit this original work as part of the requirements for the degree of Doctor of Philosophy in Developmental Biology. It is entitled: Molecular Targeting and Enhancing Anticancer Efficacy of Oncolytic HSV-1 to Midkine Expressing Tumors Student's name: Arturo R Maldonado This work and its defense approved by: Committee chair: Jeffrey Whitsett Committee member: Timothy Crombleholme, MD Committee member: Dan Wiginton, PhD Committee member: Rhonda Cardin, PhD Committee member: Tim Cripe 1297 Last Printed:1/11/2011 Document Of Defense Form Molecular Targeting and Enhancing Anticancer Efficacy of Oncolytic HSV-1 to Midkine Expressing Tumors A dissertation submitted to the Graduate School of the University of Cincinnati College of Medicine in partial fulfillment of the requirements for the degree of DOCTORATE OF PHILOSOPHY (PH.D.) in the Division of Molecular & Developmental Biology 2010 By Arturo Rafael Maldonado B.A., University of Miami, Coral Gables, Florida June 1993 M.D., New Jersey Medical School, Newark, New Jersey June 1999 Committee Chair: Jeffrey A. Whitsett, M.D. Advisor: Timothy M. Crombleholme, M.D. Timothy P. Cripe, M.D. Ph.D. Dan Wiginton, Ph.D. Rhonda D. Cardin, Ph.D. ABSTRACT Since 1999, cancer has surpassed heart disease as the number one cause of death in the US for people under the age of 85. Malignant Peripheral Nerve Sheath Tumor (MPNST), a common malignancy in patients with Neurofibromatosis, and colorectal cancer are midkine- producing tumors with high mortality rates. In vitro and preclinical xenograft models of MPNST were utilized in this dissertation to study the role of midkine (MDK), a tumor-specific gene over- expressed in these tumors and to test the efficacy of a MDK-transcriptionally targeted oncolytic HSV-1 (oHSV). -
Statistical and Bioinformatic Analysis of Hemimethylation Patterns in Non-Small Cell Lung Cancer Shuying Sun1* , Austin Zane2, Carolyn Fulton3 and Jasmine Philipoom4
Sun et al. BMC Cancer (2021) 21:268 https://doi.org/10.1186/s12885-021-07990-7 RESEARCH ARTICLE Open Access Statistical and bioinformatic analysis of hemimethylation patterns in non-small cell lung cancer Shuying Sun1* , Austin Zane2, Carolyn Fulton3 and Jasmine Philipoom4 Abstract Background: DNA methylation is an epigenetic event involving the addition of a methyl-group to a cytosine- guanine base pair (i.e., CpG site). It is associated with different cancers. Our research focuses on studying non-small cell lung cancer hemimethylation, which refers to methylation occurring on only one of the two DNA strands. Many studies often assume that methylation occurs on both DNA strands at a CpG site. However, recent publications show the existence of hemimethylation and its significant impact. Therefore, it is important to identify cancer hemimethylation patterns. Methods: In this paper, we use the Wilcoxon signed rank test to identify hemimethylated CpG sites based on publicly available non-small cell lung cancer methylation sequencing data. We then identify two types of hemimethylated CpG clusters, regular and polarity clusters, and genes with large numbers of hemimethylated sites. Highly hemimethylated genes are then studied for their biological interactions using available bioinformatics tools. Results: In this paper, we have conducted the first-ever investigation of hemimethylation in lung cancer. Our results show that hemimethylation does exist in lung cells either as singletons or clusters. Most clusters contain only two or three CpG sites. Polarity clusters are much shorter than regular clusters and appear less frequently. The majority of clusters found in tumor samples have no overlap with clusters found in normal samples, and vice versa. -
Differential Mechanisms of Tolerance to Extreme Environmental
www.nature.com/scientificreports OPEN Diferential mechanisms of tolerance to extreme environmental conditions in tardigrades Dido Carrero*, José G. Pérez-Silva , Víctor Quesada & Carlos López-Otín * Tardigrades, also known as water bears, are small aquatic animals that inhabit marine, fresh water or limno-terrestrial environments. While all tardigrades require surrounding water to grow and reproduce, species living in limno-terrestrial environments (e.g. Ramazzottius varieornatus) are able to undergo almost complete dehydration by entering an arrested state known as anhydrobiosis, which allows them to tolerate ionic radiation, extreme temperatures and intense pressure. Previous studies based on comparison of the genomes of R. varieornatus and Hypsibius dujardini - a less tolerant tardigrade - have pointed to potential mechanisms that may partially contribute to their remarkable ability to resist extreme physical conditions. In this work, we have further annotated the genomes of both tardigrades using a guided approach in search for novel mechanisms underlying the extremotolerance of R. varieornatus. We have found specifc amplifcations of several genes, including MRE11 and XPC, and numerous missense variants exclusive of R. varieornatus in CHEK1, POLK, UNG and TERT, all of them involved in important pathways for DNA repair and telomere maintenance. Taken collectively, these results point to genomic features that may contribute to the enhanced ability to resist extreme environmental conditions shown by R. varieornatus. Tardigrades are small -
Sea Anemone Genome Reveals the Gene Repertoire and Genomic Organization of the Eumetazoan Ancestor
Lawrence Berkeley National Laboratory Lawrence Berkeley National Laboratory Title Sea anemone genome reveals the gene repertoire and genomic organization of the eumetazoan ancestor Permalink https://escholarship.org/uc/item/3b01p9bc Authors Putnam, Nicholas H. Srivastava, Mansi Hellsten, Uffe et al. Publication Date 2007 Peer reviewed eScholarship.org Powered by the California Digital Library University of California Sea anemone genome reveals the gene repertoire and genomic organization of the eumetazoan ancestor Nicholas H. Putnam[1], Mansi Srivastava[2], Uffe Hellsten[1], Bill Dirks[2], Jarrod Chapman[1], Asaf Salamov[1], Astrid Terry[1], Harris Shapiro[1], Erika Lindquist[1], Vladimir V. Kapitonov[3], Jerzy Jurka[3], Grigory Genikhovich[4], Igor Grigoriev[1], JGI Sequencing Team[1], Robert E. Steele[5], John Finnerty[6], Ulrich Technau[4], Mark Q. Martindale[7], Daniel S. Rokhsar[1,2] [1] Department of Energy Joint Genome Institute, Walnut Creek, CA 94598 [2] Center for Integrative Genomics and Department of Molecular and Cell Biology, University of California, Berkeley CA 94720 [3] Genetic Information Research Institute, 1925 Landings Drive, Mountain View, CA 94043 [4] Sars International Centre for Marine Molecular Biology, University of Bergen, Thormoeøhlensgt 55; 5008, Bergen, Norway [5] Department of Biological Chemistry and the Developmental Biology Center, University of California, Irvine, CA 92697 [6] Department of Biology, Boston University, Boston, MA 02215 [7] Kewalo Marine Laboratory, University of Hawaii, Honolulu, HI 96813 Abstract Sea anemones are seemingly primitive animals that, along with corals, jellyfish, and hydras, constitute the Cnidaria, the oldest eumetazoan phylum. Here we report a comparative analysis of the draft genome of an emerging cnidarian model, the starlet anemone Nematostella vectensis.