DNA Methylation Epi-Signature Is Associated with Two Molecularly
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Mechanical Forces Induce an Asthma Gene Signature in Healthy Airway Epithelial Cells Ayşe Kılıç1,10, Asher Ameli1,2,10, Jin-Ah Park3,10, Alvin T
www.nature.com/scientificreports OPEN Mechanical forces induce an asthma gene signature in healthy airway epithelial cells Ayşe Kılıç1,10, Asher Ameli1,2,10, Jin-Ah Park3,10, Alvin T. Kho4, Kelan Tantisira1, Marc Santolini 1,5, Feixiong Cheng6,7,8, Jennifer A. Mitchel3, Maureen McGill3, Michael J. O’Sullivan3, Margherita De Marzio1,3, Amitabh Sharma1, Scott H. Randell9, Jefrey M. Drazen3, Jefrey J. Fredberg3 & Scott T. Weiss1,3* Bronchospasm compresses the bronchial epithelium, and this compressive stress has been implicated in asthma pathogenesis. However, the molecular mechanisms by which this compressive stress alters pathways relevant to disease are not well understood. Using air-liquid interface cultures of primary human bronchial epithelial cells derived from non-asthmatic donors and asthmatic donors, we applied a compressive stress and then used a network approach to map resulting changes in the molecular interactome. In cells from non-asthmatic donors, compression by itself was sufcient to induce infammatory, late repair, and fbrotic pathways. Remarkably, this molecular profle of non-asthmatic cells after compression recapitulated the profle of asthmatic cells before compression. Together, these results show that even in the absence of any infammatory stimulus, mechanical compression alone is sufcient to induce an asthma-like molecular signature. Bronchial epithelial cells (BECs) form a physical barrier that protects pulmonary airways from inhaled irritants and invading pathogens1,2. Moreover, environmental stimuli such as allergens, pollutants and viruses can induce constriction of the airways3 and thereby expose the bronchial epithelium to compressive mechanical stress. In BECs, this compressive stress induces structural, biophysical, as well as molecular changes4,5, that interact with nearby mesenchyme6 to cause epithelial layer unjamming1, shedding of soluble factors, production of matrix proteins, and activation matrix modifying enzymes, which then act to coordinate infammatory and remodeling processes4,7–10. -
Functional Genomics Analysis of Phelan-Mcdermid Syndrome 22Q13 Region During Human Neurodevelopment
Delft University of Technology Functional genomics analysis of Phelan-McDermid syndrome 22q13 region during human neurodevelopment Ziats, Catherine A.; Grosvenor, Luke P.; Sarasua, Sara M.; Thurm, Audrey E.; Swedo, Susan E.; Mahfouz, Ahmed; Rennert, Owen M.; Ziats, Mark N. DOI 10.1371/journal.pone.0213921 Publication date 2019 Document Version Final published version Published in PLoS ONE Citation (APA) Ziats, C. A., Grosvenor, L. P., Sarasua, S. M., Thurm, A. E., Swedo, S. E., Mahfouz, A., Rennert, O. M., & Ziats, M. N. (2019). Functional genomics analysis of Phelan-McDermid syndrome 22q13 region during human neurodevelopment. PLoS ONE, 14(3), 1-13. [e0213921]. https://doi.org/10.1371/journal.pone.0213921 Important note To cite this publication, please use the final published version (if applicable). Please check the document version above. Copyright Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons. Takedown policy Please contact us and provide details if you believe this document breaches copyrights. We will remove access to the work immediately and investigate your claim. This work is downloaded from Delft University of Technology. For technical reasons the number of authors shown on this cover page is limited to a maximum of 10. RESEARCH ARTICLE Functional genomics analysis of Phelan- McDermid syndrome 22q13 region during human neurodevelopment 1☯ 2,3☯ 4 2 Catherine A. ZiatsID *, Luke P. Grosvenor , Sara M. Sarasua , Audrey E. -
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. -
Functional Parsing of Driver Mutations in the Colorectal Cancer Genome Reveals Numerous Suppressors of Anchorage-Independent
Supplementary information Functional parsing of driver mutations in the colorectal cancer genome reveals numerous suppressors of anchorage-independent growth Ugur Eskiocak1, Sang Bum Kim1, Peter Ly1, Andres I. Roig1, Sebastian Biglione1, Kakajan Komurov2, Crystal Cornelius1, Woodring E. Wright1, Michael A. White1, and Jerry W. Shay1. 1Department of Cell Biology, University of Texas Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas, TX 75390-9039. 2Department of Systems Biology, University of Texas M.D. Anderson Cancer Center, Houston, TX 77054. Supplementary Figure S1. K-rasV12 expressing cells are resistant to p53 induced apoptosis. Whole-cell extracts from immortalized K-rasV12 or p53 down regulated HCECs were immunoblotted with p53 and its down-stream effectors after 10 Gy gamma-radiation. ! Supplementary Figure S2. Quantitative validation of selected shRNAs for their ability to enhance soft-agar growth of immortalized shTP53 expressing HCECs. Each bar represents 8 data points (quadruplicates from two separate experiments). Arrows denote shRNAs that failed to enhance anchorage-independent growth in a statistically significant manner. Enhancement for all other shRNAs were significant (two tailed Studentʼs t-test, compared to none, mean ± s.e.m., P<0.05)." ! Supplementary Figure S3. Ability of shRNAs to knockdown expression was demonstrated by A, immunoblotting for K-ras or B-E, Quantitative RT-PCR for ERICH1, PTPRU, SLC22A15 and SLC44A4 48 hours after transfection into 293FT cells. Two out of 23 tested shRNAs did not provide any knockdown. " ! Supplementary Figure S4. shRNAs against A, PTEN and B, NF1 do not enhance soft agar growth in HCECs without oncogenic manipulations (Student!s t-test, compared to none, mean ± s.e.m., ns= non-significant). -
The Capacity of Long-Term in Vitro Proliferation of Acute Myeloid
The Capacity of Long-Term in Vitro Proliferation of Acute Myeloid Leukemia Cells Supported Only by Exogenous Cytokines Is Associated with a Patient Subset with Adverse Outcome Annette K. Brenner, Elise Aasebø, Maria Hernandez-Valladares, Frode Selheim, Frode Berven, Ida-Sofie Grønningsæter, Sushma Bartaula-Brevik and Øystein Bruserud Supplementary Material S2 of S31 Table S1. Detailed information about the 68 AML patients included in the study. # of blasts Viability Proliferation Cytokine Viable cells Change in ID Gender Age Etiology FAB Cytogenetics Mutations CD34 Colonies (109/L) (%) 48 h (cpm) secretion (106) 5 weeks phenotype 1 M 42 de novo 241 M2 normal Flt3 pos 31.0 3848 low 0.24 7 yes 2 M 82 MF 12.4 M2 t(9;22) wt pos 81.6 74,686 low 1.43 969 yes 3 F 49 CML/relapse 149 M2 complex n.d. pos 26.2 3472 low 0.08 n.d. no 4 M 33 de novo 62.0 M2 normal wt pos 67.5 6206 low 0.08 6.5 no 5 M 71 relapse 91.0 M4 normal NPM1 pos 63.5 21,331 low 0.17 n.d. yes 6 M 83 de novo 109 M1 n.d. wt pos 19.1 8764 low 1.65 693 no 7 F 77 MDS 26.4 M1 normal wt pos 89.4 53,799 high 3.43 2746 no 8 M 46 de novo 26.9 M1 normal NPM1 n.d. n.d. 3472 low 1.56 n.d. no 9 M 68 MF 50.8 M4 normal D835 pos 69.4 1640 low 0.08 n.d. -
Plenary and Platform Abstracts
American Society of Human Genetics 68th Annual Meeting PLENARY AND PLATFORM ABSTRACTS Abstract #'s Tuesday, October 16, 5:30-6:50 pm: 4. Featured Plenary Abstract Session I Hall C #1-#4 Wednesday, October 17, 9:00-10:00 am, Concurrent Platform Session A: 6. Variant Insights from Large Population Datasets Ballroom 20A #5-#8 7. GWAS in Combined Cancer Phenotypes Ballroom 20BC #9-#12 8. Genome-wide Epigenomics and Non-coding Variants Ballroom 20D #13-#16 9. Clonal Mosaicism in Cancer, Alzheimer's Disease, and Healthy Room 6A #17-#20 Tissue 10. Genetics of Behavioral Traits and Diseases Room 6B #21-#24 11. New Frontiers in Computational Genomics Room 6C #25-#28 12. Bone and Muscle: Identifying Causal Genes Room 6D #29-#32 13. Precision Medicine Initiatives: Outcomes and Lessons Learned Room 6E #33-#36 14. Environmental Exposures in Human Traits Room 6F #37-#40 Wednesday, October 17, 4:15-5:45 pm, Concurrent Platform Session B: 24. Variant Interpretation Practices and Resources Ballroom 20A #41-#46 25. Integrated Variant Analysis in Cancer Genomics Ballroom 20BC #47-#52 26. Gene Discovery and Functional Models of Neurological Disorders Ballroom 20D #53-#58 27. Whole Exome and Whole Genome Associations Room 6A #59-#64 28. Sequencing-based Diagnostics for Newborns and Infants Room 6B #65-#70 29. Omics Studies in Alzheimer's Disease Room 6C #71-#76 30. Cardiac, Valvular, and Vascular Disorders Room 6D #77-#82 31. Natural Selection and Human Phenotypes Room 6E #83-#88 32. Genetics of Cardiometabolic Traits Room 6F #89-#94 Wednesday, October 17, 6:00-7:00 pm, Concurrent Platform Session C: 33. -
Mapping of Quantitative Trait Loci for Milk Yield Traits on Bovine Chromosome 5 in the Fleckvieh Cattle
From the Department of Veterinary Sciences Faculty of Veterinary Medicine Ludwig-Maximilians-Universität München Arbeit angefertigt unter der Leitung von Univ. Prof. Dr. Dr. habil. Martin Förster Mapping of Quantitative Trait Loci for Milk Yield Traits on Bovine Chromosome 5 in the Fleckvieh Cattle Inaugural–Dissertation For the attainment of Doctor Degree in Veterinary Medicine From the Faculty of Veterinary Medicine of the Ludwig-Maximilians-Universität München by Ashraf Fathy Said Awad from Sharkia- Egypt München 2011 Gedruckt mit Genehmigung der Tierärztlichen Fakultät der Ludwig–Maximilians–Universität München Dekan: Univ. Prof. Dr. Braun Berichterstatter: Univ. Prof. Dr. Dr. habil Förster Korreferent: Univ. Prof. Dr. Mansfeld Tag der Promotion: 12. February 2011 This work is dedicated to My Parents, my wife and my lovely daughters; Sama, Shaza, Hana CONTENTS CONTENTS ABBREVIATION……………………………………………………………… IV CHAPTER 1: GENERAL INTRODUCTION……………………………….. 1 CHAPTER 2: REVIEW OF LITERATURE………………………………… 3 2.1. DNA Markers……………………………………………………….. 3 2.1.1. Microsatellites………………………………………………………….. 3 2.1.2. Single Nucleotide Polymorphism (SNPs)…………………………… 4 2.2. Mapping of Quantitative Trait Loci (QTL)…………………….. 5 2.2.1. QTL Mapping Designs………………………………………………... 6 2.2.1.1. Daughter Design………………………………………………... 6 2.2.1.2. Granddaughter Design………………………………………… 7 2.2.1.3. Complex Pedigree Design…………………………………….. 9 2.2.2. QTL Mapping Strategies……………………………………………… 10 2.2.2.1. Candidate Gene Approach……………………………………. 10 2.2.2.2. Genome Scan Approach……………………………………… 11 2.3. Principles of Linkage Mapping…………………………………. 12 2.4. QTL Fine Mapping………………………………………………… 14 2.4.1. Linkage Disequilibrium……………………………………………… 15 2.4.2. Combined Linkage Disequilibrium and Linkage (LDL) Mapping… 17 2.5. Identification of Candidate Genes……………………………… 18 2.6. -
Genome-Wide Copy Number Variant Analysis For
An et al. BMC Medical Genomics (2016) 9:2 DOI 10.1186/s12920-015-0163-4 RESEARCH ARTICLE Open Access Genome-wide copy number variant analysis for congenital ventricular septal defects in Chinese Han population Yu An1,2,4, Wenyuan Duan3, Guoying Huang4, Xiaoli Chen5,LiLi5, Chenxia Nie6, Jia Hou4, Yonghao Gui4, Yiming Wu1, Feng Zhang2, Yiping Shen7, Bailin Wu1,4,7* and Hongyan Wang8* Abstract Background: Ventricular septal defects (VSDs) constitute the most prevalent congenital heart disease (CHD), occurs either in isolation (isolated VSD) or in combination with other cardiac defects (complex VSD). Copy number variation (CNV) has been highlighted as a possible contributing factor to the etiology of many congenital diseases. However, little is known concerning the involvement of CNVs in either isolated or complex VSDs. Methods: We analyzed 154 unrelated Chinese individuals with VSD by chromosomal microarray analysis. The subjects were recruited from four hospitals across China. Each case underwent clinical assessment to define the type of VSD, either isolated or complex VSD. CNVs detected were categorized into syndrom related CNVs, recurrent CNVs and rare CNVs. Genes encompassed by the CNVs were analyzed using enrichment and pathway analysis. Results: Among 154 probands, we identified 29 rare CNVs in 26 VSD patients (16.9 %, 26/154) and 8 syndrome-related CNVs in 8 VSD patients (5.2 %, 8/154). 12 of the detected 29 rare CNVs (41.3 %) were recurrently reported in DECIPHER or ISCA database as associated with either VSD or general heart disease. Fifteen genes (5 %, 15/285) within CNVs were associated with a broad spectrum of complicated CHD. -
ALG12 Gene Pair Kentaro Oh-Hashi1*, Hisashi Koga2, Shun Ikeda2, Kiyo Shimada2, Yoko Hirata1, Kazutoshi Kiuchi1
Oh-hashi et al. BMC Genomics 2010, 11:664 http://www.biomedcentral.com/1471-2164/11/664 RESEARCH ARTICLE Open Access Role of an ER stress response element in regulating the bidirectional promoter of the mouse CRELD2 - ALG12 gene pair Kentaro Oh-hashi1*, Hisashi Koga2, Shun Ikeda2, Kiyo Shimada2, Yoko Hirata1, Kazutoshi Kiuchi1 Abstract Background: Recently, we identified cysteine-rich with EGF-like domains 2 (CRELD2) as a novel endoplasmic reticulum (ER) stress-inducible gene and characterized its transcriptional regulation by ATF6 under ER stress conditions. Interestingly, the CRELD2 and asparagine-linked glycosylation 12 homolog (ALG12) genes are arranged as a bidirectional (head-to-head) gene pair and are separated by less than 400 bp. In this study, we characterized the transcriptional regulation of the mouse CRELD2 and ALG12 genes that is mediated by a common bidirectional promoter. Results: This short intergenic region contains an ER stress response element (ERSE) sequence and is well conserved among the human, rat and mouse genomes. Microarray analysis revealed that CRELD2 and ALG12 mRNAs were induced in Neuro2a cells by treatment with thapsigargin (Tg), an ER stress inducer, in a time- dependent manner. Other ER stress inducers, tunicamycin and brefeldin A, also increased the expression of these two mRNAs in Neuro2a cells. We then tested for the possible involvement of the ERSE motif and other regulatory sites of the intergenic region in the transcriptional regulation of the mouse CRELD2 and ALG12 genes by using variants of the bidirectional reporter construct. With regards to the promoter activities of the CRELD2-ALG12 gene pair, the entire intergenic region hardly responded to Tg, whereas the CRELD2 promoter constructs of the proximal region containing the ERSE motif showed a marked responsiveness to Tg. -
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. -
RNA Editing at Baseline and Following Endoplasmic Reticulum Stress
RNA Editing at Baseline and Following Endoplasmic Reticulum Stress By Allison Leigh Richards A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Human Genetics) in The University of Michigan 2015 Doctoral Committee: Professor Vivian G. Cheung, Chair Assistant Professor Santhi K. Ganesh Professor David Ginsburg Professor Daniel J. Klionsky Dedication To my father, mother, and Matt without whom I would never have made it ii Acknowledgements Thank you first and foremost to my dissertation mentor, Dr. Vivian Cheung. I have learned so much from you over the past several years including presentation skills such as never sighing and never saying “as you can see…” You have taught me how to think outside the box and how to create and explain my story to others. I would not be where I am today without your help and guidance. Thank you to the members of my dissertation committee (Drs. Santhi Ganesh, David Ginsburg and Daniel Klionsky) for all of your advice and support. I would also like to thank the entire Human Genetics Program, and especially JoAnn Sekiguchi and Karen Grahl, for welcoming me to the University of Michigan and making my transition so much easier. Thank you to Michael Boehnke and the Genome Science Training Program for supporting my work. A very special thank you to all of the members of the Cheung lab, past and present. Thank you to Xiaorong Wang for all of your help from the bench to advice on my career. Thank you to Zhengwei Zhu who has helped me immensely throughout my thesis even through my panic. -
TITLE PAGE Oxidative Stress and Response to Thymidylate Synthase
Downloaded from molpharm.aspetjournals.org at ASPET Journals on October 2, 2021 -Targeted -Targeted 1 , University of of , University SC K.W.B., South Columbia, (U.O., Carolina, This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted. The final version may differ from this version. This article has not been copyedited and formatted.