An Autoinhibitory Intramolecular Interaction Proof-Reads RNA
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The Splicing Factor U2AF1 Contributes to Cancer Progression Through a Noncanonical Role in Translation Regulation
Downloaded from genesdev.cshlp.org on September 30, 2021 - Published by Cold Spring Harbor Laboratory Press The splicing factor U2AF1 contributes to cancer progression through a noncanonical role in translation regulation Murali Palangat,1 Dimitrios G. Anastasakis,2 Dennis Liang Fei,3 Katherine E. Lindblad,4 Robert Bradley,5 Christopher S. Hourigan,4 Markus Hafner,2 and Daniel R. Larson1 1Laboratory of Receptor Biology and Gene Expression, National Cancer Insitute, National Institutes of Health, Bethesda, Maryland 20892, USA; 2National Institute of Arthritis and Musculoskeletal and Skin Diseases, National Institutes of Health, Bethesda, Maryland 20892, USA; 3Weill Cornell Medicine, New York, New York 10065, USA; 4Laboratory of Myeloid Malignancies, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland 20892, USA; 5Computational Biology Program, Public Health Sciences and Biological Sciences, Fred Hutchinson Cancer Center, Seattle, Washington 98109, USA Somatic mutations in the genes encoding components of the spliceosome occur frequently in human neoplasms, including myeloid dysplasias and leukemias, and less often in solid tumors. One of the affected factors, U2AF1, is involved in splice site selection, and the most common change, S34F, alters a conserved nucleic acid-binding domain, recognition of the 3′ splice site, and alternative splicing of many mRNAs. However, the role that this mutation plays in oncogenesis is still unknown. Here, we uncovered a noncanonical function of U2AF1, showing that it directly binds mature mRNA in the cytoplasm and negatively regulates mRNA translation. This splicing- independent role of U2AF1 is altered by the S34F mutation, and polysome profiling indicates that the mutation affects translation of hundreds of mRNA. -
Murine MPDZ-Linked Hydrocephalus Is Caused by Hyperpermeability of the Choroid Plexus
Thomas Jefferson University Jefferson Digital Commons Cardeza Foundation for Hematologic Research Sidney Kimmel Medical College 1-1-2019 Murine MPDZ-linked hydrocephalus is caused by hyperpermeability of the choroid plexus. Junning Yang Thomas Jefferson University Claire Simonneau Thomas Jefferson University Robert Kilker Thomas Jefferson University Laura Oakley ThomasFollow this Jeff anderson additional University works at: https://jdc.jefferson.edu/cardeza_foundation Part of the Medical Pathology Commons Matthew D. Byrne ThomasLet us Jeff knowerson Univ howersity access to this document benefits ouy Recommended Citation See next page for additional authors Yang, Junning; Simonneau, Claire; Kilker, Robert; Oakley, Laura; Byrne, Matthew D.; Nichtova, Zuzana; Stefanescu, Ioana; Pardeep-Kumar, Fnu; Tripathi, Sushil; Londin, Eric; Saugier-Veber, Pascale; Willard, Belinda; Thakur, Mathew; Pickup, Stephen; Ishikawa, Hiroshi; Schroten, Horst; Smeyne, Richard; and Horowitz, Arie, "Murine MPDZ-linked hydrocephalus is caused by hyperpermeability of the choroid plexus." (2019). Cardeza Foundation for Hematologic Research. Paper 49. https://jdc.jefferson.edu/cardeza_foundation/49 This Article is brought to you for free and open access by the Jefferson Digital Commons. The Jefferson Digital Commons is a service of Thomas Jefferson University's Center for Teaching and Learning (CTL). The Commons is a showcase for Jefferson books and journals, peer-reviewed scholarly publications, unique historical collections from the University archives, and teaching tools. The Jefferson Digital Commons allows researchers and interested readers anywhere in the world to learn about and keep up to date with Jefferson scholarship. This article has been accepted for inclusion in Cardeza Foundation for Hematologic Research by an authorized administrator of the Jefferson Digital Commons. For more information, please contact: [email protected]. -
The Utility of Genetic Risk Scores in Predicting the Onset of Stroke March 2021 6
DOT/FAA/AM-21/24 Office of Aerospace Medicine Washington, DC 20591 The Utility of Genetic Risk Scores in Predicting the Onset of Stroke Diana Judith Monroy Rios, M.D1 and Scott J. Nicholson, Ph.D.2 1. KR 30 # 45-03 University Campus, Building 471, 5th Floor, Office 510 Bogotá D.C. Colombia 2. FAA Civil Aerospace Medical Institute, 6500 S. MacArthur Blvd Rm. 354, Oklahoma City, OK 73125 March 2021 NOTICE This document is disseminated under the sponsorship of the U.S. Department of Transportation in the interest of information exchange. The United States Government assumes no liability for the contents thereof. _________________ This publication and all Office of Aerospace Medicine technical reports are available in full-text from the Civil Aerospace Medical Institute’s publications Web site: (www.faa.gov/go/oamtechreports) Technical Report Documentation Page 1. Report No. 2. Government Accession No. 3. Recipient's Catalog No. DOT/FAA/AM-21/24 4. Title and Subtitle 5. Report Date March 2021 The Utility of Genetic Risk Scores in Predicting the Onset of Stroke 6. Performing Organization Code 7. Author(s) 8. Performing Organization Report No. Diana Judith Monroy Rios M.D1, and Scott J. Nicholson, Ph.D.2 9. Performing Organization Name and Address 10. Work Unit No. (TRAIS) 1 KR 30 # 45-03 University Campus, Building 471, 5th Floor, Office 510, Bogotá D.C. Colombia 11. Contract or Grant No. 2 FAA Civil Aerospace Medical Institute, 6500 S. MacArthur Blvd Rm. 354, Oklahoma City, OK 73125 12. Sponsoring Agency name and Address 13. Type of Report and Period Covered Office of Aerospace Medicine Federal Aviation Administration 800 Independence Ave., S.W. -
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. -
Supplementary Table 1: Adhesion Genes Data Set
Supplementary Table 1: Adhesion genes data set PROBE Entrez Gene ID Celera Gene ID Gene_Symbol Gene_Name 160832 1 hCG201364.3 A1BG alpha-1-B glycoprotein 223658 1 hCG201364.3 A1BG alpha-1-B glycoprotein 212988 102 hCG40040.3 ADAM10 ADAM metallopeptidase domain 10 133411 4185 hCG28232.2 ADAM11 ADAM metallopeptidase domain 11 110695 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 195222 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 165344 8751 hCG20021.3 ADAM15 ADAM metallopeptidase domain 15 (metargidin) 189065 6868 null ADAM17 ADAM metallopeptidase domain 17 (tumor necrosis factor, alpha, converting enzyme) 108119 8728 hCG15398.4 ADAM19 ADAM metallopeptidase domain 19 (meltrin beta) 117763 8748 hCG20675.3 ADAM20 ADAM metallopeptidase domain 20 126448 8747 hCG1785634.2 ADAM21 ADAM metallopeptidase domain 21 208981 8747 hCG1785634.2|hCG2042897 ADAM21 ADAM metallopeptidase domain 21 180903 53616 hCG17212.4 ADAM22 ADAM metallopeptidase domain 22 177272 8745 hCG1811623.1 ADAM23 ADAM metallopeptidase domain 23 102384 10863 hCG1818505.1 ADAM28 ADAM metallopeptidase domain 28 119968 11086 hCG1786734.2 ADAM29 ADAM metallopeptidase domain 29 205542 11085 hCG1997196.1 ADAM30 ADAM metallopeptidase domain 30 148417 80332 hCG39255.4 ADAM33 ADAM metallopeptidase domain 33 140492 8756 hCG1789002.2 ADAM7 ADAM metallopeptidase domain 7 122603 101 hCG1816947.1 ADAM8 ADAM metallopeptidase domain 8 183965 8754 hCG1996391 ADAM9 ADAM metallopeptidase domain 9 (meltrin gamma) 129974 27299 hCG15447.3 ADAMDEC1 ADAM-like, -
High Throughput Computational Mouse Genetic Analysis
bioRxiv preprint doi: https://doi.org/10.1101/2020.09.01.278465; this version posted January 22, 2021. 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. High Throughput Computational Mouse Genetic Analysis Ahmed Arslan1+, Yuan Guan1+, Zhuoqing Fang1, Xinyu Chen1, Robin Donaldson2&, Wan Zhu, Madeline Ford1, Manhong Wu, Ming Zheng1, David L. Dill2* and Gary Peltz1* 1Department of Anesthesia, Stanford University School of Medicine, Stanford, CA; and 2Department of Computer Science, Stanford University, Stanford, CA +These authors contributed equally to this paper & Current Address: Ecree Durham, NC 27701 *Address correspondence to: [email protected] bioRxiv preprint doi: https://doi.org/10.1101/2020.09.01.278465; this version posted January 22, 2021. 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 Background: Genetic factors affecting multiple biomedical traits in mice have been identified when GWAS data that measured responses in panels of inbred mouse strains was analyzed using haplotype-based computational genetic mapping (HBCGM). Although this method was previously used to analyze one dataset at a time; but now, a vast amount of mouse phenotypic data is now publicly available, which could lead to many more genetic discoveries. Results: HBCGM and a whole genome SNP map covering 53 inbred strains was used to analyze 8462 publicly available datasets of biomedical responses (1.52M individual datapoints) measured in panels of inbred mouse strains. As proof of concept, causative genetic factors affecting susceptibility for eye, metabolic and infectious diseases were identified when structured automated methods were used to analyze the output. -
QUANTITATIVE TRAIT LOCUS ANALYSIS: in Several Variants (I.E., Alleles)
TECHNOLOGIES FROM THE FIELD QUANTITATIVE TRAIT LOCUS ANALYSIS: in several variants (i.e., alleles). QTL analysis allows one MULTIPLE CROSS AND HETEROGENEOUS to map, with some precision, the genomic position of STOCK MAPPING these alleles. For many researchers in the alcohol field, the break Robert Hitzemann, Ph.D.; John K. Belknap, Ph.D.; through with respect to the genetic determination of alcohol- and Shannon K. McWeeney, Ph.D. related behaviors occurred when Plomin and colleagues (1991) made the seminal observation that a specific panel of RI mice (i.e., the BXD panel) could be used to identify KEY WORDS: Genetic theory of alcohol and other drug use; genetic the physical location of (i.e., to map) QTLs for behavioral factors; environmental factors; behavioral phenotype; behavioral phenotypes. Because the phenotypes of the different strains trait; quantitative trait gene (QTG); inbred animal strains; in this panel had been determined for many alcohol- recombinant inbred (RI) mouse strains; quantitative traits; related traits, researchers could readily apply the strategy quantitative trait locus (QTL) mapping; multiple cross mapping of RI–QTL mapping (Gora-Maslak et al. 1991). Although (MCM); heterogeneous stock (HS) mapping; microsatellite investigators recognized early on that this panel was not mapping; animal models extensive enough to answer all questions, the emerging data illustrated the rich genetic complexity of alcohol- related phenotypes (Belknap 1992; Plomin and McClearn ntil well into the 1990s, both preclinical and clinical 1993). research focused on finding “the” gene for human The next advance came with the development of diseases, including alcoholism. This focus was rein U microsatellite maps (Dietrich et al. -
Pan-Cancer Analysis Identifies Mutations in SUGP1 That Recapitulate Mutant SF3B1 Splicing Dysregulation
Pan-cancer analysis identifies mutations in SUGP1 that recapitulate mutant SF3B1 splicing dysregulation Zhaoqi Liua,b,c,1, Jian Zhangd,1, Yiwei Suna,c, Tomin E. Perea-Chambleea,b,c, James L. Manleyd,2, and Raul Rabadana,b,c,2 aProgram for Mathematical Genomics, Columbia University, New York, NY 10032; bDepartment of Systems Biology, Columbia University, New York, NY 10032; cDepartment of Biomedical Informatics, Columbia University, New York, NY 10032; and dDepartment of Biological Sciences, Columbia University, New York, NY 10027 Contributed by James L. Manley, March 2, 2020 (sent for review January 2, 2020; reviewed by Kristen Lynch and Gene Yeo) The gene encoding the core spliceosomal protein SF3B1 is the most also resulted in the same splicing defects observed in SF3B1 frequently mutated gene encoding a splicing factor in a variety of mutant cells (11). hematologic malignancies and solid tumors. SF3B1 mutations in- In addition to SF3B1, other SF-encoding genes have also been duce use of cryptic 3′ splice sites (3′ss), and these splicing errors found to be mutated in hematologic malignancies, e.g., U2AF1, contribute to tumorigenesis. However, it is unclear how wide- SRSF2, and ZRSR2. However, these SF gene mutations do not spread this type of cryptic 3′ss usage is in cancers and what is share common alterations in splicing (1, 3), suggesting that dif- the full spectrum of genetic mutations that cause such missplicing. ferent splicing patterns may contribute to different phenotypes To address this issue, we performed an unbiased pan-cancer anal- of cancers. Because SF3B1 is the most frequently mutated ysis to identify genetic alterations that lead to the same aberrant splicing gene, the splicing defects caused by mutant SF3B1 may SF3B1 splicing as observed with mutations. -
Transcriptome Analysis of Human Diabetic Kidney Disease
ORIGINAL ARTICLE Transcriptome Analysis of Human Diabetic Kidney Disease Karolina I. Woroniecka,1 Ae Seo Deok Park,1 Davoud Mohtat,2 David B. Thomas,3 James M. Pullman,4 and Katalin Susztak1,5 OBJECTIVE—Diabetic kidney disease (DKD) is the single cases, mild and then moderate mesangial expansion can be leading cause of kidney failure in the U.S., for which a cure has observed. In general, diabetic kidney disease (DKD) is not yet been found. The aim of our study was to provide an considered a nonimmune-mediated degenerative disease unbiased catalog of gene-expression changes in human diabetic of the glomerulus; however, it has long been noted that kidney biopsy samples. complement and immunoglobulins sometimes can be de- — tected in diseased glomeruli, although their role and sig- RESEARCH DESIGN AND METHODS Affymetrix expression fi arrays were used to identify differentially regulated transcripts in ni cance is not clear (4). 44 microdissected human kidney samples. The DKD samples were The understanding of DKD has been challenged by multi- significant for their racial diversity and decreased glomerular ple issues. First, the diagnosis of DKD usually is made using filtration rate (~20–30 mL/min). Stringent statistical analysis, using clinical criteria, and kidney biopsy often is not performed. the Benjamini-Hochberg corrected two-tailed t test, was used to According to current clinical practice, the development of identify differentially expressed transcripts in control and diseased albuminuria in patients with diabetes is sufficient to make the glomeruli and tubuli. Two different Web-based algorithms were fi diagnosis of DKD (5). We do not understand the correlation used to de ne differentially regulated pathways. -
Nuclear PTEN Safeguards Pre-Mrna Splicing to Link Golgi Apparatus for Its Tumor Suppressive Role
ARTICLE DOI: 10.1038/s41467-018-04760-1 OPEN Nuclear PTEN safeguards pre-mRNA splicing to link Golgi apparatus for its tumor suppressive role Shao-Ming Shen1, Yan Ji2, Cheng Zhang1, Shuang-Shu Dong2, Shuo Yang1, Zhong Xiong1, Meng-Kai Ge1, Yun Yu1, Li Xia1, Meng Guo1, Jin-Ke Cheng3, Jun-Ling Liu1,3, Jian-Xiu Yu1,3 & Guo-Qiang Chen1 Dysregulation of pre-mRNA alternative splicing (AS) is closely associated with cancers. However, the relationships between the AS and classic oncogenes/tumor suppressors are 1234567890():,; largely unknown. Here we show that the deletion of tumor suppressor PTEN alters pre-mRNA splicing in a phosphatase-independent manner, and identify 262 PTEN-regulated AS events in 293T cells by RNA sequencing, which are associated with significant worse outcome of cancer patients. Based on these findings, we report that nuclear PTEN interacts with the splicing machinery, spliceosome, to regulate its assembly and pre-mRNA splicing. We also identify a new exon 2b in GOLGA2 transcript and the exon exclusion contributes to PTEN knockdown-induced tumorigenesis by promoting dramatic Golgi extension and secretion, and PTEN depletion significantly sensitizes cancer cells to secretion inhibitors brefeldin A and golgicide A. Our results suggest that Golgi secretion inhibitors alone or in combination with PI3K/Akt kinase inhibitors may be therapeutically useful for PTEN-deficient cancers. 1 Department of Pathophysiology, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Shanghai Jiao Tong University School of Medicine (SJTU-SM), Shanghai 200025, China. 2 Institute of Health Sciences, Shanghai Institutes for Biological Sciences of Chinese Academy of Sciences and SJTU-SM, Shanghai 200025, China. -
Transcriptomic Analysis of Short-Fruit 1 (Sf1)
www.nature.com/scientificreports OPEN Transcriptomic analysis of short- fruit 1 (sf1) reveals new insights into the variation of fruit-related Received: 15 November 2016 Accepted: 20 April 2017 traits in Cucumis sativus Published: xx xx xxxx Lina Wang, Chenxing Cao, Shuangshuang Zheng, Haiyang Zhang, Panjing Liu, Qian Ge, Jinrui Li & Zhonghai Ren Fruit size is an important quality trait in different market classes ofCucumis sativus L., an economically important vegetable cultivated worldwide, but the genetic and molecular mechanisms that control fruit size are largely unknown. In this study, we isolated a natural cucumber mutant, short fruit 1 (sf1), caused by a single recessive Mendelian factor, from the North China-type inbred line CNS2. In addition to significantly decreased fruit length, other fruit-related phenotypic variations were also observed in sf1 compared to the wild-type (WT) phenotype, indicating that sf1 might have pleiotropic effects. Microscopic imaging showed that fruit cell size in sf1 was much larger than that in WT, suggesting that the short fruit phenotype in sf1 is caused by decreased cell number. Fine mapping revealed that sf1 was localized to a 174.3 kb region on chromosome 6. Similarly, SNP association analysis of bulked segregant RNA-Seq data showed increased SNP frequency in the same region of chromosome 6. In addition, transcriptomic analysis revealed that sf1 might control fruit length through the fine-tuning of cytokinin and auxin signalling, gibberellin biosynthesis and signal transduction in cucumber fruits. Overall, our results provide important information for further study of fruit length and other fruit-related features in cucumber. Cucumber (Cucumis sativus L., 2n = 14), a member of the family Cucurbitaceae, is one of the most economically important vegetable crops cultivated throughout the world. -
Producing Cells of the Testis, Ovary and Adrenal Gland F
RESEARCH ARTICLE 4561 Development 139, 4561-4570 (2012) doi:10.1242/dev.087247 © 2012. Published by The Company of Biologists Ltd In vivo evidence for the crucial role of SF1 in steroid- producing cells of the testis, ovary and adrenal gland F. William Buaas1,*, Jennifer R. Gardiner1, Sally Clayton1, Pierre Val2 and Amanda Swain1,‡ SUMMARY Adrenal and gonadal steroids are essential for life and reproduction. The orphan nuclear receptor SF1 (NR5A1) has been shown to regulate the expression of enzymes involved in steroid production in vitro. However, the in vivo role of this transcription factor in steroidogenesis has not been elucidated. In this study, we have generated steroidogenic-specific Cre-expressing mice to lineage mark and delete Sf1 in differentiated steroid-producing cells of the testis, the ovary and the adrenal gland. Our data show that SF1 is a regulator of the expression of steroidogenic genes in all three organs. In addition, Sf1 deletion leads to a radical change in cell morphology and loss of identity. Surprisingly, sexual development and reproduction in mutant animals were not compromised owing, in part, to the presence of a small proportion of SF1-positive cells. In contrast to the testis and ovary, the mutant adult adrenal gland showed a lack of Sf1-deleted cells and our studies suggest that steroidogenic adrenal cells during foetal stages require Sf1 to give rise to the adult adrenal population. This study is the first to show the in vivo requirements of SF1 in steroidogenesis and provides novel data on the cellular consequences of the loss of this protein specifically within steroid-producing cells.