DOCSLIB.ORG

RNA and RNA-RBP Relationships Shown by Microarray Data Guang-Bin Wang, Ni-Ni Rao, Chang-Long Dong, and Xiao-Qin Lyu

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
RNA and RNA-RBP Relationships Shown by Microarray Data Guang-Bin Wang, Ni-Ni Rao, Chang-Long Dong, and Xiao-Qin Lyu Identification of the Potential Function of circRNA in Hypertrophic Cardiomyopathy Based on Mutual RNA- RNA and RNA-RBP Relationships Shown by Microarray Data Guang-Bin Wang, Ni-Ni Rao, Chang-Long Dong, and Xiao-Qin Lyu Citation: Wang Guang-Bin, Rao Ni-Ni, Dong Chang-Long, Lyu Xiao-Qin. Identification of the Potential Function of circRNA in Hypertrophic Cardiomyopathy Based on Mutual RNA-RNA and RNA-RBP Relationships Shown by Microarray Data[J]. Journal of Electronic Science and Technology, 2021, 19(1): 41-52. doi: 10.1016/j.jnlest.2021.100097 View online: https://doi.org/10.1016/j.jnlest.2021.100097 Articles you may be interested in Pei-Xin Liu, Zhao-Sheng Zhu, Xiao-Feng Ye, Xiao-Feng Li. Conditional Random Field Tracking Model Based on a Visual Long Short Term Memory Network[J]. Journal of Electronic Science and Technology, 2020, 18(4): 308-319. doi: 10.1016/j.jnlest.2020.100031 Juan Zhou, Ying Shen, Ya-Juan Xue, Li Li. Analysis of RF Feedback Chain Isolation in Wireless Co-Time Co- Frequency Full Duplex[J]. Journal of Electronic Science and Technology, 2018, 16(3): 282-288. doi: 10.11989/JEST.1674-862X.71204011 You-Han Tung, Wen-Shenq Juang. Secure and Efficient Mutual Authentication Scheme for NFC Mobile Devices[J]. Journal of Electronic Science and Technology, 2017, 15(3): 240-245. doi: 10.11989/JEST.1674-862X.60804031 Kohei Kataoka, Nobuki Tezuka, Masashi Matsuura, Satoshi Sugimoto. Fabrication of Co2Fe(Al,Si) and Co2Fe(Al,Si)/MgO on Ge(111) Substrate and Its Magnetic Properties[J]. Journal of Electronic Science and Technology, 2019, 17(2): 109-115. doi: 10.11989/JEST.1674-862X.71128011 Nyamsuren Vaanchig, Wei Chen, Zhi-Guang Qin. Attribute-Based Access Control with Efficient and Secure Attribute Revocation for Cloud Data Sharing Service[J]. Journal of Electronic Science and Technology, 2017, 15(1): 90-98. doi: 10.11989/JEST.1674-862X.5121616 Jing-Huan Yu, Zi-Meng Zhou. Components and Development in Big Data System: A Survey[J]. Journal of Electronic Science and Technology, 2019, 17(1): 51-72. doi: 10.11989/JEST.1674-862X.80926105 Follow JEST WeChat public account for more information JOURNAL OF ELECTRONIC SCIENCE AND TECHNOLOGY, VOL. 19, NO. 1, MARCH 2021 41 Digital Object Identifier: 10.1016/j.jnlest.2021.100097 Article Number: 100097 Identification of the Potential Function of circRNA in Hypertrophic Cardiomyopathy Based on Mutual RNA-RNA and RNA-RBP Relationships Shown by Microarray Data Guang-Bin Wang | Ni-Ni Rao* | Chang-Long Dong | Xiao-Qin Lyu Abstract—The pathogenesis of hypertrophic cardiomyopathy (HCM) is very complicated, particularly regarding the role of circular RNA (circRNA). This research pays special attention to the relationships of the circRNA-mediated network, including RNA-RNA relationships and RNA-RNA binding protein (RNA-RBP) relationships. We use the parameter framework technology proposed in this paper to screen differentially expressed circRNA, messenger RNA (mRNA), and microRNA (miRNA) from the expression profile of samples related to HCM. And 31 pairs of circRNA and mRNA relationship pairs were extracted, combined with the miRNA targeting database; 145 miRNA-mRNA relationship pairs were extracted; 268 circRNA-mRNA-miRNA triads were established through the common mRNA in the 2 types of relationship pairs. Thus, 268 circRNA-miRNA regulatory relationships were deduced and 30 circRNA- RBP relationship pairs were analyzed at the protein level. On this basis, a circRNA-mediated regulatory network corresponding to the two levels of RNA-RNA and RNA-RBP was established. And then the roles of circRNA in HCM were analyzed through circRNA-mRNA, circRNA-miRNA, and circRNA-RBP, and the possible role in disease development mas inferred. Index Terms—circular RNA (circRNA), circular RNA-messanger RNA-microRNA (circRNA-mRNA-miRNA), co- expression network, functions analysis, hypertrophic cardiomyopathy, regulatory network, RNA-binding protein (RNA- RBP). 1. Introduction Hypertrophic cardiomyopathy (HCM) is a common genetic cardiovascular disease caused by excessive hypertrophy of the myocardium and characterized by thickening of the left ventricular wall[1]. *Corresponding author Manuscript received 2020-09-22; revised 2020-11-02. This work was supported by the National Natural Science Foundation of China under Grant No. 61872405; the Key R&D program of Sichuan Province under Grant No. 2020YFS0243; the Key Project of Natural Science Foundation of Guangdong Province under Grant No. 2016A030311040. G.-B. Wang is with the School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054; also with the Computer Department, Chengdu College of University of Electronic Science and Technology of China, Chengdu 610097 (e-mail: [email protected]). N.-N. Rao, C.-L. Dong, and X.-Q. Lyu are with the School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054 (e-mail: [email protected]). Color versions of one or more of the figures in this paper are available online at http://www.journal.uestc.edu.cn. Publishing editor: Xin Huang 42 JOURNAL OF ELECTRONIC SCIENCE AND TECHNOLOGY, VOL. 19, NO. 1, MARCH 2021 The mutation of the junctophilin-2 (JPH2) gene is the cause of HCM and the main genetic cause of left ventricular hypertrophy and myofilament disorders, and the PH2 protein is a member of the junctophilin family and is mainly expressed in the heart[2]. At the transcriptome level, HCM is closely related to the expression levels of mRNA, microRNA (miRNA), and circRNA. A recent study showed that HCM is usually associated with missense mutations in the MYH6 and MYH7 genes. Silencing specific MYH6 alleles in mice can reduce the incidence of HCM[3]. Jin and Chen found that abnormal miR-145-5p expression affects circRNA in oxygen glucose deprivation-induced (OGD-induced) cell damage by upregulating miRNA-145-5p and the mitogen- activated extracellular signal-regulated kinase (MEK)/extracellular signal-regulated kinases (ERK) pathway to activate the mammalian target of rapamycin (mTOR) and silence circRNA_0010729, thereby protecting against HCM damage[4]. The CYTOR gene may activate the protein kinase B (PKB) and NF-kB signaling pathways through miR-155 to inhibit cardiac hypertrophy, most possibly through serving as ceRNA for miR- 155 to counteract the miR-155-mediated repression of the inhibitor of nuclear factor kappa-B kinase subunit epsilon (IKBKE)[5]. The circRNAs DNAJC6, TMEM56, and MBOAT2 can be used together to distinguish between healthy patients and who with HCM. In addition, circTMEM56 and circDNAJC6 can be used as indicators of disease severity in hypertrophic obstructive cardiomyopathy patients[6]. Thus, the circRNAs regulate gene expression at the transcriptional and post-transcriptional levels and participate in various biological processes, leading to the occurrence of HCM[7],[8]. At the protein level, the p.I603M mutation is mapped to the C4 domain of the cardiac myosin-binding protein (cMyBPC). It was found that the stability of C4 I603M was severely impaired in HCM, so p.I603M was used as a basis for reclassification of variants[9]. Serum N-terminal pro-B-type natriuretic peptide (NT-proBNP) and cardiac troponin I (cTnI) concentrations have been used to indicate the presence of a variety of heart diseases, including HCM, in various species[10]. circRNA is a non-coding RNA molecule that does not have a 5'end cap or a 3'end poly (A) tail and forms a ring structure with covalent bonds. Because circRNA is usually produced by special variable shearing, more than 80% of circRNAs contain protein exons, and has a large number of identical sequences with homologous mRNA, which acts as a sponge for adsorbing miRNA. circRNA participates in the pathological process of various diseases through spongy miRNA, but the role of circRNA in HCM is still unclear. The currently used circRNA annotation tool, circRNADb (http://reprod.njmu.edu.cn/cgi-bin/circrnadb/ resources.php)[11] is a comprehensive database of circRNA molecules in humans. It is difficult to prove the role of circRNA in disease development based on circRNA-mRNA-miRNA. Therefore, the RNA-RNA and RNA-binding protein (RNA-RBP) relationships noted in this article were used to speculate on the possible role of circRNA in HCM. The results were confirmed by Gene Ontology (GO)[12] and Kyoto Encyclopedia of Genes and Genomes (KEGG)[13] enrichment analysis and by using an experimentally verified database, which is more helpful for functional annotation of circRNA, especially in HCM research. Therefore, the method used in the present paper also has potential value for studying the role of circRNA in other complex diseases. 2. Materials The Gene Expression Omnibus (GEO, http://www.ncbi.nlm.nih.gov/geo/) is an international public repository for high-throughput microarray datasets, we used the keywords “circRNA” and “HCM” to search for relevant information. Datasets related to HCM were obtained, including the human circRNA expression profile (ID: GSE148602), which included case (n = 15 HCM samples) and control (n = 7 normal samples) data, and the miRNA expression profile (ID: GSE36946), which contained case (n = 107 HCM samples) and control (n = 20 normal samples) data. Datasets related to HCM can be downloaded from GitHub (https://github.com/ wgb2098/HCM). WANG et al.: Identification of the Potential Function of circRNA in Hypertrophic Cardiomyopathy Based on··· 43 3. Overview of Methods As shown in Fig. 1, the method used in this study consists of three steps: The 1st step, the construction of circRNA-mediated co-expression and regulatory relationship pairs; the 2nd step, the construction of the circRNA-mediated co-expression and regulatory network based on the 1st step and the deduction of circRNA- related relationship pairs; the 3rd step, functional analysis. In Fig. 1, PCC is the Pearson correlation coefficient and SCC is the Spearman coefficient. In this section, we will describe the three steps in detail.
Load more

Recommended publications
  • RSU1) in Cancer Cell Metastasis: a Tale of a Tumor Suppressor
    International Journal of Molecular Sciences Review Ras Suppressor-1 (RSU1) in Cancer Cell Metastasis: A Tale of a Tumor Suppressor Maria Louca 1, Triantafyllos Stylianopoulos 1 and Vasiliki Gkretsi 2,* 1 Cancer Biophysics Laboratory, Department of Mechanical and Manufacturing Engineering, University of Cyprus, 1678 Nicosia, Cyprus; [email protected] (M.L.); [email protected] (T.S.) 2 Biomedical Sciences Program, Department of Life Sciences, School of Sciences, European University Cyprus, 1516 Nicosia, Cyprus * Correspondence: [email protected]; Tel.: +357-22-559-630 Received: 18 May 2020; Accepted: 5 June 2020; Published: 7 June 2020 Abstract: Cancer is a multifactorial disease responsible for millions of deaths worldwide. It has a strong genetic background, as mutations in oncogenes or tumor suppressor genes contribute to the initiation of cancer development. Integrin signaling as well as the signaling pathway of Ras oncogene, have been long implicated both in carcinogenesis and disease progression. Moreover, they have been involved in the promotion of metastasis, which accounts for the majority of cancer-related deaths. Ras Suppressor-1 (RSU1) was identified as a suppressor of Ras-induced transformation and was shown to localize to cell-extracellular matrix adhesions. Recent findings indicate that its expression is elevated in various cancer types, while its role in regulating metastasis-related cellular processes remains largely unknown. Interestingly, there is no in vivo work in the field to date, and thus, all relevant knowledge stems from in vitro studies. In this review, we summarize recent studies using breast, liver and brain cancer cell lines and highlight the role of RSU1 in regulating cancer cell invasion.
    [Show full text]
  • Multi-Targeted Mechanisms Underlying the Endothelial Protective Effects of the Diabetic-Safe Sweetener Erythritol
    Multi-Targeted Mechanisms Underlying the Endothelial Protective Effects of the Diabetic-Safe Sweetener Erythritol Danie¨lle M. P. H. J. Boesten1*., Alvin Berger2.¤, Peter de Cock3, Hua Dong4, Bruce D. Hammock4, Gertjan J. M. den Hartog1, Aalt Bast1 1 Department of Toxicology, Maastricht University, Maastricht, The Netherlands, 2 Global Food Research, Cargill, Wayzata, Minnesota, United States of America, 3 Cargill RandD Center Europe, Vilvoorde, Belgium, 4 Department of Entomology and UCD Comprehensive Cancer Center, University of California Davis, Davis, California, United States of America Abstract Diabetes is characterized by hyperglycemia and development of vascular pathology. Endothelial cell dysfunction is a starting point for pathogenesis of vascular complications in diabetes. We previously showed the polyol erythritol to be a hydroxyl radical scavenger preventing endothelial cell dysfunction onset in diabetic rats. To unravel mechanisms, other than scavenging of radicals, by which erythritol mediates this protective effect, we evaluated effects of erythritol in endothelial cells exposed to normal (7 mM) and high glucose (30 mM) or diabetic stressors (e.g. SIN-1) using targeted and transcriptomic approaches. This study demonstrates that erythritol (i.e. under non-diabetic conditions) has minimal effects on endothelial cells. However, under hyperglycemic conditions erythritol protected endothelial cells against cell death induced by diabetic stressors (i.e. high glucose and peroxynitrite). Also a number of harmful effects caused by high glucose, e.g. increased nitric oxide release, are reversed. Additionally, total transcriptome analysis indicated that biological processes which are differentially regulated due to high glucose are corrected by erythritol. We conclude that erythritol protects endothelial cells during high glucose conditions via effects on multiple targets.
    [Show full text]
  • Role of PINCH and Its Partner Tumor Suppressor Rsu-1 in Regulating Liver Size and Tumorigenesis
    Role of PINCH and Its Partner Tumor Suppressor Rsu-1 in Regulating Liver Size and Tumorigenesis Shashikiran Donthamsetty1, Vishakha S. Bhave2, Wendy M. Mars1, William C. Bowen1, Anne Orr1, Meagan M. Haynes1, Chuanyue Wu1, George K. Michalopoulos1* 1 University of Pittsburgh School of Medicine, Department of Pathology, Pittsburgh, Pennsylvania, United States of America, 2 Philadelphia College of Osteopathic Medicine, School of Pharmacy, Department of Pharmaceutical Sciences, Suwannee, Georgia, United States of America Abstract Particularly interesting new cysteine-histidine-rich protein (PINCH) protein is part of the ternary complex known as the IPP (integrin linked kinase (ILK)-PINCH-Parvin-α) complex. PINCH itself binds to ILK and to another protein known as Rsu-1 (Ras suppressor 1). We generated PINCH 1 and PINCH 2 Double knockout mice (referred as PINCH DKO mice). PINCH2 elimination was systemic whereas PINCH1 elimination was targeted to hepatocytes. The genetically modified mice were born normal. The mice were sacrificed at different ages after birth. Soon after birth, they developed abnormal hepatic histology characterized by disorderly hepatic plates, increased proliferation of hepatocytes and biliary cells and increased deposition of extracellular matrix. After a sustained and prolonged proliferation of all epithelial components, proliferation subsided and final liver weight by the end of 30 weeks in livers with PINCH DKO deficient hepatocytes was 40% larger than the control mice. The livers of the PINCH DKO mice were also very stiff due to increased ECM deposition throughout the liver, with no observed nodularity. Mice developed liver cancer by one year. These mice regenerated normally when subjected to 70% partial hepatectomy and did not show any termination defect.
    [Show full text]
  • US 2014/0228556A1 Fukuda Et Al
    US 20140228556A1 (19) United States (12) Patent Application Publication (10) Pub. No.: US 2014/0228556A1 Fukuda et al. (43) Pub. Date: Aug. 14, 2014 (54) RBOZYME FOR IDENTIFYING Publication Classification MODIFICATION ON RNASEQUENCE AND RNA CLEAVAGE METHOD USING SAME (51) Int. Cl. CI2N IS/II3 (2006.01) (75) Inventors: Masatora Fukuda, Fukuoka (JP); (52) U.S. Cl. Masanobu Deshimaru, Fukuoka (JP); CPC .................................... CI2N 15/I 13 (2013.01) Kei Kurihara, Fukuoka (JP) USPC ......................................... 536/23.1; 536/25.3 (73) Assignee: Fukuoka University, Fukuoka (JP) (21) Appl. No.: 14/118,562 (57) ABSTRACT (22) PCT Fled: May 19, 2012 The hammerhead ribozyme according to the present inven tion produces a hammerhead ribozyme-target RNA con (86) PCT NO.: PCT/UP2012/062878 struct by base-pairing with an edited target RNA, and an S371 (c)(1), editing recognition site of the hammerhead ribozyme cleaves (2), (4) Date: Nov. 19, 2013 the modification site by forming a base pair with the target RNA modification site. The cleavage of the modification site Related U.S. Application Data is expected to be applicable to the research and development (60) Provisional application No. 61/488.345, filed on May of new drugs that can be used to prevent or treat diseases 20, 2011. caused by the edited target RNA. Patent Application Publication Aug. 14, 2014 Sheet 1 of 21 US 2014/0228556 A1 FIG. 1 R2C fia S-A&CAAA Gia--O f f f A SITE / ESTE R 8 S: On O-P-O S. F.G. 1 RNAEDITING AND 3. 2....Y.A38 KC 38ii, 2.O.Y.A38; {S:33:38.88: FIG 2 sk- SES / , C38.arm-Es PRES J/ Riggy, iaiti isS: Arg.
    [Show full text]
  • Accurate Prediction of Kinase-Substrate Networks Using
    bioRxiv preprint doi: https://doi.org/10.1101/865055; this version posted December 4, 2019. 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. Accurate Prediction of Kinase-Substrate Networks Using Knowledge Graphs V´ıtNov´aˇcek1∗+, Gavin McGauran3, David Matallanas3, Adri´anVallejo Blanco3,4, Piero Conca2, Emir Mu~noz1,2, Luca Costabello2, Kamalesh Kanakaraj1, Zeeshan Nawaz1, Sameh K. Mohamed1, Pierre-Yves Vandenbussche2, Colm Ryan3, Walter Kolch3,5,6, Dirk Fey3,6∗ 1Data Science Institute, National University of Ireland Galway, Ireland 2Fujitsu Ireland Ltd., Co. Dublin, Ireland 3Systems Biology Ireland, University College Dublin, Belfield, Dublin 4, Ireland 4Department of Oncology, Universidad de Navarra, Pamplona, Spain 5Conway Institute of Biomolecular & Biomedical Research, University College Dublin, Belfield, Dublin 4, Ireland 6School of Medicine, University College Dublin, Belfield, Dublin 4, Ireland ∗ Corresponding authors ([email protected], [email protected]). + Lead author. 1 bioRxiv preprint doi: https://doi.org/10.1101/865055; this version posted December 4, 2019. 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. Abstract Phosphorylation of specific substrates by protein kinases is a key control mechanism for vital cell-fate decisions and other cellular pro- cesses. However, discovering specific kinase-substrate relationships is time-consuming and often rather serendipitous.
    [Show full text]
  • Dema and Faust Et Al., Suppl. Material 2020.02.03
    Supplementary Materials Cyclin-dependent kinase 18 controls trafficking of aquaporin-2 and its abundance through ubiquitin ligase STUB1, which functions as an AKAP Dema Alessandro1,2¶, Dörte Faust1¶, Katina Lazarow3, Marc Wippich3, Martin Neuenschwander3, Kerstin Zühlke1, Andrea Geelhaar1, Tamara Pallien1, Eileen Hallscheidt1, Jenny Eichhorst3, Burkhard Wiesner3, Hana Černecká1, Oliver Popp1, Philipp Mertins1, Gunnar Dittmar1, Jens Peter von Kries3, Enno Klussmann1,4* ¶These authors contributed equally to this work 1Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Robert- Rössle-Strasse 10, 13125 Berlin, Germany 2current address: University of California, San Francisco, 513 Parnassus Avenue, CA 94122 USA 3Leibniz-Forschungsinstitut für Molekulare Pharmakologie (FMP), Robert-Rössle-Strasse 10, 13125 Berlin, Germany 4DZHK (German Centre for Cardiovascular Research), Partner Site Berlin, Oudenarder Strasse 16, 13347 Berlin, Germany *Corresponding author Enno Klussmann Max Delbrück Center for Molecular Medicine Berlin in the Helmholtz Association (MDC) Robert-Rössle-Str. 10, 13125 Berlin Germany Tel. +49-30-9406 2596 FAX +49-30-9406 2593 E-mail: [email protected] 1 Content 1. CELL-BASED SCREENING BY AUTOMATED IMMUNOFLUORESCENCE MICROSCOPY 3 1.1 Screening plates 3 1.2 Image analysis using CellProfiler 17 1.4 Identification of siRNA affecting cell viability 18 1.7 Hits 18 2. SUPPLEMENTARY TABLE S4, FIGURES S2-S4 20 2 1. Cell-based screening by automated immunofluorescence microscopy 1.1 Screening plates Table S1. Genes targeted with the Mouse Protein Kinases siRNA sub-library. Genes are sorted by plate and well. Accessions refer to National Center for Biotechnology Information (NCBI, BLA) entries. The siRNAs were arranged on three 384-well microtitre platres.
    [Show full text]
  • Whole-Exome Sequencing, Proteome Landscape, and Immune Cell Migration Patterns in a Clinical Context of Menkes Disease
    G C A T T A C G G C A T genes Article Whole-Exome Sequencing, Proteome Landscape, and Immune Cell Migration Patterns in a Clinical Context of Menkes Disease Margarita L. Martinez-Fierro 1,* , Griselda A. Cabral-Pacheco 1, Idalia Garza-Veloz 1 , Jesus Acuña-Quiñones 1, Laura E. Martinez-de-Villarreal 2 , Marisol Ibarra-Ramirez 2 , Joke Beuten 3, Samantha E. Sanchez-Guerrero 4, Laura Villarreal-Martinez 5, Ivan Delgado-Enciso 6 , Iram P. Rodriguez-Sanchez 7, Vania Z. Zuñiga-Ramirez 1, Edith Cardenas-Vargas 4 and Viktor Romero-Diaz 8 1 Molecular Medicine Laboratory, Unidad Académica de Medicina Humana y C.S, Universidad Autónoma de Zacatecas, Carretera Zacatecas-Guadalajara Km.6, Ejido la Escondida, Zacatecas 98160, Mexico; [email protected] (G.A.C.-P.); [email protected] (I.G.-V.); [email protected] (J.A.-Q.); [email protected] (V.Z.Z.-R.) 2 Departamento de Genética, Facultad de Medicina, Universidad Autónoma de Nuevo León, Monterrey 64460, Mexico; [email protected] (L.E.M.-d.-V.); [email protected] (M.I.-R.) 3 AiLife Diagnostics, 1920 Country Pl Pkwy Suite 100, Pearland, TX 77584, USA; [email protected] 4 Hospital General Zacatecas “Luz González Cosío”, Servicios de Salud de Zacatecas, Zacatecas 98160, Mexico; [email protected] (S.E.S.-G.); [email protected] (E.C.-V.) 5 Hematology Service, Hospital Universitario “Dr. José Eleuterio González”, Universidad Autónoma de Nuevo Citation: Martinez-Fierro, M.L.; León, Monterrey 64460, Mexico; [email protected] Cabral-Pacheco, G.A.;
    [Show full text]
  • Supplementary Table 1 Double Treatment Vs Single Treatment
    Supplementary table 1 Double treatment vs single treatment Probe ID Symbol Gene name P value Fold change TC0500007292.hg.1 NIM1K NIM1 serine/threonine protein kinase 1.05E-04 5.02 HTA2-neg-47424007_st NA NA 3.44E-03 4.11 HTA2-pos-3475282_st NA NA 3.30E-03 3.24 TC0X00007013.hg.1 MPC1L mitochondrial pyruvate carrier 1-like 5.22E-03 3.21 TC0200010447.hg.1 CASP8 caspase 8, apoptosis-related cysteine peptidase 3.54E-03 2.46 TC0400008390.hg.1 LRIT3 leucine-rich repeat, immunoglobulin-like and transmembrane domains 3 1.86E-03 2.41 TC1700011905.hg.1 DNAH17 dynein, axonemal, heavy chain 17 1.81E-04 2.40 TC0600012064.hg.1 GCM1 glial cells missing homolog 1 (Drosophila) 2.81E-03 2.39 TC0100015789.hg.1 POGZ Transcript Identified by AceView, Entrez Gene ID(s) 23126 3.64E-04 2.38 TC1300010039.hg.1 NEK5 NIMA-related kinase 5 3.39E-03 2.36 TC0900008222.hg.1 STX17 syntaxin 17 1.08E-03 2.29 TC1700012355.hg.1 KRBA2 KRAB-A domain containing 2 5.98E-03 2.28 HTA2-neg-47424044_st NA NA 5.94E-03 2.24 HTA2-neg-47424360_st NA NA 2.12E-03 2.22 TC0800010802.hg.1 C8orf89 chromosome 8 open reading frame 89 6.51E-04 2.20 TC1500010745.hg.1 POLR2M polymerase (RNA) II (DNA directed) polypeptide M 5.19E-03 2.20 TC1500007409.hg.1 GCNT3 glucosaminyl (N-acetyl) transferase 3, mucin type 6.48E-03 2.17 TC2200007132.hg.1 RFPL3 ret finger protein-like 3 5.91E-05 2.17 HTA2-neg-47424024_st NA NA 2.45E-03 2.16 TC0200010474.hg.1 KIAA2012 KIAA2012 5.20E-03 2.16 TC1100007216.hg.1 PRRG4 proline rich Gla (G-carboxyglutamic acid) 4 (transmembrane) 7.43E-03 2.15 TC0400012977.hg.1 SH3D19
    [Show full text]
  • Chromosome Instability, Chromosome Transcriptome, and Clonal Evolution of Tumor Cell Populations
    Chromosome instability, chromosome transcriptome, and clonal evolution of tumor cell populations ChongFeng Gao*, Kyle Furge†, Julie Koeman‡, Karl Dykema†, Yanli Su*, Mary Lou Cutler§, Adam Werts*, Pete Haak¶, and George F. Vande Woude*ʈ Laboratories of *Molecular Oncology, †Computational Biology, ‡Germline Modification, and ¶Microarray Technology, Van Andel Research Institute, 333 Bostwick Avenue, N.E., Grand Rapids, MI 49503; and §University Services University of the Health Sciences, 4301 Jones Bridge Road, Bethesda, MD 20814 Edited by Janet D. Rowley, University of Chicago Medical Center, Chicago, IL, and approved March 29, 2007 (received for review January 23, 2007) Chromosome instability and aneuploidy are hallmarks of cancer, Phenotypic switching is fundamental for malignant progression but it is not clear how changes in the chromosomal content of a cell (6), and therefore it is important to understand the responsible contribute to the malignant phenotype. Previously we have shown mechanisms. that we can readily isolate highly proliferative tumor cells and their Glioblastomas characteristically show extensive regional cytoge- revertants from highly invasive tumor cell populations, indicating netic heterogeneity (10, 11), and this diversity may be responsible how phenotypic shifting can contribute to malignant progression. for tumor evolution and progression (10, 12). Here we show that Here we show that chromosome instability and changes in chro- distinct changes in karyotype from chromosome instability accom- mosome content occur with phenotypic switching. Further, we pany phenotypic switching. These changes, in turn, dictate changes show that changes in the copy number of each chromosome in the chromosome transcriptome that provide the expression of quantitatively impose a proportional change in the chromosome individual genes that are necessary for the conversion between the transcriptome ratio.
    [Show full text]
  • A Genome-Wide Scan of Cleft Lip Triads Identifies Parent
    F1000Research 2019, 8:960 Last updated: 03 AUG 2021 RESEARCH ARTICLE A genome-wide scan of cleft lip triads identifies parent- of-origin interaction effects between ANK3 and maternal smoking, and between ARHGEF10 and alcohol consumption [version 2; peer review: 2 approved] Øystein Ariansen Haaland 1, Julia Romanowska1,2, Miriam Gjerdevik1,3, Rolv Terje Lie1,4, Håkon Kristian Gjessing 1,4, Astanand Jugessur1,3,4 1Department of Global Public Health and Primary Care, University of Bergen, Bergen, N-5020, Norway 2Computational Biology Unit, University of Bergen, Bergen, N-5020, Norway 3Department of Genetics and Bioinformatics, Norwegian Institute of Public Health, Skøyen, Oslo, Skøyen, N-0213, Norway 4Centre for Fertility and Health (CeFH), Norwegian Institute of Public Health, Skøyen, Oslo, N-0213, Norway v2 First published: 24 Jun 2019, 8:960 Open Peer Review https://doi.org/10.12688/f1000research.19571.1 Latest published: 19 Jul 2019, 8:960 https://doi.org/10.12688/f1000research.19571.2 Reviewer Status Invited Reviewers Abstract Background: Although both genetic and environmental factors have 1 2 been reported to influence the risk of isolated cleft lip with or without cleft palate (CL/P), the exact mechanisms behind CL/P are still largely version 2 unaccounted for. We recently developed new methods to identify (revision) report parent-of-origin (PoO) interactions with environmental exposures 19 Jul 2019 (PoOxE) and now apply them to data from a genome-wide association study (GWAS) of families with children born with isolated CL/P. version 1 Methods: Genotypes from 1594 complete triads and 314 dyads (1908 24 Jun 2019 report report nuclear families in total) with CL/P were available for the current analyses.
    [Show full text]
  • 1 Novel Expression Signatures Identified by Transcriptional Analysis
    ARD Online First, published on October 8, 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 October 2, 2021 by guest. Protected copyright. 1 Copyright Article author (or their employer) 2009.
    [Show full text]
  • Weight Traits in Sheep: a GWAS and Pathway Enrichment Analysis
    1 Maternal genes and pathways affecting birth weight and weaning 2 weight traits in sheep: A GWAS and pathway enrichment analysis 3 Mehdi Esmaeilifard1, Seyed Hasan Hafezian2, Mohsen Gholizadeh2, Rostam Abdollahi- 4 Arpanahi3 5 1 Ph.D. Graduate, Sari Agricultural Sciences and Natural Resources University (SANRU), Sari, Iran 6 1, 2 Associate Professor, Sari Agricultural Sciences and Natural Resources University (SANRU), Sari, Iran 7 3 Research Assistant, Department of Animal Sciences, University of Florida, Gainesville, FL, United States 8 Abstract 9 Background: Ewe productivity is considered as the most important economic trait in sheep meat 10 production. Due to very limited reports, the objective of this study was the application of 11 alternative GWAS approaches followed by gene set enrichment analysis (GSEA) on the maternal 12 genome to unravel the genomic architecture underlying ewe productivity in Iranian Baluchi sheep. 13 Six maternal composite traits including progeny birth weight (PBW), litter mean weight at birth 14 (LMWB), total litter weight at birth (TLWB), progeny weaning weight (PWW), litter mean weight 15 at weaning (LMWW) and total litter weight at weaning (TLWW) were studied. 16 Results: Genes such as RDX, FDX1, ARHGAP20, ZC3H12C, THBS1, and EPG5 on OAR6, 17 OAR7, OAR15, and OAR23 were identified for composite traits at birth. The genes are involved 18 in pregnancy, including autophagy in the placenta, progesterone production by the placenta, 19 maternal immune response and placenta formation. Some maternal pathways, related to calcium 20 ion transport, signal transduction, neurogenesis, and immune response were also identified for 21 birth weight traits. Moreover, many genes including NR2C1, VEZT, HSD17B4, RSU1, CUBN, 22 VIM, PRLR, and FTH1 were located on OAR2, OAR3, OAR5, OAR7, OAR13, OAR16, and 23 OAR25 identified as maternal genes affecting weaning weight traits.
    [Show full text]