Acute Myeloid Leukemia (AML): Proof-Of-Principle of Co-Operativity in AML
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High-Resolution SNP Arrays in Mental Retardation Diagnostics: How Much Do We Gain?
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Archivio della ricerca- Università di Roma La Sapienza European Journal of Human Genetics (2010) 18, 178–185 & 2010 Macmillan Publishers Limited All rights reserved 1018-4813/10 $32.00 www.nature.com/ejhg ARTICLE High-resolution SNP arrays in mental retardation diagnostics: how much do we gain? Laura Bernardini1, Viola Alesi1,2, Sara Loddo1,2, Antonio Novelli1, Irene Bottillo1, Agatino Battaglia3, Maria Cristina Digilio4, Giuseppe Zampino5, Adam Ertel2, Paolo Fortina*,2,6, Saul Surrey7 and Bruno Dallapiccola1 We used Affymetrix 6.0 GeneChip SNP arrays to characterize copy number variations (CNVs) in a cohort of 70 patients previously characterized on lower-density oligonucleotide arrays affected by idiopathic mental retardation and dysmorphic features. The SNP array platform includes B900 000 SNP probes and 900 000 non-SNP oligonucleotide probes at an average distance of 0.7 Kb, which facilitates coverage of the whole genome, including coding and noncoding regions. The high density of probes is critical for detecting small CNVs, but it can lead to data interpretation problems. To reduce the number of false positives, parameters were set to consider only imbalances 475 Kb encompassing at least 80 probe sets. The higher resolution of the SNP array platform confirmed the increased ability to detect small CNVs, although more than 80% of these CNVs overlapped to copy number ‘neutral’ polymorphism regions and 4.4% of them did not contain known genes. In our cohort of 70 patients, of the 51 previously evaluated as ‘normal’ on the Agilent 44K array, the SNP array platform disclosed six additional CNV changes, including three in three patients, which may be pathogenic. -
Circular RNA Hsa Circ 0005114‑Mir‑142‑3P/Mir‑590‑5P‑ Adenomatous
ONCOLOGY LETTERS 21: 58, 2021 Circular RNA hsa_circ_0005114‑miR‑142‑3p/miR‑590‑5p‑ adenomatous polyposis coli protein axis as a potential target for treatment of glioma BO WEI1*, LE WANG2* and JINGWEI ZHAO1 1Department of Neurosurgery, China‑Japan Union Hospital of Jilin University, Changchun, Jilin 130033; 2Department of Ophthalmology, The First Hospital of Jilin University, Jilin University, Changchun, Jilin 130021, P.R. China Received September 12, 2019; Accepted October 22, 2020 DOI: 10.3892/ol.2020.12320 Abstract. Glioma is the most common type of brain tumor APC expression with a good overall survival rate. UALCAN and is associated with a high mortality rate. Despite recent analysis using TCGA data of glioblastoma multiforme and the advances in treatment options, the overall prognosis in patients GSE25632 and GSE103229 microarray datasets showed that with glioma remains poor. Studies have suggested that circular hsa‑miR‑142‑3p/hsa‑miR‑590‑5p was upregulated and APC (circ)RNAs serve important roles in the development and was downregulated. Thus, hsa‑miR‑142‑3p/hsa‑miR‑590‑5p‑ progression of glioma and may have potential as therapeutic APC‑related circ/ceRNA axes may be important in glioma, targets. However, the expression profiles of circRNAs and their and hsa_circ_0005114 interacted with both of these miRNAs. functions in glioma have rarely been studied. The present study Functional analysis showed that hsa_circ_0005114 was aimed to screen differentially expressed circRNAs (DECs) involved in insulin secretion, while APC was associated with between glioma and normal brain tissues using sequencing the Wnt signaling pathway. In conclusion, hsa_circ_0005114‑ data collected from the Gene Expression Omnibus database miR‑142‑3p/miR‑590‑5p‑APC ceRNA axes may be potential (GSE86202 and GSE92322 datasets) and explain their mecha‑ targets for the treatment of glioma. -
1 Supporting Information for a Microrna Network Regulates
Supporting Information for A microRNA Network Regulates Expression and Biosynthesis of CFTR and CFTR-ΔF508 Shyam Ramachandrana,b, Philip H. Karpc, Peng Jiangc, Lynda S. Ostedgaardc, Amy E. Walza, John T. Fishere, Shaf Keshavjeeh, Kim A. Lennoxi, Ashley M. Jacobii, Scott D. Rosei, Mark A. Behlkei, Michael J. Welshb,c,d,g, Yi Xingb,c,f, Paul B. McCray Jr.a,b,c Author Affiliations: Department of Pediatricsa, Interdisciplinary Program in Geneticsb, Departments of Internal Medicinec, Molecular Physiology and Biophysicsd, Anatomy and Cell Biologye, Biomedical Engineeringf, Howard Hughes Medical Instituteg, Carver College of Medicine, University of Iowa, Iowa City, IA-52242 Division of Thoracic Surgeryh, Toronto General Hospital, University Health Network, University of Toronto, Toronto, Canada-M5G 2C4 Integrated DNA Technologiesi, Coralville, IA-52241 To whom correspondence should be addressed: Email: [email protected] (M.J.W.); yi- [email protected] (Y.X.); Email: [email protected] (P.B.M.) This PDF file includes: Materials and Methods References Fig. S1. miR-138 regulates SIN3A in a dose-dependent and site-specific manner. Fig. S2. miR-138 regulates endogenous SIN3A protein expression. Fig. S3. miR-138 regulates endogenous CFTR protein expression in Calu-3 cells. Fig. S4. miR-138 regulates endogenous CFTR protein expression in primary human airway epithelia. Fig. S5. miR-138 regulates CFTR expression in HeLa cells. Fig. S6. miR-138 regulates CFTR expression in HEK293T cells. Fig. S7. HeLa cells exhibit CFTR channel activity. Fig. S8. miR-138 improves CFTR processing. Fig. S9. miR-138 improves CFTR-ΔF508 processing. Fig. S10. SIN3A inhibition yields partial rescue of Cl- transport in CF epithelia. -
The Potential Role of SEPT6 in Liver Fibrosis and Human Hepatocellular Carcinoma. Arch Gastroenterol Res
https://www.scientificarchives.com/journal/archives-of-gastroenterology-research Archives of Gastroenterology Research Commentary The Potential Role of SEPT6 in Liver Fibrosis and Human Hepatocellular Carcinoma Yuhui Fan1,2,3*, Mei Liu3* 1Department of Medicine II, Liver Center Munich, University Hospital, Ludwig-Maximilians-University of Munich, Munich, Germany 2Comprehensive Cancer Center München TUM, Klinikum rechts der Isar, Technical University of Munich (TUM), Munich, Germany 3Institute of Liver and Gastrointestinal Diseases, Department of Gastroenterology, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China *Correspondence should be addressed to Yuhui Fan; [email protected], Mei Liu; [email protected] Received date: May 19, 2020, Accepted date: May 26, 2020 Copyright: © 2020 Fan Y, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Liver fibrosis is a reversible wound-healing response in and chemotactic has been regarded as the main driver which a variety of cells and factors are involved in and of liver fibrosis [7], thus ECM production is enhanced results in excessive deposition of extracellular matrix [8]. Paracrine signals from damaged epithelial cells, (ECM) [1]. Cirrhosis is one of the significant causes of fibrotic tissue microenvironment, disorders of immunity portal hypertension and end-stage liver disease, and it is and systemic metabolism, intestinal dysbiosis and the 14th most common cause of death around the world. hepatitis virus products can directly or indirectly induce Approximately 1.03 million people worldwide die from HSCs activation [9]. -
A Comprehensive Transcriptome Analysis of Skeletal Muscles in Two Polish Pig Breeds Differing in Fat and Meat Quality Traits
Genetics and Molecular Biology, 41, 1, 125-136 (2018) Copyright © 2018, Sociedade Brasileira de Genética. Printed in Brazil DOI: http://dx.doi.org/10.1590/1678-4685-GMB-2016-0101 Research Article A comprehensive transcriptome analysis of skeletal muscles in two Polish pig breeds differing in fat and meat quality traits Katarzyna Piórkowska1 , Kacper òukowski3, Katarzyna Ropka-Molik1, Miros»aw Tyra2 and Artur Gurgul1 1Department of Animal Molecular Biology, National Research Institute of Animal Production, Balice, Poland. 2Department of Pig Breeding, National Research Institute of Animal Production, Balice, Poland. 3Department of Cattle Breeding, National Research Institute of Animal Production, Balice, Poland. Abstract Pork is the most popular meat in the world. Unfortunately, the selection pressure focused on high meat content led to a reduction in pork quality. The present study used RNA-seq technology to identify metabolic process genes related to pork quality traits and fat deposition. Differentially expressed genes (DEGs) were identified between pigs of Pulawska and Polish Landrace breeds for two the most important muscles (semimembranosus and longissimus dorsi). A total of 71 significant DEGs were reported: 15 for longissimus dorsi and 56 for semimembranosus muscles. The genes overexpressed in Pulawska pigs were involved in lipid metabolism (APOD, LXRA, LIPE, AP2B1, ENSSSCG00000028753 and OAS2) and proteolysis (CST6, CTSD, ISG15 and UCHL1). In Polish Landrace pigs, genes playing a role in biological adhesion (KIT, VCAN, HES1, SFRP2, CDH11, SSX2IP and PCDH17), actin cytoskeletal organisation (FRMD6, LIMK1, KIF23 and CNN1) and calcium ion binding (PVALB, CIB2, PCDH17, VCAN and CDH11) were transcriptionally more active. The present study allows for better understanding of the physiological processes associated with lipid metabolism and muscle fiber organization. -
In This Table Protein Name, Uniprot Code, Gene Name P-Value
Supplementary Table S1: In this table protein name, uniprot code, gene name p-value and Fold change (FC) for each comparison are shown, for 299 of the 301 significantly regulated proteins found in both comparisons (p-value<0.01, fold change (FC) >+/-0.37) ALS versus control and FTLD-U versus control. Two uncharacterized proteins have been excluded from this list Protein name Uniprot Gene name p value FC FTLD-U p value FC ALS FTLD-U ALS Cytochrome b-c1 complex P14927 UQCRB 1.534E-03 -1.591E+00 6.005E-04 -1.639E+00 subunit 7 NADH dehydrogenase O95182 NDUFA7 4.127E-04 -9.471E-01 3.467E-05 -1.643E+00 [ubiquinone] 1 alpha subcomplex subunit 7 NADH dehydrogenase O43678 NDUFA2 3.230E-04 -9.145E-01 2.113E-04 -1.450E+00 [ubiquinone] 1 alpha subcomplex subunit 2 NADH dehydrogenase O43920 NDUFS5 1.769E-04 -8.829E-01 3.235E-05 -1.007E+00 [ubiquinone] iron-sulfur protein 5 ARF GTPase-activating A0A0C4DGN6 GIT1 1.306E-03 -8.810E-01 1.115E-03 -7.228E-01 protein GIT1 Methylglutaconyl-CoA Q13825 AUH 6.097E-04 -7.666E-01 5.619E-06 -1.178E+00 hydratase, mitochondrial ADP/ATP translocase 1 P12235 SLC25A4 6.068E-03 -6.095E-01 3.595E-04 -1.011E+00 MIC J3QTA6 CHCHD6 1.090E-04 -5.913E-01 2.124E-03 -5.948E-01 MIC J3QTA6 CHCHD6 1.090E-04 -5.913E-01 2.124E-03 -5.948E-01 Protein kinase C and casein Q9BY11 PACSIN1 3.837E-03 -5.863E-01 3.680E-06 -1.824E+00 kinase substrate in neurons protein 1 Tubulin polymerization- O94811 TPPP 6.466E-03 -5.755E-01 6.943E-06 -1.169E+00 promoting protein MIC C9JRZ6 CHCHD3 2.912E-02 -6.187E-01 2.195E-03 -9.781E-01 Mitochondrial 2- -
A Proteome-Scale Map of the Human Interactome Network
Resource A Proteome-Scale Map of the Human Interactome Network Thomas Rolland,1,2,19 Murat Tasxan,1,3,4,5,19 Benoit Charloteaux,1,2,19 Samuel J. Pevzner,1,2,6,7,19 Quan Zhong,1,2,8,19 Nidhi Sahni,1,2,19 Song Yi,1,2,19 Irma Lemmens,9 Celia Fontanillo,10 Roberto Mosca,11 Atanas Kamburov,1,2 Susan D. Ghiassian,1,12 Xinping Yang,1,2 Lila Ghamsari,1,2 Dawit Balcha,1,2 Bridget E. Begg,1,2 Pascal Braun,1,2 Marc Brehme,1,2 Martin P. Broly,1,2 Anne-Ruxandra Carvunis,1,2 Dan Convery-Zupan,1,2 Roser Corominas,13 Jasmin Coulombe-Huntington,1,14 Elizabeth Dann,1,2 Matija Dreze,1,2 Ame´ lie Dricot,1,2 Changyu Fan,1,2 Eric Franzosa,1,14 Fana Gebreab,1,2 Bryan J. Gutierrez,1,2 Madeleine F. Hardy,1,2 Mike Jin,1,2 Shuli Kang,13 Ruth Kiros,1,2 Guan Ning Lin,13 Katja Luck,1,2 Andrew MacWilliams,1,2 Jo¨ rg Menche,1,12 Ryan R. Murray,1,2 Alexandre Palagi,1,2 Matthew M. Poulin,1,2 Xavier Rambout,1,2,15 John Rasla,1,2 Patrick Reichert,1,2 Viviana Romero,1,2 Elien Ruyssinck,9 Julie M. Sahalie,1,2 Annemarie Scholz,1,2 Akash A. Shah,1,2 Amitabh Sharma,1,12 Yun Shen,1,2 Kerstin Spirohn,1,2 Stanley Tam,1,2 Alexander O. Tejeda,1,2 Shelly A. Trigg,1,2 Jean-Claude Twizere,1,2,15 Kerwin Vega,1,2 Jennifer Walsh,1,2 Michael E. -
Identification of Key Genes and Pathways for Alzheimer's Disease
Biophys Rep 2019, 5(2):98–109 https://doi.org/10.1007/s41048-019-0086-2 Biophysics Reports RESEARCH ARTICLE Identification of key genes and pathways for Alzheimer’s disease via combined analysis of genome-wide expression profiling in the hippocampus Mengsi Wu1,2, Kechi Fang1, Weixiao Wang1,2, Wei Lin1,2, Liyuan Guo1,2&, Jing Wang1,2& 1 CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China 2 Department of Psychology, University of Chinese Academy of Sciences, Beijing 10049, China Received: 8 August 2018 / Accepted: 17 January 2019 / Published online: 20 April 2019 Abstract In this study, combined analysis of expression profiling in the hippocampus of 76 patients with Alz- heimer’s disease (AD) and 40 healthy controls was performed. The effects of covariates (including age, gender, postmortem interval, and batch effect) were controlled, and differentially expressed genes (DEGs) were identified using a linear mixed-effects model. To explore the biological processes, func- tional pathway enrichment and protein–protein interaction (PPI) network analyses were performed on the DEGs. The extended genes with PPI to the DEGs were obtained. Finally, the DEGs and the extended genes were ranked using the convergent functional genomics method. Eighty DEGs with q \ 0.1, including 67 downregulated and 13 upregulated genes, were identified. In the pathway enrichment analysis, the 80 DEGs were significantly enriched in one Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, GABAergic synapses, and 22 Gene Ontology terms. These genes were mainly involved in neuron, synaptic signaling and transmission, and vesicle metabolism. These processes are all linked to the pathological features of AD, demonstrating that the GABAergic system, neurons, and synaptic function might be affected in AD. -
Mirna Regulons Associated with Synaptic Function
miRNA Regulons Associated with Synaptic Function Maria Paschou1, Maria D. Paraskevopoulou2, Ioannis S. Vlachos2, Pelagia Koukouraki1, Artemis G. Hatzigeorgiou2,3, Epaminondas Doxakis1* 1 Basic Neurosciences Division, Biomedical Research Foundation of the Academy of Athens, Athens, Greece, 2 Institute of Molecular Oncology, Biomedical Sciences Research Center ‘‘Alexander Fleming’’ Vari, Greece, 3 Department of Computer and Communication Engineering, University of Thessaly, Volos, Greece Abstract Differential RNA localization and local protein synthesis regulate synapse function and plasticity in neurons. MicroRNAs are a conserved class of regulatory RNAs that control mRNA stability and translation in tissues. They are abundant in the brain but the extent into which they are involved in synaptic mRNA regulation is poorly known. Herein, a computational analysis of the coding and 39UTR regions of 242 presynaptic and 304 postsynaptic proteins revealed that 91% of them are predicted to be microRNA targets. Analysis of the longest 39UTR isoform of synaptic transcripts showed that presynaptic mRNAs have significantly longer 39UTR than control and postsynaptic mRNAs. In contrast, the shortest 39UTR isoform of postsynaptic mRNAs is significantly shorter than control and presynaptic mRNAs, indicating they avert microRNA regulation under specific conditions. Examination of microRNA binding site density of synaptic 39UTRs revealed that they are twice as dense as the rest of protein-coding transcripts and that approximately 50% of synaptic transcripts are predicted to have more than five different microRNA sites. An interaction map exploring the association of microRNAs and their targets revealed that a small set of ten microRNAs is predicted to regulate 77% and 80% of presynaptic and postsynaptic transcripts, respectively. -
Analysis of Kidney Glomerular and Microvascular Transcriptomes
Department of Medical Biochemistry and Biophysics Karolinska Institutet, Stockholm, Sweden ANALYSIS OF KIDNEY GLOMERULAR AND MICROVASCULAR TRANSCRIPTOMES Liqun He Stockholm 2007 All previously published papers were reproduced with permission from the publisher. Published by Karolinska Institutet. Printed by US-AB © Liqun He, 2007 ISBN 978-91-7357-300-9 献给我挚爱的家人 To my beloved family ABSTRACT Kidney glomeruli play a crucial role in the maintenance of body homeostasis. Many diseases attack the kidney function by primarily affecting glomeruli. However, the transcriptome profiles and the function of the glomerulus is poorly understood. Microvascular pericytes are multifunctional cells and they are actively involved in angiogenesis at different aspects. But shortage of molecular markers for pericyte has hampered the studies for its identification, origin and function. In order to explore the transcriptome of kidney glomeruli and microvascular pericytes, several genomics and bioinformatics approaches were applied. First, we constructed and large scale sequenced four Express Sequence Tag (EST) libraries generated from pure preparations of newborn and adult mouse glomeruli. EST sequence analysis produced direct expression profiles of kidney glomerulus and revealed glomerulus- specific expression patterns (GlomBase). By comparing the transcript abundance profiles in the glomerulus EST libraries with public whole kidney libraries, we identified 497 glomerulus-enriched mouse transcripts in the newborn and/or adult mouse glomerulus, eight of which were confirmed by individual experiments. The glomerular ESTs were printed on glass slides in order to generate cDNA microarrays with broad representation of glomerulus-expressed genes (GlomChip). Subsequently, by using GlomChip to compare the RNA samples from the glomerulus with non- glomerulus kidney tissues, we identified 357 mouse genes as glomerulus-enriched and some of them were individually studied in detail. -
SEPT12 Interacts with SEPT6 and This Interaction Alters the Filament Structure of SEPT6 in Hela Cells
Journal of Biochemistry and Molecular Biology, Vol. 40, No. 6, November 2007, pp. 973-978 SEPT12 Interacts with SEPT6 and This Interaction Alters the Filament Structure of SEPT6 in Hela Cells Xiangming Ding, Wenbo Yu, Ming Liu, Suqin Shen, Fang Chen, Bo Wan and Long Yu* State Key Laboratory of Genetic Engineering, Institute of Genetics, School of Life Science, Fudan University, Shanghai 200433, PR China Received 5 June 2007, Accepted 25 July 2007 Septins are a family of conserved cytoskeletal GTPase 1997; Surka et al., 2002), septins are implicated in a variety of forming heteropolymeric filamentous structure in interphase other celluar processes including polarity determination cells, however, the mechanism of assembly are largely (Gladfelter et al., 2001; Irazoqui et al., 2004), vesicle unknown. Here we described the characterization of trafficking (Hsu et al., 1998; Beites et al., 1999), cytoskeletal SEPT12, sharing closest homology to SEPT3 and SEPT9. remodelling (Kinoshita et al., 1997; Surka et al., 2002) It was revealed that subcelluar localization of SEPT12 ,apoptosis (Larisch et al., 2000) and neoplasia (Russel and varied at interphase and mitotic phase. While SEPT12 Hall, 2005). formed filamentous structures at interphase, it was Up to date, seven yeast septins have been identified: cdc3, localized to the central spindle and to midbody during cdc10, cdc11, cdc12, SPR3, SPR28, and SEP7/SHS1 anaphase and cytokinesis, respectively. In addition, we (DeVirgilio et al., 1996; Mino et al., 1998) and at least five found that SEPT12 can interact with SEPT6 in vitro and in septins, namely PNUT1, SEP1, SEP2, SEP4 and SEP5, are vivo, and this interaction was independent of the coiled coil known in Drosophila (Adam et al., 2000). -
Understanding Multicellular Function and Disease with Human Tissue-Specific Networks
ANALYSIS Understanding multicellular function and disease with human tissue-specific networks Casey S Greene1–3,13, Arjun Krishnan4,13, Aaron K Wong5,13, Emanuela Ricciotti6,7, Rene A Zelaya1, Daniel S Himmelstein8, Ran Zhang9, Boris M Hartmann10, Elena Zaslavsky10, Stuart C Sealfon10, Daniel I Chasman11, Garret A FitzGerald6,7, Kara Dolinski4, Tilo Grosser6,7 & Olga G Troyanskaya4,5,12 Tissue and cell-type identity lie at the core of human tissue- and cell lineage–specific processes1–4. These factors combine physiology and disease. Understanding the genetic to make the understanding of tissue-specific gene functions, disease underpinnings of complex tissues and individual cell lineages is pathophysiology and gene-disease associations particularly challeng- crucial for developing improved diagnostics and therapeutics. ing. Projects such as the Encyclopedia of DNA Elements (ENCODE)5 We present genome-wide functional interaction networks for and The Cancer Genome Atlas (TCGA)6 provide comprehensive 144 human tissues and cell types developed using a data-driven genomic profiles for cell lines and cancers, but the challenge of under- Bayesian methodology that integrates thousands of diverse standing human tissues and cell lineages in the multicellular context of experiments spanning tissue and disease states. Tissue-specific a whole organism remains7. Integrative methods that infer functional networks predict lineage-specific responses to perturbation, gene interaction networks can capture the interplay of pathways, but identify the changing functional roles of genes across tissues existing networks lack tissue specificity8. and illuminate relationships among diseases. We introduce Although direct assay of tissue-specific features remains NetWAS, which combines genes with nominally significant infeasible in many normal human tissues, computational methods genome-wide association study (GWAS) P values and tissue- can infer these features from large data compendia.