Partial Deletion of Chromosome 6P Causing Developmental Delay and Mild Dysmorphisms in a Child
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Analyses of Allele-Specific Gene Expression in Highly Divergent
ARTICLES Analyses of allele-specific gene expression in highly divergent mouse crosses identifies pervasive allelic imbalance James J Crowley1,10, Vasyl Zhabotynsky1,10, Wei Sun1,2,10, Shunping Huang3, Isa Kemal Pakatci3, Yunjung Kim1, Jeremy R Wang3, Andrew P Morgan1,4,5, John D Calaway1,4,5, David L Aylor1,9, Zaining Yun1, Timothy A Bell1,4,5, Ryan J Buus1,4,5, Mark E Calaway1,4,5, John P Didion1,4,5, Terry J Gooch1,4,5, Stephanie D Hansen1,4,5, Nashiya N Robinson1,4,5, Ginger D Shaw1,4,5, Jason S Spence1, Corey R Quackenbush1, Cordelia J Barrick1, Randal J Nonneman1, Kyungsu Kim2, James Xenakis2, Yuying Xie1, William Valdar1,4, Alan B Lenarcic1, Wei Wang3,9, Catherine E Welsh3, Chen-Ping Fu3, Zhaojun Zhang3, James Holt3, Zhishan Guo3, David W Threadgill6, Lisa M Tarantino7, Darla R Miller1,4,5, Fei Zou2,11, Leonard McMillan3,11, Patrick F Sullivan1,5,7,8,11 & Fernando Pardo-Manuel de Villena1,4,5,11 Complex human traits are influenced by variation in regulatory DNA through mechanisms that are not fully understood. Because regulatory elements are conserved between humans and mice, a thorough annotation of cis regulatory variants in mice could aid in further characterizing these mechanisms. Here we provide a detailed portrait of mouse gene expression across multiple tissues in a three-way diallel. Greater than 80% of mouse genes have cis regulatory variation. Effects from these variants influence complex traits and usually extend to the human ortholog. Further, we estimate that at least one in every thousand SNPs creates a cis regulatory effect. -
Crystal Structure of LSD1 in Complex with 4-[5-(Piperidin-4-Ylmethoxy)-2-(P-Tolyl) Pyridin-3-Yl]Benzonitrile
molecules Article Crystal Structure of LSD1 in Complex with 4-[5-(Piperidin-4-ylmethoxy)-2-(p-tolyl) pyridin-3-yl]benzonitrile Hideaki Niwa 1 ID , Shin Sato 1, Tomoko Hashimoto 2, Kenji Matsuno 2 and Takashi Umehara 1,* ID 1 Laboratory for Epigenetics Drug Discovery, RIKEN Center for Biosystems Dynamics Research (BDR), 1-7-22 Suehiro-cho, Tsurumi, Yokohama 230-0045, Japan; [email protected] (H.N.); [email protected] (S.S.) 2 Department of Chemistry and Life Science, School of Advanced Engineering, Kogakuin University, 2665-1 Nakano, Hachioji, Tokyo 192-0015, Japan; [email protected] (T.H.); [email protected] (K.M.) * Correspondence: [email protected]; Tel.: +81-45-503-9457 Received: 28 May 2018; Accepted: 22 June 2018; Published: 26 June 2018 Abstract: Because lysine-specific demethylase 1 (LSD1) regulates the maintenance of cancer stem cell properties, small-molecule inhibitors of LSD1 are expected to be useful for the treatment of several cancers. Reversible inhibitors of LSD1 with submicromolar inhibitory potency have recently been reported, but their exact binding modes are poorly understood. In this study, we synthesized a recently reported reversible inhibitor, 4-[5-(piperidin-4-ylmethoxy)-2-(p-tolyl)pyridin-3- yl]benzonitrile, which bears a 4-piperidinylmethoxy group, a 4-methylphenyl group, and a 4-cyanophenyl group on a pyridine ring, and determined the crystal structure of LSD1 in complex with this inhibitor at 2.96 Å. We observed strong electron density for the compound, showing that its cyano group forms a hydrogen bond with Lys661, which is a critical residue in the lysine demethylation reaction located deep in the catalytic center of LSD1. -
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. -
82594016.Pdf
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector Structure Article Molecular Mimicry and Ligand Recognition in Binding and Catalysis by the Histone Demethylase LSD1-CoREST Complex Riccardo Baron,1,* Claudia Binda,2 Marcello Tortorici,2 J. Andrew McCammon,1 and Andrea Mattevi2,* 1Department of Chemistry and Biochemistry, Center for Theoretical Biological Physics, and Department of Pharmacology, Howard Hughes Medical Institute, University of California at San Diego, La Jolla, CA 92093-0365, USA 2Department of Genetics and Microbiology, University of Pavia, Via Ferrata 1, 27100, Pavia, Italy *Correspondence: [email protected] (R.B.), [email protected] (A.M.) DOI 10.1016/j.str.2011.01.001 SUMMARY (LSD1 or KDM1A, according to the newly adopted nomencla- ture) (Shi et al., 2004; Forneris et al., 2005). This enzyme acts Histone demethylases LSD1 and LSD2 (KDM1A/B) on mono- and dimethylated Lys4 of histone H3 through a catalyze the oxidative demethylation of Lys4 of FAD-dependent oxidative process (Figure 1A). LSD1 is often histone H3. We used molecular dynamics simula- associated to the histone deacetylases (HDAC) 1 and 2 and to tions to probe the diffusion of the oxygen substrate. the corepressor protein CoREST, which tightly binds to LSD1 Oxygen can reach the catalytic center independently enhancing both its stability and enzymatic activity. A number of from the presence of a bound histone peptide, studies have indicated that LSD1-CoREST interacts with various protein complexes involved in gene regulation and chromatin implying that LSD1 can complete subsequent deme- modification (Forneris et al., 2008; Mosammaparast and Shi, thylation cycles without detaching from the nucleo- 2010). -
Epigenome-Wide Exploratory Study of Monozygotic Twins Suggests Differentially Methylated Regions to Associate with Hand Grip Strength
Biogerontology (2019) 20:627–647 https://doi.org/10.1007/s10522-019-09818-1 (0123456789().,-volV)( 0123456789().,-volV) RESEARCH ARTICLE Epigenome-wide exploratory study of monozygotic twins suggests differentially methylated regions to associate with hand grip strength Mette Soerensen . Weilong Li . Birgit Debrabant . Marianne Nygaard . Jonas Mengel-From . Morten Frost . Kaare Christensen . Lene Christiansen . Qihua Tan Received: 15 April 2019 / Accepted: 24 June 2019 / Published online: 28 June 2019 Ó The Author(s) 2019 Abstract Hand grip strength is a measure of mus- significant CpG sites or pathways were found, how- cular strength and is used to study age-related loss of ever two of the suggestive top CpG sites were mapped physical capacity. In order to explore the biological to the COL6A1 and CACNA1B genes, known to be mechanisms that influence hand grip strength varia- related to muscular dysfunction. By investigating tion, an epigenome-wide association study (EWAS) of genomic regions using the comb-p algorithm, several hand grip strength in 672 middle-aged and elderly differentially methylated regions in regulatory monozygotic twins (age 55–90 years) was performed, domains were identified as significantly associated to using both individual and twin pair level analyses, the hand grip strength, and pathway analyses of these latter controlling the influence of genetic variation. regions revealed significant pathways related to the Moreover, as measurements of hand grip strength immune system, autoimmune disorders, including performed over 8 years were available in the elderly diabetes type 1 and viral myocarditis, as well as twins (age 73–90 at intake), a longitudinal EWAS was negative regulation of cell differentiation. -
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. -
Supplementary Table S4. FGA Co-Expressed Gene List in LUAD
Supplementary Table S4. FGA co-expressed gene list in LUAD tumors Symbol R Locus Description FGG 0.919 4q28 fibrinogen gamma chain FGL1 0.635 8p22 fibrinogen-like 1 SLC7A2 0.536 8p22 solute carrier family 7 (cationic amino acid transporter, y+ system), member 2 DUSP4 0.521 8p12-p11 dual specificity phosphatase 4 HAL 0.51 12q22-q24.1histidine ammonia-lyase PDE4D 0.499 5q12 phosphodiesterase 4D, cAMP-specific FURIN 0.497 15q26.1 furin (paired basic amino acid cleaving enzyme) CPS1 0.49 2q35 carbamoyl-phosphate synthase 1, mitochondrial TESC 0.478 12q24.22 tescalcin INHA 0.465 2q35 inhibin, alpha S100P 0.461 4p16 S100 calcium binding protein P VPS37A 0.447 8p22 vacuolar protein sorting 37 homolog A (S. cerevisiae) SLC16A14 0.447 2q36.3 solute carrier family 16, member 14 PPARGC1A 0.443 4p15.1 peroxisome proliferator-activated receptor gamma, coactivator 1 alpha SIK1 0.435 21q22.3 salt-inducible kinase 1 IRS2 0.434 13q34 insulin receptor substrate 2 RND1 0.433 12q12 Rho family GTPase 1 HGD 0.433 3q13.33 homogentisate 1,2-dioxygenase PTP4A1 0.432 6q12 protein tyrosine phosphatase type IVA, member 1 C8orf4 0.428 8p11.2 chromosome 8 open reading frame 4 DDC 0.427 7p12.2 dopa decarboxylase (aromatic L-amino acid decarboxylase) TACC2 0.427 10q26 transforming, acidic coiled-coil containing protein 2 MUC13 0.422 3q21.2 mucin 13, cell surface associated C5 0.412 9q33-q34 complement component 5 NR4A2 0.412 2q22-q23 nuclear receptor subfamily 4, group A, member 2 EYS 0.411 6q12 eyes shut homolog (Drosophila) GPX2 0.406 14q24.1 glutathione peroxidase -
Official Symbol Accession Alias / Previous Symbol Official Full Name
Official Symbol Accession Alias / Previous Symbol Official Full Name Abcc3 NM_029600.3 1700019L09Rik,MRP3,RIKEN cDNA 1700019L09 gene ATP-binding cassette, sub-family C (CFTR/MRP), member 3 Abcc8 NM_011510.3 D930031B21Rik,MGD-MRK-33673,MGI:105993,MGI:3036285,RIKEN cDNA D930031B21ATP-binding gene,sulfonylurea cassette, sub-familyreceptor,Sur,SUR1 C (CFTR/MRP), member 8 Abl1 NM_009594.4 AI325092,c-Abl,E430008G22Rik,expressed sequence AI325092,MGD-MRK-1015,MGI:2138905,MGI:2443781,RIKENc-abl oncogene 1, non-receptor cDNAtyrosine E430008G22 kinase gene Adamts16 NM_172053.2 MGC:37086 a disintegrin-like and metallopeptidase (reprolysin type) with thrombospondin type 1 motif, 16 Ago4 NM_153177.3 5730550L01Rik,AI481660,argonaute 4,Eif2c4,eukaryotic translation initiation factorargonaute 2C, 4,expressed RISC catalytic sequence subunit AI481660,MGI:2140312,RIKEN 4 cDNA 5730550L01 gene Agt NM_007428.3 AI265500,angiotensin precursor,Aogen,expressed sequence AI265500,MGD-MRK-1192,MGI:2142488,Serpina8angiotensinogen (serpin peptidase inhibitor, clade A, member 8) AI464131 NM_001085515.2 AA408153,AI604836,expressed sequence AA408153,expressed sequence expressedexpressed sequence sequence AI604836,gene AI464131 model 762, (NCBI),Gm762,MGI:2140126,MGI:2140342,MGI:2685608,NET37 Ak1 NM_001198790.1 Ak-1,B430205N08Rik,MGD-MRK-1240,MGD-MRK-1244,MGI:2445070,RIKEN cDNA B430205N08adenylate kinase gene 1 Akt1 NM_001165894.1 Akt,MGD-MRK-1257,PKB,PKB/Akt,PKBalpha thymoma viral proto-oncogene 1 Akt2 NM_001110208.1 2410016A19Rik,AW554154,expressed sequence AW554154,MGD-MRK-28173,MGI:1923730,MGI:2142261,PKB,PKBbeta,RIKENthymoma -
Supplementary Materials
Supplementary materials Supplementary Table S1: MGNC compound library Ingredien Molecule Caco- Mol ID MW AlogP OB (%) BBB DL FASA- HL t Name Name 2 shengdi MOL012254 campesterol 400.8 7.63 37.58 1.34 0.98 0.7 0.21 20.2 shengdi MOL000519 coniferin 314.4 3.16 31.11 0.42 -0.2 0.3 0.27 74.6 beta- shengdi MOL000359 414.8 8.08 36.91 1.32 0.99 0.8 0.23 20.2 sitosterol pachymic shengdi MOL000289 528.9 6.54 33.63 0.1 -0.6 0.8 0 9.27 acid Poricoic acid shengdi MOL000291 484.7 5.64 30.52 -0.08 -0.9 0.8 0 8.67 B Chrysanthem shengdi MOL004492 585 8.24 38.72 0.51 -1 0.6 0.3 17.5 axanthin 20- shengdi MOL011455 Hexadecano 418.6 1.91 32.7 -0.24 -0.4 0.7 0.29 104 ylingenol huanglian MOL001454 berberine 336.4 3.45 36.86 1.24 0.57 0.8 0.19 6.57 huanglian MOL013352 Obacunone 454.6 2.68 43.29 0.01 -0.4 0.8 0.31 -13 huanglian MOL002894 berberrubine 322.4 3.2 35.74 1.07 0.17 0.7 0.24 6.46 huanglian MOL002897 epiberberine 336.4 3.45 43.09 1.17 0.4 0.8 0.19 6.1 huanglian MOL002903 (R)-Canadine 339.4 3.4 55.37 1.04 0.57 0.8 0.2 6.41 huanglian MOL002904 Berlambine 351.4 2.49 36.68 0.97 0.17 0.8 0.28 7.33 Corchorosid huanglian MOL002907 404.6 1.34 105 -0.91 -1.3 0.8 0.29 6.68 e A_qt Magnogrand huanglian MOL000622 266.4 1.18 63.71 0.02 -0.2 0.2 0.3 3.17 iolide huanglian MOL000762 Palmidin A 510.5 4.52 35.36 -0.38 -1.5 0.7 0.39 33.2 huanglian MOL000785 palmatine 352.4 3.65 64.6 1.33 0.37 0.7 0.13 2.25 huanglian MOL000098 quercetin 302.3 1.5 46.43 0.05 -0.8 0.3 0.38 14.4 huanglian MOL001458 coptisine 320.3 3.25 30.67 1.21 0.32 0.9 0.26 9.33 huanglian MOL002668 Worenine -
Agonist and Antagonist of Retinoic Acid Receptors Cause Similar Changes in Gene Expression and Induce Senescence-Like Growth Arrest in MCF-7 Breast Carcinoma Cells
Research Article Agonist and Antagonist of Retinoic Acid Receptors Cause Similar Changes in Gene Expression and Induce Senescence-like Growth Arrest in MCF-7 Breast Carcinoma Cells Yuhong Chen,1 Milos Dokmanovic,1 Wilfred D. Stein,1,2 Robert J. Ardecky,3 and Igor B. Roninson1 1Cancer Center, Ordway Research Institute, Albany, New York; 2Institute of Life Sciences, Hebrew University, Jerusalem, Israel; and 3Ligand Pharmaceuticals, Inc., San Diego, California Abstract retinoids is most often attributed to the induction of differentia- Biological effects of retinoids are mediated via retinoic acid tion, but these compounds were also shown to stop the growth of (RA) receptors (RAR) and retinoid X receptors (RXR). The tumor cells by inducing apoptosis or accelerated senescence (1, 2). best-characterized mechanism of retinoid action is stimula- In particular, treatment of two human breast carcinoma cell lines tion of transcription from promoters containing RA response with all-trans retinoic acid (RA) or fenretinide, in vitro or in vivo, elements (RARE). Retinoids induce senescence-like growth induces a senescence-like phenotype characterized by increased h arrest in MCF-7 breast carcinoma cells; this effect is cell size and expression of senescence-associated -galactosidase h associated with the induction of several growth-inhibitory (SA- -gal; refs. 3, 4). This phenotype, as investigated in MCF-7 cells, genes. We have nowfound that these genes are induced by is associated with irreversible growth arrest and up-regulation of RAR-specific but not by RXR-specific ligands. Genome-scale several intracellular and secreted proteins with known growth- microarray analysis of gene expression was used to compare inhibitory activities. -
Gene Ontology Functional Annotations and Pleiotropy
Network based analysis of genetic disease associations Sarah Gilman Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy under the Executive Committee of the Graduate School of Arts and Sciences COLUMBIA UNIVERSITY 2014 © 2013 Sarah Gilman All Rights Reserved ABSTRACT Network based analysis of genetic disease associations Sarah Gilman Despite extensive efforts and many promising early findings, genome-wide association studies have explained only a small fraction of the genetic factors contributing to common human diseases. There are many theories about where this “missing heritability” might lie, but increasingly the prevailing view is that common variants, the target of GWAS, are not solely responsible for susceptibility to common diseases and a substantial portion of human disease risk will be found among rare variants. Relatively new, such variants have not been subject to purifying selection, and therefore may be particularly pertinent for neuropsychiatric disorders and other diseases with greatly reduced fecundity. Recently, several researchers have made great progress towards uncovering the genetics behind autism and schizophrenia. By sequencing families, they have found hundreds of de novo variants occurring only in affected individuals, both large structural copy number variants and single nucleotide variants. Despite studying large cohorts there has been little recurrence among the genes implicated suggesting that many hundreds of genes may underlie these complex phenotypes. The question -
Rna-Sequencing Applications: Gene Expression Quantification and Methylator Phenotype Identification
The Texas Medical Center Library DigitalCommons@TMC The University of Texas MD Anderson Cancer Center UTHealth Graduate School of The University of Texas MD Anderson Cancer Biomedical Sciences Dissertations and Theses Center UTHealth Graduate School of (Open Access) Biomedical Sciences 8-2013 RNA-SEQUENCING APPLICATIONS: GENE EXPRESSION QUANTIFICATION AND METHYLATOR PHENOTYPE IDENTIFICATION Guoshuai Cai Follow this and additional works at: https://digitalcommons.library.tmc.edu/utgsbs_dissertations Part of the Bioinformatics Commons, Computational Biology Commons, and the Medicine and Health Sciences Commons Recommended Citation Cai, Guoshuai, "RNA-SEQUENCING APPLICATIONS: GENE EXPRESSION QUANTIFICATION AND METHYLATOR PHENOTYPE IDENTIFICATION" (2013). The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences Dissertations and Theses (Open Access). 386. https://digitalcommons.library.tmc.edu/utgsbs_dissertations/386 This Dissertation (PhD) is brought to you for free and open access by the The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences at DigitalCommons@TMC. It has been accepted for inclusion in The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences Dissertations and Theses (Open Access) by an authorized administrator of DigitalCommons@TMC. For more information, please contact [email protected]. RNA-SEQUENCING APPLICATIONS: GENE EXPRESSION QUANTIFICATION AND METHYLATOR PHENOTYPE IDENTIFICATION