Bivalent Domains Enforce Transcriptional Memory of DNA Methylated Genes in Cancer Cells
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Prioritization and Evaluation of Depression Candidate Genes by Combining Multidimensional Data Resources
Prioritization and Evaluation of Depression Candidate Genes by Combining Multidimensional Data Resources Chung-Feng Kao1, Yu-Sheng Fang2, Zhongming Zhao3, Po-Hsiu Kuo1,2,4* 1 Department of Public Health and Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan, 2 Institute of Clinical Medicine, School of Medicine, National Cheng-Kung University, Tainan, Taiwan, 3 Departments of Biomedical Informatics and Psychiatry, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America, 4 Research Center for Genes, Environment and Human Health, National Taiwan University, Taipei, Taiwan Abstract Background: Large scale and individual genetic studies have suggested numerous susceptible genes for depression in the past decade without conclusive results. There is a strong need to review and integrate multi-dimensional data for follow up validation. The present study aimed to apply prioritization procedures to build-up an evidence-based candidate genes dataset for depression. Methods: Depression candidate genes were collected in human and animal studies across various data resources. Each gene was scored according to its magnitude of evidence related to depression and was multiplied by a source-specific weight to form a combined score measure. All genes were evaluated through a prioritization system to obtain an optimal weight matrix to rank their relative importance with depression using the combined scores. The resulting candidate gene list for depression (DEPgenes) was further evaluated by a genome-wide association (GWA) dataset and microarray gene expression in human tissues. Results: A total of 5,055 candidate genes (4,850 genes from human and 387 genes from animal studies with 182 being overlapped) were included from seven data sources. -
Transcriptional Regulation of RKIP in Prostate Cancer Progression
Health Science Campus FINAL APPROVAL OF DISSERTATION Doctor of Philosophy in Biomedical Sciences Transcriptional Regulation of RKIP in Prostate Cancer Progression Submitted by: Sandra Marie Beach In partial fulfillment of the requirements for the degree of Doctor of Philosophy in Biomedical Sciences Examination Committee Major Advisor: Kam Yeung, Ph.D. Academic William Maltese, Ph.D. Advisory Committee: Sonia Najjar, Ph.D. Han-Fei Ding, M.D., Ph.D. Manohar Ratnam, Ph.D. Senior Associate Dean College of Graduate Studies Michael S. Bisesi, Ph.D. Date of Defense: May 16, 2007 Transcriptional Regulation of RKIP in Prostate Cancer Progression Sandra Beach University of Toledo ACKNOWLDEGMENTS I thank my major advisor, Dr. Kam Yeung, for the opportunity to pursue my degree in his laboratory. I am also indebted to my advisory committee members past and present, Drs. Sonia Najjar, Han-Fei Ding, Manohar Ratnam, James Trempe, and Douglas Pittman for generously and judiciously guiding my studies and sharing reagents and equipment. I owe extended thanks to Dr. William Maltese as a committee member and chairman of my department for supporting my degree progress. The entire Department of Biochemistry and Cancer Biology has been most kind and helpful to me. Drs. Roy Collaco and Hong-Juan Cui have shared their excellent technical and practical advice with me throughout my studies. I thank members of the Yeung laboratory, Dr. Sungdae Park, Hui Hui Tang, Miranda Yeung for their support and collegiality. The data mining studies herein would not have been possible without the helpful advice of Dr. Robert Trumbly. I am also grateful for the exceptional assistance and shared microarray data of Dr. -
Learning from Cadherin Structures and Sequences: Affinity Determinants and Protein Architecture
Learning from cadherin structures and sequences: affinity determinants and protein architecture Klára Fels ıvályi Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Graduate School of Arts and Sciences COLUMBIA UNIVERSITY 2014 © 2014 Klara Felsovalyi All rights reserved ABSTRACT Learning from cadherin structures and sequences: affinity determinants and protein architecture Klara Felsovalyi Cadherins are a family of cell-surface proteins mediating adhesion that are important in development and maintenance of tissues. The family is defined by the repeating cadherin domain (EC) in their extracellular region, but they are diverse in terms of protein size, architecture and cellular function. The best-understood subfamily is the type I classical cadherins, which are found in vertebrates and have five EC domains. Among the five different type I classical cadherins, the binding interactions are highly specific in their homo- and heterophilic binding affinities, though their sequences are very similar. As previously shown, E- and N-cadherins, two prototypic members of the subfamily, differ in their homophilic K D by about an order of magnitude, while their heterophilic affinity is intermediate. To examine the source of the binding affinity differences among type I cadherins, we used crystal structures, analytical ultracentrifugation (AUC), surface plasmon resonance (SPR), and electron paramagnetic resonance (EPR) studies. Phylogenetic analysis and binding affinity behavior show that the type I cadherins can be further divided into two subgroups, with E- and N-cadherin representing each. In addition to the affinity differences in their wild-type binding through the strand-swapped interface, a second interface also shows an affinity difference between E- and N-cadherin. -
Identification of Potential Key Genes and Pathway Linked with Sporadic Creutzfeldt-Jakob Disease Based on Integrated Bioinformatics Analyses
medRxiv preprint doi: https://doi.org/10.1101/2020.12.21.20248688; this version posted December 24, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission. Identification of potential key genes and pathway linked with sporadic Creutzfeldt-Jakob disease based on integrated bioinformatics analyses Basavaraj Vastrad1, Chanabasayya Vastrad*2 , Iranna Kotturshetti 1. Department of Biochemistry, Basaveshwar College of Pharmacy, Gadag, Karnataka 582103, India. 2. Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karanataka, India. 3. Department of Ayurveda, Rajiv Gandhi Education Society`s Ayurvedic Medical College, Ron, Karnataka 562209, India. * Chanabasayya Vastrad [email protected] Ph: +919480073398 Chanabasava Nilaya, Bharthinagar, Dharwad 580001 , Karanataka, India NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice. medRxiv preprint doi: https://doi.org/10.1101/2020.12.21.20248688; this version posted December 24, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission. Abstract Sporadic Creutzfeldt-Jakob disease (sCJD) is neurodegenerative disease also called prion disease linked with poor prognosis. The aim of the current study was to illuminate the underlying molecular mechanisms of sCJD. The mRNA microarray dataset GSE124571 was downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were screened. -
Convergent Functional Genomics of Schizophrenia: from Comprehensive Understanding to Genetic Risk Prediction
Molecular Psychiatry (2012) 17, 887 -- 905 & 2012 Macmillan Publishers Limited All rights reserved 1359-4184/12 www.nature.com/mp IMMEDIATE COMMUNICATION Convergent functional genomics of schizophrenia: from comprehensive understanding to genetic risk prediction M Ayalew1,2,9, H Le-Niculescu1,9, DF Levey1, N Jain1, B Changala1, SD Patel1, E Winiger1, A Breier1, A Shekhar1, R Amdur3, D Koller4, JI Nurnberger1, A Corvin5, M Geyer6, MT Tsuang6, D Salomon7, NJ Schork7, AH Fanous3, MC O’Donovan8 and AB Niculescu1,2 We have used a translational convergent functional genomics (CFG) approach to identify and prioritize genes involved in schizophrenia, by gene-level integration of genome-wide association study data with other genetic and gene expression studies in humans and animal models. Using this polyevidence scoring and pathway analyses, we identify top genes (DISC1, TCF4, MBP, MOBP, NCAM1, NRCAM, NDUFV2, RAB18, as well as ADCYAP1, BDNF, CNR1, COMT, DRD2, DTNBP1, GAD1, GRIA1, GRIN2B, HTR2A, NRG1, RELN, SNAP-25, TNIK), brain development, myelination, cell adhesion, glutamate receptor signaling, G-protein-- coupled receptor signaling and cAMP-mediated signaling as key to pathophysiology and as targets for therapeutic intervention. Overall, the data are consistent with a model of disrupted connectivity in schizophrenia, resulting from the effects of neurodevelopmental environmental stress on a background of genetic vulnerability. In addition, we show how the top candidate genes identified by CFG can be used to generate a genetic risk prediction score (GRPS) to aid schizophrenia diagnostics, with predictive ability in independent cohorts. The GRPS also differentiates classic age of onset schizophrenia from early onset and late-onset disease. -
Gene-Based and Pathway-Based Genome-Wide Association Study of Alcohol Dependence
• 111 • Shanghai Archives of Psychiatry, 2015, Vol. 27, No. 2 •Original research article• Gene-based and pathway-based genome-wide association study of alcohol dependence Lingjun ZUO1, Clarence K. ZHANG2,3*, Frederick G. SAYWARD4,5, Kei-Hoi CHEUNG4, Kesheng WANG6, John H. KRYSTAL1, Hongyu ZHAO2, Xingguang LUO1* Background: The organization of risk genes within signaling pathways may provide clues about the converging neurobiological effects of risk genes for alcohol dependence. Aims: Identify risk genes and risk gene pathways for alcohol dependence. Methods: We conducted a pathway-based genome-wide association study (GWAS) of alcohol dependence using a gene-set-rich analytic approach. Approximately one million genetic markers were tested in the discovery sample which included 1409 European-American (EA) alcohol dependent individuals and 1518 EA healthy comparison subjects. An additional 681 African-American (AA) cases and 508 AA healthy subjects served as the replication sample. Results: We identified several genome-wide replicable risk genes and risk pathways that were significantly associated with alcohol dependence. After applying the Bonferroni correction for multiple testing, the ‘cell- extracellular matrix interactions’ pathway (p<2.0E-4 in EAs) and the PXN gene (which encodes paxillin) (p=3.9E-7 in EAs) within this pathway were the most promising risk factors for alcohol dependence. There were also two nominally replicable pathways enriched in alcohol dependence-related genes in both EAs (0.015≤p≤0.035) and AAs (0.025≤p≤0.050): the ‘Na+/Cl- dependent neurotransmitter transporters’ pathway and the ‘other glycan degradation’ pathway. Conclusions: These findings provide new evidence highlighting several genes and biological signaling processes that may be related to the risk for alcohol dependence. -
Comparative Transcriptome Profiling of the Human and Mouse Dorsal Root Ganglia: an RNA-Seq-Based Resource for Pain and Sensory Neuroscience Research
bioRxiv preprint doi: https://doi.org/10.1101/165431; this version posted October 13, 2017. 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. Title: Comparative transcriptome profiling of the human and mouse dorsal root ganglia: An RNA-seq-based resource for pain and sensory neuroscience research Short Title: Human and mouse DRG comparative transcriptomics Pradipta Ray 1, 2 #, Andrew Torck 1 , Lilyana Quigley 1, Andi Wangzhou 1, Matthew Neiman 1, Chandranshu Rao 1, Tiffany Lam 1, Ji-Young Kim 1, Tae Hoon Kim 2, Michael Q. Zhang 2, Gregory Dussor 1 and Theodore J. Price 1, # 1 The University of Texas at Dallas, School of Behavioral and Brain Sciences 2 The University of Texas at Dallas, Department of Biological Sciences # Corresponding authors Theodore J Price Pradipta Ray School of Behavioral and Brain Sciences School of Behavioral and Brain Sciences The University of Texas at Dallas The University of Texas at Dallas BSB 14.102G BSB 10.608 800 W Campbell Rd 800 W Campbell Rd Richardson TX 75080 Richardson TX 75080 972-883-4311 972-883-7262 [email protected] [email protected] Number of pages: 27 Number of figures: 9 Number of tables: 8 Supplementary Figures: 4 Supplementary Files: 6 Word count: Abstract = 219; Introduction = 457; Discussion = 1094 Conflict of interest: The authors declare no conflicts of interest Patient anonymity and informed consent: Informed consent for human tissue sources were obtained by Anabios, Inc. (San Diego, CA). Human studies: This work was approved by The University of Texas at Dallas Institutional Review Board (MR 15-237). -
HHS Public Access Author Manuscript
HHS Public Access Author manuscript Author Manuscript Author ManuscriptNat Genet Author Manuscript. Author manuscript; Author Manuscript available in PMC 2012 September 01. Published in final edited form as: Nat Genet. ; 44(3): 260–268. doi:10.1038/ng.1051. Meta-analyses identify 13 novel loci associated with age at menopause and highlights DNA repair and immune pathways A full list of authors and affiliations appears at the end of the article. Abstract To identify novel loci for age at natural menopause, we performed a meta-analysis of 22 genome- wide association studies in 38,968 women of European descent, with replication in up to 14,435 women. In addition to four known loci, we identified 13 new age at natural menopause loci (P < 5 × 10−8). The new loci included genes implicated in DNA repair (EXO1, HELQ, UIMC1, FAM175A, FANCI, TLK1, POLG, PRIM1) and immune function (IL11, NLRP11, BAT2). Gene-set Users may view, print, copy, download and text and data- mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#terms Corresponding authors: Anna Murray, Peninsula Medical School, St Lukes, Magdalen Road, Exeter, EX1 2LU, UK, [email protected]. Kathryn L Lunetta, Department of Biostatistics, Boston University School of Public Health, 801 Mass Avenue, Crosstown Center, CT313, Boston, MA 02118, [email protected]. *These authors contributed jointly to this work #These senior authors jointly oversaw this work URLS: GWAS catalog: www.genome.gov/gwastudies/, SCAN: scan.bsd.uchicago.edu. -
Towards Personalized Medicine in Psychiatry: Focus on Suicide
TOWARDS PERSONALIZED MEDICINE IN PSYCHIATRY: FOCUS ON SUICIDE Daniel F. Levey Submitted to the faculty of the University Graduate School in partial fulfillment of the requirements for the degree Doctor of Philosophy in the Program of Medical Neuroscience, Indiana University April 2017 ii Accepted by the Graduate Faculty, Indiana University, in partial fulfillment of the requirements for the degree of Doctor of Philosophy. Andrew J. Saykin, Psy. D. - Chair ___________________________ Alan F. Breier, M.D. Doctoral Committee Gerry S. Oxford, Ph.D. December 13, 2016 Anantha Shekhar, M.D., Ph.D. Alexander B. Niculescu III, M.D., Ph.D. iii Dedication This work is dedicated to all those who suffer, whether their pain is physical or psychological. iv Acknowledgements The work I have done over the last several years would not have been possible without the contributions of many people. I first need to thank my terrific mentor and PI, Dr. Alexander Niculescu. He has continuously given me advice and opportunities over the years even as he has suffered through my many mistakes, and I greatly appreciate his patience. The incredible passion he brings to his work every single day has been inspirational. It has been an at times painful but often exhilarating 5 years. I need to thank Helen Le-Niculescu for being a wonderful colleague and mentor. I learned a lot about organization and presentation working alongside her, and her tireless work ethic was an excellent example for a new graduate student. I had the pleasure of working with a number of great people over the years. Mikias Ayalew showed me the ropes of the lab and began my understanding of the power of algorithms. -
Stress Susceptibility-Specific Phenotype Associated with Different
Lisowski et al. BMC Neuroscience 2013, 14:144 http://www.biomedcentral.com/1471-2202/14/144 RESEARCH ARTICLE Open Access Stress susceptibility-specific phenotype associated with different hippocampal transcriptomic responses to chronic tricyclic antidepressant treatment in mice Pawel Lisowski1*, Grzegorz R Juszczak2, Joanna Goscik3, Adrian M Stankiewicz2, Marek Wieczorek4, Lech Zwierzchowski1 and Artur H Swiergiel5,6 Abstract Background: The effects of chronic treatment with tricyclic antidepressant (desipramine, DMI) on the hippocampal transcriptome in mice displaying high and low swim stress-induced analgesia (HA and LA lines) were studied. These mice displayed different depression-like behavioral responses to DMI: stress-sensitive HA animals responded to DMI, while LA animals did not. Results: To investigate the effects of DMI treatment on gene expression profiling, whole-genome Illumina Expres- sion BeadChip arrays and qPCR were used. Total RNA isolated from hippocampi was used. Expression profiling was then performed and data were analyzed bioinformatically to assess the influence of stress susceptibility-specific phe- notypes on hippocampal transcriptomic responses to chronic DMI. DMI treatment affected the expression of 71 genes in HA mice and 41 genes in LA mice. We observed the upregulation of Igf2 and the genes involved in neuro- genesis (HA: Sema3f, Ntng1, Gbx2, Efna5, and Rora; LA: Otx2, Rarb, and Drd1a) in both mouse lines. In HA mice, we observed the upregulation of genes involved in neurotransmitter transport, the termination of GABA and glycine ac- tivity (Slc6a11, Slc6a9), glutamate uptake (Slc17a6), and the downregulation of neuropeptide Y (Npy) and cortico- tropin releasing hormone-binding protein (Crhbp). In LA mice, we also observed the upregulation of other genes involved in neuroprotection (Ttr, Igfbp2, Prlr) and the downregulation of genes involved in calcium signaling and ion binding (Adcy1, Cckbr, Myl4, Slu7, Scrp1, Zfp330). -
Modification of Cognitive Performance in Schizophrenia by Complexin 2 Gene Polymorphisms
Supplementary Online Content Begemann M, Grube S, Papiol S, Malzahn D, Krampe H, Ribbe K, Friedrichs H, Radyushkin KA, El-Kordi A, Benseler F, Hannke K, Sperling S, Schwerdtfeger D, Thanhäuser I, Gerchen MF, Ghorbani M, Gutwinski S, Hilmes C, Leppert R, Ronnenberg A, Sowislo J, Stawicki S, Stödtke M, Szuszies C, Reim K, Riggert J, Eckstein F, Falkai P, Bickeböller H, Nave K-A, Brose N, Ehrenreich H. Modification of cognitive performance in schizophrenia by complexin 2 gene polymorphisms. Arch Gen Psychiatry. 2010;67(9):879-888. eAppendix. Collaborating Centers eMethods. Supplementary Methods Description eTable 1. Allele-Specific Melting Temperatures for Simple Probe Assays eTable 2. Characteristics of Analyzed SNPs eTable 3. Point Mutations Detected in the Sequenced Region of CPLX2 eTable 4. Frequencies of Single SNP Analysis (Case-Control) eTable 5. Pairwise Association Test on Cognitive Measures of Schizophrenic Patients eTable 6. Multilocus Association Analysis for CPLX2 eTable 7. Association Analysis of CPLX2, Testing the Effect of One Regional Variant (CTC Haplotype in CPLX2 Haploblocks 2 & 3) Adjusted for All Other Associated CPLX2 Regions eTable 8. Species Conservation eFigure 1. Influence of CPLX2 Genotypes on Cognitive Measures of Schizophrenic Patients eFigure 2. Conservation Status of the CPLX2 Gene Across 28 Species eReferences. Bibliography for the Supplementary Methods Section This supplementary material has been provided by the authors to give readers additional information about their work. © 2010 American Medical Association. All rights reserved. Downloaded From: https://jamanetwork.com/ on 09/29/2021 eAppendix. Collaborating Centers © 2010 American Medical Association. All rights reserved. Downloaded From: https://jamanetwork.com/ on 09/29/2021 No. -
NIH Public Access Author Manuscript Nat Genet
NIH Public Access Author Manuscript Nat Genet. Author manuscript; available in PMC 2012 September 01. NIH-PA Author ManuscriptPublished NIH-PA Author Manuscript in final edited NIH-PA Author Manuscript form as: Nat Genet. ; 44(3): 260–268. doi:10.1038/ng.1051. Meta-analyses identify 13 novel loci associated with age at menopause and highlights DNA repair and immune pathways Lisette Stolk1,2,*, John RB Perry3,4,*, Daniel I Chasman5,6, Chunyan He7,8, Massimo Mangino9, Patrick Sulem10, Maja Barbalic11, Linda Broer12, Enda M Byrne13, Florian Ernst14, Tõnu Esko15,16,17, Nora Franceschini18, Daniel F Gudbjartsson10, Jouke-Jan Hottenga19, Peter Kraft20,21, Patick F McArdle22, Eleonora Porcu23, So-Youn Shin24, Albert V Smith25,26, Sophie van Wingerden12, Guangju Zhai9,27, Wei V Zhuang28, Eva Albrecht29, Behrooz Z Alizadeh30, Thor Aspelund25,26, Stefania Bandinelli31, Lovorka Barac Lauc32, Jacques S Beckmann33,34, Mladen Boban35, Eric Boerwinkle11, Frank J Broekmans36, Andrea Burri9, Harry Campbell37, Stephen J Chanock38, Constance Chen20,39, Marilyn C Cornelis39, Tanguy Corre40, Andrea D Coviello41,42, Pio d’Adamo43,44, Gail Davies45, Ulf de Faire46, Eco JC de Geus19,47, Ian J Deary45,48, George VZ Dedoussis49, Panagiotis Deloukas24, Shah Ebrahim50, Gudny Eiriksdottir25, Valur Emilsson25, Johan G Corresponding authors: Anna Murray, Peninsula Medical School, St Lukes, Magdalen Road, Exeter, EX1 2LU, UK, [email protected]. Kathryn L Lunetta, Department of Biostatistics, Boston University School of Public Health, 801 Mass Avenue, Crosstown Center, CT313, Boston, MA 02118, [email protected]. *These authors contributed jointly to this work #These senior authors jointly oversaw this work URLS: GWAS catalog: www.genome.gov/gwastudies/, SCAN: scan.bsd.uchicago.edu.