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ERK Phosphorylation of MED14 in Promoter Complexes During Mitogen-Induced Gene Activation by Elk-1 Matthew D
Published online 17 September 2013 Nucleic Acids Research, 2013, Vol. 41, No. 22 10241–10253 doi:10.1093/nar/gkt837 ERK phosphorylation of MED14 in promoter complexes during mitogen-induced gene activation by Elk-1 Matthew D. Galbraith1,2, Janice Saxton1,LiLi1, Samuel J. Shelton1,3, Hongmei Zhang1,4, Joaquin M. Espinosa2 and Peter E. Shaw1,* 1School of Biomedical Sciences, University of Nottingham, Queen’s Medical Centre, Nottingham, NG7 2UH, UK, 2Department of Molecular, Cellular and Developmental Biology, Howard Hughes Medical Institute, University of Colorado at Boulder, Boulder, CO 80309, USA, 3Department of Neurology, Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, CA 90089, USA and 4Department of Pharmacology, Ningxia Medical University, Yinchuan 750004, China Received March 22, 2013; Revised August 21, 2013; Accepted August 28, 2013 ABSTRACT INTRODUCTION The ETS domain transcription factor Elk-1 stimu- The specific and temporal co-ordination of gene expres- lates expression of immediate early genes (IEGs) in sion is a fundamental process of cell-based life with response to mitogens. These events require phos- patterns of gene expression controlling proliferation, dif- phorylation of Elk-1 by extracellular signal-regulated ferentiation and cell death. Immediate early gene (IEG) expression has revealed how crucial regulatory events kinase (ERK) and phosphorylation-dependent inter- revolve around the interface between pathway-specific action of Elk-1 with co-activators, including histone transcription factors and components of the transcription acetyltransferases and the Mediator complex. Elk-1 machinery, involving a plethora of protein interactions also recruits ERK to the promoters of its target and modifications (1,2). -
Variation in Protein Coding Genes Identifies Information
bioRxiv preprint doi: https://doi.org/10.1101/679456; this version posted June 21, 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 The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.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-NC-ND 4.0 International license. Animal complexity and information flow 1 1 2 3 4 5 Variation in protein coding genes identifies information flow as a contributor to 6 animal complexity 7 8 Jack Dean, Daniela Lopes Cardoso and Colin Sharpe* 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Institute of Biological and Biomedical Sciences 25 School of Biological Science 26 University of Portsmouth, 27 Portsmouth, UK 28 PO16 7YH 29 30 * Author for correspondence 31 [email protected] 32 33 Orcid numbers: 34 DLC: 0000-0003-2683-1745 35 CS: 0000-0002-5022-0840 36 37 38 39 40 41 42 43 44 45 46 47 48 49 Abstract bioRxiv preprint doi: https://doi.org/10.1101/679456; this version posted June 21, 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-NC-ND 4.0 International license. Animal complexity and information flow 2 1 Across the metazoans there is a trend towards greater organismal complexity. How 2 complexity is generated, however, is uncertain. Since C.elegans and humans have 3 approximately the same number of genes, the explanation will depend on how genes are 4 used, rather than their absolute number. -
Genome-Wide DNA Methylation Map of Human Neutrophils Reveals Widespread Inter-Individual Epigenetic Variation
www.nature.com/scientificreports OPEN Genome-wide DNA methylation map of human neutrophils reveals widespread inter-individual Received: 15 June 2015 Accepted: 29 October 2015 epigenetic variation Published: 27 November 2015 Aniruddha Chatterjee1,2, Peter A. Stockwell3, Euan J. Rodger1, Elizabeth J. Duncan2,4, Matthew F. Parry5, Robert J. Weeks1 & Ian M. Morison1,2 The extent of variation in DNA methylation patterns in healthy individuals is not yet well documented. Identification of inter-individual epigenetic variation is important for understanding phenotypic variation and disease susceptibility. Using neutrophils from a cohort of healthy individuals, we generated base-resolution DNA methylation maps to document inter-individual epigenetic variation. We identified 12851 autosomal inter-individual variably methylated fragments (iVMFs). Gene promoters were the least variable, whereas gene body and upstream regions showed higher variation in DNA methylation. The iVMFs were relatively enriched in repetitive elements compared to non-iVMFs, and were associated with genome regulation and chromatin function elements. Further, variably methylated genes were disproportionately associated with regulation of transcription, responsive function and signal transduction pathways. Transcriptome analysis indicates that iVMF methylation at differentially expressed exons has a positive correlation and local effect on the inclusion of that exon in the mRNA transcript. Methylation of DNA is a mechanism for regulating gene function in all vertebrates. It has a role in gene silencing, tissue differentiation, genomic imprinting, chromosome X inactivation, phenotypic plasticity, and disease susceptibility1,2. Aberrant DNA methylation has been implicated in the pathogenesis of sev- eral human diseases, especially cancer3–5. Variation in DNA methylation patterns in healthy individuals has been hypothesised to alter human phenotypes including susceptibility to common diseases6 and response to drug treatments7. -
Med9 (N-17): Sc-243449
SAN TA C RUZ BI OTEC HNOL OG Y, INC . Med9 (N-17): sc-243449 BACKGROUND APPLICATIONS In mammalian cells, transcription is regulated in part by high molecular weight Med9 (N-17) is recommended for detection of Med9 of human origin by co-activating complexes that mediate signals between transcriptional activa - Western Blotting (starting dilution 1:200, dilution range 1:100-1:1000), tors and RNA polymerase II (Pol II). The mediator complex is one such multi- immunoprecipitation [1-2 µg per 100-500 µg of total protein (1 ml of cell protein structure that functions as a bridge between regulatory proteins and lysate)], immunofluorescence (starting dilution 1:50, dilution range 1:50- Pol II, thereby regulating Pol II-dependent transcription. Med9 (mediator com - 1:500) and solid phase ELISA (starting dilution 1:30, dilution range 1:30- plex subunit 9), also known as MED25, is a 146 amino acid nuclear protein 1:3000); non cross-reactive with other Med family members. and component of the mediator complex. Med9 directly interacts with Med4 Suitable for use as control antibody for Med9 siRNA (h): sc-94034, Med9 and is encoded by a gene that maps to human chromosome 17p11.2. Chromo- shRNA Plasmid (h): sc-94034-SH and Med9 shRNA (h) Lentiviral Particles: some 17 comprises over 2.5% of the human genome, encodes over 1,200 sc-94034-V. genes and is associated with two key tumor suppressor genes, namely, p53 and BRCA1. Molecular Weight of Med9: 16 kDa. Positive Controls: HeLa whole cell lysate: sc-2200, K-562 whole cell lysate: REFERENCES sc-2203 or Hep G2 cell lysate: sc-2227. -
FBXL19 Recruits CDK-Mediator to Cpg Islands of Developmental Genes Priming Them for Activation During Lineage Commitment
RESEARCH ARTICLE FBXL19 recruits CDK-Mediator to CpG islands of developmental genes priming them for activation during lineage commitment Emilia Dimitrova1, Takashi Kondo2†, Angelika Feldmann1†, Manabu Nakayama3, Yoko Koseki2, Rebecca Konietzny4‡, Benedikt M Kessler4, Haruhiko Koseki2,5, Robert J Klose1* 1Department of Biochemistry, University of Oxford, Oxford, United Kingdom; 2Laboratory for Developmental Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan; 3Department of Technology Development, Kazusa DNA Research Institute, Kisarazu, Japan; 4Nuffield Department of Medicine, TDI Mass Spectrometry Laboratory, Target Discovery Institute, University of Oxford, Oxford, United Kingdom; 5CREST, Japan Science and Technology Agency, Kawaguchi, Japan Abstract CpG islands are gene regulatory elements associated with the majority of mammalian promoters, yet how they regulate gene expression remains poorly understood. Here, we identify *For correspondence: FBXL19 as a CpG island-binding protein in mouse embryonic stem (ES) cells and show that it [email protected] associates with the CDK-Mediator complex. We discover that FBXL19 recruits CDK-Mediator to †These authors contributed CpG island-associated promoters of non-transcribed developmental genes to prime these genes equally to this work for activation during cell lineage commitment. We further show that recognition of CpG islands by Present address: ‡Agilent FBXL19 is essential for mouse development. Together this reveals a new CpG island-centric Technologies, Waldbronn, mechanism for CDK-Mediator recruitment to developmental gene promoters in ES cells and a Germany requirement for CDK-Mediator in priming these developmental genes for activation during cell lineage commitment. Competing interests: The DOI: https://doi.org/10.7554/eLife.37084.001 authors declare that no competing interests exist. -
Role of the Mediator Complex in Ethanol Tolerance in Yeast
ROLE OF THE MEDIATOR COMPLEX IN ETHANOL TOLERANCE IN YEAST An Undergraduate Research Scholars Thesis by JACKSON VALENCIA Submitted to the Undergraduate Research Scholars program at Texas A&M University in partial fulfillment of the requirements for the designation as an UNDERGRADUATE RESEARCH SCHOLAR Approved by Research Advisor: Dr. William Park May 2018 Major: Biochemistry TABLE OF CONTENTS Page ABSTRACT ............................................................................................................................ 1 ACKNOWLEDGMENTS ........................................................................................................ 2 NOMENCLATURE................................................................................................................. 3 CHAPTER I. INTRODUCTION .................................................................................................. 5 II. MATERIALS & METHODS.................................................................................. 7 Materials ........................................................................................................... 7 Methods ............................................................................................................ 8 III. RESULTS .............................................................................................................14 Ethanol tolerance in Med8138 ± TAP ................................................................14 Growth of constructs in which Med8138-176 was replaced by SBP......................15 -
2014-Platform-Abstracts.Pdf
American Society of Human Genetics 64th Annual Meeting October 18–22, 2014 San Diego, CA PLATFORM ABSTRACTS Abstract Abstract Numbers Numbers Saturday 41 Statistical Methods for Population 5:30pm–6:50pm: Session 2: Plenary Abstracts Based Studies Room 20A #198–#205 Featured Presentation I (4 abstracts) Hall B1 #1–#4 42 Genome Variation and its Impact on Autism and Brain Development Room 20BC #206–#213 Sunday 43 ELSI Issues in Genetics Room 20D #214–#221 1:30pm–3:30pm: Concurrent Platform Session A (12–21): 44 Prenatal, Perinatal, and Reproductive 12 Patterns and Determinants of Genetic Genetics Room 28 #222–#229 Variation: Recombination, Mutation, 45 Advances in Defining the Molecular and Selection Hall B1 Mechanisms of Mendelian Disorders Room 29 #230–#237 #5-#12 13 Genomic Studies of Autism Room 6AB #13–#20 46 Epigenomics of Normal Populations 14 Statistical Methods for Pedigree- and Disease States Room 30 #238–#245 Based Studies Room 6CF #21–#28 15 Prostate Cancer: Expression Tuesday Informing Risk Room 6DE #29–#36 8:00pm–8:25am: 16 Variant Calling: What Makes the 47 Plenary Abstracts Featured Difference? Room 20A #37–#44 Presentation III Hall BI #246 17 New Genes, Incidental Findings and 10:30am–12:30pm:Concurrent Platform Session D (49 – 58): Unexpected Observations Revealed 49 Detailing the Parts List Using by Exome Sequencing Room 20BC #45–#52 Genomic Studies Hall B1 #247–#254 18 Type 2 Diabetes Genetics Room 20D #53–#60 50 Statistical Methods for Multigene, 19 Genomic Methods in Clinical Practice Room 28 #61–#68 Gene Interaction -
Evolution and Diversity of Copy Number Variation in the Great Ape Lineage
Downloaded from genome.cshlp.org on September 24, 2021 - Published by Cold Spring Harbor Laboratory Press Evolution and diversity of copy number variation in the great ape lineage Peter H. Sudmant1, John Huddleston1,7, Claudia R. Catacchio2, Maika Malig1, LaDeana W. Hillier3, Carl Baker1, Kiana Mohajeri1, Ivanela Kondova4, Ronald E. Bontrop4, Stephan Persengiev4, Francesca Antonacci2, Mario Ventura2, Javier Prado-Martinez5, Tomas 5,6 1,7 Marques-Bonet , and Evan E. Eichler 1. Department of Genome Sciences, University of Washington, Seattle, WA, USA 2. University of Bari, Bari, Italy 3. The Genome Institute, Washington University School of Medicine, St. Louis, MO, USA 4. Department of Comparative Genetics, Biomedical Primate Research Centre, Rijswijk, The Netherlands 5. Institut de Biologia Evolutiva, (UPF-CSIC) Barcelona, Spain 6. Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain 7. Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA Correspondence to: Evan Eichler Department of Genome Sciences University of Washington School of Medicine Foege S-413A, Box 355065 3720 15th Ave NE Seattle, WA 98195 E-mail: [email protected] 1 Downloaded from genome.cshlp.org on September 24, 2021 - Published by Cold Spring Harbor Laboratory Press ABSTRACT Copy number variation (CNV) contributes to the genetic basis of disease and has significantly restructured the genomes of humans and great apes. The diversity and rate of this process, however, has not been extensively explored among the great ape lineages. We analyzed 97 deeply sequenced great ape and human genomes and estimate that 16% (469 Mbp) of the hominid genome has been affected by recent copy number changes. -
Maize and Millet Transcription Factors Annotated Using Comparative
Lin et al. BMC Genomics 2014, 15:818 http://www.biomedcentral.com/1471-2164/15/818 RESEARCH ARTICLE Open Access Maize and millet transcription factors annotated using comparative genomic and transcriptomic data Jinn-Jy Lin1,2,3, Chun-Ping Yu4, Yao-Ming Chang3, Sean Chun-Chang Chen3 and Wen-Hsiung Li2,3,4,5* Abstract Background: Transcription factors (TFs) contain DNA-binding domains (DBDs) and regulate gene expression by binding to specific DNA sequences. In addition, there are proteins, called transcription coregulators (TCs), which lack DBDs but can alter gene expression through interaction with TFs or RNA Polymerase II. Therefore, it is interesting to identify and classify the TFs and TCs in a genome. In this study, maize (Zea mays) and foxtail millet (Setaria italica), two important species for the study of C4 photosynthesis and kranz anatomy, were selected. Result: We conducted a comprehensive genome-wide annotation of TFs and TCs in maize B73 and in two strains of foxtail millet, Zhang gu and Yugu1, and classified them into families. To gain additional support for our predictions, we searched for their homologous genes in Arabidopsis or rice and studied their gene expression level using RNA-seq and microarray data. We identified many new TF and TC families in these two species, and described some evolutionary and functional aspects of the 9 new maize TF families. Moreover, we detected many pseudogenes and transposable elements in current databases. In addition, we examined tissue expression preferences of TF and TC families and identified tissue/condition-specific TFs and TCs in maize and millet. -
A Novel Locus for Congenital Simple Microphthalmia Family Mapping to 17P12-Q12
Genetics A Novel Locus for Congenital Simple Microphthalmia Family Mapping to 17p12-q12 Zhengmao Hu,1,2,3 Changhong Yu,3,4,5 Jingzhi Li,1 Yiqiang Wang,4 Deyuan Liu,1 Xinying Xiang,1,2 Wei Su,1 Qian Pan,1 Lixin Xie,*,4 and Kun Xia*,1,2 PURPOSE. To investigate the etiology in a family with autosomal- opia (ϩ7.00 to ϩ13.00 D), a high lens-to-eye volume ratio, and dominant congenital simple microphthalmia of Chinese origin. a high incidence of angle-closure glaucoma after middle age. ETHODS Some normal adnexal elements and eyelids are usually pres- M . A whole-genome scan was performed by using 382 1 microsatellite DNA markers after the exclusion of reported ent. It is also a common symptom in some other ocular candidates linked to microphthalmia. Additional fluorescent abnormalities. Approximately 80% of microphthalmia cases markers were genotyped for fine mapping. To find out the occur as part of syndromes that include other systemic malfor- mations, especially cardiac defects, facial clefts, microcephaly, novel predisposing gene, 14 candidate genes including 2,3 CRYBA1 and NCOR1 were selected to screen for the mutation and hydrocephaly. The reported prevalence of anophthal- mia or microphthalmia at birth is 0.66 of 10,000 around the by the PCR direct-sequencing method. Genome-wide single- 4 nucleotide polymorphism (SNP) genotyping was performed to world and 0.3 of 10,000 in China. find out the pathogenetic copy number variation, as well. Epidemiologic studies have indicated that both heritable and environmental factors cause microphthalmia. Although the RESULTS. -
Algorithms to Integrate Omics Data for Personalized Medicine
ALGORITHMS TO INTEGRATE OMICS DATA FOR PERSONALIZED MEDICINE by MARZIEH AYATI Submitted in partial fulfillment of the requirements For the degree of Doctor of Philosophy Thesis Adviser: Mehmet Koyut¨urk Department of Electrical Engineering and Computer Science CASE WESTERN RESERVE UNIVERSITY August, 2018 Algorithms to Integrate Omics Data for Personalized Medicine Case Western Reserve University Case School of Graduate Studies We hereby approve the thesis1 of MARZIEH AYATI for the degree of Doctor of Philosophy Mehmet Koyut¨urk 03/27/2018 Committee Chair, Adviser Date Department of Electrical Engineering and Computer Science Mark R. Chance 03/27/2018 Committee Member Date Center of Proteomics Soumya Ray 03/27/2018 Committee Member Date Department of Electrical Engineering and Computer Science Vincenzo Liberatore 03/27/2018 Committee Member Date Department of Electrical Engineering and Computer Science 1We certify that written approval has been obtained for any proprietary material contained therein. To the greatest family who I owe my life to Table of Contents List of Tables vi List of Figures viii Acknowledgements xxi Abstract xxiii Abstract xxiii Chapter 1. Introduction1 Chapter 2. Preliminaries6 Complex Diseases6 Protein-Protein Interaction Network6 Genome-Wide Association Studies7 Phosphorylation 10 Biweight midcorrelation 10 Chapter 3. Identification of Disease-Associated Protein Subnetworks 12 Introduction and Background 12 Methods 15 Results and Discussion 27 Conclusion 40 Chapter 4. Population Covering Locus Sets for Risk Assessment in Complex Diseases 43 Introduction and Background 43 iv Methods 47 Results and Discussion 59 Conclusion 75 Chapter 5. Application of Phosphorylation in Precision Medicine 80 Introduction and Background 80 Methods 83 Results 89 Conclusion 107 Chapter 6. -
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BioMed Research International Integrated Analysis of Multiscale Large-Scale Biological Data for Investigating Human Disease 2016 Guest Editors: Tao Huang, Lei Chen, Jiangning Song, Mingyue Zheng, Jialiang Yang, and Zhenguo Zhang Integrated Analysis of Multiscale Large-Scale Biological Data for Investigating Human Disease 2016 BioMed Research International Integrated Analysis of Multiscale Large-Scale Biological Data for Investigating Human Disease 2016 GuestEditors:TaoHuang,LeiChen,JiangningSong, Mingyue Zheng, Jialiang Yang, and Zhenguo Zhang Copyright © 2016 Hindawi Publishing Corporation. All rights reserved. This is a special issue published in “BioMed Research International.” All articles are open access articles distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Contents Integrated Analysis of Multiscale Large-Scale Biological Data for Investigating Human Disease 2016 Tao Huang, Lei Chen, Jiangning Song, Mingyue Zheng, Jialiang Yang, and Zhenguo Zhang Volume 2016, Article ID 6585069, 2 pages New Trends of Digital Data Storage in DNA Pavani Yashodha De Silva and Gamage Upeksha Ganegoda Volume 2016, Article ID 8072463, 14 pages Analyzing the miRNA-Gene Networks to Mine the Important miRNAs under Skin of Human and Mouse Jianghong Wu, Husile Gong, Yongsheng Bai, and Wenguang Zhang Volume 2016, Article ID 5469371, 9 pages Differential Regulatory Analysis Based on Coexpression Network in Cancer Research Junyi