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Analysis of Trans Esnps Infers Regulatory Network Architecture
Analysis of trans eSNPs infers regulatory network architecture Anat Kreimer 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 Anat Kreimer All rights reserved ABSTRACT Analysis of trans eSNPs infers regulatory network architecture Anat Kreimer eSNPs are genetic variants associated with transcript expression levels. The characteristics of such variants highlight their importance and present a unique opportunity for studying gene regulation. eSNPs affect most genes and their cell type specificity can shed light on different processes that are activated in each cell. They can identify functional variants by connecting SNPs that are implicated in disease to a molecular mechanism. Examining eSNPs that are associated with distal genes can provide insights regarding the inference of regulatory networks but also presents challenges due to the high statistical burden of multiple testing. Such association studies allow: simultaneous investigation of many gene expression phenotypes without assuming any prior knowledge and identification of unknown regulators of gene expression while uncovering directionality. This thesis will focus on such distal eSNPs to map regulatory interactions between different loci and expose the architecture of the regulatory network defined by such interactions. We develop novel computational approaches and apply them to genetics-genomics data in human. We go beyond pairwise interactions to define network motifs, including regulatory modules and bi-fan structures, showing them to be prevalent in real data and exposing distinct attributes of such arrangements. We project eSNP associations onto a protein-protein interaction network to expose topological properties of eSNPs and their targets and highlight different modes of distal regulation. -
Analysis of Gene Expression Data for Gene Ontology
ANALYSIS OF GENE EXPRESSION DATA FOR GENE ONTOLOGY BASED PROTEIN FUNCTION PREDICTION A Thesis Presented to The Graduate Faculty of The University of Akron In Partial Fulfillment of the Requirements for the Degree Master of Science Robert Daniel Macholan May 2011 ANALYSIS OF GENE EXPRESSION DATA FOR GENE ONTOLOGY BASED PROTEIN FUNCTION PREDICTION Robert Daniel Macholan Thesis Approved: Accepted: _______________________________ _______________________________ Advisor Department Chair Dr. Zhong-Hui Duan Dr. Chien-Chung Chan _______________________________ _______________________________ Committee Member Dean of the College Dr. Chien-Chung Chan Dr. Chand K. Midha _______________________________ _______________________________ Committee Member Dean of the Graduate School Dr. Yingcai Xiao Dr. George R. Newkome _______________________________ Date ii ABSTRACT A tremendous increase in genomic data has encouraged biologists to turn to bioinformatics in order to assist in its interpretation and processing. One of the present challenges that need to be overcome in order to understand this data more completely is the development of a reliable method to accurately predict the function of a protein from its genomic information. This study focuses on developing an effective algorithm for protein function prediction. The algorithm is based on proteins that have similar expression patterns. The similarity of the expression data is determined using a novel measure, the slope matrix. The slope matrix introduces a normalized method for the comparison of expression levels throughout a proteome. The algorithm is tested using real microarray gene expression data. Their functions are characterized using gene ontology annotations. The results of the case study indicate the protein function prediction algorithm developed is comparable to the prediction algorithms that are based on the annotations of homologous proteins. -
Molecular Basis for the Distinct Cellular Functions of the Lsm1-7 and Lsm2-8 Complexes
bioRxiv preprint doi: https://doi.org/10.1101/2020.04.22.055376; this version posted April 23, 2020. 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. Molecular basis for the distinct cellular functions of the Lsm1-7 and Lsm2-8 complexes Eric J. Montemayor1,2, Johanna M. Virta1, Samuel M. Hayes1, Yuichiro Nomura1, David A. Brow2, Samuel E. Butcher1 1Department of Biochemistry, University of Wisconsin-Madison, Madison, WI, USA. 2Department of Biomolecular Chemistry, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA. Correspondence should be addressed to E.J.M. ([email protected]) and S.E.B. ([email protected]). Abstract Eukaryotes possess eight highly conserved Lsm (like Sm) proteins that assemble into circular, heteroheptameric complexes, bind RNA, and direct a diverse range of biological processes. Among the many essential functions of Lsm proteins, the cytoplasmic Lsm1-7 complex initiates mRNA decay, while the nuclear Lsm2-8 complex acts as a chaperone for U6 spliceosomal RNA. It has been unclear how these complexes perform their distinct functions while differing by only one out of seven subunits. Here, we elucidate the molecular basis for Lsm-RNA recognition and present four high-resolution structures of Lsm complexes bound to RNAs. The structures of Lsm2-8 bound to RNA identify the unique 2′,3′ cyclic phosphate end of U6 as a prime determinant of specificity. In contrast, the Lsm1-7 complex strongly discriminates against cyclic phosphates and tightly binds to oligouridylate tracts with terminal purines. -
Mayr, Annu Rev Genet 2017
GE51CH09-Mayr ARI 12 October 2017 10:21 Annual Review of Genetics Regulation by 3-Untranslated Regions Christine Mayr Department of Cancer Biology and Genetics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; email: [email protected] Annu. Rev. Genet. 2017. 51:171–94 Keywords First published as a Review in Advance on August noncoding RNA, regulatory RNA, alternative 3-UTRs, alternative 30, 2017 polyadenylation, cotranslational protein complex formation, cellular The Annual Review of Genetics is online at organization, mRNA localization, RNA-binding proteins, cooperativity, genet.annualreviews.org accessibility of regulatory elements https://doi.org/10.1146/annurev-genet-120116- 024704 Abstract Copyright c 2017 by Annual Reviews. 3 -untranslated regions (3 -UTRs) are the noncoding parts of mRNAs. Com- All rights reserved pared to yeast, in humans, median 3-UTR length has expanded approx- imately tenfold alongside an increased generation of alternative 3-UTR isoforms. In contrast, the number of coding genes, as well as coding region length, has remained similar. This suggests an important role for 3-UTRs in the biology of higher organisms. 3-UTRs are best known to regulate ANNUAL REVIEWS Further diverse fates of mRNAs, including degradation, translation, and localiza- Click here to view this article's tion, but they can also function like long noncoding or small RNAs, as has Annu. Rev. Genet. 2017.51:171-194. Downloaded from www.annualreviews.org online features: • Download figures as PPT slides been shown for whole 3 -UTRs as well as for cleaved fragments. Further- • Navigate linked references • Download citations more, 3 -UTRs determine the fate of proteins through the regulation of Access provided by Memorial Sloan-Kettering Cancer Center on 11/30/17. -
Autism Multiplex Family with 16P11.2P12.2 Microduplication Syndrome in Monozygotic Twins and Distal 16P11.2 Deletion in Their Brother
European Journal of Human Genetics (2012) 20, 540–546 & 2012 Macmillan Publishers Limited All rights reserved 1018-4813/12 www.nature.com/ejhg ARTICLE Autism multiplex family with 16p11.2p12.2 microduplication syndrome in monozygotic twins and distal 16p11.2 deletion in their brother Anne-Claude Tabet1,2,3,4, Marion Pilorge2,3,4, Richard Delorme5,6,Fre´de´rique Amsellem5,6, Jean-Marc Pinard7, Marion Leboyer6,8,9, Alain Verloes10, Brigitte Benzacken1,11,12 and Catalina Betancur*,2,3,4 The pericentromeric region of chromosome 16p is rich in segmental duplications that predispose to rearrangements through non-allelic homologous recombination. Several recurrent copy number variations have been described recently in chromosome 16p. 16p11.2 rearrangements (29.5–30.1 Mb) are associated with autism, intellectual disability (ID) and other neurodevelopmental disorders. Another recognizable but less common microdeletion syndrome in 16p11.2p12.2 (21.4 to 28.5–30.1 Mb) has been described in six individuals with ID, whereas apparently reciprocal duplications, studied by standard cytogenetic and fluorescence in situ hybridization techniques, have been reported in three patients with autism spectrum disorders. Here, we report a multiplex family with three boys affected with autism, including two monozygotic twins carrying a de novo 16p11.2p12.2 duplication of 8.95 Mb (21.28–30.23 Mb) characterized by single-nucleotide polymorphism array, encompassing both the 16p11.2 and 16p11.2p12.2 regions. The twins exhibited autism, severe ID, and dysmorphic features, including a triangular face, deep-set eyes, large and prominent nasal bridge, and tall, slender build. The eldest brother presented with autism, mild ID, early-onset obesity and normal craniofacial features, and carried a smaller, overlapping 16p11.2 microdeletion of 847 kb (28.40–29.25 Mb), inherited from his apparently healthy father. -
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. -
Bppart and Bpmax: RNA-RNA Interaction Partition Function and Structure Prediction for the Base Pair Counting Model
BPPart and BPMax: RNA-RNA Interaction Partition Function and Structure Prediction for the Base Pair Counting Model Ali Ebrahimpour-Boroojeny, Sanjay Rajopadhye, and Hamidreza Chitsaz ∗ Department of Computer Science, Colorado State University Abstract A few elite classes of RNA-RNA interaction (RRI), with complex roles in cellular functions such as miRNA-target and lncRNAs in human health, have already been studied. Accordingly, RRI bioinfor- matics tools tailored for those elite classes have been proposed in the last decade. Interestingly, there are somewhat unnoticed mRNA-mRNA interactions in the literature with potentially drastic biological roles. Hence, there is a need for high-throughput generic RRI bioinformatics tools. We revisit our RRI partition function algorithm, piRNA, which happens to be the most comprehensive and computationally-intensive thermodynamic model for RRI. We propose simpler models that are shown to retain the vast majority of the thermodynamic information that piRNA captures. We simplify the energy model and instead consider only weighted base pair counting to obtain BPPart for Base-pair Partition function and BPMax for Base-pair Maximization which are 225 and 1350 faster ◦ × × than piRNA, with a correlation of 0.855 and 0.836 with piRNA at 37 C on 50,500 experimentally charac- terized RRIs. This correlation increases to 0.920 and 0.904, respectively, at 180◦C. − Finally, we apply our algorithm BPPart to discover two disease-related RNAs, SNORD3D and TRAF3, and hypothesize their potential roles in Parkinson's disease and Cerebral Autosomal Dominant Arteri- opathy with Subcortical Infarcts and Leukoencephalopathy (CADASIL). 1 Introduction Since mid 1990s with the advent of RNA interference discovery, RNA-RNA interaction (RRI) has moved to the spotlight in modern, post-genome biology. -
Nascent RNA Sequencing Reveals a Dynamic Global Transcriptional Response at Genes and Enhancers to the Natural Medicinal Compound Celastrol
bioRxiv preprint doi: https://doi.org/10.1101/117689; this version posted March 16, 2017. 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. Nascent RNA sequencing reveals a dynamic global transcriptional response at genes and enhancers to the natural medicinal compound celastrol Noah Dukler1,2, Gregory T. Booth3, Yi-Fei Huang1, Nathaniel Tippens2,3, Charles G. Danko4, John T. Lis3,*, Adam Siepel1,* 1Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA 2Tri-Institutional Training Program in Computational Biology and Medicine, New York, NY 10065, USA 3Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY 14850, USA 4Baker Institute for Animal Health, Cornell University, Ithaca, NY 14850, USA *Correspondence should be addressed to JTL ([email protected]) and/or AS ([email protected]) Abstract Most studies of responses to transcriptional stimuli measure changes in cellular mRNA concentrations. By sequencing nascent RNA instead, it is possible to detect changes in transcription in minutes rather than hours, and thereby distinguish primary from secondary responses to regulatory signals. Here, we describe the use of PRO-seq to characterize the immediate transcriptional response in human cells to celastrol, a compound derived from traditional Chinese medicine that has potent anti-inflammatory, tumor-inhibitory and obesity-controlling effects. Our analysis of PRO-seq data for K562 cells reveals dramatic transcriptional effects soon after celastrol treatment at a broad collection of both coding and noncoding transcription units. -
UCLA UCLA Electronic Theses and Dissertations
UCLA UCLA Electronic Theses and Dissertations Title Global and Local Regulation of Gene Expression in the Human Brain Permalink https://escholarship.org/uc/item/83g7t3g1 Author Hartl, Christopher Publication Date 2019 Peer reviewed|Thesis/dissertation eScholarship.org Powered by the California Digital Library University of California UNIVERSITY OF CALIFORNIA Los Angeles Global and Local Regulation of Gene Expression in the Human Brain A dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in Bioinformatics by Christopher Hartl 2019 © Copyright by Christopher Hartl 2019 ABSTRACT OF THE DISSERTATION Global and Local Regulation of Gene Expression in the Human Brain by Christopher Hartl Doctor of Philosophy in Bioinformatics University of California, Los Angeles, 2019 Professor Daniel H. Geschwind, Chair Neuropsychiatric disorders are behavioral conditions marked by intellectual, social, or emotional deficits that can be linked to diseases of the nervous system. Autism spectrum disorder (ASD), schizophrenia (SCZ), bipolar disorder (BP), major depressive disorder (MDD), and attention deficit and hyperactivity disorder (ADHD) are common, heritable diseases each with a prevalence exceeding 1% of the population, none of which can be characterized by discernable anatomical or neurological pathologies. Genetic association studies have identified mutations in hundreds of genes that contribute to risk for at least one of these disorders, and have shown that a substantial fraction of the genetic liability is shared between many of these neuropsychiatric diseases. It has long been hoped that with enough genetic evidence we will identify the biological pathways, developmental time points, and brain regions that, when disrupted, give rise to neuropsychiatric disorders. -
Nucleolin and Its Role in Ribosomal Biogenesis
NUCLEOLIN: A NUCLEOLAR RNA-BINDING PROTEIN INVOLVED IN RIBOSOME BIOGENESIS Inaugural-Dissertation zur Erlangung des Doktorgrades der Mathematisch-Naturwissenschaftlichen Fakultät der Heinrich-Heine-Universität Düsseldorf vorgelegt von Julia Fremerey aus Hamburg Düsseldorf, April 2016 2 Gedruckt mit der Genehmigung der Mathematisch-Naturwissenschaftlichen Fakultät der Heinrich-Heine-Universität Düsseldorf Referent: Prof. Dr. A. Borkhardt Korreferent: Prof. Dr. H. Schwender Tag der mündlichen Prüfung: 20.07.2016 3 Die vorgelegte Arbeit wurde von Juli 2012 bis März 2016 in der Klinik für Kinder- Onkologie, -Hämatologie und Klinische Immunologie des Universitätsklinikums Düsseldorf unter Anleitung von Prof. Dr. A. Borkhardt und in Kooperation mit dem ‚Laboratory of RNA Molecular Biology‘ an der Rockefeller Universität unter Anleitung von Prof. Dr. T. Tuschl angefertigt. 4 Dedicated to my family TABLE OF CONTENTS 5 TABLE OF CONTENTS TABLE OF CONTENTS ............................................................................................... 5 LIST OF FIGURES ......................................................................................................10 LIST OF TABLES .......................................................................................................12 ABBREVIATION .........................................................................................................13 ABSTRACT ................................................................................................................19 ZUSAMMENFASSUNG -
EMBC Annual Report 2007
EMBO | EMBC annual report 2007 EUROPEAN MOLECULAR BIOLOGY ORGANIZATION | EUROPEAN MOLECULAR BIOLOGY CONFERENCE EMBO | EMBC table of contents introduction preface by Hermann Bujard, EMBO 4 preface by Tim Hunt and Christiane Nüsslein-Volhard, EMBO Council 6 preface by Marja Makarow and Isabella Beretta, EMBC 7 past & present timeline 10 brief history 11 EMBO | EMBC | EMBL aims 12 EMBO actions 2007 15 EMBC actions 2007 17 EMBO & EMBC programmes and activities fellowship programme 20 courses & workshops programme 21 young investigator programme 22 installation grants 23 science & society programme 24 electronic information programme 25 EMBO activities The EMBO Journal 28 EMBO reports 29 Molecular Systems Biology 30 journal subject categories 31 national science reviews 32 women in science 33 gold medal 34 award for communication in the life sciences 35 plenary lectures 36 communications 37 European Life Sciences Forum (ELSF) 38 ➔ 2 table of contents appendix EMBC delegates and advisers 42 EMBC scale of contributions 49 EMBO council members 2007 50 EMBO committee members & auditors 2007 51 EMBO council members 2008 52 EMBO committee members & auditors 2008 53 EMBO members elected in 2007 54 advisory editorial boards & senior editors 2007 64 long-term fellowship awards 2007 66 long-term fellowships: statistics 82 long-term fellowships 2007: geographical distribution 84 short-term fellowship awards 2007 86 short-term fellowships: statistics 104 short-term fellowships 2007: geographical distribution 106 young investigators 2007 108 installation -
A Bootstrap-Based Regression Method for Comprehensive Discovery of Differential Gene Expressions: an Application to the Osteoporosis Study
A bootstrap-based regression method for comprehensive discovery of differential gene expressions: an application to the osteoporosis study Yan Lu1,2, Yao-Zhong Liu3, Peng–Yuan Liu2, Volodymyr Dvornyk4, and Hong–Wen Deng1,3 1. College of Life Sciences and Bioengineering, Beijing Jiaotong University, Beijing 100044, P. R. China 2. Department of Physiology and the Cancer Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA 3. Department of Biostatistics and Bioinformatics & Center for Bioinformatics and Genomics, Tulane University School of Public Health, New Orleans, LA 70112, USA 4. School of Biological Sciences, University of Hong Kong, Pokfulam Rd., Pokfulam, Hong Kong, P.R. China Running title: Bootstrap-based regression method for microarray analysis Key words: microarray, bootstrap, regression, osteoporosis Corresponding author: Hong–Wen Deng, Ph. D. Department of Biostatistics and Bioinformatics & Center for Bioinformatics and Genomics, Tulane University School of Public Health, 1440 Canal Street, Suite 2001, New Orleans, LA 70112 Tel: 504-988-1310 Email: [email protected] 1 Abstract A common purpose of microarray experiments is to study the variation in gene expression across the categories of an experimental factor such as tissue types and drug treatments. However, it is not uncommon that the studied experimental factor is a quantitative variable rather than categorical variable. Loss of information would occur by comparing gene-expression levels between groups that are factitiously defined according to the quantitative threshold values of an experimental factor. Additionally, lack of control for some sensitive clinical factors may bring serious false positive or negative findings. In the present study, we described a bootstrap-based regression method for analyzing gene expression data from the non-categorical microarray experiments.