DOCSLIB.ORG

Differences in Human and Chimpanzee Gene Expression Patterns Define an Evolving Network of Transcription Factors in Brain

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Differences in Human and Chimpanzee Gene Expression Patterns Define an Evolving Network of Transcription Factors in Brain Differences in human and chimpanzee gene expression patterns define an evolving network of transcription factors in brain Katja Nowicka,b, Tim Gernata,b, Eivind Almaasc, and Lisa Stubbsa,b,1 aInstitute for Genomic Biology and bDepartment of Cell and Developmental Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801; and cDepartment of Biotechnology, Norwegian University of Science and Technology, N-7491 Trondheim, Norway Communicated by Gene E. Robinson, University of Illinois at Urbana-Champaign, Urbana, IL, October 4, 2009 (received for review July 7, 2009) Humans differ from other primates by marked differences in and networking of specific TFs could be driving major changes cognitive abilities and a significantly larger brain. These differences between primate species. However, previous analyses of human correlate with metabolic changes, as evidenced by the relative and chimpanzee TF gene expression did not include a compar- up-regulation of energy-related genes and metabolites in human ison of gene expression in brain. brain. While the mechanisms underlying these evolutionary Other large microarray studies have included human and changes have not been elucidated, altered activities of key tran- chimpanzee brain comparisons (5, 7, 11), but the assessment of scription factors (TFs) could play a pivotal role. To assess this TF gene expression is complicated by several issues. In partic- possibility, we analyzed microarray data from five tissues from ular, many TF loci are members of extended gene families, yet humans and chimpanzees. We identified 90 TF genes with signif- most microarray platforms are not designed to uniquely detect icantly different expression levels in human and chimpanzee brain the specific family members. The problem is particularly acute among which the rapidly evolving KRAB-zinc finger genes are for the largest family of TFs in mammals, the KRAB zinc finger markedly over-represented. The differentially expressed TFs clus- (KRAB-ZNF) genes. About one-third of these genes are pri- ter within a robust regulatory network consisting of two distinct mate-specific, including many recent duplicates (12). In striking but interlinked modules, one strongly associated with energy contrast to other TFs, KRAB-ZNFs have on average accumu- metabolism functions, and the other with transcription, vesicular lated more amino acid differences between humans and chim- transport, and ubiquitination. Our results suggest that concerted panzees than other genes, indicating that they may have con- changes in a relatively small number of interacting TFs may tributed disproportionately to the phenotypic differences coordinate major gene expression differences in human and chim- between these species (13, 14). panzee brain. To enable an accurate comparison of TF gene expression and network structure in human and chimpanzee brain, we devised comparative transcriptomics ͉ KRAB-zinc finger genes ͉ primate evolution ͉ a strategy to reliably distinguish expression levels of individual gene regulatory network evolution gene family members. Our analysis of an established dataset (11) uncovered 90 TF genes that are differentially expressed and umans differ from chimpanzees in a number of important revealed that they are organized in a coexpression network Hanatomical and physiological respects, most strikingly in our comprised of two modules with distinct functions. Both modules enhanced cognitive abilities and a substantial increase in the are enriched for primate-specific KRAB-ZNF genes, which relative size of the human brain (1). Although the human brain despite their recent advent are robustly embedded in the chim- is relatively energy-efficient per cell compared with brains of panzee and human brain networks. Our results implicate a other species, this increased capacity imposes a significant network of TFs with differential expression in human and metabolic and oxidative burden (2, 3). Several studies have noted chimpanzee brain involved in regulation of energy metabolism, the up-regulation of genes and metabolites involved in oxidative vesicle transport, and related functions required to build and metabolism and mitochondrial function in human brains com- maintain the larger and more complex human brain. pared with chimpanzee brains (2, 4, 5). These data, together with evidence of positive selection acting on the promoters of genes Results involved in energy metabolism during human evolution, indicate TF Genes with Differential Expression in Human Compared to Chim- that increased energy production has been essential to the panzee Brain. We reexamined the expression of TF genes (15) in evolution of the human brain (6). The relative up-regulation of a published Affymetrix microarray data set that contrasts five human genes in other functional categories, including neuro- human and chimpanzee tissues: heart, kidney, liver, testis, and protection and synaptic transport, has also been documented (7). brain—specifically prefrontal cortex (PFC). Although all cortex However, the molecular mechanisms underlying these well- regions display very similar expression differences between documented species differences have not been elucidated. humans and chimpanzees (16), the PFC is a good study object Although some differences in human–chimpanzee gene ex- because of its marked differences in structure and function pression may be due to cis-regulatory element divergence, between the two species. For convenience, we will refer to these transcription factors (TFs) represent another potential source of samples simply as ‘‘brain’’ in the following discussion. expression variability. Whereas most cis-element mutations would be expected to have limited, localized effects, alterations in TF sequence and/or expression could alter the expression of Author contributions: K.N. and L.S. designed research; K.N. performed research; T.G. and E.A. contributed new reagents/analytic tools; K.N., T.G., E.A., and L.S. analyzed data; and hundreds of target genes in a coordinated fashion (8, 9). Because K.N. and L.S. wrote the paper. of these predicted consequences, it is often assumed that TFs are The authors declare no conflict of interest. evolutionarily stable, and indeed, TFs as a class are structurally 1To whom correspondence should be addressed at: Institute for Genomic Biology, Univer- well conserved (8). However, two recent studies have identified sity of Illinois at Urbana-Champaign, 1206 West Gregory Drive, Urbana, IL 61801. E-mail: TF genes as enriched among genes with expression patterns that [email protected]. are under directional selection in humans (4, 10). These studies This article contains supporting information online at www.pnas.org/cgi/content/full/ raise the intriguing hypothesis that differences in the expression 0911376106/DCSupplemental. 22358–22363 ͉ PNAS ͉ December 29, 2009 ͉ vol. 106 ͉ no. 52 www.pnas.org͞cgi͞doi͞10.1073͞pnas.0911376106 Downloaded by guest on September 24, 2021 variation within species to the interspecies difference (SI Text). On the other hand, KRAB-ZNFs are significantly depleted (PT, P ϭ 0.999) from the set of differentially expressed genes in testis. The only other large TF families, encoding Homeobox and the basic helix–loop–helix (bHLH) proteins, do not show such enrichment: Whereas 23.2% of brain-expressed KRAB-ZNFs are differentially expressed between species, only 8.2% of the Homeobox and 5.5% of the bHLH genes have changed in brain expression. Our analysis therefore revealed a clear contrast between KRAB-ZNFs and other TFs as well as between brain and other tissues (Fig. 1). To focus on the differentially expressed TFs most likely affecting brain functions, we applied three additional filters. In Fig. 1. Percentage of differentially expressed genes among human and the remainder of this paper, we will only refer to genes as chimpanzee tissues. The proportion of all genes (white), all transcription ‘‘changed’’ between humans and chimpanzees if they (i) are factors (light gray), all KRAB-ZNF (KZNF) genes (gray), conserved KRAB-ZNF significantly different in expression after correcting the P value genes (dark gray), or primate-specific KRAB-ZNF genes (black) that are differ- obtained from the two-sample t test within each tissue for entially expressed between species (t test, P Ͻ 0.01) is shown separately for multiple testing (P Ͻ 0.05; Benjamini–Hochberg correction), (ii) each tissue. Asterisks mark values that represent significant enrichment. Num- have a difference of at least 1.2-fold, and (iii) have a difference bers of genes per category are between 7 and 6,720. of 20 units of expression values. The latter criterion ensures that the gene is expressed at a modest level in at least one species. We Expression data were analyzed from all five tissues in each of found 90 TFs, including 33 KRAB-ZNFs, that met these more six individual humans and in five individual chimpanzees (11). stringent requirements for differential expression between hu- man and chimpanzee brains (Table S2). Despite the fact that To improve the reliability of the comparisons, we masked all most TFs (79 of 90) are expressed in all five tissues, about probes that do not match both genomes perfectly (10). To detect one-quarter of them (18 of 79) have changed specifically in brain. gene family members uniquely, we also removed probes with The proportion of KRAB-ZNFs that have changed only in brain more than one exact match in either genome. This approach EVOLUTION is higher (9 of 29). Interestingly, recent primate-specific KRAB-
Load more

Recommended publications
  • 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.
    [Show full text]
  • Downloaded from [266]
    Patterns of DNA methylation on the human X chromosome and use in analyzing X-chromosome inactivation by Allison Marie Cotton B.Sc., The University of Guelph, 2005 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in The Faculty of Graduate Studies (Medical Genetics) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) January 2012 © Allison Marie Cotton, 2012 Abstract The process of X-chromosome inactivation achieves dosage compensation between mammalian males and females. In females one X chromosome is transcriptionally silenced through a variety of epigenetic modifications including DNA methylation. Most X-linked genes are subject to X-chromosome inactivation and only expressed from the active X chromosome. On the inactive X chromosome, the CpG island promoters of genes subject to X-chromosome inactivation are methylated in their promoter regions, while genes which escape from X- chromosome inactivation have unmethylated CpG island promoters on both the active and inactive X chromosomes. The first objective of this thesis was to determine if the DNA methylation of CpG island promoters could be used to accurately predict X chromosome inactivation status. The second objective was to use DNA methylation to predict X-chromosome inactivation status in a variety of tissues. A comparison of blood, muscle, kidney and neural tissues revealed tissue-specific X-chromosome inactivation, in which 12% of genes escaped from X-chromosome inactivation in some, but not all, tissues. X-linked DNA methylation analysis of placental tissues predicted four times higher escape from X-chromosome inactivation than in any other tissue. Despite the hypomethylation of repetitive elements on both the X chromosome and the autosomes, no changes were detected in the frequency or intensity of placental Cot-1 holes.
    [Show full text]
  • TCEAL1 Mouse Monoclonal Antibody [Clone ID: OTI3G9] Product Data
    OriGene Technologies, Inc. 9620 Medical Center Drive, Ste 200 Rockville, MD 20850, US Phone: +1-888-267-4436 [email protected] EU: [email protected] CN: [email protected] Product datasheet for CF807707 TCEAL1 Mouse Monoclonal Antibody [Clone ID: OTI3G9] Product data: Product Type: Primary Antibodies Clone Name: OTI3G9 Applications: WB Recommended Dilution: WB 1:2000 Reactivity: Human Host: Mouse Isotype: IgG1 Clonality: Monoclonal Immunogen: Full length human recombinant protein of human TCEAL1 (NP_004771) produced in E.coli. Formulation: Lyophilized powder (original buffer 1X PBS, pH 7.3, 8% trehalose) Reconstitution Method: For reconstitution, we recommend adding 100uL distilled water to a final antibody concentration of about 1 mg/mL. To use this carrier-free antibody for conjugation experiment, we strongly recommend performing another round of desalting process. (OriGene recommends Zeba Spin Desalting Columns, 7KMWCO from Thermo Scientific) Purification: Purified from mouse ascites fluids or tissue culture supernatant by affinity chromatography (protein A/G) Conjugation: Unconjugated Storage: Store at -20°C as received. Stability: Stable for 12 months from date of receipt. Predicted Protein Size: 18.5 kDa Gene Name: Homo sapiens transcription elongation factor A like 1 (TCEAL1), transcript variant 1, mRNA. Database Link: NP_004771 Entrez Gene 9338 Human Q15170 This product is to be used for laboratory only. Not for diagnostic or therapeutic use. View online » ©2021 OriGene Technologies, Inc., 9620 Medical Center Drive, Ste 200, Rockville, MD 20850, US 1 / 2 TCEAL1 Mouse Monoclonal Antibody [Clone ID: OTI3G9] – CF807707 Background: This gene encodes a member of the transcription elongation factor A (SII)-like (TCEAL) gene family.
    [Show full text]
  • Gait Abnormalities and Progressive Myelin Degeneration in a New Murine Model of Pelizaeus-Merzbacher Disease with Tandem Genomic Duplication
    11788 • The Journal of Neuroscience, July 17, 2013 • 33(29):11788–11799 Neurobiology of Disease Gait Abnormalities and Progressive Myelin Degeneration in a New Murine Model of Pelizaeus-Merzbacher Disease with Tandem Genomic Duplication Kristi Clark,1,2 Lauren Sakowski,1,2 Karen Sperle,1 Linda Banser,1 Carlisle P. Landel,3 Denise A. Bessert,4 Robert P. Skoff,4 and Grace M. Hobson1,2,5 1Nemours Biomedical Research, Alfred I. duPont Hospital for Children, Wilmington, Delaware 19803, 2University of Delaware, Department of Biology, Newark, Delaware 19716, 3Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, Pennsylvania 19107, 4Wayne State University, Department of Anatomy and Cell Biology, Detroit, Michigan 48201, and 5Jefferson Medical College, Thomas Jefferson University, Philadelphia, Pennsylvania 19107 Pelizaeus-Merzbacher disease (PMD) is a hypomyelinating leukodystrophy caused by mutations of the proteolipid protein 1 gene (PLP1), which is located on the X chromosome and encodes the most abundant protein of myelin in the central nervous sytem. Approximately 60% of PMD cases result from genomic duplications of a region of the X chromosome that includes the entire PLP1 gene. The duplications are typically in a head-to-tail arrangement, and they vary in size and gene content. Although rodent models with extra copies of Plp1 have been developed, none contains an actual genomic rearrangement that resembles those found in PMD patients. We used mutagenic insertion chromosome engineering resources to generate the Plp1dup mouse model by introducing an X chromosome duplication in the mouse genome that contains Plp1 and five neighboring genes that are also commonly duplicated in PMD patients. The Plp1dup mice display progressive gait abnormalities compared with wild-type littermates.
    [Show full text]
  • TCEAL1 CRISPR/Cas9 KO Plasmid (M): Sc-433532
    SANTA CRUZ BIOTECHNOLOGY, INC. TCEAL1 CRISPR/Cas9 KO Plasmid (m): sc-433532 BACKGROUND APPLICATIONS The Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) and TCEAL1 CRISPR/Cas9 KO Plasmid (m) is recommended for the disruption of CRISPR-associated protein (Cas9) system is an adaptive immune response gene expression in mouse cells. defense mechanism used by archea and bacteria for the degradation of foreign genetic material (4,6). This mechanism can be repurposed for other 20 nt non-coding RNA sequence: guides Cas9 functions, including genomic engineering for mammalian systems, such as to a specific target location in the genomic DNA gene knockout (KO) (1,2,3,5). CRISPR/Cas9 KO Plasmid products enable the U6 promoter: drives gRNA scaffold: helps Cas9 identification and cleavage of specific genes by utilizing guide RNA (gRNA) expression of gRNA bind to target DNA sequences derived from the Genome-scale CRISPR Knock-Out (GeCKO) v2 library developed in the Zhang Laboratory at the Broad Institute (3,5). Termination signal Green Fluorescent Protein: to visually REFERENCES verify transfection CRISPR/Cas9 Knockout Plasmid CBh (chicken β-Actin 1. Cong, L., et al. 2013. Multiplex genome engineering using CRISPR/Cas hybrid) promoter: drives expression of Cas9 systems. Science 339: 819-823. 2A peptide: allows production of both Cas9 and GFP from the 2. Mali, P., et al. 2013. RNA-guided human genome engineering via Cas9. same CBh promoter Science 339: 823-826. Nuclear localization signal 3. Ran, F.A., et al. 2013. Genome engineering using the CRISPR-Cas9 system. Nuclear localization signal SpCas9 ribonuclease Nat. Protoc. 8: 2281-2308.
    [Show full text]
  • Content Based Search in Gene Expression Databases and a Meta-Analysis of Host Responses to Infection
    Content Based Search in Gene Expression Databases and a Meta-analysis of Host Responses to Infection A Thesis Submitted to the Faculty of Drexel University by Francis X. Bell in partial fulfillment of the requirements for the degree of Doctor of Philosophy November 2015 c Copyright 2015 Francis X. Bell. All Rights Reserved. ii Acknowledgments I would like to acknowledge and thank my advisor, Dr. Ahmet Sacan. Without his advice, support, and patience I would not have been able to accomplish all that I have. I would also like to thank my committee members and the Biomed Faculty that have guided me. I would like to give a special thanks for the members of the bioinformatics lab, in particular the members of the Sacan lab: Rehman Qureshi, Daisy Heng Yang, April Chunyu Zhao, and Yiqian Zhou. Thank you for creating a pleasant and friendly environment in the lab. I give the members of my family my sincerest gratitude for all that they have done for me. I cannot begin to repay my parents for their sacrifices. I am eternally grateful for everything they have done. The support of my sisters and their encouragement gave me the strength to persevere to the end. iii Table of Contents LIST OF TABLES.......................................................................... vii LIST OF FIGURES ........................................................................ xiv ABSTRACT ................................................................................ xvii 1. A BRIEF INTRODUCTION TO GENE EXPRESSION............................. 1 1.1 Central Dogma of Molecular Biology........................................... 1 1.1.1 Basic Transfers .......................................................... 1 1.1.2 Uncommon Transfers ................................................... 3 1.2 Gene Expression ................................................................. 4 1.2.1 Estimating Gene Expression ............................................ 4 1.2.2 DNA Microarrays ......................................................
    [Show full text]
  • 393LN V 393P 344SQ V 393P Probe Set Entrez Gene
    393LN v 393P 344SQ v 393P Entrez fold fold probe set Gene Gene Symbol Gene cluster Gene Title p-value change p-value change chemokine (C-C motif) ligand 21b /// chemokine (C-C motif) ligand 21a /// chemokine (C-C motif) ligand 21c 1419426_s_at 18829 /// Ccl21b /// Ccl2 1 - up 393 LN only (leucine) 0.0047 9.199837 0.45212 6.847887 nuclear factor of activated T-cells, cytoplasmic, calcineurin- 1447085_s_at 18018 Nfatc1 1 - up 393 LN only dependent 1 0.009048 12.065 0.13718 4.81 RIKEN cDNA 1453647_at 78668 9530059J11Rik1 - up 393 LN only 9530059J11 gene 0.002208 5.482897 0.27642 3.45171 transient receptor potential cation channel, subfamily 1457164_at 277328 Trpa1 1 - up 393 LN only A, member 1 0.000111 9.180344 0.01771 3.048114 regulating synaptic membrane 1422809_at 116838 Rims2 1 - up 393 LN only exocytosis 2 0.001891 8.560424 0.13159 2.980501 glial cell line derived neurotrophic factor family receptor alpha 1433716_x_at 14586 Gfra2 1 - up 393 LN only 2 0.006868 30.88736 0.01066 2.811211 1446936_at --- --- 1 - up 393 LN only --- 0.007695 6.373955 0.11733 2.480287 zinc finger protein 1438742_at 320683 Zfp629 1 - up 393 LN only 629 0.002644 5.231855 0.38124 2.377016 phospholipase A2, 1426019_at 18786 Plaa 1 - up 393 LN only activating protein 0.008657 6.2364 0.12336 2.262117 1445314_at 14009 Etv1 1 - up 393 LN only ets variant gene 1 0.007224 3.643646 0.36434 2.01989 ciliary rootlet coiled- 1427338_at 230872 Crocc 1 - up 393 LN only coil, rootletin 0.002482 7.783242 0.49977 1.794171 expressed sequence 1436585_at 99463 BB182297 1 - up 393
    [Show full text]
  • Global Patterns of Changes in the Gene Expression Associated with Genesis of Cancer a Dissertation Submitted in Partial Fulfillm
    Global Patterns Of Changes In The Gene Expression Associated With Genesis Of Cancer A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at George Mason University By Ganiraju Manyam Master of Science IIIT-Hyderabad, 2004 Bachelor of Engineering Bharatiar University, 2002 Director: Dr. Ancha Baranova, Associate Professor Department of Molecular & Microbiology Fall Semester 2009 George Mason University Fairfax, VA Copyright: 2009 Ganiraju Manyam All Rights Reserved ii DEDICATION To my parents Pattabhi Ramanna and Veera Venkata Satyavathi who introduced me to the joy of learning. To friends, family and colleagues who have contributed in work, thought, and support to this project. iii ACKNOWLEDGEMENTS I would like to thank my advisor, Dr. Ancha Baranova, whose tolerance, patience, guidance and encouragement helped me throughout the study. This dissertation would not have been possible without her ever ending support. She is very sincere and generous with her knowledge, availability, compassion, wisdom and feedback. I would also like to thank Dr. Vikas Chandhoke for funding my research generously during my doctoral study at George Mason University. Special thanks go to Dr. Patrick Gillevet, Dr. Alessandro Giuliani, Dr. Maria Stepanova who devoted their time to provide me with their valuable contributions and guidance to formulate this project. Thanks to the faculty of Molecular and Micro Biology (MMB) department, Dr. Jim Willett and Dr. Monique Vanhoek in embedding valuable thoughts to this dissertation by being in my dissertation committee. I would also like to thank the present and previous doctoral program directors, Dr. Daniel Cox and Dr. Geraldine Grant, for facilitating, allowing, and encouraging me to work in this project.
    [Show full text]
  • Predict AID Targeting in Non-Ig Genes Multiple Transcription Factor
    Downloaded from http://www.jimmunol.org/ by guest on September 26, 2021 is online at: average * The Journal of Immunology published online 20 March 2013 from submission to initial decision 4 weeks from acceptance to publication Multiple Transcription Factor Binding Sites Predict AID Targeting in Non-Ig Genes Jamie L. Duke, Man Liu, Gur Yaari, Ashraf M. Khalil, Mary M. Tomayko, Mark J. Shlomchik, David G. Schatz and Steven H. Kleinstein J Immunol http://www.jimmunol.org/content/early/2013/03/20/jimmun ol.1202547 Submit online. Every submission reviewed by practicing scientists ? is published twice each month by http://jimmunol.org/subscription Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts http://www.jimmunol.org/content/suppl/2013/03/20/jimmunol.120254 7.DC1 Information about subscribing to The JI No Triage! Fast Publication! Rapid Reviews! 30 days* Why • • • Material Permissions Email Alerts Subscription Supplementary The Journal of Immunology The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2013 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. This information is current as of September 26, 2021. Published March 20, 2013, doi:10.4049/jimmunol.1202547 The Journal of Immunology Multiple Transcription Factor Binding Sites Predict AID Targeting in Non-Ig Genes Jamie L. Duke,* Man Liu,†,1 Gur Yaari,‡ Ashraf M. Khalil,x Mary M. Tomayko,{ Mark J. Shlomchik,†,x David G.
    [Show full text]
  • A Network Inference Approach to Understanding Musculoskeletal
    A NETWORK INFERENCE APPROACH TO UNDERSTANDING MUSCULOSKELETAL DISORDERS by NIL TURAN A thesis submitted to The University of Birmingham for the degree of Doctor of Philosophy College of Life and Environmental Sciences School of Biosciences The University of Birmingham June 2013 University of Birmingham Research Archive e-theses repository This unpublished thesis/dissertation is copyright of the author and/or third parties. The intellectual property rights of the author or third parties in respect of this work are as defined by The Copyright Designs and Patents Act 1988 or as modified by any successor legislation. Any use made of information contained in this thesis/dissertation must be in accordance with that legislation and must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the permission of the copyright holder. ABSTRACT Musculoskeletal disorders are among the most important health problem affecting the quality of life and contributing to a high burden on healthcare systems worldwide. Understanding the molecular mechanisms underlying these disorders is crucial for the development of efficient treatments. In this thesis, musculoskeletal disorders including muscle wasting, bone loss and cartilage deformation have been studied using systems biology approaches. Muscle wasting occurring as a systemic effect in COPD patients has been investigated with an integrative network inference approach. This work has lead to a model describing the relationship between muscle molecular and physiological response to training and systemic inflammatory mediators. This model has shown for the first time that oxygen dependent changes in the expression of epigenetic modifiers and not chronic inflammation may be causally linked to muscle dysfunction.
    [Show full text]
  • Single Cell Analysis Reveals X Chromosome Upregulation Is Not
    bioRxiv preprint doi: https://doi.org/10.1101/2021.07.18.452817; this version posted July 19, 2021. 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. 1 Single cell analysis reveals X chromosome upregulation is not global and 2 primarily belongs to ancestral genes in pre-gastrulation embryos 3 Naik C H, Chandel D, and Gayen S* 4 Department of Molecular Reproduction, Development and Genetics, Indian Institute of Science, 5 Bangalore-560012, India. 6 *Correspondence: [email protected] 7 8 Abstract 9 Recent studies have provided substantial evidence supporting Ohno's hypothesis that 10 upregulation of active X chromosome genes balances the dosage of X-linked gene expression 11 relative to autosomal genes. However, the dynamics of X-chromosome upregulation (XCU) 12 during early development remain poorly Pre-gastrulation embryos E6.50 13 understood. Here, we have profiled the E6.25 E5.5 14 dynamics of XCU in different lineages of 15 female pre-gastrulation mouse embryos at 16 single cell level through allele-specific single 17 cell RNA-seq analysis. We found dynamic 18 XCU upon initiation of random X- Epiblast cells 19 chromosome inactivation (XCI) in epiblast Onset of Random X-inactivation 20 cells and cells of extraembryonic lineages, 21 which undergo imprinted XCI, also harbored 22 upregulated active-X chromosome. On the 23 other hand, the extent of XCU remains 24 controversial till date.
    [Show full text]
  • The Glucocorticoid-Mediated Dynamics of Genome Architecture
    The Glucocorticoid-Mediated Dynamics of Genome Architecture by Anthony M. D’Ippolito University Program in Genetics and Genomics Duke University Date:_______________________ Approved: ___________________________ Timothy Reddy, Supervisor ___________________________ Gregory Crawford ___________________________ Charles Gersbach ___________________________ Donald McDonnell ___________________________ Jenny Tung Dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the University Program in Genetics and Genomics in the Graduate School of Duke University 2018 ABSTRACT The Glucocorticoid-Mediated Dynamics of Genome Architecture by Anthony M. D’Ippolito University Program in Genetics and Genomics Duke University Date:_______________________ Approved: ___________________________ Timothy Reddy, Supervisor ___________________________ Gregory Crawford ___________________________ Charles Gersbach ___________________________ Donald McDonnell ___________________________ Jenny Tung An abstract of a Dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the University Program in Genetics and Genomics in the Graduate School of Duke University 2018 Copyright by Anthony M. D’Ippolito 2018 Abstract Human cells are perpetually receiving and responding to a variety of intrinsic and extrinsic signals. A primary mechanism by which cells carry out these responses is via changes in the regulation of gene expression. Many studies have examined gene regulation
    [Show full text]