Whole-Genome Sequencing for an Enhanced Understanding of Genetic Variation Among South Africans
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Primate Specific Retrotransposons, Svas, in the Evolution of Networks That Alter Brain Function
Title: Primate specific retrotransposons, SVAs, in the evolution of networks that alter brain function. Olga Vasieva1*, Sultan Cetiner1, Abigail Savage2, Gerald G. Schumann3, Vivien J Bubb2, John P Quinn2*, 1 Institute of Integrative Biology, University of Liverpool, Liverpool, L69 7ZB, U.K 2 Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, The University of Liverpool, Liverpool L69 3BX, UK 3 Division of Medical Biotechnology, Paul-Ehrlich-Institut, Langen, D-63225 Germany *. Corresponding author Olga Vasieva: Institute of Integrative Biology, Department of Comparative genomics, University of Liverpool, Liverpool, L69 7ZB, [email protected] ; Tel: (+44) 151 795 4456; FAX:(+44) 151 795 4406 John Quinn: Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, The University of Liverpool, Liverpool L69 3BX, UK, [email protected]; Tel: (+44) 151 794 5498. Key words: SVA, trans-mobilisation, behaviour, brain, evolution, psychiatric disorders 1 Abstract The hominid-specific non-LTR retrotransposon termed SINE–VNTR–Alu (SVA) is the youngest of the transposable elements in the human genome. The propagation of the most ancient SVA type A took place about 13.5 Myrs ago, and the youngest SVA types appeared in the human genome after the chimpanzee divergence. Functional enrichment analysis of genes associated with SVA insertions demonstrated their strong link to multiple ontological categories attributed to brain function and the disorders. SVA types that expanded their presence in the human genome at different stages of hominoid life history were also associated with progressively evolving behavioural features that indicated a potential impact of SVA propagation on a cognitive ability of a modern human. -
Molecular Genetics of Dyslexia: an Overview
DYSLEXIA Published online in Wiley Online Library (wileyonlinelibrary.com). DOI: 10.1002/dys.1464 ■ Molecular Genetics of Dyslexia: An Overview Amaia Carrion-Castillo1*, Barbara Franke2 and Simon E. Fisher1,2 1Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, Netherlands 2Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Netherlands Dyslexia is a highly heritable learning disorder with a complex underlying genetic architecture. Over the past decade, researchers have pinpointed a number of candidate genes that may con- tribute to dyslexia susceptibility. Here, we provide an overview of the state of the art, describing how studies have moved from mapping potential risk loci, through identification of associated gene variants, to characterization of gene function in cellular and animal model systems. Work thus far has highlighted some intriguing mechanistic pathways, such as neuronal migration, axon guidance, and ciliary biology, but it is clear that we still have much to learn about the molecular networks that are involved. We end the review by highlighting the past, present, and future contributions of the Dutch Dyslexia Programme to studies of genetic factors. In particular, we emphasize the importance of relating genetic information to intermediate neurobiological measures, as well as the value of incorporating longitudinal and developmental data into molecular designs. Copyright © 2013 John Wiley & Sons, Ltd. Keywords: molecular genetics; dyslexia; review INTRODUCTION Over the past decade or so, advances in molecular technologies have enabled researchers to begin pinpointing potential genetic risk factors implicated in human neurodevelopmental disorders (Graham & Fisher, 2013). A significant amount of work has focused on developmental dyslexia (specific reading disability). -
Role and Regulation of Snon/Skil and PLSCR1 Located at 3Q26.2
University of South Florida Scholar Commons Graduate Theses and Dissertations Graduate School 9-18-2014 Role and Regulation of SnoN/SkiL and PLSCR1 Located at 3q26.2 and 3q23, Respectively, in Ovarian Cancer Pathophysiology Madhav Karthik Kodigepalli University of South Florida, [email protected] Follow this and additional works at: https://scholarcommons.usf.edu/etd Part of the Cell Biology Commons, Microbiology Commons, and the Molecular Biology Commons Scholar Commons Citation Kodigepalli, Madhav Karthik, "Role and Regulation of SnoN/SkiL and PLSCR1 Located at 3q26.2 and 3q23, Respectively, in Ovarian Cancer Pathophysiology" (2014). Graduate Theses and Dissertations. https://scholarcommons.usf.edu/etd/5426 This Dissertation is brought to you for free and open access by the Graduate School at Scholar Commons. It has been accepted for inclusion in Graduate Theses and Dissertations by an authorized administrator of Scholar Commons. For more information, please contact [email protected]. Role and Regulation of SnoN/SkiL and PLSCR1 Located at 3q26.2 and 3q23, Respectively, in Ovarian Cancer Pathophysiology by Madhav Karthik Kodigepalli A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Cell and Molecular Biology Department of Cell Biology, Microbiology and Molecular Biology College of Arts and Sciences University of South Florida Major Professor: Meera Nanjundan, Ph.D. Richard Pollenz, Ph.D. Patrick Bradshaw, Ph.D. Sandy Westerheide, Ph.D. Date of Approval: September 18, 2014 Keywords: Chemotherapeutics, phospholipid scramblase, toll-like receptor, interferon, dsDNA Copyright © 2014, Madhav Karthik Kodigepalli Dedication I dedicate this research at the lotus feet of Bhagwan Sri Sathya Sai Baba and all the Masters for I am what I am due to their divine grace. -
Analysis of Sequence Architecture at Human-Gibbon Synteny Breaks
Downloaded from genome.cshlp.org on October 4, 2021 - Published by Cold Spring Harbor Laboratory Press Girirajan et al Sequencing human-gibbon breakpoints of synteny reveals mosaic new insertions at rearrangement sites Santhosh Girirajan1*, Lin Chen1*, Tina Graves2, Tomas Marques-Bonet1, Mario Ventura3, Catrina Fronick2, Lucinda Fulton2, Mariano Rocchi3, Robert S. Fulton2, Richard K. Wilson2, Elaine R. Mardis2 and Evan E. Eichler1† 1. Department of Genome Sciences, Howard Hughes Medical Institute, University of Washington School of Medicine, Seattle, Washington, USA 2. Genome Sequencing Center, Washington University, St. Louis, Missouri, USA 3. Department of Genetics and Microbiology, University of Bari, 70126 Bari, Italy *These authors contributed equally to work †Corresponding author: Evan E. Eichler, PhD University of Washington School of Medicine Howard Hughes Medical Institute Box 355065 Foege S413C, 1705 NE Pacific St. Seattle, WA 98195 E-mail: [email protected] 1 Downloaded from genome.cshlp.org on October 4, 2021 - Published by Cold Spring Harbor Laboratory Press Girirajan et al ABSTRACT The gibbon genome exhibits extensive karyotypic diversity with an increased rate of chromosomal rearrangements during evolution. In an effort to understand the mechanistic origin and implications of these rearrangement events, we sequenced 24 synteny breakpoint regions in the white-cheeked gibbon (Nomascus leucogenys, NLE) in the form of high-quality BAC insert sequences (4.2 Mbp). While there is a significant deficit of breakpoints in genes, we identified seven human gene structures, involved in signaling pathways (DEPDC4, GNG10), phospholipid metabolism (ENPP5, PLSCR2), β-oxidation (ECH1), cellular structure and transport (HEATR4), and transcription (GIOT1), that have been disrupted in the NLE gibbon lineage. -
Table S2.A-B. Differentially Expressed Genes Following Activation of OGR1 by Acidic Ph in Mouse Peritoneal Macrophages Ph 6.7 24 H
Table S2.A-B. Differentially expressed genes following activation of OGR1 by acidic pH in mouse peritoneal macrophages pH 6.7 24 h. A. Gene List, including gene process B. Complete Table (Excel). Rank Symbol Full name Involved in: WT/KO (Reference: Gene Card, NCBI, JAX, Uniprot, Ratio unless otherwise indicated) 1. Cyp11a1 Cholesterol side chain cleavage Cholesterol, lipid or steroid metabolism. enzyme, mitochondrial (Cytochrome Catalyses the side-chain cleavage reaction of P450 11A1) cholesterol to pregnenolone. 2. Sparc Secreted acidic cysteine rich Cell adhesion, wound healing, ECM glycoprotein (Osteonectin, Basement interactions, bone mineralization. Activates membrane protein 40 (BM-40)) production and activity of matrix metalloproteinases. 3. Tpsb2 Tryptase beta-2 or tryptase II (trypsin- Inflammatory response, proteolysis. like serine protease) 4. Inhba Inhibin Beta A or Activin beta-A chain Immune response and mediators of inflammation and tissue repair.2-5 5. Cpe Carboxypeptidase E Insulin processing, proteolysis. 6. Igfbp7 Insulin-like growth factor-binding Stimulates prostacyclin (PGI2) production and protein 7 cell adhesion. Induced by retinoic acid. 7. Clu Clusterin Chaperone-mediated protein folding, positive regulation of NF-κB transcription factor activity. Protects cells against apoptosis and cytolysis by complement. Promotes proteasomal degradation of COMMD1 and IKBKB. 8. Cma1 Chymase 1 Cellular response to glucose stimulus, interleukin-1 beta biosynthetic process. Possible roles: vasoactive peptide generation, extracellular matrix degradation. 9. Sfrp4 Secreted frizzled-related protein 4 Negative regulation of Wnt signalling. Increases apoptosis during ovulation. Phosphaturic effects by specifically inhibiting sodium-dependent phosphate uptake. 10. Ephx2 Bifunctional epoxide hydrolase Cholesterol homeostasis, xenobiotic metabolism by degrading potentially toxic epoxides. -
Inter-Chromosomal Variation in the Pattern of Human Population Genetic Structure Tesfaye M
PRIMARY RESEARCH Inter-chromosomal variation in the pattern of human population genetic structure Tesfaye M. Baye* Cincinnati Children’s Hospital Medical Center, Division of Asthma Research, Department of Pediatrics, University of Cincinnati, 3333 Burnet Avenue, Cincinnati, OH 45229, USA *Correspondence to: Tel: þ1 513 803 2766; Fax: þ1 513 636 1657; E-mail: [email protected] Date received (in revised form): 1st March 2011 Abstract Emerging technologies now make it possible to genotype hundreds of thousands of genetic variations in individuals, across the genome. The study of loci at finer scales will facilitate the understanding of genetic variation at genomic and geographic levels. We examined global and chromosomal variations across HapMap populations using 3.7 million single nucleotide polymorphisms to search for the most stratified genomic regions of human populations and linked these regions to ontological annotation and functional network analysis. To achieve this, we used five complementary statistical and genetic network procedures: principal component (PC), cluster, discriminant, fix- ation index (FST) and network/pathway analyses. At the global level, the first two PC scores were sufficient to account for major population structure; however, chromosomal level analysis detected subtle forms of population structure within continental populations, and as many as 31 PCs were required to classify individuals into homo- geneous groups. Using recommended population ancestry differentiation measures, a total of 126 regions of the genome were catalogued. Gene ontology and networks analyses revealed that these regions included the genes encoding oculocutaneous albinism II (OCA2), hect domain and RLD 2 (HERC2), ectodysplasin A receptor (EDAR) and solute carrier family 45, member 2 (SLC45A2). -
Regulation and Function of Ptf1a in the Developing Nervous System
REGULATION AND FUNCTION OF PTF1A IN THE DEVELOPING NERVOUS SYSTEM APPROVED BY SUPERVISORY COMMITTEE Jane E. Johnson, Ph.D. Raymond J. MacDonald, Ph.D. Ondine Cleaver, Ph.D. Steven L. McKnight, Ph.D. DEDICATION Work of this nature never occurs in a vacuum and would be utterly impossible without the contributions of a great many. I would like to thank my fellow lab members and collaborators, both past and present, for all of their help over the past several years, my thesis committee for their guidance and encouragement, and of course Jane for giving me every opportunity to succeed. To my friends, family, and my dear wife Maria, your love and support have made all of this possible. REGULATION AND FUNCTION OF PTF1A IN THE DEVELOPING NERVOUS SYSTEM by DAVID MILES MEREDITH DISSERTATION Presented to the Faculty of the Graduate School of Biomedical Sciences The University of Texas Southwestern Medical Center at Dallas In Partial Fulfillment of the Requirements For the Degree of DOCTOR OF PHILOSOPHY The University of Texas Southwestern Medical Center at Dallas Dallas, Texas May, 2012 REGULATION AND FUNCTION OF PTF1A IN THE DEVELOPING NERVOUS SYSTEM DAVID MILES MEREDITH The University of Texas Southwestern Medical Center at Dallas, 2012 JANE E. JOHNSON, Ph.D. Basic helix-loop-helix transcription factors serve many roles in development, including regulation of neurogenesis. Many of these factors are activated in naïve neural progenitors and function to promote neuronal differentiation and cell-type specification. Ptf1a is a basic helix-loop-helix protein that is required for proper inhibitory neuron formation in several regions of the developing nervous system, including the spinal cord, cerebellum, retina, and hypothalamus. -
Pancreatic Progenitor Cells in Mice
PANCREATIC PROGENITOR CELLS IN MICE by Megan Hussey Cleveland A dissertation submitted to Johns Hopkins University in conformity with the requirements for the degree of Doctor of Philosophy Baltimore, Maryland July, 2014 Abstract We generated a novel transgenic mouse expressing a tdTomato fluorophore, as well as a Strep/Flag-tagged version of Ptf1a from the native Ptf1a locus. I crossed this mouse line with the well-characterized Pdx1-GFP mouse, which enabled us to visualize and sort for cells of the “tip” and “trunk” progenitor domains of the mouse pancreas. The main goal of our project was to identify previously unrecognized early transcriptional targets of Ptf1at and Pdx1. I isolated early E11.5 epithelial progenitors as well as later E13.5 tip and trunk progenitors using FACS and analyzed these populations via the GeneChip Mouse Gene 1.0 ST Array. After comparison of microarray data between tip and trunk cells, differentially- expressed genes were identified, with a focus on transcription factors, with validation by in situ hybridization. Two transcription factors, Ascl2 and Lhx1, were initially identified that had no previously known role in pancreas development, and were shown by ISH to be expressed in the expected domain of the pancreas. I performed prelimary functional studies on these two transcription factors, using lentiviral shRNAs for knock down in dorsal pancreatic bud culture. ii Acknowledgments First, I would like to thank Steven Leach for accepting me into his lab and for the 7 years of mentorship he has provided. I would like to thank Sandy Muscelli, Dave Valle, Kirby Smith, Andy McCallion and the rest of the Human Genetics department for giving me the opportunity to pursue my Ph.D. -
Downloaded from Here
bioRxiv preprint doi: https://doi.org/10.1101/017566; this version posted November 19, 2015. 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 1 Testing for ancient selection using cross-population allele 2 frequency differentiation 1;∗ 3 Fernando Racimo 4 1 Department of Integrative Biology, University of California, Berkeley, CA, USA 5 ∗ E-mail: [email protected] 6 1 Abstract 7 A powerful way to detect selection in a population is by modeling local allele frequency changes in a 8 particular region of the genome under scenarios of selection and neutrality, and finding which model is 9 most compatible with the data. Chen et al. [2010] developed a composite likelihood method called XP- 10 CLR that uses an outgroup population to detect departures from neutrality which could be compatible 11 with hard or soft sweeps, at linked sites near a beneficial allele. However, this method is most sensitive 12 to recent selection and may miss selective events that happened a long time ago. To overcome this, 13 we developed an extension of XP-CLR that jointly models the behavior of a selected allele in a three- 14 population tree. Our method - called 3P-CLR - outperforms XP-CLR when testing for selection that 15 occurred before two populations split from each other, and can distinguish between those events and 16 events that occurred specifically in each of the populations after the split. -
Notch Controls Multiple Pancreatic Cell Fate Regulators Through Direct Hes1-Mediated Repression
bioRxiv preprint doi: https://doi.org/10.1101/336305; this version posted June 1, 2018. 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. Notch Controls Multiple Pancreatic Cell Fate Regulators Through Direct Hes1-mediated Repression by Kristian H. de Lichtenberg1, Philip A. Seymour1, Mette C. Jørgensen1, Yung-Hae Kim1, Anne Grapin-Botton1, Mark A. Magnuson2, Nikolina Nakic3,4, Jorge Ferrer3, Palle Serup1* 1 Novo Nordisk Foundation Center for Stem Cell Biology (Danstem), University of Copenhagen, Denmark. 2 Center for Stem Cell Biology, Vanderbilt University, Tennessee, USA. 3 Section on Epigenetics and Disease, Imperial College London, UK. 4 Current Address: GSK, Stevenage, UK. *Corresponding Author: [email protected] 1 bioRxiv preprint doi: https://doi.org/10.1101/336305; this version posted June 1, 2018. 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. Abstract Notch signaling and its effector Hes1 regulate multiple cell fate choices in the developing pancreas, but few direct target genes are known. Here we use transcriptome analyses combined with chromatin immunoprecipitation with next-generation sequencing (ChIP-seq) to identify direct target genes of Hes1. ChIP-seq analysis of endogenous Hes1 in 266-6 cells, a model of multipotent pancreatic progenitor cells, revealed high-confidence peaks associated with 354 genes. Among these were genes important for tip/trunk segregation such as Ptf1a and Nkx6-1, genes involved in endocrine differentiation such as Insm1 and Dll4, and genes encoding non-pancreatic basic-Helic-Loop-Helix (bHLH) factors such as Neurog2 and Ascl1. -
Graded Levels of Ptf1a Differentially Regulate Endocrine and Exocrine Fates in the Developing Pancreas
Downloaded from genesdev.cshlp.org on October 8, 2021 - Published by Cold Spring Harbor Laboratory Press RESEARCH COMMUNICATION factor Ptf1a is required for exocrine differentiation Graded levels of Ptf1a (Krapp et al. 1998). Ptf1a lineage tracing has also revealed differentially regulate an earlier role for Ptf1a in allocating foregut endodermal cells to the pancreas, implicating Ptf1a in pancreas speci- endocrine and exocrine fates fication. This finding is consistent with the observation in the developing pancreas that Ptf1a is expressed in precursors of all pancreatic cell types, including endocrine cells (Kawaguchi et al. 2002). P. Duc Si Dong,1,4 Elayne Provost,2 Importantly, it is not specifically known how Ptf1a regu- 2 1,3 lates endocrine development. The PTF1 complex binds Steven D. Leach, and Didier Y.R. Stainier directly to the promoters of terminal exocrine differen- 1Department of Biochemistry and Biophysics, University of tiation genes such as Trypsin and Elastase, indicating California, San Francisco, San Francisco, California 94158, that Ptf1a is also involved in exocrine cell differentiation USA; 2Department of Surgery, Johns Hopkins Medical (Cockell et al. 1989; Krapp et al. 1996). Furthermore, Institutions, Baltimore, Maryland 21287, USA Ptf1a interacts differentially with the vertebrate Sup- pressor of Hairless homologs, Rbpj and Rbpjl, to regulate The mechanisms regulating pancreatic endocrine versus pancreas specification and exocrine differentiation, re- exocrine fate are not well defined. By analyzing the ef- spectively (Masui et al. 2007). Lineage tracing of cells fects of Ptf1a partial loss of function, we uncovered novel expressing Carboxypeptidase A1, a Ptf1a target, has shown that endocrine and exocrine cells can originate roles for this transcription factor in determining pancre- from a common progenitor in the specified pancreas ptf1a atic fates. -
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 ......................................................