Evidence for Positive Selection and Population Structure at the Human MAO-A Gene
Total Page:16
File Type:pdf, Size:1020Kb

Load more
Recommended publications
-
Biology of Human Variation Fall 2014
Anthropology 2110 Biology of Human Variation Fall 2014 Professor: Dr. Tamara Varney Location: AT1010 Lecture time: Tues 7-10 Phone: 807-343-8204 Office: Braun Building 2001D Email: [email protected] Office Hours: Thurs 9-11am am until Oct 15 then by appointment**(if its more convenient feel free to set an appointment time) OR you can phone, email or drop in anytime to see if I am free – just be prepared to come at another time if I am busy with something I cannot interrupt I cannot guarantee that I will respond in a timely fashion if messages are left on my voice mail rather than email and students should NOT expect less than 24 hour turnaround time to email messages. Please DO NOT assume that your message, voice or email, has been received unless you receive an acknowledgement. Course Description: This course focuses on human microevolution. Topics include evolutionary theory, the genetic background of human variation, the distribution of human variation, human adaptability, and the role of disease and other influences on human evolution. Required Textbook: (available at the University Bookstore) Mielke JH, Konigsberg LW and Relethford JH. 2011. Human Biological Variation. 2nd Edition. Oxford University Press. ISBN 13: 978-0-19-538740-7 Also see the course Desire2Learn (D2L) site (look in MyCourseLinks on the LU website) for additional resources. Evaluation: Your final grade will be based on: Term Test 1 25% Oct 27 Term Test 2 30% Nov 18 Final Exam 45% Final examination period – Dec 9-19 **Note exam contingency date is Dec 20. Please note that Fri, November 6, 2015 is the last date for withdrawal without academic penalty from this course. -
S41467-020-18249-3.Pdf
ARTICLE https://doi.org/10.1038/s41467-020-18249-3 OPEN Pharmacologically reversible zonation-dependent endothelial cell transcriptomic changes with neurodegenerative disease associations in the aged brain Lei Zhao1,2,17, Zhongqi Li 1,2,17, Joaquim S. L. Vong2,3,17, Xinyi Chen1,2, Hei-Ming Lai1,2,4,5,6, Leo Y. C. Yan1,2, Junzhe Huang1,2, Samuel K. H. Sy1,2,7, Xiaoyu Tian 8, Yu Huang 8, Ho Yin Edwin Chan5,9, Hon-Cheong So6,8, ✉ ✉ Wai-Lung Ng 10, Yamei Tang11, Wei-Jye Lin12,13, Vincent C. T. Mok1,5,6,14,15 &HoKo 1,2,4,5,6,8,14,16 1234567890():,; The molecular signatures of cells in the brain have been revealed in unprecedented detail, yet the ageing-associated genome-wide expression changes that may contribute to neurovas- cular dysfunction in neurodegenerative diseases remain elusive. Here, we report zonation- dependent transcriptomic changes in aged mouse brain endothelial cells (ECs), which pro- minently implicate altered immune/cytokine signaling in ECs of all vascular segments, and functional changes impacting the blood–brain barrier (BBB) and glucose/energy metabolism especially in capillary ECs (capECs). An overrepresentation of Alzheimer disease (AD) GWAS genes is evident among the human orthologs of the differentially expressed genes of aged capECs, while comparative analysis revealed a subset of concordantly downregulated, functionally important genes in human AD brains. Treatment with exenatide, a glucagon-like peptide-1 receptor agonist, strongly reverses aged mouse brain EC transcriptomic changes and BBB leakage, with associated attenuation of microglial priming. We thus revealed tran- scriptomic alterations underlying brain EC ageing that are complex yet pharmacologically reversible. -
Sequence Variations in the Public Human Genome Data Reflect a Bottlenecked Population History
Sequence variations in the public human genome data reflect a bottlenecked population history Gabor Marth*†, Greg Schuler*, Raymond Yeh‡, Ruth Davenport§, Richa Agarwala*, Deanna Church*, Sarah Wheelan*¶, Jonathan Baker*, Ming Ward*, Michael Kholodov*, Lon Phan*, Eva Czabarka*, Janos Murvai*, David Cutlerʈ, Stephen Wooding**, Alan Rogers**, Aravinda Chakravartiʈ, Henry C. Harpending**, Pui-Yan Kwok†,††, and Stephen T. Sherry*† *National Center for Biotechnology Information, National Institutes of Health, Bethesda, MD 20894; ‡Department of Genetics, Washington University School of Medicine, St. Louis, MO 63130; §Division of Internal Medicine, Washington University School of Medicine, St. Louis, MO 63130; ¶Department of Molecular Biology and Genetics and ʈMcKusick–Nathans Institute of Genetic Medicine, The Johns Hopkins University School of Medicine, Baltimore, MD 21205; **Department of Anthropology, University of Utah, Salt Lake City, UT 84112; and ††Cardiovascular Research Institute and Department of Dermatology, University of California, San Francisco, CA 94143 Contributed by Henry C. Harpending, November 5, 2002 Single-nucleotide polymorphisms (SNPs) constitute the great ma- (density) distribution of genomic sequence variations. To this jority of variations in the human genome, and as heritable variable end, we built a set of reagents (pairwise sequence alignments landmarks they are useful markers for disease mapping and re- and their corresponding sets of variation) by analyzing the solving population structure. Redundant coverage in overlaps of overlapping regions of large-insert clones sequenced as part of large-insert genomic clones, sequenced as part of the Human the human genome project. These data provided marker Genome Project, comprises a quarter of the genome, and it is density observations grouped by overlap fragment length. -
Methods to Detect Selection in Populations with Applications to the Human
P1: FQP/VEN July 6, 2000 12:24 Annual Reviews AR104-19 Annu. Rev. Genomics Hum. Genet. 2000. 01:539–59 Copyright c 2000 by Annual Reviews. All rights reserved METHODS TO DETECT SELECTION IN POPULATIONS WITH APPLICATIONS TO THE HUMAN Martin Kreitman Department of Ecology and Evolution, University of Chicago, Chicago, Illinois 60637; e-mail: [email protected] Key Words natural selection, genetic drift, polymorphism, molecular evolution ■ Abstract The development of statistical tests of natural selection at the DNA level in population samples has been ongoing for the past 13 years. The current state of the field is reviewed, and the available tests of selection are described. All tests use predictions from the theory of neutrally evolving sites as a null hypothesis. Departures from equilibrium-neutral expectations can indicate the presence of natural selection acting either at one or more of the sites under investigation or at a sufficiently tightly linked site. Complications can arise in the interpretation of departures from neutrality if populations are not at equilibrium for mutation and genetic drift or if populations are subdivided, both of which are likely scenarios for humans. Attempts to understand the nonequilibrium configuration of silent polymorphism in human mitochondrial DNA illustrate the difficulty of distinguishing between selection and alternative demographic hypotheses. The range of plausible alternatives to selection will become better defined, however, as additional population genetic data sets become available, allowing better null models to be constructed. INTRODUCTION Kimura’s immensely influential formulation of the neutral theory of molecular evolution, which came in 1968, was based primarily on an argument about the magnitude of the genetic load that would be imposed by positive selection if it were the only driving force in protein evolution (56). -
Human DNA Sequences: More Variation and Less Race
AMERICAN JOURNAL OF PHYSICAL ANTHROPOLOGY 139:23–34 (2009) Human DNA Sequences: More Variation and Less Race Jeffrey C. Long,1* Jie Li,1 and Meghan E. Healy2 1Department of Human Genetics, University of Michigan, Ann Arbor, MI 48109-5618 2Department of Anthropology, University of New Mexico, Albuquerque, NM 87131 KEY WORDS race; DNA sequence; short tandem repeat; diversity; hierachical models ABSTRACT Interest in genetic diversity within and sity is one of nested subsets, such that the diversity in between human populations as a way to answer questions non-Sub-Saharan African populations is essentially a sub- about race has intensified in light of recent advances in set of the diversity found in Sub-Saharan African popula- genome technology. The purpose of this article is to apply tions. The actual pattern of DNA diversity creates some a method of generalized hierarchical modeling to two unsettling problems for using race as meaningful genetic DNA data sets. The first data set consists of a small sam- categories. For example, the pattern of DNA diversity ple of individuals (n 5 32 total, from eight populations) implies that some populations belong to more than one who have been fully resequenced for 63 loci that encode a race (e.g., Europeans), whereas other populations do not total of 38,534 base pairs. The second data set consists of belong to any race at all (e.g., Sub-Saharan Africans). As a large sample of individuals (n 5 928 total, from 46 popu- Frank Livingstone noted long ago, the Linnean classifica- lations) who have been genotyped at 580 loci that encode tion system cannot accommodate this pattern because short tandem repeats. -
Effect of Cigarette Smoke on DNA Methylation and Lung Function
de Vries et al. Respiratory Research (2018) 19:212 https://doi.org/10.1186/s12931-018-0904-y RESEARCH Open Access From blood to lung tissue: effect of cigarette smoke on DNA methylation and lung function Maaike de Vries1,2* , Diana A van der Plaat1,2, Ivana Nedeljkovic3, Rikst Nynke Verkaik-Schakel4, Wierd Kooistra2,5, Najaf Amin3, Cornelia M van Duijn3, Corry-Anke Brandsma2,5, Cleo C van Diemen6, Judith M Vonk1,2 and H Marike Boezen1,2 Abstract Background: Genetic and environmental factors play a role in the development of COPD. The epigenome, and more specifically DNA methylation, is recognized as important link between these factors. We postulate that DNA methylation is one of the routes by which cigarette smoke influences the development of COPD. In this study, we aim to identify CpG-sites that are associated with cigarette smoke exposure and lung function levels in whole blood and validate these CpG-sites in lung tissue. Methods: The association between pack years and DNA methylation was studied genome-wide in 658 current smokers with >5 pack years using robust linear regression analysis. Using mediation analysis, we subsequently selected the CpG-sites that were also associated with lung function levels. Significant CpG-sites were validated in lung tissue with pyrosequencing and expression quantitative trait methylation (eQTM) analysis was performed to investigate the association between DNA methylation and gene expression. Results: 15 CpG-sites were significantly associated with pack years and 10 of these were additionally associated with lung function levels. We validated 5 CpG-sites in lung tissue and found several associations between DNA methylation and gene expression. -
Supplemental Information Evolutionary Diversification of Protein-Protein Interactions by Interface Add-Ons
Supplemental Information Classification: BIOLOGICAL SCIENCES – Biochemistry Evolutionary diversification of protein-protein interactions by interface add-ons Maximilian G. Plach1, Florian Semmelmann1, Florian Busch2, Markus Busch1, Leonhard Heizinger1, Vicki H. Wysocki2, Rainer Merkl1*, Reinhard Sterner1* 1 Institute of Biophysics and Physical Biochemistry University of Regensburg, D-93040 Regensburg, Germany 2 Department of Chemistry and Biochemistry The Ohio State University, 460 West 12th Avenue, OH-43210 Columbus, USA *Corresponding authors: Rainer Merkl: +49-941-3086; [email protected] Reinhard Sterner: +49-941 943 3015; [email protected] SI - 1 SI Materials and Methods Materials Glutamate dehydrogenase was purchased from Roche. Chorismate was purchased from Sigma Aldrich as the barium salt and barium ions were precipitated by the addition of a slight excess of sodium sulfate. All other chemical reagents were purchased from Sigma Aldrich in analytical or HPLC grade and used without further purification. Survey of interface add-ons in heteromeric protein complexes The initial dataset contained 1739 heteromeric bacterial protein complex structures deposited in PDB that were devoid of non-protein macromolecules and had subunit stoichiometries of AB, A2B2, A3B3, A4B4, A6B6, ABC, and A2B2C2. To avoid redundancy, identical proteins crystallized under different experimental conditions were excluded, leaving a subset of 918 complex structures. The InterPro dataset distinguishes protein families, which represent groups of homologous proteins at different levels of functional and structural similarity, and domains, which often occur in numerous non-homologous proteins (1). We thus removed all complex structures whose subunits are only associated with “domain”, “repeat”, and “site” entries and selected those that were assigned to highest-level InterPro families. -
Bio-Skin-Color-Transcript.Pdf
[crickets chirp] [cymbal plays] [chime plays] [music plays] [JABLONSKI (narrated):] Human brains are gray. Human blood is red. Our bones are off-white. Doesn’t matter where you’re born or to whom. But human skin is different. [music plays] Some of us have rich dark brown skin; some of us have pinkish white skin. Most of us are somewhere in between. For the longest time, why this variation exists was a real scientific mystery … that opened the door for some to invest this biological trait with moral value, and then use that to justify the suffering of others. [elephant trumpets] But biological traits aren’t good or bad. They’re features that have evolved because they enhance an organism’s odds of surviving and passing on its genes. [JABLONSKI:] Like other animal traits, the sepia rainbow of human skin color evolved through natural selection. Now, thanks to advances in anthropology and genetics, exactly how and why it did is no longer a mystery. [music plays] [background discussion] [JABLONSKI:] Biological anthropologists like myself spend our lives studying how humans evolved, and why we differ from one another physically. [music plays] [JABLONSKI (narrated):] Our skin provides one of the most visible markers of human variability. It’s something that sets us apart from our closest animal relatives. Under their dark fur, chimpanzees have pale skin, and millions of years ago that was probably also the case for the primates that were our common ancestors. So where did humanity’s range of skin colors come from? From physics we know that the color of any object comes from the wavelengths of light that it reflects back to an observer’s eye. -
An Ontology Driven Knowledge Discovery Framework for Dynamic
An Ontology Driven Knowledge Discovery Framework for Dynamic Domains: Methodology, Tools and a Biomedical Case. Paulo Gottgtroy A thesis submitted to Auckland University of Technology in fulfilment of the requirements for the degree of Doctor of Philosophy (PhD) 2010 School of Computing and Mathematical Sciences Primary Supervisor: Prof. Nikola Kasabov Co-supervisor: Prof. Stephen MacDonell i Table of Contents INTRODUCTION ....................................................................................................................... 1 1.1. INTRODUCTION ............................................................................................................. 1 1.2. RESEARCH QUESTIONS .................................................................................................. 5 1.3. RESEARCH METHODOLOGY .......................................................................................... 8 1.3.1. Detailed Research Process ............................................................................... 12 1.4. SCOPE OF THE RESEARCH ............................................................................................ 16 1.4.1. Implementation Environment ........................................................................... 19 1.4.2. Requirements Identification .............................................................................. 23 1.5. SUMMARY .................................................................................................................. 28 CHAPTER 2 RESEARCH LITERATURE REVIEW ...................................................... -
Homo Sapiens
Global landscape of recent inferred Darwinian selection for Homo sapiens Eric T. Wang*†, Greg Kodama‡, Pierre Baldi*†‡, and Robert K. Moyzis*†§ *Department of Biological Chemistry, College of Medicine, ‡Donald Bren School of Information and Computer Sciences, and †Institute of Genomics and Bioinformatics, University of California, Irvine, CA 92697 Communicated by Douglas C. Wallace, University of California, Irvine, CA, November 9, 2005 (received for review June 8, 2005) By using the 1.6 million single-nucleotide polymorphism (SNP) F test statistics, positive scores are indicative of unusually high genotype data set from Perlegen Sciences [Hinds, D. A., Stuve, L. L., heterozygosity within the data set. Additionally, these tests Nilsen, G. B., Halperin, E., Eskin, E., Ballinger, D. G., Frazer, K. A. & usually do not take distance between variable sites into consid- Cox, D. R. (2005) Science 307, 1072–1079], a probabilistic search for eration and rely heavily on statistics obtained from rare muta- the landscape exhibited by positive Darwinian selection was con- tional events. The selection criterion for the Perlegen and ducted. By sorting each high-frequency allele by homozygosity, we HapMap genotyping efforts, however, was the high heterozy- search for the expected decay of adjacent SNP linkage disequilib- gosity and equal spacing of SNPs (1, 2). Hence, these data sets rium (LD) at recently selected alleles, eliminating the need for have high ascertainment bias. Using tests that rely on heterozy- inferring haplotype. We designate this approach the LD decay gosity and frequency of rare mutations to infer selection on such (LDD) test. By these criteria, 1.6% of Perlegen SNPs were found to biased data sets should be largely meaningless. -
Missing Proteins in Chromosome 16
Missing proteins in Chromosome 16 - Spanish HPP Manuel Fuentes1, Noelia Dasilva1, Felipe Clemente2, María Luisa Hernáez2, Paula Díez1, Maria Gonzalez-Gonzalez1, Alberto Orfao1, Felix Elortza5, Fernando Corrales4, Juan Pablo Albar3, Concha Gil2. 1Cancer Research Center. University of Salamanca-CSIC, IBSAL. Campus Miguel de Unamuno s/n. 37007 Salamanca. Spain. 2ProteoRed-ISCIII. Dpt. Microbiology & Proteomics Unit. University Complutense. Madrid. Spain. 3 ProteoRed-ISCIII. National Center of Biotechnology. CSIC. Madrid. Spain. 4ProteoRed-ISCIII. Center for Applied Medical Research (CIMA), Spain. 5ProteoRed-ISCIII. CIC bioGUNE. Bilbao. Spain. AIM In the scope of the HPP project, there is a special situation for the proteins that had not spectral and/or expression evidence, those are called "Unknown proteins".These proteins must be studied specifically to get enough information to build MRM quantitation methods. The Spanish HPP consortium has developed a specific protocol for unknown proteins in order to get MSMS information for the MRM method. MATERIALS AND METHODS Clones and plasmids All the clones used are from pANT7_cGST clone collection distributed by Plasmid repository at Arizona State University Biodesign Institute. Each clone contains an in-frame fused C-terminal GST tag. Each bacterial clone was grown overnight in 5 mL of Luria broth with 100 µg/mL ampicillin. Plasmid DNA was extracted using Mini- Prep Kit from Promega, following manufacture instructions. All plasmids were sequence to confirm the identity of the insert. DNA isolation and sequence verification Protein IVVT production Proteins were synthesized from plasmid DNA using Human In vitro Protein Expression kit (Thermo) following manufacture s protocol with a few minimal modifications in order to adapt for 1.5 mL eppendorf tubes. -
The Macrocyclizing Protease Butelase 1 Remains Auto-Catalytic and Reveals the Structural Basis for Ligase Activity
bioRxiv preprint doi: https://doi.org/10.1101/380295; this version posted October 21, 2018. 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. Amy M. James1,2,†,‡, Joel Haywood1,2,†, Julie Leroux1,2, Katarzyna Ignasiak1, Alysha G. Elliott3, Jason W. Schmidberger1, Mark F. Fisher1,2, Samuel G. Nonis1,2, Ricarda Fenske2, Charles S. Bond1, and Joshua S. Mylne1,2,* The University of Western Australia, 1 School of Molecular Sciences & 2 The ARC Centre of Excellence in Plant Energy Biology, 35 Stirling Highway, Crawley, Perth 6009, Australia; 3 The University of Queensland, Institute for Molecular Bioscience, St Lucia, Brisbane, QLD 4072, Australia † Equal author contribution ‡ Current address: University of Bristol, Life Sciences Building, 24 Tyndall Avenue, Bristol, BS8 1TQ, UK * Address correspondence to [email protected]. The macrocyclizing protease butelase 1 remains auto- catalytic and reveals the structural basis for ligase activity Short title: Cleavage and ligation by butelase 1 bioRxiv preprint doi: https://doi.org/10.1101/380295; this version posted October 21, 2018. 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. Abstract Plant asparaginyl endopeptidases (AEPs) are expressed as inactive zymogens that perform seed storage protein maturation upon cleavage dependent auto-activation in the low pH environment of storage vacuoles.