Breakpoint Determination of X;Autosome Balanced Translocations in Four Patients with Premature Ovarian Failure
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Exceptional Conservation of Horse–Human Gene Order on X Chromosome Revealed by High-Resolution Radiation Hybrid Mapping
Exceptional conservation of horse–human gene order on X chromosome revealed by high-resolution radiation hybrid mapping Terje Raudsepp*†, Eun-Joon Lee*†, Srinivas R. Kata‡, Candice Brinkmeyer*, James R. Mickelson§, Loren C. Skow*, James E. Womack‡, and Bhanu P. Chowdhary*¶ʈ *Department of Veterinary Anatomy and Public Health, ‡Department of Veterinary Pathobiology, College of Veterinary Medicine, and ¶Department of Animal Science, College of Agriculture and Life Science, Texas A&M University, College Station, TX 77843; and §Department of Veterinary Pathobiology, University of Minnesota, 295f AS͞VM, St. Paul, MN 55108 Contributed by James E. Womack, December 30, 2003 Development of a dense map of the horse genome is key to efforts ciated with the traits, once they are mapped by genetic linkage aimed at identifying genes controlling health, reproduction, and analyses with highly polymorphic markers. performance. We herein report a high-resolution gene map of the The X chromosome is the most conserved mammalian chro- horse (Equus caballus) X chromosome (ECAX) generated by devel- mosome (18, 19). Extensive comparisons of structure, organi- oping and typing 116 gene-specific and 12 short tandem repeat zation, and gene content of this chromosome in evolutionarily -markers on the 5,000-rad horse ؋ hamster whole-genome radia- diverse mammals have revealed a remarkable degree of conser tion hybrid panel and mapping 29 gene loci by fluorescence in situ vation (20–22). Until now, the chromosome has been best hybridization. The human X chromosome sequence was used as a studied in humans and mice, where the focus of research has template to select genes at 1-Mb intervals to develop equine been the intriguing patterns of X inactivation and the involve- orthologs. -
Screening and Identification of Key Biomarkers in Clear Cell Renal Cell Carcinoma Based on Bioinformatics Analysis
bioRxiv preprint doi: https://doi.org/10.1101/2020.12.21.423889; this version posted December 23, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder.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. Screening and identification of key biomarkers in clear cell renal cell carcinoma based on bioinformatics analysis Basavaraj Vastrad1, Chanabasayya Vastrad*2 , Iranna Kotturshetti 1. Department of Biochemistry, Basaveshwar College of Pharmacy, Gadag, Karnataka 582103, India. 2. Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karanataka, India. 3. Department of Ayurveda, Rajiv Gandhi Education Society`s Ayurvedic Medical College, Ron, Karnataka 562209, India. * Chanabasayya Vastrad [email protected] Ph: +919480073398 Chanabasava Nilaya, Bharthinagar, Dharwad 580001 , Karanataka, India bioRxiv preprint doi: https://doi.org/10.1101/2020.12.21.423889; this version posted December 23, 2020. 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 Clear cell renal cell carcinoma (ccRCC) is one of the most common types of malignancy of the urinary system. The pathogenesis and effective diagnosis of ccRCC have become popular topics for research in the previous decade. In the current study, an integrated bioinformatics analysis was performed to identify core genes associated in ccRCC. An expression dataset (GSE105261) was downloaded from the Gene Expression Omnibus database, and included 26 ccRCC and 9 normal kideny samples. Assessment of the microarray dataset led to the recognition of differentially expressed genes (DEGs), which was subsequently used for pathway and gene ontology (GO) enrichment analysis. -
Snapshot: Formins Christian Baarlink, Dominique Brandt, and Robert Grosse University of Marburg, Marburg 35032, Germany
SnapShot: Formins Christian Baarlink, Dominique Brandt, and Robert Grosse University of Marburg, Marburg 35032, Germany Formin Regulators Localization Cellular Function Disease Association DIAPH1/DIA1 RhoA, RhoC Cell cortex, Polarized cell migration, microtubule stabilization, Autosomal-dominant nonsyndromic deafness (DFNA1), myeloproliferative (mDia1) phagocytic cup, phagocytosis, axon elongation defects, defects in T lymphocyte traffi cking and proliferation, tumor cell mitotic spindle invasion, defects in natural killer lymphocyte function DIAPH2 Cdc42 Kinetochore Stable microtubule attachment to kinetochore for Premature ovarian failure (mDia3) chromosome alignment DIAPH3 Rif, Cdc42, Filopodia, Filopodia formation, removing the nucleus from Increased chromosomal deletion of gene locus in metastatic tumors (mDia2) Rac, RhoB, endosomes erythroblast, endosome motility, microtubule DIP* stabilization FMNL1 (FRLα) Cdc42 Cell cortex, Phagocytosis, T cell polarity Overexpression is linked to leukemia and non-Hodgkin lymphoma microtubule- organizing center FMNL2/FRL3/ RhoC ND Cell motility Upregulated in metastatic colorectal cancer, chromosomal deletion is FHOD2 associated with mental retardation FMNL3/FRL2 Constituently Stress fi bers ND ND active DAAM1 Dishevelled Cell cortex Planar cell polarity ND DAAM2 ND ND ND Overexpressed in schizophrenia patients Human (Mouse) FHOD1 ROCK Stress fi bers Cell motility FHOD3 ND Nestin, sarcomere Organizing sarcomeres in striated muscle cells Single-nucleotide polymorphisms associated with type 1 diabetes -
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. -
Genomics and Its Impact on Science and Society: the Human Genome Project and Beyond
DOE/SC-0083 Genomics and Its Impact on Science and Society The Human Genome Project and Beyond U.S. Department of Energy Genome Research Programs: genomics.energy.gov A Primer ells are the fundamental working units of every living system. All the instructions Cneeded to direct their activities are contained within the chemical DNA (deoxyribonucleic acid). DNA from all organisms is made up of the same chemical and physical components. The DNA sequence is the particular side-by-side arrangement of bases along the DNA strand (e.g., ATTCCGGA). This order spells out the exact instruc- tions required to create a particular organism with protein complex its own unique traits. The genome is an organism’s complete set of DNA. Genomes vary widely in size: The smallest known genome for a free-living organism (a bac- terium) contains about 600,000 DNA base pairs, while human and mouse genomes have some From Genes to Proteins 3 billion (see p. 3). Except for mature red blood cells, all human cells contain a complete genome. Although genes get a lot of attention, the proteins DNA in each human cell is packaged into 46 chro- perform most life functions and even comprise the mosomes arranged into 23 pairs. Each chromosome is majority of cellular structures. Proteins are large, complex a physically separate molecule of DNA that ranges in molecules made up of chains of small chemical com- length from about 50 million to 250 million base pairs. pounds called amino acids. Chemical properties that A few types of major chromosomal abnormalities, distinguish the 20 different amino acids cause the including missing or extra copies or gross breaks and protein chains to fold up into specific three-dimensional rejoinings (translocations), can be detected by micro- structures that define their particular functions in the cell. -
Irs2 and Irs4 Synergize in Non-Leprb Neurons to Control Energy Balance and Glucose Homeostasis#.” Molecular Metabolism 3 (1): 55-63
Irs2 and Irs4 synergize in non- LepRb neurons to control energy balance and glucose homeostasis# The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters Citation Sadagurski, Marianna, X. Charlie Dong, Martin G. Myers, and Morris F. White. 2013. “Irs2 and Irs4 synergize in non-LepRb neurons to control energy balance and glucose homeostasis#.” Molecular Metabolism 3 (1): 55-63. doi:10.1016/j.molmet.2013.10.004. http:// dx.doi.org/10.1016/j.molmet.2013.10.004. Published Version doi:10.1016/j.molmet.2013.10.004 Citable link http://nrs.harvard.edu/urn-3:HUL.InstRepos:11879880 Terms of Use This article was downloaded from Harvard University’s DASH repository, and is made available under the terms and conditions applicable to Other Posted Material, as set forth at http:// nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of- use#LAA Original article Irs2 and Irs4 synergize in non-LepRb neurons to control energy balance and glucose homeostasis% Marianna Sadagurski 1,*,**, X. Charlie Dong 1,**,***, Martin G. Myers Jr.2,3, Morris F. White 1,**** ABSTRACT Insulin receptor substrates (Irs1, 2, 3 and Irs4) mediate the actions of insulin/IGF1 signaling. They have similar structure, but distinctly regulate development, growth, and metabolic homeostasis. Irs2 contributes to central metabolic sensing, partially by acting in leptin receptor (LepRb)- expressing neurons. Although Irs4 is largely restricted to the hypothalamus, its contribution to metabolic regulation is unclear because Irs4-null mice barely distinguishable from controls. We postulated that Irs2 and Irs4 synergize and complement each other in the brain. -
Defining Functional Interactions During Biogenesis of Epithelial Junctions
ARTICLE Received 11 Dec 2015 | Accepted 13 Oct 2016 | Published 6 Dec 2016 | Updated 5 Jan 2017 DOI: 10.1038/ncomms13542 OPEN Defining functional interactions during biogenesis of epithelial junctions J.C. Erasmus1,*, S. Bruche1,*,w, L. Pizarro1,2,*, N. Maimari1,3,*, T. Poggioli1,w, C. Tomlinson4,J.Lees5, I. Zalivina1,w, A. Wheeler1,w, A. Alberts6, A. Russo2 & V.M.M. Braga1 In spite of extensive recent progress, a comprehensive understanding of how actin cytoskeleton remodelling supports stable junctions remains to be established. Here we design a platform that integrates actin functions with optimized phenotypic clustering and identify new cytoskeletal proteins, their functional hierarchy and pathways that modulate E-cadherin adhesion. Depletion of EEF1A, an actin bundling protein, increases E-cadherin levels at junctions without a corresponding reinforcement of cell–cell contacts. This unexpected result reflects a more dynamic and mobile junctional actin in EEF1A-depleted cells. A partner for EEF1A in cadherin contact maintenance is the formin DIAPH2, which interacts with EEF1A. In contrast, depletion of either the endocytic regulator TRIP10 or the Rho GTPase activator VAV2 reduces E-cadherin levels at junctions. TRIP10 binds to and requires VAV2 function for its junctional localization. Overall, we present new conceptual insights on junction stabilization, which integrate known and novel pathways with impact for epithelial morphogenesis, homeostasis and diseases. 1 National Heart and Lung Institute, Faculty of Medicine, Imperial College London, London SW7 2AZ, UK. 2 Computing Department, Imperial College London, London SW7 2AZ, UK. 3 Bioengineering Department, Faculty of Engineering, Imperial College London, London SW7 2AZ, UK. 4 Department of Surgery & Cancer, Faculty of Medicine, Imperial College London, London SW7 2AZ, UK. -
Genetics and Genomics of Human Population Structure 20
Genetics and Genomics of Human Population Structure 20 Sohini Ramachandran , Hua Tang , Ryan N. Gutenkunst , and Carlos D. Bustamante Abstract Recent developments in sequencing technology have created a fl ood of new data on human genetic variation, and this data has yielded new insights into human popu- lation structure. Here we review what both early and more recent studies have taught us about human population structure and history. Early studies showed that most human genetic variation occurs within populations rather than between them, and that genetically related populations often cluster geographically. Recent studies based on much larger data sets have recapitulated these observations, but have also demonstrated that high-density genotyping allows individuals to be reliably assigned to their population of origin. In fact, for admixed individuals, even the ancestry of particular genomic regions can often be reli- ably inferred. Recent studies have also offered detailed information about the composition of specifi c populations from around the world, revealing how history has shaped their genetic makeup. We also briefl y review quantitative models of human genetic history, including the role natural selection has played in shaping human genetic variation. Contents 20.2.3 Characterizing Locus-Specifi c Ancestry ...................................................... 594 20.1 Introduction ............................................................... 590 20.3 Global Patterns of Human Population Structure ....... 595 20.1.1 Evolutionary Forces Shaping 20.3.1 The Apportionment of Human Human Genetic Variation ........................... 590 Diversity ..................................................... 595 20.2 Quantifying Population Structure ............................. 592 20.3.2 The History and Geography of Human Genes ......................................... 596 20.2.1 FST and Genetic Distance ............................ 592 20.2.2 Model-Based Clustering 20.3.3 Genetic Structure of Human Populations .. -
A Brief History of Human Disease Genetics
Review A brief history of human disease genetics https://doi.org/10.1038/s41586-019-1879-7 Melina Claussnitzer1,2,3, Judy H. Cho4,5,6, Rory Collins7,8, Nancy J. Cox9, Emmanouil T. Dermitzakis10,11, Matthew E. Hurles12, Sekar Kathiresan2,13,14, Eimear E. Kenny4,6,15, Received: 16 July 2019 Cecilia M. Lindgren2,16,17, Daniel G. MacArthur2,13,18, Kathryn N. North19,20, Sharon E. Plon21,22, Accepted: 13 November 2019 Heidi L. Rehm2,13,18,23, Neil Risch24, Charles N. Rotimi25, Jay Shendure26,27,28, Nicole Soranzo12,29 & Mark I. McCarthy17,30,31,32* Published online: 8 January 2020 A primary goal of human genetics is to identify DNA sequence variants that infuence biomedical traits, particularly those related to the onset and progression of human disease. Over the past 25 years, progress in realizing this objective has been transformed by advances in technology, foundational genomic resources and analytical tools, and by access to vast amounts of genotype and phenotype data. Genetic discoveries have substantially improved our understanding of the mechanisms responsible for many rare and common diseases and driven development of novel preventative and therapeutic strategies. Medical innovation will increasingly focus on delivering care tailored to individual patterns of genetic predisposition. medicine, which was previously restricted to a few specific clinical Anniversary indications, is poised to go mainstream. collection: This Review charts recent milestones in the history of human disease go.nature.com/ genetics and provides an opportunity to reflect on lessons learned by nature150 the human genetics community. We focus first on the long-standing division between genetic discovery efforts targeting rare variants with large effects and those seeking alleles that influence predispo- sition to common diseases. -
Snps) Distant from Xenobiotic Response Elements Can Modulate Aryl Hydrocarbon Receptor Function: SNP-Dependent CYP1A1 Induction S
Supplemental material to this article can be found at: http://dmd.aspetjournals.org/content/suppl/2018/07/06/dmd.118.082164.DC1 1521-009X/46/9/1372–1381$35.00 https://doi.org/10.1124/dmd.118.082164 DRUG METABOLISM AND DISPOSITION Drug Metab Dispos 46:1372–1381, September 2018 Copyright ª 2018 by The American Society for Pharmacology and Experimental Therapeutics Single Nucleotide Polymorphisms (SNPs) Distant from Xenobiotic Response Elements Can Modulate Aryl Hydrocarbon Receptor Function: SNP-Dependent CYP1A1 Induction s Duan Liu, Sisi Qin, Balmiki Ray,1 Krishna R. Kalari, Liewei Wang, and Richard M. Weinshilboum Division of Clinical Pharmacology, Department of Molecular Pharmacology and Experimental Therapeutics (D.L., S.Q., B.R., L.W., R.M.W.) and Division of Biomedical Statistics and Informatics, Department of Health Sciences Research (K.R.K.), Mayo Clinic, Rochester, Minnesota Received April 22, 2018; accepted June 28, 2018 ABSTRACT Downloaded from CYP1A1 expression can be upregulated by the ligand-activated aryl fashion. LCLs with the AA genotype displayed significantly higher hydrocarbon receptor (AHR). Based on prior observations with AHR-XRE binding and CYP1A1 mRNA expression after 3MC estrogen receptors and estrogen response elements, we tested treatment than did those with the GG genotype. Electrophoretic the hypothesis that single-nucleotide polymorphisms (SNPs) map- mobility shift assay (EMSA) showed that oligonucleotides with the ping hundreds of base pairs (bp) from xenobiotic response elements AA genotype displayed higher LCL nuclear extract binding after (XREs) might influence AHR binding and subsequent gene expres- 3MC treatment than did those with the GG genotype, and mass dmd.aspetjournals.org sion. -
Análise Integrativa De Perfis Transcricionais De Pacientes Com
UNIVERSIDADE DE SÃO PAULO FACULDADE DE MEDICINA DE RIBEIRÃO PRETO PROGRAMA DE PÓS-GRADUAÇÃO EM GENÉTICA ADRIANE FEIJÓ EVANGELISTA Análise integrativa de perfis transcricionais de pacientes com diabetes mellitus tipo 1, tipo 2 e gestacional, comparando-os com manifestações demográficas, clínicas, laboratoriais, fisiopatológicas e terapêuticas Ribeirão Preto – 2012 ADRIANE FEIJÓ EVANGELISTA Análise integrativa de perfis transcricionais de pacientes com diabetes mellitus tipo 1, tipo 2 e gestacional, comparando-os com manifestações demográficas, clínicas, laboratoriais, fisiopatológicas e terapêuticas Tese apresentada à Faculdade de Medicina de Ribeirão Preto da Universidade de São Paulo para obtenção do título de Doutor em Ciências. Área de Concentração: Genética Orientador: Prof. Dr. Eduardo Antonio Donadi Co-orientador: Prof. Dr. Geraldo A. S. Passos Ribeirão Preto – 2012 AUTORIZO A REPRODUÇÃO E DIVULGAÇÃO TOTAL OU PARCIAL DESTE TRABALHO, POR QUALQUER MEIO CONVENCIONAL OU ELETRÔNICO, PARA FINS DE ESTUDO E PESQUISA, DESDE QUE CITADA A FONTE. FICHA CATALOGRÁFICA Evangelista, Adriane Feijó Análise integrativa de perfis transcricionais de pacientes com diabetes mellitus tipo 1, tipo 2 e gestacional, comparando-os com manifestações demográficas, clínicas, laboratoriais, fisiopatológicas e terapêuticas. Ribeirão Preto, 2012 192p. Tese de Doutorado apresentada à Faculdade de Medicina de Ribeirão Preto da Universidade de São Paulo. Área de Concentração: Genética. Orientador: Donadi, Eduardo Antonio Co-orientador: Passos, Geraldo A. 1. Expressão gênica – microarrays 2. Análise bioinformática por module maps 3. Diabetes mellitus tipo 1 4. Diabetes mellitus tipo 2 5. Diabetes mellitus gestacional FOLHA DE APROVAÇÃO ADRIANE FEIJÓ EVANGELISTA Análise integrativa de perfis transcricionais de pacientes com diabetes mellitus tipo 1, tipo 2 e gestacional, comparando-os com manifestações demográficas, clínicas, laboratoriais, fisiopatológicas e terapêuticas. -
Mouse Irs4 Knockout Project (CRISPR/Cas9)
https://www.alphaknockout.com Mouse Irs4 Knockout Project (CRISPR/Cas9) Objective: To create a Irs4 knockout Mouse model (C57BL/6J) by CRISPR/Cas-mediated genome engineering. Strategy summary: The Irs4 gene (NCBI Reference Sequence: NM_010572 ; Ensembl: ENSMUSG00000054667 ) is located on Mouse chromosome X. 2 exons are identified, with the ATG start codon in exon 1 and the TGA stop codon in exon 1 (Transcript: ENSMUST00000067841). Exon 1 will be selected as target site. Cas9 and gRNA will be co-injected into fertilized eggs for KO Mouse production. The pups will be genotyped by PCR followed by sequencing analysis. Note: Homozygotes for a targeted null mutation exhibit a 10% reduction in male adult size, slightly impaired oral glucose tolerance, and decreased reproductive ability. Exon 1 starts from about 0.03% of the coding region. Exon 1 covers 100.0% of the coding region. The size of effective KO region: ~3646 bp. The KO region does not have any other known gene. Page 1 of 8 https://www.alphaknockout.com Overview of the Targeting Strategy Wildtype allele 5' gRNA region gRNA region 3' 1 2 Legends Exon of mouse Irs4 Knockout region Page 2 of 8 https://www.alphaknockout.com Overview of the Dot Plot (up) Window size: 15 bp Forward Reverse Complement Sequence 12 Note: The 2000 bp section upstream of start codon is aligned with itself to determine if there are tandem repeats. Tandem repeats are found in the dot plot matrix. The gRNA site is selected outside of these tandem repeats. Overview of the Dot Plot (down) Window size: 15 bp Forward Reverse Complement Sequence 12 Note: The 2000 bp section downstream of stop codon is aligned with itself to determine if there are tandem repeats.