Identification of Key Proteins Involved in Axon Guidance Related Disorders: a Systems Biology Approach
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BIOINFORMATICS DOI: 10.1093/Bioinformatics/Btg1030
Vol. 19 Suppl. 1 2003, pages i222–i224 BIOINFORMATICS DOI: 10.1093/bioinformatics/btg1030 GeneLoc: exon-based integration of human genome maps Naomi Rosen, Vered Chalifa-Caspi, Orit Shmueli, Avital Adato, Michal Lapidot, Julie Stampnitzky, Marilyn Safran ∗ and Doron Lancet Weizmann Institute of Science, Rehovot, Israel Received on January 6, 2003; accepted on February 20, 2003 ABSTRACT to provide a comprehensive gene list, NCBI’s LocusLink Motivation: Despite the numerous available whole- contains thousands of model genes, categorized by level genome mapping resources, no comprehensive, inte- and type of support. Even known genes appearing in every grated map of the human genome yet exists. database may have different names in each database. The Results: GeneLoc, software adjunct to GeneCards and biologist must move among databases to figure out which UDB, integrates gene lists by comparing genomic coordi- genes are the same, and which could be a novel gene nates at the exon level and assigns unique and meaningful sought. UCSC’s Genome Browser website maps genes identifiers to each gene. from several sources on the same scale, but the maps are Availability: http://bioinfo.weizmann.ac.il/genecards and not integrated, making it difficult to relate genes from http://genecards.weizmann.ac.il/udb different sources. As stated (Jongeneel, 2000),‘there is an Supplementary information: http://bioinfo.weizmann.ac. urgent need for a human gene index that can be used to il/cards-bin/AboutGCids.cgi, http://genecards.weizmann. identify transcripts unambiguously.’ The author contends ac.il/GeneLocAlg.html that this index should have, among others, the following Contact: [email protected] qualities: comprehensiveness, uniqueness, and stability. -
Mouse Pop1 Conditional Knockout Project (CRISPR/Cas9)
https://www.alphaknockout.com Mouse Pop1 Conditional Knockout Project (CRISPR/Cas9) Objective: To create a Pop1 conditional knockout Mouse model (C57BL/6J) by CRISPR/Cas-mediated genome engineering. Strategy summary: The Pop1 gene (NCBI Reference Sequence: NM_152894 ; Ensembl: ENSMUSG00000022325 ) is located on Mouse chromosome 15. 17 exons are identified, with the ATG start codon in exon 2 and the TGA stop codon in exon 17 (Transcript: ENSMUST00000052290). Exon 4~5 will be selected as conditional knockout region (cKO region). Deletion of this region should result in the loss of function of the Mouse Pop1 gene. To engineer the targeting vector, homologous arms and cKO region will be generated by PCR using BAC clone RP23-365B13 as template. Cas9, gRNA and targeting vector will be co-injected into fertilized eggs for cKO Mouse production. The pups will be genotyped by PCR followed by sequencing analysis. Note: Exon 4 starts from about 9.92% of the coding region. The knockout of Exon 4~5 will result in frameshift of the gene. The size of intron 3 for 5'-loxP site insertion: 2480 bp, and the size of intron 5 for 3'-loxP site insertion: 1452 bp. The size of effective cKO region: ~2209 bp. The cKO 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 4 5 6 7 17 Targeting vector Targeted allele Constitutive KO allele (After Cre recombination) Legends Exon of mouse Pop1 Homology arm cKO region loxP site Page 2 of 8 https://www.alphaknockout.com Overview of the Dot Plot Window size: 10 bp Forward Reverse Complement Sequence 12 Note: The sequence of homologous arms and cKO region is aligned with itself to determine if there are tandem repeats. -
The Extracellular Matrix Phenome Across Species
bioRxiv preprint doi: https://doi.org/10.1101/2020.03.06.980169; this version posted March 6, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license. The extracellular matrix phenome across species Cyril Statzer1 and Collin Y. Ewald1* 1 Eidgenössische Technische Hochschule Zürich, Department of Health Sciences and Technology, Institute of Translational Medicine, Schwerzenbach-Zürich CH-8603, Switzerland *Corresponding authors: [email protected] (CYE) Keywords: Phenome, genotype-to-phenotype, matrisome, extracellular matrix, collagen, data mining. Highlights • 7.6% of the human phenome originates from variations in matrisome genes • 11’671 phenotypes are linked to matrisome genes of humans, mice, zebrafish, Drosophila, and C. elegans • Expected top ECM phenotypes are developmental, morphological and structural phenotypes • Nonobvious top ECM phenotypes include immune system, stress resilience, and age-related phenotypes 1 bioRxiv preprint doi: https://doi.org/10.1101/2020.03.06.980169; this version posted March 6, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license. 1 Abstract 2 Extracellular matrices are essential for cellular and organismal function. Recent 3 genome-wide and phenome-wide association studies started to reveal a broad 4 spectrum of phenotypes associated with genetic variants. However, the phenome or 5 spectrum of all phenotypes associated with genetic variants in extracellular matrix 6 genes is unknown. -
Ankrd9 Is a Metabolically-Controlled Regulator of Impdh2 Abundance and Macro-Assembly
ANKRD9 IS A METABOLICALLY-CONTROLLED REGULATOR OF IMPDH2 ABUNDANCE AND MACRO-ASSEMBLY by Dawn Hayward A dissertation submitted to The Johns Hopkins University in conformity with the requirements of the degree of Doctor of Philosophy Baltimore, Maryland April 2019 ABSTRACT Members of a large family of Ankyrin Repeat Domains proteins (ANKRD) regulate numerous cellular processes by binding and changing properties of specific protein targets. We show that interactions with a target protein and the functional outcomes can be markedly altered by cells’ metabolic state. ANKRD9 facilitates degradation of inosine monophosphate dehydrogenase 2 (IMPDH2), the rate-limiting enzyme in GTP biosynthesis. Under basal conditions ANKRD9 is largely segregated from the cytosolic IMPDH2 by binding to vesicles. Upon nutrient limitation, ANKRD9 loses association with vesicles and assembles with IMPDH2 into rod-like structures, in which IMPDH2 is stable. Inhibition of IMPDH2 with Ribavirin favors ANKRD9 binding to rods. The IMPDH2/ANKRD9 assembly is reversed by guanosine, which restores association of ANKRD9 with vesicles. The conserved Cys109Cys110 motif in ANKRD9 is required for the vesicles-to-rods transition as well as binding and regulation of IMPDH2. ANKRD9 knockdown increases IMPDH2 levels and prevents formation of IMPDH2 rods upon nutrient limitation. Thus, the status of guanosine pools affects the mode of ANKRD9 action towards IMPDH2. Advisor: Dr. Svetlana Lutsenko, Department of Physiology, Johns Hopkins University School of Medicine Second reader: -
Protein-Coding Variants Implicate Novel Genes Related to Lipid Homeostasis
bioRxiv preprint doi: https://doi.org/10.1101/352674; this version posted June 30, 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. 1 PROTEIN-CODING VARIANTS IMPLICATE NOVEL GENES RELATED TO LIPID HOMEOSTASIS 2 CONTRIBUTING TO BODY FAT DISTRIBUTION 3 Anne E Justice¥,1,2, Tugce Karaderi¥,3,4, Heather M Highland¥,1,5, Kristin L Young¥,1, Mariaelisa Graff¥,1, 4 Yingchang Lu¥,6,7,8, Valérie Turcot9, Paul L Auer10, Rebecca S Fine11,12,13, Xiuqing Guo14, Claudia 5 Schurmann7,8, Adelheid Lempradl15, Eirini Marouli16, Anubha Mahajan3, Thomas W Winkler17, Adam E 6 Locke18,19, Carolina Medina-Gomez20,21, Tõnu Esko11,13,22, Sailaja Vedantam11,12,13, Ayush Giri23, Ken Sin 7 Lo9, Tamuno Alfred7, Poorva Mudgal24, Maggie CY Ng24,25, Nancy L Heard-Costa26,27, Mary F Feitosa28, 8 Alisa K Manning11,29,30 , Sara M Willems31, Suthesh Sivapalaratnam30,32,33, Goncalo Abecasis18, Dewan S 9 Alam34, Matthew Allison35, Philippe Amouyel36,37,38, Zorayr Arzumanyan14, Beverley Balkau39, Lisa 10 Bastarache40, Sven Bergmann41,42, Lawrence F Bielak43, Matthias Blüher44,45, Michael Boehnke18, Heiner 11 Boeing46, Eric Boerwinkle47,48, Carsten A Böger49, Jette Bork-Jensen50, Erwin P Bottinger7, Donald W 12 Bowden24,25,51, Ivan Brandslund52,53, Linda Broer21, Amber A Burt54, Adam S Butterworth55,56, Mark J 13 Caulfield16,57, Giancarlo Cesana58, John C Chambers59,60,61,62,63, Daniel I Chasman11,64,65,66, Yii-Der Ida 14 Chen14, Rajiv Chowdhury55, Cramer Christensen67, -
Identification of Genes Concordantly Expressed with Atoh1 During Inner Ear Development
Original Article doi: 10.5115/acb.2011.44.1.69 pISSN 2093-3665 eISSN 2093-3673 Identification of genes concordantly expressed with Atoh1 during inner ear development Heejei Yoon, Dong Jin Lee, Myoung Hee Kim, Jinwoong Bok Department of Anatomy, Brain Korea 21 Project for Medical Science, College of Medicine, Yonsei University, Seoul, Korea Abstract: The inner ear is composed of a cochlear duct and five vestibular organs in which mechanosensory hair cells play critical roles in receiving and relaying sound and balance signals to the brain. To identify novel genes associated with hair cell differentiation or function, we analyzed an archived gene expression dataset from embryonic mouse inner ear tissues. Since atonal homolog 1a (Atoh1) is a well known factor required for hair cell differentiation, we searched for genes expressed in a similar pattern with Atoh1 during inner ear development. The list from our analysis includes many genes previously reported to be involved in hair cell differentiation such as Myo6, Tecta, Myo7a, Cdh23, Atp6v1b1, and Gfi1. In addition, we identified many other genes that have not been associated with hair cell differentiation, including Tekt2, Spag6, Smpx, Lmod1, Myh7b, Kif9, Ttyh1, Scn11a and Cnga2. We examined expression patterns of some of the newly identified genes using real-time polymerase chain reaction and in situ hybridization. For example, Smpx and Tekt2, which are regulators for cytoskeletal dynamics, were shown specifically expressed in the hair cells, suggesting a possible role in hair cell differentiation or function. Here, by re- analyzing archived genetic profiling data, we identified a list of novel genes possibly involved in hair cell differentiation. -
An Amplified Fatty Acid-Binding Protein Gene Cluster In
cancers Review An Amplified Fatty Acid-Binding Protein Gene Cluster in Prostate Cancer: Emerging Roles in Lipid Metabolism and Metastasis Rong-Zong Liu and Roseline Godbout * Department of Oncology, Cross Cancer Institute, University of Alberta, Edmonton, AB T6G 1Z2, Canada; [email protected] * Correspondence: [email protected]; Tel.: +1-780-432-8901 Received: 6 November 2020; Accepted: 16 December 2020; Published: 18 December 2020 Simple Summary: Prostate cancer is the second most common cancer in men. In many cases, prostate cancer grows very slowly and remains confined to the prostate. These localized cancers can usually be cured. However, prostate cancer can also metastasize to other organs of the body, which often results in death of the patient. We found that a cluster of genes involved in accumulation and utilization of fats exists in multiple copies and is expressed at much higher levels in metastatic prostate cancer compared to localized disease. These genes, called fatty acid-binding protein (or FABP) genes, individually and collectively, promote properties associated with prostate cancer metastasis. We propose that levels of these FABP genes may serve as an indicator of prostate cancer aggressiveness, and that inhibiting the action of FABP genes may provide a new approach to prevent and/or treat metastatic prostate cancer. Abstract: Treatment for early stage and localized prostate cancer (PCa) is highly effective. Patient survival, however, drops dramatically upon metastasis due to drug resistance and cancer recurrence. The molecular mechanisms underlying PCa metastasis are complex and remain unclear. It is therefore crucial to decipher the key genetic alterations and relevant molecular pathways driving PCa metastatic progression so that predictive biomarkers and precise therapeutic targets can be developed. -
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. -
Genome Analysis and Knowledge
Dahary et al. BMC Medical Genomics (2019) 12:200 https://doi.org/10.1186/s12920-019-0647-8 SOFTWARE Open Access Genome analysis and knowledge-driven variant interpretation with TGex Dvir Dahary1*, Yaron Golan1, Yaron Mazor1, Ofer Zelig1, Ruth Barshir2, Michal Twik2, Tsippi Iny Stein2, Guy Rosner3,4, Revital Kariv3,4, Fei Chen5, Qiang Zhang5, Yiping Shen5,6,7, Marilyn Safran2, Doron Lancet2* and Simon Fishilevich2* Abstract Background: The clinical genetics revolution ushers in great opportunities, accompanied by significant challenges. The fundamental mission in clinical genetics is to analyze genomes, and to identify the most relevant genetic variations underlying a patient’s phenotypes and symptoms. The adoption of Whole Genome Sequencing requires novel capacities for interpretation of non-coding variants. Results: We present TGex, the Translational Genomics expert, a novel genome variation analysis and interpretation platform, with remarkable exome analysis capacities and a pioneering approach of non-coding variants interpretation. TGex’s main strength is combining state-of-the-art variant filtering with knowledge-driven analysis made possible by VarElect, our highly effective gene-phenotype interpretation tool. VarElect leverages the widely used GeneCards knowledgebase, which integrates information from > 150 automatically-mined data sources. Access to such a comprehensive data compendium also facilitates TGex’s broad variant annotation, supporting evidence exploration, and decision making. TGex has an interactive, user-friendly, and easy adaptive interface, ACMG compliance, and an automated reporting system. Beyond comprehensive whole exome sequence capabilities, TGex encompasses innovative non-coding variants interpretation, towards the goal of maximal exploitation of whole genome sequence analyses in the clinical genetics practice. This is enabled by GeneCards’ recently developed GeneHancer, a novel integrative and fully annotated database of human enhancers and promoters. -
4-6 Weeks Old Female C57BL/6 Mice Obtained from Jackson Labs Were Used for Cell Isolation
Methods Mice: 4-6 weeks old female C57BL/6 mice obtained from Jackson labs were used for cell isolation. Female Foxp3-IRES-GFP reporter mice (1), backcrossed to B6/C57 background for 10 generations, were used for the isolation of naïve CD4 and naïve CD8 cells for the RNAseq experiments. The mice were housed in pathogen-free animal facility in the La Jolla Institute for Allergy and Immunology and were used according to protocols approved by the Institutional Animal Care and use Committee. Preparation of cells: Subsets of thymocytes were isolated by cell sorting as previously described (2), after cell surface staining using CD4 (GK1.5), CD8 (53-6.7), CD3ε (145- 2C11), CD24 (M1/69) (all from Biolegend). DP cells: CD4+CD8 int/hi; CD4 SP cells: CD4CD3 hi, CD24 int/lo; CD8 SP cells: CD8 int/hi CD4 CD3 hi, CD24 int/lo (Fig S2). Peripheral subsets were isolated after pooling spleen and lymph nodes. T cells were enriched by negative isolation using Dynabeads (Dynabeads untouched mouse T cells, 11413D, Invitrogen). After surface staining for CD4 (GK1.5), CD8 (53-6.7), CD62L (MEL-14), CD25 (PC61) and CD44 (IM7), naïve CD4+CD62L hiCD25-CD44lo and naïve CD8+CD62L hiCD25-CD44lo were obtained by sorting (BD FACS Aria). Additionally, for the RNAseq experiments, CD4 and CD8 naïve cells were isolated by sorting T cells from the Foxp3- IRES-GFP mice: CD4+CD62LhiCD25–CD44lo GFP(FOXP3)– and CD8+CD62LhiCD25– CD44lo GFP(FOXP3)– (antibodies were from Biolegend). In some cases, naïve CD4 cells were cultured in vitro under Th1 or Th2 polarizing conditions (3, 4). -
BC-Box Protein Domain-Related Mechanism for VHL Protein Degradation
BC-box protein domain-related mechanism for VHL protein degradation Maria Elena Pozzebona,1,2, Archana Varadaraja,1, Domenico Mattoscioa, Ellis G. Jaffrayb, Claudia Miccoloa, Viviana Galimbertic, Massimo Tommasinod, Ronald T. Hayb, and Susanna Chioccaa,3 aDepartment of Experimental Oncology, European Institute of Oncology, 20139 Milan, Italy; cSenology Division, European Institute of Oncology, 20141 Milan, Italy; dInternational Agency for Research on Cancer, World Health Organization, 69372 Lyon, France; and bCentre for Gene Regulation and Expression, University of Dundee, Dundee DD1 5EH, United Kingdom Edited by William G. Kaelin, Jr., Harvard Medical School, Boston, MA, and approved September 23, 2013 (received for review June 18, 2013) The tumor suppressor VHL (von Hippel–Lindau) protein is a sub- effects of the wild-type Gam1 protein (18, 20, 21), supporting the strate receptor for Ubiquitin Cullin Ring Ligase complexes (CRLs), idea that these effects may depend on Gam1 ability to act as containing a BC-box domain that associates to the adaptor Elongin substrate-receptor protein. B/C. VHL targets hypoxia-inducible factor 1α to proteasome- VHL (von Hippel–Lindau) protein is a cellular BC box-con- dependent degradation. Gam1 is an adenoviral protein, which also taining substrate receptor and associates with Cullin2-based E3 possesses a BC-box domain that interacts with the host Elongin B/C, ligases (22–24). VHL is a tumor suppressor, and its loss leads to – thereby acting as a viral substrate receptor. Gam1 associates with the von Hippel Lindau syndrome that often develops into renal both Cullin2 and Cullin5 to form CRL complexes targeting the host clear-cell carcinoma and other highly vascularized tumors (25, 26). -
Hepatitis C Virus As a Unique Human Model Disease to Define
viruses Review Hepatitis C Virus as a Unique Human Model Disease to Define Differences in the Transcriptional Landscape of T Cells in Acute versus Chronic Infection David Wolski and Georg M. Lauer * Liver Center at the Gastrointestinal Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA * Correspondence: [email protected]; Tel.: +1-617-724-7515 Received: 27 June 2019; Accepted: 23 July 2019; Published: 26 July 2019 Abstract: The hepatitis C virus is unique among chronic viral infections in that an acute outcome with complete viral elimination is observed in a minority of infected patients. This unique feature allows direct comparison of successful immune responses with those that fail in the setting of the same human infection. Here we review how this scenario can be used to achieve better understanding of transcriptional regulation of T-cell differentiation. Specifically, we discuss results from a study comparing transcriptional profiles of hepatitis C virus (HCV)-specific CD8 T-cells during early HCV infection between patients that do and do not control and eliminate HCV. Identification of early gene expression differences in key T-cell differentiation molecules as well as clearly distinct transcriptional networks related to cell metabolism and nucleosomal regulation reveal novel insights into the development of exhausted and memory T-cells. With additional transcriptional studies of HCV-specific CD4 and CD8 T-cells in different stages of infection currently underway, we expect HCV infection to become a valuable model disease to study human immunity to viruses. Keywords: viral hepatitis; hepatitis C virus; T cells; transcriptional regulation; transcription factors; metabolism; nucleosome 1.