DOCSLIB.ORG

Mouse Stkld1 Knockout Project (CRISPR/Cas9)

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Mouse Stkld1 Knockout Project (CRISPR/Cas9) https://www.alphaknockout.com Mouse Stkld1 Knockout Project (CRISPR/Cas9) Objective: To create a Stkld1 knockout Mouse model (C57BL/6J) by CRISPR/Cas-mediated genome engineering. Strategy summary: The Stkld1 gene (NCBI Reference Sequence: NM_198628 ; Ensembl: ENSMUSG00000049897 ) is located on Mouse chromosome 2. 19 exons are identified, with the ATG start codon in exon 2 and the TGA stop codon in exon 19 (Transcript: ENSMUST00000055406). Exon 3~11 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: Exon 3 starts from about 3.98% of the coding region. Exon 3~11 covers 45.82% of the coding region. The size of effective KO region: ~9347 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 3 4 5 6 7 8 9 10 11 19 Legends Exon of mouse Stkld1 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 Exon 3 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 1984 bp section downstream of Exon 11 is aligned with itself to determine if there are tandem repeats. No significant tandem repeat is found in the dot plot matrix. So this region is suitable for PCR screening or sequencing analysis. Page 3 of 8 https://www.alphaknockout.com Overview of the GC Content Distribution (up) Window size: 300 bp Sequence 12 Summary: Full Length(2000bp) | A(23.6% 472) | C(21.3% 426) | T(30.15% 603) | G(24.95% 499) Note: The 2000 bp section upstream of Exon 3 is analyzed to determine the GC content. No significant high GC-content region is found. So this region is suitable for PCR screening or sequencing analysis. Overview of the GC Content Distribution (down) Window size: 300 bp Sequence 12 Summary: Full Length(1984bp) | A(25.4% 504) | C(25.86% 513) | T(26.16% 519) | G(22.58% 448) Note: The 1984 bp section downstream of Exon 11 is analyzed to determine the GC content. No significant high GC-content region is found. So this region is suitable for PCR screening or sequencing analysis. Page 4 of 8 https://www.alphaknockout.com BLAT Search Results (up) QUERY SCORE START END QSIZE IDENTITY CHROM STRAND START END SPAN ----------------------------------------------------------------------------------------------- browser details YourSeq 2000 1 2000 2000 100.0% chr2 + 26935982 26937981 2000 browser details YourSeq 314 1115 1587 2000 86.9% chr4 - 74283060 74283478 419 browser details YourSeq 314 1115 1595 2000 91.0% chr1 + 164021830 164022410 581 browser details YourSeq 277 1116 1595 2000 89.0% chr2 - 167592156 167592625 470 browser details YourSeq 268 1165 1588 2000 89.5% chr6 - 120175232 120418126 242895 browser details YourSeq 258 1259 1595 2000 90.3% chr3 + 130862286 130862617 332 browser details YourSeq 250 1115 1595 2000 92.0% chr9 - 66113187 66113722 536 browser details YourSeq 250 1164 1595 2000 90.4% chr7 - 4429512 4430226 715 browser details YourSeq 249 1131 1587 2000 88.6% chr11 - 80765467 80766170 704 browser details YourSeq 247 1297 1596 2000 90.7% chr9 + 120768036 120768334 299 browser details YourSeq 242 1116 1561 2000 85.5% chrX - 48464861 48465405 545 browser details YourSeq 237 951 1596 2000 90.2% chr6 + 122884438 122885182 745 browser details YourSeq 235 1115 1595 2000 84.5% chr1 + 86539603 86539937 335 browser details YourSeq 231 950 1596 2000 90.3% chr19 + 44317825 44318599 775 browser details YourSeq 231 1298 1595 2000 90.9% chr12 + 3636250 3636580 331 browser details YourSeq 228 1115 1595 2000 84.4% chr10 + 117753606 117753925 320 browser details YourSeq 227 1307 1596 2000 89.4% chr5 + 104796861 104797151 291 browser details YourSeq 227 1289 1594 2000 89.3% chr11 + 95112102 95112404 303 browser details YourSeq 226 1307 1596 2000 89.3% chr2 - 158436148 158436429 282 browser details YourSeq 225 1115 1596 2000 87.2% chr3 + 94910727 94911078 352 Note: The 2000 bp section upstream of Exon 3 is BLAT searched against the genome. No significant similarity is found. BLAT Search Results (down) QUERY SCORE START END QSIZE IDENTITY CHROM STRAND START END SPAN ----------------------------------------------------------------------------------------------- browser details YourSeq 1984 1 1984 1984 100.0% chr2 + 26947329 26949312 1984 browser details YourSeq 231 697 1005 1984 87.7% chr1 - 166020046 166020357 312 browser details YourSeq 230 698 1012 1984 88.1% chr9 - 46437540 46437854 315 browser details YourSeq 228 703 1008 1984 87.6% chr10 - 82685955 82686264 310 browser details YourSeq 227 697 1006 1984 87.3% chr5 + 125584946 125585275 330 browser details YourSeq 226 697 1005 1984 88.3% chr7 + 35060151 35060465 315 browser details YourSeq 222 697 1007 1984 88.7% chr18 - 35753748 35754065 318 browser details YourSeq 222 697 1007 1984 92.5% chr10 - 121319708 121320020 313 browser details YourSeq 218 697 998 1984 86.9% chr5 + 92779522 92984592 205071 browser details YourSeq 213 693 1005 1984 87.5% chr13 - 9007796 9008115 320 browser details YourSeq 213 698 1009 1984 88.5% chr1 + 17136389 17136709 321 browser details YourSeq 210 717 1037 1984 84.7% chr17 - 87077808 87078119 312 browser details YourSeq 209 697 1006 1984 88.6% chr8 - 119326641 119326952 312 browser details YourSeq 208 703 998 1984 86.3% chr6 - 100769606 100769907 302 browser details YourSeq 205 369 991 1984 79.8% chr6 - 28952706 28953137 432 browser details YourSeq 202 697 1005 1984 88.0% chr5 + 37548051 37548360 310 browser details YourSeq 202 697 1005 1984 87.6% chr13 + 25145538 25145844 307 browser details YourSeq 199 703 1001 1984 87.6% chr4 + 127920149 127920453 305 browser details YourSeq 198 684 986 1984 85.9% chr10 - 127348001 127348329 329 browser details YourSeq 198 717 1005 1984 84.8% chr5 + 124642892 124643186 295 Note: The 1984 bp section downstream of Exon 11 is BLAT searched against the genome. No significant similarity is found. Page 5 of 8 https://www.alphaknockout.com Gene and protein information: Stkld1 serine/threonine kinase-like domain containing 1 [ Mus musculus (house mouse) ] Gene ID: 279029, updated on 12-Aug-2019 Gene summary Official Symbol Stkld1 provided by MGI Official Full Name serine/threonine kinase-like domain containing 1 provided by MGI Primary source MGI:MGI:2685557 See related Ensembl:ENSMUSG00000049897 Gene type protein coding RefSeq status VALIDATED Organism Mus musculus Lineage Eukaryota; Metazoa; Chordata; Craniata; Vertebrata; Euteleostomi; Mammalia; Eutheria; Euarchontoglires; Glires; Rodentia; Myomorpha; Muroidea; Muridae; Murinae; Mus; Mus Also known as Gm711; Sgk071 Expression Biased expression in testis adult (RPKM 36.3), duodenum adult (RPKM 31.6) and 8 other tissues See more Orthologs human all Genomic context Location: 2; 2 A3 See Stkld1 in Genome Data Viewer Exon count: 22 Annotation release Status Assembly Chr Location 108 current GRCm38.p6 (GCF_000001635.26) 2 NC_000068.7 (26933521..26953496) Build 37.2 previous assembly MGSCv37 (GCF_000001635.18) 2 NC_000068.6 (26789589..26809016) Chromosome 2 - NC_000068.7 Page 6 of 8 https://www.alphaknockout.com Transcript information: This gene has 2 transcripts Gene: Stkld1 ENSMUSG00000049897 Description serine/threonine kinase-like domain containing 1 [Source:MGI Symbol;Acc:MGI:2685557] Gene Synonyms Gm711, LOC279029 Location Chromosome 2: 26,934,047-26,953,496 forward strand. GRCm38:CM000995.2 About this gene This gene has 2 transcripts (splice variants), 106 orthologues and is a member of 1 Ensembl protein family. Transcripts Name Transcript ID bp Protein Translation ID Biotype CCDS UniProt Flags Stkld1-201 ENSMUST00000055406.8 2169 662aa ENSMUSP00000062967.8 Protein coding CCDS15818 Q80YS9 TSL:1 GENCODE basic APPRIS P1 Stkld1-202 ENSMUST00000153771.7 400 116aa ENSMUSP00000121332.1 Protein coding - B0R044 CDS 3' incomplete TSL:5 39.45 kb Forward strand 26.93Mb 26.94Mb 26.95Mb 26.96Mb Genes (Comprehensive set... Stkld1-202 >protein coding Stkld1-201 >protein coding Contigs AL773563.12 > Genes < Surf4-201protein coding < Rexo4-201protein coding (Comprehensive set... < Surf4-202nonsense mediated decay < Rexo4-202protein coding < Surf4-203protein coding < Rexo4-203lncRNA < Rexo4-205lncRNA < Rexo4-209lncRNA < Rexo4-207protein coding < Rexo4-208lncRNA < Rexo4-206lncRNA < Rexo4-204lncRNA Regulatory Build 26.93Mb 26.94Mb 26.95Mb 26.96Mb Reverse strand 39.45 kb Regulation Legend CTCF Enhancer Open Chromatin Promoter Promoter Flank Gene Legend Protein Coding merged Ensembl/Havana Ensembl protein coding Non-Protein Coding RNA gene processed transcript Page 7 of 8 https://www.alphaknockout.com Transcript: ENSMUST00000055406 19.43 kb Forward strand Stkld1-201 >protein coding ENSMUSP00000062... MobiDB lite Low complexity (Seg) Superfamily Protein kinase-like domain superfamily Armadillo-type fold Pfam Protein kinase domain PROSITE profiles Protein kinase domain PANTHER PTHR24363 PTHR24363:SF5 Gene3D 1.10.510.10 CDD cd00180 All sequence SNPs/i... Sequence variants (dbSNP and all other sources) Variant Legend missense variant splice region variant synonymous variant Scale bar 0 60 120 180 240 300 360 420 480 540 600 662 We wish to acknowledge the following valuable scientific information resources: Ensembl, MGI, NCBI, UCSC. Page 8 of 8.
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]
  • Integrated Analysis of Differentially Expressed Genes in Breast Cancer Pathogenesis
    2560 ONCOLOGY LETTERS 9: 2560-2566, 2015 Integrated analysis of differentially expressed genes in breast cancer pathogenesis DAOBAO CHEN and HONGJIAN YANG Department of Breast Surgery, Zhejiang Cancer Hospital, Hangzhou, Zhejiang 310022, P.R. China Received October 20, 2014; Accepted March 10, 2015 DOI: 10.3892/ol.2015.3147 Abstract. The present study aimed to detect the differences ducts or from the lobules that supply the ducts (1). Breast between breast cancer cells and normal breast cells, and inves- cancer affects ~1.2 million women worldwide and accounts tigate the potential pathogenetic mechanisms of breast cancer. for ~50,000 mortalities every year (2). Despite major advances The sample GSE9574 series was downloaded, and the micro- in surgical and nonsurgical management of the disease, breast array data was analyzed to identify differentially expressed cancer metastasis remains a significant clinical challenge genes (DEGs). Gene Ontology (GO) cluster analysis using affecting numerous of patients (3). The prognosis and survival the GO Enrichment Analysis Software Toolkit platform and rates for breast cancer are highly variable, and depend on Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway the cancer type, treatment strategy, stage of the disease and analysis for DEGs was conducted using the Gene Set Analysis geographical location of the patient (4). Toolkit V2. In addition, a protein-protein interaction (PPI) Microarray technology, which may be used to simultane- network was constructed, and target sites of potential transcrip- ously interrogate 10,000-40,000 genes, has provided new tion factors and potential microRNA (miRNA) molecules were insight into the molecular classification of different cancer screened.
    [Show full text]
  • Nucleolin and Its Role in Ribosomal Biogenesis
    NUCLEOLIN: A NUCLEOLAR RNA-BINDING PROTEIN INVOLVED IN RIBOSOME BIOGENESIS Inaugural-Dissertation zur Erlangung des Doktorgrades der Mathematisch-Naturwissenschaftlichen Fakultät der Heinrich-Heine-Universität Düsseldorf vorgelegt von Julia Fremerey aus Hamburg Düsseldorf, April 2016 2 Gedruckt mit der Genehmigung der Mathematisch-Naturwissenschaftlichen Fakultät der Heinrich-Heine-Universität Düsseldorf Referent: Prof. Dr. A. Borkhardt Korreferent: Prof. Dr. H. Schwender Tag der mündlichen Prüfung: 20.07.2016 3 Die vorgelegte Arbeit wurde von Juli 2012 bis März 2016 in der Klinik für Kinder- Onkologie, -Hämatologie und Klinische Immunologie des Universitätsklinikums Düsseldorf unter Anleitung von Prof. Dr. A. Borkhardt und in Kooperation mit dem ‚Laboratory of RNA Molecular Biology‘ an der Rockefeller Universität unter Anleitung von Prof. Dr. T. Tuschl angefertigt. 4 Dedicated to my family TABLE OF CONTENTS 5 TABLE OF CONTENTS TABLE OF CONTENTS ............................................................................................... 5 LIST OF FIGURES ......................................................................................................10 LIST OF TABLES .......................................................................................................12 ABBREVIATION .........................................................................................................13 ABSTRACT ................................................................................................................19 ZUSAMMENFASSUNG
    [Show full text]
  • Differences in Aggressive Behavior and DNA Copy Number Variants Between BALB/Cj and BALB/Cbyj Substrains
    Behav Genet (2010) 40:201–210 DOI 10.1007/s10519-009-9325-5 ORIGINAL RESEARCH Differences in Aggressive Behavior and DNA Copy Number Variants Between BALB/cJ and BALB/cByJ Substrains Lady Velez • Greta Sokoloff • Klaus A. Miczek • Abraham A. Palmer • Stephanie C. Dulawa Received: 3 February 2009 / Accepted: 3 December 2009 / Published online: 23 December 2009 Ó Springer Science+Business Media, LLC 2009 Abstract Some BALB/c substrains exhibit different Keywords Aggression Á Resident intruder Á BALB/c Á levels of aggression. We compared aggression levels CNV Á Substrain between male BALB/cJ and BALB/cByJ substrains using the resident intruder paradigm. These substrains were also assessed in other tests of emotionality and information Introduction processing including the open field, forced swim, fear conditioning, and prepulse inhibition tests. We also eval- Some substrains of BALB/c mice have previously been uated single nucleotide polymorphisms (SNPs) previously suggested to exhibit robust differences in aggressive reported between these BALB/c substrains. Finally, we behavior, although the genetic basis for this behavioral dif- compared BALB/cJ and BALB/cByJ mice for genomic ference has not been identified (Ciaranello et al. 1974). The deletions or duplications, collectively termed copy number BALB/c substrains were derived from an initial BALB/c variants (CNVs), to identify candidate genes that might stock established by 1935 (Les 1990); this BALB/c stock underlie the observed behavioral differences. BALB/cJ was then acquired by several other laboratories and were mice showed substantially higher aggression levels than maintained and bred as independent stocks including BALB/ BALB/cByJ mice; however, only minor differences in cJ, BALB/cN, and BALB/cByJ.
    [Show full text]
  • Computational Inferences of Mutations Driving Mesenchymal Differentiation in Glioblastoma
    Computational Inferences of Mutations Driving Mesenchymal Differentiation in Glioblastoma James Chen Submitted in partial fulfillment of the requirements for the Doctor of Philosophy Degree in the Graduate School of Arts and Sciences Columbia University 2013 ! 2013 James Chen All rights reserved ABSTRACT Computational Inferences of Mutations Driving Mesenchymal Differentiation in Glioblastoma James Chen This dissertation reviews the development and implementation of integrative, systems biology methods designed to parse driver mutations from high- throughput array data derived from human patients. The analysis of vast amounts of genomic and genetic data in the context of complex human genetic diseases such as Glioblastoma is a daunting task. Mutations exist by the hundreds, if not thousands, and only an unknown handful will contribute to the disease in a significant way. The goal of this project was to develop novel computational methods to identify candidate mutations from these data that drive the molecular differentiation of glioblastoma into the mesenchymal subtype, the most aggressive, poorest-prognosis tumors associated with glioblastoma. TABLE OF CONTENTS CHAPTER 1… Introduction and Background 1 Glioblastoma and the Mesenchymal Subtype 3 Systems Biology and Master Regulators 9 Thesis Project: Genetics and Genomics 20 CHAPTER 2… TCGA Data Processing 23 CHAPTER 3… DIGGIn Part 1 – Selecting f-CNVs 33 Mutual Information 40 Application and Analysis 45 CHAPTER 4… DIGGIn Part 2 – Selecting drivers 52 CHAPTER 5… KLHL9 Manuscript 63 Methods 90 CHAPTER 5a… Revisions work-in-progress 105 CHAPTER 6… Discussion 109 APPENDICES… 132 APPEND01 – TCGA classifications 133 APPEND02 – GBM f-CNV list 136 APPEND03 – MES f-CNV candidate drivers 152 APPEND04 – Scripts 149 APPEND05 – Manuscript Figures and Legends 175 APPEND06 – Manuscript Supplemental Materials 185 i ACKNOWLEDGEMENTS I would like to thank the Califano Lab and my mentor, Andrea Califano, for their intellectual and motivational support during my stay in their lab.
    [Show full text]
  • Quantitative Proteomic Characterization and Comparison of T Helper 17 and Induced Regulatory T Cells
    METHODS AND RESOURCES Quantitative proteomic characterization and comparison of T helper 17 and induced regulatory T cells Imran Mohammad1,2, Kari Nousiainen3, Santosh D. Bhosale1,2, Inna Starskaia1,2, Robert Moulder1, Anne Rokka1, Fang Cheng4, Ponnuswamy Mohanasundaram4, John E. Eriksson4, David R. Goodlett5, Harri LaÈhdesmaÈki3, Zhi Chen1* 1 Turku Centre for Biotechnology, University of Turku and Åbo Akademi University, Turku, Finland, 2 Turku Doctoral Programme of Molecular Medicine, University of Turku, Turku, Finland, 3 Department of Computer a1111111111 Science, Aalto University, Espoo, Finland, 4 Cell Biology, Biosciences, Faculty of Science and Engineering, a1111111111 Åbo Akademi University, Turku, Finland, 5 Department of Pharmaceutical Sciences, University of Maryland a1111111111 School of Pharmacy, Baltimore, Maryland, United States of America a1111111111 a1111111111 * [email protected] Abstract OPEN ACCESS The transcriptional network and protein regulators that govern T helper 17 (Th17) cell differ- Citation: Mohammad I, Nousiainen K, Bhosale SD, entiation have been studied extensively using advanced genomic approaches. For a better Starskaia I, Moulder R, Rokka A, et al. (2018) understanding of these biological processes, we have moved a step forward, from gene- to Quantitative proteomic characterization and protein-level characterization of Th17 cells. Mass spectrometry±based label-free quantita- comparison of T helper 17 and induced regulatory T cells. PLoS Biol 16(5): e2004194. https://doi.org/ tive (LFQ) proteomics analysis were made of in vitro differentiated murine Th17 and induced 10.1371/journal.pbio.2004194 regulatory T (iTreg) cells. More than 4,000 proteins, covering almost all subcellular compart- Academic Editor: Paula Oliver, University of ments, were detected. Quantitative comparison of the protein expression profiles resulted in Pennsylvania Perelman School of Medicine, United the identification of proteins specifically expressed in the Th17 and iTreg cells.
    [Show full text]
  • Sleep Alterations in Mouse Genetic Models of Human Disease
    University of Kentucky UKnowledge Theses and Dissertations--Biology Biology 2016 SLEEP ALTERATIONS IN MOUSE GENETIC MODELS OF HUMAN DISEASE Mansi Sethi University of Kentucky, [email protected] Author ORCID Identifier: http://orcid.org/0000-0002-6636-171X Digital Object Identifier: https://doi.org/10.13023/ETD.2016.522 Right click to open a feedback form in a new tab to let us know how this document benefits ou.y Recommended Citation Sethi, Mansi, "SLEEP ALTERATIONS IN MOUSE GENETIC MODELS OF HUMAN DISEASE" (2016). Theses and Dissertations--Biology. 38. https://uknowledge.uky.edu/biology_etds/38 This Doctoral Dissertation is brought to you for free and open access by the Biology at UKnowledge. It has been accepted for inclusion in Theses and Dissertations--Biology by an authorized administrator of UKnowledge. For more information, please contact [email protected]. STUDENT AGREEMENT: I represent that my thesis or dissertation and abstract are my original work. Proper attribution has been given to all outside sources. I understand that I am solely responsible for obtaining any needed copyright permissions. I have obtained needed written permission statement(s) from the owner(s) of each third-party copyrighted matter to be included in my work, allowing electronic distribution (if such use is not permitted by the fair use doctrine) which will be submitted to UKnowledge as Additional File. I hereby grant to The University of Kentucky and its agents the irrevocable, non-exclusive, and royalty-free license to archive and make accessible my work in whole or in part in all forms of media, now or hereafter known.
    [Show full text]
  • Inbred Mouse Strains Expression in Primary Immunocytes Across
    Downloaded from http://www.jimmunol.org/ by guest on September 26, 2021 Daphne is online at: average * The Journal of Immunology published online 29 September 2014 from submission to initial decision 4 weeks from acceptance to publication Sara Mostafavi, Adriana Ortiz-Lopez, Molly A. Bogue, Kimie Hattori, Cristina Pop, Daphne Koller, Diane Mathis, Christophe Benoist, The Immunological Genome Consortium, David A. Blair, Michael L. Dustin, Susan A. Shinton, Richard R. Hardy, Tal Shay, Aviv Regev, Nadia Cohen, Patrick Brennan, Michael Brenner, Francis Kim, Tata Nageswara Rao, Amy Wagers, Tracy Heng, Jeffrey Ericson, Katherine Rothamel, Adriana Ortiz-Lopez, Diane Mathis, Christophe Benoist, Taras Kreslavsky, Anne Fletcher, Kutlu Elpek, Angelique Bellemare-Pelletier, Deepali Malhotra, Shannon Turley, Jennifer Miller, Brian Brown, Miriam Merad, Emmanuel L. Gautier, Claudia Jakubzick, Gwendalyn J. Randolph, Paul Monach, Adam J. Best, Jamie Knell, Ananda Goldrath, Vladimir Jojic, J Immunol http://www.jimmunol.org/content/early/2014/09/28/jimmun ol.1401280 Koller, David Laidlaw, Jim Collins, Roi Gazit, Derrick J. Rossi, Nidhi Malhotra, Katelyn Sylvia, Joonsoo Kang, Natalie A. Bezman, Joseph C. Sun, Gundula Min-Oo, Charlie C. Kim and Lewis L. Lanier Variation and Genetic Control of Gene Expression in Primary Immunocytes across Inbred Mouse Strains Submit online. Every submission reviewed by practicing scientists ? is published twice each month by http://jimmunol.org/subscription http://www.jimmunol.org/content/suppl/2014/09/28/jimmunol.140128 0.DCSupplemental Information about subscribing to The JI No Triage! Fast Publication! Rapid Reviews! 30 days* Why • • • Material Subscription Supplementary The Journal of Immunology The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2014 by The American Association of Immunologists, Inc.
    [Show full text]
  • Title 1 Transcriptomic Analysis of Ribosome Biogenesis and Pre-Rrna
    bioRxiv preprint doi: https://doi.org/10.1101/2021.08.01.454488; this version posted August 1, 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 Title 2 Transcriptomic analysis of ribosome biogenesis and pre-rRNA processing during growth 3 stress in Entamoeba histolytica ∗1 4 Sarah Naiyer ,2, Shashi Shekhar Singh2,5, Devinder Kaur2,6, Yatendra Pratap Singh2, Amartya 5 Mukherjee2,3, Alok Bhattacharya4 and Sudha Bhattacharya2,4. 6 2- School of Environmental Sciences, Jawaharlal Nehru University, New Delhi, India-110067 7 3- Present Address: Department of Molecular Reproduction, Development and Genetics, Indian 8 Institute of Science Bangalore-560012 9 4- Present Address: Ashoka University, Rajiv Gandhi Education City, Sonipat, Haryana, India - 10 131029 11 5- Present Address: Department of inflammation and Immunity, Cleveland Clinic, Cleveland, 12 OH, USA- 44195 13 6- Present Address: Central University of Punjab, Bathinda- 151401 14 15 16 17 *-Corresponding author 18 1- Present Address 19 Sarah Naiyer, PhD 20 Department of Immunology and Microbiology 21 University of Illinois at Chicago, USA, 60612 22 Email: [email protected], [email protected] 1 bioRxiv preprint doi: https://doi.org/10.1101/2021.08.01.454488; this version posted August 1, 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.
    [Show full text]
  • Initiation of Antiviral B Cell Immunity Relies on Innate Signals from Spatially Positioned NKT Cells
    Initiation of Antiviral B Cell Immunity Relies on Innate Signals from Spatially Positioned NKT Cells The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. Citation Gaya, Mauro et al. “Initiation of Antiviral B Cell Immunity Relies on Innate Signals from Spatially Positioned NKT Cells.” Cell 172, 3 (January 2018): 517–533 © 2017 The Author(s) As Published http://dx.doi.org/10.1016/j.cell.2017.11.036 Publisher Elsevier Version Final published version Citable link http://hdl.handle.net/1721.1/113555 Terms of Use Creative Commons Attribution 4.0 International License Detailed Terms http://creativecommons.org/licenses/by/4.0/ Article Initiation of Antiviral B Cell Immunity Relies on Innate Signals from Spatially Positioned NKT Cells Graphical Abstract Authors Mauro Gaya, Patricia Barral, Marianne Burbage, ..., Andreas Bruckbauer, Jessica Strid, Facundo D. Batista Correspondence [email protected] (M.G.), [email protected] (F.D.B.) In Brief NKT cells are required for the initial formation of germinal centers and production of effective neutralizing antibody responses against viruses. Highlights d NKT cells promote B cell immunity upon viral infection d NKT cells are primed by lymph-node-resident macrophages d NKT cells produce early IL-4 wave at the follicular borders d Early IL-4 wave is required for efficient seeding of germinal centers Gaya et al., 2018, Cell 172, 517–533 January 25, 2018 ª 2017 The Authors. Published by Elsevier Inc. https://doi.org/10.1016/j.cell.2017.11.036 Article Initiation of Antiviral B Cell Immunity Relies on Innate Signals from Spatially Positioned NKT Cells Mauro Gaya,1,2,* Patricia Barral,2,3 Marianne Burbage,2 Shweta Aggarwal,2 Beatriz Montaner,2 Andrew Warren Navia,1,4,5 Malika Aid,6 Carlson Tsui,2 Paula Maldonado,2 Usha Nair,1 Khader Ghneim,7 Padraic G.
    [Show full text]
  • A Novel 2.3 Mb Microduplication of 9Q34. 3 Inserted Into 19Q13. 4 in A
    Hindawi Publishing Corporation Case Reports in Pediatrics Volume 2012, Article ID 459602, 7 pages doi:10.1155/2012/459602 Case Report A Novel 2.3 Mb Microduplication of 9q34.3 Inserted into 19q13.4 in a Patient with Learning Disabilities Shalinder Singh,1 Fern Ashton,1 Renate Marquis-Nicholson,1 Jennifer M. Love,1 Chuan-Ching Lan,1 Salim Aftimos,2 Alice M. George,1 and Donald R. Love1, 3 1 Diagnostic Genetics, LabPlus, Auckland City Hospital, P.O. Box 110031, Auckland 1148, New Zealand 2 Genetic Health Service New Zealand-Northern Hub, Auckland City Hospital, Private Bag 92024, Auckland 1142, New Zealand 3 School of Biological Sciences, University of Auckland, Private Bag 92019, Auckland 1142, New Zealand Correspondence should be addressed to Donald R. Love, [email protected] Received 1 July 2012; Accepted 27 September 2012 Academic Editors: L. Cvitanovic-Sojat, G. Singer, and V. C. Wong Copyright © 2012 Shalinder Singh et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Insertional translocations in which a duplicated region of one chromosome is inserted into another chromosome are very rare. We report a 16.5-year-old girl with a terminal duplication at 9q34.3 of paternal origin inserted into 19q13.4. Chromosomal analysis revealed the karyotype 46,XX,der(19)ins(19;9)(q13.4;q34.3q34.3)pat. Cytogenetic microarray analysis (CMA) identified a ∼2.3Mb duplication of 9q34.3 → qter, which was confirmed by Fluorescence in situ hybridisation (FISH).
    [Show full text]
  • Supplementary Appendix Table of Contents
    Supplementary Appendix This appendix has been provided by the authors to give readers additional information about their work. Table of Contents Supplementary Note ........................................................................................................................... 1 Author contributions ............................................................................................................................... 1 Additional authors from study groups .............................................................................................. 2 Task Force COVID-19 Humanitas ......................................................................................................................................... 2 TASK FORCE COVID-19 HUMANITAS GAVAZZENI & CASTELLI ............................................................................. 3 COVICAT Study Group ............................................................................................................................................................... 4 Pa COVID-19 Study Group ....................................................................................................................................................... 5 Covid-19 Aachen Study (COVAS) .......................................................................................................................................... 5 Norwegian SARS-CoV-2 Study group .................................................................................................................................
    [Show full text]