A Comprehensive Study of Chromosome 16Q in Invasive Ductal and Lobular Breast Carcinoma Usingarray CGH
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Primepcr™Assay Validation Report
PrimePCR™Assay Validation Report Gene Information Gene Name katanin p80 (WD repeat containing) subunit B 1 Gene Symbol KATNB1 Organism Human Gene Summary Microtubules polymers of alpha and beta tubulin subunits form the mitotic spindle of a dividing cell and help to organize membranous organelles during interphase. Katanin is a heterodimer that consists of a 60 kDa ATPase (p60 subunit A 1) and an 80 kDa accessory protein (p80 subunit B 1). The p60 subunit acts to sever and disassemble microtubules while the p80 subunit targets the enzyme to the centrosome. Katanin is a member of the AAA family of ATPases. Gene Aliases KAT RefSeq Accession No. NC_000016.9, NT_010498.15 UniGene ID Hs.275675 Ensembl Gene ID ENSG00000140854 Entrez Gene ID 10300 Assay Information Unique Assay ID qHsaCIP0026589 Assay Type Probe - Validation information is for the primer pair using SYBR® Green detection Detected Coding Transcript(s) ENST00000379661 Amplicon Context Sequence CACCAAGACAGCCTGGAAGTTGCAAGAGATCGTCGCGCATGCCAGCAACGTGT CCTCACTGGTGCTGGGCAAAGCCTCCGGGCGGCTGCTGGCTACAGGCGGGGAT GACTGCCGCGTCAACCTGTGGTCCATCAACAAGCCCAACTGCATCATGAGCCTG ACG Amplicon Length (bp) 132 Chromosome Location 16:57771173-57778314 Assay Design Intron-spanning Purification Desalted Validation Results Efficiency (%) 100 R2 0.9991 cDNA Cq 21.47 cDNA Tm (Celsius) 89 Page 1/5 PrimePCR™Assay Validation Report gDNA Cq 35.43 Specificity (%) 100 Information to assist with data interpretation is provided at the end of this report. Page 2/5 PrimePCR™Assay Validation Report KATNB1, Human Amplification -
Deregulated Gene Expression Pathways in Myelodysplastic Syndrome Hematopoietic Stem Cells
Leukemia (2010) 24, 756–764 & 2010 Macmillan Publishers Limited All rights reserved 0887-6924/10 $32.00 www.nature.com/leu ORIGINAL ARTICLE Deregulated gene expression pathways in myelodysplastic syndrome hematopoietic stem cells A Pellagatti1, M Cazzola2, A Giagounidis3, J Perry1, L Malcovati2, MG Della Porta2,MJa¨dersten4, S Killick5, A Verma6, CJ Norbury7, E Hellstro¨m-Lindberg4, JS Wainscoat1 and J Boultwood1 1LRF Molecular Haematology Unit, NDCLS, John Radcliffe Hospital, Oxford, UK; 2Department of Hematology Oncology, University of Pavia Medical School, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy; 3Medizinische Klinik II, St Johannes Hospital, Duisburg, Germany; 4Division of Hematology, Department of Medicine, Karolinska Institutet, Stockholm, Sweden; 5Department of Haematology, Royal Bournemouth Hospital, Bournemouth, UK; 6Albert Einstein College of Medicine, Bronx, NY, USA and 7Sir William Dunn School of Pathology, University of Oxford, Oxford, UK To gain insight into the molecular pathogenesis of the the World Health Organization.6,7 Patients with refractory myelodysplastic syndromes (MDS), we performed global gene anemia (RA) with or without ringed sideroblasts, according to expression profiling and pathway analysis on the hemato- poietic stem cells (HSC) of 183 MDS patients as compared with the the French–American–British classification, were subdivided HSC of 17 healthy controls. The most significantly deregulated based on the presence or absence of multilineage dysplasia. In pathways in MDS include interferon signaling, thrombopoietin addition, patients with RA with excess blasts (RAEB) were signaling and the Wnt pathways. Among the most signifi- subdivided into two categories, RAEB1 and RAEB2, based on the cantly deregulated gene pathways in early MDS are immuno- percentage of bone marrow blasts. -
Mouse Shcbp1 Conditional Knockout Project (CRISPR/Cas9)
https://www.alphaknockout.com Mouse Shcbp1 Conditional Knockout Project (CRISPR/Cas9) Objective: To create a Shcbp1 conditional knockout Mouse model (C57BL/6J) by CRISPR/Cas-mediated genome engineering. Strategy summary: The Shcbp1 gene (NCBI Reference Sequence: NM_011369 ; Ensembl: ENSMUSG00000022322 ) is located on Mouse chromosome 8. 13 exons are identified, with the ATG start codon in exon 1 and the TAG stop codon in exon 13 (Transcript: ENSMUST00000022945). Exon 4 will be selected as conditional knockout region (cKO region). Deletion of this region should result in the loss of function of the Mouse Shcbp1 gene. To engineer the targeting vector, homologous arms and cKO region will be generated by PCR using BAC clone RP24-78D8 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: Mice homozygous for a knock-out allele exhibit normal viability, fertility and T cell development but show decreased susceptibility to experimental autoimmune encephalomyelitis. Exon 4 starts from about 19.36% of the coding region. The knockout of Exon 4 will result in frameshift of the gene. The size of intron 3 for 5'-loxP site insertion: 2817 bp, and the size of intron 4 for 3'-loxP site insertion: 10568 bp. The size of effective cKO region: ~709 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 gRNA region 5' gRNA region 3' 1 4 13 Targeting vector Targeted allele Constitutive KO allele (After Cre recombination) Legends Exon of mouse Shcbp1 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. -
PARSANA-DISSERTATION-2020.Pdf
DECIPHERING TRANSCRIPTIONAL PATTERNS OF GENE REGULATION: A COMPUTATIONAL APPROACH by Princy Parsana A dissertation submitted to The Johns Hopkins University in conformity with the requirements for the degree of Doctor of Philosophy Baltimore, Maryland July, 2020 © 2020 Princy Parsana All rights reserved Abstract With rapid advancements in sequencing technology, we now have the ability to sequence the entire human genome, and to quantify expression of tens of thousands of genes from hundreds of individuals. This provides an extraordinary opportunity to learn phenotype relevant genomic patterns that can improve our understanding of molecular and cellular processes underlying a trait. The high dimensional nature of genomic data presents a range of computational and statistical challenges. This dissertation presents a compilation of projects that were driven by the motivation to efficiently capture gene regulatory patterns in the human transcriptome, while addressing statistical and computational challenges that accompany this data. We attempt to address two major difficulties in this domain: a) artifacts and noise in transcriptomic data, andb) limited statistical power. First, we present our work on investigating the effect of artifactual variation in gene expression data and its impact on trans-eQTL discovery. Here we performed an in-depth analysis of diverse pre-recorded covariates and latent confounders to understand their contribution to heterogeneity in gene expression measurements. Next, we discovered 673 trans-eQTLs across 16 human tissues using v6 data from the Genotype Tissue Expression (GTEx) project. Finally, we characterized two trait-associated trans-eQTLs; one in Skeletal Muscle and another in Thyroid. Second, we present a principal component based residualization method to correct gene expression measurements prior to reconstruction of co-expression networks. -
Number 2 February 2017 Atlas of Genetics and Cytogenetics in Oncology and Haematology
Volume 1 - Number 1 May - September 1997 Volume 21 - Number 2 February 2017 Atlas of Genetics and Cytogenetics in Oncology and Haematology OPEN ACCESS JOURNAL INIST-CNRS Scope The Atlas of Genetics and Cytogenetics in Oncology and Haematology is a peer reviewed on-line journal in open access, devoted to genes, cytogenetics, and clinical entities in cancer, and cancer-prone diseases. It is made for and by: clinicians and researchers in cytogenetics, molecular biology, oncology, haematology, and pathology. One main scope of the Atlas is to conjugate the scientific information provided by cytogenetics/molecular genetics to the clinical setting (diagnostics, prognostics and therapeutic design), another is to provide an encyclopedic knowledge in cancer genetics. The Atlas deals with cancer research and genomics. It is at the crossroads of research, virtual medical university (university and post-university e-learning), and telemedicine. It contributes to "meta-medicine", this mediation, using information technology, between the increasing amount of knowledge and the individual, having to use the information. Towards a personalized medicine of cancer. It presents structured review articles ("cards") on: 1- Genes, 2- Leukemias, 3- Solid tumors, 4- Cancer-prone diseases, and also 5- "Deep insights": more traditional review articles on the above subjects and on surrounding topics. It also present 6- Case reports in hematology and 7- Educational items in the various related topics for students in Medicine and in Sciences. The Atlas of Genetics and Cytogenetics in Oncology and Haematology does not publish research articles. See also: http://documents.irevues.inist.fr/bitstream/handle/2042/56067/Scope.pdf Editorial correspondance Jean-Loup Huret, MD, PhD, Genetics, Department of Medical Information, University Hospital F-86021 Poitiers, France phone +33 5 49 44 45 46 [email protected] or [email protected] . -
Molecular Profile of Tumor-Specific CD8+ T Cell Hypofunction in a Transplantable Murine Cancer Model
Downloaded from http://www.jimmunol.org/ by guest on September 25, 2021 T + is online at: average * The Journal of Immunology , 34 of which you can access for free at: 2016; 197:1477-1488; Prepublished online 1 July from submission to initial decision 4 weeks from acceptance to publication 2016; doi: 10.4049/jimmunol.1600589 http://www.jimmunol.org/content/197/4/1477 Molecular Profile of Tumor-Specific CD8 Cell Hypofunction in a Transplantable Murine Cancer Model Katherine A. Waugh, Sonia M. Leach, Brandon L. Moore, Tullia C. Bruno, Jonathan D. Buhrman and Jill E. Slansky J Immunol cites 95 articles Submit online. Every submission reviewed by practicing scientists ? is published twice each month by Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts http://jimmunol.org/subscription Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html http://www.jimmunol.org/content/suppl/2016/07/01/jimmunol.160058 9.DCSupplemental This article http://www.jimmunol.org/content/197/4/1477.full#ref-list-1 Information about subscribing to The JI No Triage! Fast Publication! Rapid Reviews! 30 days* Why • • • Material References Permissions Email Alerts Subscription Supplementary The Journal of Immunology The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2016 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. This information is current as of September 25, 2021. The Journal of Immunology Molecular Profile of Tumor-Specific CD8+ T Cell Hypofunction in a Transplantable Murine Cancer Model Katherine A. -
Propranolol-Mediated Attenuation of MMP-9 Excretion in Infants with Hemangiomas
Supplementary Online Content Thaivalappil S, Bauman N, Saieg A, Movius E, Brown KJ, Preciado D. Propranolol-mediated attenuation of MMP-9 excretion in infants with hemangiomas. JAMA Otolaryngol Head Neck Surg. doi:10.1001/jamaoto.2013.4773 eTable. List of All of the Proteins Identified by Proteomics This supplementary material has been provided by the authors to give readers additional information about their work. © 2013 American Medical Association. All rights reserved. Downloaded From: https://jamanetwork.com/ on 10/01/2021 eTable. List of All of the Proteins Identified by Proteomics Protein Name Prop 12 mo/4 Pred 12 mo/4 Δ Prop to Pred mo mo Myeloperoxidase OS=Homo sapiens GN=MPO 26.00 143.00 ‐117.00 Lactotransferrin OS=Homo sapiens GN=LTF 114.00 205.50 ‐91.50 Matrix metalloproteinase‐9 OS=Homo sapiens GN=MMP9 5.00 36.00 ‐31.00 Neutrophil elastase OS=Homo sapiens GN=ELANE 24.00 48.00 ‐24.00 Bleomycin hydrolase OS=Homo sapiens GN=BLMH 3.00 25.00 ‐22.00 CAP7_HUMAN Azurocidin OS=Homo sapiens GN=AZU1 PE=1 SV=3 4.00 26.00 ‐22.00 S10A8_HUMAN Protein S100‐A8 OS=Homo sapiens GN=S100A8 PE=1 14.67 30.50 ‐15.83 SV=1 IL1F9_HUMAN Interleukin‐1 family member 9 OS=Homo sapiens 1.00 15.00 ‐14.00 GN=IL1F9 PE=1 SV=1 MUC5B_HUMAN Mucin‐5B OS=Homo sapiens GN=MUC5B PE=1 SV=3 2.00 14.00 ‐12.00 MUC4_HUMAN Mucin‐4 OS=Homo sapiens GN=MUC4 PE=1 SV=3 1.00 12.00 ‐11.00 HRG_HUMAN Histidine‐rich glycoprotein OS=Homo sapiens GN=HRG 1.00 12.00 ‐11.00 PE=1 SV=1 TKT_HUMAN Transketolase OS=Homo sapiens GN=TKT PE=1 SV=3 17.00 28.00 ‐11.00 CATG_HUMAN Cathepsin G OS=Homo -
A Network Propagation Approach to Prioritize Long Tail Genes in Cancer
bioRxiv preprint doi: https://doi.org/10.1101/2021.02.05.429983; this version posted February 8, 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. A Network Propagation Approach to Prioritize Long Tail Genes in Cancer Hussein Mohsen1,*, Vignesh Gunasekharan2, Tao Qing2, Sahand Negahban3, Zoltan Szallasi4, Lajos Pusztai2,*, Mark B. Gerstein1,5,6,3,* 1 Computational Biology & Bioinformatics Program, Yale University, New Haven, CT 06511, USA 2 Breast Medical Oncology, Yale School of Medicine, New Haven, CT 06511, USA 3 Department of Statistics & Data Science, Yale University, New Haven, CT 06511, USA 4 Children’s Hospital Informatics Program, Harvard-MIT Division of Health Sciences and Technology, Harvard Medical School, Boston, MA 02115, USA 5 Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06511, USA 6 Department of Computer Science, Yale University, New Haven, CT 06511, USA * Corresponding author Abstract Introduction. The diversity of genomic alterations in cancer pose challenges to fully understanding the etiologies of the disease. Recent interest in infrequent mutations, in genes that reside in the “long tail” of the mutational distribution, uncovered new genes with significant implication in cancer development. The study of these genes often requires integrative approaches with multiple types of biological data. Network propagation methods have demonstrated high efficacy in uncovering genomic patterns underlying cancer using biological interaction networks. Yet, the majority of these analyses have focused their assessment on detecting known cancer genes or identifying altered subnetworks. -
KIAA0556 Is a Novel Ciliary Basal Body Component Mutated in Joubert Syndrome Anna A
Sanders et al. Genome Biology (2015) 16:293 DOI 10.1186/s13059-015-0858-z RESEARCH Open Access KIAA0556 is a novel ciliary basal body component mutated in Joubert syndrome Anna A. W. M. Sanders1†, Erik de Vrieze2,3†, Anas M. Alazami4†, Fatema Alzahrani4, Erik B. Malarkey5, Nasrin Sorusch6, Lars Tebbe6, Stefanie Kuhns1, Teunis J. P. van Dam7, Amal Alhashem8, Brahim Tabarki8, Qianhao Lu9,10, Nils J. Lambacher1, Julie E. Kennedy1, Rachel V. Bowie1, Lisette Hetterschijt2,3, Sylvia van Beersum3,11, Jeroen van Reeuwijk3,11, Karsten Boldt12, Hannie Kremer2,3,11, Robert A. Kesterson13, Dorota Monies4, Mohamed Abouelhoda4, Ronald Roepman3,11, Martijn H. Huynen7, Marius Ueffing12, Rob B. Russell9,10, Uwe Wolfrum6, Bradley K. Yoder5, Erwin van Wijk2,3*, Fowzan S. Alkuraya4,14* and Oliver E. Blacque1* Abstract Background: Joubert syndrome (JBTS) and related disorders are defined by cerebellar malformation (molar tooth sign), together with neurological symptoms of variable expressivity. The ciliary basis of Joubert syndrome related disorders frequently extends the phenotype to tissues such as the eye, kidney, skeleton and craniofacial structures. Results: Using autozygome and exome analyses, we identified a null mutation in KIAA0556 in a multiplex consanguineous family with hallmark features of mild Joubert syndrome. Patient-derived fibroblasts displayed reduced ciliogenesis potential and abnormally elongated cilia. Investigation of disease pathophysiology revealed that Kiaa0556-/- null mice possess a Joubert syndrome-associated brain-restricted phenotype. Functional studies in Caenorhabditis elegans nematodes and cultured human cells support a conserved ciliary role for KIAA0556 linked to microtubule regulation. First, nematode KIAA0556 is expressed almost exclusively in ciliated cells, and the worm and human KIAA0556 proteins are enriched at the ciliary base. -
Hypermethylation-Mediated Silencing of NDRG4 Promotes Pancreatic Ductal Adenocarcinoma by Regulating Mitochondrial Function
BMB Rep. 2020; 53(12): 658-663 BMB www.bmbreports.org Reports Hypermethylation-mediated silencing of NDRG4 promotes pancreatic ductal adenocarcinoma by regulating mitochondrial function Hao-Hong Shi1, Hai-E Liu1 & Xing-Jing Luo1,2,* 1Department of Anesthesia, Children’s Hospital of Fudan University, Shanghai 201102, 2Department of Anesthesia, Anhui Provincial Children’s Hospital, Hefei, Anhui 230022, China The N-myc downstream regulated gene (NDRG) family members are diagnosed in the advanced stage with a 5-year overall sur- are dysregulated in several tumors. Functionally, NDRGs play vival rate of less than 6%. Thus, PDAC is internationally called an important role in the malignant progression of cancer cells. the “king of cancer” (2). Unfortunately, even with the advent of However, little is known about the potential implications of diverse detection technologies and advanced treatment methods, NDRG4 in pancreatic ductal adenocarcinoma (PDAC). The aim the incidence and mortality rate of PDAC are still on the rise of the current study was to elucidate the expression pattern of year by year (3, 4). Due to the lack of in-depth understanding NDRG4 in PDAC and evaluate its potential cellular biological of molecular characteristics of malignant development, compre- effects. Here, we firstly report that epigenetic-mediated silencing hensive and in-depth research studies are urgently needed to of NDRG4 promotes PDAC by regulating mitochondrial func- better prevent and treat PDAC. tion. Data mining demonstrated that NDRG4 was significantly N-Myc downstream-regulated gene 4 (NDRG4) is a member down-regulated in PDAC tissues and cells. PDAC patients with of the NDRG family proteins (NDRG1-4) known to share 57%- low NDRG4 expression showed poor prognosis. -
Redefining the Specificity of Phosphoinositide-Binding by Human
bioRxiv preprint doi: https://doi.org/10.1101/2020.06.20.163253; this version posted June 21, 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-NC 4.0 International license. Redefining the specificity of phosphoinositide-binding by human PH domain-containing proteins Nilmani Singh1†, Adriana Reyes-Ordoñez1†, Michael A. Compagnone1, Jesus F. Moreno Castillo1, Benjamin J. Leslie2, Taekjip Ha2,3,4,5, Jie Chen1* 1Department of Cell & Developmental Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801; 2Department of Biophysics and Biophysical Chemistry, Johns Hopkins University School of Medicine, Baltimore, MD 21205; 3Department of Biophysics, Johns Hopkins University, Baltimore, MD 21218; 4Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21205; 5Howard Hughes Medical Institute, Baltimore, MD 21205, USA †These authors contributed equally to this work. *Correspondence: [email protected]. bioRxiv preprint doi: https://doi.org/10.1101/2020.06.20.163253; this version posted June 21, 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-NC 4.0 International license. ABSTRACT Pleckstrin homology (PH) domains are presumed to bind phosphoinositides (PIPs), but specific interaction with and regulation by PIPs for most PH domain-containing proteins are unclear. Here we employed a single-molecule pulldown assay to study interactions of lipid vesicles with full-length proteins in mammalian whole cell lysates. -
Supplementary Table 1: Adhesion Genes Data Set
Supplementary Table 1: Adhesion genes data set PROBE Entrez Gene ID Celera Gene ID Gene_Symbol Gene_Name 160832 1 hCG201364.3 A1BG alpha-1-B glycoprotein 223658 1 hCG201364.3 A1BG alpha-1-B glycoprotein 212988 102 hCG40040.3 ADAM10 ADAM metallopeptidase domain 10 133411 4185 hCG28232.2 ADAM11 ADAM metallopeptidase domain 11 110695 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 195222 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 165344 8751 hCG20021.3 ADAM15 ADAM metallopeptidase domain 15 (metargidin) 189065 6868 null ADAM17 ADAM metallopeptidase domain 17 (tumor necrosis factor, alpha, converting enzyme) 108119 8728 hCG15398.4 ADAM19 ADAM metallopeptidase domain 19 (meltrin beta) 117763 8748 hCG20675.3 ADAM20 ADAM metallopeptidase domain 20 126448 8747 hCG1785634.2 ADAM21 ADAM metallopeptidase domain 21 208981 8747 hCG1785634.2|hCG2042897 ADAM21 ADAM metallopeptidase domain 21 180903 53616 hCG17212.4 ADAM22 ADAM metallopeptidase domain 22 177272 8745 hCG1811623.1 ADAM23 ADAM metallopeptidase domain 23 102384 10863 hCG1818505.1 ADAM28 ADAM metallopeptidase domain 28 119968 11086 hCG1786734.2 ADAM29 ADAM metallopeptidase domain 29 205542 11085 hCG1997196.1 ADAM30 ADAM metallopeptidase domain 30 148417 80332 hCG39255.4 ADAM33 ADAM metallopeptidase domain 33 140492 8756 hCG1789002.2 ADAM7 ADAM metallopeptidase domain 7 122603 101 hCG1816947.1 ADAM8 ADAM metallopeptidase domain 8 183965 8754 hCG1996391 ADAM9 ADAM metallopeptidase domain 9 (meltrin gamma) 129974 27299 hCG15447.3 ADAMDEC1 ADAM-like,