Bioinformatic Analyses for T Helper Cell Subtypes Discrimination and Gene Regulatory Network Reconstruction
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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. -
Identify Key Genes and Pathways in Pancreatic Ductal Adenocarcinoma Via Bioinformatics Analysis
Identify key genes and pathways in pancreatic ductal adenocarcinoma via bioinformatics analysis Huatian Luo Fujian Medical University https://orcid.org/0000-0002-6505-825X Da-qiu Chen Fujian Medical University Jing-jing Pan Fujian Medical University Zhang-wei Wu Fujian Medical University Can Yang Fujian Medical University Hao-jie Xu Fujian Medical University Shang-hua Xu Fujian Medical University Hong-da Cai Fujian Medical University Shi Chen ( [email protected] ) Fujian Provincial Hospital Yao-dong Wang ( [email protected] ) Fujian Medical University Research article Keywords: Bioinformatical analysis, Microarray, Pancreatic cancer, Differentially expressed gene Posted Date: April 7th, 2020 DOI: https://doi.org/10.21203/rs.3.rs-19826/v1 License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Page 1/14 Abstract Background: Pancreatic cancer has many pathologic types, among which pancreatic ductal adenocarcinoma (PDAC) is the most common one. Bioinformatics has become a very common tool for the selection of potentially pathogenic genes. Methods: Three data sets containing the gene expression proles of PDAC were downloaded from the gene expression omnibus (GEO) database. The limma package of R language was utilized to explore the differentially expressed genes (DEGs). To analyze functions and signaling pathways, the Database Visualization and Integrated Discovery (DAVID) was used. To visualize the protein-protein interaction (PPI) of the DEGs ,Cytoscape was performed under the utilization of Search Tool for the Retrieval of Interacting Genes (STRING). With the usage of the plug-in cytoHubba in cytoscape software, the hub genes were found out. To verify the expression levels of hub genes, Gene Expression Proling Interactive Analysis (GEPIA) was performed. -
Reconstructing Cell Cycle Pseudo Time-Series Via Single-Cell Transcriptome Data—Supplement
School of Natural Sciences and Mathematics Reconstructing Cell Cycle Pseudo Time-Series Via Single-Cell Transcriptome Data—Supplement UT Dallas Author(s): Michael Q. Zhang Rights: CC BY 4.0 (Attribution) ©2017 The Authors Citation: Liu, Zehua, Huazhe Lou, Kaikun Xie, Hao Wang, et al. 2017. "Reconstructing cell cycle pseudo time-series via single-cell transcriptome data." Nature Communications 8, doi:10.1038/s41467-017-00039-z This document is being made freely available by the Eugene McDermott Library of the University of Texas at Dallas with permission of the copyright owner. All rights are reserved under United States copyright law unless specified otherwise. File name: Supplementary Information Description: Supplementary figures, supplementary tables, supplementary notes, supplementary methods and supplementary references. CCNE1 CCNE1 CCNE1 CCNE1 36 40 32 34 32 35 30 32 28 30 30 28 28 26 24 25 Normalized Expression Normalized Expression Normalized Expression Normalized Expression 26 G1 S G2/M G1 S G2/M G1 S G2/M G1 S G2/M Cell Cycle Stage Cell Cycle Stage Cell Cycle Stage Cell Cycle Stage CCNE1 CCNE1 CCNE1 CCNE1 40 32 40 40 35 30 38 30 30 28 36 25 26 20 20 34 Normalized Expression Normalized Expression Normalized Expression 24 Normalized Expression G1 S G2/M G1 S G2/M G1 S G2/M G1 S G2/M Cell Cycle Stage Cell Cycle Stage Cell Cycle Stage Cell Cycle Stage Supplementary Figure 1 | High stochasticity of single-cell gene expression means, as demonstrated by relative expression levels of gene Ccne1 using the mESC-SMARTer data. For every panel, 20 sample cells were randomly selected for each of the three stages, followed by plotting the mean expression levels at each stage. -
Temporal Proteomic Analysis of HIV Infection Reveals Remodelling of The
1 1 Temporal proteomic analysis of HIV infection reveals 2 remodelling of the host phosphoproteome 3 by lentiviral Vif variants 4 5 Edward JD Greenwood 1,2,*, Nicholas J Matheson1,2,*, Kim Wals1, Dick JH van den Boomen1, 6 Robin Antrobus1, James C Williamson1, Paul J Lehner1,* 7 1. Cambridge Institute for Medical Research, Department of Medicine, University of 8 Cambridge, Cambridge, CB2 0XY, UK. 9 2. These authors contributed equally to this work. 10 *Correspondence: [email protected]; [email protected]; [email protected] 11 12 Abstract 13 Viruses manipulate host factors to enhance their replication and evade cellular restriction. 14 We used multiplex tandem mass tag (TMT)-based whole cell proteomics to perform a 15 comprehensive time course analysis of >6,500 viral and cellular proteins during HIV 16 infection. To enable specific functional predictions, we categorized cellular proteins regulated 17 by HIV according to their patterns of temporal expression. We focussed on proteins depleted 18 with similar kinetics to APOBEC3C, and found the viral accessory protein Vif to be 19 necessary and sufficient for CUL5-dependent proteasomal degradation of all members of the 20 B56 family of regulatory subunits of the key cellular phosphatase PP2A (PPP2R5A-E). 21 Quantitative phosphoproteomic analysis of HIV-infected cells confirmed Vif-dependent 22 hyperphosphorylation of >200 cellular proteins, particularly substrates of the aurora kinases. 23 The ability of Vif to target PPP2R5 subunits is found in primate and non-primate lentiviral 2 24 lineages, and remodeling of the cellular phosphoproteome is therefore a second ancient and 25 conserved Vif function. -
MEIS2 Promotes Cell Migration and Invasion in Colorectal Cancer
ONCOLOGY REPORTS 42: 213-223, 2019 MEIS2 promotes cell migration and invasion in colorectal cancer ZIANG WAN1*, RUI CHAI1*, HANG YUAN1*, BINGCHEN CHEN1, QUANJIN DONG1, BOAN ZHENG1, XIAOZHOU MOU2, WENSHENG PAN3, YIFENG TU4, QING YANG5, SHILIANG TU1 and XINYE HU1 1Department of Colorectal Surgery, 2Clinical Research Institute and 3Department of Gastroenterology, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou, Zhejiang 310014; 4Department of Pathology, College of Basic Medical Sciences, Shenyang Medical College, Shenyang, Liaoning 110034; 5Department of Academy of Life Sciences, Zhejiang Chinese Medical University, Hangzhou, Zhejiang 310053, P.R. China Received October 9, 2018; Accepted March 18, 2019 DOI: 10.3892/or.2019.7161 Abstract. Colorectal cancer (CRC) is one of the most common 5-year survival rate of metastatic CRC is as low as ~10%. In types of malignancy worldwide. Distant metastasis is a key the past few decades, several regulators of CRC metastasis cause of CRC‑associated mortality. MEIS2 has been identified have been identified, including HNRNPLL and PGE2 (4,5). to be dysregulated in several types of human cancer. However, HNRNPLL has been revealed to modulate alternative splicing the mechanisms underlying the regulatory role of MEIS2 in of CD44 during the epithelial-mesenchymal transition (EMT), CRC metastasis remain largely unknown. For the first time, which leads to suppression of CRC metastasis (4). PGE2 the present study demonstrated that MEIS2 serves a role as a induced an expansion of CRC stem cells to promote liver promoter of metastasis in CRC. In vivo and in vitro experiments metastases in mice by activating NF-κB (5). -
SHCBP1 Promotes Synovial Sarcoma Cell Metastasis Via Targeting TGF-Β1
Peng et al. Journal of Experimental & Clinical Cancer Research (2017) 36:141 DOI 10.1186/s13046-017-0616-z RESEARCH Open Access SHCBP1 promotes synovial sarcoma cell metastasis via targeting TGF-β1/Smad signaling pathway and is associated with poor prognosis Changliang Peng1, Hui Zhao2, Yan Song3, Wei Chen4, Xiaoying Wang5, Xiaoli Liu6, Cheng Zhang1, Jie Zhao1,JiLi1, Guanghui Cheng7, Dongjin Wu1, Chunzheng Gao1 and Xiuwen Wang1* Abstract Background: Our previous studies reported that SHC SH2-domain binding protein 1 (SHCBP1) functions as an oncogene via promoting cell proliferations in synovial sarcoma (SS) cells. However, whether SHCBP1 has any effect on tumor metastasis remains unexplored. Methods: The expression of SHCBP1 was analyzed in 76 SS tissues and two SS cell lines by immunohistochemistry and real-time RT-PCR. The relationship between SHCBP1 expression and the clinicopathological features of SS was investigated. The role of SHCBP1 in SS cell adhesion, migration, invasion and angiogenesis was explored by adhesion, Wound healing, Transwell, and Matrigel tube formation assays. Western blotting was conducted to detect the protein expressions of TGF-β1/Smad signaling pathway and EMT-related markers. The key molecules associated with migration, invasion and EMT were evaluated by immunohistochemistry in tumor specimens. Results: In current study, we demonstrated that SHCBP1 overexpression significantly enhanced adhesion, migration, invasion and angiogenesis of SS cells. In contrast, SHCBP1 knockdown elicited the opposite effects on these phenotypes in vitro. SHCBP1 promoted tumor metastasis through inducing epithelial-mesenchymal transition (EMT) in SS cells. SHCBP1 knockdown could block the incidence of metastasis and EMT in SS cells. Furthermore, transforming growth factor-β1 (TGF-β1) induced SHCBP1 expression in a time-dependent pattern and SHCBP1 knockdown inhibited TGF-β1-induced EMT. -
Number 3 March 2016 Atlas of Genetics and Cytogenetics in Oncology and Haematology
Volume 1 - Number 1 May - September 1997 Volume 20 - Number 3 March 2016 Atlas of Genetics and Cytogenetics in Oncology and Haematology OPEN ACCESS JOURNAL INIST-CNRS Scope The Atlas of Genetics and Cytogenetics in Oncology and Haematologyis 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] . -
Transdifferentiation of Human Mesenchymal Stem Cells
Transdifferentiation of Human Mesenchymal Stem Cells Dissertation zur Erlangung des naturwissenschaftlichen Doktorgrades der Julius-Maximilians-Universität Würzburg vorgelegt von Tatjana Schilling aus San Miguel de Tucuman, Argentinien Würzburg, 2007 Eingereicht am: Mitglieder der Promotionskommission: Vorsitzender: Prof. Dr. Martin J. Müller Gutachter: PD Dr. Norbert Schütze Gutachter: Prof. Dr. Georg Krohne Tag des Promotionskolloquiums: Doktorurkunde ausgehändigt am: Hiermit erkläre ich ehrenwörtlich, dass ich die vorliegende Dissertation selbstständig angefertigt und keine anderen als die von mir angegebenen Hilfsmittel und Quellen verwendet habe. Des Weiteren erkläre ich, dass diese Arbeit weder in gleicher noch in ähnlicher Form in einem Prüfungsverfahren vorgelegen hat und ich noch keinen Promotionsversuch unternommen habe. Gerbrunn, 4. Mai 2007 Tatjana Schilling Table of contents i Table of contents 1 Summary ........................................................................................................................ 1 1.1 Summary.................................................................................................................... 1 1.2 Zusammenfassung..................................................................................................... 2 2 Introduction.................................................................................................................... 4 2.1 Osteoporosis and the fatty degeneration of the bone marrow..................................... 4 2.2 Adipose and bone -
Somatic Mutations in Early Onset Luminal Breast Cancer
www.oncotarget.com Oncotarget, 2018, Vol. 9, (No. 32), pp: 22460-22479 Research Paper Somatic mutations in early onset luminal breast cancer Giselly Encinas1,*, Veronica Y. Sabelnykova2,*, Eduardo Carneiro de Lyra3, Maria Lucia Hirata Katayama1, Simone Maistro1, Pedro Wilson Mompean de Vasconcellos Valle1, Gláucia Fernanda de Lima Pereira1, Lívia Munhoz Rodrigues1, Pedro Adolpho de Menezes Pacheco Serio1, Ana Carolina Ribeiro Chaves de Gouvêa1, Felipe Correa Geyer1, Ricardo Alves Basso3, Fátima Solange Pasini1, Maria del Pilar Esteves Diz1, Maria Mitzi Brentani1, João Carlos Guedes Sampaio Góes3, Roger Chammas1, Paul C. Boutros2,4,5 and Maria Aparecida Azevedo Koike Folgueira1 1Instituto do Cancer do Estado de Sao Paulo, Departamento de Radiologia e Oncologia, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil 2Ontario Institute for Cancer Research, Toronto, Canada 3Instituto Brasileiro de Controle do Câncer, São Paulo, Brazil 4Department of Medical Biophysics, University of Toronto, Toronto, Canada 5Department of Pharmacology and Toxicology, University of Toronto, Toronto, Canada *These authors have contributed equally to this work Correspondence to: Maria Aparecida Azevedo Koike Folgueira, email: [email protected] Keywords: breast cancer; young patients; somatic mutation; germline mutation; luminal subtype Received: September 26, 2017 Accepted: March 06, 2018 Published: April 27, 2018 Copyright: Encinas et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License 3.0 (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. ABSTRACT Breast cancer arising in very young patients may be biologically distinct; however, these tumors have been less well studied. -
Global Identification of MLL2-Targeted Loci Reveals Mll2ts Role in Diverse Signaling Pathways
Global identification of MLL2-targeted loci reveals MLL2’s role in diverse signaling pathways Changcun Guoa,b,c,1, Chun-Chi Changa,b,c,1, Matthew Worthama,b,c, Lee H. Chena,b,c, Dawn N. Kernagisc, Xiaoxia Qind, Young-Wook Choe,2, Jen-Tsan Chid, Gerald A. Granta,b,f, Roger E. McLendona,b,c, Hai Yana,b,c, Kai Gee, Nickolas Papadopoulosg, Darell D. Bignera,b,c, and Yiping Hea,b,c,3 aThe Preston Robert Tisch Brain Tumor Center at Duke, bPediatric Brain Tumor Foundation Institute, cDepartment of Pathology, dInstitute for Genome Sciences and Policy, and fDepartment of Surgery, Duke University, Durham, NC 27710; eLaboratory of Endocrinology and Receptor Biology, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD 20892; and gLudwig Center for Cancer Genetics and Therapeutics, Sidney Kimmel Comprehensive Cancer Center, Baltimore, MD 21231 Edited* by Bert Vogelstein, Johns Hopkins University, Baltimore, MD, and approved September 14, 2012 (received for review June 1, 2012) Myeloid/lymphoid or mixed-lineage leukemia (MLL)-family genes SWI/SNF, the MLL2 or MLL3 (hereafter referred to as MLL2/ encode histone lysine methyltransferases that play important 3) complex has been found to play essential roles as a coactivator roles in epigenetic regulation of gene transcription. MLL genes for transcriptional activation by nuclear hormone receptors (11). are frequently mutated in human cancers. Unlike MLL1, MLL2 (also Consistent with this notion, previous studies have shown that known as ALR/MLL4) and its homolog MLL3 are not well-under- MLL2/3 complexes regulate Hox gene transcription in an es- stood. -
Electronic Sorting of Immune Cell Subpopulations Based on Highly Plastic Genes
Electronic Sorting of Immune Cell Subpopulations Based on Highly Plastic Genes This information is current as Pingzhang Wang, Wenling Han and Dalong Ma of October 2, 2021. J Immunol 2016; 197:665-673; Prepublished online 10 June 2016; doi: 10.4049/jimmunol.1502552 http://www.jimmunol.org/content/197/2/665 Downloaded from Supplementary http://www.jimmunol.org/content/suppl/2016/06/10/jimmunol.150255 Material 2.DCSupplemental References This article cites 56 articles, 18 of which you can access for free at: http://www.jimmunol.org/ http://www.jimmunol.org/content/197/2/665.full#ref-list-1 Why The JI? Submit online. • Rapid Reviews! 30 days* from submission to initial decision • No Triage! Every submission reviewed by practicing scientists by guest on October 2, 2021 • Fast Publication! 4 weeks from acceptance to publication *average Subscription Information about subscribing to The Journal of Immunology is online at: http://jimmunol.org/subscription Permissions Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html Email Alerts Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts The Journal of Immunology is published twice each month by 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. The Journal of Immunology Electronic Sorting of Immune Cell Subpopulations Based on Highly Plastic Genes Pingzhang Wang, Wenling Han, and Dalong Ma Immune cells are highly heterogeneous and plastic with regard to gene expression and cell phenotype.