MEIS2 Promotes Cell Migration and Invasion in Colorectal Cancer
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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. -
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. -
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. -
Targets of Hnrnp L in Human T Cells Profiling Reveals Physical And
Transcriptome-Wide RNA Interaction Profiling Reveals Physical and Functional Targets of hnRNP L in Human T Cells Downloaded from Ganesh Shankarling, Brian S. Cole, Michael J. Mallory and Kristen W. Lynch Mol. Cell. Biol. 2014, 34(1):71. DOI: 10.1128/MCB.00740-13. Published Ahead of Print 28 October 2013. http://mcb.asm.org/ Updated information and services can be found at: http://mcb.asm.org/content/34/1/71 These include: SUPPLEMENTAL MATERIAL Supplemental material on December 12, 2013 by UNIVERSITY OF PENNSYLVANIA LIBRARY REFERENCES This article cites 58 articles, 30 of which can be accessed free at: http://mcb.asm.org/content/34/1/71#ref-list-1 CONTENT ALERTS Receive: RSS Feeds, eTOCs, free email alerts (when new articles cite this article), more» Information about commercial reprint orders: http://journals.asm.org/site/misc/reprints.xhtml To subscribe to to another ASM Journal go to: http://journals.asm.org/site/subscriptions/ Transcriptome-Wide RNA Interaction Profiling Reveals Physical and Functional Targets of hnRNP L in Human T Cells Downloaded from Ganesh Shankarling, Brian S. Cole, Michael J. Mallory, Kristen W. Lynch ‹Department of Biochemistry and Biophysics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA The RNA processing factor hnRNP L is required for T cell development and function. However, the spectrum of direct targets of hnRNP L activity in T cells has yet to be defined. In this study, we used cross-linking and immunoprecipitation followed by high- throughput sequencing (CLIP-seq) to identify the RNA binding sites of hnRNP L within the transcriptomes of human CD4؉ and cultured Jurkat T cells. -
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. -
Extracellular Matrix Protein-1 Secretory Isoform Promotes Ovarian Cancer Through Increasing Alternative Mrna Splicing and Stemness
ARTICLE https://doi.org/10.1038/s41467-021-24315-1 OPEN Extracellular matrix protein-1 secretory isoform promotes ovarian cancer through increasing alternative mRNA splicing and stemness Huijing Yin1,2,8, Jingshu Wang3,8, Hui Li3,8, Yinjue Yu3,8, Xiaoling Wang4, Lili Lu1,2, Cuiting Lv3, Bin Chang2,5, ✉ ✉ Wei Jin6, Wenwen Guo2,7, Chunxia Ren 4 & Gong Yang 1,2,3 1234567890():,; Extracellular matrix protein-1 (ECM1) promotes tumorigenesis in multiple organs but the mechanisms associated to ECM1 isoform subtypes have yet to be clarified. We report in this study that the secretory ECM1a isoform induces tumorigenesis through the GPR motif binding to integrin αXβ2 and the activation of AKT/FAK/Rho/cytoskeleton signaling. The ATP binding cassette subfamily G member 1 (ABCG1) transduces the ECM1a-integrin αXβ2 interactive signaling to facilitate the phosphorylation of AKT/FAK/Rho/cytoskeletal molecules and to confer cancer cell cisplatin resistance through up-regulation of the CD326- mediated cell stemness. On the contrary, the non-secretory ECM1b isoform binds myosin and blocks its phosphorylation, impairing cytoskeleton-mediated signaling and tumorigenesis. Moreover, ECM1a induces the expression of the heterogeneous nuclear ribonucleoprotein L like (hnRNPLL) protein to favor the alternative mRNA splicing generating ECM1a. ECM1a, αXβ2, ABCG1 and hnRNPLL higher expression associates with poor survival, while ECM1b higher expression associates with good survival. These results highlight ECM1a, integrin αXβ2, hnRNPLL and ABCG1 as potential targets for treating cancers associated with ECM1- activated signaling. 1 Cancer Institute, Fudan University Shanghai Cancer Center, Shanghai, China. 2 Department of Oncology, Shanghai Medical School, Fudan University, Shanghai, China. -
A Genome-Wide Resource and Visualization Tool to Design CRISPR/Cas9 Screens for Editing Protein-RNA Interaction Sites in the Human Genome
bioRxiv preprint doi: https://doi.org/10.1101/654640; this version posted September 3, 2019. 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. SliceIt: A genome-wide resource and visualization tool to design CRISPR/Cas9 screens for editing protein-RNA interaction sites in the human genome Sasank Vemuri1Ψ, Rajneesh Srivastava1Ψ, Quoseena Mir1, Seyedsasan Hashemikhabir1, X. Charlie Dong2, 1, 3, 4* Sarath Chandra Janga 1Department of BioHealth Informatics, School of Informatics and Computing, Indiana University Purdue University, 719 Indiana Ave Ste 319, Walker Plaza Building, Indianapolis, Indiana 46202 2Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, 635 Barnhill Drive, Indianapolis, Indiana, 46202 3Department of Medical and Molecular Genetics, Indiana University School of Medicine, Medical Research and Library Building, 975 West Walnut Street, Indianapolis, Indiana, 46202 4Centre for Computational Biology and Bioinformatics, Indiana University School of Medicine, 5021 Health Information and Translational Sciences (HITS), 410 West 10th Street, Indianapolis, Indiana, 46202 ΨBoth the authors contributed equally to this study and should be considered as joint first authors Keywords: RNA binding proteins, In silico library, CRISPR/Cas9, Guide RNA, Pooled CRISPR screens, Protein-RNA interactions, Post-transcriptional control *Correspondence should be addressed to: Sarath Chandra Janga ([email protected]) 719 Indiana Avenue Ste 319, Walker Plaza Building Indianapolis, Indiana – 46202 Tel: +1-317-278-4147, Fax: +1-317-278-9201 bioRxiv preprint doi: https://doi.org/10.1101/654640; this version posted September 3, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. -
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] . -
Integrative Genomic Analysis of Hnrnp L Splicing Regulation
University of Pennsylvania ScholarlyCommons Publicly Accessible Penn Dissertations 2015 Terrae Incognitae: Integrative Genomic Analysis of Hnrnp L Splicing Regulation Brian Sebastian Cole University of Pennsylvania, [email protected] Follow this and additional works at: https://repository.upenn.edu/edissertations Part of the Allergy and Immunology Commons, Biochemistry Commons, Bioinformatics Commons, Immunology and Infectious Disease Commons, and the Medical Immunology Commons Recommended Citation Cole, Brian Sebastian, "Terrae Incognitae: Integrative Genomic Analysis of Hnrnp L Splicing Regulation" (2015). Publicly Accessible Penn Dissertations. 1664. https://repository.upenn.edu/edissertations/1664 This paper is posted at ScholarlyCommons. https://repository.upenn.edu/edissertations/1664 For more information, please contact [email protected]. Terrae Incognitae: Integrative Genomic Analysis of Hnrnp L Splicing Regulation Abstract Alternative splicing is a critical component of human gene control that generates functional diversity from a limited genome. Defects in alternative splicing are associated with disease in humans. Alternative splicing is regulated developmentally and physiologically by the combinatorial actions of cis- and trans- acting factors, including RNA binding proteins that regulate splicing through sequence-specific interactions with pre-mRNAs. In T cells, the splicing regulator hnRNP L is an essential factor that regulates alternative splicing of physiologically important mRNAs, however the broader physical and functional impact of hnRNP L remains unknown. In this dissertation, I present analysis of hnRNP L-RNA interactions with CLIP-seq, which identifies transcriptome-wide binding sites and uncovers novel functional targets. I then use functional genomics studies to define pre-mRNA processing alterations induced by hnRNP L depletion, chief among which is cassette-type alternative splicing.