The RNA Methyltransferase NSUN2 and Its Potential Roles in Cancer
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SRC Antibody - N-Terminal Region (ARP32476 P050) Data Sheet
SRC antibody - N-terminal region (ARP32476_P050) Data Sheet Product Number ARP32476_P050 Product Name SRC antibody - N-terminal region (ARP32476_P050) Size 50ug Gene Symbol SRC Alias Symbols ASV; SRC1; c-SRC; p60-Src Nucleotide Accession# NM_005417 Protein Size (# AA) 536 amino acids Molecular Weight 60kDa Product Format Lyophilized powder NCBI Gene Id 6714 Host Rabbit Clonality Polyclonal Official Gene Full Name V-src sarcoma (Schmidt-Ruppin A-2) viral oncogene homolog (avian) Gene Family SH2D This is a rabbit polyclonal antibody against SRC. It was validated on Western Blot by Aviva Systems Biology. At Aviva Systems Biology we manufacture rabbit polyclonal antibodies on a large scale (200-1000 Description products/month) of high throughput manner. Our antibodies are peptide based and protein family oriented. We usually provide antibodies covering each member of a whole protein family of your interest. We also use our best efforts to provide you antibodies recognize various epitopes of a target protein. For availability of antibody needed for your experiment, please inquire (). Peptide Sequence Synthetic peptide located within the following region: QTPSKPASADGHRGPSAAFAPAAAEPKLFGGFNSSDTVTSPQRAGPLAGG This gene is highly similar to the v-src gene of Rous sarcoma virus. This proto-oncogene may play a role in the Description of Target regulation of embryonic development and cell growth. SRC protein is a tyrosine-protein kinase whose activity can be inhibited by phosphorylation by c-SRC kinase. Mutations in this gene could be involved in the -
By Submitted in Partial Satisfaction of the Requirements for Degree of in In
Developments of Two Imaging based Technologies for Cell Biology Researches by Xiaowei Yan DISSERTATION Submitted in partial satisfaction of the requirements for degree of DOCTOR OF PHILOSOPHY in Biochemistry and Molecular Biology in the GRADUATE DIVISION of the UNIVERSITY OF CALIFORNIA, SAN FRANCISCO Approved: ______________________________________________________________________________Ronald Vale Chair ______________________________________________________________________________Jonathan Weissman ______________________________________________________________________________Orion Weiner ______________________________________________________________________________ ______________________________________________________________________________ Committee Members Copyright 2021 By Xiaowei Yan ii DEDICATION Everything happens for the best. To my family, who supported me with all their love. iii ACKNOWLEDGEMENTS The greatest joy of my PhD has been joining UCSF, working and learning with such a fantastic group of scientists. I am extremely grateful for all the support and mentorship I received and would like to thank: My mentor, Ron Vale, who is such a great and generous person. Thank you for showing me that science is so much fun and thank you for always giving me the freedom in pursuing my interest. I am grateful for all the guidance from you and thank you for always supporting me whenever I needed. You are a person full of wisdom, and I have been learning so much from you and your attitude to science, science community and even life will continue inspire me. Thank you for being my mentor and thank you for being such a great mentor. Everyone else in Vale lab, past and present, for making our lab a sweet home. I would like to give my special thank to Marvin (Marvin Tanenbaum) and Nico (Nico Stuurman), two other mentors for me in the lab. I would like to thank them for helping me adapt to our lab, for all the valuable advice and for all the happiness during the time that we work together. -
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. -
Systematic Description of the Expression and Prognostic Value of M6A Regulators in Human Ovarian Cancer
Systematic Description of the Expression and Prognostic Value of M6A Regulators in Human Ovarian Cancer Yuwei Chen Fujian Medical University Fujian Cancer Hospital Yang Sun ( [email protected] ) Fujian Cancer Hospital https://orcid.org/0000-0003-4224-8832 Xinbei Chen Fujian Medical University Fujian Cancer Hospital Siming Li Fujian Medical University Fujian Cancer Hospital Hongmei Xia Fujian Cancer Hospital Research Keywords: m6A regulators, m6A, ovarian cancer, Prognostic values, bioinformatics analysis. Posted Date: December 22nd, 2020 DOI: https://doi.org/10.21203/rs.3.rs-131682/v1 License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Systematic description of the expression and prognostic value of m6A regulators in human ovarian cancer 1 Yuwei Chen1, Yang Sun1*, Xinbei Chen1, Siming Li1, Hongmei Xia1 2 * Correspondence: 3 Yang Sun 4 [email protected] 5 Total words:5253 6 Total Figures and Tables: 11 Figures and 3 Tables 7 Keywords: m6A regulators, m6A, ovarian cancer, Prognostic values, 8 bioinformatics analysis. 9 Abstract 10 Background: N6-methyladenine (m6A) methylation, known as a kind of RNA 11 methylation regulator, has become a hotspot for research in the life sciences in recent 12 years. The existing studies revealed that m6A regulators helped to regulate the 13 progression of several malignant tumors. However, the expression mode and 14 prognostic value of m6A regulators in ovarian cancer have not been fully elucidated. 15 Methods: ONCOMINE, GEPIA, Human protein atlas, Kaplan-meier, UALCAN, 16 cBioPortal, GeneMANIA, DAVID, Sring, and Metascape were utilized in this study. 17 Results: In this study, through a comprehensive use of multiple database systems, 18 m6A regulators-induced mRNA and protein expression levels and their prognostic 19 value in the epithelial ovarian cancer of various histological types were analyzed. -
Epigenetic Mechanisms of Lncrnas Binding to Protein in Carcinogenesis
cancers Review Epigenetic Mechanisms of LncRNAs Binding to Protein in Carcinogenesis Tae-Jin Shin, Kang-Hoon Lee and Je-Yoel Cho * Department of Biochemistry, BK21 Plus and Research Institute for Veterinary Science, School of Veterinary Medicine, Seoul National University, Seoul 08826, Korea; [email protected] (T.-J.S.); [email protected] (K.-H.L.) * Correspondence: [email protected]; Tel.: +82-02-800-1268 Received: 21 September 2020; Accepted: 9 October 2020; Published: 11 October 2020 Simple Summary: The functional analysis of lncRNA, which has recently been investigated in various fields of biological research, is critical to understanding the delicate control of cells and the occurrence of diseases. The interaction between proteins and lncRNA, which has been found to be a major mechanism, has been reported to play an important role in cancer development and progress. This review thus organized the lncRNAs and related proteins involved in the cancer process, from carcinogenesis to metastasis and resistance to chemotherapy, to better understand cancer and to further develop new treatments for it. This will provide a new perspective on clinical cancer diagnosis, prognosis, and treatment. Abstract: Epigenetic dysregulation is an important feature for cancer initiation and progression. Long non-coding RNAs (lncRNAs) are transcripts that stably present as RNA forms with no translated protein and have lengths larger than 200 nucleotides. LncRNA can epigenetically regulate either oncogenes or tumor suppressor genes. Nowadays, the combined research of lncRNA plus protein analysis is gaining more attention. LncRNA controls gene expression directly by binding to transcription factors of target genes and indirectly by complexing with other proteins to bind to target proteins and cause protein degradation, reduced protein stability, or interference with the binding of other proteins. -
'Next- Generation' Sequencing Data Analysis
Novel Algorithm Development for ‘Next- Generation’ Sequencing Data Analysis Agne Antanaviciute Submitted in accordance with the requirements for the degree of Doctor of Philosophy University of Leeds School of Medicine Leeds Institute of Biomedical and Clinical Sciences 12/2017 ii The candidate confirms that the work submitted is her own, except where work which has formed part of jointly-authored publications has been included. The contribution of the candidate and the other authors to this work has been explicitly given within the thesis where reference has been made to the work of others. This copy has been supplied on the understanding that it is copyright material and that no quotation from the thesis may be published without proper acknowledgement ©2017 The University of Leeds and Agne Antanaviciute The right of Agne Antanaviciute to be identified as Author of this work has been asserted by her in accordance with the Copyright, Designs and Patents Act 1988. Acknowledgements I would like to thank all the people who have contributed to this work. First and foremost, my supervisors Dr Ian Carr, Professor David Bonthron and Dr Christopher Watson, who have provided guidance, support and motivation. I could not have asked for a better supervisory team. I would also like to thank my collaborators Dr Belinda Baquero and Professor Adrian Whitehouse for opening new, interesting research avenues. A special thanks to Dr Belinda Baquero for all the hard wet lab work without which at least half of this thesis would not exist. Thanks to everyone at the NGS Facility – Carolina Lascelles, Catherine Daley, Sally Harrison, Ummey Hany and Laura Crinnion – for the generation of NGS data used in this work and creating a supportive and stimulating work environment. -
A Novel Hypoxic Long Noncoding RNA KB-1980E6.3 Maintains Breast Cancer Stem Cell Stemness Via Interacting with IGF2BP1 to Facilitate C-Myc Mrna Stability
Oncogene (2021) 40:1609–1627 https://doi.org/10.1038/s41388-020-01638-9 ARTICLE A novel hypoxic long noncoding RNA KB-1980E6.3 maintains breast cancer stem cell stemness via interacting with IGF2BP1 to facilitate c-Myc mRNA stability 1 2 3 4 1 1 1 1 1 Pengpeng Zhu ● Fang He ● Yixuan Hou ● Gang Tu ● Qiao Li ● Ting Jin ● Huan Zeng ● Yilu Qin ● Xueying Wan ● 1 1 5 1 Yina Qiao ● Yuxiang Qiu ● Yong Teng ● Manran Liu Received: 15 June 2020 / Revised: 13 November 2020 / Accepted: 18 December 2020 / Published online: 19 January 2021 © The Author(s), under exclusive licence to Springer Nature Limited 2021. This article is published with open access Abstract The hostile hypoxic microenvironment takes primary responsibility for the rapid expansion of breast cancer tumors. However, the underlying mechanism is not fully understood. Here, using RNA sequencing (RNA-seq) analysis, we identified a hypoxia-induced long noncoding RNA (lncRNA) KB-1980E6.3, which is aberrantly upregulated in clinical breast cancer tissues and closely correlated with poor prognosis of breast cancer patients. The enhanced lncRNA KB- 1980E6.3 facilitates breast cancer stem cells (BCSCs) self-renewal and tumorigenesis under hypoxic microenvironment both 1234567890();,: 1234567890();,: in vitro and in vivo. Mechanistically, lncRNA KB-1980E6.3 recruited insulin-like growth factor 2 mRNA-binding protein 1 (IGF2BP1) to form a lncRNA KB-1980E6.3/IGF2BP1/c-Myc signaling axis that retained the stability of c-Myc mRNA through increasing binding of IGF2BP1 with m6A-modified c-Myc coding region instability determinant (CRD) mRNA. In conclusion, we confirm that lncRNA KB-1980E6.3 maintains the stemness of BCSCs through lncRNA KB-1980E6.3/ IGF2BP1/c-Myc axis and suggest that disrupting this axis might provide a new therapeutic target for refractory hypoxic tumors. -
Large-Scale Functional Prediction of Individual M6a RNA Methylation Sites from an RNA Co-Methylation Network
Wu et al. BMC Bioinformatics (2019) 20:223 https://doi.org/10.1186/s12859-019-2840-3 RESEARCHARTICLE Open Access m6Acomet: large-scale functional prediction of individual m6A RNA methylation sites from an RNA co- methylation network Xiangyu Wu1,2, Zhen Wei1,2, Kunqi Chen1,2, Qing Zhang1,4, Jionglong Su5, Hui Liu6, Lin Zhang6* and Jia Meng1,3* Abstract Background: Over one hundred different types of post-transcriptional RNA modifications have been identified in human. Researchers discovered that RNA modifications can regulate various biological processes, and RNA methylation, especially N6-methyladenosine, has become one of the most researched topics in epigenetics. Results: To date, the study of epitranscriptome layer gene regulation is mostly focused on the function of mediator proteins of RNA methylation, i.e., the readers, writers and erasers. There is limited investigation of the functional relevance of individual m6A RNA methylation site. To address this, we annotated human m6A sites in large-scale based on the guilt-by-association principle from an RNA co-methylation network. It is constructed based on public human MeRIP-Seq datasets profiling the m6A epitranscriptome under 32 independent experimental conditions. By systematically examining the network characteristics obtained from the RNA methylation profiles, a total of 339,158 putative gene ontology functions associated with 1446 human m6A sites were identified. These are biological functions that may be regulated at epitranscriptome layer via reversible m6A RNA methylation. The results were further validated on a soft benchmark by comparing to a random predictor. Conclusions: An online web server m6Acomet was constructed to support direct query for the predicted biological functions of m6A sites as well as the sites exhibiting co-methylated patterns at the epitranscriptome layer. -
Supplementary Materials
Supplementary materials Supplementary Table S1: MGNC compound library Ingredien Molecule Caco- Mol ID MW AlogP OB (%) BBB DL FASA- HL t Name Name 2 shengdi MOL012254 campesterol 400.8 7.63 37.58 1.34 0.98 0.7 0.21 20.2 shengdi MOL000519 coniferin 314.4 3.16 31.11 0.42 -0.2 0.3 0.27 74.6 beta- shengdi MOL000359 414.8 8.08 36.91 1.32 0.99 0.8 0.23 20.2 sitosterol pachymic shengdi MOL000289 528.9 6.54 33.63 0.1 -0.6 0.8 0 9.27 acid Poricoic acid shengdi MOL000291 484.7 5.64 30.52 -0.08 -0.9 0.8 0 8.67 B Chrysanthem shengdi MOL004492 585 8.24 38.72 0.51 -1 0.6 0.3 17.5 axanthin 20- shengdi MOL011455 Hexadecano 418.6 1.91 32.7 -0.24 -0.4 0.7 0.29 104 ylingenol huanglian MOL001454 berberine 336.4 3.45 36.86 1.24 0.57 0.8 0.19 6.57 huanglian MOL013352 Obacunone 454.6 2.68 43.29 0.01 -0.4 0.8 0.31 -13 huanglian MOL002894 berberrubine 322.4 3.2 35.74 1.07 0.17 0.7 0.24 6.46 huanglian MOL002897 epiberberine 336.4 3.45 43.09 1.17 0.4 0.8 0.19 6.1 huanglian MOL002903 (R)-Canadine 339.4 3.4 55.37 1.04 0.57 0.8 0.2 6.41 huanglian MOL002904 Berlambine 351.4 2.49 36.68 0.97 0.17 0.8 0.28 7.33 Corchorosid huanglian MOL002907 404.6 1.34 105 -0.91 -1.3 0.8 0.29 6.68 e A_qt Magnogrand huanglian MOL000622 266.4 1.18 63.71 0.02 -0.2 0.2 0.3 3.17 iolide huanglian MOL000762 Palmidin A 510.5 4.52 35.36 -0.38 -1.5 0.7 0.39 33.2 huanglian MOL000785 palmatine 352.4 3.65 64.6 1.33 0.37 0.7 0.13 2.25 huanglian MOL000098 quercetin 302.3 1.5 46.43 0.05 -0.8 0.3 0.38 14.4 huanglian MOL001458 coptisine 320.3 3.25 30.67 1.21 0.32 0.9 0.26 9.33 huanglian MOL002668 Worenine -
Coding RNA Genes
Review A guide to naming human non-coding RNA genes Ruth L Seal1,2,* , Ling-Ling Chen3, Sam Griffiths-Jones4, Todd M Lowe5, Michael B Mathews6, Dawn O’Reilly7, Andrew J Pierce8, Peter F Stadler9,10,11,12,13, Igor Ulitsky14 , Sandra L Wolin15 & Elspeth A Bruford1,2 Abstract working on non-coding RNA (ncRNA) nomenclature in the mid- 1980s with the approval of initial gene symbols for mitochondrial Research on non-coding RNA (ncRNA) is a rapidly expanding field. transfer RNA (tRNA) genes. Since then, we have worked closely Providing an official gene symbol and name to ncRNA genes brings with experts in the ncRNA field to develop symbols for many dif- order to otherwise potential chaos as it allows unambiguous ferent kinds of ncRNA genes. communication about each gene. The HUGO Gene Nomenclature The number of genes that the HGNC has named per ncRNA class Committee (HGNC, www.genenames.org) is the only group with is shown in Fig 1, and ranges in number from over 4,500 long the authority to approve symbols for human genes. The HGNC ncRNA (lncRNA) genes and over 1,900 microRNA genes, to just four works with specialist advisors for different classes of ncRNA to genes in the vault and Y RNA classes. Every gene symbol has a ensure that ncRNA nomenclature is accurate and informative, Symbol Report on our website, www.genenames.org, which where possible. Here, we review each major class of ncRNA that is displays the gene symbol, gene name, chromosomal location and currently annotated in the human genome and describe how each also includes links to key resources such as Ensembl (Zerbino et al, class is assigned a standardised nomenclature. -
Long Non-Coding RNA Lncshgl Recruits Hnrnpa1 to Suppress Hepatic Gluconeogenesis and Lipogenesis
Page 1 of 60 Diabetes Long non-coding RNA LncSHGL recruits hnRNPA1 to suppress hepatic gluconeogenesis and lipogenesis Junpei Wang1,2#, Weili Yang1,2#, Zhenzhen Chen1, Ji Chen1, Yuhong Meng1, Biaoqi Feng1, Libo Sun3, Lin Dou4, Jian Li4, Qinghua Cui2*, Jichun Yang1* 1Department of Physiology and Pathophysiology, School of Basic Medical Sciences Key Laboratory of Molecular Cardiovascular Sciences of the Ministry of Education Center for Non-coding RNA Medicine Peking University Health Science Center Beijing 100191, China 2Department of Biomedical Informatics, School of Basic Medical Sciences Key Laboratory of Molecular Cardiovascular Sciences of the Ministry of Education, Center for Non-coding RNA Medicine Peking University Health Science Center, Beijing 100191, China 3Beijing You An Hospital,Capital Medical University, Beijing 100069, China 4Key Laboratory of Geriatrics, Beijing Institute of Geriatrics & Beijing Hospital, Ministry of Health, Beijing 100730, China #These authors contributed equally to this work *Correspondence to: Jichun Yang, Ph.D. Department of Physiology and Pathophysiology, School of Basic Medical Sciences Peking University Health Science Center, Beijing 100191, China Email: [email protected]; Tel: (+86) 10-82801403 Or to: Qinghua Cui, Ph.D. Department of Biomedical Informatics, School of Basic Medical Sciences Peking University Health Science Center, Beijing 100191, China Email:[email protected]; Tel:(+86)10-82801585 1 Diabetes Publish Ahead of Print, published online January 30, 2018 Diabetes Page 2 of 60 Abstract Mammalian genomes encode a huge number of LncRNAs with unknown functions. This study determined the role and mechanism of a new LncRNA, LncRNA Suppressor of Hepatic Gluconeogenesis and Lipogenesis (LncSHGL), in regulating hepatic glucose/lipid metabolism. -