Embryonic Stem Cells: Protein Interaction Networks*
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Combined Analysis of Chip-Seq and Gene Microarray Datasets Identify the E2-Mediated Genes in Erα-Dependent Manner in Osteosarcoma
ONCOLOGY REPORTS 38: 2335-2342, 2017 Combined analysis of ChIP-seq and gene microarray datasets identify the E2-mediated genes in ERα-dependent manner in osteosarcoma KANGSONG TIAN1, WEI QI1, QIAN YAN1, FEnG ZHanG1, DELEI SONG1, HaIyanG ZHanG2 and MING LV1 1Trauma Department of Orthopedics, 2Microscopic Department of Orthopedics, Zibo Central Hospital, Zibo, Shandong 255036, P.R. China Received March 14, 2017; Accepted August 11, 2017 DOI: 10.3892/or.2017.5914 Abstract. Osteosarcoma is a common bone tumor which is Introduction affected by E2, the most representative estrogen. Gene regula- tion function of E2 is highly dependent on estrogen receptor. ESR1, also known as ER-alpha or ERα, is an important The purpose of this study was to explore the gene regulation estrogen receptor (ER) and involves in the gene regula- patterns of E2 through estrogen receptor α (ESR1) in osteo- tion in various diseases and biological processes, including sarcoma based on the combined analysis of ChIP-seq and breast cancer (1,2), osteosarcoma (3) and cell growth (4). gene microarray. All of the datasets were downloaded from 17β-estradiol (E2) is one of the most representative estrogens the Gene Expression Omnibus (GEO). Differential expression responsible for the development and reproductive capability genes (DEGs) in E2 treated U2OS cells expressing ESR1 of female characteristics (5). Besides, it participates in the (U2OS-ERα) compared with those treated with vehicle were progression of many diseases, for example, E2 could regulate obtained based on R programming software. ESR1-specific the proliferation of breast cancer cells through focal adhesion binding sites (peaks) in E2 treated U2OS cells were identified and chemokine signaling pathways (6); through autophagy through MACS. -
Rep 467 Morrish & Sinclair
Reproduction (2002) 124, 447–457 Review Vertebrate sex determination: many means to an end Bronwyn C. Morrish and Andrew H. Sinclair* Murdoch Children’s Research Institute, Royal Children’s Hospital, Flemington Rd, Melbourne, Victoria 3052, Australia The differentiation of a testis or ovary from a bipotential gonadal primordium is a develop- mental process common to mammals, birds and reptiles. Since the discovery of SRY, the Y-linked testis-determining gene in mammals, extensive efforts have failed to find its orthologue in other vertebrates, indicating evolutionary plasticity in the switch that triggers sex determination. Several other genes are known to be important for sex determination in mammals, such as SOX9, AMH, WT1, SF1, DAX1 and DMRT1. Analyses of these genes in humans with gonadal dysgenesis, mouse models and using in vitro cell culture assays have revealed that sex determination results from a complex interplay between the genes in this network. All of these genes are conserved in other vertebrates, such as chickens and alligators, and show gonad-specific expression in these species during the period of sex determination. Intriguingly, the sequence, sex specificity and timing of expression of some of these genes during sex determination differ among species. This finding indicates that the interplay between genes in the regulatory network leading to gonad development differs between vertebrates. However, despite this, the development of a testis or ovary from a bipotential gonad is remarkably similar across vertebrates. The existence of two sexes is nearly universal in the animal and alligators. Ectopic administration of oestrogen or kingdom and although gonadal morphogenesis is remark- inhibitors of oestrogen synthesis during a critical period of ably similar across vertebrates, the sex-determining mecha- gonadogenesis in chickens and alligators can feminize or nism varies considerably. -
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. -
Prospective Isolation of NKX2-1–Expressing Human Lung Progenitors Derived from Pluripotent Stem Cells
The Journal of Clinical Investigation RESEARCH ARTICLE Prospective isolation of NKX2-1–expressing human lung progenitors derived from pluripotent stem cells Finn Hawkins,1,2 Philipp Kramer,3 Anjali Jacob,1,2 Ian Driver,4 Dylan C. Thomas,1 Katherine B. McCauley,1,2 Nicholas Skvir,1 Ana M. Crane,3 Anita A. Kurmann,1,5 Anthony N. Hollenberg,5 Sinead Nguyen,1 Brandon G. Wong,6 Ahmad S. Khalil,6,7 Sarah X.L. Huang,3,8 Susan Guttentag,9 Jason R. Rock,4 John M. Shannon,10 Brian R. Davis,3 and Darrell N. Kotton1,2 2 1Center for Regenerative Medicine, and The Pulmonary Center and Department of Medicine, Boston University School of Medicine, Boston, Massachusetts, USA. 3Center for Stem Cell and Regenerative Medicine, Brown Foundation Institute of Molecular Medicine, University of Texas Health Science Center, Houston, Texas, USA. 4Department of Anatomy, UCSF, San Francisco, California, USA. 5Division of Endocrinology, Diabetes and Metabolism, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA. 6Department of Biomedical Engineering and Biological Design Center, Boston University, Boston, Massachusetts, USA. 7Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, Massachusetts, USA. 8Columbia Center for Translational Immunology & Columbia Center for Human Development, Columbia University Medical Center, New York, New York, USA. 9Department of Pediatrics, Monroe Carell Jr. Children’s Hospital, Vanderbilt University, Nashville, Tennessee, USA. 10Division of Pulmonary Biology, Cincinnati Children’s Hospital, Cincinnati, Ohio, USA. It has been postulated that during human fetal development, all cells of the lung epithelium derive from embryonic, endodermal, NK2 homeobox 1–expressing (NKX2-1+) precursor cells. -
Genomic Approaches to Deconstruct Pluripotency
GG12CH08-Daley ARI 26 July 2011 14:10 Genomic Approaches to Deconstruct Pluripotency Yuin-Han Loh,1,2,∗ Lin Yang,1,2,∗ Jimmy Chen Yang,1,2,∗∗ Hu Li,3,4,∗∗ James J. Collins,3,4,5 and George Q. Daley1,2,5,6,7 1Stem Cell Transplantation Program, Division of Pediatric Hematology/Oncology, Children’s Hospital Boston; Dana-Farber Cancer Institute; and Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, Massachusetts 02115; email: [email protected] 2Harvard Stem Cell Institute, Cambridge, Massachusetts 02115 3Department of Biomedical Engineering and Center for BioDynamics, Boston University, Boston, Massachusetts 02215 4Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, Massachusetts 02115 5Howard Hughes Medical Institute, Boston, Massachusetts 02115 6Division of Hematology, Brigham and Women’s Hospital, Boston, Massachusetts 02115 7Manton Center for Orphan Disease Research, Boston, Massachusetts 02115 Annu. Rev. Genomics Hum. Genet. 2011. Keywords 12:165–85 transcription regulation, epigenetics, histone modifications, DNA First published online as a Review in Advance on July 25, 2011 methylation, pluripotent stem cells The Annual Review of Genomics and Human Genetics Abstract is online at genom.annualreviews.org Embryonic stem cells (ESCs) first derived from the inner cell mass of by Boston University on 10/07/11. For personal use only. This article’s doi: 10.1146/annurev-genom-082410-101506 blastocyst-stage embryos have the unique capacity of indefinite self- renewal and potential to differentiate into all somatic cell types. Similar Copyright c 2011 by Annual Reviews. All rights reserved developmental potency can be achieved by reprogramming differen- tiated somatic cells into induced pluripotent stem cells (iPSCs). -
Regulation of Transcription and Regulatory Networks for Muscle Growth * * * * A
Regulation Of Transcription And Regulatory Networks For Muscle Growth * * * * A. Reverter , N.J. Hudson , Q. Gu and B.P. Dalrymple Introduction The advent of microarray gene expression technology has provided animal scientists with an unprecedented ability to profile the transcriptional changes during skeletal muscle growth. With respect to meat quality, most of the effort has concentrated on the understanding of fat and energy metabolism (reviewed by Hausman et al . (2009)). Graugnard et al . (2009) explored the network among 31 genes associated with aspects of adipogenesis and energy metabolism in bovine skeletal muscle and in response to two distinct diets. Also, Freyssenet (2007) reviewed the roles that energy-sensing molecules and mitochondria have in the regulation of gene expression in muscle. However, other mechanisms such as cell cycle, glycolysis, extra-cellular matrix, ribosomal proteins and the immune system play a significant role in development, and this role can work in a tissue-specific manner. Hudson et al . (2009a) reported various functional modules underpinning the transcriptional regulation of bovine skeletal muscle. The authors integrated a total of six gene co-expression networks, each developed using the PCIT algorithm (Reverter and Chan (2008)), and proposed a Module-to-Regulator heuristic by which those transcription factors (TF) with the highest average absolute correlation co-expression with the genes present in each module are deemed to be the relevant regulators. However, this Module-to-Regulator approach failed to capture some well-known regulators of muscle fibre type composition, and the use of more sophisticated methods such as the differential wiring approach of Hudson et al . -
Watsonjn2018.Pdf (1.780Mb)
UNIVERSITY OF CENTRAL OKLAHOMA Edmond, Oklahoma Department of Biology Investigating Differential Gene Expression in vivo of Cardiac Birth Defects in an Avian Model of Maternal Phenylketonuria A THESIS SUBMITTED TO THE GRADUATE FACULTY In partial fulfillment of the requirements For the degree of MASTER OF SCIENCE IN BIOLOGY By Jamie N. Watson Edmond, OK June 5, 2018 J. Watson/Dr. Nikki Seagraves ii J. Watson/Dr. Nikki Seagraves Acknowledgements It is difficult to articulate the amount of gratitude I have for the support and encouragement I have received throughout my master’s thesis. Many people have added value and support to my life during this time. I am thankful for the education, experience, and friendships I have gained at the University of Central Oklahoma. First, I would like to thank Dr. Nikki Seagraves for her mentorship and friendship. I lucked out when I met her. I have enjoyed working on this project and I am very thankful for her support. I would like thank Thomas Crane for his support and patience throughout my master’s degree. I would like to thank Dr. Shannon Conley for her continued mentorship and support. I would like to thank Liz Bullen and Dr. Eric Howard for their training and help on this project. I would like to thank Kristy Meyer for her friendship and help throughout graduate school. I would like to thank my committee members Dr. Robert Brennan and Dr. Lilian Chooback for their advisement on this project. Also, I would like to thank the biology faculty and staff. I would like to thank the Seagraves lab members: Jailene Canales, Kayley Pate, Mckayla Muse, Grace Thetford, Kody Harvey, Jordan Guffey, and Kayle Patatanian for their hard work and support. -
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. -
The Role of at Rich Interactive Domain 3A in the Tumorigenesis of Colorectal Carcinomas
The role of AT rich interactive domain 3A in the tumorigenesis of colorectal carcinomas Meiying Song Department of Medical Science The Graduate School, Yonsei University The role of AT rich interactive domain 3A in the tumorigenesis of colorectal carcinomas Directed by Professor Hoguen Kim The Doctoral Dissertation submitted to the Department of Medicine, the Graduate School of Yonsei University in partial fulfillment of the requirements for the degree of Doctor of Philosophy Meiying Song December 2012 ACKNOWLEDGEMENTS I would like to express my sincere gratitude to all those who made invaluable contributions to my research directly or indirectly. Without their invaluable helps and generous encouragements, this thesis could not have reached its present form. I am deeply indebted to my supervisor Professor Hoguen Kim, and Dr. Hyunki Kim working in Department of Pathology, Yonsei University. Their invaluable help, stimulating suggestion, constant encouragement, and patient guidance helped me in all the time of my research. My colleagues from Department of Pathology, Yonsei University also gave me lots of valuable advice when I was faced with problems during the process of my research and writing this thesis. I want to thank them for all their helps. Especially, I should give my thanks to my parents. It was their patient love and encouragement that enabled me to finish my doctorate in education at medical college of Yonsei University. TABLE OF CONTENTS ABSTRACT…….…………………………………………………………....1 I. INTRODUCTION.……………………………………………………….…..3 II. MATERIALS AND METHODS....……………………………….………...8 1. Patients and samples……………….………………………….…………...8 2. Tissue microarray and immunohistochemistry…………………….……...8 3. Evaluation of staining……………………………………………….……..9 4. Cell lines and cultures……………………………………………………..9 5. -
4-6 Weeks Old Female C57BL/6 Mice Obtained from Jackson Labs Were Used for Cell Isolation
Methods Mice: 4-6 weeks old female C57BL/6 mice obtained from Jackson labs were used for cell isolation. Female Foxp3-IRES-GFP reporter mice (1), backcrossed to B6/C57 background for 10 generations, were used for the isolation of naïve CD4 and naïve CD8 cells for the RNAseq experiments. The mice were housed in pathogen-free animal facility in the La Jolla Institute for Allergy and Immunology and were used according to protocols approved by the Institutional Animal Care and use Committee. Preparation of cells: Subsets of thymocytes were isolated by cell sorting as previously described (2), after cell surface staining using CD4 (GK1.5), CD8 (53-6.7), CD3ε (145- 2C11), CD24 (M1/69) (all from Biolegend). DP cells: CD4+CD8 int/hi; CD4 SP cells: CD4CD3 hi, CD24 int/lo; CD8 SP cells: CD8 int/hi CD4 CD3 hi, CD24 int/lo (Fig S2). Peripheral subsets were isolated after pooling spleen and lymph nodes. T cells were enriched by negative isolation using Dynabeads (Dynabeads untouched mouse T cells, 11413D, Invitrogen). After surface staining for CD4 (GK1.5), CD8 (53-6.7), CD62L (MEL-14), CD25 (PC61) and CD44 (IM7), naïve CD4+CD62L hiCD25-CD44lo and naïve CD8+CD62L hiCD25-CD44lo were obtained by sorting (BD FACS Aria). Additionally, for the RNAseq experiments, CD4 and CD8 naïve cells were isolated by sorting T cells from the Foxp3- IRES-GFP mice: CD4+CD62LhiCD25–CD44lo GFP(FOXP3)– and CD8+CD62LhiCD25– CD44lo GFP(FOXP3)– (antibodies were from Biolegend). In some cases, naïve CD4 cells were cultured in vitro under Th1 or Th2 polarizing conditions (3, 4). -
Supplemental Materials ZNF281 Enhances Cardiac Reprogramming
Supplemental Materials ZNF281 enhances cardiac reprogramming by modulating cardiac and inflammatory gene expression Huanyu Zhou, Maria Gabriela Morales, Hisayuki Hashimoto, Matthew E. Dickson, Kunhua Song, Wenduo Ye, Min S. Kim, Hanspeter Niederstrasser, Zhaoning Wang, Beibei Chen, Bruce A. Posner, Rhonda Bassel-Duby and Eric N. Olson Supplemental Table 1; related to Figure 1. Supplemental Table 2; related to Figure 1. Supplemental Table 3; related to the “quantitative mRNA measurement” in Materials and Methods section. Supplemental Table 4; related to the “ChIP-seq, gene ontology and pathway analysis” and “RNA-seq” and gene ontology analysis” in Materials and Methods section. Supplemental Figure S1; related to Figure 1. Supplemental Figure S2; related to Figure 2. Supplemental Figure S3; related to Figure 3. Supplemental Figure S4; related to Figure 4. Supplemental Figure S5; related to Figure 6. Supplemental Table S1. Genes included in human retroviral ORF cDNA library. Gene Gene Gene Gene Gene Gene Gene Gene Symbol Symbol Symbol Symbol Symbol Symbol Symbol Symbol AATF BMP8A CEBPE CTNNB1 ESR2 GDF3 HOXA5 IL17D ADIPOQ BRPF1 CEBPG CUX1 ESRRA GDF6 HOXA6 IL17F ADNP BRPF3 CERS1 CX3CL1 ETS1 GIN1 HOXA7 IL18 AEBP1 BUD31 CERS2 CXCL10 ETS2 GLIS3 HOXB1 IL19 AFF4 C17ORF77 CERS4 CXCL11 ETV3 GMEB1 HOXB13 IL1A AHR C1QTNF4 CFL2 CXCL12 ETV7 GPBP1 HOXB5 IL1B AIMP1 C21ORF66 CHIA CXCL13 FAM3B GPER HOXB6 IL1F3 ALS2CR8 CBFA2T2 CIR1 CXCL14 FAM3D GPI HOXB7 IL1F5 ALX1 CBFA2T3 CITED1 CXCL16 FASLG GREM1 HOXB9 IL1F6 ARGFX CBFB CITED2 CXCL3 FBLN1 GREM2 HOXC4 IL1F7 -
Supplementary Table S4. FGA Co-Expressed Gene List in LUAD
Supplementary Table S4. FGA co-expressed gene list in LUAD tumors Symbol R Locus Description FGG 0.919 4q28 fibrinogen gamma chain FGL1 0.635 8p22 fibrinogen-like 1 SLC7A2 0.536 8p22 solute carrier family 7 (cationic amino acid transporter, y+ system), member 2 DUSP4 0.521 8p12-p11 dual specificity phosphatase 4 HAL 0.51 12q22-q24.1histidine ammonia-lyase PDE4D 0.499 5q12 phosphodiesterase 4D, cAMP-specific FURIN 0.497 15q26.1 furin (paired basic amino acid cleaving enzyme) CPS1 0.49 2q35 carbamoyl-phosphate synthase 1, mitochondrial TESC 0.478 12q24.22 tescalcin INHA 0.465 2q35 inhibin, alpha S100P 0.461 4p16 S100 calcium binding protein P VPS37A 0.447 8p22 vacuolar protein sorting 37 homolog A (S. cerevisiae) SLC16A14 0.447 2q36.3 solute carrier family 16, member 14 PPARGC1A 0.443 4p15.1 peroxisome proliferator-activated receptor gamma, coactivator 1 alpha SIK1 0.435 21q22.3 salt-inducible kinase 1 IRS2 0.434 13q34 insulin receptor substrate 2 RND1 0.433 12q12 Rho family GTPase 1 HGD 0.433 3q13.33 homogentisate 1,2-dioxygenase PTP4A1 0.432 6q12 protein tyrosine phosphatase type IVA, member 1 C8orf4 0.428 8p11.2 chromosome 8 open reading frame 4 DDC 0.427 7p12.2 dopa decarboxylase (aromatic L-amino acid decarboxylase) TACC2 0.427 10q26 transforming, acidic coiled-coil containing protein 2 MUC13 0.422 3q21.2 mucin 13, cell surface associated C5 0.412 9q33-q34 complement component 5 NR4A2 0.412 2q22-q23 nuclear receptor subfamily 4, group A, member 2 EYS 0.411 6q12 eyes shut homolog (Drosophila) GPX2 0.406 14q24.1 glutathione peroxidase