Comprehensive Epigenome Characterization Reveals Diverse Transcriptional Regulation Across Human Vascular Endothelial Cells
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Deciphering the Functions of Ets2, Pten and P53 in Stromal Fibroblasts in Multiple
Deciphering the Functions of Ets2, Pten and p53 in Stromal Fibroblasts in Multiple Breast Cancer Models DISSERTATION Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University By Julie Wallace Graduate Program in Molecular, Cellular and Developmental Biology The Ohio State University 2013 Dissertation Committee: Michael C. Ostrowski, PhD, Advisor Gustavo Leone, PhD Denis Guttridge, PhD Dawn Chandler, PhD Copyright by Julie Wallace 2013 Abstract Breast cancer is the second most common cancer in American women, and is also the second leading cause of cancer death in women. It is estimated that nearly a quarter of a million new cases of invasive breast cancer will be diagnosed in women in the United States this year, and approximately 40,000 of these women will die from breast cancer. Although death rates have been on the decline for the past decade, there is still much we need to learn about this disease to improve prevention, detection and treatment strategies. The majority of early studies have focused on the malignant tumor cells themselves, and much has been learned concerning mutations, amplifications and other genetic and epigenetic alterations of these cells. However more recent work has acknowledged the strong influence of tumor stroma on the initiation, progression and recurrence of cancer. Under normal conditions this stroma has been shown to have protective effects against tumorigenesis, however the transformation of tumor cells manipulates this surrounding environment to actually promote malignancy. Fibroblasts in particular make up a significant portion of this stroma, and have been shown to impact various aspects of tumor cell biology. -
(12) United States Patent (10) Patent No.: US 9,109,232 B2 Schwartz Et Al
US009 109232B2 (12) United States Patent (10) Patent No.: US 9,109,232 B2 Schwartz et al. (45) Date of Patent: Aug. 18, 2015 (54) ETS2 AND MESP1 GENERATE CARDIAC Islas et al., Transcription factors ETS2 and MESP1 transdifferentiate PROGENITORS FROM FIBROBLASTS human dermal fibroblasts into cardiac progenitors; PNAS, Published online before print Jul. 23, 2012, doi: 10.1073/pnas. 11202991.09, 2012.* (71) Applicants: University of Houston, Houston, TX Melotti et al., Ets-2 and c-Myb Act Independently in Regulating (US); Texas Heart Institute, Houston, Expression of the Hematopoietic StemCell Antigen CD34:JBC, vol. TX (US); The Texas A&M University 269, No. 41, pp. 25303-25309, 1994.* System, College Station, TX (US) Takahashi et al., Induction of pluripotent stem cells from adulthuman fibroblasts by defined factors; Cell, vol. 131, pp. 861-872, 2007.* Naldini et al. In vivo gene delivery and stable transduction of (72) Inventors: Robert J. Schwartz, Houston, TX (US); nondividing cells by a lentiviral vector; Science, vol. 272, pp. 263 Vladimir N. Potaman, Houston, TX 267, 1996.* (US); Jose Francisco Islas, Houston, TX European Patent Office; Office Action; European Application No. (US) 117114082; Jul 22, 2013. European Patent Office; Response to Office Action; European Appli (73) Assignees: University of Houston, Houston, TX cation No. 11711408.2; Aug. 30, 2013. Chinese Patent Office; Office Action; Chinese Patent Application No. (US); Texas Heart Institute, Houston, 2011800 19561.0; Sep. 18, 2013. TX (US); The Texas A&M University Chinese Patent Office; Office Action (English translation); Chinese System, College Station, TX (US) Patent Application No. 2011800 19561.0; Sep. -
EXTENDED MATERIALS and METHODS Animal Experimentation. All Experiments Were Performed in Agreement with the Swiss Law on Animal
EXTENDED MATERIALS AND METHODS Animal experimentation. All experiments were performed in agreement with the Swiss law on animal protection (LPA), under license No GE 81/14 (to DD). In situ hybridization. Whole mount in situ hybridizations were performed as described in (Woltering et al., 2014). Probes for the Hoxa11, Hoxa13, Hoxd8, Hoxd10, Hoxd12, Hoxd13 and Evx2 genes were synthetized and purified as previously reported (Herault et al., 1996; Woltering et al., 2014). Plasmids encoding the cDNAs of the Prrx2 and Dbx2 genes were purchased from Addgene and probes were synthetized as previously reported (Pierani et al., 1999; Stelnicki et al., 1998). Right or left forelimbs were dissected from stained embryos and photographied dorsally with a Leica MZ16 stereomicroscope. Pictures from left forelimbs are displayed inverted. RNA extraction. Total RNA was extracted from individual pairs of either wild type or double Hox13-/- mutant proximal and distal forelimb buds, using the RNeasy Micro Kit (Qiagen) following manufacturer instructions. A total of 100ng of pure total RNA was amplified following standard Illumina procedure for polyA-selected RNA. RNA-seq data generation. RNA sequencing (RNA-seq) libraries were prepared with the Illumina TruSeq Stranded mRNA protocol and sequenced on a HiSeq 2500 machine, as single-end, 100 base pairs (bp) reads. The preparation of libraries and sequencing were performed by the genomic platform of the University of Geneva. RNA-seq data analysis. A mutant version of the genome, encoding the Hoxd13/LacZ and the Hoxa13/Neo+ alleles (Fromental-Ramain et al., 1996; Kondo et al., 1998), was assembled and annotated and used as reference genome to map the Hoxa13-/- and Hoxd13-/- RNA-seq data. -
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. -
Detailed Review Paper on Retinoid Pathway Signalling
1 1 Detailed Review Paper on Retinoid Pathway Signalling 2 December 2020 3 2 4 Foreword 5 1. Project 4.97 to develop a Detailed Review Paper (DRP) on the Retinoid System 6 was added to the Test Guidelines Programme work plan in 2015. The project was 7 originally proposed by Sweden and the European Commission later joined the project as 8 a co-lead. In 2019, the OECD Secretariat was added to coordinate input from expert 9 consultants. The initial objectives of the project were to: 10 draft a review of the biology of retinoid signalling pathway, 11 describe retinoid-mediated effects on various organ systems, 12 identify relevant retinoid in vitro and ex vivo assays that measure mechanistic 13 effects of chemicals for development, and 14 Identify in vivo endpoints that could be added to existing test guidelines to 15 identify chemical effects on retinoid pathway signalling. 16 2. This DRP is intended to expand the recommendations for the retinoid pathway 17 included in the OECD Detailed Review Paper on the State of the Science on Novel In 18 vitro and In vivo Screening and Testing Methods and Endpoints for Evaluating 19 Endocrine Disruptors (DRP No 178). The retinoid signalling pathway was one of seven 20 endocrine pathways considered to be susceptible to environmental endocrine disruption 21 and for which relevant endpoints could be measured in new or existing OECD Test 22 Guidelines for evaluating endocrine disruption. Due to the complexity of retinoid 23 signalling across multiple organ systems, this effort was foreseen as a multi-step process. -
The International Human Epigenome Consortium (IHEC): a Blueprint for Scientific Collaboration and Discovery
The International Human Epigenome Consortium (IHEC): A Blueprint for Scientific Collaboration and Discovery Hendrik G. Stunnenberg1#, Martin Hirst2,3,# 1Department of Molecular Biology, Faculties of Science and Medicine, Radboud University, Nijmegen, The Netherlands 2Department of Microbiology and Immunology, Michael Smith Laboratories, University of British Columbia, Vancouver, BC, Canada V6T 1Z4. 3Canada’s Michael Smith Genome Science Center, BC Cancer Agency, Vancouver, BC, Canada V5Z 4S6 #Corresponding authors [email protected] [email protected] Abstract The International Human Epigenome Consortium (IHEC) coordinates the generation of a catalogue of high-resolution reference epigenomes of major primary human cell types. The studies now presented (cell.com/XXXXXXX) highlight the coordinated achievements of IHEC teams to gather and interpret comprehensive epigenomic data sets to gain insights in the epigenetic control of cell states relevant for human health and disease. One of the great mysteries in developmental biology is how the same genome can be read by cellular machinery to generate the plethora of different cell types required for eukaryotic life. As appreciation grew for the central roles of transcriptional and epigenetic mechanisms in specification of cellular fates and functions, researchers around the world encouraged scientific funding agencies to develop an organized and standardized effort to exploit epigenomic assays to shed additional light on this process (Beck, Olek et al. 1999, Jones and Martienssen 2005, American Association for Cancer Research Human Epigenome Task and European Union 2008). In March 2009, leading scientists and international health research funding agency representatives were invited to a meeting in Bethesda (MD, USA) to gauge the level of interest in an international epigenomics project and to identify potential areas of focus. -
A Genome-Wide Analysis of the ERF Gene Family in Sorghum
A genome-wide analysis of the ERF gene family in sorghum H.W. Yan, L. Hong, Y.Q. Zhou, H.Y. Jiang, S.W. Zhu, J. Fan and B.J. Cheng Key Laboratory of Crop Biology of Anhui Province, Anhui Agricultural University, Hefei, China Corresponding author: B.J. Cheng E-mail: [email protected] Genet. Mol. Res. 12 (2): 2038-2055 (2013) Received November 9, 2012 Accepted March 8, 2013 Published May 13, 2013 DOI http://dx.doi.org/10.4238/2013.May.13.1 ABSTRACT. The ethylene response factor (ERF) family are members of the APETALA2 (AP2)/ERF transcription factor superfamily; they are known to play an important role in plant adaptation to biotic and abiotic stress. ERF genes have been studied in Arabidopsis, rice, grape, and maize; however, there are few reports of ERF genes in sorghum. We identified 105 sorghum ERF (SbERF) genes, which were categorized into 12 groups (A-1 to A-6 and B-1 to B-6) based on their sequence similarity, and this new method of classification for ERF genes was then further characterized. A comprehensive bioinformatic analysis of SbERF genes was performed using a sorghum genomic database, to analyze the phylogeny of SbERF genes, identify other conserved motifs apart from the AP2/ERF domain, map SbERF genes to the 10 sorghum chromosomes, and determine the tissue-specific expression patterns of SbERF genes. Gene clustering indicates that SbERF genes were generated by tandem duplications. Comparison of SbERF genes with maize ERF homologs suggests lateral gene transfer between monocot species. These results can contribute to our understanting of Genetics and Molecular Research 12 (2): 2038-2055 (2013) ©FUNPEC-RP www.funpecrp.com.br Analysis of the ERF gene family in sorghum 2039 the evolution of the ERF gene family. -
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 -
Genome-Wide DNA Methylation Analysis of KRAS Mutant Cell Lines Ben Yi Tew1,5, Joel K
www.nature.com/scientificreports OPEN Genome-wide DNA methylation analysis of KRAS mutant cell lines Ben Yi Tew1,5, Joel K. Durand2,5, Kirsten L. Bryant2, Tikvah K. Hayes2, Sen Peng3, Nhan L. Tran4, Gerald C. Gooden1, David N. Buckley1, Channing J. Der2, Albert S. Baldwin2 ✉ & Bodour Salhia1 ✉ Oncogenic RAS mutations are associated with DNA methylation changes that alter gene expression to drive cancer. Recent studies suggest that DNA methylation changes may be stochastic in nature, while other groups propose distinct signaling pathways responsible for aberrant methylation. Better understanding of DNA methylation events associated with oncogenic KRAS expression could enhance therapeutic approaches. Here we analyzed the basal CpG methylation of 11 KRAS-mutant and dependent pancreatic cancer cell lines and observed strikingly similar methylation patterns. KRAS knockdown resulted in unique methylation changes with limited overlap between each cell line. In KRAS-mutant Pa16C pancreatic cancer cells, while KRAS knockdown resulted in over 8,000 diferentially methylated (DM) CpGs, treatment with the ERK1/2-selective inhibitor SCH772984 showed less than 40 DM CpGs, suggesting that ERK is not a broadly active driver of KRAS-associated DNA methylation. KRAS G12V overexpression in an isogenic lung model reveals >50,600 DM CpGs compared to non-transformed controls. In lung and pancreatic cells, gene ontology analyses of DM promoters show an enrichment for genes involved in diferentiation and development. Taken all together, KRAS-mediated DNA methylation are stochastic and independent of canonical downstream efector signaling. These epigenetically altered genes associated with KRAS expression could represent potential therapeutic targets in KRAS-driven cancer. Activating KRAS mutations can be found in nearly 25 percent of all cancers1. -
Functional Genomics Atlas of Synovial Fibroblasts Defining Rheumatoid Arthritis
medRxiv preprint doi: https://doi.org/10.1101/2020.12.16.20248230; this version posted December 18, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission. Functional genomics atlas of synovial fibroblasts defining rheumatoid arthritis heritability Xiangyu Ge1*, Mojca Frank-Bertoncelj2*, Kerstin Klein2, Amanda Mcgovern1, Tadeja Kuret2,3, Miranda Houtman2, Blaž Burja2,3, Raphael Micheroli2, Miriam Marks4, Andrew Filer5,6, Christopher D. Buckley5,6,7, Gisela Orozco1, Oliver Distler2, Andrew P Morris1, Paul Martin1, Stephen Eyre1* & Caroline Ospelt2*,# 1Versus Arthritis Centre for Genetics and Genomics, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK 2Department of Rheumatology, Center of Experimental Rheumatology, University Hospital Zurich, University of Zurich, Zurich, Switzerland 3Department of Rheumatology, University Medical Centre, Ljubljana, Slovenia 4Schulthess Klinik, Zurich, Switzerland 5Institute of Inflammation and Ageing, University of Birmingham, Birmingham, UK 6NIHR Birmingham Biomedical Research Centre, University Hospitals Birmingham NHS Foundation Trust, University of Birmingham, Birmingham, UK 7Kennedy Institute of Rheumatology, University of Oxford Roosevelt Drive Headington Oxford UK *These authors contributed equally #corresponding author: [email protected] NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice. 1 medRxiv preprint doi: https://doi.org/10.1101/2020.12.16.20248230; this version posted December 18, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. -
Supplementary Data
SUPPLEMENTARY DATA A cyclin D1-dependent transcriptional program predicts clinical outcome in mantle cell lymphoma Santiago Demajo et al. 1 SUPPLEMENTARY DATA INDEX Supplementary Methods p. 3 Supplementary References p. 8 Supplementary Tables (S1 to S5) p. 9 Supplementary Figures (S1 to S15) p. 17 2 SUPPLEMENTARY METHODS Western blot, immunoprecipitation, and qRT-PCR Western blot (WB) analysis was performed as previously described (1), using cyclin D1 (Santa Cruz Biotechnology, sc-753, RRID:AB_2070433) and tubulin (Sigma-Aldrich, T5168, RRID:AB_477579) antibodies. Co-immunoprecipitation assays were performed as described before (2), using cyclin D1 antibody (Santa Cruz Biotechnology, sc-8396, RRID:AB_627344) or control IgG (Santa Cruz Biotechnology, sc-2025, RRID:AB_737182) followed by protein G- magnetic beads (Invitrogen) incubation and elution with Glycine 100mM pH=2.5. Co-IP experiments were performed within five weeks after cell thawing. Cyclin D1 (Santa Cruz Biotechnology, sc-753), E2F4 (Bethyl, A302-134A, RRID:AB_1720353), FOXM1 (Santa Cruz Biotechnology, sc-502, RRID:AB_631523), and CBP (Santa Cruz Biotechnology, sc-7300, RRID:AB_626817) antibodies were used for WB detection. In figure 1A and supplementary figure S2A, the same blot was probed with cyclin D1 and tubulin antibodies by cutting the membrane. In figure 2H, cyclin D1 and CBP blots correspond to the same membrane while E2F4 and FOXM1 blots correspond to an independent membrane. Image acquisition was performed with ImageQuant LAS 4000 mini (GE Healthcare). Image processing and quantification were performed with Multi Gauge software (Fujifilm). For qRT-PCR analysis, cDNA was generated from 1 µg RNA with qScript cDNA Synthesis kit (Quantabio). qRT–PCR reaction was performed using SYBR green (Roche). -
A Machine Learning Framework for Precise 3D Domain Boundary Prediction at Base-Level Resolution
bioRxiv preprint doi: https://doi.org/10.1101/2020.09.03.282186; this version posted September 29, 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. preciseTAD: A machine learning framework for precise 3D domain boundary prediction at base-level resolution Spiro C. Stilianoudakis1 ([email protected]), Mikhail G. Dozmorov1* (mikhail.dozmorov@ vcuhealth.org) 1 Dept. of Biostatistics, Virginia Commonwealth University, Richmond, VA, 23298, USA * To whom correspondence should be addressed Abstract The low resolution of high-throughput chromatin conformation capture data limits the precise mapping of boundaries of topologically associating domains and chromatin loops. We developed preciseTAD, an optimized random forest model trained on high-resolution genome annotation data (e.g., CTCF ChIP- seq) to predict the location of domain boundaries at base-level resolution. Distance between boundaries and annotations, random under-sampling, and transcription factor binding sites resulted in best model performance. preciseTAD boundaries were more enriched for CTCF, RAD21, SMC3, and ZNF143, and conserved across cell lines. Using genome annotations, pre-trained models can detect boundaries in cells without Hi-C data. preciseTAD is available at https://bioconductor.org/packages/preciseTAD Keywords Hi-C, TAD, machine learning, random forest, DBSCAN Background The advent of chromosome conformation capture (3C) sequencing technologies, and its successor Hi-C, have revealed a hierarchy of the 3-dimensional (3D) structure of the human genome such as chromatin loops [1], Topologically Associating Domains (TADs) [2,3], and A/B compartments [4].