Supp Table4 Genes Affected by Fus Knockdown
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Legends for Supplemental Figures and Tables Figure S1. Expression of Tlx during retinogenesis. (A) Staged embryos were stained for β- galactosidase knocked into the Tlx locus to indicate Tlx expression. Tlx was expressed in the neural blast layer in the early phase of neural retina development (blue signal). (B) Expression of Tlx in neural retina was quantified using Q-PCR at multiple developmental stages. Figure S2. Expression of p27kip1 and cyclin D1 (Ccnd1) at various developmental stages in wild-type or Tlx-/- retinas. (A) Q-PCR analysis of p27kip1 mRNA expression. (B) Western blotting analysis of p27kip1 protein expression. (C) Q-PCR analysis of cyclin D1 mRNA expression. Figure S3. Q-PCR analysis of mRNA expression of Sf1 (A), Lrh1 (B), and Atn1 (C) in wild-type mouse retinas. RNAs from testis and liver were used as controls. Table S1. List of genes dysregulated both at E15.5 and P0 Tlx-/- retinas. Gene E15.5 P0 Cluste Gene Title Fold Fold r Name p-value p-value Change Change nuclear receptor subfamily 0, group B, Nr0b1 1.65 0.0024 2.99 0.0035 member 1 1 Pou4f3 1.91 0.0162 2.39 0.0031 POU domain, class 4, transcription factor 3 1 Tcfap2d 2.18 0.0000 2.37 0.0001 transcription factor AP-2, delta 1 Zic5 1.66 0.0002 2.02 0.0218 zinc finger protein of the cerebellum 5 1 Zfpm1 1.85 0.0030 1.88 0.0025 zinc finger protein, multitype 1 1 Pten 1.60 0.0155 1.82 0.0131 phospatase and tensin homolog 2 Itgb5 -1.85 0.0063 -1.85 0.0007 integrin beta 5 2 Gpr49 6.86 0.0001 15.16 0.0001 G protein-coupled receptor 49 3 Cmkor1 2.60 0.0007 2.72 0.0013 -
Down-Regulation of Stem Cell Genes, Including Those in a 200-Kb Gene Cluster at 12P13.31, Is Associated with in Vivo Differentiation of Human Male Germ Cell Tumors
Research Article Down-Regulation of Stem Cell Genes, Including Those in a 200-kb Gene Cluster at 12p13.31, Is Associated with In vivo Differentiation of Human Male Germ Cell Tumors James E. Korkola,1 Jane Houldsworth,1,2 Rajendrakumar S.V. Chadalavada,1 Adam B. Olshen,3 Debbie Dobrzynski,2 Victor E. Reuter,4 George J. Bosl,2 and R.S.K. Chaganti1,2 1Cell Biology Program and Departments of 2Medicine, 3Epidemiology and Biostatistics, and 4Pathology, Memorial Sloan-Kettering Cancer Center, New York, New York Abstract on the degree and type of differentiation (i.e., seminomas, which Adult male germ cell tumors (GCTs) comprise distinct groups: resemble undifferentiated primitive germ cells, and nonseminomas, seminomas and nonseminomas, which include pluripotent which show varying degrees of embryonic and extraembryonic embryonal carcinomas as well as other histologic subtypes patterns of differentiation; refs. 2, 3). Nonseminomatous GCTs are exhibiting various stages of differentiation. Almost all GCTs further subdivided into embryonal carcinomas, which show early show 12p gain, but the target genes have not been clearly zygotic or embryonal-like differentiation, yolk sac tumors and defined. To identify 12p target genes, we examined Affymetrix choriocarcinomas, which exhibit extraembryonal forms of differ- (Santa Clara, CA) U133A+B microarray (f83% coverage of 12p entiation, and teratomas, which show somatic differentiation along genes) expression profiles of 17 seminomas, 84 nonseminoma multiple lineages (3). Both seminomas and embryonal carcinoma GCTs, and 5 normal testis samples. Seventy-three genes on 12p are known to express stem cell markers, such as POU5F1 (4) and were significantly overexpressed, including GLUT3 and REA NANOG (5). -
Core Transcriptional Regulatory Circuitries in Cancer
Oncogene (2020) 39:6633–6646 https://doi.org/10.1038/s41388-020-01459-w REVIEW ARTICLE Core transcriptional regulatory circuitries in cancer 1 1,2,3 1 2 1,4,5 Ye Chen ● Liang Xu ● Ruby Yu-Tong Lin ● Markus Müschen ● H. Phillip Koeffler Received: 14 June 2020 / Revised: 30 August 2020 / Accepted: 4 September 2020 / Published online: 17 September 2020 © The Author(s) 2020. This article is published with open access Abstract Transcription factors (TFs) coordinate the on-and-off states of gene expression typically in a combinatorial fashion. Studies from embryonic stem cells and other cell types have revealed that a clique of self-regulated core TFs control cell identity and cell state. These core TFs form interconnected feed-forward transcriptional loops to establish and reinforce the cell-type- specific gene-expression program; the ensemble of core TFs and their regulatory loops constitutes core transcriptional regulatory circuitry (CRC). Here, we summarize recent progress in computational reconstitution and biologic exploration of CRCs across various human malignancies, and consolidate the strategy and methodology for CRC discovery. We also discuss the genetic basis and therapeutic vulnerability of CRC, and highlight new frontiers and future efforts for the study of CRC in cancer. Knowledge of CRC in cancer is fundamental to understanding cancer-specific transcriptional addiction, and should provide important insight to both pathobiology and therapeutics. 1234567890();,: 1234567890();,: Introduction genes. Till now, one critical goal in biology remains to understand the composition and hierarchy of transcriptional Transcriptional regulation is one of the fundamental mole- regulatory network in each specified cell type/lineage. -
Derivation of Stable Microarray Cancer-Differentiating Signatures Using Consensus Scoring of Multiple Random Sampling and Gene-Ranking Consistency Evaluation
Research Article Derivation of Stable Microarray Cancer-Differentiating Signatures Using Consensus Scoring of Multiple Random Sampling and Gene-Ranking Consistency Evaluation Zhi Qun Tang,1,2 Lian Yi Han,1,2 Hong Huang Lin,1,2 Juan Cui,1,2 Jia Jia,1,2 Boon Chuan Low,2,3 Bao Wen Li,2,4 and Yu Zong Chen1,2 1Bioinformatics and Drug Design Group, Department of Pharmacy; 2Center for Computational Science and Engineering; and Departments of 3Biological Sciences and 4Physics, National University of Singapore, Singapore, Singapore Abstract sampling methods. Only 1 to 5 of the 4 to 60 selected predictor Microarrays have been explored for deriving molecular genes in each of these sets are present in more than half of the signatures to determine disease outcomes, mechanisms, other nine sets (Table 1), and 2 to 20 of the predictor genes in each targets, and treatment strategies. Although exhibiting good set are cancer related (Table 2). Despite the use of sophisticated predictive performance, some derived signatures are unstable class differentiation and signature selection methods, the selected due to noises arising from measurement variability and signatures show few overlapping predictor genes, as in the case of biological differences. Improvements in measurement, anno- other microarray data sets including non–Hodgkin lymphoma, tation, and signature selection methods have been proposed. acute lymphocytic leukemia, breast cancer, lung adenocarcinoma, We explored a new signature selection method that incorpo- medulloblastoma, hepatocellular carcinoma, and acute myeloid rates consensus scoring of multiple random sampling and leukemia (9, 15). multistep evaluation of gene-ranking consistency for maxi- Although these signatures display high cancer differentiation mally avoiding erroneous elimination of predictor genes. -
Aggf1 Attenuates Neuroinflammation and BBB Disruption Via PI3K/Akt/NF-Κb Pathway After Subarachnoid Hemorrhage in Rats
Zhu et al. Journal of Neuroinflammation (2018) 15:178 https://doi.org/10.1186/s12974-018-1211-8 RESEARCH Open Access Aggf1 attenuates neuroinflammation and BBB disruption via PI3K/Akt/NF-κB pathway after subarachnoid hemorrhage in rats Qiquan Zhu1,2, Budbazar Enkhjargal2, Lei Huang2,4, Tongyu Zhang2, Chengmei Sun2, Zhiyi Xie2, Pei Wu2, Jun Mo2, Jiping Tang2, Zongyi Xie1* and John H. Zhang2,3,4* Abstract Background: Neuroinflammation and blood-brain barrier (BBB) disruption are two critical mechanisms of subarachnoid hemorrhage (SAH)-induced brain injury, which are closely related to patient prognosis. Recently, angiogenic factor with G-patch and FHA domain 1 (Aggf1) was shown to inhibit inflammatory effect and preserve vascular integrity in non-nervous system diseases. This study aimed to determine whether Aggf1 could attenuate neuroinflammation and preserve BBB integrity after experimental SAH, as well as the underlying mechanisms of its protective roles. Methods: Two hundred forty-nine male Sprague-Dawley rats were subjected to the endovascular perforation model of SAH. Recombinant human Aggf1 (rh-Aggf1) was administered intravenously via tail vein injection at 1 h after SAH induction. To investigate the underlying neuroprotection mechanism, Aggf1 small interfering RNA (Aggf1 siRNA) and PI3K-specific inhibitor LY294002 were administered through intracerebroventricular (i.c.v.) before SAH induction. SAH grade, neurological score, brain water content, BBB permeability, Western blot, and immunohistochemistry were performed. Results: Expression of endogenous Aggf1 was markedly increased after SAH. Aggf1 was primarily expressed in endothelial cells and astrocytes, as well as microglia after SAH. Administration of rh-Aggf1 significantly reduced brain water content and BBB permeability, decreased the numbers of infiltrating neutrophils, and activated microglia in the ipsilateral cerebral cortex following SAH. -
Feedback Regulation Between Initiation and Maturation Networks Orchestrates the Chromatin Dynamics of Epidermal Lineage
bioRxiv preprint doi: https://doi.org/10.1101/349308; this version posted June 18, 2018. 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-ND 4.0 International license. Li et al., p. 1 Feedback Regulation between Initiation and Maturation Networks Orchestrates the Chromatin Dynamics of Epidermal Lineage Commitment Lingjie Li1,3,4, Yong Wang2,4,7,8*, Jessica L. Torkelson1,3*, Gautam Shankar1, Jillian M. Pattison1,3, Hanson H. Zhen1,3, Zhana Duren2,4,7, Fengqin Fang5, Sandra P. Melo1, Samantha N. Piekos1,3, Jiang Li1, Eric J. Liaw1, Lang Chen7, Rui Li1,4, Marius Wernig6, Wing H. Wong2,4, Howard Y. Chang1,4, Anthony E. Oro1,3,9 1 Program in Epithelial Biology and Department of Dermatology 2 Department of Statistics and Biomedical Data Science 3 Center for Definitive and Curative Medicine 4 Center for Personal Dynamic Regulome 5 Division of Immunology and Rheumatology, Department of Medicine, 6 Institute for Stem Cell Biology and Regenerative Medicine, Department of Pathology, Stanford University School of Medicine, Stanford, CA 94305, USA. 7 CEMS, NCMIS, MDIS, Academy of Mathematics & Systems Science, Chinese Academy of Sciences, Beijing,100080, China 8 Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650223, China *These authors made equal and independent contributions. 9 Correspondence to Lead Contact: Anthony E. Oro at [email protected] bioRxiv preprint doi: https://doi.org/10.1101/349308; this version posted June 18, 2018. -
Single-Cell Sequencing of Human Ipsc-Derived Cerebellar Organoids Shows Recapitulation of Cerebellar Development
bioRxiv preprint doi: https://doi.org/10.1101/2020.07.01.182196; this version posted July 1, 2020. 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. Single-cell sequencing of human iPSC-derived cerebellar organoids shows recapitulation of cerebellar development Samuel Nayler1*, Devika Agarwal3, Fabiola Curion2, Rory Bowden2,4, Esther B.E. Becker1,5* 1Department of Physiology, Anatomy and Genetics; University of Oxford; Oxford, OX1 3PT; United Kingdom 2Wellcome Centre for Human Genetics; University of Oxford; Oxford, OX3 7BN; United Kingdom 3Weatherall Institute for Molecular Medicine; University of Oxford; Oxford, OX3 7BN; United Kingdom 4Present address: Walter and Eliza Hall Institute of Medical Research, Parkville Victoria 3052; Australia 5Lead contact *Correspondence: [email protected], [email protected] Running title: hiPSC-derived cerebellar organoids 1 bioRxiv preprint doi: https://doi.org/10.1101/2020.07.01.182196; this version posted July 1, 2020. 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. ABSTRACT Current protocols for producing cerebellar neurons from human pluripotent stem cells (hPSCs) are reliant on animal co-culture and mostly exist as monolayers, which have limited capability to recapitulate the complex arrangement of the brain. We developed a method to differentiate hPSCs into cerebellar organoids that display hallmarks of in vivo cerebellar development. Single- cell profiling followed by comparison to an atlas of the developing murine cerebellum revealed transcriptionally-discrete populations encompassing all major cerebellar cell types. -
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. -
Figure S1. Representative Report Generated by the Ion Torrent System Server for Each of the KCC71 Panel Analysis and Pcafusion Analysis
Figure S1. Representative report generated by the Ion Torrent system server for each of the KCC71 panel analysis and PCaFusion analysis. (A) Details of the run summary report followed by the alignment summary report for the KCC71 panel analysis sequencing. (B) Details of the run summary report for the PCaFusion panel analysis. A Figure S1. Continued. Representative report generated by the Ion Torrent system server for each of the KCC71 panel analysis and PCaFusion analysis. (A) Details of the run summary report followed by the alignment summary report for the KCC71 panel analysis sequencing. (B) Details of the run summary report for the PCaFusion panel analysis. B Figure S2. Comparative analysis of the variant frequency found by the KCC71 panel and calculated from publicly available cBioPortal datasets. For each of the 71 genes in the KCC71 panel, the frequency of variants was calculated as the variant number found in the examined cases. Datasets marked with different colors and sample numbers of prostate cancer are presented in the upper right. *Significantly high in the present study. Figure S3. Seven subnetworks extracted from each of seven public prostate cancer gene networks in TCNG (Table SVI). Blue dots represent genes that include initial seed genes (parent nodes), and parent‑child and child‑grandchild genes in the network. Graphical representation of node‑to‑node associations and subnetwork structures that differed among and were unique to each of the seven subnetworks. TCNG, The Cancer Network Galaxy. Figure S4. REVIGO tree map showing the predicted biological processes of prostate cancer in the Japanese. Each rectangle represents a biological function in terms of a Gene Ontology (GO) term, with the size adjusted to represent the P‑value of the GO term in the underlying GO term database. -
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 -
T-Brain Regulates Archenteron Induction Signal 5207 Range of Amplification
Development 129, 5205-5216 (2002) 5205 Printed in Great Britain © The Company of Biologists Limited 2002 DEV5034 T-brain homologue (HpTb) is involved in the archenteron induction signals of micromere descendant cells in the sea urchin embryo Takuya Fuchikami1, Keiko Mitsunaga-Nakatsubo1, Shonan Amemiya2, Toshiya Hosomi1, Takashi Watanabe1, Daisuke Kurokawa1,*, Miho Kataoka1, Yoshito Harada3, Nori Satoh3, Shinichiro Kusunoki4, Kazuko Takata1, Taishin Shimotori1, Takashi Yamamoto1, Naoaki Sakamoto1, Hiraku Shimada1 and Koji Akasaka1,† 1Department of Mathematical and Life Sciences, Graduate School of Science, Hiroshima University, Higashi-Hiroshima 739-8526, Japan 2Department of Integrated Biosciences, Graduate School of Frontier Sciences, University of Tokyo, Hongo, Bunkyo-ku, Tokyo 113-0033, Japan 3Department of Zoology, Graduate School of Science, Kyoto University, Sakyo-ku, Kyoto 606-8502, Japan 4LSL, Nerima-ku, Tokyo 178-0061, Japan *Present address: Evolutionary Regeneration Biology Group, RIKEN Center for Developmental Biology, Kobe 650-0047, Japan †Author for correspondence (e-mail: [email protected]) Accepted 30 July 2002 SUMMARY Signals from micromere descendants play a crucial role in cells, the initial specification of primary mesenchyme cells, sea urchin development. In this study, we demonstrate that or the specification of endoderm. HpTb expression is these micromere descendants express HpTb, a T-brain controlled by nuclear localization of β-catenin, suggesting homolog of Hemicentrotus pulcherrimus. HpTb is expressed that -
Α Are Regulated by Heat Shock Protein 90
The Levels of Retinoic Acid-Inducible Gene I Are Regulated by Heat Shock Protein 90- α Tomoh Matsumiya, Tadaatsu Imaizumi, Hidemi Yoshida, Kei Satoh, Matthew K. Topham and Diana M. Stafforini This information is current as of October 2, 2021. J Immunol 2009; 182:2717-2725; ; doi: 10.4049/jimmunol.0802933 http://www.jimmunol.org/content/182/5/2717 Downloaded from References This article cites 44 articles, 19 of which you can access for free at: http://www.jimmunol.org/content/182/5/2717.full#ref-list-1 Why The JI? Submit online. http://www.jimmunol.org/ • Rapid Reviews! 30 days* from submission to initial decision • No Triage! Every submission reviewed by practicing scientists • Fast Publication! 4 weeks from acceptance to publication *average by guest on October 2, 2021 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 © 2009 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. The Journal of Immunology The Levels of Retinoic Acid-Inducible Gene I Are Regulated by Heat Shock Protein 90-␣1 Tomoh Matsumiya,*‡ Tadaatsu Imaizumi,‡ Hidemi Yoshida,‡ Kei Satoh,‡ Matthew K. Topham,*† and Diana M. Stafforini2*† Retinoic acid-inducible gene I (RIG-I) is an intracellular pattern recognition receptor that plays important roles during innate immune responses to viral dsRNAs.