Overlap of Vitamin a and Vitamin D Target Genes with CAKUT- Related Processes [Version 1; Peer Review: 1 Approved with Reservations]
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Sorbonne Université/China Scholarship Council Program 2021
Sorbonne Université/China Scholarship Council program 2021 Thesis proposal Title of the research project: Hnf1b regulation during kidney development and regeneration Joint supervision: no Joint PhD (cotutelle): no Thesis supervisor: … Muriel Umbhauer. Email address of the thesis supervisor: [email protected] Institution: …… Sorbonne Université …. Doctoral school (N°+name): ED …. …… ED 515 Complexité du Vivant Research laboratory: UMR7622 CNRS Laboratory of developmental biology Name of the laboratory director: … Sylvie Schneider-Maunoury Email address of the laboratory director: [email protected] Subject description (2 pages max): 1) Study context The POU homeodomain transcription factor hepatocyte nuclear factor 1β (Hnf1b) plays an essential role in vertebrate kidney development. Heterozygous mutations in human HNF1B cause the complex multisystem syndrome known as Renal Cysts And Diabetes (RCAD). The most prominent clinical features of this autosomal dominant disorder are non-diabetic renal disease resulting from abnormal renal development and diabetes mellitus (reviewed by Clissold RL et al., 2015). During early mouse kidney development, Hnf1b has been shown to be required for ureteric bud branching and initiation of nephrogenesis (Lokmane et al., 2010). Hnf1b conditional inactivation in murine nephron progenitors has revealed an additional role in segment fate Xenopus is a well established and attractive model to study kidney development (Krneta-Stankic V. et al, 2017). Renal function at larval stages relies on two pronephroi located on both sides of the body, each consisting on one giant nephron displaying the same structural and functional organisation than the mammalian nephron. Moreover, pronephric and metanephric differentiation and morphogenesis share most of the signalling cascades and gene regulatory networks. -
Transcription Factor P73 Regulates Th1 Differentiation
ARTICLE https://doi.org/10.1038/s41467-020-15172-5 OPEN Transcription factor p73 regulates Th1 differentiation Min Ren1, Majid Kazemian 1,4, Ming Zheng2, JianPing He3, Peng Li1, Jangsuk Oh1, Wei Liao1, Jessica Li1, ✉ Jonathan Rajaseelan1, Brian L. Kelsall 3, Gary Peltz 2 & Warren J. Leonard1 Inter-individual differences in T helper (Th) cell responses affect susceptibility to infectious, allergic and autoimmune diseases. To identify factors contributing to these response differ- 1234567890():,; ences, here we analyze in vitro differentiated Th1 cells from 16 inbred mouse strains. Haplotype-based computational genetic analysis indicates that the p53 family protein, p73, affects Th1 differentiation. In cells differentiated under Th1 conditions in vitro, p73 negatively regulates IFNγ production. p73 binds within, or upstream of, and modulates the expression of Th1 differentiation-related genes such as Ifng and Il12rb2. Furthermore, in mouse experimental autoimmune encephalitis, p73-deficient mice have increased IFNγ production and less dis- ease severity, whereas in an adoptive transfer model of inflammatory bowel disease, transfer of p73-deficient naïve CD4+ T cells increases Th1 responses and augments disease severity. Our results thus identify p73 as a negative regulator of the Th1 immune response, suggesting that p73 dysregulation may contribute to susceptibility to autoimmune disease. 1 Laboratory of Molecular Immunology and the Immunology Center, National Heart, Lung, and Blood Institute, Bethesda, MD 20892-1674, USA. 2 Department of Anesthesia, Stanford University School of Medicine, Stanford, CA 94305, USA. 3 Laboratory of Molecular Immunology, National Institute of Allergy and Infectious Diseases, Bethesda, MD 20892, USA. 4Present address: Department of Biochemistry and Computer Science, Purdue University, West ✉ Lafayette, IN 37906, USA. -
Table S1 the Four Gene Sets Derived from Gene Expression Profiles of Escs and Differentiated Cells
Table S1 The four gene sets derived from gene expression profiles of ESCs and differentiated cells Uniform High Uniform Low ES Up ES Down EntrezID GeneSymbol EntrezID GeneSymbol EntrezID GeneSymbol EntrezID GeneSymbol 269261 Rpl12 11354 Abpa 68239 Krt42 15132 Hbb-bh1 67891 Rpl4 11537 Cfd 26380 Esrrb 15126 Hba-x 55949 Eef1b2 11698 Ambn 73703 Dppa2 15111 Hand2 18148 Npm1 11730 Ang3 67374 Jam2 65255 Asb4 67427 Rps20 11731 Ang2 22702 Zfp42 17292 Mesp1 15481 Hspa8 11807 Apoa2 58865 Tdh 19737 Rgs5 100041686 LOC100041686 11814 Apoc3 26388 Ifi202b 225518 Prdm6 11983 Atpif1 11945 Atp4b 11614 Nr0b1 20378 Frzb 19241 Tmsb4x 12007 Azgp1 76815 Calcoco2 12767 Cxcr4 20116 Rps8 12044 Bcl2a1a 219132 D14Ertd668e 103889 Hoxb2 20103 Rps5 12047 Bcl2a1d 381411 Gm1967 17701 Msx1 14694 Gnb2l1 12049 Bcl2l10 20899 Stra8 23796 Aplnr 19941 Rpl26 12096 Bglap1 78625 1700061G19Rik 12627 Cfc1 12070 Ngfrap1 12097 Bglap2 21816 Tgm1 12622 Cer1 19989 Rpl7 12267 C3ar1 67405 Nts 21385 Tbx2 19896 Rpl10a 12279 C9 435337 EG435337 56720 Tdo2 20044 Rps14 12391 Cav3 545913 Zscan4d 16869 Lhx1 19175 Psmb6 12409 Cbr2 244448 Triml1 22253 Unc5c 22627 Ywhae 12477 Ctla4 69134 2200001I15Rik 14174 Fgf3 19951 Rpl32 12523 Cd84 66065 Hsd17b14 16542 Kdr 66152 1110020P15Rik 12524 Cd86 81879 Tcfcp2l1 15122 Hba-a1 66489 Rpl35 12640 Cga 17907 Mylpf 15414 Hoxb6 15519 Hsp90aa1 12642 Ch25h 26424 Nr5a2 210530 Leprel1 66483 Rpl36al 12655 Chi3l3 83560 Tex14 12338 Capn6 27370 Rps26 12796 Camp 17450 Morc1 20671 Sox17 66576 Uqcrh 12869 Cox8b 79455 Pdcl2 20613 Snai1 22154 Tubb5 12959 Cryba4 231821 Centa1 17897 -
Genetic Variability in the Italian Heavy Draught Horse from Pedigree Data and Genomic Information
Supplementary material for manuscript: Genetic variability in the Italian Heavy Draught Horse from pedigree data and genomic information. Enrico Mancin†, Michela Ablondi†, Roberto Mantovani*, Giuseppe Pigozzi, Alberto Sabbioni and Cristina Sartori ** Correspondence: [email protected] † These two Authors equally contributed to the work Supplementary Figure S1. Mares and foal of Italian Heavy Draught Horse (IHDH; courtesy of Cinzia Stoppa) Supplementary Figure S2. Number of Equivalent Generations (EqGen; above) and pedigree completeness (PC; below) over years in Italian Heavy Draught Horse population. Supplementary Table S1. Descriptive statistics of homozygosity (observed: Ho_obs; expected: Ho_exp; total: Ho_tot) in 267 genotyped individuals of Italian Heavy Draught Horse based on the number of homozygous genotypes. Parameter Mean SD Min Max Ho_obs 35,630.3 500.7 34,291 38,013 Ho_exp 35,707.8 64.0 35,010 35,740 Ho_tot 50,674.5 93.8 49,638 50,714 1 Definitions of the methods for inbreeding are in the text. Supplementary Figure S3. Values of BIC obtained by analyzing values of K from 1 to 10, corresponding on the same amount of clusters defining the proportion of ancestry in the 267 genotyped individuals. Supplementary Table S2. Estimation of genomic effective population size (Ne) traced back to 18 generations ago (Gen. ago). The linkage disequilibrium estimation, adjusted for sampling bias was also included (LD_r2), as well as the relative standard deviation (SD(LD_r2)). Gen. ago Ne LD_r2 SD(LD_r2) 1 100 0.009 0.014 2 108 0.011 0.018 3 118 0.015 0.024 4 126 0.017 0.028 5 134 0.019 0.031 6 143 0.021 0.034 7 156 0.023 0.038 9 173 0.026 0.041 11 189 0.029 0.046 14 213 0.032 0.052 18 241 0.036 0.058 Supplementary Table S3. -
Transcriptomic Characterization of Fibrolamellar Hepatocellular
Transcriptomic characterization of fibrolamellar PNAS PLUS hepatocellular carcinoma Elana P. Simona, Catherine A. Freijeb, Benjamin A. Farbera,c, Gadi Lalazara, David G. Darcya,c, Joshua N. Honeymana,c, Rachel Chiaroni-Clarkea, Brian D. Dilld, Henrik Molinad, Umesh K. Bhanote, Michael P. La Quagliac, Brad R. Rosenbergb,f, and Sanford M. Simona,1 aLaboratory of Cellular Biophysics, The Rockefeller University, New York, NY 10065; bPresidential Fellows Laboratory, The Rockefeller University, New York, NY 10065; cDivision of Pediatric Surgery, Department of Surgery, Memorial Sloan-Kettering Cancer Center, New York, NY 10065; dProteomics Resource Center, The Rockefeller University, New York, NY 10065; ePathology Core Facility, Memorial Sloan-Kettering Cancer Center, New York, NY 10065; and fJohn C. Whitehead Presidential Fellows Program, The Rockefeller University, New York, NY 10065 Edited by Susan S. Taylor, University of California, San Diego, La Jolla, CA, and approved September 22, 2015 (received for review December 29, 2014) Fibrolamellar hepatocellular carcinoma (FLHCC) tumors all carry a exon of DNAJB1 and all but the first exon of PRKACA. This deletion of ∼400 kb in chromosome 19, resulting in a fusion of the produced a chimeric RNA transcript and a translated chimeric genes for the heat shock protein, DNAJ (Hsp40) homolog, subfam- protein that retains the full catalytic activity of wild-type PKA. ily B, member 1, DNAJB1, and the catalytic subunit of protein ki- This chimeric protein was found in 15 of 15 FLHCC patients nase A, PRKACA. The resulting chimeric transcript produces a (21) in the absence of any other recurrent mutations in the DNA fusion protein that retains kinase activity. -
Roles of Id3 and IL-13 in a Mouse Model of Autoimmune Exocrinopathy
Roles of Id3 and IL-13 in a Mouse Model of Autoimmune Exocrinopathy by Ian Lawrence Belle Department of Immunology Duke University Date:_______________________ Approved: ___________________________ Yuan Zhuang, Supervisor ___________________________ Michael Krangel, Chair ___________________________ Qi-jing Li ___________________________ Richard Lee Reinhardt ___________________________ Arno Greenleaf Dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Immunology in the Graduate School of Duke University 2015 ABSTRACT Roles of Id3 and IL-13 in a Mouse Model of Autoimmune Exocrinopathy by Ian Lawrence Belle Department of Immunology Duke University Date:_______________________ Approved: ___________________________ Yuan Zhuang, Supervisor ___________________________ Michael Krangel, Chair ___________________________ Qi-jing Li ___________________________ Richard Lee Reinhardt ___________________________ Arno Greenleaf An abstract of a dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Immunology in the Graduate School of Duke University 2015 Copyright by Ian Lawrence Belle 2015 Abstract Within the field of immunology, the existence of autoimmune diseases presents a unique set of challenges. The immune system typically protects the host by identifying foreign pathogens and mounting an appropriate response to eliminate them. Great strides have been made in understanding how foreign pathogens are identified and responded to, leading to the development of powerful immunological tools, such as vaccines and a myriad of models used to study infectious diseases and processes. However, it is occasionally possible for host tissues themselves to be inappropriately identified as foreign, prompting an immune response that attempts to eliminate the host tissue. The immune system has processes in place, referred to as selection, designed to prevent the development of cells capable of recognizing the self as foreign. -
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. -
PI3K Pathway Regulates ER-Dependent Transcription in Breast Cancer Through the Epigenetic Regulator KMT2D
HHS Public Access Author manuscript Author ManuscriptAuthor Manuscript Author Science Manuscript Author . Author manuscript; Manuscript Author available in PMC 2018 March 24. Published in final edited form as: Science. 2017 March 24; 355(6331): 1324–1330. doi:10.1126/science.aah6893. PI3K pathway regulates ER-dependent transcription in breast cancer through the epigenetic regulator KMT2D Eneda Toska1, Hatice U. Osmanbeyoglu2,*, Pau Castel1,3,*, Carmen Chan1, Ronald C. Hendrickson4, Moshe Elkabets1,5, Maura N. Dickler6, Maurizio Scaltriti1,7, Christina S. Leslie2, Scott A. Armstrong8,9, and José Baselga1,6 1Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, Box 20, New York, NY 10065, USA 2Computational Biology Program, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, Box 460, New York, NY 10065, USA 3Helen Diller Family Comprehensive Cancer Center, University of California–San Francisco, 1450 3rd Street, San Francisco, CA 94158, USA 4Microchemistry and Proteomics Core Laboratory, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA 5The Shraga Segal Department of Microbiology, Immunology and Genetics, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel 6Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA 7Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA 8Cancer Biology and Genetics Program, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA 9Department of Pediatric Oncology, Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA 02215, USA Abstract Activating mutations in PIK3CA, the gene encoding phosphoinositide-(3)-kinase α (PI3Kα), are frequently found in estrogen receptor (ER)–positive breast cancer. -
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 -
UNIVERSITY of CALIFORNIA, IRVINE Combinatorial Regulation By
UNIVERSITY OF CALIFORNIA, IRVINE Combinatorial regulation by maternal transcription factors during activation of the endoderm gene regulatory network DISSERTATION submitted in partial satisfaction of the requirements for the degree of DOCTOR OF PHILOSOPHY in Biological Sciences by Kitt D. Paraiso Dissertation Committee: Professor Ken W.Y. Cho, Chair Associate Professor Olivier Cinquin Professor Thomas Schilling 2018 Chapter 4 © 2017 Elsevier Ltd. © 2018 Kitt D. Paraiso DEDICATION To the incredibly intelligent and talented people, who in one way or another, helped complete this thesis. ii TABLE OF CONTENTS Page LIST OF FIGURES vii LIST OF TABLES ix LIST OF ABBREVIATIONS X ACKNOWLEDGEMENTS xi CURRICULUM VITAE xii ABSTRACT OF THE DISSERTATION xiv CHAPTER 1: Maternal transcription factors during early endoderm formation in 1 Xenopus Transcription factors co-regulate in a cell type-specific manner 2 Otx1 is expressed in a variety of cell lineages 4 Maternal otx1 in the endodermal conteXt 5 Establishment of enhancers by maternal transcription factors 9 Uncovering the endodermal gene regulatory network 12 Zygotic genome activation and temporal control of gene eXpression 14 The role of maternal transcription factors in early development 18 References 19 CHAPTER 2: Assembly of maternal transcription factors initiates the emergence 26 of tissue-specific zygotic cis-regulatory regions Introduction 28 Identification of maternal vegetally-localized transcription factors 31 Vegt and OtX1 combinatorially regulate the endodermal 33 transcriptome iii -
Acquired Evolution of Mitochondrial Metabolism Regulated by HNF1B in Ovarian Clear Cell Carcinoma
cancers Review Acquired Evolution of Mitochondrial Metabolism Regulated by HNF1B in Ovarian Clear Cell Carcinoma Ken Yamaguchi 1,*, Sachiko Kitamura 1, Yoko Furutake 1 , Ryusuke Murakami 1,2 , Koji Yamanoi 1, Mana Taki 1, Masayo Ukita 1, Junzo Hamanishi 1 and Masaki Mandai 1 1 Department of Gynecology and Obstetrics, Graduate School of Medicine, Kyoto University, Kyoto 606-8507, Japan; [email protected] (S.K.); [email protected] (Y.F.); [email protected] (R.M.); [email protected] (K.Y.); [email protected] (M.T.); [email protected] (M.U.); [email protected] (J.H.); [email protected] (M.M.) 2 Department of Gynecology, Shiga General Hospital, Moriyama, Shiga 524-8524, Japan * Correspondence: [email protected]; Tel.: +81-75-751-3269 Simple Summary: Ovarian clear cell carcinoma (CCC) exhibits unique characteristics, including slow growth, glycogen accumulation in the cytoplasm, and poor prognosis for stress resistance. Several molecular targeting agents have failed to treat ovarian CCC. Recent reports have identified metabolic alterations through HNF1B, which is highly expressed in ovarian CCC. The Warburg effect, GSH synthesis, and mitochondrial regulation occur in CCC. The metabolic behaviors of ovarian CCC resemble the evolution of life to survive in stressful environments. Understanding the fundamental biology of ovarian CCC might help in the development of novel therapeutic strategies. Citation: Yamaguchi, K.; Kitamura, Abstract: Clear cell carcinoma (CCC) of the ovary exhibits a unique morphology and clinically S.; Furutake, Y.; Murakami, R.; malignant behavior. -
Spatiotemporal DNA Methylome Dynamics of the Developing Mouse Fetus
Article Spatiotemporal DNA methylome dynamics of the developing mouse fetus https://doi.org/10.1038/s41586-020-2119-x Yupeng He1,2, Manoj Hariharan1, David U. Gorkin3, Diane E. Dickel4, Chongyuan Luo1, Rosa G. Castanon1, Joseph R. Nery1, Ah Young Lee3, Yuan Zhao2,3, Hui Huang3,5, Received: 9 August 2017 Brian A. Williams6, Diane Trout6, Henry Amrhein6, Rongxin Fang2,3, Huaming Chen1, Bin Li3, Accepted: 11 June 2019 Axel Visel4,7,8, Len A. Pennacchio4,7,9, Bing Ren3,10 & Joseph R. Ecker1,11 ✉ Published online: 29 July 2020 Open access Cytosine DNA methylation is essential for mammalian development but Check for updates understanding of its spatiotemporal distribution in the developing embryo remains limited1,2. Here, as part of the mouse Encyclopedia of DNA Elements (ENCODE) project, we profled 168 methylomes from 12 mouse tissues or organs at 9 developmental stages from embryogenesis to adulthood. We identifed 1,808,810 genomic regions that showed variations in CG methylation by comparing the methylomes of diferent tissues or organs from diferent developmental stages. These DNA elements predominantly lose CG methylation during fetal development, whereas the trend is reversed after birth. During late stages of fetal development, non- CG methylation accumulated within the bodies of key developmental transcription factor genes, coinciding with their transcriptional repression. Integration of genome- wide DNA methylation, histone modifcation and chromatin accessibility data enabled us to predict 461,141 putative developmental tissue-specifc enhancers, the human orthologues of which were enriched for disease-associated genetic variants. These spatiotemporal epigenome maps provide a resource for studies of gene regulation during tissue or organ progression, and a starting point for investigating regulatory elements that are involved in human developmental disorders.