EN1 Is a Transcriptional Dependency in Triple- Negative Breast Cancer Associated with Brain Metastasis Guillermo Peluffo1,2, Ashim Subedee1,3, Nicholas W
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Bone Morphogenetic Protein-4 Affects Both Trophoblast and Non-Trophoblast Lineage-Associated Gene Expression in Human Embryonic Stem Cells
Vol.2, No.4, 163-175 (2012) Stem Cell Discovery http://dx.doi.org/10.4236/scd.2012.24021 Bone morphogenetic protein-4 affects both trophoblast and non-trophoblast lineage-associated gene expression in human embryonic stem cells Margaret L. Shirley1,2*, Alison Venable1*, Raj R. Rao3, Nolan L. Boyd4, Steven L. Stice1,5,6, David Puett1#, Prema Narayan7# 1Department of Biochemistry and Molecular Biology, University of Georgia, Athens, USA; #Corresponding Author: [email protected] 2Department of Psychiatry, University of California, San Francisco, USA 3Department of Chemical and Life Science Engineering, School of Engineering, Virginia Commonwealth University, Richmond, USA 4Cardiovascular Innovation Institute, University of Louisville, Louisville, USA 5Regenerative Bioscience Center, University of Georgia, Athens, USA 6Department of Animal and Dairy Sciences, University of Georgia, Athens, USA 7Department of Physiology, Southern Illinois University School of Medicine, Carbondale, USA; #Corresponding Author: [email protected] Received 5 May 2012; revised 4 June 2012; accepted 1 July 2012 ABSTRACT cells were obtained. Gene expression by EB was characterized by an up-regulation of a num- Human embryonic stem cells (hESC) can be in- ber of genes associated with trophoblast, ecto- duced to differentiate to trophoblast by bone derm, endoderm, and mesoderm, and the pro- morphogenetic proteins (BMPs) and by aggre- duction of hCG and progesterone confirmed that gation to form embryoid bodies (EB), but there trophoblast-like cells were formed. These re- are many differences and controversies regard- sults suggest that, in the presence of FGF-2, ing the nature of the differentiated cells. Our BG02 cells respond to BMP4 to yield tropho- goals herein were to determine if BG02 cells form trophoblast-like cells (a) in the presence of blast-like cells, which are also obtained upon EB BMP4-plus-basic fibroblast growth factor (FGF-2) formation. -
Supplementary Table 1. Mutated Genes That Contain Protein Domains Identified Through Mutation Enrichment Analysis
Supplementary Table 1. Mutated genes that contain protein domains identified through mutation enrichment analysis A. Breast cancers InterPro ID Mutated genes (number of mutations) IPR000219 ARHGEF4(2), ECT2(1), FARP1(1), FLJ20184(1), MCF2L2(1), NET1(1), OBSCN(5), RASGRF2(2), TRAD(1), VAV3(1) IPR000225 APC2(2), JUP(1), KPNA5(2), SPAG6(1) IPR000357 ARFGEF2(2), CMYA4(1), DRIM(2), JUP(1), KPNA5(2), PIK3R4(1), SPAG6(1) IPR000533 AKAP9(2), C10orf39(1), C20orf23(1), CUTL1(1), HOOK1(1), HOOK3(1), KTN1(2), LRRFIP1(3), MYH1(3), MYH9(2), NEF3(1), NF2(1), RSN(1), TAX1BP1(1), TPM4(1) IPR000694 ADAM12(3), ADAMTS19(1), APC2(2), APXL(1), ARID1B(1), BAT2(2), BAT3(1), BCAR1(1), BCL11A(2), BCORL1(1), C14orf155(3), C1orf2(1), C1QB(1), C6orf31(1), C7orf11(1), CD2(1), CENTD3(3), CHD5(3), CIC(3), CMYA1(2), COL11A1(3), COL19A1(2), COL7A1(3), DAZAP1(1), DBN1(3), DVL3(1), EIF5(1), FAM44A(1), FAM47B(1), FHOD1(1), FLJ20584(1), G3BP2(2), GAB1(2), GGA3(1), GLI1(3), GPNMB(2), GRIN2D(3), HCN3(1), HOXA3(2), HOXA4(1), IRS4(1), KCNA5(1), KCNC2(1), LIP8(1), LOC374955(1), MAGEE1(2), MICAL1(2), MICAL‐L1(1), MLLT2(1), MMP15(1), N4BP2(1), NCOA6(2), NHS(1), NUP214(3), ODZ1(3), PER1(2), PER2(1), PHC1(1), PLXNB1(1), PPM1E(2), RAI17(2), RAPH1(2), RBAF600(2), SCARF2(1), SEMA4G(1), SLC16A2(1), SORBS1(1), SPEN(2), SPG4(1), TBX1(1), TCF1(2), TCF7L1(1), TESK1(1), THG‐1(1), TP53(18), TRIF(1), ZBTB3(2), ZNF318(2) IPR000909 CENTB1(2), PLCB1(1), PLCG1(1) IPR000998 AEGP(3), EGFL6(2), PRSS7(1) IPR001140 ABCB10(2), ABCB6(1), ABCB8(2) IPR001164 ARFGAP3(1), CENTB1(2), CENTD3(3), CENTG1(2) IPR001589 -
Overview Gene List Target Scan Vs DIANA Group a Group B Group A
Overview Gene list Target scan vs DIANA Group A Group B Group A hsa-miR-181a hsa-miR-323 hsa-miR-326 Target scan Diana microT Overlap Target scan Diana microT Overlap Target scan SEPT3 SEPT3 SEPT3 SEPT7 ADARB1 HPCAL4 ABHD2 ABL2 ABHD13 ACVR2A ADCYAP1R1 AKAP13 PDPK1 ACRBP ACAN ABI1 ADAMTS1 ALAD APOBR ACVRL1 ACCN2 ABLIM1 ADAMTSL1 ANKRD52 ATXN1 ADAM19 ACER3 ACSL1 AKAP7 ARID2 C18orf23,RNF165 ADAM33 ACVR2A ACTN2 ANKRD43 ARL3 C20orf29 ADAMTS2 ADAMTS1 ACVR2A AP1S3 ARRB1 CACNG4 AHCYL2 ADAMTS18 ACVR2B ARID2 BBC3 CCNJL ALOX15B ADAMTS5 ADAM11 ATP11A BTG1 CYP2E1 ANK1 ADAMTSL1 ADAM22 ATXN1 C18orf62 GNB1L ANKS6 ADARB1 ADAMTS1 B4GALT1 C1orf21 GPR61 APBA1 AFAP1 ADAMTS6 BAG4 CADM4 GTSE1 ARCN1 AFTPH ADAMTSL1 BAI3 CALML4 HPCAL4 ARHGEF37 AK3 ADCY9 BNC2 CAPN6 KIAA0152 ARID3B AKAP7 ADRBK1 BRD1 CBFA2T2 KIF1A ARL8A ANAPC16 AFF2 BRWD1 CEBPA MACF1 ATP2B2 ANK1 AHCTF1,AHCTF1PBTBD3 CHD1 MYO1D ATP6V1G2 ANKRD12 AKAP2,PALM2 C13orf23 CIT PCNT AUP1 ANKRD33B AKAP6 C14orf43 CLASP2 PDPK1 BCL2L2 ANKRD43 AKAP7 CAPRIN1 CLCN5 PLEKHG4B BHLHE40 ANKRD44 AKAP9 CARM1 CLIP3 PPARA BTBD3 ANKRD52 AKT3 CBX4 COL5A2 PRB1,PRB2,PRB4 BTRC AP1S3 ALG9 CCDC117 CTNS PTPRT C10orf26 APBA1 ANKRD13C CCNJ DCTN4 PYCR1 C14orf1 APLP2 ANKRD20B CDH13 DCUN1D4 RAPGEF1 C16orf45 APOO ANKRD43 CDON DDB1 SRCAP C16orf54 ARID2 ANKRD50 CDYL DDX39B TMEM63C C1orf106 ARL3 AP1G1 CEP350 DIP2C C1orf27 ARRDC3 AP1S3 CHD7 DNAJB3 C22orf29 ATF7 API5 CHIC1 EEPD1 C9orf3 ATG2B ARFGEF2 CLIP1 EIF2C1 CACNA1E ATG7 ARHGAP12 CNOT6L ELFN2 CAPN12 ATP11A ARHGAP26 CNR1 ELK1 CASKIN1 ATP2B3 ARHGAP29 CNTN4 FAM172A CBFA2T3 ATP8B2 ARHGEF3 CNTNAP2 -
Identifying the Risky SNP of Osteoporosis with ID3-PEP Decision Tree Algorithm
Hindawi Complexity Volume 2017, Article ID 9194801, 8 pages https://doi.org/10.1155/2017/9194801 Research Article Identifying the Risky SNP of Osteoporosis with ID3-PEP Decision Tree Algorithm Jincai Yang,1 Huichao Gu,1 Xingpeng Jiang,1 Qingyang Huang,2 Xiaohua Hu,1 and Xianjun Shen1 1 School of Computer Science, Central China Normal University, Wuhan 430079, China 2School of Life Science, Central China Normal University, Wuhan 430079, China Correspondence should be addressed to Jincai Yang; [email protected] Received 31 March 2017; Revised 26 May 2017; Accepted 8 June 2017; Published 7 August 2017 Academic Editor: Fang-Xiang Wu Copyright © 2017 Jincai Yang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. In the past 20 years, much progress has been made on the genetic analysis of osteoporosis. A number of genes and SNPs associated with osteoporosis have been found through GWAS method. In this paper, we intend to identify the suspected risky SNPs of osteoporosis with computational methods based on the known osteoporosis GWAS-associated SNPs. The process includes two steps. Firstly, we decided whether the genes associated with the suspected risky SNPs are associated with osteoporosis by using random walk algorithm on the PPI network of osteoporosis GWAS-associated genes and the genes associated with the suspected risky SNPs. In order to solve the overfitting problem in ID3 decision tree algorithm, we then classified the SNPs with positive results based on their features of position and function through a simplified classification decision tree which was constructed by ID3 decision tree algorithm with PEP (Pessimistic-Error Pruning). -
Molecular Regulation in Dopaminergic Neuron Development
International Journal of Molecular Sciences Review Molecular Regulation in Dopaminergic Neuron Development. Cues to Unveil Molecular Pathogenesis and Pharmacological Targets of Neurodegeneration Floriana Volpicelli 1 , Carla Perrone-Capano 1,2 , Gian Carlo Bellenchi 2,3, Luca Colucci-D’Amato 4,* and Umberto di Porzio 2 1 Department of Pharmacy, University of Naples Federico II, 80131 Naples, Italy; fl[email protected] (F.V.); [email protected] (C.P.C.) 2 Institute of Genetics and Biophysics “Adriano Buzzati Traverso”, CNR, 80131 Rome, Italy; [email protected] (G.C.B.); [email protected] (U.d.P.) 3 Department of Systems Medicine, University of Rome Tor Vergata, 00133 Rome, Italy 4 Department of Environmental, Biological and Pharmaceutical Sciences and Technologies, University of Campania “Luigi Vanvitelli”, 81100 Caserta, Italy * Correspondence: [email protected]; Tel.: +39-0823-274577 Received: 28 April 2020; Accepted: 1 June 2020; Published: 3 June 2020 Abstract: The relatively few dopaminergic neurons in the mammalian brain are mostly located in the midbrain and regulate many important neural functions, including motor integration, cognition, emotive behaviors and reward. Therefore, alteration of their function or degeneration leads to severe neurological and neuropsychiatric diseases. Unraveling the mechanisms of midbrain dopaminergic (mDA) phenotype induction and maturation and elucidating the role of the gene network involved in the development and maintenance of these neurons is of pivotal importance to rescue or substitute these cells in order to restore dopaminergic functions. Recently, in addition to morphogens and transcription factors, microRNAs have been identified as critical players to confer mDA identity. The elucidation of the gene network involved in mDA neuron development and function will be crucial to identify early changes of mDA neurons that occur in pre-symptomatic pathological conditions, such as Parkinson’s disease. -
Characterization of Human-Ipscs Derived Spinal Motor Neurons by Single
bioRxiv preprint doi: https://doi.org/10.1101/2019.12.28.889972; this version posted December 28, 2019. 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. Characterization of human-iPSCs derived spinal motor neurons by single- cell RNA sequencing Louise Thiry1, Regan Hamel2, Stefano Pluchino2, Thomas Durcan1,3, Stefano Stifani1* 1Department of Neurology and Neurosurgery, Montreal Neurological Institute-Hospital, McGill University, 3801, rue University, Montreal (Quebec) H3A 2B4, Canada 2Department of Clinical Neurosciences, Clifford Allbutt Building - Cambridge Biosciences Campus and NIHR Biomedical Research Centre, University of Cambridge, Hills Road, CB2 0HA Cambridge, UK 3Early Drug Discovery Unit, Montreal Neurological Institute-Hospital *Corresponding author: [email protected] 1 bioRxiv preprint doi: https://doi.org/10.1101/2019.12.28.889972; this version posted December 28, 2019. 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 Human induced pluripotent stem cells (iPSCs) offer the opportunity to generate specific cell types from healthy and diseased individuals, allowing the study of mechanisms of early human development, modelling a variety of human diseases, and facilitating the development of new therapeutics. Human iPSC-based applications are often limited by the variability among iPSC lines originating from a single donor, as well as the heterogeneity among specific cell types that can be derived from iPSCs. The ability to deeply phenotype different iPSC-derived cell types is therefore of primary importance to the successful and informative application of this technology. -
PLEIOTROPIC and ISOFORM-SPECIFIC FUNCTIONS of PITX2 in BRAIN DEVELOPMENT by Mindy Rachelle Waite a Dissertation Submitted In
PLEIOTROPIC AND ISOFORM-SPECIFIC FUNCTIONS OF PITX2 IN BRAIN DEVELOPMENT by Mindy Rachelle Waite A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Cellular and Molecular Biology) in The University of Michigan 2012 Doctoral Committee: Associate Professor Donna M. Martin, Chair Professor Gregory R. Dressler Professor Sue O’Shea Associate Professor Philip J. Gage Associate Professor Robert C. Thompson Yesterday is but a dream, tomorrow but a vision. But today well lived makes every yesterday a dream of happiness, and every tomorrow a vision of hope. Look well, therefore, to This Day. -Sanskrit Proverb © Mindy Rachelle Waite 2012 ACKNOWLEDGMENTS I would like to thank Dr. Donna Martin for her unwavering mentorship and support. Donna, I can never repay you enough for taking me in as one of your own and building my skillset from the ground up. You really put your heart and soul into teaching me how to do research, write, speak, and even work in a team setting. Thank you so much for the skills and self-confidence which will be necessary for my future successes. I will never forget our first “data dance” and promise to think of you every time I see red ink. I would also like to thank the rest of my lab. Liz, Jennifer, Joe, Wanda, Kaia, and Jillian – what would I have ever done without you guys? Graduate school can be a frustrating, lonely experience for some, but not for me. Every day I worked with my friends. Thank you for your unconditional support and delightful shenanigans. -
Identification of Cis-Element Regulating Expression of the Mouse Fgf10 Gene During Inner Ear Development
DEVELOPMENTAL DYNAMICS 233:177–187, 2005 PATTERNS & PHENOTYPES Identification of Cis-Element Regulating Expression of the Mouse Fgf10 Gene during Inner Ear Development Hideyo Ohuchi,1* Akihiro Yasue,1–3 Katsuhiko Ono,4 Shunsuke Sasaoka,5 Sayuri Tomonari,1 Akira Takagi,1 Mitsuo Itakura,2 Keiji Moriyama,3 Sumihare Noji,1 and Tsutomu Nohno5 Fibroblast growth factor (FGF) signaling is crucial for the induction and growth of the ear, a sensory organ that involves intimate tissue interactions. Here, we report the abnormality of Fgf10 null ear and the identification of a cis-regulatory element directing otic expression of Fgf10.InFgf10 null inner ears, we found that the initial development of semicircular, vestibular, and cochlear divisions is roughly normal, after which there are abnormalities of semicircular canal/cristae and vestibular development. The mutant semicircular disks remain without canal formation by the perinatal stage. To elucidate regulation of the Fgf10 expression during inner ear development, we isolated a 6.6-kb fragment of its 5-upstream region and examined its transcriptional activity with transgenic mice, using a lacZ-reporter system. From comparison of the mouse sequences of the 6.6-kb fragment with corresponding sequences of the human and chicken Fgf10, we identified a 0.4-kb enhancer sequence that drives Fgf10 expression in the developing inner ear. The enhancer sequences have motifs for many homeodomain-containing proteins (e.g., Prx, Hox, Nkx), in addition to POU-domain factors (e.g., Brn3), zinc-finger transcription factors (e.g., GATA-binding factors), TCF/LEF-1, and a SMAD-interacting protein. Thus, FGF10 signaling is dispensable for specification of otic compartment identity but is required for hollowing the semicircular disk. -
TFAP2 Transcription Factors Are Regulators of Lipid Droplet Biogenesis
bioRxiv preprint doi: https://doi.org/10.1101/282376; this version posted March 14, 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 4.0 International license. 1 TFAP2 transcription factors are 2 regulators of lipid droplet biogenesis 3 4 5 Cameron C Scott1, Stefania Vossio1, Jacques Rougemont2, Jean Gruenberg1,3 6 7 8 9 10 11 12 1. Department of Biochemistry, University of Geneva, 30 quai Ernest Ansermet 13 1211 Geneva 4, Switzerland 14 2. Department of Theoretical Physics, University of Geneva, 24 quai Ernest Ansermet 15 1211 Geneva 4, Switzerland 16 17 3. To whom correspondence should be addressed: [email protected] 18 19 20 21 22 1 bioRxiv preprint doi: https://doi.org/10.1101/282376; this version posted March 14, 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 4.0 International license. 1 Abstract 2 How trafficking pathways and organelle abundance adapt in response to metabolic 3 and physiological changes is still mysterious, although a few transcriptional regulators of 4 organellar biogenesis have been identified in recent years. We previously found that the Wnt 5 signaling directly controls lipid droplet formation, linking the cell storage capacity to the 6 established functions of Wnt in development and differentiation. In the present paper, we 7 report that Wnt-induced lipid droplet biogenesis does not depend on the canonical TCF/LEF 8 transcription factors. -
Supplementary File Table S1
Supplementary file Table S1 Grouping of Homeobox genes according to their main known function. Anatomical Structure Morphogenesis EN1, HOXC10, HOXC13, HOXD3, LBX1, SIX2, SIX4 Organ Morphogenesis CDX1, CDX2, HOXA11, HOXA13, ISL1, LHX1, PAX3, PDHX, PITX2, PITX3, PROX1, SIX6 Body Pattern Formation ALX3, EMX2, HHEX, HOXA11, HOXA2, HOXA4, HOXA5, HOXA6, HOXB1, HOXB5, HOXB6, HOXC5, HOXD10, HOXD8, LMX1B, PITX2 Ectoderm Development PROX1, VAX2 Endoderm Development HOXC11 Brain & Nervous System Development Brain Development ALX1, DLX2, EMX2 Nervous System Development: ARX, DLX5, DLX6, HOXD10, LBX1, LHX1, OTP, PAX3, PHOX2A, PHOX2B Skeletal Development: ALX3, ALX4, DLX3, DLX5, DLX6, EN1, HOXA11, HOXA13, HOXA2, HOXB6, HOXD10, HOXD13, MSX2 Muscle Development: BARX2, MKX, SIRT1, SIRT2, SIX1 Other Homeobox Genes Involved In BARX1, CDX4, CUX1, DLX1, EMX1, EN2, Multicellular Organismal HOXA1, HOXA7, HOXA9, HOXB13, HOXB2, Development: HOXB3, HOXB4, HOXB7, HOXB8, HOXB9, HOXC12, HOXC8, HOXC9, HOXD1, HOXD11, HOXD12, HOXD9, ISL2, LBX2, LMX1A, MEIS1, NKX3-1, OTX1, TLX1, VAX1, VSX1, VSX2 Homeobox Genes Involved In Cell ARX, EMX2, HHEX, HLX, HOPX, LBX1, LHX1, Differentiation: LMX1B, MIXL1, OTP, PHOX2A, SIRT1, VSX2 Other Genes: PHTF1, SIRT3, SIRT6, SIRT7, ZHX1, ZHX2 Homeobox genes include two subsets of genes coding for transcription factors involved in multiple functions. The clustered HOX genes are indicated in bold. Supplementary file Figure S2 5’ Spatial collinearity 3’ HOXA Chr. 7p15.3 HOXB Chr. 17q21.3 HOXC Chr. 12q13.3 HOXD Chr. 2q31 13 12 11 10 9 8 7 6 5 4 3 2 1 Paralogous HOX groups Distribution of the 39 human HOX genes in four clusters located in different chromosomal regions*. Blue indicates anterior HOX genes. Yellow, paralogy group 3 Hox genes, green and purple indicatete central HOX genes and Red the posterior HOX genes. -
Ventral Neural Patterning by Nkx Homeobox Genes: Nkx6.1 Controls Somatic Motor Neuron and Ventral Interneuron Fates
Downloaded from genesdev.cshlp.org on September 30, 2021 - Published by Cold Spring Harbor Laboratory Press RESEARCH COMMUNICATION vitro in response to two- to threefold changes in the Ventral neural patterning by concentration of Shh, and the position at which each Nkx homeobox genes: Nkx6.1 neuronal class is generated in vivo is predicted by the controls somatic motor neuron concentration required for their induction in vivo (Eric- son et al. 1997a,b; Briscoe et al. 2000). Thus, neurons and ventral interneuron fates generated in more ventral regions of the neural tube re- 1,2,6 3,6 quire progressively higher concentrations of Shh for their Maike Sander, Sussan Paydar, induction. 4,5 4 Johan Ericson, James Briscoe, The genetic programs activated in neural progenitor 3 1 Elizabeth Berber, Michael German, cells in response to Shh signaling, however, remain in- Thomas M. Jessell,4 and John L.R. Rubenstein3,7 completely defined. Emerging evidence suggests that homeobox genes function as critical intermediaries in 1Hormone Research Institute, Department of Medicine, the neural response to Shh signals (Lumsden and Krum- University of California–San Francisco, San Franscisco, California 94143 USA; 2Center for Molecular Neurobiology, lauf 1996; Tanabe and Jessell 1996; Ericson et al. 1997a,b; Hamburg, Germany; 3Nina Ireland Laboratory of Hammerschmidt et al. 1997; Rubenstein et al. 1998). Developmental Neurobiology, University of California–San Several homeobox genes are expressed by ventral pro- Francisco, San Francisco, California 94143 USA; -
Sequential Roles for Otx2 in Visceral Endoderm and Neuroectoderm for Forebrain and Midbrain Induction and Specification
Development 125, 845-856 (1998) 845 Printed in Great Britain © The Company of Biologists Limited 1998 DEV4958 Sequential roles for Otx2 in visceral endoderm and neuroectoderm for forebrain and midbrain induction and specification Muriel Rhinn1, Andrée Dierich1, William Shawlot2, Richard R. Behringer2, Marianne Le Meur1 and Siew-Lan Ang1,* 1Institut de Génétique et de Biologie Moléculaire et Cellulaire, CNRS/INSERM/Université Louis Pasteur, 67404 Illkirch cedex, CU de Strasbourg, France 2Department of Molecular Genetics, The University of Texas M. D. Anderson Cancer Center, Houston, Texas 77030, USA *Author for correspondence (e-mail: [email protected]) Accepted 12 December 1998: published on WWW 4 February 1998 SUMMARY The homeobox gene Otx2 is a mouse cognate of the However, in the absence of Otx2, expression of important Drosophila orthodenticle gene, which is required for regulatory genes, such as Hesx1/Rpx, Six3, Pax2, Wnt1 and development of the brain, rostral to rhombomere three. We En, fail to be initiated or maintained in the neural plate. have investigated the mechanisms involved in this neural Using explant-recombination assay, we could further function and specifically the requirement for Otx2 in the demonstrate that Otx2 is required in the neuroectodem for visceral endoderm and the neuroectoderm using chimeric expression of En. Altogether, these results demonstrate that analysis in mice and explant recombination assay. Analyses Otx2 is first required in the visceral endoderm for the of chimeric embryos composed of more than 90% of Otx2− induction, and subsequently in the neuroectoderm for the /− ES cells identified an essential function for Otx2 in the specification of forebrain and midbrain territories.