Candidate Downstream Regulated Genes of HOX Group 13 Transcription Factors with and Without Monomeric DNA Binding Capability
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Original Article Upregulation of HOXA13 As a Potential Tumorigenesis and Progression Promoter of LUSC Based on Qrt-PCR and Bioinformatics
Int J Clin Exp Pathol 2017;10(10):10650-10665 www.ijcep.com /ISSN:1936-2625/IJCEP0065149 Original Article Upregulation of HOXA13 as a potential tumorigenesis and progression promoter of LUSC based on qRT-PCR and bioinformatics Rui Zhang1*, Yun Deng1*, Yu Zhang1, Gao-Qiang Zhai1, Rong-Quan He2, Xiao-Hua Hu2, Dan-Ming Wei1, Zhen-Bo Feng1, Gang Chen1 Departments of 1Pathology, 2Medical Oncology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, China. *Equal contributors. Received September 7, 2017; Accepted September 29, 2017; Epub October 1, 2017; Published October 15, 2017 Abstract: In this study, we investigated the levels of homeobox A13 (HOXA13) and the mechanisms underlying the co-expressed genes of HOXA13 in lung squamous cancer (LUSC), the signaling pathways in which the co-ex- pressed genes of HOXA13 are involved and their functional roles in LUSC. The clinical significance of 23 paired LUSC tissues and adjacent non-tumor tissues were gathered. HOXA13 levels in LUSC were detected by quantita- tive real-time polymerase chain reaction (qRT-PCR). HOXA13 levels in LUSC from The Cancer Genome Atlas (TCGA) and Oncomine were analyzed. We performed receiver operator characteristic (ROC) curves of various clinicopath- ological features of LUSC. Co-expressed of HOXA13 were collected from MEM, cBioPortal and GEPIA. The func- tions and pathways of the most reliable overlapped genes were achieved from the Gene Otology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases, respectively. The protein-protein interaction (PPI) net- works were mapped using STRING. HOXA13 in LUSC were markedly upregulated compared with those in the non- cancerous controls as demonstrated by qRT-PCR (LUSC: 0.330±0.360; CONTROLS: 0.155±0.142; P=0.021). -
The Role of IL-1 in Adipose Browning and Muscle Wasting in CKD-Associated Cachexia
bioRxiv preprint doi: https://doi.org/10.1101/2021.02.05.429984; this version posted February 7, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder.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. The role of IL-1 in adipose browning and muscle wasting in CKD-associated cachexia Wai W Cheung1*, Ronghao Zheng2*, Sheng Hao3, Zhen Wang4, Alex Gonzalez1, Ping Zhou5, Hal M Hoffman6, Robert H Mak1 1 Pediatric Nephrology, Rady Children’s Hospital San Diego, University of California, San Diego, USA 2 Department of Pediatric Nephrology, Rheumatology, and Immunology, Maternal and Child Health Hospital of Hubei Province, TongJi Medical College, Huazhong University of Science and Technology, Wuhan, China 3Department of Nephrology and Rheumatology, Shanghai Children’s Hospital, Shanghai Jiao Tong University, Shanghai, China 4Department of Pediatrics, Shanghai General Hospital, Shanghai Jiao Tong University, Shanghai, China 5 Department of Pediatrics, the Second Affiliated Hospital of Harbin Medical University, Harbin, China 6 Department of Pediatrics, University of California, San Diego, USA * These authors contributed equally to this work. Correspondence: Robert H Mak Division of Pediatric Nephrology Rady Children’s Hospital University of California, San Diego 9500 Gilman Drive, MC0831, La Jolla, California 92093-0831, USA P: 858-822-6717 F: 858-822-6776 E-mail: [email protected] Running title: Anakinra attenuates uremic cachexia bioRxiv preprint doi: https://doi.org/10.1101/2021.02.05.429984; this version posted February 7, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. -
Genome-Wide Analysis of 5-Hmc in the Peripheral Blood of Systemic Lupus Erythematosus Patients Using an Hmedip-Chip
INTERNATIONAL JOURNAL OF MOLECULAR MEDICINE 35: 1467-1479, 2015 Genome-wide analysis of 5-hmC in the peripheral blood of systemic lupus erythematosus patients using an hMeDIP-chip WEIGUO SUI1*, QIUPEI TAN1*, MING YANG1, QIANG YAN1, HUA LIN1, MINGLIN OU1, WEN XUE1, JIEJING CHEN1, TONGXIANG ZOU1, HUANYUN JING1, LI GUO1, CUIHUI CAO1, YUFENG SUN1, ZHENZHEN CUI1 and YONG DAI2 1Guangxi Key Laboratory of Metabolic Diseases Research, Central Laboratory of Guilin 181st Hospital, Guilin, Guangxi 541002; 2Clinical Medical Research Center, the Second Clinical Medical College of Jinan University (Shenzhen People's Hospital), Shenzhen, Guangdong 518020, P.R. China Received July 9, 2014; Accepted February 27, 2015 DOI: 10.3892/ijmm.2015.2149 Abstract. Systemic lupus erythematosus (SLE) is a chronic, Introduction potentially fatal systemic autoimmune disease characterized by the production of autoantibodies against a wide range Systemic lupus erythematosus (SLE) is a typical systemic auto- of self-antigens. To investigate the role of the 5-hmC DNA immune disease, involving diffuse connective tissues (1) and modification with regard to the onset of SLE, we compared is characterized by immune inflammation. SLE has a complex the levels 5-hmC between SLE patients and normal controls. pathogenesis (2), involving genetic, immunologic and envi- Whole blood was obtained from patients, and genomic DNA ronmental factors. Thus, it may result in damage to multiple was extracted. Using the hMeDIP-chip analysis and valida- tissues and organs, especially the kidneys (3). SLE arises from tion by quantitative RT-PCR (RT-qPCR), we identified the a combination of heritable and environmental influences. differentially hydroxymethylated regions that are associated Epigenetics, the study of changes in gene expression with SLE. -
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 -
By Submitted in Partial Satisfaction of the Requirements for Degree of in In
Developments of Two Imaging based Technologies for Cell Biology Researches by Xiaowei Yan DISSERTATION Submitted in partial satisfaction of the requirements for degree of DOCTOR OF PHILOSOPHY in Biochemistry and Molecular Biology in the GRADUATE DIVISION of the UNIVERSITY OF CALIFORNIA, SAN FRANCISCO Approved: ______________________________________________________________________________Ronald Vale Chair ______________________________________________________________________________Jonathan Weissman ______________________________________________________________________________Orion Weiner ______________________________________________________________________________ ______________________________________________________________________________ Committee Members Copyright 2021 By Xiaowei Yan ii DEDICATION Everything happens for the best. To my family, who supported me with all their love. iii ACKNOWLEDGEMENTS The greatest joy of my PhD has been joining UCSF, working and learning with such a fantastic group of scientists. I am extremely grateful for all the support and mentorship I received and would like to thank: My mentor, Ron Vale, who is such a great and generous person. Thank you for showing me that science is so much fun and thank you for always giving me the freedom in pursuing my interest. I am grateful for all the guidance from you and thank you for always supporting me whenever I needed. You are a person full of wisdom, and I have been learning so much from you and your attitude to science, science community and even life will continue inspire me. Thank you for being my mentor and thank you for being such a great mentor. Everyone else in Vale lab, past and present, for making our lab a sweet home. I would like to give my special thank to Marvin (Marvin Tanenbaum) and Nico (Nico Stuurman), two other mentors for me in the lab. I would like to thank them for helping me adapt to our lab, for all the valuable advice and for all the happiness during the time that we work together. -
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. -
Lncrnas in Non-Small-Cell Lung Cancer
non-coding RNA Review LncRNAs in Non-Small-Cell Lung Cancer Lucy Ginn , Lei Shi, Manuela La Montagna and Michela Garofalo * Transcriptional Networks in Lung Cancer Group, Cancer Research UK Manchester Institute, University of Manchester, Alderley Park, Manchester SK10 4TG, UK; [email protected] (L.G.); [email protected] (L.S.); [email protected] (M.L.M.) * Correspondence: [email protected]; Tel.: +44-(0)-161-306-6056 Received: 27 May 2020; Accepted: 28 June 2020; Published: 30 June 2020 Abstract: Lung cancer is associated with a high mortality, with around 1.8 million deaths worldwide in 2018. Non-small-cell lung cancer (NSCLC) accounts for around 85% of cases and, despite improvement in the management of NSCLC, most patients are diagnosed at advanced stage and the five-year survival remains around 15%. This highlights a need to identify novel ways to treat the disease to reduce the burden of NSCLC. Long non-coding RNAs (lncRNAs) are non-coding RNA molecules longer than 200 nucleotides in length which play important roles in gene expression and signaling pathways. Recently, lncRNAs were implicated in cancer, where their expression is dysregulated resulting in aberrant functions. LncRNAs were shown to function as both tumor suppressors and oncogenes in a variety of cancer types. Although there are a few well characterized lncRNAs in NSCLC, many lncRNAs remain un-characterized and their mechanisms of action largely unknown. LncRNAs have success as therapies in neurodegenerative diseases, and having a detailed understanding of their function in NSCLC may guide novel therapeutic approaches and strategies. -
Supplementary Table S1. Upregulated Genes Differentially
Supplementary Table S1. Upregulated genes differentially expressed in athletes (p < 0.05 and 1.3-fold change) Gene Symbol p Value Fold Change 221051_s_at NMRK2 0.01 2.38 236518_at CCDC183 0.00 2.05 218804_at ANO1 0.00 2.05 234675_x_at 0.01 2.02 207076_s_at ASS1 0.00 1.85 209135_at ASPH 0.02 1.81 228434_at BTNL9 0.03 1.81 229985_at BTNL9 0.01 1.79 215795_at MYH7B 0.01 1.78 217979_at TSPAN13 0.01 1.77 230992_at BTNL9 0.01 1.75 226884_at LRRN1 0.03 1.74 220039_s_at CDKAL1 0.01 1.73 236520_at 0.02 1.72 219895_at TMEM255A 0.04 1.72 201030_x_at LDHB 0.00 1.69 233824_at 0.00 1.69 232257_s_at 0.05 1.67 236359_at SCN4B 0.04 1.64 242868_at 0.00 1.63 1557286_at 0.01 1.63 202780_at OXCT1 0.01 1.63 1556542_a_at 0.04 1.63 209992_at PFKFB2 0.04 1.63 205247_at NOTCH4 0.01 1.62 1554182_at TRIM73///TRIM74 0.00 1.61 232892_at MIR1-1HG 0.02 1.61 204726_at CDH13 0.01 1.6 1561167_at 0.01 1.6 1565821_at 0.01 1.6 210169_at SEC14L5 0.01 1.6 236963_at 0.02 1.6 1552880_at SEC16B 0.02 1.6 235228_at CCDC85A 0.02 1.6 1568623_a_at SLC35E4 0.00 1.59 204844_at ENPEP 0.00 1.59 1552256_a_at SCARB1 0.02 1.59 1557283_a_at ZNF519 0.02 1.59 1557293_at LINC00969 0.03 1.59 231644_at 0.01 1.58 228115_at GAREM1 0.01 1.58 223687_s_at LY6K 0.02 1.58 231779_at IRAK2 0.03 1.58 243332_at LOC105379610 0.04 1.58 232118_at 0.01 1.57 203423_at RBP1 0.02 1.57 AMY1A///AMY1B///AMY1C///AMY2A///AMY2B// 208498_s_at 0.03 1.57 /AMYP1 237154_at LOC101930114 0.00 1.56 1559691_at 0.01 1.56 243481_at RHOJ 0.03 1.56 238834_at MYLK3 0.01 1.55 213438_at NFASC 0.02 1.55 242290_at TACC1 0.04 1.55 ANKRD20A1///ANKRD20A12P///ANKRD20A2/// -
Mouse Casp8ap2 Conditional Knockout Project (CRISPR/Cas9)
https://www.alphaknockout.com Mouse Casp8ap2 Conditional Knockout Project (CRISPR/Cas9) Objective: To create a Casp8ap2 conditional knockout Mouse model (C57BL/6J) by CRISPR/Cas-mediated genome engineering. Strategy summary: The Casp8ap2 gene (NCBI Reference Sequence: NM_011997 ; Ensembl: ENSMUSG00000028282 ) is located on Mouse chromosome 4. 11 exons are identified, with the ATG start codon in exon 2 and the TAG stop codon in exon 10 (Transcript: ENSMUST00000029950). Exon 4 will be selected as conditional knockout region (cKO region). Deletion of this region should result in the loss of function of the Mouse Casp8ap2 gene. To engineer the targeting vector, homologous arms and cKO region will be generated by PCR using BAC clone RP23-75H14 as template. Cas9, gRNA and targeting vector will be co-injected into fertilized eggs for cKO Mouse production. The pups will be genotyped by PCR followed by sequencing analysis. Note: Mice homozygous for disruption of this gene die before implantation. Exon 4 starts from about 2.12% of the coding region. The knockout of Exon 4 will result in frameshift of the gene. The size of intron 3 for 5'-loxP site insertion: 819 bp, and the size of intron 4 for 3'-loxP site insertion: 639 bp. The size of effective cKO region: ~601 bp. The cKO region does not have any other known gene. Page 1 of 7 https://www.alphaknockout.com Overview of the Targeting Strategy Wildtype allele gRNA region 5' gRNA region 3' 1 3 4 5 11 Targeting vector Targeted allele Constitutive KO allele (After Cre recombination) Legends Exon of mouse Casp8ap2 Homology arm cKO region loxP site Page 2 of 7 https://www.alphaknockout.com Overview of the Dot Plot Window size: 10 bp Forward Reverse Complement Sequence 12 Note: The sequence of homologous arms and cKO region is aligned with itself to determine if there are tandem repeats. -
Hoxb1 Controls Anteroposterior Identity of Vestibular Projection Neurons
Hoxb1 Controls Anteroposterior Identity of Vestibular Projection Neurons Yiju Chen1, Masumi Takano-Maruyama1, Bernd Fritzsch2, Gary O. Gaufo1* 1 Department of Biology, University of Texas at San Antonio, San Antonio, Texas, United States of America, 2 Department of Biology, University of Iowa, Iowa City, Iowa, United States of America Abstract The vestibular nuclear complex (VNC) consists of a collection of sensory relay nuclei that integrates and relays information essential for coordination of eye movements, balance, and posture. Spanning the majority of the hindbrain alar plate, the rhombomere (r) origin and projection pattern of the VNC have been characterized in descriptive works using neuroanatomical tracing. However, neither the molecular identity nor developmental regulation of individual nucleus of the VNC has been determined. To begin to address this issue, we found that Hoxb1 is required for the anterior-posterior (AP) identity of precursors that contribute to the lateral vestibular nucleus (LVN). Using a gene-targeted Hoxb1-GFP reporter in the mouse, we show that the LVN precursors originate exclusively from r4 and project to the spinal cord in the stereotypic pattern of the lateral vestibulospinal tract that provides input into spinal motoneurons driving extensor muscles of the limb. The r4-derived LVN precursors express the transcription factors Phox2a and Lbx1, and the glutamatergic marker Vglut2, which together defines them as dB2 neurons. Loss of Hoxb1 function does not alter the glutamatergic phenotype of dB2 neurons, but alters their stereotyped spinal cord projection. Moreover, at the expense of Phox2a, the glutamatergic determinants Lmx1b and Tlx3 were ectopically expressed by dB2 neurons. Our study suggests that the Hox genes determine the AP identity and diversity of vestibular precursors, including their output target, by coordinating the expression of neurotransmitter determinant and target selection properties along the AP axis. -
Homeobox Gene Expression Profile in Human Hematopoietic Multipotent
Leukemia (2003) 17, 1157–1163 & 2003 Nature Publishing Group All rights reserved 0887-6924/03 $25.00 www.nature.com/leu Homeobox gene expression profile in human hematopoietic multipotent stem cells and T-cell progenitors: implications for human T-cell development T Taghon1, K Thys1, M De Smedt1, F Weerkamp2, FJT Staal2, J Plum1 and G Leclercq1 1Department of Clinical Chemistry, Microbiology and Immunology, Ghent University Hospital, Ghent, Belgium; and 2Department of Immunology, Erasmus Medical Center, Rotterdam, The Netherlands Class I homeobox (HOX) genes comprise a large family of implicated in this transformation proces.14 The HOX-C locus transcription factors that have been implicated in normal and has been primarily implicated in lymphomas.15 malignant hematopoiesis. However, data on their expression or function during T-cell development is limited. Using degener- Hematopoietic cells are derived from stem cells that reside in ated RT-PCR and Affymetrix microarray analysis, we analyzed fetal liver (FL) in the embryo and in the adult bone marrow the expression pattern of this gene family in human multipotent (ABM), which have the unique ability to self-renew and thereby stem cells from fetal liver (FL) and adult bone marrow (ABM), provide a life-long supply of blood cells. T lymphocytes are a and in T-cell progenitors from child thymus. We show that FL specific type of hematopoietic cells that play a major role in the and ABM stem cells are similar in terms of HOX gene immune system. They develop through a well-defined order of expression, but significant differences were observed between differentiation steps in the thymus.16 Several transcription these two cell types and child thymocytes. -
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.