Global Gene Expression of the Inner Cell Mass and Trophectoderm of The
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Replication of FTO Gene Associated with Lean Mass in a Meta
www.nature.com/scientificreports OPEN Replication of FTO Gene associated with lean mass in a Meta-Analysis of Genome-Wide Association Studies Shu Ran1, Zi-Xuan Jiang1, Xiao He1, Yu Liu1, Yu-Xue Zhang1, Lei Zhang2,3, Yu-Fang Pei3,4, Meng Zhang5, Rong Hai6, Gui-Shan Gu7, Bao-Lin Liu1, Qing Tian8, Yong-Hong Zhang3,4, Jing-Yu Wang7 & Hong-Wen Deng8* Sarcopenia is characterized by low skeletal muscle, a complex trait with high heritability. With the dramatically increasing prevalence of obesity, obesity and sarcopenia occur simultaneously, a condition known as sarcopenic obesity. Fat mass and obesity-associated (FTO) gene is a candidate gene of obesity. To identify associations between lean mass and FTO gene, we performed a genome-wide association study (GWAS) of lean mass index (LMI) in 2207 unrelated Caucasian subjects and replicated major fndings in two replication samples including 6,004 unrelated Caucasian and 38,292 unrelated Caucasian. We found 29 single nucleotide polymorphisms (SNPs) in FTO signifcantly associated with sarcopenia (combined p-values ranging from 5.92 × 10−12 to 1.69 × 10−9). Potential biological functions of SNPs were analyzed by HaploReg v4.1, RegulomeDB, GTEx, IMPC and STRING. Our results provide suggestive evidence that FTO gene is associated with lean mass. Sarcopenia is a complex disease described as the age-associated loss of skeletal muscle mass, strength and func- tion impairment1,2. Te low skeletal muscle mass will lead to many public health problems such as sarcopenia, osteoporosis and increased mortality3,4, especially in the elderly. Skeletal muscle is heritable with heritability esti- mates of 30–85% for muscle strength and 45–90% for muscle mass5. -
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 -
Genome-Wide Approach to Identify Risk Factors for Therapy-Related Myeloid Leukemia
Leukemia (2006) 20, 239–246 & 2006 Nature Publishing Group All rights reserved 0887-6924/06 $30.00 www.nature.com/leu ORIGINAL ARTICLE Genome-wide approach to identify risk factors for therapy-related myeloid leukemia A Bogni1, C Cheng2, W Liu2, W Yang1, J Pfeffer1, S Mukatira3, D French1, JR Downing4, C-H Pui4,5,6 and MV Relling1,6 1Department of Pharmaceutical Sciences, The University of Tennessee, Memphis, TN, USA; 2Department of Biostatistics, The University of Tennessee, Memphis, TN, USA; 3Hartwell Center, The University of Tennessee, Memphis, TN, USA; 4Department of Pathology, The University of Tennessee, Memphis, TN, USA; 5Department of Hematology/Oncology St Jude Children’s Research Hospital, The University of Tennessee, Memphis, TN, USA; and 6Colleges of Medicine and Pharmacy, The University of Tennessee, Memphis, TN, USA Using a target gene approach, only a few host genetic risk therapy increases, the importance of identifying host factors for factors for treatment-related myeloid leukemia (t-ML) have been secondary neoplasms increases. defined. Gene expression microarrays allow for a more 4 genome-wide approach to assess possible genetic risk factors Because DNA microarrays interrogate multiple ( 10 000) for t-ML. We assessed gene expression profiles (n ¼ 12 625 genes in one experiment, they allow for a ‘genome-wide’ probe sets) in diagnostic acute lymphoblastic leukemic cells assessment of genes that may predispose to leukemogenesis. from 228 children treated on protocols that included leukemo- DNA microarray analysis of gene expression has been used to genic agents such as etoposide, 13 of whom developed t-ML. identify distinct expression profiles that are characteristic of Expression of 68 probes, corresponding to 63 genes, was different leukemia subtypes.13,14 Studies using this method have significantly related to risk of t-ML. -
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. -
An Enhancer Directs Differential Expression of the Linked Mrf4 and Myf5 Myogenic Regulatory Genes in the Mouse
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector Developmental Biology 269 (2004) 595–608 www.elsevier.com/locate/ydbio An enhancer directs differential expression of the linked Mrf4 and Myf5 myogenic regulatory genes in the mouse Ted Hung-Tse Chang, Michael Primig,1 Juliette Hadchouel,2 Shahragim Tajbakhsh,3 Didier Rocancourt, Anne Fernandez,4 Roland Kappler,5 Harry Scherthan,6 and Margaret Buckingham* De´partement de Biologie du De´veloppement, CNRS URA 2578, Institut Pasteur, 75724 Paris Cedex 15, France Received for publication 25 September 2003, revised 3 February 2004, accepted 6 February 2004 Abstract The myogenic regulatory factors, Mrf4 and Myf5, play a key role in skeletal muscle formation. An enhancer trap approach, devised to isolate positive-acting elements from a 200-kb YAC covering the mouse Mrf4–Myf5 locus in a C2 myoblast assay, yielded an enhancer, A17, which mapped at À8kb5V of Mrf4 and À17 kb 5V of Myf5. An E-box bound by complexes containing the USF transcription factor is critical for enhancer activity. In transgenic mice, A17 gave two distinct and mutually exclusive expression profiles before birth, which correspond to two phases of Mrf4 transcription. Linked to the Tk or Mrf4 minimal promoters, the nlacZ reporter was expressed either in embryonic myotomes, or later in fetal muscle, with the majority of Mrf4 lines showing embryonic expression. When linked to the Myf5 minimal promoter, only fetal muscle expression was detected. These observations identify A17 as a sequence that targets sites of myogenesis in vivo and raise questions about the mutually exclusive modes of expression and possible promoter/enhancer interactions at the Mrf4–Myf5 locus. -
The Middle Temporal Gyrus Is Transcriptionally Altered in Patients with Alzheimer’S Disease
1 The middle temporal gyrus is transcriptionally altered in patients with Alzheimer’s Disease. 2 1 3 Shahan Mamoor 1Thomas Jefferson School of Law 4 East Islip, NY 11730 [email protected] 5 6 We sought to understand, at the systems level and in an unbiased fashion, how gene 7 expression was most different in the brains of patients with Alzheimer’s Disease (AD) by mining published microarray datasets (1, 2). Comparing global gene expression profiles between 8 patient and control revealed that a set of 84 genes were expressed at significantly different levels in the middle temporal gyrus (MTG) of patients with Alzheimer’s Disease (1, 2). We used 9 computational analyses to classify these genes into known pathways and existing gene sets, 10 and to describe the major differences in the epigenetic marks at the genomic loci of these genes. While a portion of these genes is computationally cognizable as part of a set of genes 11 up-regulated in the brains of patients with AD (3), many other genes in the gene set identified here have not previously been studied in association with AD. Transcriptional repression, both 12 pre- and post-transcription appears to be affected; nearly 40% of these genes are transcriptional 13 targets of MicroRNA-19A/B (miR-19A/B), the zinc finger protein 10 (ZNF10), or of the AP-1 repressor jun dimerization protein 2 (JDP2). 14 15 16 17 18 19 20 21 22 23 24 25 26 Keywords: Alzheimer’s Disease, systems biology of Alzheimer’s Disease, differential gene 27 expression, middle temporal gyrus. -
Ebf2 Is a Selective Marker of Brown and Beige Adipogenic Precursor Cells
Ebf2 is a selective marker of brown and beige adipogenic precursor cells Wenshan Wanga,b, Megan Kissiga,b, Sona Rajakumaria,b, Li Huanga,b, Hee-woong Lima,c, Kyoung-Jae Wona,c, and Patrick Sealea,b,1 aInstitute for Diabetes, Obesity, Metabolism, bDepartment of Cell and Developmental Biology, and cDepartment of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104 Edited by C. Ronald Kahn, Joslin Diabetes Center, Harvard Medical School, Boston, MA, and approved August 8, 2014 (received for review July 8, 2014) Brown adipocytes and muscle and dorsal dermis descend from transcriptomic analyses identified a brown-preadipose–specific precursor cells in the dermomyotome, but the factors that regulate gene signature, which included early B-cell factor 2 (Ebf2), a crit- commitment to the brown adipose lineage are unknown. Here, we ical transcriptional regulator in mature brown adipocytes (18). prospectively isolated and determined the molecular profile of We found that brown/beige preadipose activity in embryos and embryonic brown preadipose cells. Brown adipogenic precursor adult fat depots was restricted to Ebf2-expressing cells. Further- activity in embryos was confined to platelet-derived growth factor more, Ebf2 deficiency in brown preadipose cells reduced the ex- + Cre α , myogenic factor 5 -lineage–marked cells. RNA-sequence anal- pression of nearly all brown preadipose signature genes, whereas ysis identified early B-cell factor 2 (Ebf2) as one of the most selec- ectopic expression of Ebf2 in myoblasts activated brown pre- tively expressed genes in this cell fraction. Importantly, Ebf2- GFP adipose-selective genes. Altogether, our study reveals that expressing cells purified from Ebf2 embryos or brown fat tissue Ebf2 is a specific marker of brown/beige preadipose cells and did not express myoblast or dermal cell markers and uniformly dif- that Ebf2 functions at this stage to control precursor identity. -
Supplementary Table S4. FGA Co-Expressed Gene List in LUAD
Supplementary Table S4. FGA co-expressed gene list in LUAD tumors Symbol R Locus Description FGG 0.919 4q28 fibrinogen gamma chain FGL1 0.635 8p22 fibrinogen-like 1 SLC7A2 0.536 8p22 solute carrier family 7 (cationic amino acid transporter, y+ system), member 2 DUSP4 0.521 8p12-p11 dual specificity phosphatase 4 HAL 0.51 12q22-q24.1histidine ammonia-lyase PDE4D 0.499 5q12 phosphodiesterase 4D, cAMP-specific FURIN 0.497 15q26.1 furin (paired basic amino acid cleaving enzyme) CPS1 0.49 2q35 carbamoyl-phosphate synthase 1, mitochondrial TESC 0.478 12q24.22 tescalcin INHA 0.465 2q35 inhibin, alpha S100P 0.461 4p16 S100 calcium binding protein P VPS37A 0.447 8p22 vacuolar protein sorting 37 homolog A (S. cerevisiae) SLC16A14 0.447 2q36.3 solute carrier family 16, member 14 PPARGC1A 0.443 4p15.1 peroxisome proliferator-activated receptor gamma, coactivator 1 alpha SIK1 0.435 21q22.3 salt-inducible kinase 1 IRS2 0.434 13q34 insulin receptor substrate 2 RND1 0.433 12q12 Rho family GTPase 1 HGD 0.433 3q13.33 homogentisate 1,2-dioxygenase PTP4A1 0.432 6q12 protein tyrosine phosphatase type IVA, member 1 C8orf4 0.428 8p11.2 chromosome 8 open reading frame 4 DDC 0.427 7p12.2 dopa decarboxylase (aromatic L-amino acid decarboxylase) TACC2 0.427 10q26 transforming, acidic coiled-coil containing protein 2 MUC13 0.422 3q21.2 mucin 13, cell surface associated C5 0.412 9q33-q34 complement component 5 NR4A2 0.412 2q22-q23 nuclear receptor subfamily 4, group A, member 2 EYS 0.411 6q12 eyes shut homolog (Drosophila) GPX2 0.406 14q24.1 glutathione peroxidase -
Roles of Twist1 and Twist2 As Molecular Switches During Gene Transcription Hector L
Published online 8 October 2010 Nucleic Acids Research, 2011, Vol. 39, No. 4 1177–1186 doi:10.1093/nar/gkq890 SURVEY AND SUMMARY Redundant or separate entities?—roles of Twist1 and Twist2 as molecular switches during gene transcription Hector L. Franco, Jose´ Casasnovas, Jose´ R. Rodrı´guez-Medina and Carmen L. Cadilla* Human Molecular Genetics Lab, Department of Biochemistry, School of Medicine University of Puerto Rico, Medical Sciences Campus, PO Box 365067, San Juan, PR 00936, USA Received December 28, 2009; Revised September 8, 2010; Accepted September 19, 2010 ABSTRACT INTRODUCTION Twist1 and Twist2 are highly conserved members of The basic helix–loop–helix (bHLH) family of proteins the Twist subfamily of bHLH proteins responsible comprises a series of transcription factors that act as for the transcriptional regulation of the develop- master regulators on different tissues. Their complex regu- mental programs in mesenchymal cell lineages. latory functions make them fine-tuned machinery for controlling cell fate at the early stages of embryogenesis. The regulation of such processes requires that The hallmark for DNA binding of bHLH transcription Twist1 and Twist2 function as molecular switches factors is the formation of a bipartite DNA-binding to activate and repress target genes by employing domain created when two of these factors form homo or several direct and indirect mechanisms. Modes heterodimer complexes through their HLH motifs of action by these proteins include direct DNA allowing the basic stretch of amino acids to contact the binding to conserved E-box sequences and re- DNA. This DNA-binding domain is able to recognize cis cruitment of coactivators or repressors, seques- regulatory elements containing the consensus sequence tration of E-protein modulators, and interruption 50-NCANNTGN-30 (termed E-box). -
Supplementary Materials
Supplementary Materials + - NUMB E2F2 PCBP2 CDKN1B MTOR AKT3 HOXA9 HNRNPA1 HNRNPA2B1 HNRNPA2B1 HNRNPK HNRNPA3 PCBP2 AICDA FLT3 SLAMF1 BIC CD34 TAL1 SPI1 GATA1 CD48 PIK3CG RUNX1 PIK3CD SLAMF1 CDKN2B CDKN2A CD34 RUNX1 E2F3 KMT2A RUNX1 T MIXL1 +++ +++ ++++ ++++ +++ 0 0 0 0 hematopoietic potential H1 H1 PB7 PB6 PB6 PB6.1 PB6.1 PB12.1 PB12.1 Figure S1. Unsupervised hierarchical clustering of hPSC-derived EBs according to the mRNA expression of hematopoietic lineage genes (microarray analysis). Hematopoietic-competent cells (H1, PB6.1, PB7) were separated from hematopoietic-deficient ones (PB6, PB12.1). In this experiment, all hPSCs were tested in duplicate, except PB7. Genes under-expressed or over-expressed in blood-deficient hPSCs are indicated in blue and red respectively (related to Table S1). 1 C) Mesoderm B) Endoderm + - KDR HAND1 GATA6 MEF2C DKK1 MSX1 GATA4 WNT3A GATA4 COL2A1 HNF1B ZFPM2 A) Ectoderm GATA4 GATA4 GSC GATA4 T ISL1 NCAM1 FOXH1 NCAM1 MESP1 CER1 WNT3A MIXL1 GATA4 PAX6 CDX2 T PAX6 SOX17 HBB NES GATA6 WT1 SOX1 FN1 ACTC1 ZIC1 FOXA2 MYF5 ZIC1 CXCR4 TBX5 PAX6 NCAM1 TBX20 PAX6 KRT18 DDX4 TUBB3 EPCAM TBX5 SOX2 KRT18 NKX2-5 NES AFP COL1A1 +++ +++ 0 0 0 0 ++++ +++ ++++ +++ +++ ++++ +++ ++++ 0 0 0 0 +++ +++ ++++ +++ ++++ 0 0 0 0 hematopoietic potential H1 H1 H1 H1 H1 H1 PB6 PB6 PB7 PB7 PB6 PB6 PB7 PB6 PB6 PB6.1 PB6.1 PB6.1 PB6.1 PB6.1 PB6.1 PB12.1 PB12.1 PB12.1 PB12.1 PB12.1 PB12.1 Figure S2. Unsupervised hierarchical clustering of hPSC-derived EBs according to the mRNA expression of germ layer differentiation genes (microarray analysis) Selected ectoderm (A), endoderm (B) and mesoderm (C) related genes differentially expressed between hematopoietic-competent (H1, PB6.1, PB7) and -deficient cells (PB6, PB12.1) are shown (related to Table S1). -
Bioinformatic Evaluation of Transcriptional Regulation of WNT Pathway Genes with Reference to Diabetic Nephropathy
Bioinformatic evaluation of transcriptional regulation of WNT pathway genes with reference to diabetic nephropathy McKay, G. J., Kavanagh, D. H., Crean, J. K., & Maxwell, A. P. (2015). Bioinformatic evaluation of transcriptional regulation of WNT pathway genes with reference to diabetic nephropathy. Journal of Diabetes Research, [608691]. https://doi.org/10.1155/2016/7684038 Published in: Journal of Diabetes Research Document Version: Publisher's PDF, also known as Version of record Queen's University Belfast - Research Portal: Link to publication record in Queen's University Belfast Research Portal Publisher rights Copyright © 2015 Gareth J. McKay 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. General rights Copyright for the publications made accessible via the Queen's University Belfast Research Portal is retained by the author(s) and / or other copyright owners and it is a condition of accessing these publications that users recognise and abide by the legal requirements associated with these rights. Take down policy The Research Portal is Queen's institutional repository that provides access to Queen's research output. Every effort has been made to ensure that content in the Research Portal does not infringe any person's rights, or applicable UK laws. If you discover content in the Research Portal that you believe breaches copyright or violates any law, please contact [email protected]. Download date:27. Sep. 2021 Hindawi Publishing Corporation Journal of Diabetes Research Article ID 608691 Research Article Bioinformatic Evaluation of Transcriptional Regulation of WNT Pathway Genes with reference to Diabetic Nephropathy Gareth J. -
Supplementary Data
Progressive Disease Signature Upregulated probes with progressive disease U133Plus2 ID Gene Symbol Gene Name 239673_at NR3C2 nuclear receptor subfamily 3, group C, member 2 228994_at CCDC24 coiled-coil domain containing 24 1562245_a_at ZNF578 zinc finger protein 578 234224_at PTPRG protein tyrosine phosphatase, receptor type, G 219173_at NA NA 218613_at PSD3 pleckstrin and Sec7 domain containing 3 236167_at TNS3 tensin 3 1562244_at ZNF578 zinc finger protein 578 221909_at RNFT2 ring finger protein, transmembrane 2 1552732_at ABRA actin-binding Rho activating protein 59375_at MYO15B myosin XVB pseudogene 203633_at CPT1A carnitine palmitoyltransferase 1A (liver) 1563120_at NA NA 1560098_at AKR1C2 aldo-keto reductase family 1, member C2 (dihydrodiol dehydrogenase 2; bile acid binding pro 238576_at NA NA 202283_at SERPINF1 serpin peptidase inhibitor, clade F (alpha-2 antiplasmin, pigment epithelium derived factor), m 214248_s_at TRIM2 tripartite motif-containing 2 204766_s_at NUDT1 nudix (nucleoside diphosphate linked moiety X)-type motif 1 242308_at MCOLN3 mucolipin 3 1569154_a_at NA NA 228171_s_at PLEKHG4 pleckstrin homology domain containing, family G (with RhoGef domain) member 4 1552587_at CNBD1 cyclic nucleotide binding domain containing 1 220705_s_at ADAMTS7 ADAM metallopeptidase with thrombospondin type 1 motif, 7 232332_at RP13-347D8.3 KIAA1210 protein 1553618_at TRIM43 tripartite motif-containing 43 209369_at ANXA3 annexin A3 243143_at FAM24A family with sequence similarity 24, member A 234742_at SIRPG signal-regulatory protein gamma