NR0B1 Supporting Information Biorxiv
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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. -
Systematic Comparison of Sea Urchin and Sea Star Developmental Gene Regulatory Networks Explains How Novelty Is Incorporated in Early Development
ARTICLE https://doi.org/10.1038/s41467-020-20023-4 OPEN Systematic comparison of sea urchin and sea star developmental gene regulatory networks explains how novelty is incorporated in early development Gregory A. Cary 1,3,5, Brenna S. McCauley1,4,5, Olga Zueva1, Joseph Pattinato1, William Longabaugh2 & ✉ Veronica F. Hinman 1 1234567890():,; The extensive array of morphological diversity among animal taxa represents the product of millions of years of evolution. Morphology is the output of development, therefore phenotypic evolution arises from changes to the topology of the gene regulatory networks (GRNs) that control the highly coordinated process of embryogenesis. A particular challenge in under- standing the origins of animal diversity lies in determining how GRNs incorporate novelty while preserving the overall stability of the network, and hence, embryonic viability. Here we assemble a comprehensive GRN for endomesoderm specification in the sea star from zygote through gastrulation that corresponds to the GRN for sea urchin development of equivalent territories and stages. Comparison of the GRNs identifies how novelty is incorporated in early development. We show how the GRN is resilient to the introduction of a transcription factor, pmar1, the inclusion of which leads to a switch between two stable modes of Delta-Notch signaling. Signaling pathways can function in multiple modes and we propose that GRN changes that lead to switches between modes may be a common evolutionary mechanism for changes in embryogenesis. Our data additionally proposes a model in which evolutionarily conserved network motifs, or kernels, may function throughout development to stabilize these signaling transitions. 1 Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA 15213, USA. -
Table 2. Significant
Table 2. Significant (Q < 0.05 and |d | > 0.5) transcripts from the meta-analysis Gene Chr Mb Gene Name Affy ProbeSet cDNA_IDs d HAP/LAP d HAP/LAP d d IS Average d Ztest P values Q-value Symbol ID (study #5) 1 2 STS B2m 2 122 beta-2 microglobulin 1452428_a_at AI848245 1.75334941 4 3.2 4 3.2316485 1.07398E-09 5.69E-08 Man2b1 8 84.4 mannosidase 2, alpha B1 1416340_a_at H4049B01 3.75722111 3.87309653 2.1 1.6 2.84852656 5.32443E-07 1.58E-05 1110032A03Rik 9 50.9 RIKEN cDNA 1110032A03 gene 1417211_a_at H4035E05 4 1.66015788 4 1.7 2.82772795 2.94266E-05 0.000527 NA 9 48.5 --- 1456111_at 3.43701477 1.85785922 4 2 2.8237185 9.97969E-08 3.48E-06 Scn4b 9 45.3 Sodium channel, type IV, beta 1434008_at AI844796 3.79536664 1.63774235 3.3 2.3 2.75319499 1.48057E-08 6.21E-07 polypeptide Gadd45gip1 8 84.1 RIKEN cDNA 2310040G17 gene 1417619_at 4 3.38875643 1.4 2 2.69163229 8.84279E-06 0.0001904 BC056474 15 12.1 Mus musculus cDNA clone 1424117_at H3030A06 3.95752801 2.42838452 1.9 2.2 2.62132809 1.3344E-08 5.66E-07 MGC:67360 IMAGE:6823629, complete cds NA 4 153 guanine nucleotide binding protein, 1454696_at -3.46081884 -4 -1.3 -1.6 -2.6026947 8.58458E-05 0.0012617 beta 1 Gnb1 4 153 guanine nucleotide binding protein, 1417432_a_at H3094D02 -3.13334396 -4 -1.6 -1.7 -2.5946297 1.04542E-05 0.0002202 beta 1 Gadd45gip1 8 84.1 RAD23a homolog (S. -
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. -
Transcription Profiles of Age-At-Maturity-Associated Genes Suggest Cell Fate Commitment Regulation As a Key Factor in the Atlant
INVESTIGATION Transcription Profiles of Age-at-Maturity- Associated Genes Suggest Cell Fate Commitment Regulation as a Key Factor in the Atlantic Salmon Maturation Process Johanna Kurko,*,† Paul V. Debes,*,† Andrew H. House,*,† Tutku Aykanat,*,† Jaakko Erkinaro,‡ and Craig R. Primmer*,†,1 *Organismal and Evolutionary Biology Research Programme, University of Helsinki, Helsinki, Finland, 00014, †Institute of Biotechnology, University of Helsinki, Helsinki, Finland, 00014, and ‡Natural Resources Institute Finland (Luke), Oulu, Finland, 90014 ORCID IDs: 0000-0002-4598-116X (J.K.); 0000-0003-4491-9564 (P.V.D.); 0000-0001-8705-0358 (A.H.H.); 0000-0002-4825-0231 (T.A.); 0000-0002-7843-0364 (J.E.); 0000-0002-3687-8435 (C.R.P.) ABSTRACT Despite recent taxonomic diversification in studies linking genotype with phenotype, KEYWORDS follow-up studies aimed at understanding the molecular processes of such genotype-phenotype Atlantic salmon associations remain rare. The age at which an individual reaches sexual maturity is an important fitness maturation trait in many wild species. However, the molecular mechanisms regulating maturation timing process processes remain obscure. A recent genome-wide association study in Atlantic salmon (Salmo salar) vgll3 identified large-effect age-at-maturity-associated chromosomal regions including genes vgll3, akap11 mRNA and six6, which have roles in adipogenesis, spermatogenesis and the hypothalamic-pituitary-gonadal expression (HPG) axis, respectively. Here, we determine expression patterns of these genes during salmon de- cell fate velopment and their potential molecular partners and pathways. Using Nanostring transcription pro- regulation filing technology, we show development- and tissue-specific mRNA expression patterns for vgll3, akap11 and six6. Correlated expression levels of vgll3 and akap11, which have adjacent chromosomal location, suggests they may have shared regulation. -
SOX11 Interactome Analysis: Implication in Transcriptional Control and Neurogenesis
SOX11 interactome analysis: Implication in transcriptional control and neurogenesis Dissertation der Mathematisch-Naturwissenschaftlichen Fakultät der Eberhard Karls Universität Tübingen zur Erlangung des Grades eines Doktors der Naturwissenschaften (Dr. rer. nat.) vorgelegt von Birgit Heim, geb.Kick aus Augsburg Tübingen 2014 Gedruckt mit Genehmigung der Mathematisch-Naturwissenschaftlichen Fakultät der Eberhard Karls Universität Tübingen. Tag der mündlichen Qualifikation: 12.02.2015 Dekan: Prof. Dr. Wolfgang Rosenstiel 1. Berichterstatter: Prof. Dr. Olaf Rieß 2. Berichterstatter: Prof. Dr. Marius Ueffing Für meine Familie TABLE OF CONTENTS Table of contents Summary ................................................................................................................ 5 Zusammenfassung ............................................................................................... 7 1. Introduction ...................................................................................... 9 1.1. Adult neurogenesis .................................................................................... 9 1.1.1. Adult neural stem cells and neuronal precursor cells ............................ 9 1.1.2. Neurogenic niches .............................................................................. 11 1.1.3. Regulation of adult neurogenesis ........................................................ 12 1.1.3.1. Extrinsic mechanisms .................................................................. 12 1.1.3.2. Intrinsic mechanisms .................................................................. -
1 Supporting Information for a Microrna Network Regulates
Supporting Information for A microRNA Network Regulates Expression and Biosynthesis of CFTR and CFTR-ΔF508 Shyam Ramachandrana,b, Philip H. Karpc, Peng Jiangc, Lynda S. Ostedgaardc, Amy E. Walza, John T. Fishere, Shaf Keshavjeeh, Kim A. Lennoxi, Ashley M. Jacobii, Scott D. Rosei, Mark A. Behlkei, Michael J. Welshb,c,d,g, Yi Xingb,c,f, Paul B. McCray Jr.a,b,c Author Affiliations: Department of Pediatricsa, Interdisciplinary Program in Geneticsb, Departments of Internal Medicinec, Molecular Physiology and Biophysicsd, Anatomy and Cell Biologye, Biomedical Engineeringf, Howard Hughes Medical Instituteg, Carver College of Medicine, University of Iowa, Iowa City, IA-52242 Division of Thoracic Surgeryh, Toronto General Hospital, University Health Network, University of Toronto, Toronto, Canada-M5G 2C4 Integrated DNA Technologiesi, Coralville, IA-52241 To whom correspondence should be addressed: Email: [email protected] (M.J.W.); yi- [email protected] (Y.X.); Email: [email protected] (P.B.M.) This PDF file includes: Materials and Methods References Fig. S1. miR-138 regulates SIN3A in a dose-dependent and site-specific manner. Fig. S2. miR-138 regulates endogenous SIN3A protein expression. Fig. S3. miR-138 regulates endogenous CFTR protein expression in Calu-3 cells. Fig. S4. miR-138 regulates endogenous CFTR protein expression in primary human airway epithelia. Fig. S5. miR-138 regulates CFTR expression in HeLa cells. Fig. S6. miR-138 regulates CFTR expression in HEK293T cells. Fig. S7. HeLa cells exhibit CFTR channel activity. Fig. S8. miR-138 improves CFTR processing. Fig. S9. miR-138 improves CFTR-ΔF508 processing. Fig. S10. SIN3A inhibition yields partial rescue of Cl- transport in CF epithelia. -
Analysis of the Indacaterol-Regulated Transcriptome in Human Airway
Supplemental material to this article can be found at: http://jpet.aspetjournals.org/content/suppl/2018/04/13/jpet.118.249292.DC1 1521-0103/366/1/220–236$35.00 https://doi.org/10.1124/jpet.118.249292 THE JOURNAL OF PHARMACOLOGY AND EXPERIMENTAL THERAPEUTICS J Pharmacol Exp Ther 366:220–236, July 2018 Copyright ª 2018 by The American Society for Pharmacology and Experimental Therapeutics Analysis of the Indacaterol-Regulated Transcriptome in Human Airway Epithelial Cells Implicates Gene Expression Changes in the s Adverse and Therapeutic Effects of b2-Adrenoceptor Agonists Dong Yan, Omar Hamed, Taruna Joshi,1 Mahmoud M. Mostafa, Kyla C. Jamieson, Radhika Joshi, Robert Newton, and Mark A. Giembycz Departments of Physiology and Pharmacology (D.Y., O.H., T.J., K.C.J., R.J., M.A.G.) and Cell Biology and Anatomy (M.M.M., R.N.), Snyder Institute for Chronic Diseases, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada Received March 22, 2018; accepted April 11, 2018 Downloaded from ABSTRACT The contribution of gene expression changes to the adverse and activity, and positive regulation of neutrophil chemotaxis. The therapeutic effects of b2-adrenoceptor agonists in asthma was general enriched GO term extracellular space was also associ- investigated using human airway epithelial cells as a therapeu- ated with indacaterol-induced genes, and many of those, in- tically relevant target. Operational model-fitting established that cluding CRISPLD2, DMBT1, GAS1, and SOCS3, have putative jpet.aspetjournals.org the long-acting b2-adrenoceptor agonists (LABA) indacaterol, anti-inflammatory, antibacterial, and/or antiviral activity. Numer- salmeterol, formoterol, and picumeterol were full agonists on ous indacaterol-regulated genes were also induced or repressed BEAS-2B cells transfected with a cAMP-response element in BEAS-2B cells and human primary bronchial epithelial cells by reporter but differed in efficacy (indacaterol $ formoterol . -
Supplemental Figure 1. Recombination Pattern of Six3-Cre in the Adult Retina and Brain
Supplemental Figure 1. Recombination pattern of Six3-cre in the adult retina and brain. The conditional reporter line, R26R, commences expression of β-galactosidase upon Cre-mediated recombination. The recombination pattern of the Six3-cre transgene in the retina on P21 reveals widespread recombination in all layers (A-C). At the retinal margin, areas devoid of recombination are apparent, as depicted by gaps in the X-gal staining pattern in this region (C, arrowheads). Co- immunolabeling using anti-Isl1 and anti-β-galactosidase reveals that most Isll+ cells in the INL co-localize with Six3-cre's lineage (D-F), although several Isl1+ cells are devoid of detectable reporter expression (D-F, arrowheads). At the retinal margin, many more Isl1+ cells devoid of detectable reporter expression are encountered (G-I, arrowheads). The recombination pattern of Six3-cre in the brain of P21 animals reveals widespread recombination in the hypothalamus, septum and striatum (J). Scale bar equals 50 µm in B (applies to B-C), in F (applies to D-F), in I (applies to G-I), and 1mm in J. Supplemental Figure 2. Additional cell marker expression in the Isl1-null retina. Isl1-null retinas display a 71% reduction in the expression of the RGC marker Pou4f1 (B) compared to control (A; average number of Pou4f1+ cells ± standard deviation: controls: 35 ± 7, n=3; Isl1-nulls: 10 ± 2, n=3, p<0.01, Student's t test). A slight 17% increase in the numbers of the horizontal cell marker, Calbindin-28K, in Isl1-null retinas is observed, although this change is not significant (compare C to D; average number of Calbindin-28K+ cells ± standard deviation: controls: 10 ± 2, n=4; Isl1-nulls: 12 ± 1, n=4, p=0.05, Student's t test). -
Nuclear PTEN Safeguards Pre-Mrna Splicing to Link Golgi Apparatus for Its Tumor Suppressive Role
ARTICLE DOI: 10.1038/s41467-018-04760-1 OPEN Nuclear PTEN safeguards pre-mRNA splicing to link Golgi apparatus for its tumor suppressive role Shao-Ming Shen1, Yan Ji2, Cheng Zhang1, Shuang-Shu Dong2, Shuo Yang1, Zhong Xiong1, Meng-Kai Ge1, Yun Yu1, Li Xia1, Meng Guo1, Jin-Ke Cheng3, Jun-Ling Liu1,3, Jian-Xiu Yu1,3 & Guo-Qiang Chen1 Dysregulation of pre-mRNA alternative splicing (AS) is closely associated with cancers. However, the relationships between the AS and classic oncogenes/tumor suppressors are 1234567890():,; largely unknown. Here we show that the deletion of tumor suppressor PTEN alters pre-mRNA splicing in a phosphatase-independent manner, and identify 262 PTEN-regulated AS events in 293T cells by RNA sequencing, which are associated with significant worse outcome of cancer patients. Based on these findings, we report that nuclear PTEN interacts with the splicing machinery, spliceosome, to regulate its assembly and pre-mRNA splicing. We also identify a new exon 2b in GOLGA2 transcript and the exon exclusion contributes to PTEN knockdown-induced tumorigenesis by promoting dramatic Golgi extension and secretion, and PTEN depletion significantly sensitizes cancer cells to secretion inhibitors brefeldin A and golgicide A. Our results suggest that Golgi secretion inhibitors alone or in combination with PI3K/Akt kinase inhibitors may be therapeutically useful for PTEN-deficient cancers. 1 Department of Pathophysiology, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Shanghai Jiao Tong University School of Medicine (SJTU-SM), Shanghai 200025, China. 2 Institute of Health Sciences, Shanghai Institutes for Biological Sciences of Chinese Academy of Sciences and SJTU-SM, Shanghai 200025, China. -
Appendix 2. Significantly Differentially Regulated Genes in Term Compared with Second Trimester Amniotic Fluid Supernatant
Appendix 2. Significantly Differentially Regulated Genes in Term Compared With Second Trimester Amniotic Fluid Supernatant Fold Change in term vs second trimester Amniotic Affymetrix Duplicate Fluid Probe ID probes Symbol Entrez Gene Name 1019.9 217059_at D MUC7 mucin 7, secreted 424.5 211735_x_at D SFTPC surfactant protein C 416.2 206835_at STATH statherin 363.4 214387_x_at D SFTPC surfactant protein C 295.5 205982_x_at D SFTPC surfactant protein C 288.7 1553454_at RPTN repetin solute carrier family 34 (sodium 251.3 204124_at SLC34A2 phosphate), member 2 238.9 206786_at HTN3 histatin 3 161.5 220191_at GKN1 gastrokine 1 152.7 223678_s_at D SFTPA2 surfactant protein A2 130.9 207430_s_at D MSMB microseminoprotein, beta- 99.0 214199_at SFTPD surfactant protein D major histocompatibility complex, class II, 96.5 210982_s_at D HLA-DRA DR alpha 96.5 221133_s_at D CLDN18 claudin 18 94.4 238222_at GKN2 gastrokine 2 93.7 1557961_s_at D LOC100127983 uncharacterized LOC100127983 93.1 229584_at LRRK2 leucine-rich repeat kinase 2 HOXD cluster antisense RNA 1 (non- 88.6 242042_s_at D HOXD-AS1 protein coding) 86.0 205569_at LAMP3 lysosomal-associated membrane protein 3 85.4 232698_at BPIFB2 BPI fold containing family B, member 2 84.4 205979_at SCGB2A1 secretoglobin, family 2A, member 1 84.3 230469_at RTKN2 rhotekin 2 82.2 204130_at HSD11B2 hydroxysteroid (11-beta) dehydrogenase 2 81.9 222242_s_at KLK5 kallikrein-related peptidase 5 77.0 237281_at AKAP14 A kinase (PRKA) anchor protein 14 76.7 1553602_at MUCL1 mucin-like 1 76.3 216359_at D MUC7 mucin 7, -
Transcriptomic Analysis of Short-Fruit 1 (Sf1)
www.nature.com/scientificreports OPEN Transcriptomic analysis of short- fruit 1 (sf1) reveals new insights into the variation of fruit-related Received: 15 November 2016 Accepted: 20 April 2017 traits in Cucumis sativus Published: xx xx xxxx Lina Wang, Chenxing Cao, Shuangshuang Zheng, Haiyang Zhang, Panjing Liu, Qian Ge, Jinrui Li & Zhonghai Ren Fruit size is an important quality trait in different market classes ofCucumis sativus L., an economically important vegetable cultivated worldwide, but the genetic and molecular mechanisms that control fruit size are largely unknown. In this study, we isolated a natural cucumber mutant, short fruit 1 (sf1), caused by a single recessive Mendelian factor, from the North China-type inbred line CNS2. In addition to significantly decreased fruit length, other fruit-related phenotypic variations were also observed in sf1 compared to the wild-type (WT) phenotype, indicating that sf1 might have pleiotropic effects. Microscopic imaging showed that fruit cell size in sf1 was much larger than that in WT, suggesting that the short fruit phenotype in sf1 is caused by decreased cell number. Fine mapping revealed that sf1 was localized to a 174.3 kb region on chromosome 6. Similarly, SNP association analysis of bulked segregant RNA-Seq data showed increased SNP frequency in the same region of chromosome 6. In addition, transcriptomic analysis revealed that sf1 might control fruit length through the fine-tuning of cytokinin and auxin signalling, gibberellin biosynthesis and signal transduction in cucumber fruits. Overall, our results provide important information for further study of fruit length and other fruit-related features in cucumber. Cucumber (Cucumis sativus L., 2n = 14), a member of the family Cucurbitaceae, is one of the most economically important vegetable crops cultivated throughout the world.