DOCSLIB.ORG

Immunity Resolution of Inflammation and Airway Diversity in Expression

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text

Load more

Downloaded from http://www.jimmunol.org/ by guest on September 25, 2021 is online at: average * in Mouse γ The Journal of Immunology published online 1 August 2012 from submission to initial decision 4 weeks from acceptance to publication Emmanuel L. Gautier, Andrew Chow, Rainer Spanbroek, Genevieve Marcelin, Melanie Greter, Claudia Jakubzick, Milena Bogunovic, Marylene Leboeuf, Nico van Rooijen, Andreas J. Habenicht, Miriam Merad and Gwendalyn J. Randolph http://www.jimmunol.org/content/early/2012/08/01/jimmun ol.1200495 Systemic Analysis of PPAR Macrophage Populations Reveals Marked Diversity in Expression with Critical Roles in Resolution of Inflammation and Airway Immunity J Immunol Submit online. Every submission reviewed by practicing scientists ? is published twice each month by Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts http://jimmunol.org/subscription http://www.jimmunol.org/content/suppl/2012/08/01/jimmunol.120049 5.DC1 Information about subscribing to The JI No Triage! Fast Publication! Rapid Reviews! 30 days* Why • • • Material Permissions Email Alerts Subscription Supplementary The Journal of Immunology The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2012 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. This information is current as of September 25, 2021. Published August 1, 2012, doi:10.4049/jimmunol.1200495 The Journal of Immunology Systemic Analysis of PPARg in Mouse Macrophage Populations Reveals Marked Diversity in Expression with Critical Roles in Resolution of Inflammation and Airway Immunity Emmanuel L. Gautier,*,†,‡ Andrew Chow,†,x Rainer Spanbroek,{ Genevieve Marcelin,‖ Melanie Greter,†,x Claudia Jakubzick,*,†,1 Milena Bogunovic,†,x Marylene Leboeuf,†,x Nico van Rooijen,# Andreas J. Habenicht,{ Miriam Merad,†,x and Gwendalyn J. Randolph*,†,‡ Although peroxisome proliferator-activated receptor g (PPARg) has anti-inflammatory actions in macrophages, which macro- Downloaded from phage populations express PPARg in vivo and how it regulates tissue homeostasis in the steady state and during inflammation remains unclear. We now show that lung and spleen macrophages selectively expressed PPARg among resting tissue macrophages. In addition, Ly-6Chi monocytes recruited to an inflammatory site induced PPARg as they differentiated to macrophages. When PPARg was absent in Ly-6Chi–derived inflammatory macrophages, initiation of the inflammatory response was unaffected, but full resolution of inflammation failed, leading to chronic leukocyte recruitment. Conversely, PPARg activation favored resolution of inflammation in a macrophage PPARg-dependent manner. In the steady state, PPARg deficiency in red pulp macrophages did http://www.jimmunol.org/ not induce overt inflammation in the spleen. By contrast, PPARg deletion in lung macrophages induced mild pulmonary inflam- mation at the steady state and surprisingly precipitated mortality upon infection with Streptococcus pneumoniae. This accelerated mortality was associated with impaired bacterial clearance and inability to sustain macrophages locally. Overall, we uncovered critical roles for macrophage PPARg in promoting resolution of inflammation and maintaining functionality in lung macrophages where it plays a pivotal role in supporting pulmonary host defense. In addition, this work identifies specific macrophage pop- ulations as potential targets for the anti-inflammatory actions of PPARg agonists. The Journal of Immunology, 2012, 189: 000– 000. by guest on September 25, 2021 eroxisome proliferator-activated receptor g (PPARg)is nedione family, the latter being used clinically to improve insulin a ligand-controlled transcription factor of the nuclear re- sensitivity in type 2 diabetic patients (3). P ceptor family capable of regulating gene expression by The anti-inflammatory role of PPARg came to the forefront in transactivation or transrepression (1). First discovered as the master the late 1990s when 15-deoxy-d-12,14-PG J2 (15d-PGJ2) and thia- regulator of the genetic program supporting adipocyte differenti- zolidinediones were shown to dampen macrophage activation ation, PPARg is involved in the regulation of a number of phys- in vitro by activating PPARg (4, 5). Since then, the anti-inflammatory iological processes such as the response to insulin, cell proliferation, role of PPARg agonists has been extensively documented in vitro cellular lipid metabolism, and inflammation (2). Thus, PPARg and in vivo (1, 6). Indeed, PPARg agonists suppress dextran so- activation is an attractive therapeutic target in a variety of diseases dium sulfate-induced colitis (7), obesity-induced insulin resistance such as type 2 diabetes, cancer, atherosclerosis, and immune (8), and the progression of atherosclerosis (9). By contrast, dele- disorders. Activation of PPARg can be achieved by natural fatty tion of PPARg in macrophages exacerbates the development of acid derivatives as well as synthetic ligands from the thiazolidi- atherosclerosis (10, 11), colitis (12), and obesity-induced insulin *Department of Developmental and Regenerative Biology, Mount Sinai School of (10POST4160140), and A.C. is funded by a fellowship from the National Institutes Medicine, New York, NY 10029; †Immunology Institute, Mount Sinai School of of Health, National Heart, Lung, and Blood Institute 5F30HL099028-02. Medicine, New York, NY 10029; ‡Department of Pathology and Immunology, Wash- x The datasets presented in this article have been submitted to the National Center for ington University, St. Louis, MO 63110; Department of Oncological Sciences, { Biotechnology Information/Gene Expression Omnibus (http://www.ncbi.nlm.nih. Mount Sinai School of Medicine, New York, NY 10029; Institute for Vascular gov/geo/) under accession numbers GSE15907 and GSE32034. Medicine, Friedrich Schiller University of Jena, Jena University Hospital, 07743 Jena, Germany; ‖Albert Einstein College of Medicine, Bronx, NY 10461; Address correspondence and reprint requests to Dr. Emmanuel L. Gautier and and #Department of Molecular Cell Biology, Free University Medical Center, 1007 Dr. Gwendalyn J. Randolph, Department of Pathology and Immunology, Washington Amsterdam, The Netherlands University, 660 South Euclid Avenue, Campus Box 8118, St. Louis, MO 63110. E-mail addresses: [email protected] (E.L.G.) and [email protected]. 1Current address: Integrated Department of Immunology, National Jewish Health, edu (G.J.R.) University of Colorado, Denver, CO. The online version of this article contains supplemental material. Received for publication February 9, 2012. Accepted for publication July 4, 2012. Abbreviations used in this article: DC, dendritic cell; 15d-PGJ , 15-deoxy-d-12,14-PG This work was supported by National Institutes of Health Grants AI061741 and 2 J2; FABP4, fatty acid binding protein 4; PAP, pulmonary alveolar proteinosis; PPAR, AI049653 and American Heart Association Established Investigator Award peroxisome proliferator-activated receptor. 0740052 (to G.J.R.), National Institutes of Health Grant HL086899 (to M.M.), Deut- sche Forschungsgemeinschaft Project Grant SP71314-1 (to R.S.), and Deutsche Ó Forschungsgemeinschaft Project Grants Ha 1083/16-1 and Ha 1083/15-1 (to A.J.H.). Copyright 2012 by The American Association of Immunologists, Inc. 0022-1767/12/$16.00 E.L.G. is supported by a fellowship from the American Heart Association www.jimmunol.org/cgi/doi/10.4049/jimmunol.1200495 2PPARg CONTROLS SPECIFIC MACROPHAGE POPULATIONS resistance (13). On the basis of these studies, a model emerges subsets were CD11c+MHC II+ cells that differentially expressed CD4 + + 2 2 2 + wherein macrophages are universally central targets of PPARg (CD11b CD4 CD8 ) or CD8 (CD11b CD4 CD8 ) (21). RNA was pre- modulation. However, it is not known whether all monocyte/ pared from sorted populations from C57BL/6J mice after sorting directly into TRIzol reagent, amplified, and hybridized on the Affymetrix Mouse macrophage populations express PPARg or rely on its activation Gene 1.0 ST. For data analysis using ImmGen datasets, raw data for all to maintain homeostasis or to carry out their functions in different populations were normalized using the robust multiarray averaging algo- organs during inflammation. Ultimately, the design and develop- rithm. Extensive quality control documents are available on the Immgen ment of therapeutic strategies based on the use of PPARg agonists Web site. All datasets have been deposited at the National Center for Biotechnology Information/Gene Expression Omnibus under accession to combat inflammatory diseases would benefit from the identifi- number GSE15907 (http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc= cation of the specific macrophage populations potentially respon- GSE15907). Microarrays on blood monocytes treated with a PPARg ag- sive to these agonists. onist were performed as previously described (15) using Affymetrix GeneChip In this context, we decided to profile the expression of PPARg 430 2.0 arrays. Corresponding datasets have been deposited at National in a range of macrophage populations extracted from different Center for Biotechnology Information/Gene Expression Omnibus under accession number GSE32034 (http://www.ncbi.nlm.nih.gov/geo/query/acc. organs, delineate its preferential site of expression, and examine cgi?acc=GSE32034).
Recommended publications
  • Isyte: Integrated Systems Tool for Eye Gene Discovery

    Isyte: Integrated Systems Tool for Eye Gene Discovery

    Lens iSyTE: Integrated Systems Tool for Eye Gene Discovery Salil A. Lachke,1,2,3,4 Joshua W. K. Ho,1,4,5 Gregory V. Kryukov,1,4,6 Daniel J. O’Connell,1 Anton Aboukhalil,1,7 Martha L. Bulyk,1,8,9 Peter J. Park,1,5,10 and Richard L. Maas1 PURPOSE. To facilitate the identification of genes associated ther investigation. Extension of this approach to other ocular with cataract and other ocular defects, the authors developed tissue components will facilitate eye disease gene discovery. and validated a computational tool termed iSyTE (integrated (Invest Ophthalmol Vis Sci. 2012;53:1617–1627) DOI: Systems Tool for Eye gene discovery; http://bioinformatics. 10.1167/iovs.11-8839 udel.edu/Research/iSyTE). iSyTE uses a mouse embryonic lens gene expression data set as a bioinformatics filter to select candidate genes from human or mouse genomic regions impli- ven with the advent of high-throughput sequencing, the cated in disease and to prioritize them for further mutational Ediscovery of genes associated with congenital birth defects and functional analyses. such as eye defects remains a challenge. We sought to develop METHODS. Microarray gene expression profiles were obtained a straightforward experimental approach that could facilitate for microdissected embryonic mouse lens at three key devel- the identification of candidate genes for developmental disor- opmental time points in the transition from the embryonic day ders, and, as proof-of-principle, we chose defects involving the (E)10.5 stage of lens placode invagination to E12.5 lens primary ocular lens. Opacification of the lens results in cataract, a leading cause of blindness that affects 77 million persons and fiber cell differentiation.
  • Association Analyses of Known Genetic Variants with Gene

    Association Analyses of Known Genetic Variants with Gene

    ASSOCIATION ANALYSES OF KNOWN GENETIC VARIANTS WITH GENE EXPRESSION IN BRAIN by Viktoriya Strumba A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Bioinformatics) in The University of Michigan 2009 Doctoral Committee: Professor Margit Burmeister, Chair Professor Huda Akil Professor Brian D. Athey Assistant Professor Zhaohui S. Qin Research Statistician Thomas Blackwell To Sam and Valentina Dmitriy and Elizabeth ii ACKNOWLEDGEMENTS I would like to thank my advisor Professor Margit Burmeister, who tirelessly guided me though seemingly impassable corridors of graduate work. Throughout my thesis writing period she provided sound advice, encouragement and inspiration. Leading by example, her enthusiasm and dedication have been instrumental in my path to becoming a better scientist. I also would like to thank my co-advisor Tom Blackwell. His careful prodding always kept me on my toes and looking for answers, which taught me the depth of careful statistical analysis. His diligence and dedication have been irreplaceable in most difficult of projects. I also would like to thank my other committee members: Huda Akil, Brian Athey and Steve Qin as well as David States. You did not make it easy for me, but I thank you for believing and not giving up. Huda’s eloquence in every subject matter she explained have been particularly inspiring, while both Huda’s and Brian’s valuable advice made the completion of this dissertation possible. I would also like to thank all the members of the Burmeister lab, both past and present: Sandra Villafuerte, Kristine Ito, Cindy Schoen, Karen Majczenko, Ellen Schmidt, Randi Burns, Gang Su, Nan Xiang and Ana Progovac.
  • ARMCX3 (NM 177948) Human Untagged Clone – SC124834

    ARMCX3 (NM 177948) Human Untagged Clone – SC124834

    OriGene Technologies, Inc. 9620 Medical Center Drive, Ste 200 Rockville, MD 20850, US Phone: +1-888-267-4436 [email protected] EU: [email protected] CN: [email protected] Product datasheet for SC124834 ARMCX3 (NM_177948) Human Untagged Clone Product data: Product Type: Expression Plasmids Product Name: ARMCX3 (NM_177948) Human Untagged Clone Tag: Tag Free Symbol: ARMCX3 Synonyms: ALEX3; dJ545K15.2; GASP6 Vector: pCMV6-XL4 E. coli Selection: Ampicillin (100 ug/mL) Cell Selection: None Fully Sequenced ORF: >NCBI ORF sequence for NM_177948, the custom clone sequence may differ by one or more nucleotides ATGGGCTACGCCAGGAAAGTAGGCTGGGTGACCGCAGGCCTGGTGATTGGGGCTGGCGCCTGCTATTGCA TTTATAGACTGACTAGGGGAAGAAAACAGAACAAGGAAAAAATGGCTGAGGGTGGATCTGGGGATGTGGA TGATGCTGGGGACTGTTCTGGGGCCAGGTATAATGACTGGTCTGATGATGATGATGACAGCAATGAGAGC AAGAGTATAGTATGGTACCCACCTTGGGCTCGGATTGGGACTGAAGCTGGAACCAGAGCTAGGGCCAGGG CAAGGGCCAGGGCTACCCGGGCACGTCGGGCTGTCCAGAAACGGGCTTCCCCCAATTCAGATGATACCGT TTTGTCCCCTCAAGAGCTACAAAAGGTTCTTTGCTTGGTTGAGATGTCTGAAAAGCCTTATATTCTTGAA GCAGCTTTAATTGCTCTGGGTAACAATGCTGCTTATGCATTTAACAGAGATATTATTCGTGATCTGGGTG GTCTCCCAATTGTCGCAAAGATTCTCAATACTCGGGATCCCATAGTTAAGGAAAAGGCTTTAATTGTCCT GAATAACTTGAGTGTGAATGCTGAAAATCAGCGCAGGCTTAAAGTATACATGAATCAAGTGTGTGATGAC ACAATCACTTCTCGCTTGAACTCATCTGTGCAGCTTGCTGGACTGAGATTGCTTACAAATATGACTGTTA CTAATGAGTATCAGCACATGCTTGCTAATTCCATTTCTGACTTTTTTCGTTTATTTTCAGCGGGAAATGA AGAAACCAAACTTCAGGTTCTGAAACTCCTTTTGAATTTGGCTGAAAATCCAGCCATGACTAGGGAACTG CTCAGGGCCCAAGTACCATCTTCACTGGGCTCCCTCTTTAATAAGAAGGAGAACAAAGAAGTTATTCTTA AACTTCTGGTCATATTTGAGAACATAAATGATAATTTCAAATGGGAAGAAAATGAACCTACTCAGAATCA
  • Activated Peripheral-Blood-Derived Mononuclear Cells

    Activated Peripheral-Blood-Derived Mononuclear Cells

    Transcription factor expression in lipopolysaccharide- activated peripheral-blood-derived mononuclear cells Jared C. Roach*†, Kelly D. Smith*‡, Katie L. Strobe*, Stephanie M. Nissen*, Christian D. Haudenschild§, Daixing Zhou§, Thomas J. Vasicek¶, G. A. Heldʈ, Gustavo A. Stolovitzkyʈ, Leroy E. Hood*†, and Alan Aderem* *Institute for Systems Biology, 1441 North 34th Street, Seattle, WA 98103; ‡Department of Pathology, University of Washington, Seattle, WA 98195; §Illumina, 25861 Industrial Boulevard, Hayward, CA 94545; ¶Medtronic, 710 Medtronic Parkway, Minneapolis, MN 55432; and ʈIBM Computational Biology Center, P.O. Box 218, Yorktown Heights, NY 10598 Contributed by Leroy E. Hood, August 21, 2007 (sent for review January 7, 2007) Transcription factors play a key role in integrating and modulating system. In this model system, we activated peripheral-blood-derived biological information. In this study, we comprehensively measured mononuclear cells, which can be loosely termed ‘‘macrophages,’’ the changing abundances of mRNAs over a time course of activation with lipopolysaccharide (LPS). We focused on the precise mea- of human peripheral-blood-derived mononuclear cells (‘‘macro- surement of mRNA concentrations. There is currently no high- phages’’) with lipopolysaccharide. Global and dynamic analysis of throughput technology that can precisely and sensitively measure all transcription factors in response to a physiological stimulus has yet to mRNAs in a system, although such technologies are likely to be be achieved in a human system, and our efforts significantly available in the near future. To demonstrate the potential utility of advanced this goal. We used multiple global high-throughput tech- such technologies, and to motivate their development and encour- nologies for measuring mRNA levels, including massively parallel age their use, we produced data from a combination of two distinct signature sequencing and GeneChip microarrays.
  • CRISPR Screening of Porcine Sgrna Library Identifies Host Factors

    CRISPR Screening of Porcine Sgrna Library Identifies Host Factors

    ARTICLE https://doi.org/10.1038/s41467-020-18936-1 OPEN CRISPR screening of porcine sgRNA library identifies host factors associated with Japanese encephalitis virus replication Changzhi Zhao1,5, Hailong Liu1,5, Tianhe Xiao1,5, Zichang Wang1, Xiongwei Nie1, Xinyun Li1,2, Ping Qian2,3, Liuxing Qin3, Xiaosong Han1, Jinfu Zhang1, Jinxue Ruan1, Mengjin Zhu1,2, Yi-Liang Miao 1,2, Bo Zuo1,2, ✉ ✉ Kui Yang4, Shengsong Xie 1,2 & Shuhong Zhao 1,2 1234567890():,; Japanese encephalitis virus (JEV) is a mosquito-borne zoonotic flavivirus that causes ence- phalitis and reproductive disorders in mammalian species. However, the host factors critical for its entry, replication, and assembly are poorly understood. Here, we design a porcine genome-scale CRISPR/Cas9 knockout (PigGeCKO) library containing 85,674 single guide RNAs targeting 17,743 protein-coding genes, 11,053 long ncRNAs, and 551 microRNAs. Subsequently, we use the PigGeCKO library to identify key host factors facilitating JEV infection in porcine cells. Several previously unreported genes required for JEV infection are highly enriched post-JEV selection. We conduct follow-up studies to verify the dependency of JEV on these genes, and identify functional contributions for six of the many candidate JEV- related host genes, including EMC3 and CALR. Additionally, we identify that four genes associated with heparan sulfate proteoglycans (HSPGs) metabolism, specifically those responsible for HSPGs sulfurylation, facilitate JEV entry into porcine cells. Thus, beyond our development of the largest CRISPR-based functional genomic screening platform for pig research to date, this study identifies multiple potentially vulnerable targets for the devel- opment of medical and breeding technologies to treat and prevent diseases caused by JEV.
  • Core Transcriptional Regulatory Circuitries in Cancer

    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.
  • Mutations in DCPS and EDC3 in Autosomal Recessive Intellectual

    Mutations in DCPS and EDC3 in Autosomal Recessive Intellectual

    Human Molecular Genetics, 2015, Vol. 24, No. 11 3172–3180 doi: 10.1093/hmg/ddv069 Advance Access Publication Date: 20 February 2015 Original Article Downloaded from ORIGINAL ARTICLE Mutations in DCPS and EDC3 in autosomal recessive intellectual disability indicate a crucial role for mRNA http://hmg.oxfordjournals.org/ decapping in neurodevelopment Iltaf Ahmed1,2,†, Rebecca Buchert3,†, Mi Zhou5,†, Xinfu Jiao5,†, Kirti Mittal1, Taimoor I. Sheikh1, Ute Scheller3, Nasim Vasli1, Muhammad Arshad Rafiq1, 6 1 7 2 M. Qasim Brohi , Anna Mikhailov , Muhammad Ayaz , Attya Bhatti , at Universitaet Erlangen-Nuernberg, Wirtschafts- und Sozialwissenschaftliche Z on August 15, 2016 Heinrich Sticht4, Tanveer Nasr8,9, Melissa T. Carter10, Steffen Uebe3, André Reis3, Muhammad Ayub7,11, Peter John2, Megerditch Kiledjian5,*, John B. Vincent1,12,13,* and Rami Abou Jamra3,* 1Molecular Neuropsychiatry and Development Lab, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, 250 College Street, Toronto, Ontario, Canada M5T 1R8, 2Atta-ur-Rehman School of Applied Biosciences (ASAB), National University of Sciences and Technology (NUST), Islamabad 44000, Pakistan, 3Institute of Human Genetics and 4Bioinformatics, Institute of Biochemistry, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen 91054, Germany, 5Department of Cell Biology and Neuroscience, Rutgers University, Piscataway, NJ 08854, USA, 6Sir Cowasji Jehangir Institute of Psychiatry, Hyderabad, Sindh 71000, Pakistan, 7Lahore Institute of Research and Development,
  • Protein Interaction Network of Alternatively Spliced Isoforms from Brain Links Genetic Risk Factors for Autism

    Protein Interaction Network of Alternatively Spliced Isoforms from Brain Links Genetic Risk Factors for Autism

    ARTICLE Received 24 Aug 2013 | Accepted 14 Mar 2014 | Published 11 Apr 2014 DOI: 10.1038/ncomms4650 OPEN Protein interaction network of alternatively spliced isoforms from brain links genetic risk factors for autism Roser Corominas1,*, Xinping Yang2,3,*, Guan Ning Lin1,*, Shuli Kang1,*, Yun Shen2,3, Lila Ghamsari2,3,w, Martin Broly2,3, Maria Rodriguez2,3, Stanley Tam2,3, Shelly A. Trigg2,3,w, Changyu Fan2,3, Song Yi2,3, Murat Tasan4, Irma Lemmens5, Xingyan Kuang6, Nan Zhao6, Dheeraj Malhotra7, Jacob J. Michaelson7,w, Vladimir Vacic8, Michael A. Calderwood2,3, Frederick P. Roth2,3,4, Jan Tavernier5, Steve Horvath9, Kourosh Salehi-Ashtiani2,3,w, Dmitry Korkin6, Jonathan Sebat7, David E. Hill2,3, Tong Hao2,3, Marc Vidal2,3 & Lilia M. Iakoucheva1 Increased risk for autism spectrum disorders (ASD) is attributed to hundreds of genetic loci. The convergence of ASD variants have been investigated using various approaches, including protein interactions extracted from the published literature. However, these datasets are frequently incomplete, carry biases and are limited to interactions of a single splicing isoform, which may not be expressed in the disease-relevant tissue. Here we introduce a new interactome mapping approach by experimentally identifying interactions between brain-expressed alternatively spliced variants of ASD risk factors. The Autism Spliceform Interaction Network reveals that almost half of the detected interactions and about 30% of the newly identified interacting partners represent contribution from splicing variants, emphasizing the importance of isoform networks. Isoform interactions greatly contribute to establishing direct physical connections between proteins from the de novo autism CNVs. Our findings demonstrate the critical role of spliceform networks for translating genetic knowledge into a better understanding of human diseases.
  • Table 2. Significant

    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.
  • Early B-Cell Factors Are Required for Specifying Multiple Retinal Cell Types and Subtypes from Postmitotic Precursors

    Early B-Cell Factors Are Required for Specifying Multiple Retinal Cell Types and Subtypes from Postmitotic Precursors

    11902 • The Journal of Neuroscience, September 8, 2010 • 30(36):11902–11916 Development/Plasticity/Repair Early B-Cell Factors Are Required for Specifying Multiple Retinal Cell Types and Subtypes from Postmitotic Precursors Kangxin Jin,1,2 Haisong Jiang,1,2 Zeqian Mo,3 and Mengqing Xiang1,2 1Center for Advanced Biotechnology and Medicine and Department of Pediatrics, 2Graduate Program in Molecular Genetics, Microbiology and Immunology, and 3Department of Cell Biology and Neuroscience, University of Medicine and Dentistry of New Jersey-Robert Wood Johnson Medical School, Piscataway, New Jersey 08854 The establishment of functional retinal circuits in the mammalian retina depends critically on the proper generation and assembly of six classes of neurons, five of which consist of two or more subtypes that differ in morphologies, physiological properties, and/or sublaminar positions. How these diverse neuronal types and subtypes arise during retinogenesis still remains largely to be defined at the molecular level. Here we show that all four family members of the early B-cell factor (Ebf) helix-loop-helix transcription factors are similarly expressedduringmouseretinogenesisinseveralneuronaltypesandsubtypesincludingganglion,amacrine,bipolar,andhorizontalcells, and that their expression in ganglion cells depends on the ganglion cell specification factor Brn3b. Misexpressed Ebfs bias retinal precursors toward the fates of non-AII glycinergic amacrine, type 2 OFF-cone bipolar and horizontal cells, whereas a dominant-negative Ebf suppresses the differentiation of these cells as well as ganglion cells. Reducing Ebf1 expression by RNA interference (RNAi) leads to an inhibitory effect similar to that of the dominant-negative Ebf, effectively neutralizes the promotive effect of wild-type Ebf1, but has no impact on the promotive effect of an RNAi-resistant Ebf1.
  • Parallel Molecular Evolution in Pathways, Genes, and Sites in High-Elevation Hummingbirds Revealed by Comparative Transcriptomics

    Parallel Molecular Evolution in Pathways, Genes, and Sites in High-Elevation Hummingbirds Revealed by Comparative Transcriptomics

    GBE Parallel Molecular Evolution in Pathways, Genes, and Sites in High-Elevation Hummingbirds Revealed by Comparative Transcriptomics Marisa C.W. Lim1,*, Christopher C. Witt2, Catherine H. Graham1,3,andLilianaM.Davalos 1,4 1Department of Ecology and Evolution, Stony Brook University 2 Museum of Southwestern Biology and Department of Biology, University of New Mexico Downloaded from https://academic.oup.com/gbe/article-abstract/11/6/1552/5494706 by guest on 08 June 2019 3Swiss Federal Research Institute (WSL), Birmensdorf, Switzerland 4Consortium for Inter-Disciplinary Environmental Research, Stony Brook University *Corresponding author: E-mail: [email protected]. Accepted: May 12, 2019 Data deposition: The raw read data have been deposited in the NCBI Sequence Read Archive under BioProject: PRJNA543673, BioSample: SAMN11774663-SAMN11774674, SRA Study: SRP198856. All scripts used for analyses are available on Dryad: doi:10.5061/dryad.v961mb4. Abstract High-elevation organisms experience shared environmental challenges that include low oxygen availability, cold temperatures, and intense ultraviolet radiation. Consequently, repeated evolution of the same genetic mechanisms may occur across high-elevation taxa. To test this prediction, we investigated the extent to which the same biochemical pathways, genes, or sites were subject to parallel molecular evolution for 12 Andean hummingbird species (family: Trochilidae) representing several independent transitions to high elevation across the phylogeny. Across high-elevation species, we discovered parallel evolution for several pathways and genes with evidence of positive selection. In particular, positively selected genes were frequently part of cellular respiration, metabolism, or cell death pathways. To further examine the role of elevation in our analyses, we compared results for low- and high-elevation species and tested different thresholds for defining elevation categories.
  • A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus

    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.