Tablet S1. Transcription Factors Induced at Least Two Fold by OHT
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RNA-Binding Protein Hnrnpll Regulates Mrna Splicing and Stability During B-Cell to Plasma-Cell Differentiation
RNA-binding protein hnRNPLL regulates mRNA splicing and stability during B-cell to plasma-cell differentiation Xing Changa,b, Bin Lic, and Anjana Raoa,b,d,e,1 Divisions of aSignaling and Gene Expression and cVaccine Discovery, La Jolla Institute for Allergy and Immunology, La Jolla, CA 92037; bSanford Consortium for Regenerative Medicine, La Jolla, CA 92037; and dDepartment of Pharmacology and eMoores Cancer Center, University of California at San Diego, La Jolla, CA 92093 Contributed by Anjana Rao, December 2, 2014 (sent for review July 20, 2014) Posttranscriptional regulation is a major mechanism to rewire the RBP-binding sites, thus validating the specificity of RBP binding transcriptomes during differentiation. Heterogeneous nuclear to coprecipitating RNAs and mapping RBP-binding sites on the RNA-binding protein LL (hnRNPLL) is specifically induced in terminally validated RNAs at close to single-nucleotide resolution (8). differentiated lymphocytes, including effector T cells and plasma Heterogeneous nuclear RNA-binding proteins (hnRNPs) is cells. To study the molecular functions of hnRNPLL at a genome- the term applied to a collection of unrelated nuclear RBPs. wide level, we identified hnRNPLL RNA targets and binding sites in hnRNPLL was identified through a targeted lentiviral shRNA plasma cells through integrated Photoactivatable-Ribonucleoside- screen for regulators of CD45RA to CD45RO switching during Enhanced Cross-Linking and Immunoprecipitation (PAR-CLIP) and memory T-cell development (9) and independently through RNA sequencing. hnRNPLL preferentially recognizes CA dinucleo- two separate screens performed by different groups for exclusion tide-containing sequences in introns and 3′ untranslated regions of CD45 exon 4 in a minigene context (10) and for altered CD44 (UTRs), promotes exon inclusion or exclusion in a context-dependent and CD45R expression on T cells in N-ethyl-N-nitrosourea manner, and stabilizes mRNA when associated with 3′ UTRs. -
Prioritization and Evaluation of Depression Candidate Genes by Combining Multidimensional Data Resources
Prioritization and Evaluation of Depression Candidate Genes by Combining Multidimensional Data Resources Chung-Feng Kao1, Yu-Sheng Fang2, Zhongming Zhao3, Po-Hsiu Kuo1,2,4* 1 Department of Public Health and Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan, 2 Institute of Clinical Medicine, School of Medicine, National Cheng-Kung University, Tainan, Taiwan, 3 Departments of Biomedical Informatics and Psychiatry, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America, 4 Research Center for Genes, Environment and Human Health, National Taiwan University, Taipei, Taiwan Abstract Background: Large scale and individual genetic studies have suggested numerous susceptible genes for depression in the past decade without conclusive results. There is a strong need to review and integrate multi-dimensional data for follow up validation. The present study aimed to apply prioritization procedures to build-up an evidence-based candidate genes dataset for depression. Methods: Depression candidate genes were collected in human and animal studies across various data resources. Each gene was scored according to its magnitude of evidence related to depression and was multiplied by a source-specific weight to form a combined score measure. All genes were evaluated through a prioritization system to obtain an optimal weight matrix to rank their relative importance with depression using the combined scores. The resulting candidate gene list for depression (DEPgenes) was further evaluated by a genome-wide association (GWA) dataset and microarray gene expression in human tissues. Results: A total of 5,055 candidate genes (4,850 genes from human and 387 genes from animal studies with 182 being overlapped) were included from seven data sources. -
A Pathogenic Ctbp1 Missense Mutation Causes Altered Cofactor Binding and Transcriptional Activity
neurogenetics (2019) 20:129–143 https://doi.org/10.1007/s10048-019-00578-1 ORIGINAL ARTICLE A pathogenic CtBP1 missense mutation causes altered cofactor binding and transcriptional activity David B. Beck1 & T. Subramanian2 & S. Vijayalingam2 & Uthayashankar R. Ezekiel3 & Sandra Donkervoort4 & Michele L. Yang5 & Holly A. Dubbs6 & Xilma R. Ortiz-Gonzalez7 & Shenela Lakhani8 & Devorah Segal9 & Margaret Au10 & John M. Graham Jr10 & Sumit Verma11 & Darrel Waggoner12 & Marwan Shinawi13 & Carsten G. Bönnemann4 & Wendy K. Chung14 & G. Chinnadurai2 Received: 23 October 2018 /Revised: 18 March 2019 /Accepted: 9 April 2019 /Published online: 30 April 2019 # Springer-Verlag GmbH Germany, part of Springer Nature 2019 Abstract We previously reported a pathogenic de novo p.R342W mutation in the transcriptional corepressor CTBP1 in four independent patients with neurodevelopmental disabilities [1]. Here, we report the clinical phenotypes of seven additional individuals with the same recurrent de novo CTBP1 mutation. Within this cohort, we identified consistent CtBP1-related phenotypes of intellectual disability, ataxia, hypotonia, and tooth enamel defects present in most patients. The R342W mutation in CtBP1 is located within a region implicated in a high affinity-binding cleft for CtBP-interacting proteins. Unbiased proteomic analysis demonstrated reduced interaction of several chromatin-modifying factors with the CtBP1 W342 mutant. Genome-wide transcriptome analysis in human glioblastoma cell lines expressing -CtBP1 R342 (wt) or W342 mutation revealed changes in the expression profiles of genes controlling multiple cellular processes. Patient-derived dermal fibroblasts were found to be more sensitive to apoptosis during acute glucose deprivation compared to controls. Glucose deprivation strongly activated the BH3-only pro-apoptotic gene NOXA, suggesting a link between enhanced cell death and NOXA expression in patient fibroblasts. -
Feedback Regulation Between Initiation and Maturation Networks Orchestrates the Chromatin Dynamics of Epidermal Lineage
bioRxiv preprint doi: https://doi.org/10.1101/349308; this version posted June 18, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Li et al., p. 1 Feedback Regulation between Initiation and Maturation Networks Orchestrates the Chromatin Dynamics of Epidermal Lineage Commitment Lingjie Li1,3,4, Yong Wang2,4,7,8*, Jessica L. Torkelson1,3*, Gautam Shankar1, Jillian M. Pattison1,3, Hanson H. Zhen1,3, Zhana Duren2,4,7, Fengqin Fang5, Sandra P. Melo1, Samantha N. Piekos1,3, Jiang Li1, Eric J. Liaw1, Lang Chen7, Rui Li1,4, Marius Wernig6, Wing H. Wong2,4, Howard Y. Chang1,4, Anthony E. Oro1,3,9 1 Program in Epithelial Biology and Department of Dermatology 2 Department of Statistics and Biomedical Data Science 3 Center for Definitive and Curative Medicine 4 Center for Personal Dynamic Regulome 5 Division of Immunology and Rheumatology, Department of Medicine, 6 Institute for Stem Cell Biology and Regenerative Medicine, Department of Pathology, Stanford University School of Medicine, Stanford, CA 94305, USA. 7 CEMS, NCMIS, MDIS, Academy of Mathematics & Systems Science, Chinese Academy of Sciences, Beijing,100080, China 8 Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650223, China *These authors made equal and independent contributions. 9 Correspondence to Lead Contact: Anthony E. Oro at [email protected] bioRxiv preprint doi: https://doi.org/10.1101/349308; this version posted June 18, 2018. -
Transcriptome Profiling of Pediatric Core Binding Factor AML
RESEARCH ARTICLE Transcriptome Profiling of Pediatric Core Binding Factor AML Chih-Hao Hsu1, Cu Nguyen1, Chunhua Yan1, Rhonda E. Ries2, Qing-Rong Chen1, Ying Hu1, Fabiana Ostronoff2, Derek L. Stirewalt2, George Komatsoulis1, Shawn Levy3, Daoud Meerzaman1☯, Soheil Meshinchi2☯* 1 Center for Biomedical Informatics and Information Technology, National Cancer Institute, Rockville, MD, 20850, United States of America, 2 Fred Hutchinson Cancer Research Center, Seattle, WA, United States of America, 3 Hudson Alpha Institute for Biotechnology, Huntsville, AL, United States of America ☯ These authors contributed equally to this work. * [email protected] Abstract The t(8;21) and Inv(16) translocations disrupt the normal function of core binding factors alpha (CBFA) and beta (CBFB), respectively. These translocations represent two of the most com- OPEN ACCESS mon genomic abnormalities in acute myeloid leukemia (AML) patients, occurring in approxi- Citation: Hsu C-H, Nguyen C, Yan C, Ries RE, Chen mately 25% pediatric and 15% of adult with this malignancy. Both translocations are Q-R, Hu Y, et al. (2015) Transcriptome Profiling of associated with favorable clinical outcomes after intensive chemotherapy, and given the per- Pediatric Core Binding Factor AML. PLoS ONE 10(9): ceived mechanistic similarities, patients with these translocations are frequently referred to as e0138782. doi:10.1371/journal.pone.0138782 having CBF-AML. It remains uncertain as to whether, collectively, these translocations are Editor: Ken Mills, Queen's University Belfast, mechanistically the same or impact different pathways in subtle ways that have both biological UNITED KINGDOM and clinical significance. Therefore, we used transcriptome sequencing (RNA-seq) to investi- Received: June 15, 2015 gate the similarities and differences in genes and pathways between these subtypes of pediat- Accepted: September 3, 2015 ric AMLs. -
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. -
Supplementary Table 3 Complete List of RNA-Sequencing Analysis of Gene Expression Changed by ≥ Tenfold Between Xenograft and Cells Cultured in 10%O2
Supplementary Table 3 Complete list of RNA-Sequencing analysis of gene expression changed by ≥ tenfold between xenograft and cells cultured in 10%O2 Expr Log2 Ratio Symbol Entrez Gene Name (culture/xenograft) -7.182 PGM5 phosphoglucomutase 5 -6.883 GPBAR1 G protein-coupled bile acid receptor 1 -6.683 CPVL carboxypeptidase, vitellogenic like -6.398 MTMR9LP myotubularin related protein 9-like, pseudogene -6.131 SCN7A sodium voltage-gated channel alpha subunit 7 -6.115 POPDC2 popeye domain containing 2 -6.014 LGI1 leucine rich glioma inactivated 1 -5.86 SCN1A sodium voltage-gated channel alpha subunit 1 -5.713 C6 complement C6 -5.365 ANGPTL1 angiopoietin like 1 -5.327 TNN tenascin N -5.228 DHRS2 dehydrogenase/reductase 2 leucine rich repeat and fibronectin type III domain -5.115 LRFN2 containing 2 -5.076 FOXO6 forkhead box O6 -5.035 ETNPPL ethanolamine-phosphate phospho-lyase -4.993 MYO15A myosin XVA -4.972 IGF1 insulin like growth factor 1 -4.956 DLG2 discs large MAGUK scaffold protein 2 -4.86 SCML4 sex comb on midleg like 4 (Drosophila) Src homology 2 domain containing transforming -4.816 SHD protein D -4.764 PLP1 proteolipid protein 1 -4.764 TSPAN32 tetraspanin 32 -4.713 N4BP3 NEDD4 binding protein 3 -4.705 MYOC myocilin -4.646 CLEC3B C-type lectin domain family 3 member B -4.646 C7 complement C7 -4.62 TGM2 transglutaminase 2 -4.562 COL9A1 collagen type IX alpha 1 chain -4.55 SOSTDC1 sclerostin domain containing 1 -4.55 OGN osteoglycin -4.505 DAPL1 death associated protein like 1 -4.491 C10orf105 chromosome 10 open reading frame 105 -4.491 -
Evidence for Differential Alternative Splicing in Blood of Young Boys With
Stamova et al. Molecular Autism 2013, 4:30 http://www.molecularautism.com/content/4/1/30 RESEARCH Open Access Evidence for differential alternative splicing in blood of young boys with autism spectrum disorders Boryana S Stamova1,2,5*, Yingfang Tian1,2,4, Christine W Nordahl1,3, Mark D Shen1,3, Sally Rogers1,3, David G Amaral1,3 and Frank R Sharp1,2 Abstract Background: Since RNA expression differences have been reported in autism spectrum disorder (ASD) for blood and brain, and differential alternative splicing (DAS) has been reported in ASD brains, we determined if there was DAS in blood mRNA of ASD subjects compared to typically developing (TD) controls, as well as in ASD subgroups related to cerebral volume. Methods: RNA from blood was processed on whole genome exon arrays for 2-4–year-old ASD and TD boys. An ANCOVA with age and batch as covariates was used to predict DAS for ALL ASD (n=30), ASD with normal total cerebral volumes (NTCV), and ASD with large total cerebral volumes (LTCV) compared to TD controls (n=20). Results: A total of 53 genes were predicted to have DAS for ALL ASD versus TD, 169 genes for ASD_NTCV versus TD, 1 gene for ASD_LTCV versus TD, and 27 genes for ASD_LTCV versus ASD_NTCV. These differences were significant at P <0.05 after false discovery rate corrections for multiple comparisons (FDR <5% false positives). A number of the genes predicted to have DAS in ASD are known to regulate DAS (SFPQ, SRPK1, SRSF11, SRSF2IP, FUS, LSM14A). In addition, a number of genes with predicted DAS are involved in pathways implicated in previous ASD studies, such as ROS monocyte/macrophage, Natural Killer Cell, mTOR, and NGF signaling. -
1 Metabolic Dysfunction Is Restricted to the Sciatic Nerve in Experimental
Page 1 of 255 Diabetes Metabolic dysfunction is restricted to the sciatic nerve in experimental diabetic neuropathy Oliver J. Freeman1,2, Richard D. Unwin2,3, Andrew W. Dowsey2,3, Paul Begley2,3, Sumia Ali1, Katherine A. Hollywood2,3, Nitin Rustogi2,3, Rasmus S. Petersen1, Warwick B. Dunn2,3†, Garth J.S. Cooper2,3,4,5* & Natalie J. Gardiner1* 1 Faculty of Life Sciences, University of Manchester, UK 2 Centre for Advanced Discovery and Experimental Therapeutics (CADET), Central Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Sciences Centre, Manchester, UK 3 Centre for Endocrinology and Diabetes, Institute of Human Development, Faculty of Medical and Human Sciences, University of Manchester, UK 4 School of Biological Sciences, University of Auckland, New Zealand 5 Department of Pharmacology, Medical Sciences Division, University of Oxford, UK † Present address: School of Biosciences, University of Birmingham, UK *Joint corresponding authors: Natalie J. Gardiner and Garth J.S. Cooper Email: [email protected]; [email protected] Address: University of Manchester, AV Hill Building, Oxford Road, Manchester, M13 9PT, United Kingdom Telephone: +44 161 275 5768; +44 161 701 0240 Word count: 4,490 Number of tables: 1, Number of figures: 6 Running title: Metabolic dysfunction in diabetic neuropathy 1 Diabetes Publish Ahead of Print, published online October 15, 2015 Diabetes Page 2 of 255 Abstract High glucose levels in the peripheral nervous system (PNS) have been implicated in the pathogenesis of diabetic neuropathy (DN). However our understanding of the molecular mechanisms which cause the marked distal pathology is incomplete. Here we performed a comprehensive, system-wide analysis of the PNS of a rodent model of DN. -
The E–Id Protein Axis Modulates the Activities of the PI3K–AKT–Mtorc1
Downloaded from genesdev.cshlp.org on October 6, 2021 - Published by Cold Spring Harbor Laboratory Press The E–Id protein axis modulates the activities of the PI3K–AKT–mTORC1– Hif1a and c-myc/p19Arf pathways to suppress innate variant TFH cell development, thymocyte expansion, and lymphomagenesis Masaki Miyazaki,1,8 Kazuko Miyazaki,1,8 Shuwen Chen,1 Vivek Chandra,1 Keisuke Wagatsuma,2 Yasutoshi Agata,2 Hans-Reimer Rodewald,3 Rintaro Saito,4 Aaron N. Chang,5 Nissi Varki,6 Hiroshi Kawamoto,7 and Cornelis Murre1 1Department of Molecular Biology, University of California at San Diego, La Jolla, California 92093, USA; 2Department of Biochemistry and Molecular Biology, Shiga University of Medical School, Shiga 520-2192, Japan; 3Division of Cellular Immunology, German Cancer Research Center, D-69120 Heidelberg, Germany; 4Department of Medicine, University of California at San Diego, La Jolla, California 92093, USA; 5Center for Computational Biology, Institute for Genomic Medicine, University of California at San Diego, La Jolla, California 92093, USA; 6Department of Pathology, University of California at San Diego, La Jolla, California 92093, USA; 7Department of Immunology, Institute for Frontier Medical Sciences, Kyoto University, Kyoto 606-8507, Japan It is now well established that the E and Id protein axis regulates multiple steps in lymphocyte development. However, it remains unknown how E and Id proteins mechanistically enforce and maintain the naı¨ve T-cell fate. Here we show that Id2 and Id3 suppressed the development and expansion of innate variant follicular helper T (TFH) cells. Innate variant TFH cells required major histocompatibility complex (MHC) class I-like signaling and were associated with germinal center B cells. -
A SARS-Cov-2-Human Protein-Protein Interaction Map Reveals Drug Targets and Potential Drug-Repurposing
A SARS-CoV-2-Human Protein-Protein Interaction Map Reveals Drug Targets and Potential Drug-Repurposing Supplementary Information Supplementary Discussion All SARS-CoV-2 protein and gene functions described in the subnetwork appendices, including the text below and the text found in the individual bait subnetworks, are based on the functions of homologous genes from other coronavirus species. These are mainly from SARS-CoV and MERS-CoV, but when available and applicable other related viruses were used to provide insight into function. The SARS-CoV-2 proteins and genes listed here were designed and researched based on the gene alignments provided by Chan et. al. 1 2020 . Though we are reasonably sure the genes here are well annotated, we want to note that not every protein has been verified to be expressed or functional during SARS-CoV-2 infections, either in vitro or in vivo. In an effort to be as comprehensive and transparent as possible, we are reporting the sub-networks of these functionally unverified proteins along with the other SARS-CoV-2 proteins. In such cases, we have made notes within the text below, and on the corresponding subnetwork figures, and would advise that more caution be taken when examining these proteins and their molecular interactions. Due to practical limits in our sample preparation and data collection process, we were unable to generate data for proteins corresponding to Nsp3, Orf7b, and Nsp16. Therefore these three genes have been left out of the following literature review of the SARS-CoV-2 proteins and the protein-protein interactions (PPIs) identified in this study. -
Core Binding Factor Β Is Required for Group 2 Innate Lymphoid Cell Activation
Cutting Edge: Core Binding Factor β Is Required for Group 2 Innate Lymphoid Cell Activation This information is current as Xiaofei Shen, Mingwei Liang, Xiangyu Chen, Muhammad of September 24, 2021. Asghar Pasha, Shanti S. D'Souza, Kelsi Hidde, Jennifer Howard, Dil Afroz Sultana, Ivan Ting Hin Fung, Longyun Ye, Jiexue Pan, Gang Liu, James R. Drake, Lisa A. Drake, Jinfang Zhu, Avinash Bhandoola and Qi Yang J Immunol 2019; 202:1669-1673; Prepublished online 6 Downloaded from February 2019; doi: 10.4049/jimmunol.1800852 http://www.jimmunol.org/content/202/6/1669 http://www.jimmunol.org/ Supplementary http://www.jimmunol.org/content/suppl/2019/02/05/jimmunol.180085 Material 2.DCSupplemental References This article cites 20 articles, 10 of which you can access for free at: http://www.jimmunol.org/content/202/6/1669.full#ref-list-1 Why The JI? Submit online. by guest on September 24, 2021 • Rapid Reviews! 30 days* from submission to initial decision • No Triage! Every submission reviewed by practicing scientists • Fast Publication! 4 weeks from acceptance to publication *average Subscription Information about subscribing to The Journal of Immunology is online at: http://jimmunol.org/subscription Permissions Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html Email Alerts Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts The Journal of Immunology is published twice each month by The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2019 by The American Association of Immunologists, Inc. All rights reserved.