The E–Id Protein Axis Modulates the Activities of the PI3K–AKT–Mtorc1
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RBP-J Signaling − Cells Through Notch Novel IRF8-Controlled
Sca-1+Lin−CD117− Mesenchymal Stem/Stromal Cells Induce the Generation of Novel IRF8-Controlled Regulatory Dendritic Cells through Notch −RBP-J Signaling This information is current as of September 25, 2021. Xingxia Liu, Shaoda Ren, Chaozhuo Ge, Kai Cheng, Martin Zenke, Armand Keating and Robert C. H. Zhao J Immunol 2015; 194:4298-4308; Prepublished online 30 March 2015; doi: 10.4049/jimmunol.1402641 Downloaded from http://www.jimmunol.org/content/194/9/4298 Supplementary http://www.jimmunol.org/content/suppl/2015/03/28/jimmunol.140264 http://www.jimmunol.org/ Material 1.DCSupplemental References This article cites 59 articles, 19 of which you can access for free at: http://www.jimmunol.org/content/194/9/4298.full#ref-list-1 Why The JI? Submit online. • Rapid Reviews! 30 days* from submission to initial decision by guest on September 25, 2021 • 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 © 2015 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. The Journal of Immunology Sca-1+Lin2CD1172 Mesenchymal Stem/Stromal Cells Induce the Generation of Novel IRF8-Controlled Regulatory Dendritic Cells through Notch–RBP-J Signaling Xingxia Liu,*,1 Shaoda Ren,*,1 Chaozhuo Ge,* Kai Cheng,* Martin Zenke,† Armand Keating,‡,x and Robert C. -
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. -
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. -
Single Cell Transcriptomics Reveal Temporal Dynamics of Critical Regulators of Germ Cell Fate During Mouse Sex Determination
bioRxiv preprint doi: https://doi.org/10.1101/747279; this version posted November 2, 2020. 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. 1 Single cell transcriptomics reveal temporal dynamics of critical regulators of germ 2 cell fate during mouse sex determination 3 Authors: Chloé Mayère1,2, Yasmine Neirijnck1,3, Pauline Sararols1, Chris M Rands1, 4 Isabelle Stévant1,2, Françoise Kühne1, Anne-Amandine Chassot3, Marie-Christine 5 Chaboissier3, Emmanouil T. Dermitzakis1,2, Serge Nef1,2,*. 6 Affiliations: 7 1Department of Genetic Medicine and Development, University of Geneva, 1211 Geneva, 8 Switzerland; 9 2iGE3, Institute of Genetics and Genomics of Geneva, University of Geneva, 1211 10 Geneva, Switzerland; 11 3Université Côte d'Azur, CNRS, Inserm, iBV, France; 12 Lead Contact: 13 *Corresponding Author: Serge Nef, 1 rue Michel-Servet CH-1211 Genève 4, 14 [email protected]. + 41 (0)22 379 51 93 15 Running Title: Single cell transcriptomics of germ cells 1 bioRxiv preprint doi: https://doi.org/10.1101/747279; this version posted November 2, 2020. 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. 16 Abbreviations; 17 AGC: Adrenal Germ Cell 18 GC: Germ cell 19 OGC: Ovarian Germ Cell 20 TGC: Testicular Germ Cell 21 scRNA-seq: Single-cell RNA-Sequencing 22 DEG: Differentially Expressed Gene 23 24 25 Keywords: 26 Single-cell RNA-Sequencing (scRNA-seq), sex determination, ovary, testis, gonocytes, 27 oocytes, prospermatogonia, meiosis, gene regulatory network, germ cells, development, 28 RNA splicing 29 2 bioRxiv preprint doi: https://doi.org/10.1101/747279; this version posted November 2, 2020. -
Molecular Profile of Tumor-Specific CD8+ T Cell Hypofunction in a Transplantable Murine Cancer Model
Downloaded from http://www.jimmunol.org/ by guest on September 25, 2021 T + is online at: average * The Journal of Immunology , 34 of which you can access for free at: 2016; 197:1477-1488; Prepublished online 1 July from submission to initial decision 4 weeks from acceptance to publication 2016; doi: 10.4049/jimmunol.1600589 http://www.jimmunol.org/content/197/4/1477 Molecular Profile of Tumor-Specific CD8 Cell Hypofunction in a Transplantable Murine Cancer Model Katherine A. Waugh, Sonia M. Leach, Brandon L. Moore, Tullia C. Bruno, Jonathan D. Buhrman and Jill E. Slansky J Immunol cites 95 articles Submit online. Every submission reviewed by practicing scientists ? is published twice each month by Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts http://jimmunol.org/subscription Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html http://www.jimmunol.org/content/suppl/2016/07/01/jimmunol.160058 9.DCSupplemental This article http://www.jimmunol.org/content/197/4/1477.full#ref-list-1 Information about subscribing to The JI No Triage! Fast Publication! Rapid Reviews! 30 days* Why • • • Material References Permissions Email Alerts Subscription Supplementary The Journal of Immunology The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2016 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. The Journal of Immunology Molecular Profile of Tumor-Specific CD8+ T Cell Hypofunction in a Transplantable Murine Cancer Model Katherine A. -
The Title of the Dissertation
UNIVERSITY OF CALIFORNIA SAN DIEGO Novel network-based integrated analyses of multi-omics data reveal new insights into CD8+ T cell differentiation and mouse embryogenesis A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Bioinformatics and Systems Biology by Kai Zhang Committee in charge: Professor Wei Wang, Chair Professor Pavel Arkadjevich Pevzner, Co-Chair Professor Vineet Bafna Professor Cornelis Murre Professor Bing Ren 2018 Copyright Kai Zhang, 2018 All rights reserved. The dissertation of Kai Zhang is approved, and it is accept- able in quality and form for publication on microfilm and electronically: Co-Chair Chair University of California San Diego 2018 iii EPIGRAPH The only true wisdom is in knowing you know nothing. —Socrates iv TABLE OF CONTENTS Signature Page ....................................... iii Epigraph ........................................... iv Table of Contents ...................................... v List of Figures ........................................ viii List of Tables ........................................ ix Acknowledgements ..................................... x Vita ............................................. xi Abstract of the Dissertation ................................. xii Chapter 1 General introduction ............................ 1 1.1 The applications of graph theory in bioinformatics ......... 1 1.2 Leveraging graphs to conduct integrated analyses .......... 4 1.3 References .............................. 6 Chapter 2 Systematic -
Olig2 and Ngn2 Function in Opposition to Modulate Gene Expression in Motor Neuron Progenitor Cells
Downloaded from genesdev.cshlp.org on September 29, 2021 - Published by Cold Spring Harbor Laboratory Press Olig2 and Ngn2 function in opposition to modulate gene expression in motor neuron progenitor cells Soo-Kyung Lee,1 Bora Lee,1 Esmeralda C. Ruiz, and Samuel L. Pfaff2 Gene Expression Laboratory, The Salk Institute for Biological Studies, La Jolla, California 92037, USA Spinal motor neurons and oligodendrocytes are generated sequentially from a common pool of progenitors termed pMN cells. Olig2 is a bHLH-class transcription factor in pMN cells, but it has remained unclear how its transcriptional activity is modulated to first produce motor neurons and then oligodendrocytes. Previous studies have shown that Olig2 primes pMN cells to become motor neurons by triggering the expression of Ngn2 and Lhx3. Here we show that Olig2 also antagonizes the premature expression of post-mitotic motor neuron genes in pMN cells. This blockade is counteracted by Ngn2, which accumulates heterogeneously in pMN cells, thereby releasing a subset of the progenitors to differentiate and activate expression of post-mitotic motor neuron genes. The antagonistic relationship between Ngn2 and Olig2 is mediated by protein interactions that squelch activity as well as competition for shared DNA-binding sites. Our data support a model in which the Olig2/Ngn2 ratio in progenitor cells serves as a gate for timing proper gene expression during the development of pMN cells: Olig2high maintains the pMN state, thereby holding cells in reserve for oligodendrocyte generation, whereas Ngn2high favors the conversion of pMN cells into post-mitotic motor neurons. [Keywords: Motor neuron; oligodendrocyte; development; basic helix–loop–helix (bHLH); neurogenin (Ngn); Olig] Supplemental material is available at http://www.genesdev.org. -
Open Dogan Phdthesis Final.Pdf
The Pennsylvania State University The Graduate School Eberly College of Science ELUCIDATING BIOLOGICAL FUNCTION OF GENOMIC DNA WITH ROBUST SIGNALS OF BIOCHEMICAL ACTIVITY: INTEGRATIVE GENOME-WIDE STUDIES OF ENHANCERS A Dissertation in Biochemistry, Microbiology and Molecular Biology by Nergiz Dogan © 2014 Nergiz Dogan Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy August 2014 ii The dissertation of Nergiz Dogan was reviewed and approved* by the following: Ross C. Hardison T. Ming Chu Professor of Biochemistry and Molecular Biology Dissertation Advisor Chair of Committee David S. Gilmour Professor of Molecular and Cell Biology Anton Nekrutenko Professor of Biochemistry and Molecular Biology Robert F. Paulson Professor of Veterinary and Biomedical Sciences Philip Reno Assistant Professor of Antropology Scott B. Selleck Professor and Head of the Department of Biochemistry and Molecular Biology *Signatures are on file in the Graduate School iii ABSTRACT Genome-wide measurements of epigenetic features such as histone modifications, occupancy by transcription factors and coactivators provide the opportunity to understand more globally how genes are regulated. While much effort is being put into integrating the marks from various combinations of features, the contribution of each feature to accuracy of enhancer prediction is not known. We began with predictions of 4,915 candidate erythroid enhancers based on genomic occupancy by TAL1, a key hematopoietic transcription factor that is strongly associated with gene induction in erythroid cells. Seventy of these DNA segments occupied by TAL1 (TAL1 OSs) were tested by transient transfections of cultured hematopoietic cells, and 56% of these were active as enhancers. Sixty-six TAL1 OSs were evaluated in transgenic mouse embryos, and 65% of these were active enhancers in various tissues. -
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. -
The DNA Methylation of FOXO3 and TP53 As a Blood Biomarker of Late
Yuan et al. J Transl Med (2020) 18:467 https://doi.org/10.1186/s12967-020-02643-y Journal of Translational Medicine RESEARCH Open Access The DNA methylation of FOXO3 and TP53 as a blood biomarker of late-onset asthma Lin Yuan1,2,3, Leyuan Wang2, Xizi Du2, Ling Qin1,3, Ming Yang4, Kai Zhou2, Mengping Wu2, Yu Yang2, Zhiyuan Zheng1,3, Yang Xiang2, Xiangping Qu2, Huijun Liu2, Xiaoqun Qin2 and Chi Liu1,2,5* Abstract Background: Late-onset asthma (LOA) is beginning to account for an increasing proportion of asthma patients, which is often underdiagnosed in the elderly. Studies on the possible relations between aging-related genes and LOA contribute to the diagnosis and treatment of LOA. Forkhead Box O3 (FOXO3) and TP53 are two classic aging-related genes. DNA methylation varies greatly with age which may play an important role in the pathogenesis of LOA. We supposed that the diferentially methylated sites of FOXO3 and TP53 associated with clinical phenotypes of LOA may be useful biomarkers for the early screening of LOA. Methods: The mRNA expression and DNA methylation of FOXO3 and TP53 in peripheral blood of 43 LOA patients (15 mild LOA, 15 moderate LOA and 13 severe LOA) and 60 healthy controls (HCs) were determined. The association of methylated sites with age was assessed by Cox regression to control the potential confounders. Then, the correlation between diferentially methylated sites (DMSs; p-value < 0.05) and clinical lung function in LOA patients was evalu- ated. Next, candidate DMSs combining with age were evaluated to predict LOA by receiver operating characteristic (ROC) analysis and principal components analysis (PCA). -
4-6 Weeks Old Female C57BL/6 Mice Obtained from Jackson Labs Were Used for Cell Isolation
Methods Mice: 4-6 weeks old female C57BL/6 mice obtained from Jackson labs were used for cell isolation. Female Foxp3-IRES-GFP reporter mice (1), backcrossed to B6/C57 background for 10 generations, were used for the isolation of naïve CD4 and naïve CD8 cells for the RNAseq experiments. The mice were housed in pathogen-free animal facility in the La Jolla Institute for Allergy and Immunology and were used according to protocols approved by the Institutional Animal Care and use Committee. Preparation of cells: Subsets of thymocytes were isolated by cell sorting as previously described (2), after cell surface staining using CD4 (GK1.5), CD8 (53-6.7), CD3ε (145- 2C11), CD24 (M1/69) (all from Biolegend). DP cells: CD4+CD8 int/hi; CD4 SP cells: CD4CD3 hi, CD24 int/lo; CD8 SP cells: CD8 int/hi CD4 CD3 hi, CD24 int/lo (Fig S2). Peripheral subsets were isolated after pooling spleen and lymph nodes. T cells were enriched by negative isolation using Dynabeads (Dynabeads untouched mouse T cells, 11413D, Invitrogen). After surface staining for CD4 (GK1.5), CD8 (53-6.7), CD62L (MEL-14), CD25 (PC61) and CD44 (IM7), naïve CD4+CD62L hiCD25-CD44lo and naïve CD8+CD62L hiCD25-CD44lo were obtained by sorting (BD FACS Aria). Additionally, for the RNAseq experiments, CD4 and CD8 naïve cells were isolated by sorting T cells from the Foxp3- IRES-GFP mice: CD4+CD62LhiCD25–CD44lo GFP(FOXP3)– and CD8+CD62LhiCD25– CD44lo GFP(FOXP3)– (antibodies were from Biolegend). In some cases, naïve CD4 cells were cultured in vitro under Th1 or Th2 polarizing conditions (3, 4). -
Supplemental Materials ZNF281 Enhances Cardiac Reprogramming
Supplemental Materials ZNF281 enhances cardiac reprogramming by modulating cardiac and inflammatory gene expression Huanyu Zhou, Maria Gabriela Morales, Hisayuki Hashimoto, Matthew E. Dickson, Kunhua Song, Wenduo Ye, Min S. Kim, Hanspeter Niederstrasser, Zhaoning Wang, Beibei Chen, Bruce A. Posner, Rhonda Bassel-Duby and Eric N. Olson Supplemental Table 1; related to Figure 1. Supplemental Table 2; related to Figure 1. Supplemental Table 3; related to the “quantitative mRNA measurement” in Materials and Methods section. Supplemental Table 4; related to the “ChIP-seq, gene ontology and pathway analysis” and “RNA-seq” and gene ontology analysis” in Materials and Methods section. Supplemental Figure S1; related to Figure 1. Supplemental Figure S2; related to Figure 2. Supplemental Figure S3; related to Figure 3. Supplemental Figure S4; related to Figure 4. Supplemental Figure S5; related to Figure 6. Supplemental Table S1. Genes included in human retroviral ORF cDNA library. Gene Gene Gene Gene Gene Gene Gene Gene Symbol Symbol Symbol Symbol Symbol Symbol Symbol Symbol AATF BMP8A CEBPE CTNNB1 ESR2 GDF3 HOXA5 IL17D ADIPOQ BRPF1 CEBPG CUX1 ESRRA GDF6 HOXA6 IL17F ADNP BRPF3 CERS1 CX3CL1 ETS1 GIN1 HOXA7 IL18 AEBP1 BUD31 CERS2 CXCL10 ETS2 GLIS3 HOXB1 IL19 AFF4 C17ORF77 CERS4 CXCL11 ETV3 GMEB1 HOXB13 IL1A AHR C1QTNF4 CFL2 CXCL12 ETV7 GPBP1 HOXB5 IL1B AIMP1 C21ORF66 CHIA CXCL13 FAM3B GPER HOXB6 IL1F3 ALS2CR8 CBFA2T2 CIR1 CXCL14 FAM3D GPI HOXB7 IL1F5 ALX1 CBFA2T3 CITED1 CXCL16 FASLG GREM1 HOXB9 IL1F6 ARGFX CBFB CITED2 CXCL3 FBLN1 GREM2 HOXC4 IL1F7