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The N-Cadherin Interactome in Primary Cardiomyocytes As Defined Using Quantitative Proximity Proteomics Yang Li1,*, Chelsea D
© 2019. Published by The Company of Biologists Ltd | Journal of Cell Science (2019) 132, jcs221606. doi:10.1242/jcs.221606 TOOLS AND RESOURCES The N-cadherin interactome in primary cardiomyocytes as defined using quantitative proximity proteomics Yang Li1,*, Chelsea D. Merkel1,*, Xuemei Zeng2, Jonathon A. Heier1, Pamela S. Cantrell2, Mai Sun2, Donna B. Stolz1, Simon C. Watkins1, Nathan A. Yates1,2,3 and Adam V. Kwiatkowski1,‡ ABSTRACT requires multiple adhesion, cytoskeletal and signaling proteins, The junctional complexes that couple cardiomyocytes must transmit and mutations in these proteins can cause cardiomyopathies (Ehler, the mechanical forces of contraction while maintaining adhesive 2018). However, the molecular composition of ICD junctional homeostasis. The adherens junction (AJ) connects the actomyosin complexes remains poorly defined. – networks of neighboring cardiomyocytes and is required for proper The core of the AJ is the cadherin catenin complex (Halbleib and heart function. Yet little is known about the molecular composition of the Nelson, 2006; Ratheesh and Yap, 2012). Classical cadherins are cardiomyocyte AJ or how it is organized to function under mechanical single-pass transmembrane proteins with an extracellular domain that load. Here, we define the architecture, dynamics and proteome of mediates calcium-dependent homotypic interactions. The adhesive the cardiomyocyte AJ. Mouse neonatal cardiomyocytes assemble properties of classical cadherins are driven by the recruitment of stable AJs along intercellular contacts with organizational and cytosolic catenin proteins to the cadherin tail, with p120-catenin β structural hallmarks similar to mature contacts. We combine (CTNND1) binding to the juxta-membrane domain and -catenin β quantitative mass spectrometry with proximity labeling to identify the (CTNNB1) binding to the distal part of the tail. -
CLASP2 Antibody Product Type
PRODUCT INFORMATION Product name: CLASP2 antibody Product type: Primary antibodies Description: Rabbit polyclonal to CLASP2 Immunogen:3 synthetic peptides (human) conjugated to KLH Reacts with:Hu, Ms Tested applications:ELISA, WB and IF GENE INFORMATION Gene Symbol: CLASP2 Gene Name:cytoplasmic linker associated protein 2 Ensembl ID:ENSG00000163539 Entrez GeneID:23122 GenBank Accession number:AB014527 Swiss-Prot:O75122 Molecular weight of CLASP2: 165.9 & 108.6kDa Function:Microtubule plus-end tracking protein that promotes the stabilization of dynamic microtubules. Involved in the nucleation of noncentrosomal microtubules originating from the trans-Golgi network (TGN). Required for the polarization of the cytoplasmic microtubule arrays in migrating cells towards the leading edge of the cell. May act at the cell cortex to enhance the frequency of rescue of depolymerizing microtubules by attaching their plus- ends to cortical platforms composed of ERC1 and PHLDB2. This cortical microtubule stabilizing activity is regulated at least in part by phosphatidylinositol 3-kinase signaling. Also performs a similar stabilizing function at the kinetochore which is essential for the bipolar alignment of chromosomes on the mitotic spindle. Acts as a mediator of ERBB2- dependent stabilization of microtubules at the cell cortex. Expected subcellular localization:Cytoplasm › cytoskeleton. Cytoplasm › cytoskeleton › microtubule organizing center › centrosome. Chromosome › centromere › kinetochore. Cytoplasm › cytoskeleton › spindle. Golgi apparatus. Golgi apparatus › trans-Golgi network. Cell membrane. Cell projection › ruffle membrane. Note: Localizes to microtubule plus ends. Localizes to centrosomes, kinetochores and the mitotic spindle from prometaphase. Subsequently localizes to the spindle midzone from anaphase and to the midbody from telophase. In migrating cells localizes to the plus ends of microtubules within the cell body and to the entire microtubule lattice within the lamella. -
Coordinate Regulation of Long Non-Coding Rnas and Protein-Coding Genes in Germ- Free Mice Joseph Dempsey, Angela Zhang and Julia Yue Cui*
Dempsey et al. BMC Genomics (2018) 19:834 https://doi.org/10.1186/s12864-018-5235-3 RESEARCHARTICLE Open Access Coordinate regulation of long non-coding RNAs and protein-coding genes in germ- free mice Joseph Dempsey, Angela Zhang and Julia Yue Cui* Abstract Background: Long non-coding RNAs (lncRNAs) are increasingly recognized as regulators of tissue-specific cellular functions and have been shown to regulate transcriptional and translational processes, acting as signals, decoys, guides, and scaffolds. It has been suggested that some lncRNAs act in cis to regulate the expression of neighboring protein-coding genes (PCGs) in a mechanism that fine-tunes gene expression. Gut microbiome is increasingly recognized as a regulator of development, inflammation, host metabolic processes, and xenobiotic metabolism. However, there is little known regarding whether the gut microbiome modulates lncRNA gene expression in various host metabolic organs. The goals of this study were to 1) characterize the tissue-specific expression of lncRNAs and 2) identify and annotate lncRNAs differentially regulated in the absence of gut microbiome. Results: Total RNA was isolated from various tissues (liver, duodenum, jejunum, ileum, colon, brown adipose tissue, white adipose tissue, and skeletal muscle) from adult male conventional and germ-free mice (n = 3 per group). RNA-Seq was conducted and reads were mapped to the mouse reference genome (mm10) using HISAT. Transcript abundance and differential expression was determined with Cufflinks using the reference databases NONCODE 2016 for lncRNAs and UCSC mm10 for PCGs. Although the constitutive expression of lncRNAs was ubiquitous within the enterohepatic (liver and intestine) and the peripheral metabolic tissues (fat and muscle) in conventional mice, differential expression of lncRNAs by lack of gut microbiota was highly tissue specific. -
Mouse Phldb2 Knockout Project (CRISPR/Cas9)
https://www.alphaknockout.com Mouse Phldb2 Knockout Project (CRISPR/Cas9) Objective: To create a Phldb2 knockout Mouse model (C57BL/6J) by CRISPR/Cas-mediated genome engineering. Strategy summary: The Phldb2 gene (NCBI Reference Sequence: NM_001252442 ; Ensembl: ENSMUSG00000033149 ) is located on Mouse chromosome 16. 19 exons are identified, with the ATG start codon in exon 2 and the TAG stop codon in exon 19 (Transcript: ENSMUST00000076333). Exon 2 will be selected as target site. Cas9 and gRNA will be co-injected into fertilized eggs for KO Mouse production. The pups will be genotyped by PCR followed by sequencing analysis. Note: Mice homozygous for a conditional allele activated in neurons exhibit impaired LTP. Exon 2 starts from the coding region. Exon 2 covers 33.87% of the coding region. The size of effective KO region: ~1337 bp. The KO region does not have any other known gene. Page 1 of 9 https://www.alphaknockout.com Overview of the Targeting Strategy Wildtype allele 5' gRNA region gRNA region 3' 1 2 19 Legends Exon of mouse Phldb2 Knockout region Page 2 of 9 https://www.alphaknockout.com Overview of the Dot Plot (up) Window size: 15 bp Forward Reverse Complement Sequence 12 Note: The 2000 bp section upstream of Exon 2 is aligned with itself to determine if there are tandem repeats. Tandem repeats are found in the dot plot matrix. The gRNA site is selected outside of these tandem repeats. Overview of the Dot Plot (down) Window size: 15 bp Forward Reverse Complement Sequence 12 Note: The 2000 bp section downstream of Exon 2 is aligned with itself to determine if there are tandem repeats. -
Cellular and Molecular Signatures in the Disease Tissue of Early
Cellular and Molecular Signatures in the Disease Tissue of Early Rheumatoid Arthritis Stratify Clinical Response to csDMARD-Therapy and Predict Radiographic Progression Frances Humby1,* Myles Lewis1,* Nandhini Ramamoorthi2, Jason Hackney3, Michael Barnes1, Michele Bombardieri1, Francesca Setiadi2, Stephen Kelly1, Fabiola Bene1, Maria di Cicco1, Sudeh Riahi1, Vidalba Rocher-Ros1, Nora Ng1, Ilias Lazorou1, Rebecca E. Hands1, Desiree van der Heijde4, Robert Landewé5, Annette van der Helm-van Mil4, Alberto Cauli6, Iain B. McInnes7, Christopher D. Buckley8, Ernest Choy9, Peter Taylor10, Michael J. Townsend2 & Costantino Pitzalis1 1Centre for Experimental Medicine and Rheumatology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK. Departments of 2Biomarker Discovery OMNI, 3Bioinformatics and Computational Biology, Genentech Research and Early Development, South San Francisco, California 94080 USA 4Department of Rheumatology, Leiden University Medical Center, The Netherlands 5Department of Clinical Immunology & Rheumatology, Amsterdam Rheumatology & Immunology Center, Amsterdam, The Netherlands 6Rheumatology Unit, Department of Medical Sciences, Policlinico of the University of Cagliari, Cagliari, Italy 7Institute of Infection, Immunity and Inflammation, University of Glasgow, Glasgow G12 8TA, UK 8Rheumatology Research Group, Institute of Inflammation and Ageing (IIA), University of Birmingham, Birmingham B15 2WB, UK 9Institute of -
Long-Range Chromosome Interactions Mediated by Cohesin Shape Circadian Gene Expression
RESEARCH ARTICLE Long-Range Chromosome Interactions Mediated by Cohesin Shape Circadian Gene Expression Yichi Xu1,2, Weimin Guo1, Ping Li3, Yan Zhang3, Meng Zhao1,4, Zenghua Fan1,2, Zhihu Zhao3, Jun Yan1,4* 1 CAS-MPG Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China, 2 University of Chinese Academy of Sciences, Shanghai, China, 3 Beijing Institute of Biotechnology, Beijing, China, 4 Institute of Neuroscience, State Key Laboratory a11111 of Neuroscience, CAS Center for Excellence in Brain Science, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China * [email protected] Abstract OPEN ACCESS Mammalian circadian rhythm is established by the negative feedback loops consisting of a Citation: Xu Y, Guo W, Li P, Zhang Y, Zhao M, Fan Z, et al. (2016) Long-Range Chromosome Interactions set of clock genes, which lead to the circadian expression of thousands of downstream Mediated by Cohesin Shape Circadian Gene genes in vivo. As genome-wide transcription is organized under the high-order chromosome Expression. PLoS Genet 12(5): e1005992. structure, it is largely uncharted how circadian gene expression is influenced by chromo- doi:10.1371/journal.pgen.1005992 some architecture. We focus on the function of chromatin structure proteins cohesin as well — Editor: Achim Kramer, Charité Universitätsmedizin as CTCF (CCCTC-binding factor) in circadian rhythm. Using circular chromosome confor- Berlin, GERMANY mation capture sequencing, we systematically examined the interacting loci of a Bmal1- Received: October 10, 2015 bound super-enhancer upstream of a clock gene Nr1d1 in mouse liver. These interactions Accepted: March 27, 2016 are largely stable in the circadian cycle and cohesin binding sites are enriched in the interac- Published: May 2, 2016 tome. -
Further Evidence of Involvement of TMEM132E in Autosomal Recessive Nonsyndromic Hearing Impairment
Journal of Human Genetics (2020) 65:187–192 https://doi.org/10.1038/s10038-019-0691-4 BRIEF COMMUNICATION Further evidence of involvement of TMEM132E in autosomal recessive nonsyndromic hearing impairment 1,2 1,2 3 4 2,5 Khurram Liaqat ● Shabir Hussain ● Muhammad Bilal ● Abdul Nasir ● Anushree Acharya ● 3,6 1 7 2,5 3 Raja Hussain Ali ● Shoaib Nawaz ● Muhammad Umair ● Isabelle Schrauwen ● Wasim Ahmad ● Suzanne M. Leal2,5 Received: 17 July 2019 / Revised: 1 October 2019 / Accepted: 9 October 2019 / Published online: 28 October 2019 © The Author(s) 2019. This article is published with open access, corrected publication 2021 Abstract Autosomal-recessive (AR) nonsyndromic hearing impairment (NSHI) displays a high degree of genetic heterogeneity with >100 genes identified. Recently, TMEM132E, which is highly expressed in inner hair cells, was suggested as a novel ARNSHI gene for DFNB99. A missense variant c.1259G>A: p.(Arg420Gln) in TMEM132E was identified that segregated with ARNSHI in a single Chinese family with two affected members. In the present study, a family of Pakistani origin with prelingual profound sensorineural hearing impairment displaying AR mode of inheritance was investigated via exome and 1234567890();,: 1234567890();,: Sanger sequencing. Compound heterozygous variants c.382G>T: p.(Ala128Ser) and c.2204C>T: p.(Pro735Leu) in TMEM132E were observed in affected but not in unaffected family members. TMEM132E variants identified in this and the previously reported ARNSHI family are located in the extracellular domain. In conclusion, we present a second ARNSHI family with TMEM132E variants which strengthens the evidence of the involvement of this gene in the etiology of ARNSHI. -
Genomic and Transcriptome Analysis Revealing an Oncogenic Functional Module in Meningiomas
Neurosurg Focus 35 (6):E3, 2013 ©AANS, 2013 Genomic and transcriptome analysis revealing an oncogenic functional module in meningiomas XIAO CHANG, PH.D.,1 LINGLING SHI, PH.D.,2 FAN GAO, PH.D.,1 JONATHAN RUssIN, M.D.,3 LIYUN ZENG, PH.D.,1 SHUHAN HE, B.S.,3 THOMAS C. CHEN, M.D.,3 STEVEN L. GIANNOTTA, M.D.,3 DANIEL J. WEISENBERGER, PH.D.,4 GAbrIEL ZADA, M.D.,3 KAI WANG, PH.D.,1,5,6 AND WIllIAM J. MAck, M.D.1,3 1Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, California; 2GHM Institute of CNS Regeneration, Jinan University, Guangzhou, China; 3Department of Neurosurgery, Keck School of Medicine, University of Southern California, Los Angeles, California; 4USC Epigenome Center, Keck School of Medicine, University of Southern California, Los Angeles, California; 5Department of Psychiatry, Keck School of Medicine, University of Southern California, Los Angeles, California; and 6Division of Bioinformatics, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California Object. Meningiomas are among the most common primary adult brain tumors. Although typically benign, roughly 2%–5% display malignant pathological features. The key molecular pathways involved in malignant trans- formation remain to be determined. Methods. Illumina expression microarrays were used to assess gene expression levels, and Illumina single- nucleotide polymorphism arrays were used to identify copy number variants in benign, atypical, and malignant me- ningiomas (19 tumors, including 4 malignant ones). The authors also reanalyzed 2 expression data sets generated on Affymetrix microarrays (n = 68, including 6 malignant ones; n = 56, including 3 malignant ones). -
Caracterización De Complejos CDK-Ciclina Atípicos Humanos Eva Quandt Herrera
Caracterización de complejos CDK-Ciclina atípicos humanos Eva Quandt Herrera ADVERTIMENT. La consulta d’aquesta tesi queda condicionada a l’acceptació de les següents condicions d'ús: La difusió d’aquesta tesi per mitjà del servei TDX (www.tesisenxarxa.net) ha estat autoritzada pels titulars dels drets de propietat intel·lectual únicament per a usos privats emmarcats en activitats d’investigació i docència. No s’autoritza la seva reproducció amb finalitats de lucre ni la seva difusió i posada a disposició des d’un lloc aliè al servei TDX. No s’autoritza la presentació del seu contingut en una finestra o marc aliè a TDX (framing). Aquesta reserva de drets afecta tant al resum de presentació de la tesi com als seus continguts. En la utilització o cita de parts de la tesi és obligat indicar el nom de la persona autora. ADVERTENCIA. La consulta de esta tesis queda condicionada a la aceptación de las siguientes condiciones de uso: La difusión de esta tesis por medio del servicio TDR (www.tesisenred.net) ha sido autorizada por los titulares de los derechos de propiedad intelectual únicamente para usos privados enmarcados en actividades de investigación y docencia. No se autoriza su reproducción con finalidades de lucro ni su difusión y puesta a disposición desde un sitio ajeno al servicio TDR. No se autoriza la presentación de su contenido en una ventana o marco ajeno a TDR (framing). Esta reserva de derechos afecta tanto al resumen de presentación de la tesis como a sus contenidos. En la utilización o cita de partes de la tesis es obligado indicar el nombre de la persona autora. -
ID AKI Vs Control Fold Change P Value Symbol Entrez Gene Name *In
ID AKI vs control P value Symbol Entrez Gene Name *In case of multiple probesets per gene, one with the highest fold change was selected. Fold Change 208083_s_at 7.88 0.000932 ITGB6 integrin, beta 6 202376_at 6.12 0.000518 SERPINA3 serpin peptidase inhibitor, clade A (alpha-1 antiproteinase, antitrypsin), member 3 1553575_at 5.62 0.0033 MT-ND6 NADH dehydrogenase, subunit 6 (complex I) 212768_s_at 5.50 0.000896 OLFM4 olfactomedin 4 206157_at 5.26 0.00177 PTX3 pentraxin 3, long 212531_at 4.26 0.00405 LCN2 lipocalin 2 215646_s_at 4.13 0.00408 VCAN versican 202018_s_at 4.12 0.0318 LTF lactotransferrin 203021_at 4.05 0.0129 SLPI secretory leukocyte peptidase inhibitor 222486_s_at 4.03 0.000329 ADAMTS1 ADAM metallopeptidase with thrombospondin type 1 motif, 1 1552439_s_at 3.82 0.000714 MEGF11 multiple EGF-like-domains 11 210602_s_at 3.74 0.000408 CDH6 cadherin 6, type 2, K-cadherin (fetal kidney) 229947_at 3.62 0.00843 PI15 peptidase inhibitor 15 204006_s_at 3.39 0.00241 FCGR3A Fc fragment of IgG, low affinity IIIa, receptor (CD16a) 202238_s_at 3.29 0.00492 NNMT nicotinamide N-methyltransferase 202917_s_at 3.20 0.00369 S100A8 S100 calcium binding protein A8 215223_s_at 3.17 0.000516 SOD2 superoxide dismutase 2, mitochondrial 204627_s_at 3.04 0.00619 ITGB3 integrin, beta 3 (platelet glycoprotein IIIa, antigen CD61) 223217_s_at 2.99 0.00397 NFKBIZ nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor, zeta 231067_s_at 2.97 0.00681 AKAP12 A kinase (PRKA) anchor protein 12 224917_at 2.94 0.00256 VMP1/ mir-21likely ortholog -
Human-Specific Tandem Repeat Expansion and Differential Gene Expression During Primate Evolution
Human-specific tandem repeat expansion and differential gene expression during primate evolution Arvis Sulovaria, Ruiyang Lia, Peter A. Audanoa, David Porubskya, Mitchell R. Vollgera, Glennis A. Logsdona, Human Genome Structural Variation Consortium1, Wesley C. Warrenb, Alex A. Pollenc, Mark J. P. Chaissona,d, and Evan E. Eichlera,e,2 aDepartment of Genome Sciences, University of Washington School of Medicine, Seattle, WA 98195; bBond Life Sciences Center, University of Missouri, Columbia, MO 65201; cDepartment of Neurology, University of California, San Francisco, CA 94143; dQuantitative and Computational Biology, University of Southern California, Los Angeles, CA 90089; and eHoward Hughes Medical Institute, University of Washington, Seattle, WA 98195 Edited by Stephen T. Warren, Emory University School of Medicine, Atlanta, GA, and approved October 1, 2019 (received for review July 17, 2019) Short tandem repeats (STRs) and variable number tandem repeats Despite their established importance in population genetics (VNTRs) are important sources of natural and disease-causing and disease association, tandem repeats, particularly VNTRs, variation, yet they have been problematic to resolve in reference are among the least characterized forms of genetic variation in genomes and genotype with short-read technology. We created a the human genome (13, 14). Their repetitive nature and some- framework to model the evolution and instability of STRs and VNTRs times extreme GC content make them particularly challenging to in apes. We phased and assembled 3 ape genomes (chimpanzee, sequence and assemble with standard whole-genome shotgun gorilla, and orangutan) using long-read and 10x Genomics linked- sequencing assembly strategies, including next generation se- read sequence data for 21,442 human tandem repeats discovered in quencing approaches that depend on bridge amplification (15). -
Chamber-Enriched Gene Expression Profiles in Failing Human Hearts with Reduced Ejection Fraction
www.nature.com/scientificreports OPEN Chamber‑enriched gene expression profles in failing human hearts with reduced ejection fraction Xin Luo1, Jun Yin1, Denise Dwyer2, Tracy Yamawaki1, Hong Zhou1, Hongfei Ge3, Chun‑Ya Han2, Artem Shkumatov4, Karen Snyder5, Brandon Ason3, Chi‑Ming Li1, Oliver Homann1 & Marina Stolina2* Heart failure with reduced ejection fraction (HFrEF) constitutes 50% of HF hospitalizations and is characterized by high rates of mortality. To explore the underlying mechanisms of HFrEF etiology and progression, we studied the molecular and cellular diferences in four chambers of non‑failing (NF, n = 10) and HFrEF (n = 12) human hearts. We identifed 333 genes enriched within NF heart subregions and often associated with cardiovascular disease GWAS variants. Expression analysis of HFrEF tissues revealed extensive disease‑associated transcriptional and signaling alterations in left atrium (LA) and left ventricle (LV). Common left heart HFrEF pathologies included mitochondrial dysfunction, cardiac hypertrophy and fbrosis. Oxidative stress and cardiac necrosis pathways were prominent within LV, whereas TGF‑beta signaling was evident within LA. Cell type composition was estimated by deconvolution and revealed that HFrEF samples had smaller percentage of cardiomyocytes within the left heart, higher representation of fbroblasts within LA and perivascular cells within the left heart relative to NF samples. We identifed essential modules associated with HFrEF pathology and linked transcriptome discoveries with human genetics fndings. This study contributes to a growing body of knowledge describing chamber‑specifc transcriptomics and revealed genes and pathways that are associated with heart failure pathophysiology, which may aid in therapeutic target discovery. By physiological function, the human heart is a muscular pump that circulates blood, perfusing tissues through- out the body.