LRRC23 Is a Conserved Component of the Radial Spoke That Is Necessary For
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SPATA33 Localizes Calcineurin to the Mitochondria and Regulates Sperm Motility in Mice
SPATA33 localizes calcineurin to the mitochondria and regulates sperm motility in mice Haruhiko Miyataa, Seiya Ouraa,b, Akane Morohoshia,c, Keisuke Shimadaa, Daisuke Mashikoa,1, Yuki Oyamaa,b, Yuki Kanedaa,b, Takafumi Matsumuraa,2, Ferheen Abbasia,3, and Masahito Ikawaa,b,c,d,4 aResearch Institute for Microbial Diseases, Osaka University, Osaka 5650871, Japan; bGraduate School of Pharmaceutical Sciences, Osaka University, Osaka 5650871, Japan; cGraduate School of Medicine, Osaka University, Osaka 5650871, Japan; and dThe Institute of Medical Science, The University of Tokyo, Tokyo 1088639, Japan Edited by Mariana F. Wolfner, Cornell University, Ithaca, NY, and approved July 27, 2021 (received for review April 8, 2021) Calcineurin is a calcium-dependent phosphatase that plays roles in calcineurin can be a target for reversible and rapidly acting male a variety of biological processes including immune responses. In sper- contraceptives (5). However, it is challenging to develop molecules matozoa, there is a testis-enriched calcineurin composed of PPP3CC and that specifically inhibit sperm calcineurin and not somatic calci- PPP3R2 (sperm calcineurin) that is essential for sperm motility and male neurin because of sequence similarities (82% amino acid identity fertility. Because sperm calcineurin has been proposed as a target for between human PPP3CA and PPP3CC and 85% amino acid reversible male contraceptives, identifying proteins that interact with identity between human PPP3R1 and PPP3R2). Therefore, identi- sperm calcineurin widens the choice for developing specific inhibitors. fying proteins that interact with sperm calcineurin widens the choice Here, by screening the calcineurin-interacting PxIxIT consensus motif of inhibitors that target the sperm calcineurin pathway. in silico and analyzing the function of candidate proteins through the The PxIxIT motif is a conserved sequence found in generation of gene-modified mice, we discovered that SPATA33 inter- calcineurin-binding proteins (8, 9). -
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. -
Mammalian Male Germ Cells Are Fertile Ground for Expression Profiling Of
REPRODUCTIONREVIEW Mammalian male germ cells are fertile ground for expression profiling of sexual reproduction Gunnar Wrobel and Michael Primig Biozentrum and Swiss Institute of Bioinformatics, Klingelbergstrasse 50-70, 4056 Basel, Switzerland Correspondence should be addressed to Michael Primig; Email: [email protected] Abstract Recent large-scale transcriptional profiling experiments of mammalian spermatogenesis using rodent model systems and different types of microarrays have yielded insight into the expression program of male germ cells. These studies revealed that an astonishingly large number of loci are differentially expressed during spermatogenesis. Among them are several hundred transcripts that appear to be specific for meiotic and post-meiotic germ cells. This group includes many genes that were pre- viously implicated in spermatogenesis and/or fertility and others that are as yet poorly characterized. Profiling experiments thus reveal candidates for regulation of spermatogenesis and fertility as well as targets for innovative contraceptives that act on gene products absent in somatic tissues. In this review, consolidated high density oligonucleotide microarray data from rodent total testis and purified germ cell samples are analyzed and their impact on our understanding of the transcriptional program governing male germ cell differentiation is discussed. Reproduction (2005) 129 1–7 Introduction 2002, Sadate-Ngatchou et al. 2003) and the absence of cAMP responsive-element modulator (Crem) and deleted During mammalian male -
Protein Identities in Evs Isolated from U87-MG GBM Cells As Determined by NG LC-MS/MS
Protein identities in EVs isolated from U87-MG GBM cells as determined by NG LC-MS/MS. No. Accession Description Σ Coverage Σ# Proteins Σ# Unique Peptides Σ# Peptides Σ# PSMs # AAs MW [kDa] calc. pI 1 A8MS94 Putative golgin subfamily A member 2-like protein 5 OS=Homo sapiens PE=5 SV=2 - [GG2L5_HUMAN] 100 1 1 7 88 110 12,03704523 5,681152344 2 P60660 Myosin light polypeptide 6 OS=Homo sapiens GN=MYL6 PE=1 SV=2 - [MYL6_HUMAN] 100 3 5 17 173 151 16,91913397 4,652832031 3 Q6ZYL4 General transcription factor IIH subunit 5 OS=Homo sapiens GN=GTF2H5 PE=1 SV=1 - [TF2H5_HUMAN] 98,59 1 1 4 13 71 8,048185945 4,652832031 4 P60709 Actin, cytoplasmic 1 OS=Homo sapiens GN=ACTB PE=1 SV=1 - [ACTB_HUMAN] 97,6 5 5 35 917 375 41,70973209 5,478027344 5 P13489 Ribonuclease inhibitor OS=Homo sapiens GN=RNH1 PE=1 SV=2 - [RINI_HUMAN] 96,75 1 12 37 173 461 49,94108966 4,817871094 6 P09382 Galectin-1 OS=Homo sapiens GN=LGALS1 PE=1 SV=2 - [LEG1_HUMAN] 96,3 1 7 14 283 135 14,70620005 5,503417969 7 P60174 Triosephosphate isomerase OS=Homo sapiens GN=TPI1 PE=1 SV=3 - [TPIS_HUMAN] 95,1 3 16 25 375 286 30,77169764 5,922363281 8 P04406 Glyceraldehyde-3-phosphate dehydrogenase OS=Homo sapiens GN=GAPDH PE=1 SV=3 - [G3P_HUMAN] 94,63 2 13 31 509 335 36,03039959 8,455566406 9 Q15185 Prostaglandin E synthase 3 OS=Homo sapiens GN=PTGES3 PE=1 SV=1 - [TEBP_HUMAN] 93,13 1 5 12 74 160 18,68541938 4,538574219 10 P09417 Dihydropteridine reductase OS=Homo sapiens GN=QDPR PE=1 SV=2 - [DHPR_HUMAN] 93,03 1 1 17 69 244 25,77302971 7,371582031 11 P01911 HLA class II histocompatibility antigen, -
Experimental Validation of the Regulated Expression of Large Numbers of Non-Coding Rnas from the Mouse Genome
Downloaded from genome.cshlp.org on September 30, 2021 - Published by Cold Spring Harbor Laboratory Press Article Experimental validation of the regulated expression of large numbers of non-coding RNAs from the mouse genome Timothy Ravasi,1,4,5 Harukazu Suzuki,2,4 Ken C. Pang,1,3,4 Shintaro Katayama,2,4 Masaaki Furuno,2,4,6 Rie Okunishi,2 Shiro Fukuda,2 Kelin Ru,1 Martin C. Frith,1,2 M. Milena Gongora,1 Sean M. Grimmond,1 David A. Hume,1 Yoshihide Hayashizaki,2 and John S. Mattick1,7 1ARC Special Research Centre for Functional and Applied Genomics, Institute for Molecular Bioscience, University of Queensland, Brisbane QLD 4072, Australia; 2Laboratory for Genome Exploration Research Group, RIKEN Genomic Science Center, RIKEN Yokohama Institute, Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, 230-0045, Japan; 3T Cell Laboratory, Ludwig Institute for Cancer Research, Austin & Repatriation Medical Centre, Heidelberg VIC 3084, Australia Recent large-scale analyses of mainly full-length cDNA libraries generated from a variety of mouse tissues indicated that almost half of all representative cloned sequences did not contain an apparent protein-coding sequence, and were putatively derived from non-protein-coding RNA (ncRNA) genes. However, many of these clones were singletons and the majority were unspliced, raising the possibility that they may be derived from genomic DNA or unprocessed pre-mRNA contamination during library construction, or alternatively represent nonspecific “transcriptional noise.” Here we show, using reverse transcriptase-dependent PCR, microarray, and Northern blot analyses, that many of these clones were derived from genuine transcripts of unknown function whose expression appears to be regulated. -
Association of Gene Ontology Categories with Decay Rate for Hepg2 Experiments These Tables Show Details for All Gene Ontology Categories
Supplementary Table 1: Association of Gene Ontology Categories with Decay Rate for HepG2 Experiments These tables show details for all Gene Ontology categories. Inferences for manual classification scheme shown at the bottom. Those categories used in Figure 1A are highlighted in bold. Standard Deviations are shown in parentheses. P-values less than 1E-20 are indicated with a "0". Rate r (hour^-1) Half-life < 2hr. Decay % GO Number Category Name Probe Sets Group Non-Group Distribution p-value In-Group Non-Group Representation p-value GO:0006350 transcription 1523 0.221 (0.009) 0.127 (0.002) FASTER 0 13.1 (0.4) 4.5 (0.1) OVER 0 GO:0006351 transcription, DNA-dependent 1498 0.220 (0.009) 0.127 (0.002) FASTER 0 13.0 (0.4) 4.5 (0.1) OVER 0 GO:0006355 regulation of transcription, DNA-dependent 1163 0.230 (0.011) 0.128 (0.002) FASTER 5.00E-21 14.2 (0.5) 4.6 (0.1) OVER 0 GO:0006366 transcription from Pol II promoter 845 0.225 (0.012) 0.130 (0.002) FASTER 1.88E-14 13.0 (0.5) 4.8 (0.1) OVER 0 GO:0006139 nucleobase, nucleoside, nucleotide and nucleic acid metabolism3004 0.173 (0.006) 0.127 (0.002) FASTER 1.28E-12 8.4 (0.2) 4.5 (0.1) OVER 0 GO:0006357 regulation of transcription from Pol II promoter 487 0.231 (0.016) 0.132 (0.002) FASTER 6.05E-10 13.5 (0.6) 4.9 (0.1) OVER 0 GO:0008283 cell proliferation 625 0.189 (0.014) 0.132 (0.002) FASTER 1.95E-05 10.1 (0.6) 5.0 (0.1) OVER 1.50E-20 GO:0006513 monoubiquitination 36 0.305 (0.049) 0.134 (0.002) FASTER 2.69E-04 25.4 (4.4) 5.1 (0.1) OVER 2.04E-06 GO:0007050 cell cycle arrest 57 0.311 (0.054) 0.133 (0.002) -
Next Generation Massively Parallel Sequencing of Targeted
ARTICLE Next generation massively parallel sequencing of targeted exomes to identify genetic mutations in primary ciliary dyskinesia: Implications for application to clinical testing Jonathan S. Berg, MD, PhD1,2, James P. Evans, MD, PhD1,2, Margaret W. Leigh, MD3, Heymut Omran, MD4, Chris Bizon, PhD5, Ketan Mane, PhD5, Michael R. Knowles, MD2, Karen E. Weck, MD1,6, and Maimoona A. Zariwala, PhD6 Purpose: Advances in genetic sequencing technology have the potential rimary ciliary dyskinesia (PCD) is an autosomal recessive to enhance testing for genes associated with genetically heterogeneous Pdisorder involving abnormalities of motile cilia, resulting in clinical syndromes, such as primary ciliary dyskinesia. The objective of a range of manifestations including situs inversus, neonatal this study was to investigate the performance characteristics of exon- respiratory distress at full-term birth, recurrent otitis media, capture technology coupled with massively parallel sequencing for chronic sinusitis, chronic bronchitis that may result in bronchi- 1–3 clinical diagnostic evaluation. Methods: We performed a pilot study of ectasis, and male infertility. The disorder is genetically het- four individuals with a variety of previously identified primary ciliary erogeneous, rendering molecular diagnosis challenging given dyskinesia mutations. We designed a custom array (NimbleGen) to that mutations in nine different genes (DNAH5, DNAH11, capture 2089 exons from 79 genes associated with primary ciliary DNAI1, DNAI2, KTU, LRRC50, RSPH9, RSPH4A, and TX- dyskinesia or ciliary function and sequenced the enriched material using NDC3) account for only approximately 1/3 of PCD cases.4 the GS FLX Titanium (Roche 454) platform. Bioinformatics analysis DNAH5 and DNAI1 account for the majority of known muta- was performed in a blinded fashion in an attempt to detect the previ- tions, and the other genes each account for a small number of ously identified mutations and validate the process. -
Kif9 Is an Active Kinesin Motor Required for Ciliary Beating and Proximodistal Patterning of Motile Axonemes
bioRxiv preprint doi: https://doi.org/10.1101/2021.08.26.457815; this version posted August 27, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. 1 Kif9 is an active kinesin motor required for ciliary beating and proximodistal patterning of motile axonemes Mia J. Konjikusic1,2,3, Chanjae Lee1, Yang Yue4, Bikram D. Shrestha5, Ange M. Nguimtsop1, Amjad Horani6, Steven Brody7,8, Vivek N. Prakash5,9, Ryan S. Gray2,3, Kristen J. Verhey4, John B. Wallingford1* 1 Department of Molecular Biosciences, University of Texas at Austin, Austin, TX, USA. 2 Department of Pediatrics, Dell Pediatric Research Institute, 1400 Barbara Jordan Blvd, The University of Texas at Austin, Dell Medical School, Austin, TX, USA. 3 Department of Nutritional Sciences, 200 W 24th Street, The University of Texas at Austin, Austin, TX 78712, USA. 4 Department of Cell and Developmental Biology, University of Michigan Medical School, Ann Arbor, MI, 48109, USA. 5 Department of Physics, University of Miami, Coral Gables, FL, USA. 6 Department of Pediatrics, Washington University School of Medicine, St. Louis, MO, USA. 7 Department of Medicine, Washington University School of Medicine, St. Louis, MO, USA. 8 Department of Cell Biology and Physiology, Washington University School of Medicine, St. Louis, MO, 63110 USA 9 Department of Biology and Department of Marine Biology and Ecology, University of Miami, Coral Gables, FL, USA. *Corresponding Author [email protected] Patterson Labs 2401 Speedway Austin, Tx 78712 bioRxiv preprint doi: https://doi.org/10.1101/2021.08.26.457815; this version posted August 27, 2021. -
Whole Exome Sequencing in Families at High Risk for Hodgkin Lymphoma: Identification of a Predisposing Mutation in the KDR Gene
Hodgkin Lymphoma SUPPLEMENTARY APPENDIX Whole exome sequencing in families at high risk for Hodgkin lymphoma: identification of a predisposing mutation in the KDR gene Melissa Rotunno, 1 Mary L. McMaster, 1 Joseph Boland, 2 Sara Bass, 2 Xijun Zhang, 2 Laurie Burdett, 2 Belynda Hicks, 2 Sarangan Ravichandran, 3 Brian T. Luke, 3 Meredith Yeager, 2 Laura Fontaine, 4 Paula L. Hyland, 1 Alisa M. Goldstein, 1 NCI DCEG Cancer Sequencing Working Group, NCI DCEG Cancer Genomics Research Laboratory, Stephen J. Chanock, 5 Neil E. Caporaso, 1 Margaret A. Tucker, 6 and Lynn R. Goldin 1 1Genetic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; 2Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; 3Ad - vanced Biomedical Computing Center, Leidos Biomedical Research Inc.; Frederick National Laboratory for Cancer Research, Frederick, MD; 4Westat, Inc., Rockville MD; 5Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; and 6Human Genetics Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA ©2016 Ferrata Storti Foundation. This is an open-access paper. doi:10.3324/haematol.2015.135475 Received: August 19, 2015. Accepted: January 7, 2016. Pre-published: June 13, 2016. Correspondence: [email protected] Supplemental Author Information: NCI DCEG Cancer Sequencing Working Group: Mark H. Greene, Allan Hildesheim, Nan Hu, Maria Theresa Landi, Jennifer Loud, Phuong Mai, Lisa Mirabello, Lindsay Morton, Dilys Parry, Anand Pathak, Douglas R. Stewart, Philip R. Taylor, Geoffrey S. Tobias, Xiaohong R. Yang, Guoqin Yu NCI DCEG Cancer Genomics Research Laboratory: Salma Chowdhury, Michael Cullen, Casey Dagnall, Herbert Higson, Amy A. -
Ciliary Dyneins and Dynein Related Ciliopathies
cells Review Ciliary Dyneins and Dynein Related Ciliopathies Dinu Antony 1,2,3, Han G. Brunner 2,3 and Miriam Schmidts 1,2,3,* 1 Center for Pediatrics and Adolescent Medicine, University Hospital Freiburg, Freiburg University Faculty of Medicine, Mathildenstrasse 1, 79106 Freiburg, Germany; [email protected] 2 Genome Research Division, Human Genetics Department, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 KL Nijmegen, The Netherlands; [email protected] 3 Radboud Institute for Molecular Life Sciences (RIMLS), Geert Grooteplein Zuid 10, 6525 KL Nijmegen, The Netherlands * Correspondence: [email protected]; Tel.: +49-761-44391; Fax: +49-761-44710 Abstract: Although ubiquitously present, the relevance of cilia for vertebrate development and health has long been underrated. However, the aberration or dysfunction of ciliary structures or components results in a large heterogeneous group of disorders in mammals, termed ciliopathies. The majority of human ciliopathy cases are caused by malfunction of the ciliary dynein motor activity, powering retrograde intraflagellar transport (enabled by the cytoplasmic dynein-2 complex) or axonemal movement (axonemal dynein complexes). Despite a partially shared evolutionary developmental path and shared ciliary localization, the cytoplasmic dynein-2 and axonemal dynein functions are markedly different: while cytoplasmic dynein-2 complex dysfunction results in an ultra-rare syndromal skeleto-renal phenotype with a high lethality, axonemal dynein dysfunction is associated with a motile cilia dysfunction disorder, primary ciliary dyskinesia (PCD) or Kartagener syndrome, causing recurrent airway infection, degenerative lung disease, laterality defects, and infertility. In this review, we provide an overview of ciliary dynein complex compositions, their functions, clinical disease hallmarks of ciliary dynein disorders, presumed underlying pathomechanisms, and novel Citation: Antony, D.; Brunner, H.G.; developments in the field. -
3D Structure of Eukaryotic Flagella in a Quiescent State Revealed by Cryo-Electron Tomography
3D structure of eukaryotic flagella in a quiescent state revealed by cryo-electron tomography Daniela Nicastro*†, J. Richard McIntosh‡§, and Wolfgang Baumeister* *Abteilung Molekulare Strukturbiologie, Max-Planck-Institut fu¨r Biochemie, 82152 Martinsried, Germany; and ‡Laboratory for 3D Electron Microscopy of Cells, Department of Molecular, Cellular, and Developmental Biology, UCB 347, University of Colorado, Boulder, CO 80309 Contributed by J. Richard McIntosh, September 21, 2005 We have used cryo-electron tomography to investigate the 3D position. McEwen et al. (12) have used electron tomography structure and macromolecular organization of intact, frozen- (ET) to study chemically fixed and resin-embedded cilia from hydrated sea urchin sperm flagella in a quiescent state. The newt lung. ET uses 2D projection images from many different tomographic reconstructions provide information at a resolution viewing angles to reconstruct an object in three dimensions (13, better than 6 nm about the in situ arrangements of macromolecules 14). These researchers were able to identify major features of that are key for flagellar motility. We have visualized the hep- axonemes in the tomographic reconstructions of the 250-nm- tameric rings of the motor domains in the outer dynein arm thick sections, but at a resolution of Ϸ12 nm, detailed insights complex and determined that they lie parallel to the plane that into the molecular organization of the axoneme were not contains the axes of neighboring flagellar microtubules. Both the available. material associated with the central pair of microtubules and the Thanks to technological advances of the past decade, ET can radial spokes display a plane of symmetry that helps to explain the now be applied to relatively large, frozen-hydrated structures. -
Identification of Key Pathways and Genes in Dementia Via Integrated Bioinformatics Analysis
bioRxiv preprint doi: https://doi.org/10.1101/2021.04.18.440371; this version posted July 19, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Identification of Key Pathways and Genes in Dementia via Integrated Bioinformatics Analysis Basavaraj Vastrad1, Chanabasayya Vastrad*2 1. Department of Biochemistry, Basaveshwar College of Pharmacy, Gadag, Karnataka 582103, India. 2. Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karnataka, India. * Chanabasayya Vastrad [email protected] Ph: +919480073398 Chanabasava Nilaya, Bharthinagar, Dharwad 580001 , Karanataka, India bioRxiv preprint doi: https://doi.org/10.1101/2021.04.18.440371; this version posted July 19, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Abstract To provide a better understanding of dementia at the molecular level, this study aimed to identify the genes and key pathways associated with dementia by using integrated bioinformatics analysis. Based on the expression profiling by high throughput sequencing dataset GSE153960 derived from the Gene Expression Omnibus (GEO), the differentially expressed genes (DEGs) between patients with dementia and healthy controls were identified. With DEGs, we performed a series of functional enrichment analyses. Then, a protein–protein interaction (PPI) network, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network was constructed, analyzed and visualized, with which the hub genes miRNAs and TFs nodes were screened out. Finally, validation of hub genes was performed by using receiver operating characteristic curve (ROC) analysis.