Chromosome 10, Frequently Lost in Human Melanoma, Encodes Multiple Tumor-Suppressive Functions
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Ovulation-Selective Genes: the Generation and Characterization of an Ovulatory-Selective Cdna Library
531 Ovulation-selective genes: the generation and characterization of an ovulatory-selective cDNA library A Hourvitz1,2*, E Gershon2*, J D Hennebold1, S Elizur2, E Maman2, C Brendle1, E Y Adashi1 and N Dekel2 1Division of Reproductive Sciences, Department of Obstetrics and Gynecology, University of Utah Health Sciences Center, Salt Lake City, Utah 84132, USA 2Department of Biological Regulation, Weizmann Institute of Science, Rehovot, Israel (Requests for offprints should be addressed to N Dekel; Email: [email protected]) *(A Hourvitz and E Gershon contributed equally to this paper) (J D Hennebold is now at Division of Reproductive Sciences, Oregon National Primate Research Center, Oregon Health and Science University, Beaverton, Oregon 97006, USA) Abstract Ovulation-selective/specific genes, that is, genes prefer- (FAE-1) homolog, found to be localized to the inner entially or exclusively expressed during the ovulatory periantral granulosa and to the cumulus granulosa cells of process, have been the subject of growing interest. We antral follicles. The FAE-1 gene is a -ketoacyl-CoA report herein studies on the use of suppression subtractive synthase belonging to the fatty acid elongase (ELO) hybridization (SSH) to construct a ‘forward’ ovulation- family, which catalyzes the initial step of very long-chain selective/specific cDNA library. In toto, 485 clones were fatty acid synthesis. All in all, the present study accom- sequenced and analyzed for homology to known genes plished systematic identification of those hormonally with the basic local alignment tool (BLAST). Of those, regulated genes that are expressed in the ovary in an 252 were determined to be nonredundant. -
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. -
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. -
TACC1–Chtog–Aurora a Protein Complex in Breast Cancer
Oncogene (2003) 22, 8102–8116 & 2003 Nature Publishing Group All rights reserved 0950-9232/03 $25.00 www.nature.com/onc TACC1–chTOG–Aurora A protein complex in breast cancer Nathalie Conte1,Be´ ne´ dicte Delaval1, Christophe Ginestier1, Alexia Ferrand1, Daniel Isnardon2, Christian Larroque3, Claude Prigent4, Bertrand Se´ raphin5, Jocelyne Jacquemier1 and Daniel Birnbaum*,1 1Department of Molecular Oncology, U119 Inserm, Institut Paoli-Calmettes, IFR57, Marseille, France; 2Imaging Core Facility, Institut Paoli-Calmettes, Marseille, France; 3E229 Inserm, CRLC Val d’Aurelle/Paul Lamarque, Montpellier, France; 4Laboratoire du cycle cellulaire, UMR 6061 CNRS, IFR 97, Faculte´ de Me´decine, Rennes, France; 5Centre de Ge´ne´tique Mole´culaire, Gif-sur-Yvette, France The three human TACC (transforming acidic coiled-coil) metabolism, including mitosis and intracellular trans- genes encode a family of proteins with poorly defined port of molecules, is progressing but many components functions that are suspected to play a role in oncogenesis. remain to be discovered and characterized. We describe A Xenopus TACC homolog called Maskin is involved in here the interaction of the TACC1 protein with several translational control, while Drosophila D-TACC interacts protein partners that makes it a good candidate to with the microtubule-associated protein MSPS (Mini participate in microtubule-associated processes in nor- SPindleS) to ensure proper dynamics of spindle pole mal and tumoral cells. microtubules during cell division. We have delineated here In -
Genetic Variant in 3' Untranslated Region of the Mouse Pycard Gene
bioRxiv preprint doi: https://doi.org/10.1101/2021.03.26.437184; this version posted March 26, 2021. 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 4.0 International license. 1 2 3 Title: 4 Genetic Variant in 3’ Untranslated Region of the Mouse Pycard Gene Regulates Inflammasome 5 Activity 6 Running Title: 7 3’UTR SNP in Pycard regulates inflammasome activity 8 Authors: 9 Brian Ritchey1*, Qimin Hai1*, Juying Han1, John Barnard2, Jonathan D. Smith1,3 10 1Department of Cardiovascular & Metabolic Sciences, Lerner Research Institute, Cleveland Clinic, 11 Cleveland, OH 44195 12 2Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 13 44195 14 3Department of Molecular Medicine, Cleveland Clinic Lerner College of Medicine of Case Western 15 Reserve University, Cleveland, OH 44195 16 *, These authors contributed equally to this study. 17 Address correspondence to Jonathan D. Smith: email [email protected]; ORCID ID 0000-0002-0415-386X; 18 mailing address: Cleveland Clinic, Box NC-10, 9500 Euclid Avenue, Cleveland, OH 44195, USA. 19 1 bioRxiv preprint doi: https://doi.org/10.1101/2021.03.26.437184; this version posted March 26, 2021. 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 4.0 International license. 20 Abstract 21 Quantitative trait locus mapping for interleukin-1 release after inflammasome priming and activation 22 was performed on bone marrow-derived macrophages (BMDM) from an AKRxDBA/2 strain intercross. -
Actin Binding LIM 1 (Ablim1) Negatively Controls Osteoclastogenesis by Regulating Cell Migration and Fusion
Received: 14 September 2017 | Accepted: 16 March 2018 DOI: 10.1002/jcp.26605 ORIGINAL RESEARCH ARTICLE Actin binding LIM 1 (abLIM1) negatively controls osteoclastogenesis by regulating cell migration and fusion Haruna Narahara1,2 | Eiko Sakai1 | Yu Yamaguchi1 | Shun Narahara1 | Mayumi Iwatake1,* | Kuniaki Okamoto1,† | Noriaki Yoshida2 | Takayuki Tsukuba1 1 Department of Dental Pharmacology, Graduate School of Biomedical Sciences, Actin binding LIM 1 (abLIM1) is a cytoskeletal actin-binding protein that has been Nagasaki University, Nagasaki, Japan implicated in interactions between actin filaments and cytoplasmic targets. Previous 2 Department of Orthodontics and Dentofacial Orthopedics, Graduate School of Biomedical biochemical and cytochemical studies have shown that abLIM1 interacts and co- Sciences, Nagasaki University, Nagasaki, Japan localizes with F-actin in the retina and muscle. However, whether abLIM1 regulates Correspondence osteoclast differentiation has not yet been elucidated. In this study, we examined the Takayuki Tsukuba, Department of Dental role of abLIM1 in osteoclast differentiation and function. We found that abLIM1 Pharmacology, Graduate School of Biomedical Sciences, Nagasaki University, Nagasaki 852- expression was upregulated during receptor activator of nuclear factor kappa-B ligand 8588, Japan. (RANKL)-induced osteoclast differentiation, and that a novel transcript of abLIM1 was Email: [email protected] exclusively expressed in osteoclasts. Overexpression of abLIM1 in the murine Funding information monocytic cell line, RAW-D suppressed osteoclast differentiation and decreased JSPS KAKENHI, Grant numbers: 15H05298, 16K15790, 17H04379 expression of several osteoclast-marker genes. By contrast, small interfering RNA-induced knockdown of abLIM1 enhanced the formation of multinucleated osteoclasts and markedly increased the expression of the osteoclast-marker genes. Mechanistically, abLIM1 regulated the localization of tubulin, migration, and fusion in osteoclasts. -
Methods in and Applications of the Sequencing of Short Non-Coding Rnas" (2013)
University of Pennsylvania ScholarlyCommons Publicly Accessible Penn Dissertations 2013 Methods in and Applications of the Sequencing of Short Non- Coding RNAs Paul Ryvkin University of Pennsylvania, [email protected] Follow this and additional works at: https://repository.upenn.edu/edissertations Part of the Bioinformatics Commons, Genetics Commons, and the Molecular Biology Commons Recommended Citation Ryvkin, Paul, "Methods in and Applications of the Sequencing of Short Non-Coding RNAs" (2013). Publicly Accessible Penn Dissertations. 922. https://repository.upenn.edu/edissertations/922 This paper is posted at ScholarlyCommons. https://repository.upenn.edu/edissertations/922 For more information, please contact [email protected]. Methods in and Applications of the Sequencing of Short Non-Coding RNAs Abstract Short non-coding RNAs are important for all domains of life. With the advent of modern molecular biology their applicability to medicine has become apparent in settings ranging from diagonistic biomarkers to therapeutics and fields angingr from oncology to neurology. In addition, a critical, recent technological development is high-throughput sequencing of nucleic acids. The convergence of modern biotechnology with developments in RNA biology presents opportunities in both basic research and medical settings. Here I present two novel methods for leveraging high-throughput sequencing in the study of short non- coding RNAs, as well as a study in which they are applied to Alzheimer's Disease (AD). The computational methods presented here include High-throughput Annotation of Modified Ribonucleotides (HAMR), which enables researchers to detect post-transcriptional covalent modifications ot RNAs in a high-throughput manner. In addition, I describe Classification of RNAs by Analysis of Length (CoRAL), a computational method that allows researchers to characterize the pathways responsible for short non-coding RNA biogenesis. -
Gene Section Review
Atlas of Genetics and Cytogenetics in Oncology and Haematology OPEN ACCESS JOURNAL AT INIST-CNRS Gene Section Review TACC1 (transforming, acidic coiled-coil containing protein 1) Ivan Still, Melissa R Eslinger, Brenda Lauffart Department of Biological Sciences, Arkansas Tech University, 1701 N Boulder Ave Russellville, AR 72801, USA (IS), Department of Chemistry and Life Science Bartlett Hall, United States Military Academy, West Point, New York 10996, USA (MRE), Department of Physical Sciences Arkansas Tech University, 1701 N Boulder Ave Russellville, AR 72801, USA (BL) Published in Atlas Database: December 2008 Online updated version : http://AtlasGeneticsOncology.org/Genes/TACC1ID42456ch8p11.html DOI: 10.4267/2042/44620 This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 2.0 France Licence. © 2009 Atlas of Genetics and Cytogenetics in Oncology and Haematology Identity Note: - AK304507 and AK303596 sequences may be suspect Other names: Ga55; DKFZp686K18126; KIAA1103 (see UCSC Genome Bioinformatics Site HGNC (Hugo): TACC1 (http://genome.ucsc.edu) for more details. - Transcript/isoform nomenclature as per Line et al, Location: 8p11.23 2002 and Lauffart et al., 2006. TACC1F transcript Note: This gene has three proposed transcription start includes exon 1, 2 and 3 (correction to Fig 6 of Lauffart sites beginning at 38763938 bp, 38733914 bp, et al., 2006). 38705165 bp from pter. Pseudogene DNA/RNA Partially processed pseudogene: - 91% identity corresponding to base 596 to 2157 of Description AF049910. The gene is composed of 19 exons spanning 124.5 kb. Location: 10p11.21. Location base pair: starts at 37851943 and ends at Transcription 37873633 from pter (according to hg18-March_2006). -
Original Article Interactions of ABLIMI and CXCL5 with Mirnas As a Prognostic Indicator for Clinical Outcome of Osteosarcoma
Int J Clin Exp Med 2016;9(8):15345-15353 www.ijcem.com /ISSN:1940-5901/IJCEM0029430 Original Article Interactions of ABLIMI and CXCL5 with miRNAs as a prognostic indicator for clinical outcome of osteosarcoma Pengfei Gao1, Zhaowei Teng2, lixin Ji1, Wengui Xie1 1Department of Spinal Surgery, North Medical District of Linyi People’s Hospital Group, Linyi, China; 2Department of Orthopedic Surgery, People’s Hospital of Yuxi City, The 6th Affiliated Hospital of Kunming Medical College, Yuxi, China Received March 29, 2016; Accepted July 10, 2016; Epub August 15, 2016; Published August 30, 2016 Abstract: Osteosarcoma (OS) is a kind of high-grade bone-forming malignancy with poor prognosis, causing huge economic losses to the patients and society. Identification of novel biomarkers could be beneficial for the diagnosis and prognosis of OS patients. We aimed to explore the molecular mechanism of osteosarcoma by the differentially expressed miRNAs and mRNAs screened out by microarray data together with the function and metabolic pathway analysis of target genes. Expression data of miRNA and mRNA were downloaded from The Genome Expression Omnibus (GEO) dataset. Differentially expressed miRNAs of osteosarcoma were screened out by two-fold principle. Target genes of differentially expressed miRNAs were extracted out by miRTarBase software. Besides, DAVID data- set was used for the functional annotation. Differentially expressed genes of mRNA microarray were screened out for the study of relation between miRNA and mRNA. A total of 33 differentially expressed miRNAs were screened out, including 27 up-regulated miRNAs and 6 down-regulated miRNAs. Three miRNAs, hsa-miR-182, hsa-miR-486- 5p and hsa-miR760, were found to be the most differentially expressed ones, which were all up-regulated and could be used to differentiate osteosarcoma tissues from the normal ones. -
The FGF/FGFR System in Breast Cancer: Oncogenic Features and Therapeutic Perspectives
cancers Review The FGF/FGFR System in Breast Cancer: Oncogenic Features and Therapeutic Perspectives Maria Francesca Santolla and Marcello Maggiolini * Department of Pharmacy, Health and Nutritional Sciences, University of Calabria, 87036 Rende, Italy; [email protected] * Correspondence: [email protected] or [email protected] Received: 8 September 2020; Accepted: 16 October 2020; Published: 18 October 2020 Simple Summary: The fibroblast growth factor/fibroblast growth factor receptor (FGF/FGFR) system represents an emerging therapeutic target in breast cancer. Here, we discussed previous studies dealing with FGFR molecular aberrations, the alterations in the FGF/FGFR signaling across the different subtypes of breast cancer, the functional interplay between the FGF/FGFR axis and important components of the breast microenvironment, the therapeutic usefulness of FGF/FGFR inhibitors for the treatment of breast cancer. Abstract: One of the major challenges in the treatment of breast cancer is the heterogeneous nature of the disease. With multiple subtypes of breast cancer identified, there is an unmet clinical need for the development of therapies particularly for the less tractable subtypes. Several transduction mechanisms are involved in the progression of breast cancer, therefore making the assessment of the molecular landscape that characterizes each patient intricate. Over the last decade, numerous studies have focused on the development of tyrosine kinase inhibitors (TKIs) to target the main pathways dysregulated in breast cancer, however their effectiveness is often limited either by resistance to treatments or the appearance of adverse effects. In this context, the fibroblast growth factor/fibroblast growth factor receptor (FGF/FGFR) system represents an emerging transduction pathway and therapeutic target to be fully investigated among the diverse anti-cancer settings in breast cancer. -
Early Growth Response 1 Regulates Hematopoietic Support and Proliferation in Human Primary Bone Marrow Stromal Cells
Hematopoiesis SUPPLEMENTARY APPENDIX Early growth response 1 regulates hematopoietic support and proliferation in human primary bone marrow stromal cells Hongzhe Li, 1,2 Hooi-Ching Lim, 1,2 Dimitra Zacharaki, 1,2 Xiaojie Xian, 2,3 Keane J.G. Kenswil, 4 Sandro Bräunig, 1,2 Marc H.G.P. Raaijmakers, 4 Niels-Bjarne Woods, 2,3 Jenny Hansson, 1,2 and Stefan Scheding 1,2,5 1Division of Molecular Hematology, Department of Laboratory Medicine, Lund University, Lund, Sweden; 2Lund Stem Cell Center, Depart - ment of Laboratory Medicine, Lund University, Lund, Sweden; 3Division of Molecular Medicine and Gene Therapy, Department of Labora - tory Medicine, Lund University, Lund, Sweden; 4Department of Hematology, Erasmus MC Cancer Institute, Rotterdam, the Netherlands and 5Department of Hematology, Skåne University Hospital Lund, Skåne, Sweden ©2020 Ferrata Storti Foundation. This is an open-access paper. doi:10.3324/haematol. 2019.216648 Received: January 14, 2019. Accepted: July 19, 2019. Pre-published: August 1, 2019. Correspondence: STEFAN SCHEDING - [email protected] Li et al.: Supplemental data 1. Supplemental Materials and Methods BM-MNC isolation Bone marrow mononuclear cells (BM-MNC) from BM aspiration samples were isolated by density gradient centrifugation (LSM 1077 Lymphocyte, PAA, Pasching, Austria) either with or without prior incubation with RosetteSep Human Mesenchymal Stem Cell Enrichment Cocktail (STEMCELL Technologies, Vancouver, Canada) for lineage depletion (CD3, CD14, CD19, CD38, CD66b, glycophorin A). BM-MNCs from fetal long bones and adult hip bones were isolated as reported previously 1 by gently crushing bones (femora, tibiae, fibulae, humeri, radii and ulna) in PBS+0.5% FCS subsequent passing of the cell suspension through a 40-µm filter. -
Dynamic Interplay Between Locus-Specific DNA Methylation and Hydroxymethylation Regulates Distinct Biological Pathways in Prostate Carcinogenesis Shivani N
Kamdar et al. Clinical Epigenetics (2016) 8:32 DOI 10.1186/s13148-016-0195-4 RESEARCH Open Access Dynamic interplay between locus-specific DNA methylation and hydroxymethylation regulates distinct biological pathways in prostate carcinogenesis Shivani N. Kamdar1,2, Linh T. Ho1, Ken J. Kron1, Ruth Isserlin3, Theodorus van der Kwast1,4, Alexandre R. Zlotta5, Neil E. Fleshner6, Gary Bader3 and Bharati Bapat1,2* Abstract Background: Despite the significant global loss of DNA hydroxymethylation marks in prostate cancer tissues, the locus-specific role of hydroxymethylation in prostate tumorigenesis is unknown. We characterized hydroxymethylation and methylation marks by performing whole-genome next-generation sequencing in representative normal and prostate cancer-derived cell lines in order to determine functional pathways and key genes regulated by these epigenomic modifications in cancer. Results: Our cell line model shows disruption of hydroxymethylation distribution in cancer, with global loss and highly specific gain in promoter and CpG island regions. Significantly, we observed locus-specific retention of hydroxymethylation marks in specific intronic and intergenic regions which may play a novel role in the regulation of gene expression in critical functional pathways, such as BARD1 signaling and steroid hormone receptor signaling in cancer. We confirm a modest correlation of hydroxymethylation with expression in intragenic regions in prostate cancer, while identifying an original role for intergenic hydroxymethylation in differentially expressed regulatory pathways in cancer. We also demonstrate a successful strategy for the identification and validation of key candidate genes from differentially regulated biological pathways in prostate cancer. Conclusions: Our results indicate a distinct function for aberrant hydroxymethylation within each genomic feature in cancer, suggesting a specific and complex role for the deregulation of hydroxymethylation in tumorigenesis, similar to methylation.