Comprehensive Protein Interactome Analysis of a Key RNA Helicase: Detection of Novel Stress Granule Proteins
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Large-Scale Analysis of Genome and Transcriptome Alterations in Multiple Tumors Unveils Novel Cancer-Relevant Splicing Networks
Downloaded from genome.cshlp.org on September 28, 2021 - Published by Cold Spring Harbor Laboratory Press Research Large-scale analysis of genome and transcriptome alterations in multiple tumors unveils novel cancer-relevant splicing networks Endre Sebestyén,1,5 Babita Singh,1,5 Belén Miñana,1,2 Amadís Pagès,1 Francesca Mateo,3 Miguel Angel Pujana,3 Juan Valcárcel,1,2,4 and Eduardo Eyras1,4 1Universitat Pompeu Fabra, E08003 Barcelona, Spain; 2Centre for Genomic Regulation, E08003 Barcelona, Spain; 3Program Against Cancer Therapeutic Resistance (ProCURE), Catalan Institute of Oncology (ICO), Bellvitge Institute for Biomedical Research (IDIBELL), E08908 L’Hospitalet del Llobregat, Spain; 4Catalan Institution for Research and Advanced Studies, E08010 Barcelona, Spain Alternative splicing is regulated by multiple RNA-binding proteins and influences the expression of most eukaryotic genes. However, the role of this process in human disease, and particularly in cancer, is only starting to be unveiled. We system- atically analyzed mutation, copy number, and gene expression patterns of 1348 RNA-binding protein (RBP) genes in 11 solid tumor types, together with alternative splicing changes in these tumors and the enrichment of binding motifs in the alter- natively spliced sequences. Our comprehensive study reveals widespread alterations in the expression of RBP genes, as well as novel mutations and copy number variations in association with multiple alternative splicing changes in cancer drivers and oncogenic pathways. Remarkably, the altered splicing patterns in several tumor types recapitulate those of undifferen- tiated cells. These patterns are predicted to be mainly controlled by MBNL1 and involve multiple cancer drivers, including the mitotic gene NUMA1. We show that NUMA1 alternative splicing induces enhanced cell proliferation and centrosome am- plification in nontumorigenic mammary epithelial cells. -
IP6K1 Upregulates the Formation of Processing Bodies by Promoting Proteome Remodeling on the Mrna Cap
bioRxiv preprint doi: https://doi.org/10.1101/2020.07.13.199828; this version posted July 13, 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 The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.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. IP6K1 upregulates the formation of processing bodies by promoting proteome remodeling on the mRNA cap Akruti Shah1,2 and Rashna Bhandari1* 1Laboratory of Cell Signalling, Centre for DNA Fingerprinting and Diagnostics (CDFD), Inner Ring Road, Uppal, Hyderabad 500039, India. 2Graduate studies, Manipal Academy of Higher Education, Manipal 576104, India. *Correspondence to Rashna Bhandari; Email: [email protected] Running title: IP6K1 promotes mRNA turnover to induce P-bodies ORCID IDs Akruti Shah - 0000-0001-9557-4952 Rashna Bhandari - 0000-0003-3101-0204 This PDF file includes: Main Text Figures 1 to 6 Keywords mRNA decay/mRNA metabolism/P-bodies/translation suppression 1 bioRxiv preprint doi: https://doi.org/10.1101/2020.07.13.199828; this version posted July 13, 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. Abstract Inositol hexakisphosphate kinases (IP6Ks) are ubiquitously expressed small molecule kinases that catalyze the conversion of the inositol phosphate IP6 to 5-IP7. IP6Ks have been reported to influence cellular functions by protein-protein interactions independent of their enzymatic activity. -
Coupling of Spliceosome Complexity to Intron Diversity
bioRxiv preprint doi: https://doi.org/10.1101/2021.03.19.436190; this version posted March 20, 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-NC-ND 4.0 International license. Coupling of spliceosome complexity to intron diversity Jade Sales-Lee1, Daniela S. Perry1, Bradley A. Bowser2, Jolene K. Diedrich3, Beiduo Rao1, Irene Beusch1, John R. Yates III3, Scott W. Roy4,6, and Hiten D. Madhani1,6,7 1Dept. of Biochemistry and Biophysics University of California – San Francisco San Francisco, CA 94158 2Dept. of Molecular and Cellular Biology University of California - Merced Merced, CA 95343 3Department of Molecular Medicine The Scripps Research Institute, La Jolla, CA 92037 4Dept. of Biology San Francisco State University San Francisco, CA 94132 5Chan-Zuckerberg Biohub San Francisco, CA 94158 6Corresponding authors: [email protected], [email protected] 7Lead Contact 1 bioRxiv preprint doi: https://doi.org/10.1101/2021.03.19.436190; this version posted March 20, 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-NC-ND 4.0 International license. SUMMARY We determined that over 40 spliceosomal proteins are conserved between many fungal species and humans but were lost during the evolution of S. cerevisiae, an intron-poor yeast with unusually rigid splicing signals. We analyzed null mutations in a subset of these factors, most of which had not been investigated previously, in the intron-rich yeast Cryptococcus neoformans. -
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. -
Downloaded from the TCGA Data Portal ( Data.Nci.Nih.Gov/Tcga/) (Supplemental Table S1)
bioRxiv preprint doi: https://doi.org/10.1101/023010; this version posted February 11, 2016. 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. Large-scale analysis of genome and transcriptome alterations in multiple tumors unveils novel cancer-relevant splicing networks Endre Sebestyén1,*, Babita Singh1,*, Belén Miñana1,2, Amadís Pagès1, Francesca Mateo3, Miguel Angel Pujana3, Juan Valcárcel1,2,4, Eduardo Eyras1,4,5 1Universitat Pompeu Fabra, Dr. Aiguader 88, E08003 Barcelona, Spain 2Centre for Genomic Regulation, Dr. Aiguader 88, E08003 Barcelona, Spain 3Program Against Cancer Therapeutic Resistance (ProCURE), Catalan Institute of Oncology (ICO), Bellvitge Institute for Biomedical Research (IDIBELL), E08908 L’Hospitalet del Llobregat, Spain. 4Catalan Institution for Research and Advanced Studies, Passeig Lluís Companys 23, E08010 Barcelona, Spain *Equal contribution 5Correspondence to: [email protected] Keywords: alternative splicing, RNA binding proteins, splicing networks, cancer 1 bioRxiv preprint doi: https://doi.org/10.1101/023010; this version posted February 11, 2016. 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. Abstract Alternative splicing is regulated by multiple RNA-binding proteins and influences the expression of most eukaryotic genes. However, the role of this process in human disease, and particularly in cancer, is only starting to be unveiled. -
Mrna Turnover Philip Mitchell* and David Tollervey†
320 mRNA turnover Philip Mitchell* and David Tollervey† Nuclear RNA-binding proteins can record pre-mRNA are cotransported to the cytoplasm with the mRNP. These processing events in the structure of messenger proteins may preserve a record of the nuclear history of the ribonucleoprotein particles (mRNPs). During initial rounds of pre-mRNA in the cytoplasmic mRNP structure. This infor- translation, the mature mRNP structure is established and is mation can strongly influence the cytoplasmic fate of the monitored by mRNA surveillance systems. Competition for the mRNA and is used by mRNA surveillance systems that act cap structure links translation and subsequent mRNA as a checkpoint of mRNP integrity, particularly in the identi- degradation, which may also involve multiple deadenylases. fication of premature translation termination codons (PTCs). Addresses Cotransport of nuclear mRNA-binding proteins with mRNA Wellcome Trust Centre for Cell Biology, ICMB, University of Edinburgh, from the nucleus to the cytoplasm (nucleocytoplasmic shut- Kings’ Buildings, Edinburgh EH9 3JR, UK tling) was first observed for the heterogeneous nuclear *e-mail: [email protected] ribonucleoprotein (hnRNP) proteins. Some hnRNP proteins †e-mail: [email protected] are stripped from the mRNA at export [1], but hnRNP A1, Current Opinion in Cell Biology 2001, 13:320–325 A2, E, I and K are all exported (see [2]). Although roles for 0955-0674/01/$ — see front matter these hnRNP proteins in transport and translation have been © 2001 Elsevier Science Ltd. All rights reserved. reported [3•,4•], their affects on mRNA stability have been little studied. More is known about hnRNP D/AUF1 and Abbreviations AREs AU-rich sequence elements another nuclear RNA-binding protein, HuR, which act CBC cap-binding complex antagonistically to modulate the stability of a range of DAN deadenylating nuclease mRNAs containing AU-rich sequence elements (AREs) DSEs downstream sequence elements (reviewed in [2]). -
DEAD-Box RNA Helicases in Cell Cycle Control and Clinical Therapy
cells Review DEAD-Box RNA Helicases in Cell Cycle Control and Clinical Therapy Lu Zhang 1,2 and Xiaogang Li 2,3,* 1 Department of Nephrology, Renmin Hospital of Wuhan University, Wuhan 430060, China; [email protected] 2 Department of Internal Medicine, Mayo Clinic, 200 1st Street, SW, Rochester, MN 55905, USA 3 Department of Biochemistry and Molecular Biology, Mayo Clinic, 200 1st Street, SW, Rochester, MN 55905, USA * Correspondence: [email protected]; Tel.: +1-507-266-0110 Abstract: Cell cycle is regulated through numerous signaling pathways that determine whether cells will proliferate, remain quiescent, arrest, or undergo apoptosis. Abnormal cell cycle regula- tion has been linked to many diseases. Thus, there is an urgent need to understand the diverse molecular mechanisms of how the cell cycle is controlled. RNA helicases constitute a large family of proteins with functions in all aspects of RNA metabolism, including unwinding or annealing of RNA molecules to regulate pre-mRNA, rRNA and miRNA processing, clamping protein complexes on RNA, or remodeling ribonucleoprotein complexes, to regulate gene expression. RNA helicases also regulate the activity of specific proteins through direct interaction. Abnormal expression of RNA helicases has been associated with different diseases, including cancer, neurological disorders, aging, and autosomal dominant polycystic kidney disease (ADPKD) via regulation of a diverse range of cellular processes such as cell proliferation, cell cycle arrest, and apoptosis. Recent studies showed that RNA helicases participate in the regulation of the cell cycle progression at each cell cycle phase, including G1-S transition, S phase, G2-M transition, mitosis, and cytokinesis. -
RNA Components of the Spliceosome Regulate Tissue- and Cancer-Specific Alternative Splicing
Downloaded from genome.cshlp.org on September 29, 2021 - Published by Cold Spring Harbor Laboratory Press Research RNA components of the spliceosome regulate tissue- and cancer-specific alternative splicing Heidi Dvinge,1,2,4 Jamie Guenthoer,3 Peggy L. Porter,3 and Robert K. Bradley1,2 1Computational Biology Program, Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, USA; 2Basic Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, USA; 3Human Biology Division, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, USA Alternative splicing of pre-mRNAs plays a pivotal role during the establishment and maintenance of human cell types. Characterizing the trans-acting regulatory proteins that control alternative splicing has therefore been the focus of much research. Recent work has established that even core protein components of the spliceosome, which are required for splicing to proceed, can nonetheless contribute to splicing regulation by modulating splice site choice. We here show that the RNA components of the spliceosome likewise influence alternative splicing decisions. Although these small nuclear RNAs (snRNAs), termed U1, U2, U4, U5, and U6 snRNA, are present in equal stoichiometry within the spliceosome, we found that their relative levels vary by an order of magnitude during development, across tissues, and across cancer samples. Physiologically relevant perturbation of individual snRNAs drove widespread gene-specific differences in alternative splic- ing but not transcriptome-wide splicing failure. Genes that were particularly sensitive to variations in snRNA abundance in a breast cancer cell line model were likewise preferentially misspliced within a clinically diverse cohort of invasive breast ductal carcinomas. -
Supplemental Information
Supplemental information Dissection of the genomic structure of the miR-183/96/182 gene. Previously, we showed that the miR-183/96/182 cluster is an intergenic miRNA cluster, located in a ~60-kb interval between the genes encoding nuclear respiratory factor-1 (Nrf1) and ubiquitin-conjugating enzyme E2H (Ube2h) on mouse chr6qA3.3 (1). To start to uncover the genomic structure of the miR- 183/96/182 gene, we first studied genomic features around miR-183/96/182 in the UCSC genome browser (http://genome.UCSC.edu/), and identified two CpG islands 3.4-6.5 kb 5’ of pre-miR-183, the most 5’ miRNA of the cluster (Fig. 1A; Fig. S1 and Seq. S1). A cDNA clone, AK044220, located at 3.2-4.6 kb 5’ to pre-miR-183, encompasses the second CpG island (Fig. 1A; Fig. S1). We hypothesized that this cDNA clone was derived from 5’ exon(s) of the primary transcript of the miR-183/96/182 gene, as CpG islands are often associated with promoters (2). Supporting this hypothesis, multiple expressed sequences detected by gene-trap clones, including clone D016D06 (3, 4), were co-localized with the cDNA clone AK044220 (Fig. 1A; Fig. S1). Clone D016D06, deposited by the German GeneTrap Consortium (GGTC) (http://tikus.gsf.de) (3, 4), was derived from insertion of a retroviral construct, rFlpROSAβgeo in 129S2 ES cells (Fig. 1A and C). The rFlpROSAβgeo construct carries a promoterless reporter gene, the β−geo cassette - an in-frame fusion of the β-galactosidase and neomycin resistance (Neor) gene (5), with a splicing acceptor (SA) immediately upstream, and a polyA signal downstream of the β−geo cassette (Fig. -
Characterization of a 7.6-Mb Germline Deletion Encompassing the NF1 Locus and About a Hundred Genes in an NF1 Contiguous Gene Syndrome Patient
European Journal of Human Genetics (2008) 16, 1459–1466 & 2008 Macmillan Publishers Limited All rights reserved 1018-4813/08 $32.00 www.nature.com/ejhg ARTICLE Characterization of a 7.6-Mb germline deletion encompassing the NF1 locus and about a hundred genes in an NF1 contiguous gene syndrome patient Eric Pasmant*,1,2, Aure´lie de Saint-Trivier2, Ingrid Laurendeau1, Anne Dieux-Coeslier3, Be´atrice Parfait1,2, Michel Vidaud1,2, Dominique Vidaud1,2 and Ivan Bie`che1,2 1UMR745 INSERM, Universite´ Paris Descartes, Faculte´ des Sciences Pharmaceutiques et Biologiques, Paris, France; 2Service de Biochimie et de Ge´ne´tique Mole´culaire, Hoˆpital Beaujon AP-HP, Clichy, France; 3Service de Ge´ne´tique Clinique, Hoˆpital Jeanne de Flandre, Lille, France We describe a large germline deletion removing the NF1 locus, identified by heterozygosity mapping based on microsatellite markers, in an 8-year-old French girl with a particularly severe NF1 contiguous gene syndrome. We used gene-dose mapping with sequence-tagged site real-time PCR to locate the deletion end points, which were precisely characterized by means of long-range PCR and nucleotide sequencing. The deletion is located on chromosome arm 17q and is exactly 7 586 986 bp long. It encompasses the entire NF1 locus and about 100 other genes, including numerous chemokine genes, an attractive in silico-selected cerebrally expressed candidate gene (designated NUFIP2, for nuclear fragile X mental retardation protein interacting protein 2; NM_020772) and four microRNA genes. Interestingly, the centromeric breakpoint is located in intron 4 of the PIPOX gene (pipecolic acid oxidase; NM_016518) and the telomeric breakpoint in intron 5 of the GGNBP2 gene (gametogenetin binding protein 2; NM_024835) coding a transcription factor. -
1 Title 1 Loss of PABPC1 Is Compensated by Elevated PABPC4
bioRxiv preprint doi: https://doi.org/10.1101/2021.02.07.430165; this version posted February 15, 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 1 Title 2 Loss of PABPC1 is compensated by elevated PABPC4 and correlates with transcriptome 3 changes 4 5 Jingwei Xie1, 2, Xiaoyu Wei1, Yu Chen1 6 7 1 Department of Biochemistry and Groupe de recherche axé sur la structure des 8 protéines, McGill University, Montreal, Quebec H3G 0B1, Canada 9 10 2 To whom correspondence should be addressed: Dept. of Biochemistry, McGill 11 University, Montreal, QC H3G 0B1, Canada. E-mail: [email protected]. 12 13 14 15 Abstract 16 Cytoplasmic poly(A) binding protein (PABP) is an essential translation factor that binds to 17 the 3' tail of mRNAs to promote translation and regulate mRNA stability. PABPC1 is the 18 most abundant of several PABP isoforms that exist in mammals. Here, we used the 19 CRISPR/Cas genome editing system to shift the isoform composition in HEK293 cells. 20 Disruption of PABPC1 elevated PABPC4 levels. Transcriptome analysis revealed that the 21 shift in the dominant PABP isoform was correlated with changes in key transcriptional 22 regulators. This study provides insight into understanding the role of PABP isoforms in 23 development and differentiation. 24 Keywords 25 PABPC1, PABPC4, c-Myc 26 bioRxiv preprint doi: https://doi.org/10.1101/2021.02.07.430165; this version posted February 15, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. -
Gene Expression During Normal and FSHD Myogenesis Tsumagari Et Al
Gene expression during normal and FSHD myogenesis Tsumagari et al. Tsumagari et al. BMC Medical Genomics 2011, 4:67 http://www.biomedcentral.com/1755-8794/4/67 (27 September 2011) Tsumagari et al. BMC Medical Genomics 2011, 4:67 http://www.biomedcentral.com/1755-8794/4/67 RESEARCHARTICLE Open Access Gene expression during normal and FSHD myogenesis Koji Tsumagari1, Shao-Chi Chang1, Michelle Lacey2,3, Carl Baribault2,3, Sridar V Chittur4, Janet Sowden5, Rabi Tawil5, Gregory E Crawford6 and Melanie Ehrlich1,3* Abstract Background: Facioscapulohumeral muscular dystrophy (FSHD) is a dominant disease linked to contraction of an array of tandem 3.3-kb repeats (D4Z4) at 4q35. Within each repeat unit is a gene, DUX4, that can encode a protein containing two homeodomains. A DUX4 transcript derived from the last repeat unit in a contracted array is associated with pathogenesis but it is unclear how. Methods: Using exon-based microarrays, the expression profiles of myogenic precursor cells were determined. Both undifferentiated myoblasts and myoblasts differentiated to myotubes derived from FSHD patients and controls were studied after immunocytochemical verification of the quality of the cultures. To further our understanding of FSHD and normal myogenesis, the expression profiles obtained were compared to those of 19 non-muscle cell types analyzed by identical methods. Results: Many of the ~17,000 examined genes were differentially expressed (> 2-fold, p < 0.01) in control myoblasts or myotubes vs. non-muscle cells (2185 and 3006, respectively) or in FSHD vs. control myoblasts or myotubes (295 and 797, respectively). Surprisingly, despite the morphologically normal differentiation of FSHD myoblasts to myotubes, most of the disease-related dysregulation was seen as dampening of normal myogenesis- specific expression changes, including in genes for muscle structure, mitochondrial function, stress responses, and signal transduction.