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Seq2pathway Vignette
seq2pathway Vignette Bin Wang, Xinan Holly Yang, Arjun Kinstlick May 19, 2021 Contents 1 Abstract 1 2 Package Installation 2 3 runseq2pathway 2 4 Two main functions 3 4.1 seq2gene . .3 4.1.1 seq2gene flowchart . .3 4.1.2 runseq2gene inputs/parameters . .5 4.1.3 runseq2gene outputs . .8 4.2 gene2pathway . 10 4.2.1 gene2pathway flowchart . 11 4.2.2 gene2pathway test inputs/parameters . 11 4.2.3 gene2pathway test outputs . 12 5 Examples 13 5.1 ChIP-seq data analysis . 13 5.1.1 Map ChIP-seq enriched peaks to genes using runseq2gene .................... 13 5.1.2 Discover enriched GO terms using gene2pathway_test with gene scores . 15 5.1.3 Discover enriched GO terms using Fisher's Exact test without gene scores . 17 5.1.4 Add description for genes . 20 5.2 RNA-seq data analysis . 20 6 R environment session 23 1 Abstract Seq2pathway is a novel computational tool to analyze functional gene-sets (including signaling pathways) using variable next-generation sequencing data[1]. Integral to this tool are the \seq2gene" and \gene2pathway" components in series that infer a quantitative pathway-level profile for each sample. The seq2gene function assigns phenotype-associated significance of genomic regions to gene-level scores, where the significance could be p-values of SNPs or point mutations, protein-binding affinity, or transcriptional expression level. The seq2gene function has the feasibility to assign non-exon regions to a range of neighboring genes besides the nearest one, thus facilitating the study of functional non-coding elements[2]. Then the gene2pathway summarizes gene-level measurements to pathway-level scores, comparing the quantity of significance for gene members within a pathway with those outside a pathway. -
Aneuploidy: Using Genetic Instability to Preserve a Haploid Genome?
Health Science Campus FINAL APPROVAL OF DISSERTATION Doctor of Philosophy in Biomedical Science (Cancer Biology) Aneuploidy: Using genetic instability to preserve a haploid genome? Submitted by: Ramona Ramdath In partial fulfillment of the requirements for the degree of Doctor of Philosophy in Biomedical Science Examination Committee Signature/Date Major Advisor: David Allison, M.D., Ph.D. Academic James Trempe, Ph.D. Advisory Committee: David Giovanucci, Ph.D. Randall Ruch, Ph.D. Ronald Mellgren, Ph.D. Senior Associate Dean College of Graduate Studies Michael S. Bisesi, Ph.D. Date of Defense: April 10, 2009 Aneuploidy: Using genetic instability to preserve a haploid genome? Ramona Ramdath University of Toledo, Health Science Campus 2009 Dedication I dedicate this dissertation to my grandfather who died of lung cancer two years ago, but who always instilled in us the value and importance of education. And to my mom and sister, both of whom have been pillars of support and stimulating conversations. To my sister, Rehanna, especially- I hope this inspires you to achieve all that you want to in life, academically and otherwise. ii Acknowledgements As we go through these academic journeys, there are so many along the way that make an impact not only on our work, but on our lives as well, and I would like to say a heartfelt thank you to all of those people: My Committee members- Dr. James Trempe, Dr. David Giovanucchi, Dr. Ronald Mellgren and Dr. Randall Ruch for their guidance, suggestions, support and confidence in me. My major advisor- Dr. David Allison, for his constructive criticism and positive reinforcement. -
Table S2.Up Or Down Regulated Genes in Tcof1 Knockdown Neuroblastoma N1E-115 Cells Involved in Differentbiological Process Anal
Table S2.Up or down regulated genes in Tcof1 knockdown neuroblastoma N1E-115 cells involved in differentbiological process analysed by DAVID database Pop Pop Fold Term PValue Genes Bonferroni Benjamini FDR Hits Total Enrichment GO:0044257~cellular protein catabolic 2.77E-10 MKRN1, PPP2R5C, VPRBP, MYLIP, CDC16, ERLEC1, MKRN2, CUL3, 537 13588 1.944851 8.64E-07 8.64E-07 5.02E-07 process ISG15, ATG7, PSENEN, LOC100046898, CDCA3, ANAPC1, ANAPC2, ANAPC5, SOCS3, ENC1, SOCS4, ASB8, DCUN1D1, PSMA6, SIAH1A, TRIM32, RNF138, GM12396, RNF20, USP17L5, FBXO11, RAD23B, NEDD8, UBE2V2, RFFL, CDC GO:0051603~proteolysis involved in 4.52E-10 MKRN1, PPP2R5C, VPRBP, MYLIP, CDC16, ERLEC1, MKRN2, CUL3, 534 13588 1.93519 1.41E-06 7.04E-07 8.18E-07 cellular protein catabolic process ISG15, ATG7, PSENEN, LOC100046898, CDCA3, ANAPC1, ANAPC2, ANAPC5, SOCS3, ENC1, SOCS4, ASB8, DCUN1D1, PSMA6, SIAH1A, TRIM32, RNF138, GM12396, RNF20, USP17L5, FBXO11, RAD23B, NEDD8, UBE2V2, RFFL, CDC GO:0044265~cellular macromolecule 6.09E-10 MKRN1, PPP2R5C, VPRBP, MYLIP, CDC16, ERLEC1, MKRN2, CUL3, 609 13588 1.859332 1.90E-06 6.32E-07 1.10E-06 catabolic process ISG15, RBM8A, ATG7, LOC100046898, PSENEN, CDCA3, ANAPC1, ANAPC2, ANAPC5, SOCS3, ENC1, SOCS4, ASB8, DCUN1D1, PSMA6, SIAH1A, TRIM32, RNF138, GM12396, RNF20, XRN2, USP17L5, FBXO11, RAD23B, UBE2V2, NED GO:0030163~protein catabolic process 1.81E-09 MKRN1, PPP2R5C, VPRBP, MYLIP, CDC16, ERLEC1, MKRN2, CUL3, 556 13588 1.87839 5.64E-06 1.41E-06 3.27E-06 ISG15, ATG7, PSENEN, LOC100046898, CDCA3, ANAPC1, ANAPC2, ANAPC5, SOCS3, ENC1, SOCS4, -
Ykt6 Membrane-To-Cytosol Cycling Regulates Exosomal Wnt Secretion
bioRxiv preprint doi: https://doi.org/10.1101/485565; this version posted December 3, 2018. 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. Ykt6 membrane-to-cytosol cycling regulates exosomal Wnt secretion Karen Linnemannstöns1,2, Pradhipa Karuna1,2, Leonie Witte1,2, Jeanette Kittel1,2, Adi Danieli1,2, Denise Müller1,2, Lena Nitsch1,2, Mona Honemann-Capito1,2, Ferdinand Grawe3,4, Andreas Wodarz3,4 and Julia Christina Gross1,2* Affiliations: 1Hematology and Oncology, University Medical Center Goettingen, Goettingen, Germany. 2Developmental Biochemistry, University Medical Center Goettingen, Goettingen, Germany. 3Molecular Cell Biology, Institute I for Anatomy, University of Cologne Medical School, Cologne, Germany 4Cluster of Excellence-Cellular Stress Response in Aging-Associated Diseases (CECAD), Cologne, Germany *Correspondence: Dr. Julia Christina Gross, Hematology and Oncology/Developmental Biochemistry, University Medical Center Goettingen, Justus-von-Liebig Weg 11, 37077 Goettingen Germany Abstract Protein trafficking in the secretory pathway, for example the secretion of Wnt proteins, requires tight regulation. These ligands activate Wnt signaling pathways and are crucially involved in development and disease. Wnt is transported to the plasma membrane by its cargo receptor Evi, where Wnt/Evi complexes are endocytosed and sorted onto exosomes for long-range secretion. However, the trafficking steps within the endosomal compartment are not fully understood. The promiscuous SNARE Ykt6 folds into an auto-inhibiting conformation in the cytosol, but a portion associates with membranes by its farnesylated and palmitoylated C-terminus. Here, we demonstrate that membrane detachment of Ykt6 is essential for exosomal Wnt secretion. -
Integrating Protein Copy Numbers with Interaction Networks to Quantify Stoichiometry in Mammalian Endocytosis
bioRxiv preprint doi: https://doi.org/10.1101/2020.10.29.361196; this version posted October 29, 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-ND 4.0 International license. Integrating protein copy numbers with interaction networks to quantify stoichiometry in mammalian endocytosis Daisy Duan1, Meretta Hanson1, David O. Holland2, Margaret E Johnson1* 1TC Jenkins Department of Biophysics, Johns Hopkins University, 3400 N Charles St, Baltimore, MD 21218. 2NIH, Bethesda, MD, 20892. *Corresponding Author: [email protected] bioRxiv preprint doi: https://doi.org/10.1101/2020.10.29.361196; this version posted October 29, 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-ND 4.0 International license. Abstract Proteins that drive processes like clathrin-mediated endocytosis (CME) are expressed at various copy numbers within a cell, from hundreds (e.g. auxilin) to millions (e.g. clathrin). Between cell types with identical genomes, copy numbers further vary significantly both in absolute and relative abundance. These variations contain essential information about each protein’s function, but how significant are these variations and how can they be quantified to infer useful functional behavior? Here, we address this by quantifying the stoichiometry of proteins involved in the CME network. We find robust trends across three cell types in proteins that are sub- vs super-stoichiometric in terms of protein function, network topology (e.g. -
CD98 [19] Among Others [5][23]
bioRxiv preprint doi: https://doi.org/10.1101/2021.04.15.439921; this version posted April 18, 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 Physiological Substrates and Ontogeny-Specific Expression of the Ubiquitin Ligases 2 MARCH1 and MARCH8 3 4 Patrick Schriek1, Haiyin Liu1, Alan C. Ching1, Pauline Huang1, Nishma Gupta1, Kayla R. 5 Wilson1, MinHsuang Tsai1, Yuting Yan2, Christophe F. Macri1, Laura F. Dagley3,4, Giuseppe 6 Infusini3,4, Andrew I. Webb3,4, Hamish McWilliam1,2, Satoshi Ishido5, Justine D. Mintern1 and 7 Jose A. Villadangos1,2 8 9 1Department of Biochemistry and Pharmacology, Bio21 Molecular Science and Biotechnology 10 Institute, The University of Melbourne, Parkville, VIC 3010, Australia. 11 2Department of Microbiology and Immunology, Peter Doherty Institute for Infection and 12 Immunity, The University of Melbourne, Parkville, VIC 3010, Australia. 13 3Advanced Technology and Biology Division, The Walter and Eliza Hall Institute of Medical 14 Research, Parkville, VIC 3052, Australia. 15 4Department of Medical Biology, University of Melbourne, Parkville, VIC 3010, Australia. 16 5Department of Microbiology, Hyogo College of Medicine, 1-1 Mukogawa-cho, Nishinomiya 17 17 663-8501, Japan 18 19 20 21 Correspondence to Justine D. Mintern ([email protected]) or 22 Jose A. Villadangos ([email protected]) 1 bioRxiv preprint doi: https://doi.org/10.1101/2021.04.15.439921; this version posted April 18, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. -
Supplementary Material Table of Contents
Supplementary M aterial Table of Contents 1 - Online S u pplementary Methods ………………………………………………...… . …2 1.1 Study population……………………………………………………………..2 1.2 Quality control and principal component analysis …………………………..2 1.3 Statistical analyses………………………………………… ………………...3 1.3.1 Disease - specific association testing ……………………………… ..3 1.3.2 Cross - phenotype meta - analysis …………………………………… .3 1.3.3 Model search ……………………………………………………… .4 1.3.4 Novelty of the variants …………………………………………… ..4 1.3.5 Functional Enrichment Analy sis ………………………………… ...4 1.3.6 Drug Target Enrichment Analysis ………………………………… 5 2 - Supplementary Figures………………………………………...………………… . …. 7 3 - Members of the Myositis Genetics Consortium (MYOGEN) ……………………. ..16 4 - Members of the Scleroderma Genetics Consortium ………………… ……………...17 5 - Supplementary References………………………………………………………… . .18 6 - Supplementary Tables………………………………………………………… . ……22 1 Online supplementary m ethods Study population This study was conducted using 12,132 affected subjects and 23 ,260 controls of European des cent population and all of them have been included in previously published GWAS as summarized in Table S1. [1 - 6] Briefly, a total of 3,255 SLE cases and 9,562 ancestry matched controls were included from six countrie s across Europe and North America (Spain, Germany, Netherlands, Italy, UK, and USA). All of the included patients were diagnosed based on the standard American College of Rheumatology (ACR) classification criteria. [7] Previously described GWAS data from 2,363 SSc cases and 5,181 ancestry -
A High Throughput, Functional Screen of Human Body Mass Index GWAS Loci Using Tissue-Specific Rnai Drosophila Melanogaster Crosses Thomas J
Washington University School of Medicine Digital Commons@Becker Open Access Publications 2018 A high throughput, functional screen of human Body Mass Index GWAS loci using tissue-specific RNAi Drosophila melanogaster crosses Thomas J. Baranski Washington University School of Medicine in St. Louis Aldi T. Kraja Washington University School of Medicine in St. Louis Jill L. Fink Washington University School of Medicine in St. Louis Mary Feitosa Washington University School of Medicine in St. Louis Petra A. Lenzini Washington University School of Medicine in St. Louis See next page for additional authors Follow this and additional works at: https://digitalcommons.wustl.edu/open_access_pubs Recommended Citation Baranski, Thomas J.; Kraja, Aldi T.; Fink, Jill L.; Feitosa, Mary; Lenzini, Petra A.; Borecki, Ingrid B.; Liu, Ching-Ti; Cupples, L. Adrienne; North, Kari E.; and Province, Michael A., ,"A high throughput, functional screen of human Body Mass Index GWAS loci using tissue-specific RNAi Drosophila melanogaster crosses." PLoS Genetics.14,4. e1007222. (2018). https://digitalcommons.wustl.edu/open_access_pubs/6820 This Open Access Publication is brought to you for free and open access by Digital Commons@Becker. It has been accepted for inclusion in Open Access Publications by an authorized administrator of Digital Commons@Becker. For more information, please contact [email protected]. Authors Thomas J. Baranski, Aldi T. Kraja, Jill L. Fink, Mary Feitosa, Petra A. Lenzini, Ingrid B. Borecki, Ching-Ti Liu, L. Adrienne Cupples, Kari E. North, and Michael A. Province This open access publication is available at Digital Commons@Becker: https://digitalcommons.wustl.edu/open_access_pubs/6820 RESEARCH ARTICLE A high throughput, functional screen of human Body Mass Index GWAS loci using tissue-specific RNAi Drosophila melanogaster crosses Thomas J. -
A Study of Alterations in DNA Epigenetic Modifications (5Mc and 5Hmc) and Gene Expression Influenced by Simulated Microgravity I
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Digital Repository @ Iowa State University Genome Informatics Facility Publications Genome Informatics Facility 1-28-2016 A Study of Alterations in DNA Epigenetic Modifications (5mC and 5hmC) and Gene Expression Influenced by Simulated Microgravity in Human Lymphoblastoid Cells Basudev Chowdhury Purdue University Arun S. Seetharam Iowa State University, [email protected] Zhiping Wang Indiana University School of Medicine Yunlong Liu Indiana University School of Medicine Amy C. Lossie Purdue University See next page for additional authors Follow this and additional works at: https://lib.dr.iastate.edu/genomeinformatics_pubs Part of the Bioinformatics Commons, Genetics Commons, and the Genomics Commons Recommended Citation Chowdhury, Basudev; Seetharam, Arun S.; Wang, Zhiping; Liu, Yunlong; Lossie, Amy C.; Thimmapuram, Jyothi; and Irudayaraj, Joseph, "A Study of Alterations in DNA Epigenetic Modifications (5mC and 5hmC) and Gene Expression Influenced by Simulated Microgravity in Human Lymphoblastoid Cells" (2016). Genome Informatics Facility Publications. 4. https://lib.dr.iastate.edu/genomeinformatics_pubs/4 This Article is brought to you for free and open access by the Genome Informatics Facility at Iowa State University Digital Repository. It has been accepted for inclusion in Genome Informatics Facility Publications by an authorized administrator of Iowa State University Digital Repository. For more information, please contact [email protected]. A Study of Alterations in DNA Epigenetic Modifications (5mC and 5hmC) and Gene Expression Influenced by Simulated Microgravity in Human Lymphoblastoid Cells Abstract Cells alter their gene expression in response to exposure to various environmental changes. Epigenetic mechanisms such as DNA methylation are believed to regulate the alterations in gene expression patterns. -
Moreno-Layseca Et Al., Cargo-Specific Recruitment in Clathrin and Dynamin- Independent Endocytosis Supplementary Information
Moreno-Layseca et al., Cargo-specific recruitment in clathrin and dynamin- independent endocytosis Supplementary information Extended Data Figures 1-8 and associated legends Supplementary tables 1-2, supplementary videos and video legends 1-5, 1 Extended data figures and figure legends Extended Data Fig. 1. Swiprosin-1 (EFHD2, Swip1) is an interactor for Rab21. SILAC-MS analysis of Rab21 interactors from MDA-MB-231 cells expressing GFP-WT-Rab21 vs. GFP-DN- Rab21 (T31N inactive GDP-bound/nucleotide-free mutant) (A); GFP-CA-Rab21 (Q76L constitutively active GTP-bound mutant) vs. GFP (B); GFP-WT-Rab21 vs. GFP (C) or GFP-WT-Rab21 vs. GFP-CA-Rab21 (D). Each spot corresponds to one identified protein by mass spectrometry. Plots are representative of two independent experiments (forward and reverse, x- and y-axis), where every experiment consists of two independent affinity purifications. For example, in (A), swip1 is enriched by approx. 12.2x and 6.8x, and Arf1 is enriched 7.0x and 7.0x in the GFP-WT-Rab21 fraction compared to GFP-DN-Rab21 (forward and reverse experiment, respectively). In (B), swip1 is enriched about 4.4x and 11.5x, and Arf1 is enriched 3.9x and 5.5x. Swip1 was strongly enriched in the GFP-WT-Rab21 vs. GFP-DN-Rab21 (A) and GFP-CA-Rab21 and GFP- WT-Rab21 fractions compared to GFP fractions (B-C), and it was equally enriched in the GFP-CA-Rab21 compared to the GFP-WT-Rab21 fraction (D). Clathrin (CLTA, CLTB, CLTC), AP2 (AP2A1, AP2B1, AP2M1, AP2S1), caveolin (CAV1) and dynamin II (DNM2) are not strongly enriched in any fraction. -
Dynamics of Clathrin-Mediated Endocytosis and Its Requirement for Organelle Biogenesis in Dictyostelium
Research Article 5721 Dynamics of clathrin-mediated endocytosis and its requirement for organelle biogenesis in Dictyostelium Laura Macro, Jyoti K. Jaiswal* and Sanford M. Simon` Laboratory of Cellular Biophysics, The Rockefeller University, New York, NY 10065, USA *Present address: Center for Genetic Medicine Research, Children’s National Medical Center, Washington DC, DC 20010, USA `Author for correspondence ([email protected]) Accepted 21 August 2012 Journal of Cell Science 125, 5721–5732 ß 2012. Published by The Company of Biologists Ltd doi: 10.1242/jcs.108837 Summary The protein clathrin mediates one of the major pathways of endocytosis from the extracellular milieu and plasma membrane. In single-cell eukaryotes, such as Saccharomyces cerevisiae, the gene encoding clathrin is not an essential gene, raising the question of whether clathrin conveys specific advantages for multicellularity. Furthermore, in contrast to mammalian cells, endocytosis in S. cerevisiae is not dependent on either clathrin or adaptor protein 2 (AP2), an endocytic adaptor molecule. In this study, we investigated the requirement for components of clathrin-mediated endocytosis (CME) in another unicellular organism, the amoeba Dictyostelium. We identified a heterotetrameric AP2 complex in Dictyostelium that is similar to that which is found in higher eukaryotes. By simultaneously imaging fluorescently tagged clathrin and AP2, we found that, similar to higher eukaryotes, these proteins colocalized to membrane puncta that move into the cell together. In addition, the contractile vacuole marker protein, dajumin-green fluorescent protein (GFP), is trafficked via the cell membrane and internalized by CME in a clathrin-dependent, AP2-independent mechanism. This pathway is distinct from other endocytic mechanisms in Dictyostelium. -
Systematic Phenomics Analysis of Autism-Associated Genes Reveals Parallel Networks Underlying Reversible Impairments in Habituation
Systematic phenomics analysis of autism-associated genes reveals parallel networks underlying reversible impairments in habituation Troy A. McDiarmida, Manuel Belmadanib,c, Joseph Lianga, Fabian Meilia, Eleanor A. Mathewsd, Gregory P. Mullene, Ardalan Hendif, Wan-Rong Wongg, James B. Randd,h, Kota Mizumotof, Kurt Haasa, Paul Pavlidisa,b,c, and Catharine H. Rankina,i,1 aDjavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, BC V6T 2B5, Canada; bDepartment of Psychiatry, University of British Columbia, Vancouver, BC V6T 2A1, Canada; cMichael Smith Laboratories, University of British Columbia, Vancouver, BC V6T 1Z4, Canada; dGenetic Models of Disease Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK 73104; eBiology Program, Oklahoma City University, Oklahoma City, OK 73106; fDepartment of Zoology, University of British Columbia, Vancouver, BC V6T 1Z4, Canada; gDivision of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125; hOklahoma Center for Neuroscience, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104; and iDepartment of Psychology, University of British Columbia, Vancouver, BC V6T 1Z4, Canada Edited by Gene E. Robinson, University of Illinois at Urbana–Champaign, Urbana, IL, and approved October 25, 2019 (received for review July 16, 2019) A major challenge facing the genetics of autism spectrum disorders have dramatically increased the pace of gene discovery in ASD (ASDs) is the large and growing number of candidate risk genes and (5–9). There are now >100 diverse genes with established ties gene variants of unknown functional significance. Here, we used to ASD, many of which are being used in diagnosis. Impor- Caenorhabditis elegans to systematically functionally characterize tantly, each gene accounts for <1% of cases and none have ASD-associated genes in vivo.