Transcriptomic Signature and Metabolic Programming of Bovine Classical and Nonclassical Monocytes Indicate Distinct Functional Specializations
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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. -
Exploring Prostate Cancer Genome Reveals Simultaneous Losses of PTEN, FAS and PAPSS2 in Patients with PSA Recurrence After Radical Prostatectomy
Int. J. Mol. Sci. 2015, 16, 3856-3869; doi:10.3390/ijms16023856 OPEN ACCESS International Journal of Molecular Sciences ISSN 1422-0067 www.mdpi.com/journal/ijms Article Exploring Prostate Cancer Genome Reveals Simultaneous Losses of PTEN, FAS and PAPSS2 in Patients with PSA Recurrence after Radical Prostatectomy Chinyere Ibeawuchi 1, Hartmut Schmidt 2, Reinhard Voss 3, Ulf Titze 4, Mahmoud Abbas 5, Joerg Neumann 6, Elke Eltze 7, Agnes Marije Hoogland 8, Guido Jenster 9, Burkhard Brandt 10 and Axel Semjonow 1,* 1 Prostate Center, Department of Urology, University Hospital Muenster, Albert-Schweitzer-Campus 1, Gebaeude 1A, Muenster D-48149, Germany; E-Mail: [email protected] 2 Center for Laboratory Medicine, University Hospital Muenster, Albert-Schweitzer-Campus 1, Gebaeude 1A, Muenster D-48149, Germany; E-Mail: [email protected] 3 Interdisciplinary Center for Clinical Research, University of Muenster, Albert-Schweitzer-Campus 1, Gebaeude D3, Domagkstrasse 3, Muenster D-48149, Germany; E-Mail: [email protected] 4 Pathology, Lippe Hospital Detmold, Röntgenstrasse 18, Detmold D-32756, Germany; E-Mail: [email protected] 5 Institute of Pathology, Mathias-Spital-Rheine, Frankenburg Street 31, Rheine D-48431, Germany; E-Mail: [email protected] 6 Institute of Pathology, Klinikum Osnabrueck, Am Finkenhuegel 1, Osnabrueck D-49076, Germany; E-Mail: [email protected] 7 Institute of Pathology, Saarbrücken-Rastpfuhl, Rheinstrasse 2, Saarbrücken D-66113, Germany; E-Mail: [email protected] 8 Department -
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. -
In Silico Prediction and in Vitro Characterization of Multifunctional Human Rnase3
Hindawi Publishing Corporation BioMed Research International Volume 2013, Article ID 170398, 12 pages http://dx.doi.org/10.1155/2013/170398 Research Article In Silico Prediction and In Vitro Characterization of Multifunctional Human RNase3 Pei-Chun Lien,1 Ping-Hsueh Kuo,1 Chien-Jung Chen,1 Hsiu-Hui Chang,1 Shun-lung Fang,1 Wei-Shuo Wu,2 Yiu-Kay Lai,2 Tun-Wen Pai,3 and Margaret Dah-Tsyr Chang1, 4 1 InstituteofMolecularandCellularBiology,NationalTsingHuaUniversity,No.101,Section2,KuangFuRoad, Hsinchu 30013, Taiwan 2 Institute of Biotechnology, National Tsing Hua University, No. 101, Section 2, Kuang Fu Road, Hsinchu 30013, Taiwan 3 Department of Computer Science and Engineering, National Taiwan Ocean University, 2 Pei Ning Road, Keelung 20224, Taiwan 4 Department of Medical Science, National Tsing Hua University, No. 101, Section 2, Kuang Fu Road, Hsinchu 30013, Taiwan Correspondence should be addressed to Margaret Dah-Tsyr Chang; [email protected] Received 31 October 2012; Accepted 2 December 2012 Academic Editor: Hao-Teng Chang Copyright © 2013 Pei-Chun Lien et al. is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Human ribonucleases A (hRNaseA) superfamily consists of thirteen members with high-structure similarities but exhibits divergent physiological functions other than RNase activity. Evolution of hRNaseA superfamily has gained novel functions which may be preserved in a unique region or domain to account for additional molecular interactions. hRNase3 has multiple functions including ribonucleolytic, heparan sulfate (HS) binding, cellular binding, endocytic, lipid destabilization, cytotoxic, and antimicrobial activities. -
Dissecting the Non-Canonical Functions of P53 Through Novel Target Identification and P53 Acetylation
Dissecting the non-canonical functions of p53 through novel target identification and p53 acetylation Shang-Jui Wang Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy Under the Executive Committee of the Graduate School of Arts and Sciences COLUMBIA UNIVERSITY 2014 © 2014 Shang-Jui Wang All rights reserved ABSTRACT Dissecting the non-canonical functions of p53 through novel target identification and p53 acetylation Shang-Jui Wang It is well established that the p53 tumor suppressor plays a crucial role in controlling cell proliferation and apoptosis upon various types of stress. There is increasing evidence showing that p53 is also critically involved in various non-canonical pathways, including metabolism, autophagy, senescence and aging. Through a ChIP-on-chip screen, we identified a novel p53 metabolic target, pantothenate kinase-1 (PANK1). PanK1 catalyzes the rate-limiting step for CoA synthesis, and therefore, controls intracellular CoA content; Pank1 knockout mice exhibit defect in -oxidation and gluconeogenesis in the liver after starvation due to insufficient CoA levels. We demonstrated that PANK1 gene is a direct transcriptional target of p53. Although DNA damage-induced p53 upregulates PanK1 expression, depletion of PanK1 expression does not affect p53-dependent growth arrest or apoptosis. Interestingly, upon glucose starvation, PanK1 expression is significantly reduced in HCT116 p53 (-/-) but not in HCT116 p53 (+/+) cells, suggesting that p53 is required to maintain PanK1 expression under metabolic stress conditions. Moreover, by using p53-mutant mice, we observed that PanK activity and CoA levels are lower in livers of p53-null mice than that of wild-type mice upon starvation. -
Gene Ontology Functional Annotations and Pleiotropy
Network based analysis of genetic disease associations Sarah Gilman Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy under the Executive Committee of the Graduate School of Arts and Sciences COLUMBIA UNIVERSITY 2014 © 2013 Sarah Gilman All Rights Reserved ABSTRACT Network based analysis of genetic disease associations Sarah Gilman Despite extensive efforts and many promising early findings, genome-wide association studies have explained only a small fraction of the genetic factors contributing to common human diseases. There are many theories about where this “missing heritability” might lie, but increasingly the prevailing view is that common variants, the target of GWAS, are not solely responsible for susceptibility to common diseases and a substantial portion of human disease risk will be found among rare variants. Relatively new, such variants have not been subject to purifying selection, and therefore may be particularly pertinent for neuropsychiatric disorders and other diseases with greatly reduced fecundity. Recently, several researchers have made great progress towards uncovering the genetics behind autism and schizophrenia. By sequencing families, they have found hundreds of de novo variants occurring only in affected individuals, both large structural copy number variants and single nucleotide variants. Despite studying large cohorts there has been little recurrence among the genes implicated suggesting that many hundreds of genes may underlie these complex phenotypes. The question -
Unveiling the Multifaceted Antimicrobial Mechanism of Action of Human Host Defence Rnases
ADVERTIMENT. Lʼaccés als continguts dʼaquesta tesi queda condicionat a lʼacceptació de les condicions dʼús establertes per la següent llicència Creative Commons: http://cat.creativecommons.org/?page_id=184 ADVERTENCIA. El acceso a los contenidos de esta tesis queda condicionado a la aceptación de las condiciones de uso establecidas por la siguiente licencia Creative Commons: http://es.creativecommons.org/blog/licencias/ WARNING. The access to the contents of this doctoral thesis it is limited to the acceptance of the use conditions set by the following Creative Commons license: https://creativecommons.org/licenses/?lang=en Departament de Bioquímica, Biología Molecular i Biomedicina Unveiling the multifaceted antimicrobial mechanism of action of human host defence RNases Tesis presentada por Javier Arranz Trullén para optar al grado de Doctor en Bioquímica, Biología Molecular y Biomedicina bajo la dirección de la Dra. Ester Boix Borràs y el Dr. David Pulido Gómez Unitat de Biociències del Departament de Bioquímica i Biología Molecular. Universitat Autònoma de Barcelona Dra. Ester Boix Borràs Dr. David Pulido Gómez Javier Arranz Trullén Campus de Bellaterra, Septiembre 2016 1 2 Biochemistry, Molecular Biology and Biomedicine Department Unveiling the multifaceted antimicrobial mechanism of action of human host defence RNases Thesis presented by Javier Arranz Trullén to obtain the PhD in Biochemistry, Molecular Biology and Biomedicine directed by Dr. Ester Boix Borràs and Dr. David Pulido Gómez Biosciences Unit of the Biochemistry and Molecular -
Bioinformatics Analysis and Insights for the Role of COMMD7 in Hepatocellular Carcinoma
Bioinformatics Analysis and Insights for The Role of COMMD7 in Hepatocellular Carcinoma Xuehui Peng Army Medical University Yonggang He Army Medical University Xiaobing Huang Army Medical University Nan You Army Medical University Huiying Gu Army Medical University Rui Dong Army Medical University Xiaomin Yang Army Medical University Lu Zheng Army Medical University Jing Li ( [email protected] ) Army Medical University Research article Keywords: COMMD7, Hepatocellular carcinoma, tumor progression, NF-κB, CXCL10 Posted Date: October 6th, 2020 DOI: https://doi.org/10.21203/rs.3.rs-79438/v1 License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Page 1/20 Abstract Background: The tumorigenesis and development of hepatocellular carcinoma (HCC) is a process involving multiple factors. The COMMDs family proteins were reported to play important roles in various disease and cancers including HCC. We previously found COMMD7 acted as a HCC-promotion factor; however, further understanding on COMMD7 was needed. We conducted these bioinformatics analysis for the purpose of comprehensive understanding of the functional role of COMMD7 in HCC. Methods: The bioinformatics analysis of COMMD7 were launched by online platforms including KEGG, GEPIA, cBioportal, Gene Ontology and The Kaplan-Meier plotter. Data from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) were downloaded, and the data analysis and processing were conducted by RStudio (version 1.3.959) software. Results: The expression prole results of COMMD7 in TCGA and GTEx database suggested that COMMD7 expressed highly in liver tumor tissues and positively related with poorer prognosis (p<0.01); COMMD7 also contributed to the early development of HCC as its higher expression resulted in progression from stage I to stage III (p<0.01). -
Triangulating Molecular Evidence to Prioritise Candidate Causal Genes at Established Atopic Dermatitis Loci
medRxiv preprint doi: https://doi.org/10.1101/2020.11.30.20240838; this version posted November 30, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license . Triangulating molecular evidence to prioritise candidate causal genes at established atopic dermatitis loci Maria K Sobczyk1, Tom G Richardson1, Verena Zuber2,3, Josine L Min1, eQTLGen Consortium4, BIOS Consortium5, GoDMC, Tom R Gaunt1, Lavinia Paternoster1* 1) MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, UK 2) Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK 3) MRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK 4) Members of the eQTLGen Consortium are listed in: Supplementary_Consortium_members.docx 5) Members of the BIOS Consortium are listed in: Supplementary_Consortium_members.docx Abstract Background: Genome-wide association studies for atopic dermatitis (AD, eczema) have identified 25 reproducible loci associated in populations of European descent. We attempt to prioritise candidate causal genes at these loci using a multifaceted bioinformatic approach and extensive molecular resources compiled into a novel pipeline: ADGAPP (Atopic Dermatitis GWAS Annotation & Prioritisation Pipeline). Methods: We identified a comprehensive list of 103 accessible -
Single-Cell Transcriptomes Reveal a Complex Cellular Landscape in the Middle Ear and Differential Capacities for Acute Response to Infection
fgene-11-00358 April 9, 2020 Time: 15:55 # 1 ORIGINAL RESEARCH published: 15 April 2020 doi: 10.3389/fgene.2020.00358 Single-Cell Transcriptomes Reveal a Complex Cellular Landscape in the Middle Ear and Differential Capacities for Acute Response to Infection Allen F. Ryan1*, Chanond A. Nasamran2, Kwang Pak1, Clara Draf1, Kathleen M. Fisch2, Nicholas Webster3 and Arwa Kurabi1 1 Departments of Surgery/Otolaryngology, UC San Diego School of Medicine, VA Medical Center, La Jolla, CA, United States, 2 Medicine/Center for Computational Biology & Bioinformatics, UC San Diego School of Medicine, VA Medical Center, La Jolla, CA, United States, 3 Medicine/Endocrinology, UC San Diego School of Medicine, VA Medical Center, La Jolla, CA, United States Single-cell transcriptomics was used to profile cells of the normal murine middle ear. Clustering analysis of 6770 transcriptomes identified 17 cell clusters corresponding to distinct cell types: five epithelial, three stromal, three lymphocyte, two monocyte, Edited by: two endothelial, one pericyte and one melanocyte cluster. Within some clusters, Amélie Bonnefond, Institut National de la Santé et de la cell subtypes were identified. While many corresponded to those cell types known Recherche Médicale (INSERM), from prior studies, several novel types or subtypes were noted. The results indicate France unexpected cellular diversity within the resting middle ear mucosa. The resolution of Reviewed by: Fabien Delahaye, uncomplicated, acute, otitis media is too rapid for cognate immunity to play a major Institut Pasteur de Lille, France role. Thus innate immunity is likely responsible for normal recovery from middle ear Nelson L. S. Tang, infection. The need for rapid response to pathogens suggests that innate immune The Chinese University of Hong Kong, China genes may be constitutively expressed by middle ear cells. -
WO 2013/064702 A2 10 May 2013 (10.05.2013) P O P C T
(12) INTERNATIONAL APPLICATION PUBLISHED UNDER THE PATENT COOPERATION TREATY (PCT) (19) World Intellectual Property Organization I International Bureau (10) International Publication Number (43) International Publication Date WO 2013/064702 A2 10 May 2013 (10.05.2013) P O P C T (51) International Patent Classification: AO, AT, AU, AZ, BA, BB, BG, BH, BN, BR, BW, BY, C12Q 1/68 (2006.01) BZ, CA, CH, CL, CN, CO, CR, CU, CZ, DE, DK, DM, DO, DZ, EC, EE, EG, ES, FI, GB, GD, GE, GH, GM, GT, (21) International Application Number: HN, HR, HU, ID, IL, IN, IS, JP, KE, KG, KM, KN, KP, PCT/EP2012/071868 KR, KZ, LA, LC, LK, LR, LS, LT, LU, LY, MA, MD, (22) International Filing Date: ME, MG, MK, MN, MW, MX, MY, MZ, NA, NG, NI, 5 November 20 12 (05 .11.20 12) NO, NZ, OM, PA, PE, PG, PH, PL, PT, QA, RO, RS, RU, RW, SC, SD, SE, SG, SK, SL, SM, ST, SV, SY, TH, TJ, (25) Filing Language: English TM, TN, TR, TT, TZ, UA, UG, US, UZ, VC, VN, ZA, (26) Publication Language: English ZM, ZW. (30) Priority Data: (84) Designated States (unless otherwise indicated, for every 1118985.9 3 November 201 1 (03. 11.201 1) GB kind of regional protection available): ARIPO (BW, GH, 13/339,63 1 29 December 201 1 (29. 12.201 1) US GM, KE, LR, LS, MW, MZ, NA, RW, SD, SL, SZ, TZ, UG, ZM, ZW), Eurasian (AM, AZ, BY, KG, KZ, RU, TJ, (71) Applicant: DIAGENIC ASA [NO/NO]; Grenseveien 92, TM), European (AL, AT, BE, BG, CH, CY, CZ, DE, DK, N-0663 Oslo (NO). -
Downloaded Per Proteome Cohort Via the Web- Site Links of Table 1, Also Providing Information on the Deposited Spectral Datasets
www.nature.com/scientificreports OPEN Assessment of a complete and classifed platelet proteome from genome‑wide transcripts of human platelets and megakaryocytes covering platelet functions Jingnan Huang1,2*, Frauke Swieringa1,2,9, Fiorella A. Solari2,9, Isabella Provenzale1, Luigi Grassi3, Ilaria De Simone1, Constance C. F. M. J. Baaten1,4, Rachel Cavill5, Albert Sickmann2,6,7,9, Mattia Frontini3,8,9 & Johan W. M. Heemskerk1,9* Novel platelet and megakaryocyte transcriptome analysis allows prediction of the full or theoretical proteome of a representative human platelet. Here, we integrated the established platelet proteomes from six cohorts of healthy subjects, encompassing 5.2 k proteins, with two novel genome‑wide transcriptomes (57.8 k mRNAs). For 14.8 k protein‑coding transcripts, we assigned the proteins to 21 UniProt‑based classes, based on their preferential intracellular localization and presumed function. This classifed transcriptome‑proteome profle of platelets revealed: (i) Absence of 37.2 k genome‑ wide transcripts. (ii) High quantitative similarity of platelet and megakaryocyte transcriptomes (R = 0.75) for 14.8 k protein‑coding genes, but not for 3.8 k RNA genes or 1.9 k pseudogenes (R = 0.43–0.54), suggesting redistribution of mRNAs upon platelet shedding from megakaryocytes. (iii) Copy numbers of 3.5 k proteins that were restricted in size by the corresponding transcript levels (iv) Near complete coverage of identifed proteins in the relevant transcriptome (log2fpkm > 0.20) except for plasma‑derived secretory proteins, pointing to adhesion and uptake of such proteins. (v) Underrepresentation in the identifed proteome of nuclear‑related, membrane and signaling proteins, as well proteins with low‑level transcripts.