DOCSLIB.ORG

Chromatin Accessibility Landscape of Articular Knee Cartilage Reveals Aberrant

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Chromatin Accessibility Landscape of Articular Knee Cartilage Reveals Aberrant bioRxiv preprint doi: https://doi.org/10.1101/274043; this version posted March 1, 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 The copyright holder for this preprint (which was not certified by peer review) is the author/funder.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. 1 Chromatin accessibility landscape of articular knee cartilage reveals aberrant 2 enhancer regulation in osteoarthritis 3 4 Ye Liu1,2+, Jen-Chien Chang1+, Chung-Chau Hon3, Naoshi Fukui4,5, Nobuho Tanaka4, 5 Zhenya Zhang2, Ming Ta Michael Lee6,7,8*, Aki Minoda1* 6 7 1. Epigenome Technology Exploration Unit, Division of Genomic Technologies, 8 RIKEN Center for Life Science Technologies (CLST), Yokohama, Japan. 9 2. Graduate School of Life and Environmental Sciences, University of Tsukuba, 10 Tsukuba, Japan. 11 3. Genome Information Analysis Team, Division of Genomic Technologies, RIKEN 12 Center for Life Science Technologies (CLST), Yokohama, Japan. 13 4. Clinical Research Center, National Hospital Organization Sagamihara Hospital, 14 Kanagawa, Japan. 15 5. Department of Life Sciences, Graduate School of Arts and Sciences, The University 16 of Tokyo, Tokyo, Japan. 17 6. Genomic Medicine Institute, Geisinger, Danville, PA, USA. 18 7. Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan, ROC. 19 8. Laboratory for International Alliance on Genomic Research, RIKEN Center for 20 Integrative Medical Sciences, Yokohama, Japan. 21 22 + Authors contributed equally to this work 23 * Co-corresponding. Address correspondence to Aki Minoda, Epigenome Technology 24 Exploration Unit, Division of Genomic Technologies, RIKEN Center for Life Science 1 bioRxiv preprint doi: https://doi.org/10.1101/274043; this version posted March 1, 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 The copyright holder for this preprint (which was not certified by peer review) is the author/funder.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. 25 Technologies (CLST), 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan. 26 E-mail: [email protected]; Tel: 81-45-503-9309. 27 Ming Ta Michael Lee, Genomic Medicine Institute, Geisinger Health System, 100 N. 28 Academy Ave. Danville, PA, 17822, USA. E-mail: [email protected]; Tel: 1-570- 29 214-1005. 30 31 ABSTRACT 32 Background: Osteoarthritis (OA) is a common joint disorder with increasing impact 33 in an aging society; however, there is no cure or effective treatments so far due to lack 34 of sufficient understanding of its pathogenesis. While genome-wide association studies 35 (GWAS) and DNA methylation profiling identified many non-coding loci associated 36 to OA, the interpretation of them remains challenging. 37 Methods: Here, we employed Assay for Transposase-Accessible Chromatin with high 38 throughput sequencing (ATAC-seq) to map the accessible chromatin landscape in 39 articular knee cartilage of OA patients and to identify the chromatin signatures relevant 40 to OA. 41 Results: We identified 109,215 accessible chromatin regions in cartilage and 71% of 42 these regions were annotated as enhancers. We found these accessible chromatin 43 regions are enriched for OA GWAS single nucleotide polymorphisms (SNPs) and OA 44 differentially methylated loci, implying their relevance to OA. By linking these 45 enhancers to their potential target genes, we have identified a list of candidate enhancers 46 that may be relevant to OA. Through integration of ATAC-seq data with RNA-seq data, 47 we identified genes that are altered both at epigenomic and transcriptomic levels. These 48 genes are enriched in pathways regulating ossification and mesenchymal stem cell 49 (MSC) differentiation. Consistently, the differentially accessible regions in OA are 2 bioRxiv preprint doi: https://doi.org/10.1101/274043; this version posted March 1, 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. 50 enriched for mesenchymal stem cell-specific enhancers and motifs of transcription 51 factor families involved in osteoblast differentiation (e.g. bZIP and ETS). 52 Conclusions: This study marks the first investigation of accessible chromatin 53 landscape on clinically relevant hard tissues and demonstrates how accessible 54 chromatin profiling can provide comprehensive epigenetic information of a disease. 55 Our analyses provide supportive evidence towards the model of endochondral 56 ossification-like cartilage-to-bone conversion in OA knee cartilage, which is consistent 57 with the OA characteristic of thicker subchondral bone. The identified OA-relevant 58 genes and their enhancers may have a translational potential for diagnosis or drug 59 targets. 60 61 Keywords 62 osteoarthritis, epigenomics, enhancer, ATAC-seq, endochondral ossification. 63 64 Background 65 Osteoarthritis (OA) is a degenerative joint disease [1,2] that is one of the most common 66 causes of chronic disability in the world [3,4], of which the knee OA is the most 67 common. Main features of OA include cartilage degradation, subchondral bone 68 thickening, joint space narrowing and osteophytes formation [5], resulting in stiffness, 69 swelling, and pain in the joint. Currently available treatments are either pain relief or 70 joint function improvement by strengthening the supporting muscles. However, OA 71 progression ultimately leads to costly total joint replacement surgery, making it a 72 growing global health burden. 73 Although the causes of OA are not well understood, risk factors such as age, 74 weight, gender, and genetic factors have been identified [4]. Several models for OA 75 initiation, such as mechanical injury, inflammatory mediators from synovium, defects 3 bioRxiv preprint doi: https://doi.org/10.1101/274043; this version posted March 1, 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. 76 in metabolism and endochondral ossification, have been proposed to explain 77 pathogenesis of this disease [6–12]. To date, GWAS have identified more than 20 loci 78 to be associated with the risk of developing OA [13]. While next generation sequencing 79 data is being generated to discover rare variants with larger effect size, the identified 80 variants are often located in the non-coding regions of the genome [14], complicating 81 the identification of the causal genes. Transcriptomic analyses of cartilage in diseased 82 joints of OA patients (taken from the replacement surgeries) provided an opportunity 83 to pinpoint transcriptionally dysregulated genes and pathways relevant to OA [15,16]. 84 However, such studies have yet to fully reveal the underlying molecular mechanism of 85 how the transcription of these genes are dysregulated. 86 Recently, epigenetic tools have been applied to gain further insight into the 87 pathogenesis of OA. There have been several reports of DNA methylation status [17– 88 19] in cartilage of diseased joints. However, relatively few DNA methylation 89 alterations were found in OA degenerated tissues, despite many genes being 90 differentially expressed. Consistent with these findings, it was also found that change 91 of gene expression is rarely associated with DNA methylation alterations at promoters 92 [16,19,20]. Many of the identified differentially methylated sites in fact fall in enhancer 93 regions, which are non-coding regulatory elements, disruption of which may lead to 94 dysregulated transcription, and many are cell type-specific [21,22]. Recent large-scale 95 studies, such as FANTOM5 [23], Roadmap Epigenomics Project [24] and GTEx [25] 96 have enabled the prediction of regulatory networks between enhancers and their 97 potential target genes (e.g. JEME [26]), which could be applied in a clinical context to 98 explore the roles of enhancers in disease pathogenesis. 99 Here, we set out to investigate alterations of enhancers associated with OA by 100 applying ATAC-seq [27] on the knee joint cartilages from OA patients, using an 4 bioRxiv preprint doi: https://doi.org/10.1101/274043; this version posted March 1, 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. 101 optimized protocol for cartilage sample preparation. ATAC-seq maps the accessible 102 chromatin regions, which are often regulatory regions such as promoters and enhancers 103 that play roles in regulation of gene expression. By integrating our ATAC-seq data with 104 the publicly available genetic, transcriptomic and epigenomic data, we identified 105 dysregulated enhancers and their potential target genes. Our data highlights a number 106 of OA risk loci and differentially methylated loci that potentially play roles in cartilage 107 degradation during OA development. 108 109 Methods 110 Knee joint tissues collection 111 Human knee joint tibial plates were collected from patients who undertook joint 112 replacement surgery due to severe primary OA at the National Hospital Organization 113 Sagamihara Hospital (Kanagawa, Japan). Demographic information for patients is 114 listed in Additional file 1: Table S1. Diagnosis of OA was based on the criteria of the 115 American College of Rheumatology [28], and all the knees were medially involved in 116 the disease. Tissues were stored in 4°C cultured medium after removal. Informed 117 consent was obtained from each patient enrolled in this study. This study was approved 118 by the institutional review board of all the participating institutions (Sagamihara 119 National Hospital and RIKEN). 120 121 Processing of cartilage samples 122 Fresh cartilage was separated from the subchondral bone by a scalpel immediately after 123 surgery and stored in 4°C Dulbecco's Modified Eagle Medium until they were 124 processed. 100 mg cartilage from both outer region of lateral tibial plateau (oLT) and 125 inner region of medial tibial plateau (iMT) (Fig. 1a and Additional file 2: Figure S1a) 5 bioRxiv preprint doi: https://doi.org/10.1101/274043; this version posted March 1, 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.
Load more

Recommended publications
  • Supplemental Table 1. Complete Gene Lists and GO Terms from Figure 3C
    Supplemental Table 1. Complete gene lists and GO terms from Figure 3C. Path 1 Genes: RP11-34P13.15, RP4-758J18.10, VWA1, CHD5, AZIN2, FOXO6, RP11-403I13.8, ARHGAP30, RGS4, LRRN2, RASSF5, SERTAD4, GJC2, RHOU, REEP1, FOXI3, SH3RF3, COL4A4, ZDHHC23, FGFR3, PPP2R2C, CTD-2031P19.4, RNF182, GRM4, PRR15, DGKI, CHMP4C, CALB1, SPAG1, KLF4, ENG, RET, GDF10, ADAMTS14, SPOCK2, MBL1P, ADAM8, LRP4-AS1, CARNS1, DGAT2, CRYAB, AP000783.1, OPCML, PLEKHG6, GDF3, EMP1, RASSF9, FAM101A, STON2, GREM1, ACTC1, CORO2B, FURIN, WFIKKN1, BAIAP3, TMC5, HS3ST4, ZFHX3, NLRP1, RASD1, CACNG4, EMILIN2, L3MBTL4, KLHL14, HMSD, RP11-849I19.1, SALL3, GADD45B, KANK3, CTC- 526N19.1, ZNF888, MMP9, BMP7, PIK3IP1, MCHR1, SYTL5, CAMK2N1, PINK1, ID3, PTPRU, MANEAL, MCOLN3, LRRC8C, NTNG1, KCNC4, RP11, 430C7.5, C1orf95, ID2-AS1, ID2, GDF7, KCNG3, RGPD8, PSD4, CCDC74B, BMPR2, KAT2B, LINC00693, ZNF654, FILIP1L, SH3TC1, CPEB2, NPFFR2, TRPC3, RP11-752L20.3, FAM198B, TLL1, CDH9, PDZD2, CHSY3, GALNT10, FOXQ1, ATXN1, ID4, COL11A2, CNR1, GTF2IP4, FZD1, PAX5, RP11-35N6.1, UNC5B, NKX1-2, FAM196A, EBF3, PRRG4, LRP4, SYT7, PLBD1, GRASP, ALX1, HIP1R, LPAR6, SLITRK6, C16orf89, RP11-491F9.1, MMP2, B3GNT9, NXPH3, TNRC6C-AS1, LDLRAD4, NOL4, SMAD7, HCN2, PDE4A, KANK2, SAMD1, EXOC3L2, IL11, EMILIN3, KCNB1, DOK5, EEF1A2, A4GALT, ADGRG2, ELF4, ABCD1 Term Count % PValue Genes regulation of pathway-restricted GDF3, SMAD7, GDF7, BMPR2, GDF10, GREM1, BMP7, LDLRAD4, SMAD protein phosphorylation 9 6.34 1.31E-08 ENG pathway-restricted SMAD protein GDF3, SMAD7, GDF7, BMPR2, GDF10, GREM1, BMP7, LDLRAD4, phosphorylation
    [Show full text]
  • Exploring Autophagy with Gene Ontology
    Autophagy ISSN: 1554-8627 (Print) 1554-8635 (Online) Journal homepage: https://www.tandfonline.com/loi/kaup20 Exploring autophagy with Gene Ontology Paul Denny, Marc Feuermann, David P. Hill, Ruth C. Lovering, Helene Plun- Favreau & Paola Roncaglia To cite this article: Paul Denny, Marc Feuermann, David P. Hill, Ruth C. Lovering, Helene Plun- Favreau & Paola Roncaglia (2018) Exploring autophagy with Gene Ontology, Autophagy, 14:3, 419-436, DOI: 10.1080/15548627.2017.1415189 To link to this article: https://doi.org/10.1080/15548627.2017.1415189 © 2018 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. View supplementary material Published online: 17 Feb 2018. Submit your article to this journal Article views: 1097 View Crossmark data Full Terms & Conditions of access and use can be found at https://www.tandfonline.com/action/journalInformation?journalCode=kaup20 AUTOPHAGY, 2018 VOL. 14, NO. 3, 419–436 https://doi.org/10.1080/15548627.2017.1415189 RESEARCH PAPER - BASIC SCIENCE Exploring autophagy with Gene Ontology Paul Denny a,†,§, Marc Feuermann b,§, David P. Hill c,f,§, Ruth C. Lovering a,§, Helene Plun-Favreau d and Paola Roncaglia e,f,§ aFunctional Gene Annotation, Institute of Cardiovascular Science, University College London, London, UK; bSIB Swiss Institute of Bioinformatics, Geneva, Switzerland; cThe Jackson Laboratory, Bar Harbor, ME, USA; dDepartment of Molecular Neuroscience, UCL Institute of Neurology, London, UK; eEuropean Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory, Wellcome Genome Campus, Hinxton, Cambridge, UK; fThe Gene Ontology Consortium ABSTRACT ARTICLE HISTORY Autophagy is a fundamental cellular process that is well conserved among eukaryotes. It is one of the Received 18 May 2017 strategies that cells use to catabolize substances in a controlled way.
    [Show full text]
  • 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.
    [Show full text]
  • Molecular Targeting and Enhancing Anticancer Efficacy of Oncolytic HSV-1 to Midkine Expressing Tumors
    University of Cincinnati Date: 12/20/2010 I, Arturo R Maldonado , hereby submit this original work as part of the requirements for the degree of Doctor of Philosophy in Developmental Biology. It is entitled: Molecular Targeting and Enhancing Anticancer Efficacy of Oncolytic HSV-1 to Midkine Expressing Tumors Student's name: Arturo R Maldonado This work and its defense approved by: Committee chair: Jeffrey Whitsett Committee member: Timothy Crombleholme, MD Committee member: Dan Wiginton, PhD Committee member: Rhonda Cardin, PhD Committee member: Tim Cripe 1297 Last Printed:1/11/2011 Document Of Defense Form Molecular Targeting and Enhancing Anticancer Efficacy of Oncolytic HSV-1 to Midkine Expressing Tumors A dissertation submitted to the Graduate School of the University of Cincinnati College of Medicine in partial fulfillment of the requirements for the degree of DOCTORATE OF PHILOSOPHY (PH.D.) in the Division of Molecular & Developmental Biology 2010 By Arturo Rafael Maldonado B.A., University of Miami, Coral Gables, Florida June 1993 M.D., New Jersey Medical School, Newark, New Jersey June 1999 Committee Chair: Jeffrey A. Whitsett, M.D. Advisor: Timothy M. Crombleholme, M.D. Timothy P. Cripe, M.D. Ph.D. Dan Wiginton, Ph.D. Rhonda D. Cardin, Ph.D. ABSTRACT Since 1999, cancer has surpassed heart disease as the number one cause of death in the US for people under the age of 85. Malignant Peripheral Nerve Sheath Tumor (MPNST), a common malignancy in patients with Neurofibromatosis, and colorectal cancer are midkine- producing tumors with high mortality rates. In vitro and preclinical xenograft models of MPNST were utilized in this dissertation to study the role of midkine (MDK), a tumor-specific gene over- expressed in these tumors and to test the efficacy of a MDK-transcriptionally targeted oncolytic HSV-1 (oHSV).
    [Show full text]
  • RNA Sequencing Analyses Reveal Differentially Expressed Genes and Pathways As Notch2 Targets in B-Cell Lymphoma
    www.oncotarget.com Oncotarget, 2020, Vol. 11, (No. 48), pp: 4527-4540 Research Paper RNA sequencing analyses reveal differentially expressed genes and pathways as Notch2 targets in B-cell lymphoma Ashok Arasu1, Pavithra Balakrishnan1 and Thirunavukkarasu Velusamy1 1Department of Biotechnology, School of Biotechnology and Genetic Engineering, Bharathiar University, Coimbatore, India Correspondence to: Thirunavukkarasu Velusamy, email: [email protected] Keywords: SMZL; Notch2; RNA sequencing; PI3K/AKT; NF-kB Received: August 04, 2020 Accepted: October 17, 2020 Published: December 01, 2020 Copyright: © 2020 Arasu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. ABSTRACT Splenic marginal zone lymphoma (SMZL) is a low grade, indolent B-cell neoplasm that comprises approximately 10% of all lymphoma. Notch2, a pivotal gene for marginal zone differentiation is found to be mutated in SMZL. Deregulated Notch2 signaling has been involved in tumorigenesis and also in B-cell malignancies. However the role of Notch2 and the downstream pathways that it influences for development of B-cell lymphoma remains unclear. In recent years, RNA sequencing (RNA-Seq) has become a functional and convincing technology for profiling gene expression and to discover new genes and transcripts that are involved in disease development in a single experiment. In the present study, using transcriptome sequencing approach, we have identified key genes and pathways that are probably the underlying cause in the development of B-cell lymphoma. We have identified a total of 15,083 differentially expressed genes (DEGs) and 1067 differentially expressed transcripts (DETs) between control and Notch2 knockdown B cells.
    [Show full text]
  • Differentially Expressed Genes in Aneurysm Tissue Compared With
    On-line Table: Differentially expressed genes in aneurysm tissue compared with those in control tissue Fold False Discovery Direction of Gene Entrez Gene Name Function Change P Value Rate (q Value) Expression AADAC Arylacetamide deacetylase Positive regulation of triglyceride 4.46 1.33E-05 2.60E-04 Up-regulated catabolic process ABCA6 ATP-binding cassette, subfamily A (ABC1), Integral component of membrane 3.79 9.15E-14 8.88E-12 Up-regulated member 6 ABCC3 ATP-binding cassette, subfamily C (CFTR/MRP), ATPase activity, coupled to 6.63 1.21E-10 7.33E-09 Up-regulated member 3 transmembrane movement of substances ABI3 ABI family, member 3 Peptidyl-tyrosine phosphorylation 6.47 2.47E-05 4.56E-04 Up-regulated ACKR1 Atypical chemokine receptor 1 (Duffy blood G-protein–coupled receptor signaling 3.80 7.95E-10 4.18E-08 Up-regulated group) pathway ACKR2 Atypical chemokine receptor 2 G-protein–coupled receptor signaling 0.42 3.29E-04 4.41E-03 Down-regulated pathway ACSM1 Acyl-CoA synthetase medium-chain family Energy derivation by oxidation of 9.87 1.70E-08 6.52E-07 Up-regulated member 1 organic compounds ACTC1 Actin, ␣, cardiac muscle 1 Negative regulation of apoptotic 0.30 7.96E-06 1.65E-04 Down-regulated process ACTG2 Actin, ␥2, smooth muscle, enteric Blood microparticle 0.29 1.61E-16 2.36E-14 Down-regulated ADAM33 ADAM domain 33 Integral component of membrane 0.23 9.74E-09 3.95E-07 Down-regulated ADAM8 ADAM domain 8 Positive regulation of tumor necrosis 4.69 2.93E-04 4.01E-03 Up-regulated factor (ligand) superfamily member 11 production ADAMTS18
    [Show full text]
  • Identification of a Novel Autophagy Signature for Predicting Survival in Patients with Lung Adenocarcinoma
    Identification of a novel autophagy signature for predicting survival in patients with lung adenocarcinoma Jin Duan1,*, Youming Lei1,*, Guoli Lv1, Yinqiang Liu1, Wei Zhao1, Qingmei Yang1, Xiaona Su2, Zhijian Song3, Leilei Lu3 and Yunfei Shi1 1 Department of Geriatric Thoracic Surgery, The First Hospital of Kunming Medical University, Kunming City, Yunnan Province, P.R. China 2 Department of Cancer Center, Daping Hospital, Army Medical University, Chongqing, China 3 Origimed Co. Ltd., Shanghai, P.R. China * These authors contributed equally to this work. ABSTRACT Background. Lung adenocarcinoma (LUAD) is the most commonhistological lung cancer subtype, with an overall five-year survivalrate of only 17%. In this study, we aimed to identify autophagy-related genes (ARGs) and develop an LUAD prognostic signature. Methods. In this study, we obtained ARGs from three databases and downloaded gene expression profiles from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. We used TCGA-LUAD (n D 490) for a training and testing dataset, and GSE50081( n D 127) as the external validation dataset.The least absolute shrinkage and selection operator (LASSO) Cox and multivariate Cox regression models were used to generate an autophagy-related signature. We performed gene set enrichment analysis (GSEA) and immune cell analysis between the high- and low-risk groups. A nomogram was built to guide the individual treatment for LUAD patients. Results. We identified a total of 83 differentially expressed ARGs (DEARGs) from the TCGA-LUAD dataset, including 33 upregulated DEARGs and 50 downregulated DEARGs, both with thresholds of adjusted P < 0:05 and jFold changej > 1:5. Using LASSO and multivariate Cox regression analyses, we identified 10 ARGs that we used Submitted 1 May 2020 to build a prognostic signature with areas under the curve (AUCs) of 0.705, 0.715, Accepted 17 February 2021 Published 21 April 2021 and 0.778 at 1, 3, and 5 years, respectively.
    [Show full text]
  • Transcriptome Study of Muscle Tissue in Nellore Cattle Divergent for Beef Quality
    UNIVERSIDADE ESTADUAL PAULISTA - UNESP CÂMPUS DE JABOTICABAL TRANSCRIPTOME STUDY OF MUSCLE TISSUE IN NELLORE CATTLE DIVERGENT FOR BEEF QUALITY Maria Malane Magalhães Muniz Zootecnista 2020 ii UNIVERSIDADE ESTADUAL PAULISTA - UNESP CÂMPUS DE JABOTICABAL TRANSCRIPTOME STUDY OF MUSCLE TISSUE IN NELLORE CATTLE DIVERGENT FOR BEEF QUALITY Maria Malane Magalhães Muniz Orientadora: Profa. Dra. Lucia Galvão de Albuquerque Coorientadora: Dra. Larissa Fernanda Simielli Fonseca Tese apresentada à Faculdade de Ciências Agrárias e Veterinárias – Unesp, Câmpus de Jaboticabal, como parte das exigências para a obtenção do título de Doutor Genética e Melhoramento Animal 2020 iii iv v DADOS CURRICULARES DO AUTOR Maria Malane Magalhães Muniz – Nasceu em Camocim, Ceará em 19 de Outubro de 1988, filha de Lucia Maria Magalhães e Manoel Gonçalves Muniz. Iniciou sua graduação em Zootecnia na Universidade Estadual Vale do Acarau (UVA), Câmpus Central de Sobral em agosto de 2009. Durante a graduação (2009-2012) participou de projetos científicos, foi bolsista EMBRAPA e CNPq, monitora na disciplina Melhoramento Genético Animal e recebeu certificado de Mérito Acadêmico por ter obtido o primeiro lugar na apresentação de trabalhos no curso de Bacharelado em Zootecnia-UVA. Em Março de 2013, iniciou seu mestrado no programa de pós-graduação em Ciências Animais da Universidade de Brasília- UNB, onde foi bolsista CNPq. Durante o mestrado dedicou-se a estudo de associação ampla do genoma para coloração de pelagem em ovinos da raça Morada Nova, sob orientação do pesquisador Dr. Samuel Rezende Paiva, recebendo o título de mestra em Março de 2015. Foi professora (2015-2016) nos programas de gradução em Agronomia e Medicina Veterinária no Centro Universitário ICESP - Águas Claras-DF.
    [Show full text]
  • Chromatin Accessibility Landscape of Articular Knee Cartilage Reveals
    www.nature.com/scientificreports OPEN Chromatin accessibility landscape of articular knee cartilage reveals aberrant enhancer regulation in Received: 20 March 2018 Accepted: 4 October 2018 osteoarthritis Published: xx xx xxxx Ye Liu1,2,3, Jen-Chien Chang 1,2, Chung-Chau Hon 4,5, Naoshi Fukui6,7, Nobuho Tanaka6, Zhenya Zhang3, Ming Ta Michael Lee 8,9,10 & Aki Minoda 1,2 Osteoarthritis (OA) is a common joint disorder with increasing impact in an aging society. While genetic and transcriptomic analyses have revealed some genes and non-coding loci associated to OA, the pathogenesis remains incompletely understood. Chromatin profling, which provides insight into gene regulation, has not been reported in OA mainly due to technical difculties. Here, we employed Assay for Transposase-Accessible Chromatin with high throughput sequencing (ATAC-seq) to map the accessible chromatin landscape in articular knee cartilage of OA patients. We identifed 109,215 accessible chromatin regions for cartilages, of which 71% were annotated as enhancers. By overlaying them with genetic and DNA methylation data, we have determined potential OA-relevant enhancers and their putative target genes. Furthermore, through integration with RNA-seq data, we characterized genes that are altered both at epigenomic and transcriptomic levels in OA. These genes are enriched in pathways regulating ossifcation and mesenchymal stem cell (MSC) diferentiation. Consistently, the diferentially accessible regions in OA are enriched for MSC-specifc enhancers and motifs of transcription factor families involved in osteoblast diferentiation. In conclusion, we demonstrate how direct chromatin profling of clinical tissues can provide comprehensive epigenetic information for a disease and suggest candidate genes and enhancers of translational potential.
    [Show full text]
  • Computational Analysis in Vivo P53 Binding Sites in the Context of Chromatin and Repeat Regions
    Rochester Institute of Technology RIT Scholar Works Theses 12-1-2016 Computational analysis in vivo p53 binding sites in the context of chromatin and repeat regions Feifei Bao Follow this and additional works at: https://scholarworks.rit.edu/theses Recommended Citation Bao, Feifei, "Computational analysis in vivo p53 binding sites in the context of chromatin and repeat regions" (2016). Thesis. Rochester Institute of Technology. Accessed from This Thesis is brought to you for free and open access by RIT Scholar Works. It has been accepted for inclusion in Theses by an authorized administrator of RIT Scholar Works. For more information, please contact [email protected]. Computational analysis in vivo p53 binding sites in the context of chromatin and repeat regions By Feifei Bao A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Bioinformatics at the Rochester Institute of Technology R·I·T Bioinformatics Program Thomas H. Gosnell School of Life Sciences College of Science Rochester Institute of Technology Rochester, NY 1 December 2016 Committee Signatures The undersigned state that Feifei Bao, a candidate for the Master of Science degree in Bioinformatics, has submitted her thesis and has satisfactorily defended it. This completes the requirements for the Master of Science degree in Bioinformatics at Rochester Institute of Technology. Feng Cui, Ph.D. Date Adviser Gary R. Skuse, Ph.D. Date Committee Member Gregory Babbitt, Ph.D. Date Committee Member II Table of Contents LIST OF FIGURES
    [Show full text]
  • Download Date 06/10/2021 23:47:26
    Multi-omic analysis of hearing difficulty risk loci and gene regulatory networks in the mammalian cochlea Item Type dissertation Authors Kalra, Gurmannat Publication Date 2021 Abstract The sensory cells of the mammalian cochlea do not have the capacity to regenerate. Studies have identified some genes and pathways that are critical for hair cell formation; however, the conditions necessary to regenerate fully functional hair cells ... Keywords Cochlea; Gene Regulatory Networks; Hair Cells, Auditory; Hearing Loss--genetics; Systems Biology Download date 06/10/2021 23:47:26 Link to Item http://hdl.handle.net/10713/15776 CURRICULUM VITAE GURMANNAT KALRA [email protected] EDUCATION University of Maryland, Baltimore, MD Aug 2016 – May 2021 Ph.D. Candidate, Program in Molecular Medicine, Genome Biology track Dissertation: Multi-omic analysis of hearing difficulty risk loci and gene regulatory networks in the mammalian cochlea Rowan University, Glassboro, NJ Sept 2012- May 2016 B.S. in Biochemistry Magna Cum Laude Bantivoglio Honors Concentration RESEARCH EXPERIENCE Graduate Research Assistant University of Maryland, Baltimore Dec 2016 – May 2021 Project: Investigate the genetics and genomics of hearing loss (HRP Funded, PI: Seth Ament, Ph.D.) • Combine open chromatin data from neonatal mouse with GWAS of hearing difficulty to identify the enrichment of hearing difficulty risk loci in coding and regulatory regions in cochlear epithelial and non-epithelial cells. • Using mouse single cell RNA-seq data, identify differential gene expression in the different cell types in the cochlea and utricle. • Use single cell RNA-seq data to reconstruct and identify gene regulatory networks that drive transdifferentiation of supporting cells to hair cells.
    [Show full text]
  • Aberrant DNA Methylation Results in Altered Gene Expression in Non-Alcoholic Steatohepatitis-Related Hepatocellular Carcinomas
    Journal of Cancer Research and Clinical Oncology (2020) 146:2461–2477 https://doi.org/10.1007/s00432-020-03298-4 ORIGINAL ARTICLE – CANCER RESEARCH Aberrant DNA methylation results in altered gene expression in non‑alcoholic steatohepatitis‑related hepatocellular carcinomas Ying Tian1 · Eri Arai1 · Satomi Makiuchi1 · Noboru Tsuda1 · Junko Kuramoto1 · Kentaro Ohara1 · Yoriko Takahashi2 · Nanako Ito1 · Hidenori Ojima1 · Nobuyoshi Hiraoka3 · Masahiro Gotoh4 · Teruhiko Yoshida4 · Yae Kanai1 Received: 30 January 2020 / Accepted: 20 June 2020 / Published online: 19 July 2020 © The Author(s) 2020 Abstract Purpose The aim of this study was to investigate DNA methylation alterations in non-alcoholic steatohepatitis (NASH)- related hepatocellular carcinomas (HCCs). Methods Genome-wide DNA methylation analysis was performed using the Infnium Human Methylation 450 K BeadChip, and levels of mRNA expression were analyzed by quantitative reverse transcription-PCR. Results Compared to 36 samples of normal control liver tissue (C), DNA methylation alterations were observed on 19,281 probes in 22 samples of cancerous tissue (T) obtained from patients showing histological features compatible with NASH in their non-cancerous liver tissue (N). Among those probes, 1396 were located within CpG islands or their shores and shelves, designed around the transcription start sites of 726 genes. In representative genes, such as DCAF4L2, CKLF, TRIM4, PRC1, UBE2C and TUBA1B, both DNA hypomethylation and mRNA overexpression were observed in T samples relative to C samples, and the levels of DNA methylation and mRNA expression were inversely correlated with each other. DNA hypomethylation occurred even in N samples at the precancerous NASH stage, and this was inherited by or further strength- ened in T samples.
    [Show full text]