DNA Methylation Profiling of the X Chromosome Reveals an Aberrant
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Applicability of Multidimensional Fractionation to Affinity Purification Mass Spectrometry Samples and Protein Phosphatase 4 Substrate Identification
Applicability of Multidimensional Fractionation to Affinity Purification Mass Spectrometry Samples and Protein Phosphatase 4 Substrate Identification by Wade Hampton Dunham A thesis submitted in conformity with the requirements for the degree of Master of Science Department of Molecular Genetics University of Toronto © Copyright by Wade Dunham 2012 ii Applicability of Multidimensional Fractionation to Affinity Purification Mass Spectrometry Samples and Protein Phosphatase 4 Substrate Identification Wade Dunham Master of Science Department of Molecular Genetics University of Toronto 2012 Abstract Affinity-purification coupled to mass spectrometry (AP-MS) is gaining widespread use for the identification of protein-protein interactions. It is unclear however, whether typical AP sample complexity is limiting for the identification of all protein components using standard one-dimensional LC-MS/MS. Multidimensional sample separation is a useful for reducing sample complexity prior to MS analysis, and increases peptide and protein coverage of complex samples, yet the applicability of this approach to AP-MS samples remains unknown. Here I present work to show that multidimensional separation of AP-MS samples is not a cost-effective method for identifying increased peptide or protein coverage in these sample types. As such this approach was not adapted for the identification of putative Phosphoprotein Phosphatase 4 (PP4c) substrates. Instead, affinity purification coupled to one- dimensional LC-MS/MS was used to identify putative PP4c substrates, and semi- quantitative methods applied to identify possible PP4c targeted phosphosites in PP2A subfamily phosphatase inhibited (okadaic acid treated) cells. iii Acknowledgments I would like to acknowledge and thank everyone in the Gingras lab, in particular my supervisor Anne-Claude, for allowing me to take on complex projects and to be an integral part in the pursuit of high impact publications. -
Escape from X Chromosome Inactivation Is an Intrinsic Property of the Jarid1c Locus
Escape from X chromosome inactivation is an intrinsic property of the Jarid1c locus Nan Lia,b and Laura Carrela,1 aDepartment of Biochemistry and Molecular Biology and bIntercollege Graduate Program in Genetics, Pennsylvania State College of Medicine, Hershey, PA 17033 Edited by Stanley M. Gartler, University of Washington, Seattle, WA, and approved September 23, 2008 (received for review August 8, 2008) Although most genes on one X chromosome in mammalian fe- Sequences on the X are hypothesized to propagate XCI (12) and males are silenced by X inactivation, some ‘‘escape’’ X inactivation to be depleted at escape genes (8, 9). LINE-1 repeats fit such and are expressed from both active and inactive Xs. How these predictions, particularly on the human X (8–10). Distinct dis- escape genes are transcribed from a largely inactivated chromo- tributions of other repeats classify some mouse X genes (5). some is not fully understood, but underlying genomic sequences X-linked transgenes also test the role of genomic sequences in are likely involved. We developed a transgene approach to ask escape gene expression. Most transgenes are X-inactivated, whether an escape locus is autonomous or is instead influenced by although a number escape XCI (e.g., refs. 13 and 14). Such X chromosome location. Two BACs carrying the mouse Jarid1c gene transgene studies indicate that, in addition to CTCF (6), locus and adjacent X-inactivated transcripts were randomly integrated control regions and matrix attachment sites are also not suffi- into mouse XX embryonic stem cells. Four lines with single-copy, cient to escape XCI (15, 16). -
Genome-Wide Analysis of Allele-Specific Expression Patterns in Seventeen Tissues of Korean Cattle (Hanwoo)
animals Article Genome-Wide Analysis of Allele-Specific Expression Patterns in Seventeen Tissues of Korean Cattle (Hanwoo) Kyu-Sang Lim 1 , Sun-Sik Chang 2, Bong-Hwan Choi 3, Seung-Hwan Lee 4, Kyung-Tai Lee 3 , Han-Ha Chai 3, Jong-Eun Park 3 , Woncheoul Park 3 and Dajeong Lim 3,* 1 Department of Animal Science, Iowa State University, Ames, IA 50011, USA; [email protected] 2 Hanwoo Research Institute, National Institute of Animal Science, Rural Development Administration, Pyeongchang 25340, Korea; [email protected] 3 Animal Genomics and Bioinformatics Division, National Institute of Animal Science, Rural Development Administration, Wanju 55365, Korea; [email protected] (B.-H.C.); [email protected] (K.-T.L.); [email protected] (H.-H.C.); [email protected] (J.-E.P.); [email protected] (W.P.) 4 Division of Animal and Dairy Science, Chungnam National University, Daejeon 34134, Korea; [email protected] * Correspondence: [email protected] Received: 26 July 2019; Accepted: 23 September 2019; Published: 26 September 2019 Simple Summary: Allele-specific expression (ASE) is the biased allelic expression of genetic variants within the gene. Recently, the next-generation sequencing (NGS) technologies allowed us to detect ASE genes at a transcriptome-wide level. It is essential for the understanding of animal development, cellular programming, and the effect on their complexity because ASE shows developmental, tissue, or species-specific patterns. However, these aspects of ASE still have not been annotated well in farm animals and most studies were conducted mainly at the fetal stages. Hence, the current study focuses on detecting ASE genes in 17 tissues in adult cattle. -
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. -
82262967.Pdf
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector Current Biology 19, 1478–1484, September 15, 2009 ª2009 Elsevier Ltd All rights reserved DOI 10.1016/j.cub.2009.07.041 Report Key Features of the X Inactivation Process Are Conserved between Marsupials and Eutherians Shantha K. Mahadevaiah,1 Helene Royo,1 in situ hybridization (RNA FISH) [1] and semiquantitative John L. VandeBerg,2 John R. McCarrey,3 Sarah Mackay,4 reverse transcriptase-polymerase chain reaction (RT-PCR) and James M.A. Turner1,* [2] have concluded that the X chromosome of the marsupial 1MRC National Institute for Medical Research, Mill Hill, Monodelphis domestica (opossum) remains inactive during London NW7 1AA, UK spermiogenesis. However, Cot-1 RNA FISH has since been 2Department of Genetics, Southwest Foundation for shown to primarily detect silencing of repeat rather than Biomedical Research, San Antonio, TX 78227, USA coding X-linked sequences [16, 17], and RT-PCR cannot 3Department of Biology, University of Texas at San Antonio, discriminate between steady-state RNA levels and ongoing San Antonio, TX 78249, USA transcription. We therefore sought to reexamine male germline 4Division of Integrated Biology, Faculty of Biomedical & Life X silencing and its relationship to female XCI with a gene- Sciences, University of Glasgow, Glasgow G12 8QQ, specific RNA FISH approach. Scotland, UK For our analysis of XCI in the male germline, we selected ten genes distributed across the opossum X chromosome (Fig- ure 1A). We wished to compare X gene silencing in opossum Summary with that in mouse, in which MSCI and its maintenance have been well characterized [18, 19]. -
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. -
Novel Insights Into Autophagy from Multicellular Model Systems
Feature Review Eaten alive: novel insights into autophagy from multicellular model systems 1 2 Hong Zhang and Eric H. Baehrecke 1 Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China 2 Department of Molecular, Cell, and Cancer Biology, University of Massachusetts Medical School, Worcester, MA 01605, USA Autophagy delivers cytoplasmic material to lysosomes are essential for autophagosome formation [7,8]. Remark- for degradation. First identified in yeast, the core genes ably, the core autophagy machinery that is encoded by that control this process are conserved in higher organ- these genes is conserved between yeast and humans isms. Studies of mammalian cell cultures have expanded [6]. Many studies of immortalized mammalian cell lines our understanding of the core autophagy pathway, but indicate that, as in yeast, nutrient-limiting conditions cannot reveal the unique animal-specific mechanisms induce autophagy that is dependent on ATG genes. How- for the regulation and function of autophagy. Multicel- ever, several aspects of the autophagy pathway in higher lular organisms have different types of cells that possess eukaryotes are distinct from that in yeast. In yeast, all distinct composition, morphology, and organization of autophagosomes arise from the single perivacuolar preau- intracellular organelles. In addition, the autophagic ma- tophagosomal structure (PAS). In higher eukaryotes, there chinery integrates signals from other cells and environ- is no evidence for a PAS and isolation membranes can be mental conditions to maintain cell, tissue and organism generated simultaneously at multiple sites, implicating homeostasis. Here, we highlight how studies of autop- more complex sources for autophagosomal membranes. hagy in flies and worms have identified novel core Indeed, the endoplasmic reticulum (ER), mitochondria, autophagy genes and mechanisms, and provided insight plasma membrane, and recycling endosomes have been into the context-specific regulation and function of shown to contribute to autophagosomal membranes autophagy. -
Genome-Wide Identification and Analysis of Prognostic Features in Human Cancers
bioRxiv preprint doi: https://doi.org/10.1101/2021.06.01.446243; this version posted June 1, 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 4.0 International license. Genome-wide identification and analysis of prognostic features in human cancers Joan C. Smith1,2 and Jason M. Sheltzer1* 1. Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724. 2. Google, Inc., New York, NY 10011. * Lead contact; to whom correspondence may be addressed. E-mail: [email protected]. bioRxiv preprint doi: https://doi.org/10.1101/2021.06.01.446243; this version posted June 1, 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 4.0 International license. Abstract Clinical decisions in cancer rely on precisely assessing patient risk. To improve our ability to accurately identify the most aggressive malignancies, we constructed genome-wide survival models using gene expression, copy number, methylation, and mutation data from 10,884 patients with known clinical outcomes. We identified more than 100,000 significant prognostic biomarkers and demonstrate that these genomic features can predict patient outcomes in clinically-ambiguous situations. While adverse biomarkers are commonly believed to represent cancer driver genes and promising therapeutic targets, we show that cancer features associated with shorter survival times are not enriched for either oncogenes or for successful drug targets. -
To Study Mutant P53 Gain of Function, Various Tumor-Derived P53 Mutants
Differential effects of mutant TAp63γ on transactivation of p53 and/or p63 responsive genes and their effects on global gene expression. A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science By Shama K Khokhar M.Sc., Bilaspur University, 2004 B.Sc., Bhopal University, 2002 2007 1 COPYRIGHT SHAMA K KHOKHAR 2007 2 WRIGHT STATE UNIVERSITY SCHOOL OF GRADUATE STUDIES Date of Defense: 12-03-07 I HEREBY RECOMMEND THAT THE THESIS PREPARED UNDER MY SUPERVISION BY SHAMA KHAN KHOKHAR ENTITLED Differential effects of mutant TAp63γ on transactivation of p53 and/or p63 responsive genes and their effects on global gene expression BE ACCEPTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF Master of Science Madhavi P. Kadakia, Ph.D. Thesis Director Daniel Organisciak , Ph.D. Department Chair Committee on Final Examination Madhavi P. Kadakia, Ph.D. Steven J. Berberich, Ph.D. Michael Leffak, Ph.D. Joseph F. Thomas, Jr., Ph.D. Dean, School of Graduate Studies 3 Abstract Khokhar, Shama K. M.S., Department of Biochemistry and Molecular Biology, Wright State University, 2007 Differential effect of TAp63γ mutants on transactivation of p53 and/or p63 responsive genes and their effects on global gene expression. p63, a member of the p53 gene family, known to play a role in development, has more recently also been implicated in cancer progression. Mice lacking p63 exhibit severe developmental defects such as limb truncations, abnormal skin, and absence of hair follicles, teeth, and mammary glands. Germline missense mutations of p63 have been shown to be responsible for several human developmental syndromes including SHFM, EEC and ADULT syndromes and are associated with anomalies in the development of organs of epithelial origin. -
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Patterns of DNA methylation on the human X chromosome and use in analyzing X-chromosome inactivation by Allison Marie Cotton B.Sc., The University of Guelph, 2005 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in The Faculty of Graduate Studies (Medical Genetics) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) January 2012 © Allison Marie Cotton, 2012 Abstract The process of X-chromosome inactivation achieves dosage compensation between mammalian males and females. In females one X chromosome is transcriptionally silenced through a variety of epigenetic modifications including DNA methylation. Most X-linked genes are subject to X-chromosome inactivation and only expressed from the active X chromosome. On the inactive X chromosome, the CpG island promoters of genes subject to X-chromosome inactivation are methylated in their promoter regions, while genes which escape from X- chromosome inactivation have unmethylated CpG island promoters on both the active and inactive X chromosomes. The first objective of this thesis was to determine if the DNA methylation of CpG island promoters could be used to accurately predict X chromosome inactivation status. The second objective was to use DNA methylation to predict X-chromosome inactivation status in a variety of tissues. A comparison of blood, muscle, kidney and neural tissues revealed tissue-specific X-chromosome inactivation, in which 12% of genes escaped from X-chromosome inactivation in some, but not all, tissues. X-linked DNA methylation analysis of placental tissues predicted four times higher escape from X-chromosome inactivation than in any other tissue. Despite the hypomethylation of repetitive elements on both the X chromosome and the autosomes, no changes were detected in the frequency or intensity of placental Cot-1 holes. -
Guidelines for the Use and Interpretation of Assays for Monitoring Autophagy (3Rd Edition)
AUTOPHAGY 2016, VOL. 12, NO. 1, 1–222 http://dx.doi.org/10.1080/15548627.2015.1100356 EDITORIAL Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition) Daniel J Klionsky1745,1749*, Kotb Abdelmohsen840, Akihisa Abe1237, Md Joynal Abedin1762, Hagai Abeliovich425, Abraham Acevedo Arozena789, Hiroaki Adachi1800, Christopher M Adams1669, Peter D Adams57, Khosrow Adeli1981, Peter J Adhihetty1625, Sharon G Adler700, Galila Agam67, Rajesh Agarwal1587, Manish K Aghi1537, Maria Agnello1826, Patrizia Agostinis664, Patricia V Aguilar1960, Julio Aguirre-Ghiso784,786, Edoardo M Airoldi89,422, Slimane Ait-Si-Ali1376, Takahiko Akematsu2010, Emmanuel T Akporiaye1097, Mohamed Al-Rubeai1394, Guillermo M Albaiceta1294, Chris Albanese363, Diego Albani561, Matthew L Albert517, Jesus Aldudo128, Hana Algul€ 1164, Mehrdad Alirezaei1198, Iraide Alloza642,888, Alexandru Almasan206, Maylin Almonte-Beceril524, Emad S Alnemri1212, Covadonga Alonso544, Nihal Altan-Bonnet848, Dario C Altieri1205, Silvia Alvarez1497, Lydia Alvarez-Erviti1395, Sandro Alves107, Giuseppina Amadoro860, Atsuo Amano930, Consuelo Amantini1554, Santiago Ambrosio1458, Ivano Amelio756, Amal O Amer918, Mohamed Amessou2089, Angelika Amon726, Zhenyi An1538, Frank A Anania291, Stig U Andersen6, Usha P Andley2079, Catherine K Andreadi1690, Nathalie Andrieu-Abadie502, Alberto Anel2027, David K Ann58, Shailendra Anoopkumar-Dukie388, Manuela Antonioli832,858, Hiroshi Aoki1791, Nadezda Apostolova2007, Saveria Aquila1500, Katia Aquilano1876, Koichi Araki292, Eli Arama2098, -
Aberrant Promoter Methylation and Tumor Suppressive Activity of the DFNA5 Gene in Colorectal Carcinoma
Oncogene (2008) 27, 3624–3634 & 2008 Nature Publishing Group All rights reserved 0950-9232/08 $30.00 www.nature.com/onc ORIGINAL ARTICLE Aberrant promoter methylation and tumor suppressive activity of the DFNA5 gene in colorectal carcinoma MS Kim1, X Chang1, K Yamashita1, JK Nagpal1, JH Baek2,GWu3, B Trink1, EA Ratovitski1, M Mori4 and D Sidransky1 1Department of Otolaryngology, Head and Neck Cancer Research Division, Johns Hopkins University, Baltimore, MD, USA; 2Department of Genetic Medicine, Institute of Cell Engineering, Johns Hopkins University, Baltimore, MD, USA; 3Karmanos Cancer Institute, Department of Pathology, Wayne State University, Detroit, MI, USA and 4Department of Surgical Oncology, Medical Institute of Bioregulation, Kyushu University, Tsurumibaru, Beppu, Japan To identify novel methylated gene promoters, we com- Introduction pared differential RNA expression profiles of colorectal cancer (CRC) cell lines with or without treatment of Aberrant gene expression is a characteristic of human 5-aza-20-deoxycytidine (5-aza-dC). Out of 1776 genes cancers, and changes in DNA methylation status can that were initially ‘absent (that is, silenced)’ by gene have profound effects on the expression of genes. Tumor expression array analysis, we selected 163 genes that were suppressor genes (TSGs) display both genetic and increased after 5-aza-dC treatment in at least two of three epigenetic inactivation in human tumors, and the CRC cell lines. The microarray results were confirmed by transcriptional silencing of TSGs has established hy- Reverse Transcription–PCR, and CpG island of the gene permethylation as a common mechanism for loss of promoters were amplified and sequenced for examination TSG function in human cancer (Herman, 1999).