A Genetic, Deletion, Physical, and Human Homology Map of the Long Fin Region on Zebrafish Linkage Group 2 M
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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. -
A Population-Specific Major Allele Reference Genome from the United
Edith Cowan University Research Online ECU Publications Post 2013 2021 A population-specific major allele efr erence genome from the United Arab Emirates population Gihan Daw Elbait Andreas Henschel Guan K. Tay Edith Cowan University Habiba S. Al Safar Follow this and additional works at: https://ro.ecu.edu.au/ecuworkspost2013 Part of the Life Sciences Commons, and the Medicine and Health Sciences Commons 10.3389/fgene.2021.660428 Elbait, G. D., Henschel, A., Tay, G. K., & Al Safar, H. S. (2021). A population-specific major allele reference genome from the United Arab Emirates population. Frontiers in Genetics, 12, article 660428. https://doi.org/10.3389/ fgene.2021.660428 This Journal Article is posted at Research Online. https://ro.ecu.edu.au/ecuworkspost2013/10373 fgene-12-660428 April 19, 2021 Time: 16:18 # 1 ORIGINAL RESEARCH published: 23 April 2021 doi: 10.3389/fgene.2021.660428 A Population-Specific Major Allele Reference Genome From The United Arab Emirates Population Gihan Daw Elbait1†, Andreas Henschel1,2†, Guan K. Tay1,3,4,5 and Habiba S. Al Safar1,3,6* 1 Center for Biotechnology, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates, 2 Department of Electrical Engineering and Computer Science, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates, 3 Department of Biomedical Engineering, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates, 4 Division of Psychiatry, Faculty of Health and Medical Sciences, The University of Western Australia, Crawley, WA, Australia, 5 School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia, 6 Department of Genetics and Molecular Biology, College of Medicine and Health Sciences, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates The ethnic composition of the population of a country contributes to the uniqueness of each national DNA sequencing project and, ideally, individual reference genomes are required to reduce the confounding nature of ethnic bias. -
Whole Exome Sequencing in Families at High Risk for Hodgkin Lymphoma: Identification of a Predisposing Mutation in the KDR Gene
Hodgkin Lymphoma SUPPLEMENTARY APPENDIX Whole exome sequencing in families at high risk for Hodgkin lymphoma: identification of a predisposing mutation in the KDR gene Melissa Rotunno, 1 Mary L. McMaster, 1 Joseph Boland, 2 Sara Bass, 2 Xijun Zhang, 2 Laurie Burdett, 2 Belynda Hicks, 2 Sarangan Ravichandran, 3 Brian T. Luke, 3 Meredith Yeager, 2 Laura Fontaine, 4 Paula L. Hyland, 1 Alisa M. Goldstein, 1 NCI DCEG Cancer Sequencing Working Group, NCI DCEG Cancer Genomics Research Laboratory, Stephen J. Chanock, 5 Neil E. Caporaso, 1 Margaret A. Tucker, 6 and Lynn R. Goldin 1 1Genetic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; 2Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; 3Ad - vanced Biomedical Computing Center, Leidos Biomedical Research Inc.; Frederick National Laboratory for Cancer Research, Frederick, MD; 4Westat, Inc., Rockville MD; 5Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; and 6Human Genetics Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA ©2016 Ferrata Storti Foundation. This is an open-access paper. doi:10.3324/haematol.2015.135475 Received: August 19, 2015. Accepted: January 7, 2016. Pre-published: June 13, 2016. Correspondence: [email protected] Supplemental Author Information: NCI DCEG Cancer Sequencing Working Group: Mark H. Greene, Allan Hildesheim, Nan Hu, Maria Theresa Landi, Jennifer Loud, Phuong Mai, Lisa Mirabello, Lindsay Morton, Dilys Parry, Anand Pathak, Douglas R. Stewart, Philip R. Taylor, Geoffrey S. Tobias, Xiaohong R. Yang, Guoqin Yu NCI DCEG Cancer Genomics Research Laboratory: Salma Chowdhury, Michael Cullen, Casey Dagnall, Herbert Higson, Amy A. -
Network Pharmacology Interpretation of Fuzheng–Jiedu Decoction Against Colorectal Cancer
Hindawi Evidence-Based Complementary and Alternative Medicine Volume 2021, Article ID 4652492, 16 pages https://doi.org/10.1155/2021/4652492 Research Article Network Pharmacology Interpretation of Fuzheng–Jiedu Decoction against Colorectal Cancer Hongshuo Shi ,1 Sisheng Tian,2 and Hu Tian 3 1College of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China 2School of Management, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China 3College of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China Correspondence should be addressed to Hu Tian; [email protected] Received 7 April 2020; Revised 3 January 2021; Accepted 21 January 2021; Published 20 February 2021 Academic Editor: George B. Lenon Copyright © 2021 Hongshuo Shi 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. Introduction. Traditional Chinese medicine (TCM) believes that the pathogenic factors of colorectal cancer (CRC) are “deficiency, dampness, stasis, and toxin,” and Fuzheng–Jiedu Decoction (FJD) can resist these factors. In this study, we want to find out the potential targets and pathways of FJD in the treatment of CRC and also explain from a scientific point of view that FJD multidrug combination can resist “deficiency, dampness, stasis, and toxin.” Methods. We get the composition of FJD from the TCMSP database and get its potential target. We also get the potential target of colorectal cancer according to the OMIM Database, TTD Database, GeneCards Database, CTD Database, DrugBank Database, and DisGeNET Database. -
Open Data for Differential Network Analysis in Glioma
International Journal of Molecular Sciences Article Open Data for Differential Network Analysis in Glioma , Claire Jean-Quartier * y , Fleur Jeanquartier y and Andreas Holzinger Holzinger Group HCI-KDD, Institute for Medical Informatics, Statistics and Documentation, Medical University Graz, Auenbruggerplatz 2/V, 8036 Graz, Austria; [email protected] (F.J.); [email protected] (A.H.) * Correspondence: [email protected] These authors contributed equally to this work. y Received: 27 October 2019; Accepted: 3 January 2020; Published: 15 January 2020 Abstract: The complexity of cancer diseases demands bioinformatic techniques and translational research based on big data and personalized medicine. Open data enables researchers to accelerate cancer studies, save resources and foster collaboration. Several tools and programming approaches are available for analyzing data, including annotation, clustering, comparison and extrapolation, merging, enrichment, functional association and statistics. We exploit openly available data via cancer gene expression analysis, we apply refinement as well as enrichment analysis via gene ontology and conclude with graph-based visualization of involved protein interaction networks as a basis for signaling. The different databases allowed for the construction of huge networks or specified ones consisting of high-confidence interactions only. Several genes associated to glioma were isolated via a network analysis from top hub nodes as well as from an outlier analysis. The latter approach highlights a mitogen-activated protein kinase next to a member of histondeacetylases and a protein phosphatase as genes uncommonly associated with glioma. Cluster analysis from top hub nodes lists several identified glioma-associated gene products to function within protein complexes, including epidermal growth factors as well as cell cycle proteins or RAS proto-oncogenes. -
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). -
Digital Transcriptome Profiling of Normal and Glioblastoma-Derived Neural Stem Cells Identifies Genes Associated with Patient Survival Engström Et Al
Digital transcriptome profiling of normal and glioblastoma-derived neural stem cells identifies genes associated with patient survival Engström et al. Engström et al. Genome Medicine 2012, 4:76 http://genomemedicine.com/content/4/10/76 (9 October 2012) Engström et al. Genome Medicine 2012, 4:76 http://genomemedicine.com/content/4/10/76 RESEARCH Open Access Digital transcriptome profiling of normal and glioblastoma-derived neural stem cells identifies genes associated with patient survival Pär G Engström1, Diva Tommei1, Stefan H Stricker2, Christine Ender2, Steven M Pollard2 and Paul Bertone1,3,4* Abstract Background: Glioblastoma multiforme, the most common type of primary brain tumor in adults, is driven by cells with neural stem (NS) cell characteristics. Using derivation methods developed for NS cells, it is possible to expand tumorigenic stem cells continuously in vitro. Although these glioblastoma-derived neural stem (GNS) cells are highly similar to normal NS cells, they harbor mutations typical of gliomas and initiate authentic tumors following orthotopic xenotransplantation. Here, we analyzed GNS and NS cell transcriptomes to identify gene expression alterations underlying the disease phenotype. Methods: Sensitive measurements of gene expression were obtained by high-throughput sequencing of transcript tags (Tag-seq) on adherent GNS cell lines from three glioblastoma cases and two normal NS cell lines. Validation by quantitative real-time PCR was performed on 82 differentially expressed genes across a panel of 16 GNS and 6 NS cell lines. The molecular basis and prognostic relevance of expression differences were investigated by genetic characterization of GNS cells and comparison with public data for 867 glioma biopsies. -
Hypermethylation of Genes in Testicular Embryonal Carcinomas
FULL PAPER British Journal of Cancer (2016) 114, 230–236 | doi: 10.1038/bjc.2015.408 Keywords: Embryonal carcinoma; DNA methylation; sex-linked genes; USP13; RBMY1A Hypermethylation of genes in testicular embryonal carcinomas Hoi-Hung Cheung*,1, Yanzhou Yang2, Tin-Lap Lee3, Owen Rennert4 and Wai-Yee Chan*,1,3 1The Chinese University of Hong Kong—Shandong University Joint Laboratory on Reproductive Genetics, School of Biomedical Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong SAR; 2Key Laboratory of Fertility Preservation and Maintenance, Ministry of Education, Key Laboratory of Reproduction and Genetics in Ningxia, Ningxia Medical University, Ningxia 750004, China; 3Reproduction, Development and Endocrinology Theme, School of Biomedical Sciences, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong SAR and 4The Eunice Kennedy Shriver National Institute of Child Health & Human Development, National Institutes of Health, Bethesda, MD 20892, USA Background: Testicular embryonal carcinoma (EC) is a major subtype of non-seminomatous germ cell tumours in males. Embryonal carcinomas are pluripotent, undifferentiated germ cell tumours believed to originate from primordial germ cells. Epigenetic changes during testicular EC tumorigenesis require better elucidation. Methods: To identify epigenetic changes during testicular neoplastic transformation, we profiled DNA methylation of six ECs. These samples represent different stages (stage I and stage III) of divergent invasiveness. Non-cancerous testicular tissues were included. Expression of a number of hypermethylated genes were examined by quantitative RT-PCR and immunohis- tochemistry (IHC). Results: A total of 1167 tumour-hypermethylated differentially methylated regions (DMRs) were identified across the genome. Among them, 40 genes/ncRNAs were found to have hypermethylated promoters. -
(NF1) As a Breast Cancer Driver
INVESTIGATION Comparative Oncogenomics Implicates the Neurofibromin 1 Gene (NF1) as a Breast Cancer Driver Marsha D. Wallace,*,† Adam D. Pfefferle,‡,§,1 Lishuang Shen,*,1 Adrian J. McNairn,* Ethan G. Cerami,** Barbara L. Fallon,* Vera D. Rinaldi,* Teresa L. Southard,*,†† Charles M. Perou,‡,§,‡‡ and John C. Schimenti*,†,§§,2 *Department of Biomedical Sciences, †Department of Molecular Biology and Genetics, ††Section of Anatomic Pathology, and §§Center for Vertebrate Genomics, Cornell University, Ithaca, New York 14853, ‡Department of Pathology and Laboratory Medicine, §Lineberger Comprehensive Cancer Center, and ‡‡Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27514, and **Memorial Sloan-Kettering Cancer Center, New York, New York 10065 ABSTRACT Identifying genomic alterations driving breast cancer is complicated by tumor diversity and genetic heterogeneity. Relevant mouse models are powerful for untangling this problem because such heterogeneity can be controlled. Inbred Chaos3 mice exhibit high levels of genomic instability leading to mammary tumors that have tumor gene expression profiles closely resembling mature human mammary luminal cell signatures. We genomically characterized mammary adenocarcinomas from these mice to identify cancer-causing genomic events that overlap common alterations in human breast cancer. Chaos3 tumors underwent recurrent copy number alterations (CNAs), particularly deletion of the RAS inhibitor Neurofibromin 1 (Nf1) in nearly all cases. These overlap with human CNAs including NF1, which is deleted or mutated in 27.7% of all breast carcinomas. Chaos3 mammary tumor cells exhibit RAS hyperactivation and increased sensitivity to RAS pathway inhibitors. These results indicate that spontaneous NF1 loss can drive breast cancer. This should be informative for treatment of the significant fraction of patients whose tumors bear NF1 mutations. -
Detection of H3k4me3 Identifies Neurohiv Signatures, Genomic
viruses Article Detection of H3K4me3 Identifies NeuroHIV Signatures, Genomic Effects of Methamphetamine and Addiction Pathways in Postmortem HIV+ Brain Specimens that Are Not Amenable to Transcriptome Analysis Liana Basova 1, Alexander Lindsey 1, Anne Marie McGovern 1, Ronald J. Ellis 2 and Maria Cecilia Garibaldi Marcondes 1,* 1 San Diego Biomedical Research Institute, San Diego, CA 92121, USA; [email protected] (L.B.); [email protected] (A.L.); [email protected] (A.M.M.) 2 Departments of Neurosciences and Psychiatry, University of California San Diego, San Diego, CA 92103, USA; [email protected] * Correspondence: [email protected] Abstract: Human postmortem specimens are extremely valuable resources for investigating trans- lational hypotheses. Tissue repositories collect clinically assessed specimens from people with and without HIV, including age, viral load, treatments, substance use patterns and cognitive functions. One challenge is the limited number of specimens suitable for transcriptional studies, mainly due to poor RNA quality resulting from long postmortem intervals. We hypothesized that epigenomic Citation: Basova, L.; Lindsey, A.; signatures would be more stable than RNA for assessing global changes associated with outcomes McGovern, A.M.; Ellis, R.J.; of interest. We found that H3K27Ac or RNA Polymerase (Pol) were not consistently detected by Marcondes, M.C.G. Detection of H3K4me3 Identifies NeuroHIV Chromatin Immunoprecipitation (ChIP), while the enhancer H3K4me3 histone modification was Signatures, Genomic Effects of abundant and stable up to the 72 h postmortem. We tested our ability to use H3K4me3 in human Methamphetamine and Addiction prefrontal cortex from HIV+ individuals meeting criteria for methamphetamine use disorder or not Pathways in Postmortem HIV+ Brain (Meth +/−) which exhibited poor RNA quality and were not suitable for transcriptional profiling. -
Coexpression Networks Based on Natural Variation in Human Gene Expression at Baseline and Under Stress
University of Pennsylvania ScholarlyCommons Publicly Accessible Penn Dissertations Fall 2010 Coexpression Networks Based on Natural Variation in Human Gene Expression at Baseline and Under Stress Renuka Nayak University of Pennsylvania, [email protected] Follow this and additional works at: https://repository.upenn.edu/edissertations Part of the Computational Biology Commons, and the Genomics Commons Recommended Citation Nayak, Renuka, "Coexpression Networks Based on Natural Variation in Human Gene Expression at Baseline and Under Stress" (2010). Publicly Accessible Penn Dissertations. 1559. https://repository.upenn.edu/edissertations/1559 This paper is posted at ScholarlyCommons. https://repository.upenn.edu/edissertations/1559 For more information, please contact [email protected]. Coexpression Networks Based on Natural Variation in Human Gene Expression at Baseline and Under Stress Abstract Genes interact in networks to orchestrate cellular processes. Here, we used coexpression networks based on natural variation in gene expression to study the functions and interactions of human genes. We asked how these networks change in response to stress. First, we studied human coexpression networks at baseline. We constructed networks by identifying correlations in expression levels of 8.9 million gene pairs in immortalized B cells from 295 individuals comprising three independent samples. The resulting networks allowed us to infer interactions between biological processes. We used the network to predict the functions of poorly-characterized human genes, and provided some experimental support. Examining genes implicated in disease, we found that IFIH1, a diabetes susceptibility gene, interacts with YES1, which affects glucose transport. Genes predisposing to the same diseases are clustered non-randomly in the network, suggesting that the network may be used to identify candidate genes that influence disease susceptibility. -
An Integrative Genomic Analysis of the Longshanks Selection Experiment for Longer Limbs in Mice
bioRxiv preprint doi: https://doi.org/10.1101/378711; this version posted August 19, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 1 Title: 2 An integrative genomic analysis of the Longshanks selection experiment for longer limbs in mice 3 Short Title: 4 Genomic response to selection for longer limbs 5 One-sentence summary: 6 Genome sequencing of mice selected for longer limbs reveals that rapid selection response is 7 due to both discrete loci and polygenic adaptation 8 Authors: 9 João P. L. Castro 1,*, Michelle N. Yancoskie 1,*, Marta Marchini 2, Stefanie Belohlavy 3, Marek 10 Kučka 1, William H. Beluch 1, Ronald Naumann 4, Isabella Skuplik 2, John Cobb 2, Nick H. 11 Barton 3, Campbell Rolian2,†, Yingguang Frank Chan 1,† 12 Affiliations: 13 1. Friedrich Miescher Laboratory of the Max Planck Society, Tübingen, Germany 14 2. University of Calgary, Calgary AB, Canada 15 3. IST Austria, Klosterneuburg, Austria 16 4. Max Planck Institute for Cell Biology and Genetics, Dresden, Germany 17 Corresponding author: 18 Campbell Rolian 19 Yingguang Frank Chan 20 * indicates equal contribution 21 † indicates equal contribution 22 Abstract: 23 Evolutionary studies are often limited by missing data that are critical to understanding the 24 history of selection. Selection experiments, which reproduce rapid evolution under controlled 25 conditions, are excellent tools to study how genomes evolve under strong selection. Here we 1 bioRxiv preprint doi: https://doi.org/10.1101/378711; this version posted August 19, 2018.