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Cytogenomic SNP Microarray - Fetal ARUP Test Code 2002366 Maternal Contamination Study Fetal Spec Fetal Cells
Patient Report |FINAL Client: Example Client ABC123 Patient: Patient, Example 123 Test Drive Salt Lake City, UT 84108 DOB 2/13/1987 UNITED STATES Gender: Female Patient Identifiers: 01234567890ABCD, 012345 Physician: Doctor, Example Visit Number (FIN): 01234567890ABCD Collection Date: 00/00/0000 00:00 Cytogenomic SNP Microarray - Fetal ARUP test code 2002366 Maternal Contamination Study Fetal Spec Fetal Cells Single fetal genotype present; no maternal cells present. Fetal and maternal samples were tested using STR markers to rule out maternal cell contamination. This result has been reviewed and approved by Maternal Specimen Yes Cytogenomic SNP Microarray - Fetal Abnormal * (Ref Interval: Normal) Test Performed: Cytogenomic SNP Microarray- Fetal (ARRAY FE) Specimen Type: Direct (uncultured) villi Indication for Testing: Patient with 46,XX,t(4;13)(p16.3;q12) (Quest: EN935475D) ----------------------------------------------------------------- ----- RESULT SUMMARY Abnormal Microarray Result (Male) Unbalanced Translocation Involving Chromosomes 4 and 13 Classification: Pathogenic 4p Terminal Deletion (Wolf-Hirschhorn syndrome) Copy number change: 4p16.3p16.2 loss Size: 5.1 Mb 13q Proximal Region Deletion Copy number change: 13q11q12.12 loss Size: 6.1 Mb ----------------------------------------------------------------- ----- RESULT DESCRIPTION This analysis showed a terminal deletion (1 copy present) involving chromosome 4 within 4p16.3p16.2 and a proximal interstitial deletion (1 copy present) involving chromosome 13 within 13q11q12.12. This -
A Genome-Wide Association Study of a Coronary Artery Disease Risk Variant
Journal of Human Genetics (2013) 58, 120–126 & 2013 The Japan Society of Human Genetics All rights reserved 1434-5161/13 www.nature.com/jhg ORIGINAL ARTICLE A genome-wide association study of a coronary artery diseaseriskvariant Ji-Young Lee1,16, Bok-Soo Lee2,16, Dong-Jik Shin3,16, Kyung Woo Park4,16, Young-Ah Shin1, Kwang Joong Kim1, Lyong Heo1, Ji Young Lee1, Yun Kyoung Kim1, Young Jin Kim1, Chang Bum Hong1, Sang-Hak Lee3, Dankyu Yoon5, Hyo Jung Ku2, Il-Young Oh4, Bong-Jo Kim1, Juyoung Lee1, Seon-Joo Park1, Jimin Kim1, Hye-kyung Kawk1, Jong-Eun Lee6, Hye-kyung Park1, Jae-Eun Lee1, Hye-young Nam1, Hyun-young Park7, Chol Shin8, Mitsuhiro Yokota9, Hiroyuki Asano10, Masahiro Nakatochi11, Tatsuaki Matsubara12, Hidetoshi Kitajima13, Ken Yamamoto13, Hyung-Lae Kim14, Bok-Ghee Han1, Myeong-Chan Cho15, Yangsoo Jang3,17, Hyo-Soo Kim4,17, Jeong Euy Park2,17 and Jong-Young Lee1,17 Although over 30 common genetic susceptibility loci have been identified to be independently associated with coronary artery disease (CAD) risk through genome-wide association studies (GWAS), genetic risk variants reported to date explain only a small fraction of heritability. To identify novel susceptibility variants for CAD and confirm those previously identified in European population, GWAS and a replication study were performed in the Koreans and Japanese. In the discovery stage, we genotyped 2123 cases and 3591 controls with 521 786 SNPs using the Affymetrix SNP Array 6.0 chips in Korean. In the replication, direct genotyping was performed using 3052 cases and 4976 controls from the KItaNagoya Genome study of Japan with 14 selected SNPs. -
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. -
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SAN TA C RUZ BI OTEC HNOL OG Y, INC . HHIPL1 (N-14): sc-247140 BACKGROUND APPLICATIONS Hedgehog (Hh) signaling proteins are critical for growth and tissue pattern - HHIPL1 (N-14) is recommended for detection of HHIPL1 of human origin ing during development. Patched (Ptc), a putative 12 transmembrane recep - by Western Blotting (starting dilution 1:200, dilution range 1:100-1:1000), tor, binds to Sonic hedgehog and is suspected to be a negative regulator of immunofluorescence (starting dilution 1:50, dilution range 1:50-1:500) and Hh signaling. A family member of patched, designated patched 2, has been solid phase ELISA (starting dilution 1:30, dilution range 1:30-1:3000); non found to be co-expressed with Sonic hedgehog. Smoothened (Smo), a seven cross-reactive with HHIPL2. transmembrane receptor, is complexed with patched in many tissues and Suitable for use as control antibody for HHIPL1 siRNA (h): sc-92168, HHIPL1 is believed to be an essential component in the Hh signaling pathway. Hhip shRNA Plasmid (h): sc-92168-SH and HHIPL1 shRNA (h) Lentiviral Particles: (hedgehog-interacting protein) is able to bind to and may be a tran scriptional sc-92168-V. target of all Hh proteins. Binding of Hhip to Hh proteins attenuates Hedgehog signaling. HHIPL1 (hedgehog-interacting protein-like protein 1), also known Molecular Weight of HHIPL1 isoforms 1/2: 88/68 kDa. as HHIP2, is a 782 amino acid secreted protein that contains a HHIP domain and is expressed in trabecular bone. There are two isoforms of HHIPL1 that RECOMMENDED SECONDARY REAGENTS are produced as a result of alternative splicing events. -
Transposon Activation Mutagenesis As a Screening Tool for Identifying
Chen et al. BMC Cancer 2013, 13:93 http://www.biomedcentral.com/1471-2407/13/93 RESEARCH ARTICLE Open Access Transposon activation mutagenesis as a screening tool for identifying resistance to cancer therapeutics Li Chen1,2*, Lynda Stuart2, Toshiro K Ohsumi3, Shawn Burgess4, Gaurav K Varshney4, Anahita Dastur1, Mark Borowsky3, Cyril Benes1, Adam Lacy-Hulbert2 and Emmett V Schmidt2 Abstract Background: The development of resistance to chemotherapies represents a significant barrier to successful cancer treatment. Resistance mechanisms are complex, can involve diverse and often unexpected cellular processes, and can vary with both the underlying genetic lesion and the origin or type of tumor. For these reasons developing experimental strategies that could be used to understand, identify and predict mechanisms of resistance in different malignant cells would be a major advance. Methods: Here we describe a gain-of-function forward genetic approach for identifying mechanisms of resistance. This approach uses a modified piggyBac transposon to generate libraries of mutagenized cells, each containing transposon insertions that randomly activate nearby gene expression. Genes of interest are identified using next- gen high-throughput sequencing and barcode multiplexing is used to reduce experimental cost. Results: Using this approach we successfully identify genes involved in paclitaxel resistance in a variety of cancer cell lines, including the multidrug transporter ABCB1, a previously identified major paclitaxel resistance gene. Analysis of co-occurring transposons integration sites in single cell clone allows for the identification of genes that might act cooperatively to produce drug resistance a level of information not accessible using RNAi or ORF expression screening approaches. Conclusion: We have developed a powerful pipeline to systematically discover drug resistance in mammalian cells in vitro. -
Algorithms for Transcriptome Quantification and Reconstruction from RNA-Seq Data
Georgia State University ScholarWorks @ Georgia State University Computer Science Dissertations Department of Computer Science Fall 11-16-2012 Algorithms for Transcriptome Quantification and Reconstruction from RNA-Seq Data Serghei Mangul Follow this and additional works at: https://scholarworks.gsu.edu/cs_diss Recommended Citation Mangul, Serghei, "Algorithms for Transcriptome Quantification and Reconstruction from RNA-Seq Data." Dissertation, Georgia State University, 2012. https://scholarworks.gsu.edu/cs_diss/71 This Dissertation is brought to you for free and open access by the Department of Computer Science at ScholarWorks @ Georgia State University. It has been accepted for inclusion in Computer Science Dissertations by an authorized administrator of ScholarWorks @ Georgia State University. For more information, please contact [email protected]. ALGORITHMS FOR TRANSCRIPTOME QUANTIFICATION AND RECONSTRUCTION FROM RNA-SEQ DATA by SERGHEI MANGUL Under the Direction of Dr. Alexander Zelikovsky ABSTRACT Massively parallel whole transcriptome sequencing and its ability to generate full tran- scriptome data at the single transcript level provides a powerful tool with multiple inter- related applications, including transcriptome reconstruction, gene/isoform expression esti- mation, also known as transcriptome quantification. As a result, whole transcriptome se- quencing has become the technology of choice for performing transcriptome analysis, rapidly replacing array-based technologies. The most commonly used transcriptome sequencing pro- tocol, referred to as RNA-Seq, generates short (single or paired) sequencing tags from the ends of randomly generated cDNA fragments. RNA-Seq protocol reduces the sequencing cost and significantly increases data throughput, but is computationally challenging to re- construct full-length transcripts and accurately estimate their abundances across all cell types. We focus on two main problems in transcriptome data analysis, namely, transcriptome reconstruction and quantification. -
Supplementary Table S4. FGA Co-Expressed Gene List in LUAD
Supplementary Table S4. FGA co-expressed gene list in LUAD tumors Symbol R Locus Description FGG 0.919 4q28 fibrinogen gamma chain FGL1 0.635 8p22 fibrinogen-like 1 SLC7A2 0.536 8p22 solute carrier family 7 (cationic amino acid transporter, y+ system), member 2 DUSP4 0.521 8p12-p11 dual specificity phosphatase 4 HAL 0.51 12q22-q24.1histidine ammonia-lyase PDE4D 0.499 5q12 phosphodiesterase 4D, cAMP-specific FURIN 0.497 15q26.1 furin (paired basic amino acid cleaving enzyme) CPS1 0.49 2q35 carbamoyl-phosphate synthase 1, mitochondrial TESC 0.478 12q24.22 tescalcin INHA 0.465 2q35 inhibin, alpha S100P 0.461 4p16 S100 calcium binding protein P VPS37A 0.447 8p22 vacuolar protein sorting 37 homolog A (S. cerevisiae) SLC16A14 0.447 2q36.3 solute carrier family 16, member 14 PPARGC1A 0.443 4p15.1 peroxisome proliferator-activated receptor gamma, coactivator 1 alpha SIK1 0.435 21q22.3 salt-inducible kinase 1 IRS2 0.434 13q34 insulin receptor substrate 2 RND1 0.433 12q12 Rho family GTPase 1 HGD 0.433 3q13.33 homogentisate 1,2-dioxygenase PTP4A1 0.432 6q12 protein tyrosine phosphatase type IVA, member 1 C8orf4 0.428 8p11.2 chromosome 8 open reading frame 4 DDC 0.427 7p12.2 dopa decarboxylase (aromatic L-amino acid decarboxylase) TACC2 0.427 10q26 transforming, acidic coiled-coil containing protein 2 MUC13 0.422 3q21.2 mucin 13, cell surface associated C5 0.412 9q33-q34 complement component 5 NR4A2 0.412 2q22-q23 nuclear receptor subfamily 4, group A, member 2 EYS 0.411 6q12 eyes shut homolog (Drosophila) GPX2 0.406 14q24.1 glutathione peroxidase -
Muscle Enriched Lamin Interacting Protein (Mlip) Binds Chromatin and Is Required for Myoblast Differentiation
cells Article Muscle Enriched Lamin Interacting Protein (Mlip) Binds Chromatin and Is Required for Myoblast Differentiation Elmira Ahmady 1,2, Alexandre Blais 1,3,4 and Patrick G. Burgon 5,* 1 Department of Biochemistry, Microbiology, and Immunology, University of Ottawa, Ottawa, ON K1H 8M5, Canada; [email protected] (E.A.); [email protected] (A.B.) 2 Molecular Signaling Laboratory, University of Ottawa Heart Institute, Ottawa, ON K1Y 4W7, Canada 3 Ottawa Institute of Systems Biology, University of Ottawa, Ottawa, ON K1H 8M5, Canada 4 University of Ottawa Centre for Infection, Immunity and Inflammation (CI3), Ottawa, ON K1H 8M5, Canada 5 Department of Chemistry and Earth Sciences, College of Arts and Sciences, Qatar University, Doha 999043, Qatar * Correspondence: [email protected] Abstract: Muscle-enriched A-type lamin-interacting protein (Mlip) is a recently discovered Amniota gene that encodes proteins of unknown biological function. Here we report Mlip’s direct interaction with chromatin, and it may function as a transcriptional co-factor. Chromatin immunoprecipitations with microarray analysis demonstrated a propensity for Mlip to associate with genomic regions in close proximity to genes that control tissue-specific differentiation. Gel mobility shift assays confirmed that Mlip protein complexes with genomic DNA. Blocking Mlip expression in C2C12 myoblasts down- regulates myogenic regulatory factors (MyoD and MyoG) and subsequently significantly inhibits myogenic differentiation and the formation of myotubes. Collectively our data demonstrate that Mlip is required for C2C12 myoblast differentiation into myotubes. Mlip may exert this role as a transcriptional regulator of a myogenic program that is unique to amniotes. Citation: Ahmady, E.; Blais, A.; Burgon, P.G. -
Differential Gene Expression in the Skin of Xiphophorus
DIFFERENTIAL GENE EXPRESSION IN THE SKIN OF XIPHOPHORUS MACULATUS JP 163 B IN RESPONSE TO FULL SPECTRUM (10,000 K) FLUORESCENT LIGHT by Kaela Caballero, B.S. A thesis submitted to the Graduate Council of Texas State University in partial fulfillment of the requirements for the degree of Master of Science with a Major in Biochemistry August 2015 Committee Members: Ronald Walter, Chair Rachell Booth Steven Whitten COPYRIGHT by Kaela L. Caballero 2015 FAIR USE AND AUTHOR’S PERMISSION STATEMENT Fair Use This work is protected by the Copyright Laws of the United States (Public Law 94-553, section 107). Consistent with fair use as defined in the Copyright Laws, brief quotations from this material are allowed with proper acknowledgment. Use of this material for financial gain without the author’s express written permission is not allowed. Duplication Permission As the copyright holder of this work I, Kaela L. Caballero, authorize duplication of this work, in whole or in part, for educational or scholarly purposes only. DEDICATION To my parents and family, who have always supported and encouraged me, my education and my coffee addiction. And to Max, my study buddy; where you have gone, there is no need for coffee fueled late nights. Rest in peace. ACKNOWLEDGEMENTS This work could not have been accomplished without the support and mentorship that I have received throughout my life from family, teachers, mentors and friends. It is impossible to name everyone here, but I would like to use a few lines to thank those that have helped me achieve my goals. Thank you to Dr. -
DIPPER, a Spatiotemporal Proteomics Atlas of Human Intervertebral Discs
TOOLS AND RESOURCES DIPPER, a spatiotemporal proteomics atlas of human intervertebral discs for exploring ageing and degeneration dynamics Vivian Tam1,2†, Peikai Chen1†‡, Anita Yee1, Nestor Solis3, Theo Klein3§, Mateusz Kudelko1, Rakesh Sharma4, Wilson CW Chan1,2,5, Christopher M Overall3, Lisbet Haglund6, Pak C Sham7, Kathryn Song Eng Cheah1, Danny Chan1,2* 1School of Biomedical Sciences, , The University of Hong Kong, Hong Kong; 2The University of Hong Kong Shenzhen of Research Institute and Innovation (HKU-SIRI), Shenzhen, China; 3Centre for Blood Research, Faculty of Dentistry, University of British Columbia, Vancouver, Canada; 4Proteomics and Metabolomics Core Facility, The University of Hong Kong, Hong Kong; 5Department of Orthopaedics Surgery and Traumatology, HKU-Shenzhen Hospital, Shenzhen, China; 6Department of Surgery, McGill University, Montreal, Canada; 7Centre for PanorOmic Sciences (CPOS), The University of Hong Kong, Hong Kong Abstract The spatiotemporal proteome of the intervertebral disc (IVD) underpins its integrity *For correspondence: and function. We present DIPPER, a deep and comprehensive IVD proteomic resource comprising [email protected] 94 genome-wide profiles from 17 individuals. To begin with, protein modules defining key †These authors contributed directional trends spanning the lateral and anteroposterior axes were derived from high-resolution equally to this work spatial proteomes of intact young cadaveric lumbar IVDs. They revealed novel region-specific Present address: ‡Department profiles of regulatory activities -
S41467-019-13840-9.Pdf
ARTICLE https://doi.org/10.1038/s41467-019-13840-9 OPEN Accurate quantification of circular RNAs identifies extensive circular isoform switching events Jinyang Zhang 1,2, Shuai Chen1, Jingwen Yang1 & Fangqing Zhao1,2,3* Detection and quantification of circular RNAs (circRNAs) face several significant challenges, including high false discovery rate, uneven rRNA depletion and RNase R treatment efficiency, and underestimation of back-spliced junction reads. Here, we propose a novel algorithm, fi 1234567890():,; CIRIquant, for accurate circRNA quanti cation and differential expression analysis. By con- structing pseudo-circular reference for re-alignment of RNA-seq reads and employing sophisticated statistical models to correct RNase R treatment biases, CIRIquant can provide more accurate expression values for circRNAs with significantly reduced false discovery rate. We further develop a one-stop differential expression analysis pipeline implementing two independent measures, which helps unveil the regulation of competitive splicing between circRNAs and their linear counterparts. We apply CIRIquant to RNA-seq datasets of hepa- tocellular carcinoma, and characterize two important groups of linear-circular switching and circular transcript usage switching events, which demonstrate the promising ability to explore extensive transcriptomic changes in liver tumorigenesis. 1 Computational Genomics Lab, Beijing Institutes of Life Science, Chinese Academy of Sciences, 100101 Beijing, China. 2 University of Chinese Academy of Sciences, 100049 Beijing, China. -
Novel Gene Discovery in Primary Ciliary Dyskinesia
Novel Gene Discovery in Primary Ciliary Dyskinesia Mahmoud Raafat Fassad Genetics and Genomic Medicine Programme Great Ormond Street Institute of Child Health University College London A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy University College London 1 Declaration I, Mahmoud Raafat Fassad, confirm that the work presented in this thesis is my own. Where information has been derived from other sources, I confirm that this has been indicated in the thesis. 2 Abstract Primary Ciliary Dyskinesia (PCD) is one of the ‘ciliopathies’, genetic disorders affecting either cilia structure or function. PCD is a rare recessive disease caused by defective motile cilia. Affected individuals manifest with neonatal respiratory distress, chronic wet cough, upper respiratory tract problems, progressive lung disease resulting in bronchiectasis, laterality problems including heart defects and adult infertility. Early diagnosis and management are essential for better respiratory disease prognosis. PCD is a highly genetically heterogeneous disorder with causal mutations identified in 36 genes that account for the disease in about 70% of PCD cases, suggesting that additional genes remain to be discovered. Targeted next generation sequencing was used for genetic screening of a cohort of patients with confirmed or suggestive PCD diagnosis. The use of multi-gene panel sequencing yielded a high diagnostic output (> 70%) with mutations identified in known PCD genes. Over half of these mutations were novel alleles, expanding the mutation spectrum in PCD genes. The inclusion of patients from various ethnic backgrounds revealed a striking impact of ethnicity on the composition of disease alleles uncovering a significant genetic stratification of PCD in different populations.