Associations Between Human Disease Genes and Overlapping Gene Groups and Multiple Amino Acid Runs
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Whole-Genome Microarray Detects Deletions and Loss of Heterozygosity of Chromosome 3 Occurring Exclusively in Metastasizing Uveal Melanoma
Anatomy and Pathology Whole-Genome Microarray Detects Deletions and Loss of Heterozygosity of Chromosome 3 Occurring Exclusively in Metastasizing Uveal Melanoma Sarah L. Lake,1 Sarah E. Coupland,1 Azzam F. G. Taktak,2 and Bertil E. Damato3 PURPOSE. To detect deletions and loss of heterozygosity of disease is fatal in 92% of patients within 2 years of diagnosis. chromosome 3 in a rare subset of fatal, disomy 3 uveal mela- Clinical and histopathologic risk factors for UM metastasis noma (UM), undetectable by fluorescence in situ hybridization include large basal tumor diameter (LBD), ciliary body involve- (FISH). ment, epithelioid cytomorphology, extracellular matrix peri- ϩ ETHODS odic acid-Schiff-positive (PAS ) loops, and high mitotic M . Multiplex ligation-dependent probe amplification 3,4 5 (MLPA) with the P027 UM assay was performed on formalin- count. Prescher et al. showed that a nonrandom genetic fixed, paraffin-embedded (FFPE) whole tumor sections from 19 change, monosomy 3, correlates strongly with metastatic death, and the correlation has since been confirmed by several disomy 3 metastasizing UMs. Whole-genome microarray analy- 3,6–10 ses using a single-nucleotide polymorphism microarray (aSNP) groups. Consequently, fluorescence in situ hybridization were performed on frozen tissue samples from four fatal dis- (FISH) detection of chromosome 3 using a centromeric probe omy 3 metastasizing UMs and three disomy 3 tumors with Ͼ5 became routine practice for UM prognostication; however, 5% years’ metastasis-free survival. to 20% of disomy 3 UM patients unexpectedly develop metas- tases.11 Attempts have therefore been made to identify the RESULTS. Two metastasizing UMs that had been classified as minimal region(s) of deletion on chromosome 3.12–15 Despite disomy 3 by FISH analysis of a small tumor sample were found these studies, little progress has been made in defining the key on MLPA analysis to show monosomy 3. -
The Genomic Structure and Expression of MJD, the Machado-Joseph Disease Gene
J Hum Genet (2001) 46:413–422 © Jpn Soc Hum Genet and Springer-Verlag 2001 ORIGINAL ARTICLE Yaeko Ichikawa · Jun Goto · Masahira Hattori Atsushi Toyoda · Kazuo Ishii · Seon-Yong Jeong Hideji Hashida · Naoki Masuda · Katsuhisa Ogata Fumio Kasai · Momoki Hirai · Patrícia Maciel Guy A. Rouleau · Yoshiyuki Sakaki · Ichiro Kanazawa The genomic structure and expression of MJD, the Machado-Joseph disease gene Received: March 7, 2001 / Accepted: April 17, 2001 Abstract Machado-Joseph disease (MJD) is an autosomal relative to the MJD gene in B445M7 indicate that there are dominant neurodegenerative disorder that is clinically char- three alternative splicing sites and eight polyadenylation acterized by cerebellar ataxia and various associated symp- signals in MJD that are used to generate the differently toms. The disease is caused by an unstable expansion of the sized transcripts. CAG repeat in the MJD gene. This gene is mapped to chromosome 14q32.1. To determine its genomic structure, Key words Machado-Joseph disease (MJD) · 14q32.1 · we constructed a contig composed of six cosmid clones and CAG repeat · Genome structure · Alternative splicing · eight bacterial artificial chromosome (BAC) clones. It spans mRNA expression approximately 300kb and includes MJD. We also deter- mined the complete sequence (175,330bp) of B445M7, a human BAC clone that contains MJD. The MJD gene was found to span 48,240bp and to contain 11 exons. Northern Introduction blot analysis showed that MJD mRNA is ubiquitously expressed in human tissues, and in at least four different Machado-Joseph disease (MJD) is an autosomal dominant sizes; namely, 1.4, 1.8, 4.5, and 7.5kb. -
The Utility of Genetic Risk Scores in Predicting the Onset of Stroke March 2021 6
DOT/FAA/AM-21/24 Office of Aerospace Medicine Washington, DC 20591 The Utility of Genetic Risk Scores in Predicting the Onset of Stroke Diana Judith Monroy Rios, M.D1 and Scott J. Nicholson, Ph.D.2 1. KR 30 # 45-03 University Campus, Building 471, 5th Floor, Office 510 Bogotá D.C. Colombia 2. FAA Civil Aerospace Medical Institute, 6500 S. MacArthur Blvd Rm. 354, Oklahoma City, OK 73125 March 2021 NOTICE This document is disseminated under the sponsorship of the U.S. Department of Transportation in the interest of information exchange. The United States Government assumes no liability for the contents thereof. _________________ This publication and all Office of Aerospace Medicine technical reports are available in full-text from the Civil Aerospace Medical Institute’s publications Web site: (www.faa.gov/go/oamtechreports) Technical Report Documentation Page 1. Report No. 2. Government Accession No. 3. Recipient's Catalog No. DOT/FAA/AM-21/24 4. Title and Subtitle 5. Report Date March 2021 The Utility of Genetic Risk Scores in Predicting the Onset of Stroke 6. Performing Organization Code 7. Author(s) 8. Performing Organization Report No. Diana Judith Monroy Rios M.D1, and Scott J. Nicholson, Ph.D.2 9. Performing Organization Name and Address 10. Work Unit No. (TRAIS) 1 KR 30 # 45-03 University Campus, Building 471, 5th Floor, Office 510, Bogotá D.C. Colombia 11. Contract or Grant No. 2 FAA Civil Aerospace Medical Institute, 6500 S. MacArthur Blvd Rm. 354, Oklahoma City, OK 73125 12. Sponsoring Agency name and Address 13. Type of Report and Period Covered Office of Aerospace Medicine Federal Aviation Administration 800 Independence Ave., S.W. -
Complete Article
The EMBO Journal Vol. I No. 12 pp. 1539-1544, 1982 Long terminal repeat-like elements flank a human immunoglobulin epsilon pseudogene that lacks introns Shintaro Ueda', Sumiko Nakai, Yasuyoshi Nishida, lack the entire IVS have been found in the gene families of the Hiroshi Hisajima, and Tasuku Honjo* mouse a-globin (Nishioka et al., 1980; Vanin et al., 1980), the lambda chain (Hollis et al., 1982), Department of Genetics, Osaka University Medical School, Osaka 530, human immunoglobulin Japan and the human ,B-tubulin (Wilde et al., 1982a, 1982b). The mouse a-globin processed gene is flanked by long terminal Communicated by K.Rajewsky Received on 30 September 1982 repeats (LTRs) of retrovirus-like intracisternal A particles on both sides, although their orientation is opposite to each There are at least three immunoglobulin epsilon genes (C,1, other (Lueders et al., 1982). The human processed genes CE2, and CE) in the human genome. The nucleotide sequences described above have poly(A)-like tails -20 bases 3' to the of the expressed epsilon gene (CE,) and one (CE) of the two putative poly(A) addition signal and are flanked by direct epsilon pseudogenes were compared. The results show that repeats of several bases on both sides (Hollis et al., 1982; the CE3 gene lacks the three intervening sequences entirely and Wilde et al., 1982a, 1982b). Such direct repeats, which were has a 31-base A-rich sequence 16 bases 3' to the putative also found in human small nuclear RNA pseudogenes poly(A) addition signal, indicating that the CE3 gene is a pro- (Arsdell et al., 1981), might have been formed by repair of cessed gene. -
Identification of Genes Concordantly Expressed with Atoh1 During Inner Ear Development
Original Article doi: 10.5115/acb.2011.44.1.69 pISSN 2093-3665 eISSN 2093-3673 Identification of genes concordantly expressed with Atoh1 during inner ear development Heejei Yoon, Dong Jin Lee, Myoung Hee Kim, Jinwoong Bok Department of Anatomy, Brain Korea 21 Project for Medical Science, College of Medicine, Yonsei University, Seoul, Korea Abstract: The inner ear is composed of a cochlear duct and five vestibular organs in which mechanosensory hair cells play critical roles in receiving and relaying sound and balance signals to the brain. To identify novel genes associated with hair cell differentiation or function, we analyzed an archived gene expression dataset from embryonic mouse inner ear tissues. Since atonal homolog 1a (Atoh1) is a well known factor required for hair cell differentiation, we searched for genes expressed in a similar pattern with Atoh1 during inner ear development. The list from our analysis includes many genes previously reported to be involved in hair cell differentiation such as Myo6, Tecta, Myo7a, Cdh23, Atp6v1b1, and Gfi1. In addition, we identified many other genes that have not been associated with hair cell differentiation, including Tekt2, Spag6, Smpx, Lmod1, Myh7b, Kif9, Ttyh1, Scn11a and Cnga2. We examined expression patterns of some of the newly identified genes using real-time polymerase chain reaction and in situ hybridization. For example, Smpx and Tekt2, which are regulators for cytoskeletal dynamics, were shown specifically expressed in the hair cells, suggesting a possible role in hair cell differentiation or function. Here, by re- analyzing archived genetic profiling data, we identified a list of novel genes possibly involved in hair cell differentiation. -
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. -
High-Throughput Discovery of Novel Developmental Phenotypes
High-throughput discovery of novel developmental phenotypes The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters Citation Dickinson, M. E., A. M. Flenniken, X. Ji, L. Teboul, M. D. Wong, J. K. White, T. F. Meehan, et al. 2016. “High-throughput discovery of novel developmental phenotypes.” Nature 537 (7621): 508-514. doi:10.1038/nature19356. http://dx.doi.org/10.1038/nature19356. Published Version doi:10.1038/nature19356 Citable link http://nrs.harvard.edu/urn-3:HUL.InstRepos:32071918 Terms of Use This article was downloaded from Harvard University’s DASH repository, and is made available under the terms and conditions applicable to Other Posted Material, as set forth at http:// nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of- use#LAA HHS Public Access Author manuscript Author ManuscriptAuthor Manuscript Author Nature. Manuscript Author Author manuscript; Manuscript Author available in PMC 2017 March 14. Published in final edited form as: Nature. 2016 September 22; 537(7621): 508–514. doi:10.1038/nature19356. High-throughput discovery of novel developmental phenotypes A full list of authors and affiliations appears at the end of the article. Abstract Approximately one third of all mammalian genes are essential for life. Phenotypes resulting from mouse knockouts of these genes have provided tremendous insight into gene function and congenital disorders. As part of the International Mouse Phenotyping Consortium effort to generate and phenotypically characterize 5000 knockout mouse lines, we have identified 410 Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:http://www.nature.com/authors/editorial_policies/license.html#terms #Corresponding author: [email protected]. -
Supplementary Materials
1 Supplementary Materials: Supplemental Figure 1. Gene expression profiles of kidneys in the Fcgr2b-/- and Fcgr2b-/-. Stinggt/gt mice. (A) A heat map of microarray data show the genes that significantly changed up to 2 fold compared between Fcgr2b-/- and Fcgr2b-/-. Stinggt/gt mice (N=4 mice per group; p<0.05). Data show in log2 (sample/wild-type). 2 Supplemental Figure 2. Sting signaling is essential for immuno-phenotypes of the Fcgr2b-/-lupus mice. (A-C) Flow cytometry analysis of splenocytes isolated from wild-type, Fcgr2b-/- and Fcgr2b-/-. Stinggt/gt mice at the age of 6-7 months (N= 13-14 per group). Data shown in the percentage of (A) CD4+ ICOS+ cells, (B) B220+ I-Ab+ cells and (C) CD138+ cells. Data show as mean ± SEM (*p < 0.05, **p<0.01 and ***p<0.001). 3 Supplemental Figure 3. Phenotypes of Sting activated dendritic cells. (A) Representative of western blot analysis from immunoprecipitation with Sting of Fcgr2b-/- mice (N= 4). The band was shown in STING protein of activated BMDC with DMXAA at 0, 3 and 6 hr. and phosphorylation of STING at Ser357. (B) Mass spectra of phosphorylation of STING at Ser357 of activated BMDC from Fcgr2b-/- mice after stimulated with DMXAA for 3 hour and followed by immunoprecipitation with STING. (C) Sting-activated BMDC were co-cultured with LYN inhibitor PP2 and analyzed by flow cytometry, which showed the mean fluorescence intensity (MFI) of IAb expressing DC (N = 3 mice per group). 4 Supplemental Table 1. Lists of up and down of regulated proteins Accession No. -
Noninvasive Sleep Monitoring in Large-Scale Screening of Knock-Out Mice
bioRxiv preprint doi: https://doi.org/10.1101/517680; this version posted January 11, 2019. 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-ND 4.0 International license. Noninvasive sleep monitoring in large-scale screening of knock-out mice reveals novel sleep-related genes Shreyas S. Joshi1*, Mansi Sethi1*, Martin Striz1, Neil Cole2, James M. Denegre2, Jennifer Ryan2, Michael E. Lhamon3, Anuj Agarwal3, Steve Murray2, Robert E. Braun2, David W. Fardo4, Vivek Kumar2, Kevin D. Donohue3,5, Sridhar Sunderam6, Elissa J. Chesler2, Karen L. Svenson2, Bruce F. O'Hara1,3 1Dept. of Biology, University of Kentucky, Lexington, KY 40506, USA, 2The Jackson Laboratory, Bar Harbor, ME 04609, USA, 3Signal solutions, LLC, Lexington, KY 40503, USA, 4Dept. of Biostatistics, University of Kentucky, Lexington, KY 40536, USA, 5Dept. of Electrical and Computer Engineering, University of Kentucky, Lexington, KY 40506, USA. 6Dept. of Biomedical Engineering, University of Kentucky, Lexington, KY 40506, USA. *These authors contributed equally Address for correspondence and proofs: Shreyas S. Joshi, Ph.D. Dept. of Biology University of Kentucky 675 Rose Street 101 Morgan Building Lexington, KY 40506 U.S.A. Phone: (859) 257-2805 FAX: (859) 257-1717 Email: [email protected] Running title: Sleep changes in knockout mice bioRxiv preprint doi: https://doi.org/10.1101/517680; this version posted January 11, 2019. 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. -
SETD1B-Associated Neurodevelopmental Disorder
Genotype- phenotype correlations J Med Genet: first published as 10.1136/jmedgenet-2019-106756 on 16 June 2020. Downloaded from Original research SETD1B- associated neurodevelopmental disorder Alexandra Roston ,1 Dan Evans,2 Harinder Gill,1,3 Margaret McKinnon,1 Bertrand Isidor,4 Benjamin Cogné ,4,5 Jill Mwenifumbo,1,6 Clara van Karnebeek,7,8 Jianghong An,9 Steven J M Jones,9 Matthew Farrer,2 Michelle Demos,10 Mary Connolly,10 William T Gibson ,1 CAUSES Study, EPGEN Study ► Additional material is ABSTRACT same gene allows causal inference for those geno- published online only. To view Background Dysfunction of histone methyltransferases type–phenotype correlations. This is especially true please visit the journal online (http:// dx. doi. org/ 10. 1136/ and chromatin modifiers has been implicated in complex when perturbation of the general biological process jmedgenet- 2019- 106756). neurodevelopmental syndromes and cancers. SETD1B has, in similar contexts, been shown reproducibly encodes a lysine- specific methyltransferase that assists to result in similar phenotypes. For numbered affiliations see in transcriptional activation of genes by depositing Individual case reports have appeared in the end of article. H3K4 methyl marks. Previous reports of patients with literature describing neurodevelopmental delays rare variants in SETD1B describe a distinctive phenotype associated with rare coding variants in SETD1B, Correspondence to Dr Alexandra Roston, that includes seizures, global developmental delay and and with hemizygosity for SETD1B due to CNVs. Department of Medical intellectual disability. Here we show that pathogenic variants within Genetics, The University of Methods Two of the patients described herein were SETD1B contribute to a conserved phenotype that British Columbia, Vancouver, BC identified via genome-wide and exome-wide testing, includes intellectual disability and childhood- onset, V6T 1Z4, Canada; with microarray and research- based exome, through treatment- refractory seizures. -
Benefits of Cancerplex
CancerPlexSM is a comprehensive genetic assessment of a patient’s tumor that guides oncologists towards effective treatment options. What is CancerPlex? CancerPlex is a next generation DNA sequencing test for solid SM tumors. The specific coding regions of over 400 known cancer Potential outcomes from CancerPlex genes are simultaneously determined using a small amount of Identification of variants associated with response or resis- DNA extracted from tumor samples, including formalin-fixed, tance to an FDA-approved therapy for the patient’s disease. paraffin-embedded (FFPE) tissue and cell blocks from fine-needle aspirates or effusions. This analysis is performed in a single assay, Identification of variants associated with response or resis- simplifying and streamlining the test ordering process, and eliminat- tance to a therapy associated with another clinical indication. ing time consuming serial testing. Clinically actionable information unique to each patient’s tumor is consolidated into a simple report. Identification of variants associated with a therapy(s) in CancerPlex reveals missense changes, insertions and deletions, clinical development. and previously described rearrangements of ALK, RET, and ROS. Benefits of CancerPlex: CancerPlex genes were selected because of their importance in tumor The average turn-around-time for CancerPlex is under 10 biology. Analyzing more genes increases the chance of discovering business days, dramatically shortening the waiting period for actionable findings that lead to more choices for treatment. Our initial the start of treatment. results indicate that CancerPlex analysis identifies actionable findings up to 20% more frequently than previously published studies. CancerPlex ordering is simple: KEW provides all necessary shipping materials, can facilitate tissue retrieval and return with Since knowledge of tumor biology changes rapidly, CancerPlex pathologists, and manages 3rd party payment for the test. -
Supplementary Table 1: Adhesion Genes Data Set
Supplementary Table 1: Adhesion genes data set PROBE Entrez Gene ID Celera Gene ID Gene_Symbol Gene_Name 160832 1 hCG201364.3 A1BG alpha-1-B glycoprotein 223658 1 hCG201364.3 A1BG alpha-1-B glycoprotein 212988 102 hCG40040.3 ADAM10 ADAM metallopeptidase domain 10 133411 4185 hCG28232.2 ADAM11 ADAM metallopeptidase domain 11 110695 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 195222 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 165344 8751 hCG20021.3 ADAM15 ADAM metallopeptidase domain 15 (metargidin) 189065 6868 null ADAM17 ADAM metallopeptidase domain 17 (tumor necrosis factor, alpha, converting enzyme) 108119 8728 hCG15398.4 ADAM19 ADAM metallopeptidase domain 19 (meltrin beta) 117763 8748 hCG20675.3 ADAM20 ADAM metallopeptidase domain 20 126448 8747 hCG1785634.2 ADAM21 ADAM metallopeptidase domain 21 208981 8747 hCG1785634.2|hCG2042897 ADAM21 ADAM metallopeptidase domain 21 180903 53616 hCG17212.4 ADAM22 ADAM metallopeptidase domain 22 177272 8745 hCG1811623.1 ADAM23 ADAM metallopeptidase domain 23 102384 10863 hCG1818505.1 ADAM28 ADAM metallopeptidase domain 28 119968 11086 hCG1786734.2 ADAM29 ADAM metallopeptidase domain 29 205542 11085 hCG1997196.1 ADAM30 ADAM metallopeptidase domain 30 148417 80332 hCG39255.4 ADAM33 ADAM metallopeptidase domain 33 140492 8756 hCG1789002.2 ADAM7 ADAM metallopeptidase domain 7 122603 101 hCG1816947.1 ADAM8 ADAM metallopeptidase domain 8 183965 8754 hCG1996391 ADAM9 ADAM metallopeptidase domain 9 (meltrin gamma) 129974 27299 hCG15447.3 ADAMDEC1 ADAM-like,