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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 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. -
Extensive Variation Between Inbred Mouse Strains Due to Endogenous L1 Retrotransposition
Downloaded from genome.cshlp.org on October 5, 2021 - Published by Cold Spring Harbor Laboratory Press Letter Extensive variation between inbred mouse strains due to endogenous L1 retrotransposition Keiko Akagi,1,5 Jingfeng Li,2,5 Robert M. Stephens,3,5 Natalia Volfovsky,3 and David E. Symer2,4,6 1Mouse Cancer Genetics Program, Center for Cancer Research, National Cancer Institute, Frederick, Maryland 21702, USA; 2Basic Research Laboratory, Center for Cancer Research, National Cancer Institute, Frederick, Maryland 21702, USA; 3Advanced Biomedical Computing Center, Advanced Technology Program, SAIC-Frederick, Inc., Frederick, Maryland 21702, USA; 4Laboratory of Biochemistry and Molecular Biology, Center for Cancer Research, National Cancer Institute, Frederick, Maryland 21702, USA Numerous inbred mouse strains comprise models for human diseases and diversity, but the molecular differences between them are mostly unknown. Several mammalian genomes have been assembled, providing a framework for identifying structural variations. To identify variants between inbred mouse strains at a single nucleotide resolution, we aligned 26 million individual sequence traces from four laboratory mouse strains to the C57BL/6J reference genome. We discovered and analyzed over 10,000 intermediate-length genomic variants (from 100 nucleotides to 10 kilobases), distinguishing these strains from the C57BL/6J reference. Approximately 85% of such variants are due to recent mobilization of endogenous retrotransposons, predominantly L1 elements, greatly exceeding that reported in humans. Many genes’ structures and expression are altered directly by polymorphic L1 retrotransposons, including Drosha (also called Rnasen), Parp8, Scn1a, Arhgap15, and others, including novel genes. L1 polymorphisms are distributed nonrandomly across the genome, as they are excluded significantly from the X chromosome and from genes associated with the cell cycle, but are enriched in receptor genes. -
Whole Proteome Analysis of Human Tankyrase Knockout Cells Reveals Targets of Tankyrase- Mediated Degradation
ARTICLE DOI: 10.1038/s41467-017-02363-w OPEN Whole proteome analysis of human tankyrase knockout cells reveals targets of tankyrase- mediated degradation Amit Bhardwaj1, Yanling Yang2, Beatrix Ueberheide2 & Susan Smith1 Tankyrase 1 and 2 are poly(ADP-ribose) polymerases that function in pathways critical to cancer cell growth. Tankyrase-mediated PARylation marks protein targets for proteasomal 1234567890 degradation. Here, we generate human knockout cell lines to examine cell function and interrogate the proteome. We show that either tankyrase 1 or 2 is sufficient to maintain telomere length, but both are required to resolve telomere cohesion and maintain mitotic spindle integrity. Quantitative analysis of the proteome of tankyrase double knockout cells using isobaric tandem mass tags reveals targets of degradation, including antagonists of the Wnt/β-catenin signaling pathway (NKD1, NKD2, and HectD1) and three (Notch 1, 2, and 3) of the four Notch receptors. We show that tankyrases are required for Notch2 to exit the plasma membrane and enter the nucleus to activate transcription. Considering that Notch signaling is commonly activated in cancer, tankyrase inhibitors may have therapeutic potential in targeting this pathway. 1 Kimmel Center for Biology and Medicine at the Skirball Institute, Department of Pathology, New York University School of Medicine, New York, NY 10016, USA. 2 Proteomics Laboratory, Department of Biochemistry and Molecular Pharmacology, New York University School of Medicine, New York, NY 10016, USA. Correspondence and requests for materials should be addressed to S.S. (email: [email protected]) NATURE COMMUNICATIONS | 8: 2214 | DOI: 10.1038/s41467-017-02363-w | www.nature.com/naturecommunications 1 ARTICLE NATURE COMMUNICATIONS | DOI: 10.1038/s41467-017-02363-w ankyrases function in cellular pathways that are critical to function in human cells will provide insights into the clinical cancer cell growth including telomere cohesion and length utility of tankyrase inhibitors. -
A Peripheral Blood Gene Expression Signature to Diagnose Subclinical Acute Rejection
CLINICAL RESEARCH www.jasn.org A Peripheral Blood Gene Expression Signature to Diagnose Subclinical Acute Rejection Weijia Zhang,1 Zhengzi Yi,1 Karen L. Keung,2 Huimin Shang,3 Chengguo Wei,1 Paolo Cravedi,1 Zeguo Sun,1 Caixia Xi,1 Christopher Woytovich,1 Samira Farouk,1 Weiqing Huang,1 Khadija Banu,1 Lorenzo Gallon,4 Ciara N. Magee,5 Nader Najafian,5 Milagros Samaniego,6 Arjang Djamali ,7 Stephen I. Alexander,2 Ivy A. Rosales,8 Rex Neal Smith,8 Jenny Xiang,3 Evelyne Lerut,9 Dirk Kuypers,10,11 Maarten Naesens ,10,11 Philip J. O’Connell,2 Robert Colvin,8 Madhav C. Menon,1 and Barbara Murphy1 Due to the number of contributing authors, the affiliations are listed at the end of this article. ABSTRACT Background In kidney transplant recipients, surveillance biopsies can reveal, despite stable graft function, histologic features of acute rejection and borderline changes that are associated with undesirable graft outcomes. Noninvasive biomarkers of subclinical acute rejection are needed to avoid the risks and costs associated with repeated biopsies. Methods We examined subclinical histologic and functional changes in kidney transplant recipients from the prospective Genomics of Chronic Allograft Rejection (GoCAR) study who underwent surveillance biopsies over 2 years, identifying those with subclinical or borderline acute cellular rejection (ACR) at 3 months (ACR-3) post-transplant. We performed RNA sequencing on whole blood collected from 88 indi- viduals at the time of 3-month surveillance biopsy to identify transcripts associated with ACR-3, developed a novel sequencing-based targeted expression assay, and validated this gene signature in an independent cohort. -
Common Differentially Expressed Genes and Pathways Correlating Both Coronary Artery Disease and Atrial Fibrillation
EXCLI Journal 2021;20:126-141– ISSN 1611-2156 Received: December 08, 2020, accepted: January 11, 2021, published: January 18, 2021 Supplementary material to: Original article: COMMON DIFFERENTIALLY EXPRESSED GENES AND PATHWAYS CORRELATING BOTH CORONARY ARTERY DISEASE AND ATRIAL FIBRILLATION Youjing Zheng, Jia-Qiang He* Department of Biomedical Sciences and Pathobiology, College of Veterinary Medicine, Virginia Tech, Blacksburg, VA 24061, USA * Corresponding author: Jia-Qiang He, Department of Biomedical Sciences and Pathobiology, Virginia Tech, Phase II, Room 252B, Blacksburg, VA 24061, USA. Tel: 1-540-231-2032. E-mail: [email protected] https://orcid.org/0000-0002-4825-7046 Youjing Zheng https://orcid.org/0000-0002-0640-5960 Jia-Qiang He http://dx.doi.org/10.17179/excli2020-3262 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/). Supplemental Table 1: Abbreviations used in the paper Abbreviation Full name ABCA5 ATP binding cassette subfamily A member 5 ABCB6 ATP binding cassette subfamily B member 6 (Langereis blood group) ABCB9 ATP binding cassette subfamily B member 9 ABCC10 ATP binding cassette subfamily C member 10 ABCC13 ATP binding cassette subfamily C member 13 (pseudogene) ABCC5 ATP binding cassette subfamily C member 5 ABCD3 ATP binding cassette subfamily D member 3 ABCE1 ATP binding cassette subfamily E member 1 ABCG1 ATP binding cassette subfamily G member 1 ABCG4 ATP binding cassette subfamily G member 4 ABHD18 Abhydrolase domain -
Figure S1. Reverse Transcription‑Quantitative PCR Analysis of ETV5 Mrna Expression Levels in Parental and ETV5 Stable Transfectants
Figure S1. Reverse transcription‑quantitative PCR analysis of ETV5 mRNA expression levels in parental and ETV5 stable transfectants. (A) Hec1a and Hec1a‑ETV5 EC cell lines; (B) Ishikawa and Ishikawa‑ETV5 EC cell lines. **P<0.005, unpaired Student's t‑test. EC, endometrial cancer; ETV5, ETS variant transcription factor 5. Figure S2. Survival analysis of sample clusters 1‑4. Kaplan Meier graphs for (A) recurrence‑free and (B) overall survival. Survival curves were constructed using the Kaplan‑Meier method, and differences between sample cluster curves were analyzed by log‑rank test. Figure S3. ROC analysis of hub genes. For each gene, ROC curve (left) and mRNA expression levels (right) in control (n=35) and tumor (n=545) samples from The Cancer Genome Atlas Uterine Corpus Endometrioid Cancer cohort are shown. mRNA levels are expressed as Log2(x+1), where ‘x’ is the RSEM normalized expression value. ROC, receiver operating characteristic. Table SI. Clinicopathological characteristics of the GSE17025 dataset. Characteristic n % Atrophic endometrium 12 (postmenopausal) (Control group) Tumor stage I 91 100 Histology Endometrioid adenocarcinoma 79 86.81 Papillary serous 12 13.19 Histological grade Grade 1 30 32.97 Grade 2 36 39.56 Grade 3 25 27.47 Myometrial invasiona Superficial (<50%) 67 74.44 Deep (>50%) 23 25.56 aMyometrial invasion information was available for 90 of 91 tumor samples. Table SII. Clinicopathological characteristics of The Cancer Genome Atlas Uterine Corpus Endometrioid Cancer dataset. Characteristic n % Solid tissue normal 16 Tumor samples Stagea I 226 68.278 II 19 5.740 III 70 21.148 IV 16 4.834 Histology Endometrioid 271 81.381 Mixed 10 3.003 Serous 52 15.616 Histological grade Grade 1 78 23.423 Grade 2 91 27.327 Grade 3 164 49.249 Molecular subtypeb POLE 17 7.328 MSI 65 28.017 CN Low 90 38.793 CN High 60 25.862 CN, copy number; MSI, microsatellite instability; POLE, DNA polymerase ε. -
Mechanisms of Action of Coxiella Burnetii Effectors Inferred from Host-Pathogen Protein Interactions
RESEARCH ARTICLE Mechanisms of action of Coxiella burnetii effectors inferred from host-pathogen protein interactions Anders Wallqvist1, Hao Wang1, Nela Zavaljevski1, Vesna MemisÏević1, Keehwan Kwon2, Rembert Pieper2, Seesandra V. Rajagopala2, Jaques Reifman1* 1 Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Fort Detrick, Maryland, United States of America, 2 J. Craig Venter Institute, Rockville, Maryland, United States of America a1111111111 a1111111111 * [email protected] a1111111111 a1111111111 a1111111111 Abstract Coxiella burnetii is an obligate Gram-negative intracellular pathogen and the etiological agent of Q fever. Successful infection requires a functional Type IV secretion system, which OPEN ACCESS translocates more than 100 effector proteins into the host cytosol to establish the infection, Citation: Wallqvist A, Wang H, Zavaljevski N, restructure the intracellular host environment, and create a parasitophorous vacuole where MemisÏević V, Kwon K, Pieper R, et al. (2017) the replicating bacteria reside. We used yeast two-hybrid (Y2H) screening of 33 selected C. Mechanisms of action of Coxiella burnetii effectors burnetii effectors against whole genome human and murine proteome libraries to generate inferred from host-pathogen protein interactions. a map of potential host-pathogen protein-protein interactions (PPIs). We detected 273 PLoS ONE 12(11): e0188071. https://doi.org/ 10.1371/journal.pone.0188071 unique interactions between 20 pathogen and 247 human proteins, and 157 between 17 pathogen and 137 murine proteins. We used orthology to combine the data and create a sin- Editor: Zhao-Qing Luo, Purdue University, UNITED STATES gle host-pathogen interaction network containing 415 unique interactions between 25 C. -
Bioinformatics Tools for the Analysis of Gene-Phenotype Relationships Coupled with a Next Generation Chip-Sequencing Data Processing Pipeline
Bioinformatics Tools for the Analysis of Gene-Phenotype Relationships Coupled with a Next Generation ChIP-Sequencing Data Processing Pipeline Erinija Pranckeviciene Thesis submitted to the Faculty of Graduate and Postdoctoral Studies in partial fulfillment of the requirements for the Doctorate in Philosophy degree in Cellular and Molecular Medicine Department of Cellular and Molecular Medicine Faculty of Medicine University of Ottawa c Erinija Pranckeviciene, Ottawa, Canada, 2015 Abstract The rapidly advancing high-throughput and next generation sequencing technologies facilitate deeper insights into the molecular mechanisms underlying the expression of phenotypes in living organisms. Experimental data and scientific publications following this technological advance- ment have rapidly accumulated in public databases. Meaningful analysis of currently avail- able data in genomic databases requires sophisticated computational tools and algorithms, and presents considerable challenges to molecular biologists without specialized training in bioinfor- matics. To study their phenotype of interest molecular biologists must prioritize large lists of poorly characterized genes generated in high-throughput experiments. To date, prioritization tools have primarily been designed to work with phenotypes of human diseases as defined by the genes known to be associated with those diseases. There is therefore a need for more prioritiza- tion tools for phenotypes which are not related with diseases generally or diseases with which no genes have yet been associated in particular. Chromatin immunoprecipitation followed by next generation sequencing (ChIP-Seq) is a method of choice to study the gene regulation processes responsible for the expression of cellular phenotypes. Among publicly available computational pipelines for the processing of ChIP-Seq data, there is a lack of tools for the downstream analysis of composite motifs and preferred binding distances of the DNA binding proteins. -
Mouse Parp16 Knockout Project (CRISPR/Cas9)
https://www.alphaknockout.com Mouse Parp16 Knockout Project (CRISPR/Cas9) Objective: To create a Parp16 knockout Mouse model (C57BL/6J) by CRISPR/Cas-mediated genome engineering. Strategy summary: The Parp16 gene (NCBI Reference Sequence: NM_177460 ; Ensembl: ENSMUSG00000032392 ) is located on Mouse chromosome 9. 7 exons are identified, with the ATG start codon in exon 2 and the TGA stop codon in exon 7 (Transcript: ENSMUST00000069000). Exon 3~5 will be selected as target site. Cas9 and gRNA will be co-injected into fertilized eggs for KO Mouse production. The pups will be genotyped by PCR followed by sequencing analysis. Note: Exon 3 starts from about 18.12% of the coding region. Exon 3~5 covers 53.52% of the coding region. The size of effective KO region: ~7788 bp. The KO region does not have any other known gene. Page 1 of 9 https://www.alphaknockout.com Overview of the Targeting Strategy Wildtype allele 5' gRNA region gRNA region 3' 1 3 4 5 7 Legends Exon of mouse Parp16 Knockout region Page 2 of 9 https://www.alphaknockout.com Overview of the Dot Plot (up) Window size: 15 bp Forward Reverse Complement Sequence 12 Note: The 2000 bp section upstream of Exon 3 is aligned with itself to determine if there are tandem repeats. Tandem repeats are found in the dot plot matrix. The gRNA site is selected outside of these tandem repeats. Overview of the Dot Plot (down) Window size: 15 bp Forward Reverse Complement Sequence 12 Note: The 2000 bp section downstream of Exon 5 is aligned with itself to determine if there are tandem repeats. -
Supplementary Tables S1-S3
Supplementary Table S1: Real time RT-PCR primers COX-2 Forward 5’- CCACTTCAAGGGAGTCTGGA -3’ Reverse 5’- AAGGGCCCTGGTGTAGTAGG -3’ Wnt5a Forward 5’- TGAATAACCCTGTTCAGATGTCA -3’ Reverse 5’- TGTACTGCATGTGGTCCTGA -3’ Spp1 Forward 5'- GACCCATCTCAGAAGCAGAA -3' Reverse 5'- TTCGTCAGATTCATCCGAGT -3' CUGBP2 Forward 5’- ATGCAACAGCTCAACACTGC -3’ Reverse 5’- CAGCGTTGCCAGATTCTGTA -3’ Supplementary Table S2: Genes synergistically regulated by oncogenic Ras and TGF-β AU-rich probe_id Gene Name Gene Symbol element Fold change RasV12 + TGF-β RasV12 TGF-β 1368519_at serine (or cysteine) peptidase inhibitor, clade E, member 1 Serpine1 ARE 42.22 5.53 75.28 1373000_at sushi-repeat-containing protein, X-linked 2 (predicted) Srpx2 19.24 25.59 73.63 1383486_at Transcribed locus --- ARE 5.93 27.94 52.85 1367581_a_at secreted phosphoprotein 1 Spp1 2.46 19.28 49.76 1368359_a_at VGF nerve growth factor inducible Vgf 3.11 4.61 48.10 1392618_at Transcribed locus --- ARE 3.48 24.30 45.76 1398302_at prolactin-like protein F Prlpf ARE 1.39 3.29 45.23 1392264_s_at serine (or cysteine) peptidase inhibitor, clade E, member 1 Serpine1 ARE 24.92 3.67 40.09 1391022_at laminin, beta 3 Lamb3 2.13 3.31 38.15 1384605_at Transcribed locus --- 2.94 14.57 37.91 1367973_at chemokine (C-C motif) ligand 2 Ccl2 ARE 5.47 17.28 37.90 1369249_at progressive ankylosis homolog (mouse) Ank ARE 3.12 8.33 33.58 1398479_at ryanodine receptor 3 Ryr3 ARE 1.42 9.28 29.65 1371194_at tumor necrosis factor alpha induced protein 6 Tnfaip6 ARE 2.95 7.90 29.24 1386344_at Progressive ankylosis homolog (mouse) -
NRF1) Coordinates Changes in the Transcriptional and Chromatin Landscape Affecting Development and Progression of Invasive Breast Cancer
Florida International University FIU Digital Commons FIU Electronic Theses and Dissertations University Graduate School 11-7-2018 Decipher Mechanisms by which Nuclear Respiratory Factor One (NRF1) Coordinates Changes in the Transcriptional and Chromatin Landscape Affecting Development and Progression of Invasive Breast Cancer Jairo Ramos [email protected] Follow this and additional works at: https://digitalcommons.fiu.edu/etd Part of the Clinical Epidemiology Commons Recommended Citation Ramos, Jairo, "Decipher Mechanisms by which Nuclear Respiratory Factor One (NRF1) Coordinates Changes in the Transcriptional and Chromatin Landscape Affecting Development and Progression of Invasive Breast Cancer" (2018). FIU Electronic Theses and Dissertations. 3872. https://digitalcommons.fiu.edu/etd/3872 This work is brought to you for free and open access by the University Graduate School at FIU Digital Commons. It has been accepted for inclusion in FIU Electronic Theses and Dissertations by an authorized administrator of FIU Digital Commons. For more information, please contact [email protected]. FLORIDA INTERNATIONAL UNIVERSITY Miami, Florida DECIPHER MECHANISMS BY WHICH NUCLEAR RESPIRATORY FACTOR ONE (NRF1) COORDINATES CHANGES IN THE TRANSCRIPTIONAL AND CHROMATIN LANDSCAPE AFFECTING DEVELOPMENT AND PROGRESSION OF INVASIVE BREAST CANCER A dissertation submitted in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY in PUBLIC HEALTH by Jairo Ramos 2018 To: Dean Tomás R. Guilarte Robert Stempel College of Public Health and Social Work This dissertation, Written by Jairo Ramos, and entitled Decipher Mechanisms by Which Nuclear Respiratory Factor One (NRF1) Coordinates Changes in the Transcriptional and Chromatin Landscape Affecting Development and Progression of Invasive Breast Cancer, having been approved in respect to style and intellectual content, is referred to you for judgment.