Comparative Mrna and Mirna Expression in European
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Gene Expression Profiling of Human Oocytes Developed and Matured in Vivo Or in Vitro
Hindawi Publishing Corporation BioMed Research International Volume 2013, Article ID 879489, 20 pages http://dx.doi.org/10.1155/2013/879489 Review Article Gene Expression Profiling of Human Oocytes Developed and Matured In Vivo or In Vitro Irma Virant-Klun,1 Katja Knez,1 Tomaz Tomazevic,1 and Thomas Skutella2 1 Reproductive Unit, Department of Obstetrics and Gynecology, University Medical Centre Ljubljana, Slajmerjeva 3, 1000 Ljubljana, Slovenia 2 Institute for Anatomy and Cell Biology, Medical Faculty, University of Heidelberg, 69120 Heidelberg, Germany Correspondence should be addressed to Irma Virant-Klun; [email protected] Received 30 September 2012; Revised 7 December 2012; Accepted 8 December 2012 Academic Editor: Xuan Jin Copyright © 2013 Irma Virant-Klun et al. This 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. The quality of the human oocyte determines the success of fertilization and affects the consequent embryo development, pregnancy and birth; it therefore serves as a basis for human reproduction and fertility. The possibility to evaluate oocyte quality in the in vitro fertilization programme is very limited. The only criterion which is commonly used to evaluate oocyte quality is its morphology. There is a mass of oocytes in the in vitro fertilization programme which are not fertilized in spite of normal morphology. In the past, several attempts focused on oocyte gene expression profiling by different approaches. The results elucidated groups of genes related to the human oocyte. It was confirmed that some factors, such as oocyte in vitro maturation, are detectable at the molecular level of human oocytes and their polar bodies in terms of gene expression profile. -
Mathiomica: an Integrative Platform for Dynamic Omics George I
MathIOmica: An Integrative Platform for Dynamic Omics George I. Mias1,*, Tahir Yusufaly2, Raeuf Roushangar1, Lavida R. K. Brooks1, Vikas V. Singh1, and Christina Christou3 1Michigan State University, Biochemistry and Molecular Biology, East Lansing, MI 48824, USA 2University of Southern California, Department of Physics and Astronomy, Los Angeles, CA, 90089, USA 3Mercy Cancer Center, Department of Radiation Oncology, Mason City, IA 50401, USA *[email protected] SUPPLEMENTARY NOTE 1 1 1 MathIOmica: Omics Analysis Tutorial Loading the MathIOmica Package Metabolomic Data Data in MathIOmica Combined Data Clustering Transcriptome Data Visualization Proteomic Data Annotation and Enrichment MathIOmica is an omics analysis package designed to facilitate method development for the analysis of multiple omics in Mathematica, particularly for dynamics (time series/longitudinal data). This extensive tutorial follows the analysis of multiple dynamic omics data (transcriptomics, proteomics, and metabolomics from human samples). Various MathIOmica functions are introduced in the tutorial, including additional discussion of related functionality. We should note that the approach methods are simply an illustration of MathIOmica functionality, and should not be considered as a definitive appoach. Additionally, certain details are included to illustrate common complications (e.g. renaming samples, combining datasets, transforming accessions from one database to another, dealing with replicates and Missing data, etc.). After a brief discussion of data in MathIOmica, each example data (transcriptome, proteome and metabolome) are imported and preprocessed. Next a simulation is carried out to obtain datasets for each omics used to assess statistical significance cutoffs. The datasets are combined, and classified for time series patterns, followed by clustering. The clusters are visualized, and biological annotation of Gene Ontology (GO) and pathway analysis (KEGG: Kyoto Encyclopedia of Genes and Genomes) are finally considered. -
Molecular Dynamics and Evolutionary Aspects of the Transition from the Fully Grown Oocyte to Embryo
Downloaded from genesdev.cshlp.org on September 26, 2021 - Published by Cold Spring Harbor Laboratory Press Cracking the egg: molecular dynamics and evolutionary aspects of the transition from the fully grown oocyte to embryo Alexei V. Evsikov,1,5 Joel H. Graber,1 J. Michael Brockman,1,2 Aleš Hampl,3 Andrea E. Holbrook,1 Priyam Singh,1,2 John J. Eppig,1 Davor Solter,1,4 and Barbara B. Knowles1 1The Jackson Laboratory, Bar Harbor, Maine 04609, USA; 2 Bioinformatics Program, Boston University, Boston, Massachusetts 02215, USA; 3Masaryk University Brno and Institute of Experimental Medicine, 625 00 Brno, Czech Republic; 4Max Planck Institute of Immunobiology, 79108 Freiburg, Germany Fully grown oocytes (FGOs) contain all the necessary transcripts to activate molecular pathways underlying the oocyte-to-embryo transition (OET). To elucidate this critical period of development, an extensive survey of the FGO transcriptome was performed by analyzing 19,000 expressed sequence tags of the Mus musculus FGO cDNA library. Expression of 5400 genes and transposable elements is reported. For a majority of genes expressed in mouse FGOs, homologs transcribed in eggs of Xenopus laevis or Ciona intestinalis were found, pinpointing evolutionary conservation of most regulatory cascades underlying the OET in chordates. A large proportion of identified genes belongs to several gene families with oocyte-restricted expression, a likely result of lineage-specific genomic duplications. Gene loss by mutation and expression in female germline of retrotransposed genes specific to M. musculus is documented. These findings indicate rapid diversification of genes involved in female reproduction. Comparison of the FGO and two-cell embryo transcriptomes demarcated the processes important for oogenesis from those involved in OET and identified novel motifs in maternal mRNAs associated with transcript stability. -
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. -
Epigenome-Wide Exploratory Study of Monozygotic Twins Suggests Differentially Methylated Regions to Associate with Hand Grip Strength
Biogerontology (2019) 20:627–647 https://doi.org/10.1007/s10522-019-09818-1 (0123456789().,-volV)( 0123456789().,-volV) RESEARCH ARTICLE Epigenome-wide exploratory study of monozygotic twins suggests differentially methylated regions to associate with hand grip strength Mette Soerensen . Weilong Li . Birgit Debrabant . Marianne Nygaard . Jonas Mengel-From . Morten Frost . Kaare Christensen . Lene Christiansen . Qihua Tan Received: 15 April 2019 / Accepted: 24 June 2019 / Published online: 28 June 2019 Ó The Author(s) 2019 Abstract Hand grip strength is a measure of mus- significant CpG sites or pathways were found, how- cular strength and is used to study age-related loss of ever two of the suggestive top CpG sites were mapped physical capacity. In order to explore the biological to the COL6A1 and CACNA1B genes, known to be mechanisms that influence hand grip strength varia- related to muscular dysfunction. By investigating tion, an epigenome-wide association study (EWAS) of genomic regions using the comb-p algorithm, several hand grip strength in 672 middle-aged and elderly differentially methylated regions in regulatory monozygotic twins (age 55–90 years) was performed, domains were identified as significantly associated to using both individual and twin pair level analyses, the hand grip strength, and pathway analyses of these latter controlling the influence of genetic variation. regions revealed significant pathways related to the Moreover, as measurements of hand grip strength immune system, autoimmune disorders, including performed over 8 years were available in the elderly diabetes type 1 and viral myocarditis, as well as twins (age 73–90 at intake), a longitudinal EWAS was negative regulation of cell differentiation. -
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, -
ZP4 (C-Term) Rabbit Polyclonal Antibody – AP54737PU-N | Origene
OriGene Technologies, Inc. 9620 Medical Center Drive, Ste 200 Rockville, MD 20850, US Phone: +1-888-267-4436 [email protected] EU: [email protected] CN: [email protected] Product datasheet for AP54737PU-N ZP4 (C-term) Rabbit Polyclonal Antibody Product data: Product Type: Primary Antibodies Applications: IHC, WB Recommended Dilution: ELISA: 1:1;000. Western blot: 1:100~500. Immunohistochemistry on paraffin sections: 1:10~50. Reactivity: Human Host: Rabbit Isotype: Ig Clonality: Polyclonal Immunogen: KLH conjugated synthetic peptide between 452-482 amino acids from the C-terminal region of human ZP4 Specificity: This antibody detects ZP4 / ZPB (C-term). Formulation: PBS with 0.09% (W/V) sodium azide State: Aff - Purified State: Liquid Ig fraction Concentration: lot specific Purification: Protein A column followed by peptide affinity purification Conjugation: Unconjugated Storage: Store at 2 - 8 °C for up to six months or (in aliquots) at -20 °C for longer. Avoid repeated freezing and thawing. Stability: Shelf life: one year from despatch. Gene Name: Homo sapiens zona pellucida glycoprotein 4 (ZP4) Database Link: Entrez Gene 57829 Human Q12836 This product is to be used for laboratory only. Not for diagnostic or therapeutic use. View online » ©2021 OriGene Technologies, Inc., 9620 Medical Center Drive, Ste 200, Rockville, MD 20850, US 1 / 2 ZP4 (C-term) Rabbit Polyclonal Antibody – AP54737PU-N Background: The zona pellucida is an extracellular matrix that surrounds the oocyte and early embryo. It is composed primarily of three or four glycoproteins with various functions during fertilization and preimplantation development. The nascent protein contains a N-terminal signal peptide sequence, a conserved ZP domain, a consensus furin cleavage site, and a C-terminal transmembrane domain. -
Identification of Potential Key Genes and Pathway Linked with Sporadic Creutzfeldt-Jakob Disease Based on Integrated Bioinformatics Analyses
medRxiv preprint doi: https://doi.org/10.1101/2020.12.21.20248688; this version posted December 24, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission. Identification of potential key genes and pathway linked with sporadic Creutzfeldt-Jakob disease based on integrated bioinformatics analyses Basavaraj Vastrad1, Chanabasayya Vastrad*2 , Iranna Kotturshetti 1. Department of Biochemistry, Basaveshwar College of Pharmacy, Gadag, Karnataka 582103, India. 2. Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karanataka, India. 3. Department of Ayurveda, Rajiv Gandhi Education Society`s Ayurvedic Medical College, Ron, Karnataka 562209, India. * Chanabasayya Vastrad [email protected] Ph: +919480073398 Chanabasava Nilaya, Bharthinagar, Dharwad 580001 , Karanataka, India NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice. medRxiv preprint doi: https://doi.org/10.1101/2020.12.21.20248688; this version posted December 24, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission. Abstract Sporadic Creutzfeldt-Jakob disease (sCJD) is neurodegenerative disease also called prion disease linked with poor prognosis. The aim of the current study was to illuminate the underlying molecular mechanisms of sCJD. The mRNA microarray dataset GSE124571 was downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were screened. -
Supplementary Materials
Supplementary materials Supplementary Table S1: MGNC compound library Ingredien Molecule Caco- Mol ID MW AlogP OB (%) BBB DL FASA- HL t Name Name 2 shengdi MOL012254 campesterol 400.8 7.63 37.58 1.34 0.98 0.7 0.21 20.2 shengdi MOL000519 coniferin 314.4 3.16 31.11 0.42 -0.2 0.3 0.27 74.6 beta- shengdi MOL000359 414.8 8.08 36.91 1.32 0.99 0.8 0.23 20.2 sitosterol pachymic shengdi MOL000289 528.9 6.54 33.63 0.1 -0.6 0.8 0 9.27 acid Poricoic acid shengdi MOL000291 484.7 5.64 30.52 -0.08 -0.9 0.8 0 8.67 B Chrysanthem shengdi MOL004492 585 8.24 38.72 0.51 -1 0.6 0.3 17.5 axanthin 20- shengdi MOL011455 Hexadecano 418.6 1.91 32.7 -0.24 -0.4 0.7 0.29 104 ylingenol huanglian MOL001454 berberine 336.4 3.45 36.86 1.24 0.57 0.8 0.19 6.57 huanglian MOL013352 Obacunone 454.6 2.68 43.29 0.01 -0.4 0.8 0.31 -13 huanglian MOL002894 berberrubine 322.4 3.2 35.74 1.07 0.17 0.7 0.24 6.46 huanglian MOL002897 epiberberine 336.4 3.45 43.09 1.17 0.4 0.8 0.19 6.1 huanglian MOL002903 (R)-Canadine 339.4 3.4 55.37 1.04 0.57 0.8 0.2 6.41 huanglian MOL002904 Berlambine 351.4 2.49 36.68 0.97 0.17 0.8 0.28 7.33 Corchorosid huanglian MOL002907 404.6 1.34 105 -0.91 -1.3 0.8 0.29 6.68 e A_qt Magnogrand huanglian MOL000622 266.4 1.18 63.71 0.02 -0.2 0.2 0.3 3.17 iolide huanglian MOL000762 Palmidin A 510.5 4.52 35.36 -0.38 -1.5 0.7 0.39 33.2 huanglian MOL000785 palmatine 352.4 3.65 64.6 1.33 0.37 0.7 0.13 2.25 huanglian MOL000098 quercetin 302.3 1.5 46.43 0.05 -0.8 0.3 0.38 14.4 huanglian MOL001458 coptisine 320.3 3.25 30.67 1.21 0.32 0.9 0.26 9.33 huanglian MOL002668 Worenine -
Literature Mining Sustains and Enhances Knowledge Discovery from Omic Studies
LITERATURE MINING SUSTAINS AND ENHANCES KNOWLEDGE DISCOVERY FROM OMIC STUDIES by Rick Matthew Jordan B.S. Biology, University of Pittsburgh, 1996 M.S. Molecular Biology/Biotechnology, East Carolina University, 2001 M.S. Biomedical Informatics, University of Pittsburgh, 2005 Submitted to the Graduate Faculty of School of Medicine in partial fulfillment of the requirements for the degree of Doctor of Philosophy University of Pittsburgh 2016 UNIVERSITY OF PITTSBURGH SCHOOL OF MEDICINE This dissertation was presented by Rick Matthew Jordan It was defended on December 2, 2015 and approved by Shyam Visweswaran, M.D., Ph.D., Associate Professor Rebecca Jacobson, M.D., M.S., Professor Songjian Lu, Ph.D., Assistant Professor Dissertation Advisor: Vanathi Gopalakrishnan, Ph.D., Associate Professor ii Copyright © by Rick Matthew Jordan 2016 iii LITERATURE MINING SUSTAINS AND ENHANCES KNOWLEDGE DISCOVERY FROM OMIC STUDIES Rick Matthew Jordan, M.S. University of Pittsburgh, 2016 Genomic, proteomic and other experimentally generated data from studies of biological systems aiming to discover disease biomarkers are currently analyzed without sufficient supporting evidence from the literature due to complexities associated with automated processing. Extracting prior knowledge about markers associated with biological sample types and disease states from the literature is tedious, and little research has been performed to understand how to use this knowledge to inform the generation of classification models from ‘omic’ data. Using pathway analysis methods to better understand the underlying biology of complex diseases such as breast and lung cancers is state-of-the-art. However, the problem of how to combine literature- mining evidence with pathway analysis evidence is an open problem in biomedical informatics research. -
Investigation of the Role of Capicua in the FGF Signalling Pathway and the Wound Response
Investigation of the role of Capicua in the FGF signalling pathway and the wound response Laura May-Seen Cowell Master by Research University of York Biology September 2019 Abstract Fibroblast growth factor (FGF) signalling is critical for the initiation and regulation of multiple developmental processes including gastrulation, mesoderm induction and limb development. Despite extensive understanding of FGF signal transduction via tyrosine kinase receptors (RTKs), the specific mechanism responsible for regulation of target gene transcription is still not fully understood. The protein Capicua (CIC) has been linked to transcriptional regulation in RTK signalling via the ERK pathway in multiple organisms. ERK signalling cascades also mediate wound signal transduction and transcription of associated genes. We hypothesise that transcription of a subset of FGF target genes, and genes involved in the wound response, rely on ERK mediated relief of CIC transcriptional repression. The aims of this project were to establish if CIC operates downstream of FGF signalling through analysis and validation of RNA-seq data, and to investigate the relationship between CIC and ERK in FGF signalling and wound healing in Xenopus embryos. The work in this thesis shows that CIC knockdown and FGF overexpressing embryos exhibit similar phenotypes and transcriptomes. Immunostaining for myc-tagged CIC indicates that CIC expression is reduced following activation of FGF signalling or the wound response. 75% of the putative CIC and FGF regulated genes analysed have enriched CIC binding sites and 75% were upregulated in RT- PCR analysis of CIC knockdown and FGF overexpressing embryos. Additionally, genes associated with wound healing (fos and gadd45a) are upregulated in CIC knockdown embryos. -
Towards Personalized Medicine in Psychiatry: Focus on Suicide
TOWARDS PERSONALIZED MEDICINE IN PSYCHIATRY: FOCUS ON SUICIDE Daniel F. Levey Submitted to the faculty of the University Graduate School in partial fulfillment of the requirements for the degree Doctor of Philosophy in the Program of Medical Neuroscience, Indiana University April 2017 ii Accepted by the Graduate Faculty, Indiana University, in partial fulfillment of the requirements for the degree of Doctor of Philosophy. Andrew J. Saykin, Psy. D. - Chair ___________________________ Alan F. Breier, M.D. Doctoral Committee Gerry S. Oxford, Ph.D. December 13, 2016 Anantha Shekhar, M.D., Ph.D. Alexander B. Niculescu III, M.D., Ph.D. iii Dedication This work is dedicated to all those who suffer, whether their pain is physical or psychological. iv Acknowledgements The work I have done over the last several years would not have been possible without the contributions of many people. I first need to thank my terrific mentor and PI, Dr. Alexander Niculescu. He has continuously given me advice and opportunities over the years even as he has suffered through my many mistakes, and I greatly appreciate his patience. The incredible passion he brings to his work every single day has been inspirational. It has been an at times painful but often exhilarating 5 years. I need to thank Helen Le-Niculescu for being a wonderful colleague and mentor. I learned a lot about organization and presentation working alongside her, and her tireless work ethic was an excellent example for a new graduate student. I had the pleasure of working with a number of great people over the years. Mikias Ayalew showed me the ropes of the lab and began my understanding of the power of algorithms.