Comparative Genomics Using Fugu Reveals Insights Into Regulatory Comment Subfunctionalization Adam Woolfe*† and Greg Elgar*
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Proteomic Profile of Human Spermatozoa in Healthy And
Cao et al. Reproductive Biology and Endocrinology (2018) 16:16 https://doi.org/10.1186/s12958-018-0334-1 REVIEW Open Access Proteomic profile of human spermatozoa in healthy and asthenozoospermic individuals Xiaodan Cao, Yun Cui, Xiaoxia Zhang, Jiangtao Lou, Jun Zhou, Huafeng Bei and Renxiong Wei* Abstract Asthenozoospermia is considered as a common cause of male infertility and characterized by reduced sperm motility. However, the molecular mechanism that impairs sperm motility remains unknown in most cases. In the present review, we briefly reviewed the proteome of spermatozoa and seminal plasma in asthenozoospermia and considered post-translational modifications in spermatozoa of asthenozoospermia. The reduction of sperm motility in asthenozoospermic patients had been attributed to factors, for instance, energy metabolism dysfunction or structural defects in the sperm-tail protein components and the differential proteins potentially involved in sperm motility such as COX6B, ODF, TUBB2B were described. Comparative proteomic analysis open a window to discover the potential pathogenic mechanisms of asthenozoospermia and the biomarkers with clinical significance. Keywords: Proteome, Spermatozoa, Sperm motility, Asthenozoospermia, Infertility Background fertilization failure [4] and it has become clear that iden- Infertility is defined as the lack of ability to achieve a tifying the precise proteins and the pathways involved in clinical pregnancy after one year or more of unprotected sperm motility is needed [5]. and well-timed intercourse with the same partner [1]. It is estimated that around 15% of couples of reproductive age present with infertility, and about half of the infertil- Application of proteomic techniques in male ity is associated with male partner [2, 3]. -
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. -
Genetic Analysis of Hereditary Sensory, Motor and Autonomic
Genetic analysis of hereditary sensory, motor and autonomic neuropathies, including a rat model Ming-Jen Lee A thesis submitted to the University of London for the degree of Doctor of Philosophy August 2002 Institute of Neurology University of London ProQuest Number: 10016056 All rights reserved INFORMATION TO ALL USERS The quality of this reproduction is dependent upon the quality of the copy submitted. In the unlikely event that the author did not send a complete manuscript and there are missing pages, these will be noted. Also, if material had to be removed, a note will indicate the deletion. uest. ProQuest 10016056 Published by ProQuest LLC(2016). Copyright of the Dissertation is held by the Author. All rights reserved. This work is protected against unauthorized copying under Title 17, United States Code. Microform Edition © ProQuest LLC. ProQuest LLC 789 East Eisenhower Parkway P.O. Box 1346 Ann Arbor, Ml 48106-1346 To my wife and my parents Who supported me throughout my studies. Acknowledgements I would like to thank Dr. Mike Groves and Professor Francesco Scaravilli, for their help in the animal breeding and phenotype characterization. I am also indebted to Dr. Dennis Stephenson, MacLaughlin Institute, Grate Fall, Montana, USA. for advice on positional cloning and on the construction of the rat/mouse/human comparative genetic map. His idea on BLAST searches between Celera mouse genome database and rat markers, made a breakthrough in selecting candidate genes, which lead me to identify the m f gene. I am grateful to Dr. Pete Dixon and Dr. Mary Davis for their advice on genetic linkage and physical mapping. -
The Role of Polyadenylation in the Induction of Inflammatory Genes
The role of polyadenylation in the induction of inflammatory genes Raj Gandhi BSc & ARCS Thesis submitted for the degree of Doctor of Philosophy September 2016 Declaration Except where acknowledged in the text, I declare that this thesis is my own work and is based on research that was undertaken by me in the School of Pharmacy, Faculty of Science, The University of Nottingham. i Acknowledgements First and foremost, I give thanks to my primary supervisor Dr. Cornelia de Moor. She supported me at every step, always made time for me whenever I needed it, and was sympathetic during times of difficulty. I feel very, very fortunate to have been her student. I would also like to thank Dr. Catherine Jopling for her advice and Dr. Graeme Thorn for being so patient and giving me so much help in understanding the bioinformatics parts of my project. I am grateful to Dr. Anna Piccinini and Dr. Sadaf Ashraf for filling in huge gaps in my knowledge about inflammation and osteoarthritis, and to Dr. Sunir Malla for help with the TAIL-seq work. I thank Dr. Richa Singhania and Kathryn Williams for proofreading. Dr. Hannah Parker was my “big sister” in the lab from my first day, and I am very grateful for all her help and for her friendship. My project was made all the more enjoyable/bearable by the members of the Gene Regulation and RNA Biology group, especially Jialiang Lin, Kathryn Williams, Dr. Richa Singhania, Aimée Parsons, Dan Smalley, and Hibah Al-Masmoum. Barbara Rampersad was a wonderful technician. Mike Thomas, James Williamson, Will Hawley, Tom Upton, and Jamie Ware were some of the best of friends I could have hoped to make in Nottingham. -
Physical and Linkage Mapping of Mammary-Derived Expressed Sequence Tags in Cattle
Genomics 83 (2004) 148–152 www.elsevier.com/locate/ygeno Physical and linkage mapping of mammary-derived expressed sequence tags in cattle E.E. Connor,a,* T.S. Sonstegard,a J.W. Keele,b G.L. Bennett,b J.L. Williams,c R. Papworth,c C.P. Van Tassell,a and M.S. Ashwella a U.S. Beltsville Agricultural Research Center, ARS, U.S. Department of Agriculture, 10300 Baltimore Avenue, Beltsville, MD 20705, USA b U.S. Meat Animal Research Center, ARS, U.S. Department of Agriculture, P.O. Box 166, Clay Center, NE 68933-0166, USA c Roslin Institute (Edinburgh), Roslin, Midlothian EH25 9PS, Scotland, United Kingdom Received 2 June 2003; accepted 5 July 2003 Abstract This study describes the physical and linkage mapping of 42 gene-associated markers developed from mammary gland-derived expressed sequence tags to the cattle genome. Of the markers, 25 were placed on the USDA reference linkage map and 37 were positioned on the Roslin 3000-rad radiation hybrid (RH) map, with 20 assignments shared between the maps. Although no novel regions of conserved synteny between the cattle and the human genomes were identified, the coverage was extended for bovine chromosomes 3, 7, 15, and 29 compared with previously published comparative maps between human and bovine genomes. Overall, these data improve the resolution of the human–bovine comparative maps and will assist future efforts to integrate bovine RH and linkage map data. Crown Copyright D 2003 Published by Elsevier Inc. All rights reserved. Keywords: RH mapping; Linkage mapping; SNP; Cattle; EST Selection of positional candidate genes controlling eco- pig [4,5], and cattle [6], and serve as a resource for nomically important traits in cattle requires a detailed candidate gene identification. -
Supplemental Information
Supplemental information Dissection of the genomic structure of the miR-183/96/182 gene. Previously, we showed that the miR-183/96/182 cluster is an intergenic miRNA cluster, located in a ~60-kb interval between the genes encoding nuclear respiratory factor-1 (Nrf1) and ubiquitin-conjugating enzyme E2H (Ube2h) on mouse chr6qA3.3 (1). To start to uncover the genomic structure of the miR- 183/96/182 gene, we first studied genomic features around miR-183/96/182 in the UCSC genome browser (http://genome.UCSC.edu/), and identified two CpG islands 3.4-6.5 kb 5’ of pre-miR-183, the most 5’ miRNA of the cluster (Fig. 1A; Fig. S1 and Seq. S1). A cDNA clone, AK044220, located at 3.2-4.6 kb 5’ to pre-miR-183, encompasses the second CpG island (Fig. 1A; Fig. S1). We hypothesized that this cDNA clone was derived from 5’ exon(s) of the primary transcript of the miR-183/96/182 gene, as CpG islands are often associated with promoters (2). Supporting this hypothesis, multiple expressed sequences detected by gene-trap clones, including clone D016D06 (3, 4), were co-localized with the cDNA clone AK044220 (Fig. 1A; Fig. S1). Clone D016D06, deposited by the German GeneTrap Consortium (GGTC) (http://tikus.gsf.de) (3, 4), was derived from insertion of a retroviral construct, rFlpROSAβgeo in 129S2 ES cells (Fig. 1A and C). The rFlpROSAβgeo construct carries a promoterless reporter gene, the β−geo cassette - an in-frame fusion of the β-galactosidase and neomycin resistance (Neor) gene (5), with a splicing acceptor (SA) immediately upstream, and a polyA signal downstream of the β−geo cassette (Fig. -
(P -Value<0.05, Fold Change≥1.4), 4 Vs. 0 Gy Irradiation
Table S1: Significant differentially expressed genes (P -Value<0.05, Fold Change≥1.4), 4 vs. 0 Gy irradiation Genbank Fold Change P -Value Gene Symbol Description Accession Q9F8M7_CARHY (Q9F8M7) DTDP-glucose 4,6-dehydratase (Fragment), partial (9%) 6.70 0.017399678 THC2699065 [THC2719287] 5.53 0.003379195 BC013657 BC013657 Homo sapiens cDNA clone IMAGE:4152983, partial cds. [BC013657] 5.10 0.024641735 THC2750781 Ciliary dynein heavy chain 5 (Axonemal beta dynein heavy chain 5) (HL1). 4.07 0.04353262 DNAH5 [Source:Uniprot/SWISSPROT;Acc:Q8TE73] [ENST00000382416] 3.81 0.002855909 NM_145263 SPATA18 Homo sapiens spermatogenesis associated 18 homolog (rat) (SPATA18), mRNA [NM_145263] AA418814 zw01a02.s1 Soares_NhHMPu_S1 Homo sapiens cDNA clone IMAGE:767978 3', 3.69 0.03203913 AA418814 AA418814 mRNA sequence [AA418814] AL356953 leucine-rich repeat-containing G protein-coupled receptor 6 {Homo sapiens} (exp=0; 3.63 0.0277936 THC2705989 wgp=1; cg=0), partial (4%) [THC2752981] AA484677 ne64a07.s1 NCI_CGAP_Alv1 Homo sapiens cDNA clone IMAGE:909012, mRNA 3.63 0.027098073 AA484677 AA484677 sequence [AA484677] oe06h09.s1 NCI_CGAP_Ov2 Homo sapiens cDNA clone IMAGE:1385153, mRNA sequence 3.48 0.04468495 AA837799 AA837799 [AA837799] Homo sapiens hypothetical protein LOC340109, mRNA (cDNA clone IMAGE:5578073), partial 3.27 0.031178378 BC039509 LOC643401 cds. [BC039509] Homo sapiens Fas (TNF receptor superfamily, member 6) (FAS), transcript variant 1, mRNA 3.24 0.022156298 NM_000043 FAS [NM_000043] 3.20 0.021043295 A_32_P125056 BF803942 CM2-CI0135-021100-477-g08 CI0135 Homo sapiens cDNA, mRNA sequence 3.04 0.043389246 BF803942 BF803942 [BF803942] 3.03 0.002430239 NM_015920 RPS27L Homo sapiens ribosomal protein S27-like (RPS27L), mRNA [NM_015920] Homo sapiens tumor necrosis factor receptor superfamily, member 10c, decoy without an 2.98 0.021202829 NM_003841 TNFRSF10C intracellular domain (TNFRSF10C), mRNA [NM_003841] 2.97 0.03243901 AB002384 C6orf32 Homo sapiens mRNA for KIAA0386 gene, partial cds. -
Proteomic Expression Profile in Human Temporomandibular Joint
diagnostics Article Proteomic Expression Profile in Human Temporomandibular Joint Dysfunction Andrea Duarte Doetzer 1,*, Roberto Hirochi Herai 1 , Marília Afonso Rabelo Buzalaf 2 and Paula Cristina Trevilatto 1 1 Graduate Program in Health Sciences, School of Medicine, Pontifícia Universidade Católica do Paraná (PUCPR), Curitiba 80215-901, Brazil; [email protected] (R.H.H.); [email protected] (P.C.T.) 2 Department of Biological Sciences, Bauru School of Dentistry, University of São Paulo, Bauru 17012-901, Brazil; [email protected] * Correspondence: [email protected]; Tel.: +55-41-991-864-747 Abstract: Temporomandibular joint dysfunction (TMD) is a multifactorial condition that impairs human’s health and quality of life. Its etiology is still a challenge due to its complex development and the great number of different conditions it comprises. One of the most common forms of TMD is anterior disc displacement without reduction (DDWoR) and other TMDs with distinct origins are condylar hyperplasia (CH) and mandibular dislocation (MD). Thus, the aim of this study is to identify the protein expression profile of synovial fluid and the temporomandibular joint disc of patients diagnosed with DDWoR, CH and MD. Synovial fluid and a fraction of the temporomandibular joint disc were collected from nine patients diagnosed with DDWoR (n = 3), CH (n = 4) and MD (n = 2). Samples were subjected to label-free nLC-MS/MS for proteomic data extraction, and then bioinformatics analysis were conducted for protein identification and functional annotation. The three Citation: Doetzer, A.D.; Herai, R.H.; TMD conditions showed different protein expression profiles, and novel proteins were identified Buzalaf, M.A.R.; Trevilatto, P.C. -
In This Table Protein Name, Uniprot Code, Gene Name P-Value
Supplementary Table S1: In this table protein name, uniprot code, gene name p-value and Fold change (FC) for each comparison are shown, for 299 of the 301 significantly regulated proteins found in both comparisons (p-value<0.01, fold change (FC) >+/-0.37) ALS versus control and FTLD-U versus control. Two uncharacterized proteins have been excluded from this list Protein name Uniprot Gene name p value FC FTLD-U p value FC ALS FTLD-U ALS Cytochrome b-c1 complex P14927 UQCRB 1.534E-03 -1.591E+00 6.005E-04 -1.639E+00 subunit 7 NADH dehydrogenase O95182 NDUFA7 4.127E-04 -9.471E-01 3.467E-05 -1.643E+00 [ubiquinone] 1 alpha subcomplex subunit 7 NADH dehydrogenase O43678 NDUFA2 3.230E-04 -9.145E-01 2.113E-04 -1.450E+00 [ubiquinone] 1 alpha subcomplex subunit 2 NADH dehydrogenase O43920 NDUFS5 1.769E-04 -8.829E-01 3.235E-05 -1.007E+00 [ubiquinone] iron-sulfur protein 5 ARF GTPase-activating A0A0C4DGN6 GIT1 1.306E-03 -8.810E-01 1.115E-03 -7.228E-01 protein GIT1 Methylglutaconyl-CoA Q13825 AUH 6.097E-04 -7.666E-01 5.619E-06 -1.178E+00 hydratase, mitochondrial ADP/ATP translocase 1 P12235 SLC25A4 6.068E-03 -6.095E-01 3.595E-04 -1.011E+00 MIC J3QTA6 CHCHD6 1.090E-04 -5.913E-01 2.124E-03 -5.948E-01 MIC J3QTA6 CHCHD6 1.090E-04 -5.913E-01 2.124E-03 -5.948E-01 Protein kinase C and casein Q9BY11 PACSIN1 3.837E-03 -5.863E-01 3.680E-06 -1.824E+00 kinase substrate in neurons protein 1 Tubulin polymerization- O94811 TPPP 6.466E-03 -5.755E-01 6.943E-06 -1.169E+00 promoting protein MIC C9JRZ6 CHCHD3 2.912E-02 -6.187E-01 2.195E-03 -9.781E-01 Mitochondrial 2- -
Definition of the Landscape of Promoter DNA Hypomethylation in Liver Cancer
Published OnlineFirst July 11, 2011; DOI: 10.1158/0008-5472.CAN-10-3823 Cancer Therapeutics, Targets, and Chemical Biology Research Definition of the Landscape of Promoter DNA Hypomethylation in Liver Cancer Barbara Stefanska1, Jian Huang4, Bishnu Bhattacharyya1, Matthew Suderman1,2, Michael Hallett3, Ze-Guang Han4, and Moshe Szyf1,2 Abstract We use hepatic cellular carcinoma (HCC), one of the most common human cancers, as a model to delineate the landscape of promoter hypomethylation in cancer. Using a combination of methylated DNA immunopre- cipitation and hybridization with comprehensive promoter arrays, we have identified approximately 3,700 promoters that are hypomethylated in tumor samples. The hypomethylated promoters appeared in clusters across the genome suggesting that a high-level organization underlies the epigenomic changes in cancer. In normal liver, most hypomethylated promoters showed an intermediate level of methylation and expression, however, high-CpG dense promoters showed the most profound increase in gene expression. The demethylated genes are mainly involved in cell growth, cell adhesion and communication, signal transduction, mobility, and invasion; functions that are essential for cancer progression and metastasis. The DNA methylation inhibitor, 5- aza-20-deoxycytidine, activated several of the genes that are demethylated and induced in tumors, supporting a causal role for demethylation in activation of these genes. Previous studies suggested that MBD2 was involved in demethylation of specific human breast and prostate cancer genes. Whereas MBD2 depletion in normal liver cells had little or no effect, we found that its depletion in human HCC and adenocarcinoma cells resulted in suppression of cell growth, anchorage-independent growth and invasiveness as well as an increase in promoter methylation and silencing of several of the genes that are hypomethylated in tumors. -
Bypass Budget Proposal for Fiscal Year 2020 �
Open Science, � Big Data, and You � Working Together to Treat and Prevent Alzheimer’s Disease and Related Dementias NIH BYPASS BUDGET PROPOSAL FOR FISCAL YEAR 2020 � National Institutes of Health CONTENTS OPEN SCIENCE, BIG DATA, AND YOU: WORKING TOGETHER TO TREAT AND PREVENT ALZHEIMER’S DISEASE AND RELATED DEMENTIAS ....................................................................... 1 INTRODUCTION .............................................................................................................................. 3 A Sense of Urgency ..................................................................................................................... 4 The Nation’s Commitment Becomes Law ................................................................................... 5 Increasing and Targeting the Investment in Research ............................................................... 6 Budgeting in FY 2020 to Fight Dementia .................................................................................... 7 Together, We Make the Difference .......................................................................................... 11 FISCAL YEAR 2020 PROFESSIONAL JUDGMENT BUDGET: ALZHEIMER’S DISEASE AND RELATED DEMENTIAS ................................................................................................................................... 12 THE ROAD TO TREATMENT AND PREVENTION OF ALZHEIMER’S DISEASE AND RELATED DEMENTIAS .................................................................................................................................. -
Human Social Genomics in the Multi-Ethnic Study of Atherosclerosis
Getting “Under the Skin”: Human Social Genomics in the Multi-Ethnic Study of Atherosclerosis by Kristen Monét Brown A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Epidemiological Science) in the University of Michigan 2017 Doctoral Committee: Professor Ana V. Diez-Roux, Co-Chair, Drexel University Professor Sharon R. Kardia, Co-Chair Professor Bhramar Mukherjee Assistant Professor Belinda Needham Assistant Professor Jennifer A. Smith © Kristen Monét Brown, 2017 [email protected] ORCID iD: 0000-0002-9955-0568 Dedication I dedicate this dissertation to my grandmother, Gertrude Delores Hampton. Nanny, no one wanted to see me become “Dr. Brown” more than you. I know that you are standing over the bannister of heaven smiling and beaming with pride. I love you more than my words could ever fully express. ii Acknowledgements First, I give honor to God, who is the head of my life. Truly, without Him, none of this would be possible. Countless times throughout this doctoral journey I have relied my favorite scripture, “And we know that all things work together for good, to them that love God, to them who are called according to His purpose (Romans 8:28).” Secondly, I acknowledge my parents, James and Marilyn Brown. From an early age, you two instilled in me the value of education and have been my biggest cheerleaders throughout my entire life. I thank you for your unconditional love, encouragement, sacrifices, and support. I would not be here today without you. I truly thank God that out of the all of the people in the world that He could have chosen to be my parents, that He chose the two of you.