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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]. -
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. -
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. -
Variation in Protein Coding Genes Identifies Information Flow
bioRxiv preprint doi: https://doi.org/10.1101/679456; this version posted June 21, 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-NC-ND 4.0 International license. Animal complexity and information flow 1 1 2 3 4 5 Variation in protein coding genes identifies information flow as a contributor to 6 animal complexity 7 8 Jack Dean, Daniela Lopes Cardoso and Colin Sharpe* 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Institute of Biological and Biomedical Sciences 25 School of Biological Science 26 University of Portsmouth, 27 Portsmouth, UK 28 PO16 7YH 29 30 * Author for correspondence 31 [email protected] 32 33 Orcid numbers: 34 DLC: 0000-0003-2683-1745 35 CS: 0000-0002-5022-0840 36 37 38 39 40 41 42 43 44 45 46 47 48 49 Abstract bioRxiv preprint doi: https://doi.org/10.1101/679456; this version posted June 21, 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-NC-ND 4.0 International license. Animal complexity and information flow 2 1 Across the metazoans there is a trend towards greater organismal complexity. How 2 complexity is generated, however, is uncertain. Since C.elegans and humans have 3 approximately the same number of genes, the explanation will depend on how genes are 4 used, rather than their absolute number. -
Epigenetic Changes in Human Model KMT2A Leukemias Highlight Early Events During Leukemogenesis
Epigenetic changes in human model KMT2A leukemias highlight early events during leukemogenesis Thomas Milan1, Magalie Celton1, Karine Lagacé1, Élodie Roques1, Safia Safa-Tahar-Henni1, Eva Bresson2,3,4, Anne Bergeron2,3,4, Josée Hebert5,6, Soheil Meshinchi7, Sonia Cellot8, Frédéric Barabé2,3,4, 1,6 Brian T Wilhelm Author contributions: BTW and TM designed the study, analyzed data and drafted the manuscript. TM and KL performed ChIP-seq and ATAC-seq, analysed the data and generated figures. MC performed Methyl-seq experiments, analysed data, generated figures and drafted the manuscript. SS-T-H assisted with the ATAC-seq analysis and generation of figures. KL, ER, EB, and AB helped with molecular biology work, cloning and cell culture. EB, AB and FB generated the model on mice from CD34+ cells. SM provided expression and clinical data for patient samples and JH and SC collected, characterized, and banked the local patient samples used in this study. Affiliations: 1Laboratory for High Throughput Biology, Institute for Research in Immunology and Cancer, Montréal, QC, Canada 2Centre de recherche en infectiologie du CHUL, Centre de recherche du CHU de Québec – Université Laval, Québec City, QC, Canada, 3CHU de Québec – Université Laval – Hôpital Enfant-Jésus; Québec City, QC, Canada; 4Department of Medicine, Université Laval, Quebec City, QC, Canada 5Division of Hematology-Oncology and Leukemia Cell Bank of Quebec, Maisonneuve-Rosemont Hospital, Montréal, QC, Canada, 6Department of Medicine, Université de Montréal, Montréal, QC, Canada, 7Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA 8Department of pediatrics, division of Hematology, Ste-Justine Hospital, Montréal, QC, Canada Running head: Early epigenetic changes in KM3-AML *Correspondence to: Brian T Wilhelm Institute for Research in Immunology and Cancer Université de Montréal P.O. -
Isolation and Identification of Proteins from Swine Sperm Chromatin and Nuclear Matrix
DOI: 10.21451/1984-3143-AR816 Anim. Reprod., v.14, n.2, p.418-428, Apr./Jun. 2017 Isolation and identification of proteins from swine sperm chromatin and nuclear matrix Guilherme Arantes Mendonça1,3, Romualdo Morandi Filho2, Elisson Terêncio Souza2, Thais Schwarz Gaggini1, Marina Cruvinel Assunção Silva-Mendonça1, Robson Carlos Antunes1, Marcelo Emílio Beletti1,2 1Post-graduation Program in Veterinary Science, Federal University of Uberlandia, Uberlandia, MG, Brazil. 2Post-graduation Program in Cellular and Molecular Biology, Federal University of Uberlandia, Uberlandia, MG, Brazil. Abstract (Yamauchi et al., 2011). According to the same authors, these active sperm chromatin sites in protamine toroids The aim of this study was to perform a may contain important epigenetic information for the proteomic analysis to isolate and identify proteins from developing embryo. the swine sperm nuclear matrix to contribute to a The isolated use of genomic and transcriptomic database of swine sperm nuclear proteins. We used pre- information may be insufficient to fully understand a chilled diluted semen from seven boars (19 to 24 week- complex organism because proteomics and old) from the commercial line Landrace x Large White transcriptomics can be discordant and DNA-RNA x Pietran. The semen was processed to separate the relationships cannot be fully correlated. Thus, sperm heads and extract the chromatin and nuclear measurements of other metabolic levels should also be matrix for protein quantification and analysis by mass obtained, such as the study of proteins (Wright et al., spectrometry, by LTQ Orbitrap ELITE mass 2012). According to these same authors, large-scale spectrometer (Thermo-Finnigan) coupled to a nanoflow protein research in organisms (i.e., the proteome-protein chromatography system (LC-MS/MS). -
UC San Diego Electronic Theses and Dissertations
UC San Diego UC San Diego Electronic Theses and Dissertations Title Cardiac Stretch-Induced Transcriptomic Changes are Axis-Dependent Permalink https://escholarship.org/uc/item/7m04f0b0 Author Buchholz, Kyle Stephen Publication Date 2016 Peer reviewed|Thesis/dissertation eScholarship.org Powered by the California Digital Library University of California UNIVERSITY OF CALIFORNIA, SAN DIEGO Cardiac Stretch-Induced Transcriptomic Changes are Axis-Dependent A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Bioengineering by Kyle Stephen Buchholz Committee in Charge: Professor Jeffrey Omens, Chair Professor Andrew McCulloch, Co-Chair Professor Ju Chen Professor Karen Christman Professor Robert Ross Professor Alexander Zambon 2016 Copyright Kyle Stephen Buchholz, 2016 All rights reserved Signature Page The Dissertation of Kyle Stephen Buchholz is approved and it is acceptable in quality and form for publication on microfilm and electronically: Co-Chair Chair University of California, San Diego 2016 iii Dedication To my beautiful wife, Rhia. iv Table of Contents Signature Page ................................................................................................................... iii Dedication .......................................................................................................................... iv Table of Contents ................................................................................................................ v List of Figures ................................................................................................................... -
Whole Genome Sequencing of Familial Non-Medullary Thyroid Cancer Identifies Germline Alterations in MAPK/ERK and PI3K/AKT Signaling Pathways
Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 13 October 2019 doi:10.20944/preprints201910.0154.v1 Article Whole genome sequencing of familial non-medullary thyroid cancer identifies germline alterations in MAPK/ERK and PI3K/AKT signaling pathways Aayushi Srivastava 1,2,3,4, Abhishek Kumar 1,5,6, Sara Giangiobbe 1, Elena Bonora 7, Kari Hemminki 1, Asta Försti 1,2,3 and Obul Reddy Bandapalli 1,2,3,* 1 Division of Molecular Genetic Epidemiology, German Cancer Research Center (DKFZ), D-69120, Heidelberg, Germany; [email protected] (A.S.), [email protected] (A.K.); [email protected] (S.G.); [email protected] (K.H.); [email protected] (A.F.) 2 Hopp Children’s Cancer Center (KiTZ), D-69120, Heidelberg, Germany 3 Division of Pediatric Neurooncology, German Cancer Research Center (DKFZ), German Cancer Consortium (DKTK), D-69120, Heidelberg, Germany 4 Medical Faculty, Heidelberg University, D-69120, Heidelberg, Germany 5 Institute of Bioinformatics, International Technology Park, Bangalore, 560066, India 6 Manipal Academy of Higher Education (MAHE), Manipal, Karnataka, 576104, India 7 S.Orsola-Malphigi Hospital, Unit of Medical Genetics,40138, Bologna, Italy ; [email protected] * Correspondence: [email protected]; Tel.: +49-6221-42-1709 Abstract: Evidence of familial inheritance in non-medullary thyroid cancer (NMTC) has accumulated over the last few decades. However, known variants account for a very small percentage of the genetic burden. Here, we focused on the identification of common pathways and networks enriched in NMTC families to better understand its pathogenesis with the final aim of identifying one novel high/moderate-penetrance germline predisposition variant segregating with the disease in each studied family. -
Patel, a Et Al. 1 Integrative Genomic and Epigenomic Analyses Identify A
bioRxiv preprint doi: https://doi.org/10.1101/852939; this version posted November 29, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Patel, A et al. 1 Integrative genomic and epigenomic analyses identify a distinct role of c-Myc and L-Myc for lineage determination in small cell lung cancer Ayushi S. Patel1,2, Seungyeul Yoo3,4, Ranran Kong1,2,5, Takashi Sato1,2, Maya Fridrikh1,2, Abhilasha Sinha1,2, German Nudelman6, Charles A. Powell1,2, Mary Beth Beasley7, Jun Zhu2,3,4, Hideo Watanabe1,2,3,8* 1Division of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA 2Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA 3Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA 4Sema4, a Mount Sinai venture, Stamford, CT 06902, USA. 5Department of Thoracic Surgery, The Second Affiliated Hospital of Medical School, Xi'an Jiaotong University, Xi'an, Shaanxi, 710004, China 6 Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA 7Department of Pathology and Laboratory Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA 8Lead Contact *Correspondence: [email protected] bioRxiv preprint doi: https://doi.org/10.1101/852939; this version posted November 29, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. -
Table S1. 103 Ferroptosis-Related Genes Retrieved from the Genecards
Table S1. 103 ferroptosis-related genes retrieved from the GeneCards. Gene Symbol Description Category GPX4 Glutathione Peroxidase 4 Protein Coding AIFM2 Apoptosis Inducing Factor Mitochondria Associated 2 Protein Coding TP53 Tumor Protein P53 Protein Coding ACSL4 Acyl-CoA Synthetase Long Chain Family Member 4 Protein Coding SLC7A11 Solute Carrier Family 7 Member 11 Protein Coding VDAC2 Voltage Dependent Anion Channel 2 Protein Coding VDAC3 Voltage Dependent Anion Channel 3 Protein Coding ATG5 Autophagy Related 5 Protein Coding ATG7 Autophagy Related 7 Protein Coding NCOA4 Nuclear Receptor Coactivator 4 Protein Coding HMOX1 Heme Oxygenase 1 Protein Coding SLC3A2 Solute Carrier Family 3 Member 2 Protein Coding ALOX15 Arachidonate 15-Lipoxygenase Protein Coding BECN1 Beclin 1 Protein Coding PRKAA1 Protein Kinase AMP-Activated Catalytic Subunit Alpha 1 Protein Coding SAT1 Spermidine/Spermine N1-Acetyltransferase 1 Protein Coding NF2 Neurofibromin 2 Protein Coding YAP1 Yes1 Associated Transcriptional Regulator Protein Coding FTH1 Ferritin Heavy Chain 1 Protein Coding TF Transferrin Protein Coding TFRC Transferrin Receptor Protein Coding FTL Ferritin Light Chain Protein Coding CYBB Cytochrome B-245 Beta Chain Protein Coding GSS Glutathione Synthetase Protein Coding CP Ceruloplasmin Protein Coding PRNP Prion Protein Protein Coding SLC11A2 Solute Carrier Family 11 Member 2 Protein Coding SLC40A1 Solute Carrier Family 40 Member 1 Protein Coding STEAP3 STEAP3 Metalloreductase Protein Coding ACSL1 Acyl-CoA Synthetase Long Chain Family Member 1 Protein -
Evolutionary Origin and Methylation Status of Human Intronic Cpg Islands That Are Not Present in Mouse
GBE Evolutionary Origin and Methylation Status of Human Intronic CpG Islands that Are Not Present in Mouse Katrin Rademacher1, Christopher Schro¨ der2, Deniz Kanber1, Ludger Klein-Hitpass3, Stefan Wallner4, Michael Zeschnigk1, and Bernhard Horsthemke1,* 1Institut fu¨ r Humangenetik, Universita¨tsklinikum Essen, Universita¨t Duisburg-Essen, Essen, Germany 2Genominformatik, Institut fu¨ r Humangenetik, Medizinische Fakulta¨t, Universita¨t Duisburg-Essen, Essen, Germany 3BioChip Labor, Institut fu¨ r Zellbiologie, Medizinische Fakulta¨t, Universita¨t Duisburg-Essen, Essen, Germany 4Institut fu¨ r Klinische Chemie und Laboratoriumsmedizin, Universita¨tsklinikum Regensburg, Universita¨t Regensburg, Germany *Corresponding author: E-mail: [email protected]. Accepted: June 8, 2014 Data deposition: This project (methylome 1) has been deposited at ENA under the accession PRJEB5800 and methylome 2 at EGA under the accession EGAS000001000719. Abstract Imprinting of the human RB1 gene is due to the presence of a differentially methylated CpG island (CGI) in intron 2, which is part of a retrocopy derived from the PPP1R26 gene on chromosome 9. The murine Rb1 gene does not have this retrocopy and is not imprinted. We have investigated whether the RB1/Rb1 locus is unique with respect to these differences. For this, we have com- pared the CGIs from human and mouse by in silico analyses. We have found that the human genome does not only contain more CGIs than the mouse, but the proportion of intronic CGIs is also higher (7.7% vs. 3.5%). At least 2,033 human intronic CGIs are not present in the mouse. Among these CGIs, 104 show sequence similarities elsewhere in the human genome, which suggests that they arose from retrotransposition.