Transcriptomic Analysis of the Oleaginous Microalga Neochloris Oleoabundans Reveals Metabolic Insights Into Triacylglyceride Accumulation
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BMC Genomics Biomed Central
BMC Genomics BioMed Central Research article Open Access Differential gene expression in femoral bone from red junglefowl and domestic chicken, differing for bone phenotypic traits Carl-Johan Rubin1, Johan Lindberg2, Carolyn Fitzsimmons3, Peter Savolainen2, Per Jensen4, Joakim Lundeberg2, Leif Andersson3,5 and Andreas Kindmark*1 Address: 1Department of Medical Sciences, Uppsala University, Sweden, 2Department of Gene Technology, School of Biotechnology, Royal Institute of Technology, Stockholm, Sweden, 3Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden, 4IFM Biology, Linköping University, SE-585 83, Linköping, Sweden and 5Department of Medical Biochemistry and Microbiology, Uppsala University, Box 597, SE-75124 Uppsala, Sweden Email: Carl-Johan Rubin - [email protected]; Johan Lindberg - [email protected]; Carolyn Fitzsimmons - [email protected]; Peter Savolainen - [email protected]; Per Jensen - [email protected]; Joakim Lundeberg - [email protected]; Leif Andersson - [email protected]; Andreas Kindmark* - [email protected] * Corresponding author Published: 2 July 2007 Received: 2 April 2007 Accepted: 2 July 2007 BMC Genomics 2007, 8:208 doi:10.1186/1471-2164-8-208 This article is available from: http://www.biomedcentral.com/1471-2164/8/208 © 2007 Rubin et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract Background: Osteoporosis is frequently observed among aging hens from egg-producing strains (layers) of domestic chicken. -
Depicting Gene Co-Expression Networks Underlying Eqtls Nathalie Vialaneix, Laurence Liaubet, Magali San Cristobal
Depicting gene co-expression networks underlying eQTLs Nathalie Vialaneix, Laurence Liaubet, Magali San Cristobal To cite this version: Nathalie Vialaneix, Laurence Liaubet, Magali San Cristobal. Depicting gene co-expression networks underlying eQTLs. Haja N. Kadarmideen. Systems Biology in Animal Production and Health vol 2, 2, Springer International Publishing, pp.1-31, 2016, 978-3-319-43330-1. 10.1007/978-3-319-43332-5_1. hal-01390589 HAL Id: hal-01390589 https://hal.archives-ouvertes.fr/hal-01390589 Submitted on 2 Nov 2016 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Depicting gene co-expression networks underlying eQTLs Nathalie Villa-Vialaneix, Laurence Liaubet and Magali SanCristobal Abstract Deciphering the biological mechanisms underlying a list of genes whose expression is under partial genetic control (i.e., having at least one eQTL) may not be as easy as for a list of differential genes. Indeed, no specific phenotype (e.g., health or production phenotype) is linked to the list of transcripts under study. There is a need to find a coherent biological interpretation of a list of genes under (partial) genetic control. We propose a pipeline using appropriate statistical tools to build a co-expression network from the list of genes, then to finely depict the network structure. -
Prioritization of Metabolic Genes As Novel Therapeutic Targets in Estrogen-Receptor Negative Breast Tumors Using Multi-Omics Data and Text Mining
www.oncotarget.com Oncotarget, 2019, Vol. 10, (No. 39), pp: 3894-3909 Research Paper Prioritization of metabolic genes as novel therapeutic targets in estrogen-receptor negative breast tumors using multi-omics data and text mining Dinesh Kumar Barupal1,*, Bei Gao1,*, Jan Budczies2, Brett S. Phinney4, Bertrand Perroud4, Carsten Denkert2,3 and Oliver Fiehn1 1West Coast Metabolomics Center, University of California, Davis, CA, USA 2Institute of Pathology, Charité University Hospital, Berlin, Germany 3German Institute of Pathology, Philipps-University Marburg, Marburg, Germany 4UC Davis Genome Center, University of California, Davis, CA, USA *Co-first authors and contributed equally to this work Correspondence to: Oliver Fiehn, email: [email protected] Keywords: set-enrichment; ChemRICH; multi-omics; metabolic networks; candidate gene prioritization Received: March 12, 2019 Accepted: May 13, 2019 Published: June 11, 2019 Copyright: Barupal et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License 3.0 (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. ABSTRACT Estrogen-receptor negative (ERneg) breast cancer is an aggressive breast cancer subtype in the need for new therapeutic options. We have analyzed metabolomics, proteomics and transcriptomics data for a cohort of 276 breast tumors (MetaCancer study) and nine public transcriptomics datasets using univariate statistics, meta- analysis, Reactome pathway analysis, biochemical network mapping and text mining of metabolic genes. In the MetaCancer cohort, a total of 29% metabolites, 21% proteins and 33% transcripts were significantly different (raw p <0.05) between ERneg and ERpos breast tumors. -
Whole Genome Sequencing of Familial Non-Medullary Thyroid Cancer Identifies Germline Alterations in MAPK/ERK and PI3K/AKT Signaling Pathways
biomolecules 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 Received: 29 August 2019; Accepted: 10 October 2019; Published: 13 October 2019 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. -
Clinical Characterization of Chromosome 5Q21.1–21.3 Microduplication: a Case Report
Open Medicine 2020; 15: 1123–1127 Case Report Shuang Chen, Yang Yu, Han Zhang, Leilei Li, Yuting Jiang, Ruizhi Liu, Hongguo Zhang* Clinical characterization of chromosome 5q21.1–21.3 microduplication: A case report https://doi.org/10.1515/med-2020-0199 Keywords: chromosome 5, prenatal diagnosis, microdu- received May 20, 2020; accepted September 28, 2020 plication, genetic counseling Abstract: Chromosomal microdeletions and microdupli- cations likely represent the main genetic etiologies for children with developmental delay or intellectual dis- ability. Through prenatal chromosomal microarray ana- 1 Introduction lysis, some microdeletions or microduplications can be detected before birth to avoid unnecessary abortions or Chromosomal microdeletions,microduplications,and birth defects. Although some microdeletions or microdu- unbalanced rearrangements represent the main genetic plications of chromosome 5 have been reported, nu- etiological factors for children with developmental delay [ ] - merous microduplications remain undescribed. We de- or intellectual disability 1 . Currently, chromosomal mi ( ) fi - - scribe herein a case of a 30-year-old woman carrying a croarray analysis CMA is considered a rst tier diag [ ] - fetus with a chromosome 5q21.1–q21.3 microduplication. nostic tool for these children 2 . Through prenatal diag Because noninvasive prenatal testing indicated a fetal nosis of CMA, some microdeletions or microduplications - chromosome 5 abnormality, the patient underwent am- can be detected before birth to avoid unnecessary abor [ ] niocentesis at 22 weeks 4 days of gestation. Karyotyping tions or birth defects 3 . The clinical features of some and chromosomal microarray analysis were performed on chromosome 5 microduplications have been described [ – ] [ ] amniotic fluid cells. Fetal behavioral and structural ab- previously 4 8 . -
High-Resolution Mapping of a Genetic Locus Regulating Preferential Carbohydrate Intake, Total Kilocalories, and Food Volume on Mouse Chromosome 17
High-Resolution Mapping of a Genetic Locus Regulating Preferential Carbohydrate Intake, Total Kilocalories, and Food Volume on Mouse Chromosome 17 Rodrigo Gularte-Me´rida1¤, Lisa M. DiCarlo2, Ginger Robertson2, Jacob Simon2, William D. Johnson4, Claudia Kappen3, Juan F. Medrano1, Brenda K. Richards2* 1 Department of Animal Science, University of California Davis, Davis, California, United States of America, 2 Genetics of Eating Behavior Laboratory, Pennington Biomedical Research Center, Louisiana State University System, Baton Rouge, Louisiana, United States of America, 3 Department of Developmental Biology, Pennington Biomedical Research Center, Louisiana State University System, Baton Rouge, Louisiana, United States of America, 4 Biostatistics Department, Pennington Biomedical Research Center, Louisiana State University System, Baton Rouge, Louisiana, United States of America Abstract The specific genes regulating the quantitative variation in macronutrient preference and food intake are virtually unknown. We fine mapped a previously identified mouse chromosome 17 region harboring quantitative trait loci (QTL) with large effects on preferential macronutrient intake-carbohydrate (Mnic1), total kilcalories (Kcal2), and total food volume (Tfv1) using interval-specific strains. These loci were isolated in the [C57BL/6J.CAST/EiJ-17.1-(D17Mit19-D17Mit50); B6.CAST-17.1] strain, possessing a ,40.1 Mb region of CAST DNA on the B6 genome. In a macronutrient selection paradigm, the B6.CAST-17.1 subcongenic mice eat 30% more calories from the carbohydrate-rich diet, ,10% more total calories, and ,9% more total food volume per body weight. In the current study, a cross between carbohydrate-preferring B6.CAST-17.1 and fat- preferring, inbred B6 mice was used to generate a subcongenic-derived F2 mapping population; genotypes were determined using a high-density, custom SNP panel. -
Biological Pathways, Candidate Genes, and Molecular Markers Associated with Quality-Of-Life Domains: an Update
Qual Life Res (2014) 23:1997–2013 DOI 10.1007/s11136-014-0656-1 REVIEW Biological pathways, candidate genes, and molecular markers associated with quality-of-life domains: an update Mirjam A. G. Sprangers • Melissa S. Y. Thong • Meike Bartels • Andrea Barsevick • Juan Ordon˜ana • Qiuling Shi • Xin Shelley Wang • Pa˚l Klepstad • Eddy A. Wierenga • Jasvinder A. Singh • Jeff A. Sloan Accepted: 19 February 2014 / Published online: 7 March 2014 Ó Springer International Publishing Switzerland 2014 Abstract (depressed mood) and positive (well-being/happiness) Background There is compelling evidence of a genetic emotional functioning, social functioning, and overall foundation of patient-reported quality of life (QOL). Given QOL. the rapid development of substantial scientific advances in Methods We followed a purposeful search algorithm of this area of research, the current paper updates and extends existing literature to capture empirical papers investigating reviews published in 2010. the relationship between biological pathways and molecu- Objectives The objective was to provide an updated lar markers and the identified QOL domains. overview of the biological pathways, candidate genes, and Results Multiple major pathways are involved in each molecular markers involved in fatigue, pain, negative QOL domain. The inflammatory pathway has the strongest evidence as a controlling mechanism underlying fatigue. Inflammation and neurotransmission are key processes On behalf of the GeneQol Consortium. involved in pain perception, and the catechol-O-methyl- transferase (COMT) gene is associated with multiple sorts Electronic supplementary material The online version of this article (doi:10.1007/s11136-014-0656-1) contains supplementary of pain. The neurotransmitter and neuroplasticity theories material, which is available to authorized users. -
Prioritization of Metabolic Genes As Novel Therapeutic Targets
bioRxiv preprint doi: https://doi.org/10.1101/515403; this version posted January 9, 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. 1 Prioritization of metabolic genes as novel therapeutic targets 2 in estrogen-receptor negative breast tumors using multi-omics data and text mining 3 4 Dinesh Kumar Barupal#,1, Bei Gao#, 1, Jan Budczies2, Brett S. Phinney4, Bertrand Perroud4, 5 Carsten Denkert2,3 and Oliver Fiehn*,1 6 Affiliations 7 1West Coast Metabolomics Center, University of California, Davis, CA, 95616 8 2Institute of Pathology, Charité University Hospital, Berlin, 9 3German Institute of Pathology, Philipps-University Marburg, Germany 10 4UC Davis Genome Center, University of California, Davis, CA, 95616 11 #Co-first authors and contributed equally. 12 Email address for all authors 13 Dinesh Kumar Barupal: [email protected] 14 Bei Gao: [email protected] 15 Carsten Denkert: [email protected] 16 Brett S. Phinney: [email protected] 17 Bertrand Perroud: [email protected] 18 Jan Budczies: [email protected] 19 Oliver Fiehn: [email protected] 20 21 * Corresponding Author: 22 Oliver Fiehn 23 West Coast Metabolomics Center, 24 University of California, Davis, CA, 95616 25 Email: [email protected] 1 bioRxiv preprint doi: https://doi.org/10.1101/515403; this version posted January 9, 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. -
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) -
POGLUT1, the Putative Effector Gene Driven by Rs2293370 in Primary
www.nature.com/scientificreports OPEN POGLUT1, the putative efector gene driven by rs2293370 in primary biliary cholangitis susceptibility Received: 6 June 2018 Accepted: 13 November 2018 locus chromosome 3q13.33 Published: xx xx xxxx Yuki Hitomi 1, Kazuko Ueno2,3, Yosuke Kawai1, Nao Nishida4, Kaname Kojima2,3, Minae Kawashima5, Yoshihiro Aiba6, Hitomi Nakamura6, Hiroshi Kouno7, Hirotaka Kouno7, Hajime Ohta7, Kazuhiro Sugi7, Toshiki Nikami7, Tsutomu Yamashita7, Shinji Katsushima 7, Toshiki Komeda7, Keisuke Ario7, Atsushi Naganuma7, Masaaki Shimada7, Noboru Hirashima7, Kaname Yoshizawa7, Fujio Makita7, Kiyoshi Furuta7, Masahiro Kikuchi7, Noriaki Naeshiro7, Hironao Takahashi7, Yutaka Mano7, Haruhiro Yamashita7, Kouki Matsushita7, Seiji Tsunematsu7, Iwao Yabuuchi7, Hideo Nishimura7, Yusuke Shimada7, Kazuhiko Yamauchi7, Tatsuji Komatsu7, Rie Sugimoto7, Hironori Sakai7, Eiji Mita7, Masaharu Koda7, Yoko Nakamura7, Hiroshi Kamitsukasa7, Takeaki Sato7, Makoto Nakamuta7, Naohiko Masaki 7, Hajime Takikawa8, Atsushi Tanaka 8, Hiromasa Ohira9, Mikio Zeniya10, Masanori Abe11, Shuichi Kaneko12, Masao Honda12, Kuniaki Arai12, Teruko Arinaga-Hino13, Etsuko Hashimoto14, Makiko Taniai14, Takeji Umemura 15, Satoru Joshita 15, Kazuhiko Nakao16, Tatsuki Ichikawa16, Hidetaka Shibata16, Akinobu Takaki17, Satoshi Yamagiwa18, Masataka Seike19, Shotaro Sakisaka20, Yasuaki Takeyama 20, Masaru Harada21, Michio Senju21, Osamu Yokosuka22, Tatsuo Kanda 22, Yoshiyuki Ueno 23, Hirotoshi Ebinuma24, Takashi Himoto25, Kazumoto Murata4, Shinji Shimoda26, Shinya Nagaoka6, Seigo Abiru6, Atsumasa Komori6,27, Kiyoshi Migita6,27, Masahiro Ito6,27, Hiroshi Yatsuhashi6,27, Yoshihiko Maehara28, Shinji Uemoto29, Norihiro Kokudo30, Masao Nagasaki2,3,31, Katsushi Tokunaga1 & Minoru Nakamura6,7,27,32 Primary biliary cholangitis (PBC) is a chronic and cholestatic autoimmune liver disease caused by the destruction of intrahepatic small bile ducts. Our previous genome-wide association study (GWAS) identifed six susceptibility loci for PBC. -
ATR16 Syndrome: Mechanisms Linking Monosomy to Phenotype 2 3 4 Christian Babbs,*1 Jill Brown,1 Sharon W
bioRxiv preprint doi: https://doi.org/10.1101/768895; this version posted October 7, 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. 1 ATR16 Syndrome: Mechanisms Linking Monosomy to Phenotype 2 3 4 Christian Babbs,*1 Jill Brown,1 Sharon W. Horsley,1 Joanne Slater,1 Evie Maifoshie,1 5 Shiwangini Kumar,2 Paul Ooijevaar,3 Marjolein Kriek,3 Amanda Dixon-McIver,2 6 Cornelis L. Harteveld,3 Joanne Traeger-Synodinos,4 Douglas Higgs1 and Veronica 7 Buckle*1 8 9 10 11 12 1. MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular 13 Medicine, University of Oxford, Oxford, UK. 14 15 2. IGENZ Ltd, Auckland, New Zealand. 16 17 3. Department of Clinical Genetics, Leiden University Medical Center, Leiden, The 18 Netherlands. 19 20 4. Department of Medical Genetics, National and Kapodistrian University of Athens, 21 Greece. 22 23 24 25 *Authors for correspondence 26 [email protected] 27 [email protected] 28 29 1 bioRxiv preprint doi: https://doi.org/10.1101/768895; this version posted October 7, 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. 1 Abstract 2 3 Background: Sporadic deletions removing 100s-1000s kb of DNA, and 4 variable numbers of poorly characterised genes, are often found in patients 5 with a wide range of developmental abnormalities. In such cases, 6 understanding the contribution of the deletion to an individual’s clinical 7 phenotype is challenging. -
Computational Techniques for Analyzing Tumor DNA Data
Computational Techniques for Analyzing Tumor DNA Data A DISSERTATION SUBMITTED TO THE FACULTY OF THE GRADUATE SCHOOL OF THE UNIVERSITY OF MINNESOTA BY Sean R. Landman IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY Adviser: Vipin Kumar Co-Adviser: Michael Steinbach June, 2016 c Sean R. Landman 2016 ALL RIGHTS RESERVED Acknowledgments It's been a long road to reach this point, and throughout the course of this journey I've realized how fortunate I am to be surrounded by an abundance of supportive and influential people in my life. I wouldn't be where I am today, and this dissertation wouldn't have been possible, without the guidance, advise, support, encouragement, and friendship of so many people that I would like to thank. First and foremost, I would like to thank my adviser, Vipin Kumar. Your positivity and enthusiasm for research has been a constant source of encouragement throughout my time in graduate school. You've given me the freedom to explore my own research ideas, pushed me to take on new challenges, and have always given me the support I've needed to succeed. I would also like to express my gratitude to my co-adviser, Michael Steinbach. Thank you for all of the countless times you've helped me by discussing ideas and working through problems together. Your insights have been so influential in helping me grow as a researcher. Imad Rahal, my adviser during my time at St. John's University, deserves special recognition for helping to send me along this career path I have chosen.