Identification and Analysis of Long Non-Coding Rnas and Mrnas in Chicken Macrophages Infected with Avian Infectious Bronchitis Coronavirus
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Genomic Correlates of Relationship QTL Involved in Fore- Versus Hind Limb Divergence in Mice
Loyola University Chicago Loyola eCommons Biology: Faculty Publications and Other Works Faculty Publications 2013 Genomic Correlates of Relationship QTL Involved in Fore- Versus Hind Limb Divergence in Mice Mihaela Palicev Gunter P. Wagner James P. Noonan Benedikt Hallgrimsson James M. Cheverud Loyola University Chicago, [email protected] Follow this and additional works at: https://ecommons.luc.edu/biology_facpubs Part of the Biology Commons Recommended Citation Palicev, M, GP Wagner, JP Noonan, B Hallgrimsson, and JM Cheverud. "Genomic Correlates of Relationship QTL Involved in Fore- Versus Hind Limb Divergence in Mice." Genome Biology and Evolution 5(10), 2013. This Article is brought to you for free and open access by the Faculty Publications at Loyola eCommons. It has been accepted for inclusion in Biology: Faculty Publications and Other Works by an authorized administrator of Loyola eCommons. For more information, please contact [email protected]. This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License. © Palicev et al., 2013. GBE Genomic Correlates of Relationship QTL Involved in Fore- versus Hind Limb Divergence in Mice Mihaela Pavlicev1,2,*, Gu¨ nter P. Wagner3, James P. Noonan4, Benedikt Hallgrı´msson5,and James M. Cheverud6 1Konrad Lorenz Institute for Evolution and Cognition Research, Altenberg, Austria 2Department of Pediatrics, Cincinnati Children‘s Hospital Medical Center, Cincinnati, Ohio 3Yale Systems Biology Institute and Department of Ecology and Evolutionary Biology, Yale University 4Department of Genetics, Yale University School of Medicine 5Department of Cell Biology and Anatomy, The McCaig Institute for Bone and Joint Health and the Alberta Children’s Hospital Research Institute for Child and Maternal Health, University of Calgary, Calgary, Canada 6Department of Anatomy and Neurobiology, Washington University *Corresponding author: E-mail: [email protected]. -
Meta-Analysis of Gene Signatures and Key Pathways Indicates
www.nature.com/scientificreports OPEN Meta‑analysis of gene signatures and key pathways indicates suppression of JNK pathway as a regulator of chemo‑resistance in AML Parastoo Modarres1, Farzaneh Mohamadi Farsani1,3, Amir Abas Nekouie2 & Sadeq Vallian1* The pathways and robust deregulated gene signatures involved in AML chemo‑resistance are not fully understood. Multiple subgroups of AMLs which are under treatment of various regimens seem to have similar regulatory gene(s) or pathway(s) related to their chemo‑resistance phenotype. In this study using gene set enrichment approach, deregulated genes and pathways associated with relapse after chemotherapy were investigated in AML samples. Five AML libraries compiled from GEO and ArrayExpress repositories were used to identify signifcantly diferentially expressed genes between chemo‑resistance and chemo‑sensitive groups. Functional and pathway enrichment analysis of diferentially expressed genes was performed to assess molecular mechanisms related to AML chemotherapeutic resistance. A total of 34 genes selected to be diferentially expressed in the chemo‑ resistance compared to the chemo‑sensitive group. Among the genes selected, c-Jun, AKT3, ARAP3, GABBR1, PELI2 and SORT1 are involved in neurotrophin, estrogen, cAMP and Toll‑like receptor signaling pathways. All these pathways are located upstream and regulate JNK signaling pathway which functions as a key regulator of cellular apoptosis. Our expression data are in favor of suppression of JNK pathway, which could induce pro‑apoptotic gene expression as well as down regulation of survival factors, introducing this pathway as a key regulator of drug‑resistance development in AML. Acute myeloid leukemia (AML) is one of the most aggressive, life-threatening hematological malignancies char- acterized by uncontrolled proliferation of abnormal diferentiated and nonfunctional myeloid precursor cells1. -
Download Special Issue
BioMed Research International Novel Bioinformatics Approaches for Analysis of High-Throughput Biological Data Guest Editors: Julia Tzu-Ya Weng, Li-Ching Wu, Wen-Chi Chang, Tzu-Hao Chang, Tatsuya Akutsu, and Tzong-Yi Lee Novel Bioinformatics Approaches for Analysis of High-Throughput Biological Data BioMed Research International Novel Bioinformatics Approaches for Analysis of High-Throughput Biological Data Guest Editors: Julia Tzu-Ya Weng, Li-Ching Wu, Wen-Chi Chang, Tzu-Hao Chang, Tatsuya Akutsu, and Tzong-Yi Lee Copyright © 2014 Hindawi Publishing Corporation. All rights reserved. This is a special issue published in “BioMed Research International.” All articles are open access articles distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Contents Novel Bioinformatics Approaches for Analysis of High-Throughput Biological Data,JuliaTzu-YaWeng, Li-Ching Wu, Wen-Chi Chang, Tzu-Hao Chang, Tatsuya Akutsu, and Tzong-Yi Lee Volume2014,ArticleID814092,3pages Evolution of Network Biomarkers from Early to Late Stage Bladder Cancer Samples,Yung-HaoWong, Cheng-Wei Li, and Bor-Sen Chen Volume 2014, Article ID 159078, 23 pages MicroRNA Expression Profiling Altered by Variant Dosage of Radiation Exposure,Kuei-FangLee, Yi-Cheng Chen, Paul Wei-Che Hsu, Ingrid Y. Liu, and Lawrence Shih-Hsin Wu Volume2014,ArticleID456323,10pages EXIA2: Web Server of Accurate and Rapid Protein Catalytic Residue Prediction, Chih-Hao Lu, Chin-Sheng -
The Human Gene Connectome As a Map of Short Cuts for Morbid Allele Discovery
The human gene connectome as a map of short cuts for morbid allele discovery Yuval Itana,1, Shen-Ying Zhanga,b, Guillaume Vogta,b, Avinash Abhyankara, Melina Hermana, Patrick Nitschkec, Dror Friedd, Lluis Quintana-Murcie, Laurent Abela,b, and Jean-Laurent Casanovaa,b,f aSt. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University, New York, NY 10065; bLaboratory of Human Genetics of Infectious Diseases, Necker Branch, Paris Descartes University, Institut National de la Santé et de la Recherche Médicale U980, Necker Medical School, 75015 Paris, France; cPlateforme Bioinformatique, Université Paris Descartes, 75116 Paris, France; dDepartment of Computer Science, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel; eUnit of Human Evolutionary Genetics, Centre National de la Recherche Scientifique, Unité de Recherche Associée 3012, Institut Pasteur, F-75015 Paris, France; and fPediatric Immunology-Hematology Unit, Necker Hospital for Sick Children, 75015 Paris, France Edited* by Bruce Beutler, University of Texas Southwestern Medical Center, Dallas, TX, and approved February 15, 2013 (received for review October 19, 2012) High-throughput genomic data reveal thousands of gene variants to detect a single mutated gene, with the other polymorphic genes per patient, and it is often difficult to determine which of these being of less interest. This goes some way to explaining why, variants underlies disease in a given individual. However, at the despite the abundance of NGS data, the discovery of disease- population level, there may be some degree of phenotypic homo- causing alleles from such data remains somewhat limited. geneity, with alterations of specific physiological pathways under- We developed the human gene connectome (HGC) to over- come this problem. -
Ubinet: an Online Resource for Exploring the Functional Associations and Regulatory Networks of Protein Ubiquitylation
Database, 2016, 1–14 doi: 10.1093/database/baw054 Original article Original article UbiNet: an online resource for exploring the functional associations and regulatory networks of protein ubiquitylation Van-Nui Nguyen1,2,†, Kai-Yao Huang1,†, Julia Tzu-Ya Weng1,3, K. Robert Lai1,3,* and Tzong-Yi Lee1,3,* 1Department of Computer Science and Engineering, Yuan Ze University, Taoyuan, 320, Taiwan, 2University of Information and Communication Technology, Thai Nguyen University, Vietnam and 3Innovation Center for Big Data and Digital Convergence, Yuan Ze University, 320, Taiwan *Corresponding author: Tel: +886928560313, Email: [email protected] †These authors contributed equally to this work. Correspondence may also be addressed to or K. Robert Lai. Email: [email protected] Citation details: Nguyen,V.-N., Huang,K.-Y., Weng,J.T.-Y., et al. UbiNet: an online resource for exploring the functional as- sociations and regulatory networks of protein ubiquitylation. Database (2016) Vol. 2016: article ID baw054; doi:10.1093/ database/baw054 Received 18 August 2015; Revised 30 September 2015; Accepted 20 March 2016 Abstract Protein ubiquitylation catalyzed by E3 ubiquitin ligases are crucial in the regulation of many cellular processes. Owing to the high throughput of mass spectrometry-based proteomics, a number of methods have been developed for the experimental determin- ation of ubiquitylation sites, leading to a large collection of ubiquitylation data. However, there exist no resources for the exploration of E3-ligase-associated regulatory networks of for ubiquitylated proteins in humans. Therefore, the UbiNet database was developed to provide a full investigation of protein ubiquitylation networks by incorporating experi- mentally verified E3 ligases, ubiquitylated substrates and protein–protein interactions (PPIs). -
A Sex-Stratified Genome-Wide Association Study of Tuberculosis Using a Multi-Ethnic Genotyping Array
bioRxiv preprint doi: https://doi.org/10.1101/405571; this version posted August 31, 2018. 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. A sex-stratified genome-wide association study of tuberculosis using a multi-ethnic genotyping array Haiko Schurz 1,2*, Craig J Kinnear 1, Chris Gignoux 3, Genevieve Wojcik 4, Paul D van Helden 1, Gerard Tromp 1,2,5, Brenna Henn 6, Eileen G Hoal 1, Marlo Möller 1 1 DST-NRF Centre of Excellence for Biomedical Tuberculosis Research; South African Medical Research Council Centre for Tuberculosis Research; Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa. 2 South African Tuberculosis Bioinformatics Initiative (SATBBI), Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa. 3 Colorado Center for Personalized Medicine and Department of Biostatistics and Informatics, University of Colorado, Anschutz Medical Campus, Aurora, CO, 80045. 4 Department of Genetics, Stanford University, Stanford, CA, 94305. 5 Centre for Bioinformatics and Computational Biology, Stellenbosch University, Cape Town, South Africa. 6 Department of Anthropology, and the UC Davis Genome Center, University of California, Davis, CA, 95616. * Corresponding author: [email protected] Page 1 of 22 bioRxiv preprint doi: https://doi.org/10.1101/405571; this version posted August 31, 2018. 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. Abstract Tuberculosis (TB), caused by Mycobacterium tuberculosis, is a complex disease with a known human genetic component. -
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 ................................................................................................................... -
393LN V 393P 344SQ V 393P Probe Set Entrez Gene
393LN v 393P 344SQ v 393P Entrez fold fold probe set Gene Gene Symbol Gene cluster Gene Title p-value change p-value change chemokine (C-C motif) ligand 21b /// chemokine (C-C motif) ligand 21a /// chemokine (C-C motif) ligand 21c 1419426_s_at 18829 /// Ccl21b /// Ccl2 1 - up 393 LN only (leucine) 0.0047 9.199837 0.45212 6.847887 nuclear factor of activated T-cells, cytoplasmic, calcineurin- 1447085_s_at 18018 Nfatc1 1 - up 393 LN only dependent 1 0.009048 12.065 0.13718 4.81 RIKEN cDNA 1453647_at 78668 9530059J11Rik1 - up 393 LN only 9530059J11 gene 0.002208 5.482897 0.27642 3.45171 transient receptor potential cation channel, subfamily 1457164_at 277328 Trpa1 1 - up 393 LN only A, member 1 0.000111 9.180344 0.01771 3.048114 regulating synaptic membrane 1422809_at 116838 Rims2 1 - up 393 LN only exocytosis 2 0.001891 8.560424 0.13159 2.980501 glial cell line derived neurotrophic factor family receptor alpha 1433716_x_at 14586 Gfra2 1 - up 393 LN only 2 0.006868 30.88736 0.01066 2.811211 1446936_at --- --- 1 - up 393 LN only --- 0.007695 6.373955 0.11733 2.480287 zinc finger protein 1438742_at 320683 Zfp629 1 - up 393 LN only 629 0.002644 5.231855 0.38124 2.377016 phospholipase A2, 1426019_at 18786 Plaa 1 - up 393 LN only activating protein 0.008657 6.2364 0.12336 2.262117 1445314_at 14009 Etv1 1 - up 393 LN only ets variant gene 1 0.007224 3.643646 0.36434 2.01989 ciliary rootlet coiled- 1427338_at 230872 Crocc 1 - up 393 LN only coil, rootletin 0.002482 7.783242 0.49977 1.794171 expressed sequence 1436585_at 99463 BB182297 1 - up 393 -
Identification of Novel Regulatory Genes in Acetaminophen
IDENTIFICATION OF NOVEL REGULATORY GENES IN ACETAMINOPHEN INDUCED HEPATOCYTE TOXICITY BY A GENOME-WIDE CRISPR/CAS9 SCREEN A THESIS IN Cell Biology and Biophysics and Bioinformatics Presented to the Faculty of the University of Missouri-Kansas City in partial fulfillment of the requirements for the degree DOCTOR OF PHILOSOPHY By KATHERINE ANNE SHORTT B.S, Indiana University, Bloomington, 2011 M.S, University of Missouri, Kansas City, 2014 Kansas City, Missouri 2018 © 2018 Katherine Shortt All Rights Reserved IDENTIFICATION OF NOVEL REGULATORY GENES IN ACETAMINOPHEN INDUCED HEPATOCYTE TOXICITY BY A GENOME-WIDE CRISPR/CAS9 SCREEN Katherine Anne Shortt, Candidate for the Doctor of Philosophy degree, University of Missouri-Kansas City, 2018 ABSTRACT Acetaminophen (APAP) is a commonly used analgesic responsible for over 56,000 overdose-related emergency room visits annually. A long asymptomatic period and limited treatment options result in a high rate of liver failure, generally resulting in either organ transplant or mortality. The underlying molecular mechanisms of injury are not well understood and effective therapy is limited. Identification of previously unknown genetic risk factors would provide new mechanistic insights and new therapeutic targets for APAP induced hepatocyte toxicity or liver injury. This study used a genome-wide CRISPR/Cas9 screen to evaluate genes that are protective against or cause susceptibility to APAP-induced liver injury. HuH7 human hepatocellular carcinoma cells containing CRISPR/Cas9 gene knockouts were treated with 15mM APAP for 30 minutes to 4 days. A gene expression profile was developed based on the 1) top screening hits, 2) overlap with gene expression data of APAP overdosed human patients, and 3) biological interpretation including assessment of known and suspected iii APAP-associated genes and their therapeutic potential, predicted affected biological pathways, and functionally validated candidate genes. -
A Genome-Wide Scan of Cleft Lip Triads Identifies Parent
F1000Research 2019, 8:960 Last updated: 03 AUG 2021 RESEARCH ARTICLE A genome-wide scan of cleft lip triads identifies parent- of-origin interaction effects between ANK3 and maternal smoking, and between ARHGEF10 and alcohol consumption [version 2; peer review: 2 approved] Øystein Ariansen Haaland 1, Julia Romanowska1,2, Miriam Gjerdevik1,3, Rolv Terje Lie1,4, Håkon Kristian Gjessing 1,4, Astanand Jugessur1,3,4 1Department of Global Public Health and Primary Care, University of Bergen, Bergen, N-5020, Norway 2Computational Biology Unit, University of Bergen, Bergen, N-5020, Norway 3Department of Genetics and Bioinformatics, Norwegian Institute of Public Health, Skøyen, Oslo, Skøyen, N-0213, Norway 4Centre for Fertility and Health (CeFH), Norwegian Institute of Public Health, Skøyen, Oslo, N-0213, Norway v2 First published: 24 Jun 2019, 8:960 Open Peer Review https://doi.org/10.12688/f1000research.19571.1 Latest published: 19 Jul 2019, 8:960 https://doi.org/10.12688/f1000research.19571.2 Reviewer Status Invited Reviewers Abstract Background: Although both genetic and environmental factors have 1 2 been reported to influence the risk of isolated cleft lip with or without cleft palate (CL/P), the exact mechanisms behind CL/P are still largely version 2 unaccounted for. We recently developed new methods to identify (revision) report parent-of-origin (PoO) interactions with environmental exposures 19 Jul 2019 (PoOxE) and now apply them to data from a genome-wide association study (GWAS) of families with children born with isolated CL/P. version 1 Methods: Genotypes from 1594 complete triads and 314 dyads (1908 24 Jun 2019 report report nuclear families in total) with CL/P were available for the current analyses. -
Korpal Et Al, Supplementary Information, P.1 An
Korpal et al, Supplementary Information, p.1 An F876L Mutation in Androgen Receptor Confers Genetic and Phenotypic Resistance to MDV3100 (Enzalutamide) Manav Korpal1, Joshua M. Korn1, Xueliang Gao2, Daniel P. Rakiec3, David A. Ruddy3, Shivang Doshi1, Jing Yuan1, Steve G. Kovats1, Sunkyu Kim1, Vesselina G. Cooke1, John E. Monahan3, Frank Stegmeier1, Thomas M. Roberts2, William R. Sellers1, Wenlai Zhou1 and Ping Zhu1 SUPPLEMENTARY FIGURES LEGENDS Supplementary Figure S1. Weakly and strongly resistant clones show partial resistance to MDV3100. Long-term colony formation assays for control 1 (C1, left), strongly resistant clone #1 (middle) and weakly resistant clone #14 (right) treated with various concentrations of MDV3100 (indicated in yellow font, µM). Supplementary Figure S2. Strongly resistant clones fail to show modulation of AR pathway activity when treated with MDV3100. A, clustering analysis was performed for controls (aggregate) and resistant lines using an androgen-induced gene signature. All probesets matching genes from the androgen-induced gene signature were used. All expression data is presented as average fold change in MDV3100-treated vs. DMSO- treated samples. B, pathway enrichment analysis showing alterations in AR pathway activity in controls (left), weakly (middle) and strongly resistant (right) lines when treated with 10 µM MDV3100 for 24 h. Correlation between an AR gene signature in comparison to the top-ranked genes upon treatment with 10 µM MDV3100 for 24 h in Korpal et al, Supplementary Information, p.2 controls (left), weakly (middle) and strongly (right) resistant lines. Green line represents level of pathway activity— stronger deviation from black diagonal represents greater inhibition of pathway activity by MDV3100 treatment. -
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