Gene Expression Profiling to Identify Eggshell Proteins Involved In
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A Yeast Phenomic Model for the Gene Interaction Network Modulating
Louie et al. Genome Medicine 2012, 4:103 http://genomemedicine.com/content/4/12/103 RESEARCH Open Access A yeast phenomic model for the gene interaction network modulating CFTR-ΔF508 protein biogenesis Raymond J Louie3†, Jingyu Guo1,2†, John W Rodgers1, Rick White4, Najaf A Shah1, Silvere Pagant3, Peter Kim3, Michael Livstone5, Kara Dolinski5, Brett A McKinney6, Jeong Hong2, Eric J Sorscher2, Jennifer Bryan4, Elizabeth A Miller3* and John L Hartman IV1,2* Abstract Background: The overall influence of gene interaction in human disease is unknown. In cystic fibrosis (CF) a single allele of the cystic fibrosis transmembrane conductance regulator (CFTR-ΔF508) accounts for most of the disease. In cell models, CFTR-ΔF508 exhibits defective protein biogenesis and degradation rather than proper trafficking to the plasma membrane where CFTR normally functions. Numerous genes function in the biogenesis of CFTR and influence the fate of CFTR-ΔF508. However it is not known whether genetic variation in such genes contributes to disease severity in patients. Nor is there an easy way to study how numerous gene interactions involving CFTR-ΔF would manifest phenotypically. Methods: To gain insight into the function and evolutionary conservation of a gene interaction network that regulates biogenesis of a misfolded ABC transporter, we employed yeast genetics to develop a ‘phenomic’ model, in which the CFTR-ΔF508-equivalent residue of a yeast homolog is mutated (Yor1-ΔF670), and where the genome is scanned quantitatively for interaction. We first confirmed that Yor1-ΔF undergoes protein misfolding and has reduced half-life, analogous to CFTR-ΔF. Gene interaction was then assessed quantitatively by growth curves for approximately 5,000 double mutants, based on alteration in the dose response to growth inhibition by oligomycin, a toxin extruded from the cell at the plasma membrane by Yor1. -
Co-Expression Module Analysis Reveals Biological Processes
Shi et al. BMC Systems Biology 2010, 4:74 http://www.biomedcentral.com/1752-0509/4/74 RESEARCH ARTICLE Open Access Co-expressionResearch article module analysis reveals biological processes, genomic gain, and regulatory mechanisms associated with breast cancer progression Zhiao Shi1,2, Catherine K Derow3 and Bing Zhang*3 Abstract Background: Gene expression signatures are typically identified by correlating gene expression patterns to a disease phenotype of interest. However, individual gene-based signatures usually suffer from low reproducibility and interpretability. Results: We have developed a novel algorithm Iterative Clique Enumeration (ICE) for identifying relatively independent maximal cliques as co-expression modules and a module-based approach to the analysis of gene expression data. Applying this approach on a public breast cancer dataset identified 19 modules whose expression levels were significantly correlated with tumor grade. The correlations were reproducible for 17 modules in an independent breast cancer dataset, and the reproducibility was considerably higher than that based on individual genes or modules identified by other algorithms. Sixteen out of the 17 modules showed significant enrichment in certain Gene Ontology (GO) categories. Specifically, modules related to cell proliferation and immune response were up-regulated in high- grade tumors while those related to cell adhesion was down-regulated. Further analyses showed that transcription factors NYFB, E2F1/E2F3, NRF1, and ELK1 were responsible for the up-regulation of the cell proliferation modules. IRF family and ETS family proteins were responsible for the up-regulation of the immune response modules. Moreover, inhibition of the PPARA signaling pathway may also play an important role in tumor progression. -
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Identification of Mechanisms and Pathways Involved in MLL2-Mediated Tumorigenesis by Chun-Chi Chang Department of Pathology Duke University Date:_______________________ Approved: ___________________________ Yiping He, Supervisor ___________________________ Salvatore Pizzo ___________________________ Hai Yan Thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in the Department of Pathology in the Graduate School of Duke University 2013 ABSTRACT Identification of Mechanisms and Pathways Involved in MLL2-Mediated Tumorigenesis by Chun-Chi Chang Department of Pathology Duke University Date:_______________________ Approved: ___________________________ Yiping He, Supervisor ___________________________ Salvatore Pizzo ___________________________ Hai Yan An abstract of a thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in the Department of Pathology in the Graduate School of Duke University 2013 Copyright by Chun-Chi Chang 2013 Abstract Myeloid/lymphoid or mixed-lineage leukemia (MLL)-family genes encode histone lysine methyltransferases that play important roles in epigenetic regulation of gene transcription, and these genes are frequently mutated in human cancers. While MLL1 and MLL4 have been the most extensively studied, MLL2 and its homolog MLL3 are not well-understood. Specifically, little is known regarding the extent of global MLL2 involvement in the regulation of gene expression and the mechanism underlying its alterations in mediating tumorigenesis. To study the role of MLL2 in tumorigenesis, we somatically knocked out MLL2 in a colorectal carcinoma cell line, HCT116. We observed that the MLL2 loss of function results in significant reduction of cell growth and multinuclear morphology. We further profiled MLL2 regulated genes and pathways by analyzing gene expression in MLL2 wild-type versus MLL2-null isogenic cell lines. -
A SARS-Cov-2 Bioid-Based Virus-Host Membrane Protein Interactome and Virus Peptide Compendium: New Proteomics Resources for COVID-19 Research
bioRxiv preprint doi: https://doi.org/10.1101/2020.08.28.269175; this version posted August 28, 2020. 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. A SARS-CoV-2 BioID-based virus-host membrane protein interactome and virus peptide compendium: new proteomics resources for COVID-19 research Jonathan R. St-Germain1, Audrey Astori*1, Payman Samavarchi-Tehrani*2, Hala Abdouni2, Vinitha Macwan1, Dae-Kyum Kim2, Jennifer J. Knapp2, Frederick P. Roth2,3,4, Anne-Claude Gingras†2,3 and Brian Raught†1,5 1. Princess Margaret Cancer Centre, University Health Network, 101 College St., Toronto, ON, Canada 2. Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada 3. Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada 4. Department of Computer Science, University of Toronto, Toronto, ON, Canada 5. Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada *these authors contributed equally † corresponding authors bioRxiv preprint doi: https://doi.org/10.1101/2020.08.28.269175; this version posted August 28, 2020. 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. Summary Key steps of viral replication take place at host cell membranes, but the detection of membrane- associated protein-protein interactions using standard affinity-based approaches (e.g. -
Autocrine IFN Signaling Inducing Profibrotic Fibroblast Responses By
Downloaded from http://www.jimmunol.org/ by guest on September 23, 2021 Inducing is online at: average * The Journal of Immunology , 11 of which you can access for free at: 2013; 191:2956-2966; Prepublished online 16 from submission to initial decision 4 weeks from acceptance to publication August 2013; doi: 10.4049/jimmunol.1300376 http://www.jimmunol.org/content/191/6/2956 A Synthetic TLR3 Ligand Mitigates Profibrotic Fibroblast Responses by Autocrine IFN Signaling Feng Fang, Kohtaro Ooka, Xiaoyong Sun, Ruchi Shah, Swati Bhattacharyya, Jun Wei and John Varga J Immunol cites 49 articles Submit online. Every submission reviewed by practicing scientists ? is published twice each month by Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts http://jimmunol.org/subscription Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html http://www.jimmunol.org/content/suppl/2013/08/20/jimmunol.130037 6.DC1 This article http://www.jimmunol.org/content/191/6/2956.full#ref-list-1 Information about subscribing to The JI No Triage! Fast Publication! Rapid Reviews! 30 days* Why • • • Material References Permissions Email Alerts Subscription Supplementary The Journal of Immunology The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2013 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. This information is current as of September 23, 2021. The Journal of Immunology A Synthetic TLR3 Ligand Mitigates Profibrotic Fibroblast Responses by Inducing Autocrine IFN Signaling Feng Fang,* Kohtaro Ooka,* Xiaoyong Sun,† Ruchi Shah,* Swati Bhattacharyya,* Jun Wei,* and John Varga* Activation of TLR3 by exogenous microbial ligands or endogenous injury-associated ligands leads to production of type I IFN. -
An Integrative Genomic Analysis of the Longshanks Selection Experiment for Longer Limbs in Mice
bioRxiv preprint doi: https://doi.org/10.1101/378711; this version posted August 19, 2018. 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. 1 Title: 2 An integrative genomic analysis of the Longshanks selection experiment for longer limbs in mice 3 Short Title: 4 Genomic response to selection for longer limbs 5 One-sentence summary: 6 Genome sequencing of mice selected for longer limbs reveals that rapid selection response is 7 due to both discrete loci and polygenic adaptation 8 Authors: 9 João P. L. Castro 1,*, Michelle N. Yancoskie 1,*, Marta Marchini 2, Stefanie Belohlavy 3, Marek 10 Kučka 1, William H. Beluch 1, Ronald Naumann 4, Isabella Skuplik 2, John Cobb 2, Nick H. 11 Barton 3, Campbell Rolian2,†, Yingguang Frank Chan 1,† 12 Affiliations: 13 1. Friedrich Miescher Laboratory of the Max Planck Society, Tübingen, Germany 14 2. University of Calgary, Calgary AB, Canada 15 3. IST Austria, Klosterneuburg, Austria 16 4. Max Planck Institute for Cell Biology and Genetics, Dresden, Germany 17 Corresponding author: 18 Campbell Rolian 19 Yingguang Frank Chan 20 * indicates equal contribution 21 † indicates equal contribution 22 Abstract: 23 Evolutionary studies are often limited by missing data that are critical to understanding the 24 history of selection. Selection experiments, which reproduce rapid evolution under controlled 25 conditions, are excellent tools to study how genomes evolve under strong selection. Here we 1 bioRxiv preprint doi: https://doi.org/10.1101/378711; this version posted August 19, 2018. -
Supplementary Figure S1 A
Supplementary Figure S1 A B C 1 4 1 3 1 2 1 2 1 0 1 1 (Normalized signal values)] 2 (Normalized signal values) (Normalized 8 2 10 Log 6 AFFX-BioC AFFX-BioB AFFX-BioDn AFFX-CreX hDFs [Log 6 8 10 12 14 hOFs [Log2 (Normalized signal values)] Supplementary Figure S2 GLYCOLYSIS PENTOSE-PHOSPHATE PATHWAY Glucose Purine/pyrimidine Glucose-6-phosphate metabolism AMINO ACID Fluctose-6-phosphate AMPK METABOLISM TIGAR PFKFB2 methylgloxal GloI Ser, Gly, Thr Glyceraldehyde-3-phosphate ALDH Lactate PYRUVATE LDH METABOLISM acetic acid Ethanol Pyruvate GLYCOSPHINGOLIPID NADH BIOSYNTHESIS Ala, Cys DLD PDH PDK3 DLAT Fatty acid Lys, Trp, Leu, Acetyl CoA ACAT2 Ile, Tyr, Phe β-OXIDATION ACACA Citrate Asp, Asn Citrate Acetyl CoA Oxaloacetate Isocitrate MDH1 IDH1 Glu, Gln, His, ME2 TCA Pro, Arg 2-Oxoglutarate MDH1 CYCLE Pyruvate Malate ME2 GLUTAMINOLYSIS FH Succinyl-CoA Fumalate SUCLA2 Tyr, Phe Var, Ile, Met Supplementary Figure S3 Entrez Gene Symbol Gene Name hODs hDFs hOF-iPSCs GeneID 644 BLVRA biliverdin reductase A 223.9 259.3 253.0 3162 HMOX1 heme oxygenase 1 1474.2 2698.0 452.3 9365 KL klotho 54.1 44.8 36.5 nicotinamide 10135 NAMPT 827.7 626.2 2999.8 phosphoribosyltransferase nuclear factor (erythroid- 4780 NFE2L2 2134.5 1331.7 1006.2 derived 2) related factor 2 peroxisome proliferator- 5467 PPARD 1534.6 1352.9 330.8 activated receptor delta peroxisome proliferator- 5468 PPARG 524.4 100.8 63.0 activated receptor gamma 5621 PRNP prion protein 4059.0 3134.1 1065.5 5925 RB1 retinoblastoma 1 882.9 805.8 739.3 23411 SIRT1 sirtuin 1 231.5 216.8 1676.0 7157 TP53 -
Homozygosity Mapping and Sequencing Identify Two Genes That
Akkad et al. Canine Genetics and Epidemiology (2015) 2:5 DOI 10.1186/s40575-015-0018-5 RESEARCH Open Access Homozygosity mapping and sequencing identify two genes that might contribute to pointing behavior in hunting dogs Denis A Akkad1*†, Wanda M Gerding1†, Robin B Gasser2 and Jörg T Epplen1,3 Abstract Background: The domestic dog represents an important model for studying the genetics of behavior. In spite of technological advances in genomics and phenomics, the genetic basis of most specific canine behaviors is largely unknown. Some breeds of hunting dogs exhibit a behavioral trait called “pointing” (a prolonged halt of movement to indicate the position of a game animal). Here, the genomes of pointing dogs (Large Munsterlander and Weimaraner) were compared with those of behaviorally distinct herding dogs (Berger des Pyrenées and Schapendoes). We assumed (i) that these four dog breeds initially represented inbred populations and (ii) that selective breeding for pointing behavior promotes an enrichment of the genetic trait in a homozygous state. Results: The homozygosity mapping of 52 dogs (13 of each of the four breeds) followed by subsequent interval resequencing identified fixed genetic differences on chromosome 22 between pointers and herding dogs. In addition, we identified one non-synonomous variation in each of the coding genes SETDB2 and CYSLTR2 that might have a functional consequence. Genetic analysis of additional hunting and non-hunting dogs revealed consistent homozygosity forthesetwovariationsinsixofsevenpointingbreeds. Conclusions: Based on the present findings, we propose that, together with other genetic, training and/or environmental factors, the nucleotide and associated amino acid variations identified in genes SETDB2 and CYSLTR2 contribute to pointing behavior. -
Graphical Models for Zero-Inflated Single Cell Gene Expression
arXiv: arXiv:1610.05857 GRAPHICAL MODELS FOR ZERO-INFLATED SINGLE CELL GENE EXPRESSION , By Andrew McDavid∗ Raphael Gottardo† ‡ Noah Simon§ and Mathias Drton‡ Department of Biostatistics and Computational Biology∗, University of Rochester Medical Center; Rochester, New York. Vaccine and Infectuous Disease Division†, Fred Hutchinson Cancer Research Center, Department of Statistics‡ and Department of Biostatistics§, University of Washington; Seattle, Washington. Bulk gene expression experiments relied on aggregations of thou- sands of cells to measure the average expression in an organism. Ad- vances in microfluidic and droplet sequencing now permit expression profiling in single cells. This study of cell-to-cell variation reveals that individual cells lack detectable expression of transcripts that appear abundant on a population level, giving rise to zero-inflated expression patterns. To infer gene co-regulatory networks from such data, we propose a multivariate Hurdle model. It is comprised of a mixture of singular Gaussian distributions. We employ neighborhood selection with the pseudo-likelihood and a group lasso penalty to select and fit undirected graphical models that capture conditional independences between genes. The proposed method is more sensi- tive than existing approaches in simulations, even under departures from our Hurdle model. The method is applied to data for T follicu- lar helper cells, and a high-dimensional profile of mouse dendritic cells. It infers network structure not revealed by other methods; or in bulk data sets. An R implementation is available at https: //github.com/amcdavid/HurdleNormal. 1. Introduction. Graphical models have been used to synthesize high- throughput gene expression experiments into understandable, canonical forms [Dobra et al., 2004, Markowetz and Spang, 2007]. -
Universidad Autónoma De Madrid
Universidad Autónoma de Madrid Departamento de Bioquímica Identification of the substrates of the protease MT1-MMP in TNFα- stimulated endothelial cells by quantitative proteomics. Analysis of their potential use as biomarkers in inflammatory bowel disease. Agnieszka A. Koziol Tesis doctoral Madrid, 2013 2 Departamento de Bioquímica Facultad de Medicina Universidad Autónoma de Madrid Identification of the substrates of the protease MT1-MMP in TNFα- stimulated endothelial cells by quantitative proteomics. Analysis of their potential use as biomarkers in inflammatory bowel disease. Memoria presentada por Agnieszka A. Koziol licenciada en Ciencias Biológicas para optar al grado de Doctor. Directora: Dra Alicia García Arroyo Centro Nacional de Investigaciones Cardiovasculares (CNIC) Madrid, 2013 3 4 ACKNOWLEDGEMENTS - ACKNOWLEDGEMENTS - First and foremost I would like to express my sincere gratitude to my supervisor Dr. Alicia García Arroyo for giving me the great opportunity to study under her direction. Her encouragement, guidance and support from the beginning to the end, enabled me to develop and understand the subject. Her feedback to this manuscript, critical reading and corrections was inappreciable to finish this dissertation. Next, I would like to express my gratitude to those who helped me substantially along the way. To all members of MMPs’ lab, for their interest in the project, teaching me during al these years and valuable contribution at the seminary discussion. Without your help it would have not been possible to do some of those experiments. Thank you all for creating a nice atmosphere at work and for being so good friends in private. I would like to also thank all of the collaborators and technical units for their support and professionalism. -
PDF, Also Known As Version of Record
King’s Research Portal DOI: 10.1038/s41467-018-03283-z Document Version Publisher's PDF, also known as Version of record Link to publication record in King's Research Portal Citation for published version (APA): Patel, N., Weekes, D., Drosopoulos, K., Gazinska, P., Noel, E., Rashid, M., Mirza, H., Quist, J., Brasó-Maristany, F., Mathew, S., Ferro, R., Pereira, A. M., Prince, C., Noor, F., Francesch-Domenech, E., Marlow, R., de Rinaldis, E., Grigoriadis, A., Linardopoulos, S., ... Tutt, A. N. J. (2018). Integrated genomics and functional validation identifies malignant cell specific dependencies in triple negative breast cancer. Nature Communications, 9(1), [1044]. https://doi.org/10.1038/s41467-018-03283-z Citing this paper Please note that where the full-text provided on King's Research Portal is the Author Accepted Manuscript or Post-Print version this may differ from the final Published version. If citing, it is advised that you check and use the publisher's definitive version for pagination, volume/issue, and date of publication details. And where the final published version is provided on the Research Portal, if citing you are again advised to check the publisher's website for any subsequent corrections. General rights Copyright and moral rights for the publications made accessible in the Research Portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognize and abide by the legal requirements associated with these rights. •Users may download and print one copy of any publication from the Research Portal for the purpose of private study or research. -
Profiling Dynamic Chromatome Reveals HP1BP3 As a Key Regulator of Cell Cycle and Hypoxia Cancer Progression
This document is downloaded from DR‑NTU (https://dr.ntu.edu.sg) Nanyang Technological University, Singapore. Profiling dynamic chromatome reveals HP1BP3 as a key regulator of cell cycle and hypoxia cancer progression Bamaprasad Dutta 2014 Bamaprasad Dutta. (2014). Profiling dynamic chromatome reveals HP1BP3 as a key regulator of cell cycle and hypoxia cancer progression. Doctoral thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/59912 https://doi.org/10.32657/10356/59912 Downloaded on 06 Oct 2021 14:05:24 SGT PROFILING DYNAMIC CHROMATOME REVEALS HP1BP3 AS A KEY REGULATOR OF CELL CYCLE AND HYPOXIA CANCER PROGRESSION BAMAPRASAD DUTTA SCHOOL OF BIOLOGICAL SCIENCES 2014 Profiling dynamic chromatome reveals HP1BP3 as a key regulator of cell cycle and hypoxia cancer progression Bamaprasad Dutta School of Biological Sciences A thesis submitted to the Nanyang Technological University in partial fulfillment of the requirement of the degree of Doctor of Philosophy 2014 Acknowledgements Acknowledgements I would like to express my sincere gratitude to my supervisor Dr. Siu Kwan Sze, for his expert guidance and warm encouragement. He shared his wealth of experience on numerous occasions and this has provided me with a great learning experience. Special thanks go to Dr. Ren Yan for her invaluable discussions and suggestions, which helped me a lot in this project and also for helping me to learn the basic experiments. I am indebted to Dr. Sunil Shankar Adav for sharing his experience and helping. I would also like to acknowledge the kind support of my current and former laboratory collogues, especially Dr. Park Jung Eun, Tiannan Gao, Li Xin, Arnab Datta, Hao Piliang, Sim Kae Hwan, and Cheow Sok Hwee Esther for extending their helping hand anytime I needed.