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Whole-Genome Linkage Scan Combined with Exome Sequencing Identifies Novel Candidate Genes for Carotid Intima-Media Thickness
fgene-09-00420 October 5, 2018 Time: 14:5 # 1 ORIGINAL RESEARCH published: 09 October 2018 doi: 10.3389/fgene.2018.00420 Whole-Genome Linkage Scan Combined With Exome Sequencing Identifies Novel Candidate Genes for Carotid Intima-Media Thickness Dina Vojinovic1, Maryam Kavousi1, Mohsen Ghanbari1,2, Rutger W. W. Brouwer3, Jeroen G. J. van Rooij4, Mirjam C. G. N. van den Hout3, Robert Kraaij4, Wilfred F. J. van Ijcken3, Andre G. Uitterlinden1,4, Cornelia M. van Duijn1,5 and Najaf Amin1* 1 Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, Netherlands, 2 Department of Genetics, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran, 3 Department of Cell Biology, Center for Biomics, Erasmus MC University Medical Center, Rotterdam, Netherlands, 4 Department of Internal Medicine, Erasmus MC University Medical Center, Rotterdam, Netherlands, 5 Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom Carotid intima-media thickness (cIMT) is an established heritable marker for subclinical atherosclerosis. In this study, we aim to identify rare variants with large effects driving Edited by: differences in cIMT by performing genome-wide linkage analysis of individuals in the Robert Klein, extremes of cIMT trait distribution (>90th percentile) in a large family-based study from Icahn School of Medicine at Mount a genetically isolated population in the Netherlands. Linked regions were subsequently Sinai, United States explored by fine-mapping using exome sequencing. We observed significant evidence Reviewed by: Elizabeth Hauser, of linkage on chromosomes 2p16.3 [rs1017418, heterogeneity LOD (HLOD) = 3.35], Duke University, United States 19q13.43 (rs3499, HLOD = 9.09), 20p13 (rs1434789, HLOD = 4.10), and 21q22.12 Mark Z. -
Coexpression Networks Based on Natural Variation in Human Gene Expression at Baseline and Under Stress
University of Pennsylvania ScholarlyCommons Publicly Accessible Penn Dissertations Fall 2010 Coexpression Networks Based on Natural Variation in Human Gene Expression at Baseline and Under Stress Renuka Nayak University of Pennsylvania, [email protected] Follow this and additional works at: https://repository.upenn.edu/edissertations Part of the Computational Biology Commons, and the Genomics Commons Recommended Citation Nayak, Renuka, "Coexpression Networks Based on Natural Variation in Human Gene Expression at Baseline and Under Stress" (2010). Publicly Accessible Penn Dissertations. 1559. https://repository.upenn.edu/edissertations/1559 This paper is posted at ScholarlyCommons. https://repository.upenn.edu/edissertations/1559 For more information, please contact [email protected]. Coexpression Networks Based on Natural Variation in Human Gene Expression at Baseline and Under Stress Abstract Genes interact in networks to orchestrate cellular processes. Here, we used coexpression networks based on natural variation in gene expression to study the functions and interactions of human genes. We asked how these networks change in response to stress. First, we studied human coexpression networks at baseline. We constructed networks by identifying correlations in expression levels of 8.9 million gene pairs in immortalized B cells from 295 individuals comprising three independent samples. The resulting networks allowed us to infer interactions between biological processes. We used the network to predict the functions of poorly-characterized human genes, and provided some experimental support. Examining genes implicated in disease, we found that IFIH1, a diabetes susceptibility gene, interacts with YES1, which affects glucose transport. Genes predisposing to the same diseases are clustered non-randomly in the network, suggesting that the network may be used to identify candidate genes that influence disease susceptibility. -
Interphase Chromatin
Proteomics of a fuzzy organelle: interphase chromatin Article (Accepted Version) Kustatscher, Georg, Hégarat, Nadia, Willis, Karen L H, Furlan, Cristina, Bukowski-Wills, Jimi- Carlo, Hochegger, Helfrid and Rappsilber, Juri (2014) Proteomics of a fuzzy organelle: interphase chromatin. The EMBO Journal, 33 (6). pp. 648-664. ISSN 0261-4189 This version is available from Sussex Research Online: http://sro.sussex.ac.uk/id/eprint/80788/ This document is made available in accordance with publisher policies and may differ from the published version or from the version of record. If you wish to cite this item you are advised to consult the publisher’s version. Please see the URL above for details on accessing the published version. Copyright and reuse: Sussex Research Online is a digital repository of the research output of the University. Copyright and all moral rights to the version of the paper presented here belong to the individual author(s) and/or other copyright owners. To the extent reasonable and practicable, the material made available in SRO has been checked for eligibility before being made available. Copies of full text items generally can be reproduced, displayed or performed and given to third parties in any format or medium for personal research or study, educational, or not-for-profit purposes without prior permission or charge, provided that the authors, title and full bibliographic details are credited, a hyperlink and/or URL is given for the original metadata page and the content is not changed in any way. http://sro.sussex.ac.uk Proteomics of a fuzzy organelle: interphase chromatin Georg Kustatscher1&, Nadia Hegarat2&, Karen L. -
Interphase Chromatin
Resource Proteomics of a fuzzy organelle: interphase chromatin Georg Kustatscher1,†, Nadia Hegarat2,†, Karen L H Wills1, Cristina Furlan1, Jimi-Carlo Bukowski-Wills1, Helfrid Hochegger2,* & Juri Rappsilber1,3,** Abstract on co-fractionation with marker proteins on density gradients (Andersen et al, 2003; Dunkley et al, 2004; Foster et al, 2006). Chromatin proteins mediate replication, regulate expression, and Defining organelles in this way critically depends on biochemical ensure integrity of the genome. So far, a comprehensive inventory procedures and inherently introduces a series of purification arti- of interphase chromatin has not been determined. This is largely facts. We have recently circumvented some of these by an approach due to its heterogeneous and dynamic composition, which makes called Multiclassifier Combinatorial Proteomics (MCCP; Ohta et al, conclusive biochemical purification difficult, if not impossible. As a 2010). A common feature of these investigations is that they attempt fuzzy organelle, it defies classical organellar proteomics and cannot to completely separate genuine components from contaminants be described by a single and ultimate list of protein components. through biochemical and/or bioinformatics approaches. Crucially, Instead, we propose a new approach that provides a quantitative the underlying assumption is that definite component lists can accu- assessment of a protein’s probability to function in chromatin. rately describe complex biological structures. In light of the dynamic We integrate chromatin composition over a range of different nature of organelles, an alternative concept may be needed. biochemical and biological conditions. This resulted in interphase Through examination of human interphase chromatin, we develop chromatin probabilities for 7635 human proteins, including 1840 an approach to capture the dynamic composition of biological struc- previously uncharacterized proteins. -
A Deep Transcriptome Meta-Analysis Reveals Sex-Based Molecular Differences in Multiple Sclerosis
medRxiv preprint doi: https://doi.org/10.1101/2021.08.31.21262175; this version posted September 2, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license . A deep transcriptome meta-analysis reveals sex-based molecular differences in Multiple Sclerosis José Francisco Català-Senent1†, Zoraida Andreu2†, Francisco José Roig1,3, Marta R. Hidalgo1, Natalia Yanguas-Casás4, Almudena Neva-Alejo1, Adolfo López-Cerdán5, Irene Soler-Sáez1, María de la Iglesia-Vayá5, Francisco García-García1 Correspondence: Francisco García-García, [email protected] †José Francisco Català-Senent and Zoraida Andreu contributed equally to this study 1Bioinformatics and Biostatistics Unit, Principe Felipe Research Center (CIPF), 46012, Valencia, Spain 2Foundation Valencian Institute of Oncology (FIVO), 46009, Valencia, Spain 3Faculty of Health Sciences. San Jorge University, 50830, Zaragoza, Spain 4Instituto de Investigación Sanitaria Puerta de Hierro-Segovia de Arana (IDIPHISA), Grupo de Investigación en Linfomas, C/Joaquín Rodrigo 2, Majadahonda, 28222 Madrid, Spain 5Biomedical Imaging Unit FISABIO-CIPF, Fundación para el Fomento de la Investigación Sanitaria y Biomédica de la Comunidad Valenciana, 46012, Valencia, Spain NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice. 1 medRxiv preprint doi: https://doi.org/10.1101/2021.08.31.21262175; this version posted September 2, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. -
1 Imipramine Treatment and Resiliency Exhibit Similar
Imipramine Treatment and Resiliency Exhibit Similar Chromatin Regulation in the Mouse Nucleus Accumbens in Depression Models Wilkinson et al. Supplemental Material 1. Supplemental Methods 2. Supplemental References for Tables 3. Supplemental Tables S1 – S24 SUPPLEMENTAL TABLE S1: Genes Demonstrating Increased Repressive DimethylK9/K27-H3 Methylation in the Social Defeat Model (p<0.001) SUPPLEMENTAL TABLE S2: Genes Demonstrating Decreased Repressive DimethylK9/K27-H3 Methylation in the Social Defeat Model (p<0.001) SUPPLEMENTAL TABLE S3: Genes Demonstrating Increased Repressive DimethylK9/K27-H3 Methylation in the Social Isolation Model (p<0.001) SUPPLEMENTAL TABLE S4: Genes Demonstrating Decreased Repressive DimethylK9/K27-H3 Methylation in the Social Isolation Model (p<0.001) SUPPLEMENTAL TABLE S5: Genes Demonstrating Common Altered Repressive DimethylK9/K27-H3 Methylation in the Social Defeat and Social Isolation Models (p<0.001) SUPPLEMENTAL TABLE S6: Genes Demonstrating Increased Repressive DimethylK9/K27-H3 Methylation in the Social Defeat and Social Isolation Models (p<0.001) SUPPLEMENTAL TABLE S7: Genes Demonstrating Decreased Repressive DimethylK9/K27-H3 Methylation in the Social Defeat and Social Isolation Models (p<0.001) SUPPLEMENTAL TABLE S8: Genes Demonstrating Increased Phospho-CREB Binding in the Social Defeat Model (p<0.001) SUPPLEMENTAL TABLE S9: Genes Demonstrating Decreased Phospho-CREB Binding in the Social Defeat Model (p<0.001) SUPPLEMENTAL TABLE S10: Genes Demonstrating Increased Phospho-CREB Binding in the Social -
Structure-Function Relationships of Rna and Protein in Synaptic Plasticity
University of Pennsylvania ScholarlyCommons Publicly Accessible Penn Dissertations 2017 Structure-Function Relationships Of Rna And Protein In Synaptic Plasticity Sarah Middleton University of Pennsylvania, [email protected] Follow this and additional works at: https://repository.upenn.edu/edissertations Part of the Bioinformatics Commons, Biology Commons, and the Neuroscience and Neurobiology Commons Recommended Citation Middleton, Sarah, "Structure-Function Relationships Of Rna And Protein In Synaptic Plasticity" (2017). Publicly Accessible Penn Dissertations. 2474. https://repository.upenn.edu/edissertations/2474 This paper is posted at ScholarlyCommons. https://repository.upenn.edu/edissertations/2474 For more information, please contact [email protected]. Structure-Function Relationships Of Rna And Protein In Synaptic Plasticity Abstract Structure is widely acknowledged to be important for the function of ribonucleic acids (RNAs) and proteins. However, due to the relative accessibility of sequence information compared to structure information, most large genomics studies currently use only sequence-based annotation tools to analyze the function of expressed molecules. In this thesis, I introduce two novel computational methods for genome-scale structure-function analysis and demonstrate their application to identifying RNA and protein structures involved in synaptic plasticity and potentiation—important neuronal processes that are thought to form the basis of learning and memory. First, I describe a new method for de novo identification of RNA secondary structure motifs enriched in co-regulated transcripts. I show that this method can accurately identify secondary structure motifs that recur across three or more transcripts in the input set with an average recall of 0.80 and precision of 0.98. Second, I describe a tool for predicting protein structural fold from amino acid sequence, which achieves greater than 96% accuracy on benchmarks and can be used to predict protein function and identify new structural folds. -
Glomerular Expression Pattern of Long Non-Coding Rnas in the Type 2
www.nature.com/scientificreports OPEN Glomerular expression pattern of long non-coding RNAs in the type 2 diabetes mellitus BTBR mouse Received: 13 August 2018 Accepted: 11 June 2019 model Published: xx xx xxxx Simone Reichelt-Wurm 1, Tobias Wirtz1, Dominik Chittka1, Maja Lindenmeyer2,3, Robert M. Reichelt4, Sebastian Beck1, Panagiotis Politis5, Aristidis Charonis6, Markus Kretz7, Tobias B. Huber3, Shuya Liu3, Bernhard Banas 1 & Miriam C. Banas1 The prevalence of type 2 diabetes mellitus (T2DM) and by association diabetic nephropathy (DN) will continuously increase in the next decades. Nevertheless, the underlying molecular mechanisms are largely unknown and studies on the role of new actors like long non-coding RNAs (lncRNAs) barely exist. In the present study, the inherently insulin-resistant mouse strain “black and tan, brachyuric” (BTBR) served as T2DM model. While wild-type mice do not exhibit pathological changes, leptin- defcient diabetic animals develop a severe T2DM accompanied by a DN, which closely resembles the human phenotype. We analyzed the glomerular expression of lncRNAs from wild-type and diabetic BTBR mice (four, eight, 16, and 24 weeks) applying the “GeneChip Mouse Whole Transcriptome 1.0 ST” array. This microarray covered more lncRNA gene loci than any other array before. Over the observed time, our data revealed diferential expression patterns of 1746 lncRNAs, which markedly difered from mRNAs. We identifed protein-coding and non-coding genes, that were not only co-located but also co- expressed, indicating a potentially cis-acting function of these lncRNAs. In vitro-experiments strongly suggested a cell-specifc expression of these lncRNA-mRNA-pairs. Additionally, protein-coding genes, being associated with signifcantly regulated lncRNAs, were enriched in various biological processes and pathways, that were strongly linked to diabetes. -
The Molecular Karyotype of 25 Clinical-Grade Human Embryonic Stem Cell Lines
Edinburgh Research Explorer The molecular karyotype of 25 clinical-grade human embryonic stem cell lines Citation for published version: Canham, MA, Van Deusen, A, Brison, DR, De Sousa, PA, Downie, J, Devito, L, Hewitt, ZA, Ilic, D, Kimber, SJ, Moore, HD, Murray, H & Kunath, T 2015, 'The molecular karyotype of 25 clinical-grade human embryonic stem cell lines', Scientific Reports, vol. 5, 17258. https://doi.org/10.1038/srep17258 Digital Object Identifier (DOI): 10.1038/srep17258 Link: Link to publication record in Edinburgh Research Explorer Document Version: Publisher's PDF, also known as Version of record Published In: Scientific Reports General rights Copyright for the publications made accessible via the Edinburgh Research Explorer is retained by the author(s) and / or other copyright owners and it is a condition of accessing these publications that users recognise and abide by the legal requirements associated with these rights. Take down policy The University of Edinburgh has made every reasonable effort to ensure that Edinburgh Research Explorer content complies with UK legislation. If you believe that the public display of this file breaches copyright please contact [email protected] providing details, and we will remove access to the work immediately and investigate your claim. Download date: 06. Oct. 2021 www.nature.com/scientificreports OPEN The Molecular Karyotype of 25 Clinical-Grade Human Embryonic Stem Cell Lines Received: 07 August 2015 1 1 2 3,4 Accepted: 27 October 2015 Maurice A. Canham , Amy Van Deusen , Daniel R. Brison , Paul A. De Sousa , 3 5 6 5 7 Published: 26 November 2015 Janet Downie , Liani Devito , Zoe A. -
Genome-Wide Association Studies of Autoimmune Vitiligo Identify 23 New Risk Loci and Highlight Key Pathways and Regulatory Variants
CORE Metadata, citation and similar papers at core.ac.uk Provided by University of Liverpool RepositoryHHS Public Access Author manuscript Author ManuscriptAuthor Manuscript Author Nat Genet Manuscript Author . Author manuscript; Manuscript Author available in PMC 2017 April 10. Published in final edited form as: Nat Genet. 2016 November ; 48(11): 1418–1424. doi:10.1038/ng.3680. Genome-wide association studies of autoimmune vitiligo identify 23 new risk loci and highlight key pathways and regulatory variants Ying Jin1,2, Genevieve Andersen1, Daniel Yorgov3, Tracey M Ferrara1, Songtao Ben1, Kelly M Brownson1, Paulene J Holland1, Stanca A Birlea1,4, Janet Siebert5, Anke Hartmann6, Anne Lienert6, Nanja van Geel7, Jo Lambert7, Rosalie M Luiten8, Albert Wolkerstorfer8, JP Wietze van der Veen8,9, Dorothy C Bennett10, Alain Taïeb11, Khaled Ezzedine11, E Helen Kemp12, David J Gawkrodger12, Anthony P Weetman12, Sulev Kõks13, Ele Prans13, Külli Kingo14, Maire Karelson14, Margaret R Wallace15, Wayne T McCormack16, Andreas Overbeck17, Silvia Moretti18, Roberta Colucci18, Mauro Picardo19, Nanette B Silverberg20,21, Mats Olsson22, Yan Valle23, Igor Korobko23,24, Markus Böhm25, Henry W. Lim26, Iltefat Hamzavi26, Li Zhou26, Qing-Sheng Mi26, Pamela R. Fain1,2, Stephanie A Santorico1,3,27, and Richard A Spritz1,2 1Human Medical Genetics and Genomics Program, University of Colorado School of Medicine, Aurora, Colorado, USA 2Department of Pediatrics, University of Colorado School of Medicine, Aurora, Colorado, USA 3Department of Mathematical and Statistical -
Attractor Metafeatures and Their Application in Biomolecular Data Analysis
Attractor Metafeatures and Their Application in Biomolecular Data Analysis Tai-Hsien Ou Yang Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Graduate School of Arts and Sciences COLUMBIA UNIVERSITY 2018 ©2018 Tai-Hsien Ou Yang All rights reserved ABSTRACT Attractor Metafeatures and Their Application in Biomolecular Data Analysis Tai-Hsien Ou Yang This dissertation proposes a family of algorithms for deriving signatures of mutually associated features, to which we refer as attractor metafeatures, or simply attractors. Specifically, we present multi-cancer attractor derivation algorithms, identifying correlated features in signatures from multiple biological data sets in one analysis, as well as the groups of samples or cells that exclusively express these signatures. Our results demonstrate that these signatures can be used, in proper combinations, as biomarkers that predict a patient’s survival rate, based on the transcriptome of the tumor sample. They can also be used as features to analyze the composition of the tumor. Through analyzing large data sets of 18 cancer types and three high-throughput platforms from The Cancer Genome Atlas (TCGA) PanCanAtlas Project and multiple single-cell RNA-seq data sets, we identified novel cancer attractor signatures and elucidated the identity of the cells that express these signatures. Using these signatures, we developed a prognostic biomarker for breast cancer called the Breast Cancer Attractor Metagenes (BCAM) biomarker as well as a software platform -
RNA Sequencing Unravels the Genetics of Refractory/Relapsed T-Cell Acute Lymphoblastic Leukemia
Acute Lymphoblastic Leukemia SUPPLEMENTARY APPENDIX RNA sequencing unravels the genetics of refractory/relapsed T-cell acute lymphoblastic leukemia. Prognostic and therapeutic implications Valentina Gianfelici, 1* Sabina Chiaretti, 1* Sofie Demeyer, 2,3 * Filomena Di Giacomo, 1,4 Monica Messina, 1 Roberta La Starza, 5 Nadia Peragine, 1 Francesca Paoloni, 6 Ellen Geerdens, 2,3 Valentina Pierini, 5 Loredana Elia, 1 Marco Mancini, 1 Maria Stefania De Propris, 1 Valerio Apicella, 1 Gianluca Gaidano, 7 Anna Maria Testi, 1 Antonella Vitale, 1 Marco Vignetti, 1,6 Cristina Mecucci, 5 Anna Guarini, 1 Jan Cools, 2,3 and Robin Foà 1 1Hematology, Department of Cellular Biotechnologies and Hematology, Sapienza University, Rome, Italy; 2Center for Human Genetics, KU Leuven, Belgium; 3Center for the Biology of Disease, VIB, Leuven, Belgium; 4Department of Molecular Biotechnology and Health Science and Center for Experimental Research and Medical Studies (CeRMS), University of Turin, Italy; 5Hematology and Bone Marrow Transplantation Unit, Department of Medicine, University of Perugia, Italy; 6GIMEMA Data Center, Rome, Italy; and 7Division of Hematol - ogy, Department of Translational Medicine, Amedeo Avogadro University of Eastern Piedmont, Novara, Italy * VG, SC and SD contributed equally to this work. ©2016 Ferrata Storti Foundation. This is an open-access paper. doi:10.3324/haematol. 2015.139410 Received: November 12, 2015. Accepted: April 29, 2016. Pre-published: May 5, 2016. [email protected] SUPPLEMENTAL MATERIALS AND METHODS FISH analysis FISH was performed as previously described1 using probes selected from the genomic databases “NCBI” (National Center for Biotechnology Information, Annotation Release 106 and previous assembly) and “UCSC” (University of California, Santa Cruz, Genome Browser Feb.