Analysis of RNA Expression of Normal and Cancer Tissues Reveals High Correlation of COP9 Gene Expression with Respiratory Chain Complex Components Christina A
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Old Data and Friends Improve with Age: Advancements with the Updated Tools of Genenetwork
bioRxiv preprint doi: https://doi.org/10.1101/2021.05.24.445383; this version posted May 25, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.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 4.0 International license. Old data and friends improve with age: Advancements with the updated tools of GeneNetwork Alisha Chunduri1, David G. Ashbrook2 1Department of Biotechnology, Chaitanya Bharathi Institute of Technology, Hyderabad 500075, India 2Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN 38163, USA Abstract Understanding gene-by-environment interactions is important across biology, particularly behaviour. Families of isogenic strains are excellently placed, as the same genome can be tested in multiple environments. The BXD’s recent expansion to 140 strains makes them the largest family of murine isogenic genomes, and therefore give great power to detect QTL. Indefinite reproducible genometypes can be leveraged; old data can be reanalysed with emerging tools to produce novel biological insights. To highlight the importance of reanalyses, we obtained drug- and behavioural-phenotypes from Philip et al. 2010, and reanalysed their data with new genotypes from sequencing, and new models (GEMMA and R/qtl2). We discover QTL on chromosomes 3, 5, 9, 11, and 14, not found in the original study. We narrowed down the candidate genes based on their ability to alter gene expression and/or protein function, using cis-eQTL analysis, and variants predicted to be deleterious. Co-expression analysis (‘gene friends’) and human PheWAS were used to further narrow candidates. -
Analysis of Trans Esnps Infers Regulatory Network Architecture
Analysis of trans eSNPs infers regulatory network architecture Anat Kreimer Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Graduate School of Arts and Sciences COLUMBIA UNIVERSITY 2014 © 2014 Anat Kreimer All rights reserved ABSTRACT Analysis of trans eSNPs infers regulatory network architecture Anat Kreimer eSNPs are genetic variants associated with transcript expression levels. The characteristics of such variants highlight their importance and present a unique opportunity for studying gene regulation. eSNPs affect most genes and their cell type specificity can shed light on different processes that are activated in each cell. They can identify functional variants by connecting SNPs that are implicated in disease to a molecular mechanism. Examining eSNPs that are associated with distal genes can provide insights regarding the inference of regulatory networks but also presents challenges due to the high statistical burden of multiple testing. Such association studies allow: simultaneous investigation of many gene expression phenotypes without assuming any prior knowledge and identification of unknown regulators of gene expression while uncovering directionality. This thesis will focus on such distal eSNPs to map regulatory interactions between different loci and expose the architecture of the regulatory network defined by such interactions. We develop novel computational approaches and apply them to genetics-genomics data in human. We go beyond pairwise interactions to define network motifs, including regulatory modules and bi-fan structures, showing them to be prevalent in real data and exposing distinct attributes of such arrangements. We project eSNP associations onto a protein-protein interaction network to expose topological properties of eSNPs and their targets and highlight different modes of distal regulation. -
ACE2 Interaction Networks in COVID-19: a Physiological Framework for Prediction of Outcome in Patients with Cardiovascular Risk Factors
Journal of Clinical Medicine Article ACE2 Interaction Networks in COVID-19: A Physiological Framework for Prediction of Outcome in Patients with Cardiovascular Risk Factors Zofia Wicik 1,2 , Ceren Eyileten 2, Daniel Jakubik 2,Sérgio N. Simões 3, David C. Martins Jr. 1, Rodrigo Pavão 1, Jolanta M. Siller-Matula 2,4,* and Marek Postula 2 1 Centro de Matemática, Computação e Cognição, Universidade Federal do ABC, Santo Andre 09606-045, Brazil; zofi[email protected] (Z.W.); [email protected] (D.C.M.J.); [email protected] (R.P.) 2 Department of Experimental and Clinical Pharmacology, Medical University of Warsaw, Center for Preclinical Research and Technology CEPT, 02-091 Warsaw, Poland; [email protected] (C.E.); [email protected] (D.J.); [email protected] (M.P.) 3 Federal Institute of Education, Science and Technology of Espírito Santo, Serra, Espírito Santo 29056-264, Brazil; [email protected] 4 Department of Internal Medicine II, Division of Cardiology, Medical University of Vienna, 1090 Vienna, Austria * Correspondence: [email protected]; Tel.: +43-1-40400-46140; Fax: +43-1-40400-42160 Received: 9 October 2020; Accepted: 17 November 2020; Published: 21 November 2020 Abstract: Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (coronavirus disease 2019; COVID-19) is associated with adverse outcomes in patients with cardiovascular disease (CVD). The aim of the study was to characterize the interaction between SARS-CoV-2 and Angiotensin-Converting Enzyme 2 (ACE2) functional networks with a focus on CVD. Methods: Using the network medicine approach and publicly available datasets, we investigated ACE2 tissue expression and described ACE2 interaction networks that could be affected by SARS-CoV-2 infection in the heart, lungs and nervous system. -
Transcriptome Analyses of Rhesus Monkey Pre-Implantation Embryos Reveal A
Downloaded from genome.cshlp.org on September 23, 2021 - Published by Cold Spring Harbor Laboratory Press Transcriptome analyses of rhesus monkey pre-implantation embryos reveal a reduced capacity for DNA double strand break (DSB) repair in primate oocytes and early embryos Xinyi Wang 1,3,4,5*, Denghui Liu 2,4*, Dajian He 1,3,4,5, Shengbao Suo 2,4, Xian Xia 2,4, Xiechao He1,3,6, Jing-Dong J. Han2#, Ping Zheng1,3,6# Running title: reduced DNA DSB repair in monkey early embryos Affiliations: 1 State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650223, China 2 Key Laboratory of Computational Biology, CAS Center for Excellence in Molecular Cell Science, Collaborative Innovation Center for Genetics and Developmental Biology, Chinese Academy of Sciences-Max Planck Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China 3 Yunnan Key Laboratory of Animal Reproduction, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650223, China 4 University of Chinese Academy of Sciences, Beijing, China 5 Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan 650204, China 6 Primate Research Center, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China * Xinyi Wang and Denghui Liu contributed equally to this work 1 Downloaded from genome.cshlp.org on September 23, 2021 - Published by Cold Spring Harbor Laboratory Press # Correspondence: Jing-Dong J. Han, Email: [email protected]; Ping Zheng, Email: [email protected] Key words: rhesus monkey, pre-implantation embryo, DNA damage 2 Downloaded from genome.cshlp.org on September 23, 2021 - Published by Cold Spring Harbor Laboratory Press ABSTRACT Pre-implantation embryogenesis encompasses several critical events including genome reprogramming, zygotic genome activation (ZGA) and cell fate commitment. -
Seq2pathway Vignette
seq2pathway Vignette Bin Wang, Xinan Holly Yang, Arjun Kinstlick May 19, 2021 Contents 1 Abstract 1 2 Package Installation 2 3 runseq2pathway 2 4 Two main functions 3 4.1 seq2gene . .3 4.1.1 seq2gene flowchart . .3 4.1.2 runseq2gene inputs/parameters . .5 4.1.3 runseq2gene outputs . .8 4.2 gene2pathway . 10 4.2.1 gene2pathway flowchart . 11 4.2.2 gene2pathway test inputs/parameters . 11 4.2.3 gene2pathway test outputs . 12 5 Examples 13 5.1 ChIP-seq data analysis . 13 5.1.1 Map ChIP-seq enriched peaks to genes using runseq2gene .................... 13 5.1.2 Discover enriched GO terms using gene2pathway_test with gene scores . 15 5.1.3 Discover enriched GO terms using Fisher's Exact test without gene scores . 17 5.1.4 Add description for genes . 20 5.2 RNA-seq data analysis . 20 6 R environment session 23 1 Abstract Seq2pathway is a novel computational tool to analyze functional gene-sets (including signaling pathways) using variable next-generation sequencing data[1]. Integral to this tool are the \seq2gene" and \gene2pathway" components in series that infer a quantitative pathway-level profile for each sample. The seq2gene function assigns phenotype-associated significance of genomic regions to gene-level scores, where the significance could be p-values of SNPs or point mutations, protein-binding affinity, or transcriptional expression level. The seq2gene function has the feasibility to assign non-exon regions to a range of neighboring genes besides the nearest one, thus facilitating the study of functional non-coding elements[2]. Then the gene2pathway summarizes gene-level measurements to pathway-level scores, comparing the quantity of significance for gene members within a pathway with those outside a pathway. -
Epigenetic Mechanisms of Lncrnas Binding to Protein in Carcinogenesis
cancers Review Epigenetic Mechanisms of LncRNAs Binding to Protein in Carcinogenesis Tae-Jin Shin, Kang-Hoon Lee and Je-Yoel Cho * Department of Biochemistry, BK21 Plus and Research Institute for Veterinary Science, School of Veterinary Medicine, Seoul National University, Seoul 08826, Korea; [email protected] (T.-J.S.); [email protected] (K.-H.L.) * Correspondence: [email protected]; Tel.: +82-02-800-1268 Received: 21 September 2020; Accepted: 9 October 2020; Published: 11 October 2020 Simple Summary: The functional analysis of lncRNA, which has recently been investigated in various fields of biological research, is critical to understanding the delicate control of cells and the occurrence of diseases. The interaction between proteins and lncRNA, which has been found to be a major mechanism, has been reported to play an important role in cancer development and progress. This review thus organized the lncRNAs and related proteins involved in the cancer process, from carcinogenesis to metastasis and resistance to chemotherapy, to better understand cancer and to further develop new treatments for it. This will provide a new perspective on clinical cancer diagnosis, prognosis, and treatment. Abstract: Epigenetic dysregulation is an important feature for cancer initiation and progression. Long non-coding RNAs (lncRNAs) are transcripts that stably present as RNA forms with no translated protein and have lengths larger than 200 nucleotides. LncRNA can epigenetically regulate either oncogenes or tumor suppressor genes. Nowadays, the combined research of lncRNA plus protein analysis is gaining more attention. LncRNA controls gene expression directly by binding to transcription factors of target genes and indirectly by complexing with other proteins to bind to target proteins and cause protein degradation, reduced protein stability, or interference with the binding of other proteins. -
Genetic and Genomic Analysis of Hyperlipidemia, Obesity and Diabetes Using (C57BL/6J × TALLYHO/Jngj) F2 Mice
University of Tennessee, Knoxville TRACE: Tennessee Research and Creative Exchange Nutrition Publications and Other Works Nutrition 12-19-2010 Genetic and genomic analysis of hyperlipidemia, obesity and diabetes using (C57BL/6J × TALLYHO/JngJ) F2 mice Taryn P. Stewart Marshall University Hyoung Y. Kim University of Tennessee - Knoxville, [email protected] Arnold M. Saxton University of Tennessee - Knoxville, [email protected] Jung H. Kim Marshall University Follow this and additional works at: https://trace.tennessee.edu/utk_nutrpubs Part of the Animal Sciences Commons, and the Nutrition Commons Recommended Citation BMC Genomics 2010, 11:713 doi:10.1186/1471-2164-11-713 This Article is brought to you for free and open access by the Nutrition at TRACE: Tennessee Research and Creative Exchange. It has been accepted for inclusion in Nutrition Publications and Other Works by an authorized administrator of TRACE: Tennessee Research and Creative Exchange. For more information, please contact [email protected]. Stewart et al. BMC Genomics 2010, 11:713 http://www.biomedcentral.com/1471-2164/11/713 RESEARCH ARTICLE Open Access Genetic and genomic analysis of hyperlipidemia, obesity and diabetes using (C57BL/6J × TALLYHO/JngJ) F2 mice Taryn P Stewart1, Hyoung Yon Kim2, Arnold M Saxton3, Jung Han Kim1* Abstract Background: Type 2 diabetes (T2D) is the most common form of diabetes in humans and is closely associated with dyslipidemia and obesity that magnifies the mortality and morbidity related to T2D. The genetic contribution to human T2D and related metabolic disorders is evident, and mostly follows polygenic inheritance. The TALLYHO/ JngJ (TH) mice are a polygenic model for T2D characterized by obesity, hyperinsulinemia, impaired glucose uptake and tolerance, hyperlipidemia, and hyperglycemia. -
Aneuploidy: Using Genetic Instability to Preserve a Haploid Genome?
Health Science Campus FINAL APPROVAL OF DISSERTATION Doctor of Philosophy in Biomedical Science (Cancer Biology) Aneuploidy: Using genetic instability to preserve a haploid genome? Submitted by: Ramona Ramdath In partial fulfillment of the requirements for the degree of Doctor of Philosophy in Biomedical Science Examination Committee Signature/Date Major Advisor: David Allison, M.D., Ph.D. Academic James Trempe, Ph.D. Advisory Committee: David Giovanucci, Ph.D. Randall Ruch, Ph.D. Ronald Mellgren, Ph.D. Senior Associate Dean College of Graduate Studies Michael S. Bisesi, Ph.D. Date of Defense: April 10, 2009 Aneuploidy: Using genetic instability to preserve a haploid genome? Ramona Ramdath University of Toledo, Health Science Campus 2009 Dedication I dedicate this dissertation to my grandfather who died of lung cancer two years ago, but who always instilled in us the value and importance of education. And to my mom and sister, both of whom have been pillars of support and stimulating conversations. To my sister, Rehanna, especially- I hope this inspires you to achieve all that you want to in life, academically and otherwise. ii Acknowledgements As we go through these academic journeys, there are so many along the way that make an impact not only on our work, but on our lives as well, and I would like to say a heartfelt thank you to all of those people: My Committee members- Dr. James Trempe, Dr. David Giovanucchi, Dr. Ronald Mellgren and Dr. Randall Ruch for their guidance, suggestions, support and confidence in me. My major advisor- Dr. David Allison, for his constructive criticism and positive reinforcement. -
A Compendium of Co-Regulated Protein Complexes in Breast Cancer Reveals Collateral Loss Events
bioRxiv preprint doi: https://doi.org/10.1101/155333; this version posted June 26, 2017. 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 4.0 International license. A compendium of co-regulated protein complexes in breast cancer reveals collateral loss events Colm J. Ryan*1, Susan Kennedy1, Ilirjana Bajrami2, David Matallanas1, Christopher J. Lord2 1Systems Biology Ireland, School of Medicine, University College Dublin, Dublin 4, Ireland 2The Breast Cancer Now Toby Robins Breast Cancer Research Centre and CRUK Gene Function Laboratory, The Institute of Cancer Research, London, SW3 6JB, United Kingdom. * Correspondence: [email protected] Summary Protein complexes are responsible for the bulk of activities within the cell, but how their behavior and composition varies across tumors remains poorly understood. By combining proteomic profiles of breast tumors with a large-scale protein-protein interaction network, we have identified a set of 258 high-confidence protein complexes whose subunits have highly correlated protein abundance across tumor samples. We used this set to identify complexes that are reproducibly under- or over- expressed in specific breast cancer subtypes. We found that mutation or deletion of one subunit of a complex was often associated with a collateral reduction in protein expression of additional complex members. This collateral loss phenomenon was evident from proteomic, but not transcriptomic, profiles suggesting post- transcriptional control. Mutation of the tumor suppressor E-cadherin (CDH1) was associated with a collateral loss of members of the adherens junction complex, an effect we validated using an engineered model of E-cadherin loss. -
Cops5 Safeguards Genomic Stability of Embryonic Stem Cells Through Regulating Cellular Metabolism and DNA Repair
Cops5 safeguards genomic stability of embryonic stem cells through regulating cellular metabolism and DNA repair Peng Lia, Lulu Gaoa, Tongxi Cuia, Weiyu Zhanga, Zixin Zhaoa, and Lingyi Chena,1 aState Key Laboratory of Medicinal Chemical Biology, Collaborative Innovation Center of Tianjin for Medical Epigenetics, Collaborative Innovation Center for Biotherapy, Tianjin Key Laboratory of Protein Sciences, National Demonstration Center for Experimental Biology Education and College of Life Sciences, Nankai University, 300071 Tianjin, China Edited by Janet Rossant, Hospital for Sick Children, University of Toronto, Toronto, Canada, and approved December 24, 2019 (received for review August 29, 2019) The highly conserved COP9 signalosome (CSN), composed of 8 transiently expressed in about 5% of ESCs at a given time, subunits (Cops1 to Cops8), has been implicated in pluripotency promotes rapid telomere elongation by telomere recombination maintenance of human embryonic stem cells (ESCs). Yet, the mech- and regulates genomic stability (11). Induced by genotoxic stress, anism for the CSN to regulate pluripotency remains elusive. We Filia stimulates the PARP1 activity and relocates from centro- previously showed that Cops2, independent of the CSN, is essential somes to DNA damage sites and mitochondria to regulate DDR for the pluripotency maintenance of mouse ESCs. In this study, we and apoptosis (12). Sall4, a pluripotency transcription factor, set out to investigate how Cops5 and Cops8 regulate ESC differ- facilitates the ataxia telangiectasia-mutated activation in re- entiation and tried to establish Cops5 and Cops8 knockout (KO) sponse to DSBs (13). To minimize the ROS-induced genomic ESC lines by CRISPR/Cas9. To our surprise, no Cops5 KO ESC clones DNA damage, ESCs produce lower levels of mitochondrial ROS were identified out of 127 clones, while three Cops8 KO ESC lines and express higher levels of antioxidants than differentiated cells were established out of 70 clones. -
Viewed Graphically with a Java Graphical User Interface (GUI), Allowing Users to Evaluate Contig Sequence Quality and Predict Snps
BMC Research Notes BioMed Central Short Report Open Access BEAP: The BLAST Extension and Alignment Program- a tool for contig construction and analysis of preliminary genome sequence James E Koltes†, Zhi-Liang Hu†, Eric Fritz and James M Reecy* Address: Department of Animal Science, Iowa State University, Ames, Iowa 50011-3150, USA Email: James E Koltes - [email protected]; Zhi-Liang Hu - [email protected]; Eric Fritz - [email protected]; James M Reecy* - [email protected] * Corresponding author †Equal contributors Published: 22 January 2009 Received: 29 October 2008 Accepted: 22 January 2009 BMC Research Notes 2009, 2:11 doi:10.1186/1756-0500-2-11 This article is available from: http://www.biomedcentral.com/1756-0500/2/11 © 2009 Reecy 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: Fine-mapping projects require a high density of SNP markers and positional candidate gene sequences. In species with incomplete genomic sequence, the DNA sequences needed to generate markers for fine-mapping within a linkage analysis confidence interval may be available but may not have been assembled. To manually piece these sequences together is laborious and costly. Moreover, annotation and assembly of short, incomplete DNA sequences is time consuming and not always straightforward. Findings: We have created a tool called BEAP that combines BLAST and CAP3 to retrieve sequences and construct contigs for localized genomic regions in species with unfinished sequence drafts. -
Gene Co-Expression Network Mining Using Graph Sparsification
Gene Co-expression Network Mining Using Graph Sparsification THESIS Presented in Partial Fulfillment of the Requirements for the Degree Master of Science in the Graduate School of The Ohio State University By Jinchao Di Graduate Program in Electrical and Computer Engineering The Ohio State University 2013 Master’s Examination Committee: Dr. Kun Huang, Advisor Dr. Raghu Machiraju Dr. Yuejie Chi ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! Copyright by Jinchao Di 2013 ! ! Abstract Identifying and analyzing gene modules is important since it can help understand gene function globally and reveal the underlying molecular mechanism. In this thesis, we propose a method combining local graph sparsification and a gene similarity measurement method TOM. This method can detect gene modules from a weighted gene co-expression network more e↵ectively since we set a local threshold which can detect clusters with di↵erent densities. In our algorithm, we only retain one edge for each gene, which can generate more balanced gene clusters. To estimate the e↵ectiveness of our algorithm we use DAVID to functionally evaluate the gene list for each module we detect and compare our results with some well known algorithms. The result of our algorithm shows better biological relevance than the compared methods and the number of the meaningful biological clusters is much larger than other methods, implying we discover some previously missed gene clusters. Moreover, we carry out a robustness test by adding Gaussian noise with di↵erent variance to the expression data. We find that our algorithm is robust to noise. We also find that some hub genes considered as important genes could be artifacts.