Chapter 2 Gene Regulation and Speciation in House Mice
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Analyses of Inter-Individual Variations of Sperm DNA Methylation and Their Potential Implications in Cattle Shuli Liu1,2†, Lingzhao Fang2,3,4†, Yang Zhou5, Daniel J.A
Liu et al. BMC Genomics (2019) 20:888 https://doi.org/10.1186/s12864-019-6228-6 RESEARCH ARTICLE Open Access Analyses of inter-individual variations of sperm DNA methylation and their potential implications in cattle Shuli Liu1,2†, Lingzhao Fang2,3,4†, Yang Zhou5, Daniel J.A. Santos3, Ruidong Xiang6,7, Hans D. Daetwyler7,8, Amanda J. Chamberlain7, John B. Cole2, Cong-jun Li2, Ying Yu1,LiMa3, Shengli Zhang1* and George E. Liu2* Abstract Background: DNA methylation has been shown to be involved in many biological processes, including X chromosome inactivation in females, paternal genomic imprinting, and others. Results: Based on the correlation patterns of methylation levels of neighboring CpG sites among 28 sperm whole genome bisulfite sequencing (WGBS) data (486 × coverage), we obtained 31,272 methylation haplotype blocks (MHBs). Among them, we defined conserved methylated regions (CMRs), variably methylated regions (VMRs) and highly variably methylated regions (HVMRs) among individuals, and showed that HVMRs might play roles in transcriptional regulation and function in complex traits variation and adaptive evolution by integrating evidence from traditional and molecular quantitative trait loci (QTL), and selection signatures. Using a weighted correlation network analysis (WGCNA), we also detected a co-regulated module of HVMRs that was significantly associated with reproduction traits, and enriched for glycosyltransferase genes, which play critical roles in spermatogenesis and fertilization. Additionally, we identified 46 VMRs significantly associated with reproduction traits, nine of which were regulated by cis-SNPs, implying the possible intrinsic relationships among genomic variations, DNA methylation, and phenotypes. These significant VMRs were co-localized (± 10 kb) with genes related to sperm motility and reproduction, including ZFP36L1, CRISP2 and HGF. -
Gene Regulation and Speciation in House Mice
Downloaded from genome.cshlp.org on September 26, 2021 - Published by Cold Spring Harbor Laboratory Press Research Gene regulation and speciation in house mice Katya L. Mack,1 Polly Campbell,2 and Michael W. Nachman1 1Museum of Vertebrate Zoology and Department of Integrative Biology, University of California, Berkeley, California 94720-3160, USA; 2Department of Integrative Biology, Oklahoma State University, Stillwater, Oklahoma 74078, USA One approach to understanding the process of speciation is to characterize the genetic architecture of post-zygotic isolation. As gene regulation requires interactions between loci, negative epistatic interactions between divergent regulatory elements might underlie hybrid incompatibilities and contribute to reproductive isolation. Here, we take advantage of a cross between house mouse subspecies, where hybrid dysfunction is largely unidirectional, to test several key predictions about regulatory divergence and reproductive isolation. Regulatory divergence between Mus musculus musculus and M. m. domesticus was charac- terized by studying allele-specific expression in fertile hybrid males using mRNA-sequencing of whole testes. We found ex- tensive regulatory divergence between M. m. musculus and M. m. domesticus, largely attributable to cis-regulatory changes. When both cis and trans changes occurred, they were observed in opposition much more often than expected under a neutral model, providing strong evidence of widespread compensatory evolution. We also found evidence for lineage-specific positive se- lection on a subset of genes related to transcriptional regulation. Comparisons of fertile and sterile hybrid males identified a set of genes that were uniquely misexpressed in sterile individuals. Lastly, we discovered a nonrandom association between these genes and genes showing evidence of compensatory evolution, consistent with the idea that regulatory interactions might contribute to Dobzhansky-Muller incompatibilities and be important in speciation. -
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. -
Environmental Influences on Endothelial Gene Expression
ENDOTHELIAL CELL GENE EXPRESSION John Matthew Jeff Herbert Supervisors: Prof. Roy Bicknell and Dr. Victoria Heath PhD thesis University of Birmingham August 2012 University of Birmingham Research Archive e-theses repository This unpublished thesis/dissertation is copyright of the author and/or third parties. The intellectual property rights of the author or third parties in respect of this work are as defined by The Copyright Designs and Patents Act 1988 or as modified by any successor legislation. Any use made of information contained in this thesis/dissertation must be in accordance with that legislation and must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the permission of the copyright holder. ABSTRACT Tumour angiogenesis is a vital process in the pathology of tumour development and metastasis. Targeting markers of tumour endothelium provide a means of targeted destruction of a tumours oxygen and nutrient supply via destruction of tumour vasculature, which in turn ultimately leads to beneficial consequences to patients. Although current anti -angiogenic and vascular targeting strategies help patients, more potently in combination with chemo therapy, there is still a need for more tumour endothelial marker discoveries as current treatments have cardiovascular and other side effects. For the first time, the analyses of in-vivo biotinylation of an embryonic system is performed to obtain putative vascular targets. Also for the first time, deep sequencing is applied to freshly isolated tumour and normal endothelial cells from lung, colon and bladder tissues for the identification of pan-vascular-targets. Integration of the proteomic, deep sequencing, public cDNA libraries and microarrays, delivers 5,892 putative vascular targets to the science community. -
A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus
Page 1 of 781 Diabetes A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus Robert N. Bone1,6,7, Olufunmilola Oyebamiji2, Sayali Talware2, Sharmila Selvaraj2, Preethi Krishnan3,6, Farooq Syed1,6,7, Huanmei Wu2, Carmella Evans-Molina 1,3,4,5,6,7,8* Departments of 1Pediatrics, 3Medicine, 4Anatomy, Cell Biology & Physiology, 5Biochemistry & Molecular Biology, the 6Center for Diabetes & Metabolic Diseases, and the 7Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; 2Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202; 8Roudebush VA Medical Center, Indianapolis, IN 46202. *Corresponding Author(s): Carmella Evans-Molina, MD, PhD ([email protected]) Indiana University School of Medicine, 635 Barnhill Drive, MS 2031A, Indianapolis, IN 46202, Telephone: (317) 274-4145, Fax (317) 274-4107 Running Title: Golgi Stress Response in Diabetes Word Count: 4358 Number of Figures: 6 Keywords: Golgi apparatus stress, Islets, β cell, Type 1 diabetes, Type 2 diabetes 1 Diabetes Publish Ahead of Print, published online August 20, 2020 Diabetes Page 2 of 781 ABSTRACT The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray datasets generated using human islets from donors with diabetes and islets where type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated. -
Genomic Selection Signatures in Sheep from the Western Pyrenees Otsanda Ruiz-Larrañaga, Jorge Langa, Fernando Rendo, Carmen Manzano, Mikel Iriondo, Andone Estonba
Genomic selection signatures in sheep from the Western Pyrenees Otsanda Ruiz-Larrañaga, Jorge Langa, Fernando Rendo, Carmen Manzano, Mikel Iriondo, Andone Estonba To cite this version: Otsanda Ruiz-Larrañaga, Jorge Langa, Fernando Rendo, Carmen Manzano, Mikel Iriondo, et al.. Genomic selection signatures in sheep from the Western Pyrenees. Genetics Selection Evolution, BioMed Central, 2018, 50 (1), pp.9. 10.1186/s12711-018-0378-x. hal-02405217 HAL Id: hal-02405217 https://hal.archives-ouvertes.fr/hal-02405217 Submitted on 11 Dec 2019 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. Distributed under a Creative Commons Attribution| 4.0 International License Ruiz-Larrañaga et al. Genet Sel Evol (2018) 50:9 https://doi.org/10.1186/s12711-018-0378-x Genetics Selection Evolution RESEARCH ARTICLE Open Access Genomic selection signatures in sheep from the Western Pyrenees Otsanda Ruiz‑Larrañaga1* , Jorge Langa1, Fernando Rendo2, Carmen Manzano1, Mikel Iriondo1 and Andone Estonba1 Abstract Background: The current large spectrum of sheep phenotypic diversity -
Alterations of Genetic Variants and Transcriptomic Features of Response to Tamoxifen in the Breast Cancer Cell Line
Alterations of Genetic Variants and Transcriptomic Features of Response to Tamoxifen in the Breast Cancer Cell Line Mahnaz Nezamivand-Chegini Shiraz University Hamed Kharrati-Koopaee Shiraz University https://orcid.org/0000-0003-2345-6919 seyed taghi Heydari ( [email protected] ) Shiraz University of Medical Sciences https://orcid.org/0000-0001-7711-1137 Hasan Giahi Shiraz University Ali Dehshahri Shiraz University of Medical Sciences Mehdi Dianatpour Shiraz University of Medical Sciences Kamran Bagheri Lankarani Shiraz University of Medical Sciences Research Keywords: Tamoxifen, breast cancer, genetic variants, RNA-seq. Posted Date: August 17th, 2021 DOI: https://doi.org/10.21203/rs.3.rs-783422/v1 License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Page 1/33 Abstract Background Breast cancer is one of the most important causes of mortality in the world, and Tamoxifen therapy is known as a medication strategy for estrogen receptor-positive breast cancer. In current study, two hypotheses of Tamoxifen consumption in breast cancer cell line (MCF7) were investigated. First, the effect of Tamoxifen on genes expression prole at transcriptome level was evaluated between the control and treated samples. Second, due to the fact that Tamoxifen is known as a mutagenic factor, there may be an association between the alterations of genetic variants and Tamoxifen treatment, which can impact on the drug response. Methods In current study, the whole-transcriptome (RNA-seq) dataset of four investigations (19 samples) were derived from European Bioinformatics Institute (EBI). At transcriptome level, the effect of Tamoxifen was investigated on gene expression prole between control and treatment samples. -
1 Supporting Information for a Microrna Network Regulates
Supporting Information for A microRNA Network Regulates Expression and Biosynthesis of CFTR and CFTR-ΔF508 Shyam Ramachandrana,b, Philip H. Karpc, Peng Jiangc, Lynda S. Ostedgaardc, Amy E. Walza, John T. Fishere, Shaf Keshavjeeh, Kim A. Lennoxi, Ashley M. Jacobii, Scott D. Rosei, Mark A. Behlkei, Michael J. Welshb,c,d,g, Yi Xingb,c,f, Paul B. McCray Jr.a,b,c Author Affiliations: Department of Pediatricsa, Interdisciplinary Program in Geneticsb, Departments of Internal Medicinec, Molecular Physiology and Biophysicsd, Anatomy and Cell Biologye, Biomedical Engineeringf, Howard Hughes Medical Instituteg, Carver College of Medicine, University of Iowa, Iowa City, IA-52242 Division of Thoracic Surgeryh, Toronto General Hospital, University Health Network, University of Toronto, Toronto, Canada-M5G 2C4 Integrated DNA Technologiesi, Coralville, IA-52241 To whom correspondence should be addressed: Email: [email protected] (M.J.W.); yi- [email protected] (Y.X.); Email: [email protected] (P.B.M.) This PDF file includes: Materials and Methods References Fig. S1. miR-138 regulates SIN3A in a dose-dependent and site-specific manner. Fig. S2. miR-138 regulates endogenous SIN3A protein expression. Fig. S3. miR-138 regulates endogenous CFTR protein expression in Calu-3 cells. Fig. S4. miR-138 regulates endogenous CFTR protein expression in primary human airway epithelia. Fig. S5. miR-138 regulates CFTR expression in HeLa cells. Fig. S6. miR-138 regulates CFTR expression in HEK293T cells. Fig. S7. HeLa cells exhibit CFTR channel activity. Fig. S8. miR-138 improves CFTR processing. Fig. S9. miR-138 improves CFTR-ΔF508 processing. Fig. S10. SIN3A inhibition yields partial rescue of Cl- transport in CF epithelia. -
The Role of ARF Family Proteins and Their Regulators and Effectors in Cancer Progression: a Therapeutic Perspective
fcell-08-00217 April 17, 2020 Time: 19:19 # 1 REVIEW published: 21 April 2020 doi: 10.3389/fcell.2020.00217 The Role of ARF Family Proteins and Their Regulators and Effectors in Cancer Progression: A Therapeutic Perspective Cristina Casalou†, Andreia Ferreira† and Duarte C. Barral* CEDOC, NOVA Medical School, Faculdade de Ciências Médicas, Universidade NOVA de Lisboa, Lisbon, Portugal The Adenosine diphosphate-Ribosylation Factor (ARF) family belongs to the RAS superfamily of small GTPases and is involved in a wide variety of physiological processes, such as cell proliferation, motility and differentiation by regulating membrane Edited by: traffic and associating with the cytoskeleton. Like other members of the RAS Sunil Kumar Verma, superfamily, ARF family proteins are activated by Guanine nucleotide Exchange Factors Centre for Cellular & Molecular (GEFs) and inactivated by GTPase-Activating Proteins (GAPs). When active, they bind Biology (CCMB), India effectors, which mediate downstream functions. Several studies have reported that Reviewed by: Wei-Hsiung Yang, cancer cells are able to subvert membrane traffic regulators to enhance migration and Mercer University, United States invasion. Indeed, members of the ARF family, including ARF-Like (ARL) proteins have Ira Daar, National Cancer Institute (NCI), been implicated in tumorigenesis and progression of several types of cancer. Here, we United States review the role of ARF family members, their GEFs/GAPs and effectors in tumorigenesis *Correspondence: and cancer progression, highlighting the ones that can have a pro-oncogenic behavior Duarte C. Barral or function as tumor suppressors. Moreover, we propose possible mechanisms and [email protected] approaches to target these proteins, toward the development of novel therapeutic †These authors have contributed equally to this work strategies to impair tumor progression. -
Temporal Proteomic Analysis of HIV Infection Reveals Remodelling of The
1 1 Temporal proteomic analysis of HIV infection reveals 2 remodelling of the host phosphoproteome 3 by lentiviral Vif variants 4 5 Edward JD Greenwood 1,2,*, Nicholas J Matheson1,2,*, Kim Wals1, Dick JH van den Boomen1, 6 Robin Antrobus1, James C Williamson1, Paul J Lehner1,* 7 1. Cambridge Institute for Medical Research, Department of Medicine, University of 8 Cambridge, Cambridge, CB2 0XY, UK. 9 2. These authors contributed equally to this work. 10 *Correspondence: [email protected]; [email protected]; [email protected] 11 12 Abstract 13 Viruses manipulate host factors to enhance their replication and evade cellular restriction. 14 We used multiplex tandem mass tag (TMT)-based whole cell proteomics to perform a 15 comprehensive time course analysis of >6,500 viral and cellular proteins during HIV 16 infection. To enable specific functional predictions, we categorized cellular proteins regulated 17 by HIV according to their patterns of temporal expression. We focussed on proteins depleted 18 with similar kinetics to APOBEC3C, and found the viral accessory protein Vif to be 19 necessary and sufficient for CUL5-dependent proteasomal degradation of all members of the 20 B56 family of regulatory subunits of the key cellular phosphatase PP2A (PPP2R5A-E). 21 Quantitative phosphoproteomic analysis of HIV-infected cells confirmed Vif-dependent 22 hyperphosphorylation of >200 cellular proteins, particularly substrates of the aurora kinases. 23 The ability of Vif to target PPP2R5 subunits is found in primate and non-primate lentiviral 2 24 lineages, and remodeling of the cellular phosphoproteome is therefore a second ancient and 25 conserved Vif function. -
The Viral Oncoproteins Tax and HBZ Reprogram the Cellular Mrna Splicing Landscape
bioRxiv preprint doi: https://doi.org/10.1101/2021.01.18.427104; this version posted January 18, 2021. 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. The viral oncoproteins Tax and HBZ reprogram the cellular mRNA splicing landscape Charlotte Vandermeulen1,2,3, Tina O’Grady3, Bartimee Galvan3, Majid Cherkaoui1, Alice Desbuleux1,2,4,5, Georges Coppin1,2,4,5, Julien Olivet1,2,4,5, Lamya Ben Ameur6, Keisuke Kataoka7, Seishi Ogawa7, Marc Thiry8, Franck Mortreux6, Michael A. Calderwood2,4,5, David E. Hill2,4,5, Johan Van Weyenbergh9, Benoit Charloteaux2,4,5,10, Marc Vidal2,4*, Franck Dequiedt3*, and Jean-Claude Twizere1,2,11* 1Laboratory of Viral Interactomes, GIGA Institute, University of Liege, Liege, Belgium.2Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA, USA.3Laboratory of Gene Expression and Cancer, GIGA Institute, University of Liege, Liege, Belgium.4Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA, USA. 5Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, USA.6Laboratory of Biology and Modeling of the Cell, CNRS UMR 5239, INSERM U1210, University of Lyon, Lyon, France.7Department of Pathology and Tumor Biology, Kyoto University, Japan.8Unit of Cell and Tissue Biology, GIGA Institute, University of Liege, Liege, Belgium.9Laboratory of Clinical and Epidemiological Virology, Rega Institute for Medical Research, Department of Microbiology, Immunology and Transplantation, Catholic University of Leuven, Leuven, Belgium.10Department of Human Genetics, CHU of Liege, University of Liege, Liege, Belgium.11Lead Contact. *Correspondence: [email protected]; [email protected]; [email protected] bioRxiv preprint doi: https://doi.org/10.1101/2021.01.18.427104; this version posted January 18, 2021. -
Gene Ontology Functional Annotations and Pleiotropy
Network based analysis of genetic disease associations Sarah Gilman Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy under the Executive Committee of the Graduate School of Arts and Sciences COLUMBIA UNIVERSITY 2014 © 2013 Sarah Gilman All Rights Reserved ABSTRACT Network based analysis of genetic disease associations Sarah Gilman Despite extensive efforts and many promising early findings, genome-wide association studies have explained only a small fraction of the genetic factors contributing to common human diseases. There are many theories about where this “missing heritability” might lie, but increasingly the prevailing view is that common variants, the target of GWAS, are not solely responsible for susceptibility to common diseases and a substantial portion of human disease risk will be found among rare variants. Relatively new, such variants have not been subject to purifying selection, and therefore may be particularly pertinent for neuropsychiatric disorders and other diseases with greatly reduced fecundity. Recently, several researchers have made great progress towards uncovering the genetics behind autism and schizophrenia. By sequencing families, they have found hundreds of de novo variants occurring only in affected individuals, both large structural copy number variants and single nucleotide variants. Despite studying large cohorts there has been little recurrence among the genes implicated suggesting that many hundreds of genes may underlie these complex phenotypes. The question