DOCSLIB.ORG

Modeling Gene Regulation from Paired Expression and Chromatin Accessibility Data

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Modeling Gene Regulation from Paired Expression and Chromatin Accessibility Data Modeling gene regulation from paired expression and chromatin accessibility data Zhana Durena,b,c, Xi Chenb, Rui Jiangd,1, Yong Wanga,c,1, and Wing Hung Wongb,1 aAcademy of Mathematics and Systems Science, National Center for Mathematics and Interdisciplinary Sciences, Chinese Academy of Sciences, Beijing 100080, China; bDepartment of Statistics, Department of Biomedical Data Science, Bio-X Program, Stanford University, Stanford, CA 94305; cSchool of Mathematical Sciences, University of Chinese Academy of Sciences, Beijing 100049, China; and dMinistry of Education Key Laboratory of Bioinformatics, Bioinformatics Division and Center for Synthetic & Systems Biology, Tsinghua National Laboratory for Information Science and Technology, Department of Automation, Tsinghua University, Beijing 100084, China Contributed by Wing Hung Wong, May 8, 2017 (sent for review March 20, 2017; reviewed by Christina Kendziorski and Sheng Zhong) The rapid increase of genome-wide datasets on gene expression, gene expression data, accessibility data are available for a diverse set chromatin states, and transcription factor (TF) binding locations offers of cellular contexts (Fig. 1, blue boxes). In fact, we expect the an exciting opportunity to interpret the information encoded in amount of matched expression and accessibility data (i.e., measured genomes and epigenomes. This task can be challenging as it requires on the same sample) will increase very rapidly in the near future. joint modeling of context-specific activation of cis-regulatory ele- The purpose of the present work is to show that, by using ments (REs) and the effects on transcription of associated regulatory matched expression and accessibility data across diverse cellular factors. To meet this challenge, we propose a statistical approach contexts, it is possible to recover a significant portion of the in- based on paired expression and chromatin accessibility (PECA) data formation in the missing data on binding location and chromatin across diverse cellular contexts. In our approach, we model (i)the state and to achieve accurate inference of the gene regulatory localization to REs of chromatin regulators (CRs) based on their in- relations. In our approach, key events in the regulatory process, teraction with sequence-specific TFs, (ii) the activation of REs due to such as recruitment of chromatin remodeling factors to a regu- CRs that are localized to them, and (iii) the effect of TFs bound to latory element, activation of regulatory elements, etc., are activated REs on the transcription of target genes (TGs). The transcrip- regarded as latent unobserved variables in a statistical model that tional regulatory network inferred by PECA provides a detailed view describes the relations among these variables and the gene ex- trans cis of how -and -regulatory elements work together to affect pression variables, conditional on accessibility data on the regula- gene expression in a context-specific manner. We illustrate the fea- tory elements. By fitting this model to expression and accessibility sibility of this approach by analyzing paired expression and accessi- data across a large number of cellular contexts, we can infer many bility data from the mouse Encyclopedia of DNA Elements (ENCODE) details of the gene regulatory system helpful in the interpretation of and explore various applications of the resulting model. new data or the generation of new hypotheses. We end this Introduction with comments on related works. gene regulation | transcription factor | regulatory element | Several methods have recently been proposed to detect tran- chromatin regulator | chromatin activity scription factor (TF) binding sites by “footprinting” in which the presence of a bound TF is reflected by the shape of the DNase- ver since the emergence of high-throughput gene expression seq (or ATAC-seq) profile around its binding site (6–8). These Eexperiments (1), computational biologists have been inter- works focus on the effect of TF binding on the frequency of ested in the inference of gene regulatory relationships from gene cleavage near the site and do not attempt to model gene regulatory expression data across diverse cellular contexts corresponding to diverse cell types and experimental conditions (Fig. 1, red boxes). Significance However, progress has been hindered by the fact that gene expres- sion measurements provide little information on underlying regula- tory mechanisms such as transcription factor binding and chromatin Chromatin plays a critical role in the regulation of gene ex- modification. To fill this gap, chromatin immunoprecipitation- pression. Interactions among chromatin regulators, sequence- based methods (2, 3) have been developed for the genome-wide specific transcription factors, and cis-regulatory sequence ele- mapping of transcriptional regulator binding locations and the ments are the main driving forces shaping context-specific detection of epigenetic marks characteristic of specific chromatin chromatin structure and gene expression. However, because states. For example, by performing thousands of ChIP-seq exper- of the large number of such interactions, direct data on them iments, the Encyclopedia of DNA Elements (ENCODE) consor- are often missing in most cellular contexts. The purpose of the tium has generated such data for many chromatin marks and present work is to show that, by modeling matched expression transcriptional regulators on a small number of cell lines (Fig. 1, and accessibility data across diverse cellular contexts, it is green boxes). However, because a large number of transcriptional possible to recover a significant portion of the information in regulators and chromatin marks have to be analyzed one by one, it the missing data on binding locations and chromatin states and is unlikely that such comprehensive data will become available for to achieve accurate inference of gene regulatory relations. many other cell lines. For most cellular contexts, the desired data will remain missing in the foreseeable future (Fig. 1, gray boxes). Author contributions: R.J., Y.W., and W.H.W. designed research; Z.D. and X.C. performed – research; Z.D., R.J., Y.W., and W.H.W. analyzed data; and Z.D., R.J., Y.W., and W.H.W. On the other hand, it is known that many of the protein DNA wrote the paper. interactions important for gene regulation occur in regulatory Reviewers: C.K., University of Wisconsin; and S.Z., University of California, San Diego. elements (REs) such as enhancers and insulators, which com- The authors declare no conflict of interest. pose only a small portion of the noncoding sequences in a ge- nome. The REs active in gene regulation in a given cellular state Freely available online through the PNAS open access option. tend to have an open chromatin structure so that they are ac- Data deposition: The sequence data reported in this paper have been deposited in the Gene Expression Omnibus (GEO) database, https://www.ncbi.nlm.nih.gov/geo (accession cessible for binding by relevant transcriptional regulators. This no. GSE98479). suggests that many of the relevant regulatory relations may be 1To whom correspondence may be addressed. Email: [email protected], ruijiang@ revealed by analyzing the accessible REs. Fortunately, genome-wide tsinghua.edu.cn, or [email protected]. measurement of chromatin accessibility is now straightforward by This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10. recent methods such as DNase-seq (4) or ATAC-seq (5). Similar to 1073/pnas.1704553114/-/DCSupplemental. E4914–E4923 | PNAS | Published online June 2, 2017 www.pnas.org/cgi/doi/10.1073/pnas.1704553114 Downloaded by guest on September 28, 2021 PNAS PLUS ChIP-seq Biological RNA-seq DNase-seq Ctcf Zmiz1 Bhlhe40 Cebpb Chd1 Chd2 Ep300 Fli1 Gabpa Gata1 Gata2 Hcfc1 Jund Mafk Maz Myb Myod1 Myog Pax5 Rad21 Rdbp Sin3a Srf Tbp Tcf12 Ubtf Usf1 Usf2 Zc3h11a Zkscan1 Znf384 Fosl1 Kat2a Max Polr2a Smc3 system Cell types ENCODE sample ID E2f4 Ets1 Jun Mxi1 Myc Rcor1 Rest Tal1 Tcf3 Muscular SkMuscle SkmuscleC57bl6MAdult8wks Circulatory G1E-ER4 G1eer4S129ME0Diffd24h G1 E G1eS12 9ME0 Cerebrum CerebrumC57bl6MAdult8wks Nervous Cerebellum CerebellumC57bl6MAdult8wks WholeBrain WbrainC57bl6ME18half Respiratory Lung LungC57bl6MAdult8wks NIH-3T3 Nih3t3NihsMImmortal LgIntestine LgintC57bl6MAdult8wks Liver liver129dlcrME14half Digestive Liver LiverC57bl6MAdult8wks Liver LiverC57bl6ME14half Excretory Kidney KidneyC57bl6MAdult8wks Endocrine FatPad FatC57bl6MAdult8wks GenitalFatPad GfatC57bl6MAdult8wks 416B 416bC57bl6MAdult8wks A20 A20BalbcannMAdult8wks B-cell(CD19+) Bcellcd19pC57bl6MAdult8wks B-cell(CD43-) Bcellcd43nC57bl6MAdult8wks MEL MelC57bl6MAdult8wks Spleen SpleenC57bl6MAdult8wks Lymphatic Thymus ThymusC57bl6MAdult8wks T-Naïve TnaiveC57bl6MAdult8wks Fig. 1. Genome-wide data for gene-regulatory inference. Each row represents a particular cellular context under which multiple types of genome-wide data may be available. In this paper we illustrate our method by analyzing data from 25 contexts studied in the mouse ENCODE project covering a variety of mouse cell types and developmental stages. Expression data (from RNA-seq, red boxes) and chromatin accessibility data (from DNase-seq or ATAC-seq, blue boxes) are available for each context, but most of the location data (from ChIP-seq data, green boxes) for transcriptional regulators are missing. We expect that the number of contexts (i.e., number of rows) with expression and accessibility data will increase rapidly in the
Load more

Recommended publications
  • Genetic Mutation Analysis of High and Low Igy Chickens by Capture Sequencing
    animals Article Genetic Mutation Analysis of High and Low IgY Chickens by Capture Sequencing 1,2, 1,2, 1,3 1,2 1,2 1,2 Qiao Wang y , Fei Wang y, Lu Liu , Qinghe Li , Ranran Liu , Maiqing Zheng , Huanxian Cui 1,2, Jie Wen 1,2 and Guiping Zhao 1,2,4,* 1 Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China; [email protected] (Q.W.); [email protected] (F.W.); [email protected] (L.L.); [email protected] (Q.L.); [email protected] (R.L.); [email protected] (M.Z.); [email protected] (H.C.); [email protected] (J.W.) 2 State Key Laboratory of Animal Nutrition, Beijing 100193, China 3 College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China 4 School of Life Science and Engineering, Foshan University, Foshan 528225, China * Correspondence: [email protected] These authors contributed equally to this work. y Received: 6 March 2019; Accepted: 20 May 2019; Published: 23 May 2019 Simple Summary: Immunoglobulin Y (IgY) is the major antibody produced by hens and it endows their offspring with effective humoral immunity against the pathogens. In previous research, we identified 13 genomic regions that were significantly associated with the serum IgY level or antibody responses to sheep red-blood-cells, but the specific mutations in these regions have not been reported. Therefore, we screened for variations in these regions in White Leghorn and Beijing-You chickens with high and low IgY. Our study identified 35,154 mutations and 829 Indels which were associated with IgY levels in both lines.
    [Show full text]
  • In Silico Prediction of High-Resolution Hi-C Interaction Matrices
    ARTICLE https://doi.org/10.1038/s41467-019-13423-8 OPEN In silico prediction of high-resolution Hi-C interaction matrices Shilu Zhang1, Deborah Chasman 1, Sara Knaack1 & Sushmita Roy1,2* The three-dimensional (3D) organization of the genome plays an important role in gene regulation bringing distal sequence elements in 3D proximity to genes hundreds of kilobases away. Hi-C is a powerful genome-wide technique to study 3D genome organization. Owing to 1234567890():,; experimental costs, high resolution Hi-C datasets are limited to a few cell lines. Computa- tional prediction of Hi-C counts can offer a scalable and inexpensive approach to examine 3D genome organization across multiple cellular contexts. Here we present HiC-Reg, an approach to predict contact counts from one-dimensional regulatory signals. HiC-Reg pre- dictions identify topologically associating domains and significant interactions that are enri- ched for CCCTC-binding factor (CTCF) bidirectional motifs and interactions identified from complementary sources. CTCF and chromatin marks, especially repressive and elongation marks, are most important for HiC-Reg’s predictive performance. Taken together, HiC-Reg provides a powerful framework to generate high-resolution profiles of contact counts that can be used to study individual locus level interactions and higher-order organizational units of the genome. 1 Wisconsin Institute for Discovery, 330 North Orchard Street, Madison, WI 53715, USA. 2 Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53715, USA. *email: [email protected] NATURE COMMUNICATIONS | (2019) 10:5449 | https://doi.org/10.1038/s41467-019-13423-8 | www.nature.com/naturecommunications 1 ARTICLE NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-019-13423-8 he three-dimensional (3D) organization of the genome has Results Temerged as an important component of the gene regulation HiC-Reg for predicting contact count using Random Forests.
    [Show full text]
  • File Download
    The genetic dissection of Myo7a gene expression in the retinas of BXD mice Ye Lu, Zhejiang University Diana Zhou, University of Tennessee Rebeccca King, Emory University Shuang Zhu, University of Texas Medical Branch Claire L. Simpson, University of Tennessee Byron C. Jones, University of Tennessee Wenbo Zhang, University of Texas Medical Branch Eldon Geisert Jr, Emory University Lu Lu, University of Tennessee Journal Title: Molecular Vision Volume: Volume 24 Publisher: Molecular Vision | 2018-02-03, Pages 115-126 Type of Work: Article | Final Publisher PDF Permanent URL: https://pid.emory.edu/ark:/25593/s87np Final published version: http://www.molvis.org/molvis/ Copyright information: © 2018 Molecular Vision. This is an Open Access work distributed under the terms of the Creative Commons Attribution-NonCommerical-NoDerivs 3.0 Unported License (http://creativecommons.org/licenses/by-nc-nd/3.0/). Accessed September 30, 2021 2:32 AM EDT Molecular Vision 2018; 24:115-126 <http://www.molvis.org/molvis/v24/115> © 2018 Molecular Vision Received 7 June 2017 | Accepted 1 February 2018 | Published 3 February 2018 The genetic dissection of Myo7a gene expression in the retinas of BXD mice Ye Lu,1 Diana Zhou,2 Rebecca King,3 Shuang Zhu,4 Claire L. Simpson,2 Byron C. Jones,2 Wenbo Zhang,4 Eldon E. Geisert,3 Lu Lu2 (The first two authors contributed equally to this work.) 1Department of Ophthalmology, The First Affiliated Hospital, Zhejiang University College of Medicine, Hangzhou, China; 2Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN; 3Department of Ophthalmology and Emory Eye Center, Emory University, Atlanta, GA; 4Department of Ophthalmology & Visual Sciences, University of Texas Medical Branch, Galveston, TX Purpose: Usher syndrome (US) is characterized by a loss of vision due to retinitis pigmentosa (RP) and deafness.
    [Show full text]
  • Biomarker Discovery for Chronic Liver Diseases by Multi-Omics
    www.nature.com/scientificreports OPEN Biomarker discovery for chronic liver diseases by multi-omics – a preclinical case study Daniel Veyel1, Kathrin Wenger1, Andre Broermann2, Tom Bretschneider1, Andreas H. Luippold1, Bartlomiej Krawczyk1, Wolfgang Rist 1* & Eric Simon3* Nonalcoholic steatohepatitis (NASH) is a major cause of liver fbrosis with increasing prevalence worldwide. Currently there are no approved drugs available. The development of new therapies is difcult as diagnosis and staging requires biopsies. Consequently, predictive plasma biomarkers would be useful for drug development. Here we present a multi-omics approach to characterize the molecular pathophysiology and to identify new plasma biomarkers in a choline-defcient L-amino acid-defned diet rat NASH model. We analyzed liver samples by RNA-Seq and proteomics, revealing disease relevant signatures and a high correlation between mRNA and protein changes. Comparison to human data showed an overlap of infammatory, metabolic, and developmental pathways. Using proteomics analysis of plasma we identifed mainly secreted proteins that correlate with liver RNA and protein levels. We developed a multi-dimensional attribute ranking approach integrating multi-omics data with liver histology and prior knowledge uncovering known human markers, but also novel candidates. Using regression analysis, we show that the top-ranked markers were highly predictive for fbrosis in our model and hence can serve as preclinical plasma biomarkers. Our approach presented here illustrates the power of multi-omics analyses combined with plasma proteomics and is readily applicable to human biomarker discovery. Nonalcoholic fatty liver disease (NAFLD) is the major liver disease in western countries and is ofen associated with obesity, metabolic syndrome, or type 2 diabetes.
    [Show full text]
  • AKAP8L Rabbit Polyclonal Antibody – TA329433 | Origene
    OriGene Technologies, Inc. 9620 Medical Center Drive, Ste 200 Rockville, MD 20850, US Phone: +1-888-267-4436 [email protected] EU: [email protected] CN: [email protected] Product datasheet for TA329433 AKAP8L Rabbit Polyclonal Antibody Product data: Product Type: Primary Antibodies Applications: WB Recommended Dilution: WB Reactivity: Human Host: Rabbit Isotype: IgG Clonality: Polyclonal Immunogen: The immunogen for Anti-AKAP8L antibody is: synthetic peptide directed towards the C- terminal region of Human AKAP8L. Synthetic peptide located within the following region: NNKLISKKLERYLKGENPFTDSPEEEKEQEEAEGGALDEGAQGEAAGISE Formulation: Liquid. Purified antibody supplied in 1x PBS buffer with 0.09% (w/v) sodium azide and 2% sucrose. Note that this product is shipped as lyophilized powder to China customers. Purification: Affinity Purified Conjugation: Unconjugated Storage: Store at -20°C as received. Stability: Stable for 12 months from date of receipt. Predicted Protein Size: 64 kDa Gene Name: A-kinase anchoring protein 8 like Database Link: NP_055186 Entrez Gene 26993 Human Q9ULX6 Background: AKAP8L could play a role in constitutive transport element (CTE)-mediated gene expression. It does not seem to be implicated in the binding of regulatory subunit II of PKA. It may be involved in nuclear envelope breakdown and chromatin condensation. It may regulate the initiation phase of DNA replication when associated with TMPO-beta. Synonyms: HA95; HAP95; NAKAP; NAKAP95 This product is to be used for laboratory only. Not for diagnostic
    [Show full text]
  • Loss-Of-Function Mutation in the Dioxygenase-Encoding FTO Gene
    Loss-of-Function Mutation in the Dioxygenase-Encoding FTO Gene Causes Severe Growth Retardation and Multiple Malformations Sarah Boissel, Orit Reish, Karine Proulx, Hiroko Kawagoe-Takaki, Barbara Sedgwick, Giles Yeo, David Meyre, Christelle Golzio, Florence Molinari, Noman Kadhom, et al. To cite this version: Sarah Boissel, Orit Reish, Karine Proulx, Hiroko Kawagoe-Takaki, Barbara Sedgwick, et al.. Loss-of- Function Mutation in the Dioxygenase-Encoding FTO Gene Causes Severe Growth Retardation and Multiple Malformations. American Journal of Human Genetics, Elsevier (Cell Press), 2009, 85 (1), pp.106-111. 10.1016/j.ajhg.2009.06.002. hal-02044723 HAL Id: hal-02044723 https://hal.archives-ouvertes.fr/hal-02044723 Submitted on 21 Feb 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. REPORT Loss-of-Function Mutation in the Dioxygenase-Encoding FTO Gene Causes Severe Growth Retardation and Multiple Malformations Sarah Boissel,1,7 Orit Reish,2,7 Karine Proulx,3,7 Hiroko Kawagoe-Takaki,4 Barbara Sedgwick,4 Giles S.H. Yeo,3 David Meyre,5 Christelle Golzio,1 Florence Molinari,1 Noman Kadhom,1 Heather C. Etchevers,1 Vladimir Saudek,3 I. Sadaf Farooqi,3 Philippe Froguel,5,6 Tomas Lindahl,4 Stephen O’Rahilly,3 Arnold Munnich,1 and Laurence Colleaux1,* FTO is a nuclear protein belonging to the AlkB-related non-haem iron- and 2-oxoglutarate-dependent dioxygenase family.
    [Show full text]
  • 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.
    [Show full text]
  • A Curated Benchmark of Enhancer-Gene Interactions for Evaluating Enhancer-Target Gene Prediction Methods
    University of Massachusetts Medical School eScholarship@UMMS Open Access Articles Open Access Publications by UMMS Authors 2020-01-22 A curated benchmark of enhancer-gene interactions for evaluating enhancer-target gene prediction methods Jill E. Moore University of Massachusetts Medical School Et al. Let us know how access to this document benefits ou.y Follow this and additional works at: https://escholarship.umassmed.edu/oapubs Part of the Bioinformatics Commons, Computational Biology Commons, Genetic Phenomena Commons, and the Genomics Commons Repository Citation Moore JE, Pratt HE, Purcaro MJ, Weng Z. (2020). A curated benchmark of enhancer-gene interactions for evaluating enhancer-target gene prediction methods. Open Access Articles. https://doi.org/10.1186/ s13059-019-1924-8. Retrieved from https://escholarship.umassmed.edu/oapubs/4118 Creative Commons License This work is licensed under a Creative Commons Attribution 4.0 License. This material is brought to you by eScholarship@UMMS. It has been accepted for inclusion in Open Access Articles by an authorized administrator of eScholarship@UMMS. For more information, please contact [email protected]. Moore et al. Genome Biology (2020) 21:17 https://doi.org/10.1186/s13059-019-1924-8 RESEARCH Open Access A curated benchmark of enhancer-gene interactions for evaluating enhancer-target gene prediction methods Jill E. Moore, Henry E. Pratt, Michael J. Purcaro and Zhiping Weng* Abstract Background: Many genome-wide collections of candidate cis-regulatory elements (cCREs) have been defined using genomic and epigenomic data, but it remains a major challenge to connect these elements to their target genes. Results: To facilitate the development of computational methods for predicting target genes, we develop a Benchmark of candidate Enhancer-Gene Interactions (BENGI) by integrating the recently developed Registry of cCREs with experimentally derived genomic interactions.
    [Show full text]
  • Integrating Single-Step GWAS and Bipartite Networks Reconstruction Provides Novel Insights Into Yearling Weight and Carcass Traits in Hanwoo Beef Cattle
    animals Article Integrating Single-Step GWAS and Bipartite Networks Reconstruction Provides Novel Insights into Yearling Weight and Carcass Traits in Hanwoo Beef Cattle Masoumeh Naserkheil 1 , Abolfazl Bahrami 1 , Deukhwan Lee 2,* and Hossein Mehrban 3 1 Department of Animal Science, University College of Agriculture and Natural Resources, University of Tehran, Karaj 77871-31587, Iran; [email protected] (M.N.); [email protected] (A.B.) 2 Department of Animal Life and Environment Sciences, Hankyong National University, Jungang-ro 327, Anseong-si, Gyeonggi-do 17579, Korea 3 Department of Animal Science, Shahrekord University, Shahrekord 88186-34141, Iran; [email protected] * Correspondence: [email protected]; Tel.: +82-31-670-5091 Received: 25 August 2020; Accepted: 6 October 2020; Published: 9 October 2020 Simple Summary: Hanwoo is an indigenous cattle breed in Korea and popular for meat production owing to its rapid growth and high-quality meat. Its yearling weight and carcass traits (backfat thickness, carcass weight, eye muscle area, and marbling score) are economically important for the selection of young and proven bulls. In recent decades, the advent of high throughput genotyping technologies has made it possible to perform genome-wide association studies (GWAS) for the detection of genomic regions associated with traits of economic interest in different species. In this study, we conducted a weighted single-step genome-wide association study which combines all genotypes, phenotypes and pedigree data in one step (ssGBLUP). It allows for the use of all SNPs simultaneously along with all phenotypes from genotyped and ungenotyped animals. Our results revealed 33 relevant genomic regions related to the traits of interest.
    [Show full text]
  • Physical and Linkage Mapping of Mammary-Derived Expressed Sequence Tags in Cattle
    Genomics 83 (2004) 148–152 www.elsevier.com/locate/ygeno Physical and linkage mapping of mammary-derived expressed sequence tags in cattle E.E. Connor,a,* T.S. Sonstegard,a J.W. Keele,b G.L. Bennett,b J.L. Williams,c R. Papworth,c C.P. Van Tassell,a and M.S. Ashwella a U.S. Beltsville Agricultural Research Center, ARS, U.S. Department of Agriculture, 10300 Baltimore Avenue, Beltsville, MD 20705, USA b U.S. Meat Animal Research Center, ARS, U.S. Department of Agriculture, P.O. Box 166, Clay Center, NE 68933-0166, USA c Roslin Institute (Edinburgh), Roslin, Midlothian EH25 9PS, Scotland, United Kingdom Received 2 June 2003; accepted 5 July 2003 Abstract This study describes the physical and linkage mapping of 42 gene-associated markers developed from mammary gland-derived expressed sequence tags to the cattle genome. Of the markers, 25 were placed on the USDA reference linkage map and 37 were positioned on the Roslin 3000-rad radiation hybrid (RH) map, with 20 assignments shared between the maps. Although no novel regions of conserved synteny between the cattle and the human genomes were identified, the coverage was extended for bovine chromosomes 3, 7, 15, and 29 compared with previously published comparative maps between human and bovine genomes. Overall, these data improve the resolution of the human–bovine comparative maps and will assist future efforts to integrate bovine RH and linkage map data. Crown Copyright D 2003 Published by Elsevier Inc. All rights reserved. Keywords: RH mapping; Linkage mapping; SNP; Cattle; EST Selection of positional candidate genes controlling eco- pig [4,5], and cattle [6], and serve as a resource for nomically important traits in cattle requires a detailed candidate gene identification.
    [Show full text]
  • Investigation of the Underlying Hub Genes and Molexular Pathogensis in Gastric Cancer by Integrated Bioinformatic Analyses
    bioRxiv preprint doi: https://doi.org/10.1101/2020.12.20.423656; this version posted December 22, 2020. 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. Investigation of the underlying hub genes and molexular pathogensis in gastric cancer by integrated bioinformatic analyses Basavaraj Vastrad1, Chanabasayya Vastrad*2 1. Department of Biochemistry, Basaveshwar College of Pharmacy, Gadag, Karnataka 582103, India. 2. Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karanataka, India. * Chanabasayya Vastrad [email protected] Ph: +919480073398 Chanabasava Nilaya, Bharthinagar, Dharwad 580001 , Karanataka, India bioRxiv preprint doi: https://doi.org/10.1101/2020.12.20.423656; this version posted December 22, 2020. 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 The high mortality rate of gastric cancer (GC) is in part due to the absence of initial disclosure of its biomarkers. The recognition of important genes associated in GC is therefore recommended to advance clinical prognosis, diagnosis and and treatment outcomes. The current investigation used the microarray dataset GSE113255 RNA seq data from the Gene Expression Omnibus database to diagnose differentially expressed genes (DEGs). Pathway and gene ontology enrichment analyses were performed, and a proteinprotein interaction network, modules, target genes - miRNA regulatory network and target genes - TF regulatory network were constructed and analyzed. Finally, validation of hub genes was performed. The 1008 DEGs identified consisted of 505 up regulated genes and 503 down regulated genes.
    [Show full text]
  • Mitoxplorer, a Visual Data Mining Platform To
    mitoXplorer, a visual data mining platform to systematically analyze and visualize mitochondrial expression dynamics and mutations Annie Yim, Prasanna Koti, Adrien Bonnard, Fabio Marchiano, Milena Dürrbaum, Cecilia Garcia-Perez, José Villaveces, Salma Gamal, Giovanni Cardone, Fabiana Perocchi, et al. To cite this version: Annie Yim, Prasanna Koti, Adrien Bonnard, Fabio Marchiano, Milena Dürrbaum, et al.. mitoXplorer, a visual data mining platform to systematically analyze and visualize mitochondrial expression dy- namics and mutations. Nucleic Acids Research, Oxford University Press, 2020, 10.1093/nar/gkz1128. hal-02394433 HAL Id: hal-02394433 https://hal-amu.archives-ouvertes.fr/hal-02394433 Submitted on 4 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 Nucleic Acids Research, 2019 1 doi: 10.1093/nar/gkz1128 Downloaded from https://academic.oup.com/nar/advance-article-abstract/doi/10.1093/nar/gkz1128/5651332 by Bibliothèque de l'université la Méditerranée user on 04 December 2019 mitoXplorer, a visual data mining platform to systematically analyze and visualize mitochondrial expression dynamics and mutations Annie Yim1,†, Prasanna Koti1,†, Adrien Bonnard2, Fabio Marchiano3, Milena Durrbaum¨ 1, Cecilia Garcia-Perez4, Jose Villaveces1, Salma Gamal1, Giovanni Cardone1, Fabiana Perocchi4, Zuzana Storchova1,5 and Bianca H.
    [Show full text]