PCGIMA: developing the web server for human position-defined CpG islands methylation analysis

被引:0
作者
Xiao, Ming [1 ,2 ]
Xiao, Yi [1 ]
Yu, Jun [3 ,4 ]
Zhang, Le [1 ,5 ,6 ]
机构
[1] Sichuan Univ, Coll Comp Sci, Chengdu, Peoples R China
[2] Tianfu Engn Oriented Numer Simulat & Software Inno, Chengdu, Peoples R China
[3] Chinese Acad Sci, CAS Key Lab Genome Sci & Informat, Beijing Inst Genom, Beijing, Peoples R China
[4] Univ Chinese Acad Sci, Beijing, Peoples R China
[5] Univ Chinese Acad Sci, Chinese Acad Sci, Key Lab Syst Biol, Hangzhou Inst Adv Study, Hangzhou, Peoples R China
[6] Univ Chinese Acad Sci, Hangzhou Inst Adv Study, Key Lab Syst Hlth Sci Zhejiang Prov, Hangzhou, Peoples R China
基金
中国国家自然科学基金; 中国博士后科学基金;
关键词
position-defined CGIs; DNA methylation; genome annotation; high performance computing; genome analysis; DNA METHYLATION; GENOME; DATABASE; SITES;
D O I
10.3389/fgene.2024.1367731
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
Introduction: CpG island (CGI) methylation is one of the key epigenomic mechanisms for gene expression regulation and chromosomal integrity. However, classical CGI prediction methods are neither easy to locate those short and position-sensitive CGIs (CpG islets), nor investigate genetic and expression pattern for CGIs under different CpG position- and interval- sensitive parameters in a genome-wide perspective. Therefore, it is urgent for us to develop such a bioinformatic algorithm that not only can locate CpG islets, but also provide CGI methylation site annotation and functional analysis to investigate the regulatory mechanisms for CGI methylation.Methods: This study develops Human position-defined CGI prediction method to locate CpG islets using high performance computing, and then builds up a novel human genome annotation and analysis method to investigate the connections among CGI, gene expression and methylation. Finally, we integrate these functions into PCGIMA to provide relevant online computing and visualization service.Results: The main results include: (1) Human position-defined CGI prediction method is more efficient to predict position-defined CGIs with multiple consecutive (d) values and locate more potential short CGIs than previous CGI prediction methods. (2) Our annotation and analysis method not only can investigate the connections between position-defined CGI methylation and gene expression specificity from a genome-wide perspective, but also can analysis the potential association of position-defined CGIs with gene functions. (3) PCGIMA (http://www.combio-lezhang.online/pcgima/home.html) provides an easy-to-use analysis and visualization platform for human CGI prediction and methylation.Discussion: This study not only develops Human position-defined CGI prediction method to locate short and position-sensitive CGIs (CpG islets) using high performance computing to construct MR-CpGCluster algorithm, but also a novel human genome annotation and analysis method to investigate the connections among CGI, gene expression and methylation. Finally, we integrate them into PCGIMA for online computing and visualization.
引用
收藏
页数:9
相关论文
共 51 条
  • [1] The genomic loci of specific human tRNA genes exhibit ageing-related DNA hypermethylation
    Acton, Richard J.
    Yuan, Wei
    Gao, Fei
    Xia, Yudong
    Bourne, Emma
    Wozniak, Eva
    Bell, Jordana
    Lillycrop, Karen
    Wang, Jun
    Dennison, Elaine
    Harvey, Nicholas
    Mein, Charles A.
    Spector, Tim D.
    Hysi, Pirro G.
    Cooper, Cyrus
    Bell, Christopher G.
    [J]. NATURE COMMUNICATIONS, 2021, 12 (01)
  • [2] CpG Island Chromatin Is Shaped by Recruitment of ZF-CxxC Proteins
    Blackledge, Neil P.
    Thomson, John P.
    Skene, Peter J.
    [J]. COLD SPRING HARBOR PERSPECTIVES IN BIOLOGY, 2013, 5 (11):
  • [3] CpG island mapping by epigenome prediction
    Bock, Christoph
    Walter, Joern
    Paulsen, Martina
    Lengauer, Thomas
    [J]. PLOS COMPUTATIONAL BIOLOGY, 2007, 3 (06) : 1055 - 1070
  • [4] Bond G.W., 2002, P 6 TH IASTED INT C, P149
  • [5] The UCSC Genome Browser database: 2018 update
    Casper, Jonathan
    Zweig, Ann S.
    Villarreal, Chris
    Tyner, Cath
    Speir, Matthew L.
    Rosenbloom, Kate R.
    Raney, Brian J.
    Lee, Christopher M.
    Lee, Brian T.
    Karolchik, Donna
    Hinrichs, Angie S.
    Haeussler, Maximilian
    Guruvadoo, Luvina
    Gonzalez, Jairo Navarro
    Gibson, David
    Fiddes, Ian T.
    Eisenhart, Christopher
    Diekhans, Mark
    Clawson, Hiram
    Barber, Galt P.
    Armstrong, Joel
    Haussler, David
    Kuhn, Robert M.
    Kent, W. James
    [J]. NUCLEIC ACIDS RESEARCH, 2018, 46 (D1) : D762 - D769
  • [6] GenBank
    Clark, Karen
    Karsch-Mizrachi, Ilene
    Lipman, David J.
    Ostell, James
    Sayers, Eric W.
    [J]. NUCLEIC ACIDS RESEARCH, 2016, 44 (D1) : D67 - D72
  • [7] Processing Cassandra Datasets with Hadoop-Streaming Based Approaches
    Dede, E.
    Sendir, B.
    Kuzlu, P.
    Weachock, J.
    Govindaraju, M.
    Ramakrishnan, L.
    [J]. IEEE TRANSACTIONS ON SERVICES COMPUTING, 2016, 9 (01) : 46 - 58
  • [8] Efficient Big Data Processing in Hadoop MapReduce
    Dittrich, Jens
    Quiane-Ruiz, Jorge-Arnulfo
    [J]. PROCEEDINGS OF THE VLDB ENDOWMENT, 2012, 5 (12): : 2014 - 2015
  • [9] Principles of DNA methylation and their implications for biology and medicine
    Dor, Yuval
    Cedar, Howard
    [J]. LANCET, 2018, 392 (10149) : 777 - 786
  • [10] Methylation levels at selected CpG sites in the factor VIII and FGFR3 genes, in mature female and male germ cells: Implications for male-driven evolution
    El-Maarri, O
    Olek, A
    Balaban, B
    Montag, M
    van der Ven, H
    Urman, B
    Olek, K
    Caglayan, SH
    Walter, J
    Oldenburg, J
    [J]. AMERICAN JOURNAL OF HUMAN GENETICS, 1998, 63 (04) : 1001 - 1008