 CpG Islands
"CpG Islands" is a descriptor in the National Library of Medicine's controlled vocabulary thesaurus,
MeSH (Medical Subject Headings). Descriptors are arranged in a hierarchical structure,
which enables searching at various levels of specificity.
Areas of increased density of the dinucleotide sequence cytosine--phosphate diester--guanine. They form stretches of DNA several hundred to several thousand base pairs long. In humans there are about 45,000 CpG islands, mostly found at the 5' ends of genes. They are unmethylated except for those on the inactive X chromosome and some associated with imprinted genes.
| Descriptor ID |
D018899
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| MeSH Number(s) |
G02.111.570.080.380.160 G05.360.080.380.160 G05.360.340.024.159
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| Concept/Terms |
CpG Islands- CpG Islands
- CpG Island
- Island, CpG
- Islands, CpG
- CpG-Rich Islands
- CpG Rich Islands
- CpG-Rich Island
- Island, CpG-Rich
- Islands, CpG-Rich
CpG Clusters- CpG Clusters
- Cluster, CpG
- Clusters, CpG
- CpG Cluster
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Below are MeSH descriptors whose meaning is more general than "CpG Islands".
Below are MeSH descriptors whose meaning is more specific than "CpG Islands".
This graph shows the total number of publications written about "CpG Islands" by people in this website by year, and whether "CpG Islands" was a major or minor topic of these publications.
To see the data from this visualization as text, click here.
| Year | Major Topic | Minor Topic | Total |
|---|
| 2002 | 0 | 1 | 1 | | 2003 | 0 | 1 | 1 | | 2004 | 0 | 1 | 1 | | 2005 | 0 | 1 | 1 | | 2009 | 0 | 1 | 1 | | 2011 | 0 | 1 | 1 | | 2012 | 0 | 2 | 2 | | 2013 | 0 | 3 | 3 | | 2014 | 0 | 4 | 4 | | 2015 | 1 | 4 | 5 | | 2016 | 2 | 2 | 4 | | 2017 | 0 | 3 | 3 | | 2018 | 1 | 1 | 2 | | 2019 | 1 | 2 | 3 | | 2020 | 0 | 1 | 1 |
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Below are the most recent publications written about "CpG Islands" by people in Profiles.
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Allum F, Grundberg E. Capturing functional epigenomes for insight into metabolic diseases. Mol Metab. 2020 08; 38:100936.
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Shao X, Hudson M, Colmegna I, Greenwood CMT, Fritzler MJ, Awadalla P, Pastinen T, Bernatsky S. Rheumatoid arthritis-relevant DNA methylation changes identified in ACPA-positive asymptomatic individuals using methylome capture sequencing. Clin Epigenetics. 2019 07 31; 11(1):110.
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Harutyunyan AS, Krug B, Chen H, Papillon-Cavanagh S, Zeinieh M, De Jay N, Deshmukh S, Chen CCL, Belle J, Mikael LG, Marchione DM, Li R, Nikbakht H, Hu B, Cagnone G, Cheung WA, Mohammadnia A, Bechet D, Faury D, McConechy MK, Pathania M, Jain SU, Ellezam B, Weil AG, Montpetit A, Salomoni P, Pastinen T, Lu C, Lewis PW, Garcia BA, Kleinman CL, Jabado N, Majewski J. H3K27M induces defective chromatin spread of PRC2-mediated repressive H3K27me2/me3 and is essential for glioma tumorigenesis. Nat Commun. 2019 03 19; 10(1):1262.
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Allum F, Hedman ÅK, Shao X, Cheung WA, Vijay J, Guénard F, Kwan T, Simon MM, Ge B, Moura C, Boulier E, Rönnblom L, Bernatsky S, Lathrop M, McCarthy MI, Deloukas P, Tchernof A, Pastinen T, Vohl MC, Grundberg E. Dissecting features of epigenetic variants underlying cardiometabolic risk using full-resolution epigenome profiling in regulatory elements. Nat Commun. 2019 03 14; 10(1):1209.
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Caron M, St-Onge P, Drouin S, Richer C, Sontag T, Busche S, Bourque G, Pastinen T, Sinnett D. Very long intergenic non-coding RNA transcripts and expression profiles are associated to specific childhood acute lymphoblastic leukemia subtypes. PLoS One. 2018; 13(11):e0207250.
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Shokoohi F, Stephens DA, Bourque G, Pastinen T, Greenwood CMT, Labbe A. A hidden markov model for identifying differentially methylated sites in bisulfite sequencing data. Biometrics. 2019 03; 75(1):210-221.
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Cheung WA, Shao X, Morin A, Siroux V, Kwan T, Ge B, Aïssi D, Chen L, Vasquez L, Allum F, Guénard F, Bouzigon E, Simon MM, Boulier E, Redensek A, Watt S, Datta A, Clarke L, Flicek P, Mead D, Paul DS, Beck S, Bourque G, Lathrop M, Tchernof A, Vohl MC, Demenais F, Pin I, Downes K, Stunnenberg HG, Soranzo N, Pastinen T, Grundberg E. Functional variation in allelic methylomes underscores a strong genetic contribution and reveals novel epigenetic alterations in the human epigenome. Genome Biol. 2017 03 10; 18(1):50.
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Ecker S, Chen L, Pancaldi V, Bagger FO, Fernández JM, Carrillo de Santa Pau E, Juan D, Mann AL, Watt S, Casale FP, Sidiropoulos N, Rapin N, Merkel A, Stunnenberg HG, Stegle O, Frontini M, Downes K, Pastinen T, Kuijpers TW, Rico D, Valencia A, Beck S, Soranzo N, Paul DS. Genome-wide analysis of differential transcriptional and epigenetic variability across human immune cell types. Genome Biol. 2017 01 26; 18(1):18.
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Morin A, Laviolette M, Pastinen T, Boulet LP, Laprise C. Combining omics data to identify genes associated with allergic rhinitis. Clin Epigenetics. 2017; 9:3.
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Paul DS, Teschendorff AE, Dang MA, Lowe R, Hawa MI, Ecker S, Beyan H, Cunningham S, Fouts AR, Ramelius A, Burden F, Farrow S, Rowlston S, Rehnstrom K, Frontini M, Downes K, Busche S, Cheung WA, Ge B, Simon MM, Bujold D, Kwan T, Bourque G, Datta A, Lowy E, Clarke L, Flicek P, Libertini E, Heath S, Gut M, Gut IG, Ouwehand WH, Pastinen T, Soranzo N, Hofer SE, Karges B, Meissner T, Boehm BO, Cilio C, Elding Larsson H, Lernmark Å, Steck AK, Rakyan VK, Beck S, Leslie RD. Increased DNA methylation variability in type 1 diabetes across three immune effector cell types. Nat Commun. 2016 11 29; 7:13555.
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