Literature DB >> 20212320

Redefining CpG islands using hidden Markov models.

Hao Wu1, Brian Caffo, Harris A Jaffee, Rafael A Irizarry, Andrew P Feinberg.   

Abstract

The DNA of most vertebrates is depleted in CpG dinucleotide: a C followed by a G in the 5' to 3' direction. CpGs are the target for DNA methylation, a chemical modification of cytosine (C) heritable during cell division and the most well-characterized epigenetic mechanism. The remaining CpGs tend to cluster in regions referred to as CpG islands (CGI). Knowing CGI locations is important because they mark functionally relevant epigenetic loci in development and disease. For various mammals, including human, a readily available and widely used list of CGI is available from the UCSC Genome Browser. This list was derived using algorithms that search for regions satisfying a definition of CGI proposed by Gardiner-Garden and Frommer more than 20 years ago. Recent findings, enabled by advances in technology that permit direct measurement of epigenetic endpoints at a whole-genome scale, motivate the need to adapt the current CGI definition. In this paper, we propose a procedure, guided by hidden Markov models, that permits an extensible approach to detecting CGI. The main advantage of our approach over others is that it summarizes the evidence for CGI status as probability scores. This provides flexibility in the definition of a CGI and facilitates the creation of CGI lists for other species. The utility of this approach is demonstrated by generating the first CGI lists for invertebrates, and the fact that we can create CGI lists that substantially increases overlap with recently discovered epigenetic marks. A CGI list and the probability scores, as a function of genome location, for each species are available at http://www.rafalab.org.

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Year:  2010        PMID: 20212320      PMCID: PMC2883304          DOI: 10.1093/biostatistics/kxq005

Source DB:  PubMed          Journal:  Biostatistics        ISSN: 1465-4644            Impact factor:   5.899


  19 in total

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Journal:  Nature       Date:  2001-02-15       Impact factor: 49.962

2.  Mining Bacillus subtilis chromosome heterogeneities using hidden Markov models.

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3.  The human genome browser at UCSC.

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Journal:  Genome Res       Date:  2002-06       Impact factor: 9.043

4.  A Bayesian approach to DNA sequence segmentation.

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Review 5.  CpG-rich islands and the function of DNA methylation.

Authors:  A P Bird
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6.  Stochastic models for heterogeneous DNA sequences.

Authors:  G A Churchill
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7.  CpG islands in vertebrate genomes.

Authors:  M Gardiner-Garden; M Frommer
Journal:  J Mol Biol       Date:  1987-07-20       Impact factor: 5.469

8.  Comprehensive analysis of CpG islands in human chromosomes 21 and 22.

Authors:  Daiya Takai; Peter A Jones
Journal:  Proc Natl Acad Sci U S A       Date:  2002-03-12       Impact factor: 11.205

9.  A species-generalized probabilistic model-based definition of CpG islands.

Authors:  Rafael A Irizarry; Hao Wu; Andrew P Feinberg
Journal:  Mamm Genome       Date:  2009-09-24       Impact factor: 2.957

10.  The human colon cancer methylome shows similar hypo- and hypermethylation at conserved tissue-specific CpG island shores.

Authors:  Rafael A Irizarry; Christine Ladd-Acosta; Andrew P Feinberg; Bo Wen; Zhijin Wu; Carolina Montano; Patrick Onyango; Hengmi Cui; Kevin Gabo; Michael Rongione; Maree Webster; Hong Ji; James Potash; Sarven Sabunciyan
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  86 in total

1.  Deep History of East Asian Populations Revealed Through Genetic Analysis of the Ainu.

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2.  Relationship between methylome and transcriptome in patients with nonalcoholic fatty liver disease.

Authors:  Susan K Murphy; Hyuna Yang; Cynthia A Moylan; Herbert Pang; Andrew Dellinger; Manal F Abdelmalek; Melanie E Garrett; Allison Ashley-Koch; Ayako Suzuki; Hans L Tillmann; Michael A Hauser; Anna Mae Diehl
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3.  A-clustering: a novel method for the detection of co-regulated methylation regions, and regions associated with exposure.

Authors:  Tamar Sofer; Elizabeth D Schifano; Jane A Hoppin; Lifang Hou; Andrea A Baccarelli
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Review 4.  Dark matters in AMD genetics: epigenetics and stochasticity.

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5.  Comprehensive mapping of the methylation landscape of 16 CpG-dense regions in oral and pharyngeal squamous cell carcinoma.

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6.  Age-associated DNA methylation changes in naive CD4+ T cells suggest an evolving autoimmune epigenotype in aging T cells.

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7.  Conflicts of CpG density and DNA methylation are proximally and distally involved in gene regulation in human and mouse tissues.

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8.  CpG island structure and trithorax/polycomb chromatin domains in human cells.

Authors:  David A Orlando; Matthew G Guenther; Garrett M Frampton; Richard A Young
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9.  How has the study of the human placenta aided our understanding of partially methylated genes?

Authors:  Diane I Schroeder; Janine M LaSalle
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10.  Prediction of CpG-island function: CpG clustering vs. sliding-window methods.

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