% This file was created with JabRef 2.3.
% Encoding: ANSI_X3.4-1968

@ARTICLE{Chavez2010,
  author = {Lukas Chavez and Justyna Jozefczuk and Christina Grimm and Joern
	Dietrich and Bernd Timmermann and Hans Lehrach and Ralf Herwig and
	James Adjaye},
  title = {Computational analysis of genome-wide DNA methylation during the
	differentiation of human embryonic stem cells along the endodermal
	lineage.},
  journal = {Genome Res},
  year = {2010},
  month = {Aug},
  abstract = {The generation of genome-wide data derived from methylated DNA immunoprecipitation
	followed by sequencing (MeDIP-seq) has become a major tool for epigenetic
	studies in health and disease. The computational analysis of such
	data, however, still falls short on accuracy, sensitivity, and speed.
	We propose a time-efficient statistical method that is able to cope
	with the inherent complexity of MeDIP-seq data with similar performance
	compared with existing methods. In order to demonstrate the computational
	approach, we have analyzed alterations in DNA methylation during
	the differentiation of human embryonic stem cells (hESCs) to definitive
	endoderm. We show improved correlation of normalized MeDIP-seq data
	in comparison to available whole-genome bisulfite sequencing data,
	and investigated the effect of differential methylation on gene expression.
	Furthermore, we analyzed the interplay between DNA methylation, histone
	modifications, and transcription factor binding and show that in
	contrast to de novo methylation, demethylation is mainly associated
	with regions of low CpG densities.},
  institution = {Department of Vertebrate Genomics, Max-Planck-Institute for Molecular
	Genetics, D-14195 Berlin, Germany;},
  owner = {chavez},
  pii = {gr.110114.110},
  pmid = {20802089},
  timestamp = {2010.09.27}  
}

@ARTICLE{Down2008,
  author = {Thomas A Down and Vardhman K Rakyan and Daniel J Turner and Paul
	Flicek and Heng Li and Eugene Kulesha and Stefan Graef and Nathan
	Johnson and Javier Herrero and Eleni M Tomazou and Natalie P Thorne
	and Liselotte Baeckdahl and Marlis Herberth and Kevin L Howe and
	David K Jackson and Marcos M Miretti and John C Marioni and Ewan
	Birney and Tim J P Hubbard and Richard Durbin and Simon Tavare and
	Stephan Beck},
  title = {A Bayesian deconvolution strategy for immunoprecipitation-based DNA
	methylome analysis.},
  journal = {Nat Biotechnol},
  year = {2008},
  volume = {26},
  pages = {779--785},
  number = {7},
  month = {Jul},
  abstract = {DNA methylation is an indispensible epigenetic modification required
	for regulating the expression of mammalian genomes. Immunoprecipitation-based
	methods for DNA methylome analysis are rapidly shifting the bottleneck
	in this field from data generation to data analysis, necessitating
	the development of better analytical tools. In particular, an inability
	to estimate absolute methylation levels remains a major analytical
	difficulty associated with immunoprecipitation-based DNA methylation
	profiling. To address this issue, we developed a cross-platform algorithm-Bayesian
	tool for methylation analysis (Batman)-for analyzing methylated DNA
	immunoprecipitation (MeDIP) profiles generated using oligonucleotide
	arrays (MeDIP-chip) or next-generation sequencing (MeDIP-seq). We
	developed the latter approach to provide a high-resolution whole-genome
	DNA methylation profile (DNA methylome) of a mammalian genome. Strong
	correlation of our data, obtained using mature human spermatozoa,
	with those obtained using bisulfite sequencing suggest that combining
	MeDIP-seq or MeDIP-chip with Batman provides a robust, quantitative
	and cost-effective functional genomic strategy for elucidating the
	function of DNA methylation.},
  institution = {Wellcome Trust Cancer Research UK Gurdon Institute, and Department
	of Genetics, University of Cambridge, Tennis Court Road, Cambridge
	CB2 1QR, UK. thomas.down@gurdon.cam.ac.uk},
  keywords = {Algorithms; Base Sequence; Bayes Theorem; Chromatin Immunoprecipitation;
	Chromosome Mapping; DNA; DNA Methylation; Molecular Sequence Data;
	Pattern Recognition, Automated; Sequence Analysis, DNA},
  owner = {chavez},
  pii = {nbt1414},
  pmid = {18612301},
  timestamp = {2010.01.25}
}

@ARTICLE{Eckhardt2006,
  author = {Florian Eckhardt and Joern Lewin and Rene Cortese and Vardhman K
	Rakyan and John Attwood and Matthias Burger and John Burton and Tony
	V Cox and Rob Davies and Thomas A Down and Carolina Haefliger and
	Roger Horton and Kevin Howe and David K Jackson and Jan Kunde and
	Christoph Koenig and Jennifer Liddle and David Niblett and Thomas
	Otto and Roger Pettett and Stefanie Seemann and Christian Thompson
	and Tony West and Jane Rogers and Alex Olek and Kurt Berlin and Stephan
	Beck},
  title = {DNA methylation profiling of human chromosomes 6, 20 and 22.},
  journal = {Nat Genet},
  year = {2006},
  volume = {38},
  pages = {1378--1385},
  number = {12},
  month = {Dec},
  abstract = {DNA methylation is the most stable type of epigenetic modification
	modulating the transcriptional plasticity of mammalian genomes. Using
	bisulfite DNA sequencing, we report high-resolution methylation profiles
	of human chromosomes 6, 20 and 22, providing a resource of about
	1.9 million CpG methylation values derived from 12 different tissues.
	Analysis of six annotation categories showed that evolutionarily
	conserved regions are the predominant sites for differential DNA
	methylation and that a core region surrounding the transcriptional
	start site is an informative surrogate for promoter methylation.
	We find that 17\% of the 873 analyzed genes are differentially methylated
	in their 5' UTRs and that about one-third of the differentially methylated
	5' UTRs are inversely correlated with transcription. Despite the
	fact that our study controlled for factors reported to affect DNA
	methylation such as sex and age, we did not find any significant
	attributable effects. Our data suggest DNA methylation to be ontogenetically
	more stable than previously thought.},
  institution = {Epigenomics AG, Kleine Pr?sidentstrasse 1, 10178 Berlin, Germany.},
  keywords = {5' Untranslated Regions; Adult; Age Factors; Aged; Animals; Chromosomes,
	Human, Pair 20; Chromosomes, Human, Pair 22; Chromosomes, Human,
	Pair 6; CpG Islands; DNA Methylation; Epigenesis, Genetic; Evolution,
	Molecular; Female; Humans; Male; Mice; Middle Aged; Organ Specificity;
	Promoter Regions, Genetic; Sex Characteristics; Species Specificity;
	Transcription, Genetic},
  owner = {chavez},
  pii = {ng1909},
  pmid = {17072317},
  timestamp = {2010.01.25}
}

@ARTICLE{Lister2009,
  author = {Ryan Lister and Mattia Pelizzola and Robert H Dowen and R. David
	Hawkins and Gary Hon and Julian Tonti-Filippini and Joseph R Nery
	and Leonard Lee and Zhen Ye and Que-Minh Ngo and Lee Edsall and Jessica
	Antosiewicz-Bourget and Ron Stewart and Victor Ruotti and A. Harvey
	Millar and James A Thomson and Bing Ren and Joseph R Ecker},
  title = {Human DNA methylomes at base resolution show widespread epigenomic
	differences.},
  journal = {Nature},
  year = {2009},
  volume = {462},
  pages = {315--322},
  number = {7271},
  month = {Nov},
  abstract = {DNA cytosine methylation is a central epigenetic modification that
	has essential roles in cellular processes including genome regulation,
	development and disease. Here we present the first genome-wide, single-base-resolution
	maps of methylated cytosines in a mammalian genome, from both human
	embryonic stem cells and fetal fibroblasts, along with comparative
	analysis of messenger RNA and small RNA components of the transcriptome,
	several histone modifications, and sites of DNA-protein interaction
	for several key regulatory factors. Widespread differences were identified
	in the composition and patterning of cytosine methylation between
	the two genomes. Nearly one-quarter of all methylation identified
	in embryonic stem cells was in a non-CG context, suggesting that
	embryonic stem cells may use different methylation mechanisms to
	affect gene regulation. Methylation in non-CG contexts showed enrichment
	in gene bodies and depletion in protein binding sites and enhancers.
	Non-CG methylation disappeared upon induced differentiation of the
	embryonic stem cells, and was restored in induced pluripotent stem
	cells. We identified hundreds of differentially methylated regions
	proximal to genes involved in pluripotency and differentiation, and
	widespread reduced methylation levels in fibroblasts associated with
	lower transcriptional activity. These reference epigenomes provide
	a foundation for future studies exploring this key epigenetic modification
	in human disease and development.},
  institution = {Genomic Analysis Laboratory, The Salk Institute for Biological Studies,
	La Jolla, California 92037, USA.},
  keywords = {Cell Line; Cluster Analysis; DNA; DNA Methylation; DNA-Binding Proteins;
	Embryonic Stem Cells; Epigenesis, Genetic; Genome; Humans},
  owner = {chavez},
  pii = {nature08514},
  pmid = {19829295},
  timestamp = {2010.01.25}
}

@ARTICLE{Pelizzola2008,
  author = {Mattia Pelizzola and Yasuo Koga and Alexander Eckehart Urban and
	Michael Krauthammer and Sherman Weissman and Ruth Halaban and Annette
	M Molinaro},
  title = {MEDME: an experimental and analytical methodology for the estimation
	of DNA methylation levels based on microarray derived MeDIP-enrichment.},
  journal = {Genome Res},
  year = {2008},
  volume = {18},
  pages = {1652--1659},
  number = {10},
  month = {Oct},
  abstract = {DNA methylation is an important component of epigenetic modifications
	that influences the transcriptional machinery and is aberrant in
	many human diseases. Several methods have been developed to map DNA
	methylation for either limited regions or genome-wide. In particular,
	antibodies specific for methylated CpG have been successfully applied
	in genome-wide studies. However, despite the relevance of the obtained
	results, the interpretation of antibody enrichment is not trivial.
	Of greatest importance, the coupling of antibody-enriched methylated
	fragments with microarrays generates DNA methylation estimates that
	are not linearly related to the true methylation level. Here, we
	present an experimental and analytical methodology, MEDME (modeling
	experimental data with MeDIP enrichment), to obtain enhanced estimates
	that better describe the true values of DNA methylation level throughout
	the genome. We propose an experimental scenario for evaluating the
	true relationship in a high-throughput setting and a model-based
	analysis to predict the absolute and relative DNA methylation levels.
	We successfully applied this model to evaluate DNA methylation status
	of normal human melanocytes compared to a melanoma cell strain. Despite
	the low resolution typical of methods based on immunoprecipitation,
	we show that model-derived estimates of DNA methylation provide relatively
	high correlation with measured absolute and relative levels, as validated
	by bisulfite genomic DNA sequencing. Importantly, the model-derived
	DNA methylation estimates simplify the interpretation of the results
	both at single-loci and at chromosome-wide levels.},
  institution = {Department of Epidemiology and Public Health, Yale University School
	of Medicine, New Haven, Connecticut 06520, USA.},
  keywords = {Algorithms; CpG Islands; DNA; DNA Methylation; DNA, Neoplasm; Epigenesis,
	Genetic; Genome, Human; Humans; Immunoprecipitation; Infant, Newborn;
	Melanocytes; Oligonucleotide Array Sequence Analysis; Sequence Analysis,
	DNA},
  owner = {chavez},
  pii = {gr.080721.108},
  pmid = {18765822},
  timestamp = {2010.01.25}
}

@ARTICLE{Weber2005a,
  author = {Michael Weber and Jonathan J Davies and David Wittig and Edward J
	Oakeley and Michael Haase and Wan L Lam and Dirk Schuebeler},
  title = {Chromosome-wide and promoter-specific analyses identify sites of
	differential DNA methylation in normal and transformed human cells.},
  journal = {Nat Genet},
  year = {2005},
  volume = {37},
  pages = {853--862},
  number = {8},
  month = {Aug},
  abstract = {Cytosine methylation is required for mammalian development and is
	often perturbed in human cancer. To determine how this epigenetic
	modification is distributed in the genomes of primary and transformed
	cells, we used an immunocapturing approach followed by DNA microarray
	analysis to generate methylation profiles of all human chromosomes
	at 80-kb resolution and for a large set of CpG islands. In primary
	cells we identified broad genomic regions of differential methylation
	with higher levels in gene-rich neighborhoods. Female and male cells
	had indistinguishable profiles for autosomes but differences on the
	X chromosome. The inactive X chromosome (Xi) was hypermethylated
	at only a subset of gene-rich regions and, unexpectedly, overall
	hypomethylated relative to its active counterpart. The chromosomal
	methylation profile of transformed cells was similar to that of primary
	cells. Nevertheless, we detected large genomic segments with hypomethylation
	in the transformed cell residing in gene-poor areas. Furthermore,
	analysis of 6,000 CpG islands showed that only a small set of promoters
	was methylated differentially, suggesting that aberrant methylation
	of CpG island promoters in malignancy might be less frequent than
	previously hypothesized.},
  institution = {Friedrich Miescher Institute for Biomedical Research, Maulbeerstrasse
	66, 4058 Basel, Switzerland.},
  keywords = {Cell Line, Transformed; Cells, Cultured; Chromosomes, Human; CpG Islands;
	DNA Methylation; Female; Humans; Male; Promoter Regions, Genetic;
	Reverse Transcriptase Polymerase Chain Reaction},
  owner = {chavez},
  pii = {ng1598},
  pmid = {16007088},
  timestamp = {2010.01.25}
}

@comment{jabref-meta: selector_publisher:}

@comment{jabref-meta: selector_author:}

@comment{jabref-meta: selector_journal:}

@comment{jabref-meta: selector_keywords:}

