Andrew P Feinberg

Publications of Andrew P Feinberg

• DNA methylation shows genome-wide association of NFIX, RAPGEF2 and MSRB3 with gestational age at birth.

  Authors: Hwajin Lee, Andrew E Jaffe, Jason I Feinberg, Rakel Tryggvadottir, Shannon Brown, Carolina Montano, Martin J Aryee, Rafael A Irizarry, Julie Herbstman, Frank R Witter, Lynn R Goldman, Andrew P Feinberg, M Daniele Fallin

  International journal of epidemiology. 02/2012; 41(1):188-199.

  BACKGROUND: Gestational age at birth strongly predicts neonatal, adolescent and adult morbidity and mortality through mostly unknown mechanisms. Identification of specific genes that are undergoingBACKGROUND: Gestational age at birth strongly predicts neonatal, adolescent and adult morbidity and mortality through mostly unknown mechanisms. Identification of specific genes that are undergoing regulatory change prior to birth, such as through changes in DNA methylation, would increase our understanding of developmental changes occurring during the third trimester and consequences of pre-term birth (PTB). METHODS: We performed a genome-wide analysis of DNA methylation (using microarrays, specifically CHARM 2.0) in 141 newborns collected in Baltimore, MD, using novel statistical methodology to identify genomic regions associated with gestational age at birth. Bisulphite pyrosequencing was used to validate significant differentially methylated regions (DMRs), and real-time PCR was performed to assess functional significance of differential methylation in a subset of newborns. RESULTS: We identified three DMRs at genome-wide significance levels adjacent to the NFIX, RAPGEF2 and MSRB3 genes. All three regions were validated by pyrosequencing, and RAGPEF2 also showed an inverse correlation between DNA methylation levels and gene expression levels. Although the three DMRs appear very dynamic with gestational age in our newborn sample, adult DNA methylation levels at these regions are stable and of equal or greater magnitude than the oldest neonate, directionally consistent with the gestational age results. CONCLUSIONS: We have identified three differentially methylated regions associated with gestational age at birth. All three nearby genes play important roles in the development of several organs, including skeletal muscle, brain and haematopoietic system. Therefore, they may provide initial insight into the basis of PTB's negative health outcomes. The genome-wide custom DNA methylation array technology and novel statistical methods employed in this study could constitute a model for epidemiologic studies of epigenetic variation.

• Bump hunting to identify differentially methylated regions in epigenetic epidemiology studies.

  Authors: Andrew E Jaffe, Peter Murakami, Hwajin Lee, Jeffrey T Leek, M Daniele Fallin, Andrew P Feinberg, Rafael A Irizarry

  International journal of epidemiology. 02/2012; 41(1):200-9.

  During the past 5 years, high-throughput technologies have been successfully used by epidemiology studies, but almost all have focused on sequence variation through genome-wide association studiesDuring the past 5 years, high-throughput technologies have been successfully used by epidemiology studies, but almost all have focused on sequence variation through genome-wide association studies (GWAS). Today, the study of other genomic events is becoming more common in large-scale epidemiological studies. Many of these, unlike the single-nucleotide polymorphism studied in GWAS, are continuous measures. In this context, the exercise of searching for regions of interest for disease is akin to the problems described in the statistical 'bump hunting' literature. New statistical challenges arise when the measurements are continuous rather than categorical, when they are measured with uncertainty, and when both biological signal, and measurement errors are characterized by spatial correlation along the genome. Perhaps the most challenging complication is that continuous genomic data from large studies are measured throughout long periods, making them susceptible to 'batch effects'. An example that combines all three characteristics is genome-wide DNA methylation measurements. Here, we present a data analysis pipeline that effectively models measurement error, removes batch effects, detects regions of interest and attaches statistical uncertainty to identified regions. We illustrate the usefulness of our approach by detecting genomic regions of DNA methylation associated with a continuous trait in a well-characterized population of newborns. Additionally, we show that addressing unexplained heterogeneity like batch effects reduces the number of false-positive regions. Our framework offers a comprehensive yet flexible approach for identifying genomic regions of biological interest in large epidemiological studies using quantitative high-throughput methods.

• Genome-wide DNA methylation scan in major depressive disorder.

  Authors: Sarven Sabunciyan, Martin J Aryee, Rafael A Irizarry, Michael Rongione, Maree J Webster, Walter E Kaufman, Peter Murakami, Andree Lessard, Robert H Yolken, Andrew P Feinberg, James B Potash, Genred Consortium

  PloS one. 01/2012; 7(4):e34451.

  While genome-wide association studies are ongoing to identify sequence variation influencing susceptibility to major depressive disorder (MDD), epigenetic marks, such as DNA methylation, which can beWhile genome-wide association studies are ongoing to identify sequence variation influencing susceptibility to major depressive disorder (MDD), epigenetic marks, such as DNA methylation, which can be influenced by environment, might also play a role. Here we present the first genome-wide DNA methylation (DNAm) scan in MDD. We compared 39 postmortem frontal cortex MDD samples to 26 controls. DNA was hybridized to our Comprehensive High-throughput Arrays for Relative Methylation (CHARM) platform, covering 3.5 million CpGs. CHARM identified 224 candidate regions with DNAm differences >10%. These regions are highly enriched for neuronal growth and development genes. Ten of 17 regions for which validation was attempted showed true DNAm differences; the greatest were in PRIMA1, with 12-15% increased DNAm in MDD (p = 0.0002-0.0003), and a concomitant decrease in gene expression. These results must be considered pilot data, however, as we could only test replication in a small number of additional brain samples (n = 16), which showed no significant difference in PRIMA1. Because PRIMA1 anchors acetylcholinesterase in neuronal membranes, decreased expression could result in decreased enzyme function and increased cholinergic transmission, consistent with a role in MDD. We observed decreased immunoreactivity for acetylcholinesterase in MDD brain with increased PRIMA1 DNAm, non-significant at p = 0.08.While we cannot draw firm conclusions about PRIMA1 DNAm in MDD, the involvement of neuronal development genes across the set showing differential methylation suggests a role for epigenetics in the illness. Further studies using limbic system brain regions might shed additional light on this role.

• Stem cell differentiation as a renewal-reward process: predictions and validation in the colonic crypt.

  Authors: Kiran Gireesan Vanaja, Andrew P Feinberg, Andre Levchenko

  Advances in experimental medicine and biology. 01/2012; 736:199-209.

  Stem cells serve as persistent reservoirs for replenishment of rapidly renewing tissues, frequently also ensuring that the correct tissue morphology is maintained. This process is inherentlyStem cells serve as persistent reservoirs for replenishment of rapidly renewing tissues, frequently also ensuring that the correct tissue morphology is maintained. This process is inherently stochastic due to the small number and stochastic division patterns within the stem cell compartments, as well as the essentially stochastic differentiation events that follow the initial stem cell expansion. Here we propose a new formalism to describe this process, by employing the approach known in statistics as the renewal-reward process. Using this approximation allows application of the mathematical apparatus developed for renewal-reward processes to the stochastic stem cell biology. We show in the context of colonic crypts that the resulting predictions match the experimental results, while also providing a convenient tool for analysis of normal and abnormal differentiation processes.

• Donor cell type can influence the epigenome and differentiation potential of human induced pluripotent stem cells.

  Authors: Kitai Kim, Rui Zhao, Akiko Doi, Kitwa Ng, Juli Unternaehrer, Patrick Cahan, Hongguang Huo, Yuin-Han Loh, Martin J Aryee, M William Lensch, Hu Li, James J Collins, Andrew P Feinberg, George Q Daley

  Nature biotechnology. 11/2011; 29(12):1117-9.

  We compared bona fide human induced pluripotent stem cells (iPSCs) derived from umbilical cord blood (CB) cells and neonatal keratinocytes (K). As a consequence of both incomplete erasure ofWe compared bona fide human induced pluripotent stem cells (iPSCs) derived from umbilical cord blood (CB) cells and neonatal keratinocytes (K). As a consequence of both incomplete erasure of tissue-specific methylation and aberrant de novo methylation, CB-iPSCs and K-iPSCs were distinct in genome-wide DNA methylation profiles and differentiation potential. Extended passage of some iPSC clones in culture did not improve their epigenetic resemblance to embryonic stem cells, implying that some human iPSCs retain a residual 'epigenetic memory' of their tissue of origin.

• Adaptation of the CHARM DNA methylation platform for the rat genome reveals novel brain region-specific differences.

  Authors: Richard S Lee, Kellie L K Tamashiro, Martin J Aryee, Peter Murakami, Fayaz Seifuddin, Brian Herb, Yuqing Huo, Michael Rongione, Andrew P Feinberg, Timothy H Moran, James B Potash

  Epigenetics : official journal of the DNA Methylation Society. 11/2011; 6(11).

  Comprehensive High-throughput Arrays for Relative Methylation (CHARM) was recently developed as an experimental platform and analytic approach to assess DNA methylation (DNAm) at a genome-wide level.Comprehensive High-throughput Arrays for Relative Methylation (CHARM) was recently developed as an experimental platform and analytic approach to assess DNA methylation (DNAm) at a genome-wide level. Its initial implementation was for human and mouse. We adapted it for rat and sought to examine DNAm differences across tissues and brain regions in this model organism. We extracted DNA from liver, spleen, and three brain regions: cortex, hippocampus, and hypothalamus from adult Sprague Dawley rats. DNA was digested with McrBC, and the resulting methyl-depleted fraction was hybridized to the rat CHARM array along with a mock-treated fraction. Differentially methylated regions (DMRs) between tissue types were detected using normalized methylation log-ratios. In validating 24 of the most significant DMRs by bisulfite pyrosequencing, we detected large mean differences in DNAm, ranging from 33-59%, among the most significant DMRs in the across-tissue comparisons. The comparable figures for the hippocampus vs. hypothalamus DMRs were 14-40%, for the cortex vs. hippocampus DMRs, 12-29%, and for the cortex vs. hypothalamus DMRs, 5-35%, with a correlation of r ( 2) = 0.92 between the methylation differences in 24 DMRs predicted by CHARM and those validated by bisulfite pyrosequencing. Our adaptation of the CHARM array for the rat genome yielded highly robust results that demonstrate the value of this method in detecting substantial DNAm differences between tissues and across different brain regions. This platform should prove valuable in future studies aimed at examining DNAm differences in particular brain regions of rats exposed to environmental stimuli with potential epigenetic consequences.

• A nucleolar protein, H19 opposite tumor suppressor (HOTS), is a tumor growth inhibitor encoded by a human imprinted H19 antisense transcript.

  Authors: Patrick Onyango, Andrew P Feinberg

  Proceedings of the National Academy of Sciences of the United States of America. 09/2011; 108(40):16759-64.

  The H19 gene, which localizes within a chromosomal region on human chromosome 11p15 that is commonly lost in Wilms tumor (WT), encodes an imprinted untranslated RNA. However, the biologicalThe H19 gene, which localizes within a chromosomal region on human chromosome 11p15 that is commonly lost in Wilms tumor (WT), encodes an imprinted untranslated RNA. However, the biological significance of the H19 noncoding transcript remains unresolved because replacement of the RNA transcript with a neocassette has no obvious phenotypic effect. Here we show that the human H19 locus also encodes a maternally expressed, translated gene, antisense to the known H19 transcript, which is conserved in primates. This gene, termed HOTS for H19 opposite tumor suppressor, encodes a protein that localizes to the nucleus and nucleolus and that interacts with the human enhancer of rudimentary homolog (ERH) protein. WTs that show loss of heterozygosity of 11p15 or loss of imprinting of IGF2 also silence HOTS (7/7 and 10/10, respectively). Overexpression of HOTS inhibits Wilms, rhabdoid, rhabdomyosarcoma, and choriocarcinoma tumor cell growth, and silencing HOTS by RNAi increases in vitro colony formation and in vivo tumor growth. These results demonstrate that the human H19 locus harbors an imprinted gene encoding a tumor suppressor protein within the long-sought WT2 locus.

• Genome-scale epigenetic reprogramming during epithelial-to-mesenchymal transition.

  Authors: Oliver G McDonald, Hao Wu, Winston Timp, Akiko Doi, Andrew P Feinberg

  Nature structural & molecular biology. 07/2011; 18(8):867-74.

  Epithelial-to-mesenchymal transition (EMT) is an extreme example of cell plasticity that is important for normal development, injury repair and malignant progression. Widespread epigeneticEpithelial-to-mesenchymal transition (EMT) is an extreme example of cell plasticity that is important for normal development, injury repair and malignant progression. Widespread epigenetic reprogramming occurs during stem cell differentiation and malignant transformation, but EMT-related epigenetic reprogramming is poorly understood. Here we investigated epigenetic modifications during EMT mediated by transforming growth factor beta. Although DNA methylation was unchanged during EMT, we found a global reduction in the heterochromatin mark H3 Lys9 dimethylation (H3K9Me2), an increase in the euchromatin mark H3 Lys4 trimethylation (H3K4Me3) and an increase in the transcriptional mark H3 Lys36 trimethylation (H3K36Me3). These changes depended largely on lysine-specific demethylase-1 (Lsd1), and loss of Lsd1 function had marked effects on EMT-driven cell migration and chemoresistance. Genome-scale mapping showed that chromatin changes were mainly specific to large organized heterochromatin K9 modifications (LOCKs), which suggests that EMT is characterized by reprogramming of specific chromatin domains across the genome.

• Increased methylation variation in epigenetic domains across cancer types.

  Authors: Kasper Daniel Hansen, Winston Timp, Héctor Corrada Bravo, Sarven Sabunciyan, Benjamin Langmead, Oliver G McDonald, Bo Wen, Hao Wu, Yun Liu, Dinh Diep, Eirikur Briem, Kun Zhang, Rafael A Irizarry, Andrew P Feinberg

  Nature genetics. 06/2011; 43(8):768-75.

  Tumor heterogeneity is a major barrier to effective cancer diagnosis and treatment. We recently identified cancer-specific differentially DNA-methylated regions (cDMRs) in colon cancer, which alsoTumor heterogeneity is a major barrier to effective cancer diagnosis and treatment. We recently identified cancer-specific differentially DNA-methylated regions (cDMRs) in colon cancer, which also distinguish normal tissue types from each other, suggesting that these cDMRs might be generalized across cancer types. Here we show stochastic methylation variation of the same cDMRs, distinguishing cancer from normal tissue, in colon, lung, breast, thyroid and Wilms' tumors, with intermediate variation in adenomas. Whole-genome bisulfite sequencing shows these variable cDMRs are related to loss of sharply delimited methylation boundaries at CpG islands. Furthermore, we find hypomethylation of discrete blocks encompassing half the genome, with extreme gene expression variability. Genes associated with the cDMRs and large blocks are involved in mitosis and matrix remodeling, respectively. We suggest a model for cancer involving loss of epigenetic stability of well-defined genomic domains that underlies increased methylation variability in cancer that may contribute to tumor heterogeneity.

• Significance analysis and statistical dissection of variably methylated regions.

  Authors: Andrew E Jaffe, Andrew P Feinberg, Rafael A Irizarry, Jeffrey T Leek

  Biostatistics (Oxford, England). 06/2011; 13(1):166-78.

  It has recently been proposed that variation in DNA methylation at specific genomic locations may play an important role in the development of complex diseases such as cancer. Here, we develop 1- andIt has recently been proposed that variation in DNA methylation at specific genomic locations may play an important role in the development of complex diseases such as cancer. Here, we develop 1- and 2-group multiple testing procedures for identifying and quantifying regions of DNA methylation variability. Our method is the first genome-wide statistical significance calculation for increased or differential variability, as opposed to the traditional approach of testing for mean changes. We apply these procedures to genome-wide methylation data obtained from biological and technical replicates and provide the first statistical proof that variably methylated regions exist and are due to interindividual variation. We also show that differentially variable regions in colon tumor and normal tissue show enrichment of genes regulating gene expression, cell morphogenesis, and development, supporting a biological role for DNA methylation variability in cancer.

• Accurate genome-scale percentage DNA methylation estimates from microarray data.

  Authors: Martin J Aryee, Zhijin Wu, Christine Ladd-Acosta, Brian Herb, Andrew P Feinberg, Srinivasan Yegnasubramanian, Rafael A Irizarry

  Biostatistics (Oxford, England). 04/2011; 12(2):197-210.

  DNA methylation is a key regulator of gene function in a multitude of both normal and abnormal biological processes, but tools to elucidate its roles on a genome-wide scale are still in theirDNA methylation is a key regulator of gene function in a multitude of both normal and abnormal biological processes, but tools to elucidate its roles on a genome-wide scale are still in their infancy. Methylation sensitive restriction enzymes and microarrays provide a potential high-throughput, low-cost platform to allow methylation profiling. However, accurate absolute methylation estimates have been elusive due to systematic errors and unwanted variability. Previous microarray preprocessing procedures, mostly developed for expression arrays, fail to adequately normalize methylation-related data since they rely on key assumptions that are violated in the case of DNA methylation. We develop a normalization strategy tailored to DNA methylation data and an empirical Bayes percentage methylation estimator that together yield accurate absolute methylation estimates that can be compared across samples. We illustrate the method on data generated to detect methylation differences between tissues and between normal and tumor colon samples.

• Epigenomics reveals a functional genome anatomy and a new approach to common disease.

  Authors: Andrew P Feinberg

  Nature biotechnology. 10/2010; 28(10):1049-52.

  Epigenomics provides the context for understanding the function of genome sequence, analogous to the functional anatomy of the human body provided by Vesalius a half-millennium ago. Much of theEpigenomics provides the context for understanding the function of genome sequence, analogous to the functional anatomy of the human body provided by Vesalius a half-millennium ago. Much of the seemingly inconclusive genetic data related to common diseases could therefore become meaningful in an epigenomic context.

• Comprehensive methylome map of lineage commitment from haematopoietic progenitors.

  Authors: Hong Ji, Lauren I R Ehrlich, Jun Seita, Peter Murakami, Akiko Doi, Paul Lindau, Hwajin Lee, Martin J Aryee, Rafael A Irizarry, Kitai Kim, Derrick J Rossi, Matthew A Inlay, Thomas Serwold, Holger Karsunky, Lena Ho, George Q Daley, Irving L Weissman, Andrew P Feinberg

  Nature. 09/2010; 467(7313):338-42.

  Epigenetic modifications must underlie lineage-specific differentiation as terminally differentiated cells express tissue-specific genes, but their DNA sequence is unchanged. Haematopoiesis providesEpigenetic modifications must underlie lineage-specific differentiation as terminally differentiated cells express tissue-specific genes, but their DNA sequence is unchanged. Haematopoiesis provides a well-defined model to study epigenetic modifications during cell-fate decisions, as multipotent progenitors (MPPs) differentiate into progressively restricted myeloid or lymphoid progenitors. Although DNA methylation is critical for myeloid versus lymphoid differentiation, as demonstrated by the myeloerythroid bias in Dnmt1 hypomorphs, a comprehensive DNA methylation map of haematopoietic progenitors, or of any multipotent/oligopotent lineage, does not exist. Here we examined 4.6 million CpG sites throughout the genome for MPPs, common lymphoid progenitors (CLPs), common myeloid progenitors (CMPs), granulocyte/macrophage progenitors (GMPs), and thymocyte progenitors (DN1, DN2, DN3). Marked epigenetic plasticity accompanied both lymphoid and myeloid restriction. Myeloid commitment involved less global DNA methylation than lymphoid commitment, supported functionally by myeloid skewing of progenitors following treatment with a DNA methyltransferase inhibitor. Differential DNA methylation correlated with gene expression more strongly at CpG island shores than CpG islands. Many examples of genes and pathways not previously known to be involved in choice between lymphoid/myeloid differentiation have been identified, such as Arl4c and Jdp2. Several transcription factors, including Meis1, were methylated and silenced during differentiation, indicating a role in maintaining an undifferentiated state. Additionally, epigenetic modification of modifiers of the epigenome seems to be important in haematopoietic differentiation. Our results directly demonstrate that modulation of DNA methylation occurs during lineage-specific differentiation and defines a comprehensive map of the methylation and transcriptional changes that accompany myeloid versus lymphoid fate decisions.

• Personalized epigenomic signatures that are stable over time and covary with body mass index.

  Authors: Andrew P Feinberg, Rafael A Irizarry, Delphine Fradin, Martin J Aryee, Peter Murakami, Thor Aspelund, Gudny Eiriksdottir, Tamara B Harris, Lenore Launer, Vilmundur Gudnason, M Daniele Fallin

  Science translational medicine. 09/2010; 2(49):49ra67.

  The epigenome consists of non-sequence-based modifications, such as DNA methylation, that are heritable during cell division and that may affect normal phenotypes and predisposition to disease. Here,The epigenome consists of non-sequence-based modifications, such as DNA methylation, that are heritable during cell division and that may affect normal phenotypes and predisposition to disease. Here, we have performed an unbiased genome-scale analysis of ~4 million CpG sites in 74 individuals with comprehensive array-based relative methylation (CHARM) analysis. We found 227 regions that showed extreme interindividual variability [variably methylated regions (VMRs)] across the genome, which are enriched for developmental genes based on Gene Ontology analysis. Furthermore, half of these VMRs were stable within individuals over an average of 11 years, and these VMRs defined a personalized epigenomic signature. Four of these VMRs showed covariation with body mass index consistently at two study visits and were located in or near genes previously implicated in regulating body weight or diabetes. This work suggests an epigenetic strategy for identifying patients at risk of common disease.

• Addition of H19 'loss of methylation testing' for Beckwith-Wiedemann syndrome (BWS) increases the diagnostic yield.

  Authors: Jochen K Lennerz, Robert J Timmerman, Dorothy K Grange, Michael R DeBaun, Andrew P Feinberg, Barbara A Zehnbauer

  The Journal of molecular diagnostics : JMD. 09/2010; 12(5):576-88.

  Beckwith-Wiedemann syndrome (BWS) is a clinical diagnosis; however, molecular confirmation via abnormal methylation of DMR2(LIT1) and/or DMR1(H19) has clinical utility due to epigenotype-tumorBeckwith-Wiedemann syndrome (BWS) is a clinical diagnosis; however, molecular confirmation via abnormal methylation of DMR2(LIT1) and/or DMR1(H19) has clinical utility due to epigenotype-tumor association. Despite the strong link between H19 hypermethylation and tumor risk, several diagnostic laboratories only test for hypomethylation of LIT1. We assessed the added diagnostic value of combined LIT1 and H19 testing in a large series of referred samples from 1298 patients, including 53 well-characterized patients from the St. Louis Children's Hospital BWS-Registry (validation samples) and 1245 consecutive nationwide referrals (practice samples). Methylation-sensitive enzymatic digestion with Southern hybridization assessed loss of normal imprinting. In the validation group, abnormal LIT1 hypomethylation was detected in 60% (32/52) of patients but LIT1/H19-combined testing was abnormal in 68% (36/53); sensitivity in the practice setting demonstrated 27% (342/1245) abnormal LIT1 and 32% (404/1245) abnormal LIT1/H19-combined. In addition, H19 methylation was abnormal in 7% of LIT1-normal patients. We observed absence of uniparental disomy (UPD) in 27% of combined LIT1/H19-abnormal samples, diagnostic of multilocus methylation abnormalities; in contrast to studies implicating that combined LIT1/H19 abnormalities are diagnostic of UPD. The overall low detection rate, even in validated patient samples and despite characterization of both loci and UPD status, emphasizes the importance of clinical diagnosis in BWS.

• Comprehensive high-throughput arrays for relative methylation (CHARM).

  Authors: Christine Ladd-Acosta, Martin J Aryee, Jared M Ordway, Andrew P Feinberg

  Current protocols in human genetics / editorial board, Jonathan L. Haines ... [et al.]. 04/2010; Chapter 20:Unit 20.1.1-19.

  DNA methylation (DNAm) is a term used to describe the heritable covalent addition of a methyl group to cytosines at CpG dinucleotides in mammals. While methods for examining DNAm status at specificDNA methylation (DNAm) is a term used to describe the heritable covalent addition of a methyl group to cytosines at CpG dinucleotides in mammals. While methods for examining DNAm status at specific loci have existed for several years, recent technological advances have begun to enable the examination of DNAm across the genome. In this unit, we describe comprehensive high-throughput arrays for relative methylation (CHARM), a highly sensitive and specific approach to measure DNA methylation across the genome. This method makes no assumptions about where functionally important DNAm occurs, i.e., CpG island or promoter regions, and includes lower-CpG-density regions of the genome. In addition, it uses a novel genome-weighted smoothing algorithm to correct for CpG density and fragment biases present in methyl-enrichment or methyl-depletion DNA-fractionation methods. It can be applied to studying epigenomic changes in DNAm for normal and diseased samples.

• Redefining CpG islands using hidden Markov models.

  Authors: Hao Wu, Brian Caffo, Harris A Jaffee, Rafael A Irizarry, Andrew P Feinberg

  Biostatistics (Oxford, England). 03/2010; 11(3):499-514.

  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) heritableThe 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.

• Evolution in health and medicine Sackler colloquium: Stochastic epigenetic variation as a driving force of development, evolutionary adaptation, and disease.

  Authors: Andrew P Feinberg, Rafael A Irizarry

  Proceedings of the National Academy of Sciences of the United States of America. 01/2010; 107 Suppl 1:1757-64.

  Neo-Darwinian evolutionary theory is based on exquisite selection of phenotypes caused by small genetic variations, which is the basis of quantitative trait contribution to phenotype and disease.Neo-Darwinian evolutionary theory is based on exquisite selection of phenotypes caused by small genetic variations, which is the basis of quantitative trait contribution to phenotype and disease. Epigenetics is the study of nonsequence-based changes, such as DNA methylation, heritable during cell division. Previous attempts to incorporate epigenetics into evolutionary thinking have focused on Lamarckian inheritance, that is, environmentally directed epigenetic changes. Here, we propose a new non-Lamarckian theory for a role of epigenetics in evolution. We suggest that genetic variants that do not change the mean phenotype could change the variability of phenotype; and this could be mediated epigenetically. This inherited stochastic variation model would provide a mechanism to explain an epigenetic role of developmental biology in selectable phenotypic variation, as well as the largely unexplained heritable genetic variation underlying common complex disease. We provide two experimental results as proof of principle. The first result is direct evidence for stochastic epigenetic variation, identifying highly variably DNA-methylated regions in mouse and human liver and mouse brain, associated with development and morphogenesis. The second is a heritable genetic mechanism for variable methylation, namely the loss or gain of CpG dinucleotides over evolutionary time. Finally, we model genetically inherited stochastic variation in evolution, showing that it provides a powerful mechanism for evolutionary adaptation in changing environments that can be mediated epigenetically. These data suggest that genetically inherited propensity to phenotypic variability, even with no change in the mean phenotype, substantially increases fitness while increasing the disease susceptibility of a population with a changing environment.

• Reply to "Reassessing the abundance of H3K9me2 chromatin domains in embryonic stem cells".

  Authors: Bo Wen, Hao Wu, Yoichi Shinkai, Rafael A Irizarry, Andrew P Feinberg

  Nature genetics. 01/2010; 42(1):5-6.

• Differential methylation of tissue- and cancer-specific CpG island shores distinguishes human induced pluripotent stem cells, embryonic stem cells and fibroblasts.

  Authors: Akiko Doi, In-Hyun Park, Bo Wen, Peter Murakami, Martin J Aryee, Rafael Irizarry, Brian Herb, Christine Ladd-Acosta, Junsung Rho, Sabine Loewer, Justine Miller, Thorsten Schlaeger, George Q Daley, Andrew P Feinberg

  Nature genetics. 11/2009;

  Induced pluripotent stem (iPS) cells are derived by epigenetic reprogramming, but their DNA methylation patterns have not yet been analyzed on a genome-wide scale. Here, we find substantialInduced pluripotent stem (iPS) cells are derived by epigenetic reprogramming, but their DNA methylation patterns have not yet been analyzed on a genome-wide scale. Here, we find substantial hypermethylation and hypomethylation of cytosine-phosphate-guanine (CpG) island shores in nine human iPS cell lines as compared to their parental fibroblasts. The differentially methylated regions (DMRs) in the reprogrammed cells (denoted R-DMRs) were significantly enriched in tissue-specific (T-DMRs; 2.6-fold, P < 10(-4)) and cancer-specific DMRs (C-DMRs; 3.6-fold, P < 10(-4)). Notably, even though the iPS cells are derived from fibroblasts, their R-DMRs can distinguish between normal brain, liver and spleen cells and between colon cancer and normal colon cells. Thus, many DMRs are broadly involved in tissue differentiation, epigenetic reprogramming and cancer. We observed colocalization of hypomethylated R-DMRs with hypermethylated C-DMRs and bivalent chromatin marks, and colocalization of hypermethylated R-DMRs with hypomethylated C-DMRs and the absence of bivalent marks, suggesting two mechanisms for epigenetic reprogramming in iPS cells and cancer.