Integrative Model-based clustering of microarray methylation and expression data

In many fields, researchers are interested in large and complex biological processes. Two important examples are gene expression and DNA methylation in genetics. One key problem is to identify aberrant patterns of these processes and discover biologically distinct groups. In this article we develop a model-based method for clustering such data. The basis of our method involves the construction of a likelihood for any given partition of the subjects. We introduce cluster specific latent indicators that, along with some standard assumptions, impose a specific mixture distribution on each cluster. Estimation is carried out using the EM algorithm. The methods extend naturally to multiple data types of a similar nature, which leads to an integrated analysis over multiple data platforms, resulting in higher discriminating power.Comment: Published in at http://dx.doi.org/10.1214/11-AOAS533 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Supervised Classification Using Sparse Fisher's LDA

It is well known that in a supervised classification setting when the number of features is smaller than the number of observations, Fisher's linear discriminant rule is asymptotically Bayes. However, there are numerous modern applications where classification is needed in the high-dimensional setting. Naive implementation of Fisher's rule in this case fails to provide good results because the sample covariance matrix is singular. Moreover, by constructing a classifier that relies on all features the interpretation of the results is challenging. Our goal is to provide robust classification that relies only on a small subset of important features and accounts for the underlying correlation structure. We apply a lasso-type penalty to the discriminant vector to ensure sparsity of the solution and use a shrinkage type estimator for the covariance matrix. The resulting optimization problem is solved using an iterative coordinate ascent algorithm. Furthermore, we analyze the effect of nonconvexity on the sparsity level of the solution and highlight the difference between the penalized and the constrained versions of the problem. The simulation results show that the proposed method performs favorably in comparison to alternatives. The method is used to classify leukemia patients based on DNA methylation features

Cell Type of Origin Influences the Molecular and Functional Properties of Mouse Induced Pluripotent Stem Cells

Induced pluripotent stem cells (iPSCs) have been derived from various somatic cell populations through ectopic expression of defined factors. It remains unclear whether iPSCs generated from different cell types are molecularly and functionally similar. Here we show that iPSCs obtained from mouse fibroblasts, hematopoietic and myogenic cells exhibit distinct transcriptional and epigenetic patterns. Moreover, we demonstrate that cellular origin influences the in vitro differentiation potentials of iPSCs into embryoid bodies and different hematopoietic cell types. Notably, continuous passaging of iPSCs largely attenuates these differences. Our results suggest that early-passage iPSCs retain a transient epigenetic memory of their somatic cells of origin, which manifests as differential gene expression and altered differentiation capacity. These observations may influence ongoing attempts to use iPSCs for disease modeling and could also be exploited in potential therapeutic applications to enhance differentiation into desired cell lineages.Stem Cell and Regenerative Biolog

Cytosine Methylation Dysregulation in Neonates Following Intrauterine Growth Restriction

Perturbations of the intrauterine environment can affect fetal development during critical periods of plasticity, and can increase susceptibility to a number of age-related diseases (e.g., type 2 diabetes mellitus; T2DM), manifesting as late as decades later. We hypothesized that this biological memory is mediated by permanent alterations of the epigenome in stem cell populations, and focused our studies specifically on DNA methylation in CD34+ hematopoietic stem and progenitor cells from cord blood from neonates with intrauterine growth restriction (IUGR) and control subjects.Our epigenomic assays utilized a two-stage design involving genome-wide discovery followed by quantitative, single-locus validation. We found that changes in cytosine methylation occur in response to IUGR of moderate degree and involving a restricted number of loci. We also identify specific loci that are targeted for dysregulation of DNA methylation, in particular the hepatocyte nuclear factor 4alpha (HNF4A) gene, a well-known diabetes candidate gene not previously associated with growth restriction in utero, and other loci encoding HNF4A-interacting proteins.Our results give insights into the potential contribution of epigenomic dysregulation in mediating the long-term consequences of IUGR, and demonstrate the value of this approach to studies of the fetal origin of adult disease

High-resolution genome-wide cytosine methylation profiling with simultaneous copy number analysis and optimization for limited cell numbers

Many genome-wide assays involve the generation of a subset (or representation) of the genome following restriction enzyme digestion. The use of enzymes sensitive to cytosine methylation allows high-throughput analysis of this epigenetic regulatory process. We show that the use of a dual-adapter approach allows us to generate genomic representations that includes fragments of <200 bp in size, previously not possible when using the standard approach of using a single adapter. By expanding the representation to smaller fragments using HpaII or MspI, we increase the representation by these isoschizomers to more than 1.32 million loci in the human genome, representing 98.5% of CpG islands and 91.1% of refSeq promoters. This advance allows the development of a new, high-resolution version of our HpaII-tiny fragment Enrichment by Ligation-mediated PCR (HELP) assay to study cytosine methylation. We also show that the MspI representation generates information about copy-number variation, that the assay can be used on as little as 10 ng of DNA and that massively parallel sequencing can be used as an alternative to microarrays to read the output of the assay, making this a powerful discovery platform for studies of genomic and epigenomic abnormalities

Stem and progenitor cells in myelodysplastic syndromes show aberrant stage-specific expansion and harbor genetic and epigenetic alterations

Even though hematopoietic stem cell (HSC) dysfunction is presumed in myelodysplastic syndrome (MDS), the exact nature of quantitative and qualitative alterations is unknown. We conducted a study of phenotypic and molecular alterations in highly fractionated stem and progenitor populations in a variety of MDS subtypes. We observed an expansion of the phenotypically primitive long-term HSCs (lineage ؊ /CD34 ؉ /CD38 ؊ /CD90 ؉ ) in MDS, which was most pronounced in higher-risk cases. These MDS HSCs demonstrated dysplastic clonogenic activity. Examination of progenitors revealed that lower-risk MDS i

Role for the DNA methylation system in polycomb proteinmediated gene regulation

Chromatin structure and epigenetic mechanisms play an important role in initiating and maintaining the intricate patterns of gene expression required for embryonic development. One such mechanism, DNA methylation (5mC), involves the chemical modification of cytosine bases in DNA and is implicated in maintaining patterns of transcription. However, many fundamental aspects of DNA methylation are not fully understood, including the mechanisms by which it influences transcriptional states. Recent data suggest functional links between DNA methylation and a second epigenetic mechanism that has important roles in transcriptional repression, the polycomb group (PcG) repressor system. Here, I suggest that an intact DNA methylation system is required for the repression of many PcG target genes by influencing the genomic targeting of the polycomb repressor 2 complex (PRC2) and its signature histone modification, H3K27me3 (K27me3). I demonstrate differential genomic localisation of K27me3 at gene promoter regions in hypomethylated mouse embryonic fibroblast (MEF) cells deficient for the major maintenance DNA methyltransferase, Dnmt1. Globally, Dnmt1-/- MEFs have a higher level of the K27me3 mark than controls, as assessed by western blot and immunofluorescence. I observe increased K27me3 at a relatively small number of gene promoters in Dnmt1-/- MEFs that often are associated with high levels of DNA methylation in wildtype MEFs, consistent with the notion that DNA methylation is capable of antagonising PRC2 binding at certain loci. Conversely, I show that a large number of developmentally important genes that are normally repressed and highly bound by K27me3, including classic polycomb targets, the Hox genes, display dramatically reduced association with K27me3 in Dnmt1-/- MEFs. Many of these genes, but not all, show reciprocal increases in promoter H3K4me3 modification and are transcriptionally de-repressed in Dnmt1-/- MEFs. I suggest that these genes are mostly associated with CpG-rich promoters with low levels of DNA methylation in wildtype cells, implying that their silencing is not dependent on the canonical role of DNA methylation. Consistent with the findings of recently published work, I suggest a working model where PRC2 binding in wildtype cells is restricted by CpG methylation. According to this model, the differential genomic location of K27me3 in hypomethylated Dnmt1-/- MEFs is explained by a redistribution of PRC2 to normally DNA methylated, unbound loci, resulting in a titration effect and coincident loss of K27me3 from normal targets. It was also apparent that certain PRC2-target genes, including the developmentally important Hox gene clusters, are strongly affected in Dnmt1-/- MEFs, displaying striking loss of K27me3. As intergenic transcription has been implicated in relief from polycomb silencing and abundant intergenic transcription has been reported within Hox clusters, I measured RNA expression at Hox clusters and a small number of other PcG target genes in Dnmt1-/- MEFs using highdensity tiling arrays. In Dnmt1-deficient MEFs, widespread increases in intergenic transcription were observed within Hox clusters. In addition, mapping of the elongatingpolymerase- associated H3K36me3 histone modification showed widespread increases in this mark at intergenic and promoter regions in Dnmt1-/- MEFs. Increased local intergenic RNA and H3K36me3 were found to correlate with K27me3 loss for this cohort of genes. I suggest a working model where increased intergenic transcription and H3K36me3 in Dnmt1-/- MEFs leads to accelerated loss of K27me3 at certain loci, including Hox clusters. Taken together with recently published data, this work suggests that a major role of DNA methylation is in shaping the PRC2/K27me3 landscape. The potential implications of this putative role for DNA methylation are widespread, including our knowledge of how DNA methylation influences transcriptional regulation, and the consequence of rearranged DNA methylation patterns that are observed in many diseases including cancers