REDEFINING CpG ISLANDS USING A HIDEEN MARKOV MODEL

The DNA of most vertebrates is depleted in CpG dinucleotides; 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, motive 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 summarized 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 specie are available at http://www.rafalab.org

“Gap hunting” to characterize clustered probe signals in Illumina methylation array data

Additional file 6: Figures S26–S31. All remaining SBE site scenarios. Each additional scenario of a SBE site-mapping SNP delimited in Fig. 4 not including the scenario shown in Fig. 5. Each of these figures contains 4 plots, showing every combination of CpG site interrogations on the forward and reverse strand as well as which nucleotide is the reference nucleotide

Evaluation of techniques for performing cellular isolation and preservation during microgravity conditions

Genomic and epigenomic studies require the precise transfer of microliter volumes among different types of tubes in order to purify DNA, RNA, or protein from biological samples and subsequently perform analyses of DNA methylation, RNA expression, and chromatin modifications on a genome-wide scale. Epigenomic and transcriptional analyses of human blood cells, for example, require separation of purified cell types to avoid confounding contributions of altered cellular proportions, and long-term preservation of these cells requires their isolation and transfer into appropriate freezing media. There are currently no protocols for these cellular isolation procedures on the International Space Station (ISS). Currently human blood samples are either frozen as mixed cell populations (within the CPT collection tubes) with poor yield of viable cells required for cell-type isolations, or returned under ambient conditions, which requires timing with Soyuz missions. Here we evaluate the feasibility of translating terrestrial cell purification techniques to the ISS. Our evaluations were performed in microgravity conditions during parabolic atmospheric flight. The pipetting of open liquids in microgravity was evaluated using analog-blood fluids and several types of pipette hardware. The best-performing pipettors were used to evaluate the pipetting steps required for peripheral blood mononuclear cell (PBMC) isolation following terrestrial density-gradient centrifugation. Evaluation of actual blood products was performed for both the overlay of diluted blood, and the transfer of isolated PBMCs. We also validated magnetic purification of cells. We found that positive-displacement pipettors avoided air bubbles, and the tips allowed the strong surface tension of water, glycerol, and blood to maintain a patent meniscus and withstand robust pipetting in microgravity. These procedures will greatly increase the breadth of research that can be performed on board the ISS, and allow improvised experimentation by astronauts on extraterrestrial missions

Measuring cell-type specific differential methylation in human brain tissue

The behavior of epigenetic mechanisms in the brain is obscured by tissue heterogeneity and disease-related histological changes. Not accounting for these confounders leads to biased results. We develop a statistical methodology that estimates and adjusts for celltype composition by decomposing neuronal and non-neuronal differential signal. This method provides a conceptual framework for deconvolving heterogeneous epigenetic data from postmortem brain studies. We apply it to find cell-specific differentially methylated regions between prefrontal cortex and hippocampus. We demonstrate the utility of the method on both Infinium 450k and CHARM data

Large hypomethylated blocks as a universal defining epigenetic alteration in human solid tumors

Background: One of the most provocative recent observations in cancer epigenetics is the discovery of large hypomethylated blocks, including single copy genes, in colorectal cancer, that correspond in location to heterochromatic LOCKs (large organized chromatin lysine-modifications) and LADs (lamin-associated domains). Methods: Here we performed a comprehensive genome-scale analysis of 10 breast, 28 colon, nine lung, 38 thyroid, 18 pancreas cancers, and five pancreas neuroendocrine tumors as well as matched normal tissue from most of these cases, as well as 51 premalignant lesions. We used a new statistical approach that allows the identification of large hypomethylated blocks on the Illumina HumanMethylation450 BeadChip platform. Results: We find that hypomethylated blocks are a universal feature of common solid human cancer, and that they occur at the earliest stage of premalignant tumors and progress through clinical stages of thyroid and colon cancer development. We also find that the disrupted CpG islands widely reported previously, including hypermethylated island bodies and hypomethylated shores, are enriched in hypomethylated blocks, with flattening of the methylation signal within and flanking the islands. Finally, we found that genes showing higher between individual gene expression variability are enriched within these hypomethylated blocks. Conclusion: Thus hypomethylated blocks appear to be a universal defining epigenetic alteration in human cancer, at least for common solid tumors. Electronic supplementary material The online version of this article (doi:10.1186/s13073-014-0061-y) contains supplementary material, which is available to authorized users

Comprehensive methylome map of lineage commitment from haematopoietic progenitors.

Epigenetic 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

Autism-Associated DNA Methylation at Birth From Multiple Tissues Is Enriched for Autism Genes in the Early Autism Risk Longitudinal Investigation

Background: Pregnancy measures of DNA methylation, an epigenetic mark, may be associated with autism spectrum disorder (ASD) development in children. Few ASD studies have considered prospective designs with DNA methylation measured in multiple tissues and tested overlap with ASD genetic risk loci. Objectives: To estimate associations between DNA methylation in maternal blood, cord blood, and placenta and later diagnosis of ASD, and to evaluate enrichment of ASD-associated DNA methylation for known ASD-associated genes. Methods: In the Early Autism Risk Longitudinal Investigation (EARLI), an ASD-enriched risk birth cohort, genome-scale maternal blood (early n = 140 and late n = 75 pregnancy), infant cord blood (n = 133), and placenta (maternal n = 106 and fetal n = 107 compartments) DNA methylation was assessed on the Illumina 450k HumanMethylation array and compared to ASD diagnosis at 36 months of age. Differences in site-specific and global methylation were tested with ASD, as well as enrichment of single site associations for ASD risk genes (n = 881) from the Simons Foundation Autism Research Initiative (SFARI) database. Results: No individual DNA methylation site was associated with ASD at genome-wide significance, however, individual DNA methylation sites nominally associated with ASD (P < 0.05) in each tissue were highly enriched for SFARI genes (cord blood P = 7.9 × 10-29, maternal blood early pregnancy P = 6.1 × 10-27, maternal blood late pregnancy P = 2.8 × 10-16, maternal placenta P = 5.6 × 10-15, fetal placenta P = 1.3 × 10-20). DNA methylation sites nominally associated with ASD across all five tissues overlapped at 144 (29.5%) SFARI genes. Conclusion: DNA methylation sites nominally associated with later ASD diagnosis in multiple tissues were enriched for ASD risk genes. Our multi-tissue study demonstrates the utility of examining DNA methylation prior to ASD diagnosis

DNA Methylation Signatures within the Human Brain

DNA methylation is a heritable modification of genomic DNA central to development, imprinting, transcriptional regulation, chromatin structure, and overall genomic stability. Aberrant DNA methylation of individual genes is a hallmark of cancer and has been shown to play an important role in neurological disorders such as Rett syndrome. Here, we asked whether normal DNA methylation might distinguish individual brain regions. We determined the quantitative DNA methylation levels of 1,505 CpG sites representing 807 genes with diverse functions, including proliferation and differentiation, previously shown to be implicated in human cancer. We initially analyzed 76 brain samples representing cerebral cortex (n=35), cerebellum (n=34), and pons (n=7), along with liver samples (n=3) from 43 individuals. Unsupervised hierarchical analysis showed clustering of 33 of 35 cerebra distinct from the clustering of 33 of 34 cerebella, 7 of 7 pons, and all 3 livers. By use of comparative marker selection and permutation testing, 156 loci representing 118 genes showed statistically significant differences—a ⩾17% absolute change in DNA methylation (P<.004)—among brain regions. These results were validated for all six genes tested in a replicate set of 57 samples. Our data suggest that DNA methylation signatures distinguish brain regions and may help account for region-specific functional specialization