methylKit: a comprehensive R package for the analysis of genome-wide DNA methylation profiles

DNA methylation is a chemical modification of cytosine bases that is pivotal for gene regulation, cellular specification and cancer development. Here, we describe an R package, methylKit, that rapidly analyzes genome-wide cytosine epigenetic profiles from high-throughput methylation and hydroxymethylation sequencing experiments. methylKit includes functions for clustering, sample quality visualization, differential methylation analysis and annotation features, thus automating and simplifying many of the steps for discerning statistically significant bases or regions of DNA methylation. Finally, we demonstrate methylKit on breast cancer data, in which we find statistically significant regions of differential methylation and stratify tumor subtypes. methylKit is available at http://code.google.com/p/methylkit

Effects of Spaceflight on Human Induced Pluripotent Stem Cell-Derived Cardiomyocyte Structure and Function.

With extended stays aboard the International Space Station (ISS) becoming commonplace, there is a need to better understand the effects of microgravity on cardiac function. We utilized human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) to study the effects of microgravity on cell-level cardiac function and gene expression. The hiPSC-CMs were cultured aboard the ISS for 5.5 weeks and their gene expression, structure, and functions were compared with ground control hiPSC-CMs. Exposure to microgravity on the ISS caused alterations in hiPSC-CM calcium handling. RNA-sequencing analysis demonstrated that 2,635 genes were differentially expressed among flight, post-flight, and ground control samples, including genes involved in mitochondrial metabolism. This study represents the first use of hiPSC technology to model the effects of spaceflight on human cardiomyocyte structure and function

An optimized algorithm for detecting and annotating regional differential methylation

Background: DNA methylation profiling reveals important differentially methylated regions (DMRs) of the genome that are altered during development or that are perturbed by disease. To date, few programs exist for regional analysis of enriched or whole-genome bisulfate conversion sequencing data, even though such data are increasingly common. Here, we describe an open-source, optimized method for determining empirically based DMRs (eDMR) from high-throughput sequence data that is applicable to enriched whole-genome methylation profiling datasets, as well as other globally enriched epigenetic modification data. Results: Here we show that our bimodal distribution model and weighted cost function for optimized regional methylation analysis provides accurate boundaries of regions harboring significant epigenetic modifications. Our algorithm takes the spatial distribution of CpGs into account for the enrichment assay, allowing for optimization of the definition of empirical regions for differential methylation. Combined with the dependent adjustment for regional p-value combination and DMR annotation, we provide a method that may be applied to a variety of datasets for rapid DMR analysis. Our method classifies both the directionality of DMRs and their genome-wide distribution, and we have observed that shows clinical relevance through correct stratification of two Acute Myeloid Leukemia (AML) tumor sub-types. Conclusions: Our weighted optimization algorithm eDMR for calling DMRs extends an established DMR R pipeline (methylKit) and provides a needed resource in epigenomics. Our method enables an accurate and scalable way of finding DMRs in high-throughput methylation sequencing experiments. eDMR is available for download at http://code.google.com/p/edmr/.Sheng Li, Francine E Garrett-Bakelman, Altuna Akalin, Paul Zumbo, Ross Levine, Bik L To, Ian D Lewis, Anna L Brown, Richard J D’Andrea, Ari Melnick, Christopher E Maso

Dynamic evolution of clonal epialleles revealed by methclone

We describe methclone, a novel method to identify epigenetic loci that harbor large changes in the clonality of their epialleles (epigenetic alleles). Methclone efficiently analyzes genome-wide DNA methylation sequencing data. We quantify the changes using a composition entropy difference calculation and also introduce a new measure of global clonality shift, loci with epiallele shift per million loci covered, which enables comparisons between different samples to gauge overall epiallelic dynamics. Finally, we demonstrate the utility of methclone in capturing functional epiallele shifts in leukemia patients from diagnosis to relapse. Methclone is open-source and freely available at https://code.google.com/p/methclone.Sheng Li, Francine Garrett-Bakelman, Alexander E Perl, Selina M Luger, Chao Zhang, Bik L To, Ian D Lewis, Anna L Brown, Richard J D’Andrea, M Elizabeth Ross, Ross Levine, Martin Carroll, Ari Melnick, and Christopher E Maso

Global meta‐analysis of over 50 years of multidisciplinary and international collaborations on transmissible cancers

International audienceAlthough transmissible cancers have, so far, only been documented in three independent animal groups, they not only impact animals that have high economic, environmental and social significance, but they are also one of the most virulent parasitic life forms. Currently known transmissible cancers traverse terrestrial and marine environments, and are predicted to be more widely distributed across animal groups; thus, the implementation of effective collaborative scientific networks is important for combating existing and emerging forms. Here, we quantify how collaborative effort on the three known transmissible cancers has advanced through the formation of collaborative networks among institutions and disciplines. These three cancers occur in bivalves (invertebrates—disseminated neoplasia; DN), Tasmanian devils (vertebrate—marsupial; devil facial tumour disease; DFTD) and dogs (vertebrate—eutherian mammal; canine transmissible venereal tumour; CTVT). Research on CTVT and DN has been conducted since 1876 and 1969, respectively, whereas systematic research on DFTD only started in 2006. Yet, collaborative effort on all three diseases is global, encompassing six major Scopus subject areas. Collaborations steadily increased between 1963 and 2006 for CTVT and DN, with similar acceleration for all three cancers since 2006. Network analyses demonstrated that scientists are organizing themselves into efficient collaborative networks; however, these networks appear to be far stronger for DFTD and DN, possibly due to the recent detection of new strains adding impetus to research and associated publications (enhancing citation trajectories). In particular, global and multidisciplinary collaborations formed almost immediately after DFTD research was initiated, leading to similar research effort and relatively greater research outputs compared to the other two diseases. Therefore, in the event of outbreaks of new lineages of existing transmissible cancers, or the discovery of new transmissible cancers in the future, the rapid formation of international collaborations spanning relevant disciplines is vital for the efficient management of these diseases

An Esrrb and nanog cell fate regulatory module controlled by feed forward loop interactions

Cell fate decisions during development are governed by multi-factorial regulatory mechanisms including chromatin remodeling, DNA methylation, binding of transcription factors to specific loci, RNA transcription and protein synthesis. However, the mechanisms by which such regulatory 'dimensions' coordinate cell fate decisions are currently poorly understood. Here we quantified the multi-dimensional molecular changes that occur in mouse embryonic stem cells (mESCs) upon depletion of Estrogen related receptor beta (Esrrb), a key pluripotency regulator. Comparative analyses of expression changes subsequent to depletion of Esrrb or Nanog, indicated that a system of interlocked feed-forward loops involving both factors, plays a central part in regulating the timing of mESC fate decisions. Taken together, our meta-analyses support a hierarchical model in which pluripotency is maintained by an Oct4-Sox2 regulatory module, while the timing of differentiation is regulated by a Nanog-Esrrb module

DNA methylation landscapes of 1538 breast cancers reveal a replication-linked clock, epigenomic instability and cis-regulation.

DNA methylation is aberrant in cancer, but the dynamics, regulatory role and clinical implications of such epigenetic changes are still poorly understood. Here, reduced representation bisulfite sequencing (RRBS) profiles of 1538 breast tumors and 244 normal breast tissues from the METABRIC cohort are reported, facilitating detailed analysis of DNA methylation within a rich context of genomic, transcriptional, and clinical data. Tumor methylation from immune and stromal signatures are deconvoluted leading to the discovery of a tumor replication-linked clock with genome-wide methylation loss in non-CpG island sites. Unexpectedly, methylation in most tumor CpG islands follows two replication-independent processes of gain (MG) or loss (ML) that we term epigenomic instability. Epigenomic instability is correlated with tumor grade and stage, TP53 mutations and poorer prognosis. After controlling for these global trans-acting trends, as well as for X-linked dosage compensation effects, cis-specific methylation and expression correlations are uncovered at hundreds of promoters and over a thousand distal elements. Some of these targeted known tumor suppressors and oncogenes. In conclusion, this study demonstrates that global epigenetic instability can erode cancer methylomes and expose them to localized methylation aberrations in-cis resulting in transcriptional changes seen in tumors