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Summary: During mammalian embryogenesis, changes in morphology and gene expression are concurrent with epigenomic reprogramming. Using human embryonic stem cells representing the preimplantation blastocyst (naive) and postimplantation epiblast (primed), our data in 2iL/I/F naive cells demonstrate that a substantial portion of known human enhancers are premarked by H3K4me1, providing an enhanced open chromatin state in naive pluripotency. The 2iL/I/F enhancer repertoire occupies 9% of the genome, three times that of primed cells, and can exist in broad chromatin domains over 50 kb. Enhancer chromatin states are largely poised. Seventy-seven percent of 2iL/I/F enhancers are decommissioned in a stepwise manner as cells become primed. While primed topologically associating domains are largely unaltered upon differentiation, naive 2iL/I/F domains expand across primed boundaries, affecting three-dimensional genome architecture. Differential topologically associating domain edges coincide with 2iL/I/F H3K4me1 enrichment. Our results suggest that naive-derived 2iL/I/F cells have a unique chromatin landscape, which may reflect early embryogenesis. : Human ESCs grown in 2iL/I/F are useful for studying the transition from naive to primed pluripotency. Battle et al. show that the naive epigenome is globally enhanced for H3K4me1. Many of the H3K4me1 regions are putative enhancers and are lost, or decommissioned, during the transition to primed. Differential topologically associating domains (TADs) exist between states and contain H3K4me1 enrichment at TAD boundaries. Keywords: enhancers, 3D genome architecture, naive hESCs, embryogenesis

Summary Human bone marrow stromal cells, or mesenchymal stem cells (BM-MSCs), need expansion prior to use as cell-based therapies in immunological and tissue repair applications. Aging and expansion of BM-MSCs induce epigenetic changes that can impact therapeutic outcomes. By applying sequencing-based methods, we reveal that the breadth of DNA methylation dynamics associated with aging and expansion is greater than previously reported. Methylation changes are enriched at known distal transcription factor binding sites such as enhancer elements, instead of CpG-rich regions, and are associated with changes in gene expression. From this, we constructed hypo- and hypermethylation-specific regulatory networks, including a sub-network of BM-MSC master regulators and their predicted target genes, and identified putatively disrupted signaling pathways. Our genome-wide analyses provide a broader overview of age- and expansion-induced DNA methylation changes and a better understanding of the extent to which these changes alter gene expression and functionality of human BM-MSCs., Graphical Abstract, Highlights • Global DNA methylome analysis for human bone marrow mesenchymal stromal cells • Young versus aged adult donors compared at early and late passages • Differential methylation is enriched at distal transcription factor binding sites • These TFBSs are frequently found within BM-MSC enhancers indicated by H3K4me1, Bone marrow MSCs are of great therapeutic interest. Hawkins and colleagues show that sequencing-based approaches to study differential DNA methylation induced by donor age or cell passage reveal more extensive changes than previous array-based studies. These changes are enriched at known transcription factor binding sites within BM-MSC enhancer elements and can be associated with changes in gene expression.

Oocyte maturation is a coordinated process that is tightly linked to reproductive potential. A better understanding of gene regulation during human oocyte maturation will not only answer an important question in biology, but also facilitate the development of in vitro maturation technology as a fertility treatment. We generated single-cell transcriptome and used our previously published single-cell methylome data from human oocytes at different maturation stages to investigate how genes are regulated during oocyte maturation, focusing on the potential regulatory role of non-CpG methylation. DNMT3B, a gene encoding a key non-CpG methylation enzyme, is one of the 1,077 genes upregulated in mature oocytes, which may be at least partially responsible for the increased non-CpG methylation as oocytes mature. Non-CpG differentially methylated regions (DMRs) between mature and immature oocytes have multiple binding motifs for transcription factors, some of which bind with DNMT3B and may be important regulators of oocyte maturation through non-CpG methylation. Over 98% of non-CpG DMRs locate in transposable elements, and these DMRs are correlated with expression changes of the nearby genes. Taken together, this data indicates that global non-CpG hypermethylation during oocyte maturation may play an active role in gene expression regulation, potentially through the interaction with transcription factors.

To reveal how cells exit human pluripotency, we designed a CRISPR-Cas9 screen exploiting the metabolic and epigenetic differences between naïve and primed pluripotent cells. We identify the tumor suppressor, Folliculin(FLCN) as a critical gene required for the exit from human pluripotency. Here we show that FLCN Knock-out (KO) hESCs maintain the naïve pluripotent state but cannot exit the state since the critical transcription factor TFE3 remains active in the nucleus. TFE3 targets up-regulated in FLCN KO exit assay are members of Wnt pathway and ESRRB. Treatment of FLCN KO hESC with a Wnt inhibitor, but not ESRRB/FLCN double mutant, rescues the cells, allowing the exit from the naïve state. Using co-immunoprecipitation and mass spectrometry analysis we identify unique FLCN binding partners. The interactions of FLCN with components of the mTOR pathway (mTORC1 and mTORC2) reveal a mechanism of FLCN function during exit from naïve pluripotency., The pathways involved in exit from pluripotency in human embryonic stem cells are poorly understood. Here, the authors performed a CRISPR-based screen to identify genes that promote exit from naïve pluripotency and find a role for folliculin (FLCN) by regulating the mTOR and Wnt pathways.

For nearly a century developmental biologists have recognized that cells from embryos can differ in their potential to differentiate into distinct cell types. Recently, it has been recognized that embryonic stem cells derived from both mice and humans exhibit two stable yet epigenetically distinct states of pluripotency: naive and primed. We now show that nicotinamide N-methyltransferase (NNMT) and the metabolic state regulate pluripotency in human embryonic stem cells (hESCs). Specifically, in naive hESCs, NNMT and its enzymatic product 1-methylnicotinamide are highly upregulated, and NNMT is required for low S-adenosyl methionine (SAM) levels and the H3K27me3 repressive state. NNMT consumes SAM in naive cells, making it unavailable for histone methylation that represses Wnt and activates the HIF pathway in primed hESCs. These data support the hypothesis that the metabolome regulates the epigenetic landscape of the earliest steps in human development.

Background ChIP-seq is highly utilized for mapping histone modifications that are informative about gene regulation and genome annotations. For example, applying ChIP-seq to histone modifications such as H3K4me1 has facilitated generating epigenomic maps of putative enhancers. This powerful technology, however, is limited in its application by the large number of cells required. ChIP-seq involves extensive manipulation of sample material and multiple reactions with limited quality control at each step, therefore, scaling down the number of cells required has proven challenging. Recently, several methods have been proposed to overcome this limit but most of these methods require extensive optimization to tailor the protocol to the specific antibody used or number of cells being profiled. Results Here we describe a robust, yet facile method, which we named carrier ChIP-seq (cChIP-seq), for use on limited cell amounts. cChIP-seq employs a DNA-free histone carrier in order to maintain the working ChIP reaction scale, removing the need to tailor reactions to specific amounts of cells or histone modifications to be assayed. We have applied our method to three different histone modifications, H3K4me3, H3K4me1 and H3K27me3 in the K562 cell line, and H3K4me1 in H1 hESCs. We successfully obtained epigenomic maps for these histone modifications starting with as few as 10,000 cells. We compared cChIP-seq data to data generated as part of the ENCODE project. ENCODE data are the reference standard in the field and have been generated starting from tens of million of cells. Our results show that cChIP-seq successfully recapitulates bulk data. Furthermore, we showed that the differences observed between small-scale ChIP-seq data and ENCODE data are largely to be due to lab-to-lab variability rather than operating on a reduced scale. Conclusions Data generated using cChIP-seq are equivalent to reference epigenomic maps from three orders of magnitude more cells. Our method offers a robust and straightforward approach to scale down ChIP-seq to as low as 10,000 cells. The underlying principle of our strategy makes it suitable for being applied to a vast range of chromatin modifications without requiring expensive optimization. Furthermore, our strategy of a DNA-free carrier can be adapted to most ChIP-seq protocols. Electronic supplementary material The online version of this article (doi:10.1186/s12864-015-2285-7) contains supplementary material, which is available to authorized users.

Background:Discovering patient subtypes and molecular drivers of a subtype are difficult and driving problems underlying most modern disease expression studies collected across patient populations. Expression patterns conserved across multiple expression datasets from independent disease studies are likely to represent important molecular events underlying the disease.Methods:We present the INSPIRE (INferring Shared modules from multiPle gene expREssion datasets) method to infer highly coherent and robust modules of co-expressed genes and the dependencies among the modules from multiple expression datasets. Focusing on inferring modules and their dependencies conserved across multiple expression datasets is important for several reasons. First, using multiple datasets will increase the power to detect robust and relevant patterns (modules and dependencies among modules). Second, INSPIRE enables the use of multiple datasets that contain different sets of genes due to, e.g., the difference in microarray platforms. Many methods designed for expression data analysis cannot integrate multiple datasets with variable discrepancy to infer a single combined model, whereas INSPIRE can naturally model the dependencies among the modules even when a large proportion of genes are not observed on a certain platform.Results:We evaluated INSPIRE on synthetically generated datasets with known underlying network structure among modules, and gene expression datasets from multiple ovarian cancer studies. We show that the model learned by INSPIRE can explain unseen data better and can reveal prior knowledge on gene functions more accurately than alternative methods. We demonstrate that applying INSPIRE to nine ovarian cancer datasets leads to the identification of a new marker and potential molecular driver of tumor-associated stroma - HOPX. We also demonstrate that the HOPXmodule strongly overlaps with the genes defining the mesenchymal patient subtype identified in The Cancer Genome Atlas (TCGA) ovarian cancer data. We provide evidence for a previously unknown molecular basis of tumor resectability efficacy involving tumor-associated mesenchymal stem cells represented by HOPX.Conclusions:INSPIRE extracts a low-dimensional description from multiple gene expression data, which consists of modules and their dependencies. The discovery of a new tumor-associated stroma marker, HOPX, and its module suggests a previously unknown mechanism underlying tumor-associated stroma.