How Does Reprogramming to Pluripotency Affect Genomic Imprinting?

Human induced Pluripotent Stem Cells (hiPSCs) have the capacity to generate a wide range of somatic cells, thus representing an ideal tool for regenerative medicine. Patient-derived hiPSCs are also used for in vitro disease modeling and drug screenings. Several studies focused on the identification of DNA mutations generated, or selected, during the derivation of hiPSCs, some of which are known to drive cancer formation. Avoiding such stable genomic aberrations is paramount for successful use of hiPSCs, but it is equally important to ensure that their epigenetic information is correct, given the critical role of epigenetics in transcriptional regulation and its involvement in a plethora of pathologic conditions. In this review we will focus on genomic imprinting, a prototypical epigenetic mechanism whereby a gene is expressed in a parent-of-origin specific manner, thanks to the differential methylation of specific DNA sequences. Conventional hiPSCs are thought to be in a pluripotent state primed for differentiation. They display a hypermethylated genome with an unexpected loss of DNA methylation at imprinted loci. Several groups recently reported the generation of hiPSCs in a more primitive developmental stage, called naïve pluripotency. Naïve hiPSCs share several features with early human embryos, such as a global genome hypomethylation, which is also accompanied by a widespread loss of DNA methylation at imprinted loci. Given that loss of imprinting has been observed in genetic developmental disorders as well as in a wide range of cancers, it is fundamental to make sure that hiPSCs do not show such epigenetic aberrations. We will discuss what specific imprinted genes, associated with human pathologies, have been found commonly misregulated in hiPSCs and suggest strategies to effectively detect and avoid such undesirable epigenetic abnormalities

A Method to Identify and Analyze Biological Programs through Automated Reasoning.

Predictive biology is elusive because rigorous, data-constrained, mechanistic models of complex biological systems are difficult to derive and validate. Current approaches tend to construct and examine static interaction network models, which are descriptively rich but often lack explanatory and predictive power, or dynamic models that can be simulated to reproduce known behavior. However, in such approaches implicit assumptions are introduced as typically only one mechanism is considered, and exhaustively investigating all scenarios is impractical using simulation. To address these limitations, we present a methodology based on automated formal reasoning, which permits the synthesis and analysis of the complete set of logical models consistent with experimental observations. We test hypotheses against all candidate models, and remove the need for simulation by characterizing and simultaneously analyzing all mechanistic explanations of observed behavior. Our methodology transforms knowledge of complex biological processes from sets of possible interactions and experimental observations to precise, predictive biological programs governing cell function

Stat3 promotes mitochondrial transcription and oxidative respiration during maintenance and induction of naive pluripotency.

Transcription factor Stat3 directs self-renewal of pluripotent mouse embryonic stem (ES) cells downstream of the cytokine leukemia inhibitory factor (LIF). Stat3 upregulates pivotal transcription factors in the ES cell gene regulatory network to sustain naïve identity. Stat3 also contributes to the rapid proliferation of ES cells. Here, we show that Stat3 increases the expression of mitochondrial-encoded transcripts and enhances oxidative metabolism. Chromatin immunoprecipitation reveals that Stat3 binds to the mitochondrial genome, consistent with direct transcriptional regulation. An engineered form of Stat3 that localizes predominantly to mitochondria is sufficient to support enhanced proliferation of ES cells, but not to maintain their undifferentiated phenotype. Furthermore, during reprogramming from primed to naïve states of pluripotency, Stat3 similarly upregulates mitochondrial transcripts and facilitates metabolic resetting. These findings suggest that the potent stimulation of naïve pluripotency by LIF/Stat3 is attributable to parallel and synergistic induction of both mitochondrial respiration and nuclear transcription factors.GM’s laboratory is supported by grants from Armenise-Harvard Foundation and Telethon Foundation (TCP13013). The Cambridge Stem Cell Institute receives core funding from the Wellcome Trust and Medical Research Council. GM was supported by a Human Frontier Science Program Fellowship. AS is a Medical Research Professor.This is the final version of the article. It first appeared from Wiley via http://dx.doi.org/10.15252/embj.20159262

ESRRB Is a Pivotal Target of the Gsk3/Tcf3 Axis Regulating Embryonic Stem Cell Self-Renewal

博士（医学）神戸大

BrewerIX enables allelic expression analysis of imprinted and X-linked genes from bulk and single-cell transcriptomes

Genomic imprinting and X chromosome inactivation (XCI) are two prototypical epigenetic mechanisms whereby a set of genes is expressed mono-allelically in order to fine-tune their expression levels. Defects in genomic imprinting have been observed in several neurodevelopmental disorders, in a wide range of tumours and in induced pluripotent stem cells (iPSCs). Single Nucleotide Variants (SNVs) are readily detectable by RNA-sequencing allowing the determination of whether imprinted or X-linked genes are aberrantly expressed from both alleles, although standardised analysis methods are still missing. We have developed a tool, named BrewerIX, that provides comprehensive information about the allelic expression of a large, manually-curated set of imprinted and X-linked genes. BrewerIX does not require programming skills, runs on a standard personal computer, and can analyze both bulk and single-cell transcriptomes of human and mouse cells directly from raw sequencing data. BrewerIX confirmed previous observations regarding the bi-allelic expression of some imprinted genes in naive pluripotent cells and extended them to preimplantation embryos. BrewerIX also identified misregulated imprinted genes in breast cancer cells and in human organoids and identified genes escaping XCI in human somatic cells. We believe BrewerIX will be useful for the study of genomic imprinting and XCI during development and reprogramming, and for detecting aberrations in cancer, iPSCs and organoids. Due to its ease of use to non-computational biologists, its implementation could become standard practice during sample assessment, thus raising the robustness and reproducibility of future studies

A Method to Identify and Analyze Biological Programs through Automated Reasoning.

Predictive biology is elusive because rigorous, data-constrained, mechanistic models of complex biological systems are difficult to derive and validate. Current approaches tend to construct and examine static interaction network models, which are descriptively rich but often lack explanatory and predictive power, or dynamic models that can be simulated to reproduce known behavior. However, in such approaches implicit assumptions are introduced as typically only one mechanism is considered, and exhaustively investigating all scenarios is impractical using simulation. To address these limitations, we present a methodology based on automated formal reasoning, which permits the synthesis and analysis of the complete set of logical models consistent with experimental observations. We test hypotheses against all candidate models, and remove the need for simulation by characterizing and simultaneously analyzing all mechanistic explanations of observed behavior. Our methodology transforms knowledge of complex biological processes from sets of possible interactions and experimental observations to precise, predictive biological programs governing cell function.G.M. holds a career development award from the Armenise Harvard foundation, and a Telethon-DTI career award. A.G.S. is a Medical Research Council Professor

Metabolic control of DNA methylation in naive pluripotent cells.

Naive epiblast and embryonic stem cells (ESCs) give rise to all cells of adults. Such developmental plasticity is associated with genome hypomethylation. Here, we show that LIF-Stat3 signaling induces genomic hypomethylation via metabolic reconfiguration. Stat3-/- ESCs show decreased α-ketoglutarate production from glutamine, leading to increased Dnmt3a and Dnmt3b expression and DNA methylation. Notably, genome methylation is dynamically controlled through modulation of α-ketoglutarate availability or Stat3 activation in mitochondria. Alpha-ketoglutarate links metabolism to the epigenome by reducing the expression of Otx2 and its targets Dnmt3a and Dnmt3b. Genetic inactivation of Otx2 or Dnmt3a and Dnmt3b results in genomic hypomethylation even in the absence of active LIF-Stat3. Stat3-/- ESCs show increased methylation at imprinting control regions and altered expression of cognate transcripts. Single-cell analyses of Stat3-/- embryos confirmed the dysregulated expression of Otx2, Dnmt3a and Dnmt3b as well as imprinted genes. Several cancers display Stat3 overactivation and abnormal DNA methylation; therefore, the molecular module that we describe might be exploited under pathological conditions

Metabolic control of DNA methylation in naive pluripotent cells.

Naive epiblast and embryonic stem cells (ESCs) give rise to all cells of adults. Such developmental plasticity is associated with genome hypomethylation. Here, we show that LIF-Stat3 signaling induces genomic hypomethylation via metabolic reconfiguration. Stat3-/- ESCs show decreased α-ketoglutarate production from glutamine, leading to increased Dnmt3a and Dnmt3b expression and DNA methylation. Notably, genome methylation is dynamically controlled through modulation of α-ketoglutarate availability or Stat3 activation in mitochondria. Alpha-ketoglutarate links metabolism to the epigenome by reducing the expression of Otx2 and its targets Dnmt3a and Dnmt3b. Genetic inactivation of Otx2 or Dnmt3a and Dnmt3b results in genomic hypomethylation even in the absence of active LIF-Stat3. Stat3-/- ESCs show increased methylation at imprinting control regions and altered expression of cognate transcripts. Single-cell analyses of Stat3-/- embryos confirmed the dysregulated expression of Otx2, Dnmt3a and Dnmt3b as well as imprinted genes. Several cancers display Stat3 overactivation and abnormal DNA methylation; therefore, the molecular module that we describe might be exploited under pathological conditions