Gilles Gasparoni

Human cytomegalovirus drives epigenetic imprinting of the IFNG locus in NKG2Chi natural killer cells.

Memory type 1 T helper (TH1) cells are characterized by the stable expression of interferon (IFN)-γ as well as by the epigenetic imprinting of the IFNG locus. Among innate cells, NK cells play a crucial role in the defense against cytomegalovirus (CMV) and represent the main source of IFN-γ. Recently, it was shown that memory-like features can be observed in NK cell subsets after CMV infection. However, the molecular mechanisms underlying NK cell adaptive properties have not been completely defined. In the present study, we demonstrated that only NKG2Chi NK cells expanded in human CMV (HCMV) seropositive individuals underwent epigenetic remodeling of the IFNG conserved non-coding sequence (CNS) 1, similar to memory CD8+ T cells or TH1 cells. The accessibility of the CNS1 was required to enhance IFN-γ transcriptional activity in response to NKG2C and 2B4 engagement, which led to consistent IFN-γ production in NKG2Chi NK cells. Thus, our data identify epigenetic imprinting of the IFNG locus as selective hallmark and crucial mechanism driving strong and stable IFN-γ expression in HCMV-specific NK cell expansions, providing a molecular basis for the regulation of adaptive features in innate cells.

Adult monozygotic twins discordant for intra-uterine growth have indistinguishable genome-wide DNA methylation profiles

BackgroundLow birth weight is associated with an increased adult metabolic disease risk. It is widely discussed that poor intra-uterine conditions could induce long-lasting epigenetic modifications, leading to systemic changes in regulation of metabolic genes. To address this, we acquire genome-wide DNA methylation profiles from saliva DNA in a unique cohort of 17 monozygotic monochorionic female twins very discordant for birth weight. We examine if adverse prenatal growth conditions experienced by the smaller co-twins lead to long-lasting DNA methylation changes.ResultsOverall, co-twins show very similar genome-wide DNA methylation profiles. Since observed differences are almost exclusively caused by variable cellular composition, an original marker-based adjustment strategy was developed to eliminate such variation at affected CpGs. Among adjusted and unchanged CpGs 3,153 are differentially methylated between the heavy and light co-twins at nominal significance, of which 45 show sensible absolute mean β-value differences. Deep bisulfite sequencing of eight such loci reveals that differences remain in the range of technical variation, arguing against a reproducible biological effect. Analysis of methylation in repetitive elements using methylation-dependent primer extension assays also indicates no significant intra-pair differences.ConclusionsSevere intra-uterine growth differences observed within these monozygotic twins are not associated with long-lasting DNA methylation differences in cells composing saliva, detectable with up-to-date technologies. Additionally, our results indicate that uneven cell type composition can lead to spurious results and should be addressed in epigenomic studies.

reChIP-seq reveals widespread bivalency of H3K4me3 and H3K27me3 in CD4(+) memory T cells.

The combinatorial action of co-localizing chromatin modifications and regulators determines chromatin structure and function. However, identifying co-localizing chromatin features in a high-throughput manner remains a technical challenge. Here we describe a novel reChIP-seq approach and tailored bioinformatic analysis tool, normR that allows for the sequential enrichment and detection of co-localizing DNA-associated proteins in an unbiased and genome-wide manner. We illustrate the utility of the reChIP-seq method and normR by identifying H3K4me3 or H3K27me3 bivalently modified nucleosomes in primary human CD4+ memory T cells. We unravel widespread bivalency at hypomethylated CpG-islands coinciding with inactive promoters of developmental regulators. reChIP-seq additionally uncovered heterogeneous bivalency in the population, which was undetectable by intersecting H3K4me3 and H3K27me3 ChIP-seq tracks. Finally, we provide evidence that bivalency is established and stabilized by an interplay between the genome and epigenome. Our reChIP-seq approach augments conventional ChIP-seq and is broadly applicable to unravel combinatorial modes of action.

Epigenetic dynamics of monocyte-to-macrophage differentiation

BackgroundMonocyte-to-macrophage differentiation involves major biochemical and structural changes. In order to elucidate the role of gene regulatory changes during this process, we used high-throughput sequencing to analyze the complete transcriptome and epigenome of human monocytes that were differentiated in vitro by addition of colony-stimulating factor 1 in serum-free medium.ResultsNumerous mRNAs and miRNAs were significantly up- or down-regulated. More than 100 discrete DNA regions, most often far away from transcription start sites, were rapidly demethylated by the ten eleven translocation enzymes, became nucleosome-free and gained histone marks indicative of active enhancers. These regions were unique for macrophages and associated with genes involved in the regulation of the actin cytoskeleton, phagocytosis and innate immune response.ConclusionsIn summary, we have discovered a phagocytic gene network that is repressed by DNA methylation in monocytes and rapidly de-repressed after the onset of macrophage differentiation.

Combining transcription factor binding affinities with open-chromatin data for accurate gene expression prediction

The binding and contribution of transcription factors (TF) to cell specific gene expression is often deduced from open-chromatin measurements to avoid costly TF ChIP-seq assays. Thus, it is important to develop computational methods for accurate TF binding prediction in open-chromatin regions (OCRs). Here, we report a novel segmentation-based method, TEPIC, to predict TF binding by combining sets of OCRs with position weight matrices. TEPIC can be applied to various open-chromatin data, e.g. DNaseI-seq and NOMe-seq. Additionally, Histone-Marks (HMs) can be used to identify candidate TF binding sites. TEPIC computes TF affinities and uses open-chromatin/HM signal intensity as quantitative measures of TF binding strength. Using machine learning, we find low affinity binding sites to improve our ability to explain gene expression variability compared to the standard presence/absence classification of binding sites. Further, we show that both footprints and peaks capture essential TF binding events and lead to a good prediction performance. In our application, gene-based scores computed by TEPIC with one open-chromatin assay nearly reach the quality of several TF ChIP-seq data sets. Finally, these scores correctly predict known transcriptional regulators as illustrated by the application to novel DNaseI-seq and NOMe-seq data for primary human hepatocytes and CD4+ T-cells, respectively.

The miRNome of Alzheimer's disease: consistent downregulation of the miR-132/212 cluster

MicroRNAs (miRNAs) are small noncoding RNA molecules, with essential functions in RNA silencing and post-transcriptional regulation of gene expression. miRNAs appear to regulate the development and function of the nervous system. Alterations of miRNA expression have been associated with Alzheimers disease (AD). To characterize the AD miRNA signature, we examined genome-wide miRNA and mRNA expression patterns in the temporal cortex of AD and control samples. We validated our miRNA results by semiquantitative real-time polymerase chain reaction (PCR) in independent prefrontal cortex. Furthermore, we separated gray and white matter brain sections to identify the cellular origin of the altered miRNA expression. We observed genome-wide downregulation of hsa-miR-132-3p and hsa-miR-212-3p in AD with a stronger decrease in gray matter AD samples. We further identified 10 differently expressed transcripts achieving genome-wide levels of significance. Significantly deregulated miRNAs and mRNAs were correlated and examined for potential binding sites (in silico). This miRNome-wide study in AD provides supportive evidence and corroborates an important contribution of miR-132/212 and corresponding target mRNAs to the pathogenesis of AD.

MeDeCom: discovery and quantification of latent components of heterogeneous methylomes

It is important for large-scale epigenomic studies to determine and explore the nature of hidden confounding variation, most importantly cell composition. We developed MeDeCom as a novel reference-free computational framework that allows the decomposition of complex DNA methylomes into latent methylation components and their proportions in each sample. MeDeCom is based on constrained non-negative matrix factorization with a new biologically motivated regularization function. It accurately recovers cell-type-specific latent methylation components and their proportions. MeDeCom is a new unsupervised tool for the exploratory study of the major sources of methylation variation, which should lead to a deeper understanding and better biological interpretation.

Peptide-specific recognition of human cytomegalovirus strains controls adaptive natural killer cells

Natural killer (NK) cells are innate lymphocytes that lack antigen-specific rearranged receptors, a hallmark of adaptive lymphocytes. In some people infected with human cytomegalovirus (HCMV), an NK cell subset expressing the activating receptor NKG2C undergoes clonal-like expansion that partially resembles anti-viral adaptive responses. However, the viral ligand that drives the activation and differentiation of adaptive NKG2C+ NK cells has remained unclear. Here we found that adaptive NKG2C+ NK cells differentially recognized distinct HCMV strains encoding variable UL40 peptides that, in combination with pro-inflammatory signals, controlled the population expansion and differentiation of adaptive NKG2C+ NK cells. Thus, we propose that polymorphic HCMV peptides contribute to shaping of the heterogeneity of adaptive NKG2C+ NK cell populations among HCMV-seropositive people.NK cells constrain infection by cytomegalovirus. Romagnani and colleagues show that human NKG2C+ NK cells recognize distinct HCMV UL40 viral peptides, which can vary among viral isolates. NKG2C+ NK cells thereby demonstrate adaptive-like recognition that can discriminate between closely related viral strains.

The Begain gene marks the centromeric boundary of the imprinted region on mouse chromosome 12

Although the central portion of the imprinted region on mouse chromosome 12 has been intensively analysed in the past, little is known about the neighbouring centromeric genes. A DNA sequence comparison shows that the region upstream of Dlk1 and Gtl2 is dominated by an expanded cluster of repetitive elements in the mouse. These elements separate the paternally expressed Dlk1 gene from the centromeric Begain gene. Despite the long physical distance to the IG-DMR imprinting centre, Begain is subjected to genomic imprinting. Similar to the ovine Begain gene, the homologous mouse gene encodes two different transcript variants, one of which shows a strong bias toward paternal transcription. Nevertheless, imprinting effects do not spread further centromeric to the Wdr25 gene, which is biallelically expressed as the previously studied neighbouring Wars and Yy1 genes.

Molecular Plasticity of Male and Female Murine Gonadotropes Revealed by mRNA Sequencing

Gonadotropes in the anterior pituitary gland are of particular importance within the hypothalamic-pituitary-gonadal axis because they provide a means of communication and thus a functional link between the brain and the gonads. Recent results indicate that female gonadotropes may be organized in the form of a network that shows plasticity and adapts to the altered endocrine conditions of different physiological states. However, little is known about functional changes on the molecular level within gonadotropes during these different conditions. In this study we capitalize on a binary genetic strategy in order to fluorescently label murine gonadotrope cells. Using this mouse model allows to produce an enriched gonadotrope population using fluorescence activated cell sorting to perform mRNA sequencing. By using this strategy, we analyze and compare the expression profile of murine gonadotropes in different genders and developmental and hormonal stages. We find that gonadotropes taken from juvenile males and females, from cycling females at diestrus and at proestrus, from lactating females, and from adult males each have unique gene expression patterns with approximately 100 to approximately 500 genes expressed only in one particular stage. We also demonstrate extensive gene-expression profile changes with up to approximately 2200 differentially expressed genes when comparing female and male development, juveniles and adults, and cycling females. Differentially expressed genes were significantly enriched in the GnRH signaling, calcium signaling, and MAPK signaling pathways by Kyoto Encyclopedia of Genes and Genomes analysis. Our data provide an unprecedented molecular view of the primary gonadotropes and reveal a high degree of molecular plasticity within the gonadotrope population.