Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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Dissecting neural differentiation regulatory networks through epigenetic footprinting

ABSTRACT: Human pluripotent stem cell derived models that accurately recapitulate neural development in vitro and allow for the generation of specific neuronal subtypes are of major interest to the stem cell and biomedical community. Notch signaling, particularly through the Notch effector HES5, is a major pathway critical for the onset and maintenance of neural progenitor cells (NPCs) in the embryonic and adult nervous system1-3. Use of a HES5 reporter enables the isolation distinct populations of human embryonic stem (ES) cell derived NPCs that represent building blocks of cortical development in vitro4. Here, we report the transcriptional and epigenomic analysis of six consecutive stages of human ES cell differentiation along the neural lineage aimed at modeling key cell fate decisions including specification, expansion and patterning during the ontogeny of neural stem and progenitor cells. In order to dissect the regulatory mechanisms that orchestrate the stage-specific differentiation process we developed a computational framework to infer key regulators of each cell state transition based on the progressive remodeling of the epigenetic landscape and then validated these through a pooled shRNA screen. We were also able to refine our previous observations on epigenetic priming at transcription factor binding sites and show here that they are mediated by combinations of core and stage-specific factors. Taken together, we demonstrate the utility of our reference maps and outline a general framework, not limited to the context of the neural lineage, to dissect regulatory circuits of differentiation. hESC were differentiated in vitro into 5 different NPC populations (NE, ERG, MRG, LRG and LNP) over a time period of 220 days. The hESCs and the first 3 NPC populations (NE, ERG, MRG) were subjected to ChIP-Seq for H3K4m3, H3K4me1, H3K27ac and H3K27me3 as well as RNA-Seq with two biological replicates each as well as whole genome bisulfite sequencing in singlicate. The last two populations (LRG, LNP) were both profiled by RRBS and the LRG populations also by RNA-Seq. In addition, each of the first three NPC populations were differentiated into more mature neuronal populations (NEdN, ERGdN, MRGdN). The LRG population was differentiated along the astrocyte fate (LRGdA). Each of these more mature populations was subjected to RNA-Seq in replicate. Finally, the NE and MRG populations were profiled for the transcription facctor OTX2 by ChIP-Seq.

ORGANISM(S): Homo sapiens

SUBMITTER: Michael Ziller

PROVIDER: E-GEOD-62193 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:DNA hydroxymethylation (5hmC) represents a new layer of epigenetic regulation in addition to DNA methylation (5mC). The genome-wide patterns of 5hmC distribution in many tissues and cells have recently been revealed by hydroxymethylated DNA immunoprecipitation (hMeDIP) followed by high throughput sequencing or tiling arrays. However, the DNA hydroxymethylome data generated by the conventional hMeDIP-seq method can not be used for direct quantitative comparison across different samples. In this study, we report a new quantitative hMeDIP-seq method, which uses barcode technology to label different DNA samples and performs hMeDIP-seq for multiple samples in one reaction system. Using this new method, we profiled and compared the DNA hydroxymethylomes of mouse ES cells (ESCs) and mouse ESCs-derived neural progenitor cells (NPCs). 5hmC levels around TSS in either ESCs or NPCs had negative correlation with gene expression levels，while 5hmC levels at gene body regions had different correlation with gene expression, depending on cell types. We identified differential hydroxymethylated regions (DHMRs) by comparing the 5hmC density of all 5hmC peaks between ESCs and NPCs. Many selected DHMRs (e.g., Ankrd23, Hist1h2aa, Fbxw7, and Epha2) were validated by hMeDIP-qPCR. Furthermore, we analyzed the relationship between the alteration of DNA hydroxymethylation and the gene expression change during neural differentiation, and our data suggest that both up- and down-regulated genes exhibited dramatic decrease in 5hmC during neural differentiation while the alteration of 5hmC had weak positive correlation with the changes in gene expression. Taken together, our data demonstrate that quantitative hMeDIP-seq is a powerful approach for genome-wide comparison of DNA hydroxymethylation across multiple samples. Importantly, the DHMRs between ESCs and NPCs uncovered in this study may provide clues for further investigation of the function of 5hmC in gene regulation and neural differentiation. Comparision of the genome-wide distribution of 5hmC in mouse embryonic stem cells and mouse ES-derived neural progenitor cells.

Project description:The incorporation of histone H3 variants has been implicated in the epigenetic memory of cellular state. Using genome editing with zinc finger nucleases to tag endogenous H3.3, we report genome-wide profiles of H3 variants in mammalian embryonic stem (ES) cells and neuronal precursor cells. Genome-wide patterns of H3.3 are dependent on amino acid sequence, and change with cellular differentiation at developmentally regulated loci. The H3.3 chaperone Hira is required for H3.3 enrichment at active and repressed genes. Strikingly, Hira is not essential for localization of H3.3 at telomeres and many transcription factor binding sites. Immunoaffinity purification and mass spectrometry reveal that the proteins Atrx and Daxx associate with H3.3 in a Hira-independent manner. Atrx is required for Hira-independent localization of H3.3 at telomeres, and for the repression of telomeric RNA. Our data demonstrate that multiple and distinct factors are responsible for H3.3 localization at specific genomic locations in mammalian cells. Crosslinking ChIP-seq: Examination of 1 histone variant (H3.3), 2 histone modifications, and Serine-5 phosphorylated RNA polymerase in 2 different cell types (H3.3-HA ES samples 1-4, and H3.3-HA NPC samples 7-10). Examination of 1 histone variant (H3.2), and one histone modification (H3K36me3) in 2 different cell types (H3.2-HA ES samples 5-6, and H3.2-HA NPC samples 11-12). Examination of 1 histone variant (H3.3), input control, and one histone modification (H3K36me3) in one cell type (H3.3-HA hybrid ES, samples 13-15). Examination of 1 histone variant (H3.1S31), input control, and one histone modification (H3K36me3) in one cell type (H3.1S31-HA hybrid ES, samples 16-18). Native ChIP-seq: Examination of 1 histone variant (H3.3), input control, and one histone modification (H3K4me3) in one cell type (H3.3-HA ES, samples 19-21). Examination of 1 histone variant (H3.2), input control, and two histone modifications (H3K4me3 and H3K27me3) in one cell type (H3.2-HA ES, samples 22-25). Examination of 1 histone variant (H3.3), input control, and two histone modifications (H3K4me1 and H3K36me3) in one cell type (H3.3-EYFP ES, samples 26-29). Examination of 1 histone variant (H3.3), input control, and two histone modifications (H3K4me1 and H3K36me3) in one cell type (Hira -/- H3.3-EYFP ES, samples 30-33). Examination of 1 histone variant (H3.3) and input control in one cell type (Atrxflox H3.3-EYFP ES, samples 34-37). Examination of HA antibody background in one cell type (wild-type ES, sample 38).

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Dissecting neural differentiation regulatory networks through epigenetic footprinting

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