bioRxivGenomicsPreprint
Nucleosome dynamics of human iPSC during the early stages of neurodevelopment
Janet C HarwoodiD, Nicholas A. KentiD, Nicholas D. AlleniD, Adrian J. HarwoodiD
Abstract
Regulation of nucleosome positioning is important for neurodevelopment, and mutation of genes mediating chromatin remodelling are strongly associated with human neurodevelopmental disorders. Unicellular organisms possess arrays of highly positioned nucleosomes within their chromatin, occupying up to 80% of their genomes. These span gene-coding and regulatory regions, and can be associated with local changes of gene transcription. In the much larger genome of human cells, the roles of nucleosome positioning are less clear, and this raises questions of how nucleosome dynamics interfaces with human neurodevelopment.\n\nWe have generated genome-wide nucleosome maps from an undifferentiated human induced pluripotent stem cell (hiPSC) line and after its differentiation to the neuronal progenitor cell (NPC) stage. We found that approximately 3% of nucleosomes are highly positioned in NPC. In contrast, there are 8-fold less positioned nucleosomes in pluripotent cells, with the majority arising de novo or relocating during cell differentiation. Positioned nucleosomes do not directly correlate with active chromatin or gene transcription, such as marking Transcriptional Start Sites (TSS). Unexpectedly, we find a small population of nucleosomes that remain positioned after differentiation, occupying similar positions in pluripotent and NPC cells. They flank the binding sites of the key gene regulators NRSF/REST and CTCF, but remain in place whether or not their regulatory complexes are present. Together, these results present an alternative view in human cells, where positioned nucleosomes are sparse and dynamic, but act to alter gene expression at a distance via structural conformation at sites of chromatin regulation, not local changes in gene organisation.
- organism: human
- assay: DNA methylation
- assay: ChIP-seq
- research focus: gene regulatory network inference
- research focus: differential expression
- research focus: spatial domain detection
- approach: statistical model
- Citations
- 1
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