E-GEOD-48256 - Developmental establishment of DNA methylation in hypothalamic neurons and glia
Released on 1 October 2013, last updated on 25 November 2013
Human epidemiologic and animal model data indicate that early environmental influences can persistently alter an individual’s risk of obesity. Environmental effects on hypothalamic developmental epigenetics provide a strong candidate mechanism to explain such ‘developmental programming’ of obesity. To advance our understanding of these processes, it is essential to determine to what extent the diversity of hypothalamic cell types is regulated by epigenetic differences, and when these are established. By performing genome-scale DNA methylation profiling in hypothalamic neurons and non-neuronal cells at postnatal day 0 (P0) and P21, we found that most of the DNA methylation differences distinguishing these two cell types are established postnatally. We found dramatic neuron-specific increases in DNA methylation from P0 to P21. Gene ontology analyses indicated that cell-type specific P0 to P21 methylation changes are key regulators of hypothalamic development. Quantitative bisulfite pyrosequencing verified our methylation profiling results in 16 of 16 selected regions. Expression differences were associated with DNA methylation in several genes analyzed. Our data indicate that future studies of hypothalamic epigenetics in developmental programming of obesity will gain far greater sensitivity and insight by examining outcomes at the cell-type specific level. Moreover, our results provide new evidence that early postnatal life is a critical period for murine hypothalamic developmental epigenetics. Hypothalami were dissected from inbred male C57 mice at postnatal day 0 (P0) and P21. Non-neuronal and neuronal nuclei were separated via fluorescence-activated sorting based on staining for the neuron-specific nuclear surface marker NeuN; each sample for sorting was comprised of 2 age-matched hypothalami. Genome-scale DNA methylation profiling was performed by methylation specific amplification coupled with next generation sequencing (MSA-seq) as decribed below (5 independent samples per age).
methylation profiling by high throughput sequencing
Ge Li, Govindarajan K Ramamoorthy, Robert A Waterland