bioRxivDevelopmental BiologyPreprint
Epigenetic change induced by in utero dietary challenge provokes phenotypic variability across multiple generations of mice
Mathew Van de PetteiD, António Miguel GalvãoiD, Steven J. MillershipiD, Wilson To, Andrew DimondiD, Chiara Prodani, Gráinne I. McNamaraiD, Ludovica BrunoiD, Alessandro SardiniiD, Zoë WebsteriD, James McGintyiD, P. M. W. FrenchiD, Anthony G. UreniD, Juan Castillo FernandeziD, Rosalind M. JohniD, Anne C. Ferguson‐SmithiD, Matthias MerkenschlageriD, Gavin KelseyiD, Amanda G. FisheriD
Abstract
Transmission of epigenetic information between generations occurs in nematodes, flies and plants, mediated by specialised small RNA pathways, histone H3K9me3, H3K27me3, H4K16ac and DNA methylation1-3. In higher vertebrates, epidemiological and experimental evidence supports similar trans-generational effects4,5 although the mechanisms that underpin these are incompletely understood6-9. We generated a luciferase reporter knock-in mouse for the imprinted Dlk1 locus, to visualise and track epigenetic fidelity across generations. We showed that exposure to high-fat diet (HFD) in pregnancy provokes sustained re-expression of the normally silent maternal Dlk1 allele in offspring, coincident with increased DNA methylation at the Dlk1 sDMR. Interestingly, maternal Dlk1 mis-expression was also evident in the next generation (F2), exclusively in animals derived from F1-exposed females. Oocytes from these females showed altered microRNA and gene expression, without any major changes in underlying DNA methylation, and correctly imprinted Dlk1 expression resumed in subsequent generations (F3 onwards). Our results reveal how canonical and non-canonical imprinting mechanisms enable the foetal epigenome to adapt to in utero challenge to modulate the properties of two successive generations of offspring.
- organism: mouse
- assay: DNA methylation
- assay: multiome
- research focus: gene regulatory network inference
- research focus: differential expression
- research focus: cell type annotation
- approach: statistical model
- approach: experimental assay
- Citations
- 2
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