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Early-life nutrition modulates the epigenetic state of specific rDNA genetic variants in mice.

Accepted version
Peer-reviewed

Type

Article

Change log

Authors

Holland, Michelle L 
Lowe, Robert 
Caton, Paul W 
Gemma, Carolina 
Carbajosa, Guillermo 

Abstract

A suboptimal early-life environment, due to poor nutrition or stress during pregnancy, can influence lifelong phenotypes in the progeny. Epigenetic factors are thought to be key mediators of these effects. We show that protein restriction in mice from conception until weaning induces a linear correlation between growth restriction and DNA methylation at ribosomal DNA (rDNA). This epigenetic response remains into adulthood and is restricted to rDNA copies associated with a specific genetic variant within the promoter. Related effects are also found in models of maternal high-fat or obesogenic diets. Our work identifies environmentally induced epigenetic dynamics that are dependent on underlying genetic variation and establishes rDNA as a genomic target of nutritional insults.

Description

Keywords

Animals, DNA Methylation, DNA, Ribosomal, Diet, High-Fat, Diet, Protein-Restricted, Epigenesis, Genetic, Female, Gene-Environment Interaction, Genetic Variation, Male, Maternal Nutritional Physiological Phenomena, Mice, Nutritional Status, Obesity, Pregnancy, Promoter Regions, Genetic, Weaning

Journal Title

Science

Conference Name

Journal ISSN

0036-8075
1095-9203

Volume Title

353

Publisher

American Association for the Advancement of Science (AAAS)
Sponsorship
Medical Research Council (MC_UU_12012/4)
British Heart Foundation (None)
Medical Research Council (MC_PC_12012)
This work was supported by the following grants and fellowships: Biotechnology and Biological Sciences Research Council, UK (BB/M012494/1) to V.K.R. and (BB/G00711/X/1) to V.K.R. and C.G.; and a Research Council UK Academic Fellowship to M.L.H. R.L. is supported by EU-FP7 BLUEPRINT. S.E.O. is supported by the British Heart Foundation (FS/12/64/30001) and the Medical Research Council (MC_UU_12012/4). This research used Queen Mary’s MidPlus computational facilities, supported by Queen Mary University of London Research-IT and funded by Engineering and Physical Sciences Research Council grant EP/K000128/1. We thank King’s College London FWB Genomics Centre and Barts and The London Genome Centre for performing high-throughput sequencing.