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Variably methylated retrotransposons are refractory to a range of environmental perturbations

Nature Genetics volume 53, pages 1233–1242 (2021)Cite this article

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Abstract

The agouti viable yellow (Avy) allele is an insertional mutation in the mouse genome caused by a variably methylated intracisternal A particle (VM-IAP) retrotransposon. Avy expressivity is sensitive to a range of early-life chemical exposures and nutritional interventions, suggesting that environmental perturbations can have long-lasting effects on the methylome. However, the extent to which VM-IAP elements are environmentally labile with phenotypic implications is unknown. Using a recently identified repertoire of VM-IAPs, we assessed the epigenetic effects of different environmental contexts. A longitudinal aging analysis indicated that VM-IAPs are stable across the murine lifespan, with only small increases in DNA methylation detected for a subset of loci. No significant effects were observed after maternal exposure to the endocrine disruptor bisphenol A, an obesogenic diet or methyl donor supplementation. A genetic mouse model of abnormal folate metabolism exhibited shifted VM-IAP methylation levels and altered VM-IAP-associated gene expression, yet these effects are likely largely driven by differential targeting by polymorphic KRAB zinc finger proteins. We conclude that epigenetic variability at retrotransposons is not predictive of environmental susceptibility.

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Fig. 1: VM-IAP methylation levels are stable throughout the murine lifespan.
Fig. 2: VM-IAP methylation is unresponsive to maternal exposure to the endocrine disruptor BPA.
Fig. 3: Maternal exposure to an obesogenic diet has no effect on VM-IAP methylation levels.
Fig. 4: A mouse model of abnormal folate metabolism exhibits altered VM-IAP methylation.
Fig. 5: VM-IAP-associated gene expression is altered in Mtrrgt/gt mice.
Fig. 6: VM-IAP methylation levels in the Mtrrgt mouse line display parental zygotic effects and may be driven by polymorphic KRAB-ZFPs.
Fig. 7: VM-IAP methylation is unaffected by maternal dietary methyl donor supplementation.

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Data availability

The data supporting the findings of this study can be found within the article and its supplementary information files.

Code availability

All computational tools have been described previously; no custom computational pipelines were employed in this study.

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Acknowledgements

This research was funded by grants from the Wellcome Trust (nos. WT095606 and 210757/Z/18/Z) and Medical Research Council (nos. MR/R009791/1 and MR/J00159) to A.C.F.-S., from the Lister Institute of Preventative Medicine to E.D.W., the National Institutes of Health (no. R01 ES 023284 to M.S.B. and R.A.S.) and the MRC (nos. MC_UU_12012/4 and MC_UU_00014/4) and British Heart Foundation (no. RG/17/12/33167) to D.S.F.-T. and S.E.O. We thank the following for for PhD scholarships: Cambridge Trust, Downing College and Pomona College to T.M.B.; Wellcome Trust to G.E.T.B.; and European Union’s Horizon 2020 research and innovation programme (under a Marie Skłodowska Curie grant no. 812660) to J.L.B. We thank N. Kessler, J. Elmer, A. Hay, N. Takahashi and other members of the Ferguson-Smith laboratory for valuable discussions. We thank M. Castle for contributions to our statistical analyses, A. Robinson and C. Krapp for technical assistance and J. Webster and D. Oxley from the Babraham Institute Mass Spectrometry Facility for sample processing.

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  1. Amita Bansal

    Present address: Australian National University Medical School, John Curtin School of Medical Research, College of Health and Medicine, Australian National University, Canberra, Australian Capital Territory, Australia

Authors and Affiliations

  1. Department of Genetics, University of Cambridge, Cambridge, UK

    Tessa M. Bertozzi, Jessica L. Becker & Anne C. Ferguson-Smith

  2. Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK

    Georgina E. T. Blake & Erica D. Watson

  3. Centre for Trophoblast Research, University of Cambridge, Cambridge, UK

    Georgina E. T. Blake, Erica D. Watson & Anne C. Ferguson-Smith

  4. Center for Research on Reproduction and Women’s Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    Amita Bansal & Rebecca A. Simmons

  5. Center of Excellence in Environmental Toxicology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    Amita Bansal, Marisa S. Bartolomei & Rebecca A. Simmons

  6. Department of Cell and Developmental Biology, Perelman School of Medicine, Epigenetics Institute, University of Pennsylvania, Philadelphia, PA, USA

    Duy K. Nguyen & Marisa S. Bartolomei

  7. University of Cambridge Metabolic Research Laboratories and Medical Research Council Metabolic Diseases Unit, Wellcome Trust Medical Research Council Institute of Metabolic Science, Cambridge, UK

    Denise S. Fernandez-Twinn & Susan E. Ozanne

  8. Division of Neonatology, Children’s Hospital of Philadelphia, Philadelphia, PA, USA

    Rebecca A. Simmons

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Contributions

T.M.B. collected and analyzed the data. T.M.B. and J.L.B. performed the pyrosequencing assays. T.M.B., J.L.B., G.E.T.B., A.B. and D.K.N. carried out the DNA extractions. T.M.B., G.E.T.B., E.D.W., A.B. and D.S.F.-T. performed the somatic tissue dissections. G.E.T.B. collected the sperm samples. E.D.W. developed the Mtrrgt model, R.A.S. and M.S.B. developed the BPA exposure model and S.E.O. developed the diet-induced obesity model. A.C.F.-S. conceived the study. T.M.B., E.D.W. and A.C.F.-S. designed the experiments and interpreted the results. T.M.B., E.D.W. and A.C.F.-S. wrote the manuscript. All authors read and revised the manuscript.

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Correspondence to Anne C. Ferguson-Smith.

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Peer review information Nature Genetics thanks Qi Chen, Deborah Bourc’his and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 VM-IAP methylation in F1 females is unresponsive to maternal exposure to the endocrine disruptor BPA.

F0 dams were fed either a control diet (7% corn oil, grey) or one of two BPA-supplemented diets two weeks prior to mating, throughout pregnancy and lactation (lower BPA dose: 10 μg/kg/day, light blue; upper BPA dose: 10 mg/kg/day, dark blue). Adult F1 female liver tissue was collected from one mouse per litter. Comparison of the average percentage of CpG methylation at 11 VM-IAPs in F1 females across exposure groups shows no significant differences (Welch’s ANOVA; n = 12, 9, and 13 females for the control diet, lower BPA dose, and upper BPA dose, respectively). Data points represent the average of the four or five most distal CpGs of the VM-IAP 5′ LTRs. Box-plot elements: centre line, median; box limits, 25th and 75th percentiles; whiskers, maximum and minimum; all data points shown.

Extended Data Fig. 2 Characterisation of VM-IAP methylation levels in the Mtrrgt/gt mouse model.

a, VM-IAP methylation levels are altered in Mtrrgt/gt brain. VM-IAP methylation levels were compared between C57BL/6J (n = 8, grey box plots) and Mtrrgt/gt (n = 8, red box plots) brains. P-values were calculated by two-tailed Welch’s t-tests (ns indicates p > 0.05). b, Global DNA methylation levels are equivalent between C57BL/6J (n = 8, grey circles) and Mtrrgt/gt (n = 8, red circles) brain (left; p-value = 0.147) and kidney (right; p-value = 0.989) samples (unpaired two-tailed Student’s t-test; ns indicates p > 0.05). Global 5-methyl-cytosine (5mC) content was determined by liquid chromatography-tandem mass spectrometry and expressed as a percentage relative to total cytosine in the genome. c, VM-IAP methylation levels are unaffected by the Mtrrgt allele in mature sperm. VM-IAP methylation levels were quantified in sperm collected from the cauda epididymides and vas deferens of C57BL/6J (n = 8, grey circles), Mtrr+/+ (n = 8, hollow red circles), Mtrr+/gt (n = 8, half-filled red circles), and Mtrrgt/gt (n = 8, red circles) adult fertile males. d, VM-IAP methylation states are not associated with phenotypic severity in whole Mtrrgt/gt embryos. VM-IAP methylation levels were compared across C57BL/6J embryos (n = 7, grey circles), phenotypically normal Mtrrgt/gt embryos (n = 7, red circles), and severely affected Mtrrgt/gt embryos (n = 6, red circles) at E10.5 by Welch’s ANOVA. Adjusted p-values were calculated by two-tailed Tamhane T2 post hoc tests (ns indicates p > 0.05). Methylation data in all panels are shown as average percentage of DNA methylation across the four most distal CpGs at VM-IAP 5′ LTRs. Box-plot elements: centre line, median; box limits, 25th and 75th percentiles; whiskers, maximum and minimum; all data points shown.

Extended Data Fig. 3 VM-IAP-neighbouring genes unaffected in Mtrrgt/gt mice.

Left-hand graphs assess the correlation between VM-IAP methylation and adjacent Marveld2 (a), Rnf157 (b), Mbnl1(c), and Bmf (d) gene expression in C57BL/6J livers (n = 8, r: Pearson’s correlation coefficient; p: two-tailed p-value associated with r). Centre graphs show qRT-PCR expression data of VM-IAP-neighbouring genes Marveld2 (a), Rnf157 (b), Mbnl1(c), and Bmf (d) in C57BL/6J (n = 8, grey circles) and Mtrrgt/gt (n = 8, red circles) liver (two-tailed Welch’s t-tests; ns indicates p > 0.5; means shown as black lines). Right-hand graphs incorporate both control and Mtrrgt/gt data and assess the correlation between gene expression and VM-IAP methylation (n = 16, r: Pearson’s correlation coefficient; p: two-tailed p-value associated with r). Diagrams of VM-IAPs in relation to their neighbouring gene are depicted on the far left. Gene transcripts, extracted from the University of California, Santa Cruz (UCSC) Genome Browser65, are shown in black and VM-IAPs in purple. Green arrows represent the location of qRT-PCR primers. Diagrams are drawn to scale.

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Bertozzi, T.M., Becker, J.L., Blake, G.E.T. et al. Variably methylated retrotransposons are refractory to a range of environmental perturbations. Nat Genet 53, 1233–1242 (2021). https://doi.org/10.1038/s41588-021-00898-9

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