Evidence map›Paper›PMID 34665921›Full record

ArticleMolecular ecology resources2022

DNA methylation as a tool to explore ageing in wild roe deer populations.

Jean-François Lemaître, Benjamin Rey, Jean-Michel Gaillard, Corinne Régis, Emmanuelle Gilot-Fromont, François Débias, Jeanne Duhayer, Sylvia Pardonnet, Maryline Pellerin, Amin Haghani and 3 more

Abstract read
In one paragraph

Article in Molecular ecology resources, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

  1. Article
  2. Estimating Polar Bear (Ecology and evolution · 2025
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  3. Article
  4. Article
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  12. DNA methylation clocks for dogs and humans.Proceedings of the National Academy of Sciences of the United States of America · 2022
    Article
  13. Article
  14. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Jean-François LemaîtreLaboratoire de Biométrie et Biologie Evolutive, UMR5558, Université de Lyon, Université Lyon 1, CNRS, Villeurbanne, France.ORCID https://orcid.org/0000-0001-9898-2353
Benjamin ReyLaboratoire de Biométrie et Biologie Evolutive, UMR5558, Université de Lyon, Université Lyon 1, CNRS, Villeurbanne, France.ORCID https://orcid.org/0000-0002-0464-5573
Jean-Michel GaillardLaboratoire de Biométrie et Biologie Evolutive, UMR5558, Université de Lyon, Université Lyon 1, CNRS, Villeurbanne, France.ORCID https://orcid.org/0000-0003-0174-8451
Corinne RégisLaboratoire de Biométrie et Biologie Evolutive, UMR5558, Université de Lyon, Université Lyon 1, CNRS, Villeurbanne, France.
Emmanuelle Gilot-FromontLaboratoire de Biométrie et Biologie Evolutive, UMR5558, Université de Lyon, Université Lyon 1, CNRS, Villeurbanne, France.ORCID https://orcid.org/0000-0003-0011-7519
François DébiasLaboratoire de Biométrie et Biologie Evolutive, UMR5558, Université de Lyon, Université Lyon 1, CNRS, Villeurbanne, France.
Jeanne DuhayerLaboratoire de Biométrie et Biologie Evolutive, UMR5558, Université de Lyon, Université Lyon 1, CNRS, Villeurbanne, France.
Sylvia PardonnetLaboratoire de Biométrie et Biologie Evolutive, UMR5558, Université de Lyon, Université Lyon 1, CNRS, Villeurbanne, France.
Maryline PellerinDirection de la Recherche et de l'Appui Scientifique, Office Français de la Biodiversité, Unité Ongulés Sauvages, Gap, France.
Amin HaghaniHuman Genetics, David Geffen School of Medicine, University of California, Los Angeles California, USA.
Joseph A ZollerDepartment of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, California, USA.ORCID https://orcid.org/0000-0001-6309-0291
Caesar Z LiDepartment of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, California, USA.
Steve HorvathHuman Genetics, David Geffen School of Medicine, University of California, Los Angeles California, USA.ORCID https://orcid.org/0000-0002-4110-3589

Funding

Paul G. Allen Frontiers Group
6 · The paper itself

Abstract

DNA methylation-based biomarkers of ageing (epigenetic clocks) promise to lead to new insights into evolutionary biology of ageing. Relatively little is known about how the natural environment affects epigenetic ageing effects in wild species. In this study, we took advantage of a unique long-term (>40 years) longitudinal monitoring of individual roe deer (Capreolus capreolus) living in two wild populations (Chizé and Trois-Fontaines, France) facing different ecological contexts, to investigate the relationship between chronological age and levels of DNA methylation (DNAm). We generated novel DNA methylation data from n = 94 blood samples, from which we extracted leucocyte DNA, using a custom methylation array (HorvathMammalMethylChip40). We present three DNA methylation-based estimators of age (DNAm or epigenetic age), which were trained in males, females, and both sexes combined. We investigated how sex differences influenced the relationship between DNAm age and chronological age using sex-specific epigenetic clocks. Our results highlight that old females may display a lower degree of biological ageing than males. Further, we identify the main sites of epigenetic alteration that have distinct ageing patterns between the two sexes. These findings open the door to promising avenues of research at the crossroads of evolutionary biology and biogerontology.

Indexed as

DeerDNA MethylationAgingAnimalsEpigenesis, GeneticEpigenomicsFemaleMaleepigenetic clockgrowthlife-historysenescencesex differences in lifespan

Identifiers

PMID34665921
PMCPMC9297961

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.