Evidence map›Paper›PMID 42162411›Full record

ArticleNature genetics2026

Non-Mendelian inheritance of DNA methylation patterns in mice.

Adam Davidovich, Danila Cuomo, Hang Su, Sandeep Kambhampati, Qingqing Gong, Alexandra Naron, Rakel Tryggvadottir, Leonard McMillan, Kasper D Hansen, David W Threadgill and 1 more

Abstract read
In one paragraph

Article in Nature genetics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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

11 authors.

Adam DavidovichCenter for Epigenetics, Johns Hopkins School of Medicine, Baltimore, MD, USA.ORCID http://orcid.org/0000-0002-2543-1873
Danila CuomoDepartment of Cell Biology and Genetics, Texas A&M University, College Station, TX, USA.
Hang SuBioinformatics and Computational Biology Curriculum, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Sandeep KambhampatiDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.ORCID http://orcid.org/0000-0002-3765-4679
Qingqing GongProgram in Biochemistry, Cellular, and Molecular Biology, Johns Hopkins University, Baltimore, MD, USA.ORCID http://orcid.org/0009-0003-2425-1701
Alexandra NaronDepartment of Cell Biology and Genetics, Texas A&M University, College Station, TX, USA.
Rakel TryggvadottirCenter for Epigenetics, Johns Hopkins School of Medicine, Baltimore, MD, USA.
Leonard McMillanBioinformatics and Computational Biology Curriculum, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Kasper D HansenDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA. khansen@jhsph.edu.ORCID http://orcid.org/0000-0003-0086-0687
David W ThreadgillDepartment of Cell Biology and Genetics, Texas A&M University, College Station, TX, USA. dwthreadgill@tamu.edu.ORCID http://orcid.org/0000-0003-3538-1635
Andrew P FeinbergCenter for Epigenetics, Johns Hopkins School of Medicine, Baltimore, MD, USA. afeinberg@jhu.edu.ORCID http://orcid.org/0000-0002-8364-1991

Funding

Integration of Genomics and the EnvironmentRM1HG008529 · NHGRI · JOHNS HOPKINS UNIVERSITY · PI FEINBERG, ANDREW P., THREADGILL, DAVID W. · 2016 to 2020
$5.3M
Epigenetic Drivers of Intrinsic Phenotypic Variability in Metabolic DiseaseDP1DK119129 · NIDDK · JOHNS HOPKINS UNIVERSITY · PI FEINBERG, ANDREW P. · 2018 to 2023
$3.9M
Foundational studies for precision nutritionR01DK130333 · NIDDK · TEXAS A&M AGRILIFE RESEARCH · PI THREADGILL, DAVID W. · 2021 to 2024
$2.6M
Data Science Tools to Increase Insight in Genomics DataR35GM149323 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI Kasper Daniel Hansen · 2023 to 2026
$1.8M
National Science Foundation (NSF) 1933303NHGRI NIH HHS RM1 HG008529NIDDK NIH HHS DP1 DK119129NIDDK NIH HHS R01 DK130333NIGMS NIH HHS R35 GM149323U.S. Department of Health & Human Services | National Institutes of Health (NIH) DP1DK119129U.S. Department of Health & Human Services | National Institutes of Health (NIH) R01DK130333U.S. Department of Health & Human Services | National Institutes of Health (NIH) R35GM149323U.S. Department of Health & Human Services | National Institutes of Health (NIH) RM1HG008529
6 · The paper itself

Abstract

Epigenetic mechanisms such as genomic imprinting demonstrate that molecular inheritance can deviate from typical Mendelian patterns. Despite this, the intergenerational inheritance of DNA methylation remains poorly understood. Here we developed a genome-wide approach to study epigenetic inheritance in mice using long-read nanopore sequencing. Using this approach in both liver and muscle, we found that ~93% of autosomal epigenetic inheritance patterns followed Mendel's laws, primarily driven by cis-acting methylation quantitative trait loci. However, we also identified extensive non-Mendelian inheritance, including emergent epigenetic inheritance patterns, widespread sex-specific DNA methylation patterns localized to the liver, and five seemingly new autosomal and X-linked imprinted genes. Notably, we also report an example of naturally occurring intergenerational paramutation, confirmed over strain-specific transposable elements within Capn11 and highly likely at Vps37c. Overall, an unexpectedly high ~7% of autosomal epigenetic inheritance patterns identified were non-Mendelian, highlighting the importance of epigenetic information in the analysis of inherited traits and disorders.

Indexed as

DNA MethylationEpigenetic MemoryInheritance PatternsAnimalsCalpainFemaleGenomic ImprintingLiverMaleMiceNanopore SequencingQuantitative Trait LociCalpain

Identifiers

PMID42162411
PMCPMC13263155

What OpenQuestion holds

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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.