Evidence map›Paper›PMID 25539727›Full record

ArticleGenome biology and evolution2014

A neutrality test for detecting selection on DNA methylation using single methylation polymorphism frequency spectrum.

Jun Wang, Chuanzhu Fan

Abstract read
In one paragraph

Article in Genome biology and evolution, 2014. 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

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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

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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. Article
  3. Review
  4. Article
  5. Article
  6. Population Genetics and Natural Selection in Rheumatic Disease.Rheumatic diseases clinics of North America · 2017
    Review
  7. Review
  8. Review
  9. Methylome evolution in plants.Genome biology · 2016
    Review
  10. Review
  11. Article
  12. Article
  13. Review
  14. Rate, spectrum, and evolutionary dynamics of spontaneous epimutations.Proceedings of the National Academy of Sciences of the United States of America · 2015
    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

2 authors.

Jun WangDepartment of Biological Sciences, Wayne State University.
Chuanzhu FanDepartment of Biological Sciences, Wayne State University cfan@wayne.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Inheritable epigenetic mutations (epimutations) can contribute to transmittable phenotypic variation. Thus, epimutations can be subject to natural selection and impact the fitness and evolution of organisms. Based on the framework of the modified Tajima's D test for DNA mutations, we developed a neutrality test with the statistic "D(m)" to detect selection forces on DNA methylation mutations using single methylation polymorphisms. With computer simulation and empirical data analysis, we compared the D(m) test with the original and modified Tajima's D tests and demonstrated that the D(m) test is suitable for detecting selection on epimutations and outperforms original/modified Tajima's D tests. Due to the higher resetting rate of epimutations, the interpretation of D(m) on epimutations and Tajima's D test on DNA mutations could be different in inferring natural selection. Analyses using simulated and empirical genome-wide polymorphism data suggested that genes under genetic and epigenetic selections behaved differently. We applied the D(m) test to recently originated Arabidopsis and human genes, and showed that newly evolved genes contain higher level of rare epialleles, suggesting that epimutation may play a role in origination and evolution of genes and genomes. Overall, we demonstrate the utility of the D(m) test to detect whether the loci are under selection regarding DNA methylation. Our analytical metrics and methodology could contribute to our understanding of evolutionary processes of genes and genomes in the field of epigenetics. The Perl script for the "D(m)" test is available at http://fanlab.wayne.edu/ (last accessed December 18, 2014).

Indexed as

Epigenesis, GeneticGenetic DriftComputer SimulationDNA MethylationGenetic VariationHumansMutationSelection, Geneticepigeneticsepimutationneutrality testsingle methylation polymorphismsite frequencyTajima’s D

Identifiers

PMID25539727
PMCPMC4316624

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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.