Evidence map›Paper›PMID 31533538›Full record

ArticleEpigenetics2020

A method for identifying allele-specific hydroxymethylation.

Yoichi Yamada, Sho Sasaki

Open access · bronzeAbstract read
In one paragraph

Article in Epigenetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact, top 92% of its field
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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. InAIMS microbiology · 2025
    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 at 1 institution in 1 country.

Yoichi YamadaFaculty of Electrical and Computer Engineering, Institute of Science and Engineering, Kanazawa University, Kanazawa, Japan.
Sho SasakiDivision of Electrical and Computer Engineering, Graduate School of Natural Science and Technology, Kanazawa University, Kanazawa, Japan.
Kanazawa University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We previously identified sequence-dependent allele-specific methylation (sd-ASM) in adult human peripheral blood leukocytes, in which ASM occurs in cis depending on adjacent polymorphic sequences. A number of groups have identified sd-ASM sites in the human and mouse genomes, illustrating the prevalence of sd-ASM in mammalian genomes. In addition, sd-ASM can lead to sequence-dependent allele-specific expression of neighbouring genes. Imprinted genes also often exhibit parent-of-origin-dependent allele-specific methylation (pd-ASM), which causes parent-of-origin-dependent allele-specific expression. However, whether most of the already known sd-ASM and pd-ASM sites are methylated or hydroxymethylated remains unclear due to technical restrictions. Accordingly, a novel method that enables examination of allelic methylation and hydroxymethylation status and also overcomes the drawbacks of conventional methods is needed. Such a method could also be used to elucidate the mechanisms underlying polymorphism-associated inter-individual differences in disease susceptibility and the mechanism of genomic imprinting. Here, we developed a simple method to determine allelic hydroxymethylation status and identified novel sequence- and parent-of-origin-dependent allele-specific hydroxymethylation sites. Correlation analyses of TF binding sequences and methylation or hydroxymethylation between three mouse strains revealed the involvement of

Indexed as

AllelesDNA MethylationAnimalsEpigenomicsMiceMice, Inbred C57BLProtein BindingSequence Analysis, DNATranscription FactorsTranscription Factorsallele-specific methylationDNA methylationhydroxymethylationimprintingrestriction enzyme

Identifiers

PMID31533538
PMCPMC7028324
OpenAlexW2972211089

What OpenQuestion holds

Textmetadata
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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.