Evidence map›Paper›PMID 30014809›Full record

ArticleGenetics research2018

Stage-specific differential DNA methylation data analysis during human erythropoiesis in chromosome 16.

Najyah A Garoot, Byung Guk Kim

Open access · bronzeAbstract read
In one paragraph

Article in Genetics research, 2018. 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 94% 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. 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.

Najyah A GarootDepartment of Computer Science,University of Massachusetts,Lowell,1 University Ave,Lowell,MA 03062,USA.
Byung Guk KimDepartment of Computer Science,University of Massachusetts,Lowell,1 University Ave,Lowell,MA 03062,USA.
University of Massachusetts Lowell · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Previous studies have generated controversial findings regarding the correlation between DNA methylation in the human genome and gene expression. Some reports have indicated that promoter methylation is negatively correlated with gene expression levels; however, in some cases, a poor or positive correlation was reported. Most previous findings were based on general trends observed with whole-genome data analysis. Here, we present a novel chromosome-specific statistical analysis design of empirical Bayes differential tests for five phases of erythroid development. To better understand the common methylation patterns of differentially methylated regions (DMRs) during specific stages, we defined differential phases for each CpG locus, based on a maximum log2 fold change. Analyzing hypermethylated and hypomethylated CpG loci separately showed variations in methylation patterns during erythropoiesis in the gene body, promoter and enhancer regions. Hypomethylated DMRs showed stronger associations with erythroid-specific enhancers at the differentiation start phase and with exons in the intermediate phase. To investigate the hypomethylated DMRs further, transcription factor binding site-enrichment analysis was conducted. This analysis highlighted novel transcription factors during each differentiation stage that were not detected by previous differential methylation data analysis. In contrast, hypermethylated DMRs showed a consistent methylation pattern over the different genomic regions. Thus, a closer examination of DNA methylation patterns in a single chromosome during each developmental stage can contribute to verify the association nature between gene expression and DNA methylation.

Indexed as

Chromosomes, Human, Pair 16DNA MethylationDatasets as TopicEnhancer Elements, GeneticErythropoiesisHumansTranscription FactorsTranscription Factors

Identifiers

PMID30014809
PMCPMC6865142
OpenAlexW2883936256

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.