Evidence map›Paper›PMID 31264905›Full record

ArticleAmerican journal of respiratory cell and molecular biology2019

A Practical Guide to the Measurement and Analysis of DNA Methylation.

Benjamin D Singer

Abstract read
In one paragraph

Article in American journal of respiratory cell and molecular biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 74 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
74citing papers in PubMed, 1 pooled it
–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

74 citing papers in PubMed, 1 synthesis or guideline pooled it.

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14 more citing papers are in PubMed but not listed here.

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

1 author.

Benjamin D SingerDivision of Pulmonary and Critical Care Medicine, Department of Biochemistry and Molecular Genetics, and Simpson Querrey Center for Epigenetics, Northwestern University Feinberg School of Medicine, Chicago, Illinois.ORCID 0000-0001-5775-8427

Funding

Technology CoreU19AI135964 · NIAID · NORTHWESTERN UNIVERSITY AT CHICAGO · PI RICHARD G WUNDERINK · 2018 to 2026
$24.7M
Regulatory T cell Uhrf1 and DNA methylation in repair of acute lung injuryK08HL128867 · NHLBI · NORTHWESTERN UNIVERSITY AT CHICAGO · PI SINGER, BENJAMIN DAVID · 2015 to 2019
$779k
NHLBI NIH HHS K08 HL128867NIAID NIH HHS U19 AI135964
6 · The paper itself

Abstract

DNA methylation represents a fundamental epigenetic mark that is associated with transcriptional repression during development, maintenance of homeostasis, and disease. In addition to methylation-sensitive PCR and targeted deep-amplicon bisulfite sequencing to measure DNA methylation at defined genomic loci, numerous unsupervised techniques exist to quantify DNA methylation on a genome-wide scale, including affinity enrichment strategies and methods involving bisulfite conversion. Both affinity-enriched and bisulfite-converted DNA can serve as input material for array hybridization or sequencing using next-generation technologies. In this practical guide to the measurement and analysis of DNA methylation, the goal is to convey basic concepts in DNA methylation biology and explore genome-scale bisulfite sequencing as the current gold standard for assessment of DNA methylation. Bisulfite conversion chemistry and library preparation are discussed in addition to a bioinformatics approach to quality assessment, trimming, alignment, and methylation calling of individual cytosine residues. Bisulfite-converted DNA presents challenges for standard next-generation sequencing library preparation protocols and data-processing pipelines, but these challenges can be met with elegant solutions that leverage the power of high-performance computing systems. Quantification of DNA methylation, data visualization, statistical approaches to compare DNA methylation between sample groups, and examples of integrating DNA methylation data with other -omics data sets are also discussed. The reader is encouraged to use this article as a foundation to pursue advanced topics in DNA methylation measurement and data analysis, particularly the application of bioinformatics and computational biology principles to generate a deeper understanding of mechanisms linking DNA methylation to cellular function.

Indexed as

DNA Methylation5-MethylcytosineBase SequenceComputational BiologyCpG IslandsDNADNA (Cytosine-5-)-Methyltransferase 1High-Throughput Nucleotide SequencingImmunoprecipitationMethylationMolecular StructureNucleic Acid HybridizationQuality ControlSequence AlignmentSulfites5-MethylcytosineDNADNA (Cytosine-5-)-Methyltransferase 1DNMT1 protein, humanhydrogen sulfiteSulfitesbioinformaticsbisulfite sequencingDNA methylationepigeneticsnext-generation sequencing

Identifiers

PMID31264905
PMCPMC6775954

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.