Evidence map›Paper›PMID 39012608›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2024

Amplicon-Based Bisulfite Conversion-NGS DNA Methylation Analysis Protocol.

Claudia Albrecht, Pavel Bashtrykov, Albert Jeltsch

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Article in Methods in molecular biology (Clifton, N.J.), 2024. 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

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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

4 citing papers in PubMed.

  1. Review
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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

3 authors.

Claudia AlbrechtDepartment of Biochemistry, Institute of Biochemistry and Technical Biochemistry, University of Stuttgart, Stuttgart, Germany.
Pavel BashtrykovDepartment of Biochemistry, Institute of Biochemistry and Technical Biochemistry, University of Stuttgart, Stuttgart, Germany. pavel.bashtrykov@ibtb.uni-stuttgart.de.
Albert JeltschDepartment of Biochemistry, Institute of Biochemistry and Technical Biochemistry, University of Stuttgart, Stuttgart, Germany. albert.jeltsch@ibtb.uni-stuttgart.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

DNA methylation is an important epigenetic modification that regulates chromatin structure and the cell-type-specific expression of genes. The association of aberrant DNA methylation with many diseases, as well as the increasing interest in modifying the methylation mark in a directed manner at genomic sites using epigenome editing for research and therapeutic purposes, increases the need for easy and efficient DNA methylation analysis methods. The standard approach to analyze DNA methylation with a single-cytosine resolution is bisulfite conversion of DNA followed by next-generation sequencing (NGS). In this chapter, we describe a robust, powerful, and cost-efficient protocol for the amplification of target regions from bisulfite-converted DNA, followed by a second PCR step to generate libraries for Illumina NGS. In the two consecutive PCR steps, first, barcodes are added to individual amplicons, and in the second PCR, indices and Illumina adapters are added to the samples. Finally, we describe a detailed bioinformatics approach to extract DNA methylation levels of the target regions from the sequencing data. Combining barcodes with indices enables a high level of multiplexing allowing to sequence multiple pooled samples in the same sequencing run. Therefore, this method is a robust, accurate, quantitative, and cheap approach for the readout of DNA methylation patterns at defined genomic regions.

Indexed as

DNA MethylationHigh-Throughput Nucleotide SequencingPolymerase Chain ReactionSulfitesComputational BiologyDNAEpigenesis, GeneticEpigenomicsHumansSequence Analysis, DNADNAhydrogen sulfiteSulfitesAmplicon sequencingBisulfite conversionDNA methylationDual-indexingIn-line barcodingMultiplexingNext-generation sequencing

Identifiers

PMID39012608

What OpenQuestion holds

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Registered trials

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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.