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Epigenome Editing

Overview of attention for book
Cover of 'Epigenome Editing'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Editing the Epigenome: Overview, Open Questions, and Directions of Future Development
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    Chapter 2 Zinc Fingers, TALEs, and CRISPR Systems: A Comparison of Tools for Epigenome Editing
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    Chapter 3 Designing Epigenome Editors: Considerations of Biochemical and Locus Specificities
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    Chapter 4 Generation of TALE-Based Designer Epigenome Modifiers
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    Chapter 5 Neuroepigenetic Editing
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    Chapter 6 Allele-Specific Epigenome Editing
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    Chapter 7 Key to Delivery: The (Epi-)genome Editing Vector Toolbox
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    Chapter 8 CRISPR/dCas9 Switch Systems for Temporal Transcriptional Control
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    Chapter 9 Delivery of Designer Epigenome Modifiers into Primary Human T Cells
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    Chapter 10 Viral Expression of Epigenome Editing Tools in Rodent Brain Using Stereotaxic Surgery Techniques
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    Chapter 11 Stable Expression of Epigenome Editors via Viral Delivery and Genomic Integration
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    Chapter 12 Purified Protein Delivery to Activate an Epigenetically Silenced Allele in Mouse Brain
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    Chapter 13 Non-viral Methodology for Efficient Co-transfection
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    Chapter 14 Chromatin Immunoprecipitation in Human and Yeast Cells
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    Chapter 15 Chromatin Immunoprecipitation and High-Throughput Sequencing (ChIP-Seq): Tips and Tricks Regarding the Laboratory Protocol and Initial Downstream Data Analysis
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    Chapter 16 Generation of Whole Genome Bisulfite Sequencing Libraries for Comprehensive DNA Methylome Analysis
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    Chapter 17 Approaches for the Analysis and Interpretation of Whole Genome Bisulfite Sequencing Data
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    Chapter 18 Whole-Genome Bisulfite Sequencing for the Analysis of Genome-Wide DNA Methylation and Hydroxymethylation Patterns at Single-Nucleotide Resolution
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    Chapter 19 Locus-Specific DNA Methylation Analysis by Targeted Deep Bisulfite Sequencing
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    Chapter 20 DNA Methylation Analysis by Bisulfite Conversion Coupled to Double Multiplexed Amplicon-Based Next-Generation Sequencing (NGS)
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    Chapter 21 Cell-to-Cell Transcription Variability as Measured by Single-Molecule RNA FISH to Detect Epigenetic State Switching
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    Chapter 22 Establishment of Cell Lines Stably Expressing dCas9-Fusions to Address Kinetics of Epigenetic Editing
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    Chapter 23 Editing of DNA Methylation Using dCas9-Peptide Repeat and scFv-TET1 Catalytic Domain Fusions
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    Chapter 24 Chemical Inducible dCas9-Guided Editing of H3K27 Acetylation in Mammalian Cells
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    Chapter 25 Screening Regulatory Element Function with CRISPR/Cas9-based Epigenome Editing
Attention for Chapter 19: Locus-Specific DNA Methylation Analysis by Targeted Deep Bisulfite Sequencing
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (53rd percentile)
  • High Attention Score compared to outputs of the same age and source (81st percentile)

Mentioned by

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Citations

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Chapter title
Locus-Specific DNA Methylation Analysis by Targeted Deep Bisulfite Sequencing
Chapter number 19
Book title
Epigenome Editing
Published in
Methods in molecular biology, January 2018
DOI 10.1007/978-1-4939-7774-1_19
Pubmed ID
Book ISBNs
978-1-4939-7773-4, 978-1-4939-7774-1
Authors

Elsa Leitão, Jasmin Beygo, Michael Zeschnigk, Ludger Klein-Hitpass, Marcel Bargull, Sven Rahmann, Bernhard Horsthemke, Leitão, Elsa, Beygo, Jasmin, Zeschnigk, Michael, Klein-Hitpass, Ludger, Bargull, Marcel, Rahmann, Sven, Horsthemke, Bernhard

Abstract

DNA methylation, i.e., the methylation of cytosine at carbon atom C5, has an important role in the regulation of gene expression. The methylation status of each cytosine in a specific genomic region can be determined by targeted deep bisulfite sequencing at single-molecule resolution. Here we describe the design of PCR primers that are used to amplify specific sequences from bisulfite-converted DNA, the preparation of sequencing libraries, the sequencing of these libraries on the MiSeq system, as well as the analysis of the sequence reads. Using appropriate software tools such as amplikyzer2, it is easy to analyze complex multiplexed samples with several regions of interest, to determine the mean methylation values of all CpG dinucleotides in a region or of each CpG dinucleotide across all or selected reads, and to compare these values between different samples and between different alleles within a sample.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 42 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 42 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 24%
Student > Ph. D. Student 8 19%
Student > Bachelor 7 17%
Student > Master 3 7%
Student > Postgraduate 2 5%
Other 3 7%
Unknown 9 21%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 16 38%
Agricultural and Biological Sciences 12 29%
Medicine and Dentistry 2 5%
Social Sciences 1 2%
Nursing and Health Professions 1 2%
Other 0 0%
Unknown 10 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 21 September 2023.
All research outputs
#8,165,687
of 24,479,790 outputs
Outputs from Methods in molecular biology
#2,531
of 13,797 outputs
Outputs of similar age
#157,718
of 451,912 outputs
Outputs of similar age from Methods in molecular biology
#239
of 1,482 outputs
Altmetric has tracked 24,479,790 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,797 research outputs from this source. They receive a mean Attention Score of 3.5. This one has done well, scoring higher than 75% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 451,912 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 53% of its contemporaries.
We're also able to compare this research output to 1,482 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.