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CpG Islands

Overview of attention for book
Cover of 'CpG Islands'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 CpG Islands: A Historical Perspective
  3. Altmetric Badge
    Chapter 2 Biochemical Identification of Nonmethylated DNA by BioCAP-Seq
  4. Altmetric Badge
    Chapter 3 Prediction of CpG Islands as an Intrinsic Clustering Property Found in Many Eukaryotic DNA Sequences and Its Relation to DNA Methylation
  5. Altmetric Badge
    Chapter 4 CpG Islands in Cancer: Heads, Tails, and Sides
  6. Altmetric Badge
    Chapter 5 Infinium DNA Methylation Microarrays on Formalin-Fixed, Paraffin-Embedded Samples
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    Chapter 6 The Use of Methylation-Sensitive Multiplex Ligation-Dependent Probe Amplification for Quantification of Imprinted Methylation
  8. Altmetric Badge
    Chapter 7 The Pancancer DNA Methylation Trackhub: A Window to The Cancer Genome Atlas Epigenomics Data
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    Chapter 8 Methylation-Sensitive Amplification Length Polymorphism (MS-AFLP) Microarrays for Epigenetic Analysis of Human Genomes
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    Chapter 9 Genome-Wide Profiling of DNA Methyltransferases in Mammalian Cells
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    Chapter 10 Experimental Design and Bioinformatic Analysis of DNA Methylation Data
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    Chapter 11 Assay for Transposase Accessible Chromatin (ATAC-Seq) to Chart the Open Chromatin Landscape of Human Pancreatic Islets
  13. Altmetric Badge
    Chapter 12 Defining Regulatory Elements in the Human Genome Using Nucleosome Occupancy and Methylome Sequencing (NOMe-Seq)
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    Chapter 13 Genome-Wide Mapping of Protein–DNA Interactions on Nascent Chromatin
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    Chapter 14 Analysis of Chromatin Interactions Mediated by Specific Architectural Proteins in Drosophila Cells
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    Chapter 15 High-Throughput Single-Cell RNA Sequencing and Data Analysis
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    Chapter 16 Functional Insulator Scanning of CpG Islands to Identify Regulatory Regions of Promoters Using CRISPR
  18. Altmetric Badge
    Chapter 17 An Application-Directed, Versatile DNA FISH Platform for Research and Diagnostics
Attention for Chapter 12: Defining Regulatory Elements in the Human Genome Using Nucleosome Occupancy and Methylome Sequencing (NOMe-Seq)
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Chapter title
Defining Regulatory Elements in the Human Genome Using Nucleosome Occupancy and Methylome Sequencing (NOMe-Seq)
Chapter number 12
Book title
CpG Islands
Published in
Methods in molecular biology, January 2018
DOI 10.1007/978-1-4939-7768-0_12
Pubmed ID
Book ISBNs
978-1-4939-7767-3, 978-1-4939-7768-0
Authors

Suhn Kyong Rhie, Shannon Schreiner, Peggy J. Farnham

Abstract

NOMe-seq (nucleosome occupancy and methylome sequencing) identifies nucleosome-depleted regions that correspond to promoters, enhancers, and insulators. The NOMe-seq method is based on the treatment of chromatin with the M.CviPI methyltransferase, which methylates GpC dinucleotides that are not protected by nucleosomes or other proteins that are tightly bound to the chromatin (GpCmdoes not occur in the human genome and therefore there is no endogenous background of GpCm). Following bisulfite treatment of the M.CviPI-methylated chromatin (which converts unmethylated Cs to Ts and thus allows the distinction of GpC from GpCm) and subsequent genomic sequencing, nucleosome-depleted regions can be ascertained on a genome-wide scale. The bisulfite treatment also allows the distinction of CpG from CmpG (most endogenous methylation occurs at CpG dinucleotides) and thus the endogenous methylation status of the genome can also be obtained in the same sequencing reaction. Importantly, open chromatin is expected to have high levels of GpCmbut low levels of CmpG; thus, each of the two separate methylation analyses serve as independent (but opposite) measures which provide matching chromatin designations for each regulatory element.NOMe-seq has advantages over ChIP-seq for identification of regulatory elements because it is not reliant upon knowing the exact modifications on the surrounding nucleosomes. Also, NOMe-seq has advantages over DHS (DNase hypersensitive site)-seq, FAIRE (Formaldehyde-Assisted Isolation of Regulatory Elements)-seq, and ATAC (Assay for Transposase-Accessible Chromatin)-seq because it also gives positioning information for several nucleosomes on either side of each open regulatory element. Here, we provide a detailed protocol for NOMe-seq that begins with the isolation of chromatin, followed by methylation of GpCs with M.CviPI and treatment with bisulfite, and ending with the creation of next generation sequencing libraries. We also include sequencing QC analysis metrics and bioinformatics steps that can be used to identify nucleosome-depleted regions throughout the genome.

Twitter Demographics

The data shown below were collected from the profiles of 5 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 12 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 25%
Student > Doctoral Student 2 17%
Unspecified 1 8%
Student > Bachelor 1 8%
Student > Master 1 8%
Other 3 25%
Unknown 1 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 4 33%
Biochemistry, Genetics and Molecular Biology 3 25%
Engineering 2 17%
Computer Science 1 8%
Chemistry 1 8%
Other 1 8%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 02 April 2018.
All research outputs
#6,899,749
of 12,745,229 outputs
Outputs from Methods in molecular biology
#1,876
of 8,372 outputs
Outputs of similar age
#123,952
of 273,184 outputs
Outputs of similar age from Methods in molecular biology
#6
of 7 outputs
Altmetric has tracked 12,745,229 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 8,372 research outputs from this source. They receive a mean Attention Score of 2.1. This one has done well, scoring higher than 76% 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 273,184 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 52% of its contemporaries.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one.