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Histone Variants

Overview of attention for book
Cover of 'Histone Variants'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Methods for Preparing Nucleosomes Containing Histone Variants
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    Chapter 2 Characterization of Posttranslational Modifications on Histone Variants
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    Chapter 3 Purification of Histone Variant-Interacting Chaperone Complexes
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    Chapter 4 Detection of Histone Modification Dynamics during the Cell Cycle by MS-Based Proteomics
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    Chapter 5 Histone Native Chromatin Immunoprecipitation
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    Chapter 6 How to Tackle Challenging ChIP-Seq, with Long-Range Cross-Linking, Using ATRX as an Example
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    Chapter 7 time-ChIP: A Method to Determine Long-Term Locus-Specific Nucleosome Inheritance
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    Chapter 8 MINCE-Seq: Mapping In Vivo Nascent Chromatin with EdU and Sequencing
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    Chapter 9 RChIP-Seq: Chromatin-Associated RNA Sequencing in Developmentally Staged Mouse Testes
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    Chapter 10 Bioinformatic Analysis of Nucleosome and Histone Variant Positioning
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    Chapter 11 Imaging Newly Synthesized and Old Histone Variant Dynamics Dependent on Chaperones Using the SNAP-Tag System
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    Chapter 12 Real-Time De Novo Deposition of Centromeric Histone-Associated Proteins Using the Auxin-Inducible Degradation System
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    Chapter 13 Live Imaging of Parental Histone Variant Dynamics in UVC-Damaged Chromatin
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    Chapter 14 CRISPR/Cas9 Gene Editing of Human Histone H2A Variant H2AX and MacroH2A
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    Chapter 15 Studying the Evolution of Histone Variants Using Phylogeny
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    Chapter 16 Characterization of Post-Meiotic Male Germ Cell Genome Organizational States
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    Chapter 17 An Animal Model for Genetic Analysis of Multi-Gene Families: Cloning and Transgenesis of Large Tandemly Repeated Histone Gene Clusters
  19. Altmetric Badge
    Chapter 18 Imaging and Quantitation of Assembly Dynamics of the Centromeric Histone H3 Variant CENP-A in Drosophila melanogaster Spermatocytes by Immunofluorescence and Fluorescence In-Situ Hybridization (Immuno-FISH)
  20. Altmetric Badge
    Chapter 19 Probing the Function of Oncohistones Using Mutant Transgenes and Knock-In Mutations
Attention for Chapter 6: How to Tackle Challenging ChIP-Seq, with Long-Range Cross-Linking, Using ATRX as an Example
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (54th percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

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Chapter title
How to Tackle Challenging ChIP-Seq, with Long-Range Cross-Linking, Using ATRX as an Example
Chapter number 6
Book title
Histone Variants
Published in
Methods in molecular biology, August 2018
DOI 10.1007/978-1-4939-8663-7_6
Pubmed ID
Book ISBNs
978-1-4939-8662-0, 978-1-4939-8663-7
Authors

Julia Truch, Jelena Telenius, Douglas R. Higgs, Richard J. Gibbons

Abstract

Chromatin immunoprecipitation coupled with high-throughput, next-generation DNA sequencing (ChIP-seq) has enabled researchers to establish the genome-wide patterns of chromatin modifications and binding of chromatin-associated proteins. Well-established protocols produce robust ChIP-seq data for many proteins by sequencing the DNA obtained following immunoprecipitation of fragmented chromatin using a wide range of specific antibodies. In general, the quality of these data mainly depends on the specificity and avidity of the antibody used. However, even using optimal antibodies, ChIP-seq can become more challenging when the protein associates with chromatin via protein-protein interactions rather than directly binding DNA. An example of such a protein is the alpha-thalassaemia mental retardation X-linked (ATRX) protein; a chromatin remodeler that associates with the histone chaperone DAXX, in the deposition of the replication-independent histone variant H3.3 and plays an important role in maintaining chromatin integrity. Inherited mutations of ATRX cause syndromal mental retardation (ATR-X Syndrome) whereas acquired mutations are associated with myelodysplasia, acute myeloid leukemia (ATMDS syndrome), and a range of solid tumors. Therefore, high quality ChIP-seq data have been needed to analyze the genome-wide distribution of ATRX, to advance our understanding of its normal role and to comprehend how mutations contribute to human disease. Here, we describe an optimized ChIP-seq protocol for ATRX which can also be used to produce high quality data sets for other challenging proteins which are indirectly associated with DNA and complement the ChIP-seq toolkit for genome-wide analyses of histone chaperon complexes and associated chromatin remodelers. Although not a focus of this chapter, we will also provide some insight for the analysis of the large dataset generated by ChIP-seq. Even though this protocol has been fully optimized for ATRX, it should also provide guidance for efficient ChIP-seq analysis, using the appropriate antibodies, for other proteins interacting indirectly with DNA.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 25 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 28%
Student > Doctoral Student 3 12%
Student > Bachelor 3 12%
Researcher 3 12%
Student > Master 2 8%
Other 1 4%
Unknown 6 24%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 12 48%
Agricultural and Biological Sciences 3 12%
Immunology and Microbiology 1 4%
Medicine and Dentistry 1 4%
Neuroscience 1 4%
Other 1 4%
Unknown 6 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 09 April 2019.
All research outputs
#7,574,392
of 23,098,660 outputs
Outputs from Methods in molecular biology
#2,350
of 13,208 outputs
Outputs of similar age
#129,919
of 331,034 outputs
Outputs of similar age from Methods in molecular biology
#32
of 193 outputs
Altmetric has tracked 23,098,660 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 13,208 research outputs from this source. They receive a mean Attention Score of 3.4. 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 331,034 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 54% of its contemporaries.
We're also able to compare this research output to 193 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.