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Plant Epigenetics

Overview of attention for book
Cover of 'Plant Epigenetics'

Table of Contents

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    Book Overview
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    Chapter 1 Chromatin Immunoprecipitation Protocol for Histone Modifications and Protein-DNA Binding Analyses in Arabidopsis.
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    Chapter 2 Chromatin Conformation Capture-Based Analysis of Nuclear Architecture.
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    Chapter 3 Meta-analysis of Genome-Wide Chromatin Data.
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    Chapter 4 Localization of miRNAs by In Situ Hybridization in Plants Using Conventional Oligonucleotide Probes.
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    Chapter 5 The Combined Bisulfite Restriction Analysis (COBRA) Assay for the Analysis of Locus-Specific Changes in Methylation Patterns.
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    Chapter 6 Analysis of Global Genome Methylation Using the Cytosine-Extension Assay.
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    Chapter 7 In Situ Analysis of DNA Methylation in Plants.
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    Chapter 8 Plant Epigenetics
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    Chapter 9 Analysis of DNA Cytosine Methylation Patterns Using Methylation-Sensitive Amplification Polymorphism (MSAP).
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    Chapter 10 Differentially Methylated Region-Representational Difference Analysis (DMR-RDA): A Powerful Method to Identify DMRs in Uncharacterized Genomes.
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    Chapter 11 Analysis of Small RNA Populations Using Hybridization to DNA Tiling Arrays.
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    Chapter 12 Northern Blotting Techniques for Small RNAs.
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    Chapter 13 Stem-Loop qRT-PCR for the Detection of Plant microRNAs.
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    Chapter 14 Profiling New Small RNA Sequences.
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    Chapter 15 Small RNA Library Preparation and Illumina Sequencing in Plants.
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    Chapter 16 Bioinformatics Analysis of Small RNA Transcriptomes: The Detailed Workflow.
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    Chapter 17 Increasing a Stable Transformation Efficiency of Arabidopsis by Manipulating the Endogenous Gene Expression Using Virus-Induced Gene Silencing.
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    Chapter 18 The Random Oligonucleotide-Primed Synthesis Assay for the Quantification of DNA Strand Breaks.
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    Chapter 19 Profiling Transposable Elements and Their Epigenetic Effects in Non-model Species.
Attention for Chapter 10: Differentially Methylated Region-Representational Difference Analysis (DMR-RDA): A Powerful Method to Identify DMRs in Uncharacterized Genomes.
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Chapter title
Differentially Methylated Region-Representational Difference Analysis (DMR-RDA): A Powerful Method to Identify DMRs in Uncharacterized Genomes.
Chapter number 10
Book title
Plant Epigenetics
Published in
Methods in molecular biology, January 2017
DOI 10.1007/978-1-4899-7708-3_10
Pubmed ID
Book ISBNs
978-1-4899-7706-9, 978-1-4899-7708-3
Authors

Pavlina Sasheva, Ueli Grossniklaus

Editors

Igor Kovalchuk

Abstract

Over the last years, it has become increasingly clear that environmental influences can affect the epigenomic landscape and that some epigenetic variants can have heritable, phenotypic effects. While there are a variety of methods to perform genome-wide analyses of DNA methylation in model organisms, this is still a challenging task for non-model organisms without a reference genome. Differentially methylated region-representational difference analysis (DMR-RDA) is a sensitive and powerful PCR-based technique that isolates DNA fragments that are differentially methylated between two otherwise identical genomes. The technique does not require special equipment and is independent of prior knowledge about the genome. It is even applicable to genomes that have high complexity and a large size, being the method of choice for the analysis of plant non-model systems.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Professor 1 25%
Student > Ph. D. Student 1 25%
Researcher 1 25%
Unknown 1 25%
Readers by discipline Count As %
Agricultural and Biological Sciences 2 50%
Nursing and Health Professions 1 25%
Unknown 1 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 24 October 2016.
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#18,478,448
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Outputs from Methods in molecular biology
#7,926
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#310,506
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Outputs of similar age from Methods in molecular biology
#691
of 1,074 outputs
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