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Plant Stress Tolerance

Overview of attention for book
Cover of 'Plant Stress Tolerance'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Epigenetics and RNA Processing: Connections to Drought, Salt, and ABA?
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    Chapter 2 The Fundamental Role of Reactive Oxygen Species in Plant Stress Response
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    Chapter 3 The Role of Long Noncoding RNAs in Plant Stress Tolerance
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    Chapter 4 Toward a Resilient, Functional Microbiome: Drought Tolerance-Alleviating Microbes for Sustainable Agriculture
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    Chapter 5 Mining and Quantifying In Vivo Molecular Interactions in Abiotic Stress Acclimation
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    Chapter 6 Generation of a Stress-Inducible Luminescent Arabidopsis and Its Use in Genetic Screening for Stress-Responsive Gene Deregulation Mutants
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    Chapter 7 Detection of Differential DNA Methylation Under Stress Conditions Using Bisulfite Sequence Analysis
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    Chapter 8 ChIP-Seq Analysis for Identifying Genome-Wide Histone Modifications Associated with Stress-Responsive Genes in Plants
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    Chapter 9 Isolation of Polysomal RNA for Analyzing Stress-Responsive Genes Regulated at the Translational Level in Plants
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    Chapter 10 Global Proteomic Profiling and Identification of Stress-Responsive Proteins Using Two-Dimensional Gel Electrophoresis
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    Chapter 11 Phosphoproteomics Analysis for Probing Plant Stress Tolerance
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    Chapter 12 Probing Posttranslational Redox Modifications
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    Chapter 13 Zymographic Method for Distinguishing Different Classes of Superoxide Dismutases in Plants
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    Chapter 14 Determination of Enzymes Associated with Sulfite Toxicity in Plants: Kinetic Assays for SO, APR, SiR, and In-Gel SiR Activity
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    Chapter 15 Determination of Total Sulfur, Sulfate, Sulfite, Thiosulfate, and Sulfolipids in Plants
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    Chapter 16 Determining Glutathione Levels in Plants
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    Chapter 17 Porous Graphitic Carbon Liquid Chromatography–Mass Spectrometry Analysis of Drought Stress-Responsive Raffinose Family Oligosaccharides in Plant Tissues
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    Chapter 18 Profiling Abscisic Acid-Induced Changes in Fatty Acid Composition in Mosses
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    Chapter 19 Detection of Free Polyamines in Plants Subjected to Abiotic Stresses by High-Performance Liquid Chromatography (HPLC)
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    Chapter 20 Determination of Polyamines by Dansylation, Benzoylation, and Capillary Electrophoresis
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    Chapter 21 Rapid Quantification of Abscisic Acid by GC-MS/MS for Studies of Abiotic Stress Response
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    Chapter 22 Silencing of Stress-Regulated miRNAs in Plants by Short Tandem Target Mimic (STTM) Approach
  24. Altmetric Badge
    Chapter 23 Rhizosphere Sampling Protocols for Microbiome (16S/18S/ITS rRNA) Library Preparation and Enrichment for the Isolation of Drought Tolerance-Promoting Microbes
Attention for Chapter 9: Isolation of Polysomal RNA for Analyzing Stress-Responsive Genes Regulated at the Translational Level in Plants
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Chapter title
Isolation of Polysomal RNA for Analyzing Stress-Responsive Genes Regulated at the Translational Level in Plants
Chapter number 9
Book title
Plant Stress Tolerance
Published in
Methods in molecular biology, July 2017
DOI 10.1007/978-1-4939-7136-7_9
Pubmed ID
Book ISBNs
978-1-4939-7134-3, 978-1-4939-7136-7
Authors

Yong-Fang Li, Ramamurthy Mahalingam, Ramanjulu Sunkar, Li, Yong-Fang, Mahalingam, Ramamurthy, Sunkar, Ramanjulu

Abstract

Alteration of gene expression is an essential mechanism, which allows plants to respond and adapt to adverse environmental conditions. Transcriptome and proteome analyses in plants exposed to abiotic stresses revealed that protein levels are not correlated with the changes in corresponding mRNAs, indicating regulation at translational level is another major regulator for gene expression. Analysis of translatome, which refers to all mRNAs associated with ribosomes, thus has the potential to bridge the gap between transcriptome and proteome. Polysomal RNA profiling and recently developed ribosome profiling (Ribo-seq) are two main methods for translatome analysis at global level. Here, we describe the classical procedure for polysomal RNA isolation by sucrose gradient ultracentrifugation followed by highthroughput RNA-seq to identify genes regulated at translational level. Polysomal RNA can be further used for a variety of downstream applications including Northern blot analysis, qRT-PCR, RNase protection assay, and microarray-based gene expression profiling.

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X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 25%
Student > Ph. D. Student 1 13%
Student > Doctoral Student 1 13%
Unknown 4 50%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 2 25%
Agricultural and Biological Sciences 2 25%
Unknown 4 50%
Attention Score in Context

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 24 July 2017.
All research outputs
#14,946,971
of 22,990,068 outputs
Outputs from Methods in molecular biology
#4,722
of 13,150 outputs
Outputs of similar age
#188,074
of 316,114 outputs
Outputs of similar age from Methods in molecular biology
#71
of 249 outputs
Altmetric has tracked 22,990,068 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,150 research outputs from this source. They receive a mean Attention Score of 3.4. This one has gotten more attention than average, scoring higher than 59% 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 316,114 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 249 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 64% of its contemporaries.