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Plant Transcription Factors

Overview of attention for book
Cover of 'Plant Transcription Factors'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Master Regulatory Transcription Factors in Plant Development: A Blooming Perspective
  3. Altmetric Badge
    Chapter 2 Application of CRISPR/Cas to Understand Cis- and Trans-Regulatory Elements in Plants
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    Chapter 3 The Long-Term “In Natura” Study Sites of Arabidopsis halleri for Plant Transcription and Epigenetic Modification Analyses in Natural Environments
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    Chapter 4 Generation of Inducible Transgenic Lines of Arabidopsis Transcription Factors Regulated by MicroRNAs
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    Chapter 5 A Specific Knockdown of Transcription Factor Activities in Arabidopsis
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    Chapter 6 Using CRISPR/Cas9 System to Introduce Targeted Mutation in Arabidopsis
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    Chapter 7 CRISPR/Cas9-Based Genome Editing of Transcription Factor Genes in Marchantia polymorpha
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    Chapter 8 Cell-Type-Specific Promoter Identification Using Enhancer Trap Lines
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    Chapter 9 Isolation of Arabidopsis Palisade and Spongy Mesophyll Cells
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    Chapter 10 Ectopic Vascular Induction in Arabidopsis Cotyledons for Sequential Analysis of Phloem Differentiation
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    Chapter 11 High Impact Gene Discovery: Simple Strand-Specific mRNA Library Construction and Differential Regulatory Analysis Based on Gene Co-Expression Network
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    Chapter 12 Laser Capture Micro-Dissection Coupled to RNA Sequencing: A Powerful Approach Applied to the Model Legume Medicago truncatula in Interaction with Sinorhizobium meliloti
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    Chapter 13 NanoCAGE-XL: An Approach to High-Confidence Transcription Start Site Sequencing
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    Chapter 14 Genome-Wide TSS Identification in Maize
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    Chapter 15 Three-Dimensional Multiphoton Imaging of Transcription Factor by ClearSee
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    Chapter 16 Two-Color In Situ Hybridization: A Technique for Simultaneous Detection of Transcripts from Different Loci
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    Chapter 17 Gene Expression and Transcription Factor Binding Tests Using Mutated-Promoter Reporter Lines
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    Chapter 18 Rapid and Quantitative CELD Assay to Measure the Specificity of Transcription Factor-DNA-Binding Interactions and Identify cis-Elements
  20. Altmetric Badge
    Chapter 19 In Situ Proximity Ligation Assay to Detect the Interaction Between Plant Transcription Factors and Other Regulatory Proteins
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    Chapter 20 Cell-Free Protein Synthesis of Plant Transcription Factors
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    Chapter 21 Application of MNase-Seq in the Global Mapping of Nucleosome Positioning in Plants
  23. Altmetric Badge
    Chapter 22 Genome-Wide Mapping of DNase I Hypersensitive Sites in Tomato
  24. Altmetric Badge
    Chapter 23 Genome-Wide Identification of Chromatin Domains Anchored at the Nuclear Periphery in Plants
Attention for Chapter 11: High Impact Gene Discovery: Simple Strand-Specific mRNA Library Construction and Differential Regulatory Analysis Based on Gene Co-Expression Network
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (82nd percentile)
  • High Attention Score compared to outputs of the same age and source (95th percentile)

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Chapter title
High Impact Gene Discovery: Simple Strand-Specific mRNA Library Construction and Differential Regulatory Analysis Based on Gene Co-Expression Network
Chapter number 11
Book title
Plant Transcription Factors
Published in
Methods in molecular biology, January 2018
DOI 10.1007/978-1-4939-8657-6_11
Pubmed ID
Book ISBNs
978-1-4939-8656-9, 978-1-4939-8657-6
Authors

Yasunori Ichihashi, Atsushi Fukushima, Arisa Shibata, Ken Shirasu, Ichihashi, Yasunori, Fukushima, Atsushi, Shibata, Arisa, Shirasu, Ken

Abstract

Plant transcription factors have potential to behave as hubs in gene regulatory networks through altering the expression of many downstream genes, and identification of such hub transcription factors strongly enhances our understating of biological processes. Transcriptome analysis has become a staple of gene expression analyses. In addition to current advances in Next Generation Sequencing (NGS) technology, various methods for mRNA library construction and downstream data analyses have been enthusiastically developed. Here, we describe Breath Adapter Directional sequencing (BrAD-seq), a simple strand-specific mRNA library preparation for the Illumina platform, allowing easy scaling of transcriptome experiments with low reagent and labor costs. This protocol includes our recent modifications and the detailed practical procedure for BrAD-seq. Because extracting biological meanings from large-scale transcriptome data presents a significant challenge, we also describe a new analytical method that goes beyond differential expression. Differential regulatory analysis (DRA) is based on a gene co-expression network to address which regulatory factor or factors have the ability to predict the abundance of differentially expressed genes between two groups or conditions. This protocol provides a ready-to-use informatics pipeline from raw sequence data to DRA for plant transcriptome datasets.

X Demographics

X Demographics

The data shown below were collected from the profiles of 18 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 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 35 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 20%
Student > Master 6 17%
Student > Ph. D. Student 5 14%
Student > Doctoral Student 2 6%
Other 1 3%
Other 4 11%
Unknown 10 29%
Readers by discipline Count As %
Agricultural and Biological Sciences 12 34%
Biochemistry, Genetics and Molecular Biology 7 20%
Environmental Science 2 6%
Unspecified 1 3%
Computer Science 1 3%
Other 1 3%
Unknown 11 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 01 August 2018.
All research outputs
#3,328,983
of 23,096,849 outputs
Outputs from Methods in molecular biology
#810
of 13,208 outputs
Outputs of similar age
#76,545
of 442,670 outputs
Outputs of similar age from Methods in molecular biology
#64
of 1,499 outputs
Altmetric has tracked 23,096,849 research outputs across all sources so far. Compared to these this one has done well and is in the 84th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
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 particularly well, scoring higher than 93% 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 442,670 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 82% of its contemporaries.
We're also able to compare this research output to 1,499 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 95% of its contemporaries.