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Plant Transcription Factors

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

Table of Contents

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    Book Overview
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    Chapter 1 Master Regulatory Transcription Factors in Plant Development: A Blooming Perspective
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    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
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    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
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    Chapter 22 Genome-Wide Mapping of DNase I Hypersensitive Sites in Tomato
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    Chapter 23 Genome-Wide Identification of Chromatin Domains Anchored at the Nuclear Periphery in Plants
Attention for 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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About this Attention Score

  • Good Attention Score compared to outputs of the same age (70th percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

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Chapter title
Laser Capture Micro-Dissection Coupled to RNA Sequencing: A Powerful Approach Applied to the Model Legume Medicago truncatula in Interaction with Sinorhizobium meliloti
Chapter number 12
Book title
Plant Transcription Factors
Published in
Methods in molecular biology, January 2018
DOI 10.1007/978-1-4939-8657-6_12
Pubmed ID
Book ISBNs
978-1-4939-8656-9, 978-1-4939-8657-6

Brice Roux, Nathalie Rodde, Sandra Moreau, Marie-Françoise Jardinaud, Pascal Gamas, Roux, Brice, Rodde, Nathalie, Moreau, Sandra, Jardinaud, Marie-Françoise, Gamas, Pascal


Understanding the development of multicellular organisms requires the identification of regulators, notably transcription factors, and specific transcript populations associated with tissue differentiation. Laser capture microdissection (LCM) is one of the techniques that enable the analysis of distinct tissues or cells within an organ. Coupling this technique with RNA sequencing (RNAseq) makes it extremely powerful to obtain a genome-wide and dynamic view of gene expression. Moreover, RNA sequencing allows two or potentially more interacting organisms to be analyzed simultaneously. In this chapter, a LCM-RNAseq protocol optimized for root and symbiotic root nodule analysis is presented, using the model legume Medicago truncatula (in interaction with Sinorhizobium meliloti in the nodule samples). This includes the description of procedures for plant material fixation, embedding, and micro-dissection; it is followed by a presentation of techniques for RNA extraction and amplification, adapted for the simultaneous analysis of plant and bacterial cells in interaction or, more generally, polyadenylated and non-polyadenylated RNAs. Finally, step-by-step statistical analyses of RNAseq data are described. Those are critical for quality assessment of the whole procedure and for the identification of differentially expressed genes.

Twitter Demographics

The data shown below were collected from the profiles of 8 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 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 11 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 4 36%
Student > Ph. D. Student 3 27%
Lecturer > Senior Lecturer 1 9%
Researcher 1 9%
Unknown 2 18%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 5 45%
Agricultural and Biological Sciences 2 18%
Neuroscience 1 9%
Unknown 3 27%

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 10 October 2018.
All research outputs
of 23,096,849 outputs
Outputs from Methods in molecular biology
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Outputs of similar age
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Outputs of similar age from Methods in molecular biology
of 1,499 outputs
Altmetric has tracked 23,096,849 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
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 85% 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 gotten more attention than average, scoring higher than 70% 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 well, scoring higher than 88% of its contemporaries.