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Combining laser-assisted microdissection (LAM) and RNA-seq allows to perform a comprehensive transcriptomic analysis of epidermal cells of Arabidopsis embryo

Overview of attention for article published in Plant Methods, February 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (77th percentile)
  • High Attention Score compared to outputs of the same age and source (81st percentile)

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8 X users
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1 patent
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1 Facebook page

Citations

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53 Mendeley
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Title
Combining laser-assisted microdissection (LAM) and RNA-seq allows to perform a comprehensive transcriptomic analysis of epidermal cells of Arabidopsis embryo
Published in
Plant Methods, February 2018
DOI 10.1186/s13007-018-0275-x
Pubmed ID
Authors

Kaori Sakai, Ludivine Taconnat, Nero Borrega, Jennifer Yansouni, Véronique Brunaud, Christine Paysant-Le Roux, Etienne Delannoy, Marie-Laure Martin Magniette, Loïc Lepiniec, Jean Denis Faure, Sandrine Balzergue, Bertrand Dubreucq

Abstract

Genome-wide characterization of tissue- or cell-specific gene expression is a recurrent bottleneck in biology. We have developed a sensitive approach based on ultra-low RNA sequencing coupled to laser assisted microdissection for analyzing different tissues of the small Arabidopsis embryo. We first characterized the number of genes detected according to the quantity of tissue yield and total RNA extracted. Our results revealed that as low as 0.02 mm2 of tissue and 50 pg of total RNA can be used without compromising the number of genes detected. The optimised protocol was used to compare the epidermal versus mesophyll cell transcriptomes of cotyledons at the torpedo-shaped stage of embryo development. The approach was validated by the recovery of well-known epidermal genes such AtML1 or AtPDF2 and genes involved in flavonoid and cuticular waxes pathways. Moreover, the interest and sensitivity of this approach were highlighted by the characterization of several transcription factors preferentially expressed in epidermal cells. This technical advance unlocks some current limitations of transcriptomic analyses and allows to investigate further and efficiently new biological questions for which only a very small amounts of cells need to be isolated. For instance, it paves the way to increasing the spatial accuracy of regulatory networks in developing small embryo of Arabidopsis or other plant tissues.

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X Demographics

The data shown below were collected from the profiles of 8 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 53 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 53 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 14 26%
Student > Ph. D. Student 12 23%
Student > Master 5 9%
Other 3 6%
Student > Doctoral Student 3 6%
Other 6 11%
Unknown 10 19%
Readers by discipline Count As %
Agricultural and Biological Sciences 27 51%
Biochemistry, Genetics and Molecular Biology 13 25%
Unspecified 1 2%
Business, Management and Accounting 1 2%
Physics and Astronomy 1 2%
Other 2 4%
Unknown 8 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 03 November 2021.
All research outputs
#4,223,900
of 23,020,670 outputs
Outputs from Plant Methods
#236
of 1,088 outputs
Outputs of similar age
#94,848
of 438,547 outputs
Outputs of similar age from Plant Methods
#5
of 27 outputs
Altmetric has tracked 23,020,670 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,088 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.3. This one has done well, scoring higher than 78% 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 438,547 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 77% of its contemporaries.
We're also able to compare this research output to 27 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.