Evidence map›Paper›PMID 34687312›Full record

ArticlePlant physiology2022

Single-cell transcriptomics sheds light on the identity and metabolism of developing leaf cells.

Rubén Tenorio Berrío, Kevin Verstaen, Niels Vandamme, Julie Pevernagie, Ignacio Achon, Julie Van Duyse, Gert Van Isterdael, Yvan Saeys, Lieven De Veylder, Dirk Inzé and 1 more

Abstract read
In one paragraph

Article in Plant physiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers.

0numbers the graph read from it
0cells of the map it votes in
52citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

52 citing papers in PubMed.

  1. Article
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  3. Single-cell insights into plant growth, adaptation, and evolution.Journal of integrative plant biology · 2026
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Rubén Tenorio BerríoDepartment of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium.ORCID 0000-0002-8033-5841
Kevin VerstaenDepartment of Applied Mathematics, Ghent University, Computer Science and Statistics, Ghent, Belgium.ORCID 0000-0003-3582-0298
Niels VandammeDepartment of Applied Mathematics, Ghent University, Computer Science and Statistics, Ghent, Belgium.ORCID 0000-0001-6582-0040
Julie PevernagieDepartment of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium.ORCID 0000-0002-9868-7474
Ignacio AchonDepartment of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium.ORCID 0000-0002-4553-1257
Julie Van DuyseVIB Center for Inflammation Research, Ghent, Belgium.
Gert Van IsterdaelVIB Center for Inflammation Research, Ghent, Belgium.ORCID 0000-0001-6626-1316
Yvan SaeysDepartment of Applied Mathematics, Ghent University, Computer Science and Statistics, Ghent, Belgium.ORCID 0000-0002-0415-1506
Lieven De VeylderDepartment of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium.ORCID 0000-0003-1150-4426
Dirk InzéDepartment of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium.ORCID 0000-0002-3217-8407
Marieke DuboisDepartment of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium.ORCID 0000-0002-5190-2130

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As the main photosynthetic instruments of vascular plants, leaves are crucial and complex plant organs. A strict organization of leaf mesophyll and epidermal cell layers orchestrates photosynthesis and gas exchange. In addition, water and nutrients for leaf growth are transported through the vascular tissue. To establish the single-cell transcriptomic landscape of these different leaf tissues, we performed high-throughput transcriptome sequencing of individual cells isolated from young leaves of Arabidopsis (Arabidopsis thaliana) seedlings grown in two different environmental conditions. The detection of approximately 19,000 different transcripts in over 1,800 high-quality leaf cells revealed 14 cell populations composing the young, differentiating leaf. Besides the cell populations comprising the core leaf tissues, we identified subpopulations with a distinct identity or metabolic activity. In addition, we proposed cell-type-specific markers for each of these populations. Finally, an intuitive web tool allows for browsing the presented dataset. Our data present insights on how the different cell populations constituting a developing leaf are connected via developmental, metabolic, or stress-related trajectories.

Indexed as

Single-Cell AnalysisTranscriptomeArabidopsisGene Expression ProfilingPlant CellsPlant Leaves

Identifiers

PMID34687312
PMCPMC8825278

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.