Evidence map›Paper›PMID 36540021›Full record

ReviewPlant communications2023

Single-cell and spatial multi-omics in the plant sciences: Technical advances, applications, and perspectives.

Xiaole Yu, Zhixin Liu, Xuwu Sun

Abstract readReview
In one paragraph

Review in Plant communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 74 papers.

0numbers the graph read from it
0cells of the map it votes in
74citing 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

74 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Review
  5. Structural Variation and Its Roles in Plant Genomes.Plants (Basel, Switzerland) · 2026
    Review
  6. Article
  7. Review
  8. Review
  9. Article
  10. Review
  11. Review
  12. Article
  13. Article
  14. Review
  15. Review
  16. Review
  17. Review
  18. Review
  19. Article
  20. Article

14 more citing papers are in PubMed but not listed here.

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

3 authors.

Xiaole YuState Key Laboratory of Cotton Biology, State Key Laboratory of Crop Stress Adaptation and Improvement, Key Laboratory of Plant Stress Biology, School of Life Sciences, Henan University, 85 Minglun Street, Kaifeng 475001, P.R. China.
Zhixin LiuState Key Laboratory of Cotton Biology, State Key Laboratory of Crop Stress Adaptation and Improvement, Key Laboratory of Plant Stress Biology, School of Life Sciences, Henan University, 85 Minglun Street, Kaifeng 475001, P.R. China.
Xuwu SunState Key Laboratory of Cotton Biology, State Key Laboratory of Crop Stress Adaptation and Improvement, Key Laboratory of Plant Stress Biology, School of Life Sciences, Henan University, 85 Minglun Street, Kaifeng 475001, P.R. China. Electronic address: sunxuwussd@sina.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Plants contain a large number of cell types and exhibit complex regulatory mechanisms. Studies at the single-cell level have gradually become more common in plant science. Single-cell transcriptomics, spatial transcriptomics, and spatial metabolomics techniques have been combined to analyze plant development. These techniques have been used to study the transcriptomes and metabolomes of plant tissues at the single-cell level, enabling the systematic investigation of gene expression and metabolism in specific tissues and cell types during defined developmental stages. In this review, we present an overview of significant breakthroughs in spatial multi-omics in plants, and we discuss how these approaches may soon play essential roles in plant research.

Indexed as

MultiomicsPlantsGene Expression ProfilingMetabolomeMetabolomicsmass spectrometry imagingplantssingle-cell transcriptomicsspatial metabolomicsspatial transcriptomics

Identifiers

PMID36540021
PMCPMC10203395

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.