Evidence map›Paper›PMID 36304478›Full record

ReviewaBIOTECH2021

Single-cell profiling lights different cell trajectories in plants.

Hong-Xiang Zheng, Feng-Hui Wu, Si-Min Li, Xian Sheng Zhang, Na Sui

Open access · greenAbstract readReview
In one paragraph

Review in aBIOTECH, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.4field-weighted citation impact, top 42% of its field
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

2 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Review
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

5 authors at 2 institutions in 1 country.

Hong-Xiang Zheng *Shandong Provincial Key Laboratory of Plant Stress, College of Life Sciences, Shandong Normal University, Ji'nan, 250014 Shandong China.
Feng-Hui Wu *Shandong Provincial Key Laboratory of Plant Stress, College of Life Sciences, Shandong Normal University, Ji'nan, 250014 Shandong China.
Si-Min LiShandong Provincial Key Laboratory of Plant Stress, College of Life Sciences, Shandong Normal University, Ji'nan, 250014 Shandong China.
Xian Sheng ZhangState Key Laboratory of Crop Biology, College of Life Sciences, Shandong Agricultural University, Tai'an, 271018 Shandong China.
Na SuiShandong Provincial Key Laboratory of Plant Stress, College of Life Sciences, Shandong Normal University, Ji'nan, 250014 Shandong China.
Shandong Normal University · CNShandong Agricultural University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The molecular mechanism of the maintenance and differentiation of plant stem cells is an eternal theme in studies on plant growth and development. Recent advances in single-cell RNA sequencing (scRNA-seq) methods have completely changed the understanding of cell heterogeneity and cell function, allowing research precision to identify the differentiation trajectory of stem cells maintained and differentiated at the cellular level. This review aimed to mainly discuss the novel insights provided by scRNA-seq for the maintenance and initiation of plant stem cells, cell differentiation, cell response to environmental changes, and improvement strategies for scRNA-seq. In addition, it highlighted additional perspectives beyond scRNA-seq, such as spatial transcriptomes, epigenomes, and single-cell multiomics, for a renewed understanding of stem cell maintenance and cell differentiation, thus providing potential targets and theoretical foundations for crop improvement.

Indexed as

EpigenomesPlant developmentPlant stem cellsSingle-cell multi-omicsSingle-cell RNA sequencing

Identifiers

PMID36304478
PMCPMC9590582
OpenAlexW3142067932

What OpenQuestion holds

Textmetadata
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.