Evidence map›Paper›PMID 41393869›Full record

ArticleFrontiers in plant science2025

Single-cell RNA sequencing reveals cellular diversity and gene expression dynamics in maize root development.

Jianwen Bian, Zelong Zhuang, Rui Tang, Wanling Ta, Zhenping Ren, Yunling Peng

Abstract read
In one paragraph

Article in Frontiers in plant science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

6 authors.

Jianwen BianCollege of Agronomy, Gansu Agricultural University, Lanzhou, China.
Zelong ZhuangCollege of Agronomy, Gansu Agricultural University, Lanzhou, China.
Rui TangCollege of Agronomy, Gansu Agricultural University, Lanzhou, China.
Wanling TaCollege of Agronomy, Gansu Agricultural University, Lanzhou, China.
Zhenping RenCollege of Agronomy, Gansu Agricultural University, Lanzhou, China.
Yunling PengCollege of Agronomy, Gansu Agricultural University, Lanzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Roots are essential for plant growth, functioning in nutrient and water uptake and anchorage. Methods: To elucidate the molecular basis of maize root development at single-cell resolution, single-cell RNA sequencing (scRNA-seq) was performed on maize root tips. Results: This analysis identified nine cell types and ten transcriptionally distinct clusters based on marker and cluster-specific gene expression. Cyclin gene profiling revealed M-phase enrichment across most root tissues, indicating active cell division in the meristem. Further investigation uncovered cell-type expression patterns of hormone-related genes in maize roots, which diverged from those observed in A. thaliana and rice. Pseudotime analysis reconstructed the developmental trajectory from early to mature cortex, revealing candidate regulators of cell fate determination. Weighted gene co-expression network analysis (WGCNA) identified Zm00001d021775 (sugar transport protein STP4) as a hub gene in the mature cortex. Discussion: Functional inference suggests STP4 promotes early seedling growth by facilitating glucose transport into glycolysis and the TCA cycle. These findings provide a high-resolution map of transcriptional landscapes in maize roots, offering new insights into cellular heterogeneity, developmental regulation, and potential molecular targets for enhancing root function and crop resilience.

Indexed as

cell heterogeneitymaize root developmentpseudotimescRNA-seqSTP4

Identifiers

PMID41393869
PMCPMC12695853

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.