Evidence map›Paper›PMID 42577626›Full record

ArticleBio-protocol2026

Sample Preparation for Imaging-Based Spatial Transcriptomics in Rigid Plant Tissues (Roots, Shoots).

Hanhong Liu, Jingyuan Zhang, Mingyuan Zhu

Abstract read
In one paragraph

Article in Bio-protocol, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Hanhong LiuDepartment of Biochemistry and Biophysics, Texas A&M University, College Station, TX, USA.
Jingyuan ZhangDepartment of Biology, Duke University, Durham, NC, USA.
Mingyuan ZhuDepartment of Biochemistry and Biophysics, Texas A&M University, College Station, TX, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Plant roots dynamically respond to environmental changes and serve as an ideal system for studying cell development and gene regulation. Recent advances in imaging-based spatial transcriptomics have enabled high-resolution mapping of gene expression while preserving spatial context. However, existing sample preparation techniques remain inadequate for handling rigid plant tissues such as crop roots. Here, we present a detailed and practical protocol for preparing rigid plant tissue samples for imaging-based spatial transcriptomics. The workflow ensures effective tissue handling while maintaining RNA integrity and spatial organization. Within approximately eight days, samples can be processed and mounted onto commercial slides, making them ready for subsequent probe hybridization and imaging. This protocol also includes an integrated sample attachment test performed to assess slide quality. It has been optimized to produce consistent and reliable results across experiments. Overall, our method provides a robust solution for spatial transcriptomic analysis in rigid plant tissues, facilitating broader application of these technologies in plant research. Key features • Builds upon the method developed by Zhu et al. [1] and introduces an optimized sample preparation protocol for imaging-based spatial transcriptomics in rigid rice roots. • Ensures effective tissue fixation and sectioning, while preserving RNA integrity and spatial organization. • Includes an integrated sample attachment test to assess the adhesion of tissue sections to commercial slides. • Requires approximately 8 days to complete the sample preparation, with another 6 days for the attachment test.

Indexed as

Crop rootsImaging-based spatial transcriptomicsParaffin-embedded tissue sectioningPFA-based fixationRigid plant tissuesSection adhesion test

Identifiers

PMID42577626
PMCPMC13454941

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.