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Updated: Jan 11, 2026

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Published on: March 12, 2021

PscOA: a plant scRNA-seq marker gene database for enhanced cellular transcriptome understanding.

He Xu¹, Bin Li^1,2, Xiaohua Zhang¹

¹Agricultural Big-Data Research Center and College of Plant Protection, Shandong Agricultural University, Tai'an 271018, China.

Plant & Cell Physiology

|November 17, 2025

Summary

This summary is machine-generated.

A new database, PscOA, provides 39,347 plant marker genes for single-cell RNA sequencing (scRNA-seq) analysis. This resource aids in understanding plant cellular diversity and function, advancing plant science research.

Keywords:

cellular transcriptome marker gene database plant scRNA-seq stress

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Area of Science:

Plant biology
Genomics
Bioinformatics

Background:

Single-cell RNA sequencing (scRNA-seq) offers high-resolution transcriptome analysis, revealing cellular heterogeneity.
Plant science research using scRNA-seq is limited by a scarcity of specific marker genes compared to animal studies.

Purpose of the Study:

To develop a comprehensive database of plant scRNA-seq marker genes.
To facilitate cell type annotation and marker gene discovery in plants.
To advance the understanding of plant cellular diversity and function.

Main Methods:

Development of PscOA, a plant scRNA-seq marker gene database containing 39,347 genes.
Integration of BLAST for homology-based mining and SCSA for cell type annotation.
Application of PscOA in case studies using *A. thaliana* and *P. alba*, and prediction of markers for *Nicotiana tabacum*.

Main Results:

PscOA successfully enabled cell type annotation in *A. thaliana* and *P. alba*.
258 potential marker genes were predicted for *Nicotiana tabacum*.
Differential expression analysis under stress provided insights into plant cellular responses.

Conclusions:

PscOA is a valuable resource for plant scRNA-seq analysis, enhancing the study of cellular heterogeneity.
The database supports marker gene discovery and functional analysis in diverse plant species.
PscOA deepens the understanding of plant cellular transcriptomes and responses to stress.