Single-Cell RNA Sequencing Efficiently Predicts Transcription Factor Targets in Plants

Area of Science:

• Plant Molecular Biology
• Genomics
• Transcriptomics

Background:

• Identifying transcription factor (TF) targets is crucial for understanding gene regulation in plants.
• Current predictive technologies for TF targets in plants are limited in efficiency.

Purpose of the Study:

• To develop a simple and efficient system for predicting TF targets in rice (Oryza sativa) leaf cells.
• To leverage single-cell RNA sequencing (scRNA-seq) for high-resolution TF target identification.

Main Methods:

• Utilized a transient expression system to induce differential expression of a specific TF (OsNAC78) in individual rice leaf cells.
• Employed 10x Genomics' single-cell RNA sequencing to profile transcriptomes of individual cells.
• Performed expression profile analysis and gene overlapping analysis to identify candidate TF targets.

Main Results:

• Identified 35 candidate TF targets with strong correlations to OsNAC78 expression.
• Discovered 78 differentially expressed genes between cell clusters with the lowest and highest OsNAC78 expression.
• Confirmed Os01g0934800 and Os01g0949900 as direct targets of OsNAC78 through various assays.
• Observed highly similar expression trajectories between OsNAC78 and its validated targets.

Conclusions:

• Established a robust and simple system for predicting TF targets in rice using scRNA-seq.
• Demonstrated the utility of scRNA-seq for high-resolution TF target discovery in plants.
• Provided novel insights into the regulatory roles of OsNAC78 in rice leaf cells.