Single-Cell RNA Sequencing for Plant Research

Overview Features Project Workflow Bioinformatic Analysis Sample Requirements Demo Results Cases & FAQ Resources Inquiry

The potential of scRNA-seq technology is immense, offering insights into the intricate mechanisms of gene regulation and the identification of distinct cell types and their functions. The potential of scRNA-seq technology is immense, offering insights into the intricate mechanisms of gene regulation and the identification of distinct cell types and their functions.

CD Genomics harnessing the power of single-cell genomics platform, enables a deeper understanding of plant developmental processes and their responses to various stimuli.


It has a wide range of applications in plant research. Compared with traditional bulk RNA-seq, single-cell RNA sequencing (scRNA-seq) plant developmental processes encompass multiple regulatory factors as well as significant heterogeneity among different cells, and single-cell transcriptomics provides a breakthrough approach to delve into the unique gene expression profiles of individual cells. The ability to reveal new and rare plant cell types with precision at the individual cell level also enriches our understanding of cell developmental trajectories and cellular functions.

Currently, plant single-cell transcriptome studies are mainly carried out in species such as Arabidopsis, rice, maize, tomato and poplar. Among them, the model plant Arabidopsis thaliana is a popular choice for single-cell studies. Samples typically include a range of plant organs, including roots, stems, leaves, flowers, pollen, spermatozoa, and seed endosperm.

Due to the complex composition of plant cell walls, plant single-cell transcriptome studies fall into two main categories: protoplast RNA sequencing (scRNA-seq) and cytoplasmic transcriptome sequencing (snRNA-seq). Protoplast-based methods have been the main focus of research efforts.

The basic technical steps in our plant single-cell transcriptome analysis include tissue dissociation, protoplast preparation, single-cell capture, library construction, sequencing, and in-depth data analysis.

At CD Genomics, we integrate a variety of sequencing platforms to provide comprehensive sequencing services for spatial transcriptome, single-cell transcriptome, general transcriptome, and epigenetic sequencing (such as scATAC-seq/snATAC-seq). For more information, please feel free to consult with our dedicated technical team.


Mapping Developmental Differentiation Mechanism Research Environmental Response
The cellular makeup of a species' tissues is meticulously structured to unveil its cellular diversity, facilitating the discovery of novel cell types. Integrating mapping techniques with time series analysis offers a comprehensive approach to unraveling the developmental path of specific tissues. Delving into the intricacies of gene and transcription factor functionality, we aim to elucidate the underlying mechanisms driving distinct biological activities, such as the regulation of stomatal aperture. Our service endeavors involve an in-depth exploration of cellular stress response mechanisms, pinpointing the specific responsive cells and the associated genes.

Project Workflow

Sample Preparation

1. Sample Preparation

Tissue dissociation, protoplasmic preparation, single cell capture.

Library Preparation

2. Library Preparation


3. Sequencing

Illumina HiSeq;
>10G clean data.

Data Analysis

4. Data Analysis & Delivery

Visualize and preprocess results, and perform custom bioinformatics analysis.

Bioinformatic Analysis

Dimensionality Reduction and Clustering: Complex data is simplified to reveal cellular diversity and organization within plant tissues.

Cellular Annotation: Different cell types are identified and labeled to understand the makeup of plant samples.

Subpopulation Segmentation: Distinct cell groups within tissues are uncovered, providing a finer-grained view of cellular diversity.

Cell Developmental Trajectories: Cell development paths are traced, shedding light on growth and differentiation.

Identification of New or Rare Cellular Taxa: Previously unknown or rare cell types are discovered.

(Novel) Marker Gene Mining: A novel approach is introduced to find cell type-specific marker genes.

Time-Series Analysis: How cells change over time is examined, enhancing our understanding of plant development.

Transcription Factor-Gene Regulatory Networks: Gene regulation within different cell types is explored.

Cell Communication Analysis: The interactions between plant cells are studied, revealing communication networks.

Sample Requirements

Sample Collection

Sample Types

Plant Protoplast Preparation

Custom Requirements

For any specific or unique requirements beyond these general guidelines, please contact our technical team. We are here to assist you in tailoring our services to meet your individual needs and research goals.


FastQ, BAM, coverage summary, QC report, custom bioinformatics analysis.

Demo Results

Data quality controlData quality control

Cell filtration and statisticsCell filtration and statistics

Dimensionality reduction and clusteringDimensionality reduction and clustering

Identification of cell subpopulationsIdentification of cell subpopulations

Differentially expressed gene analysisDifferentially expressed gene analysis

KEGG pathway functional analysisKEGG pathway functional analysis

Pseudotime trajectory analysisPseudotime trajectory analysis

Case Studies


* For Research Use Only. Not for use in diagnostic procedures.

Research Areas
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