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.

Overview

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.

Features

Project Workflow

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 Selection: For optimal results, select young and tender plant parts for sampling. These parts are recommended due to their higher cellular activity and sensitivity to experimental conditions.
• Sample Size: Ensure that each sample weighs at least 1-2 grams for a single experiment. This ensures an adequate amount of material for analysis.
• Sample Replication: It is advisable to send 3 copies of each sample to increase the reliability of your experiment's results. This redundancy helps mitigate potential errors and provides more comprehensive data.

Sample Types

• Roots: Since roots typically have lower cellular content, it's essential to provide a more substantial sample for accurate testing.
• Leaves: Focus on sending young leaves, as they contain more chloroplasts and larger cells, making them ideal for testing.
• Fruit: Given that most fruit cells are relatively large, standard sampling practices apply.
• Stem: Stem samples require normal sample delivery.
• Flower: Flowers, especially pollen cells with thick walls, necessitate specific sampling for testing due to their complex structure.

Plant Protoplast Preparation

• Cell Wall Removal: The primary method for cell wall removal is enzymatic, employing a mixture of cellulase and pectinase. This process ensures the integrity of the protoplasts while removing the cell walls effectively.
• Quality Assessment: After cell wall removal, quality control measures are vital. Protoplast activity, concentration, and impurity levels are evaluated through manual microscopy to ensure the integrity of your samples.

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.

Deliverable

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

Demo Results

Case Studies

• • Single-Cell Transcriptome Resolves Cell-Specific Stress Tolerance Gene Functions
    • Multiple cell types exist in plant organs and tissues, and each cell type may respond to stressors to different degrees. Single-cell technology has a unique advantage in identifying stress resistance genes, revealing gene expression changes masked by other non-responsive cells at the cellular level, identifying cell-type-specific stress resistance genes, and analyzing their biological functions.
• • Single-Cell Transcriptome Explores Developmental Differentiation Trajectories Under the Influence of Stress

    • Stress can have important effects on plant cell type differentiation. For example, it inhibits the proliferative capacity of plant cells, hinders or delays the process of cell type differentiation, affects the size of cells and the composition of cell populations, and triggers a change in cell fate, resulting in the initiation of differentiation of cells that would otherwise have differentiated into one cell type to other cell types. The single-cell transcriptome can be used to reconstruct the trajectory of plant cell differentiation before and after the effects of stress by different analytical tools and to identify key genes during different developmental processes.

• • Single-Cell Transcriptome Constructs Stress-Responsive Regulatory Networks

    • By analyzing the gene expression patterns of individual cells, the single-cell transcriptome can identify the inter-regulatory relationships among different genes, infer the signaling pathways and regulatory mechanisms under stress conditions, and construct a stress-responsive gene regulatory network for an in-depth understanding of the plant response process under the influence of stress. In addition, by mining the gene regulatory network, we can also identify key stress regulators and provide new targets for subsequent research and crop line improvement.

FAQ

• • My samples do not have a reference genome, can I do plant single-cell transcriptome?

    • Yes, it is possible to perform single-cell transcriptomes for plants without a reference genome. The success of this depends on the preparation of your phytoplasma sample. If you lack a reference genome, there are alternative approaches you can consider:

      • Utilize a well-assembled and annotated relative species: In the absence of a reference genome for your specific plant species, you can use a closely related species with a known genome. Ensure that the mapping rate is suitable, typically requiring it to be above 65%. This approach can be effective as long as the mapping rate and the number of expressed genes meet the desired criteria.
      • Choose long-read full-length transcriptome sequencing: If there is no reference genome available for a related species, you can opt for a full-length transcriptome of your target species. This approach is acceptable as long as the mapping rate and the number of expressed genes is within acceptable ranges.
• • Which parts of plants are generally used to prepare protoplasts?

    • It is generally recommended to use parts with thin and soft cell walls, few secondary products, and healthy and intact tissue states, such as leaf buds, flower buds, stem tips, and root tips located at the tips of plants, which are exuberantly dividing and relatively young. Then there are the cotyledons, soft leaves, calyx, and some other softer parts. Another is the ovule, seed, embryo or healing tissue.