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.|
Tissue dissociation, protoplasmic preparation, single cell capture.
>10G clean data.
Visualize and preprocess results, and perform custom bioinformatics 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.
Plant Protoplast Preparation
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.
Data quality control
Cell filtration and statistics
Dimensionality reduction and clustering
Identification of cell subpopulations
Differentially expressed gene analysis
KEGG pathway functional analysis
Pseudotime trajectory analysis
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.
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.
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:
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.