Plant cell atlas (PCA) combines information on the high-resolution location of nucleic acids, proteins, and metabolites within plant cells by accumulating data to better understand different plant types. PCA uses scRNA-seq technology to obtain genomic data from plant cells. Different plant species have different compositions and thicknesses and differ in their gene expression patterns according to plant species, developmental level, specific tissues, and available environmental conditions. These structural variations may raise plant-specific, cell type-related, and cell location-related challenges in scRNA-seq analysis. In conclusion, a framework for constructing a PCA is essential for understanding and designing plant developmental, physiological, and environmental responses.

Fig.1. Core activities, relationships, and phases for building a plant cell atlas (PCA) community. (Rhee S Y, et al., 2019)

What We Offer

Plant tissues are composed of cells with different morphologies and specific functions, and the gene expression patterns vary among cell types. Based on the scRNA-seq platform, Lifeasible provides single-cell solutions for building plant cell atlases to help customers comprehensively characterize the composition of cell types in plant tissues, obtain unique transcript information for each cell to identify cell identity and function and integrate information on nucleic acids, proteins, and metabolites at high resolution.

Lifeasible is committed to constructing a comprehensive, organ-scale atlas of plant cells at single-cell resolution. Our strategies are as follows:

• By applying scRNA-seq to plant samples, we can identify different cell populations and determine their unique gene expression profiles by PCA. This knowledge will be invaluable for deciphering the molecular basis of plant development, physiology, and responses to environmental cues.
• We can use PCA to map cellular and subcellular protein localization patterns, track the dynamics and various interactions between proteins, identify the molecular components of different cellular substructures, identify the complete states and transitions of specific cell types, and integrate these different types of data to generate testable models of cell function.
• In addition, we can combine spatial information with single-cell data to reveal the precise organization and localization of molecules in plant tissues through PCA. This spatially resolved molecular atlas will provide unprecedented insights into the cellular structure of plants.
• Our technical team is working to employ data science, proteomics, single-cell analysis, imaging, nanotechnology, and data visualization innovations to create high-resolution, molecular, temporal, and spatial maps of plant cells.

Based on a state-of-the-art single-cell analysis platform, we can perform a comprehensive analysis of plant cells at the single-cell level, providing the high-resolution data needed to build plant cell atlases. Our single-cell solutions for building plant cell atlases are designed to identify and map all plant cell types, annotate molecular localization, and understand the organization of molecules at the cellular and tissue levels. If you are interested in our services or have some questions, please feel free to contact us or make an online inquiry.

Reference

1. Rhee S Y, Birnbaum K D, Ehrhardt D W. Towards building a plant cell atlas[J]. Trends in plant science, 2019, 24(4): 303-310.

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