Single-cell Solutions for Plant Cell Developmental Dynamics

Determining the fate of cells during plant development is a complex biological process. Pluripotent stem cells in the meristematic tissues of higher plants are mainly found in the root tip meristematic tissue and stem tip meristematic tissue, which divides through differentiation and self-replication to maintain the plant growth and development process. Exploring the molecular mechanisms of pluripotent stem cell initiation and maintenance and the stages of cell fate determination during early differentiation has been a constant theme in plant growth and development research. Recent advances in single-cell RNA sequencing (scRNA-seq) methods have completely changed the understanding of cell heterogeneity and cell function, allowing studies to pinpoint the differentiation trajectory of stem cells maintained and differentiated at the cellular level. Due to the relatively small number of root cells and cell types, Arabidopsis growth and differentiation exhibit a strict spatial and temporal profile. It has been extensively studied as a model for plant stem cell differentiation.

Differentiation track of rice radicle epidermal cells.Fig.1. Differentiation track of rice radicle epidermal cells. (Zhang TQ et al., 2021)

What We Offer

Pseudotemporal analysis refers to the sequencing of single cells along a trajectory based on the similarity of expression patterns between cells, as a way to infer the differentiation trajectory of cells or the evolution of cell subtypes during development. Lifeasible provides professional single-cell solutions for plant cell developmental dynamics to map developmental differentiation trajectories among plant cells to reshape the cellular change process over time. Our solutions provide insight into the changes in cell types as cell states change and further resolve plant cell differentiation pathways to understand the dynamic developmental processes of plant cells.

Using Arabidopsis as a model for plant stem cell differentiation, our technical team develops scRNA-seq strategies to systematically identify the dynamic trajectory of Arabidopsis root development and cell differentiation at the gene expression level of individual cells. We aim to identify rare stem cells in and around resting centers in root-tip meristematic tissue.

We provide various computational approaches to infer developmental trajectories and predict cell fate. Our strategies are as follows:

  • Inferring trajectories from snapshot data. Starting from snapshot scRNA-seq data, represented as a gene-by-gene matrix of the transcriptome, a value is assigned to each cell called pseudo time. Based on the pseudotime, cells can be sorted, and their progression along this pseudotime axis can summarize the biological, developmental process.
  • RNA velocity. We determine the chemical kinetic parameters of RNA processing for each gene by scRNA-seq reads and predict the rate of change of mature mRNA.
  • Trajectory inference with temporal information. We provide time-series experiments that analyze individual cells at multiple time points, enabling the reconstruction of dynamic processes from static measurements.
  • Cell fate modeling with genealogical tracing. Combined with scRNA-seq, we offer genealogy tracking techniques to improve trajectory inference and interrogate developmental processes.

Applications for Establishing Plant Cell Developmental Trajectories:

  • Analyze the expression and redistribution of essential genes during stem cell maintenance and differentiation.
  • Explore stem cell maintenance differences, fate of terminally differentiated cells.

Lifeasible aims to provide customers with a more robust ability to systematically and comprehensively analyze plant stem cell maintenance and initiation, cell differentiation, and thus provide a complete model of plant development to guide crop improvement and agricultural production. If you are interested in our services or have some questions, please feel free to contact us or make an online inquiry.

Reference

  1. Zhang TQ, Chen Y, Liu Y, et al. Single-cell transcriptome atlas and chromatin accessibility landscape reveal differentiation trajectories in the rice root. Nat Commun. 2021 Apr 6;12(1):2053.

The services provided by Lifeasible cover all aspects of plant research, please contact us to find out how we can help you achieve the next research breakthrough.

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For research use only, not intended for any clinical use.

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