TedSim – temporal dynamics simulation of single-cell RNA sequencing data and cell division history

Recently, lineage tracing technology using CRISPR/Cas9 genome editing has enabled simultaneous readouts of gene expressions and lineage barcodes, which allows for the reconstruction of the cell division tree and makes it possible to reconstruct ancestral cell types and trace the origin of each cell type. Meanwhile, trajectory inference methods are widely used to infer cell trajectories and pseudotime in a dynamic process using gene expression data of present-day cells.

Researchers at the Georgia Institute of Technology have developed TedSim (single-cell temporal dynamics simulator), which simulates the cell division events from the root cell to present-day cells, simultaneously generating two data modalities for each single cell: the lineage barcode and gene expression data. TedSim is a framework that connects the two problems: lineage tracing and trajectory inference. Using TedSim, the researchers conducted analysis to show that (i) TedSim generates realistic gene expression and barcode data, as well as realistic relationships between these two data modalities; (ii) trajectory inference methods can recover the underlying cell state transition mechanism with balanced cell type compositions; and (iii) integrating gene expression and barcode data can provide more insights into the temporal dynamics in cell differentiation compared to using only one type of data, but better integration methods need to be developed.

TedSim workflow

The cell state tree models the true trajectories of cell differentiation and the cell division tree represents the true lineage. When traversing the cell division tree from root to leaves, the cell states are determined based on the state tree and the asymmetric division events (denoted by red edges in the cell division tree). TedSim simultaneously simulates gene expressions and lineage barcodes of all the cells, while the state and lineage relationships of the cells are maintained. The simulated data can be used to test not only TI or tree reconstruction methods, but also hybrid methods that use both gene expression and lineage barcode data.