Single-cell genomics offers a means of precisely quantifying the state of individual cells and thus may enable the construction of explicit, genome-scale dynamical cellular models. Early single-cell transcriptomic studies lend support to the idea that cells are occupants of a vast, complex landscape of possible states and raise doubts that cell types are precisely defined, discrete entities. Time series experiments of differentiation have observed cells transitioning between a starting state and one or more end states, with many cells distributed along a “trajectory” between them. The Monocle algorithm introduced the notion of pseudotime, a quantitative measure of biological progression through a process such as cell differentiation.

The trajectory plot above shows the trajectory followed by olfactory neurons as the develop in mice. Each point is a cell, where are connected into a minimum spanning tree, the core data structure Monocle uses to find the trajectory, shown in black. Each cell’s pseudotime value is measured as the distance along the trajectory from its position back to the beginning. In order to describe complex differentiation processes in which cells make fate decisions, Monocle allows these trajectories to have a branched structure with multiple possible outcomes.

The Trapnell laboratory is currently focused on three ways to extend single-cell trajectory analysis:

  1. Methods to identify genes that are differentially regulated along the trajectory, particularly near branches
  2. Algorithms for distinguishing “driver” genes that regulate progress along a trajectory or govern branching
  3. Building trajectories from new single-cell data types, such as single-cell ATAC-Seq.

Inferring Causal Gene Regulatory Networks from Coupled Single-Cell Expression Dynamics Using Scribe

Connect-seq to superimpose molecular on anatomical neural circuit maps

Massively multiplex chemical transcriptomics at single cell resolution

Supervised classification enables rapid annotation of cell atlases

A pooled single-cell genetic screen identifies regulatory checkpoints in the continuum of the epithelial-to-mesenchymal transition

Thyroid hormone regulates distinct paths to maturation in pigment cell lineages

Wnt Signaling Separates the Progenitor and Endocrine Compartments during Pancreas Development

Dynamics of gene expression in single root cells of Arabidopsis thaliana

The accessible chromatin landscape of the murine hippocampus at single-cell resolution

The single-cell transcriptional landscape of mammalian organogenesis

A Peninsular Structure Coordinates Asynchronous Differentiation with Morphogenesis to Generate Pancreatic Islets

A genome-wide framework for mapping gene regulation via cellular genetic screens

Aligning Single-Cell Developmental and Reprogramming Trajectories Identifies Molecular Determinants of Myogenic Reprogramming Outcome

Single-Cell Multi-omics: An Engine for New Quantitative Models of Gene Regulation

Reversed graph embedding resolves complex single-cell trajectories

Single-cell mRNA quantification and differential analysis with Census

Single-cell transcriptome sequencing recent advances and remaining challenges

Single-cell transcriptomics reveals receptor transformations during olfactory neurogenesis

Defining cell types and states with single-cell genomics

The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells