Final state machine representation of corticogenesis

Cortical neurogenesis is a complex process in which progenitor cells have the ability to acquire specific fates and eventually differentiate toward a final cell type. The adoption of a particular cell state is the result of intrinsic genetic programs, which regulate cell behaviour, cell-cell interactions, and the influence of environmental cues. However there is still no comprehensive understanding of the control of cell fate specification and more in general on the self-constructing principles involved in the process. Insight into the mechanisms underlying corticogenesis is provided by the genealogical history of every precursor cell (cell lineage). We use a method based on spectral clustering to identify recurrent developmental patterns on reconstructed cortical lineages. The obtained state diagram represent compact state machine description of the developmental process. We evaluate the degree of similarities between precursors types and compare it to known single-cell gene expression profiles, with good agreement between the data and the model. Additionally we recast the model into a formal gene-like language and discuss the implications for genetic regulation