The search for genes that regulate stem cell self-renewal and differentiation has been hindered by a paucity of markers that uniquely label stem cells and early progenitors.

We have applied this marker-free approach to screen for transcription factors that regulate mammary stem cell differentiation in a 3D model of tissue morphogenesis and identified RUNX1 as a stem cell regulator.

Inhibition of RUNX1 expanded bipotent stem cells and blocked their differentiation into ductal and lobular tissue rudiments.

The discovery of stem cell regulators is a major goal of biological research, but progress is often limited by a lack of definitive markers capable of distinguishing stem cells from early progenitors.

PEACS t0 mammary stem cells resulted in the identification of RUNXI as a key regulator of eXit from the bipotent state.

Adult stem cells are functionally defined based on their ability to regenerate tissues.

This unique regenerative ability can be recapitulated in culture models, Where single stem cells , but not differentiated cells, form tissue rudiments in three-dimensional extracellular matrices.

For example, mammary stem cells form ducts and lobules in collagen matrices that resemble structures present in the breast [1—3] , While colon stem cells form mini-crypts in Matrigel that resemble analogous structures in the small intestine [4].

Identifying control strategies for biological networks is paramount for practical applications that involve reprogramming a cell’s fate, such as disease therapeutics and stem cell reprogramming.

Practical applications in modern molecular and systems biology such as the search for new therapeutic targets for diseases and stem cell reprogramming have generated a great interest in controlling the internal dynamics of a cell.

Identifying control targets for intracellular networks is of crucial importance for practical applications such as disease treatment and stem cell reprogramming.

Finally, the stable motif control interventions for our case studies target only a few nodes (between one and five out of more than fifty), which matches what is expected from stem cell reprogramming experiments [1—3, 8].

Practical applications such as stem cell reprogramming [1—3] and the search for new therapeutic targets for diseases [4—6] have also motivated a great interest in the general task of cell fate reprogramming, i.e., controlling the internal state of a cell so that it is driven from an initial state to a final target state (see references [7—13]).

In contrast, experimental work in stem cell reprogramming suggests that for biologically admissible states the number of nodes required for control is drastically lower (five or fewer genes [1—3, 8]).