The study of enhancers has been hampered by the scarcity of methods to systematically quantify their endogenous activity. We develop Mosaic-seq to systematically perturb enhancers and measure their endogenous activities at single-cell resolution. Mosaic-seq uses a CRISPR barcoding system to jointly measure a cell's transcriptome and its sgRNA modulators, thus quantifying the effects of dCas9-KRAB-mediated enhancer repression in single cells. Applying Mosaic-seq to 71 constituent enhancers from 15 super-enhancers, our analysis of 51,448 sgRNA-induced transcriptomes finds that only a small number of constituents are major effectors of target gene expression. Binding of p300 and RNAPII are key features of these constituents. We determine two key parameters of enhancer activity in single cells: their penetrance in a population and their contribution to expression in these cells. Through combinatorial interrogation, we find that simultaneous repression of multiple weak constituents can alter super-enhancer activity in a manner greatly exceeding repression of individual constituents.

Significance Outside the neurogenic niches, the adult brain lacks multipotent progenitor cells. In this study, we performed a series of in vivo screens and reveal that a single factor can induce resident brain astrocytes to become induced neural progenitor cells (iNPCs), which then generate neurons, astrocytes, and oligodendrocytes. Such a conclusion is supported by single-cell RNA sequencing and multiple lineage-tracing experiments. Our discovery of iNPCs is fundamentally important for regenerative medicine since neural injuries or degeneration often lead to loss/dysfunction of all three neural lineages. Our findings also provide insights into cell plasticity in the adult mammalian brain, which has largely lost the regenerative capacity.

SUMMARY Ectopic expression of transcription factors (TFs) can reprogram cell state. However, because of the large combinatorial space of possible TF cocktails, it remains difficult to identify TFs that reprogram specific cell types. Here, we develop Reprogram-Seq to experimentally screen thousands of TF cocktails for reprogramming performance. Reprogram-Seq leverages organ-specific cell-atlas data with single-cell perturbation and computational analysis to predict, evaluate, and optimize TF combinations that reprogram a cell type of interest. Focusing on the cardiac system, we perform Reprogram-Seq on MEFs using an undirected library of 48 cardiac factors and, separately, a directed library of 10 epicardial-related TFs. We identify a combination of three TFs, which efficiently reprogram MEFs to epicardial-like cells that are transcriptionally, molecularly, morphologically, and functionally similar to primary epicardial cells. Reprogram-Seq holds promise to accelerate the generation of specific cell types for regenerative medicine.

As we near a complete catalog of mammalian cell types, the capability to engineer specific cell types on demand would transform biomedical research and regenerative medicine. However, the current pace of discovering new cell types far outstrips our ability to engineer them. One attractive strategy for cellular engineering is direct reprogramming, where induction of specific transcription factor (TF) cocktails orchestrates cell state transitions. Here, we review the foundational studies of TF-mediated reprogramming in the context of a general framework for cell fate engineering, which consists of: discovering new reprogramming cocktails, assessing engineered cells, and revealing molecular mechanisms. Traditional bulk reprogramming methods established a strong foundation for TF-mediated reprogramming, but were limited by their small scale and difficulty resolving cellular heterogeneity. Recently, single-cell technologies have overcome these challenges to rapidly accelerate progress in cell fate engineering. In the next decade, we anticipate that these tools will enable unprecedented control of cell state.