Project Summary The World Health Organization estimates that over 65 million people suffer from moderate to severe chronic obstructive pulmonary disease, a condition characterized by poor airflow and restricted breathing 1. The ability to regenerate damaged lung tissue would dramatically improve the quality of life for these individuals while reducing the prevalence and burden of pulmonary diseases worldwide. A promising approach to this problem is to use human pluripotent stem cells to produce lung and airway progenitor cells. Indeed, specialized protocols have been developed to convert stem cells into definitive endoderm, a lung precursor cell type 10-19. These protocols use small molecules to modulate the expression of key regulators of lung development including WNT, TGFβ, BMP, and FGF; however, these protocols are limited by the inability to generate a homogeneous population of definitive endoderm cells 11,15. This problem necessitates a better mechanistic understanding of how individual cells transition from their pluripotent cell state into definitive endoderm. Specifically, there is a critical need to understand how the gene regulatory networks in a given cell control its morphogenesis, proliferation, and differentiation decisions. Therefore, with the long-term goal of increasing homogeneity in lung precursor cells, the research objective of this fellowship is to determine how transcriptional heterogeneity in human embryonic stem cells influences their commitment to definitive endoderm. I hypothesize that heterogeneity in the starting population of cells generates alternate trajectories to definitive endoderm (or other cell types) and that these differences increase over time due to mutual inhibition between specific pairs of transcription factors (e.g., OCT4/SOX17, NANOG/GATA6). To test this hypothesis, I will first use single-cell RNA sequencing26 to define the transcriptional heterogeneity in human pluripotent stem cells during differentiation to definitive endoderm. I will then quantify the time-dependent changes in gene expression for each cell using RNA velocity, a computational method that uses spliced and unspliced transcript counts to estimate future gene expression states 28-29. Using these single-cell measurements, I will then develop a mechanistic model of the gene regulatory networks governing differentiation to DE and validate the model using known gene-gene interactions. Model simulations will: (1) confirm major gene regulators that drive differentiation; (2) identify novel gene networks that control heterogeneity before and during differentiation; and (3) reveal crosstalk among gene regulatory networks governing differentiation and other ongoing cellular processes such as proliferation and metabolism. The proposed experimental and computational studies provide a general framework to systematically identify gene regulatory mechanisms controlling differentiation to definitive endoderm and aid in the development of more effic...