Neighborhood-Informed Positional Information for Precise Cell Identity Specification

Abstract

During development cells reliably establish their identities, a process that is enabled in part by positional information encoded in gene expression patterns. Previous works showed that cells in Drosophila embryos can utilize this information to decode their position along the anterior-posterior axis with 1% accuracy. However, this precision is insufficient to uniquely determine position, leading to a positional information gap. Here, we propose a neighborhood-informed information-theoretic framework where cells integrate local gene expression information as well as information from neighboring cells. We formulate how much additional information exists in neighboring cells as a function of spatial variation in gene expression. In Drosophila embryos, we show that the additional information encoded by local neighborhoods is sufficient to uniquely specify cell identities, closing the information gap. Furthermore, neighborhood-informed decoders predict cell positions and downstream gene expression patterns more accurately than cell-independent decoders, resulting in lower decoding variability, which is maintained in mutant embryos. Our results provide a basis for the analysis of cellular decision making in the context of their microenvironments.