Link to bioRxiv paper:
http://biorxiv.org/cgi/content/short/2023.07.28.551057v1?rss=1
Authors: Flores-Bautista, E., Thomson, M.
Abstract:
Understanding the circuits that control cell differentiation is a fundamental problem in developmental biology. Single-cell RNA sequencing has emerged as a powerful tool for investigating this problem. However, the reconstruction of developmental trajectories is based on the assumption that cell states traverse a tree-like structure, which may bias our understanding of critical developmental mechanisms. To address this limitation, we propose a topological approach that enables identifying signatures of functional biological circuits as persistent homology groups in transcriptome space. In this work, we applied our approach to more than ten single-cell developmental atlases and found that topological transcriptome spaces are predominantly path-connected and only sometimes simply connected. We developed a framework, TopGen, that identifies transiently expressed genes along topological motifs using homology generators. We show that TopGen can identify genetic drivers of topological structures in simulated datasets. Finally, we applied TopGen to analyze topological loops representing stem-like, transdifferentiation, and convergent cell circuits, found in C. elegans, H. vulgaris, and N. vectensis, respectively. Our results show that some essential differentiation mechanisms use non-trivial topological motifs, and that these motifs can be conserved in a cell-type--specific manner. Thus, our approach to studying the topological properties of developmental datasets opens new possibilities for understanding cell development and differentiation.
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