bioRxivDevelopmental BiologyPreprint
Reconstructing whole-organism cell phylogenies with resolved ancestral transcriptional states
Zhan LiuiD, Shanjun DengiD, Mengdong Zhang, Boliang Liu, Huimin Xiang, Zhiyun CheniD, Ao Zhang, Jay ShendureiD, Xionglei HeiD
Abstract
Combining cell lineage tracing with single-cell RNA sequencing can reconstruct a phylogenetic tree to integrate single-cell transcriptomic atlas. However, the internal nodes of this tree - representing ancestral cells - remain transcriptionally silent, preventing along-lineage longitudinal tracing of cell state dynamics. Here, we overcome this by reconstructing high-resolution zygote-to-larva developmental cell phylogenies for 15 zebrafish larvae, with directly measured transcriptomes of the terminal nodes (i.e., sampled cells). Leveraging a set of lineage-committed upregulated genes (LUGs), we developed LUG-encoded ancestral projection (LEAP), a novel phylogeny-based computational framework, and successfully imputed the transcriptional states of internal nodes of the phylogenies. This enabled, for the first time in a non-nematode organism, lineage-informed longitudinal analysis of cell state dynamics throughout development. Our analysis revealed a major, previously unappreciated wave of fate specializations associated with hatching, distinct from the well-characterized events of gastrulation. Furthermore, we uncovered abundant incipient cell states that are already fate-determined but exhibit minimal transcriptional differentiation, revealing a hidden layer of developmental fate specializations. In sum, by resolving ancestral transcriptional states of a reconstructed cell phylogeny, this work paves the way for constructing lineage-resolved cell atlases in complex organisms to characterize comprehensive cell state dynamics.
- organism: zebrafish
- assay: scRNA-seq
- research focus: trajectory inference
- research focus: gene regulatory network inference
- research focus: cell type annotation
- approach: statistical model
- Citations
- 0
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