bioRxivDevelopmental BiologyPreprint
Acoel single-cell atlas reveals expression dynamics and heterogeneity of a pluripotent stem cell population
Ryan E. HulettiD, Julian O. Kimura, Diana Marcela BolanosiD, Yi‐Jyun LuoiD, Lorenzo RicciiD, Mansi SrivastavaiD
Abstract
Pluripotent adult stem cell populations underlie whole-body regeneration in many distantly related animal lineages. These collectively pluripotent populations of cells share some features across species, such as the expression of piwi and other germline-related genes. Studies of how these cells operate during regeneration are needed in diverse systems to determine how underlying cellular and molecular mechanisms of renewal and differentiation compare. Here, we sought to characterize stem cells and their dynamics in the acoel Hofstenia miamia, a highly regenerative marine worm with a piwi-expressing stem cell population called neoblasts. Transcriptome profiling at single cell resolution revealed cell types shared across postembryonic stages, including stem cells and differentiated cell types such as neural, epidermal, muscle, and digestive cells. Reconstruction of single-cell differentiation trajectories followed by functional studies confirmed that neoblasts are the source of differentiated cells and identified transcription factors needed for the formation of major cell types. Next, analysis of single-cell transcriptomes from regenerating worms showed that both differentiated cells and stem cells dynamically alter gene expression in response to amputation. Further analysis of the stem cells recovered subpopulations of neoblasts, each with specific transcriptional profiles suggesting that the majority of neoblasts are specialized to differentiated lineages, reflecting putatively lineage-primed progenitors. Notably, neoblast subsets in Hofstenia were identifiable consistently across postembryonic stages and also displayed differential expression dynamics in response to wounding. Altogether, these data suggest that whole-body regeneration is accomplished by the coordination of cells with distinct and dynamic transcriptomic profiles through time. Furthermore, the data generated here will enable the study of how this coordination is achieved, enhancing our understanding of pluripotent stem cells and their evolution across metazoans.
- assay: scRNA-seq
- research focus: cell type annotation
- research focus: clustering
- research focus: trajectory inference
- approach: statistical model
- Citations
- 13
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