Transcriptomics

Dataset Information

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In silico lineage tracing through single cell transcriptomes identifies a neural stem cell population in planarians


ABSTRACT: Background: The planarian, Schmidtea mediterranea, is a master regenerator with a large adult stem cell compartment. The lack of transgenic labeling techniques in this animal have hindered the study of lineage progression and has made understanding the mechanisms of tissue replacement during regeneration a challenge. However, recent advances in single cell transcriptomics and analysis methods may allow for the discovery of novel cell lineages as differentiation progresses from stem cell to terminally differentiated cell. Here we apply Waterfall analysis and single cell transcriptomics to identify adult stem cells belonging to specific cellular lineages and identify novel candidate genes for future in vivo lineage studies. Results: Single-cell-RNA-deep sequencing (scRNAseq) of 168 purified single stem and progeny cells from the planarian head was used to identify a molecularly distinct, neural stem cell population (νNeoblasts). Hierarchical clustering revealed 10 distinct subgroups and pseudotime analysis with Waterfall predicted a neural lineage trajectory as well as a novel alternative lineage. Previously undescribed neural lineage genes identified in silico were characterized in vivo and were shown to have neural expression patterns. Using the predicted νNeoblast markers, we demonstrate that a novel piwi-2+piwi-1lo stem cell population exists adjacent to the brain and immediately takes up BrdU. Conclusions: scRNAseq coupled with in silico lineage analysis offers a new approach for studying lineage progression in planarians. The lineages identified here were extracted from a highly heterogeneous dataset with minimal prior knowledge of planarian lineages, demonstrating that lineage purification by transgenic labelling is not a prerequisite for this approach. The identification of the νNeoblast lineage demonstrates the usefulness of the planarian system for computationally predicting cellular lineages in an adult context coupled with in vivo verification.

ORGANISM(S): Schmidtea mediterranea

PROVIDER: GSE79866 | GEO | 2016/04/08

SECONDARY ACCESSION(S): PRJNA317292

REPOSITORIES: GEO

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