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

Abstract

BackgroundThe planarian Schmidtea mediterranea is a master regenerator with a large adult stem cell compartment. The lack of transgenic labeling techniques in this animal has hindered the study of lineage progression and has made understanding the mechanisms of tissue regeneration a challenge. However, recent advances in single-cell transcriptomics and analysis methods allow for the discovery of novel cell lineages as differentiation progresses from stem cell to terminally differentiated cell.ResultsHere we apply pseudotime 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. We purify 168 single stem and progeny cells from the planarian head, which were subjected to single-cell RNA sequencing (scRNAseq). Pseudotime analysis with Waterfall and gene set enrichment analysis predicts a molecularly distinct neoblast sub-population with neural character (νNeoblasts) as well as a novel alternative lineage. Using the predicted νNeoblast markers, we demonstrate that a novel proliferative stem cell population exists adjacent to the brain.ConclusionsscRNAseq coupled with in silico lineage analysis offers a new approach for studying lineage progression in planarians. The lineages identified here are extracted from a highly heterogeneous dataset with minimal prior knowledge of planarian lineages, demonstrating that lineage purification by transgenic labeling 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.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-016-0937-9) contains supplementary material, which is available to authorized users.

Neuronal sources of hedgehog modulate neurogenesis in the adult planarian brain

“…Recent studies have begun using single-cell RNA sequencing (scRNAseq) technologies, to investigate the complete transcriptional profiles of individual planarian stem cells and mature cell types (Wurtzel et al, 2015; Molinaro and Pearson, 2016). From the scRNAseq dataset generated by Wurtzel et al ., all cells from uninjured animals (including stem cells, neurons, gut, epithelial, muscle, and parapharyngeal cells) as well as neurons from injured worms were analyzed for expression of hh .…”

“…In order to support these dFISH findings, we examined gene expression from a recent dataset (Molinaro and Pearson, 2016) containing 96 single stem cells in the head (isolated from a FACS gate termed X1) as well as 72 cells from a FACS gate termed X2 that contains a mixture of stem cells and their immediate division progeny (Zhu et al, 2015; Hayashi et al, 2006). These cells were examined for expression of ptc , smo , or gli-1 .…”

“…In order to support the expression of nkx2.1 and arx within planarian neoblasts, we again examined the pool of 168×1 and X2 cells from the head of the animal (Molinaro and Pearson, 2016). Both nkx2.1 and arx were found to be expressed within these cells and a total of 31/168 cells expressed at least one factor (Figure 5G).…”

“…While this loose grouping of stem cells offers few similarities to a true neuroepithelium in terms of structure or cellular origin, the local signaling microenvironment may fulfill a similar function. Computationally, neural-committed stem cells, termed νNeoblasts, were recently detected and may be the targets of brain-derived signals (Molinaro and Pearson, 2016). However, while nkx2.1 + and arx + stem cells exhibit a spatial distribution and transcriptional profile suggestive of neuronal lineage commitment (Figure 5G), without definitive lineage-tracing studies, these neoblasts cannot yet be classified as true neural stem cells.…”

Comparison of SureSelect and Nextera Exome Capture Performance in Single-Cell Sequencing

“…Compared with traditional bulk sequencing which measures undifferentiated signals from a mixture of heterogeneous populations, SCS focuses on genetic mosaicism at a single-cell level. This unprecedented resolution allows us to study complex and dynamic biological processes such as tumor clonal evolution [5,7], immune response [8], and the central nervous system [9].…”